National Immunization Survey-Child 

A User’s Guide for the 2017

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

October 2018
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, Larry Wilkinson, and Zhen Zhao. 

NORC at the University of Chicago – Rachel Bavley, Benjamin Skalland, Xian Tao, and Kirk Wolter. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page i 
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............................................. 15

3. Content of NIS-Child Questionnaires............................................................................................ 16

3.1. Content of the Household Questionnaire.................................................................................. 16

3.2. Content of the Immunization History Questionnaire (IHQ)..................................................... 18

4. Data Preparation and Processing Procedures............................................................................... 20

4.1. Data Preparation ....................................................................................................................... 20

4.1.1. Editing in the CATI System ........................................................................................ 21

4.1.2. Post-CATI Edits .......................................................................................................... 21

4.1.3. Editing of Provider Data.............................................................................................. 22

4.2. Limitations of Data Editing Procedures.................................................................................... 23

4.3. Variable-Naming Conventions................................................................................................. 24

4.4. Missing Value Codes................................................................................................................ 24

4.5. Imputation for Item Non-Response .......................................................................................... 24

4.6. Vaccine-Specific Recoding of Verbatim Responses................................................................ 26

4.7. Composite Variables................................................................................................................. 26

4.8. Subsets of the NIS-Child Data.................................................................................................. 29

4.9. Confidentiality and Disclosure Avoidance ............................................................................... 29

5. Quality Control and Quality Assurance Procedures.................................................................... 29

6. Sampling Weights............................................................................................................................ 31

6.1. Base Sampling Weight ............................................................................................................. 32

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

Interview Non-Response .......................................................................................................... 32

6.3. Adjustment for Multiple Telephone Lines and Deriving Annual Weights............................... 34

6.4. Calibration ................................................................................................................................ 35

6.5. Adjustment for Provider Non-Response................................................................................... 37

7. Contents of the Public-Use Data File ............................................................................................. 41

7.1. Section 1: ID, Weight, and Flag Variables............................................................................... 45

7.2. Section 2: Household-Reported Vaccination and Chickenpox Information............................. 45

7.3. Section 3: Demographic, Socio-Economic, and Other Household/Child Information............. 45

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page ii
7.4. Section 4: Geographic Variables.............................................................................................. 47

7.5. Section 5: Number of Providers Identified and Consent Variables.......................................... 47

7.6. Section 6: Number of Responding Providers Variables........................................................... 48

7.7. Section 7: Characteristics of Providers Variables..................................................................... 48

7.8. Section 8: Provider-Reported Up-To-Date Vaccination Variables .......................................... 50

7.8.1. Hib Up-To-Date Variables .......................................................................................... 53

7.8.2. Rotavirus Up-To-Date Variables................................................................................. 55

7.9. Section 9: Provider-Reported Age-At-Vaccination Variables.................................................. 56

7.10. Section 10: Health Insurance Module Variables ...................................................................... 57

8. Analytic and Reporting Guidelines................................................................................................ 58

8.1. Use of NIS-Child Sampling Weights........................................................................................ 59

8.2. Estimation and Analysis........................................................................................................... 60

8.2.1. Estimating Vaccination Coverage Rates ..................................................................... 60

8.2.2. Estimating Standard Errors of Vaccination Coverage Rates....................................... 61

8.3. Combining Multiple Years of NIS-Child Data......................................................................... 62

8.3.1. Estimation of Multi-Year Means................................................................................. 62

8.3.2. Estimation of Multi-Year Contrasts............................................................................. 65

9. Summary Tables.............................................................................................................................. 72

10. Assessment of Total Survey Error.................................................................................................. 73

11. Limitations........................................................................................................................................ 77

12. Citations for NIS-Child Data .......................................................................................................... 78

13. References......................................................................................................................................... 84

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page iii
Appendices

Appendix A: Glossary of Abbreviations and Terms................................................................................... 87

Appendix B: Summary Statistics for Sampling Weights by Estimation Area............................................ 90

Appendix C: Flags for Inconsistent Values in the Breastfeeding Data....................................................... 94

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................................................................................................................................... 95

Appendix E: Alphabetical Listing of Variables that are in the 2004-2017 Public-Use Data Files........... 128

Appendix F: Summary Tables.................................................................................................................. 169

Appendix G: Trends in NIS-Child Response Rates and Vaccination Coverage Rates, 1995-2017 ....... 1788

Appendix H: Vaccine Type Codes.......................................................................................................... 1877

Appendix I: Key NIS-Child Response Rates by Area ............................................................................ 1888

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page iv
List of Tables and Figures 

Table 1: Selected Operational Results of Q1/2017-Q4/2017 NIS-Child Data Collection (Excluding 

U.S. Territories) ..................................................................................................................... 14

Table 2: Content of the Household Interview, National Immunization Survey - Child, 2017............. 17

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

Immunization Survey - Child, 2017....................................................................................... 26

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, 2017 ........................................................................ 28

Table 5: NIS-Child Variables Commonly Used in Analyses or for Published Estimates.................... 42

Table 6: Vaccine Categories and Vaccine Types, National Immunization Survey - Child, 2017 ....... 51

Table 7: Up-To-Date Variables for Hib, National Immunization Survey - Child, 2009-2017 ............ 54

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

Child, 2009-2017 ................................................................................................................... 55

Table 9: Summary of Weights and Stratum Variables, National Immunization Survey - Child, 2017 60

Table 10: Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP17, and Common 

Denominator Estimation Area (CDIAP), National Immunization Survey - Child, 2017 ...... 67

Figure 1: Comparison of Estimated Mean Total Error for 4:3:1:3:3:1 Series, ≥1 MMR, and ≥4 DTaP 

by Survey Year, Including Components for Coverage Error, Nonresponse Error, and 

Sampling Error, National Immunization Survey - Child, 2009-2013 .................................... 75

Figure 2: Comparison of Estimated Mean Total Error for 4:3:1:3:3:1 Series, ≥1 MMR, and ≥4 DTaP 

by Survey Year, Including Components for Coverage Error, Nonresponse Error, UnderReporting Error, and Sampling Error, National Immunization Survey - Child, 2012-2013.. 76

Table B.1: Distribution of Dual-Frame Sampling Weights for Children with Completed Household 

Interviews, National Immunization Survey - Child, 2017 ..................................................... 90

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

National Immunization Survey - Child, 2017 ........................................................................ 92

Table E.1 Alphabetical Listing of Variables that are in the 2004-2017 Public-Use Data Files ........... 128

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, 2017 ................................... 169

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

National Immunization Survey - Child, 2017 ...................................................................... 171

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

Immunization Survey - Child, 2017..................................................................................... 172

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

National Immunization Survey - Child, 2017 ...................................................................... 173

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

Immunization Survey - Child, 2017..................................................................................... 174

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

Immunization Survey - Child, 2017..................................................................................... 175

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, Q1/2017-Q4/2017................................................................ 176

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page v 
Table G.1: Key Indicators from Landline Sample Household and Provider Data Collection by Survey 

Year, National Immunization Survey - Child, 1995-2017 ................................................... 178

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

Survey Year, National Immunization Survey - Child, 1995-2017....................................... 179

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

Year, National Immunization Survey - Child, 2011-2017 ................................................... 180

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

by Survey Year, National Immunization Survey - Child, 2011-2017.................................. 181

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

Year, National Immunization Survey - Child, 2011-2017 ................................................... 183

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....................................... 183

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

by Survey Year, National Immunization Survey - Child, 1995-2017.................................. 184

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, 1995-2017 ........... 185

Table H.1: 2017 NIS-Child Vaccine Type Codes.................................................................................. 187

Table I.1: Key Indicators for the Landline Sample by Estimation Area, National Immunization Survey 

- Child, 2017 ........................................................................................................................ 188

Table I.2: Key Indicators for the Cell-Phone Sample by Estimation Area, National Immunization 

Survey - Child, 2017 ............................................................................................................ 190

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

Area, National Immunization Survey - Child, 2017 ............................................................ 192

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page vi
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. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page vii
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Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page viii
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 with assistance from 

NCHS.

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. 2017). 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;

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 1 
● 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 (varicella) – 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 2017, there are 60 geographic strata for which vaccination coverage levels 

can be estimated (see Table F.1), including 8 local areas; the remaining 52 estimation areas are either an 

entire state, the District of Columbia, a territory (Guam), 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 8 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 

(6 awardee urban areas and 50 state or “rest of state” areas). In addition, starting in 2007, state 

immunization programs could choose city/county areas of interest to have sample design that ensured 

adequate sample size to produce estimates for the area, using their Section 317 funds. In 2017, four 

additional area were chosen: El Paso County, TX; Dallas County, TX; Travis County, TX; and 

Guam. As noted throughout this report, several of the sampling, data collection, and estimation 

procedures differed for Guam when compared to the rest of the United States.

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The 60 = 56 + 3 + 1 (territory) areas are called estimation areas. Table 10 in Section 8 shows a crosswalk of estimation areas between years. 

Data for Guam are not included in the 2017 public-use data file to protect respondent confidentiality, as 

the sampling fractions were large in this small-population area. Interested researchers can access data for 

Guam by submitting a proposal and working through the NCHS Research Data Center. The link and 

guidelines for developing a proposal are located at the following URL: www.cdc.gov/rdc. Data for the 

U.S. Virgin Islands and Puerto Rico are not available for 2017 as data collection in these areas was 

suspended due to Hurricane Maria.

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.

In 2017, the NIS-Child utilized a dual-frame sampling design with independent samples drawn from 

landline and cell-phone sampling frames. The cell-phone component was added to the survey in 2011 in 

order to address the rapid rise of cell-phone-only households. Preliminary results from the JulyDecember 2017 National Health Interview Survey (NHIS) indicate that the number of households 

with only cell phones continues to increase. Approximately 61.8% of all children under 18 years of 

age—over 45 million children—live in households with access to only wireless telephones 

(Blumberg and Luke 2018). Several of the sampling, data collection, and estimation procedures differ 

for the cell-phone sample as compared to the landline sample, as noted throughout this report. 

For the 2017 NIS-Child landline sample, the household interviews began on January 7, 2017 and 

ended on January 22, 2018. For the 2017 NIS-Child cell-phone sample, the household interviews 

began on January 5, 2017 and ended on January 26, 2018. Provider data collection extended from 

February 2017 to April 2018 for both sample sources. A total sample (including sample from 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 4 
Guam) of approximately 25.2 million telephone numbers (7.9 million landline and 17.3 million cellphone) yielded household interviews for 28,905 children (2,364 landline and 26,541 cell-phone), 

15,599 of whom (1,362 landline and 14,237 cell-phone) had adequate provider data (providerreported vaccination data adequate to determine whether the child was up-to-date with respect to 

the recommended immunization schedule). The 2017 NIS-Child public-use data file (which does not 

include data for Guam) contains data for 28,465 children with completed household interviews, and 

more extensive data (e.g. provider-reported vaccinations and facility data) for 15,333 children with 

adequate provider data (including 290 unvaccinated children). Data were collected in Guam in 

2017, although children in this area are not included on the public-use data file in order to protect 

confidentiality. Data for the U.S. Virgin Islands and Puerto Rico are also not included on the 2017 

public-use data file as data collection in these areas was suspended due to Hurricane Maria.

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 2015a) 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 providerData User’s Guide for the 2017 NIS-Child Public-Use Data File Page 5 
reported data are adequate. Previous NIS-Child public-use data files have also provided analysts with 

these capabilities. 

The 2017 NIS-Child public-use data file includes only dual-frame weights. Dual-frame estimates are the 

best estimates for the NIS-Child in terms of minimizing any bias due to the incompleteness of the landline 

sampling frame. Section 6 of this user’s guide provides information about the creation of the weight 

variables included in the 2017 NIS-Child public-use data file, and Section 8 provides guidance for their 

use. 

Vaccination coverage estimates for 2017 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. The accompanying codebook (NCIRD 2018) documents 

the contents of the 2017 NIS-Child public-use data file. For reference, Appendix E (Alphabetical Listing 

of Variables in the 2004-2017 Public-Use Data Files) provides a full list of variables in the 2017 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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 6 
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 telephone numbers.

Sampling frames were provided by Marketing Systems Group (MSG). Landline telephone and cell-phone 

numbers were sampled within estimation areas in each quarter of 2017. Table F.1 (in Appendix F) lists 

the estimation areas for the 2017 NIS-Child by state and shows the estimated number of children living in 

each state and estimation area in 2017. 

The NIS-Child uses the list-assisted method of RDD (Lepkowski 1988) to sample landline telephone 

numbers. This method selects a random sample of telephone numbers from “banks” of 100 consecutive 

telephone numbers (e.g., 773-256-0000 to 773-256-0099) that contain at least one directory-listed 

residential telephone number. Because directory listings are not available for cell phones, the NIS-Child

cell-phone sample did not use the list-assisted method of RDD, but rather used RDD without listassistance. That is, the cell-phone sample was selected from all banks of cell-phone numbers, not just 

those containing at least one directory-listed residential telephone number. Directory listings were also 

unavailable for landline sample in Guam, so the landline and cell-phone samples for this area were 

selected without list-assistance using simple random sampling.

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 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 7 
from provider-reported vaccination histories, given a true coverage parameter of 50%. Landline telephone 

and cell-phone sample sizes were chosen such that the two samples combined meet the target coefficient 

of variation of 7.5%. 

In 2017, including Guam sample, 54.0% of children (57.6% of landline sample children and 53.6% 

of cell-phone sample children) with a completed household interview were determined to have 

adequate provider data. Excluding Guam, this proportion was 53.9% (57.2% for the landline 

sample and 53.6% for the cell-phone sample). The percentage of children with adequate provider 

data varies among the non-territory estimation areas (from 42.7% in Dallas County, TX to 62.6% 

in Vermont). 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 293 in 2017, including Guam). 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 landline sample involves four procedures. First, 

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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 8 
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 a 

portion of the non-working and non-residential telephone numbers, plus numbers on the NIS do-not-call 

list, from the sample before the interviewers dial them. Fourth, the sample telephone numbers are 

matched against a national database of residential telephone numbers in order to obtain usable mailing 

addresses for as many sample households as possible. To promote participation in the NIS-Child, an 

advance letter is sent to these addresses approximately two weeks prior to calling to conduct the 

household interview. 

The design and implementation of the cell-phone sample differs from that of the landline sample in two 

ways:

• Prior to 2014, there was no process to remove non-working and non-residential cell-phone 

numbers before dialing them. Beginning 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 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 non-working cell-phone numbers was no 

longer cost effective, and beginning in 2017 this process was no longer used in the cell-phone 

sample.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 9 
● Cell-phone numbers were not matched to an external database to obtain mailing addresses. Cellphone sample cases were not sent advance letters.

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 

Provider Record Check is conducted in the same manner for both landline and cell-phone sample cases. 

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 2017. To 

facilitate comparisons with prior years, the numbers in Table 1 are presented separately for the landline 

and cell-phone samples, and exclude the U.S. territory samples. Children aged 19 through 35 months 

during 2017 data collection were born between January 2014 and May 2016.

The landline RDD sample (in replicates that were released for use) consisted of 7,699,528 telephone 

numbers. Of those, 4,622,931 were eliminated before release to the telephone centers by the 

automated procedure as non-working numbers, non-residential numbers, or numbers on the NIS

do-not-call list. The remaining 3,076,597 numbers were sent to the telephone centers to be dialed, 

and 348,222 households were identified, as shown in Rows C and F. Among the identified 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 10
households, 293,907 (84.4%) were successfully screened. Of these, 2,857 (1.0%) contained one or 

more age-eligible children. Among these households, 2,174 (76.1%) completed the household 

interview.

The cell-phone sample (in replicates that were released for use) consisted of 17,183,133 telephone 

numbers. Of those, 31,396 were eliminated before release to the telephone centers as numbers on 

the NIS do-not-call list. The remaining 17,151,737 numbers were sent to the telephone centers to be 

dialed, and 1,383,595 active personal cell-phone numbers (APCNs) were identified, as shown in 

Row F. Among the identified APCNs, 1,158,106 (83.7%) were successfully screened. Of these, 

36,481 (3.2%) were deemed eligible for the NIS-Child interview. Among the identified eligible 

respondents, 25,343 (69.5%) 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 2017, the CASRO response rate (Row J, 

Table 1) for the landline sample was 51.9%. The CASRO response rate equals the product of the 

resolution rate (80.8%, Row E), the screening completion rate (84.4%, Row G), and the interview 

completion rate among eligible households (76.1%, 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.

The CASRO response rate (Row J) for the cell-phone sample in 2017 was 25.0%. As with the 

landline sample, it equals the product of the resolution rate (43.0%, Row E), the screening 

completion rate (83.7%, Row G), and the interview completion rate among eligible households 

(69.5%, Row I). 

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The CASRO response rate (Row J) for the combined landline and cell-phone sample was 26.1% in 

2017. See footnote 6 of Table 1 for a description of the calculation of the combined CASRO 

response rate.

Row K of Table 1 shows that household interviews were completed on behalf of 2,235 age-eligible

children in the landline sample and 26,230 children in the cell-phone sample. 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 – 64.2% 

for landline sample cases and 62.7% for cell-phone sample cases in 2017. 

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 from the landline sample, 1,658

(95.2%, Row N) were returned. Among the children with completed household interviews, 1,279 

(57.2%, Row O) had adequate vaccination histories based on provider reporting (1,261) or were 

determined to be unvaccinated (18). The other 42.8% 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.

Of the questionnaires mailed to providers of children from the cell-phone sample, 18,910 (93.9%, 

Row N) were returned. Among the cell-phone sample children with completed household 

interviews, 14,054 (53.6%, Row O) had adequate vaccination histories based on provider reporting 

(13,782) or had no vaccinations based on household reporting (272). The other 46.4% 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), or the provider(s) did not have medical records for the child.

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In 2017, data from the Health Insurance Module (HIM) were collected. Among the 2,235 children 

in the landline sample with completed household interviews, 1,489 (66.6%, Row P) completed the 

HIM. Among the 26,230 children in the cell-phone sample with completed household interviews, 

16,955 (64.6%, 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.

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Table 1: Selected Operational Results of Q1/2017-Q4/2017 NIS-Child Data Collection 

(Excluding U.S. Territories) 

Row Key Indicator Landline Sample Cell-Phone Sample Combined Samples Formula 

Number Percent Number Percent Number Percent 

Household Phase

A 

Total Selected Telephone 

Numbers in Released 

Replicates

 7,699,528 -- 17,183,133 -- 24,882,661 -- 

B 

Phone Numbers Resolved 

before Computer-Assisted 

Telephone Interviewing

 4,622,931 60.0% 31,396 0.2% 4,654,327 18.7% B/A 

C 

Total Phone Numbers 

Released to Telephone 

Centers 

 3,076,597 -- 17,151,737 -- 20,228,334 A-B 

D Advance Letters Mailed 1,084,034 35.2% 0 0.0% 1,084,034 5.4% D/C

E Resolved Phone Numbers1 – 

Resolution Rate 6,222,213 80.8% 7,387,566 43.0% 13,609,779 54.7% E/A

F Households Identified – 

WRN/APCN Rate2 348,222 5.6% 1,383,595 18.7% 1,731,817 12.7% F/E

G 

Households Successfully 

Screened3 – Screener 

Completion Rate

 293,907 84.4% 1,158,106 83.7% 1,452,013 83.8% G/F

H Eligible Households – 

Eligibility Rate4 2,857 1.0% 36,481 3.2% 39,338 2.7% H/G

I 

Households with Completed 

Household Interviews – 

Interview Completion Rate

 2,174 76.1% 25,343 69.5% 27,517 70.0% I/H 

J CASRO Response Rate5 -- 51.9% -- 25.0% 26.1% E*G*I6

K 

Age-Eligible Children with 

Completed Household 

Interviews7

 2,235 -- 26,230 -- 28,465 -- 

Provider Phase

L 

Children with Consent to 

Contact Vaccination 

Providers 

1,435 64.2% 16,455 62.7% 17,890 62.8% L/K

M 

Immunization History 

Questionnaires Mailed to 

Providers 

1,742 -- 20,132 -- 21,874 -- 

N 

Immunization History 

Questionnaires Returned 

from Providers

1,658 95.2% 18,910 93.9% 20,568 94.0% N/M

O Children with Adequate 

Provider Data

1,279 

(includes 18 

unvaccinated 

children) 

57.2% 

14,054 

(includes 

272 

unvaccinated 

children) 

53.6% 

15,333 

(includes 

290 

unvaccinated 

children) 

53.9% O/K

Modules

P 

Age-Eligible Children with 

Completed Household 

Interview and Completed 

Health Insurance Module

 1,489 66.6% 16,955 64.6% 18,444 64.8% P/K

1 Includes phone numbers resolved before CATI (Row 2).

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 14
2 For the landline sample, this is the working residential number (WRN) rate; for the cell-phone sample, it is the active personal cell-phone 

number (APCN) rate.

3 For the landline sample, this is the age-eligibility screener; for the cell-phone sample, it is a combination of the screener for non-minor-only cell 

phone status and the age-eligibility screener.

4 For the landline sample, this is the age-eligibility rate; for the cell-phone sample, it reflects a combination of the non-minor-only cell-phone rate 

and the age-eligibility rate.

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. Within each sample type (landline or cell phone), the number of eligible households 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, 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). 

7 Rows K-P reflect the removal of children with an ineligible best date of birth.

2.4. Informed Consent, Security, and Confidentiality of Information

The advance letter, 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 NCHS Disclosure Review Board to protect participant privacy as well as data

confidentiality.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 15
3. Content of NIS-Child Questionnaires 

This section describes the questionnaires used in the 2017 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. For the cell-phone sample, 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 minoronly cell phone). If the household has more than one age-eligible child, data are collected for each eligible 

child. 

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Table 2: Content of the Household Interview, National Immunization Survey - Child, 2017

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 not administered to any respondents 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 

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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. 

Some changes were made to the NIS-Child questionnaire during 2017. These are listed below. 

• Year references for income questions were updated to refer to the previous year, 2016. That 

is, the question text at CFAMINC, C13_DON’T_KNOW, and C13_REFUSED was updated 

to ask about 2016 income rather than 2015. 

• While one set of questions about influenza vaccinations are asked in Section B throughout 

the year, additional questions are asked only between April and June and often change year 

to year; the influenza question responses are not included on the PUF, so the PUF contents 

are not affected by these changes. 

• Guam respondents with shot records were administered Section B instead of Section A, and 

questions about the availability of shot records were removed. Guam respondents also 

began to be asked about Medicaid coverage. These changes do not affect the PUF as Guam 

respondents are not included on the 2017 PUF in order to protect respondent confidentially. 

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 

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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 

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. 

In Q4/2017, the IHQ was modified to remove Question 5b, which asks if the practice has been 

deputized to administer Vaccines for Children vaccines to underinsured children. This change does 

not affect the contents of the PUF.

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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). 

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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. 

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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 2017 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 2017 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 2018). 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 2018). 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 2017 NIS-Child Public-Use Data File Page 24
for up to four recipients. The “Notes” line for each variable in the codebook (NCIRD 2018) 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.

Table 3 shows the distribution of age in days at the birth dose of hepatitis B for children in 2017 with a 

provider-reported birth dose. A similar table is included in the 2000-2016 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 2017 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, 2017

Age in Days at

Birth Dose

Unweighted Percentage

Of Birth Doses* 

0 59.4 

1 26.7 

2 8.7 

3 2.2 

4 1.3 

5 0.9 

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 2017 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 2017 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, 2017

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 26.84 70.39 (1.78) 81.82 (1.59) 91.77 (1.14)

Non-Hispanic white only 47.01 71.51 (0.90) 84.16 (0.74) 90.33 (0.56)

Non-Hispanic black only 12.78 66.47 (2.22) 78.14 (1.83) 89.28 (1.24)

Non-Hispanic American 

Indian or Alaska Native only 0.92 65.92 (5.11) 72.54 (4.84) 88.13 (3.15)

Non-Hispanic Asian only 5.40 72.36 (3.44) 82.12 (3.15) 95.68 (1.00) 

Non-Hispanic Native 

Hawaiian or Pacific Islander 

only

0.23 67.72 (7.61) 80.00 (6.21) 86.07 (5.62)

Multiple races 6.81 69.79 (2.82) 82.27 (2.33) 92.90 (1.20) 

Non-Hispanic white/black 3.11 71.06 (4.21) 82.58 (3.25) 91.95 (1.96)

Non-Hispanic white/ 

American Indian or Alaska 

Native

0.86 58.95 (7.74) 74.38 (8.55) 93.31 (2.13)

Non-Hispanic white/Asian 1.84 73.67 (5.19) 88.35 (3.21) 95.60 (2.11)

Non-Hispanic other 

combination 0.99 68.00 (6.32) 76.91 (6.28) 90.52 (3.35)

Note: UTD = up-to-date. Weighted by PROVWT_D. Children with an unknown Hispanic origin and/or race were imputed by a hot-deck method. This table includes both landline 

and cell-phone interviews, but 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 2017 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_D) 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_D), 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 2017 managed 

over 490 sample frame by estimation area by quarter samples and used a number of performance 

measures to track their progress toward completion. Important aspects of the quality assurance program 

for the RDD component of the NIS-Child included on-line interviewer monitoring; on-line provider lookData User’s Guide for the 2017 NIS-Child Public-Use Data File Page 29
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 2017 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 dual-frame RDD-phase 

sampling weight variable for producing estimates for children with completed household interviews is 

called RDDWT_D. The dual-frame provider-phase sampling weight variable for producing estimates for 

children with adequate provider data is called PROVWT_D. 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, and RDDWT_D in 2017. 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, and PROVWT_D in 2017. 

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 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 31
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 telephone lines in the household, combination of landline and cell-phone sample 

sources, raking for differential coverage rates and non-coverage of households that do not have 

telephones, non-response by providers, and a final raking adjustment. Note that when deriving dual-frame 

weights, the initial adjustments described below are performed separately for the landline and cell-phone 

samples, and then both samples are combined and further adjustments are performed on the combined 

samples.

6.1. Base Sampling Weight

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

sampling weight. For all four quarters of the landline and cell-phone samples, the base sampling weight is 

equal to the total of telephone numbers in the sampling frame for the estimation area divided by the total 

of telephone numbers that were randomly sampled from that sampling frame and released for interview 

during that quarter. 

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 User’s Guide for the 2017 NIS-Child Public-Use Data File Page 32
data collection up to the household interview. As a result, the base sampling weights must be adjusted so 

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. For the landline sample, each of these adjustments is carried out within each estimation area 

by forming weighting cells based on the residential directory-listed status of the sample telephone 

number, percent of the population that is white in the telephone exchange, and MSA status of the 

telephone exchange (i.e., weighting cells were formed from directory-listed versus non-directory-listed 

telephone number; telephone exchanges with 75% or higher white population versus telephone exchanges 

with less than 75% white population; and MSA/non-MSA status). For the cell-phone sample, each of 

these adjustments is carried out within estimation area by forming weighting cells based on MSA/nonMSA status of the wire center associated with the cell-phone number. Each cell in each stage of 

adjustment must have sufficient resolved/responding cases (usually 20, but 15 for interview nonresponse) at that stage of adjustment; cells with a deficient number of responding cases are collapsed into

neighboring cells. The order of the variables in cell collapsing for the landline sample is MSA status, 

percent of population that is white, and directory listed status of the telephone number, and for the cellphone sample, both MSA categories are collapsed if either of the cells have a deficient number of 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 33
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 Telephone Lines and Deriving Annual 

Weights

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

adjusted for additional telephone lines in the household. Because households with multiple telephone 

lines have a greater chance of being sampled, for the landline sample each child’s household interview 

weight is adjusted by dividing it by the total number of residential landlines reported in the household (up 

to a maximum of 3), and for the cell-phone sample 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). Prior 

to 2005, the adjustment for multiple telephone lines was made by adjusting the base sampling weights 

before making any other adjustments. Beginning in 2005, the adjustment for multiple telephone lines has 

been shifted after the interview non-response adjustment, because the information on the number of 

telephone lines in a household is available only for households with completed household interviews. 

This shifts the adjustment for multiple telephone lines to the point where the information about the 

number of telephone lines is actually collected.

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

(landline, cell-phone), 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 of the landline and cell-phone 

samples are combined. The adjustment factor is proportional to the number of households with completed 

household interviews in each quarter within sample type (landline, cell-phone) and estimation area. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 34
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 2014, 2015b). Because the Vital Statistics data give the counts of all live births in the 

United States, regardless of whether the household has telephone service, the control totals include all 

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

from 2014 and 2015 (children born between July 1, 2014 and November 30, 2015 would have been 19

through 35 months on June 30, 2017). 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 2017, the combined 2014, 2015, and 2016 one-year American 

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

and migration adjustments.

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 

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.

Survey weights for the landline and cell-phone samples must be integrated to provide dual-frame weights 

for the full target population of age-eligible children. The landline and cell-phone sampling frames 

overlap in coverage of children in landline and cell-phone dual use households and exclude children in 

phoneless households. The critical issues associated with combining the landline and cell-phone samples 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 35
are: a) adjustment for overlap of the landline and cell-phone samples; and b) adjustment for noncoverage 

of children in phoneless households.

Prior to combining the landline and cell-phone samples, survey weights are adjusted to agree with 

independent estimates of the population total by telephone status. Adjustments to population totals by 

telephone status are made separately for the landline sample and the cell-phone sample (with the overlap 

adjusted for in the next step, as explained below). Since the proportion of children living in landline-only 

households is continuously decreasing (and thus, the number of landline-only sample cases is small), 

children in dual landline and cell-phone households from the landline sample are combined with children 

in landline-only households and then adjusted to the combined population estimate of children living in 

dual user and landline-only households within each estimation area. In the cell-phone sample, 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.

Next, since the landline and cell-phone sampling frames overlap in coverage of children in landline and 

cell-phone dual-use households, children in dual-user households from both samples are combined based 

on the effective number of children with a completed household interview within each sample type 

(landline, cell-phone), and are weighted to represent children in dual-use households within each 

estimation area. Finally, children in phoneless households, which are excluded from the dual-frame 

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 36
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_D).

6.5. Adjustment for Provider Non-Response

Among the 28,465 children with a completed household interview from the landline and cell-phone 

samples (excluding Guam), 15,333 (53.9%) had adequate provider data. Starting with the 2002 NISChild 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 15,333 children with 

adequate provider data, 290 were unvaccinated children. Failure to obtain adequate provider data for the 

remaining 46.1% was attributable to: 

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

vaccination provider(s) (36.6%); 

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

history questionnaire (5.1%); and

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 37
● 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 (4.5%). 

The 13,132 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 central city of a Metropolitan 

Statistical Area. Also, a child with missing provider data is less likely to live in the state where the mother 

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 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 38
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. The model for children with adequate provider data 

includes significant main effects, and also significant two-way interactions between sample type 

(landline, cell-phone) and all other variables.

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 

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_D). 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_D and PROVWT_D) in 

each estimation area.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 39
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 2017 NIS-Child Public-Use Data File Page 40
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 2018). 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 

2004-2017 NIS-Child public-use data files appears in Appendix E, along with the reason for the addition, 

subtraction, or modification of the variables in 2005-2017. 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 2017 NIS-Child Public-Use Data File Page 41
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

ESTIAP17 – 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) 

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 2017 NIS-Child Public-Use Data File Page 42
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 2017 NIS-Child Public-Use Data File Page 43
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

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 2016 and 2017 NIS-Child public-use data files:

● Because the 2017 estimation areas differ from those used in prior years, a new 2017

estimation area variable has been added (ESTIAP17) and the 2016 estimation area variable 

(ESTIAP16) has been dropped. Note that Travis County, Texas, a new estimation area 

added for 2017, is identified by ESTIAPT17=108. Although data were collected for Guam in 

2017, children in this area are not included on the public-use data file in order to protect 

confidentiality. Data for the U.S. Virgin Islands and Puerto Rico are also not included on 

the 2017 public-use data file as data collection in these areas was suspended due to 

Hurricane Maria.

● The health insurance status variable INS_STAT_I was replaced by a new variable 

INS_STAT2_I, which provides the same information except that children with both private 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 44
insurance and another non-private, non-Medicaid type of insurance are now categorized as 

(3) Other insurance, instead of (1) Private insurance, and category (1) now designates 

children with private insurance only.

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_D and PROVWT_D are the final household- and provider-phase weights, respectively.

PROVWT_D 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. 

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, 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 45
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 <= 

$75,000; below poverty; unknown), and INCPORAR gives the ratio of the family’s income to the 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 46
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 ESTIAP17 and STATE give the 2017 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 2017 NIS-Child Public-Use Data File Page 47
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 5c, 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 5c. 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 2017 NIS-Child Public-Use Data File Page 48
(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 2017 NIS-Child Public-Use Data File Page 49
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 2017 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 2017 NIS-Child Public-Use Data File Page 50
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. 

Table 6: Vaccine Categories and Vaccine Types, National Immunization Survey - Child, 2017

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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 51
Vaccine Category 

Abbreviation

Vaccination 

Category Description

Vaccine 

Type Code Vaccine Type Description

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

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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 52
Vaccine Category 

Abbreviation

Vaccination 

Category Description

Vaccine 

Type Code Vaccine Type Description

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-date file beginning in 2009: in 

addition to the existing up-to-date indicator based on 3+ Hib of any type (P_UTDHIB), an indicator 

based on the “shortage” (i.e., primary series) recommendations accounting for manufacturer (3+ Hib of 

any type or 2+ Hib of Merck types) and an indicator based on the “routine” (i.e., full series) 

recommendations accounting for manufacturer (4+ Hib of any type or 2 Hib of Merck types followed by 

1 Hib of any type) were added. Table 8 shows the up-to-date series variables that include Hib appearing 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 53
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 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.

Beginning with the 2010 NIS-Child public-use data file, two new vaccination series up-to-date indicators 

were added that ignore the Hib component altogether. These are PU431_31 (indicates up-to-date status as 

measured by PU431331, but excluding the Hib component) and PU431_314 (indicates up-to-date status 

as measured by PU4313314, but excluding the Hib component).

Table 7: Up-To-Date Variables for Hib, National Immunization Survey - Child, 2009-2017

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 2017 NIS-Child Public-Use Data File Page 54
Table 8: Up-To-Date Variables for Vaccine Series Including Hib, National Immunization 

Survey - Child, 2009-2017

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 2017 NIS-Child Public-Use Data File Page 55
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 2017 NIS-Child Public-Use Data File Page 56
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 2017 NIS-Child Public-Use Data File Page 57
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 using the PROVWT_D weight. 

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 two 

sample frames and the 62 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 vaccination coverage rates. The estimation area variable ESTIAP17 defines 

mutually exclusive and exhaustive geographic areas, while STRATUM is a combination of the 

estimation area variable for that year and the sampling frame (landline or cell-phone).

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 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 58
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 2017 NIS-Child public-use data file contains two child-level weights. The RDDWT_D variable 

gives the household-phase weight for all children 19 through 35 months in the United States. 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 telephone lines in the household, for combining the landline and cell-phone samples, for poststratification to population control totals, and for the exclusion of households without telephones. 

The weight variable that applies to children with adequate provider data is PROVWT_D. 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_D. 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.

The 2017 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 U.S. that are private providers), because the NIS-Child sample was not designed for that purpose.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 59
Table 9: Summary of Weights and Stratum Variables, National Immunization Survey - Child, 

2017

Weight Variable Population* Sample 

Frame Strata Stratum Variable

RDDWT_D United States excluding 

territories Dual Frame Sample Type by Estimation Area STRATUM

PROVWT_D

United States excluding 

territories, children with 

adequate provider data

Dual Frame Sample Type by 

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_D). 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 PROVWT_D for this child. Then, letting 

and , the national estimator of the vaccination coverage rate may be 

expressed as

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 60
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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 61

(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 

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 2017 NIS-Child public-use data file, 22 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, and RDDWT_D 

in 2017; and provider-phase weights W0 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, and 

PROVWT_D in 2017) should be divided by the number of years being combined. For example, if data for 

2015, 2016, and 2017 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

2015-2017 – should be divided by 3 to obtain revised weights, which should be saved as a new variable, 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 62
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., 2017).

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. 

The years 2005 to 2017 bring an important new complication 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 2005-2017 are defined by the variables ESTIAP for 2005, ESTIAP06 for 

2006, ESTIAP07 for 2007, ESTIAP08 for 2008, ESTIAP09 for 2009, ESTIAP10 for 2010, 

STRATUM_D/ESTIAP11 for 2011, and STRATUM for 2012-2017, 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-

ESTIAP17 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 and 2016-

2017 but not in 2013-2015. Other areas, such as New York City, NY and Rest of New York, are 

estimation areas in all years, including 2005-2017. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 63
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 2012-2017 public-use data files 

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 64
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 2016 and in 2017.

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 65
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 2016 to the 2017 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 2017 NIS-Child Public-Use Data File Page 66
Table 10: Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP17, and Common 

Denominator Estimation Area (CDIAP), National Immunization Survey - Child, 2017

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 2017 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) 

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 

53 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-Rest of State 51 51 51 51 51 51 51 51 

64 Utah 64 64 64 64 64 64 64 64 

7 Vermont 7 7 7 7 7 7 7 7 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 68
CDIAP Area Name ITRUEIAP

(1995-2004) 

ESTIAP

(2005) 

ESTIAP06 

(2006) 

ESTIAP07 

(2007) 

ESTIAP08 

(2008) 

ESTIAP09 

(2009) 

ESTIAP10 

(2010) 

ESTIAP11 

(2011) 

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 2017 NIS-Child Public-Use Data File Page 69
Table 10 (continued): Cross-Walk Between ITRUEIAP, ESTIAP, ESTIAP06-ESTIAP17, and 

Common Denominator Estimation Area (CDIAP), National Immunization 

Survey - Child, 2017

CDIAP Area Name ESTIAP12 

(2012) 

ESTIAP13 

(2013) 

ESTIAP14 

(2014) 

ESTIAP15 

(2015) 

ESTIAP16 

(2016) 

ESTIAP17 

(2017) 

Alabama 

20 AL-Jefferson County 20 20 20 20 20 20 

20 AL-Rest of State 20 20 20 20 20 20 

74 Alaska 74 74 74 74 74 74 

Arizona 

66 AZ-Maricopa County 66 66 66 66 66 66 

66 AZ-Rest of State 66 66 66 66 66 66 

46 Arkansas 46 46 46 46 46 46 

California 

68 CA-Fresno County 68 68 68 68 68 68 

68 CA-Los Angeles County 68 68 68 68 68 68 

68 CA-Northern CA 68 68 68 68 68 68 

68 CA-San Diego County 68 68 68 68 68 68 

68 CA-Santa Clara County 68 68 68 68 68 68 

68 CA-San Bernardino County 68 68 68 68 68 68 

68 CA-Alameda County 68 68 68 68 68 68 

68 CA-Rest of State 68 68 68 68 68 68 

Colorado 

60 CO-Denver 60 60 60 60 60 60 

60 CO-Rest of State 60 60 60 60 60 60 

1 Connecticut 1 1 1 1 1 1 

13 Delaware 13 13 13 13 13 13 

12 District of Columbia 12 12 12 12 12 12 

Florida 

22 FL-Miami-Dade County 22 22 22 22 22 22 

22 FL-Duval County 22 22 22 22 22 22 

22 FL-Orange County 22 22 22 22 22 22 

22 FL-Rest of State 22 22 22 22 22 22 

Georgia 

25 GA-Fulton/DeKalb Counties 25 25 25 25 25 25 

25 GA-Rest of State 25 25 25 25 25 25 

72 Hawaii 72 72 72 72 72 72 

75 Idaho 75 75 75 75 75 75 

Illinois 

35 IL-City of Chicago 35 35 35 35 35 35 

34 IL-Madison and St. Clair Counties 34 34 34 34 34 34 

34 IL-Rest of State 34 34 34 34 34 34 

Indiana 

36 IN-Lake County 36 36 36 36 36 36 

36 IN-Marion County 36 36 36 36 36 36 

36 IN-Rest of State 36 36 36 36 36 36 

56 Iowa 56 56 56 56 56 56 

Kansas 

57 KS-Eastern KS 57 57 57 57 57 57 

57 KS-Rest of State 57 57 57 57 57 57 

27 Kentucky 27 27 27 27 27 27 

Louisiana 

47 LA-Orleans Parish 47 47 47 47 47 47 

47 LA-Rest of State 47 47 47 47 47 47 

4 Maine 4 4 4 4 4 4 

Maryland 

14 MD-City of Baltimore 14 14 14 14 14 14 

14 MD-Prince George’s County 14 14 14 14 14 14 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 70
CDIAP Area Name ESTIAP12 

(2012) 

ESTIAP13 

(2013) 

ESTIAP14 

(2014) 

ESTIAP15 

(2015) 

ESTIAP16 

(2016) 

ESTIAP17 

(2017) 

14 MD-Rest of State 14 14 14 14 14 14 

Massachusetts 

2 MA-City of Boston 2 2 2 2 2 2 

2 MA-Rest of State 2 2 2 2 2 2 

Michigan 

38 MI-City of Detroit 38 38 38 38 38 38 

38 MI-Rest of State 38 38 38 38 38 38 

Minnesota 

40 MN-Twin Cities 40 40 40 40 40 40 

40 MN-Rest of State 40 40 40 40 40 40 

28 Mississippi 28 28 28 28 28 28 

Missouri 

58 MO-St. Louis County/City 58 58 58 58 58 58 

58 MO-Rest of State 58 58 58 58 58 58 

61 Montana 61 61 61 61 61 61 

59 Nebraska 59 59 59 59 59 59 

Nevada 

73 NV-Clark County 73 73 73 73 73 73 

73 NV-Rest of State 73 73 73 73 73 73 

5 New Hampshire 5 5 5 5 5 5 

New Jersey 

8 NJ-City of Newark 8 8 8 8 8 8 

8 NJ-Rest of State 8 8 8 8 8 8 

New Mexico 

49 NM-Southern NM 49 49 49 49 49 49 

49 NM-Rest of State 49 49 49 49 49 49 

New York 

11 NY-City of New York 11 11 11 11 11 11 

10 NY-Rest of State 10 10 10 10 10 10 

29 North Carolina 29 29 29 29 29 29 

62 North Dakota 62 62 62 62 62 62 

Ohio 

41 OH-Cuyahoga County 41 41 41 41 41 41 

41 OH-Franklin County 41 41 41 41 41 41 

41 OH-Rest of State 41 41 41 41 41 41 

50 Oklahoma 50 50 50 50 50 50 

76 Oregon 76 76 76 76 76 76 

Pennsylvania 

16 PA-Allegheny County 16 16 16 16 16 16 

17 PA-Philadelphia County 17 17 17 17 17 17 

16 PA-Rest of State 16 16 16 16 16 16 

6 Rhode Island 6 6 6 6 6 6 

30 South Carolina 30 30 30 30 30 30 

63 South Dakota 63 63 63 63 63 63 

Tennessee 

31 TN-Davidson County 31 31 31 31 31 31 

31 TN-Shelby County 31 31 31 31 31 31 

31 TN-Rest of State 31 31 31 31 31 31 

Texas 

55 TX-Bexar County 55 55 55 55 55 55 

54 TX-City of Houston 54 54 54 54 54 54 

51 TX-Dallas County 52 51 51 51 52 52 

53 TX-El Paso County 53 53 53 53 53 53 

51 TX-Hidalgo County 51 51 51 107 51 51 

51 TX-Travis County 51 51 51 51 51 108 

51 TX-Rest of State 51 51 51 51 51 51 

64 Utah 64 64 64 64 64 64 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 71
CDIAP Area Name ESTIAP12 

(2012) 

ESTIAP13 

(2013) 

ESTIAP14 

(2014) 

ESTIAP15 

(2015) 

ESTIAP16 

(2016) 

ESTIAP17 

(2017) 

7 Vermont 7 7 7 7 7 7 

18 Virginia 18 18 18 18 18 18 

Washington* 

77 WA-Eastern WA 77 77 77 77 77 77 

77 WA-Western WA 77 77 77 77 77 77 

77 WA-King County 77 77 77 77 77 77 

77 WA-Rest of State 77 77 77 77 77 77 

19 West Virginia 19 19 19 19 19 19 

Wisconsin 

44 WI-Milwaukee County 44 44 44 44 44 44 

44 WI-Rest of State 44 44 44 44 44 44 

65 Wyoming 65 65 65 65 65 65 

- Puerto Rico - - 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 62 estimation areas for the 2017 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 2017, and (from 2017 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 2017 NIS-Child

public-use data file. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 72
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 2017 NIS-Child public-use data file. 

Appendix I presents key response rate components and the overall CASRO response rate by estimation 

area in the 2017 NIS-Child landline and cell-phone samples.

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 from a single-frame landline RDD sampling design to a dualframe landline and 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). 

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), including components for 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 73
coverage error, nonresponse error, and sampling error. Figure 1 charts the estimated mean total error for 

2009-2013 NIS-Child vaccination coverage rate estimators using the base/design weights (i.e., unadjusted 

for nonresponse and not calibrated to population totals) and using the final weights. For the 4:3:1:3:3:1 

vaccine series, ≥1 MMR, and ≥4 DTaP, total error is smaller in 2010-2013 than in 2009. For 2013, final

weights appear to reduce error relative to the design weights for the 4:3:1:3:3:1 series and 4+ DTaP 

vaccination coverage rate estimators but not for 1+ MMR. 

For 2012 and 2013, the TSE model was extended to include a form of measurement error called “provider 

under-reporting” error, in addition to the coverage and nonresponse error components previously included 

in the model (Wolter et al. 2017b). Sometimes also called “under-ascertainment,” provider underreporting error arises when a child with adequate provider data is truly vaccinated but is reported as 

unvaccinated 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. Figure 2 presents the estimated mean total error for 2012-2013 NISChild vaccination coverage rate estimators, including components for coverage error, nonresponse error, 

under-reporting error, and sampling error, using the design weights and using the final weights. The 

addition of under-reporting error into the TSE model results in negative estimates of TSE for both 2012 

and 2013 for the two vaccines and the vaccine series; that is, the results suggest that the NIS-Child

vaccination coverage rate estimates may be lower than the true vaccination coverage rates for these 

vaccines and this series, and that the total error is largely due to under-reporting error.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 74
Figure 1: Comparison of Estimated Mean Total Error for 4:3:1:3:3:1 Series, ≥1 MMR, and ≥4 

DTaP by Survey Year, Including Components for Coverage Error, Nonresponse 

Error, and Sampling Error, National Immunization Survey - Child, 2009-2013 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 75
Figure 2: Comparison of Estimated Mean Total Error for 4:3:1:3:3:1 Series, ≥1 MMR, and ≥4 

DTaP by Survey Year, Including Components for Coverage Error, Nonresponse 

Error, Under-Reporting Error, and Sampling Error, National Immunization Survey - 

Child, 2012-2013 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 76
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 telephones, 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 are subject to potential bias that may remain after weighting 

adjustments because of the switch from landline to dual landline and cell-phone sample frames in 2011. 

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 2017 NIS-Child Public-Use Data File Page 77
12. Citations for NIS-Child Data 

In publications, please acknowledge the original data source. The citation for the 2017 NIS-Child publicuse data file is:

U.S. Department of Health and Human Services (DHHS). National Center for Immunization and 

Respiratory Diseases . The 2017 National Immunization Survey-Child, Atlanta, GA : Centers for Disease 

Control and Prevention, 2018. 

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: 

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.

 

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 78
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.

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 79
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.

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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 80
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.

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

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Page 81
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.

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.

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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.

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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.

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 2017 NIS-Child Public-Use Data File Page 86
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 2017 NIS-Child Public-Use Data File Appendix A

Page 87
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

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 2017 NIS-Child Public-Use Data File Appendix A

Page 88
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 2017 NIS-Child Public-Use Data File Appendix A

Page 89
Appendix B: Summary Statistics for Sampling Weights by 

Estimation Area

Table B.1: Distribution of Dual-Frame Sampling Weights* for Children with Completed 

Household Interviews, National Immunization Survey - Child, 2017

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

U.S. National† 28,465 5,777,734.93 2.90 6,240.05 202.98 160.83

Alabama 528 86,294.72 5.49 478.13 163.44 64.02

Alaska 431 15,724.71 12.15 74.66 36.48 36.27

Arizona 499 125,593.22 15.51 742.69 251.69 62.55

Arkansas 456 54,096.03 13.44 331.33 118.63 64.39

California 628 724,844.35 4.33 6,240.05 1154.21 122.92

Colorado 456 96,362.40 4.07 782.94 211.32 74.26

Connecticut 530 53,956.06 7.45 303.12 101.80 58.57

Delaware 428 15,956.53 8.66 94.13 37.28 50.06

District of Columbia 495 11,907.99 7.07 75.13 24.06 61.88

Florida 624 333,967.39 2.90 2,287.94 535.20 98.29

Georgia 546 191,399.40 4.31 1,117.07 350.55 75.40

Hawaii 432 25,841.20 20.23 134.32 59.82 42.83

Idaho 356 32,714.85 26.86 228.83 91.90 47.98

Illinois 875 221,145.14 10.04 669.24 252.74 51.92

 IL-City of Chicago 254 55,734.70 10.04 669.24 219.43 62.22

 IL-Rest of State 621 165,410.44 64.87 618.34 266.36 47.53

Indiana 491 121,654.56 6.47 692.56 247.77 62.69

Iowa 368 56,511.73 10.68 388.19 153.56 50.40

Kansas 346 57,394.28 6.44 489.04 165.88 63.67

Kentucky 455 78,507.05 2.90 482.36 172.54 57.84

Louisiana 577 89,898.15 14.89 424.53 155.80 66.64

Maine 507 18,126.70 11.49 89.75 35.75 50.15

Maryland 667 106,853.05 7.27 886.14 160.20 139.65

Massachusetts 498 103,772.92 5.39 966.90 208.38 94.88

Michigan 419 162,700.80 53.07 1,020.63 388.31 59.14

Minnesota 471 101,355.73 6.24 839.54 215.19 76.68

Mississippi 553 54,325.00 10.53 284.50 98.24 62.63

Missouri 439 109,009.31 4.20 656.86 248.31 58.47

Montana 360 17,803.72 4.90 139.85 49.45 67.45

Nebraska 397 38,977.56 6.28 286.20 98.18 51.06

Nevada 442 53,030.52 3.65 324.06 119.98 55.51

New Hampshire 436 18,721.80 13.64 96.20 42.94 39.31

New Jersey 710 150,877.95 6.24 668.97 212.50 64.77

New Mexico 441 37,622.84 6.61 234.77 85.31 51.24

New York 1,099 336,084.55 5.71 948.74 305.81 58.75

 NY-City of New York 550 168,118.80 8.89 948.74 305.67 61.68

 NY-Rest of State 549 167,965.75 5.71 840.64 305.95 55.72

North Carolina 514 178,152.60 9.48 1,221.73 346.60 79.95

North Dakota 425 17,055.35 6.54 106.38 40.13 47.95

Ohio 506 198,393.56 7.17 1,048.28 392.08 60.00

Oklahoma 418 76,868.53 4.98 487.82 183.90 53.55

Oregon 421 65,926.80 4.17 400.01 156.60 56.55

Pennsylvania 1,066 203,622.02 7.10 1,151.64 191.02 140.29

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX B 

90
State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

 PA-Philadelphia County 420 32,047.24 10.50 232.73 76.30 55.79

 PA-Rest of State 646 171,574.78 7.10 1,151.64 265.60 120.99

Rhode Island 435 15,601.31 16.21 83.39 35.87 35.93

South Carolina 486 84,346.96 8.70 513.53 173.55 69.27

South Dakota 401 18,176.56 9.30 120.47 45.33 54.79

Tennessee 463 120,737.85 8.60 736.65 260.77 67.25

Texas 2,998 597,274.70 8.07 1,136.41 199.22 110.01

 TX-Bexar County 432 41,341.20 10.63 276.90 95.70 59.64

 TX-City of Houston 267 81,761.14 27.54 925.12 306.22 62.56

 TX-Dallas County 391 60,343.43 11.05 468.87 154.33 62.04

 TX-El Paso County 364 20,193.58 9.09 151.94 55.48 56.89

 TX-Travis County 388 24,670.43 22.87 129.63 63.58 29.71

 TX-Rest of State 1,156 368,964.92 8.07 1,136.41 319.17 86.95

Utah 403 74,288.54 3.17 524.35 184.34 62.61

Vermont 401 8,247.80 7.59 45.83 20.57 42.02

Virginia 679 148,412.16 5.60 1,121.54 218.57 145.10

Washington 489 131,871.37 8.11 1,036.21 269.68 78.21

West Virginia 536 29,298.81 10.35 136.81 54.66 54.93

Wisconsin 383 96,464.15 5.34 654.51 251.86 53.50

Wyoming 481 9,963.68 4.51 55.85 20.71 55.80

* Distribution of RDDWT_D.

† Excludes U.S. territories. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX B 

91
Table B.2: Distribution of Dual-Frame Sampling Weights* for Children with Adequate Provider 

Data, National Immunization Survey - Child, 2017

State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

U.S. National† 15,333 5,777,734.93 3.17 11,555.06 376.82 171.66

Alabama 295 86,294.72 14.28 973.95 292.52 82.11

Alaska 251 15,724.71 19.97 149.19 62.65 43.49

Arizona 265 125,593.22 27.78 1,387.23 473.94 72.03

Arkansas 258 54,096.03 18.06 648.29 209.67 74.42

California 324 724,844.35 13.03 11,555.06 2237.17 131.09

Colorado 264 96,362.40 8.59 1,418.76 365.01 78.97

Connecticut 266 53,956.06 18.61 606.12 202.84 67.05

Delaware 232 15,956.53 13.53 187.14 68.78 55.78

District of Columbia 269 11,907.99 5.15 148.11 44.27 82.97

Florida 314 333,967.39 10.60 4,617.23 1063.59 107.85

Georgia 299 191,399.40 12.53 2,040.10 640.13 84.12

Hawaii 236 25,841.20 25.49 318.88 109.50 53.74

Idaho 198 32,714.85 39.79 462.41 165.23 54.63

Illinois 473 221,145.14 13.48 1,534.61 467.54 60.84

 IL-City of Chicago 137 55,734.70 13.48 1,534.61 406.82 77.49

 IL-Rest of State 336 165,410.44 86.80 1,408.15 492.29 54.34

Indiana 256 121,654.56 11.94 1,749.82 475.21 79.26

Iowa 226 56,511.73 24.66 612.98 250.05 52.37

Kansas 192 57,394.28 11.74 1,042.22 298.93 77.78

Kentucky 229 78,507.05 33.49 986.48 342.83 64.13

Louisiana 282 89,898.15 12.97 1,044.35 318.79 82.62

Maine 271 18,126.70 13.17 179.64 66.89 55.16

Maryland 361 106,853.05 8.04 1,395.37 295.99 138.74

Massachusetts 271 103,772.92 7.22 1,790.77 382.93 101.93

Michigan 237 162,700.80 95.33 2,075.78 686.50 61.74

Minnesota 249 101,355.73 13.99 1,751.13 407.05 88.47

Mississippi 247 54,325.00 22.46 732.53 219.94 74.87

Missouri 229 109,009.31 9.08 1,366.92 476.02 65.51

Montana 216 17,803.72 8.20 270.72 82.42 72.60

Nebraska 246 38,977.56 12.27 427.10 158.45 49.32

Nevada 235 53,030.52 5.01 663.41 225.66 62.70

New Hampshire 236 18,721.80 20.23 197.03 79.33 45.33

New Jersey 356 150,877.95 16.70 1,348.48 423.81 71.50

New Mexico 233 37,622.84 8.87 496.49 161.47 60.04

New York 543 336,084.55 12.82 2,310.52 618.94 65.11

 NY-City of New York 264 168,118.80 16.98 2,310.52 636.81 69.39

 NY-Rest of State 279 167,965.75 12.82 1,720.67 602.03 60.19

North Carolina 298 178,152.60 10.60 2,021.73 597.83 83.16

North Dakota 222 17,055.35 11.49 232.86 76.83 58.27

Ohio 279 198,393.56 13.83 2,263.11 711.09 66.59

Oklahoma 219 76,868.53 14.46 1,107.01 351.00 63.12

Oregon 254 65,926.80 5.69 847.07 259.55 66.67

Pennsylvania 543 203,622.02 11.36 2,377.24 374.99 134.00

 PA-Philadelphia County 195 32,047.24 28.09 534.16 164.34 69.92

 PA-Rest of State 348 171,574.78 11.36 2,377.24 493.03 119.67

Rhode Island 249 15,601.31 22.26 169.73 62.66 49.39

South Carolina 238 84,346.96 10.91 1,181.29 354.40 77.31

South Dakota 244 18,176.56 16.21 212.24 74.49 65.53

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX B 

92
State/Estimation Area n Sum Minimum Maximum Mean

Coefficient 

of Variation

Tennessee 272 120,737.85 21.59 1,448.48 443.89 77.10

Texas 1,545 597,274.70 11.11 2,289.58 386.59 109.23

 TX-Bexar County 239 41,341.20 21.73 493.02 172.98 59.21

 TX-City of Houston 122 81,761.14 73.56 1,930.08 670.17 66.37

 TX-Dallas County 167 60,343.43 67.20 1,060.87 361.34 63.71

 TX-El Paso County 198 20,193.58 11.11 308.08 101.99 61.40

 TX-Travis County 220 24,670.43 32.43 279.14 112.14 43.94

 TX-Rest of State 599 368,964.92 37.74 2,289.58 615.97 82.35

Utah 249 74,288.54 3.17 1,015.26 298.35 61.55

Vermont 251 8,247.80 13.06 87.42 32.86 54.39

Virginia 356 148,412.16 7.05 2,100.29 416.89 139.50

Washington 272 131,871.37 12.63 2,033.53 484.82 85.67

West Virginia 298 29,298.81 13.63 280.53 98.32 63.75

Wisconsin 218 96,464.15 9.32 1,171.49 442.50 57.13

Wyoming 267 9,963.68 7.18 110.33 37.32 61.17

* Distribution of PROVWT_D.

†

 Excludes U.S. territories. 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX B 

93
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 2017 NIS-Child Public-Use Data File APPENDIX C 

94
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 96

II. SAS (SAS, 2003) Page 109

III. ‘R’ (Lumley, 2009) Page 120

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

95
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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let estiap=estiap17; * --- ESTIMATION AREA VARIABLE TO USE ---*;

%let wt=provwt_d; * --- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. Use 

PROVWT_D_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"

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

96
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"

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"

108 = "TX-Travis County" 

; 

run; 

Data User’s Guide for the 2017 NIS-Child Public-Use Data FileAPPENDIX D 

97
data sud_file;

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 108 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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

98
*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_d; *--- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. Use 

PROVWT_D_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 '

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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 '

; 

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 56 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 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))) label noobs; 

format state statef.; 

var state rowper serow ;

label

rowper='Percent 4:3:1:3:3:1:4 Up-to-Date'

serow='Standard Error'

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; 

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_D. 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;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=rddwt_d; * --- WEIGHT TO USE (RDDWT_D is the dual-frame weight excluding territories. Use 

RDDWT_D_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 '

11 ='District of Columbia'

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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 '

; 

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) ===*;

proc sort; 

by &strat nseqnumh;

run; 

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proc crosstab data=sud_file filetype=sas design=wr;

weight &wt;

nest &strat nseqnumh;

subgroup state had_cpox ;

levels 56 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 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))) 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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

libname out 'c:\nispuf17'; *--- SPECIFY THE PATH FOR WHERE YOU WANT THE CHART OUTPUT TO GO ---*;

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%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_d; *--- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. Use 

PROVWT_D_TERR to include territories) ---*;

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

%let qtr_lab=Q1/2017 - Q4/2017; *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 '

23 ='Maine '

24 ='Maryland '

25 ='Massachusetts '

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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 '

; 

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;

run; 

title3 "Table 4A. &qtr_lab: Unweighted Frequencies"; 

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)"

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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 "&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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

%let out='c:\nispuf17'; *--- 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=Q1/2017 - Q4/2017; *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 sud_est4;

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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;

TITLE1 HEIGHT=3 "Percentage of Children Up-to-date with Vaccine Series 4:3:1:3:3:1:4 "; 

TITLE2 HEIGHT=3 "by Race and Poverty Status, National Immunization Survey - Child, 2017"; 

footnote j=r 'graph_4sud'; 

pattern1 value = solid color = blue;

pattern2 value = x3 color = green;

pattern3 value = l3 color = red;

pattern4 value = empty color = lib;

axis width = 3; 

run; 

proc gchart data=sud_est4;

vbar race_k

/frame

discrete

sumvar=rowper

group=incpov1

gspace = 5

gaxis = axis

raxis = axis

name = 'graph_4_sud'

patternid = midpoint

; 

run; 

quit; 

ods html close; 

ods listing; 

ods html close; 

ods listing; 

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Data User’s Guide for the 2017 NIS

-Child Public-Use Data FileAPPENDIX D 

108
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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let estiap=estiap17; * --- ESTIMATION AREA VARIABLE TO USE ---*;

%let wt=provwt_d; * --- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. Use 

PROVWT_D_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"

30 = "SC"

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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"

108 = "TX=Travis County" 

; 

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;

weight &wt;

class P_UTD431H314_ROUT_S; 

var P_UTD431H314_ROUT_S; 

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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 3,7,14,43,52,57-71,73-77. 

**********************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_d; * --- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. Use 

PROVWT_D_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"

0 ='U.S. Total '

1 ='Alabama '

2 ='Alaska '

4 ='Arizona '

5 ='Arkansas '

6 ='California '

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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 '

; 

run; 

data sas_file;

set &in_file(keep= seqnumhh seqnumc P_UTD431H314_ROUT_S state &wt &strat);

run; 

proc sort data = sas_file;

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112
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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=rddwt_d; *--- WEIGHT TO USE (RDDWT_D is the dual-frame weight excluding territories. Use 

RDDWT_D_TERR to include territories) ---*;

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

PROC FORMAT; 

value hadcpoxf

1='Yes'

2='No'

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113
; 

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 '

44 ='Rhode Island '

45 ='South Carolina '

46 ='South Dakota '

47 ='Tennessee '

48 ='Texas '

49 ='Utah '

50 ='Vermont '

51 ='Virginia '

53 ='Washington '

54 ='West Virginia '

Data User’s Guide for the 2017 NIS-Child Public-Use Data FileAPPENDIX D 

114
55 ='Wisconsin '

56 ='Wyoming '

; 

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 ESTIMATION AREA"; 

run; 

**********************;

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:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

libname library 'c:\nispuf17'; *--- IF DATASET WAS CREATED WITH FORMATS

STORED ---*;

*--- PERMANENTLY SPECIFY PATH TO LIBRARY ---*;

*--- OTHERWISE COMMENT THIS STATEMENT OUT ---*;

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

115
libname out 'c:\nispuf17'; *--- SPECIFY THE PATH FOR 

WHERE YOU WANT THE CHART OUTPUT TO GO ---*;

%let in_file=dd.nispuf17; *--- NAME OF SAS DATASET ---*;

%let wt=provwt_d; *--- WEIGHT TO USE (PROVWT_D is the dual-frame weight excluding territories. use 

PROVWT_D_TERR to include territories) ---*;

%let strat=stratum; * --- STRATUM VARIABLE TO USE FOR VARIANCE ESTIMATION;

%let qtr_lab=Q1/2017 - Q4/2017; *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;

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; 

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116
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, Percent 4:3:1:3:3:1:4 Up-to-Date and Estimated

Standard Errors"; 

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

END.

*************************************************************************;

options ps=78 ls=90 obs= max;

libname dd 'c:\nispuf17'; *--- SPECIFY PATH TO SAS DATASET ---*;

%let out='c:\nispuf17'; *--- 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=Q1/2017 - Q4/2017; *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"

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

117
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;

TITLE1 HEIGHT=3 "Percentage of Children Up-to-date with Vaccine Series 4:3:1:3:3:1:4 "; 

TITLE2 HEIGHT=3 "by Race and Poverty Status, National Immunization Survey - Child, 2017"; 

footnote j=r 'graph_4'; 

pattern1 value = solid color = blue;

pattern2 value = x3 color = green;

pattern3 value = l3 color = red;

pattern4 value = empty color = lib;

axis width = 3; 

run; 

proc gchart data=sas_est4;

vbar race_k

/frame

discrete

sumvar=mean

group=incpov1

gspace = 5

gaxis = axis

raxis = axis

name = 'graph_4'

patternid = midpoint

; 

run; 

quit; 

ods html close; 

ods listing; 

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX D 

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Data User’s Guide for the 2017 NIS

-Child Public-Use Data FileAPPENDIX D 

119
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:/nispuf17" #"path-to-dataset"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF17.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, 108) 

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", "TX-Travis County") 

#---PROVWT_D WILL BE USED AS A WEIGHT (PROVWT_D IS THE DUAL-FRAME WEIGHT EXCLUDING TERRITORIES. USE 

PROVWT_D_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF17, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, ESTIAP17, 

PROVWT_D, 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

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120
r_est <- subset(r_est, select=c(1,3,5))

#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:/nispuf17" #"path-to-data"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF17.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)

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",

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121
"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"

) 

#---PROVWT_D WILL BE USED AS A WEIGHT (PROVWT_D IS THE DUAL-FRAME WEIGHT EXCLUDING TERRITORIES USE 

PROVWT_D_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF17, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, 

STATE, PROVWT_D, 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_D. 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()

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122
library(Hmisc) #TO USE prn() 

library(prettyR) #TO USE freq()

dd <- "c:/nispuf17" #"path-to-dataset"

#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF17.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)

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",

Data User’s Guide for the 2017 NIS-Child Public-Use Data FileAPPENDIX D 

123
"VERMONT",

"VIRGINIA", 

"WASHINGTON",

"WEST VIRGINIA",

"WISCONSIN",

"WYOMING"

) 

#---RDDWT_D WILL BE USED AS A WEIGHT (RDDWT_D IS THE DUAL-FRAME WEIGHT EXCLUDING TERRITORIES. USE 

RDDWT_D_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF17, select=c(SEQNUMHH, SEQNUMC, STATE,

HAD_CPOX, RDDWT_D, 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:/nispuf17" #"path-to-dataset"

out <-"c:/nispuf17" #"path-to-output" 

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124
#--- NAME OF R DATASET ---# 

in.file <- paste(dd,"/NISPUF17.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")

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_D WILL BE USED AS A WEIGHT (PROVWT_D IS THE DUAL-FRAME WEIGHT EXCLUDING TERRITORIES. USE 

PROVWT_D_TERR TO INCLUDE TERRITORIES)---# 

#---STRATUM WILL BE USED AS A STRATUM VARIABLE FOR VARIANCE ESTIMATION ---# 

R_FILE <- subset(NISPUF17, select=c(SEQNUMHH, SEQNUMC, P_UTD431H314_ROUT_S, RACE_K, INCPOV1, PROVWT_D, 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. Q1/2017 - Q4/2017', '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. Q1/2017 - Q4/2017, 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.

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125
#2. A FILE PATH IS SEPERATED BY SLASH(/)

######################################################################### 

library(survey) #TO USE svydesign(), svymean(), and svyby()

library(Hmisc) #TO USE prn()

dd <- "c:/nispuf17" #---SPECIFY PATH TO R DATASET THAT WAS THE OUTPUT OF R_PROG_4---# 

out <- "c:/nispuf17" #---SPECIFY THE PATH FOR WHERE YOU WANT THE CHART OUTPUT TO GO---# 

#---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=0.75, ylim=c(0,120),

 xlab="Poverty Status",

 ylab="4:3:1:3:3:1:4 Up-To-Date (%)", cex=0.75, cex.names=0.75, border=NA)

legend("top", rownames(utd431H314), col=c("wheat", "lightpink2",

 "forestgreen"), title="Race of Child", pch=15, cex=0.75)

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, 2017\n" 

mtext(paste(title1,title2), cex=1)

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Data User’s Guide for the 2017 NIS

-Child Public-Use Data FileAPPENDIX D 

127
Appendix E: Alphabetical Listing of Variables that are in the 2004-2017 Public-Use Data 

Files

Table E.1 Alphabetical Listing of Variables that are in the 2004-2017 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 Notes§

AGECPOXR AGE IN MONTHS AT CHICKEN POX 

DISEASE (RECODE) 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 

ALL4SHOT HH REPORT OF 4:3:1:3 UP-TO-DATE 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 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 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 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 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 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. 

C_4313 HH REPORT OF 4:3:1:3 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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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

C_DTP HH REPORT OF 4+ DT-CONTAINING 

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+ HIB-CONTAINING 

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 

C5R RELATIONSHIP OF RESPONDENT TO 

CHILD (RECODE) 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 

CEN_REG CENSUS REGION BASED ON TRUE 

STATE OF RESIDENCE 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 

CWIC_01 CHILD EVER RECEIVED WIC 

BENEFITS? 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 

D6R 

NUMBER OF VACCINATION 

PROVIDERS IDENTIFIED BY 

RESPONDENT (RECODE)

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 

DDTP1 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP2 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP3 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP4 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #4 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 Notes§

DDTP5 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP6 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP7 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP8 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DDTP9 AGE IN DAYS OF PROV-REPTD DTCONTAINING SHOT #9 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 

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 

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 

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 

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 

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 

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 

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 

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 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.

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.

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130
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 

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 

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 

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 

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 

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 

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 

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 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 

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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 

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 

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 

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 

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 

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 Starting in 2005, nine shot variables are included for 

each vaccine category.

DHIB1 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB2 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB3 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB4 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB5 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB6 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB7 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB8 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DHIB9 AGE IN DAYS OF PROV-REPTD HIBCONTAINING SHOT #9 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 

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 

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 

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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

DMMR5 AGE IN DAYS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #5 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 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 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 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 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 

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 

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 

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 

DMP5 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #5 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.

DMP6 AGE IN DAYS OF PROV-REPTD 

MUMPS-ONLY SHOT #6 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 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 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 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 

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 

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 

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 

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 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 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 Starting in 2005, nine shot variables are included for each vaccine category.

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133
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 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 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 

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 

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 

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 

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 

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 

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 

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 

DPCV9 

AGE IN DAYS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #9

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 

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 

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 

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 

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 

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 

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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

DPOLIO9 AGE IN DAYS OF PROV-REPTD 

POLIO-CONTAINING SHOT #9 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 

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 

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 

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 

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 

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 

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 

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 

DRB9 AGE IN DAYS OF PROV-REPTD 

RUBELLA-ONLY SHOT #9 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 

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 

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 

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 

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 

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 

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 

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 

DROT9 AGE IN DAYS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #9 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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

DTP1_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP2_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP3_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP4_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP5_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP6_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP7_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP8_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

DTP9_AGE AGE IN MONTHS OF PROV-REPTD 

DT-CONTAINING SHOT #9 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 

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 

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 

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 

DVRC5 AGE IN DAYS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #5 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 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 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 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 Starting in 2005, nine shot variables are included for each vaccine category.

EDUC1 EDUCATION OF MOTHER 

CATEGORIES (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

EST_GRANT 

AREA OF RESIDENCE ACCORDING 

TO THE 56 ORIGINAL CORE 

GRANTEE AREAS

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. 

ESTIAP17 ESTIMATION AREA OF 

RESIDENCE Y Replaced ESTIAP16 in 2017 because estimation areas were modified. 

FLU1_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU2_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU3_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU4_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU5_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #5

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 Notes§

FLU6_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU7_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU8_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

FLU9_AGE 

AGE IN MONTHS OF PROV-REPTD 

SEASONAL FLU-CONTAINING 

VACCINATION #9

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 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. 

FULL_DTP HH REPORT OF 4+ DT-CONTAINING 

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+ HIB-CONTAINING 

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 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.

H1N2_AGE 

AGE IN MONTHS 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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

H1N3_AGE 

AGE IN MONTHS 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.

H1N4_AGE 

AGE IN MONTHS 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.

H1N5_AGE 

AGE IN MONTHS 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.

H1N6_AGE 

AGE IN MONTHS 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.

H1N7_AGE 

AGE IN MONTHS 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.

H1N8_AGE 

AGE IN MONTHS 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.

H1N9_AGE 

AGE IN MONTHS 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.

HAD_CPOX CHILD EVER HAD CHICKEN POX 

DISEASE? 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 PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA2_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA3_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA4_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA5_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA6_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA7_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA8_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEA9_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS A-CONTAINING SHOT #9 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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

HEP_FLAG HEPATITIS B BIRTH SHOT DATE 

IMPUTATION FLAG Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP1_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP2_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP3_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP4_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP5_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP6_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP7_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP8_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HEP9_AGE AGE IN MONTHS OF PROV-REPTD 

HEPATITIS B-CONTAINING SHOT #9 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 mid-year 

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.

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 POLIOCONTAINING 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 Notes§

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 PROV-REPTD 

HIB-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB2_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB3_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB4_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB5_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB6_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB7_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB8_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

HIB9_AGE AGE IN MONTHS OF PROV-REPTD 

HIB-CONTAINING SHOT #9 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 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.

INCPORAR INCOME TO POVERTY RATIO 

(RECODE) 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 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 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 

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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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.

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 CHAMP-VA? 

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 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 Replaced INS_STAT_I starting in 2017.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 

(RECODE) 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 

(RECODE) Y Y Y Y Y Y Y Y Y Replaced MARITAL starting in 2009.

MMR1_AGE AGE IN MONTHS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR2_AGE AGE IN MONTHS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR3_AGE AGE IN MONTHS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR4_AGE AGE IN MONTHS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MMR5_AGE AGE IN MONTHS OF PROV-REPTD 

MEASLES-CONTAINING SHOT #5 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 PROV-REPTD 

MEASLES-CONTAINING SHOT #6 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 PROV-REPTD 

MEASLES-CONTAINING SHOT #7 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 PROV-REPTD 

MEASLES-CONTAINING SHOT #8 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 PROV-REPTD 

MEASLES-CONTAINING SHOT #9 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

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 PROV-REPTD 

MUMPS-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP2_AGE AGE IN MONTHS OF PROV-REPTD 

MUMPS-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP3_AGE AGE IN MONTHS OF PROV-REPTD 

MUMPS-ONLY SHOT #3 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 Notes§

MP4_AGE AGE IN MONTHS OF PROV-REPTD 

MUMPS-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MP5_AGE AGE IN MONTHS OF PROV-REPTD 

MUMPS-ONLY SHOT #5 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 PROV-REPTD 

MUMPS-ONLY SHOT #6 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 PROV-REPTD 

MUMPS-ONLY SHOT #7 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 PROV-REPTD 

MUMPS-ONLY SHOT #8 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 PROV-REPTD 

MUMPS-ONLY SHOT #9 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.

MPR1_AGE AGE IN MONTHS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR2_AGE AGE IN MONTHS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR3_AGE AGE IN MONTHS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR4_AGE AGE IN MONTHS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

MPR5_AGE AGE IN MONTHS OF PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #5 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 PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #6 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 PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #7 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 PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #8 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 PROV-REPTD 

(MUMPS/RUBELLA)-ONLY SHOT #9 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 

NUM_CELLS_HH

NUMBER OF WORKING CELL 

PHONES HOUSEHOLD MEMBERS 

HAVE AVAILABLE FOR PERSONAL 

USE 

Y Y Y Y Y Y Y Y Y Question added to household questionnaire in 2009.

NUM_CELLS_PARE

NTS

NUMBER OF WORKING CELL 

PHONES USUALLY USED BY 

PARENTS OR GUARDIANS

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 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 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 

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 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 

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 

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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 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 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 

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 

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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 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 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 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 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 

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 Added in 2006 so that each vaccine type on the IHQ 

has a corresponding shot count variable.

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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 

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 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 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 

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 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 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 Added in 2009 due to change to IHQ shotgrid.

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 Replaced P_NUMH2 starting in 2010 due to a change 

in the IHQ shotgrid. 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 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 

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 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 

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 

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 

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 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 Notes§

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 

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 

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 

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 

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 

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 

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 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 Added in 2010 due to new PCV vaccination 

recommendations. 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 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 

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 

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 

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 

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 

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 Starting in 2009, rotavirus 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 Notes§

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 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 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 

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.

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 

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 

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 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 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 Notes§

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 

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 

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 

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 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 Added in 2009 due to new Hib vaccination 

recommendations. 

P_UTD431H31_ROU

T_S

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 4:3:1:3:3:1 BY 36 MONTHS 

OF AGE (INCLUDES 1+ VARICELLACONTAINING 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 Added in 2009 due to new Hib vaccination 

recommendations. 

P_UTD431H313_RO

UT_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 Added in 2009 due to new Hib vaccination 

recommendations. 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

P_UTD431H314_RO

UT_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 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. 

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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 Added in 2011 to aid analysis. 

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 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 

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 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 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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

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 

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 

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 Added in 2010 due to new PCV vaccination 

recommendations. 

P_UTDPOL 

UTD (UP-TO-DATE) FLAG FOR 

PROVIDER 3+ POLIO-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 

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 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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

PCV1_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #1

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV2_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #2

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV3_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #3

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV4_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #4

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV5_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #5

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV6_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #6

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV7_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #7

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV8_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #8

Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

PCV9_AGE 

AGE IN MONTHS OF PROV-REPTD 

PNEUMOCOCCAL-CONTAINING 

SHOT #9

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 

POL1_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL2_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL3_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL4_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL5_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #5 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 Notes§

POL6_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL7_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL8_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

POL9_AGE AGE IN MONTHS OF PROV-REPTD 

POLIO-CONTAINING SHOT #9 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 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_D 

FINAL DUAL-FRAME PROVIDERPHASE WEIGHT (EXCLUDES 

TERRITORIES)

Y Y Y Y Y Y Y Added in 2011 as dual-frame weight. 

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. 

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 dualframe weight PROVWTVI_D in 2012.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 Added in 2010 to aid analysis. 

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 Added in 2010 to aid analysis. 

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 

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 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 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 

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 

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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 (RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RACEETHK RACE/ETHNICITY OF CHILD 

(RECODE) Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB1_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB2_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB3_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB4_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB5_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB6_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB7_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB8_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

RB9_AGE AGE IN MONTHS OF PROV-REPTD 

RUBELLA-ONLY SHOT #9 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_D FINAL DUAL-FRAME RDD-PHASE 

WEIGHT (EXCLUDES TERRITORIES) Y Y Y Y Y Y Y Added in 2011 as dual-frame weight. 

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 HH-PHASE 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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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. 

RDDWTVI_LL

LANDLINE-FRAME HH-PHASE 

CHILD INTERIVEW WEIGHT 

(INCLUDING U.S. VIRGIN ISLANDS)

Y Replaced RDDWTVI in 2011. Replaced with dualframe 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 

RENT_OWN

IS HOME OWNED/BEING BOUGHT, 

RENTED, OR OCCUPIED BY SOME 

OTHER ARRANGEMENT? 

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 PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT2_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT3_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT4_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT5_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT6_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #6 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT7_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #7 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT8_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #8 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

ROT9_AGE AGE IN MONTHS OF PROV-REPTD 

ROTAVIRUS-CONTAINING SHOT #9 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 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_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.

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.

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

SC_DTP HH SHOT CARD REPORT OF 4+ DTCONTAINING 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 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_HIB HH SHOT CARD REPORT OF 3+ HIBCONTAINING 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-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_VRC 

HH SHOT CARD REPORT OF 1+ 

VARICELLA-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.

SEQNUMC UNIQUE CHILD IDENTIFIER 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 

SEX SEX OF CHILD 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 

STRATUM STRATUM VARIABLE FOR DUALFRAME VARIANCE ESTIMATION 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 Added 2011 to aid analysis. 

U2D_HEP 

BIRTH DOSE HEPATITIS BCONTAINING GIVEN FROM BIRTH 

TO DAY 2 FLAG

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 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.

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162
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 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 PROV-REPTD 

VARICELLA-CONTAINING SHOT #1 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC2_AGE AGE IN MONTHS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #2 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC3_AGE AGE IN MONTHS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #3 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC4_AGE AGE IN MONTHS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #4 Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

VRC5_AGE AGE IN MONTHS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #5 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 PROV-REPTD 

VARICELLA-CONTAINING SHOT #6 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 PROV-REPTD 

VARICELLA-CONTAINING SHOT #7 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 PROV-REPTD 

VARICELLA-CONTAINING SHOT #8 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.

VRC9_AGE AGE IN MONTHS OF PROV-REPTD 

VARICELLA-CONTAINING SHOT #9 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 

XDTPTY2 DT-CONTAINING VACCINATION #2 

TYPE CODE 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 

XDTPTY4 DT-CONTAINING VACCINATION #4 

TYPE CODE 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 

XDTPTY6 DT-CONTAINING VACCINATION #6 

TYPE CODE 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 

XDTPTY8 DT-CONTAINING VACCINATION #8 

TYPE CODE Y Y Y Y Y Y Y Y Y Y Y Y Y Y 

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163
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

XDTPTY9 DT-CONTAINING VACCINATION #9 

TYPE CODE 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 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 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 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 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 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 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 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 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 Starting in 2008, influenza type boxes were added to 

the IHQ shot grid.

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.

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164
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

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 

XHEPTY2 HEPATITIS B-CONTAINING 

VACCINATION #2 TYPE CODE 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 

XHEPTY4 HEPATITIS B-CONTAINING 

VACCINATION #4 TYPE CODE 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 

XHEPTY6 HEPATITIS B-CONTAINING 

VACCINATION #6 TYPE CODE 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 

XHEPTY8 HEPATITIS B-CONTAINING 

VACCINATION #8 TYPE CODE 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 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 

XHIBTY2 HIB-CONTAINING VACCINATION #2 

TYPE CODE 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 

XHIBTY4 HIB-CONTAINING VACCINATION #4 

TYPE CODE 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 

XHIBTY6 HIB-CONTAINING VACCINATION #6 

TYPE CODE 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 

XHIBTY8 HIB-CONTAINING VACCINATION #8 

TYPE CODE 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 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 

XMMRTY2 MEASLES-CONTAINING 

VACCINATION #2 TYPE CODE 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 Notes§

XMMRTY3 MEASLES-CONTAINING 

VACCINATION #3 TYPE CODE 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 

XMMRTY5 MEASLES-CONTAINING 

VACCINATION #5 TYPE CODE 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 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 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 Starting in 2005, nine shot variables are included for 

each vaccine category.

XMMRTY9 MEASLES-CONTAINING 

VACCINATION #9 TYPE CODE 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 

XPCVTY2 PNEUMOCOCCAL-CONTAINING 

VACCINATION #2 TYPE CODE 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 

XPCVTY4 PNEUMOCOCCAL-CONTAINING 

VACCINATION #4 TYPE CODE 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 

XPCVTY6 PNEUMOCOCCAL-CONTAINING 

VACCINATION #6 TYPE CODE 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 

XPCVTY8 PNEUMOCOCCAL-CONTAINING 

VACCINATION #8 TYPE CODE 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 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 

XPOLTY2 POLIO-CONTAINING VACCINATION 

#2 TYPE CODE 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 

XPOLTY4 POLIO-CONTAINING VACCINATION 

#4 TYPE CODE 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 

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Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

XPOLTY6 POLIO-CONTAINING VACCINATION 

#6 TYPE CODE 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 

XPOLTY8 POLIO-CONTAINING VACCINATION 

#8 TYPE CODE 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 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 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 Rotavirus vaccination types were added to the IHQ 

starting 2009.

XROTTY3 ROTAVIRUS-CONTAINING 

VACCINATION #3 TYPE CODE 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 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 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 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 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 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 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 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 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 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 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 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 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 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 Varicella vaccination types were added to the IHQ starting 2006.

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167
Variable Name Variable Label† 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Notes§

XVRCTY9 VARICELLA-CONTAINING 

VACCINATION #9 TYPE CODE 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 

* 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 2017 NIS-Child public-use data file, then the 2017 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.

Data User’s Guide for the 2017 NIS-Child Public-Use Data File APPENDIX E 

168
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, 2017

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* 5,777,735 28,465 15,333 53.9%

Alabama 20 86,295 528 295 55.9%

Alaska 74 15,725 431 251 58.2%

Arizona 66 125,593 499 265 53.1%

Arkansas 46 54,096 456 258 56.6%

California 68 724,844 628 324 51.6%

Colorado 60 96,362 456 264 57.9%

Connecticut 1 53,956 530 266 50.2%

Delaware 13 15,957 428 232 54.2%

District of Columbia 12 11,908 495 269 54.3%

Florida 22 333,967 624 314 50.3%

Georgia 25 191,399 546 299 54.8%

Hawaii 72 25,841 432 236 54.6%

Idaho 75 32,715 356 198 55.6%

Illinois 221,145 875 473 54.1%

 IL-City of Chicago 35 55,735 254 137 53.9%

 IL-Rest of State 34 165,410 621 336 54.1%

Indiana 36 121,655 491 256 52.1%

Iowa 56 56,512 368 226 61.4%

Kansas 57 57,394 346 192 55.5%

Kentucky 27 78,507 455 229 50.3%

Louisiana 47 89,898 577 282 48.9%

Maine 4 18,127 507 271 53.5%

Maryland 14 106,853 667 361 54.1%

Massachusetts 2 103,773 498 271 54.4%

Michigan 38 162,701 419 237 56.6%

Minnesota 40 101,356 471 249 52.9%

Mississippi 28 54,325 553 247 44.7%

Missouri 58 109,009 439 229 52.2%

Montana 61 17,804 360 216 60.0%

Nebraska 59 38,978 397 246 62.0%

Nevada 73 53,031 442 235 53.2%

New Hampshire 5 18,722 436 236 54.1%

New Jersey 8 150,878 710 356 50.1%

New Mexico 49 37,623 441 233 52.8%

Data User’s Guide for the 2017 NIS-Child Public-Use Data File Appendix F

169
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 336,085 1,099 543 49.4%

 NY-City of New York 11 168,119 550 264 48.0%

 NY-Rest of State 10 167,966 549 279 50.8%

North Carolina 29 178,153 514 298 58.0%

North Dakota 62 17,055 425 222 52.2%

Ohio 41 198,394 506 279 55.1%

Oklahoma 50 76,869 418 219 52.4%

Oregon 76 65,927 421 254 60.3%

Pennsylvania 203,622 1,066 543 50.9%

 PA-Philadelphia County 17 32,047 420 195 46.4%

 PA-Rest of State 16 171,575 646 348 53.9%

Rhode Island 6 15,601 435 249 57.2%

South Carolina 30 84,347 486 238 49.0%

South Dakota 63 18,177 401 244 60.8%

Tennessee 31 120,738 463 272 58.7%

Texas 597,275 2,998 1,545 51.5%

 TX-Bexar County 55 41,341 432 239 55.3%

 TX-City of Houston 54 81,761 267 122 45.7%

 TX-Dallas County 52 60,343 391 167 42.7%

 TX-El Paso County 53 20,194 364 198 54.4%

 TX-Travis County 108 24,670 388 220 56.7%

 TX-Rest of State 51 368,965 1,156 599 51.8%

Utah 64 74,289 403 249 61.8%

Vermont 7 8,248 401 251 62.6%

Virginia 18 148,412 679 356 52.4%

Washington 77 131,871 489 272 55.6%

West Virginia 19 29,299 536 298 55.6%

Wisconsin 44 96,464 383 218 56.9%

Wyoming 65 9,964 481 267 55.5%

*Excludes U.S. territories. 

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170
Table F.2: Estimated Population Totals and Sample Sizes for Age Group by Maternal Education, 

National Immunization Survey - Child, 2017

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 854 269,939 483 272,066

19-23 12 Years 1,518 442,858 782 453,285

19-23

>12, Non College 

Graduate 2,059 387,061 1,041 346,564

19-23 College Grad 3,983 633,519 2,212 661,462

24-29 <12 Years 835 272,913 462 284,360

24-29 12 Years 1,420 463,830 741 455,903

24-29

>12, Non College 

Graduate 2,128 447,322 1,107 466,988

24-29 College Grad 4,127 773,379 2,230 750,194

30-35 <12 Years 1,215 349,893 694 367,752

30-35 12 Years 1,968 501,929 980 467,737

30-35

>12, Non College 

Graduate 2,812 464,964 1,491 482,186

30-35 College Grad 5,546 770,128 3,110 769,238

Total 28,465 5,777,735 15,333 5,777,735

* Excludes U.S. territories. 

† Weighted by RDDWT_D.

§ Weighted by PROVWT_D.

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

National Immunization Survey - Child, 2017

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 3,363 535,424 1,883 551,396

19-23 Months Above poverty, <= $75K 2,781 549,994 1,475 564,046

19-23 Months Below poverty 1,784 519,757 967 497,473

19-23 Months Unknown 486 128,202 193 120,461

24-29 Months Above poverty, > $75K 3,436 648,449 1,872 668,412

24-29 Months Above poverty, <= $75K 2,821 631,297 1,509 637,153

24-29 Months Below poverty 1,740 518,159 988 530,242

24-29 Months Unknown 513 159,539 171 121,638

30-35 Months Above poverty, > $75K 4,678 648,711 2,619 635,307

30-35 Months Above poverty, <= $75K 3,808 673,178 2,034 654,799

30-35 Months Below poverty 2,396 612,219 1,382 630,598

30-35 Months Unknown 659 152,806 240 166,210

Total 28,465 5,777,735 15,333 5,777,735

* Excludes U.S. territories. 

† Weighted by RDDWT_D.

§ Weighted by PROVWT_D.

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172
Table F.4: Estimated Population Totals and Sample Sizes for Race/Ethnicity by Poverty Status, 

National Immunization Survey - Child, 2017

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 1,206 215,652 620 201,982

Hispanic Above poverty, <= $75K 1,906 468,413 1,004 477,433

Hispanic Below poverty 2,260 699,984 1,284 690,798

Hispanic Unknown 575 168,036 261 180,571

Non-Hispanic White Only Above poverty, > $75K 8,080 1,219,732 4,638 1,248,158

Non-Hispanic White Only Above poverty, <= $75K 5,346 900,488 2,967 898,176

Non-Hispanic White Only Below poverty 1,960 439,989 1,143 443,703

Non-Hispanic White Only Unknown 687 150,001 210 128,096

Non-Hispanic Black Only Above poverty, > $75K 558 118,002 223 126,394

Non-Hispanic Black Only Above poverty, <= $75K 884 248,618 384 238,099

Non-Hispanic Black Only Below poverty 890 315,205 437 324,098

Non-Hispanic Black Only Unknown 178 64,873 58 49,937

Non-Hispanic Other & 

Multiple Races Above poverty, > $75K 1,633 279,199 893 278,581

Non-Hispanic Other & 

Multiple Races Above poverty, <= $75K 1,274 236,951 663 242,291

Non-Hispanic Other & 

Multiple Races Below poverty 810 194,957 473 199,714

Non-Hispanic Other & 

Multiple Races Unknown 218 57,637 75 49,704

Total 28,465 5,777,735 15,333 5,777,735

* Excludes U.S. territories.

† Race/Ethnicity is self-reported and mutually exclusive.

§ Weighted by RDDWT_D.

¶ Weighted by PROVWT_D.

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173
Table F.5: Estimated Population Totals and Sample Sizes for Age Group by Race/Ethnicity, 

National Immunization Survey - Child, 2017

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 1,749 452,405 939 434,660

19-23 Months Non-Hispanic White Only 4,805 833,442 2,658 825,385

19-23 Months Non-Hispanic Black Only 725 226,172 319 245,063

19-23 Months

Non-Hispanic Other & 

Multiple Races 1,135 221,358 602 228,269

24-29 Months Hispanic 1,788 501,799 951 522,051

24-29 Months Non-Hispanic White Only 4,780 939,213 2,647 965,668

24-29 Months Non-Hispanic Black Only 778 250,851 336 220,491

24-29 Months

Non-Hispanic Other & 

Multiple Races 1,164 265,581 606 249,236

30-35 Months Hispanic 2,410 597,882 1,279 594,074

30-35 Months Non-Hispanic White Only 6,488 937,554 3,653 927,081

30-35 Months Non-Hispanic Black Only 1,007 269,674 447 272,974

30-35 Months

Non-Hispanic Other & 

Multiple Races 1,636 281,803 896 292,785

Total 28,465 5,777,735 15,333 5,777,735

* Excludes U.S. territories.

† Race/Ethnicity is self-reported and mutually exclusive.

§ Weighted by RDDWT_D.

¶ Weighted by PROVWT_D.

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174
Table F.6: Estimated Population Totals and Sample Sizes for Age Group by Sex, National 

Immunization Survey - Child, 2017

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 4,371 924,748 2,308 934,214

19-23 Months Female 4,043 808,628 2,210 799,163

 

24-29 Months Male 4,425 989,935 2,337 977,205

24-29 Months Female 4,085 967,509 2,203 980,240

 

30-35 Months Male 5,921 1,041,121 3,174 1,044,295

30-35 Months Female 5,620 1,045,792 3,101 1,042,619

Total 28,465 5,777,735 15,333 5,777,735

* Excludes U.S. territories. 

† Weighted by RDDWT_D.

§ Weighted by PROVWT_D.

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175
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, Q1/2017-Q4/2017†

 ≥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¶¶¶ 83.2 ± 1.2 92.7 ± 0.8 91.5 ± 0.9 91.8 ± 0.9 91.4 ± 0.9 73.6 ± 1.6 86.0 ± 1.1 91.0 ± 0.9 82.4 ± 1.3 73.2 ± 1.6 70.4 ± 1.5

Alabama 81.4 ± 6.1 94.2 ± 3.4 92.3 ± 3.8 94.9 ± 3.2 92.1 ± 3.7 77.6 ± 6.3 86.1 ± 5.3 92.0 ± 4.0 82.0 ± 6.1 74.2 ± 6.8 71.2 ± 6.8

Alaska 75.1 ± 6.0 90.3 ± 3.6 89.3 ± 4.0 88.2 ± 4.4 91.9 ± 3.3 70.8 ± 6.3 86.2 ± 4.7 85.6 ± 4.7 79.5 ± 5.5 72.4 ± 6.0 69.5 ± 6.3

Arizona 82.2 ± 5.6 94.3 ± 2.8 91.7 ± 3.9 92.6 ± 3.2 91.6 ± 3.5 80.0 ± 5.5 90.2 ± 4.7 92.4 ± 3.4 79.1 ± 5.9 70.6 ± 7.0 66.5 ± 7.0

Arkansas 80.0 ± 6.4 91.5 ± 4.2 92.6 ± 3.9 89.4 ± 4.7 92.1 ± 4.4 80.2 ± 6.0 88.8 ± 4.9 91.2 ± 4.2 79.2 ± 6.5 70.7 ± 7.1 69.4 ± 7.2

California 83.9 ± 6.6 91.9 ± 4.5 92.9 ± 4.7 92.9 ± 4.8 90.9 ± 5.3 66.1 ± 9.4 87.2 ± 6.4 92.6 ± 4.7 81.0 ± 7.4 64.7 ± 9.4 68.6 ± 8.5

Colorado 79.9 ± 6.4 90.9 ± 4.5 87.2 ± 4.8 88.8 ± 4.9 88.2 ± 4.7 73.9 ± 6.5 83.3 ± 5.7 87.6 ± 4.7 79.6 ± 6.2 73.7 ± 7.1 71.0 ± 7.3

Connecticut 86.8 ± 5.8 94.0 ± 3.8 94.6 ± 3.5 95.5 ± 3.1 93.2 ± 3.7 78.5 ± 6.0 94.6 ± 3.4 95.4 ± 3.0 87.7 ± 5.0 84.0 ± 5.5 75.3 ± 7.1

Delaware 88.9 ± 4.5 95.4 ± 3.1 92.9 ± 3.8 94.8 ± 3.1 89.4 ± 4.9 72.9 ± 6.8 94.9 ± 3.0 92.1 ± 3.9 92.0 ± 3.9 84.3 ± 5.2 77.1 ± 6.3

Dist. of Columbia 85.3 ± 6.0 91.3 ± 5.1 94.1 ± 4.3 91.7 ± 4.8 90.3 ± 5.1 69.8 ± 7.5 90.8 ± 5.2 93.5 ± 4.5 85.2 ± 6.0 77.3 ± 7.0 74.0 ± 7.2

Florida 85.3 ± 5.4 92.4 ± 4.2 91.9 ± 4.3 90.6 ± 4.6 90.4 ± 4.6 66.0 ± 7.5 78.3 ± 6.6 93.2 ± 3.7 83.8 ± 5.7 69.1 ± 7.5 76.2 ± 6.7

Georgia 80.1 ± 6.3 92.8 ± 3.8 90.7 ± 4.5 88.2 ± 5.1 93.3 ± 3.4 74.6 ± 6.7 88.9 ± 4.6 92.4 ± 4.1 79.4 ± 6.4 71.2 ± 7.1 65.6 ± 7.2

Hawaii 82.3 ± 5.5 90.3 ± 4.4 90.5 ± 4.3 89.6 ± 4.6 89.0 ± 4.7 76.3 ± 6.7 86.3 ± 5.0 90.0 ± 4.2 80.2 ± 5.8 73.2 ± 6.8 69.8 ± 6.8

Idaho 82.3 ± 6.4 90.8 ± 4.8 92.2 ± 4.4 92.0 ± 4.4 90.7 ± 4.7 75.6 ± 6.9 90.6 ± 4.8 90.1 ± 4.8 82.4 ± 6.3 78.5 ± 6.7 69.2 ± 7.6

Illinois 84.4 ± 4.1 95.6 ± 1.9 91.9 ± 2.9 94.3 ± 2.3 92.9 ± 2.6 73.4 ± 4.7 86.5 ± 3.7 92.4 ± 2.8 84.1 ± 3.9 75.4 ± 4.8 75.4 ± 4.6

IL-City of Chicago 81.8 ± 8.7 96.6 ± 3.2 94.0 ± 6.2 96.6 ± 3.2 95.0 ± 4.0 79.9 ± 8.5 91.9 ± 6.5 93.2 ± 6.4 83.8 ± 8.2 77.6 ± 9.3 75.3 ± 9.3

IL-Rest of State 85.2 ± 4.6 95.3 ± 2.3 91.2 ± 3.3 93.5 ± 2.9 92.2 ± 3.1 71.2 ± 5.6 84.7 ± 4.4 92.2 ± 3.1 84.1 ± 4.4 74.7 ± 5.7 75.5 ± 5.4

Indiana 82.1 ± 6.0 91.1 ± 4.6 87.0 ± 5.2 89.9 ± 4.8 90.1 ± 4.8 78.0 ± 6.2 86.2 ± 5.5 86.4 ± 5.3 79.4 ± 6.5 77.6 ± 6.5 66.3 ± 7.6

Iowa 83.9 ± 5.7 95.7 ± 3.0 91.5 ± 4.4 92.1 ± 4.3 95.2 ± 3.3 82.3 ± 6.3 82.6 ± 6.0 90.1 ± 4.8 86.2 ± 5.5 76.4 ± 6.7 72.8 ± 6.7

Kansas 78.5 ± 7.5 93.3 ± 3.8 89.8 ± 5.5 90.2 ± 5.2 91.5 ± 4.5 72.6 ± 8.1 86.6 ± 5.9 87.1 ± 5.9 83.0 ± 6.6 75.5 ± 7.6 69.5 ± 8.3

Kentucky 84.6 ± 5.7 96.0 ± 2.8 92.7 ± 4.3 95.8 ± 2.9 93.7 ± 3.8 84.1 ± 5.6 88.1 ± 4.7 92.3 ± 4.4 84.9 ± 5.6 80.4 ± 6.1 71.0 ± 7.1

Louisiana 80.7 ± 6.4 93.4 ± 4.3 91.3 ± 4.5 93.3 ± 4.0 96.4 ± 2.0 78.6 ± 6.4 85.2 ± 5.3 89.8 ± 4.7 80.7 ± 6.2 72.4 ± 7.0 70.0 ± 7.3

Maine 90.3 ± 3.9 92.7 ± 3.3 93.7 ± 3.1 91.9 ± 3.4 88.9 ± 4.0 63.1 ± 6.7 84.9 ± 5.0 91.6 ± 3.5 82.4 ± 5.1 75.6 ± 5.9 72.7 ± 6.0

Maryland 82.4 ± 7.6 90.9 ± 5.9 92.4 ± 5.4 91.3 ± 5.8 89.2 ± 6.2 76.0 ± 7.7 87.5 ± 6.3 90.2 ± 6.0 80.8 ± 7.6 74.6 ± 8.1 75.2 ± 8.1

Massachusetts 92.6 ± 4.7 96.1 ± 3.1 98.3 ± 1.9 94.1 ± 4.6 92.9 ± 4.6 75.0 ± 7.5 90.0 ± 5.3 97.6 ± 2.0 92.0 ± 4.2 80.1 ± 7.5 82.1 ± 7.0

Michigan 81.3 ± 5.8 96.4 ± 2.7 92.2 ± 4.0 93.6 ± 3.6 93.7 ± 3.6 81.2 ± 5.7 86.6 ± 5.2 93.9 ± 3.6 82.6 ± 5.9 76.0 ± 7.0 69.9 ± 7.4

Minnesota 83.3 ± 6.4 96.2 ± 2.8 94.3 ± 3.3 94.3 ± 3.2 92.4 ± 4.9 72.1 ± 7.5 89.3 ± 5.2 93.1 ± 3.5 80.5 ± 7.1 70.9 ± 8.0 66.1 ± 8.1

Mississippi 82.9 ± 5.8 94.1 ± 3.7 91.8 ± 4.1 91.8 ± 4.0 93.7 ± 3.7 71.0 ± 7.4 74.6 ± 6.8 92.4 ± 3.7 83.8 ± 5.5 75.6 ± 6.6 68.7 ± 7.3

Missouri 77.0 ± 6.9 89.3 ± 5.2 85.8 ± 6.0 87.2 ± 5.8 89.0 ± 5.1 80.4 ± 5.8 80.0 ± 6.4 85.9 ± 5.8 79.0 ± 6.7 74.7 ± 6.8 71.2 ± 7.2

Montana 80.1 ± 6.7 92.7 ± 4.2 92.3 ± 4.1 92.8 ± 3.9 92.4 ± 4.3 72.7 ± 7.3 77.8 ± 6.9 90.3 ± 5.1 84.1 ± 5.8 73.2 ± 7.5 66.2 ± 7.9

Nebraska 86.4 ± 4.9 94.8 ± 3.1 93.7 ± 3.5 94.0 ± 3.4 93.7 ± 3.5 83.1 ± 5.7 88.6 ± 4.5 93.4 ± 3.6 86.1 ± 4.9 78.7 ± 5.8 77.9 ± 5.9

Nevada 82.0 ± 5.6 94.1 ± 3.0 92.4 ± 3.8 92.3 ± 3.5 95.6 ± 2.4 80.6 ± 6.1 90.9 ± 4.3 93.8 ± 3.3 81.4 ± 5.8 66.0 ± 7.5 71.3 ± 6.6

New Hampshire 89.8 ± 4.4 97.9 ± 2.0 94.1 ± 3.5 97.2 ± 2.2 93.9 ± 3.8 67.2 ± 7.0 88.0 ± 4.6 92.1 ± 3.9 88.8 ± 4.7 84.5 ± 5.5 78.9 ± 5.9

New Jersey 82.8 ± 5.2 92.5 ± 3.5 89.0 ± 4.2 91.7 ± 3.9 91.2 ± 3.9 60.0 ± 6.5 82.8 ± 5.0 90.8 ± 3.6 84.1 ± 4.9 70.2 ± 6.0 69.3 ± 6.1

New Mexico 88.1 ± 4.8 93.4 ± 3.9 89.3 ± 5.0 92.9 ± 4.0 92.4 ± 4.3 71.7 ± 6.8 87.7 ± 5.3 86.4 ± 5.7 81.6 ± 6.2 76.4 ± 6.8 71.9 ± 7.1

New York 83.3 ± 3.7 93.3 ± 2.5 92.5 ± 2.3 92.3 ± 2.7 91.9 ± 2.8 71.3 ± 4.6 81.6 ± 3.9 91.4 ± 2.6 80.4 ± 4.1 74.3 ± 4.5 67.5 ± 4.8

NY-City of New York 79.5 ± 5.7 90.7 ± 4.1 91.9 ± 3.5 90.3 ± 4.3 87.2 ± 4.9 67.1 ± 7.1 79.8 ± 5.9 89.4 ± 3.9 74.6 ± 6.5 67.9 ± 7.0 61.8 ± 7.3

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176
 ≥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§§§

NY-Rest of State 87.2 ± 4.7 95.9 ± 2.7 93.1 ± 3.1 94.4 ± 3.2 96.5 ± 2.4 75.5 ± 6.0 83.5 ± 5.1 93.4 ± 3.4 86.2 ± 4.7 80.7 ± 5.5 73.1 ± 6.2

North Carolina 86.7 ± 5.4 91.1 ± 4.8 92.2 ± 3.9 91.0 ± 4.4 88.8 ± 5.1 77.7 ± 6.6 82.7 ± 6.0 91.0 ± 4.4 84.6 ± 5.7 79.1 ± 6.2 70.9 ± 6.8

North Dakota 86.1 ± 5.3 96.2 ± 2.6 95.7 ± 2.7 94.4 ± 3.0 97.7 ± 1.6 84.0 ± 6.0 94.3 ± 3.2 95.0 ± 2.9 88.1 ± 4.6 83.1 ± 5.7 78.8 ± 6.2

Ohio 81.1 ± 5.5 88.2 ± 4.2 88.3 ± 4.5 88.8 ± 4.1 89.5 ± 4.0 76.5 ± 6.7 78.5 ± 6.3 85.2 ± 5.7 78.8 ± 5.9 67.2 ± 7.1 66.4 ± 7.1

Oklahoma 78.5 ± 6.6 92.7 ± 4.0 91.7 ± 3.9 90.3 ± 4.9 89.8 ± 4.9 78.8 ± 6.7 89.0 ± 4.7 91.5 ± 3.9 78.7 ± 6.6 67.3 ± 7.5 67.3 ± 7.5

Oregon 79.7 ± 6.2 86.4 ± 5.5 90.3 ± 4.2 87.7 ± 5.2 89.0 ± 4.9 76.4 ± 6.2 88.2 ± 4.8 88.9 ± 4.7 77.6 ± 6.4 74.1 ± 6.8 70.3 ± 6.9

Pennsylvania 83.1 ± 5.9 92.0 ± 4.5 91.7 ± 4.6 90.6 ± 4.6 93.3 ± 4.1 78.9 ± 6.1 84.0 ± 5.9 88.4 ± 5.2 83.0 ± 6.0 74.4 ± 6.9 70.4 ± 6.9

PA-Philadelphia County 86.4 ± 5.9 95.3 ± 3.4 95.4 ± 3.5 92.9 ± 4.1 96.6 ± 2.2 76.2 ± 7.6 92.5 ± 4.4 94.6 ± 3.7 79.1 ± 7.5 69.7 ± 8.2 70.4 ± 8.1

PA-Rest of State 82.5 ± 6.9 91.4 ± 5.3 91.0 ± 5.4 90.2 ± 5.4 92.7 ± 4.9 79.4 ± 7.2 82.4 ± 6.9 87.2 ± 6.1 83.8 ± 7.0 75.3 ± 8.0 70.4 ± 8.0

Rhode Island 89.2 ± 4.2 97.3 ± 2.0 95.3 ± 3.0 92.3 ± 3.7 96.9 ± 2.2 75.7 ± 5.9 92.9 ± 3.4 94.6 ± 2.8 89.2 ± 4.3 85.1 ± 5.4 74.4 ± 6.0

South Carolina 81.4 ± 6.7 92.8 ± 4.5 88.0 ± 5.3 86.8 ± 6.0 94.3 ± 4.1 72.4 ± 7.8 85.2 ± 6.0 90.3 ± 4.8 80.5 ± 7.1 67.2 ± 8.3 66.0 ± 8.1

South Dakota 81.8 ± 6.0 90.3 ± 4.8 89.9 ± 4.6 90.0 ± 4.8 90.4 ± 4.6 80.2 ± 5.9 85.3 ± 5.5 89.9 ± 4.7 83.1 ± 5.9 75.9 ± 6.4 74.7 ± 6.7

Tennessee 88.5 ± 4.6 93.9 ± 3.8 92.3 ± 4.2 92.7 ± 4.1 95.0 ± 3.2 73.9 ± 6.5 91.7 ± 4.2 93.1 ± 4.1 87.0 ± 5.0 75.6 ± 7.3 79.3 ± 5.9

Texas 81.2 ± 2.9 93.1 ± 1.9 90.3 ± 2.3 92.4 ± 2.0 90.1 ± 2.2 76.3 ± 3.2 90.7 ± 2.2 89.1 ± 2.6 83.0 ± 2.8 76.0 ± 3.1 67.8 ± 3.5

TX-Bexar County 84.8 ± 5.3 95.8 ± 2.5 96.1 ± 2.6 95.1 ± 2.6 93.4 ± 3.5 76.6 ± 5.9 94.2 ± 3.4 95.7 ± 2.7 87.5 ± 4.7 75.0 ± 6.5 75.6 ± 6.5

TX-City of Houston 81.6 ± 7.7 95.8 ± 3.9 87.8 ± 6.8 93.6 ± 4.9 89.2 ± 6.8 78.8 ± 9.1 87.2 ± 6.7 86.8 ± 7.2 85.0 ± 7.2 78.7 ± 8.4 74.3 ± 9.1

TX-El Paso County 84.2 ± 6.1 94.0 ± 4.2 89.3 ± 5.3 92.5 ± 4.5 92.4 ± 4.3 75.8 ± 7.4 90.8 ± 5.0 89.9 ± 5.3 80.6 ± 6.7 77.2 ± 7.0 66.2 ± 8.0

TX-Dallas County 81.9 ± 7.3 96.0 ± 3.9 93.2 ± 4.6 96.1 ± 4.1 90.8 ± 5.8 76.0 ± 8.0 96.1 ± 2.9 97.6 ± 2.2 86.1 ± 6.4 74.9 ± 8.0 65.6 ± 8.9

TX-Travis County 81.5 ± 5.9 93.5 ± 3.5 92.1 ± 4.0 90.9 ± 4.2 93.0 ± 3.4 75.9 ± 6.1 92.3 ± 3.9 92.9 ± 3.7 83.0 ± 5.7 72.7 ± 6.7 66.7 ± 6.9

TX-Rest of State 80.5 ± 4.2 91.6 ± 2.9 89.7 ± 3.3 91.3 ± 2.9 89.5 ± 3.1 75.8 ± 4.6 90.0 ± 3.1 87.2 ± 3.8 81.6 ± 4.1 75.8 ± 4.4 66.0 ± 4.9

Utah 80.6 ± 5.8 90.3 ± 4.1 88.7 ± 4.4 89.1 ± 4.4 90.5 ± 4.0 78.2 ± 6.1 86.8 ± 4.7 86.9 ± 4.7 81.1 ± 5.8 77.0 ± 6.2 67.9 ± 6.9

Vermont 85.5 ± 5.0 93.9 ± 3.3 93.7 ± 3.5 93.4 ± 3.8 92.3 ± 3.5 52.4 ± 7.2 83.1 ± 5.4 88.6 ± 4.3 89.6 ± 4.3 75.8 ± 6.2 74.0 ± 6.0

Virginia 92.8 ± 4.1 96.9 ± 2.5 97.6 ± 1.9 97.0 ± 2.5 92.9 ± 4.6 71.0 ± 8.7 93.2 ± 3.8 97.2 ± 2.0 90.9 ± 5.7 81.2 ± 7.8 77.1 ± 7.9

Washington 81.0 ± 6.2 88.7 ± 4.8 88.5 ± 4.9 89.4 ± 4.7 88.3 ± 4.8 67.4 ± 7.2 84.6 ± 5.6 89.2 ± 4.8 81.3 ± 6.2 73.6 ± 7.1 69.9 ± 7.2

West Virginia 85.3 ± 4.7 92.7 ± 3.3 89.9 ± 4.2 92.5 ± 3.6 90.5 ± 4.0 69.7 ± 6.2 90.7 ± 4.0 92.3 ± 3.6 85.9 ± 4.7 77.4 ± 5.7 74.7 ± 5.9

Wisconsin 81.1 ± 6.5 89.7 ± 4.8 89.9 ± 5.0 89.7 ± 4.7 90.3 ± 4.2 80.9 ± 5.7 80.5 ± 6.6 87.1 ± 5.3 80.6 ± 6.4 79.1 ± 6.4 69.2 ± 7.4

Wyoming 77.6 ± 6.0 92.9 ± 3.1 89.1 ± 4.3 90.2 ± 4.0 92.1 ± 3.5 65.8 ± 6.5 69.0 ± 6.5 89.2 ± 4.0 84.3 ± 4.9 78.2 ± 5.6 72.0 ± 6.4

* Estimates presented as point estimate (%) ± 95% Confidence Interval. 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 Q1/2017-Q4/2017 National Immunization Survey - Child were born from January 2014 through May 2016. § 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.

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Appendix G: Trends in NIS-Child Response Rates and 

Vaccination Coverage Rates, 1995-2017 

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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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 present. We observe that the trend in the data collection rates is 

downward, with the exception of the percentage of children with adequate provider data, which had

been essentially flat from 1997-2012, but also trending downward since 2013. Note that this chart

reflects the landline sample only. 

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

by Survey Year, National Immunization Survey - Child, 2011-2017†

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

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

Collection by Survey Year, National Immunization Survey - Child, 2011-2017*

* 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 have 

been essentially flat, aside from a declining percentage of children with adequate provider data, a 

moderate increase in the resolution rate in 2014 that is likely due to the introduction of a process for

removing and classifying as non-working cell-phone numbers flagged as having no recent activity, 

and a decline in the resolution rate in 2017 when this process was discontinued.

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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 

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.

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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.

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

United States by Survey Year, National Immunization Survey - Child, 1995-2017*

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

* Excludes U.S. territories. 

† Prior to 2011, estimates are single-frame, landline-sample estimates. From 2011 onward, estimates are dual-frame 

(landline plus 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. 

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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-

2017*†¶

* Excludes U.S. territories. 

† Prior to 2011, estimates are single-frame, landline-sample estimates. From 2011 onward, estimates are dual-frame 

(landline plus 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 slightly upward for the longerestablished vaccines through 2015, while the early trends for new vaccines are strongly upward. 

Vaccination coverage estimates declined slightly in 2016 and have since remained stable. Note that 

this chart reflects the landline sample prior to 2011 and the dual-frame sample thereafter. For more 

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 185
information on interpreting trends in vaccination coverage, see online reports at 

https://www.cdc.gov/vaccines/imz-managers/coverage/childvaxview/pubs-presentations/NIS-vaxtrends-2012-2016.html.

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 186
Appendix H: Vaccine Type Codes 

Table H.1: 2017 NIS-Child Vaccine Type Codes

Vaccine Code Description

03 DTaP/DTP/DT-containing, unknown type

04 DTaP/DTP/DT

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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187
Appendix I: Key NIS-Child Response Rates by Area

Table I.1: Key Indicators* for the Landline Sample by Estimation Area, National 

Immunization Survey - Child, 2017

Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

U.S. National† 80.8 84.4 76.1 51.9 57.2

Alabama 83.0 86.1 70.6 50.5 62.5

Alaska 87.3 88.3 86.4 66.6 39.5

Arizona 83.5 85.8 76.6 54.9 45.7

Arkansas 84.3 88.1 77.4 57.5 65.4

California 80.8 82.7 85.2 57.0 44.3

Colorado 83.5 81.8 80.6 55.1 51.9

Connecticut 76.7 80.4 71.6 44.1 56.4

Delaware 69.5 78.0 71.4 38.7 66.0

District of Columbia 82.4 80.2 78.5 51.9 61.9

Florida 82.5 86.0 68.8 48.8 51.2

Georgia 82.4 83.3 67.6 46.3 66.7

Hawaii 82.7 81.2 66.7 44.8 56.5

Idaho 85.8 86.8 81.0 60.3 54.5

Illinois 84.1 86.2 75.0 54.4 47.3

 IL-City of Chicago 85.7 84.1 75.8 54.6 40.9

 IL-Rest of State 83.0 87.5 74.4 54.0 51.5

Indiana 84.3 86.5 82.4 60.0 58.6

Iowa 86.0 90.3 78.8 61.2 63.0

Kansas 83.8 88.4 90.6 67.1 57.1

Kentucky 81.9 86.9 82.1 58.4 53.1

Louisiana 84.0 86.8 71.9 52.4 42.0

Maine 79.2 88.2 75.8 53.0 65.4

Maryland 77.2 83.3 82.8 53.2 62.3

Massachusetts 74.3 82.6 72.6 44.6 55.8

Michigan 84.3 84.5 78.1 55.6 57.1

Minnesota 84.3 87.1 80.6 59.2 55.6

Mississippi 85.4 87.0 66.7 49.5 57.6

Missouri 83.1 87.6 81.3 59.1 46.4

Montana 83.8 86.5 70.5 51.0 75.0

Nebraska 82.6 86.4 93.1 66.4 68.0

Nevada 79.4 84.2 69.8 46.7 58.7

New Hampshire 78.0 82.7 78.0 50.3 54.5

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Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

New Jersey 76.1 78.1 70.8 42.1 67.8

New Mexico 85.2 88.0 78.6 58.9 67.6

New York 76.4 84.3 79.1 50.9 51.3

 NY-City of New York 76.3 81.7 76.0 47.5 47.3

 NY-Rest of State 76.5 86.6 82.1 54.4 54.9

North Carolina 79.1 85.0 84.8 57.0 66.7

North Dakota 86.3 88.9 91.4 70.1 66.7

Ohio 82.4 85.4 69.8 49.1 53.1

Oklahoma 83.9 85.9 69.2 49.9 74.1

Oregon 85.2 89.5 84.2 64.2 51.4

Pennsylvania 72.6 83.4 75.0 45.4 52.4

 PA-Philadelphia County 71.9 83.7 63.5 38.2 43.5

 PA-Rest of State 73.8 83.1 89.7 54.9 59.6

Rhode Island 74.2 80.5 73.8 44.1 67.4

South Carolina 81.5 86.8 67.4 47.7 54.5

South Dakota 87.6 86.8 83.3 63.4 63.3

Tennessee 83.5 88.0 64.0 47.1 63.6

Texas 83.4 83.5 71.5 49.8 48.0

 TX-Bexar County 80.1 83.2 56.8 37.9 45.5

 TX-City of Houston 86.0 83.4 65.2 46.7 46.4

 TX-Dallas County 85.0 83.9 78.9 56.3 25.9

 TX-El Paso County 83.9 84.3 76.3 53.9 51.9

 TX-Travis County 82.0 81.8 77.8 52.2 47.8

 TX-Rest of State 82.3 83.9 77.5 53.5 60.4

Utah 85.1 86.4 90.6 66.6 74.1

Vermont 79.9 86.8 85.7 59.5 68.2

Virginia 77.7 83.6 62.8 40.8 65.5

Washington 82.6 84.4 83.9 58.5 60.0

West Virginia 76.7 88.1 85.5 57.7 70.0

Wisconsin 81.3 87.2 81.6 57.9 61.3

Wyoming 83.6 86.3 87.9 63.4 46.4

* For the definition of the key indicators see Table 1 of NIS-Child Data User’s Guide.

† Excludes U.S. territories. 

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189
Table I.2: Key Indicators* for the Cell-Phone Sample by Estimation Area, National 

Immunization Survey - Child, 2017

Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

U.S. National† 43.0 83.7 69.5 25.0 53.6

Alabama 48.6 84.4 65.5 26.9 55.6

Alaska 63.9 86.7 79.9 44.3 60.1

Arizona 38.3 86.2 65.6 21.7 53.7

Arkansas 53.2 85.6 68.2 31.1 56.0

California 39.9 85.1 63.3 21.5 52.4

Colorado 35.8 87.6 70.3 22.0 58.3

Connecticut 32.9 82.1 70.9 19.2 49.1

Delaware 38.6 77.9 69.0 20.7 52.8

District of Columbia 40.1 80.7 73.1 23.6 53.6

Florida 39.8 84.7 63.3 21.3 50.3

Georgia 42.4 85.7 66.1 24.0 54.2

Hawaii 39.8 80.3 65.1 20.8 54.5

Idaho 36.8 87.2 73.5 23.5 55.7

Illinois 48.7 85.2 66.4 27.5 54.5

 IL-City of Chicago 54.1 84.6 65.6 30.0 55.2

 IL-Rest of State 46.7 85.4 66.8 26.6 54.3

Indiana 40.1 85.4 71.6 24.5 51.7

Iowa 47.5 87.6 75.8 31.6 61.3

Kansas 45.4 86.1 68.8 26.9 55.3

Kentucky 48.1 84.8 73.3 29.9 50.1

Louisiana 50.4 84.5 67.9 28.9 49.5

Maine 39.5 83.6 73.6 24.3 52.8

Maryland 40.0 82.3 66.7 22.0 53.4

Massachusetts 40.1 82.3 70.1 23.1 54.3

Michigan 41.7 85.9 72.5 26.0 56.5

Minnesota 38.1 86.4 73.2 24.1 52.7

Mississippi 46.9 83.2 63.7 24.9 43.8

Missouri 41.3 86.6 71.9 25.7 52.6

Montana 45.8 88.1 76.0 30.7 58.5

Nebraska 53.9 85.6 74.6 34.5 61.6

Nevada 40.8 85.8 65.1 22.8 52.5

New Hampshire 39.3 79.8 71.0 22.3 54.1

New Jersey 38.0 81.7 64.2 19.9 47.6

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190
Area Resolution 

Rate (%)

Screener 

Completion 

Rate (%)

Interview 

Completion 

Rate (%)

CASRO 

Response 

Rate (%)

Children with 

Adequate Provider 

Data (%)

New Mexico 44.5 86.9 71.5 27.6 51.6

New York 39.8 83.3 61.4 20.4 49.1

 NY-City of New York 41.6 82.7 60.9 20.9 48.1

 NY-Rest of State 38.3 83.9 62.1 20.0 50.1

North Carolina 40.4 84.8 69.9 23.9 57.5

North Dakota 52.8 85.4 73.8 33.3 51.0

Ohio 37.7 85.8 70.4 22.8 55.3

Oklahoma 52.6 84.5 67.0 29.8 50.9

Oregon 35.0 88.5 74.4 23.0 61.1

Pennsylvania 38.1 81.6 67.5 21.0 50.8

 PA-Philadelphia County 38.9 80.8 66.7 20.9 46.8

 PA-Rest of State 35.1 85.2 70.9 21.2 53.3

Rhode Island 39.0 77.1 67.7 20.4 56.0

South Carolina 42.6 84.6 67.8 24.4 48.6

South Dakota 44.4 84.9 78.1 29.4 60.6

Tennessee 42.0 85.8 73.0 26.3 58.4

Texas 41.4 83.6 67.8 23.4 51.8

 TX-Bexar County 46.0 83.5 66.2 25.4 55.9

 TX-City of Houston 39.6 83.2 66.0 21.7 45.6

 TX-Dallas County 38.1 83.0 68.8 21.8 44.0

 TX-El Paso County 41.2 84.5 63.3 22.0 54.6

 TX-Travis County 40.1 83.9 72.8 24.5 57.3

 TX-Rest of State 50.4 81.7 61.0 25.1 51.4

Utah 38.6 87.6 76.9 26.0 60.9

Vermont 40.5 78.5 76.5 24.3 61.9

Virginia 37.9 83.1 70.1 22.1 51.3

Washington 34.4 86.8 69.7 20.8 55.4

West Virginia 45.1 83.1 70.1 26.3 54.1

Wisconsin 43.2 85.4 73.0 26.9 56.5

Wyoming 66.7 84.2 73.1 41.0 56.1

* For the definition of the key indicators see Table 1 of NIS-Child Data User’s Guide. 

† Excludes U.S. territories. 

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191
Table I.3: CASRO Response Rate for the Combined Landline and Cell-Phone Samples* by 

Estimation Area, National Immunization Survey - Child, 2017

Area CASRO Response Rate 

(%)

U.S. National† 26.1

Alabama 27.4

Alaska 45.6

Arizona 22.8

Arkansas 31.8

California 24.4

Colorado 23.1

Connecticut 20.5

Delaware 21.6

District of Columbia 24.1

Florida 22.4

Georgia 24.7

Hawaii 21.3

Idaho 25.0

Illinois 28.5

 IL-City of Chicago 31.4

 IL-Rest of State 27.4

Indiana 25.4

Iowa 32.8

Kansas 28.4

Kentucky 31.0

Louisiana 30.0

Maine 24.9

Maryland 26.0

Massachusetts 24.9

Michigan 27.0

Minnesota 25.2

Mississippi 25.5

Missouri 26.7

Montana 31.7

Nebraska 35.6

Nevada 24.0

New Hampshire 23.4

New Jersey 21.5

New Mexico 28.8

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Area CASRO Response Rate 

(%)

New York 22.2

 NY-City of New York 22.5

 NY-Rest of State 22.2

North Carolina 25.0

North Dakota 34.5

Ohio 23.6

Oklahoma 30.7

Oregon 24.4

Pennsylvania 22.1

 PA-Philadelphia County 21.5

 PA-Rest of State 24.4

Rhode Island 21.3

South Carolina 25.3

South Dakota 30.4

Tennessee 27.2

Texas 24.2

 TX-Bexar County 25.8

 TX-City of Houston 22.6

 TX-Dallas County 22.4

 TX-El Paso County 22.9

 TX-Travis County 25.0

 TX-Rest of State 33.3

Utah 27.3

Vermont 25.7

Virginia 25.0

Washington 21.9

West Virginia 27.4

Wisconsin 28.3

Wyoming 41.8

* For the definition of the CASRO response rate for the combined landline and cell-phone samples, see footnote 6 of Table 

1.

† Excludes U.S. territories.

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