National Immunization Survey-Child

A User’s Guide for the 2019 

Public-Use Data File

Centers for Disease Control and Prevention 

National Center for Immunization 

and Respiratory Diseases 

Presented by:

NORC at the University of Chicago

December 2020
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page i 

Acknowledgments

The development and production of the NIS-Child public-use data files is a team effort that has included 

contributions from many individuals (listed in alphabetical order) in the two organizations:

National Center for Immunization and Respiratory Diseases, CDC – Laurie D. Elam-Evans, Holly A. 

Hill, James A. Singleton, Chalanda S. Smith, and Larry Wilkinson. 

NORC at the University of Chicago – Rachel Bavley, Benjamin Skalland, Kirk Wolter, and Maggie 

Yarbrough.
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Table of Contents 

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

2. Sample Design .................................................................................................................................... 7

2.1. The NIS-Child RDD Telephone Survey ..................................................................................... 7

2.2. The NIS-Child Provider Record Check .................................................................................... 10

2.3. Summary of Data Collection .................................................................................................... 10

2.4. Informed Consent, Security, and Confidentiality of Information ............................................. 14

3. Content of NIS-Child Questionnaires............................................................................................ 15

3.1. Content of the Household Questionnaire .................................................................................. 15

3.2. Content of the Immunization History Questionnaire (IHQ) ..................................................... 17

4. Data Preparation and Processing Procedures............................................................................... 19

4.1. Data Preparation ....................................................................................................................... 19

4.1.1. Editing in the CATI System ........................................................................................ 20

4.1.2. Post-CATI Edits .......................................................................................................... 20

4.1.3. Editing of Provider Data .............................................................................................. 21

4.2. Limitations of Data Editing Procedures.................................................................................... 22

4.3. Variable-Naming Conventions................................................................................................. 23

4.4. Missing Value Codes................................................................................................................ 23

4.5. Imputation for Item Non-Response .......................................................................................... 23

4.6. Vaccine-Specific Recoding of Verbatim Responses ................................................................ 25

4.7. Composite Variables................................................................................................................. 25

4.8. Subsets of the NIS-Child Data.................................................................................................. 28

4.9. Confidentiality and Disclosure Avoidance ............................................................................... 28

5. Quality Control and Quality Assurance Procedures.................................................................... 28

6. Sampling Weights............................................................................................................................ 30

6.1. Base Sampling Weight ............................................................................................................. 31

6.2. Adjustments for Non-Resolution of Telephone Numbers, Screener Non-Response, and 

Interview Non-Response .......................................................................................................... 31

6.3. Adjustment for Multiple Cell Phones and Deriving Annual Weights ...................................... 32

6.4. Calibration ................................................................................................................................ 33

6.5. Adjustment for Provider Non-Response ................................................................................... 35

6.6. Sampling Weights for Territories............................................................................................. 38

7. Contents of the Public-Use Data File ............................................................................................. 39

7.1. Section 1: ID, Weight, and Flag Variables ............................................................................... 43

7.2. Section 2: Household-Reported Vaccination and Chickenpox Information............................. 43
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7.3. Section 3: Demographic, Socio-Economic, and Other Household/Child Information ............. 43

7.4. Section 4: Geographic Variables.............................................................................................. 45

7.5. Section 5: Number of Providers Identified and Consent Variables .......................................... 45

7.6. Section 6: Number of Responding Providers Variables ........................................................... 46

7.7. Section 7: Characteristics of Providers Variables..................................................................... 46

7.8. Section 8: Provider-Reported Up-To-Date Vaccination Variables .......................................... 48

7.8.1. Hib Up-To-Date Variables .......................................................................................... 51

7.8.2. Rotavirus Up-To-Date Variables................................................................................. 53

7.9. Section 9: Provider-Reported Age-At-Vaccination Variables.................................................. 54

7.10. Section 10: Health Insurance Module Variables ...................................................................... 55

8. Analytic and Reporting Guidelines................................................................................................ 56

8.1. Use of NIS-Child Sampling Weights........................................................................................ 57

8.2. Estimation and Analysis........................................................................................................... 58

8.2.1. Estimating Vaccination Coverage Rates ..................................................................... 58

8.2.2. Estimating Standard Errors of Vaccination Coverage Rates....................................... 59

8.3. Combining Multiple Years of NIS-Child Data ......................................................................... 60

8.3.1. Estimation of Multi-Year Means................................................................................. 60

8.3.2. Estimation of Multi-Year Contrasts............................................................................. 63

9. Summary Tables.............................................................................................................................. 70

10. Assessment of Total Survey Error.................................................................................................. 71

11. Limitations........................................................................................................................................ 80

12. Citations for NIS-Child Data.......................................................................................................... 81

13. References......................................................................................................................................... 88
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Appendices

Appendix A: Glossary of Abbreviations and Terms ................................................................................... 93

Appendix B: Summary Statistics for Sampling Weights by Estimation Area............................................ 96

Appendix C: Flags for Inconsistent Values in the Breastfeeding Data ..................................................... 100

Appendix D: Programs for Estimation: Examples of the Use of SUDAAN, SAS, and R to Estimate 

Vaccination Coverage Rates and Their Standard Errors, and an Example of the Production of a CrossTabulation and Chart................................................................................................................................. 101

Appendix E: Alphabetical Listing of Variables that are in the 2004-2019 Public-Use Data Files........... 133

Appendix F: Summary Tables .................................................................................................................. 179

Appendix G: Trends in NIS-Child Response Rates and Vaccination Coverage Rates, 1995-2019 ......... 188

Appendix H: Vaccine Type Codes............................................................................................................ 196

Appendix I: Key NIS-Child Response Rates by Area .............................................................................. 197
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List of Tables and Figures

Table 1: Selected Operational Results of Q1/2019-Q4/2019 NIS-Child Data Collection (Excluding 

U.S. Territories) ..................................................................................................................... 13

Table 2: Content of the Household Interview, National Immunization Survey - Child, 2019 ............. 16

Table 3: Distribution of Age (in Days) at the Birth Dose of Hepatitis B Vaccine, National 

Immunization Survey - Child, 2019 ....................................................................................... 25

Table 4: Weighted Distribution of Children by Race/Ethnicity and Corresponding Combined Vaccine 

Series (4:3:1:3*:3:1:4), Pneumococcal, and Varicella Vaccination Coverage Estimates, 

National Immunization Survey - Child, 2019 ........................................................................ 27

Table 5: NIS-Child Variables Commonly Used in Analyses or for Published Estimates .................... 40

Table 6: Vaccine Categories and Vaccine Types, National Immunization Survey - Child, 2019 ....... 50

Table 7: Up-To-Date Variables for Hib, National Immunization Survey - Child, 2009-2019 ............ 52

Table 8: Up-To-Date Variables for Vaccine Series Including Hib, National Immunization Survey - 

Child, 2009-2019 ................................................................................................................... 53

Table 9: Summary of Weights and Stratum Variables, National Immunization Survey - Child, 2019 58

Table 10: Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP19, and Common 

Denominator Estimation Area (CDIAP), National Immunization Survey - Child, 2019 ...... 65

Figure 1: Scatter Plot of Difference between NIS-Child and IISAR Vaccination Coverage Rates for 

the Combined 7-Vaccine Series vs. IIS Child Participation Rate (CPR) with Regression 

Line: 54 Estimation Areas, 2018............................................................................................ 74

Table 11: Mean and 95% Credible Interval for the Estimated Total Survey Error (TSE) Distribution 

and Component Error Distributions for National Vaccination Coverage Rate Estimates, 

National Immunization Survey - Child, 2019 ........................................................................ 78

Table B.1: Distribution of Sampling Weights for Children with Completed Household Interviews, 

National Immunization Survey - Child, 2019 ........................................................................ 96

Table B.2: Distribution of Sampling Weights for Children with Adequate Provider Data, National 

Immunization Survey - Child, 2019 ....................................................................................... 98

Table E.1 Alphabetical Listing of Variables that are in the 2004-2019 Public-Use Data Files ........... 133

Table F.1: Estimated Population Totals and Sample Sizes of Children 19-35 Months of Age by State 

and Estimation Area, National Immunization Survey - Child, 2019 ................................... 179

Table F.2: Estimated Population Totals and Sample Sizes for Age Group by Maternal Education, 

National Immunization Survey - Child, 2019 ...................................................................... 181

Table F.3: Estimated Population Totals and Sample Sizes for Age Group by Poverty Status, National 

Immunization Survey - Child, 2019 ..................................................................................... 182

Table F.4: Estimated Population Totals and Sample Sizes for Race/Ethnicity by Poverty Status, 

National Immunization Survey - Child, 2019 ...................................................................... 183

Table F.5: Estimated Population Totals and Sample Sizes for Age Group by Race/Ethnicity, National 

Immunization Survey - Child, 2019 ..................................................................................... 184

Table F.6: Estimated Population Totals and Sample Sizes for Age Group by Sex, National 

Immunization Survey - Child, 2019 ..................................................................................... 185

Table F.7: Estimated Vaccination Coverage with Individual Vaccines and Selected Vaccination Series 

Among Children 19-35 Months of Age by State and Estimation Area, National 

Immunization Survey - Child, Q1/2019-Q4/2019................................................................ 186
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Table G.1: Key Indicators from Landline Sample Household and Provider Data Collection by Survey 

Year, National Immunization Survey - Child, 1995-2017 ................................................... 188

Figure G.1: Trends in Landline Sample Key Indicators from Household and Provider Data Collection by 

Survey Year, National Immunization Survey - Child, 1995-2017 ....................................... 189

Table G.2: Key Indicators from Cell-Phone Sample Household and Provider Data Collection by Survey 

Year, National Immunization Survey - Child, 2011-2019 ................................................... 190

Figure G.2: Trends in Cell-Phone Sample Key Indicators from Household and Provider Data Collection 

by Survey Year, National Immunization Survey - Child, 2011-2019 .................................. 191

Table G.3: CASRO Response Rate for the Combined Landline and Cell-Phone Samples by Survey 

Year, National Immunization Survey - Child, 2011-2017 ................................................... 193

Figure G.3: Trend in CASRO Response Rate for the Combined Landline and Cell-Phone Samples by 

Survey Year, National Immunization Survey - Child, 2011-2017 ....................................... 193

Table G.4: Vaccine-Specific Coverage Levels Among Children Age 19-35 Months in the United States 

by Survey Year, National Immunization Survey - Child, 1995-2019 .................................. 194

Figure G.4: Trends in Vaccine-Specific Coverage Levels among Children 19-35 Months of Age in the 

United States by Survey Year, National Immunization Survey - Child, 1995-2019 ........... 195

Table H.1: 2019 NIS-Child Vaccine Type Codes .................................................................................. 196

Table I.1: Key Indicators for the Cell-Phone Sample by Estimation Area, National Immunization 

Survey - Child, 2019 ............................................................................................................ 197
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Convention for Bolding Text

The Data User’s Guide uses bold font 

to highlight substantive changes in the 

methodology or study design from the 

previous year’s Guide. 
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1. Introduction 

In 1992, the Childhood Immunization Initiative (CII) (CDC 1994) was established to 1) improve the 

delivery of vaccines to children; 2) reduce the cost of childhood vaccines; 3) enhance awareness, 

partnerships, and community participation; 4) improve vaccinations and their use; and 5) monitor 

vaccination coverage and occurrences of disease. Subsequently, the Healthy People 2020 objectives 

established a target of having at least 90% of 2-year-old children fully vaccinated with most

recommended vaccines (targets are 85% for HepA and the birth dose of HepB, and 80% for rotavirus) and 

80% of 2-year-old children vaccinated with the basic immunization series. To fulfill the CII mandate of 

monitoring vaccination coverage and marking progress toward achieving those objectives, the National 

Immunization Survey - Child (NIS-Child) was implemented by the National Center for Immunization and 

Respiratory Diseases (NCIRD) and the National Center for Health Statistics (NCHS) of the Centers for 

Disease Control and Prevention (CDC) in 1994. From 1994 to 2014, the NIS-Child was conducted jointly 

by NCIRD and NCHS; since 2015, the NIS-Child has been conducted by NCIRD.

The target population for the NIS-Child is non-institutionalized children aged 19 through 35 months 

living in United States households at the time of the interview. The official coverage estimates reported 

from the NIS-Child are proportions of children up-to-date with respect to the requisite numbers of doses 

of all routinely recommended vaccines for this age group (Robinson et al. 2019). These vaccines and their 

recommended numbers of doses are: 

● diphtheria and tetanus toxoids and acellular pertussis vaccine adsorbed, diphtheria and tetanus 

toxoids and pertussis vaccine, or diphtheria and tetanus toxoids adsorbed (DTaP/DTP/DT) – 4 

doses;

● poliovirus vaccine (polio) – 3 doses;

● measles, mumps, and rubella vaccine (MMR) – 1 dose;
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● Haemophilus influenzae type b conjugate vaccine (Hib) – 3 or 4 doses depending on product 

type;

● hepatitis B vaccine (Hep B) – 3 doses;

● varicella (chicken pox) vaccine (VAR) – 1 dose;

● pneumococcal conjugate vaccine (PCV) – 4 doses;

● hepatitis A vaccine (Hep A) – 2 doses; 

● influenza vaccine; (For the recommended number of doses of influenza vaccine and other 

vaccines, see http://www.cdc.gov/vaccines/hcp/acip-recs/vacc-specific/index.html.)

● rotavirus vaccine (RV) – 2 or 3 doses depending on product type.

In addition to these vaccines, interest focuses on the combined vaccine series 4:3:1:3*:3:1:4 (4+ 

DTaP/DTP/DT; 3+ polio; 1+ measles-containing vaccine (MCV); full series Hib, i.e., 3 or 4 doses 

depending on type of vaccine received; 3+ Hep B; 1+ varicella at or after 12 months of age; and 4+ PCV). 

The NIS-Child collects data on each of these vaccines. Varicella vaccine was added in Quarter 3, 1996, 

pneumococcal conjugate vaccine in Quarter 4, 2000, influenza vaccine and hepatitis A vaccine in Quarter 

1, 2003, and rotavirus vaccine in Quarter 3, 2007. The remainder of the vaccines have been included in 

the NIS-Child from its start in 1994. Information about current and past recommendations for each 

vaccine can be found at https://www.cdc.gov/vaccines/hcp/acip-recs/index.html. 

The NIS-Child uses random digit dialing (RDD) telephone survey methodology to identify households 

containing children in the target age range, and interviews are conducted with the adult who is most 

knowledgeable about the child’s vaccinations. With consent of the child’s parent or guardian, the NISChild also contacts (by mail) the child’s health care provider(s) to request information on vaccinations 

from the child’s medical records. Since 2005, NIS-Child sampling, data collection, and weighting 

operations have been conducted by NORC at the University of Chicago. 
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Samples of telephone numbers are drawn independently, for each calendar quarter, within selected 

geographical areas, or strata. In 2019, there are 61 geographic strata for which vaccination coverage levels 

can be estimated (see Table F.1), including 7 local areas; the remaining 54 estimation areas are either an 

entire state, the District of Columbia, a territory (the U.S. Virgin Islands, Guam, or Puerto Rico), or a 

“rest of state” area. For states with “rest of state” or local estimation areas, estimates for the whole-state 

area can be produced as well. This design makes it possible to produce annual estimates of vaccination 

coverage levels for each state or territory, each “rest of state” area, the District of Columbia, and for each 

of the 7 local estimation areas with a specified degree of precision (a coefficient of variation of 

approximately 7.5%). Further, by using the same data collection methodology and survey instruments in 

all estimation areas, the NIS-Child produces comparable vaccination coverage levels among estimation 

areas and over time. 

When the NIS-Child was established in 1994, 78 areas were chosen for sampling strata, including the 50 

states, 6 urban areas that receive federal Section 317 immunization grants (Bexar County, TX; Chicago, 

IL; District of Columbia; Houston, TX; New York City, NY; Philadelphia County, PA), and 22 other 

urban areas. These areas were called “Immunization Action Plan” (IAP) areas in reference to plans 

developed to improve vaccination coverage following the resurgence of measles during 1989-1991. In 

2005 and 2006, selected non-awardee IAP areas – areas that do not receive separate Section 317 funds – 

were “rotated off” (i.e., sample design no longer ensured adequate sample size to produce estimates for 

the area), and replaced by new areas “rotated on” (i.e., sample design ensured adequate sample size to 

produce estimates for the area). Starting in 2007, the base NIS-Child geographic strata included 56 areas 

(5 sub-state awardee urban areas, the District of Columbia, and 50 state or “rest of state” areas). In 

addition, starting in 2007, state immunization programs could choose additional city/county areas of 

interest to have adequate sample size to produce estimates for the area, using their Section 317 funds. In 

2019, the NIS-Child included five additional areas: Dallas County, TX; El Paso County, TX; the 

U.S. Virgin Islands; Guam; and Puerto Rico. As noted throughout this report, some procedures 
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differed for territories when compared to the rest of the United States, including the creation of separate 

survey weight variables for analysis that is to include territories.

The 61 = 56 + 2 + 3 areas are called estimation areas. Table 10 in Section 8 shows a cross-walk of 

estimation areas between years. To maintain consistency with past NIS-Child public-use data files, or 

PUFs, variable names and descriptions continue to use the term “IAP” to designate areas included as 

strata, which was the term used prior to 2008. The changing geographic strata over time will not cause a 

problem with bias in estimation of state and national coverage levels since the geographic strata are 

nested within state.

Data for the U.S. Virgin Islands and Guam are not included in the 2019 public-use data file to protect 

respondent confidentiality, as the sampling fractions were larger in these small-population areas. 

Interested researchers can access data for the U.S. Virgin Islands and Guam by submitting a proposal and 

working through the Research Data Center. The link and guidelines for developing a proposal are located 

at the following URL: www.cdc.gov/rdc. 

For the 2019 NIS-Child, telephone interviewing began on January 3, 2019 and ended on February 

6, 2020. Provider data collection extended from January 2019 through March 2020. A total sample, 

including the U.S. territory samples, of approximately 26 million telephone numbers yielded 

household interviews for 34,452 children, 16,849 of whom had adequate provider data (i.e., 

provider-reported vaccination data adequate to determine whether the child was up-to-date with 

respect to the recommended immunization schedule). The 2019 NIS-Child public-use data file

(which includes data from Puerto Rico but does not include data for the U.S. Virgin Islands and 

Guam) contains data for 33,799 children with completed household interviews, and more extensive 

data (e.g. provider-reported vaccinations and facility data) for 16,562 children with adequate 

provider data (including 289 unvaccinated children). Data were collected in the U.S. Virgin Islands 
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and Guam in 2019, but children in these areas are not included on the public-use data file in order 

to protect confidentiality. 

In 2012, to reduce the length of the household interview, decrease respondent burden, and potentially 

improve response rates, the NIS-Child household questionnaire was modified. Official NIS-Child

vaccination coverage estimates are based on the provider-reported vaccination histories for each child. 

Among children with data received from vaccination providers identified in the household interview, it 

must be determined which children have “adequate provider data,” that is, which children have provider 

data adequate to determine whether the child is up to date with respect to the recommended immunization 

schedule. Beginning in 2012, questions that were previously used to define adequate provider data were 

no longer available. With this questionnaire change, it was no longer possible to use the same definition 

of adequate provider data as was used prior to 2012, and so beginning in 2012 all children with any 

provider-reported vaccination data are considered to have adequate provider data. See the user’s guide for 

the 2014 NIS-Child public-use data file (NCHS 2015) for more detail about this change and its impact. 

The weights included in this public-use data file afford the data analyst the capability of conducting 

several different types of analyses, depending on interests and aims. One can choose to analyze all 

children with completed household interviews or only the subset of children for whom the providerreported data are adequate. Also, one can choose to include or exclude teens who reside in U.S. territories

in the analysis. Previous NIS-Child public-use data files have also provided analysts with these 

capabilities. Section 6 of this user’s guide provides information about the creation of the weight variables 

included in the 2019 NIS-Child public-use data file, and Section 8 provides guidance for their use. 

Vaccination coverage estimates are available on the ChildVaxView website, 

https://www.cdc.gov/vaccines/imz-managers/coverage/childvaxview/index.html. An article summarizing 

key findings from the NIS-Child data, as published in the Morbidity and Mortality Weekly Report 

(MMWR), will also be available on this website. Historically, these estimates have been based on NIS-
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Child data collected in a single survey year (e.g., the 2019 NIS-Child) and applied to the population of 

children age 19-35 months; beginning in 2018, the estimates on ChildVaxView and in the MMWR are 

based on data pooled over 2-3 survey years (e.g., the 2017-2019 NIS-Child surveys) and apply to the 

population of children in particular annual birth cohorts (e.g., children born in 2016 or 2017). This cohortbased approach to estimating vaccination coverage has been described by Singleton et al., (2019) and 

Singleton (2019). The 2019 NIS-Child public-use file and this user’s guide focus on a single survey 

year (2019) and the production of vaccination coverage estimates for children age 19-35 months in 

2019. Therefore, estimates produced from this public-use file will differ from birth cohort-based 

estimates on ChildVaxView and in the MMWR (Hill et al. 2020). Researchers interested in 

analyzing the NIS-Child data by birth year can request access to the required data via the Research 

Data Center (http://www.cdc.gov/rdc).

The accompanying codebook (NCIRD 2020) documents the contents of the 2019 NIS-Child public-use 

data file. For reference, Appendix E (Alphabetical Listing of Variables in the NIS-Child Public-Use Data 

Files) provides a full list of variables in the 2019 and previous NIS-Child public-use data files. 

Additional information on the NIS-Child is available at: http://www.cdc.gov/vaccines/imzmanagers/nis/about.html. 

For additional information on the NIS-Child public-use data file, please contact the NCIRD Information 

Dissemination Staff:

Information Dissemination Staff, NCIRD 

1600 Clifton Road 

Atlanta, GA 30333 

E-mail: cdcinfo@cdc.gov

Internet: http://www.cdc.gov/vaccines/imz-managers/nis/index.html
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2. Sample Design

The NIS-Child uses two phases of data collection to obtain vaccination information for a large national 

probability sample of young children: an RDD telephone survey designed to identify households with 

children 19 through 35 months of age, followed by the Provider Record Check, a mailed survey to 

children’s vaccination providers. This section summarizes these two phases of data collection. Other 

descriptions of the sample design are given by Ezzati-Rice et al. (1995), Zell et al. (2000), Smith et al. 

(2001a, 2005), and Wolter et al. (2017a). 

2.1. The NIS-Child RDD Telephone Survey 

The NIS-Child RDD telephone survey phase uses independent, quarterly samples of cell-phone numbers.

Sampling frames were provided by Marketing Systems Group (MSG). Cell-phone numbers were sampled 

within estimation areas in each quarter of 2019. Table F.1 (in Appendix F) lists the estimation areas for 

the 2019 NIS-Child by state and shows the estimated number of children living in each state and 

estimation area in 2019. 

Prior to 2011, the NIS-Child used a single-frame landline RDD sample design. In 2011, a cell-phone 

sample was added, and from 2011-2017, the NIS-Child used a dual-frame landline and cell-phone RDD 

sample design. In 2018, the landline sample was dropped, and the NIS-Child now uses a single-frame 

cell-phone RDD sample design. 

The target sample size of completed telephone interviews in each estimation area is designed to achieve 

an approximately equal coefficient of variation of 7.5% for an estimator of vaccination coverage derived 

from provider-reported vaccination histories, given a true coverage parameter of 50%. Cell-phone sample 

sizes were chosen to meet the target coefficient of variation of 7.5%. 

The 2019 NIS-Child sample design included a modification to increase the efficiency of data 

collection. Immunization Information Systems (IIS) are state or local confidential, computerized, 
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population-based data systems that collect and consolidate vaccination doses administered to 

individuals by participating vaccination providers. In 12 of the geographic estimation areas,

1

 a twophase RDD sample of cell-phone numbers was selected, with the second-phase sample stratified by 

the status of the telephone number in the corresponding IIS: 

• Stratum 1: Phone number associated with a 19-35 month old child in the IIS

• Stratum 2: Phone number associated with a 13-17 year old adolescent in the IIS (but not 

with a 19-35 month old child in the IIS)

• Stratum 3: Phone number associated with a 6-18 month or 3-12 year old child in the IIS

(but not with a 19-35 month old child or 13-17 year old adolescent in the IIS)

• Stratum 4: Phone number not associated with a 6 month to 17 year old child in the IIS

In the second phase of sampling, phone numbers falling into Stratum 1 were oversampled. The 

method was designed to maximize the NIS-Child effective sample size, given fixed cost of data 

collection, within each of the 12 geographic estimation areas.

In 2019, including the U.S. territory samples, 48.9% of children with a completed household 

interview were determined to have adequate provider data. Excluding territories, this proportion 

was 49.4%. These rates are lower than were achieved in 2018 (54.1%) due to the COVID-19 

pandemic, which forced an early end to Provider Record Check data collection operations – data 

collection ceased on March 19, 2020 whereas it usually extends into April. The percentage of 

children with adequate provider data varies among the non-territory estimation areas (from 38.6% 

 

1 The geographic areas were Arkansas, Florida, Kansas, Louisiana, Maryland, Michigan, Missouri, New York – City 

of New York, Nevada, New Mexico, Vermont, and Washington. Not all of these areas utilized the IIS-NIS 

integration design in every quarter of 2019. Arkansas, New York – City of New York, Vermont, and Washington

used the integration design only in Quarters 2, 3, and 4; Michigan and Missouri used the integration design only in 

Quarter 4. 
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in New Jersey to 62.9% in Kansas). Among the U.S. territories, the percentages were 29.8% in 

Puerto Rico, 43.0% in the U.S. Virgin Islands, and 44.6% in Guam. The phrase “adequate provider 

data” originally meant that sufficient vaccination history information was obtained from the provider(s) to 

determine whether the child is up-to-date with respect to the recommended vaccination schedule. Starting 

with the 2002 NIS-Child public-use data file, the definition of children with adequate provider data was 

expanded to include unvaccinated children. These are children for whom either (1) the respondent 

reported during the household interview that the child had received no vaccinations and has no providers, 

or (2) the respondent reported during the household interview that the child had received no vaccinations 

but has one or more providers, and those providers all reported administering no vaccinations. An NCHS 

Series 2 Report on the statistical methodology of the NIS-Child (Smith et al. 2005) includes details of 

how unvaccinated children are included in the estimates of vaccine coverage. This report can be viewed at

http://www.cdc.gov/nchs/data/series/sr_02/sr02_138.pdf. This modification to the NIS-Child produces 

only small changes in vaccination coverage for estimation areas and states, because the number of 

unvaccinated children in the sample is very small (only 296 in 2019, including the U.S. territory 

samples). As described in the introduction, the definition of adequate provider data was modified in 2012 

to include all children with provider-reported vaccination data, plus unvaccinated children. 

The design and implementation of the NIS-Child cell-phone sample involves three procedures. First, 

statistical models predict the number of sample telephone numbers needed in each estimation area to meet 

the target precision requirements. Second, the sample for an estimation area is divided into random subsamples called replicates. By releasing replicates as needed, it is possible to spread the interviews for each 

sampling area evenly across the entire calendar quarter. Third, an automated procedure eliminates 

numbers on the NIS do-not-call list from the sample before the interviewers dial them. 

In 2014 and 2015, an automated process was implemented to remove cell-phone numbers flagged as 

having no recent activity and that were therefore very likely to be non-working cell phones. In 2016, a 

different automated process found to be more efficient in removing non-working cell-phone numbers was 
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used. Following a July 2016 Federal Communications Commission (FCC) declaratory ruling (FCC 16-72, 

CG Docket No. 02-278) stating that the federal government and contractors working on behalf of the 

federal government are not subject to the restrictions on cell-phone dialing in the Telephone Consumer 

Protection Act of 1991 (TCPA, 47 U.S.C. 227), the NIS transitioned from manual dialing of cell phones 

to auto-dialing cell phones in November 2016. After this transition, the automated process to remove nonworking cell-phone numbers was no longer cost effective, and beginning in 2017 this process was no 

longer used in the cell-phone sample. 

2.2. The NIS-Child Provider Record Check

At the end of the household interview, consent to contact the child’s vaccination provider(s) is requested 

from the parent/guardian. When oral consent is obtained, each provider is mailed an immunization history 

questionnaire. This mail survey portion of the NIS-Child is the Provider Record Check (PRC). 

The instructions ask vaccination providers to mail or fax the immunization history questionnaire back 

upon completion. Two weeks after the initial mailing, a telephone call is made to providers who have still 

not responded, to remind and encourage them to complete the form and either mail or fax the information 

back. In some instances, provider-reported vaccination histories are completed over the telephone. The 

data from the questionnaires are edited, entered, cleaned, and merged with the household information 

from the RDD survey to produce a child-level record. 

2.3. Summary of Data Collection

Table 1 presents selected operational results of NIS-Child data collection for calendar year 2019. To 

facilitate comparisons with prior years, the numbers in Table 1 and discussed in this section exclude the 

U.S. territory samples. Children aged 19 through 35 months during 2019 data collection were born 

between January 2016 and May 2018. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 11

The total cell-phone sample consisted of 24,829,559 telephone numbers. Of those, 102,952 were 

eliminated before release to the telephone centers as numbers on the NIS do-not-call list. The 

remaining 24,726,607 numbers were sent to the telephone centers to be dialed, and 1,602,885 active 

personal cell-phone numbers (APCNs) were identified, as shown in Row F. Among the identified 

APCNs, 1,352,882 (84.4%) were successfully screened. Of these, 44,834 (3.3%) were deemed eligible 

for the NIS-Child interview. Among the identified eligible respondents, 31,859 (71.1%) completed 

the interview.

A standard approach for measuring response rates in telephone surveys has been defined by the Council 

of American Survey Research Organizations (CASRO 1982). The CASRO response rate is equivalent to 

“RR3” of AAPOR Standard Definitions (AAPOR 2016). In 2019, the CASRO response rate (Table 1, 

Row J) was 21.1%. The CASRO response rate equals the product of the resolution rate (35.2%, 

Row E), the screening completion rate (84.4%, Row G), and the interview completion rate among 

eligible households (71.1%, Row I). The resolution rate is the percentage of the total telephone numbers 

selected that are classifiable as non-working, non-residential, or residential. The screening completion 

rate is the percentage of known households that are successfully screened for the presence of age-eligible 

children. The interview completion rate is the percentage of households with one or more age-eligible 

children who complete the household interview.

Row K of Table 1 shows that household interviews were completed on behalf of 33,137 age-eligible 

children. Rows L through O give results for the Provider Record Check phase. Specifically, Row L 

gives the rate of obtaining oral consent from household respondents to contact their children’s 

vaccination providers – 62.7% in 2019. 

The number of immunization history questionnaires mailed to vaccination providers exceeds the number 

of completed interviews for children with consent because some children have more than one vaccination 

provider. Of the questionnaires mailed to providers of children, 21,594 (83.9%, Row N) were 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 12

returned. Among the children with completed household interviews, 16,365 (49.4%, Row O) had 

adequate vaccination histories based on provider reporting (16,078) or were determined to be 

unvaccinated (287). The other 50.6% of children lacked adequate provider data for a variety of 

reasons, such as the parent did not give consent to contact the child’s provider(s), the provider(s) 

did not have records for the child, or the provider(s) did not report the vaccination history. 

In 2019, data from the Health Insurance Module (HIM) were collected. Among the 33,137 children 

with completed household interviews, 21,441 (64.7%, Row P) completed the HIM. 

For each estimation area and each state, Table F.1 (see Appendix F) shows the number of children with 

completed household interviews and the number of children with adequate provider data. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 13

Table 1: Selected Operational Results of Q1/2019-Q4/2019 NIS-Child Data Collection 

(Excluding U.S. Territories) 

Row Key Indicator 

 

Cell-Phone Sample Formula

Number Percent 

Household Phase

A Total Selected Telephone Numbers in Released Replicates 24,829,559 -- -- 

B Phone Numbers Resolved before Computer-Assisted Telephone Interviewing 102,952 0.4% B/A 

C Total Phone Numbers Released to Telephone Centers 24,726,607 -- A-B 

D Advance Letters Mailed 0 0.0% D/C

E Resolved Phone Numbers1 – Resolution Rate 8,748,039 35.2% E/A

F Households Identified – APCN Rate2 1,602,885 18.3% F/E

G Households Successfully Screened3 – Screener Completion Rate 1,352,882 84.4% G/F

H Eligible Households – Eligibility Rate4 44,834 3.3% H/G

I Households with Completed Household Interviews – Interview Completion Rate 31,859 71.1% I/H 

J CASRO5 Response Rate6 -- 21.1% E*G*I

K Age-Eligible Children with Completed Household Interviews7 33,137 -- -- 

Provider Phase

L Children with Consent to Contact Vaccination Providers 20,779 62.7% L/K

M Immunization History Questionnaires Mailed to Providers 25,723 -- -- 

N Immunization History Questionnaires Returned from Providers 21,594 83.9% N/M

O Children with Adequate Provider Data

16,365 

(includes 287 

unvaccinated 

children)

49.4% O/K

Modules

P Age-Eligible Children with Completed Household Interview and Completed 

Health Insurance Module 21,441 64.7% P/K

1 Includes phone numbers resolved before CATI (Row B).

2 Active personal cell-phone number (APCN) rate.

3 The household screener screens for non-minor-only cell phone households with age-eligible children.

4 Of the screened households, the proportion that were non-minor-only cell-phone households with age-eligible children.

5 CASRO, Council of American Survey Research Organizations.

6 The response rate is the number of households with a completed household interview divided by the estimated number of eligible 

households in the sample. The number of eligible households in the sample was estimated using the CASRO assumptions; these 

assumptions are that the rate of households among the unresolved telephone numbers is the same as the observed rate of households among 

the resolved telephone numbers, and the rate of eligible households among unscreened households is the same as the observed rate of 

eligible households among screened households. Under these assumptions, the CASRO response rate is equal to the product of the 

resolution rate, the screener completion rate, and the interview completion rate. 

7 Rows K-P reflect the removal of children with a completed interview that were later found to be ineligible based on post-survey data 

cleaning operations.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 14

2.4. Informed Consent, Security, and Confidentiality of Information

The introduction to the telephone survey and oral consent assure the respondent of the confidentiality of 

his/her responses and the voluntary nature of the survey. Informed consent is obtained from the person in 

the household most knowledgeable about the eligible child’s vaccination history (generally the parent or 

guardian of the child). Informed consent to contact the child’s vaccination provider(s) is obtained at the 

end of the interview. 

Information in the NIS-Child is collected and processed under high security. To ensure privacy of the 

respondents and confidentiality of sensitive information, standards have been established for release of 

data from this survey. All CDC staff and contractor staff involved with the NIS-Child sign confidentiality 

agreements and follow instructions to prevent disclosure.

All information in the NIS-Child is collected under strict confidentiality and can be used only for research 

[Section 308(d) of the Public Health Service Act, 42 U.S. Code 242m(d) and the Privacy Act of 1974 (5 

U.S. Code 552a)]. Prior to public release, the contents of the public-use data file go through extensive 

review by the NCIRD Disclosure Review Board to protect participant privacy as well as data

confidentiality.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 15

3. Content of NIS-Child Questionnaires 

This section describes the questionnaires used in the 2019 NIS-Child telephone interview of households 

and in the NIS-Child Provider Record Check. 

3.1. Content of the Household Questionnaire 

The computer-assisted telephone interview (CATI) questionnaire used in the RDD phase of NIS-Child

data collection consists of two parts: a screener to identify households with children aged 19 through 35 

months and an interview portion. The questionnaire is modeled on the Immunization Supplement to the 

National Health Interview Survey (NHIS) (NCHS 1999). The NIS-Child CATI questionnaire has been 

translated into Spanish, and LanguageLine Solutions® (formerly part of AT&T) is used for real-time 

translation into many other languages (Wall et al. 1995). Table 2 summarizes the content of each section 

of the NIS-Child household interview. The CATI questionnaire is available at

http://www.cdc.gov/vaccines/imz-managers/nis/datasets.html.

In the screener, the purpose of the survey is explained to the respondent, and the household is screened to 

determine whether it contains any children aged 19 through 35 months (any child who was or would be 

aged 19 through 35 months during the calendar quarter is eligible). If the household has an eligible child, 

the respondent is asked whether he/she is the most knowledgeable person for the child’s vaccination 

history. If the respondent indicates that another person in the household is more knowledgeable, the 

interviewer asks to speak to him/her at that time. If that person is unavailable to be interviewed, the 

interview proceeds to Section MR, the name of the most knowledgeable person is recorded, and a 

“callback” is scheduled for a later date. Prior to screening for age-eligibility, the household is screened to 

ensure that the cell-phone is used by an adult (i.e., to ensure it is not a minor-only cell phone). If the 

household has more than one age-eligible child, data are collected for each eligible child. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 16

Table 2: Content of the Household Interview, National Immunization Survey - Child, 2019 

Questionnaire 

Section Content of Section

Section S Screening questions to determine NIS-Child eligibility

Section MR Most-knowledgeable-respondent callback questions

Section B Ever vaccinated and influenza vaccination questions

Section C Demographic and socioeconomic questions

Section D Provider information and request for consent to contact the eligible child’s 

vaccination provider(s)

Section E Health Insurance Module (HIM)

Prior to Q1/2012, the person being interviewed was asked during the screener section whether he/she had 

a written record (shot card) of the child’s vaccination history and whether it was easily accessible. If a 

shot card was available, the respondent was asked to provide information directly from it in Section A 

(which asked respondents with shot cards about the shots on the card). However, beginning in Q1/2012, 

Section A and most of Section B were eliminated from the regular questionnaire, and therefore all 

interviews proceeded directly to a reduced form of Section B, which asks the respondent to recall 

information about the child’s influenza vaccinations. In 2015 and 2016, Section A was reinstated for 

Guam respondents, but was discontinued for all respondents beginning in 2017. 

Section C obtains information that includes relationship of respondent to the child, race and Hispanic 

origin of the child, household income, educational attainment of the mother, and other information on the 

socioeconomic characteristics of the household and its eligible children. 

In Section D of the NIS-Child household interview, identifying information (such as name, address, and 

telephone number) for the child’s vaccination provider(s) is requested, as well as the full names of the 

child(ren) and the respondent, so that NIS-Child personnel can contact the provider(s) and identify the 

child(ren) whose immunization information the NIS-Child is requesting. After this information is 

obtained, consent to contact the child’s vaccination provider(s) is requested. When oral consent and 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 17

sufficient identifying information are obtained, the immunization history questionnaire is mailed to the 

child’s vaccination provider(s). 

Beginning in 2006, a Health Insurance Module (HIM) was administered upon completion of Section D to 

collect data regarding the types of medical insurance coverage the child has had since birth. If a 

respondent provided consent to contact medical providers and completed Section D, he/she flowed 

directly into the HIM. If, however, consent or any other critical provider question was refused, the call 

was terminated; only upon callback on which consent was granted or a second refusal given within 

Section D was the respondent asked the HIM. 

Two changes were made to the NIS-Child questionnaire for 2019: 

• Year references for income questions were updated to refer to the previous year, 2018. That 

is, the question text at CFAMINC, C12_DONT_KNOW, and C12_REFUSED was updated 

to ask about 2018 income rather than 2017 income. 

• A new response option (98-Not in Guam) was added for the question C19VIL which asks 

respondents sampled in Guam for their current village of residence. Respondents sampled 

from the Guam cell-phone sampling frame who reported not currently living in Guam were 

asked for their current city, county, state, and zip code, and were asked questions about 

their health insurance coverage based on their current state of residence.

3.2. Content of the Immunization History Questionnaire (IHQ) 

The immunization history questionnaire mailed to the vaccination providers is designed to be simple and 

brief, to minimize provider burden and encourage survey participation. The structure and content of this 

form were initially derived from the National Immunization Provider Record Check Study 

(NHIS/NIPRCS), which collected and reconciled vaccination data from the providers of respondents to 

the Immunization Supplement to the National Health Interview Survey. The immunization history 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 18

questionnaire consists of two double-sided pages. Page 1 includes space for a label that gives the child’s 

name, date of birth, and sex. The remainder of page 1 contains questions about the facility and 

vaccination provider. Page 2 gives instructions for filling out the shot grid, which appears on page 3. Page 

4 thanks the vaccination provider for providing the information, and lists websites and telephone numbers 

that can be used to obtain more information about the NIS-Child and the NCIRD. The Immunization 

History Questionnaire is available at http://www.cdc.gov/vaccines/imz-managers/nis/datasets.html. 

Since 2015, a Spanish-translated version of the NIS-Child IHQ has been used for Puerto Rico. This 

version differs slightly from the IHQ used for other estimation areas in that it does not contain the 

response options for Indian Health Service and Pharmacy at Question 5b.

No changes were made to the NIS-Child IHQ for 2019. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 19

4. Data Preparation and Processing Procedures

The household and provider data collection in the NIS-Child incorporate extensive data preparation and 

processing procedures. During the household interview, the CATI system supports reconciliation of 

critical errors as interviewers enter the data. After completion of interviewing for a quarter, post-CATI 

editing and data cleaning produce a final interview data file. The editing of the provider data begins with 

a manual review of returned immunization history questionnaires, data entry of the questionnaires, and 

cleaning of the provider data file. After the provider data are merged with the household interview data 

and responses from multiple providers for a child are consolidated into a child-level data record, the 

editing continues. A quality assurance check is performed based on the name, sex, and date-of-birth 

information from all sources to ensure that the provider completed the questionnaire for the correct child 

and to confirm age-eligibility. Editing of the provider-reported vaccination dates then attempts to resolve 

specific types of discrepancies in the provider data. The end product is an analytic file containing 

household and provider data for use in estimating vaccination coverage.

4.1. Data Preparation

The editing and cleaning of NIS-Child data involve several steps. First, the CATI system enables 

interviewers to reconcile potential errors while the respondent is on the telephone. Further cleaning and 

editing take place in a post-CATI clean-up stage, involving an extensive review of data values, cross 

tabulations, and the recoding of verbatim responses for race and ethnicity. The next step involves the 

creation of numerous composite variables. Provider data are cleaned in a separate step. After these steps 

have been completed, imputations are performed for item non-response on selected variables, and weights 

are calculated. The procedures and rules of the National Health Interview Survey serve as the standard in 

all stages of data editing and cleaning (http://www.cdc.gov/nchs/nhis.htm).
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 20

4.1.1. Editing in the CATI System 

The CATI software checks consistency across data elements and does not allow interviewers to enter 

invalid values. Catching potential errors early increases the efficiency of post-survey data cleaning and 

processing. 

To prevent an overly complicated CATI system, out-of-range and inconsistent responses produce a 

warning screen, allowing the interviewer to correct real time errors. This allows the interviewer to 

reconcile errors while respondent is on the telephone. CATI warning screens focus on items critical to the 

survey, such as those that determine a child’s eligibility (e.g., date of birth). 

A CATI system cannot simultaneously incorporate every possible type of error check and maximize 

system performance. To reconcile this trade-off, post-CATI edits are used to resolve problems that do not 

require access to the respondent, as well as unanticipated logic problems that appear in the data.

4.1.2. Post-CATI Edits

The post-CATI editing process produces final, cleaned data files for each quarter. The steps in this 

process, implemented after all data collection activities for a quarter are completed, are described below.

Initial Post-CATI Edits and File Creation

After completion of interviewing each quarter, the raw data are extracted from the CATI data system and 

used to create two files: the sample file and the interview data file. The sample file contains one record for 

each sample telephone number and summary information for telephone numbers and households. The 

interview data file contains one record for each eligible sampled child and all data reported for the child 

during the household survey. 

Following creation of these two files, a preliminary analysis of each file identifies out-of-range values and 

extraneous codes. The first check verifies the eligibility status of children. Once the required corrections 

are verified, invalid values are replaced with either an appropriate data value or a missing value code. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 21

Frequency Review

After the pre-programmed edits are run, frequency distributions of all variables in each file are produced 

and reviewed. Each variable’s range of values is examined for any invalid values or unusual distributions. 

If blank values exist for a variable, they are checked to see whether they are allowable and whether they 

occur in excessive numbers. Any problems are investigated and corrected as appropriate. 

File Crosschecks

Crosscheck programs ensure that cases exist across files in a consistent manner. Specifically, checks 

ensure that each case in the interview data file is also present in the sample file and that each case in the 

sample file was released to the telephone center. Checks also ensure that no duplicate households exist in 

the sample file and no duplicate children exist in the interview data file. 

When all checks have been performed, the final quarterly interview data file is created. Programmers and 

statisticians then create composite variables constructed from basic variables for each child. Sampling 

weights (described in Section 6 of this Guide) are added to each record.

4.1.3. Editing of Provider Data 

Six to eight weeks after the close of household data collection for a quarter, the majority of the

immunization history questionnaires have been collected from providers. The data from the hard-copy 

questionnaires are entered and independently re-entered to provide 100% verification. The provider data 

file is cleaned, in a similar fashion to the household data file, for out-of-range values and consistency. A 

computer program back-codes “other shot” verbatim responses into the proper vaccine category (e.g., 

Engerix B counts as Hep B, and Tetramune counts as DTP and Hib). These translations come from a file 

that contains all such verbatim responses ever encountered in the NIS-Child. Also, the provider data file is 

checked for duplicate records, and exact duplicates are removed. If the provider data contain a date of 

birth, sex, or name for the child that differs from the household interview for that child, the questionnaire 

is re-examined to see whether it may have been filled out for the incorrect child. Provider data that appear 

to have been filled out for the wrong child are removed from the provider database. When a child has data 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 22

from multiple providers, decision rules are applied to produce the most complete picture of the child’s 

vaccination history. 

Once these data have been cleaned, they are combined with the household data file. Information from up 

to five providers can be added to a child’s record. If more than one provider reported vaccination data for 

the child, the data from the multiple provider reports are combined into a single history for the child, 

called the “synthesized provider-reported vaccination history.” The determination of whether the child is 

up-to-date for recommended vaccines and vaccine series is based on the child’s synthesized providerreported vaccination history.

Many variables in the household data file are checked against or verified with the provider data file. For 

example, a child’s date of birth as recorded by the provider is checked against the date of birth as given 

by the household, to verify that the provider was reporting for that specific child and to form a “best” date 

of birth for the child. All children with at least one provider-reported vaccination are considered to have 

adequate provider data.

4.2. Limitations of Data Editing Procedures

Although data editing procedures were used for the NIS-Child, the data user should be aware that some 

inconsistent data might remain in the public-use data file. The variables that indicate whether a child is 

up-to-date on each vaccine or series (on which the estimates of vaccination coverage are based) are 

derived from provider-reported data, and the NIS-Child does not re-contact households or providers to 

attempt to reconcile potential discrepancies in provider-reported vaccination dates or to resolve date-ofbirth reporting errors. However, beginning with the 1999 NIS-Child, the provider-reported data are 

manually reviewed and edited to correct specific reporting errors. The National Immunization Survey: 

Guide to Quality Control Procedures (CDC 2002) discusses the change in editing procedures in more 

detail. Some children with adequate provider data may have incomplete vaccination histories. These 

incomplete histories arise from three primary sources: 1) the household does not identify all vaccination 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 23

providers, 2) some but not all providers respond with vaccination data, and 3) all identified providers 

respond with vaccination data but fail to list all the vaccinations in the child’s medical record. Even with 

these limitations, the NIS-Child overall is a rich source of data for assessment of up-to-date status and 

age-appropriate vaccination. Also, the NIS-Child is the only source to provide comparable providerreported vaccination data across states and local areas in the United States. 

4.3. Variable-Naming Conventions

The names of variables follow a systematic pattern as much as possible. The codebook for the public-use 

data file groups the variables into ten broad categories according to the source of the data (household or 

provider) and the content of the variable (NCIRD 2020). See Section 7 of this report for detailed 

information on the contents of the public-use data file.

4.4. Missing Value Codes

Missing value codes for each variable can be found in the codebook (NCIRD 2020). For household 

variables, the missing value codes usually are 77 for DON’T KNOW and 99 for REFUSED. Some 

household variables may also contain blanks, if the question was not asked. The variables developed from 

the immunization history questionnaire generally do not have specific missing value codes.

4.5. Imputation for Item Non-Response

The NIS-Child uses imputation primarily to replace missing values in the socioeconomic and 

demographic variables used in weighting. Missing values of these variables are imputed for all children 

with a completed household interview – i.e., all children appearing on the public-use data file. Missing 

values of health insurance variables are also imputed for children with adequate provider data. A 

sequential hot-deck method is used to assign imputed values (Ford 1983). Class variables are used to 

separate respondents into cells. Donors and recipients must agree on the categories of the class variables, 

which include the estimation area. Within the categories of the class variables, respondents are sorted by 

variables related to the variable to be imputed. The last case with an observed value is used as the donor 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 24

for up to four recipients. The “Notes” line for each variable in the codebook (NCIRD 2020) identifies 

variables that contain imputed values. These variables include the sex, Hispanic origin, race, health 

insurance status, and first-born status of the child; the education level, age group, marital status, and 

mobility status of the mother; and the income-to-poverty ratio of the household. 

The count of vaccinations for a specific vaccine is based on the number of unique vaccination dates

reported by the child’s provider(s). In filling out the immunization history questionnaire a provider may 

not know the date of the first dose of hepatitis B, which is typically given at birth. The provider does, 

however, have the option of checking the “Given at Birth” box for the first dose of hepatitis B. If it was 

checked “yes” and the date of the birth dose of hepatitis B was not reported, a program assigns the date of 

the birth dose for this vaccine. A value is imputed from the distribution of provider-reported dates for the 

birth dose of hepatitis B. The birth dose for this imputation is defined as being given in the first 7 days of 

life--between the date of birth (i.e., 0 days) and the date of birth plus 6 days. This imputation procedure 

was first implemented for Quarter 1, 2000 – Quarter 4, 2000. For 2019 (excluding U.S. territories), a 

total of 48 children had the date of the birth dose of hepatitis B assigned using the above procedure 

(see HEP_FLAG).

Table 3 shows the distribution of age in days at the birth dose of hepatitis B for children in 2019 with a 

provider-reported birth dose. A similar table is included in the 2000-2018 data user’s guides. For 1997, 

1998, and 1999, Section 5 of the data user’s guide provides information on the distribution of age in days 

for the birth dose of hepatitis B vaccine and gives guidance on imputing age in days at birth dose for 

children with a missing date, but for whom the provider checked the box indicating that a dose was 

administered at birth (see HEP_BRTH). 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 25

Table 3: Distribution of Age (in Days) at the Birth Dose of Hepatitis B Vaccine, National 

Immunization Survey - Child, 2019 

Age in Days at 

Birth Dose

Unweighted Percentage

Of Birth Doses*

0 61.3 

1 26.2 

2 7.2 

3 2.1 

4 1.4 

5 1.0 

6+ 0.8 

*Excludes U.S. territories. 

4.6. Vaccine-Specific Recoding of Verbatim Responses

On the IHQ, providers can list vaccinations in the “other” section of the IHQ shot grid. After data 

collection, they are reclassified into the listed categories, if possible, using a vaccination recoding table.

This table is reviewed by NCIRD personnel to ensure the shots are recoded into the appropriate category 

or categories (for combination shots).

4.7. Composite Variables

A number of composite variables (constructed from basic variables) are created and included in the NISChild public-use data file. Composite variables assist users and data analysts by eliminating duplication of 

effort and making NIS-Child data easier to use. 

Since the initial years of NIS-Child data collection, the household composite variables have included upto-date status on individual vaccinations, race of child, household income, and up-to-date status on 

several vaccination series. Many of these household composite variables are included in the NIS-Child

public-use data file. See Section 7 of this report for information on the key variables.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 26

In Quarter 3, 1999, the NIS-Child race questions (see questions C3, C9 and C10 in the household 

questionnaire) were expanded to include Alaska Native, Native Hawaiian, and Pacific Islander, 

implementing the revised Office of Management and Budget (OMB) standards for classification of race 

and ethnicity (https://www.whitehouse.gov/wp-content/uploads/2017/11/Revisions-to-the-Standards-forthe-Classification-of-Federal-Data-on-Race-and-Ethnicity-October30-1997.pdf). The composite race 

variables in the 2002 through present NIS-Child public-use data files, however, contain only three 

categories: white alone; black alone; and all other races alone/multiple races. (The variable RACE_K 

classifies each child into one of these three categories, while the variable RACEETHK includes a separate 

“Hispanic” category.) The “all other races alone” category includes Asian, American Indian or Alaska 

Native, Native Hawaiian or Pacific Islander, and other races. If more than one race was selected during 

administration of the child race questions, the child is classified as multiple races. Because of small 

sample sizes and risk of disclosure within estimation areas, the 2002 through present NIS-Child publicuse data files do not contain any variables with separate multiple-race categories. Rather, the children 

with multiple races are included in the “all other races” category. Table 4 shows some characteristics of 

the current race/ethnicity categories.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 27

Table 4: Weighted Distribution of Children by Race/Ethnicity and Corresponding Combined Vaccine Series* (4:3:1:3*:3:1:4), 

Pneumococcal, and Varicella Vaccination Coverage Estimates, National Immunization Survey - Child, 2019 

Race/Ethnicity 

Classification

Weighted Distribution 

of Children aged 19-35 

Months in U.S.

Estimate (%)

Weighted Percentage 

4:3:1:3*:3:1:4 UTD 

Estimate (%)

(Standard Error (%))

Weighted Percentage 4+ 

Pneumococcal

Estimate (%)

(Standard Error (%))

Weighted Percentage 1+ 

Varicella at 12+ Months

Estimate (%)

(Standard Error (%))

Hispanic 27.3 70.0 (2.0) 80.4 (1.8) 90.2 (1.4) 

Non-Hispanic white only 47.2 75.9 (0.9) 85.6 (0.7) 91.8 (0.6) 

Non-Hispanic black only 12.7 66.1 (2.2) 76.4 (2.1) 90.6 (1.2) 

Non-Hispanic American 

Indian or Alaska Native only 0.9 68.2 (8.5) 73.9 (7.7) 87.5 (4.9) 

Non-Hispanic Asian only 4.4 76.4 (2.8) 86.0 (2.0) 93.2 (1.5) 

Non-Hispanic Native 

Hawaiian or Pacific Islander 

only 

0.2 59.2 (8.5) 66.6 (8.0) 78.1 (6.8) 

Multiple races 7.4 72.4 (3.1) 80.0 (3.1) 88.0 (3.1) 

Non-Hispanic white/black 3.0 73.6 (3.6) 81.2 (3.1) 91.2 (2.0) 

Non-Hispanic white/ 

American Indian or Alaska 

Native

0.9 78.4 (3.8) 82.8 (3.4) 89.0 (2.7) 

Non-Hispanic white/Asian 1.9 71.9 (8.1) 80.0 (8.7) 86.7 (9.0) 

Non-Hispanic other 

combination 1.6 67.7 (8.0) 76.3 (7.9) 83.2 (7.9) 

Note: UTD = up-to-date. Weighted by PROVWT_C. Children with an unknown Hispanic origin and/or race were imputed by a hot-deck method. This table excludes U.S. 

territories. 

* 4+ diphtheria and tetanus toxoids and acellular pertussis vaccine adsorbed, diphtheria and tetanus toxoids and pertussis vaccine, or diphtheria and tetanus toxoids vaccine 

adsorbed (DTaP/DTP/DT); 3+ poliovirus vaccine; 1+ measles-containing vaccine (MCV); full series Haemophilus influenzae type b conjugate vaccine (Hib), i.e., 3 or 4 doses 

depending on type of vaccine received; 3+ hepatitis B vaccine (Hep B); 1+ varicella at or after 12 months of age; and 4+ pneumococcal conjugate vaccine (PCV). 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 28

4.8. Subsets of the NIS-Child Data

The NIS-Child public-use data file contains data for all eligible children who have a completed household 

interview. An interview is considered complete if the respondent completed Section C of the 

questionnaire. As explained in Section 6 of this guide, each child with a completed household interview is 

assigned a weight (RDDWT_C for the United States, excluding U.S. territories; RDDWT_C_TERR for 

the United States, including U.S. territories) for use in estimation.

The NIS-Child uses the synthesized provider-reported vaccination histories to form the estimates of 

vaccination coverage because the provider data are considered more accurate than household-reported 

data. Thus, the most important subset of the data consists of children with adequate provider data. For 

these children, one or more providers returned an immunization history questionnaire that included 

vaccination data. Unvaccinated children are also considered to have adequate provider data. As discussed 

in Section 7 below, the PDAT variable identifies the children with adequate provider data (PDAT=1). 

These children have a separate weight (PROVWT_C for the United States, excluding U.S. territories; 

PROVWT_C_TERR for the United States, including U.S. territories), which should be used to form 

estimates of vaccination coverage (see Section 6).

4.9. Confidentiality and Disclosure Avoidance

To prevent identification of participants in the NIS-Child and the resulting disclosure of information, 

certain items from the questionnaires are not included in the public-use data file. In addition, some of the 

released variables either are top- or bottom-coded, or have their categories collapsed. Variable labels 

indicate which variables have been re-coded in these ways.

5. Quality Control and Quality Assurance Procedures

A major contributor to NIS-Child data quality is its sample management system, which in 2019 managed 

over 240 estimation area by quarter samples and used a number of performance measures to track their 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 29

progress toward completion. Important aspects of the quality assurance program for the RDD component 

of the NIS-Child included interviewer monitoring; on-line provider look-ups in a database system

integrated with the CATI system, including names, addresses, and telephone numbers of vaccination 

providers; and automated range-edits and consistency checks. These and other quality assurance 

procedures contributed to a reduction in total data collection cost by minimizing interviewer labor and 

overall burden to respondents. Khare et al. (2000), Khare et al. (2001), and the National Immunization 

Survey: Guide to Quality Control Procedures (CDC 2002) describe quality assurance procedures. 

The Provider Record Check component used quality control measures at four junctions: prior to mailing 

packets to providers; during the telephone prompting effort; during the editing of returned questionnaires; 

and during and after their data entry. The final quality assurance activities are implemented during postprocessing of the returned questionnaires or vaccination records. All returned questionnaires were

examined to identify and correct any obvious errors prior to data entry and then key-entered with 100% 

verification. The keying error rate is estimated, by way of a second verification process, to be less than 

1%. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 30

6. Sampling Weights

Each of the two phases of data collection results in a separate sampling weight for each child that has data 

at that phase. The RDD-phase sampling weights permit analyses of data for children with completed 

household interviews. Each child with adequate provider data (the subset on which official estimates of 

vaccination coverage are based) has a provider-phase sampling weight. The RDD-phase sampling weight

variable for producing estimates for children with completed household interviews in the United States 

excluding U.S. territories is called RDDWT_C; the RDD-phase weight variable for producing estimates 

for the United States including U.S. territories is called RDDWT_C_TERR. The provider-phase 

sampling weight variable for producing estimates for children with adequate provider data in the United 

States excluding U.S. territories is called PROVWT_C; the provider-phase weight variable for producing 

estimates for the United States including U.S. territories is called PROVWT_C_TERR. See Section 8 of 

this user’s guide for more information about the weights included in the data file and the proper way to 

use them.

As discussed below, revisions in weighting methodology were made on various occasions and the names 

of the weight variables were also changed to keep track of the revisions. The RDD-phase sampling 

weights were called HY_WGT in 1995-2001, RDD_WT in 2002, WGT_RDD in 2003- 2004, RDDWT in 

2005-2008, RDDWT/RDDWTVI in 2009-2010, RDDWT_LL/RDDWTVI_LL/RDDWT_D in 2011, 

RDDWT_D/RDDWTVI_D in 2012, RDDWT_D/RDDWTVIGU_D in 2013, 

RDDWT_D/RDDWT_D_TERR in 2014-2016, RDDWT_D in 2017, RDDWT_C in 2018, and 

RDDWT_C/RDDWT_C_TERR in 2019. The provider-phase sampling weights were called W0 in 1995-

2001, WT in 2002, WGT in 2003- 2004, PROVWT in 2005-2008, PROVWT/PROVWTVI in 2009-2010, 

PROVWT_LL/PROVWTVI_LL/PROVWT_D in 2011, PROVWT_D/PROVWTVI_D in 2012, 

PROVWT_D/PROVWTVIGU_D in 2013, PROVWT_D/PROVWT_D_TERR in 2014-2016, 

PROVWT_D in 2017, PROVWT_C in 2018, and PROVWT_C/PROVWT_C_TERR in 2019. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 31

A sampling weight may be interpreted as the approximate number of children in the target population that 

a child in the sample represents. Thus, for example, the sum of the sampling weights of children with 

adequate provider data who are up-to-date (on a particular vaccine or series of vaccines) yields an 

estimate of the total number of children in the target population who are up-to-date. Dividing this sum by 

the total of the sampling weights for all children with adequate provider data gives an estimate of the 

corresponding vaccination coverage rate. 

This section describes how these weights are developed and adjusted so as to achieve an accurate 

representation of the target population. The base weights reflect each telephone number’s probability of 

being selected into the sample; the adjustments take into account non-resolution of residential/nonresidential/non-working status of a telephone number, non-response to the screener and household 

interviews, number of cell phones used by parents in the household, raking for differential coverage rates

and non-coverage of households that do not have cell phones, non-response by providers, and a final 

raking adjustment. 

6.1. Base Sampling Weight

In each quarterly NIS-Child sample, each child with a completed household interview receives a base 

sampling weight. The base sampling weight is equal to the inverse of the probability the phone number 

was sampled from the sampling frame for the quarter and estimation area.

6.2. Adjustments for Non-Resolution of Telephone Numbers, Screener 

Non-Response, and Interview Non-Response 

Non-response occurs in population-based surveys when potential respondents refuse to participate, are not 

available at the time of the interview, or could not be reached during the survey period. Thus, the sum of 

the base sampling weights of children with completed household interviews will underestimate the size of 

the target population in the estimation area, because not all sampled households respond to all stages of 

data collection up to the household interview. As a result, the base sampling weights must be adjusted so 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 32

they accurately reflect the number of children in the target population that each sampled child with a 

completed household interview represents. 

Some sampled households with age-eligible children fail to complete the household interview because of 

unit non-response: for some telephone numbers, it is never determined whether or not the number is a 

working residential number despite multiple call attempts; for some households it is never determined 

whether or not the household contains age-eligible children; and some households with age-eligible 

children do not complete the household interview. To compensate for these three types of unit nonresponse, the sampling weights of children with a completed household interview are adjusted to account 

for the estimated number of age-eligible children in households whose telephone numbers are never 

resolved, the estimated number of age-eligible children in households that fail to complete the screening 

interview, and the number of identified age-eligible children for whom the household interview is not 

completed. Each of these adjustments is carried out within each estimation area by forming weighting 

cells based on the Metropolitan Statistical Area (MSA) status of the wire center associated with the cellphone number (MSA/non-MSA). Each cell in each stage of adjustment must have sufficient 

resolved/responding cases (usually 20, but 15 for interview non-response) at that stage of adjustment. 

The cells with a deficient number of responding cases are collapsed into neighboring cells, i.e., both MSA 

categories are collapsed if either of the cells have a deficient number of responding cases. Once the 

adjustment cells are formed, the weights of the unresolved/non-responding records from the previous 

adjustment step are distributed to the weights of the resolved/responding records within each cell. 

6.3. Adjustment for Multiple Cell Phones and Deriving Annual Weights

Once the non-response-adjusted interview weights for households are computed, these weights are 

adjusted for additional cell phones in the household. Because households with multiple cell phones have a 

greater chance of being sampled, each child’s household interview weight is adjusted by dividing it by the 

total number of cell-phones used by parents or guardians (up to a maximum of 3). 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 33

Up to the previous step, the sampling weights are adjusted separately for each quarter, and the weights in 

each quarter pertain to the target population. However, annual vaccination coverage estimates are 

obtained from data for four consecutive quarters, so the weights in each quarterly file are adjusted when 

the data from the four quarters are combined. The adjustment factor is proportional to the number of 

households with completed household interviews in each quarter and estimation area. 

6.4. Calibration 

Next, survey weights are calibrated to population control totals as described below. The control totals 

used for the NIS-Child are derived from current natality data from the National Center for Health 

Statistics (NCHS 2016, 2017). Because the Vital Statistics data give the counts of all live births in the 

United States, regardless of whether the household has any cell phones, the control totals include all 

eligible children. The control total for each raking dimension is derived from the NCHS natality files 

from 2016 and 2017 (children born between July 1, 2016 and November 30, 2017 would have been 

19 through 35 months on June 30, 2019). Use of the natality data to form the required population 

control totals for the NIS-Child has three limitations: 1) the natality file provides a universe of live births 

and therefore does not reflect infant mortality; 2) the natality file does not include children born outside 

the United States who immigrate to this country before reaching ages 19 through 35 months; and 3) the 

natality file records residence at time of birth, and some children may move from one estimation area to 

another by the time they reach 19 through 35 months of age. Adjustments are made to the natality data to 

account for these three factors. For 2019, the combined 2016, 2017, and 2018 one-year American 

Community Survey Public Use Microdata Sample data files were used to make the immigration 

and migration adjustments (U.S. Census Bureau 2017, 2018, 2019). 

Survey weights are adjusted to agree with independent estimates of the population total by telephone 

status. The proportions of 19 through 35 month old children by detailed telephone status (cell-phone-only, 

landline and cell-phone dual user, landline-only, phoneless) within each estimation area were derived 

using a similar small area modeling approach as described in Blumberg et al. (2011). These modeled 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 34

telephone status estimates are applied to the population control total for the estimation area to estimate the 

control totals by detailed telephone status within the estimation area. In each estimation area, children in 

dual landline and cell-phone households are weighted to represent children living in dual landline and 

cell-phone households in the estimation area, and children in cell-phone-only households are weighted to 

represent children in cell-phone-only households in the estimation area. Children in landline-only and 

phoneless households, which are excluded from the cell phone sample, are accounted for in the raking 

step described below.

To reduce sampling variability and improve the precision of estimation, extreme weights are trimmed and 

then recalibrated to control totals. RDD sampling weight values exceeding the median weight plus three

times the interquartile range of the weights within an estimation area are truncated and then recalibrated 

to control totals. This is done by up to five iterations. This weight trimming prevents children with 

unusually large weights from having an unusually large impact on immunization coverage estimates. 

The final step in adjusting the RDD sampling weights is a raking adjustment (Deming 1943) of the 

trimmed, telephone status adjusted weights. The raking procedure uses estimation area-level control totals 

for maternal education categories, maternal race/ethnicity, age group of the child, sex of the child, and 

telephone status. Briefly, raking takes each variable in turn and applies a proportional adjustment to the 

current weights of the children who belong to the same category of the variable. After a number of 

iterations over all the variables, the raked weights have totals that match all the desired control totals. 

Raking makes it possible to incorporate additional variables into the weighting and to use more detailed 

categories for those variables. Wolter et al. (2017a) gives the details of various aspects of the NIS-Child

estimation procedures.

The sampling weights after all the foregoing adjustments constitute the “RDD sampling weights” 

(RDDWT_C for the United States excluding territories; RDDWT_C_TERR for the United States 

including territories).
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 35

6.5. Adjustment for Provider Non-Response

Among the 33,137 children with a completed household interview (excluding U.S. territories), 

16,365 (49.4%) had adequate provider data. Starting with the 2002 NIS-Child public-use data file, the

definition of children with adequate provider data includes unvaccinated children. These are children for 

whom the respondent reported during the household interview that the child had received no vaccinations 

and has no providers, or for whom one or more providers were reported but those providers reported 

administering no vaccinations. Among the 16,365 children with adequate provider data, 287 were 

unvaccinated children. Failure to obtain adequate provider data for the remaining 50.6% was attributable 

to: 

● parent or guardian not identifying any providers or not giving consent to contact the child’s 

vaccination provider(s) (36.8%);

● consent to contact vaccination providers obtained but no providers returned the immunization 

history questionnaire (9.8%); and

● one or more providers returned the immunization history questionnaire, but no providers reported 

any vaccination data, despite the parent or guardian indicating that the child has received 

vaccinations (4.0%).

The 16,772 children for whom a household interview was completed but adequate provider data were not 

obtained are classified as “partial non-responders” because they have only a partial response to the NISChild as a whole.

Empirical results suggest that children with adequate provider data have characteristics believed to be 

associated with a greater likelihood of being up-to-date, compared with children who had missing 

provider data. Specifically, children with adequate provider data are more likely to live in households that 

have higher total family income, have a white mother, and live outside a principal city of a Metropolitan 

Statistical Area. Also, a child with missing provider data is less likely to live in the state where the mother 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 36

lived when the child was born. These factors indicate a potential lack of continuity of health care, and are 

associated with lower vaccination coverage (Coronado et al. 2000). If no adjustment is made to the RDD 

sampling weights to account for these differences, estimated vaccination coverage rates may be biased. 

To reduce potential bias in estimators of vaccination coverage attributable to partial non-response, a 

weighting-class adjustment is used in each estimation area (Brick and Kalton 1996). This adjustment 

involves three steps. In the first step, sampled children are classified according to the quintile of their 

estimated probabilities of having adequate provider data. In the statistical literature these probabilities are 

called response propensities (Rosenbaum and Rubin 1983, 1984; Rosenbaum 1987). Children who have 

similar response propensities will also be similar with respect to variables that are strongly associated 

with the probability of having adequate provider data. In this important respect, children in each class are 

comparable. Because of this comparability, any sub-sample of children in a class may represent all 

children in the class. Therefore, the weighting-class adjustment uses the children with adequate provider 

data to represent all children in the class. An NCHS Series 2 Report on the statistical methodology of the 

NIS-Child (Smith et al. 2005) includes details of the methodology for forming weighting classes based on 

propensity scores. This report can be viewed at http://www.cdc.gov/nchs/data/series/sr_02/sr02_138.pdf. 

In the second step of this weighting-class adjustment, within each class an adjustment factor redistributes 

the RDD sample weights of the children with missing provider data to the weights of the children who 

have adequate provider data. These adjusted sampling weights of children with adequate provider data are 

initial non-response-adjusted provider-phase weights. 

Within an estimation area, the sums of non-response adjusted weights of children with adequate provider 

data for the various levels of important socio-demographic variables (such as race/ethnicity) may not be 

equal to corresponding population totals. To reduce bias attributable to these differences, raking was used 

in the third step to adjust the non-response adjusted weights to match estimation area control totals. 

Control totals for these variables were estimated using the weighted totals from the sample of children 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 37

with completed household interviews. Smith et al. (2001b, 2005) describe the development of this 

approach in more detail. Similar to the RDD weighting, the extreme weights exceeding the median weight 

plus three times the interquartile range of the weights within an estimation area are truncated and then 

recalibrated to control totals. These raked weights of children with adequate provider data are called 

“final provider-phase weights” (PROVWT_C for the United States excluding territories and 

PROVWT_C_TERR for the United States including territories). Because of the comparability of 

children within each weighting class, any estimate that uses data only from the children with adequate 

provider data along with their provider-phase sampling weights will have less bias attributable to 

differences between children with adequate provider data and children with missing provider data.

Appendix B summarizes the distribution of the sampling weights (RDDWT_C, PROVWT_C, 

RDDWT_C_TERR, and PROVWT_C_TERR) in each estimation area.

NIS-Child public-use data files for 1995 to 2001 do not include sampling weights that account for the 

effect of unvaccinated children. An assessment of the effect of accounting for unvaccinated children for 

the period 1995 to 2003 was made. Weights were calculated for each year with and without unvaccinated 

children and the vaccination coverage estimates compared. Details of this assessment and the results are 

available in the user’s guide for the 2004 NIS-Child public-use data file. At the national level, accounting 

for unvaccinated children had very little effect on the estimates of 4:3:1:3 vaccination coverage. Within 

estimation areas also, the two coverage estimates differed little. The largest difference (in either direction) 

was most often around 2 percentage points. Differences of that magnitude are small relative to the 

standard errors of the estimates. Although accounting for unvaccinated children has a small effect on 

estimates of vaccination coverage, data users who use the pre-2002 public-use data files to examine 

estimation area-level trends over time are advised to interpret the results with appropriate caution. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 38

6.6. Sampling Weights for Territories

The NIS-Child weighting process was followed as closely as possible for U.S. territories. Due to 

differences in the availability of external data sources for U.S. territories, slight changes were necessary to 

accurately estimate vaccination coverage for these areas. These differences are stated below.

In step 6.2, each of the non-response adjustments for U.S. territories was done at the estimation area level. 

That is, no weighting cells were formed for U.S. territories. 

For the U.S. Virgin Islands, 2017 natality data were not available, so 2016 data (NCHS 2016) were 

used to create the control totals for the U.S. Virgin Islands. Similar to the weights for the United 

States excluding territories, the final step in adjusting the RDD sampling weights for U.S. territories is a 

raking adjustment. For Guam and Puerto Rico, a different set of race/ethnicity categories were used for 

post-stratification and raking adjustments than were used in other areas. The three Guam race/ethnicity 

categories were: Chamorro/Guamanian, Other Asian/Pacific Islander, and All Other. The two Puerto Rico 

race/ethnicity categories were: White and All Other.

After sampling weights were calculated for all children, they were stored in the variables 

RDDWT_C_TERR and PROVWT_C_TERR. These weight variables permit one to conduct analysis 

of all estimation areas, including U.S. territories. The weight variables RDDWT_C and PROVWT_C

are equal to RDDWT_C_TERR and PROVWT_C_TERR for all children except those in U.S. 

territories, for whom the value of these weight variables is blank or missing. RDDWT_C and 

PROVWT_C permit one to conduct analysis of all estimation areas, excluding U.S. territories.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 39

7. Contents of the Public-Use Data File

The NIS-Child public-use data file contains a record for each eligible child for whom Section C of the 

household interview was completed, along with household-reported information about the child and the 

child’s mother. For children with Immunization History Questionnaires (IHQs) returned by one or more 

providers, the file also contains provider characteristic variables, as well as variables based on the child’s 

synthesized provider-reported vaccination history: the age of the child at each vaccination, the number of 

each type of vaccination received, and indicators of whether the child is up-to-date with respect to various 

recommended vaccines and vaccine series.

The public-use data file consists of ten sections, the contents of which are described below in detail. For 

additional information, users are encouraged to consult the codebook (NCIRD 2020). The codebook is 

divided into the ten sections described below and contains variable names, labels, and response 

frequencies (for categorical variables). For select variables, the codebook also gives additional 

information about the variable in the “Notes” field.

Table 5 lists key NIS-Child variables commonly used in analyses. A full list of variables appearing on the 

2004-2019 NIS-Child public-use data files appears in Appendix E, along with the reason for the addition, 

subtraction, or modification of the variables in 2005-2019. Information on changes made between 1995-

2004 can be found in the Alphabetical Listing of Variables that are Not Available in All Public-Use Data 

Files, National Immunization Survey, 1995-2004. 

http://www.cdc.gov/nchs/data/nis/pufvariables1995to2004.pdf 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 40

Table 5: NIS-Child Variables Commonly Used in Analyses or for Published Estimates

Variable Categories

ID Variables -

SEQNUMC – unique child ID variable -

SEQNUMHH – unique household ID variable -

Geographic Variables -

ESTIAP19 – estimation area number

(ITRUEIAP used through 2004; ESTIAP in 2005; 

ESTIAP06 in 2006; ESTIAP07 in 2007; ESTIAP08 in 

2008; ESTIAP09 in 2009; ESTIAP10 in 2010; 

ESTIAP11 in 2011; ESTIAP12 in 2012; ESTIAP13 in 

2013; ESTIAP14 in 2014; ESTIAP15 in 2015; 

ESTIAP16 in 2016; ESTIAP17 in 2017; ESTIAP18 in 

2018; ESTIAP19 in 2019) 

-

STATE – state FIPS code -

CEN_REG – census region

Northeast

Midwest

South

West

Child Demographic Variables

AGEGRP – age category of child

19-23 months

24-29 months

30-35 months

RACEETHK – race/ethnicity of child

(introduced in 2002; RACEKIDR used in 1995-2001)

Hispanic

White alone, non-Hispanic

Black alone, non-Hispanic

All other races alone and multiple races, 

non-Hispanic

SEX – sex of child Male

Female

FRSTBRN – firstborn status of the child No

Yes

Mother Demographic Variables

EDUC1 – education of the mother

<12 years

12 years

>12 years, not a college graduate

College graduate

MARITAL2 – marital status of mother

(Living with partner response option added to 

questionnaire in 2015)

Currently married

Never married, widowed, divorced, separated, 

deceased, or living with partner

M_AGEGRP2 – age group of mother 

(introduced in 2016; M_AGEGRP used through 2015) 

<=29 years

30 years or older

Poverty Variables

INCPOV1 – poverty status

(introduced in 2005; INCPOV1R used through 2004)

At or above poverty level, income > $75,000

At or above poverty level, income <= $75,000

Below poverty level

Not determined

INCPORAR – income-to-poverty ratio

(introduced in 2005; INCPORAT used through 2004)

-

INCPORAR_I – imputed income-to-poverty ratio

(introduced in 2016) 

-

WIC Variables -
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 41

Variable Categories

CWIC_01 – child ever participated in WIC program

Yes

No 

Never heard of WIC

Don’t know

Refused

Missing

CWIC_02 – child currently participating in WIC program

Yes

No

Don’t know

Refused

Missing

Breastfeeding Variables

CBF_01 – child ever fed breast milk

Yes

No

Don’t know

Missing

BF_ENDR06 – length of time in days child was fed 

breast milk -

BF_EXCLR06 – length of time in days child was 

exclusively fed breast milk or formula (introduced in 

2006)

-

BF_FORMR08 – age in days when child was first fed 

formula (introduced in 2008; BF_FORMR06 used in 

2006 and 2007)

-

Chicken Pox Variables

HAD_CPOX – did child ever have chicken pox 

(introduced in 2005; I_HADCPX used through 2004)

Yes

No

Don’t know

Refused

Missing

AGECPOXR – age in months when child had chicken 

pox (introduced in 2005; IAGECPXR used through 2004)

0-6 months

7-12 months

13-18 months

19-24 months

25-30 months

31 months or older

Missing

Presence of Provider Data Variables

PDAT – adequate provider data indicator Yes

No

Number of Provider-Reported Doses of Vaccine 

Variables

P_NUMDTP – total number of DTaP/DTP/DT doses -

P_NUMPOL – total number of polio doses -

P_NUMMMR – total number of MCV doses -

P_NUMHIB – total number of Hib doses -

P_NUMHEP – total number of hepatitis B doses -

P_NUMVRC – total number of varicella doses -

P_NUMPCV – total number of pneumococcal doses -

P_NUMFLU – total number of seasonal influenza doses -

P_NUMHEA – total number of hepatitis A doses -

P_NUMROT – total number of rotavirus doses -

Provider Characteristic Variables
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 42

Variable Categories

PROV_FAC – provider facility type

All public facilities

All hospital facilities

All private facilities

All military/other facilities

Mixed types

Unknown

VFC_ORDER – do child’s providers order vaccines for 

children from state/local health department? (introduced 

in 2006)

All providers

Some but not all providers

No providers

Unknown

REGISTRY – provider(s) reported child’s vaccination(s)

to state or community immunization registry

All providers

Some but not all providers

No providers

Unknown

Insurance Status Variables

INS_STAT2_I – child’s current health insurance 

coverage status (introduced in 2017, INS_STAT_I used 

in 2016) 

Private insurance only

Any Medicaid

Other insurance (CHIP, IHS, military, or some other 

form of insurance, alone or in combination with

private insurance)

Uninsured

INS_BREAK_I – child’s insurance history since birth

(introduced in 2016)

Currently insured but uninsured since birth

Currently insured and never uninsured since birth

Currently uninsured but insured since birth

Currently uninsured and never insured since birth

Before describing the sections of the public-use data file below, we first summarize the differences 

between the 2018 and 2019 NIS-Child public-use data files:

• A new 2019 estimation area variable (ESTIAP19) has been added and the 2018 estimation 

area variable (ESTIAP18) has been dropped. Note that three new estimation areas have 

been added for 2019: Dallas County, TX is identified by ESTIAP19=52; El Paso County, TX 

is identified by ESTIAP19=53; and Puerto Rico is identified by ESTIAP19=106. Although 

data were collected for the U.S. Virgin Islands and Guam in 2019, children in these areas 

were not included on the public-use data file in order to protect confidentiality.

• The weight variables RDDWT_C_TERR and PROVWT_C_TERR have been added to the 

public-use data file for producing estimates for the United States including Puerto Rico. 

• Due to a Hib vaccine shortage in 2007-2009, vaccine series up-to-date indicator variables 

that exclude Hib (PU431_31, PU431_314) were previously created so that trends in vaccine 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 43

series coverage rates could be examined without the Hib component. It has been determined 

that these variables are no longer necessary, and thus have been dropped from the 2019 

NIS-Child public-use data file.

7.1. Section 1: ID, Weight, and Flag Variables

SEQNUMHH and SEQNUMC are the unique household and child identifiers, respectively. PDAT 

indicates which children are considered to have adequate provider data. As described in Section 6 of this 

report, RDDWT_C/RDDWT_C_TERR and PROVWT_C/PROVWT_C_TERR are the final 

household- and provider-phase weights, respectively. PROVWT_C/PROVWT_C_TERR should be 

used when analyzing the provider-reported data, i.e., the variables in Sections 7, 8, and 9 of the NIS-Child

public-use data file.

7.2. Section 2: Household-Reported Vaccination and Chickenpox

Information

Section 2 of the public-use data file contains variables derived from the information collected in Section 

B of the household questionnaire. In particular, it contains variables indicating whether the respondent 

reported that the child has had chicken pox disease (HAD_CPOX) and the child’s age in months at 

chicken pox disease (AGECPOXR).

7.3. Section 3: Demographic, Socio-Economic, and Other 

Household/Child Information

Section 3 of the NIS-Child public-use data file consists of information collected during the household 

screening interview and Section C of the household main interview. To protect confidentiality, many of 

these variables have been collapsed, top-coded, or bottom-coded from the original, fully-detailed 

versions; the variable labels (see the public-use date file codebook) indicate which variables have been 

collapsed or recoded. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 44

AGEGRP is the age of the child in months in three categories (19-23 months, 24-29 months, 30-35 

months), based on the child’s best date of birth and the eligibility date. SEX gives the sex of the child, 

and FRSTBRN indicates whether the child is the first born, with missing values of these variables 

imputed. The language in which the interview was conducted is stored in variable LANGUAGE, and

C5R gives the relationship of the respondent to the child.

The breastfeeding variables include whether the child was ever fed breast milk (CBF_01), length of time 

in days the child was fed breast milk (BF_ENDR06), the age in days when the child was first fed formula 

(BF_FORMR08), and the length of time in days the child was exclusively fed breast milk or formula 

(BF_EXCLR06). Two types of inconsistencies arise in the breastfeeding data: 1) duration of any 

breastfeeding can exceed age of the child, and 2) age when the child was first fed formula can exceed the 

age of the child. BFENDFL06 is set equal to 1 when BF_ENDR06 exceeds the age of the child (with a 

buffer), and BFFORMFL06 is set equal to 1 when BF_FORMR08 exceeds the age of the child (with a 

buffer). Appendix C provides details on how the flags were created. Data users are cautioned to review 

Appendix C before analyzing any of the breastfeeding variables.

The WIC variables include whether the child ever participated in the WIC program (CWIC_01) and 

whether the child is currently participating (CWIC_02).

C1R and CHILDNM give the number of people and children, respectively, in the household. The child’s

Hispanic origin indicator, race with three categories, and race/ethnicity with four categories are presented 

in variables I_HISP_K, RACE_K, and RACEETHK, respectively; for each of these variables, missing 

values have been imputed. The age, education level, and marital status of the mother of the child are 

stored in variables M_AGEGRP2, EDUC1, and MARITAL2 (married vs. not married), with missing 

values imputed. 

The categorized total combined income for the child’s family is given by INCQ298A. INCPOV1 gives 

the family’s poverty status (at or above poverty, income > $75,000; at or above poverty, income <= 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 45

$75,000; below poverty; unknown), and INCPORAR gives the ratio of the family’s income to the 

poverty level. INCPORAR_I gives the same ratio after missing values of family income have been 

imputed. Household tenure is given by RENT_OWN. 

The number of landline telephone numbers in the household, the number of working cell phones 

household members have available for personal use, and the number of these cell phones that are usually 

used by parents or guardians are given by NUM_PHONE, NUM_CELLS_HH, and 

NUM_CELLS_PARENTS, respectively.

Variable CEN_REG gives the census region of the respondent’s current residence, and MOBIL_I 

indicates whether the mother’s current state of residence is the same as her state of residence at the time 

of the child’s birth. 

7.4. Section 4: Geographic Variables

Variables ESTIAP19 and STATE give the 2019 estimation area and state of residence, respectively, for 

each child. EST_GRANT indicates which of the 50 states, District of Columbia, and 5 local areas that 

receive federal Section 317 immunization awards (Bexar County, TX; City of Chicago, IL; City of 

Houston, TX; New York City, NY; Philadelphia County, PA) the child resides in.

7.5. Section 5: Number of Providers Identified and Consent Variables

Variable D7 indicates whether the respondent gave consent to contact the child’s providers. If D7=1, then 

consent was granted; if D7=2 then consent was explicitly denied; and if D7 is missing, consent was not 

granted because the respondent broke off the interview before being explicitly asked for consent. 

Variable D6R gives the number of providers identified by the respondent. Note that sometimes 

respondents report erroneous provider counts and sometimes report the same provider more than one 

time, and D6R does not reflect cleaning or de-duplication of the initially-reported provider count.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 46

7.6. Section 6: Number of Responding Providers Variables

Variable N_PRVR indicates the number of providers returning IHQs with vaccination information for the 

child. That is, N_PRVR is the number of IHQs that were returned for the child that contain information 

on the IHQ shot grid. 

7.7. Section 7: Characteristics of Providers Variables

The variables in this section of the public-use data file summarize the information collected in IHQ 

questions 5b, 6, and 7 across the child’s providers who returned IHQs containing vaccination (i.e., shot 

grid) data. 

PROV_FAC indicates the facility type of the child’s vaccination providers based on responses to IHQ 

question 5b. If all of the child’s providers that returned IHQs containing shot grid data (see Section 6 

variable N_PRVR) reported the facility type to be:

● a public health department-operated clinic, community health center, or rural health clinic, then 

PROV_FAC=1 (all public facilities);

● a hospital-based clinic, then PROV_FAC=2 (all hospital facilities);

● a private practice, then PROV_FAC=3 (all private facilities); 

● a military health care facility, WIC clinic, school-based health center, pharmacy, or other type of 

facility, then PROV_FAC=4 (all military/WIC/school/pharmacy or other facilities).

If the responses of providers that returned IHQs containing shot grid data fell into more than one of the 

above bulleted categories, PROV_FAC=5 (mixed); otherwise, if at least one of the child’s providers 

returned an IHQ containing shot grid data, PROV_FAC=6 (unknown). If none of the child’s providers 

returned an IHQ containing shot grid data, PROV_FAC is set to missing.

The Vaccines For Children (VFC) program is a federally-funded program that provides vaccines at no 

cost to children who might not otherwise be vaccinated because of inability to pay 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 47

(http://www.cdc.gov/vaccines/programs/vfc/index.html). CDC buys vaccines at a discount and distributes 

them to awardees—i.e., state health departments and certain local and territorial public health agencies—

which in turn distribute them at no charge to those private physicians’ offices and public health clinics 

registered as VFC providers. VFC_ORDER, based on responses to IHQ question 6, indicates whether the 

child’s vaccination providers order vaccines from a state or local health department to administer to 

children. If all of the child’s providers that returned IHQs containing shot grid data (see Section 6 variable 

N_PRVR) reported that they order vaccines from a state or local health department to administer to 

children, then VFC_ORDER=1 (all providers); if at least one of the child’s providers that returned an 

IHQ containing shot grid data reported that the practice orders vaccines from a state or local health 

department to administer to children and the child’s other providers that returned IHQs containing shot 

grid data reported either that they did not order such vaccines or that they did not know whether or not 

they did, then VFC_ORDER=2 (some but possibly or definitely not all providers); if all of the child’s

providers that returned IHQs containing shot grid data reported that they do not order vaccines from a 

state or local health department to administer to children, then VFC_ORDER=3 (no providers); if none of 

the conditions for VFC_ORDER=1, 2, or 3 were met but at least one of the child’s providers returned an 

IHQ containing shot grid data, VFC_ORDER=4 (unknown). If none of the child’s providers returned an 

IHQ containing shot grid data, VFC_ORDER is set to missing. Note that having a provider that orders 

VFC vaccines does not imply that the child is VFC-entitled; providers enrolled in the VFC program could 

also vaccinate children who are not VFC-entitled. 

REGISTRY is based on responses to IHQ question 7 and indicates whether the child’s vaccination 

providers reported the child’s vaccinations to a local or state immunization registry (also known as an 

Immunization Information System, or IIS). If all of the child’s providers that returned IHQs containing 

shot grid data (see Section 6 variable N_PRVR) indicated that they reported to a registry, then 

REGISTRY=1 (all providers); if at least one of the child’s providers that returned an IHQ containing shot 

grid data indicated that the practice reported to a registry and the child’s other providers that returned 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 48

IHQs containing shot grid data indicated that they did not report to a registry, that they did not know 

whether or not they reported to a registry, or that the question is not applicable, then REGISTRY=2 (some 

but possibly or definitely not all providers); if all of the child’s providers that returned IHQs containing 

shot grid data indicated that they did not report to a registry or that the question is not applicable, then 

REGISTRY=3 (no providers); if none of the conditions for REGISTRY=1, 2, or 3 were met but at least 

one of the child’s providers returned an IHQ containing shot grid data, REGISTRY=4 (unknown). If none 

of the child’s providers returned an IHQ containing shot grid data, REGISTRY is set to missing. 

7.8. Section 8: Provider-Reported Up-To-Date Vaccination Variables

This section contains vaccination count and up-to-date variables based on the child’s synthesized 

provider-reported vaccination history. To facilitate data processing and to accommodate the large and 

continually growing number of vaccination types covered by the NIS-Child, the provider-reported 

vaccination data are organized around the concept of vaccine categories and vaccine types within vaccine 

category. The vaccine categories correspond to the sections of the IHQ shot grid, and the vaccine types 

correspond to the type boxes on the IHQ shot grid. (For each vaccine category, an “unknown” vaccine 

type is created for vaccinations that are reported without a type box being checked. Also, a few vaccine 

types, such as Measles-Mumps, arise through the backcoding of shots initially reported in the “other” 

section of the IHQ shot grid.) Table 6 shows the vaccine categories and types for the 2019 NIS-Child. 

Note that a single vaccination can fall into more than one vaccine category; for example, an MMRVaricella vaccination is part of both the Measles-containing and Varicella-containing vaccine categories.

(The full list of vaccine type codes can also be found in Appendix H.) 

For each vaccine category, Section 8 of the public-use data file contains a variable typically named 

P_NUMYYY – where “YYY” is the vaccine category abbreviation given in Table 6 – that stores the 

number of vaccinations in that vaccine category in the child’s synthesized provider-reported vaccination 

history. For each vaccine type in Table 6, Section 8 also contains a variable that stores the number of 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 49

vaccinations of that vaccine type in the child’s synthesized provider-reported vaccination history. For 

example, P_NUMDHI is the number of DTaP/HepB/IPV shots in the child’s history. 

This section of the public-use data file also contains up-to-date indicators for a variety of recommended 

vaccines and vaccine series. These variables’ names typically begin with “P_UTD”. Additional variables 

indicate whether the child is up-to-date for various vaccine series. For example, P_UTD431 indicates 

whether the child has received 4 or more DTaP/DTP/DT shots, 3 or more polio shots, and one or more 

measles-containing shots. The variable labels indicate what is needed to be considered up-to-date for each 

variable, and the “Notes” field in the codebook shows the vaccine type codes (see Table 6) being included 

when determining whether the child is up-to-date.

Note that it is possible that the administration of the NIS-Child interview itself prompts some respondents 

to vaccinate their children following the interview; to ensure that the vaccination coverage estimates are 

not artificially boosted because of this, the synthesized vaccination history count and up-to-date variables 

in this section of the public-use data file count only vaccinations received before the date the household 

interview was completed. Note also that because children are eligible for the NIS-Child if they are 19 to 

35 months old on any day of the survey quarter, some children are less than 19 months old or greater than 

35 months old on the date the household interview is completed. For children with interviews conducted 

before they became 19 months old, the Provider Record Check is not conducted until after the child has 

become 19 months old, and all vaccinations given up to age 19 months are counted, including those given 

after the household interview date. For children with interviews conducted after they became 36 months 

old, only vaccinations given through age 35 months are counted. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 50

Table 6: Vaccine Categories and Vaccine Types, National Immunization Survey - Child, 2019 

Vaccine Category 

Abbreviation

Vaccination 

Category Description

Vaccine 

Type Code Vaccine Type Description

DTP DTaP/DTP/DTcontaining vaccine 03 DTaP/DTP/DT-containing, unknown 

type

04 DTaP/DTP/DT

07 DTaP-Hib

08 DTaP-HepB-IPV

D3 DTaP-IPV-Hib

POL or POLIO Polio-containing 

vaccine 08 DTaP-HepB-IPV

20 OPV

21 IPV

22 Polio-containing, unknown type 

D3 DTaP-IPV-Hib

MCV or MMR Measles-containing 

vaccine 30 MMR

31 Measles only

32 Measles-mumps

33 Measles-rubella 

MM Measles-containing, unknown type 

VM MMR-Varicella

HIB Hib-containing 

vaccine 07 DTaP-Hib

43 HepB-Hib

44 Hib-only, unknown type 

D3 DTaP-IPV-Hib

HG Hib-only (GSK) 

HI Hib-containing, unknown type 

HM Hib-only (Merck)

HS Hib-only (Sanofi) 

HY Hib-MenCY

HEPB or HEP Hepatitis B-containing 

vaccine 08 DTaP-HepB-IPV

43 HepB-Hib

60 HepB-only 

HB HepB-containing, unknown type 

VRC Varicella-containing 

vaccine VA Varicella-containing, unknown type 

VM MMR-Varicella

VO Varicella-only 

PCV Pneumococcalcontaining vaccine 70 Conjugate-unknown 

71 Polysaccharide

72 Pneumococcal-containing, unknown 

type

73 Conjugate-7 

74 Conjugate-13 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 51

Vaccine Category 

Abbreviation

Vaccination 

Category Description

Vaccine 

Type Code Vaccine Type Description

HEPA or HEA Hepatitis A-containing 

vaccine HA Hepatitis A

INFLUENZA Seasonal influenza 

vaccine FL Seasonal influenza, unknown type 

FM Seasonal influenza spray

FN Injected seasonal influenza

MP Mumps-only vaccine MP Mumps-only 

MPRB or MPR Mumps-Rubella-only 

vaccine MB Mumps-Rubella-only 

RB Rubella-only vaccine RB Rubella-only 

ROT Rotavirus-containing 

vaccine RG Rotarix® (GSK)

RM RotaTeq® (Merck)

RO Rotavirus, unknown type 

7.8.1. Hib Up-To-Date Variables

A Hib vaccine shortage and interim recommendation to suspend the booster dose for healthy children 

occurred December 2007 to September 2009 (CDC 2010). Furthermore, the NIS-Child has historically 

considered children to be up-to-date for Hib if the child had 3 or more doses of any Hib-containing 

vaccine, but for some Hib vaccine product types, 4 doses are required. Because the NIS-Child has 

historically not distinguished between product types for Hib vaccine, children who received 3 doses of a 

vaccine product that required 4 doses were misclassified as up-to-date for Hib (CDC 2010). 

Because of the Hib vaccine shortage and because of the dependence of the Hib recommendation on 

product type, in 2009 the IHQ was modified to capture the manufacturer of the Hib vaccinations the child 

has received. Beginning with the 2009 NIS-Child public-use data file, new up-to-date variables were 

added to indicate up-to-date status based on Hib recommendation (i.e., the primary series recommended 

during the shortage vs. the full series) and on the Hib manufacturer. 

Table 7 shows the Hib up-to-date variables appearing on the public-use data file beginning in 2009 and 

Table 8 shows the up-to-date series variables that include Hib appearing on the public-use-date file 

beginning in 2009: in addition to the existing vaccine series up-to-date variables based on 3+ Hib of any 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 52

type (PUTD4313, PUT43133, PU431331, PU4313313, PU4313314), variables based on the “routine” 

(i.e., full series) Hib recommendations accounting for manufacturer (4+ Hib of any type or 2 Hib of 

Merck types followed by 1 Hib of any type) were added (P_UTD431H_ROUT_S, 

P_UTD431H3_ROUT_S, P_UTD431H31_ROUT_S, P_UTD431H313_ROUT_S, 

P_UTD431H314_ROUT_S).

Note that for these Hib up-to-date variables that account for the manufacturer, if the manufacturer is 

unknown because the provider failed to check a type box on the IHQ, it has been assumed that the 

manufacturer of the Hib vaccine is not Merck; that is, these variables are based on a “strict” treatment of 

Hib vaccinations of unknown type, erring on the side of classifying the child as not up-to-date.

Table 7: Up-To-Date Variables for Hib, National Immunization Survey - Child, 2009-2019 

Name Description Up-To-Date Criteria

P_UTDHIB Historical UTD flag for Hib. 3+ of any type 

(07,43,44,D3,HG,HI,HM,HS,HY) 

P_UTDHIB_SHORT_S

UTD flag for Hib-shortage (i.e., 

primary series) recommendation, 

accounting for manufacturer. 

Introduced in 2009. 

3+ of any type 

(07,43,44,D3,HG,HI,HM,HS,HY) 

OR

2+ Merck types (HM,43)

P_UTDHIB_ROUT_S

UTD flag for routine (i.e., full series) 

Hib recommendation, accounting for 

manufacturer. Introduced in 2009. 

4+ of any type 

(07,43,44,D3,HG,HI,HM,HS,HY) 

OR

2 Merck types (HM,43) followed by 

1 of any type 

(07,43,44,D3,HG,HI,HM,HS,HY) 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 53

Table 8: Up-To-Date Variables for Vaccine Series Including Hib, National Immunization 

Survey - Child, 2009-2019 

Name Description

PUTD4313 UTD flag for the 4:3:1:3 series using the 3+ any type UTD definition 

for HIB

P_UTD431H_ROUT_S UTD flag for the 4:3:1:3 series using the routine (i.e., full series) UTD 

definition for HIB 

PUT43133 UTD flag for the 4:3:1:3:3 series using the 3+ any type UTD definition 

for HIB

P_UTD431H3_ROUT_S UTD flag for the 4:3:1:3:3 series using the routine (i.e., full series) 

UTD definition for HIB 

PU431331 UTD flag for the 4:3:1:3:3:1 series using the 3+ any type UTD 

definition for HIB 

P_UTD431H31_ROUT_S UTD flag for the 4:3:1:3:3:1 series using the routine (i.e., full series) 

UTD definition for HIB 

PU4313313 UTD flag for the 4:3:1:3:3:1:3 series using the 3+ any type UTD 

definition for HIB 

P_UTD431H313_ROUT_S UTD flag for the 4:3:1:3:3:1:3 series using the routine (i.e., full series) 

UTD definition for HIB

PU4313314 UTD flag for the 4:3:1:3:3:1:4 series using the 3+ any type UTD 

definition for HIB 

P_UTD431H314_ROUT_S UTD flag for the 4:3:1:3:3:1:4 series using the routine (i.e., full series) 

UTD definition for HIB 

7.8.2. Rotavirus Up-To-Date Variables

The up-to-date status for rotavirus vaccine depends on the manufacturer of the vaccines received; the 

requirement is two or more doses of Rotarix® (GSK) or three or more doses of rotavirus vaccine of any 

type. Beginning with the 2009 NIS-Child public-use data file, an up-to-date variable for rotavirus vaccine 

(P_UTDROT_S) was added to indicate up-to-date status, accounting for the manufacturer (3+ rotavirus 

doses of any type or 2+ Rotarix® doses). 

Note that for this rotavirus up-to-date variable, if the manufacturer is unknown because the provider failed 

to check a type box on the IHQ, it has been assumed that the rotavirus vaccine dose is not Rotarix®; that 

is, this variable is based on a “strict” treatment of rotavirus vaccinations of unknown type, erring on the 

side of classifying the child as not up-to-date.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 54

7.9. Section 9: Provider-Reported Age-At-Vaccination Variables

This section contains variables storing the child’s age in days and months at each vaccination in the 

synthesized provider-reported vaccination history, along with the vaccine types of those vaccinations.

For each vaccine category, variables named DYYY1 - DYYY9 and YYY_AGE1 - YYY_AGE9 store the 

age in days and months, respectively, of the child when the vaccination was administered for up to nine 

vaccinations in the child’s synthesized provider-reported vaccination history, where “YYY” is the vaccine 

category abbreviation given in Table 6. For vaccine categories that contain multiple vaccine types, 

variables XYYYTY1 - XYYYTY9 give the corresponding vaccine type code (see Table 6).

Unlike the vaccination count and up-to-date variables in Section 8 of the public-use data file, the variables 

in Section 9 include vaccinations given both before and after the household interview was completed. If 

desired, users can limit the Section 9 variables to only those before the household interview date by 

examining the corresponding Section 8 “P_NUM” variable and limiting the analysis of the Section 9 

variables to only the first n variables, where n is equal to the number of vaccinations in the vaccine 

category before the household interview date as indicated by the corresponding “P_NUM” variable. 

Users of the public-use data file should be aware that the age-at-vaccination variables included in Section 

9 may contain a small number of vaccination ages that are implausible according to the recommended 

immunization schedules (http://www.cdc.gov/vaccines/schedules/hcp/child-adolescent.html). Such ages 

may arise if a medical provider inadvertently records an erroneous vaccination date or if a vaccination 

date is incorrectly transcribed onto an IHQ. The quality control procedures of the NIS-Child address 

implausible ages to every extent possible. Suspicious dates are manually reviewed and corrected if there 

is evidence either from the household interview or from another provider that the date is incorrect. In rare 

cases, however, when there is no further information with which to correct the reported vaccination date, 

the vaccination is treated as having actually occurred and the implausible age at vaccination persists on 

the data file. The data user should consider these issues in deciding how to analyze the NIS-Child data.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 55

7.10. Section 10: Health Insurance Module Variables

The Health Insurance Module (HIM) (Section E) was introduced in 2006 to gather information on the 

health insurance coverage of the child. HIM data were included in the NIS-Child public-use data file for 

the first time in 2007. Prior to 2016, seven variables containing HIM data were included in the NIS-Child

public-use data file:

● INS_1 – “Is child covered by health insurance provided through employer or union?”; 

● INS_2 – “Is child covered by any MEDICAID plan?”;

● INS_3 – “Is child covered by S-CHIP?”;

● INS_3A – “Is child covered by any MEDICAID plan or S-CHIP?”;

● INS_4_5 – “Is the child covered by Indian Health Service, Military Health Care, TRICARE, 

CHAMPUS, or CHAMP-VA?”; 

● INS_6 – “Is child covered by any other health insurance or health care plan?”; and

● INS_11 - “Anytime when child was not covered by health insurance?”

In 2016, these variables were replaced by two health insurance variables, INS_STAT_I and 

INS_BREAK_I, which summarize the child’s health insurance status and history across all of the 

insurance questions listed above, while also incorporating the imputation of missing values and recoding 

of verbatim responses. In 2017, INS_STAT_I was replaced with INS_STAT2_I, which provides a 

different categorization of children with both private and non-private, non-Medicaid insurance.

INS_STAT2_I identifies the child’s current health insurance coverage status. If the child has a form of 

private health insurance and is not covered by any other type of health insurance, he/she is classified as 

(1) Private only. If the child is on any form of Medicaid, alone or in addition to other forms of insurance, 

he/she is classified as (2) Any Medicaid. If the child is not covered by Medicaid but is covered by some 

other type of health insurance (including, but not limited to, CHIP, Indian Health Service, Military Health 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 56

Care, TRICARE, CHAMPUS, or CHAMP-VA), either alone or in combination with private insurance, 

he/she is classified as (3) Other. If the child is not covered by any kind of health insurance, he/she is 

classified as (4) Uninsured. 

INS_BREAK_I describes the child’s coverage history since birth and indicates whether there have been 

any breaks in coverage during this period. A child may be (1) currently insured but uninsured at some 

point since birth, (2) currently insured and never uninsured since birth, (3) currently uninsured but insured 

at some point since birth, or (4) currently uninsured and never insured since birth. 

Both of these variables are only available for children with adequate provider data who live in the nonterritory United States.

8. Analytic and Reporting Guidelines

Data from the NIS-Child public-use data file can be used to produce national, state, and estimation-area 

estimates of vaccination coverage for children age 19-35 months surveyed in 2019 using the 

PROVWT_C weight (PROVWT_C_TERR if U.S. territories are to be included). As noted in Section 1 

of this user’s guide, beginning in 2018 vaccination coverage estimates appearing on ChildVaxView and in 

the MMWR are based on a birth-cohort estimation approach. That is, the estimates are derived from the 

combination of 2 or 3 years of NIS-Child surveys (e.g., 2017-2019), and the estimates apply to the 

population of children born in particular years (e.g., 2016 or 2017). Therefore, estimates produced using 

the 2019 public-use file, which are based on 2019 NIS-Child data alone and apply to the population of 19-

35 month old children, will differ from those appearing on ChildVaxView and in the MMWR. 

Information in the data file can also be used to calculate standard errors of the vaccination coverage 

estimates that reflect the complex sample design of the NIS-Child. The sample is stratified by the 61 

estimation areas. The stratum identifier (STRATUM) and the coded household identifier (SEQNUMHH) 

are key variables for obtaining standard errors for estimation area, state, and national estimates of 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 57

vaccination coverage rates. The estimation area variable ESTIAP19 defines mutually exclusive and 

exhaustive geographic areas, while STRATUM is a combination of the estimation area variable for that 

year and the sampling frame (since 2018, all sample is from the cell-phone sample frame).

Demographic and socioeconomic variables in the file can be used to obtain national vaccination coverage 

estimates for sub-groups of the population. Data users should, however, be aware that estimates for such 

sub-groups at the state or estimation area level will generally have large standard errors because of small 

sample sizes. The CDC standard for precision of sub-group estimates is that the ratio of the standard error 

to the estimate should be less than or equal to 0.3, and each analytic cell should contain at least 30 

respondents. 

8.1. Use of NIS-Child Sampling Weights

The 2019 NIS-Child public-use data file contains two sets of child-level weights. The RDDWT_C

variable gives the household-phase weight for all children 19 through 35 months in the United States

excluding territories (RDDWT_C_TERR if territories are to be included). These weights should be used 

to form estimates from children with completed household interviews. The weights reflect the stratified 

sample design and also have been adjusted for unit non-response, for the number of cell phones in the 

household, for post-stratification to population control totals, and for the exclusion of households without 

cell phones. 

The weight variables that apply to children with adequate provider data are

PROVWT_C/PROVWT_C_TERR. These weights should be used to form estimates of vaccination 

coverage. Each child with adequate provider data (PDAT = 1) has a positive value for 

PROVWT_C/PROVWT_C_TERR. Starting with the 2002 file, the definition of children with adequate 

provider data was expanded to include unvaccinated children (as discussed in Section 2). Table 9 presents 

a summary of the appropriate weights and stratum variables to use for various types of analyses.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 58

The 2019 NIS-Child public-use data file does not contain any provider-level weights. The NIS-Child does 

not sample providers directly; rather, they are included in the survey through the children they vaccinate. 

A user of the file should not attempt provider-level analyses (e.g., estimate the percentage of providers in 

the United States that are private providers), because the NIS-Child sample was not designed for that 

purpose.

Table 9: Summary of Weights and Stratum Variables, National Immunization Survey - Child, 

2019 

Weight Variable Population* Sample 

Frame Strata Stratum Variable 

RDDWT_C United States excluding 

territories

Single-Frame 

Cell-Phone Estimation Area STRATUM

RDDWT_C_TERR United States including 

territories

Single-Frame 

Cell-Phone Estimation Area STRATUM

PROVWT_C 

United States excluding 

territories, children with 

adequate provider data

Single-Frame 

Cell-Phone Estimation Area STRATUM

PROVWT_C_TERR

United States including 

territories, children with 

adequate provider data

Single-Frame 

Cell-Phone Estimation Area STRATUM

*Each weight will contain a missing value for all records that are not included in the population covered by the 

weight.

8.2. Estimation and Analysis

8.2.1. Estimating Vaccination Coverage Rates 

Vaccination coverage rates are ratio estimators, as described in the statistical literature on methods for 

complex sample surveys. Because of the adjustment to the sampling weights for provider-phase nonresponse, statistical analyses require only data from children with adequate provider data (PDAT = 1), 

along with their final provider sampling weights (PROVWT_C/PROVWT_C_TERR). To summarize 

the statistical methodology by which vaccination coverage rates and their standard errors are obtained 

from these data, let Yhij be an indicator, for the jth child with adequate provider data in the ith sampled 

household in the hth stratum of the NIS-Child sampling design, equal to 1 if the child is up-to-date 

according to the provider data and 0 otherwise. Also, let Whij denote the value of 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 59

PROVWT_C/PROVWT_C_TERR for this child. Then, letting and , 

the national estimator of the vaccination coverage rate may be expressed as

where L denotes the number of strata, nh denotes the number of sampled households containing children 

with adequate provider data in the hth stratum, and mhi denotes the number of age-eligible children with 

adequate provider data in the ith household in the hth stratum. 

Letting L instead denote the number of strata in a state, the above formula can also be used to calculate 

vaccination coverage rates for states (regardless of whether the state contains only one or more than one

stratum). 

8.2.2. Estimating Standard Errors of Vaccination Coverage Rates 

The Taylor-series method can be used to estimate the sampling variance of vaccination coverage rates for 

the U.S., the states, and estimation areas. Letting , , and 

yields an estimator of the variance of the estimated vaccination coverage rate, , equal to

(Wolter, 2007). The standard error is the square root of the variance. The estimation of standard errors for 

estimates of vaccination coverage rates in the NIS-Child can be implemented in specialized statistical 

software such as SUDAAN (Research Triangle Institute 2008), SAS (SAS Institute Inc. 2003), R 

(Lumley, 2010), and Stata (Stata Corporation 2009). Appendix D gives several examples of the use of 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 60

SAS, R, and SUDAAN to estimate vaccination coverage rates and their standard errors for estimation 

areas and states. For all procedures, the option of with-replacement sampling of primary sampling units 

within strata is used, because the sampling fractions for households within an estimation area are all quite 

small. For all estimates, the variable STRATUM is used as the stratum variable and the household 

identifier (SEQNUMHH) is used as the primary sampling unit identifier. The data file should be sorted 

first on STRATUM and then on SEQNUMHH before running the programs for SUDAAN and SAS. 

8.3. Combining Multiple Years of NIS-Child Data

8.3.1. Estimation of Multi-Year Means

With release of the 2019 NIS-Child public-use data file, 24 years of public-use NIS-Child data are now 

available. The precision of estimates of vaccination coverage for sub-domains (e.g., by race/ethnicity of 

child) within estimation areas or states can be improved by combining two or more years of NIS-Child

data. Data users should, however, be aware that estimates from combined years of NIS-Child data 

represent an average over two or more years. Although combining several years of NIS-Child data will 

yield a larger sample size for estimation areas and states, the composition of the population in a 

geographic area may change over time, making interpretation of the results difficult. Furthermore, if 

vaccination administration schedules or vaccination coverage changes over time, the estimate of 

vaccination coverage for the combined time period applies to a hypothetical population that existed at the 

middle of the time period, making interpretation of the results even more difficult. Given the use of 

independent RDD samples in the NIS-Child, it is also possible that a child could appear in more than one 

public-use data file.

To estimate a multi-year mean for a given NIS-Child variable, the weights in each participating file

(RDD-phase weights HY_WGT in 1995-2001, RDD_WT in 2002, WGT_RDD in 2003-2004, RDDWT 

in 2005-2010, RDDWT_D/RDDWT_LL in 2011, RDDWT_D/RDDWTVI_D in 2012, 

RDDWT_D/RDDWTVIGU_D in 2013, RDDWT_D/RDDWT_D_TERR in 2014-2016, RDDWT_D in 

2017, RDDWT_C in 2018, and RDDWT_C/RDDWT_C_TERR in 2019; and provider-phase weights W0 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 61

in 1995-2001, WT in 2002, WGT in 2003-2004, PROVWT in 2005-2010, PROVWT_D/PROVWT_LL 

in 2011, PROVWT_D/PROVWTVI_D in 2012, PROVWT_D/PROVWTVIGU_D in 2013, 

PROVWT_D/PROVWT_D_TERR in 2014-2016, PROVWT_D in 2017, PROVWT_C in 2018, and 

PROVWT_C/PROVWT_C_TERR in 2019) should be divided by the number of years being combined. 

For example, if data for 2017, 2018, and 2019 for children in the United States (excluding territories) with 

adequate provider data are to be combined, then the weights that exclude the territories in the three files – 

called PROVWT_D in 2017 and PROVWT_C in 2018 and 2019 – should be divided by 3 to obtain 

revised weights, which should be saved as a new variable, say NEWWT. It is necessary to use NEWWT

in the analysis to obtain correct weighted estimates for children aged 19 through 35 months. Furthermore, 

the child and household ID numbers (SEQNUMC and SEQNUMHH) in the files are unique only within 

a year, not across years. It is important for the user to create revised, unique ID numbers when combining 

data from multiple years. 

The following SAS code can be used: 

YRSEQC = 1 * (YEAR || SEQNUMC);

YRSEQHH = 1 * (YEAR || SEQNUMHH);

YEAR is the 4-digit year variable for the NIS-Child data year (e.g., 2019).

To produce valid estimates of sampling variability and valid confidence intervals for multi-year coverage 

rates and other multi-year means, it is necessary to use specialized software such as SAS or SUDAAN. 

Beginning in 2005, an important new complication was introduced for variance estimation not 

encountered in previous NIS-Child years, because some traditional estimation areas were removed and 

other new areas were defined and introduced to the survey (see Section 2 above for more information 

about rotating estimation areas). The variance strata for 2004 and all prior years are defined by the 

variable ITRUEIAP, while the variance strata for 2005-2019 are defined by the variables ESTIAP for 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 62

2005, ESTIAP06 for 2006, ESTIAP07 for 2007, ESTIAP08 for 2008, ESTIAP09 for 2009, ESTIAP10

for 2010, STRATUM_D/ESTIAP11 for 2011, and STRATUM for 2012-2019, with STRATUM_D and 

STRATUM being a combination of the estimation area variable for that year and the sampling frame 

(landline or cell-phone). The estimation area variables ITRUEIAP, ESTIAP, and ESTIAP06-

ESTIAP19 define mutually exclusive and exhaustive geographic areas. However, they are not exactly the 

same areas. For example, Dallas County, TX, was a separate estimation area in 2005-2012, 2016-

2017, and 2019 but not in 2013-2015 and 2018. Other areas, such as New York City, NY and Rest of 

New York, are estimation areas in all years, including 2005-2019.

To make inferences concerning multi-year means, the user must take two actions. First, he/she must 

define and save a new stratum variable with a common name for all years included in the analysis.

Second, he/she must define a common set of estimation domains that can be supported by each of the files 

included in the multi-year analysis. To take these actions, the user should follow the following seven-step 

procedure (or its equivalent): 

i. Compute and save the new, common variance-stratum variable for each year participating in the 

analysis. The variable should be defined by the equation 

STRATUMV = ITRUEIAP, for children in the 2004 or prior years’ public-use data files

= ESTIAP, for children in the 2005 public-use data file

= ESTIAP06, for children in the 2006 public-use data file

= ESTIAP07, for children in the 2007 public-use data file

= ESTIAP08, for children in the 2008 public-use data file

= ESTIAP09, for children in the 2009 public-use data file

= ESTIAP10, for children in the 2010 public-use data file

= STRATUM_D if using PROVWT_D or

ESTIAP11 if using PROVWT_LL, for children in the 2011 public-use data file

= STRATUM, for children in the 2012-2019 public-use data files
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 63

ii. Compute and save the new, common weight variable, NEWWT, as instructed above for each

year participating in the analysis.

iii. Compute and save the new, unique child and household identification numbers, YRSEQC and 

YRSEQHH, as instructed above for each year participating in the analysis.

iv. Compute and save a variable defining the common estimation domains to be studied for each year

participating in the analysis. For example, one could use the CDIAP (Common Denominator 

Estimation Area) variable set forth in Table 10 or states as geographic domains.

v. Merge the multiple files into one consolidated file in a format compatible with the specialized 

software to be used.

vi. Sort the consolidated file by YEAR, STRATUMV, and YRSEQHH.

vii. Run the specialized software on the consolidated file, computing estimates, variance estimates, 

and confidence intervals. For SUDAAN users, sampling levels or stages may be specified by the 

statement

NEST YEAR STRATUMV YRSEQHH / PSULEV = 3;

the specification of weights by 

WEIGHT NEWWT;

and the specification of estimation domains, for example, by the two statements 

CLASS YEAR CDIAP STATE;

TABLES CDIAP; 

or 

CLASS YEAR CDIAP STATE;

TABLES STATE; 

8.3.2. Estimation of Multi-Year Contrasts

Considerations similar to those for multi-year means arise in the estimation of contrasts between NISChild years. For example, a typical contrast of interest would be the difference between the immunization 

coverage parameters in 2018 and in 2019.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 64

To make inferences concerning a multi-year contrast, the user will need to work with the original weights 

reported on the files and store them in a common variable. One must not divide the original weights by 

the number of years included in the contrast. For example, one may define the new, common weight 

variable as

NEWWT2 = PROVWT_D/PROVWT_LL , if the child is in the 2011 PUF 

= PROVWT_D , if the child is in the 2012-2017 PUF

= PROVWT_C , if the child is in the 2018-2019 PUF.

The user should follow the seven-step procedure set forth in the section on multi-year means, using 

NEWWT2 in lieu of NEWWT. In SUDAAN, the user should also specify the contrast of interest

through use of a CONTRAST statement or an appropriate regression model. For example, to compare the 

4:3:1:3:3:1 up-to-date estimate from 2018 to the 2019 estimate, SUDAAN users can use the following 

WEIGHT, VAR, and CONTRAST statements:

WEIGHT NEWWT2;

VAR PU431331; 

CONTRAST YEAR = (-1 1);
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 65

Table 10: Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP19, and Common 

Denominator Estimation Area (CDIAP), National Immunization Survey - Child, 2019 

CDIAP Area Name ITRUEIAP

(1995-2004)

ESTIAP

(2005)

ESTIAP06

(2006)

ESTIAP07

(2007)

ESTIAP08

(2008)

ESTIAP09

(2009)

ESTIAP10 

(2010)

ESTIAP11 

(2011)

Alabama 

20 AL-Jefferson County 21 21 20 20 20 20 20 20

20 AL-Rest of State 20 20 20 20 20 20 20 20

74 Alaska 74 74 74 74 74 74 74 74

Arizona 

66 AZ-Maricopa County 67 67 67 66 66 66 66 66

66 AZ-Rest of State 66 66 66 66 66 66 66 66

46 Arkansas 46 46 46 46 46 46 46 46

California 

68 CA-Fresno County 68 68 84 68 68 68 68 68

68 CA-Los Angeles County 69 69 69 69 69 69 69 68

68 CA-Northern CA 68 68 85 68 85 68 68 68

68 CA-San Diego County 71 68 71 68 68 68 68 68

68 CA-Santa Clara County 70 68 70 68 70 68 68 68

68 CA-San Bernardino County 68 80 68 80 68 68 68 68

68 CA-Alameda County 68 79 68 79 68 68 68 68

68 CA-Rest of State 68 68 68 68 68 68 68 68

Colorado 

60 CO-Denver 60 81 60 60 60 60 60 60

60 CO-Rest of State 60 60 60 60 60 60 60 60

1 Connecticut 1 1 1 1 1 1 1 1 

13 Delaware 13 13 13 13 13 13 13 13

12 District of Columbia 12 12 12 12 12 12 12 12

Florida 

22 FL-Miami-Dade County 24 22 24 24 24 22 22 22

22 FL-Duval County 23 23 23 22 22 22 22 22

22 FL-Orange County 22 22 22 22 91 22 22 22

22 FL-Rest of State 22 22 22 22 22 22 22 22

Georgia 

25 GA-Fulton/DeKalb Counties 26 26 26 25 25 25 25 25

25 GA-Rest of State 25 25 25 25 25 25 25 25

72 Hawaii 72 72 72 72 72 72 72 72

75 Idaho 75 75 75 75 75 75 75 75

Illinois 

35 IL-City of Chicago 35 35 35 35 35 35 35 35

34 IL-Madison and St. Clair 

Counties 34 34 34 34 92 34 34 34

34 IL-Rest of State 34 34 34 34 34 34 34 34

Indiana 

36 IN-Lake County 36 36 36 36 36 96 36 36

36 IN-Marion County 37 36 37 37 36 37 36 36

36 IN-Rest of State 36 36 36 36 36 36 36 36

56 Iowa 56 56 56 56 56 56 56 56

Kansas 

57 KS-Eastern KS 57 57 86 57 57 57 57 57

57 KS-Rest of State 57 57 57 57 57 57 57 57

27 Kentucky 27 27 27 27 27 27 27 27

Louisiana 

47 LA-Orleans Parish 48 47 47 47 47 47 47 47

47 LA-Rest of State 47 47 47 47 47 47 47 47

4 Maine 4 4 4 4 4 4 4 4 

Maryland 

14 MD-City of Baltimore 15 15 15 14 15 15 14 14

14 MD-Prince George’s County 14 14 14 14 14 14 14 103

14 MD-Rest of State 14 14 14 14 14 14 14 14
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 66

CDIAP Area Name ITRUEIAP

(1995-2004)

ESTIAP

(2005)

ESTIAP06

(2006)

ESTIAP07

(2007)

ESTIAP08

(2008)

ESTIAP09

(2009)

ESTIAP10 

(2010)

ESTIAP11 

(2011)

Massachusetts 

2 MA-City of Boston 3 2 3 2 2 2 2 2 

2 MA-Rest of State 2 2 2 2 2 2 2 2 

Michigan 

38 MI-City of Detroit 39 39 39 38 38 38 38 38

38 MI-Rest of State 38 38 38 38 38 38 38 38

Minnesota 

40 MN-Twin Cities 40 40 40 40 93 40 40 40

40 MN-Rest of State 40 40 40 40 40 40 40 40

28 Mississippi 28 28 28 28 28 28 28 28

Missouri 

58 MO-St. Louis County/City 58 82 58 58 58 58 58 58

58 MO-Rest of State 58 58 58 58 58 58 58 58

61 Montana 61 61 61 61 61 61 61 61

59 Nebraska 59 59 59 59 59 59 59 59

Nevada 

73 NV-Clark County 73 83 73 73 73 73 73 73

73 NV-Rest of State 73 73 73 73 73 73 73 73

5 New Hampshire 5 5 5 5 5 5 5 5 

New Jersey 

8 NJ-City of Newark 9 9 9 8 8 8 8 8 

8 NJ-Rest of State 8 8 8 8 8 8 8 8 

New Mexico 

49 NM-Southern NM 49 49 88 49 49 49 49 49

49 NM-Rest of State 49 49 49 49 49 49 49 49

New York 

11 NY-City of New York 11 11 11 11 11 11 11 11

10 NY-Rest of State 10 10 10 10 10 10 10 10

29 North Carolina 29 29 29 29 29 29 29 29

62 North Dakota 62 62 62 62 62 62 62 62

Ohio 

41 OH-Cuyahoga County 42 42 42 41 41 41 41 41

41 OH-Franklin County 43 43 41 41 41 41 41 41

41 OH-Rest of State 41 41 41 41 41 41 41 41

50 Oklahoma 50 50 50 50 50 50 50 50

76 Oregon 76 76 76 76 76 76 76 76

Pennsylvania

16 PA-Allegheny County 16 16 87 16 16 16 16 16

17 PA-Philadelphia County 17 17 17 17 17 17 17 17

16 PA-Rest of State 16 16 16 16 16 16 16 16

6 Rhode Island 6 6 6 6 6 6 6 6 

30 South Carolina 30 30 30 30 30 30 30 30

63 South Dakota 63 63 63 63 63 63 63 63

Tennessee 

31 TN-Davidson County 33 33 31 31 31 31 31 31

31 TN-Shelby County 32 32 32 31 31 31 31 31

31 TN-Rest of State 31 31 31 31 31 31 31 31

Texas 

55 TX-Bexar County 55 55 55 55 55 55 55 55

54 TX-City of Houston 54 54 54 54 54 54 54 54

51 TX-Dallas County 52 52 52 52 52 52 52 52

51 TX-El Paso County 53 53 53 53 53 53 53 53

51 TX-Hidalgo County 51 51 51 51 51 51 51 51

51 TX-Travis County 51 51 51 51 51 51 51 51

51 TX-Tarrant County 51 51 51 51 51 51 51 51

51 TX-Rest of State 51 51 51 51 51 51 51 51

64 Utah 64 64 64 64 64 64 64 64
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 67

CDIAP Area Name ITRUEIAP

(1995-2004)

ESTIAP

(2005)

ESTIAP06

(2006)

ESTIAP07

(2007)

ESTIAP08

(2008)

ESTIAP09

(2009)

ESTIAP10 

(2010)

ESTIAP11 

(2011)

7 Vermont 7 7 7 7 7 7 7 7 

18 Virginia 18 18 18 18 18 18 18 18

Washington*

77 WA-Eastern WA 77 77 771 77 774 774 97 77

77 WA-Western WA 77 77 77 773 774 774 102 77

77 WA-King County 78 78 78 77 77 77 102 77

77 WA-Rest of State 77 77 772 77 77 77 - 77

19 West Virginia 19 19 19 19 19 19 19 19

Wisconsin 

44 WI-Milwaukee County 45 45 45 44 44 44 44 44

44 WI-Rest of State 44 44 44 44 44 44 44 44

65 Wyoming 65 65 65 65 65 65 65 65

- Puerto Rico - - - - - - - - 

* The estimation area WA-Eastern WA was introduced in 2006, and while this estimation area also existed in 2010, 

the county definition of the area changed, making cross-year comparisons inadvisable. The estimation area WAWestern WA, introduced in 2007, presents the same issue. The counties included in the area changed (e.g., in 2010 it

included King County). Analysis of Washington state data across years should use the entire state as the “Common 

Denominator”.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 68

Table 10 (continued): Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP19, and 

Common Denominator Estimation Area (CDIAP), National Immunization 

Survey - Child, 2019 

CDIAP Area Name ESTIAP12 

(2012)

ESTIAP13

(2013)

ESTIAP14

(2014)

ESTIAP15

(2015)

ESTIAP16

(2016)

ESTIAP17 

(2017) 

ESTIAP18 

(2018) 

ESTIAP19 

(2019)

Alabama 

20 AL-Jefferson County 20 20 20 20 20 20 20 20

20 AL-Rest of State 20 20 20 20 20 20 20 20

74 Alaska 74 74 74 74 74 74 74 74

Arizona 

66 AZ-Maricopa County 66 66 66 66 66 66 66 66

66 AZ-Rest of State 66 66 66 66 66 66 66 66

46 Arkansas 46 46 46 46 46 46 46 46

California 

68 CA-Fresno County 68 68 68 68 68 68 68 68

68 CA-Los Angeles County 68 68 68 68 68 68 68 68

68 CA-Northern CA 68 68 68 68 68 68 68 68

68 CA-San Diego County 68 68 68 68 68 68 68 68

68 CA-Santa Clara County 68 68 68 68 68 68 68 68

68 CA-San Bernardino County 68 68 68 68 68 68 68 68

68 CA-Alameda County 68 68 68 68 68 68 68 68

68 CA-Rest of State 68 68 68 68 68 68 68 68

Colorado 

60 CO-Denver 60 60 60 60 60 60 60 60

60 CO-Rest of State 60 60 60 60 60 60 60 60

1 Connecticut 1 1 1 1 1 1 1 1 

13 Delaware 13 13 13 13 13 13 13 13

12 District of Columbia 12 12 12 12 12 12 12 12

Florida 

22 FL-Miami-Dade County 22 22 22 22 22 22 22 22

22 FL-Duval County 22 22 22 22 22 22 22 22

22 FL-Orange County 22 22 22 22 22 22 22 22

22 FL-Rest of State 22 22 22 22 22 22 22 22

Georgia 

25 GA-Fulton/DeKalb Counties 25 25 25 25 25 25 25 25

25 GA-Rest of State 25 25 25 25 25 25 25 25

72 Hawaii 72 72 72 72 72 72 72 72

75 Idaho 75 75 75 75 75 75 75 75

Illinois 

35 IL-City of Chicago 35 35 35 35 35 35 35 35

34 IL-Madison and St. Clair Counties 34 34 34 34 34 34 34 34

34 IL-Rest of State 34 34 34 34 34 34 34 34

Indiana 

36 IN-Lake County 36 36 36 36 36 36 36 36

36 IN-Marion County 36 36 36 36 36 36 36 36

36 IN-Rest of State 36 36 36 36 36 36 36 36

56 Iowa 56 56 56 56 56 56 56 56

Kansas 

57 KS-Eastern KS 57 57 57 57 57 57 57 57

57 KS-Rest of State 57 57 57 57 57 57 57 57

27 Kentucky 27 27 27 27 27 27 27 27

Louisiana 

47 LA-Orleans Parish 47 47 47 47 47 47 47 47

47 LA-Rest of State 47 47 47 47 47 47 47 47

4 Maine 4 4 4 4 4 4 4 4 

Maryland 

14 MD-City of Baltimore 14 14 14 14 14 14 14 14

14 MD-Prince George’s County 14 14 14 14 14 14 14 14
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 69

CDIAP Area Name ESTIAP12 

(2012)

ESTIAP13

(2013)

ESTIAP14

(2014)

ESTIAP15

(2015)

ESTIAP16

(2016)

ESTIAP17 

(2017) 

ESTIAP18 

(2018) 

ESTIAP19 

(2019)

14 MD-Rest of State 14 14 14 14 14 14 14 14

Massachusetts 

2 MA-City of Boston 2 2 2 2 2 2 2 2 

2 MA-Rest of State 2 2 2 2 2 2 2 2 

Michigan 

38 MI-City of Detroit 38 38 38 38 38 38 38 38

38 MI-Rest of State 38 38 38 38 38 38 38 38

Minnesota 

40 MN-Twin Cities 40 40 40 40 40 40 40 40

40 MN-Rest of State 40 40 40 40 40 40 40 40

28 Mississippi 28 28 28 28 28 28 28 28

Missouri 

58 MO-St. Louis County/City 58 58 58 58 58 58 58 58

58 MO-Rest of State 58 58 58 58 58 58 58 58

61 Montana 61 61 61 61 61 61 61 61

59 Nebraska 59 59 59 59 59 59 59 59

Nevada 

73 NV-Clark County 73 73 73 73 73 73 73 73

73 NV-Rest of State 73 73 73 73 73 73 73 73

5 New Hampshire 5 5 5 5 5 5 5 5 

New Jersey 

8 NJ-City of Newark 8 8 8 8 8 8 8 8 

8 NJ-Rest of State 8 8 8 8 8 8 8 8 

New Mexico 

49 NM-Southern NM 49 49 49 49 49 49 49 49

49 NM-Rest of State 49 49 49 49 49 49 49 49

New York 

11 NY-City of New York 11 11 11 11 11 11 11 11

10 NY-Rest of State 10 10 10 10 10 10 10 10

29 North Carolina 29 29 29 29 29 29 29 29

62 North Dakota 62 62 62 62 62 62 62 62

Ohio 

41 OH-Cuyahoga County 41 41 41 41 41 41 41 41

41 OH-Franklin County 41 41 41 41 41 41 41 41

41 OH-Rest of State 41 41 41 41 41 41 41 41

50 Oklahoma 50 50 50 50 50 50 50 50

76 Oregon 76 76 76 76 76 76 76 76

Pennsylvania

16 PA-Allegheny County 16 16 16 16 16 16 16 16

17 PA-Philadelphia County 17 17 17 17 17 17 17 17

16 PA-Rest of State 16 16 16 16 16 16 16 16

6 Rhode Island 6 6 6 6 6 6 6 6 

30 South Carolina 30 30 30 30 30 30 30 30

63 South Dakota 63 63 63 63 63 63 63 63

Tennessee 

31 TN-Davidson County 31 31 31 31 31 31 31 31

31 TN-Shelby County 31 31 31 31 31 31 31 31

31 TN-Rest of State 31 31 31 31 31 31 31 31

Texas 

55 TX-Bexar County 55 55 55 55 55 55 55 55

54 TX-City of Houston 54 54 54 54 54 54 54 54

51 TX-Dallas County 52 51 51 51 52 52 51 52

51 TX-El Paso County 53 53 53 53 53 53 51 53

51 TX-Hidalgo County 51 51 51 107 51 51 107 51

51 TX-Travis County 51 51 51 51 51 108 51 51

51 TX-Tarrant County 51 51 51 109 51 51 109 51

51 TX-Rest of State 51 51 51 51 51 51 51 51
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 70

CDIAP Area Name ESTIAP12 

(2012)

ESTIAP13

(2013)

ESTIAP14

(2014)

ESTIAP15

(2015)

ESTIAP16

(2016)

ESTIAP17 

(2017) 

ESTIAP18 

(2018) 

ESTIAP19 

(2019)

64 Utah 64 64 64 64 64 64 64 64

7 Vermont 7 7 7 7 7 7 7 7 

18 Virginia 18 18 18 18 18 18 18 18

Washington*

77 WA-Eastern WA 77 77 77 77 77 77 77 77

77 WA-Western WA 77 77 77 77 77 77 77 77

77 WA-King County 77 77 77 77 77 77 77 77

77 WA-Rest of State 77 77 77 77 77 77 77 77

19 West Virginia 19 19 19 19 19 19 19 19

Wisconsin 

44 WI-Milwaukee County 44 44 44 44 44 44 44 44

44 WI-Rest of State 44 44 44 44 44 44 44 44

65 Wyoming 65 65 65 65 65 65 65 65

- Puerto Rico - - 106 106 106 - - 106

* The estimation area WA-Eastern WA was introduced in 2006, and while this estimation area also existed in 2010, 

the county definition of the area changed, making cross-year comparisons inadvisable. The estimation area WAWestern WA, introduced in 2007, presents the same issue. The counties included in the area changed (e.g., in 2010 it 

included King County). Analysis of Washington state data across years should use the entire state as the “Common 

Denominator”.

9. Summary Tables

Appendix F contains seven tables. Appendix Table F.1 lists the 61 estimation areas for the 2019 NISChild by state. At the national level and for each state and estimation area, it provides the estimated 

population total of children aged 19 through 35 months of age in 2019, and (from 2019 NIS-Child data 

collection) the number of children with completed household interviews and number of children with 

adequate provider data.

Appendix Tables F.2 through F.6 summarize pairs of variables: age group of child by maternal education 

(Appendix Table F.2), age group by family poverty status (Appendix Table F.3), race/ethnicity by family 

poverty status (Appendix Table F.4), age group by race/ethnicity (Appendix Table F.5), and age group by 

sex (Appendix Table F.6). Each of these tables gives the unweighted and weighted counts of children who 

have completed household interviews and the unweighted and weighted counts of children with adequate 

provider data. 

Appendix Table F.7 presents estimates of vaccination coverage and symmetric 95% confidence intervals 

obtained from SUDAAN. The data user should obtain the same estimates from the 2019 NIS-Child

public-use data file. (As noted in Section 1 of this report, these estimates will differ from those appearing 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 71

on ChildVaxView and in the MMWR, which use multiple years of NIS-Child data and apply to the 

population of children born in particular years rather than using a single year of NIS-Child data and 

applying to the population of children age 19-35 months.) 

Appendix G contains four tables and time-series charts. Table G.1 and Figure G.1 show key components 

of the NIS-Child response rates and the CASRO response rates for the landline sample by year of the 

survey. Table G.2 and Figure G.2 show key components of the NIS-Child response rates and the CASRO 

response rates for the cell-phone sample by year of the survey. Table G.3 and Figure G.3 show the 

CASRO response rates for the combined landline and cell-phone samples. Table G.4 and Figure G.4 

show vaccination coverage estimates since 1995. 

Appendix H shows the vaccine type codes used in the 2019 NIS-Child public-use data file. 

Appendix I presents key response rate components and the overall CASRO response rate by estimation 

area in the 2019 NIS-Child. 

10. Assessment of Total Survey Error

Assessing the validity of the NIS-Child estimates of vaccination coverage is a critical and ongoing aspect 

of the NIS-Child surveillance program. CDC frequently conducts evaluation studies and controlled 

experiments to understand the causes and impacts of sampling and nonsampling errors on the estimates 

and to enable formulation of methodological refinements that have the demonstrated capacity to improve 

data quality. As landline phone use decreased and cell phone use increased dramatically over the past 

decade, and the NIS-Child transitioned first from a single-frame landline RDD sampling design to a dualframe landline and cell-phone RDD design and then to a single-frame cell-phone RDD design, CDC has 

monitored the NIS-Child estimates utilizing a Total Survey Error (TSE) approach.

TSE is the sum of the errors that arise at every step of a survey, including both sampling error and 

nonsampling errors such as coverage, nonresponse, and measurement errors (Mulry and Spencer, 1991). 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 72

Pooling information from multiple evaluations of their precision and accuracy, we have conducted TSE

analyses for the 2009-2013 NIS-Child and NIS-Teen data (Molinari et al. 2011; NORC 2011; Pineau et 

al. 2012; Pineau et al. 2013; Skalland et al. 2016; Wolter et al. 2017b) and for the 2018 NIS-Child and 

NIS-Teen data (see the Data User’s Guides for the 2018 NIS-Child and NIS-Teen public use data files).

An assessment based on 2019 NIS-Child data was conducted in 2020, with results summarized in 

this report. 

Comparison of Demographic Distributions. Demographic distributions (age, sex, mother’s 

race/ethnicity, mother’s education, mother’s age) among children with adequate provider data

were compared to benchmark values derived from natality data supplied by the National Vital 

Statistics System. When using design weights that have not been adjusted for nonresponse or 

calibrated to external population totals, demographic distributions as estimated in the NIS-Child

were generally close to the benchmark distributions. Before calibration of the weights to external 

population totals, the 2019 NIS-Child somewhat over-represented children whose mothers are 

college graduates, non-Hispanic White, or age 30 or greater, and somewhat under-represented 

children whose mothers are not college graduates, are non-Hispanic Black, or are age 20 to 29 

years. When using the final weights that have been adjusted for nonresponse and calibrated to 

external population totals, the demographic differences between survey and population are 

reduced, but the 2019 NIS-Child still overrepresented children whose mothers are four-year college 

graduates (39.1% in survey, 32.2% in population) or are age 30 or greater (65.8% in survey, 59.4% 

in population). 

Comparison to IISAR Vaccination Coverage Rates. Next, NIS-Child vaccination coverage rate 

estimates were compared to vaccination coverage rates set forth in the Immunization Information 

Systems Annual Report (IISAR). The IISAR is an annual assessment sponsored and conducted by 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 73

NCIRD of immunization information systems (IIS)2 activity among the 64 immunization program 

awardees, which include the 50 states, 6 cities (Chicago, District of Columbia, Houston, New York 

City, Philadelphia and San Antonio), and 8 U.S. territories. To evaluate each awardee’s 

performance, the immunization program manager in the awardee area is asked to complete a selfadministered, web-based questionnaire asking for demographic and immunization information, 

public and private provider site participation levels, and information about achievement of IIS 

functional standards. NCIRD provides competitive supplemental funds to awardees that have met 

high data timeliness and participation (child and adolescent) in the IIS. During the period 2013-

2017 six awardees were recognized as IIS sentinel sites, including Michigan, Minnesota, North 

Dakota, New York City, Oregon, and Wisconsin. Because of increased timeliness and higher child 

and adolescent saturation levels in the IIS, vaccination coverage rates reported in IISAR by sentinel 

sites are thought to be relatively more accurate than vaccination rates reported by non-sentinel 

sites.

NIS-Child vaccination coverage rate estimates were found to be generally higher than IISAR 

vaccination coverage rates. For four sentinel sites, reasonably good agreement was observed 

between the NIS-Child and IISAR vaccination coverage rates, with the absolute difference in rates 

in 2018 ranging between 0 and 6 percentage points for the 7-vaccine series for Michigan, New York 

City, Oregon, and Wisconsin. For the remaining two sites, Minnesota and Oregon, the absolute 

differences were larger, ranging from 8 to 10 percentage points. Further, it was established that the 

child participation rate – the proportion of children in the IIS jurisdiction with two or more vaccine 

doses in the IIS database – is a reasonable indicator of the quality of the corresponding IIS 

database, as the IIS vaccination coverage rate was found to increase as the child participation rate 

increases. It was also observed (Figure 1) that the difference between NIS-Child and IISAR 

 

2 State IIS’s are computer databases that aspire to contain information about all of the doses of all vaccines 

administered to all children resident within the state. It is known that different state IIS’s vary in their completeness 

of both children and the doses they received.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 74

vaccination coverage rates declines as the child participation rate increases (i.e., as the quality of 

the IIS increases). These findings are consistent with the view that IIS vaccination coverage rates 

converge towards NIS-Child vaccination coverage rates as the quality of the IIS increases.

Figure 1: Scatter Plot of Difference between NIS-Child and IISAR Vaccination Coverage Rates 

for the Combined 7-Vaccine Series vs. IIS Child Participation Rate (CPR) with 

Regression Line: 54 Estimation Areas, 2018 

Comparison of Health Insurance Distributions. NIS-Child health insurance distributions were 

compared to similar distributions produced by the Current Population Survey (CPS), the National 

Health Interview Survey (NHIS), and the American Community Survey (ACS). All of these surveys 

use somewhat different definitions of insurance status and report for different age ranges of 

children. Nevertheless, we found the NIS-Child distributions to be broadly similar to those from the 

CPS, NHIS, and ACS, but with some differences. NIS-Child estimates of percent of children with 

any public insurance (52.6% in 2018; 51.3% in 2019) were higher than the corresponding 

benchmark estimates (46.6% (NHIS), 47.9% (CPS), and 46.4% (ACS) in 2018; 41.1% (CPS) in 

2019), and the NIS-Child estimates of uninsured children (3.2% in 2018; 3.3% in 2019) were lower 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 75

than the estimates from the benchmark surveys (4.6% (NHIS), 4.5% (CPS), and 4.1% (ACS) in 

2018; 5.6% (CPS) in 2018). 

Comparison to State Immunization Surveys. A comparison was undertaken of NIS-Child vaccination 

coverage rate estimates to estimates from eight state immunization surveys: Florida (Florida 

Department of Health, 2020), Georgia (Machado, n.d.), Kansas (Gillespie, 2019), Michigan 

(Michigan Department of Health and Human Services, 2020), Tennessee (Tennessee Department of 

Health, 2020), Virginia (Virginia Department of Health, 2019), Washington (Washington State 

Department of Health, n.d.), and Wisconsin (Wisconsin Department of Health Services, 2020).

Some aspects of NIS-Child and state survey practices are hard to compare and limit the import of 

the results. That said, there is reasonable agreement between NIS-Child and state vaccination rates 

in many of the states. Where NIS-Child and state practices were comparable, similar vaccination 

rates were found. For state surveys that rely on IIS vaccination histories, NIS-Child rates were 

generally found to be greater than the corresponding states’ rates. While this work did not provide 

specific measures of error in NIS-Child statistics, it did provide general support for the accuracy of 

the vaccination coverage rates.

Next, an assessment of all sources of error in the 2019 NIS-Child was conducted, including sampleframe coverage error, nonresponse error, and measurement error; the component errors were then

combined to assess total survey error. The change in total survey error between the 2018 NIS-Child 

and 2019 NIS-Child was also estimated.

Coverage Error. The NIS-Child cell-phone RDD sampling frame fails to cover the landline only and 

phoneless populations; vaccination coverage rates in the former were estimated using data collected 

in the 2017 NIS-Child (the last year a dual-frame landline and cell-phone sample was fielded for the 

NIS) and vaccination coverage rates in the latter were estimated using data collected in the 2012 

NHIS Provider Record Check. The vaccination coverage rates in the population covered by the 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 76

sampling-frame were found to be greater than the vaccination rates in the uncovered population. 

Because the sampling-frame uncovered population is so small relative to the covered population, 

however, mean sampling-frame coverage error was estimated to be only around 0.5 percentage 

points for most vaccines/series.

Nonresponse Error. Nonresponse error in the 2019 NIS-Child was assessed through comparison to 

the cell-phone domain within the combined 2017 and 2018 NHIS. NHIS does not offer direct 

estimates of vaccination coverage rates. Instead, a model-based technique was used to impute NHIS 

vaccination status, and then the resulting NHIS vaccination coverage rates (treated as vaccination 

coverage rates void of nonresponse error) were compared to NIS-Child vaccination coverage rates, 

with the difference treated as nonresponse error in the NIS-Child. Despite nonresponse in the 2019 

NIS-Child, including household nonresponse, non-consent to contact vaccination providers, and 

provider nonresponse, mean nonresponse error in vaccination rates was estimated to be quite small 

(0.1 to 0.9 percentage points when using design weights for NIS-Child, 0.1 to 1.4 percentage when 

using final weights that account for the survey’s nonresponse adjustments) and not statistically 

significant.

Measurement Error. A form of measurement error called “provider under-reporting” error was 

assessed. Sometimes called “under-ascertainment,” provider under-reporting error arises when a 

child with adequate provider data is truly vaccinated but is reported as unvaccinated for one or 

more recommended doses in the child’s provider-reported vaccination history. Under-reporting 

error can occur if the household respondent fails to nominate all of the child’s vaccination 

providers, if one or more of the child’s nominated vaccination providers fails to report a 

vaccination history for the child, or if one or more of the child’s nominated providers reports a 

vaccination history but fails to report all of the vaccinations the child has received. Underreporting 

error was estimated using data from projects sponsored by CDC in which the 2017 NIS-Child 

sample of children in 17 jurisdictions was matched to the state or local IIS for the jurisdiction. In 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 77

this work, the standard of truth for a given child is taken to be the synthesis of the NIS-Child and 

IIS vaccination histories. In prior studies conducted in 2012 and 2013 using similar methods, 

measurement error was found to be by far the largest component of error in the NIS-Child 

vaccination rates. Similar conclusions were reached for the 2019 NIS-Child, where it was estimated 

that measurement error depressed observed vaccination rates by about 2 to 9 percentage points.

Total Survey Error. Finally, all of the component errors were combined to assess the distribution of 

total error in the NIS-Child vaccination coverage rates, using a Monte Carlo technique. The mean 

of the distribution is an estimate of the total error, and the 2.5 and 97.5 percentiles of the 

distribution form a 95% credible interval for the total error. The estimated component errors and 

total survey errors are presented in Table 11. For the 4+ DTaP vaccination coverage rate, the mean 

of the TSE distribution was found to be -3.1 percentage points with a 95% credible interval of (-6.6, 

1.2) percentage points. That is, the NIS-Child vaccination coverage rate was on average about 3.1 

percentage points too low. For the 1+ MMR vaccination coverage rate, the mean of the TSE 

distribution was found to be -2.2 percentage points with a 95% credible interval of (-4.3, 1.3) 

percentage points. That the credible intervals for 4+ DTaP and 1+ MMR contain zero signifies that 

the statistical evidence is not inconsistent with the hypothesis that mean total error is near zero for 

these vaccines. Of the three vaccination outcomes evaluated, only the combined 7-vaccine series had 

a credible interval that did not include zero: the mean of the TSE distribution -9.0 percentage 

points with a credible interval of (-12.6, -4.0) percentage points. Thus, the statistical evidence for 

the 7-vaccine series is inconsistent with the hypothesis of near zero mean total error. According to 

best estimates, under-ascertainment of the provider-reported vaccination history dominated total 

survey error.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 78

Table 11: Mean and 95% Credible Interval for the Estimated Total Survey Error (TSE) 

Distribution and Component Error Distributions for National Vaccination Coverage 

Rate Estimates, National Immunization Survey - Child, 2019 

Vaccine or 

Series Component Mean TSE

(pct points)

95% Credible Interval

(pct points)

4+ DTaP

TSE (final weighted) -3.1 (-6.6, 1.2)

TSE (design weighted) -3.6 (-7.1, 0.6)

Noncoverage error 0.2 (-0.5, 1.2)

Nonresponse error 1.0 (-3.2, 5.8)

Measurement error -4.8 (-6.6, -2.8)* 

Sampling error 0.1 (-2.0, 2.3)

1+ MMR

TSE (final weighted) -2.2 (-4.3, 1.3)

TSE (design weighted) -2.5 (-5.2, 0.5)

Noncoverage error 0.2 (-0.3, 1.0)

Nonresponse error 1.0 (-3.7, 3.1)

Measurement error -3.6 (-3.9, -0.7)* 

Sampling error 0.2 (-1.6, 1.9)

7-vaccine 

series

TSE (final weighted) -9.0 (-12.6, -4.0)* 

TSE (design weighted) -8.2 (-12.5, -3.8)* 

Noncoverage error 0.6 (-0.4, 1.8) 

Nonresponse error 0.4 (-4.7, 5.3) 

Measurement error -9.2 (-11.1, -6.8)* 

Sampling error 0.1 (-2.4, 2.6)

* 95% credible interval excludes zero.

Change in Total Survey Error. Change in TSE between the 2018 and 2019 NIS-Child was measured 

using the bridging cohort method pioneered by NCIRD (Yankey, Hill, Elam-Evans, et al. 2015). 

Each survey quarter includes children born in 20 monthly birth cohorts. Every pair of adjacent 

survey quarters spans 23 monthly birth cohorts, of which 17 are in common and 6 are not in 

common. In turn, every survey year represents 29 monthly birth cohorts. Every pair of adjacent 

survey years spans 39 monthly birth cohorts, of which 17 are in common and 22 are not in 

common. The 17 common months comprise the bridging cohort, and for 2018 and 2019, the 

bridging cohort extends from children born in January 2016 through children born in May 2017. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 79

Consider a vaccination coverage rate estimated from the bridging cohort as of a given child age, 

such as 19 months or 24 months. Two estimates are possible, one using the sample of children in the 

bridging cohort within the 2018 NIS-Child sample and the second using the corresponding sample 

of children within the 2019 NIS-Child sample. Ideally, the two estimators should exhibit the same 

statistical expectation (i.e., average value in hypothetical repeated sampling). A large difference 

between the two estimates may signal a change in the statistical expectation of total survey error

from one survey year to the next, which could result from a change in the distribution of samplingframe coverage error, nonresponse error, or measurement error. Differences may also result 

simply from the effects of random sampling error.

One of the differences between the 2018 and 2019 national-level vaccination coverage rates for the 

bridging cohort was found to be statistically significant at the 0.05 level: the vaccination coverage 

rate for 3+ Polio was 1.8 percentage points lower when using the 2019 sample than when using the 

2018 sample, with a p-value of 0.041. However, all other vaccines studied did not exhibit a 

statistically significant difference between 2018 and 2019, suggesting that there is little evidence of a 

change in the statistical expectation of total survey error between 2018 and 2019.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 80

11. Limitations 

The findings in this report are subject to at least four limitations. First, because NIS-Child is a telephone 

survey, results are weighted to be representative of all children aged 19 through 35 months. Although 

statistical adjustments were made to account for non-response and households without cell phones, some 

bias might remain. Second, underestimates of vaccination coverage might have resulted from the 

exclusive use of provider-reported vaccination histories because completeness of these records is 

unknown. Third, although national estimates of vaccination coverage are precise, estimates for state and 

local areas should be interpreted with caution because their sample sizes are smaller and their confidence 

intervals generally are wider than those for national estimates. Finally, analysis of trends across data years 

that span from 2010 and earlier to 2011-2017 and from 2011-2017 to 2018-2019 are subject to potential 

bias that may remain after weighting adjustments because of the switch from landline to dual landline and 

cell-phone frames in 2011, and from dual landline and cell-phone frames to a single cell-phone frame in 

2018 (Hill et al., 2019). In addition, analysis of trends across data years that span from 2011 to 2017 are 

subject to potential bias that may remain after weighting adjustments because of the expansions and 

reductions of the share of the total sample that came from the cell-phone frame across these years. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 81

12. Citations for NIS-Child Data 

In publications, please acknowledge the original data source. The citation for the 2019 NIS-Child publicuse data file is:

U.S. Department of Health and Human Services (DHHS). National Center for Immunization and 

Respiratory Diseases . The 2019 National Immunization Survey-Child, Atlanta, GA : Centers for Disease 

Control and Prevention, 2020. 

Information about the NIS-Child is located at http://www.cdc.gov/vaccines/imz-managers/nis/about.html. 

The NIS-Child public-use data files are located at http://www.cdc.gov/vaccines/imzmanagers/nis/datasets.html.

Please place the acronym “NIS-Child” in the titles, keywords, or abstracts of journal articles and other 

publications in order to facilitate retrieval of such materials in bibliographic searches. 

The following publications use NIS-Child data, published from 2010 or later: 

2020 

Adebanjo TA, Pondo T, Yankey D, Hill HA, Gierke R, Apostol M, Barnes M, Petit S, Farley M, Harrison 

LH, Holtzman C, Baumbach J, Bennett N, McGuire S, Thomas A, Schaffner W, Beall B,

Whitney CG, Pilishvili T. Pneumococcal conjugate vaccine breakthrough infections: 2001-2016. 

Pediatrics 2020 Mar;145(3):e20190836.

Bleser WK, Salmon DA, Miranda PY. A hidden vulnerable population: Young children up-to-date on 

vaccine series recommendations except influenza vaccines. PLoS One 2020;15(6):e0234466. 

Hill HA, Yankey D, Elam-Evans LD, Singleton JA, Pingali SC, Santibanez TA. Vaccination Coverage by 

Age 24 Months Among Children Born in 2016 and 2017 — National Immunization Survey-Child, United 

States, 2017–2019. MMWR Morb Mortal Wkly Rep 2020;69:1505–1511. 

DOI: http://dx.doi.org/10.15585/mmwr.mm6942a1

Vader DT, Lee BK, Evans AA. Hepatitis B birth dose effects on childhood immunization in the U.S. 

American Journal of Preventive Medicine 2020;58(2):208-215. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 82

2019 

Beauregard JL, Hamner HC, Chen J, Avila-Rodriguez W, Elam-Evans LD, Perrine CG. Racial Disparities 

in Breastfeeding Initiation and Duration Among U.S. Infants Born in 2015. MMWR Morb Mortal Wkly 

Rep 2019;68:745–748. DOI: http://dx.doi.org/10.15585/mmwr.mm6834a3

Grubesic TH, Durbin KM. A spatial analysis of breastfeeding and breastfeeding support in the United 

States: The leaders and laggards landscape. Journal of Human Lactation 2019. Epub ahead of print. 

Hamad R, Modrek S, White JS. Paid family leave effects on breastfeeding: A quasi-experimental study of 

US policies. Am J Public Health 2019;109:164-166. 

Hill HA, Singleton JA, Yankey D, Elam-Evans LD, Pingali SC, Kang Y. Vaccination Coverage by Age 

24 Months Among Children Born in 2015 and 2016 — National Immunization Survey-Child, United 

States, 2016–2018. MMWR Morb Mortal Wkly Rep 2019;68:913–918. DOI: 

http://dx.doi.org/10.15585/mmwr.mm6841e2external icon 

Li R, Perrine CG, Anstey EH, Chen J, MacGowen CA, Elam-Evans LD. Breastfeeding trends by 

race/ethnicity among US children born from 2009 to 2015. JAMA Pediatr 2019 Oct 14;173(12):e193319. 

Sederdahl BK, Orenstein WA, Yi J, Anderson EJ, Bednarczyk RA. Missed opportunities for rotavirus 

vaccination. Pediatrics 2019;143(5) (online) 

Wolter KM, Ganesh N, Copeland KR, Singleton JA, Khare M. Estimation tools for reducing the impact 

of sampling and nonresponse errors in dual-frame RDD telephone surveys. Stat Med 2019 38(23):4718-

4732. 

2018 

Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kang Y. Vaccination Coverage Among Children 

Aged 19–35 Months — United States, 2017. MMWR Morb Mortal Wkly Rep 2018;67(40):1123-1128. 

DOI: http://doi.org/10.15585/mmwr.mm6740a4

Lavrakas PJ, Skalland B, Ward C, Geng C, Welch V, Jeyarajah J, Knighton C. Testing the effects of 

envelope features on survey response in a telephone survey advance letter mailing experiment. Journal of 

Survey Statistics and Methodology 2018;6:262-283. 

Mulligan K, Snider JT, Arthur P, Frank G, Tebeka M, Walker A, Abrevaya J. Examination of universal 

purchase programs as a driver of vaccine uptake among US States, 1995-2014. Vaccine 2018;36:4032-

4038. 

 

Zhao Z, Smith PJ, Hill HA. Factors associated with missed opportunities for simultaneous administration 

of the fourth dose of pneumococcal conjugate vaccine for children in the United States. International 

Journal of Science and Research Methodology 2018;9(1):149-162. 

2017 

Anstey EH, Chen J, Elam-Evans LD, Perrine CG. Racial and Geographic Differences in Breastfeeding — 

United States, 2011–2015. MMWR Morb Mortal Wkly Rep 2017;66:723–727. 

 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 83

Casillas SM, Bednarczyk RA. Missed opportunities for hepatitis A vaccination, National Immunization 

Survey-Child, 2013. J Pediatr 2017;187:265-71. 

 

Chen W, Elam-Evans LD, Hill HA, Yankey D. Employment and socioeconomic factors associated with 

children’s up-to-date vaccination status. Clinical Pediatrics 2017;56(4):348-356. 

Childs L, Bednarczyk RA. Estimating pertussis susceptibility among 0—23-month-old children in the 

United States. Pediatr Infect Dis J 2017;36:705-711. 

Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kang Y. Vaccination coverage among children aged 

19-35 months – United States, 2016. MMWR Morb Mortal Wkly Rep 2017;66:1171-1177. 

Kurosky SK, Davis KL, Galindo CM. Effect of combination vaccines on hepatitis B vaccine compliance 

in children in the United States. Pediatr Infect Dis J 2017;36:e179-e196. 

Kurosky SK, Davis KL, Krishnarajah G. Effect of combination vaccines on completion and compliance 

of childhood vaccinations in the United States. Human Vaccines & Immunotherapeutics 

2017;13(11):2494-2502. 

Lo NC, Hotez PJ. Public health and economic consequences of vaccine hesitancy for measles in the 

United States. JAMA Pediatrics 2017;17(9):887-892. 

Varan AK, Rodriguez-Lainz A, Hill HA, Elam-Evans LD, Yankey D, Li Q. Vaccination coverage 

disparities between foreign-born and U.S.-born children aged 19-35 months, United States, 2010-2012. J 

Immigrant Minority Health 2017;19:779-789. 

Zhao Z, Smith PJ, Hill HA. Missed opportunities for simultaneous administration of the fourth dose of 

DTaP among children in the United States. Vaccine 2017;35:3191-3195. 

2016 

Cardemil CV, Cullen KA, Harris L, Greby SM, Santibanez TA. Factors associated with provider 

reporting of child and adolescent vaccination history to Immunization Information Systems: Results from 

the National Immunization Survey, 2006-2012. J Public Health Management Practice 2016;22(3):245-

254. 

Curran D, Terlinden A, Poirrier J-E, Masseria C, Krishnarajah G. Vaccine timeliness: A cost analysis of 

the potential implications of delayed pertussis vaccination in the US. Pediatr Infect Dis J 2016;35(5):542-

547. 

Gilkey MB, McRee A-L, Magnus BE, Reiter PL, Dempsey AF, Brewer NT. Vaccination confidence and 

parental refusal/delay of early childhood vaccines. PLOS ONE | DOI: 10.1371/journal/pone.0159087 July 

8, 2016. 

Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Dietz V. Vaccination Coverage Among Children 

Aged 19–35 Months — United States, 2015. MMWR Morb Mortal Wkly Rep 2016;65:1065–1071. 

Hu T, Decker SL, Chou S-Y. Medicaid pay for performance programs and childhood immunization 

status. Am J Prev Med 2016;50(5S1):S51-S57. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 84

Kurosky SK, Davis KL, Krishnarajah G. Completion and compliance of childhood vaccinations in the 

United States. Vaccine 2016 Jan 12;34(3):387-394. 

Murphy TV, Denniston MM, Hill HA, McDonald M, Klevens M, Elam-Evans LD, Nelson NP, Iskander 

J, Ward JD. Progress toward eliminating hepatitis A disease in the United States. MMWR Suppl 

2016;65(1):29-41. 

Santibanez TA, Grohskopf LA, Zhai Y, Kahn KE. Complete influenza vaccination trends for children six 

to twenty-three months. Pediatrics 2016;137(3):e20153280. 

Walsh B, Doherty E, O’Neill C. Since the start of the Vaccines for Children program, uptake has 

increased, and most disparities have decreased. Health Affairs 2016;35(2):356-364. 

Zhao Z, Smith PJ, Hill HA. Evaluation of potentially achievable vaccination coverage with simultaneous 

administration of vaccines among children in the United States. Vaccine 2016;34:3030-3036. 

2015 

Crouch E, Dickes LA. A prediction model of childhood immunization rates. Appl Health Econ Health

Policy 2015 Apr;13(2):243-251. 

Dunn, AC, Black CL, Arnold J, Brodine S, Waalen J, Binkin N. Childhood vaccination coverage rates 

among military dependents in the United States. Pediatrics 2015 May;135(5):e1148-56. 

Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kolasa M. National, state, and selected local area 

vaccination coverage among children aged 19-35 months – United States, 2014. MMWR 

2015;64(33):889-896. 

Joyce T, Reeder J. Changes in Breastfeeding among WIC participants following implementation of the 

new food package. Matern Child Health J 2015 Apr;19(4):868-76. 

Smith PJ, Marcuse EK, Seward JF, Zhao Z, Orenstein WA. Children and adolescents unvaccinated 

against measles: geographic clustering, parents’ beliefs, and missed opportunities. Public Health Rep 

2015 Sep-Oct;130(5):485-504. 

Srivastav A, Zhai Y, Santibanez TA, Kahn KE, Smith PJ, Singleton JA. Influenza vaccination coverage 

of Vaccine for Children (VFC)-entitled versus privately insured children, United States, 2011-2013. 

Vaccine 2015. To appear. 

Wolter KM, Tao X, Montgomery R, Smith PJ. Optimum allocation for a dual-frame telephone survey. 

Survey Methodology 2015 Dec;41(2):389-401. 

2014 

Elam-Evans LD, Yankey D, Singleton JA, Kolasa M. National, state, and selected local area vaccination 

coverage among children aged 19-35 months - United States, 2013. MMWR 2014;63(34):741-8. 

Johnson NB, Hayes LD, Brown K, Hoo EC, Ethier KA. CDC National Health Report: leading causes of 

morbidity and mortality and associated behavioral risk and protective factors--United States, 2005-2013 

MMWR 2014;63(Suppl-4):1-27. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 85

Santibanez TA, Lu PJ, O’Halloran A, Meghani A, Grabowsky M, Singleton JA. Trends in childhood 

influenza vaccination coverage—U.S., 2004-2012. Public Health Rep 2014;129(5):417-27. 

Thomas TN, Kolasa MS, Zhang F, Shefer AM. Assessing immunization interventions in the Women, 

Infants, and Children (WIC) Program. Am J Prev Med 2014 Sep 10. [Epub ahead of print: DOI: 

10.1016/j.amepre.2014.06.017] 

Walker AT, Smith PJ, Kolasa M. Reduction of racial/ethnic disparities in vaccination coverage, 1995-

2011. MMWR Surveill Summ 2014 Apr 18;63 Suppl 1:7-12. 

Whitney CG, Zhou F, Singleton J, Schuchat A. Benefits from immunization during the vaccines for 

children program era - United States, 1994-2013. MMWR 2014 Apr 25;63(16):352-5. 

Yang YT, Debold V. A longitudinal analysis of the effect of nonmedical exemption law and vaccine 

uptake on vaccine-targeted disease rates. Am J Public Health 2014;104:371-377. 

Zhao Z, Smith PJ, Yankey D, Copeland KR. Calculating adjusted survival functions for complex sample 

survey data and application to vaccination coverage studies with National Immunization Survey. British 

Journal of Mathematics & Computer Science 2014;4(18):2686-2698. 

2013 

Allen JA, Li R, Scanlon KS, Perrine CG, Chen J, Odom E, Black C. Progress in increasing breastfeeding 

and reducing racial/ethnic differences — United States, 2000–2008 births. MMWR 2013 Feb 8;62(5):77-

80. 

Black CL, Yankey D, Kolasa M. National, state, and local area vaccination coverage among children aged 

19–35 months — United States, 2012. MMWR 2013 Sept 13;62(36):733-740. 

Schuller KA, Probst JC. Factors associated with influenza vaccination among US children in 2008. J 

Infect Public Health 2013;6(2):80-88. 

Zhao Z, Murphy TV. Which newborns missed the hepatitis B birth dose vaccination among U.S. 

children? Preventive Medicine. 2013, 57, 613-7. 

Zhao Z, Smith P. Trends in vaccination coverage disparities among children, United States, 2001-2010. 

Vaccine. 2013, 31(19), 2324-2327 

2012 

Black CL, Yankey D, Kolasa M. National, state, and local area vaccination coverage among children aged 

19-35 months – United States, 2011. MMWR 2012 Sept 7;61(35):689-696. 

Bundy DG, Solomon BS, Kim JM, Miller MR. Accuracy and usefulness of the HEDIS childhood 

immunization measures. Pediatrics 2012;129(4):648-656. 

Groom AV, Santibanez TA, Bryan RT. Vaccination coverage among American Indian and Alaska Native 

Children, 2006 – 2010. Pediatrics 2012;130(6):e1592-e1599. 

Jensen E. Participation in the Supplemental Nutrition Program for Women, Infants, and Children (WIC) 

and breastfeeding: national, regional, and state level analyses. Matern Child Health J 2012;16:624-631. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 86

Ransom J, Schaff K, Kan L. Is there an association between local health department organizational and 

administrative factors and childhood immunization coverage rates? J Health Hum Serv Adm 2012 

Spring;34(4):418-455. 

Santibanez TA, Shefer A, Briere EC, Cohn AC, Groom AV. Effects of a nationwide Hib vaccine shortage 

on vaccination coverage. Vaccine 2012;30:941-947. 

Thompson KM, Wallace GS, Tebbens RJD, Smith PJ, Barskey AE, Pallansch MA, Gallagher KM, 

Alexander JP, Armstrong GL, Cochi SL, Wassilak SGF. Trends in the risk of U.S. polio outbreaks and 

poliovirus vaccine availability for response. Public Health Rep 2012;127:23-37. 

Zhao Z, Murphy TV. The association of hepatitis B vaccine supply policy with timing of receipt of the 

first dose of hepatitis B vaccination. Open Journal of Statistics 2012;2:429-434. 

2011 

Black CL, Wooten KG, Yankey D, Kolasa M. National and state vaccination coverage among children 

aged 19-35 months – United States, 2010. MMWR 2011 Sept 2;60(34):1157-1163. 

Byrd KK, Santibanez TA, Chaves SS. Predictors of hepatitis A vaccination among young children in the 

United States. Vaccine 2011;29:3254-3259. 

Dozier AM, McKee KS. State breastfeeding worksite statutes... breastfeeding rates ... and..... Breastfeed 

Med 2011;6(5):319-324. 

Flaherman VJ, Chien AT, McCulloch CE, Dudley RA. Breastfeeding rates differ significantly by method 

used: a cause for concern for public health measurement. Breastfeed Med 2011;6(1):31-35. 

Molinari NM, Wolter KM, Skalland B, Montgomery R, Khare M, Smith PJ, Barron ML, Copeland K, 

Santos K, Singleton JA. Quantifying bias in a health survey: modeling total survey error in the National 

Immunization Survey. Stat Med 2011;30:505-514. 

Smith PJ, Humiston SG, Marcuse EK, Zhao Z, Dorell CG, Howes C, Hibbs B. Parental delay or refusal of 

vaccine doses, childhood vaccination coverage at 24 months of age, and the health belief model. Public 

Health Rep. 2011 Jul-Aug;126 Suppl 2:135-46. 

Smith PJ, Lindley MC, Rodewald LE. Vaccination coverage among U.S. Children aged 19-35 months 

entitled by the Vaccines for Children Program, 2009. Public Health Rep 2011 Jul-Aug;126 Suppl 2:109-

23. 

Smith PJ, Singleton JA. County-level trends in vaccination coverage among children aged 19-35 months 

– United States, 1995 – 2008. MMWR Surveill Summ 2011 Apr 29;60(4):1-86. 

Smith PJ, Singleton JA. County-level trends in vaccination coverage for selected counties in the U.S., 

children aged 19-35 months, United States, 1995-2008: attainment of the healthy people 2010 objectives 

and association with county-level indices of access to care, economic conditions, and demographic 

composition. Morbidity and Mortality Weekly Report. Surveillance Summaries. 2011;60(4):1-86. 

Smith PJ, Wood D, Darden PM. Highlights of historical events leading to national surveillance of 

vaccination coverage in the United States. Public Health Reports. 2011;(Suppl 2):3-12. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 87

Zhao Z. Power of tests for comparing trend curves with application to National Immunization Survey 

(NIS). Stat Med 2011;30:531-540. 

Zhao Z, Murphy TV, Jacques-Carroll L. Progress in newborn hepatitis B vaccination by birth year cohorts 

– 1998-2007, USA. Vaccine 2011;30:14-20. 

2010 

Cohen SA, Ahmed S, Klassen AC, Agree EM, Louis TA, Naumova EN. Childhood Hib vaccination and 

pneumonia and influenza burden in US seniors. Vaccine 2010;28:4462-4469. 

Committee on Practice and Ambulatory Medicine and Council on Community Pediatrics. Increasing 

immunization coverage. Pediatrics 2010;125:1295-1304. 

Groom H, Kennedy A, Evans V, Fasano N. Qualitative analysis of immunization programs with most 

improved childhood vaccination coverage from 2001 to 2004. J Public Health Management Practice 

2010;16(1):E1-E8.

Kennedy A, Groom H, Evans V, Fasano N. A qualitative analysis of immunization programs with 

sustained high coverage, 200-2005. J Public Health Management Practice 2010;16(1):E9-E17. 

McElligott JT, Darden PM. Are patient-held vaccination records associated with improved vaccination 

coverage rates? Pediatrics 2010;125(3):e467-e472. 

Mennito SH, Darden PM. Impact of practice policies on pediatric immunization rates. J Pediatr 

2010;156:618-622. 

Santibanez TA, Singleton JA, Shefer A, Cohn A. Changes in measurement of Haemophilus influenzae

serotype b (Hib) vaccination coverage – National Immunization Survey, United States, 2009. MMWR 

2010 Aug 27;59(33):1069-1072. 

Scanlon KS, Grummer-Strawn L, Li R, Chen J. Racial and ethnic differences in breastfeeding initiation 

and duration, by state – National Immunization Survey, United States, 2004-2008. MMWR 2010 Mar 

26;59(11):327-334. 

Smith PJ, Humiston SG, Parnell T, Vannice KS, Salmon DA. The association between intentional delay 

of vaccine administration and timely childhood vaccination coverage. Public Health Rep 2010;125:534-

541. 

Wooten KG, Kolasa M, Singleton JA, Shefer A. National, state, and local area vaccination coverage 

among children aged 19-35 months – United States, 2009. MMWR 2010 Sep 17;59(36):1171-1177. 

Zhao Z, Luman ET. Progress Toward eliminating disparities in vaccination coverage among U.S. 

children, 2000–2008. Am J Prev Med 2010;38(2):127–137. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 88

13. References

The American Association for Public Opinion Research (2016). Standard Definitions: Final Dispositions 

of Case Codes and Outcome Rates for Surveys. 9th edition. 

Blumberg, S.J., Luke, J.V., Ganesh, N., Davern, M.E., Boudreaux, M.H. and Soderberg, K. (2011). 

Wireless substitution: State-level estimates from the National Health Interview Survey, January 2007–

June 2010. National Center for Health Statistics. http://www.cdc.gov/nchs/data/nhsr/nhsr039.pdf

Brick, J.M. and Kalton, G. (1996). Handling missing data in survey research. Statistical Methods in 

Medical Research, 5:215–238. 

Council of American Survey Research Organizations (1982). On the Definition of Response Rates: A 

Special Report of the CASRO Task Force on Completion Rates. Council of American Survey Research 

Organizations: http://www.casro.org. 

Centers for Disease Control and Prevention (1994). Reported vaccine-preventable diseases - United 

States, 1993, and the Childhood Immunization Initiative. MMWR, 43:57-60. 

Centers for Disease Control and Prevention (2002). National Immunization Survey: Guide to Quality 

Control Procedures. http://www.cdc.gov/nchs/data/nis/qcman.pdf. 

Centers for Disease Control and Prevention (2010). Changes in measurement of Haemophilus influenzae

serotype b (Hib) vaccination coverage—National Immunization Survey, United States, 2009. MMWR

2010;59:1069--72. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5933a3.htm. 

Coronado, V.G., Maes, E.F., Rodewald, L.E., Chu, S., Battaglia, M.P., Hoaglin, D.C., Merced, N.L., 

Yusuf, H., Cordero, J.F., and Orenstein, W.A. (2000). Risk factors for underimmunization among 19-35 

month-old children in the United States: National Immunization Survey, July 1996-June 1998. 

Unpublished manuscript, Centers for Disease Control and Prevention, Atlanta. 

Deming, W.E. (1943). Statistical Adjustment of Data. New York: Wiley.

Ezzati-Rice, T.M., Zell, E.R., Battaglia, M.P., Ching, P.L.Y.H., and Wright, R.A. (1995). The design of 

the National Immunization Survey. 1995 Proceedings of the Section on Survey Research Methods,

Alexandria, VA: American Statistical Association, pp. 668-672. 

The Florida Department of Health (2020). Results of the Survey of Immunization Levels in 2 - Year - Old 

Children (2019). http://www.floridahealth.gov/programs-andservices/immunization/resources/surveys/_documents/2yo2019.pdf 

Ford, B.L. (1983). An overview of hot-deck procedures, in: Incomplete data in sample surveys, Madow 

W. G., Olkin I., Rubin D. B. (Eds.), Academic Press, New York, pp. 185-207. 

Gillespie, K. (2019). Retrospective Vaccination Coverage Survey 2013-2014 Results (School Year 2017-

2018). Kansas Department of Health and Environment, Topeka, KS. 

https://www.kdheks.gov/immunize/download/Retrospective_2017-2018.pdf

Hill HA, Yankey D, Elam-Evans LD, Singleton JA, Pingali SC, Santibanez TA. Vaccination Coverage by 

Age 24 Months Among Children Born in 2016 and 2017 — National Immunization Survey-Child, United 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 89

States, 2017–2019. MMWR Morb Mortal Wkly Rep 2020;69:1505–1511. 

DOI: http://dx.doi.org/10.15585/mmwr.mm6942a1

Hill, H.A., Singleton, J.A., Elam-Evans, L.D., Nguyen, K., Pingali, S., Walker, T., et al. (2019). 

Transition from a dual-frame (cell-phone and landline) to a single-frame (cell-phone) sample design: 

Impact on vaccination coverage estimates, National Immunization Survey-Child, 2014-2018. Available 

at: https://www.cdc.gov/vaccines/imz-managers/coverage/childvaxview/pubs-presentations/NIS-childvac-coverage-estimates-2014-2018.html. 

Khare, M., Battaglia, M.P., Huggins, V.J., Stokley, S., Hoaglin, D.C., Wright, R.A., and Rodén, A.-S. 

(2000). Accuracy of vaccination dates reported by immunization providers in the National Immunization 

Survey. 2000 Proceedings of the Section on Survey Research Methods. Alexandria, VA: American 

Statistical Association, pp. 665-670. 

Khare, M., Battaglia, M.P., Stokley, S., Wright, R.A., and Huggins, V.J. (2001). Quality of immunization 

histories reported in the National Immunization Survey. Proceedings of the International Conference on 

Quality in Official Statistics (CD-ROM). Stockholm: Statistics Sweden.

Lumley, T. (2010). Survey Analysis in R. http://faculty.washington.edu/tlumley/survey/ 

Machado, F. (n.d.). Georgia Immunization Study 2017, edited by Tuttle, J., Drenzek, C., and Lovett, S. 

Georgia Department of Public Health, Immunization program / Acute Disease Epidemiology Section, 

Atlanta, GA. https://dph.georgia.gov/sites/dph.georgia.gov/files/Immunizations/GIS_2017_web.pdf

Michigan Department of Health & Human Services (2020). Michigan’s Statewide Quarterly 

Immunization Report Card. 

https://www.michigan.gov/documents/mdhhs/State_Level_ReportCard_621826_7.pdf

Molinari, N., Wolter, K., Skalland, B., Montgomery, R., Khare, M., Smith, P., and Singleton, J. (2011). 

Quanitfying Bias in a Health Surey: Modeling Total Surey Error in the National Immunization Survey. 

Statistics in Medicine, 505-515. 

Mulry, M. H. and Spencer, B. C. (1991). Total Error in PES Estimates of Population. Journal of the 

American Statistical Association, 839-863. 

National Center for Health Statistics (1999). National Health Interview Survey: Research for the 1995-

2004 Redesign. Vital and Health Statistics, Series 2, No. 126 (DHHS publication no. (PHS) 99-1326). 

Hyattsville, MD: National Center for Health Statistics.

National Center for Health Statistics. (2015). National Immunization Survey 2014 Public-Use Data File: 

Documentation, Codebook and Frequencies. Hyattsville, MD.

National Center for Health Statistics. (2016). Natality Data, Public-Use Data Files. 

http://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. 

National Center for Health Statistics. (2017). Natality Data, Public-Use Data Files. 

http://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

National Center for Immunization and Respiratory Diseases. (2020). National Immunization Survey - 

Child 2019 Public-Use Data File: Documentation, Codebook and Frequencies. Atlanta, GA. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 90

NORC at the University of Chicago (NORC) (2011). Modeling Total Survey Error in the 2009 and 2010 

NIS: Young Children and Teens. Report submitted to the Centers for Disease Control and Prevention. 

Chicago, IL: NORC.

Pineau, V., Wolter, K., Skalland, B., Zeng, W., Zhao, Z. and Khare, M. (2012). Modeling Total Survey 

Error in the 2010 National Immunization Survey (NIS): Pre-School Children and Teens. Presented at the 

2012 American Statistical Association (ASA) Joint Statistical Meetings, San Diego, CA. 

Pineau, V., Wolter, K., Skalland, B., Zeng, W., Black, C., Dorell, C., Khare, M., and Yankey, D. (2013). 

Modeling Total Surey Error in the 2011 National Immunization Survey (NIS): Pre-School Children and 

Teens. Presented at the 2013 American Statistical Association (ASA) Joint Statistical Meetings, Montreal, 

Canada. 

Research Triangle Institute (2008). SUDAAN Language Manual, Release 9.0. Research Triangle Park, 

NC: Research Triangle Institute.

Robinson, C.L., Bernstein, H., Romero, J.R., and Szilagyi, P. (2019). Advisory committee on 

immunization practices recommended immunization schedule for children and adolescents aged 18 years 

or younger – United States, 2019. MMWR 68(5): 112-114. 

Rosenbaum, P.R. (1987). Model-based direct adjustment. Journal of the American Statistical Association, 

82:387-394. 

Rosenbaum, P.R. and Rubin, D.B. (1983). The central role of the propensity score in observational 

studies for causal effects. Biometrika, 70:41-55. 

Rosenbaum, P.R. and Rubin, D.B. (1984). Reducing bias in observational studies using subclassification 

on the propensity score. Journal of the American Statistical Association, 79:516-534. 

SAS Institute Inc. (2009). SAS/STAT User’s Guide, Version 8. Cary, NC: SAS Institute Inc. 

Singleton, J.A. (2019). Evolving Approaches for Vaccination Coverage Assessment of Young Children. 

Presented at the American Immunization Registry Association National Meeting, Indianapolis, IN, 

August, 2019. 

Singleton, J.A., Hill, H., Yankey, D., Zhao, Z., Fredua, B., Li, Q., Elam-Evans, L., Ma, Q., Skalland, B., 

Tao, X., and Wolter, K. (2019). Monitoring Vaccination Coverage by Annual Birth Cohort: A Paradigm 

Shift. Poster presented at the conference of the American Association for Public Opinion Research, 

Toronto, May, 2019. 

Skalland, B., Wolter, K., Ma, Q., Pineau, V., Singleton, J., Yankey, D., and Smith, P. (2016). A Total 

Survey Error Framework and Assessment for the 2013 National Immunization Survey. Presented at the 

International Total Survey Error Workshop, Sydney, Australia, October, 2016. 

Smith, P.J., Battaglia, M.P., Huggins, V.J., Hoaglin, D.C., Rodén, A.-S., Khare, M., Ezzati-Rice, T.M., 

and Wright, R.A. (2001a). Overview of the sampling design and statistical methods used in the National 

Immunization Survey. American Journal of Preventive Medicine, 20(4S):17-24. 

Smith, P.J., Rao, J.N.K., Battaglia, M.P., Ezzati-Rice, T.M., Daniels, D., and Khare, M. (2001b). 

Compensating for Provider Non-response Using Response Propensities to Form Adjustment Cells: The 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 91

National Immunization Survey. Vital and Health Statistics, Series 2, No. 133 (DHHS publication no. 

(PHS) 2001-1333). Hyattsville, MD: National Center for Health Statistics.

Smith, P.J., Hoaglin, D.C., Battaglia, M.P., Khare, M., and Barker, L.E. (2005), Statistical Methodology 

of the National Immunization Survey: 1994-2002. National Center for Health Statistics. Vital Health Stat 

2(138). 

StataCorp (2005). Stata Statistical Software: Release 9. College Station, TX: StataCorp LP. 

Tennessee Department of Health (2020). Results of the 2019 Immunization Status Survey of 24 Month 

Old Children in Tennessee. https://www.tn.gov/content/dam/tn/health/documents/cedepweeklyreports/2019-24-Month-Old-Survey.pdf

U.S. Census Bureau (2017). American Community Survey: 1-Year Public Use Microdata Sample 

(PUMS) (2016). Retrieved from http://www.census.gov/programs-surveys/acs/data/pums.html 

U.S. Census Bureau (2018). American Community Survey: 1-Year Public Use Microdata Sample 

(PUMS) (2017). Retrieved from http://www.census.gov/programs-surveys/acs/data/pums.html 

U.S. Census Bureau (2019). American Community Survey: 1-Year Public Use Microdata Sample 

(PUMS) (2018). Retrieved from http://www.census.gov/programs-surveys/acs/data/pums.html 

Virginia Department of Health. (2019). Virginia Immunization Survey, SY 2019 Single Antigen 

Coverage Rates (%) at 24 Months of Age for PubKG, PrivKG, Combined KG & DC. 

https://www.vdh.virginia.gov/content/uploads/sites/11/2016/04/VAISAgRates.pdf

Wall, T.P., Kochanek, K.M., Fitti, J.E., and Zell, E.R. (1995). The use of real time translation services in 

RDD telephone surveys. Presented at the 1995 Conference of the American Association for Public 

Opinion Research, Fort Lauderdale, FL. 

Washington State Department of Health (n.d.). Public Health Measures. Retrieved from 

https://www.doh.wa.gov/DataandStatisticalReports/HealthDataVisualization/ImmunizationDataDashboar

ds/PublicHealthMeasures

Wisconsin Department of Health Services. (2020). Vaccination Coverage among Wisconsin Children by 

Age 24 Months, by Vaccines or Series, Region of Residence and Year. 

https://www.dhs.wisconsin.gov/publications/p02003a.pdf

Wolter, K. M. (2007). Introduction to Variance Estimation. New York, NY: Springer-Verlag.

Wolter, K., Smith, P., Khare, M., Welch, B., Copeland, K., Pineau, V., and Davis, N. (2017a). Statistical 

Methodology of the National Immunization Survey, 2005-2014. National Center for Health Statistics. 

Vital Health Stat 1(61): 1-96. 

Wolter, K., Pineau, V., Skalland, B., Zeng, W., Singleton, J., Khare, M., Zhao, Z., Yankey, D., and Smith, 

P. (2017b). Total survey error assessment for socio-demographic subgroups in the 2012 U.S. National 

Immunization Survey. In Biemer, P., De Leeuw, E., Edwards, B., Kreuter, F., Lyberg, L., Tucker, C., and 

West, B. (Eds.) Total Survey Error in Practice, John Wiley & Sons, Inc., Hoboken, NJ, USA. 

Yankey, D., Hill, H.A., Elam-Evans, L.D., Khare, M., Singleton, J.A., Pineau, V., and Wolter, K. (2015). 

Estimating change in telephone survey bias in an era of declining response rates and transition to wireless 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Page 92

telephones – evidence from the National Immunization Survey (NIS), 1995-2013. Presented at the annual 

conference of the American Association for Public Opinion Research, Hollywood, FL. 

Zell, E.R., Ezzati-Rice, T.M., Battaglia, M.P., and Wright, R.A. (2000). National Immunization Survey: 

The methodology of a vaccination surveillance system. Public Health Reports, 115(1):65-77. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX A 

Page 93

Appendix A: Glossary of Abbreviations and Terms

3:3:1 The series of 3 or more DTaP vaccinations, 3 or more polio vaccinations, and 1 or 

more MCV vaccinations

4:3:1 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, and 1 or 

more MCV vaccinations

4:3:1:3 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or more 

MCV vaccinations, and 3 or more Hib vaccinations of any type 

4:3:1:3* The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 

(routine Hib) or more MCV vaccinations, and 3 or 4 Hib vaccinations depending on manufacturer 

(routine recommendation) 

4:3:1:3:3 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or more 

MCV vaccinations, 3 or more Hib vaccinations of any type, and 3 or more hepatitis B 

vaccinations

4:3:1:3*:3 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 

(routine Hib) or more MCV vaccinations, 3 or 4 Hib vaccinations depending on manufacturer 

(routine recommendation), and 3 or more hepatitis B vaccinations 

4:3:1:3:3:1 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or more 

MCV vaccinations, 3 or more Hib vaccinations of any type, 3 or more hepatitis B 

vaccinations, and 1 or more varicella vaccinations given at age 12 months or older

4:3:1:3*:3:1 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or 

(routine Hib) more MCV vaccinations, 3 or 4 Hib vaccinations depending on manufacturer (routine 

recommendation), 3 or more hepatitis B vaccinations, and 1 or more varicella 

vaccinations given at age 12 months or older 

4:3:1:3:3:1:3 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or more 

MCV vaccinations, 3 or more Hib vaccinations of any type, 3 or more hepatitis B 

vaccinations, 1 or more varicella vaccinations given at age 12 months or older, and 3 

or more pneumococcal vaccinations 

4:3:1:3*:3:1:3 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or 

(routine Hib) more MCV vaccinations, 3 or 4 Hib vaccinations depending on manufacturer (routine 

recommendation), 3 or more hepatitis B vaccinations, 1 or more varicella 

vaccinations given at age 12 months or older, and 3 or more pneumococcal 

vaccinations

4:3:1:3:3:1:4 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or more 

MCV vaccinations, 3 or more Hib vaccinations of any type, 3 or more hepatitis B 

vaccinations, 1 or more varicella vaccinations given at age 12 months or older, and 4 

or more pneumococcal vaccinations 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX A 

Page 94

4:3:1:3*:3:1:4 The series of 4 or more DTaP vaccinations, 3 or more polio vaccinations, 1 or 

(routine Hib) more MCV vaccinations, 3 or 4 Hib vaccinations depending on manufacturer (routine 

recommendation), 3 or more hepatitis B vaccinations, 1 or more varicella 

vaccinations given at age 12 months or older, and 4 or more pneumococcal 

vaccinations

CATI Computer-assisted telephone interviewing

CDC Centers for Disease Control and Prevention

CII Childhood Immunization Initiative 

DOB Date of birth

DTaP Diphtheria and tetanus toxoids and acellular pertussis vaccine adsorbed

DTP Diphtheria and tetanus toxoids and pertussis vaccine

DT Diphtheria and tetanus toxoids adsorbed

H1N Monovalent 2009 H1N1 influenza 

Hep A Hepatitis A vaccine

Hep B Hepatitis B vaccine

Hib Haemophilus influenzae type b conjugate vaccine 

Hib routine Four or more doses of Hib vaccine of any type, or two or more doses of Hib 

recommendation vaccine of Merck types followed by one dose of Hib vaccine of any type 

Hib shortage Three or more doses of Hib vaccine of any type or two or more doses of Hib

recommendation vaccine of Merck types

 

IAP Immunization Action Plan 

IHQ Immunization history questionnaire 

IIS Immunization Information System

IPV Inactivated poliovirus vaccine

MCV Measles-containing vaccine

MMR Measles, mumps, and rubella vaccine

NCHS National Center for Health Statistics

NCIRD National Center for Immunization and Respiratory Diseases

NIS National Immunization Surveys 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX A 

Page 95

NIS-Child National Immunization Survey-Child

NHIS National Health Interview Survey

NIP National Immunization Program

OPV Oral poliovirus vaccine

PCV Pneumococcal conjugate vaccine

PRC Provider Record Check 

PUF Public-use (Data) File

RDD Random digit dialing 

RV Rotavirus 

SC Shot card 

UTD Up-to-date 

VFC Vaccines for Children 

VAR Varicella vaccine
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX B 

96

Appendix B: Summary Statistics for Sampling Weights by 

Estimation Area

Table B.1: Distribution of Sampling Weights* for Children with Completed Household 

Interviews, National Immunization Survey - Child, 2019 

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient of 

Variation

U.S. National† 33,137 5,638,848.81 1.00 5,375.81 170.17 184.41

Alabama 570 84,564.87 7.15 459.48 148.36 67.36

Alaska 417 14,352.98 2.27 106.22 34.42 62.91

Arizona 516 122,825.86 3.32 672.87 238.03 64.83

Arkansas 713 53,724.47 7.46 240.53 75.35 84.88

California 668 692,638.94 1.70 5,375.81 1036.88 150.28

Colorado 467 94,635.67 2.13 828.43 202.65 94.16

Connecticut 329 51,298.71 2.25 492.40 155.92 73.46

Delaware 505 15,807.35 7.52 76.98 31.30 52.15

District of Columbia 612 12,598.70 5.42 64.69 20.59 80.15

Florida 953 333,773.37 1.59 1,355.74 350.23 106.72

Georgia 667 190,558.89 2.65 997.55 285.70 89.86

Hawaii 468 24,112.93 17.63 134.18 51.52 52.25

Idaho 367 31,918.14 3.91 249.06 86.97 56.31

Illinois 958 212,867.91 2.60 636.02 222.20 70.54

 IL-City of Chicago 298 51,792.03 2.60 520.65 173.80 69.19

 IL-Rest of State 660 161,075.88 6.38 636.02 244.05 68.10

Indiana 527 119,709.08 5.90 639.13 227.15 56.65

Iowa 378 56,069.06 7.25 398.45 148.33 59.12

Kansas 633 53,542.56 2.26 287.97 84.59 81.93

Kentucky 350 78,401.95 8.82 681.35 224.01 71.61

Louisiana 748 86,819.72 3.76 448.29 116.07 107.60

Maine 494 17,495.42 2.81 98.17 35.42 59.58

Maryland 1,343 105,498.23 4.42 295.80 78.55 101.89

Massachusetts 492 104,470.08 2.64 956.87 212.34 109.51

Michigan 636 162,221.08 4.78 819.27 255.06 78.27

Minnesota 415 100,463.05 1.79 998.91 242.08 97.73

Mississippi 655 53,162.75 9.02 249.19 81.16 68.21

Missouri 597 104,028.80 5.94 518.06 174.25 70.36

Montana 485 17,579.87 2.73 105.04 36.25 59.82

Nebraska 404 37,493.02 14.95 211.76 92.80 45.63

Nevada 765 54,052.53 7.21 248.24 70.66 88.15

New Hampshire 426 18,859.79 3.15 132.06 44.27 63.70

New Jersey 684 151,852.82 35.78 799.21 222.01 73.88

New Mexico 974 32,869.40 3.85 117.92 33.75 89.65

New York 1,261 324,738.48 1.66 1,606.45 257.52 107.71

 NY-City of New York 839 160,885.13 4.37 630.03 191.76 82.92

 NY-Rest of State 422 163,853.35 1.66 1,606.45 388.28 101.13

North Carolina 647 177,580.47 2.80 866.19 274.47 75.72

North Dakota 442 15,615.90 9.89 91.44 35.33 50.33

Ohio 560 196,363.50 6.93 1,076.74 350.65 71.50

Oklahoma 606 72,262.12 4.77 331.14 119.24 60.45

Oregon 341 66,060.03 1.90 577.71 193.72 66.16

Pennsylvania 1,093 200,324.12 7.59 976.11 183.28 118.31
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX B 

97

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient of 

Variation

 PA-Philadelphia County 462 31,398.42 7.81 217.30 67.96 66.42

 PA-Rest of State 631 168,925.70 7.59 976.11 267.71 93.84

Rhode Island 420 15,540.87 12.92 101.01 37.00 45.65

South Carolina 610 82,108.98 3.22 407.25 134.60 68.49

South Dakota 437 17,939.03 3.21 104.09 41.05 54.08

Tennessee 378 119,220.27 8.52 1,057.80 315.40 89.42

Texas 3,068 576,489.40 2.09 1,014.29 187.90 108.19

 TX-Bexar County 443 40,493.35 6.30 274.34 91.41 60.83

 TX-City of Houston 397 78,214.27 9.71 613.60 197.01 66.25

 TX-Dallas County 500 60,343.79 4.28 326.52 120.69 53.67

 TX-El Paso County 389 17,982.02 17.83 128.45 46.23 49.05

 TX-Rest of State 1,339 379,455.97 2.09 1,014.29 283.39 91.47

Utah 463 71,936.94 1.90 396.89 155.37 55.57

Vermont 611 8,289.28 1.63 40.00 13.57 62.53

Virginia 725 144,097.46 11.42 961.61 198.76 133.14

Washington 723 129,938.50 1.00 649.21 179.72 83.29

West Virginia 586 27,357.73 14.84 115.23 46.69 42.29

Wisconsin 518 94,261.37 3.70 505.98 181.97 61.22

Wyoming 432 8,456.37 5.70 52.15 19.57 50.08

 

Puerto Rico 662 32,198.23 7.64 145.58 48.64 51.65

U.S. Virgin Islands 258 1,518.79 1.00 21.51 5.89 86.23

Guam 395 4,841.45 1.27 42.94 12.26 80.09

* Distribution of RDDWT_C_TERR. 

† Excludes U.S. territories. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX B 

98

Table B.2: Distribution of Sampling Weights* for Children with Adequate Provider Data, 

National Immunization Survey - Child, 2019 

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

U.S. National† 16,365 5,638,848.81 1.08 13,396.24 344.57 200.43

Alabama 278 84,564.87 11.97 1,141.22 304.19 94.31

Alaska 240 14,352.98 4.60 193.55 59.80 67.19

Arizona 260 122,825.86 9.32 1,476.76 472.41 74.57

Arkansas 376 53,724.47 16.52 505.23 142.88 96.77

California 292 692,638.94 3.36 13,396.24 2372.05 147.57

Colorado 240 94,635.67 3.17 1,474.58 394.32 101.91

Connecticut 159 51,298.71 4.17 1,143.28 322.63 92.04

Delaware 249 15,807.35 10.63 187.21 63.48 65.56

District of Columbia 285 12,598.70 6.24 160.70 44.21 100.83

Florida 390 333,773.37 5.84 3,471.55 855.83 116.98

Georgia 301 190,558.89 5.80 2,512.84 633.09 103.79

Hawaii 210 24,112.93 22.65 363.25 114.82 76.72

Idaho 190 31,918.14 8.32 523.63 167.99 70.37

Illinois 456 212,867.91 12.81 1,597.86 466.82 89.77

 IL-City of Chicago 148 51,792.03 13.09 1,078.51 349.95 71.83

 IL-Rest of State 308 161,075.88 12.81 1,597.86 522.97 89.75

Indiana 280 119,709.08 16.47 1,248.40 427.53 73.23

Iowa 203 56,069.06 14.30 738.67 276.20 61.01

Kansas 398 53,542.56 14.05 467.64 134.53 86.61

Kentucky 182 78,401.95 13.29 1,535.77 430.78 85.02

Louisiana 355 86,819.72 3.93 1,120.08 244.56 125.24

Maine 238 17,495.42 2.87 246.06 73.51 85.12

Maryland 700 105,498.23 7.26 586.77 150.71 107.30

Massachusetts 270 104,470.08 3.00 1,884.73 386.93 127.59

Michigan 324 162,221.08 7.82 1,778.41 500.68 95.67

Minnesota 190 100,463.05 5.17 1,958.82 528.75 102.83

Mississippi 307 53,162.75 16.76 615.61 173.17 90.76

Missouri 321 104,028.80 7.56 1,123.63 324.08 82.57

Montana 256 17,579.87 12.78 202.60 68.67 70.34

Nebraska 228 37,493.02 23.65 416.78 164.44 46.84

Nevada 387 54,052.53 7.21 537.89 139.67 104.56

New Hampshire 223 18,859.79 7.95 262.00 84.57 83.47

New Jersey 264 151,852.82 52.49 2,189.75 575.20 93.43

New Mexico 505 32,869.40 5.21 245.19 65.09 109.55

New York 527 324,738.48 3.17 3,385.84 616.20 113.89

 NY-City of New York 326 160,885.13 9.15 1,857.04 493.51 94.30

 NY-Rest of State 201 163,853.35 3.17 3,385.84 815.19 115.01

North Carolina 337 177,580.47 6.37 1,872.36 526.95 91.76

North Dakota 232 15,615.90 17.96 205.89 67.31 60.77

Ohio 266 196,363.50 17.18 2,599.53 738.21 91.39

Oklahoma 302 72,262.12 19.77 710.97 239.28 70.31

Oregon 161 66,060.03 6.51 1,450.11 410.31 78.74

Pennsylvania 500 200,324.12 12.90 2,156.24 400.65 118.25

 PA-Philadelphia County 196 31,398.42 12.90 544.79 160.20 91.12

 PA-Rest of State 304 168,925.70 23.37 2,156.24 555.68 97.65

Rhode Island 249 15,540.87 14.56 177.73 62.41 57.73

South Carolina 287 82,108.98 6.68 1,009.69 286.09 87.42

South Dakota 240 17,939.03 16.92 198.19 74.75 65.18
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX B 

99

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

Tennessee 179 119,220.27 18.04 2,464.64 666.04 100.42

Texas 1,397 576,489.40 3.36 2,156.22 412.66 114.62

 TX-Bexar County 204 40,493.35 15.54 608.47 198.50 73.08

 TX-City of Houston 160 78,214.27 29.08 1,627.02 488.84 84.16

 TX-Dallas County 198 60,343.79 26.49 1,002.38 304.77 70.75

 TX-El Paso County 186 17,982.02 20.97 280.25 96.68 61.20

 TX-Rest of State 649 379,455.97 3.36 2,156.22 584.68 99.87

Utah 256 71,936.94 3.03 822.67 281.00 69.77

Vermont 318 8,289.28 6.12 75.64 26.07 61.53

Virginia 358 144,097.46 6.81 2,223.46 402.51 138.46

Washington 389 129,938.50 1.08 1,224.26 334.03 96.51

West Virginia 280 27,357.73 22.26 263.11 97.71 55.13

Wisconsin 259 94,261.37 8.20 1,171.50 363.94 81.24

Wyoming 271 8,456.37 7.07 90.85 31.20 58.39

 

Puerto Rico 197 32,198.23 17.44 493.86 163.44 63.28

U.S. Virgin Islands 111 1,518.79 1.49 56.93 13.68 83.12

Guam 176 4,841.45 1.59 110.18 27.51 94.60

* Distribution of PROVWT_C_TERR. † Excludes U.S. territories. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX C 

100

Appendix C: Flags for Inconsistent Values in the 

Breastfeeding Data 

Two different types of inconsistency can arise in breastfeeding data. The first is that the duration of any 

breastfeeding can exceed the age of the child, and the second is that the age of the child when first fed 

formula can exceed the age of child. BF_ENDR06 stores the duration of any breastfeeding, and 

BF_ENDFL06 flags the inconsistency; BF_FORMR08 stores the age of the child when first fed formula, 

and BF_FORMFL06 flags the inconsistency. 

1. Both BF_ENDR06 and BF_FORMR08 are formulated using the following conversion 

factors: 

if unit=1(days) then BF_ENDR06 = number x 1 

if unit=2(weeks) then BF_ENDR06 = number x 7 

if unit=3(months) then BF_ENDR06 = number x 30.4375 

if unit=4(years) then BF_ENDR06 = number x 365.25 

if unit=1(days) then BF_FORMR08 = number x 1 

if unit=2(weeks) then BF_FORMR08 = number x 7 

if unit=3(months) then BF_FORMR08 = number x 30.4375 

if unit=4(years) then BF_FORMR08 = number x 365.25 

2. Flagging BF_ENDR06 when the duration of any breastfeeding exceeds the age in days with a 

buffer for different units: 

if unit=1(days) flag when BF_ENDR06 > age + 1 

if unit=2(weeks) flag when BF_ENDR06 > age + 3 

if unit=3(months) flag when BF_ENDR06 > age + 15 

if unit=4(years) flag when BF_ENDR06 > age + 182 

The different buffers allow for the impact of rounding durations upward in the specified units (for 

example, 50 days might be reported as 2 months). 

3. Flagging BF_FORMR08 when the age when first fed formula exceeds the age in days with a 

buffer for different units: 

if unit=1(days) flag when BF_FORMR08 > age + 1 

if unit=2(weeks) flag when BF_FORMR08 > age + 3 

if unit=3(months) flag when BF_FORMR08 > age + 15 

if unit=4(years) flag when BF_FORMR08 > age + 182

The different buffers allow for the impact of rounding durations upward in the specified units (for 

example, 50 days might be reported as 2 months). 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

101

Appendix D: Programs for Estimation: Examples of the Use 

of SUDAAN, SAS, and R to Estimate Vaccination Coverage 

Rates and Their Standard Errors, and an Example of the 

Production of a Cross-Tabulation and Chart

I. SUDAAN (RTI, 2008) Page 102

II. SAS (SAS, 2009) Page 115 

III. ‘R’ (Lumley, 2009) Page 126 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

102

A. SUDAAN

**********************;

title1 'SUD_IAP.SAS'; 

********************************************************************** 

THIS PROGRAM WILL PRODUCE ESTIMATION AREA ESTIMATES AND STANDARD ERRORS FOR 

P_UTD431H314_ROUT_S USING SAS CALLABLE SUDAAN. 

SUDAAN NOTES:

1. ALL VARIABLES USED MUST BE NUMERIC.

2. VARIABLES IN THE SUBGROUP STATEMENT MUST HAVE VALUES 1,2,..K

WHERE K IS THE NUMBER OF LEVELS FOR EACH VARIABLE.

3. DATA MUST BE SORTED ACCORDING TO THE SAMPLE DESIGN VARIABLES

(STRATUM AND PRIMARY SAMPLING UNIT), SPECIFIED IN THE

NEST STATEMENT.

**********************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let estiap=estiap19; * --- ESTIMATION AREA VARIABLE TO USE ---*;

%let wt=provwt_c; * --- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. 

Use PROVWT_C_TERR to include territories) --*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

/*

THE FOLLOWING FORMAT WILL BE USED FOR P_UTD431H314_ROUT_S. 

ORIGINAL VALUES OF P_UTD431H314_ROUT_S ARE 1,0. 

MUST BE CONVERTED TO 1,2 IN SUDAAN.

*/

value putd431h314f 

1='4:3:1:3:3:1:4 Up-to-Date'

2='Not 4:3:1:3:3:1:4 Up-to-Date'; 

value estiapf

. = "Missing"

0 = "US Total"

1 = "CT"

2 = "MA"

4 = "ME"

5 = "NH"

6 = "RI"

7 = "VT"

8 = "NJ"

10 = "NY-Rest of State"

11 = "NY-City of New York"

12 = "DC"
Data User’s Guide for the 2019 NIS

-Child Public-Use Data FileAPPENDIX D 

103

13 = "DE"

14 = "MD"

16 = "PA-Rest of State"

17 = "PA-Philadelphia County"

18 = "VA"

19 = "WV"

20 = "AL"

22 = "FL"

25 = "GA"

27 = "KY"

28 = "MS"

29 = "NC"

30 = "SC"

31 = "TN"

34 = "IL-Rest of State"

35 = "IL-City of Chicago"

36 = "IN"

38 = "MI"

40 = "MN"

41 = "OH"

44 = "WI"

46 = "AR"

47 = "LA"

49 = "NM"

50 = "OK"

51 = "TX-Rest of State"

52 = "TX-Dallas County" 

53 = "TX-El Paso County" 

54 = "TX-City of Houston"

55 = "TX-Bexar County"

56 = "IA"

57 = "KS"

58 = "MO"

59 = "NE"

60 = "CO"

61 = "MT"

62 = "ND"

63 = "SD"

64 = "UT"

65 = "WY"

66 = "AZ"

68 = "CA"

72 = "HI"

73 = "NV"

74 = "AK"

75 = "ID"

76 = "OR"

77 = "WA"

106 = "Puerto Rico" 

; 

run; 

data sud_file; 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

104

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S &estiap &wt &strat);

if P_UTD431H314_ROUT_S=0 then P_UTD431H314_ROUT_S=2; *--- CONVERT P_UTD431H314_ROUT_S=0 TO 

P_UTD431H314_ROUT_S=2 ---*; 

nseqnumh=1*seqnumhh; *---CONVERT HOUSEHOLD ID SEQNUMHH FROM CHARACTER TO NUMERIC ---*;

run; 

*=== SORT BY NEST VARIABLES: STRATUM (STRATUM) NSEQNUMH (PRIMARY SAMPLING UNIT) ===*;

proc sort; 

by &strat nseqnumh;

run; 

proc crosstab data=sud_file filetype=sas design=wr;

weight &wt;

nest &strat nseqnumh;

subgroup &estiap P_UTD431H314_ROUT_S ; 

levels 106 2 ; 

tables &estiap * P_UTD431H314_ROUT_S ; 

print nsum wsum rowper serow/style=nchs ; 

rtitle "4:3:1:3:3:1:4 ESTIMATES BY ESTIMATION AREA"; 

rformat &estiap estiapf.; 

rformat P_UTD431H314_ROUT_S putd431h314f.; 

output rowper serow/filename=sud_est filetype=sas replace; 

run; 

proc print data=sud_est(where=(P_UTD431H314_ROUT_S=1 and rowper ne .)) noobs label; 

format &estiap estiapf.; 

var &estiap rowper serow ;

label

rowper='Percent 4:3:1:3:3:1:4 Up-to-Date'

serow='Standard Error'

; 

title "4:3:1:3:3:1:4 ESTIMATES BY ESTIMATION AREA"; 

run; 

**********************;

title1 'SUDSTATE.SAS'; 

************************************************************************* 

THIS PROGRAM WILL PRODUCE STATE ESTIMATES AND STANDARD ERRORS

FOR P_UTD431H314_ROUT_S USING SAS CALLABLE SUDAAN.

NOTE: THE STATE VARIABLE IS BASED ON FIPSTATE CODES, THERE ARE

NO STATES WITH FIPS CODES 3,7,14,43,52,57-71,73-78. 

SUDAAN NOTES:

1. ALL VARIABLES USED MUST BE NUMERIC.

2. VARIABLES IN THE SUBGROUP STATEMENT MUST HAVE VALUES 1,2,..K

WHERE K IS THE NUMBER OF LEVELS FOR EACH VARIABLE.

3. DATA MUST BE SORTED ACCORDING TO THE SAMPLE DESIGN VARIABLES

(STRATUM AND PRIMARY SAMPLING UNIT), SPECIFIED IN THE

NEST STATEMENT.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

105

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS STORED ---*; 

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_c; *--- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. Use 

PROVWT_C_TERR to include territories) --*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

/*

THE FOLLOWING FORMAT WILL BE USED FOR P_UTD431H314_ROUT_S. 

ORIGINAL VALUES OF P_UTD431H314_ROUT_S ARE 1,0. 

MUST BE CONVERTED TO 1,2 IN SUDAAN.

*/

value putd431h314f 

1='4:3:1:3:3:1:4 Up-to-Date'

2='Not 4:3:1:3:3:1:4 Up-to-Date'

; 

value statef

0 ='U.S. Total'

1 ='Alabama '

2 ='Alaska '

4 ='Arizona '

5 ='Arkansas '

6 ='California '

8 ='Colorado '

9 ='Connecticut '

10 ='Delaware '

11 ='District of Columbia'

12 ='Florida '

13 ='Georgia '

15 ='Hawaii '

16 ='Idaho '

17 ='Illinois '

18 ='Indiana '

19 ='Iowa '

20 ='Kansas '

21 ='Kentucky '

22 ='Louisiana '

23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

26 ='Michigan '

27 ='Minnesota '

28 ='Mississippi '

29 ='Missouri '

30 ='Montana '

31 ='Nebraska '

32 ='Nevada '

33 ='New Hampshire '

34 ='New Jersey '

35 ='New Mexico '
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

106

36 ='New York '

37 ='North Carolina '

38 ='North Dakota '

39 ='Ohio '

40 ='Oklahoma '

41 ='Oregon '

42 ='Pennsylvania '

44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

55 ='Wisconsin '

56 ='Wyoming '

72 ='Puerto Rico ' 

; 

run; 

data sud_file; 

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S state &wt &strat);

if P_UTD431H314_ROUT_S=0 then P_UTD431H314_ROUT_S=2; *** CONVERT P_UTD431H314_ROUT_S=0 TO 

P_UTD431H314_ROUT_S=2 ***;

nseqnumh=1*seqnumhh; *** CONVERT HOUSEHOLD ID SEQNUMH FROM CHARACTER TO NUMERIC ***;

run; 

*=== SORT BY NEST VARIABLES: STRATUM (STRATUM) NSEQNUMH (PRIMARY SAMPLING UNIT) ===*;

proc sort; 

by &strat nseqnumh;

run; 

proc crosstab data=sud_file filetype=sas design=wr;

weight &wt;

nest &strat nseqnumh;

subgroup state P_UTD431H314_ROUT_S ; 

levels 72 2 ; 

tables state * P_UTD431H314_ROUT_S ; 

print nsum wsum rowper serow/style=nchs ; 

rtitle "4:3:1:3:3:1:4 ESTIMATES BY STATE"; 

rformat state statef.; 

rformat P_UTD431H314_ROUT_S putd431h314f.; 

output rowper serow / filename=sud_est2 filetype=sas replace;

run; 

*** EXCLUDE 3,7,14,43,52, 57-71, 73-78 THERE ARE NO STATES WITH THESE FIPS CODES *** ;

option spool; 

proc print data=sud_est2(where=(P_UTD431H314_ROUT_S=1 and rowper ne . 

& state notin (3,7,14,43,52) and not(57<=state<=71) and not (73<=state<=78)))label noobs; 

format state statef.; 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

107

var state rowper serow ;

label

rowper='Percent 4:3:1:3:3:1:4 Up-to-Date'

serow='Standard Error'

; 

title "4:3:1:3:3:1:4 ESTIMATES BY STATE"; 

run; 

option nospool; 

**********************;

title1 'PROG_3.SAS'; 

************************************************************************* 

THIS PROGRAM WILL PRODUCE A TABLE OF HAD_CPOX BY STATE FOR ALL RDD

COMPLETES USING RDDWT_C. THE PROGRAM USES SAS CALLABLE SUDAAN.

SUDAAN NOTES:

1. ALL VARIABLES USED MUST BE NUMERIC.

2. VARIABLES IN THE SUBGROUP STATEMENT MUST HAVE VALUES 1,2,..K

WHERE K IS THE NUMBER OF LEVELS FOR EACH VARIABLE.

3. DATA MUST BE SORTED ACCORDING TO THE SAMPLE DESIGN VARIABLES

(STRATUM AND PRIMARY SAMPLING UNIT), SPECIFIED IN THE

NEST STATEMENT.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS STORED ---*; 

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=rddwt_c; * --- WEIGHT TO USE (RDDWT_C is the single-frame cell-phone weight excluding territories. Use 

RDDWT_C_TERR to include territories) ---*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

/*

THE FOLLOWING FORMAT WILL BE USED FOR HAD_CPOX. 

*/

value hadcpoxf 

1='Yes'

2='No'

; 

value statef

0 ='U.S. Total '

1 ='Alabama '

2 ='Alaska '

4 ='Arizona '

5 ='Arkansas '

6 ='California '

8 ='Colorado '

9 ='Connecticut '

10 ='Delaware '
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

108

11 ='District of Columbia'

12 ='Florida '

13 ='Georgia '

15 ='Hawaii '

16 ='Idaho '

17 ='Illinois '

18 ='Indiana '

19 ='Iowa '

20 ='Kansas '

21 ='Kentucky '

22 ='Louisiana '

23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

26 ='Michigan '

27 ='Minnesota '

28 ='Mississippi '

29 ='Missouri '

30 ='Montana '

31 ='Nebraska '

32 ='Nevada '

33 ='New Hampshire '

34 ='New Jersey '

35 ='New Mexico '

36 ='New York '

37 ='North Carolina '

38 ='North Dakota '

39 ='Ohio '

40 ='Oklahoma '

41 ='Oregon '

42 ='Pennsylvania '

44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

55 ='Wisconsin '

56 ='Wyoming '

72 ='Puerto Rico ' 

; 

run; 

data sud_file; 

set &in_file(keep= seqnumhh seqnumc state had_cpox &wt &strat);

nseqnumh=1*seqnumhh; *** CONVERT HOUSEHOLD ID SEQNUMH FROM CHARACTER TO NUMERIC ***;

run; 

*=== SORT BY NEST VARIABLES: STRATUM (STRATUM) NSEQNUMH (PRIMARY SAMPLING UNIT) ===*;
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

109

proc sort; 

by &strat nseqnumh;

run; 

proc crosstab data=sud_file filetype=sas design=wr;

weight &wt;

nest &strat nseqnumh;

subgroup state had_cpox ; 

levels 72 2 ; 

tables state * had_cpox ;

print nsum wsum rowper serow/style=nchs ;

rtitle "HAD_CPOX ESTIMATES BY STATE"; 

rtitle "WEIGHT = &WT"; 

rformat state statef.; 

rformat had_cpox hadcpoxf.; 

output rowper serow / filename=sud_est3 filetype=sas replace; 

run; 

*** EXCLUDE 3,7,14,43,52, 57-71, 73-78 THERE ARE NO STATES WITH THESE FIPS CODES *** ;

option spool; 

proc print data=sud_est3(where=(had_cpox=1 and rowper ne .

& state notin (3,7,14,43,52) and not (57<=state<=71) and not (73<=state<=78))) label noobs; 

format state statef.; 

var state rowper serow ;

label

rowper='Percent HAD_CPOX = Yes'

serow='Standard Error'

; 

title "CHILD HAD CHICKEN POX BY STATE"; 

run; 

option nospool; 

**********************;

title1 'PROG_4.SAS'; 

************************************************************************* 

TABLE OF P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. SAVE % UTD

ESTIMATES (NOT S.E.'S) FOR USE IN THE PROGRAM CHART_4.

THIS PROGRAM WILL PRODUCE ESTIMATES USING SAS CALLABLE SUDAAN.

SUDAAN NOTES:

1. ALL VARIABLES USED MUST BE NUMERIC.

2. VARIABLES IN THE SUBGROUP STATEMENT MUST HAVE VALUES 1,2,..K

WHERE K IS THE NUMBER OF LEVELS FOR EACH VARIABLE.

3. DATA MUST BE SORTED ACCORDING TO THE SAMPLE DESIGN VARIABLES

(STRATUM AND PRIMARY SAMPLING UNIT), SPECIFIED IN THE

NEST STATEMENT.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

110

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

libname out 'c:\nispuf19'; *--- SPECIFY THE PATH FOR WHERE YOU WANT THE CHART OUTPUT TO GO ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_c; *--- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. Use 

PROVWT_C_TERR to include territories) ---*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

%let qtr_lab=Q1/2019 - Q4/2019; *NIS 4 QUARTER PERIOD*;

proc format; 

/*

THE FOLLOWING FORMAT WILL BE USED FOR P_UTD431H314_ROUT_S. 

ORIGINAL VALUES OF P_UTD431H314_ROUT_S ARE 1,0. 

MUST BE CONVERTED TO 1,2 IN SUDAAN.

*/

value putd431h314f 

1='4:3:1:3:3:1:4 Up-to-Date'

2='Not 4:3:1:3:3:1:4 Up-to-Date'

; 

VALUE race_kf

1 = "WHITE ONLY"

2 = "BLACK ONLY"

3 = "OTHER AND MULTIPLE RACE"

; 

VALUE incpvr2f 

1 = "ABOVE, > $75,000"

2 = "ABOVE, <= $75,000"

3 = "BELOW"

4 = "UNKNOWN"

; 

value statef

0 ='U.S. Total '

1 ='Alabama '

2 ='Alaska '

4 ='Arizona '

5 ='Arkansas '

6 ='California '

8 ='Colorado '

9 ='Connecticut '

10 ='Delaware '

11 ='District of Columbia '

12 ='Florida '

13 ='Georgia '

15 ='Hawaii '

16 ='Idaho '

17 ='Illinois '

18 ='Indiana '

19 ='Iowa '

20 ='Kansas '

21 ='Kentucky '

22 ='Louisiana '
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23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

26 ='Michigan '

27 ='Minnesota '

28 ='Mississippi '

29 ='Missouri '

30 ='Montana '

31 ='Nebraska '

32 ='Nevada '

33 ='New Hampshire '

34 ='New Jersey '

35 ='New Mexico '

36 ='New York '

37 ='North Carolina '

38 ='North Dakota '

39 ='Ohio '

40 ='Oklahoma '

41 ='Oregon '

42 ='Pennsylvania '

44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

55 ='Wisconsin '

56 ='Wyoming '

72 ='Puerto Rico ' 

; 

run; 

data sud_file; 

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S race_k incpov1 &wt &strat); 

nseqnumh=1*seqnumhh; *** CONVERT HOUSEHOLD ID SEQNUMH FROM CHARACTER TO NUMERIC ***;

if P_UTD431H314_ROUT_S=0 then P_UTD431H314_ROUT_S=2; *** CONVERT P_UTD431H314_ROUT_S=0 TO 

P_UTD431H314_ROUT_S=2 ***;

run; 

*=== SORT BY NEST VARIABLES: STRATUM (STRATUM) NSEQNUMH (PRIMARY SAMPLING UNIT) ===*;

proc sort; 

by &strat nseqnumh;

run; 

proc freq; 

tables P_UTD431H314_ROUT_S incpov1 race_k; 

title1 "Table 4A. &qtr_lab: Unweighted Frequencies"; 

run; 
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proc crosstab data=sud_file filetype=sas design=wr;

weight &wt;

nest &strat nseqnumh;

subgroup incpov1 race_k P_UTD431H314_ROUT_S ; 

levels 4 3 2 ; 

tables (incpov1 * race_k * P_UTD431H314_ROUT_S) ;

print nsum wsum rowper="4:3:1:3:3:1:4 Up-to-Date (ROWPER)"

serow="Standard Error (SEROW)" /style=nchs ;

rtitle "Table 4B. &qtr_lab, Percent 4:3:1:3:3:1:4 Up-to-Date and Estimated Standard Errors"; 

rtitle "WEIGHT = &WT"; 

rformat P_UTD431H314_ROUT_S putd431h314f.; 

rformat incpov1 incpvr2f.; 

rformat race_k race_kf.; 

output rowper serow / filename=sud_est4 filetype=sas replace; 

run; 

data out.sud_est4; 

set sud_est4(where=(P_UTD431H314_ROUT_S=1 & incpov1 > 0 & race_k > 0));

keep incpov1 race_k rowper serow; 

label rowper='4:3:1:3:3:1:4 Up-to-Date'; 

format rowper 5.2; 

format serow 5.2; 

run; 

proc print data=out.sud_est4 label; 

format race_k race_kf.; 

format incpov1 incpvr2f.; 

title "Table 4B. &qtr_lab, 4:3:1:3:3:1:4 ESTIMATES AND STANDARD ERRORS BY INCPOV1 BY RACE_K"; 

run; 

**********************;

title1 'SAS_GRAPH_4.SAS'; 

************************************************************************* 

THIS PROGRAM BUILDS OFF OF THE PROGRAM SAS_PROG_4. IT PRODUCES A CHART OF

P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. IT CREATES A BAR CHART IN SAS GRAPH FOR

THE 4X3 = 12 CELLS. THE OUTPUT OF THE FOLLOWING EXAMPLE IS ATTACHED AT THE

END.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

%let out='c:\nispuf19'; *--- SPECIFY THE PATH FOR WHERE YOU WANT THE CHART

OUTPUT TO GO ---*;

%let in_file=dd.sud_est4; *--- NAME OF SAS DATASET OUTPUT FROM PROG_4 ---*;

%let qtr_lab=Q1/2019 - Q4/2019; *NIS 4 QUARTER PERIOD*;

proc format; 

value incpvr2f

1 = "ABOVE, > $75,000"

2 = "ABOVE, <= $75,000"
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3 = "BELOW"

4 = "UNKNOWN"

; 

value race_kf

1 = "WHITE ONLY"

2 = "BLACK ONLY"

3 = "OTHER/MULT RACE"

; 

run; 

data sud_est4;

set &in_file;

format rowper 3.

race_k race_kf.

incpov1 incpvr2f.

; 

label

race_k = 'Race of Child'

incpov1 = 'Poverty Status'

; 

filename odsout &out; 

ods listing close; 

/* SET THE GRAPHICS ENVIRONMENT */

goptions reset=global gunit=pct border

ftext=swissb htitle=4 htext=1.5

device=gif

; 

ods html body='graph_4_sud.html' path=odsout; 

run; 

title1 h=12pt "Percentage of Children Up-to-Date with Vaccine Series 4:3:1:3:3:1:4"; 

title2 h=12pt "by Race and Poverty Status, National Immunization Survey - Child, 2019"; 

footnote j=r 'graph_4sud'; 

proc sgplot data=sud_est4; 

styleattrs datacolors=(wheat lightpink forestgreen) datacontrastcolors=(wheat lightpink forestgreen) 

datalinepatterns=(solid);

vbar INCPOV1 / response=rowper group=RACE_K groupdisplay=cluster stat=mean barwidth=0.8; 

xaxis display=(noticks); 

yaxis grid; 

keylegend / across=1 position=top;

run; 

ods html close; 

ods listing; 
Data User’s Guide for the 2019 NIS

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114
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

115

B. SAS

**********************;

title1 'SAS_IAP.SAS'; 

********************************************************************** 

THIS PROGRAM WILL PRODUCE ESTIMATION AREA ESTIMATES AND STANDARD ERRORS

FOR P_UTD431H314_ROUT_S USING SAS.

**********************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let estiap=estiap19; * --- ESTIMATION AREA VARIABLE TO USE ---*;

%let wt=provwt_c; * --- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. 

Use PROVWT_C_TERR to include territories) --*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

value putd431h314f

0='Not 4:3:1:3:3:1:4 Up-To-Date'

1='4:3:1:3:3:1:4 Up-To-Date'; 

value estiapf

. = "Missing"

0 = "US Total"

1 = "CT"

2 = "MA"

4 = "ME"

5 = "NH"

6 = "RI"

7 = "VT"

8 = "NJ"

10 = "NY-Rest of State"

11 = "NY-City of New York"

12 = "DC"

13 = "DE"

14 = "MD"

16 = "PA-Rest of State"

17 = "PA-Philadelphia County"

18 = "VA"

19 = "WV"

20 = "AL"

22 = "FL"

25 = "GA"

27 = "KY"

28 = "MS"

29 = "NC"
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30 = "SC"

31 = "TN"

34 = "IL-Rest of State"

35 = "IL-City of Chicago"

36 = "IN"

38 = "MI"

40 = "MN"

41 = "OH"

44 = "WI"

46 = "AR"

47 = "LA"

49 = "NM"

50 = "OK"

51 = "TX-Rest of State"

52 = "TX-Dallas County" 

53 = "TX-El Paso County" 

54 = "TX-City of Houston"

55 = "TX-Bexar County"

56 = "IA"

57 = "KS"

58 = "MO"

59 = "NE"

60 = "CO"

61 = "MT"

62 = "ND"

63 = "SD"

64 = "UT"

65 = "WY"

66 = "AZ"

68 = "CA"

72 = "HI"

73 = "NV"

74 = "AK"

75 = "ID"

76 = "OR"

77 = "WA"

106 = "Puerto Rico" 

; 

run; 

data sas_file;

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S &estiap &wt &strat);

run; 

proc sort data = sas_file;

by &estiap;

run; 

title1 '4:3:1:3:3:1:4 ESTIMATES BY ESTIMATION AREA'; 

ods output Statistics=sas_est;

proc surveymeans data = sas_file nobs sum mean stderr;

stratum &strat;

cluster seqnumhh; 
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weight &wt;

class P_UTD431H314_ROUT_S; 

var P_UTD431H314_ROUT_S; 

by &estiap;

format P_UTD431H314_ROUT_S putd431h314f.; 

format &estiap estiapf.; 

run; 

data sas_est;

set sas_est;

mean = mean*100; *CONVERT TO PERCENT ESTIMATES;

stderr = stderr*100; 

run; 

proc print data=sas_est(where=(varlevel='4:3:1:3:3:1:4 Up-To-Date')) noobs

label; 

format &estiap estiapf.; 

format mean stderr 5.2; 

var &estiap mean stderr;

label

mean='Percent 4:3:1:3:3:1:4 Up-to-Date'

stderr='Standard Error'; 

title "4:3:1:3:3:1:4 ESTIMATES BY ESTIMATION AREA"; 

run; 

**********************;

title1 'SASSTATE.SAS'; 

********************************************************************** 

THIS PROGRAM WILL PRODUCE STATE ESTIMATES AND STANDARD ERRORS

FOR P_UTD431H314_ROUT_S USING SAS.

NOTE: THE STATE VARIABLE IS BASED ON FIPSTATE CODES, THERE ARE

NO STATES WITH FIPS CODES 3,7,14,43,52,57-71,73-78. 

**********************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_c; * --- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. 

Use PROVWT_C_TERR to include territories) --*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

value putd431h314f

0='Not 4:3:1:3:3:1:4 Up-To-Date'

1='4:3:1:3:3:1:4 Up-To-Date'; 

value statef

. ="Missing"
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0 ='U.S. Total ' 1 ='Alabama ' 2 ='Alaska ' 4 ='Arizona ' 5 ='Arkansas ' 6 ='California ' 8 ='Colorado ' 9 ='Connecticut '

10 ='Delaware '

11 ='District of Columbia '

12 ='Florida '

13 ='Georgia '

15 ='Hawaii '

16 ='Idaho '

17 ='Illinois '

18 ='Indiana '

19 ='Iowa '

20 ='Kansas '

21 ='Kentucky '

22 ='Louisiana '

23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

26 ='Michigan '

27 ='Minnesota '

28 ='Mississippi '

29 ='Missouri '

30 ='Montana '

31 ='Nebraska '

32 ='Nevada '

33 ='New Hampshire '

34 ='New Jersey '

35 ='New Mexico '

36 ='New York '

37 ='North Carolina '

38 ='North Dakota '

39 ='Ohio '

40 ='Oklahoma '

41 ='Oregon '

42 ='Pennsylvania '

44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

55 ='Wisconsin '

56 ='Wyoming '

72 ='Puerto Rico ' 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

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; 

run; 

data sas_file;

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S state &wt &strat);

run; 

proc sort data = sas_file;

by state;

title1 '4:3:1:3:3:1:4 ESTIMATES BY STATE'; 

ods output Statistics=sas_est2;

run; 

proc surveymeans data = sas_file nobs sum mean stderr;

stratum &strat;

cluster seqnumhh; 

weight &wt;

class P_UTD431H314_ROUT_S; 

var P_UTD431H314_ROUT_S; 

by state;

format P_UTD431H314_ROUT_S putd431h314f.; 

format state statef.; 

run; 

data sas_est2;

set sas_est2;

mean = mean*100; *CONVERT TO PERCENT ESTIMATES;

stderr = stderr*100; 

run; 

proc print data=sas_est2(where=(varlevel='4:3:1:3:3:1:4 Up-To-Date')) noobs

label; 

format state statef.; 

format mean stderr 5.2; 

var state mean stderr;

label

mean='Percent 4:3:1:3:3:1:4 Up-to-Date'

stderr='Standard Error'; 

title "4:3:1:3:3:1:4 ESTIMATES BY STATE"; 

run; 

**********************;

title1 'SAS_PROG_3.SAS'; 

************************************************************************* 

THIS PROGRAM WILL PRODUCE A TABLE OF HAD_CPOX BY STATE FOR ALL RDD

COMPLETES USING RDDWT. THE PROGRAM USES SAS.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;
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*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=rddwt_c; *--- WEIGHT TO USE (RDDWT_C is the single-frame cell-phone weight excluding territories) ---*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

proc format; 

value hadcpoxf 

1='Yes'

2='No'

; 

value statef

0 ='U.S. Total '

1 ='Alabama '

2 ='Alaska '

4 ='Arizona '

5 ='Arkansas '

6 ='California '

8 ='Colorado '

9 ='Connecticut '

10 ='Delaware '

11 ='District of Columbia '

12 ='Florida '

13 ='Georgia '

15 ='Hawaii '

16 ='Idaho '

17 ='Illinois '

18 ='Indiana '

19 ='Iowa '

20 ='Kansas '

21 ='Kentucky '

22 ='Louisiana '

23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

26 ='Michigan '

27 ='Minnesota '

28 ='Mississippi '

29 ='Missouri '

30 ='Montana '

31 ='Nebraska '

32 ='Nevada '

33 ='New Hampshire '

34 ='New Jersey '

35 ='New Mexico '

36 ='New York '

37 ='North Carolina '

38 ='North Dakota '

39 ='Ohio '

40 ='Oklahoma '

41 ='Oregon '

42 ='Pennsylvania '
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44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

55 ='Wisconsin '

56 ='Wyoming '

72 =Puerto Rico ' 

; 

run; 

data sas_file;

set &in_file(keep= seqnumhh seqnumc state had_cpox &wt &strat);

run; 

proc sort data = sas_file;

by state;

title1 'HAD_CPOX ESTIMATES BY STATE'; 

ods output Statistics=sas_est3;

run; 

proc surveymeans data = sas_file nobs sum mean stderr;

stratum &strat;

cluster seqnumhh; 

weight &wt;

class had_cpox; 

var had_cpox; 

by state;

format had_cpox hadcpoxf.; 

format state statef.; 

run; 

data sas_est3;

set sas_est3;

mean = mean*100; *CONVERT TO PERCENT ESTIMATES;

stderr = stderr*100; 

run; 

proc print data=sas_est3(where=(varlevel='Yes')) noobs label; 

format state statef.; 

format mean stderr 5.2; 

var state mean stderr;

label

mean='Percent HAD_CPOX = Yes'

stderr='Standard Error'; 

title "CHILD HAD CHICKEN POX BY STATE"; 

run; 
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**********************;

title1 'SAS_PROG_4.SAS'; 

************************************************************************* 

TABLE OF P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. SAVE % UTD

ESTIMATES (NOT S.E.'S) FOR USE IN THE PROGRAM SAS_GRAPH_4.

THIS PROGRAM WILL PRODUCE ESTIMATES USING SAS.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf19'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

libname out 'c:\nispuf19'; *--- SPECIFY THE PATH FOR 

WHERE YOU WANT THE CHART OUTPUT TO GO ---*;

%let in_file=dd.nispuf19; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_c; *--- WEIGHT TO USE (PROVWT_C is the single-frame cell-phone weight excluding territories. Use 

PROVWT_C_TERR to include territories) --*; 

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

%let qtr_lab=Q1/2019 - Q4/2019; *NIS 4 QUARTER PERIOD*;

proc format; 

value putd431h314f

0='Not 4:3:1:3:3:1:4 Up-To-Date'

1='4:3:1:3:3:1:4 Up-To-Date'

; 

value race_kf

1 = "WHITE ONLY"

2 = "BLACK ONLY"

3 = "OTHER AND MULTIPLE RACE"

; 

value incpvr2f

1 = "ABOVE, > $75,000"

2 = "ABOVE, <= $75,000"

3 = "BELOW"

4 = "UNKNOWN"

; 

run; 

data sas_file;

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S race_k incpov1 &wt &strat); 

run; 

proc sort data = sas_file;

by incpov1 race_k; 

run; 

proc freq; 

tables P_UTD431H314_ROUT_S incpov1 race_k; 
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123

title1 "Table 4A. &qtr_lab: Unweighted Frequencies"; 

run; 

data sas_file;

set sas_file;

if P_UTD431H314_ROUT_S < 0 | incpov1 < 0 | race_k < 0 | &wt. < 0 then delete; 

run; 

proc surveymeans data = sas_file nobs sum mean stderr;

ods output Domain=sas_est4; 

stratum &strat;

cluster seqnumhh; 

weight &wt;

class P_UTD431H314_ROUT_S; 

var P_UTD431H314_ROUT_S; 

domain incpov1*race_k; 

format P_UTD431H314_ROUT_S putd431h314f.; 

format incpov1 incpvr2f.; 

format race_k race_kf.; 

run; 

data sas_est4;

set sas_est4;

mean = mean*100; *CONVERT TO PERCENT ESTIMATES;

stderr = stderr*100; 

run; 

proc print data=sas_est4(where=(varlevel='4:3:1:3:3:1:4 Up-To-Date')) noobs

label; 

format incpov1 incpvr2f.; 

format race_k race_kf.; 

format mean stderr 5.2; 

var incpov1 race_k mean stderr;

label

mean='4:3:1:3:3:1:4 Up-To-Date'

stderr='Standard Error'; 

title1 "Table 4B. &qtr_lab, 4:3:1:3:3:1:4 ESTIMATES AND STANDARD ERRORS BY INCPOV1 BY RACE_K"; 

run; 

data out.sas_est4; 

set sas_est4(where=(varlevel='4:3:1:3:3:1:4 Up-To-Date'));

keep incpov1 race_k mean; 

label mean='4:3:1:3:3:1:4 Up-to-Date'; 

format mean 5.2; 

run; 

**********************;

title1 'SAS_GRAPH_4.SAS'; 

************************************************************************* 

THIS PROGRAM BUILDS OFF OF THE PROGRAM SAS_PROG_4. IT PRODUCES A CHART OF

P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. IT CREATES A BAR CHART IN SAS GRAPH FOR

THE 4X3 = 12 CELLS. THE OUTPUT OF THE FOLLOWING EXAMPLE IS ATTACHED AT THE
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

124

END.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf19'; *--- SPECIFY PATH TO SAS DATASET ---*;

%let out='c:\nispuf19'; *--- SPECIFY THE PATH FOR WHERE YOU WANT THE CHART

OUTPUT TO GO ---*;

%let in_file=dd.sas_est4; *--- NAME OF SAS DATASET OUTPUT FROM PROG_4 ---*; 

%let qtr_lab=Q1/2019 - Q4/2019; *NIS 4 QUARTER PERIOD*;

proc format; 

value incpvr2f

1 = "ABOVE, > $75,000"

2 = "ABOVE, <= $75,000"

3 = "BELOW"

4 = "UNKNOWN"

; 

value race_kf

1 = "WHITE ONLY"

2 = "BLACK ONLY"

3 = "OTHER/MULT RACE"

; 

run; 

data sas_est4;

set &in_file;

format mean 3.

race_k race_kf.

incpov1 incpvr2f.

; 

label

race_k = 'Race of Child'

incpov1 = 'Poverty Status'

; 

filename odsout &out; 

ods listing close; 

/* SET THE GRAPHICS ENVIRONMENT */

goptions reset=global gunit=pct border

ftext=swissb htitle=4 htext=1.5

device=gif

; 

ods html body='graph_4.html' path=odsout; 

run; 

title1 h=12pt "Percentage of Children Up-to-Date with Vaccine Series 4:3:1:3:3:1:4 "; 

title2 h=12pt "by Race and Poverty Status, National Immunization Survey - Child, 2019"; 

footnote j=r 'graph_4'; 

proc sgplot data=sas_est4;

styleattrs datacolors=(wheat lightpink forestgreen) datacontrastcolors=(wheat lightpink forestgreen) 

datalinepatterns=(solid);
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vbar INCPOV1 / response=mean group=RACE_K groupdisplay=cluster stat=mean barwidth=0.8; 

xaxis display=(noticks); 

yaxis grid; 

keylegend / across=1 position=top;

run; 

ods html close; 

ods listing; 
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126

C. ‘R’

######################

title <- "R_IAP.R" 

######################################################################

#THIS PROGRAM WILL PRODUCE ESTIMATION AREA ESTIMATES AND STANDARD ERRORS

#FOR P_UTD431H314_ROUT_S USING R.

# 

#R NOTES:

#1. R IS CASE SENSITIVE.

#2. A FILE PATH IS SEPERATED BY SLASH(/)

######################################################################

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

dd <- "c:/nispuf19" #"path-to-dataset"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF19.RData",sep="")

#---READ R DATASET---# 

load(in.file)

#---FORMAT---# 

UTD431H314levels=c(0,1)

UTD431H314labels=c("NOT 4:3:1:3:3:1:4 UTD", "4:3:1:3:3:1:4 UTD")

ESTIAPlevels=c(0, 1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 22, 25, 27, 28, 29, 30, 31, 34, 35, 36, 38, 40, 41, 44, 46, 47, 49, 50, 51, 52, 

53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 72, 73, 74, 75, 76, 77, 106) 

ESTIAPlabels=c("US Total", "CT", "MA", "ME", "NH", "RI", "VT", "NJ", "NY-Rest of State", "NY-City of New York", "DC", "DE", "MD", "PARest of State", "PA-Philadelphia County", "VA", "WV", "AL", "FL", "GA", "KY", "MS", "NC", "SC", "TN", "IL-Rest of State", "IL-City of 

Chicago", "IN", "MI", "MN", "OH", "WI", "AR", "LA", "NM", "OK", "TX-Rest of State", “TX-Dallas County”, “TX-El Paso County”, "TX-City of 

Houston", "TX-Bexar County", "IA", "KS", "MO", "NE", "CO", "MT", "ND", "SD", "UT", "WY", "AZ", "CA", "HI", "NV", "AK", "ID", "OR", 

"WA", “Puerto Rico”) 

#---PROVWT_C WILL BE USED AS A WEIGHT (PROVWT_C IS THE SINGLE-FRAME CELL-PHONE WEIGHT EXCLUDING 

TERRITORIES; USE PROVWT_C_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF19, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, ESTIAP19, 

PROVWT_C, STRATUM))

names(R_FILE) <- c("SEQNUMHH", "SEQNUMC", "P_UTD431H314_ROUT_S", "ESTIAP", "WT", "STRATUM")

R_FILE <- na.omit(R_FILE) 

#---ASSIGN LABELS---# 

R_FILE$P_UTD431H314_ROUT_S <- factor(R_FILE$P_UTD431H314_ROUT_S, levels=UTD431H314levels,

labels=UTD431H314labels)

R_FILE$ESTIAP <- factor(R_FILE$ESTIAP, levels=ESTIAPlevels,

labels=ESTIAPlabels)

#---SPECIFY A SAMPLING DESIGN AND FORCE WT AS NUMERIC---# 

svydsg <- svydesign(id=~SEQNUMHH, strata=~STRATUM, weights=~(as.numeric(WT)),

data=R_FILE)

#---U.S. TOTAL ESTIMATES AND STANDARD ERRORS---# 

r_nation <- svymean(~P_UTD431H314_ROUT_S, svydsg)

PERCENT_UTD <- round(r_nation*100,2) #CONVERT INTO PERCENT ESTIMATES(MEAN)

SE_UTD <- round(SE(r_nation)*100,2) #CONVERT INTO PERCENT ESTIMATES(SE)

r_nation_est <- cbind(PERCENT_UTD, SE_UTD)

title <- "PERCENT 4:3:1:3:3:1:4 ESTIMATES AT A NATIONAL LEVEL"

prn(r_nation_est, title)

#---ESTIMATION AREA ESTIMATES AND STANDARD ERRORS---# 

r_est <- svyby(~P_UTD431H314_ROUT_S, ~ESTIAP, svydsg, svymean)

r_est[,-c(1)] <- round(r_est[,-c(1)]*100,2) #CONVERT INTO PERCENT ESTIMATES

r_est <- subset(r_est, select=c(1,3,5))
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127

#SELECT ESTIMATES FOR UP-TO-DATE CASES

names(r_est) <- c("ESTIMATION AREA", "PERCENT 4:3:1:3:3:1:4 UTD", "STANDARD ERROR UTD")

title <- "PERCENT 4:3:1:3:3:1:4 ESTIMATES BY ESTIMATION AREA"

prn(r_est, title)

######################

title <- "R_STATE.R"

######################################################################

#THIS PROGRAM WILL PRODUCE STATE ESTIMATES AND STANDARD ERRORS

#FOR P_UTD431H314_ROUT_S USING R.

# 

#NOTE : THE STATE VARIABLE IS BASED ON FIPSTATE CODES ,THERE ARE

#NO STATES WITH FIPS CODES 3,7,14,43,52,57-71,73-78. 

# 

#R NOTES:

#1. R IS CASE SENSITIVE.

#2. A FILE PATH IS SEPERATED BY SLASH(/)

######################################################################

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

dd <- "c:/nispuf19" #"path-to-data"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF19.RData",sep="")

#---READ R DATASET---# 

load(in.file)

#---FORMAT---# 

UTD431H314levels=c(0,1)

UTD431H314labels=c("NOT 4:3:1:3:3:1:4 UTD", "4:3:1:3:3:1:4 UTD")

STATElevels=c(1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 16, 17,

18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,

36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53,

54, 55, 56, 72) 

STATElabels=c(

"ALABAMA",

"ALASKA",

"ARIZONA",

"ARKANSAS",

"CALIFORNIA",

"COLORADO",

"CONNECTICUT",

"DELAWARE",

"DISTRICT OF COLUMBIA",

"FLORIDA",

"GEORGIA",

"HAWAII",

"IDAHO",

"ILLINOIS", 

"INDIANA",

"IOWA",

"KANSAS",

"KENTUCKY",

"LOUISIANA",

"MAINE",

"MARYLAND",

"MASSACHUSETTS",

"MICHIGAN",

"MINNESOTA",

"MISSISSIPPI",

"MISSOURI", 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

128

"MONTANA",

"NEBRASKA",

"NEVADA",

"NEW HAMPSHIRE",

"NEW JERSEY",

"NEW MEXICO",

"NEW YORK",

"NORTH CAROLINA",

"NORTH DAKOTA",

"OHIO",

"OKLAHOMA",

"OREGON",

"PENNSYLVANIA",

"RHODE ISLAND",

"SOUTH CAROLINA", 

"SOUTH DAKOTA",

"TENNESSEE",

"TEXAS",

"UTAH",

"VERMONT",

"VIRGINIA", 

"WASHINGTON",

"WEST VIRGINIA",

"WISCONSIN", 

"WYOMING", 

“PUERTO RICO”

) 

#---PROVWT_C WILL BE USED AS A WEIGHT (PROVWT_C IS THE SINGLE-FRAME CELL-PHONE WEIGHT EXCLUDING 

TERRITORIES; USE PROVWT_C_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF19, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, 

STATE, PROVWT_C, STRATUM))

names(R_FILE) <- c("SEQNUMHH", "SEQNUMC", "P_UTD431H314_ROUT_S", "STATE",

"WT","STRATUM")

R_FILE <- na.omit(R_FILE) 

#---ASSIGN LABELS---# 

R_FILE$P_UTD431H314_ROUT_S <- factor(R_FILE$P_UTD431H314_ROUT_S, levels=UTD431H314levels,

labels=UTD431H314labels)

R_FILE$STATE <- factor(R_FILE$STATE, levels=STATElevels,

labels=STATElabels)

#---SPECIFY A SAMPLING DESIGN AND FORCE WT AS NUMERIC---# 

svydsg <- svydesign(id=~SEQNUMHH, strata=~STRATUM, weights=~(as.numeric(WT)),

data=R_FILE)

#---STATE ESTIMATES AND STANDARD ERRORS---# 

r_est2 <- svyby(~P_UTD431H314_ROUT_S, ~STATE, svydsg, svymean)

r_est2[,-c(1)] <- round(r_est2[,-c(1)]*100,2) #CONVERT INTO PERCENT ESTIMATES

r_est2 <- subset(r_est2, select=c(1,3,5)) #SELECT ESTIMATES FOR UP-TO-DATE CASES

names(r_est2) <- c("STATE", "PERCENT 4:3:1:3:3:1:4 UTD", "STANDARD ERROR UTD")

prn(r_est2, '4:3:1:3:3:1:4 ESTIMATES BY STATE')

######################

title <- "R_PROG_3.R" 

######################################################################

#THIS PROGRAM WILL PRODUCE A TABLE OF HAD_CPOX BY STATE FOR ALL RDD

#COMPLETES USING RDDWT_C. THE PROGRAM USES R.

# 

#R NOTES:

#1. R IS CASE SENSITIVE.

#2. A FILE PATH IS SEPERATED BY SLASH(/)

######################################################################

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

library(prettyR) #TO USE freq()

dd <- "c:/nispuf19" #"path-to-dataset"
Data User’s Guide for the 2019 NIS

-Child Public-Use Data FileAPPENDIX D 

129

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF19.RData",sep="")

#---READ R DATASET---# 

load(in.file)

#---FORMAT---# 

HAD_CPOXlevels=c(1,2,77,99)

HAD_CPOXlabels=c("YES", "NO", "DON'T KNOW", "REFUSED")

STATElevels=c(1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 16, 17,

18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,

36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53,

54, 55, 56, 72) 

STATElabels=c(

"ALABAMA",

"ALASKA",

"ARIZONA",

"ARKANSAS",

"CALIFORNIA",

"COLORADO",

"CONNECTICUT",

"DELAWARE",

"DISTRICT OF COLUMBIA",

"FLORIDA",

"GEORGIA",

"HAWAII",

"IDAHO",

"ILLINOIS", 

"INDIANA",

"IOWA",

"KANSAS",

"KENTUCKY",

"LOUISIANA",

"MAINE",

"MARYLAND",

"MASSACHUSETTS",

"MICHIGAN",

"MINNESOTA",

"MISSISSIPPI",

"MISSOURI", 

"MONTANA",

"NEBRASKA",

"NEVADA",

"NEW HAMPSHIRE",

"NEW JERSEY",

"NEW MEXICO",

"NEW YORK",

"NORTH CAROLINA",

"NORTH DAKOTA",

"OHIO",

"OKLAHOMA",

"OREGON",

"PENNSYLVANIA",

"RHODE ISLAND",

"SOUTH CAROLINA",

"SOUTH DAKOTA",

"TENNESSEE",

"TEXAS",

"UTAH",

"VERMONT",

"VIRGINIA", 

"WASHINGTON",

"WEST VIRGINIA",

"WISCONSIN", 

"WYOMING", 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX D 

130

“PUERTO RICO”

) 

#---RDDWT_C WILL BE USED AS A WEIGHT (RDDWT_C IS THE SINGLE-FRAME CELL-PHONE WEIGHT EXCLUDING 

TERRITORIES; USE RDDWT_C_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF19, select=c(SEQNUMHH, SEQNUMC, STATE,

HAD_CPOX, RDDWT_C, STRATUM))

names(R_FILE) <- c("SEQNUMHH", "SEQNUMC", "STATE", "HAD_CPOX",

"WT", "STRATUM")

#---ASSIGN LABELS---# 

R_FILE$HAD_CPOX <- factor(R_FILE$HAD_CPOX, levels=HAD_CPOXlevels,

labels=HAD_CPOXlabels)

R_FILE$STATE <- factor(R_FILE$STATE, levels=STATElevels,

labels=STATElabels)

R_FILE <- na.omit(R_FILE) 

summary(R_FILE$HAD_CPOX) 

#---SPECIFY A SAMPLING DESIGN AND FORCE WT AS NUMERIC---# 

svydsg <- svydesign(id=~SEQNUMHH, strata=~STRATUM, weights=~(as.numeric(WT)),

data=R_FILE)

#---U.S. TOTAL ESTIMATES AND STANDARD ERRORS---# 

r_nation <- svymean(~HAD_CPOX, svydsg)

PERCENT_UTD <- round(r_nation*100,2) #CONVERT INTO PERCENT ESTIMATES(MEAN)

SE_UTD <- round(SE(r_nation)*100,2) #CONVERT INTO PERCENT ESTIMATES(SE)

r_nation_est3 <- cbind(PERCENT_UTD, SE_UTD)

prn(r_nation_est3, "PERCENT HAD_CPOX = YES ESTIMATES AT A NATIONAL

LEVEL\n")

#---HAD_CPOX = YES ESTIMATES BY STATE---# 

r_est3 <- svyby(~HAD_CPOX, ~STATE, svydsg, svymean)

r_est3[,-c(1)] <- round(r_est3[,-c(1)]*100,2) #CONVERT INTO PERCENT ESTIMATES

r_est3 <- subset(r_est3, select=c(1,2,6)) #SELECT ESTIMATES FOR HAD_CPOX=YES

names(r_est3) <- c("STATE", "PERCENT HAD_CPOX=YES", "STANDARD ERROR

HAD_CPOX=Y")

prn(r_est3, 'PERCENT HAD_CPOX ESTIMATES BY STATE')

######################

title <- "PROG_4.R" 

#########################################################################

#TABLE OF P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. SAVE % UTD

#ESTIMATES (NOT S.E.'S) FOR USE IN THE PROGRAM GRAPH_4.

# 

#THIS PROGRAM WILL PRODUCE ESTIMATES USING R.

# 

#R NOTES:

#1. R IS CASE SENSITIVE.

#2. A FILE PATH IS SEPERATED BY SLASH(/)

#########################################################################

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

dd <- "c:/nispuf19" #"path-to-dataset"

out <-"c:/nispuf19" #"path-to-output"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF19.RData",sep="")

#---READ R DATASET---# 

load(in.file)
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131

#---FORMAT---# 

UTD431H314levels=c(0,1)

UTD431H314labels=c("NOT 4:3:1:3:3:1:4 UTD", "4:3:1:3:3:1:4 UTD")

RACE_PUFlevels=c(1,2,3)

RACE_PUFlabels=c("WHITE ONLY", "BLACK ONLY", "OTHER + MULTIPLE RACE")

INCPOVlevels=c(1,2,3,4)

INCPOVlabels=c("ABOVE POVERTY, > $75K", "ABOVE POVERTY, <= $75K", "BELOW POVERTY", "UNKNOWN")

#---PROVWT_C WILL BE USED AS A WEIGHT (PROVWT_C IS THE SINGLE-FRAME CELL-PHONE WEIGHT EXCLUDING 

TERRITORIES; USE PROVWT_C_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF19, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, RACE_K, INCPOV1, PROVWT_C, STRATUM))

names(R_FILE) <- c("SEQNUMHH", "SEQNUMC", "P_UTD431H314_ROUT_S", "RACE_K", "INCPOV1", "WT", "STRATUM")

#---ASSIGN LABELS---# 

R_FILE$P_UTD431H314_ROUT_S <- factor(R_FILE$P_UTD431H314_ROUT_S, levels=UTD431H314levels, labels=UTD431H314labels, 

exclude=NULL)

R_FILE$RACE_K <- factor(R_FILE$RACE_K, levels=RACE_PUFlevels, labels=RACE_PUFlabels, exclude=NULL)

R_FILE$INCPOV1 <- factor(R_FILE$INCPOV1, levels=INCPOVlevels,labels=INCPOVlabels, exclude=NULL)

#---UNWEIGHTED FREQUENCIES---# 

unwt_freq <- function(UNWT.VAR){#FUNCTION TO PRINT UNWEIGHTED FREQUENCIES

unwt.tab <- wtd.table(UNWT.VAR, weights= NULL, type='table')

unwtd.freq <- data.frame(cbind(

unwt.tab, round(unwt.tab/sum(unwt.tab)*100,2),

cumsum(unwt.tab), cumsum(round(unwt.tab/sum(unwt.tab)*100,2))))

names(unwtd.freq) <- c("Frequency", "Percent", "Cumulative Frequency", "Cumulative Percent")

unwtd.title <- paste('Table 4A. Q1/2019 - Q4/2019', 'UNWEIGHTED FREQUENCIES', label(UNWT.VAR), sep="\n")

label(unwtd.freq) <- unwtd.title

print(unwtd.freq)

} 

unwt_freq(R_FILE$P_UTD431H314_ROUT_S) 

unwt_freq(R_FILE$INCPOV1)

unwt_freq(R_FILE$RACE_K)

R_FILE <- na.omit(R_FILE) 

#---SPECIFY A SAMPLING DESIGN AND FORCE WT AS NUMERIC---# 

svydsg <- svydesign(id=~SEQNUMHH, strata=~STRATUM, weights=~(as.numeric(WT)),

data=R_FILE)

#---PERCENT 4:3:1:3:3:1:4 UP-TO-DATE AND ESTIMATED STANDARD ERRORS---# 

r_est4 <- svyby(~P_UTD431H314_ROUT_S, ~RACE_K+INCPOV1, svydsg, svymean)

r_est4[,-c(1,2)] <- round(r_est4[,-c(1,2)]*100,2) #CONVERT INTO PERCENT ESTIMATES

r_est4 <- subset(r_est4, select=c(1,2,4,6)) #SELECT ESTIMATES FOR UP-TODATE CASES

names(r_est4) <- c("RACE", "INCOME", "PERCENT_UTD", "STANDARD_ERROR_UTD")

title <- "Table 4B. Q1/2019 - Q4/2019, Percent 4:3:1:3:3:1:4 UTD and Estimated Standard Errors"

prn(r_est4, title)

#---SAVE PERCENT UP-TO-DATE ESTIMATES FOR USE IN THE PROGRAM GRAPH_4---# 

r_est4 <- subset(r_est4, select=c(RACE, INCOME, PERCENT_UTD))

save(r_est4, file=paste(out, "/r_est4", sep=""))

######################

title <- "GRAPH_4.R"

#########################################################################

#THIS PROGRAM BUILDS OFF OF THE PROGRAM PROG_4. IT PRODUCES A CHART OF

#P_UTD431H314_ROUT_S BY INCPOV1 BY RACE_K. IT CREATES A BAR CHART IN R GRAPH FOR

#THE 4X3 = 12 CELLS.

#R NOTES:

#1. R IS CASE SENSITIVE.

#2. A FILE PATH IS SEPERATED BY SLASH(/)

#########################################################################

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

dd <- "c:/nispuf19" #---SPECIFY PATH TO R DATASET THAT WAS THE OUTPUT OF R_PROG_4---# 

out <- "c:/nispuf19" #---SPECIFY THE PATH FOR WHERE YOU WANT THE CHART OUTPUT TO GO---# 
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132

#---NAME OF R DATASET OUTPUT FROM R_PROG_4---# 

in.file <- paste(dd,"/r_est4",sep="")

#---READ R DATASET---# 

load(in.file)

#---BARCHART---# 

#NOTE:R DOES NOT SUPPORT CREATING A HTML FILE CONTAINING A BARCHART#

#CREATE A DATA MATRIX FOR DRAWING A BARCHART#

utd431H314 <- matrix(r_est4$PERCENT_UTD, nrow=3, ncol=4, byrow=F, dimnames=list(levels(r_est4$RACE), levels(r_est4$INCOME)))

#CREATE GRAPH_4.GIF#

barplot(utd431H314, beside=TRUE, space=c(0.2,1),

 col = c("wheat", "lightpink2", "forestgreen"),

 axis.lty = 1,

 sub="(Graph 4 using 'R')", cex.sub=1, ylim=c(0,120),

 xlab="Poverty Status",

 ylab="4:3:1:3:3:1:4 Up-To-Date (%)", cex=1.1, cex.names=1, cex.lab=1.5, border=NA)

legend("top", rownames(utd431H314), col=c("wheat", "lightpink2",

 "forestgreen"), title="Race of Child", pch=10, cex=1.25)

title1 <- "Percentage of Children Up-to-Date with Vaccine Series 4:3:1:3:3:1:4 \n"

title2 <- "by Race and Poverty Status, National Immunization Survey - Child, 2019\n"

mtext(paste(title1,title2), cex=1.5)
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133

Appendix E: Alphabetical Listing of Variables that are in the 2004-2019 Public-Use Data 

Files

Table E.1 Alphabetical Listing of Variables that are in the 2004-2019 Public-Use Data Files*

Year of Data Collection

Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

AGECPOXR AGE IN MONTHS AT CHICKEN 

POX DISEASE (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced IAGECPXR starting 2005. This version is not imputed.

AGEGRP AGE CATEGORY OF CHILD (19-

23, 24-29, 30-35 MO) (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ALL4SHOT HH REPORT OF 4:3:1:3 UP-TODATE Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

BF_ENDR DURATION OF BREASTFEEDING 

IN DAYS (TOPCODE) Y Y Dropped starting in 2006 because of question wording change. Replaced by BF_ENDR06.

BF_ENDR06 DURATION OF BREASTFEEDING 

IN DAYS (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced BF_ENDR starting 2006.

BF_EXCLR

DURATION OF EXCLUSIVE 

BREASTFEEDING IN DAYS 

(TOPCODE)

Y Y Dropped starting in 2006 because of question 

wording change. Replaced by BF_EXCLR06.

BF_EXCLR06

DURATION OF EXCLUSIVE 

BREAST/FORMULA FEEDING IN 

DAYS (RECODE)

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced BF_EXCLR starting 2006.

BF_FORMR06 AGE IN DAYS WHEN CHILD 

FIRST FED FORMULA (TOPCODE) Y Y Question CBF_03_X added starting 2006. 

Replaced by BF_FORMR06 starting 2008.

BF_FORMR08 AGE IN DAYS WHEN CHILD 

FIRST FED FORMULA (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Replaced BF_FORMR06 to add a "never fed 

formula" code.

BFENDFL

DURATION OF BREAST FEEDING 

EXCEEDS CHILD AGE IN DAYS, 

WITH BUFFER

Y Y Dropped starting in 2006 because of question 

wording change. Replaced by BFENDFL06.

BFENDFL06

DURATION OF BREAST FEEDING 

EXCEEDS CHILD AGE IN DAYS, 

WITH BUFFER

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced BFENDFL starting 2006.

BFEXCLFL

DURATION OF EXCLUSIVE 

BREAST FEEDING EXCEEDS 

TOTAL BREASTFEEDING, WITH 

BUFFER

Y Y 

Dropped starting in 2006 because question 

wording change does not allow it to be 

derived.

BFFORMFL06

AGE IN DAYS WHEN CHILD 

FIRST FED FORMULA EXCEEDS 

CHILD AGE IN DAYS, WITH 

BUFFER

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Question CBF_03_X added starting 2006.

C_431 HH REPORT OF 4:3:1 UP-TO-DATE 

BY SHOT CARD USE Y Y Dropped starting in 2006 because no longer possible to derive due to questionnaire change. 
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134

Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

C_4313 HH REPORT OF 4:3:1:3 UP-TODATE BY SHOT CARD USE Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_DTP

HH REPORT OF 4+ DTCONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_HEP

HH REPORT OF 3+ HEPATITIS BCONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_HIB

HH REPORT OF 3+ HIBCONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_MMR

HH REPORT OF 1+ MEASLESCONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_POL

HH REPORT OF 3+ POLIOCONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C_VRC

HH REPORT OF 1+ VARICELLACONTAINING UP-TO-DATE BY 

SHOT CARD USE

Y Y Dropped starting in 2006 because no longer 

possible to derive due to questionnaire change. 

C1R NUMBER OF PEOPLE IN 

HOUSEHOLD (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

C5R RELATIONSHIP OF RESPONDENT 

TO CHILD (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

CBF_01 WAS CHILD EVER BREASTFED 

OR FED BREAST MILK? Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

CEN_REG CENSUS REGION BASED ON 

TRUE STATE OF RESIDENCE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

CHILDNM NUMBER OF CHILDREN LESS 

THAN 18 YEARS IN HH (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

CWIC_01 CHILD EVER RECEIVED WIC 

BENEFITS? Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

CWIC_02 CHILD CURRENTLY RECEIVING 

WIC BENEFITS? Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

D6R

NUMBER OF VACCINATION 

PROVIDERS IDENTIFIED BY 

RESPONDENT (RECODE)

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

D7

CONSENT TO OBTAIN CHILD'S 

IMMUNIZATION RECORDS FROM 

PROVIDERS

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP1 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP2 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DDTP3 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP4 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP5 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP6 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP7 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP8 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP9 AGE IN DAYS OF PROV-REPTD 

DT-CONTAINING SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DFLU1

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU2

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU3

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU4

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU5

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU6

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU7

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU8

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DFLU9

AGE IN DAYS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DH1N1

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #1

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DH1N2

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #2

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N3

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #3

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N4

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #4

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N5

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #5

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N6

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #6

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N7

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #7

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N8

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #8

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DH1N9

AGE IN DAYS OF PROV-REPTD 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #9

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

DHEPA1

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA2

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA3

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA4

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA5

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DHEPA6

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA7

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA8

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPA9

AGE IN DAYS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DHEPB1

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB2

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB3

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB4

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB5

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB6

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB7

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB8

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHEPB9

AGE IN DAYS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DHIB1 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB2 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB3 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DHIB4 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB5 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB6 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB7 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB8 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB9 AGE IN DAYS OF PROV-REPTD 

HIB-CONTAINING SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DISPCODE NIS PROVIDER RECORD-CHECK 

DISPOSITION CODE Y Y Y Y Y Y Y Y Dropped starting in 2012 because no longer possible to derive due to questionnaire change

DMMR1 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMMR2 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMMR3 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMMR4 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMMR5 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMMR6 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMMR7 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMMR8 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMMR9 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMP1 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMP2 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMP3 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMP4 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMP5 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DMP6 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMP7 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMP8 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMP9 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMPRB1

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMPRB2

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMPRB3

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMPRB4

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DMPRB5

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMPRB6

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMPRB7

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMPRB8

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DMPRB9

AGE IN DAYS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DPCV1

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV2

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV3

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DPCV4

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV5

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV6

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV7

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV8

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPCV9

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DPOLIO1 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO2 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO3 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO4 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO5 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO6 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO7 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO8 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DPOLIO9 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DRB1 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB2 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB3 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB4 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DRB5 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB6 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB7 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB8 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DRB9 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DROT1

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT2

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT3

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT4

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT5

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT6

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT7

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT8

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DROT9

AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DTP_SOUR SHOT CARD USED FOR DTP 

REPORTING Y Dropped starting in 2005 because this variable is redundant with variable SHOTCARD.

DTP1_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP2_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP3_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

DTP4_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP5_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP6_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP7_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP8_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP9_AGE AGE IN MONTHS OF PROVREPTD DT-CONTAINING SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DVRC1

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DVRC2

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DVRC3

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DVRC4

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DVRC5

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DVRC6

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DVRC7

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DVRC8

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

DVRC9

AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

EDUC1

EDUCATION OF MOTHER 

CATEGORIES: IMPUTED

(RECODE)

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

ENTRY2

CHILD LIVES IN STATE WITH 

HEPATITIS B STATE ENTRY LAW 

FOR DAY CARE/HEAD START 

(2001-2002 SCHOOL YEAR)

Y Dropped starting in 2005.

EST_GRANT

AREA OF RESIDENCE 

ACCORDING TO THE 56 

ORIGINAL CORE GRANTEE 

AREAS

Y Y Y Y Y Y Y Y Added in 2012 to facilitate production of 

estimates for the 56 core areas.

ESTIAP ESTIMATION IAP AREA OF 

RESIDENCE Y 

Replaced ITRUEIAP in 2005 because 

estimation areas were modified. Replaced by 

ESTIAP06 in 2006.

ESTIAP06 ESTIMATION IAP AREA OF 

RESIDENCE Y 

Replaced ESTIAP in 2006 because estimation 

areas were modified. Replaced by ESTIAP07

in 2007.

ESTIAP07 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP06 in 2007 because 

estimation areas were modified. Replaced by 

ESTIAP08 in 2008.

ESTIAP08 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP07 in 2008 because 

estimation areas were modified. Replaced by 

ESTIAP09 in 2009.

ESTIAP09 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP08 in 2009 because 

estimation areas were modified. Replaced by 

ESTIAP10 in 2010.

ESTIAP10 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP09 in 2010 because 

estimation areas were modified. Replaced by 

ESTIAP11 in 2011.

ESTIAP11 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP10 in 2011 because 

estimation areas were modified. Replaced by 

ESTIAP12 in 2012.

ESTIAP12 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP11 in 2012 because 

estimation areas were modified. Replaced by 

ESTIAP13 in 2013.

ESTIAP13 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP12 in 2013 because 

estimation areas were modified. Replaced by 

ESTIAP14 in 2014.

ESTIAP14 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP13 in 2014 because 

estimation areas were modified. Replaced by 

ESTIAP15 in 2015.

ESTIAP15 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP14 in 2015 because 

estimation areas were modified. Replaced by 

ESTIAP16 in 2016.

ESTIAP16 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP15 in 2016 because 

estimation areas were modified. Replaced by 

ESTIAP17 in 2017.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

ESTIAP17 ESTIMATION AREA OF 

RESIDENCE Y 

Replaced ESTIAP16 in 2017 because 

estimation areas were modified. Replaced by 

ESTIAP18 in 2018.

ESTIAP18 ESTIMATION AREA OF 

RESIDENCE Y

Replaced ESTIAP17 in 2018 because 

estimation areas were modified. Replaced 

by ESTIAP19 in 2019.

ESTIAP19 ESTIMATION AREA OF 

RESIDENCE Y Replaced ESTIAP18 in 2019 because estimation areas were modified.

FLU1_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU2_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU3_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU4_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU5_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU6_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU7_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU8_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU9_AGE

AGE IN MONTHS OF PROVREPTD SEASONAL FLUCONTAINING VACCINATION #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

FRSTBRN FIRST BORN STATUS OF CHILD: 

IMPUTED Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FUL2_MMR HOUSEHOLD REPORT OF 1+ 

MMR AT ANY AGE Y Replaced by FULL_MMR starting in 2005.

FULL_CPO HH REPORT OF 1+ VARICELLACONTAINING SHOT AT ANY AGE Y Y 

Starting 2005, a code of 88 added for children 

with unknown UTD status. Dropped starting 

in 2006 because no longer possible to derive 

due to questionnaire change. 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

FULL_DTP HH REPORT OF 4+ DTCONTAINING SHOT Y Y 

Starting 2005, a code of 88 added for children 

with unknown UTD status. Dropped starting 

in 2006 because no longer possible to derive 

due questionnaire change. 

FULL_HEP HH REPORT OF 3+ HEPATITIS BCONTAINING SHOTS Y Y 

Starting 2005, a code of 88 added for children 

with unknown UTD status. Dropped starting 

in 2006 because no longer possible to derive 

due to questionnaire change. 

FULL_HIB HH REPORT OF 3+ HIBCONTAINING SHOTS Y Y 

Starting 2005, a code of 88 added for children 

with unknown UTD status. Dropped starting 

in 2006 because no longer possible to derive 

due to questionnaire change. 

FULL_MMR HH REPORT OF 1+ MEASLESCONTAINING SHOT AT ANY AGE Y 

Replaced FUL2_MMR starting in 2005. A 

code of 88 added for children with unknown 

UTD status. Dropped starting in 2006 because 

no longer possible to derive due to 

questionnaire change. 

FULL_POL HH REPORT OF 3+ POLIOCONTAINING SHOTS Y Y 

Starting 2005, a code of 88 added for children 

with unknown UTD status. Dropped starting 

in 2006 because no longer possible to derive 

due to questionnaire change. 

H1N1_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #1

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N2_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #2 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N3_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #3 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N4_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #4 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N5_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #5 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N6_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #6 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

H1N7_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #7 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N8_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #8 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

H1N9_AGE

AGE IN MONTHS OF PROVREPTD MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #9 

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

HAD_CPOX CHILD EVER HAD CHICKEN POX 

DISEASE? Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced I_HADCPX starting in 2005. This 

version is not imputed.

HEA1_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA2_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA3_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA4_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA5_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA6_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA7_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA8_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA9_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS ACONTAINING SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

HEP_BRTH HEPATITIS B-CONTAINING SHOT 

GIVEN AT BIRTH FLAG Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP_FLAG HEPATITIS B BIRTH SHOT DATE 

IMPUTATION FLAG Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

HEP1_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP2_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP3_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP4_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP5_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP6_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP7_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP8_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP9_AGE

AGE IN MONTHS OF PROVREPTD HEPATITIS BCONTAINING SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

HH_DTP HH REPORT OF NUMBER OF DTCONTAINING SHOTS RECEIVED Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

HH_FLU

HH REPORT OF NUMBER OF 

SEASONAL INFLUENZA 

VACCINATIONS RECEIVED IN 

THE 12 MONTHS PRIOR TO 

INTERVIEW

Y Y Y 

Influenza questions added to the HH 

questionnaire starting in 2007. Dropped in 

2009 due to mid-year questionnaire changes. 

Reinstated in 2010. Dropped again in 2011 

due to mid-year questionnaire changes.

HH_H1N

HH REPORT OF NUMBER OF 

MONOVALENT 2009 H1N1

INFLUENZA VACCINATIONS 

RECEIVED IN THE 12 MONTHS 

PRIOR TO INTERVIEW

Y 

H1N1 influenza questions added to the HH 

questionnaire starting in 2009. Introduced in 

the PUF in 2010. Dropped in 2011 due to midyear questionnaire changes.

HH_HEPB

HH REPORT OF NUMBER OF 

HEPATITIS B-CONTAINING 

SHOTS RECEIVED

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

HH_HIB HH REPORT OF NUMBER OF HIBCONTAINING SHOTS RECEIVED Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

HH_MCV

HH REPORT OF NUMBER OF 

MEASLES-CONTAINING SHOTS 

RECEIVED

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

HH_POL

HH REPORT OF NUMBER OF 

POLIO-CONTAINING SHOTS 

RECEIVED

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

HH_VRC

HH REPORT OF NUMBER OF 

VARICELLA-CONTAINING SHOTS 

RECEIVED

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

HIB1_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB2_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB3_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB4_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB5_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB6_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB7_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB8_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB9_AGE

AGE IN MONTHS OF PROVREPTD HIB-CONTAINING SHOT 

#9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

HUTD4313 HOUSEHOLD REPORT OF 4:3:1:3 

UTD (UP-TO-DATE) Y Dropped starting in 2005 because this variable is redundant with variable ALL4SHOT.

I_HADCPX DID CHILD EVER HAVE CHICKEN 

POX? Y Replaced by HAD_CPOX starting in 2005.

I_HISP_K HISPANIC ORIGIN OF CHILD: 

IMPUTED Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

IAGECPXR AGE IN MONTHS WHEN CHILD 

HAD CHICKEN POX (RECODE) Y Replaced by AGECPOXR starting in 2005.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

INCPORAR INCOME TO POVERTY RATIO 

(RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Replaced INCPORAT starting in 2005. 

INCPORAT used categories whereas 

INCPORAR is continuous. INCPORAR has 

been top- and bottom-coded.

INCPORAR_I INCOME TO POVERTY RATIO: 

IMPUTED (RECODE) Y Y Y Y Imputed version of INCPORAR added in 2016.

INCPORAT INCOME TO POVERTY RATIO Y Replaced by INCPORAR starting in 2005.

INCPOV1 POVERTY STATUS Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Replaced INCPOV1R starting in 2005. 

INCPOV1R used two categories whereas 

INCPOV1 uses three.

INCPOV1R POVERTY STATUS (RECODE) Y Replaced by INCPOV1 starting in 2005.

INCQ298A FAMILY INCOME CATEGORIES 

(RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Replaced INCQ298R starting in 2005. 

INCQ298A uses different categories than were 

used by INCQ298R.

INCQ298R FAMILY INCOME CATEGORIES 

(RECODE) Y Replaced by INCQ298A starting in 2005.

INOPHONR

LENGTH OF INTERRUPTION IN 

TELEPHONE SERVICE IN DAYS 

(RECODE)

Y Y Y Y Y Y Dropped starting in 2010 due to questionnaire 

change.

INS_1

IS CHILD COVERED BY HEALTH 

INSURANCE PROVIDED 

THROUGH EMPLOYER OR 

UNION?

Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_11

ANY TIME WHEN CHILD WAS 

NOT COVERED BY ANY HEALTH 

INSURANCE?

Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_2 IS CHILD COVERED BY ANY 

MEDICAID PLAN? Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_3 IS CHILD COVERED BY S-CHIP? Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_3A IS CHILD COVERED BY ANY 

MEDICAID PLAN OR S-CHIP? Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_4 IS CHILD COVERED BY INDIAN 

HEALTH SERVICE? Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced by INS_4_5 starting in 

2009.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

INS_4_5

IS CHILD COVERED BY INDIAN 

HEALTH SERVICE, MILITARY 

HEALTH CARE, TRICARE, 

CHAMPUS, OR CHAMP-VA?

Y Y Y Y Y Y Y 

Replaced INS_4 and INS_5 starting in 2009. 

Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_5

IS CHILD COVERED BY 

MILITARY HEALTH CARE, 

TRICARE, CHAMPUS, OR CHAMPVA?

Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced by INS_4_5 starting in 

2009.

INS_6

IS CHILD COVERED BY ANY 

OTHER HEALTH INSURANCE OR 

HEALTH CARE PLAN?

Y Y Y Y Y Y Y Y Y 

Health insurance questions were added to the 

questionnaire in 2006 and first included on the 

PUF in 2007. Replaced with INS_STAT_I and 

INS_BREAK_I in 2016.

INS_BREAK_I

CONTINUITY OF INSURANCE 

COVERAGE SINCE BIRTH: 

IMPUTED

Y Y Y Y Replaced INS_1-INS_11 starting in 2016.

INS_STAT_I INSURANCE STATUS: IMPUTED Y Replaced INS_1-INS_11 starting in 2016. 

Replaced by INS_STAT2_I starting in 2017.

INS_STAT2_I

INSURANCE STATUS (PRIVATE 

ONLY/ANY MEDICAID/OTHER 

INSURANCE/UNINSURED): 

IMPUTED

Y Y Y Replaced INS_STAT_I starting in 2017.

INTRP PHONE INTERRUPTION OF 7 

DAYS OR MORE IN PAST YEAR? Y Y Y Y Y Y Y Y Y Y Y Y Dropped starting in 2016 due to questionnaire change.

ITRUEIAP IAP AREA OF CURRENT 

RESIDENCE Y Replaced by ESTIAP in 2005 because estimation areas were modified. 

LANGUAGE LANGUAGE IN WHICH 

INTERVIEW WAS CONDUCTED Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

M_AGEGRP AGE OF MOTHER CATEGORIES 

(RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Replaced by M_AGEGRP2 starting in 2016.

M_AGEGRP2 AGE OF MOTHER CATEGORIES: 

IMPUTED (RECODE) Y Y Y Y Replaced M_AGEGRP starting in 2016.

MARITAL MARITAL STATUS OF MOTHER 

CATEGORIES (RECODE) Y Y Y Y Y Replaced by MARITAL2 starting in 2009.

MARITAL2 MARITAL STATUS OF MOTHER: 

IMPUTED (RECODE) Y Y Y Y Y Y Y Y Y Y Y Replaced MARITAL starting in 2009.

MMR1_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR2_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR3_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

MMR4_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR5_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MMR6_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MMR7_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MMR8_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MMR9_AGE

AGE IN MONTHS OF PROVREPTD MEASLES-CONTAINING 

SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MOBIL

GEOGRAPHIC MOBILITY 

STATUS: STATE OF RESIDENCE 

OF CHILD AT BIRTH VERSUS 

CURRENT STATE

Y Replaced by MOBIL_I starting in 2005.

MOBIL_I

GEOGRAPHIC MOBILITY 

STATUS: STATE OF RESIDENCE 

OF CHILD AT BIRTH VERSUS 

CURRENT STATE: IMPUTED

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Replaced MOBIL starting in 2005. This 

version is imputed.

MP1_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP2_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP3_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP4_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP5_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MP6_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MP7_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MP8_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MP9_AGE AGE IN MONTHS OF PROVREPTD MUMPS-ONLY SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

MPR1_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR2_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR3_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR4_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR5_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MPR6_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MPR7_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MPR8_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

MPR9_AGE

AGE IN MONTHS OF PROVREPTD (MUMPS/RUBELLA)-ONLY 

SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

N_PRVR

NUMBER OF PROVIDERS 

RESPONDING WITH 

VACCINATION DATA FOR CHILD 

(RECODE)

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

NUM_CELLS_HH

NUMBER OF WORKING CELL 

PHONES HOUSEHOLD MEMBERS 

HAVE AVAILABLE FOR 

PERSONAL USE

Y Y Y Y Y Y Y Y Y Y Y Question added to household questionnaire in 

2009.

NUM_CELLS_PARENTS

NUMBER OF WORKING CELL 

PHONES USUALLY USED BY 

PARENTS OR GUARDIANS

Y Y Y Y Y Y Y Y Y Y Y Question added to household questionnaire in 

2009.

NUM_PHONE

NUMBER OF RESIDENTIAL 

TELEPHONE NUMBERS IN 

HOUSEHOLD (EXCLUDING CELL 

PHONES)

Y Y Y Y Y Y Y Y Y Y Y Question added to household questionnaire in 

2009.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUHEPX

NUMBER OF HEPATITIS B-ONLY 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUHIBX

NUMBER OF HIB-ONLY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUHPHB

NUMBER OF HEPATITIS B/HIB 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUM1L

NUMBER OF MONOVALENT 2009 

H1N1 INFLUENZA 

VACCINATIONS OF UNKNOWN 

TYPE BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_NUM1M

NUMBER OF MONOVALENT 2009 

H1N1 INFLUENZA SPRAY 

VACCINATIONS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_NUM1N

NUMBER OF INJECTED 

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATIONS BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_NUMDAH

NUMBER OF DTAP/HIB COMBO 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMDHB

NUMBER OF DTP/HIB 

CONTAINING SHOTS 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Dropped in 2009 due to change to IHQ 

shotgrid.

P_NUMDHI

NUMBER OF DTAP/HEPB/IPV 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMDHM

NUMBER OF DTP/HIB COMBO 

SHOTS DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Dropped in 2009 due to change to IHQ 

shotgrid.

P_NUMDIH

NUMBER OF DTAP/IPV/HIB 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to change to IHQ shotgrid.

P_NUMDTA

NUMBER OF DTAP-ONLY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMDTM

NUMBER OF DT-ONLY SHOTS 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Dropped in 2009 due to change to IHQ 

shotgrid.

P_NUMDTP

NUMBER OF DT-CONTAINING 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMFLU

NUMBER OF SEASONAL FLUCONTAINING VACCINATIONS BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMFLUL

NUMBER OF SEASONAL FLUCONTAINING VACCINATIONS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

P_NUMFLUM

NUMBER OF SEASONAL FLU 

SPRAY VACCINATIONS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

P_NUMFLUN

NUMBER OF INJECTED 

SEASONAL FLU VACCINATIONS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

P_NUMH1N

NUMBER OF MONOVALENT 2009 

H1N1 INFLUENZA 

VACCINATIONS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_NUMH2

NUMBER OF HIB-SANOFI or HIBGLAXOSMITHKLINE SHOTS BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y 

Added in 2009 due to change to IHQ shotgrid. 

Replaced by P_NUMHG and P_NUMHS 

starting in 2010.

P_NUMHEA

NUMBER OF HEPATITIS ACONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMHEN

NUMBER OF HEPATITIS BCONTAINING SHOTS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMHEP

NUMBER OF HEPATITIS BCONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMHG

NUMBER OF HIBGLAXOSMITHKLINE SHOTS BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Replaced P_NUMH2 starting in 2010 due to a 

change to the IHQ shotgrid. 

P_NUMHHY

NUMBER OF HIB-MENCY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Added in 2014 due to change in IHQ shotgrid.

P_NUMHIB

NUMBER OF HIB-CONTAINING 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMHIN

NUMBER OF HIB-CONTAINING 

SHOTS OF UNKNOWN TYPE BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMHION

NUMBER OF HIB-ONLY SHOTS 

OF UNKNOWN TYPE BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to change to IHQ shotgrid.

P_NUMHM

NUMBER OF HIB-MERCK SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to change to IHQ shotgrid.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMHS

NUMBER OF HIB-SANOFI SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Replaced P_NUMH2 starting in 2010 due to a 

change in the IHQ shotgrid. 

P_NUMIPV

NUMBER OF IPV-ONLY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMCN

NUMBER OF MEASLESCONTAINING SHOTS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMMMR

NUMBER OF MEASLESCONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMMRX

NUMBER OF MMR-ONLY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMMMX

NUMBER OF MMR-CONTAINING 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMP

NUMBER OF MUMPS-ONLY 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMMPR

NUMBER OF (MUMPS/RUBELLA)-

ONLY SHOTS BY 36 MONTHS OF 

AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMRV

NUMBER OF MMR/VARICELLA 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMMS

NUMBER OF MEASLES-ONLY 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMSM

NUMBER OF MEASLES/MUMPS 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMMSR

NUMBER OF MEASLES/RUBELLA 

COMBO SHOTS BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMOLN

NUMBER OF POLIO SHOTS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMOPV

NUMBER OF OPV-ONLY SHOTS 

BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMPCC

NUMBER OF PNEUMOCOCCAL

CONJUGATE SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMPCC13

NUMBER OF PNEUMOCOCCAL 

CONJUGATE-13 SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Added in 2010 due to new PCV vaccination 

recommendations.

P_NUMPCC7

NUMBER OF PNEUMOCOCCAL 

CONJUGATE-7 SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Added in 2010 due to new PCV vaccination 

recommendations.

P_NUMPCCN

NUMBER OF PNEUMOCOCCAL 

CONJUGATE SHOTS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Added in 2010 due to new PCV vaccination 

recommendations.

P_NUMPCN

NUMBER OF PNEUMOCOCCAL

SHOTS OF UNKNOWN TYPE BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMPCP

NUMBER OF PNEUMOCOCCAL

POLYSACCHARIDE SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMPCV

NUMBER OF PNEUMOCOCCALCONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMPOL

NUMBER OF POLIO-CONTAINING 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMRB

NUMBER OF RUBELLA-ONLY 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMRG

NUMBER OF ROTARIX-GSK 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Starting in 2009, rotavirus type boxes were 

added to the IHQ shot grid.

P_NUMRM

NUMBER OF ROTATEQ-MERCK 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Starting in 2009, rotavirus type boxes were 

added to the IHQ shot grid.

P_NUMRO

NUMBER OF ROTAVIRUS SHOTS 

OF UNKNOWN TYPE BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Starting in 2009, rotavirus type boxes were 

added to the IHQ shot grid.

P_NUMROT

NUMBER OF ROTAVIRUSCONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMTPM

NUMBER OF DTP-ONLY SHOTS 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Dropped in 2009 due to change to IHQ 

shotgrid.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_NUMTPN

NUMBER OF DT-CONTAINING 

SHOTS OF UNKNOWN TYPE BY 

36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMVRC

NUMBER OF VARICELLACONTAINING SHOTS BY 36 

MONTHS OF AGE DETERMINED 

FROM PROVIDER INFO, 

EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_NUMVRN

NUMBER OF VARICELLACONTAINING SHOTS OF 

UNKNOWN TYPE BY 36 MONTHS 

OF AGE DETERMINED FROM 

PROVIDER INFO, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HH INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_NUMVRX

NUMBER OF VARICELLA-ONLY 

SHOTS BY 36 MONTHS OF AGE 

DETERMINED FROM PROVIDER 

INFO, EXCLUDING ANY 

VACCINATIONS AFTER THE HH 

INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Added in 2006 so that each vaccine type on 

the IHQ has a corresponding shot count 

variable.

P_U12VRC

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 1+ VARICELLACONTAINING SHOT AT 12+ 

MONTHS OF AGE, BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTD331

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3:3:1 BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTD431

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1 BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_UTD431H_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3 BY 36 MONTHS 

OF AGE, USING THE ROUTINE, 

STRICT DEFINITION OF HIB UTD, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTD431H3_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3 BY 36 

MONTHS OF AGE, USING THE 

ROUTINE, STRICT DEFINITION 

OF HIB UTD, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTD431H31_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1 BY 36 

MONTHS OF AGE (INCLUDES 1+ 

VARICELLA-CONTAINING AT 

AGE 12+ MTHS) USING THE 

ROUTINE, STRICT DEFINITION 

OF HIB UTD, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTD431H313_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1:3 BY 36 

MONTHS OF AGE (INCLUDES 1+ 

VARICELLA-CONTAINING AT 

AGE 12+ MTHS) USING THE 

ROUTINE, STRICT DEFINITION 

OF HIB UTD, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTD431H314_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1:4 BY 36 

MONTHS OF AGE (INCLUDES 1+ 

VARICELLA-CONTAINING AT 

AGE 12+ MTHS) USING THE 

ROUTINE, STRICT DEFINITION 

OF HIB UTD, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTDFL1

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER SEASONAL 

INFLUENZA VARIABLE 1 BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Dropped starting in 2014 due to change in 

ACIP recommendations.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_UTDFL2

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER SEASONAL 

INFLUENZA VARIABLE 2 BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Dropped starting in 2014 due to change in 

ACIP recommendations.

P_UTDFL3

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER SEASONAL 

INFLUENZA VARIABLE 3 BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y 

Added in 2007 due to new influenza 

vaccination recommendations. Dropped 

starting in 2014 due to change in ACIP 

recommendations.

P_UTDH1N_1

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 1+ MONOVALENT 

2009 H1N1 INFLUENZA 

VACCINATION BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE 

AND EXCLUDING 

VACCINATIONS GIVEN PRIOR TO 

10/5/2009.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_UTDH1N_2

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 2+ MONOVALENT 

2009 H1N1 INFLUENZA 

VACCINATIONS BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE 

AND EXCLUDING 

VACCINATIONS GIVEN PRIOR TO 

10/5/2009.

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

P_UTDHEP

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ HEPATITIS BCONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDHEPA1

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 1+ HEPATITIS ACONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Added in 2011 to aid analysis. 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_UTDHEPA2

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 2+ HEPATITIS ACONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Added in 2010 to aid analysis. 

P_UTDHIB

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ HIB-CONTAINING 

SHOTS BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDHIB_ROUT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ HIB DOSES BY 36 

MONTHS OF AGE, BASED ON 

THE ROUTINE (NON-SHORTAGE) 

HIB RECOMMENDATIONS AND A 

STRICT TREATMENT OF HIB 

SHOTS OF UNKNOWN TYPE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTDHIB_SHORT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ HIB DOSES BY 36 

MONTHS OF AGE, BASED ON 

THE HIB SHORTAGE 

RECOMMENDATIONS AND A 

STRICT TREATMENT OF HIB 

SHOTS OF UNKNOWN TYPE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 due to new Hib vaccination 

recommendations.

P_UTDMCV

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 1+ MEASLESCONTAINING SHOT BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDMMX

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 1+ MMR COMBO 

SHOT BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

P_UTDPC3

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ PNEUMOCOCCALCONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDPCV

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4+ PNEUMOCOCCALCONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDPCVB13

UTD (UP-TO-DATE) INDICATOR 

FOR PROVIDER 1+ 

PNEUMOCOCCAL 

VACCINATIONS OF TYPE 

CONJUGATE-13, GIVEN 4+ DOSES 

OF TYPE CONJUGATE-7, BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Added in 2010 due to new PCV vaccination 

recommendations.

P_UTDPOL

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ POLIOCONTAINING SHOTS BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDROT_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ ROTAVIRUS DOSES 

BY 36 MONTHS OF AGE, BASED 

ON A STRICT TREATMENT OF 

ROTAVIRUS VACCINATIONS OF 

UNKNOWN TYPE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Added in 2009 to aid analysis. 

P_UTDTP3

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ DT-CONTAINING 

SHOTS BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

P_UTDTP4

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4+ DT-CONTAINING 

SHOTS BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

PCV1_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV2_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV3_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV4_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV5_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV6_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV7_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV8_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV9_AGE

AGE IN MONTHS OF PROVREPTD PNEUMOCOCCALCONTAINING SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

PDAT CHILD HAS ADEQUATE 

PROVIDER DATA Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL1_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL2_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL3_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL4_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL5_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

POL6_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL7_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL8_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL9_AGE

AGE IN MONTHS OF PROVREPTD POLIO-CONTAINING 

SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

PROV_FAC PROVIDER FACILITY TYPES: 

IMPUTED Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PROVWT

WEIGHT FOR CHILDREN WITH 

ADEQUATE PROVIDER DATA 

AND UNVACCINATED CHILDREN 

(EXCLUDING U.S. VIRGIN 

ISLANDS)

Y Y Y Y Y Y 

Added in 2005 to replace WGT. Replaced by 

PROVWT_LL in 2011 due to addition of 

dual-frame weights.

PROVWT_C

FINAL SINGLE-FRAME CELLPHONE PROVIDER-PHASE 

WEIGHT (EXCLUDES 

TERRITORIES)

Y Y Replaced PROVWT_D in 2018 due to 

removal of the landline sample.

PROVWT_C_TERR

FINAL SINGLE-FRAME CELLPHONE PROVIDER-PHASE 

WEIGHT INCLUDING 

TERRITORIES

Y 

Added in 2019 to replace 

PROVWT_D_TERR due to removal of the 

landline sample

PROVWT_D

FINAL DUAL-FRAME PROVIDERPHASE WEIGHT (EXCLUDES 

TERRITORIES)

Y Y Y Y Y Y Y 

Added in 2011 as dual-frame weight.

Replaced by PROVWT_C in 2018 due to 

removal of the landline sample.

PROVWT_LL

LANDLINE-FRAME WEIGHT FOR 

CHILDREN WITH ADEQUATE 

PROVIDER DATA AND 

UNVACCINATED CHILDREN 

(EXCLUDING U.S. VIRGIN 

ISLANDS)

Y 

Replaced PROVWT in 2011 to distinguish 

from new dual-frame weight PROVWT_D. 

Removed in 2012. 

PROVWTVI

WEIGHT FOR CHILDREN WITH 

ADEQUATE PROVIDER DATA 

AND UNVACCINATED CHILDREN 

(INCLUDING U.S. VIRGIN 

ISLANDS)

Y Y 

Added in 2009 to include U.S. Virgin Island 

sample. Replaced by PROVWTVI_LL in 

2011 due to addition of dual-frame weights. 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

PROVWTVI_D

COMBINATION OF THE DUALFRAME WEIGHT FOR CHILDREN 

IN THE U.S. PROPER AND 

LANDLINE WEIGHT FOR 

CHILDREN IN THE U.S. VIRGIN

ISLANDS FOR CHILDREN WITH 

ADEQUATE PROVIDER DATA 

AND UNVACCINATED CHILDREN

Y 

Replaced PROVWTVI_LL in 2012. Replaced 

with PROVWTVIGU_D in 2013 due to the 

addition of Guam sample.

PROVWTVIGU_D

THE DUAL-FRAME WEIGHT FOR 

CHILDREN IN THE U.S. PROPER, 

THE U.S. VIRGIN ISLANDS AND 

GUAM FOR CHILDREN WITH 

ADEQUATE PROVIDER DATA 

AND UNVACCINATED CHILDREN

Y 

Replaced PROVWTVI_D in 2013 due to the 

addition of Guam sample. Replaced with 

PROVWT_D_TERR in 2014 due to addition 

of Puerto Rico sample.

PROVWT_D_TERR

FINAL DUAL-FRAME PROVIDERPHASE WEIGHT INCLUDING 

TERRITORIES

Y Y Y 

Replaced PROVWTVIGU_D in 2014 due to 

addition of Puerto Rico sample. Not available 

on the 2017 PUF as no data from U.S. 

territories were included.

PROVWTVI_LL

LANDLINE-FRAME WEIGHT FOR 

CHILDREN WITH ADEQUATE 

PROVIDER DATA AND 

UNVACCINATED CHILDREN 

(INCLUDING U.S. VIRGIN 

ISLANDS)

Y Replaced PROVWTVI in 2011. Replaced with 

dual-frame weight PROVWTVI_D in 2012.

PU431_31

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1::3:1 (4:3:1:3:3:1 

EXCLUDING HIB; INCLUDES 1+ 

VARICELLA AT AGE 12+ MTHS) 

BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW 

DATE.

Y Y Y Y Y Y Y Y Y Added in 2010 to aid analysis. Dropped in 

2019.

PU431_314

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1::3:1:4 

(4:3:1:3:3:1:4 EXCLUDING HIB; 

INCLUDES 1+ VARICELLA AT 

AGE 12+ MTHS) BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW 

DATE.

Y Y Y Y Y Y Y Y Y Added in 2010 to aid analysis. Dropped in 

2019.

PU431331

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1 (INCLUDES 

1+ VARICELLA AT AGE 12+ 

MTHS) BY 36 MONTHS OF AGE, 

EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

PU4313313

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1:3 

(INCLUDES 1+ VARICELLA AT 

AGE 12+ MTHS) BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Added in 2007 to aid analysis. 

PU4313314

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1:4 

(INCLUDES 1+ VARICELLA AT 

AGE 12+ MTHS) BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Added in 2007 to aid analysis. 

PUT43133

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3 BY 36 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PUTD4313

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3 BY 36 MONTHS 

OF AGE, EXCLUDING ANY 

VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

Q5WEB1 INTEREST IN IHQ ON WEBSITE 

PROVIDER #1 Y Question was not asked starting in 2005.

Q5WEB2 INTEREST IN IHQ ON WEBSITE 

PROVIDER #2 Y Question was not asked starting in 2005.

Q5WEB3 INTEREST IN IHQ ON WEBSITE 

PROVIDER #3 Y Question was not asked starting in 2005.

Q5WEB4 INTEREST IN IHQ ON WEBSITE 

PROVIDER #4 Y Question was not asked starting in 2005.

Q5WEB5 INTEREST IN IHQ ON WEBSITE 

PROVIDER #5 Y Question was not asked starting in 2005.

RACE_K RACE OF CHILD: IMPUTED

(RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RACEETHK RACE/ETHNICITY OF CHILD: 

IMPUTED (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB1_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB2_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB3_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB4_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

RB5_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB6_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB7_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB8_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB9_AGE AGE IN MONTHS OF PROVREPTD RUBELLA-ONLY SHOT #9 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

RDDWT

HH-PHASE CHILD INTERVIEW 

WEIGHT (EXCLUDING U.S. 

VIRGIN ISLANDS)

Y Y Y Y Y Y 

Added in 2005 to replace WGT_RDD. 

Replaced by RDDWT_LL in 2011 due to 

addition of dual-frame weights.

RDDWT_C

FINAL SINGLE-FRAME CELLPHONE RDD-PHASE WEIGHT 

(EXCLUDES TERRITORIES)

Y Y Replaced RDDWT_D in 2018 due to removal 

of the landline sample.

RDDWT_C_TERR

FINAL SINGLE-FRAME CELLPHONE RDD-PHASE WEIGHT 

INCLUDES TERRITORIES

Y 

Added in 2019 to replace 

RDDWT_D_TERR due to removal of the 

landline sample.

RDDWT_D

FINAL DUAL-FRAME RDD-PHASE

WEIGHT (EXCLUDES 

TERRITORIES)

Y Y Y Y Y Y Y 

Added in 2011 as dual-frame weight. 

Replaced by RDDWT_C in 2018 due to 

removal of the landline sample.

RDDWT_LL

LANDLINE-FRAME HH-PHASE 

CHILD INTERIVEW WEIGHT 

(EXCLUDING U.S. VIRGIN 

ISLANDS)

Y 

Replaced RDDWT in 2011 to distinguish from 

new dual-frame weight RDDWT_D. Removed 

in 2012.

RDDWTVI

HH-PHASE CHILD INTERVIEW 

WEIGHT (INCLUDING U.S. 

VIRGIN ISLANDS)

Y Y 

Added in 2009 to include U.S. Virgin Island 

sample. Replaced by RDDWTVI_LL in 2011 

due to addition of dual-frame weights.

RDDWTVI_D

COMBINATION OF THE DUALFRAME HH-PHASE WEIGHT FOR 

HOUSEHOLDS IN THE U.S. 

PROPER AND LANDLINE HHPHASE WEIGHT FOR 

HOUSEHOLDS IN THE U.S. 

VIRGIN ISLANDS

Y 

Replaced RDDWTVI_LL in 2012. Replaced 

with RDDWTVIGU_D in 2013 due to the 

addition of Guam sample.

RDDWTVIGU_D

THE DUAL-FRAME HH-PHASE 

WEIGHT FOR HOUSEHOLDS IN 

THE U.S. PROPER, THE U.S. 

VIRGIN ISLANDS AND GUAM

Y 

Replaced RDDWTVI_D in 2013 due to the 

addition of Guam sample. Replaced with 

RDDWT_D_TERR in 2014 due to addition of 

Puerto Rico sample.

RDDWT_D_TERR

FINAL DUAL-FRAME RDD-PHASE 

WEIGHT INCLUDING 

TERRITORIES

Y Y Y 

Replaced RDDWTVIGU_D in 2014 due to 

addition of Puerto Rico sample. Not available 

on the 2017 PUF as no data from U.S. 

territories were included.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

RDDWTVI_LL

LANDLINE-FRAME HH-PHASE 

CHILD INTERIVEW WEIGHT 

(INCLUDING U.S. VIRGIN 

ISLANDS)

Y Replaced RDDWTVI in 2011. Replaced with 

dual-frame weight RDDWTVI_D in 2012.

REGISTRY

CHILD'S PROVIDERS REPORTED 

CHILD'S VACCINATIONS TO 

IMMUNIZATION REGISTRY

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RENT_OWN

IS HOME OWNED/BEING 

BOUGHT, RENTED, OR 

OCCUPIED BY SOME OTHER 

ARRANGEMENT?

Y Y Y Y Y Y Y Y Y Y Y Question added to the questionnaire starting in 

late 2008, and introduced in the PUF in 2009. 

ROT1_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT2_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT3_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT4_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT5_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT6_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT7_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT8_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT9_AGE

AGE IN MONTHS OF PROVREPTD ROTAVIRUSCONTAINING SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

SC_431 HH SHOT CARD REPORT OF 4:3:1 

UP-TO-DATE Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_4313 HH SHOT CARD REPORT OF 

4:3:1:3 UP-TO-DATE Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

SC_43133 HH SHOT CARD REPORT OF 

4:3:1:3:3 UP-TO-DATE Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_DTP HH SHOT CARD REPORT OF 4+ 

DT-CONTAINING UP-TO-DATE Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_HEPB

HH SHOT CARD REPORT OF 3+ 

HEPATITIS B-CONTAINING UPTO-DATE

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_HIB HH SHOT CARD REPORT OF 3+ 

HIB-CONTAINING UP-TO-DATE Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_MCV

HH SHOT CARD REPORT OF 1+ 

MEASLES-CONTAINING UP-TODATE

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_POL

HH SHOT CARD REPORT OF 3+ 

POLIO-CONTAINING UP-TODATE

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SC_VRC

HH SHOT CARD REPORT OF 1+ 

VARICELLA-CONTAINING UPTO-DATE

Y Y Y Y Y Y 

Added in 2006 as a partial replacement for the 

"FULL" and "C_" variables. Dropped in 2012 

due to questionnaire changes.

SEQNUMC UNIQUE CHILD IDENTIFIER Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

SEQNUMHH UNIQUE HOUSEHOLD 

IDENTIFIER Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

SEX SEX OF CHILD: IMPUTED Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

SHORT Q1/2004 SHORT QUESTIONNAIRE 

STUDY FLAG Y There was no short questionnaire study starting in 2005.

STATE TRUE STATE OF RESIDENCE 

(STATE FIPS CODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

STRATUM STRATUM VARIABLE FOR 

VARIANCE ESTIMATION Y Y Y Y Y Y Y Y Replaced STRATUM_D in 2012. Equal to 

sample frame by estimation area.

STRATUM_D STRATUM VARIABLE FOR DUALFRAME VARIANCE ESTIMATION Y 

Added in 2011. Equal to sample frame by 

estimation area. Replaced by STRATUM in 

2012.

TEL_SAMPFRAME SAMPLE FRAME INDICATOR Y Added in 2011. Dropped in 2012 due to use of 

only dual-frame weights. 

U1D_HEP

BIRTH DOSE HEPATITIS BCONTAINING GIVEN FROM 

BIRTH TO DAY 1 FLAG

Y Y Y Y Y Y Y Y Y Added 2011 to aid analysis. 
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173

Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

U24_FLU_24D

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 2+ INFLUENZA 

VACCINATIONS AT LEAST 4 

WEEKS-4 DAYS APART BY 24 

MONTHS OF AGE, EXCLUDING 

ANY VACCINATIONS AFTER THE 

HOUSEHOLD INTERVIEW DATE.

Y Y New up-to-date variable added in 2018.

U2D_HEP

BIRTH DOSE HEPATITIS BCONTAINING GIVEN FROM 

BIRTH TO DAY 2 FLAG

Y Y Y Y Y Y Y Y Y Added 2011 to aid analysis. 

U3D_HEP

BIRTH DOSE HEPATITIS BCONTAINING GIVEN FROM 

BIRTH TO DAY 3 FLAG

Y Y Y Y Y Y Y Y Y Added 2011 to aid analysis. 

VFC_I DERIVED: IS CHILD VFC 

ELIGIBLE? Y Y Y Added in 2009 to aid analysis. Dropped 

starting in 2012 due to a change in the IHQ.

VFC_ORDER

DO CHILD'S PROVIDERS ORDER 

VACCINES FROM STATE/LOCAL 

HEALTH DEPT?

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Added in 2006 due to a change in the IHQ.

VFC_PRO

PARTICIPATION OF CHILD'S 

PROVIDERS IN VACCINES FOR 

CHILDREN PROGRAM

Y Y Question was not asked starting in 2006.

VRC1_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC2_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC3_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC4_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC5_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

VRC6_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

VRC7_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

VRC8_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

VRC9_AGE

AGE IN MONTHS OF PROVREPTD VARICELLA-CONTAINING 

SHOT #9

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

WGT

NEW WEIGHT FOR CHILDREN 

WITH ADEQUATE PROVIDER 

DATA AND UNVACCINATED 

CHILDREN

Y Replaced by PROVWT starting in 2005.

WGT_RDD RDD CHILD INTERVIEW WEIGHT Y Replaced by RDDWT starting in 2005.

XDTPTY1 DT-CONTAINING VACCINATION 

#1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY2 DT-CONTAINING VACCINATION 

#2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY3 DT-CONTAINING VACCINATION 

#3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY4 DT-CONTAINING VACCINATION 

#4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY5 DT-CONTAINING VACCINATION 

#5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY6 DT-CONTAINING VACCINATION 

#6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY7 DT-CONTAINING VACCINATION 

#7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY8 DT-CONTAINING VACCINATION 

#8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XDTPTY9 DT-CONTAINING VACCINATION 

#9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XFLUTY1 SEASONAL FLU-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY2 SEASONAL FLU-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY3 SEASONAL FLU-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY4 SEASONAL FLU-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY5 SEASONAL FLU-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY6 SEASONAL FLU-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY7 SEASONAL FLU-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY8 SEASONAL FLU-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.

XFLUTY9 SEASONAL FLU-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2008, influenza type boxes were 

added to the IHQ shot grid.
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

XH1NTY1

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #1 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY2

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #2 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY3

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #3 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY4

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #4 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY5

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #5 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY6

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #6 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY7

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #7 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY8

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #8 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XH1NTY9

MONOVALENT 2009 H1N1 

INFLUENZA VACCINATION #9 

TYPE CODE

Y Y Y 

H1N1 influenza added to the IHQ shotgrid 

starting in late 2009, and introduced in the 

PUF in 2010. Removed from the IHQ and the 

PUF in 2013.

XHEPTY1 HEPATITIS B-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY2 HEPATITIS B-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY3 HEPATITIS B-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY4 HEPATITIS B-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY5 HEPATITIS B-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 
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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

XHEPTY6 HEPATITIS B-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY7 HEPATITIS B-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY8 HEPATITIS B-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHEPTY9 HEPATITIS B-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XHIBTY1 HIB-CONTAINING VACCINATION 

#1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY2 HIB-CONTAINING VACCINATION 

#2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY3 HIB-CONTAINING VACCINATION 

#3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY4 HIB-CONTAINING VACCINATION 

#4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY5 HIB-CONTAINING VACCINATION 

#5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY6 HIB-CONTAINING VACCINATION 

#6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY7 HIB-CONTAINING VACCINATION 

#7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY8 HIB-CONTAINING VACCINATION 

#8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XHIBTY9 HIB-CONTAINING VACCINATION 

#9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XMMRTY1 MEASLES-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XMMRTY2 MEASLES-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XMMRTY3 MEASLES-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XMMRTY4 MEASLES-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XMMRTY5 MEASLES-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XMMRTY6 MEASLES-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XMMRTY7 MEASLES-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XMMRTY8 MEASLES-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.
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177

Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

XMMRTY9 MEASLES-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XPCVTY1 PNEUMOCOCCAL-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY2 PNEUMOCOCCAL-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY3 PNEUMOCOCCAL-CONTAINING

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY4 PNEUMOCOCCAL-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY5 PNEUMOCOCCAL-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY6 PNEUMOCOCCAL-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY7 PNEUMOCOCCAL-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY8 PNEUMOCOCCAL-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPCVTY9 PNEUMOCOCCAL-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XPOLTY1 POLIO-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY2 POLIO-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY3 POLIO-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY4 POLIO-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY5 POLIO-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY6 POLIO-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY7 POLIO-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY8 POLIO-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

XPOLTY9 POLIO-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Starting in 2005, nine shot variables are 

included for each vaccine category.

XROTTY1 ROTAVIRUS-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY2 ROTAVIRUS-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.
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178

Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Notes§

XROTTY3 ROTAVIRUS-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY4 ROTAVIRUS-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY5 ROTAVIRUS-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY6 ROTAVIRUS-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY7 ROTAVIRUS-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY8 ROTAVIRUS-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XROTTY9 ROTAVIRUS-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Rotavirus vaccination types were added to the 

IHQ starting 2009.

XVRCTY1 VARICELLA-CONTAINING 

VACCINATION #1 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY2 VARICELLA-CONTAINING 

VACCINATION #2 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY3 VARICELLA-CONTAINING 

VACCINATION #3 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY4 VARICELLA-CONTAINING 

VACCINATION #4 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY5 VARICELLA-CONTAINING 

VACCINATION #5 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY6 VARICELLA-CONTAINING 

VACCINATION #6 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY7 VARICELLA-CONTAINING 

VACCINATION #7 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY8 VARICELLA-CONTAINING 

VACCINATION #8 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

XVRCTY9 VARICELLA-CONTAINING 

VACCINATION #9 TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y Varicella vaccination types were added to the 

IHQ starting 2006.

YEAR YEAR OF INTERVIEW Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

* For a list of variables that appeared in one or more (but not all) NIS-Child public-use data files from 1995-2004, see "Alphabetical Listing of Variables that are Not Available in All Public-Use Data 

Files, National Immunization Survey, 1995-2004": http://www.cdc.gov/nchs/data/nis/pufvariables1995to2004.pdf

† If the variable appeared in the 2019 NIS-Child public-use data file, then the 2019 label is given; otherwise the label from the most recent NIS-Child public-use data file in which the variable 

appeared is given.

§ Starting in 2005, a code of 77 is used for "Don't Know" responses and a code of 99 is used for "Refused" responses.
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179

Appendix F: Summary Tables

Table F.1: Estimated Population Totals and Sample Sizes of Children 19-35 Months of Age by 

State and Estimation Area, National Immunization Survey - Child, 2019 

State/Estimation Area ESTIAP

Estimated 

Population 

Total of 

Children

Number of 

Children 

with 

Complete 

Household 

Interviews

Number of 

Children 

with 

Adequate 

Provider 

Data

Percent of 

Children with 

Adequate 

Provider Data

U.S. National* 5,638,849 33,137 16,365 49.4%

Alabama 20 84,565 570 278 48.8%

Alaska 74 14,353 417 240 57.6%

Arizona 66 122,826 516 260 50.4%

Arkansas 46 53,724 713 376 52.7%

California 68 692,639 668 292 43.7%

Colorado 60 94,636 467 240 51.4%

Connecticut 1 51,299 329 159 48.3%

Delaware 13 15,807 505 249 49.3%

District of Columbia 12 12,599 612 285 46.6%

Florida 22 333,773 953 390 40.9%

Georgia 25 190,559 667 301 45.1%

Hawaii 72 24,113 468 210 44.9%

Idaho 75 31,918 367 190 51.8%

Illinois 212,868 958 456 47.6%

 IL-City of Chicago 35 51,792 298 148 49.7%

 IL-Rest of State 34 161,076 660 308 46.7%

Indiana 36 119,709 527 280 53.1%

Iowa 56 56,069 378 203 53.7%

Kansas 57 53,543 633 398 62.9%

Kentucky 27 78,402 350 182 52.0%

Louisiana 47 86,820 748 355 47.5%

Maine 4 17,495 494 238 48.2%

Maryland 14 105,498 1,343 700 52.1%

Massachusetts 2 104,470 492 270 54.9%

Michigan 38 162,221 636 324 50.9%

Minnesota 40 100,463 415 190 45.8%

Mississippi 28 53,163 655 307 46.9%

Missouri 58 104,029 597 321 53.8%

Montana 61 17,580 485 256 52.8%

Nebraska 59 37,493 404 228 56.4%

Nevada 73 54,053 765 387 50.6%

New Hampshire 5 18,860 426 223 52.3%

New Jersey 8 151,853 684 264 38.6%

New Mexico 49 32,869 974 505 51.8%
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180

State/Estimation Area ESTIAP

Estimated 

Population 

Total of 

Children

Number of 

Children 

with 

Complete 

Household 

Interviews

Number of 

Children 

with 

Adequate 

Provider 

Data

Percent of 

Children with 

Adequate 

Provider Data

New York 324,738 1,261 527 41.8%

 NY-City of New York 11 160,885 839 326 38.9%

 NY-Rest of State 10 163,853 422 201 47.6%

North Carolina 29 177,580 647 337 52.1%

North Dakota 62 15,616 442 232 52.5%

Ohio 41 196,363 560 266 47.5%

Oklahoma 50 72,262 606 302 49.8%

Oregon 76 66,060 341 161 47.2%

Pennsylvania 200,324 1,093 500 45.7%

 PA-Philadelphia County 17 31,398 462 196 42.4%

 PA-Rest of State 16 168,926 631 304 48.2%

Rhode Island 6 15,541 420 249 59.3%

South Carolina 30 82,109 610 287 47.0%

South Dakota 63 17,939 437 240 54.9%

Tennessee 31 119,220 378 179 47.4%

Texas 576,489 3,068 1,397 45.5%

 TX-Bexar County 55 40,493 443 204 46.0%

 TX-City of Houston 54 78,214 397 160 40.3%

 TX-Dallas County 52 60,344 500 198 39.6%

 TX-El Paso County 53 17,982 389 186 47.8%

 TX-Rest of State 51 379,456 1,339 649 48.5%

Utah 64 71,937 463 256 55.3%

Vermont 7 8,289 611 318 52.0%

Virginia 18 144,097 725 358 49.4%

Washington 77 129,938 723 389 53.8%

West Virginia 19 27,358 586 280 47.8%

Wisconsin 44 94,261 518 259 50.0%

Wyoming 65 8,456 432 271 62.7%

Puerto Rico 106 32,198 662 197 29.8%

*Excludes U.S. territories. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File Appendix F

181

Table F.2: Estimated Population Totals and Sample Sizes for Age Group by Maternal Education, 

National Immunization Survey - Child, 2019 

Age Group 

in Months Maternal Education

Children 

with 

Completed 

Household 

Interviews* 

Unweighted 

Completes

Children with 

Completed 

Household 

Interviews* 

Weighted 

Completes†

Children 

with 

Adequate 

Provider 

Data* 

Unweighted 

Completes

Children with 

Adequate 

Provider 

Data* 

Weighted 

Completes§

19-23 <12 Years 937 251,324 433 256,332

19-23 12 Years 1,763 434,007 778 453,659

19-23

>12, Non College 

Graduate

2,547 380,628 1,260 363,089

19-23 College Graduate 4,844 628,405 2,597 621,285

24-29 <12 Years 922 257,528 432 265,943

24-29 12 Years 1,819 461,954 823 437,694

24-29

>12, Non College 

Graduate

2,596 449,860 1,327 416,517

24-29 College Graduate 4,787 725,779 2,470 774,968

30-35 <12 Years 1,191 294,079 533 278,577

30-35 12 Years 2,147 498,575 951 505,017

30-35

>12, Non College 

Graduate

3,413 480,700 1,617 458,568

30-35 College Graduate 6,171 776,009 3,144 807,201

Total 33,137 5,638,849 16,365 5,638,849

* Excludes U.S. territories. 

† Weighted by RDDWT_C. 

§ Weighted by PROVWT_C. 
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182

Table F.3: Estimated Population Totals and Sample Sizes for Age Group by Poverty Status, 

National Immunization Survey - Child, 2019 

Age Group in 

Months Poverty Status

Children 

with 

Completed 

Household 

Interviews*

Unweighted 

Completes

Children 

with 

Completed 

Household 

Interviews* 

Weighted 

Completes†

Children

with 

Adequate 

Provider 

Data* 

Unweighted 

Completes

Children 

with 

Adequate 

Provider 

Data* 

Weighted 

Completes§

19-23 Months Above poverty, > $75K 4,441 612,335 2,430 614,345

19-23 Months Above poverty, <= $75K 3,059 512,213 1,495 521,056

19-23 Months Below poverty 2,015 462,627 978 450,896

19-23 Months Unknown 576 107,190 165 108,069

24-29 Months Above poverty, > $75K 4,400 715,544 2,279 744,175

24-29 Months Above poverty, <= $75K 3,152 564,328 1,609 577,087

24-29 Months Below poverty 1,993 479,048 998 459,656

24-29 Months Unknown 579 136,201 166 114,203

30-35 Months Above poverty, > $75K 5,705 756,691 2,959 786,926

30-35 Months Above poverty, <= $75K 4,062 639,123 1,940 617,139

30-35 Months Below poverty 2,400 505,523 1,148 512,711

30-35 Months Unknown 755 148,026 198 132,586

Total 33,137 5,638,849 16,365 5,638,849

* Excludes U.S. territories. 

† Weighted by RDDWT_C. 

§ Weighted by PROVWT_C. 
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Table F.4: Estimated Population Totals and Sample Sizes for Race/Ethnicity by Poverty Status, 

National Immunization Survey - Child, 2019 

Race/Ethnicity† Poverty Status

Children with 

Completed 

Household 

Interviews* 

Unweighted 

Completes

Children 

with 

Completed 

Household 

Interviews* 

Weighted 

Completes§

Children 

with 

Adequate 

Provider 

Data* 

Unweighted 

Completes

Children 

with 

Adequate 

Provider 

Data* 

Weighted 

Completes¶

Hispanic Above poverty, > $75K 1,729 301,722 803 305,804

Hispanic Above poverty, <= $75K 2,265 451,208 1,042 437,550

Hispanic Below poverty 2,610 635,844 1,249 629,162

Hispanic Unknown 673 149,916 217 165,066

Non-Hispanic White Only Above poverty, > $75K 10,049 1,308,959 5,575 1,379,815

Non-Hispanic White Only Above poverty, <= $75K 5,700 806,394 2,982 833,193

Non-Hispanic White Only Below poverty 1,992 370,078 1,053 350,795

Non-Hispanic White Only Unknown 787 137,072 193 95,116

Non-Hispanic Black Only Above poverty, > $75K 808 170,676 297 158,171

Non-Hispanic Black Only Above poverty, <= $75K 1,015 244,770 403 246,799

Non-Hispanic Black Only Below poverty 962 279,492 399 275,098

Non-Hispanic Black Only Unknown 210 52,673 45 33,617

Non-Hispanic Other & 

Multiple Races Above poverty, > $75K 1,960 303,214 993 301,655

Non-Hispanic Other & 

Multiple Races Above poverty, <= $75K 1,293 213,292 617 197,739

Non-Hispanic Other & 

Multiple Races Below poverty 844 161,783 423 168,208

Non-Hispanic Other & 

Multiple Races Unknown 240 51,756 74 61,059

Total 33,137 5,638,849 16,365 5,638,849

* Excludes U.S. territories.

† Race/Ethnicity is self-reported and mutually exclusive.

§ Weighted by RDDWT_C. 

¶ Weighted by PROVWT_C. 
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Table F.5: Estimated Population Totals and Sample Sizes for Age Group by Race/Ethnicity, 

National Immunization Survey - Child, 2019 

Age Group in 

Months Race/Ethnicity of Child†

Children with 

Completed 

Household 

Interviews*

Unweighted 

Completes

Children 

with 

Completed 

Household 

Interviews* 

Weighted 

Completes§

Children 

with 

Adequate 

Provider 

Data* 

Unweighted 

Completes

Children 

with 

Adequate 

Provider 

Data* 

Weighted 

Completes¶

19-23 Months Hispanic 2,215 463,863 1,017 471,601

19-23 Months Non-Hispanic White Only 5,568 775,768 3,002 790,584

19-23 Months Non-Hispanic Black Only 927 230,042 358 214,424

19-23 Months

Non-Hispanic Other & Multiple 

Races 

1,381 224,692 691 217,755

24-29 Months Hispanic 2,214 507,954 1,021 503,307

24-29 Months Non-Hispanic White Only 5,680 898,097 3,004 905,310

24-29 Months Non-Hispanic Black Only 924 250,195 374 247,426

24-29 Months

Non-Hispanic Other & Multiple 

Races 

1,306 238,875 653 239,078

30-35 Months Hispanic 2,848 566,872 1,273 562,673

30-35 Months Non-Hispanic White Only 7,280 948,638 3,797 963,026

30-35 Months Non-Hispanic Black Only 1,144 267,375 412 251,836

30-35 Months

Non-Hispanic Other & Multiple 

Races 

1,650 266,477 763 271,828

Total 33,137 5,638,849 16,365 5,638,849

* Excludes U.S. territories.

† Race/Ethnicity is self-reported and mutually exclusive.

§ Weighted by RDDWT_C. 

¶ Weighted by PROVWT_C. 
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Table F.6: Estimated Population Totals and Sample Sizes for Age Group by Sex, National 

Immunization Survey - Child, 2019 

Age Group in 

Months Sex 

Children with 

Completed 

Household 

Interviews*

Unweighted 

Completes

Children with 

Completed 

Household 

Interviews* 

Weighted 

Completes†

Children 

with 

Adequate 

Provider 

Data* 

Unweighted 

Completes

Children 

with 

Adequate 

Provider 

Data* 

Weighted 

Completes§

19-23 Months Male 5,308 868,845 2,689 874,788

19-23 Months Female 4,783 825,520 2,379 819,577

 

24-29 Months Male 5,283 984,975 2,650 954,422

24-29 Months Female 4,841 910,146 2,402 940,699

 

30-35 Months Male 6,730 1,030,680 3,250 1,055,290

30-35 Months Female 6,192 1,018,683 2,995 994,072

Total 33,137 5,638,849 16,365 5,638,849

* Excludes U.S. territories. 

† Weighted by RDDWT_C. 

§ Weighted by PROVWT_C. 
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Table F.7: Estimated Vaccination Coverage* with Individual Vaccines and Selected Vaccination Series Among Children 19-35 Months 

of Age by State and Estimation Area, National Immunization Survey - Child, Q1/2019-Q4/2019†

 ≥4 DTaP§ ≥3 Polio¶ ≥1 MMR** Hib-FS†† ≥3 HepB¶¶ HepB Birth 

Dose ≥1 HepA ≥1 Var*** ≥4 PCV††† Rotavirus 4:3:1:3*:3:1:4§§§

U.S. National¶¶¶ 83.3 ± 1.4 92.3 ± 1.0 91.3 ± 1.1 81.0 ± 1.4 91.3 ± 1.1 76.0 ± 1.6 87.9 ± 1.2 90.9 ± 1.1 82.5 ± 1.4 76.0 ± 1.5 72.7 ± 1.6

Alabama 81.0 ± 6.4 95.6 ± 2.4 92.9 ± 3.5 79.8 ± 6.5 91.9 ± 4.7 80.2 ± 6.7 89.2 ± 4.5 93.8 ± 3.2 82.8 ± 6.5 69.1 ± 7.9 70.3 ± 7.7

Alaska 72.3 ± 7.4 87.1 ± 5.3 85.1 ± 5.4 73.9 ± 7.2 86.0 ± 5.7 66.0 ± 7.6 82.5 ± 5.9 81.8 ± 6.0 73.7 ± 7.2 63.0 ± 7.9 61.6 ± 7.6

Arizona 83.1 ± 5.6 94.2 ± 3.4 94.6 ± 3.3 79.5 ± 6.2 91.7 ± 3.8 85.9 ± 4.9 92.0 ± 4.2 94.6 ± 3.2 80.9 ± 5.8 76.4 ± 6.4 72.7 ± 6.7

Arkansas 83.1 ± 5.3 94.9 ± 2.8 93.4 ± 3.2 84.5 ± 4.8 94.1 ± 3.0 78.6 ± 6.0 90.2 ± 4.1 93.2 ± 3.2 83.4 ± 5.2 79.6 ± 5.7 73.9 ± 6.2

California 80.2 ± 8.5 91.4 ± 6.2 86.6 ± 7.0 77.1 ± 8.8 88.0 ± 7.0 70.6 ± 9.3 86.7 ± 6.9 86.8 ± 6.9 77.5 ± 8.6 79.3 ± 8.5 67.4 ± 9.7

Colorado 90.6 ± 4.7 96.1 ± 3.0 96.0 ± 2.9 85.3 ± 6.4 93.0 ± 4.5 75.6 ± 7.7 90.6 ± 4.7 94.2 ± 3.9 89.6 ± 5.3 79.3 ± 7.3 75.2 ± 7.9

Connecticut 90.7 ± 5.5 94.1 ± 4.7 94.5 ± 4.6 86.7 ± 7.1 91.7 ± 5.6 78.9 ± 8.4 91.4 ± 5.6 94.2 ± 4.7 88.3 ± 6.8 83.9 ± 6.8 83.0 ± 7.7

Delaware 88.1 ± 5.6 98.0 ± 1.6 94.9 ± 3.3 86.4 ± 5.8 96.0 ± 2.4 84.5 ± 5.5 93.6 ± 3.5 93.7 ± 3.5 91.5 ± 4.5 79.8 ± 6.7 80.9 ± 6.3

Dist. of Columbia 82.9 ± 6.5 94.3 ± 3.9 90.0 ± 5.3 80.1 ± 6.9 90.1 ± 5.4 83.3 ± 5.9 90.9 ± 5.0 89.1 ± 5.4 83.2 ± 6.6 79.5 ± 6.6 71.5 ± 7.7

Florida 85.4 ± 5.3 92.9 ± 3.5 93.1 ± 3.4 84.0 ± 5.6 94.3 ± 3.0 60.9 ± 7.5 83.7 ± 5.7 93.6 ± 3.3 85.0 ± 5.5 71.4 ± 7.0 75.3 ± 6.5

Georgia 79.8 ± 6.8 94.4 ± 3.8 95.0 ± 3.5 78.4 ± 7.2 93.8 ± 3.9 77.2 ± 6.7 92.2 ± 4.5 94.6 ± 3.5 84.1 ± 6.3 74.2 ± 8.3 71.9 ± 7.4

Hawaii 79.9 ± 7.1 90.1 ± 5.4 88.3 ± 5.8 80.0 ± 7.2 88.9 ± 5.6 82.0 ± 6.7 84.7 ± 6.6 87.2 ± 5.9 79.9 ± 7.2 76.4 ± 7.5 73.2 ± 7.9

Idaho 75.5 ± 7.9 93.0 ± 3.9 91.1 ± 4.7 80.2 ± 7.4 93.4 ± 3.5 71.2 ± 7.8 94.4 ± 2.9 88.1 ± 5.2 76.8 ± 7.7 77.8 ± 7.7 66.5 ± 8.4

Illinois 88.0 ± 3.9 95.7 ± 2.1 94.5 ± 2.5 82.5 ± 4.8 95.2 ± 2.1 79.7 ± 4.8 90.0 ± 3.5 95.6 ± 2.1 87.1 ± 3.9 82.0 ± 4.7 77.0 ± 5.4

IL-City of Chicago 84.7 ± 7.0 94.7 ± 3.9 93.8 ± 4.4 76.3 ± 9.6 91.5 ± 5.2 80.1 ± 7.7 93.0 ± 4.7 94.8 ± 4.3 83.7 ± 6.8 74.4 ± 9.3 68.2 ± 11.9

IL-Rest of State 89.1 ± 4.6 96.1 ± 2.5 94.8 ± 3.0 84.4 ± 5.5 96.4 ± 2.2 79.6 ± 5.8 89.0 ± 4.4 95.8 ± 2.4 88.2 ± 4.7 84.4 ± 5.3 79.9 ± 5.9

Indiana 82.4 ± 5.5 94.5 ± 2.9 91.7 ± 3.8 81.6 ± 5.5 92.8 ± 3.4 80.1 ± 5.9 91.8 ± 4.0 93.5 ± 3.2 80.7 ± 5.8 75.5 ± 6.4 71.6 ± 6.4

Iowa 86.8 ± 5.5 98.3 ± 1.6 95.7 ± 2.7 89.0 ± 4.8 96.3 ± 2.7 86.0 ± 5.4 89.7 ± 4.5 94.9 ± 3.0 89.6 ± 4.8 77.4 ± 6.8 78.7 ± 6.6

Kansas 80.2 ± 6.1 92.3 ± 3.5 93.0 ± 3.5 81.2 ± 5.9 94.3 ± 2.6 83.2 ± 4.8 91.1 ± 3.9 91.1 ± 3.9 85.1 ± 5.4 82.6 ± 5.2 73.9 ± 6.4

Kentucky 86.4 ± 7.2 93.1 ± 5.5 88.4 ± 6.8 80.4 ± 8.4 90.7 ± 5.8 76.6 ± 8.5 85.1 ± 7.3 88.4 ± 6.8 82.5 ± 7.4 67.9 ± 9.4 69.6 ± 9.3

Louisiana 81.0 ± 7.1 90.8 ± 5.3 94.8 ± 3.6 79.1 ± 7.4 94.0 ± 4.1 75.3 ± 7.6 88.7 ± 5.4 93.3 ± 4.2 82.0 ± 7.0 78.7 ± 7.0 71.6 ± 8.0

Maine 89.1 ± 4.8 95.3 ± 3.2 93.5 ± 3.8 87.7 ± 5.1 93.1 ± 3.5 71.2 ± 7.6 88.3 ± 5.1 92.4 ± 3.9 86.2 ± 5.6 77.2 ± 7.2 78.9 ± 6.7

Maryland 86.1 ± 4.1 94.7 ± 2.5 95.6 ± 2.1 84.7 ± 4.1 93.4 ± 2.7 77.4 ± 4.9 91.9 ± 3.1 94.6 ± 2.4 88.3 ± 3.7 82.3 ± 4.5 76.4 ± 5.0

Massachusetts 89.1 ± 6.1 96.8 ± 2.9 96.8 ± 2.9 87.5 ± 6.2 94.9 ± 3.7 87.3 ± 6.2 94.0 ± 4.0 96.6 ± 2.9 88.5 ± 6.0 80.9 ± 8.2 80.1 ± 7.5

Michigan 88.8 ± 5.4 94.7 ± 3.2 92.1 ± 5.1 86.5 ± 6.0 92.4 ± 4.9 79.1 ± 6.1 91.1 ± 4.2 92.6 ± 5.0 86.0 ± 6.0 75.9 ± 7.2 78.7 ± 6.7

Minnesota 88.3 ± 6.7 95.8 ± 3.6 95.2 ± 4.5 88.3 ± 6.6 94.9 ± 3.7 74.6 ± 9.5 91.4 ± 5.6 94.4 ± 4.7 88.0 ± 7.3 82.1 ± 8.2 84.4 ± 7.5

Mississippi 83.2 ± 6.0 95.4 ± 3.0 91.2 ± 4.3 78.8 ± 6.3 96.6 ± 2.0 75.9 ± 6.3 72.3 ± 6.9 91.3 ± 4.3 80.9 ± 6.2 68.0 ± 7.5 73.4 ± 6.7

Missouri 79.0 ± 6.0 87.4 ± 5.0 88.9 ± 4.8 77.0 ± 6.0 89.7 ± 4.4 79.4 ± 5.9 83.0 ± 5.3 88.8 ± 4.5 78.3 ± 6.0 70.7 ± 6.7 69.7 ± 6.4

Montana 78.1 ± 6.6 93.2 ± 4.0 92.7 ± 3.3 80.7 ± 5.9 95.3 ± 3.4 76.8 ± 6.0 84.5 ± 5.0 86.6 ± 5.0 81.8 ± 6.3 69.7 ± 7.4 69.2 ± 7.2

Nebraska 89.8 ± 4.5 96.4 ± 2.4 96.5 ± 2.4 87.7 ± 4.7 96.4 ± 2.7 81.2 ± 5.7 91.5 ± 3.8 95.0 ± 3.3 88.4 ± 4.5 79.5 ± 6.0 81.8 ± 5.7

Nevada 82.8 ± 5.5 91.7 ± 3.7 92.4 ± 3.8 78.5 ± 6.0 91.2 ± 3.8 77.0 ± 5.8 89.8 ± 4.7 92.3 ± 3.9 80.0 ± 6.0 74.1 ± 6.6 69.6 ± 6.8

New Hampshire 85.8 ± 6.5 92.2 ± 5.5 92.7 ± 5.1 83.3 ± 7.3 92.8 ± 5.3 73.6 ± 7.8 89.6 ± 5.7 90.2 ± 6.1 87.6 ± 6.3 86.6 ± 6.3 78.0 ± 8.0

New Jersey 85.1 ± 5.9 93.8 ± 4.3 88.9 ± 5.3 83.0 ± 6.3 92.6 ± 4.5 68.4 ± 7.9 82.7 ± 6.3 86.9 ± 6.0 81.1 ± 6.7 70.6 ± 7.9 70.4 ± 7.8

New Mexico 84.6 ± 4.8 91.9 ± 3.6 93.9 ± 3.1 79.4 ± 5.4 90.8 ± 3.9 74.9 ± 5.4 90.5 ± 3.7 92.1 ± 3.6 79.4 ± 5.5 75.7 ± 5.7 67.3 ± 6.2

New York 82.4 ± 5.0 88.2 ± 4.4 91.1 ± 3.7 78.9 ± 5.3 87.9 ± 4.3 74.8 ± 5.6 79.8 ± 5.3 88.4 ± 4.2 77.0 ± 5.4 68.0 ± 6.3 69.5 ± 5.8

NY-City of New York 80.2 ± 6.4 87.1 ± 5.5 90.7 ± 4.2 74.6 ± 6.9 87.2 ± 5.2 72.8 ± 7.0 78.8 ± 6.3 88.8 ± 4.6 71.1 ± 7.1 65.2 ± 7.5 63.6 ± 7.4

NY-Rest of State 84.5 ± 7.8 89.2 ± 6.9 91.4 ± 6.0 83.1 ± 7.9 88.5 ± 6.8 76.7 ± 8.7 80.8 ± 8.6 88.1 ± 6.9 82.8 ± 8.0 70.7 ± 10.1 75.3 ± 8.9
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187

 ≥4 DTaP§ ≥3 Polio¶ ≥1 MMR** Hib-FS†† ≥3 HepB¶¶ HepB Birth 

Dose ≥1 HepA ≥1 Var*** ≥4 PCV††† Rotavirus 4:3:1:3*:3:1:4§§§

North Carolina 87.3 ± 5.1 94.3 ± 3.6 93.3 ± 3.5 86.7 ± 5.2 95.1 ± 3.1 81.8 ± 6.2 90.1 ± 4.5 93.2 ± 3.5 85.1 ± 5.6 74.9 ± 7.2 80.1 ± 6.1

North Dakota 78.8 ± 6.3 93.0 ± 3.8 94.7 ± 3.3 84.9 ± 5.2 95.0 ± 3.4 85.8 ± 6.2 91.4 ± 4.2 93.7 ± 3.7 81.3 ± 6.1 79.1 ± 6.3 72.8 ± 6.8

Ohio 72.6 ± 8.5 84.5 ± 7.2 82.2 ± 7.7 75.4 ± 8.2 85.7 ± 7.1 76.1 ± 8.9 79.7 ± 8.0 81.2 ± 7.7 76.6 ± 8.2 71.3 ± 8.6 67.9 ± 8.6

Oklahoma 83.7 ± 4.9 90.3 ± 3.9 89.1 ± 4.3 79.2 ± 5.7 90.2 ± 3.9 75.0 ± 6.0 87.6 ± 4.5 88.5 ± 4.4 82.0 ± 5.1 68.0 ± 6.6 73.1 ± 6.2

Oregon 74.2 ± 8.6 91.2 ± 5.3 92.6 ± 4.5 71.1 ± 8.8 85.0 ± 7.1 78.0 ± 7.7 87.9 ± 6.0 91.4 ± 5.2 73.0 ± 8.8 71.3 ± 9.1 61.6 ± 9.4

Pennsylvania 89.6 ± 4.4 94.0 ± 3.8 94.4 ± 3.4 86.9 ± 5.1 92.4 ± 4.1 82.1 ± 5.8 89.7 ± 4.3 94.1 ± 3.4 89.7 ± 4.4 83.8 ± 5.5 79.3 ± 5.9

PA-Philadelphia County 89.5 ± 5.1 95.7 ± 3.1 93.3 ± 4.4 85.9 ± 6.3 93.5 ± 3.9 75.5 ± 8.4 89.1 ± 6.7 91.5 ± 5.4 82.6 ± 7.0 74.9 ± 8.7 76.2 ± 7.6

PA-Rest of State 89.6 ± 5.2 93.7 ± 4.5 94.6 ± 3.9 87.1 ± 5.9 92.2 ± 4.8 83.3 ± 6.7 89.9 ± 5.0 94.6 ± 4.0 91.0 ± 5.1 85.5 ± 6.3 79.9 ± 6.8

Rhode Island 90.0 ± 4.1 95.7 ± 2.9 94.9 ± 3.0 87.6 ± 5.0 96.7 ± 2.5 74.0 ± 6.9 93.9 ± 3.2 94.0 ± 3.1 89.4 ± 4.6 85.1 ± 5.4 78.0 ± 6.2

South Carolina 83.7 ± 5.4 92.8 ± 3.2 92.6 ± 3.7 78.9 ± 6.4 94.2 ± 2.9 79.3 ± 6.6 90.4 ± 4.4 91.9 ± 3.9 85.8 ± 5.1 81.5 ± 5.8 72.8 ± 6.8

South Dakota 83.5 ± 5.7 95.2 ± 2.9 92.5 ± 3.7 79.3 ± 6.2 94.4 ± 3.4 78.7 ± 6.6 91.6 ± 3.7 94.6 ± 2.7 82.7 ± 5.8 74.2 ± 7.3 76.0 ± 6.5

Tennessee 78.9 ± 9.1 92.2 ± 6.1 91.9 ± 5.9 77.8 ± 9.1 96.0 ± 3.5 76.3 ± 8.2 92.7 ± 4.9 94.3 ± 4.5 78.9 ± 9.1 75.2 ± 9.2 65.7 ± 10.2

Texas 80.6 ± 3.2 89.2 ± 2.7 88.5 ± 2.7 77.1 ± 3.5 87.8 ± 2.8 76.4 ± 3.8 88.7 ± 2.5 88.7 ± 2.6 79.9 ± 3.4 73.5 ± 3.7 69.1 ± 3.9

TX-Bexar County 80.3 ± 6.8 93.9 ± 3.9 94.6 ± 3.9 77.9 ± 6.9 93.7 ± 4.5 79.0 ± 7.3 96.1 ± 2.9 94.6 ± 3.9 85.5 ± 5.9 77.6 ± 7.4 74.6 ± 7.4

TX-City of Houston 76.7 ± 9.3 92.3 ± 6.0 90.5 ± 6.9 76.3 ± 9.1 92.2 ± 6.0 82.6 ± 8.0 90.7 ± 6.9 90.3 ± 6.9 79.7 ± 8.4 72.7 ± 9.2 68.0 ± 9.8

TX-Dallas County 77.7 ± 7.2 90.6 ± 5.1 86.7 ± 5.9 77.6 ± 7.1 88.1 ± 5.2 80.6 ± 6.3 83.6 ± 6.5 83.7 ± 6.6 88.1 ± 5.0 72.0 ± 7.6 77.7 ± 6.8

TX-El Paso County 86.7 ± 5.1 95.6 ± 2.9 95.4 ± 3.3 87.7 ± 5.0 96.7 ± 2.4 86.6 ± 5.8 92.5 ± 3.9 95.1 ± 3.6 77.3 ± 7.1 81.3 ± 6.7 64.4 ± 8.3

TX-Rest of State 81.6 ± 4.3 87.6 ± 3.8 87.5 ± 3.7 76.6 ± 4.8 85.9 ± 3.9 73.6 ± 5.3 83.6 ± 6.5 88.2 ± 3.5 79.3 ± 4.6 73.1 ± 5.1 69.0 ± 5.3

Utah 86.2 ± 5.0 92.9 ± 3.6 91.3 ± 4.2 87.5 ± 4.6 93.5 ± 3.4 83.0 ± 5.5 88.2 ± 3.4 91.5 ± 4.1 85.2 ± 5.2 82.8 ± 5.7 79.2 ± 6.0

Vermont 87.1 ± 4.6 91.9 ± 4.0 95.1 ± 3.0 87.6 ± 4.6 91.6 ± 4.1 61.8 ± 6.3 92.0 ± 4.0 90.5 ± 4.0 90.6 ± 4.1 77.1 ± 5.9 79.0 ± 5.5

Virginia 89.1 ± 5.5 95.8 ± 3.6 93.9 ± 4.3 82.2 ± 6.9 94.5 ± 3.7 76.1 ± 7.8 88.7 ± 4.2 94.4 ± 3.8 89.5 ± 5.2 87.6 ± 5.8 78.3 ± 7.3

Washington 86.4 ± 4.8 91.8 ± 4.1 93.3 ± 3.4 83.4 ± 5.3 89.5 ± 4.3 73.6 ± 6.3 91.5 ± 5.1 92.8 ± 3.4 84.4 ± 5.1 77.0 ± 6.1 76.1 ± 5.8

West Virginia 82.5 ± 5.2 93.1 ± 3.5 91.1 ± 3.4 84.6 ± 4.9 90.7 ± 4.1 77.0 ± 5.7 90.6 ± 4.0 90.4 ± 3.8 84.7 ± 4.8 72.0 ± 6.3 73.5 ± 6.0

Wisconsin 84.2 ± 6.2 88.3 ± 5.7 88.1 ± 5.5 82.8 ± 6.2 87.4 ± 5.8 82.7 ± 6.1 92.3 ± 3.0 86.0 ± 6.2 84.3 ± 6.1 75.2 ± 7.4 73.3 ± 7.3

Wyoming 78.6 ± 5.7 92.0 ± 3.3 91.5 ± 3.4 82.4 ± 5.2 91.3 ± 3.7 75.3 ± 6.0 84.9 ± 6.4 89.6 ± 3.8 84.1 ± 4.9 73.9 ± 6.3 72.1 ± 6.2

Puerto Rico 79.6 ± 6.7 89.2 ± 5.5 86.4 ± 5.6 74.1 ± 7.5 91.9 ± 4.2 80.3 ± 6.3 87.3 ± 5.7 87.5 ± 5.1 69.1 ± 7.9 69.3 ± 7.6 65.7 ± 8.1

U.S. Virgin Islands 46.9 ± 11.9 74.6 ± 10.5 76.9 ± 9.5 50.6 ± 12.2 73.0 ± 11.5 59.8 ± 12.0 71.6 ± 10.4 77.1 ± 9.5 40.2 ± 11.6 34.5 ± 11.7 33.3 ± 10.9

Guam 58.2 ± 10.2 78.0 ± 8.0 76.9 ± 8.2 61.0 ± 10.0 79.6 ± 7.9 91.0 ± 5.2 74.1 ± 8.6 72.1 ± 8.8 59.9 ± 10.1 53.6 ± 10.3 50.5 ± 10.1

* Estimates presented as point estimate (%) ± 95% Confidence Interval half width. Estimate=NA (Not Available) if the unweighted sample size for the denominator was < 30, or (CI half width)/Estimate 

> 0.588, or (CI half width) >10.

† Children in the Q1/2019-Q4/2019 National Immunization Survey - Child were born from January 2016 through May 2018. § 4 or more doses of diphtheria and tetanus toxoids and acellular pertussis vaccine adsorbed, diphtheria and tetanus toxoids and pertussis vaccine, or diphtheria and tetanus toxoids vaccine adsorbed 

(DTaP/DTP/DT). ¶ 3 or more doses of any poliovirus vaccine.

** 1 or more doses of measles-mumps-rubella vaccine †† 4 or more doses of Haemophilus influenzae type b (Hib) vaccine of any type or 2 doses of Hib of Merck types followed by 1+ dose of Hib of any type. ¶¶ 3 or more doses of hepatitis B vaccine.

*** 1 or more doses of varicella at or after child’s first birthday, unadjusted for history of varicella illness. ††† 4 or more doses of pneumococcal conjugate vaccine (PCV). §§§ 4+ diphtheria and tetanus toxoids and acellular pertussis vaccine adsorbed, diphtheria and tetanus toxoids and pertussis vaccine, or diphtheria and tetanus toxoids vaccine adsorbed (DTaP/DTP/DT); 

3+ poliovirus vaccine; 1+ measles-containing vaccine (MCV); full series Haemophilus influenzae type b conjugate vaccine (Hib), i.e., 3 or 4 doses depending on type of vaccine received; 3+ hepatitis B 

vaccine (Hep B); 1+ varicella at or after 12 months of age; and 4+ pneumococcal conjugate vaccine (PCV).

¶¶¶ U.S. national estimates exclude U.S. territories.
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX G 

188

Appendix G: Trends in NIS-Child Response Rates and 

Vaccination Coverage Rates, 1995-2019 

Table G.1: Key Indicators* from Landline Sample Household and Provider Data Collection by 

Survey Year, National Immunization Survey - Child, 1995-2017†

Survey 

Year

Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response Rate 

(%)

Children with 

Adequate 

Provider Data 

(%)

1995 96.5 96.4 93.5 87.1 50.6 

1996 94.3 96.8 94.0 85.8 63.4 

1997 92.1 97.9 93.8 84.6 69.7 

1998 90.4 97.8 93.6 82.7 67.1 

1999 88.6 97.0 93.4 80.2 65.4 

2000 88.1 96.0 93.1 78.7 67.4 

2001 86.8 96.2 91.1 76.1 70.4 

2002 84.8 96.6 90.6 74.2 67.6 

2003 83.6 94.0 88.7 69.8 68.9 

2004 83.8 94.8 92.0 73.1 71.0 

2005 83.3 92.8 84.2 65.1 63.6 

2006 83.3 90.5 85.6 64.5 70.4 

2007 82.9 90.2 86.8 64.9 68.6 

2008 82.3 90.3 85.1 63.2 71.0 

2009 82.9 92.4 83.2 63.8 68.7 

2010 83.3 91.5 83.6 63.8 71.2 

2011 83.0 90.7 81.7 61.6 72.3 

2012 84.1 90.7 84.6 64.5 67.9 

2013 83.2 91.0 82.3 62.3 63.5 

2014 82.7 92.2 82.1 62.6 63.3 

2015 81.9 89.9 80.3 59.1 59.7 

2016 81.6 88.4 77.2 55.7 58.6 

2017 80.8 84.4 76.1 51.9 57.2 

* For the definition of the key indicators see Table 1 of NIS-Child Data User’s Guide for the survey year of interest.

† Excludes U.S. territories. 
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 189

Figure G.1: Trends in Landline Sample Key Indicators from Household and Provider Data 

Collection by Survey Year, National Immunization Survey - Child, 1995-2017* 

* Excludes U.S. territories. 

Figure G.1 provides a graphical representation of the data contained in Table G.1. It shows how 

selected landline sample key indicators from the household and provider data collection performed 

throughout the years, from 1995 to 2017. (The NIS utilized a single-frame cell-phone design 

beginning in 2018.) We observe that the trend in the data collection rates was downward, with the 

exception of the percentage of children with adequate provider data, which had been essentially flat 

from 1997-2012, but also trended downward from 2013-2017. Note that this chart reflects the 

landline sample only. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX G 

 190

Table G.2: Key Indicators* from Cell-Phone Sample Household and Provider Data Collection 

by Survey Year, National Immunization Survey - Child, 2011-2019†

Survey 

Year§

Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response Rate 

(%)

Children with 

Adequate 

Provider Data 

(%)

2011 47.0 76.2 70.4 25.2 66.7 

2012 52.4 77.5 75.5 30.6 63.9 

2013 53.8 79.3 71.6 30.5 59.8 

2014 58.7 78.5 72.6 33.5 58.9 

2015 56.3 79.3 72.2 32.2 55.5 

2016 54.0 83.9 70.9 32.1 54.0 

2017 43.0 83.7 69.5 25.0 53.6 

2018 41.2 84.9 70.3 24.6 54.0 

2019 35.2 84.4 71.1 21.1 49.4 

*For the definition of the key indicators see Table 1 of NIS-Child Data User’s Guide for the survey year of interest.

† Excludes U.S. territories. 

§ Cell-phone sample was added to the NIS-Child in 2011.
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 191

Figure G.2: Trends in Cell-Phone Sample Key Indicators from Household and Provider Data 

Collection by Survey Year, National Immunization Survey - Child, 2011-2019* 

* Excludes U.S. territories. 

Figure G.2 provides a graphical representation of the data contained in Table G.2. It shows how 

selected cell-phone sample key indicators from the household and provider data collection performed 

from 2011 to present. We observe that the rates since the inception of the cell-phone sample were

fairly flat from 2011 to 2016, with the exception of the percent of children with adequate provider 

data, which fell throughout this period. There was a decline in the resolution rate beginning in 2017, 

leading to a decline in the CASRO response rate. 

The response rate is the number of households with a completed household interview divided by the 

estimated number of eligible households in the sample. Within each sample type (landline or cell 

phone), the number of eligible households was estimated using the CASRO assumptions; these 

0

10

20

30

40

50

60

70

80

90

100

2011 2012 2013 2014 2015 2016 2017 2018 2019

Percent

Year

Resolution Rate (%)

Screener Completion Rate (%)

Interview Completion Rate (%)

CASRO Response Rate (%)

Children with Adequate Provider Data (%)
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX G 

 192

assumptions are that the rate of households among the unresolved telephone numbers is the same as 

the observed rate of households among the resolved telephone numbers, and the rate of eligible 

households among unscreened households is the same as the observed rate of eligible households 

among screened households. Under these assumptions, within each sample type the CASRO response 

rate is equal to the product of the resolution rate, the screener completion rate, and the interview 

completion rate. For the combined samples, we have defined the CASRO response rate as the total 

number of households with a completed interview divided by the estimated total number of eligible 

households across both sample types, where the estimated total number of eligible households is 

equal to the sum of the estimated number of eligible households in the landline sample (using 

CASRO assumptions) and the estimated number of eligible households in the cell-phone sample 

(using CASRO assumptions). Table G.3 presents the CASRO response rate calculated in this way for

the combined landline and cell-phone samples, by survey year, and Figure G.3 presents a graphical 

representation. Because the CASRO response rate is lower for the cell-phone sample than for the 

landline sample, the CASRO response rate for the combined landline and cell-phone samples was 

lower in years with a larger cell-phone sample and higher in years with a smaller cell-phone sample. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX G 

 193

Table G.3: CASRO Response Rate for the Combined Landline and Cell-Phone Samples by 

Survey Year, National Immunization Survey - Child, 2011-2017*

Survey Year†

CASRO Response Rate 

(%)

2011 52.2 

2012 41.2 

2013 34.4 

2014 42.5 

2015 34.9 

2016 33.9 

2017 26.1 

* Excludes U.S. territories. 

† Cell-phone sample was added to the NIS-Child in 2011. The NIS-Child transitioned from a dual-frame landline and cellphone RDD sample design to a single-frame cell phone RDD sample design beginning in 2018.

Figure G.3: Trend in CASRO Response Rate for the Combined Landline and Cell-Phone 

Samples by Survey Year, National Immunization Survey - Child, 2011-2017*

* Excludes U.S. territories.
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 194

Table G.4: Vaccine-Specific Coverage Levels Among Children Age 19-35 Months in the 

United States by Survey Year, National Immunization Survey - Child, 1995-2019*

Survey 

Year†

4+ 

DTaP

3+ 

Polio

1+ 

MMR

3+ 

Hib§

3+ 

Hep B

1+ 

Varicella¶

4+ 

PCV 4:3:1** 4:3:1:3††

1995 78.4 87.8 89.8 91.2 67.9 N.A. N.A. 76.0 73.7 

1996 81.1 91.0 90.6 91.4 81.8 12.0 N.A. 78.4 76.4 

1997 81.5 90.7 90.4 92.5 83.6 25.8 N.A. 77.9 76.2 

1998 83.9 90.8 92.0 93.4 87.0 43.2 N.A. 80.6 79.2 

1999 83.3 89.6 91.5 93.5 88.1 57.5 N.A. 79.9 78.4 

2000 81.7 89.5 90.5 93.4 90.3 67.8 N.A. 77.6 76.2 

2001 82.1 89.4 91.4 93.0 88.9 76.3 N.A. 78.6 77.2 

2002 81.6 90.2 91.6 93.1 89.9 80.6 N.A. 78.5 77.5 

2003 84.8 91.6 93.0 93.9 92.4 84.8 N.A. 82.2 81.3 

2004 85.5 91.6 93.0 93.5 92.4 87.5 N.A. 83.5 82.5 

2005 85.7 91.7 91.5 93.9 92.9 87.9 53.7 83.1 82.4 

2006 85.2 92.8 92.3 93.4 93.3 89.2 68.4 83.1 82.2 

2007 84.5 92.6 93.2 92.6 92.7 90.0 75.3 82.8 80.1 

2008 84.6 93.6 92.1 90.9 93.5 90.7 80.1 82.5 79.6 

2009 83.9 92.8 90.0 83.6 92.4 89.6 80.4 81.5 73.4 

2010 84.4 93.3 91.5 90.4 91.8 90.4 83.3 82.0 78.8 

2011 84.6 93.9 91.6 94.0 91.1 90.8 84.4 82.6 81.9 

 2012§§ 82.5 92.8 90.8 93.0 89.7 90.2 81.9 80.5 80.0 

2013 83.1 92.7 91.9 92.8 90.8 91.2 82.0 81.5 81.1 

2014 84.2 93.3 91.5 92.6 91.6 91.0 82.9 82.6 82.0 

2015 84.6 93.7 91.9 93.2 92.6 91.8 84.1 83.2 82.6 

2016 83.4 91.9 91.1 91.6 90.5 90.6 81.8 81.9 81.2 

2017 83.2 92.7 91.5 91.8 91.4 91.0 82.4 81.7 80.9 

2018 83.8 93.6 92.1 91.6 92.1 92.0 83.3 82.5 81.7 

2019 83.3 92.3 91.3 90.9 91.3 90.9 82.5 82.3 81.7 

* Excludes U.S. territories. 

† Prior to 2011, estimates are single-frame, landline-sample estimates. From 2011-2017, estimates are dual-frame (landline 

plus cell-phone) estimates. From 2018 onward, estimates are single-frame, cell-phone estimates.

§ Beginning in 2009, the number of doses required to be up-to-date on Hib depends on the manufacturer of the vaccine. 

However, the figures shown here refer to 3 or more doses of Hib vaccine regardless of manufacturer.

¶ Varicella was added to the NIS-Child in 1996.

** Four or more doses of DTaP, three or more doses of poliovirus vaccine, and one or more doses of MCV.

†† Four or more doses of DTaP, three or more does of poliovirus vaccine, one or more doses of MCV, and three or more 

doses of Hib.

§§ Revised definition of adequate provider data (APD) implemented. 
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX G 

 195

Figure G.4: Trends in Vaccine-Specific Coverage Levels among Children 19-35 Months of Age 

in the United States by Survey Year, National Immunization Survey - Child, 1995-

2019*†¶

* Excludes U.S. territories. 

† Prior to 2011, estimates are single-frame, landline-sample estimates. From 2011-2017, estimates are dual-frame (landline 

plus cell-phone) estimates. From 2018 onward, estimates are single-frame, cell-phone estimates.

¶ Revised definition of adequate provider data (APD) implemented in 2012. 

Figure G.4 provides a graphical representation of the data contained in Table G.4. It displays the trend 

in vaccine-specific coverage levels among children aged 19 through 35 months from 1995 to present. 

We observe that the trend in the vaccination coverage levels is stable or slightly upward for the 

longer-established vaccines, while the early trends for new vaccines are strongly upward. Note that 

this chart reflects the landline sample prior to 2011, the dual-frame sample in 2011-2017, and the 

single-frame cell-phone sample thereafter. For more information on interpreting trends in vaccination 

coverage, see online reports at https://www.cdc.gov/vaccines/imzmanagers/coverage/childvaxview/pubs-presentations/NIS-vax-trends-2012-2016.html.

0

10

20

30

40

50

60

70

80

90

100

Percent

Year

4+ DTaP 3+ Polio 1+ MMR 3+ Hib 3+ Hep B

1+ Varicella 4+ PCV 4:3:1** 4:3:1:3
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196

Appendix H: Vaccine Type Codes

Table H.1: 2019 NIS-Child Vaccine Type Codes

Vaccine Code Description

03 DTaP/DTP/DT-containing, unknown type 

04 DTaP/DTP/DT-only 

07 DTaP-Hib

08 DTaP-HepB-IPV

20 OPV

21 IPV

22 Polio-containing, unknown type 

30 Measles-mumps-rubella 

31 Measles-only 

32 Measles-mumps

33 Measles-rubella 

43 HepB-Hib

44 Hib-only, unknown type 

60 HepB-only 

70 Pneumococcal conjugate, unknown type 

71 Pneumococcal polysaccharide 

72 Pneumococcal-containing, unknown type 

73 Pneumococcal conjugate-7 

74 Pneumococcal conjugate-13 

D3 DTaP-IPV-Hib

FL Seasonal influenza, unknown type 

FM Seasonal influenza spray

FN Injected seasonal influenza

HB HepB-containing, unknown type 

HG Hib-only (GSK) 

HI Hib-containing, unknown type 

HM Hib-only (Merck)

HS Hib-only (Sanofi) 

HY Hib-MenCY

MM Measles-containing, unknown type 

RG Rotarix (GSK)

RM Rotateq (Merck)

RO Rotavirus-containing, unknown type 

VA Varicella-containing, unknown type 

VM MMR-varicella

VO Varicella-only 
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197

Appendix I: Key NIS-Child Response Rates by Area

Table I.1: Key Indicators* for the Cell-Phone Sample by Estimation Area, National 

Immunization Survey - Child, 2019 

Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

U.S. National† 35.2 84.4 71.1 21.1 49.4

Alabama 39.3 86.9 66.0 22.6 48.8

Alaska 61.1 87.3 72.3 38.6 57.6

Arizona 32.4 88.6 67.0 19.2 50.4

Arkansas 44.1 86.7 71.7 27.4 52.7

California 31.2 88.4 70.4 19.4 43.7

Colorado 30.3 90.2 70.2 19.2 51.4

Connecticut 25.2 86.2 66.6 14.5 48.3

Delaware 30.7 73.3 65.5 14.8 49.3

District of Columbia 27.3 75.2 74.9 15.4 46.6

Florida 28.5 85.9 73.5 18.0 40.9

Georgia 34.2 88.2 65.7 19.8 45.1

Hawaii 29.8 79.6 65.8 15.6 44.9

Idaho 32.3 88.1 76.0 21.6 51.8

Illinois 37.5 88.9 68.9 23.0 47.6

 IL-City of Chicago 37.1 87.4 67.1 21.7 49.7

 IL-Rest of State 37.7 89.7 69.9 23.6 46.7

Indiana 35.5 89.5 70.7 22.4 53.1

Iowa 43.0 91.0 77.4 30.3 53.7

Kansas 32.6 88.7 77.4 22.4 62.9

Kentucky 41.3 88.5 63.7 23.3 52.0

Louisiana 38.1 86.7 69.2 22.9 47.5

Maine 37.8 81.8 74.6 23.1 48.2

Maryland 28.5 83.9 77.6 18.6 52.1

Massachusetts 28.2 89.4 71.2 18.0 54.9

Michigan 34.3 90.2 75.4 23.3 50.9

Minnesota 33.0 90.6 77.0 23.0 45.8

Mississippi 42.1 83.3 64.2 22.5 46.9

Missouri 35.2 89.6 75.3 23.8 53.8

Montana 44.3 86.8 73.8 28.3 52.8

Nebraska 29.8 89.1 74.7 19.8 56.4

Nevada 30.2 84.9 74.3 19.0 50.6

New Hampshire 34.0 79.0 71.0 19.0 52.3
Data User’s Guide for the 2019 NIS-Child Public-Use Data File APPENDIX I 

198

Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

New Jersey 29.8 86.9 64.6 16.7 38.6

New Mexico 38.0 85.2 74.0 24.0 51.8

New York 27.7 86.3 66.8 16.0 41.8

 NY-City of New York 26.0 84.9 66.9 14.8 38.9

 NY-Rest of State 30.5 89.1 66.7 18.1 47.6

North Carolina 32.3 89.2 70.7 20.4 52.1

North Dakota 51.6 82.5 75.3 32.1 52.5

Ohio 33.3 89.8 73.4 21.9 47.5

Oklahoma 43.2 87.9 69.0 26.2 49.8

Oregon 30.8 90.8 75.0 21.0 47.2

Pennsylvania 30.9 83.5 69.3 17.9 45.7

 PA-Philadelphia County 30.8 82.7 69.1 17.6 42.4

 PA-Rest of State 31.6 90.7 71.2 20.4 48.2

Rhode Island 28.4 75.6 70.4 15.1 59.3

South Carolina 34.6 87.7 67.7 20.5 47.0

South Dakota 46.9 84.7 74.0 29.4 54.9

Tennessee 34.5 89.0 68.6 21.1 47.4

Texas 31.9 86.7 66.7 18.5 45.5

 TX-Bexar County 37.1 85.4 68.6 21.7 46.0

 TX-City of Houston 29.4 87.2 66.4 17.0 40.3

 TX-Dallas County 29.7 87.0 65.8 17.0 39.6

 TX-El Paso County 31.6 86.8 66.2 18.2 47.8

 TX-Rest of State 38.6 89.4 66.2 22.8 48.5

Utah 30.3 88.6 78.0 21.0 55.3

Vermont 36.9 74.4 75.7 20.8 52.0

Virginia 27.6 91.2 77.0 19.4 49.4

Washington 28.9 87.2 82.8 20.9 53.8

West Virginia 37.9 79.2 71.7 21.5 47.8

Wisconsin 39.1 90.4 75.4 26.6 50.0

Wyoming 65.5 77.3 76.3 38.6 62.7

Puerto Rico 49.0 91.7 53.5 24.0 29.8

U.S. Virgin Islands 65.2 88.2 60.4 34.8 43.0

Guam 52.2 76.5 54.4 21.7 44.6

* For the definition of the key indicators see Table 1 of NIS-Child Data User’s Guide. 

† Excludes U.S. territories.