Series 2, Number 136

Estimating the Prevalence of

Uninsured Children: An

Evaluation of Data From the

National Survey of Children

with Special Health Care

Needs, 2001

Data Evaluation and Methods

Research

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Hyattsville, Maryland

January 2004

DHHS Publication No. (PHS) 2004-1336
Copyright information

All material appearing in this report is in the public domain and may be

reproduced or copied without permission; citation as to source, however, is

appreciated.

Suggested Citation

Blumberg SJ, Osborn L, Luke JV, et al. Estimating the prevalence of uninsured

children: An evaluation of data from the National Survey of Children with

Special Health Care Needs, 2001. National Center for Health Statistics.

Vital Health Stat 2(136). 2004.

For sale by the U.S. Government Printing Office

Superintendent of Documents

Mail Stop: SSOP

Washington, DC 20402-9328

Printed on acid-free paper.
National Center for Health Statistics

Edward J. Sondik, Ph.D., Director

Jack R. Anderson, Deputy Director

Jack R. Anderson, Acting Associate Director for

International Statistics

Jennifer H. Madans, Ph.D., Associate Director for Science

Lawrence H. Cox, Ph.D., Associate Director for Research

and Methodology

Diane M. Makuc, Dr.P.H., Acting Associate Director for

Analysis, Epidemiology, and Health Promotion

Edward L. Hunter, Associate Director for Planning, Budget,

and Legislation

Michael Sadagursky, Associate Director for

Management and Operations

Margot A. Palmer, Acting Associate Director for Information

Technology and Services

Division of Health Interview Statistics

Jane F. Gentleman, Ph.D., Director

Anne K. Stratton, M.S., Associate Director for Planning and

Production

Eve Powell-Griner, Ph.D., Associate Director for Science

Susan S. Jack, M.S., Special Assistant for Data Quality and

User Services

Eve Powell-Griner, Ph.D., Acting Chief, Data Analysis

Branch

Marcie Cynamon, M.A., Acting Chief, Special Population

Surveys Branch

Howard Riddick, Ph.D., Chief, Survey Planning and

Development Branch

Anne K. Stratton, M.S., Acting Chief, Systems and

Programming Branch
Acknowledgments

The National Survey of Children 

with Special Health Care Needs 

was sponsored and funded by the 

Maternal and Child Health Bureau of 

the Health Resources and Services 

Administration. Additional funding for 

the health insurance coverage questions 

was received from the Office of the 

Assistant Secretary for Planning and 

Evaluation of the U.S. Department of 

Health and Human Services. 

The evaluation of the health 

insurance questions was jointly planned 

by the National Center for Health 

Statistics and by Abt Associates Inc. The 

project director was Marcie Cynamon. 

Terry Richardson and Kathy O’Connor 

provided extensive advice and 

assistance. The authors gratefully 

acknowledge the statistical support of 

K. P. Srinath, Sergei Rodkin, Linda 

Piccinino, Christopher Becker, 

Annabella Battaglia, Pamela Giambo, 

and David Hoaglin. Special thanks also 

go to Robin Cohen, John Czajka, 

Jennifer Haley, Genevieve Kenney, and 

Paul Newacheck for their helpful review 

and comments. The National Survey of 

America’s Families and Current 

Population Survey estimates in tables E 

and F were provided by Angela Yip and 

Marie Wang of The Urban Institute. 

This report was edited by 

Klaudia M. Cox and typeset by 

Zung T. N. Le of the Information 

Design and Publishing Branch, Division 

of Information Services. 

iii
Contents

Acknowledgments ......................................................................................... iii

Introduction .............................................................................................. 1

Survey Methods ........................................................................................... 2

Sample Design .......................................................................................... 2

Response .............................................................................................. 2

Survey Content ......................................................................................... 2

Weighting and Estimation ................................................................................. 4

Prevalence of Uninsured Children ............................................................................ 4

Comparison of Uninsurance Estimates with Other Data Sources.................................................. 4

Comparison of Demographic Distribution of Low-Income Uninsured Children ...................................... 4

Comparison of State-Specific Prevalence Estimates for Low-Income Uninsured Children ............................. 6

Evaluation of Prevalence Estimates ........................................................................... 7

National Survey of CSHCN Uninsurance Estimates May Be More Accurate ........................................ 7

Uninsured Children May Be Missing From the Sample ......................................................... 7

Parents May Be Misreporting Insurance Coverage ............................................................. 7

Survey Methodology and Health Insurance Coverage Estimates .................................................... 8

Recall Period ........................................................................................... 9

Verification of Uninsured Status ............................................................................ 11

Other Questionnaire Effects ............................................................................... 11

Underestimation of Medicaid Coverage ...................................................................... 11

Recoding of Verbatim Responses ........................................................................... 12

Weighting and Estimation ................................................................................. 12

Nonresponse Bias ......................................................................................... 13

Cooperation Rates by Demographic Characteristics ............................................................ 13

Representation of Telephone Population ..................................................................... 14

Representation If Poststratification Was Not Used ............................................................. 14

Bias Following Poststratification by Demographic Characteristics................................................. 15

Bias Following Poststratification by Service Interruption Status .................................................. 16

Reporting Bias ............................................................................................ 18

Experimental Approach ................................................................................... 18

Methods ............................................................................................... 19

Results ................................................................................................ 20

Tests for Other Biases ...................................................................................... 21

Interviewer Effects ...................................................................................... 21

Respondent Fatigue ...................................................................................... 23

Context Effects ......................................................................................... 24

Summary and Conclusions .................................................................................. 25

References ............................................................................................. 26

Appendixes

I. Program Names Used for Medicaid and SCHIP Questions .................................................. 28

II.Health Insurance Coverage Estimates ................................................................... 30

Insurance Coverage Estimates by Type of Insurance .................................................... 30

Uninsurance Estimates by Key Demographic Characteristics ............................................. 30

v
Text Tables

A. Health insurance questions used in the National Survey of Children with Special Health Care Needs ............... 3

B. Insurance coverage rates and survey design characteristics for five national surveys of children under 18 years

of age ............................................................................................ 5

C. Percent of children under 18 years of age without health insurance coverage by selected demographic characteristics

and national survey .................................................................................. 6

D. Percent of children under 18 years of age without health insurance coverage by race/ethnicity, household poverty

status, and national survey ............................................................................ 7

E. Percent of uninsured children under 18 years of age from low-income households (less than 200% of the Federal

poverty level) with selected demographic characteristics by national survey .................................... 8

F. Standard errors for the percent of uninsured children under 18 years of age from low-income households (less than

200% of the Federal poverty level) with selected demographic characteristics by national survey................... 9

G. Percent of children without health insurance and with income below 200% of the Federal poverty level, by State

and survey ......................................................................................... 10

H. Cooperation rates by expected distribution of selected demographic characteristics within telephone exchanges ....... 14

J. Composition of the population of households with children under 18 years of age and with telephone service, by

selected demographic characteristics .................................................................... 15

K. Composition of the population of households with children under 18 years of age by selected demographic

characteristics ...................................................................................... 16

L. Percent of children under 18 years of age with selected demographic characteristics by national survey ............. 17

M. Uninsurance rates for children under 18 years of age by telephone service status ................................ 18

N. Disposition of the experimental sample by question design group ............................................ 20

O. Insurance coverage rates by question design group ........................................................ 20

P. Uninsurance rates by interviewer tenure at Abt Associates and by tenure on the National Survey of Children with

Special Health Care Needs at the time of interview completion .............................................. 21

Q. Maximum-likelihood estimates and adjusted odds ratios from logistic regression predicting uninsurance rate from

household, child, and interviewer characteristics .......................................................... 22

R. Uninsurance rates by telephone center location ........................................................... 24

S. Uninsurance rates by National Immunization Survey eligibility .............................................. 24

T. Uninsurance rates by length of National Survey of Children with Special Health Care Needs interview ............. 24

U. Length of National Survey of Children with Special Health Care Needs interview by household income and

respondent education ................................................................................ 25

W. Insurance coverage rates by context of health insurance questions............................................ 25

Appendix Tables

I.State-specific insurance program names used for questions about Medicaid and the State Children’s Health Insurance

Program ........................................................................................... 29

II. Percent of children under 18 years of age by type of health insurance coverage and State: United States, 2001 ....... 31

III. Standard errors for the percent of children under 18 years of age by type of health insurance coverage and State ..... 32

IV. Percent of children under 18 years of age with special health care needs by type of health insurance coverage and

State: United States, 2001 ............................................................................ 33

V. Standard errors for the percent of children under 18 years of age with special health care needs by type of health

insurance coverage and State .......................................................................... 34

VI.Percent of children under 18 years of age without special health care needs by type of health insurance coverage

and State: United States, 2001 ......................................................................... 35

VII.Standard errors for the percent of children under 18 years of age without special health care needs by type of health

insurance coverage and State .......................................................................... 36

VIII.Results of statistical tests to identify differences between uninsurance rates for children under 18 years of age with

and without special health care needs, by State ........................................................... 37

IX.Percent of children under 18 years of age without health insurance coverage by selected demographic characteristics

and health status: United States, 2001 ................................................................... 38

vi
Objectives

The National Survey of Children with Estimating the Prevalence of 

Special Health Care Needs revealed

that 8.3% of children under 18 years of Uninsured Children: An 

age were uninsured, a rate lower than

the rate estimated by other national

surveys. This report presents the Evaluation of Data From the 

results of an evaluation of the quality of

this estimate, based on analyses of National Survey of Children with 

nonresponse, question design,

interviewer and respondent effects, and

the weighting and estimation process. Special Health Care Needs, 2001 

National and State-level statistics on

health insurance coverage for children by Stephen J. Blumberg, Ph.D., Centers for Disease Control and

with special health care needs

(CSHCN) and for children without Prevention; Larry Osborn, M.P.H., Abt Associates Inc.; Julian V.

special needs are included in an Luke, Centers for Disease Control and Prevention; Lorayn Olson,

appendix. Ph.D., Abt Associates Inc.; Martin R. Frankel, Ph.D., Baruch College,

City University of New York and Abt Associates Inc.

Source of Data

The National Survey of CSHCN is a

survey module of the State and Local

Area Integrated Telephone Survey. This

survey of parents and guardians

collected health insurance coverage needs. These data would facilitate the 

information for a national sample of Introduction comparison of health insurance coverage 215,162 children. Data were collected estimates for children with and without from October 2000 through April 2002.

he National Survey of Children special needs and would permit 

Results T with Special Health Care Needs State-specific estimates of health 

Compared with other surveys, was designed to estimate the insurance coverage for all children. 

Health insurance data were weighted data from the National Survey national and State-specific prevalence of 

collected for a total of 215,162 of CSHCN describe a population with a children with special health care needs

slightly larger proportion of Hispanic (CSHCN), describe the types of services children—38,866 children with special

children and children from households that they need and use, and assess needs and 176,296 children without

with higher incomes. The National shortcomings in the system of care for special needs. Funding for the collection

Survey of CSHCN was also the only CSHCN (1). The survey, fielded from of data concerning children without

survey to use a child-level design: A October 2000 through April 2002, was special needs was provided by MCHB

randomized experiment that varied the sponsored by the Maternal and Child and OASPE. OASPE funds came, in

health insurance questions found that Health Bureau (MCHB) of the Health part, from the Congressional allocation

repeating the coverage questions for Resources and Services Administration. for the DHHS evaluation of the State

each child produced lower uninsurance The initial design of the National Children’s Health Insurance Program

rates than household-level questions Survey of CSHCN called for collection (SCHIP), as mandated in the Balanced

that first asked if anyone in the

household was insured. of health insurance coverage data for Budget Refinement Act of 1999.

CSHCN only. However, given that only This report compares estimates of 

Conclusion 13% of children have special health care the prevalence of uninsured children 

Question design differences explain needs (2), a considerable number of from the National Survey of CSHCN 

much of the discrepancy between children without special health care with estimates from other surveys. 

survey estimates of the uninsurance needs would also be identified during Possible explanations for observed 

rate, but a definitive conclusion the screening process. MCHB and the differences are explored with a focus on 

regarding the relative accuracy of the Office of the Assistant Secretary for differences in survey design, potential 

uninsurance rates is not possible. Planning and Evaluation (OASPE) in demographic biases in the National 

the Department of Health and Human Survey of CSHCN sample, and two 

Keywords: Health insurance c health Services (DHHS) recognized the benefit experiments on the influence of 

surveys c data quality of collecting health insurance coverage questionnaire design. 

data for the children without special 

Page 1
Page 2 [ Series 2, No. 136

Survey Methods 

Details concerning the 

questionnaire and survey 

methods are available in a Vital 

and Health Statistics Series report 

entitled Design and Operation of the

National Survey of Children with

Special Health Care Needs, 2001 (3). 

This section provides an overview of 

these topics. 

Sample Design

The National Survey of CSHCN 

was conducted as a module of the State 

and Local Area Integrated Telephone 

Survey (SLAITS). The SLAITS 

program, sponsored by the Centers for 

Disease Control and Prevention (CDC), 

National Center for Health Statistics 

(NCHS), is a broad-based, ongoing 

surveillance system available at the 

State and local levels for tracking and 

monitoring the health and well-being of 

children and adults. SLAITS uses the 

same sampling frame as the National 

Immunization Survey (NIS), which is 

conducted jointly by NCHS and the 

CDC’s National Immunization 

Program (4). The NIS is a large-scale 

random-digit-dial telephone survey that 

screens for the presence of young 

children in sampled households and 

collects vaccination history information 

for eligible children (5). The size of the 

NIS sample provides an economical 

opportunity to survey other populations 

in addition to the rare population that 

eventually screens into the NIS itself. 

The goal of the National Survey of 

CSHCN was to generate samples 

representative of the State populations 

of noninstitutionalized children with and 

without special health care needs. An 

additional goal of the National Survey 

of CSHCN was to obtain State-specific 

sample sizes that were sufficiently large 

to permit precise estimates of the 

characteristics of CSHCN in each State. 

To achieve these goals, State samples 

were designed to obtain 750 completed 

interviews concerning CSHCN. A target 

number of health insurance interviews 

for children without special needs was 

not set. Rather, for each contacted 

household with children, a health 

insurance interview for a child without 

special needs was done if at least one 

such child was identified. 

The target population for the survey 

consisted of households with children 

under 18 years of age. Telephone 

households within each of the 50 States 

and the District of Columbia were 

identified via random-digit dialing. 

These households were screened for 

children within the eligible age range. If 

children were in the household, 

screening questions were asked about 

their health status and care needs. If any 

children in the household were 

identified as having special health care 

needs, one was randomly selected for a 

detailed interview. Similarly, if there 

were children without special needs, one 

was randomly selected for a brief health 

insurance interview. Therefore, eligible 

households with children could have 

either one or two children selected for 

an interview, depending on the care 

needs of the children in the household. 

The health insurance sections of the 

interviews for children with and without 

special needs were identical. 

Response

Data collection and processing was 

conducted by Abt Associates Inc., under 

contract to NCHS. Health insurance 

interviews were completed with the 

parents and guardians of 215,162 

children from 192,321 households. Of 

these children, 38,866 had special health 

care needs and 176,296 did not. 

The respondent for the National 

Survey of CSHCN was the parent or 

guardian in the household who was 

most knowledgeable about the children’s 

health and health care. The majority of 

respondents were mothers or female 

guardians of the children (78.9%). The 

remaining respondents were fathers or 

male guardians (17.2%), grandparents 

(2.4%), or other relatives or 

friends (1.5%). 

A weighted response rate was 

calculated for the National Survey of 

CSHCN to reflect the potential for 

nonresponse bias in the sample of 

children for whom health insurance data 

were collected. This response rate, based 

on the Council of American Survey 

Research Organizations guidelines, was

calculated in accordance with the

American Association for Public

Opinion Research’s standard

definitions (6) and using the

assumptions for Response Rate #3

detailed by Ezzati-Rice and others (7).

Nationally, the response rate was 61.8%.

Survey Content

The National Survey of CSHCN 

questionnaire included several questions 

regarding insurance coverage. These 

questions appear in table A. Questions 

asked separately about private coverage 

(defined as employer- or union-based or 

purchased directly), Medicaid, SCHIP, 

military coverage, and Title V. After the 

series of coverage-specific items, a 

catch-all question asked whether the 

child was covered by any other 

insurance not previously mentioned. If 

‘‘other’’ insurance was reported, an 

open-ended item captured the name or 

type of insurance. When either private 

or ‘‘other’’ insurance was reported, a 

followup question to determine the 

comprehensiveness of the coverage 

asked whether the insurance covered 

doctor visits and hospital stays. 

If the respondent answered 

negatively to coverage under all of the 

types mentioned, a confirmation 

question was asked. If a respondent 

indicated that the child was insured, the 

respondent was asked what kind of 

health insurance the child had. As with 

the initial series of insurance items, if 

‘‘other’’ insurance was reported at this 

point, an open-ended item captured the 

name or type of insurance. When private 

or ‘‘other’’ insurance was reported, a 

followup question asked whether the 

reported insurance covered doctor visits 

and hospital stays. 

No questions asked directly about 

single-service plans (e.g., dental or 

accident insurance) or health coverage 

plans for American Indians or Alaska 

Natives (e.g., Indian Health Service). 

When these types of coverage were 

reported (e.g., in the verbatim response 

following a report of ‘‘other’’ 

insurance), they were not considered to 

be a comprehensive type of insurance. 
Series 2, No. 136 [ Page 3

Table A. Health insurance questions used in the National Survey of Children with Special Health Care Needs

Stem

question Followup questions

1. Now I have a few questions about health insurance and health care coverage for your child. At this time, is your child covered by health insurance that is

provided through an employer or union or obtained directly from an insurance company?

(IF YES TO #1) Does this health insurance help pay for both doctor visits and hospital stays?

2. At this time, is your child covered by Medicaid, a health insurance program for persons with certain income levels and persons with disabilities?

[IF APPLICABLE: In this State, the program is sometimes called .]

3. At this time, is your child covered by the State Children’s Health Insurance Program or SCHIP?

[IF APPLICABLE: In this State, the program is sometimes called .]

4. At this time, is your child covered by military health care, TRICARE, CHAMPUS, or CHAMP-VA?

5. At this time, is your child enrolled in a Title Five program?

[IF APPLICABLE: In this State, the program is sometimes called .]

6. At this time, is your child covered by any other kind of health insurance or health care plan that pays for services obtained from hospitals, doctors, and other

health professionals?

(IF YES TO #6) What kind of health plan is it?

(IF YES TO #6) Does this health insurance help pay for both doctor visits and hospital stays?

(IF YES TO #6) Is this health insurance provided through an employer?

7. (IF NO TO #1–#6) It appears that your child does not have any health insurance coverage to pay for services from both hospitals and doctors and other health

professionals. Is that correct?

(IF NO TO #7) What kind of health coverage does your child have?

(IF PRIVATE/OTHER) Does this health insurance help pay for both doctor visits and hospital stays?

NOTE: See ‘‘Appendix I’’ for a list of States with applicable Medicaid and SCHIP program names. For more detail about interviewer instructions and response coding, see the specifications in the

Design and Operation of the National Survey of Children with Special Health Care Needs, 2001 (3).

The National Survey of CSHCN + Because the phrase ‘‘private + In the questions regarding Medicaid, 

made a number of efforts to effectively insurance’’ may not have been SCHIP, and Title V coverage, the 

capture the insurance status of the familiar to all respondents, it was State-specific program names for each 

children. Careful attention was paid to not used in the question about type of coverage were included in the 

wording of the introductory script and private coverage. Instead, the question text, in case respondents 

question text, appropriate use of question asked specifically about recognized the State program name, 

followup questions to establish coverage through an employer or but not the national program 

comprehensiveness of coverage reported, union or purchased directly. affiliation. The terms ‘‘Medicaid,’’ 

and development of help-screen text to + The private coverage question was ‘‘SCHIP,’’ and ‘‘Title V’’ were also 

guide interviewers and respondents in asked first in the series of insurance used, in case the reverse was true. 

accurate reporting and coding. The items. Because respondents often These program names are included in 

following are a few examples: answered this question with a plan ‘‘Appendix I.’’ 

+ During pretesting, the introduction 

to the health insurance section of the 

interview referred to questions about 

health insurance that the sampled 

child ‘‘may have.’’ To more clearly 

indicate that the questions pertained 

to coverage that the child did, in 

fact, have, the introductory script 

used in the main study was, ‘‘Now I 

have a few questions about health 

insurance and health care coverage 

for (CHILD).’’ 

+ To establish the fact that current 

point-in-time coverage was the focus 

of the insurance items, the words 

‘‘at this time’’ were added to the 

beginning of each individual 

coverage question. 

+

+

name, an on-screen instruction 

prompted interviewers to probe 

further in such cases so as to 

determine whether the plan was 

provided through an employer or 

union or was purchased directly. 

Because single-service plans were 

not considered to be comprehensive 

coverage, on-screen text for the 

private and ‘‘other’’ coverage items 

prompted the interviewers not to 

include dental, vision, school, or 

accident insurance in the answers. 

If only initials or a partial plan 

name were offered at the 

open-ended ‘‘other’’ insurance item, 

interviewers were instructed to 

probe for a full plan name. 

+

+

+

A followup question was used to 

determine the comprehensiveness of 

reported private or ‘‘other’’ 

insurance. 

Several help screens were developed 

for the individual insurance items. 

Each help screen provided a 

definition of the coverage in 

question. In addition, the help screen 

provided an explanation for the need 

to ask multiple questions regarding 

coverage to capture all types of 

coverage for the sampled child. 

Because it was important to ensure 

that comprehensiveness of each type 

of insurance was reported accurately, 

interviewer training emphasized the 

need to determine the type of 
Page 4 [ Series 2, No. 136

insurance and whether it was 

comprehensive. Reminders of this 

training were included in each help 

screen: ‘‘The two most important 

things to help respondents determine 

what type of insurance they have are 

(a) where it comes from, and 

(b) what it covers. If necessary, to 

help respondents determine what 

kind of insurance they have, probe, 

‘Did you get that insurance through 

an employer? Does it help pay for 

both doctor visits and hospital 

stays?’ ’’ 

Weighting and Estimation

To produce population-based 

estimates, each child for whom complete 

insurance data were available was 

assigned a sampling weight. This weight 

combined the base weight, which 

reflects the probability of selection of a 

respondent’s telephone number, with an 

adjustment for households that have 

multiple telephone numbers, an 

adjustment for households that have 

more than one child, and adjustments 

that compensate for nonresponse. 

Finally, weights were adjusted to match 

known population control estimates and 

to adjust for the noncoverage of 

nontelephone households. Further details 

about this adjustment are included in the 

Design and Operation of the National

Survey of Children with Special Health

Care Needs, 2001 (3) and are also 

summarized in a later section of this 

report. 

Prevalence of 

Uninsured Children 

To establish insurance status, 

respondents were asked about 

various types of coverage. For 

each type, the respondent indicated 

whether the sampled child had that 

coverage. A negative response for each 

question was required for a child to be 

considered uninsured. Alternatively, a 

child could also be considered uninsured 

if the type of coverage was not reported 

to be comprehensive (e.g., if the 

respondent indicated that the insurance 

did not cover doctor visits and hospital 

stays or if the insurance only covered 

dental care, vision, or accident care) or 

if the insurance was not considered to 

be comprehensive (e.g., Indian Health 

Service and other health insurance plans 

specifically for American Indians and 

Alaska Natives). 

The overall estimated prevalence of 

uninsured children from the National 

Survey of CSHCN is 8.3%. The 

uninsurance rates for each State and 

State-specific insurance estimates by 

type of insurance are presented in 

‘‘Appendix II.’’ 

Comparison of

Uninsurance Estimates

With Other Data

Sources

Estimated uninsurance rates for 

noninstitutionalized children 0–17 years 

of age from the National Survey of 

CSHCN, the 2001 National Health 

Interview Survey (NHIS), the 1999 

National Survey of America’s Families 

(NSAF), the 2002 Current Population 

Survey (CPS) Annual Demographic 

Supplement, and the 2001 Medical 

Expenditure Panel Survey (MEPS) are 

compared in table B. Public-use data 

were used to derive estimates for all 

surveys (8–12). The National Survey of 

CSHCN produced the lowest 

uninsurance estimate at 8.3%. The other 

surveys generated rates ranging from 

11.0% in the 2001 NHIS to 14.6% in 

the 2001 MEPS. It should be noted, 

however, that these surveys differ in 

their methods of collecting health 

insurance data (e.g., by using a 

confirmation question to verify 

noncoverage). As table B indicates, the 

recall and data collection periods also 

vary considerably. 

Survey-specific differences in the 

overall survey estimate of uninsurance 

could result from reporting differences 

for just one demographic subgroup. A 

comparison of the estimated uninsurance 

rates for specific demographic groups 

from the National Survey of CSHCN 

and the 2001 NHIS are presented in 

tables C and D. In general, trends in 

uninsurance rates among demographic 

subgroups were similar for both surveys. 

That is, for both surveys, rates of 

uninsurance were higher for older 

children, for Hispanic children, for 

children living in non-English-speaking 

households, and for children whose 

mothers had less education. 

For nearly every demographic 

subcategory, however, uninsurance rates 

from the National Survey of CSHCN 

were lower than rates from the NHIS. 

This consistency in the direction of the 

differences was found for every 

demographic subcategory except for 

children living in households with an 

income below 50% of the Federal 

Poverty Level. For these very poor 

children, the uninsurance rate from the 

National Survey of CSHCN was greater 

than the rate from the NHIS (though 

this difference was not statistically 

significant, p = .13). 

Despite the consistency in the 

direction of the differences, the 

magnitude of the difference between the 

National Survey of CSHCN and the 

NHIS uninsurance rates varied by 

demographic subcategory. For example, 

the differences for children living in 

households with an income between 

50% and 199% of the Federal Poverty 

Level were statistically significant 

(p < .05) for Hispanic children, but were 

not statistically significant for 

non-Hispanic black children and for 

other non-Hispanic children. Overall, the 

magnitude of the difference between the 

uninsurance rates was greatest for 

non-Hispanic other than black 

children (32.7% lower, relative to the 

NHIS rate) and for children in 

households with an income between 

150% and 199% of the Federal Poverty 

Level (29.6% lower). 

Comparison of

Demographic Distribution

of Low-Income Uninsured

Children

Given these differences in the 

uninsurance rate among specific 

demographic subgroups, there was 

reason to believe that the composition of 

the population of uninsured children 

described by the National Survey of 

CSHCN would differ from the 

population described by the other 
Series 2, No. 136 [ Page 5

Table B. Insurance coverage rates and survey design characteristics for five national surveys of children under 18 years of age

Current

Population

National National Survey Medical

National Health Survey of Annual Expenditure

Survey of Interview America’s Demographic Panel

Characteristic CSHCN1 Survey Families Supplement Survey

Insurance coverage rate:

Insured ...................... 91.7 89.0 87.4 88.3 85.5

Uninsured .................... 8.3 11.0 12.6 11.7 14.6

Survey design:

Recall period for insurance coverage Time of Time of Time of Prior calendar Varies from 3 to

rate2 ....................... interview interview interview year 5 months prior

to interview

Dates of data collection ............ Oct. 2000– Jan. 2001– Feb. 1999– Feb. 2002– Jan. 2001–

Apr. 2002 Dec. 2001 Oct. 1999 Apr. 2002 Jul. 2001

Mode of data collection ............ Telephone In person Telephone, with in- In person and In person and

person supplement telephone telephone

Sample frame .................. Random-digit-dial Area probability Random-digit-dial for Area probability NHIS

telephone households, respondents

and area probability for

nontelephone

households

Uninsurance verification ............ Yes Yes Yes Yes No

Question design ................ Child-level Family-level Family-level Family-level Family-level

First insurance question ............ Private insurance Any insurance Employer-based Employer-based Medicare

insurance insurance

Context ...................... Health Health Employment, Employment and Health

program participation, income

health care, and

education

Medicaid coverage may be assigned .... No No Yes Yes Yes

‘‘Other’’ verbatim responses permitted . . . Yes Yes Yes No Yes

Names of health plans obtained ....... No Yes No No Yes

1CSHCN is children with special health care needs.

2The National Survey of CSHCN, the National Health Interview Survey, and the National Survey of America’s Families also include questions about coverage during the prior 12 months.

surveys. These differences were of children whose parents could not or composition of the low-income 

particular concern for the National would not answer the income questions uninsured population would affect key 

Survey of CSHCN because data from were also eligible for the supplement, estimates of familiarity with, perceptions 

the survey would be used for the but their data were not included in the of, and experiences with Medicaid and 

Congressionally mandated DHHS analyses reported here.) SCHIP programs (13). Sensitivity 

evaluation of SCHIP. Congress Tables E and F present the analyses were conducted by adjusting 

stipulated that the evaluation must demographic characteristics of the the sampling weights for income and/or 

include the collection of information population of low-income uninsured education subgroups and then estimating 

about the reasons that many children children as estimated by the National key variables from the Low-Income 

eligible for SCHIP are not enrolled. Survey of CSHCN, the 2001 NHIS, the Uninsured Supplement. The similarity 

Therefore, OASPE funded the 1999 NSAF, and the 2002 CPS. was remarkable. The key estimates 

Low-Income Uninsured Supplement to Consistent differences were observed for derived, using the various adjusted 

the National Survey of CSHCN. The income and maternal education. The sampling weights, differed by less than 

goal for this supplement was to gather National Survey of CSHCN identified a 4 percentage points for both national 

data on parents’ knowledge and use of smaller proportion of low-income estimates and for key subgroup 

SCHIP and Medicaid programs for uninsured children in the higher income differences. Thus, researchers can have 

uninsured children from low-income brackets (e.g., 150%–199% of poverty) confidence that results of analyses from 

households. Regardless of special-needs and in the higher education brackets the Low-Income Uninsured Supplement 

status, all sampled children who were (e.g., mother had post-high-school are robust and are unlikely to have been 

uninsured and who resided in a education). biased by the existing demographic 

household with an annual income below Using data from the first 6 months differences in the composition of the 

200% of the DHHS Federal Poverty of data collection, NCHS collaborated low-income uninsured population. 

Guidelines received the Low-Income with The Urban Institute to investigate 

Uninsured Supplement. (Uninsured whether these differences in the 
Page 6 [ Series 2, No. 136

Table C. Percent of children under 18 years of age without health insurance coverage by selected demographic characteristics and national

survey

National Survey National Health National Survey National Health

of CSHCN1 Interview Survey of CSHCN Interview Survey

Selected demographic characteristic (2001) (2001) (2001) (2001)

Percent uninsured Standard error of percent

Age

0–5 years ............................. 7.2 9.7 0.21 0.44

6–11 years ............................ 8.4 11.3 0.23 0.47

12–17 years ........................... 9.2 12.0 0.22 0.46

Sex

Female .............................. 8.4 11.0 0.18 0.38

Male ................................ 8.2 11.0 0.18 0.40

Race/ethnicity

Hispanic .............................. 19.2 24.6 0.53 0.88

Black non-Hispanic ....................... 7.3 10.6 0.31 0.90

White non-Hispanic and all others .............. 5.8 7.8 0.11 0.37

Language of interview

English .............................. 6.3 8.8 0.11 0.34

Spanish or other language .................. 27.5 34.9 0.83 1.43

Household income

Up to $9,999 ........................... 17.0 14.5 0.76 1.43

$10,000–$19,999 ........................ 17.7 18.8 0.58 1.48

$20,000–$39,999 ........................ 14.0 17.0 0.40 0.90

$40,000–$59,999 ........................ 6.7 8.6 0.30 0.71

$60,000 and over ........................ 2.5 2.4 0.12 0.26

Poverty status2,3

Up to 49% of FPL ........................ 18.5 15.3 0.87 1.89

50%–99% of FPL ........................ 18.4 20.9 0.67 1.52

100%–149% of FPL ...................... 15.5 18.5 0.60 1.23

150%–199% of FPL ...................... 11.4 16.1 0.48 1.36

200% of FPL and over ..................... 3.8 4.5 0.11 0.25

Maternal education

8th grade or less ........................ 28.3 34.8 1.15 2.10

Some high school ........................ 16.3 19.4 0.60 1.15

High school graduate or GED4 ................ 8.3 10.4 0.21 0.50

Some post-high school, but no college degree ...... 5.5 7.1 0.19 0.44

4-year college degree or higher ............... 2.8 3.2 0.10 0.37

1CSHCN is children with special health care needs.

2Poverty status is assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey.

3FPL is Federal poverty level.

4GED is General Educational Development high school equivalency diploma.

Comparison of StateSpecific Prevalence

Estimates for Low-Income

for the National Survey of CSHCN and 

the CPS. CPS estimates were based on the 

average of 3 years of Annual 

Demographic Supplement estimates 

CSHCN in 45 States and the District of 

Columbia. Surprisingly, perhaps, these 

differences were statistically significant 

(p < .05) for only 14 States. However, 

Uninsured Children (2000–2002), as published by the U.S. meaningful differences in other States 

Census Bureau (14). Three years of data may not have reached statistical 

The reported prevalence estimates were necessary to stabilize the estimates significance due to the small CPS 

have been estimates for the Nation, but because of small annual sample sizes in sample size, relatively large standard 

State-level estimates can also be some States. Low income was defined as error, and the inclusion of 18-year-old 

compared across data sources. Of the an annual household income level below children in the CPS estimates. 

data sources considered (NHIS, NSAF, 200% of the Federal Poverty Level. State rankings by prevalence were 

CPS, and MEPS), only the CPS permits As expected based on the national very similar across surveys. Spearman’s 

State-specific estimates for all States. estimates, the prevalence of low-income rank-order correlation coefficient, 

Table G presents the prevalence of uninsured children was greater for the adjusted for tied ranks, was 0.88, 

low-income uninsured children by State CPS than for the National Survey of p < .001. 
Series 2, No. 136 [ Page 7

Table D. Percent of children under 18 years of age without health insurance coverage by race/ethnicity, household poverty status, and

national survey

National National

National Health National Health

Survey of Interview Survey of Interview

Race/ethnicity and CSHCN2 Survey CSHCN2 Survey

poverty status1 (2001) (2001) (2001) (2001)

Percent uninsured Standard error of percent

Hispanic

Up to 49% of FPL ........................ 29.2 27.1 1.80 3.12

50%–99% of FPL ........................ 27.5 33.6 1.41 2.32

100%–149% of FPL ...................... 22.8 31.4 1.53 2.25

150%–199% of FPL ...................... 15.7 23.7 1.50 2.28

200% of FPL and over ..................... 7.5 9.7 0.71 0.90

Black non-Hispanic

Up to 49% of FPL ........................ 12.4 11.6 1.24 2.34

50%–99% of FPL ........................ 11.7 12.0 1.15 2.32

100%–149% of FPL ...................... 10.6 10.0 1.01 2.16

150%–199% of FPL ...................... 7.7 10.8 0.95 2.12

200% of FPL and over ..................... 3.2 4.7 0.31 0.79

White non-Hispanic and all others

Up to 49% of FPL ........................ 10.9 12.0 1.01 3.34

50%–99% of FPL ........................ 13.5 16.2 0.75 2.48

100%–149% of FPL ...................... 13.4 14.1 0.67 1.62

150%–199% of FPL ...................... 10.9 14.8 0.52 1.99

200% of FPL and over ..................... 3.5 3.8 0.11 0.29

1Poverty status is assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey.

2CSHCN is children with special health care needs.

NOTE: FPL is Federal poverty level.

Evaluation of 

Prevalence Estimates 

t is clear that the National Survey of 

CSHCN uninsurance rate differs 

from those of other surveys. The 

remainder of this report will examine 

three possible reasons for this 

difference. 

National Survey of CSHCN

Uninsurance Estimates

May Be More Accurate

Although the uninsurance rate from 

the National Survey of CSHCN data is 

quite different than the rates calculated 

from other national survey data, the 

rates from these other surveys have 

historically disagreed with each other. 

Considerable investigation has been 

devoted to the challenge of disparate 

measures of the uninsured population 

(15–19). This body of literature 

addresses the insurance estimates and 

survey methodologies of national 

surveys, including the CPS, NHIS, and 

NSAF. In particular, the literature cites 

the following six areas as being 

potential sources for the differences 

observed among surveys and between 

surveys and administrative records: 

recall periods, determination of 

coverage, questionnaire design, 

undercounts of Medicaid enrollees, data 

editing procedures, and the estimation 

processes used to bring the demographic 

data from the surveys in line with 

established population totals. 

Given the variation in data 

collection methodologies across surveys, 

it is possible that the National Survey of 

CSHCN method of gathering health 

insurance information results in more 

accurate reporting. The viability of this 

explanation will be explored in detail as 

the two other possible reasons for the 

observed differences are considered. 

Uninsured Children May

Be Missing From Sample

A comparison of uninsurance rates 

by subpopulation and by characteristics 

within subpopulation among surveys 

indicates that the National Survey of 

CSHCN uninsured group may be 

different from that of other surveys. If 

the National Survey of CSHCN sample 

excluded groups that were more likely 

to be uninsured, an uninsurance rate 

lower than that found in other surveys 

might be expected. To investigate this 

possibility, the demographic profile of 

the overall National Survey of CSHCN 

sample was compared with those of 

other surveys that produced differing 

uninsurance rates. This report explores 

the results of analyses of National 

Survey of CSHCN sample-related 

characteristics that examined this 

potential sample bias in more detail. 

Parents May Be

Misreporting Insurance

Coverage

Given the methodological 

differences in the collection of insurance 

data among surveys, it may be that 

characteristics of the National Survey of 

CSHCN questionnaire design led parents 

I
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Page 8 [ Series 2, No. 136

Table E. Percent of uninsured children under 18 years of age from low-income households (less than 200% of the Federal poverty level)

with selected demographic characteristics by national survey

Current Population

National National Survey Survey Annual

Survey of National Health of America’s Demographic

CSHCN1 Interview Survey Families Supplement

Selected demographic characteristic (2001) (2001) (1999) (2002)

Age

0–5 years ............................. 28.3 28.9 28.6 28.9

6–11 years ............................ 34.6 35.7 37.9 32.9

12–17 years ........................... 37.1 35.4 33.6 38.2

Sex

Female .............................. 50.2 48.2 51.0 49.9

Male ................................ 49.8 51.9 49.0 50.1

Race/ethnicity

Hispanic .............................. 47.1 45.8 35.8 42.3

Black non-Hispanic ....................... 14.6 13.5 19.7 19.3

White non-Hispanic and all others .............. 38.3 40.7 44.5 38.4

Language of interview

English .............................. 62.0 67.9 77.8

Spanish or other language .................. 38.0 32.1 22.2

Income2

Up to $9,999 ........................... 16.4 12.9 18.7 30.0

$10,000–$19,999 ........................ 28.9 29.1 33.2 27.5

$20,000–$39,999 ........................ 49.2 49.8 41.9 35.4

$40,000–$59,999 ........................ 5.5 7.5 4.5 6.2

$60,000 and over ........................ 0.0 0.7 1.7 0.8

Poverty status2,3

Up to 49% of FPL ........................ 17.0 13.7 16.4 24.6

50%–99% of FPL ........................ 30.8 32.2 29.5 25.0

100%–149% of FPL ...................... 31.5 29.9 28.8 28.4

150%–199% of FPL ...................... 20.7 24.2 25.3 22.0

Maternal education

8th grade or less ........................ 22.0 26.2 24.0 23.1

Some high school ........................ 26.1 23.5 16.3 22.6

High school graduate or GED4 ................ 32.1 27.4 31.2 30.0

Some post-high school, but no college degree ...... 14.9 19.4 23.0 19.4

4-year college degree or higher ............... 4.9 3.5 5.6 4.9

0.0 Quantity more than zero but less than 0.05.

Category not available.

1CSHCN is children with special health care needs.

2Income and poverty status are assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey, National Survey of America’s

Families, and Current Population Survey.

3FPL is Federal poverty level.

4GED is General Educational Development high school equivalency diploma.

to misreport coverage for their children. 

A small error rate in the reporting of 

insurance can become a large error in 

experimental studies are described. The 

first study, conducted by the U.S. 

Census Bureau, examined the effect of 

Survey Methodology 

and Health Insurance 

the estimate of the uninsured. ‘‘With the 

number of children insured at a point in 

collecting insurance data using a 

person-level versus a household-level Coverage Estimates 

time being eight to nine times the design. The second study, conducted by 

number without insurance...errors in the 

reporting of insurance coverage are 

multiplied many times in their impact 

on estimates of the uninsured’’ (18). 

To investigate the possible influence 

of question design on the overall 

uninsurance rate for children, two 

Abt Associates, investigated the effects 

of question design and context on 

reporting of insurance. This report also 

provides the results of analyses of other 

possible factors that might lead to 

misreporting, such as respondent fatigue 

and interviewer effects. 

As table B indicates, there are 

several methodological 

differences between the National 

Survey of CSHCN and the other 

national surveys that produced differing 

uninsurance estimates. This section 

discusses the potential impact of these 
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Series 2, No. 136 [ Page 9

Table F. Standard errors for the percent of uninsured children under 18 years of age from low-income households (less than 200% of the

Federal poverty level) with selected demographic characteristics by national survey

Current Population

National National Health National Survey of Survey Annual

Survey of Interview America’s Demographic

CSHCN1 Survey Families Supplement

Selected demographic characteristic (2001) (2001) (1999) (2002)

Age

0–5 years ............................. 0.99 1.33 1.23 0.97

6–11 years ............................ 1.06 1.20 1.43 1.00

12–17 years ........................... 1.06 1.59 1.72 1.04

Sex

Female .............................. 1.10 1.35 1.71 1.07

Male ................................ 1.10 1.35 1.71 1.07

Race/ethnicity

Hispanic .............................. 1.15 2.55 1.91 1.13

Black non-Hispanic ....................... 0.75 1.45 1.38 0.90

White non-Hispanic and all others .............. 1.04 2.73 2.33 1.04

Language of interview

English .............................. 1.17 2.21 1.50

Spanish or other language .................. 1.17 2.21 1.50

Income2

Up to $9,999 ........................... 0.77 1.16 1.45 0.98

$10,000–$19,999 ........................ 0.95 2.17 1.92 0.95

$20,000–$39,999 ........................ 1.14 2.15 1.94 1.02

$40,000–$59,999 ........................ 0.62 1.32 0.99 0.52

$60,000 and over ........................ 0.02 0.46 0.94 0.19

Poverty status2,3

Up to 49% of FPL ........................ 0.83 1.57 1.44 0.92

50%–99% of FPL ........................ 1.06 1.95 1.63 0.92

100%–149% of FPL ...................... 1.09 2.06 1.48 0.96

150%–199% of FPL ...................... 0.86 1.86 1.74 0.88

Maternal education

8th grade or less ........................ 1.11 2.42 2.86 0.84

Some high school ........................ 1.07 1.74 1.35 0.84

High school graduate or GED4 ................ 1.02 2.01 1.89 0.93

Some post-high school, but no college degree ...... 0.73 1.74 1.77 0.78

4-year college degree or higher ............... 0.31 0.85 0.58 0.42

Category not available.

1CSHCN is children with special health care needs.

2Income and poverty status are assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey, National Survey of America’s

Families, and Current Population Survey.

3FPL is Federal poverty level.

4GED is General Educational Development high school equivalency diploma.

methodological differences based on a between the recall period specified in a recall period. The CPS is similar in that 

review of the literature. questionnaire and the period that the respondent must be uninsured for 

respondents actually use to form their the entire recall period to be considered 

Recall Period responses. uninsured. It differs in that the recall 

The NHIS, the NSAF, and the period is the full calendar year that 

Although researchers tend to National Survey of CSHCN ask ended 2–4 months prior to the interview. 

compare insurance rates among surveys, respondents about insurance coverage at In effect, by considering coverage over 

the recall periods used to produce those the time of the interview. In contrast, time rather than at a point in time, the 

rates can differ dramatically. At least the MEPS asks respondents to report MEPS and the CPS questions are 

two issues related to a survey’s recall whether they had various types of conceptually different than the questions 

period can lead to potential reporting insurance coverage at any time during from the other surveys. 

differences. The first issue is the length the preceding 3–6 months. Respondents However, the recall period specified 

of the recall period specified. The are considered to be uninsured only if by the interviewer is not necessarily the 

second issue is the possible disconnect they lacked coverage for the entire period that they use to form their 
Page 10 [ Series 2, No. 136

Table G. Percent of children without health insurance and with income below 200% of the Federal poverty level, by State and survey

Current Population Survey Annual

National Survey of CSHCN1 (2001) Demographic Supplement (2000–2002)2

State Prevalence Standard error Rank3 Prevalence Standard error Rank3

All States4 ................ 5.6 0.12 . . . 7.9 0.2 . . .

Alabama .................. 5.6 0.53 35.0 6.4 1.2 26.0

Alaska ................... 6.0 0.48 37.0 7.0 1.2 32.0

Arizona .................. 9.8 0.66 48.0 12.9 1.7 48.0

Arkansas ................. 7.5 0.64 42.0 8.7 1.5 41.0

California4 ................. 6.9 0.54 40.0 10.4 0.7 43.0

Colorado ................. 6.2 0.48 38.0 8.6 1.3 40.0

Connecticut4 ............... 1.6 0.29 3.0 4.8 1.1 15.5

Delaware ................. 3.3 0.47 16.0 4.0 1.1 12.0

District of Columbia ........... 4.5 0.53 27.0 6.5 1.6 28.0

Florida4 .................. 8.4 0.70 43.0 11.3 1.0 46.0

Georgia .................. 5.3 0.57 32.0 7.4 1.2 34.0

Hawaii4 .................. 1.8 0.27 4.0 5.0 1.1 17.5

Idaho .................... 8.7 0.65 44.5 11.1 1.6 44.0

Illinois ................... 4.8 0.59 28.0 6.7 0.8 29.0

Indiana4 .................. 3.3 0.45 17.0 6.4 1.1 26.0

Iowa .................... 3.8 0.41 21.0 3.7 0.9 9.0

Kansas .................. 4.9 0.49 29.0 7.1 1.3 33.0

Kentucky4 ................. 4.0 0.42 23.0 6.9 1.4 30.5

Louisiana ................. 10.1 0.90 49.0 13.4 1.8 49.0

Maine ................... 4.2 0.46 25.0 3.4 0.9 6.0

Maryland4 ................. 2.0 0.33 6.0 4.6 1.1 14.0

Massachusetts .............. 2.0 0.36 5.0 3.6 0.8 7.5

Michigan ................. 2.5 0.38 9.0 3.9 0.7 11.0

Minnesota ................. 3.1 0.45 13.0 3.0 0.8 5.0

Mississippi ................ 5.4 0.56 33.0 7.7 1.4 37.5

Missouri .................. 2.1 0.30 7.0 2.6 0.7 3.0

Montana .................. 10.8 0.71 50.0 10.2 1.7 42.0

Nebraska ................. 3.0 0.36 12.0 5.0 1.1 17.5

Nevada .................. 8.8 0.63 46.0 11.2 1.5 45.0

New Hampshire ............. 4.0 0.53 22.0 2.5 0.7 2.0

New Jersey ................ 4.1 0.49 24.0 5.4 0.8 19.0

New Mexico4 ............... 9.0 0.78 47.0 14.8 1.9 50.0

New York4 ................ 3.6 0.42 19.0 6.1 0.6 22.5

North Carolina .............. 5.2 0.54 30.0 7.5 1.1 35.5

North Dakota ............... 5.9 0.56 36.0 6.4 1.3 26.0

Ohio4 ................... 3.2 0.43 15.0 5.7 0.8 20.0

Oklahoma ................. 8.7 0.70 44.5 11.7 1.7 47.0

Oregon .................. 6.7 0.58 39.0 7.9 1.4 39.0

Pennsylvania ............... 3.4 0.42 18.0 4.3 0.7 13.0

Rhode Island ............... 1.6 0.29 2.0 2.9 0.9 4.0

South Carolina4 ............. 3.7 0.42 20.0 6.9 1.4 30.5

South Dakota .............. 4.5 0.41 26.0 4.8 1.1 15.5

Tennessee ................ 2.9 0.40 10.0 3.6 1.0 7.5

Texas4 ................... 13.2 0.80 51.0 15.9 1.0 51.0

Utah .................... 5.2 0.43 31.0 5.8 1.0 21.0

Vermont .................. 1.6 0.32 1.0 2.1 0.8 1.0

Virginia4 .................. 2.9 0.35 11.0 6.1 1.2 22.5

Washington4 ............... 3.2 0.38 14.0 6.2 1.2 24.0

West Virginia ............... 5.6 0.56 34.0 7.7 1.5 37.5

Wisconsin ................. 2.2 0.38 8.0 3.8 0.9 10.0

Wyoming ................. 7.4 0.58 41.0 7.5 1.4 35.5

. . . Category not applicable.

1CSHCN is children with special health care needs.

2Current Population Survey prevalence estimates and standard errors were drawn from summary tables published by the U. S. Census Bureau (U. S. Census Bureau, Housing and Household

Economic Statistics Division. Low-income uninsured children by State: 1999, 2000, and 2001. October 22, 2002. http://www.census.gov/hhes/hlthins/liuc01.html).

3Tied observations were assigned the average rank that would have been assigned without ties.

4The difference between the survey estimates of prevalence is statistically significant, p <.05.

NOTE: Poverty status is assessed at the household level in the National Survey of CSHCN and at the family level for the Current Population Survey. Prevalence estimates from the National Survey of

CSHCN are for children under 18 years of age; prevalence estimates from the Current Population Survey are for children under 19 years of age.
Series 2, No. 136 [ Page 11

responses. This may be particularly true 

for the CPS, which asks respondents 

about coverage during the preceding 

calendar year. Some analysts think that 

CPS respondents report current 

insurance coverage rather than insurance 

coverage during the preceding 

year (19–21). In 1994, several questions 

were added that asked about insurance 

coverage during the preceding week. 

The questions followed a series of 

questions that asked about coverage in 

the preceding year. The CPS 

uninsurance rates during the preceding 

week were twice the rate of those 

collected by NHIS for uninsurance 

during the preceding 30 days. The 

experimental CPS questions were 

discontinued in 1998. Researchers are 

still unclear about the reasons for the 

observed rate disparity. However, there 

seems to be general agreement that 

estimates from surveys that ask about 

current, point-in-time coverage (as did 

the National Survey of CSHCN) are 

more accurate than other estimates. 

Verification of Uninsured

Status

Prior to 2000, the CPS did not ask 

respondents to confirm their status 

regarding health insurance. If the 

respondents denied coverage for all 

types of insurance, the survey 

considered them to be uninsured. 

Experiments included in the NSAF 

found that a verification question 

lowered the estimated proportion of 

children who were uninsured, from 

about 15% to 11.9% (22). As a result of 

this research, the Annual Demographic 

Supplement of the CPS added a 

question in 2000 to verify the insurance 

status of a respondent. The addition of 

the verification question lowered rates 

of uninsurance among children under 

age 18 by over a full percentage point, 

from 13.9% to 12.6% (23). 

Although the NSAF and the CPS 

observed a dramatic decrease in the 

overall uninsurance rate by including a 

verification question, the National 

Survey of CSHCN found almost no 

change. A total of 689 respondents 

reported comprehensive insurance 

coverage as a result of the verification 

question, decreasing the overall 

uninsurance rate from 8.5% to 8.3%. 

Still, given the difficulties 

respondents have in understanding 

insurance coverage, the direct approach 

of verifying insurance coverage, rather 

than assuming lack of coverage, seems 

more prudent. This indicates that 

estimates of the uninsured population 

from the NHIS, NSAF, National Survey 

of CSHCN, and the CPS (2000 and 

beyond), which all use a verification 

question, may be more accurate. 

Other Questionnaire

Effects

The selection of a short recall 

period and the use of a verification 

question are two types of questionnaire 

design features that have been 

mentioned as potential sources of 

differences in uninsurance estimates. 

The magnitude of the effects of 

switching from one design feature to 

another is usually unclear, and it may 

differ depending on other features of the 

survey. For example, one reason for the 

more significant impact observed by the 

NSAF and CPS regarding the 

verification question could be the 

manner in which information on 

insurance status is collected. The NSAF 

first asks about insurance at the family 

level for all targeted persons in the 

family, and then assigns people to 

policies held by family members. In 

contrast, the National Survey of CSHCN 

asks about insurance at the person level. 

It is possible that the person-level 

structure of the National Survey of 

CSHCN is less conducive to initial 

response error than the family-focused 

questions of the NSAF. (For more 

discussion of this issue, see ‘‘Reporting 

Bias’’ in this report.) 

Another questionnaire attribute that 

might affect estimates of insurance 

coverage is the order of presentation of 

the various types of insurance. The 

majority of surveys ask about 

employer-sponsored insurance first, and 

this includes the National Survey of 

CSHCN and the NSAF. The U.S. 

Census Bureau conducted an experiment 

that varied the order of presentation for 

some respondents under the age of 65 

by presenting a question about Medicaid 

coverage first for half the households 

and presenting a question about 

employer-sponsored coverage first for 

the remaining households (24). The type 

of insurance presented first suffered 

from a higher rate of false-negative 

reporting than coverage types presented 

elsewhere. Because the concept of 

insurance may be cognitively demanding 

to some respondents, they may not grasp 

it until later in the series. However, 

because these respondents presumably 

do grasp the concept of insurance later 

in the series, the uninsurance rates did 

not differ as a result of changes in the 

order of presentation. Thus, while order 

of presentation may affect coverage 

estimates for specific types of insurance, 

this questionnaire attribute is unlikely to 

affect estimates of the prevalence of 

uninsured children. 

Another possible questionnaire effect 

is survey context. Prior to asking about 

health insurance, the National Survey of 

CSHCN questionnaire contained a number 

of questions related to the health of the 

children in the household and special 

health care needs that they may have. 

Questioning respondents in such detail 

about the health of their children may 

predispose them to falsely report health 

insurance to avoid the stigma of having an 

uninsured child. Therefore, response error 

may be greater for the National Survey of 

CSHCN than for surveys with less 

attention devoted to health-related issues. 

(For more discussion of this issue, see 

‘‘Context Effects’’ in this report.) 

Underestimation of

Medicaid Coverage

The number of people enrolled in 

Medicaid, as recorded in administrative 

records by the Centers for Medicare and 

Medicaid Services, is often greater than 

the number estimated by surveys of the 

population (15,17,25). For example, 

using questions similar to those used for 

the National Survey of CSHCN, a 

previous SLAITS module found that the 

prevalence of Medicaid enrollment 

among children should have been 13.8% 

to 20.5% greater than the survey-based 

estimate (25). 
Page 12 [ Series 2, No. 136

Although the administrative records 

may be incorrect, researchers have 

focused on reasons why the survey data 

may be inaccurate. For example, people 

may not report Medicaid coverage 

because of social desirability concerns 

(e.g., Medicaid may carry the stigma 

associated with welfare participation), 

lack of knowledge (e.g., respondents 

may not realize that the child was 

eligible because eligibility can vary 

from month to month), or 

misunderstanding (e.g., Medicaidmanaged care programs may be 

mistaken for private coverage). Given 

that States have increased use of 

Medicaid-managed care plans and that 

some States have enrolled Medicaideligible persons in the same insurance 

used for State employees, enrollees may 

become less certain of the nature of 

their insurance. Therefore, this Medicaid 

undercount can be expected to increase. 

In fact, the size of the CPS undercount 

of Medicaid-enrolled children under 15 

years of age grew by 3 million between 

1994 and 1998 (18). 

Surveys differ in their approach to 

‘‘correcting’’ for this undercount. For 

example, the Census Bureau adjusts 

Medicaid coverage estimates from the 

CPS by assigning Medicaid coverage to 

children who receive Supplemental 

Security Income or other government 

benefits that would also include 

automatic Medicaid eligibility (17). A 

similar adjustment is used for NSAF 

estimates of Medicaid coverage and was 

used for NHIS estimates prior to 1997. 

No such adjustment has been used for 

the National Survey of CSHCN. 

Adjustments that assign Medicaid 

coverage to reportedly uninsured 

children will reduce the estimated 

number of uninsured children in the 

population. There is evidence, however, 

to suggest that such an adjustment may 

not improve the accuracy of these 

estimates about the size of the uninsured 

population. Though people may not 

accurately report the type of insurance 

coverage they have, they may be 

generally accurate about whether they 

have coverage (26). For example, the 

1999 Minnesota Health Access Survey 

estimates of the prevalence of uninsured 

persons decreased by less than 

three-tenths of a percentage point when 

all sources of Medicaid reporting biases 

were accounted for (27). The lack of 

adjustments on the National Survey of 

CSHCN may bias estimates of Medicaid 

coverage, but the lack of adjustments 

may not have reduced the accuracy of 

the uninsurance estimates from the 

survey. 

Recoding of Verbatim

Responses

Additional survey-specific 

differences in health insurance data 

adjustments can also impact estimates of 

uninsurance. For example, the NHIS 

adjusts the raw survey responses 

concerning health insurance coverage 

using the names of the private or public 

health insurance plans that were 

provided by the respondents. This 

recoding has the greatest impact on 

estimates of private health insurance 

coverage. More than 1,000 of the nearly 

69,000 persons under 65 years of age 

reporting private health insurance in 

1998 were reclassified, with the majority 

being classified as not having insurance. 

These data adjustments increased the 

uninsurance rate for this population 

from 15.6% to 16.8% (28). It is 

generally agreed that such recoding 

improves the validity of the insurance 

estimates. Yet, most surveys do not have 

the resources to permit such careful 

adjustments. 

The National Survey of CSHCN did 

not capture the names of private or 

public health insurance plans when 

respondents identified their coverage as 

either private or public. However, for 

cases where a respondent reported 

‘‘other’’ insurance, an open-ended item 

did capture the name or type of 

insurance. At the end of the data 

collection period, verbatim responses for 

this item were reviewed, and verbatim 

responses that could be recoded to an 

existing coverage type (i.e., private 

coverage, Medicaid, SCHIP, military 

coverage, or Title V) or to uninsured 

status were coded as such. Remaining 

verbatim responses were categorized 

according to whether the respondent 

identified the coverage as 

comprehensive. Coverage that was said 

to be comprehensive conferred insured 

status to the child. If the coverage was 

not said to be comprehensive, and this 

‘‘other’’ insurance was the only 

insurance type reported, the child was 

considered to be uninsured. The 

thorough review and recoding of 

verbatim items increased the number of 

children considered to be uninsured by 

1,474 and increased the uninsured rate 

from 7.7% to 8.3%. Because the 

National Survey of CSHCN did not 

follow the NHIS procedures and did not 

look for similar misreports when 

respondents identified private or public 

health insurance directly, the estimated 

uninsurance rate from the National 

Survey of CSHCN might still be lower 

than the true rate. 

Weighting and Estimation

Random sampling error and 

nonrandom response biases can result in 

discrepancies between the characteristics 

of the survey’s sample and the 

population of interest. Sampling weights 

are adjusted so that the survey’s 

population totals for key demographic 

characteristics match totals that are 

obtained from an independent source 

such as the census or CPS. This process 

is called poststratification. 

Surveys differ in the independent 

source used for this poststratification. 

The National Survey of CSHCN 

adjusted the weights to match the 2000 

census count of children, projected to 

July 2001. The weights were further 

adjusted to match CPS estimates for 

certain demographic characteristics. In 

contrast, surveys such as the 1999 

NSAF and the 2001 NHIS adjusted their 

weights to match the 1990 census count 

of children, projected to the relevant 

time period for the survey. 

Surveys also differ in the 

demographic characteristics selected for 

this poststratification. For example, the 

NHIS adjusts for discrepancies by age, 

sex, and race/ethnicity. The NSAF adds 

home ownership (i.e., owning vs. 

renting) to the list of key demographic 

characteristics. For the National Survey 

of CSHCN, poststratification included 

several additional variables and was 

conducted in two stages. First, the 

weights for each household with 

children were adjusted to account for 
Series 2, No. 136 [ Page 13

discrepancies by household size, 

income, children’s race, and resident 

mother’s education. Second, after 

applying the household weight to each 

child and adjusting for the number of 

children in the household, the weights 

for each child were adjusted to match 

the census count stratified by age, sex, 

and race/ethnicity. The child weights 

were also adjusted to match CPS 

estimates of the population of children 

by household size, income, and mother’s 

education. 

Both stages of poststratification also 

compensated for the potential bias that 

may exist because the National Survey 

of CSHCN, as a telephone survey, could 

not select households without telephone 

service at the time of the survey. To 

make this adjustment, the total number 

of households with children—as 

projected from the census—was split, 

with one total for telephone households 

and one total for those without 

telephones or with an interruption in 

telephone service for at least 1 week 

during the prior 12 months. The 

proportion allocated to each of these 

two groups was based on CPS data for 

households with children but without 

telephone service and National Survey 

of CSHCN data for households with 

interrupted telephone service. 

Households with interrupted 

telephone service were used in the 

weighting process because there is 

evidence to suggest that households with 

telephone service at the time of the 

survey, but with interruptions in 

telephone service during the year, are 

more similar to households with no 

telephone service at the time of the 

survey than are households with 

uninterrupted telephone service during 

the year (29–31). Therefore, 

noncoverage of households without a 

telephone can be somewhat 

compensated for by proportionately 

increasing the weights for those 

interviews that could be completed in 

households with interrupted service. In 

this way, households with interrupted 

service represent the households without 

telephone service at the time of the 

interview. 

Given that the National Survey of 

CSHCN used a different source for its 

population control totals and used a 

greater number of demographic 

characteristics during poststratification, 

the final estimates from the survey 

would not be expected to perfectly 

match estimates from other surveys of 

the same population. Moreover, because 

the characteristics are estimated from 

sample surveys, there is also no 

conclusive way to determine which 

survey has most accurately described the 

population. 

Nonresponse Bias 

As previously demonstrated, 

surveys disagree about the 

number of uninsured children. 

However, because the survey 

methodology also varies considerably 

among these surveys, it becomes unclear 

whether rates should be compared 

among surveys. The literature seems 

clear on only one thing: There is no 

consensus in the research community on 

which rate is more accurate. Therefore, 

the National Survey of CSHCN must be 

examined to determine whether 

nonrandom response biases may be 

present and whether these biases raise 

doubts about the accuracy of the 

uninsurance rate. 

Cooperation Rates by

Demographic

Characteristics

If parents whose children were 

more likely to be uninsured (e.g., 

parents in lower-income households) 

were less willing to participate in the 

National Survey of CSHCN, these 

systematic response biases would lead to 

an uninsurance rate that is lower than 

that found in other surveys. Direct 

determination of whether the survey 

sample missed children who were more 

likely to be uninsured is impossible 

because information on the individual 

characteristics of nonrespondents is not 

available. However, the characteristics 

of households in the same telephone 

exchange as nonrespondents can serve 

as a proxy for the individual 

characteristics of the nonrespondents. 

The National Survey of CSHCN 

used the GENESYS Sampling System 

(a proprietary product of Marketing 

Systems Group) to obtain several 

sample variables derived from the 1990 

census regarding demographic 

characteristics of the telephone exchange 

for each randomly generated telephone 

number. These variables included 

estimated race and ethnic composition, 

income, and educational characteristics 

for all households with that exchange. 

Using these exchange-level variables, 

analyses were performed to determine 

National Survey of CSHCN response 

rates by demographic composition at the 

telephone exchange level. 

For these analyses, telephone 

exchanges in the National Survey of 

CSHCN sample were first divided into 

quartiles by exchange-level percentage 

of each demographic characteristic of 

interest. (Quartiles were chosen to 

facilitate comparisons within the 

sample.) Cooperation rates were 

calculated by quartile. The cooperation 

rate is the proportion of all telephone 

numbers (excluding those resolved as 

out-of-scope, such as businesses) that 

resulted in a completed screener or 

interview, as applicable. Unweighted 

cooperation rates were analyzed at the 

telephone exchange level by the 

exchange-level percentages of 

African-American and Hispanic persons, 

by the exchange-level percentage of 

households having an annual income 

below $25,000, and by the exchangelevel percentage of persons with a 

4-year college degree. Results are 

summarized in table H. 

A negative relationship was found 

between the exchange-level percentages 

of African-American and Hispanic 

persons and cooperation rates; 

households in telephone exchanges 

having a higher percentage of Hispanic 

or African-American persons were less 

likely to participate in the National 

Survey of CSHCN. Because minority 

households, particularly Hispanic 

households, were more likely to have an 

uninsured child, the differential response 

in exchanges that were expected to 

include a greater proportion of minority 

persons may have decreased the 

estimated uninsurance rate from the 

National Survey of CSHCN. 
Page 14 [ Series 2, No. 136

Table H. Cooperation rates by expected distribution of selected demographic

characteristics within telephone exchanges

Selected demographic characteristic and Unweighted household

expected distribution cooperation rate

African-American persons

0.0–0.8 percent ............................ 69.2

0.9–3.7 percent ............................ 65.3

3.8 –13.5 percent ........................... 62.9

13.6 –100.0 percent ......................... 63.1

Hispanic persons

0.0–1.2 percent ............................ 69.3

1.3–3.4 percent ............................ 66.1

3.5–11.3 percent ............................ 62.9

11.4–100.0 percent .......................... 62.2

Households with annual

income above $25,000

0.0–58.1 percent ........................... 68.8

58.2–66.4 percent ........................... 67.0

66.5–76.4 percent ........................... 64.9

76.5–100.0 percent .......................... 61.4

College graduates

0.0–11.3 percent ............................ 68.9

11.4–17.4 percent ........................... 67.2

17.5–28.1 percent ........................... 64.7

28.2–100.0 percent .......................... 61.0

NOTE: Expected distribution within each telephone exchange is based on 1990 census data.

However, a negative relationship 

was also found between the exchangelevel percentage of higher-income 

households and cooperation rates. 

Similarly, the exchange-level 

percentages of college graduates and 

cooperation rates were negatively 

correlated. That is, households in 

telephone exchanges having a higher 

percentage of higher-income households 

were less likely to participate, and 

households in telephone exchanges 

having a higher percentage of college 

graduates were less likely to participate. 

One would expect that higher levels of 

nonresponse by households with higher 

incomes and/or higher education levels 

would result in an increase (rather than 

a decrease) in the estimated uninsurance 

rate. 

The analyses of cooperation rates 

suggest that the potential for 

nonresponse bias was greater among 

minority households, higher-income 

households, and households with a 

college graduate. These three groups 

may also be underrepresented in the 

National Survey of CSHCN. Whether or 

not the latter is true is the next question 

for discussion. 

Representation of

Telephone Population

To better understand the extent to 

which the National Survey of 

CSHCN—a telephone survey—is 

representative of the U.S. population of 

children in households with telephone 

service, weighted National Survey of 

CSHCN data were compared with 

weighted NHIS data for children living 

in households with telephone service. 

The weighting and estimation 

procedures for the National Survey of 

CSHCN include a poststratification step 

that adjusts for the potential bias due to 

the exclusion of nontelephone 

households from the sample. For 

purposes of comparison with the NHIS 

telephone population, weighted, but not 

poststratified, data from the National 

Survey of CSHCN were used. 

Characteristics of the weighted, but 

not poststratified, National Survey of 

CSHCN telephone population are 

compared with those of the NHIS 

telephone population in table J. The 

telephone population described by the 

National Survey of CSHCN was more 

likely to be Hispanic (19.0% compared 

with 16.6%), but less likely to be 

non-Hispanic black (11.1% compared 

with 14.0%). In addition, the National 

Survey of CSHCN included more 

children with college-educated mothers 

(34.6% with a 4-year college degree or 

above compared with 24.8%). 

Otherwise, the two groups are 

demographically similar. 

Higher-income households, minority 

households, and households with a 

college graduate were not underrepresented in the National Survey of 

CSHCN sample. However, even if such 

demographic biases in the sample had 

been revealed, the effect of this 

differential response on the National 

Survey of CSHCN uninsurance rate 

would have been reduced during the 

National Survey of CSHCN weighting 

process. The poststratification process 

included adjustments based on 

household income, children’s race, and 

children’s ethnicity. The weighting 

process did not specifically include an 

adjustment for the presence of any 

college-educated household member. 

However, an adjustment for education of 

the sampled child’s mother was included 

and can serve as a proxy measure for 

overall education in the household. 

Representation If

Poststratification Was Not

Used

One may conclude from the 

previous discussion that the 

poststratification process was not 

necessary or that it should be limited to 

race, ethnicity, and educational 

attainment. Although the previous 

analysis provides an indication of the 

extent to which the sample of the 

National Survey of CSHCN is 

representative of the population of 

children in households with telephones, 

it does not reflect its relation to the 

overall U.S. population of 

noninstitutionalized children. Therefore, 

an additional comparison of 

demographic characteristics to those of 

population estimates from the 2002 CPS 

was performed. The results are shown in 

table K. As with the comparison 

presented in table J, the National Survey 

of CSHCN data were weighted, but not 

poststratified. 
Series 2, No. 136 [ Page 15

Table J. Composition of the population of households with children under 18 years of age and with telephone service, by selected

demographic characteristics

National Survey of CSHCN1 (2001) National Health Interview Survey (2001)

Demographic characteristic of child Percent Standard error Percent Standard error

Insurance status

Insured .............................. 91.7 0.11 89.4 0.34

Uninsured ............................. 8.3 0.11 10.6 0.34

Age

0–5 years ............................. 32.0 0.17 32.5 0.38

6–11 years ............................ 35.6 0.17 33.8 0.35

12–17 years ........................... 32.4 0.17 33.8 0.40

Sex

Female .............................. 48.6 0.18 48.8 0.34

Male ................................ 51.4 0.18 51.2 0.34

Race/ethnicity

Hispanic .............................. 19.0 0.17 16.6 0.46

Black non-Hispanic ....................... 11.1 0.11 14.0 0.48

White non-Hispanic and all others .............. 70.0 0.18 69.4 0.60

Language of interview

English .............................. 89.6 0.14 92.3 0.33

Spanish or other language .................. 10.4 0.14 7.7 0.33

Poverty status2,3

0%–49% of FPL ......................... 5.9 0.12 5.4 0.29

50%–99% of FPL ........................ 10.6 0.14 9.9 0.39

100%–149% of FPL ...................... 11.8 0.14 10.7 0.38

150%–199% of FPL ...................... 10.9 0.12 10.1 0.38

At or above 200% of FPL ................... 60.8 0.20 63.8 0.69

Maternal education

8th grade or less ........................ 4.9 0.11 5.7 0.29

Some high school ........................ 7.8 0.11 10.0 0.33

High school graduate or GED4 ................ 28.4 0.17 27.8 0.51

Some post-high school, but no college degree ...... 24.3 0.16 31.7 0.57

4-year college degree or higher ............... 34.6 0.18 24.8 0.54

1CSHCN is children with special health care needs.

2Poverty status was assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey.

3FPL is Federal poverty level.

4GED is General Educational Development high school equivalency diploma.

NOTE: To approximate the population of households with children and with telephone service from the National Survey of CSHCN, sampling weights obtained prior to poststratification were used for

this analysis.

The telephone population described 

by the National Survey of CSHCN was 

more likely than the U.S. population 

described by the CPS to be Hispanic 

were underrepresented in the National 

Survey of CSHCN sample when 

poststratification was not conducted. 

This result suggests not only that 

Bias Following

Poststratification by

Demographic

(19.0% compared with 16.3%) and less poststratification is required to produce Characteristics

likely to be non-Hispanic black (11.1% more accurate estimates of the 

compared with 14.7%). The population population, but also that As noted with the comparison 

described by the National Survey of poststratification should not be limited between the National Survey of CSHCN 

CSHCN also tended to be younger (32.4% to race, ethnicity, and educational and NHIS telephone populations, any 

were 12–17 years of age compared with attainment. As indicated in table C, effect that slight variations between the 

37.4% in the CPS), and it included a older children and children from National Survey of CSHCN telephone 

smaller proportion of households with households in the lowest income range population of children and the CPS 

children in the lowest income range (6.3% are more likely to be uninsured. population of children samples may 

with an income of $9,999 or less Uninsurance estimates calculated have on uninsurance rates should have 

compared with 10.3% in the CPS). without the appropriate adjustments to been tempered by the poststratification 

Older children and children from the sampling weights would be too low. adjustments during the National Survey 

households in the lowest income range of CSHCN weighting process. A look at 
Page 16 [ Series 2, No. 136

Table K. Composition of the population of households with children under 18 years of age by selected demographic characteristics

National Survey of CSHCN1 Current Population Survey Annual

(2001: households with telephones) Demographic Supplement (2002)

Demographic characteristic of child Percent Standard error Percent Standard error

Age

0–5 years ............................. 32.0 0.17 30.6 0.18

6–11 years ............................ 35.6 0.17 32.0 0.11

12–17 years ........................... 32.4 0.17 37.4 0.12

Sex

Female .............................. 48.6 0.18 48.8 0.30

Male ................................ 51.4 0.18 51.2 0.30

Race/ethnicity

Hispanic .............................. 19.0 0.17 16.3 0.28

Black non-Hispanic ....................... 11.1 0.11 14.7 0.24

White non-Hispanic and all others .............. 70.0 0.18 69.0 0.30

Income2

Up to $9,999 ........................... 6.3 0.11 10.3 0.16

$10,000–$19,999 ........................ 11.1 0.14 10.6 0.20

$20,000–$39,999 ........................ 23.4 0.17 22.1 0.27

$40,000–$59,999 ........................ 19.9 0.15 18.0 0.25

$60,000 and above ....................... 39.4 0.19 39.0 0.32

1CSHCN is children with special health care needs.

2Income was assessed at the household level in the National Survey of CSHCN and at the family level for the Current Population Survey.

NOTE: To approximate the population of households with children and with telephone service from the National Survey of CSHCN, sampling weights obtained prior to poststratification were used for

this analysis.

table L raises questions about whether from the March 2000 Annual proportionately increasing the weights 

the weighting process sufficiently Demographic Supplement to the CPS for those interviews that could be 

adjusted for variations in household were reweighted to be consistent with completed in households with a 

income. Table L compared the estimated the 2000 census, the proportion of telephone that had experienced an 

population demographics from the Hispanic children in the United States interruption in telephone service. In this 

weighted and poststratified National increased from approximately 16.2% to way, households with interrupted service 

Survey of CSHCN to those from the 17.1% (32). If the data from the other were used to represent households 

NHIS, NSAF, CPS, and MEPS. Despite surveys were similarly reweighted to be without telephone service at the time of 

poststratification, a greater proportion of consistent with the 2000 census, the the interview. To examine the potential 

households were still in the highest proportion of Hispanic children should effect of the nontelephone adjustment on 

income range (44.0% with an income of increase and more closely approximate the uninsurance rate, it is of interest to 

$60,000 or more compared with 28.1% the proportion estimated by the National compare uninsurance rates in continuousto 39.9% in the other surveys). The Survey of CSHCN. Nevertheless, versus interrupted-service households. This 

greater proportion of households in the because Hispanic children are more comparison showed that among 

highest income range may help explain likely to be uninsured (see table C), the households with a telephone at the time of 

the lower uninsurance rate for the greater proportion of Hispanic children the survey, telephone service interruption 

National Survey of CSHCN relative to in the population estimated by the within the past 12 months is related to 

the other surveys. National Survey of CSHCN does not uninsurance. Children in households with 

The population estimated by the help explain the lower uninsurance rate a telephone that had experienced an 

National Survey of CSHCN was also relative to the other surveys. interruption in telephone service were 

more likely to be Hispanic (17.3% more than twice as likely to be uninsured 

compared with 16.3% to 16.7% in the 

other surveys). This difference, however, 

was expected given differences in the 

Bias Following

Poststratification by

(table M). Because the weights of 

households with interrupted telephone 

service were increased to represent 

population control totals used during the 

preparation of the sampling weights. As 

Service Interruption Status households without a telephone, and 

because children in interrupted-service 

noted previously, the National Survey of The poststratification process for the households were more likely to be 

CSHCN used control totals based on the National Survey of CSHCN also uninsured, the adjustment for those 

2000 census, whereas the other surveys included an adjustment that somewhat without telephones resulted in an 

used control totals based on projections compensated for the noncoverage of increased National Survey of CSHCN 

from the 1990 census. When the data households without a telephone by uninsurance rate. 
- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - - - - -

- - -

Series 2, No. 136 [ Page 17

Table L. Percent of children under 18 years of age with selected demographic characteristics by national survey

Current

National National Population Medical

National Health Survey of Survey Annual Expenditure

Survey of Interview America’s Demographic Panel

CSHCN1 Survey Families Supplement Survey

Selected demographic characteristic (2001) (2001) (1999) (2002) (2001)

Age

0–5 years ............................. 31.9 32.7 32.2 30.6 32.7

6–11 years ............................ 34.9 33.8 34.0 32.0 33.7

12–17 years ........................... 33.2 33.5 32.8 37.4 33.7

Sex

Female .............................. 48.8 48.9 48.9 48.8 48.6

Male ................................ 51.2 51.1 51.1 51.2 51.4

Race/ethnicity

Hispanic .............................. 17.3 16.7 16.3 16.3 16.6

Black non-Hispanic ....................... 14.0 14.4 15.5 14.7 15.4

White non-Hispanic and all others .............. 68.6 68.8 68.2 69.0 68.0

Language of interview

English .............................. 90.6 92.2 94.2

Spanish or other language .................. 9.4 7.8 5.8

Income2

Up to $9,999 ........................... 5.4 6.1 9.5 10.3 2.3

$10,000–$19,999 ........................ 9.2 10.3 13.1 10.6 14.6

$20,000–$39,999 ........................ 22.0 23.3 26.1 22.1 32.9

$40,000–$59,999 ........................ 19.4 20.3 21.1 18.0 22.0

$60,000 and over ........................ 44.0 39.9 30.2 39.0 28.1

Poverty status2,3

Up to 49% of FPL ........................ 5.2 6.0 6.1

50%–99% of FPL ........................ 9.4 10.4 10.5

100%–149% of FPL ...................... 11.3 11.0 11.5

150%–199% of FPL ...................... 10.2 10.1 11.8

200% of FPL and over ..................... 63.9 62.5 60.2

Maternal education

8th grade or less ........................ 5.7 5.9 5.7

Some high school ........................ 11.3 10.6 8.1

High school graduate or GED4 ................ 32.2 28.0 29.9

Some post-high school, but no college degree ...... 28.0 31.4 31.3

4-year college degree or higher ............... 22.8 24.2 25.1

Category not available.

1CSHCN is children with special health care needs.

2Income and poverty status are assessed at the household level in the National Survey of CSHCN and at the family level for the National Health Interview Survey, National Survey of America’s

Families, and Current Population Survey.

3FPL is Federal poverty level.

4GED is General Educational Development high school equivalency diploma.

The adjustment is based on the children in each type of household can those with continuous telephone service, 

assumption that characteristics of be examined (table M). Children in these children did not have identical 

children in households without a households without telephone service or uninsurance rates. The difference in the 

telephone are more similar to children in in households that had experienced an uninsurance rates between children in 

households with interrupted telephone interruption in service in the past 12 households with no telephone service 

service in the past 12 months than to months were much more likely to have and children in households with 

those with continuous telephone service. an uninsured child. This examination interrupted telephone service did not 

Because the NHIS gathers data in supports the premise of the National reach the conventional level of statistical 

households without a telephone, and Survey of CSHCN adjustment. significance (p < .05), due perhaps to the 

because the NHIS asks households with Although children in households small sample sizes in the NHIS. A 

a telephone about interruptions in without telephone service were more simple comparison of the two rates, 

telephone service within the past 12 similar to children in households that however, suggests that using children 

months, NHIS uninsurance rates for experienced interrupted service than to from households with interrupted 
Page 18 [ Series 2, No. 136

Table M. Uninsurance rates for children under 18 years of age by telephone service status

National Survey of CSHCN1 (2001) National Health Interview Survey (2001)

Sample Uninsurance Standard Sample Uninsurance Standard

Household telephone service status size rate error size rate error

No telephone service at the time of the interview .......... . . . . . . . . . 936 24.4 3.15

Telephone service at the time of the interview, but an

interruption in service during the past 12 months ......... 11,323 16.8 0.69 805 17.4 1.96

Telephone service at the time of the interview, and

continuous service during the past 12 months ........... 202,734 7.2 0.11 26,571 10.4 0.34

. . . Category not applicable.

1CSHCN is children with special health care needs.

telephone service (17.4% uninsured) to 

represent children from households 

without telephone service (24.4% 

uninsured) resulted in estimated 

uninsurance rates that were still lower 

than the true rate. 

This difference in uninsurance rates 

between households with no telephone 

service and households with interrupted 

telephone service was not sufficient, 

however, to fully account for the 

difference in uninsurance rates between 

the National Survey of CSHCN and the 

other surveys. If the uninsurance rate 

from households with no telephone 

service was artificially set at the NHIS 

rate of 24.4% (rather than being 

approximated based on data from 

telephone households with interrupted 

service), the overall uninsurance rate for 

the National Survey of CSHCN would 

have increased to only 8.7%. To achieve 

an overall uninsurance rate of 11.0% 

(the NHIS rate from table B) using the 

National Survey of CSHCN estimates 

presented in table M, the rate for 

uninsured children from households with 

no telephone service would need to have 

been set at 62.6%. An actual rate at this 

level is highly unlikely. 

Reporting Bias 

Surveys collect insurance data in 

various contexts and using 

different types of questions, and 

these differences could lead parents to 

misreport health insurance coverage for 

their children. For example, a recent 

Questionnaire Design Experimental 

Research Survey by the U.S. Census 

Bureau included a component 

comparing person-level and householdlevel versions of questionnaire 

items (33). The person-level interview 

asked questions for all eligible 

household members by repeating the 

entire question for each eligible 

household member. The alternative 

household-level approach used a 

screening question to determine whether 

anyone in the household had the 

characteristic of interest and then 

followed an affirmative response with a 

question determining which household 

members had the characteristic of 

interest. For most demographic 

characteristics and for receipt of income 

from government programs, the two 

versions produced estimates without 

clear or consistent differences. There 

was some evidence, however, that the 

household-level approach increased the 

risk of underreporting of functional 

limitations, coverage by employer- or 

union-based health insurance plans, and 

asset ownership. 

For health insurance questions, 

when households included more than 

one person, the person-level approach 

produced more privately insured persons 

than did the household-level approach. 

Respondents were asked about various 

types of insurance plans (e.g., plans 

provided by employers/unions, plans 

purchased directly, plans obtained by 

nonhousehold members, Medicare, 

Medicaid, and plans provided by the 

military). Of these types, only the 

prevalence rate for employer- and 

union-based plans differed significantly 

(p < .01) by questionnaire version: 

75.1% of persons of all ages had this 

type of insurance when the person-level 

questions were asked compared with 

65.3% of persons when the householdlevel questions were asked. 

There was also a statistically 

significant difference in the overall 

uninsurance rate as constructed from the 

questions about various insurance plan 

types. With the household-level 

questions, 12.6% of persons were 

considered uninsured compared with 

6.6% using the person-level questions. 

Based on further reliability analyses, the 

authors concluded that the person-level 

approach produces more complete and 

accurate reporting for health insurance 

coverage. 

Experimental Approach

To better understand the effect of 

question design on the uninsurance rates 

from the National Survey of CSHCN 

and other surveys, a randomized 

experiment was planned and 

implemented by Abt Associates, in 

collaboration with NCHS. Using the 

SLAITS mechanism, health insurance 

questions were fielded using either a 

child-level design or a household-level 

design. The child-level design was the 

approach implemented in the National 

Survey of CSHCN. Household-level or 

family-level designs were used for the 

NSAF, CPS, and the initial health 

insurance question of the NHIS. 

Two-thirds of the sample was 

randomly assigned to the child-level 

design. Of this two-thirds, one-half was 

administered the questionnaire that was 

used for the National Survey of 

CSHCN. That is, demographic 

information was gathered on all children 

in the household, and then the CSHCN 

Screener (34) was administered for each 

child. The CSHCN Screener included 

five stem questions regarding health 

care consequences that might indicate a 

special health care need (e.g., limitation 
Series 2, No. 136 [ Page 19

in ability, need for prescription 

medication, need for special therapy). If 

a child had experienced one of the 

consequences, followup questions 

determined whether the consequence 

was due to a medical, behavioral, or 

other health condition that had lasted or 

was expected to last for 12 months or 

longer. Using these answers to 

determine the special-needs status of 

each child in the household, one child 

with special health care needs and one 

child without special health care needs 

were sampled. The questionnaire for 

sampled children with special needs 

included sections on health and 

functional status, access to care, care 

coordination, satisfaction with care, 

health insurance, adequacy of coverage, 

and the impact of the child’s special 

needs on the family. The questionnaire 

for children without a special need 

consisted only of the health insurance 

section. 

The other half of the sample 

receiving the child-level design received 

an abbreviated version of the National 

Survey of CSHCN questionnaire. 

Similar to that questionnaire, 

demographic information regarding all 

children in the household was collected. 

However, after the initial demographic 

questions, the CSHCN Screener was not 

administered. Instead, one child in the 

household was randomly sampled to 

receive the health insurance questions. 

The health insurance questions for this 

group were identical to those used for 

the National Survey of CSHCN. 

The remaining third of the sample 

was randomly assigned to the 

household-level design. These 

households were administered a 

modified version of the 1999 NSAF 

questionnaire, up to and including the 

section on health insurance. Prior to the 

questions on health insurance, this 

questionnaire asked about the medical 

care, health status, and education of the 

children in the household and included 

household demographics and a detailed 

household roster. Following the 

household roster, a target group within 

the household was randomly selected for 

further questions on health insurance. 

Where possible, the target group 

consisted of one child between birth and 

5 years of age, one child between 6 and 

17 years of age, and the children’s 

parents or guardians. For each type of 

insurance included in the questionnaire, 

an initial item asked whether any target 

group member was covered by that type 

of insurance. If an affirmative response 

was received, additional items asked 

which target group members were 

covered by the insurance type. Names of 

the policyholders were also obtained. 

The interview concluded with additional 

demographic items drawn from the 

National Survey of CSHCN 

questionnaire. 

For the latter two groups, the 

introduction to the insurance questions 

included the following statement: ‘‘I 

want to assure you that I am not selling 

anything. This is a government study on 

health care and other services in the 

State of (NAME).’’ The questionnaires 

administered to these two groups 

included few questions prior to those 

about health insurance. This wording 

was added to prevent respondents from 

misinterpreting the call as a marketing 

approach to solicit the purchase of 

health insurance. This statement did not 

appear in the National Survey of 

CSHCN questionnaire. 

Methods

Because the SLAITS program uses 

the sampling frame of the National 

Immunization Survey (NIS), it was 

necessary to identify NIS reporting areas 

that could provide a sufficient sample 

that was not already committed to the 

National Survey of CSHCN project. 

Fielding each of the experimental survey 

groups in the same NIS reporting areas 

was essential to ensure that the samples 

would be parallel. However, because of 

this restriction, the sample used for the 

experiment could not be used to produce 

national estimates. The sample was 

representative of selected NIS reporting 

areas, but levels of insurance cannot be 

projected nationally. Within the areas 

with a sufficient NIS sample, the 

telephone numbers randomly generated 

for NIS administration were randomly 

assigned to the question design 

conditions. The sample assigned to 

receive the original version of the 

National Survey of CSHCN 

questionnaire was included as part of 

the National Survey of CSHCN 

sample. 

Regardless of the question design 

condition, the respondent was the adult 

in the household who was most 

knowledgeable about the health and 

health care of the children living there. 

To reduce the potential variability 

among the test groups, no interviews 

were conducted in households where the 

parent or guardian could not complete 

the interview in English. In addition, as 

was the case in the U.S. Census Bureau 

experiment described earlier, no 

callbacks or refusal-conversion attempts 

were made because of budgetary 

constraints. At the time this experiment 

was conducted, the NIS interview 

included health insurance questions. 

Because this experiment could not be 

conducted in these households, a 

decision was made to exclude all 

NIS-eligible households (i.e., those with 

a child 19–35 months of age) from the 

experiment. 

Questionnaires were administered 

using a computer-assisted telephone 

interview (CATI) system. All 

questionnaires used in the experiment 

were programmed as modules of the 

NIS, integrating the NIS screener and 

each questionnaire into a single 

interview. Interviewers for the 

experiment received cases in the 

question design groups at random. 

Computer screens for each questionnaire 

were color-coded to alert the 

interviewers as to which design would 

be used for a particular call. Questionspecific instructions and help screens 

used for the 1999 administration of the 

NSAF were incorporated into the 

household-level questionnaire. 

A total of 138 interviewers were 

trained for the experiment. All had 

worked previously on the National 

Survey of CSHCN. The material 

covered in the training sessions included 

an overview of the project, introduction 

of CATI screens, review of questionspecific instructions and help screens, 

and a review of refusal aversion 

techniques. Special emphasis was placed 

on the importance of gaining immediate 

cooperation from respondents, because 

neither callbacks nor refusal conversion 

would be attempted for the study. 
Page 20 [ Series 2, No. 136

Table N. Disposition of the experimental sample by question design group

Child-level design

Child-level design (abbreviated Household-level

(full National Survey National Survey design

of CSHCN1 of CSHCN1 (modified NSAF2

Disposition questionnaire) questionnaire) questionnaire)

Initial telephone numbers ........................ 16,272 16,272 16,272

Residential status determined ..................... 13,620 13,805 13,732

Known households ............................ 4,980 5,005 4,979

Households screened for children ................... 4,760 4,796 4,773

Households identified as having children ............... 828 894 892

Children screened and selected for interview ............ 476 472 534

Children with a completed interview .................. 396 420 486

1CSHCN is children with special health care needs.

2NSAF is National Survey of America’s Families.

Telephone center supervisors and 

project staff extensively monitored 

interviews via remote telephone and 

computer monitoring technology. This 

formal monitoring was conducted to 

ensure that project specifications were 

followed (i.e., that introductory materials 

were properly read, that item wording 

and sequence of the questionnaires were 

followed correctly, that respondent 

questions were answered properly, and 

that any vague responses were properly 

probed). Computer monitoring also 

allowed monitors to ensure that answers 

were entered into the CATI system 

accurately. 

The number of initial telephone 

numbers, the number of telephone 

numbers where residential status was 

determined, the number of households 

identified, the number of households 

successfully screened for the presence of 

children, and the number of households 

with at least one child (excluding 

NIS-eligible households) are presented 

in table N. This table also shows the 

number of children selected for 

interview and the number of children 

for whom interviews were successfully 

completed. In the child-level design 

group that received the original 

National Survey of CSHCN 

questionnaire, a maximum of two 

interviews were possible: one for a 

randomly selected child with special 

health care needs (if present) and one 

for a randomly selected child without 

special health care needs (if present). 

In the child-level design group that 

received the abbreviated questionnaire, 

a single child was randomly selected 

from all the children in the household. 

In the household-level design group 

that received the NSAF questionnaire, 

information was obtained for one 

randomly selected child aged 5 years 

or younger (if present) and one 

randomly selected child over the age 

of 5 years (if present). 

Because health insurance 

information was not obtained for all 

children within a household, it was 

necessary to apply weights reflecting the 

differential within-household selection 

probabilities. The weighting also 

adjusted for differences in the 

proportion of Hispanics among the 

groups. The effect of the differential 

weighting was incorporated into the 

hypothesis tests by reducing the overall 

sample size in proportion to the variance 

of the weights. 

Results

The first analysis examined 

differences in insurance rates between 

the two child-level design groups. 

Because the prevalence of uninsured 

children was the same for the two 

groups, they were pooled to increase 

power for comparisons with the 

household-level design group. Details 

about this comparison are provided in 

the section titled ‘‘Context Effects.’’ 

The hypothesis of the experiment 

was that child-level questions about 

insurance would lead to higher rates of 

reported coverage than would 

household-level items. That is, it was 

anticipated that the combined child-level 

design group would produce a lower 

uninsurance rate than the householdlevel design group. Table O compares 

the rates of uninsurance and the 

prevalence of various insurance types 

for the two question design groups. 

The results of this experiment 

suggest that the child-level design of the 

National Survey of CSHCN health 

insurance items will yield lower 

uninsurance rates than the householdlevel and family-level designs 

incorporated into the other national 

surveys. The child-level insurance 

questions produced an uninsurance rate 

of 4.8%, whereas the household-level 

insurance questions produced an 

uninsurance rate of 7.0%. This 

difference approached the conventional 

level of statistical significance, based on 

Fisher’s Exact Test and a single-tailed 

distribution. (A one-sided significance 

Table O. Insurance coverage rates by question design group

Question design group

One-sided

Child- Household- Fisher’s

level level Exact

Type of insurance coverage design design Test

Private insurance ................. 78.1 72.4 0.013

Medicaid ...................... 17.4 14.4 0.090

SCHIP1 ....................... 6.6 7.8 0.761

Uninsured ...................... 4.8 7.0 0.061

1SCHIP is State Children’s Health Insurance Program.

NOTES: Data are from a randomized experiment with 1,302 completed interviews. Respondents could report more than one type

of insurance. Thus, the total of the reported coverage rates exceeds 100%.
Series 2, No. 136 [ Page 21

test was appropriate because the 

directionality of the difference was 

hypothesized prior to data collection 

and analysis, based on the previous 

U.S. Census Bureau results.) 

Differences in the expected direction 

were also found for private insurance 

and Medicaid. 

The data collected during this 

experiment do not permit an analysis of 

the relative accuracy of the insurance 

coverage reported. The reliability results 

reported by the U.S. Census Bureau and 

the cognitive simplicity of the 

person-level questions provide reasons 

to believe that the child-level approach 

used for the National Survey of CSHCN 

yields more accurate data. However, 

social desirability demands may be 

greater for the child-level approach. 

That is, the desire to present oneself in a 

favorable light (to ‘‘say the right thing’’) 

may predispose parents of uninsured 

children to erroneously report health 

insurance coverage, but these parents 

may feel less pressure to fabricate 

insurance coverage for the child when 

reporting the uninsurance status of the 

entire family rather than the uninsurance 

status of just the individual child. This 

hypothesis would suggest that the 

child-level approach used for the 

National Survey of CSHCN can yield 

less accurate data, partially offsetting the 

aforementioned benefits of a child-level 

approach. Further research on question 

design in surveys that assess health 

insurance is clearly needed. 

Tests for Other Biases 

Aside from nonresponse bias, 

inadequate weight adjustments, 

and reporting bias due to 

question wording, other potential 

reasons for the difference in the 

uninsurance rate between the National 

Survey of CSHCN and other surveys 

include interviewer effects, respondent 

fatigue, and the context of the questions 

within the questionnaire. This section 

details several analyses performed to 

examine the effect of each of these 

potential reasons on the National Survey 

of CSHCN uninsurance rate. 

Table P. Uninsurance rates by interviewer tenure at Abt Associates and by tenure on the

National Survey of Children with Special Health Care Needs at the time of interview

completion

Sample Uninsurance Standard

Tenure size rate error

Overall experience

1 month or less ......................... 25,846 6.31 0.31

2–3 months ............................ 41,944 7.08 0.26

4–6 months ............................ 35,847 8.12 0.33

7–12 months ........................... 38,935 7.84 0.30

13 months or more ....................... 68,650 9.86 0.25

National Survey of CSHCN experience

1 month or less ......................... 32,912 6.71 0.29

2–3 months ............................ 52,880 8.00 0.26

4–6 months ............................ 42,917 8.40 0.29

7–12 months ........................... 40,533 8.30 0.29

13 months or more ....................... 17,325 9.41 0.51

NOTE: CSHCN is children with special health care needs.

Interviewer Effects collection period for the study spanned 

approximately 18 months and 

Something specific to the National interviewers were recruited and trained 

Survey of CSHCN interviewers or for the study throughout data collection, 

interviewing setting may have interviewers accrued varying levels of 

contributed to the observed difference in experience working on the study. To 

insurance reporting between the determine whether interviewer 

National Survey of CSHCN and other experience might be correlated with 

surveys. To address the possibility that rates of uninsurance, rates were 

interviewers affected insurance examined by interviewer tenure at Abt 

reporting, analyses of interviewer Associates and by tenure on the 

training, interviewer experience, and National Survey of CSHCN at the time 

telephone center location were of interview completion (table P). A 

undertaken. general increase in uninsurance rates by 

The National Survey of CSHCN interviewer experience was observed, 

interviewer training program was both overall and specifically on the 

reviewed to determine whether this National Survey of CSHCN. However, 

training could have encouraged there are confounding reasons 

interviewers to record insurance explaining such an increase. For 

coverage when none was reported or to example, experienced interviewers were 

persuade parents of uninsured children more likely to serve as refusal 

to falsely report insurance coverage. The converters. Children whose parents had 

importance of the health insurance refused the interview at some point, but 

component of the study was strongly had been converted, were slightly more 

stressed in training, but the emphasis likely to be uninsured (8.3% compared 

was on accurate recording of answers to with 8.0%). Experienced interviewers 

help determine accurate coverage also tended to staff daytime shifts; 

estimates. In addition, to ensure that children whose parents had been 

training regarding the collection of interviewed before 5:00 p.m. were more 

insurance data was similar to that likely to be uninsured (9.2% compared 

performed for outside surveys, training with 7.5%). 

materials and question-specific A logistic regression analysis was 

instructions for the NSAF were obtained undertaken to determine whether the 

and incorporated into National Survey uninsurance rate was related to 

of CSHCN training sessions. interviewer experience. The explanatory 

Interviewers with varying degrees variables included interviewer 

of prior interviewing experience were experience, geographic location (i.e., 

trained for the National Survey of census division) of sampled household, 

CSHCN. In addition, because the data total number of calling attempts for the 
Page 22 [ Series 2, No. 136

case, time of day of the call resulting in 

a completed interview, race and 

ethnicity of interviewer, race and 

ethnicity of the child, interviewer-child 

race match status, special-needs status of 

the child, whether the household 

included a child with special health care 

needs, poverty level of the child’s 

household, and maternal education. 

Adjusting for all other factors, the 

insurance status of the child was not 

predicted by interviewer experience 

(table Q). 

Abt Associates employs telephone 

centers in Amherst, Massachusetts; 

Chicago, Illinois; and Las Vegas, 

Nevada. Any differences among the 

telephone centers are minimized by a 

case delivery system that delivers the 

next available case to the next available 

interviewer, regardless of the location of 

the telephone center. However, the 

telephone centers differ in the 

percentage of bilingual interviewers, the 

percentage of refusal converters, and the 

hours of operation. Therefore, variation 

in the uninsurance rates for interviews 

administered in Amherst, Chicago, and 

Las Vegas was expected. In particular, 

because the majority of bilingual 

interviewing and refusal-conversion 

activities occur in the Chicago telephone 

center, it is not surprising that the 

highest uninsurance rate was observed at 

that location (table R). Yet, as table Q 

illustrates, the association between the 

uninsurance rate and telephone center 

location was not statistically significant 

after adjusting for the other factors in 

the model. Although there are 

differences in uninsurance rates across 

telephone center locations, the 

regression analysis showed that they 

could be explained by other factors. 

Table Q. Maximum-likelihood estimates and adjusted odds ratios from logistic regression predicting uninsurance rate from household,

child, and interviewer characteristics

Logistic Adjusted 95%

Characteristic regression coefficient odds ratio confidence limits

Household poverty status1

0%–49% of FPL ................................ 1.66 5.25 2(4.36, 6.31)

50%–99% of FPL ............................... 1.73 5.65 2

(4.78, 6.67)

100%–132% of FPL ............................. 1.73 5.64 2

(4.73, 6.73)

133%–149% of FPL ............................. 1.59 4.89 2

(3.98, 6.00)

150%–184% of FPL ............................. 1.53 4.61 2

(3.89, 5.47)

185%–199% of FPL ............................. 1.31 3.69 2

(2.91, 4.69)

200%–299% of FPL ............................. 1.05 2.85 2

(2.45, 3.30)

300%–399% of FPL ............................. 0.46 1.58 2

(1.32, 1.88)

At or above 400% of FPL .......................... . . . 1.00 . . .

Education of respondent

8th grade or less ............................... 0.43 1.54 2

(1.29, 1.84)

Some high school ............................... 0.31 1.36 2

(1.20, 1.54)

High school graduate ............................. . . . 1.00 . . .

Some post-high school, but no degree .................. –0.15 0.86 2

(0.78, 0.95)

4-year college degree or higher ...................... –0.50 0.61 2

(0.54, 0.68)

Race/ethnicity of child

Hispanic ..................................... 0.17 1.18 2

(1.05, 1.33)

Black non-Hispanic .............................. –0.36 0.70 2

(0.61, 0.80)

Other, missing ................................. 0.22 1.24 2

(1.03, 1.50)

White non-Hispanic .............................. . . . 1.00 . . .

Race/ethnicity of interviewer

Hispanic ..................................... 0.31 1.36 2

(1.13, 1.64)

Black, non-Hispanic .............................. –0.01 1.00 (0.87, 1.14)

Other, missing ................................. 0.09 1.09 (0.86, 1.37)

White, non-Hispanic ............................. . . . 1.00 . . .

Interviewer-child race match status

Match ...................................... . . . 1.00 . . .

Non-match ................................... 0.01 1.01 (0.90, 1.13)

Insufficient information ............................ 0.13 1.13 (0.84, 1.53)

Child has special health care needs

No ........................................ 0.26 1.29 2

(1.15, 1.45)

Yes ........................................ . . . 1.00 . . .

Presence of at least one child with

special health care needs in household

No ........................................ 0.70 2.01 2

(1.66, 2.44)

Yes ........................................ . . . 1.00 . . .

See footnotes at end of table.
Series 2, No. 136 [ Page 23

Respondent Fatigue for the National Survey of CSHCN 

interview), NIS-eligible respondents 

point higher than the rate for 

NIS-ineligible children. 

The NIS interview was administered might be more fatigued by the time that To further examine the effect of 

prior to the National Survey of CSHCN they reported insurance status for their administration time on uninsurance 

interview in NIS-eligible households. child, leading to misreporting. To rates, rates by interview length were 

Therefore, these households were determine whether administration of the examined. (In these analyses, the 

generally on the telephone considerably NIS interview had an effect on interview length did not include the time 

longer than were NIS-ineligible insurance reporting, rates of uninsurance to administer the NIS interview in 

households before providing insurance for NIS-eligible and NIS-ineligible NIS-eligible households, and the 

information. Because of the children were compared (table S). The interview length did not include the time 

administration time of the combined uninsurance rate for NIS-eligible to administer the Low-Income 

interview (approximately 20 minutes for children was just over 1 percentage Uninsured Supplement for eligible 

the NIS interview and 10 to 15 minutes 

Table Q. Maximum-likelihood estimates and adjusted odds ratios from logistic regression predicting uninsurance rate from household,

child, and interviewer characteristics–Con.

Logistic Adjusted 95%

Characteristic regression coefficient odds ratio confidence limits

Time of call resulting in completed interview

Before noon .................................. –0.04 0.96 (0.82, 1.12)

Noon–5 pm ................................... –0.02 0.99 (0.88, 1.10)

5–7 pm ..................................... –0.11 0.90 (0.80, 1.00)

7–9 pm ..................................... . . . 1.00 . . .

Number of call attempts

1–2 calls .................................... 0.00 1.00 (0.91, 1.11)

3–5 calls .................................... 0.05 1.05 (0.95, 1.17)

6 calls or more ................................. . . . 1.00 . . .

Length of interview3

5 minutes or less ............................... –1.14 0.32 2(0.27, 0.38)

6–10 minutes .................................. –0.51 0.60 2

(0.54, 0.67)

11–20 minutes ................................. . . . 1.00 . . .

21–30 minutes ................................. 0.03 1.03 (0.86, 1.24)

31–45 minutes ................................. 0.17 1.19 (0.92, 1.53)

46–60 minutes ................................. 0.13 1.14 (0.62, 2.09)

61 minutes or more .............................. 0.18 1.20 (0.40, 3.58)

Interviewer experience (overall)

1 month or less ................................ –0.06 0.97 (0.84, 1.07)

2–3 months ................................... 0.05 1.05 (0.92, 1.20)

4–6 months ................................... 0.12 1.13 (0.99, 1.29)

7–12 months .................................. 0.06 1.06 (0.94, 1.21)

13 months or more .............................. . . . 1.00 . . .

U.S. Census division

New England .................................. –0.29 0.75 2

(0.62, 0.91)

Middle Atlantic ................................. –0.03 0.97 (0.81, 1.17)

South Atlantic ................................. 0.36 1.43 2

(1.22, 1.67)

East South Central .............................. 0.16 1.17 (0.99, 1.38)

West South Central .............................. 0.87 2.38 2

(2.02, 2.82)

East North Central .............................. 0.05 1.05 (0.89, 1.25)

West North Central .............................. –0.02 0.98 (0.83, 1.15)

Mountain .................................... 0.55 1.73 2

(1.50, 2.00)

Pacific ...................................... . . . 1.00 . . .

Telephone center location

Amherst, Massachusetts ........................... 0.09 1.09 (0.91, 1.31)

Chicago, Illinois ................................ 0.03 1.03 (0.92, 1.15)

Las Vegas, Nevada .............................. . . . 1.00 . . .

. . . Category not applicable.

1FPL is Federal poverty level.

2This confidence interval does not include 1.00 and indicates a statistically significant odds ratio, p < .05.

3The length of the interview did not include the time to administer the NIS interview in NIS-eligible households and did not include the time to administer the Low-Income Uninsured Supplement for

eligible children.

NOTE: Sample size for this analysis was 170,522 due to missing data, particularly for household poverty status.
Page 24 [ Series 2, No. 136

Table R. Uninsurance rates by telephone center location

Sample Uninsurance Standard

Location size rate error

Amherst, Massachusetts ............... 12,261 6.56 0.46

Chicago, Illinois .................... 119,360 9.23 0.19

Las Vegas, Nevada .................. 83,533 7.11 0.19

Table S. Uninsurance rates by National Immunization Survey eligibility

Eligibility of Sample Uninsurance Standard

child’s household size rate error

Eligible .......................... 24,135 9.25 0.42

Ineligible ......................... 191,026 8.13 0.14

NOTE: Households were eligible for the National Immunization Survey if they included a child 19–35 months of age.

children.) Rates of uninsurance generally 

increased as the administration time 

increased (table T). However, longer 

interviews were more likely in 

households with lower income and 

where the respondent was less educated 

(table U). Such respondents may not be 

familiar with research and survey 

questions and are, therefore, likely to 

take longer to respond overall. Thus, 

children from households with lower 

income and less education are more 

likely to be uninsured and are more 

likely to be the subject of a longer 

interview. In other words, the 

relationship between uninsurance and 

interview length may be due to income 

and education. 

To determine whether the 

uninsurance rate was directly related to 

interview length, the logistic regression 

presented in table Q included interview 

length, poverty level of the child’s 

household, and maternal education as 

predictors of the uninsurance rate. The 

regression analysis showed that the 

relationship between uninsurance and 

interview length could not be explained 

entirely by other factors. Shorter 

interviews still predicted lower 

uninsurance rates. Children without 

special needs were more likely to be the 

subject of a shorter interview. However, 

there are two reasons why this fact 

alone does not explain the relationship 

between uninsurance and interview 

length. First, the effect of a child’s 

special-needs status was controlled by 

including the status as a separate 

predictor variable in the model. Second, 

children without special needs had 

higher (rather than lower) uninsurance 

rates (see table Q and ‘‘Appendix II’’). 

These analyses demonstrated that 

longer administration time for the 

National Survey of CSHCN was related 

to greater uninsurance rates. For most 

children without special needs, the 

National Survey of CSHCN asked about 

health insurance coverage early in the 

interview, following only the initial 

demographics and the CSHCN Screener. 

Table T. Uninsurance rates by length of National Survey of Children with Special Health

Care Needs interview

Sample Uninsurance Standard

Length of interview1 size rate error

5 minutes or less ................... 31,277 3.56 0.20

6–10 minutes ...................... 94,761 7.32 0.17

11–20 minutes ..................... 41,411 13.19 0.37

21–30 minutes2 .................... 34,090 7.48 0.37

31–45 minutes ..................... 8,117 10.96 0.82

46–60 minutes ..................... 807 11.72 2.33

61 minutes or more .................. 156 25.34 7.67

1The length of the interview did not include the time to administer the National Immunization Survey (NIS) interview in NIS-eligible

households and did not include the time to administer the Low-Income Uninsured Supplement for eligible children.

2The majority of interviews in this category pertain to children with special health care needs. Because children with special health

care needs were more likely to be insured than children without special needs, the lower uninsurance rate in this category was

expected.

In contrast, the NHIS, NSAF, and CPS 

include the health insurance coverage 

questions later in the interview. 

Consistent with the results just 

described, the surveys with greater 

length prior to the insurance questions 

also yield greater uninsurance rates. 

The relationship between interview 

length and reported uninsurance rates 

suggests that respondent fatigue may 

contribute to higher uninsurance rates. 

Assuming that respondent fatigue is 

more likely in the NHIS, NSAF, and 

CPS relative to the National Survey of 

CSHCN (especially for children without 

special needs), this fatigue could 

contribute to the observed differences in 

the uninsurance rate among the surveys. 

Assuming further that fatigue results in 

misreporting of insurance coverage, one 

could hypothesize that respondents’ 

answers about their children’s health 

insurance coverage on the National 

Survey of CSHCN are more accurate 

than the answers reported on other 

surveys. Further research on the 

potential influence of respondent fatigue 

on uninsurance rates is needed to 

confirm or refute these hypotheses. 

Context Effects

The demands of a particular 

situation can lead respondents to give 

socially desirable responses rather than 

accurate responses. As noted previously, 

this desire to present oneself in a 

favorable light may predispose parents 

of uninsured children to erroneously 

report health insurance coverage. These 

demands may be especially strong if the 

health insurance questions follow a 

battery of other health-related questions. 

In the National Survey of CSHCN, 

health insurance questions for most 

children without special needs were 

administered after the CSHCN Screener, 

a set of five questions about 

consequences that children may 

experience due to special health care 

needs (34). For children with special 

needs, the health insurance questions 

followed questions about health status, 

care utilization, unmet needs, and 

satisfaction with care. In contrast, health 

insurance questions in the CPS follow 

questions about employment and 

income. 
Series 2, No. 136 [ Page 25

To examine whether context might Table U. Length of National Survey of Children with Special Health Care Needs interview by

influence reports of uninsurance, an household income and respondent education

abbreviated version of the National 

Survey of CSHCN questionnaire was 

used for half the sample that received 

the child-level health insurance 

questions in the randomized experiment 

described earlier. The abbreviated 

version omitted the CSHCN Screener 

prior to the health insurance questions. 

In other words, the health-related 

context was removed. As reported 

earlier, the uninsurance rate did not 

differ by the context of the insurance 

questions. Observed differences in the 

reported levels of private insurance, 

Medicaid, and SCHIP were not 

statistically significant (table W). 

Therefore, the context of the insurance 

questions within the questionnaire did 

not appear to be related to insurance 

reporting. 

Summary and 

Conclusions 

The National Survey of CSHCN 

revealed that 8.3% of children 

under 18 years of age were 

uninsured, a rate that is significantly 

lower than the uninsurance rates from 

other surveys. For example, the rate was 

one-quarter lower than the NHIS 

estimate (11.0%) and one-third lower 

than the NSAF estimate (12.6%). 

Considerable analyses and investigations 

have examined the difference between 

the National Survey of CSHCN 

uninsurance rate and the uninsurance 

rates calculated from other surveys. 

These have included an examination of 

potential nonresponse bias, effects 

Mean

interview

Sample length Standard

Demographic characteristic size (in minutes) deviation

Household income

Up to $9,999 ...................... 10,327 15.5 10.49

$10,000–$19,999 ................... 18,770 14.6 10.16

$20,000–$39,999 ................... 44,635 13.3 9.28

$40,000–$59,999 ................... 39,715 12.4 8.60

$60,000 and above .................. 72,764 12.3 8.18

Education of respondent

8th grade or less ................... 5,570 15.4 10.82

Some high school ................... 13,496 14.9 10.26

High school graduate ................. 58,761 12.7 8.78

Some post-high school, but no degree ...... 57,756 13.2 8.99

4-year college degree or higher .......... 79,024 12.3 8.43

the National Survey of CSHCN 

telephone population with the NHIS 

telephone population and with 

population estimates from the CPS 

revealed that the National Survey of 

CSHCN described a telephone 

population with a slightly larger 

proportion of Hispanic children, younger 

children, children from households with 

college-educated members, and children 

from households with higher incomes. 

Any effect that these response biases 

might have had on the National Survey 

of CSHCN uninsurance rate should have 

been reduced in the survey’s 

poststratification process, which 

included controls based on ethnicity, 

age, mother’s education, and household 

income. 

Following poststratification, the 

National Survey of CSHCN still 

described a population with a slightly 

larger proportion of children from 

households with higher incomes relative 

to the populations described by other 

surveys. Differences in the estimated 

size of the Hispanic population of 

children also remained following 

poststratification (though it should be 

noted that the weighted data from the 

National Survey of CSHCN more 

closely approximate the 2000 census 

results). These demographic differences 

would have opposing effects on the 

uninsurance rate, suggesting that these 

demographic differences were unlikely 

to account for much of the discrepancy 

between the uninsurance rates. 

A more likely explanation for the 

discrepancy comes from the results of a 

randomized experiment that varied the 

design of the health insurance questions. 

For items about private health insurance, 

household-level questions that first ask 

if anyone in the household is insured 

produced lower rates of coverage than 

did child-level questions that ask if each 

individual was insured. When this 

Table W. Insurance coverage rates by context of health insurance questions

arising from the survey’s weighting and 

estimation process, respondent and 

interviewer effects, and question design. 

Telephone exchange-level analyses 

using National Survey of CSHCN 

cooperation rates suggested that 

households were less likely to respond 

to the survey when they resided in 

geographic areas with a higher 

concentration of Hispanic and 

African-American persons, collegeeducated persons, and higher-income 

households. However, comparisons of 

Context

Abbreviated

Full National National

Survey Survey of Two-sided

of CSHCN1 CSHCN1 Fisher’s

Type of insurance coverage questionnaire questionnaire Exact Test

Private insurance ................. 77.1 78.8 0.613

Medicaid ...................... 16.2 18.7 0.357

SCHIP2 ....................... 7.6 5.6 0.148

Uninsured ...................... 4.8 4.8 1.000

1CSHCN is children with special health care needs.

2SCHIP is State Children’s Health Insurance Program.

NOTES: Data are from a randomized experiment with 1,302 completed interviews. Respondents could report more than one type

of insurance. Thus, the total of the reported coverage rates exceeds 100%.
Page 26 [ Series 2, No. 136

difference was added to the smaller 

differences for other types of insurance, 

the uninsurance rate differed by 

2.2 percentage points. That is, the 

uninsurance rate from child-level 

questions was 31% lower than the rate 

from household-level questions. The 

U.S. Census Bureau found substantially 

similar results for persons of all ages 

living in multiperson households: The 

uninsurance rate from person-level 

questions was 48% lower than the rate 

from household-level questions (33). 

Such great differences explain much of 

the discrepancy between the rate of 

uninsured children for the National 

Survey of CSHCN (with its child-level 

questions) and the rate for other surveys 

(with their household-level and 

family-level questions). 

A key question remains 

unanswered: Which health insurance 

coverage estimates are the most 

accurate? As a telephone survey, the 

National Survey of CSHCN requires 

complex statistical adjustments to 

account for households without 

telephones and to best approximate the 

size of the uninsured population. It 

would ordinarily be folly to presume 

that these adjustments yield more 

accurate estimates than do surveys that 

directly interview households without 

telephones, especially when evidence 

from the NHIS shows that children in 

households without telephones may be 

more likely to be uninsured than 

other children (including children in 

households with interruption in 

telephone service). However, the 

analyses in this report demonstrated 

that the bias from these statistical 

adjustments was relatively small 

(only four-tenths of a percentage 

point). 

This report also described several 

reasons why the data collected in the 

National Survey of CSHCN could be 

less prone to reporting errors than data 

from other national surveys. For 

example, the literature indicates that 

surveys asking about current point-intime coverage and including a 

verification question to clarify lack of 

coverage are more likely to obtain 

accurate estimates of uninsurance. The 

National Survey of CSHCN included 

both of these features. More accurate 

estimates of uninsurance may also be 

obtained from the National Survey of 

CSHCN because its brevity—for 

children without special needs, in 

particular—reduced the likelihood of 

respondent fatigue. 

Despite these suggestions that 

uninsurance estimates derived from the 

National Survey of CSHCN could be 

more accurate than those generated from 

other national surveys, a definitive 

conclusion regarding the relative 

accuracy of the uninsurance rates is not 

possible. Research on the relative 

accuracy of survey-based uninsurance 

rates requires a reliable external 

determination of a child’s insurance 

status, which was not available for the 

children whose parents participated in 

the National Survey of CSHCN. Until 

research is conducted using an external 

standard with the sampling frames and 

questionnaire designs of the National 

Survey of CSHCN and the other 

national surveys, this key question will 

remain unanswered. 

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Care Needs Chartbook. Rockville, MD: 

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2001. October 22, 2002. (http:// 

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et al. Adjustments for non-telephone 

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Page 28 [ Series 2, No. 136

Appendix I.

Program Names Used

for Medicaid and

SCHIP Questions

For questions regarding the 

Medicaid and the State Children’s 

Health Insurance Program 

(SCHIP), the State-specific program 

names for each type of coverage were 

included in the question text, in case 

respondents recognized the State 

program name but not the national 

program affiliation. These program 

names are shown in table I. 

States could be divided into three 

classes depending on how they named 

the created or expanded programs that 

use Title XXI funds. In 2000, 29 States 

had distinct Medicaid and SCHIP 

programs and used different names for 

their SCHIP programs than for their 

Medicaid programs. For seven States 

and the District of Columbia, the SCHIP 

program was an expansion of the 

Medicaid program, but was given a 

name that differed from the original 

Medicaid program in that State. The 

remaining 14 States did not have a 

SCHIP program, used the same (or 

substantially similar) name for both the 

SCHIP and Medicaid programs, or used 

Title XXI funds to expand the Medicaid 

program without giving it a new name. 

The use of State-specific program 

names was based on this classification. 

For States that either did not have a 

SCHIP program or had a SCHIP 

program with the same name as its 

Medicaid program, questions about the 

SCHIP program were not asked. For 

States that named their Medicaid 

expansion programs differently from 

their original Medicaid programs, the 

name of the Medicaid expansion 

program was used for questions 

regarding SCHIP. For all other States, 

the name of the Medicaid program was 

used for questions regarding Medicaid, 

and the name of the SCHIP program 

was used for questions regarding the 

SCHIP program. The classification of 

each State and the names used in the 

Medicaid and SCHIP questions are 

included in table I. 

Because the names of Medicaidexpansion programs were used for 

questions regarding SCHIP in seven 

States and the District of Columbia, 

survey analysts may find it difficult to 

distinguish between Medicaid and 

SCHIP in these States. One possible 

approach is to take account of responses 

to the SCHIP questions when 

characterizing Medicaid in these States. 

This is the approach used by researchers 

at The Urban Institute (13). 

Alternatively, analysts may choose to 

avoid the Medicaid/SCHIP distinction 

by only reporting on ‘‘public’’ insurance. 

This approach has been used for this 

report. 
Series 2, No. 136 [ Page 29

Table I. State-specific insurance program names used for questions about Medicaid and the State Children’s Health Insurance Program

State Category1 Name used with Medicaid questions Name used with SCHIP2 questions

Alabama .................. A Patient 1st Program ALL Kids

Alaska ................... B None Denali KidCare

Arizona .................. A AHCCCS KidsCare

Arkansas ................. B ConnectCare ARKids First

California ................. A Medi-Cal Healthy Families Program

Colorado ................. A Medicaid’s Baby Care/Kids Care Program, Child Health Plan Plus

Colorado Access, or the Primary Care

Physician Program

Connecticut ................ C The HUSKY Plan . . .

Delaware ................. A Diamond State Health Plan Delaware Healthy Children Program

District of Columbia ........... B Medical Assistance Program DC Healthy Families

Florida ................... A None Florida KidCare, which includes Healthy Kids and

Medi-Kids

Georgia .................. A Georgia Better Health Care Program PeachCare for Kids

Hawaii ................... D Hawaii-QUEST . . .

Idaho .................... B Healthy Connections Children’s Health Insurance Program (CHIP)

Illinois ................... A None KidCare

Indiana .................. C The Hoosier Healthwise program . . .

Iowa .................... A MediPASS HAWK-I (Healthy and Well Kids in Iowa)

Kansas .................. A HealthConnect Kansas, or PrimeCare Kansas HealthWave

Kentucky ................. A Passport, Kentucky Health Select, or KENPAC Kentucky Children’s Health Insurance Program

(K-CHIP)

Louisiana ................. B CommunityCARE program Louisiana Children’s Health Insurance Program

(La-CHIP)

Maine ................... A PrimeCare Cub Care

Maryland ................. D Medical Assistance Program, or HealthChoice . . .

Massachusetts .............. C MassHealth . . .

Michigan ................. A Medical Assistance Program MI-Child

Minnesota ................. D Medical Assistance . . .

Mississippi ................ A HealthMACS Mississippi Health Benefits Program, which includes

CHIP, the Children’s Health Insurance Program

Missouri .................. D MC-Plus For Kids . . .

Montana .................. A Passport to Health program Montana Child Health Insurance Plan (CHIP)

Nebraska ................. B Medical Assistance Program, or the Nebraska Kids Connection

Health Connection program

Nevada .................. A None Nevada Check Up

New Hampshire ............. A Healthy Kids Gold Healthy Kids Silver

New Jersey ................ A New Jersey Care 2000 New Jersey KidCare

New Mexico ............... B SALUD! New MexiKids

New York ................. A None Child Health Plus, or CH Plus

North Carolina .............. A Carolina ACCESS, or Healthcare Connection North Carolina Health Choice for Children

North Dakota ............... A None Healthy Steps Children’s Health Insurance Plan

Ohio .................... D Healthy Start . . .

Oklahoma ................. D SoonerCare or SoonerCare Choice . . .

Oregon .................. A None Oregon Health Plan, which includes the Oregon

Children’s Health Insurance Program

Pennsylvania ............... A None Pennsylvania Children’s Health Insurance Program

(PaCHIP)

Rhode Island ............... D RIte Care . . .

South Carolina .............. D Partners for Healthy Children program . . .

South Dakota .............. D The PRIME program, or the Child Health ...

Insurance Program

Tennessee ................ D TennCare . . .

Texas ................... A State of Texas Access Reform program, or STAR TexCare Partnership, which includes the Texas

program Children’s Health Insurance Program

Utah .................... A None Utah Children’s Health Insurance Program (CHIP)

Vermont .................. C Dr. Dynasaur . . .

Virginia .................. A Medallion, or the Options program Virginia Children’s Medical Security Insurance Plan

Washington ................ A Healthy Options, or Basic Health Plus Washington State’s Children’s Health Insurance

Program

West Virginia ............... A West Virginia Physician Assured Access System, West Virginia Children’s Health Insurance Program

or the Mountain Health Trust program

Wisconsin ................. B None BadgerCare

Wyoming ................. A None Wyoming KidCare

. . . Category not applicable. No SCHIP questions were asked in this State.

1States in category A had distinct Medicaid and SCHIP programs and used different names for their SCHIP programs than for their Medicaid programs. For States in category B, the SCHIP program

was an expansion of the Medicaid program, but was given a name that differed from the original Medicaid program in that State. The name of the Medicaid expansion program was used with SCHIP

questions. States in category C used the same (or substantially similar) name for both the SCHIP and Medicaid program. States in category D did not have SCHIP program or used Title XXI funds to

expand the Medicaid program without giving it a new name. For States in categories C and D, no SCHIP questions were asked.

2SCHIP is State Children’s Health Insurance Program.
Page 30 [ Series 2, No. 136

Appendix II. 

Health Insurance 

Coverage Estimates 

This appendix presents weighted 

estimates of insurance coverage 

by type from the National Survey 

of CSHCN, followed by a summary of 

uninsurance rates by key demographic 

characteristics. Estimates of insured and 

uninsured status were based on 

information from all coverage-related 

questionnaire items. A child was 

considered to be insured if any type of 

comprehensive coverage was reported. If 

no coverage was reported or if the 

coverage reported was not 

comprehensive, the child was considered 

to be uninsured. 

Tables II–IX show the percentages 

weighted to represent children 0–17 

years of age in each State by 

special-needs status. Standard errors and 

hypothesis tests using data from the 

National Survey of CSHCN were 

conducted using SUDAAN, which 

accounts for the complex sample design 

of the survey. 

Insurance Coverage

Estimates by Type of

Insurance

Estimates for the type of insurance 

coverage are limited to public, private, 

and other comprehensive insurance. 

Public insurance included Medicaid, 

SCHIP, Title V, and any other public 

insurance reported as ‘‘other’’ coverage. 

Private insurance includes employmentbased coverage, union-based coverage, 

military insurance, and insurance 

purchased directly. Other comprehensive 

insurance includes insurance reported as 

‘‘other’’ coverage that was said to be 

comprehensive, but could not be 

definitively classified as either public or 

private. This category does not include 

insurance that only covers dental care, 

vision, or accident care. It also does not 

include health insurance plans 

specifically for American Indians and 

Alaska Natives. Children whose 

insurance only covers dental care, 

vision, or accident care, and children 

who only had Indian Health Service 

coverage were considered uninsured. 

The overall estimated insurance rate 

from the National Survey of CSHCN is 

91.7%. Most of these insured children 

had private health insurance only 

(75.6% of the insured children, which is 

69.3% of all children). Estimated State 

insurance rates ranged from 82.6% in 

Texas to 97.2% in Rhode Island and are 

presented by type of insurance in 

table II. Standard errors for the 

insurance rates are presented in table III. 

Tables IV–VII present the State-specific 

insurance estimates and standard errors 

by type of insurance for children with 

and without special needs. 

Uninsurance Estimates by

Key Demographic

Characteristics

To establish insured status, 

respondents were asked about various 

types of coverage. For each item, the 

respondent indicated whether the 

sampled child had that coverage. For a 

child to be considered uninsured, a 

negative response for every question 

was required. Alternatively, a child 

could also be considered uninsured if 

the type of coverage was not reported to 

be comprehensive (e.g., if the 

respondent indicated that the insurance 

did not cover doctor visits and hospital 

stays) or was not considered to be 

comprehensive (e.g., single-service 

plans). 

Children without special health care 

needs were more likely to be uninsured 

than were CSHCN. Nationally, the 

estimated uninsurance rate for children 

without special needs was 8.7%, 

compared with a rate of 5.2% for 

children with special needs. This 

difference was statistically significant, 

p < .001. Similarly, for 31 States, the 

estimated uninsurance rate for children 

without special needs was higher than 

for CSHCN, p < .05. Table VIII presents 

the results of State-specific analyses 

testing the statistical significance of 

observed differences between the 

estimated uninsurance rates for children 

with and without special needs. 

Uninsurance rates by other key 

demographic characteristics from the 

National Survey of CSHCN are 

summarized in table IX, and they are 

presented separately for children with 

and without special health care needs. 

Trends in uninsurance rates among 

demographic groups matched 

expectations based on historical data 

from other studies. For example, 

uninsurance rates were lower for 

younger children, for children living in 

households with higher incomes, and for 

children whose mothers have more 

education. Hispanic children and 

children in non-English-speaking 

households were more likely to be 

uninsured than were non-Hispanic 

children or children in English-speaking 

households. 
Series 2, No. 136 [ Page 31

Table II. Percent of children under 18 years of age by type of health insurance coverage and State: United States, 2001

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 69.3 16.8 5.1 0.5 8.3

Alabama .............................. 66.5 20.8 5.1 0.2 7.4

Alaska ............................... 63.6 17.3 6.0 0.4 12.6

Arizona .............................. 66.1 16.4 3.8 0.7 13.0

Arkansas ............................. 62.4 22.2 4.0 0.3 11.1

California ............................. 65.1 19.5 5.3 0.6 9.5

Colorado ............................. 76.5 10.3 2.5 0.5 10.2

Connecticut ............................ 79.2 12.2 4.8 0.6 3.2

Delaware ............................. 69.7 17.9 6.6 0.3 5.5

District of Columbia ....................... 52.8 28.5 12.8 0.2 5.7

Florida ............................... 63.2 19.7 4.9 0.5 11.7

Georgia .............................. 65.4 20.8 5.8 0.3 7.7

Hawaii ............................... 78.1 11.1 6.3 0.7 3.7

Idaho ................................ 66.0 17.2 4.4 0.6 12.0

Illinois ............................... 73.9 14.4 3.5 0.5 7.6

Indiana .............................. 74.4 14.0 5.3 0.2 6.1

Iowa ................................ 78.6 10.2 5.1 0.5 5.7

Kansas .............................. 76.2 11.8 4.1 0.5 7.4

Kentucky ............................. 68.9 19.9 4.5 0.2 6.5

Louisiana ............................. 56.9 22.9 5.8 0.6 13.9

Maine ............................... 71.0 16.3 5.2 0.1 7.4

Maryland ............................. 80.0 10.6 4.7 0.6 4.1

Massachusetts .......................... 71.1 18.2 6.6 0.6 3.6

Michigan ............................. 75.5 13.1 5.3 0.1 5.9

Minnesota ............................. 79.7 10.3 4.4 0.5 5.1

Mississippi ............................ 60.6 24.5 5.7 0.5 8.8

Missouri .............................. 73.0 18.0 5.0 0.3 3.7

Montana .............................. 61.8 17.4 4.2 0.8 15.7

Nebraska ............................. 73.9 15.7 5.1 0.3 5.0

Nevada .............................. 72.0 10.4 3.9 0.3 13.5

New Hampshire ......................... 75.9 13.3 3.9 0.3 6.6

New Jersey ............................ 75.5 11.8 5.3 0.4 7.0

New Mexico ........................... 50.4 30.3 6.1 0.3 12.9

New York ............................. 66.0 21.3 7.7 0.3 4.7

North Carolina .......................... 67.3 19.3 5.0 0.3 8.1

North Dakota ........................... 74.3 13.4 3.8 0.6 8.0

Ohio ................................ 75.5 14.4 5.3 0.4 4.5

Oklahoma ............................. 61.6 20.0 4.4 0.5 13.5

Oregon .............................. 71.2 13.4 5.3 0.6 9.5

Pennsylvania ........................... 73.1 13.0 6.4 1.3 6.3

Rhode Island ........................... 73.5 16.9 5.5 1.4 2.8

South Carolina .......................... 65.3 20.5 8.0 0.2 6.0

South Dakota .......................... 73.6 13.5 4.9 0.5 7.5

Tennessee ............................ 67.0 21.0 6.9 0.3 4.9

Texas ............................... 61.6 17.3 3.3 0.4 17.4

Utah ................................ 79.9 8.5 3.0 0.4 8.2

Vermont .............................. 60.2 23.6 12.0 0.6 3.7

Virginia .............................. 81.4 9.4 4.0 0.4 4.9

Washington ............................ 70.1 18.0 5.8 0.6 5.6

West Virginia ........................... 58.5 27.4 5.5 0.4 8.2

Wisconsin ............................. 81.5 9.7 4.1 0.4 4.3

Wyoming ............................. 70.4 13.9 3.6 0.6 11.5
Page 32 [ Series 2, No. 136

Table III. Standard errors for the percent of children under 18 years of age by type of health insurance coverage and State

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 0.21 0.17 0.10 0.03 0.13

Alabama .............................. 1.02 0.91 0.46 0.08 0.54

Alaska ............................... 0.93 0.74 0.50 0.12 0.64

Arizona .............................. 1.01 0.82 0.43 0.18 0.69

Arkansas ............................. 1.05 0.93 0.43 0.15 0.69

California ............................. 0.93 0.78 0.45 0.13 0.57

Colorado ............................. 0.86 0.64 0.28 0.14 0.59

Connecticut ............................ 0.85 0.70 0.46 0.14 0.36

Delaware ............................. 1.08 0.94 0.59 0.14 0.51

District of Columbia ....................... 1.12 1.04 0.83 0.08 0.51

Florida ............................... 1.03 0.86 0.44 0.11 0.70

Georgia .............................. 1.05 0.94 0.53 0.15 0.57

Hawaii ............................... 0.88 0.68 0.49 0.19 0.39

Idaho ................................ 0.98 0.79 0.40 0.13 0.70

Illinois ............................... 1.03 0.87 0.38 0.15 0.63

Indiana .............................. 0.97 0.77 0.52 0.10 0.53

Iowa ................................ 0.81 0.61 0.42 0.12 0.46

Kansas .............................. 0.93 0.72 0.44 0.14 0.56

Kentucky ............................. 0.98 0.84 0.40 0.06 0.51

Louisiana ............................. 1.16 1.01 0.54 0.20 0.91

Maine ............................... 0.97 0.80 0.45 0.06 0.56

Maryland ............................. 0.90 0.69 0.49 0.17 0.41

Massachusetts .......................... 1.11 0.96 0.63 0.21 0.45

Michigan ............................. 0.98 0.79 0.48 0.07 0.56

Minnesota ............................. 0.94 0.73 0.48 0.15 0.52

Mississippi ............................ 1.09 1.00 0.50 0.14 0.64

Missouri .............................. 0.92 0.81 0.44 0.10 0.38

Montana .............................. 1.00 0.84 0.41 0.19 0.75

Nebraska ............................. 0.91 0.75 0.47 0.12 0.44

Nevada .............................. 0.88 0.61 0.37 0.10 0.68

New Hampshire ......................... 1.02 0.83 0.42 0.12 0.61

New Jersey ............................ 0.92 0.70 0.48 0.12 0.55

New Mexico ........................... 1.10 1.03 0.52 0.10 0.83

New York ............................. 0.93 0.80 0.53 0.09 0.43

North Carolina .......................... 1.07 0.95 0.49 0.11 0.61

North Dakota ........................... 0.97 0.83 0.38 0.16 0.57

Ohio ................................ 0.98 0.82 0.50 0.18 0.45

Oklahoma ............................. 1.12 0.99 0.49 0.11 0.77

Oregon .............................. 0.99 0.77 0.48 0.15 0.67

Pennsylvania ........................... 0.89 0.67 0.46 0.27 0.51

Rhode Island ........................... 1.00 0.87 0.49 0.25 0.36

South Carolina .......................... 1.03 0.89 0.60 0.08 0.48

South Dakota .......................... 0.89 0.73 0.44 0.11 0.52

Tennessee ............................ 1.01 0.89 0.53 0.09 0.46

Texas ............................... 1.00 0.76 0.35 0.14 0.81

Utah ................................ 0.76 0.52 0.32 0.11 0.51

Vermont .............................. 1.10 0.97 0.74 0.17 0.47

Virginia .............................. 0.85 0.63 0.46 0.13 0.44

Washington ............................ 0.93 0.76 0.50 0.15 0.46

West Virginia ........................... 1.15 1.10 0.53 0.13 0.62

Wisconsin ............................. 0.84 0.64 0.38 0.15 0.45

Wyoming ............................. 0.93 0.72 0.36 0.14 0.64

NOTE: These standard errors are associated with the estimates in table II.
Series 2, No. 136 [ Page 33

Table IV. Percent of children under 18 years of age with special health care needs by type of health insurance coverage and State:

United States, 2001

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 64.7 21.7 8.1 0.4 5.2

Alabama .............................. 58.0 30.6 7.0 0.3 4.2

Alaska ............................... 56.1 23.5 11.6 0.5 8.4

Arizona .............................. 67.2 20.5 6.4 0.8 5.1

Arkansas ............................. 50.7 36.0 7.0 0.1 6.2

California ............................. 71.9 16.5 6.8 0.5 4.3

Colorado ............................. 76.7 13.7 5.3 – 4.3

Connecticut ............................ 73.9 17.0 6.2 0.9 2.0

Delaware ............................. 60.5 21.8 14.3 0.8 2.7

District of Columbia ....................... 42.6 33.2 18.6 0.0 5.6

Florida ............................... 55.0 30.2 7.6 0.4 6.9

Georgia .............................. 59.9 28.7 8.1 0.1 3.3

Hawaii ............................... 70.7 15.0 9.9 2.1 2.3

Idaho ................................ 55.2 27.4 10.7 0.5 6.1

Illinois ............................... 72.2 18.1 4.5 1.0 4.2

Indiana .............................. 65.0 19.3 11.0 – 4.8

Iowa ................................ 66.4 19.5 8.8 1.0 4.3

Kansas .............................. 70.5 16.8 8.0 0.3 4.4

Kentucky ............................. 59.5 29.0 6.7 0.2 4.6

Louisiana ............................. 46.0 33.6 12.2 0.1 8.1

Maine ............................... 58.3 26.1 10.8 0.1 4.9

Maryland ............................. 77.4 12.8 6.7 0.4 2.7

Massachusetts .......................... 62.0 24.0 11.9 – 2.1

Michigan ............................. 70.1 17.0 8.7 0.2 4.0

Minnesota ............................. 71.4 13.4 10.7 0.2 4.4

Mississippi ............................ 48.8 34.6 9.6 0.4 6.7

Missouri .............................. 64.9 23.9 8.0 0.2 3.1

Montana .............................. 51.4 27.2 8.2 1.1 12.1

Nebraska ............................. 62.5 24.3 9.4 0.2 3.6

Nevada .............................. 66.8 18.1 7.1 0.5 7.6

New Hampshire ......................... 65.7 21.8 6.5 0.1 5.9

New Jersey ............................ 72.1 13.2 9.3 0.1 5.2

New Mexico ........................... 46.4 38.2 6.5 0.1 8.8

New York ............................. 59.4 28.4 7.7 0.2 4.2

North Carolina .......................... 59.9 27.2 7.1 – 5.9

North Dakota ........................... 62.9 22.7 9.6 0.1 4.7

Ohio ................................ 67.0 19.9 8.8 0.6 3.7

Oklahoma ............................. 57.8 27.1 5.9 0.3 8.9

Oregon .............................. 69.3 15.0 9.2 0.3 6.3

Pennsylvania ........................... 59.4 20.6 13.8 1.4 4.9

Rhode Island ........................... 63.8 23.2 9.4 1.4 2.3

South Carolina .......................... 54.8 25.8 14.8 0.2 4.5

South Dakota .......................... 65.3 20.8 8.8 0.1 5.0

Tennessee ............................ 60.5 26.4 9.9 0.2 3.0

Texas ............................... 65.6 18.4 4.0 – 12.0

Utah ................................ 74.5 12.0 8.0 0.3 5.2

Vermont .............................. 46.3 30.0 20.1 0.6 3.0

Virginia .............................. 78.0 10.4 7.2 0.4 3.9

Washington ............................ 63.7 23.6 7.6 0.1 5.0

West Virginia ........................... 42.1 41.9 7.5 0.2 8.4

Wisconsin ............................. 72.0 15.4 10.1 0.1 2.4

Wyoming ............................. 60.1 22.5 7.3 0.9 9.2

– Quantity zero.

0.0 Quantity more than zero but less than 0.05.
Page 34 [ Series 2, No. 136

Table V. Standard errors for the percent of children under 18 years of age with special health care needs by type of health insurance

coverage and State

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 0.46 0.41 0.25 0.06 0.21

Alabama .............................. 2.33 2.28 1.16 0.19 0.89

Alaska ............................... 2.25 1.89 1.62 0.34 1.19

Arizona .............................. 2.52 2.35 1.09 0.51 1.13

Arkansas ............................. 2.32 2.31 1.17 0.06 1.31

California ............................. 2.20 1.89 1.24 0.27 0.78

Colorado ............................. 2.00 1.65 1.23 . . . 0.74

Connecticut ............................ 2.01 1.76 1.12 0.40 0.62

Delaware ............................. 2.42 2.22 1.83 0.62 0.57

District of Columbia ....................... 2.42 2.45 2.28 0.03 1.21

Florida ............................... 2.49 2.48 1.28 0.24 1.18

Georgia .............................. 2.51 2.46 1.38 0.05 0.72

Hawaii ............................... 2.43 1.89 1.64 0.90 0.81

Idaho ................................ 2.40 2.34 1.46 0.36 1.09

Illinois ............................... 2.35 2.11 0.97 0.67 0.90

Indiana .............................. 2.38 1.99 1.78 . . . 0.98

Iowa ................................ 2.11 1.78 1.20 0.43 1.13

Kansas .............................. 2.21 1.84 1.45 0.17 1.02

Kentucky ............................. 2.21 2.10 1.08 0.15 0.84

Louisiana ............................. 2.35 2.47 1.72 0.11 1.49

Maine ............................... 2.13 1.95 1.35 0.06 0.95

Maryland ............................. 2.00 1.77 1.01 0.25 0.67

Massachusetts .......................... 2.56 2.25 2.05 . . . 0.63

Michigan ............................. 2.19 1.90 1.30 0.14 0.87

Minnesota ............................. 2.36 1.88 1.70 0.11 1.00

Mississippi ............................ 2.56 2.51 1.73 0.29 1.54

Missouri .............................. 1.75 1.56 1.13 0.09 0.73

Montana .............................. 2.24 2.07 1.32 0.40 1.60

Nebraska ............................. 2.36 2.21 1.47 0.18 0.91

Nevada .............................. 2.34 2.10 1.20 0.35 1.27

New Hampshire ......................... 2.38 2.27 1.00 0.10 1.24

New Jersey ............................ 2.32 1.70 1.59 0.06 1.29

New Mexico ........................... 2.49 2.61 1.06 0.05 1.73

New York ............................. 2.30 2.22 1.16 0.14 0.91

North Carolina .......................... 2.31 2.18 1.25 . . . 1.11

North Dakota ........................... 2.36 2.28 1.36 0.14 0.94

Ohio ................................ 2.20 1.95 1.29 0.56 0.84

Oklahoma ............................. 2.53 2.40 1.29 0.18 1.39

Oregon .............................. 2.13 1.67 1.35 0.16 1.09

Pennsylvania ........................... 2.29 2.00 1.65 0.47 0.88

Rhode Island ........................... 2.19 1.96 1.39 0.54 0.65

South Carolina .......................... 2.30 2.11 1.75 0.24 0.94

South Dakota .......................... 2.25 2.08 1.19 0.07 0.95

Tennessee ............................ 2.25 2.11 1.39 0.14 0.74

Texas ............................... 2.30 1.91 0.90 . . . 1.66

Utah ................................ 2.07 1.61 1.38 0.29 0.93

Vermont .............................. 2.34 2.21 1.87 0.27 1.03

Virginia .............................. 1.92 1.42 1.29 0.27 0.81

Washington ............................ 2.10 1.92 1.02 0.11 1.00

West Virginia ........................... 2.39 2.62 1.31 0.14 1.43

Wisconsin ............................. 2.09 1.69 1.50 0.10 0.67

Wyoming ............................. 2.16 1.89 1.00 0.37 1.28

. . . Category not applicable.

NOTE: These standard errors are associated with the estimates in table IV.
Series 2, No. 136 [ Page 35

Table VI. Percent of children under 18 years of age without special health care needs by type of health insurance coverage and State:

United States, 2001

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 70.0 16.1 4.7 0.5 8.7

Alabama .............................. 67.8 19.2 4.8 0.2 7.9

Alaska ............................... 64.5 16.6 5.4 0.4 13.1

Arizona .............................. 66.0 15.9 3.5 0.7 14.0

Arkansas ............................. 64.3 19.9 3.5 0.4 11.9

California ............................. 64.3 19.8 5.2 0.6 10.1

Colorado ............................. 76.5 9.8 2.2 0.6 10.9

Connecticut ............................ 80.0 11.4 4.6 0.6 3.4

Delaware ............................. 71.4 17.2 5.2 0.3 6.0

District of Columbia ....................... 54.4 27.7 11.9 0.3 5.7

Florida ............................... 64.4 18.1 4.5 0.5 12.4

Georgia .............................. 66.2 19.7 5.5 0.3 8.4

Hawaii ............................... 79.0 10.7 5.9 0.5 3.9

Idaho ................................ 67.4 15.8 3.5 0.6 12.7

Illinois ............................... 74.2 13.9 3.4 0.5 8.1

Indiana .............................. 75.9 13.1 4.4 0.3 6.3

Iowa ................................ 80.3 8.9 4.5 0.5 5.8

Kansas .............................. 77.2 10.9 3.5 0.5 7.9

Kentucky ............................. 70.7 18.2 4.1 0.2 6.8

Louisiana ............................. 58.9 20.9 4.6 0.6 15.0

Maine ............................... 73.3 14.5 4.2 0.2 7.9

Maryland ............................. 80.4 10.2 4.4 0.7 4.4

Massachusetts .......................... 72.6 17.2 5.7 0.7 3.8

Michigan ............................. 76.4 12.5 4.7 0.1 6.2

Minnesota ............................. 80.9 9.9 3.5 0.6 5.2

Mississippi ............................ 62.3 23.0 5.1 0.5 9.1

Missouri .............................. 74.4 17.0 4.5 0.4 3.8

Montana .............................. 63.2 16.2 3.7 0.8 16.2

Nebraska ............................. 75.6 14.4 4.5 0.4 5.2

Nevada .............................. 72.6 9.4 3.5 0.3 14.2

New Hampshire ......................... 77.7 11.8 3.5 0.3 6.7

New Jersey ............................ 76.0 11.6 4.7 0.5 7.2

New Mexico ........................... 50.9 29.3 6.0 0.4 13.5

New York ............................. 66.8 20.4 7.7 0.3 4.8

North Carolina .......................... 68.5 18.0 4.7 0.4 8.4

North Dakota ........................... 75.9 12.1 2.9 0.6 8.5

Ohio ................................ 76.8 13.5 4.7 0.4 4.6

Oklahoma ............................. 62.3 18.8 4.1 0.6 14.3

Oregon .............................. 71.5 13.1 4.7 0.6 10.0

Pennsylvania ........................... 75.2 11.8 5.3 1.3 6.5

Rhode Island ........................... 75.0 15.9 4.8 1.4 2.9

South Carolina .......................... 66.9 19.7 7.0 0.2 6.3

South Dakota .......................... 74.6 12.6 4.4 0.6 7.8

Tennessee ............................ 68.1 20.1 6.4 0.3 5.2

Texas ............................... 61.1 17.1 3.2 0.5 18.1

Utah ................................ 80.6 8.0 2.4 0.4 8.6

Vermont .............................. 62.8 22.4 10.5 0.5 3.8

Virginia .............................. 82.0 9.2 3.4 0.4 5.1

Washington ............................ 71.1 17.1 5.6 0.7 5.7

West Virginia ........................... 61.8 24.5 5.1 0.5 8.2

Wisconsin ............................. 82.9 8.8 3.2 0.5 4.6

Wyoming ............................. 71.9 12.7 3.1 0.6 11.8
Page 36 [ Series 2, No. 136

Table VII. Standard errors for the percent of children under 18 years of age without special health care needs by type of health insurance

coverage and State

Type of health insurance coverage

Private Other

and comprehensive

State Private Public public insurance Uninsured

All States ............................. 0.22 0.18 0.10 0.03 0.14

Alabama .............................. 1.04 0.91 0.47 0.09 0.60

Alaska ............................... 0.97 0.76 0.48 0.12 0.69

Arizona .............................. 1.05 0.84 0.45 0.19 0.75

Arkansas ............................. 1.10 0.93 0.46 0.17 0.75

California ............................. 0.97 0.81 0.47 0.15 0.62

Colorado ............................. 0.88 0.64 0.27 0.16 0.64

Connecticut ............................ 0.88 0.69 0.49 0.14 0.40

Delaware ............................. 1.12 0.97 0.54 0.12 0.58

District of Columbia ....................... 1.17 1.09 0.80 0.10 0.53

Florida ............................... 1.04 0.84 0.45 0.12 0.75

Georgia .............................. 1.09 0.95 0.54 0.17 0.63

Hawaii ............................... 0.88 0.70 0.49 0.16 0.42

Idaho ................................ 1.01 0.79 0.38 0.14 0.76

Illinois ............................... 1.05 0.87 0.40 0.14 0.67

Indiana .............................. 0.99 0.78 0.50 0.12 0.57

Iowa ................................ 0.82 0.60 0.43 0.12 0.49

Kansas .............................. 0.96 0.73 0.44 0.15 0.62

Kentucky ............................. 1.01 0.85 0.42 0.07 0.58

Louisiana ............................. 1.22 1.02 0.52 0.24 1.00

Maine ............................... 0.99 0.80 0.43 0.06 0.61

Maryland ............................. 0.93 0.70 0.51 0.20 0.46

Massachusetts .......................... 1.16 1.00 0.63 0.24 0.51

Michigan ............................. 1.03 0.82 0.49 0.07 0.62

Minnesota ............................. 0.96 0.75 0.45 0.17 0.54

Mississippi ............................ 1.12 1.01 0.49 0.15 0.67

Missouri .............................. 1.00 0.89 0.47 0.12 0.41

Montana .............................. 1.04 0.86 0.41 0.20 0.79

Nebraska ............................. 0.92 0.74 0.46 0.13 0.48

Nevada .............................. 0.90 0.59 0.37 0.10 0.72

New Hampshire ......................... 1.02 0.79 0.45 0.13 0.65

New Jersey ............................ 0.94 0.72 0.46 0.14 0.58

New Mexico ........................... 1.14 1.04 0.57 0.11 0.88

New York ............................. 0.95 0.80 0.55 0.10 0.46

North Carolina .......................... 1.09 0.94 0.50 0.13 0.66

North Dakota ........................... 0.96 0.79 0.35 0.18 0.62

Ohio ................................ 1.02 0.86 0.52 0.19 0.49

Oklahoma ............................. 1.17 1.01 0.49 0.13 0.84

Oregon .............................. 1.06 0.81 0.50 0.17 0.73

Pennsylvania ........................... 0.91 0.67 0.45 0.28 0.55

Rhode Island ........................... 1.02 0.88 0.50 0.26 0.37

South Carolina .......................... 1.07 0.93 0.59 0.08 0.52

South Dakota .......................... 0.92 0.72 0.45 0.13 0.56

Tennessee ............................ 1.05 0.93 0.54 0.10 0.51

Texas ............................... 1.04 0.80 0.36 0.16 0.86

Utah ................................ 0.77 0.51 0.30 0.12 0.55

Vermont .............................. 1.15 1.01 0.75 0.18 0.49

Virginia .............................. 0.89 0.68 0.44 0.14 0.49

Washington ............................ 0.98 0.79 0.54 0.18 0.50

West Virginia ........................... 1.18 1.08 0.56 0.15 0.65

Wisconsin ............................. 0.83 0.64 0.35 0.17 0.49

Wyoming ............................. 0.97 0.73 0.37 0.15 0.69

NOTE: These standard errors are associated with the estimates in table VI.
Series 2, No. 136 [ Page 37

Table VIII. Results of statistical tests to identify differences between uninsurance rates for children under 18 years of age with and without

special health care needs, by State

Uninsurance rate Uninsurance rate

for children for children

with special without special Test

health care health care statistic

State needs needs (chi-square) p value1

All States ............................. 5.2 8.7 213.2 0.00

Alabama .............................. 4.2 7.9 12.3 0.00

Alaska ............................... 8.4 13.1 13.3 0.00

Arizona .............................. 5.1 14.0 42.4 0.00

Arkansas ............................. 6.2 11.9 16.0 0.00

California ............................. 4.3 10.1 35.5 0.00

Colorado ............................. 4.3 10.9 45.8 0.00

Connecticut ............................ 2.0 3.4 4.3 0.04

Delaware ............................. 2.7 6.0 17.7 0.00

District of Columbia ....................... 5.6 5.7 0.0 0.94

Florida ............................... 6.9 12.4 18.3 0.00

Georgia .............................. 3.3 8.4 28.0 0.00

Hawaii ............................... 2.3 3.9 3.5 0.06

Idaho ................................ 6.1 12.7 27.1 0.00

Illinois ............................... 4.2 8.1 15.0 0.00

Indiana .............................. 4.8 6.3 2.2 0.14

Iowa ................................ 4.3 5.8 1.6 0.21

Kansas .............................. 4.4 7.9 9.5 0.00

Kentucky ............................. 4.6 6.8 5.0 0.03

Louisiana ............................. 8.1 15.0 17.2 0.00

Maine ............................... 4.9 7.9 8.5 0.00

Maryland ............................. 2.7 4.4 4.5 0.03

Massachusetts .......................... 2.1 3.8 4.9 0.03

Michigan ............................. 4.0 6.2 5.0 0.03

Minnesota ............................. 4.4 5.2 0.6 0.44

Mississippi ............................ 6.7 9.1 2.2 0.14

Missouri .............................. 3.1 3.8 0.8 0.36

Montana .............................. 12.1 16.2 5.9 0.02

Nebraska ............................. 3.6 5.2 2.5 0.11

Nevada .............................. 7.6 14.2 22.7 0.00

New Hampshire ......................... 5.9 6.7 0.4 0.54

New Jersey ............................ 5.2 7.2 2.3 0.13

New Mexico ........................... 8.8 13.5 6.4 0.01

New York ............................. 4.2 4.8 0.3 0.59

North Carolina .......................... 5.9 8.4 4.3 0.04

North Dakota ........................... 4.7 8.5 12.7 0.00

Ohio ................................ 3.7 4.6 1.0 0.33

Oklahoma ............................. 8.9 14.3 12.4 0.00

Oregon .............................. 6.3 10.0 9.3 0.00

Pennsylvania ........................... 4.9 6.5 2.8 0.09

Rhode Island ........................... 2.3 2.9 1.0 0.32

South Carolina .......................... 4.5 6.3 3.0 0.09

South Dakota .......................... 5.0 7.8 6.8 0.01

Tennessee ............................ 3.0 5.2 6.4 0.01

Texas ............................... 12.0 18.1 12.0 0.00

Utah ................................ 5.2 8.6 11.1 0.00

Vermont .............................. 3.0 3.8 0.7 0.41

Virginia .............................. 3.9 5.1 1.5 0.22

Washington ............................ 5.0 5.7 0.4 0.52

West Virginia ........................... 8.4 8.2 0.0 0.86

Wisconsin ............................. 2.4 4.6 8.9 0.00

Wyoming ............................. 9.2 11.8 3.6 0.06

0.0 Quantity more than zero but less than 0.05.

0.00 Quantity more than zero but less than 0.005.

1Values less than 0.05 indicate that the difference between the uninsurance rates was statistically significant. The uninsurance rate for children without special health care needs was greater than the

uninsurance rate for children with special health care needs.
Page 38 [ Series 2, No. 136

Table IX. Percent of children under 18 years of age without health insurance coverage by selected demographic characteristics and health

status: United States, 2001

Children with Children without Children with Children without

special health special health All special health special health All

Selected demographic characteristic care needs care needs children care needs care needs children

Percent uninsured Standard error of percent

Age

0–5 years ............................. 4.8 7.4 7.2 0.45 0.22 0.21

6–11 years ............................ 4.7 9.1 8.4 0.33 0.26 0.23

12–17 years ........................... 5.9 9.8 9.2 0.35 0.25 0.22

Sex

Female .............................. 5.4 8.7 8.4 0.33 0.20 0.18

Male ................................ 5.1 8.7 8.2 0.28 0.20 0.18

Race/ethnicity

Hispanic .............................. 10.1 20.0 19.2 0.90 0.56 0.53

Black non-Hispanic ....................... 5.3 7.6 7.3 0.60 0.33 0.31

White non-Hispanic and all others .............. 4.5 6.0 5.8 0.23 0.12 0.11

Language of interview

English .............................. 4.7 6.5 6.3 0.21 0.11 0.11

Spanish or other language .................. 21.0 27.9 27.5 2.22 0.85 0.83

Household income

Up to $9,999 ........................... 8.6 18.4 17.0 1.05 0.86 0.76

$10,000–$19,999 ........................ 10.2 18.9 17.7 0.88 0.63 0.58

$20,000–$39,999 ........................ 8.9 14.8 14.0 0.65 0.44 0.40

$40,000–$59,999 ........................ 4.9 7.0 6.7 0.45 0.32 0.30

$60,000 and over ........................ 2.0 2.6 2.5 0.25 0.13 0.12

Household poverty status1

Up to 49% of FPL ........................ 9.2 19.9 18.5 1.19 0.97 0.87

50%–99% of FPL ........................ 9.8 19.8 18.4 0.97 0.74 0.67

100%–149% of FPL ...................... 9.7 16.4 15.5 0.99 0.65 0.60

150%–199% of FPL ...................... 7.8 11.9 11.4 0.78 0.52 0.48

200% of FPL and over ..................... 3.0 4.0 3.8 0.22 0.12 0.11

Maternal education

8th grade or less ........................ 18.3 29.0 28.3 2.54 1.20 1.15

Some high school ........................ 7.9 17.6 16.3 0.86 0.65 0.60

High school graduate or GED2 ................ 6.0 8.6 8.3 0.40 0.22 0.21

Some post-high school, but no college degree ...... 4.6 5.7 5.5 0.39 0.20 0.19

4-year college degree or higher ............... 2.1 2.9 2.8 0.17 0.11 0.10

1FPL is Federal poverty level.

2GED is General Educational Development high school equivalency diploma.
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 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 Branch

National Center for Health Statistics

Centers for Disease Control and Prevention

3311 Toledo Road, Room 5412

Hyattsville, MD 20782

(301) 458–4636

E-mail: nchsquery@cdc.gov

Internet: www.cdc.gov/nchs
U.S. DEPARTMENT OF

HEALTH & HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

3311 Toledo Road

Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALTY FOR PRIVATE USE, $300

DHHS Publication No. (PHS) 2004-1336, Series 2, No. 136

3-0449 (1/2004)