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pdfAugust 2008
Series 1, Number 46
Design and Operation of
the National Asthma
Survey
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Suggested citation
O’Connor KS, Osborn L, Olson L, Blumberg SJ, Frankel MR, Srinath KP, et al.
Design and operation of the National Asthma Survey. National Center for Health
Statistics. Vital Health Stat 1(46). 2008.
Library of Congress Cataloging-in-Publication Data
Design and operation of the National Asthma Survey : program and collection
procedures / Department of Health and Human Services, Centers for Disease
Control and Prevention, National Center for Health Statistics.
p. ; cm.
‘‘August 2008.’’
Includes bibliographical references.
ISBN 0-8406-0622-2
1. National Asthma Survey (U.S.) 2. Asthma--United States. I. National Center
for Health Statistics (U.S.)
[DNLM: 1. National Asthma Survey (U.S.) 2. Asthma--United States. 3.
Health Surveys--United States. 4. Data Collection--methods--United States. WA
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Series 1, Number 46
Design and Operation of
the National Asthma Survey
Programs and Collection Procedures
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Disease Control and Prevention
National Center for Health Statistics
Hyattsville, Maryland
August 2008
DHHS Publication No. (PHS) 2008–1322
National Center for Health Statistics
Edward J. Sondik, Ph.D., Director
Jennifer H. Madans, Ph.D., Acting Co-Deputy Director
Michael H. Sadagursky, Acting Co-Deputy Director
Jennifer H. Madans, Ph.D., Associate Director for Science
Jennifer H. Madans, Ph.D., Acting Associate Director for
Planning, Budget, and Legislation
Michael H. Sadagursky, Associate Director for
Management and Operations
Lawrence H. Cox, Ph.D., Associate Director for Research
and Methodology
Linda B. Torian, Acting Director for Information Technology
Linda B. Torian, Acting Director for Information Services
Linda T. Bilheimer, Ph.D., Associate Director for Analysis
and Epidemiology
Charles J. Rothwell, M.S., Director for Vital Statistics
Jane E. Sisk, Ph.D., Director for Health Care Statistics
Jane F. Gentleman, Ph.D., Director for Health Interview
Statistics
Clifford L. Johnson, M.S.P.H., Director for Health and
Nutrition Examination Surveys
Division of Health Interview Statistics
Jane F. Gentleman, Ph.D., Director
Anne K. Stratton, M.S., Deputy Director
Eve Powell-Griner, Ph.D., Associate Director for Science
Marcie L. Cynamon, M.A., Chief, Survey Planning and
Special Surveys Branch
Eve Powell-Griner, Ph.D., Chief, Data Analysis and Quality
Assurance Branch
Contents
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
iii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Asthma in the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
The Role of the National Asthma Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Frequently Asked Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Sample Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Proxy Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Development and Implementation of NAS Interviewer Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
4
5
6
9
9
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Quality Control—Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Weighting and Estimation Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Data Files. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Quality Control—Data Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Citations and Further Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
29
Guidelines for Data Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
30
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
30
Appendix I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Specification of the National Asthma Education and Prevention Program Severity Indices Using the National Asthma
Survey Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
32
32
Appendix II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Sampling and Weighting Technical Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Appendix III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
National Study Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Appendix IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Four-State Study Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Appendix V . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Summary of NAS Pretests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Appendix VI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Advance Letters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
117
117
Appendix VII . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Disposition Code Frequencies and Unweighted Response Rate Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Appendix VIII . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
Weighted Frequencies and Percentages for Selected Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
v
Text Tables
A.
B.
C.
D.
E.
F.
G.
H.
J.
K.
L.
M.
N.
O.
Percentage of overall sample that is an augmentation sample: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Weighted error rates in proxy reporting: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Questionnaire flow in the national study: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Completed screening and detailed interviews for national study: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Completed screening and detailed interviews for four-state study: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Number of interviews completed by month: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mean and median interview length in minutes and seconds: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mean and median length of screening interview for national study in minutes and seconds, by respondent NIS
eligibility: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mean and median length in minutes and seconds for national study detailed interview, by NIS eligibility:
NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mean and median length of interview in minutes and seconds for four-state study detailed interview, by NIS
eligibility: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Weighted response rates: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Response rates for the detailed interview by sampled adult or child status: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . .
Final sample disposition, national and four-state studies: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Description of the weights, national and four-state samples: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5
6
8
10
10
10
13
13
13
14
14
15
16
28
Appendix Tables
I.
II.
III.
Number of values imputed for 2003 NAS poststratification variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Summary statistics for poststratified weights, total screener and detailed interviews, national sample: NAS, 2003 . . . . .
Summary statistics for poststratified weights, total screening and detailed interviews, by state and the entire four-state
sample: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
IV.
NAS Pretest III unweighted response rates by group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
V.
NAS Pretest IV unweighted response rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
VI.
SLAITS 2003 National Asthma Survey: Summary of pretests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
VII. SLAITS 2003 National Asthma Survey: National study case disposition frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . .
VIII. Unweighted response rate calculations for the National Asthma Survey, national sample: 2003 . . . . . . . . . . . . . . . . . . .
IX.
SLAITS 2003 National Asthma Survey: Four-state study case disposition frequencies . . . . . . . . . . . . . . . . . . . . . . . . . .
X.
Unweighted response rate calculations for the National Asthma Survey, four-state sample: 2003. . . . . . . . . . . . . . . . . .
XI.
Unweighted and weighted estimates of the frequency and percentage of persons diagnosed with asthma during their
lifetime (ASTHSTAT), national sample, all ages: NAS, 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
XII. Unweighted and weighted estimates of the frequency and percentage of persons of all ages who had an asthma
episode or attack in the 12 months prior to the date of interview (S4Q5), four-state sample (weight_int): NAS, 2003 .
vi
39
39
39
107
107
108
119
120
120
121
122
122
Acknowledgments
The National Asthma Survey was
sponsored and funded by the National
Center for Environmental Health
(NCEH) of the Centers for Disease
Control and Prevention (CDC). Design,
production, and analysis assistance for
this project was provided by NCEH
staff including Stephen Redd, Jeanne
Moorman, and the late Luann Rhodes.
The survey was conducted by
CDC’s National Center for Health
Statistics (NCHS). The project director
was Marcie Cynamon, and design,
production, and analysis assistance for
this project was provided by Stephen
Blumberg, Julian Luke, Terry
Richardson, and Kathleen O’Connor,
Division of Health Interview Statistics,
Survey Planning and Special Surveys
Branch. CDC’s National Center for
Infectious and Respiratory Diseases
(formerly known as the National
Immunization Program) graciously
permitted the use of the National
Immunization Survey sampling frame
for this survey.
Abt Associates Incorporated and
their subcontractors conducted all
interviews for the project. Technical
assistance was contributed by Sergei
Rodkin, Chris Becker, and Annabella
Battaglia. David Hoaglin provided
editorial assistance. Mary Cay Murray
and Michael P. Battaglia provided
management support.
This report was edited by Megan
M. Cox and Demarius V. Miller,
CDC/CCHIS/NCHM/Division of
Creative Services, Writer-Editor Services
Branch, and typeset by Annette F.
Holman, CDC/CCHIS/NCHM/Division
of Creative Services.
Finally, our appreciation is extended
to the respondents who were willing to
share their stories. Their efforts made
this project a reality.
iii
Objectives
This report presents detailed
information on the National Asthma
Survey (NAS), a module of the State
and Local Area Integrated Survey
program conducted by the Centers for
Disease Control and Prevention’s
(CDC) National Center for Health
Statistics. NAS, sponsored by the
CDC’s National Center for
Environmental Health, was designed to
produce national prevalence estimates
of adults and children with asthma; to
describe the health, socioeconomic,
behavioral, and environmental
predictors that relate to controlling
asthma better; and to characterize the
content of care and limitations of
persons with asthma. National
prevalence estimates were constructed
to be consistent with those produced
from the CDC’s National Health
Interview Survey (NHIS), although
prevalence estimates for
subpopulations may or may not be
consistent with NHIS.
Methods
Two separate random-digit-dial
telephone studies were fielded: a
national study and a four-state study in
Alabama, California, Illinois, and Texas.
Children aged 0–17 years and adults
aged 18 years and over were included
in both studies. The screening
procedure differed between the studies.
Percentages can be generated for the
four states combined or for each state
separately. A substudy was conducted
in the national study to examine the
accuracy of proxy reports of asthma.
Results
Data were collected from February
2003 to March 2004. A total of 955
detailed asthma interviews were
completed in the national study and
5,741 in the four-state study. A data file
has been released for each study that
contains asthma, health, and
demographic data, as well as sampling
weights. The weighted overall response
rates were 47.2% for the national sample
and 48.5% for the four-state sample.
Keywords: health surveys c needs
assessment c State and Local Area
Integrated Telephone Survey
Design and Operation of the
National Asthma Survey
by Kathleen S. O’Connor, M.P.H., CDC; Larry Osborn, M.P.H.,† and
Lorayn Olson, Ph.D.,† Abt Associates Inc.; Stephen J. Blumberg,
Ph.D., CDC; Martin R. Frankel, Ph.D., Baruch College at the City
University of New York and Abt Associates Inc.; and K. P. Srinath,
Ph.D., and Pamela Giambo, M.S.,† Abt Associates Inc.
Introduction
Asthma in the United
States
This document reports detailed
procedural information on a unique
source of asthma data, the National
Asthma Survey (NAS). The 2003 NAS
data were collected by the State and
Local Area Integrated Telephone Survey
(SLAITS) mechanism of the Centers for
Disease Control and Prevention’s (CDC)
National Center for Health Statistics
(NCHS). The survey was sponsored by
CDC’s National Center for
Environmental Health (NCEH). Two
separate studies were fielded for NAS: a
national study and a four-state study in
Alabama, California, Illinois, and Texas.
Information is provided on asthma
and its affect on the U.S. population.
This report describes NAS and its
unique characteristics and discusses in
detail the methods used in NAS,
including information on the
development of the survey instrument
and procedures; sample design,
selection, and characteristics; the
collection, storage, and cleaning of data;
and the construction of public-use data
files. To reduce confusion and enhance
data use, especially for novice analysts,
a short list of frequently asked questions
is included at the end of the
introduction.
Asthma is a chronic disease that
causes swelling in the inner lining of the
airway leading to the lungs. Adults and
children with asthma may experience
wheezing, breathlessness, chest
tightness, and coughing. A
nonexhaustive list of common triggers
that may cause bronchial constriction
and asthma includes inhalant allergens
such as pet dander, dust mites,
cockroach allergens, and mold; outdoor
allergens; environmental exposures such
as tobacco smoke, fumes, air pollution,
and chemicals; and occupational
exposures (1,2). Stress and exercise may
also contribute to asthma symptoms in
persons who suffer from exerciseinduced asthma.
Asthma is a costly and common
chronic condition in the United States
(3). In 1998, asthma cost $12.7 billion
dollars in the United States alone (4).
According to CDC’s National Health
Interview Survey (NHIS), in 2002 just
over 12% of all children under 18 years
of age had ever been told they have
asthma (resulting in almost 8.9 million
asthmatic children) (5). Almost 6% of
children had an asthma attack in the 12
months prior to the interview (5).
†Indicates authors who are no longer affiliated with Abt Associates Inc. at the time of publication.
Page 1
Page 2 [ Series 1, No. 46
According to the 2002 NHIS, 10.7% of
adults in the United States were
diagnosed with asthma and 6.8% still
had asthma (which means almost 22
million U.S. adults have ever been
diagnosed and almost 14 million adults
had asthma at the time of the interview)
(6). Data from the 2002 Behavioral Risk
Factor Surveillance System (BRFSS)
show considerable state-to-state
variation in asthma prevalence rates for
adults, with lifetime asthma prevalence
ranging from 8.6% (South Dakota) to
14.5% (Montana), and current asthma
prevalence ranging from 5.8% (South
Carolina) to 10.0% (Maine) (7).
Uncontrolled asthma can be fatal.
The asthma death rate in the United
States for children under 18 years of age
increased from 1.8 deaths per million
children in 1980 to 3.3 deaths per
million children in 1998, representing an
average increase of 3.4% per year (8).
The total age-adjusted (to the 2000 U.S.
population) annual death rate increased
from 14.4 deaths per million children in
1980 to 17.2 deaths per million children
in 1999, although this rate has been
decreasing since 1995 (9).
The Role of the National
Asthma Survey
NAS complements and extends
other surveys conducted at CDC and
elsewhere. Within the CDC, data on
asthma are collected through various
mechanisms such as NHIS, the Youth
Risk Behavior Surveillance System
(YRBSS), the National Health Care
Survey (NHCS), and BRFSS. NAS
addresses several deficits in these data
collection systems. For instance,
although NHIS collects information on
asthma for adults and children, estimates
are only available at the national level.
BRFSS collects asthma data at the state
level and permits calculation of a
national estimate; however, data were
only collected for adults aged 18 years
and over at the time of NAS data
collection. However, by adding annual
optional modules at the state and
territory levels, BRFSS collects selected
information on the nonadult population
17 years of age and under. More
information on asthma surveillance for
children and adults using BRFSS is
available at http://www.cdc.gov/asthma/
brfss/default.htm. Asthma prevalence
data for children have been collected for
a number of years in states that chose to
ask the childhood asthma module
questions, and participation varies each
year. YRBSS collects self-reported
behavioral and health risk data from
9th- through 12th-grade students but
collects minimal asthma data.
NHCS is a family of establishment
surveys that provide information on
health care facilities, services, and
patient characteristics. NHCS collects
information on many subjects, including
asthma; however, it can only provide
data on asthma care provided in
ambulatory care, ambulatory surgery,
emergency room, long-term care, and
inpatient settings, and it cannot provide
data on asthma care provided by
household members. NAS addressed
these issues by expanding the range of
information available. NAS collected
detailed asthma data on the sampled
respondents’ access and use of health
care (primary care, emergency room);
asthma knowledge and behavior;
medication use; family history; and
environmental exposures for adults and
children who live in households.
This survey adds depth to the
existing body of asthma data and helps
address critical questions about the
health and experiences of people with
asthma. A nonexhaustive list of potential
research questions that may be answered
using NAS data includes the following:
+ What are the demographic
characteristics of persons with
asthma? What is the asthma status
of critical populations, such as
children or the population over 50
years of age?
+ How well are asthma attacks,
episodes, and symptoms controlled
through medication use and
preventive measures?
+ What is the range of ages when first
diagnosed?
+ Which systems of care are most
often utilized by people with
asthma: urgent, hospital, or primary
care?
+ Do persons with asthma know the
symptoms, and do they understand
+
+
+
+
+
+
+
what to do when they have an
asthma attack?
Have people with asthma received a
written management plan from their
health care provider?
What modifications have been made
to home, school, or work
environments because of the
disease?
What treatment modalities are most
often used by those with asthma?
Is the use of asthma medication
consistent with guidelines?
What does family history of asthma
suggest about predisposition for
asthma?
To what extent have guidelines for
the diagnosis and management of
asthma been translated into practice?
To what extent does asthma cluster
within households?
NAS was designed to improve
understanding of how demographic
differences, patterns in health care
utilization, medication use, and
environmental modifications are related
to treatment and symptom control for
children and adults with asthma. The
data can potentially identify subgroups
that may benefit from behavioral
interventions.
The State and Local Area
Integrated Telephone Survey
program
SLAITS modules use the large
sampling frame of the CDC’s National
Immunization Survey (NIS) to identify
samples and cases. NIS is a large-scale
random-digit-dial (RDD) telephone
survey that screens for the presence of
young children in sampled households
and collects detailed vaccination history
information for eligible children. The
size of this sample provides a
cost-effective opportunity for SLAITS
projects to survey other populations, in
addition to the rare population that
eventually screens into NIS. NIS sample
design is described in more detail in this
report, at the NIS website located at
http://www.cdc.gov/vaccines/stats-surv/
default.htm#nis, and in the Vital and
Health Statistics series report by Smith
et al. (10).
Series 1, No. 46 [ Page 3
Frequently Asked
Questions
To reduce confusion and enhance
data use, especially for novice analysts,
this short list of frequently asked
questions is included.
How is this report organized?
The main body contains detailed
information on the entire survey process.
Appendices contain additional detail on
selected topics such as pretests,
instruments, and weighting.
What are the names of the Primary
Sampling Unit (PSU) and stratum
variables for each file?
For the national file, the PSU
variable is IDNUMR and the stratum
variable is STRATUM. For the
four-state file, the PSU variable is
IDNUMR and the stratum variable is
STATE. See page 27 for more
information.
What are the names of the weights
for each file?
The weights in the national file are
post_pr_int and post_sr_int. The weights
in the four-state file are post_adult_int,
post_child_int, and weight_int. See page
28 for more information.
In the national file, when was it
acceptable to collect proxy-reported
data on asthma status in adults?
Proxy reports were acceptable if 1)
the adult sampled respondent was too ill
or infirm to answer but still wanted to
participate or 2) the sampled adult was
not available at the time of the
screening contact. In this case, a very
short proxy interview was conducted
with the adult household member who
answered the telephone. If the sampled
adult was reported to be asthmapositive, an appointment was scheduled
to complete a detailed interview directly
with the sampled person. Asthma status
was confirmed with that person at
callback. The initial design of the
national study also called for a subset of
500 sampled adults who were reported
by a proxy respondent as asthmanegative to be called back to confirm
their asthma status and determine proxy
reporting error.
In the national data file, why is proxy
information included that has been
verified or changed by the adult
sampled respondent?
This information is provided for
methodological purposes only.
In the national file, which weight do I
use to examine asthma in children?
This depends. The national file does
not include a single child-level weight.
Instead, it includes two weights, both of
which include all sampled children:
post_sr_int and post_pr_int. Estimates
for children can be produced using
either weight, but one should remember
that adults are included in both weights
too (in case there is no interest in
estimates for adults). The weight to use
for children must still be decided, as
these individual weights may vary
slightly for any given child because of
the difference in the number of sampled
adult cases used to calculate the weight.
Therefore, which adult cases should be
included: those with self-reported data
only or those that have self- and
proxy-reported data? The preferred
weight to use for child and adult-level
estimates is post_sr_int because it only
includes sampled adult self-report cases
in addition to all children. The alternate
weight is post_pr_int, which includes
sampled adult self- and proxy reports, in
addition to all children. The post_pr_int
weight should be used for
methodological research to examine
differences between self- and proxy
reporting in adults.
In the national file, what is the
relationship between the proxy and
sampled respondents for the screener
contact and main interview?
In the national sample, proxy
interviews were allowed in two
situations: 1) if the adult sampled
respondent was too ill or infirm to
complete the interview over the
telephone or 2) a subset of sampled
adults was unavailable at the screener
contact and reported by a proxy
respondent to be asthma-negative. These
latter cases were called back to confirm
their asthma status. Based on the
observed proxy-report error rate for this
subset, a decision was made to expand
confirmation calls to all adult sampled
persons with proxy-reported asthmanegative status. For a sampled child, all
interviews were conducted with a
knowledgeable adult household member.
For the four-state file, are the weights
for the total population the same as
the separate weights for children and
adults, and can weighted data be
examined individually for each state,
or only as the four-state block?
Yes, the separate weights for the
total population comprise the individual
weights for children and adults.
Weighted data can be examined for each
state individually, as well as for the
four-state block as a whole.
Why can’t I use the four-state data
file to calculate prevalence estimates?
The four-state file cannot be used to
calculate prevalence because crucial
information needed to do so was
purposely not collected because of the
selected screening process. This decision
was made after extensive tests were
conducted. The four-state sample can be
used to describe the characteristics of
children or adults with asthma.
What can I use the national data file
for?
The national file can be used to
calculate prevalence estimates.
In the national file, what is the
relationship between the proxy and
sampled respondents for the screener
and main interviews?
In the screener interview, proxy
respondent reports were allowed if the
sampled adult respondent was either too
ill or infirm but wanted to participate or
the respondent was unavailable at the
screening contact (initially this
unavailable status only applied to a
subset of cases for the validation
substudy). If the sampled respondent
was available at the time of contact, he
or she completed the screener interview
directly.
Page 4 [ Series 1, No. 46
In the main interview, several
scenarios were possible:
+ If the sampled adult respondent was
too ill or infirm, the detailed
interview was conducted or
terminated depending on the
respondent’s asthma status.
+ If the proxy-reported asthmanegative sampled adult was finally
reached (or called in), he or she
was asked to confirm their
proxy-reported asthma status; the
data file contains the information
from both calls. If the proxynegative report was wrong and the
sampled adult did in fact have
asthma, the interview continued with
the asthmatic sampled respondent
through self-report. If the sampled
respondent was asthma-positive, he
or she completed the detailed
interview. If the respondent did not
have asthma, the interview was
terminated after a few demographic
questions were asked.
+ If the proxy-reported asthmanegative sampled adult was never
reached, only the proxy-reported
responses were included in the file.
Please contact slaits@cdc.gov if you
still need assistance after you read the
appropriate sections in this report.
Methods
Sample Design
SLAITS studies benefit from the
large number of screening calls required
for NIS. NIS was established in 1994 to
monitor immunization levels of very
young children in the United States. It
screens well over one million
households per year but conducts
detailed interviews in only a small
portion (those that contain at least one
child aged 19 to 35 months, the primary
target of immunization programs).
Because this large screening sample has
been contacted, SLAITS enjoys
considerable cost savings by avoiding
the expense of frame development,
sample selection, and residential
screening.
The 2003 NAS consisted of two
samples: a national sample and a
four-state sample that includes Alabama,
California, Illinois, and Texas. NAS
used the NIS sample to assess asthma
prevalence at the national level and
characterize the content of care and
limitations of people with asthma in the
four states and at the national levels.
Because the four-state file contains only
respondents who screened in as
asthma-positive, this sample can be used
to examine detailed characteristics and
behaviors of asthma-positive persons but
cannot be used to determine prevalence.
Information needed to calculate the
prevalence rate was not obtained during
screening for the four-state sample.
Because of the weighting procedures
used for the national sample (which are
covered in ‘‘Weighting and Estimation
Procedures’’ as well as in Appendix B),
national prevalence estimates are
consistent with those produced by
NHIS. Prevalence estimates for
subpopulations within the national
sample may or may not be consistent
with NHIS. The two NAS files should
NOT be combined to produce more
precise estimates. Weighted estimates
can be calculated for each state in the
four-state sample (using a ‘‘where’’
statement to select the appropriate cases)
or for the four-state sample as a whole.
Each state was weighted up to its
appropriate population control totals.
The goal was to complete screening
interviews in 10,000 households in the
national study and in 12,000 households
in each of the states selected by NCEH
that comprise the four-state study. To
accomplish this, telephone numbers
were randomly selected from the NIS
sample.
The National Immunization
Survey sampling plan
This section describes the basic NIS
sample design and serves as a
nontechnical description of the NAS
sample design and allocation procedures.
Appendix B of this report includes a
more technical description of the NAS
sample design and weighting
procedures.
Each quarter of the year, NIS
screens telephone numbers to identify
households that contain at least one
child aged 19–35 months. Because less
than 4% of households in the United
States contain children in this age range,
a large number of households must be
contacted and screened to identify
households with eligible children.
Households are selected for screening
through list-assisted RDD methods.
In the United States, telephone
numbers consist of an area code of three
digits, a central-office code of three
digits, and a suffix of four digits.
Combined, an area code and centraloffice code form a prefix area. For
example, 617–492 is the prefix area
corresponding to the 492 central office
in the 617 area code. For NIS, prior to
the selection of the sample of telephone
numbers, banks of 100 consecutive
numbers in the same area code and
prefix combination that contain zero
directory-listed residential telephone
numbers—that is, banks of 100 numbers
that have a low probability of containing
working residential numbers—are
deleted from the sampling frame. For
this step, the GENESYS Sampling
System (a proprietary product of
Marketing Systems Group) uses a file of
directory-listed residential numbers from
Donnelley Marketing Information
Services. The sampling frame of
telephone numbers is updated each
quarter to reflect new telephone
exchanges and area codes. The NIS
sampling frame excludes cellular
telephone exchanges. A random sample
of 10-digit telephone numbers is then
drawn from the retained banks of 100
numbers. A further step eliminates
business and nonworking telephone
numbers from the sample prior to
dialing.
Each remaining telephone number is
then called by an interviewer. If it
belongs to a household, the person
answering the telephone is asked
whether any children aged 19–35
months are living or staying in the
household. If the household contains an
NIS-eligible child or children, NIS is
conducted in its entirety. This is
followed by a NAS screening and the
full NAS interview (if eligible). In
Series 1, No. 46 [ Page 5
households that do not contain a 19- to
35-month-old child, the NAS interview
immediately follows the NAS screener
(if eligible).
The National Asthma Survey
sample design and allocation
When the 2003 NAS was
conducted, the NIS sample design
consisted of 78 distinct geographical
areas that comprised the United States.
Of these 78 Immunization Action Plan
(IAP) areas, 50 were states and 28 were
urbanized areas. To achieve the target of
10,000 completed household screeners
for the national study and 12,000 in
each of the four states, the sample was
allocated in proportion to the total
number of households in a specific
geographic area. In the national NAS,
the number of households required to be
selected in each state was determined by
allocating the desired number of
screened households among states in
proportion to the total number of
households in each state. Then, the
number of telephone numbers that
needed to be called was computed using
the expected working residential number
rate in each geographic area. The
number of telephone numbers drawn
compensated for the fact that not all
respondents would agree to participate.
Because of the quarterly selection
and release of the NIS sample in each
IAP, some telephone numbers were
selected more than once during the NAS
data collection period. Such numbers
were not contacted a second time for the
study. Instead, these cases were
automatically finalized and assigned the
final disposition code from the original
sample. Response rates reflect the final
disposition of a telephone number from
its original sampling.
The national study screened a single
randomly selected household member
about his or her asthma status.
Regardless of asthma status, the
screening interview included a series of
demographic questions concerning the
sampled person and the household to
allow for the production of asthma
prevalence rates. If sampled respondents
indicated that they had ever been told
by a doctor or other health professional
that they had asthma, a detailed
interview on asthma management and
treatment was completed. If a
respondent was asthma-negative, a small
subset of items from the detailed
interview was administered. In contrast,
the four-state study involved screening
all household members for the presence
of someone with asthma. If no one was
reported to have asthma, the interview
was terminated. In households where
asthma was reported, up to one
asthma-positive adult and one
asthma-positive child were randomly
selected per household for a detailed
interview on asthma management and
treatment.
Augmentation sample
Insufficient NIS sample was
available to complete the desired
number of interviews for both studies.
Additional telephone numbers were
drawn to add cases to (or ‘‘augment’’)
the overall sample using the GENESYS
Sampling System. The augmentation
cases did not receive the NIS
age-screening question or immunization
questions. The augmentation cases only
received the NAS screening interview
(and if appropriate, the entire asthma
interview). The NAS-only sample adds
cases to the overall traditional sample
and is called the ‘‘augmentation
sample.’’ To protect confidentiality, the
variable that indicates augmentation
sample status has been suppressed.
Table A shows, by sample, the
proportion of the NAS sample that is
from the augmentation sample. That is,
for each sample and state listed in
Table A, the proportion listed is the
proportion of telephone numbers that
were called specifically for NAS.
Proxy Interviews
As noted above, the national study
selected a single household member at
random for asthma screening. If the
sampled household member was a child
under the age of 18 years, screening
questions were answered by an adult
knowledgeable about the child’s health.
If the sampled household member was
aged 18 years or over, screening
questions were asked of that sampled
adult whenever possible. However, in
the initial design, if the sampled adult
was not available at the time of the
screening contact, a proxy interview was
conducted with the adult household
member who answered the telephone.
The proxy interview included, at a
minimum, questions about the sampled
adult’s asthma status, age, and sex. If
the sampled adult was reported to be
asthma-positive, an appointment was
scheduled to complete a detailed
interview directly with the sampled
person, and asthma status was confirmed
with that person upon callback. The
initial design of the national study also
called for a subset of 500 sampled
adults who were reported by a proxy
respondent to be asthma-negative to be
called back to confirm their asthma
status (to assess the extent of
proxy-report error).
Error rates in proxy reporting are
shown in Table B and were calculated
using weighted data; chi-square
significance testing was performed using
SUDAAN software (11). Proxies
incorrectly reported 37.3% of lifetime
asthma cases, but correctly identified
99.3% of asthma-negative cases. The
overall proxy reporting error rate was
4.7%, computed by dividing the false
Table A. Percentage of overall sample that is an augmentation sample: NAS, 2003
Percent of sample called
only for NAS
Sample
National . .
Four-state
Total. . . .
Alabama .
California.
Illinois. . .
Texas . . .
. . . . . . . . . . . . . . . . . . . . .
75.0
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.
52.4
61.5
36.9
61.9
50.0
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NOTE: NAS is National Asthma Survey.
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Page 6 [ Series 1, No. 46
Table B. Weighted error rates in proxy reporting: NAS, 2003
1
Proxy-reported lifetime asthma status
Self-reported lifetime asthma status
Positive n
Percent
Negative n
Percent
Positive . . . . . . . . . . . . . . . . . . .
Negative. . . . . . . . . . . . . . . . . . .
72
7
62.7
0.7
50
955
37.3
99.3
1
Sample sizes are unweighted; error rates are weighted.
NOTES: p < 0.001. NAS is National Asthma Survey.
reports by all reports (12). The proxy
error reporting rate of lifetime asthma
status for current asthma cases is lower
than the proxy error reporting rate of
lifetime asthma status for former asthma
cases (data now shown). Proxies
correctly identified the lifetime asthma
status of 71.5% of the current asthma
cases but only correctly identified the
lifetime status of 61.7% of the former
asthma cases (data not shown). Although
this difference is not statistically
significant, it does suggest that proxies
are more likely to identify lifetime
status correctly if the asthma is currently
active (12). The relationship of the
proxy to the sampled person was also
related to the accuracy of reporting, with
mothers committing the fewest reporting
errors (data not shown) (12). Based on
these results, a decision was made to
expand confirmation calls to all sampled
persons with proxy-reported asthmanegative status.
These findings also greatly
influenced the reporting of results
through the creation of specific flag
variables and two weights for the
national sample. A flag variable was
added to the national sample data file
(FLG_ASTHMA) to indicate whether
asthma status for the sampled
respondent was obtained from the
sampled or proxy respondent. Proxy
respondents reported asthma status in
12.8% of cases (n = 1,100) in the
national sample.
Two different weights were created
for the national sample as a result of the
verification substudy findings. Both
weights include all sample child cases,
but they differ on the inclusion of
sample adult cases. For example, the
weight post_pr_int includes all sample
adult proxy and self-report cases, in
contrast to the second weight
(post_sr_int), which only includes
sample adult self-report screener and
interview cases. These weights are
discussed in more detail in the
weighting and estimation procedures
chapter and Appendix B.
Proxy responses due to illness or
infirmity—Detailed asthma interviews
were conducted for cases in both
samples with proxy respondents if the
sampled respondent was too ill or infirm
to answer questions. In the national
sample, 103 cases, or 1.2% of the
sample, were completed by a proxy
respondent because of a respondent’s
illness. In the four-state sample, 68
cases (1.2%) were completed by a proxy
respondent because of a respondent’s
illness or infirmity.
Tracking proxy cases—For both
studies, a variable called FLG_TYPE
was created to facilitate data navigation
and establish the questionnaire path per
respondent. The FLG_TYPE variable
has 11 values for the national sample to
account for the verification substudy
paths, in contrast to 4 values for the
four-state file. For the national sample,
proxy and sampled respondent
information is available for some cases
if the sampled respondent was able to
be contacted and interviewed after
researchers spoke with the proxy
respondent.
Questionnaire
Questionnaire development
The initial questionnaires were
designed by NCEH and further refined
based on cognitive testing and a series
of four pretests that are described in
more detail in Appendix E. Many
questions included in the instruments
were borrowed directly from other
national surveys (such as NHIS, the
National Health and Nutrition
Examination Survey [NHANES], and
BRFSS) to facilitate comparison and
because many of these questions had
already undergone extensive testing.
Other questions were written for this
survey to measure progress toward
Healthy People 2010 goals and the
translation of the National Asthma
Education and Prevention Program
guidelines into practice.
Content
The NAS questionnaires were
designed to immediately follow a
completed NIS interview in households
with an NIS-eligible child or to follow
the NIS screener in households without
an NIS-eligible child. They were divided
into eight sections:
1. NAS eligibility screening,
respondent selection, and initial
demographics—For both studies, a
person who answered the telephone
in group quarters such as barracks,
dormitories, hospitals, or schools
was coded as ‘‘does not live in a
household.’’ In the national study,
one respondent was randomly
selected out of all household
members, and the asthma status of
the selected respondent was
determined. The sampled person’s
age and sex were also obtained. In
the four-state study, an entire
household was screened for asthma.
If no one was reported to have
asthma, the interview was
terminated. In households where
asthma was reported, up to one
asthma-positive adult and one
asthma-positive child were
randomly selected for a detailed
interview, and the age and sex of
the sampled respondents were
collected.
2. History of asthma (symptoms and
episodes)—This section, the first in
the detailed interview, assessed the
length of time since the sampled
respondents had experienced asthma
symptoms, taken asthma medication,
or seen a doctor for an asthmarelated reason. This section also
addressed the frequency and severity
Series 1, No. 46 [ Page 7
3.
4.
5.
6.
7.
8.
of asthma symptoms and attacks or
episodes.
Health care utilization—These
questions asked about the
availability of asthma-related
medical services and the degree to
which these services were used.
Respondents were asked whether
they had visited a doctor, urgent care
center, or emergency room for
asthma treatment within the past
year. Respondents were also asked
questions about their current health
insurance coverage.
Knowledge of asthma management
plan—This section asked respondents
whether they had ever received specific
types of asthma-related information or
treatment from a health professional,
including a written asthma management
plan and a description of methods for
recognizing asthma symptoms and
episodes.
Modifications to environment—The
goal of this section was to determine
whether respondents had made a
series of modifications to their home
environment to reduce exposure to
indoor asthma triggers. Additional
questions for adult respondents
asked whether they had been
exposed to asthma triggers at their
place of employment.
Medications—In this section,
respondents were asked whether they
took asthma medications in inhaler,
pill, syrup, or nebulizer form. A list
of the medications taken in each
manner was obtained. For inhaler
medications, additional questions
asked about the frequency and
pattern of medication use.
Family history of asthma—This section
included questions regarding the
asthma history of the respondent’s
siblings, parents, and grandparents. In
the national study, respondents were
also asked whether any household
members other than the person sampled
or family member of the sampled
person had asthma.
Demographic information—A series
of demographic items such as race,
ethnicity, highest level of education,
and income were asked. Respondents
were also asked about the number of
landline telephone numbers in the
household and whether interruptions
in household telephone service
occurred during the past year.
Although height, weight, and
birthweight are not usually
considered demographic variables,
they were deliberately placed in the
last section of the instrument to
reduce item and section nonresponse.
The answers to these items may be
considered to be very personal and
sensitive for some respondents, and,
as a result, these respondents may
hang up the phone immediately
when asked these questions. A
respondent would probably not hang
up the telephone at the final stage of
an interview after investing a
considerable amount of time to
answer other questions.
The two instruments are included in
Appendixes III (national study) and IV
(four-state study). In the national study,
the questionnaire sections that were
administered depended upon the type of
respondent (proxy compared with
sampled respondent) and the sampled
person’s asthma status. Table C
illustrates the various paths that the
national study questionnaire could take
and are classified from optimal to least
optimal. The optimal situation was for
the sampled adult respondent to provide
screener and detailed interview
information. If a proxy respondent
provided screener information initially,
the adult sampled respondent was
recontacted directly, proxy-reported
information was verified, and the
detailed interview was completed with
the adult sampled respondent.
Proxy-reported information that was
verified or changed by the sampled
respondent is only provided for
methodological purposes. The next best
scenario was a proxy report for screener
and selected interview items because the
subject was not available or too ill to
participate. The least favorable scenario
was if the adult sampled respondent
could not be located at all, and proxy
responses provided the only information.
For sampled children under the age of
18 years in both samples, a
knowledgeable respondent 18 years of
age or over provided all screener and
detailed interview information for the
sampled child. All questionnaire sections
were administered in the four-state study
interviews.
CATI programming
NAS was conducted using a
computer-assisted telephone
interviewing (CATI) system. The CATI
data collection software presents the
questionnaire on computer screens to
each interviewer. The program guides
the interviewer through the
questionnaire, automatically routing the
interviewer to appropriate questions
based on previous responses.
Interviewers enter the responses to the
questions directly into the computer; the
CATI program determines whether the
selected response is within an allowable
range, checks it for consistency against
other data collected during the interview,
and saves the responses in a survey data
file. This data collection technology
reduces the time required for
transferring, processing, and releasing
data and also promotes data accuracy.
The NAS questionnaire was
programmed as a module of NIS,
integrating the two surveys into a single
interview. The instrument made full use
of the CATI system’s ability to check
whether a response was within a
legitimate range, to follow skip patterns,
and to employ ‘‘pick lists’’ for response
categories. Certain household and
demographic questions were identical in
the NIS and NAS portions of the
interview. If a respondent answered
these questions during NIS
administration, the system was
programmed so that the questions were
not repeated in NAS. Instead, the
answers to the appropriate NIS
questions were copied to the data file
for NAS. Once initial programming was
completed, the instrument underwent
rigorous testing to ensure correct
functioning of the CATI system.
Development and
Implementation of NAS
Interviewer Training
Outline and materials
Training sessions lasted
approximately 12 hours and were
If the sampled respondent is
asthma-positive
If the sampled respondent is asthma-negative
Questionnaire section
Is the proxy respondent
asked these questions?
Is the sampled respondent
asked these questions?
Are these questions asked
in the callback interview for
adults with proxy-reported
asthma-negative status?
NAS eligibility screening, respondent
selection, and initial demographics . .
Yes
Yes
Yes
Yes
History of asthma (symptoms and
episodes) . . . . . . . . . . . . . . . . . .
No
No
No
No
Health care utilization. . . . . . . . . . .
Health care
coverage
items only
Health care
coverage
items only
Health care
coverage
items only
Health care
coverage
items only
Knowledge of asthma/management
plan . . . . . . . . . . . . . . . . . . . . .
No
No
No
No
Modifications to environment . . . . . .
Subset of
household
environment items
Subset of
household
environment items
Subset of
household
environment items
Subset of
household
environment items
Medications . . . . . . . . . . . . . . . . .
No
No
No
No
Family history of asthma . . . . . . . . .
Single question on
asthma status of other
household members
Yes
Yes
Single question on
asthma status of
other household members
Demographic information . . . . . . . .
Yes
Yes
Yes
Is the proxy respondent
asked these questions?
Yes
NOTE: NAS is National Asthma Survey.
Page 8 [ Series 1, No. 46
Table C. Questionnaire flow in the national study: NAS, 2003
Series 1, No. 46 [ Page 9
conducted over 2 consecutive days. The
following topics were covered:
1. Overview of the project—
Background information and an
introduction to the study and its
sponsors.
2. Purpose and importance of the
study—An explanation of why the
study was being conducted and
what it was designed to accomplish.
3. Goals and expectations of the
study—A description of the target
goals for the number of completed
interviews and the expected time
frame for data collection.
4. Relationship to NIS—A discussion
of how NAS was conducted in
conjunction with NIS, including
information about the eligibility
criteria for the two studies, the
length of time required to conduct
both surveys, and the procedures to
be followed for gaining cooperation
for each study.
5. Discussion of each questionnaire
section and question-by-question
specifications—An analysis of each
questionnaire section and its
purpose. Mock interviews were
conducted to acquaint interviewers
with the questionnaire and to
provide them with the project
knowledge and refusal aversion
skills necessary to conduct an
interview. Two types of mock
interviews were performed:
trainer-led interviews (in which the
trainer played the role of the
respondent and the interviewers
conducted the interview using the
CATI system) and dual-trainee
interviews (in which one trainee
performed the role of the
interviewer and another acted as the
respondent).
6. Skills necessary to display project
knowledge and gain cooperation—
In-class practice of answers to
questions frequently asked by
respondents and refusal aversion
techniques as well as role-playing
exercises. A project-specific job aid
facilitated mastery of these
concepts.
Because the NAS questionnaire
required interviewers to be able to
pronounce the names of a number
of asthma medications, emphasis
was placed on the correct
pronunciation of those names.
Interviewers were provided with
audiotape pronunciations to allow
them to practice outside of training
sessions, and exercises within the
sessions stressed correct
pronunciation.
7. Capacity to conduct the interview
with the CATI program—Mock
interviews were performed to
accomplish this objective, including
a final evaluation mock interview in
which interviewers were required to
demonstrate successfully their
ability to administer the
questionnaire.
Interviewer training materials for
NAS included the following:
1. Interviewer manual—An
interviewer training manual served
as a reference guide during training
and data collection. The manual
included an agenda that listed the
topics to be covered, an overview
of the study, a description of each
questionnaire section, techniques for
gaining cooperation, and case
management procedures.
2. Slide-show presentation—A
PowerPoint slide show was used as
a training tool during trainer
lectures to facilitate the learning
process.
3. Question-by-question
specifications—This documentation
provided further information on
administering selected questions and
included special instructions to the
interviewers on how to probe for
answers and code key data
elements.
4. Job aids on refusal aversion and
frequently asked questions—Refusal
aversion responses and questions
frequently asked by respondents
were discussed during the
gaining-cooperation module of
interviewer training. The discussion
covered general interviewing and
NAS project-specific issues.
Final review exercises at the
conclusion of each training session
consisted of a question-and-answer
discussion summarizing the topics
taught during the course of the session
and an interactive review modeled after
a game-show format, in which
interviewers split into two teams and
competed for points based on project
knowledge and refusal aversion
techniques.
A final test mock interview and
written evaluation were administered at
the end of each training session. This
mock interview was standardized,
allowing interviewers to be evaluated
against the same standard on their
ability to navigate through CATI, gain
cooperation, and display project
knowledge. The written evaluation
aimed to reinforce what was learned
during the course of training. Each
trainer received a written evaluation
answer guide to rate the proficiency
level of the interviewer. Interviewers
had to complete successfully both
evaluations before they were permitted
to collect data for NAS.
Training
The initial NAS data collection staff
members were recruited during January
2003. To offset interviewer attrition,
recruitment and training continued to be
offered throughout 2003 at centralized
telephone call centers in Chicago,
Illinois, and Las Vegas, Nevada. The use
of two telephone centers facilitated
sample dialing across multiple time
zones. A total of 115 Chicago
interviewers and 177 Las Vegas
interviewers were trained for the study.
Data Collection
Telephone interviews were
conducted from February 27, 2003,
through February 20, 2004, for the
national study, and March 1, 2003,
through March 10, 2004, for the
four-state study. A total of 10,054
household screening interviews and 955
detailed asthma interviews were
completed in the national study. In the
four-state study, 48,185 households were
screened for the presence of someone
with asthma, and 5,741 detailed asthma
interviews were completed. The mean
number of calls made to complete a
national study interview was six, with a
median of four calls. In the four-state
Page 10 [ Series 1, No. 46
Table D. Completed screening and detailed interviews for national study: NAS, 2003
Age
Screening interviews: household level . . . . . . . . . .
Detailed interviews: person level . . . . . . . . . . . . .
Total
Less than
18 years
10,054
955
1,351
164
18 years
or over
8,703
791
NOTE: NAS is National Asthma Survey.
Table E. Completed screening and detailed interviews for four-state study: NAS, 2003
Age
Screening interviews: household
level . . . . . . . . . . . . . . . . . . . .
Detailed interviews: person level . . . .
been resolved as households without
respondent eligibility being determined
(1.4% of the initial sample for the
national study and 4.2% of the initial
sample for the four-state study). An
even smaller number of households with
an eligible respondent did not complete
the interview (0.4% of the initial
national study sample and 1.1% of the
initial four-state study sample).
Data collection by month
State
Total
Less than
18 years
18 years
and over
Alabama
Illinois
California
Texas
48,185
5,741
...
2,005
...
3,736
12,160
1,488
11,898
1,313
11,998
1,433
12,129
1,507
Table F lists the number of
interviews conducted per month by
study from February 2003 through
March 2004.
Pretests
. . . Category not applicable.
NOTE: NAS is National Asthma Survey.
Table F. Number of interviews completed by month: NAS, 2003
Month and year
National study
Four-state study
Total . . . . . . . . . . . . . . . . . . . . .
10,054
5,741
.
.
.
.
.
.
.
.
.
.
.
13
761
870
316
1,139
460
878
1,142
458
1,076
1,799
...
102
850
456
447
377
411
411
597
187
241
January . . . . . . . . . . . . . . . . . . .
February . . . . . . . . . . . . . . . . . .
March . . . . . . . . . . . . . . . . . . . .
1,016
126
...
1,142
464
56
2003
February .
March . . .
April . . . .
May . . . .
June . . . .
July . . . .
August . .
September
October . .
November .
December .
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2004
. . . Category not applicable.
NOTE: NAS is National Asthma Survey.
study, the mean number of calls to
complete an interview was five, with a
median of three calls.
Table D details the total number of
screening and detailed interviews
completed in the national study overall
and by age.
Table E lists the number of
households screened and detailed
interviews completed in the four-state
study overall, by age, and by state.
Pending cases at the end of
data collection
For most cases pending at the end
of the data collection period, the
telephone number had not yet been
resolved as residential or nonresidential
(72.7% of pending cases and 21.0% of
the initial sample for the national study;
76.8% of pending cases and 19.4% of
the initial sample for the four-state
study). A smaller number of cases had
A series of four pretests was fielded
to determine the most effective data
collection methodology for the main
study—one that would obtain the
highest possible response rates, produce
asthma prevalence estimates, and gather
high-quality analytic data for people
with asthma. Appendix E provides
details on each pretest, as well as the
advance letters and introductory scripts.
Address matching process
To obtain addresses that
corresponded to RDD-generated
telephone numbers, generated telephone
numbers (i.e., the initial sample) were
first matched against a database that
contained telephone numbers that are
directory listed in a business yellow
pages and are not directory listed in a
residential white pages. Any business
numbers so identified were removed
from the sample. Numbers listed in the
residential white pages were identified
and temporarily set aside. A
computerized system screened the
remaining sample to remove
nonworking numbers. The residential
white pages directory-listed numbers
were then combined with those not
removed by the computerized system to
produce the sample. To obtain addresses
that corresponded to the RDD-generated
telephone numbers in the sample, a file
containing the RDD-generated telephone
numbers was sent to a subcontractor to
be processed through that company’s
address-matching program. This
Series 1, No. 46 [ Page 11
computerized name-and-address-locating
service uses a database of more than
160 million residential and business
telephone numbers, including
unpublished telephone numbers. In some
instances, by customer preference, a
listing might not have contained a street
address. The resulting file contained
listed and unlisted numbers for the
released sample. Matched listings
contained a business or residential
identifier.
Advance letter
An advance letter was mailed to
presumed households where the address
matching process identified a mailing
address for sampled telephone
numbers—41.9%(initial sample) and
69.6% (released sample) for the national
study, and 41.2% (initial sample) and
67.3% (released sample) for the
four-state study. Recipients were asked
to participate in a voluntary study on the
immunization of their children, and the
letter also noted that some households
might be asked questions about asthma
and other health-related topics or
services. The letter advised recipients
that their telephone numbers had been
chosen randomly and indicated that they
might be called in the next few weeks.
A toll-free telephone number was
provided for those who wished to
participate immediately or to learn more
about the study.
As described earlier, a NAS-only
(or ‘‘augmentation’’) sample was
fielded. Households in the NAS-only
sample with an identified mailing
address were mailed an advance letter
different from that used for households
in the NIS sample. This advance letter
asked respondents to participate in a
study specifically regarding asthma and
provided asthma-related key health
statistics. No mention was made of NIS
or childhood immunization. The advance
letters used for the main NAS studies
are in Appendix VI.
Toll-free telephone number
A toll-free telephone number was
provided in the advance letter, in
answering-machine messages, and by
interviewers at the request of
respondents. Potential respondents could
use this number to ask questions about
the study or to complete an interview. In
the national study, a total of 260
screening interviews and 44 detailed
interviews were completed with
respondents who called the toll-free
telephone number. In the four-state
study, 912 households were screened
and 208 detailed interviews were
completed via the toll-free telephone
line.
Informed consent
Consent for study participation was
obtained from NAS respondents
immediately upon determining that at
least one person with asthma lived in
the household. Respondents were
informed about the voluntary nature of
the survey, the authorizing legislation,
and the confidentiality of data collected.
In addition, the informed consent script
provided information about the content
of the survey and the expected duration.
These procedures were approved by the
Abt Associates Incorporated Institutional
Review Board and the NCHS Research
Ethics Review Board.
Assurance of confidentiality
Participation in surveys conducted
by NCHS is voluntary, and information
collected on persons is confidential. For
NAS, assurance of confidentiality was
provided to potential respondents as part
of the informed consent procedures. In
the CATI system, interviewers
acknowledged that they had read the
following script to potential respondents:
Before we continue, I’d like you to
know that this research is
authorized by the U.S. Public
Health Service Act so your answers
will be kept strictly private. Your
participation is voluntary. You may
choose not to answer any question
you don’t want to answer or stop at
any time without penalty.
If a respondent requested a description
of the authorizing legislation, the
interviewer read the following:
The Public Health Service Act is
Volume 42 of the US Code, Section
242k. The collection of information
in this survey is authorized by
Section 306 of this Act. The
confidentiality of your responses is
assured by Section 308d of this Act.
Section 308d of the Public Health
Service Act (42 U.S.C. 242m) states the
following:
No information, if an establishment
or person supplying the information
or described in it is identifiable,
obtained in the course of activities
undertaken or supported under
section . . . 306 . . . may be used for
any purpose other than the purpose
for which it was supplied unless
such establishment or person has
consented (as determined under
regulations of the Secretary) to its
use for such other purpose and in
the case of information obtained in
the course of health statistical or
epidemiological activities under
section . . . 306, such information
may not be published or released in
other form if the particular
establishment or person supplying
the information or described in it is
identifiable unless such
establishment or person has
consented (as determined under
regulations of the Secretary) to its
publication or release in other form.
Strict procedures are used to prevent
disclosure of confidential data in survey
operations and data dissemination.
Respondent selection process:
national sample
As described earlier, the national
study selected a single household
member at random. First, a household
member aged 18 years or over was
asked the number of people of all ages
living in the household, followed by the
number of females living in the
household. The CATI system created an
internal household roster of oldest to
youngest household members by sex
Page 12 [ Series 1, No. 46
based on this information and randomly
selected a household member from that
roster (e.g., the oldest male or the
second oldest female). Once a household
member was sampled, the asthma status
of that person was determined by asking
‘‘[Have you/Has the (selected person) in
your household] ever been told by a
doctor or other health professional that
[you have/(he or she has)] asthma?’’
Persons with a positive response to this
question were classified as having a
lifetime asthma-positive status.
Regardless of the sampled person’s
lifetime asthma status, the screening
interview included a series of
demographic questions about the
sampled person and the household to
allow for the production of asthma
prevalence rates. If the sampled
respondent was asthma-positive, a
detailed interview regarding asthma
management and treatment was also
completed. If the sampled target of the
interview was a child under 18 years of
age, the entire interview was conducted
with an adult household member (18
years of age or over) knowledgeable
about the child’s health, regardless of
sample type.
Based on asthma status and
availability of the sampled person, six
outcomes were possible for national
sample respondents:
+ The sampled person had asthma and
was immediately available for
interview. In these cases, a detailed
asthma interview, including all
demographic and household
information as well as asthmaspecific items, was completed.
+ The sampled person had asthma,
was not immediately available for
interview, but completed the detailed
interview on a later calling attempt.
In these cases, the person who was
on the telephone at the initial call
(i.e., a proxy) was asked a select
group of household and
demographic questions. On a later
call with the sampled person, a
detailed asthma interview including
all demographic and household
information as well as asthmaspecific items was completed.
+ The sampled person had asthma,
was not immediately available for
interview, and future attempts to
complete a detailed interview with
that person were not successful. In
these cases, the person who was on
the telephone at the initial call (i.e.,
a proxy) was asked a select group of
household and demographic
questions only. No further data were
collected.
+ The sampled person did not have
asthma and was immediately
available for interview. In these
cases, demographic and household
information was gathered from the
sampled person to allow for the
production of national asthma
prevalence rates.
+ The sampled person did not have
asthma, was not immediately
available for interview, but did
complete a verification interview on
a later calling attempt. In these
cases, the person who was on the
telephone at the initial call (i.e., a
proxy) was asked a select group of
household and demographic
questions. On a later call with the
sampled person, that person’s
asthma status was verified.
+ The sampled person did not have
asthma, was not immediately
available for interview, and future
attempts to complete a verification
interview with that person were not
successful. In these cases,
demographic and household
information was gathered from the
person who was on the telephone at
the initial call (i.e., a proxy) to
allow for the production of national
asthma prevalence rates. No further
data were collected.
In the national sample, proxy
interviews were also conducted if the
adult sampled respondent was ill or
unable to complete the interview over
the telephone. These interviews were
conducted with another adult in the
household. For a sampled child, all
interviews were conducted with a
knowledgeable adult household member.
Respondent selection process:
four-state sample
The four-state survey immediately
screened households for the presence of
someone with asthma, using a single
question: ‘‘Including yourself, has
anyone living in your household ever
been told by a doctor or other health
professional that they have asthma?’’
(exercise-induced asthma was coded as
a positive response to this question). If
no one in the household was reported to
have asthma, the interview was
terminated. In households where asthma
was reported, the number of asthmapositive adults aged 18 years and over
and asthma-positive children under 18
years of age were obtained. The CATI
system created internal rosters of
asthma-positive adults and children
based on this information and randomly
selected a maximum of one asthmapositive adult and one asthma-positive
child for a detailed interview about
asthma management and treatment. If a
household had a sampled adult and a
sampled child, two detailed interviews
were administered in that household.
Thus, for the four-state study in
asthma-positive households, there were
three possible sampling outcomes:
+ One adult sampled for a detailed
interview, but no child sampled for a
detailed interview.
+ One child sampled for a detailed
interview, but no adult sampled for a
detailed interview.
+ One adult and one child sampled for
detailed interviews.
Interview length
Mean and median interview length
varied by NIS eligibility because some
demographic and household questions
necessary for NIS and NAS were
administered as part of the NIS
interview and were not repeated during
the NAS interview. In the four-state
study, interview length also varied
according to whether one or two
household members were sampled. As
noted earlier, four-state study interviews
consisted of the full questionnaire.
Mean and median interview lengths
(excluding the NIS interview) are shown
in Table G.
Table H reports mean and median
screening interview lengths by NIS
eligibility for the national study. NIS
eligibility refers to household eligibility
Series 1, No. 46 [ Page 13
Table G. Mean and median interview length in minutes and seconds: NAS, 2003
Study
National study
Screening interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Detailed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Four-state study
Detailed interview: households in which only an adult was sampled
Detailed interview: households in which only a child was sampled .
Detailed interview: households in which both an adult and a child
were sampled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mean
Median
. .
. .
7:15
9:27
6:20
8:59
. .
. .
17:20
17:46
16:21
16:55
. .
27:57
26:37
asthmatic child per household were
eligible to be selected for inclusion. In
households in which an adult and a
child were sampled as targets of the
interview, household-level questions
were not repeated in both interviews.
Thus, the mean and median lengths of
an adult and child interview cannot be
added together to calculate a combined
total interview length.
NOTE: NAS is National Asthma Survey.
Refusals
Table H. Mean and median length of screening interview for national study in minutes and
seconds, by respondent NIS eligibility: NAS, 2003
NIS eligible
NIS ineligible
Section
Mean
Median
Mean
Median
Overall length . . . . . . . . . . . . . . .
Section 1:
Detailed asthma screening . . . . . . .
Section 8:
Demographics . . . . . . . . . . . . . . .
5:35
5:13
7:17
6:21
3:47
3:34
3:35
2:59
2:06
1:52
3:41
3:06
NOTES: NIS is National Immunization Survey. NAS is National Asthma Survey.
Table J. Mean and median length in minutes and seconds for national study detailed
interview, by NIS eligibility: NAS, 2003
NIS eligible
Spanish-language interviewing
Mean
Median
Mean
Median
. .
9:04
9:05
9:28
8:59
. .
1:10
0:59
1:06
1:01
. .
1:10
1:08
1:20
1:10
. .
1:00
0:58
0:47
0:50
. .
2:39
2:32
2:47
2:34
. .
2:10
2:16
2:39
2:10
. .
0:53
0:49
0:47
0:43
Interview section
Overall length . . . . . . . . . . . . .
Section 2:
History of asthma . . . . . . . . . . .
Section 3:
Health care utilization. . . . . . . . .
Section 4:
Knowledge of asthma/management
plan . . . . . . . . . . . . . . . . . . .
Section 5:
Modification to environment . . . .
Section 6:
Medications . . . . . . . . . . . . . . .
Section 7:
Family history of asthma . . . . . . .
NIS ineligible
NOTES: NIS is National Immunization Survey. NAS is National Asthma Survey.
(i.e., at least one child in the household
was 19–35 months of age at the time of
the interview). The NIS-eligible child in
the household may or may not have
been the child sampled for the NAS
interview.
Table J reports mean and median
interview lengths by section and NIS
eligibility for the national study detailed
interview. As described previously, the
In cases where an interview was
begun but not completed, speciallytrained interviewers attempted refusal
conversion. By the end of data
collection for the national study, these
interviewers completed 2,384 screening
interviews and 111 detailed interviews
with households that had originally
refused to participate, or 23.7% of all
screening interviews and 11.6% of all
detailed interviews. For the four-state
study, these interviewers completed 615
detailed interviews with households
(including all person-level interviews
necessary within the household) that had
originally refused to participate (e.g.,
12.0% of all detailed interviews at the
household level).
national sample data were only
self-reported if the sampled adult was
available at the time of the screening
interview. If the sampled adult was not
available, proxy responses from another
adult in the household were accepted.
Table K reports mean and median
interview lengths by section and NIS
eligibility for the four-state study. In this
study, up to one asthmatic adult and one
NAS interviews were administered
in Spanish as well as English. A
professional translator, with extensive
experience in the translation of surveys,
produced a Spanish-language version of
the NAS questionnaire. A team of
experienced Spanish-language telephone
interviewers and supervisors reviewed
the translation, evaluating it for accuracy
and cultural appropriateness. Issues
raised during this review were resolved
in consultation with the original
translator, and a Spanish-language CATI
instrument reflecting the final translation
was produced.
For data collection and sample
management purposes, a calling queue
was used for households thought by
interviewers to be Spanish speaking. A
CATI flag indicated such households.
Cases with this flag were then delivered
through the CATI system to bilingual
interviewers who were specially trained
to conduct interviews in Spanish and
Page 14 [ Series 1, No. 46
Table K. Mean and median length of interview in minutes and seconds for four-state study
detailed interview, by NIS eligibility: NAS, 2003
NIS eligible
NIS ineligible
Interview section
Mean
Median
Mean
Median
Overall length . . . . . . . . . . . . . . . . . . . . . . . . .
16:08
14:34
18:31
17:13
Households in which only an adult was sampled . . .
13:56
13:14
17:23
16:23
Households in which only a child was sampled . . . .
15:44
14:36
17:52
17:05
Households in which both an adult and child were
sampled . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22:53
22:34
28:08
26:49
Section 1:
Detailed asthma screening . . . . . . . . . . . . . . . . .
4:04
3:29
4:07
3:22
Section 2:
History of asthma . . . . . . . . . . . . . . . . . . . . . . .
1:09
0:59
1:20
1:14
Section 3:
Health care utilization . . . . . . . . . . . . . . . . . . . .
1:34
1:33
1:38
1:29
Section 4:
Knowledge of asthma/management Plan . . . . . . . .
0:59
0:55
1:00
0:55
Section 5:
Modification to environment . . . . . . . . . . . . . . . .
2:32
2:31
2:49
2:38
Section 6:
Medications . . . . . . . . . . . . . . . . . . . . . . . . . .
2:32
2:10
3:16
2:58
Section 7:
Family history of asthma . . . . . . . . . . . . . . . . . .
0:49
0:42
0:48
0:41
Section 8:
Demographics . . . . . . . . . . . . . . . . . . . . . . . . .
2:27
2:08
3:34
3:11
NOTE: NIS is National Immunization Survey. NAS is National Asthma Survey.
English. In the national study, a total of
570 households in the Spanish-language
queue were screened, resulting in 28
completed detailed interviews. These
cases account for 5.7% of all screening
interviews and 2.9% of all detailed
interviews. In the four-state study, a
total of 282 Spanish-queue detailed
interviews were completed, accounting
for 4.9% of all detailed interviews.
weights were used in the calculations).
Rates were calculated separately for the
national and four-state studies. Within
each study, rates were calculated in total
and by sample type (i.e., the NIS sample
compared with the NAS-only sample).
Response rates calculated include the
interview completion rate (the
percentage of completed interviews
among eligible respondents), the
screener completion rate (the proportion
of known households screened for
asthma status), and the resolution rate
(the proportion of telephone numbers
Response rates
Weighted response rates for NAS
are shown in Table L (base sampling
that could be identified as nonworking,
residential, or nonresidential).
A standard approach for measuring
response rates in telephone surveys,
known as the ‘‘CASRO household
response rate,’’ has been defined by the
Council of American Survey Research
Organizations (CASRO) (13). The
CASRO response rate equals the
product of these rates and provides an
overall measure of response. CASRO
response rates were calculated in
accordance with the American
Association for Public Opinion
Research’s Standard Definitions: Final
Dispositions of Case Codes and
Outcome Rates for Surveys (14).
For the calculation of NAS response
rates, the assumptions for the American
Association for Public Opinion Research
(AAPOR) Response Rate 3 (RR3) were
used with one exception. The
denominator of RR3 includes a factor
called e, which is an estimate of ‘‘the
proportion of cases of unknown
eligibility that are in fact eligible’’ (15).
When calculating e, CASRO and
AAPOR guidelines indicate that the
survey researcher must estimate and
assume identical eligibility rates for
screened and unscreened households
when using the ‘‘proportional
allocation’’ or CASRO method (15,16).
However, if these assumptions are
incorrect (i.e., screened and unscreened
households are not eligible at the same
proportion), the RR3 formula will yield
an incorrect and conservative response
rate (15,16).
To estimate more accurately these
proportions and address the exception,
the NAS response rate calculation
incorporated research findings reported
by Frankel et al. (17), which used an
Table L. Weighted response rates: NAS, 2003
National study
Screening interview
Rates (expressed as percentage)
Resolution rate . . . . . . .
Screener completion rate .
Interview completion rate .
CASRO response rate. . .
...
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Four-state study
Detailed interview
Detailed interview
Total
sample
NIS
sample
NAS-only
sample
Total
sample
NIS
sample
NAS-only
sample
Total
sample
NIS
sample
NAS-only
sample
87.50
66.60
...
58.30
91.40
64.60
...
59.00
86.40
67.30
...
58.10
87.50
66.60
81.00
47.20
91.40
64.60
81.00
47.80
86.40
67.30
80.90
47.00
90.10
76.70
70.20
48.50
91.30
74.60
70.10
47.80
88.50
79.60
70.40
49.60
Category not applicable.
NOTES: NAS is National Asthma Survey. NIS is National Immunization Survey. CASRO is the Council of American Survey Research Organizations.
Series 1, No. 46 [ Page 15
alternate method to calculate e. In this
research, data were collected to estimate
the percentage of residential telephone
numbers among unresolved numbers
that had been finalized as ‘‘ring-no
answer at all attempts.’’ The presence of
ring-no-answer numbers in a telephone
sample makes calculating an accurate
estimate of the response rate difficult
because considerable uncertainty exists
regarding the proportion of such
numbers that are residential. In the
fourth quarter of 2002, a national
random subsample of telephone numbers
that had ring-no-answer to all NIS call
attempts was drawn (17). These
numbers were called 42 additional times
over an approximately 2-week period
with three attempts per day—morning,
afternoon, and evening. From this NIS
subsample, 20.4% of ring-no-answer
telephone numbers were estimated to be
residential and 79.6% were estimated to
be nonresidential, resulting in a
2.4 percentage point increase in the
CASRO rate over the standard CASRO
formula. Based on these results,
ring-no-answer cases in NAS were
redistributed: 20.4% were categorized as
known unscreened households and
79.6% were categorized as out of scope.
Response rates reflect this adjustment.
National study: screening interview
response rates—The overall CASRO
response rate for the national study
screening interview was 58.3%,
calculated as the product of the
resolution rate (87.5%) and the screener
completion rate (66.6%). The CASRO
response rate for cases in the NIS
sample was 59.0%, and the rate for
NAS-only cases was 58.1%.
National study: detailed interview
response rates—The overall CASRO
response rate for the national study
detailed interview was 47.2%, calculated
as the product of the resolution rate
(87.5%), the screener completion rate
(66.6%), and the interview completion
rate (81.0%). The CASRO response rate
for cases in the NIS sample was 47.8%,
and the rate for NAS-only cases was
47.0%.
Four-state study: detailed interview
response rates—The overall CASRO
response rate for the four-state study
detailed interview was 48.5%, calculated
as the product of the following: the
resolution rate (90.1%), the screener
completion rate (76.7%), and an
interview completion rate at the person
level (70.2%) based on the 5,741
person-level interviews completed in
5,125 households. Because the unit of
analysis for the detailed interview in the
four-state study was the sampled adult
or child, a person-level interview
completion rate is appropriate for this
calculation. The CASRO response rate
for cases in the NIS sample was 47.8%
and the rate for NAS-only cases was
49.6%.
The interview completion and
screener completion rates differed
substantially between the two studies.
One likely reason for the observed
difference in screening rates had to do
with the greater complexity of the
screening process in the national study.
A series of items had to be completed in
the national study screener, whereas the
screener for the four-state study
consisted of a single item. Another
possible reason for the difference might
be related to differential use of the
NAS-only sample. Though both surveys
used the NAS-only sample in addition
to the NIS sample, the NAS-only
sample proportion was much higher in
the national study. The NAS-only
sample cases received an advance letter
and interview introduction that made
specific mention of asthma as the
interview topic, whereas cases in the
NIS sample received the usual NIS
advance letter and interview
introduction.
Impact of adult or child status on
interview completion rates
The impact of child or adult status
of the sampled household member on
interview completion rates (and
subsequent affect on CASRO response
rates) is examined in Table M. The
national study selected only one person
per household, so its household
interview completion rate was a
weighted average of the rates for
children and adults. In the four-state
study, all interviews with selected
asthmatic household members had to be
completed before a household could be
included in the calculation of the
interview completion rate.
In both studies, the interview
completion rate for children was
substantially higher than the rate for
adults. This difference may have been
related to flexibility in determining the
respondent for a child—the only
requirement was that he or she be a
parent or guardian who was
knowledgeable about the child’s health.
Therefore, someone may have been
more likely to be available to complete
an interview for a child immediately,
whereas repeated callbacks were
sometimes required to complete
interviews with adults. Another possible
explanation for the observed difference
might be that the study used the NIS
sample, and thus potential respondents
were more easily able to make a
transition from the NIS screening or
interview to NAS questions about a
child than to questions about an adult.
Finally, parents or guardians could
simply be more invested in or more
accustomed to providing information
about their children’s health than they
are about their own health.
The final disposition of the NAS
study samples is detailed in Table N.
More detailed information on final
sample disposition and unweighted
response rate calculations is in Appendix
VII. One should recall that study
eligibility was based on asthma status.
Ineligible households were those in
which no household members were
reported to have asthma in the four-state
study.
Table M. Response rates for the detailed interview by sampled adult or child status: NAS,
2003
National study
Rate (percentage)
Interview completion rate . . . . . . . .
CASRO response rate . . . . . . . . . .
Four-state study
Sampled adults Sampled children Sampled adults Sampled children
80.00
46.60
86.00
50.10
68.60
47.40
NOTES: NAS is National Asthma Survey. CASRO is the Council of American Survey Research Organizations.
75.50
52.20
Page 16 [ Series 1, No. 46
Table N. Final sample disposition, national and four-state studies: NAS, 2003
period, prevent the release of excess
cases to telephone centers, and assist in
timely sample management decision
making.
Number of selected telephone lines
National study
Four-state study
Final disposition
Total
sample
NIS
sample
NAS-only
sample
Total
sample
NIS
sample
NAS-only
sample
Total . . . . . . . . . . . . . . . . . . . . .
55,204
12,779
42,425
210,109
109,401
100,708
Not resolved as residential or
nonresidential. . . . . . . . . . . . . . .
11,626
2,229
9,397
40,824
19,638
21,186
Out of scope (i.e., business or
nonworking) . . . . . . . . . . . . . . . .
29,369
6,795
22,574
110,956
58,003
52,953
not
. . .
. . .
4,155
8,852
1,190
2,321
2,965
6,531
10,144
40,852
6,450
21,794
3,694
19,058
. . .
19
3
16
10
7
3
. . .
228
46
182
2,198
1,052
1,146
. . .
955
195
760
5,125
2,457
2,668
Known household, study eligibility
determined . . . . . . . . . . . . .
Screened ineligible household . .
Screened eligible household,
language barrier . . . . . . . . . .
Screened eligible household,
interview not completed . . . . .
Screened eligible household,
interview completed . . . . . . . .
NOTES: NAS is National Asthma Survey. NIS is National Immunization Survey.
Efforts to maximize response rates
A number of approaches were used
to maximize NAS response rates,
including the following:
+ Careful attention to the introductory
questionnaire script to ensure it
engaged the interest of potential
respondents and provided clear
information on the study sponsor.
+ Thorough pretesting of the
instrument to ensure it was clear to
respondents and not unduly
burdensome.
+ An advance mailing to households
that had directory-listed telephone
numbers to establish study
legitimacy and increase rapport prior
to first contact, as well as convey
information about strict
confidentiality procedures in place.
+ A toll-free telephone number to
allow respondents to directly contact
interviewers and to encourage
potential respondents to obtain study
information, immediately establish
study eligibility, or voice any
concerns.
+ A Spanish-language version of the
instrument to reduce nonresponse
among Spanish-speaking households.
+ A sample management system that
provided daily review of
appointment and refusal case status
to ensure timely recontact.
+ Flexible call schedules to permit
respondents to complete the
interview at their convenience.
+ An interviewer training program in
refusal aversion to reduce the
number of unresolved cases and
refusals from eligible respondents.
+ The use of refusal conversion
attempts by specially trained
interviewers, who prepared
case-specific strategies for each
conversion call based on call history.
Results
Quality Control—Data
Collection
To ensure high quality data, project
staff monitored the sample selection and
case release processes, interview
administration, data consistency, and the
estimation process. Below is a brief
overview of the NAS quality control
measures.
Sample monitoring
The prepared sample of telephone
numbers was checked to ensure that it
met sample design specifications. The
sample dynamics were monitored daily
to ensure a consistent pace of data
collection across the data collection
Interviewing
Telephone center supervisors were
available to interviewing staff at all
times to resolve any questions or
concerns about a case. Supervisors
regularly observed data collection to
monitor interviewers informally. In
addition, supervisory staff used remote
telephone and computer monitoring
technology to evaluate whether
interviewers were performing according
to project specifications. They evaluated
whether introductory materials were
properly read, item wording and
sequence of the questionnaire were
followed correctly, respondent questions
were answered properly, and any vague
responses were properly probed.
Computer monitoring also allowed
supervisors to ascertain whether answers
were entered accurately into the CATI
system. NCHS staff also periodically
monitored interviews, especially at the
start of data collection.
Supervisory staff monitored 5% of
all NAS calls made. The selection of
which interviewers to monitor was
automated using an algorithm that
ensured newly trained interviewers were
monitored more often than experienced
interviewers. Experienced interviewers
were prioritized for monitoring based
upon the length of time since their last
monitoring session and recent
monitoring scores. Each interviewer was
typically monitored at least once a
week, but some interviewers were
monitored more often.
Data collection
The CATI system was programmed
to help ensure complete and accurate
data collection and used automated data
checking techniques during the
interview (such as response-value range
checks and consistency edits). These
features enabled interviewers to obtain
needed clarifications while still on the
telephone with the respondent. Online
help facilities were also available to aid
interviewers.
Series 1, No. 46 [ Page 17
Throughout the data collection
period, modified versions of programs
that were ultimately used to clean the
final data produced weekly checks of
interview data. These programs
identified any out-of-range values,
incorrect skip logic, missing data
elements, and inconsistency between
data fields. Any issues identified were
resolved during the data collection
process.
Data file production
Another set of programs, produced
independently of the cleaning programs,
performed three main quality control
checks of the cleaned data. First, these
programs identified any out-of-range
values and incorrect skip logic. Second,
derived variables were independently
created and cross-checked against
variables created during the initial
cleaning process. Any discrepancies
were flagged for resolution. Third, the
programs checked for the correct
assignment of special reserve codes
designed to differentiate among types of
missing data (e.g., data missing because
of eligibility criteria or interview
breakoff or data missing in error).
Variable labels and statements were
checked for consistency with the data
documentation provided.
The quality control programs were
run iteratively on each new version of
the data files until no problems were
identified. The quality control reviewer
then signed off on the data file. The
final step of the quality control process
involved review of the file by a senior
project manager. Once this last step was
completed, the data file was ready for
production.
Estimation
Staff compared the formulas for the
weights and adjustments developed by
the sampling statistician with the actual
weights and adjustments constructed by
the statistical programmer. The variables
delivered by the data collection staff to
the statistical programmer were used in
independent calculations of the weights
to verify the programmer’s
implementation of the statistician’s
weighting specifications.
In addition to this independent
check, univariate statistics were
produced and reviewed for the
adjustments and weights. Reviewers
used general knowledge about the size
of the population and expectations to
examine responses for geographic areas.
The sums of various weights were also
compared to ensure that differences
were in the expected direction.
Weighting and Estimation
Procedures
This section provides a nontechnical
overview of NAS weighting procedures;
for a more-detailed technical description,
refer to Appendix B.
To obtain population-based
estimates, each sampled respondent for
whom data were collected was assigned
a final sampling weight. The national
sample data file includes two final
weights from which the analyst may
choose depending on the population and
analysis of interest, whereas the
four-state sample data file includes three
final weights from which the analyst
may choose (again, depending on the
population and analysis of interest).
Each final sampling weight incorporates
a base sampling weight, an adjustment
for multiple telephone lines within a
household, and various adjustments for
nonresponse. Each adjusted weight is
then poststratified so that the sum of the
weights for each state equals selected
population control totals from an outside
source. For the national study, the
outside source was the 2002 NHIS, and
for the four-state study, the sources were
the 2003 BRFSS for adults and the 2003
National Survey of Children’s Health for
children. The steps to produce the
national and four-state sampling weights
are described below.
Sampling weights for the
national study
Questions were asked of an adult
knowledgeable about that child’s health
if the sampled household member was a
child under 18 years of age. If the
sampled household member was an
adult aged 18 years or over, questions
were asked of that sampled adult
whenever possible. However, if the
sampled adult was not available at the
time of screening contact, a proxy
interview was conducted with the adult
household member who answered the
telephone.
Because of the observed error rate
in proxy reporting of adult asthma
status, two versions of the national study
sampling weight were calculated to
permit production of estimates that
include or exclude proxy cases for
adults. The first version includes all
adult respondents with data regardless of
whether the data were collected by
self-report or a proxy respondent. The
second includes only the adult
respondents from whom data were
collected personally. Sampled children
are included in the calculation of both
weights. The process for creating the
two weights was identical; the
difference is in the set of cases to which
the weights are assigned.
Base sampling weight
The first step in the weighting
process determines the base sampling
weight for each selected household. The
base sampling weight attached to a
household is the reciprocal of the
probability of selection of the household
(e.g., equal to the probability of
selecting the household’s telephone
number).
The telephone lines selected to be
screened for NAS represent a random
sample of all possible telephone lines in
each geographic area. The probability
that any given telephone line will be
selected from the population of all
possible telephone lines can be
calculated. If 1,000 total telephone lines
are in a given area and 100 of those
lines were selected for the study, the
probability that any single telephone line
would be selected is 100/1000, or 0.10.
Therefore, each telephone line selected
represents some larger number of
telephone lines in that geographic area
(calculated as the reciprocal of the
probability of selection for any single
telephone line). If the probability of
selection for any single telephone line is
0.10, then each telephone line selected
represents 1/0.10 (or 10) telephone lines
in the geographic area. This number—
the reciprocal of the probability of
Page 18 [ Series 1, No. 46
selection for any single telephone
line—is the base sampling weight for
each completed interview in that
geographic area.
The base sampling weight varied by
geographic area in NAS, but was the
same for every completed interview
within that geographic area. Because the
population of telephone numbers did not
change much by each quarter, the base
sampling weight was calculated for the
overall survey and not separately for
each quarter.
Adjustment for multiple-telephone
households
If a household has multiple
voice-use telephone lines, it has a
greater chance of being included in the
survey than a household with only a
single voice-use telephone line. If
selecting a simple random sample of
households were possible, each
household would have equal probability
of being included. To adjust for a
multiple-telephone household’s increased
probability of being included in the
sample, the base sampling weight is
divided by the number of voice-use
telephone lines in the household, to a
maximum of three lines.
If a household has two voice-use
telephone lines, it could be included in
the sample two times. If it is included
twice and its base sampling weight is
10, the household would be allowed to
represent 10 (base sampling weight) x 2
(number of telephone lines) = 20
households. To adjust the weight so that
such a multiple-telephone household in
the sample represents the same number
of households in the geographic area as
does a single-line household in the
sample, the base sampling weight (10) is
divided by the number of telephone
lines (2). With an adjusted weight of 5,
this household (had it been selected
twice) would still represent only 10
households (5 x 2 = 10).
Unit nonresponse adjustment 1
(residential status unknown)
When selected telephone lines are
called, three results are possible:
1. The telephone line is determined to
belong to a household.
2. The telephone line is determined to
not be a working residential
number, but rather a business or
nonworking number.
3. The status remains unknown.
This third category includes some
household telephone lines, but the exact
number is unknown. Still, the completed
household interviews must represent the
households in this ‘‘unknown’’ category.
When the number of households in the
unknown category is large, the weight
for each completed household interview
must be increased substantially. When
the number of households in the
unknown category is small, the weight
for each completed household interview
must be increased only slightly. This
proportional adjustment is the first unit
nonresponse adjustment.
The size of the adjustment is based
on the size of the unknown category and
on previous research in which telephone
company business offices reported on
the number of households among the
unknown numbers. This adjustment
varies by geographic area, telephone
area code, and whether the telephone
line was directory listed. When many
telephone numbers in a geographic area
and area code go unanswered and most
of these numbers are highly likely to be
households, the weights for completed
interviews in that geographic area and
area code are increased greatly. When
few telephone numbers in a geographic
area and area code go unanswered, or
few of these numbers are likely to be
households, the weights for completed
interviews in that geographic area and
area code are increased only slightly.
Thus, based on the level of nonresponse
in a given area, the weights are
proportionately increased for interviews
that could be completed in that area to
compensate for nonresponse. The
completed interviews represent the
households in the unknown category.
Unit nonresponse adjustment 2
(households of unknown eligibility)
In the national study, a screening
interview determines eligibility (i.e.,
whether the sampled person has
asthma). When a household has been
identified, two results are possible:
1. A screening interview is completed.
2. A screening interview is not
completed.
The households with completed
screening interviews must represent the
households in which an interview is not
completed. When the number of
incomplete screening interviews is large,
the weight for each completed interview
must be increased substantially. When
the number of incomplete interviews is
small, the weight for each completed
interview must be increased only
slightly. The size of the adjustment is
based on the size of the two categories
and is calculated simply as the ratio of
the weighted total number of identified
households to the weighted number of
completed interviews.
The adjustment is done separately
within three urban setting categories
based on U.S. Census Bureau-defined
Metropolitan Statistical Areas (MSA),
which are geographic entities associated
with at least one urbanized area that has
a population of at least 50,000. The
MSA comprises the central county or
counties containing the core, plus
adjacent outlying counties having a high
degree of social and economic
integration with the central county as
measured through commuting (18). The
three categories, from most urban to
most rural, used for the adjustment are
1) within a central city of an MSA, 2)
outside of a central city but still within
an MSA, and 3) not within an MSA.
Subsampling adjustment
One household member was
randomly selected from among all
household members. In households with
more than one household member, the
randomly selected person represented all
of the nonselected people in the
household. Therefore, the sampling
weight must reflect the total number of
household members.
Unit nonresponse adjustment 3
(sampled persons who do not
complete the interview)
When a person has been sampled
for an interview, two results are
possible:
1. An interview is completed.
2. An interview is not completed.
Series 1, No. 46 [ Page 19
The completed interviews must
represent the interviews that were not
completed. The size of the adjustment is
based on the size of the two categories
and is calculated simply as the ratio of
the weighted total number of sampled
persons to the weighted number of
completed interviews. This adjustment is
made separately for each IAP.
Poststratification
Despite the weighting and the
nonresponse adjustments, the estimated
number of people is unlikely to match
perfectly the number of people in the
population sampled. Discrepancies are
likely to be due to random sampling
error and nonrandom response biases.
These biases may vary by age, sex, and
race. Poststratification of the weights to
match population control totals for key
demographic variables obtained from an
independent source may reduce this
bias. When several poststratification
variables exist and control totals are
available for the separate variables but
not for their cross-classifications, this
adjustment is carried out through a
process known as raking, which
involves creating a separate margin for
each poststratification variable
containing control totals for categories
of the variable.
For NAS, the independent source
for population control totals was the
2002 NHIS. The NAS weights were
adjusted so that their sum equaled the
2002 NHIS population counts for the
following groups:
+ Number of males and number of
females in nine age groups.
+ Household size.
+ Number of persons of various racial
and ethnic backgrounds.
+ Asthma status.
+ Number of males and females by
asthma status.
Adjustment for noncoverage of
households without landline
telephones
The poststratification process also
included an adjustment for potential bias
that might exist because NAS, as a
telephone survey, could not select
households that had no landline
telephone service at the time of the
survey. This adjustment incorporated
information about household
interruptions in telephone service from
NAS. Evidence suggests that households
that have telephone service at the time
of the survey, but have had service
interruptions of one week or more
during the year, are more similar to
households with no service at the time
of the survey than are households with
uninterrupted service during the year
(17,19–21). Therefore, noncoverage of
households without telephones can be
somewhat offset by proportionately
increasing the weights for those
interviews that were completed in
households with interrupted service. In
this way, completed interviews in
households with interrupted service
represent the households without
telephone service at the time of the
survey.
To make the adjustment for
nontelephone households, the proportion
of telephone and nontelephone
households was determined from the
2002 NHIS. These proportions were
then applied to the control totals of the
number of households to derive the
estimated numbers of telephone and
nontelephone households. Next, from
NAS, the weighted proportion of
telephone households having an
interruption in telephone service for at
least one week during the past 12
months was computed. This proportion
was then applied to the number of
telephone households to estimate the
number of telephone households with
interruption. These calculations
produced two control totals: one is for
households with landline telephones and
no interruption in telephone service, and
the other is for those without landline
telephones or with an interruption in
landline telephone service. These control
totals are mutually exclusive and
exhaustive.
No weighting or poststratification
adjustments were made for households
whose only telephone service was
available through cellular telephones.
Truncation of large weights
Extremely large weights were
truncated in order to prevent a small
number of cases with large weights
from having undue influence on the
estimates.
Sampling weights for the
four-state study
The process to produce four-state
study sampling weights was identical to
that used for the national study up to the
point of the subsampling adjustment.
For the four-state study, subsampling
adjustments were made separately for
adults with asthma and children with
asthma, because each could be sampled
within a single household. In households
with multiple asthma-positive adults, the
randomly selected adult represents all of
the nonselected asthma-positive adults in
the household. Therefore, the sampling
weight for the completed adult interview
must be increased proportionally. The
adjustment simply multiplies the weight
by the number of asthma-positive adults
in the household. The same logic applies
to sampled children.
Similarly, the nonresponse
adjustment to the four-state study
detailed interview was completed
separately for adults and children and
for each geographic area within the
adult and child categories. The four-state
study used two independent sources for
population control totals for
poststratification: the 2003 BRFSS for
adults and the 2003 NSCH for children.
The NAS weights for sampled adults
were adjusted so the sum of the weights
equaled the 2003 BRFSS counts of
asthma-positive adults in the following
groups:
+ Six age groups.
+ Males and females.
+ Adults grouped by various racial
and ethnic backgrounds.
NAS weights for sampled children
were adjusted so the sum of the weights
equaled the 2003 NSCH counts of
asthma-positive children in the
following groups:
+ Three age groups.
+ Males and females.
+ Children grouped by various racial
and ethnic backgrounds.
Finally, the adjustment for
nontelephone households was slightly
different for the four-state study. The
Page 20 [ Series 1, No. 46
separate proportions of adults and
children in telephone and nontelephone
households were determined from the
2004 Current Population Survey’s
Annual Social and Economic
Supplement conducted in March 2004.
These proportions were then applied to
the state control totals of the numbers of
adults and children to derive the
estimated numbers of adults and
children in each state in telephone and
nontelephone households. Next, from
NAS, the weighted proportions of adults
and children in telephone households
having an interruption in telephone
service for at least 1 week during the
past 12 months were computed. These
proportions were then applied to the
numbers of adults and children in
telephone households to estimate the
number of adults and children in
telephone households with interruption.
These calculations produced two control
totals for adults and two control totals
for children: one for those in households
with telephones and no interruption in
service and the other for those in
households without telephones or with
an interruption in telephone service.
These control totals are mutually
exclusive and exhaustive.
Weights
For both samples, the weight
specified will vary depending on the
analytic plan.
The national sample data file
contains two weights from which to
choose:
+ Post_pr_int—Includes all sample
adult proxy and self-report cases and
all sample children.
+ Post_sr_int—Includes only sample
adult self-report cases and all
sample children.
The national file does not include a
single child-level weight. Sampled
children are included in the calculation
of both weights, but the two weights for
any given sample child will differ
slightly because of the difference in the
number of sample adult cases used to
calculate post_pr_int compared with
post_sr_int.
Estimates for children can be
produced using either weight, but adults
are included in both weights as well
(even if the analyst is not interested in
asthma in adults). Therefore, analysts
need to determine which adult cases to
include: those that contain self-reported
information only or adult cases that
contain information from the sampled
and proxy respondents. The preferred
weight to use for child-level estimates is
post_sr_int because it only includes
sampled adult self-report information, in
addition to all information for children.
The alternate weight is post_pr_int,
which includes sampled adult self- and
proxy reports, in addition to all children.
The post_pr_int weight should be used
for methodological research to examine
differences between self- and proxy
reporting in adults. One should recall
that because of proxy reporting error, all
asthma negative proxy responses for
adults were verified with the sampled
adult if possible.
The four-state sample data file
contains three weights from which to
choose:
+ Post_adult_int—A person-level
interview weight that only includes
sample adults 18 years of age and
over; it should be used if the analyst
is interested only in examining
characteristics of asthmatic adults.
+ Post_child_int—A person-level
interview weight that only includes
sample children under 18 years of
age; it should be used if the analyst
is interested only in examining
characteristics of asthmatic children.
+ Weight_int—This person-level
interview weight includes all sample
adults and sample children in the
sample and reduces the analyst’s
work by eliminating the need to
aggregate the adult and child
weights to examine the whole
sample. It should be used if the
analyst wishes to examine
characteristics of people with asthma
in the entire sample across all ages.
Data Files
From the various CATI production
files, two data files were constructed for
release to the general public. All data
files are in SAS version 8 format (22).
Formatted value labels are not
permanently attached to the files;
instead, executable SAS programs are
included to enable users to create their
own format libraries.
The national sample data file
contains screening data (age, sex,
asthma status) for all cases as well as
accompanying interview data for all
cases in which a detailed interview was
completed and for those who completed
a partial interview (i.e., sampledrespondent cases that are complete at
least through the variable BATH_FAN
[S7Q16] or proxy-respondent cases that
are complete at least through the
variable S_INSIDEP [S7Q10P]). There
are 10,054 screening records in the
national file. It contains asthma-specific
interview data for 955 adults and
children, as well as person-level
demographic characteristics such as age,
race, ethnicity, education level, and
asthma status of each sampled
respondent. The file also contains
household-level variables.
The four-state sample data file
contains all screening and interview
information for 5,227 households and
5,741 persons. This file contains
asthma-specific interview data for adults
and children, as well as individual
demographic characteristics such as age,
race, ethnicity, and education level of
each sampled respondent as well as
household-level variables.
Missing data
The CATI system is designed to
minimize missing data. However, there
are several reasons why data may be
missing. Most analysts ignore records
with missing data regardless of why the
data is missing. However, SAS provides
a mechanism to differentiate between
different types of missing values. The
following key describes the various
codes used to represent missing data in
the data files.
(.N) Not in universe (sample
logic)—Respondents skipped entire
sections of questions based on
eligibility criteria (e.g., asthma
status).
(.L) Legitimate skip (question
logic)—Respondents skipped one or
Series 1, No. 46 [ Page 21
more questions within a section
because of an answer provided to a
root question.
(.P) Partially completed case—The
question was not answered because
the respondent broke off the
interview prior to completing this
question. Partially completed
interviews, or ‘‘partial completes,’’
are interviews that were completed
though question S7Q16 in sampled
respondent interviews or S7Q10P in
proxy interviews. These cases have
interview records and are treated as
‘‘completes,’’ even though data are
missing for questions that were
asked late in the interview.
(.M) Missing in error —A response
should have been captured for this
question but was not. Data may be
missing in error if records were not
properly written to a data file; an
interviewer did not properly follow
procedures to return to a previous
question to edit a response, a CATI
programming error, or a data
transfer failure; or the recorded
answer was determined to be
invalid.
SAS treats all of these codes
similarly in statistical analyses (i.e., as
missing data), so analysts who use SAS
and are not interested in the reasons for
missing data may continue to analyze
the data as usual.
One should note that derived
variables (i.e., variables whose response
was not directly provided by the
respondent) do not include the detailed
coding of missing data. All missing
values for derived variables received an
‘‘.M’’ code regardless of the reason for
the missing data. Similarly, ‘‘.M’’ was
used when derived variables were
suppressed to protect the confidentiality
of the survey participants.
Data missing because the
respondent did not know or refused to
provide the answer have been treated
differently. Rather than assigning a
missing value to these records, a
numeric code was used to identify these
responses. Typically, unknown answers
are coded as ‘‘6,’’ ‘‘96,’’ or ‘‘996.’’
Refused answers are coded as ‘‘7,’’
‘‘97,’’ or ‘‘997.’’ However, the codes
may be different for specific variables;
analysts are encouraged to consult the
data documentation and frequency lists
to identify the correct codes for each
variable. Failure to do so may result in
inappropriate calculations, especially for
variables measured using ordinal,
interval, or ratio scales.
Edits to protect confidentiality
NCHS takes extraordinary measures
to ensure that the identity of survey
respondents and subjects cannot be
disclosed. The risk of inadvertent
disclosure of confidential information
about individual respondents is higher
with a publicly released data set having
detailed geography variables, a detailed
and extensive set of survey observations,
or a sizeable proportion of the total
population of interest. Coarsening a data
set by suppressing survey variables,
collapsing multiple variables into one,
collapsing response categories for other
variables, or introducing noise in the
data are common techniques to reduce
the risk of inadvertent disclosure.
Details on the various edits to protect
confidentiality are listed below for both
samples.
Education—The education variable
for the highest level of schooling
completed by the sampled respondent
was not asked if the sampled child was
under 5 years of age. These data were
suppressed for sampled children aged
6–17 years because of the relationship
between age and grade at school.
Geography—Geographic
information that would identify the
specific IAP area was suppressed.
Three versions of the ‘‘state of
residence’’ identifiers are included in the
four-state file. The STATE variable
identifies the state with a numeric code;
the STATES variable identifies the state
with a two character abbreviation; and
the STATEL variable identifies the full
name of the state.
In addition, a variable identifying
whether the household resides inside or
outside of a MSA was included in both
files. It was suppressed whenever the
total population for all MSA areas or all
non-MSA areas in the state of residence
was less than 500,000 persons.
Race—Respondents were permitted
to identify all possible categories that
described the sampled person’s race. For
the national file, responses for the race
variable were collapsed to five
categories: white only, black only, Asian
only, multiple race, and other race. The
‘‘other race’’ category included people
for whom only one of the other two
categories (American Indian or Alaska
Native [AIAN] and Native Hawaiian or
Other Pacific Islander [NHOPI]) was
reported. People for whom more than
one race was reported (e.g., Asian and
NHOPI) were included in the ‘‘multiple
race’’ category.
For the four-state file, responses for
the race variable were collapsed to four
categories: white only, black only,
multiple race, and other race. The
‘‘other race’’ category included persons
for whom only one of the other three
categories (Asian, AIAN, and NHOPI)
was reported. People for whom more
than one race was reported (e.g., Asian
and NHOPI) were included in the
‘‘multiple race’’ category.
Number of persons in the household
(national sample)—Information on the
total number of persons in each
household significantly increases the
risk of inadvertent disclosure of
confidential information in households
with large numbers of persons.
Therefore, the number of persons of all
ages that live in the household was top
coded at ‘‘10+’’ (ROSTER10) to
suppress the identity of large
households.
Number of children and adults in
the household who are diagnosed with
asthma (four-state sample)—Information
on the total number of asthmatic adults
and children in the household can
increase the risk of inadvertent
disclosure in households with large
numbers of persons with asthma.
Therefore, the number of children in the
household diagnosed with asthma was
top coded at four and above. The
number of adults in the household
diagnosed with asthma was top coded at
three and above.
Relationship of respondent to
sample child or adult—If a child was
randomly selected as the sampled person
in the household, a parent or guardian
knowledgeable about the health of the
Page 22 [ Series 1, No. 46
child answered the survey questions.
Additionally, for adult sampled
respondents who were too ill to
participate, another adult in the
household was allowed to answer as a
proxy respondent for the sampled adult.
As detailed earlier, a separate proxy
substudy was conducted for sampled
adult respondents in the national study
who were unable to be reached at the
time of the screening interview.
The original response categories to
assess the relationship of the
knowledgeable adult respondent to the
sampled person (question S3Q6,
RELA_CHILD) listed in the
questionnaire included the following:
mother (birth, adoptive, step, or foster)
or female guardian, father (birth,
adoptive, step, or foster) or male
guardian, sister or brother (step, foster,
half, or adoptive), in-law of any type,
aunt or uncle, grandparent, other family
member, or friend. In the national
sample public-use data file, all responses
above were included except for in-law
of any type. To mask households that
contain unique family characteristics, the
responses were collapsed into the
following categories for the four-state
sample: mother (birth, adoptive, step, or
foster) or female guardian, father (birth,
adoptive, step, or foster) or male
guardian, and other.
Other variables—Several other
frequency variables were top or bottom
coded to suppress outliers at low and
high ends of the distribution of
responses. Because of their unusual
characteristics, records that included
these outliers might have been more
readily identifiable. For the remaining
variables, the sample frequency
distributions were examined and cut
points were created at natural breaks.
The following variables were top
coded in both samples:
+ Age of the respondent or household
member, top coded at ‘‘85+’’
(S2Q5R).
+ Age of respondent when he or she
was first told by a health care
professional that he or she had
asthma, top coded at ‘‘85+’’
(S3Q8R).
+ Number of times in the past 12
months the sampled person saw a
+
+
+
+
+
doctor or other health professional
for a routine checkup for asthma,
top coded at ‘‘13+’’ (S5Q1R).
Number of times in the past 12
months the sampled person visited
an emergency room or urgent care
center because of asthma, top coded
at ‘‘13+’’ (S5Q3R).
Number of times in the past 12
months the sampled person saw a
doctor or other health professional
for urgent treatment of worsening
asthma symptoms or an asthma
episode or attack, top coded at
‘‘16+’’ (S5Q4R).
Number of times in the past 12
months the sampled person stayed in
any hospital overnight or longer
because of asthma, top coded at
‘‘6+’’ (S5Q6R).
Number of days in the past 12
months the sampled person was
unable to work or carry out usual
activities because of asthma, top
coded at ‘‘36+’’ (S5Q9R).
Number of days in the past 12
months the sampled child missed
daycare, preschool, or school
because of asthma, top coded at
‘‘32+’’ (S5Q11R).
The following variables were top
coded in the four-state sample:
+ Age of respondent or household
member, top coded at ‘‘85+’’
(S2Q5R).
+ Age of respondent when he or she
was first told by a health care
professional that he or she had
asthma, top coded at ‘‘85+’’
(S3Q8R).
+ Number of times in the past 12
months the sampled person saw a
doctor or other health professional
for a routine checkup for asthma,
top coded at ‘‘13+’’ (S5Q1R).
+ Number of times in the past 12
months the sampled person visited
an emergency room or urgent care
center because of asthma, top coded
at ‘‘13+’’ (S5Q3R).
+ Number of times in the past 12
months the sampled person saw a
doctor or other health professional
for urgent treatment of worsening
asthma symptoms or an asthma
episode or attack, top coded at
‘‘16+’’ (S5Q4R).
+ Number of times in the past 12
months the sampled person stayed in
any hospital overnight or longer
because of asthma, top coded at
‘‘6+’’ (S5Q6R).
+ Number of days in the past 12
months the sampled person was
unable to work or carry out usual
activities because of asthma, top
coded at ‘‘36+’’ (S5Q9R).
+ Number of days in the past 12
months the sampled child missed
daycare, preschool, or school
because of asthma, top coded at
‘‘32+’’ (S5Q11R).
The following variables were top
and bottom coded in the four-state and
national samples:
+ Birthweight in grams
(BRTHWHT5).
+ Respondent height in inches
(HEIGHTR).
+ Respondent weight in pounds
(WEIGHTR).
The birthweight variable was asked
of sampled children under the age of 18
years. This question permitted
respondents to report the sampled
child’s birthweight in pounds and
ounces or grams. For both samples, the
reported birthweight was recoded into
grams such that at least 5% of the
sample was contained in either the top
or bottom code after examining relevant
NHANES data. The resulting bottom
code was 1,814 grams (about 4 pounds)
and a top code of 4,282 grams (about
9.4 pounds).
The height question permitted
respondents to report the sampled
person’s height in feet and inches or
centimeters. The reported height was
recoded into inches. The weight
question permitted respondents to report
the sampled person’s weight in either
pounds or kilograms. This value was
recoded into pounds.
Because the single-age samples for
children in the survey were so small,
specifications developed for the SLAITS
NSCH were used to create the top and
bottom cut points for height and weight.
These cut points were applied by age
for children 0–17 years of age. To
protect the confidentiality of individual
children, very short or very tall heights
Series 1, No. 46 [ Page 23
and very low and very high weights
were suppressed. Extreme values were
identified within each single-age group
and recoded to less extreme values. For
example, for 11-year-old children, all
reported heights shorter than 43 inches
were recoded to 43 inches, and all
reported heights taller than 68 inches
were recoded to 68 inches.
The height and weight cut points
for adults used the NHIS specifications
because the single-age samples for
adults were so small. For men, weights
less than or equal to 125 pounds were
recoded to 125, and weights greater than
285 pounds were recoded to 285. For
men, heights less than 63 inches were
recoded to 63 inches, and heights
greater than 76 inches were recoded to
76 inches. For women, weights less than
or equal to 98 pounds were recoded to
98 pounds, and weights greater than 259
pounds were recoded to 259 pounds. For
women, heights less than or equal to 58
inches were recoded to 58 inches, and
heights greater than 70 inches were
recoded to 70 inches. Two flag
variables, HGHT_FLG and
WGHT_FLG, were added to the dataset
to enable analysts to determine whether
the height and weight values for
children and adults were reported or
assigned.
Body mass index (BMI)—BMI
indicates total body fat based on the
height and weight of adult men and
women. Because suppression of height
and weight variables may hinder
calculations of BMI (calculated as body
weight in kilograms [kg] divided by
height in meters [m] squared), variables
identifying BMI for children
(BMICLASSC) and adults
(BMICLASSA) have been added to the
dataset.
Children aged 2–17 years have been
identified as either underweight
(BMI-for-age is in the 5th percentile or
lower), normal weight, at risk for
overweight (BMI-for-age is in the 85th
percentile or greater but lower than the
95th percentile), or overweight
(BMI-for-age is in the 95th percentile or
greater). Percentiles are based on sex
and age (see http://www.cdc.gov/
nccdphp/dnpa/growthcharts/resources/
sas.htm); however, this program relies
on the child’s age in months. Because
age was only reported in years for this
survey, children were assumed to be at
the midpoint of the age-year (i.e., a
10-year-old was assumed to be 126
months of age) to calculate BMI-for
age. Children’s height and weight were
reported by the parent or guardian and
were not independently measured or
verified.
The following classifications were
used for the adult BMI variable and
correspond to those used by the
National Institutes of Health:
underweight is less than 18.5 kg/m2,
normal weight is 18.5 to 24.9 kg/m2,
overweight is 25 to 29.9 kg/m2, and
obese is greater than or equal to 30
kg/m2.
Access to suppressed data
Analysts interested in working with
suppressed data may access unmodified
data files through the NCHS Research
Data Center (RDC). For information
about charges and how to apply for
access, visit the RDC website at
www.cdc.gov/nchs/r&d/rdc.htm.
Derived variables
A number of derived variables
created for estimation and analysis are
included in the national and four-state
data files. The derived variables in the
national sample data file provide
household information on lifetime and
current asthma prevalence, height and
weight of sampled respondents (as well
as birthweight for sampled children),
respondent race, and household income.
The four-state data file also contains
derived variables listed above, with the
exception of prevalence data.
An alphabetical list of derived
variables created for the 2003 NAS
four-state and national data files follows.
Derived variables marked with a dagger
(†) take advantage of the fact that some
household and demographic information
could have been obtained from sampled
and proxy respondents. If data were
supplied by a sampled respondent only
or a sampled and a proxy respondent,
data provided by the sampled
respondent were used to calculate
derived variables. If the only data
available were supplied by a proxy
respondent, then these data were used to
calculate derived variables.
ASTATUS1—The variable
ASTATUS1 describes whether a
respondent self-identifies as currently
having asthma. It requires a positive
lifetime asthma status (as described
below in ASTHSTAT) and a positive
response to S3Q2 (or S3Q9, if it has a
value), which explicitly asks whether the
respondent currently has asthma.
ASTATUS2—A second measure of
current asthma status, ASTATUS2, relies
on behaviors, not self-identification, to
indicate whether a respondent currently
suffers from asthma. It requires a
positive lifetime asthma status (as
described in ASTHSTAT) and one of the
following criteria:
1. Respondent has spoken to a doctor
or health professional about his or
her asthma within the last 3 years.
2. Respondent has taken asthma
medication within the last 3 years.
3. Respondent has had symptoms of
asthma within the last 3 years.
These behaviors are assessed in
questions S3Q10, S3Q11, and S3Q12.
ASTHMST—This variable computes
asthma status according to programmatic
rules developed for the BRFSS. It
indicates whether the respondent has
been told by a doctor or other health
professional that he or she currently,
formerly, or never has had asthma. It is
calculated from the variables
R_ASTHMX01 (or S3Q7, if it has a
value) and S3Q2 (or S3Q9, if it has a
value), which assess lifetime and current
asthma status.
ASTHSTAT—The variable
ASTHSTAT, a measure of lifetime
asthma status, is created for each
sampled household member from the
variable R_ASTHMX01 (or S3Q7, if it
has a value), which asks whether the
sampled person has been told by a
doctor or other health professional that
he or she has asthma.
BESTINCOMEG1†—The
BESTINCOMEG1 variable is derived
from the best income variable
(BESTINCOME) of the respondent,
grouped into the following categories:
$0 to $4,999; $5,000 to $9,999; $10,000
to $14,999; $15,000 to $19,999; $20,000
to $24,999; $25,000 to $34,999; $35,000
Page 24 [ Series 1, No. 46
to $44,999; $45,000 to $54,999; $55,000
to $64,999; $65,000 to $74,999; and
$75,000 and over. For respondents who
reported an exact household income, the
BESTINCOME field contains that actual
dollar amount. When respondents did
not supply a specific dollar amount for
household income, a series or cascade of
questions asking respondents whether
the household income was below,
exactly at, or above threshold amounts
was necessary. A matrix was then
created to categorize responses to these
income cascade questions. Each cell in
the matrix was assigned to one of the
following income categories: less than
$7,500; $7,500 to less than $10,000;
$10,000 to less than $12,500; $12,500
to less than $15,000; $15,000 to less
than $17,500; $17,500 to less than
$20,000; $20,000 to less than $25,000;
$25,000 to less than $30,000; $30,000
to less than $35,000; $35,000 to less
than $40,000; $40,000 to less than
$45,000; $45,000 to less than $50,000;
$50,000 to less than $60,000; $60,000
to less than $75,000; and $75,000 or
higher.
The BESTINCOME variable, for
respondents who went through the
cascade of income questions, was
calculated as the midpoint of their
income category as determined by their
location in the matrix. Respondents with
an income range of $75,000 or higher
were assigned a BESTINCOME value
of $100,000, based on the median
income reported for NAS households
that provided an exact income above
$75,000. Respondents who did not
complete the income cascade, either
because they refused or did not know
the answer to one of the cascade
questions, have a missing value for
BESTINCOME.
BMICLASSA—This variable
classifies the BMI value for age for
adults.
BMICLASSC—This variable
classifies the BMI value for age for
children.
BRTHWHT5†—The variable
BRTHWHT5 provides a standardized
measure of birthweight in grams for
sampled children. Birthweight values
given by respondents in pounds and
ounces were converted into grams by
multiplying the amount given in pounds
by 16, adding any additional weight
given in ounces, and multiplying by a
conversion factor of 28.350.
CASTHMA—This variable indicates
who is at risk for current asthma
prevalence according to BRFSS
programmatic rules. These respondents
are at risk for having been told
sometime in their lifetime by a doctor or
other health professional that they had,
and still have, asthma. It is calculated
from the variables R_ASTHMX01 (or
S3Q7, if it has a value) and S3Q2 (or
S3Q9, if it has a value).
COMPLETE_STATUS (national
sample only)—This variable indicates
whether a screener and interview were
completed and who provided the data
(i.e., the sampled person or a proxy
respondent). Because respondents could
break off the interview at any point, this
flag was created to categorize cases by
the number of valid responses given
(number 1 was not assigned a code):
2. Screener complete, sampled person
interview complete through at least
S7Q16.
3. Screener complete, proxy
respondent interview complete
through at least S7Q10P.
4. Screener complete, sampled person
(through at least S7Q16) and proxy
respondent interviews complete
(through at least S7Q10P).
FLG_ASTHMA (national sample
only)—This variable indicates whether
asthma status for the sampled
respondent was obtained from the
sampled respondent or from a proxy
respondent. FLG_ASTHMA has the
following values:
1. Sampled person reported asthma
status.
2. Proxy reported asthma status.
FLG_PROXY—In instances where a
sampled adult respondent or the
knowledgeable parent or guardian was
unable to complete the interview
because of an illness or disability,
another household member was able to
serve as a proxy respondent in his or
her place. FLG_PROXY is a derived
variable that notes whether an interview
was or was not conducted by a proxy
because of a respondent’s illness or
disability.
FLG_TYPE—This variable is
included for both samples to facilitate
data navigation. It establishes the
respondent’s expected questionnaire path
or interview type based on asthma and
respondent status. Variables that affect
the questionnaire path (asthma status,
current asthma status, and identity of the
respondent) are determined in the third
section of the questionnaire.
For the national file, the variable
FLG_TYPE had the following values:
1. Current asthma—Sampled person
was interviewed: data in original
fields.
2. Asthma, not current—Sampled
person was interviewed: data in
original fields.
3. No asthma—Sampled person was
interviewed: data in original fields.
4. Asthma—Proxy interviewed
because sampled person was
unavailable: data in proxy fields.
5. No asthma—Proxy interviewed
because sampled person was
unavailable, and sampled person
was never interviewed: data in
proxy fields.
6. No asthma—Proxy interviewed
because sampled person was
unavailable, and sampled person
was interviewed at callback: data in
both fields
7. Current asthma—Sampled person
and proxy were interviewed: data in
both fields.
8. Asthma, not current—Sampled
person and proxy were interviewed:
data in both fields
9. Current asthma—Proxy interviewed
because sampled person was ill:
data in original fields.
10. Asthma, not current—Proxy
interviewed because sampled
person was ill: data in original
fields.
11. No asthma—Proxy interviewed
because sampled person was ill:
data in original fields.
For the four-state file, the variable
FLG_TYPE had the following values:
1. Sampled person was interviewed:
asthma symptoms, medications, and
doctor visits in past 3 years.
2. Sampled person was interviewed:
no asthma symptoms, medications,
Series 1, No. 46 [ Page 25
and doctor visits in past 3 years
3. Sampled person was ill, and proxy
was interviewed: asthma symptoms,
medications, and doctor visits in
past 3 years.
4. Sampled person was ill, and proxy
was interviewed: no asthma
symptoms, medications, and doctor
visits in past 3 years
HEIGHTR†—The variable
HEIGHTR provides a standardized
measure of height in inches. Height
values given by a respondent in feet
were multiplied by 12 and added to any
inch values provided. If height was
provided in centimeters, the values were
multiplied by a constant, 0.3937, to
produce the value for the derived
HEIGHTR. This variable was top and
bottom coded (as previously discussed)
for each sample.
HISPANIC_DERIVED†—This
variable indicates whether or not the
sampled household member is of
Hispanic or Latino origin.
LTASTHM—This variable indicates
who is at risk for lifetime asthma
prevalence according to BRFSS program
rules. It indicates whether the
respondent was told sometime in their
lifetime by a doctor, nurse, or other
health professional that they had asthma,
and it is calculated from the variable
R_ASTHMX01 (or S3Q7, if it has a
value).
RACE_MAIN†—Respondents were
permitted to identify all possible
categories that described the sampled
person’s race. The RACE_MAIN
variable was created using all of these
pieces of information. If a respondent
offered a verbatim ‘‘other’’ race
response, these open-ended responses
were entered into a text field by the
interviewer and, wherever possible, back
coded into existing categories of the
RACE variable. If all race components
had a value of ‘‘don’t know,’’ the race
variable was assigned a value of ‘‘don’t
know.’’ If all race components had a
value of ‘‘refused,’’ the race variable
was assigned a value of ‘‘refused.’’ If
any race component had a nonvalid
value (i.e., missing), the race variable
was assigned a value of ‘‘.M.’’ Race
categories were then collapsed as
appropriate for the national and
four-state public-use data files as
previously described.
WEIGHTR†—The variable
WEIGHTR provides a standardized
measure of weight in pounds. Weight
values given by a respondent in
kilograms were multiplied by a constant
(2.205) to produce the value for the
derived WEIGHTR. To protect the
confidentiality of individual children and
adults, very low and very high weights
were suppressed. Extreme values were
identified within each single-year age
group and were recoded to less extreme
values. The weight cut points were
previously described in this report for
children and adults.
Flag variables
The following flag variables were
created for the four-state and national
data files:
+ FLG_ASTHMA (national sample
only).
+ FLG_PROXY.
+ FLG_TYPE.
+ HGHT_FLG and WGHT_FLG.
+ SPANISH—For sample management
purposes, a calling queue was used
for households thought by
interviewers to be Spanish-speaking.
The CATI flag, SPANISH, indicates
such households. If on subsequent
calls the screener or interview was
not conducted in Spanish, this flag
was not reset and retained a value of
‘‘1.’’ However, in past research, this
flag was shown to indicate reliably
the language of interview
administration in more than 97% of
cases, which suggests it is a useful
proxy for language of
administration.
Grouped variables
Several variables such as age
(S2Q5G1, S2Q5G2, and S2Q5G3), state
(STATE, STATES, and STATEL),
education level (EDUCATION and
EDUCATION2), and age at first
diagnosis (S3Q8G1, S3Q8G2, and
S3Q8G3) have been included in the
datasets with multiple grouped
classifications to assist the analyst.
These grouped categories match the
response categories that other large
surveys use (such as NHIS or BRFSS).
The analyst is free to choose the
variable grouping that would be most
useful. For example, the first age
grouping (S2Q5G1) is under 5 years,
5–17 years, 18–24 years, 25–44 years,
45–64 years, 65–69 years, 70–74 years,
and 75 years and over. The second age
grouping (S2Q5G2) is under 6 years,
6–16 years, 17–24 years, 25–34 years,
35–44 years, 45–54 years, 55–64 years,
65–74 years, and 75 years and over. The
third age grouping, S2Q5G3, is under 5
years, 5–11 years, 12–17 years, 18–44
years, 45–64 years, 65–74 years, and 75
years and over.
The following variables have
different grouped responses for both
samples: age (S2Q5G1, S2Q5G2, and
S2Q5G3), education level
(EDUCATION and EDUCATION2), and
age at first diagnosis (S3Q8G1,
S3Q8G2, and S3Q8G3).
National sample proxy
variables
As previously described, the
national sample included a proxy
response verification substudy. A proxy
response was accepted in this substudy
if the sampled person was not home or
unavailable. This is in contrast to the
typical proxy rule, which is that proxy
responses will only be accepted because
of illness, disability, or infirmity of the
sampled respondent. Proxy respondents
in the national sample substudy
answered the following detailed
questions: S3Q6B, S5Q1_AP, S5Q1_BP,
S7Q1P–S7Q10P, S7Q18P, S7Q19P,
S7Q20P, S7Q22P (if applicable),
OTHERASTHP, HISPANICP,
R_RAC2P, S2Q18P, S2Q14_1P,
S2Q14_2P, S2Q14_3P, S2Q15_1P,
S2Q15_2P, S2Q16_1P, S2Q16_2P,
S2Q16_3P, BIRTHRFP, INCTOTP,
EDUCATIONP, and EDUCATION2P.
Recoding of prescription
medication data
In the Medication section,
respondents were asked whether they
took asthma medications in inhaler, pill,
syrup, or nebulizer form. A list of the
medications taken in each manner was
obtained. A probe that asked ‘‘any other
Page 26 [ Series 1, No. 46
medications?’’ was asked after
respondents answered for each drug
type. If respondents replied yes to this
probe, the verbatim response was
cross-checked against the detailed
medication lists for each drug type. If
appropriate, the verbatim response was
reclassified to the proper category.
Recoding was not necessary for records
with a valid ‘‘other medication’’
response.
Examples of valid recoding of the
verbatim response to the ‘‘other
medication’’ questions include the
following:
+ Respondents who offered a verbatim
response of a generic medication
name of a drug that was in the
detailed list of brand names. This
response was back coded to the
appropriate category.
+ A number of respondents
erroneously offered the name of an
over-the-counter cold or allergy
medication or an over-the-counter
inhaler, pill, or syrup as a verbatim
response for a prescription asthma
medication. In these cases, the
verbatim response was set to
‘‘missing,’’ and any questions before
or after the verbatim response were
set to the appropriate response.
+ Some respondents offered a
verbatim response with an
unidentifiable word or a word that
was not the name of a type of
medication. In these cases, the
verbatim response was set to
‘‘missing,’’ and any questions before
or after the verbatim response were
set to the appropriate response.
+ Some respondents offered a
verbatim response that was valid,
but not for the type of medication in
question. For example, if a
respondent answered ‘‘Singulair’’ for
the question concerning other
inhalers, the text response for the
other inhaler question was set to
‘‘missing,’’ and the response was
moved to the Singulair pill questions
(if the respondent did not already
give Singulair as one of the pill
responses).
Additional data notes
The following systematic problems
were identified for the national sample
data file:
+ RELA_CHLD (S3Q6) was
incorrectly skipped in 50 interviews
regarding children without asthma.
This CATI system error was
corrected on March 20, 2003.
+ In 15 cases, a programming error
caused items in Section 5 after INS2
(S5Q1_B) and all items in Section 6
to be incorrectly skipped. This CATI
system error was corrected on June
20, 2003.
+ Items in Section 5 after INS2
(S5Q1_B) and all of the items in
Section 6 were incorrectly skipped
for nine illness-related proxy
interviews. This CATI system error
was corrected on October 20, 2003.
+ ILP04 (S8Q19) was to be skipped
for sampled children under the age
of 6 years. In three cases, the flag
variable that indicated the sampled
respondent’s age to trigger this skip
was blank, causing the variable to
be incorrectly skipped for
respondents 6 years of age and over.
This CATI system error was
corrected on July 18, 2003.
+ In 13 asthma-negative cases, a
programming error caused S11Q1
through S11Q9 and HISPANIC to be
incorrectly skipped. This CATI
system error was corrected on May
28, 2003.
+ A CATI problem caused data to be
lost for variables S7Q1P through
S7Q10P and S11Q1P through
S11Q9P for two cases. This CATI
system error was corrected on
December 3, 2003.
+ S7Q21 was incorrectly skipped for
eight cases where the sampled
person had asthma. This CATI error
was corrected on November 14,
2003.
The following systematic problems
were identified for the four-state sample
data file:
+ ILP04 (S8Q19) was to be skipped
for sampled children under the age
of 6 years. A flag variable that
indicated the sampled respondent’s
age to trigger this skip was
inadvertently left blank, causing this
variable to be incorrectly skipped
for respondents 6 years of age and
over early in the data collection
period. This caused S8Q19_03 to be
skipped for 100 cases and
S8Q19_24 to be skipped for 19
cases. This CATI system error was
corrected on July 18, 2003.
+ Because of a CATI system error,
OTC (S8Q1), INHALERE (S8Q2),
and INHALERH (S8Q3) were
incorrectly skipped for nine cases
where the respondent did not have
current asthma and had not gone to
a doctor, taken medication, or had
symptoms recently.
Quality Control—Data
Files
Construction of the data files
A lead programmer modified the
cleaning programs used to monitor the
interview data during each quarter of
data collection and cleaned the data at
the end of the data collection period. A
second programmer was responsible for
reviewing the work of the lead
programmer and signing off on each
completed task. The cleaned data file
was also thoroughly checked by project
staff. A brief summary follows of the
steps involved to produce the final data
file, including the data monitoring
process, data cleaning, and quality
control review of the final file.
Data monitoring
During each quarter of data
collection, weekly monitoring of the
interview data served as a quality
control check prior to the data cleaning
process. The programs for this task were
designed to identify out-of-range values
and incorrect skip logic and to report on
any missing data elements or
inconsistencies between data fields. The
necessary edit rules were developed and
documented. Inconsistencies identified
Series 1, No. 46 [ Page 27
during the monitoring process were
resolved, and any missing data elements
were sent to the telephone center for
hard-copy data recovery. Recovered data
were entered manually into the CATI
system with the data entry
independently checked to ensure
accuracy. Additionally, at the beginning
of each quarter, data for a sample of
cases were printed and reviewed for
consistency to pick up possible
discrepancies that had not been
identified by the monitoring programs.
Data cleaning
Using the CATI questionnaire
specifications as a base, the lead
programmer followed detailed cleaning
specifications and produced a series of
cleaning programs. The programmer
annotated each cleaning program so that
results could be replicated and reviewed
by others. These programs were created
to do the following:
1. Check for duplicate cases across
NAS data collection quarters.
2. Verify the valid number of
completed and partially completed
cases in the data file.
3. Check that all data elements for a
completed case were present.
4. Apply any final data corrections
based on data recovery.
5. Verify that values were within
specified ranges and that skip
patterns were followed.
6. Create derived variables from
existing variables.
7. Assign special SAS reserve codes, as
appropriate, to reflect missing data
of various kinds (e.g., sections or
questions skipped based on
eligibility criteria or answers to
earlier questions with data missing
in error).
After all edits were made, a final
frequency report was reviewed for
completeness. Once the programmer
produced a cleaned interview data file, a
rigorous quality control process began.
Estimation and hypothesis
testing
The NAS data were obtained
through a complex sample design
involving clustering of persons within
households and stratification of
households within IAP areas. To
produce accurate estimates, sampling
weights had to be used. The sampling
weights accounted for the complex
survey design and included adjustments
for multiple-telephone households, unit
nonresponse, noncoverage of
nontelephone households, and
adjustments to known population control
estimates.
Variables used for variance
estimation
The interview records have unequal
weights because of the complex design
of NAS. Therefore, statistical software
programs that assume a simple random
sampling design will most often
compute standard errors that are too
low. Tests of statistical hypotheses may
then suggest statistically significant
differences or associations that are
misleading. However, computer
programs are available that provide the
capability of variance estimation for
complex sample designs (e.g.,
SUDAAN, STATA, SPSS, and WesVar)
(11,23,24). Stratum identifiers and
primary sampling unit (PSU) codes were
included on the data files to allow users
to estimate complex sample variances.
These variables and the sample weights
are necessary for the calculation of
variances.
The stratum identifiers reported on
the data set are not identical to the strata
used for drawing the sample. In states
with multiple IAP areas, independent
samples were selected from each IAP
area in proportion to the total number of
households with children in each IAP
area. Therefore, these IAP areas should
be considered strata for variance
estimation. However, disclosure of the
specific IAP area for each child (even if
the code was scrambled) could increase
the risk of disclosure of a respondent’s
identity. For example, the IAP area with
the lowest frequency of responses in
Texas would be readily identifiable as
El Paso.
In the absence of IAP-specific
identifiers in the four-state sample, data
users should use the state identifier
(STATE) as the stratum identifier. By
using the state identifier rather than the
suppressed IAP identifier for the
four-state sample, the standard errors for
estimates of key variables are affected
only slightly and not in a consistent
direction. For the national sample, data
users should use the stratum identifier
(STRATUM). The PSU for the national
and four-state files is the household,
represented on the data sets by the
unique household identifier IDNUMR.
Analysts should review and be
mindful of the sample sizes of the file
with which they are working. Analysis
of rare responses or subclasses can lead
to estimators that are unreliable. Small
sample sizes used in variance
calculations may also produce unstable
variance estimates. Consequently, the
user must pay particular attention to the
coefficient of variation for the estimates
of means, proportions, and totals.
Variance estimation on subsets
of the data
Some NAS analyses may focus on
specific population subgroups, such as
children living in poverty. Analysts may
be tempted to delete all records outside
of the domain of interest so they can
work with smaller data files and run
computer programs more quickly. This
procedure of keeping only select records
and deleting other records is called
subsetting the data. Subsetted data that
are appropriately weighted can be used
to generate correct point estimates (e.g.,
estimates of population subgroup
frequencies or means), but most
software packages that analyze complex
survey data will incorrectly compute
standard errors for subsetted data. When
complex survey data are subsetted, the
sample design structure is often
compromised because the complete
design information is not available.
Subsetting the data can delete important
design information needed for variance
estimation (e.g., deleting all records for
certain subgroups will result in entire
PSUs being removed from the design
structure). SUDAAN has a SUBPOPN
option that allows for specific
subpopulations to be targeted in
analyses while retaining the full data set
and sample design information. To
reiterate, analysts interested in specific
Page 28 [ Series 1, No. 46
population subgroups must include the
SUBPOPN statement in SUDAAN code
(and the equivalent statement in other
software programs) instead of subsetting
the data sets.
Weighted sample frequencies,
prevalence estimates, and
standard errors
Weighted sample frequencies for
selected variables appear in Appendix I
to assist users in verifying the correct
use of the weights. The two NAS files
should not be combined to produce
more precise estimates.
National estimates generated from
the national sample file should be
described as being consistent with those
produced by NHIS. Disaggregated
prevalence estimates from the national
sample file are NAS prevalence
estimates that may or may not be
consistent with NHIS.
Weighted estimates can be
calculated for each state in the four-state
sample (using a ‘‘where’’ statement to
select the appropriate cases) or for the
four-state sample as a whole. The
poststratified state weights were
weighted up to appropriate population
control totals. One should keep in mind
that the four-state sample cannot be
used to calculate prevalence estimates of
current asthma, lifetime asthma, or any
other variables of interest. The four-state
file can be used to calculate weighted
percentages, proportions, etc., but
labeling these as prevalence estimates is
inaccurate because crucial information
needed to calculate prevalence was
purposely not collected because of the
screening process selected. This decision
was made after extensive tests were
conducted.
Using the appropriate weight
Table O summarizes the weights for
both samples. The weight that is
specified will vary depending on the
analytic plan.
Variance estimation using
SUDAAN or STATA
The sampling variance (e.g.,
standard errors) of estimates can be
calculated for the United States (national
sample) as well as Alabama, California,
Illinois, and Texas (four-state sample)
using the Taylor series approximation
method in software such as SUDAAN,
WesVar, STATA, SPSS, and the SAS
SURVEY procedures (SURVEYFREQ,
etc.). The simplifying assumption that
PSUs have been sampled with
replacement allows most complex
survey sample design computer
programs to calculate
Table O. Description of the weights, national and four-state samples: NAS, 2003
Variable name
Description
Comments
National sample
post_pr_int . . . . . . . . . .
Includes all sample adult proxy and self-report cases and
all sample children
The national file does not include a single child-level
weight. Sampled children are included in the calculation of
both weights, but the two weights for any given sample child
will differ slightly because of the difference in the number of
sample adult cases used to calculate post_pr_int compared with
post_sr_int.
Estimates for children can be produced using either
weight, but adults are included in both weights as well
(even if the analyst is not interested in asthma in adults).
Therefore, analysts need to determine which adult cases to
include: those that contain self-reported information only,
or adult cases that contain information from both the sampled
and proxy respondents. The preferred weight to use for
child-level estimates is post_sr_int because it only includes
sampled adult self-report information, in addition to all
information for children. The alternate weight is post_pr_int,
which includes sampled adult self- and proxy reports, in
addition to all children. The post_pr_int weight should be used
for methodological research to examine differences between
self- and proxy reporting in adults. One should recall that,
because of proxy reporting error, all asthma negative
proxy responses for adults were verified with the sampled
adult if possible.
post_sr_int . . . . . . . . . .
Includes only sample adult self-report cases and all sample children
...
Four-state sample
post_adult_int . . . . . . . .
Includes sample adults 18 years of age and over
This is used to examine characteristics of asthmatic adults.
post_child_int . . . . . . . .
Includes sample children ages 17 years of age and under
This is used to examine characteristics of asthmatic children.
weight_int. . . . . . . . . . .
Includes all sample adults and sample children
This is used to examine characteristics of the
asthmatic population across all ages; it is provided to reduce
the analyst’s work by eliminating the need to aggregate the adult
and child weights to examine the whole sample.
. . . Category not applicable.
NOTE: NAS is National Asthma Survey.
Series 1, No. 46 [ Page 29
Taylor-series standard errors in a
straightforward way. This method
requires no recoding of design variables,
but it is statistically less efficient and
therefore more conservative than some
other methods because the PSU is
treated as being sampled with
replacement within the stratum. The
with-replacement option is used because
the sampling fractions for households
within a stratum are all very small.
To summarize, analysts must ensure
that the following key points are
attended to before running any code:
+ The program must be able to
accommodate a complex sample
design and with-replacement
sampling to estimate variance
properly.
+ The data file must be sorted by
stratum (variable name is STATE in
the four-state file and STRATUM in
the national file) and PSU (variable
name for both files is IDNUMR)
within stratum prior to invoking the
code.
+ The correct weight must be used to
calculate estimates properly.
The syntax examples below offer
simple guidance to an analyst; one
should refer to the appropriate program
manual for more in-depth details. The
syntax listed below does not take
advantage of the full range of options
available in SUDAAN and STATA.
SUDAAN
SUDAAN code example, four-state
sample
Research question—What is the
frequency, percentage, and standard
error of current asthma (using the
derived variable ASTATUS1) for all
females by income group?
One should assume the following:
1) SAS-callable SUDAAN is being
used, 2) the name of the four-state SAS
data file is ‘‘fourstate,’’ 3) the variables
have been recoded to exclude
‘‘missing,’’ ‘‘don’t know,’’ and
‘‘refused’’ answer categories in the
analysis, 4) appropriate variables with
answer categories of ‘‘0’’ (zero) have
been recoded with a nonzero number
category to run in SUDAAN, and 5)
females of all ages should be included
in the analysis. The variable ASTATUS1
is a derived variable that denotes the
current asthma status of the sampled
household member based on selfidentification. The following is the code
example:
PROC SORT DATA = FOURSTATE;
BY STATE IDNUMR;
RUN;
PROC CROSSTAB DATA =
FOURSTATE DESIGN = WR;
NEST STATE IDNUMR;
WEIGHT WEIGHT_INT;
SUBPOPN S2Q6 = 2;
SUBGROUP ASTATUS1
BESTINCOMEG1;
LEVELS 2 11;
TABLES ASTATUS1*
BESTINCOMEG1;
PRINT NSUM WSUM ROWPER
SEROW / SYTLE = NCHS
WSUMFMT = F7.0 SEROWFMT =
F5.4;
RTITLE1 ‘WEIGHTED FREQ,
PERCENT & SE OF CURRENT
ASTHMA: ASTATUS1’;
RTITLE2 ‘IN FEMALES OF ALL
AGES BY INCOME GROUPS’;
RTITLE3 ‘FOUR-STATE
SAMPLE’;
RUN;
SUDAAN code example, national
sample
Research question—What is the
prevalence and standard error of current
asthma (using the derived variable
ASTATUS1) for all females by income
group?
One should assume the following:
1) SAS-callable SUDAAN is being
used, 2) the name of the national SAS
data file is ‘‘nation,’’ 3) the variables
have been recoded to exclude
‘‘missing,’’ ‘‘don’t know,’’ and
‘‘refused’’ answer categories in the
analysis, 4) appropriate variables with
answer categories of ‘‘0’’ (zero) have
been recoded with a nonzero number
answer category to run in SUDAAN,
and 5) self-reported data for adult
female respondents should be included
(recall that children are included in both
national sample weights, but the analyst
must decide whether to include adults
who self-report only or to include
self-report and proxy responses for
adults). The variable ASTATUS1 is a
derived variable that denotes the current
asthma status of the sampled household
member based on self-identification. The
following is the code example:
PROC SORT DATA = NATION;
BY STRATUM IDNUMR;
RUN;
PROC CROSSTAB DATA =
NATION DESIGN = WR;
NEST STRATUM IDNUMR;
WEIGHT POST_SR_INT;
SUBPOPN S2Q6 = 2;
SUBGROUP ASTATUS1
BESTINCOMEG1;
LEVELS 2 11;
TABLES ASTATUS1*
BESTINCOMEG1;
PRINT NSUM WSUM ROWPER
SEROW / STYLE = NCHS
WSUMFMT = F7.0 SEROWFMT =
F5.4;
RTITLE1 ‘WEIGHTED
PREVALENCE & SE OF
CURRENT ASTHMA:
ASTATUS1’;
RTITLE2 ‘IN FEMALES OF ALL
AGES BY INCOME GROUPS’;
RTITLE3 ‘SELF-REPORTED
ADULT DATA, NATIONAL SAMPLE’;
RUN;
STATA
STATA uses essentially the same
variance estimation method as
SUDAAN (e.g., assumes withreplacement sampling). The SVY
commands in STATA handle complex
survey data. The relevant arguments
should be structured as follows:
+ SVYSET STRATA (STATE or
STRATUM as appropriate; do not
include the parenthesis).
+ SVYSET PSU (IDNUMR).
+ SYVSET PWEIGHT (insert the
appropriate weight variable name).
For a more-detailed description of the
SVY commands, review the STATA
documentation for the appropriate
version.
Page 30 [ Series 1, No. 46
Citations and Further
Information
Any published material derived
from NAS data should acknowledge
CDC, NCHS, and SLAITS as the
original source. The suggested citation,
‘‘Data Source: Centers for Disease
Control and Prevention, National Center
for Health Statistics, State and Local
Area Integrated Telephone Survey,
National Asthma Survey, 2003,’’ should
appear at the bottom of all tables. A
disclaimer should be included that
credits the authors (i.e., the recipient of
the data file) with any analyses,
interpretations, or conclusions reached.
NCHS and SLAITS are only responsible
for the initial data. In addition, the
acronyms ‘‘NAS’’ and ‘‘SLAITS’’
should be placed in titles, keywords, and
abstracts of journal articles and
publications to facilitate retrieval in
bibliographic searches.
Data users can obtain the latest
information about the SLAITS
mechanism by periodically checking the
website at http://www.cdc.gov/nchs/
slaits.htm. This site features
downloadable public-use data files and
documentation for SLAITS modules,
important information about any
modifications or updates to data and
documentation, and current contact
information. Questions should be sent
by electronic mail to slaits@cdc.gov,
and a staff member will respond as soon
as possible.
Researchers may also wish to join
the SLAITS electronic mail listserv. To
subscribe or unsubscribe, visit
http://www.cdc.gov/nchs/about/major/
slaits/slaitslistserv.htm and follow the
directions as listed. The listserv has
approximately 1,000 subscribers around
the world who use SLAITS data or are
interested in the SLAITS mechanism.
Subscribers periodically receive e-mail
with news about SLAITS surveys, new
releases of data or documentation,
publications, or related conferences.
Listserv membership is not shared.
Although the SLAITS mechanism
uses the NIS sampling frame, the
websites listed below should be visited
for further information on vaccines and
immunization. For general information
on child and adult vaccinations, please
visit http://www.cdc.gov/vaccines. For
more information on the NIS sampling
frame, please visit http://www.cdc.gov/
vaccines/stats-surv/default.htm#nis. For
more information on vaccine and
immunization surveillance and statistics,
please visit http://www.cdc.gov/vaccines/
stats-surv/default.htm.
For more information on NCHS and
its publications or data files, please
contact the following:
Data Dissemination Branch, NCHS
3311 Toledo Road
Hyattsville, MD 20782–2003
Phone: 301–458–INFO (4636) or
866–441–NCHS (6247)
E-mail: nchsquery@cdc.gov
Internet: http://www.cdc.gov/nchs/
For more information on CDC,
contact CDC’s Information Contact
Center (CDC-INFO) in English or
Spanish by calling 800–CDC–INFO
(800–232–4636), or email
cdcinfo@cdc.gov. If you are hearing
impaired, you may contact CDC-INFO
with a TTY (text telephone) machine at
888–232–6348. The CDC-INFO fax
machine line is 770–488–4760.
Guidelines for Data
Use
With the goal of mutual benefit,
NCHS requests that recipients of data
files cooperate in certain actions related
to their use.
Data users who wish to publish a
technical description of the data should
make a reasonable effort to ensure that
the description is not inconsistent with
that published by NCHS.
The Public Health Service Act
(Section 308d) provides that data
collected by NCHS may be used only
for the purpose of health statistical
reporting and analysis. Any effort to
determine the identity of any reported
case is prohibited by this law. NCHS
does everything possible to ensure that
the identity of data subjects cannot be
disclosed. All direct identifiers, as well
as any characteristics that might lead to
identification, are omitted from the data
files. Any intentional identification or
disclosure of a person or establishment
violates the assurances of confidentiality
given to the providers of the
information. Therefore, users must
adhere to the following:
+ Use the data in these files for
statistical reporting and analysis
only.
+ Make no use of the identity of any
person discovered, inadvertently or
otherwise, and immediately advise
the Director of NCHS of any such
discovery at 301–458–4500.
+ Not link these data files with
individually identifiable data from
any other NCHS or non-NCHS data
files.
By downloading and using these data,
you signify your agreement to comply
with the above-stated statutory-based
requirements.
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Weiss KB, Sullivan SD. The health
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Akinbami LJ, Schoendorf KC. Trends
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Smith T. A review of methods to
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Westat, Inc. Available from: http://
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asthma—Updated on selected topics,
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Page 32 [ Series 1, No. 46
Appendix I
Specification of the
National Asthma Education
and Prevention Program
Severity Indices Using the
National Asthma Survey
Data
In 1989, the National Heart, Lung,
and Blood Institute of the National
Institutes of Health initiated the National
Asthma Education and Prevention
Program (NAEPP) to educate people
with asthma, the general public, and
health care providers about asthma and
update clinical treatment guidelines. The
NAEPP Expert Panel developed an
asthma severity classification scheme to
document medication adjustments that
should be implemented to maintain
long-term control of asthma adequately
in children and adults. In 2002, this
severity classification scheme was
updated to reflect clinical practice more
accurately. The prior iteration included
three severity categories—mild,
moderate, and severe—and a stepwise
approach to treatment (i.e., the
medications were adjusted as needed by
reviewing the frequency of daytime and
nighttime symptoms). The revised
classification uses four descriptive
severity categories to describe asthma
before treatment or adequate control:
mild intermittent, mild persistent,
moderate persistent, and severe
persistent (25). Under the revised
classification, at any level of severity
the patient can have ‘‘mild, moderate, or
severe exacerbations’’ (25). The National
Asthma Survey (NAS) data can be
explored using these revised NAEPP
classifications as specified below.
Please note: all values of ‘‘don’t
know’’ (coded as 96, 996) and
‘‘refused’’ (coded as 97, 997) are treated
as missing.
30-day index
Recoding before calculation:
If S4Q1 equals .L or .N, recode S4Q1
to 0.
If S4Q3 equals .L or .N, recode S4Q3
to 0.
A) Question S4Q1
1. Mild intermittent (0 to 8)
2. Mild persistent (9 to 29)
3. Moderate persistent (30 and S4Q2
equals 0)
4. Severe persistent (30 and S4Q2
equals 1)
B) Question S4Q3
1. Mild intermittent (0, 1, 2)
2. Mild persistent (3, 4)
3. Moderate persistent (5 to 10)
4. Severe persistent (more than 10)
The severity rating is the higher of
elements ‘‘A)’’ and ‘‘B)’’ above. If only
one element is nonmissing, that element
should be used to assign the index
value.
12-month index
Recoding before calculation:
If S5Q2 equals 0, recode S5Q3 to 0.
If S3Q10 equals 0, 2, 3, or 4 and
S5Q3 equals .L and S5Q4 equals .L,
recode S5Q3 and S5Q4 to 0.
C) First, add responses from S5Q3 and
S5Q4. If one of the two variables is
missing, take the value of the
nonmissing variable as the sum. Then
code as follows:
1. Mild intermittent (0)
2. Mild persistent (1, 2)
3. Moderate persistent (3 to 6)
4. Severe persistent (7 and over)
D) Question S5Q9
1. Mild intermittent (0)
2. Mild persistent (1 to 5)
3. Moderate persistent (6 to 75)
4. Severe persistent (more than 75)
If age (S2Q5) is less than 18 years,
the severity rating is the value of
element ‘‘3).’’
If S2Q5 (age) is greater or equal to
18 years, the severity rating is the
higher of elements ‘‘C)’’ and ‘‘D)’’
above. If only one element is
nonmissing, use that element to assign
the index value.
Combined index
The severity rating is the higher of
the 30-day or 12-month index above. If
only one of the two indices above is
nonmissing, set the value of the
combined index to the nonmissing
index.
Series 1, No. 46 [ Page 33
Appendix II
Sampling and Weighting
Technical Description
Sample design
The basic design objective of the
State and Local Area Integrated
Telephone Survey (SLAITS) 2003 NAS
was to select a random sample of
households for asthma-status screening.
The target number of households was
set at 10,000 for the national study and
12,000 in each of the four states
comprising the four-state study. The
sample of households selected for
screening for NAS was derived from the
sampling frame for the National
Immunization Survey (NIS), a
continuous list-assisted random-digit
dialing (RDD) survey administered in
78 Immunization Action Plan (IAP)
areas (consisting of the 50 states and 28
metropolitan areas, including the District
of Columbia). Therefore, the sampling
design for the selection of households in
NAS was essentially the same as in
NIS.
Drawing NIS sample
The household selection procedure
and NIS sample design is briefly
described below. For additional
information, please consult the Smith et
al. (10) publication or the NIS website
at http://www.cdc.gov/vaccines/stats
surv/default.htm#nis.
Associating telephone numbers with
estimation (IAP) areas
To draw a sample of telephone
numbers in an IAP area, one must (in
effect) compile a list of all telephone
numbers that belong to that area. For
some IAP areas, this step is
straightforward. For example, when the
IAP area is a state with a single area
code, the list would consist of all
telephone numbers within the
central-office codes that are in service in
that area code. Combined, an area code
and a central-office code form a ‘‘prefix
area.’’ For example, 617–492 is the
prefix area corresponding to the 492
central office in the 617 area code.
For other IAP areas, however, this
step is more complicated. When the IAP
area is a city, county, or combination of
counties, some prefix areas may cover
part of the IAP area and part of an
adjacent IAP area. In such situations,
NIS applies a plurality rule: if at least
50% of the directory-listed households
in a prefix area fall inside an IAP area,
the prefix area is assigned to that IAP
area.
Drawing the initial NIS sample
The sampling frame for an IAP area
consists of banks of 100 consecutive
telephone numbers within the prefix
areas assigned to the IAP area. For
example, the numbers from 617–492–
7100 to 617–492–7199 constitute a
working bank in the 617–492 prefix
area. Banks that contain zero
directory-listed residential telephone
numbers (‘‘zero banks’’) are excluded
from the frame because they have very
little chance of containing working
residential numbers. For this preliminary
step, the GENESYS Sampling System
(a proprietary product of Marketing
Systems Group [MSG]) uses a file of
directory-listed residential numbers from
Donnelley Marketing Information
Services. The result is a file that lists
the remaining banks (the ‘‘1+ working
banks’’). From the 1+ working banks, a
random sample of complete 10-digit
telephone numbers is drawn for each
quarter in such a way that each number
has a known and equal probability of
being selected. The sample is then
segmented into replicates, or random
subsamples, with each replicate
containing sample telephone numbers
from each of the 78 IAP areas.
Segmenting the sample into replicates
allows for the release of telephone
numbers over time in a controlled
manner.
Updating the NIS sampling frame
The set of telephone banks with at
least one directory-listed residential
telephone number changes over time. As
a result, the sampling frame of 1+
working banks also needs to be updated.
The phenomenon of frequent area-code
splits has produced additional changes
to the sampling frame. The GENESYS
database reflects these changes in a
quarterly update. MSG has developed a
separate sampling frame for each IAP
area. Quarterly, the database is
examined to determine whether
currently included banks should be
assigned to different IAP areas and to
assign newly included banks to IAP
areas. The rules for assignment are the
same as in the initial definitions of the
IAP areas. Once all modifications have
been made to the GENESYS database, a
number of checks ensure that all
changes have been applied correctly and
that the new database produces samples
that are consistent with those produced
prior to the changes. These checks
compare the number of active banks and
RDD-selectable lines in each IAP area
before and after the update. In parallel,
the actual exchanges assigned to each
IAP area before and after the update are
compared. Small changes are
expected—new banks are put into
service as new numbers are assigned. In
the event of a major discrepancy in any
of these checks, MSG is notified of the
difference and asked to provide
documentation of the reasons for the
change.
Forming NIS sample replicates
The total size of the initial sample
for an IAP area is calculated according
to the following formula:
Total sample size = (1.5)T/(AC)
Where T is the quarterly target
number of completed interviews for the
IAP area (this number ranged from 95
to 126 in 2003), A is the proportion of
telephone numbers that remain after
identifiable business and nonworking
numbers have been removed (as
discussed below), and C is the
proportion of telephone numbers sent to
the telephone center that result in a
completed interview.
In the formula, A and C are specific
to the IAP area and are adjusted each
quarter, taking into account the results
from prior quarters. The target, T, may
also reflect results from previous
quarters. If the three previous quarters
have not produced their target total of
completes, T is raised accordingly.
Likewise, if the three previous quarters
have exceeded their target total of
completes, T is reduced accordingly. The
Page 34 [ Series 1, No. 46
factor 1.5 allows for variation in actual
performance among IAP areas and
among quarters.
The total sample selected is then
randomly divided into replicates. In the
first quarter of 2003, the number of
replicates was 36; the first 26 were
equal in size and the last 10 were
one-half that size. For the second, third,
and fourth quarters, the number of
replicates was 30: 24 full-size replicates
and 6 half-size replicates. This
procedure permits smoother release of
the sample at the rate of one or two
replicates per week for each IAP area
separately (as needed). Toward the end
of the quarter, the half-size replicates
allow tighter control over the total
amount of sample released. The aim is
to produce an even distribution of work
in the telephone center over the course
of a quarter and to give all cases an
equal probability of being completed.
Removing business and nonworking
numbers
In a traditional RDD survey, all
sampled telephone numbers are given to
interviewers for dialing. Because more
than one-half of all selected telephone
numbers are businesses, modem lines, or
unassigned, a large part of interviewers’
efforts may be directed simply to
identify and remove these numbers from
active sample. MSG has produced
companion products to their GENESYS
Sampling System that quickly and
accurately reduce the size of this task.
First, the selected sample is
matched against a GENESYS data file
that contains telephone numbers that are
directory listed in business yellow pages
and are not directory listed in residential
white pages. These business numbers
are removed from the sample. Second,
numbers listed in residential white pages
are identified and temporarily set aside.
Third, a computer system
(GENESYS-IDplus) screens the
remaining sample to remove a portion
of nonworking numbers. Using personal
computers with special hardware and
software, this system (called an
‘‘auto-dialer’’) automatically dials the
telephone numbers to detect nonworking
and modem numbers. Nonworking
numbers are usually indicated by the
familiar tritone signal for out-of-service
numbers, an extended period of silence,
or continuous noise on the line. If the
telephone number starts to ring, an
attendant responds if the telephone is
answered. Nationally, approximately
15% to 20% of the numbers are
answered. The GENESYS-IDplus
equipment is operated only during
daytime hours on weekdays in an
attempt to reduce the number of
answered calls. In addition, the white
pages directory-listed numbers identified
in the second step are not dialed. Rather,
those numbers are combined with the
numbers that were not removed by the
auto-dialer to produce the sample for the
telephone centers. These steps cull out
approximately 40% of the sampled NIS
lines.
Obtaining addresses for advance
letters
To obtain addresses that correspond
to sample telephone numbers, the
numbers for each replicate are sent to a
company that provides this
computerized matching service. It uses a
large database of residential and
business telephone numbers including
unpublished numbers. A listing may not
contain a street address by customer
request. The resulting file contains
numbers with and without address
matches. Matched listings contain a
business or residential identifier.
‘‘Do not call’’ requests
NIS maintains a file containing
telephone numbers of people who have
requested that they not be called. Each
quarter’s sample is compared with this
file, and numbers in the contractor’s
‘‘Do Not Call List’’ are excluded in the
quarterly sample of numbers loaded into
the CATI system.
Duplicate telephone numbers
Some telephone numbers may be
selected more than once because of the
repeated quarterly sample selection in
each IAP area. To avoid respondent
problems created by being recontacted
for the same survey, a further processing
step identifies duplicate numbers. Each
complete replicate sample file is
compared with all sample files released
during the four prior quarters (taking
into account area code splits). For NIS,
identified duplicates are processed as
follows.
If GENESYS-IDplus removes an
identified duplicate number, that result
supersedes the disposition of that
sampled number from the original
quarter in which it was sampled.
Otherwise, the processing depends on
whether the number was sampled in the
immediately preceding quarter.
Duplicates from earlier quarters are
mailed advance letters and released with
their assigned replicate. Duplicates from
the immediate preceding quarter are not
mailed advance letters because they
might have received such a letter
recently. If the sample telephone
numbers are released before the
immediate preceding quarter has
finished, they are put on hold until
household data collection for that
quarter has closed to ensure that they do
not receive calls simultaneously for two
quarters. Numbers that have certain
types of refusals (e.g., ‘‘take me off the
calling list’’) as their final disposition in
the earlier quarter are counted as
refusals in the current quarter. Certain
final outcomes from the immediate
preceding quarter are counted in the
current quarter. For example, if the case
is called for the preceding quarter in a
month when data collection for the
current quarter is also open, and the
final outcome is ‘‘nonworking number,’’
‘‘no child in range,’’ or ‘‘complete,’’ the
outcome is counted for both quarters
and data are copied for the current
quarter.
Because of repeated quarterly
selection of NIS sample in each IAP
area, some telephone numbers were
selected more than once over the course
of the NAS data collection period. Such
numbers were not contacted a second
time for the NAS. Instead, these cases
were automatically finalized. Response
rates reflect the final disposition of a
telephone line from its original
sampling.
Sampling design and allocation for
NAS
As noted earlier, the target number
of households to be screened was set at
10,000 for the national study and 12,000
in each of the four states comprising the
four-state study. The number of
Series 1, No. 46 [ Page 35
households required to be selected in
each IAP area within a state was
determined by allocating the desired
number of screened households among
the IAP areas within the state in
proportion to the total number of
households in each IAP area. In the
national study, the number of
households required to be selected in
each state was determined similarly by
allocating the desired number of
screened households among states in
proportion to the total number of
households in each state. Estimates of
the proportion of households were
obtained from the March 2004 Current
Population Survey’s Annual Social and
Economic Supplement (ASEC). The
number of telephone numbers that
needed to be called was computed using
the expected working residential number
rate, and it was increased to compensate
for refusals.
A random subsample of the required
number of NAS telephone numbers in
each IAP area was selected from the
NIS sample. These numbers were called
to identify NIS- and NAS-eligible
households. The sample selection was
spread over four quarters of NIS data
collection (quarters 1 through 4 of
2003). The split of the total sample
among quarters varied among IAP areas.
A screening interview was
conducted once a NAS-eligible
household was identified. The national
study selected a single household
member at random and asked about the
asthma status of that person. Regardless
of asthma status, the screening interview
included a series of demographic
questions about the sampled person and
household to produce asthma prevalence
rates. If the sampled respondent was
asthma-positive, a detailed interview
about asthma management and treatment
was also completed. In contrast, the
four-state study immediately screened
households for the presence of someone
with asthma. If no one was reported to
have asthma, the interview was
terminated and no information was
obtained on the household members. In
households where asthma was reported,
up to one asthma-positive adult and one
asthma-positive child were randomly
selected for a detailed interview about
asthma management and treatment. A
few questions in both studies asked
about nonsampled persons, such as the
asthma status of biological parents,
grandparents, and siblings, total
household income, and indoor air
quality questions relevant to the entire
household. In the national study only,
the age of each person in the household
and whether anyone else in the
household had asthma were also asked.
By design, the national and
four-state studies also used some
NAS-only sample, allowing an
examination of response rates with and
without the conduct of NIS. Sample
design and allocation were identical
regardless of whether the NIS was
conducted, except that respondents in
the NAS-only sample received an
NAS-only version of the questionnaire
and advance letter, and the NIS screener
and interview were not administered.
Sampling weights
Overview
Each sampled respondent for whom
enough data were collected was
assigned a sampling weight to obtain
population-based estimates. This weight
should be used for all analyses. The
sampling weight is composed of a base
sampling weight, an adjustment for
multiple telephone lines within a
household, and various adjustments for
nonresponse. The final, adjusted weight
is poststratified so that the sum of the
weights at the national level or for each
state (as applicable) equals selected
population control totals from an outside
source. For the NAS national study, the
source was the 2002 NHIS. For the
four-state study, the sources were the
2003 BRFSS for adults and 2003
SLAITS National Survey of Children’s
Health for children. The steps to
produce the national study sampling
weights are described below, followed
by a similar discussion for the four-state
study weights.
Production of sampling weights for
the national study
If a sampled household member
was a child under the age of 18 years,
questions were asked of an adult
knowledgeable about that child’s health.
If the sampled household member was
an adult aged 18 years or over,
questions were asked of that sampled
adult whenever possible. However, if the
sampled adult was not available at the
time of the screening contact, a proxy
interview was conducted with the adult
household member who answered the
telephone. Because of the observed error
rate in proxy reporting of adult asthma
status, two versions of the national study
sampling weight were calculated to
allow for production of estimates with
and without proxy cases. The first
version included all adult respondents
with data regardless of whether the data
were collected through a self-report or a
proxy respondent. The second included
only the adult respondents from whom
data were collected personally. Sampled
children were included in the calculation
of both weights. The process to create
the two weights was identical, and the
difference is in the set of cases to which
the weights were assigned.
Base sampling weight—A sample of
NAS telephone numbers was selected in
each IAP area (as applicable) over four
quarters of NIS data collection. In NIS,
an independent sample of telephone
numbers is selected each quarter. A
telephone number could have been
selected for NAS in any of the four
quarters of the data collection period.
Once a telephone number was selected,
it was not selected again for data
collection in subsequent quarters. To
compute the base sampling weight, the
overall probability of selection was
determined considering the probabilities
of selection over four quarters.
The number of quarters over which
the total sample is selected is q; pi
denotes the probability of selecting a
telephone number in the ith quarter, and
p is the overall probability of selection
of the telephone number of the
household. Therefore,
q
p=
∑ pi
.
i=1
Because the sample was selected over
four quarters,
n1
p1 =
N1
for the first quarter, where n1 is the
number of telephone numbers selected
Page 36 [ Series 1, No. 46
in the first quarter, and N1 is the number
of telephone numbers available for
selection.
n1 n2
p2 = (1 – )
,
N 1 N2
for the second quarter, where n2 is the
number of telephone numbers selected
in the second quarter, and N2 is the
number of telephone numbers available
for selection.
n2 n 3
n1
p3 = (1 – ) (1 – )
,
N2 N3
N1
for the third quarter, where n3 is the
number of telephone numbers selected
in the third quarter, and N3 is the
number of telephone numbers available
for selection.
n2
n3 n 4
n1
p4 = (1 – ) (1 – ) (1 – )
,
N2
N3 N4
N1
for the fourth quarter, where n4 is the
number of telephone numbers selected
in the third quarter, and N4 is the
number of telephone numbers available
for selection.
The base sampling weight for a
household in a particular IAP area is
given by w = 1 / p. Generally, this
weight is the same for all households
within an IAP area.
Households with multiple telephone
lines—The base sampling weight of
eligible households that have multiple
voice-use landline telephone lines was
adjusted to compensate for the higher
probability of selection of these
households. The adjustment divides the
base sampling weight by the number of
telephone lines in that household.
The number of telephone lines in
the kth household in an IAP area is tk.
The adjusted base sampling weight for
that household is given by
wk =
w
.
tk
If the household had only one telephone
line, the adjusted weight is the same as
the base sampling weight.
Unit nonresponse adjustment 1
(residential status unknown)—When a
selected telephone number is called,
three results are possible: 1) the number
called is a household, 2) the number
called is not a working residential
number (i.e., a business number or
nonworking number), or 3) the
residential status of the telephone
number is unknown. A minimum of 10
call attempts were made before a
number was assigned unresolved status.
Adjustment of the base sampling
weight to account for numbers of
unknown residential status occurred in
two steps. First, unresolved telephone
numbers that had been finalized as
‘‘ring-no-answer at all attempts’’ were
redistributed as follows: 20.4% were
grouped with known, unscreened
households (category 1), and 79.6%
were grouped with nonresidential
numbers (category 2). This redistribution
is based on research by Frankel et al.
(17), who drew a national sample to
estimate the percentage of residential
telephone numbers among ‘‘ring-no
answer at all attempt’’ numbers. Second,
adjustment of the base sampling weight
to account for nonresponse in the
remaining category 3 numbers used the
same method as NIS. This method,
described in detail in the 1999 National
Immunization Survey Methodology
Report, uses information external to the
survey to allocate these unknown
numbers as either residential or
nonresidential (26).
Among the telephone numbers in
the sample for an IAP area, let the count
in each of the three categories
mentioned above be n1, n2, and n3. The
first nonresponse adjustment factor is
A1 =
n1 + n^ 31
,
n1
where n^31 is the estimated number of
households among the n3 in the ‘‘status
unknown’’ category. The procedure to
estimate the number of households in
the unknown category is based on a
study conducted in 1994 and 1995,
which asked telephone company
business offices to report the status of a
sample of category 3 telephone numbers
(27). The results showed the proportion
of residential numbers varies according
to regional groupings of IAP areas by
whether the telephone number was
directory listed and by type of
noncontact (e.g., ring-no-answer
compared with answering machine).
Therefore, the nonresponse adjustment
factors for each IAP area were defined
by IAP area grouping and calling
disposition code and by whether the
number was directory listed. To keep the
notation simple, the adjustment factor is
denoted by A1, although it could differ
among households within an IAP area.
The nonresponse-adjusted base sampling
weight after nonresponse adjustment 1
for the kth household in an IAP area is
given by
A1wk .
Each known household has an adjusted
weight.
Unit nonresponse adjustment 2
(households of unknown eligibility)—A
second form of nonresponse may occur
because a household respondent does
not complete the screener questions that
determine eligibility (i.e., asthma status).
The adjustment for this form of
nonresponse is completed separately
within three urban setting categories
based on the U.S. Census Bureaudefined Metropolitan Statistical Areas
(MSAs). An MSA is a geographic entity
associated with at least one urbanized
area with a population of at least
50,000. The MSA comprises the central
county or counties containing the core
and adjacent outlying counties having a
high degree of social and economic
integration with the central county
measured through commuting (18). The
three categories used for the adjustment
are (from most urban to most rural)
within a central city of an MSA; outside
a central city, but still within an MSA;
and not within an MSA.
The number of households (within
each urban setting category) in which
the selected person had asthma out of
the n1 households contacted is q1. The
number of households in which the
selected person did not have asthma is
q2, and q3 denotes the number of
households that did not respond to
screening questions:
n1 = q1 + q2 + q3 .
The nonresponse adjustment to the
sampling weight to account for not
being able to screen households is given
by
Series 1, No. 46 [ Page 37
n1
∑ A1wk
A2 =
k=1
.
q1 + q2
∑ A1wk
q1households in which the sampled
respondent had asthma is q*1. The
nonresponse adjustment factor for the
interview nonresponse is given by
q1
∑ wpkmk
k=1
The nonresponse-adjusted base sampling
weight after nonresponse adjustment 2 is
given by
wak = A2A1wk .
This adjusted weight is defined for all
households in which a screening
interview was completed.
Subsampling adjustment—A single
household member was randomly
selected from among all household
members to be the focus of the
interview. The interviewer first asked
the number of people of all ages living
in the household and then the number of
females living in the household. The
computer-assisted telephone
interviewing (CATI) system created an
internal household roster of oldest to
youngest household members by sex
based on this information and randomly
selected a household member from that
roster (e.g., the oldest male or the
second oldest female). In households
with more than one household member,
the randomly selected person
represented all of the people in the
household. Therefore, the sampling
weight for this completed interview
must be increased to reflect the selection
probability. This adjustment simply
multiplies the weight by the total
number of household members. The
number of household members in the
kth household in an IAP area is mk.
The sampling weight for the
selected person is
wpk = wak mk .
Unit nonresponse adjustment 3
(sampled persons who do not complete
the interview)—Data were not obtained
for all persons selected for an interview.
Therefore, the weights of the persons for
whom data were available were adjusted
to account for those for whom no data
were collected. The nonresponse
adjustment factor A3 within an IAP area
was computed as follows.
The number of households in which
interviews were completed among the
A3 =
k=1
.
q*1
∑
wpk mk
k=1
The numerator gives the estimated
number of respondents who had asthma
based on the sampled households in
which the respondent had asthma. The
denominator gives the estimated number
of sampled respondents with asthma
based on the households in which an
interview was completed. The
nonresponse-adjusted sampling weight
for respondents is
wpak = A3wpk .
Poststratification weight
adjustment—Despite the weighting and
nonresponse adjustments, the estimated
number of people is unlikely to match
perfectly the number of people in the
sampled population. Any discrepancies
are likely due to random sampling error
and nonrandom response biases. Among
these biases may be greater nonresponse
for some categories of age, sex, or race.
Poststratification adjusts the weights to
match population control totals for key
demographic variables obtained from an
independent source. Thus, the NAS
sampling weight was further adjusted so
that the sum of all person weights
equaled external population control
totals.
The sample of interviewed
households was divided into cells
representing more detailed categories of
selected variables. Poststratification
adjustments were not made in each cell
formed by cross-classification of
categories of the stratification variables
because control totals for each cell were
not available. Only the marginal
population control totals for those
variables were determined. Therefore,
raking was used to adjust the weights
(28). Raking iteratively adjusts the
weights so they match the marginal
control totals.
The independent source for NAS
population control totals was the 2002
NHIS. The NAS weights were adjusted
so that the sum of the weights equaled
the 2002 NHIS population counts for
the following groups:
+ Number of males and females in
nine age groups.
+ Household size.
+ Number of persons of various racial
and ethnic backgrounds.
+ Number of males and females by
asthma status.
The poststratification process also
included an adjustment for potential bias
that may exist because households that
had no telephone at the time of the
survey could not be contacted. This
adjustment incorporated information
about household interruptions in
telephone service from NAS itself.
Evidence suggests that households that
had telephones at the time of the survey,
but had interruptions in telephone
service of 1 week or more during the
year, were more similar to households
with no telephone service at the time of
the survey than were households with
uninterrupted telephone service during
the year (17,19–21). Therefore,
noncoverage of households without
telephones could be somewhat
compensated for by proportionately
increasing the weights for interviews
completed in households with
interrupted service. Completed
interviews in households with
interrupted service represent the
households without telephone service at
the time of the survey.
To adjust for households without
telephones, the numbers of telephone
and nontelephone households were
determined from the 2002 NHIS. Next,
from NAS, the weighted proportion of
telephone households having an
interruption in telephone service for at
least 1 week during the past 12 months
was computed. This proportion was then
applied to the number of telephone
households to estimate the number of
telephone households with interruption.
These calculations produced two control
totals: one for households with
telephones and no interruption in service
and the other for those without
telephones or with an interruption in
telephone service. These control totals
are mutually exclusive and exhaustive.
Page 38 [ Series 1, No. 46
From NHIS, the total number of
persons in telephone and nontelephone
households is denoted by M and the
number of persons in telephone
households is Mt. The number in
nontelephone households is M – Mt.
From NAS, the weighted proportion
of persons in households with an
interruption in telephone service is
denoted as pIt. The number of persons in
telephone households with interruptions
in telephone service is given by
M1t = Mt pit. The number of persons in
telephone households without
interruptions in telephone service is
given by M t – MIt.
The other control total combines
persons in telephone households with
interruptions and persons in
nontelephone households:
MIt + (M – Mt).
The final sampling weight for the
responding household member in
household k in an IAP area is denoted
by
wak = wakmak .
The sampling weight for the selected
child with asthma is
wck = wakmck .
Similarly, the nonresponse
adjustment for the four-state study
detailed interview was implemented
separately for adults and children, with
completed adult interviews representing
sampled adults without a completed
interview and completed child
interviews representing sampled children
without a completed interview. Again,
the adjustment also varied by
geographic area within the adult and
child categories.
Households in which the selected
adult had asthma is denoted as q, and q*
is the number of households in which
the selected adult respondent completed
a detailed interview. The nonresponse
adjustment factor to account for selected
adults with asthma who did not respond
(in other households) is given by
wpfk .
The subscript f denotes the final weight.
q
∑
Aa3 = k = 1
wak
.
‘‘Have you ever been told by a
doctor or other health professional that
you have asthma?’’
The questions that determined
asthma-positive status in the BRFSS and
NSCH were these:
BRFSS—‘‘Have you ever been told
by a doctor, nurse, or other health
professional that you had asthma?’’
NSCH—‘‘Has a doctor or other
health professional ever told you that
[the sampled child] has asthma?’’
The NAS weights for sampled
adults were adjusted so that the sum of
the weights equaled the 2003 BRFSS
counts of asthma-positive adults in the
following groups by each state:
+ Six age groups.
+ Males and females.
+ Number of adults of various racial
and ethnic backgrounds.
The NAS weights for sampled children
were adjusted so that the sum of the
weights equaled the 2003 SLAITS
NSCH counts of asthma-positive
children in the following groups by each
state:
q
Production of sampling weights for
the four-state study
The process to produce four-state
study sampling weights was identical to
that for the national study to the point
of the subsampling adjustment. For the
four-state study, these adjustments were
made separately for each specific state
for adults with asthma and children with
asthma because up to one such adult
and one such child could be sampled
within a single household. In households
with multiple asthma-positive adults, the
randomly selected adult represents all of
the nonselected asthma-positive adults in
the household. Therefore, the sampling
weight for the completed adult interview
must be increased to reflect the selection
probability. The adjustment multiplied
the weight by the number of eligible
adults in the household. The same
process occured for sampled children.
Here, mak denotes the number of
adults with asthma in the household,
and mck denotes the number of children
with asthma in the household. The
sampling weight for the selected adult
with asthma is
∑ wak
k=1
Similarly, the adjustment for
nonresponse by selected children with
asthma is given by
u
∑
Ac3 =
wkc
k=1
.
u
∑
wck
k=1
To compute the nonresponse-adjusted
weights, wak is multiplied by Aa3 and wck
by Ac3.
The four-state study used two
independent sources of population
control totals for poststratification: the
2003 BRFSS for adults and 2003
SLAITS NSCH for children. Because
the NAS four-state study was restricted
to asthma-positive adults and children
(i.e., those who had ever been diagnosed
as having asthma), only totals for those
groups were culled from the BRFSS and
NSCH. In NAS, asthma-positive status
was determined by a positive response
to the following question:
+ Three age groups.
+ Males and females.
+ Number of children of various racial
and ethnic backgrounds.
Finally, the adjustment for
nontelephone households was slightly
different for the four-state study. The
separate proportions of adults and
children in telephone and nontelephone
households were determined from the
March 2004 ASEC. These proportions
were applied to the state control totals
of the numbers of adults and children to
derive the estimated numbers of adults
and children in each state in telephone
and nontelephone households. The
weighted proportions of adults and
children in telephone households having
an interruption in telephone service for
at least 1 week during the past 12
months were computed from NAS.
These proportions were applied to the
number of adults and children in
telephone households to estimate the
number of adults and children in
telephone households with interruption.
These calculations produced two control
totals for adults and two control totals
Series 1, No. 46 [ Page 39
for children: one for those in households
with telephones and no interruption in
service and the other for those in
households without telephones or with
an interruption in telephone service.
These control totals are mutually
exclusive and exhaustive.
The final sampling weights for adult
and child respondents after
poststratification are denoted by
wafk = wcfk .
Table I. Number of values imputed for 2003 NAS poststratification variables
Number of missing values
Variable
Age. . . . . . . . . . . . . . . . .
Sex . . . . . . . . . . . . . . . . .
Race . . . . . . . . . . . . . . . .
Hispanic ethnicity . . . . . . . .
Number of telephone lines. . .
Interrupted telephone service .
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National study
Four-state study
...
...
310
61
59
124
10
11
122
123
82
106
.
.
.
.
.
.
. . . Category not applicable.
NOTE: NAS is National Asthma Survey.
Imputation of missing values of
poststratification variables
Missing values of required
poststratification variables were imputed
either by Weighted Sequential Hot Deck
(WSHD) (29) or the use of models.
Table I shows the number of cases
imputed for each of these variables.
In the national study, only 6.1% of
the 10,054 cases required imputation of
any variable, and no single variable
required imputation in more than 3.1%
of cases. Similarly, in the four-state
study, only 3.1% of the 5,741 cases
required imputation of any variable, and
no single variable required imputation in
more than 2.1% of cases.
Table II. Summary statistics for poststratified weights, total screener and detailed
interviews, national sample: NAS, 2003
Unweighted
sample size
Minimum
weight
Maximum
weight
United States . . . . . . . . . . .
8,621
9,108.50
114,806.07
United States . . . . . . . . . . .
7,521
9,102.80
150,939.64
Standard errors of estimates
SUDAAN software can be used to
compute standard errors of estimates
using the with-replacement option (See
Tables II and III).
Imputation methods
Age—For the national study, no
cases were missing age. The 10 cases
missing age data in the four-state study
Median
weight
Sum of
weights
26,971.21
278,795,037
31,259.29
278,795,037
Weight = post_pr_int
32,339.06
Weight = post_sr_int
37,068.88
NOTE: NAS is National Asthma Survey.
Table III. Summary statistics for poststratified weights, total screening and detailed
interviews, by state and the entire four-state sample: NAS, 2003
Trimming weights
The weighting process resulted in a
small number of extremely large
weights, which can increase the variance
of estimates. Extremely large weights
were trimmed to reduce their impact.
Trimming introduces bias in the
estimates, so trimming should be
minimized. Therefore, only weights that
were greater than the median plus five
times the interquartile range were
defined as extreme and were truncated
to the median plus five times the
interquartile range.
Mean
weight
Unweighted Minimum
sample size
weight
Four-state sample
Maximum
weight
Mean
weight
Median
weight
Sum of
weights
Weight = weight_int1
Total . . . . . . . . . . . . . . . . . . . . .
5,741
56.026
14,910.770 1,596.073 1,169.764 9,163,056
Alabama.
California
Illinois . .
Texas . .
1,488
1,433
1,313
1,507
56.026
408.729
213.474
342.057
1,698.840
353.095
302.576
525,405
14,910.770 3,228.165 2,883.732 4,625,961
4,434.976 1,068.409
922.778 1,402,821
6,772.682 1,731.167 1,414.565 2,608,869
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Weight = post_adult_int2
Total . . . . . . . . . . . . . . . . . . . . .
Alabama.
California
Illinois . .
Texas . .
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3,736
65.538
14,910.770 1,794.087 1,269.086 6,702,710
987
931
888
930
65.538
817.640
213.474
503.346
1,698.840
396.830
324.731
391,671
14,910.770 3,730.567 3,314.775 3,473,158
4,434.976 1,178.439 1,007.008 1,046,454
6,772.682 1,926.266 1,662.099 1,791,427
Weight = post_child_int3
Total . . . . . . . . . . . . . . . . . . . . .
Alabama.
California
Illinois . .
Texas . .
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.
2,005
56.026
501
502
425
577
56.026
408.729
247.825
342.057
10,119.622 1,227.105
949.506 2,460,346
967.894
266.934
219.651
133,734
10,119.622 2,296.420 1,695.575 1,152,803
3,113.136
838.511
640.074
356,367
4,994.654 1,416.711 1,232.606
817,442
1
weight_int is a person-level interview weight that includes all sample adults and sample children in the sample and reduces the
analyst’s work by eliminating the need to aggregate the adult and child weights to examine the whole sample. It should be used if
the analyst wishes to examine characteristics of asthmatics in the entire sample across all ages.
2
post_adult_int is a person-level interview weight that only includes sample adults 18 years of age and over; it should be used if
the analyst is only interested in examining characteristics of asthmatic adults.
3
post_child_int is a person-level interview weight that only includes sample children under 18 years of age; it should be used if the
analyst is only interested in examining characteristics of asthmatic children.
NOTE: NAS is National Asthma Survey.
Page 40 [ Series 1, No. 46
were assigned to the largest age
category (for adults or children as
applicable) used in the weighting
process.
Sex—For the national study, no
cases were missing sex. For the
four-state study, WSHD was used to
impute sex. States were used as donor
pools.
Race and ethnicity—A combination
race and ethnicity variable was used for
weighting. If information on ethnicity
was missing, the variable was imputed
using WSHD. For cases imputed as
non-Hispanic that were missing data on
race, race was imputed using WSHD
with the household base weight. The
donor pools for both imputations were
IAP areas for the national study and
states for the four-state study.
Number of telephone lines—WSHD
was used to impute the number of
household telephone lines. Donor pools
were defined by household size (one
person, two people, three or more
people) for the national study and IAP
area for both studies.
Interrupted telephone service—For
interruption in telephone service, WSHD
was used with donor pools defined by
IAP area for the national study, by state
for the four-state study, and by income
(those with an income below $30,000 or
who did not know their income and
those with income at or above $30,000
or with refused income) for both studies.
Weight trimming
In sample surveys, very large or
extreme sampling weights are often
truncated, or ‘‘trimmed,’’ because large
variation in weights can result in large
sampling variances of survey estimates.
This is especially true if the sampling
weights are not correlated with values or
characteristics of interest. In such
situations, the few observations with
very large weights may contribute
unduly to the overall estimate. Large
weights can also be a result of sample
selection procedures and adjustments for
unit nonresponse.
Though a trimming procedure
reduces estimate variance, it may result
in increased estimate bias. The objective
of trimming is to reduce variance, so
this reduction more than compensates
for the increase in bias, resulting in a
smaller mean squared error than that
before trimming. Therefore, trimming as
little as possible is advisable.
No strict rules or procedures exist
to define or trim extreme weights, and
various methods of weight trimming are
practiced. In some surveys that employ
weighting, the size of nonresponse and
other adjustments to the base sampling
weights are restricted to avoid large
final weights altogether. Other surveys
examine the distribution of final weights
to identify extreme weights and propose
trimming rules. This method is more
common because identifying extreme
weights by examining the entire weight
distribution is easier.
Some common procedures to trim
weights are 1) to identify any sampling
weight larger than four to five times the
mean weight as an outlier weight and
trim that weight by making it equal to
the limit, 2) to identify any weight
larger than the median weight plus five
to six times the interquartile range of
the final weights and trim the weight by
making it equal to the limit, and 3) to
truncate weights above a certain
percentile (e.g., 95 or 99) in the
distribution of weights. The standard
deviation of weights is not used to guide
trimming because it is affected by
extreme weights.
Typically, once trimming has been
completed, the weights of observations
with untrimmed weights are increased
such that the sum of the new weights
equals the sum of the weights before
trimming.
Trimming NAS weights—The
distribution of final NAS weights was
examined to identify extreme weights. A
decision was made to define a final
weight as extreme if it exceeded the
median plus five times the interquartile
range to avoid undue trimming. A
formal description of the trimming
process is given below.
The final poststratified sampling
weight for the responding person in a
household in the sample is denoted by
wpfk. The number of respondent persons
in the sample with a final sampling
weight is n. The median of these n
weights is wm, and the interquartile
range is qr. Any weight exceeding the
value wm + 5qr is set equal to wm + 5qr.
Assuming that there are trimmed g
weights, the sum of the original
n
weights is
∑
w
p
fk
.
i=1
The sum of the new
n–g
weights is
∑
w
p
fk
+ g (wm + 5qr).
k=1
For the two sums to be equal, the
untrimmed weights are adjusted by a
factor equal to
This adjustment is done as part of
raking the weights, such that the sum of
the weights agrees with various control
totals in the other margins. A second
round of raking occurs after trimming is
complete.
Estimation of variance for national
study estimates—The final weight
attached to a responding person in the
national study
in household k in an IAP
p
area is wfk. For variance estimation, IAP
areas should be distinguished, as these
are strata for sample selection.
Therefore, the final weight in IAP area
h is denoted by wpfhk.
Some characteristic of interest for
the respondent in household k in stratum
h is denoted by yhk, and yhk equals 1 if
the person has the characteristic and 0 if
the person does not have the
characteristic. Assuming nh households
are in the sample in IAP area h, the
estimated proportion of persons having
the characteristic in stratum h is given
by
nh
R^h =
p
yhk
∑
wfhk
k=1
.
nh
p
∑
wfhk
k=1
The numerator is the sum of the
weights of all responding persons over
all households in IAP area h having the
characteristic, and it is an estimate of
the number of persons with the
characteristic. The denominator is the
Series 1, No. 46 [ Page 41
sum of the weights of all persons and
therefore gives an estimate of the
number of persons in IAP area h.
The estimated total number of
persons in IAP area h is denoted
by
nh
∑w
^
Nh =
p
fhk
.
k=1
For estimating the variance of the
sample proportion R^ h , define
^
p
wfhk
(yhk — R h)
zhk =
L
∑ ∑ zhk
h=1 k=1
^
R=
,
L
^
∑ Nh
h=1
where L is the number of strata (IAP
areas).
^ define
For estimating the variance of R,
^
p
wfhk
(yhk — R)
z hk =
,
^
N
where wpfhk and yhk are as defined
earlier. Also zhk and –zh are defined as
before and
^
Nh
and
nh
∑ z hk
zh =
k=1
nh
n
h
∑ (z hk – z h)2 .
k=1
The basic building block to
compute variance is the IAP area
because sample selection occurred at
this level. For states consisting of a
single IAP area, the estimate of the
variance is computed using the formula
given above. For states consisting of
multiple IAP areas and for national-level
estimates, zhk is defined slightly
differently. The estimated proportion at
the national level is given by
L
∑ N^h .
N^ =
.
An estimate of the variance of the
proportion of persons having the
characteristic in IAP area is given by
nh
^
v (R h) =
nh – 1
nh
h=1
The variance of R^ is given by
^)=
v (R
L
nh
nh
∑ (nh – 1) ∑ (zhk – z h)2 .
h=1
k=1
Estimation of variance for four-state
study estimates—There are two sets of
estimates for the four-state study: adults
and children. Variance estimation is
similar to the procedure described for
the national study except for adult-level
estimates; the final adult weight (wafk) is
used. For child-level estimates the final
child weight (wcfk) is used. Because each
of the four states in the study (Alabama,
California, Illinois, and Texas) contains
multiple IAP areas, the variance is
estimated at the IAP area level. The
final weights at the IAP area level for
adults and children are denoted by wafhk
for adults and wcfhkfor children.
Underestimation of variance—The
formulas for variance estimation assume
the weights are fixed. That is, in
repeated samples of households and
persons, weights attached to each person
in an IAP area are assumed to be
constant. However, the final weights are
actually obtained after various
adjustments to the base sampling
weight, and these adjustments depend on
the sample selected. Therefore, the
variance estimates do not reflect the
sampling variability of the weights. To a
certain extent, the variance is
underestimated. In addition, a slight
overestimation of variance is due to the
assumption of with-replacement
sampling of households when
households were actually selected
without replacement. The extent of
underestimation depends on variability
in weights in repeated samples.
This underestimation may not be
severe, as the weights have been raked
to multiple control totals, and may not
be highly variable in repeated samples.
An alternative method of variance
estimation would use a jackknife
technique or resampling procedure, such
as bootstrap estimation. For NIS,
jackknife variance estimates of
vaccination coverage rates were
computed but found to be very similar
to estimates obtained using Taylor-series
approximation (30). Using a resampling
procedure may involve a substantial
amount of work, in view of the large
number of strata.
Page 42 [ Series 1, No. 46
Appendix III
National Study Questionnaire
SLAITS National Asthma Survey
National Study Questionnaire
Form Approved
OMB No. 0920–0406
Exp. Date 12/31/04
Section
Subject
Section 1
NAS Eligibility Screening, Respondent Selection,
and Initial Demographics
Section 2
History of Asthma (Symptoms & Episodes)
Section 3
Health Care Utilization
Section 4
Knowledge of Asthma/Management Plan
Section 5
Modifications to Environment
Section 6
Medications
Section 7
Family History of Asthma
Section 8
Demographic Information
Proxy Interview Variable Listing
The following public burden estimate statement will be available as a CATI screen:
Public reporting burden of this collection of information is estimated to average 10 minutes per response, including the time for
reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing
the collection of information. An agency may not conduct or sponsor, and a person is not required to respond to a collection of
information unless it displays a currently valid OMB control number. Send comments regarding this burden estimate or any other
aspect of this collection of information, including suggestions for reducing this burden to CDC/ATSDR Reports Clearance Officer,
1600 Clifton Road NE, MS D-24, Atlanta, Georgia 30333; ATTN: PRA (0920–0406).
NOTE: CATI variable names are provided with corresponding SAS data file variable names in parentheses (if different).
Series 1, No. 46 [ Page 43
Section 1. NAS Eligibility Screening, Respondent Selection, and Initial Demographics
CASEID
UNIQUE HOUSEHOLD ID NUMBER
SAMP_TYPE
DERIVED. NIS/NAS OR NAS-ONLY SAMPLE GROUP
(1) NIS/NAS SAMPLE
(2) NAS-ONLY SAMPLE
PROX_STAT
DERIVED. DATA PROVIDED BY PROXY ONLY, SAMPLED RESPONDENT ONLY, OR BOTH PROXY
AND SAMPLED RESPONDENT
(0)
(1)
(2)
(3)
NEITHER SAMPLED PERSON NOR PROXY DATA
ONLY PROXY DATA
ONLY SAMPLED PERSON DATA
BOTH PROXY AND SAMPLED PERSON DATA
COMPLETE_STATUS DERIVED. SCREENER AND INTERVIEW COMPLETE STATUS
(0) DID NOT COMPLETE SCREENER
(1) SCREENER COMPLETE ONLY
(2) SAMPLED R INTERVIEW COMPLETED
(3) PROXY R INTERVIEW COMPLETED
(4) BOTH SAMPLED & PROXY R INTERVIEWS COMPLETED
IAPID
IAP AREA LOCATION
SPANISH
CATI FLAG. CASE PLACED IN SPANISH QUEUE
(0) NOT PLACED IN SPANISH QUEUE
(1) PLACED IN SPANISH QUEUE
LTR
ADVANCE LETTER MAILED TO HOUSEHOLD
(0) NO, LETTER WAS NOT MAILED
(1) YES, LETTER MAILED
CALLDATE
CATI DATE. DATE THE INTERVIEW WAS COMPLETED OR THE LAST DATE THE HOUSEHOLD WAS
CONTACTED, IF A COMPLETED INTERVIEW WAS NOT OBTAINED.
INTRODUCTORY STATEMENT
Now I have some important questions for both adults and children in your household that will allow us to
compare people who do and do not have asthma. If nobody in your household has asthma, the interview will be
very brief.
ROSTER
I need to ask questions about just one person in your household. Please tell me how many people of all ages live
in your household.
ENTER NUMBER ____
(96) DON’T KNOW
(97) REFUSED
FEMROSTER
[END INTERVIEW]
[END INTERVIEW]
[IF ROSTER = 1, SKIP TO R_ASTHMX01.]
Of these people, how many are female?
ENTER NUMBER ____
(96) DON’T KNOW
(97) REFUSED
RANDOMLY SAMPLE ONE PERSON FROM HOUSEHOLD ROSTER CREATED FROM ROSTER AND
FEMROSTER.
R_ASTHMX01
[Have you/Has the (SELECTED PERSON) in your household] ever been told by a doctor or other health
professional that [you have/(he or she has)] asthma?
(0)
(1)
(6)
(7)
CUR_AST (S3Q2)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO R_DOB (S3Q2)]
[SKIP TO R_DOB (S3Q2)]
[SKIP TO R_DOB (S3Q2)]
(Do you/Does he/Does she) still have asthma?
NO
YES
DON’T KNOW
REFUSED
Page 44 [ Series 1, No. 46
R_DOB (S2Q5) Please tell me [your age/the age of the (SELECTED PERSON)] in your household.
ENTER NUMBER ____
[SKIP TO R_SEX]
(996) DON’T KNOW
(997) REFUSED
AGECAT
For the purposes of this survey, it is important to get at least an age range for the person selected for the
interview. Would you please tell me if [you are/the (SELECTED PERSON) is] 18 years of age or older?
(1)
(2)
(6)
(7)
AGECAT_K
AGECAT_A
UNDER 18
18 OR OLDER
DON’T KNOW
REFUSED
Would you say that [the (SELECTED
(1) 0 to 5
(2) 6 to 11 or
(3) 12 to 17 years of age
(6) DON’T KNOW
(7) REFUSED
[SKIP TO AGECAT_K]
[SKIP TO AGECAT_A]
[END INTERVIEW]
[END INTERVIEW]
PERSON) is]:
[SKIP TO R_SEX (S2Q6)]
[SKIP TO R_SEX (S2Q6)]
[SKIP TO R_SEX (S2Q6)]
[END INTERVIEW]
[END INTERVIEW]
Would you say that [you are/the (SELECTED PERSON) is]:
(1) 18 to 24
(2) 25 to 34
(3) 35 to 44
(4) 45 to 54
(5) 55 to 64 or
(6) 65 or older
(96) DON’T KNOW
[END INTERVIEW]
(97) REFUSED
[END INTERVIEW]
R_SEX (S2Q6) [READ IF NECESSARY]:
Are you/Is the (AGE) year old] male or female?
(1) MALE
(2) FEMALE
(7) REFUSED
FLG_PROXY
DERIVED. INTERVIEW DONE BY PROXY BECAUSE OF ILLNESS.
(0) INTERVIEW NOT CONDUCTED BY PROXY FOR ILLNESS
(1) INTERVIEW CONDUCTED BY PROXY FOR ILLNESS
FLG_TYPE
DERIVED. EXPECTED INTERVIEW TYPE
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
CURRENT ASTHMA-SAMPLED PERSON INTERVIEW: DATA IN ORIGINAL FIELDS
ASTHMA, NOT CURRENT-SAMPLED PERSON INT: DATA IN ORIGINAL FIELDS
NO ASTHMA-SAMPLED PERSON INTERVIEW: DATA IN ORIGINAL FIELDS
ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE: DATA IN PROXY FIELDS
NO ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE, SAMPLED NEVER
INTERVIEWED: DATA IN PROXY FIELDS
NO ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE, SAMPLED PERSON
INTERVIEWED AT CALLBACK: DATA IN BOTH FIELDS
CURRENT ASTHMA-SAMPLED PERSON & PROXY INTS: DATA IN BOTH FIELDS
ASTHMA, NOT CURRENT-SAMPLED PERSON & PROXY INTS: DATA IN BOTH FIELDS
CURRENT ASTHMA-PROXY INT B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS
ASTHMA, NOT CURRENT-PROXY INT B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS
NO ASTHMA-PROXY INTERVIEW B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS
SAMPLED PERSON OR ASTHMA STATUS NOT DETERMINED
Series 1, No. 46 [ Page 45
PROXYREL (S3Q6B)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(90)
(96)
(97)
What is your relationship to [the (AGE) year old]?
SPOUSE
UNMARRIED PARTNER, BOYFRIEND/GIRLFRIEND
CHILD
GRANDCHILD
MOTHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)
FATHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)
BROTHER/SISTER
GRANDFATHER/GRANDMOTHER
OTHER RELATIVE
FOSTER CHILD
HOUSEMATE/ROOMMATE
ROOMER/BOARDER
OTHER NON-RELATIVE
UNRELATED LEGAL GUARDIAN
DON’T KNOW
REFUSED
RELA_CHLD (S3Q6) [IF R_DOB (S2Q5) > 17, SKIP TO OTH_CHLD (S3Q7).]
What is your relationship to [the (AGE) year old] who lives in this household?
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(96)
(97)
OTH_CHLD (S3Q7)
(0)
(1)
(6)
(7)
MOTHER (STEP, FOSTER, ADOPTIVE) OR FEMALE GUARDIAN
FATHER (STEP, FOSTER, ADOPTIVE) OR MALE GUARDIAN
SISTER OR BROTHER (STEP/FOSTER/HALF/ADOPTIVE)
IN-LAW OF ANY TYPE
AUNT/UNCLE
GRANDPARENT
OTHER FAMILY MEMBER
FRIEND
DON’T KNOW
REFUSED
[IF SAMPLED RESPONDENT IS SAME PERSON WHO ANSWERED R_ASTHMX01, SKIP TO
AGEDGNOS (S3Q8)] {Have you/Has [the (AGE) year old/NAME]} ever been told by a doctor or other
health professional that {you have/he has/she has} asthma?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
AGEDGNOS (S3Q8) [IF OTH_CHLD (S3Q7) = 0, 6, 7 SKIP TO INS1_A).]
How old {were you/was [the (AGE) year old]} when {you were/he or his parent or guardian was/she or her
parent or guardian was} first told by a doctor or other health professional that {you/he/she} had
asthma?
[INTERVIEWER: ENTER 0 IF LESS THAN ONE YEARS OLD]
__ __ __ (ENTER AGE IN YEARS)
(996) DON’T KNOW
(997) REFUSED
CUR_AST2 (S3Q9)
(0)
(1)
(6)
(7)
[IF SAMPLED RESPONDENT IS SAME PERSON WHO ANSWERED CUR_AST (S3Q2), SKIP TO
LAST_MD (S3Q10)] {Do you/Does [the (AGE) year old]} still have asthma?
NO
YES
DON’T KNOW
REFUSED
Section 2. History of Asthma (Symptoms & Episodes)
LAST_MD (S3Q10)
(0)
(1)
(2)
(3)
(4)
(6)
(7)
How long has it been since {you/[the (AGE) year old]/[the (AGE) year old]’s parents or guardians} last
talked to a doctor or other health professional about (your/his/her) asthma?
[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY.]
NEVER
WITHIN THE PAST YEAR
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEARS TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
Page 46 [ Series 1, No. 46
LAST_MED (S3Q11)
(0)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
LASTSYMP (S3Q12)
How long has it been since {you/[the (AGE) year old]} last took asthma medication?
[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY.]
NEVER
LESS THAN ONE DAY AGO
1–6 DAYS AGO
1 WEEK TO LESS THAN 3 MONTHS AGO
3 MONTHS TO LESS THAN 1 YEAR AGO
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEARS TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
Symptoms of asthma include coughing, wheezing, shortness of breath, chest tightness or phlegm
production when {you do not/[the (AGE) year old/NAME] does not} have a cold or respiratory infection.
How long has it been since {you/[the (AGE) year old]} last had any symptoms of asthma?
[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY]
(0)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
NEVER
LESS THAN ONE DAY AGO
1–6 DAYS AGO
1 WEEK TO LESS THAN 3 MONTHS AGO
3 MONTHS TO LESS THAN 1 YEAR AGO
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEARS TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
FLG_ASTHMA DERIVED. SOURCE OF ASTHMA STATUS REPORT
ASTHSTAT
DERIVED. ASTHMA STATUS OF HOUSEHOLD MEMBER
(0) NO, PERSON DOES NOT HAVE ASTHMA
(1) YES, PERSON HAS ASTHMA
LTASTHM
DERIVED. RISK FACTOR FOR LIFETIME ASTHMA PREVALENCE BASED ON BRFSS RULES
(1) NOT AT RISK
(2) AT RISK
(9) DON’T KNOW/NOT SURE OR REFUSED
ASTATUS1
DERIVED. CURRENT ASTHMA STATUS OF HOUSEHOLD MEMBER BASED ON SELF
IDENTIFICATION
(1) PERSON SELF-IDENTIFIED ASTHMA
(0) PERSON DID NOT SELF-IDENTIFY ASTHMA
(6) DON’T KNOW
CASTHMA
DERIVED. RISK FACTOR FOR CURRENT ASTHMA PREVALENCE BASED ON BRFSS RULES
(1) NOT AT RISK
(2) AT RISK
(9) DON’T KNOW/NOT SURE OR REFUSED
ASTHMST
DERIVED. COMPUTED ASTHMA STATUS BASED ON BRFSS RULES
(1)
(2)
(3)
(9)
ASTATUS2
CURRENT
FORMER
NEVER
DON’T KNOW/NOT SURE OR REFUSED
DERIVED. CURRENT ASTHMA STATUS OF HOUSEHOLD MEMBER BASED ON SELF-REPORTED
BEHAVIORS
(1) BEHAVIORS INDICATE ASTHMA
(0) BEHAVIORS DO NOT INDICATE ASTHMA
(6) DON’T KNOW
IF {[CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5},
SKIP TO SECTION 3.
Series 1, No. 46 [ Page 47
ELSE IF CUR_AST (S3Q2) = 1 OR CUR_AST2 (S3Q9) = 1,
CONTINUE.
ELSE IF {[CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
[LAST_MD (S3Q10) = 1, 2 OR
LAST_MED (S3Q11) ≥ 1 AND ≤ 5 OR
LASTSYMP (S3Q12) ≥ 1 AND ≤ 5]},
CONTINUE.
SYMP_30D (S4Q1)
IF LASTSYMP (S3Q12) = 0 OR ≥ 5 AND ≤ 7, SKIP TO SECTION 3.
IF LASTSYMP (S3Q12) = 4, SKIP TO EPIS_INT.
During the past 30 days, how many days did {you/[the (AGE) year old/NAME]} have any symptoms of
asthma?
__ __DAYS (1–29)
(0) NO SYMPTOMS IN THE PAST 30 DAYS
(30) EVERY DAY
(96) DON’T KNOW
(97) REFUSED
DUR_30D (S4Q2)
(0)
(1)
(6)
(7)
[SKIP TO ASLEEP30 (S4Q3)]
[SKIP TO EPIS_INT]
[SKIP TO ASLEEP30 (S4Q3)]
[SKIP TO ASLEEP30 (S4Q3)]
{Do you/Does [the (AGE) year old/NAME]} have symptoms all the time?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘ALL THE TIME’’ MEANS SYMPTOMS THAT CONTINUE THROUGHOUT THE DAY. IT
DOES NOT MEAN SYMPTOMS FOR A LITTLE WHILE EACH DAY.
ASLEEP30 (S4Q3)
During the past 30 days, on how many days did symptoms of asthma make it difficult for {you/[the (AGE)
year old/NAME]} to stay asleep?
__ __ DAYS/NIGHTS
(0) NONE
(96) DON’T KNOW
(97) REFUSED
SYMPFREE (S4Q4)
[IF SYMP_30D (S4Q1) = 30, SKIP TO EPIS_INT.] During the past two weeks, on how many days {were
you/was [the (AGE) year old/NAME]} completely symptom-free, that is no coughing, wheezing, or other
symptoms of asthma?
__ __ NUMBER OF DAYS
(96) DON’T KNOW
(97) REFUSED
INTRODUCTORY STATEMENT
Asthma attacks, sometimes called episodes, refer to periods of worsening asthma symptoms that make {you limit
your/limit [the (AGE) year old/NAME]’s} activity more than [you usually do/(he/she) usually does], or make
(you/him/her) seek medical care. [CONTINUE]
EPIS_12M (S4Q5)
(0)
(1)
(6)
(7)
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], {have you/has
[the (AGE) year old/NAME]} had an episode of asthma or an asthma attack?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
HELP SCREEN: (ADD TO ALL QUESTIONS THAT REFER TO ‘‘ASTHMA ATTACKS OR EPISODES’’)
Asthma attacks, sometimes called episodes, refer to periods of worsening asthma symptoms that make {you limit
your/limit [the (AGE) year old/NAME]’s} activity more than [you usually do/(he/she) usually does], or make
(you/him/her) seek medical care.
EPIS_TP (S4Q6)
__
(0)
(996)
(997)
During the past 3 months, how many asthma episodes or attacks {have you/has [the (AGE) year
old/NAME]} had?
ATTACKS OR EPISODES DURING PAST 3 MONTHS
NONE
DON’T KNOW
REFUSED
Page 48 [ Series 1, No. 46
DUR_ASTH (S4Q7)
How long did {your/[the (AGE) year old/NAME]’s} most recent asthma episode or attack last?
_ _ENTER AMOUNT
(96) DON’T KNOW
(97) REFUSED
DUR2ASTH (S4Q8)
(1)
(2)
(3)
(4)
(6)
(7)
COMPASTH (S4Q9)
(1)
(2)
(3)
(4)
(6)
(7)
[SKIP TO COMPASTH (S4Q9)]
[SKIP TO COMPASTH (S4Q9)]
ENTER PERIOD
MINUTES
HOURS
DAYS
WEEKS
DON’T KNOW
REFUSED
Compared with other episodes or attacks, was this most recent attack shorter, longer, or about the
same?
SHORTER
LONGER
ABOUT THE SAME
THE MOST RECENT ATTACK WAS ACTUALLY THE FIRST ATTACK
DON’T KNOW
REFUSED
Section 3. Health Care Utilization
INS1 (S5Q1_A)
{Do you/[Does the (AGE) year old/NAME]} have any kind of health care coverage, including health insurance,
prepaid plans such as HMOs, or government plans such as Medicare?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INS2 (S5Q1_B)]
IF (A) INS1 (S5Q1_A) = 0, 6, 7 OR
(B) R_ASTHMX01 = 0, 6, 7 OR S3Q7 = 0, 6, 7
(C) {[CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5},
SKIP TO SECTION 5.
ELSE IF INS1 (S5Q1_A) = 1, CONTINUE TO INS2 (S5Q1_B).
ELSE SKIP TO NER_TIME (S5Q1).
INS2 (S5Q1_B) [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], was there any time
that {you/[the (AGE) year old/NAME]} did not have any health insurance or coverage?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
IF (A) (R_ASTHMX01 = 0, 6, 7 OR S3Q7 = 0, 6, 7) OR
(B) {[CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5},
SKIP TO SECTION 5.
ELSE SKIP TO NER_TIME (S5Q1).
NER_TIME (S5Q1) [IF LAST_MD (S3Q10) = 0, 2, 3, 4, SKIP TO MISS_DAY (S5Q9).] [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since
birth’’/ELSE FILL: ‘‘During the past 12 months’’], how many times did {you/[the (AGE) year old/NAME]}
see a doctor or other health professional for a routine checkup for (your/his/her) asthma?
_ _ _ ENTER NUMBER
(0) NONE
(996) DON’T KNOW
(997) REFUSED
Series 1, No. 46 [ Page 49
ER_VISIT (S5Q2) [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], {have you/has [the
(AGE) year old/NAME]} had to visit an emergency room or urgent care center because of (your/his/her)
asthma?
(0)
(1)
(6)
(7)
ER_TIMES (S5Q3)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO URG_TIME (S5Q4)]
[SKIP TO URG_TIME (S5Q4)]
[SKIP TO URG_TIME (S5Q4)]
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], how many times
did {you/[the (AGE) year old/NAME]} visit an emergency room or urgent care center because of (your/his/
her) asthma?
_ _ _ ENTER NUMBER
(996) DON’T KNOW
(997) REFUSED
URG_TIME (S5Q4)
[IF ER_TIMES (S5Q3) > 0, INSERT: ‘‘Besides those emergency room or urgent care center visits,’’] [IF
R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], how many times did
{you/[the (AGE) year old/NAME]} see a doctor or other health professional for urgent treatment of
worsening asthma symptoms or an asthma episode or attack?
___
(0)
(996)
(997)
HOSP_VST (S5Q5)
(0)
(1)
(6)
(7)
HOSPTIME (S5Q6)
ENTER NUMBER
NONE
DON’T KNOW
REFUSED
[IF LASTSYMP (S3Q12) = 0 OR > 5 AND < 7, SKIP TO MISS_DAY (S5Q9).] ‘‘Since birth’’/ELSE FILL:
‘‘During the past 12 months,’’ that is since (1 YEAR AGO TODAY)], {have you/has [the
(AGE) year old/NAME]} had to stay overnight in a hospital because of (your/his/her) asthma? Do not
include an overnight stay in the emergency room.
NO
YES
DON’T KNOW
REFUSED
[SKIP TO MISS_DAY (S5Q9)]
[SKIP TO MISS_DAY (S5Q9)]
[SKIP TO MISS_DAY (S5Q9)]
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], how many
different times did {you/[the (AGE) year old/NAME]} stay in any hospital overnight or longer because of
(your/his/her) asthma?
_ _ _ TIMES
(996) DON’T KNOW
(997) REFUSED
HOSPPLAN (S5Q8)
(0)
(1)
(6)
(7)
The last time {you/[the (AGE) year old/NAME]} left the hospital, did a health professional talk with
{you/(AGE) year old/NAME] or [the (AGE) year old/NAME]’s parents or guardians} about how to better
control (your/his/her) asthma to prevent serious episodes or attacks and hospitalizations in the future?
NO
YES
DON’T KNOW
REFUSED
[SKIP THIS QUESTION IF INTERVIEW IS FOR SAMPLED CHILD (S2Q5 < 18).]
MISS_DAY (S5Q9) During the past 12 months, how many days were you unable to work or carry out your usual activities
because of your asthma?
_ _ _ ENTER NUMBER DAYS
(0) ZERO
(996) DON’T KNOW
(997) REFUSED
Page 50 [ Series 1, No. 46
[SKIP THIS QUESTION IF INTERVIEW IS FOR SAMPLED ADULT (S2Q > 17).]
[FOR CHILDREN 0–4, INSERT ‘‘DAYCARE OR PRESCHOOL’’ IN FILL.
FOR CHILDREN 5–13, INSERT ‘‘SCHOOL’’ IN FILL.
FOR CHILDREN 14–17, INSERT ‘‘SCHOOL OR WORK’’ IN FILL.]
MISS_SCH (S5Q11)
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months,’’ that is since (1
YEAR AGO TODAY)] about how many days of (daycare or preschool/school/school or work) did [the
(AGE) year old/NAME] miss because of (his/her) asthma?
___
(0)
(994)
(995)
(996)
(997)
ACT_DAYS (S5Q12)
(1)
(2)
(3)
(4)
(6)
(7)
ENTER NUMBER
ZERO
CHILD DID NOT GO TO SCHOOL IN PAST 12 MONTHS
HOME SCHOOLED
DON’T KNOW
REFUSED THIS QUESTION
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth’’/ELSE FILL: ‘‘During the past 12 months’’], would you say
{you/[the (AGE) year old/NAME]} limited (your/his/her) usual activities due to asthma not at all, a little, a
moderate amount, or a lot?
NOT AT ALL
A LITTLE
A MODERATE AMOUNT
A LOT
DON’T KNOW
REFUSED
Section 4. Knowledge of Asthma/Management Plan
TCH_SIGN (S6Q1)
Has a doctor or other health professional ever taught {you/(AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian}
a. How to recognize early signs or symptoms of an asthma episode?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
TCH_RESP (S6Q2)
Has a doctor or other health professional ever taught {you/(AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian}
b. What to do during an asthma episode or attack?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP IF R_DOB (S2Q5) < 5 YEARS OLD.]
TCH_MON (S6Q3)
Has a doctor or other health professional ever taught {you/(AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian}
c. How to use a peak flow meter, a device that measures how much air you can blow out of your lungs, to
adjust daily medications?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 51
MGT_PLAN (S6Q4)
(0)
(1)
(6)
(7)
MGT_CLAS (S6Q5)
(0)
(1)
(6)
(7)
An asthma management plan is a printed form that tells when to change the amount or type of medicine,
when to call the doctor for advice, and when to go to the emergency room. Has a doctor or other health
professional EVER given {you/(AGE) year old/NAME] or [the (AGE) year old/NAME]’s parent or
guardian} an asthma management plan?
[READ IF NECESSARY: Include nurses and asthma educators]
NO
YES
DON’T KNOW
REFUSED
Have {you/(AGE) year old/NAME] or [the (AGE) year old/NAME]’s parent or guardian}, ever taken a
course or class on how to manage (your/his/her) asthma?
NO
YES
DON’T KNOW
REFUSED
Section 5. Modifications to Environment
IF R_ASTHMX01 = 0, 6, 7 OR S3Q7 = 0, 6, 7,
ASK HH_INT THROUGH S_INSIDE (S7Q10), CIGARETS (S7Q18) THROUGH EMP_STAT (S7Q20),
UNEMP_R (S7Q22). THEN SKIP TO SECTION 7.
ELSE, IF {[CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5},
ASK HH_INT THROUGH S_INSIDE (S7Q10), CIGARETS (S7Q18) THROUGH UNEMP_R (S7Q22), THEN
SKIP TO SECTION 6.
ELSE, CONTINUE.
INTRODUCTORY STATEMENT
READ: The following questions are about {your/[the (AGE) year old/NAME]’s} household and living
environment. (IF R_ASTHMX01 = 1 OR S3Q7 = 1) I will be asking about various things that may be related to
experiencing asthma symptoms. [CONTINUE]
AIRCLEANER (S7Q1) Is an air cleaner or purifier regularly used inside your home?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
DEHUMID (S7Q2) Is a dehumidifier regularly used to reduce moisture inside your home?
(0)
(1)
(6)
(7)
KITC_FAN (S7Q3)
(0)
(1)
(6)
(7)
COOK_GAS (S7Q4)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?
NO
YES
DON’T KNOW
REFUSED
Is gas used for cooking?
NO
YES
DON’T KNOW
REFUSED
Page 52 [ Series 1, No. 46
ENV_MOLD (S7Q5)
In the past 30 days, has anyone seen or smelled mold or a musty odor inside your home? Do not include
mold on food.
NO
YES
DON’T KNOW
REFUSED
(0)
(1)
(6)
(7)
ENV_PETS (S7Q6)
Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets
that arekept inside?
NO
YES
DON’T KNOW
REFUSED
(0)
(1)
(6)
(7)
C_ROACH (S7Q7)
(0)
(1)
(6)
(7)
In the past 30 days, has anyone seen cockroaches inside your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: Studies have shown that cockroaches are a leading cause of asthma in children that live in
urban areas. Cockroach droppings and carcasses can cause children to experience symptoms of asthma.
WOOD_STOVE (S7Q8)
(0)
(1)
(6)
(7)
Is a fireplace or wood burning stove used in your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: OCCASIONAL USE SHOULD BE CODED AS ‘‘YES.’’
GAS_STOVE (S7Q9)
(0)
(1)
(6)
(7)
Are unvented gas logs, an unvented gas fireplace, or an unvented gas stove used in your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Unvented’’ means no chimney.
S_INSIDE (S7Q10)
(0)
(1)
(6)
(7)
In the past week, has anyone smoked inside your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Smoked’’ means ‘‘anything.’’
MOD_ENV (S7Q11)
FOR ADULT INTERVIEW, READ:
[FILL ONLY IF QUESTIONS HH_INT THROUGH S_INSIDE WERE ASKED OF THIS RESPONDENT]:
Now, back to questions specifically about you. Has a health professional ever advised you to change
things in your home, school, or work to improve your asthma?
FOR CHILD INTERVIEW, READ:
[FILL ONLY IF QUESTIONS HH_INT THROUGH S_INSIDE WERE ASKED OF THIS RESPONDENT]: Now,
back to questions specifically about [the (AGE) year old/NAME]. Has a health professional ever advised you to
change things in [the (AGE) year old/NAME]’s home, school, or work to improve [the (AGE) year old/NAME]’s
asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 53
MATTRESS (S7Q12)
(0)
(1)
(6)
(7)
E_PILLOW (S7Q13)
(0)
(1)
(6)
(7)
{Do you/Does [the (AGE) year old/NAME]} use a mattress cover that is made especially for controlling
dust mites?
NO
YES
DON’T KNOW
REFUSED
{Do you/Does [the (AGE) year old/NAME]} use a pillow cover that is made especially for controlling dust
mites?
NO
YES
DON’T KNOW
REFUSED
CARPET (S7Q14) Do you have carpeting or rugs in {your/[the (AGE) year old/NAME]’s} bedroom?
(0) NO
(1) YES
(6) DON’T KNOW
(7) REFUSED
HOTWATER (S7Q15) Are {your/[the (AGE) year old/NAME]’s} sheets and pillowcases washed in cold, warm, or hot water?
(1) COLD
(2) WARM
(3) HOT
(6) DON’T KNOW
(7) REFUSED
BATH_FAN (S7Q16)
(0)
(1)
(6)
(7)
In {your/[the (AGE) year old/NAME]’s} bathroom, {do you/does [the (AGE) year old/NAME]} regularly
use an exhaust fan that vents to the outside?
NO OR ‘‘NO FAN’’
YES
DON’T KNOW
REFUSED
HELP SCREEN: IF RESPONDENT INDICATES THEY HAVE MORE THAN ONE BATHROOM, THIS
QUESTION REFERS TO THE BATHROOM THEY USE MOST FREQUENTLY FOR SHOWERING AND
BATHING.
[SKIP THIS QUESTION IF ENV_PETS (S7Q6) = 0, 6, 7.]
PETBEDRM (S7Q17)
(0)
(1)
(2)
(6)
(7)
Is the pet allowed in {your/[the (AGE) year old/NAME]’s} bedroom?
NO
YES
SOME ARE/SOME AREN’T
DON’T KNOW
REFUSED
SKIP TO SECTION 6 IF INTERVIEW IS FOR SAMPLED CHILD (R_DOB/S2Q5 <18).
CIGARETS (S7Q18)
(0)
(1)
(6)
(7)
CIG_FREQ (S7Q19)
(1)
(2)
(3)
(6)
(7)
Have you smoked at least 100 cigarettes in your entire life?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO EMP_STAT (S7Q20)]
[SKIP TO EMP_STAT (S7Q20)]
[SKIP TO EMP_STAT (S7Q20)]
Do you now smoke cigarettes every day, some days, or not at all?
EVERY DAY
SOME DAYS
NOT AT ALL
DON’T KNOW
REFUSED
Page 54 [ Series 1, No. 46
EMP_STAT (S7Q20)
[IF R_ASTHMX01 = 1 OR S3Q7 = 1:] We are interested in things that affect asthma in the workplace.
However, first I’d like to ask how you would describe {your/[the (AGE) year old/ NAME]’s} current
employment status. Would you say {you/[the (AGE) year old/NAME]} is . . .
(1)
(2)
(3)
(6)
(7)
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
DON’T KNOW
REFUSED
WORKENV2 (S7Q21)
[IF R_ASTHMX01 = 0, 6, 7 OR S3Q7 = 0, 6, 7, SKIP TO UNEMP_R (S7Q22).] Was your asthma
caused or made worse by chemicals, smoke, fumes, or dust in any job you ever had?
NO
YES
NEVER BEEN EMPLOYED
DON’T KNOW
REFUSED
(0)
(1)
(2)
(6)
(7)
UNEMP_R (S7Q22)
[IF EMP_STAT (S7Q20) = 1 OR 2, SKIP TO OTC (S8Q1).] What is the main reason you are not
employed?
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(96)
(97)
KEEPING HOUSE
GOING TO SCHOOL
RETIRED
DISABLED
UNABLE TO WORK FOR OTHER HEALTH REASONS
LOOKING FOR WORK
LAID OFF
OTHER
DON’T KNOW
REFUSED
Section 6. Medications
IF LAST_MED (S3Q11) = 0, SKIP TO SECTION 7.
IF [CUR_AST (S3Q2) = 0, 6, 7 OR CUR_AST2 (S3Q9) = 0, 6, 7] AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LASTSYMP (S3Q12) = 0 OR > 5 AND
LAST_MED (S3Q11) = 6 OR 7,
ASK OTC (S8Q1), INHALERE (S8Q2), INHALERH (S8Q3), THEN SKIP TO SECTION 7.
OTC (S8Q1)
Over-the-counter medication can be bought without a doctor’s order. {Have you/Has [the (AGE) year old/
NAME]} ever used over-the-counter medication for (your/his/her) asthma?
(0)
(1)
(6)
(7)
INHALERE (S8Q2)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
{Have you/Has [the (AGE) year old/NAME]} ever used a prescription inhaler?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SCR_MED1 (S8Q4)]
[SKIP TO SCR_MED1 (S8Q4)]
[SKIP TO SCR_MED1 (S8Q4)]
Series 1, No. 46 [ Page 55
INHALERH (S8Q3)
(0)
(1)
(6)
(7)
Did a health professional show {you/the (AGE) year old/NAME] or [the (AGE) year old/NAME]’s parents
or guardians} how to use the inhaler?
NO
YES
DON’T KNOW
REFUSED
SCR_MED1 (S8Q4)
[IF LAST_MED (S3Q11) = 4, 5, 6, 7, 96, OR 97, SKIP TO SECTION 7.] Now I am going to ask
questions about specific prescription medications {you /[the (AGE) year old/NAME]} may have taken for
asthma in the past 3 months. I will be asking for the names, amount, and how often {you take/[the (AGE)
year old/NAME] takes} each medicine. I will ask separately about medication taken in various forms: pill or
syrup, inhaler, and Nebulizer.
It may help to get {your/[the (AGE) year old/NAME]’s} medicines so you can read the labels. Are {your/[the
(AGE) year old/NAME]’s} asthma medicines handy?
(0)
(1)
(2)
(6)
(7)
SCR_MED2 (S8Q5)
(0)
(1)
(6)
(7)
SCR_MED3 (S8Q6)
(0)
(1)
(2)
(6)
(7)
INH_SCR (S8Q7)
(0)
(1)
(6)
(7)
NO
YES
RESPONDENT KNOWS THE MEDS
DON’T KNOW
REFUSED
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
Can you please go get the asthma medicines while I wait on the phone?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
Am I correct that you have all the medications?
NO
YES I HAVE ALL THE MEDICATIONS
YES I HAVE SOME OF THE MEDICATIONS BUT NOT ALL
DON’T KNOW
REFUSED
In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription asthma
medicine using an inhaler?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO PILLS (S8Q27)]
[SKIP TO PILLS (S8Q27)]
[SKIP TO PILLS (S8Q27)]
Page 56 [ Series 1, No. 46
INH_MEDS (S8Q8_01 to S8Q8_34)
In the past 3 months, what medications did {you/[the (AGE) year old/NAME]} take by inhaler? [MARK ALL
THAT APPLY. PROBE: Any other medications?]
Variable Name
INH_MEDX01 (S8Q8_01)
INH_MEDX02 (S8Q8_02)
INH_MEDX03 (S8Q8_03)
INH_MEDX04 (S8Q8_04)
INH_MEDX05 (S8Q8_05)
INH_MEDX06 (S8Q8_06)
INH_MEDX07 (S8Q8_07)
INH_MEDX08 (S8Q8_08)
INH_MEDX09 (S8Q8_09)
INH_MEDX10 (S8Q8_10)
INH_MEDX11 (S8Q8_11)
INH_MEDX12 (S8Q8_12)
INH_MEDX13 (S8Q8_13)
INH_MEDX14 (S8Q8_14)
INH_MEDX15 (S8Q8_15)
INH_MEDX16 (S8Q8_16)
INH_MEDX17 (S8Q8_17)
INH_MEDX18 (S8Q8_18)
INH_MEDX19 (S8Q8_19)
INH_MEDX20 (S8Q8_20)
INH_MEDX21 (S8Q8_21)
INH_MEDX22 (S8Q8_22)
INH_MEDX23 (S8Q8_23)
INH_MEDX24 (S8Q8_24)
INH_MEDX25 (S8Q8_25)
INH_MEDX26 (S8Q8_26)
INH_MEDX27 (S8Q8_27)
INH_MEDX28 (S8Q8_28)
INH_MEDX29 (S8Q8_29)
INH_MEDX30 (S8Q8_30)
INH_MEDX31 (S8Q8_31)
INH_MEDX32 (S8Q8_32)
INH_MEDX33 (S8Q8_33)
INH_MEDX34 (S8Q8_34)
Brand Name
Type (not shown in CATI)
Advair
Aerobid
Corticosteroids
Albuterol
Beta 2 agonist
Alupent
Beta 2 agonist
Atrovent
Anti-inflammatories
Azmacort
Corticosteroids
Beclomethasone dipropionate
Corticosteroids
Beclovent
Corticosteroids
Bitolterol
Beta 2 agonist
Brethaire
Beta 2 agonist
Budesonide
Corticosteroids
Combivent
Cromolyn
Anti-inflammatories
Flovent
Inhaled corticosteroid
Flovent Rotadisk
Inhaled corticosteroid
Flunisolide
Corticosteroids
Fluticasone
Inhaled corticosteroid
Intal
Anti-inflammatories
Ipratropium Bromide
Anti-inflammatories
Maxair
Beta 2 agonist
Metaproteronol
Beta 2 agonist
Nedocromil
Anti-inflammatories
Pirbuterol
Beta 2 agonist
Proventil
Beta 2 agonist
Pulmicort Turbuhaler
Corticosteroids
Salmeterol
Corticosteroids (long lasting)
Serevent
Beta 2 agonist (long lasting)
Terbutaline
Beta 2 agonist
Tilade
Anti-inflammatories
Tornalate
Beta 2 agonist
Triamcinolone acetonide
Corticosteroids
Vanceril
Corticosteroids
Ventolin
Beta 2 agonist
Other, please specify
[SKIP TO OTH_I1 (S8Q8_34A)]
IF ANY ANSWER SELECTED FROM INH_MEDX01 (S8Q8_01)–INH_MEDX33 (S8Q8_33), SKIP TO ILP01
(S8Q16_nn).
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO REC_MED1]
[SKIP TO PILLS (S8Q27)]
OTH_I1 (S8Q8_34A)
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
______________________ ENTER TEXT
INTRODUCTORY STATEMENT
READ: I’m going to read a list of medicines to see if you recognize the name of any of the medications {you
have/[CHILD’S NAME] has} taken. Please let me know if you hear the name. [CONTINUE]
Series 1, No. 46 [ Page 57
DK1INHLR (S8Q9)
(0)
(1)
(6)
(7)
DK2INHLR (S8Q10)
(0)
(1)
(6)
(7)
DK3INHLR (S8Q11)
(0)
(1)
(6)
(7)
DK4INHLR (S8Q12)
(0)
(1)
(6)
(7)
DK5INHLR (S8Q13)
(0)
(1)
(6)
(7)
DK6INHLR (S8Q14)
(0)
(1)
(6)
(7)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take Flovent or Flovent Rotadisk using an
inhaler?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Beclovent, Vanceril, Beclomethasone dipropionate,
Pulmicort Turbuhaler, Budesonide,
Aerobid, Flunisolide,
Azmacort or Triamcinolone acetonide?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Ventolin, Proventil, Albuterol,
Alupent, Metaproteronol,
Tornalate, Bitolterol,
Maxair, Pirbuterol
Brethaire, Terbutaline
Serevent?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Intal, Cromolyn,
Tilade, or Nedocromil?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Atrovent or Ipratropium Bromide?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication by inhaler that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO DK7INHLR (S8Q15)]
IF DK6INHLR (S8Q14) = 1, CONTINUE. ALL OTHERS, SKIP TO ILP01 (S8Q16_nn).
Page 58 [ Series 1, No. 46
DK7INHLR (S8Q15)
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
REPEAT ILP01 (S8Q16_nn)–ILP11 (S8Q26_nn) FOR EACH MEDICINE REPORTED IN INH_MEDS
(S8Q8_nn), OR IF AN ANSWER OF (1) ‘‘YES’’ IS GIVEN FOR ANY ITEM IN DK1INHLR (S8Q9)
THROUGH DK7INHLR (S8Q15). IF AN ANSWER OF (1) ‘‘YES’’ IS PROVIDED DURING QUESTIONS
DK1INHLR (S8Q9) THROUGH DK6INHLR (S8Q14), USE THE PHRASE ‘‘THIS MEDICATION’’ FOR FILL
‘‘[MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]’’ FOR QUESTIONS ILP01 (S8Q16_nn) THROUGH
ILP11 (S8Q26_nn).
ILP01 (S8Q16_01 to S8Q16_34)
How long {have you/has [the (AGE) year old/NAME]} been taking [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES]? Would you say less than 6 months, 6 months to 1 year, or longer than 1 year?
(1)
(2)
(3)
(6)
(7)
Less than 6 months
6 months to 1 year
Longer than 1 year
DON’T KNOW
REFUSED
ILP02 (S8Q17_01 to S8Q17_34)
A spacer is a small attachment for an inhaler that makes it easier to use. {Do you/Does [the (AGE) year
old/NAME]} use a spacer with [MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: A spacer is a device that attaches to a metered dose inhaler. It holds the medicine in its
chamber long enough for you to inhale it in one or two slow, deep breaths. The spacer makes it easy to take the
medicines the right way, especially for young children.
ASK IF INH_MEDS (S8Q8_nn) = 03, 04, 09, 10, 20, 21, 23, 24, 28, 30, 33, OR DK3INHLR
(S8Q11) = 1; ELSE, SKIP TO ILP06 (S8Q21_nn).
ILP03 (S8Q18_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES] when {you/he/she had} an asthma episode or attack?
(0)
(1)
(2)
(6)
(7)
NO
YES
NO ATTACK IN PAST 3 MONTHS
DON’T KNOW
REFUSED
ILP04 (S8Q19_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
[IF THE AGE OF THE CHILD IS LESS THAN 6 YEARS OLD (S2Q5 < 6), SKIP TO ILP05 (S8Q20_nn).] In
the past 3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES] before exercising?
(0)
(1)
(2)
(6)
(7)
NO
YES
DIDN’T EXERCISE IN PAST 3 MONTHS
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 59
ILP05
(S8Q20_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES] on a regular schedule everyday?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
ASK IF INH_MEDS (S8Q8_nn) = 14, 15, 17, OR DK1_INHLR (S8Q9) = 1;
ELSE SKIP TO ILP07 (S8Q22_nn).
ILP06 (S8Q21_14, _15, _17, _34)
Is the dosage 44, 50, 100, 110, 220, or 250 micrograms for the Flovent?
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
ILP07
44 MICROGRAMS
50 MICROGRAMS
100 MICROGRAMS
110 MICROGRAMS
220 MICROGRAMS
250 MICROGRAMS
TOOK MORE THAN 1 IN PAST 3 MONTHS
DON’T KNOW
REFUSED
(S8Q22_01 to S8Q22_34)
On average, how many puffs {Do you/does [the (AGE) year old/NAME]} take each time {you use/he uses/she
uses} [MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]?
__ __ PUFFS EACH TIME
(96) DON’T KNOW
(97) REFUSED
INTERVIEWER: PROBE FOR NUMBER OF PUFFS IF RANGE IS GIVEN.
ILP09 (S8Q24_01 to S8Q24_34)
How many times per day or per week {do you/does [the (AGE) year old/NAME]} use [MEDICINE FROM
INH_MEDS SERIES]?
__ __ __ TIMES
(994) LESS OFTEN THAN ONCE A WEEK
(996) DON’T KNOW
(997) REFUSED
[SKIP TO ILP11 (S8Q26_nn)]
[SKIP TO ILP11 (S8Q26_nn)]
[SKIP TO ILP11 (S8Q26_nn)]
ILP10 (S8Q25_01 to S8Q25_34)
ENTER PERIOD
(1)
(2)
(6)
(7)
PER DAY
PER WEEK
DON’T KNOW
REFUSED
ILP11 (S8Q26_01 to S8Q26_34)
How many full canisters of this inhaler {have you /has [the (AGE) year old/NAME]} used in the past 3 months?
[INTERVIEWER: IF RESPONDENT USED LESS THAN ONE CANISTER IN THE PAST 3 MONTHS,
CODE IT AS ‘00’]
___ CANISTERS
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: IF RESPONDENT INDICATES HE/SHE HAS MULTIPLE CANISTERS, (I.E., ONE IN THE
CAR, ONE IN PURSE, ETC.) ASK THE RESPONDENT TO ESTIMATE HOW MANY CANISTERS HE/SHE
USED.
Page 60 [ Series 1, No. 46
PILLS (S8Q27)
In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken any medicine in pill form for
[your/his/her] asthma?
(0) NO
[SKIP TO SYRUP (S8Q38)]
(1) YES
(6) DON’T KNOW
[SKIP TO SYRUP (S8Q38)]
(7) REFUSED
[SKIP TO SYRUP (S8Q38)]
PILLS_MD (S8Q28_01 to S8Q28_48)
What medications {Do you/does [the (AGE) year old/NAME]} take in pill form?
[MARK ALL THAT APPLY. PROBE: Any other medications?]
VARIABLE NAMES
PILLS_MX01 (S8Q28_01)
PILLS_MX02 (S8Q28_02)
PILLS_MX03 (S8Q28_03)
PILLS_MX04 (S8Q28_04)
PILLS_MX05 (S8Q28_05)
PILLS_MX06 (S8Q28_06)
PILLS_MX07 (S8Q28_07)
PILLS_MX08 (S8Q28_08)
PILLS_MX09 (S8Q28_09)
PILLS_MX10 (S8Q28_10)
PILLS_MX11 (S8Q28_11)
PILLS_MX12 (S8Q28_12)
PILLS_MX13 (S8Q28_13)
PILLS_MX14 (S8Q28_14)
PILLS_MX15 (S8Q28_15)
PILLS_MX16 (S8Q28_16)
PILLS_MX17 (S8Q28_17)
PILLS_MX18 (S8Q28_18)
PILLS_MX19 (S8Q28_19)
PILLS_MX20 (S8Q28_20)
PILLS_MX21 (S8Q28_21)
PILLS_MX22 (S8Q28_22)
PILLS_MX23 (S8Q28_23)
PILLS_MX24 (S8Q28_24)
PILLS_MX25 (S8Q28_25)
PILLS_MX26 (S8Q28_26)
PILLS_MX27 (S8Q28_27)
PILLS_MX28 (S8Q28_28)
PILLS_MX29 (S8Q28_29)
PILLS_MX30 (S8Q28_30)
PILLS_MX31 (S8Q28_31)
PILLS_MX32 (S8Q28_32)
PILLS_MX33 (S8Q28_33)
PILLS_MX34 (S8Q28_34)
PILLS_MX35 (S8Q28_35)
PILLS_MX36 (S8Q28_36)
PILLS_MX37 (S8Q28_37)
PILLS_MX38 (S8Q28_38)
PILLS_MX39 (S8Q28_39)
PILLS_MX40 (S8Q28_40)
PILLS_MX41 (S8Q28_41)
PILLS_MX42 (S8Q28_42)
PILLS_MX43 (S8Q28_43)
PILLS_MX44 (S8Q28_44)
PILLS_MX45 (S8Q28_45)
PILLS_MX46 (S8Q28_46)
PILLS_MX47 (S8Q28_47)
PILLS_MX48 (S8Q28_48)
Medication
Accolate
Aerolate
Albuterol
Alupent
Choledyl
Cromolyn
Deltasone
Elixophyllin
Intal
Marax
Medrol
Metaprel
Metaproteronol
Methylpredinisolone
Montelukast
Nedocromil
Pediapred
Prednisolone
Prednisone
Prelone
Proventil
Quibron
Respid
Singulair
Slo-phyllin
Slo-bid
Sustaire
Theo-24
Theobid
Theochron
Theoclear
Theodur
Theo-Dur
Theolair
Theophylline
Theo-Sav
Theospan
Theox
Tilade
T-Phyl
Unidur
Uniphyl
Ventolin
Volmax
Zafirlukast
Zileuton
Zyflo Filmtab
Other, please specify:
Type (not shown in CATI)
Leukotriene modifiers
Methylxanthines
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Methylxanthines
Anti-Inflammatories
Corticosteriods
Methylxanthines
Anti-Inflammatories
Methylxanthines
Corticosteriods
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Corticosteriods
Leukotriene modifiers
Corticosteriods
Corticosteriods
Corticosteriods
Corticosteriods
Corticosteriods
Beta 2 agonist – Rescue bronchodilators
Methylxanthines
Methylxanthines
Leukotriene modifiers
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Corticosteriods
Methylxanthines
Methylxanthines
Methylxanthines
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Leukotriene modifiers
Leukotriene modifiers
Leukotriene modifiers
[SKIP TO OTH_P1 (S8Q29)]
Series 1, No. 46 [ Page 61
IF ANY ANSWER SELECTED FROM PILLS_MX01 (S8Q28_01)–PILLS_MX47 (S8Q28_47), SKIP TO PILLX (S8Q37_nn).
(0) NO
(1) YES
(6) DON’T KNOW
[SKIP TO REC_MED2]
(7) REFUSED
[SKIP TO SYRUP (S8Q38)]
OTH_P1 (S8Q29) ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
INTRODUCTORY STATEMENT
READ: I’m going to read a list of medicines to see if you recognize the name of the medications {you
have/[CHILD’S NAME] has} taken within the past 3 months. If you recognize any that were taken, please let
me know. [CONTINUE]
DK1_PILL (S8Q30)
(0)
(1)
(6)
(7)
DK2_PILL (S8Q31)
(0)
(1)
(6)
(7)
DK3_PILL (S8Q32)
(0)
(1)
(6)
(7)
DK4_PILL (S8Q33)
(0)
(1)
(6)
(7)
DK5_PILL (S8Q34)
(0)
(1)
(6)
(7)
Did {you/[the (AGE) year old/NAME]} take:
Accolate or Zafirlukast
Zyflo Filmtab or Zileuton
Singulair or Montelukast?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Intal or Cromolyn
Tilade or Nedocromil?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Medrol, Methylpredinisolone,
Deltasone, Prednisone,
Pediapred,
Prelone, or Prednisolone?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Proventil, Ventolin, Volmax, or Albuterol
Alupent, Metaprel, or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Theophylline, Elixophyllin, Theo-Dur, Choledyl, Theo-Sav, Theospan, Theoclear, T-Phyl, Theodur, Unidur,
Uniphyl, Aerolate, Theox, Marax, Theobid, Quibron, Theo-24, Sustaire, Slo-phyllin, Slo-bid, Respid,
Theochron, or Theolair?
NO
YES
DON’T KNOW
REFUSED
Page 62 [ Series 1, No. 46
DK6_PILL (S8Q35)
Did {you/[the (AGE) year old/NAME]} take a medication in pill form that we have not mentioned?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
DK7_PILL (S8Q36)
[SKIP TO PILLX (S8Q37_nn)]
[SKIP TO DK7_PILL (S8Q36)]
[SKIP TO PILLX (S8Q37_nn)]
[SKIP TO PILLX (S8Q37_nn)]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
REPEAT PILLX (S8Q37_nn) FOR EACH PILL REPORTED IN PILLS_MD (S8Q28_nn), OR IF AN ANSWER
OF (1) ‘‘YES’’ IS GIVEN FOR QUESTIONS DK1_PILL (S8Q30) THROUGH DK6_PILL (S8Q35). IF AN
ANSWER OF (1) ‘‘YES’’ IS PROVIDED DURING QUESTIONS DK1_PILL (S8Q30) THROUGH DK6_PILL
(S8Q35), USE THE PHRASE ‘‘THIS MEDICATION’’ FOR FILL ‘‘[MEDICATION LISTED IN PILLS_MD
(S8Q28_nn)]’’ FOR QUESTION PILLX (S8Q37_nn).
PILLX (S8Q37_01 TO S8Q37_48)
How long {have you/has [the (AGE) year old/NAME]} been taking [MEDICATION LISTED IN PILLS_MD
(S8Q28_nn)]?
SYRUP (S8Q38)
(1)
(2)
(3)
(6)
(7)
LESS THAN 6 MONTHS
6 MONTHS TO 1 YEAR
LONGER THAN 1 YEAR
DON’T KNOW
REFUSED
In
(0)
(1)
(6)
(7)
the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription medicine in syrup form?
NO
[SKIP TO NEB_SCR (S8Q47)]
YES
DON’T KNOW
[SKIP TO NEB_SCR (S8Q47)]
REFUSED
[SKIP TO NEB_SCR (S8Q47)]
SYRUP_ID (S8Q39_01 to S8Q39_11)
What prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
[MARK ALL THAT APPLY. PROBE: Any other medications?]
Variable Names
SYRUP_IX01 (S8Q39_01)
SYRUP_IX02 (S8Q39_02)
SYRUP_IX03 (S8Q39_03)
SYRUP_IX04 (S8Q39_04)
SYRUP_IX05 (S8Q39_05)
SYRUP_IX06 (S8Q39_06)
SYRUP_IX07 (S8Q39_07)
SYRUP_IX08 (S8Q39_08)
SYRUP_IX09 (S8Q39_09)
SYRUP_IX10 (S8Q39_10)
SYRUP_IX11 (S8Q39_11)
Medication
Aerolate
Albuterol
Alupent
Metaproteronol
Prednisolone
Prelone
Proventil
Slo-Phyllin
Theophylline
Ventolin
Other, please specify: [SKIP TO OTH_S1 (S8Q40)]
IF ANY ANSWER SELECTED FROM SYRUP_IX01 (S8Q39_01)–SYRUP_IX10 (S8Q39_10), SKIP TO
NEB_SCR (S8Q47).
(0)
(1)
(6)
(7)
OTH_S1 (S8Q40)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO REC_MED3]
[SKIP TO NEB_SCR (S8Q47)]
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
Series 1, No. 46 [ Page 63
INTRODUCTORY STATEMENT
READ: I’m going to read a list of medicines to see if you recognize the name of the medications {you
have/[CHILD’S NAME] has} taken within the past 3 months. [CONTINUE]
DK1_SYRP (S8Q41)
(0)
(1)
(6)
(7)
DK2_SYRP (S8Q42)
(0)
(1)
(6)
(7)
DK3_SYRP (S8Q43)
(0)
(1)
(6)
(7)
DK4_SYRP (S8Q44)
(0)
(1)
(6)
(7)
DK5_SYRP (S8Q45)
(0)
(1)
(6)
(7)
DK6_SYRP (S8Q46)
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Alupent or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Ventolin or Proventil or Albuterol?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Aerolate, Slo-Phyllin, or Theophylline?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Prelone or Prednisolone?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication in syrup form that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
NEB_SCR (S8Q47)
(0)
(1)
(6)
(7)
A nebulizer is a small machine with a tube and facemask or mouthpiece that you breathe through
continuously. In the past 3 months, were any of {your/[the (AGE) year old/NAME]’s} asthma medicines
used with a nebulizer?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
NEB_ID (S8Q48_01 to S8Q48_08)
In the past 3 months, what prescriptions medications {have you/has [the (AGE) year old/NAME]} taken using a
nebulizer?
[MARK ALL THAT APPLY, PROBE: Any other medications?]
Page 64 [ Series 1, No. 46
Variable Names
NEB_IDX01 (S8Q48_01)
NEB_IDX02 (S8Q48_02)
NEB_IDX03 (S8Q48_03)
NEB_IDX04 (S8Q48_04)
NEB_IDX05 (S8Q48_05)
NEB_IDX06 (S8Q48_06)
NEB_IDX07 (S8Q48_07)
NEB_IDX08 (S8Q48_08)
Medication
Albuterol
Alupent
Cromolyn
Intal
Metaproteronol
Proventil
Ventolin
Other, please specify: [SKIP TO OTH_N1 (S8Q49)]
IF AN ANSWER SELECTED FROM NEB_IDX01 (S8Q48_01)–NEB_IDX07 (S8Q48_07), SKIP TO
SECTION 9.
(0)
(1)
(6)
(7)
OTH_N1 (S8Q49)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO DK1_NEB (S8Q50)]
[SKIP TO SECTION 7]
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
DK1_NEB (S8Q50)
(0)
(1)
(6)
(7)
DK2_NEB (S8Q51)
(0)
(1)
(6)
(7)
DK3_NEB (S8Q52)
(0)
(1)
(6)
(7)
DK4_NEB (S8Q53)
(0)
(1)
(6)
(7)
DK5_NEB (S8Q54)
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Alupent or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Ventolin, Proventil or Albuterol?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Intal or Cromolyn
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication using a nebulizer that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
Series 1, No. 46 [ Page 65
Section 7. Family History of Asthma
OTHRASTH
[IF ROSTER = 1, SKIP TO BRO_N (S9Q1).] Besides {you/[the (AGE) year old}, has anyone else in your
household ever been told by a doctor or health professional that they have asthma?
(0)
(1)
(6)
(7)
BRO_N (S9Q1)
NO
YES
DON’T KNOW
REFUSED
How many biological brothers [have you/ has the (AGE) year old] ever had?
__ __NUMBER
(0) NONE
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS
‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
HALF-BROTHERS SHOULD BE INCLUDED.
SIS_N (S9Q2)
How many biological sisters [have you/has the (AGE) year old] ever had?
__ __ NUMBER
(0) NONE
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS
‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
HALF-SISTERS SHOULD BE INCLUDED.
PARENTS1 (S9Q3)
(0)
(1)
(6)
(7)
Were either of [your/the (AGE) year old’s] biological parents ever told they have asthma?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO BROASTH1 (S9Q5)]
[SKIP TO BROASTH1 (S9Q5)]
[SKIP TO BROASTH1 (S9Q5)]
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS
‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
PARENTS2 (S9Q4)
(1)
(2)
(3)
(6)
(7)
Who?
FATHER
MOTHER
BOTH
DON’T KNOW
REFUSED
BROASTH1 (S9Q5)
[IF BRO_N (S9Q1) = 0, 96, 97, SKIP TO SISASTH1 (S9Q7). ELSE IF BRO_N (S9Q1) > 1, SKIP TO
BROASTH2 (S9Q6).] Was [your/the (AGE) year old’s] biological brother ever told that he had asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
ALL SKIP TO SISASTH1 (S9Q7).
Page 66 [ Series 1, No. 46
BROASTH2 (S9Q6)
How many of [your/the (AGE) year old’s] biological brothers were ever told they had asthma?
__ __NUMBER
(0) ZERO
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS
‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
SISASTH1 (S9Q7)
[IF SIS_N (S9Q2) = 0, 96, 97, SKIP TO GRANDSCR (S9Q9). ELSE IF SIS_N (S9Q2) > 1, SKIP TO
SISASTH2 (S9Q8).] [IF SIS_N (S9Q2) = 1, ASK:] Was [your/the (AGE) year old’s] biological sister ever
told that she had asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
ALL SKIP TO GRANDSCR (S9Q9).
SISASTH2 (S9Q8)
How many of [your/the (AGE) year old’s] biological sisters were ever told they had asthma?
__ __
(0)
(96)
(97)
NUMBER
ZERO
DON’T KNOW
REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS
‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
GRANDSCR (S9Q9)
(0)
(1)
(6)
(7)
Were any of [your/the (AGE) year old’s] biological grandparents ever told they had asthma?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO OTHER_T (S11Q1)]
[SKIP TO OTHER_T (S11Q1)]
[SKIP TO OTHER_T (S11Q1)]
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL GRANDPARENTS SHOULD BE CODED AS ‘‘DON’T
KNOW.’’
GRANDPARENTS WHO ARE DECEASED SHOULD BE INCLUDED.
GRNDASTH
Which of {your/the (AGE) year old’s} biological grandparents were told they had asthma?
[MARK ALL THAT APPLY]
(S9Q10_01)
(S9Q10_02)
(S9Q10_03)
(S9Q10_04)
MOTHER’S MOTHER
MOTHER’S FATHER
FATHER’S MOTHER
FATHER’S FATHER
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH
INFORMATION REGARDING THEIR BIOLOGICAL GRANDPARENTS SHOULD BE CODED AS ‘‘DON’T
KNOW.’’
GRANDPARENTS THAT ARE DECEASED SHOULD BE INCLUDED.
Series 1, No. 46 [ Page 67
Section 8. Demographic Information
OTHER_T (S11Q1)
Now, I just have a few more general questions about you and your household. Do you have any other home
phone numbers in addition to (AREA CODE AND TELEPHONE NUMBER CALLED)? Please do not
include cellular phones in your answer.
(0)
(1)
(6)
(7)
SEC_USE (S11Q2)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this second number for home use only, for business use only, or for both home and business use?
(1)
(2)
(3)
(6)
(7)
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
[SKIP TO THIRD_TN (S11Q4)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
SEC_FAX (S11Q3)
(0)
(1)
(6)
(7)
Is this second number used only for computer or fax communications?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
THIRD_TN (S11Q4)
Do you have a third home phone number in addition to the two you have already told me
about? Please do not include cellular phones in your answer.
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
THIRD_USE (S11Q5) Is this third number for home use only, for business use only, or for both home and
business use?
(1)
(2)
(3)
(6)
(7)
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
THIRD_FAX (S11Q6)
(0)
(1)
(6)
(7)
NUM_PHON
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this third number used only for computer or fax communications?
NO
YES
DON’T KNOW
REFUSED
DERIVED. NUMBER OF TELEPHONES FOR HOME USE
WO_SERVICE (S11Q7)
(0)
(1)
(6)
(7)
C11Q21_A (S11Q8)
During the past 12 months, has your household been without telephone service for 1 week or more?
Please do not include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
For how long was your household without telephone service in the past 12 months?
(ENTER THE NUMBER, THEN CONTINUE TO THE NEXT SCREEN TO ENTER TIME PERIOD.)
ENTER NUMBER __ __ __
(996) DON’T KNOW
(997) REFUSED
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
Page 68 [ Series 1, No. 46
C11Q21 (S11Q9)
ENTER PERIOD
(1)
(2)
(3)
(6)
(7)
NOPHONE
DAYS
WEEK(S)
MONTH(S)
DON’T KNOW
REFUSED
DERIVED. NUMBER OF DAYS WITHOUT TELEPHONE SERVICE
R_ETH_2 (HISPANIC) [Are you/Is the (AGE) year old] of Hispanic or Latino origin?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HISPANIC_DERIVED
R_RACE2
(S2Q11_01)
(S2Q11_02)
(S2Q11_03)
(S2Q11_04)
(S2Q11_05)
(S2Q11_06)
(S2Q11_07)
DERIVED. HISPANIC ORIGIN OF HOUSEHOLD MEMBER.
Now, I’m going to read a list of categories. Please choose one or more of the following categories to describe
[yourself/the (AGE) year old]. [Are you/Is the (AGE) year old] white, black or African-American, American Indian,
Alaska Native, Asian, or Native Hawaiian or Other Pacific Islander?
[MARK ALL THAT APPLY]
WHITE
BLACK/AFRICAN-AMERICAN
AMERICAN INDIAN
ALASKA NATIVE
ASIAN
NATIVE HAWAIIAN
PACIFIC ISLANDER
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: BE SURE TO READ THE ENTIRE QUESTION AS WRITTEN (INCLUDING ALL
RESPONSE CATEGORIES).
RACE INFORMATION IS COLLECTED BY SELF-IDENTIFICATION. IT IS ‘‘WHATEVER RACE YOU
CONSIDER YOURSELF TO BE.’’ DO NOT TRY TO EXPLAIN OR DEFINE ANY OF THE GROUPS.
MULTIPLE RACES MAY BE SELECTED.
RACE
DERIVED. RACE OF HOUSEHOLD MEMBER
RACEARRAY
DERIVED. ARRAY OF RESPONSES TO RACE VARIABLE
R_EDUC
HEIGHT1 (S2Q18)
[IF THE SAMPLED PERSON IS UNDER 5, I.E. R_DOB (S2Q5) < 05, SKIP TO (S2Q14_1).] The next
questions are about [your/the (AGE) year old’s] education level. What is the highest level of school that [you
have/the (AGE) year old has] completed?
_ _ENTER HIGHEST GRADE COMPLETED (1–12)
(13) GRADUATED HIGH SCHOOL
(14) SOME POST-HIGH SCHOOL, BUT NOT BACHELOR’S DEGREE (B.A.)
(15) COLLEGE GRADUATE—BACHELOR’S DEGREE OR B.A.
(16) SOME GRADUATE OR PROFESSIONAL SCHOOL (WITH OR WITHOUT DEGREE)
(17) PRESCHOOL/HEADSTART
(18) KINDERGARTEN
(19) NO FORMAL SCHOOLING
(96) DON’T KNOW
(97) REFUSED
Series 1, No. 46 [ Page 69
HEIGHT1—FEET
(S2Q14_1)
HEIGHT2—INCHES
(S2Q14_2)
HEIGHT3—CENTIMETERS
(S2Q14_3)
How tall [are you/is the (AGE) year old]?
__ __ feet/__ __inches OR __ __ __centimeters
(96) DON’T KNOW (996) DON’T KNOW
(97) REFUSED
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE
RELATED TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
HEIGHT
DERIVED. RESPONDENT HEIGHT IN INCHES.
WEIGHT1—POUNDS
(S2Q15_1)
WEIGHT2—KILOGRAMS
(S2Q15_2)
How much [do you/does the (AGE) year old] weigh?
__ __ __ pounds OR __ __ __kilograms
(996) DON’T KNOW (996) DON’T KNOW
(997) REFUSED
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE
RELATED TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
WEIGHT
DERIVED. RESPONDENT WEIGHT IN POUNDS.
BIRTHW1—POUNDS
(S2Q16_1) BIRTHW2—OUNCES
(S2Q16_2)
BIRTHW3—GRAMS
(S2Q16_3)
[ASK BIRTHWT ONLY FOR SAMPLED PERSON’S AGE (S2Q5) < 18.] How much did [the (AGE) year old]
weigh at birth?
__ __ pounds /__ __ ounces
(96) DON’T KNOW
(97) REFUSED
BIRTHWEIGHT
OR __ __ __ __ grams
(9996) DON’T KNOW
(9997) REFUSED
[SKIP TO INC_TOT (S10Q1)]
[SKIP TO BIRTHRF (S2Q17)]
[SKIP TO BIRTHRF (S2Q17)]
DERIVED. CHILD’S BIRTHWEIGHT IN GRAMS
BIRTHRF (S2Q17)
(0)
(1)
(6)
(7)
INC_TOT (S10Q1)
At birth, did [the (AGE) year old/NAME] weigh less than 5 1/2 pounds?
[INTERVIEWER NOTE: 5 1/2 pounds = 2500 GRAMS]
NO
YES
DON’T KNOW
REFUSED
What was the total combined income of your household in (FILL LAST CALENDAR YEAR), including
income from all sources including wages, salaries, unemployment payments, public assistance, Social
Security or retirement benefits, help from relatives, and so forth? Can you tell me that amount before taxes?
{___________________ RECORD INCOME
(999999996) DON’T KNOW
[SKIP TO RANGE_20 (S10Q3)]
(999999997) REFUSED
[SKIP TO RANGE_20 (S10Q3)]
HELP SCREEN: RESPONDENT MAY GIVE A RANGE AS AN ANSWER TO THIS QUESTION. BE
PREPARED TO PROBE FOR A MORE ACCURATE ANSWER.
Page 70 [ Series 1, No. 46
RANGE_20 (S10Q3)
For the purposes of this survey, it is important to get at least a range for the total income received by all
members of your household in [FILL YEAR]. Would you say that the total combined income, before taxes,
was above or below $20,000?
(1)
(2)
(3)
(6)
(7)
MORE THAN $20,000
$20,000
LESS THAN $20,000
DON’T KNOW
REFUSED
RANGE_10 (S10Q4)
Was the total combined household income more or less than $10,000?
(1)
(2)
(3)
(6)
(7)
RANGE_7 (S10Q5)
[SKIP TO RANGE_40 (S10Q9)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_10 (S10Q4)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
MORE THAN $10,000
$10,000
LESS THAN $10,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_15 (S10Q6)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_7 (S10Q5)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was it more than $7,500?
(0)
(1)
(6)
(7)
RANGE_15 (S10Q6)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was it more than $15,000?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO RANGE_12 (S10Q8)]
[SKIP TO RANGE_17 (S10Q7)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
RANGE_17 (S10Q7) Was it more than $17,500?
(0)
(1)
(6)
(7)
RANGE_12 (S10Q8)
(0)
(1)
(6)
(7)
RANGE_40 (S10Q9)
(1)
(2)
(3)
(6)
(7)
RANGE_60 (S10Q10)
(1)
(2)
(3)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was it more than $12,500?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $40,000?
MORE THAN $40,000
$40,000
LESS THAN $40,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_60 (S10Q10)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_30 (S10Q13)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $60,000?
MORE THAN $60,000
$60,000
LESS THAN $60,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_75 (S10Q16)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_50 (S10Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Series 1, No. 46 [ Page 71
RANGE_50 (S10Q11)
(1)
(2)
(3)
(6)
(7)
Was the total combined household income more or less than $50,000?
MORE THAN $50,000
$50,000
LESS THAN $50,000
DON’T KNOW
REFUSED
RANGE_45 (S10Q12)
(1)
(2)
(6)
(7)
RANGE_30 (S10Q13)
(1)
(2)
(3)
(6)
(7)
RANGE_35 (S10Q14)
(1)
(2)
(6)
(7)
RANGE_25 (S10Q15)
(1)
(2)
(6)
(7)
RANGE_75 (S10Q16)
(1)
(2)
(3)
(6)
(7)
BESTINCOME
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_45 (S10Q12)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $45,000?
MORE THAN $45,000
LESS THAN $45,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $30,000?
MORE THAN $30,000
$30,000
LESS THAN $30,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_35 (S10Q14)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_25 (S10Q15)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $35,000?
MORE THAN $35,000
LESS THAN $35,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $25,000?
MORE THAN $25,000
LESS THAN $25,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $75,000?
MORE THAN $75,000
$75,000
LESS THAN $75,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
DERIVED. BEST INCOME VALUE
C11Q22 (S11Q11) Please tell me your Zip Code.
___ ___ ___ ___ ___ (00001–99995)
(99996) DON’T KNOW
(99997) REFUSED
CLOSING STATEMENT
Those are all the questions I have for you. I’d like to thank you on behalf of the Centers for Disease Control and
Prevention for the time and effort you’ve spent answering these questions. If you have any questions about this
survey, you may call my supervisor toll-free at 1–866–775–6858. If you have questions about your rights as a
survey participant, you may call the chairman of the Institutional Review Board at 1–800–223–8118. Thanks
again.
Page 72 [ Series 1, No. 46
Proxy Variable Listing
[THE FOLLOWING QUESTIONS ARE ASKED IF SAMPLED ADULT NOT AVAILABLE AT THE INITIAL
CALL.]
INS1P (S5Q1_AP)
Does [the (AGE) year old/NAME] have any kind of health care coverage, including
health insurance, prepaid plans such as HMOs, or government plans such as Medicare?
(0)
(1)
(6)
(7)
INS2P (S5Q1_BP)
NO
YES
DON’T KNOW
REFUSED
[IF INS1P (S5Q1_AP) = 0, 6, 7, SKIP TO AIRCLEANEP (S7Q1P).] [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since
birth’’/ELSE FILL: ‘‘During the past 12 months’’], was there any time that [the (AGE) year old/NAME] did
not have any health insurance or coverage?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
AIRCLEANEP (S7Q1P)
(0)
(1)
(6)
(7)
(0)
(1)
(6)
(7)
Is a dehumidifier regularly used to reduce moisture inside your home?
NO
YES
DON’T KNOW
REFUSED
KITC_FANP (S7Q3P)
(0)
(1)
(6)
(7)
Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?
NO
YES
DON’T KNOW
REFUSED
COOK_GASP (S7Q4P)
(0)
(1)
(6)
(7)
ENV_PETSP (S7Q6P)
Is gas used for cooking?
NO
YES
DON’T KNOW
REFUSED
ENV_MOLDP (S7Q5P)
(0)
(1)
(6)
(7)
Is an air cleaner or purifier regularly used inside your home?
NO
YES
DON’T KNOW
REFUSED
DEHUMIDP (S7Q2P)
(0)
(1)
(6)
(7)
[SKIP TO INS2P (S5Q1_BP)]
In the past 30 days, has anyone seen or smelled mold or a musty odor inside your home? Do not
include mold on food.
NO
YES
DON’T KNOW
REFUSED
Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets
that are kept inside?
NO
YES
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 73
C_ROACHP (S7Q7P)
(0)
(1)
(6)
(7)
In the past 30 days, has anyone seen cockroaches inside your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: Studies have shown that cockroaches are a leading cause of asthma in children that live in
urban areas. Cockroach droppings and carcasses can cause children to experience symptoms of asthma.
WOOD_STOVP (S7Q8P)
(0)
(1)
(6)
(7)
Is a fireplace or wood burning stove used in your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: OCCASIONAL USE SHOULD BE CODED AS ‘‘YES.’’
GAS_STOVEP (S7Q9P)
(0)
(1)
(6)
(7)
Are unvented gas logs, an unvented gas fireplace, or an unvented gas stove used in your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Unvented’’ means no chimney.
S_INSIDE (S7Q10P)
(0)
(1)
(6)
(7)
In the past week, has anyone smoked inside your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Smoked’’ means ‘‘anything.’’
SKIP TO OTHRASTHP IF INTERVIEW IS FOR SAMPLED CHILD (R_DOB/S2Q5 < 18).
CIGARETSP (S7Q18P)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
CIG_FREQP (S7Q19P)
(1)
(2)
(3)
(6)
(7)
[SKIP TO EMP_STATP (S7Q20P)]
[SKIP TO EMP_STATP (S7Q20P)]
[SKIP TO EMP_STATP (S7Q20P)]
Does [the (AGE) year old] now smoke cigarettes every day, some days, or not at all?
EVERY DAY
SOME DAYS
NOT AT ALL
DON’T KNOW
REFUSED
EMP_STATP (S7Q20P)
(1)
(2)
(3)
(6)
(7)
{Has (the (AGE) year old) smoked at least 100 cigarettes in [his or her]} entire life?
[IF R_ASTHMX01 = 1 OR S3Q7 = 1:] We are interested in things that affect
asthma in the workplace. However, first I’d like to ask how you would describe [the
(AGE) year old/NAME]’s current employment status. Would you say [the (AGE) year old/NAME] is . . .
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
DON’T KNOW
REFUSED
Page 74 [ Series 1, No. 46
UNEMP_RP (S7Q22P)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(96)
(97)
OTHRASTHP
[IF EMP_STATP (S7Q20P) = 1 OR 2, SKIP TO OTHRASTHP] What is the main reason [the (AGE)
year old is] not employed?
KEEPING HOUSE
GOING TO SCHOOL
RETIRED
DISABLED
UNABLE TO WORK FOR OTHER HEALTH REASONS
LOOKING FOR WORK
LAID OFF
OTHER
DON’T KNOW
REFUSED
Besides [the (AGE) year old/NAME], has anyone else in your household ever been told by a doctor or health
professional that they have asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
OTHER_TP (S11Q1P)
(0)
(1)
(6)
(7)
Now, I just have a few more general questions about you and your household. Do you have any other
home phone numbers in addition to (AREA CODE AND TELEPHONE NUMBER CALLED)? Please do
not include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
SEC_USEP (S11Q2P)
(1)
(2)
(3)
(6)
(7)
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
Do you have a third home phone number in addition to the two you have already told me about? Please
do not include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
THIRD_USEP (S11Q5P)
(1)
(2)
(3)
(6)
(7)
[SKIP TO THIRD_TNP (S11Q4P)]
Is this second number used only for computer or fax communications?
THIRD_TNP (S11Q4P)
(0)
(1)
(6)
(7)
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
Is this second number for home use only, for business use only, or for both home and business use?
SEC_FAXP (S11Q3P)
(0)
(1)
(6)
(7)
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
Is this third number for home use only, for business use only, or for both home and business use?
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
[SKIP TO WO_SERVICP (S11Q7P)]
Series 1, No. 46 [ Page 75
THIRD_FAXP (S11Q6P)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
WO_SERVICP (S11Q7P)
(0)
(1)
(6)
(7)
Is this third number used only for computer or fax communications?
During the past 12 months, has your household been without telephone service for 1 week or more?
Please do not include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
C11Q21_AP (S11Q8P)
[SKIP TO R_ETH_2P (HISPANICP)]
[SKIP TO R_ETH_2P (HISPANICP)]
[SKIP TO R_ETH_2P (HISPANICP)]
For how long was your household without telephone service in the past 12 months?
(ENTER THE DAYS, WEEKS, OR MONTHS, THEN CONTINUE TO THE NEXT SCREEN TO ENTER
TIME PERIOD.)
ENTER NUMBER __ __ __
(996) DON’T KNOW
(997) REFUSED
C11Q21P (S11Q9P)
(1)
(2)
(3)
(6)
(7)
[SKIP TO R_ETH_2P (HISPANICP)]
[SKIP TO R_ETH_2P (HISPANICP)]
ENTER PERIOD
DAYS
WEEK(S)
MONTH(S)
DON’T KNOW
REFUSED
[NOTE: DEMOGRAPHICS (R_ETH_2P to BIRTHRFP) ARE ONLY ASKED FOR THE SAMPLED
RESPONDENT.]
R_ETH_2P (HISPANICP) (Is the (AGE) year old) of Hispanic or Latino origin?
(0)
(1)
(6)
(7)
R_RAC2P
NO
YES
DON’T KNOW
REFUSED
Now, I’m going to read a list of categories. Please choose one or more of the following categories to describe (the
(AGE) year old/NAME). (Is the (AGE) year old/NAME) White, Black or African-American, American Indian, Alaska
Native, Asian, or Native Hawaiian or Other Pacific Islander?
[MARK ALL THAT APPLY]
(S2Q11_01P)
(S2Q11_02P)
(S2Q11_03P)
(S2Q11_04P)
(S2Q11_05P)
(S2Q11_06P)
(S2Q11_07P)
WHITE
BLACK/AFRICAN-AMERICAN
AMERICAN INDIAN
ALASKA NATIVE
ASIAN
NATIVE HAWAIIAN
PACIFIC ISLANDER
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: BE SURE TO READ THE ENTIRE QUESTION AS WRITTEN (INCLUDING ALL
RESPONSE CATEGORIES).
RACE INFORMATION IS COLLECTED BY SELF-IDENTIFICATION. IT IS ‘‘WHATEVER RACE YOU
CONSIDER YOURSELF TO BE.’’ DO NOT TRY TO EXPLAIN OR DEFINE ANY OF THE GROUPS.
MULTIPLE RACES MAY BE SELECTED.]
Page 76 [ Series 1, No. 46
R_EDUCP (S2Q18P)
__
(13)
(14)
(15)
(16)
(17)
(18)
(19)
(96)
(97)
[SKIP IF A PERSON’S AGE IS UNDER 5, I.E. R_DOB < 05.] The next questions are about [the (AGE)
year old/NAME]’s education level. What is the highest level of school that [the (AGE) year old/NAME]
has completed?
ENTER HIGHEST GRADE COMPLETED (1–12)
GRADUATED HIGH SCHOOL
SOME POST-HIGH SCHOOL, BUT NOT BACHELOR’S DEGREE (B.A.)
COLLEGE GRADUATE—BACHELOR’S DEGREE OR B.A.
SOME GRADUATE OR PROFESSIONAL SCHOOL (WITH OR WITHOUT DEGREE)
PRESCHOOL/HEADSTART
KINDERGARTEN
NO FORMAL SCHOOLING
DON’T KNOW
REFUSED
HEIGHT1P—FEET
(S2Q14_1P)
HEIGHT2P—INCHES
(S2Q14_2P)
HEIGHT3P—CENTIMETERS
(S2Q14_3P)
How tall is {the (AGE) year old/NAME}?
__ __ feet/__ __inches OR __ __ __centimeters
(96) DON’TKNOW (996) DON’TKNOW
(97) REFUSED
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE
RELATED TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
WEIGHT1P—POUNDS
(S2Q15_1P)
WEIGHT2P—KILOGRAMS
(S2Q15_2P)
How much does {the (AGE) year old/NAME} weigh?
__ __ __ pounds OR __ __ __kilograms
(996) DON’T KNOW (996) DON’T KNOW
(997) REFUSED
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE
RELATED TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
BIRTHW1P—POUNDS
(S2Q16_1P)
BIRTHW2P—OUNCES
(S2Q16_2P)
BIRTHW3P—GRAMS
(S2Q16_3P)
[ASK BIRTHWTP ONLY FOR SAMPLED PERSONS WITH AGE < 18 (R_DOB/S2Q5).] How much did [the
(AGE) year old/NAME] weigh at birth?
__ __ pounds /__ __ ounces OR __ __ __ __ grams [SKIP TO INC_TOTP (S10Q1P)]
(96) DON’T KNOW
(97) REFUSED
(9996) DON’T KNOW [SKIP TO BIRTHRFP (S2Q17P)]
(9997) REFUSED [SKIP TO BIRTHRFP (S2Q17P)]
Series 1, No. 46 [ Page 77
BIRTHRFP (S2Q17P)
(0)
(1)
(6)
(7)
At birth, did [the (AGE) year old/NAME] weigh less than 5 1/2 pounds?
[INTERVIEWER NOTE: 5 1/2 pounds = 2500 GRAMS]
NO
YES
DON’T KNOW
REFUSED
INC_TOTP (S10Q1P)
What was the total combined income of your household in [CATI: FILL LAST CALENDAR YEAR],
including income from all sources including wages, salaries, unemployment payments, public assistance,
Social Security or retirement benefits, help from relatives, and so forth? Can you tell me that amount
before taxes?
$___________________ RECORD INCOME
(999999996) DON’T KNOW
[SKIP TO RANGE_20P (S10Q3P)]
(999999997) REFUSED
[SKIP TO RANGE_20P (S10Q3P)]
HELP SCREEN: RESPONDENT MAY GIVE A RANGE AS AN ANSWER TO THIS QUESTION. BE
PREPARED TO PROBE FOR A MORE ACCURATE ANSWER.
RANGE_20P (S10Q3P)
(1)
(2)
(3)
(6)
(7)
MORE THAN $20,000
$20,000
LESS THAN $20,000
DON’T KNOW
REFUSED
RANGE_10P (S10Q4P)
(1)
(2)
(3)
(6)
(7)
[SKIP TO RANGE_40P (S10Q9P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_10P (S10Q4P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $10,000?
MORE THAN $10,000
$10,000
LESS THAN $10,000
DON’T KNOW
REFUSED
RANGE_7P (S10Q5P)
(0)
(1)
(6)
(7)
For the purposes of this survey, it is important to get at least a range for the total income received by all
members of your household in [FILL YEAR]. Would you say that the total combined income, before
taxes, was above or below $20,000?
[SKIP TO RANGE_15P (S10Q6P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_7P (S10Q5P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was it more than $7,500?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
RANGE_15P (S10Q6P) Was it more than $15,000?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
RANGE_17P (S10Q7P)
(0)
(1)
(6)
(7)
(0)
(1)
(6)
(7)
Was it more than $17,500?
NO
YES
DON’T KNOW
REFUSED
RANGE_12P (S10Q8P)
[SKIP TO RANGE_12P (S10Q8P)]
[SKIP TO RANGE_17P (S10Q7P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was it more than $12,500?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Page 78 [ Series 1, No. 46
RANGE_40P (S10Q9P)
(1)
(2)
(3)
(6)
(7)
MORE THAN $40,000
$40,000
LESS THAN $40,000
DON’T KNOW
REFUSED
RANGE_60P (S10Q10P)
(1)
(2)
(3)
(6)
(7)
(1)
(2)
(6)
(7)
(1)
(2)
(3)
(6)
(7)
(1)
(2)
(6)
(7)
(1)
(2)
(6)
(7)
(1)
(2)
(3)
(6)
(7)
C11Q22P (S11Q11P)
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $25,000?
MORE THAN $25,000
LESS THAN $25,000
DON’T KNOW
REFUSED
RANGE_75P (S10Q16P)
[SKIP TO RANGE_35P (S10Q14P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_25P (S10Q15P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $35,000?
MORE THAN $35,000
LESS THAN $35,000
DON’T KNOW
REFUSED
RANGE_25P (S10Q15P)
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $30,000?
MORE THAN $30,000
$30,000
LESS THAN $30,000
DON’T KNOW
REFUSED
RANGE_35P (S10Q14P)
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_45P (S10Q12P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $45,000?
MORE THAN $45,000
LESS THAN $45,000
DON’T KNOW
REFUSED
RANGE_30P (S10Q13P)
[SKIP TO RANGE_75P (S10Q16P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_50P (S10Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $50,000?
MORE THAN $50,000
$50,000
LESS THAN $50,000
DON’T KNOW
REFUSED
RANGE_45P (S10Q12P)
[SKIP TO RANGE_60P (S10Q10P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO RANGE_30P (S10Q13P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $60,000?
MORE THAN $60,000
$60,000
LESS THAN $60,000
DON’T KNOW
REFUSED
RANGE_50P (S10Q11P)
(1)
(2)
(3)
(6)
(7)
Was the total combined household income more or less than $40,000?
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
[SKIP TO C11Q22P (S11Q11P)]
Was the total combined household income more or less than $75,000?
MORE THAN $75,000
$75,000
LESS THAN $75,000
DON’T KNOW
REFUSED
Please tell me your Zip Code.
___ ___ ___ ___ ___ (00001–99995) (99996)
DON’T KNOW
(99997) REFUSED
Series 1, No. 46 [ Page 79
CLOSING STATEMENT
Those are all the questions I have for you. I’d like to thank you on behalf of the Centers for Disease Control and
Prevention for the time and effort you’ve spent answering these questions. [the (AGE) year old/NAME] about
(his/her) asthma.] If you have any questions about this survey, you may call my supervisor toll-free at
1–866–775–6858. If you have questions about your rights as a survey participant, you may call the chairman of
the Institutional Review Board at 1–800–223–8118. Thanks again.
Page 80 [ Series 1, No. 46
Appendix IV
Four-State Study Questionnaire
Form Approved
OMB No. 0920–0406
Exp. Date 12/31/04
SLAITS National Asthma Survey
National Study Questionnaire
Section
Subject
Section 1
NAS Eligibility Screening, Respondent Selection,
and Initial Demographics
Section 2
History of Asthma (Symptoms & Episodes)
Section 3
Health Care Utilization
Section 4
Knowledge of Asthma/Management Plan
Section 5
Modifications to Environment
Section 6
Medications
Section 7
Family History of Asthma
Section 8
Demographic Information
The following public burden estimate statement will be available as a CATI screen:
Public reporting burden of this collection of information is estimated to average 18 minutes per response, including the time for
reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing
the collection of information. An agency may not conduct or sponsor, and a person is not required to respond to a collection of
information unless it displays a currently valid OMB control number. Send comments regarding this burden estimate or any other
aspect of this collection of information, including suggestions for reducing this burden to CDC/ATSDR Reports Clearance Officer,
1600 Clifton Road NE, MS D-24, Atlanta, Georgia 30333; ATTN: PRA (0920–0406).
NOTE: CATI variable names are provided with corresponding SAS data file variable names, if different, in parentheses.
Series 1, No. 46 [ Page 81
Section 1. NAS Eligibility Screening, Respondent Selection, and Initial Demographics
CASEID
CASEIDX
HOUSEHOLD ID NUMBER
UNIQUE ASTHMA INTERVIEW ID NUMBER
CALLDATE
CATI DATE. DATE THE INTERVIEW WAS COMPLETED OR THE LAST DATE THE HOUSEHOLD WAS
CONTACTED, IF A COMPLETED INTERVIEW WAS NOT OBTAINED.
SAMP_TYPE
DERIVED. NIS/NAS OR NAS-ONLY SAMPLE GROUP
(1) NIS/NAS SAMPLE
(2) NAS-ONLY SAMPLE
IAPID
IAP AREA LOCATION
SPANISH
CATI FLAG. CASE PLACED IN SPANISH QUEUE
(0) NOT PLACED IN SPANISH QUEUE
(1) PLACED IN SPANISH QUEUE
LTR
Advance letter mailed to household
(0) NO, LETTER WAS NOT MAILED
(1) YES, LETTER MAILED
INTRODUCTORY STATEMENT
Now I have some questions regarding asthma for both adults and children in your household.
SCR_OTHRS (S2Q2)
(0)
(1)
(6)
(7)
Including yourself, has anyone living in your household ever been told by a doctor or other health
professional that they have asthma?
[INCLUDE EXERCISE-INDUCED ASTHMA]
NO
YES
DON’T KNOW
REFUSED
IF SCR_OTHRS (S2Q2) = 0, 6, 7, END INTERVIEW.
ROST
I need to randomly select household members for the interview. How many people 18 years of age or older who live
in your household have been diagnosed with asthma?
_ _ _ ENTER NUMBER OF PEOPLE (RANGE 00–30)
(96) DON’T KNOW
(97) REFUSED
ROSTKID
[SKIP TO ROSTKID]
[END INTERVIEW]
[END INTERVIEW]
How many people under 18 years of age who live in your household have been diagnosed with asthma?
_ _ _ ENTER NUMBER OF PEOPLE (RANGE 00–30)
(96) DON’T KNOW
(97) REFUSED
[END INTERVIEW]
[END INTERIVEW]
RANDOMLY SAMPLE ONE ADULT FROM ROST IF > 0 AND ONE CHILD FROM ROSTKID IF > 0.
R_DOB (S2Q5) Please tell me [your age/the age of the (SELECTED PERSON) in your household].
ENTER NUMBER ____
(996) DON’T KNOW
(997) REFUSED
[END INTERVIEW]
[END INTERVIEW]
R_SEX (S2Q6) [READ IF NECESSARY] [Are you/Is the (AGE) year old] male or female?
(1) MALE
(2) FEMALE
(7) REFUSED
HH_TOTAL
DERIVED. NUMBER OF PEOPLE WITH ASTHMA IN THE HOUSEHOLD
COMPLETE
DERIVED. TOTAL NUMBER OF HOUSEHOLD MEMBERS WHO WERE SAMPLED AND COMPLETED AN
INTERVIEW
FLG_PROXY
DERIVED. INTERVIEW DONE BY PROXY BECAUSE OF ILLNESS
Page 82 [ Series 1, No. 46
PROXYREL (S3Q6B)
[ASK IF ADULT INTERVIEW IS TO BE DONE BY PROXY BECAUSE OF ILLNESS.] What is your
relationship to [the (AGE) year old]?
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(90)
(96)
(97)
SPOUSE
UNMARRIED PARTNER, BOYFRIEND/GIRLFRIEND
CHILD
GRANDCHILD
MOTHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)
FATHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)
BROTHER/SISTER
GRANDFATHER/GRANDMOTHER
OTHER RELATIVE
FOSTER CHILD
HOUSEMATE/ROOMMATE
ROOMER/BOARDER
OTHER NON-RELATIVE
UNRELATED LEGAL GUARDIAN
DON’T KNOW
REFUSED
RELA_CHLD (S3Q6)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(96)
(97)
OTH_CHLD (S3Q7)
(0)
(1)
(6)
(7)
AGEDGNOS (S3Q8)
[RELA_CHLD IS ONLY ASKED FOR AGE (R_DOB/S2Q5) < 18] What is your relationship to [the
(AGE) year old/NAME] who lives in this household?
MOTHER (STEP, FOSTER, ADOPTIVE) OR FEMALE GUARDIAN
FATHER (STEP, FOSTER, ADOPTIVE) OR MALE GUARDIAN
SISTER OR BROTHER (STEP/FOSTER/HALF/ADOPTIVE)
IN-LAW OF ANY TYPE
AUNT/UNCLE
GRANDPARENT
OTHER FAMILY MEMBER
FRIEND
DON’T KNOW
REFUSED
{Have you/Has [the (AGE) year old/NAME]} ever been told by a doctor or other health professional that {you
have/he has/she has} asthma?
NO
YES
DON’T KNOW
REFUSED
[END INTERVIEW]
[END INTERVIEW]
[END INTERVIEW]
How old {were you/was [the (AGE) year old/NAME]} when (you were/he or his parent or guardian was/she
or her parent or guardian was) first told by a doctor or other health professional that (you/he/she) had asthma?
[INTERVIEWER: ENTER 0 IF LESS THAN ONE YEARS OLD]
__ __ __ (ENTER AGE IN YEARS)
(996) DON’T KNOW
(997) REFUSED
CUR_AST2 (S3Q9)
(0)
(1)
(6)
(7)
{Do you/Does [the (AGE) year old/NAME]} still have asthma?
NO
YES
DON’T KNOW
REFUSED
Section 2. History of Asthma (Symptoms & Episodes)
LAST_MD (S3Q10) How long has it been since {you/[the (AGE) year old/NAME] or [the (AGE) year old/NAME]’s parents or
guardians} last talked to a doctor or other health professional about (your/his/her) asthma?
(0)
(1)
(2)
(3)
(4)
(6)
(7)
NEVER
WITHIN THE PAST YEAR
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEARS TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 83
LAST_MED (S3Q11)
(0)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
How long has it been since {you/[the (AGE) year old/NAME]} last took asthma medication?
NEVER
LESS THAN ONE DAY AGO
1–6 DAYS AGO
1 WEEK TO LESS THAN 3 MONTHS AGO
3 MONTHS TO LESS THAN 1 YEAR AGO
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEARS TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
INTRODUCTORY STATEMENT
READ: Symptoms of asthma include coughing, wheezing, shortness of breath, chest tightness, or phlegm production
when {you do not/[the (AGE) year old/NAME] does not} have a cold or respiratory infection. [CONTINUE]
LASTSYMP (S3Q12)
(0)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
ASTHSTAT
How long has it been since {you/[the (AGE) year old/NAME] last had any symptoms of asthma?
[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY]
NEVER
LESS THAN ONE DAY AGO
1–6 DAYS AGO
1 WEEK TO LESS THAN 3 MONTHS AGO
3 MONTHS TO LESS THAN 1 YEAR AGO
1 YEAR TO LESS THAN 3 YEARS AGO
3 YEAR TO 5 YEARS AGO
MORE THAN 5 YEARS AGO
DON’T KNOW
REFUSED
DERIVED. ASTHMA STATUS OF HOUSEHOLD MEMBER
(0) NO, PERSON DOES NOT HAVE ASTHMA
(1) YES, PERSON HAS ASTHMA
LTASTHM
DERIVED. RISK FACTOR FOR LIFETIME ASTHMA PREVALENCE BASED ON BRFSS RULES
(1) NOT AT RISK
(2) AT RISK
(9) DON’T KNOW/NOT SURE OR REFUSED
ASTATUS1
DERIVED. CURRENT ASTHMA STATUS OF HOUSEHOLD MEMBER BASED ON SELF-IDENTIFICATION
(1) PERSON SELF-IDENTIFIED ASTHMA
(0) PERSON DID NOT SELF-IDENTIFY ASTHMA
(6) DON’T KNOW
CASTHMA
DERIVED. RISK FACTOR FOR CURRENT ASTHMA PREVALENCE BASED ON BRFSS RULES
(1) NOT AT RISK
(2) AT RISK
(9) DON’T KNOW/NOT SURE OR REFUSED
ASTHMST
DERIVED. COMPUTED ASTHMA STATUS BASED ON BRFSS RULES
(1)
(2)
(3)
(9)
ASTATUS2
CURRENT
FORMER
NEVER
DON’T KNOW/NOT SURE OR REFUSED
DERIVED. CURRENT ASTHMA STATUS OF HOUSEHOLD MEMBER BASED ON SELF-REPORTED
BEHAVIORS
(1) BEHAVIORS INDICATE ASTHMA
(0) BEHAVIORS DO NOT INDICATE ASTHMA
(6) DON’T KNOW
FLG_TYPE
DERIVED. EXPECTED INTERVIEW TYPE
(1)
(2)
(3)
(4)
(5)
SAMPLED
SAMPLED
SAMPLED
SAMPLED
SAMPLED
PERSON
PERSON
PERSON
PERSON
PERSON
INT: SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS
INT: NO SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS
ILL, PROXY INT: SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS
ILL, PROXY INT: NO SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS
OR ASTHMA STATUS NOT DETERMINED
Page 84 [ Series 1, No. 46
IF THIS IS AN ADULT INTERVIEW (R_DOB/S2Q5 > 17) AND
CUR_AST2 (S3Q9) = 0, 6, 7 AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5,
SKIP TO INS1 (S5Q1_A). COMPLETE INS1 (S5Q1_A), INS2 (S5Q1_B), HH_INT through S_INSIDE (S7Q10),
CIGARETS (S7Q18) through UNEMP_R (S7Q22), SECTION 6 [OTC (S8Q1) through INHALERH (S8Q3), if
applicable], SECTION 7 [START AT BRO_N (S9Q1)], AND DEMOGRAPHICS [OTHER_T (S11Q1) THROUGH
C11Q22 (S11Q11)].
IF THIS IS A CHILD INTERVIEW (R_DOB/S2Q5 < 18) AND
CUR_AST2 (S3Q9) = 0, 6, 7 AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5,
SKIP TO INS1 (S5Q1_A). COMPLETE INS1 (S5Q1_A), INS2 (S5Q1_B), HH_INT through S_INSIDE (S7Q10),
SECTION 6 [OTC (S8Q1) through INHALERH (S8Q3), if applicable], SECTION 7 [START AT BRO_N (S9Q1)]
and DEMOGRAPHICS [OTHER_T (S11Q1) through C11Q22 (S11Q11)].
IF CUR_AST2 (S3Q9) = 1, CONTINUE.
IF CUR_AST2 (S3Q9) = 0, 6, 7 AND
[LAST_MD (S9Q10) = 1, 2 OR
LAST_MED (S3Q11) ≥ 1 AND ≤ 5 OR
LASTSYMP (S3Q12) ≥ 1 AND ≤ 5],
CONTINUE.
IF BOTH AN ADULT AND CHILD WERE SAMPLED, COMPLETE DETAILED INTERVIEWS FOR BOTH,
BUT ASK HOUSEHOLD-LEVEL QUESTIONS ONLY FOR THE FIRST INTERVIEW COMPLETED.
SYMP_30D (S4Q1)
IF LASTSYMP (S3Q12) = 0 OR ≥ 5 AND ≤ 7, SKIP TO SECTION 3.
IF LASTSYMP (S3Q12) = 4, SKIP TO EPIS_INT.
During the past 30 days, how many days did {you/[the (AGE) year old/NAME]} have any symptoms of asthma?
__ __
(0)
(30)
(96)
(97)
DAYS (1–29)
NO SYMPTOMS IN THE PAST 30 DAYS
EVERY DAY
DON’T KNOW
REFUSED
[SKIP TO ASLEEP30 (S4Q3)]
[SKIP TO EPIS_INT]
[SKIP TO ASLEEP30 (S4Q3)]
[SKIP TO ASLEEP30 (S4Q3)]
DUR_30D (S4Q2) {Do you/Does [the (AGE) year old/NAME]} have symptoms all the time?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘ALL THE TIME’’ MEANS SYMPTOMS THAT CONTINUE THROUGHOUT THE DAY. IT
DOES NOT MEAN SYMPTOMS FOR A LITTLE WHILE EACH DAY.
ASLEEP30 (S4Q3)
During the past 30 days, on how many days did symptoms of asthma make it difficult for {you/[the (AGE) year
old/NAME]} to stay asleep?
__ __
(0)
(96)
(97)
DAYS/NIGHTS
NONE
DON’T KNOW
REFUSED
SYMPFREE (S4Q4) [IF SYMP_30D = 30, SKIP TO EPIS_INT.] During the past two weeks, on how many days {were you/was [the
(AGE) year old/NAME]} completely symptom-free, that is no coughing, wheezing, or other symptoms of
asthma?
__ __ NUMBER OF DAYS
(96) DON’T KNOW
(97) REFUSED
INTRODUCTORY STATEMENT
READ: Asthma attacks, sometimes called episodes, refer to periods of worsening asthma symptoms that make {you
limit your/limit [the (AGE) year old/NAME]’s} activity more than {you usually do/[he/she] usually does}, or make
{you/him/her} seek medical care. [CONTINUE]
Series 1, No. 46 [ Page 85
EPIS_12M (S4Q5)
During the past 12 months, {have you/has [the (AGE) year old/NAME]} had an episode of asthma or an asthma
attack?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
[SKIP TO INS1 (S5Q1_A)]
HELP SCREEN: (ADD TO ALL QUESTIONS THAT REFER TO ‘‘ASTHMA ATTACKS OR EPISODES’’)
Asthma attacks, sometimes called episodes, refer to periods of worsening asthma symptoms that make {you limit
your/limit [the (AGE) year old/NAME]’s} activity more than [you usually do/(he/she) usually does], or make
(you/him/her) seek medical care.
EPIS_TP (S4Q6)
During the past 3 months, how many asthma episodes or attacks {have you/has [the (AGE) year old/NAME]}
had?
__ __
(0)
(996)
(997)
DUR_ASTH (S4Q7)
ATTACKS OR EPISODES DURING PAST 3 MONTHS
NONE
DON’T KNOW
REFUSED
How long did {your/[the (AGE) year old/NAME]’s} most recent asthma episode or attack last?
ENTER AMOUNT
__ __
(96) DON’T KNOW
(97) REFUSED
DUR2ASTH (S4Q8)
(1)
(2)
(3)
(4)
(6)
(7)
ENTER PERIOD
MINUTES
HOURS
DAYS
WEEKS
DON’T KNOW
REFUSED
COMPASTH (S4Q9)
(1)
(2)
(3)
(4)
(6)
(7)
[SKIP TO COMPASTH (S4Q9)]
[SKIP TO COMPASTH (S4Q9)]
Compared with other episodes or attacks, was this most recent attack shorter, longer, or about the same?
SHORTER
LONGER
ABOUT THE SAME
THE MOST RECENT ATTACK WAS ACTUALLY THE FIRST ATTACK
DON’T KNOW
REFUSED
Section 3. Health Care Utilization
INS1 (S5Q1_A)
{Do you/[Does the (AGE) year old/NAME]} have any kind of health care coverage, including health insurance,
prepaid plans such as HMOs, or government plans such as Medicare or Medicaid?
(0)
(1)
(6)
(7)
INS2 (S5Q1_B)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO NER_TIME (S5Q1)]
[SKIP TO NER_TIME (S5Q1)]
[SKIP TO NER_TIME (S5Q1)]
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months], was there any time that
{you/[the (AGE) year old/NAME]} did not have any health insurance or coverage?
(0)
(1)
(6)
(7)
NER_TIME (S5Q1)
NO
YES
DON’T KNOW
REFUSED
[IF LAST_MD (S3Q10) = 0, 2, 3, OR 4, SKIP TO MISS_DAY (S5Q9).] [IF
R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months], how many times did
{you/[the (AGE) year old/NAME]} see a doctor or other health professional for a routine checkup for
(your/his/her) asthma?
__ __
(0)
(996)
(997)
__ ENTER NUMBER
NONE
DON’T KNOW
REFUSED
Page 86 [ Series 1, No. 46
ER_VISIT (S5Q2) [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months], {have you/has [the
(AGE) year old/NAME]} had to visit an emergency room or urgent care center because of (your/his/her) asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO URG_TIME (S5Q4)]
[SKIP TO URG_TIME (S5Q4)]
[SKIP TO URG_TIME (S5Q4)]
HELP SCREEN: An urgent care center treats people with illnesses or injuries that must be addressed immediately
and cannot wait for a regular medical appointment.
ER_TIMES (S5Q3)
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months’’], how many times did
{you/[the (AGE) year old/NAME]} visit an emergency room or urgent care center because of (your/his/her)
asthma?
__ __ __ ENTER NUMBER
(996) DON’T KNOW
(997) REFUSED
HELP SCREEN: An urgent care center treats people with illnesses or injuries that must be addressed immediately
and cannot wait for a regular medical appointment.
URG_TIME (S5Q4)
[IF ER_TIMES (S5Q3) > 0, INSERT: ‘‘Besides those emergency room or urgent care
center visits,’’] [IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months], how
many times did {you/[the (AGE) year old/NAME]} see a doctor or other health professional for urgent
treatment of worsening asthma symptoms or an asthma episode or attack?
__ __ __ ENTER NUMBER
(0)
NONE
(996) DON’T KNOW
(997) REFUSED
HELP SCREEN: An urgent care center treats people with illnesses or injuries that must be addressed immediately
and cannot wait for a regular medical appointment.
HOSP_VST (S5Q5)
(0)
(1)
(6)
(7)
HOSPTIME (S5Q6)
[IF LASTSYMP (S3Q12) = 0 OR > 5 AND < 7, SKIP TO MISS_DAY (S5Q9).] [IF R_DOB (S2Q5) = 0, FILL:
‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months, that is since (1 YEAR AGO TODAY)], {have you/has
[the (AGE) year old/NAME]} had to stay overnight in a hospital because of (your/his/her) asthma? Do not
include an overnight stay in the emergency room.
NO
YES
DON’T KNOW
REFUSED
[SKIP TO MISS_DAY (S5Q9)]
[SKIP TO MISS_DAY (S5Q9)]
[SKIP TO MISS_DAY (S5Q9)]
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months’’], how many different
times did {you/[the (AGE) year old/NAME]} stay in any hospital overnight or longer because of (your/his/her)
asthma?
__ __ __ TIMES
(996) DON’T KNOW
(997) REFUSED
HOSPPLAN (S5Q8)
(0)
(1)
(6)
(7)
The last time {you/[the (AGE) year old/NAME]} left the hospital, did a health professional talk with
{you/(AGE) year old/NAME] or [the (AGE) year old/NAME] parents or guardians} about how to better
control (your/his/her) asthma to prevent serious episodes or attacks and hospitalizations in the future?
NO
YES
DON’T KNOW
REFUSED
[SKIP THIS QUESTION IF INTERVIEW IS FOR SAMPLED CHILD (S2Q5< 18).]
MISS_DAY (S5Q9) During the past 12 months, how many days were you unable to work or carry out your usual activities because
of your asthma?
__ __ __ENTER NUMBER DAYS
(0) ZERO
(996) DON’T KNOW
(997) REFUSED
[SKIP THIS QUESTION IF INTERVIEW IS FOR SAMPLED ADULT (S2Q5 > 17).]
[FOR CHILDREN 0–4, INSERT ‘‘DAYCARE OR PRESCHOOL’’ IN FILL.
FOR CHILDREN 5–13, INSERT ‘‘SCHOOL’’ IN FILL.
FOR CHILDREN 14–17, INSERT ‘‘SCHOOL OR WORK’’ IN FILL.]
Series 1, No. 46 [ Page 87
MISS_SCH (S5Q11)
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months, that is since (1 YEAR
AGO TODAY)’’] about how many days of [daycare or preschool/school/ school or work] did [the (AGE) year
old/NAME] miss because of (his/her) asthma?
__ __
(0)
(994)
(995)
(996)
(997)
ACT_DAYS (S5Q12)
(1)
(2)
(3)
(4)
(6)
(7)
__ ENTER NUMBER
ZERO
CHILD DID NOT GO TO SCHOOL IN PAST 12 MONTHS
HOME SCHOOLED
DON’T KNOW
REFUSED
[IF R_DOB (S2Q5) = 0, FILL: ‘‘Since birth,’’/ELSE FILL: ‘‘During the past 12 months,’’ would you say
{you/[the (AGE) year old/NAME]} limited (your/his/her) usual activities due to asthma not at all, a little, a
moderate amount, or a lot?
NOT AT ALL
A LITTLE
A MODERATE AMOUNT
A LOT
DON’T KNOW
REFUSED
Section 4. Knowledge of Asthma/Management Plan
TCH_SIGN (S6Q1)
Has a doctor or other health professional ever taught {you/the (AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian} . . .
a. How to recognize early signs or symptoms of an asthma episode?
(0)
(1)
(6)
(7)
TCH_RESP (S6Q2)
NO
YES
DON’T KNOW
REFUSED
Has a doctor or other health professional ever taught {you/the (AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian} . . .
b. What to do during an asthma episode or attack?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP IF SAMPLED CHILD (R_DOB/S2Q5) < 5 YEARS OLD.]
TCH_MON (S6Q3) Has a doctor or other health professional ever taught {you/the (AGE) year old/NAME] or [the (AGE) year
old/NAME]’s parent or guardian} . . .
c. How to use a peak flow meter, a device that measures how much air you can blow out of your lungs, to adjust
daily medications?
(0)
(1)
(6)
(7)
MGT_PLAN (S6Q4)
(0)
(1)
(6)
(7)
MGT_CLAS (S6Q5)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
An asthma management plan is a printed form that tells when to change the amount or type of medicine, when
to call the doctor for advice, and when to go to the emergency room. Has a doctor or other health professional
EVER given {you/the (AGE) year old/NAME] or [the (AGE) year old/NAME]’s parent or guardian} an
asthma management plan?
[READ IF NECESSARY: Include nurses and asthma educators]
NO
YES
DON’T KNOW
REFUSED
Have {you/the (AGE) year old/NAME] or [the (AGE)year old/NAME]’s parent or guardian} ever taken a
course or class on how to manage (your/his/her) asthma?
NO
YES
DON’T KNOW
REFUSED
Page 88 [ Series 1, No. 46
Section 5. Modifications to Environment
IF CUR_AST2 = 0, 6, 7 AND
LAST_MD (S3Q10) = 0 > 2 AND
LAST_MED (S3Q11) = 0 OR > 5 AND
LASTSYMP (S3Q12) = 0 OR > 5,
ASK HH_INT THROUGH S_INSIDE (S7Q10), CIGARETS (S7Q18) THROUGH UNEMP_R (S7Q22). THEN,
SKIP TO SECTION 6 [OTC (S8Q1) THROUGH INHALERH (S8Q3), IF APPLICABLE.
QUESTIONS HH_INT THROUGH S_INSIDE (S7Q10) ARE HOUSEHOLD-LEVEL
QUESTIONS AND SHOULD BE ASKED ONLY ONCE IN A HOUSEHOLD.
QUESTIONS MOD_ENV (S7Q11) THROUGH UNEMP_R (S7Q22) ARE INDIVIDUAL-LEVEL
QUESTIONS AND SHOULD BE ASKED OF (OR ABOUT) EACH PERSON WITH ASTHMA.
INTRODUCTORY STATEMENT
READ: The following questions are about {your/[the (AGE) year old/NAME]’s} household and living environment.
I will be asking about various things that may be related to experiencing asthma symptoms. [CONTINUE]
AIRCLEANER (S7Q1)
(0)
(1)
(6)
(7)
Is an air cleaner or purifier regularly used inside your home?
NO
YES
DON’T KNOW
REFUSED
DEHUMID (S7Q2) Is a dehumidifier regularly used to reduce moisture inside your home?
(0)
(1)
(6)
(7)
KITC_FAN (S7Q3)
(0)
(1)
(6)
(7)
COOK_GAS (S7Q4)
(0)
(1)
(6)
(7)
ENV_MOLD (S7Q5)
(0)
(1)
(6)
(7)
ENV_PETS (S7Q6)
(0)
(1)
(6)
(7)
C_ROACH (S7Q7)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?
NO
YES
DON’T KNOW
REFUSED
Is gas used for cooking?
NO
YES
DON’T KNOW
REFUSED
In the past 30 days, has anyone seen or smelled mold or a musty odor inside your home? Do not include mold
on food.
NO
YES
DON’T KNOW
REFUSED
Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets that
are kept inside?
NO
YES
DON’T KNOW
REFUSED
In the past 30 days, has anyone seen cockroaches inside your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: Studies have shown that cockroaches are a leading cause of asthma in children that live in urban
areas. Cockroach droppings and carcasses can cause children to experience symptoms of asthma.
Series 1, No. 46 [ Page 89
WOOD_STOVE (S7Q8)
(0)
(1)
(6)
(7)
Is a fireplace or wood burning stove used in your home?
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: OCCASIONAL USE SHOULD BE CODED AS ‘‘YES.’’
GAS_STOVE (S7Q9)
Are unvented gas logs, an unvented gas fireplace, or an unvented gas stove used in your home?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Unvented’’ means no chimney.
S_INSIDE (S7Q10)
In the past week, has anyone smoked inside your home?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: ‘‘Smoked’’ means ‘‘anything.’’
MOD_ENV (S7Q11)
FOR ADULT INTERVIEW, READ: [FILL ONLY IF QUESTIONS HH_INT THROUGH S_INSIDE WERE
ASKED OF THIS RESPONDENT]: Now, back to questions specifically about you. Has a health professional
ever advised you to change things in your home, school, or work to improve your asthma?
FOR CHILD INTERVIEW, READ: [FILL ONLY IF QUESTIONS HH_INT THROUGH S_INSIDE WERE
ASKED OF THIS RESPONDENT]: Now, back to questions specifically about [the (AGE) year old/NAME].
Has a health professional ever advised you to change things in [the (AGE) year old/NAME]’s home, school, or
work to improve [the (AGE) year old/NAME]’s asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
MATTRESS (S7Q12)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
E_PILLOW (S7Q13)
(0)
(1)
(6)
(7)
CARPET (S7Q14)
{Do you/Does [the (AGE) year old/NAME]} use a pillow cover that is made especially for controlling dust
mites?
NO
YES
DON’T KNOW
REFUSED
Do you have carpeting or rugs in {your/[the (AGE) year old/NAME]’s} bedroom?
(0)
(1)
(6)
(7)
HOTWATER (S7Q15)
(1)
(2)
(3)
(6)
(7)
{Do you/Does [the (AGE) year old/NAME]} use a mattress cover that is made especially for controlling dust
mites?
NO
YES
DON’T KNOW
REFUSED
Are {your/[the (AGE) year old/NAME]’s} sheets and pillowcases washed in cold, warm, or hot water?
COLD
WARM
HOT
DON’T KNOW
REFUSED
Page 90 [ Series 1, No. 46
BATH_FAN (S7Q16)
In {your/[the (AGE) year old/NAME]’s} bathroom, {Do you/does [the (AGE) year old/NAME]} regularly
use an exhaust fan that vents to the outside?
(0)
(1)
(6)
(7)
NO OR ‘‘NO FAN’’
YES
DON’T KNOW
REFUSED
HELP SCREEN: IF RESPONDENT INDICATES THEY HAVE MORE THAN ONE BATHROOM, THIS
QUESTION REFERS TO THE BATHROOM THEY USE MOST FREQUENTLY FOR SHOWERING AND
BATHING.
[SKIP THIS QUESTION IF ENV_PETS = 0, 6, 7.
PETBEDRM (S7Q17) Is the pet allowed in {your/[the (AGE) year old/NAME]’s} bedroom?
(0)
(1)
(2)
(6)
(7)
NO
YES
SOME ARE/SOME AREN’T
DON’T KNOW
REFUSED
SKIP TO SECTION 6 IF INTERVIEW IS FOR SAMPLED CHILD (R_DOB/S2Q5 < 18).
CIGARETS (S7Q18)
Have you smoked at least 100 cigarettes in your entire life?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
CIG_FREQ (S7Q19)
[SKIP TO EMP_STAT (S7Q20)]
[SKIP TO EMP_STAT (S7Q20)]
Do you now smoke cigarettes every day, some days or not at all?
(1)
(2)
(3)
(6)
(7)
EVERY DAY
SOME DAYS
NOT AT ALL
DON’T KNOW
REFUSED
EMP_STAT (S7Q20)
We are interested in things that affect asthma in the workplace. However, first I’d like to ask how you would
describe your current employment status. Would you say . . .
(1)
(2)
(3)
(6)
(7)
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
DON’T KNOW
REFUSED
WORKENV2 (S7Q21)
(0)
(1)
(2)
(6)
(7)
Was your asthma caused or made worse by chemicals, smoke, fumes, or dust in any job you ever had?
NO
YES
NEVER BEEN EMPLOYED
DON’T KNOW
REFUSED
UNEMP_R (S7Q22)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(96)
(97)
[SKIP TO EMP_STAT (S7Q20)]
[IF EMP_STAT (S7Q20) = 1 OR 2, SKIP TO OTC (S8Q1).] What is the main reason you are not employed?
KEEPING HOUSE
GOING TO SCHOOL
RETIRED
DISABLED
UNABLE TO WORK FOR OTHER HEALTH REASONS
LOOKING FOR WORK
LAID OFF
OTHER
DON’T KNOW
REFUSED
Section 6. Medications
IF LAST_MED (S3Q11) = 0, SKIP TO SECTION 7.
IF CUR_AST2 (S3Q9) = 0, 6, 7, AND
LAST_MD (S3Q10) = 0 OR > 2 AND
LASTSYMP (S3Q12) = 0 OR > 5 AND
LAST_MED (S3Q11) = 6 OR 7,
Series 1, No. 46 [ Page 91
ASK OTC (S8Q1), INHALERE (S8Q2), INHALERH (S8Q3), THEN SKIP TO SECTION 7.
OTC (S8Q1)
Over-the-counter medication can be bought without a doctor’s order. {Have you/Has [the (AGE) year old/NAME]}
ever used over-the-counter medication for (your/his/her) asthma?
(0)
(1)
(6)
(7)
INHALERE (S8Q2)
(0)
(1)
(6)
(7)
INHALERH (S8Q3)
(0)
(1)
(6)
(7)
SCR_MED1 (S8Q4)
NO
YES
DON’T KNOW
REFUSED
{Have you/Has [the (AGE) year old/NAME]} ever used a prescription inhaler?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SCR_MED1 (S8Q4)]
[SKIP TO SCR_MED1 (S8Q4)]
[SKIP TO SCR_MED1 (S8Q4)]
Did a health professional show {you/the (AGE) year old/NAME] or [the (AGE) year old/NAME’s] parents or
guardians} how to use the inhaler?
NO
YES
DON’T KNOW
REFUSED
[IF LAST_MED (S3Q11) = 4, 5, 6, 7, 96, or 97, SKIP TO SECTION 7.] Now I am going to ask questions
about specific prescription medications {you/[the (AGE) year old/NAME]} may have taken for asthma in the
past 3 months. I will be asking for the names, amount, and how often {you take/[the (AGE) year old/NAME]
takes} each medicine. I will ask separately about medication taken in various forms: pill or syrup, inhaler, and
Nebulizer.
It may help to get {your/[the (AGE) year old/NAME]’s} medicines so you can read the labels. Are {your/[the
(AGE) year old/NAME]’s} asthma medicines handy?
(0)
(1)
(2)
(6)
(7)
SCR_MED2 (S8Q5)
(0)
(1)
(8)
(9)
SCR_MED3 (S8Q6)
(0)
(1)
(2)
(6)
(7)
INH_SCR (S8Q7)
(0)
(1)
(6)
(7)
NO
YES
RESPONDENT KNOWS THE MEDS
DON’T KNOW
REFUSED
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
Can you please go get the asthma medicines while I wait on the phone?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO INH_SCR (S8Q7)]
[SKIP TO INH_SCR (S8Q7)]
Am I correct that you have all the medications?
NO
YES, I HAVE ALL THE MEDICATIONS
YES, I HAVE SOME OF THE MEDICATIONS BUT NOT ALL
DON’T KNOW
REFUSED
In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription asthma medicine using an
inhaler?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO PILLS (S8Q27)]
[SKIP TO PILLS (S8Q27)]
[SKIP TO PILLS (S8Q27)]
INH_MEDS (S8Q8_01 to S8Q8_34)
In the past 3 months, what medications did {you/[the (AGE) year old/NAME]} take by inhaler? [MARK ALL
THAT APPLY. PROBE: Any other medications?]
Page 92 [ Series 1, No. 46
INH_MEDS (S8Q8_01 to S8Q8_34)
In the past 3 months, what medications did {you/[the (AGE) year old/NAME]} take by inhaler? [MARK ALL
THAT APPLY. PROBE: Any other medications?]
Variable Name
INH_MEDX01 (S8Q8_01)
INH_MEDX02 (S8Q8_02)
INH_MEDX03 (S8Q8_03)
INH_MEDX04 (S8Q8_04)
INH_MEDX05 (S8Q8_05)
INH_MEDX06 (S8Q8_06)
INH_MEDX07 (S8Q8_07)
INH_MEDX08 (S8Q8_08)
INH_MEDX09 (S8Q8_09)
INH_MEDX10 (S8Q8_10)
INH_MEDX11 (S8Q8_11)
INH_MEDX12 (S8Q8_12)
INH_MEDX13 (S8Q8_13)
INH_MEDX14 (S8Q8_14)
INH_MEDX15 (S8Q8_15)
INH_MEDX16 (S8Q8_16)
INH_MEDX17 (S8Q8_17)
INH_MEDX18 (S8Q8_18)
INH_MEDX19 (S8Q8_19)
INH_MEDX20 (S8Q8_20)
INH_MEDX21 (S8Q8_21)
INH_MEDX22 (S8Q8_22)
INH_MEDX23 (S8Q8_23)
INH_MEDX24 (S8Q8_24)
INH_MEDX25 (S8Q8_25)
INH_MEDX26 (S8Q8_26)
INH_MEDX27 (S8Q8_27)
INH_MEDX28 (S8Q8_28)
INH_MEDX29 (S8Q8_29)
INH_MEDX30 (S8Q8_30)
INH_MEDX31 (S8Q8_31)
INH_MEDX32 (S8Q8_32)
INH_MEDX33 (S8Q8_33)
INH_MEDX34 (S8Q8_34)
Brand Name
Type (not shown in CATI)
Advair
Aerobid
Corticosteroids
Albuterol
Beta 2 agonist
Alupent
Beta 2 agonist
Atrovent
Anti-inflammatories
Azmacort
Corticosteroids
Beclomethasone dipropionate
Corticosteroids
Beclovent
Corticosteroids
Bitolterol
Beta 2 agonist
Brethaire
Beta 2 agonist
Budesonide
Corticosteroids
Combivent
Cromolyn
Anti-inflammatories
Flovent
Inhaled corticosteroid
Flovent Rotadisk
Inhaled corticosteroid
Flunisolide
Corticosteroids
Fluticasone
Inhaled corticosteroid
Intal
Anti-inflammatories
Ipratropium Bromide
Anti-inflammatories
Maxair
Beta 2 agonist
Metaproteronol
Beta 2 agonist
Nedocromil
Anti-inflammatories
Pirbuterol
Beta 2 agonist
Proventil
Beta 2 agonist
Pulmicort Turbuhaler
Corticosteroids
Salmeterol
Corticosteroids (long lasting)
Serevent
Beta 2 agonist (long lasting)
Terbutaline
Beta 2 agonist
Tilade
Anti-inflammatories
Tornalate
Beta 2 agonist
Triamcinolone acetonide
Corticosteroids
Vanceril
Corticosteroids
Ventolin
Beta 2 agonist
Other, please specify
[SKIP TO OTH_I1 (S8Q8_34A)]
IF ANY ANSWER SELECTED FROM INH_MEDX01 (S8Q8_01)–INH_MEDX33 (S8Q8_33), SKIP TO ILP01
(S8Q16_nn).
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO REC_MED1]
[SKIP TO PILLS (S8Q27)]
OTH_I1 (S8Q8_34A)
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
_____________________ ENTER TEXT
INTRODUCTORY STATEMENT
READ: I’m going to read a list of medicines to see if you recognize the name of any of the medications {you
have/[CHILD’S NAME] has} taken. Please let me know if you hear the name. [CONTINUE]
DK1INHLR (S8Q9)
(0)
(1)
(6)
(7)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take Flovent or Flovent Rotadisk using an
inhaler?
NO
YES
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 93
DK2INHLR (S8Q10)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Beclovent, Vanceril, Beclomethasone dipropionate,
Pulmicort Turbuhaler, Budesonide,
Aerobid, Flunisolide,
Azmacort, or Triamcinolone acetonide?
(0)
(1)
(6)
(7)
DK3INHLR (S8Q11)
(0)
(1)
(6)
(7)
DK4INHLR (S8Q12)
(0)
(1)
(6)
(7)
DK5INHLR (S8Q13)
(0)
(1)
(6)
(7)
DK6INHLR (S8Q14)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Ventolin, Proventil, Albuterol,
Alupent, Metaproteronol,
Tornalate, Bitolterol,
Maxair, Pirbuterol,
Brethaire, Terbutaline, or
Serevent?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Intal, Cromolyn,
Tilade, or Nedocromil?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, did {you/[the (AGE) year old/NAME]} take:
Atrovent or Ipratropium Bromide?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication by inhaler that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO DK7INHLR (S8Q15)]
IF DK6INHLR (S8Q14) = 1, CONTINUE. ALL OTHERS, SKIP TO ILP01 (S8Q16_nn).
DK7INHLR (S8Q15)
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
REPEAT ILP01 (S8Q16_nn)–ILP11 (S8Q26_nn) FOR EACH MEDICINE REPORTED IN INH_MEDS
(S8Q8_nn), OR IF AN ANSWER OF (1) ‘‘YES’’ IS GIVEN FOR ANY ITEM IN DK1INHLR (S8Q9) THROUGH
DK7INHLR (S8Q15). IF AN ANSWER OF (1) ‘‘YES’’ IS PROVIDED DURING QUESTIONS DK1INHLR
(S8Q9) THROUGH DK6INHLR (S8Q15), USE THE PHRASE ‘‘THIS MEDICATION’’ FOR FILL ‘‘[MEDICINE
FROM INH_MEDS (S8Q8_nn) SERIES]’’ FOR QUESTIONS ILP01 (S8Q16_nn) THROUGH ILP11 (S8Q26_nn).
ILP01 (S8Q16_01 to S8Q16_34)
How long {have you/has [the (AGE) year old/NAME]} been taking [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES]? Would you say less than 6 months, 6 months to 1 year, or longer than 1 year?
(1)
(2)
(3)
(6)
(7)
LESS THAN 6 MONTHS
6 MONTHS TO 1 YEAR
LONGER THAN 1 YEAR
DON’T KNOW
REFUSED
Page 94 [ Series 1, No. 46
ILP02 (S8Q17_01 to S8Q17_34)
A spacer is a small attachment for an inhaler that makes it easier to use. {Do you/Does [the (AGE) year
old/NAME]} use a spacer with [MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]?
0) NO
(1) YES
(6) DON’T KNOW
(7) REFUSED
HELP SCREEN: A spacer is a device that attaches to a metered dose inhaler. It holds the medicine in its
chamber long enough for you to inhale it in one or two slow, deep breaths. The spacer makes it easy to take the
medicines the right way, especially for young children.
ASK IF INH_MEDS (S8Q8_nn) = 03, 04, 09, 10, 20, 21, 23, 24, 28, 30, 33, OR DK3INHLR (S8Q11) = 1;
ELSE, SKIP TO ILP06 (S8Q21_nn).
ILP03 (S8Q18_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES] when {you/he/she had} an asthma episode or attack?
(0)
(1)
(2)
(6)
(7)
NO
YES
NO ATTACK IN PAST 3 MONTHS
DON’T KNOW
REFUSED
ILP04 (S8Q19_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
[IF THE AGE OF THE CHILD IS LESS THAN 6 YEARS (S2Q5 < 6), SKIP TO ILP05 (S8Q20_nn).] In the past
3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]
before exercising?
(0)
(1)
(2)
(6)
(7)
NO
YES
DIDN’T EXERCISE IN PAST 3 MONTHS
DON’T KNOW
REFUSED
ILP05 (S8Q20_03, _04, _09, _10, _20, _21, _23, _24, _28, _30, _33, _34)
In the past 3 months, did {you/[the (AGE) year old/NAME]} take [MEDICINE FROM INH_MEDS (S8Q8_nn)
SERIES] on a regular schedule everyday?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
ASK IF INH_MEDS (S8Q8_nn) = 14, 15, 17, OR DK1_INHLR (S8Q9) = 1;
ELSE SKIP TO ILP07 (S8Q22_nn).
ILP06 (S8Q21_14, _15, _17, _34)
Is the dosage 44, 50, 100, 110, 220, or 250 micrograms for the Flovent?
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(96)
(97)
44 MICROGRAMS
50 MICROGRAMS
100 MICROGRAMS
110 MICROGRAMS
220 MICROGRAMS
250 MICROGRAMS
TOOK MORE THAN 1 IN PAST 3 MONTHS
DON’T KNOW
REFUSED
ILP07 (S8Q22_01 to S8Q22_34)
On average, how many puffs {Do you/does [the (AGE) year old/NAME]} take each time {you use/he uses/she uses}
[MEDICINE FROM INH_MEDS (S8Q8_nn) SERIES]?
__ __ PUFFS EACH TIME
(96) DON’T KNOW
(97) REFUSED
INTERVIEWER: PROBE FOR NUMBER OF PUFFS IF RANGE IS GIVEN.
Series 1, No. 46 [ Page 95
ILP09 (S8Q24_01 to S8Q24_34)
How many times per day or per week {Do you/does [the (AGE) year old/NAME]} use [MEDICINE FROM
INH_MEDS (S8Q8_nn) SERIES]?
__ __ __ TIMES
(994) LESS OFTEN THAN ONCE A WEEK
(996) DON’T KNOW
(997) REFUSED
[SKIP TO ILP11 (S8Q26_nn)]
[SKIP TO ILP11 (S8Q26_nn)]
[SKIP TO ILP11 (S8Q26_nn)]
ILP10 (S8Q25_01 to S8Q25_34)
ENTER PERIOD
(1)
(2)
(6)
(7)
PER DAY
PER WEEK
DON’T KNOW
REFUSED
ILP11 (S8Q26_01 to S8Q26_34)
How many full canisters of this inhaler {have you /has [the (AGE) year old/NAME]} used in the past 3 months?
[INTERVIEWER: IF RESPONDENT USED LESS THAN ONE CANISTER IN THE PAST 3 MONTHS,
CODE IT AS ‘00’]
___ CANISTERS
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: IF RESPONDENT INDICATES HE/SHE HAS MULTIPLE CANISTERS, (I.E., ONE IN THE
CAR, ONE IN PURSE, ETC.) ASK THE RESPONDENT TO ESTIMATE HOW MANY CANISTERS HE/SHE
USED.
PILLS (S8Q27)
In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken any medicine in pill form for your/his/her
asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SYRUP (S8Q38)]
[SKIP TO SYRUP (S8Q38)]
[SKIP TO SYRUP (S8Q38)]
PILLS_MD (S8Q28_01 to S8Q28_48)
What medications {Do you/does [the (AGE) year old/NAME]} take in pill form?
[MARK ALL THAT APPLY. PROBE: Any other medications?]
Variable names
PILLS_MX01 (S8Q28_01)
PILLS_MX02 (S8Q28_02)
PILLS_MX03 (S8Q28_03)
PILLS_MX04 (S8Q28_04)
PILLS_MX05 (S8Q28_05)
PILLS_MX06 (S8Q28_06)
PILLS_MX07 (S8Q28_07)
PILLS_MX08 (S8Q28_08)
PILLS_MX09 (S8Q28_09)
PILLS_MX10 (S8Q28_10)
PILLS_MX11 (S8Q28_11)
PILLS_MX12 (S8Q28_12)
PILLS_MX13 (S8Q28_13)
PILLS_MX14 (S8Q28_14)
PILLS_MX15 (S8Q28_15)
PILLS_MX16 (S8Q28_16)
PILLS_MX17 (S8Q28_17)
PILLS_MX18 (S8Q28_18)
PILLS_MX19 (S8Q28_19)
PILLS_MX20 (S8Q28_20)
PILLS_MX21 (S8Q28_21)
PILLS_MX22 (S8Q28_22)
PILLS_MX23 (S8Q28_23)
PILLS_MX24 (S8Q28_24)
PILLS_MX25 (S8Q28_25)
PILLS_MX26 (S8Q28_26)
PILLS_MX27 (S8Q28_27)
PILLS_MX28 (S8Q28_28)
PILLS_MX29 (S8Q28_29)
Medication
Accolate
Aerolate
Albuterol
Alupent
Choledyl
Cromolyn
Deltasone
Elixophyllin
Intal
Marax
Medrol
Metaprel
Metaproteronol
Methylpredinisolone
Montelukast
Nedocromil
Pediapred
Prednisolone
Prednisone
Prelone
Proventil
Quibron
Respid
Singulair
Slo-phyllin
Slo-bid
Sustaire
Theo-24
Theobid
Type (not shown in CATI)
Leukotriene modifiers
Methylxanthines
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Methylxanthines
Anti-inflammatories
Corticosteriods
Methylxanthines
Anti-inflammatories
Methylxanthines
Corticosteriods
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Corticosteriods
Leukotriene modifiers
Corticosteriods
Corticosteriods
Corticosteriods
Corticosteriods
Corticosteriods
Beta 2 agonist – Rescue bronchodilators
Methylxanthines
Methylxanthines
Leukotriene modifiers
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Page 96 [ Series 1, No. 46
PILLS_MX30
PILLS_MX31
PILLS_MX32
PILLS_MX33
PILLS_MX34
PILLS_MX35
PILLS_MX36
PILLS_MX37
PILLS_MX38
PILLS_MX39
PILLS_MX40
PILLS_MX41
PILLS_MX42
PILLS_MX43
PILLS_MX44
PILLS_MX45
PILLS_MX46
PILLS_MX47
PILLS_MX47
(S8Q28_30)
(S8Q28_31)
(S8Q28_32)
(S8Q28_33)
(S8Q28_34)
(S8Q28_35)
(S8Q28_36)
(S8Q28_37)
(S8Q28_38)
(S8Q28_39)
(S8Q28_40)
(S8Q28_41)
(S8Q28_42)
(S8Q28_43)
(S8Q28_44)
(S8Q28_45)
(S8Q28_46)
(S8Q28_47)
(S8Q28_48)
Theochron
Theoclear
Theodur
Theo-Dur
Theolair
Theophylline
Theo-Sav
Theospan
Theox
Tilade
T-Phyl
Unidur
Uniphyl
Ventolin
Volmax
Zafirlukast
Zileuton
Zyflo Filmtab
Other, please specify:
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Methylxanthines
Corticosteriods
Methylxanthines
Methylxanthines
Methylxanthines
Beta 2 agonist – Rescue bronchodilators
Beta 2 agonist – Rescue bronchodilators
Leukotriene modifiers
Leukotriene modifiers
Leukotriene modifiers
[SKIP TO OTH_P1 (S8Q29)]
IF ANY ANSER SELECTED FROM PILLS_MX01 (S8Q28_01)–PILLS_MX47 (S8Q28_47), SKIP TO PILLX
(S8Q37_nn).
(0)
(1)
(6)
(7)
OTH_P1 (S8Q29)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO REC_MED2]
[SKIP TO SYRUP (S8Q38)]
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
REC_MED2 READ: I’m going to read a list of medicines to see if you recognize the name of the medications {you have/[CHILD’S
NAME] has} taken within the past 3 months. If you recognize any that were taken, please let me know.
[CONTINUE]
DK1_PILL (S8Q30)
(0)
(1)
(6)
(7)
DK2_PILL (S8Q31)
(0)
(1)
(6)
(7)
DK3_PILL (S8Q32)
(0)
(1)
(6)
(7)
Did {you/[the (AGE) year old/NAME]} take:
Accolate or Zafirlukast
Zyflo Filmtab or Zileuton
Singulair or Montelukast?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Intal or Cromolyn
Tilade or Nedocromil?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Medrol, Methylpredinisolone,
Deltasone, Prednisone,
Pediapred,
Prelone, or Prednisolone?
NO
YES
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 97
DK4_PILL (S8Q33)
(0)
(1)
(6)
(7)
DK5_PILL (S8Q34)
(0)
(1)
(6)
(7)
DK6_PILL (S8Q35)
(0)
(1)
(6)
(7)
DK7_PILL (S8Q36)
Did {you/[the (AGE) year old/NAME]} take:
Proventil, Ventolin, Volmax, or Albuterol
Alupent, Metaprel, or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take:
Theophylline, Elixophyllin, Theo-Dur, choledyl, Theo-Sav, Theospan, Theoclear, T-Phyl, Theodur, Unidur,
Uniphyl, Aerolate, Theox, Marax, Theobid, Quibron, Theo-24, Sustaire, Slo-phyllin, Slo-bid, Respid,
Theochron, or Theolair?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication in pill form that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO PILLX (S8Q37_nn)]
[SKIP TO DK7_PILL (S8Q36)]
[SKIP TO PILLX (S8Q37_nn)]
[SKIP TO PILLX (S8Q37_nn)]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
REPEAT PILLX (S8Q37_nn) FOR EACH PILL REPORTED IN PILLS_MD (S8Q28_nn), OR IF AN ANSWER
OF (1) ‘‘YES’’ IS GIVEN FOR QUESTIONS DK1_PILL (S8Q30) THROUGH DK6_PILL (S8Q35). IF AN
ANSWER OF (1) ‘‘YES’’ IS PROVIDED DURING QUESTIONS DK1_PILL (S8Q30) THROUGH DK6_PILL
(S8Q35), USE THE PHRASE ‘‘THIS MEDICATION’’ FOR FILL ‘‘[MEDICATION LISTED IN PILLS_MD
(S8Q28_nn)]’’ FOR QUESTION PILLX (S8Q37_nn).
PILLX (S8Q37_01 TO S8Q37_48)
How long {have you/has [the (AGE) year old/NAME]} been taking [MEDICATION LISTED IN PILLS_MD
(S8Q28_nn)]?
(1)
(2)
(3)
(6)
(7)
SYRUP (S8Q38)
LESS THAN 6 MONTHS
6 MONTHS TO 1 YEAR
LONGER THAN 1 YEAR
DON’T KNOW
REFUSED
In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription medicine in syrup form?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
SYRUP_ID (S8Q39_01 to S8Q39_11)
What prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
[MARK ALL THAT APPLY. PROBE: Any other medications?]
Variable names
SYRUP_IX01 (S8Q39_01)
SYRUP_IX02 (S8Q39_02)
SYRUP_IX03 (S8Q39_03)
SYRUP_IX04 (S8Q39_04)
SYRUP_IX05 (S8Q39_05)
SYRUP_IX06 (S8Q39_06)
SYRUP_IX07 (S8Q39_07)
SYRUP_IX08 (S8Q39_08)
SYRUP_IX09 (S8Q39_09)
SYRUP_IX10 (S8Q39_10)
SYRUP_IX11 (S8Q39_11)
Medication
Aerolate
Albuterol
Alupent
Metaproteronol
Prednisolone
Prelone
Proventil
Slo-Phyllin
Theophylline
Ventolin
Other, please specify: [SKIP TO OTH_S1 (S8Q40)]
Page 98 [ Series 1, No. 46
IF ANY ANSWER SELECTED FROM SYRUP_IX01 (S8Q39_01)–SYRUP_IX10 (S8Q39_10), SKIP TO
NEB_SCR (S8Q47).
(0)
(1)
(6)
(7)
OTH_S1 (S8Q40)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO REC_MED3]
[SKIP TO NEB_SCR (S8Q47)]
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
REC_MED3
READ: I’m going to read a list of medicines to see if you recognize the name of the medications {you have/[CHILD’S
NAME] has} taken within the past 3 months. [CONTINUE]
DK1_SYRP (S8Q41)
(0)
(1)
(6)
(7)
DK2_SYRP (S8Q42)
(0)
(1)
(6)
(7)
DK3_SYRP (S8Q43)
(0)
(1)
(6)
(7)
DK4_SYRP (S8Q44)
(0)
(1)
(6)
(7)
DK5_SYRP (S8Q45)
(0)
(1)
(6)
(7)
DK6_SYRP (S8Q46)
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Alupent or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Ventolin or Proventil or Albuterol?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Aerolate, Slo-Phyllin, or Theophylline?
NO
YES
DON’T KNOW
REFUSED
Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?
Prelone or Prednisolone?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication in syrup form that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
[SKIP TO NEB_SCR (S8Q47)]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
NEB_SCR (S8Q47)
(0)
(1)
(6)
(7)
A nebulizer is a small machine with a tube and facemask or mouthpiece that you breathe through continuously.
In the past 3 months, were any of {your/[the (AGE) year old/NAME]’s} asthma medicines used with a
nebulizer?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
NEB_ID (S8Q48_01 to S8Q48_08)
In the past 3 months, what prescriptions medications {have you/has [the (AGE) year old/NAME]} taken using a
nebulizer?
[MARK ALL THAT APPLY. PROBE: Any other medications?]
Series 1, No. 46 [ Page 99
Variable names
NEB_IDX01 (S8Q48_01)
NEB_IDX02 (S8Q48_02)
NEB_IDX03 (S8Q48_03)
NEB_IDX04 (S8Q48_04)
NEB_IDX05 (S8Q48_05)
NEB_IDX06 (S8Q48_06)
NEB_IDX07 (S8Q48_07)
NEB_IDX08 (S8Q48_08)
Medication
Albuterol
Alupent
Cromolyn
Intal
Metaproteronol
Proventil
Ventolin
Other, please specify: [SKIP TO OTH_N1 (S8Q49)]
IF AN ANSWER SELECTED FROM NEB_IDX01 (S8Q48_01)–NEB_IDX07 (S8Q48_07), SKIP TO SECTION 9.
(0)
(1)
(6)
(7)
OTH_N1 (S8Q49)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO DK1_NEB (S8Q50)]
[SKIP TO SECTION 7]
ENTER OTHER MEDICATION.
IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.
________________________ ENTER TEXT
DK1_NEB (S8Q50)
(0)
(1)
(6)
(7)
DK2_NEB (S8Q51)
(0)
(1)
(6)
(7)
DK3_NEB (S8Q52)
(0)
(1)
(6)
(7)
DK4_NEB (S8Q53)
(0)
(1)
(6)
(7)
DK5_NEB (S8Q54)
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Alupent or Metaproteronol?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Ventolin, Proventil or Albuterol?
NO
YES
DON’T KNOW
REFUSED
In the past 3 months, which of these prescriptions medications {have you/has [the (AGE) year old/NAME]}
taken using a nebulizer?
Intal or Cromolyn?
NO
YES
DON’T KNOW
REFUSED
Did {you/[the (AGE) year old/NAME]} take a medication using a nebulizer that we have not mentioned?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
[SKIP TO SECTION 7]
Will you please tell me what that medication was?
SPELL OUT: _____________________________________
Section 7. Family History of Asthma
BRO_N (S9Q1)
How many biological brothers [have you/has the (AGE) year old] ever had?
__ __NUMBER
(0) NONE
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
HALF-BROTHERS SHOULD BE INCLUDED.
Page 100 [ Series 1, No. 46
SIS_N (S9Q2)
How many biological sisters [have you/has the (AGE) year old] ever had?
__ __NUMBER
(0) NONE
(96) DON’T KNOW
(97) REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
HALF-SISTERS SHOULD BE INCLUDED.
PARENTS1 (S9Q3)
Were either of [your/the (AGE) year old’s] biological parents ever told they have asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO BROASTH1 (S9Q5)]
[SKIP TO BROASTH1 (S9Q5)]
[SKIP TO BROASTH1 (S9Q5)]
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
PARENTS2 (S9Q4)
Who?
(1)
(2)
(3)
(6)
(7)
FATHER
MOTHER
BOTH
DON’T KNOW
REFUSED
BROASTH1 (S9Q5)
[IF BRO_N (S9Q1) = 0, 96, 97, SKIP TO SISASTH1 (S9Q7). ELSE IF BRO_N (S9Q1) > 1, SKIP TO
BROASTH2 (S9Q6).] IF BRO_N (S9Q1) = 1, ASK: Was {your/the (AGE) year old’s} biological brother ever
told that he had asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
ALL SKIP TO SISASTH1 (S9Q7).
BROASTH2 (S9Q6)
How many of {your/the (AGE) year old’s} biological brothers were ever told they had asthma?
__ _
(0)
(96)
(97)
_NUMBER
ZERO
DON’T KNOW
REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
SISASTH1 (S9Q7)
(0)
(1)
(6)
(7)
[IF SIS_N (S9Q2) = 0, 96, 97, SKIP TO GRANDSCR (S9Q9). ELSE IF SIS_N (S9Q2) > 1, SKIP TO
SISASTH2 (S9Q8).] [IF SIS_N = 1, ASK:] Was {your/the (AGE) year old’s} biological sister ever told that she
had asthma?
NO
YES
DON’T KNOW
REFUSED
ALL SKIP TO GRANDSCR (S9Q9).
SISASTH2 (S9Q8)
How many of {your/the (AGE) year old’s} biological sisters were ever told they had asthma?
__ __
(0)
(96)
(97)
NUMBER
ZERO
DON’T KNOW
REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL PARENTS/SIBLINGS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
PARENTS/SIBLINGS WHO ARE DECEASED SHOULD BE INCLUDED.
Series 1, No. 46 [ Page 101
GRANDSCR (S9Q9)
Were any of {your/the (AGE) year old’s} biological grandparents ever told they had asthma?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO OTHER_T (S11Q1)]
[SKIP TO OTHER_T (S11Q1)]
[SKIP TO OTHER_T (S11Q1)]
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL GRANDPARENTS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
GRANDPARENTS WHO ARE DECEASED SHOULD BE INCLUDED.
GRNDASTH
(S9Q10_01)
(S9Q10_02)
(S9Q10_03)
(S9Q10_04)
Which of {your/the (AGE) year old’s} biological grandparents were told they had asthma?]
MOTHER’S MOTHER
MOTHER’S FATHER
FATHER’S MOTHER
FATHER’S FATHER
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: RESPONDENTS WHO ARE ADOPTED AND DO NOT HAVE ANY HEALTH INFORMATION
REGARDING THEIR BIOLOGICAL GRANDPARENTS SHOULD BE CODED AS ‘‘DON’T KNOW.’’
GRANDPARENTS THAT ARE DECEASED SHOULD BE INCLUDED.
Section 8. Demographic Information
OTHER_T (S11Q1)
[IF THE FIRST ASTHMA DETAILED INTERVIEW HAS BEEN DONE, SKIP TO R_ETH_2 (HISPANIC),
ELSE ASK:] Now, I just have a few more general questions about you and your household. Do you have any
other home phone numbers in addition to (AREA CODE AND TELEPHONE NUMBER CALLED)? Please do
not include cellular phones in your answer.
(0)
(1)
(6)
(7)
SEC_USE (S11Q2)
NO
YES
DON’T KNOW
REFUSED
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
[SKIP TO THIRD_TN (S11Q4)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this second number used only for computer or fax communications?
(0)
(1)
(6)
(7)
THIRD_TN (S11Q4)
(0)
(1)
(6)
(7)
THIRD_USE (S11Q5)
(1)
(2)
(3)
(6)
(7)
THIRD_FAX (S11Q6)
(0)
(1)
(6)
(7)
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this second number for home use only, for business use only, or for both home and business use?
(1)
(2)
(3)
(6)
(7)
SEC_FAX (S11Q3)
[SKIP TO WO_SERVICE (S11Q7)]
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
Do you have a third home phone number in addition to the two you have already told me about? Please do not
include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this third number for home use only, for business use only, or for both home and business use?
HOME ONLY
BUSINESS ONLY
BOTH HOME AND BUSINESS
DON’T KNOW
REFUSED
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
[SKIP TO WO_SERVICE (S11Q7)]
Is this third number used only for computer or fax communications?
NO
YES
DON’T KNOW
REFUSED
Page 102 [ Series 1, No. 46
NUM_PHON
DERIVED. NUMBER OF TELEPHONES FOR HOME USE
WO_SERVICE (S11Q7)
(0)
(1)
(6)
(7)
During the past 12 months, has your household been without telephone service for 1 week or more? Please
do not include cellular phones in your answer.
NO
YES
DON’T KNOW
REFUSED
C11Q21_A (S11Q8)
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
For how long was your household without telephone service in the past 12 months?
(ENTER THE NUMBER, THEN CONTINUE TO THE NEXT SCREEN TO ENTER TIME PERIOD.)
ENTER NUMBER __ __ __
(996) DON’T KNOW
(997) REFUSED
C11Q21 (S11Q9)
ENTER PERIOD
(1)
(2)
(3)
(6)
(7)
NOPHONE
[SKIP TO R_ETH_2 (HISPANIC)]
[SKIP TO R_ETH_2 (HISPANIC)]
DAYS
WEEK(S)
MONTH(S)
DON’T KNOW
REFUSED
DERIVED. NUMBER OF DAYS WITHOUT TELEPHONE SERVICE
R_ETH_2 (HISPANIC) (Are you/Is [the (AGE) year old]) of Hispanic or Latino origin?
(0)
(1)
(6)
(7)
R_RACE2
NO
YES
DON’T KNOW
REFUSED
Now, I’m going to read a list of categories. Please choose one or more of the following categories to describe
(yourself/the (AGE) year old). (Are you/Is the (AGE) year old) White, Black or African-American, American Indian
or Alaska Native, Asian, or Native Hawaiian or Other Pacific Islander?
[MARK ALL THAT APPLY]
(S2Q11_01)
(S2Q11_02)
(S2Q11_03)
(S2Q11_04)
(S2Q11_05)
(S2Q11_06)
(S2Q11_07)
(0)
(1)
(6)
(7)
WHITE
BLACK/AFRICAN-AMERICAN
AMERICAN INDIAN
ALASKA NATIVE
ASIAN
NATIVE HAWAIIAN
PACIFIC ISLANDER
NO
YES
DON’T KNOW
REFUSED
HELP SCREEN: BE SURE TO READ THE ENTIRE QUESTION AS WRITTEN (INCLUDING ALL RESPONSE
CATEGORIES).
RACE INFORMATION IS COLLECTED BY SELF-IDENTIFICATION. IT IS ‘‘WHATEVER RACE YOU
CONSIDER YOURSELF TO BE.’’ DO NOT TRY TO EXPLAIN OR DEFINE ANY OF THE GROUPS.
MULTIPLE RACES MAY BE SELECTED.
RACE
DERIVED. RACE OF HOUSEHOLD MEMBER
RACEARRAY
DERIVED. ARRAY OF RESPONSES TO RACE VARIABLE
R_EDUC (S2Q18)
[IF THE SAMPLED PERSON IS UNDER 5, I.E. R_DOB (S2Q5) < 05, SKIP TO HEIGHT1 (S2Q14_1).] The
next questions are about [your/the (AGE) year old’s] education level. What is the highest level of school that
[you have/the (AGE) year old has] completed?
__
(13)
(14)
(15)
(16)
(17)
(18)
(19)
(96)
(97)
ENTER HIGHEST GRADE COMPLETED (1–12)
GRADUATED HIGH SCHOOL
SOME POST-HIGH SCHOOL, BUT NOT BACHELOR’S DEGREE (B.A.)
COLLEGE GRADUATE—BACHELOR’S DEGREE OR B.A.
SOME GRADUATE OR PROFESSIONAL SCHOOL (WITH OR WITHOUT DEGREE)
PRESCHOOL/HEADSTART
KINDERGARTEN
NO FORMAL SCHOOLING
DON’T KNOW
REFUSED
Series 1, No. 46 [ Page 103
HEIGHT1—FEET
(S2Q14_1)
HEIGHT2—INCHES
(S2Q14_2)
HEIGHT3—CENTIMETERS
(S2Q14_3)
How tall {are you/is [the (AGE) year old]}?
__ __ feet / __ __inches
(96) DON’T KNOW
(97) REFUSED
OR __ __ __centimeters
(996) DON’T KNOW
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE RELATED
TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
HEIGHT
DERIVED. RESPONDENT HEIGHT IN INCHES.
WEIGHT1—POUNDS
(S2Q15_1)
WEIGHT2—KILOGRAMS
(S2Q15_2)
How much {do you/ does the (AGE) year old} weigh?
__ __ __ pounds OR __ __ __kilograms
(996) DON’T KNOW
(997) REFUSED
(996) DON’T KNOW
(997) REFUSED
HELP SCREEN: WE ARE INTERESTED IN LOOKING AT HOW HEIGHT AND WEIGHT MAY BE RELATED
TO ASTHMA FOR PEOPLE WHO DO AND DO NOT HAVE ASTHMA.
WEIGHT
DERIVED. RESPONDENT WEIGHT IN POUNDS.
BIRTHW1—POUNDS
(S2Q16_1)
BIRTHW2—OUNCES
(S2Q16_2)
BIRTHW3—GRAMS
(S2Q16_3)
[ASK BIRTHWT ONLY FOR SAMPLED PERSONS AGE (S2Q5) < 18.] How much did [the (AGE) year old]
weigh at birth?
__ __ pounds /__ __ ounces
(96) DON’T KNOW
(97) REFUSED
BIRTHWEIGHT
OR __ __ __ __ grams
[SKIP TO INC_TOT (S10Q1)]
(9996) DON’T KNOW [SKIP TO BIRTHRF S2Q17]
(9997) REFUSED
[SKIP TO BIRTHRF (S2Q17)]
DERIVED. CHILD’S BIRTHWEIGHT IN GRAMS
BIRTHRF At birth, did [the (AGE) year old/NAME] weigh less than 5 1/2 pounds?
(S2Q17)
[INTERVIEW NOTE: 5 1/2 pounds = 2500 GRAMS]
(0)
(1)
(6)
(7)
INC_TOT (S10Q1)
NO
YES
DON’T KNOW
REFUSED
What was the total combined income of your household in (FILL LAST CALENDAR YEAR), including
income from all sources including wages, salaries, unemployment payments, public assistance, Social Security
or retirement benefits, help from relatives, and so forth? Can you tell me that amount before taxes?
$___________________ RECORD INCOME
(999999996) DON’T KNOW
(999999997) REFUSED
[SKIP TO RANGE_20 (S10Q3)]
[SKIP TO RANGE_20 (S10Q3)]
HELP SCREEN: RESPONDENT MAY GIVE A RANGE AS AN ANSWER TO THIS QUESTION. BE
PREPARED TO PROBE FOR A MORE ACCURATE ANSWER.
Page 104 [ Series 1, No. 46
RANGE_20 (S10Q3)
For the purposes of this survey, it is important to get at least a range for the total income received by all
members of your household in [FILL YEAR]. Would you say that the total combined income, before taxes,
was above or below $20,000?
(1)
(2)
(3)
(6)
(7)
MORE THAN $20,000
$20,000
LESS THAN $20,000
DON’T KNOW
REFUSED
RANGE_10 (S10Q4)
[SKIP TO RANGE_40 (S10Q9)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_10 (S10Q4)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $10,000?
(1)
(2)
(3)
(6)
(7)
MORE THAN $10,000
$10,000
LESS THAN $10,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_15 (S10Q6)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_7 (S10Q5)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
RANGE_7 (S10Q5) Was it more than $7,500?
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
RANGE_15 (S10Q6) Was it more than $15,000?
(0)
(1)
(6)
(7)
RANGE_17 (S10Q7)
(0)
(1)
(6)
(7)
NO
YES
DON’T KNOW
REFUSED
Was it more than $17,500?
NO
YES
DON’T KNOW
REFUSED
RANGE_12 (S10Q8)
(0)
(1)
(6)
(7)
[SKIP TO RANGE_12 (S10Q8)]
[SKIP TO RANGE_17 (S10Q7)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was it more than $12,500?
NO
YES
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
RANGE_40 (S10Q9) Was the total combined household income more or less than $40,000?
(1)
(2)
(3)
(6)
(7)
RANGE_60 S10Q10)
(1)
(2)
(3)
(6)
(7)
RANGE_50 (S10Q11)
(1)
(2)
(3)
(6)
(7)
MORE THAN $40,000
$40,000
LESS THAN $40,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_60 (S10Q10)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_30 (S10Q13)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $60,000?
MORE THAN $60,000
$60,000
LESS THAN $60,000
DON’T KNOW
REFUSED
[SKIP TO RANGE_75 (S10Q16)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_50 (S10Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $50,000?
MORE THAN $50,000
$50,000
LESS THAN $50,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_45 (S10Q12)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Series 1, No. 46 [ Page 105
RANGE_45 (S10Q12)
(1)
(2)
(6)
(7)
MORE THAN $45,000
LESS THAN $45,000
DON’T KNOW
REFUSED
RANGE_30 (S10Q13)
(1)
(2)
(3)
(6)
(7)
(1)
(2)
(6)
(7)
(1)
(2)
(6)
(7)
BESTINCOME
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $25,000?
MORE THAN $25,000
LESS THAN $25,000
DON’T KNOW
REFUSED
RANGE_75 (S10Q16)
[SKIP TO RANGE_35 (S10Q14)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO RANGE_25 (S10Q15)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $35,000?
MORE THAN $35,000
LESS THAN $35,000
DON’T KNOW
REFUSED
RANGE_25 (S10Q15)
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $30,000?
MORE THAN $30,000
$30,000
LESS THAN $30,000
DON’T KNOW
REFUSED
RANGE_35 (S10Q14)
(1)
(2)
(3)
(6)
(7)
Was the total combined household income more or less than $45,000?
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
Was the total combined household income more or less than $75,000?
MORE THAN $75,000
$75,000
LESS THAN $75,000
DON’T KNOW
REFUSED
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
[SKIP TO C11Q22 (S11Q11)]
DERIVED. BEST INCOME VALUE
C11Q22 (S11Q11)
Please tell me your Zip Code.
___ ___ ___ ___ ___ (00001–99995)
(99996) DON’T KNOW
(99997) REFUSED
CLOSING STATEMENT
Those are all the questions I have. I’d like to thank you on behalf of the Centers for Disease Control and Prevention
for the time and effort you’ve spent answering these questions. If you have any questions about this survey, you may
call my supervisor toll-free at 1–866–775–6858. If you have questions about your rights as a survey participant, you
may call the chairman of the Institutional Review Board at 1–800–223–8118. Thanks again.
Page 106 [ Series 1, No. 46
Appendix V
Summary of NAS Pretests
The SLAITS 2003 NAS fielded a
series of four pretests to determine the
most effective data collection
methodology for the main study—one
that would obtain the highest possible
response rates, produce asthma
prevalence estimates, and gather
high-quality analytic data on people
with asthma. Although the basic
questionnaire remained the same
(particularly for the detailed asthma
interview), the sampling and screening
procedures varied substantially among
the pretests. This appendix briefly
summarizes each of the four pretests.
Table VI provides detail on how specific
elements differed by pretest.
Pretest I
Sample design—The Pretest I
screening methodology collected
demographic information (i.e., age, sex,
race, and ethnicity) and asthma status
for all household members to allow
calculation of asthma prevalence rates.
These items were administered at the
beginning of the interview. The
screening interview respondent was the
household member who was determined
to be most knowledgeable about the
health of all members. Detailed
interviews were conducted with up to
one asthma-positive adult and one
asthma-positive child.
Data collection—The NIS advance
letter in use at the time was mailed to
address-matched cases. No mention of
asthma was made in the letter. The
pretest was conducted between
September 17, 2001, and November 15,
2001, in eight urban areas within the
four pilot states initially chosen for the
study (Jefferson County, Alabama;
Chicago, Illinois; Dallas, El Paso,
Houston, and Bexar Counties and
Houston, Texas; and Santa Clara and
San Diego Counties, California).
Results—A total of 461 household
screening interviews and 73 detailed
asthma interviews were completed. The
Pretest I interview completion rate was
82.8%, the screener completion rate was
54.4%, and the resolution rate was
82.6%. The unweighted CASRO
response rate, equal to the product of
these three components, was 37.2%.
Because the screener completion rate
was lower than anticipated, a second
pretest was planned to examine ways to
increase screener-level response.
Pretest II
Sample design—For Pretest II, the
study design was modified in several
ways. First, three new general
recruitment questions related to
‘‘breathing problems’’ were added at the
beginning of the screening interview in
an attempt to increase salience and
respondent interest. The request for the
most knowledgeable household
respondent to come to the telephone to
answer the household screening
questions was eliminated. Instead,
anyone over the age of 17 years who
answered the telephone was asked to
complete the screening interview. In
households where no one had asthma,
the person who answered the telephone
provided the demographic information
needed to develop prevalence rates.
Finally, the screening interview time
was reduced by shortening the informed
consent script, revising the ethnicity
question to yes or no format, and
dropping a question that asked for the
total number of people in the household
(which was now derived from the
household roster). No changes were
made in the procedures for detailed
interviews.
Data collection—As in the first
pretest, the NIS advance letter in use at
the time was mailed to address-matched
cases. However, for Pretest II, the letter
was revised to note that some
households might be asked questions
about asthma. The second pretest was
conducted from November 13, 2001,
through January 7, 2002, in three urban
areas (Jefferson County, Alabama;
Chicago, Illinois; and Houston, Texas).
Pretest II was designed and
implemented prior to the actual
completion of Pretest I.
Results—A total of 313 household
screening interviews and 47 detailed
asthma interviews were completed in the
second pretest. The interview
completion rate was 95.5%. The
screener completion rate was 68.0%,
and the resolution rate was 84.7%. The
unweighted CASRO response rate was
55.0%. Though response rates in Pretest
II were substantially higher than those
of Pretest I, there was interest in testing
other approaches to improve response
rates. Therefore, a third pretest was
fielded.
Pretest III
Sample design—The goal of Pretest
III was to investigate additional methods
to increase response. The data collection
approach was changed to uncouple the
NIS screener and interview and the
NAS interview. Rather than proceeding
directly to the NAS interview,
households that completed the NIS
screener and interview were mailed a
separate NAS-specific advance letter
and recontacted for NAS after
approximately 3 weeks using an
introduction that mentioned only NAS.
In addition, known households that did
not complete the NIS screener or
interview during NIS data collection
were contacted for the NAS after the
NIS data collection period closed.
The recontacted sample was divided
into two groups to test differing content
of advance letters and introductory
scripts. The NAS-specific advance letter
and introductory script for the first
group had an asthma-specific focus.
These items for the second group
focused more generally on air quality
and health. The second group also
received two additional questions at the
beginning of the survey asking about air
quality in their neighborhood. This
experiment was designed to determine
whether the more general air quality
focus might increase response in
asthma-negative households.
The final change implemented for
the third pretest moved the initial
demographic questions to the end of the
survey for respondents eligible for the
detailed interview. This change was
intended to minimize the number of
breakoffs occurring before a household
member was sampled.
Data collection—As noted above,
separate NAS-specific advance letters
were mailed to households identified
Series 1, No. 46 [ Page 107
Table IV. NAS Pretest III unweighted response rates by group
Percentage rate
Interview completion rate
Screener completion rate
Resolution rate. . . . . . .
CASRO response rate . .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Percent of
asthma group
Percent of
air quality group
Percent of
total sample
76.2
54.2
77.9
32.2
79.5
52.8
77.9
32.7
77.9
53.5
77.9
32.5
.
.
.
.
NOTES: NAS is National Asthma Survey. CASRO is the Council of American Survey Research Organizations.
during earlier NIS administration. The
third pretest was conducted from March
6, 2002, through July 10, 2002, in four
states (Alabama, California, Illinois, and
Texas). Full-state samples were used for
this pretest, as opposed to the urban
samples used in the first two pretests.
Results—A total of 5,529 household
screening interviews and 981 detailed
asthma interviews were completed in the
third pretest. The overall interview
completion rate was 77.9%. The
screener completion rate was 53.5%,
and the resolution rate was 77.9%. The
unweighted CASRO response rate was
32.5%. No significant differences were
observed in the CASRO response rate
between the asthma-focused and air
quality-focused groups (Table IV).
The changes implemented as part of
the third pretest were unsuccessful in
raising response rates. In fact, the
response rates were lower than those
observed in either of the previous
pretests, so a fourth pretest was
designed and implemented.
Pretest IV
Sample design—In Pretest IV, the
NIS and NAS interviews were rejoined,
and two separate screening approaches
were tested. In the first screening
approach (Approach A), all household
members were rostered, one adult was
sampled in all households, and one child
was sampled in households with
children. Once selected, the sampled
persons were screened for asthma. If the
sampled adult or child had asthma, the
adult (or, for a child, a parent or
guardian) completed a detailed
interview. A shorter screening interview,
which included household environment
questions and demographics, was
administered to sampled respondents
who screened negative for lifetime
asthma. In the second screening
approach (Approach B), households
were immediately screened for the
presence of asthma. In asthma-negative
households, the interview was
terminated. In asthma-positive
households, a maximum of one adult
and one child with asthma were
randomly sampled for a detailed
interview.
Data collection—The NIS advance
letter in use at the time was mailed to
address-matched cases. As in Pretest I,
no mention of asthma was made in the
letter. The data collection for the fourth
pretest took place between July 17,
2002, and November 4, 2002. Full-state
samples in Alabama, California, Illinois,
and Texas were used for Pretest IV.
Results—Among the 4,268 persons
screened using Approach A, 250 detailed
asthma interviews were completed. As
Table V shows, the interview completion
rate was 88.1%. The screener
completion rate was 50.5%, and the
resolution rate was 82.9%. The
unweighted CASRO response rate was
36.9%. Among the 2,800 households
that were screened using Approach B, a
total of 266 detailed asthma interviews
Table V. NAS Pretest IV unweighted response rates
Percentage rate
Interview completion rate
Screener completion rate
Resolution rate. . . . . . .
CASRO response rate . .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
Percent of
Approach A
Percent of
Approach B
88.1
50.5
82.9
36.9
76.8
84.5
83.4
54.1
NOTE: NAS is National Asthma Survey. CASRO is the Council of American Survey Research Organizations.
were completed. The interview
completion rate was 76.8%. The
screener completion rate was 84.5%,
and the resolution rate was 83.4%. The
unweighted CASRO response rate was
54.1%.
Conclusion
A plan for main study data
collection in 2003 was developed by
incorporating selected design elements
from the four pretests. A national study,
with an estimated 10,000 completed
screening interviews, would be fielded.
In addition, a separate state-specific
study would be fielded in four states
used for the pretests—Alabama,
California, Illinois, and Texas—with an
estimated 12,000 screening interviews
completed per state. The national study
questionnaire synthesized and refined
the previous pretest methodologies in
that it retained the most successful
elements of previous questionnaires,
sampled only one person, and allowed
proxy interviews for sampled
respondents not immediately available.
The questionnaire, which was most
similar to the questionnaire used in
Pretest IV, Approach A, was designed to
produce prevalence rates and detailed
analytical data on persons with asthma.
The questionnaire chosen for the
state-specific study was used in Pretest
IV, Approach B, which gathered detailed
analytical data for persons with asthma
without allowing production of
prevalence rates.
Although Pretest II generated the
highest response rates of the four
pretests and could be used to calculate
prevalence rates, it was not chosen for
the main study because of the
burdensome screening household roster
process. This protocol collected
demographic information (i.e., age, sex,
race, and ethnicity) and asthma status
for all household members at the
beginning of the interview, which can be
burdensome, especially to respondents
who reside in large or transient
households (See Table VI).
Data collection period
Pretest I
Pretest II
Pretest III
Pretest IV
September 17, 2001–
November 15, 2001
November 13, 2001–
January 7, 2002
March 6, 2002–
July 10, 2002
July 17, 2002–
November 4, 2002
Asthma prevalence . . . . . . . . . .
All household
members screened
All household
members screened
All household
members screened
Number of household
members sampled for detailed
interview . . . . . . . . . . . . . . . .
Randomly select up
to two with asthma:
one adult and one
child
Randomly select up to
two with asthma: one
adult and one child
Randomly select up to
two with asthma: one
adult and one child
Most knowledgeable person
Any household member
over age 17
Any household member
over age 17
Any household member
over age 17
Advance letter . . . . . . . . . . . . .
NIS advance letter; no
mention of asthma
NIS advance letter that
mentions asthma
Separate NAS advance letter
mailed approximately 3 weeks
after NIS is complete.
Two experimental groups:
asthma and air quality
NIS advance letter; no
mention of asthma
Informed consent script for
screening . . . . . . . . . . . . . . . .
Standard script with most
knowledgeable person
providing informed consent
before screening questions
Shortened and moved to
follow initial ‘‘breathing’’
questions
Shortened and moved
to follow initial
‘‘breathing’’ questions
Approach A: Standard script
with most knowledgeable person
providing informed consent before
screening questions
Approach B: After-asthma screening,
rostering, and sampling of respondents
Total number of persons in
household . . . . . . . . . . . . . . .
Separate question asking
total persons in household
Question removed;
information derived from
household roster
Question removed;
information derived
from household roster
Approach A: Derived from household roster
Approach B: Not determined
Hispanic ethnicity question . . . . .
Detailed Hispanic categories
General yes or no question
General yes or no question
General yes or no question
Breathing and air quality
questions . . . . . . . . . . . . . . . .
None
Addition of general
‘‘breathing’’ questions
Addition of general ‘‘breathing’’
questions plus general ‘‘air
quality’’ questions in one-half
of the sample
None
Placement of demographic
measures. . . . . . . . . . . . . . . .
Household with asthma:
telephone information and
income at end of survey;
all others after initial
informed consent script
Household without asthma:
All demographics asked after
informed consent
Household with asthma:
telephone information and
income at end of survey; all
others after initial informed
consent script
Household without asthma:
All demographics asked after
informed consent
Household with asthma:
age and sex of household
members after initial informed
consent script; all others
asked at the end of detailed
asthma interview
Household without asthma:
All demographics asked after
informed consent
Approach A: Household
with asthma: asked at the end
of the detailed asthma interview
Household without asthma:
Asked after informed consent
Approach B: All demographics
asked at the end of the
detailed asthma interview
Respondent to provide
household screening
information necessary for
sampling . . . . . . . . . . . . . . . .
Approach A: One adult
and one child screened
Approach B: Household is
immediately screened (any household
member)
Approach A: Randomly select one
adult and one child; asthma
status unknown
Approach B: Randomly select up to
two with asthma: one adult and
one child
Page 108 [ Series 1, No. 46
Table VI. SLAITS 2003 National Asthma Survey: Summary of pretests
Table VI. SLAITS 2003 National Asthma Survey: Summary of pretests—Con.
Pretest I
Pretest II
Pretest III
Pretest IV
September 17, 2001–
November 15, 2001
November 13, 2001–
January 7, 2002
March 6, 2002–
July 10, 2002
July 17, 2002–
November 4, 2002
Location . . . . . . . . . . . . . . . .
Jefferson County, Alabama;
Chicago, Illinois; Dallas,
El Paso, and Bexar
Counties and Houston,
Texas; Santa
Clara and San Diego
Counties, California
Jefferson County, Alabama;
Chicago, Illinois;
Houston, Texas
California, Illinois, Alabama,
and Texas state samples
California, Illinois, Alabama,
and Texas state samples
Connection to NIS . . . . . . . . . .
Occurs immediately after
NIS screener or interview
Occurs immediately after
NIS screener or interview
Minimum of 3-week delay
after NIS screener or interview
Occurs immediately after
NIS screener or interview
NIS unresolved cases . . . . . . . .
Finalized with NIS-level
disposition
Finalized with NIS-level
disposition
Dialed for NAS after the
close of the NIS quarter
Finalized with NIS-level disposition
Data collection period
NOTES: SLAITS is State and Local Area Integrated Telephone Survey. NIS is National Immunization Survey. NAS is National Asthma Survey.
Series 1, No. 46 [ Page 109
Page 110 [ Series 1, No. 46
Advance letter for Pretest I
FROM THE DIRECTOR
NATIONAL CENTER FOR HEALTH STATISTICS
Within the next few weeks, your household may be called to take part in an important national study about the health of children
and teenagers. The survey is being conducted by the U.S. Department of Health and Human Services.
We are relying on your help to make this study a success. Local, State, and federal health authorities depend on the results of this
study to measure the progress of health care for the country. Although participation is completely voluntary and there is no penalty
for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health
care policy in the years ahead.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. This study is authorized by the Public Health Service Act [Secs. 306 & 2102 (a)(7)], and by law, information you provide
during the interview will be kept strictly confidential. The information reported in this survey will be summarized for research
purposes only.
You may call our toll-free telephone number (1–800–290–1296) to participate immediately or visit the study’s web site at
http://www.cdc.gov/nis to learn more about the study. This study has been approved by the NCHS Institutional Review Board. If
you have questions about your rights as a study participant, you may call Margot Palmer, Institutional Review Board chairman,
toll-free at 1–800–223–8118.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Edward J. Sondik, Ph.D.
Director, National Center for Health Statistics
Centers for Disease Control and Prevention
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–800–290–
1296 be called.
Series 1, No. 46 [ Page 111
Advance letter for Pretest II
FROM THE DIRECTOR
NATIONAL CENTER FOR HEALTH STATISTICS
Within the next few weeks, your household will be called to take part in an important national study being conducted by the U.S.
Department of Health and Human Services. This study, designed to help local, State, and federal health authorities understand
how to improve health care services, is about health-related topics including asthma in adults and children and vaccinations for
young children.
Childhood immunization rates are at an all-time high of 78%, but many children have not received all of their immunizations.
Asthma is one of the nation’s most common and costly chronic conditions, affecting more than 14.5 million Americans, including
about 4.5 million children. The Department of Health and Human Services is committed to improving immunization and other
health care services.
You may call the study’s toll-free telephone number (1–866–775–6858) to participate immediately or to obtain more information
about the study’s background and content. You may also visit the study’s web site at http://www.cdc.gov/nis for more information.
If you have a child between 18 and 35 months of age, please take a moment to locate the child’s immunization records. They will
help you during the interview.
We are relying on your help to make this study a success. Although participation is completely voluntary and there is no penalty
for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health
care policy in the years ahead. If you would like to learn more about your rights as a respondent, please contact the Chair of the
Institutional Review Board at 1–800–223–8118.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. When the interviewer calls, you will be asked a few questions to determine whether or not your household is eligible for
participation in this study.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Edward J. Sondik, Ph.D.
Director, National Center for Health Statistics
Centers for Disease Control and Prevention
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Page 112 [ Series 1, No. 46
Advance letters and introductory scripts for Pretest III
NIS advance letter
FROM THE DIRECTOR
NATIONAL CENTER FOR HEALTH STATISTICS
Within the next few weeks, your household will be called to take part in an important national study being conducted by the U.S.
Department of Health and Human Services. This study provides important information for measuring the progress of
vaccination for young children for the country.
Childhood immunization rates are at an all-time high of 78%, but many children have not received all of their immunizations. The
Department of Health and Human Services is committed to improving immunization services and reducing the costs of vaccines.
Local, State, and federal health authorities depend on the results of this study to measure the progress of immunization for the
country.
The results of this study also help local, State, and federal health authorities understand how to improve health care services for all
children. Therefore, some households may be asked questions about the types of health and related services their children need or
use.
You may call Jim Murphy at the study’s toll-free telephone number (1–866–775–6858) to participate immediately or to obtain
more information about the study’s background and content. You may also visit the study’s web site at http://www.cdc.gov/nis for
more information. If you have a child between 18 and 35 months of age, please take a moment to locate the child’s immunization
records. They will help you during the interview.
We are relying on your help to make this study a success. Although participation is completely voluntary and there is no penalty
for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health
care policy in the years ahead. If you would like to learn more about your rights as a respondent, please contact the Chair of the
Institutional Review Board at 1–800–223–8118.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. When the interviewer calls, you will be asked a few questions to determine whether or not your household is eligible for
participation in this study.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Edward J. Sondik, Ph.D.
Director, National Center for Health Statistics
Centers for Disease Control and Prevention
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Series 1, No. 46 [ Page 113
Asthma-focused NAS advanced letter
Dear Resident,
The National Center for Environmental Health and the National Center for Health Statistics, Centers for Disease Control and
Prevention, are requesting your help for an important study about asthma comparing characteristics of people who do and do not
have asthma. A professional interviewer will be contacting you soon to conduct an interview at your convenience.
Asthma is one of the nation’s most common and costly chronic conditions, affecting more than 14.5 million Americans. Untreated
or improperly treated asthma results in higher health care costs for everyone. This study will provide important information to help
the National Center for Environmental Health improve health care for people with asthma and reduce health care costs overall.
Your help in this study is voluntary, but we urge you to participate. Because we are talking to only a sample of households in your
area, everyone’s participation is extremely important to the completeness and accuracy of the study’s results. The information you
provide will be kept completely confidential, as required by law. No individual person or household will be identified in reports
resulting from the study.
We hope that you will take a few minutes to help with this important research, and thank you in advance for your time. You may
call our toll-free telephone number (1–866–775–6858) to participate immediately.
If you have any questions about the study, please call our toll-free number, 1–866–775–6858. This study has been approved by the
National Center for Health Statistics Institutional Review Board. If you have questions about your rights as a study participant,
you may call the Institutional Review Board chairman, toll-free at 1–800–223–8118.
Sincerely,
Richard Joseph Jackson, MD, MPH
Director
National Center for Environmental Health
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Page 114 [ Series 1, No. 46
Air quality-focused NAS advance letter
Dear Resident,
The National Center for Environmental Health and the National Center for Health Statistics, Centers for Disease Control and
Prevention, are requesting your help for an important study about air quality and health. A professional interviewer will be
contacting you soon to conduct an interview at your convenience.
Your help in this study is voluntary, but we urge you to participate. Because we are talking to only a sample of households in your
area, everyone’s participation is extremely important to the completeness and accuracy of the study’s results. The information you
provide will be kept completely confidential, as required by law. No individual person or household will be identified in reports
resulting from the study.
Your telephone number was randomly selected from all possible telephone numbers in your area. We obtained your address from
commercial listings in order to mail you this letter.
We hope that you will take a few minutes to help with this important research, and thank you in advance for your time. You may
call our toll-free telephone number (1–866–775–6858) to participate immediately.
If you have any questions about the study, please call our toll-free number, 1–866–775–6858. This study has been approved by the
National Center for Health Statistics Institutional Review Board. If you have questions about your rights as a study participant,
you may call the Institutional Review Board chairman, toll-free at 1–800–223–8118.
Sincerely,
Richard Joseph Jackson, MD, MPH
Director
National Center for Environmental Health
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Series 1, No. 46 [ Page 115
Asthma-focused introductory script
Hello, my name is [INTERVIEWER NAME]. I’m calling on behalf of the Centers for Disease Control and Prevention. We’re
conducting a study regarding asthma, comparing characteristics of people who do and do not have asthma. Your telephone number
has been selected at random. Your participation is voluntary and your answers will be kept private.
Air quality-focused introductory script
Hello, my name is [INTERVIEWER NAME]. I’m calling on behalf of the Centers for Disease Control and Prevention. We’re
conducting a study regarding air quality and health. Your telephone number has been selected at random. Your participation is
voluntary and your answers will be kept private.
Page 116 [ Series 1, No. 46
Advance letter for Pretest IV
FROM THE DIRECTOR
NATIONAL CENTER FOR HEALTH STATISTICS
Within the next few weeks, your household will be called to take part in an important national study being conducted by the U.S.
Department of Health and Human Services. This study provides important information for measuring the progress of
vaccination for young children for the country.
Childhood immunization rates are at an all-time high of 78%, but many children have not received all of their immunizations. The
Department of Health and Human Services is committed to improving immunization services and reducing the costs of vaccines.
Local, State, and federal health authorities depend on the results of this study to measure the progress of immunization for the
country.
The results of this study also help local, State, and federal health authorities understand how to improve health care services for all
children. Therefore, some households may be asked questions about the types of health and related services their children need or
use.
You may call Jim Murphy at the study’s toll-free telephone number (1–866–775–6858) to participate immediately or to obtain
more information about the study’s background and content. You may also visit the study’s web site at http://www.cdc.gov/nis for
more information. If you have a child between 18 and 35 months of age, please take a moment to locate the child’s immunization
records. They will help you during the interview.
We are relying on your help to make this study a success. Although participation is completely voluntary and there is no penalty
for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health
care policy in the years ahead. If you would like to learn more about your rights as a respondent, please contact the Chair of the
Institutional Review Board at 1–800–223–8118.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. When the interviewer calls, you will be asked a few questions to determine whether or not your household is eligible for
participation in this study.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Edward J. Sondik, Ph.D.
Director, National Center for Health Statistics
Centers for Disease Control and Prevention
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Series 1, No. 46 [ Page 117
Appendix VI
Advance Letters
Advance letter for cases in the NIS and NAS sample
FROM THE DIRECTOR
NATIONAL CENTER FOR HEALTH STATISTICS
Within the next few weeks, your household will be called to take part in an important national study being conducted by the U.S.
Department of Health and Human Services. This study provides important information for measuring the progress of
vaccination for young children for the country.
Childhood immunization rates are at an all-time high of 78%, but many children have not received all of their immunizations. The
Department of Health and Human Services is committed to improving immunization services and reducing the costs of vaccines.
Local, State, and federal health authorities depend on the results of this study to measure the progress of immunization for the
country.
The results of this study also help local, State, and federal health authorities understand how to improve health care services.
Therefore, some households may be asked questions about asthma and other health-related topics or services.
You may call Jim Murphy at the study’s toll-free telephone number (1–866–775–6858) to participate immediately or to obtain
more information about the study’s background and content. You may also visit the study’s web site at http://www.cdc.gov/nis for
more information. If you have a child between 18 and 35 months of age, please take a moment to locate the child’s immunization
records. They will help you during the interview.
We are relying on your help to make this study a success. Although participation is completely voluntary and there is no penalty
for not answering any question, we hope you will agree to participate. The information we are gathering will help shape health
care policy in the years ahead.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. When the interviewer calls, you will be asked a few questions to determine whether or not your household is eligible for
participation in this study.
This study is authorized by the Public Health Service Act, and by law, information you provide during the interview will be kept
strictly confidential. The information reported in this survey will be summarized for research purposes only.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Edward J. Sondik, Ph.D.
Director, National Center for Health Statistics
Centers for Disease Control and Prevention
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Page 118 [ Series 1, No. 46
Advance letter for cases in the NAS-only (augmentation) sample
FROM THE DIRECTOR
NATIONAL CENTER FOR ENVIRONMENTAL HEALTH
Dear Resident,
The National Center for Environmental Health and the National Center for Health Statistics, Centers for Disease Control and
Prevention, are requesting your help in an important health study about asthma. A professional interviewer will be contacting you
soon to conduct a telephone interview at your convenience. If no one in your household has asthma, we have only a few questions
about your household so that people with and without asthma can be compared. For most households, this interview will be very
brief.
Asthma is one of the nation’s most common and costly chronic conditions, affecting more than 14.5 million Americans. Untreated
or improperly treated asthma results in higher health care costs for everyone. Your participation in this study will provide
important information to assist the National Center for Environmental Health in improving the health of people with asthma and in
reducing the cost of health care.
Your telephone number was selected at random using scientific methods, and your address was obtained through commercial
listings. Your participation in this study is completely voluntary and there is no penalty for not answering any question. All
information you provide will be kept confidential as required by law. No individual person or household will be identified in any
reports resulting from the study.
We hope that you will take a few minutes to help with this important research, and thank you in advance for your time. You may
call our toll-free telephone number (1–866–775–6858) to participate immediately if you want.
We appreciate your taking the time to talk to us. Thank you for your assistance.
Sincerely,
Henry Falk, M.D., M.P.H., Director
National Center for Environmental Health
You may have questions about your rights as a participant in this research study. If so, please call the office of the Institutional
Review Board at the National Center for Health Statistics, toll-free, at 1–800–223–8118. Please leave a brief message with your
name and phone number. Say that you are calling about Protocol #2001–06. Your call will be returned as soon as possible.
If you prefer to contact us using a TTY, please call the AT&T Relay Service at 1–800–682–8786 and request that 1–866–775–
6858 be called.
Series 1, No. 46 [ Page 119
Appendix VII
Disposition Code Frequencies and Unweighted Response Rate Calculations
Table VII. SLAITS 2003 National Asthma Survey: National study case disposition frequencies
Disposition
Sample
category code
Number
Percent of
total sample
Total number of phone lines in the sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
...
55,204
100.00
No contact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
UH
4,692
8.50
3 + fax or modem prior to any contact
2 + temporarily not in service . . . . . .
Nonworking number . . . . . . . . . . . .
Number changed . . . . . . . . . . . . .
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Z
Z
Z
Z
913
799
3,227
288
1.65
1.45
5.85
0.52
machine—known household . . . . . .
machine—nonresidential . . . . . . . .
machine—residential status unknown
service—nonresidential . . . . . . . . .
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UO
Z
UH
Z
91
262
1,705
5
0.16
0.47
3.09
0.01
Spanish case—residential status unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Other language case—residential status unknown . . . . . . . . . . . . . . . . . . . . . . . . . .
Physical or mental impairment case—residential status unknown . . . . . . . . . . . . . . . . .
UH
UH
UH
2
4
6
0.00
0.01
0.01
Appointment at introduction—residential status unknown
Callback at introduction—residential status unknown . . .
Hangup during introduction . . . . . . . . . . . . . . . . . . .
Refusal at introduction. . . . . . . . . . . . . . . . . . . . . .
Callback—known household . . . . . . . . . . . . . . . . . .
Appointment—known household . . . . . . . . . . . . . . .
Refusal—known household. . . . . . . . . . . . . . . . . . .
NIS-level callback . . . . . . . . . . . . . . . . . . . . . . . .
NIS-level appointment . . . . . . . . . . . . . . . . . . . . .
NIS-level refusal . . . . . . . . . . . . . . . . . . . . . . . . .
Not residential . . . . . . . . . . . . . . . . . . . . . . . . . .
Refusal prior to NAS screening . . . . . . . . . . . . . . . .
Callback prior to NAS screening . . . . . . . . . . . . . . .
Appointment prior to NAS screening . . . . . . . . . . . . .
Refusal at or prior to NAS item BATH_FAN (S7Q16)1 . .
Callback at or prior to NAS item BATH_FAN (S7Q16)1 . .
Refusal—partial interview . . . . . . . . . . . . . . . . . . . .
Callback—partial interivew . . . . . . . . . . . . . . . . . . .
Answering
Answering
Answering
Answering
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UH
UH
UH
UH
UO
UO
UO
UO
UO
UO
Z
UO
UO
UO
R
R
P
P
502
88
1,337
3,290
222
73
295
3
2
22
1,967
2,469
370
154
10
218
11
23
0.91
0.16
2.42
5.96
0.40
0.13
0.53
0.01
0.00
0.04
3.56
4.47
0.67
0.28
0.02
0.39
0.02
0.04
Emancipated minor household—known household, unknown eligibility; interviews were not
conducted in households in which no one over the age of 17 years resided.. . . . . . . . .
Other language case—known household, unknown eligibility . . . . . . . . . . . . . . . . . . .
Other language case—known eligible household . . . . . . . . . . . . . . . . . . . . . . . . . .
Screened—asthma-negative household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Completed household interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Converted household interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
GENESYS IDplus—resolved numbers (nonworking, business, and modem numbers) . . . .
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UO
UO
Y
X
I
I
Z
24
430
19
8,852
870
51
21,908
0.04
0.78
0.03
16.04
1.58
0.09
39.69
. . . Category not applicable.
1
The variable BATH_FAN (S7Q16) denotes the point at which a sampled respondent interview is considered a ‘‘partially complete’’ interview (also known as ‘‘partial complete’’). That is, sampled-
respondent cases need to complete at least through the variable BATH_FAN (S7Q16) and proxy-respondent cases need to complete at least through the variable S_INSIDEP (S7Q10P) for these
cases to be considered partially completed interviews (in contrast to full interviews, where all questions are asked).
NOTES: SLAITS is State and Local Area Integrated Telephone Survey. NIS is National Immunization Survey. NAS is National Asthma Survey.
Page 120 [ Series 1, No. 46
Table VIII. Unweighted response rate calculations for the National Asthma Survey, national sample: 2003
Calculation of response rates
Calculated
rate (percent)
Interview completion rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
79.50
Formula
(I+P)/(I+P+R+Y)
Screener completion rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
70.80
(I+P+R+X+Y)/(I+P+R+X+Y+UO)
Resolution rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
78.90
(I+P+R+X+Y+UO+Z)/(I+P+R+X+Y+UO+Z+UH)
CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
44.40
...
. . . Category not applicable.
NOTES: Formulas based on letter codes identified in Table VII, ‘‘Design and Operation of the National Asthma Survey,’’ Vital and Health Statistics series report, vol 1, no 46. CASRO is the Council of
American Survey Research Organizations.
Table IX. SLAITS 2003 National Asthma Survey: Four-state study case disposition frequencies
Disposition
Sample
category code
Number
Percent of
total sample
Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
...
210,109
100.00
No contact . . . . . . . . . . . . . . . . . . . . . . . .
3 + fax or modem prior to any contact . . . . . . .
2 + temporarily not in service . . . . . . . . . . . .
Nonworking number . . . . . . . . . . . . . . . . . .
Number changed . . . . . . . . . . . . . . . . . . . .
Answering machine—known household . . . . . .
Answering machine—nonresidential. . . . . . . . .
Answering machine—residential status unknown
Answering service—nonresidential . . . . . . . . .
Answering service—residential status unknown .
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UH
Z
Z
Z
Z
UO
Z
UH
Z
UH
18,962
3,063
3,131
14,768
1,359
379
1,020
6,514
28
4
9.02
1.46
1.49
7.03
0.65
0.18
0.49
3.10
0.01
0.00
Spanish case—residential status unknown . . . . . . . . . . . . . .
Other language case—residential status unknown . . . . . . . . .
Physical or mental impairment case—residential status unknown
Appointment at introduction—residential status unknown . . . . .
Callback at introduction—residential status unknown . . . . . . . .
Hangup during introduction . . . . . . . . . . . . . . . . . . . . . . . .
Refusal at introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .
Callback—known household . . . . . . . . . . . . . . . . . . . . . . .
Appointment—known household . . . . . . . . . . . . . . . . . . . . .
Refusal—known household . . . . . . . . . . . . . . . . . . . . . . . .
NIS-level callback . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
NIS-level appointment . . . . . . . . . . . . . . . . . . . . . . . . . . .
NIS-level refusal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Not residential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Refusal prior to NAS screening . . . . . . . . . . . . . . . . . . . . .
Callback prior to NAS screening . . . . . . . . . . . . . . . . . . . .
Appointment prior to NAS screening . . . . . . . . . .1 . . . . . . . .
Refusal at or prior to NAS item BATH_FAN (S7Q16) . . . . . . .
Callback at or prior to NAS item BATH_FAN (S7Q16)1 . . . . . . .
Appointment at or prior to NAS item BATH_FAN (S7Q16)1 . . . .
Refusal—partial interview . . . . . . . . . . . . . . . . . . . . . . . . .
Callback—partial interivew . . . . . . . . . . . . . . . . . . . . . . . .
Appointment—partial interview . . . . . . . . . . . . . . . . . . . . . .
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33
58
28
1,961
281
5,140
7,843
1,323
334
1,199
37
7
216
6,302
4,572
645
84
1,673
334
183
84
20
9
0.02
0.03
0.01
0.93
0.13
2.45
3.73
0.63
0.16
0.57
0.02
0.00
0.10
3.00
2.18
0.31
0.04
0.80
0.16
0.09
0.04
0.01
0.00
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UH
UH
UH
UH
UH
UH
UH
UO
UO
UO
UO
UO
UO
Z
UO
UO
UO
R
R
R
P
P
P
Emancipated minor household—known household, unknown eligibility; interviews
were not conducted in households in which no one over the age of 17 years
resided. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Other language case—known household, unknown eligibility . . . . . . . . . . . . .
Other language case—known eligible household. . . . . . . . . . . . . . . . . . . . .
Physical or mental impairment case—known eligible household . . . . . . . . . . .
Screened—asthma-negative household . . . . . . . . . . . . . . . . . . . . . . . . . .
Completed household interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Converted household interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
GENESYS IDplus—resolved numbers (nonworking, business, and modem
numbers) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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UO
UO
Y
R
X
I
I
88
1,260
10
8
40,852
4,664
348
0.04
0.60
0.00
0.00
19.44
2.22
0.17
. .
Z
81,285
38.69
............
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. . . Category not applicable.
1
The variable BATH_FAN (S7Q16) denotes the point at which a sampled respondent interview is considered a ‘‘partially complete’’ interview (also known as ‘‘partial complete’’). That is, sampled-
respondent cases need to complete at least through the variable BATH_FAN (S7Q16) and proxy-respondent cases need to complete at least through the variable S_INSIDEP (S7Q10P) for these
cases to be considered partially completed interviews (in contrast to full interviews, where all questions are asked).
NOTES: SLAITS is State and Local Area Integrated Telephone Survey. NIS is National Immunization Survey. NAS is National Asthma Survey.
Series 1, No. 46 [ Page 121
Table X. Unweighted response rate calculations for the National Asthma Survey, four-state sample: 2003
Calculation of response rates
Interview completion rate .
Screener completion rate .
Resolution rate . . . . . . .
CASRO response rate. . .
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Calculated
rate
(percent)
Formula
69.90
82.60
80.60
46.50
(I+P)/(I+P+R+Y)
(I+P+R+X+Y)/(I+P+R+X+Y+UO)
(I+P+R+X+Y+UO+Z)/(I+P+R+X+Y+UO+Z+UH)
...
. . . Category not applicable.
NOTES: Formulas based on letter codes identified in Table IX, ‘‘Design and Operation of the National Asthma Survey,’’ Vital and Health Statistics series report, vol 1, no 46. CASRO is the Council of
American Survey Research Organizations.
Page 122 [ Series 1, No. 46
Appendix VIII
Weighted Frequencies and Percentages for Selected Variables
Table XI. Unweighted and weighted estimates of the frequency and percentage of persons diagnosed with asthma during their lifetime
(ASTHSTAT), national sample, all ages: NAS, 2003
Reporting status of adult data
Unweighted number
of persons of all
ages with asthma
Weighted estimate
of number of
persons of all
ages with
asthma
Standard error
of weighted
estimate of
number of
persons of all
ages with asthma
Percent of
persons with
asthma
Standard error
of percent of
persons with
asthma
Self-reported responses only; excludes proxy
responses . . . . . . . . . . . . . . . . . . . . . .
919
30,877,453
1,143,131.27
11.08
0.40
Self-reported and proxy-reported responses .
976
30,877,453
1,099,091.58
11.08
0.39
NOTE: NAS is National Asthma Survey.
Table XII. Unweighted and weighted estimates of the frequency and percentage of persons of all ages who had an asthma episode or attack
in the 12 months prior to the date of interview (S4Q5), four-state sample (weight_int): NAS, 2003
Four-state sample
Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Alabama .
California .
Illinois . . .
Texas . . .
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NOTE: NAS is National Asthma Survey.
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Unweighted number
of asthmatic
persons who
had an asthma
attack in the
past 12 months
Weighted estimate
of number of
asthmatic persons
who had
an asthma attack
in the past
12 months
Standard error of
weighted estimate
of asthmatic
persons who had
an asthma attack
in the past
12 months
Percent of asthmatic
persons who had
an asthma attack
in the past
12 months
Standard error
of percent of
asthmatic persons
who had an
asthma attack
in the past
12 months
2,896
4,418,991.02
97,708.02
64.33
1.05
790
676
641
789
270,955.64
2,155,905.86
671,753.18
1,320,376.34
9,291.01
81,894.68
27,828.96
44,489.82
66.36
62.68
63.34
67.35
1.71
1.79
1.82
1.64
Vital and Health Statistics
series descriptions
SERIES 1.
Programs and Collection Procedures—These reports
describe the data collection programs of the National Center
for Health Statistics. They include descriptions of the methods
used to collect and process the data, definitions, and other
material necessary for understanding the data.
SERIES 2.
Data Evaluation and Methods Research—These reports
are studies of new statistical methods and include analytical
techniques, objective evaluations of reliability of collected
data, and contributions to statistical theory. These studies
also include experimental tests of new survey methods and
comparisons of U.S. methodology with those of other
countries.
SERIES 3.
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present analytical or interpretive studies based on vital and
health statistics. These reports carry the analyses further than
the expository types of reports in the other series.
SERIES 4.
Documents and Committee Reports—These are final
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SERIES 5.
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vital and health statistics with those of other countries or
present other international data of relevance to the health
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SERIES 10. Data From the National Health Interview Survey—These
reports contain statistics on illness; unintentional injuries;
disability; use of hospital, medical, and other health services;
and a wide range of special current health topics covering
many aspects of health behaviors, health status, and health
care utilization. They are based on data collected in a
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SERIES 11. Data From the National Health Examination Survey, the
National Health and Nutrition Examination Surveys, and
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Data from direct examination, testing, and measurement on
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prevalence of specific diseases or conditions in the United
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physical, physiological, and psychological characteristics, and
(2) analyses of trends and relationships among various
measurements and between survey periods.
SERIES 12. Data From the Institutionalized Population Surveys—
Discontinued in 1975. Reports from these surveys are
included in Series 13.
SERIES 13. Data From the National Health Care Survey—These
reports contain statistics on health resources and the public’s
use of health care resources including ambulatory, hospital,
and long-term care services based on data collected directly
from health care providers and provider records.
SERIES 14. Data on Health Resources: Manpower and Facilities—
Discontinued in 1990. Reports on the numbers, geographic
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SERIES 16. Compilations of Advance Data From Vital and Health
Statistics—Advance Data Reports provide early release of
information from the National Center for Health Statistics’
health and demographic surveys. They are compiled in the
order in which they are published. Some of these releases
may be followed by detailed reports in Series 10–13.
SERIES 20. Data on Mortality—These reports contain statistics on
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SERIES 22. Data From the National Mortality and Natality Surveys—
Discontinued in 1975. Reports from these sample surveys,
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health topics. These statistics are based on national surveys
of women and men of childbearing age.
SERIES 24. Compilations of Data on Natality, Mortality, Marriage, and
Divorce—These include advance reports of births, deaths,
marriages, and divorces based on final data from the National
Vital Statistics System that were published as National Vital
Statistics Reports (NVSR), formerly Monthly Vital Statistics
Report. These reports provide highlights and summaries of
detailed data subsequently published in Vital Statistics of the
United States. Other special reports published here provide
selected findings based on final data from the National Vital
Statistics System and may be followed by detailed reports in
Series 20 or 21.
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| File Type | application/pdf |
| File Title | Vital and Health Statistics Series 1, Number 46 (August 2008) |
| Subject | health surveys, needs assessment, State and Local Area Integrated Telephone Survey |
| Author | National Center for Health Statistics |
| File Modified | 2008-08-08 |
| File Created | 2008-08-06 |