Monitoring the
­

Nation's Health
­

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Center for Health Statistics 

SAFER • HEALTHIER • PEOPLE TM 

Vital and Health StatisticsSeries 1, Number 59 July 2017

Design and Operation of the 

National Survey of Children’s 

Health, 2011–2012
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

Bramlett MD, Blumberg SJ, Zablotsky B, et al. Design and operation of the 

National Survey of Children’s Health, 2011–2012. National Center for Health 

Statistics. Vital Health Stat 1(59). 2017.

Library of Congress Cataloging-in-Publication Data

Names: National Center for Health Statistics (U.S.), issuing body.

Title: Design and operation of the National Survey of Children's Health, 

 2011-2012.

Other titles: Vital and health statistics. Ser. 1, Programs and collection 

 procedures ; no. 59 | DHHS publication ; no. (PHS) 2017-1335. 0276-4733

Description: Hyattsville, Maryland : U.S. Department of Health and Human 

 Services, Centers for Disease Control and Prevention, National Center for 

 Health Statistics, July 2017. | Series: Vital and health statistics. 

 Series 1, Program and collection procedures ; number 59 | Series: DHHS pub 

 ; number (PHS) 2017-1335 | Includes bibliographical references.

Identifiers: LCCN 2017026807 | ISBN 0840606796 (pbk.)

Subjects: | MESH: National Survey of Children's Health (U.S.) | Child Health 

 | Health Surveys | Research Design | Infant Health | Adolescent Health | 

 United States

Classification: LCC RA407.3 | NLM W2 A N148va no.59 2017 | DDC 614.4/273--

dc23 LC record available at https://lccn.loc.gov/2017026807

For sale by the U.S. Government Printing Office

Superintendent of Documents

Mail Stop: SSOP

Washington, DC 20402–9328

Printed on acid-free paper.
Vital and Health Statistics

Series 1, Number 59

Design and Operation of the 

National Survey of Children’s 

Health, 2011–2012

Programs and Collection Procedures

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Hyattsville, Maryland 

July 2017 

DHHS Publication No. (PHS) 2017–1335
National Center for Health Statistics

Charles J. Rothwell, M.S., M.B.A., Director

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

Division of Health Interview Statistics

Marcie L. Cynamon, Director

Stephen J. Blumberg, Ph.D., Associate Director for Science
iii

Contents 

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

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

SLAITS Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

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

NIS Sampling Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

NSCH Sample Design and Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Drawing the Samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Conducting NSCH Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Computer-assisted Telephone Interviewing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

NSCH Augmentation Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Interviewer Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Training Sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Advance Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Toll-free Telephone Numbers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Selection of Respondent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Informed Consent. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Assurance of Confidentiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Selection of Sampled Child. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Finding NIS-eligible Children in NSCH Rostering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Interviews in Spanish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Interviews in Languages Other Than English or Spanish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

USVI Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Cell-phone Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Interview Length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Interview Breakoffs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Cases Pending at Close of Data Collection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Response Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Efforts to Improve Response Rates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Nonresponse Bias. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Quality Control of Interviewing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
iv

Data Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Missing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Coding of Verbatim Answers Into Question Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Edits to Protect Confidentiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Other Derived and Collapsed or Topcoded Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Dummy Variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Additional Data Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Procedures for Developing Sampling Weights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Base sampling weights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Derivation of Annual Sampling Weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Adjustment for Nonresolution of Released Telephone Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Adjustment for Incomplete CPO/M Screener . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Adjustment for Incomplete S_KIDS Screener . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Adjustment for Incomplete Age-eligibility Screener. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Adjustment for Subsampling of Children Within Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Adjustment for Nonresponse to NSCH Interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Adjustment for Households With Multiple Cell-phone Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Trimming of Extreme Weights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Adjustment for Combined Landline and Cell-phone Samples and for Noncovered Populations . . . . . . . . . . . . . . . . . 27

Poststratification of Child Interview Weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Estimation and Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Interpretation of Weighted Estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Variables Used for Variance Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Variance Estimation Using SUDAAN or Stata. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Variance Estimation for Subsets of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Weighted Frequencies, Prevalence Estimates, and Standard Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Guidelines for Data Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Further Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Appendix I. Sampling and Weighting Technical Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Appendix II. 2011–2012 National Survey of Children’s Health Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Appendix III. Summary of Key Differences Between 2007 and 2011–2012 Questionnaires. . . . . . . . . . . . . . . . . . . . 166

Appendix IV. Summary of Questionnaire Changes During Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

Appendix V. Program Names Used for Medicaid and Children’s Health Insurance Program Questions. . . . . . . . . . . . . . 172

Appendix VI. Program Names Used for Questions on Temporary Assistance for Needy Families. . . . . . . . . . . . . . . . . 175

Appendix VII. Procedures for Assigning Household Poverty Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

Appendix VIII. Letters Sent to Sampled Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Appendix IX. Disposition Code Frequencies and Response Rate Calculations. . . . . . . . . . . . . . . . . . . . . . . . . . . 197

Appendix X. Alternative Response Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202

Appendix XI. Incentive Effort. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

Appendix XII. Envelope Types Used in Incentive Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

Appendix XIII. Nonresponse Bias Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Appendix XIV. Multiple Imputation of Income and Household Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

Appendix XV. Key Prevalence Estimates and Weighted Frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
v

Text Tables

A. Augmentation sample, by state and sample type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

B. External technical expert panel members . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

C. Number of interviewers trained, by month and telephone center location . . . . . . . . . . . . . . . . . . . . . . . . . . .9

D. Number of completed interviews, by state and telephone sample type . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

E. Number and percentage of respondents, by relationship to sampled child . . . . . . . . . . . . . . . . . . . . . . . . . . 11

F. Mean and median length of National Survey of Children’s Health interview in minutes and seconds, 

by interview type, section, and National Immunization Survey eligibility: Landline sample. . . . . . . . . . . . . . . . . 13

G. Mean and median length of National Survey of Children’s Health interview in minutes and seconds, 

by interview type, section, and National Immunization Survey eligibility: Cell-phone sample . . . . . . . . . . . . . . . 14

H. Final disposition of age-eligible households where interview was not completed . . . . . . . . . . . . . . . . . . . . . . 14

J. Final disposition of 2011–2012 National Survey of Children’s Health sample . . . . . . . . . . . . . . . . . . . . . . . . 15

K. Weighted National Survey of Children’s Health completion rates, nationally and by 

sampling state: Landline sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

M. Weighted National Survey of Children’s Health completion rates, nationally and by 

sampling state: Cell-phone sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

N. National Survey of Children’s Health 2011–2012 response rates overall, nationally and by sampling state . . . . . . . . . 19

Appendix Figures

1. U.S. Department of Health and Human Services official business mailing envelope . . . . . . . . . . . . . . . . . . . . 210

2. Mailing envelope labeled Priority Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

3. Survey stages and types of nonrespondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

Appendix Tables

I. Covariates used to create nonresolution adjustment cells within sampling area, by 

census region and directory-listed status: Landline sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

II. Covariates used to create nonresponse adjustment cells for age-eligibility screener within state, by 

census region and directory-listed status: Landline sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

III. State-specific program names for Medicaid and Children’s Health Insurance Program . . . . . . . . . . . . . . . . 172

IV. State-specific program names for Temporary Assistance for Needy Families . . . . . . . . . . . . . . . . . . . . . 175

V. Year 2011 Federal Poverty Guidelines for families in the 48 contiguous states and Washington, D.C. . . . . . . . . 176

VI. Year 2011 Federal Poverty Guidelines for families in Alaska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

VII Year 2011 Federal Poverty Guidelines for families in Hawaii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

VIII. Year 2012 Federal Poverty Guidelines for families in the 48 contiguous states and Washington, D.C. . . . . . . . . 177

IX. Year 2012 Federal Poverty Guidelines for families in Alaska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178

X. Year 2012 Federal Poverty Guidelines for families in Hawaii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178

XI. Year 2011 reference table for additional income cascade questions for families in the 48 contiguous states and

Washington, D.C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

XII. Year 2011 reference table for additional income cascade questions for families in Alaska . . . . . . . . . . . . . . 180

XIII. Year 2011 reference table for additional income cascade questions for families in Hawaii . . . . . . . . . . . . . . 181

XIV. Year 2012 reference table for additional income cascade questions for families in the 48 contiguous states and

Washington, D.C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

XV. Year 2012 reference table for additional income cascade questions for families in Alaska . . . . . . . . . . . . . . 183

XVI. Year 2012 reference table for additional income cascade questions for families in Hawaii . . . . . . . . . . . . . . 184

XVII. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: All sample . . . . . . 197

XVIII. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: 

Landline sample, excluding U.S. Virgin Islands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198

XIX. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: 

Landline sample, including U.S. Virgin Islands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199

XX. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: 

Landline sample, U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

XXI. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: 

Cell-phone sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

XXII. Weighted National Survey of Children’s Health response rates, nationally and by sampling state: 

Landline sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204

XXIII. Weighted National Survey of Children’s Health response rates, nationally and by sampling state: 

Cell-phone sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
vi

XXIV. Weighted National Survey of Children’s Health response rate overall, nationally and by sampling state . . . . . . . 206

XXV. Incentive model, by telephone sample type. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

XXVI. Number of incentive-eligible cases and percentage completed, by quarter: 2011 and first quarter, 2012 . . . . . . . 209

XXVII. Number of cases and response rates, by incentive experiment group: Second quarter, 2011 . . . . . . . . . . . . . 209

XXVIII. Number of cases and response rates, by incentive experiment group: Third quarter, 2011 . . . . . . . . . . . . . . 209

XXIX. Number of cases and response rates, by incentive group: Fourth quarter, 2011 . . . . . . . . . . . . . . . . . . . . 209

XXX. Information available for both respondents and nonrespondents: Landline sample . . . . . . . . . . . . . . . . . . 213

XXXI. Key survey estimates: Dual-frame sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

XXXII. Weight variables used in nonresponse analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214

XXXIII. Response rates, by subgroup: Landline sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215

XXXIV. Comparing respondents and nonrespondents at each stage, using frame information: Landline sample . . . . . . . 216

XXXV. Observed and expected means of frame variables for respondents: Landline sample . . . . . . . . . . . . . . . . . 217

XXXVI. Estimates of nonresponse biases in key survey estimates attributable to biases in frame information:

Landline sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218

XXXVII. Comparing demographic, socioeconomic, and health estimates with benchmarks. . . . . . . . . . . . . . . . . . . 219

XXXVIII. Estimates of bias in key survey estimates attributable to biases in demographic, socioeconomic, and

health characteristics, based on comparisons with benchmark estimates: Dual-frame sample. . . . . . . . . . . . . 221

XXXIX. Comparing non-HUDIs with converted HUDIs, by sample type. . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

XL. Comparing non-HUDIs with converted HUDIs: Dual-frame sample . . . . . . . . . . . . . . . . . . . . . . . . . 222

XLI. Comparing nonrefusals with converted refusals, by sample type . . . . . . . . . . . . . . . . . . . . . . . . . . . 223

XLII. Comparing nonrefusals with converted refusals: Dual-frame sample . . . . . . . . . . . . . . . . . . . . . . . . . 224

XLIII. Comparing low-call-attempt respondents with high-call-attempt respondents, by sample type . . . . . . . . . . . . 224

XLIV. Comparing low-call-attempt respondents with high-call-attempt respondents: Dual-frame sample . . . . . . . . . . 225

XLV. Estimates of nonresponse biases in key survey estimates, based on comparing respondents with five or

more calls with all respondents: Dual-frame sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

XLVI. Estimates of survey bias in key survey variables, by method used to estimate bias . . . . . . . . . . . . . . . . . . 227

XLVII. Analysis of variance table for linear regression model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230

XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from

largest partial R-squared to smallest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

XLIX. Unweighted and weighted estimates of frequency and prevalence of children with excellent or

very good health, as assessed by National Survey of Children's Health respondent . . . . . . . . . . . . . . . . . . 244
vii

Acknowledgments

The National Survey of Children’s 

Health was sponsored and funded by 

the Maternal and Child Health Bureau 

of the Health Resources and Services 

Administration. It was conducted by 

the National Center for Health Statistics 

(NCHS) as a module of the State and 

Local Area Integrated Telephone Survey 

(SLAITS) mechanism. The SLAITS 

project director is Marcie Cynamon. 

Design, production, and analytic 

assistance for this project were provided 

by Rosa Avila, Julian Luke, and Kathleen 

S. O’Connor. The Centers for Disease 

Control and Prevention’s National 

Center for Immunization and Respiratory 

Diseases graciously permitted the use 

of the National Immunization Survey 

sampling frame for this survey.

NORC at the University of Chicago 

conducted all interviews for this project. 

Technical assistance was contributed by 

Nada Ganesh, Ph.D.; Wei Zeng, M.S.; 

Erin Raasch; and Dustin Simons. Kirk 

Wolter, Ph.D.; Kennon Copeland, Ph.D.; 

Eric Lopez; and Tiffani Balok provided 

management support.

This report was edited and produced 

by NCHS Office of Information Services, 

Information Design and Publishing Staff: 

Jane Sudol edited the report; typesetting 

was done by Kyung Park; tables were 

produced by Odell Eldridge, contractor; 

and graphics were produced by Simon 

McCann. The report’s outline and some 

text were borrowed with permission from 

earlier Vital and Health Statistics Series 

reports.

Finally, the authors extend their 

appreciation to the thousands of parents 

and other family members who were 

willing to share their stories. Their efforts 

made this project a reality.

Page 1 

Introduction

For more than a century, the 

Maternal and Child Health Bureau 

(MCHB) of the Health Resources and 

Services Administration (HRSA) and 

its predecessors have been charged with 

promoting and improving the health of 

mothers, children, and families in the 

United States. MCHB’s current mission 

is to “provide leadership, in partnership 

with key stakeholders, to improve the 

physical and mental health, safety, and 

well-being of the maternal and [child 

population] which includes all of the 

nation’s women, infants, children, 

adolescents, and their families, including 

fathers and children with special health 

care needs” (1). MCHB staff rely on 

data from population-based systems to 

evaluate how well this broad mission is 

fulfilled and to determine the impact of 

MCHB programs and activities. 

Although national data on children’s 

health and well-being indicators are 

available from numerous ongoing 

surveys, these data sets cannot be used to 

produce valid and reliable state estimates 

for all 50 states and Washington, D.C. 

(D.C.). Therefore, in 2003, MCHB 

sponsored the first National Survey of 

Children’s Health (NSCH) (2) through 

the State and Local Area Integrated 

Telephone Survey (SLAITS) program 

to create meaningful and comparable 

estimates of health and well-being across 

the 50 states and D.C. for all children. 

MCHB also sponsored the 2007 NSCH 

(3) and the 2011–2012 NSCH to continue 

monitoring the health of U.S. children. 

This methodology report documents the 

2011–2012 NSCH design and procedures. 

SLAITS Program

The SLAITS program, conducted 

by the National Center for Health 

Statistics (NCHS), is a broad-based 

surveillance system available at national, 

state, and local levels to track and 

monitor the health and well-being of 

children and adults. SLAITS surveys 

use the same sampling frame as the 

National Immunization Survey (NIS) 

and immediately follow NIS in selected 

households for efficiency and economy. 

In the course of identifying households 

with age-eligible children, NIS uses a 

random-digit-dial (RDD) sample and 

computer-assisted telephone interview 

(CATI) technology to screen more than 

1 million households each year. The 

process to identify this large number 

of households—most of which are 

ultimately age-ineligible for NIS—is an 

opportunity to administer other surveys 

on a range of health and welfare-related 

topics in an operationally seamless, costeffective, and statistically sound manner. 

Using the NIS sampling frame reduces 

the expense of developing a separate 

sampling frame and screening the sample 

for eligible households.

SLAITS surveys, also called 

modules, vary in content, duration, 

Design and Operation of the 

National Survey of Children’s 

Health, 2011–2012

by Matthew D. Bramlett, Ph.D., Stephen J. Blumberg, Ph.D., and 

Benjamin Zablotsky, Ph.D., National Center for Health Statistics; and 

Jacquelyn M. George, A. Elizabeth Ormson, M.S., Alicia M. Frasier, 

M.P.H., Danielle M. Vsetecka, M.A., Kim L. Williams, M.S., Benjamin J. 

Skalland, M.S., Heather M. Morrison, M.A., Kathleen B. Santos, M.S., 

Steven Pedlow, M.S., and Fang Wang, M.S., NORC at the University of 

Chicago

Objectives

This report presents the 

development, plan, and operation 

of the 2011–2012 National Survey 

of Children’s Health, a module of 

the State and Local Area Integrated 

Telephone Survey, conducted by 

the National Center for Health 

Statistics. Funding was provided 

by the Maternal and Child Health 

Bureau, Health Resources and 

Services Administration. The survey 

was designed to produce national 

and state prevalence estimates of 

the physical and emotional health 

of children aged 0–17 years, as well 

as factors that may relate to child 

well-being including medical homes, 

family interactions, parental health, 

school and after-school experiences, 

and neighborhood characteristics.

Methods

A random-digit-dial sample of 

households with children under 

age 18 years, comprising both 

landline and cell- phone numbers, 

was constructed for each of the 

50 states and District of Columbia. 

Households were screened for 

children who lived or stayed in the 

household. If one or more children 

were identified, the interview was 

conducted for one randomly selected 

child. Respondents were parents or 

guardians familiar with the children’s 

health and health care. An additional 

sample was fielded in the U.S. Virgin 

Islands (USVI).

Results 

Excluding USVI, 847,881 

households were screened from 

February 2011 through June 2012. 

Of these households, 187,422 

reported age-eligible children living or 

staying in the household. Interviews 

regarding 95,677 eligible children 

were completed, including 31,972 

from cell-phone interviews. The 

weighted overall Council of American 

Survey Research Organizations or 

CASRO rate for interviews was 38.2% 

for landline sample, 15.5% for cellphone sample, and 23.0% overall. 

Keywords: child health services • 

child well-being • family functioning • 

physical and emotional health 

Abstract
Page 2  Series 1, No. 59

and sample size based on the research 

needs of their sponsors. Sponsors work 

with NCHS to establish parameters 

including questionnaire design, sample 

size, number of completions, and other 

requirements. Since 2005, NORC at the 

University of Chicago has administered 

all aspects of SLAITS data collection 

operations. The staff at NORC program 

and test the CATI instrument, recruit 

and train interviewers who complete 

the targeted number of interviews, 

and prepare data files and related 

documentation.

Background

MCHB works to eliminate health 

barriers and disparities; improve the 

health infrastructure and systems of 

care; assure quality care; and acquire 

the best available evidence to develop 

and promote guidelines and practices 

for communities, states, and the nation. 

Findings from the 2011–2012 NSCH 

support these goals and provide an 

objective basis for federal and state 

program planning and evaluation efforts, 

especially the MCHB strategic plan goals 

and national performance measures. 

More information on MCHB is available 

from: http://mchb.hrsa.gov/.

To support these efforts, NSCH 

content is intentionally broad and 

addresses a variety of physical, 

emotional, and behavioral health 

indicators and measures of children’s 

health experiences with the health 

care system. The survey includes an 

extensive battery of questions about the 

family such as parental health, stress 

and coping, and family activities, and 

it assesses the respondent’s perceptions 

of the child’s neighborhood. No other 

survey provides the breadth and depth 

of information about children, families, 

and neighborhoods with sample sizes 

sufficient to produce comparable state 

estimates. 

NSCH data have a variety of uses 

for different stakeholders. For example, 

MCHB and state maternal and child 

health agencies can use these data to 

better characterize children’s health 

status, understand their families and 

communities, and identify the challenges 

they face in navigating the health 

care system. Federal and state Title V 

programs can use these data to plan 

and evaluate programs (4). Researchers 

and public policy analysts at state and 

federal levels can study the prevalence 

of uninsured children, the relationship 

of family health to children’s health, and 

the effect of state programs on children’s 

health and well-being. Finally, these 

data also provide baseline estimates 

for numerous Healthy People 2020 

objectives (5).

Sample Design

The 2011–2012 NSCH used a statelevel sample design that included landline 

telephone and cell-phone samples to 

address potential coverage bias. In 

2011, 38.1% of all children aged 0–17 

years lived in wireless-only households 

(6) and would not be included in the

traditional RDD sample. Research has

found that wireless-only households

were significantly different from landline

households; for example, adults in

wireless-only households tended to be

renters, were more likely to be nonHispanic, and were more likely to live

below the federal poverty level (FPL).

The targeted number of completed 

interviews in each state and D.C. was 

1,800, with at least 600 from cellphone interviews. Both the landline and 

cell-phone samples took advantage of 

the fact that NIS screening preceded a 

case’s being screened and interviewed 

for NSCH; that is, these cases were 

already known to be households with 

children prior to being called for NSCH. 

Telephone numbers were initially 

selected from the telephone numbers 

randomly generated for the NIS screening 

effort. Therefore, procedures to draw the 

NIS sample were the first steps to draw 

the NSCH sample. However, additional 

sample cases were needed to achieve the 

targeted number of completed interviews 

in certain states for the landline sample, 

and in all states and D.C. for the 

cell-phone sample. In these cases, an 

augmentation sample was drawn for 

administering only the NSCH interview. 

A separate landline RDD sample was 

also fielded for the U.S. Virgin Islands 

(USVI) during calendar Quarter 3, 2011. 

Because a cell-phone sample frame was 

not available for USVI at the time of 

fielding, a cell-phone sample was not 

fielded there. 

The following two sections describe 

the basic NIS sample design and serve as 

a nontechnical description of the NSCH 

sample design and allocation procedures. 

Appendix I includes a more technical 

description of the sample design and 

weighting procedures. Further detail on 

the NIS sample design is available from: 

https://www.cdc.gov/vaccines/imzmanagers/nis/about.html. 

NIS Sampling Plan

NIS, conducted by the Centers 

for Disease Control and Prevention 

(CDC), was established to monitor 

vaccination levels of children within 

states and local areas. The estimation 

areas were nonoverlapping and cover the 

United States and USVI. In effect, NIS 

conducted a separate survey in each 

estimation area each quarter. The target 

number of completed interviews in each 

estimation area reflected the goal of 

obtaining an equal, effective number of 

children with adequate provider data in 

each estimation area. Thus, the national 

target for the total number of completed 

interviews was the sum of the targeted 

number of completed interviews in each 

estimation area. If necessary, the target 

for an estimation area in a quarter was 

adjusted to compensate for any shortfall 

or excess in previous quarters. 

NIS consisted of two components: a 

survey of very young children (NIS–

Child) and a separate survey of teenagers 

(NIS–Teen). The target population 

for NIS–Child was children aged 19 

to 35 months, the primary target of 

immunization programs. Because less 

than 5% of U.S. households contain 

children in this age range, more than 

1 million households per year were 

screened to identify enough households 

with eligible children. 

In addition to the main NIS–Child 

survey, the second survey called NIS–

Teen was also fielded with the NIS 
Series 1, No. 59  Page 3 

sample. NIS–Teen monitored vaccination 

levels for children aged 13–17 years. 

Because the NIS–Teen target age range 

was much larger, fewer households were 

screened in the landline sample. Only a 

portion of the NIS landline sample was 

needed to meet the NIS–Teen targeted 

number of completed interviews. 

Therefore, only a portion of the NIS 

landline sample was selected for the 

NIS–Teen survey. SLAITS modules 

also used the NIS screening sample and 

immediately followed the NIS–Child or 

NIS–Teen surveys. To reduce respondent 

burden, the sample selection process 

minimized the amount of the NIS 

sample that was selected for potential 

administration of both the NIS–Teen and 

SLAITS surveys.

The NIS cell-phone sample went 

through the same selection process to 

minimize the amount of sample selected 

for both NIS–Teen and SLAITS surveys 

in a given sampling area. However, the 

eligibility rate for NIS–Teen was much 

lower in the cell-phone sample, so a 

higher sample selection rate was required 

than in the landline sample. This resulted 

in a higher proportion of the available 

cell-phone sample being selected for both 

the NIS–Teen and NSCH interviews. 

The NIS sample was an estimationlevel design with 60 estimation areas 

(including USVI) for the landline sample 

and 59 estimation areas (excluding 

USVI) for the cell-phone sample. In 

2011, NIS implemented a full dualframe sample with cell-phone samples 

stratified at the estimation area level. At 

the start of 2012, the proportion of the 

cell-phone sample was increased, based 

on an optimum allocation given cost 

differentials between landline and cellphone samples. 

NIS used the list-assisted RDD 

method (7) for the landline sample, and 

the RDD method without list assistance 

for the cell sample because no directory 

listings existed for cell-phone numbers. 

The list-assisted method of RDD 

selected a random sample of telephone 

numbers from banks of 100 consecutive 

telephone numbers (e.g., 773–256–0000 

to 773–256–0099) that contained at least 

one directory-listed residential telephone 

number. The sampling frames of 

telephone numbers for both sample types 

were updated each quarter to reflect new 

telephone exchanges and area codes. For 

certain states, the landline and cell-phone 

augmentation samples used the same 

process as NIS to select sample lines, 

while ensuring no overlap with what had 

been selected for NIS. 

NSCH Sample Design 

and Allocation

The goals of the NSCH sample 

design were to generate samples 

representative of populations of children 

aged 0–17 years within each state, and 

to obtain state-specific sample sizes that 

were sufficiently large to permit precise 

estimates of the population’s health 

characteristics. 

To achieve these goals, state samples 

were designed to obtain 1,800 completed 

interviews with parents or guardians, 

with 600 of the interviews attained from 

the cell-phone sample and the remaining 

1,200 interviews from the landline 

sample. For states with multiple NIS 

landline sampling areas, the number of 

children selected in each sampling area 

was determined by allocating the total of 

1,200 children in a state to each sampling 

area within the state in proportion to the 

total projected number of households 

with children in the sampling area. This 

projected number was adjusted in each 

sampling area as needed, based on initial 

data collected from the NIS survey. 

Given this allocation, the number of 

households that needed to be screened in 

each sampling area was calculated, using 

the expected proportion of households 

with children under age 18 years in the 

sampling area. Then, the number of 

telephone numbers that needed to be 

called was computed using the expected 

working residential (household) number 

rate. The number of telephone numbers 

drawn was increased to compensate for 

the fact that not all respondents would 

agree to participate, leading to some 

degree of nonresponse. 

The cell-phone sample was selected 

at the state level. Based on the target of 

600 cell-phone interviews, the number 

of cell-phone lines that needed to be 

screened in each state was calculated 

using the expected proportion of 

households with children under age 18 

in the state. However, the NIS sample 

was not large enough to support this. 

In calendar Quarters 3 and 4 (July–

December), 2011, and calendar Quarter 

1 (January–March), 2012, cell-phone 

augmentation samples were fielded to 

attain the number of NSCH cell-phone 

targets for each state. Some states gained 

a large portion of cell-phone-completed 

interviews through the NIS cell-phone 

sample due to the large population within 

those states (e.g., Texas and California) 

and needed minimal amounts of 

augmentation sample to attain the target 

of 600 completed interviews. 

For the cell-phone augmentation 

sample, the phone numbers were 

randomly selected at the state level, 

and the states were defined by the area 

codes of the phone number. In NIS, 

the estimation areas for the cell-phone 

sample were constructed based on the 

cell phone’s wire-center location.

The sample line needs were 

estimated using response rate information 

by state. An additional step was 

implemented in the calculation of sample 

lines for the cell-phone sample by taking 

into account higher mobility rates within 

the frame (e.g., people are likely to keep 

the same cell-phone number even if they 

have moved to a different state). 

Drawing the Samples

After estimating the number 

of landline and cell-phone numbers 

needed to achieve the target number of 

interviews by sample type (landline and 

cell phone) in each area, the samples 

were drawn. The sample draw proceeded 

in two steps: First, telephone numbers 

were sampled in each area for NIS–

Child and NIS–Teen as described above. 

Second, a portion of these telephone 

numbers in each area were flagged to be 

part of the NSCH sample. Thus, after 

these steps, every landline and cell-phone 

number sampled for NIS fell into one 

of four categories: (1) NIS–Child, (2) 

NIS–Child and NIS–Teen, (3) NIS–Child 

and NSCH, or (4) NIS–Child, NIS–Teen, 

and NSCH. Every effort was made to 
Page 4  Series 1, No. 59

minimize the flagging of cases for both 

NIS–Teen and NSCH, but some overlap 

was necessary between the two surveys 

in certain estimation areas (overlap 

sample). Overlap sample was required for 

both the landline and cell-phone samples 

of NSCH that were fielded through the 

NIS sample frame. 

For the landline sample, in 13 states 

(Alabama, Colorado, Delaware, Florida, 

Indiana, Michigan, Minnesota, Missouri, 

Montana, North Carolina, North Dakota, 

South Dakota, and Wyoming) and 

D.C., the NIS sample was insufficient 

to obtain the desired number of NSCH 

completed interviews. Therefore, 

additional telephone numbers were drawn 

in the same manner as the NIS sample 

and categorized as NSCH-only sample 

(augmentation sample) during Quarter 1, 

2012. 

Because NIS could not provide 

enough cell-phone lines for all states, 

an augmentation cell-phone sample was 

fielded for all states and D.C. during 

Quarter 3, 2011, and for most states 

during Quarter 4, 2011, and Quarter 1, 

2012. Table A shows the proportion of 

the NSCH sample that was augmented 

for each state by sample type; that is, 

for each state in Table A, the proportion 

listed is the proportion of NSCH sample 

telephone numbers that were called 

specifically from the augmentation 

sample.

Conducting NSCH 

Interviews

Each telephone number selected 

for NSCH was called and screened for 

residential status and the presence of 

NIS age-eligible children (as necessary, 

i.e., the augmentation sample was an 

exception to this rule, because it was 

selected solely to administer NSCH and 

not NIS—these households were not 

screened for NIS age-eligible children, 

but for the presence of any children). 

NIS–Child interviews were conducted 

if an NIS–Child age-eligible child lived 

in the household. If multiple NIS–

Child age-eligible children lived in the 

household, then the NIS–Child interview 

was conducted for all eligible children. If 

the household was also selected for the 

NIS–Teen survey, the household was then 

screened for the presence of a teenager 

(aged 13–17), and if an NIS–Teen ageeligible child lived in the household, 

an interview was conducted about the 

teenager’s vaccination history before 

moving on to the NSCH screener. If more 

than one NIS–Teen age-eligible child 

was in the household, one was randomly 

selected for the NIS–Teen interview. For 

NSCH, if children were in the household, 

each child’s sex and age were recorded 

(unless this information had been 

collected during the NIS interview(s), in 

which case the questions were not asked 

again). If more than one age-eligible 

child was in the household, one child was 

randomly selected to be the subject of the 

NSCH interview. 

Table A. Augmentation sample, by state and sample type 

Area

Percent of 

landline sample

called 

for NSCH only

Percent of 

cell-phone 

sample called 

for NSCH only

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 42.8

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 41.6

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 45.7

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 49.6

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 5.5

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 36.9

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 38.9

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . 4.7 56.0

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.7 40.7

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 28.9

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 35.9

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 43.8

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 41.7

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 53.7

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 5.8

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 47.3

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 51.5

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 47.1

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 45.4

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 46.6

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 10.6

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 37.0

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 37.0

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 46.7

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 40.7

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 50.8

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 40.2

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 38.6

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 34.9

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 36.9

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 40.1

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 55.9

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 44.8

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 38.5

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 16.7

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 42.6

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 48.5

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 41.2

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 2.7

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 31.5

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 55.4

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 60.3

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 25.5

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ...

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 65.2

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 30.3

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 35.6

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 35.0

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 43.5

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 41.2

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 34.9

. . . Category not applicable.

NOTE: NSCH is National Survey of Children’s Health.
Series 1, No. 59  Page 5 

In addition to age-eligibility 

screening, the NIS cell-phone sample 

was screened to keep just those numbers 

for households that either did not have 

a landline (cell phone-only [CPO]), or 

were unlikely to be reached through a 

landline if the household had one (cell 

phone-mainly [CPM]) in Quarter 1, 2011. 

However, starting in Quarter 2, 2011, NIS 

implemented the “take all” cell-phone 

approach where respondents were no 

longer screened for cell-phone status, and 

all cell-phone respondents were selected 

for NIS if an eligible child was in the 

household. 

For the NSCH cell-phone 

augmentation sample, a slightly different 

approach in screening households for the 

presence of children was implemented 

to minimize the burden on age-ineligible 

households (8). Once contact with a 

person was established, a cognitively 

simple question (“Are there any 

children living in your household?”) 

was asked immediately after the survey 

introduction. After this question, these 

cases followed the process described 

previously for the landline augmentation 

sample. 

Questionnaire

The framework for the 2003 NSCH 

was initially discussed in September 

2001. A panel consisting of selected 

state and federal maternal and child 

health program directors, representatives 

of family organizations, child health 

services researchers, and survey design 

experts met to discuss content domains. 

Eight domains were selected for their 

epidemiological and policy importance, 

including demographics; physical and 

mental health status; health insurance; 

health care use and access to health 

care; medical home; family functioning; 

parental health; and neighborhood 

characteristics. A subset of this panel 

assembled questions to capture these 

domains. Questionnaire items identified 

for inclusion were then assessed through 

reviews by outside experts and selected 

members of the community of potential 

data users. Upon final approval by 

MCHB, these questions were pretested 

in 2002 and fielded in 2003 as the first 

NSCH (2).

Although the overall structure of 

the NSCH questionnaire remained static 

across the 2003, 2007, and 2011–2012 

administrations, questionnaire revisions 

occurred prior to each survey to improve 

data quality, accommodate new sample, 

and address research questions of interest. 

Selected examples follow; consult the 

Design and Operation report for each 

NSCH module for specific information 

(2,3). The 2003 questionnaire included 

several questions on asthma, mental and 

emotional health, Hepatitis A vaccination, 

dental insurance coverage, number of 

emergency room visits, and accidental 

poisoning, among other topics, that were 

dropped in 2007. Many of the questions 

used to assess medical home in the 2005–

2006 National Survey of Children with 

Special Health Care Needs (NS–CSHCN) 

instrument were added to the 2007 NSCH 

instrument, in lieu of using the 2003 

NSCH questions. The 2007 questionnaire 

included questions on influenza 

vaccination in children and adults 

who lived with children that were not 

included in 2011–2012. The 2011–2012 

questionnaire included new questions on 

adverse child experiences asked about all 

children, and a new section that targeted 

families with income below a certain 

level who had one or more children 

eligible for, but unenrolled in, their state’s 

Children’s Health Insurance Program 

(CHIP) and Medicaid programs. These 

respondents were asked for reasons why 

the children were uninsured and assessed 

on their knowledge of, attitudes toward, 

and experience with CHIP and Medicaid 

enrollment. The 2011–2012 questionnaire 

also included questions that collected 

information to bolster maternal and child 

health surveillance and assessment under 

the life course paradigm (9). 

In January 2010, NCHS staff 

distributed an e-mail to members of 

several electronic mail lists to ask NSCH 

data users for their input and suggestions 

on questions and topics to delete, add, 

or revise. In April 2010, a technical 

expert panel (TEP) (Table B) was 

convened by MCHB to review the 2007 

questionnaire, consider all suggested 

revisions that originated from data users 

and TEP members, assemble questions 

to address newly proposed content 

areas, and provide recommendations to 

MCHB. Selected questions in the 2011 

NSCH instrument were cognitively tested 

by the NCHS Questionnaire Design 

Research Laboratory in late 2010. The 

questionnaire was finalized by MCHB 

senior staff and NCHS shortly afterward. 

Content

The 2011–2012 NSCH interview 

was designed to immediately follow 

a completed NIS–Child interview in 

households with an NIS-eligible child, 

or to follow the NIS–Child screener 

in households without NIS-eligible 

children. The NSCH questionnaire also 

immediately followed the NIS–Teen 

interview in some households that had 

been flagged for both NIS–Teen and 

NSCH surveys (i.e., overlap sample). 

The NSCH augmentation sample 

Table B. External technical expert panel members

Name Affiliation (in 2010) 

Christina Bethell, Ph.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Oregon Health & Science University

Paula Braveman, M.D., M.P.H. . . . . . . . . . . . . . . . . . . . . . . . . . University of California, San Francisco

Brian Castrucci, M.A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Georgia Department of Community Health

Laurence Grummer-Strawn, Ph.D. . . . . . . . . . . . . . . . . . . . . . . Centers for Disease Control and Prevention

Neal Halfon, M.D., M.P.H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . University of California, Los Angeles

Charles Irwin Jr., M.D.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . University of California, San Francisco

Renee Jenkins, M.D.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Howard University

Kristin Anderson Moore, Ph.D.. . . . . . . . . . . . . . . . . . . . . . . . . Child Trends

Paul Newacheck, Dr.P.H. (chairman) . . . . . . . . . . . . . . . . . . . . University of California, San Francisco

William P. O’Hare, Ph.D.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Annie E. Casey Foundation

Kathy Sanders-Phillips, Ph.D.. . . . . . . . . . . . . . . . . . . . . . . . . . Howard University

Laura Schieve, Ph.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . National Center on Birth Defects and 

Developmental Disabilities

Edward Schor, M.D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Commonwealth Fund

Fan Tait, M.D., F.A.A.P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . American Academy of Pediatrics

NOTES: External panel members are nongovernmental. Panel members made recommendations to the Maternal and Child Health 

Bureau regarding questionnaire content for the 2011–2012 National Survey of Children’s Health.
Page 6  Series 1, No. 59

questionnaire began with the NSCH 

screener. The questionnaire fielded 

in 2011–2012 was divided into 13 

sections, summarized below. A copy of 

the questionnaire as administered in the 

final quarter (Quarter 1, 2012) appears 

in Appendix II. Appendix III lists the 

key differences between the 2007 and 

2011–2012 questionnaires from the start 

of data collection. Appendix IV provides 

a list of changes made to the 2011–2012 

questionnaire over the data collection 

period.

● Section 1: Age-eligibility Screening 

and Initial Demographics—This 

section consists of the introduction 

to the interview and the question 

to determine if any children under 

age 18 live in the household. All 

children under age 18 who lived in 

the household were rostered by age, 

and one child was randomly sampled 

for the detailed NSCH interview. 

Rostering was followed by questions 

about the respondent’s relationship 

to the sampled child, the sex of the 

sampled child, and the primary 

language spoken in the household. 

● Section 2: Health and Functional 

Status—This section included 

questions regarding the sampled 

child’s acute or chronic physical, 

mental, behavioral, learning, or 

developmental conditions, and when 

present, the effect of these conditions 

upon the child’s life. This section 

also contained the Children with 

Special Health Care Needs (CSHCN) 

Screener, a consequence-based 

screening tool to identify special 

health care needs in children (10). 

Respondents were also asked about 

the sampled child’s past and current 

specific conditions; behavioral, 

medical, and dental health; and any 

limits on activity the child might 

have had based on their special 

health care needs status.

● Section 3: Health Insurance 

Coverage—This section established 

whether sampled children had any 

type of private or public health care 

coverage at the time of the telephone 

interview and in the 12 months prior 

to interview. State-specific health 

insurance program names were 

used according to the respondent’s 

reported state (Appendix V). If the 

sampled child had health insurance, 

additional questions were asked to 

determine if the coverage met his 

or her needs and if the costs were 

reasonable.

● Section 4: Health Care Access and 

Utilization—The questions in this 

section addressed the availability of 

medical, dental, and mental health 

services for the sampled child within 

the 12 months prior to interview, and 

the degree to which these services 

were needed and used during that 

period.

● Section 5: Medical Home—This 

section asked questions to determine 

whether the sampled child had a 

primary health care provider; to 

assess the quality of care for, and 

communication with, the sampled 

child and his or her parents or 

guardians; and whether the child’s 

primary health care provider 

coordinated care received from 

various providers and services. 

Together, these items determined 

whether children had access to a 

medical home as defined by the 

American Academy of Pediatrics 

(e.g., primary care that is accessible, 

continuous, comprehensive, 

family-centered, coordinated, 

compassionate, and culturally 

effective) (11).

● Section 6: Early Childhood (0–5 

years)—This section, administered 

if the sampled child was aged 5 

years or under, included questions 

about developmental screening, 

learning, child care arrangements, 

the occurrence of accidental injuries, 

and length of breastfeeding, use of 

formula, and solid food introduction. 

Additional questions asked about 

reading to the child, the amount of 

television the child watched, level of 

play, and flourishing. This section 

also included copyrighted questions 

from the Parent’s Evaluation of 

Developmental Status (PEDS) 

Child Development Screening Test, 

a tool used to identify children at 

risk for developmental, behavioral, 

or social delays (12). It was used 

in this section as a risk assessment 

tool to identify children who either 

had or were more likely to have 

problems. Researchers interested in 

analyzing PEDS data should consult 

the PEDS documentation for scoring 

instructions (12). The clinical version 

of PEDS was not used in NSCH.

● Section 7: Middle Childhood and 

Adolescence (6–17 years)—This 

section, administered if the sampled 

child was aged 6 years or over, 

focused on school performance, 

activities outside school, and 

behaviors exhibited by the child. 

Respondents were also asked about 

their attendance at the sampled 

child’s events and activities; whether 

they had met all, some, or none of 

the sampled child’s friends; and the 

amount of time the sampled child 

spent caring for him- or herself. 

Questions were also asked about 

bullying and emotional difficulties, 

and flourishing at school and home.

● Section 8: Family Functioning—

The questions in this section 

measured the number of recreational 

outings and religious services 

attended by the sampled child, the 

level of parental involvement with 

the sampled child, and the level of 

stress on the family resulting from 

the demands of parenting. Three of 

the parental stress questions (K8Q31, 

K8Q32, and K8Q34) comprised the 

Aggravation in Parenting Scale, 

which was derived from the Parental 

Stress Index (13) and the Parental 

Attitudes Toward Childrearing Scale 

(14). The parenting scale had been 

used previously in the Panel Study 

of Income Dynamics (University 

of Michigan), Survey of Income 

and Program Participation (U.S. 

Census Bureau), and Survey of 

Program Dynamics (U.S. Census 

Bureau). This section also included 

several questions from the National 

Survey of Families and Households 

(University of Wisconsin) and the 

Early Childhood Longitudinal 

Survey (National Center for 

Education Statistics) on how families 

deal with serious disagreements. 

These questions were modified 

slightly to refer to all household 

members.
Series 1, No. 59  Page 7 

● Section 9: Parental Health—

Questions in this section were 

designed to obtain the number and 

type of parents (or those serving 

as parents) who lived inside the 

sampled child’s household, and to 

assess their physical, mental, and 

emotional health; exercise frequency; 

and whether smoking occurred in the 

household. This section also included 

a series of questions about adverse 

family experiences.

● Section 10: Neighborhood and 

Community Characteristics—

The primary goal of this section 

was to determine respondents’ 

perceptions of their neighborhoods, 

and to determine the degree to which 

respondents believed their children 

were safe in the neighborhood and in 

school. Four of the questions in this 

section (K10Q30, K10Q31, K10Q32, 

and K10Q34) considered parents’ 

perceived level of neighborhood 

social capital, focusing specifically 

on positive aspects of social capital 

relating to children (15). This 

concept, alternatively called “social 

support,” was similar to the concept 

of “social cohesion and trust,” which 

was related to variations in violence 

among inner-city neighborhoods 

(16). These questions were originally 

developed for the Longitudinal 

Studies of Child Abuse and Neglect 

(University of North Carolina) and 

have also been used for the Survey of 

Income and Program Participation.

● Section 11: Additional 

Demographic Characteristics—In 

this section, respondents were asked 

a series of demographic questions, 

including the number of times the 

family had moved since the child was 

born and household use of assistance 

from a state or county welfare 

program. Appendix VI contains the 

state-specific Temporary Assistance 

for Needy Families (TANF) program 

names used. Additional questions 

determined the race and ethnicity 

of the child and whether the child 

and his or her parents were born 

in the United States. This section 

also included questions on family 

income. The annual family income 

was mapped to Department of 

Health and Human Services (HHS) 

federal poverty guidelines for 

households in order to categorize 

the household’s income relative to 

FPL. Appendix VII lists the federal 

poverty guidelines tables used to 

determine household poverty status 

at interview, and a description of the 

process used to assign poverty status 

to households.

● Section 12: Additional Health 

Insurance Questions—With 

funding from the HHS Office of the 

Assistant Secretary for Planning 

and Evaluation, new questions were 

added in 2011–2012 to explore why 

some children who were eligible 

for their state’s CHIP and Medicaid 

programs were not enrolled. It was 

administered only to cases that 

reported a household income less 

than 400% FPL and indicated that 

the sampled child did not have health 

insurance coverage. Respondents 

were asked why the child was 

uninsured; what their experiences 

and history were with Medicaid 

or CHIP; if they were interested 

in and understood the enrollment 

process associated with Medicaid or 

CHIP; and, if parents had employersponsored insurance, what coverage 

was available for the child.

● Section 13: Locating 

Information—This section collected 

information about the telephone lines 

in the household and, beginning 

in Quarter 2, 2011, telephone 

status to better describe landline 

compared with cell-phone usage 

in the household. Questions also 

collected locating information from 

all respondents such as address and 

alternate telephone numbers, among 

others, in case respondents needed 

to be contacted in the future. All 

respondents were asked to confirm 

their zip code.

Computer-assisted 

Telephone Interviewing

The 2011–2012 NSCH was 

conducted using a CATI system. The 

CATI data collection method uses 

computer software that presents the 

questionnaire on a computer screen to 

each interviewer. The computer program 

guides the interviewer through the 

questionnaire, automatically routing 

the interviewer to appropriate questions 

based on answers to previous questions. 

Interviewers enter survey responses 

directly into the computer, and the CATI 

program determines if the selected 

response is within an allowable range, 

checks it for consistency against other 

data collected during the interview, and 

saves the responses in a survey data 

file. On-screen help text is available 

to aid interviewers administering the 

CATI questionnaire. This data collection 

technology reduces the time required to 

transfer, process, and release data, and 

ensures accurate questionnaire flow. 

The NSCH questionnaire was 

programmed as a module of NIS, 

integrating the two surveys into a single 

questionnaire. The instrument made 

full use of the CATI system’s ability to 

check whether a response was within a 

legitimate range, to follow skip patterns, 

to fill state-specific information in 

questions as applicable (e.g., names of 

state Medicaid and CHIP programs), 

and to employ pick lists for response 

categories. Certain household and 

demographic questions were identical 

across the NIS–Child, NIS–Teen, and 

NSCH portions of the interview. If a 

respondent answered these questions 

during administration of the NIS 

interview, the system was programmed 

so that the questions were not repeated 

in NSCH. Instead, answers to these 

questions in NIS were copied to the data 

file for NSCH as appropriate. 

NSCH Augmentation 

Questionnaire

As noted earlier, the amount of 

sample required to reach the target 

number of completed interviews for the 

NSCH sample exceeded the NIS sample 

available in some states. For these states, 

an additional NSCH–only augmentation 

sample was drawn. Augmentation 

sample respondents did not receive 

any questions from the NIS screener or 

interview. Rather, the CATI system was 

programmed to begin with the NSCH 
Page 8  Series 1, No. 59

introduction and proceed to the NSCH 

interview in the same manner as the main 

sample. 

Interviewer Training

Training Sessions

The data collection contractor 

NORC and its subcontractor conducted 

all interviews for the 2011–2012 NSCH. 

Interviewer training was conducted by 

NORC staff at production centers located 

in Chicago, Illinois, and Las Vegas, 

Nevada. The use of multiple sites ensured 

continuous coverage in all time zones 

across the United States.

In addition, NORC employed a 

small number of distributed computerassisted telephone interviewing (DCATI) 

interviewers who resided in the Grand 

Rapids, Michigan, area. As a component 

of NORC’s disaster preparedness plan, 

DCATI staff worked from their home 

office space. NORC provided them with 

the full desktop computer and telephone 

setup required to conduct interviews just 

as they would have if they were stationed 

at the Chicago or Las Vegas production 

centers. NORC staff traveled to Grand 

Rapids, Michigan, to train DCATI 

interviewers in person for their initial 

project training. All subsequent refresher 

or specialty training for DCATI staff took 

place over voice- and videoconferencing 

and was led by the Chicago training team.

The interviewer training sessions 

began with an introduction and project 

overview. Interviewers were informed 

about project goals, the purpose and 

history of the study, study sponsors, and 

study design. An overview of the screener 

and each section of the questionnaire 

was provided, with emphasis on quality 

data collection. The relationship between 

NSCH and NIS was also covered. Several 

exercises on gaining cooperation were 

conducted throughout the training to 

ensure that interviewers were equipped 

to answer frequently asked questions 

(FAQs) and handle refusals. Part of the 

exercises included pronunciation of 

medical conditions and a review of the 

FAQ and other job aids provided for 

interviewers. Interviewers were also 

specifically trained in cell-phone sample 

dialing protocols: how to manually dial 

cell-phone cases, screen cell-phone cases 

appropriately, and respond to cell-phonespecific questions. 

Two types of mock interviews 

were used during training: trainer-led 

interviews and dual-trainee interviews. 

The trainer-led mock interviews were 

conducted by the trainer and focused on 

gaining cooperation skills and increasing 

the interviewers’ project knowledge. For 

the dual-trainee mock interviews, trainees 

were paired up and alternated playing 

the role of respondent and interviewer. 

The first dual-trainee mock interview 

was integrated into the section-bysection lecture that progressed through 

the questionnaire. The interviewers 

first listened to a lecture regarding each 

section, then practiced moving through 

that section in CATI before moving on 

to a discussion about the next section. 

This method ensured that interviewers 

became acclimated to the questionnaire, 

navigating CATI, and gaining cooperation 

as new topics were introduced. Additional 

mock interviews that simulated more 

realistic interviewing situations in real 

time were then conducted. Each mock 

interview was designed to highlight 

various sections of the screener and 

the main questionnaire, and provide 

different scenarios requiring alternative 

approaches to gain cooperation. 

At the end of training, interviewers 

completed a certification mock interview 

and written evaluation. The certification 

mock interview was administered by 

trained supervisors. It was approximately 

30 minutes in length and standardized 

to ensure that all interviewers were 

assessed equally in reading the 

questionnaire verbatim, project 

knowledge, pronunciation, and the ability 

to answer respondent questions. The 

written evaluation was administered to 

reinforce what was learned during the 

training sessions. Its nine questions took 

approximately 15 minutes to complete, 

covering FAQs, survey procedures, 

and question-specific information. 

Interviewers had to pass both the 

written evaluation and certification 

mock interview to be certified to call 

NSCH cases. Table C notes the number 

of interviewers trained by location and 

month over the course of NSCH data 

collection.

Data Collection

Data collection for the 2011–2012 

NSCH started February 28, 2011, and 

ended June 25, 2012, resulting in a 

total of 98,019 interviews including 

USVI. Age-eligibility screening was 

completed for 861,375 households. Of 

these households, 190,846 reported ageeligible children living or staying in the 

household. From each household, one 

child was randomly selected to be the 

target of the detailed NSCH interview. 

Interviews were completed for 95,689 

of these sampled children and partially 

completed for 2,330. Interviews were 

considered partially complete if the 

interview was completed through the 

end of Section 6 (for households with 

children under age 6 years) or Section 7 

(for households with children aged 6–17 

years). Table D presents the total number 

of completed interviews by state and 

telephone sample type. 

Every state started with a target of 

1,800 completed interviews. Throughout 

data collection, sample release was 

determined by estimating the number 

of completed interviews still needed to 

reach the target and achieve reasonable 

response rates. The target number of 

completed interviews was achieved 

and exceeded in every state and D.C. 

The number of children with completed 

interviews per state ranged from 1,811 

in South Dakota to 2,200 in Texas in the 

combined sample. 

Of the 95,677 detailed completed 

interviews excluding USVI, 31,972 were 

completed with the cell-phone sample. 

The number of detailed interviews 

completed with cell-phone sample in 

each state ranged from 592 in Wisconsin 

to 942 in Maryland. The target number 

of completed interviews with cell-phone 

sample (600) was not achieved in four 

states: Wisconsin (592), Alaska (595), 

and Utah and Washington (597 each). 

Adding telephone lines at the end of the 

data collection period to reach the target 

was not recommended because biased 
Series 1, No. 59  Page 9 

estimates may result if some lines are 

called less frequently or over shorter 

periods of time than others. 

Advance Letter

Advance letters have been shown 

to decrease nonresponse by confirming 

study legitimacy and communicating 

the survey’s value (17). When a mailing 

address could be identified for a 

sampled landline telephone number, an 

advance letter was mailed prior to any 

calls. Cell-phone numbers do not have 

matched addresses and, therefore, are 

not sent advance letters. Because address 

matching was not available in USVI, 

this sample also did not receive advance 

letters. Every household with an available 

mailing address identified through reverse 

address services was sent an advance 

letter—22.7% of the landline telephone 

numbers randomly generated, and 42.3% 

of the telephone numbers dialed by 

interviewers. Appendix VIII contains the 

full complement of advance letters used 

during data collection.

Because NSCH typically follows 

NIS, the advance letter sent to the main 

sample was the NIS advance letter. In the 

letter, recipients were asked to participate 

in a voluntary study of the immunization 

status of their children and the types 

of health and related services that their 

children need and use. The letter advised 

recipients that their telephone numbers 

had been chosen randomly and indicated 

that they might be called in the next few 

weeks. A toll-free telephone number 

was provided for those who wished to 

participate immediately or learn more 

about the study. 

As described earlier, the landline 

sample was augmented with additional 

sample cases in states where the NIS 

sample was insufficient to meet NSCH 

sample targets. Such households with 

an identified address were sent a similar 

advance letter, asking recipients to 

participate in a study regarding the types 

of health and related services that their 

children need or use. The letter did not 

mention NIS or immunizations, and it 

included a unique SLAITS-only toll-free 

number for recipients who wished to 

participate immediately or learn more 

about the study.

Toll-free Telephone 

Numbers

A toll-free telephone line established 

for the survey offered respondents the 

flexibility to call at their convenience if 

they had questions about the survey or 

wanted to establish eligibility, complete 

the interview, or submit feedback on any 

aspect of the survey. Advance letters, 

incentive letters, answering machine 

scripts, and closing scripts referenced 

the toll-free number, and interviewers 

provided that number to respondents 

who requested such a resource during 

the interview. NSCH cases in the NIS 

sample frame were provided a toll-free 

number accessed by both NIS and NSCH 

respondents, while NSCH augmentation 

sample households were given a unique 

SLAITS-only toll-free number to call.

Both toll-free telephone lines were 

answered by interviewers trained on 

NSCH. During the course of the survey, 

77,862 calls were made to the toll-free 

line by cases in the NSCH sample, 61% 

of which were from cell-phone sample 

cases. Of these calls, 22,638 households 

were determined ineligible for NSCH. 

An additional 27,494 households were 

eligible for the survey, and of these, 9,495 

cases completed the survey. The 27,730 

remaining calls were either nonresidential 

numbers, out-of-scope households, 

households not able to be screened for 

age eligibility, or unresolved cases. 

Table C. Number of interviewers trained, by month and telephone center location

Month

Trained Passed

Total

trained

Total

passed

Percent 

Chicago, Ill. Las Vegas, Nev. DCATI Chicago, Ill. Las Vegas, Nev. DCATI passed

2011

February . . . . . . . . . . . . . . . . . . 437 147 10 437 147 10 594 594 100

March. . . . . . . . . . . . . . . . . . . . 4 – – 4 – – 4 4 100

April . . . . . . . . . . . . . . . . . . . . . 53 35 – 46 34 – 88 80 91

May. . . . . . . . . . . . . . . . . . . . . . 7 – – 7 0 – 7 7 100

June . . . . . . . . . . . . . . . . . . . . . 44 37 – 42 32 – 81 74 91

July . . . . . . . . . . . . . . . . . . . . . . 44 58 – 40 55 – 102 95 93

August . . . . . . . . . . . . . . . . . . . 22 75 – 22 69 – 97 91 94

September . . . . . . . . . . . . . . . . 43 34 – 37 30 – 77 67 87

October. . . . . . . . . . . . . . . . . . . 23 17 – 21 15 – 40 36 90

November. . . . . . . . . . . . . . . . . – – – – – – – – . . . 

December. . . . . . . . . . . . . . . . . 25 34 – 24 32 – 59 56 95 

2012

January. . . . . . . . . . . . . . . . . . . 17 14 – 17 9 – 31 26 84

February . . . . . . . . . . . . . . . . . . 77 58 – 73 54 – 135 127 94

March. . . . . . . . . . . . . . . . . . . . 151 41 – 137 40 – 192 177 92

April . . . . . . . . . . . . . . . . . . . . . 47 – – 40 – – 47 40 85

Total . . . . . . . . . . . . . . . . . . . . . 994 550 10 947 517 10 1,554 1,474 95 

– Quantity zero.

. . . Category not applicable.

NOTE: DCATI is distributed computer-assisted telephone interviewing.
Page 10  Series 1, No. 59

Table D. Number of completed interviews, by state and telephone sample type

Area Total Completed

 Partially 

completed

Landline Cell phone

Total Completed

Partially 

completed Total Completed

Partially 

completed

All areas (excluding USVI)1

. . . . . . . . . . . . . 95,677 93,406 2,271 63,705 62,438 1,267 31,972 30,968 1,004

All areas (including USVI)1

 . . . . . . . . . . . . . 98,019 95,689 2,330 66,047 64,721 1,326 31,972 30,968 1,004

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,820 1,774 46 1,205 1,181 24 615 593 22

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 1,809 37 1,251 1,230 21 595 579 16

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,845 1,807 38 1,232 1,210 22 613 597 16

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,849 1,798 51 1,239 1,210 29 610 588 22

California . . . . . . . . . . . . . . . . . . . . . . . . . . 1,903 1,845 58 1,298 1,260 38 605 585 20

Colorado . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,820 1,785 35 1,211 1,191 20 609 594 15

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . 1,888 1,828 60 1,259 1,226 33 629 602 27

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,824 1,783 41 1,213 1,190 23 611 593 18

District of Columbia . . . . . . . . . . . . . . . . . . 1,861 1,782 79 1,261 1,234 27 600 548 52

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,855 1,810 45 1,234 1,200 34 621 610 11

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,848 1,807 41 1,230 1,212 18 618 595 23

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,881 1,821 60 1,251 1,217 34 630 604 26

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,857 1,823 34 1,243 1,222 21 614 601 13

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,071 2,028 43 1,421 1,402 19 650 626 24

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,829 1,795 34 1,224 1,203 21 605 592 13

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,847 1,815 32 1,226 1,208 18 621 607 14

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,836 1,796 40 1,224 1,199 25 612 597 15

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,864 1,816 48 1,245 1,217 28 619 599 20

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 1,794 52 1,233 1,199 34 613 595 18

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,823 1,791 32 1,214 1,197 17 609 594 15

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . 2,181 2,151 30 1,239 1,219 20 942 932 10

Massachusetts. . . . . . . . . . . . . . . . . . . . . . 1,861 1,816 45 1,260 1,231 29 601 585 16

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,833 1,787 46 1,226 1,198 28 607 589 18

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . 1,830 1,798 32 1,211 1,199 12 619 599 20

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . 1,883 1,814 69 1,244 1,207 37 639 607 32

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,859 1,806 53 1,220 1,196 24 639 610 29

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,824 1,790 34 1,217 1,191 26 607 599 8

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . 1,818 1,780 38 1,210 1,190 20 608 590 18

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,901 1,846 55 1,286 1,251 35 615 595 20

New Hampshire . . . . . . . . . . . . . . . . . . . . . 1,934 1,898 36 1,328 1,308 20 606 590 16

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . 1,858 1,806 52 1,237 1,206 31 621 600 21

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . 1,847 1,805 42 1,229 1,204 25 618 601 17

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,989 1,918 71 1,344 1,309 35 645 609 36

North Carolina . . . . . . . . . . . . . . . . . . . . . . 1,852 1,801 51 1,225 1,204 21 627 597 30

North Dakota . . . . . . . . . . . . . . . . . . . . . . . 1,835 1,793 42 1,213 1,198 15 622 595 27

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,916 1,880 36 1,293 1,271 22 623 609 14

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . 1,886 1,835 51 1,262 1,229 33 624 606 18

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 1,800 46 1,217 1,194 23 629 606 23

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . 1,886 1,832 54 1,259 1,231 28 627 601 26

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . 1,889 1,841 48 1,257 1,227 30 632 614 18

South Carolina . . . . . . . . . . . . . . . . . . . . . . 1,930 1,868 62 1,285 1,260 25 645 608 37

South Dakota . . . . . . . . . . . . . . . . . . . . . . . 1,811 1,779 32 1,192 1,180 12 619 599 20

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . 1,862 1,814 48 1,231 1,204 27 631 610 21

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,200 2,146 54 1,504 1,467 37 696 679 17

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,823 1,801 22 1,226 1,209 17 597 592 5

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,856 1,824 32 1,222 1,206 16 634 618 16

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,909 1,873 36 1,260 1,236 24 649 637 12

Washington. . . . . . . . . . . . . . . . . . . . . . . . . 1,843 1,812 31 1,246 1,228 18 597 584 13

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . 1,827 1,785 42 1,191 1,166 25 636 619 17

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . 1,838 1,802 36 1,246 1,222 24 592 580 12

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . 1,837 1,798 39 1,211 1,189 22 626 609 17

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . 2,342 2,283 59 2,342 2,283 59 ... ... ...

. . . Category not applicable.

1

USVI is U.S. Virgin Islands.
Series 1, No. 59  Page 11 

Selection of Respondent

Upon contacting a household, 

interviewers asked to speak to a parent 

or guardian living in the household who 

knew about the health and health care 

of the child(ren) in the household. The 

respondent’s relationship to the child 

was collected in two questions (K1Q02 

and C10Q02A). The relationship of 

respondent to the child was determined 

using C10Q02A for completed cases; 

however, for partial cases and where 

C10Q02A was missing, K1Q02 was used 

to determine this relationship. Table E

shows the frequency and percentage of 

respondents by their relationship with the 

child randomly selected for the detailed 

interview. The respondent was the parent 

of the child (mother or father, of any 

type) for 93.1% of sampled children. 

A parent, guardian, or other adult 

aged 18 or over was not identified in 

25,102 households (these were largely 

telephone numbers that had been 

resolved as households but screening 

was incomplete). No interviews were 

conducted in these households, even if a 

minor who lived there was the parent of 

an age-eligible child.

Informed Consent

After a knowledgeable respondent 

came to the phone, or after the person 

who answered the call identified him- or 

herself as a knowledgeable parent or 

guardian, the respondent was informed of 

his or her rights as a survey participant. 

Verbal consent for study participation 

was then obtained and documented in 

the CATI system. The consent script 

informed respondents of the voluntary 

nature of the survey, assured them 

that their responses would be kept 

confidential, and informed them that 

there was no penalty for not answering 

questions. Respondents were also told 

that the interview might be recorded and 

monitored by a supervisor for quality 

purposes. If the case qualified for a 

monetary incentive, the incentive amount 

was also provided in the informed 

consent statement. Because the interview 

length depended on whether children 

were in the household, the respondent 

was told that the estimate of the 

interview’s duration would be provided 

after a few questions. 

The NCHS Research Ethics Review 

Board and the NORC Institutional 

Review Board approved all study 

procedures and modifications. The federal 

Office of Management and Budget 

control number for this data collection is 

0920–0406.

Assurance of 

Confidentiality

Participation in surveys conducted by 

NCHS is voluntary, and all individually 

identifiable information collected is 

confidential. For NSCH, assurance of 

confidentiality was provided to potential 

respondents as part of the informed 

consent procedures. Interviewers read the 

following statement to respondents: 

We are required by Federal laws to 

develop and follow strict procedures 

to protect your information and use 

your answers only for statistical 

research. I can describe these laws if 

you wish.

If respondents requested to hear 

more about the actual laws, they were 

read the following:

The Public Health Service Act is 

Title 42 of the U.S. Code, Section 

242k. The collection of information 

in this survey is authorized by 

Section 306 of this Act. Through 

the National Center for Health 

Statistics, the confidentiality of your 

responses is assured by Section 308d 

of this Act and by the Confidential 

Information Protection and Statistical 

Efficiency Act. Would you like me 

to read the Confidential Information 

Protection provisions to you?

If respondents indicated that they 

would like to hear the provisions, 

interviewers read the following:

The information you provide will 

be used for statistical purposes only. 

In accordance with the Confidential 

Information Protection provisions of 

Title V, Subtitle A, Public Law 107–

347 and other applicable Federal 

laws, your responses will be kept 

confidential and will not be disclosed 

in identifiable form to anyone other 

than employees or agents. By law, 

every employee of the National 

Center for Health Statistics, the 

National Center for Immunization 

and Respiratory Diseases, and its 

agent, NORC at the University of 

Chicago, who works on this survey 

has taken an oath and is subject to 

a jail term of up to 5 years, a fine of 

up to $250,000, or both, if he or she 

willingly discloses ANY identifiable 

information about you or your 

household members.

If respondents had any additional 

questions or concerns, they were directed 

to the project website at https://www.cdc.

gov/nchs/slaits.htm for more information 

and were provided a toll-free telephone 

number. 

When NCHS (including its 

contractors and agents) collects 

personally identifiable information under 

a pledge of confidentiality for exclusive 

statistical purposes, Section 308d of the 

Public Health Service Act and Section 

512b of the Confidential Information 

Protection and Statistical Efficiency Act 

(CIPSEA) require that confidentiality 

be maintained without exception. 

Violations of CIPSEA are a class E 

felony, punishable by imprisonment for 

not more than 5 years, a fine not more 

than $250,000, or both. Strict procedures 

Table E. Number and percentage of respondents, by relationship to sampled child

Relationship of respondent to sampled child Number Percent

Mother or female guardian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67,603 68.97

Father or male guardian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23,602 24.08

Grandparent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5,154 5.26

Other relative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,554 1.59

Nonrelative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 0.09

Don’t know or refused. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 0.02

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98,019 100.00
Page 12  Series 1, No. 59

are used by NCHS, its data collection 

contractors, and other agents to prevent 

disclosure of confidential data in survey 

operations and data dissemination. 

Selection of Sampled Child

All households were screened for 

the presence of children under age 18 

either living or staying in the household. 

For households with children, the ages 

of all children living or staying in the 

household were rostered. If a household 

had only one child, that child was 

selected as the focus of the interview 

by default. In households with multiple 

children, one child was randomly selected 

by the CATI system to be the focus of the 

interview. 

Finding NIS-eligible 

Children in NSCH 

Rostering

NSCH was designed to follow the 

administration of the NIS–Child or NIS–

Teen interview(s) for eligible households. 

On occasion, a household would indicate 

that no NIS–Child or NIS–Teen eligible 

children were in the household, but 

upon rostering the children by age in the 

NSCH screener, NIS-eligible children 

were found. When this occurred, the 

interview returned to the NIS–Child or 

NIS–Teen interview for completion prior 

to continuing with the NSCH interview. 

A total of 191 such households were 

identified during data collection, and 54 

of these cases completed NIS and then 

completed NSCH. 

Interviews in Spanish 

The questionnaire was translated 

into Spanish by a professional translator. 

Spanish-speaking telephone interviewers 

and supervisors at NORC reviewed the 

translation and evaluated it for accuracy 

and cultural appropriateness. Issues 

raised during this review were resolved in 

consultation with the original translator. 

Any necessary modifications were made 

and the translated questionnaire was 

programmed into the CATI system for 

testing and eventual production. 

All households were first called 

by an English-speaking interviewer. 

If a potential respondent answered 

the telephone in a language other than 

English, interviewers asked, “What 

language do you speak?” If it was 

determined that the respondent needed a 

Spanish-speaking interviewer, the case 

was placed in a Spanish calling queue. 

If the interviewer placing the initial call 

was a Spanish speaker and trained to 

administer the Spanish version of the 

questionnaire, the interviewer was able 

to toggle to the Spanish questionnaire 

and continue the interview with no 

interruption. If not, the case was flagged 

in the CATI system as needing a Spanishspeaking interviewer, and all subsequent 

calls were made by Spanish-speaking 

interviewers. Nevertheless, the interview 

may have been conducted in English if 

a subsequent call by a Spanish-speaking 

interviewer reached an English-speaking 

respondent. 

During data collection, 36,272 

telephone numbers were placed in the 

Spanish calling queue. Of these, 27,479 

were determined as having reached 

households and 21,517 were screened 

for age eligibility. Some telephone 

numbers in the Spanish calling queue 

were determined to be businesses, 

whereas others remained unresolved 

due to hang-ups, answering machines, 

or lack of answer after multiple attempts 

by a Spanish-speaking interviewer. 

Age-eligible children were identified in 

10,743 households, and 4,905 households 

completed the NSCH interview. Spanishspeaking households, as defined by the 

response to variable K1Q03 (“What 

is the primary language spoken in 

your home?”) comprised 5.3% of all 

completed NSCH interviews.

Interviews in Languages 

Other Than English or 

Spanish 

Based on experience from the 2007 

NSCH, four languages were identified 

as the most probable languages that 

interviewers would encounter other 

than English or Spanish: Mandarin, 

Cantonese, Vietnamese, and Korean. The 

2011–2012 NSCH was administered in 

these languages as well as in English 

and Spanish. Independent translators 

translated the questionnaire into these 

Asian languages using the same 

procedures as were used for the Spanish 

questionnaire. Although the Spanish 

questionnaire was programmed into 

the CATI system, given the expected 

low incidence of the other languages, 

a different procedure was followed 

to screen and interview these Asianlanguage households. 

When a household was first 

identified as needing a language other 

than English or Spanish, the case was 

sent to specially trained interviewers 

who would determine the necessary 

language with a language service used by 

NORC, Language Line Services (LLS). 

LLS provides a real-time translation 

service in more than 170 languages. 

These households were then screened 

for NIS age-eligible children and, if they 

were eligible for NIS, the interviewer 

immediately conducted the NIS interview 

with the assistance of the LLS interpreter. 

After a completed NIS interview, or if 

no NIS age-eligible children were living 

in the household, the interviewer (with 

the help of the interpreter) screened the 

household for children under age 18. In 

the event that the household included 

children and spoke one of the four Asian 

languages, the case was assigned to the 

appropriate language queue to be called 

by a specially trained interviewer who 

spoke that language. Special language 

interviewers entered the respondent’s 

answers into the English CATI system 

while using a hard-copy version of the 

translated questionnaire to reference the 

appropriate translation for each question. 

This allowed for the data to be captured 

immediately in the CATI system and 

to be subject to all built-in logic and 

validation checks.

Throughout the course of data 

collection, 249 sampled telephone lines 

were identified as needing an interview in 

one of the four available Asian languages. 

The full NSCH interview was completed 

with 229 of the age-eligible households. 

Households that were identified as 

needing an Asian language interviewer 

comprised 0.1% of all screened 

households with children, and 0.2% of all 

fully completed NSCH interviews. 
Series 1, No. 59  Page 13 

If the household included 

age-eligible children but potential 

respondents apparently did not speak 

English, Spanish, or one of the four 

Asian languages, the case was coded as 

“age-eligible, interview incomplete” and 

the case was finalized. A total of 1,143 

households with children were finalized 

due to language.

USVI Sample

NSCH was administered in USVI in 

Quarter 3, 2011. All of the USVI sample 

was composed of landline sample, and 

because address matching for this sample 

was not available, advance letters were 

not mailed. To ensure that the NSCH 

questionnaire was appropriate for USVI 

residents, certain questions were modified 

or added. Rather than ask respondents for 

a zip code, the question, “On what island 

do you live?” was asked in its place. In 

addition, because Indian Health Service 

is not available to USVI residents, the 

question regarding access to this service 

was not displayed for these cases. 

Finally, all references to “state” in the 

questionnaire were replaced with “area.” 

A total of 13,494 households in 

USVI were screened for age-eligible 

children using a landline sample. Of 

these households, 3,424 reported ageeligible children living or staying in the 

household. Detailed interviews were 

completed for 2,342 children in USVI. 

Data files and documentation for the 

2011–2012 NSCH in USVI are available 

on the SLAITS website: https://www.cdc.

gov/nchs/slaits.htm. 

Cell-phone Sample

Cell-phone dialing began in Quarter 

3, 2011, for NIS cell-phone sample 

lines flagged for NSCH and for SLAITS 

augmentation cases. To accommodate 

cell-phone dialing, several questionnaire 

and system modifications were made, 

including: 

● Addition of a safety screener 

question (S_WARM) to ensure 

respondents were not driving or 

doing anything that required their 

full attention. 

● Addition of a question to confirm the 

state in which the respondent lived, 

to determine as early as possible if 

the respondent lived in a state that 

was different from their sampled 

area code.

● Modification of all introduction 

and answering-machine scripts to 

inform respondents that they were 

intentionally being called on their 

cellular device. 

● Modification of the Telephone and 

Household Information section to 

collect information on the number 

of personal cell phones in the 

household, the number of cell phones 

that adults in the household usually 

use, and the household’s cell phonemostly and cell phone-mainly (CPM) 

status (as defined in “Conducting 

NSCH Interviews”).

● Creation of cell-phone-specific 

termination paths, documenting 

when a case terminated due to a 

minor-only cell phone, among other 

reasons.

● Modification of the dialing system 

so that cell-phone numbers were 

manually dialed.

Interview Length

The length of time to administer the 

interview depended on whether any ageeligible children lived in the household. 

Interview times also varied by NIS 

eligibility, because some demographic 

and household questions necessary for 

NSCH were administered as part of the 

NIS interview and were not repeated 

during the NSCH interview. Mean and 

median interview lengths, by section 

and NIS eligibility, appear in Table F for 

landline sample interviews and Table G

for cell-phone sample interviews.

Table F. Mean and median length of National Survey of Children’s Health interview in minutes and seconds, by interview type, section, and 

National Immunization Survey eligibility: Landline sample 

Section and type of interview

NIS ineligible NIS eligible

Median Mean Median Mean

Overall length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:31:43 0:33:06 0:30:35 0:31:47

Screener: Age Eligibility—Selection of Sampled Child and Informed Consent. . . . . . . . 0:01:25 0:01:32 0:01:23 0:01:26

Section 1: Initial Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:00:33 0:00:40 0:00:31 0:00:37

Section 2: Health and Functional Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:04:05 0:04:33 0:04:02 0:04:30

Section 3: Health Insurance Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:02:03 0:02:12 0:01:56 0:02:02

Section 4: Health Care Access and Utilization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:03:21 0:03:33 0:03:19 0:03:31

Section 5: Medical Home. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:02:13 0:02:19 0:02:11 0:02:16

Section 6: Early Childhood (0–5 years) (entire section). . . . . . . . . . . . . . . . . . . . . . . . . 0:05:54 0:06:09 0:05:38 0:05:53

Section 7: Middle Childhood and Adolescence (6–17 years). . . . . . . . . . . . . . . . . . . . . 0:05:04 0:04:17 0:05:09 0:04:23

Section 8: Family Functioning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:01:38 0:01:47 0:01:38 0:01:46

Section 9: Parental Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:03:58 0:04:13 0:03:55 0:04:09

Section 10: Neighborhood and Community Characteristics . . . . . . . . . . . . . . . . . . . . . . 0:02:05 0:02:15 0:02:04 0:02:13

Section 11: Additional Demographics (entire section). . . . . . . . . . . . . . . . . . . . . . . . . . . 0:02:51 0:03:06 0:02:35 0:02:47

Section 12: Additional Health Insurance Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:05:23 0:05:44 0:05:19 0:05:39

Section 13: Locating Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:01:21 0:01:27 0:01:12 0:01:11

NOTES: NIS is National Immunization Survey. NIS ineligible includes cases where NIS–Child and NIS–Teen were not completed. NIS eligible includes cases that completed NIS–Child or NIS–Teen. 

Augmentation sample is categorized as NIS ineligible. Overall interview length is calculated only for cases that began and completed the interview on the same call. Individual section timings are 

calculated only for cases that began and completed that particular section on the same call.
Page 14  Series 1, No. 59

Interview Breakoffs

Households that initially refused 

participation in the interview were 

placed into a queue that was worked 

by interviewers specially trained in 

refusal conversion strategies. These 

interviewers attempted to convert 

incomplete interviews into completed 

interviews. By the end of data collection, 

31.6% of all completed interviews were 

completed with households that had 

refused to participate at least once after 

age eligibility was established; 29.4% of 

these were cell-phone cases.

More than 95,000 known ageeligible cases did not complete the full 

interview; see Table H for their final 

disposition. Most of these cases were 

determined to be age-eligible (97.6%) 

but did not reach the point of partial 

completion in the NSCH interview. A 

total of 2,330 cases partially completed 

the NSCH interview through the end of 

Section 6 or Section 7, depending on the 

age of the selected child.

Among cases that completed the 

age rostering but were neither partially 

nor fully completed interviews, 58.2% 

did not reach the start of Section 1 after 

completing the age roster. Another 18.4% 

of cases started Section 1 but did not 

reach the beginning of Section 2. From 

this point on, the number of cases that 

advanced to the next section declined 

relatively steadily.

Cases Pending at Close of 

Data Collection

Approximately five-sixths of 

the cases pending at the end of data 

collection (n = 1,705,693) were those 

in which the sampled telephone number 

had not yet been resolved as a residential 

or nonresidential number (86.9% of 

pending cases, or 27.7% of the initial 

sample). Age eligibility had not yet 

been determined in less than one-tenth 

of the pending residential cases (8.4%, 

or 2.7% of the initial sample). A small 

number of households were determined 

to be age-eligible, but the interview was 

not partially or fully completed (4.7% 

of all pending cases, or 1.5% of the 

initial sample). Table J and Appendix IX

provide more information about the final 

disposition of these cases.

Response Rates

Response rates provide one measure 

of the potential for nonresponse bias—

that is, the possibility that the sample 

interviewed differs from the actual 

population in some meaningful way. 

Three weighted overall response rates 

were calculated for NSCH: 

● Household-level resolution rate 

reflects the potential for nonresponse 

bias in the sample of telephone lines 

that were identified as belonging to 

households that contained at least 

one age-eligible child.

● Child-level age-screener response 

rate reflects the potential for 

nonresponse bias in the sample of 

screened children aged 0–17 years.

● Interview response rate reflects the 

potential for nonresponse bias in 

the sample of children for whom the 

NSCH interview was completed.

These rates were calculated for 

the landline, cell-phone, and combined 

Table G. Mean and median length of National Survey of Children’s Health interview in minutes and seconds, by interview type, section, and 

National Immunization Survey eligibility: Cell-phone sample 

Section and type of interview

NIS ineligible NIS eligible

 Median Mean Median Mean

Overall length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:31:39 0:33:06 0:31:00 0:32:24

Screener: Age Eligibility—Selection of Sampled Child and Informed Consent. . . . . . . . 0:01:22 0:01:30 0:01:25 0:01:32

Section 1: Initial Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:00:36 0:00:44 0:00:34 0:00:41

Section 2: Health and Functional Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:04:13 0:04:41 0:04:13 0:04:41

Section 3: Health Insurance Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:02:07 0:02:17 0:02:01 0:02:08

Section 4: Health Care Access and Utilization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:03:26 0:03:39 0:03:25 0:03:39

Section 5: Medical Home. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:02:16 0:02:21 0:02:15 0:02:20

Section 6: Early Childhood (0–5 years) (entire section). . . . . . . . . . . . . . . . . . . . . . . . . 0:06:01 0:06:17 0:05:52 0:06:08

Section 7: Middle Childhood and Adolescence (6–17 years). . . . . . . . . . . . . . . . . . . . . 0:04:53 0:03:49 0:05:02 0:04:00

Section 8: Family Functioning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:01:39 0:01:47 0:01:39 0:01:48

Section 9: Parental Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:04:05 0:04:20 0:04:03 0:04:18

Section 10: Neighborhood and Community Characteristics . . . . . . . . . . . . . . . . . . . . . . 0:02:09 0:02:19 0:02:09 0:02:19

Section 11: Additional Demographics (entire section). . . . . . . . . . . . . . . . . . . . . . . . . . . 0:03:01 0:03:16 0:02:48 0:03:01

Section 12: Additional Health Insurance Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:05:29 0:05:51 0:05:29 0:05:50

Section 13: Locating Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0:01:28 0:01:31 0:01:14 0:01:21 

NOTES: NIS is National Immunization Survey. NIS ineligible includes cases where NIS–Child and NIS–Teen were not completed. NIS eligible includes cases that completed NIS–Child or NIS–Teen. 

Augmentation sample is categorized as NIS ineligible. Overall interview length is calculated only for cases that began and completed the interview on the same call. Individual section timings are 

calculated only for cases that began and completed that particular section on the same call.

Table H. Final disposition of age-eligible households where interview was not completed 

Final disposition

Age-eligible incompletes

Number Percent 

Known age-eligible household

Interview not completed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92,827 97.6

Interview partially completed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,330 2.4

Total, full interview not completed. . . . . . . . . . . . . . . . . . . . . . . . . . 95,157 100.0
Series 1, No. 59  Page 15 

landline and cell-phone samples at the 

national and state levels. The NSCH 

interview response rate can be calculated 

as the product of component completion 

rates: resolution rate, age screener 

completion rate, and NSCH interview 

completion rate, which are discussed 

below. (The response rates presented 

in this section were weighted by base 

weights; see Appendix I for further 

details.)

In the tables in this section, “state” is 

the state to which the telephone number 

was assigned at the time the sample of 

telephone numbers was selected. For the 

landline sample, this “sampling state” is 

almost always the same as the state where 

the household with that telephone number 

is located, but this is not true for the cellphone sample, where the sampling state 

often differs from the state of residence. 

However, because the true state of 

residence is known only for households 

that have completed the interview, the 

sampling state must be used to compute 

the response rates. 

For the landline and cell-phone 

samples, national rates including and 

excluding USVI are presented. However, 

the national rates cited below exclude 

USVI.

Resolution rate

Response rates for telephone surveys 

are typically lower than response rates 

for household in-person surveys, because 

some telephone calls ring with no 

indication of whether the number belongs 

to a household or to a business. The 

national resolution rate, which measures 

the proportion of sampled telephone 

numbers that could be identified as 

residential or nonresidential, was 80.9% 

in the landline sample and 48.6% in the 

cell-phone sample. 

These resolution rates treat all 

telephone numbers that resulted in no 

contact (i.e., all attempts resulting in 

rings with no answer or a busy signal) 

as unresolved. Because every telephone 

number was dialed at least six times 

at different times on different days, 

it is possible that these “noncontact” 

numbers are actually nonworking 

residential numbers. An alternative 

national resolution rate, which treats 

these numbers as nonworking, was 88.7% 

in the landline sample and 54.0% in the 

cell-phone sample.

The original and alternative 

resolution rates for each state are 

presented in Table K for the landline 

sample and Table M for the cell-phone 

sample.

Screener completion rate 

After a telephone number had been 

determined to belong to a household, 

that household was screened for the 

presence of children under age 18. Each 

household was first screened for NIS–

Child eligibility; that is, each household 

was screened for the presence of children 

aged 19–35 months. A portion of these 

households was also screened for 

NIS–Teen, that is, for the presence of a 

teenager aged 13–17. If the household 

was found to be age-eligible for NIS–

Child or NIS–Teen, then the household 

was also considered to be age-eligible 

for NSCH. If the household was ageineligible for NIS–Child or NIS–Teen, 

then that household proceeded to the 

rostering portion of NSCH where, if the 

respondent indicated that the household 

contained children under age 18 years, 

the household was considered to be ageeligible for NSCH. (NSCH augmentation 

households were not screened for 

NIS–Child or NIS–Teen and, so, were 

age-screened only during the rostering 

portion of NSCH.) If, during the NIS–

Child screener, the NIS–Teen screener, 

or the rostering portion of NSCH, the 

respondent indicated that the household 

contained no children, the household was 

considered age-ineligible for NSCH. 

During Quarter 1, 2011, an 

additional screener was put in place for 

the cell-phone sample to identify cellphone-only (CPO) and cell-phone-mainly 

(CPM) households. In this quarter, if the 

household reached through the cellphone sample had a landline telephone 

that was somewhat or extremely likely 

to be answered, the household was 

ineligible for the cell-phone sample. To 

calculate component completion rates 

and response rates for the cell-phone 

sample, in this quarter this cell phoneonly or -mainly (CPO/M) screener was 

treated as part of a single telephonestatus screener to identify cell phones 

used by adults in CPO/M households. 

An additional screener was put in place 

for the cell-phone augmentation sample 

to quickly screen out households with 

no children. In this quarter, after a 

cell-phone number was determined to 

belong to a household but prior to cellphone status screening, the respondent 

was asked, “Are there any children 

living in your household?” Households 

Table J. Final disposition of 2011–2012 National Survey of Children’s Health sample

Final disposition

Total1 Landline1 Cell phone1

 Number Percent Number Percent Number Percent

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6,152,487 100.0 4,252,193 100.0 1,900,294 100.0

Not resolved as residential or nonresidential2

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,705,693 27.7 755,007 17.8 950,686 50.0

Out of scope (business, nonworking, fax, or modem). . . . . . . . . . . . . . . . . . . . . . . . . . . 3,389,715 55.1 2,860,125 67.3 529,590 27.9

Cell phone-screened household, minor-only cell or landline-mainly cell. . . . . . . . . . . . . 30,387 0.5 0.0 0.0 30,387 1.6

Known household, age eligibility undetermined2

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165,317 2.7 76,320 1.8 88,997 4.7

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 670,529 10.9 442,146 10.4 228,383 12.0

Known age-eligible household, interview not completed2

. . . . . . . . . . . . . . . . . . . . . . . . 92,827 1.5 52,548 1.2 40,279 2.1

Known age-eligible household, interview partially completed. . . . . . . . . . . . . . . . . . . . . 2,330 0.0 1,326 0.0 1,004 0.1

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95,689 1.6 64,721 1.5 30,968 1.6

1

Selected telephone lines.

2

Pending cases at the end of data collection.
Page 16  Series 1, No. 59

Table K. Weighted National Survey of Children’s Health completion rates, nationally and by state: Landline sample

Area Resolution rate

Alternative 

resolution rate

Screener 

completion rate

Interview 

completion rate

Total (excluding USVI)1 . . . . . . . . . . . . . . . . . . . . . . . . . . 80.9 88.7 87.2 54.1

Total (including USVI)1

 . . . . . . . . . . . . . . . . . . . . . . . . . . 80.9 88.8 87.2 54.1

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.0 89.4 87.6 58.9

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.7 91.7 87.7 53.6

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.8 88.5 86.8 50.7

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.4 91.9 90.6 56.6

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75.2 87.7 84.7 49.4

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.6 87.9 89.0 59.6

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.0 84.0 85.5 53.9

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76.3 84.5 87.3 52.5

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.5 91.6 87.4 58.1

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.5 88.3 86.3 51.1

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.9 89.3 86.9 55.0

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.4 90.3 85.3 49.6

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.5 90.1 89.9 54.1

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.1 90.3 88.0 54.3

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.8 91.1 89.1 62.1

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.3 91.0 90.9 60.0

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.5 90.5 89.3 60.0

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.9 89.6 87.9 53.6

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.4 90.9 86.2 52.1

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.5 89.1 90.3 57.6

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.5 86.9 85.8 58.3

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.3 84.1 86.1 53.2

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.6 90.2 88.2 58.2

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.6 89.3 90.2 57.2

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.4 91.4 87.4 55.2

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.2 90.7 89.2 59.4

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.9 90.3 90.8 64.6

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.3 90.8 89.1 58.4

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.5 87.8 86.0 49.6

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.4 85.7 88.0 53.5

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.7 87.2 85.1 50.8

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.8 89.4 88.3 58.5

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.3 87.9 85.1 46.9

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.0 88.6 88.2 54.8

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.3 92.7 90.5 56.1

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.6 89.6 88.3 55.3

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.8 90.0 87.5 51.0

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.3 90.2 90.7 60.9

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.4 86.7 88.0 54.8

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.8 85.1 86.7 55.7

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.8 89.1 87.5 51.8

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87.6 91.9 90.3 57.8

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.3 89.4 89.0 55.1

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.0 89.5 85.6 53.2

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.3 89.2 89.3 58.7

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.2 89.3 91.0 64.6

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.3 87.7 87.6 58.0

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.5 88.0 89.0 58.4

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.9 86.6 88.2 57.1

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.5 89.9 90.0 57.7

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.6 90.2 89.9 57.2

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.1 96.0 92.2 68.4

1

USVI is U.S. Virgin Islands.
Series 1, No. 59  Page 17 

Table M. Weighted National Survey of Children’s Health completion rates, nationally and by state: Cell-phone sample

Area Resolution rate

Alternative 

resolution rate

Screener 

completion rate

Interview 

completion rate

Total (excluding USVI)1 . . . . . . . . . . . . . . . . . . . . . . . . . . 48.6 54.0 77.2 41.2

Total (including USVI)1

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

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.8 62.1 78.8 43.0

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59.7 73.0 81.0 53.3

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.5 53.9 80.0 44.8

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.8 59.3 79.9 48.2

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.4 51.0 73.4 37.0

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.8 53.4 78.5 47.2

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.4 47.0 76.1 40.8

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.0 50.3 81.9 44.4

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40.6 52.9 84.7 50.7

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.9 53.6 77.3 37.1

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.8 58.8 77.6 41.8

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.5 49.2 77.9 41.2

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.1 55.5 81.8 51.9

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.1 56.8 74.2 38.4

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.8 56.9 80.9 44.0

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.0 59.4 81.7 46.7

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.0 60.1 82.1 49.3

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.4 56.3 79.1 44.1

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.8 56.8 77.6 42.0

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.7 50.3 80.8 45.0

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.1 47.4 78.2 41.8

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.6 49.9 78.3 45.1

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.6 56.2 79.4 41.2

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.9 56.1 81.8 45.8

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.7 62.9 80.4 42.1

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.0 53.9 80.7 46.7

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.9 67.6 82.8 51.5

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.0 57.6 80.5 52.4

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.5 51.2 78.0 43.5

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.4 49.5 78.4 44.8

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.9 53.0 78.6 38.5

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56.4 61.8 81.1 45.3

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.0 50.4 74.3 34.0

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.8 56.6 78.0 43.5

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64.8 71.0 82.2 49.2

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.2 52.1 78.5 40.6

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.7 60.0 80.2 43.5

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47.4 51.0 81.6 47.2

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.9 48.8 75.7 31.8

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.5 47.4 77.0 45.5

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.9 57.4 79.8 41.1

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64.0 67.1 83.8 50.1

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.8 52.9 77.0 44.0

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.5 53.1 72.9 39.6

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.4 58.6 81.5 51.5

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.5 50.4 79.9 50.1

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.7 50.7 79.8 44.2

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.6 48.1 79.3 45.7

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.6 48.3 78.6 42.9

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.5 56.3 79.3 47.0

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.2 73.3 80.0 52.0

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... ...

. . . Category not applicable. 1

USVI is U.S. Virgin Islands.
Page 18  Series 1, No. 59

reporting no children were ineligible for 

NSCH. Because the age screener was 

administered before the cell-phone status 

screener for some households and after 

the same screener for others, the age- and 

cell-status screeners were treated as a 

single screener to identify CPO or CPM 

households containing children when 

calculating component completion rates 

and response rates for the cell-phone 

sample.

Some households did not complete 

the age and cell-phone-status screeners. 

For the landline sample, the age-screener 

completion rate is the proportion of 

identified households for which it was 

determined whether the household 

contained children under age 18. For 

the cell-phone sample, the age-screener 

completion rate is the proportion of 

identified households for which it was 

determined whether the cell phone was 

used by an adult in a household that 

contained children under age 18. In the 

Quarter 1, 2011, cell-phone sample, 

the age and cell-phone-status screener 

completion rate is the proportion of 

identified households for which it was 

determined whether the cell phone was 

used by an adult in a CPO/M household 

that contained children under age 18. The 

national screener completion rate was 

87.2% for the landline sample and 77.2% 

for the cell-phone sample. The screener 

completion rates for each state are given 

in Table K for the landline sample and 

Table M for the cell-phone sample.

Interview completion rate 

Once a child was randomly chosen 

from the household, an attempt was 

made to conduct a full interview about 

the selected child. Not all households 

containing children completed the full 

interview. The interview completion rate 

is the proportion of households known to 

contain a child that completed Section 6 

(for children aged 0–5 years) or Section 

7 (for children aged 6–17 years). The 

national interview completion rate was 

54.1% for the landline sample and 41.2% 

for the cell-phone sample. The rates for 

each state are given in Table K for the 

landline sample and Table M for the cellphone sample.

Overall response rate

The NSCH interview response rate is 

the product of the resolution rate, age and 

cell-phone-status screener completion 

rate, and interview completion rate. 

Using the original resolution rate, this 

calculation returns response rates of 

38.2% for the landline sample, 15.5% 

for the cell-phone sample, and 23.0% for 

the overall sample. Using the alternative 

resolution rate described earlier (which 

treats telephone numbers with no contact 

as nonworking numbers), the resulting 

response rates are 41.9% for the landline 

sample, 17.2% for the cell-phone sample, 

and 25.4% for the overall sample. The 

true estimate of the response rate likely 

lies between the original and alternative 

calculation, depending on the proportion 

of noncontact numbers that were 

nonworking. Table N shows the overall 

response rates nationally and by state.

Other methods exist to calculate 

response rates that result in different 

rates. Appendix X contains the overall 

response rate for the landline, cell-phone, 

and overall samples for each state and 

the nation, as well as alternative response 

rates and guidance on comparing 

response rates across surveys. 

Efforts to Improve 

Response Rates

Advance letters, toll-free numbers, 

refusal conversion efforts, and translated 

questionnaires were used to help improve 

response rates. In addition, other efforts 

included questionnaire review and 

revision, sample management, and 

monetary incentives.

NCHS and MCHB worked with data 

collection contractor NORC to make 

specific improvements to the 2011–2012 

instrument based on feedback from 

data users. After every quarter of data 

collection, a list of potential changes to 

the instrument also was reviewed and 

implemented if necessary. These changes 

were based on analysis of questionnaire 

breakoffs and reports from interviewers 

of problem areas within the questionnaire 

(Appendixes III and IV).

Two integrated sample management 

teams—one focused on NIS and one on 

SLAITS—met frequently to manage 

the sample effectively and efficiently. 

Ongoing assessments and modifications 

of the data collection instrument, data 

collection procedures, and calling rules 

were conducted. 

Response rates were monitored 

closely throughout the data collection 

period. Specially trained refusal 

converters attempted to convert 

nonrespondents by targeting the casespecific source of the refusal, based on 

the case history. In addition, an extensive 

incentive protocol was conducted to 

increase the rate of refusal conversions 

and response rates in general. An 

incentive experiment was conducted 

to identify best practices to present 

the incentive offer and its value. A full 

explanation of the incentive experiment, 

the resulting incentive methods chosen, 

and the effect on NSCH response rates 

can be found in Appendix XI. 

Incentive treatment was generally 

applied to cases with one or two refusals 

in their case history (Appendix XI). To 

further increase response rates, incentives 

were also offered to cases that reported 

having age-eligible children in the 

household and subsequently refused 

participation in a passive manner, by not 

engaging in live contact with a telephone 

interviewer for at least 21 days. Passive 

cases had either zero or one refusal in 

their case history, and following the 

21-day period, became eligible for 

the two-refusal incentive treatment. A 

total of 7,510 cases that received the 

passive refusal incentive treatment went 

on to complete the survey, effectively 

increasing survey response rates 

(Appendix XI). Appendix XII shows the 

envelopes used for mailing incentives as 

described in Appendix XI.

Nonresponse Bias

Although the efforts outlined above 

improved the response rate, much 

nonresponse to the survey remained. 

Appendix XIII details the nonresponse 

bias analysis that was performed to 

examine the extent that nonresponse bias 

affected survey estimates. Generally, 

the results indicate that the interviewed 

population was more likely to live 

in rural and other areas with lower 

household density when compared with 
Series 1, No. 59  Page 19 

the nonresponding population. The 

interviewed population was also more 

likely to live in areas associated with 

higher levels of homeownership, lower 

home values, and a greater percentage 

of non-Hispanic white persons. When 

nonresponse-adjusted weights were used, 

minor differences by homeownership, 

home values, and race remained. In 

general, the analysis showed that 

response biases could have had a small 

impact on key survey estimates, but 

that the nonresponse adjustment to 

the weights substantially reduced the 

potential magnitude of those biases. Of 

the 10 key survey estimates examined, 

3 showed maximum estimated biases 

of less than 1 percentage point, and 5 

showed maximum estimated biases 

that were within the 95% confidence 

interval for the “biased” estimate, 

indicating that nonresponse bias was 

smaller than potential sampling error. 

Family structure showed a maximum 

bias for the percentage of two-parent 

biological or adoptive families that was 

similarly smaller than sampling error; the 

percentages of two-parent stepfamilies, 

single-mother families, and other family 

structures showed maximum biases 

of 4.4, 2.0, and 2.3 percentage points, 

respectively, but all three also showed 

biases in the opposite direction depending 

on which method is used to estimate bias. 

Of the remaining key survey estimates 

examined, one showed a maximum 

estimated bias of 1.72 percentage points 

but also showed other estimates of bias 

in the opposite direction, and the other 

showed estimated biases of 0.12–2.5 

percentage points, depending on the 

method used to estimate bias. In fact, bias 

estimates were so small that, for most 

of the key survey variables examined, 

changing the method used to estimate 

bias changed the estimated direction of 

the bias. Without a true gold standard, 

it is impossible to accurately measure 

bias and, thus, bias cannot be completely 

ruled out, but the low estimated biases 

and inconsistent direction of estimated 

biases do not suggest the presence of 

substantial bias.

Quality Control of 

Interviewing 

The CATI system was programmed 

to help ensure complete and accurate data 

collection using automated data-checking 

techniques, such as response-value range 

checks and consistency edits, during 

the interview process. These features 

enabled interviewers to obtain needed 

clarifications while still on the telephone 

with the respondent. Throughout 

data collection, interview data were 

reviewed for consistency between fields, 

appropriate response-value ranges, skip 

logic patterns, and missing information. 

Telephone center supervisors 

were immediately available to assist 

interviewing staff at all times to resolve 

any questions or concerns about a 

case. Supervisors regularly observed 

the data collection process to monitor 

interviewers. In addition, supervisory 

staff used remote telephone and 

Table N. National Survey of Children’s Health 2011–2012 response rates overall, nationally 

and by state

Area

Overall response rate 

(percent)

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.0

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.5

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.6

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.4

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.5

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.3

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.5

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.3

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.2

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.8

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.0

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.4

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.2

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.0

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.1

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.3

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.7

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.9

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.9

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.4

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.3

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.6

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.8

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.7

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.3

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.5

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.8

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.5

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.8

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.3

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.7

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.7

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.8

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.7

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.8

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.5

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.0

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.9

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.2

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.1

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.8

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30.4

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.7

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.2

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.8

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.3

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.3
Page 20  Series 1, No. 59

computer-monitoring technology to 

evaluate whether interviewers performed 

according to project specifications. 

This formal monitoring was conducted 

to ensure that introductory materials 

were properly read, item wording and 

sequence of the questionnaire were 

followed correctly, respondent questions 

were answered properly, and any 

vague responses were properly probed. 

Computer monitoring also allowed 

supervisors to determine whether answers 

were entered accurately into the CATI 

system. 

New supervisors attended an 8-hour 

training session that introduced them to 

the monitoring procedures. In addition, 

supervisors participated in an exercise 

to learn how to give effective feedback 

and coach interviewers. After this 

training session, each new supervisor 

conducted dual-monitoring sessions with 

experienced staff. Each new monitor 

observed live monitoring side by side 

with an experienced monitor, and each 

completed a Monitoring Evaluation 

Form. At the end of each session, the 

new supervisor and experienced monitor 

compared notes, discussed proper scoring 

guidelines, and created a strategy to give 

feedback. These training procedures 

ensured that all supervisors were 

monitoring interviewers using the same 

criteria for evaluation. 

The CATI monitoring system 

automatically selected which 

interviewers to monitor and gave the 

highest priority for monitoring to newly 

trained interviewers, those with the 

fewest monitoring sessions, or those 

with the weakest performance reviews. 

Experienced interviewers were prioritized 

for monitoring based on the length of 

time since their last monitoring session 

and their recent monitoring scores. Each 

interviewer was typically monitored 

at least once a week; however, some 

interviewers were monitored more often. 

Throughout data collection, 

interviews were recorded as well, after 

obtaining agreement from respondents. 

These recordings were valuable tools 

for training, and when necessary, they 

allowed supervisors to document specific 

case-related performance and provide 

tailored feedback to interviewers. 

Recordings were destroyed after 1 year.

Questionnaire updating

After every quarter of data 

collection, a list of potential changes 

to the instrument was reviewed and 

implemented if necessary. These changes 

were based on analysis of questionnaire 

breakoffs and reports from interviewers 

of problem areas within the questionnaire 

(Appendixes III and IV). 

Toll-free telephone number

As discussed in “Data Collection: 

Toll-free Telephone Numbers,” toll-free 

numbers were maintained and listed 

in all letters to respondents. The tollfree numbers allowed respondents to 

participate immediately, ask questions 

regarding the survey, or obtain additional 

survey-related information. 

Data Files 

One data file was created, using 

SAS version 9.2. The file included 

data from 2011 and 2012 complete 

interviews, that is, complete through 

Section 6: Early Childhood (0–5 years) 

or Section 7: Middle Childhood and 

Adolescence (6–17 years). To maintain 

confidentiality, certain variables that 

could be used to identify respondents 

were excluded from the file. One record 

was created for each child who was 

randomly selected to be the subject of the 

interview. This file (n = 98,019) contains 

data on the sampled child’s health 

and health care, family functioning, 

parental health, neighborhood and 

community characteristics, health 

insurance coverage, and demographics 

such as family composition. Of the 

98,019 records, 95,689 cases were fully 

completed interviews, and 2,330 were 

partially completed interviews.

This data file was split into two files 

for public release: one containing data 

from the 50 states and D.C. (n = 95,677), 

and the other containing data for USVI 

(n = 2,342). 

Separate data files contain multiply 

imputed values for missing poverty 

status. As with the main data files, one 

file is for the 50 states and D.C., and one 

file is for USVI. Appendix XIV describes 

the procedures used to multiply impute 

household income and household size to 

allow computation of poverty status for 

households with missing income or size.

Editing

The CATI system was designed to 

perform edits as an interviewer entered 

data into the computer system. To prevent 

interviewer error, the CATI system was 

developed to include range checks and 

consistency checks. If an interviewer 

entered a value that was “out of range,” a 

warning screen would appear, instructing 

the interviewer that the data would not be 

accepted and that he or she would have 

to enter a different answer (and possibly 

re-ask the question). For example, a 

respondent might report three people in 

the household but had earlier reported 

four children. In that event, a consistency 

check would appear, saying, “NUMBER 

OF PEOPLE IN THIS HOUSEHOLD 

CANNOT BE LESS THAN NUMBER 

OF KIDS+1,” indicating that the numbers 

did not add up correctly. To the extent 

possible without making the CATI 

system overly complicated, out-of-range 

and inconsistent responses resulted in 

a warning screen for the benefit of the 

interviewer, who was trained to correct 

errors as they occurred. These messages 

were designed primarily to prevent 

data entry errors and respondent errors 

and not to challenge respondents who 

gave logically inconsistent responses. 

Logically inconsistent responses given by 

the respondent were left inconsistent.

Even with many built-in CATI 

checks, data cleaning was still necessary. 

Invalid values were deleted and missing 

values were investigated. On rare 

occasions, certain data were not collected 

as expected, but the missing data were 

easy to determine based on related 

questions. The most important part of 

data cleaning was making sure that each 

household had the expected number of 

children’s ages rostered, as well as the 

age and sex for the child that was selected 

for the full interview. Finally, missing 

data had to be determined to be a result 

of legitimate skip, a partially completed 

interview, or data that were missing in 

error.
Series 1, No. 59  Page 21 

Missing Data

Missing data are not desirable 

when doing analyses and are often 

ignored completely. However, it can be 

helpful to know why data are missing. 

The SAS data files for NSCH include 

special missing-value codes for analysts 

who may wish to differentiate between 

different types of missing values. The 

following key provides a description 

of the various codes that were used to 

represent missing data in the file:

(.N) Not in universe—Respondents 

skipped an entire section of questions 

based on eligibility criteria. For NSCH, 

sampled children aged 0–5 years were 

not eligible for Section 7 of the survey, 

and children aged 6–17 years were not 

eligible for survey Section 6. Sampled 

children with health insurance, or living 

in households that reported an income 

over 400% FPL, were not eligible for 

Section 12 of the survey.

(.L) Legitimate skip—Variable is 

missing due to valid questionnaire paths, 

based on a previous answer to a root 

question.

(.P) Partially completed 

interview—Variable is missing because 

the respondent ended the call after 

completing Section 6 or Section 7 but 

before completing the full interview.

(.M) Missing in error—Variable is 

missing due to interviewer or system 

errors. In cases of interviewer error, the 

interviewer may have deleted the data 

accidentally or may have not entered the 

response. In cases of system error, the 

response may not have been collected or 

saved properly after it was entered by the 

interviewer in the CATI system.

(.A) Added question—Variable is 

missing because this question was added 

after the start of data collection, and 

the interview was conducted before the 

question was added. 

Derived variables (i.e., variables 

whose response was not directly 

provided by the respondent) do not 

include the detailed coding of missing 

data. All missing values for derived 

variables received a “.M” code regardless 

of the reason for the missing data. 

Similarly, “.M” was used when derived 

variables were suppressed to protect the 

confidentiality of survey participants.

Data missing because the respondent 

did not know the answer or refused to 

provide the answer have been treated 

differently. Rather than assigning 

a missing value to these records, a 

numeric code was used to identify these 

responses. Typically, unknown answers 

are coded as “6,” “96,” or “996.” Refused 

responses are coded as “7,” “97,” or 

“997.” Analysts are encouraged to consult 

the data documentation and frequency 

lists to identify the correct codes for each 

variable. Failure to do so may result in 

inappropriate calculations, especially 

for variables measured using ordinal, 

interval, or ratio scales.

Coding of Verbatim 

Answers Into Question 

Responses

For some questions in the NSCH 

interview, respondents provided a 

response that did not match any preexisting category. If this occurred, the 

interviewer entered “other” and typed 

in the exact response provided by the 

respondent. At the end of the data 

collection period, an attempt was made 

to recode the verbatim responses into 

existing categories where appropriate. 

For certain variables listed below, new 

response categories were added to the 

data file to capture verbatim responses. 

This back-coding occurred for a number 

of variables, listed below showing the 

sampled child as [S.C.]:

● Type of doctor or other health care 

provider who first told respondent 

that [S.C.] had autism or autism 

spectrum disorder (K2Q35D)

● Any other reasons why respondent 

thinks [S.C.] may no longer have 

autism or autism spectrum disorder? 

(K2Q35G)

● Any other reasons why a doctor or 

other health care provider may have 

told you that [S.C.] had autism or 

autism spectrum disorder when [he/

she] never had it? (K2Q35J)

● Place of health care provider 

(K4Q02)

Three additional response categories 

were used in the back-coding of this 

variable:

○ Places a telephone call (e.g., 

hotline, nurse’s line)

○ Mental health service provider 

(e.g., counselor, therapist, 

psychiatrist)

○ Alternative health care (e.g., 

chiropractor, homeopath, 

naturopath)

● Kind of place or places [S.C.] had 

[his/her] vision tested (K4Q32)

Two additional response categories 

were used in the back-coding of this 

variable:

○ Retail center (e.g., Walmart)

○ Department of Motor Vehicles 

● What is the main reason [S.C.] does 

not have health insurance now? 

(K12Q01)

● What is the main reason that [S.C.]’s 

[Medicaid] enrollment ended? 

(K12Q14)

● What is the main reason that you 

were unable to enroll [S.C.] in 

Medicaid? (K12Q17)

● What is the main reason that [S.C.]’s 

[State CHIP name] enrollment 

ended? (K12Q24)

● What is the main reason that you 

were unable to enroll [S.C.] in 

[STATE CHIP NAME]? (K12Q27)

● What is the main reason you would 

NOT want to enroll [S.C.]? (K12Q36)

● What is the main reason [S.C.] is not 

enrolled in [PROGRAM]? (K12Q37)

● What is the main reason that you 

think [S.C.] is not eligible for 

[PROGRAM]? (K12Q38)

● What is the main reason that [S.C.] 

is not covered by insurance provided 

through this [employer/union/

employer or union]? (K12Q45, 

K12Q55, K12Q65)

For respondents who did not choose 

one of the pre-existing categories 

for the race and ethnicity questions 

(C10Q31, C10Q32X01–C10Q32X08, 

and C10Q32A), three new variables 

were created to capture the verbatim 

response: RACE, RACERECODE, and 

RACEARRAY.
Page 22  Series 1, No. 59

Edits to Protect 

Confidentiality

NCHS takes extraordinary measures 

to ensure that the identity of survey 

subjects cannot be determined. The risk 

of inadvertent disclosure of confidential 

information regarding individual 

respondents is higher with a publicly 

released data set that includes detailed 

geography variables, a detailed and 

extensive set of survey observations, or a 

sizeable proportion of the total population 

of interest. Coarsening a data set by 

suppressing survey variables, collapsing 

multiple variables into one, collapsing 

response categories for other variables, 

or introducing noise in the data are 

common techniques to reduce the risk of 

inadvertent disclosure.

Geography 

Geographic information that would 

identify the specific estimation area in 

states with multiple estimation areas 

has been suppressed. However, state 

identifiers are included. In addition, 

an indicator identifying whether the 

household resides inside or outside of 

a metropolitan statistical area (MSA) 

has been included for some states. 

This indicator, called MSA_STAT, was 

suppressed whenever the total population 

for all MSA areas in a given state was 

less than 500,000 persons, or whenever 

the total population for all of the nonMSA areas in a given state was less than 

500,000 persons. This resulted in the 

suppression of the MSA identifier in 16 

states. 

Due to the suppression of this 

identifier in 16 states, national estimates 

by MSA status are not possible with 

the publicly available NSCH data set, 

and analysts should use caution when 

including this variable in statistical 

models. Analysts may consider using 

imputation to assign an MSA indicator 

to children in states where the indicator 

was suppressed. One option for analyses 

at the national level is to assign MSA 

status to children in states that are 

predominantly metropolitan and to assign 

non-MSA status to children in states that 

are predominantly nonmetropolitan. If 

MSA status is imputed to all children in 

Alaska, Connecticut, Delaware, Hawaii, 

Idaho, Maine, Maryland, Massachusetts, 

New Hampshire, Nevada, and Rhode 

Island, the MSA identifier will be correct 

for 78% of the children (16,339 out of 

20,885). If non-MSA status is imputed to 

all children in Montana, North Dakota, 

South Dakota, Vermont, and Wyoming, 

the MSA identifier will be correct for 

63% of the children (5,755 out of 9,163). 

For weighted analyses, this imputation 

procedure will result in erroneous 

classifications for 1.7% of children 

nationally. 

Race

Question K11Q02 asked about 

the sampled child’s race. Respondents 

were permitted to identify all possible 

categories that described the child’s 

race. If a race other than one of the 

seven existing categories was indicated, 

then a verbatim response was captured. 

Verbatim responses were reviewed and 

matched against a database of alternative 

race terminology maintained by the U.S. 

Census Bureau. Where possible, “other” 

race responses were back-coded into one 

of the seven existing categories. Once all 

possible verbatim responses were backcoded, a new race variable was created by 

collapsing the seven categories into one 

of six categories: white, black or African 

American, American Indian or Alaska 

Native (AIAN), Asian, Native Hawaiian 

or Other Pacific Islander (NHOPI), and 

multiple race. Multiple race was reserved 

for those cases where more than one of 

the other five categories applied. 

To protect the confidentiality of 

individual respondents and children, 

responses for the race variable were 

further collapsed into four categories: 

white only, African American or black 

only, other race, and multiple race. The 

“other race” category includes children 

for whom only one of the other three 

categories (Asian, AIAN, or NHOPI) was 

reported. Children for whom more than 

one race was identified (for example, 

Asian as well as NHOPI) were included 

in the multiple race category. If the 

respondent did not know or refused to 

provide the race, then race was coded 

as missing. Cases where a verbatim 

response could not be conclusively 

back-coded (for example, American, 

Indian, or Jewish), and no other race was 

reported, were also coded as missing. 

This new derived race variable (called 

RACER) is the only classification publicly 

available for all 50 states and D.C. 

In several states, however, minority 

group populations are sufficiently 

large that the release of additional race 

categories was possible while still 

protecting the confidentiality of the 

respondents and children. To identify 

these states, data from the American 

Community Survey (ACS) were 

examined to identify minority groups 

that comprise at least 5% of the total 

population of children in a specific 

state. Based on this criterion, the data 

files identify AIAN children in Alaska, 

Arizona, Montana, New Mexico, North 

Dakota, Oklahoma, and South Dakota. 

This race classification variable is called 

RACEAIAN. Asian children’s race 

is reported for children in California, 

Hawaii, Maryland, Massachusetts, 

Minnesota, Nevada, New Jersey, New 

York, Virginia, and Washington. This 

race classification variable is called 

RACEASIA. The data file identifies both 

Asian children and NHOPI children in 

Hawaii, using the race classification 

variable called RACE_HI. 

Note that national estimates for 

AIAN, Asian, and NHOPI children are 

not possible using the publicly available 

NSCH data set. Children with these race 

classifications are identified in selected 

states only. These race classifications 

were suppressed in other states for 1,084 

AIAN children, 1,439 Asian children, and 

350 NHOPI children. Nationally, children 

with suppressed race classifications 

represent 65.5% of AIAN children, 

38.8% of Asian children, and 85.9% of 

NHOPI children. 

Language 

Question K1Q03 collected data 

on the primary language spoken in 

the household. Of the 7,451 children 

living in households with a non-English 

language as the primary language, 71.9% 

(n = 5,359) lived in Spanish-language 

households. Of the remaining nonEnglish-language households, 488 (6.5%) 

spoke one of the four Asian languages in 
Series 1, No. 59  Page 23 

which the interview was conducted, and 

1,604 (21.5%) spoke another language. 

To protect confidentiality, the specific 

language spoken in non-English language 

households, and the specific language 

used for any non-English interview 

(OTH_LANG), have been suppressed. 

Height and weight 

To protect the confidentiality of 

individual children, specific height and 

weight have been suppressed in the 

public data file. In their place, a fourcategory variable identifying underweight 

and overweight children (BMICLASS) 

has been added to the data set. Children 

aged 10–17 years have been identified 

as having a BMI-for-age that is 1) equal 

to the 5th percentile or lower, 2) greater 

than the 5th percentile but lower than 

the 85th percentile, 3) equal to the 85th 

percentile or greater but lower than the 

95th percentile, or 4) equal to the 95th 

percentile or greater. Percentiles are 

based on sex and age. For example, if 

the value of a child’s BMI is equal to the 

95th percentile, then that child is among 

the 95% of children of that age and 

sex whose BMI is equal to or less than 

that value. Percentiles were determined 

using the CDC growth charts and a SAS 

statistical analysis software program 

provided online by CDC (a version of 

this SAS program, updated in 2016, is 

available online) (18). However, this 

program relies on the child’s age in 

months; because age was reported only 

in years for this survey, children were 

assumed to be at the midpoint of the 

age–year (that is, a child aged 10 years 

was assumed to be aged 126 months) for 

purposes of calculating BMI-for-age. 

Height and weight were based on 

parent report and were not independently 

measured. Researchers attempting 

to validate parent report of height 

and weight in the 2003 NSCH have 

concluded that parent-reported data 

should not be used to estimate overweight 

prevalence among preschool-aged 

and elementary school-aged children 

(19). Parents’ reports significantly 

underestimated height; as a result, too 

many young children were classified 

as overweight in the 2003 NSCH. 

Due to concerns about the validity of 

the 2011–2012 data, calculated BMI 

categorizations (BMICLASS) have been 

suppressed for children under age 10 

years. 

Family structure 

To protect the confidentiality of 

individual children whose families have 

unique structural characteristics, a single 

measure of family structure and parental 

marital status (FAM_MAR_COHAB) 

was created from C10Q02A, C10Q02B, 

and C10Q10–C10Q13C. This variable 

refers to parents living in the household 

and has nine levels: 1) two-parent 

household with both a biological or 

adoptive mother and a biological or 

adoptive father who are currently 

married; 2) two-parent household with 

both a biological or adoptive mother 

and a biological or adoptive father 

who are currently cohabiting; 3) twoparent household with both a mother 

and a father who are currently married 

and at least one is a stepparent to the 

child; 4) two-parent household with 

both a mother and a father who are 

currently cohabiting and at least one is 

a stepparent to the child; 5) one-parent 

household with a biological, step, foster, 

or adoptive mother and no father of any 

type present, and the mother is currently 

married and living apart from her spouse 

or is formerly married; 6) one-parent 

household with a biological, step, foster, 

or adoptive mother and no father of any 

type present, and the mother is never 

married; 7) other family structures where 

the parent(s) are currently or formerly 

married; 8) other family structures where 

the parent(s) are never married; and 9) 

other family structures with no parents 

in the household. Any of these family 

structures may include other people who 

serve as parents, such as grandparents, 

aunts, uncles, or unmarried partners of 

the parents. Legal guardians were not 

considered to be mothers or fathers.

Other Derived and 

Collapsed or Topcoded 

Variables 

Some variables have been recoded 

for inclusion in the public data file, either 

by combining information from multiple 

raw variables in to a new derived variable 

or by collapsing, topcoding, or otherwise 

coarsening a single variable into fewer or 

less detailed categories. The definitions of 

these variables follow. An “R” appended 

to the end of the variable name indicates 

that a recode of some kind has occurred, 

and analysts should consult the codebook 

of frequencies released with the public 

data file to understand the differences 

between the questions asked in the 

questionnaire and the variables available 

in the public data. 

AGEPOS4—This variable uses 

information from the rostering of children 

in the household to categorize the birth 

position of the focal child.

C10Q14R—C10Q14 bottom-coded 

at 22 or younger and topcoded at 85 or 

more.

CSHCN—This variable uses 

information from variables K2Q10–

K2Q23 to indicate whether a child has 

special health care needs.

EDUC_MOMR—This variable, 

based on K11Q20, reports the highest 

level of school that the sampled child’s 

mother in the household has achieved, 

categorized in three levels: less than high 

school, high school, or more than high 

school.

EDUC_DADR—This variable, 

based on K11Q21, reports the highest 

level of school that the sampled child’s 

father in the household has achieved, 

categorized in three levels: less than high 

school, high school, or more than high 

school.

EDUC_RESR—This variable, 

based on K11Q22, reports the highest 

level of school that the sampled child’s 

nonparent respondent in the household 

has achieved, categorized in three levels: 

less than high school, high school, or 

more than high school.

EDUC_PARR—This variable, based 

on K11Q20, K11Q21, and K11Q22, 

reports the highest level of school that 

the sampled child’s mother, father, or 

nonparent respondent in the household 

has achieved, categorized in three levels: 

less than high school, high school, or 

more than high school.

HISPANIC—This variable, based 

on K11Q01 updated with back-coding 

from “other” race responses recorded in 
Page 24  Series 1, No. 59

K11Q02_OS, indicates whether a child is 

of Hispanic or Latino origin. 

HOUSE_GEN—This variable uses 

information from K11Q30, K11Q31, and 

K11Q32 to categorize household-level 

immigrant generational status. Firstgeneration households include those 

in which the child was born outside 

the United States (except for children 

adopted from other countries, who are not 

considered immigrants), while secondgeneration households are those in which 

one or both resident parents were born 

outside the United States but the child 

was born in the United States. 

K11Q03R—This variable, based 

on K11Q03, has been suppressed in 

the public data file for all states except 

Alaska, Arizona, Montana, New Mexico, 

North Dakota, Oklahoma, and South 

Dakota. 

K11Q43R—K11Q43 topcoded at 12 

or more.

K12Q13R—K12Q13 standardized to 

months.

K12Q16R—K12Q16 standardized to 

months.

K12Q23R—K12Q23 standardized to 

months.

K12Q26R—K12Q26 standardized to 

months.

K2Q04R—K2Q04 standardized to 

ounces.

K4Q20R—K4Q20 topcoded at 20 or 

more.

K4Q21R—K4Q21 topcoded at 12 or 

more.

K6Q41R—K6Q41 standardized to 

age in days and topcoded at 1,095 or 

more.

K6Q42R—K6Q42 standardized to 

age in days.

K6Q43R—K6Q43 standardized to 

age in days.

K7Q02R—K7Q02 topcoded at 40 or 

more.

K7Q04R—K7Q04 topcoded at 25 or 

more.

K7Q05R—This variable uses 

information from K7Q05 and K7Q05_A 

to indicate the most recent grade of 

school that was repeated.

K8Q12R—K8Q12 recoded into the 

following categories: never, at least once 

a year but less than once a month, at least 

once a month but less than once a week, 

at least once a week but less than daily, 

and daily.

K9Q16R—K9Q16 bottom-coded 

at 20 or younger and topcoded at 59 or 

more.

MULT_REPEATS—This variable 

uses information from K7Q05 and 

K7Q05_A to indicate whether the child 

had repeated more than one grade of 

school.

NUMB_SERVICES—This variable 

sums the number of health care services 

the child needed as recorded in section 

4, subdomain 2, of the questionnaire 

(S4Q01–K4Q35).

POVERTY_LEVELR—This 

variable is based on total household 

members (K9Q00) and the household 

income value. If data for either of 

these components are missing, refused, 

or had a “don’t know” response, this 

variable is assigned a missing value. 

Once an income-to-household-size 

measure is computed, it is compared 

with HHS federal poverty guidelines 

(Appendix VII). This variable is based on 

POVERTY_LEVEL, collapsing the nine 

categories into eight.

RELATION—This variable, based 

on question C10Q02A, describes the 

relationship between the respondent and 

the child selected for the interview.

SAMPLE—This variable indicates 

the telephone sample type (i.e., landline 

or cell phone).

SEX—This variable, based on 

K1Q01, specifies the child’s sex. 

SUMMER—This variable uses 

date of interview to indicate whether the 

interview was completed in June, July, or 

August.

STATE—This variable, based on 

sampling state, is updated to true state 

when respondent-reported zip code at 

C11Q22 indicated that the telephone 

number had been migrated to a household 

in a different state.

TOTADULT3—This variable 

is based on the difference between 

K9Q00 (total people in household) and 

TOTKIDS (total children in household). 

It gives the total number of adults in the 

household and equals .M if one or both 

of the variables K9Q00 and TOTKIDS 

equal “don’t know,” refused, or missing. 

This variable has been topcoded at 3 or 

more.

TOTKIDS4—This is a categorical 

variable that indicates the number of 

children in the household and has been 

topcoded at 4 or more.

Dummy Variables

When respondents were permitted 

to provide multiple answers for the same 

question, a variable was created for each 

possible answer. The values for these new 

dummy variables are “yes, this answer 

was given” and “no, this answer was not 

given.” When respondents could not or 

did not provide an answer to the question, 

a value of “don’t know” or refused was 

reported for each of the dummy variables.

● K4Q28 is represented by 

K4Q28X01–K4Q28X05.

● K4Q32 is represented by K4Q32X01–

K4Q32X07.

Additional Data Notes

● NSCH partial completes occur 

where the NIS–Child or NIS–Teen 

interview was fully completed. 

Where applicable, responses 

from NIS–Child or NIS–Teen 

questions have been used to fill the 

corresponding NSCH responses.

● Upon beginning Section 12, a small 

number of respondents indicated 

that they misspoke earlier in the 

survey and did, in fact, have health 

coverage for the selected child. For 

these cases, Section 3 and Section 

12 insurance variables were updated 

accordingly in postprocessing. This 

resulted in several variables from 

Section 3 being coded as missing in 

error.

● To accommodate the new cell-phone 

screening approach, changes were 

made to the cell-phone questions 

between Q1/2011 and Q2/2011. First, 

SL_LANDLINE and SL_CELLUSE 

were added in Q2/2011 to collect 

cell-phone status from all cellphone respondents. In Q1/2011, 

landline-only cases skipped C11Q16; 

however, starting in Q2/2011, both 

landline-only and cell phone-only 

cases skipped C11Q16. Finally, in 

Q1/2011, both cell phone-only (CPO) 

and cell phone-mainly (CPM) cases 

skipped C11Q20; however, starting 
Series 1, No. 59  Page 25 

in Q2/2011 (and continuing through 

Q1/2012), only CPO cases skipped 

C11Q20.

● During data review, special attention

was given to the telephone section

within Section 13 for cell-phone

sample. This review identified a

number of cell-phone cases that

indicated having no cell phones

at C11Q15_CELL or having no

adults who usually use the cell

phones in the household at C11Q15_

CELL_USUALLY. Cases that were

identified to have been minor-only

or business-only cell phones were

removed from the interview file.

Corrections to C11Q15_CELL

resulted in a number of cases in

C11Q15_CELL_USUALLY and

C11Q16 being set to missing in error.

● Skip logic for K9Q19 changed from

Q1/2011 to Q2/2011. In Q1/2011,

K9Q19 asked if there was no mother

or father of any type in the household

but did include any older relative

or guardian (i.e., grandmother or

grandfather, aunt or uncle, or male

or female guardian). In Q2/2011, the

logic was modified such that K9Q19

asked if there was no mother or

father of any type in the household

but did include any older relative

or guardian and C10Q02C was not

equal to “1.”

Quality Control

Using the questionnaire 

specifications, NORC project staff 

produced several programs to review 

the data and identify data items that 

required cleaning. These programs 

were also used during data collection to 

monitor production. The programming 

team developed cleaning programs 

so that the resulting cleaned data file 

could be replicated and reviewed by 

others. These programs applied any 

final data corrections based on data 

recovery, checked that skip patterns were 

followed, created derived variables from 

questionnaire variables, and assigned 

special codes to reflect various missing 

data.

Project staff then ran numerous 

quality control checks on the cleaned data 

file. Variable frequencies were reviewed 

to confirm skip patterns, missing code 

assignments, and expected distributions. 

Derived variable specifications and 

computations were carefully reviewed. 

Variable labels were compared against 

the questionnaire to confirm accurate 

label assignments.

The cleaning programs were run on 

each new version of the data file until no 

problems were identified in the quality 

control checks. 

Procedures for 

Developing Sampling 

Weights

This section provides a nontechnical

overview of the weighting procedures for

the 2011–2012 NSCH. A more detailed

and technical description is in Appendix I.

Base Sampling Weights

The landline telephone and cellphone lines selected for screening for the 

2011–2012 NSCH represent a random 

sample of all possible landline and cellphone lines in each geographic area. 

The probability that any given landline 

or cell-phone line was selected from 

the population of all possible landline 

and cell-phone lines was calculated by 

dividing the number of telephone lines 

selected for the study by the total number 

of telephone lines in a given sampling 

area by sample type (landline or cell 

phone).

Each landline or cell-phone line 

selected for the 2011–2012 NSCH 

represented some larger number of 

telephone lines in the geographic area. 

This number was calculated as the 

inverse of the probability of selection 

for any telephone line within sample 

type. This number became the base 

weight associated with each completed 

household interview in that geographic 

area within sample type. Base weights 

varied by geographic areas and sample 

type.

Derivation of Annual 

Sampling Weight

The quarterly weights were adjusted 

so that the samples from all quarters 

jointly represented the corresponding full 

population. Because the weights were 

calculated for each quarter separately, 

the sum of base weights in each quarter 

represented the full population for each 

state within sample type. The weights 

were adjusted by the released sample size 

within each quarter (i.e., quarters with 

larger released sample sizes represented 

a larger portion of the annual sampling 

weight). 

 Adjustment for 

Nonresolution of Released 

Telephone Lines

When the selected landline and cellphone numbers were called, three results 

were possible:

1. It was determined that the telephone

number belonged to a household or

an active personal cell-phone number

(APCN).

2. It was determined that the telephone

number was not a working

residential number or APCN (i.e., a

business number or a nonworking

number).

3. The status was undetermined

because the telephone rang without

an answer, the person answering the

telephone hung up immediately, or

the telephone-answering device did

not indicate whether the telephone

line belonged to a household.

The last category likely included

some household telephone lines, but 

the exact number in this category was 

unknown. The completed household 

interviews needed to represent the 

households in this unknown category. 

The size of the adjustment depended 

on the size of the unknown category 

after all telephone numbers had been 

called several times. This adjustment 

varied based on sample type, geographic 

area, proportion of owners or renters, 

proportion of population that is minority, 

median household income level, 

median education level, median age, 
Page 26  Series 1, No. 59

MSA status, and whether the telephone 

line was directory-listed. Based on 

the frequency of the nonresponse in a 

given area, compensation was made 

for this nonresponse separately for the 

landline and cell-phone samples by 

proportionately increasing the weights 

for those interviews that were completed 

in that area, so that the completed 

interviews represented the households in 

the unknown category.

Adjustment for Incomplete 

CPO/M Screener

In Quarter 1, 2011, the cellphone sample was released for NSCH. 

This sample was screened to include 

only those numbers associated with 

households that had no landline telephone 

(CPO) or where the respondent was 

unlikely to answer the landline (CPM). 

When a cell-phone sample household was 

identified, three results were possible:

1. It was determined that the respondent 

was living in a cell phone-only/

mainly or CPO/M household and 

was eligible for further screening.

2. It was determined that the 

respondent was not living in a 

CPO/M household and was not 

eligible.

3. The screening interview was not 

completed, and the eligibility of the 

household was unknown.

The last category included some 

CPO/M households, however, the 

exact number of CPO/M households 

in this category was unknown. The 

completed cell-phone sample household 

interviews needed to represent the 

CPO/M households in this unknown 

category for the cell sample. The size 

of the adjustment was based on the 

size of the first two categories. The 

proportion of CPO/M households in the 

unknown category was assumed to be 

the same as the proportion of CPO/M 

households among all households where 

the screening interview for CPO/M 

was completed. This adjustment varied 

based on geographic area and MSA 

status. Based on the frequency of 

nonresponse to the CPO/M screening 

interview in a given area and a given 

sample, compensation was made for 

this nonresponse by proportionately 

increasing the weights for those 

interviews that were completed in that 

area, thus representing the CPO/M 

households in the unknown category. 

No adjustment was calculated for the 

cell-phone sample in the remaining 

quarters (Quarter 2, Quarter 3, Quarter 4, 

2011, and Quarter 1, 2012), the landline 

sample, or USVI. 

Adjustment for Incomplete 

S_KIDS Screener

In Quarter 3, 2011; Quarter 4, 2011; 

and Quarter 1, 2012, the cell-phone 

augmentation sample had an additional 

screener implemented only for this 

portion of the sample. After the standard 

NSCH introduction, the first question 

asked was, “Are there any children living 

in your household?” When a household 

had been identified in the cell-phone 

augmentation sample, three results were 

possible:

1. It was determined that the household 

includes a child and was eligible for 

further screening.

2. It was determined that the household 

does not include a child and was not 

eligible.

3. The screening interview was not 

completed, and the eligibility of the 

household was unknown.

The last category included some 

child-eligible households, however, the 

exact number of child-eligible households 

in this category was unknown. The 

completed household interviews needed 

to represent the child-eligible households 

in this unknown category. The size of 

the adjustment was based on the size of 

the first two categories. The proportion 

of child-eligible households in the 

unknown category was assumed to be 

the same as the proportion of childeligible households among all households 

where the screening interview for the 

presence of children was completed. 

This adjustment varied based on 

geographic area and MSA status. Based 

on the frequency of nonresponse to the 

child-eligible screening interview in 

a given area, compensation was made 

for this nonresponse by proportionately 

increasing the weights for those 

interviews that were completed in that 

area, thus representing the child-eligible 

households in the unknown category. 

No adjustment was calculated for the 

landline sample, USVI, or NIS cell 

sample.

Adjustment for Incomplete 

Age-eligibility Screener

For all non-cell-phone augmentation 

sample (all landline sample including 

USVI and NIS cell-phone sample), age 

eligibility was determined by a question 

that asked for the number of people under 

age 18 living or staying in the household. 

When a household was identified, three 

results were possible:

1. It was determined that the household 

included an age-eligible child.

2. It was determined that the household 

did not include a child and was not 

eligible.

3. The screening interview was not 

completed, and the eligibility of the 

household was unknown.

The last category included some 

age-eligible households, however, the 

exact number of age-eligible households 

in this category was unknown. The 

completed household interviews needed 

to represent the age-eligible households 

in this unknown category. The size 

of the adjustment was based on the 

size of the first two categories. The 

proportion of age-eligible households in 

the unknown category was assumed to 

be the same as the proportion of ageeligible households among all households 

where the screening interview for the 

presence of children was completed. This 

adjustment varied based on geographic 

area, proportion of the population from 

minorities, MSA status, number of call 

attempts to resolution (cell sample only), 

median age, and whether the telephone 

number was directory-listed within 

sample type. Based on the frequency of 

nonresponse to the age-eligible screening 

interview in a given area and a given 

sample, compensation was made for 

this nonresponse by proportionately 

increasing the weights for those 
Series 1, No. 59  Page 27 

interviews that were completed in that 

area, thus representing the age-eligible 

households in the unknown category.

Adjustment for 

Subsampling of Children 

Within Households

One child was randomly selected 

from among all children in the household 

to be the subject of the NSCH interview. 

In households with multiple eligible 

children, the randomly selected child 

represented all of the nonselected 

children in the household. Therefore, 

the sampling weight for the completed 

interview was increased to reflect the fact 

that the completed interview represented 

multiple children in that household. This 

adjustment multiplied the adjusted child 

weight by the number of eligible children 

in the household. 

Adjustment for 

Nonresponse to NSCH 

Interview

When a child had been sampled, two 

results were possible:

1. An interview was completed.

2. An interview was not completed.

The completed child interviews 

needed to represent the children who 

were sampled but had not completed the 

interview. The size of the adjustment was 

based on the size of the two categories 

and calculated as the ratio of the total 

number of sampled children to the 

number of completed interviews. In 

other words, based on the frequency of 

nonresponse among sampled children in 

a given area, compensation was made 

for this nonresponse by proportionately 

increasing the weights for those 

interviews that were completed in 

that area. The completed interviews, 

therefore, represented the sampled 

children with incomplete interviews.

Adjustment for Households 

With Multiple Cell-phone 

Lines

Among the households that 

completed the interview within the cell 

sample, some reported more than one 

cell-phone line for personal use by adults. 

An adjustment to the weight was required 

for these households to compensate 

for their multiple chances of selection. 

This adjustment divided the adjusted 

interview weight by the number of 

personal cell-phone lines used by adults 

in the household. This approach excluded 

lines used solely by minors, and was not 

applied to the landline sample or USVI. 

Trimming of Extreme 

Weights

Within the cell-phone sample, 

significant movement occurred from 

sample state to respondent-reported state 

because the area code of the cell-phone 

number did not sufficiently indicate the 

true state of residence in many cases. As 

a result, when the sample was stratified 

by true state, large variability occurred 

in the weights due to cases sampled from 

State A (sample state) being combined 

with cases from State B (respondentreported state). Therefore, extreme 

weights were trimmed to reduce the 

variability of the weights.

Adjustment for Combined 

Landline and Cellphone Samples and for 

Noncovered Populations

The full-sample household weights 

were adjusted within each state to 

accomplish these goals:

1. Adjustment for noncoverage of ageeligible children.

2. Adjustment for overlap of the 

landline and cell-phone samples.

3. Adjustment to residual landline 

population controls.

4. Adjustment to residual cell phoneonly population controls.

5. Trimming of extreme weights.

Adjustment for noncoverage of ageeligible children. A Keeter adjustment 

(20) was carried out to adjust weights 

to account for households with children 

not covered by the combined landline 

and cell-phone samples (i.e., phoneless 

households). In the Keeter adjustment, 

weights for landline households with 

an interruption in telephone service 

were adjusted to represent phoneless 

households with children. The method 

was based on empirical evidence 

suggesting that landline households with 

an interruption in telephone service are 

more similar to phoneless households 

than are households with no interruptions, 

with respect to the variables under study 

(20,21). 

Adjustment for overlap of the 

landline and cell-phone samples. The 

landline and cell-phone samples, while 

selected from distinct sampling frames, 

partially overlapped in their coverage 

of the population. The landline sample 

included dual landline and cell-phone 

households, while the cell-phone sample 

also included dual landline and cellphone households. Thus, survey weights 

for dual landline and cell-phone cases 

from the two sampling frames were 

adjusted to account for this overlap. 

Adjustment to residual landline 

population controls. A ratio adjustment 

was carried out to adjust weights to 

population controls for the residual set of 

landline-only households with children. 

Adjustment to residual cell phoneonly population controls. A ratio 

adjustment was carried out to adjust 

weights to population controls for 

the residual set of cell phone-only 

households with children. 

Poststratification of Child 

Interview Weight

Despite the weighting efforts and 

nonresponse adjustments, the estimated 

number of children was unlikely to 

match the population sampled. Any 

discrepancies were likely to be due to 

random sampling error and nonrandom 

response biases. These biases included 

increased nonresponse based on age, sex, 

or race of the child. Poststratification 

adjusted the weights to match population 
Page 28  Series 1, No. 59

control totals for key demographic 

variables obtained from an independent 

source. For the child interview weight, 

the independent source was the 2011 

ACS count of children, stratified by sex, 

age, and race and ethnicity. The following 

demographic subgroups were used as 

population control totals: 

● Number of male and female children 

in five age groups: 0–2 years, 3–5 

years, 6–8 years, 9–12 years, and 

13–17 years.

● Number of children of various racial 

and ethnic backgrounds: Hispanic; 

non-Hispanic Asian, Hawaiian, 

or Pacific Islander; non-Hispanic 

American Indian or Alaska Native; 

and children of all other backgrounds 

including non-Hispanic white and 

multiple-race children (categories 

with small number of cases were 

collapsed with the predominant race 

category within each state).

● Number of children in one-child 

households, two-child households, 

and three-plus-child households.

● Number of children in households 

that had a household income of: 

less than $10,000, $10,000–$19,999, 

$20,000–$39,999, $40,000–$59,999, 

or $60,000 or more.

● Number of children in households 

where the highest reported education 

of parents was: less than a high 

school education, high school, or 

more than high school.

● Number of children in owneroccupied households, renter-occupied 

households, or in neither owner- nor 

renter-occupied households (in 

another arrangement).

● Number of children in households 

by telephone status: CPO, CPM, All 

Other (AO).

Extremely large weights were 

truncated to prevent a small number of 

cases with large weights from having 

undue influence on the estimates. The 

technical appendix (Appendix I) 

describes how the weights were 

truncated.

For USVI, detailed population 

control totals were not available, because 

ACS was not conducted in USVI and 

the detailed 2010 census files had not 

been released at the time of weighting. 

The 2010 census totals for age group 

by sex were available, however, and a 

post-stratification was done using those 

results. The age groups used for USVI 

are: 0–4 years, 5–9 years, 10–14 years, 

and 15–17 years.

Quality Control

Staff compared the formulas for the 

weights and adjustments developed by 

the sampling statistician with the actual 

weights and adjustments constructed by 

the statistical programmer. Thorough 

review of both programs and data outputs 

were reviewed by senior statisticians for 

accuracy. In addition, univariate statistics 

were produced and reviewed for the 

adjustments and weights. 

Estimation and 

Hypothesis Testing

NSCH data were obtained through 

a complex sample design involving 

clustering of children within households, 

stratification of households within states, 

and separate sample frames for landline 

telephone and cell-phone numbers. To 

produce estimates representative of 

children nationally and within each state, 

sampling weights must be used. These 

sampling weights account for the unequal 

probability of selection of each household 

and child, and they include adjustments 

for multiple-telephone households, 

unit nonresponse, and noncoverage of 

nontelephone households, as well as 

adjustments to known population control 

estimates. As described earlier, a single 

sampling weight (NSCHWT) has been 

developed for NSCH. This weight should 

be used for both national and state-level 

analysis.

Interpretation of Weighted 

Estimates

Estimates based on the sampling 

weights generalize only to the population 

of U.S. noninstitutionalized children 

aged 0–17 years at the time of interview. 

These estimates do not generalize to 

the population of parents, mothers, or 

children’s health care providers. 

Two examples may help make this 

distinction clearer. Weighted estimates 

based on K8Q11 can be interpreted as 

the proportion of children whose families 

regularly eat meals together, but should 

not be interpreted as the proportion 

of families who regularly eat meals 

together. Similarly, weighted estimates 

based on K8Q30 can be interpreted as 

the proportion of children whose parents 

are coping well with the demands of 

parenthood, but should not be interpreted 

as the proportion of parents who are 

coping well.

Variables Used for Variance 

Estimation

Because of the complex design 

of NSCH, the interviewed cases have 

unequal weights. Therefore, statistical 

software programs that assume simple 

random sampling will most often 

compute standard errors that are too low. 

Tests of statistical hypotheses may then 

suggest statistically significant differences 

or associations that are misleading. 

However, computer programs are 

available that provide the capability of 

variance estimation for complex sample 

designs (e.g., SUDAAN, Stata, WesVar). 

To provide the user with the capability of 

estimating the complex sample variances 

for the NS–CSHCN data, sample type 

and stratum identifiers and primary 

sampling unit (PSU) codes are provided 

on the data files. These variables and the 

sample weights are necessary to properly 

calculate variances.

The stratum identifiers reported 

on the data set are not identical to the 

strata used to draw the main sample. In 

states with multiple estimation areas, 

independent samples were selected from 

each estimation area in proportion to the 

total number of households with children 

in each estimation area. Therefore, these 

estimation areas should be considered 

strata for variance estimation. However, 

disclosure of the specific estimation area 

for each child (even if the code were 

scrambled) could increase the risk of 

disclosure of a respondent’s identity. In 

the absence of estimation area-specific 

identifiers, data users should use the 
Series 1, No. 59  Page 29 

state identifier (STATE) as the stratum 

identifier. By using the state identifier 

rather than the suppressed estimation area 

identifier, standard errors for national 

and state estimates with key variables 

are affected only slightly and not in a 

consistent direction. The PSU for NSCH 

is the household, represented on the data 

sets by the unique household identifier, 

IDNUMR. The sample type (landline or 

cell phone) is represented on the data sets 

by the identifier SAMPLE. 

The overall number of persons in this 

survey is sufficient for most statistical 

inference purposes. However, analyses 

of some rare responses and analyses of 

subclasses can lead to estimators that are 

unreliable. Small sample sizes used in the 

variance calculations may also produce 

unstable estimates of the variances. 

Consequently, these analyses require 

that the user pay particular attention to 

the variability of estimates of means, 

proportions, and totals.

Variance Estimation Using 

SUDAAN or Stata

Standard errors of estimates from 

NSCH can be obtained using the Taylorseries approximation method, available 

in software such as SUDAAN, SAS, and 

Stata. The state and sample type should 

be identified as stratum variables, and 

the household should be identified as 

the PSU. The simplifying assumption 

that PSUs have been sampled with 

replacement allows most complex survey 

sample design computer programs to 

calculate Taylor-series standard errors 

in a straightforward way. This method 

requires no recoding of design variables 

but is statistically less efficient (and 

therefore more conservative) than 

some other methods, because the PSU 

unit is treated as being sampled with 

replacement within the stratum unit. 

For SUDAAN, the data file needs to 

be sorted by stratum (STATE), sample 

type (SAMPLE), and PSU (IDNUMR). 

The default number of stratum and 

PSU variables to be included in the 

NEST statement is two; because three 

such variables occur here, the PSULEV 

statement is included to indicate that 

PSU is the third variable in the list. The 

following SUDAAN design statements 

are then used for analyses at the 

household level:

PROC . . . DESIGN = WR;

NEST STATE SAMPLE IDNUMR / 

PSULEV = 3;

WEIGHT NSCHWT;

For Stata, the following design 

statements are used. Because Stata only 

allows for a single strata variable, STATE 

and SAMPLE should first be combined 

into a single variable with (51 × 2 = 102) 

levels (here called STATESAMP):

svyset strata STATESAMP

svyset psu IDNUMR

svyset pweight NSCHWT

svyset

Other variance estimation procedures 

are also applicable to NSCH. Specifically, 

the jackknife method with replicate 

weights, and the bootstrap resampling 

method with replicate weights, can also 

be used (via software such as WesVar) to 

obtain standard errors that fully reflect 

the impact of the weighting adjustments 

on standard errors.

Variance Estimation for 

Subsets of Data

Many analyses of NSCH data will 

focus on specific population subgroups, 

such as children in only one state or 

living in poverty. Some analysts will 

therefore be tempted to delete all records 

outside of the domain of interest in 

order to work with smaller data files 

and run computer jobs more quickly. 

This procedure of keeping only selected 

records and listwise deleting other 

records is called subsetting the data. 

Subsetted data that are appropriately 

weighted can be used to generate 

correct point estimates (e.g., estimates 

of population subgroup frequencies or 

means), but many software packages 

that analyze complex survey data will 

incorrectly compute standard errors for 

subsetted data. When complex survey 

data are subsetted, the sample design 

structure is often compromised because 

the complete design information is not 

available. Subsetting the data can delete 

important design information needed 

for variance estimation (e.g., deleting all 

records for certain subgroups may result 

in entire PSUs being removed from the 

design structure). 

The NSCH sample was designed to 

provide independent data sets for each 

of the 50 states and D.C. Subsetting the 

survey data to a particular state does not 

compromise the design structure of the 

survey. That is, standard errors calculated 

in SUDAAN for a particular state will 

not be affected if the data set has been 

subsetted to that particular state.

However, subsetting to specific 

population subgroups (within or across 

states) can result in incorrect standard 

errors. For example, subsetting the data to 

those children who live in poverty within 

a specific state will result in incorrectly 

calculated standard errors. Typically, 

the standard errors for subsetted data 

will be inflated, resulting in a higher 

probability of type-II error (i.e., failing to 

detect significant differences that do, in 

fact, exist). SUDAAN has a SUBPOPN 

option that allows the user to target 

specific subpopulations for analysis 

while retaining the full unsubsetted data 

set that includes the full sample design 

information; Stata has a similar option 

called SUBPOP. Analysts interested in 

specific population subgroups must use 

these subpopulation options rather than 

subsetting the data sets.

Weighted Frequencies, 

Prevalence Estimates, and 

Standard Errors

Unweighted and weighted estimates 

of the frequency and prevalence of 

children with excellent or very good 

health as assessed by the survey 

respondent appear in Appendix XV. 

Weighted frequencies, prevalence 

estimates, and standard errors for other 

survey measures are available from the 

Data Resource Center for Child and 

Adolescent Health. This online center is 

led by the Child and Adolescent Health 

Measurement Initiative and is supported 

through a cooperative agreement with 

MCHB. The data resource center 

is accessible from: https://www.

childhealthdata.org.
Page 30 Series 1, No. 59

Guidelines for 

Data Use

With the goal of mutual benefit, 

NCHS requests that recipients of 

data files cooperate in certain actions 

related to their use. Any published 

material derived from the data should 

acknowledge NCHS as the original 

source. The suggested citation, “Data 

Source: National Center for Health 

Statistics, State and Local Area Integrated 

Telephone Survey, National Survey of 

Children’s Health, 2011–2012,” should 

appear at the bottom of all tables and 

figures. Published material derived from 

the data should also include a disclaimer 

that credits any analyses, interpretations, 

or conclusions reached to the author 

and not to NCHS, which is responsible 

only for the initial data. Consumers who 

wish to publish a technical description 

of the data should make a reasonable 

effort to ensure that the description is 

consistent with that published by NCHS. 

A disclaimer should also be including 

crediting any analyses, interpretations, 

or conclusions reached to the author(s) 

(i.e., recipients of the data file). NCHS 

and SLAITS are responsible only for the 

initial data. 

Using the acronyms NSCH and 

SLAITS in titles, keywords, and 

abstracts of journal articles, documents, 

PowerPoint slides, and publications 

facilitates retrieval in bibliographic 

searches. 

CIPSEA and the Public Health 

Service Act (Section 308d) provide 

that these data collected by NCHS may 

be used only for the purpose of health 

statistical reporting and analysis. Any 

effort to determine the identity of any 

reported case is prohibited by these laws. 

NCHS takes extraordinary measures to 

assure that the identity of survey subjects 

cannot be disclosed. All direct identifiers, 

as well as any characteristics that might 

lead to identification, have been omitted 

from the data set. Any intentional 

identification or disclosure of a person or 

establishment violates the assurances of 

confidentiality given to the providers of 

the information. Therefore, users must:

● Use the data in this data set for

statistical reporting and analysis

only.

● Make no use of the identity of any

person discovered, inadvertently or

otherwise, and advise the director

of NCHS of any such discovery

(301–458–4500).

● Not link this data set with

individually identifiable data from

any other NCHS or non-NCHS data

sets.

Use of the data set signifies users’ 

agreement to comply with the abovestated statutory-based requirements. 

Further Information

Data users can obtain the latest 

information about SLAITS by 

periodically checking the SLAITS 

website: https://www.cdc.gov/nchs/slaits.

htm. This site features downloadable 

data files and documentation for 

SLAITS modules, as well as important 

information about any modifications 

and updates to data or documentation. 

Data users will also find current contact 

information for any additional questions. 

Data users with questions may also send 

an e-mail to slaits@cdc.gov.

Note, however, that SLAITS staff 

cannot respond to questions about 

individual medical cases, provide second 

medical opinions, or make specific 

recommendations regarding therapy. 

These issues should be addressed directly 

with personal health care providers.

References

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Page 32  Series 1, No. 59

Appendix I. Sampling and Weighting Technical Summary

Sample Design

The basic design objective of the 

National Survey of Children’s Health 

(NSCH) sample was to select a sample 

to achieve 1,800 completed interviews 

of children under age 18 years in each 

state and Washington, D.C. (D.C.). Of 

the 1,800 completed interviews, 600 

were targeted to be completed from 

cell-phone lines. The landline telephone 

and cell-phone samples were selected by 

first identifying households with children 

under age 18. For households with 

children, the ages of all children living 

or staying in the household were then 

rostered. If a household had only one 

child, that child was selected as the focus 

of the interview by default. In households 

with multiple children, one child was 

randomly selected by the computerassisted telephone interview (CATI) 

system to be the focus of the interview. 

Drawing National Immunization 

Survey sample

The sample of households selected to 

be screened for NSCH was a subsample 

of the households screened for the 

National Immunization Survey (NIS), 

a continuous list-assisted random-digitdial (RDD) survey. Starting in 2007, 

the base NIS estimation areas included 

56 regions (50 state or “rest of state” 

areas plus 6 grantee urban areas). The 

6 grantee urban areas were: Chicago, 

Ill.; Philadelphia, Pa.; New York City, 

N.Y.; Bexar and Houston counties, Tex.;

and D.C. Also starting in 2007, state

immunization programs could identify

cities or counties of interest on an annual

basis to be oversampled. In 2011, four

regions were selected and added to the

base NIS estimation areas to equal a total

of 60 estimation areas. These areas were

Prince George’s County, Md.; Dallas and

El Paso counties, Tex.; and U.S. Virgin

Islands (USVI).

Associating telephone numbers 

with sampling areas

Drawing a sample of telephone 

numbers in a sampling area requires 

compiling a list of all telephone 

numbers that belong to that area. 

For some sampling areas, this step is 

straightforward. For example, when the 

sampling area is a state, the list would 

consist of all telephone numbers within 

the central-office codes that are in service 

in the area codes assigned to that state. 

(Combined, an area code and a centraloffice code form a “prefix area.” For 

example, 312–555–xxxx is the prefix area 

corresponding to the 555 central office in 

the 312 area code.)

For other sampling areas, however, 

this step is more complicated. When 

the sampling area is a city, county, or 

combination of counties, some prefix 

areas may cover part of the sampling area 

and part of an adjacent sampling area. In 

such situations, NIS applies a majority 

rule: If at least 50% of the directory-listed 

households in a prefix area fall inside a 

sampling area, the prefix area is assigned 

to that sampling area. 

The sampling area for the landline 

sample was defined as the NIS sampling 

area. The sampling area for the cellphone sample was defined as the state 

(based on area code) and estimated 

NIS sample area (based on the federal 

information processing standard or 

FIPS code, which was associated with 

the wire-center geographic location). 

This resulted in a 51-state by 59 NIS 

sampling-area matrix, although certain 

State*NIS sampling areas had neither 

universe counts nor released sample (e.g., 

Wyoming State by El Paso NIS sampling 

area).

Drawing initial NIS sample

The sampling frame of landline 

telephone numbers for a sampling area 

consists of banks of 100 consecutive 

telephone numbers within the prefix 

areas assigned to the sampling area. To 

exclude banks that contain zero directorylisted residential telephone numbers, the 

Genesys Sampling System (a proprietary 

product of Marketing Systems Group 

[MSG]) uses a file of directory-listed 

residential numbers from Donnelley 

Marketing Information Services. The 

result is a file that lists the remaining 

banks (“1+ working banks,” or banks 

that contain one or more directory-listed 

numbers). From the 1+ working banks, 

a random sample of complete 10-digit 

telephone numbers is drawn for each 

quarter in such a way that each number 

has a known and equal probability of 

selection within each sampling area. 

This process is not applicable to 

the cell-phone sample, because no 

comparable directory-listed file exists 

for this sample. Therefore, a sample 

from all known cell-phone numbers is 

drawn for each quarter in such a way 

that each number has a known and equal 

probability of selection within each state.

Updating NIS sampling frame

The set of telephone banks with 

at least one directory-listed residential 

telephone number changes over time. 

Therefore, the sampling frame is 

updated on a quarterly basis. Area-code 

splits produce additional changes to 

the sampling frame. MSG maintains 

a separate sampling frame for each 

sampling area. Each quarter, MSG 

examines the database to determine 

whether any currently included banks 

should be assigned to different sampling 

areas, and to assign newly included 

banks to sampling areas. The rules for 

assignment are the same as in the initial 

definitions of the sampling areas. 

Once all modifications have been 

made to the Genesys database, NORC 

at the University of Chicago performs 

a number of checks to ensure that all 

changes have been applied correctly and 

that the new database produces samples 

consistent with those produced prior 

to the changes. These checks compare 

the numbers of active banks and RDDselectable lines in each sampling area 

before and after the update. In parallel, 

the numbers of exchanges assigned to 

each sampling area before and after the 
Series 1, No. 59  Page 33 

update are compared. Small changes are 

expected, because new banks are put into 

service as new numbers are assigned. 

In the event of a major discrepancy in 

any of these checks, MSG is notified 

of the difference and asked to provide 

documentation of the reasons for the 

change. Similar checks are performed on 

the cell-phone sample where applicable, 

although these updates do not happen as 

frequently on the cell-phone frame.

Forming NIS sample replicates

Instead of releasing all sample lines 

within a sampling area at the same time, 

NIS divides the sample in each area into 

26 equally sized groups called replicates. 

This procedure permits smoother release 

of the sample, at the rate of one or two 

replicates per week, for each sampling 

area separately, as needed. Toward the 

end of the quarter, half-size replicates 

allow tighter control over the total 

amount of sample that is released. The 

aim is to produce an even distribution 

of work in the telephone center over the 

course of a quarter.

Preparation of sample

Coordinated management of the 

sample follows a sequence of steps. 

Before a replicate is loaded into 

the CATI system, several stages of 

processing remove as many business 

and nonworking numbers as possible. A 

separate step identified phone numbers 

on NIS’ “do not call list” for removal 

from the sample. For each quarter, any 

duplicate phone numbers (i.e., numbers 

that had appeared in the sample in the 3 

prior quarters) also were identified and 

omitted from the sample files. 

Removing business and 

nonworking numbers from 

landline sample

The majority of selected landline 

telephone numbers typically are 

businesses or unassigned. It would be 

incredibly inefficient to require the 

interviewers to dial and classify all of 

these landline numbers. To prevent such 

potential expense, NIS used another MSG 

product (a companion to the Genesys 

Sampling System) to quickly and 

accurately reduce the size of this task.

First, the selected landline sample 

was matched against a Genesys file 

containing telephone numbers that are 

directory-listed in a business Yellow 

Pages and not directory-listed in a 

residential White Pages. Any business 

numbers so identified were removed from 

the sample. Second, landline numbers 

listed in residential White Pages were 

identified and temporarily set aside. 

Third, a hardware system screened the 

remaining landline sample to remove 

a portion of the nonworking numbers. 

Using personal computers with special 

hardware and software, this system (the 

autodialer) automatically dialed the 

landline telephone numbers to detect 

nonworking landline numbers, which are 

indicated by the familiar tritone signal for 

out-of-service numbers, by an extended 

period of silence, or by continuous 

noise on the line. Finally, the directorylisted residential landline numbers were 

combined with the landline numbers 

that were not removed by the autodialer 

to produce the landline sample for the 

telephone center. The landline numbers 

removed within released replicates were 

considered released, and they were also 

considered prescreened and assigned 

disposition codes indicating that they 

were resolved, nonresidential landline 

numbers.

“Do not call” requests

A file was maintained containing 

phone numbers of people who had been 

contacted for NIS and had requested that 

they not be called. Throughout NSCH 

data collection, new requests to not be 

called resulted in updates to the list. Each 

quarter’s sample was compared with this 

file, and numbers that had been added 

to the “do not call” list within 2 years 

prior to the current survey year were 

not included in the quarterly sample of 

numbers loaded into the CATI system. 

Duplicate phone numbers

Because of the repeated quarterly 

sampling operations in each sampling 

area by sample type (landline and cell 

phone), some telephone numbers may 

have been selected more than once. To 

avoid any respondent problems created 

by recontacts for the same survey, a 

further sampling step identified duplicate 

numbers. Each quarterly sample file was 

compared with all sample files for the 

3 prior quarters, and duplicate numbers 

were excluded from the quarterly sample 

file. 

Obtaining addresses for advance 

letters

To obtain addresses that correspond 

to telephone numbers in the landline 

sample, the numbers for each replicate 

were sent to a vendor, TARGUSinfo 

(now Neustar Information Services). 

Neustar maintains a large database, 

updated daily, for its PhoneData Express 

program that contains more than 

160 million residential and business 

landline telephone numbers, including 

unpublished landline numbers. Sources 

for the data include call centers and 

companies in telecommunications, 

consumer goods, and the insurance and 

credit industries. No similar database 

exists for cell-phone numbers.

Following the preresolution 

operations described in the previous three 

sections, the use of TARGUSinfo yielded 

addresses for about 42.2% of the landline 

telephone numbers loaded into the CATI 

system. Advance letters were sent to this 

set of landline numbers. The mailing 

was issued approximately 10 days, or 

2 weekends, prior to the time when the 

telephone numbers in the corresponding 

replicates were scheduled to be called. 

No advance letters were mailed to the 

cell-phone sample.

Ported cell phones

A significant development in the 

telecommunications industry was the 

Federal Communications Commission 

(FCC) regulation on portability. Local 

number portability allows wireless 

phone customers to switch from one 

company to another while retaining the 

same phone number. Landline sampling 

typically includes automated dialing 

procedures to reduce data collection 

costs, but FCC rules bar automated calls 

to wireless phone numbers. Consumers 
Page 34  Series 1, No. 59

could take advantage of the wireless 

number portability provisions in three 

ways: 1) wireless-to-wireless, 2) 

wireless-to-landline, and 3) landline-towireless. The first two ways did not affect 

the RDD landline sampling strategy, 

because cell-phone numbers were not 

in the RDD landline sampling frame. 

However, the third way—the porting 

of landline numbers to wireless service 

providers—created the possibility of 

inadvertently including wireless phone 

numbers in the RDD landline sample. 

To preidentify landlines that have been 

ported to wireless, the selected landline 

sample was matched to the Neustar 

database, which contains the national list 

of ported phone numbers. Each quarterly 

sample was compared with the database, 

and the ported numbers were flagged 

accordingly. The flagged numbers were 

assigned an out-of-scope disposition 

code and were not called as part of the 

landline sample. Classifying such cases 

as out-of-scope for landline dialing did 

not remove those numbers from the 

overall universe, because they still could 

have been randomly selected for the cellphone sample. Rather, classifying them 

as out-of-scope for the landline sample 

prevented the landline and cell-phone 

sample frames from overlapping. The 

landline numbers in released replicates 

were also matched to the Neustar 

database daily to identify any new ports 

that had not already been finalized within 

the phone center. 

Because any number selected for the 

cell-phone sample was not autodialed, 

ported numbers were not an issue for the 

cell-phone sample.

Weighting and Estimation

This section summarizes the 

methodology used for weighting the 

2011–2012 NSCH sample. The weighting 

scheme involves the following steps:

1. Base sampling weight

2. Derivation of annual sampling 

weight

3. Adjustment for nonresolution of 

released telephone numbers

4. Adjustment for incomplete cell 

phone-only/mainly (CPO/M) 

screener (affects Q1/2011 cell-phone 

sample only)

5. Adjustment for incomplete S_KIDS 

screener (affects Q3/2011, Q4/2011, 

and Q1/2012 augmentation cellphone sample only)

6. Adjustment for incomplete ageeligibility screener

7. Adjustment for subsampling of 

children within households

8. Adjustment for nonresponse to 

NSCH interview

9. Adjustment for multiple cell-phone 

lines

10. Trimming of extreme weights

11. Adjustment for combined landline 

and cell-phone sample and 

noncovered children

12. Raking adjustment of child weights

Each individual weighting step is 

discussed in detail below.

Step 1: Base weights

The weighting process started with 

computing the base sampling weights of 

the sampled telephone numbers, where 

the base weight is the reciprocal of the 

selection probability of a phone number. 

Sample cases were selected from both 

landline and cell-phone numbers. Sample 

source was designated by t = 1 (landline) 

and 2 (cell). The base weight for the 

k-th telephone number from the t-th 

source type in the released sample for a 

sampling area, At, was defined by:

 

where

 = probability of selecting the k-th 

telephone number from the t-th 

source type in the initial release for 

quarter q,

ntq = sample size (in initial released 

replicates) for the quarter q from 

the t-th source type in the sampling 

area, and

Ntq = total telephone numbers on the 

sampling frame for quarter q from 

the t-th source type in the sampling 

area, as determined by Genesys.

For the landline sample, the base 

weight was a constant for all telephone 

numbers within a quarter, source type, 

and sampling area. 

Step 2: Derivation of annual 

sampling weight

In this step, all quarterly samples 

were combined for the landline and 

cell-phone samples separately, and the 

quarterly base weights were adjusted 

so that the samples from all quarters 

jointly represented the corresponding full 

population within each state. Because 

the base weights were calculated for 

each quarter separately, the sum of 

base weights in each quarter represents 

the full population for each state. The 

annual sample weights were computed 

from quarterly weights by applying 

composition factors proportional to the 

number of released sample telephone 

numbers in a quarter. The annual weights 

were defined as:

W2tk = if k ∈ t, q R2tk

W1tk

where

R2tk = , for t = 1

n1q

q' = 1

5

∑n1q

, for t = 2

n2q

q' = 1

5

∑n2q

and

ntq = sample size for the q-th quarter in 

the t-th source type in the sampling 

area. 

Note that USVI had sample 

released only during one quarter of data 

collection; therefore, no adjustment 

was done during this step for the USVI 

sample. 

Step 3: Adjustment for 

nonresolution of released 

telephone numbers

Once the sample of telephone 

numbers was released, the first step was 

to identify whether the number was a 

working residential number (WRN) 

for landlines or an active personal 

cell number (APCN) for cell phones. 

However, even after repeated callbacks, 

the WRN–APCN status of many 

telephone numbers remained unresolved. 

An adjustment to the weight of resolved 
Series 1, No. 59  Page 35 

cases was necessary to account for cases 

in which the WRN–APCN status was 

unknown.

To make the adjustment, a number 

of adjustment cells within each sampling 

area were formed by controlling for 

known covariates. The adjustment in 

each cell was made by assuming that 

the rate of WRNs to APCNs among 

unresolved numbers was the same as the 

rate of WRNs to APCNs among resolved 

numbers. Within each sampling area, the 

adjusted weights were computed as:

W3tk = if k ∈ t, Bt, l R3tl

W2tk

= 0 otherwise

where

R3tl = k ∈ t, Bt

k ∈ t, At

∑ δ3tklW2tk

∑ δ3tklW2tk

Bt = subset in At of resolved telephone 

numbers from the t-th source 

type (WRN or non-WRN/APCN 

or non-APCN), and

δ3tkl = 1 if the k-th number from the t-th 

source type was in the l-th cell and 

= 0 otherwise.

The covariates used to define the 

adjustment cells (l) for the landline 

sample within each sampling area are 

shown in Table I by census region of the 

sampling area. Different sets of variables 

were used for sampling areas in different 

census regions. The variables were 

identified through an analysis using the 

interim 2011–2012 NSCH data. Each 

cell included at least 20 resolved cases to 

enable stable estimation of the adjustment 

factor R3tl .

To define the adjustment cells (l) for 

the cell-phone sample, only metropolitan 

statistical area (MSA) status associated 

with the released case was used, due to 

smaller sample sizes for the cell-phone 

sample and the smaller correlation 

between exchange and geographic 

area for cell-phone numbers relative to 

landline numbers. The adjustment cells 

needed to include at least 20 resolved 

cases to enable stable estimation of the 

adjustment factor, R3tl .

Step 4: Adjustment for 

incomplete CPO/M screener

Some resolved cases in the cellphone sample did not complete the cell 

phone-only/mainly, or CPO/M, screener. 

This step applied only to Q1/2011, 

because the remainder of the cell-phone 

sample released was no longer screened 

for specific cell-phone status. To account 

for the cases for which CPO/M status 

was unknown, the weights of the resolved 

cell-phone sample cases were adjusted. 

The adjustment in each cell was made by 

assuming that the rate of CPO/M among 

screener-completed APCNs is the same 

as the rate of CPO/M among those that 

had not completed the CPO/M screener. 

Within each state, the adjusted weights 

were computed as: 

W4tk = if k ∈ t = 2, v, Dt, l R42vl

W32vk

and

 = W3lk otherwise

where

R42vl = k ∈ t = 2, v, D2

∑δ42klW32vk

k ∈ t = 2, v, C12

∑δ42klW32vk

v = 2 if the k-th cell number was in 

Aug Q4,c and 

= 1 otherwise (including for 

landline telephone numbers),

Dt = set of cell-phone numbers for the 

quarter from the t-th source type 

in C1t that completed the CPO/M 

screener in the state,

C1t = set of telephone numbers for the 

quarter from the t-th source type 

in Bt that were WRNs or APCNs 

in the state, and, if in AugQ4,c, 

were also in CAugS_Kids (i.e., had yet 

to screen out), and

δ42kl = 1 if the k-th cell number was in 

the l-th cell and

= 0 otherwise.

To define the adjustment cells 

(l) for cell-phone sample within each 

state, the number of call attempts to 

resolve the telephone number (1, 2+) 

was used. The adjustment cells needed 

to include at least 20 resolved cases 

to enable stable estimation of the 

adjustment factor, R4tl. To achieve this 

goal when the number of resolved cases 

was less than 20, adjustment cells were 

broadened by collapsing the number of 

call attempts. For all sample cases other 

than the Q1/2011 cell-phone sample, the 

adjustment factor was 1. 

Step 5: Adjustment for 

incomplete S_KIDS screener

In Q3/2011, Q4/2011, and Q1/2012, 

additional cell-phone sample was released 

for NSCH to augment the NIS cell-phone 

sample that had been released. This 

augmentation sample asked an additional 

screener question at the beginning of the 

Table I. Covariates used to create nonresolution adjustment cells within sampling area, by census region and directory-listed status: 

Landline sample

Sampling area

Northeast Midwest South West 

Listed Unlisted Listed Unlisted Listed Unlisted Listed Unlisted

Rent Rent Income Rent Rent Grad Rent Rent

Grad Minority Grad Owner Owner Rent Minority Age

Income MSA Rent MSA Age Owner Income Minority

NOTES: Covariates are listed in order of importance within a group, based on the strength of the relationship between the covariate and observed nonresponse rates. Listed and Unlisted refer to 

the directory-listed status of the phone number. The remaining covariates are telephone exchange-level measures: Percentage renting (Rent), percentage who own their homes (Owner), percentage 

college-educated (Grad), percentage Hispanic or nonwhite (Minority), percentage in income and age categories (Income, Age), and percentage living in a metropolitan statistical area (MSA).
Page 36  Series 1, No. 59

interview to determine whether a child 

lived in the household. This screener 

question (labeled “S_KIDS”) was asked 

in an attempt to reduce the overall 

screening cost and was separate from the 

full age-eligibility screener conducted 

later in the interview. Therefore, an 

adjustment for the cell augmentation 

sample (Augc) was necessary to account 

for incomplete S_KIDS screener cases. 

To compensate for this, the weights 

of the phone numbers from the cell 

augmentation sample with completed 

S_KIDS screeners were adjusted. The 

adjusted weight for the k-th number from 

the t-th source type is derived as:

if k ∈ t = 2, CAug, S_Kids, Augc W5tk = , l R52l

W42k

and

= W4tk otherwise

where

R52l = k ∈ t, CAug, S_kids, AugQ3,c

∑ δ52klW42k

k ∈ t = 2, B1t, AugQ3,c

∑ δ52klW42k

Augc = subset of telephone numbers 

from the augmentation cellphone sample, 

CAugS_Kids = set of augmentation cellphone numbers from B1Aug

that completed the S_KIDS 

screener in the state,

B1Aug = set of augmentation cell-phone 

numbers for the quarter from 

Bt that were APCNs in the 

state, and

δ52kl = 1 if the k-th augmentation cell 

number was in the l-th cell and

= 0 otherwise.

To define the adjustment cells (l) for 

the cell-phone sample within each state, 

MSA status associated with the released 

case was used. The adjustment cells 

included at least 20 resolved cases to 

enable stable estimation of the adjustment 

factor, R52l .

For all sample cases other than the 

augmentation cell-phone sample, the 

adjustment factor was 1. 

Step 6: Adjustment for 

incomplete age-eligibility 

screener 

Among the resolved landline WRNs 

and cell-phone APCNs, some sample 

cases did not complete the age-eligibility 

screener. For such cases, it was not 

known if any age-eligible children lived 

in the household. To compensate for this, 

the weights of the telephone numbers 

from the t-th source type with completed 

age-eligibility screeners were adjusted. 

The adjusted weight for the k-th number 

from the t-th source type was calculated 

as:

if k ∈ t, v, Et W6tk = , l R6tvl

W5tvk

and

= 0 otherwise

where

R6tvl =

k ∈ t, v, D1t

∑δ6tvklW5tvk

∑δ6tvklW5tvk

k ∈ t, v, Et

Et = subset of telephone numbers for 

the quarter from the t-th source 

type in D1t that completed the ageeligibility screener in the state,

D1t = set of landline telephone numbers 

for the quarter that are WRNs (if t 

= 1) or set of cell-phone numbers 

for the quarter that are APCNs (if 

t = 2) in the state, and

δ6tkl = 1 if the k-th number from the t-th 

source type is in the l-th cell and

= 0 otherwise.

To define the adjustment cells (l) 

for landline sample within each state, the 

covariates listed in Table II were used by 

census region of the state. The adjustment 

for age screening was made within each 

state (as opposed to the sampling area 

used for the nonresolution adjustment), 

due to smaller sample sizes at this stage. 

The adjustment cells included at least 20 

resolved cases to enable stable estimation 

of the adjustment factor.

To define the adjustment cells (l) for 

the cell-phone sample within each state, 

the number of call attempts to resolve the 

telephone number (1, 2+) was used. Each 

cell included at least 20 resolved cases to 

enable stable estimation of the adjustment 

factor, R6tl, by collapsing across call 

attempts when necessary.

For this step, cell augmentation 

sample and NIS cell-phone sample were 

treated separately, due to prescreening 

for the presence of children for the 

augmentation cell-phone sample. After 

this step, the cell-phone samples were 

treated together.

Step 7: Adjustment for 

subsampling of children within 

households

In households with more than 

one child, only one child was selected 

randomly for the NSCH interview. The 

child age-eligibility screener weights 

were adjusted to account for the children 

who were not selected. The subsampling 

weight for the j-th child was defined by:

W7j = nkW6j if j ∈ F and

= 0 otherwise

where

F = subset of children that are 

subsampled for NSCH interview,

n*

k = the number of children in household 

k where, j ∈ F and

nk = min(3, ) n*

k .

Table II. Covariates used to create nonresponse adjustment cells for age-eligibility screener 

within state, by census region and directory-listed status: Landline sample

Census region

Northeast Midwest South West

Minority Listed Listed Minority

Listed Minority Age Listed

MSA MSA Minority Age

NOTES: Covariates are listed in order of importance within a group, based on the strength of the relationship between the covariate 

and observed nonresponse rates. Listed refers to the directory-listed status of the phone number. The remaining covariates 

are telephone exchange-level measures: Percentage Hispanic or nonwhite (Minority), percentage in age categories (Age), and 

percentage living in a metropolitan statistical area (MSA).
Series 1, No. 59  Page 37 

The factor to adjust for number of 

children in a household was capped at 

3 to control variability. The resulting 

weight is the basic child-level weight for 

the NSCH interview.

Step 8: Adjustment for 

nonresponse to NSCH interview

Not all households with children that 

completed the age-eligibility screener 

completed the interview. The weights 

assigned to households responding to 

the NSCH interview were adjusted to 

account for the nonresponse of other 

households. The adjustment was made by 

forming nonresponse adjustment cells (l). 

The nonresponse-adjusted weight for the 

j-th child was calculated as:

W8k = if j ∈ G , l R8q

W7k

and

= 0 otherwise

where

R8q =

∑ δ8jlW7k

k ∈ F

∑ δ8jlW7k

k ∈ E

G = subset of all children with a 

completed NSCH interview, and

δ8jl = 1 if the j-th child is in the l-th 

adjustment cell and

= 0 otherwise.

The adjustment cells (l) were formed 

from categories of age group and total 

number of children in the household. 

Any adjustment cell with less than 20 

responding records was collapsed with a 

neighboring cell.

Step 9: Adjustment for multiple 

cell-phone lines

Among the households that 

completed the interview within the cellphone sample, some households reported 

more than one cell-phone number for 

adult use. An adjustment to the weight 

was required for these households to 

compensate for their multiple chances 

of selection. The adjusted weight for the 

k-th cell-phone number with a complete 

age-eligibility screener is defined by:

W9tk = pk,c

W8tk

where

p'

k,c = number of cell-phone numbers 

for adult use in the household of 

the k-th cell-phone number with a 

completed NSCH interview, and

pk,c = min(3, ) p'

k,c .

The number of adult cell-phone 

lines was capped at 3 for purposes of 

the weight adjustment, both to control 

variability and to guard against reporting 

bias.

For all landline and USVI sample 

cases, the adjustment factor was 1. 

The remaining weighting 

adjustments were done using true state of 

residence as opposed to sampling state.

Step 10: Trimming of extreme 

weights 

Within the cell-phone sample, 

significant movement occurred from 

sample state to state of residence because, 

in many cases, the area code of the 

cell-phone number had not sufficiently 

indicated the true state of residence. As 

a result, when the sample was stratified 

by true state, large variability occurred 

in the weights due to cases sampled from 

State A being combined with cases from 

State B. Therefore, extreme weights were 

trimmed as:

W10j = min(W9j,Wt,Threshold) if j ∈ t

where

Wt, Threshold = mediant(W9,t) + 4

• InterQuartileRanget (W9,t)

and

W9,t = weights of all cases 

associated with the t-th 

source type within the true 

state.

Step 11: Adjustments for 

combined landline and 

cell-phone samples and for 

noncovered populations 

The full-sample child weights (W10tk) 

with a complete NSCH interview were 

adjusted to accomplish six goals:

1. Adjustment for noncoverage of ageeligible children

2. Adjustment for overlap of the 

landline and cell-phone samples

3. Adjustment to residual landline 

population totals

4. Adjustment to residual cell-phoneonly population totals

5. Trimming of extreme weights

6. Adjustment for USVI

Adjustment for noncoverage of ageeligible children—A Keeter adjustment 

(20) was carried out to adjust weights 

to account for households with children 

not covered by the combined landline 

and cell-phone samples (i.e., phoneless 

households). In the Keeter adjustment, 

weights for landline households with 

an interruption in telephone service 

are adjusted to represent phoneless 

households with children. The method 

was based on empirical evidence 

suggesting that landline households with 

an interruption in telephone service are 

more similar to phoneless households 

than are households with no interruptions, 

with respect to the variables under study 

(20,21). The adjustment is given as: 

ŶNP = ωŶLL(Int)

where

ω = adjustment factor, and

ŶLL(Int) = estimated prevalence of service 

interruption based on sample 

households from the landline 

sampling frame, where the 

household had a noncell/mostly 

telephone status and for which 

a household interview was 

completed.

The adjustment factor can be 

expressed as:

W10k

k ∈ LL(Int)

∑ ωLL(Int) = NNP

where

NNP = population control for phoneless 

households with children.

The adjusted weights for noncell/

mostly landline sample households with a 

telephone service interruption, controlled 

to the total population of phoneless 

households with children, can then be 

expressed as:

W11k = ωLL(Int)W10k, k ∈ LL(Int)

Adjustment for overlap of the 

landline and cell-phone samples—The 
Page 38  Series 1, No. 59

landline and cell-phone samples, while 

selected from distinct sampling frames, 

partially overlap in their coverage of the 

population. The landline sample includes 

dual landline and cell-phone households, 

while the cell-phone sample includes 

dual landline and cell-phone households 

self-identifying as cell phone-mainly 

(i.e., they said they were unlikely to be 

reached through their landline). Thus, 

survey weights for dual landline and 

cell-phone cases from the two sampling 

frames must be adjusted to account for 

this overlap. For purposes of weighting, 

cell phone-mainly cases were treated as 

cell phone-mostly because the majority 

of cell phone-mainly cases also selfidentified as being cell phone-mostly (i.e., 

they said that they received all or almost 

all calls on their cell phone). However, 

the cell phone-mainly sample cases were 

assumed to be biased when estimating for 

the cell phone-mostly population. 

The sum of the annualized weights 

for the landline sample (which estimated 

the number of landline households with 

children) and the sum for the cell-phone 

sample (which estimated the number of 

cell-phone households with children) 

both include some dual landline and 

cell-phone households that were cell 

phone-mostly. Thus, when combining 

the landline and cell-phone samples, the 

annualized weights for cell phone-mostly 

households must be adjusted so the sum 

of the adjusted weights across landline 

and cell-phone samples provides an 

appropriate estimate of cell phone-mostly 

households. The composite adjustment 

factor was derived based on the relative 

sample size of completed interviews 

within each frame, within each telephone 

status (Cell-Mostly, Other Dual Users). 

The adjusted weights for cell phonemostly sample cases, controlled to the 

total population of cell phone-mostly 

households with a child, can be expressed 

as:

W11k =

λW10k, k ∈ CP(CM)

(1 – λ)W10k, k ∈ LL(CM)

W10k

k ∈ CP(CM)

∑

NCM

W10k k ∈ LL(CM)

∑

NCM

where

NCM = population control for cell phonemostly households with children, 

and

W10, t λ = W10t

k ∈ CM(LLandCP)

∑

The adjusted weights for Other Dual 

Users sample cases, controlled to the total 

population of other dual-users households 

with a child, can then be expressed as:

W11k =

λW10k, k ∈ CP(ODU)

(1–λ)W10k, k ∈ LL(ODU)

W10k k ∈ CP(ODU)

∑

NCM

W10k k ∈ LL(ODU)

∑

NCM

where

NCM = population control for other dualusers households with children, and

λ = W10t

k ∈ ODU (LLandCP)

∑

W10, t k ∈ ODU (CP)

∑

Adjustment to residual landline 

population controls—A ratio adjustment 

was carried out to adjust weights to 

population controls for the residual set 

of landline households with children. 

The adjusted weights for landline-only 

sample households controlled to the total 

population of landline-only households 

with children was defined as:

W11k = ΨLLO W10k, k ∈ LLO 

where

W10k k ∈ LLO

∑ ΨLLO = NLLO

 and

NLLO = population control for landlineonly households with children.

Adjustment to residual cellphone-only population controls—A 

ratio adjustment was carried out to 

adjust weights to population controls 

for the residual set of cell-phone-only 

households with children. The adjusted 

weights for cell-phone-only sample 

households controlled to the total 

population of cell-phone-only households 

with children was defined as:

W11k = ΨCPOW10k, k ∈ CPO 

where

W10k k ∈ CPO

∑ ΨCPO = NCPO

 and

NCPO = population control for landlineonly households with children.

Trimming of extreme weights—After 

the adjustment, extreme weights were 

again trimmed. The upper threshold for 

the weights was again defined as the 

median of the weight + 4 • (Inter Quartile 

Range). 

Adjustment for USVI—A Keeter 

adjustment was not possible for USVI, 

because no current accurate information 

was available on the number of children 

in phoneless households. Additionally, 

because no cell-phone sample was fielded 

in USVI, there was no need for the 

above steps to be applied. Therefore, this 

adjustment was not carried out for USVI 

and the adjustment factor was 1.

Step 12: Raking adjustment of 

child weights 

The combined landline and cellphone sample weights (W11k) were raked 

within each state, such that the sums of 

the weights at the household level agreed 

with the control totals in each category of 

each margin used for raking. The required 

demographic control totals were obtained 

from the public-use 2011 American 

Community Survey (ACS) data, and 

the raking adjustments within each state 

and D.C. were made using the following 

margins and categories:

● Number of households with 

male and female children in five 

nonoverlapping age groups

● Number of households with children 

in five nonoverlapping race and 

ethnicity categories

● Number of households with one 

child, two children, and three or 

more children

● Number of households with children 

that have a household income in five 

nonoverlapping categories

● Number of households with children 

in which the highest reported 

education is in each of three 

nonoverlapping categories

● Number of households that own 

their housing unit, rent their housing 

unit, and neither own nor rent their 

housing unit (other arrangement)

● Number of households with children 
Series 1, No. 59  Page 39 

by telephone status: cell phone-only, 

cell phone-mostly, and all others. 

The categories of raking dimensions 

were collapsed where the number of 

cases was small (less than 40) or if any 

difficulty occurred in raking convergence. 

In some cases, the values of the raking 

variables mentioned above may have 

been missing. The missing values for all 

of these variables were imputed using 

weighted sequential hot-deck imputation 

method after forming appropriate 

imputation classes.

To allow for raking to telephone 

status, the combined landline and cellphone sample weights were decomposed 

into respective component weights for 

each telephone status type (cell phoneonly, cell phone-mostly, and all others). 

This decomposition was not applied to 

USVI because no cell-phone sample 

occurred there.

For USVI, detailed population 

control totals for the dimensions 

described above were not available, 

because the 2011 ACS was not completed 

in USVI and the detailed 2010 census 

files were not released at the time of 

weighting. The 2010 census totals for age 

group by sex were available, and a simple 

poststratification was done using those 

results. 

The raked weight for the k-th 

household was W12k = R12k W11k if 

k∈ G and

= 0 otherwise

where R12

k was the raking adjustment 

factor for the k-th household, which was 

determined iteratively, and G was the set 

of all telephone numbers that completed 

the NSCH interview as defined above.

At this stage, the weights were 

checked and all extreme weights were 

trimmed to avoid any undue influence on 

the variances of the estimate. The raking 

adjustment was rerun after truncating the 

extreme weights.

The raked household weight is the 

final weight to be used for obtaining all 

estimates.
Page 40  Series 1, No. 59 

Appendix II. 2011–2012 National Survey of Children’s Health 

Questionnaire 

The following public burden estimate statement will be available as a CATI screen: 

Public reporting burden for this collection of information is estimated to average 27 minutes per response, including 

the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and 

completing and reviewing the collection of information. An agency may not conduct or sponsor, and a person is not 

required to respond to, a collection of information unless it displays a currently valid OMB control number. Send 

comments regarding this burden estimate or any other aspect of the collection of this information, including 

suggestions for reducing this burden, to CDC/ATSDR Reports Clearance Officer, 1600 Clifton Road, MS D-74, 

Atlanta, GA 30333, ATTN: PRA (0920-0406).

Data collection conducted under contract to the CDC by NORC at the University of Chicago

Form approved 

OMB No. 0920-0406

Exp. Date 04/30/14

All information which would permit identification of any individual, a practice, or an establishment will be held 

confidential, will be used for statistical purposes only by NCHS staff, contractors, and agents only when required 

and with necessary controls, and will not be disclosed or released to other persons without the consent of the 

individual or the establishment in accordance with section 308(d) of the Public Health Service Act (42 USC 242m) 

and the Confidential Information Protection and Statistical Efficiency Act (PL-107-347).

2011 NATIONAL SURVEY OF CHILDREN’S HEALTH

NIS/SLAITS SCREENING.........................................................................................................................................3

NIS SCREENING.........................................................................................................................................................9

AUGMENTATION SAMPLE ........................................................................................................................................10

INFORMED CONSENT................................................................................................................................................21

SECTION 1: INITIAL DEMOGRAPHICS...........................................................................................................24

SECTION 2: HEALTH AND FUNCTIONAL STATUS ......................................................................................26

SUBDOMAIN 1: GENERAL HEALTH STATUS ..........................................................................................................26

SUBDOMAIN 2: PRESENCE OF A SPECIAL HEALTH CARE NEED..............................................................................27

SUBDOMAIN 3: COMMON CHRONIC CONDITIONS ................................................................................................. 31

SECTION 3: HEALTH INSURANCE COVERAGE ...........................................................................................41

SUBDOMAIN 1: CURRENT COVERAGE AND PAST YEAR COVERAGE ......................................................................41

SUBDOMAIN 2: ADEQUACY OF HEALTH INSURANCE............................................................................................43

SUBDOMAIN 3: EXPENSES AND BARRIERS TO CARE ............................................................................................44

SECTION 4: HEALTH CARE ACCESS AND UTILIZATION..........................................................................45

SUBDOMAIN 1: USUAL PLACE FOR CARE .............................................................................................................45

SUBDOMAIN 2: UTILIZATION OF SERVICES ..........................................................................................................46

SUBDOMAIN 3: USE OF DEVELOPMENTAL SERVICES ............................................................................................50

SECTION 5: MEDICAL HOME............................................................................................................................51

SUBDOMAIN 1: REFERRALS ................................................................................................................................. 51

SUBDOMAIN 2: CARE COORDINATION .................................................................................................................51

SUBDOMAIN 3: PROVIDER COMMUNICATION.......................................................................................................53

SUBDOMAIN 4: COMPASSIONATE, CULTURALLY EFFECTIVE, FAMILY-CENTERED CARE.......................................54
Series 1, No. 59  Page 41 

SECTION 6: EARLY CHILDHOOD (0-5 YEARS) .............................................................................................56

SUBDOMAIN 1: PARENT’S EVALUATION OF DEVELOPMENTAL STATUS...............................................................56

UBDOMAIN 2: DEVELOPMENTAL SCREENING.....................................................................................................57

SUBDOMAIN 3: CHILD CARE ................................................................................................................................58

SUBDOMAIN 4: BREASTFEEDING .........................................................................................................................59

SUBDOMAIN 5: FLOURISHING ..............................................................................................................................59

SUBDOMAIN 6: TIME USE.....................................................................................................................................60

SECTION 7: MIDDLE CHILDHOOD AND ADOLESCENCE (6-17 YEARS) ................................................62

SUBDOMAIN 1: SCHOOL ENROLLMENT ................................................................................................................62

SUBDOMAIN 2: AFTER-SCHOOL ACTIVITIES AND PARENTAL INVOLVEMENT........................................................64

SUBDOMAIN 3: SLEEP AND EXERCISE ..................................................................................................................65

SUBDOMAIN 4: READING.....................................................................................................................................67

SUBDOMAIN 5: MEDIA CONSUMPTION.................................................................................................................67

SUBDOMAIN 6: BULLYING AND EMOTIONAL DIFFICULTIES..................................................................................69

SUBDOMAIN 7: FLOURISHING ..............................................................................................................................69

SECTION 8: FAMILY FUNCTIONING...............................................................................................................70

SUBDOMAIN 1: FAMILY ACTIVITIES.....................................................................................................................70

SUBDOMAIN 2: PARENT/CHILD RELATIONSHIP.....................................................................................................70

SUBDOMAIN 3: FAMILY STRESS ...........................................................................................................................71

SECTION 9: PARENTAL HEALTH.....................................................................................................................73

SUBDOMAIN 1: HOUSEHOLD COMPOSITION .........................................................................................................73

SUBDOMAIN 2: AGE AND MARITAL STATUS OF ADULTS IN HOUSEHOLD ..............................................................76

SUBDOMAIN 3: GENERAL HEALTH STATUS ..........................................................................................................80

SUBDOMAIN 4: SMOKING ....................................................................................................................................82

SUBDOMAIN 5: ADVERSE FAMILY EXPERIENCES ................................................................................................. 82

SUBDOMAIN 6: PRESENCE OF ADULT MENTOR.....................................................................................................83

SECTION 10: NEIGHBORHOOD AND COMMUNITY CHARACTERISTICS.............................................84

SUBDOMAIN 1: NEIGHBORHOOD AMENITIES........................................................................................................84

SUBDOMAIN 2: NEIGHBORHOOD CONDITION .......................................................................................................84

SUBDOMAIN 3: SOCIAL CAPITAL..........................................................................................................................84

SUBDOMAIN 4: PERCEIVED SAFETY .....................................................................................................................85

SECTION 11: ADDITIONAL DEMOGRAPHICS...............................................................................................86

SUBDOMAIN 1: RACE AND ETHNICITY OF CHILD..................................................................................................86

SUBDOMAIN 2: EDUCATION OF PARENTS .............................................................................................................88

SUBDOMAIN 3: BIRTHPLACE OF CHILD AND PARENTS..........................................................................................89

SUBDOMAIN 4: RESIDENTIAL MOBILITY ..............................................................................................................93

SUBDOMAIN 5: EMPLOYMENT AND INCOME ........................................................................................................94

SUBDOMAIN 6: PROGRAM PARTICIPATION...........................................................................................................98

SECTION 12: ADDITIONAL HEALTH INSURANCE QUESTIONS ..............................................................99

SUBDOMAIN 1: REASONS FOR UNINSURANCE......................................................................................................99

SUBDOMAIN 2: HISTORY WITH MEDICAID.........................................................................................................100

SUBDOMAIN 3: HISTORY WITH CHIP ................................................................................................................103

SUBDOMAIN 4: INTEREST IN ENROLLING IN MEDICAID/CHIP ...........................................................................106

SUBDOMAIN 5: PARENTS’ COVERAGE AND AVAILABILITY OFEMPLOYER-SPONSORED INSURANCE.................110

SECTION 13: LOCATING INFORMATION.....................................................................................................118

SUBDOMAIN 1: TELEPHONE LINE INFORMATION................................................................................................118

SUBDOMAIN 2: ZIP CODE..................................................................................................................................120

SUBDOMAIN 3: LOCATING QUESTIONS...............................................................................................................121
Page 42  Series 1, No. 59 

SUBDOMAIN 4: CLOSING SCRIPT .......................................................................................................................122

CALLBACK AND REFUSAL CONVERSION SCRIPTS..................................................................................124

ANSWERING MACHINE SCRIPTS....................................................................................................................125

NIS/SLAITS Screening

INTRO_1 Hello, my name is . I’m calling on behalf of the Centers for DiseaseControl and 

Prevention. We’re conducting a nationwide immunization study to find out how many children 

under 4 years of age, are receiving all of the recommended vaccinations for childhood diseases. 

Your telephone number has been selected at random to be included in the study.

(1) CONTINUE ............................................................................ SEE LOGIC BELOW

IF INTRO_1=1 AND RDD_NCCELL_CCELL = 1, GO TO S1

ELSE IF INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 1 , GO 

TO S_CELL

ELSE IF INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND S_KIDS_FLAG=0, GO TO S_WARM

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=3,5,6 AND PRE_KIDS=1 AND S_KIDS=NULL AND 

S_UNDR18=NULL) THEN GO TO S_KIDS

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=3,5,6 AND PRE_KIDS=1 AND S_KIDS NOT MISSING) 

GO TO S_WARM.

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=1,2,4 AND PRE_KIDS=1 ) GO TO S_WARM.

(2) CONFIRM BUSINESS........................................................... GO TO SALZ

(3) OUT OF SCOPE ..................................................................... GO TO THANK_YOU_OOS

(4) TERMINATE THE INTERVIEW.......................................... GO TO T1 

IF RDD_NCCELL_CCELL = 1 DISPLAY:

(5) CELL PHONE........................................................ GO TO CELL_1 

ELSE IF RDD_NCCELL_CCELL = 2, 3 AND TXFLG = 1 DISPLAY:

(5) LANDLINE - YOU WILL NOT TERMINATE ................. GO TO S1 and set

RDD_NCCELL_CCELL = 1

ELSE IF RDD_NCCELL_CCELL = 2, 3 AND TXFLG = 0 DISPLAY:

(5) LANDLINE........................................................... GO TO LANDLINE EXIT - 

set ITS=88

(6) ANSWERING MACHINE [FILL] ......................................... GO TO S1

If message is to be left then GO TO SASERV else hang up and set ITS =35

(7) R WILL CALL 800 LINE/VERIFY WEBSITE ..................... GO TO P1/VERIFY_INFO

set ITS =69

(8) R ASKS FOR LETTER........................................................... GO TO M1_NAME

(9) SUPERVISOR REVIEW........................................................ Set ITS = 49

(15) Test sample - use only if respondent instruct that this call was a test => set ITS=119

(16) CONTINUE THE CASE WITH LANGUAGELINE
Series 1, No. 59  Page 43 

IF RDD_NCCELL_CCELL = 2, 3 DISPLAY:

(17) DROPPED CALL............................................. GO TO CNOTES_1_1> set

ITS=81(SCHEDULE A CALL 

BACK FOR 1 MINUTE)

INTRO_1_HUDI Hello, my name is . I’m calling on behalf of the Centers for Disease Control and Prevention.

We’re conducting a nationwide study to prevent future outbreaks of childhood diseases.

CONTINUE WITH INTERVIEW...........................................1 GO TO S1

CONFIRM BUSINESS............................................................2 GO TO SALZ

ANSWERING MACHINE ......................................................4 GO TO MSG_Y

INTRO_1

(for partial

completes) Hello, my name is and I am calling on behalf of the Centersfor Disease

Control and Prevention. We recently spoke to (MKR / an adult in this household) and began an 

important nationwide immunization study regarding (child's name or initials)'s vaccinations. I'm 

calling to complete the interview now, may I please speak with (MKR / that adult)?

CONTINUE WITH INTERVIEW...........................................1 GO TO S1

CONFIRM BUSINESS............................................................2 GO TO SALZ

Out of scope .............................................................................3 GO TO THANK_YOU_OOS

Terminate the Interview ...........................................................4 GO TO UNIVERSAL EXITT1 

Cell phone ................................................................................5 GO TO UNIVERSAL EXITCELL_1 

Answering machine .................................................................6 GO TO MSG_Y

R will call 800 line/verify website ...........................................7 GO TO CNOTES_1_1

R asks for letter ........................................................................8 GO TO UNIVERSAL EXIT

M1_NAME 

Supervisor review.....................................................................9 GO TO CNOTES_1_1

(Raise your hand to get permission before using this code)

INTRO_1 [Incentives_10/Address Available]

Hello. I’m calling on behalf of the Centers for Disease Control and Prevention to follow up on a 

letter that was sent to your home. Earlier, we had contacted your household to participate in a 

survey regarding the immunizations of the [IF S_NUMB=1, THEN "child who lives"{IF 

S_NUMB>1, THEN "children who live"] there. I’m calling back to continue the interview. In 

appreciation for your time, we will send you $10.

CONTINUE WITH INTERVIEW...........................................1 GO TO S1

CONFIRM BUSINESS............................................................2 GO TO SALZ

Out of scope .............................................................................3 GO TO THANK_YOU_OOS

Terminate the Interview ...........................................................4 GO TO UNIVERSAL EXITT1 

Cell phone ................................................................................5 GO TO UNIVERSAL EXITCELL_1 

Answering machine .................................................................6 GO TO MSG_Y

R will call 800 line/verify website ...........................................7 GO TO CNOTES_1_1

R asks for letter ........................................................................8 GO TO UNIVERSAL EXIT

M1_NAME 

Supervisor review.....................................................................9 GO TO CNOTES_1_1

(Raise your hand to get permission before using this code) 

INTRO_1 [Incentives_15/Telephone Only]
Page 44  Series 1, No. 59 

Hello. I’m calling on behalf of the Centers for Disease Control and Prevention. Earlier, we had 

contacted your household to participate in a survey regarding the immunizations of the [IF 

S_NUMB=1, THEN "child who lives"/IF S_NUMB>1, THEN "children who live"] there. I’m 

calling back to continue the interview. In appreciation for your time, we will send you $15.

CONTINUE WITH INTERVIEW...........................................1 GO TO S1

CONFIRM BUSINESS............................................................2 GO TO SALZ

Out of scope .............................................................................3 GO TO THANK_YOU_OOS

Terminate the Interview ...........................................................4 GO TO UNIVERSAL EXITT1 

Cell phone ................................................................................5 GO TO UNIVERSAL EXITCELL_1 

Answering machine .................................................................6 GO TO MSG_Y

R will call 800 line/verify website ...........................................7 GO TO CNOTES_1_1

R asks for letter ........................................................................8 GO TO UNIVERSAL EXIT

M1_NAME

Supervisor review.....................................................................9 GO TO CNOTES_1_1

(Raise your hand to get permission before using this code)

[IF MOST KNOWLEDGEABLE PARENT HAS NOT BEEN IDENTIFIED:

May I please speak with the parent or guardian who knows the most about the health of the 

child[ren] in the household?]

[IF MOST KNOWLEDGEABLE PARENT HAS BEEN DETERMINED:

May I please speak with [NAME]/the person who had started the interview?]

THANK_YOU

_OOS We are only interviewing families living in their usual place of residence, those are all the

questions I have. Thank you.

SALZ Is this telephone number for business useonly?

Yes ...........................................................................................1 GO TO SALZ_BUS

No.............................................................................................2 GO TO INTRO_1 

DORM/PRISON/HOSTEL .....................................................3 GO TO SALZ_BUS

PAGING SERVICE.................................................................4 GO TO SALZ_BUS

SASERV WAS THIS A BUSINESS, HOUSEHOLD, [IF RDD_NCCELL_CCELL = 1DISPLAY "CELL

PHONE”], OR COULD NOT BE DETERMINED? 

(1) Business – set to business disposition (ITS 38)

(3) See the logic in the Additional skip logic

(4) Could not determine – set as call back - ITS = 37

(5) Answering Machine said "Take Me Off YourList"

(9) See the logic in the Additional skip logic 

Additional skip logic: 

Response Option (3): 

IF RDD_NCCELL_CCELL = 1, 2, OR 3 AND TXFLG = 0 or 2 DISPLAY

(3) Household – set to call back - ITS = 36

ELSE IF RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 1 DISPLAY

(3) LANDLINE - ITS = 37 - SET RDD_NCCELL_CCELL = 1
Series 1, No. 59  Page 45 

Response Option (9): 

IF RDD_NCCELL_CCELL = 1 display

(9) Cell phone

IF TXFLG = 1 THEN SET RDD_NCCELL_CCELL = 3 AND SET ITS = 37, ELSE 

TERMINATE AS ITS = 41

S_KIDS Are there any children living in yourhousehold?

(1) YES [GO TO S_WARM]

(0) NO [GO TO NOCHILD]

(6) DON'T KNOW [GO TO S_WARM]

(7) REFUSED [GO TO S_WARM] 

S_CELL Am I speaking to you on your cell phone?

(1) YES [GO TO S_WARM]

(0) NO [GO TO S1 - SET RDD_NCCELL_CCELL =1]

S_WARM If you are currently driving a car or doing any activity that requires your full attention I need to 

call you back at a later time.

[If RDD_NCCELL_CCELL=2,3 and NEWPHONE_FLAG=1 display "INTERVIEWER NOTE: 

THE NUMBER FOR THIS CASE WAS CHANGED BY THE RESPONDENT ON A 

PREVIOUS CALL. THE ORIGINAL NUMBER IS [OLD_NUMBER].

(1) CONTINUE [GO TO S1]

(2) R UNABLE TO CONTINUE [GO TO S_ATTN] 

(3) NOT A CELL PHONE [GO TO S1]

S_ATTN For your safety, we will call you back at anothertime.

EVEN IF THE RESPONDENT IS USING A HANDS-FREE DEVICE WHILE DRIVING, YOU 

MUST END THE CALL.

(1) CALL BACK ANOTHER TIME [GO TO CB1]

(2) CALL BACK AT ANOTHER NUMBER REQUESTED [GO TO CB1N_WARNING]

(3) WRONG TIME ZONE FOR CELL PHONE [GO TO CELL_TZ_1] 

(4) GO BACK TO S_WARM

CELL_TZ_1 In what time zone would you like to be called?

(1) ATLANTIC TIME [Change TZ variable to 58 and GO TO CB1]

(2) EASTERN STANDARD TIME [Change TZ variable to 62 and GO TO CB1]

(3) CENTRAL STANDARD TIME [Change TZ variable to 65 and GO TO CB1]

(4) STANDARD MOUNTAIN TIME [Change TZ variable to 69 and GO TO CB1]

(5) US STANDARD MOUNTAIN TMIE (AZ) [Change TZ variable to 68 & GO TO CB1]

(6) PACIFIC STANDARD TIME [Change TZ variable to 70 and GO TO CB1]

(7) ALASKAN STANDARD TIME [Change TZ variable to 71 and GO TO CB1]

(8) HAWAIIAN STANDARD TIME [Change TZ variable to 72 and GO TO CB1]

(10) Go Back to INTRO_1 [GO TO INTRO_1 ELSE GO TO

N_INTRO1]

(12) RESPONDENT DOESN'T KNOW / KEEP OLD TIME ZONE [GO TO CB1]

(97) Refused to continue/ hung up [TERMINATE, SET ITS=41]
Page 46  Series 1, No. 59 

CELL_1 I have called (READ PHONE NUMBER FROM TOP SCREEN) is this your cell phone number

or has this number been forwarded to your cellphone?

DO NOT USE THE HAND ON THIS SCREEN. IF YOU DON’T KNOW HOW TO CODE 

THIS CASE, ASK A SUPERVISOR FOR HELP.

(1) Cell phone [GO TO CELL_EXIT]

(2) Number forwarded to cell phone [GO TO CB1]

(3) Respondent Hung Up Before Confirmation [TERMINATE, set ITS = 41]

(4) Go Back to INTRO_1

CELL_EXIT We are not interviewing cell telephone numbers at the moment, sorry for the interruption. Thank 

you very much.

No Call Notes; TERMINATE INTERVIEW and Set ITS=41

S1 IF TXFLG=1 READ: Am I speaking to someone who lives inthis household who is over 17 years

old?

ELSE READ: Am I speaking to someone [IF RDD_NCCELL_CCELL = 1 "who lives in this 

household"] who is over 17 years old?

[IF RDD_NCCELL_CELL=1 then display: "IF THE RESPONDENT SAYS NO: ASK TO 

SPEAK WITH SOMEONE OVER 17 WHO LIVES IN THE HOUSEHOLD."]

I AM THAT PERSON................................................................1 IF RDD_NCCELL_CCELL = 

2 OR 3 AND 

TAKE_ALL_CELL_FLAG = 

0, GO TO LANDLINE, ELSE 

GO TO S_NUMB

THIS IS A BUSINESS ...............................................................2 GO TO SALZ

NEW PERSON COMES TO PHONE........................................3 GO TO INTRO_1

IF RDD_NCCELL_CCELL = 1 OR TXFLG = 1 DISPLAY:

DOESN’T LIVE IN HOUSEHOLD...........................................8 GO TO CALLBACK, SET

DISP AND TERMINATE - 

Set ITS=27, 28 or 29

ELSE IF RDD_NCCELL_CCELL = 2 or 3 DISPLAY:

DOESN”T USUALLY USE THIS PHONE...............................8 GO TO CALLBACK, SET

DISP AND TERMINATE - 

Set ITS=27, 28 or 29

IF RDD_NCCELL_CCELL = 1 OR TXFLG = 1 DISPLAY:

NO PERSON AT HOME WHO IS OVER 17............................9 GO TO S2_B

ELSE IF RDD_NCCELL_CCELL = 2 or 3 DISPLAY:

NO, R IS NOT 18 OR OLDER...................................................9 GO TO S2_B

REFUSED.................................................................................97 GO TO UNIVERSAL EXIT

R1
Series 1, No. 59  Page 47 

SALZ_BUS We are interviewing only private residences. Thank youvery much. 

[TERMINATE INTERVIEW]

S2_B Does anyone [IF RDD_NCCELL_CCELL =1 live in your household / IF

RDD_NCCELL_CCELL = 2, 3 use this cell phone ] who is over 17 yearsold?

IF THE RESPONDENT SAYS NO, READ. "Just to clarify, no one 18 years of age or older [IF 

RDD_NCCELL_CCELL = 1 lives in this household / IF RDD_NCCELL_CCELL = 2, 3 uses this

cell phone]?")

(1) Yes, They are coming to the phone ......................................... GO TO appropriate INTRO

(2) Yes, But no one is home, so set a callback.............................. GO TO

S2_B_1_WARNING_TEXT

(3) No, No adults [ IF RDD_NCCELL_CCELL=1 live in the household at any time / IF 

RDD_NCCELL_CCELL =2,3 use this cell phone]................. [GO TO MINOR_EXIT]

IF RDD_NCCELL_CCELL=1 DISPLAY:

(4) Teen Line (Collect another telephone number)....................... GO TO 

S2_C (97) REFUSED ................................................................... GO TOR1

S2_B_ 

WARNING_

TEXT Thank you, we’ll try back anothertime.

[CREATE AN APPOINTMENT OR SET GENERAL CALL BACK. ENTER DATE/TIME AND 

CONTACT NAME IF KNOWN]

MINOR_EXIT Those are all the questions I have. I’d like to thank you on behalf of the Centers for Disease

Control and Prevention for the time and effort you’ve spent answering these questions.

IF RDD_NCCELL_CCELL = 2, 3 THEN TERMINATE AND ASSIGN ITS 79

ELSE IF RDD_NCCELL_CCELL = 1 TERMINATE AND ASSIGN ITS 60 - [If call count of

ITS 60 =1 delay it for 7 days or 21 shifts else if call count of ITS 60 >1 then finalize the case] 

S2_C Is there another telephone number that I shouldcall? 

GO TO INSTRUCTION: WARNING: THE PHONE NUMBER FOR THIS INTERVIEW IS 

CHANGED NOW FROM X TO X.

GO TO CB1 (APPOINTMENT SCREEN) THEN C_NOTES_1_1
Page 48  Series 1, No. 59 

NIS Screening

S_NUMB How many children between the ages of 12 months and 3 years old are living or staying in your 

household?

IF ONE OR MORE, ENTER # OF CHILDREN ....................... (ENTER 01 to 09)

IF NO CHILDREN ENTER 0 ................................................... (SEE ADDITIONAL SKIP

INSTRUCTIONS BELOW)

(96) DON’T KNOW ................................................................. GO TO SOFTCHECK_77

(97) REFUSED ......................................................................... GO TO UNIVERSAL EXIT-R1

IF S_NUMB=0THEN:

IF SUC=1 & ASK_TEEN=0, THEN (GO TO LF_INTRO) 

ELSE IF ASK_TEEN=1, THEN GO TO TIS_UNDER18

IF SUC=2, THEN GO TO S_UNDER18 (CSHCN-SCREENER) 

IF SUC=4 & ASK_TEEN=0 THEN GO TO S_UNDER18 

ELSE IF ASK_TEEN=1 THEN GO TO TIS_UNDER18

SOFT

CHECK_77 ASK FOR ANOTHER PERSON OR SCHEDULE APPOINTMENT ON THE NEXTSCREEN

(1) CONTINUE......................................................................... GO TO S_NUMB

(2) APPOINTMENT................................................................. GO TO UNIVERSAL EXITCB1
Series 1, No. 59  Page 49 

Augmentation Sample

INTRO_AUG IF SAMPLE_USE_CODE = 3, READ INTRO_AUG.

Hello, my name is . I am calling on behalf of the Centers for DiseaseControl and 

Prevention. We are doing a national survey [IF RDD_NCCELL_CCELL=2, 3 "on cell phones"] 

about the health of children and teenagers. Your [IF RDD_NCCELL_CCELL=2,3 "cell phone"; 

ELSE "telephone"] number has been selected at random to be included in thestudy.

(1) CONTINUE ............................................................................ SEE LOGIC BELOW 

IF INTRO_1=1 AND RDD_NCCELL_CCELL = 1, GO TO S1

ELSE IF INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 1 , GO 

TO S_CELL

ELSE IF INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND S_KIDS_FLAG=0, GO TO S_WARM

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=3,5,6 AND PRE_KIDS=1 AND S_KIDS=NULL AND 

S_UNDR18=NULL) THEN GO TO S_KIDS

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=3,5,6 AND PRE_KIDS=1 AND S_KIDS NOT MISSING) 

GO TO S_WARM.

ELSE IF (INTRO_1=1 AND RDD_NCCELL_CCELL = 2 OR 3 AND TXFLG = 0 or 2 

AND SAMPLE_USE_CODE=1,2,4 AND PRE_KIDS=1 ) GO TO S_WARM.

(2) CONFIRM BUSINESS........................................................... GO TO SALZ

(3) OUT OF SCOPE ..................................................................... GO TO THANK_YOU_OOS

(4) TERMINATE THE INTERVIEW.......................................... GO TO T1 

IF RDD_NCCELL_CCELL = 1 DISPLAY :

(5) CELL PHONE......................................................................... GO TO CELL_1 

ELSE IF RDD_NCCELL_CCELL = 2, 3 AND TXFLG = 1 DISPLAY:

(5) LANDLINE - YOU WILL NOT TERMINATE..................... GO TO S1 and set

RDD_NCCELL_CCELL=1 

ELSE IF RDD_NCCELL_CCELL = 2, 3 AND TXFLG = 0 DISPLAY:

(5) LANDLINE............................................................................. GO TO LANDLINE EXIT and

set ITS=88

(6) ANSWERING MACHINE [FILL] ......................................... GO TO S1

If message is to be left then GO TO SASERV else hang up and set ITS =35

(7) R WILL CALL 800 LINE/VERIFY WEBSITE ..................... GO TO P1/VERIFY_INFO / 

Set ITS =69

(8) R ASKS FOR LETTER........................................................... GO TO M1_NAME

(9) SUPERVISOR REVIEW........................................................ Set ITS = 49

(15) Test sample - use only if respondent instruct that this call was a test - Set ITS =119

(16) CONTINUE THE CASE WITH LANGUAGELINE

IF RDD_NCCELL_CCELL = 2, 3 DISPLAY:

(17) DROPPED CALL GO TO CNOTES_1_1> set ITS=81 

(SCHEDULE A CALL BACK FOR 1 

MINUTES) 
Page 50  Series 1, No. 59 

S_KIDS Are there any children living in your household?

HELP TEXT DISPLAYED FOR SLAITS-ONLY CASES: 

A CHILD IS COUNTED AS "LIVING IN THE HOUSEHOLD" IF THE CHILD:

- HAS BEEN STAYING THERE (OR IS EXPECTED TO STAY THERE) FOR AT 

LEAST TWO MONTHS

- THE LENGTH OF THE CURRENT STAY IS UNKNOWN, BUT THERE IS NO 

OTHER PLACE WHERE THE CHILD USUALLY STAYS

- USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR 

LESS THAN TWO MONTHS (WHETHER TRAVELING, IN THE HOSPITAL, OR 

AWAY FOR ANY OTHER REASON)

- USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR 

TWO MONTHS OR MORE BECAUSE THEY ARE AT SCHOOL (COLLEGE, 

BOARDING SCHOOL, MILITARY ACADEMY, PREP SCHOOL,ETC.)

- ONLY LIVES PART-TIME IN THE HOUSEHOLD BECAUSE OF CUSTODY 

ISSUES, BUT IS STAYING THERE AT THE TIME OF THECALL

(1) YES ......................................................................................... [GO TO S_WARM]

(0) NO........................................................................................... [GO TO NOCHILD]

(6) DON'T KNOW...................................................................... [GO TO S_WARM]

(7) REFUSED ............................................................................. [GO TO S_WARM]

S_CELL Am I speaking to you on your cell phone?

(1) YES [GO TO S_WARM]

(0) NO [GO TO S1 - SET RDD_NCCELL =1]

S_WARM If you are currently driving a car or doing any activity that requires your full attention I need to 

call you back at a later time.

(1) CONTINUE [GO TO S1]

(2) R UNABLE TO CONTINUE [GO TO S_ATTN]

(3) NOT A CELL PHONE [GO TO S1] 

S_ATTN For your safety, we will call you back at anothertime.

EVEN IF THE RESPONDENT IS USING A HANDS-FREE DEVICE WHILE DRIVING, YOU 

MUST END THE CALL.

(1) CALL BACK ANOTHER TIME [GO TO CB1]

(2) CALL BACK AT ANOTHER NUMBER REQUESTED [GO TOCB1N_WARNING]

(3) WRONG TIME ZONE FOR CELL PHONE [GO TO CELL_TZ_1] 

(4) GO BACK TO S_WARM

CELL_TZ_1 In what time zone would you like to be called?

(1) ATLANTIC TIME [Change TZ variable to 58 and GO TO CB1]

(2) EASTERN STANDARD TIME [Change TZ variable to 62 and GO TO CB1]

(3) CENTRAL STANDARD TIME [Change TZ variable to 65 and GO TO CB1]

(4) STANDARD MOUNTAIN TIME [Change TZ variable to 69 and GO TO CB1]

(5) US STANDARD MOUNTAIN TIME (ARIZONA) [Change TZ variable to 68 & GO

TO CB1]

(6) PACIFIC STANDARD TIME [Change TZ variable to 70 and GO TO CB1]

(7) ALASKAN STANDARD TIME [Change TZ variable to 71 and GO TO CB1]

(8) HAWAIIAN STANDARD TIME [Change TZ variable to 72 and GO TO CB1]
Series 1, No. 59  Page 51 

(10) Go Back to INTRO_1 [GO TO INTRO_1 ELSE GO TO N_INTRO1]

(12) RESPONDENT DOESN'T KNOW / KEEP OLD TIME ZONE [GO TO CB1]

(97) Refused to continue/ hung up [TERMINATE , SET ITS=41]

CELL_1 I have called (READ PHONE NUMBER FROM TOP SCREEN), is this your cell phone number

or has this number been forwarded to your cellphone?

DO NOT USE THE HAND ON THIS SCREEN. IF YOU DON’T KNOW HOW TO CODE 

THIS CASE, ASK A SUPERVISOR FOR HELP.

(1) Cell phone [GO TO CELL_EXIT]

(2) Number forwarded to cell phone [GO TO CB1]

(3) Respondent Hung Up Before Confirmation [TERMINATE, set ITS = 41]

(4) Go Back to INTRO_1

CELL_EXIT We are not interviewing cell telephone numbers at the moment, sorry for the interruption. Thank 

you very much.

[No Call Notes; TERMINATE INTERVIEW and Set ITS=41]

S1 IF TXFLG=1 READ: Am I speaking to someone who lives inthis household who is over 17 years

old?

ELSE READ: Am I speaking to someone [IF RDD_NCCELL_CCELL = 1 "who lives in this 

household"] who is over 17 years old?

[IF RDD_NCCELL_CELL=1 then display: "IF THE RESPONDENT SAYS NO: ASK TO 

SPEAK WITH SOMEONE OVER 17 WHO LIVES IN THE HOUSEHOLD."]

I AM THAT PERSON................................................................1 IF [S.C.] IS SELECTED,GO 

TO REMIND1/ ELSE 

CONTINUE WITH 

INTERVIEW

THIS IS A BUSINESS ...............................................................2 GO TO SALZ

NEW PERSON COMES TO PHONE........................................3 GO TO INTRO_1

IF RDD_NCCELL_CCELL = 1 OR TXFLG = 1 DISPLAY:

DOESN’T LIVE IN HOUSEHOLD...........................................8 GO TO CALLBACK, SET

DISP AND TERMINATE - 

Set ITS=27, 28 or 29

ELSE IF RDD_NCCELL_CCELL = 2 or 3 DISPLAY:

DOESN’T USUALLY USE THIS PHONE...............................8 GO TO CALLBACK, SET

DISP AND TERMINATE - 

Set ITS=27, 28 or 29

IF RDD_NCCELL_CCELL = 1 OR TXFLG = 1 DISPLAY:

NO PERSON AT HOME WHO IS OVER 17............................9 GO TO S2_B

ELSE IF RDD_NCCELL_CCELL = 2 or 3 DISPLAY: 

NO, R IS NOT 18 OR OLDER...................................................9 GO TO S2_B

REFUSED.................................................................................97 GO TO UNIVERSAL EXIT

R1
Page 52  Series 1, No. 59 

S2_B Does anyone [IF RDD_NCCELL_CCELL =1 live in your household / IF

RDD_NCCELL_CCELL = 2, 3 use this cell phone ] who is over 17 yearsold?

IF THE RESPONDENT SAYS NO, READ. "Just to clarify, no one 18 years of age or older [IF 

RDD_NCCELL_CCELL = 1 lives in this household / IF RDD_NCCELL_CCELL = 2, 3 uses this 

cell phone]?")

(1) Yes, They are coming to the phone ...................................... GO TO appropriate INTRO

(2) Yes, But no one is home, so set a callback........................... GO TO

S2_B_1_WARNING_TEXT

(3) No, No adults [ IF RDD_NCCELL_CCELL=1 live in the household at any time / IF 

RDD_NCCELL_CCELL =2,3 use this cell phone] [GO TO MINOR_EXIT]

IF RDD_NCCELL_CCELL=1 DISPLAY:

(4) Teen Line (Collect another telephone number) .................. GO TO S2_C 

(7) REFUSED ....................................................................... GO TOR1

CP_LANDLINE

IF PAN_BANK=1 then skip to CP_CELLUSE, ELSE GO TO LANDLINE

LANDLINE Do you have a landline telephone in yourhousehold?

READ AS NECESSARY: Please do not include:

- modem-only lines,

- fax-only lines,

- lines used just for home security systems, 

- beepers,

- Skype

- pagers, or

- cell phones.

Please include Voice Over I.P. or VOIP numbers.

(1) YES [GO TO CELLUSE] 

(0) NO [GO TO CP_CELLUSE] 

(6) DON’T KNOW [GO TO CP_CELLUSE]

(7) REFUSED [GO TO CP_CELLUSE]

CELLUSE Thinking just about the land line home phone, not your cell phone, if that telephonerang and 

someone were home, under normal circumstances how likely is it that it would beanswered? 

Would you say extremely likely, somewhat likely, somewhat unlikely, or not at all likely?

(1) EXTREMELY LIKELY [GO TO LANDLINE_EXIT]

(2) SOMEWHAT LIKELY [GO TO LANDLINE_EXIT]

(3) SOMEWHAT UNLIKELY [GO TO CP_CELLUSE] 

(4) NOT AT ALL LIKELY [GO TO CP_CELLUSE] 

(6) DON’T KNOW [GO TO LANDLINE_EXIT]

(7) REFUSED [GO TO LANDLINE_EXIT]

IF CELLUSE = 3 OR 4 OR LANDLINE 0,6,7 SET CELL_OM=1, ELSE CELL_OM=NULL

(default)

CP_CELLUSE IF SAMPLE_USE_CODE = 3,5,6, FOLLOW AUGMENTIONPATHWAYS.
Series 1, No. 59  Page 53 

S_UNDR18 [IF S_NUMB GE 1 AND NIS IS DONE, FILL S_UNDR18 FROMNIS DATA

S_UNDR18 = C1 – C1A. C1 – C1A CANNOT BE LE 0. IF THAT IS THE CASE, ASK 

S_UNDR18]

[(IF RDD_NCCELL_CCELL=2,3 and PRE_KIDS=1 and S_KIDS=1) then display: "Please tell 

me how many people less than 18 years old live in this household."

ELSE IF (RDD_NCCELL_CCELL=1 OR (RDD_NCCELL_CCELL=2,3 and

S_KIDS_FLAG=0)) then display "How many people less than 18 years old live in this 

household?"]

1 OR GREATER [SKIP TO ISC200]

(0) ZERO [SKIP TO NOCHILD]

(6) DON’T KNOW [GO TO ASK_ANOTHER]

(7) REFUSED [TERMINATE AND SET AS REFUSAL ((IF INCENTIVE > 0 THEN

GO TO ADDRESS COLLECTION), THEN GO TO R1, SET ITS = 

23)]

A CHILD IS COUNTED AS "LIVING IN THE HOUSEHOLD" IF THE CHILD:

- HAS BEEN STAYING THERE (OR IS EXPECTED TO STAY THERE) FOR AT LEAST 

TWO MONTHS

- THE LENGTH OF THE CURRENT STAY IS UNKNOWN, BUT THERE IS NO OTHER 

PLACE WHERE THE CHILD USUALLY STAYS

- USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR LESS THAN 

TWO MONTHS (WHETHER TRAVELING, IN THE HOSPITAL, OR AWAY FOR ANY 

OTHER REASON)

- USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR TWO 

MONTHS OR MORE BECAUSE THEY ARE AT SCHOOL (COLLEGE, BOARDING 

SCHOOL, MILITARY ACADEMY, PREP SCHOOL,ETC.)

- ONLY LIVES PART-TIME IN THE HOUSEHOLD BECAUSE OF CUSTODY ISSUES, BUT 

IS STAYING THERE AT THE TIME OF THECALL

NUMBER OF CHILDREN = 0 [GO TO NOCHILD]

NUMBER OF CHILDREN > 1 AND HH NIS-ELIGIBLE [GO TO SL_INTRO] 

NUMBER OF CHILDREN > 1 AND HH NIS-INELIGIBLE [GO TO ISC200]

S_UNDR18_CONF

WARNING: ACCORDING TO NIS THERE [IF S_NUMB=1 THEN FILL: IS / IF S_NUMB > 1 

THEN FILL: ARE] AT LEAST [FILL S_NUMB] [if S_NUMB=1 THEN FILL: CHILD / IF 

S_NUMB > 1 THEN FILL: CHILDREN] IN THE HOUSEHOLD.

PLEASE RE-ASK S_UNDR18 ASKING FOR ALL OF THE CHILDREN IN THE 

HOUSEHOLD.

(1) Count incorrect - change total number of children [SKIP BACK TO S_UNDR18]

(2) Total number of children confirmed as correct [GO TO LL_TYPE if Language

Line case, ELSE go to 

CHECKPOINT.]

LL_TYPE WHAT LANGUAGE WAS NEEDED TO COMPLETE THISINTERVIEW?

(1) KOREAN [Go to LL_END] 

(2) MANDARIN [Go to LL_END] 

(3) CANTONESE [Go to LL_END] 
Page 54  Series 1, No. 59 

(4) VIETNEMESE [Go to LL_END] 

(5) ARABIC [Go to LL_END] 

(6) FRENCH/CREOLE/HAITIAN [Go to LL_END]

(7) ITALIAN [Go to LL_END] 

(8) JAPANESE [Go to LL_END] 

(9) POLISH [Go to LL_END] 

(10) PORTUGESE [Go to LL_END] 

(11) TAGALOG/FILIPINO [Go to LL_END] 

(12) ENGLISH [CONTINUE WITH INTERVIEW AS USUAL]

(13) SPANISH [CONTINUE WITH INTERVIEW AS USUAL]

(14) ANOTHER LANGUAGE [Go to LL_END]

LL_END IF LL_TYPE = 1,2,3, or 4 DISPLAY:

Those are all the questions I have at this time. Someone who speaks [IF LL_TYPE=1 display 

"Korean"; IF LL_TYPE=2 display "Mandarin"; IF LL_TYPE=3 display "Cantonese"; IF 

LL_TYPE=4 display "Vietnamese"] will call you back to complete the interview as soon as 

possible. I’d like to thank you on behalf of the Centers for Disease Control and Prevention for the 

time and effort you’ve spent answering these questions. If you have any questions about this 

survey, you may call my supervisor toll-free at [IF SUC = 1, 2, 4 FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 /

IF SUC = 3, 5, 6 FILL 1 - 8 8 8 - 9 9 0 - 9 9 8 6 ] . If you have questions about your rights as a 

survey participant, you may call the chairman of the Research Ethics Review Board at 1-800-223- 

8118. Thank you again.

ELSE, DISPLAY:

Those are all the questions I have. I’d like to thank you on behalf of the Centers for Disease 

Control and Prevention for the time and effort you’ve spent answering these questions. If you 

have any questions about this survey, you may call my supervisor toll-free at [IF SUC = 1, 2, 4 

FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC = 3, 5, 6 FILL 1 - 8 8 8 - 9 9 0 - 9 9 8 6 ]. If you have

questions about your rights as a survey participant, you may call the chairman of the Research 

Ethics Review Board at 1-800-223-8118. Thank you again.

(1) EXIT SCRIPT READ

(2) ASIAN LANGUAGE INTERVIEWERS CONTINUEINTERVIEW

ASK_ANOTHER

Is there anyone in your household who knows how many people in this household are less than 18 

years old?

(1) NEW PERSON COMES TO PHONE [GO TO INTRO_SWITCH]

(0) NO [IF INCENTIVE>0 THEN GO TO ADDRESS

COLLECTION THEN GO TO NSCH_TERM]

NSCH_TERM Thank you, we’ll try back another time. 

INTRO_SWITCH

Hello, my name is . I'm calling on behalf of the Centers forDisease Control

and Prevention. We are doing a national survey about the health of children and teenagers, and I 

was told that you were the person to talk with about the health of the [IF S_UNDR18 =1, INSERT 

"child"; IF S_UNDR18 > 1 INSERT "children"] in thehousehold.

(0) CONTINUE
Series 1, No. 59  Page 55 

GO TO S_UNDR18

NOCHILD (IF INCENTIVE > 0 THEN GO TO ADDRESS COLLECTION), THEN READNOCHILD

Those are all the questions I have. We are only interviewing in households with children. I’d like 

to thank you on behalf of the Centers for Disease Control and Prevention for the time and effort 

you’ve spent answering these questions.

TERMINATE [SET ITS = 61]

NEW_RESP Hello, my name is . I'm calling on behalf of the Centers forDisease Control

and Prevention. We are doing a national survey about the health of children and teenagers, and I 

was told that you were the person to talk with about the health of the [IF S_UNDR18 =1, INSERT 

"child"; IF S_UNDR18 > 1 INSERT "children"] in thehousehold.

(1) CONTINUE

S3_NSCH_LTR

IF NO ADVANCE LETTER SENT, THEN SKIP TO SL_INTRO

A letter describing this survey may have been sent to your home recently. Do you remember 

seeing the letter?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 

AGE_X CATI INSTRUCTION (AGE_GRID) IF S_UNDR18 = 1, FILL “age” AND “child”. ELSE, FILL

“ages” AND “children”.

IF S_NUMB = 0, DISPLAY THIS TEXT WHEN ASKING ABOUT FIRST CHILD: “Many of

my questions are only for children of certain ages. So I'll know which questions to ask, please tell 

me the [age/ages] of the [child/children] less than 18 years old living in this household." FOR 

ALL SUBSEQUENT CHILDREN (LOOP UNTIL # OF CHILDREN=S_UNDR18) DISPLAY:

(READ IF NECESSARY): "Please tell me the age of the next child who lives in this household."

ELSE IF (S_NUMB=S_UNDR18 then FILL AGE_1 (and AGE_1Y_X as needed) with age of 

child and skip to AGE_CONF.

ELSE IF S_NUMB > 0 AND S_UNDR18 – S_NUMB > 0, FILL: "You have already given me 

(FILL NAME OF NIS-ELIGIBLE CHILD OR CHILDREN)'s birth date(s). Now, would you 

please tell me the [age/ages] of the other [IF S_UNDER18 - S_NUMB = 1, INSERT "child"; IF 

S_UNDR18 - S_NUMB > 1, INSERT "children"] living in this household.” FOR ALL 

SUBSEQUENT CHILDREN (LOOP UNTIL # OF CHILDREN=S_UNDR18 - S_NUMB)

DISPLAY: (READ IF NECESSARY: "Please tell me the age of the next child who lives in this 

household.")

Display for AGE_1

INTERVIEWER: IF R PROVIDES AGES FOR ALL CHILDREN UP FRONT, TYPE IN THE 

AGES AS CATI PROMPTS FOR THEM.

ENTER 77 FOR DON'T KNOW AND 99 FOR REFUSED
Page 56  Series 1, No. 59 

IF AGE IS LESS THAN 1 MONTH OLD, RECORD 0 MONTHS. A CHILD IS COUNTED AS 

"LIVING IN THE HOUSEHOLD" IF THE CHILD:

• HAS BEEN STAYING THERE (OR IS EXPECTED TO STAY THERE) FOR AT LEAST 

TWO MONTHS

• THE LENGTH OF THE CURRENT STAY IS UNKNOWN, BUT THERE IS NO OTHER 

PLACE WHERE THE CHILD USUALLY STAYS

• USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR LESS 

THAN TWO MONTHS (WHETHER TRAVELING, IN THE HOSPITAL, OR AWAY FOR 

ANY OTHER REASON)

• USUALLY STAYS IN THE HOUSEHOLD, BUT IS CURRENTLY AWAY FOR TWO 

MONTHS OR MORE BECAUSE THEY ARE AT SCHOOL (COLLEGE, BOARDING 

SCHOOL, MILITARY ACADEMY, PREP SCHOOL,ETC.)

• ONLY LIVES PART-TIME IN THE HOUSEHOLD BECAUSE OF CUSTODY ISSUES, 

BUT IS STAYING THERE AT THE TIME OF THE CALL

 ENTER VALUE

[IF 77 GO TO WHEN_CALL, 

IF 99 GO TO AGE_REF]

AGES SHOULD BE STORED IN AGE_1 - AGE_9.

PLEASE VERIFY THAT TEEN "BACKGROUND" VARIABLES FOR ROSTER FILL 

APPROPRIATELY TO CSHCN. PLEASE ALSO VERIFY THAT MAGE AND YAGE FILL 

CORRECTLY.

IF SAMPLE_USE_CODE = 4: FILL AGE ROSTER FROM TEEN ROSTER. 

AGE1_X (1) MONTHS

 (2) YEARS

CONTINUE TO LOOP FOR ALL REMAINING CHILDREN 

IF MONTHS, RANGE CHECK = 1-24;

IF YEARS, RANGE CHECK = 1-17

THESE SHOULD APPEAR ON THE SAME SCREEN AS AGE_X. 

AFTER LOOP ENDS, GO TO AGE_1Y_1.

WHEN_CALL What would be a good time to reach a person who knows the child's age?

(1) SET APPOINTMENT FOR CALLBACK [GO TO CB1]

(2) PERSON AVAILABLE [GO TO INTRO_AGE]

ON A CALL-BACK, POR IS AGE_X.

AGE_REF The reason we need your child's age is to know which health and health care questions toask. The

information you provide is completely confidential.

(1) YES [GO TO AGE_X]

(0) NO [GO TO AGE_TERM] 
Series 1, No. 59  Page 57 

AGE_TERM IF INCENTIVE>0 THEN GO TO ADDRESS COLLECTION THEN READAGE_TERM.

Those are all the questions I have. I’d like to thank you on behalf of the Centers for Disease 

Control and Prevention for the time and effort you’ve spent answering these questions.

INTRO_AGE Hello, my name is . I'm calling on behalf of the Centers forDisease Control

and Prevention. We are doing a nationwide survey about the health of children and teenagers, and 

I was told that you were the person to talk with about the health of the (IF S_UNDR18 =1,

INSERT "child"; IF S_UNDR18 > 1 INSERT "children") in your household

(1) CONTINUE [RETURN TO AGE_X]

AGE_1Y_1 IF EXACTLY 1 AGE_X=1 YEAR OLD OR 0 YEARS OLD, THEN ASK "Because some ofour

questions are only for children of certain ages, can you please tell me the age of the [1-year-old/0- 

year-old] child in months? "

ELSE IF > 1 AGE_X = 1 YEAR OLD OR 0 YEARS OLD, THEN ASK "Because some of our

questions are only for children of certain ages, can you please tell me the age of the first [1-yearold/0-year-old] child in months? "

ELSE IF 0 AGE_X = 1 YEAR OLD THEN SKIP TO AGE_CONF.

MONTHS [RANGE: 0-24]

IF EXACTLY 1 AGE_X = 1 YEAR OLD, GO TO AGE_CONF, ELSE IF > 1 AGE_X = 1 YEAR 

OLD GO TO AGE_1Y_2-9.

AGE_1Y_2- 

AGE_1Y_9 And how about the next [1 year old / 0 year old]?

MONTHS [RANGE: 0-24]

CONTINUE TO LOOP FOR ALL REMAINING 1 YEAR OLDS. THEN GO TO AGE_CONF. 

AGE_CONF So, you have a [FILL WITH AGE IN YEARS FOR ALL CHILDREN 2 YEARS OLDOR

OLDER, AND AGE IN MONTHS FOR ALL CHILDREN UNDER 24 MONTHS OLD., 

INCLUDING AGES FOR ANY NIS-ELIGIBLE CHILDREN. E.G., 16 month old, 10 year old,

and 15 year old/ IF > 1 CHILD, INSERT 'and' BEFORE THE LAST AGE_X] living at this 

address all or most of the time. Is that correct?

(1) YES [SKIP TO MULTIAGE] 

(2) NO, WRONG AGES [RETURN TO AGE_X]

(3) NO, WRONG NUMBER OF CHILDREN [SKIP TO S_UNDR18]

(4) NO, NOT ALL CHILDREN LIVING AT THIS ADDRESS ALL OR MOST OF THETIME

[RETURN TO S_UNDR18]

MULTIAGE CATI INSTRUCTION (MULTIAGE): IF NO CHILDREN ARE THE SAME AGE,SKIP TO

C2Q03_X, ELSE ASK

Since you have more than one child who is [FILL DUPLICATE AGES FROM AGE_CONF, E.G. 

3 years old], I need a way to refer to each of them during the interview.

(1) CONTINUE [RECORD NAMES IN NAME_1 – NAME_9]

(6) DON'T KNOW [GO TO REFNAME1] 

(7) REFUSED [GO TO REFNAME1] 
Page 58  Series 1, No. 59 

IF SUC=4 THEN FILL FROM TIS_MULTIAGE.

CATI INSTRUCTION: loop for all NAME_X. GO TO NSCH RANDOM SELECTION 

PROCESS.

NAME_1 -NAME_9

CATI INSTRUCTION: loop for all NAME_X. GO TO NSCH RANDOM SELECTION 

PROCESS.

IF REFNAME1=99 THEN DISPLAY: INTERVIEWER INSTRUCTION: RESPONDENT 

REFUSED CHILD'S NAME, ENTER 99

IF REFNAME1 not equal 99 THEN DISPLAY: What is the [other] [FILL AGE] year old child's 

name or initials?

For all cases display the following in red: 

ENTER NAME

(6) DON'T KNOW

(7) REFUSED

NAME: 

IF SUC=4 THEN FILL FROM TIS_NAME_X. 

FILL FROM NIS IF APPROPRIATE.

IF NAME_x = 77 or 99 then the AGEID for that child="[FILL AGE] CHILD [FILL x]" (where x 

is the roster position for that child).

REFNAME1 I would like to assure you that ALL information will be kept in strict confidence and will be 

summarized for research purposes only. Since you have two or more children of the same age, we 

must have some way to tell them apart. You could give me a first name, nickname, or their 

initials.

(1) RESPONDENT WILL GIVE NAMES [RETURN TO NAME_1 THROUGH

NAME_9 AND ENTER]

(2) REFUSED [GO TO REFNAME2] 

REFNAME2 (IF INCENTIVE > 0 THEN GO TO ADDRESS COLLECTION), THEN READREFNAME2.

Those are all the questions I have. I’d like to thank you on behalf of the Centers for Disease 

Control and Prevention for the time and effort you’ve spent answering these questions.

TERMINATE > SET ITS = 23; POINT OF RETURN SHOULD BE MULTIAGE

CPNIS_ELIG IF SAMPLE_USE_CODE = 2: IF AGE_X= 19-35 MONTHS AND S3_3M/D/Y_x = NULL, GO

TO S2Q02A; ELSE SKIP TO NSCH RANDOM SELECTIONPROCESS

ELSE IF SAMPLE_USE_CODE = 3, 4, 5, OR 6: IGNORE LOGIC ABOVE.

S2Q02A Based on the ages you have given me, I now have some questions about [AGEID ORAGEIDs].

(1) CONTINUE [GO TO S3_X]

FILL S_NUMB APPROPRIATELY AND GO TO S3_X. ASK 

NIS FOR ALL CHILDREN THAT HAVE QUALIFIED.

AFTER NIS COMPLETE, SKIP TO NSCH SELECTION PROCESS
Series 1, No. 59  Page 59 

NSCH RANDOM SELECTION PROCESS

AT THIS POINT, A SAMPLE CHILD MUST BE SELECTED FOR THE REST OF THE INTERVIEW FROM 

ALL CHILDREN ROSTERED. IF ONLY ONE CHILD UNDER 18 YEARS OLD (AGE_GRID HAS 1 CHILD 

LISTED), THAT CHILD IS THE SAMPLE CHILD [S.C.] FROM THIS POINT. IF THERE IS MORE THAN 

ONE CHILD UNDER THE AGE OF 18 (AGE_X HAS > 1 CHILD LISTED), ONE OF THESE CHILDREN 

SHOULD BE RANDOMLY SAMPLED AND THAT CHILD IS THE SAMPLE CHILD [S.C.] FROM THIS 

POINT.

STORE SAMPLED CHILD IN VARIABLE: SC_NSCH

S.C. = "your N month/year old" or name from NAME_1 - NAME_9

IF SAMPLE_USE_CODE=4: PERFORM NEW RANDOM SELECTION OF CHILD FROM FULL ROSTER 

COMPLETELY INDEPENDENT OF TEEN SELECTION
Page 60  Series 1, No. 59 

Informed consent

SCQ02 IF S_NUMB=0 or SUC=3,5 or 6 or no ELIG_1-9 =1, SKIP TOSCQ05. IF

SAMPLE_USE_CODE=4 AND NOT NIS OR TEEN ELIGIBLE, SKIP TO SCQ05. ELSE IF 

NIS INTERVIEW WAS CONDUCTED BUT [S.C.] WAS NOT NIS-ELIGIBLE, SKIP TO 

SCQ03 AND DISPLAY SCRIPT 1. IF SAMPLE_USE_CODE=4 AND NIS OR TEEN DONE, 

BUT [S.C.] WAS NOT NIS OR TEEN-ELIGIBLE, SKIP TO SCQO3 AND DISPLAYSCRIPT

1. ELSE IF ELIG_1-9 NOT EQ 1, AND S3_INTRO DISPLAYED, SKIP TO SCQ03 AND 

DISPLAY SCRIPT 2. IF SAMPLE_USE_CODE=4 AND ELIG_1-9 NOT EQ 1, AND 

S3_INTRO DISPLAYED, AND TEEN NOT DONE, SKIP TO SCQ03 AND DISPLAY SCQ03 

SCRIPT 2.

IF S_UNDR18 = 01, SAY: “Next, I have some other questions about the health and health care 

of [S.C.]. As before, you may choose not to answer any questions you don’t wish to answer, or 

end the interview at any time with no impact on the benefits you may receive. [IF NSCH 

INCENTIVE CASE DISPLAY: In appreciation for your time, we will send you

$[MONEY_1/MONEY_2].] This part of the survey will take about [IF NSCH_TIME=0 THEN 

DISPLAY "half an hour"; ELSE IF NSCH_TIME=1 THEN DISPLAY "[MINUTES_1]

minutes"; ELSE IF NSCH_TIME=2 THEN DISPLAY "[MINUTES_2] minutes"]. I’d like to 

continue now unless you have any questions.”

IF S_UNDR18 > 01, SAY: “I appreciate your answers about the immunizations of [NISELIGIBLE CHILDREN, IF SAMPLE_USE_CODE=4 AND TEEN INTERVIEW COMPLETE 

FILL WITH TEEN S.C., ELSE FILL WITH NIS-ELIGIBLE CHILDREN]. The next questions

are about the health and health care of [S.C.]. As before, you may choose not to answer any 

questions you don’t wish to answer, or end the interview at any time with no impact on the 

benefits you may receive. [IF NSCH INCENTIVE CASE DISPLAY: In appreciation for your

time, we will send you $[MONEY_1/MONEY_2].] This part of the survey will take about [IF 

NSCH_TIME=0 THEN DISPLAY "half an hour"; ELSE IF NSCH_TIME=1 THEN DISPLAY 

"[MINUTES_1] minutes"; ELSE IF NSCH_TIME=2 THEN DISPLAY "[MINUTES_2]

minutes"]. I’d like to continue now unless you have any questions.”

(1) CONTINUE [SKIP TO K1Q01]

SCQ03 SCRIPT 1:

I appreciate your answers about the immunizations of [IF SAMPLE_USE_CODE = 2 then fill 

with NIS-ELIGIBLE CHILDREN, IF SAMPLE_USE_CODE=4 AND NIS DONE BUT NO 

TEEN THEN FILL WITH NIS-ELIGIBLE CHILDREN, IF SAMPLE_USE_CODE=4 AND

TEEN INTERVIEW DONE THEN FILL WITH ST]. The next questions are about the health 

and health care of [S.C.]. We need to talk to a parent or guardian who lives in this household 

who knows about the health and health care of [S.C.]. Who would that be?

SCRIPT 2:

Most of this survey will be about the health and health care of [S.C.]. We need to talk to a 

parent or guardian who lives in this household who knows about the health and health care of 

[S.C.]. Who would that be?

(1) MYSELF [SKIP TO SCQ04]

(2) SOMEONE ELSE [SKIP TO SCQ06]
Series 1, No. 59  Page 61 

SCQ04 As before, you may choose not to answer any questions you don’t wish to answer, or end the

interview at any time with no impact on the benefits you may receive. [IF NSCH INCENTIVE 

CASE DISPLAY: In appreciation for your time, we will send you $[MONEY_1/MONEY_2].] 

This part of the survey will take about [IF NSCH_TIME=0 THEN DISPLAY "half an hour"; 

ELSE IF NSCH_TIME=1 THEN DISPLAY "[MINUTES_1] minutes"; ELSE IF NSCH_TIME=2 

THEN DISPLAY "[MINUTES_2] minutes"]. I’d like to continue now unless you have any 

questions.

(1) CONTINUE [SKIP TO K1Q01]

SCQ05 Most of this survey will be about the health and health care of [S.C.]. We need to talk to a parent

or guardian who lives in this household who knows about the health and health care of [S.C.].

Who would that be?

(1) MYSELF [SKIP TO S3_NSCH_LTR]

(2) SOMEONE ELSE [SKIP TO SCQ06]

SCQ06 May I speak with that person now?

(1) YES [SKIP TO NEW_RESP]

(0) NO [SET APPOINTMENT FOR CALLBACK, GO TO CB1] 
Page 62  Series 1, No. 59 

NEW_RESP Hello, my name is . I'm calling on behalf of the Centers forDisease Control 

and Prevention. We are doing a nationwide survey about the health of children and teenagers, and 

I was told that you were the person to talk with about the health and health care of[S.C.].

(1) CONTINUE

S3_NSCH_LTR IF NO ADVANCE LETTER SENT, THEN SKIP TO SL_INTRO.

A letter describing this survey may have been sent to your home recently. Do you remember 

seeing the letter?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

SL_INTRO Before we continue, I’d like you to know that taking part in this research is voluntary. You may 

choose not to answer any questions you don’t wish to answer, or end the interview at any time 

with no impact on the benefits you may receive. We are required by Federal law to develop and 

follow strict procedures to protect the confidentiality of your information and use your answers 

only for statistical research. I can describe these laws if you wish. [IF NSCH INCENTIVE CASE 

DISPLAY: In appreciation for your time, we will send you $[MONEY_1/MONEY_2].] The 

survey will take about [IF NSCH_TIME=0 THEN DISPLAY "half an hour"; ELSE IF 

NSCH_TIME=1 THEN DISPLAY "[MINUTES_1] minutes"; ELSE IF NSCH_TIME=2THEN

DISPLAY "[MINUTES_2] minutes"]. In order to review my work, this call will be recorded and 

my supervisor may listen as I ask the questions. I’d like to continue now unless you have any 

questions.

READ IF NECESSARY: The Public Health Service Act is Title 42 of the US Code, Section 242k. 

The collection of information in this survey is authorized by Section 306 of this Act. Through the 

National Center for Health Statistics, the confidentiality of your responses is assured by Section 

308d of this Act and by the Confidential Information Protection and Statistical Efficiency Act.

Would you like me to read the Confidential Information Protection provisions to you?

IF RESPONDENT WOULD LIKE TO HEAR PROVISIONS, READ: The information you

provide will be used for statistical purposes only. In accordance with the Confidential Information 

Protection provisions of Title V, Subtitle A, Public Law 107-347 and other applicable Federal 

laws, your responses will be kept confidential and will not be disclosed in identifiable form to 

anyone other than employees or agents. By law, every employee of the National Center for Health 

Statistics, the National Center for Immunization and Respiratory Diseases, and its agent, N-O-R-C 

at the University of Chicago, who works on this survey has taken an oath and is subject to a jail 

term of up to 5 years, a fine of up to $250,000, or both, if he or she willingly discloses ANY 

identifiable information about you or your household members.

(1) CONTINUE, RECORDING ACCEPTABLE

(2) CONTINUE, DO NOTRECORD
Series 1, No. 59  Page 63 

Section 1: Initial Demographics

K1Q01_INTRO

[SKIP TO K1Q01 IF NAME OF S.C. ALREADY GATHERED NAME_1-NAME_9 OR NIS 

INTERVIEW]

I can continue to refer to your child as (your N month/year old) for the rest of the interview, or if 

you prefer, you could give me a first name or initials.

(1) CONTINUE TO USE AGE REFERENCE [GO TO K1Q01]

(2) USE NAME [GO TO SELECTION1_NAME_A] 

SELECTION 

1_NAME_A ENTER NAME/INITIALS: [GO TO K1Q01]

K1Q01 Is [S.C.] male or female?

(1) MALE

(2) FEMALE 

(6) DON'T KNOW

(7) REFUSED

K1Q02 What is your relationship to [S.C.]?

PARENT

(1) MOTHER (BIOLOGICAL, STEP, FOSTER,ADOPTIVE)

(2) FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE)

OLDER RELATIVES OR GUARDIANS

(11) GRANDMOTHER

(12) GRANDFATHER

(13) AUNT

(14) UNCLE

(15) FEMALE GUARDIAN

(16) MALE GUARDIAN

OTHER RELATIVES

(17) SISTER (BIOLOGICAL, STEP, FOSTER, HALF,ADOPTIVE)

(18) BROTHER (BIOLOGICAL, STEP, FOSTER, HALF,ADOPTIVE)

(19) COUSIN

(20) IN-LAW OF ANY TYPE

(22) OTHER RELATIVE / FAMILY MEMBER

OTHER NON-RELATIVES

(23) PARENT’S BOYFRIEND / MALE PARTNER

(24) PARENT’S GIRLFRIEND / FEMALE PARTNER 

(25) PARENT’S PARTNER, but SEX REFUSED

(26) OTHER NON-RELATIVE ORFRIEND

(96) DON’T KNOW

(97) REFUSED 
Page 64  Series 1, No. 59 

K1Q03 What is the primary language spoken in yourhome?

(1) ENGLISH 

(2) SPANISH

(3) ARABIC

(4) CHINESE

(5) FRENCH

(6) ITALIAN

(7) JAPANESE 

(8) KOREAN

(9) POLISH

(10) RUSSIAN

(11) TAGALOG

(12) VIETNAMESE

(13) ANY OTHER LANGUAGE

(96) DON’T KNOW

(97) REFUSED 
Series 1, No. 59  Page 65 

Section 2: Health and Functional Status

Subdomain 1: General health status

K2Q01 In general, how would you describe [S.C.]’s health? Would you say [his/her] health is excellent, 

very good, good, fair, or poor?

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON'T KNOW

(7) REFUSED

IF AGE < 12 MONTHS, SKIP TO K2Q02.

K2Q01_D How would you describe the condition of [S.C.]’s teeth: excellent, very good, good, fair, or poor?

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) HAS NO NATURAL TEETH 

(96) DON'T KNOW

(97) REFUSED

K2Q02 How tall is [S.C.] now?

FEET / INCHES / CENTIMETERS / 

(96) DON'T KNOW

(97) REFUSED

K2Q03 How much does [S.C.] weigh now?

POUNDS / KILOGRAMS / 

(96) DON'T KNOW

(97) REFUSED

K2Q04 What was [S.C.]’s birth weight?

POUNDS / OUNCES / GRAMS / 

(96) DON'T KNOW

(97) REFUSED

K2Q05 Was [S.C.] born prematurely, that is, more than 3 weeks before [his/her] duedate?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

READ IF NECESSARY: Most pregnancies last about 40 weeks. A premature birth is when a baby 

is born more than three weeks before the due date.
Page 66  Series 1, No. 59 

Subdomain 2: Presence of a special health care need

K2Q10_INTRO The next questions are about any kind of health problems, concerns, or conditions that may affect 

[S.C.]’s behavior, learning, growth, or physical development.

K2Q10 Does [S.C.] currently need or use medicine prescribed by a doctor, other than vitamins?

READ IF NECESSARY: This only applies to medications prescribed by a doctor. Over-thecounter medications such as cold or headache medication, or other vitamins, minerals, or 

supplements purchased without a prescription are not included.

HELP TEXT: THIS QUESTION REFERS ONLY TO CURRENT NEED FOR PRESCRIPTION 

MEDICINE. THE RESPONDENT SHOULD REPLY WITH “YES” IF THE CHILD 

CURRENTLY NEEDS OR USES PRESCRIPTION MEDICINE.

(1) YES [SKIP TO K2Q11]

(0) NO [SKIP TO K2Q13]

(6) DON’T KNOW [SKIP TO K2Q13]

(7) REFUSED [SKIP TO K2Q13]

K2Q11 Is [his/her] need for prescription medicine because of ANY medical, behavioral, or other health 

condition?

(1) YES [SKIP TO K2Q12]

(0) NO [SKIP TO K2Q13]

(6) DON’T KNOW [SKIP TO K2Q13]

(7) REFUSED [SKIP TO K2Q13]

K2Q12 Is this a condition that has lasted or is expected to last 12 months or longer?

(1) YES [SKIP TO K2Q13]

(0) NO [SKIP TO K2Q13]

(6) DON'T KNOW [SKIP TO K2Q13]

(7) REFUSED [SKIP TO K2Q13]

K2Q13 Does [S.C.] need or use more medical care, mental health, or educational services than isusual for 

most children of the same age?

READ IF NECESSARY: The child requires more medical care, the use of more mental health 

services, or the use of more educational services than most children the same age.

HELP TEXT: THIS QUESTION REFERS ONLY TO CURRENT NEED FOR SERVICES. THE 

RESPONDENT SHOULD REPLY WITH “YES” IF THE CHILD CURRENTLY NEEDS OR 

USES SERVICES

(1) YES [SKIP TO K2Q14]

(0) NO [SKIP TO K2Q16]

(6) DON’T KNOW [SKIP TO K2Q16]

(7) REFUSED [SKIP TO K2Q16]
Series 1, No. 59  Page 67 

K2Q14 Is [his/her] need for medical care, mental health or educational services because of ANY medical, 

behavioral, or other health condition?

(1) YES [SKIP TO K2Q15]

(0) NO [SKIP TO K2Q16]

(6) DON’T KNOW [SKIP TO K2Q16]

(7) REFUSED [SKIP TO K2Q16]

K2Q15 Is this a condition that has lasted or is expected to last 12 months or longer?

HELP TEXT: IF THE CONDITION, NEED, OR PROBLEM LASTS FOR SHORT PERIODS 

OF TIME BUT IS EXPECTED TO KEEP COMING BACK FOR 12 MONTHS OR LONGER, 

THE ANSWER SHOULD BE “YES.”

(1) YES [SKIP TO K2Q15]

(0) NO [SKIP TO K2Q16]

(6) DON’T KNOW [SKIP TO K2Q16]

(7) REFUSED [SKIP TO K2Q16]

K2Q16 Is [S.C.] limited or prevented in any way in [his/her] ability to do the things most childrenof the

same age can do?

READ IF NECESSARY: A child is limited or prevented when there are things the child can’t do 

as much or can’t do at all that most children the same age can.

HELP TEXT: THIS QUESTION REFERS ONLY TO CURRENT LIMITATIONS. THE 

RESPONDENT SHOULD REPLY WITH “YES” IF THE CHILD IS CURRENTLY LIMITED.

(1) YES [SKIP TO K2Q17]

(0) NO [SKIP TO K2Q19]

(6) DON’T KNOW [SKIP TO K2Q19]

(7) REFUSED [SKIP TO K2Q19]

K2Q17 Is [his/her] limitation in abilities because of ANY medical, behavioral, or other health condition?

(1) YES [SKIP TO K2Q18]

(0) NO [SKIP TO K2Q19]

(6) DON’T KNOW [SKIP TO K2Q19]

(7) REFUSED [SKIP TO K2Q19]

K2Q18 Is this a condition that has lasted or is expected to last 12 months or longer?

HELP TEXT: IF THE CONDITION, NEED, OR PROBLEM LASTS FOR SHORT PERIODS 

OF TIME BUT IS EXPECTED TO KEEP COMING BACK FOR 12 MONTHS OR LONGER, 

THE ANSWER SHOULD BE “YES.”

(1) YES [SKIP TO K2Q19]

(0) NO [SKIP TO K2Q19]

(6) DON’T KNOW [SKIP TO K2Q19]

(7) REFUSED [SKIP TO K2Q19]
Page 68  Series 1, No. 59 

K2Q19 Does [S.C.] need or get special therapy, such as physical, occupational, or speech therapy?

READ IF NECESSARY: Special therapy includes physical, occupational, or speech therapy. Do 

not include psychological therapy.

HELP TEXT: THIS QUESTION REFERS ONLY TO CURRENT NEED FOR SPECIAL 

THERAPY. THE RESPONDENT SHOULD REPLY WITH “YES” IF THE CHILD 

CURRENTLY NEEDS OR USES SPECIAL THERAPY.

(1) YES [SKIP TO K2Q20]

(0) NO [SKIP TO K2Q22]

(6) DON’T KNOW [SKIP TO K2Q22]

(7) REFUSED [SKIP TO K2Q22]

K2Q20 Is [his/her] need for special therapy because of ANY medical, behavioral, or other health 

condition?

(1) YES [SKIP TO K2Q21]

(0) NO [SKIP TO K2Q22]

(6) DON’T KNOW [SKIP TO K2Q22]

(7) REFUSED [SKIP TO K2Q22]

K2Q21 Is this a condition that has lasted or is expected to last 12 months or longer?

HELP TEXT: IF THE CONDITION, NEED, OR PROBLEM LASTS FOR SHORT PERIODS 

OF TIME BUT IS EXPECTED TO KEEP COMING BACK FOR 12 MONTHS OR LONGER, 

THE ANSWER SHOULD BE “YES.”

(1) YES [SKIP TO K2Q22]

(0) NO [SKIP TO K2Q22]

(6) DON’T KNOW [SKIP TO K2Q22]

(7) REFUSED [SKIP TO K2Q22]

K2Q22 Does [S.C.] have any kind of emotional, developmental, or behavioral problem for which [he/she]

needs treatment or counseling?

READ IF NECESSARY: These are remedies, therapy, or guidance a child may receive for his/her 

emotional, developmental, or behavioral problem.

(1) YES [SKIP TO K2Q23]

(0) NO [SKIP TO CATI INSTRUCTION BELOW]

(6) DON’T KNOW [SKIP TO CATI INSTRUCTION BELOW]

(7) REFUSED [SKIP TO CATI INSTRUCTION BELOW]

K2Q23 Has [his/her] emotional, developmental or behavioral problem lasted or is it expected to last 12 

months or longer?

HELP TEXT: IF THE CONDITION, NEED, OR PROBLEM LASTS FOR SHORT PERIODS 

OF TIME BUT IS EXPECTED TO KEEP COMING BACK FOR 12 MONTHS OR LONGER, 

THE ANSWER SHOULD BE “YES.”

(1) YES 

(0) NO

(6) DON'T KNOW
Series 1, No. 59  Page 69 

(7) REFUSED 

CATI INSTRUCTION (SECTION 2, SUBDOMAIN 2): CREATE CATI SYSTEM FLAG 

(CSHCN) INDICATING WHETHER THE CHILD HAS A SPECIAL HEALTH CARE NEED. 

THIS FLAG SHOULD BE POSITIVE (CSHCN = 1) IF K2Q12 = 1, K2Q15 = 1, K2Q18 = 1, 

K2Q21 = 1, OR K2Q23 = 1.
Page 70  Series 1, No. 59 

Subdomain 3: Common chronic conditions

IF S.C. < 36 MONTHS, SKIP TO K2Q31_INTRO.

K2Q30A Has a doctor, health care provider, teacher, or school official ever told you [S.C.] had a learning 

disability?

(1) YES [SKIP TO K2Q30B]

(0) NO [SKIP TO K2Q31_INTRO]

(6) DON’T KNOW [SKIP TO K2Q31_INTRO]

(7) REFUSED [SKIP TO K2Q31_INTRO]

K2Q30B Does [S.C.] currently have a learningdisability?

(1) YES [SKIP TO K2Q30C]

(0) NO [SKIP TO K2Q31_INTRO]

(6) DON’T KNOW [SKIP TO K2Q31_INTRO]

(7) REFUSED [SKIP TO K2Q31_INTRO]

K2Q30C Would you describe [his/her] learning disability as mild, moderate, or severe?

(1) MILD

(2) MODERATE

(3) SEVERE 

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 71 

K2Q31_INTRO Now I am going to read you a list of conditions. For each condition, please tell me if a doctor or 

other health care provider ever told you that [S.C.] had the condition, even if [he/she] does not 

have the condition now.

INTERVIEWER INSTRUCTION: IF THE RESPONDENT HAS NEVER HEARD OF THE 

MEDICAL CONDITION OR DOES NOT KNOW WHAT THE CONDITION IS, THEN A 

DOCTOR OR OTHER HEALTH CARE PROVIDER PROBABLY HAS NOT TOLD THE 

RESPONDENT THAT THE S.C. HAS THE CONDITION. IF A DOCTOR OR OTHER 

HEALTH CARE PROVIDER HAS NOT TOLD THE RESPONDENT THAT THE S.C. HAS 

THE CONDITION, BUT THE RESPONDENT INSISTS THAT THE S.C. HAS THE 

CONDITION, WE STILL NEED TO CODE THE ANSWER AS “NO.”

IF AGE_NSCH < 24 MONTHS SKIP TO K2Q40A.

(READ IF NECESSARY: Has a doctor or other health care provider ever told you that [S.C.]

had...)

K2Q31A Attention Deficit Disorder or Attention-Deficit/Hyperactivity Disorder, that is, ADD orADHD?

HELP SCREEN: A child with Attention Deficit Disorder or Attention Deficit Hyperactive 

Disorder has problems paying attention or sitting still. It may cause the child to be easily 

distracted.

K2Q32A Depression?

HELP SCREEN: Depression is an illness that involves the body, mood, and thoughts. It is marked 

by persistent sadness or an anxious or empty mood. It affects how a person feels, and the way a 

person eats, sleeps, and functions.

K2Q33A Anxiety problems?

HELP SCREEN: Anxiety is a feeling of constant worrying. Children with severe anxiety 

problems may be diagnosed as having anxiety disorders. Anxiety disorders include panic 

disorder, obsessive-compulsive disorder, post-traumatic stress disorder, and phobias.

K2Q34A Behavioral or conduct problems, such as oppositional defiant disorder or conduct disorder?

HELP SCREEN: Oppositional defiant disorder is an ongoing pattern of defiant and hostile 

behavior that interferes with a child’s life and daily activities.

K2Q35A Autism, Asperger's Disorder, pervasive developmental disorder, or other autism spectrum

disorder?

HELP SCREEN: Children with autism have delays in language, communication, and social skills, 

as well as routine repetitive behaviors or movements. They may have an intense interest in a single 

subject or topic. Children with Asperger's disorder have impaired social skills but may not have 

speech or language delays. Children with pervasive developmental disorder have severe and 

persistent delays in language, communication, and social skills.
Page 72  Series 1, No. 59 

INTERVIEWER INSTRUCTION: IF THE DOCTOR OR OTHER HEALTH CARE PROVIDER 

IS UNSURE ABOUT THE DIAGNOSIS AND HAS NOT OFFICALLY DIAGNOSED S.C., 

ALSO CODE RESPONSE AS “NO”.

K2Q36A Any developmental delay?

HELP SCREEN: A child with a developmental delay does not achieve certain skills as quickly 

other children of the same age. A developmental delay is a major delay in motor, language, social, 

or thinking skills.

K2Q60A Intellectual disability or mental retardation?

HELP SCREEN: Children with intellectual disabilities or mental retardation learn and develop 

more slowly than a typical child.

K2Q61A Cerebral palsy?

HELP SCREEN: Cerebral palsy is caused by damage that occurs to the brain prior to or shortly 

after birth that can affect body movement and muscle coordination.

K2Q37A Speech or other language problems?

K2Q38A Tourette Syndrome?

HELP SCREEN: Tourette Syndrome is a disorder that causes frequent sudden movements or 

sounds.

K2Q40A Asthma?

HELP SCREEN: Asthma is a disease that causes swelling in the tubes that carry air to the lungs. 

Sometimes asthma blocks or restricts the airways making it difficult to breathe.

K2Q41A Diabetes?

HELP SCREEN: Diabetes is a disease in which the body does not properly make or use insulin.

K2Q42A Epilepsy or seizure disorder?

HELP SCREEN: Epilepsy is a brain disease that involves recurrent seizures.

K2Q43A Hearing problems?

K2Q44A Vision problems that cannot be corrected with standard glasses or contact lenses?

K2Q45A Bone, joint, or muscle problems?
Series 1, No. 59  Page 73 

K2Q46A A brain injury or concussion?

HELP SCREEN: A concussion is an injury of the brain that causes a brief disruption in brain 

function. Developmental and neurological conditions (such as autism or cerebral palsy) should not 

be included as head or brain injuries.

BRAIN TUMORS SHOULD NOT BE CONSIDERED BRAIN INJURIES.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

FOR EACH ITEM
Page 74  Series 1, No. 59 

BEGIN LOOP TO BE ASKED FOR EACH CONDITION IDENTIFIED BY PARENT. USE THE FOLLOWING 

TEXT FOR CONDITION FILLS:

[ADD or ADHD] [developmental delay]

[depression] [intellectual disability or mentalretardation]

[anxiety problems] [cerebral palsy]

[behavioral or conduct problems] [speech or other language problems]

[autism or autism spectrum disorder] [Tourette Syndrome]

K2QXXA_1 SKIP TO K2QXXB IF CONDITION IS DEPRESSION OR ANXIETY PROBLEMS. 

Earlier you told me that [S.C.] has been diagnosed with [CONDITION].

How old was [S.C.] when you were first told by a doctor or other health care provider that [he/she] 

had [CONDITION]?

RECORD AGE IN YEARS OR MONTHS

(96) DON'T KNOW

(97) REFUSED

SKIP TO K2QXXB IF CONDITION IS NOT AUTISM OR ASD.

K2Q35A_1 Earlier you told me that [S.C.] has been diagnosed with Autism or an autismspectrum disorder, 

such as Asperger's disorder or pervasive developmental disorder.

How old was [S.C.] when you were first told by a doctor or other health care provider that [he/she] 

had autism or autism spectrum disorder?

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER,

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

RECORD AGE IN YEARS OR MONTHS

(96) DON'T KNOW

(97) REFUSED

K2Q35D What type of doctor or other health care provider first told you that [S.C.] hadautism or 

autism spectrum disorder?

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER, 

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

(1) PEDIATRICIAN OR OTHER GENERAL PEDIATRIC HEALTH CARE PROVIDER 

(SUCH AS NURSE PRACTITIONER OR PHYSICIAN’S ASSISTANT IN 

PEDIATRIC CLINIC)

(2) ANOTHER TYPE OF GENERAL HEALTH CARE PROVIDER (SUCH AS FAMILY 

PRACTICE DOCTOR OR NURSE PRACTITIONER OR PHYSICIAN’SASSISTANT 

IN GENERAL PRACTICE)

(3) A SPECIALIST PEDIATRICIAN SUCH AS A DEVELOPMENTAL PEDIATRICIAN

(4) SCHOOL PSYCHOLOGIST / COUNSELOR

(5) OTHER PSYCHOLOGIST (NON-SCHOOL)

(6) PSYCHIATRIST (MEDICAL DOCTOR)

(7) NEUROLOGIST

(8) SCHOOL NURSE

(9) PHYSICAL, OCCUPATIONAL, SPEECH, OR OTHERTHERAPIST

(10) A SPECIALIST DOCTOR (OTHER THAN A DEVELOPMENTALPEDIATRICIAN, 

PSYCHIATRIST, OR NEUROLOGIST)

(11) OTHER [RECORD VERBATIM RESPONSE] 

(12) WASN’T TOLD BY A DOCTOR OR OTHER HEALTH CAREPROFESSIONAL
Series 1, No. 59  Page 75 

(96) DON’T KNOW

(97) REFUSED 

K2QXXB IF CONDITION IS DEPRESSION OR ANXIETY PROBLEM,DISPLAY:

Earlier you told me that [S.C.] has been diagnosed with [CONDITION]. 

Does [S.C.] currently have [CONDITION]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

END OF LOOP IF K2QXXB = DK/RF.

END OF LOOP IF K2QXXB = NO AND CONDITION IS NOT AUTISM. 

SKIP TO K2Q35E IF K2QXXB = NO AND CONDITION IS AUTISM. 

SKIP TO K2Q61C IF CONDITION IS CEREBRAL PALSY.

IF CONDITION IS AUTISM OR AUTISM SPECTRUM DISORDER, THENDISPLAY: 

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER, 

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTALDISORDER.

K2QXXC Would you describe [his/her] [CONDITION] as mild, moderate, orsevere?

(1) MILD

(2) MODERATE

(3) SEVERE 

(6) DON'T KNOW

(7) REFUSED

END OF LOOP IF CONDITION IS NOT ADD/ADHDIF CONDITION IS AUTISM OR AUTISM 

SPECTRUM DISORDER, THEN DISPLAY:

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER, 

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

K2Q31D Is [S.C.] currently taking medication for ADD orADHD?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

END OF LOOP. RETURN TO K2QXXA_1 FOR EACH ADDITIONAL CONDITION.

K2Q61C How would you describe [his/her] usual ability towalk?

Would you say [he/she]...

walks without a cane, crutches or walker, 

walks with a cane, crutches or walker,

or has limited or no walking?
Page 76  Series 1, No. 59 

HELP TEXT: SOME CHILDREN USE MORE THAN ONE METHOD. FOR EXAMPLE, A 

CHILD MAY WALK WITH A CANE, CRUTCHES, OR A WALKER AT HOME BUT DO 

LIMITED OR NO WALKING OUTDOORS. FOR CHILDREN WHO USE MORE THAN ONE

METHOD, READ THE FOLLOWING PROMPT "Please tell me what [he/she] does in the setting 

where [he/she] spends the most time in a typical weekday. This could be the child's at home, 

school, or other community setting."

HELP TEXT: WHETHER OR NOT A CHILD WEARS BRACES SHOULD NOT BE 

CONSIDERED IN DETERMINING [HIS/HER] USUAL ABILITY TO WALK. CHILDREN AT 

ALL THREE LEVELS OF WALKING ABILITY CAN WEAR BRACES.

(1) WALKS WITHOUT A CANE, CRUTCHES, OR A WALKER

(2) WALKS WITH A CANE, CRUTCHES, OR A WALKER

(3) LIMITED OR NO WALKING

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 77 

K2Q35E To the best of your knowledge, did [S.C.] ever have autism or autism spectrum disorder?

(1) YES 

(0) NO [SKIP TO K2Q35H_1]

(6) DON'T KNOW [END LOOP]

(7) REFUSED [END LOOP]

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER,

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

K2Q35F_INTRO

I am going to read a list of reasons why [S.C.] may no longer have autism or autism spectrum 

disorder. For each reason, please tell me if it applies to [S.C.].

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER,

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

K2Q35F_1. Treatment helped the condition go away 

K2Q35F_2. The condition seemed to go away on its own 

K2Q35F_3. The behaviors or symptoms changed

K2Q35F_4. A doctor or health care provider changed the diagnosis

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

FOR EACH ITEM

K2Q35G Are there any other reasons why you think [S.C.] may no longer haveautism or 

autism spectrum disorder?

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER,

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

(1) YES [RECORD VERBATIM RESPONSE, THEN END LOOP]

(0) NO [END LOOP]

(6) DON'T KNOW [END LOOP]

(7) REFUSED [END LOOP]

K2Q35H_INTRO

I am going to read a list of reasons why a doctor, health care provider, or school professional may 

have told you that [S.C.] had a condition that (he/she) never had. For each reason, please tell me if 

it applies to [S.C.].

K2Q35H_1. With more information, the diagnosis was changed

K2Q35H_2. The diagnosis was given so that [S.C.] could receive needed services

K2Q35H_3. You disagree with the doctor or other health provider about his or her opinion that 

[S.C.] had autism or autism spectrum disorder.

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER, 

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

(1) YES 
Page 78  Series 1, No. 59 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

FOR EACH ITEM

K2Q35J Are there any other reasons why a doctor or other health care provider may have told you that 

[S.C.] had autism or autism spectrum disorder when [he/she] never hadit?

HELP TEXT: AUTISM SPECTRUM DISORDER INCLUDES AUTISTIC DISORDER,

ASPERGER’S DISORDER, AND PERVASIVE DEVELOPMENTAL DISORDER.

(1) YES [RECORD VERBATIM RESPONSE, THEN END LOOP]

(0) NO [END LOOP]

(6) DON'T KNOW [END LOOP]

(7) REFUSED [END LOOP]

END OF LOOP. RETURN TO K2QXXA_1 FOR EACH ADDITIONAL CONDITION.
Series 1, No. 59  Page 79 

BEGIN LOOP TO BE ASKED FOR EACH CONDITION IDENTIFIED BY PARENT. USE THE FOLLOWING 

TEXT FOR CONDITION FILLS:

[asthma] [vision problems]

[diabetes] [bone, joint, or muscle problems]

[epilepsy or seizure disorder] [brain injury]

[hearing problems]

K2Q44A_1 SKIP TO K2QXXB IF CONDITION IS NOT VISIONPROBLEMS.

Earlier you told me that [S.C.] has been diagnosed with vision problems.

How old was [S.C.] when you were first told by a doctor or other health care provider that [he/she] 

had vision problems that cannot be corrected with standard glasses or contact lenses?

RECORD AGE IN YEARS OR MONTHS /

(96) DON'T KNOW

(97) REFUSED

K2QXXB Does [S.C.] currently have [CONDITION]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[END OF LOOP IF NO/DK/RF]

K2QXXC Would you describe [his/her] [CONDITION] as mild, moderate, orsevere?

(1) MILD

(2) MODERATE

(3) SEVERE 

(6) DON'T KNOW

(7) REFUSED

END OF LOOP. RETURN TO K2QXXB FOR EACH ADDITIONAL CONDITION.
Page 80  Series 1, No. 59 

Section 3: Health Insurance Coverage

Subdomain 1: Current coverage and past year coverage

K3Q01_INTRO The next questions are about health insurance.

K3_STATE Because many health insurance programs are state specific, can you please tell me whatstate you 

live in?

(DROP DOWN MENU OF STATE NAMES)

(96) DON'T KNOW

(97) REFUSED

IF VIRGIN ISLAND CASE, THEN SKIP K3_STATE; ELSE FOLLOW LOGIC BELOW.

THE STATE GIVEN AT K3_STATE SHOULD DETERMINE THE MEDICAID/CHIP TEXT 

FILLS FOR K3Q02, K11Q60 AND FOR ALL QUESTIONS IN SECTION 12. THE STATE 

GIVEN AT K3_STATE SHOULD ALSO DETERMINE WHICH POVERTY TABLE IS 

REFERENCED DURING THE INCOME CASCADE. THE PRELOAD VARIABLE "STATE" 

SHOULD NO LONGER BE USED EXCEPT WHEN K3_STATE HAS A VALUE OF "DON'T 

KNOW" OR "REFUSED"

K3Q01 Does [S.C.] have any kind of health care coverage, including health insurance, prepaidplans such 

as HMOs, or government plans such asMedicaid?

(1) YES [SKIP TO K3Q02]

(0) NO [SKIP TO K3Q01_CONF]

(6) DON’T KNOW [SKIP TO K3Q02]

(7) REFUSED [SKIP TO K3Q02]

K3Q01_CONF Just to confirm, I entered that [S.C.] is not covered by any type of health insurance. Is this

correct?

(1) CONFIRMED - CHILD IS NOT COVERED BY ANY TYPE OF HEALTHINSURANCE 

[SKIP TO K3Q04]

(2) NOT CORRECT - CHILD HAS INSURANCE - RETURN TO K3Q01 AND ENTER 

CORRECT RESPONSE [SKIP TO K3Q01]

K3Q02 IF K3Q01 = 1 THEN FILL “Is that coverage”. ELSE, fill “Is [he/she] insuredby...]

[Is that coverage/Is [he/she] insured by] Medicaid or the Children’s Health Insurance Program, 

CHIP? [IF VIRGIN ISLANDS CASE, DISPLAY "In this area," ELSE DISPLAY "In this state,"],

the program is sometimes called [FILL MEDICAID NAME, CHIP NAME].

READ IF NECESSARY: CHIP, also known as S-CHIP, is a type of state-sponsored health 

insurance coverage that a child may have. The name of the plan varies from state-to-state.

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health Insurance 

Program specific to the state in which you live.

(1) YES 

(0) NO
Series 1, No. 59  Page 81 

(6) DON'T KNOW

(7) REFUSED

K3Q03 IF [(K3Q01 = 6, or 7) AND (K3Q02 = 0, 6, or 7)], SKIP TO K3Q04; ELSE,SKIP TO

K3Q03.

[During the past 12 months / Since [his/her] birth], was there any time when [he/she] was not 

covered by ANY health insurance?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[ALL SKIP TO K3Q20]

K3Q04 [During the past 12 months / Since [his/her] birth], was there anytime when [he/she] had health 

care coverage?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

[ALL SKIP TO K3Q25]
Page 82  Series 1, No. 59 

Subdomain 2: Adequacy of health insurance

K3Q20 [IF K3Q01 OR K3Q02 OR K3Q03 ASKED AND NOT FILLED FROM NIS OR TEEN,then

display: "The next questions are about [S.C.]'s health insurance or health care plans."] Does 

[S.C.]’s health insurance offer benefits or cover services that meet [his/her] needs? Would you 

say never, sometimes, usually, always?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON'T KNOW

(7) REFUSED

K3Q22 Does [S.C.]’s health insurance allow [him/her] to see the health care providers [he/she]needs?

Would you say never, sometimes, usually, always?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON'T KNOW

(7) REFUSED

K3Q21A Not including health insurance premiums or costs that are covered by insurance, do youpay any 

money for [S.C.]’s health care?

READ IF NECESSARY: Include out-of-pocket payments for all types of health-related needs 

such as co-payments, dental or vision care, medications, and any kind of therapy.

(1) YES [SKIP TO K3Q21B]

(0) NO [SKIP TO K3Q25]

(6) DON’T KNOW [SKIP TO K3Q25]

(7) REFUSED [SKIP TO K3Q25]

K3Q21B How often are these costs reasonable? Would you say never, sometimes, usually,always?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(5) NO OUT OF POCKET COSTS

(6) DON'T KNOW

(7) REFUSED

INTERVIEWER INSTRUCTION: IF THE PARENT SEEMS CONFUSED BY HOW TO

ANSWER, ASK: Do you have any out-of-pocket costs for your child's health care? 

IF YES, THEN ASK: How often are those costs reasonable?
Series 1, No. 59  Page 83 

Subdomain 3: Expenses and Barriers to Care

K3Q25 In the past 12 months did your family have problems paying or were unable to pay any of [S.C.]'s

medical bills? Include bills for doctors, dentists, hospitals, therapists, medication, equipment, or 

home care.

(1) YES 

(0) NO

(3) NO EXPENSES

(6) DON'T KNOW

(7) REFUSED

C4Q04 [Duringthe past 12 months / [WHEN S.C. IS YOUNGER THAN 12 MONTHS] Since [his/her]

birth], how often have you been frustrated in your efforts to obtain health care services for [S.C.]? 

Would you say never, sometimes, usually, or always?

(1)NEVER 

(2)SOMETIMES

(3)USUALLY

(4)ALWAYS

(6) DON'T KNOW

(7) REFUSED 
Page 84  Series 1, No. 59 

Section 4: Health Care Access and Utilization

Subdomain 1: Usual place for care

K4Q01 Is there a place that [S.C.] USUALLY goes when [he/she] is sick or you needadvice about 

[his/her] health?

(1) YES 

(0) NO [SKIP TO K4Q04]

(3) THERE IS MORE THAN ONE PLACE

(6) DON’T KNOW [SKIP TO K4Q04]

(7) REFUSED [SKIP TO K4Q04]

K4Q02 IF K4Q01 = 1, SAY “What kind of place isit?”

IF K4Q01 = 3, SAY “What kind of place does [S.C.] go to most often?”

Is it a doctor’s office, emergency room, hospital outpatient department, clinic, or some other 

place?

(1) DOCTOR’S OFFICE

(2) HOSPITAL EMERGENCY ROOM

(3) HOSPITAL OUTPATIENT DEPARTMENT 

(4) CLINIC OR HEALTH CENTER

(5) RETAIL STORE CLINIC OR “MINUTECLINIC”

(6) SCHOOL (NURSE, ATHLETIC TRAINER, ETC) 

(7) FRIEND/RELATIVE

(8) MEXICO/OTHER LOCATIONS OUT OF US

(9) SOME OTHER PLACE [RECORD VERBATIMRESPONSE]

(10) DOES NOT GO TO ONE PLACE MOST OFTEN 

(96) DON’T KNOW

(97) REFUSED

K3Q03 READ IF NECESSARY: ( IF K4Q01 = 1, READ “WHAT KIND OF PLACE IS IT?”; IFK4Q01

= 3, READ: “What kind of place does [S.C.] go to most often?”) 

RECORD VERBATIM RESPONSE

K4Q04 A personal doctor or nurse is a health professional who knows your child well and isfamiliar with 

your child’s health history. This can be a general doctor, a pediatrician, a specialist doctor, a nurse 

practitioner, or a physician’s assistant. Do you have one or more persons you think of as [S.C.]’s 

personal doctor or nurse?

(1) YES, ONE PERSON

(2) YES, MORE THAN ONE PERSON

(3) NO

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 85 

Subdomain 2: Utilization of services

S4Q01 [During the past 12 months/Since [his/her] birth], did [S.C.] see a doctor, nurse, or other health 

care professional for any kind of medical care, including sick-child care, well-child check-ups, 

physical exams, and hospitalizations?

(1) YES 

(0) NO [SKIP TO K4Q30]

(6) DON'T KNOW [SKIP TO K4Q30]

(7) REFUSED [SKIP TO K4Q30]

K4Q20 [During the past 12 months/Since [his/her] birth], how many times did [S.C.] see a doctor, nurse, 

or other health care provider for preventive medical care such as a physical exam or well-child 

checkup?

TIMES 

(96) DON’T KNOW

(97) REFUSED

K4Q30 [During the past 12 months/Since [his/her] birth], did [S.C.] see a dentist for any kindof dental

care, including check-ups, dental cleanings, x-rays, or filling cavities?

(1) YES 

(0) NO [SKIP TO K4Q39]

(6) DON'T KNOW [SKIP TO K4Q39]

(7) REFUSED [SKIP TO K4Q39]

K4Q21 [During the past 12 months/Since [his/her] birth], how many times did [S.C.] see a dentistfor

preventive dental care, such as check-ups and dental cleanings?

TIMES 

(96) DON’T KNOW

(97) REFUSED

K4Q39 IF AGE < 12 MONTHS, SKIP TO K4Q24.

[During the past 12 months/Since [his/her] birth], did [S.C.] have a toothache, decayed teeth, or 

unfilled cavities?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

IF AGE < 24 MONTHS, SKIP TO K4Q24.

K4Q22 Mental health professionals include psychiatrists, psychologists, psychiatric nurses, and clinical

social workers. During the past 12 months, has [S.C.] received any treatment or counseling from a 

mental health professional?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 

IF K2Q31D = 1, SKIP TO K4Q24.
Page 86  Series 1, No. 59 

K4Q23 During the past 12 months, has [S.C.] taken any medication because of difficulties with [his/her]

emotions, concentration, or behavior?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K4Q24 Specialists are doctors like surgeons, heart doctors, allergy doctors, skin doctors, and others who 

specialize in one area of health care. [During the past 12 months/Since [his/her] birth], did [S.C.] 

see a specialist [IF K4Q22 = 1, THEN INSERT: other than a mental health professional]?

(1) YES [SKIP TO K4Q26]

(0) NO

(6) DON’T KNOW

(7) REFUSED

K4Q25 [During the past 12 months/Since [his/her] birth], did you or a doctor thinkthat [he/she] needed to 

see a specialist?

(1) YES 

(0) NO [SKIP TO K4Q31]

(6) DON’T KNOW [SKIP TO K4Q31]

(7) REFUSED [SKIP TO K4Q31]

K4Q26 [During the past 12 months/Since [his/her] birth], how much of a problem, if any, was it toget the

care from the specialists that [S.C.] needed? Would you say it was a big problem, a small 

problem, or not a problem? 

(1) BIG PROBLEM

(2) SMALL PROBLEM 

(3) NOT A PROBLEM 

(6) DON’T KNOW

(7) REFUSED

K4Q31 IF AGE < 5 YEARS, READ: Has [S.C.] ever had [his/her] vision tested with pictures,shapes, or 

letters?

IF AGE 5+ YEARS, READ: During the past 2 years, that is, since [FILL INTDATE – 48 

MONTHS], has [S.C.] had [his/her] vision tested with pictures, shapes, or letters?

(1) YES 

(0) NO [SKIP TO K4Q27]

(6) DON'T KNOW [SKIP TO K4Q27]

(7) REFUSED [SKIP TO K4Q27]

K4Q32 What kind of place or places did [S.C.] have [his/her] vision tested? Was it an eyedoctor’s office, 

a general doctor’s office, clinic, school, or some other place? [Mark all thatapply] 

(1) EYE DOCTOR OR EYE SPECIALIST (OPHTHALMOLOGIST, OPTOMETRIST)OFFICE

(2) PEDIATRICIAN OR OTHER GENERAL DOCTOR’SOFFICE

(3) CLINIC OR HEALTH CENTER 

(4) SCHOOL

(5) OTHER [RECORD VERBATIM RESPONSE]
Series 1, No. 59  Page 87 

(6) DON’T KNOW

(7) REFUSED

K4Q27 Sometimes people have difficulty getting health care when they need it. By health care, I mean

medical care as well as other kinds of care like dental care, vision care, and mental health services. 

[During the past 12 months/Since [his/her] birth], was there any time when [S.C.] needed health 

care but it was delayed or notreceived?

(1) YES 

(0) NO [SKIP TO K4Q35]

(6) DON’T KNOW [SKIP TO K4Q35]

(7) REFUSED [SKIP TO K4Q35]

K4Q28 What type of care was delayed or not received? Was it medical care, dental care, vision care, 

mental health services, or something else? [Mark all that apply] 

(1) MEDICAL CARE

(2) DENTAL CARE

(3) VISION CARE

(4) MENTAL HEALTH SERVICES

(5) SOMETHING ELSE 

(6) DON’T KNOW

(7) REFUSED 

*Note: In the dataset, this variable will appear as variables K4Q28X01-K4Q28X05 where:

(1) YES

(0) NO

(6) DON'T KNOW

(7) REFUSED
Page 88  Series 1, No. 59 

K4Q35 ASK K4Q35 ONLY IF AGE=0-3 YEARS 

Some new parents are helped by programs that send nurses, healthcare workers, social workers, or

other professionals to their home to help prepare for the new baby or take care of the baby or 

mother. Between the time [you were / [his/her] mother was] pregnant with [S.C.] and up until the 

present day, did someone from such a program visit your home?

INTERVIEWER INSTRUCTION: IF R HAS ADOPTED S.C., SAY "Pease think about the time 

between adopting [S.C.] and up until the present day."

(1) YES [GO TO K4Q35A]

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 THEN GO TO K4Q36

K4Q35A How many different professionals came to your home?

ENTER VALUE

(96) DON'T KNOW

(97) REFUSED

IF >4 GO TO SC_K4Q35A; ELSE GO TO K4Q35B_INTRO

K4Q35B_INTRO

Parents, especially new parents, often have concerns about their children and families. Please tell 

me if [the professional / any of the professionals] who visited your home talked about any of the 

following:

K4Q35B_1. [Your/[S.C.]’s mother’s] emotional well-being? 

K4Q35B_2. Smoking or alcohol use in your home?

K4Q35B_3. How to build a close relationship with [S.C.]?

K4Q35B_4. How to use toys, playtime, and story time to help [S.C.] learn, grow, and develop? 

K4Q35B_5. How to make sure that [S.C.] is safe and does not get hurt?

K4Q35B_6. How to get the health care that [S.C.] needs?

K4Q35B_7. Other services that might help your family, such as public assistance, transportation, 

or job training?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 89 

Subdomain 3: Use of developmental services

SKIP TO NEXT SECTION IF CHILD HAS NEVER BEEN DIAGNOSED WITH ASD OR DEV DELAY.

K4Q36 Earlier you told me that you had been told by a doctor or other health care provider that[S.C.] had 

(a condition / conditions) that affected [his/her] learning or development. Has [S.C.] ever received 

therapy services to meet [his/her] developmental needs, such as Early Intervention, occupational 

therapy, speech therapy, or behavioral therapy?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

INTERVIEWER INSTRUCTION: IF A PARENT ASKS WHICH CONDITIONS ARE BEING 

REFERRED TO, YOU MAY READ THIS LIST: [LIST]

CATI PROGRAMMER INSTRUCTION: K4Q36 IS ONLY TO BE ASKED IF CHILD HAS 

BEEN DIAGNOSED WITH AUTISM/ASD AND/OR DEVELOPMENTAL DELAY. 

HOWEVER, IN LIST, INCLUDE ALL CONDITIONS THAT HAD A YES TO “EVER TOLD” 

FROM: ADHD, BEHAVIORAL/CONDUCT PROBLEMS, AUTISM/ASD, 

DEVELOPMENTAL DELAY, TOURETTE SYNDROME, CEREBRAL PALSY, 

INTELLECTUAL DISABILITY, SPEECH OR OTHER LANGUAGE PROBLEMS. USE 

NUMBER OF CONDITIONS IN THIS LIST TO DETERMINE WHETHER TO FILL 

“CONDITION” OR “CONDITIONS.”

K4Q37 How old was [S.C.] when [he/she] began receiving services?

ENTER VALUE

(96) DON'T KNOW

(97) REFUSED

RECORD AGE IN MONTHS FOR 0 TO 23 MONTHS. IF 2 YEARS OR OLDER AND 

MONTHS NOT GIVEN, RECORD AGE IN YEARS.

K4Q38 Is [S.C.] currently receiving therapy services?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 
Page 90  Series 1, No. 59 

Section 5: Medical Home

Subdomain 1: Referrals

K5Q10 [During the past 12 months / Since [his/her] birth], did [S.C.] need a referral to see any doctors or 

receive any services?

(1) YES 

(0) NO [SKIP TO K5Q20]

(6) DON’T KNOW [SKIP TO K5Q20]

(7) REFUSED [SKIP TO K5Q20]

K5Q11 Was getting referrals a big problem, a small problem, or not a problem?

(1) BIG PROBLEM

(2) SMALL PROBLEM 

(3) NOT A PROBLEM 

(6) DON’T KNOW

(7) REFUSED

Subdomain 2: Care coordination

SUM UP THE NUMBER OF SERVICES FROM SECTION 4, SUBDOMAIN 2 AND ASSIGN TO VARIABLE 

NUMB_SERVICES. 

IF NUMB_SERVICES = 0 AND AGE ≤ 5 YEARS, THEN SKIP TO K6Q01. 

IF NUMB_SERVICES = 0 AND AGE ≥ 6 YEARS, THEN SKIP TO K7Q01. 

IF NUMB_SERVICES = 1, THEN SKIP TO K5Q31.

K5Q20 Does anyone help you arrange or coordinate [S.C.]’s care among the different doctorsor services

that [he/she] uses?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

READ IF NECESSARY: By “arrange or coordinate,” I mean: Is there anyone who helps you 

make sure that [S.C.] gets all the health care and services [he/she] needs, that health care providers 

share information, and that these services fit together and are paid for in a way that works for you?

READ IF NECESSARY: Anyone means anyone.

K5Q21 [During the past 12 months / Since [his/her] birth], have you felt that you could haveused extra

help arranging or coordinating [S.C.]’s care among the different health care providers or services?

(1) YES 

(0) NO [SKIP TO K5Q30]

(6) DON’T KNOW [SKIP TO K5Q30]

(7) REFUSED [SKIP TO K5Q30]
Series 1, No. 59  Page 91 

K5Q22 [During the past 12 months / Since [his/her] birth], how often did you get as much help as you 

wanted with arranging or coordinating [S.C.]’s care? Would you say never, sometimes, or 

usually?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(6) DON’T KNOW

(7) REFUSED 
Page 92  Series 1, No. 59 

Subdomain 3: Provider communication

K5Q30 Overall, are you very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied

with the communication among [S.C.]’s doctors and other health careproviders?

(1) VERY SATISFIED

(2) SOMEWHAT SATISFIED

(3) SOMEWHAT DISSATISFIED

(4) VERY DISSATISFIED

(5) NO COMMUNICATION NEEDED OR WANTED

(6) DON’T KNOW

(7) REFUSED 

K5Q31 Do [S.C.]’s doctors or other healthcare providers need to communicate with [his/her]

[IF AGE < 36 MONTHS, INSERT: child care providers or early interventionprogram?]

[IF AGE ≥ 36 MONTHS AND < 72 MONTHS, INSERT: child care providers, school, or special 

education program?]

[IF AGE ≥72 MONTHS AND CHILD DOES NOT HAVE SPECIAL HEALTH CARE NEEDS,

INSERT: school or special education program?]

[IF AGE ≥ 72 MONTHS AND < 144 MONTHS AND CHILD DOES HAVE SPECIAL

HEALTH CARE NEEDS, INSERT: school or special education program?]

[IF AGE ≥ 144 MONTHS AND CHILD DOES HAVE SPECIAL HEALTH CARE NEEDS,

INSERT: school, special education program, or vocational education program?]

(1) YES 

(0) NO [SKIP TO K5Q40]

(6) DON’T KNOW [SKIP TO K5Q40 ] 

(7) REFUSED [SKIP TO K5Q40 ] 

K5Q32 Overall, are you very satisfied, somewhat satisfied, somewhat dissatisfied, or very dissatisfied 

with that communication?

(1) VERY SATISFIED

(2) SOMEWHAT SATISFIED

(3) SOMEWHAT DISSATISFIED

(4) VERY DISSATISFIED

(5) NO COMMUNICATION NEEDED OR WANTED

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 93 

Subdomain 4: Compassionate, culturally effective, family-centeredcare

K5Q40 [During the past 12 months / Since [his/her] birth], how often did [S.C.]’s doctors and other health 

care providers spend enough time with [him/her]? Would you say never, sometimes, usually, or 

always?

READ IF NECESSARY: This question refers to doctors or any other health care providers 

including nurses, dentists, mental health professionals, or medical specialists.

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED

K5Q41 [During the past 12 months / Since [his/her] birth], how often did [S.C.]’s doctors and other health 

care providers listen carefully to you? Would you say never, sometimes, usually, or always?

READ IF NECESSARY: This question refers to doctors or any other health care providers 

including nurses, dentists, mental health professionals, or medical specialists.

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED

K5Q42 When [S.C.] is seen by doctors or other health care providers, how often are they sensitive to your 

family’s values and customs? Would you saynever, sometimes, usually, or always?

READ IF NECESSARY: This question refers to doctors or any other health care providers 

including nurses, dentists, mental health professionals, or medical specialists.

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED

K5Q43 Information about a child’s health or health care can include things such as the causesof any 

health problems, how to care for a child now, and what changes to expect in the future. [During 

the past 12 months / Since [his/her] birth], how often did you get the specific information you 

needed from [S.C.]’s doctors and other health care providers? Would you say never, sometimes, 

usually, or always?

READ IF NECESSARY: This question refers to doctors or any other health care providers 

including nurses, dentists, mental health professionals, or medical specialists.

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW
Page 94  Series 1, No. 59 

(7) REFUSED

K5Q44 [During the past 12 months / Since [his/her] birth], how often did [S.C.]’s doctors or other health 

care providers help you feel like a partner in [his/her] care? Would you say never, sometimes, 

usually, or always?

READ IF NECESSARY: This question refers to doctors or any other health care providers 

including nurses, dentists, mental health professionals, or medical specialists.

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED

IF AGE ≤ 5 YEARS, THEN SKIP TO K6Q01. 

IF AGE ≥ 6 YEARS, THEN SKIP TO K7Q01.
Series 1, No. 59  Page 95 

Section 6: Early Childhood (0-5 years)

Subdomain 1: Parent’s Evaluation of Developmental Status

Questions K6Q01-K6Q09 are from the Parent’s Evaluation of Developmental Status (PEDS) child development 

screening test. The PEDS is protected by U.S.. and international copyright law. All rights are reserved by Frances 

Page Glascoe. Permission to use these items in the NSCH has been granted by Dr. Glascoe. Permission must be 

requested from the publisher (forepath.org, PO Box 23186, Washington, DC, 20026, www.forepath.org,

support@forepath.org) before using these items for other purposes.

K6Q01 Do you have any concerns about [S.C.]’s learning, development, orbehavior?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF AGE < 4 MONTHS, SKIP TO K6Q10.

K6Q02_INTRO [IF K6Q01 = NO, READ: Although you told me you have no concerns, I need to ask a few 

specific questions about concerns that some parents may have. Please tell me if you are currently 

concerned a lot, a little, or not at all about the following.]

[ELSE, READ: The next section asks about specific concerns some parents may have. Please tell 

me if you are currently concerned a lot, a little, or not at all about the following.]

(READ IF NECESSARY: Are you concerned a lot, a little, or not at all about...) 

K6Q02 How [S.C.] talks and makes speech sounds?

K6Q03 How [he/she] understands what you say?

K6Q04 How [he/she] uses [his/her] hands and fingers todo things?

K6Q05 How [he/she] uses [his/her] arms and legs?

K6Q06 How [he/she] behaves?

K6Q07 How [he/she] gets along with others?

IF AGE < 10 MONTHS, SKIP TO K6Q10.

K6Q08 How[he/she] is learning to do things for (himself/herself)?

IF AGE < 18 MONTHS, SKIP TO K6Q10.

K6Q09 How [he/she] is learning pre-school or schoolskills?

(1) A LOT

(2) A LITTLE

(3) NOT AT ALL 

(6) DON'T KNOW

(7) REFUSED 

FOR EACH ITEM
Page 96  Series 1, No. 59 

Subdomain 2: Developmental screening

K6Q10 IF NUMB_SERVICES = 0, THEN SKIP TO K6Q15.

[During the past 12 months / Since [S.C.]’s birth], did [S.C.]’s doctors or other health care 

providers ask if you have concerns about [his/her] learning, development, or behavior?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K6Q12 IF AGE_NSCH < 10 MONTHS, SKIP TO K6Q15.

Sometimes a child’s doctor or other health care provider will ask a parent to fill out a 

questionnaire at home or during their child’s visit. During the past 12 months, did a doctor or 

other health care provider have you fill out a questionnaire about specific concerns or observations 

you may have about [S.C.]’s development, communication, or socialbehaviors?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [SKIP TO K6Q15 IF NO/DK/RF]

INTERVIEWER INSTRUCTION: IF ANOTHER PERSON READ THE QUESTIONNAIRE TO 

THE PARENT AND FILLED IN THE ANSWERS FOR THE PARENT, THEN THIS

QUESTION SHOULD BE ANSWERED YES. BUT IF A DOCTOR OR NURSE JUST ASKED 

ABOUT CONCERNS AND DID NOT FILL OUT A QUESTIONNAIRE, THEN THIS 

QUESTION SHOULD BE ANSWERED NO.

IF AGE_NSCH = 24-71 MONTHS, SKIP TO K6Q14A.

K6Q13A Did this questionnaire ask about your concerns or observations about how [S.C.] talksor makes

speech sounds?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K6Q13B Did this questionnaire ask about your concerns or observations about how [S.C.]interacts with 

you and others?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [ALL SKIP TO K6Q15]

K6Q14A Did this questionnaire ask about your concerns or observations about words and phrases [S.C.] 

uses and understands?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 97 

K6Q14B Did this questionnaire ask about your concerns or observations about how [S.C.] behaves and gets

along with you and others?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K6Q15 Does [S.C.] have any developmental problems for which [he/she] has a writtenintervention plan

called an [IF AGE < 36 MONTHS, INSERT: Individualized Family Services Plan or an IFSP?; IF 

AGE ≥ 36 MONTHS, INSERT: Individualized Education Program orIEP?]

READ IF NECESSARY: Some young children have developmental delays or other problems for 

which they receive services from a program called Early Intervention Services or Special 

Education. Children receiving these services have a written intervention plan called an IFSP if the 

child is under 3 years old, or an IEP if 3 years or older. Services on an IFSP or an IEP might 

include things such as special instruction; speech language therapy; vision and hearing services; 

psychological services; health services; social work services; family counseling and support; 

transportation; service coordination or other services needed to support the child’s development.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

Subdomain 3: Child care

K6Q20 The next questions are about child care. Does [S.C.] receive care for at least 10 hoursper week 

from someone not related to [him/her]? This could be a day care center, preschool, Head Start 

program, nanny, au pair, or any other non-relative.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

READ IF NECESSARY: Child care should be reported regardless of whether care is paid or 

unpaid, or provided by certified or uncertified providers. Occasional babysitting is not included.

Head Start is a federally-funded program to help young children from low-income families get 

ready for kindergarten and grade school. Children who participate are usually between three and 

five years old, but there are Head Start programs for even younger children.

K6Q27 [During the past 12 months / Since [S.C]’s birth], did you or anyone in the family have to quit a

job, not take a job, or greatly change your job because of problems with child care for[S.C.]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7)REFUSED
Page 98  Series 1, No. 59 

Subdomain 4: Breastfeeding

K6Q40 Was [S.C.] ever breastfed or fed breastmilk?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [SKIP TO NEXT SUBDOMAIN IF NO/DK/RF]

K6Q41 How old was [he/she] when [he/she] completely stopped breastfeeding or being fed breast milk?

RECORD AGE /

(995) STILL BREASTFEEDING

(996) DON'T KNOW

(997) REFUSED

K6Q42 How old was [S.C.] when [he/she] was first fed formula?

RECORD AGE /

ENTER 994 FOR "AT BIRTH"

(995) "CHILD HAS NEVER BEEN FED FORMULA" 

(996) DON'T KNOW

(997) REFUSED

K6Q43 This next question is about the first thing that [S.C.] was given other than breast milk or formula.

Please include juice, cow’s milk, sugar water, baby food, or anything else that [S.C.] might have 

been given, even water. How old was [S.C.] when [he/she] was first fed anything other than 

breast milk or formula?

RECORD AGE /

ENTER 994 FOR "AT BIRTH"

(995) "CHILD HAS NEVER BEEN FED ANYTHING OTHER THAN BREAST MILK OR 

FORMULA"

(996) DON'T KNOW

(997) REFUSED

Subdomain 5: Flourishing

SKIP TO K6Q65 IF AGE < 6 MONTHS

INTRO I am going to read a list of items that sometimes describe children. For each item, please tell me

how often this was true for [S.C.] during the pastmonth.

K6Q70 [He/She] is affectionate and tender with you. Would you say never, rarely, sometimes, usually, or 

always true for [S.C.] during the pastmonth?

K6Q73 [He/She] bounces back quickly when things don’t go [his/her] way. Would you say never, rarely, 

sometimes, usually, or always true for [S.C.] during the pastmonth?

K6Q71 [He/She] shows interest and curiosity in learning new things. Would you saynever, rarely, 

sometimes, usually, or always true for [S.C.] during the pastmonth?

K6Q72 [He/She] smiles and laughs a lot.
Series 1, No. 59  Page 99 

READ AS NECESSARY: Would you say never, rarely, sometimes, usually, or always true for 

[S.C.] during the past month?

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON'T KNOW

(7) REFUSED

FOR EACH ITEM

Subdomain 6: Time use 

K6Q65 On an average weekday, about how much time does [S.C.] usually spend in front of a TV

watching TV programs, videos, or playing videogames?

RECORD NUMBER OF HOURS OR MINUTES / 

ENTER 0 FOR NO TIME SPENT IN FRONT OF TV

(995) DON'T OWN A TV 

(996) DON'T KNOW

(997) REFUSED

IF 1-665, THEN GO TO K6Q65A; ELSE GO TO K6Q66

K6Q66 On an average weekday, about how much time does [S.C.] usually spend withcomputers, cell 

phones, handheld video games, and other electronicdevices?

RECORD NUMBER OF HOURS OR MINUTES /

ENTER 0 FOR NO TIME SPENT IN FRONT OF THESE DEVICES

(995) DON'T OWN ANY OF THESE DEVICES 

(996) DON'T KNOW

(997) REFUSED

IF 1-665, THEN GO TO K6Q65A; ELSE GO TO K6Q66

K6Q60 During the past week, how many days did you or other family members read to[S.C.]?

NUMBER OF DAYS

(96) DON’T KNOW

(97) REFUSED

READ IF NECESSARY: Reading stories includes books with words or pictures but not books 

read by an audio tape, record, CD, or computer.

READ IF NECESSARY: "During the past week" means "during the last seven days."

K6Q61 During the past week, how many days did you or other family members tell stories or sing songs

to [S.C.]?
Series 1, No. 59  Page 101 

NUMBER OF DAYS

(96) DON’T KNOW

(97) REFUSED

READ IF NECESSARY: "During the past week" means "during the last seven days." 

K6Q63 During the past week, how many days did [S.C.] play with other children [his/her]age?

NUMBER OF DAYS

(96) DON’T KNOW

(97) REFUSED

READ IF NECESSARY: "During the past week" means "during the last seven days."

K6Q64 During the past week, how many days did you or any family member take [S.C.] on anykind of 

outing, such as to the park, library, zoo, shopping, church, restaurants, or family gatherings?

NUMBER OF DAYS

(96) DON’T KNOW

(97) REFUSED

READ IF NECESSARY: "During the past week" means "during the last seven days."
Page 100  Series 1, No. 59 

Section 7: Middle Childhood and Adolescence (6-17 years)

Subdomain 1: School enrollment

K7Q01 IF CURRENT MONTH IS JUNE, JULY, OR AUGUST, ASK: “During the last school year, what

kind of school was [S.C.] enrolled in? Is it a public school, private school, or home-school?” 

ELSE ASK: “What kind of school is [S.C.] currently enrolled in? Is it a public school, private 

school, or home-school?

(1) PUBLIC [SKIP TO K7Q02]

(2) PRIVATE [SKIP TO K7Q02]

(3) HOME-SCHOOLED [SKIP TO K7Q05]

(4) [S.C.] IS NOT ENROLLED IN SCHOOL. [SKIP TO K7Q01F]

(6) DON’T KNOW [SKIP TO K7Q02]

(7) REFUSED [SKIP TO K7Q02]

INTERVIEWER INSTRUCTION: IF THE CHILD WAS ENROLLED IN MORE THAN ONE 

TYPE OF SCHOOL DURING THE CURRENT OR LAST SCHOOL YEAR, ASK THE TYPE 

OF SCHOOL THAT THE CHILD HAS MOST RECENTLY ATTENDED.

K7Q01F At any time during the past 12 months, was [S.C.] enrolled in a public school, a privateschool, or 

home school?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K7Q05 IF NO/DK/RF]

K7Q02 During the past 12 months, that is since [FILL: CURRENT MONTH, 1 YEAR AGO], about how

many days did [S.C.] miss school because of illness orinjury?

ENTER THE FOLLOWING AS NEEDED:

(000) NONE

(993) ENTIRE SCHOOL YEAR

(994) HOME SCHOOLED

(995) DID NOT GO TO SCHOOL 

(996) DON'T KNOW

(997) REFUSED

INCLUDE ANSWER CHOICES FOR ENTIRE SCHOOL YEAR (993), HOME SCHOOLED 

(994), OR DID NOT GO TO SCHOOL (995). INCLUDE QUESTION CONFIRMING 

ANSWER IF NUMBER OF DAYS IS GREATER THAN 20.

SKIP TO K7Q05 IF CHILD WAS HOME SCHOOLED OR DID NOT GO TO SCHOOL.

K7Q04 During the past 12 months, how many times has [S.C.]’s school contacted you or another adult in 

your household about any problems [he/she] is having withschool?

TIMES 

(96) DON'T KNOW
Page 102  Series 1, No. 59 

(97) REFUSED

IF 21-76 GO TO SC_K7Q04

ELSE IF 1-20, 96, 97 GO TO K7Q05

READ IF NECESSARY: This includes school related problems but not health related problems.

INTERVIEWER INSTRUCTION: THIS INCLUDES SCHOOL RELATED PROBLEMS BUT 

NOT HEALTH RELATED PROBLEMS.

K7Q05 Since starting kindergarten, has [he/she] repeated anygrades?

(1) YES 

(0) NO [SKIP TO K7Q11]

(6) DON'T KNOW [SKIP TO K7Q11]

(7) REFUSED [SKIP TO K7Q11]

K7Q05_A Which grade or grades did [he/she] repeat? [Mark all that apply.] 

(1) FIRST GRADE

(2) SECOND GRADE

(3) THIRD GRADE

(4) FOURTH GRADE

(5) FIFTH GRADE

(6) SIXTH GRADE

(7) SEVENTH GRADE

(8) EIGHTH GRADE

(9) NINTH GRADE (FRESHMAN YEAR)

(10) TENTH GRADE (SOPHMORE YEAR)

(11) ELEVENTH GRADE (JUNIOR YEAR)

(12) TWELFTH GRADE (SENIOR YEAR)

(13) KINDERGARTEN

(96) DON'T KNOW

(97) REFUSED

K7Q11 Does [S.C.] have a health problem, condition, or disability for which [he/she] has a written 

intervention plan called an Individualized Education Program orIEP?

READ IF NECESSARY: Some children have difficulty in school because of a health problem, 

condition, or a disability. These children may receive services from a program called Special 

Education and have a written intervention plan called an Individualized Education Program or 

IEP. Services on an IEP might include things such as special instruction; speech language 

therapy; vision and hearing services; psychological services; health services; social work services; 

family counseling and support; transportation; or other services needed to support the child’s 

educational performance.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 103 

Subdomain 2: After-school activities and parental involvement

K7Q30 During the past 12 months, was [S.C.] on a sports team or did [he/she] take sports lessons after

school or on weekends?

READ IF NECESSARY: Include any teams run by your child’s school or community groups.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K7Q31 During the past 12 months, did [he/she] participate in any clubs or organizations after school or on

weekends?

READ IF NECESSARY: Examples of clubs or organizations are scouts, arts, religious groups, 

and boys/girls clubs.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K7Q32 During the past 12 months, did [he/she] participate in any other organizedactivities or lessons, 

such as music, dance, language, or other arts?

READ IF NECESSARY: This question can include organized lessons in music, dance, foreign 

languages, performing arts, computers, and more.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

SKIP TO K7Q34 IF K7Q30, K7Q31, AND K7Q32 ARE ALL NO/DK/RF.

K7Q33 During the past 12 months, how often did you attend events or activitiesthat [S.C.] participated

in? Would you say never, sometimes, usually or always?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON'T KNOW

(7) REFUSED

K7Q34 Regarding [S.C.]’s friends, would you say that you have met all of [his/her] friends,most of 

[his/her] friends, some of [his/her] friends, or none of [his/her] friends?

(1) ALL OF [HIS/HER] FRIENDS

(2) MOST OF [HIS/HER] FRIENDS

(3) SOME OF [HIS/HER] FRIENDS

(4) NONE OF [HIS/HER] FRIENDS

(5) CHILD HAS NO FRIENDS

(6) DON'T KNOW

(7) REFUSED 
Page 104  Series 1, No. 59 

IF AGE < 144 MONTHS (12 YEARS), SKIP TO K7Q40.

K7Q37 During the past 12 months, how often has [S.C.] been involved in any type of community service 

or volunteer work at school, church, or in the community? Would you say once a week or more, a 

few times a month, a few times a year, or never?

(1) ONCE A WEEK OR MORE

(2) A FEW TIMES A MONTH

(3) A FEW TIMES A YEAR

(4) NEVER 

(6) DON'T KNOW

(7) REFUSED

K7Q38 During the past week, did [S.C.] earn money from any work, including regular jobs as well as

babysitting, cutting grass, or other occasionalwork?

(1) YES [SKIP TO K7Q39]

(0) NO [SKIP TO K7Q40]

(6) DON’T KNOW [SKIP TO K7Q40]

(7) REFUSED [SKIP TO K7Q40]

READ AS NECESSARY: Do not include household chores.

READ IF NECESSARY: "During the past week" means "during the last sevendays." 

K7Q39 During the past week, how many hours did [S.C.] work forpay?

(995) MORE THAN ZERO BUT LESS THAN 1 HOUR 

(996) DON'T KNOW

(997) REFUSED

READ IF NECESSARY: "During the past week" means "during the last seven days."

Subdomain 3: Sleep and exercise

K7Q40 During the past week, on how many nights did [S.C.] get enough sleep for a child [his/her] age?

NUMBER OF DAYS

(96) DON'T KNOW

(97) REFUSED

READ IF NECESSARY: “Enough sleep” is whatever you define it as for this child. 

READ IF NECESSARY: "During the past week" means "during the last seven days."
Series 1, No. 59  Page 105 

K7Q41 During the past week, on how many days did [S.C.] exercise, play a sport, orparticipate in 

physical activity for at least 20 minutes that made [him/her] sweat and breathehard?

NUMBER OF DAYS

(96) DON'T KNOW

(97) REFUSED

READ IF NECESSARY: Include active sports such as baseball, softball, basketball, swimming, 

soccer, tennis, or football; riding a bike or rollerskating; walking or jogging; jumping rope; 

gymnastics; and active dance such as ballet.

READ IF NECESSARY: "During the past week" means "during the last seven days."
Page 106  Series 1, No. 59 

Subdomain 4: Reading

K7Q50 On an average weekday, about how much time does [he/she] usually spend reading for pleasure?

ENTER 0 FOR NO TIME SPENT READING 

(995) FOR CHILD CAN'T READ

(996) FOR DON'T KNOW 

(997) FOR REFUSED

INTERVIEWER NOTE: RESPONSE MUST BE IN EITHER HOURS OR MINUTES

READ IF NECESSARY: Time spent reading includes the time a child spends reading to 

themselves or being read to by another person.

IF THE PARENT ASKS WHAT TIME FRAME THE QUESTION REFERS TO, SAY: It refers

to average weekdays "recently."

Subdomain 5: Media consumption

K7Q60 On an average weekday, about how much time does [S.C.] usually spend in front of a TV

watching TV programs, videos, DVDs, or playing videogames?

READ IF NECESSARY: Do not include time spent watching TV programs, videos, or DVDs at 

school.

READ IF NECESSARY: Do not include time spent doing any of these activities in front of a 

computer.

RECORD NUMBER OF HOURS OR MINUTES 

(995) DON'T OWN A TV

(996) DON’T KNOW

(997) REFUSED

K7Q91 On an average weekday, about how much time does [S.C.] usually spend with computers, cell

phones, handheld video games, and other electronic devices, doing things other than schoolwork?

ENTER 0 FOR NO TIME SPENT IN FRONT OF A TV

 ENTER NUMBER 

(995) DON'T OWN A TV

(996) DON’T KNOW

(997) REFUSED

IF K7Q60 IN (000, 995, 996, 997) [SKIP TO K7Q61 K7Q91] 

ELSE, [SKIP TO K7Q60A]

K7Q61A Do you monitor the content of what [he/she] watches on TV, plays on the computer, or does on 

electronic devices?

READ IF RESPONDENT ASKS WHAT “MONITOR” MEANS: We want to know if you check 

or pre-screen these media for topics you might not approve of, such as violence, drugs or alcohol, 

fighting, guns, or sexual content.

INTERVIEWER INSTRUCTION: IF A RESPONDENT STATES THAT HE/SHE USES 

THESE MEDIA TOGETHER WITH THE CHILD (SUCH AS WATCHING TV SHOWS OR 

MOVIES TOGETHER) TO EXPLAIN THE CONTENT TO THE CHILD, CODE THIS AS A
Series 1, No. 59  Page 107 

“YES” RESPONSE.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K7Q61 Do you limit the amount of time [he/she] spends watching TV, playing on the computer,or using 

electronic devices?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K7Q62 Does [he/she] have a TV, computer, or access to electronic devices in [his/her] bedroom?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 
Page 108  Series 1, No. 59 

Subdomain 6: Bullying and emotional difficulties

K7Q70_INTRO I am going to read a list of items that sometimes describe children. For each item, please tell me 

how often this was true for [S.C.] during the past month.

K7Q70 [He/She] argues too much. Would you say never, rarely, sometimes, usually, or always true for 

[S.C.] during the past month?

K7Q71 [He/She] bullies or is cruel or mean to others. Would you say never, rarely, sometimes, usually, or 

always true for [S.C.] during the pastmonth?

K7Q79 [He/She] is unhappy, sad, or depressed. Would you say never, rarely, sometimes, usually, or 

always true for [S.C.] during the pastmonth?

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON’T KNOW

(7) REFUSED 

FOR EACH ITEM

Subdomain 7: Flourishing

K7Q84 [He/She] finishes the tasks [he/she] starts and follows through with what [he/she] says

[he’ll/she’ll] do.

K7Q85 [He/She] stays calm and in control when faced with a challenge.

K7Q86 [He/She] shows interest and curiosity in learning newthings.

K7Q82 [He/She] cares about doing well in school.

K7Q83 [He/She] does all required homework.

(READ IF NECESSARY: Would you say never, rarely, sometimes, usually, or always true for 

[S.C.] during the past month?)

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON’T KNOW

(7) REFUSED 

FOR EACH ITEM
Series 1, No. 59  Page 109 

Section 8: Family Functioning

Subdomain 1: Family activities

K8Q12 About how often does [S.C.] attend a religiousservice?

ENTER (000) NEVER OR ZERO TIMES OR DOES NOT ATTEND

[ENTER NUMBER]

(96) DON'T KNOW

(97) REFUSED

K8Q11 During the past week, on how many days did all the family members who live in the household eat

a meal together?

DAYS

(96) DON'T KNOW

(97) REFUSED

READ IF NECESSARY: "During the past week" means "during the last seven days."

Subdomain 2: Parent/child relationship

IF AGE < 72 MONTHS (6 YEARS), SKIP TO K8Q30.

K8Q21 How well can you and [S.C.] share ideas or talk about things that really matter? Would you say 

very well, somewhat well, not very well, or not very well atall?

(1) VERY WELL

(2) SOMEWHAT WELL 

(3) NOT VERY WELL 

(4) NOT WELL AT ALL 

(6) DON'T KNOW

(7) REFUSED 
Page 110  Series 1, No. 59 

Subdomain 3: Family stress

K8Q30 IF RESPONDENT IS MOTHER/FATHER, FILL “parenthood”. ELSE FILL “raisingchildren”.

In general, how well do you feel you are coping with the day to day demands of [parenthood / 

raising children]? Would you say that you are coping very well, somewhat well, not very well, or 

not well at all?

(1) VERY WELL

(2) SOMEWHAT WELL 

(3) NOT VERY WELL 

(4) NOT VERY WELL AT ALL

(6) DON'T KNOW

(7) REFUSED

K8Q31 During the past month, howoften have you felt [S.C.] is much harder to care for than most

children [his/her] age? Would you say never, rarely, sometimes, usually, oralways?

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON’T KNOW

(7) REFUSED

K8Q32 During the past month, how often have you felt [he/she] does things that really bother you alot?

READ IF NECESSARY: Would you say never, rarely, sometimes, usually, or always?

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON’T KNOW

(7) REFUSED

K8Q34 During the past month, how often have you felt angry with[him/her]?

READ IF NECESSARY: Would you say never, rarely, sometimes, usually, or always?

(1) NEVER 

(2) RARELY

(3) SOMETIMES

(4) USUALLY

(5) ALWAYS

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 111 

K8Q35 IF RESPONDENT IS MOTHER/FATHER, FILL “parenthood”. ELSE FILL “raising children”.

Is there someone that you can turn to for day-to-day emotional help with [parenthood/raising 

children]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

READ IF NECESSARY: This can be any person, including your spouse.
Page 112  Series 1, No. 59 

Section 9: Parental Health

Subdomain 1: Household composition

K9Q00 Including the adults and all the children, how many people live in this household?

RECORD NUMBER OF PEOPLE.

[Answer must be greater than the number of children to proceed.]

INTERVIEWER INSTRUCTION: EACH PERSON IN THE HOUSEHOLD MUST BE A 

CURRENT RESIDENT OF THE HOUSEHOLD. A CURRENT RESIDENT IS DEFINED AS A 

PLACE WHERE THE PERSON IS STAYING FOR MORE THAN TWO MONTHS AT THE 

TIME OF THE SURVEY CONTACT. IF A PERSON HAS NO PLACE WHERE HE OR SHE 

USUALLY STAYS, THE PERSON SHOULD BE CONSIDERED A CURRENT RESIDENT 

REGARDLESS OF THE LENGTH OF THE CURRENT STAY.

PERSONS AWAY FROM THEIR RESIDENCE FOR TWO MONTHS OR LESS, WHETHER

TRAVELING OR IN THE HOSPITAL, ARE CONSIDERED “IN RESIDENCE.”

PERSONS AWAY FROM THEIR RESIDENCE FOR MORE THAN TWO MONTHS ARE 

CONSIDERED “NOT IN RESIDENCE” UNLESS THE PERSON IS AWAY AT SCHOOL (I.E., 

BOARDING SCHOOL, MILITARY ACADEMY, PREP SCHOOL, ETC.).

CHILDREN WHO ONLY LIVE PART-TIME IN THE HOUSEHOLD BECAUSE OF 

CUSTODY ISSUES SHOULD BE INCLUDED IF THEY ARE STAYING THERE WHEN 

CONTACT WITH THE HOUSEHOLD IS MADE.

ENTER NUMBER; 

(96) DON'T KNOW

(97) REFUSED

CP_K9Q10A IF K1Q02=96, 97 GO TO C10Q02A

ELSE GO TO K9Q10A

K9Q10A I have that you are [S.C.]'s [FILL FROM K1Q02]. Is that correct?

(1) YES [GO TO CP_C10Q02A]

(0) NO [GO TO CP_C10Q02A]

(6) DON'T KNOW [GO TO CP_C10Q02A]

(7) REFUSED [GO TO CP_C10Q02A]

CP_C10Q02A IF K9Q10A=0, 6, 7 THEN GO TO C10Q02A

IF K9Q10A=01 and K1Q02=01, 02 THEN GO TO C10Q02A

IF K9Q10A=01 and K1Q02=11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26 THEN GO

TO C10Q02B and fill C10Q02A with C10Q02A=K1Q02value 

C10Q02A IF K1Q02=96, 97 OR K9Q10A=0, 6, 7 THENDISPLAY:

What is your relationship to [S.C.]?

IF R RESPONDS “Mother” or “Father,” YOU MUST PROBE: Are you [S.C.]’s biological, step, 

foster, or adoptive mother/father?

IF R RESPONDS “Parent's Partner,” PROBE IF NOT SURE: Are you male or female?
Series 1, No. 59  Page 113 

IF K9Q10A=01 AND K1Q02=01 THEN DISPLAY:

Are you [S.C.]’s biological, adoptive, step, or foster mother? 

IF K9Q10A=01 AND K1Q02=02 THEN DISPLAY:

Are you [S.C.]’s biological, adoptive, step, or foster father?

PARENT

(1) BIOLOGICAL MOTHER

(2) STEP MOTHER

(3) FOSTER MOTHER 

(4) ADOPTIVE MOTHER 

(5) MOTHER, but TYPE REFUSED

(6) BIOLOGICAL FATHER

(7) STEP FATHER

(8) FOSTER FATHER

(9) ADOPTIVE FATHER 

(10) FATHER, but TYPE REFUSED

OLDER RELATIVES OR GUARDIANS

(11) GRANDMOTHER

(12) GRANDFATHER

(13) AUNT

(14) UNCLE

(15) FEMALE GUARDIAN

(16) MALE GUARDIAN

OTHER RELATIVES

(17) SISTER (BIOLOGICAL, STEP, FOSTER, HALF,ADOPTIVE)

(18) BROTHER (BIOLOGICAL, STEP, FOSTER, HALF,ADOPTIVE)

(19) COUSIN

(20) IN-LAW OF ANY TYPE

(22) OTHER RELATIVE / FAMILY MEMBER

OTHER NON-RELATIVES

(23) PARENT’S BOYFRIEND / MALE PARTNER

(24) PARENT’S GIRLFRIEND / FEMALE PARTNER 

(25) PARENT’S PARTNER, but SEX REFUSED

(26) OTHER NON-RELATIVE ORFRIEND

(96) DON’T KNOW

(97) REFUSED

SC_C10Q02A [IF K1Q02 = 01 AND C10Q02A NOT IN (1, 2, 3, 4, 5)] OR [IF K2Q02 = 02 AND C10Q02A

NOT IN (6, 7, 8, 9, 10)] OR [IF K9Q10A=0, 6, 7] THEN DISPLAY:

INTERVIEWER CHECK:

YOU ARE CHANGING THE RESPONDENT FROM [FILL WITH ANSWER FROM K1Q02] 

TO [FILL WITH ANSWER FROM C10Q02A] . IS THIS CORRECT?

(1) YES [GO TO C10Q02B]

(2) NO - RETURN TO C10Q02A AND ENTER CORRECT RESPONSE [GO BACK TO 

C10Q02A]

C10Q02B IF K9Q00 = 2 THEN SKIP TO C10Q02B_CONF
Page 114  Series 1, No. 59 

IF K9Q00 = DK/RF, THEN READ:

For the other people that live in your household with you and [S.C.], what is their relationship to 

[S.C.]? [Mark all that apply] 

IF K9Q00 > 2, THEN READ:

In addition to you and [S.C.], I have that [FILL: K9Q00 - 2] [other person lives/other people live] 

in your household. What is their relationship to [S.C.]? [Mark all that apply] 

IF R RESPONDS “Mother” or “Father,” YOU MUST PROBE: Is that [S.C.]’s biological, step, 

foster, or adoptive mother/father?

IF R RESPONDS “Partner,” PROBE: Is the partner male or female? 

PARENT

(1) BIOLOGICAL MOTHER (6) BIOLOGICAL FATHER

(2) STEP MOTHER (7) STEP FATHER

(3) FOSTER MOTHER (8) FOSTER FATHER 

(4) ADOPTIVE MOTHER (9) ADOPTIVE FATHER

(5) MOTHER, but TYPE REFUSED (10) FATHER, but TYPE REFUSED

OLDER RELATIVES OR GUARDIANS

(11) GRANDMOTHER (14) UNCLE

(12) GRANDFATHER (15) FEMALE GUARDIAN

(13) AUNT (16) MALE GUARDIAN

OTHER RELATIVES

(17) SISTER

(18) BROTHER

(19) COUSIN

(20) IN-LAW OF ANY TYPE

(21) [S.C.]’S CHILD, SON, OR DAUGHTER

(22) OTHER RELATIVE / FAMILY MEMBER

OTHER NON-RELATIVES

(23) PARENT’S BOYFRIEND / MALE PARTNER

(24) PARENT’S GIRLFRIEND / FEMALE PARTNER 

(25) PARENT’S PARTNER, but SEX REFUSED

(26) OTHER NON-RELATIVE ORFRIEND

(96) DON’T KNOW

(97) REFUSED

C10Q02B_

CONF I am now going to list all the people that live in your household.

I have that [LIST OF RELATIONSHIPS ROSTERED] live in this household with [S.C.]. 

Is this a correct list of everyone living in your household?

(1) CONFIRMED - THIS LIST ISCORRECT

(2) NOT CORRECT - RETURN TO K9Q00 AND STARTAGAIN

C10Q02B_ Earlier you told me that there are [VALUE FROM K9Q00] people living in your household. 

WARNING However, based on the relationships you just gave, I have [COUNT OFRELATIONSHIPS

INCLUDING R & S.C.] people living in your household. Let's re-confirm your answers.
Series 1, No. 59  Page 115 

(1) RETURN TO RE-CONFIRM ANSWERS [GO TO K9Q00]

USE RARELY:

(2) ISSUE CANNOT BE RESOLVED - CONTINUE ON [GO TO C10Q02C]

SKIP TO K9Q16 IF ANY BIOLOGICAL MOTHER OR BIOLOGICAL FATHER IN 

HOUSEHOLD.

SKIP TO K9Q16 IF RESPONDENT IS ADOPTIVE MOTHER OR ADOPTIVE FATHER.

C10Q02C Have you legally adopted [S.C.]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

Subdomain 2: Age and marital status of adults in household

K9Q16 SKIP TO C10Q14 IF NO MOTHER-TYPE IN HOUSEHOLD

IF C10Q02A=1-5 OR C10Q02B=1-5 ASK K9Q16. ELSE, SKIP TO C10Q14. 

IF C10Q02A=1-5 FILL “are you”. ELSE, FILL “is [S.C.]’s [MOTHER TYPE]”

How old [are you / is [S.C.]’s [MOTHER TYPE]]?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

YEARS 

(996) DON’T KNOW

(997) REFUSED

C10Q14 What is the age of the oldest adult living in the household?

 YEARS 

(996) DON'T KNOW

(997) REFUSED

IF HOUSEHOLD INCLUDES A MOTHER AND A FATHER, ASK C10Q10. ELSE, SKIP TO 

C10Q11A.

SC_C10Q14 INTERVIEWER CHECK: YOU ENTERED [FILL WITH ANSWER FROM C10Q14]FOR THE

OLDEST ADULT LIVING IN THE HOUSEHOLD. IS THATCORRECT?

(1) YES [GO TO C10Q10]

(2) NO [GO BACK TO C10Q14]

C10Q10 IF THE RESPONDENT IS THE MOTHER, THEN READ: Are you and [S.C.]’s[FATHER

TYPE] currently married, separated, divorced, or never married?

IF THE RESPONDENT IS THE FATHER, THEN READ: Are you and [S.C.]’s [MOTHER

TYPE] currently married, separated, divorced, or never married?
Page 116  Series 1, No. 59 

IF THE RESPONDENT IS NEITHER THE MOTHER NOR THE FATHER, THEN READ: Are

[S.C.]’s [MOTHER TYPE] and [FATHER TYPE] currently married, separated, divorced, or never 

married?

(1) CURRENTLY MARRIED [SKIP TO K9Q18]

(2) SEPARATED 

(3) DIVORCED

(4) NEVER MARRIED

(6) DON'T KNOW

(7) REFUSED

C10Q10A IF THE RESPONDENT IS THE MOTHER, THEN READ: Are you and [S.C.]’s[FATHER

TYPE] currently living together as partners?

IF THE RESPONDENT IS THE FATHER, THEN READ: Are you and [S.C.]’s [MOTHER

TYPE] currently living together as partners?

IF THE RESPONDENT IS NEITHER THE MOTHER NOR THE FATHER, THEN READ: Are

[S.C.]’s [MOTHER TYPE] and [FATHER TYPE] currently living together as partners?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [ALL SKIP TO K9Q18]

C10Q11A IF HOUSEHOLD INCLUDES A MOTHER BUT NOT A FATHER, ASK C10Q11A. ELSE, SKIP 

TO C10Q12A.

IF THE RESPONDENT IS THE MOTHER, THEN READ: Are you currently married, separated, 

divorced, widowed, or never married?

IF THE RESPONDENT IS NOT THE MOTHER, THEN READ: Is [S.C.]’s [MOTHER TYPE]

currently married, separated, divorced, widowed, or never married?

(1) MARRIED

(2) SEPARATED 

(3) DIVORCED

(4) WIDOWED

(5) NEVER MARRIED

(6) DON'T KNOW

(7) REFUSED

SKIP TO C10Q11C IF NOT MARRIED.

SKIP TO K9Q18 IF MOTHER TYPE IS FOSTER OR ADOPTIVE

C10Q11B IF RESPONDENT IS THE MOTHER (C10Q02A = 1, 2, or 5), FILL “Are you”; ELSE FILL “Is

[S.C.]’S [MOTHER TYPE]”. 

(Are you / Is [S.C.]’s [MOTHER TYPE]) married to [S.C.]’s biological father?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [ALL SKIP TO K9Q18]

C10Q11C IF THE RESPONDENT IS THE MOTHER (C10Q02A = 1-5), THEN READ: Are you currently
Series 1, No. 59  Page 117 

living with anyone as partners?

IF THE RESPONDENT IS NOT THE MOTHER, THEN READ: Is [S.C.]’s [MOTHER TYPE]

currently living with anyone as partners?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [ALL SKIP TO K9Q18]

C10Q12A IF HOUSEHOLD INCLUDES A FATHER BUT NOT A MOTHER, ASK C10Q12A. ELSE, SKIP 

TO C10Q13A.

IF THE RESPONDENT IS THE FATHER (C10Q02A= 6-10), THEN READ: Are you currently

married, separated, divorced, widowed, or never married?

IF THE RESPONDENT IS NOT THE FATHER, THEN READ: Is [S.C.]’s [FATHER TYPE]

currently married, separated, divorced, widowed, or never married?

(1) MARRIED

(2) SEPARATED 

(3) DIVORCED

(4) WIDOWED

(5) NEVER MARRIED

(6) DON'T KNOW

(7) REFUSED

SKIP TO C10Q12C IF NOT MARRIED.

SKIP TO K9Q18 IF FATHER TYPE IS FOSTER OR ADOPTIVE

C10Q12B IF RESPONDENT IS THE FATHER (C10Q02A = 6, 7, or10) FILL “Are you”; ELSE FILL “Is

[S.C.]’s [FATHER TYPE]”.

(Are you / Is [S.C.]’s [FATHER TYPE]) married to [S.C.]’s biological mother?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED [ALL SKIP TO K9Q18]

C10Q12C IF THE RESPONDENT IS THE FATHER (C10Q02A= 6-10), THEN READ: Are you currently

living with anyone as partners?

IF THE RESPONDENT IS NOT THE FATHER, THEN READ: Is [S.C.]’s [FATHER TYPE]

currently living with anyone as partners?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[ALL SKIP TO K9Q18]

C10Q13A Are you currently married, separated, divorced, widowed, or never married?

(1) MARRIED

(2) SEPARATED 
Page 118  Series 1, No. 59 

(3) DIVORCED

(4) WIDOWED

(5) NEVER MARRIED 

(6) DON'T KNOW

(7) REFUSED

SKIP TO C10Q13C IF NOT MARRIED.

C10Q13B Does your spouse currently live in the household with [S.C.]?

(1) YES [SKIP TO K9Q18]

(0) NO [SKIP TO K9Q18]

(6) DON’T KNOW [SKIP TO K9Q18]

(7) REFUSED [SKIP TO K9Q18]

C10Q13C Are you currently living with a partner?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K9Q19 IF HOUSEHOLD INCLUDES A MOTHER OR FATHER OF ANY TYPE(THAT IS, 

1<=C10Q02A<=10 OR 1<=C10Q02B<=10), SKIP TO K9Q18. ELSE, IF HOUSEHOLD 

INCLUDES NEITHER A MOTHER NOR A FATHER OF ANY TYPE, BUT INCLUDES ANY 

OLDER RELATIVE/GUARDIAN TYPES (THAT IS, 11<=C10Q02A<=16 OR 

11<=C10Q02B<=16) AND C10Q02C NOT EQUAL TO "1" THEN ASK K9Q19. ELSE, SKIP 

TO K9Q18.

Is [S.C.] currently in foster care? That is, are you or another adult in the household acting as a 

foster parent to [S.C.] under the supervision of a state or county child welfare agency?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K9Q18 ASK K9Q18 ONLY IF RESPONDENT HAS A SPOUSE OR PARTNER((C10Q02A=1-10 AND

((C10Q10=1 OR C10Q10A=1 OR C10Q11A=1 OR C10Q11C=1 OR C10Q12A=1 OR 

C10Q12C=1)) OR (C10Q02A NOT EQ 1-10 AND (C10Q13A=1 OR C10Q13C=1)) ; ELSE 

SKIP TO K9Q20.

The next question is about your relationship with your spouse or partner. Would you say that your 

relationship is completely happy, very happy, fairly happy, or not too happy?

(1) COMPLETELY HAPPY

(2) VERY HAPPY

(3) FAIRLY HAPPY

(4) NOT TOO HAPPY

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 119 

Subdomain 3: General health status

K9Q20 IF (C10Q02A=1-5 OR C10Q02B=1-5) ASK K9Q20. ELSE, SKIP TOK9Q21.

IF C10Q02A=1-5 FILL “your”. ELSE, FILL "[S.C.]’s [MOTHER TYPE]'s/your"

Would you say that, in general, ([S.C.]’s [MOTHER TYPE]'s/your) health is excellent, very good, 

good, fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON’T KNOW

(7) REFUSED

K9Q21 IF (C10Q02A=6-10 OR C10Q02B=6-10) ASK K9Q21. ELSE, SKIP TOK9Q22.

IF C10Q02A=6-10, FILL “your”. ELSE, "[S.C.]’s [FATHER TYPE]'s"

Would you say that, in general, ([S.C.]’s [FATHER TYPE]'s/your) health is excellent, very good, 

good, fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON’T KNOW

(7) REFUSED

K9Q22 IF (C10Q02A NE 1-10) ASK K9Q22. ELSE SKIP TOK9Q23.

Would you say that, in general, your health is excellent, very good, good, fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE

[TEXTFILL: answer from C10Q02A] LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON’T KNOW

(7) REFUSED 

K9Q23 IF (C10Q02A=1-5 OR C10Q02B=1-5) ASK K9Q23. ELSE, SKIP TOK9Q24.
Page 120  Series 1, No. 59 

IF C10Q02A=1-5 FILL “your”. ELSE, FILL [MOTHER TYPE].

Would you say that, in general, ([S.C.]’s [MOTHER TYPE]'s/your) mental and emotional health 

is excellent, very good, good, fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON’T KNOW

(7) REFUSED

K9Q24 IF (C10Q02A=6-10 OR C10Q02B=6-10), ASK K9Q24. ELSE, SKIP TOK9Q25.

IF C10Q02A=6-10 FILL “your”. ELSE, FILL [FATHER TYPE].

Would you say that, in general, ([S.C.]’s [FATHER TYPE]'s/your) mental and emotional health is 

excellent, very good, good, fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR 

(6) DON’T KNOW

(7) REFUSED

K9Q25 IF C10Q02A NE (1-10), ASK K9Q25. ELSE SKIP TOK9Q30.

Would you say that, in general, your mental and emotional health is excellent, very good, good, 

fair, or poor?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[TEXTFILL: answer from C10Q02A] LIVING IN THIS HOUSE.

(1) EXCELLENT 

(2) VERY GOOD

(3) GOOD

(4) FAIR

(5) POOR

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 121 

Subdomain 4: Smoking

K9Q40 Does anyone living in your household use cigarettes, cigars, or pipe tobacco?

(1) YES 

(0) NO [SKIP TO INTRO_ACE]

(6) DON’T KNOW [SKIP TO INTRO_ACE]

(7) REFUSED [SKIP TO INTRO_ACE]

K9Q41 Does anyone smoke inside [S.C.]’s home?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

Subdomain 5: Adverse family experiences

INTRO_ACE I’d like to ask you some questions about events that may have happened during [S.C.]’slife.

These things that can happen to any family, but some people may feel uncomfortable with these 

questions. You can ask me to skip any question you do not want to answer.

ACE1 Since [S.C.] was born, how often has it been very hard to get by on your family's income, for 

example, it was hard to cover the basics like food or housing? Would you say very often, 

somewhat often, not very often, or never?

(1) VERY OFTEN

(2) SOMEWHAT OFTEN

(3) RARELY

(4) NEVER 

(6) DON'T KNOW

(7) REFUSED

ACE3 Did [S.C.] ever live with a parent or guardian who got divorced or separated after [S.C.]was born?

ACE4 Did [S.C.] ever live with a parent or guardian whodied?

ACE5 Did [S.C.] ever live with a parent or guardian who served time in jail or prison after [S.C.] was

born?

ACE6 Did [S.C.] ever see or hear any parents, guardians, or any other adults in [his/her] home slap, hit,

kick, punch, or beat each other up?

ACE7 Was [S.C.] ever the victim of violence or witness any violence in [his/her] neighborhood?

ACE8 Did [S.C.] ever live with anyone who was mentally ill or suicidal, or severely depressedfor more

than a couple of weeks?

ACE9 Did [S.C.] ever live with anyone who had a problem with alcohol ordrugs?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

FOR EACH ITEM 
Page 122  Series 1, No. 59 

ACE10 Was [S.C.] ever treated or judged unfairly because of [his/her] race or ethnicgroup?

(1) YES [SKIP TO ACE11]

(0) NO [SKIP TO K9Q96]

(6) DON'T KNOW [SKIP TO K9Q96]

(7) REFUSED [SKIP TO K9Q96]

ACE11 During the past year, how often was [S.C.] treated or judged unfairly? Would you say very often, 

somewhat often, rarely, or never?

READ AS NECESSARY: This question refers to how often [S.C.] was treated or judged unfairly 

because of [his/her] race or ethnic group.

(1) VERY OFTEN

(2) SOMEWHAT OFTEN

(3) RARELY

(4) NEVER 

(6) DON'T KNOW

(7) REFUSED

Subdomain 6: Presence of adult mentor

SKIP TO NEXT SECTION IF AGE < 6 YEARS.

K9Q96 Other than adults in your home or [S.C.]’s parents, is there at least one other adult in [S.C.]’s

school, neighborhood, or community who knows [him/her] well and who [he/she] can rely on for 

advice or guidance?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 123 

Section 10: Neighborhood and Community Characteristics

Subdomain 1: Neighborhood amenities

INTRO Now, I have a few questions about your neighborhood and community. Please tell meif the 

following places and things are available to children in your neighborhood, even if [S.C.] does not 

actually use them.

K10Q11 Sidewalks or walking paths?

K10Q12 A park or playground area?

K10Q13 A recreation center, community center, or boys’ or girls’ club?

K10Q14 A library or bookmobile?

READ IF NECESSARY: Do those exist in your neighborhood?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 

FOR EACH ITEM

Subdomain 2: Neighborhood condition

K10Q20 In your neighborhood, is there litter or garbage on the streetor sidewalk? 

K10Q22 How about poorly kept or rundown housing?

K10Q23 How about vandalism such as broken windows orgraffiti?

READ IF NECESSARY: Does that exist in your neighborhood?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 

FOR EACH ITEM

Subdomain 3: Social capital

INTRO Now, for the next questions, I am going to ask how much you agree or disagree with each of these 

statements about your neighborhood or community.

K10Q30 “People in this neighborhood help each otherout.”

K10Q31 “We watch out for each other’s children inthis neighborhood.”

K10Q32 “There are people I can count on in thisneighborhood.”

K10Q34 “If my child were outside playing and got hurt or scared, there are adults nearby who I trust to help 

my child.”

IF RESPONDENT SAYS THEIR CHILD IS TOO YOUNG TO PLAY OUTSIDE, SAY: Please

answer the question as IF your child were playing outside.

(1) DEFINITELY AGREE

(2) SOMEWHAT AGREE

(3) SOMEWHAT DISAGREE

(4) DEFINITELY DISAGREE
Page 124  Series 1, No. 59 

(6) DON’T KNOW

(7) REFUSED 

FOR EACH ITEM

Subdomain 4: Perceived safety

K10Q40 How often do you feel [S.C.] is safe in your community or neighborhood? Would you say never, 

sometimes, usually, or always?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED

IF SC_NSCH < 6 YEARS, SKIP TO K11Q01_INTRO. IF K7Q01F = 0, 6, 7, OR K7Q02 = 994, 

995, OR K7Q01 = 3 [I.E. NOT ENROLLED IN PAST 12 MONTHS/HOME-SCHOOLED], SKIP 

TO K11Q01_INTRO.

K10Q41 How often do you feel [he/she] is safe atschool?

(1) NEVER 

(2) SOMETIMES

(3) USUALLY

(4) ALWAYS

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 125 

Section 11: Additional Demographics

Subdomain 1: Race and ethnicity of child

K11Q01_INTRO Now I have a few more general questions about [S.C.] and your household. 

K11Q01 Is [S.C.] of Hispanic, Latino or Spanishorigin?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

HISPANIC OR LATINO INCLUDES MEXICAN, MEXICAN-AMERICAN, CENTRAL 

AMERICAN, SOUTH AMERICAN OR PUERTO RICAN, CUBAN, OR OTHER SPANISHCARIBBEAN.

K11Q02 Now, I'm going to read a list of categories. Please choose one or more of the following categories

to describe [S.C.]’s race. Is [S.C.] White, Black or African American, American Indian, Alaska 

Native, Asian, or Native Hawaiian or other Pacific Islander? [Mark all thatapply] 

(1) WHITE / CAUCASIAN

(2) BLACK/AFRICAN-AMERICAN

(3) AMERICAN INDIAN / NATIVEAMERICAN

(4) ALASKA NATIVE

(5) ASIAN

(6) NATIVE HAWAIIAN

(7) PACIFIC ISLANDER

(8) OTHER [RECORD VERBATIM RESPONSE ATK11Q02_OS]

(96) DON’T KNOW

(97) REFUSED 

INTERVIEWER INSTRUCTION: BE SURE TO READ THE ENTIRE QUESTION AS 

WRITTEN, INCLUDING ALL RESPONSE CATEGORIES. RACE INFORMATION IS 

COLLECTED BY SELF-IDENTIFICATION. IT IS “WHATEVER RACE YOU CONSIDER 

YOURSELF TO BE.” DO NOT TRY TO EXPLAIN OR DEFINE ANY OF THE GROUPS. 

MULTIPLE RACES MAY BE SELECTED.

SKIP TO K11Q20 IF CHILD IS NOT AMERICAN INDIAN OR ALASKA NATIVE.

K11Q02_OS RECORD VERBATIM RESPONSE

INTERVIEWER NOTE: IF RESPONDENT SAYS "INDIAN" PLEASE PROBE, "Do you mean

Asian Indian or American Indian"?

INTERVIEWER NOTE: IF RESPONDENT SAYS "EUROPEAN" PLEASE PROBE, "Can you

be more specific"?

K11Q03 IF NOT A VIRGIN ISLAND CASE AND (K11Q02 = 03 OR K11Q02 = 04) 

THEN ASK K11Q03. ELSE, SKIP TO K11Q20.

At any time during the past 12 months, did [S.C.] receive services from any Indian Health Service 

hospital or clinic?
Page 126  Series 1, No. 59 

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED
Series 1, No. 59  Page 127 

Subdomain 2: Education of parents

K11Q20 IF HOUSEHOLD INCLUDES A MOTHER (C10Q02A=1-5 OR C10Q02B=1-5) ASKK11Q20.

ELSE, SKIP TO K11Q21.

IF C10Q02A=1-5, FILL “you have”. ELSE, FILL “[S.C.]’s [MOTHER TYPE] has”

What is the highest grade or year of school [you have / [S.C.]’s [MOTHER TYPE] has 

completed?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) 8th GRADE OR LESS 

(2) 9th-12th GRADE NO DIPLOMA

(3) HIGH SCHOOL GRADUATE OR GED COMPLETED 

(4) COMPLETED A VOCATIONAL, TRADE, OR BUSINESS SCHOOL PROGRAM

(5) SOME COLLEGE CREDIT BUT NO DEGREE

(6) ASSOCIATE DEGREE (AA, AS)

(7) BACHELOR’S DEGREE (BA, BS, AB)

(8) MASTER’S DEGREE (MA, MS, MSW,MBA)

(9) DOCTORATE (PhD, EdD) or PROFESSIONAL DEGREE (MD, DDS, DVM,JD)

(96) DON’T KNOW

(97) REFUSED

K11Q21 IF K11Q20 NOT BLANK AND C10Q02A=6-10, ASK: “And how aboutyou?”

READ AS NECESSARY: “What is the highest grade or year of school you have completed?”

IF K11Q20 NOT BLANK AND (C10Q02A NE 6-10) ASK: “And how about [S.C.]’s [FATHER 

TYPE]?” 

READ AS NECESSARY: “What is the highest grade or year of school [S.C.]’s [FATHER TYPE] 

has completed?”

IF K11Q20 IS BLANK AND C10Q02A=6-10 ASK: “What is the highest grade or year of school 

you have completed?”

IF K11Q20 IS BLANK AND (C10Q02A NE 6-10), ASK: “What is the highest grade or year of 

school [S.C.]’s [FATHER TYPE] has completed?”

If K11Q20 filled from NIS and C10Q02A=6-10, Ask : "What is the highest grade or year of 

school you have completed?"

IF K11Q20 FILLED FROM NIS OR TEEN AND (C10Q02A NE 6-10), ASK: "What is the

highest grade or year of school [S.C.]'s [FATHER TYPE] has completed?"

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) 8th GRADE OR LESS 

(2) 9th-12th GRADE NO DIPLOMA

(3) HIGH SCHOOL GRADUATE OR GED COMPLETED 

(4) COMPLETED A VOCATIONAL, TRADE, OR BUSINESS SCHOOLPROGRAM

(5) SOME COLLEGE CREDIT BUT NO DEGREE

(6) ASSOCIATE DEGREE (AA, AS)
Page 128  Series 1, No. 59 

(7) BACHELOR’S DEGREE (BA, BS, AB)

(8) MASTER’S DEGREE (MA, MS, MSW,MBA)

(9) DOCTORATE (PhD, EdD) or PROFESSIONAL DEGREE (MD, DDS, DVM,JD)

(96) DON’T KNOW

(97) REFUSED

K11Q22 IF R IS NOT MOTHER OR FATHER (C10Q02A NE 1-10) ASK K11Q22. ELSESKIP TO

K11Q22A.

IF K11Q20 IS NOT BLANK and not filled from NIS or Teen, OR K11Q21 IS NOT BLANK, 

ASK: "And how about you"?

READ AS NECESSARY: "What is the highest grade or year of school you have completed"?

IF K11Q20 AND K11Q21 ARE BLANK, OR K11Q20 filled from NIS or TEEN AND K11Q21 is

blank, ASK: "What is the highest grade or year of school you have completed"?

READ AS NECESSARY: “What is the highest grade or year of school you have completed?”

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[TEXTFILL: answer from C10Q02A (see TEXTFILL logic)] LIVING IN THIS HOUSE.

(1) 8th GRADE OR LESS 

(2) 9th-12th GRADE NO DIPLOMA

(3) HIGH SCHOOL GRADUATE OR GED COMPLETED 

(4) COMPLETED A VOCATIONAL, TRADE, OR BUSINESS SCHOOLPROGRAM

(5) SOME COLLEGE CREDIT BUT NO DEGREE

(6) ASSOCIATE DEGREE (AA, AS)

(7) BACHELOR’S DEGREE (BA, BS, AB)

(8) MASTER’S DEGREE (MA, MS, MSW,MBA)

(9) DOCTORATE (PhD, EdD) or PROFESSIONAL DEGREE (MD, DDS, DVM,JD)

(96) DON’T KNOW

(97) REFUSED

K11Q22A Thinking back to who you lived with when you were about 13 years old, what wasthe highest

grade or year of school completed by your mother, father, or main guardian? If you lived with 

more than one parent or guardian, please tell me about the one who had the most education.

(1) 8th GRADE OR LESS 

(2) 9th-12th GRADE NO DIPLOMA

(3) HIGH SCHOOL GRADUATE OR GED COMPLETED 

(4) COMPLETED A VOCATIONAL, TRADE, OR BUSINESS SCHOOLPROGRAM

(5) SOME COLLEGE CREDIT BUT NO DEGREE

(6) ASSOCIATE DEGREE (AA, AS)

(7) BACHELOR’S DEGREE (BA, BS, AB)

(8) MASTER’S DEGREE (MA, MS, MSW, MBA)

(9) DOCTORATE (PhD, EdD) or PROFESSIONAL DEGREE (MD, DDS, DVM,JD)

(96) DON’T KNOW

(97) REFUSED

Subdomain 3: Birthplace of child and parents

K11Q30 IF C10Q02A=1-5, FILL “Were you”. ELSE, FILL “Was [S.C.]’s [MOTHER TYPE] ” 

[Were you / Was [S.C.]’s [MOTHER TYPE]] born in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?
Series 1, No. 59  Page 129 

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q31 IF K11Q30 NOT BLANK AND C10Q02A=6-10 ASK: “And how aboutyou?”

READ AS NECESSARY: “Were you born in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?”

IF K11Q30 NOT BLANK AND (C10Q02A NE 6-10), ASK: “And how about [S.C.]’s [FATHER 

TYPE]?” 

READ AS NECESSARY: “Was [S.C.]’s [FATHER TYPE] born in the United States [IF IAP=095 

DISPLAY, “including the Virgin Islands”]?”

IF K11Q30 IS BLANK AND C10Q02A=6-10, ASK: “Were you born in the United States [IF 

IAP=095 DISPLAY, “including the Virgin Islands”]?”

IF K11Q30 IS BLANK AND (C10Q02A NE 6-10), ASK: “Was [S.C.]’s [FATHER TYPE] born

in the United States [IF IAP=095 DISPLAY, “including the Virgin Islands”]?”

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q32 IF K11Q30 OR K11Q31 ARE NOT BLANK, ASK: “And how aboutyou?” 

READ AS NECESSARY: “Were you born in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?”

IF K11Q30 AND K11Q31 ARE BLANK, ASK: “Were you born in the United States [IF 

IAP=095 DISPLAY, “including the Virgin Islands”]?”

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[TEXTFILL: answer from C10Q02A (see TEXTFILL logic)] LIVING IN THIS HOUSE.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q33 And how about [S.C.]?

READ AS NECESSARY: Was [S.C.] born in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?

(1) YES 

(0) NO
Page 130  Series 1, No. 59 

(6) DON’T KNOW

(7) REFUSED

K11Q34A IF C10Q02A=1-5, FILL “have you”. ELSE, FILL “has [S.C.]’s [MOTHER TYPE]” 

How long [have you / has [S.C.]’s [MOTHER TYPE]] been in the United States [IF IAP=095 

DISPLAY, “including the Virgin Islands”]?

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

MOTHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

RECORD LENGTH OF TIME IN DAYS OR WEEKS OR MONTHS OR YEARS / 

(96) DON’T KNOW

(97) REFUSED

K11Q35A IF K11Q34A NOT BLANK AND C10Q02A=6-10 ASK: “And how aboutyou?”

READ AS NECESSARY: “How long have you been in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?”

IF K11Q34A NOT BLANK AND (C10Q02A NE 6-10), ASK: “And how about [S.C.]’s 

[FATHER TYPE]?”

READ AS NECESSARY: “How long has [S.C.]’s [FATHER TYPE] been in the United States [IF 

IAP=095 DISPLAY, “including the Virgin Islands”]?”

IF K11Q34A IS BLANK AND C10Q02A=6-10, ASK: “How long have you been in the United 

States [IF IAP=095 DISPLAY, “including the Virgin Islands”]?”

IF K11Q34A IS BLANK AND (C10Q02A NE 6-10) ASK: “How long has [S.C.]’s [FATHER

TYPE] been in the United States [IF IAP=095 DISPLAY, “including the Virgin Islands”]?”

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

FATHER (BIOLOGICAL, STEP, FOSTER, ADOPTIVE) LIVING IN THIS HOUSE.

RECORD LENGTH OF TIME IN DAYS OR WEEKS OR MONTHS OR YEARS / 

(96) DON’T KNOW

(97) REFUSED

K11Q36A IF K11Q34A OR K11Q35A ARE NOT BLANK, ASK: “And how aboutyou?”

READ AS NECESSARY: “How long have you been in the United States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]?”

IF K11Q34A AND K11Q35A ARE BLANK, ASK: “How long have you been in the United 

States [IF IAP=095 DISPLAY, “including the Virgin Islands”]?”

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[TEXTFILL: answer from C10Q02A (see TEXTFILL logic)] LIVING IN THIS HOUSE.

RECORD LENGTH OF TIME IN DAYS OR WEEKS OR MONTHS OR YEARS / 

(96) DON’T KNOW

(97) REFUSED

K11Q37A IF K11Q33 = 2, ASK K11Q37A. ELSE SKIP TOK11Q40
Series 1, No. 59  Page 131 

IF K11Q34A, K11Q35A, OR K11Q36A ARE NOT BLANK, ASK: “And how about [S.C.]?”

READ AS NECESSARY: “How long has [S.C.] been in the United States [IF IAP=095 

DISPLAY, “including the Virgin Islands”]?”

IF K11Q34A, K11Q35A, AND K11Q36A ARE BLANK, ASK: “How long has [S.C.] been in the

United States [IF IAP=095 DISPLAY, “including the Virgin Islands”]?”

RECORD LENGTH OF TIME IN DAYS OR WEEKS OR MONTHS OR YEARS / 

(96) DON’T KNOW

(97) REFUSED

K11Q38 IF ANY BIOLOGICAL MOTHER OR BIOLOGICAL FATHER IN HOUSEHOLD,SKIP TO

K11Q43. IF NO BIOLOGICAL PARENT IN HOUSEHOLD AND IF ANY ADOPTIVE PARENT 

OR GUARDIAN IN HOUSEHOLD, ASK K11Q38. ELSE, SKIP TOK11Q43.

Was [S.C.] adopted from another country?

[IF IAP=095 DISPLAY: HELP TEXT: IF S.C. WAS ADOPTED FROM THE UNITED 

STATES, CODE THIS QUESTION AS ‘NO’. THE VIRGIN ISLANDS ARE 

CONSIDERED PART OF THE UNITED STATES.]

(1) YES [SKIP TO K11Q41]

(0) NO

(6) DON’T KNOW

(7) REFUSED 
Page 132  Series 1, No. 59 

Subdomain 4: Residential mobility

K11Q40 IF ANY BIOLOGICAL MOTHER OR BIOLOGICAL FATHER IN HOUSEHOLD,SKIP TO

K11Q43. IF NO BIOLOGICAL PARENT IN HOUSEHOLD AND IF ANY ADOPTIVE PARENT 

OR GUARDIAN IN HOUSEHOLD, ASK K11Q40. ELSE, SKIP TOK11Q43.

Prior to being adopted, was [S.C.] in the legal custody of a state or county child welfare agency in 

the United States [IF IAP=095 DISPLAY, “including the Virgin Islands”]? That is, was [S.C.] in 

the U.S. [IF IAP=095 DISPLAY “or Virgin Islands”] foster care system?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q41 Has [S.C.]’s adoption been finalized?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q43 [IF CHILD WAS ADOPTED, INSERT: Since [he/she]was adopted,] 

How many times has [S.C.] ever moved to a newaddress?

RECORD NUMBER OF MOVES /

(996) DON’T KNOW

(997) REFUSED

READ IF NECESSARY: Please include any and all times a child has changed their primary 

residence. Do not include temporary changes in residence such as a child visiting another 

residence during summer vacation or other breaks in the school year.
Series 1, No. 59  Page 133 

Subdomain 5: Employment and income

K11Q50 Was anyone in the household employed at least 50 weeks out of the past 52weeks?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

C10Q41 Do you own or rent your home?

HELP SCREEN: IF THE HOME IS OWNED OR BEING BOUGHT BY SOMEONE IN THE 

HOUSEHOLD, THE ANSWER SHOULD BE MARKED AS “OWNED.” IF THE HOME IS 

NOT OWNED BY SOMEONE IN THE HOUSEHOLD AND IS BEING OCCUPIED 

WITHOUT PAYMENT OF RENT, THE ANSWER SHOULD BE MARKED AS “SOME 

OTHER ARRANGEMENT.”

(1) OWNED OR BEING BOUGHT

(2) RENTED 

(3) SOME OTHER ARRANGEMENT

(6) DON’T KNOW

(7) REFUSED

K11Q51 Now I am going to ask you a fewquestions about your income. Please think about your total

combined family income during (FILL LAST CALENDAR YEAR) for all members of the family. 

Can you tell me that amount before taxes?

HELP SCREEN: INCLUDE MONEY FROM JOBS, CHILD SUPPORT, SOCIAL SECURITY, 

RETIREMENT INCOME, UNEMPLOYMENT PAYMENTS, PUBLIC ASSISTANCE, AND 

SO FORTH. ALSO, INCLUDE INCOME FROM INTEREST, DIVIDENDS, NET INCOME 

FROM BUSINESS, FARM, OR RENT, AND ANY OTHER MONEY INCOME RECEIVED.

RECORD INCOME AMOUNT /

(6) DON'T KNOW

(7) REFUSED [SKIP TO K11Q52 IF DK/RF]

K11Q52 For the purposes of this survey, it is important to get at least a range for the totalincome received 

by all members of your household in [LAST CALENDAR YEAR]. Would you say that the total 

combined family income, before taxes, was above or below$20,000?

(1) MORE THAN $20,000 [SKIP TO K11Q56] 

(2) $20,000 [SKIP TO K11Q60]

(3) LESS THAN $20,000 [SKIP TO K11Q53]

(6) DON'T KNOW [SKIP TO K11Q60]

(7) REFUSED [SKIP TO K11Q60] 

K11Q53 Was the total combined family income more or less than $10,000?

(1) MORE THAN $10,000 [SKIP TO K11Q55]

(2) $10,000 [SKIP TO K11Q60]

(3) LESS THAN $10,000 [SKIP TO K11Q54]

(6) DON'T KNOW [SKIP TO K11Q60]

K11Q54

(7) REFUSED

Was it more than $7,500?

[SKIP TO K11Q60]
Page 134  Series 1, No. 59 

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q55 Was it more than $15,000?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q55A] 

[SKIP TO K11Q55B] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q55A Was it more than $17,500?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q55B Was it more than $12,500?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q56 Was it more or less than $40,000?

(1) MORE THAN $40,000 

(2) $40,000

(3) LESS THAN $40,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q56A] 

[SKIP TO K11Q60] 

[SKIP TO K11Q57] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q56A More or less than $60,000?

(1) MORE THAN $60,000 

(2) $60,000

(3) LESS THAN $60,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q58] 

[SKIP TO K11Q60] 

[SKIP TO K11Q56B] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q56B More or less than $50,000?

(1) MORE THAN $50,000 

(2) $50,000

(3) LESS THAN $50,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q56C] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q56C More or less than $45,000?

(1) MORE THAN $45,000 

(2) $45,000

(3) LESS THAN $45,000

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q59]
Series 1, No. 59  Page 135 

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q57 More or less than $30,000?

(1) MORE THAN $30,000 

(2) $30,000

(3) LESS THAN $30,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q57A] 

[SKIP TO K11Q60] 

[SKIP TO K11Q57B] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q57A More or less than $35,000?

(1) MORE THAN $35,000 

(2) $35,000

(3) LESS THAN $35,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q57B More or less than $25,000?

(1) MORE THAN $25,000 

(2) $25,000

(3) LESS THAN $25,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q58 More or less than $75,000?

(1) MORE THAN $75,000 

(2) $75,000

(3) LESS THAN $75,000

(6) DON'T KNOW

(7) REFUSED

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q59] 

[SKIP TO K11Q60] 

[SKIP TO K11Q60]

K11Q59 IF NIS OR TEEN INTERVIEW INCOME SECTION COMPLETED, SKIP TOK11Q60

ELSE READ: Was the total combined family income more or less than [$REF]? 

[$REF IS BASED ON A POVERTY REFERENCE TABLE]

(1) MORE THAN [$REF]

(2) EXACTLY [$REF]

(3) LESS THAN [$REF]

(6) DON'T KNOW

(7) REFUSED 

SKIP TO K11Q60 IF ANSWER IS EXACTLY/LESS THAN/DK/RF OR IF THERE WAS ONLY 

ONE VALUE IN THE POVERTY REFERENCE TABLE.
Page 136  Series 1, No. 59 

K11Q59A Would you say this income was MORE or LESS than[$REF]?

(1) MORE THAN [$REF]

(2) EXACTLY [$REF]

(3) LESS THAN [$REF]

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 137 

Subdomain 6: Program participation

CATI INSTRUCTION: Calculate household poverty level from household size and reported income, or from the 

income cascade.

SKIP TO SECTION 12 IF HOUSEHOLD POVERTY LEVEL > 300%

K11Q60 At any time during the past 12 months, even for one month, did anyone in this household receive 

any cash assistance from a state or county welfare program, such as [STATE TANFNAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state or county welfare programs that are specific to the 

state in which you live.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

K11Q61 IF S_UNDR18 > 1, FILL “any child in the household”. ELSE, FILL[S.C.].

During the past 12 months, did [[S.C.]/ any child in the household] receive Food Stamps or 

Supplemental Nutrition Assistance Program benefits?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

SKIP TO S9Q34 IF ONLY ONE CHILD IN HOUSEHOLD AND AGE < 24 MONTHS.

K11Q62 During the past 12 months, did [[S.C.]/any child in the household] receive freeor reduced-cost

breakfasts or lunches atschool?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

S9Q34 Does anyone who lives in the household currently receive benefits from the Women, Infants, and 

Children (WIC) Program?

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED 
Page 138  Series 1, No. 59 

Section 12: Additional Health Insurance Questions

SKIP TO NEXT SECTION IF CHILD IS INSURED (K3Q01 = YES), IF INSURANCE STATUS IS UNKNOWN 

(K3Q01 IS DK/RF AND K3Q02 IS NO/DK/RF), OR IF INCOME IS 400% OF FPL OR GREATER.

INTERVIEWER TRAINING NOTE: Throughout this section, the lists of answer choices should not be read to the 

respondent. Individual answer choices may be repeated back to the respondent if confirming the respondent’s 

answer. It is important that a concerted effort is made to find the appropriate answer for each question. Too many 

“Other” responses will make it difficult to analyze the data.

INTERVIEWER NOTE: PLEASE USE “OTHER” RESPONSE OPTIONS RARELY IN THIS SECTION. 

PROMPT RESPONDENT TO FIND AN APPROPRIATE ANSWER FOR EACH QUESTION. YOU MAY 

REPEAT RESPONSE OPTIONS BACK TO RESPONDENT IF YOU ARE CONFIRMING THE 

RESPONDENT’S ANSWER.

Subdomain 1: Reasons for Uninsurance

K12Q01 Earlier, you told me that [S.C.] does not have health insurance. What is the mainreason [S.C.] 

does not have health insurance now?

COST

(01) COSTS TOO MUCH

(02) HEALTH INSURANCE NOT WORTH THE MONEY ITCOSTS

EMPLOYMENT/MOVING

(03) NO ONE IN FAMILY CURRENTLY EMPLOYED / JOB WASLOST

(04) CAN’T GET INSURANCE THROUGH EMPLOYER 

(05) CHANGING JOBS OR INSURANCEPOLICIES

(06) MOVING BETWEEN STATES ORREGIONS

ELIGIBILITY

(07) INSURANCE COMPANY REFUSED TO COVER / PREEXISTINGCONDITION

(08) INSURANCE COMPANY TERMINATED COVERAGE / RULEVIOLATION

(09) INCOME TOO HIGH FOR PUBLICPROGRAM

(10) AGE / CHILD IS TOO OLD OR TOO YOUNG TO BE ELIGIBLE 

(11) CANNOT MEET RESIDENCY/CITIZENSHIP REQUIREMENTS, LACK OFSSN

(12) INELIGIBLE DUE TO OTHER PROGRAMREQUIREMENT

APPLICATION PROCESS

(13) DID NOT REAPPLY WHEN COVERAGE ENDED

(14) ISSUES WITH THE APPLICATION ORPAPERWORK

IN TRANSITION BETWEEN COVERAGE

(15) HAVE APPLIED – NOW JUST WAITING

(16) INTEND TO APPLY BUT JUST HAVEN’T DONE SO

(17) DON'T KNOW HOW TO GET INSURANCE

OTHER

(18) CHILD DOES NOT NEED INSURANCE / DOES NOT GETSICK

(19) OTHER PARENT’S RESPONSIBILITY, LACK OF LEGALCUSTODY

(20) OTHER [RECORD VERBATIM RESPONSE]

(96) DON’T KNOW

(97) REFUSED
Series 1, No. 59  Page 139 

K12Q02 About how long has it been since [S.C.] last had any kind of health insurance?

(1) SIX MONTHS OR LESS

(2) MORE THAN 6 MONTHS, BUT NOT MORE THAN 1 YEARAGO

(3) MORE THAN 1 YEAR, BUT NOT MORE THAN 3 YEARS AGO

(4) MORE THAN 3 YEARS

(5) NEVER [SKIP TO K12Q11]

(6) DON’T KNOW

(7) REFUSED

K12Q03 Has [S.C.] ever been covered by health insurance that was provided through anemployer or 

union?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K12Q04 Has [S.C.] ever been covered by health insurance that was purchased directly froman insurance 

company?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

Subdomain 2: History with Medicaid

K12Q11 Before today, had you ever heard of Medicaid [or STATE MEDICAIDNAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid program specific to the state in which you 

live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q21. 

K12Q12 Has [S.C.] ever been enrolled in Medicaid [or STATE MEDICAIDNAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid program specific to the state in which you 

live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q15. 
Page 140  Series 1, No. 59 

K12Q13 When was the last time that [S.C.] was enrolled in Medicaid [or STATE MEDICAIDNAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid program specific to the state in which you 

live.

RECORD DATE 

(95) RECORD LENGTH OF TIME (MONTHS OR YEARS) [SKIP TO K12Q13_1]

(96) DON’T KNOW

(97) REFUSED

K12Q14 What is the main reason that [S.C.]’s enrollment ended?

COST

(01) COST TOO MUCH

(02) FORGOT TO PAY THE PREMIUM

ELIGIBILITY

(03) MOVING BETWEEN STATES ORREGIONS

(04) INSURANCE TERMINATED BY INSURER / RULE VIOLATION

(05) CHILD BECAME TOO OLD TO BE ELIGIBLE

(06) FINANCIAL SITUATION CHANGED / NO LONGER QUALIFIED FOR MEDICAID

(07) CHILD OBTAINED OTHER INSURANCE: CHIP / OTHERPUBLIC

(08) CHILD OBTAINED OTHER INSURANCE: EMPLOYER / UNION /PRIVATE

APPLICATION PROCESS

(09) DID NOT REAPPLY WHEN COVERAGE ENDED

(10) ISSUES WITH PAPERWORK

PROBLEMS WITH SERVICE OR AVAILABILITY

(11) DID NOT LIKE THE DOCTORS / MEDICAL STAFF / CLINICS / QUALITY OFCARE 

WHERE CHILD RECEIVED SERVICES 

(12) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE 

WHEN NEEDED

(13) COULD NOT FIND DOCTORS WHO WOULD ACCEPTMEDICAID

OTHER

(14) CHILD DOES NOT NEED INSURANCE / DOES NOT GETSICK 

(15) OTHER [SKIP TO K12Q14_OTHER]

(96) DON’T KNOW

(97) REFUSED

ALL EXCEPT 15 SKIP TO K12Q21.
Series 1, No. 59  Page 141 

K12Q15 Have you ever applied for Medicaid [or STATE MEDICAID NAME] for[S.C.]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid program specific to the state in which you 

live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q21. 

K12Q16 When was the last time that you applied?

RECORD DATE 

(95) RECORD LENGTH OF TIME (MONTHS OR YEARS) [SKIP TO K12Q16_1]

(96) DON’T KNOW

(97) REFUSED

K12Q17 What is the main reason that you were unable to enroll [S.C.] in Medicaid [or STATE

NAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid program specific to the state in which 

you live.

COST

(01) EARNED TOO MUCH MONEY

ELIGIBILITY

(02) ASSETS/RESOURCES TOO HIGH

(03) CHILD WAS TOO OLD 

(04) CHILD NEEDED TO BE UNINSURED FOR LONGER PERIOD OF TIME TOQUALIFY

(05) CHILD DID NOT MEET RESIDENCY OR CITIZENSHIP REQUIREMENTS 

(06) CHILD WAS ALREADY INSURED BY OTHERINSURANCE

APPLICATION PROCESS

(07) DID NOT PROVIDE ALL PAPERWORK / DOCUMENTS NEEDED

OTHER

(08) CHILD QUALIFIED FOR CHIP INSTEAD OFMEDICAID

(09) APPLICATION RECENTLY SUBMITTED / NOW JUSTWAITING

(10) OTHER [SKIP TO K12Q17_OTHER] 

(96) DON’T KNOW

(97) REFUSED 
Page 142  Series 1, No. 59 

Subdomain 3: History with CHIP 

SKIP TO NEXT SUBDOMAIN (K12Q30) IF STATE USES THE SAME OR SUBSTANTIALLY THE SAME NAME 

FOR THEIR MEDICAID AND CHIP PROGRAMS.

K12Q21 Before today, had you ever heard of [STATE CHIP NAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state-sponsored Children's Health Insurance Program 

specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED 

IF 0,6,7 SKIP TO K12Q30.

K12Q22 Has [S.C.] ever been enrolled in [STATE CHIP NAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state-sponsored Children's Health Insurance Program 

specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q25.

K12Q23 When was the last time that [S.C.] was enrolled in [STATE CHIP NAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state-sponsored Children's Health Insurance Program 

specific to the state in which you live.

RECORD DATE 

(95) RECORD LENGTH OF TIME (MONTHS OR YEARS) [SKIP TO K12Q23_1]

(96) DON’T KNOW

(97) REFUSED

K12Q24 What is the main reason that [S.C.]’s enrollment ended?

COST

(01) COST TOO MUCH

(02) FORGOT TO PAY THE PREMIUM

ELIGIBLITY

(03) MOVING BETWEEN STATES ORREGIONS

(04) INSURANCE TERMINATED BY INSURER / RULEVIOLATION

(05) CHILD BECAME TOO OLD TO BE ELIGIBLE

(06) FINANCIAL SITUATION CHANGED / NO LONGER QUALIFIED FORCHIP

(07) CHILD OBTAINED OTHER INSURANCE: MEDICAID / OTHERPUBLIC
Series 1, No. 59  Page 143 

(08) CHILD OBTAINED OTHER INSURANCE: EMPLOYER / UNION /PRIVATE

APPLICATION PROCESS

(09) DID NOT REAPPLY WHEN COVERAGE ENDED

(10) ISSUES WITH PAPERWORK

PROBLEMS WITH SERVICE OR AVAILABILITY

(11) DID NOT LIKE THE DOCTORS / MEDICAL STAFF / CLINICS / QUALITY OFCARE 

WHERE CHILD RECEIVED SERVICES 

(12) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE 

WHEN NEEDED 

(13) COULD NOT FIND DOCTORS WHO WOULD ACCEPTCHIP

OTHER

(14) CHILD DOES NOT NEED INSURANCE / DOES NOT GETSICK

(15) OTHER [SKIP TO K12Q24_OTHER]

(96) DON’T KNOW

(97) REFUSED

SKIP TO K12Q30.

K12Q25 Have you ever applied for [STATE CHIP NAME] for[S.C.]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state-sponsored Children's Health Insurance Program 

specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q30. 

K12Q26 When was the last time that you applied?

RECORD DATE 

(95) RECORD LENGTH OF TIME (MONTHS OR YEARS) [SKIP TO K12Q26_1]

(96) DON’T KNOW

(97) REFUSED

K12Q27 What is the main reason that you were unable to enroll [S.C.] in [STATE CHIPNAME]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the state-sponsored Children's Health Insurance Program 

specific to the state in which you live.

COST

(01) EARNED TOO MUCH MONEY

ELIGIBILITY

(02) ASSETS/RESOURCES TOO HIGH

(03) CHILD WAS TOO OLD 

(04) CHILD NEEDED TO BE UNINSURED FOR LONGER PERIOD OF TIME TOQUALIFY

(05) CHILD DID NOT MEET RESIDENCY OR CITIZENSHIP REQUIREMENTS 

(06) CHILD WAS ALREADY INSURED BY OTHERINSURANCE
Page 144  Series 1, No. 59 

APPLICATION PROCESS

(07) DID NOT PROVIDE ALL PAPERWORK / DOCUMENTS NEEDED

OTHER

(08) CHILD QUALIFIED FOR MEDICAID INSTEAD OFCHIP

(09) APPLICATION RECENTLY SUBMITTED / NOW JUSTWAITING

(10) OTHER [RECORD VERBATIM RESPONSE]

(96) DON’T KNOW

(97) REFUSED
Series 1, No. 59  Page 145 

Subdomain 4: Interest in Enrolling inMedicaid/CHIP

SKIP TO NEXT SUBDOMAIN (K12Q40) IF K12Q11 = NO/DK/RF AND K12Q21 = NO/DK/RF/MISSING. 

FOR PROGRAM FILLS IN THIS SUBDOMAIN,

● IF K12Q11 = YES AND K12Q21 = NO/DK/RF/MISSING, USE: Medicaid [or STATE MEDICAID

NAME]

● IF K12Q11 = NO/DK/RF AND K12Q21 = YES, USE: [STATE CHIPNAME]

● IF K12Q11 = YES AND K12Q21 = YES, USE: Medicaid [or STATEMEDICAID NAME] or [CHIP 

NAME]

K12Q30 If you wanted to get more information about [PROGRAM], do you know where to go to get 

that information?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health 

Insurance Program specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K12Q31 If you wanted to enroll [S.C.] in [PROGRAM], do you know how to dothat?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health 

Insurance Program specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K12Q32 IF K12Q11=0,6,7 THEN SKIP TO K12Q33. 

IF K12Q12=1 THEN ASK: Based on what you know about Medicaid [or STATE 

MEDICAID NAME], how easy or difficult do you think it is to re-enroll? Would you say 

very easy, somewhat easy, somewhat difficult, or very difficult?

ELSE ASK: Based on what you know about Medicaid [or STATE MEDICAID NAME], 

how easy or difficult do you think it is to complete an application? Would you say very easy, 

somewhat easy, somewhat difficult, or very difficult?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid program specific to the state in which 

you live.

(1) VERY EASY

(2) SOMEWHAT EASY

(3) SOMEWHAT DIFFICULT

(4) VERY DIFFICULT

(6) DON'T KNOW

(7) REFUSED 
Page 146  Series 1, No. 59 

K12Q33 SKIP TO K11Q34 IF RESPONDENT HAS NEVER HEARD OF CHIP(K12Q21=0,6,7) OR 

IF STATE USES THE SAME OR SUBSTANTIALLY THE SAME NAME FOR THEIR 

MEDICAID AND CHIP PROGRAMS (CATEGORY "C" IN MEDICAID TABLE) 

IF K12Q22=1 THEN ASK: Based on what you know about [STATE CHIP NAME], how 

easy or difficult do you think it is to re-enroll? Would you say very easy, somewhat easy, 

somewhat difficult, or very difficult?

ELSEASK: Based on what you know about [STATE CHIP NAME], how easy or difficult do 

you think it is to complete an application? Would you say very easy, somewhat easy, 

somewhat difficult, or very difficult?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the state-sponsored Children's Health Insurance 

Program specific to the state in which you live.

(1) VERY EASY

(2) SOMEWHAT EASY

(3) SOMEWHAT DIFFICULT

(4) VERY DIFFICULT

(6) DON'T KNOW

(7) REFUSED

K12Q34 Based on what you knowabout [PROGRAM], do you think [S.C.] is eligible now?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health 

Insurance Program specific to the state in which you live.

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

K12Q35 If you were told that [S.C.] was eligible for [PROGRAM], would you wantto enroll 

[him/her]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED

IN THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health 

Insurance Program specific to the state in which you live.

(1) YES 

(0) NO [SKIP TO K12Q36]

(6) DON'T KNOW

(7) REFUSED

IF K12Q35 = YES AND K12Q34 = YES, THEN SKIP TO K12Q37. 

IF K12Q35 = YES AND K12Q34 = NO, THEN SKIP TO K12Q38.

IF K12Q35 = 6,7 OR IF (K12Q35 = 1 AND K12Q34 = 6,7), THEN SKIP TO K12Q40.

K12Q36 What is the main reason you would NOT want to enroll[S.C.]?

COST

(01) COSTS TOO MUCH
Series 1, No. 59  Page 147 

APPLICATION PROCESS

(02) APPLICATION PROCESS TOO DIFFICULT, TAKES TOO MUCHTIME

(03) DON’T WANT TO MEET PROGRAM APPLICATION REQUIREMENTS 

(04) DON’T LIKE PEOPLE AT APPLICATION OFFICE

(05) WORRIES ABOUT CITIZENSHIP

NEGATIVE VIEWS OF PROGRAM

(06) DON’T ACCEPT WELFARE, DON’T WANT TO BE IN PUBLICPROGRAM

(07) HEARD BAD THINGS ABOUT PROGRAM

(08) DO NOT LIKE THE DOCTORS / MEDICAL STAFF / CLINICS WHERE CHILD 

WOULD RECEIVE SERVICES 

(09) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE 

WHEN NEEDED

OTHER

(10) CHILD DOES NOT NEED INSURANCE / DOES NOT GETSICK

(11) EXPECT TO HAVE INSURANCE FROM ANOTHER SOURCESOON

(12) OTHER [SKIP TO K12Q36_OTHER]

(96) DON’T KNOW

(97) REFUSED

ALL EXCEPT 12 SKIP TO K12Q40.

K12Q37 What is the main reason [S.C.] is not enrolled in [PROGRAM]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health Insurance 

Program specific to the state in which you live.

COST

(01) COSTS TOO MUCH

ELIGIBILITY

(02) MOVING BETWEEN STATES ORREGIONS

(03) INELIGIBLE DUE TO INCOME TOO HIGH FOR PUBLICPROGRAM

(04) INELIGIBLE DUE TO AGE

(05) INELIGIBLE DUE TO RESIDENCY, CITIZENSHIP, OR LACK OFSSN

(06) INELIGIBLE DUE TO OTHER PROGRAMREQUIREMENT

APPLICATION PROCESS

(07) DON’T HAVE THE NECESSARY DOCUMENTS

(08) APPLICATION PROCESS TOO DIFFICULT, TAKES TOO MUCHTIME

(09) DON’T WANT TO MEET PROGRAM APPLICATION REQUIREMENTS 

(10) WORRIES ABOUT CITIZENSHIP

IN TRANSITION BETWEEN COVERAGE

(11) HAVE APPLIED – NOW JUST WAITING

(12) INTEND TO APPLY BUT JUST HAVEN’T DONE SO

(13) DON'T KNOW WHERE OR HOW TO APPLY
Page 148  Series 1, No. 59 

OTHER

(14) CHILD DOES NOT NEED INSURANCE / DOES NOT GETSICK

(15) OTHER [SKIP TO K12Q37]

(96) DON’T KNOW

(97) REFUSED

ALL EXCEPT 08 SKIP TO K12Q40.

K12Q38 What is the main reason that you think [S.C.] is not eligible for [PROGRAM]?

READ IF R MENTIONS THAT HE/SHE DOES NOT LIVE IN THE STATE MENTIONED IN

THE QUESTION: Please think about the Medicaid or state-sponsored Children's Health Insurance 

Program specific to the state in which you live.

INCOME

(01) EARN TOO MUCH MONEY

(02) ASSETS/RESOURCES TOO HIGH

ELIGIBILITY

(03) CHILD IS TOO OLD

(04) CHILD NEEDS TO BE UNINSURED FOR LONGER PERIOD OF TIME TOQUALIFY

(05) CHILD DOES NOT MEET RESIDENCY OR CITIZENSHIPREQUIREMENTS

(06) CHILD IS ALREADY INSURED BY OTHERINSURANCE

OTHER

(07) CANNOT OR WILL NOT PROVIDE ALL PAPERWORK / DOCUMENTSNEEDED

(08) OTHER [SKIP TO K12Q38_OTHER]

(96) DON’T KNOW

(97) REFUSED

SKIP TO NEXT SUBDOMAIN (K12Q40).
Series 1, No. 59  Page 149 

Subdomain 5: Parents’ Coverage and Availability of Employer-Sponsored Insurance 

K12Q40 SKIP TO K12Q50 IF NO MOTHER-TYPE IN HOUSEHOLD ((C10Q02A NE 1-5) AND

(C10Q02B NOT EQ 1-5))

IF (C10Q02A=1-5), FILL "do you" ELSE, FILL "does S.C.’s [MOTHER TYPE]". 

At this time, [do you / does S.C.’s MOTHER TYPE] have any kind of health care coverage, 

including health insurance, prepaid plans such as HMOs, or government plans such as Medicaid or 

Medicare?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q42. 

K12Q41 IF C10Q02A=1-5, FILL "your" ELSE, FILL "her".

Is that health insurance provided through [your/her] current employer, former employer, union, or 

some other source?

(1) HER CURRENT EMPLOYER [SKIP TO K12Q43] 

(2) HER FORMER EMPLOYER 

(3) HER UNION [SKIP TO K12Q43] 

(4) SOME OTHER SOURCE

(6) DON’T KNOW

(7) REFUSED

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS THAT INSURANCE IS 

PROVIDED THROUGH MULTIPLE SOURCES, ASK WHICH SOURCE PROVIDES 

PRIMARY COVERAGE FOR BOTH DOCTOR VISITS AND HOSPITAL STAYS.

K12Q42 IF (C10Q02A=1-5), FILL "are you" ELSE, FILL "does [S.C.]’s [MOTHER TYPE]".

At this time, [are you/is S.C.’s MOTHER TYPE’s] eligible for health insurance through [your/her] 

current employer or union?

(1) YES, HER CURRENT EMPLOYER 

(2) YES, HER UNION

(3) YES, BOTH

(4) NO [SKIP TO K12Q50]

(6) DON’T KNOW

(7) REFUSED [SKIP TO K12Q50]

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS NOT BEING EMPLOYED, 

RECORD ANSWER AS NO.

K12Q43 IF K12Q41 OR K12Q42 = 1, FILL WITH “employer”

IF K12Q41 = 3 OR K12Q42 = 2, FILL WITH “union”

IF K12Q42 = 3 or 6, FILL WITH “employer or union”
Page 150  Series 1, No. 59 

Does this [employer/union/employer or union] offer health insurance that could help pay for 

doctor visits and hospital stays for [S.C.]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[MOTHER TYPE]'S EMPLOYER.

IF 0,6,7 SKIP TO K12Q46.

K12Q44 If [S.C.] was covered by insurance provided through this [employer/union/employer or union], 

would this [employer/union/employer or union] pay for all, some, or none of [his/her] health 

insurance premium?

(1) ALL 

(2) SOME

(3) NONE

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[MOTHER TYPE]'S EMPLOYER.

K12Q45 What is the main reason that [S.C.] is not covered by insurance providedthrough this

[employer/union/employer or union]?

COST

(1) COST IS TOO HIGH

(2) TRADED HEALTH INSURANCE FOR HIGHER PAY

ELIGIBILITY

(3) INSURER REFUSED TO COVER / PREEXISTINGCONDITION

(4) CHILD NOT ELIGIBLE DUE TO TYPE OF JOB

(5) CHILD NOT ELIGIBLE DUE TO NUMBER OF HOURSWORKED

(6) CHILD NOT ELIGIBLE DUE TO LENGTH OF TIME ATJOB

(7) CHILD NOT ELIGIBLE FOR SOME OTHERREASON

APPLICATION PROCESS

(8) HAVE APPLIED – NOW JUST WAITING

(9) INTEND TO APPLY BUT JUST HAVEN’T DONE SO

(10) DON'T KNOW WHERE OR HOW TO APPLY

(11) APPLICATION PROCESS TOO DIFFICULT, TAKES TOO MUCHTIME

NEGATIVE VIEWS OF PROGRAM

(12) HEARD BAD THINGS ABOUT INSURANCEPROGRAM

(13) DO NOT LIKE DOCTORS / MEDICAL STAFF / CLINIC IN HEALTHPLAN

(14) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE 

WHEN NEEDED

OTHER

(15) DOES NOT NEED INSURANCE / DOES NOT GETSICK

(16) EXPECT TO HAVE INSURANCE FROM ANOTHER SOURCESOON

(17) OTHER [SKIP TO K12Q45]
Series 1, No. 59  Page 151 

(96) DON’T KNOW

(97) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[MOTHER TYPE]'S EMPLOYER.

K12Q46 IF K12Q41 = 3 OR K12Q42 = 2, SKIP TO K12Q50. 

IF C10Q02A=1-5, FILL “your” ELSE, FILL “[S.C.]'s [MOTHER TYPE]”.

Think about all locations where [your/ S.C.’s MOTHER TYPE’s] employer operates. Would you 

say that the total number of persons who work for this employer is above or below 100?

(1) MORE THAN 100

(2) EXACTLY 100

(3) LESS THAN 100

(4) NOT EMPLOYED 

(6) DON'T KNOW

(7) REFUSED

K12Q47 ASK K12Q47 ONLY IF ANSWER TO K12Q46 IS “LESS THAN 100.” OTHERWISE,SKIP TO

K12Q50.

Is the total number of persons who work for [your/her] employer above or below 50?

(1) MORE THAN 50

(2) EXACTLY 50

(3) LESS THAN 50

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[MOTHER TYPE]'S EMPLOYER.

K12Q50 SKIP TO K12Q60 IF NO FATHER-TYPE IN HOUSEHOLD((C10Q02A NE 6-10) AND

(C10Q02B NOT EQ 6-10)

IF C10Q02A=6-10, FILL “do you”. ELSE, FILL “does [S.C.]’s [FATHER TYPE]”. 

At this time, [do you / does S.C.’s FATHER TYPE] have any kind of health care coverage, 

including health insurance, prepaid plans such as HMOs, or government plans such as Medicaid or 

Medicare?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q52.

K12Q51 IF C10Q02A=6-10, FILL “your” ELSE, FILL “does [S.C.]’s [FATHERTYPE]”. 

Is that health insurance provided through [your/his] current employer, former employer, union, or 

some other source?

(1) CURRENT EMPLOYER [SKIP TO K12Q53] 

(2) FORMER EMPLOYER 
Page 152  Series 1, No. 59 

(3) UNION [SKIP TO K12Q53] 

(4) SOME OTHER SOURCE

(6) DON’T KNOW

(7) REFUSED

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS THAT INSURANCE IS 

PROVIDED THROUGH MULTIPLE SOURCES, ASK WHICH SOURCE PROVIDES 

PRIMARY COVERAGE FOR BOTH DOCTOR VISITS AND HOSPITAL STAYS.

K12Q52 At this time, [are you/is S.C.’s FATHER TYPE’s] eligible for health insurance through

[your/his] current employer or union?

(1) YES, CURRENT EMPLOYER

(2) YES, UNION

(3) YES, BOTH

(4) NO [SKIP TO K12Q60]

(6) DON’T KNOW

(7) REFUSED [SKIP TO K12Q60]

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS NOT BEING EMPLOYED, 

RECORD ANSWER AS NO.

K12Q53 IF K12Q51 OR K12Q52 = 1, FILL WITH “employer”

IF K12Q51 = 3 OR K12Q52 = 2, FILL WITH “union”

IF K12Q52 = 3 or 6, FILL WITH “employer or union”

Does this [employer/union/employer or union] offer health insurance that could help pay for 

doctor visits and hospital stays for [S.C.]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[FATHER TYPE]'S EMPLOYER.

IF 0,6,7 SKIP TO K12Q56. 

K12Q54 If [S.C.] was covered by insurance provided through this [employer/union/employer or union], 

would this [employer/union/employer or union] pay for all, some, or none of [his/her] health 

insurance premium??

(1) ALL 

(2) SOME

(3) NONE

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[FATHER TYPE]'S EMPLOYER.

K12Q55 What is the main reason that [S.C.] is not covered by insurance providedthrough this

[employer/union/employer or union]?

COST
Series 1, No. 59  Page 153 

(01) COST IS TOO HIGH

(02) TRADED HEALTH INSURANCE FOR HIGHER PAY

ELIGIBILITY

(03) INSURER REFUSED TO COVER / PREEXISTINGCONDITION

(04) CHILD NOT ELIGIBLE DUE TO TYPE OF JOB

(05) CHILD NOT ELIGIBLE DUE TO NUMBER OF HOURSWORKED

(06) CHILD NOT ELIGIBLE DUE TO LENGTH OF TIME ATJOB

(07) CHILD NOT ELIGIBLE FOR SOME OTHERREASON

APPLICATION PROCESS

(08) HAVE APPLIED – NOW JUST WAITING

(09) INTEND TO APPLY BUT JUST HAVEN’T DONE SO

(10) DON'T KNOW WHERE OR HOW TO APPLY

(11) APPLICATION PROCESS TOO DIFFICULT, TAKES TOO MUCHTIME

NEGATIVE VIEWS OF PROGRAM

(12) HEARD BAD THINGS ABOUT INSURANCEPROGRAM

(13) DO NOT LIKE DOCTORS / MEDICAL STAFF / CLINIC IN HEALTHPLAN

(14) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE

WHEN NEEDED

OTHER

(15) DOES NOT NEED INSURANCE / DOES NOT GETSICK

(16) EXPECT TO HAVE INSURANCE FROM ANOTHER SOURCESOON

(17) OTHER [SKIP TO K12Q45]

(96) DON’T KNOW

(97) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[FATHER TYPE]'S EMPLOYER.

K12Q56 IF K12Q51 = 3 OR K12Q52 = 2, SKIP TO K12Q60.

Think about all locations where [your/ S.C.’s FATHER TYPE’s] employer operates. Would you 

say that the total number of persons who work for this employer is above or below 100?

(1) MORE THAN 100

(2) EXACTLY 100

(3) LESS THAN 100

(4) NOT EMPLOYED 

(6) DON'T KNOW

(7) REFUSED

K12Q57 ASK K12Q57 ONLY IF ANSWER TO K12Q56 IS “LESS THAN 100.” OTHERWISE,SKIP TO

K12Q60.

IF C10Q02A=6-10, FILL “do you”, ELSE, FILL “his”. 

Is the total number of persons who work for [your/his] employer above or below 50?

(1) MORE THAN 50

(2) EXACTLY 50

(3) LESS THAN 50

(6) DON'T KNOW

(7) REFUSED 
Page 154  Series 1, No. 59 

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

[FATHER TYPE]'S EMPLOYER.

K12Q60 SKIP TO CPC11Q14 IF RESPONDENT IS MOTHER OR FATHER(C10Q02A=1-10).

QUESTIONS ABOUT THE RESPONDENT’S INSURANCE ARE ONLY ASKED HERE IFTHE 

RESPONDENT HAS NOT ALREADY ANSWERED FOR HIMSELF/HERSELF IN K12Q40 OR 

K12Q50.

At this time, do you have any kind of health care coverage, including health insurance, prepaid 

plans such as HMOs, or government plans such as Medicaid or Medicare?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED

IF 0,6,7 SKIP TO K12Q62. 

K12Q61 Is that health insurance provided through your current employer, former employer, union, or some 

other source?

(1) CURRENT EMPLOYER [SKIP TO K12Q63]

(2) FORMER EMPLOYER 

(3) UNION [SKIP TO K12Q63]

(4) SOME OTHER SOURCE

(6) DON’T KNOW

(7) REFUSED

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS THAT INSURANCE IS 

PROVIDED THROUGH MULTIPLE SOURCES, ASK WHICH SOURCE PROVIDES 

PRIMARY COVERAGE FOR BOTH DOCTOR VISITS AND HOSPITAL STAYS.

K12Q62 At this time, are you eligible for health insurance through your current employer or union?

(1) YES, CURRENT EMPLOYER

(2) YES, UNION

(3) YES, BOTH

(4) NO [SKIP TO NEXT SECTION] 

(6) DON’T KNOW

(7) REFUSED [SKIP TO NEXT SECTION] 

INTERVIEWER NOTE: IF THE RESPONDENT REPORTS NOT BEING EMPLOYED, 

RECORD ANSWER AS NO.

K12Q63 IF K12Q61 OR K12Q62 = 1, FILL WITH “employer”

IF K12Q61 = 3 OR K12Q62 = 2, FILL WITH “union”

IF K12Q62 = 3 or 6, FILL WITH “employer or union”

Does this [employer/union/employer or union] offer health insurance that could help pay for 

doctor visits and hospital stays for [S.C.]?

(1) YES 

(0) NO

(6) DON'T KNOW

(7) REFUSED
Series 1, No. 59  Page 155 

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

RESPONDENT'S EMPLOYER.

IF 0,6,7 SKIP TO K12Q66. 

K12Q64 If [S.C.] was covered by insurance provided through this [employer/union/employer or union], 

would this [employer/union/employer or union] pay for all, some, or none of [his/her] health 

insurance premium?

(1) ALL 

(2) SOME

(3) NONE

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

RESPONDENT'S EMPLOYER.

K12Q65 What is the main reason that [S.C.] is not covered by insurance providedthrough this

[employer/union/employer or union]?

COST

(01) COST IS TOO HIGH

(02) TRADED HEALTH INSURANCE FOR HIGHER PAY

ELIGIBILITY 

(03) INSURER REFUSED TO COVER / PREEXISTING CONDITION

(04) CHILD NOT ELIGIBLE DUE TO TYPE OF JOB

(05) CHILD NOT ELIGIBLE DUE TO NUMBER OF HOURSWORKED

(06) CHILD NOT ELIGIBLE DUE TO LENGTH OF TIME ATJOB

(07) CHILD NOT ELIGIBLE FOR SOME OTHERREASON

APPLICATION PROCESS

(08) HAVE APPLIED – NOW JUST WAITING

(09) INTEND TO APPLY BUT JUST HAVEN’T DONE SO

(10) DON'T KNOW WHERE OR HOW TO APPLY

(11) APPLICATION PROCESS TOO DIFFICULT, TAKES TOO MUCHTIME

NEGATIVE VIEWS OF PROGRAM

(12) HEARD BAD THINGS ABOUT INSURANCEPROGRAM

(13) DO NOT LIKE DOCTORS / MEDICAL STAFF / CLINIC IN HEALTHPLAN

(14) SERVICES PROVIDED NOT CONVENIENTLY LOCATED OR NOTAVAILABLE 

WHEN NEEDED

OTHER

(15) DOES NOT NEED INSURANCE / DOES NOT GETSICK

(16) EXPECT TO HAVE INSURANCE FROM ANOTHER SOURCESOON

(17) OTHER [SKIP TO K12Q45]

(96) DON’T KNOW

(97) REFUSED 

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

RESPONDENT'S EMPLOYER.

K12Q66 IF K12Q61 = 3 OR K12Q62 = 2, SKIP TO NEXTSECTION.
Page 156  Series 1, No. 59 

Think about all locations where your employer operates. Would you say that the total number of 

persons who work for this employer is above or below 100?

(1) MORE THAN 100

(2) EXACTLY 100

(3) LESS THAN 100

(4) NOT EMPLOYED 

(6) DON'T KNOW

(7) REFUSED

K12Q67 ASK K12Q67 ONLY IF K12Q66=3 OTHERWISE, SKIP TO NEXTSECTION.

Is the total number of persons who work for your employer above or below 50?

(1) MORE THAN 50

(2) EXACTLY 50

(3) LESS THAN 50

(6) DON'T KNOW

(7) REFUSED

NOTE TO INTERVIEWER: AT THIS QUESTION, COLLECT INFORMATION ABOUT THE 

RESPONDENT'S EMPLOYER.
Series 1, No. 59  Page 157 

Section 13: Locating Information

Subdomain 1: Telephone line information

CPC11Q14 IF (RDD_NCCELL_CCELL=2,3 AND TAKE_ALL_CELL_FLAG=1) THEN ASK

SL_LANDLINE; ELSE SKIP TO C11Q15_CELL

SL_LANDLINE The next few questions are about the telephones in your household.

Do you have a landline telephone in your household? 

READ AS NECESSARY: Please do not include:

- modem-only lines,

- fax-only lines,

- lines used just for home security systems, 

- beepers,

- Skype

- pagers, or

- cell phones.

Please include Voice Over I.P. or VOIP numbers.

(1) YES 

(0) NO

(6) DON’T KNOW

(7) REFUSED

C11Q15_CELL [IF SL_LANDLINE NOT DISPLAYED, THEN DISPLAY: The next few questions are about the 

telephones in your household. ]

In total, how many working cell phones do you and your household members have available for 

personal use? Please do not count cell phones that are used exclusively for business purposes [If 

RDD_NCCELL_CCELL=2,3 and NEWPHONE_FLAG=0 then display: "and please include the 

number we called." ELSE If RDD_NCCELL_CCELL=2,3 and NEWPHONE_FLAG=1 then 

display: “and please include [OLD_NUMBER].” ]

[If RDD_NCCELL_CCELL=2,3 and NEWPHONE_FLAG=1 display "INTERVIEWER NOTE: 

THE NUMBER FOR THIS CASE WAS CHANGED BY THE RESPONDENT ON A 

PREVIOUS CALL.”]

(1) ONE

(2) TWO

(3) THREE OR MORE

(4) NONE [GO TO C11Q20]

(6) DON'T KNOW

(7) REFUSED 
Page 158  Series 1, No. 59 

CP_CELLUSUALLY 

IF ((NIS OR TEEN COMPLETED) AND (C21_06Q3_CELL = 1, 2, 3, 6, 7 OR

TIS_C21_06Q3_CELL = 1, 2, 3, 6, 7)), GO TO C11Q15_CELL_USUALLY

ELSE IF (NIS OR TEEN COMPLETED) AND (C21_06Q3_CELL = 4 OR 

TIS_C21_06Q3_CELL = 4), GO TO C11Q20

ELSE GO TO C11Q15_CELL_USUALLY

C11Q15_CELL_USUALLY

[IF NIS OR TEEN COMPLETED AND (C21_06Q3_CELL = 1, 2, 3 or TIS_C21_06Q3_CELL =

1, 2, 3) AND SAMPLE_USE_CODE IN (2,4) READ: Earlier you told me that you have at least 

one cell phone in your household.]

[IF NIS OR TEEN COMPLETED AND (C21_06Q3_CELL = 6, 7 or TIS_C21_06Q3_CELL =

6, 7) AND SAMPLE_USE_CODE IN (2,4) READ: The next few questions are about the 

telephones in your household.]

How many [IF C11Q15_CELL = 1, 2, 3 THEN DISPLAY: "of these"] cell phones do the adults in 

this household usually use? [If RDD_NCCELL_CELL=2,3 and NEWPHONE_FLAG=0 then 

display: "Please include the number we called." ELSE If RDD_NCCELL_CCELL=2,3 and 

NEWPHONE_FLAG=1 then display “Please include [OLD_NUMBER].”]

[IF RDD_NCCELL_CELL=2,3 then display: "INTERVIEWER NOTE: THE NUMBER WE 

CALLED IS ASSUMED TO BE USUALLY USED, SO THE ANSWER MUST BE AT LEAST 

"ONE""]

[If RDD_NCCELL_CCELL=2,3 and NEWPHONE_FLAG=1 display "INTERVIEWER NOTE: 

THE NUMBER FOR THIS CASE WAS CHANGED BY THE RESPONDENT ON A 

PREVIOUS CALL.]

(1) ONE

(2) TWO

(3) THREE OR MORE

(0) NONE

(6) DON’T KNOW

(7) REFUSED

CP_C11Q16 IF (RDD_NCCELL_CCELL=2,3 AND (SL_LANDLINE=2 OR LANDLINE=2)) THEN SKIP

TO CPC11_AWAY; ELSE ASK C11Q16

C11Q16 Of all the telephone calls that you and your household receive, are nearly all receivedon cell

phones, nearly all received on regular phones, or some received on cell phones and somereceived 

on regular phones?

HELP TEXT: "REGULAR PHONES" REFERS TO LANDLINE PHONES

(1) NEARLY ALL RECEIVED ON CELL PHONES

(2) NEARLY ALL RECEIVED ON REGULARPHONES

(3) SOME RECEIVED ON CELL PHONES AND SOME RECEIVED ON REGULARPHONES

(6) DON’T KNOW

(7) REFUSED

CPC11_AWAY IF (RDD_NCCELL_CELL=2,3 AND CELL_AWAY = 1) THEN GO TO C11_AWAY; ELSE GO 

TO SL_CELLUSE
Series 1, No. 59  Page 159 

C11_AWAY Would you mind telling me if I reached you today away from home or athome?

INTERVIEWER NOTE: IF THE RESPONDENT WAS AWAY FROM HOME DURING ANY 

PART OF THE CALL, THEN CODE AS AWAY FROM HOME.

(1) AWAY FROM HOME

(2) AT HOME

(6) DON'T KNOW

(7) REFUSED

SL_CELLUSE IF [(RDD_NCCEL_CCELL=1 AND C11Q15_CELL=1,2,3,6,7) OR 

(TAKE_ALL_CELL_FLAG=1 AND RDD_NCCELL_CCELL=2,3 AND 

SL_LANDLINE=1,6,7)] THEN ASK SL_CELLUSE; ELSE SKIP TOCP_CELLONLY

Thinking just about the landline home phone, not your cell phone, if that telephone rang and 

someone were home, under normal circumstances how likely is it that it would be answered? 

Would you say extremely likely, somewhat likely, somewhat unlikely, or not at all likely?

(1) EXTREMELY LIKELY 

(2) SOMEWHAT LIKELY 

(3) SOMEWHAT UNLIKELY

(4) NOT AT ALL LIKELY 

(6) DON’T KNOW

(7) REFUSED

CP_CELLONLY IF (RDD_NCCELL_CELL=2,3 AND (SL_LANDLINE=2 OR LANDLINE=2) THEN GO TO 

CPV_ISLAND; ELSE GO TO C11Q20

C11Q20 Not including cellular telephones, has your family been without telephone service for 1 week or 

more during the past 12 months?

(1) YES [SKIP TO CPV_ISLAND]

(0) NO [SKIP TO CPV_ISLAND]

(6) DON’T KNOW [SKIP TO CPV_ISLAND]

(7) REFUSED [SKIP TO CPV_ISLAND]

Subdomain 2: ZIP Code

CPV_ISLAND IF IAP=95 THEN GO TO V_ISLAND, ELSE GO TO C11Q22. 

V_ISLAND IF NIS COMPLETE FILL FROM C_ISLAND. 

IF TEEN COMPLETE FROM TIS_C_ISLAND. 

On what island do you live?

(1) SAINT CROIX [GO TO CP_ADDRESS]

(2) SAINT THOMAS [GO TO CP_ADDRESS]

(3) SAINT JOHN [GO TO CP_ADDRESS]

(4) WATER ISLAND [GO TO CP_ADDRESS]

(5) DON’T LIVE IN VIRGIN ISLANDS [GO TO C11Q22]

(6) DON’T KNOW [GO TO C11Q22]
Page 160  Series 1, No. 59 

(7) REFUSED [GO TO C11Q22]

C11Q22 [Filled from C19A, C19A_NEW_ZIP, TIS_C19A, or TIS_C19A_NEW_ZIP if it is not 

equal to missing, '99996', or '99997'.]

Please tell me your zip code.

[CATI: 5 NUMERIC-CHARACTER-FIELD, RANGE 00001-99998]

 (00001-99998)

(99996) DON’T KNOW

(99997) REFUSED

C11Q22_CONF [IF C11Q22 FILLED FROM C19A or TIS_C19A, THEN "Earlier you told me your zip 

code is" / IF C11Q22 ASKED, THEN "I entered"] [FILL C11Q22], is that correct?

(1) YES [GO TO LOC_STATE]

(2) NO [GO TO C11Q22]

LOC_STATE What state do you live in?

 (DROP DOWN MENU OF STATE NAMES) [THIS DOES NOT CHANGE

‘STATE’ FROM THE SAMPLE PRE-FILL TABLE]

(96) DON’T KNOW

(97) REFUSED

Subdomain 3: Locating questions

CP_ADDRESS IF LOCATE_FLAG = 1 THEN GO TO LOCATE_TRANSITION 

IF LOCATE_FLAG = 0 AND CASE DID NOT QUALIFY FOR NIS OR NSCH 

INCENTIVES, GO TO K_END

ELSE IF LOCATE_FLAG = 0 AND CASE DID QUALIFY FOR NIS OR NSCH INCENTIVES, GO TO 

NSCH_ADDRESS_CONF

LOCATE_TRANSITION We may want to contact you in the future to ask questions about the health and health 

care of [S.C.]. By participating in future surveys, you will help us better understand the 

health and health care needs of children and adolescents in your state and the nation.

LOCATE_NUMBER Is there another number where we can reach you if this number isn't working for some 

reason?

INTERVIEWER INSTRUCTION: IF THE RESPONDENT SAYS NO, PROBE THE

RESPONDENT FURTHER BY SAYING: "An alternate number can be a work or cell 

phone number, or even a number for a relative who you keep in touch with."

READ AS NECESSARY: We will only call you back to participate in future surveys 

about the health or health care of [S.C.], and will not sell or disclose your telephone 

number to any other party. If we do contact you in the future, you can choose whether or 

not to participate at that time.

LOCATE_ 

(1) YES [GO TO LOCATE_NUMBERGIVEN]

(2) NO OR REFUSED [GO TO LOCATE_ADDRESS]

NUMBERGIVEN ENTER TELEPHONE NUMBER ( ) 
Series 1, No. 59  Page 161 

LOCATE_ 

NUMBERGIVEN_A (1) TELEPHONE NUMBER COMPLETE [GO TO TELETYPE] 

(2) ENTER TELEPHONE EXTENSION [GO TO LOCATE_NUMBER_EXT]

LOCATE_ 

NUMBER_EXT ENTER EXTENSION TO TELEPHONE NUMBER. (ALLOW FOR UP TO FIVE 

NUMBERS)

TELETYPE Is this telephone number a cell phone, landline, work number or othertype?

(1) CELL 

(2) WORK

(3) OTHER 

(6) DON'T KNOW

(7) REFUSED

LOCATE_ADDRESS If we call you back in the future, we may want to mail you a letter explainingmore about 

the survey and the questions we will ask.

IF CASE QUALIFIED FOR NSCH INCENTIVE THEN READ: We'd also like to mail

you [$XX] as a token of our appreciation for taking the time to answer our questions.

If AC_NIS_INCENT_EXIT not previously read, READ: In addition, the National 

Immunization Study will be sending you $[X], which you may have already received.

IF NO ADDRESS, READ: Would you please give me your address?

IF ADDRESS ALREADY OBTAINED, READ: Would you please verify your address?

PROCEED THROUGH ADDRESS COLLECTION OR VERIFICATION. 

IF NAME OF S.C. GIVEN DURING SURVEY, THEN SKIP TO PNAME.

LOCATING_NAME I could refer to your child as [AGEID] if we call you back, or if you prefer,you could 

give me a first name or initials.

(1) CONTINUE TO USE AGE REFERENCE [GO TO PNAME]

(2) USE NAME [GO TO LOCATING_NAME_A] 

LOCATING_NAME_A ENTER NAME/INITIALS: 

PNAME Since following up with your household maybe easier if we have your name, could you 

please give me your name or initials?

(1) YES [GO TO PNAME_A]

(0) NO [GO TO K_END]

PNAME_A ENTER NAME/INITIALS 

GO TO K_END

Subdomain 4: Closing Script

K_END Those are all the questions I have. You may be re-contacted in the future to participate in related

studies. If you are contacted to participate in future surveys, you have the right to refuse. I’d like 

to thank you on behalf of the Centers for Disease Control and Prevention for the time and effort
Page 162  Series 1, No. 59 

you’ve spent answering these questions. If you have any questions about this survey, you may 

call my supervisor toll-free at [IF SUC = 1, 2, 4, 5, 6, FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC =3,

FILL 1 - 8 6 6 - 9 0 0 - 9 6 0 1]. If you have questions about your rights as a survey participant, 

you may call the chairman of the Research Ethics Review Board at 1-800-223-8118. Thank you 

again.

TERMINATE INTERVIEW WITH RESPONDENT.

LANG1 APPEARS AFTER COMPLETED INTERVIEWS ONLY.

INTERVIEWER: WAS THIS INTERVIEW COMPLETED USING ENGLISH ONLY?

(1) YES [TERMINATE INTERVIEW, IF ITS <> 67, GO TOCOMMENTS]

(0) NO [SKIP TO LANG2]

LANG2 INTERVIEWER: WHICH LANGUAGES WERE NEEDED TO COMPLETE THISINTERVIEW?

[Mark all that apply.] 

(1) ENGLISH 

(2) SPANISH

(4) CANTONESE

(8) KOREAN

(9) MANDARIN

(13) VIETNAMESE

(14) ANOTHER LANGUAGE [GO TO LANG2_OTHER]

LANG2_

OTHER OTHER LANGUAGE

LANG3 INTERVIEWER: WAS THIS INTERVIEW COMPLETED “MOSTLY INENGLISH” OR

“MOSTLY IN ANOTHERLANGUAGE”?

(1) MOSTLY IN ENGLISH 

(2) MOSTLY IN OTHER LANGUAGE

(3) ABOUT HALF AND HALF
Series 1, No. 59  Page 163 

Callback and Refusal Conversion Scripts

INTRO_1 Hello, my name is . I’m calling on behalf of the Centers for Disease Controland Prevention 

[(NSCH11_INCENT_FLAG = 2 OR NSCH11_PASSIVE = 1 or 2) AND NSCH11_LTR_FLAG

= 1 THEN, " to follow up on a letter that was sent to your home"/ ELSE NO FILL]. Earlier, we 

contacted your household to participate in a survey about the health of children and teenagers. I’m 

calling back to continue the interview.

(IF NAME WAS GIVEN FOR APPOINTMENT, ASK FOR THAT PERSON.)

INTRO_1A Hello, my name is . I’m calling on behalf of the Centers for Disease Controland Prevention 

[IF SUC=5, 6 AND NSCH11_INCENT = 5 or 6 AND (NSCH11_INCENT_FLAG = 2OR

NSCH11_PASSIVE = 1 or 2) AND NSCH11_LTR_FLAG = 1 THEN, “ to follow up on a letter 

that was sent to your home”/ ELSE NO FILL]. Earlier we contacted your household to 

participate in a survey about the health of children and teenagers. After just a few questions I can 

determine if your household is eligible to participate. [IF SUC=5, 6 AND NSCH INCENTIVE 

CASE, THEN DISPLAY: "In appreciation for your time, we will send you $[MONEY_1 / 

MONEY_2]."]

(IF NAME WAS GIVEN FOR APPOINTMENT, ASK FOR THAT PERSON.)

INTRO_1B Hello, my name is . I’m calling on behalf of the Centers for Disease Controland Prevention 

[IF NSCH11_INCENT = 5 or 6 AND (NSCH11_INCENT_FLAG = 2 OR NSCH11_PASSIVE = 

1 or 2) AND NSCH11_LTR_FLAG = 1 THEN, “ to follow up on a letter that was sent to your 

home”/ ELSE NO FILL]. Earlier, someone in your household started a survey about the health of 

children and teenagers. I'm calling back now to continue the interview. [IF NSCH INCENTIVE 

CASE, THEN DISPLAY: "In appreciation for your time, we will send you $[MONEY_1 / 

MONEY_2]."]

(IF NAME WAS GIVEN FOR APPOINTMENT, ASK FOR THAT PERSON.) 

INTRO_CLOSEDOWN

Hello, my name is . I'm calling on behalf of the Centers for Disease Controland Prevention 

[(IF NSCH11_INCENT_FLAG = 2 AND NSCH11_LTR_FLAG = 1 ) OR (NSCH11_PASSIVE = 

1 OR 2 AND NSCH11_LTR_FLAG = 1 ) THEN DISPLAY "to follow up on a letter that was sent 

to your home"/ ELSE NO FILL]. Earlier, we contacted your household to participate in a survey 

about the health of children and teenagers. I'm calling back to continue the interview. The study 

will be over in the next few days, so we would greatly appreciate a few minutes of your time. [IF 

INCENTIVE CASE: "In appreciation of your time, we will send you $[MONEY_1 / 

MONEY_2]."]

S1 Am I speaking to someone who lives in this household who is over 17 yearsold?

(1) YES, I AM THAT PERSON [ IF [S.C.] IS SELECTED, GO TO

REMIND1/ ELSE CONTINUE WITH INTERVIEW] 

(2) THIS IS A BUSINESS [GO TO SALZ]

(3) NEW PERSON COMES TO PHONE [GO BACK TO INTRO_1]

(8) DOES NOT LIVE IN HOUSEHOLD [ASK FOR ANOTHER PERSON

OR SCHEDULE APPOINTMENT ON THE NEXT SCREEN]

(9) NO PERSON AT HOME WHO IS OVER 17 [GO TO S2_B]

(97) REFUSED [GO TO REFUSAL CONVERSION, 

SET DISP AND TERMINATE]
Page 164  Series 1, No. 59 

REMIND1 [CONTINUE WITH INTERVIEW AT POINT OF BREAKOFF]

I want to remind you that we will be asking questions about [S.C.] for the rest of this 

interview.

Answering Machine Scripts

MSG_AUG (PLEASE READ SLOWLY AND CLEARLY.) Hello. The Centers for Disease Control and 

Prevention is conducting a survey about the health of children and teenagers. Your [IF 

RDD_NCCELL_CCELL IN 2,3 THEN FILL "cell"] telephone number has been selected at 

random to participate in this survey. We’re sorry we missed you and will try back at another time. 

Or, you can call us at [IF SUC = 1, 2, 4, 5, 6, FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC = 3, FILL 1 

- 8 6 6 - 9 0 0 - 9 6 0 1]. [If SUC=5,6 AND INCENTIVE CASE, DISPLAY "In appreciation for

your time, we will send you $[MONEY_1 / MONEY_2]."]. Thank you.

MSG_Y_APPT (PLEASE READ SLOWLY AND CLEARLY.) Hello. I am calling on behalf of the Centers for 

Disease Control and Prevention regarding a national study [IF RDD_NCCELL_CCELL IN 2,3 

THEN FILL of cell telephone users] about the health of children and teenagers. I'm sorry that 

we've missed you. When we spoke previously about this important study, you requested that we 

call you back at this time. We'll try to contact you again soon but please feel free to return our call 

anytime at [IF SUC = 1, 2, 4, 5, 6, FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC = 3, 1 - 8 6 6 - 9 0 0 - 9 

6 0 1 ]. [If INCENTIVE CASE, DISPLAY "In appreciation for your time, we will send you

$[MONEY_1 / MONEY_2]."]. Thank you.

MSG_NSCH (PLEASE READ SLOWLY AND CLEARLY.) Hello. I’m calling on behalf of theCenters for 

Disease Control and Prevention [(IF NSCH_INCENT_FLAG = 2 AND NSCH_LTR_FLAG = 1 ) 

OR (NSCH_PASSIVE = 1 OR 2 AND NSCH_LTR_FLAG = 1 ) THEN, “ to follow up on a letter 

that was sent to your home”/ ELSE NO FILL]. We recently contacted [IF 

RDD_NCCELL_CCELL IN 2,3 THEN FILL you on your cell telephone / ELSE FILL your 

household] and began a children's health survey. I’m calling back to continue the survey. (IF 

INCENTIVE CASE, DISPLAY: "In appreciation for your time, we will send you $[MONEY_1 / 

MONEY_2]."). If you would like to participate right away, please call our toll-free number, at [IF 

SUC = 1, 2, 4,5, 6, FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC = 3, FILL 1 - 8 6 6 - 9 0 0 - 9 6 0 1].

Thank you.

MSG_CLOSEDOWN

(PLEASE READ SLOWLY AND CLEARLY.) Hello. I'm calling on behalf of the Centers for 

Disease Control and Prevention [(IF NSCH11_INCENT_FLAG = 2 AND NSCH11_LTR_FLAG

= 1 ) OR (NSCH11_PASSIVE = 1 OR 2 AND NSCH11_LTR_FLAG = 1 ) THEN, "to follow up

on a letter that was sent to your home"/ ELSE NO FILL]. We recently contacted [IF 

RDD_NCCELL_CCELL IN 2,3 THEN FILL "you on your cell telephone" / ELSE FILL "your 

household"] and began a children's health survey. I'm calling back to continue the survey. The 

study will be over in the next few days, so we would greatly appreciate if you call us back as soon 

as possible. Our toll-free number is [If SAMPLE_USE_CODE=2,4,5,6 display: 1 - 8 6 6 - 9 9 9 - 

3 3 4 0 / If SAMPLE_USE_CODE=3 display: 1 - 8 6 6 - 9 0 0 - 9 6 0 1]. [IF INCENTIVE CASE:

"In appreciation of your time, we will send you $[MONEY_1 / MONEY_2]."]. Thank you.

MSG_Y_APPT

_CLOSEDOWN (PLEASE READ SLOWLY AND CLEARLY.) Hello. I am calling on behalf of the Centers for 

Disease Control and Prevention regarding a national study about the health of children and 

teenagers. I'm sorry that we've missed you. When we spoke previously about this important study,
Series 1, No. 59  Page 165 

you requested that we call you back at this time. The study will be over in the next few days, so 

we would greatly appreciate if you call us back as soon as possible. Our toll-free number is [IF 

SUC = 1, 2, 4, 5, 6, FILL 1 - 8 6 6 - 9 9 9 - 3 3 4 0 / IF SUC = 3, FILL 1 - 8 6 6 - 9 0 0 - 9 6 0 1].

[If INCENTIVE CASE, DISPLAY "In appreciation for your time, we will send you $[MONEY_1

/ MONEY_2]."]. Thank you.
Page 166 Series 1, No. 59

Appendix III. Summary of Key Differences Between 2007 and 2011–

2012 Questionnaires

This appendix summarizes the key 

differences between the 2007 National 

Survey of Children’s Health (NSCH) 

questionnaire and the 2011–2012 

questionnaire. Changes made after the 

start of data collection in Quarter 1, 2011, 

are reflected in Appendix IV. 

Section 2: Initial Screening

Additions

● A safety screener was added

(S_WARM) to ensure that call

respondents were not driving or

doing anything else requiring their

full attention.

● Specific language was added to the

introduction script (INTRO_1) to

inform respondents that they were

intentionally being called on their

cellular device.

● Questions were also added to assess

cell-phone respondents’ phone status

(LANDLINE and CELLUSE) and to

screen out households that were not

cell phone-only or cell phone-mainly.

These questions were used only for

Quarter 1, 2011, prior to modifying

the cell- phone screening approach in

Quarter 2, 2011.

Section 2: Health and 

Functional Status

Additions

● A question was added that asked

if the sample child was born

prematurely (K2Q05).

● Two questions on conditions were

added, regarding intellectual

disability or mental retardation

(K2Q60A) and cerebral palsy

(K2Q61A):

○ Follow-up questions included age

at first diagnosis (K2Q60A_1

and K2Q61A_1), whether the

child currently had the condition

(K2Q60B and K2Q61B), and the

severity of the current condition

(K2Q60C and K2Q61C).

○ Age at first diagnosis was

also collected for Attention

deficit disorder, Attentiondeficit/hyperactivity disorder

(K2Q31A_1), Behavioral or

conduct problems (K2Q34A_1),

Autism or autism spectrum

disorder (ASD) (K2Q35A_1),

Developmental delay

(K2Q36A_1), Speech or other

language problems (K2Q37A_1),

Tourette syndrome (K2Q38A_1),

and vision problems that cannot

be corrected with standard glasses

or contact lenses (K2Q44A_1).

○ Follow-up questions were added

regarding children ever diagnosed

with autism or ASD, including

who first told the respondent

that the child had autism or ASD

(K2Q35D), and if the respondent

thought that the child ever had

autism or ASD (K2Q35E).

● Questions assessing the reasons that

the child may no longer have autism

or ASD were added:

○ “Treatment helped condition go

away” (K2Q35F_1).

○ “Condition went away on its own”

(K2Q35F_2).

○ “Behaviors or symptoms

changed” (K2Q35F_3).

○ “A doctor or health care

provider changed the diagnosis”

(K2Q35F_4).

○ “Any other reasons (verbatim)”

(K2Q35G).

● Additional questions assessed

reasons why a doctor, health care

professional (HCP), or school

professional may have told the

respondent the child had a condition

that he or she never had:

○ “With more information,

diagnosis was changed”

(K2Q35H_1).

○ “Diagnosis was given so child

could receive needed services”

(K2Q35H_2).

○ “You disagree with the doctor

or other HCP about [his/her]

opinion that [S.C.] had autism or

ASD” (K2Q35H_3), where S.C. is

sampled child.

○ “Any other reasons (verbatim)”

(K2Q35J).

Deletions

● Children with Special Health Care

Needs Screener test questions were

removed regarding prescription

use (K2Q12A); medical care,

mental health, or education

services (K2Q15A); limitations in

abilities (K2Q18A); special therapy

(K2Q12A); special arrangements

(K2Q30D); number of visits to

the doctor because of a condition

(K2QTEST1); and reasons for not

seeing a doctor (K2QTEST2).

● Ratings of the overall severity

of several conditions (K2Q47C,

K2Q48C, K2Q49C, and K2Q50C)

were removed.

● The follow-up question regarding

current bone, joint, or muscle

problems was removed (K2Q45D).

● Dental health questions (K2Q54A

and K2Q55) were removed.

● A series of questions pertaining

to family activities were removed

(K2Q60A through K2Q60E).

● A series of immunization questions

were removed (K2Q81 through

K2Q85).

Revisions

● The text “that affects [his/her] ability

to learn” was dropped from the end

of K2Q36A.

● The text “speech or other language

problems” replaced “stuttering,

stammering, or other speech

problems” in K2Q37A.

● The word “standard” was added to

K2Q44A.

● The 2011–2012 NSCH combined

K2Q52 (toothache) and K2Q53

(decayed teeth or cavities) into one

question and moved it to Section 4,
Series 1, No. 59  Page 167 

Subdomain 2. The word “unfilled” 

was also added to the question, and 

the reference period was lengthened 

from “past 6 months” to “past 12 

months.”

Section 3: Health Insurance 

Coverage

Additions

● A question was added to determine 

if the cost of the child’s health care 

was causing financial problems 

for his or her family (K3Q25), as 

was a question to determine if the 

respondent had been frustrated in 

efforts to obtain health care services 

for the child (C4Q04).

Revisions

● Because the official program name 

changed, “State Children’s Health 

Insurance Program, S–CHIP” was 

replaced with “Children’s Health 

Insurance Program (CHIP)” in 

K3Q02. Help text was also added to 

assist respondents who did not reside 

in the state that the program name 

fill was referencing. 

Section 4: Health Care 

Access and Utilization

Additions

● The 2011–2012 NSCH added 

questions regarding recent medical 

(S4Q01) and dental (K4Q30) care 

and vision screening (K4Q31 and 

K4Q32). 

● A line of questioning was added 

inquiring if the child had received 

any home visits from nurses, health 

care workers, social workers, or other 

professionals to help prepare for the 

new baby or to take care of the baby 

or mother (K4Q35), and how many 

visits were made (K435A).

● Follow-up questions were added 

to determine topics raised by the 

professionals who visited the home, 

including the mother’s emotional 

well-being (K4Q35B_1), presence of 

smoking or alcohol use in the home 

(K4Q35B_2), building a relationship 

with the child (K4Q35B_3), how 

to make sure the child is safe 

(K4Q35B_5), how to get the health 

care the child needs (K4Q35B_6), 

and other services (K4Q35B_7). 

● A series of question were added 

regarding therapy services for autism 

or ASD or developmental delay, 

including the age that the child began 

receiving services and if he or she 

currently receives services (K4Q36 

through K4Q38).

Revisions

● “Retail store clinic or ‘minute clinic’ ” 

was added as a response option to 

K4Q02.

● “Vision care” was added as a 

response option to K4Q28.

Section 5: Medical Home

Deletions

● A question (K5Q45) and follow-up 

frequency question (K5Q46) were 

removed regarding whether an 

interpreter was needed to speak with 

the child’s doctors or other health 

care professional.

Section 6: Early Childhood

Additions

● A series of flourishing questions 

assessing attachment (K6Q70), 

aspiration (K7Q71), happiness 

(K7Q72), and resiliency (K6Q73) 

were added.

● A question was added to determine 

the amount of time spent with 

computers, cell phones, handheld 

video games, and other electronic 

devices (K6Q66).

Revisions

● The text in K6Q65 was revised from 

“On an average weekday, about how 

much time does [S.C.] usually watch 

TV or watch videos?” to: 

○ “On an average weekday, about 

how much time does [S.C.] 

usually spend in front of a TV 

watching TV programs, videos, or 

playing video games?”

Deletions

● A question pertaining to provider 

response to parental concerns 

(K6Q11), two questions regarding 

injury (K6Q30 and K6Q31), and 

a series of child care questions 

(K6Q20B, K6Q21, K6Q22, K6Q25B, 

and K6Q25C) were removed.

Section 7: Middle 

Childhood and Adolescence 

(6–17 years)

Additions

● As in Section 6, a series of 

flourishing questions were added to 

Section 7 (K6Q70 through K6Q73).

● A question was added asking which 

specific grades were repeated, if any 

(K7Q05_A).

Revisions

● Similar to Section 6, a question 

to determine the amount of time 

spent with computers, cell phones, 

handheld video games, and other 

electronic devices on an average 

weekday was added (K7Q91).

○ A follow-up question was added 

to capture whether the respondent 

monitors the content of the 

devices listed in K7Q91. 

● Questions K7Q61 and K7Q62 

were edited to capture information 

regarding the additional devices 

referenced in K7Q91.

● The text in question K7Q32 was 

revised to include “lessons, such 

as music dance, language, or other 

arts.” 

● The skip logic at K7Q32 was revised 

so all cases that completed Section 7 

received the question. The previous 

logic, which dictated that the 

question be skipped if a response of 

“yes” was given at K7Q30 or K7Q31, 

was retained through Quarter 2, 

2011, due to a system error. The new 

logic was implemented in Quarter 3, 

2011.
Page 168  Series 1, No. 59

Deletions

● A series of social competence scale 

questions was removed (K7Q72 

through K7Q77).

● Two questions regarding a depressed 

mood were also removed (K7Q78 

and K7Q80).

Section 9: Parental Health

Additions

● A question to determine the age 

of the oldest adult living in the 

household was added (C10Q14).

● A series of questions regarding 

adverse family experiences was 

added (ACE1 and ACE3 through 

ACE11).

● A question was added asking 

about the presence of at least one 

adult mentor in the child’s school, 

neighborhood, or community (apart 

from other adults in his or her home) 

to rely on for advice or guidance 

(K9Q96).

Revisions

● The household roster (C10Q02B) 

was modified from a parental roster 

(the identification of “parents or 

people who act as parents”) to a 

family roster that captured the 

relationships of all the people living 

in the household to the selected child. 

This change was made to align with 

the 2009–2010 National Survey of 

Children with Special Health Care 

Needs (NS–CSHCN) expanded 

roster approach.

Deletions

● Questions were removed that 

assessed the number of days in the 

past week that the mother-type, 

father-type, and respondent (if 

not the child’s mother or father) 

exercised, played sports, or 

participated in physical activity for 

at least 20 minutes (K9Q30 through 

K9Q32).

Section 11: Additional 

Demographics

Additions

● A question determining the highest 

grade or year of school completed 

by any of respondent’s parents or 

guardians was added (K11Q22A).

● A question asking if anyone in 

household currently receives Special 

Supplemental Nutrition Program for 

Women, Infants, and Children (WIC) 

benefits was added (S9Q34).

Revisions

● The text “Supplemental Nutrition 

Assistance Program” was added to 

K11Q61.

Section 12: Additional 

Health Insurance Questions

Additions

● This section, supported by the 

Office of the Assistant Secretary 

for Planning and Evaluation, U.S. 

Department of Health and Human 

Services, was added to the 2011–

2012 NSCH to obtain additional 

health insurance information. Only 

households with uninsured children 

received the section to determine:

○ Reasons for uninsurance.

○ The child’s enrollment history 

with Medicaid or CHIP.

○ Attitudes toward and interest in 

enrolling in Medicaid or CHIP.

○ Parents’ insurance coverage.

○ Availability of employersponsored insurance. 

Section 13: Locating 

Information

Additions

● Based on the 2009–2010 NS–

CSHCN approach, locating questions 

were added to aid in contacting the 

household for future surveys. These 

questions included requesting:

○ Another phone number at 

which the respondent could be 

reached in the future (LOCATE_

NUMBER).

○ The respondent’s address 

(LOCATE_ADDRESS).

○ The respondent’s name or initial 

(PNAME).

○ The child’s first name or initials, if 

not already given (LOCATING_

NAME).

Revisions

● Also in alignment with the 2009–

2010 NS–CSHCN approach, the 

following questions on phone lines 

and household information were 

added: 

○ A question regarding the number 

of working cell phones for 

personal use for all household 

members (C11Q15_CELL).

○ A question regarding cell-phone 

use relative to landline use for 

households with both services 

(C11Q16) was added, allowing a 

household to be categorized as 

either a “cell phone mostly” or 

“landline mostly” household.

○ Confirmation questions for zip 

code and state of residence were 

added for all households (C11Q22 

and LOC_STATE).
Series 1, No. 59  Page 169 

Appendix IV. Summary of Questionnaire Changes During Data 

Collection

During the course of data collection, 

a number of changes were made to the 

National Survey of Children’s Health 

(NSCH) questionnaire to improve the 

quality of data collected, accommodate 

methodological changes, and address 

concerns voiced by respondents, 

interviewers, and study sponsors. 

Questionnaire changes made following 

the launch of Quarter 1, 2011, are 

listed by the date on which they were 

implemented. 

On April 7, 2011 (Quarter 2, 2011), 

the following changes were made: 

● A confirmation question (K3Q01_

CONF) was added after K3Q01 if the 

respondent answered “no.”

● The word “FAMILY” in K11Q51 was 

changed from all capital letters to 

lowercase italicized, “family.”

● Names of several state Medicaid 

programs were added to the 

Medicaid name fill table. Areas 

with updated program names were: 

Alabama, Arizona, Connecticut, 

Delaware, District of Columbia, 

Georgia, Idaho, Illinois, Iowa, 

Kansas, Kentucky, Michigan, 

Mississippi, Nebraska, Nevada, 

Oregon, Rhode Island, South 

Carolina, South Dakota, Virginia, 

Washington, West Virginia, and 

Wisconsin. 

● A soft check after C10Q14 (“What 

is the age of the oldest adult living 

in the household?”) was added to 

appear when the response to C10Q14 

was less than K9Q16 (the age of the 

mother-type in the household).

● To reduce respondent confusion, 

help text was added to the following 

questions that refer to behavior 

during “the past week” (K6Q60, 

K6Q61, K6Q63, K6Q64, K7Q38–

K7Q41, and K8Q11).

● The poverty category assigned, 

which depends on the state in which 

the respondent lives, was previously 

determined by the sampled state as a 

preload variable (STATE). An update 

was made so that the respondent’s 

reported state (K3_STATE) was used 

for the poverty category assignment 

as well as for the state-specific 

Medicaid and Children’s Health 

Insurance Program or CHIP program 

names.

● The following help text was 

added to K4Q35, where R is 

respondent and S.C. is sample child: 

“INTERVIEWER INSTRUCTION: 

IF R HAS ADOPTED S.C., SAY 

‘Please think about the time between 

adopting [S.C.] and up until the 

present day.’ ”

● Skip logic was added to K9Q19 so 

that the question was not asked when 

the respondent had legally adopted 

the sample child. 

● K7Q60 was updated to include 

the use of DVDs, and help text 

was added to accurately capture 

data: READ IF NECESSARY: Do 

not include time spent watching 

television shows, videos, or DVDs 

at school. READ IF NECESSARY: 

Do not include time spent doing 

any of these activities in front of a 

computer.

● The skip logic at K11Q59 was 

modified so that additional NSCH 

income follow-up questions 

(K11Q59 and K11Q59A) would not 

appear when the income cascade 

was completed in the National 

Immunization Survey (NIS–Child or 

NIS–Teen). 

● K2Q61C was modified to include 

response options in the text of the 

question. Additionally, help text was 

added for further clarification for the 

respondent.

● The word “ever” in K4Q36 was 

italicized for emphasis to increase 

respondent and interviewer clarity.

● The word “preventive” in both 

K4Q20 and K4Q21 was italicized for 

added emphasis and respondent and 

interviewer clarity. 

● To improve clarity in coding for 

interviewers, category headings 

(such as “Cost,” “Employment/

Moving,” “Eligibility,” “Application 

Process,” and “Other”) were added 

to long-response option lists at 

insurance section variables that ask 

the reasons why the sample child is 

not enrolled in an insurance type. 

The variables affected were K12Q01, 

K12Q14, K12Q17, K12Q24, K12Q27, 

K12Q36–K12Q38, K12Q45, K12Q55, 

and K12Q65.

● To align with the protocol for similar 

questions, the response options at 

K6Q73 and K6Q72 were made a 

mandatory read rather than “READ 

AS NECESSARY.” 

● The text “who visited your home” 

was added into the stem of the 

follow-up questions to K4Q35_

INTRO.

● For series of questions with identical 

response options, response options 

were read to the respondent for the 

first three questions in the series 

and then provided as “READ 

AS NECESSARY” text for the 

remaining questions. The following 

questions were edited so that they 

corresponded with this convention 

used throughout the survey: K6Q70–

K7Q79 and K7Q84–K7Q83.

● The word “things” in INTRO_ACE 

was changed to “events.” 

● The dash in ACE1 was replaced with 

“for example, it was.”

● The text “after [S.C.] was born” was 

added to the end of ACE5. 

● The text “guardians, or any other” 

was added to ACE6 for improved 

respondent understanding. 

● Help text was added to ACE11 to 

specify that the question is referring 

to racial or ethnic group. 

● The help text at K2Q35A was 

updated to more accurately describe 

the conditions referenced.

● The help text “ ‘REGULAR 

PHONES’ REFERS TO LANDLINE 

PHONES” was added to C11Q16.

Also on April 7, 2011 (Quarter 2, 

2011), the following changes were made 

to accommodate the newly adopted 

“take-all” cell-phone approach:
Page 170  Series 1, No. 59

● A question (SL_LANDLINE) 

was added for all cell-phone cases 

following Section 12 if not already 

answered in the NIS–Child or NIS–

Teen surveys.

● The lead-in text at C11Q15_CELL 

was edited to display only if the case 

did not receive SL_LANDLINE, 

where the same lead-in text appears.

● Skip logic was changed for C11Q16 

so that the question was administered 

only to cell-phone cases with a 

landline in the household or landline 

cases with at least one cell phone in 

the household.

● A question (SL_CELLUSE) was 

added to be administered to cellphone cases with a landline in the 

household or landline cases with at 

least one cell phone in the household 

that did not answer the question in 

either NIS survey.

● A modification was made to the 

skip logic surrounding C11Q20 to 

ensure that the question was not 

administered to cell phone-only 

households.

On July 7, 2011 (Quarter 3, 2011), 

the following changes were made: 

● To reduce interviewer miscodes, a 

soft check was added after C10Q02A 

to require the interviewer to confirm 

the respondent’s relationship to child 

if the relationship given at C10Q02A 

differed from the relationship given 

at the beginning of the interview at 

K1Q02. 

● Help text was added to K2Q35A.

● All questions mentioning “Autism 

or ASD” (K2Q35A_1, K2Q35D, 

K2Q35B, K2Q35C, K2Q35E, 

K2Q35F_INTRO, K2Q35G, 

K2Q35H_3, K2Q35J) were modified 

to clarify the question for both the 

respondent and the interviewer as 

follows:

○ “ASD” was changed to “autism 

spectrum disorder.”

○ Help text was added for 

the interviewer: “AUTISM 

SPECTRUM DISORDER 

INCLUDES AUTISTIC 

DISORDER, ASPERGER’S 

DISORDER, AND PERVASIVE 

DEVELOPMENTAL 

DISORDER.” 

● After reporting that the sample 

child had been diagnosed with 

certain conditions in Section 2, 

the respondent received followup questions for each diagnosis at 

the end of the section. To ease the 

transition for these questions, the 

following lead-in text was added to 

the first of the follow-up questions 

pertaining to each condition: “Earlier 

you told me that S.C. has been 

diagnosed with [condition] ... .” This 

affected the following variables: 

K2Q31A_1, K2Q32B, K2Q33B, 

K2Q34A_1, K2Q36A_1, K2Q60A_1, 

K2Q61A_1, K2Q37A_1, K2Q38A_1, 

K2Q38A_2, K2Q38B, K2Q38C, 

K2Q40B, K2Q41B, K2Q42B, 

K2Q43B, K2Q44A_1, K2Q45B, and 

K2Q46B.

● Wording changes were made to 

several questions in Section 11 to 

accommodate dialing in the U.S. 

Virgin Islands (USVI) for these 

cases.

○ The text “, including the Virgin 

Islands” was added to questions 

determining birth inside the 

United States or USVI for 

the mother-type, father-type, 

respondent (if not the mother 

or father), and sample child 

(K11Q30– K11Q33), and to 

questions determining how long 

the mother-type, father-type, 

respondent (if not the mother or 

father), and sample child have 

lived in the United States or USVI 

if born outside of the country 

(K11Q34A, K11Q35A, K11Q36A, 

K11Q37A).

○ The following help text was 

added to K11Q38: “IF S.C. 

WAS ADOPTED FROM THE 

UNITED STATES, CODE 

THIS QUESTION AS ‘NO.’ 

THE VIRGIN ISLANDS ARE 

CONSIDERED PART OF THE 

UNITED STATES.”

○ The text “, including the Virgin 

Islands” and “or Virgin Islands” 

was added to K11Q40: “Prior to 

being adopted, was [S.C.] in the 

legal custody of a state or county 

child welfare agency in the United 

States [IF IAP=095 DISPLAY, 

“including the Virgin Islands”]? 

That is, was [S.C.] in the U.S. [IF 

IAP=095 DISPLAY “or Virgin 

Islands”] foster care system?”

● Logic was added to K3_STATE to 

skip K3_STATE for USVI cases. 

● Skip logic was added to K11Q03 so 

that the question was not asked for 

USVI cases. 

● The following text was removed 

from MSG_AUG: “For most people, 

this will only take a few minutes.” 

● An experiment was conducted on 

cases released in Quarter 3, 2011, 

to determine the difference in 

language used in the time estimate 

of the survey length provided in the 

introduction. Logic and text were 

added so that respondents were 

randomly told either “half an hour” 

or “30 minutes.” Based on results of 

the experiment, all cases in Quarter 

4, 2011, and Quarter 1, 2012, were 

told “half an hour.”

● Spanish translations of state 

Temporary Assistance for Needy 

Families or TANF program names 

were edited with correct translations 

of “or” to “o” during a Spanish 

interview. 

On August 16, 2011, the following 

change was made:

● The telephone number given as 

a contact for questions about the 

survey at the closing script for 

augmentation sample cases that exit 

through the NIS flu module was 

updated to provide a unique number 

for NSCH-only cases.

On October 6, 2011 (Quarter 4, 

2011), the following changes were made: 

● To ease respondent confusion, 

help text was added to follow-up 

questions regarding being seen by a 

doctor or other health care provider 

in K5Q40–K5Q44.

● The Spanish versions of K6Q01–

K6Q09 were updated to more closely 

align with the standard Parents’ 

Evaluation of Developmental 

Status or PEDS text from which the 

questions originated.

● For cases that received both NIS and 

the State and Local Area Integrated 

Telephone Survey (SLAITS), when 
Series 1, No. 59  Page 171 

an eligible NIS child was rostered 

but the birth dates provided indicated 

that no NIS-eligible children were in 

the household, the case then received 

the NIS consent language and the 

full SLAITS consent language very 

close together. In such instances, the 

logic was modified so that shortened 

consent language was displayed 

(SCQ02 and SCQ04) rather than 

SL_INTRO.

On January 5, 2012 (Quarter 1, 

2012), the following changes were made: ● To assist the interviewer in capturing 

accurate data, help text was 

added to the following Section 12 

questions specifying if the question 

was referring to the mother-type 

in the household, father-type in 

the household, or respondent (if 

another relation to the sample child 

was reported): K12Q43–K12Q45, 

K12Q47, K12Q53– K12Q55, 

K12Q57, K12Q63–K12Q65, and 

K12Q67. 

● The fill logic at C11Q22 was updated 

so that a fill from the same question 

in the NIS–Child or NIS–Teen 

questionnaire was excluded if these 

variables have a value of “Don’t 

know” or “Refused.” For these cases, 

the question was asked again.

● The READ IF NECESSARY text 

at K6Q15 was edited to accurately 

define the age ranges for Individual 

Family Service Plan, or IFSP, and 

Individualized Education Program, 

or IEP, written interventions plans. 
Page 172  Series 1, No. 59

Appendix V. Program Names Used for Medicaid and Children’s Health 

Insurance Program Questions

For survey questions regarding 

Medicaid and Children’s Health 

Insurance Program (CHIP), the statespecific 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 III. 

States could be divided into two 

classes depending on how they named 

the expanded or created programs that 

use Title XXI funds. During 2011–2012, 

26 states had distinct Medicaid and 

CHIP (known as S–CHIP prior to 2011) 

programs and used different names for 

their CHIP programs compared with their 

Medicaid programs. The remaining 24 

states, as well as Washington, D.C., and 

U.S. Virgin Islands, had distinct Medicaid 

and CHIP programs but used the same 

name (or substantially similar names) for 

both programs. 

Eligibility for specific health 

insurance questions and the use of statespecific program names were based 

on this classification. Because a single 

question (K3Q02) was asked about both 

Medicaid and S-CHIP, survey analysts 

will not be able to distinguish between 

Medicaid and S-CHIP coverage in 

national or regional analyses. Analysts 

may be required to report on “public” 

insurance only. 

See footnotes at end of table.

Table III. State-specific program names for Medicaid and Children’s Health Insurance Program

Area

Type of 

program  Category1

Name used 

with Medicaid 

questions

Name used 

with CHIP 

questions

Name used 

with combination 

questions

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Patient 1st or SOBRA ALL Kids ...

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... Denali KidCare

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Arizona Health Care 

Cost Containment 

System (AHCCCS) 

or SOBRA

KidsCare ...

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... ARKids 

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

Colorado . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Child Health Plan 

Plus (CHP+)

...

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . Separate C ... ... HUSKY Health or 

Medical Assistance

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Diamond State 

Health Plan

Delaware Healthy 

Children Program

...

District of Columbia . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... DC Healthy Families or 

Medical Assistance

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A ... Florida KidCare, 

which includes 

Healthy Kids and 

MediKids

...

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Right from the

Start 

PeachCare for Kids ...

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... Hawaii QUEST

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Medical Assistance Idaho Children’s 

Health Insurance 

Program (CHIP)

...

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... All Kids or Medical 

Assistance

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... Hoosier Healthwise

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Medical Assistance Healthy and Well 

Kids in Iowa (HAWK-I)

...

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate C ... ... HealthWave or Kansas 

Medical Assistance 

Program (KMAP)

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... KyHealth Choices or 

Family Choices or 

Kentucky Children’s 

Health Insurance 

Program (KCHIP)
Series 1, No. 59  Page 173 

Table III. State-specific program names for Medicaid and Children’s Health Insurance Program—Con.

Area

Type of

program  Category1

Name used

with Medicaid

questions

Name used 

with CHIP

questions

Name used 

with combination

questions

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A ... Louisiana Children’s 

Health Insurance 

Program (LaCHIP)

...

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... MaineCare 

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Maryland Medical 

Assistance

Maryland Children’s 

Health Insurance 

Program (MCHP)

...

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

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Healthy Kids or 

Medical Assistance

MIChild ...

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... Medical Assistance or 

MinnesotaCare

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Medical Assistance Mississippi Children’s 

Health Insurance 

Program (CHIP)

...

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... MO HealthNet for Kids

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate C ... ... Healthy Montana Kids 

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... Kids Connection or 

Medical Assistance

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Child Health 

Assurance 

Program (CHAP)

Nevada Check Up ...

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

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... NJ FamilyCare

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... New Mexico SALUD! 

or New MexiKids/New 

MexiTeens

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Child Health Plus ...

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Health Choice for 

Children 

...

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . Combination A ... Healthy Steps ...

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medicaid expansion C ... ... Healthy Start and 

Healthy Families

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... SoonerCare

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate C ... ... Oregon Healthy 

Kids or Oregon 

Health Plan

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Pennsylvania 

Children’s Health 

Insurance Program 

(CHIP)

...

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... RIteCare or 

Rhode Island 

Medical Assistance 

Program

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... Healthy Connections 

Kids or Partners for 

Healthy Children

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . Combination A Medical Assistance South Dakota 

Children’s Health 

Insurance Program 

(CHIP)

...

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination A TennCare Tennessee 

CoverKids 

...

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Children’s Medicaid Texas Children’s 

Health Insurance 

Program (CHIP)

...

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Utah Children’s Health 

Insurance Program 

(CHIP)

...

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A ... Dr. Dynasaur ...

See footnotes at end of table.
Page 174  Series 1, No. 59

Table III. State-specific program names for Medicaid and Children’s Health Insurance Program—Con.

Area

Type of

program  Category1

Name used

with Medicaid

questions

Name used 

with CHIP

questions

Name used 

with combination

questions

Virginia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... FAMIS

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . Separate C ... ... Apple Health for 

Kids or Basic 

Health Plus

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Medical Assistance West Virginia 

Children’s Health 

Insurance Program 

(WVCHIP)

...

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combination C ... ... BadgerCare 

Plus or Medical 

Assistance 

or Healthy Start

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Separate A Equality Care Wyoming Kid Care 

or Kid Care CHIP

...

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . ... C ... ... Medical Assistance 

Program (MAP)

... Category not applicable.

1States in category A had separate programs for Medicaid and CHIP and used different names for CHIP than for their Medicaid programs. States in category C had separate programs for Medicaid and 

CHIP, but they used the same (or substantially similar) name for both programs. For all cases, a single question about public insurance coverage was asked using the program name(s).

NOTE: CHIP is Children’s Health Insurance Program.
Series 1, No. 59  Page 175 

Appendix VI. Program Names Used for Questions on Temporary 

Assistance for Needy Families

When respondents were asked 

if their household received any cash 

assistance from a state or county welfare 

program within the past year (K11Q60), 

state-specific Temporary Assistance for 

Needy Families (TANF) program names 

were included in the question text, in case 

respondents recognized the state program 

name but not the welfare program 

affiliation. TANF program names are 

shown in Table IV.

Table IV. State-specific program names for Temporary Assistance for Needy Families

Area TANF program name

Alabama . . . . . . . . . . . . . . . . . . . . . . . Family Assistance Program

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . Alaska Temporary Assistance Program (ATAP)

Arizona . . . . . . . . . . . . . . . . . . . . . . . . Employing and Moving People off Welfare and Encouraging 

Responsibility (EMPOWER)

Arkansas. . . . . . . . . . . . . . . . . . . . . . . Transitional Employment Assistance (TEA)

California . . . . . . . . . . . . . . . . . . . . . . California Work Opportunity and Responsibility to Kids (CalWORKS)

Colorado. . . . . . . . . . . . . . . . . . . . . . . Colorado Works 

Connecticut. . . . . . . . . . . . . . . . . . . . . Jobs First 

Delaware. . . . . . . . . . . . . . . . . . . . . . . A Better Chance (ABC)

District of Columbia . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Florida. . . . . . . . . . . . . . . . . . . . . . . . . Welfare Transition Program 

Georgia. . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Families in Idaho (TAFI)

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families(TANF) 

Indiana. . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . Family Investment Program (FIP)

Kansas. . . . . . . . . . . . . . . . . . . . . . . . Kansas Works 

Kentucky. . . . . . . . . . . . . . . . . . . . . . . Kentucky Transitional Assistance Program (K–TAP)

Louisiana . . . . . . . . . . . . . . . . . . . . . . Family Independence Temporary Assistance Program (FITAP)

Maine. . . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Maryland. . . . . . . . . . . . . . . . . . . . . . . Family Investment Program (FIP)

Massachusetts. . . . . . . . . . . . . . . . . . Transitional Aid to Families with Dependent Children (TAFDC)

Michigan . . . . . . . . . . . . . . . . . . . . . . . Family Independence Program (FIP)

Minnesota. . . . . . . . . . . . . . . . . . . . . . Minnesota Family Investment Program (MFIP)

Mississippi . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Missouri . . . . . . . . . . . . . . . . . . . . . . . Beyond Welfare 

Montana. . . . . . . . . . . . . . . . . . . . . . . Families Achieving Independence in Montana (FAIM)

Nebraska . . . . . . . . . . . . . . . . . . . . . . Employment First 

Nevada . . . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

New Hampshire . . . . . . . . . . . . . . . . . Family Assistance Program (FAP) or New Hampshire Employment 

Program (NHEP)

New Jersey . . . . . . . . . . . . . . . . . . . . . WorkFirst NJ 

New Mexico . . . . . . . . . . . . . . . . . . . . NMWorks 

New York. . . . . . . . . . . . . . . . . . . . . . . Family Assistance Program (FAP)

North Carolina . . . . . . . . . . . . . . . . . . Work First 

North Dakota . . . . . . . . . . . . . . . . . . . Training, Employment, and Education Management (TEEM)

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . Ohio Works First (OWF)

Oklahoma . . . . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF) 

Oregon. . . . . . . . . . . . . . . . . . . . . . . . Jobs Opportunity and Basic Skills (JOBS) 

Pennsylvania. . . . . . . . . . . . . . . . . . . . Pennsylvania Temporary Assistance for Needy Families (TANF)

Rhode Island . . . . . . . . . . . . . . . . . . . Family Independence Program (FIP)

South Carolina . . . . . . . . . . . . . . . . . . Family Independence 

South Dakota . . . . . . . . . . . . . . . . . . . Temporary Assistance for Needy Families (TANF)

Tennessee . . . . . . . . . . . . . . . . . . . . . Families First 

Texas . . . . . . . . . . . . . . . . . . . . . . . . . Texas Works 

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . Family Employment Program (FEP)

Vermont . . . . . . . . . . . . . . . . . . . . . . . Aid to Needy Families with Children (ANFC)

Virginia. . . . . . . . . . . . . . . . . . . . . . . . Virginia Initiative for Employment Not Welfare (VIEW)

Washington. . . . . . . . . . . . . . . . . . . . . WorkFirst 

West Virginia. . . . . . . . . . . . . . . . . . . . WV Works 

Wisconsin . . . . . . . . . . . . . . . . . . . . . . Wisconsin Works (W–2)

Wyoming. . . . . . . . . . . . . . . . . . . . . . . Personal Opportunities With Employment Responsibilities (POWER)

U.S. Virgin Islands. . . . . . . . . . . . . . . . Family Improvement Program (FIP)

NOTE: TANF is Temporary Assistance for Needy Families.
Page 176  Series 1, No. 59

Appendix VII. Procedures for Assigning Household Poverty Status

The U.S. Department of Health and 

Human Services (HHS) publishes federal 

poverty guidelines for the determination 

of household poverty status, available 

from: https://aspe.hhs.gov/poverty. 

These guidelines are produced annually 

and developed separately for the 48 

contiguous states plus Washington, D.C. 

(D.C.), Alaska, and Hawaii. 

The 2011–2012 National Survey 

of Children’s Health (NSCH) used the 

HHS guidelines to assign poverty status. 

Year 2011 guidelines (Table V for the 48 

contiguous states and D.C., Table VI for 

Alaska, and Table VII for Hawaii) were 

used with 2010 income for interviews 

conducted from February 28, 2011, 

through February 8, 2012. Year 2012 

guidelines (Tables VIII, IX, and X) were 

used with 2011 income for interviews 

conducted from February 9, 2012, 

through June 25, 2012. 

The tables were used to group 

households into the following poverty 

status categories:

● Category AA—At or below 50% 

poverty level

● Category A—Above 50% up to and 

including 100% poverty level

● Category B—Above 100% up to and 

including 138% poverty level

● Category C—Above 138% up to and 

including 150% poverty level

Table V. Year 2011 Federal Poverty Guidelines for families in the 48 contiguous states and Washington, D.C.

Family size

Percent of federal poverty level and status category

50 100 138 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $7,355 14,710 20,300 22,065 27,214 29,420 44,130 58,840 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $9,265 18,530 25,571 27,795 34,281 37,060 55,590 74,120 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $11,175 22,350 30,843 33,525 41,348 44,700 67,050 89,400 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $13,085 26,170 36,115 39,255 48,415 52,340 78,510 104,680 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $14,995 29,990 41,386 44,985 55,482 59,980 89,970 119,960 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $16,905 33,810 46,658 50,715 62,549 67,620 101,430 135,240 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $18,815 37,630 51,929 56,445 69,616 75,260 112,890 150,520 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $20,725 41,450 57,201 62,175 76,683 82,900 124,350 165,800 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $22,635 45,270 62,473 67,905 83,750 90,540 135,810 181,080 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $24,545 49,090 67,744 73,635 90,817 98,180 147,270 196,360 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $26,455 52,910 73,016 79,365 97,884 105,820 158,730 211,640 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $28,365 56,730 78,287 85,095 104,951 113,460 170,190 226,920 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $30,275 60,550 83,559 90,825 112,018 121,100 181,650 242,200 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $32,185 64,370 88,831 96,555 119,085 128,740 193,110 257,480 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $34,095 68,190 94,102 102,285 126,152 136,380 204,570 272,760 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $36,005 72,010 99,374 108,015 133,219 144,020 216,030 288,040 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $37,915 75,830 104,645 113,745 140,286 151,660 227,490 303,320 

NOTE: See Appendix VII for full definitions of poverty status categories.

Table VI. Year 2011 Federal Poverty Guidelines for families in Alaska

Family size

Percent of federal poverty level and status category

50 100 133 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $9,190 18,380 25,364 27,570 34,003 36,760 55,140 73,520 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $11,580 23,160 31,961 34,740 42,846 46,320 69,480 92,640 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $13,970 27,940 38,557 41,910 51,689 55,880 83,820 111,760 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $16,360 32,720 45,154 49,080 60,532 65,440 98,160 130,880 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $18,750 37,500 51,750 56,250 69,375 75,000 112,500 150,000 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $21,140 42,280 58,346 63,420 78,218 84,560 126,840 169,120 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $23,530 47,060 64,943 70,590 87,061 94,120 141,180 188,240 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $25,920 51,840 71,539 77,760 95,904 103,680 155,520 207,360 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $28,310 56,620 78,136 84,930 104,747 113,240 169,860 226,480 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $30,700 61,400 84,732 92,100 113,590 122,800 184,200 245,600 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $33,090 66,180 91,328 99,270 122,433 132,360 198,540 264,720 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $35,480 70,960 97,925 106,440 131,276 141,920 212,880 283,840 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $37,870 75,740 104,521 113,610 140,119 151,480 227,220 302,960 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $40,260 80,520 111,118 120,780 148,962 161,040 241,560 322,080 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $42,650 85,300 117,714 127,950 157,805 170,600 255,900 341,200 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $45,040 90,080 124,310 135,120 166,648 180,160 270,240 360,320 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $47,430 94,860 130,907 142,290 175,491 189,720 284,580 379,440 

NOTE: See Appendix VII for full definitions of poverty status categories.
Series 1, No. 59  Page 177 

● Category D—Above 150% up to and 

including 185% poverty level

● Category E—Above 185% up to and 

including 200% poverty level

● Category F—Above 200% up to and 

including 300% poverty level

● Category G—Above 300% up to and 

including 400% poverty level

● Category H—Above 400% poverty 

level

Two variables were used to 

determine an NSCH household’s poverty 

status: the number of people residing 

in the household and the household’s 

income during the prior year. Income 

data were gathered using one of three 

methods during NSCH administration: 

A respondent could provide 1) an exact 

income, 2) an income range based on 

a closed-ended series of questions, 

or 3) an income range using a set of 

cascade questions revised to allow exact 

determination of household poverty status 

in cases where that would not otherwise 

be possible. A brief description of each 

method and the household poverty status 

assignment process follows: 

Respondent reported exact 

income—Poverty status was assigned 

by comparing the number of household 

members and the exact income reported 

with the appropriate guidelines table. 

Respondent reported income 

range based on a closed-ended series 

of questions—When respondents did 

not supply a specific dollar amount for 

household income, a series of questions 

was asked on whether the household 

income was below, exactly at, or above 

threshold amounts. A matrix was then 

created to categorize responses. Each cell 

Table VII. Year 2011 Federal Poverty Guidelines for families in Hawaii

Family size

Percent of federal poverty level and status category

50 100 133 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $8,465 16,930 23,363 25,395 31,321 33,860 50,790 67,720 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10,660 21,320 29,422 31,980 39,442 42,640 63,960 85,280 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $12,855 25,710 35,480 38,565 47,564 51,420 77,130 102,840 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $15,050 30,100 41,538 45,150 55,685 60,200 90,300 120,400 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $17,245 34,490 47,596 51,735 63,807 68,980 103,470 137,960 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $19,440 38,880 53,654 58,320 71,928 77,760 116,640 155,520 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $21,635 43,270 59,713 64,905 80,050 86,540 129,810 173,080 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $23,830 47,660 65,771 71,490 88,171 95,320 142,980 190,640 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $26,025 52,050 71,829 78,075 96,293 104,100 156,150 208,200 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $28,220 56,440 77,887 84,660 104,414 112,880 169,320 225,760 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $30,415 60,830 83,945 91,245 112,536 121,660 182,490 243,320 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $32,610 65,220 90,004 97,830 120,657 130,440 195,660 260,880 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $34,805 69,610 96,062 104,415 128,779 139,220 208,830 278,440 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $37,000 74,000 102,120 111,000 136,900 148,000 222,000 296,000 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $39,195 78,390 108,178 117,585 145,022 156,780 235,170 313,560 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $41,390 82,780 114,236 124,170 153,143 165,560 248,340 331,120 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $43,585 87,170 120,295 130,755 161,265 174,340 261,510 348,680 

NOTE: See Appendix VII for full definitions of poverty status categories.

Table VIII. Year 2012 Federal Poverty Guidelines for families in the 48 contiguous states and Washington, D.C.

Family size

Percent of federal poverty level and status category

50 100 133 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $7,565 15,130 20,879 22,695 27,991 30,260 45,390 60,520 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $9,545 19,090 26,344 28,635 35,317 38,180 57,270 76,360 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $11,525 23,050 31,809 34,575 42,643 46,100 69,150 92,200 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $13,505 27,010 37,274 40,515 49,969 54,020 81,030 108,040 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $15,485 30,970 42,739 46,455 57,295 61,940 92,910 123,880 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $17,465 34,930 48,203 52,395 64,621 69,860 104,790 139,720 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $19,445 38,890 53,668 58,335 71,947 77,780 116,670 155,560 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $21,425 42,850 59,133 64,275 79,273 85,700 128,550 171,400 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $23,405 46,810 64,598 70,215 86,599 93,620 140,430 187,240 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $25,385 50,770 70,063 76,155 93,925 101,540 152,310 203,080 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $27,365 54,730 75,527 82,095 101,251 109,460 164,190 218,920 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $29,345 58,690 80,992 88,035 108,577 117,380 176,070 234,760 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $31,325 62,650 86,457 93,975 115,903 125,300 187,950 250,600 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $33,305 66,610 91,922 99,915 123,229 133,220 199,830 266,440 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $35,285 70,570 97,387 105,855 130,555 141,140 211,710 282,280 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $37,265 74,530 102,851 111,795 137,881 149,060 223,590 298,120 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $39,245 78,490 108,316 117,735 145,207 156,980 235,470 313,960 

NOTE: See Appendix VII for full definitions of poverty status categories.
Page 178  Series 1, No. 59

in the matrix was assigned to one of the 

following income categories:

● Less than $7,500

● $7,500–$9,999

● $10,000–$12,499

● $12,500–$14,999

● $15,000–$17,499

● $17,500–$19,999

● $20,000–$24,999

● $25,000–$29,999

● $30,000–$34,999

● $35,000–$39,999

● $40,000–$44,999

● $45,000–$49,999

● $50,000–$59,999

● $60,000–$74,999

● $75,000 or higher

Respondents who went through 

the cascade of income questions were 

assigned a household poverty status by 

comparing the number of household 

members and the assigned income range 

with the appropriate guidelines table. 

For example, a respondent living in 

Alaska reporting a household size of 

three persons and an income (based on 

Table X. Year 2012 Federal Poverty Guidelines for families in Hawaii

Family size

Percent of federal poverty level and status category

50 100 133 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $8,705 17,410 24,026 26,115 32,209 34,820 52,230 69,640 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10,980 21,960 30,305 32,940 40,626 43,920 65,880 87,840 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $13,255 26,510 36,584 39,765 49,044 53,020 79,530 106,040 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $15,530 31,060 42,863 46,590 57,461 62,120 93,180 124,240 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $17,805 35,610 49,142 53,415 65,879 71,220 106,830 142,440 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $20,080 40,160 55,421 60,240 74,296 80,320 120,480 160,640 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $22,355 44,710 61,700 67,065 82,714 89,420 134,130 178,840 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $24,630 49,260 67,979 73,890 91,131 98,520 147,780 197,040 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $26,905 53,810 74,258 80,715 99,549 107,620 161,430 215,240 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $29,180 58,360 80,537 87,540 107,966 116,720 175,080 233,440 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $31,455 62,910 86,816 94,365 116,384 125,820 188,730 251,640 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $33,730 67,460 93,095 101,190 124,801 134,920 202,380 269,840 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $36,005 72,010 99,374 108,015 133,219 144,020 216,030 288,040 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $38,280 76,560 105,653 114,840 141,636 153,120 229,680 306,240 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $40,555 81,110 111,932 121,665 150,054 162,220 243,330 324,440 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $42,830 85,660 118,211 128,490 158,471 171,320 256,980 342,640 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $45,105 90,210 124,490 135,315 166,889 180,420 270,630 360,840 

NOTE: See Appendix VII for full definitions of poverty status categories.

Table IX. Year 2012 Federal Poverty Guidelines for families in Alaska

Family size

Percent of federal poverty level and status category

50 100 133 150 185 200 300 400

AA A B C D E F G

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $9,460 18,920 26,110 28,380 35,002 37,840 56,760 75,680 

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $11,935 23,870 32,941 35,805 44,160 47,740 71,610 95,480 

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $14,410 28,820 39,772 43,230 53,317 57,640 86,460 115,280 

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $16,885 33,770 46,603 50,655 62,475 67,540 101,310 135,080 

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $19,360 38,720 53,434 58,080 71,632 77,440 116,160 154,880 

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $21,835 43,670 60,265 65,505 80,790 87,340 131,010 174,680 

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $24,310 48,620 67,096 72,930 89,947 97,240 145,860 194,480 

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $26,785 53,570 73,927 80,355 99,105 107,140 160,710 214,280 

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $29,260 58,520 80,758 87,780 108,262 117,040 175,560 234,080 

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $31,735 63,470 87,589 95,205 117,420 126,940 190,410 253,880 

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $34,210 68,420 94,420 102,630 126,577 136,840 205,260 273,680 

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $36,685 73,370 101,251 110,055 135,735 146,740 220,110 293,480 

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $39,160 78,320 108,082 117,480 144,892 156,640 234,960 313,280 

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $41,635 83,270 114,913 124,905 154,050 166,540 249,810 333,080 

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $44,110 88,220 121,744 132,330 163,207 176,440 264,660 352,880 

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $46,585 93,170 128,575 139,755 172,365 186,340 279,510 372,680 

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $49,060 98,120 135,406 147,180 181,522 196,240 294,360 392,480 

NOTE: See Appendix VII for full definitions of poverty status categories.

the cascade) of $35,000–$39,000 would 

be classified into Category D (above 

150% up to and including 185% of 

poverty level), based on the 2011 federal 

guidelines in Table VI. When respondents 

did not complete the income cascade, 

either because they refused or did not 

know the answer to one of the cascade 

questions, household poverty status could 

not be assigned. 

Respondent reported income range 

based on revised series of cascade 

questions—In some cases, the income 

categories described above encompassed 
Series 1, No. 59  Page 179 

one or more income category limits for 

determining household poverty status. 

In such cases, additional income cascade 

questions beyond the standard set were 

asked to permit definitive assignment 

of poverty status. For these questions, 

customized income reference values, 

based on household size and state of 

residence, were used to obtain a range 

that would fit into the poverty-level table. 

For example, the income category cutoff 

indicating that a two-person household in 

the contiguous 48 states was below 150% 

poverty level (using the 2011 guidelines) 

was $22,065. This income category 

cutoff is encompassed in the income 

category of “$25,000 or less.” Therefore, 

for respondents who went through the 

cascade and reported income less than 

$25,000, an additional cascade question 

asked whether the household was above, 

at, or below $22,100 (based on rounding 

rules described in the notes to the poverty 

guideline tables). If the household 

reported an income below $22,100 but 

above $20,000, their assigned household 

poverty status would be Category C 

(below 150% poverty level). 

Using HHS guidelines, tables were 

developed to provide reference values for 

the additional income cascade questions. 

Reference values using the 2011 

guidelines are presented in Tables XI, 

XII, and XIII. Reference values using the 

2012 guidelines are presented in Tables 

XIV, XV, and XVI.

Table XI. Year 2011 reference table for additional income cascade questions for families in the 48 contiguous states and Washington, D.C.

Family 

size

 Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA A A A B B 22,100 27,200 F F F G 58,800 H H

3 . . . . . . . . AA AA A A A 18,500 B 27,800 D 37,100 F F 55,600 G H

4 . . . . . . . . AA AA 11,200 A A A 22,400 B 33,500 D 41,300 F F 67,000 90,000 

5 . . . . . . . . AA AA AA A A A A 26,200 B 36,100 D 48,400 52,300 F 80,000/

105,000

6 . . . . . . . . AA AA AA AA A A A A B B 41,400 D 55,500 F 90,000/

120,000

7 . . . . . . . . AA AA AA AA 16,900 A A A 33,800 B B 46,700 D 62,500/ 

67,600

100,000/

135,000

8 . . . . . . . . AA AA AA AA AA 18,800 A A A 37,600 B B 51,900/ 

56,400

69,600 115,000/

150,000

9 . . . . . . . . AA AA AA AA AA AA A A A A 41,500 B 57,200 62,200 85,000/

125,000

10 . . . . . . . AA AA AA AA AA AA 22,600 A A A A B B 62,500/ 

67,900

90,000/

135,000

11 . . . . . . . AA AA AA AA AA AA AA A A A A A B 67,700/ 

73,600

100,000/

150,000

12 . . . . . . . AA AA AA AA AA AA AA 26,500 A A A A 52,900 73,000 105,000/

160,000

13 . . . . . . . AA AA AA AA AA AA AA 28,400 A A A A 56,700 B 115,000/

170,000

14 . . . . . . . AA AA AA AA AA AA AA AA A A A A A B 120,000/

180,000

15 . . . . . . . AA AA AA AA AA AA AA AA 32,200 A A A A 64,400 130,000/

195,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA A A A A 68,200 135,000/

205,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA 36,000 A A A 72,000 145,000/

215,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA 37,900 A A A A 150,000/

225,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Page 180  Series 1, No. 59

Table XII. Year 2011 reference table for additional income cascade questions for families in Alaska

Family 

size

Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA AA A A A 18,400 B 27,600 34,000 36,800 F F 55,100 73,500 H

3 . . . . . . . . AA AA 11,600 A A A 23,200 B 32,000 D 42,800 46,300 F 69,500 95,000 

4 . . . . . . . . AA AA AA 14,000 A A A 27,900 B 38,600 41,900 D 51,700/ 

55,900

F 85,000/

110,000

5 . . . . . . . . AA AA AA AA 16,400 A A A 32,700 B B C D 65,400 100,000/ 

130,000

6 . . . . . . . . AA AA AA AA AA 18,800 A A A 37,500 B B 51,800/ 

56,300

69,400 115,000/ 

150,000

7 . . . . . . . . AA AA AA AA AA AA 21,100 A A A 42,300 B 58,300 63,400 85,000/ 

125,000

8 . . . . . . . . AA AA AA AA AA AA 23,500 A A A A 47,100 B 64,900/ 

70,600

95,000/ 

140,000

9 . . . . . . . . AA AA AA AA AA AA AA 25,900 A A A A 51,800 71,500 105,000/ 

155,000

10 . . . . . . . AA AA AA AA AA AA AA 28,300 A A A A 56,600 B 115,000/ 

170,000

11 . . . . . . . AA AA AA AA AA AA AA AA A A A A A 61,400 125,000/ 

185,000

12 . . . . . . . AA AA AA AA AA AA AA AA 33,100 A A A A 66,200 130,000/ 

200,000

13 . . . . . . . AA AA AA AA AA AA AA AA AA A A A A 71,000 140,000/ 

215,000

14 . . . . . . . AA AA AA AA AA AA AA AA AA 37,900 A A A A 150,000/ 

225,000

15 . . . . . . . AA AA AA AA AA AA AA AA AA AA A A A A 160,000/ 

240,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA AA 42,700 A A A 170,000/ 

255,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA A A A 180,000/ 

270,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA 47,400 A A 190,000/ 

285,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Series 1, No. 59  Page 181 

Table XIII. Year 2011 reference table for additional income cascade questions for families in Hawaii

Family 

size

Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA 8,500 A A 16,900 B 23,400 D 31,300/ 

33,900

F F F G 67,700 H

3 . . . . . . . . AA AA A A A A 21,300 B 32,000 D 42,600 F F 64,000 85,000 

4 . . . . . . . . AA AA AA A A A A B B 38,600 D 47,600 51,400 F 105,000 

5 . . . . . . . . AA AA AA AA A A A A B B 41,500 D 55,700 F 90,000/ 

120,000

6 . . . . . . . . AA AA AA AA AA A A A A B B 47,600 51,700 63,800/ 

69,000

105,000/ 

140,000

7 . . . . . . . . AA AA AA AA AA AA A A A 39,000 B B 53,700/ 

58,300

71,900 80,000/ 

115,000

8 . . . . . . . . AA AA AA AA AA AA 21,600 A A A 43,300 B B 64,900 85,000/ 

130,000

9 . . . . . . . . AA AA AA AA AA AA 23,800 A A A A 47,700 B 65,800/ 

71,500

95,000/ 

145,000

10 . . . . . . . AA AA AA AA AA AA AA 26,000 A A A A 52,000 71,800 105,000/ 

155,000

11 . . . . . . . AA AA AA AA AA AA AA 28,200 A A A A 56,400 B 115,000/ 

170,000

12 . . . . . . . AA AA AA AA AA AA AA AA A A A A A B 120,000/ 

180,000

13 . . . . . . . AA AA AA AA AA AA AA AA 32,600 A A A A 65,200 130,000/ 

195,000

14 . . . . . . . AA AA AA AA AA AA AA AA AA A A A A 69,600 140,000/ 

210,000

15 . . . . . . . AA AA AA AA AA AA AA AA AA 37,000 A A A 74,000 150,000/ 

220,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA AA A A A A 155,000/ 

235,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA AA 41,400 A A A 165,000/ 

250,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA AA 43,600 A A A 175,000/ 

260,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Page 182  Series 1, No. 59

Table XIV. Year 2012 reference table for additional income cascade questions for families in the 48 contiguous states and Washington, D.C.

Family 

size

Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA A A A B B 22,700 28,000 F F F G G H H

3 . . . . . . . . AA AA A A A 19,100 B 26,300/ 

28,600

D 38,200 F F 57,300 G H

4 . . . . . . . . AA AA 11,500 A A A 23,000 B 31,800 D 42,600 46,100 F 69,200 90,000 

5 . . . . . . . . AA AA AA 13,500 A A A 27,000 B 37,300 D D 54,000 F 80,000/ 

11,0000

6 . . . . . . . . AA AA AA AA A A A A 31,000 B 42,700 46,500 57,300 61,900 95,000/ 

125,000

7 . . . . . . . . AA AA AA AA AA A A A A B B 48,200 52,400 64,600/ 

69,900

105,000/ 

140,000

8 . . . . . . . . AA AA AA AA AA AA A A A 38,900 B B 53,700/ 

58,300

71,900 115,000/ 

155,000

9 . . . . . . . . AA AA AA AA AA AA 21,400 A A A 42,900 B B 64,300 85,000/ 

130,000

10 . . . . . . . AA AA AA AA AA AA 23,400 A A A A 46,800 B 64,600/ 

70,200

95,000/ 

140,000

11 . . . . . . . AA AA AA AA AA AA AA A A A A A B 70,000 100,000/ 

150,000

12 . . . . . . . AA AA AA AA AA AA AA 27,400 A A A A 54,700 B 110,000/ 

165,000

13 . . . . . . . AA AA AA AA AA AA AA AA A A A A 58,700 B 120,000/ 

175,000

14 . . . . . . . AA AA AA AA AA AA AA AA 31,300 A A A A 62,700 125,000/ 

190,000

15 . . . . . . . AA AA AA AA AA AA AA AA 33,300 A A A A 66,600 135,000/ 

200,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA A A A A 70,600 140,000/ 

210,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA 37,300 A A A A 150,000/ 

225,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA AA A A A A 155,000/ 

235,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Series 1, No. 59  Page 183 

Table XV. Year 2012 reference table for additional income cascade questions for families in Alaska

Family 

size

Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA AA A A A 18,900 B 26,100/ 

28,400

D 37,800 F F 56,800 G H

3 . . . . . . . . AA AA 11,900 A A A 23,900 B 32,900 D D 47,700 F 71,600 95,000 

4 . . . . . . . . AA AA AA AA A A A 28,800 B B 43,200 D 53,300/ 

57,600

F 85,000/ 

115,000

5 . . . . . . . . AA AA AA AA 16,900 A A A 33,800 B B 46,600 D 62,500/ 

67,500

100,000/ 

135,000

6 . . . . . . . . AA AA AA AA AA AA A A A 38,700 B B 53,400/ 

58,000

71,600 115,000/ 

155,000

7 . . . . . . . . AA AA AA AA AA AA 21,800 A A A 43,700 B B 65,500 85,000/ 

130,000

8 . . . . . . . . AA AA AA AA AA AA AA A A A A 48,600 B 67,000/ 

72,900

95,000/ 

145,000

9 . . . . . . . . AA AA AA AA AA AA AA 26,800 A A A A 53,600 73,900 105,000/ 

160,000

10 . . . . . . . AA AA AA AA AA AA AA AA A A A A 58,500 B 115,000/ 

175,000

11 . . . . . . . AA AA AA AA AA AA AA AA 31,700 A A A A 63,500 125,000/ 

190,000

12 . . . . . . . AA AA AA AA AA AA AA AA AA A A A A 68,400 135,000/ 

205,000

13 . . . . . . . AA AA AA AA AA AA AA AA AA 36,700 A A A 73,400 145,000/ 

220,000

14 . . . . . . . AA AA AA AA AA AA AA AA AA AA A A A A 155,000/ 

235,000

15 . . . . . . . AA AA AA AA AA AA AA AA AA AA 41,600 A A A 165,000/ 

250,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA A A A 175,000/ 

265,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA 46,600 A A 185,000/ 

280,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA AA A A 195,000/ 

295,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Page 184  Series 1, No. 59

Table XVI. Year 2012 reference table for additional income cascade questions for families in Hawaii

Family 

size

Reported range of household income

Less than 

$7,500

$7,500–

$9,999

$10,000–

$12,499

$12,500–

$14,999

$15,000–

$17,499

$17,500–

$19,999

$20,000–

$24,999

$25,000–

$29,999

$30,000–

$34,999

$35,000–

$39,999

$40,000–

$44,999

$45,000–

$49,999

$50,000–

$59,999

$60,000–

$74,999

$75,000 

and over

2 . . . . . . . . AA 8,700 A A A B 24,000 26,100 32,200 F F F 52,200 69,600 H

3 . . . . . . . . AA AA 11,000 A A A 22,000 B 32,900 D 43,900 F F 65,900 90,000 

4 . . . . . . . . AA AA AA 13,300 A A A 26,500 B 36,900 D 49,000 53,000 F 80,000/ 

105,000

5 . . . . . . . . AA AA AA AA A A A A 31,100 B 42,900 46,600 57,500 62,100 95,000/ 

125,000

6 . . . . . . . . AA AA AA AA AA A A A A B B B 53,400 65,900/ 

71,200

105,000/ 

140,000

7 . . . . . . . . AA AA AA AA AA AA A A A A B B 55,400 D 80,000/ 

120,000

8 . . . . . . . . AA AA AA AA AA AA 22,400 A A A A B B 61,700/ 

67,100

90,000/ 

135,000

9 . . . . . . . . AA AA AA AA AA AA AA A A A A A B 68,000/ 

73,900

100,000/ 

150,000

10 . . . . . . . AA AA AA AA AA AA AA 26,900 A A A A 53,800 B 110,000/ 

160,000

11 . . . . . . . AA AA AA AA AA AA AA AA A A A A 58,400 B 115,000/ 

175,000

12 . . . . . . . AA AA AA AA AA AA AA AA 31,500 A A A A 62,900 125,000/ 

190,000

13 . . . . . . . AA AA AA AA AA AA AA AA 33,700 A A A A 67,500 135,000/ 

200,000

14 . . . . . . . AA AA AA AA AA AA AA AA AA 36,000 A A A 72,000 145,000/ 

215000

15 . . . . . . . AA AA AA AA AA AA AA AA AA 38,300 A A A A 155,000/ 

230,000

16 . . . . . . . AA AA AA AA AA AA AA AA AA AA A A A A 160,000/ 

245,000

17 . . . . . . . AA AA AA AA AA AA AA AA AA AA 42,800 A A A 170,000/ 

255,000

18 . . . . . . . AA AA AA AA AA AA AA AA AA AA AA A A A 180,000/ 

270,000

NOTES: When the reported range of household income was included within two or more poverty ranges, additional questions (K11Q59 and K11Q59A) were asked to determine the poverty range 

for the household. Values in this table represent the border between two poverty ranges. Additional income questions were asked with such values (“Would you say this income was above or below 

[value]?”) to identify the proper poverty range for the household. Values were rounded to the nearest $100 if income was below $75,000, and to the nearest $5,000 if income was over $75,000. The 

additional income questions were not asked if the value (i.e., the range border) was less than $900 from either endpoint of the reported range of household income. Letters in this table signify that the 

reported range of household income was entirely within one poverty range; see Appendix VII for full definitions of poverty status categories.
Series 1, No. 59  Page 185 

Appendix VIII. Letters Sent to Sampled Households

The letters sent to sampled households for the National Survey of Children’s Health (NSCH), 2011–2012, are included in this 

appendix. Advance letters were sent prior to calling to encourage response. Thank you letters were sent after interview completion 

to accompany incentive payments.

National Immunization Survey Advance Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

NSCH Advance Letter (Augmentation Sample). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

$1 Prepaid/$10 Promise Refusal Conversion Letter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190

$5 Prepaid/$10 Promise Refusal Conversion Letter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

$10 Thank You Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194

$11 Thank You Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

$15 Thank You Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
DEPARTMENT OF HEALTH & HUMAN SERVICES Public Health Service 

Centers for Disease Control and Prevention 

National Center for health Statistics 

3311 Toledo Road 

H yattsville, Maryland 20782 

Page 186  Series 1, No. 59

National Immunization Survey Advance Letter

From the Director of the National Center for Health Statistics:

I am asking for your help with an important study conducted by the Centers for Disease Control 

and Prevention (CDC) called the National Immunization Survey (NIS). This survey tells us which 

vaccines people in the U.S. have received and about other important health topics. Results from 

the NIS are used to help health officials in their efforts to improve health care programs. In the 

next few weeks, NORC at the University of Chicago will call your household to take part in this 

study for CDC. 

For this study, we need to ask about vaccinations and about children’s health. Some

households also may be asked questions about the health services their children need or use. If 

you have a child between 17 and 37 months of age, it would be helpful to have your child’s 

immunization records handy when answering our questions. However, you can also answer 

these questions without the records.

Your phone number was chosen randomly by computer. It is important for us to interview every 

household we call to get a complete picture of your area’s immunization rates and key factors 

that might affect them. The study is important, but you do not have to take part, or you can 

decide not to answer one or more questions. 

You may call this toll free number at 1-866-999-3340 if you would like to take part in the study 

now. You can also call this number to learn more about the study and what you will be asked.

For more information, turn this letter over or go to the study’s web site: 

http://www.cdc.gov/nchs/nis.htm.

Your answers to the NIS will provide information to help improve the nation’s health now and in 

the years ahead. We need your help to make this study a success. We hope you will decide to 

take part when we call. 

Thank you for your cooperation. I am grateful for your help.

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention
Series 1, No. 59  Page 187 

What is NORC at the University of Chicago?

NORC at the University of Chicago (NORC) is an independent research organization 

that conducts interviews on immunizations and children’s health for the CDC. Additional 

information on NORC can be found on its website at www.norc.org.

NORC Toll Free Number: 1-866-999-3340

You can call the NORC toll free number to take part in the study right away, learn more 

about the study, and hear what you will be asked.

Who sees my answers?

You will be called by a trained interviewer who enters your answers into a computer.

Everyone who works on the survey must sign an oath that promises they will never give 

out anyone's personal information. Only a few people who work on this survey ever see 

any personal information. Answers that could identify you or your family in any way are 

separated from your other answers. Survey findings are put into summary reports that 

contain no names or other information that identifies you.

How do you protect my information?

Your answers are used for health research purposes only. We conduct this survey under 

the Public Health Service Act. It and other strict U.S. laws require that we protect your 

family’s information and keep it confidential. If you would like to know more about how 

we protect your answers, these laws are described in detail at 

www.cdc.gov/nchs/about/policy/confidentiality.htm.

If you want to know more about your rights as a study participant you may call 1-800-

223-8118, toll free. This is the number for the Research Ethics Review Board at CDC. 

You will be asked to leave a message. Say you are calling about Protocol 2006-04.

How do I find more about immunizations and places to get them?

You may call toll free 1-800-CDC-INFO (1-800-232-4636) for more information about 

vaccinations or to get the phone number of a doctor or clinic near you.

If you prefer to use a TTY

Please call the AT&T Relay Service at 1-800-855-2880 and request that NORC be called 

at 1-866-999-3340.
Page 188  Series 1, No. 59

NSCH Advance Letter (Augmentation Sample)

Dear Resident,

The CDC needs your help!

In the next few weeks, we will call your household to participate in a study about the health of children 

and teenagers. Information about all children will help the U.S. Department of Health and Human 

Services develop programs to promote the health of children in your state and throughout the United 

States. 

Although your participation is voluntary, it is very important that we include your household because it 

has been scientifically selected and cannot be replaced. It is important that we talk to your household to 

learn about the health of children in your community. When we call you, we will ask a few questions to 

see if your household is eligible for this study. 

We hope you will share this important information with us by phone when an interviewer calls to ask 

you to take part in the study. If you do, you can choose not to answer any questions you do not wish to 

answer. All information collected for this study is confidential and protected by federal law. The back of 

this letter provides answers to some questions you may have and ways to get more information about 

the survey.

To learn more about the study or to take part right away, call 1-866-900-9601, toll-free. CDC has hired 

the NORC at the University of Chicago to conduct the survey. Our website shows how we have used the 

data from the previous survey conducted in 2007 - http://mchb.hrsa.gov/nsch/.

Thank you very much for your help with this important research. 

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention

If you prefer to use TTY

Please call the AT&T Relay Service at 1-800-855-2880 and request that 

1-866-900-9601 be called. The call is toll-free.
Series 1, No. 59  Page 189 

National Survey of Children’s Health

Frequently Asked Questions

What is the purpose of this study? 

This survey is designed to describe the health and health care of children and teenagers. People have 

very different experiences with their children’s health and health care. In order to improve children’s 

health and well-being, it is important that we learn about how children use health care services and 

about any problems that they have in getting care that they need.

Does this study apply to me?

We are interested in talking with all sampled households. We need your information to get a complete 

picture of your area’s child health needs. It will take a few minutes or less to determine if you are 

eligible for the study.

How will you protect my privacy?

We are bound by law to maintain strict confidentiality standards. Your information and the child’s 

information will never be associated with any results. If you would like more information about the 

confidentiality of the research or the federal laws that ensure the protection of your information, 

including the Public Health Service Act and the Confidential Information Protection and Statistical 

Efficiency Act, these are described in detail at: 

http://www.cdc.gov/nchs/about/policy/confidentiality.htm. If you want to know more about your 

rights as a study participant you may call 1-800-223-8118, toll-free. This is the number for the Research 

Ethics Review Board at CDC. You will be asked to leave a message and say you are calling about Protocol 

2011-05.

How will this information be used?

Maternal and child health agencies in your state will use this information to improve health care services 

for children and their families. The federal government will also use this information to learn about the 

types of support services that states need for children’s health care. You may visit 

http://www.cdc.gov/nchs/slaits/nsch.htm to find general information about the study. To find results 

from the last time the survey was done, please visit http://mchb.hrsa.gov/nsch/. 

Who is NORC?

NORC at the University of Chicago is the name of the organization CDC hired to conduct this survey. It is 

a not-for-profit, academic research organization. 

NORC's Toll-Free Number: 1-866-900-9601 

You can call NORC's toll-free number to take part in the study right away, learn more about the study, 

and hear what you will be asked.
Page 190  Series 1, No. 59

$1 Prepaid/$10 Promise Refusal Conversion Letter

Dear Parent or Guardian, 

The CDC needs your help!

Recently, your family was asked to take part in a survey about the health of children and teenagers, but 

we have not been able to complete the interview yet. We hope you will reconsider our request. 

Information about your child and other children will help the U.S. Department of Health and Human 

Services develop programs to promote the health of children in your state and throughout the United 

States. 

We hope you will share this important information with us by phone when an interviewer calls to ask 

you to take part in the study. If you would like to participate right away or find out more about the 

survey, please call the toll-free telephone number 1-866-999-3340.

Your household is very important to the study because it has been scientifically selected and cannot be 

replaced. All information collected for this study is confidential and protected by federal law. The back 

of this letter provides answers to some questions you may have and ways to get more information 

about the survey.

Thank you very much for your help with this important research.

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention

P.S. In appreciation for your time and effort, we have enclosed $1. We will send an additional $10 in 

cash once you complete the interview. 
Series 1, No. 59  Page 191 

National Survey of Children’s Health

Frequently Asked Questions

Why is this study being conducted?

The Centers for Disease Control and Prevention is committed to improving children’s health and wellbeing. State and federal health authorities are depending on the results of this study to help them 

understand how best to meet children’s needs.

How will this information be used?

Maternal and child health agencies in your state will use this information to improve programs and 

services for children and their families. The federal government will also use this information to learn 

about the types of support services that states need for children’s health and well-being. 

You may visit http://www.cdc.gov/nchs/slaits/nsch.htm to find general information about the study.

To find results from the last time the survey was done, please visit http://mchb.hrsa.gov/nsch/. 

How will you protect my privacy?

We are bound by law to maintain strict confidentiality standards. Your information and the child’s 

information will never be associated with any results.

If you would like more information about the confidentiality of the research, the federal laws, including 

the Public Health Service Act and the Confidential Information Protection and Statistical Efficiency Act, 

that ensure the protection of your information have been described in detail at: 

http://www.cdc.gov/nchs/about/policy/confidentiality.htm.

If you want to know more about your rights as a study participant you may call 1-800-223-8118, toll 

free. This is the number for the Research Ethics Review Board at CDC. You will be asked to leave a 

message and say you are calling about Protocol 2011-05.

How can I find out more about this survey?

If you have any questions about this research study, please call 1-866-999-3340.
Page 192  Series 1, No. 59

$5 Prepaid/$10 Promise Refusal Conversion Letter

Dear Parent or Guardian, 

The CDC needs your help!

Recently, your family was asked to take part in a survey about the health of children and teenagers, but 

we have not been able to complete the interview yet. We hope you will reconsider our request.

Information about your child and other children will help the U.S. Department of Health and Human 

Services develop programs to promote the health of children in your state and throughout the United 

States.

We hope you will share this important information with us by phone when an interviewer calls to ask 

you to take part in the study. If you would like to participate right away or find out more about the 

survey, please call the toll-free telephone number 1-866-999-3340.

Your household is very important to the study because it has been scientifically selected and cannot be 

replaced. All information collected for this study is confidential and protected by federal law. The back 

of this letter provides answers to some questions you may have and ways to get more information 

about the survey.

Thank you very much for your help with this important research.

Sincerely,

Edward J. Sondik, Ph.D. 

Director, National Center for Health Statistics

Centers for Disease Control and Prevention

P.S. In appreciation for your time and effort, we have enclosed $5. We will send an additional $10 in 

cash once you complete the interview.
Series 1, No. 59  Page 193 

National Survey of Children’s Health

Frequently Asked Questions

Why is this study being conducted?

The Centers for Disease Control and Prevention is committed to improving children’s health and wellbeing. State and federal health authorities are depending on the results of this study to help them 

understand how best to meet children’s needs.

How will this information be used?

Maternal and child health agencies in your state will use this information to improve programs and 

services for children and their families. The federal government will also use this information to learn 

about the types of support services that states need for children’s health and well-being. 

You may visit http://www.cdc.gov/nchs/slaits/nsch.htm to find general information about the study.

To find results from the last time the survey was done, please visit http://mchb.hrsa.gov/nsch/. 

How will you protect my privacy?

We are bound by law to maintain strict confidentiality standards. Your information and the child’s 

information will never be associated with any results.

If you would like more information about the confidentiality of the research, the federal laws, including 

the Public Health Service Act and the Confidential Information Protection and Statistical Efficiency Act, 

that ensure the protection of your information have been described in detail at: 

http://www.cdc.gov/nchs/about/policy/confidentiality.htm. 

If you want to know more about your rights as a study participant you may call 1-800-223-8118, toll 

free. This is the number for the Research Ethics Review Board at CDC. You will be asked to leave a 

message and say you are calling about Protocol 2011-05.

How can I find out more about this survey?

If you have any questions about this research study, please call 1-866-999-3340.
Page 194  Series 1, No. 59

$10 Thank You Letter

Dear Parent or Guardian,

Thank you for taking part in the National Survey of Children’s Health. The information that you gave 

about your child will help the Centers for Disease Control and Prevention develop programs to promote 

the health of children in your state and throughout the United States.

In appreciation for your time and effort spent answering our questions, we have enclosed $10. 

If you would like more information about the survey, you may visit 

http://www.cdc.gov/nchs/slaits/nsch.htm, or call the toll-free telephone number for the study at 1-

866-999-3340. To find results from the last time the survey was done, please visit 

http://mchb.hrsa.gov/nsch/.

Thank you again for your help with this important research.

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention
Series 1, No. 59  Page 195 

$11 Thank You Letter

Dear Parent or Guardian,

Thank you for taking part in the National Survey of Children’s Health. The information that you gave 

about your child will help the Centers for Disease Control and Prevention develop programs to promote 

the health of children in your state and throughout the United States.

In appreciation for your time and effort spent answering our questions, we have enclosed $11. 

If you would like more information about the survey, you may visit 

http://www.cdc.gov/nchs/slaits/nsch.htm, or call the toll-free telephone number for the study at 1-

866-999-3340. To find results from the last time the survey was done, please visit 

http://mchb.hrsa.gov/nsch/.

Thank you again for your help with this important research.

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention
Page 196  Series 1, No. 59

$15 Thank You Letter

Dear Parent or Guardian,

Thank you for taking part in the National Survey of Children’s Health. The information that you gave about your 

child will help the Centers for Disease Control and Prevention develop programs to promote the health of 

children in your state and throughout the United States.

In appreciation for your time and effort spent answering our questions, we have enclosed $15. 

If you would like more information about the survey, you may visit http://www.cdc.gov/nchs/slaits/nsch.htm, 

or call the toll-free telephone number for the study at 1-866-999-3340. To find results from the last time the 

survey was done, please visit http://mchb.hrsa.gov/nsch/.

Thank you again for your help with this important research.

Sincerely,

Edward J. Sondik, Ph.D.

Director, National Center for Health Statistics

Centers for Disease Control and Prevention
Series 1, No. 59  Page 197 

Appendix IX. Disposition Code Frequencies and Response Rate 

Calculations

This appendix consists of tables showing the disposition code frequencies and how response rates were calculated. Table 

XVII shows unweighted response rate calculations for the overall sample. Table XVIII shows calculations for the landline sample, 

excluding the U.S. Virgin Islands (USVI) sample; Table XIX shows calculations for the total landline sample including USVI; and 

Table XX shows calculations for the USVI sample only. Table XXI shows calculations for the cell-phone sample.

Table XVII. Unweighted response rate calculations for 2011–2012 National Survey of Children’s Health: All sample

Disposition category and response rate

Frequency or 

calculated rate

Disposition category code 

or formula

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6,152,487 Total

Not resolved as residential or nonresidential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,705,693 A

Answering machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685,481 A1

No contact. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412,885 A2

Likely household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607,327 A3

Out of scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,389,715 B

Nonworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,876,625 B1

Nonresidential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513,090 B2

Cell-screened household, minor-only cell or landline-mainly cell . . . . . . . . . . . . . . . . . . . . . 30,387 C

Known household, mainly landline (for cell screening only). . . . . . . . . . . . . . . . . . . . . . . 5,362 C1

Cell phone owned by minor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25,025 C2

Known household, age eligibility undetermined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165,317 D

Known household, not screened for age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152,561 D1

Known household, known cell status, not age screened . . . . . . . . . . . . . . . . . . . . . . . . . 1,178 D2

S_KIDS = yes, full age eligibility undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11,578 D3

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 670,529 E

Age-ineligible household. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559,701 E1

Age ineligible via S_UNDR18 (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . 2,484 E2

Age ineligible via S_KIDS (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . . . . 108,344 E3

Known age-eligible household, interview not completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 92,827 F

Age-eligible household, interview incomplete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86,015 F1

Age-eligible household via NIS, not yet in SLAITS1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6,812 F2

Known age-eligible household, partially completed interview. . . . . . . . . . . . . . . . . . . . . . . . 2,330 G

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95,689 H

Calculation of response rate (percent)

Resolution rate (RR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.28 Total – A / Total

Screener completion rate (SCR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.36 (C + E + F + G + H) / (C + D + E + F + G + H)

Interview completion rate (ICR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.36 (G + H) / (F + G + H)

CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.32 (RR * SCR * ICR)

CASRO response rate alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.59 ((Total – A1 – A3) / Total) * SCR * ICR

1

NIS is National Immunization Survey; SLAITS is State and Local Area Integrated Telephone Survey. 

NOTE: CASRO is Council of American Survey Research Organizations.
Page 198  Series 1, No. 59

Table XVIII. Unweighted response rate calculations for 2011–2012 National Survey of Children's Health: Landline sample, excluding 

U.S. Virgin Islands

Disposition category and response rate

Frequency or 

calculated rate

Disposition category code 

or formula

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,143,460 Total

Not resolved as residential or nonresidential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 742,085 A

Answering machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221,198 A1

No contact. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296,245 A2

Likely household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224,642 A3

Out of scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,778,954 B

Nonworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,307,653 B1

Nonresidential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471,301 B2

Cell-screened household, minor-only cell or landline-mainly cell . . . . . . . . . . . . . . . . . . . . . ... C

Known household, mainly landline (for cell screening only). . . . . . . . . . . . . . . . . . . . . . . ... C1

Cell phone owned by minor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... C2

Known household, age eligibility undetermined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75,174 D

Known household, not screened for age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75,174 D1

Known household, known cell status, not age screened . . . . . . . . . . . . . . . . . . . . . . . . . ... D2

S_KIDS = yes, full age eligibility undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... D3

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432,076 E

Age-ineligible household. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432,076 E1

Age ineligible via S_UNDR18 (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . ... E2

Age ineligible via S_KIDS (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . . . . ... E3

Known age-eligible household, interview not completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 51,466 F

Age-eligible household, interview incomplete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47,597 F1

Age-eligible household via NIS, not yet in SLAITS1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,869 F2

Known age-eligible household, partially completed interview. . . . . . . . . . . . . . . . . . . . . . . . 1,267 G

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62,438 H

Calculation of response rate (percent)

Resolution rate (RR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.09 Total – A / Total

Screener completion rate (SCR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87.92 (C + E + F + G + H) / (C + D + E + F + G + H)

Interview completion rate (ICR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.31 (G + H) / (F + G + H)

CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.92 (RR * SCR * ICR)

CASRO response rate alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.40 ((Total – A1 – A3) / Total) * SCR * ICR

. . . Category not applicable.

1

NIS is National Immunization Survey; SLAITS is State and Local Area Integrated Telephone Survey. 

NOTE: CASRO is Council of American Survey Research Organizations.
Series 1, No. 59  Page 199 

Table XIX. Unweighted response rate calculations for 2011–2012 National Survey of Children's Health: Landline sample, including 

U.S. Virgin Islands

Disposition category and response rate

Frequency or 

calculated rate

Disposition category code 

or formula

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,252,193 Total

Not resolved as residential or nonresidential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 755,007 A

Answering machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223,639 A1

No contact. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304,821 A2

Likely household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226,547 A3

Out of scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,860,125 B

Nonworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,376,798 B1

Nonresidential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483,327 B2

Cell-screened household, minor-only cell or landline-mainly cell . . . . . . . . . . . . . . . . . . . . . ... C

Known household, mainly landline (for cell screening only). . . . . . . . . . . . . . . . . . . . . . . ... C1

Cell phone owned by minor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... C2

Known household, age eligibility undetermined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76,320 D

Known household, not screened for age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76,320 D1

Known household, known cell status, not age screened . . . . . . . . . . . . . . . . . . . . . . . . . ... D2

S_KIDS = yes, full age eligibility undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... D3

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442,146 E

Age-ineligible household. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442,146 E1

Age ineligible via S_UNDR18 (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . ... E2

Age ineligible via S_KIDS (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . . . . ... E3

Known age-eligible household, interview not completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 52,548 F

Age-eligible household, interview incomplete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48,592 F1

Age-eligible household via NIS, not yet in SLAITS1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,956 F2

Known age-eligible household, partially completed interview. . . . . . . . . . . . . . . . . . . . . . . . 1,326 G

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64,721 H

Calculation of response rate (percent)

Resolution rate (RR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.24 Total – A / Total

Screener completion rate (SCR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.02 (C + E + F + G + H) / (C + D + E + F + G + H)

Interview completion rate (ICR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.69 (G + H) / (F + G + H)

CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40.32 (RR * SCR * ICR)

CASRO response rate alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.83 ((Total – A1 – A3) / Total) * SCR * ICR

. . . Category not applicable.

1

NIS is National Immunization Survey; SLAITS is State and Local Area Integrated Telephone Survey. 

NOTE: CASRO is Council of American Survey Research Organizations.
Page 200  Series 1, No. 59

Table XX. Unweighted response rate calculations for 2011–2012 National Survey of Children's Health: Landline sample,

U.S. Virgin Islands

Disposition category and response rate

Frequency or 

calculated rate

Disposition category code 

or formula

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108,733 Total

Not resolved as residential or nonresidential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,922 A

Answering machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,441 A1

No contact. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,576 A2

Likely household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,905 A3

Out of scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81,171 B

Nonworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69,145 B1

Nonresidential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,026 B2

Cell-screened household, minor-only cell or landline-mainly cell . . . . . . . . . . . . . . . . . . . . . ... C

Known household, mainly landline (for cell screening only). . . . . . . . . . . . . . . . . . . . . . . ... C1

Cell phone owned by minor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... C2

Known household, age eligibility undetermined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,146 D

Known household, not screened for age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,146 D1

Known household, known cell status, not age screened . . . . . . . . . . . . . . . . . . . . . . . . . ... D2

S_KIDS = yes, full age eligibility undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... D3

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,070 E

Age-ineligible household. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,070 E1

Age ineligible via S_UNDR18 (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . ... E2

Age ineligible via S_KIDS (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . . . . ... E3

Known age-eligible household, interview not completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,082 F

Age-eligible household, interview incomplete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 F1

Age-eligible household via NIS, not yet in SLAITS1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 F2

Known age-eligible household, partially completed interview. . . . . . . . . . . . . . . . . . . . . . . . 59 G

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,283 H

Calculation of response rate (percent)

Resolution rate (RR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.12 Total – A / Total

Screener completion rate (SCR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.17 (C + E + F + G + H) / (C + D + E + F + G + H)

Interview completion rate (ICR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68.40 (G + H) / (F + G + H)

CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.55 (RR * SCR * ICR)

CASRO response rate alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60.53 ((Total – A1 – A3) / Total) * SCR * ICR

. . . Category not applicable.

1

NIS is National Immunization Survey; SLAITS is State and Local Area Integrated Telephone Survey. 

NOTE: CASRO is Council of American Survey Research Organizations.
Series 1, No. 59  Page 201 

Table XXI. Unweighted response rate calculations for 2011–2012 National Survey of Children's Health: Cell-phone sample

Disposition category and response rate

Frequency or 

calculated rate

Disposition category code 

or formula

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,900,294 Total

Not resolved as residential or nonresidential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 950,686 A

Answering machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461,842 A1

No contact. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108,064 A2

Likely household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380,780 A3

Out of scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529,590 B

Nonworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499,827 B1

Nonresidential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29,763 B2

Cell-screened household, minor-only cell or landline-mainly cell . . . . . . . . . . . . . . . . . . . . . 30,387 C

Known household, mainly landline (for cell screening only). . . . . . . . . . . . . . . . . . . . . . . 5,362 C1

Cell phone owned by minor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25,025 C2

Known household, age eligibility undetermined. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88,997 D

Known household, not screened for age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76,241 D1

Known household, known cell status, not age screened . . . . . . . . . . . . . . . . . . . . . . . . . 1,178 D2

S_KIDS = yes, full age eligibility undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11,578 D3

Age-screened household, no age-eligible child . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228,383 E

Age-ineligible household. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117,555 E1

Age ineligible via S_UNDR18 (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . 2,484 E2

Age ineligible via S_KIDS (cell augmentation sample) . . . . . . . . . . . . . . . . . . . . . . . . . . . 108,344 E3

Known age-eligible household, interview not completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 40,279 F

Age-eligible household, interview incomplete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37,423 F1

Age-eligible household via NIS, not yet in SLAITS1

 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,856 F2

Known age-eligible household, partially completed interview. . . . . . . . . . . . . . . . . . . . . . . . 1,004 G

Completed interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30,968 H

Calculation of response rate (percent)

Resolution rate (RR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.97 Total – A / Total

Screener completion rate (SCR). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.81 (C + E + F + G + H) / (C + D + E + F + G + H)

Interview completion rate (ICR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.25 (G + H) / (F + G + H)

CASRO response rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.43 (RR * SCR * ICR)

CASRO response rate alternative. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.41 ((Total – A1 – A3) / Total) * SCR * ICR

. . . Category not applicable.

1

NIS is National Immunization Survey; SLAITS is State and Local Area Integrated Telephone Survey. 

NOTE: CASRO is Council of American Survey Research Organizations.
Page 202  Series 1, No. 59

Appendix X. Alternative Response Rates

By definition, the response rate is 

the number of completed interviews as a 

proportion of the number of eligible units 

in the sample:

Eligibles

Complete Interviews

For the National Survey of 

Children’s Health (NSCH), the numerator 

is the number of households that 

completed the interview through Section 

6 or Section 7 (depending on the child’s 

age), and the denominator is the number 

of eligible households in the sample. 

However, due to nonresponse before the 

screener was completed, eligibility status 

was not observed for all sample units, and 

the number of eligible units in the sample 

had to be estimated. The response rate 

formula is, therefore, often written as:

Observed Eligibles + eU

Complete Interviews

where U is the number of sampled 

telephone numbers for which the 

eligibility status has not been observed 

and e is the assumed rate of eligibility 

among these unobserved units. This 

equation is of the form of the response 

rate formulas from the American 

Association for Public Opinion 

Research’s (AAPOR) “Standard 

Definitions: Final Dispositions of Case 

Codes and Outcome Rates for Surveys” 

(22). 

Setting e = 1 (i.e., assuming that 

all sample units with unobserved 

eligibility status were actually eligible) 

represents the minimum response rate 

and corresponds to AAPOR response 

rate 1 (RR1). For NSCH, the minimum 

response rate was 6.6% for the landline 

sample and 2.7% for the cell-phone 

sample. Setting e = 0 represents the 

maximum response rate, reflecting an 

assumption that all of the sample units 

with unobserved eligibility status are 

actually ineligible and corresponding 

to AAPOR response rate 5 (RR5). For 

NSCH, the maximum response rate was 

54.1% for the landline sample and 41.2% 

for the cell-phone sample. The minimum 

and maximum response rates for each 

state are given in Tables XXII and XXIII.

Setting e between 0 and 1 

corresponds to AAPOR response rate 

3 (RR3). Survey researchers have used 

several methods to choose a value for e 

(23). Perhaps the most common method 

is to set e equal to the observed eligibility 

rate among those sample units for which 

the eligibility status has been determined, 

as in, 

Observed Eligibles + Observed Ineligibles

Observed Eligibles e = 

where the observed ineligibles 

include all types of ineligible units. For 

NSCH, observed ineligibles include 

nonworking phone numbers, businesses, 

households without children, cell phones 

that are not used by adults, and, for the 

Quarter 1, 2011, cell-phone sample, 

households that are not cell phone-only 

or cell phone-mainly. This proportional 

allocation method is sometimes 

called the CASRO method because 

it is recommended by the Council of 

American Survey Research Organizations 

(CASRO) (24). This approach yields a 

national response rate of 42.7% for the 

landline sample and 17.8% for the cellphone sample. The rates for each state are 

given in Tables XXII and XXIII.

The method above used a single 

value of e for all sample units for which 

eligibility status was not determined. 

Another method commonly used in 

telephone surveys divides the units with 

undetermined eligibility into groups 

corresponding to nonrespondents to 

different components of the survey and 

assumes a separate e for each group. For 

NSCH, the response rate formula under 

this approach became:

Observed Eligibles + e1e2U1 + e2U2

Completed Interviews

where, 

U1 = the number of unresolved telephone 

numbers,

e1 = the assumed working residential 

number rate among U1,

U2 = the number of known residential 

telephone numbers where the 

screener was not completed, 

and

e2 = the assumed eligibility rate among 

U2.

Again, the proportional allocation 

(CASRO) method is commonly used to 

estimate e1 and e2, letting e1 equal the 

observed working residential number rate 

among the resolved telephone numbers 

and e2 equal the observed eligibility 

rate among the screened households. 

Note that under these assumptions, 

the response rate can be written as the 

product of the component completion 

rates given in Tables K and M. This 

approach yielded national response rates 

of 38.2% for the landline sample and 

15.5% for the cell-phone sample. The 

response rates for each state are given in 

Tables XXII and XXIII.

The response rates above treat all 

telephone numbers that resulted in no 

contact (i.e., all attempts resulted in 

rings with no answer or in busy signals) 

as unresolved. An alternative approach 

that treated these noncontact numbers as 

nonworking resulted in national response 

rates of 41.9% for the landline sample 

and 17.2% for the cell-phone sample. The 

alternative response rates for each state 

are given in Tables XXII and XXIII.

Thus far, response rates have been 

presented separately for the landline and 

cell-phone samples; however, an overall 

response rate is desirable that combines 

the sample from both sample frames. A 

common method for constructing a dualframe response rate is to weight together 

the response rates for the landline and 

cell-phone samples in proportion to the 

distribution of eligible units across the 

sample frames:

RRdual = (RRLL • pa) + RRLL • pab

2 ( (

RRCELL • pab

2 ( ( + + (RRCELL • pb)

where, for NSCH,
Series 1, No. 59  Page 203 

RRdual = the dual-frame response rate,

RRLL = the landline-frame response 

rate,

RRCELL = the cell phone-frame response 

rate,

p

a = the proportion of households 

with children that are landlineonly,

pab = the proportion of households 

with children that have both 

landline and cell phones, and

p

b = the proportion of households 

with children that are cell 

phone-only.

Because households that have 

both landline and cell phones appeared 

on both sample frames and, thus, had 

twice the probability of selection, their 

contributions to the dual-frame response 

rates were divided by two. This equation, 

with p

a, 

pab, and p

b estimated at the 

national and state levels (i.e., the same 

telephone status distribution estimates 

that were used to produce the final NSCH 

weights) was used to compute dual-frame 

response rates. The dual-frame response 

rates for the nation and each state are 

given in Table XXIV.
Page 204  Series 1, No. 59

Table XXII. Weighted National Survey of Children’s Health response rates, nationally and by sampling state: Landline sample

Area Minimum Maximum

Single e, 

proportional 

allocation

Separate e

for each type of 

nonrespondent, 

proportional allocation

Separate e

for each type of 

nonrespondent, 

proportional 

allocation 

(alternative)

Total (excluding USVI) . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 54.1 42.7 38.2 41.9

Total (including USVI) . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 54.1 42.7 38.2 41.9

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 58.9 46.0 41.3 46.1

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 53.6 44.0 39.3 43.1

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 50.7 40.0 35.6 38.9

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 56.6 47.5 43.8 47.1

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 49.4 35.9 31.4 36.7

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 59.6 47.8 43.3 46.7

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 53.9 40.1 35.5 38.7

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 52.5 38.9 34.9 38.7

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 58.1 46.5 41.4 46.5

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 51.1 40.2 35.5 38.9

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 55.0 44.0 39.1 42.7

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 49.6 40.3 35.2 38.2

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 54.1 45.0 41.1 43.9

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 54.3 44.1 39.7 43.1

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 62.1 51.5 46.9 50.4

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 60.0 50.4 46.5 49.6

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 60.0 49.8 45.3 48.5

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 53.6 42.9 38.6 42.2

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 52.1 42.4 37.4 40.8

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 57.6 46.5 42.8 46.3

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 58.3 44.5 39.3 43.5

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 53.2 39.8 35.4 38.5

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 58.2 47.7 42.9 46.3

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 57.2 47.5 43.7 46.1

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 55.2 45.6 40.7 44.1

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.7 59.4 48.9 44.6 48.1

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 64.6 54.7 50.4 53.0

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6 58.4 48.9 44.4 47.2

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 49.6 37.9 33.5 37.4

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 53.5 41.4 37.4 40.4

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 50.8 38.3 33.6 37.7

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0 58.5 48.0 43.3 46.2

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 46.9 36.1 31.7 35.1

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 54.8 43.4 39.2 42.9

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.9 56.1 48.8 44.8 47.1

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0 55.3 45.2 40.8 43.7

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 51.0 40.7 36.5 40.1

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 60.9 50.5 46.6 49.8

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 54.8 42.2 38.3 41.8

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 55.7 42.5 38.0 41.1

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 51.8 40.8 36.6 40.4

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.9 57.8 50.0 45.8 48.0

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 55.1 44.4 40.3 43.8

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 53.2 42.1 36.9 40.7

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 58.7 47.9 43.6 46.7

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.0 64.6 52.7 48.9 52.5

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 58.0 44.8 40.3 44.5

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 58.4 47.2 42.9 45.7

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 57.1 43.7 39.8 43.6

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.8 57.7 47.3 43.4 46.7

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 57.2 47.6 43.5 46.4

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4 68.4 59.5 55.6 60.5

NOTE: USVI is U.S. Virgin Islands.
Series 1, No. 59  Page 205 

Table XXIII. Weighted National Survey of Children’s Health response rates, nationally and by sampling state: Cell-phone sample

Area Minimum Maximum

Single e, 

proportional 

allocation

Separate e

or each type of 

nonrespondent, 

proportional 

allocation

Separate e

for each type of 

nonrespondent, 

proportional 

allocation 

(alternative)

Total (excluding USVI) . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 41.2 17.8 15.5 17.2

Total (including USVI) . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... ... ... ...

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 43.0 22.3 18.9 21.0

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 53.3 30.1 25.8 31.5

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 44.8 18.7 16.7 19.3

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 48.2 25.0 21.5 22.8

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 37.0 14.6 12.6 13.9

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 47.2 19.6 17.3 19.8

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 40.8 14.6 12.8 14.6

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 44.4 17.2 15.6 18.3

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 50.7 18.8 17.5 22.7

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 37.1 16.5 14.3 15.4

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 41.8 20.0 17.1 19.1

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 41.2 16.0 14.3 15.8

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 51.9 24.0 21.7 23.5

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 38.4 17.6 14.9 16.2

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 44.0 20.6 18.5 20.3

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 46.7 22.7 20.2 22.7

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 49.3 25.2 22.2 24.3

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 44.1 20.2 17.6 19.6

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 42.0 19.8 16.9 18.5

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 45.0 19.0 17.0 18.3

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 41.8 13.6 12.5 15.5

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 45.1 17.2 15.0 17.6

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 41.2 18.8 16.2 18.4

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 45.8 20.8 18.7 21.0

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 42.1 22.5 19.5 21.3

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 46.7 20.6 18.5 20.3

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 51.5 30.9 26.8 28.8

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 52.4 25.8 22.8 24.3

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 43.5 17.1 15.1 17.4

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 44.8 17.9 15.6 17.4

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 38.5 15.8 13.9 16.0

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 45.3 23.6 20.7 22.7

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 34.0 13.6 11.6 12.8

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 43.5 20.3 17.6 19.2

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 49.2 30.4 26.2 28.7

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 40.6 16.8 14.7 16.6

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 43.5 21.9 19.1 21.0

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 47.2 19.8 18.2 19.6

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 31.8 11.8 10.3 11.7

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 45.5 16.9 14.9 16.6

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 41.1 19.9 17.3 18.8

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 50.1 30.5 26.9 28.2

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 44.0 19.1 16.5 17.9

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 39.6 16.5 14.0 15.3

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 51.5 22.6 20.3 24.6

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 50.1 21.1 18.6 20.1

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 44.2 16.3 14.7 17.9

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 45.7 17.0 15.5 17.4

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 42.9 17.3 15.0 16.3

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 47.0 22.1 19.2 21.0

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 52.0 35.7 29.6 30.5

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... ... ... ...

. . . Category not applicable.

NOTE: USVI is U.S. Virgin Islands.
Page 206  Series 1, No. 59

Table XXIV. Weighted National Survey of Children’s Health response rates overall, nationally and by sampling state

Area Minimum Maximum

Single e, 

proportional 

allocation

Separate e

for each type of 

nonrespondent, 

proportional 

allocation

Separate e

for each type of 

nonrespondent, 

proportional 

allocation 

(alternative)

Total (excluding USVI) . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 45.5 26.1 23.0 25.4

Total (including USVI) . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... ... ... ...

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 47.7 29.3 25.5 28.4

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 53.4 36.0 31.6 36.5

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 46.6 25.2 22.4 25.3

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 50.1 30.1 26.5 28.3

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 41.5 22.4 19.5 22.2

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 51.0 28.2 25.3 28.0

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 46.9 26.6 23.5 25.9

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 47.6 25.8 23.3 26.4

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 52.5 25.5 23.2 28.5

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 41.4 23.8 20.8 22.6

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 46.0 27.6 24.0 26.5

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 44.0 24.1 21.3 23.2

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 52.4 29.1 26.4 28.5

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 43.5 26.2 22.9 24.9

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 49.6 30.0 27.2 29.5

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 51.1 31.9 29.0 31.6

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 52.5 32.5 29.1 31.5

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 47.1 27.4 24.3 26.8

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 44.9 26.3 22.7 24.9

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 49.3 28.5 25.9 28.0

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 48.2 25.6 22.9 26.3

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 48.4 26.5 23.4 26.2

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 46.4 27.5 24.3 26.9

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 49.8 30.3 27.6 29.9

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 44.7 27.2 23.8 25.9

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 50.7 29.5 26.7 29.1

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 55.7 38.4 34.3 36.5

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 54.4 33.4 29.8 31.8

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 45.6 24.3 21.5 24.3

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 48.1 26.7 23.8 26.0

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 43.8 25.6 22.5 25.5

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 48.9 30.2 26.8 29.0

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 39.6 23.4 20.3 22.5

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 46.7 26.9 23.7 25.9

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 51.3 36.0 31.9 34.3

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 45.1 25.5 22.7 24.9

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 45.9 28.0 24.8 27.2

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 51.8 30.1 27.7 29.7

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 40.4 23.2 20.8 23.0

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 50.1 28.6 25.5 27.8

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 44.3 26.1 23.0 25.2

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 52.5 36.7 32.9 34.5

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 47.1 26.1 23.2 25.2

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 43.2 23.4 20.1 22.1

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 53.8 30.7 27.8 31.7

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 55.7 33.4 30.4 32.8

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 49.6 27.4 24.7 28.3

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 50.2 27.7 25.2 27.5

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 48.5 27.7 24.8 27.0

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 50.6 30.6 27.3 29.6

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 53.7 39.7 34.3 35.8

U.S. Virgin Islands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... ... ... ...

. . . Category not applicable.

NOTE: USVI is U.S. Virgin Islands.
Series 1, No. 59  Page 207 

Appendix XI. Incentive Effort

To improve the likelihood that ageeligible households would participate 

in the National Survey of Children’s 

Health (NSCH) and contribute to a more 

complete data set, an incentive plan was 

developed and executed during NSCH 

data collection. This plan was guided by 

previously successful incentive efforts in 

the 2007 NSCH and 2009–2010 National 

Survey of Children with Special Health 

Care Needs. This appendix summarizes 

the design and results of the NSCH 

incentive model, and the results from 

an experiment conducted throughout 

Quarters 2–4, 2011, to identify best 

practices for the presentation of prepaid 

incentives.

Eligible Cases

Cases eligible for an incentive were 

known age-eligible households that had 

not completed the NSCH interview and 

had refused participation at least once. 

The incentive models included in the 

experiment, and those ultimately chosen, 

were primarily refusal-based. Refusals 

were defined by specific combinations of 

“hung up during introduction” (HUDI), 

active (or verbal) refusals, and passive 

(i.e., persistent noncontact) refusals. 

For cases eligible for the National 

Immunization Survey’s NIS–Child or 

NIS–Teen that had refusals in either 

survey, those refusals counted toward 

NSCH incentive eligibility.

Passive refusals, or cases with zero 

or one active refusal in which multiple 

attempts resulted in no contact for 21 

days, received treatment similar to 

incentive cases with two active refusals 

(or the equivalent HUDI–refusal 

combination). Hostile refusals and cases 

that requested to be taken off the list of 

sampled phone numbers were not eligible 

for incentives and not dialed again. Cases 

that had been previously offered an 

incentive by NIS were also eligible for an 

NSCH incentive.

Incentive Experiment 

The experiment included two 

treatments intended to provide insight 

into methods of increasing the chance 

that a potential respondent would open 

the mailing: standard compared with 

Priority-like mailing envelope and 

dollar bill compared with dollar coin. 

To explore the effects of envelope type 

and dollar type, the 2011–2012 NSCH 

incentive experiment used a 2x2 factorial 

design to include variations on both the 

type of dollar insertion included in each 

mailing (either a $1 bill or a $1 coin), 

as well as the type of envelope used to 

mail the letter (either a standard white 

envelope or an envelope that resembled 

a U.S. Postal Service Priority Mail 

envelope (Appendix XII). The outside of 

the Priority-like envelope was designed 

to resemble a Priority mailer with a red, 

white, and blue design, but requiring only 

first-class postage. This variation on the 

standard envelope was introduced as a 

method to decrease postage costs while 

also hypothetically retaining the salience 

of a Priority mailer. Together with the 

variation in dollar type, the following 

four experimental groups were applied 

to cases that qualified for the $1 prepaid 

incentive:

● Group 1: Standard envelope with a 

dollar coin 

● Group 2: Standard envelope with a 

dollar bill

● Group 3: Priority-like envelope with 

a dollar coin

● Group 4: Priority-like envelope with 

a dollar bill

The experiment was designed to 

investigate the following questions to 

determine the best incentive mailing 

type for the remainder of the 2011–2012 

NSCH, when taking into account the 

effect on completion rates:

Does the envelope’s appearance 

(standard compared with Priority-like) 

affect completion rates?

Does the type of dollar (coin 

compared with bill) affect completion 

rates?

Does a specific combination of 

each of these factors make a significant 

difference on completion rates?

The experiment protocol was applied 

to all cases released during Quarter 2, 

2011. To implement the experiment, 

each case flagged for NSCH Quarter 

2, 2011, was randomly assigned to an 

incentive treatment group during sample 

preparation. On average, each incentive 

group had approximately 1,650 incentiveeligible households. The experiment 

continued through Quarter 3, 2011, and 

Quarter 4, 2011; however, prior to the 

start of each quarter, the group with the 

poorest performance was eliminated from 

the experiment.

Incentive Models

Because addresses were not available 

for the cell-phone sample in advance, 

the incentive model for the cell-phone 

sample relied less on prepaid incentives. 

Table XXV illustrates the different 

incentive models for the landline and 

cell-phone samples.

Response Rates

A total of 61,480 cases (32.2% of all 

age-eligible cases) became eligible for 

some type of an incentive across all five 

Table XXV. Incentive model, by telephone sample type

Sample type After first refusal

After second refusal

With mailing 

address

Without mailing 

address

Landline . . . . . . . . . . . . . . . . . . . No offer (not eligible 

for incentive) 

$1 coin mailing with 

promise of $10

Offer $11 upon 

callback

Cell phone . . . . . . . . . . . . . . . . . Offer $10 upon 

callback

... Offer $15 upon 

callback

. . . Category not applicable; addresses not available for cell-phone sample.
Page 208  Series 1, No. 59

quarters of NSCH data collection. Active 

refusal cases accounted for 58.1% (n = 

35,730) of all cases eligible for incentive 

treatment, and passive refusal cases 

accounted for the remainder (41.9% or 

n = 25,750). Of the cases eligible for an 

incentive treatment, 30.5% (n = 18,728) 

fully completed the NSCH survey. Table 

XXVI details the total incentive cases by 

quarter. 

Response Rates by Quarter

During Quarter 2, 2011, Group 2 

(standard envelope/dollar bill) provided 

the highest completion rate and CASRO 

rate for both full and partial interviews, 

as well as the highest overall yield rate 

(Table XXVII). Group 3 (Priority-like 

envelope/dollar coin) achieved the lowest 

completion rates in all categories.

Significance testing was conducted 

using a chi-squared statistic to compare 

interview completion rates between 

incentive groups as well as between 

money type and envelope type alone. 

Although not significant, the standard 

envelope groups (Groups 1 and 2) had a 

higher completion rate than the Prioritylike envelope groups (Groups 3 and 

4), χ2 (1, N = 6,630) = 3.23, p = 0.07. 

Similarly, the dollar bill groups (Groups 2 

and 4) had a higher interview completion 

rate than the dollar coin groups (Groups 1 

and 3), although this was not found to be 

significant, χ2 (1, N = 6,630) = 2.33, 

p = 0.13. No significant difference was 

found when comparing all four groups, 

χ2 (1, N = 6,630) = 5.79, p = 0.12; 

however, when comparing the highestperforming (Group 2) and lowestperforming (Group 3) groups, Group 2 

(standard envelope with dollar bill) had a 

significantly higher interview completion 

rate, χ2 (1, N = 3,274) = 5.60, p = 0.02.

As a result, Group 3 (Priority-like 

envelope with dollar coin) was dropped 

from future mailings to best maximize 

the incentive effort as data collection 

approached Quarter 3, 2011. Beginning 

August 12, 2011, cases identified as 

incentive-eligible in Quarter 3, 2011, 

were randomly assigned to the remaining 

three mailing-type groups (Groups 1, 2, 

or 4). Each group performed similarly 

to what was observed in Quarter 2, 

2011 (Table XXVIII). Again, Group 

2 (standard envelope with dollar bill) 

provided the highest completion rate and 

CASRO rate for both partial and full 

interviews, as well as the highest overall 

yield rate. The lowest rates were found 

in Group 4 (Priority-like envelope with 

dollar bill). Significance testing revealed 

no significant differences between 

groups, money type, or envelope type.

Based on the Quarter 3, 2011, 

results, only the two top-performing 

groups (Groups 1 and 2) were included 

in the experiment in Quarter 4, 2011. 

Beginning October 21, 2011, cases 

identified as incentive-eligible in Quarter 

4, 2011, were randomly assigned to either 

Group 1 (standard envelope with dollar 

coin) or Group 2 (standard envelope with 

dollar bill). The final results from Quarter 

4, 2011, revealed Group 1 (standard 

envelope with dollar coin) achieved 

the highest partial completion rate, the 

highest partial and full interview CASRO 

response rates, and the highest yield 

rate (Table XXIX). Group 2 (standard 

envelope with dollar bill) achieved 

the highest full-interview completion 

rate. Significance testing revealed no 

significant differences between groups, 

money type, or envelope type.

Although Group 1 (standard 

envelope with dollar coin) achieved 

higher rates in all but full interview 

completion in Quarter 4, 2011, Group 

2 (standard envelope with dollar bill) 

consistently maintained the highest rates 

in all categories in previous quarters. 

Based on this performance, NSCH 

proceeded with the Group 2 mailing type 

(standard envelope with dollar bill) for all 

Quarter 1, 2012, cases. 
Series 1, No. 59  Page 209 

Table XXVI. Number of incentive-eligible cases and percentage completed, by quarter: 2011 and first quarter, 2012

Number of cases and percentage completed

2011 2012

Quarter 1 Quarter 2 Quarter 3 Quarter 4 Quarter 1 Overall

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,859 11,486 18,410 9,766 16,959 61,480

Number of completed cases. . . . . . . . . . . . . . . . . . . . . . . . 1,541 3,770 5,745 3,158 4,514 18,728

Percentage of incentive-eligible cases

completed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.71 32.82 31.21 32.34 26.62 30.46

NOTES: Incentive-eligible cases include those with one or two refusals, depending on the incentive treatment, and S_UNDR18 = 1–9; they do not include hostile refusals or requests for removal from 

the call list. Completed cases are those in which the entire interview was completed.

Table XXVII. Number of cases and response rates, by incentive experiment group: Second quarter, 2011

Group

Money 

type

Envelope 

type

Released 

cases

Age

eligible 

NSCH Section 

7 completed

Full interview 

completed 

Completion rate CASRO response rate

Yield 

rate 

Partial 

interview

Full 

interview

Partial 

interview 

Full 

interview 

Total ... ... 6,630 6,591 2,293 2,106 34.79 31.95 34.77 31.93 31.76

1 Dollar coin Standard 1,692 1,684 589 544 34.98 32.3 34.98 32.3 32.15

2 Dollar bill Standard 1,626 1,613 583 544 36.14 33.73 36.12 33.71 33.46

3 Dollar coin Priority-like 1,648 1,641 539 488 32.85 29.74 32.81 29.7 29.61

4 Dollar bill Priority-like 1,664 1,653 582 530 35.21 32.06 35.19 32.04 31.85

. . . Category not applicable.

NOTE: NSCH is National Survey of Children’s Health; CASRO is Council of American Survey Research Organizations.

Table XXVIII. Number of cases and response rates, by incentive experiment group: Third quarter, 2011

Group

Money 

type

Envelope 

type

Released 

cases

Age

eligible 

NSCH Section 

7 completed

Full interview 

completed 

Completion rate CASRO response rate

Yield 

rate 

Partial 

interview

Full 

interview

Partial 

interview

Full 

interview

Total ... ... 7,299 7,242 2,432 2,246 33.58 31.01 33.51 30.95 30.77

1 Dollar coin Standard 2,430 2,408 817 751 33.93 31.19 33.84 31.11 30.91

2 Dollar bill Standard 2,436 2,421 838 779 34.61 32.18 34.56 32.12 31.98

4 Dollar bill Priority-like 2,433 2,413 777 716 32.2 29.67 32.12 29.6 29.43

. . . Category not applicable.

NOTE: NSCH is National Survey of Children’s Health; CASRO is Council of American Survey Research Organizations.

Table XXIX. Number of cases and response rates, by incentive group: Fourth quarter, 2011

Group

Money 

type

Envelope 

type

Released 

cases

Age

eligible 

NSCH Section 

7 completed

Full interview 

completed 

Completion rate CASRO response rate

Yield 

rate 

Partial 

interview 

Full 

interview 

Partial 

interview

Full 

interview

Total ... ... 2,872 2,855 974 920 34.12 32.22 34.04 32.16 32.03

1 Dollar coin Standard 1,433 1,424 487 463 34.2 32.51 34.08 32.4 32.31

2 Dollar bill Standard 1,439 1,431 487 457 34.03 31.94 34.01 31.91 31.76

. . . Category not applicable.

NOTE: NSCH is National Survey of Children’s Health; CASRO is Council of American Survey Research Organizations.
Page 210  Series 1, No. 59

Appendix XII. Envelope Types Used in Incentive Experiment 

This appendix includes examples of the two envelope types used in the incentive experiment described in Appendix XI. 

Figure 1 shows the U.S. Department of Health and Human Services official business mailing envelope. Figure 2 shows the Priority 

Processing mailing envelope.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SOURCE: U.S. Department of Health and Human Services.

Figure 1. U.S. Department of Health and Human Services official business mailing envelope
PRIORI Mailing Envelope

W T USE:

PRIORITY PROCESSING

HO O 

1.

Figure 2. Mailing envelope labeled Priority Processing

Place pre-addressed envelope inside this mailer

• Make sure the address shows through the window

• This envelope bares 1st Class postage

2. Affix postage or meter strip to the front of the mailer

3. Seal flap on mailer envelope

SOURCE: NCHS, National Survey of Children's Health, 2011-2012.

Series 1, No. 59  Page 211 

PRIORITY PROCESSING Mailing Envelope

HOW TO USE:

1. Place pre-addressed envelope inside this mailer

2. Affix postage or meter strip to the front of the mailer

3. Seal flap on mailer envelope

• Make sure the address shows through the window

• This envelope bares 1st Class postage
Page 212  Series 1, No. 59

Appendix XIII. Nonresponse Bias Analysis

The stages of the 2011–2012 

National Survey of Children’s Health 

(NSCH), and the types of nonrespondent 

associated with each stage, are shown 

in Figure 3. Nonresponse occurred at 

each stage: For some telephone numbers, 

it was never determined whether the 

number belonged to a household (i.e., 

some numbers remained unresolved); 

some identified households did not 

complete the age-eligibility or cell phonestatus screeners; and some households 

that were identified as eligible did not 

complete the detailed interview. This 

appendix explores the effect of the 

nonrespondents—that is, unresolved 

telephone numbers, age- and cell phonestatus screener nonrespondents, and 

interview nonrespondents—on key 

national survey estimates. 

Nonresponse Bias

Nonresponse bias in a survey 

estimate ȳr can be expressed in two 

forms (25), given the data collection 

protocol. The first formulation assumes 

that each unit in the target population 

is, a priori, either a respondent or a 

nonrespondent:

(1) Bias (ȳr) = (Ȳr – Ȳm)

M

N

where M is the number of nonrespondents 

in the population, N is the total number 

of units in the target population, ȳr

is the respondent mean in the target 

population, and Ȳm is the nonrespondent 

mean in the target population. The second 

formulation assumes that each unit (i) in 

the target population has a propensity ρi

to respond:

(2) Bias (ȳr) ≈ 

σyρ

ρ

where σyρ is the correlation between 

the survey variable and the response 

propensity, and ρ is the mean response 

propensity in the population. In either 

formulation, the bias is related to both 

the response rate and the degree to 

which the respondents differ from the 

nonrespondents with respect to the survey 

variable. 

Nonresponse rates represent a 

potential for substantial nonresponse 

bias. However, this is only a potential. 

In a meta-analysis of nonresponse bias 

studies, Robert Groves found little to 

no relationship between the magnitude 

of nonresponse and nonresponse bias; 

in fact, Groves found more variation in 

nonresponse bias between estimates from 

the same survey than between estimates 

from different surveys with differing 

response rates (25).

The second important factor 

contributing to nonresponse bias is the 

degree to which respondents differ from 

nonrespondents with respect to the survey 

variables. This quantity is generally 

unknown, and nonresponse bias analyses 

attempt to measure this difference either 

directly or indirectly. Groves summarizes 

the typical approaches as (25):

1. Response rate comparisons across 

subgroups

2. Using rich sampling frame data or 

supplemental matched data

3. Comparison to similar estimates 

from other sources

4. Studying variation within the 

existing survey

5. Contrasting alternative postsurvey 

adjustments for nonresponse

This appendix presents the results 

of analyses using approaches 1–4 for 

the 2011–2012 NSCH. (Alternative 

postsurvey adjustments for nonresponse 

are not available for NSCH.) Each of 

these approaches has its weaknesses; 

using many different approaches may 

arrive at conclusions that overcome the 

weaknesses of any individual approach 

and provide an accurate picture of the 

nonresponse bias.

 

 

 

 

 

 

 

 

Figure 3. Survey stages and types of nonrespondents
Series 1, No. 59  Page 213 

Information Available on 

Nonrespondents 

Several approaches used to assess 

nonresponse bias rely on the availability 

of information for both respondents 

and nonrespondents. Because NSCH 

is a random-digit-dial (RDD) survey, 

information available on nonrespondents 

was very limited. Table XXX shows 

information known for both respondents 

and nonrespondents in the 2011–2012 

NSCH landline sample. The first two 

variables—residential-listed status and 

advance-letter status—are case-specific; 

the remaining variables are ecological, 

that is, they contain information not 

about each case specifically but about 

the telephone exchange containing the 

case’s telephone number. (The telephone 

exchange is the area code plus the first 

three digits of the telephone number.) For 

example, while the income of each case 

was unknown, the median income for 

households sharing the case’s telephone 

exchange was known. This ecological 

information is based on census tractlevel data, aggregated to the telephoneexchange level. Because no directories 

of cell-phone numbers exist, and because 

cell-phone numbers are not tied to 

geography in the way landline numbers 

are, these frame variables were available 

only for the landline sample, not for the 

cell-phone sample.

Key Survey Estimates

The assessment of nonresponse bias 

focused on 10 key survey estimates:

1. The percentage of children in 

excellent or very good health.

2. The percentage of children with 

consistent insurance coverage in the 

past 12 months.

3. The percentage of children with at 

least one medical preventive care 

visit in the past 12 months.

4. The percentage of children with a 

medical home.

5. The percentage of children whose 

families ate a meal together every 

day in the past week.

6. The percentage of children who 

are usually or always safe in their 

community or neighborhood.

7. The percentage of children with 

a two-parent family structure 

(biological or adoptive).

8. The percentage of children with 

a two-parent family structure 

(stepfamily).

9. The percentage of children with a 

single-mother family structure.

10. The percentage of children with 

another kind of family structure.

Table XXX. Information available for both respondents and nonrespondents: 

Landline sample

Variable name Description

Listed . . . . . . . . . . . . . . . . . . . . Indicator of residential listed status

Advance_letter . . . . . . . . . . . . . Indicator of advance letter sent status

MSA . . . . . . . . . . . . . . . . . . . . . Indicator of metropolitan statistical area status

Median_HH_income. . . . . . . . . Median household income in telephone exchange

Median_home_val . . . . . . . . . . Median home value in telephone exchange

Median_rent. . . . . . . . . . . . . . . Median rent in telephone exchange

Median_years_educ . . . . . . . . . Median years of education of population in telephone exchange

College_graduate . . . . . . . . . . . Percentage of population in telephone exchange who are college graduates

Approx_median_age. . . . . . . . . Approximate median age of population in telephone exchange

Hispanic_p. . . . . . . . . . . . . . . . Percentage of population in telephone exchange who are Hispanic

White_p. . . . . . . . . . . . . . . . . . . Percentage of population in telephone exchange who are non-Hispanic white

Black_p. . . . . . . . . . . . . . . . . . . Percentage of population in telephone exchange who are non-Hispanic black

Asian_pacif_p. . . . . . . . . . . . . . Percentage of population in telephone exchange who are non-Hispanic Asian 

or Pacific Islander

Household_density. . . . . . . . . . Household density in telephone exchange

Percent_listed . . . . . . . . . . . . . . Percentage of telephone numbers in telephone exchange that are residential 

listed

Owner_occupied_p. . . . . . . . . . Percentage of homes in telephone exchange that are owner-occupied

Rent_other_p . . . . . . . . . . . . . . Percentage of homes in telephone exchange that are rented or otherwise not 

owner-occupied

Table XXXI. Key survey estimates: Dual-frame sample

Analysis variable

Using design weight Using final weight

Estimate

95%

confidence

interval Estimate

95%

confidence

interval

Percentage of children in excellent 

or very good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.20 (82.38, 86.02) 84.16 (82.79, 85.53)

Percentage of children with consistent insurance 

coverage in past 12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.80 (86.76, 90.85) 88.72 (87.11, 90.33)

Percentage of children with one or more medical 

preventive care visits in past 12 months . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.78 (95.32, 96.23) 95.86 (95.38, 96.34)

Percentage of children with medical home . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.78 (52.20, 57.35) 53.92 (51.75, 56.09)

Percentage of children whose families ate a meal 

together every day in past week . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.72 (47.26, 50.18) 46.71 (45.52, 47.90)

Percentage of children usually or always safe in 

community or neighborhood. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86.83 (85.29, 88.36) 86.57 (85.28, 87.86)

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.86 (63.73, 67.99) 65.51 (63.50, 67.53)

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.77 (7.16, 8.37) 8.76 (8.01, 9.50)

Percentage of children with single-mother family 

structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.87 (18.20, 21.55) 19.02 (17.66, 20.38)

Percentage of children with other family structure . . . . . . . . . . . . . . . . . . . . . . . . . . 6.50 (6.09, 6.90) 6.71 (6.20, 7.22)
Page 214  Series 1, No. 59

These key survey estimates, which 

are computed among children with a 

completed interview, are shown in Table 

XXXI. Note that in computing these 

estimates, “don’t know” and “refused” 

responses were excluded from the 

denominators. 

NSCH Weighting

Although understanding how 

nonrespondents differ from respondents 

is important, a greater consideration for 

data users is how well the weighting 

adjustments that were made to correct for 

nonresponse actually did so. Thus, the 

following analyses attempted to answer 

two questions:

1. What level of bias would be 

present in the key survey estimates 

if no postsurvey adjustments for 

nonresponse were performed? That 

is, what is the effect of nonresponse 

on the raw estimates?

2. How well do the postsurvey 

adjustments for nonresponse 

mitigate the raw nonresponse bias?

To answer these questions, each 

of the analyses is presented twice, first 

using only the base weights—that is, the 

weights that reflect the probabilities of 

telephone number selection but do not 

reflect postsurvey adjustments—and then 

using either the nonresponse-adjusted 

weights (adjusted for nonresponse at each 

stage) or the final weights (both adjusted 

for nonresponse at each stage and raked 

to population control totals). Table 

XXXII shows the weight variables used 

in these analyses.

Assessing Nonresponse Bias 

in 2011–2012 NSCH

Response rate comparisons 

across subgroups

Comparing response rates across 

subgroups could reveal the presence 

of nonresponse bias in a survey. If the 

response rate is lower (or higher) for a 

particular subgroup relative to that of 

other subgroups, then it would indicate 

that the subgroup is underrepresented (or 

overrepresented) in the final sample, and, 

to the extent that the key survey estimate 

for that particular subgroup differs from 

other subgroups, bias would be indicated 

in the overall survey estimate. If, on 

the other hand, the response rate is the 

same across subgroups, or if the key 

survey estimate does not differ by these 

subgroups, the key survey estimate could 

still be biased, but unequal response rates 

across these subgroups will have been 

ruled out as a source of bias.

Table XXXIII presents the national 

response rates for various subgroups. The 

response rates are presented first using 

only the base weights, and then using 

the weights that have been sequentially 

adjusted for nonresponse at each stage. 

The subgroups were formed based on 

the sample frame information listed in 

Table XXX; for each continuous variable 

in this table, cases were classified 

into two subgroups: those with values 

above, and those with values below, 

the median value of the variable for all 

cases in the landline sample. Because 

the frame information is available only 

for the landline sample, the response 

rate comparisons in Table XXXIII are 

presented only for the landline sample. 

Table XXXIII shows that it was 

more difficult to interview households 

in urban areas, wealthier areas, and 

areas with larger nonwhite populations. 

The response rates were more than four 

percentage points higher for cases outside 

of metropolitan statistical areas (MSAs) 

than for cases inside MSAs, and about 

four percentage points lower for areas 

with higher household density. Response 

rates were lower in areas above the 

median in terms of measures associated 

with wealth (household income, home 

value, and rental costs), and higher in 

areas with a relatively older population. 

Finally, the response rates were four to 

five percentage points higher in areas 

above the median in terms of percentage 

of the population that is white, and 

lower in areas above the median in terms 

of percentage of the population that 

is Hispanic, black, or Asian. As when 

comparing base-weighted response rates 

to those using adjusted weights, the 

weighting adjustments for nonresponse 

did little to remove these response rate 

differences. These results are nearly 

identical to those observed in the 2007 

NSCH (3). 

There are a few limitations to this 

approach. First, to form subgroups, each 

continuous sampling frame variable in 

Table XXX had to be categorized into 

groups, resulting in a loss of some of the 

information contained in these variables. 

Second, the adjusted response rates 

presented in Table XXXIII necessarily 

reflect only the weighting adjustments 

for nonresponse at each stage, not the 

final raking of the weights to population 

control totals; the extent to which 

this final raking reduced the under- or 

overrepresentativeness of a particular 

subgroup in the final weighted sample 

was not captured by this analysis. Finally, 

because the frame information is not 

available for the cell-phone sample, 

Table XXXII. Weight variables used in nonresponse analysis

Weight name Description

BASE_WT Weight reflecting the initial selection probability of each telephone number in 

the sample (adjusted within each sampling frame in each sampling area by the 

proportion of released sample in each quarter). This weight is valid for all sampled 

telephone numbers.

DESIGN_WT BASE_WT adjusted for number of children in household and number of telephones 

(landlines or cell phones in household used by adults) and for overlapping sample 

frames. This weight is valid for all children with completed interviews.

RES_WT BASE_WT adjusted for nonresolution of telephone numbers. This weight is valid for 

all resolved telephone numbers.

AGE_SCR_WT RES_WT adjusted for nonresponse to age- and cell-phone-status eligibility 

screeners. This weight is valid for all households that completed the age- and cellstatus-eligibility screeners.

CH_SS_WT AGE_SCR_WT adjusted for subsampling of children within household. This weight 

is valid for all households that completed the age- and cell-status-eligibility 

screeners.

INT_WT CH_SS_WT adjusted for interview nonresponse. This weight is valid for all children 

with completed interviews.

CHILD_WT Final raked child weight. This weight is valid for all children with completed 

interviews.
Series 1, No. 59  Page 215 

the analysis was limited to the landline 

sample. 

The next section presents a similar 

approach that is not subject to the first 

limitation.

Using rich sampling frame data 

or supplemental matched data

Using the frame information, 

respondents at each stage of the survey 

were compared to all of the cases eligible 

for the stage. That is, the nonresponse 

bias in each frame variable was directly 

measured at each stage. (Because the 

frame information was available for both 

respondents and nonrespondents at each 

stage, the stage-specific nonresponse 

bias in these variables can be measured 

directly.) The overall nonresponse 

bias for the survey was estimated for 

each frame variable (i.e., the stagespecific measures of bias in the frame 

variables were used to estimate the total 

nonresponse bias in each frame variable 

across the stages of the survey). Logistic 

regression models were used to translate 

estimated overall biases in the frame 

variables into estimates of bias in the key 

survey estimates. 

Table XXXIV shows, for each 

stage of the survey, a comparison of the 

frame information for the entire landline 

sample eligible for the stage and the 

landline sample respondents to the stage, 

first using the base weights only and 

then using the weights that have been 

sequentially adjusted for nonresponse at 

each stage. For example, for the “Listed” 

variable in Table XXXIV, using the base 

weights generated an estimate of 40.7% 

of the entire landline sample of telephone 

numbers as residential-listed, while 

among the landline sample resolved cases 

(i.e., the respondents to the resolution 

stage), 35.7% were residential-listed. 

That is, after the resolution stage, without 

any adjustments for nonresolution, the 

landline sample is biased downward 

12.4% in terms of residential-listed 

status. However, using the weights that 

have been adjusted for nonresolution, 

40.7% of the landline sample resolved 

cases are residential-listed; that is, all of 

the bias in residential-listed status due 

to nonresolution has been removed by 

the nonresponse adjustment. (This is no 

accident; residential-listed status was one 

of the variables used to form the landline 

sample nonresponse adjustment cells.) 

Moving to the age-screener stage and 

using only the unadjusted base weights, 

among all landline sample resolved 

households, 89.5% were residentiallisted, and among landline sample 

age-screener respondents, 90.1% were 

residential-listed; i.e., the age-screener 

respondents were 0.7% more residentiallisted than they would have been if there 

had been full response at the age-screener 

stage, meaning that an upward bias of 

0.7% was introduced in residential-listed 

status at the age-screener stage. However, 

using the nonresolution adjusted 

weights, 91.3% of resolved households 

were listed, and, using the weights that 

were adjusted for nonresponse to the 

age-screener, 91.3% of age-screened 

households were listed. The weighting 

adjustment for non-age-screening 

removed all of the bias introduced by 

nonresponse to the age-screener stage.

Finally, moving to the interview 

stage and using only the base weights, 

87.0% of identified age-eligible 

households were residential-listed, and 

88.5% of the completed interviews 

were residential-listed—that is, among 

households completing the interview, 

1.7% more were residential-listed than 

all households that screened as eligible 

Table XXXIII. Response rates, by subgroup: Landline sample

Frame variable Subgroup

Response rate

Using 

base 

weight

Using 

adjusted 

weight

Listed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Not listed 34.60 34.21

Listed 34.24 34.16

Advance_letter . . . . . . . . . . . . . . . . . . . . . . Not sent 34.28 34.20

Sent 32.47 32.45

MSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outside MSA 41.84 42.09

In MSA 37.44 37.40

Median_HH_income. . . . . . . . . . . . . . . . . . Below median 39.72 39.65

Above median 36.80 36.84

Median_home_val . . . . . . . . . . . . . . . . . . . Below median 40.55 40.56

Above median 36.07 36.07

Median_rent. . . . . . . . . . . . . . . . . . . . . . . . Below median 40.80 40.90

Above median 35.86 35.81

Median_years_educ . . . . . . . . . . . . . . . . . . Below median 38.31 38.24

Above median 37.99 38.02

College_graduate . . . . . . . . . . . . . . . . . . . . Below median 38.46 38.39

Above median 37.84 37.87

Approx_median_age. . . . . . . . . . . . . . . . . . Below median 37.28 37.23

Above median 39.08 39.15

Hispanic_p. . . . . . . . . . . . . . . . . . . . . . . . . Below median 40.67 40.87

Above median 35.68 35.57

White_p. . . . . . . . . . . . . . . . . . . . . . . . . . . . Below median 35.84 35.71

Above median 40.25 40.40

Black_p. . . . . . . . . . . . . . . . . . . . . . . . . . . . Below median 38.81 38.92

Above median 37.45 37.29

Asian_pacif_p. . . . . . . . . . . . . . . . . . . . . . . Below median 40.14 40.27

Above median 36.38 36.30

Household_density. . . . . . . . . . . . . . . . . . . Below median 40.60 40.63

Above median 36.83 36.84

Percent_listed . . . . . . . . . . . . . . . . . . . . . . . Below median 38.27 38.13

Above median 37.61 37.67

Owner_occupied_p. . . . . . . . . . . . . . . . . . . Below median 37.11 36.89

Above median 38.96 39.12

Rent_other_p . . . . . . . . . . . . . . . . . . . . . . . Below median 38.96 39.12

Above median 37.12 36.89

NOTE: MSA is metropolitan statistical area.
Page 216  Series 1, No. 59

Table XXXIV. Comparing respondents and nonrespondents at each stage, using frame information: Landline sample

Frame variable Stage

Using base weight

Using 

nonresponseadjusted 

weight from 

previous stage

Using 

nonresponseadjusted weight

All cases 

eligible for 

stage

Respondents 

at stage

Respondent– 

All, percent 

difference

All cases 

eligible for 

stage

Respondents 

at stage

Respondent– 

All, percent 

difference

Listed . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.407 0.357 –0.124 0.407 0.407 2

0.000

2. Age screener 0.895 0.901 0.007 0.913 0.913 2

0.000

3. Interview 0.870 0.885 0.017 0.884 0.896 0.013

Overall1 ... ... –0.103 ... ... 0.013

Advance letter sent . . . . . . . . . . . . . . . . . 1. Resolution 0.241 0.192 –0.203 0.241 0.216 –0.102

2. Age screener 0.728 0.737 0.012 0.734 0.740 0.008

3. Interview 0.701 0.739 0.055 0.703 0.739 0.052

Overall ... ... –0.149 ... ... –0.048

In MSA . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.821 0.815 –0.007 0.821 0.821 2

0.000

2. Age screener 0.816 0.812 –0.005 0.819 0.819 –0.001

3. Interview 0.843 0.836 –0.008 0.850 0.848 –0.002

Overall ... ... –0.019 ... ... –0.003

Median_HH_income. . . . . . . . . . . . . . . . 1. Resolution 58,048 57,552 –0.009 58,048 58,012 –0.001

2. Age screener 59,279 59,164 –0.002 59,576 59,530 –0.001

3. Interview 62,254 62,052 –0.003 62,695 62,793 0.002

Overall ... ... –0.014 ... ... 2

0.000

Median_home_val . . . . . . . . . . . . . . . . . 1. Resolution 223,852 220,162 –0.017 223,852 223,732 –0.001

2. Age screener 222,173 220,718 –0.007 224,427 224,168 –0.001

3. Interview 234,208 229,556 –0.020 237,068 236,250 –0.004

Overall ... ... –0.042 ... ... –0.005

Median_rent . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 575 569 –0.011 575 575 –0.001

2. Age screener 573 570 –0.005 577 576 –0.001

3. Interview 599 592 –0.011 604 603 –0.002

Overall ... ... –0.026 ... ... –0.003

Median_years_educ . . . . . . . . . . . . . . . . 1. Resolution 13.41 13.40 –0.001 13.41 13.41 2

0.000

2. Age screener 13.41 13.41 2

0.000 13.41 13.42 20.000

3. Interview 13.47 13.49 0.001 13.47 13.48 0.001

Overall ... ... 0.001 ... ... 0.001

College_graduate . . . . . . . . . . . . . . . . . . 1. Resolution 0.299 0.297 –0.006 0.299 0.299 3

–0.000

2. Age screener 0.297 0.297 0.001 0.298 0.298 0.001

3. Interview 0.308 0.309 0.003 0.309 0.310 0.004

Overall ... ... –0.002 ... ... 0.005

Approx_median_age. . . . . . . . . . . . . . . . 1. Resolution 37.86 37.87 2

0.000 37.86 37.86 20.000

2. Age screener 37.96 38.02 0.001 37.96 37.98 0.001

3. Interview 37.33 37.36 0.001 37.21 37.23 0.001

Overall ... ... 0.003 ... ... 0.001

Hispanic_p . . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.140 0.138 –0.014 0.140 0.140 –0.000

2. Age screener 0.128 0.125 –0.026 0.130 0.129 –0.007

3. Interview 0.137 0.131 –0.044 0.144 0.142 –0.009

Overall ... ... –0.081 ... ... –0.016

White_p. . . . . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.662 0.664 0.002 0.662 0.662 3

–0.000

2. Age screener 0.692 0.698 0.008 0.691 0.692 0.002

3. Interview 0.683 0.693 0.014 0.677 0.681 0.006

Overall ... ... 0.024 ... ... 0.007

Black_p. . . . . . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.123 0.125 0.013 0.123 0.123 0.002

2. Age screener 0.109 0.108 –0.013 0.108 0.108 –0.002

3. Interview 0.104 0.103 –0.012 0.102 0.101 –0.013

Overall ... ... –0.012 ... ... –0.013

Asian_pacif_p. . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.046 0.045 –0.025 0.046 0.046 –0.003

2. Age screener 0.042 0.042 –0.018 0.043 0.043 –0.003

3. Interview 0.047 0.045 –0.045 0.048 0.047 –0.018

Overall ... ... –0.086 ... ... –0.024

Household_density. . . . . . . . . . . . . . . . . 1. Resolution 2.53 2.53 –0.002 2.53 2.53 2

0.000

2. Age screener 2.56 2.55 –0.003 2.56 2.55 –0.001

3. Interview 2.62 2.61 –0.005 2.64 2.63 –0.002

Overall ... ... –0.010 ... ... –0.003

See footnotes at end of table.
Series 1, No. 59  Page 217 

to complete the interview—indicating 

an upward bias of 1.7% at the interview 

stage. Using the weights adjusted for 

screener nonresponse, 88.4% of the 

identified eligible households were 

listed, and, using the weights that were 

adjusted for nonresponse to the interview, 

89.6% of interviewed households were 

listed. Thus, the interview nonresponse 

adjustment lowered, but did not 

completely eliminate, the residentiallisted bias introduced due to interview 

nonresponse. 

Multiplying together the biases 

at the resolution, age-screener, and 

interview stages, calculated using only 

the base weights, generated an estimate 

of the eligible household population 

identified and interviewed that is 10.3% 

less residential-listed than the eligible 

household population as a whole. 

(For this calculation, the proportion of 

residential-listed among unresolved 

cases that are actually households was 

assumed to be equal to the proportion 

residential-listed among the resolved 

households, and the proportion 

residential-listed among the non-agescreened households that are really 

age-eligible was assumed to be equal to 

the proportion residential-listed among 

age-screened eligible households.) 

Doing the same calculation but using the 

weights that were sequentially adjusted 

for nonresponse to each stage generated 

an estimate of the eligible household 

population identified and interviewed that 

is 1.3% more residential-listed than the 

eligible household population as a whole. 

That is, while a bias of about 10.3% in 

residential-listed status was introduced 

due to nonresponse at the resolution, 

age-screener, and interview stages, the 

weighting adjustments for nonresponse 

eliminated nearly all of that bias. 

Table XXXIV shows that this 

Table XXXIV. Comparing respondents and nonrespondents at each stage, using frame information: Landline sample—Con.

Frame variable Stage

Using base weight

Using 

nonresponseadjusted 

weight from 

previous stage

Using 

nonresponseadjusted weight

All cases 

eligible for

stage

Respondents 

at stage

Respondent–

All, percent

difference

All cases 

eligible for

stage

Respondents 

at stage

Respondent–

All, percent 

difference

Percent_listed . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.510 0.506 –0.009 0.510 0.508 –0.005

2. Age screener 0.554 0.555 0.001 0.555 0.554 –0.001

3. Interview 0.558 0.559 0.003 0.558 0.558 2

0.000

Overall ... ... –0.006 ... ... –0.005

Owner_occupied_p. . . . . . . . . . . . . . . . . 1. Resolution 0.661 0.661 3

–0.000 0.661 0.662 20.000

2. Age screener 0.689 0.691 0.002 0.689 0.689 2

0.000

3. Interview 0.690 0.694 0.005 0.689 0.691 0.003

Overall ... ... 0.007 ... ... 0.003

Rent_other_p . . . . . . . . . . . . . . . . . . . . . 1. Resolution 0.339 0.339 0.001 0.339 0.339 3

–0.000

2. Age screener 0.311 0.309 –0.005 0.311 0.311 2

0.000

3. Interview 0.310 0.306 –0.012 0.311 0.309 –0.006

Overall 190 ... –0.016 ... ... –0.006

. . . Category not applicable.

1

Equal to the product of Respondent–All percent difference across the resolution, age-screener, and interview stages. This provides an estimate of the percentage difference in the frame variable 

between interview respondents and nonrespondents at any stage who are eligible for interview (households with children); that is, the resulting estimate is of the over- or underrepresentativeness of 

the interviewed households compared with eligible households as a whole. This technique assumes that the mean of the frame variable for eligible nonrespondents equals the observed mean of the 

frame variable for respondents. Using Residential listed as an example, this approach assumes that, among nonresolved numbers that are actually households, the proportion that are listed is equal to 

proportion that are listed among resolved households; and it assumes that, among nonage-screened households that actually contain children, the proportion that are listed is equal to the proportion 

that are listed among age-screened-eligible households.

2

0.000 quantity more than zero but less than 0.0005. 

3

–0.000 quantity more than –0.0005 but less than zero.

NOTES: MSA is metropolitan statistical area. Median_HH_income, Median_home_val, and Median_rent variables are in dollars.

Table XXXV. Observed and expected means of frame variables for respondents: Landline 

sample

Frame variable

Through interview stage

Using base weight

Using nonresponseadjusted weight

Observed Expected Observed Expected

Listed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.45 98.59 89.55 88.40

Advance_letter . . . . . . . . . . . . . . . . . . . . . . 73.94 86.92 73.94 77.66

MSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.64 85.27 84.75 84.97

Median_HH_income. . . . . . . . . . . . . . . . . . 62,052 62,913 62,793 62,783

Median_home_val . . . . . . . . . . . . . . . . . . . 229,556 239,702 236,250 237,469

Median_rent. . . . . . . . . . . . . . . . . . . . . . . . 592 608 603 603

Median_years_educ . . . . . . . . . . . . . . . . . . 13.49 13.48 13.48 13.47

College_graduate . . . . . . . . . . . . . . . . . . . . 30.92 30.97 30.98 30.84

Approx_median_age. . . . . . . . . . . . . . . . . . 37.36 37.27 37.23 37.19

Hispanic_p. . . . . . . . . . . . . . . . . . . . . . . . . 13.10 14.26 14.22 14.46

White_p. . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.25 67.60 68.07 67.59

Black_p. . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.29 10.41 10.09 10.22

Asian_pacif_p. . . . . . . . . . . . . . . . . . . . . . . 4.50 4.92 4.72 4.83

Household_density. . . . . . . . . . . . . . . . . . . 2.61 2.63 2.63 2.64

Percent_listed . . . . . . . . . . . . . . . . . . . . . . . 55.93 56.25 55.78 56.09

Owner_occupied_p. . . . . . . . . . . . . . . . . . . 69.38 68.88 69.13 68.94

Rent_other_p . . . . . . . . . . . . . . . . . . . . . . . 30.62 31.12 30.87 31.06

NOTES: MSA is metropolitan statistical area. Median_HH_income, Median_home_val, and Median_rent variables are in dollars.
Page 218  Series 1, No. 59

is generally the case for the other 

frame variables as well. Nonresponse 

introduced small biases, but the 

nonresponse adjustments substantially 

reduced those biases. The variables with 

the largest biases remaining after the 

nonresponse adjustments are advancedletter status (–4.8%), the percentage of 

the population in the telephone exchange 

that is non-Hispanic Asian or Pacific 

Islander (–2.4%), the percentage of the 

population in the telephone exchange that 

is Hispanic (–1.6%), and the percentage 

of the population in the telephone 

exchange that is non-Hispanic black 

(–1.3%). 

Table XXXV shows the observed 

means of the frame variables for the 

landline sample respondents, and the 

means that would be expected under 

full response. The biases in the frame 

information translate into biases in the 

key survey estimates only to the extent 

that the frame information is related to 

the key survey estimates. To examine 

these relationships for each key survey 

estimate, a logistic regression model was 

estimated of the form,

pi = e Xi

'

 ß

1+e Xi

'

 ß

where pi is the probability that the ith 

respondent’s child is positive for the key 

survey variable (i.e., is in excellent or 

very good health, has a medical home, 

and so on), Xi

' is a vector containing the 

frame information for the ith child, and β

is a vector of unknown parameters to be 

estimated. By evaluating the fitted model 

first at the observed means of the frame 

information and then at the expected 

means of the frame information from 

Table XXXV, an estimate of the bias in 

each key survey estimate was generated 

that could be attributed to biases in the 

frame variables due to nonresponse. 

These estimates of biases in the key 

survey estimates using this approach are 

shown in Table XXXVI.

As Table XXXVI shows, the small 

biases in the frame information translate 

into small biases in the key survey 

estimates for the landline sample. In these 

analyses, the largest landline sample 

bias found when the base weights were 

used was in the percentage of children 

with a two-parent (stepparent) family 

structure (8.8% bias), but this bias was 

reduced to 0.4% when the nonresponseadjusted weights were used. The largest 

landline sample absolute bias when the 

nonresponse-adjusted weights were used 

was in the percentage of children with a 

single-mother family structure (–0.8% 

bias).

Although these results suggest that 

differences between landline sample 

respondents and nonrespondents in terms 

of the frame information lead to very 

little bias in the key survey estimates, this 

does not necessarily mean that the key 

survey estimates are biased very little. 

It is possible that differences between 

the landline sample respondents and 

nonrespondents are not reflected in the 

frame information. 

Indeed, the relationship between 

the frame information and the key 

survey variables is poor. One method of 

assessing how well the logistic regression 

model relates the frame information to 

the key survey variable is to examine 

the receiver operating characteristic 

(ROC) curve. For each child, the model 

produces a predicted probability of, for 

example, the child being in excellent or 

very good health; the ROC curve shows 

how well the model prediction of whether 

the child is in excellent or very good 

health agrees with whether the child 

truly is in excellent or very good health, 

using various cutoff values for turning 

the model’s predicted probability into a 

binary prediction of special-needs status. 

If the area under the ROC curve equals 

1.0, then the model perfectly predicts the 

response for all cutoff values; if the area 

under the ROC curve equals 0.5, then 

Table XXXVI. Estimates of nonresponse biases in key survey estimates attributable to biases in frame information: Landline sample

Key survey variable

Using base weight Using nonresponse-adjusted weight

Model evaluated 

at observed 

respondent 

means of frame 

information1

Model evaluated 

at means of 

frame information 

expected under 

full response

Estimated 

percent 

bias2

Model evaluated 

at observed 

respondent 

means of frame 

information1

Model evaluated 

at means of 

frame information 

expected under 

full response

Estimated 

percent 

bias2

Percentage of children in excellent 

or very good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.82 88.97 –0.17 88.56 88.46 0.12

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . . . . . . . . . 93.04 93.35 –0.34 93.07 93.04 0.03

Percentage of children with one or more medical 

preventive care visits in past 12 months . . . . . . . . . . . . . . 95.46 95.52 –0.06 95.64 95.68 –0.04

Percentage of children with medical home . . . . . . . . . . . . . 60.54 61.16 –1.02 60.50 60.33 0.27

Percentage of children whose families ate a meal 

together every day in past week . . . . . . . . . . . . . . . . . . . . 42.85 41.84 2.42 43.30 43.25 0.12

Percentage of children usually or always safe in 

community or neighborhood. . . . . . . . . . . . . . . . . . . . . . . 92.40 92.45 –0.05 92.18 92.06 0.13

Percentage of children with two-parent family structure 

(biological or adoptive) . . . . . . . . . . . . . . . . . . . . . . . . . . . 74.75 76.04 –1.71 76.51 76.38 0.17

Percentage of children with two-parent family structure 

(stepfamily) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.97 4.57 8.77 5.34 5.32 0.36

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.76 13.19 4.33 12.46 12.55 –0.74

Percentage of children with other family structure . . . . . . . 5.61 5.42 3.60 4.84 4.87 –0.67

1

Although the logistic regression models at the observed means of the frame information were evaluated, the results are not the observed means of the key survey variables (i.e., the final estimates of 

the proportion of children in excellent or very good health, the proportion of children with a medical home, and so on), as would be the case for linear regression models.

2

Calculated as (model evaluated at observed means – model evaluated at expected means) / model evaluated at expected means. 
Series 1, No. 59  Page 219 

Table XXXVII. Comparing demographic, socioeconomic, and health estimates with benchmarks

Characteristic

Benchmark Using design weight Using final weight Design 

weight to 

benchmark 

difference

Final 

weight to 

benchmark

Estimate difference

Standard 

error Estimate

Standard 

error Estimate

Standard 

error

Age group (years) 

of child (ACS)1,2

0–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.76 0.04 15.29 0.28 15.76 0.27 –0.47 30.00

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.97 0.05 18.41 0.31 16.97 0.27 *1.44 3

0.00

6–8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.54 0.05 18.49 0.36 16.54 0.27 *1.95 3

0.00

9–12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.46 0.05 22.91 0.30 22.46 0.30 0.46 3

0.00

13–17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.27 0.05 24.90 0.34 28.27 0.33 *–3.37 3

0.00

Sex of child (ACS)1,2

Male. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.14 0.03 52.11 0.40 51.14 0.37 **0.96 30.00

Female. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.86 0.03 47.89 0.40 48.86 0.37 **–0.96 3

0.00

Race and ethnicity 

of child (ACS)1,2

Hispanic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.55 0.01 23.92 0.43 23.51 0.36 0.37 –0.04

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . . . . 13.78 0.03 11.29 0.24 13.73 0.25 *–2.49 –0.05

Non-Hispanic Asian or Hawaiian or

 other Pacific Islander. . . . . . . . . . . . . . . . . . . . . 4.48 0.02 3.64 0.13 4.43 0.18 *–0.84 –0.04

Non-Hispanic American Indian or 

Alaska Native. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.78 0.01 0.98 0.05 0.95 0.05 *0.20 *0.16

Non-Hispanic other. . . . . . . . . . . . . . . . . . . . . . . . 57.41 0.04 60.17 0.41 57.38 0.37 *2.76 –0.03

Number of children in 

household (ACS)1,2

One. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.23 0.20 22.12 0.24 23.23 0.27 *–1.11 30.00

Two . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.33 0.12 38.62 0.36 38.33 0.35 0.28 3

0.00

Three or more. . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.44 0.26 39.26 0.43 38.44 0.38 0.83 3

0.00

Household income (ACS)1,2

Less than $10,000 . . . . . . . . . . . . . . . . . . . . . . . . 6.83 0.06 8.11 0.33 6.80 0.19 *1.28 –0.03

$10,000–$19,999 . . . . . . . . . . . . . . . . . . . . . . . . . 9.23 0.07 12.47 0.35 9.27 0.22 *3.23 0.03

$20,000–$39,999 . . . . . . . . . . . . . . . . . . . . . . . . . 19.28 0.09 18.96 0.33 19.28 0.30 –0.32 3

0.00

$40,000–$59,999 . . . . . . . . . . . . . . . . . . . . . . . . . 16.35 0.09 13.23 0.25 16.35 0.29 *–3.13 3

0.00

$60,000 or more . . . . . . . . . . . . . . . . . . . . . . . . . . 48.31 0.14 47.24 0.38 48.31 0.36 *–1.07 3

0.00

Highest education of adults 

in household (ACS)1,2

Less than 12 years . . . . . . . . . . . . . . . . . . . . . . . . 11.57 0.09 11.52 0.38 11.56 0.29 –0.05 –0.01

High school graduate (12 years). . . . . . . . . . . . . . 19.96 0.09 17.56 0.32 19.99 0.31 *–2.40 0.03

Some college or college graduate . . . . . . . . . . . . 68.47 0.13 70.92 0.43 68.45 0.37 *2.45 –0.02

Housing tenure (ACS)1,2

Owner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60.96 0.19 62.67 0.42 60.96 0.37 *1.71 30.00

Renter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37.25 0.20 35.61 0.42 37.34 0.37 *–1.64 0.09

Other arrangement . . . . . . . . . . . . . . . . . . . . . . . . 1.79 0.03 1.72 0.11 1.70 0.09 –0.07 –0.09

Family type (ACS)2

Other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.99 0.13 33.81 0.41 33.29 0.35 –0.18 –0.69

Married parents . . . . . . . . . . . . . . . . . . . . . . . . . . 66.01 0.13 66.19 0.41 66.71 0.35 0.18 0.69

Insurance coverage (ACS)2

With insurance coverage . . . . . . . . . . . . . . . . . . . 92.51 0.06 94.45 0.30 94.50 0.19 *1.94 *2.00

Without insurance coverage . . . . . . . . . . . . . . . . . 7.49 0.06 5.55 0.30 5.50 0.19 *–1.94 *–2.00

Insurance coverage (NHIS)2

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93.00 0.27 94.45 0.30 94.50 0.19 *1.45 *1.50

No. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.00 0.27 5.55 0.30 5.50 0.19 *–1.45 *–1.50

Health status (NHIS)

Excellent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56.16 0.51 60.38 0.40 60.52 0.36 *4.21 *4.36

Very good . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.58 0.43 23.83 0.36 23.64 0.31 *–2.75 *–2.94

Good. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 0.38 12.59 0.30 12.69 0.27 *–2.71 *–2.61

Fair or poor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.96 0.12 3.20 0.16 3.15 0.14 *1.25 *1.19

See footnotes at end of table.
Page 220  Series 1, No. 59

the model does no better than random 

chance in predicting the response. The 

models relating the frame information to 

the key survey variables had areas under 

the ROC curves ranging from 0.56 to 

0.71, indicating that the models do not 

do much better than randomly choosing 

the response. Therefore, while the models 

indicate little bias in the key survey 

estimates, they have little power to detect 

such bias because the frame information 

is not well-related to the key survey 

variables.

The results in this section include 

only the landline sample and do 

not reflect the final raking of the 

nonresponse-adjusted weights to 

population control totals. This final 

raking could have reduced or increased 

bias, but if so, that reduction or increase 

was not captured in the analysis in 

this section. The next sections present 

analyses that made use of the final, raked 

weights for the dual-frame sample.

Comparison to similar estimates 

from other sources

A more direct method of estimating 

survey bias than the methods explored 

so far is to compare the survey estimates 

to benchmark estimates from other, 

potentially higher-quality sources. 

Table XXXVII presents demographic, 

socioeconomic, and health estimates 

for variables in common between the 

2011–2012 NSCH and external sources, 

including the 2011 American Community 

Survey (ACS), 2011 National Health 

Interview Survey (NHIS), and 2011 

Medical Expenditure Panel Survey 

(MEPS). Each of these external surveys 

included in-person interviewing and 

achieved a higher response rate than 

NSCH, and, therefore, may be higherquality sources of estimates for these 

variables and serve as benchmarks. 

A comparison between the NSCH 

estimate and the benchmark estimate 

from the external source was made for 

the following: age category of the child, 

sex of the child, race and ethnicity of 

the child, number of children in the 

household, household income, highest 

education of adults in the household, 

housing tenure, family type, insurance 

coverage, health status of the child, 

special health care needs status of the 

child, and indicators of whether the 

respondent has been told the child has 

asthma and whether the child has a usual 

place for health care. 

When the design weights are used 

to produce the NSCH estimates, a 

statistically significant difference between 

the NSCH estimate and the benchmark 

estimate is seen for nearly all of the 

comparisons, although the differences 

are quite small in magnitude, with 

most differences being less than two 

percentage points. The largest difference 

is in the proportion of children reported 

to be in excellent health: The NSCH 

estimate is 4.2 percentage points higher 

than the NHIS estimate (although 2.6 

percentage points higher than the MEPS 

estimate). 

When the final weights—adjusted 

for nonresponse and raked to population 

control totals—are used to produce the 

NSCH estimates, the differences between 

the NSCH estimates and the benchmark 

estimates fall to nearly zero for all of 

the demographic and socioeconomic 

variables (except insurance status), 

because nearly all of these variables 

were used in raking the NSCH weights, 

as indicated in the footnote to Table 

XXXVII. Statistically significant 

differences between the NSCH estimate 

and the benchmark estimate remain 

for the percentage of children who are 

Table XXXVII. Comparing demographic, socioeconomic, and health estimates with benchmarks—Con.

Characteristic

Benchmark Using design weight Using final weight Design 

weight to 

benchmark 

difference

Final 

weight to 

benchmark

Estimate difference

Standard 

error Estimate

Standard

error Estimate

Standard

error

Health status (MEPS)

Excellent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.74 1.01 60.38 0.40 60.52 0.36 **2.64 *2.78

Very good . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.08 0.66 23.83 0.36 23.64 0.31 *–2.25 *–2.44

Good. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4 0.67 12.59 0.30 12.69 0.27 –0.80 –0.71

Fair . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.35 0.20 2.78 0.15 2.73 0.13 0.43 0.37

Poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.44 0.09 0.42 0.05 0.43 0.05 –0.02 –0.01

Special health care needs (MEPS)

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.48 0.61 19.89 0.30 19.8 0.28 **1.41 **1.33

No. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.52 0.62 80.11 0.30 80.2 0.28 **–1.41 –1.33

Ever told child has asthma (NHIS)

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.04 0.39 14.11 0.25 14.65 0.25 0.07 0.61

No. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.96 0.39 85.89 0.25 85.35 0.25 –0.07 –0.61

Has usual place for health care (NHIS)

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96.70 0.19 93.78 0.22 93.58 0.21 *–2.92 *–3.12

No. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.30 0.19 6.22 0.22 6.42 0.21 *2.92 *3.12

* Statistically significant at the 0.01 level.

** Statistically significant at the 0.05 level. 1

Variable used in the raking adjustment of final National Survey of Children’s Health weights. 

2

Missing values have been imputed. 

3

0.00 quantity more than zero but less than 0.005. 

NOTE: ACS is American Community Survey, NHIS is National Health Interview Survey, and MEPS is Medical Expenditure Panel Survey.
Series 1, No. 59  Page 221 

Native American or Alaska Native, the 

percentage with insurance coverage, 

health status, the percentage with special 

health care needs, and the percentage 

with a usual place for health care.

While the preceding analyses aimed 

to describe and measure nonresponse 

bias, these comparisons between NSCH 

and benchmark estimates are measuring 

bias due not only to nonresponse but 

also to noncoverage of the sampling 

frames and measurement error. Moreover, 

these comparisons are measuring only 

differential bias between the NSCH 

and benchmark surveys—although the 

benchmark surveys are likely higherquality sources, they may themselves 

suffer from bias due to nonresponse, 

noncoverage, and measurement error.

To turn these estimates of bias in the 

estimates common between the NSCH 

and benchmark surveys into estimates of 

bias in the NSCH key survey estimates, 

for each key survey estimate, a logistic 

regression model was fitted relating the 

variables in Table XXXVII to the NSCH 

key survey variable. The fitted model was 

then evaluated, first using values of the 

NSCH estimates and then using values 

of the benchmark estimates. (This is the 

same approach as used above to relate 

biases in the frame variables to biases in 

the key survey variables.) The estimates 

of biases in the NSCH key survey 

estimates using this approach are shown 

in Table XXXVIII. Note that when fitting 

the model for the percentage of children 

in excellent or very good health, the 

health status variable in Table XXXVII

was excluded from the covariates because 

that is the same variable being modeled. 

Similarly, when fitting the model for the 

percentage of children with consistent 

insurance, insurance status was excluded 

from the covariates; when fitting the 

model for the percentage of children with 

a medical home, the indicator of whether 

the child has a usual place for health 

care was excluded from the covariates; 

and when fitting the model for family 

structure, family type was excluded from 

the covariates. When evaluating the 

models using the benchmark estimates, 

the ACS insurance coverage estimate 

was used (rather than the NHIS insurance 

coverage estimate), and the NHIS health 

status estimates were used (rather than 

the MEPS health status estimates).

As seen in Table XXXVIII, the 

small differences in the demographic, 

socioeconomic, and health estimates 

between the NSCH and benchmark 

surveys from Table XXXVII translate 

into even smaller differences in the key 

survey estimates. The largest absolute 

bias estimated using the design weights is 

in the percentage of children with a twoparent stepfamily structure (–2.49% bias), 

but this bias is reduced to –0.13% when 

the final weights are used. The largest 

absolute bias when the final weights are 

used is in the percentage of children with 

a medical home (1.37% bias).

Estimates of bias using this method 

rely on models relating the characteristics 

in Table XXXVII to the NSCH key 

survey variables. Biases are possible 

in the NSCH key survey estimates that 

are not related to the characteristics in 

Table XXXVII. The area under the ROC 

curve values for these models ranged 

from 0.65 to 0.79, indicating that while 

these models are somewhat better than 

the models described previously relating 

the frame information to the key survey 

variables, the models are not perfect.

Studying variation within the 

existing survey

In a “level of effort” analysis, those 

respondents who respond only after a 

great deal of interviewing effort has 

been applied are assumed to resemble 

nonrespondents. Given this assumption, 

a difference in a survey estimate between 

Table XXXVIII. Estimates of bias in key survey estimates attributable to biases in demographic, socioeconomic, and health characteristics, 

based on comparisons with benchmark estimates: Dual-frame sample

Key survey variable 

Using design weight Using final weight

Model evaluated 

at NSCH 

estimates of 

characteristics1

Model evaluated 

at benchmark 

estimates of 

characteristics

Estimated 

percent 

bias2

Model evaluated 

at NSCH 

estimates of 

characteristics1

Model evaluated 

at benchmark 

estimates of 

characteristics

Estimated 

percent 

bias2

Percentage of children in excellent 

or very good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.91 89.12 –0.24 88.77 89.01 –0.27

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . . . . . . . . . 90.92 91.00 –0.09 90.74 90.95 –0.23

Percentage of children with one or more medical 

preventive care visits in past 12 months . . . . . . . . . . . . . . 96.56 96.61 –0.05 96.63 96.54 0.09

Percentage of children with medical home . . . . . . . . . . . . . 54.54 53.36 2.20 53.68 52.95 1.37

Percentage of children whose families ate a meal 

together every day in past week . . . . . . . . . . . . . . . . . . . . 48.64 47.50 2.40 46.46 46.22 0.52

Percentage of children usually or always safe in 

community or neighborhood. . . . . . . . . . . . . . . . . . . . . . . 89.90 89.71 0.22 89.40 89.32 0.09

Percentage of children with two-parent family structure 

(biological or adoptive) . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.44 69.48 –0.06 68.67 68.87 –0.29

Percentage of children with two-parent family structure 

(stepfamily) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.50 5.64 –2.49 6.43 6.44 –0.13

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.44 14.09 2.44 14.00 13.88 0.82

Percentage of children with other family structure . . . . . . . 5.24 5.33 –1.70 5.43 5.40 0.67

1

Although the logistic regression models at the National Survey of Children’s Health (NSCH) estimates of the characteristics were evaluated, the results are not the observed estimates of the key 

survey variables (i.e., the final estimates of the proportion of children in excellent or very good health, the proportion of children with a medical home,and so on), as would be the case for linear 

regression models. 

2

Calculated as (model evaluated at NSCH estimates – model evaluated at benchmark estimates) / model evaluated at benchmark estimates. 
Page 222  Series 1, No. 59

Table XXXIX. Comparing non-HUDIs with converted HUDIs, by sample type

Key survey outcome

Landline sample Cell-phone sample

Non-HUDIs 

estimate

Converted 

HUDIs 

estimate

High-effort 

to low-effort 

respondents,

percent

difference1

p value 

for test of no 

difference

Non-HUDIs 

estimate

Converted 

HUDIs 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Percentage of children in excellent 

or very good health. . . . . . . . . . . . . . . . . . . . . . 88.26 82.16 –6.91 2

0.000000 82.99 78.96 –4.86 0.006373

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 92.44 90.12 –2.51 0.000005 87.05 82.96 –4.71 0.044709

Percentage of children with one or more 

medical preventive care visits in past 

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.33 95.25 –0.08 0.809604 96.12 96.51 0.40 0.539438

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 62.09 53.65 –13.60 2

0.000000 52.26 43.55 –16.66 0.000002

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 44.78 44.61 –0.37 0.845207 51.93 53.59 3.20 0.362083

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 90.97 87.44 –3.89 2

0.000000 85.05 80.18 –5.73 0.009424

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 75.32 71.04 –5.68 0.171837 59.69 54.03 –9.48 0.002898

Percentage of children with two-parent 

family structue (stepfamily). . . . . . . . . . . . . . . . 6.04 6.55 8.39 0.171837 8.99 9.88 9.85 0.407695

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 13.29 16.19 21.79 0.000009 23.92 29.04 21.44 0.009198

Percentage of children with 

other family structure . . . . . . . . . . . . . . . . . . . . 5.35 6.22 16.38 0.019321 7.40 7.04 –4.84 0.619973

1

Calculated as (converted HUDI respondent mean – non-HUDI respondent mean) / non-HUDI respondent mean.

20.000000 quantity more than zero but less than 0.0000005.

NOTES: HUDI is hung up during introduction. Estimates in this table are weighted by the design weights. 

Table XL. Comparing non-HUDIs with converted HUDIs: Dual-frame sample

Key survey outcome

Using design weight Using final weight

Non-HUDIs 

estimate

Converted 

HUDIs 

estimate

High-effort

to low-effort

respondents,

percent

difference1

p value 

for test of no 

difference

Non-HUDIs 

estimate

Converted 

HUDIs 

estimate

High-effort

to low-effort

respondents, 

percent

difference1

p value 

for test of no 

difference

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.42 80.61 –5.63 2

0.000000 85.26 80.99 –5.01 20.000000

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 89.54 86.65 –3.23 0.006497 89.13 87.54 –1.78 0.010425

Percentage of children with one or more 

medical preventive care visits in past

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.75 95.86 0.12 0.755726 95.91 95.72 –0.20 0.583534

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 56.81 48.74 –14.21 2

0.000000 55.98 47.96 –14.33 20.000000

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 48.63 48.96 0.67 0.746665 46.83 46.35 –1.02 0.575015

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 87.80 83.94 –4.39 0.000092 87.47 83.96 –4.01 2

0.000000

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 66.90 62.81 –6.10 0.000123 66.13 63.73 –3.64 0.003597

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 7.63 8.16 6.91 0.345845 8.81 8.60 –2.40 0.658776

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 19.02 22.41 17.83 0.001444 18.46 20.63 11.75 0.001777

Percentage of children with 

other family structure . . . . . . . . . . . . . . . . . . . . 6.46 6.62 2.57 0.682164 6.59 7.04 6.84 0.313725

1

Calculated as (converted HUDI respondent mean – non-HUDI respondent mean) / non-HUDI respondent mean.

20.000000 quantity more than zero but less than 0.0000005.

NOTE: HUDI is hung up during introduction.
Series 1, No. 59  Page 223 

“high-effort” respondents and “loweffort” respondents would indicate that a 

difference exists between the respondents 

and nonrespondents, and, therefore, the 

survey estimate is biased. 

“Interviewing effort” was measured 

in three ways: verbal refusal status, 

nonverbal refusal status (i.e., whether 

the respondent “hung up during the 

introduction” [HUDI]), and the number 

of calls placed. It was assumed that 

respondents who verbally refused at least 

once, who nonverbally refused at least 

once, or who required more calls before 

completing the interview were “higheffort” respondents and would resemble 

the nonrespondents with respect to the 

key survey variables.

Table XXXIX compares, by 

sample type, the key survey estimates 

for converted HUDI cases with those 

for cases that completed the interview 

without a HUDI, using the design 

weights. Table XL shows the same 

comparison for the dual-frame sample, 

first using the design weights and then 

using the final weights. Tables XLI

and XLII show the comparisons for 

converted verbal refusals compared 

with cases that completed without a 

verbal refusal. Tables XLIII and XLIV

show the comparisons for households 

completing the interview in five or more 

calls compared with those completing 

in four or fewer calls. If high-effort 

respondents resemble nonrespondents, 

then a difference in the survey estimate 

between converted HUDIs and nonHUDIs, between converted refusals and 

nonrefusals, or between those completing 

in five calls or more and those completing 

in four calls or fewer would suggest the 

presence of nonresponse bias.

Findings of the level-of-effort 

analyses for each of the key survey 

estimates presented in the tables are 

summarized as:

● The percentage of children in 

excellent or very good health is 

significantly lower for converted 

HUDIs than non-HUDIs and for 

households completing in five calls 

or more than for those completing 

in fewer than five calls, and does 

not significantly differ by converted 

refusals status. These results hold 

both for the dual-frame estimates as 

well as for the landline and cellphone samples individually.

● The percentage of children with 

consistent insurance coverage in 

the past 12 months is significantly 

lower for converted HUDIs than 

for non-HUDIs, for the dual-frame 

estimates as well as for the landline 

and cell-phone samples individually. 

The estimate does not significantly 

differ by converted refusals status 

in the landline sample but is 

significantly higher for converted 

refusals in the cell-phone sample. 

For the dual-frame sample, it is 

significantly higher for converted 

refusals when the design weights are 

used but not significantly different 

for converted refusals when the 

final weights are used. It is not 

significantly different in the landline 

sample for households completing in 

five calls or more but is significantly 

lower for such households in the cellphone sample; it is not significantly 

different for households completing 

in five calls or more in the dualframe sample.

● The percentage of children with 

one or more medical preventive 

care visits in the past 12 months

Table XLI. Comparing nonrefusals with converted refusals, by sample type

Key survey outcome

Landline sample Cell-phone sample

Nonrefusals 

estimate

Converted 

refusals 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Nonrefusals 

estimate

Converted 

refusals 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 86.69 86.18 –0.58 0.447945 82.32 80.63 –2.05 0.255847

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 91.73 92.07 0.38 0.504661 85.64 88.54 3.38 0.023283

Percentage of children with one or more 

medical preventive care visits in past

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.34 95.16 –0.19 0.612689 96.29 95.77 –0.55 0.451086

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 59.80 59.76 –0.07 0.959741 50.08 50.95 1.73 0.648161

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 44.98 43.79 –2.65 0.163179 52.15 53.20 2.01 0.565239

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 90.05 89.85 –0.22 0.737948 84.02 83.40 –0.73 0.678775

Percentage of children withtwo-parent family 

structure (biological or adoptive) . . . . . . . . . . . 74.28 73.59 –0.93 0.258397 59.11 54.33 –8.08 0.012286

Percentage of children withtwo-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 6.08 6.55 7.72 0.258397 9.17 9.40 2.51 0.802020

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 14.33 13.15 –8.24 0.041193 24.67 27.49 11.42 0.165187

Percentage of children with other 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 5.30 6.70 26.47 0.000686 7.05 8.78 24.57 0.046685

1

Calculated as (converted refusal respondent mean – nonrefusal respondent mean) / nonrefusal respondent mean.

NOTE: Estimates in this table are weighted by the design weights.
Page 224  Series 1, No. 59

Table XLII. Comparing nonrefusals with converted refusals: Dual-frame sample

Key survey outcome

Using design weight Using final weight

Nonrefusals 

estimate

Converted 

refusals 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Nonrefusals 

estimate

Converted 

refusals 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.32 83.64 –0.80 0.387218 84.34 83.37 –1.15 0.212067

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 88.44 90.46 2.28 0.002985 88.52 89.61 1.23 0.086810

Percentage of children with one or more 

medical preventive care visits in past

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.85 95.44 –0.43 0.274216 95.99 95.31 –0.71 0.103692

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 54.56 55.77 2.22 0.226337 53.86 54.18 0.60 0.735497

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 48.86 48.09 –1.57 0.437109 46.72 46.65 –0.17 0.933623

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 86.81 86.92 0.14 0.879602 86.78 85.62 –1.34 0.131287

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 66.09 64.82 –1.92 0.224943 65.59 65.20 –0.59 0.669436

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 7.75 7.85 1.29 0.837928 8.69 9.04 4.01 0.532538

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 19.92 19.68 –1.18 0.823169 19.17 18.38 -4.12 0.299814

Percentage of children with 

other family structure . . . . . . . . . . . . . . . . . . . . 6.24 7.65 22.50 0.002362 6.55 7.38 12.65 0.088420

1

Calculated as (converted refusal respondent mean – nonrefusal respondent mean) / nonrefusal respondent mean.

Table XLIII. Comparing low-call-attempt respondents with high-call-attempt respondents, by sample type

Key survey outcome

Landline sample Cell-phone sample

Respondents 

with four calls 

or fewer 

estimate

Respondents 

with five calls 

or more 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Respondents 

with four calls 

or fewer 

estimate

Respondents 

with five calls 

or more 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value 

for test of no 

difference

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.63 85.23 –3.84 2

0.000000 83.68 80.69 –3.58 0.006375

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 91.89 91.74 –0.16 0.726831 87.63 84.81 –3.21 0.020603

Percentage of children withone or more 

medical preventive 

 care visits in past 12 months . . . . . . . . . . . . . . 94.86 95.60 0.78 0.010992 95.73 96.62 0.94 0.127282

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 62.09 58.27 –6.15 2

0.000000 52.31 48.46 –7.35 0.005593

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 47.33 43.03 –9.09 2

0.000000 53.06 51.69 –2.59 0.307987

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 90.69 89.55 –1.26 0.017422 84.69 83.28 –1.66 0.260514

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 73.85 74.33 0.64 0.451926 57.91 58.75 1.45 0.543220

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 6.54 5.94 –9.19 0.083627 9.63 8.85 –8.11 0.315847

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 13.72 14.33 4.45 0.223155 24.89 25.30 1.63 0.758344

Percentage of children with 

other family structure . . . . . . . . . . . . . . . . . . . . 5.88 5.40 –8.21 0.139186 7.57 7.11 –6.13 0.451419

1

Calculated as (five or more calls respondent mean – four or fewer calls respondent mean) / (four or fewer calls respondent mean).

20.000000 quantity more than zero but less than 0.0000005.

NOTE: Estimates in this table are weighted by the design weights. 
Series 1, No. 59  Page 225 

is not significantly different for 

converted HUDIs or converted 

refusals. It is significantly higher 

for households completing in five 

calls or more in the landline sample 

but not significantly different for 

such households in the cell-phone 

sample; it is significantly higher for 

households completing in five calls 

or more in the dual-frame sample.

● The percentage of children with a 

medical home is significantly lower 

for converted HUDIs and households 

completing in five calls or more, 

but is not significantly different 

for converted refusals. These 

results hold for both the dual-frame 

estimates and the landline and cellphone samples individually.

● The percentage of children whose 

families ate a meal together 

every day in the past week is not 

significantly different for converted 

refusals or converted HUDIs, but it 

is significantly lower for households 

completing in five calls or more in 

the landline and dual-frame samples 

(although not in the cell-phone 

sample).

● The percentage of children who 

are usually or always safe in the 

community or neighborhood is 

significantly lower for converted 

HUDIs, not significantly different 

for converted refusals, significantly 

lower for households completing 

in five calls or more in the landline 

sample, and not significantly 

different for households completing 

in five calls or more in the cell-phone 

and dual-frame samples.

● The percentage of children with 

a two-parent family structure 

(biological or adoptive) is 

significantly lower for converted 

HUDIs in the cell-phone and dualframe samples (although not in the 

landline sample), significantly lower 

for converted refusals in the cellphone sample (although not in the 

landline or dual-frame samples), and 

significantly higher for households 

completing in five calls or more in 

the dual-frame sample (although 

not in the landline or cell-phone 

samples).

● The percentage of children with 

a two-parent family structure 

(stepfamily) is not significantly 

different for converted HUDIs or 

converted refusals but is significantly 

lower for households completing in 

five calls or more in the dual-frame 

sample (although not in the landline 

or cell-phone samples).

● The percentage of children with a 

single-mother family structure is 

significantly higher for converted 

HUDIs, significantly lower for 

converted refusals in the landline 

sample (although not in the cellphone or dual-frame samples), and 

significantly lower for households 

completing in five calls or more in 

the dual-frame sample when the 

final weights are used (although not 

when the design weights are used 

and not in the landline or cell-phone 

samples).

● The percentage of children 

with other family structures is 

significantly higher for converted 

HUDIs in the landline sample 

(although not in the cell-phone or 

dual-frame samples), significantly 

higher for converted refusals 

(although not in the dual-frame 

sample when the final weights are 

used), and not significantly different 

for households completing in five 

calls or more.

The conclusions that might be 

drawn from this level-of-effort analysis 

rely on the assumption that high-effort 

respondents resemble nonrespondents 

with respect to the survey variables. 

Table XLIV. Comparing low-call-attempt respondents with high-call-attempt respondents: Dual-frame sample

Key survey outcome

Using design weight Using final weight

Respondents 

with four calls

or fewer 

estimate

Respondents 

with five 

calls or more 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value for 

test of no 

difference

Respondents 

with four calls

or fewer 

estimate

Respondents 

with five calls

or more 

estimate

High-effort 

to low-effort 

respondents, 

percent 

difference1

p value for 

test of no 

difference

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 85.86 82.96 –3.38 0.000005 85.72 83.04 –3.13 0.000004

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 89.50 88.28 –1.37 0.067697 88.97 88.54 –0.48 0.414014

Percentage of children with one or more 

medical preventive care visits in past 

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.34 96.10 0.80 0.025285 95.49 96.14 0.68 0.035131

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 56.63 53.39 –5.73 0.000066 55.73 52.61 –5.59 0.000036

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 50.54 47.35 –6.30 0.000059 48.76 45.23 –7.24 0.000002

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 87.35 86.43 –1.05 0.190661 87.15 86.15 –1.15 0.076770

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 64.94 66.55 2.48 0.045331 63.91 66.67 4.33 0.000111

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 8.27 7.39 –10.59 0.047262 9.42 8.28 –12.11 0.009306

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 19.97 19.81 –0.80 0.830853 19.70 18.53 –5.93 0.048567

Percentage of children with other family 

structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.83 6.25 –8.42 0.109683 6.97 6.52 –6.57 0.248930

1

Calculated as (five or more calls respondent mean – four or fewer calls respondent mean) / (four or fewer calls respondent mean).
Page 226  Series 1, No. 59

The validity of this assumption is 

questionable, and some studies have 

found that it does not hold (26,27). As 

part of the nonresponse bias analysis 

of the 2005–2006 National Survey of 

Children with Special Health Care Needs 

and the 2007 NSCH, this assumption 

was tested using the frame information, 

which is available for both respondents 

and nonrespondents at each stage of 

the survey. In both tests, converted 

refusals were not found to resemble 

nonrespondents in terms of the frame 

information, and while converted 

HUDIs resembled nonrespondents better 

than converted refusals, respondents 

completing in five calls or more most 

resembled nonrespondents in terms of the 

frame information.

The tests of the assumptions, then, 

supported the idea that high-effort 

respondents resemble nonrespondents 

when effort is defined in terms of the 

number of call attempts. Under the 

assumption that respondents requiring 

five calls or more to complete resemble 

nonrespondents, the analysis of key 

survey variables by the number of calls 

needed to complete the survey suggests 

that the final survey estimates of the 

percentage of children with one or more 

medical preventive care visits in the past 

12 months and the percentage of children 

with a two-parent family structure 

(biological or adoptive) are too low (i.e., 

they are biased downward). It would also 

appear that the other key survey estimates 

are too high (i.e., they are biased 

upward).

To translate the differences between 

those completing in five calls or more 

and those completing in four calls or 

fewer into numerical estimates of bias 

for each key survey estimate, the fiveor-more-calls respondent mean of the 

key survey estimate was assigned to all 

nonrespondents. The results are presented 

in Table XLV. For example, when using 

the design weights, the percentage of 

children in excellent or very good health 

based on all respondents is 84.2%, and 

Table XLIV shows that this rate for 

respondents completing in five calls or 

more is 83.0%. The overall dual-frame 

response rate is 23.0% (and, therefore, 

the nonresponse rate is 77.0%). Assigning 

a weight of 0.23 to the 84.2% estimate for 

respondents, and assuming an estimate 

of 83.0% for the nonrespondents and 

assigning them a weight of 0.77, derives 

an overall estimate for the percentage of 

children in excellent or very good health 

for both respondents and nonrespondents 

of 83.2%.

This method results in estimates 

of bias in the key survey estimates that 

range in absolute value from 0.16% to 

4.38%. Since the estimates of the biases 

are similar when the design weights and 

final weights are used, the weighting 

adjustments seem to have had little effect 

on the bias.

Conclusions

Assessing the extent to which 

nonresponse produces biased survey 

estimates is difficult, particularly in a 

multistage RDD survey where little 

information about the nonrespondents 

is known. This analysis has applied the 

most commonly used methods, each of 

which has its shortcomings. By taking 

multiple approaches, it was hoped that 

reasonably accurate conclusions about the 

level of nonresponse bias in key survey 

estimates could be drawn.

Generally, the interviewed landline 

sample population was found more likely 

to live in rural and other areas with lower 

household density compared with the 

nonresponding population. The same 

sample population was also more likely 

to live in areas associated with higher 

Table XLV. Estimates of nonresponse biases in key survey estimates, based on comparing respondents with five or more calls with all 

respondents: Dual-frame sample

Key survey outcome

Using design weight Using final weight

All

respondents 

estimate

Respondents 

with five

calls or more 

estimate

Respondents 

and 

nonrespondents 

estimate1

Estimated 

percent

bias2

All

respondents 

estimate

Respondents 

with five calls 

or more 

estimate

Respondents 

and 

nonrespondents 

estimate1

Estimated 

percent

bias2

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.20 82.96 83.24 1.15 84.16 83.04 83.29 1.04

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 88.80 88.28 88.40 0.46 88.72 88.54 88.58 0.16

Percentage of children with one or more 

medical preventive care visits in past

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.78 96.10 96.03 –0.26 95.86 96.14 96.07 –0.22

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 54.78 53.39 53.71 1.99 53.92 52.61 52.91 1.90

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 48.72 47.35 47.67 2.20 46.71 45.23 45.57 2.50

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 86.83 86.43 86.52 0.35 86.57 86.15 86.25 0.38

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 65.86 66.55 66.39 –0.80 65.51 66.67 66.41 –1.34

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 7.77 7.39 7.48 3.85 8.76 8.28 8.39 4.38

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 19.87 19.81 19.82 0.26 19.02 18.53 18.65 2.02

Percentage of children with other family 

structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.50 6.25 6.31 3.00 6.71 6.52 6.56 2.25

1

Calculated as (all respondents estimate • response rate) + (respondents with five or more calls estimate • nonresponse rate). 

2

Calculated as (all respondents estimate – respondents and nonrespondents estimate) / respondents and nonrespondents estimate.
Series 1, No. 59  Page 227 

levels of homeownership, lower home 

values, and greater percentage of 

non-Hispanic white persons. Even 

when the nonresponse-adjusted 

weights are used, minor differences by 

homeownership, home values, and race 

remained. 

In terms of the NSCH key survey 

estimates, estimates of bias were 

generally small but depended on the 

method used to estimate the bias. 

Table XLVI presents estimates of bias for 

each key survey estimate; conclusions 

regarding the presence of nonresponse 

bias in each are summarized below, along 

with some limitations.

Percentage of children in 

excellent or very good health

The estimate of the percentage of 

children in excellent or very good health 

may be biased upward slightly.

The final NSCH estimate and 95% 

confidence limits are 84.2% (82.8%, 

85.5%), and the estimates of bias in 

this estimate are 0.12% (from the frame 

analysis based on only the landline 

sample), 1.04% (from the level-ofeffort analysis), and –0.27% (from the 

benchmark analysis). For this variable, 

direct estimates are available from the 

2011 NHIS (82.7%) and the 2011 MEPS 

(83.8%); this suggests that the bias in 

the NSCH estimate is 1.72% or 0.42%, 

depending on whether the 2011 NHIS 

or 2011 MEPS estimate is used as the 

benchmark. (Note that here, as elsewhere 

in this report, biases are presented in 

percentage terms, not absolute terms, 

so that a 1.04% bias in an estimate of 

84.16% means that the estimate is 1.04% 

higher than the benchmark; i.e., the true 

value is 84.16% / 1.0104 = 83.29%.)

Percentage of children with 

consistent insurance coverage in 

past 12 months

Little bias was detected in the 

estimate of the percentage of children 

with consistent insurance coverage in the 

past 12 months.

The final NSCH estimate is 88.7% 

(87.1%, 90.3%), and the estimates of 

bias in this estimate are 0.03% (from the 

frame analysis based only on the landline 

sample), 0.16% (from the level-ofeffort analysis), and –0.23% (from the 

benchmark analysis).

Percentage of children with one 

or more medical preventive care 

visits in past 12 months

The analysis found no evidence of 

bias in the percentage of children with 

one or more medical preventive care visit 

in the past 12 months.

The final NSCH estimate is 95.9% 

(95.4%, 96.3%). The estimate of the bias 

in this estimate is –0.04% from the frame 

analysis, –0.22% from the level-of-effort 

analysis, and 0.09% from the benchmark 

analysis.

Percentage of children with a 

medical home

The estimate of the percentage of 

children with a medical home may be 

biased upward slightly.

The final NSCH estimate is 53.9% 

(51.8%, 56.1%), and the bias was 

estimated to be 0.27% (frame analysis), 

1.90% (level-of-effort analysis), and 

1.37% (benchmark analysis).

Percentage of children whose 

families ate a meal together 

every day in the past week

The estimate of the percentage 

of children whose families ate a meal 

together every day in the past week may 

be biased upward slightly.

The final NSCH estimate is 46.7% 

(45.5%, 47.9%). The bias in this 

estimate was estimated to be 0.12% 

(frame analysis), 2.50% (level-ofeffort analysis), and 0.52% (benchmark 

analysis).

Percentage of children usually 

or always safe in the community 

or neighborhood

Little bias was found in the estimate 

of the percentage of children usually 

or always safe in the community or 

neighborhood.

The final NSCH estimate is 86.6% 

(85.3%, 87.9%). The bias in this 

estimate was estimated to be 0.13% 

(frame analysis), 0.38% (level-ofeffort analysis), and 0.09% (benchmark 

analysis).

Table XLVI. Estimates of survey bias in key survey variables, by method used to estimate 

bias

Key survey variable

Key survey 

estimate1

 (95% 

confidence interval)

Estimates of bias in key survey estimate, 

by method used2

Frame 

information 

analysis3

Levelof-effort 

analysis

Benchmark 

analysis

Percentage of children in excellent or very 

good health. . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.16 (82.79, 85.53) 0.12 1.04 –0.27

Percentage of children with consistent 

insurance coverage in past 12 months . . . . . . . 88.72 (87.11, 90.33) 0.03 0.16 –0.23

Percentage of children with one or more 

medical preventive care visits in past 

12 months. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.86 (95.38, 96.34) –0.04 –0.22 0.09

Percentage of children with 

medical home . . . . . . . . . . . . . . . . . . . . . . . . . . 53.92 (51.75, 56.09) 0.27 1.90 1.37

Percentage of children whose families ate 

a meal together every day in past week . . . . . . 46.71 (45.52, 47.90) 0.12 2.50 0.52

Percentage of children usually or always safe 

in community or neighborhood . . . . . . . . . . . . . 86.57 (85.28, 87.86) 0.13 0.38 0.09

Percentage of children with two-parent family 

structure (biological or adoptive) . . . . . . . . . . . 65.51 (63.50, 67.53) 0.17 –1.34 –0.29

Percentage of children with two-parent family 

structure (stepfamily) . . . . . . . . . . . . . . . . . . . . 8.76 (8.01, 9.50) 0.36 4.38 –0.13

Percentage of children with single-mother 

family structure . . . . . . . . . . . . . . . . . . . . . . . . . 19.02 (17.66, 20.38) –0.74 2.02 0.82

Percentage of children with 

other family structure . . . . . . . . . . . . . . . . . . . . 6.71 (6.20, 7.22) –0.67 2.25 0.67

1

Using final weights adjusted for nonresponse and raked to population control totals.

2

Using nonresponse-adjusted or raked weights, depending on the analysis. Biases are presented in percentage terms, not absolute 

terms; for example, a 0.12% bias in an estimate of 84.16 means that the reported estimate is 0.12% higher than the true value, that 

is, the true value is 84.16 / 1.0012 = 84.06.

3

Bias estimates apply only to the landline sample, due to frame information availability.
Page 228  Series 1, No. 59

Family structure

The results for family structure 

distribution are mixed, with the frame 

analysis and benchmark analysis methods 

showing little to no bias, and the level-ofeffort analysis showing small biases.

The final NSCH estimate of the 

percentage of children with a two-parent 

family structure (biological or adoptive) 

is 65.5% (63.5%, 67.5%). The bias in 

this estimate was estimated to be 0.17% 

(frame analysis), –1.34% (level-of-effort 

analysis), and –0.29% (benchmark 

analysis).

The final NSCH estimate of the 

percentage of children with a two-parent 

family structure (stepfamily) is 8.8% 

(8.0%, 9.5%), and the bias was estimated 

to be 0.36% (frame analysis), 4.38% 

(level-of-effort analysis), and –0.13% 

(benchmark analysis).

The final NSCH estimate of the 

percentage of children with a singlemother family structure is 19.0% (17.7%, 

20.4%), and the bias was estimated 

to be –0.74% (frame analysis), 2.02% 

(level-of-effort analysis), and 0.82% 

(benchmark analysis).

The final NSCH estimate of the 

percentage of children with other family 

structures is 6.7% (6.2%, 7.2%), and 

the bias was estimated to be –0.67% 

(frame analysis), 2.25% (level-ofeffort analysis), and 0.67% (benchmark 

analysis).

Limitations

Any nonresponse bias analysis is 

limited by the information available 

about the nonrespondents, and this report 

is no exception. In transforming the 

measured bias in the frame information 

into bias in the key survey estimates, 

models were used to relate the frame 

information to the key survey estimates. 

However, the frame variables (which 

are nearly all measured at the telephoneexchange level and not the case level, 

and which are not available for the 

cell-phone sample) are not strongly 

related to the key survey estimates, so the 

models may not have had much power to 

detect bias in the key survey estimates. 

The level-of-effort analysis relied on 

the assumption that those responding 

only after five call attempts or more 

resemble nonrespondents with respect 

to the key survey variables; although 

past analysis has found this to be true 

with respect to the frame variables for 

landline samples, it is not necessarily 

true for the key survey variables and 

may not be true for cell-phone samples. 

Finally, the comparison of demographic, 

socioeconomic, and health estimates to 

those from external sources (benchmarks) 

relied on the assumption that the 

estimates from these external sources are 

accurate, which may not be the case—the 

benchmark estimates are based on survey 

data and can suffer from their own biases. 

Moreover, models were used to translate 

the differences between the NSCH and 

benchmark estimates into estimates of 

bias in the NSCH key survey estimates, 

and these models may not be accurate or 

complete. To the extent that the models 

and assumptions used in this report’s 

analyses are not valid, conclusions may 

not be correct.
Series 1, No. 59  Page 229 

Appendix XIV. Multiple Imputation of Income and Household Size 

As in many household interview 

surveys, item nonresponse in the 

2011–2012 National Survey of Children’s 

Health (NSCH) was high for the question 

on total combined household income 

for the previous calendar year. Answers 

to this question, along with answers to 

a question about the number of people 

living in the household, were used to 

create an index of income following the 

U.S. Department of Health and Human 

Services federal poverty guidelines. If 

data for either of these two components 

were missing, refused, or had a “don’t 

know” response, the household poverty 

status indicator was assigned a missingvalue code. (Further details about the 

procedures for assigning household 

poverty status are available in 

Appendix V). 

For the 2011–2012 NSCH, 

poverty status was missing for 9.3% 

of the households (8,856 of 95,677). 

Missing values for poverty status were 

predominantly the result of missing data 

for income rather than missing data for 

household size. A total of 409 households 

(0.4%) did not report household size.

Nonresponse analysis shows that 

income nonresponse is related to several 

variables including items pertaining to 

health, neighborhood and community 

characteristics, and demographics. Thus, 

the respondents cannot be treated as a 

random subset of the original sample. It 

follows that the most common method 

for handling missing data in software 

packages, complete-case analysis 

(also known as listwise deletion), will 

generally be biased, because this method 

deletes cases that are missing any of 

the variables involved in the analysis. 

Moreover, since deletion of incomplete 

cases discards some of the observed 

data, complete-case analysis is generally 

inefficient as well; that is, it produces 

inferences that are less precise than those 

produced by methods that use all of the 

observed data.

Imputation is a more appropriate 

approach to handling nonresponse on 

items in a survey for several reasons. 

First, imputation adjusts for observed 

differences between item nonrespondents 

and respondents; such an adjustment is 

generally not made by complete-case 

analysis. Second, imputation results 

in a completed data set, so that the 

data can be analyzed using standard 

software packages without discarding 

any observed values. Third, when a data 

set is being produced for analysis by the 

public, imputation by the data producer 

allows the incorporation of specialized 

knowledge about the reasons for missing 

data in the imputation procedure, 

including confidential information 

that cannot be released to the public. 

Moreover, the nonresponse problem is 

addressed in the same way for all users, 

so that analyses will be consistent across 

users. 

Although single imputation (i.e., 

imputing one value for each missing 

datum) derives the benefits listed above, 

analysis of a singly imputed data set 

using standard software generally fails 

to reflect the uncertainty that although 

the imputed values are plausible 

replacements for the missing values, they 

are not the true values themselves. As a 

result, analyses of singly imputed data 

tend to produce estimated standard errors 

that are too small, confidence intervals 

that are too narrow, and significance tests 

that reject the null hypothesis too often 

when it is true.

Multiple imputation is a technique 

that retains the advantages of single 

imputation while also allowing the 

uncertainty due to imputation to be 

reflected in the analysis. The idea 

is to first simulate M > 1 plausible 

sets of replacements for the missing 

values, which are then combined with 

the nonmissing values to generate M 

complete data sets. The M complete data 

sets are then analyzed separately using a 

standard method for analyzing complete 

data. Finally, results of the M analyses 

are combined in a way that reflects the 

uncertainty due to imputation. 

Imputation Procedures

Income and household size were 

each imputed five times. The literature 

on multiple imputation suggests that this 

is a sufficient number of imputations 

unless the amount of missing information 

is extreme (28). As noted earlier, the 

number of survey records with missing 

household size values was much smaller 

than the number of survey records with 

missing household income values. 

Because very little data were missing for 

household size, predictors for household 

size were not explored separately 

from predictors for household income. 

Therefore, household size was imputed 

using the same predictors used for 

household income. If both household size 

and household income were missing for a 

single case, five pairs of imputed values 

were produced.

The imputation of household income 

and household size was complicated 

by two issues. First, neither household 

income nor size was normally distributed. 

This is a disadvantage because linear 

regression modeling assumes that the 

dependent variable being modeled has 

a normal distribution. Therefore, a 

transformed variable for modeling and 

imputation was used. To determine the 

suitable transformation to conform to the 

normality assumption in the imputation 

model, Box-Cox transformations (29) 

were estimated from the observed 

data. For household size, the log 

transformation led to normality. For 

income, the optimal transformation was 

to the 0.15 power, which was rounded to 

the power of 0.20 (the fifth root). After 

the imputation procedure was completed, 

the imputed values were transformed 

back to their original scale.

Second, in some cases, the imputed 

values of household income and 

household size needed to be constrained 

within certain bounds. Household 

respondents were asked to provide an 

exact household income. However, 

when respondents did not provide an 

exact household income, a series (i.e., 

cascade) of questions asking whether the 

household income was below, exactly 

at, or above threshold amounts was 

then asked. The multiple imputation 

procedures for NSCH imputed the 

income value so that it was consistent 

with any information gathered from 
Page 230  Series 1, No. 59

the cascade questions. For households 

with missing data on household size, the 

imputed values needed to be restricted 

for consistency with other information 

provided in the survey (for example, 

household size is greater than the number 

of children in the household). 

The software IVEware, available 

from: http://www.isr.umich.edu/src/

smp/ive, allows the user to specify lower 

and upper limits of imputed values, 

constraining the imputation distribution 

from which draws are made. This 

software has been used to impute family 

income and family earnings for the 

National Health Interview Survey and to 

impute household income and household 

size (to derive household poverty status) 

for the 2001, 2005–2006, and 2009–2010 

National Surveys of Children with 

Special Health Care Needs as well as 

the 2003 and 2007 NSCH. IVEware 

uses sequential regression multivariate 

imputation (SRMI). With sequential 

regression imputations, income and 

household size had separate models that 

used the same covariates, including each 

other. This technique was not as robust 

as some other imputation techniques 

that specify a joint model for both 

income and household size conditional 

on the predictor variables. However, 

this slight disadvantage of using SRMI 

is outweighed by IVEware’s ability to 

constrain the imputed values within 

specified lower and upper limits.

IVEware builds regression models 

and then multiply imputes variables 

based on the models built. For 

understanding relationships between 

variables, parsimony is desired, but in 

prediction (imputation can be thought of 

as “predicting” the missing values), more 

complicated models are often better for 

two reasons. First, using more variables 

leads to a higher correlation between 

the observed and predicted values for a 

model. Second, the validity of analyses 

conducted on multiply imputed data 

sets is broader when more variables are 

included in the model.

As many predictors as possible 

were included in this imputation model. 

To produce high-quality imputations, 

variables that were potentially related 

to household income and potentially 

related to the missing status of household 

income were included. Another important 

consideration was to include variables 

that account for features of the sampling 

design, so that approximately valid 

inferences would be obtained when the 

multiply imputed data are analyzed.

The imputation model included 

variables related to the questionnaire 

items on demographics (for the child and 

household), health and functional status 

of the child, health insurance coverage, 

health care access and utilization, medical 

home, and characteristics of the telephone 

exchange. For most of the variables, the 

“refused” or “don't know” answers were 

recoded to missing. For some variables 

having logical skips, logical imputation 

was used to obtain more complete 

variables. For example, the variable 

K11Q60 (receipt of cash assistance) is 

missing when the household's income 

does not qualify for the cash assistance. 

Therefore, it was recoded as a “no” 

response for such households. Some 

categorical variables also were recoded or 

collapsed to reduce the number of rarer 

categories. For example, for the variable 

K4Q20 (number of doctor visits), the 

values ranged from 0 to 365, with small 

frequencies for values greater than 10. 

The number of categories was reduced to 

11, with category 10 defined as 10 visits 

or more. 

Because fitting the regressions in the 

SRMI procedure does not automatically 

account for features of the sample design, 

variables reflecting the design were 

included as predictors in the regression 

models. The strata for this design were 

the 50 states and Washington, D.C. To 

account for the stratum effect, states, in 

the form of 50 indicator variables, and 

state-level income summary variables 

(mean and standard deviation with log 

transformation) were considered as 

possible covariates in the imputation 

model. Survey weights were also 

considered as covariates in the model, 

after transforming the weights to a 

logarithmic scale. Ultimately, the statelevel income summary variables were 

dropped before the final imputations 

were carried out, while the state indicator 

variables and the weight variable were 

retained in the final model.

Results of Modeling

Tables XLVII and XLVIII present 

the results from a linear regression of 

transformed family income (tincome) on 

the 118 selected predictors. Table XLVII

shows that the model is highly significant 

F(282,73,451) = 210.53, p < 0.0001. 

The R-squared value for this model 

was 0.447, and the adjusted R-squared 

was 0.445. Table XLVIII shows the 

linear regression parameters for the 118 

independent variables. The variables 

are ordered by their contribution to the 

R-squared value of the model; variables 

with larger partial R-squared values 

are listed first. Those with negative 

parameters are associated with decreased 

predicted income, whereas those with 

positive parameters are associated with 

increased predicted income. 

Due to missing values for the 

variables (especially tincome), only 

74,734 observations were used in the 

regression model (no U.S. Virgin Islands 

cases had any complete cases on all 

variables, so none of these cases appear 

in Table XLVIII).

Note that the imputed values for 

family income were not obtained from 

this regression model. The imputed 

values were drawn from the posterior 

distribution of missing family income 

based on the model derived from this 

regression. 

Table XLVII. Analysis of variance table for linear regression model

Source

Degrees of 

freedom

Sum of 

squares

Mean 

square F value

Model. . . . . . . . . . . . . . . . . . . . . 282 112,044 397.32 210.53

Error. . . . . . . . . . . . . . . . . . . . . . 73,451 138,619 1.89 ...

Corrected total . . . . . . . . . . . . . . 73,733 250,663 ... ...

. . . Category not applicable.
Series 1, No. 59  Page 231 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest

Parameter 

or level Label

Degrees 

of freedom Estimate

Standard 

error t value p value

Intercept. . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 1 6.8962 0.2976 23.1694 1

0.0000

EDUC4 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Highest level of education attained 

by mother, father, nonparent respondent in 

household (4 categories)

1 –1.1602 0.0301 –38.5145 1

0.0000

EDUC4 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Highest level of education attained 

by mother, father, nonparent respondent in 

household (4 categories)

1 –0.8518 0.0176 –48.4678 1

0.0000

EDUC4 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Highest level of education attained 

by mother, father, nonparent respondent in 

household (4 categories)

1 –0.5614 0.0136 –41.2782 1

0.0000

EDUC4 4 (reference) . . . . . . . . . . . . . . . . . . Derived. Highest level of education attained 

by mother, father, nonparent respondent in 

household (4 categories)

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

ACE1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Since [s.c.] was born, how often has it 

been very hard to get by on your family’s 

income, for example, it was hard to cover 

the basics like food or housing?

1 –0.9187 0.0261 –35.1660 1

0.0000

ACE1 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Since [s.c.] was born, how often has it 

been very hard to get by on your family’s 

income, for example, it was hard to cover 

the basics like food or housing?

1 –0.7136 0.0169 –42.3366 1

0.0000

ACE1 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Since [s.c.] was born, how often has it 

been very hard to get by on your family’s 

income, for example, it was hard to cover 

the basics like food or housing?

1 –0.4486 0.0125 –35.9933 1

0.0000

ACE1 4 (reference). . . . . . . . . . . . . . . . . . . . Since [s.c.] was born, how often has it 

been very hard to get by on your family’s 

income, for example, it was hard to cover 

the basics like food or housing?

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

C10Q41 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . Do you own or rent your home? 1 0.8822 0.0414 21.3073 1

0.0000

C10Q41 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . Do you own or rent your home? 1 0.2219 0.0424 5.2293 1

0.0000

C10Q41 3 (reference). . . . . . . . . . . . . . . . . . Do you own or rent your home? ... ... ... ... ...

K11Q50 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . Was anyone in the household employed at 

least 50 weeks out of the past 52 weeks?

1 –0.7935 0.0178 –44.5447 1

0.0000

K11Q50 1 (reference) . . . . . . . . . . . . . . . . . . Was anyone in the household employed at 

least 50 weeks out of the past 52 weeks?

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

Inc_75_p_q 1. . . . . . . . . . . . . . . . . . . . . . . . Percentage of income $75,000 or more by 

exchange (quartiles)

1 –0.0227 0.0587 –0.3864 0.6992

Inc_75_p_q 2. . . . . . . . . . . . . . . . . . . . . . . . Percentage of income $75,000 or more by 

exchange (quartiles)

1 0.0438 0.0510 0.8580 0.3909

Inc_75_p_q 3. . . . . . . . . . . . . . . . . . . . . . . . Percentage of income $75,000 or more by 

exchange (quartiles)

1 0.0407 0.0416 0.9780 0.3281

Inc_75_p_q 4 (reference) . . . . . . . . . . . . . . . Percentage of income $75,000 or more by 

exchange (quartiles)

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

C11Q15_CELL. . . . . . . . . . . . . . . . . . . . . . . In total, how many working cell phones do 

you and your household members have 

available for personal use?

1 0.2502 0.0098 25.4331 1

0.0000

TELEPHONE_STATUS 1 . . . . . . . . . . . . . . . Derived. Telephone status for household 1 –0.2658 0.0413 –6.4320 1

0.0000

TELEPHONE_STATUS 2 . . . . . . . . . . . . . . . Derived. Telephone status for household 1 0.0453 0.0393 1.1526 0.2491

TELEPHONE_STATUS 3 . . . . . . . . . . . . . . . Derived. Telephone status for household 1 –0.0348 0.0370 –0.9392 0.3476

TELEPHONE_STATUS 4 . . . . . . . . . . . . . . . Derived. Telephone status for household 1 –0.2337 0.0375 –6.2273 1

0.0000

TELEPHONE_STATUS 5 (reference) . . . . . . Derived. Telephone status for household ... ... ... ... ...

RACEARRAY_11CAT 1 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child 

(11 categories)

1 0.0758 0.0792 0.9569 0.3386

RACEARRAY_11CAT 2 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child 

(11 categories)

1 –0.3538 0.0813 –4.3509 1

0.0000

RACEARRAY_11CAT 3 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child 

(11 categories)

1 0.1201 0.0853 1.4083 0.1590

RACEARRAY_11CAT 4 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.1963 0.0884 –2.2210 0.0264

RACEARRAY_11CAT 5 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.0447 0.1006 –0.4443 0.6568

RACEARRAY_11CAT 6 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.1792 0.0871 –2.0562 0.0398

RACEARRAY_11CAT 7 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 0.2039 0.0897 2.2725 0.0231

RACEARRAY_11CAT 8 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.0789 0.0878 –0.8979 0.3693

RACEARRAY_11CAT 9 . . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.1886 0.1006 –1.8749 0.0608

RACEARRAY_11CAT 10. . . . . . . . . . . . . . . . Race and ethnicity of the selected child

(11 categories)

1 –0.0669 0.1107 –0.6045 0.5455

See footnotes at end of table.
Page 232  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

RACEARRAY_11CAT 11 (reference). . . . . . . Race and ethnicity of the selected child 

(11 categories)

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

TRUEST AK . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1161 0.0572 2.0304 0.0423

TRUEST AL . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0240 0.0579 –0.4151 0.6781

TRUEST AR . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0120 0.0559 0.2142 0.8304

TRUEST AZ . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0206 0.0575 –0.3573 0.7209

TRUEST CA . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1459 0.0658 2.2154 0.0267

TRUEST CO. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0246 0.0554 –0.4442 0.6569

TRUEST CT. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1235 0.0581 2.1265 0.0335

TRUEST DC . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.4474 0.0612 7.3136 1

0.0000

TRUEST DE . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0003 0.0582 0.0044 0.9965

TRUEST FL . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0528 0.0591 0.8930 0.3719

TRUEST GA . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0240 0.0586 0.4091 0.6825

TRUEST HI. . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0913 0.0648 –1.4085 0.1590

TRUEST IA. . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0635 0.0545 –1.1653 0.2439

TRUEST ID. . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1567 0.0538 –2.9150 0.0036

TRUEST IL . . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0212 0.0552 0.3840 0.7010

TRUEST IN. . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0361 0.0569 –0.6331 0.5267

TRUEST KS. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0477 0.0547 –0.8715 0.3835

TRUEST KY. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1121 0.0565 –1.9825 0.0474

TRUEST LA . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0192 0.0581 0.3301 0.7413

TRUEST MA. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1797 0.0587 3.0630 0.0022

TRUEST MD. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.3085 0.0580 5.3158 1

0.0000

TRUEST ME. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1086 0.0579 –1.8753 0.0608

TRUEST MI . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0695 0.0579 –1.2007 0.2299

TRUEST MN. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0266 0.0553 0.4805 0.6309

TRUEST MO. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0515 0.0559 –0.9211 0.3570

TRUEST MS. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0585 0.0591 –0.9890 0.3227

TRUEST MT . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0971 0.0535 –1.8141 0.0697

TRUEST NC . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0351 0.0571 –0.6144 0.5390

TRUEST ND . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1497 0.0559 2.6763 0.0074

TRUEST NE . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0037 0.0546 –0.0678 0.9460

TRUEST NH . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0407 0.0578 –0.7053 0.4807

TRUEST NJ . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1151 0.0601 1.9145 0.0556

TRUEST NM. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0398 0.0589 –0.6759 0.4991

TRUEST NV . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0324 0.0590 –0.5494 0.5827

TRUEST NY . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1648 0.0595 2.7684 0.0056

TRUEST OH. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0850 0.0570 –1.4921 0.1357

TRUEST OK . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0469 0.0564 –0.8310 0.4060

TRUEST OR. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1211 0.0559 –2.1674 0.0302

TRUEST PA . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0634 0.0581 1.0909 0.2753

TRUEST RI. . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0574 0.0588 –0.9764 0.3289

TRUEST SC . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1178 0.0577 –2.0399 0.0414

TRUEST SD . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0598 0.0552 –1.0837 0.2785

TRUEST TN . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0408 0.0569 –0.7160 0.4740

TRUEST TX . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0776 0.0588 1.3199 0.1869

TRUEST UT. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.1693 0.0561 –3.0186 0.0025

TRUEST VA . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.1420 0.0573 2.4786 0.0132

TRUEST VT . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0405 0.0578 –0.7006 0.4835

TRUEST WA. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 0.0570 0.0564 1.0093 0.3128

TRUEST WI . . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0085 0.0555 –0.1528 0.8786

TRUEST WV. . . . . . . . . . . . . . . . . . . . . . . . . True state of residence 1 –0.0389 0.0585 –0.6658 0.5056

TRUEST WY (reference) . . . . . . . . . . . . . . . True state of residence ... ... ... ... ...

RELATION 1. . . . . . . . . . . . . . . . . . . . . . . . . Derived. Respondent’s relationship to 

selected child

1 –0.0052 0.0434 –0.1201 0.9044

RELATION 2. . . . . . . . . . . . . . . . . . . . . . . . . Derived. Respondent’s relationship to 

selected child

1 0.2231 0.0443 5.0347 1

0.0000

RELATION 3. . . . . . . . . . . . . . . . . . . . . . . . . Derived. Respondent’s relationship to 

selected child

1 0.0885 0.0491 1.8024 0.0715

RELATION 5 (reference). . . . . . . . . . . . . . . . Derived. Respondent’s relationship to 

selected child

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

language_hh 1. . . . . . . . . . . . . . . . . . . . . . . Primary language of the household 1 0.2463 0.0434 5.6773 1

0.0000

language_hh 2. . . . . . . . . . . . . . . . . . . . . . . Primary language of the household 1 –0.1296 0.0569 –2.2781 0.0227

language_hh 3 (reference) . . . . . . . . . . . . . . Primary language of the household ... ... ... ... ...

K8Q11 0. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1356 0.0301 4.5097 1

0.0000

See footnotes at end of table.
Series 1, No. 59  Page 233 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K8Q11 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1261 0.0311 4.0567 10.0000

K8Q11 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1390 0.0225 6.1704 10.0000

K8Q11 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1328 0.0192 6.9069 10.0000

K8Q11 4. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1437 0.0173 8.2892 10.0000

K8Q11 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1005 0.0151 6.6624 10.0000

K8Q11 6. . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

1 0.1167 0.0203 5.7490 10.0000

K8Q11 7 (reference) . . . . . . . . . . . . . . . . . . . During the past week, on how many days 

did all the family members who live in the 

household eat a meal together?

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

College_Graduate_q 1 . . . . . . . . . . . . . . . . . Number of college graduates by exchange 

(quartiles)

1 –0.0782 0.0400 –1.9558 0.0505

College_Graduate_q 2 . . . . . . . . . . . . . . . . . Number of college graduates by exchange 

(quartiles)

1 –0.0369 0.0327 –1.1283 0.2592

College_Graduate_q 3 . . . . . . . . . . . . . . . . . Number of college graduates by exchange 

(quartiles)

1 –0.0379 0.0245 –1.5489 0.1214

College_Graduate_q 4 (reference) . . . . . . . . Number of college graduates by exchange 

(quartiles)

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

K10Q30 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . People in this neighborhood help each 

other out.

1 0.1499 0.0382 3.9245 0.0001

K10Q30 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . People in this neighborhood help each 

other out.

1 0.1115 0.0367 3.0373 0.0024

K10Q30 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . People in this neighborhood help each 

other out.

1 0.0777 0.0391 1.9883 0.0468

K10Q30 4 (reference) . . . . . . . . . . . . . . . . . . People in this neighborhood help each 

other out.

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

K4Q30 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] see a dentist for any kind 

of dental care, including check-ups, dental 

cleanings, x-rays, or filling cavities?

1 –0.1054 0.0323 –3.2598 0.0011

K4Q30 1 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] see a dentist for any kind 

of dental care, including check-ups, dental 

cleanings, x-rays, or filling cavities?

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

ACE3 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who got divorced or separated after [s.c.] 

was born?

1 0.1163 0.0156 7.4512 10.0000

ACE3 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who got divorced or separated after [s.c.] 

was born?

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

K4Q02 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . What kind of place is it? / what kind of place 

does [s.c.] go to most often?

1 0.0525 0.0485 1.0818 0.2793

K4Q02 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . What kind of place is it? / what kind of place 

does [s.c.] go to most often?

1 –0.1046 0.0680 –1.5393 0.1237

K4Q02 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . What kind of place is it? / what kind of place 

does [s.c.] go to most often?

1 –0.0273 0.0598 –0.4565 0.6481

K4Q02 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . What kind of place is it? / what kind of place 

does [s.c.] go to most often?

1 –0.0550 0.0499 –1.1013 0.2708

K4Q02 9 (reference). . . . . . . . . . . . . . . . . . . What kind of place is it? / what kind of place 

does [s.c.] go to most often?

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

K10Q20 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . In your neighborhood, is there litter or 

garbage on the street or sidewalk?

1 0.1266 0.0160 7.9241 10.0000

K10Q20 1 (reference) . . . . . . . . . . . . . . . . . . In your neighborhood, is there litter or 

garbage on the street or sidewalk?

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

lhhsize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of people in a household (after log 

transformation)

1 0.8924 0.0799 11.1655 10.0000

K2Q01 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . In general, how would you describe [s.c.]’s 

health?

1 0.1177 0.0390 3.0210 0.0025

K2Q01 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . In general, how would you describe [s.c.]’s 

health?

1 0.0260 0.0387 0.6705 0.5025

K2Q01 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . In general, how would you describe [s.c.]’s 

health?

1 –0.0102 0.0401 –0.2554 0.7984

See footnotes at end of table.
Page 234  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K2Q01 4 (reference) . . . . . . . . . . . . . . . . . . . In general, how would you describe [s.c.]’s 

health?

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

K4Q24 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] see a specialist [other than 

a mental health professional]?

1 –0.1032 0.0295 –3.4940 0.0005

K4Q24 1 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] see a specialist [other than 

a mental health professional]?

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

K9Q40 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Does anyone living in your household use 

cigarettes, cigars, or pipe tobacco?

1 0.0985 0.0133 7.3895 10.0000

K9Q40 1 (reference). . . . . . . . . . . . . . . . . . . Does anyone living in your household use 

cigarettes, cigars, or pipe tobacco?

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

K8Q34 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt angry with [him/her]?

1 –0.0913 0.0454 –2.0127 0.0441

K8Q34 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt angry with [him/her]?

1 –0.0108 0.0443 –0.2436 0.8076

K8Q34 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt angry with [him/her]?

1 –0.0140 0.0434 –0.3227 0.7469

K8Q34 4 (reference) . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt angry with [him/her]?

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

K4Q04 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Do you have one or more persons you think 

of as [s.c.]’s personal doctor or nurse?

1 0.1243 0.0220 5.6630 10.0000

K4Q04 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Do you have one or more persons you think 

of as [s.c.]’s personal doctor or nurse?

1 0.1521 0.0230 6.6065 10.0000

K4Q04 3 (reference). . . . . . . . . . . . . . . . . . . Do you have one or more persons you think 

of as [s.c.]’s personal doctor or nurse?

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

Inc_50_75p_q 1. . . . . . . . . . . . . . . . . . . . . . Percentage of income $50,000–$75,000 by 

exchange (quartiles)

1 0.1662 0.0235 7.0832 10.0000

Inc_50_75p_q 2. . . . . . . . . . . . . . . . . . . . . . Percentage of income $50,000–$75,000 by 

exchange (quartiles)

1 0.0707 0.0194 3.6468 0.0003

Inc_50_75p_q 3. . . . . . . . . . . . . . . . . . . . . . Percentage of income $50,000–$75,000 by 

exchange (quartiles)

1 0.0407 0.0159 2.5653 0.0103

Inc_50_75p_q 4 (reference) . . . . . . . . . . . . . Percentage of income $50,000–$75,000 by 

exchange (quartiles)

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

Age_35_54_p_q 1 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 35–54 by 

exchange (quartiles)

1 –0.0858 0.0237 –3.6164 0.0003

Age_35_54_p_q 2 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 35–54 by 

exchange (quartiles)

1 –0.0355 0.0199 –1.7799 0.0751

Age_35_54_p_q 3 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 35–54 by 

exchange (quartiles)

1 –0.0011 0.0168 –0.0638 0.9491

Age_35_54_p_q 4 (reference) . . . . . . . . . . . Percentage of people aged 35–54 by 

exchange (quartiles)

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

SAMPLE 1 . . . . . . . . . . . . . . . . . . . . . . . . . . Telephone sample type 1 0.1156 0.0183 6.3263 10.0000

SAMPLE 2 (reference). . . . . . . . . . . . . . . . . Telephone sample type ... ... ... ... ...

Median_Rent_q 1 . . . . . . . . . . . . . . . . . . . . . Median rent by exchange (quartiles) 1 –0.0977 0.0380 –2.5698 0.0102

Median_Rent_q 2 . . . . . . . . . . . . . . . . . . . . . Median rent by exchange (quartiles) 1 –0.0664 0.0282 –2.3570 0.0184

Median_Rent_q 3 . . . . . . . . . . . . . . . . . . . . . Median rent by exchange (quartiles) 1 –0.0456 0.0196 –2.3266 0.0200

Median_Rent_q 4 (reference) . . . . . . . . . . . . Median rent by exchange (quartiles) ... ... ... ... ...

K8Q35 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Is there someone that you can turn to for 

day-to-day emotional help with 

[parenthood / raising children]?

1 –0.0834 0.0213 –3.926 0.0001

K8Q35 1 (reference). . . . . . . . . . . . . . . . . . . Is there someone that you can turn to for 

day-to-day emotional help with 

[parenthood / raising children]?

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

ACE4 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who died?

1 0.1465 0.0316 4.6329 10.0000

ACE4 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who died?

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

K8Q30 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . In general, how well do you feel you are 

coping with the day to day demands of 

[parenthood / raising children]?

1 –0.1140 0.0479 –2.3774 0.0174

K8Q30 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . In general, how well do you feel you are 

coping with the day to day demands of 

[parenthood / raising children]?

1 –0.0484 0.0476 –1.0155 0.3099

K8Q30 3 (reference). . . . . . . . . . . . . . . . . . . In general, how well do you feel you are 

coping with the day to day demands of 

[parenthood / raising children]?

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

K11Q43. . . . . . . . . . . . . . . . . . . . . . . . . . . . . (Since [he/she] was adopted,) how many 

times has [s.c.] ever moved to a new 

address?

1 0.0155 0.0028 5.5439 10.0000

See footnotes at end of table.
Series 1, No. 59  Page 235 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

ACE5 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who served time in jail or prison after [s.c.] 

was born?

1 0.1426 0.0254 5.6081 10.0000

ACE5 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with a parent or guardian 

who served time in jail or prison after [s.c.] 

was born?

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

TOTKIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Total number of children in 

household aged 0–17 years

1 –0.1598 0.0189 –8.4413 10.0000

TOTADULT. . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Total number of adults in 

household

1 –0.1483 0.0197 –7.5084 10.0000

K5Q40 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers spend enough 

time with [him/her]?

1 –0.0507 0.0313 –1.6200 0.1052

K5Q40 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers spend enough 

time with [him/her]?

1 –0.0855 0.0198 –4.3193 10.0000

K5Q40 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers spend enough 

time with [him/her]?

1 –0.0321 0.0148 –2.1666 0.0303

K5Q40 4 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers spend enough 

time with [him/her]?

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

ACE10 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Was [s.c.] ever treated or judged unfairly 

because of [his/her] race or ethnic group?

1 –0.1583 0.0301 –5.2517 10.0000

ACE10 1 (reference). . . . . . . . . . . . . . . . . . . Was [s.c.] ever treated or judged unfairly 

because of [his/her] race or ethnic group?

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

Median_HH_Income_q 1. . . . . . . . . . . . . . . Median household income by exchange 

(quartiles)

1 –0.1540 0.0608 –2.5334 0.0113

Median_HH_Income_q 2. . . . . . . . . . . . . . . Median household income by exchange 

(quartiles)

1 –0.1146 0.0506 –2.2660 0.0235

Median_HH_Income_q 3. . . . . . . . . . . . . . . Median household income by exchange 

(quartiles)

1 -0.0773 0.0403 –1.9197 0.0549

Median_HH_Income_q 4 (reference) . . . . . . Median household income by exchange 

(quartiles)

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

Black_p_q 1 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of black by exchange (quartiles) 1 0.0015 0.0295 0.0523 0.9583

Black_p_q 2 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of black by exchange (quartiles) 1 –0.0504 0.0248 –2.0341 0.0419

Black_p_q 3 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of black by exchange (quartiles) 1 –0.0146 0.0205 –0.7098 0.4778

Black_p_q 4 (reference) . . . . . . . . . . . . . . . . Percentage of black by exchange (quartiles) ... ... ... ... ...

K2Q16 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Is [s.c.] limited or prevented in any way 

in [his/her] ability to do the things most 

children of the same age can do?

1 0.1216 0.0265 4.5934 10.0000

K2Q16 1 (reference) . . . . . . . . . . . . . . . . . . . Is [s.c.] limited or prevented in any way 

in [his/her] ability to do the things most 

children of the same age can do?

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

K10Q40 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . How often do you feel [s.c.] is safe in your 

community or neighborhood?

1 –0.0598 0.0472 –1.2647 0.2060

K10Q40 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . How often do you feel [s.c.] is safe in your 

community or neighborhood?

1 –0.0712 0.0223 –3.1920 0.0014

K10Q40 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . How often do you feel [s.c.] is safe in your 

community or neighborhood?

1 –0.0200 0.0123 –1.6319 0.1027

K10Q40 4 (reference) . . . . . . . . . . . . . . . . . . How often do you feel [s.c.] is safe in your 

community or neighborhood?

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

K10Q13 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Does a recreation center, community 

center, or boys’ or girls’ club exist in your 

community?

1 –0.0412 0.0125 –3.2966 0.0010

K10Q13 1 (reference) . . . . . . . . . . . . . . . . . . Does a recreation center, community 

center, or boys’ or girls’ club exist in your 

community?

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

Median_Home_Val_q 1 . . . . . . . . . . . . . . . . Median home value by exchange (quartiles) 1 –0.1295 0.0361 –3.5883 0.0003

Median_Home_Val_q 2 . . . . . . . . . . . . . . . . Median home value by exchange (quartiles) 1 –0.0892 0.0281 –3.1723 0.0015

Median_Home_Val_q 3 . . . . . . . . . . . . . . . . Median home value by exchange (quartiles) 1 –0.0609 0.0194 –3.1371 0.0017

Median_Home_Val_q 4 (reference) . . . . . . . Median home value by exchange (quartiles) ... ... ... ... ...

C10Q14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . What is the age of the oldest adult living in 

the household?

1 –0.0020 0.0006 –3.2122 0.0013

See footnotes at end of table.
Page 236  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

S4Q01 0. . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his / 

her] birth], did [s.c.] see a doctor, nurse, or 

other health care professional for any kind 

of medical care, including sick-child care, 

well-child check-ups, physical exams, and 

hospitalizations?

1 –0.0670 0.0348 –1.9256 0.0542

S4Q01 1 (reference) . . . . . . . . . . . . . . . . . . . [During the past 12 months/ since [his/her] 

birth], did [s.c.] see a doctor, nurse, or 

other health care professional for any kind 

of medical care, including sick-child care, 

well-child check-ups, physical exams, and 

hospitalizations?

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

White_p_q 1 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of white by exchange (quartiles) 1 0.0630 0.0352 1.7904 0.0734

White_p_q 2 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of white by exchange (quartiles) 1 0.0492 0.0283 1.7343 0.0829

White_p_q 3 . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of white by exchange (quartiles) 1 0.0254 0.0206 1.2348 0.2169

White_p_q 4 (reference) . . . . . . . . . . . . . . . . Percentage of white by exchange (quartiles) ... ... ... ... ...

K10Q34 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . If my child were outside playing and got hurt 

or scared, there are adults nearby who I 

trust to help my child.

1 0.0271 0.0344 0.7871 0.4312

K10Q34 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . If my child were outside playing and got hurt 

or scared, there are adults nearby who I 

trust to help my child.

1 –0.0131 0.0340 –0.3843 0.7008

K10Q34 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . If my child were outside playing and got hurt 

or scared, there are adults nearby who I 

trust to help my child.

1 –0.0123 0.0396 –0.3108 0.7559

K10Q34 4 (reference) . . . . . . . . . . . . . . . . . . If my child were outside playing and got hurt 

or scared, there are adults nearby who I 

trust to help my child.

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

K8Q32 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [he/she] does things that really bother 

you a lot?

1 0.0082 0.0525 0.1558 0.8762

K8Q32 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [he/she] does things that really bother 

you a lot?

1 0.0239 0.0521 0.4594 0.6460

K8Q32 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [he/she] does things that really bother 

you a lot?

1 –0.0229 0.0512 –0.4476 0.6545

K8Q32 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [he/she] does things that really bother 

you a lot?

1 –0.0513 0.0567 –0.9053 0.3653

K8Q32 5 (reference). . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [he/she] does things that really bother 

you a lot?

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

ACE9 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with anyone who had a 

problem with alcohol or drugs?

1 –0.0780 0.0202 –3.8655 0.0001

ACE9 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with anyone who had a 

problem with alcohol or drugs?

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

Age_18_34_p_q 1 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 18–34 by 

exchange (quartiles)

1 0.0241 0.0245 0.9853 0.3245

Age_18_34_p_q 2 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 18–34 by 

exchange (quartiles)

1 0.0130 0.0202 0.6406 0.5218

Age_18_34_p_q 3 . . . . . . . . . . . . . . . . . . . . Percentage of people aged 18–34 by 

exchange (quartiles)

1 –0.0042 0.0171 –0.2422 0.8086

Age_18_34_p_q 4 . . . . . . . . . . . . . . . . . . . . 

(reference) 

Percentage of people aged 18–34 by 

exchange (quartiles)

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

Owner_Occupied_p_q 1. . . . . . . . . . . . . . . . Percentage of housing ownership by 

exchange (quartiles)

1 0.1261 0.1769 0.7129 0.4759

Owner_Occupied_p_q 2. . . . . . . . . . . . . . . . Percentage of housing ownership by 

exchange (quartiles)

1 0.0642 0.1328 0.4832 0.6290

Owner_Occupied_p_q 3. . . . . . . . . . . . . . . . Percentage of housing ownership by 

exchange (quartiles)

1 –0.0711 0.0873 –0.8148 0.4152

Owner_Occupied_p_q 4 (reference) . . . . . . Percentage of housing ownership by 

exchange (quartiles)

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

Inc_25_50_p_q 1. . . . . . . . . . . . . . . . . . . . . Percentage of income $25,000–$50,000 by 

exchange (quartiles)

1 0.0963 0.0331 2.9051 0.0037

Inc_25_50_p_q 2. . . . . . . . . . . . . . . . . . . . . Percentage of income $25,000–$50,000 by 

exchange (quartiles)

1 0.0196 0.0229 0.8574 0.3912

Inc_25_50_p_q 3. . . . . . . . . . . . . . . . . . . . . Percentage of income $25,000–$50,000 by 

exchange (quartiles)

1 –0.0050 0.0181 –0.2763 0.7823

Inc_25_50_p_q 4 (reference) . . . . . . . . . . . . Percentage of income $25,000–$50,000 by 

exchange (quartiles)

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

See footnotes at end of table.
Series 1, No. 59  Page 237 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K5Q44 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], how often did [s.c.]’s doctors or 

other health care providers help you feel 

like a partner in [his/her] care?

1 0.0506 0.0393 1.2890 0.1974

K5Q44 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], how often did [s.c.]’s doctors or 

other health care providers help you feel 

like a partner in [his/her] care?

1 0.0720 0.0266 2.7037 0.0069

K5Q44 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], how often did [s.c.]’s doctors or 

other health care providers help you feel 

like a partner in [his/her] care?

1 0.0281 0.0161 1.7436 0.0812

K5Q44 4 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], how often did [s.c.]’s doctors or 

other health care providers help you feel 

like a partner in [his/her] care?

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

K5Q42 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . When [s.c.] is seen by doctors or other 

health care providers, how often are 

they sensitive to your family’s values and 

customs?

1 –0.1375 0.0481 –2.8567 0.0043

K5Q42 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . When [s.c.] is seen by doctors or other 

health care providers, how often are 

they sensitive to your family’s values and 

customs?

1 –0.0666 0.0276 –2.4153 0.0157

K5Q42 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . When [s.c.] is seen by doctors or other 

health care providers, how often are 

they sensitive to your family’s values and 

customs?

1 –0.0146 0.0158 –0.9230 0.3560

K5Q42 4 (reference). . . . . . . . . . . . . . . . . . . When [s.c.] is seen by doctors or other 

health care providers, how often are 

they sensitive to your family’s values and 

customs?

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

C4Q04 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often have you been frustrated 

in your efforts to get services for [s.c.]?

1 –0.0245 0.0363 –0.6743 0.5001

C4Q04 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often have you been frustrated 

in your efforts to get services for [s.c.]?

1 –0.0571 0.0369 –1.5479 0.1216

C4Q04 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often have you been frustrated 

in your efforts to get services for [s.c.]?

1 0.0272 0.0488 0.5562 0.5781

C4Q04 4 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often have you been frustrated 

in your efforts to get services for [s.c.]?

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

Inc_0_25_p_q 1. . . . . . . . . . . . . . . . . . . . . . Percentage of income $0–$25,000 by 

exchange (quartiles)

1 0.0903 0.0447 2.0180 0.0436

Inc_0_25_p_q 2. . . . . . . . . . . . . . . . . . . . . . Percentage of income $0–$25,000 by 

exchange (quartiles)

1 0.0840 0.0366 2.2946 0.0218

Inc_0_25_p_q 3. . . . . . . . . . . . . . . . . . . . . . Percentage of income $0–$25,000 by 

exchange (quartiles)

1 0.0746 0.0276 2.7067 0.0068

Inc_0_25_p_q 4 (reference) . . . . . . . . . . . . . Percentage of income $0–$25,000 by 

exchange (quartiles)

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

K5Q10 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] need a referral to see any 

doctors or receive any services?

1 0.0432 0.0154 2.8088 0.0050

K5Q10 1 (reference) . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], did [s.c.] need a referral to see any 

doctors or receive any services?

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

CSHCN 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Child with special health care need 1 –0.0986 0.0226 –4.3659 10.0000

CSHCN 1 (reference) . . . . . . . . . . . . . . . . . . Child with special health care need ... ... ... ... ...

K2Q10 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Does [s.c.] currently need or use medicine 

prescribed by a doctor, other than 

vitamins?

1 0.0475 0.0190 2.4930 0.0127

K2Q10 1 (reference) . . . . . . . . . . . . . . . . . . . Does [s.c.] currently need or use medicine 

prescribed by a doctor, other than 

vitamins?

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

Total_HHn_q 1 . . . . . . . . . . . . . . . . . . . . . . . Total number of exchange households 

(quartiles)

1 0.1460 0.0865 1.6875 0.0915

Total_HHn_q 2 . . . . . . . . . . . . . . . . . . . . . . . Total number of exchange households 

(quartiles)

1 0.0695 0.0410 1.6944 0.0902

Total_HHn_q 3 . . . . . . . . . . . . . . . . . . . . . . . Total number of exchange households 

(quartiles)

1 0.0306 0.0233 1.3147 0.1886

Total_HHn_q 4 (reference) . . . . . . . . . . . . . . Total number of exchange households 

(quartiles)

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

See footnotes at end of table.
Page 238  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

oldest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Age of the oldest child in the household 1 –0.0106 0.0029 –3.6276 0.0003

K4Q31 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Has [s.c.] ever had [his/her] vision tested 

with pictures, shapes, or letters?

1 –0.0435 0.0131 –3.3186 0.0009

K4Q31 1 (reference). . . . . . . . . . . . . . . . . . . Has [s.c.] ever had [his/her] vision tested 

with pictures, shapes, or letters?

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

K8Q31 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [s.c.] is much harder to care for than 

most children [his/her] age?

1 0.0619 0.0377 1.6421 0.1006

K8Q31 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [s.c.] is much harder to care for than 

most children [his/her] age?

1 0.0362 0.0387 0.9361 0.3492

K8Q31 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [s.c.] is much harder to care for than 

most children [his/her] age?

1 0.0456 0.0385 1.1827 0.2369

K8Q31 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [s.c.] is much harder to care for than 

most children [his/her] age?

1 0.0967 0.0461 2.0996 0.0358

K8Q31 5 (reference). . . . . . . . . . . . . . . . . . . During the past month, how often have you 

felt [s.c.] is much harder to care forthan 

most children [his/her] age?

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

K4Q27 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], was there any time when [s.c.] 

needed health care but it was delayed or 

not received?

1 0.0591 0.0245 2.4183 0.0156

K4Q27 1 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/

her] birth], was there any time when [s.c.] 

needed health care but it was delayed or 

not received?

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

youngest. . . . . . . . . . . . . . . . . . . . . . . . . . . . Age of youngest child in the household 1 0.0061 0.0029 2.1151 0.0344

Percent_Listed_q 1. . . . . . . . . . . . . . . . . . . . Percentage in white pages by exchange 

(quartiles)

1 –0.0357 0.0245 –1.4577 0.1449

Percent_Listed_q 2. . . . . . . . . . . . . . . . . . . . Percentage in white pages by exchange 

(quartiles)

1 –0.0083 0.0171 –0.4828 0.6292

Percent_Listed_q 3. . . . . . . . . . . . . . . . . . . . Percentage in white pages by exchange 

(quartiles)

1 –0.0283 0.0139 –2.0414 0.0412

Percent_Listed_q 4 (reference). . . . . . . . . . . Percentage in white pages by exchange 

(quartiles)

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

TRUEMSA3 1 . . . . . . . . . . . . . . . . . . . . . . . . True MSA status (3 categories) 1 0.1578 0.0338 4.6724 10.0000

TRUEMSA3 2 . . . . . . . . . . . . . . . . . . . . . . . . True MSA status (3 categories) 1 0.1487 0.0317 4.6948 10.0000

TRUEMSA33. . . . . . . . . . . . . . . . . . . . . . . . . True MSA status (3 categories) ... ... ... ... ...

Msa 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MSA Type (4 categories) 1 –0.1274 0.0345 –3.6893 0.0002

Msa 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MSA Type (4 categories) 1 –0.1210 0.0334 –3.6218 0.0003

Msa 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MSA Type (4 categories) 1 –0.1360 0.0347 –3.9181 0.0001

Msa 4 (reference) . . . . . . . . . . . . . . . . . . . . . MSA Type (4 categories) ... ... ... ... ...

K5Q41 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers listen carefully 

to you?

1 0.0396 0.0494 0.8010 0.4232

K5Q41 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers listen carefully 

to you?

1 0.0142 0.0280 0.5065 0.6125

K5Q41 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers listen carefully 

to you?

1 0.0360 0.0160 2.2454 0.0247

K5Q41 4 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did [s.c.]’s doctors and 

other health care providers listen carefully 

to you?

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

ACE8 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with anyone who 

was mentally ill or suicidal, or severely 

depressed for more than a couple of 

weeks?

1 0.0436 0.0197 2.2087 0.0272

ACE8 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever live with anyone who 

was mentally ill or suicidal, or severely 

depressed for more than a couple of 

weeks?

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

HISPANIC 0 . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Indicates whether child is of 

Hispanic origin/ ethnicity (after back 

coding)

1 0.0483 0.0209 2.3155 0.0206

See footnotes at end of table.
Series 1, No. 59  Page 239 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

HISPANIC 1 (reference). . . . . . . . . . . . . . . . Derived. Indicates whether child is of 

Hispanic origin/ ethnicity (after back 

coding)

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

K11Q33 0. . . . . . . . . . . . . . . . . . . . . . . . . . . And how about [s.c.]? (Born in the United 

States?)

1 –0.0836 0.0360 –2.3261 0.0200

K11Q33 1 (reference) . . . . . . . . . . . . . . . . . . And how about [s.c.]? (Born in the United 

States?)

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

K3Q25 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . In the past 12 months did your family have 

problems paying or were unable to pay 

any of [s.c.]’s medical bills? Include bills 

for doctors, dentists, hospitals, therapists, 

medication, equipment, or home care.

1 0.0422 0.0191 2.2136 0.0269

K3Q25 1 (reference). . . . . . . . . . . . . . . . . . . In the past 12 months did your family have 

problems paying or were unable to pay 

any of [s.c.]’s medical bills? Include bills 

for doctors, dentists, hospitals, therapists, 

medication, equipment, or home care.

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

K5Q43 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did you get the specific 

information you needed from [s.c.]’s 

doctors and other health care providers?

1 0.0283 0.0326 0.8671 0.3859

K5Q43 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did you get the specific 

information you needed from [s.c.]’s 

doctors and other health care providers?

1 0.0132 0.0231 0.5725 0.5670

K5Q43 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did you get the specific 

information you needed from [s.c.]’s 

doctors and other health care providers?

1 0.0307 0.0147 2.0951 0.0362

K5Q43 4 (reference). . . . . . . . . . . . . . . . . . . [During the past 12 months / since [his/her] 

birth], how often did you get the specific 

information you needed from [s.c.]’s 

doctors and other health care providers?

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

K2Q19 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Does [s.c.] need or get special therapy, 

such as physical, occupational, or speech 

therapy?

1 0.0682 0.0254 2.6808 0.0073

K2Q19 1 (reference) . . . . . . . . . . . . . . . . . . . Does [s.c.] need or get special therapy, 

such as physical, occupational, or speech 

therapy?

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

K2Q45A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had bone, joint, or 

muscle problems?

1 –0.0635 0.0294 –2.1559 0.0311

K2Q45A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had bone, joint, or 

muscle problems?

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

K2Q35A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care 

provider ever told you that [s.c.] had 

autism, Asperger’s disorder, pervasive 

developmental disorder, or other autism 

spectrum disorder?

1 –0.0787 0.0413 –1.9054 0.0567

K2Q35A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care 

provider ever told you that [s.c.] had 

autism, Asperger’s disorder, pervasive 

developmental disorder, or other autism 

spectrum disorder?

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

K2Q31A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had attention deficit 

disorder or attention deficit hyperactive 

disorder, that is, ADD or ADHD?

1 0.0471 0.0222 2.1204 0.0340

K2Q31A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had attention deficit 

disorder or attention deficit hyperactive 

disorder, that is, ADD or ADHD?

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

K10Q22 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . How about poorly kept or [dilapidated/

rundown] housing?

1 0.0299 0.0158 1.8881 0.0590

K10Q22 1 (reference) . . . . . . . . . . . . . . . . . . How about poorly kept or [dilapidated/

rundown] housing?

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

K10Q32 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . There are people I can count on in this 

neighborhood.

1 0.0662 0.0361 1.8317 0.0670

K10Q32 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . There are people I can count on in this 

neighborhood.

1 0.0467 0.0348 1.3416 0.1797

K10Q32 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . There are people I can count on in this 

neighborhood.

1 0.0263 0.0384 0.6835 0.4943

See footnotes at end of table.
Page 240  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K10Q32 4 (reference) . . . . . . . . . . . . . . . . . . There are people I can count on in this 

neighborhood.

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

Hispanic_p_q 1. . . . . . . . . . . . . . . . . . . . . . . Percentage of Hispanic by exchange 

(quartiles)

1 –0.0524 0.0293 –1.7888 0.0737

Hispanic_p_q 2. . . . . . . . . . . . . . . . . . . . . . . Percentage of Hispanic by exchange 

(quartiles)

1 –0.0436 0.0241 –1.8048 0.0711

Hispanic_p_q 3. . . . . . . . . . . . . . . . . . . . . . . Percentage of Hispanic by exchange 

(quartiles)

1 –0.0283 0.0199 –1.4232 0.1547

Hispanic_p_q 4 (reference) . . . . . . . . . . . . . Percentage of Hispanic by exchange 

(quartiles)

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

K10Q31 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . We watch out for each other’s children in 

this neighborhood.

1 0.0074 0.0387 0.1922 0.8476

K10Q31 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . We watch out for each other’s children in 

this neighborhood.

1 0.0296 0.0375 0.7904 0.4293

K10Q31 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . We watch out for each other’s children in 

this neighborhood.

1 0.0132 0.0401 0.3291 0.7421

K10Q31 4 (reference). . . . . . . . . . . . . . . . . . We watch out for each other’s children in 

this neighborhood.

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

Age_55_p_q 1 . . . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 55 and over by 

exchange (quartiles)

1 –0.0497 0.0311 –1.6016 0.1092

Age_55_p_q 2 . . . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 55 and over by 

exchange (quartiles)

1 –0.0304 0.0252 –1.2079 0.2271

Age_55_p_q 3 . . . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 55 and over by 

exchange (quartiles)

1 0.0033 0.0202 0.1617 0.8715

Age_55_p_q 4 (reference) . . . . . . . . . . . . . . Percentage of people aged 55 and over by 

exchange (quartiles)

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

Age_0_17_p_q 1 . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 0–17 years by 

exchange (quartiles)

1 –0.0487 0.0260 –1.8740 0.0609

Age_0_17_p_q 2 . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 0–17 years by 

exchange (quartiles)

1 –0.0589 0.0210 –2.8036 0.0051

Age_0_17_p_q 3 . . . . . . . . . . . . . . . . . . . . . Percentage of people aged 0–17 years by 

exchange (quartiles)

1 –0.0356 0.0172 –2.0722 0.0383

Age_0_17_p_q 4 (reference) . . . . . . . . . . . . Percentage of people aged 0-17 years by 

exchange (quartiles)

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

Household_Density_q 1 . . . . . . . . . . . . . . . . Household density by exchange (quartiles) 1 0.0427 0.0251 1.7023 0.0887

Household_Density_q 2 . . . . . . . . . . . . . . . . Household density by exchange (quartiles) 1 0.0376 0.0213 1.7648 0.0776

Household_Density_q 3 . . . . . . . . . . . . . . . . Household density by exchange (quartiles) 1 0.0271 0.0176 1.5344 0.1249

Household_Density_q 4 (reference) . . . . . . . Household density by exchange (quartiles) ... ... ... ... ...

Rent_Other_p_q 1 . . . . . . . . . . . . . . . . . . . . Percentage of nonowners by exchange 

(quartiles)

1 0.0736 0.1770 0.4158 0.6776

Rent_Other_p_q 2 . . . . . . . . . . . . . . . . . . . . Percentage of nonowners by exchange 

(quartiles)

1 0.1671 0.1540 1.0850 0.2779

Rent_Other_p_q 3 . . . . . . . . . . . . . . . . . . . . Percentage of nonowners by exchange 

(quartiles)

1 0.0704 0.1169 0.6022 0.5471

Rent_Other_p_q 4 (reference). . . . . . . . . . . Percentage of nonowners by exchange 

(quartiles)

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

K2Q03 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . How much does [s.c.] weigh now? 1 0.0003 0.0002 1.4748 0.1403

Annual_wt. . . . . . . . . . . . . . . . . . . . . . . . . . . Annual sample weight for each case 1 –0.0001 – –1.5382 0.1240

K2Q36A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care 

provider ever told you that [s.c.] had any 

developmental delay that affects [his/her] 

ability to learn?

1 –0.0408 0.0296 –1.3787 0.1680

K2Q36A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care 

provider ever told you that [s.c.] had any 

developmental delay that affects [his/her] 

ability to learn?

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

K2Q40A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had asthma?

1 0.0235 0.0164 1.4347 0.1514

K2Q40A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had asthma?

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

K10Q12 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Does a park or playground area exist in 

your neighborhood?

1 –0.0158 0.0160 –0.9858 0.3243

K10Q12 1 (reference) . . . . . . . . . . . . . . . . . . Does a park or playground area exist in 

your neighborhood?

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

SEX 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Derived. Sex of selected child 1 0.0127 0.0104 1.2221 0.2217

SEX 2 (reference). . . . . . . . . . . . . . . . . . . . . Derived. Sex of selected child ... ... ... ... ...

K4Q01 0. . . . . . . . . . . . . . . . . . . . . . . . . . . . Is there a place that [s.c.] usually goes 

when [he/she] is sick or you need advice 

about [his/her] health?

1 0.0519 0.0624 0.8321 0.4054

K4Q01 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . Is there a place that [s.c.] usually goes 

when [he/she] is sick or you need advice 

about [his/her] health?

1 0.0393 0.0318 1.2360 0.2165

See footnotes at end of table.
Series 1, No. 59  Page 241 

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K4Q01 2 (reference) . . . . . . . . . . . . . . . . . . . Is there a place that [s.c.] usually goes 

when [he/she] is sick or you need advice 

about [his/her] health?

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

Listed_HHn_q 1 . . . . . . . . . . . . . . . . . . . . . . Households in white pages by exchange 

(quartiles)

1 –0.0404 0.0575 –0.7028 0.4822

Listed_HHn_q 2 . . . . . . . . . . . . . . . . . . . . . . Households in white pages by exchange 

(quartiles)

1 –0.0131 0.0306 –0.4290 0.6679

Listed_HHn_q 3 . . . . . . . . . . . . . . . . . . . . . . Households in white pages by exchange 

(quartiles)

1 –0.0173 0.0185 –0.9354 0.3496

Listed_HHn_q 4 (reference) . . . . . . . . . . . . . Households in white pages by exchange 

(quartiles)

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

ACE7 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Was [s.c.] ever the victim of violence 

or witnessed any violence in [his/her] 

neighborhood?

1 0.0222 0.0221 1.0072 0.3138

ACE7 1 (reference). . . . . . . . . . . . . . . . . . . . Was [s.c.] ever the victim of violence 

or witnessed any violence in [his/her] 

neighborhood?

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

Median_Years_Educ_q 1. . . . . . . . . . . . . . . Median years of education by exchange 

(quartiles)

1 0.0072 0.0389 0.1859 0.8526

Median_Years_Educ_q 2. . . . . . . . . . . . . . . Median years of education by exchange 

(quartiles)

1 –0.0049 0.0317 –0.1559 0.8761

Median_Years_Educ_q 3. . . . . . . . . . . . . . . Median years of education by exchange 

(quartiles)

1 –0.0141 0.0241 –0.5849 0.5586

Median_Years_Educ_q 4 (reference) . . . . . . Median years of education by exchange 

(quartiles)

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

K3Q01 0. . . . . . . . . . . . . . . . . . . . . . . . . . . . Does [s.c.] have any kind of health care 

coverage, including health insurance, 

prepaid plans such as HMOs, or 

government plans such as Medicaid?

1 0.0279 0.0294 0.9491 0.3426

K3Q01 1 (reference) . . . . . . . . . . . . . . . . . . . Does [s.c.] have any kind of health care 

coverage, including health insurance, 

prepaid plans such as HMOs, or 

government plans such as Medicaid?

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

K8Q12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . About how often does [s.c.] attend a 

religious service? (frequency)

1 0.0012 0.0014 0.9083 0.3637

Asian_Pacif_p_q 1. . . . . . . . . . . . . . . . . . . . Percentage of Asian or Pacific Islander by 

exchange (quartiles)

1 –0.0193 0.0287 –0.6714 0.5020

Asian_Pacif_p_q 2. . . . . . . . . . . . . . . . . . . . Percentage of Asian or Pacific Islander by 

exchange (quartiles)

1 –0.0152 0.0227 –0.6700 0.5029

Asian_Pacif_p_q 3. . . . . . . . . . . . . . . . . . . . Percentage of Asian or Pacific Islander by 

exchange (quartiles)

1 –0.0032 0.0176 –0.1807 0.8566

Asian_Pacif_p_q 4 (reference) . . . . . . . . . . . Percentage of Asian or Pacific Islander by 

exchange (quartiles)

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

K2Q46A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had a brain injury 

or concussion?

1 –0.0255 0.0296 –0.8620 0.3887

K2Q46A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had a brain injury 

or concussion?

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

K2Q22 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Does [s.c.] have any kind of emotional, 

developmental, or behavioral problem 

for which [he/she] needs treatment or 

counseling?

1 0.0263 0.0286 0.9213 0.3569

K2Q22 1 (reference). . . . . . . . . . . . . . . . . . . Does [s.c.] have any kind of emotional, 

developmental, or behavioral problem 

for which [he/she] needs treatment or 

counseling?

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

K2Q13 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Does [s.c.] need or use more medical care, 

mental health, or educational services 

than is usual for most children of the same 

age?

1 –0.0211 0.0216 –0.9782 0.3280

K2Q13 1 (reference) . . . . . . . . . . . . . . . . . . . Does [s.c.] need or use more medical care, 

mental health, or educational services 

than is usual for most children of the same 

age?

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

K10Q11 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . Do sidewalks or walking paths exist in your 

neighborhood?

1 –0.0120 0.0138 –0.869 0.3848

K10Q11 1 (reference). . . . . . . . . . . . . . . . . . Do sidewalks or walking paths exist in your 

neighborhood?

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

Total_Population_q 1 . . . . . . . . . . . . . . . . . . Total population by exchange (quartiles) 1 –0.0519 0.0827 –0.6268 0.5308

Total_Population_q 2 . . . . . . . . . . . . . . . . . . Total population by exchange (quartiles) 1 –0.0213 0.0394 –0.5423 0.5876

Total_Population_q 3 . . . . . . . . . . . . . . . . . . Total population by exchange (quartiles) 1 –0.0027 0.0229 –0.1184 0.9058

Total_Population_q 4 (reference) . . . . . . . . . Total population by exchange (quartiles) ... ... ... ... ...

See footnotes at end of table.
Page 242  Series 1, No. 59

Table XLVIII. Parameter estimates for linear regression model on transformed family income, sorted from largest partial R-squared to 

smallest—Con.

Parameter 

or level Label

Degrees

of freedom Estimate

Standard

error t value p value

K10Q14 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Does a library or bookmobile exist in your 

community?

1 0.0123 0.0191 0.6442 0.5194

K10Q14 1 (reference) . . . . . . . . . . . . . . . . . . Does a library or bookmobile exist in your 

community?

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

K2Q33A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had anxiety 

problems?

1 –0.0193 0.0281 –0.6858 0.4929

K2Q33A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had anxiety 

problems?

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

K2Q43A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had hearing 

problems?

1 0.0165 0.0289 0.5710 0.5680

K2Q43A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had hearing 

problems?

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

K10Q23 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . How about vandalism such as broken 

windows or graffiti?

1 0.0102 0.0197 0.5178 0.6046

K10Q23 1 (reference) . . . . . . . . . . . . . . . . . . How about vandalism such as broken 

windows or graffiti?

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

AGEYR_CHILD . . . . . . . . . . . . . . . . . . . . . . Selected child’s age in years at interview 1 –0.0016 0.0033 –0.4746 0.6351

INC_YR 2010 . . . . . . . . . . . . . . . . . . . . . . . . Income reference year 1 0.0060 0.0138 0.4327 0.6652

INC_YR 2011 (reference). . . . . . . . . . . . . . . Income reference year ... ... ... ... ...

K2Q05 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Was [s.c.] born prematurely, that is, more 

than 3 weeks before [his/her] due date?

1 –0.0064 0.0162 –0.3963 0.6919

K2Q05 1 (reference). . . . . . . . . . . . . . . . . . . Was [s.c.] born prematurely, that is, more 

than 3 weeks before [his/her] due date?

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

K2Q34A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had behavioral or 

conduct problems, such as oppositional 

defiant disorder or conduct disorder?

1 0.0118 0.0348 0.3401 0.7338

K2Q34A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had behavioral or 

conduct problems, such as oppositional 

defiant disorder or conduct disorder?

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

K2Q37A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had stuttering, 

stammering, or other speech problems?

1 0.0073 0.0237 0.3086 0.7576

K2Q37A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had stuttering, 

stammering, or other speech problems?

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

K5Q31 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Do [s.c.]’s doctors or other health care 

providers need to communicate with 

[his/her] [child care providers, early 

intervention program, school, special 

education program, vocational education 

program]?

1 0.0048 0.0173 0.2770 0.7818

K5Q31 1 (reference). . . . . . . . . . . . . . . . . . . Do [s.c.]’s doctors or other health care 

providers need to communicate with 

[his/her] [child care providers, early 

intervention program, school, special 

education program, vocational education 

program]?

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

K2Q32A 0. . . . . . . . . . . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had depression?

1 0.0039 0.0343 0.1123 0.9106

K2Q32A 1 (reference). . . . . . . . . . . . . . . . . . Has a doctor or other health care provider 

ever told you that [s.c.] had depression?

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

K4Q22 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . During the past 12 months, has [s.c.] 

received any treatment or counseling from 

a mental health professional?

1 0.0018 0.0378 0.0472 0.9624

K4Q22 1 (reference). . . . . . . . . . . . . . . . . . . During the past 12 months, has [s.c.] 

received any treatment or counseling from 

a mental health professional?

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

ACE6 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Did [s.c.] ever see or hear any parents or 

adults in [his/her] home slap, hit, kick, 

punch, or beat each other up?

1 –0.0009 0.0253 –0.0372 0.9703

ACE6 1 (reference). . . . . . . . . . . . . . . . . . . . Did [s.c.] ever see or hear any parents or 

adults in [his/her] home slap, hit, kick, 

punch, or beat each other up?

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

NUMB_SERVICES. . . . . . . . . . . . . . . . . . . . Number of services required 1 0.0008 0.0288 0.0273 0.9782

... Category not applicable.

10.0000 quantity more than zero but less than 0.00005.

NOTE: s.c. is selected child.
Series 1, No. 59  Page 243 

Use of Multiply Imputed 

Values

The derived poverty level variable 

available for public use was calculated 

from household income and household 

size. When either or both were missing, 

the derived poverty level was calculated 

from the imputed values. A flag 

(POVLEVEL_F) indicates whether 

the derived poverty level was based on 

reported or imputed values.

When missing, household income 

and household size were imputed five 

times. Therefore, the resulting data set 

contains five times as many observations 

as in the original data set. For the 

2011–2012 NSCH, the data sets have 

5(95,677) = 478,385 records. Each 

complete set of derived poverty-level 

values is distinguished by the SAS 

variable IMPUTATION. Therefore, each 

IDNUMR appears five times in the file, 

with IMPUTATION having values of 

1, 2, 3, 4, and 5 corresponding to the 

five separate complete sets of derived 

poverty-level values.

The public-use data files for NSCH 

do not include household income, to 

protect against inadvertent disclosure of 

survey subjects’ identities. Only poverty 

level is reported on the public-use data 

files. Similarly, imputed household 

income is not released as public-use data. 

Researchers interested in accessing the 

original and imputed household income 

data may access the data through the 

National Center for Health Statistics’ 

Research Data Center (visit https://www.

cdc.gov/rdc).

Three possible ways to analyze the 

data are described below; one invalid 

way that researchers should not attempt is 

also described. 

Considering valid methods, a 

complete-case (only) analysis is the 

simplest, using only those cases with 

observed values. This can be done 

by using the poverty-level variable 

(POVERTY_LEVELR) in the NSCH 

data file. Any analysis using this variable 

could be biased due to nonresponse, and 

the variability will likely be larger due to 

smaller sample size. 

The second possible way of 

analyzing the data is to use only a single 

imputation from the multiple imputation 

files. Each of the five imputations has 

been drawn from a valid distribution 

based on a regression model, but this 

model and the distribution are slightly 

different for each imputation. To analyze 

only one imputation, choose only the 

subset of cases with IMPUTATION 

= c, where c is 1, 2, 3, 4, or 5. Single 

imputation analyses result in estimated 

standard errors that tend to be too small, 

because the imputed values are treated as 

if they were observed. This ignores the 

inherent uncertainty resulting from lack 

of knowledge about the true (unobserved) 

value, but it is superior to the completecase analysis. Note that slightly different 

results will be obtained depending on 

which subset of cases is chosen, but no 

subset is superior to another.

The most statistically valid way to 

analyze the data is to analyze all five 

imputed data sets together. To do this, 

five separate analyses are conducted—

one on each of the five imputed data 

sets. These analyses are then combined, 

following the standard multipleimputation combining rules (28). This is 

superior to the previous two methods. 

An invalid way to analyze the data is 

to combine the five imputed values into 

one analysis. For example, taking the 

average poverty level (which might not 

be an integer) to derive one “average” 

poverty status value per case is invalid. 

Poverty status should be analyzed 

as a multiply imputed variable with 

SAS, SUDAAN, IVEware, or another 

appropriate statistical software package 

to make use of the multiply imputed data. 

Regardless of the statistical software 

used to analyze the data, analysts must 

merge the survey data from the publicuse analysis files with the data from the 

multiple imputation file by the unique 

household identifier (IDNUMR). To 

combine these files, analysts must first 

sort both files by IDNUMR and then 

merge them, using this identifier as the 

merge variable. 

For SAS analyses, it is also very 

important to have the data set sorted 

by IMPUTATION, because analyses 

of the multiply imputed data need to 

be done separately by IMPUTATION. 

Separate analyses are specified in SAS 

by using the procedure option keyword 

BY (“BY IMPUTATION;” should be 

one line within the analysis). In SAS, 

the two basic steps to using the multiply 

imputed data are to 1) analyze the data 

separately by IMPUTATION as if each 

were a separate data set, and 2) combine 

the results from the different imputed 

data sets using PROC MIANALYZE. In 

the first step, separate analyses are done 

with options set to keep the covariances 

that are needed to combine the analyses. 

Then, PROC MIANALYZE combines 

the different analyses using the standard 

multiple-imputation combining rules. 

For SUDAAN analyses, a separate 

analytical file is necessary for each of 

the five imputations. The five data sets 

should then be sorted by the stratum 

variables (STATE and SAMPLE) and 

the primary sampling unit (IDNUMR) 

variable (see “Estimation and Hypothesis 

Testing” section of main report). To 

analyze the data using the five imputation 

files, the MI_COUNT command should 

be added to the SUDAAN procedure 

call. The MI_COUNT command tells 

SUDAAN how many imputation files to 

expect (MI_COUNT = 5).
Page 244  Series 1, No. 59

Appendix XV. Key Prevalence Estimates and Weighted Frequencies

This appendix consists of Table XLIX, which shows weighted frequencies of the number of children with excellent or very 

good health by state. Prevalence estimates and standard errors are also provided. Analysts may wish to replicate this table to 

determine if they are using the weights correctly.

Table XLIX. Unweighted and weighted estimates of frequency and prevalence of children with excellent or very good health, as assessed by 

National Survey of Children’s Health respondent

Area

Total children Children with excellent or very good health

Unweighted 

number

Weighted 

estimate

Unweighted 

number 

Weighted 

estimate 

Standard error 

of weighted 

estimate Percentage1

Standard error 

of percentage

Total (excluding U.S. Virgin Islands) 95,677 73,716,714 83,985 62,014,809 370,442 84.13 0.30

Alabama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,820 1,121,493 1,572 954,999 23,699 85.15 1.23

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 187,218 1,653 165,753 4,462 88.53 1.14

Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,845 1,620,552 1,555 1,297,338 35,446 80.06 1.46

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,849 709,031 1,557 579,654 15,632 81.75 1.42

California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,903 9,248,443 1,549 7,179,542 222,937 77.63 1.51

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,820 1,224,557 1,623 1,065,436 29,629 87.01 1.22

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,888 801,603 1,670 687,642 14,450 85.78 1.14

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,824 204,471 1,602 171,920 4,898 84.08 1.34

District of Columbia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,861 104,927 1,603 85,391 3,159 81.38 1.68

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,855 3,984,726 1,609 3,328,052 90,121 83.52 1.33

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,848 2,484,940 1,620 2,116,791 55,891 85.18 1.20

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,881 304,085 1,644 261,333 6,000 85.94 1.12

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,857 427,810 1,635 375,691 10,099 87.82 1.18

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,071 3,088,140 1,782 2,594,254 64,610 84.01 1.23

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,829 1,591,416 1,588 1,336,131 34,935 83.96 1.32

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,847 720,096 1,659 636,689 14,064 88.42 1.06

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,836 720,400 1,621 624,437 14,535 86.68 1.18

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,864 1,019,825 1,620 871,888 21,253 85.49 1.19

Louisiana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 1,116,814 1,580 954,553 25,931 85.47 1.23

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,823 268,807 1,635 238,752 5,380 88.82 1.01

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,181 1,343,898 1,941 1,160,287 34,421 86.34 1.23

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,861 1,399,869 1,691 1,239,090 27,183 88.51 1.10

Michigan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,833 2,284,102 1,632 2,012,250 51,151 88.1 1.12

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,830 1,277,521 1,646 1,118,907 27,998 87.58 1.19

Mississippi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,883 749,413 1,618 632,531 17,740 84.40 1.33

Missouri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,859 1,406,516 1,667 1,262,287 27,926 89.75 0.95

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,824 220,046 1,660 197,292 4,560 89.66 1.04

Nebraska . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,818 457,759 1,616 399,322 8,960 87.23 1.11

Nevada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,901 661,419 1,588 522,315 16,145 78.97 1.52

New Hampshire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,934 280,057 1,780 254,807 5,651 90.98 1.00

New Jersey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,858 2,036,617 1,605 1,705,082 43,389 83.72 1.28

New Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,847 517,036 1,567 421,029 12,588 81.43 1.48

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,989 4,266,861 1,733 3,547,871 80,350 83.15 1.25

North Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,852 2,287,997 1,617 1,937,842 54,301 84.70 1.37

North Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,835 150,969 1,684 137,914 3,553 91.35 0.95

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,916 2,682,054 1,712 2,327,596 61,241 86.78 1.21

Oklahoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,886 932,265 1,592 786,661 19,903 84.38 1.21

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,846 859,845 1,620 715,649 16,630 83.23 1.32

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,886 2,752,138 1,686 2,400,525 73,298 87.22 1.28

Rhode Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,889 218,241 1,675 189,346 4,737 86.76 1.14

South Carolina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,930 1,078,316 1,653 927,052 24,438 85.97 1.14

South Dakota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,811 201,731 1,647 185,027 3,990 91.72 0.84

Tennessee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,862 1,486,878 1,619 1,249,445 32,924 84.03 1.33

Texas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,200 6,946,024 1,831 5,697,388 177,883 82.02 1.41

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,823 878,099 1,633 763,361 17,202 86.93 1.17

Vermont . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,856 126,393 1,701 114,033 2,470 90.22 0.97

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,909 1,849,178 1,747 1,643,230 46,173 88.86 1.18

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,843 1,575,209 1,607 1,329,923 36,289 84.43 1.31

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,827 384,491 1,579 331,763 7,420 86.29 1.07

Wisconsin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,838 1,322,180 1,644 1,161,993 27,219 87.88 1.08

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,837 134,238 1,617 116,747 2,718 86.97 1.09

1

Denominator includes children for whom health status was not reported because the respondent did not know or refused to answer the health status question.
Vital and Health Statistics

Series Descriptions

Active Series

Series 1. Programs and Collection Procedures

Reports describe the programs and data systems of the 

National Center for Health Statistics, and the data collection 

and survey methods used. Series 1 reports also include 

definitions, survey design, estimation, and other material 

necessary for understanding and analyzing the data.

Series 2. Data Evaluation and Methods Research

Reports present new statistical methodology including 

experimental tests of new survey methods, studies of vital and 

health statistics collection methods, new analytical techniques, 

objective evaluations of reliability of collected data, and 

contributions to statistical theory. Reports also include 

comparison of U.S. methodology with those of other countries.

Series 3. Analytical and Epidemiological Studies

Reports present data analyses, epidemiological studies, and 

descriptive statistics based on national surveys and data 

systems. As of 2015, Series 3 includes reports that would 

have previously been published in Series 5, 10–15, and 20–23.

Discontinued Series

Series 4. Documents and Committee Reports

Reports contain findings of major committees concerned with 

vital and health statistics and documents. The last Series 4 

report was published in 2002; these are now included in 

Series 2 or another appropriate series.

Series 5. International Vital and Health Statistics Reports

Reports present analytical and descriptive comparisons of 

U.S. vital and health statistics with those of other countries. 

The last Series 5 report was published in 2003; these are now 

included in Series 3 or another appropriate series.

Series 6. Cognition and Survey Measurement

Reports use methods of cognitive science to design, evaluate, 

and test survey instruments. The last Series 6 report was 

published in 1999; these are now included in Series 2.

Series 10. Data From the National Health Interview Survey

Reports present statistics on illness; accidental injuries; 

disability; use of hospital, medical, dental, and other services; 

and other health-related topics. As of 2015, these are included 

in Series 3.

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

National Health and Nutrition Examination Surveys, and 

the Hispanic Health and Nutrition Examination Survey

Reports present 1) estimates of the medically defined 

prevalence of specific diseases in the United States and the 

distribution of the population with respect to physical, 

physiological, and psychological characteristics and 2) 

analysis of relationships among the various measurements. 

As of 2015, these are included in Series 3.

Series 12. Data From the Institutionalized Population Surveys

The last Series 12 report was published in 1974; these reports 

were included in Series 13, and as of 2015 are in Series 3.

Series 13. Data From the National Health Care Survey

Reports present statistics on health resources and use of 

health care resources based on data collected from health 

care providers and provider records. As of 2015, these reports 

are included in Series 3.

Series 14. Data on Health Resources: Manpower and Facilities

The last Series 14 report was published in 1989; these reports 

were included in Series 13, and are now included in Series 3.

Series 15. Data From Special Surveys

Reports contain statistics on health and health-related topics 

from surveys that are not a part of the continuing data systems 

of the National Center for Health Statistics. The last Series 15 

report was published in 2002; these reports are now included 

in Series 3.

Series 16. Compilations of Advance Data From Vital and Health 

Statistics

The last Series 16 report was published in 1996. All reports 

are available online; compilations are no longer needed.

Series 20. Data on Mortality

Reports include analyses by cause of death and demographic 

variables, and geographic and trend analyses. The last Series 

20 report was published in 2007; these reports are now 

included in Series 3.

Series 21. Data on Natality, Marriage, and Divorce

Reports include analyses by health and demographic 

variables, and geographic and trend analyses. The last Series 

21 report was published in 2006; these reports are now 

included in Series 3.

Series 22. Data From the National Mortality and Natality Surveys

The last Series 22 report was published in 1973. Reports from 

sample surveys of vital records were included in Series 20 or 

21, and are now included in Series 3.

Series 23. Data From the National Survey of Family Growth

Reports contain statistics on factors that affect birth rates, 

factors affecting the formation and dissolution of families, and 

behavior related to the risk of HIV and other sexually 

transmitted diseases. The last Series 23 report was published 

in 2011; these reports are now included in Series 3.

Series 24. Compilations of Data on Natality, Mortality, Marriage, and 

Divorce

The last Series 24 report was published in 1996. All reports 

are available online; compilations are no longer needed.

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

in these series, contact:

Information Dissemination Staff

National Center for Health Statistics

Centers for Disease Control and Prevention

3311 Toledo Road, Room 5419, MS P08

Hyattsville, MD 20782

Tel: 1–800–CDC–INFO (1–800–232–4636)

TTY: 1–888–232–6348

Internet: https://www.cdc.gov/nchs

Online request form: https://www.cdc.gov/info

For e-mail updates on NCHS publication releases, subscribe 

online at: https://www.cdc.gov/nchs/govdelivery.htm.
U.S. DEPARTMENT OF

HEALTH & HUMAN SERVICES

Centers for Disease Control and Prevention 

National Center for Health Statistics 

3311 Toledo Road, Room 4551, MS P08

Hyattsville, MD 20782–2064

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DHHS Publication No. (PHS) 2017–1335, Series 1, No. 59

CS275039