Series 1, Number 46 August 2008

Design and Operation of

the National Asthma

Survey
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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.

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Design and operation of the National Asthma Survey : program and collection

procedures / Department of Health and Human Services, Centers for Disease

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1. National Asthma Survey (U.S.) 2. Asthma--United States. I. National Center

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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 .................................................................................................. 4 
 

Sample Design........................................................................................... 4 
 

Proxy Interviews ........................................................................................ 5 
 

Questionnaire ............................................................................................ 6 
 

Development and Implementation of NAS Interviewer Training ................................................... 9 
 

Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 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 .............................................................................................. 32 
 

Specification of the National Asthma Education and Prevention Program Severity Indices Using the National Asthma

Survey Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 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............................................................................................ 117 
 

Advance Letters........................................................................................ 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.	 Percentage of overall sample that is an augmentation sample: NAS, 2003 ...................................... 5 
 

B.	 Weighted error rates in proxy reporting: NAS, 2003 ........................................................ 6 
 

C.	 Questionnaire flow in the national study: NAS, 2003 ....................................................... 8 
 

D.	 Completed screening and detailed interviews for national study: NAS, 2003 ................................... 10 
 

E.	 Completed screening and detailed interviews for four-state study: NAS, 2003 .................................. 10 
 

F.	 Number of interviews completed by month: NAS, 2003 .................................................... 10 
 

G.	 Mean and median interview length in minutes and seconds: NAS, 2003 ...................................... 13 
 

H.	 Mean and median length of screening interview for national study in minutes and seconds, by respondent NIS
 

eligibility: NAS, 2003 ............................................................................... 13 
 

J.	 Mean and median length in minutes and seconds for national study detailed interview, by NIS eligibility:
 

NAS, 2003 ........................................................................................ 13 
 

K.	 Mean and median length of interview in minutes and seconds for four-state study detailed interview, by NIS
 

eligibility: NAS, 2003 ............................................................................... 14 
 

L.	 Weighted response rates: NAS, 2003 ................................................................... 14 
 

M.	 Response rates for the detailed interview by sampled adult or child status: NAS, 2003 .......................... 15 
 

N.	 Final sample disposition, national and four-state studies: NAS, 2003 ......................................... 16 
 

O.	 Description of the weights, national and four-state samples: NAS, 2003 ....................................... 28 
 

Appendix Tables

I.	 Number of values imputed for 2003 NAS poststratification variables......................................... 39 
 

II.	 Summary statistics for poststratified weights, total screener and detailed interviews, national sample: NAS, 2003 ..... 39 
 

III.	 Summary statistics for poststratified weights, total screening and detailed interviews, by state and the entire four-state
 

sample: NAS, 2003 ................................................................................. 39 
 

IV.	 NAS Pretest III unweighted response rates by group ..................................................... 107 
 

V.	 NAS Pretest IV unweighted response rates ............................................................. 107 
 

VI.	 SLAITS 2003 National Asthma Survey: Summary of pretests.............................................. 108 
 

VII.	 SLAITS 2003 National Asthma Survey: National study case disposition frequencies ........................... 119 
 

VIII.	 Unweighted response rate calculations for the National Asthma Survey, national sample: 2003 ................... 120 
 

IX.	 SLAITS 2003 National Asthma Survey: Four-state study case disposition frequencies .......................... 120 
 

X.	 Unweighted response rate calculations for the National Asthma Survey, four-state sample: 2003.................. 121 
 

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 .............................................. 122 
 

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 . 122
 

vi
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 projecta 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
 

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 in the United

States

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).
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

Series 1, No. 46 [ Page 3

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

Sample only for NAS

National ....................... 75.0

Four-state

Total. . . . . . . . . . . . . . . . . . . . . . . . . 52.4

Alabama ...................... 61.5

California. . . . . . . . . . . . . . . . . . . . . . 36.9

Illinois. . . . . . . . . . . . . . . . . . . . . . . . 61.9

Texas ........................ 50.0

NOTE: NAS is National Asthma Survey.
Page 6 [ Series 1, No. 46

Table B. Weighted error rates in proxy reporting: NAS, 2003

Self-reported lifetime asthma status

Proxy-reported lifetime asthma status1

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

of asthma symptoms and attacks or

episodes.

3.	 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.

4.	 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.

5.	 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.

6.	 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.

7.	 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.

8.	 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
ational study: NAS, 2003

If the sampled respondent is asthma-negative

If the sampled respondent is

asthma-positive

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?

Is the proxy respondent

asked these questions?

Yes Yes Yes Yes

No No No No

Health care

coverage

items only

Health care

coverage

items only

Health care

coverage

items only

Health care

coverage

items only

No No No No

Subset of

household

environment items

Subset of

household

environment items

Subset of

household

environment items

Subset of

household

environment items

No No No No

Single question on

asthma status of other

household members Yes Yes

Single question on

asthma status of

other household members

Yes Yes Yes

Yes

Page8[ Series 1, No. 46
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

Less than 18 years

Total 18 years or over

Screening interviews: household level .......... 10,054 1,351 8,703 
 

Detailed interviews: person level ............. 955 164 791 
 

NOTE: NAS is National Asthma Survey.

Table E. Completed screening and detailed interviews for four-state study: NAS, 2003

Age State

Less than 18 years

Total 18 years and over Alabama Illinois California Texas

Screening interviews: household

level .................... 48,185 ... ... 12,160 11,898 11,998 12,129

Detailed interviews: person level .... 5,741 2,005 3,736 1,488 1,313 1,433 1,507

. . . 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 
 

2003
 

February .................. 13 ... 
 

March .................... 761 102 
 

April ..................... 870 850 
 

May ..................... 316 456 
 

June ..................... 1,139 447 
 

July ..................... 460 377 
 

August ................... 878 411 
 

September ................. 1,142 411 
 

October ................... 458 597 
 

November.................. 1,076 187 
 

December.................. 1,799 241 
 

2004

January ................... 1,016 1,142

February .................. 126 464

March .................... ... 56

. . . Category not applicable.

NOTE: NAS is National Asthma Survey.

study, the mean number of calls to Pending cases at the end of

complete an interview was five, with a data collection

median of three calls.

Table D details the total number of For most cases pending at the end

screening and detailed interviews of the data collection period, the

completed in the national study overall telephone number had not yet been

and by age. resolved as residential or nonresidential

Table E lists the number of (72.7% of pending cases and 21.0% of

households screened and detailed the initial sample for the national study;

interviews completed in the four-state 76.8% of pending cases and 19.4% of

study overall, by age, and by state. the initial sample for the four-state

study). A smaller number of cases had

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

Table F lists the number of

interviews conducted per month by

study from February 2003 through

March 2004.

Pretests

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 Mean Median

National study

Screening interview ................................ 7:15 6:20

Detailed interview ................................. 9:27 8:59

Four-state study

Detailed interview: households in which only an adult was sampled . . 17:20 16:21

Detailed interview: households in which only a child was sampled . . . 17:46 16:55

Detailed interview: households in which both an adult and a child

were sampled ................................... 27:57 26:37

NOTE: NAS is National Asthma Survey.

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

3:47

2:06

5:13

3:34

1:52

7:17

3:35

3:41

6:21

2:59

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 NIS ineligible

Interview section Mean Median Mean Median

Overall length ............... 9:04 9:05 9:28 8:59

Section 2:

History of asthma ............. 1:10 0:59 1:06 1:01

Section 3:

Health care utilization. . . . . . . . . . . 1:10 1:08 1:20 1:10

Section 4:

Knowledge of asthma/management

plan ..................... 1:00 0:58 0:47 0:50

Section 5:

Modification to environment ...... 2:39 2:32 2:47 2:34

Section 6:

Medications. . . . . . . . . . . . . . . . . 2:10 2:16 2:39 2:10

Section 7:

Family history of asthma ......... 0:53 0:49 0:47 0:43

NOTES: NIS is National Immunization Survey. NAS is National Asthma Survey.

(i.e., at least one child in the household national sample data were only

was 19–35 months of age at the time of self-reported if the sampled adult was

the interview). The NIS-eligible child in available at the time of the screening

the household may or may not have interview. If the sampled adult was not

been the child sampled for the NAS available, proxy responses from another

interview. adult in the household were accepted.

Table J reports mean and median Table K reports mean and median

interview lengths by section and NIS interview lengths by section and NIS

eligibility for the national study detailed eligibility for the four-state study. In this

interview. As described previously, the study, up to one asthmatic adult and one

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.

Refusals

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).

Spanish-language interviewing

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 weights were used in the calculations).

570 households in the Spanish-language Rates were calculated separately for the

queue were screened, resulting in 28 national and four-state studies. Within

completed detailed interviews. These each study, rates were calculated in total

cases account for 5.7% of all screening and by sample type (i.e., the NIS sample

interviews and 2.9% of all detailed compared with the NAS-only sample).

interviews. In the four-state study, a Response rates calculated include the

total of 282 Spanish-queue detailed interview completion rate (the

interviews were completed, accounting percentage of completed interviews

for 4.9% of all detailed interviews. among eligible respondents), the

screener completion rate (the proportion

Response rates of known households screened for

asthma status), and the resolution rate

Weighted response rates for NAS (the proportion of telephone numbers

are shown in Table L (base sampling

Table L. Weighted response rates: NAS, 2003

National study Four-state study

Screening interview Detailed interview Detailed interview

Rates (expressed as percentage)

Total

sample

NIS

sample

NAS-only

sample

Total

sample

NIS

sample

NAS-only

sample

Total

sample

NIS

sample

NAS-only

sample

Resolution rate ........................

Screener completion rate ..................

Interview completion rate ..................

CASRO response rate....................

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.
 

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
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-noanswer 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

Rate (percentage)

National study Four-state study
 

Sampled adults Sampled children Sampled adults Sampled children
 

Interview completion rate ........ 80.00 86.00 68.60 75.50 
 

CASRO response rate .......... 46.60 50.10 47.40 52.20 
 

NOTES: NAS is National Asthma Survey. CASRO is the Council of American Survey Research Organizations.
Page 16 [ Series 1, No. 46

Table N. Final sample disposition, national and four-state studies: NAS, 2003	 

Number of selected telephone lines

National study Four-state study

Final disposition

Total

sample

NIS NAS-only Total NIS NAS-only

sample sample sample sample sample

Total .....................

Not resolved as residential or

nonresidential...............

Out of scope (i.e., business or

nonworking)................

Known household, study eligibility not

determined ................

Screened ineligible household .....

Screened eligible household,

language barrier .............

Screened eligible household,

interview not completed ........

Screened eligible household,

interview completed ...........

55,204

11,626

29,369

4,155

8,852

19

228

955

12,779

2,229

6,795

1,190

2,321

3

46

195

42,425

9,397

22,574

2,965

6,531

16

182

760

210,109

40,824

110,956

10,144

40,852

10

2,198

5,125

109,401

19,638

58,003

6,450

21,794

7

1,052

2,457

100,708

21,186

52,953

3,694

19,058

3

1,146

2,668

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

period, prevent the release of excess

cases to telephone centers, and assist in

timely sample management decision

making.

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-forage. 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.

References

1.	 Department of Health and Human

Services, Office of the Assistant

Secretary for Planning and Evaluation,

Office of Science and Data Policy.

Action against asthma: A strategic plan

for the Department of Health and

Human Services [online]. [cited 2006

Sept 25] Available from: http://

aspe.hhs.gov/sp/asthma/. 2000.

2.	 Beach J, Rowe BH, Blitz S, et al.

Diagnosis and management of

work-related asthma. Contract number

290–02–0023. Evidence Report/

Technology Assessment No. 129.

AHRQ publication no. 06–E003–2.

Rockville, MD: Agency for Healthcare

Research and Quality. 2005.

3.	 Adams PF, Hendershot GE, Marano

MA. Current estimates from the

National Health Interview Survey,

1996. National Center for Health

Statistics. Vital Health Stat 10(200).

1999.

4.	 Weiss KB, Sullivan SD. The health

economics of asthma and rhinitis. I.

Assessing the economic impact. J

Allergy Clin Immunol 107(1):3–8.

2001.

5.	 Dey AN, Schiller JS, Tai DA. Summary

health statistics for U.S. children:

National Health Interview Survey,

2002. National Center for Health

Statistics. Vital Health Stat 10(221).

2004.
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6. Lethbridge-Çejku M, Schiller JS,

Bernadel L. Summary health statistics

for U.S. adults: National Health

Interview Survey, 2002. National

Center for Health Statistics. Vital

Health Stat 10(222). 2004.

7. Centers for Disease Control and

Prevention. Asthma prevalence and

control characteristics by race/

ethnicity—United States, 2002.

MMWR 53(7):145–8. 2004.

8. Akinbami LJ, Schoendorf KC. Trends

in asthma: Prevalence, health care

utilization, and mortality. Pediatrics

110(2):315–22. 2002.

9. Centers for Disease Control and

Prevention. Surveillance for asthma,

United States—1980–1999. MMWR

S1:1–14. 2002.

10. Smith PJ, Hoaglin DC, Battaglia MP, et

al. Statistical methodology of the

National Immunization Survey,

1994–2002. National Center for Health

Statistics. Vital Health Stat 2(138).

2005.

11. SUDAAN [computer program].

Software release 8.0. Research Triangle

Park, NC: Research Triangle Institute.

2003.

12. Becker C, Rodkin S, O’Connor KS, et

al. How accurate are proxy reports:

Results of a verification study. In:

Proceedings of the Section on Survey

Research Methods. Alexandria, VA:

American Statistical Association. p.

4920–2. 2004.

13. Frankel LR. The report of the CASRO

task force on response rates. In:

Wiseman F, editor. Improving data

quality in sample surveys. Cambridge,

MA: Marketing Science Institute. p.

1–11. 1983.

14. American Association for Public

Opinion Research. Standard definitions:

Final dispositions of case codes and

outcome rates for surveys. Ann Arbor,

MI: American Association for Public

Opinion Research. 2004.

15. Smith T. A review of methods to

estimate the status of cases with

unknown eligibility, version 1.1.

Presented at: Annual meeting of the

American Association of Public

Opinion Research; Phoenix, AZ. May

15, 2004.

16. Ezzati-Rice TM, Frankel MR, Hoaglin

DC, et al. An alternative measure of

response rate in random-digit-dialing

surveys that screen for eligible

subpopulations. J Econ Soc Meas

26(2):99–109. 2000.

17. Frankel MR, Battaglia MP, Kulp DW,

et al. The impact of ring-no-answer

telephone numbers on response rates in

random-digit-dialing surveys. Presented

at: Annual meeting of the American

Statistical Association: San Francisco,

CA. August 5, 2003.

18. U.S. Office of Management and

Budget. Standards for defining

Metropolitan and Micropolitan

Statistical Areas. Federal Register

65(249). 2000.

19. Keeter S. Estimating telephone

noncoverage bias with a telephone

survey. Public Opinion Q 59(2):

196–217. 1995.

20. Brick JM, Waksberg J, Keeter S. Using

data on interruptions in telephone

service as coverage adjustments.

Survey Methodology 22(2):185–97.

1996.

21. Frankel MR, Srinath KP, Hoaglin DC,

et al. Adjustments for non-telephone

bias in random-digit-dialing surveys.

Stat Med 22(9):1611–26. 2003.

22. SAS [computer program]. SAS version

8. Cary, NC: SAS Institute Inc. 1999.

23. STATA [computer program]. Data

Analysis and Statistical Software

release 8. College Station, TX:

StataCorp L.P. 2003.

24. WesVar [computer program]. WesVar:

Software for Analysis of data from

complex samples. Rockville, MD:

Westat, Inc. Available from: http://

www.westat.com/wesvar/.

25. National Asthma Education and

Prevention Program (NAEPP), NAEPP

Expert Panel Report. Guidelines for the

diagnosis and management of

asthma—Updated on selected topics,

2002. NIH publication number

02–5075. Bethesda, MD: National

Institutes of Health. 2002.

26. Abt Associates Inc. The National

Immunization Survey (NIS): 1999

annual methodology report. Cambridge,

MA: Abt Associates Inc. 2002.

27. Shapiro G, Battaglia M, Camburn D, et

al. Calling local telephone company

business offices to determine the

residential status of a wide class of

unresolved telephone numbers in a

random-digit-dialing sample. In:

Proceedings of the Section on Survey

Research Methods. Alexandria, VA:

American Statistical Association. p.

975–80. 1995.

28. Lohr S. Sampling: Design and analysis.

Pacific Grove, CA: Duxbury Press. p.

269–71. 1999.

29. Cox BG. The weighted sequential hot

deck imputation procedure. In:

Proceedings of the Section on Survey

Research Methods. Washington, DC:

American Statistical Association. p.

721–6. 1980.

30. Smith PJ, Srinath KP, Battaglia MP, et

al. Issues relating to the use of

jackknife methods in the National

Immunization Survey. In: Proceedings

of the Section on Survey Research

Methods. Alexandria, VA: American

Statistical Association. p. 709–14. 2000.
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-digitdialing (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/statssurv/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 – ) , N1 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.

n1 n2 n3

p3 = (1 – ) (1 – ) , N1 N2 N3

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.

n1 n2 n3 n4

p4 = (1 – ) (1 – ) (1 – ) , N1 N2 N3 N4

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

w

wk = . 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-noanswer 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

n ^ 1 + n31 A1 = , n1

^

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).

where n31 is the estimated number of

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

k = 1

A2 = . q1 +

∑ 

q2

A1wk

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

wp

k = 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

q1households in which the sampled

respondent had asthma is q*

1. The

nonresponse adjustment factor for the

interview nonresponse is given by q1

p ∑ wkmk

k = 1

A3 = . q*1

p ∑ wkmk

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

wp

ak = 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

p wfk .

The subscript f denotes the final weight.

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, ma

k denotes the number of

adults with asthma in the household,

and mc

k denotes the number of children

with asthma in the household. The

sampling weight for the selected adult

with asthma is

a a wk = wakmk .

The sampling weight for the selected

child with asthma is

wc c

k . k = wakm

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

q

a ∑ wk

Aa k = 1

3 = . q

a ∑ wk

k = 1

Similarly, the adjustment for

nonresponse by selected children with

asthma is given by

u

c ∑ wk

k = 1

Ac = . 3 u

c ∑ wk

k = 1

To compute the nonresponse-adjusted

weights, wa

k is multiplied by Aa3 and wck

by Ac

3.

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:

‘‘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:

+	 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

wa = c

fk wfk .

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.

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.

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

Table I. Number of values imputed for 2003 NAS poststratification variables

Number of missing values

Variable National study Four-state study

Age. . . . . . . . . . . . . . . . . . . . . . . . . 10 
 

Sex . . . . . . . . . . . . . . . . . . . . . . ... 11 
 

Race . . . . . . . . . . . . . . . . . . . . . 310 122 
 

Hispanic ethnicity ............. 61 123 
 

Number of telephone lines........ 59 82 
 

Interrupted telephone service ...... 124 106 
 

. . . Category not applicable.

NOTE: NAS is National Asthma Survey.

Table II. Summary statistics for poststratified weights, total screener and detailed

interviews, national sample: NAS, 2003

Unweighted

sample size

Minimum

weight

Maximum

weight

Mean

weight

Median

weight

Sum of

weights

United States ........... 8,621 9,108.50

Weight = post_pr_int

114,806.07 32,339.06 26,971.21 278,795,037

United States ........... 7,521 9,102.80

Weight = post_sr_int

150,939.64 37,068.88 31,259.29 278,795,037

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

Unweighted Minimum Maximum Mean Median Sum of

Four-state sample sample size weight weight weight weight weights

Weight = weight_int1

Total ..................... 5,741 56.026 14,910.770 1,596.073 1,169.764 9,163,056

Alabama................... 1,488 56.026 1,698.840 353.095 302.576 525,405

California .................. 1,433 408.729 14,910.770 3,228.165 2,883.732 4,625,961

Illinois .................... 1,313 213.474 4,434.976 1,068.409 922.778 1,402,821

Texas .................... 1,507 342.057 6,772.682 1,731.167 1,414.565 2,608,869

Weight = post_adult_int2

Total ..................... 3,736 65.538 14,910.770 1,794.087 1,269.086 6,702,710

Alabama................... 987 65.538 1,698.840 396.830 324.731 391,671

California .................. 931 817.640 14,910.770 3,730.567 3,314.775 3,473,158

Illinois .................... 888 213.474 4,434.976 1,178.439 1,007.008 1,046,454

Texas .................... 930 503.346 6,772.682 1,926.266 1,662.099 1,791,427

Weight = post_child_int3

Total ..................... 2,005 56.026 10,119.622 1,227.105 949.506 2,460,346

Alabama................... 501 56.026 967.894 266.934 219.651 133,734

California .................. 502 408.729 10,119.622 2,296.420 1,695.575 1,152,803

Illinois .................... 425 247.825 3,113.136 838.511 640.074 356,367

Texas .................... 577 342.057 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

wp

fk. 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 ∑
wp

fk .

i = 1

The sum of the new

n–g

weights is ∑
wp

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

area is w

p

fk. 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 wp

fhk.

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

wp

fhk yhk

^ k = 1

R .

h =

∑


nh

wp

fhk

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
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

n h

^ p Nh = ∑wfhk .

k = 1

For estimating the variance of the ^ sample proportion Rh , define

p ^ wfhk (yhk — Rh)

zhk = ^

Nh

and n h

∑ z hk

k = 1

z h = . nh

An estimate of the variance of the

proportion of persons having the

characteristic in IAP area is given by

^ n h n h

v (Rh) = (z hk – z h)

2 . nh – 1 ∑ 

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 nh

∑ ∑ zhk

^ h = 1 k = 1

R = , L ^ ∑ Nh

h = 1

where L is the number of strata (IAP

areas).

^ For estimating the variance of R, define

p ^ w ) fhk (yhk — R

z , hk = ^

N

where wp

fhk and yhk are as defined – earlier. Also zhk and zh are defined as

before and

L ^ ^ N = ∑ Nh .

h = 1

The variance of R

^ is given by

L n n h h v (R^ ) = ∑ – z h)

2 . (nh – 1) ∑ (zhk

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 (wa

fk) is

used. For child-level estimates the final

child weight (wc

fk) 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

Series 1, No. 46 [ Page 41

adults and children are denoted by wa

fhk

for adults and wc

fhkfor 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

CASEIDUNIQUE HOUSEHOLD ID NUMBER

SAMP_TYPEDERIVED. 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) NEITHER SAMPLED PERSON NOR PROXY DATA

(1) ONLY PROXY DATA

(2) ONLY SAMPLED PERSON DATA

(3) 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

IAPIDIAP AREA LOCATION

SPANISHCATI FLAG. CASE PLACED IN SPANISH QUEUE

(0) NOT PLACED IN SPANISH QUEUE

(1) PLACED IN SPANISH QUEUE

LTRADVANCE LETTER MAILED TO HOUSEHOLD

(0) NO, LETTER WAS NOT MAILED

(1) YES, LETTER MAILED

CALLDATECATI 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.

ROSTERI 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 [END INTERVIEW]

(97) REFUSED[END INTERVIEW]

FEMROSTER [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) NO[SKIP TO R_DOB (S3Q2)]

(1) YES

(6) DON’T KNOW [SKIP TO R_DOB (S3Q2)]

(7) REFUSED[SKIP TO R_DOB (S3Q2)]

CUR_AST (S3Q2) (Do you/Does he/Does she) still have asthma?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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

AGECATFor 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)UNDER 18 [SKIP TO AGECAT_K]

(2)18 OR OLDER [SKIP TO AGECAT_A]

(6)DON’T KNOW [END INTERVIEW]

(7)REFUSED [END INTERVIEW]

AGECAT_KWould you say that [the (SELECTED PERSON) is]:

(1)0 to 5 [SKIP TO R_SEX (S2Q6)]

(2)6 to 11 or [SKIP TO R_SEX (S2Q6)]

(3)12 to 17 years of age [SKIP TO R_SEX (S2Q6)]

(6)DON’T KNOW [END INTERVIEW]

(7)REFUSED [END INTERVIEW]

AGECAT_AWould 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) CURRENT ASTHMA-SAMPLED PERSON INTERVIEW: DATA IN ORIGINAL FIELDS

(2)ASTHMA, NOT CURRENT-SAMPLED PERSON INT: DATA IN ORIGINAL FIELDS

(3)NO ASTHMA-SAMPLED PERSON INTERVIEW: DATA IN ORIGINAL FIELDS

(4)ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE: DATA IN PROXY FIELDS

(5)NO ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE, SAMPLED NEVER

INTERVIEWED: DATA IN PROXY FIELDS

(6)NO ASTHMA-PROXY INT B/C SAMPLED PERSON UNAVAILABLE, SAMPLED PERSON

INTERVIEWED AT CALLBACK: DATA IN BOTH FIELDS

(7)CURRENT ASTHMA-SAMPLED PERSON & PROXY INTS: DATA IN BOTH FIELDS

(8)ASTHMA, NOT CURRENT-SAMPLED PERSON & PROXY INTS: DATA IN BOTH FIELDS

(9)CURRENT ASTHMA-PROXY INT B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS

(10) ASTHMA, NOT CURRENT-PROXY INT B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS

(11) NO ASTHMA-PROXY INTERVIEW B/C SAMPLED PERSON ILL: DATA IN ORIGINAL FIELDS

(12) SAMPLED PERSON OR ASTHMA STATUS NOT DETERMINED
Series 1, No. 46 [ Page 45

PROXYREL (S3Q6B) What is your relationship to [the (AGE) year old]?

(1) SPOUSE

(2) UNMARRIED PARTNER, BOYFRIEND/GIRLFRIEND

(3) CHILD

(4) GRANDCHILD

(5) MOTHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)

(6) FATHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)

(7) BROTHER/SISTER

(8) GRANDFATHER/GRANDMOTHER

(9) OTHER RELATIVE

(10) FOSTER CHILD

(11) HOUSEMATE/ROOMMATE

(12) ROOMER/BOARDER

(13) OTHER NON-RELATIVE

(90) UNRELATED LEGAL GUARDIAN

(96) DON’T KNOW

(97) 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) MOTHER (STEP, FOSTER, ADOPTIVE) OR FEMALE GUARDIAN

(2) FATHER (STEP, FOSTER, ADOPTIVE) OR MALE GUARDIAN

(3) SISTER OR BROTHER (STEP/FOSTER/HALF/ADOPTIVE)

(4) IN-LAW OF ANY TYPE

(5) AUNT/UNCLE

(6) GRANDPARENT

(7) OTHER FAMILY MEMBER

(8) FRIEND

(96) DON’T KNOW

(97) REFUSED

OTH_CHLD (S3Q7) [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?

(0) NO[SKIP TO INS1 (S5Q1_A)]

(1) YES

(6) DON’T KNOW [SKIP TO INS1 (S5Q1_A)]

(7) REFUSED [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)[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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

Section 2. History of Asthma (Symptoms & Episodes)

LAST_MD (S3Q10)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.]

(0) NEVER

(1) WITHIN THE PAST YEAR

(2) 1 YEAR TO LESS THAN 3 YEARS AGO

(3) 3 YEARS TO 5 YEARS AGO

(4) MORE THAN 5 YEARS AGO

(6) DON’T KNOW

(7) REFUSED
Page 46 [ Series 1, No. 46

LAST_MED (S3Q11)How long has it been since {you/[the (AGE) year old]} last took asthma medication?

[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY.]

(0) NEVER

(1) LESS THAN ONE DAY AGO

(2) 1–6 DAYS AGO

(3) 1 WEEK TO LESS THAN 3 MONTHS AGO

(4) 3 MONTHS TO LESS THAN 1 YEAR AGO

(5) 1 YEAR TO LESS THAN 3 YEARS AGO

(6) 3 YEARS TO 5 YEARS AGO

(7) MORE THAN 5 YEARS AGO

(96) DON’T KNOW

(97) REFUSED

LASTSYMP (S3Q12)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) NEVER

(1) LESS THAN ONE DAY AGO

(2) 1–6 DAYS AGO

(3) 1 WEEK TO LESS THAN 3 MONTHS AGO

(4) 3 MONTHS TO LESS THAN 1 YEAR AGO

(5) 1 YEAR TO LESS THAN 3 YEARS AGO

(6) 3 YEARS TO 5 YEARS AGO

(7) MORE THAN 5 YEARS AGO

(96) DON’T KNOW

(97) REFUSED

FLG_ASTHMA DERIVED. SOURCE OF ASTHMA STATUS REPORT

ASTHSTATDERIVED. ASTHMA STATUS OF HOUSEHOLD MEMBER

(0) NO, PERSON DOES NOT HAVE ASTHMA

(1) YES, PERSON HAS ASTHMA

LTASTHMDERIVED. 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

ASTATUS1DERIVED. CURRENT ASTHMA STATUS OF HOUSEHOLD MEMBER BASED ON SELFIDENTIFICATION

(1) PERSON SELF-IDENTIFIED ASTHMA

(0) PERSON DID NOT SELF-IDENTIFY ASTHMA

(6) DON’T KNOW

CASTHMADERIVED. 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

ASTHMSTDERIVED. COMPUTED ASTHMA STATUS BASED ON BRFSS RULES

(1) CURRENT

(2) FORMER

(3) NEVER

(9) DON’T KNOW/NOT SURE OR REFUSED

ASTATUS2DERIVED. 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) [SKIP TO ASLEEP30 (S4Q3)]

(0) NO SYMPTOMS IN THE PAST 30 DAYS [SKIP TO EPIS_INT]

(30) EVERY DAY

(96) DON’T KNOW [SKIP TO ASLEEP30 (S4Q3)]

(97) REFUSED [SKIP TO ASLEEP30 (S4Q3)]

DUR_30D (S4Q2){Do you/Does [the (AGE) year old/NAME]} have symptoms all the time?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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)[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?

(0) NO[SKIP TO INS1 (S5Q1_A)]

(1) YES

(6) DON’T KNOW[SKIP TO INS1 (S5Q1_A)]

(7) REFUSED[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?

_ _ ATTACKS OR EPISODES DURING PAST 3 MONTHS

(0) NONE

(996) DON’T KNOW

(997) 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 [SKIP TO COMPASTH (S4Q9)]

(97) REFUSED [SKIP TO COMPASTH (S4Q9)]

DUR2ASTH (S4Q8)ENTER PERIOD

(1)MINUTES

(2)HOURS

(3)DAYS

(4)WEEKS

(6)DON’T KNOW

(7)REFUSED

COMPASTH (S4Q9)Compared with other episodes or attacks, was this most recent attack shorter, longer, or about the

same?

(1)SHORTER

(2)LONGER

(3)ABOUT THE SAME

(4)THE MOST RECENT ATTACK WAS ACTUALLY THE FIRST ATTACK

(6)DON’T KNOW

(7)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)NO

(1)YES [SKIP TO INS2 (S5Q1_B)]

(6)DON’T KNOW

(7)REFUSED

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)NO

(1)YES

(6)DON’T KNOW

(7)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) NO [SKIP TO URG_TIME (S5Q4)]

(1) YES

(6) DON’T KNOW [SKIP TO URG_TIME (S5Q4)]

(7) REFUSED [SKIP TO URG_TIME (S5Q4)]

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

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

HOSP_VST (S5Q5)[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.

(0)NO [SKIP TO MISS_DAY (S5Q9)]

(1)YES

(6)DON’T KNOW [SKIP TO MISS_DAY (S5Q9)]

(7)REFUSED [SKIP TO MISS_DAY (S5Q9)]

HOSPTIME (S5Q6) [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)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?

(0)NO

(1)YES

(6)DON’T KNOW

(7)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?

_ _ _ ENTER NUMBER

(0)ZERO

(994) CHILD DID NOT GO TO SCHOOL IN PAST 12 MONTHS

(995) HOME SCHOOLED

(996) DON’T KNOW

(997) REFUSED THIS QUESTION

ACT_DAYS (S5Q12)[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?

(1)NOT AT ALL

(2)A LITTLE

(3)A MODERATE AMOUNT

(4)A LOT

(6)DON’T KNOW

(7) 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)NO

(1)YES

(6)DON’T KNOW

(7)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)NO

(1)YES

(6)DON’T KNOW

(7)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)NO

(1)YES

(6)DON’T KNOW

(7)REFUSED
Series 1, No. 46 [ Page 51

MGT_PLAN (S6Q4) 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]

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

MGT_CLAS (S6Q5)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DEHUMID (S7Q2) Is a dehumidifier regularly used to reduce moisture inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

KITC_FAN (S7Q3) Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

COOK_GAS (S7Q4) Is gas used for cooking?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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.

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

ENV_PETS (S7Q6)Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets

that arekept inside?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

C_ROACH (S7Q7) In the past 30 days, has anyone seen cockroaches inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) Is a fireplace or wood burning stove used in your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HELP SCREEN: ‘‘Unvented’’ means no chimney.

S_INSIDE (S7Q10) In the past week, has anyone smoked inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 46 [ Page 53

MATTRESS (S7Q12){Do you/Does [the (AGE) year old/NAME]} use a mattress cover that is made especially for controlling

dust mites?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

E_PILLOW (S7Q13){Do you/Does [the (AGE) year old/NAME]} use a pillow cover that is made especially for controlling dust

mites?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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)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) NO OR ‘‘NO FAN’’

(1) YES

(6) DON’T KNOW

(7) 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) Is the pet allowed in {your/[the (AGE) year old/NAME]’s} bedroom?

(0) NO

(1) YES

(2) SOME ARE/SOME AREN’T

(6) DON’T KNOW

(7) 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) NO [SKIP TO EMP_STAT (S7Q20)]

(1) YES

(6) DON’T KNOW [SKIP TO EMP_STAT (S7Q20)]

(7) REFUSED [SKIP TO EMP_STAT (S7Q20)]

CIG_FREQ (S7Q19) Do you now smoke cigarettes every day, some days, or not at all?

(1) EVERY DAY

(2) SOME DAYS

(3) NOT AT ALL

(6) DON’T KNOW

(7) 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) EMPLOYED FULL-TIME

(2) EMPLOYED PART-TIME

(3) NOT EMPLOYED

(6) DON’T KNOW

(7) 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?

(0) NO

(1) YES

(2) NEVER BEEN EMPLOYED

(6) DON’T KNOW

(7) REFUSED

UNEMP_R (S7Q22)[IF EMP_STAT (S7Q20) = 1 OR 2, SKIP TO OTC (S8Q1).] What is the main reason you are not

employed?

(1) KEEPING HOUSE

(2) GOING TO SCHOOL

(3) RETIRED

(4) DISABLED

(5) UNABLE TO WORK FOR OTHER HEALTH REASONS

(6) LOOKING FOR WORK

(7) LAID OFF

(8) OTHER

(96) DON’T KNOW

(97) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

INHALERE (S8Q2) {Have you/Has [the (AGE) year old/NAME]} ever used a prescription inhaler?

(0) NO[SKIP TO SCR_MED1 (S8Q4)]

(1) YES

(6) DON’T KNOW [SKIP TO SCR_MED1 (S8Q4)]

(7) REFUSED[SKIP TO SCR_MED1 (S8Q4)]
Series 1, No. 46 [ Page 55

INHALERH (S8Q3)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO [SKIP TO INH_SCR (S8Q7)]

(1) YES

(2) RESPONDENT KNOWS THE MEDS [SKIP TO INH_SCR (S8Q7)]

(6) DON’T KNOW

(7) REFUSED [SKIP TO INH_SCR (S8Q7)]

SCR_MED2 (S8Q5) Can you please go get the asthma medicines while I wait on the phone?

(0) NO [SKIP TO INH_SCR (S8Q7)]

(1) YES

(6) DON’T KNOW

(7) REFUSED [SKIP TO INH_SCR (S8Q7)]

SCR_MED3 (S8Q6) Am I correct that you have all the medications?

(0) NO

(1) YES I HAVE ALL THE MEDICATIONS

(2) YES I HAVE SOME OF THE MEDICATIONS BUT NOT ALL

(6) DON’T KNOW

(7) REFUSED

INH_SCR (S8Q7)In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription asthma

medicine using an inhaler?

(0) NO[SKIP TO PILLS (S8Q27)]

(1) YES

(6) DON’T KNOW [SKIP TO PILLS (S8Q27)]

(7) REFUSED[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 Brand Name Type (not shown in CATI)

INH_MEDX01 (S8Q8_01) Advair

INH_MEDX02 (S8Q8_02) Aerobid Corticosteroids

INH_MEDX03 (S8Q8_03) Albuterol Beta 2 agonist

INH_MEDX04 (S8Q8_04) Alupent Beta 2 agonist

INH_MEDX05 (S8Q8_05) Atrovent Anti-inflammatories

INH_MEDX06 (S8Q8_06) Azmacort Corticosteroids

INH_MEDX07 (S8Q8_07) Beclomethasone dipropionate Corticosteroids

INH_MEDX08 (S8Q8_08) Beclovent Corticosteroids

INH_MEDX09 (S8Q8_09) Bitolterol Beta 2 agonist

INH_MEDX10 (S8Q8_10) Brethaire Beta 2 agonist

INH_MEDX11 (S8Q8_11) Budesonide Corticosteroids

INH_MEDX12 (S8Q8_12) Combivent

INH_MEDX13 (S8Q8_13) Cromolyn Anti-inflammatories

INH_MEDX14 (S8Q8_14) Flovent Inhaled corticosteroid

INH_MEDX15 (S8Q8_15) Flovent Rotadisk Inhaled corticosteroid

INH_MEDX16 (S8Q8_16) Flunisolide Corticosteroids

INH_MEDX17 (S8Q8_17) Fluticasone Inhaled corticosteroid

INH_MEDX18 (S8Q8_18) Intal Anti-inflammatories

INH_MEDX19 (S8Q8_19) Ipratropium Bromide Anti-inflammatories

INH_MEDX20 (S8Q8_20) Maxair Beta 2 agonist

INH_MEDX21 (S8Q8_21) Metaproteronol Beta 2 agonist

INH_MEDX22 (S8Q8_22) Nedocromil Anti-inflammatories

INH_MEDX23 (S8Q8_23) Pirbuterol Beta 2 agonist

INH_MEDX24 (S8Q8_24) Proventil Beta 2 agonist

INH_MEDX25 (S8Q8_25) Pulmicort Turbuhaler Corticosteroids

INH_MEDX26 (S8Q8_26) Salmeterol Corticosteroids (long lasting)

INH_MEDX27 (S8Q8_27) Serevent Beta 2 agonist (long lasting)

INH_MEDX28 (S8Q8_28) Terbutaline Beta 2 agonist

INH_MEDX29 (S8Q8_29) Tilade Anti-inflammatories

INH_MEDX30 (S8Q8_30) Tornalate Beta 2 agonist

INH_MEDX31 (S8Q8_31) Triamcinolone acetonide Corticosteroids

INH_MEDX32 (S8Q8_32) Vanceril Corticosteroids

INH_MEDX33 (S8Q8_33) Ventolin Beta 2 agonist

INH_MEDX34 (S8Q8_34) 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) NO

(1) YES

(6) DON’T KNOW [SKIP TO REC_MED1]

(7) REFUSED [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)In the past 3 months, did {you/[the (AGE) year old/NAME]} take Flovent or Flovent Rotadisk using an

inhaler?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3INHLR (S8Q11)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4INHLR (S8Q12)In the past 3 months, did {you/[the (AGE) year old/NAME]} take:

Intal, Cromolyn,

Tilade, or Nedocromil?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5INHLR (S8Q13)In the past 3 months, did {you/[the (AGE) year old/NAME]} take:

Atrovent or Ipratropium Bromide?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK6INHLR (S8Q14) Did {you/[the (AGE) year old/NAME]} take a medication by inhaler that we have not mentioned?

(0) NO

(1) YES [SKIP TO DK7INHLR (S8Q15)]

(6) DON’T KNOW

(7) REFUSED

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) Less than 6 months

(2) 6 months to 1 year

(3) Longer than 1 year

(6) DON’T KNOW

(7) 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) 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) NO

(1) YES

(2) NO ATTACK IN PAST 3 MONTHS

(6) DON’T KNOW

(7) 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) NO

(1) YES

(2) DIDN’T EXERCISE IN PAST 3 MONTHS

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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) 44 MICROGRAMS

(2) 50 MICROGRAMS

(3) 100 MICROGRAMS

(4) 110 MICROGRAMS

(5) 220 MICROGRAMS

(6) 250 MICROGRAMS

(7) TOOK MORE THAN 1 IN PAST 3 MONTHS

(96) DON’T KNOW

(97) 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.

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 [SKIP TO ILP11 (S8Q26_nn)]

(996) DON’T KNOW [SKIP TO ILP11 (S8Q26_nn)]

(997) REFUSED [SKIP TO ILP11 (S8Q26_nn)]

ILP10 (S8Q25_01 to S8Q25_34)

ENTER PERIOD

(1) PER DAY

(2) PER WEEK

(6) DON’T KNOW

(7) 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 Medication Type (not shown in CATI)

PILLS_MX01 (S8Q28_01) Accolate Leukotriene modifiers

PILLS_MX02 (S8Q28_02) Aerolate Methylxanthines

PILLS_MX03 (S8Q28_03) Albuterol Beta 2 agonist – Rescue bronchodilators

PILLS_MX04 (S8Q28_04) Alupent Beta 2 agonist – Rescue bronchodilators

PILLS_MX05 (S8Q28_05) Choledyl Methylxanthines

PILLS_MX06 (S8Q28_06) Cromolyn Anti-Inflammatories

PILLS_MX07 (S8Q28_07) Deltasone Corticosteriods

PILLS_MX08 (S8Q28_08) Elixophyllin Methylxanthines

PILLS_MX09 (S8Q28_09) Intal Anti-Inflammatories

PILLS_MX10 (S8Q28_10) Marax Methylxanthines

PILLS_MX11 (S8Q28_11) Medrol Corticosteriods

PILLS_MX12 (S8Q28_12) Metaprel Beta 2 agonist – Rescue bronchodilators

PILLS_MX13 (S8Q28_13) Metaproteronol Beta 2 agonist – Rescue bronchodilators

PILLS_MX14 (S8Q28_14) Methylpredinisolone Corticosteriods

PILLS_MX15 (S8Q28_15) Montelukast Leukotriene modifiers

PILLS_MX16 (S8Q28_16) Nedocromil Corticosteriods

PILLS_MX17 (S8Q28_17) Pediapred Corticosteriods

PILLS_MX18 (S8Q28_18) Prednisolone Corticosteriods

PILLS_MX19 (S8Q28_19) Prednisone Corticosteriods

PILLS_MX20 (S8Q28_20) Prelone Corticosteriods

PILLS_MX21 (S8Q28_21) Proventil Beta 2 agonist – Rescue bronchodilators

PILLS_MX22 (S8Q28_22) Quibron Methylxanthines

PILLS_MX23 (S8Q28_23) Respid Methylxanthines

PILLS_MX24 (S8Q28_24) Singulair Leukotriene modifiers

PILLS_MX25 (S8Q28_25) Slo-phyllin Methylxanthines

PILLS_MX26 (S8Q28_26) Slo-bid Methylxanthines

PILLS_MX27 (S8Q28_27) Sustaire Methylxanthines

PILLS_MX28 (S8Q28_28) Theo-24 Methylxanthines

PILLS_MX29 (S8Q28_29) Theobid Methylxanthines

PILLS_MX30 (S8Q28_30) Theochron Methylxanthines

PILLS_MX31 (S8Q28_31) Theoclear Methylxanthines

PILLS_MX32 (S8Q28_32) Theodur Methylxanthines

PILLS_MX33 (S8Q28_33) Theo-Dur Methylxanthines

PILLS_MX34 (S8Q28_34) Theolair Methylxanthines

PILLS_MX35 (S8Q28_35) Theophylline Methylxanthines

PILLS_MX36 (S8Q28_36) Theo-Sav Methylxanthines

PILLS_MX37 (S8Q28_37) Theospan Methylxanthines

PILLS_MX38 (S8Q28_38) Theox Methylxanthines

PILLS_MX39 (S8Q28_39) Tilade Corticosteriods

PILLS_MX40 (S8Q28_40) T-Phyl Methylxanthines

PILLS_MX41 (S8Q28_41) Unidur Methylxanthines

PILLS_MX42 (S8Q28_42) Uniphyl Methylxanthines

PILLS_MX43 (S8Q28_43) Ventolin Beta 2 agonist – Rescue bronchodilators

PILLS_MX44 (S8Q28_44) Volmax Beta 2 agonist – Rescue bronchodilators

PILLS_MX45 (S8Q28_45) Zafirlukast Leukotriene modifiers

PILLS_MX46 (S8Q28_46) Zileuton Leukotriene modifiers

PILLS_MX47 (S8Q28_47) Zyflo Filmtab Leukotriene modifiers

PILLS_MX48 (S8Q28_48) Other, please specify: [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) Did {you/[the (AGE) year old/NAME]} take:

Accolate or Zafirlukast

Zyflo Filmtab or Zileuton

Singulair or Montelukast?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_PILL (S8Q31)Did {you/[the (AGE) year old/NAME]} take:

Intal or Cromolyn

Tilade or Nedocromil?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_PILL (S8Q32)Did {you/[the (AGE) year old/NAME]} take:

Medrol, Methylpredinisolone,

Deltasone, Prednisone,

Pediapred,

Prelone, or Prednisolone?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4_PILL (S8Q33)Did {you/[the (AGE) year old/NAME]} take:

Proventil, Ventolin, Volmax, or Albuterol

Alupent, Metaprel, or Metaproteronol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5_PILL (S8Q34)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO [SKIP TO PILLX (S8Q37_nn)]

(1) YES [SKIP TO DK7_PILL (S8Q36)]

(6) DON’T KNOW [SKIP TO PILLX (S8Q37_nn)]

(7) REFUSED [SKIP TO PILLX (S8Q37_nn)]

DK7_PILL (S8Q36) 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) LESS THAN 6 MONTHS

(2) 6 MONTHS TO 1 YEAR

(3) LONGER THAN 1 YEAR

(6) DON’T KNOW

(7) REFUSED

SYRUP (S8Q38) In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription medicine in syrup form?

(0) NO [SKIP TO NEB_SCR (S8Q47)]

(1) YES

(6) DON’T KNOW [SKIP TO NEB_SCR (S8Q47)]

(7) 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 Medication

SYRUP_IX01 (S8Q39_01) Aerolate

SYRUP_IX02 (S8Q39_02) Albuterol

SYRUP_IX03 (S8Q39_03) Alupent

SYRUP_IX04 (S8Q39_04) Metaproteronol

SYRUP_IX05 (S8Q39_05) Prednisolone

SYRUP_IX06 (S8Q39_06) Prelone

SYRUP_IX07 (S8Q39_07) Proventil

SYRUP_IX08 (S8Q39_08) Slo-Phyllin

SYRUP_IX09 (S8Q39_09) Theophylline

SYRUP_IX10 (S8Q39_10) Ventolin

SYRUP_IX11 (S8Q39_11) 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) NO

(1) YES

(6) DON’T KNOW [SKIP TO REC_MED3]

(7) REFUSED [SKIP TO NEB_SCR (S8Q47)]

OTH_S1 (S8Q40) 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)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Alupent or Metaproteronol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_SYRP (S8Q42)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Ventolin or Proventil or Albuterol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_SYRP (S8Q43)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Aerolate, Slo-Phyllin, or Theophylline?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4_SYRP (S8Q44)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Prelone or Prednisolone?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5_SYRP (S8Q45) Did {you/[the (AGE) year old/NAME]} take a medication in syrup form that we have not mentioned?

(0) NO [SKIP TO NEB_SCR (S8Q47)]

(1) YES

(6) DON’T KNOW [SKIP TO NEB_SCR (S8Q47)]

(7) REFUSED [SKIP TO NEB_SCR (S8Q47)]

DK6_SYRP (S8Q46)Will you please tell me what that medication was?

SPELL OUT: _____________________________________

NEB_SCR (S8Q47)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?

(0) NO[SKIP TO SECTION 7]

(1) YES

(6) DON’T KNOW[SKIP TO SECTION 7]

(7) REFUSED[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 Medication

NEB_IDX01 (S8Q48_01) Albuterol

NEB_IDX02 (S8Q48_02) Alupent

NEB_IDX03 (S8Q48_03) Cromolyn

NEB_IDX04 (S8Q48_04) Intal

NEB_IDX05 (S8Q48_05) Metaproteronol

NEB_IDX06 (S8Q48_06) Proventil

NEB_IDX07 (S8Q48_07) Ventolin

NEB_IDX08 (S8Q48_08) 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) NO

(1) YES

(6) DON’T KNOW[SKIP TO DK1_NEB (S8Q50)]

(7) REFUSED[SKIP TO SECTION 7]

OTH_N1 (S8Q49)ENTER OTHER MEDICATION.

IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.

________________________ ENTER TEXT

DK1_NEB (S8Q50)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_NEB (S8Q51)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_NEB (S8Q52)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

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4_NEB (S8Q53) Did {you/[the (AGE) year old/NAME]} take a medication using a nebulizer that we have not mentioned?

(0) NO[SKIP TO SECTION 7]

(1) YES

(6) DON’T KNOW[SKIP TO SECTION 7]

(7) REFUSED[SKIP TO SECTION 7]

DK5_NEB (S8Q54)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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

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.

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) NO [SKIP TO BROASTH1 (S9Q5)]

(1) YES

(6) DON’T KNOW [SKIP TO BROASTH1 (S9Q5)]

(7) REFUSED [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) FATHER

(2) MOTHER

(3) BOTH

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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?

__ __ 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.

GRANDSCR (S9Q9) Were any of [your/the (AGE) year old’s] biological grandparents ever told they had asthma?

(0) NO [SKIP TO OTHER_T (S11Q1)]

(1) YES

(6) DON’T KNOW [SKIP TO OTHER_T (S11Q1)]

(7) REFUSED [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.

GRNDASTHWhich of {your/the (AGE) year old’s} biological grandparents were told they had asthma?

[MARK ALL THAT APPLY]

(S9Q10_01) MOTHER’S MOTHER

(S9Q10_02) MOTHER’S FATHER

(S9Q10_03) FATHER’S MOTHER

(S9Q10_04) FATHER’S FATHER

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO [SKIP TO WO_SERVICE (S11Q7)]

(1) YES

(6) DON’T KNOW [SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED [SKIP TO WO_SERVICE (S11Q7)]

SEC_USE (S11Q2) Is this second number for home use only, for business use only, or for both home and business use?

(1) HOME ONLY

(2) BUSINESS ONLY[SKIP TO THIRD_TN (S11Q4)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED [SKIP TO WO_SERVICE (S11Q7)]

SEC_FAX (S11Q3) Is this second number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO[SKIP TO WO_SERVICE (S11Q7)]

(1) YES

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED[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) HOME ONLY

(2) BUSINESS ONLY[SKIP TO WO_SERVICE (S11Q7)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED [SKIP TO WO_SERVICE (S11Q7)]

THIRD_FAX (S11Q6) Is this third number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

NUM_PHON DERIVED. NUMBER OF TELEPHONES FOR HOME USE

WO_SERVICE (S11Q7) 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.

(0) NO[SKIP TO R_ETH_2 (HISPANIC)]

(1) YES

(6) DON’T KNOW[SKIP TO R_ETH_2 (HISPANIC)]

(7) REFUSED [SKIP TO R_ETH_2 (HISPANIC)]

C11Q21_A (S11Q8) 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[SKIP TO R_ETH_2 (HISPANIC)]

(997) REFUSED[SKIP TO R_ETH_2 (HISPANIC)]
Page 68 [ Series 1, No. 46

C11Q21 (S11Q9) ENTER PERIOD

(1) DAYS

(2) WEEK(S)

(3) MONTH(S)

(6) DON’T KNOW

(7) REFUSED

NOPHONE DERIVED. NUMBER OF DAYS WITHOUT TELEPHONE SERVICE

R_ETH_2 (HISPANIC) [Are you/Is the (AGE) year old] of Hispanic or Latino origin?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HISPANIC_DERIVED DERIVED. HISPANIC ORIGIN OF HOUSEHOLD MEMBER.

R_RACE2Now, 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]

(S2Q11_01) WHITE

(S2Q11_02) BLACK/AFRICAN-AMERICAN

(S2Q11_03) AMERICAN INDIAN

(S2Q11_04) ALASKA NATIVE

(S2Q11_05) ASIAN

(S2Q11_06) NATIVE HAWAIIAN

(S2Q11_07) PACIFIC ISLANDER

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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 OR __ __ __ __ grams [SKIP TO INC_TOT (S10Q1)]

(96) DON’T KNOW (9996) DON’T KNOW [SKIP TO BIRTHRF (S2Q17)]

(97) REFUSED (9997) REFUSED [SKIP TO BIRTHRF (S2Q17)]

BIRTHWEIGHT DERIVED. CHILD’S BIRTHWEIGHT IN GRAMS

BIRTHRF (S2Q17) At birth, did [the (AGE) year old/NAME] weigh less than 5 1/2 pounds?

[INTERVIEWER NOTE: 5 1/2 pounds = 2500 GRAMS]

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

INC_TOT (S10Q1)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) MORE THAN $20,000 [SKIP TO RANGE_40 (S10Q9)]

(2) $20,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $20,000[SKIP TO RANGE_10 (S10Q4)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_10 (S10Q4) Was the total combined household income more or less than $10,000?

(1) MORE THAN $10,000 [SKIP TO RANGE_15 (S10Q6)]

(2) $10,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $10,000[SKIP TO RANGE_7 (S10Q5)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_7 (S10Q5) Was it more than $7,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_15 (S10Q6) Was it more than $15,000?

(0) NO[SKIP TO RANGE_12 (S10Q8)]

(1) YES[SKIP TO RANGE_17 (S10Q7)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_17 (S10Q7) Was it more than $17,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_12 (S10Q8) Was it more than $12,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_40 (S10Q9) Was the total combined household income more or less than $40,000?

(1) MORE THAN $40,000 [SKIP TO RANGE_60 (S10Q10)]

(2) $40,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $40,000[SKIP TO RANGE_30 (S10Q13)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_60 (S10Q10) Was the total combined household income more or less than $60,000?

(1) MORE THAN $60,000 [SKIP TO RANGE_75 (S10Q16)]

(2) $60,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $60,000[SKIP TO RANGE_50 (S10Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]
Series 1, No. 46 [ Page 71

RANGE_50 (S10Q11) Was the total combined household income more or less than $50,000?

(1) MORE THAN $50,000 [SKIP TO C11Q22 (S11Q11)]

(2) $50,000 [SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $50,000 [SKIP TO RANGE_45 (S10Q12)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_45 (S10Q12) Was the total combined household income more or less than $45,000?

(1) MORE THAN $45,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $45,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_30 (S10Q13) Was the total combined household income more or less than $30,000?

(1) MORE THAN $30,000 [SKIP TO RANGE_35 (S10Q14)]

(2) $30,000 [SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $30,000 [SKIP TO RANGE_25 (S10Q15)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_35 (S10Q14) Was the total combined household income more or less than $35,000?

(1) MORE THAN $35,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $35,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_25 (S10Q15) Was the total combined household income more or less than $25,000?

(1) MORE THAN $25,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $25,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_75 (S10Q16) Was the total combined household income more or less than $75,000?

(1) MORE THAN $75,000 [SKIP TO C11Q22 (S11Q11)]

(2) $75,000 [SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $75,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

BESTINCOME 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) NO

(1) YES [SKIP TO INS2P (S5Q1_BP)]

(6) DON’T KNOW

(7) REFUSED

INS2P (S5Q1_BP) [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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

AIRCLEANEP (S7Q1P) Is an air cleaner or purifier regularly used inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DEHUMIDP (S7Q2P) Is a dehumidifier regularly used to reduce moisture inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

KITC_FANP (S7Q3P) Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

COOK_GASP (S7Q4P) Is gas used for cooking?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

ENV_MOLDP (S7Q5P)In the past 30 days, has anyone seen or smelled mold or a musty odor inside your home? Do not

include mold on food.

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

ENV_PETSP (S7Q6P)Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets

that are kept inside?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 46 [ Page 73

C_ROACHP (S7Q7P) In the past 30 days, has anyone seen cockroaches inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) Is a fireplace or wood burning stove used in your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HELP SCREEN: OCCASIONAL USE SHOULD BE CODED AS ‘‘YES.’’

GAS_STOVEP (S7Q9P) Are unvented gas logs, an unvented gas fireplace, or an unvented gas stove used in your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HELP SCREEN: ‘‘Unvented’’ means no chimney.

S_INSIDE (S7Q10P) In the past week, has anyone smoked inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HELP SCREEN: ‘‘Smoked’’ means ‘‘anything.’’

SKIP TO OTHRASTHP IF INTERVIEW IS FOR SAMPLED CHILD (R_DOB/S2Q5 < 18).

CIGARETSP (S7Q18P) {Has (the (AGE) year old) smoked at least 100 cigarettes in [his or her]} entire life?

(0) NO [SKIP TO EMP_STATP (S7Q20P)]

(1) YES

(6) DON’T KNOW [SKIP TO EMP_STATP (S7Q20P)]

(7) REFUSED [SKIP TO EMP_STATP (S7Q20P)]

CIG_FREQP (S7Q19P) Does [the (AGE) year old] now smoke cigarettes every day, some days, or not at all?

(1) EVERY DAY

(2) SOME DAYS

(3) NOT AT ALL

(6) DON’T KNOW

(7) REFUSED

EMP_STATP (S7Q20P)[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 . . .

(1) EMPLOYED FULL-TIME

(2) EMPLOYED PART-TIME

(3) NOT EMPLOYED

(6) DON’T KNOW

(7) REFUSED
Page 74 [ Series 1, No. 46

UNEMP_RP (S7Q22P)[IF EMP_STATP (S7Q20P) = 1 OR 2, SKIP TO OTHRASTHP] What is the main reason [the (AGE)

year old is] not employed?

(1) KEEPING HOUSE

(2) GOING TO SCHOOL

(3) RETIRED

(4) DISABLED

(5) UNABLE TO WORK FOR OTHER HEALTH REASONS

(6) LOOKING FOR WORK

(7) LAID OFF

(8) OTHER

(96) DON’T KNOW

(97) REFUSED

OTHRASTHPBesides [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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

OTHER_TP (S11Q1P)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) NO[SKIP TO WO_SERVICP (S11Q7P)]

(1) YES

(6) DON’T KNOW[SKIP TO WO_SERVICP (S11Q7P)]

(7) REFUSED [SKIP TO WO_SERVICP (S11Q7P)]

SEC_USEP (S11Q2P) Is this second number for home use only, for business use only, or for both home and business use?

(1) HOME ONLY

(2) BUSINESS ONLY[SKIP TO THIRD_TNP (S11Q4P)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICP (S11Q7P)]

(7) REFUSED [SKIP TO WO_SERVICP (S11Q7P)]

SEC_FAXP (S11Q3P) Is this second number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED[SKIP TO WO_SERVICP (S11Q7P)]

THIRD_TNP (S11Q4P)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) NO[SKIP TO WO_SERVICP (S11Q7P)]

(1) YES

(6) DON’T KNOW[SKIP TO WO_SERVICP (S11Q7P)]

(7) REFUSED [SKIP TO WO_SERVICP (S11Q7P)]

THIRD_USEP (S11Q5P) Is this third number for home use only, for business use only, or for both home and business use?

(1) HOME ONLY

(2) BUSINESS ONLY[SKIP TO WO_SERVICP (S11Q7P)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICP (S11Q7P)]

(7) REFUSED[SKIP TO WO_SERVICP (S11Q7P)]
Series 1, No. 46 [ Page 75

THIRD_FAXP (S11Q6P) Is this third number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

WO_SERVICP (S11Q7P) 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.

(0) NO [SKIP TO R_ETH_2P (HISPANICP)]

(1) YES

(6) DON’T KNOW [SKIP TO R_ETH_2P (HISPANICP)]

(7) REFUSED [SKIP TO R_ETH_2P (HISPANICP)]

C11Q21_AP (S11Q8P) 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 [SKIP TO R_ETH_2P (HISPANICP)]

(997) REFUSED [SKIP TO R_ETH_2P (HISPANICP)]

C11Q21P (S11Q9P) ENTER PERIOD

(1) DAYS

(2) WEEK(S)

(3) MONTH(S)

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

R_RAC2PNow, 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) WHITE

(S2Q11_02P) BLACK/AFRICAN-AMERICAN

(S2Q11_03P) AMERICAN INDIAN

(S2Q11_04P) ALASKA NATIVE

(S2Q11_05P) ASIAN

(S2Q11_06P) NATIVE HAWAIIAN

(S2Q11_07P) PACIFIC ISLANDER

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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)[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)

(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

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 (9996) DON’T KNOW [SKIP TO BIRTHRFP (S2Q17P)]

(97) REFUSED (9997) REFUSED [SKIP TO BIRTHRFP (S2Q17P)]
Series 1, No. 46 [ Page 77

BIRTHRFP (S2Q17P)At birth, did [the (AGE) year old/NAME] weigh less than 5 1/2 pounds?

[INTERVIEWER NOTE: 5 1/2 pounds = 2500 GRAMS]

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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)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) MORE THAN $20,000[SKIP TO RANGE_40P (S10Q9P)]

(2) $20,000[SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $20,000[SKIP TO RANGE_10P (S10Q4P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_10P (S10Q4P) Was the total combined household income more or less than $10,000?

(1) MORE THAN $10,000[SKIP TO RANGE_15P (S10Q6P)]

(2) $10,000[SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $10,000[SKIP TO RANGE_7P (S10Q5P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_7P (S10Q5P) Was it more than $7,500?

(0) NO[SKIP TO C11Q22P (S11Q11P)]

(1) YES[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_15P (S10Q6P) Was it more than $15,000?

(0) NO[SKIP TO RANGE_12P (S10Q8P)]

(1) YES[SKIP TO RANGE_17P (S10Q7P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_17P (S10Q7P) Was it more than $17,500?

(0) NO[SKIP TO C11Q22P (S11Q11P)]

(1) YES[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_12P (S10Q8P) Was it more than $12,500?

(0) NO[SKIP TO C11Q22P (S11Q11P)]

(1) YES[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED[SKIP TO C11Q22P (S11Q11P)]
Page 78 [ Series 1, No. 46

RANGE_40P (S10Q9P) Was the total combined household income more or less than $40,000?

(1) MORE THAN $40,000 [SKIP TO RANGE_60P (S10Q10P)]

(2) $40,000 [SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $40,000 [SKIP TO RANGE_30P (S10Q13P)]

(6) DON’T KNOW [SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_60P (S10Q10P) Was the total combined household income more or less than $60,000?

(1) MORE THAN $60,000[SKIP TO RANGE_75P (S10Q16P)]

(2) $60,000[SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $60,000[SKIP TO RANGE_50P (S10Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_50P (S10Q11P) Was the total combined household income more or less than $50,000?

(1) MORE THAN $50,000[SKIP TO C11Q22P (S11Q11P)]

(2) $50,000[SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $50,000[SKIP TO RANGE_45P (S10Q12P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_45P (S10Q12P) Was the total combined household income more or less than $45,000?

(1) MORE THAN $45,000[SKIP TO C11Q22P (S11Q11P)]

(2) LESS THAN $45,000[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_30P (S10Q13P) Was the total combined household income more or less than $30,000?

(1) MORE THAN $30,000[SKIP TO RANGE_35P (S10Q14P)]

(2) $30,000[SKIP TO C11Q22P (S11Q11P)]

(3) LESS THAN $30,000[SKIP TO RANGE_25P (S10Q15P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_35P (S10Q14P) Was the total combined household income more or less than $35,000?

(1) MORE THAN $35,000[SKIP TO C11Q22P (S11Q11P)]

(2) LESS THAN $35,000[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_25P (S10Q15P) Was the total combined household income more or less than $25,000?

(1) MORE THAN $25,000[SKIP TO C11Q22P (S11Q11P)]

(2) LESS THAN $25,000[SKIP TO C11Q22P (S11Q11P)]

(6) DON’T KNOW[SKIP TO C11Q22P (S11Q11P)]

(7) REFUSED [SKIP TO C11Q22P (S11Q11P)]

RANGE_75P (S10Q16P) Was the total combined household income more or less than $75,000?

(1) MORE THAN $75,000

(2) $75,000

(3) LESS THAN $75,000

(6) DON’T KNOW

(7) REFUSED

C11Q22P (S11Q11P)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 HOUSEHOLD ID NUMBER

CASEIDX 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)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]

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

IF SCR_OTHRS (S2Q2) = 0, 6, 7, END INTERVIEW.

ROSTI 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) [SKIP TO ROSTKID]

(96) DON’T KNOW[END INTERVIEW]

(97) REFUSED[END INTERVIEW]

ROSTKIDHow 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[END INTERVIEW]

(97) REFUSED [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[END INTERVIEW]

(997) 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

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) SPOUSE

(2) UNMARRIED PARTNER, BOYFRIEND/GIRLFRIEND

(3) CHILD

(4) GRANDCHILD

(5) MOTHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)

(6) FATHER (BIRTH/ADOPTIVE/STEP/FOSTER/OTHER)

(7) BROTHER/SISTER

(8) GRANDFATHER/GRANDMOTHER

(9) OTHER RELATIVE

(10) FOSTER CHILD

(11) HOUSEMATE/ROOMMATE

(12) ROOMER/BOARDER

(13) OTHER NON-RELATIVE

(90) UNRELATED LEGAL GUARDIAN

(96) DON’T KNOW

(97) REFUSED

RELA_CHLD (S3Q6)[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?

(1) MOTHER (STEP, FOSTER, ADOPTIVE) OR FEMALE GUARDIAN

(2) FATHER (STEP, FOSTER, ADOPTIVE) OR MALE GUARDIAN

(3) SISTER OR BROTHER (STEP/FOSTER/HALF/ADOPTIVE)

(4) IN-LAW OF ANY TYPE

(5) AUNT/UNCLE

(6) GRANDPARENT

(7) OTHER FAMILY MEMBER

(8) FRIEND

(96) DON’T KNOW

(97) REFUSED

OTH_CHLD (S3Q7){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?

(0) NO[END INTERVIEW]

(1) YES

(6) DON’T KNOW [END INTERVIEW]

(7) REFUSED[END INTERVIEW]

AGEDGNOS (S3Q8)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) {Do you/Does [the (AGE) year old/NAME]} still have asthma?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NEVER

(1) WITHIN THE PAST YEAR

(2) 1 YEAR TO LESS THAN 3 YEARS AGO

(3) 3 YEARS TO 5 YEARS AGO

(4) MORE THAN 5 YEARS AGO

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 46 [ Page 83

LAST_MED (S3Q11)How long has it been since {you/[the (AGE) year old/NAME]} last took asthma medication?

(0) NEVER

(1) LESS THAN ONE DAY AGO

(2) 1–6 DAYS AGO

(3) 1 WEEK TO LESS THAN 3 MONTHS AGO

(4) 3 MONTHS TO LESS THAN 1 YEAR AGO

(5) 1 YEAR TO LESS THAN 3 YEARS AGO

(6) 3 YEARS TO 5 YEARS AGO

(7) MORE THAN 5 YEARS AGO

(96) DON’T KNOW

(97) 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)How long has it been since {you/[the (AGE) year old/NAME] last had any symptoms of asthma?

[INTERVIEWER: READ RESPONSE OPTIONS IF NECESSARY]

(0) NEVER

(1) LESS THAN ONE DAY AGO

(2) 1–6 DAYS AGO

(3) 1 WEEK TO LESS THAN 3 MONTHS AGO

(4) 3 MONTHS TO LESS THAN 1 YEAR AGO

(5) 1 YEAR TO LESS THAN 3 YEARS AGO

(6) 3 YEAR TO 5 YEARS AGO

(7) MORE THAN 5 YEARS AGO

(96) DON’T KNOW

(97) REFUSED

ASTHSTATDERIVED. 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

ASTATUS1DERIVED. 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

CASTHMADERIVED. 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

ASTHMSTDERIVED. COMPUTED ASTHMA STATUS BASED ON BRFSS RULES

(1) CURRENT

(2) FORMER

(3) NEVER

(9) DON’T KNOW/NOT SURE OR REFUSED

ASTATUS2DERIVED. 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_TYPEDERIVED. EXPECTED INTERVIEW TYPE

(1) SAMPLED PERSON INT: SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS

(2) SAMPLED PERSON INT: NO SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS

(3) SAMPLED PERSON ILL, PROXY INT: SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS

(4) SAMPLED PERSON ILL, PROXY INT: NO SYMPTOMS, MEDS, DR VISITS IN PAST 3 YRS

(5) SAMPLED PERSON 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?

__ __ DAYS (1–29)[SKIP TO ASLEEP30 (S4Q3)]

(0) NO SYMPTOMS IN THE PAST 30 DAYS [SKIP TO EPIS_INT]

(30) EVERY DAY

(96) DON’T KNOW[SKIP TO ASLEEP30 (S4Q3)]

(97) REFUSED[SKIP TO ASLEEP30 (S4Q3)]

DUR_30D (S4Q2) {Do you/Does [the (AGE) year old/NAME]} have symptoms all the time?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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 = 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) NO [SKIP TO INS1 (S5Q1_A)]

(1) YES

(6) DON’T KNOW [SKIP TO INS1 (S5Q1_A)]

(7) REFUSED [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?

__ __ ATTACKS OR EPISODES DURING PAST 3 MONTHS

(0) NONE

(996) DON’T KNOW

(997) REFUSED

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[SKIP TO COMPASTH (S4Q9)]

(97) REFUSED[SKIP TO COMPASTH (S4Q9)]

DUR2ASTH (S4Q8)ENTER PERIOD

(1) MINUTES

(2) HOURS

(3) DAYS

(4) WEEKS

(6) DON’T KNOW

(7) REFUSED

COMPASTH (S4Q9)Compared with other episodes or attacks, was this most recent attack shorter, longer, or about the same?

(1) SHORTER

(2) LONGER

(3) ABOUT THE SAME

(4) THE MOST RECENT ATTACK WAS ACTUALLY THE FIRST ATTACK

(6) DON’T KNOW

(7) 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) NO[SKIP TO NER_TIME (S5Q1)]

(1) YES

(6) DON’T KNOW [SKIP TO NER_TIME (S5Q1)]

(7) REFUSED[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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

NER_TIME (S5Q1) [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?

__ __ __ ENTER NUMBER

(0) NONE

(996) DON’T KNOW

(997) 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) NO [SKIP TO URG_TIME (S5Q4)]

(1) YES

(6) DON’T KNOW [SKIP TO URG_TIME (S5Q4)]

(7) REFUSED [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)[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.

(0) NO[SKIP TO MISS_DAY (S5Q9)]

(1) YES

(6) DON’T KNOW[SKIP TO MISS_DAY (S5Q9)]

(7) REFUSED[SKIP TO MISS_DAY (S5Q9)]

HOSPTIME (S5Q6)[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)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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?

__ __ __ ENTER NUMBER

(0) ZERO

(994) CHILD DID NOT GO TO SCHOOL IN PAST 12 MONTHS

(995) HOME SCHOOLED

(996) DON’T KNOW

(997) REFUSED

ACT_DAYS (S5Q12)[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?

(1) NOT AT ALL

(2) A LITTLE

(3) A MODERATE AMOUNT

(4) A LOT

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

TCH_RESP (S6Q2) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

MGT_PLAN (S6Q4)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]

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

MGT_CLAS (S6Q5)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) Is an air cleaner or purifier regularly used inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DEHUMID (S7Q2)Is a dehumidifier regularly used to reduce moisture inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

KITC_FAN (S7Q3)Is an exhaust fan that vents to the outside used regularly when cooking in your kitchen?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

COOK_GAS (S7Q4) Is gas used for cooking?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

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.

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

ENV_PETS (S7Q6)Does your household have indoor pets such as dogs, cats, hamsters, birds, or other feathered or furry pets that

are kept inside?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

C_ROACH (S7Q7) In the past 30 days, has anyone seen cockroaches inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) Is a fireplace or wood burning stove used in your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

HELP SCREEN: ‘‘Unvented’’ means no chimney.

S_INSIDE (S7Q10) In the past week, has anyone smoked inside your home?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

MATTRESS (S7Q12){Do you/Does [the (AGE) year old/NAME]} use a mattress cover that is made especially for controlling dust

mites?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

E_PILLOW (S7Q13) {Do you/Does [the (AGE) year old/NAME]} use a pillow cover that is made especially for controlling dust

mites?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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
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) NO OR ‘‘NO FAN’’

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(2) SOME ARE/SOME AREN’T

(6) DON’T KNOW

(7) 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) NO[SKIP TO EMP_STAT (S7Q20)]

(1) YES

(6) DON’T KNOW [SKIP TO EMP_STAT (S7Q20)]

(7) REFUSED[SKIP TO EMP_STAT (S7Q20)]

CIG_FREQ (S7Q19)Do you now smoke cigarettes every day, some days or not at all?

(1) EVERY DAY

(2) SOME DAYS

(3) NOT AT ALL

(6) DON’T KNOW

(7) 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) EMPLOYED FULL-TIME

(2) EMPLOYED PART-TIME

(3) NOT EMPLOYED

(6) DON’T KNOW

(7) REFUSED

WORKENV2 (S7Q21) Was your asthma caused or made worse by chemicals, smoke, fumes, or dust in any job you ever had?

(0) NO

(1) YES

(2) NEVER BEEN EMPLOYED

(6) DON’T KNOW

(7) REFUSED

UNEMP_R (S7Q22)[IF EMP_STAT (S7Q20) = 1 OR 2, SKIP TO OTC (S8Q1).] What is the main reason you are not employed?

(1) KEEPING HOUSE

(2) GOING TO SCHOOL

(3) RETIRED

(4) DISABLED

(5) UNABLE TO WORK FOR OTHER HEALTH REASONS

(6) LOOKING FOR WORK

(7) LAID OFF

(8) OTHER

(96) DON’T KNOW

(97) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

INHALERE (S8Q2){Have you/Has [the (AGE) year old/NAME]} ever used a prescription inhaler?

(0) NO[SKIP TO SCR_MED1 (S8Q4)]

(1) YES

(6) DON’T KNOW [SKIP TO SCR_MED1 (S8Q4)]

(7) REFUSED[SKIP TO SCR_MED1 (S8Q4)]

INHALERH (S8Q3)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO[SKIP TO INH_SCR (S8Q7)]

(1) YES

(2) RESPONDENT KNOWS THE MEDS [SKIP TO INH_SCR (S8Q7)]

(6) DON’T KNOW

(7) REFUSED[SKIP TO INH_SCR (S8Q7)]

SCR_MED2 (S8Q5)Can you please go get the asthma medicines while I wait on the phone?

(0) NO[SKIP TO INH_SCR (S8Q7)]

(1) YES

(8) DON’T KNOW

(9) REFUSED [SKIP TO INH_SCR (S8Q7)]

SCR_MED3 (S8Q6)Am I correct that you have all the medications?

(0) NO

(1) YES, I HAVE ALL THE MEDICATIONS

(2) YES, I HAVE SOME OF THE MEDICATIONS BUT NOT ALL

(6) DON’T KNOW

(7) REFUSED

INH_SCR (S8Q7)In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription asthma medicine using an

inhaler?

(0) NO[SKIP TO PILLS (S8Q27)]

(1) YES

(6) DON’T KNOW [SKIP TO PILLS (S8Q27)]

(7) REFUSED [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 Brand Name Type (not shown in CATI)

INH_MEDX01 (S8Q8_01) Advair

INH_MEDX02 (S8Q8_02) Aerobid Corticosteroids

INH_MEDX03 (S8Q8_03) Albuterol Beta 2 agonist

INH_MEDX04 (S8Q8_04) Alupent Beta 2 agonist

INH_MEDX05 (S8Q8_05) Atrovent Anti-inflammatories

INH_MEDX06 (S8Q8_06) Azmacort Corticosteroids

INH_MEDX07 (S8Q8_07) Beclomethasone dipropionate Corticosteroids

INH_MEDX08 (S8Q8_08) Beclovent Corticosteroids

INH_MEDX09 (S8Q8_09) Bitolterol Beta 2 agonist

INH_MEDX10 (S8Q8_10) Brethaire Beta 2 agonist

INH_MEDX11 (S8Q8_11) Budesonide Corticosteroids

INH_MEDX12 (S8Q8_12) Combivent

INH_MEDX13 (S8Q8_13) Cromolyn Anti-inflammatories

INH_MEDX14 (S8Q8_14) Flovent Inhaled corticosteroid

INH_MEDX15 (S8Q8_15) Flovent Rotadisk Inhaled corticosteroid

INH_MEDX16 (S8Q8_16) Flunisolide Corticosteroids

INH_MEDX17 (S8Q8_17) Fluticasone Inhaled corticosteroid

INH_MEDX18 (S8Q8_18) Intal Anti-inflammatories

INH_MEDX19 (S8Q8_19) Ipratropium Bromide Anti-inflammatories

INH_MEDX20 (S8Q8_20) Maxair Beta 2 agonist

INH_MEDX21 (S8Q8_21) Metaproteronol Beta 2 agonist

INH_MEDX22 (S8Q8_22) Nedocromil Anti-inflammatories

INH_MEDX23 (S8Q8_23) Pirbuterol Beta 2 agonist

INH_MEDX24 (S8Q8_24) Proventil Beta 2 agonist

INH_MEDX25 (S8Q8_25) Pulmicort Turbuhaler Corticosteroids

INH_MEDX26 (S8Q8_26) Salmeterol Corticosteroids (long lasting)

INH_MEDX27 (S8Q8_27) Serevent Beta 2 agonist (long lasting)

INH_MEDX28 (S8Q8_28) Terbutaline Beta 2 agonist

INH_MEDX29 (S8Q8_29) Tilade Anti-inflammatories

INH_MEDX30 (S8Q8_30) Tornalate Beta 2 agonist

INH_MEDX31 (S8Q8_31) Triamcinolone acetonide Corticosteroids

INH_MEDX32 (S8Q8_32) Vanceril Corticosteroids

INH_MEDX33 (S8Q8_33) Ventolin Beta 2 agonist

INH_MEDX34 (S8Q8_34) 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) NO

(1) YES

(6) DON’T KNOW[SKIP TO REC_MED1]

(7) REFUSED[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)In the past 3 months, did {you/[the (AGE) year old/NAME]} take Flovent or Flovent Rotadisk using an

inhaler?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3INHLR (S8Q11)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4INHLR (S8Q12)In the past 3 months, did {you/[the (AGE) year old/NAME]} take:

Intal, Cromolyn,

Tilade, or Nedocromil?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5INHLR (S8Q13) In the past 3 months, did {you/[the (AGE) year old/NAME]} take:

Atrovent or Ipratropium Bromide?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK6INHLR (S8Q14)Did {you/[the (AGE) year old/NAME]} take a medication by inhaler that we have not mentioned?

(0) NO

(1) YES [SKIP TO DK7INHLR (S8Q15)]

(6) DON’T KNOW

(7) REFUSED

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) LESS THAN 6 MONTHS

(2) 6 MONTHS TO 1 YEAR

(3) LONGER THAN 1 YEAR

(6) DON’T KNOW

(7) 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) NO

(1) YES

(2) NO ATTACK IN PAST 3 MONTHS

(6) DON’T KNOW

(7) 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) NO

(1) YES

(2) DIDN’T EXERCISE IN PAST 3 MONTHS

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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) 44 MICROGRAMS

(2) 50 MICROGRAMS

(3) 100 MICROGRAMS

(4) 110 MICROGRAMS

(5) 220 MICROGRAMS

(6) 250 MICROGRAMS

(7) TOOK MORE THAN 1 IN PAST 3 MONTHS

(96) DON’T KNOW

(97) 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 [SKIP TO ILP11 (S8Q26_nn)]

(996) DON’T KNOW [SKIP TO ILP11 (S8Q26_nn)]

(997) REFUSED [SKIP TO ILP11 (S8Q26_nn)]

ILP10 (S8Q25_01 to S8Q25_34)

ENTER PERIOD

(1) PER DAY

(2) PER WEEK

(6) DON’T KNOW

(7) 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) 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 Medication Type (not shown in CATI)

PILLS_MX01 (S8Q28_01) Accolate Leukotriene modifiers

PILLS_MX02 (S8Q28_02) Aerolate Methylxanthines

PILLS_MX03 (S8Q28_03) Albuterol Beta 2 agonist – Rescue bronchodilators

PILLS_MX04 (S8Q28_04) Alupent Beta 2 agonist – Rescue bronchodilators

PILLS_MX05 (S8Q28_05) Choledyl Methylxanthines

PILLS_MX06 (S8Q28_06) Cromolyn Anti-inflammatories

PILLS_MX07 (S8Q28_07) Deltasone Corticosteriods

PILLS_MX08 (S8Q28_08) Elixophyllin Methylxanthines

PILLS_MX09 (S8Q28_09) Intal Anti-inflammatories

PILLS_MX10 (S8Q28_10) Marax Methylxanthines

PILLS_MX11 (S8Q28_11) Medrol Corticosteriods

PILLS_MX12 (S8Q28_12) Metaprel Beta 2 agonist – Rescue bronchodilators

PILLS_MX13 (S8Q28_13) Metaproteronol Beta 2 agonist – Rescue bronchodilators

PILLS_MX14 (S8Q28_14) Methylpredinisolone Corticosteriods

PILLS_MX15 (S8Q28_15) Montelukast Leukotriene modifiers

PILLS_MX16 (S8Q28_16) Nedocromil Corticosteriods

PILLS_MX17 (S8Q28_17) Pediapred Corticosteriods

PILLS_MX18 (S8Q28_18) Prednisolone Corticosteriods

PILLS_MX19 (S8Q28_19) Prednisone Corticosteriods

PILLS_MX20 (S8Q28_20) Prelone Corticosteriods

PILLS_MX21 (S8Q28_21) Proventil Beta 2 agonist – Rescue bronchodilators

PILLS_MX22 (S8Q28_22) Quibron Methylxanthines

PILLS_MX23 (S8Q28_23) Respid Methylxanthines

PILLS_MX24 (S8Q28_24) Singulair Leukotriene modifiers

PILLS_MX25 (S8Q28_25) Slo-phyllin Methylxanthines

PILLS_MX26 (S8Q28_26) Slo-bid Methylxanthines

PILLS_MX27 (S8Q28_27) Sustaire Methylxanthines

PILLS_MX28 (S8Q28_28) Theo-24 Methylxanthines

PILLS_MX29 (S8Q28_29) Theobid Methylxanthines
Page 96 [ Series 1, No. 46

PILLS_MX30 (S8Q28_30) Theochron Methylxanthines

PILLS_MX31 (S8Q28_31) Theoclear Methylxanthines

PILLS_MX32 (S8Q28_32) Theodur Methylxanthines

PILLS_MX33 (S8Q28_33) Theo-Dur Methylxanthines

PILLS_MX34 (S8Q28_34) Theolair Methylxanthines

PILLS_MX35 (S8Q28_35) Theophylline Methylxanthines

PILLS_MX36 (S8Q28_36) Theo-Sav Methylxanthines

PILLS_MX37 (S8Q28_37) Theospan Methylxanthines

PILLS_MX38 (S8Q28_38) Theox Methylxanthines

PILLS_MX39 (S8Q28_39) Tilade Corticosteriods

PILLS_MX40 (S8Q28_40) T-Phyl Methylxanthines

PILLS_MX41 (S8Q28_41) Unidur Methylxanthines

PILLS_MX42 (S8Q28_42) Uniphyl Methylxanthines

PILLS_MX43 (S8Q28_43) Ventolin Beta 2 agonist – Rescue bronchodilators

PILLS_MX44 (S8Q28_44) Volmax Beta 2 agonist – Rescue bronchodilators

PILLS_MX45 (S8Q28_45) Zafirlukast Leukotriene modifiers

PILLS_MX46 (S8Q28_46) Zileuton Leukotriene modifiers

PILLS_MX47 (S8Q28_47) Zyflo Filmtab Leukotriene modifiers

PILLS_MX47 (S8Q28_48) Other, please specify: [SKIP TO OTH_P1 (S8Q29)]

IF ANY ANSER 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

REC_MED2READ: 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)Did {you/[the (AGE) year old/NAME]} take:

Accolate or Zafirlukast

Zyflo Filmtab or Zileuton

Singulair or Montelukast?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_PILL (S8Q31)Did {you/[the (AGE) year old/NAME]} take:

Intal or Cromolyn

Tilade or Nedocromil?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_PILL (S8Q32)Did {you/[the (AGE) year old/NAME]} take:

Medrol, Methylpredinisolone,

Deltasone, Prednisone,

Pediapred,

Prelone, or Prednisolone?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 46 [ Page 97

DK4_PILL (S8Q33)Did {you/[the (AGE) year old/NAME]} take:

Proventil, Ventolin, Volmax, or Albuterol

Alupent, Metaprel, or Metaproteronol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5_PILL (S8Q34)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK6_PILL (S8Q35)Did {you/[the (AGE) year old/NAME]} take a medication in pill form that we have not mentioned?

(0) NO[SKIP TO PILLX (S8Q37_nn)]

(1) YES[SKIP TO DK7_PILL (S8Q36)]

(6) DON’T KNOW[SKIP TO PILLX (S8Q37_nn)]

(7) REFUSED[SKIP TO PILLX (S8Q37_nn)]

DK7_PILL (S8Q36)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) LESS THAN 6 MONTHS

(2) 6 MONTHS TO 1 YEAR

(3) LONGER THAN 1 YEAR

(6) DON’T KNOW

(7) REFUSED

SYRUP (S8Q38) In the past 3 months, {have you/has [the (AGE) year old/NAME]} taken prescription medicine in syrup form?

(0) NO[SKIP TO NEB_SCR (S8Q47)]

(1) YES

(6) DON’T KNOW[SKIP TO NEB_SCR (S8Q47)]

(7) 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 Medication

SYRUP_IX01 (S8Q39_01) Aerolate

SYRUP_IX02 (S8Q39_02) Albuterol

SYRUP_IX03 (S8Q39_03) Alupent

SYRUP_IX04 (S8Q39_04) Metaproteronol

SYRUP_IX05 (S8Q39_05) Prednisolone

SYRUP_IX06 (S8Q39_06) Prelone

SYRUP_IX07 (S8Q39_07) Proventil

SYRUP_IX08 (S8Q39_08) Slo-Phyllin

SYRUP_IX09 (S8Q39_09) Theophylline

SYRUP_IX10 (S8Q39_10) Ventolin

SYRUP_IX11 (S8Q39_11) 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) NO

(1) YES

(6) DON’T KNOW[SKIP TO REC_MED3]

(7) REFUSED[SKIP TO NEB_SCR (S8Q47)]

OTH_S1 (S8Q40)ENTER OTHER MEDICATION.

IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.

________________________ ENTER TEXT

REC_MED3READ: 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)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Alupent or Metaproteronol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_SYRP (S8Q42)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Ventolin or Proventil or Albuterol?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_SYRP (S8Q43)Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Aerolate, Slo-Phyllin, or Theophylline?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4_SYRP (S8Q44) Which of these prescriptions medications {have you/has [the (AGE) year old/NAME]} taken as a syrup?

Prelone or Prednisolone?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK5_SYRP (S8Q45)Did {you/[the (AGE) year old/NAME]} take a medication in syrup form that we have not mentioned?

(0) NO[SKIP TO NEB_SCR (S8Q47)]

(1) YES

(6) DON’T KNOW[SKIP TO NEB_SCR (S8Q47)]

(7) REFUSED[SKIP TO NEB_SCR (S8Q47)]

DK6_SYRP (S8Q46)Will you please tell me what that medication was?

SPELL OUT: _____________________________________

NEB_SCR (S8Q47)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?

(0) NO[SKIP TO SECTION 7]

(1) YES

(6) DON’T KNOW[SKIP TO SECTION 7]

(7) REFUSED[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 Medication

NEB_IDX01 (S8Q48_01) Albuterol

NEB_IDX02 (S8Q48_02) Alupent

NEB_IDX03 (S8Q48_03) Cromolyn

NEB_IDX04 (S8Q48_04) Intal

NEB_IDX05 (S8Q48_05) Metaproteronol

NEB_IDX06 (S8Q48_06) Proventil

NEB_IDX07 (S8Q48_07) Ventolin

NEB_IDX08 (S8Q48_08) 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) NO

(1) YES

(6) DON’T KNOW[SKIP TO DK1_NEB (S8Q50)]

(7) REFUSED[SKIP TO SECTION 7]

OTH_N1 (S8Q49)ENTER OTHER MEDICATION.

IF MORE THAN ONE MEDICATION IS GIVEN, ENTER ALL MEDICATIONS ON ONE LINE.

________________________ ENTER TEXT

DK1_NEB (S8Q50)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK2_NEB (S8Q51)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK3_NEB (S8Q52)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?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

DK4_NEB (S8Q53)Did {you/[the (AGE) year old/NAME]} take a medication using a nebulizer that we have not mentioned?

(0) NO[SKIP TO SECTION 7]

(1) YES

(6) DON’T KNOW[SKIP TO SECTION 7]

(7) REFUSED[SKIP TO SECTION 7]

DK5_NEB (S8Q54)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) NO [SKIP TO BROASTH1 (S9Q5)]

(1) YES

(6) DON’T KNOW [SKIP TO BROASTH1 (S9Q5)]

(7) REFUSED [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) FATHER

(2) MOTHER

(3) BOTH

(6) DON’T KNOW

(7) 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) NO

(1) YES

(6) DON’T KNOW

(7) 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?

__ _ _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 = 1, ASK:] Was {your/the (AGE) year old’s} biological sister ever told that she

had asthma?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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?

__ __ 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.
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) NO [SKIP TO OTHER_T (S11Q1)]

(1) YES

(6) DON’T KNOW [SKIP TO OTHER_T (S11Q1)]

(7) REFUSED [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?]

(S9Q10_01) MOTHER’S MOTHER

(S9Q10_02) MOTHER’S FATHER

(S9Q10_03) FATHER’S MOTHER

(S9Q10_04) FATHER’S FATHER

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO[SKIP TO WO_SERVICE (S11Q7)]

(1) YES

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED[SKIP TO WO_SERVICE (S11Q7)]

SEC_USE (S11Q2) Is this second number for home use only, for business use only, or for both home and business use?

(1) HOME ONLY

(2) BUSINESS ONLY[SKIP TO THIRD_TN (S11Q4)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED[SKIP TO WO_SERVICE (S11Q7)]

SEC_FAX (S11Q3)Is this second number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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) NO[SKIP TO WO_SERVICE (S11Q7)]

(1) YES

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED[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) HOME ONLY

(2) BUSINESS ONLY[SKIP TO WO_SERVICE (S11Q7)]

(3) BOTH HOME AND BUSINESS

(6) DON’T KNOW[SKIP TO WO_SERVICE (S11Q7)]

(7) REFUSED[SKIP TO WO_SERVICE (S11Q7)]

THIRD_FAX (S11Q6) Is this third number used only for computer or fax communications?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED
Page 102 [ Series 1, No. 46

NUM_PHON DERIVED. NUMBER OF TELEPHONES FOR HOME USE

WO_SERVICE (S11Q7)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.

(0) NO[SKIP TO R_ETH_2 (HISPANIC)]

(1) YES

(6) DON’T KNOW[SKIP TO R_ETH_2 (HISPANIC)]

(7) REFUSED[SKIP TO R_ETH_2 (HISPANIC)]

C11Q21_A (S11Q8)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[SKIP TO R_ETH_2 (HISPANIC)]

(997) REFUSED[SKIP TO R_ETH_2 (HISPANIC)]

C11Q21 (S11Q9) ENTER PERIOD

(1) DAYS

(2) WEEK(S)

(3) MONTH(S)

(6) DON’T KNOW

(7) REFUSED

NOPHONE DERIVED. NUMBER OF DAYS WITHOUT TELEPHONE SERVICE

R_ETH_2 (HISPANIC) (Are you/Is [the (AGE) year old]) of Hispanic or Latino origin?

(0) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

R_RACE2Now, 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) WHITE

(S2Q11_02) BLACK/AFRICAN-AMERICAN

(S2Q11_03) AMERICAN INDIAN

(S2Q11_04) ALASKA NATIVE

(S2Q11_05) ASIAN

(S2Q11_06) NATIVE HAWAIIAN

(S2Q11_07) PACIFIC ISLANDER

(0) NO

(1) YES

(6) DON’T KNOW

(7) 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?

_ _ 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 103

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 PERSONS AGE (S2Q5) < 18.] How much did [the (AGE) year old]

weigh at birth?

__ __ pounds /__ __ ounces OR __ __ __ __ grams [SKIP TO INC_TOT (S10Q1)]

(96) DON’T KNOW (9996) DON’T KNOW [SKIP TO BIRTHRF S2Q17]

(97) REFUSED (9997) REFUSED [SKIP TO BIRTHRF (S2Q17)]

BIRTHWEIGHT 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) NO

(1) YES

(6) DON’T KNOW

(7) REFUSED

INC_TOT (S10Q1) 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 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) MORE THAN $20,000[SKIP TO RANGE_40 (S10Q9)]

(2) $20,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $20,000[SKIP TO RANGE_10 (S10Q4)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_10 (S10Q4)Was the total combined household income more or less than $10,000?

(1) MORE THAN $10,000[SKIP TO RANGE_15 (S10Q6)]

(2) $10,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $10,000[SKIP TO RANGE_7 (S10Q5)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_7 (S10Q5) Was it more than $7,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_15 (S10Q6) Was it more than $15,000?

(0) NO[SKIP TO RANGE_12 (S10Q8)]

(1) YES[SKIP TO RANGE_17 (S10Q7)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_17 (S10Q7) Was it more than $17,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_12 (S10Q8)Was it more than $12,500?

(0) NO[SKIP TO C11Q22 (S11Q11)]

(1) YES[SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_40 (S10Q9) Was the total combined household income more or less than $40,000?

(1) MORE THAN $40,000[SKIP TO RANGE_60 (S10Q10)]

(2) $40,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $40,000[SKIP TO RANGE_30 (S10Q13)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_60 S10Q10) Was the total combined household income more or less than $60,000?

(1) MORE THAN $60,000[SKIP TO RANGE_75 (S10Q16)]

(2) $60,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $60,000[SKIP TO RANGE_50 (S10Q11)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]

RANGE_50 (S10Q11) Was the total combined household income more or less than $50,000?

(1) MORE THAN $50,000[SKIP TO C11Q22 (S11Q11)]

(2) $50,000[SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $50,000[SKIP TO RANGE_45 (S10Q12)]

(6) DON’T KNOW[SKIP TO C11Q22 (S11Q11)]

(7) REFUSED[SKIP TO C11Q22 (S11Q11)]
Series 1, No. 46 [ Page 105

RANGE_45 (S10Q12) Was the total combined household income more or less than $45,000?

(1) MORE THAN $45,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $45,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_30 (S10Q13) Was the total combined household income more or less than $30,000?

(1) MORE THAN $30,000 [SKIP TO RANGE_35 (S10Q14)]

(2) $30,000 [SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $30,000 [SKIP TO RANGE_25 (S10Q15)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_35 (S10Q14) Was the total combined household income more or less than $35,000?

(1) MORE THAN $35,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $35,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_25 (S10Q15) Was the total combined household income more or less than $25,000?

(1) MORE THAN $25,000 [SKIP TO C11Q22 (S11Q11)]

(2) LESS THAN $25,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

RANGE_75 (S10Q16) Was the total combined household income more or less than $75,000?

(1) MORE THAN $75,000 [SKIP TO C11Q22 (S11Q11)]

(2) $75,000 [SKIP TO C11Q22 (S11Q11)]

(3) LESS THAN $75,000 [SKIP TO C11Q22 (S11Q11)]

(6) DON’T KNOW [SKIP TO C11Q22 (S11Q11)]

(7) REFUSED [SKIP TO C11Q22 (S11Q11)]

BESTINCOME 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

Interview completion rate ........ 76.2 79.5 77.9

Screener completion rate ........ 54.2 52.8 53.5

Resolution rate............... 77.9 77.9 77.9

CASRO response rate .......... 32.2 32.7 32.5

Percent of Percent of Percent of

Percentage rate asthma group air quality group total sample

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

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).

Table V. NAS Pretest IV unweighted response rates

Percentage rate

Percent of

Approach A

Percent of

Approach B

Interview completion rate ........

Screener completion rate ........

Resolution rate...............

88.1

50.5

82.9

76.8

84.5

83.4

CASRO response rate .......... 36.9 54.1

NOTE: NAS is National Asthma Survey. CASRO is the Council of American Survey Research Organizations.
hma Survey: Summary of pretests

Pretest I

September 17, 2001–

November 15, 2001

Pretest II

November 13, 2001–

January 7, 2002

Pretest III

March 6, 2002–

July 10, 2002

Pretest IV

July 17, 2002–

November 4, 2002

All household All household All household Approach A: One adult

members screened members screened members screened and one child screened

Approach B: Household isimmediately screened (any householdmember)

Randomly select up Randomly select up to Randomly select up to Approach A: Randomly select oneto two with asthma: two with asthma: one two with asthma: one adult and one child; asthmaone adult and one adult and one child adult and one child status unknownchild Approach B: Randomly select up to

two with asthma: one adult andone child

Any household member Any household member Any household member

Most knowledgeable person over age 17 over age 17 over age 17

NIS advance letter; no NIS advance letter that Separate NAS advance letter NIS advance letter; no

mention of asthma mentions asthma mailed approximately 3 weeks mention of asthma

after NIS is complete.Two experimental groups:asthma and air quality

Standard script with most Shortened and moved to Shortened and moved Approach A: Standard scriptknowledgeable person follow initial ‘‘breathing’’ to follow initial with most knowledgeable personproviding informed consent questions ‘‘breathing’’ questions providing informed consent beforebefore screening questions screening questions

Approach B: After-asthma screening,rostering, and sampling of respondents

Separate question asking Question removed; Question removed; Approach A: Derived from household rostertotal persons in household information derived from information derived Approach B: Not determined

household roster from household roster

Detailed Hispanic categories General yes or no question General yes or no question General yes or no question

None Addition of general Addition of general ‘‘breathing’’ None

‘‘breathing’’ questions questions plus general ‘‘air

quality’’ questions in one-halfof the sample

Household with asthma: Household with asthma: Household with asthma: Approach A: Householdtelephone information and telephone information and age and sex of household with asthma: asked at the endincome at end of survey; income at end of survey; all members after initial informed of the detailed asthma interviewall others after initial others after initial informed consent script; all others Household without asthma:informed consent script consent script asked at the end of detailed Asked after informed consentHousehold without asthma: Household without asthma: asthma interview Approach B: All demographicsAll demographics asked after All demographics asked after Household without asthma: asked at the end of theinformed consent informed consent All demographics asked after detailed asthma interview

informed consent

Page 108[ Series 1, No. 46
hma 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

Jefferson County, Alabama;

Chicago, Illinois; Dallas,El Paso, and BexarCounties and Houston,Texas; SantaClara and San DiegoCounties, California

Jefferson County, Alabama;Chicago, Illinois;Houston, Texas

California, Illinois, Alabama,and Texas state samples

California, Illinois, Alabama,and Texas state samples

Occurs immediately after

NIS screener or interview

Occurs immediately afterNIS screener or interview

Minimum of 3-week delayafter NIS screener or interview

Occurs immediately afterNIS screener or interview

Finalized with NIS-level

disposition

Finalized with NIS-leveldisposition

Dialed for NAS after theclose of the NIS quarter

Finalized with NIS-level disposition

d 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 ...............................

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 ....................................

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 ...................................

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 .........................................

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) .....

...

UH

Z

Z

Z

Z

UO

Z

UH

Z

UH

UH

UH

UH

UH

UH

UH

UO

UO

UO

UO

UO

UO

Z

UO

UO

UO

R

R

P

P

UO

UO

Y

X

I

I

Z

55,204

4,692

913

799

3,227

288

91

262

1,705

5

2

4

6

502

88

1,337

3,290

222

73

295

3

2

22

1,967

2,469

370

154

10

218

11

23

24

430

19

8,852

870

51

21,908

100.00
 

8.50
 

1.65
 

1.45
 

5.85
 

0.52
 

0.16
 

0.47
 

3.09
 

0.91
 

0.16
 

2.42
 

5.96
 

0.40
 

0.13
 

0.53
 

0.04
 

3.56
 

4.47
 

0.67
 

0.28
 

0.02
 

0.39
 

0.02
 

0.04
 

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, sampledrespondent 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.
 

0.01 

0.00 

0.01 

0.01 

0.01 

0.00 
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) Formula

Interview completion rate ..................................... 79.50 (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

Sample Percent of

Disposition category code Number total sample

Total .................................................. . . . 210,109 100.00

No contact .............................................. UH 18,962 9.02

3 + fax or modem prior to any contact ............................. Z 3,063 1.46

2 + temporarily not in service .................................. Z 3,131 1.49

Nonworking number ........................................ Z 14,768 7.03

Number changed .......................................... Z 1,359 0.65

Answering machine—known household ............................ UO 379 0.18

Answering machine—nonresidential............................... Z 1,020 0.49

Answering machine—residential status unknown ...................... UH 6,514 3.10

Answering service—nonresidential ............................... Z 28 0.01

Answering service—residential status unknown ....................... UH 4 0.00

Spanish case—residential status unknown .......................... UH 33 0.02

Other language case—residential status unknown ..................... UH 58 0.03

Physical or mental impairment case—residential status unknown ............ UH 28 0.01

Appointment at introduction—residential status unknown ................. UH 1,961 0.93

Callback at introduction—residential status unknown .................... UH 281 0.13

Hangup during introduction .................................... UH 5,140 2.45

Refusal at introduction ....................................... UH 7,843 3.73

Callback—known household ................................... UO 1,323 0.63

Appointment—known household................................. UO 334 0.16

Refusal—known household .................................... UO 1,199 0.57

NIS-level callback ......................................... UO 37 0.02

NIS-level appointment ....................................... UO 7 0.00

NIS-level refusal........................................... UO 216 0.10

Not residential ........................................... Z 6,302 3.00

Refusal prior to NAS screening ................................. UO 4,572 2.18

Callback prior to NAS screening ................................ UO 645 0.31

Appointment prior to NAS screening .............................. 1 UO 84 0.04

Refusal at or prior to NAS item BATH_FAN (S7Q16) ................... R 1,673 0.80

Callback at or prior to NAS item BATH_FAN (S7Q16)1 ................... R 334 0.16

Appointment at or prior to NAS item BATH_FAN (S7Q16)1 ................ R 183 0.09

Refusal—partial interview ..................................... P 84 0.04

Callback—partial interivew .................................... P 20 0.01

Appointment—partial interview .................................. P 9 0.00

Emancipated minor household—known household, unknown eligibility; interviews

were not conducted in households in which no one over the age of 17 years

resided. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . UO 88 0.04

Other language case—known household, unknown eligibility ............... UO 1,260 0.60

Other language case—known eligible household....................... Y 10 0.00

Physical or mental impairment case—known eligible household ............. R 8 0.00

Screened—asthma-negative household ............................ X 40,852 19.44

Completed household interview ................................. I 4,664 2.22

Converted household interview ................................. I 348 0.17

GENESYS IDplus—resolved numbers (nonworking, business, and modem

numbers) .............................................. Z 81,285 38.69

. . . 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, sampledrespondent 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

Calculated

rate

Calculation of response rates (percent) Formula

Interview completion rate . . . . . . . . . . . . . . . . . . 69.90 (I+P)/(I+P+R+Y)
 

Screener completion rate .................. 82.60 (I+P+R+X+Y)/(I+P+R+X+Y+UO)
 

Resolution rate ............ ............ 80.60 (I+P+R+X+Y+UO+Z)/(I+P+R+X+Y+UO+Z+UH)
 

CASRO response rate.................... 46.50 ... 
 

. . . 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

Standard error

Weighted estimate of weighted

of number of estimate of Standard error

Unweighted number persons of all number of Percent of of percent of

of persons of all ages with persons of all persons with persons with

Reporting status of adult data ages with asthma asthma ages with asthma asthma 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

Weighted estimate
 Standard error of
 Standard error
 

Unweighted number
 of number of
 weighted estimate
 of percent of
 

of asthmatic
 asthmatic persons
 of asthmatic
 Percent of asthmatic
 asthmatic persons
 

persons who
 who had
 persons who had
 persons who had
 who had an
 

had an asthma
 an asthma attack
 an asthma attack
 an asthma attack
 asthma attack
 

attack in the
 in the past
 in the past
 in the past
 in the past
 

Four-state sample past 12 months
 12 months
 12 months
 12 months
 12 months
 

Total .............................. 2,896 4,418,991.02 97,708.02 64.33 1.05
 

Alabama ............................ 790 270,955.64 9,291.01 66.36 1.71
 

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676 2,155,905.86 81,894.68 62.68 1.79
 

Illinois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641 671,753.18 27,828.96 63.34 1.82
 

Texas .............................. 789 1,320,376.34 44,489.82 67.35 1.64
 

NOTE: NAS is National Asthma Survey.
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.	 Analytical and Epidemiological Studies—These reports

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

reports of major committees concerned with vital and health

statistics and documents such as recommended model vital

registration laws and revised birth and death certificates.

SERIES 5.	 International Vital and Health Statistics Reports—These

reports are analytical or descriptive reports that compare U.S.

vital and health statistics with those of other countries or

present other international data of relevance to the health

statistics system of the United States.

SERIES 6.	 Cognition and Survey Measurement—These reports are

from the National Laboratory for Collaborative Research in

Cognition and Survey Measurement. They use methods of

cognitive science to design, evaluate, and test survey

instruments.

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

continuing national household interview survey.

SERIES 11.	 Data From the National Health Examination Survey, the

National Health and Nutrition Examination Surveys, and

the Hispanic Health and Nutrition Examination Survey—

Data from direct examination, testing, and measurement on

representative samples of the civilian noninstitutionalized

population provide the basis for (1) medically defined total

prevalence of specific diseases or conditions in the United

States and the distributions of the population with respect to

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

distribution, and characteristics of health resources are now

included in Series 13.

SERIES 15.	 Data From Special Surveys—These reports contain

statistics on health and health-related topics collected in

special surveys that are not part of the continuing data

systems of the National Center for Health Statistics.

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

mortality that are not included in regular, annual, or monthly

reports. Special analyses by cause of death, age, other

demographic variables, and geographic and trend analyses

are included.

SERIES 21.	 Data on Natality, Marriage, and Divorce—These reports

contain statistics on natality, marriage, and divorce that are

not included in regular, annual, or monthly reports. Special

analyses by health and demographic variables and

geographic and trend analyses are included.

SERIES 22.	 Data From the National Mortality and Natality Surveys—

Discontinued in 1975. Reports from these sample surveys,

based on vital records, are now published in Series 20 or 21.

SERIES 23.	 Data From the National Survey of Family Growth—These

reports contain statistics on factors that affect birth rates,

including contraception, infertility, cohabitation, marriage,

divorce, and remarriage; adoption; use of medical care for

family planning and infertility; and related maternal and infant

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.

For answers to questions about this report or for a list of reports published

in these series, contact:

Information Dissemination Staff

National Center for Health Statistics

Centers for Disease Control and Prevention

3311 Toledo Road, Room 5412

Hyattsville, MD 20782

1–800–232–4636
 

E-mail: cdcinfo@cdc.gov
 

Internet: www.cdc.gov/nchs
 
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