National Health Statistics Reports

Number 109  April 02, 2018

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Use of the National Health Interview Survey Linked to 

Medicaid Analytic eXtract Data to Identify Children With 

Medicaid-covered Births

by Patricia C. Lloyd, Anne K. Driscoll, Alan E. Simon, and Jennifer D. Parker, National Center for Health Statistics

Abstract

Background—The National Center for Health Statistics (NCHS) links survey data 

with administrative data sets, such as Medicaid enrollment and claims data, to enhance 

the scientific value of NCHS population health survey sources.

Objective—This report illustrates the use of National Health Interview Survey 

(NHIS) data linked to Medicaid Analytic eXtract (MAX) data to identify children 

whose births were covered by Medicaid, as indicated in MAX data, among those 

participating in NHIS in early childhood, and briefly describes their selected health 

characteristics.

Methods—The 1999–2005 NHIS linked to 1999–2001 MAX data were used. The 

approach for using MAX data to identify child survey participants who were enrolled 

in Medicaid at birth is described. Selected demographic and health characteristics of 

these children are reported.

Results—Using the linked data files, 2,492 children aged 0–4 years at the time 

of NHIS interview were identified as having been enrolled in Medicaid at birth as 

captured in the MAX data. Most of these children continued to have public insurance 

at the time of interview (69.9%), while 18.7% had private insurance, and 11.4% were 

uninsured. Most of the children were in very good or excellent health (79.1%) and had 

not experienced an unmet medical care need due to cost in the past year (95.3%).

Conclusions—Longitudinal follow-up of children who were enrolled in Medicaid 

at birth is feasible with the linked NHIS and MAX data files. Nearly 2,500 child 

survey participants aged 0–4 years in the 1999–2005 NHIS were identified as enrolled 

in Medicaid at birth during 1999–2001. The 1999–2001 MAX files linked to NHIS 

through 2015, available in 2018, will be able to examine health characteristics for 

older children and adolescents who were enrolled in Medicaid at birth.

Keywords: mothers • longitudinal • health insurance • access to care • health status • 

NHIS

Introduction

Federal health surveys provide 

critical public health information for the 

United States. Collaborating with other 

public and private health partners, the 

National Center for Health Statistics 

(NCHS) uses a variety of data collection 

mechanisms to obtain information from 

multiple sources, including several 

population-based health surveys, 

establishment surveys, and vital statistics. 

This process provides a broad perspective 

to help describe the population’s 

health, influences on health, and health 

outcomes. As the nation’s principal health 

statistics agency, NCHS is expanding the 

use of administrative data for statistical 

purposes to provide the public and policy 

makers with more comprehensive and 

objective data. NCHS is also providing 

additional information to inform policy, 

budget, and operational and management 

decision-making.

NCHS’ record linkage program 

is designed to maximize the value of 

NCHS population-based surveys by 

augmenting survey data with information 

from administrative data sources, 

such as vital statistics, Medicare and 

Medicaid enrollment and claims, and 

Social Security benefit history. Beyond 

enhancing survey data, record linkage 
Page 2 National Health Statistics Reports  Number 109  April 02, 2018

also reduces the cost burden of obtaining 

additional information from survey 

participants, given the expense of 

active follow-up of survey respondents. 

Linkages are conducted between several 

NCHS population-based surveys and 

Medicaid and Medicare records from 

the Centers for Medicare & Medicaid 

Services (CMS) (1). These linked survey 

files provide a unique opportunity to 

examine the factors that influence health 

status, disability, chronic disease, health 

care utilization, and expenditures in the 

elderly, disabled, and poor populations of 

the United States.

Over time, Medicaid has covered 

an increasingly higher percentage 

of deliveries in the United States (2) 

and is now a sizeable source of health 

insurance coverage for U.S. births. In 

2016, 42.6 % of births were covered by 

Medicaid (2). Some children enrolled in 

Medicaid at the time of birth continue to 

have Medicaid coverage throughout their 

childhood whereas others do not. While 

children may be enrolled and unenrolled 

several times throughout the course of 

their childhood, sometimes referred to 

as Medicaid “churning,” many children 

who are ever covered by Medicaid are 

covered continuously by Medicaid for 

several years during their childhood. A 

longitudinal analysis following children 

during a 5-year period showed that, of 

all children enrolled in Medicaid at some 

point during the 5-year timeframe, 51.5% 

were enrolled in Medicaid during all 5 

years (3).

While population health surveys, 

such as the National Health Interview 

Survey (NHIS), can be used to describe 

children enrolled in Medicaid at the 

time of survey participation, Medicaid 

status as reported on surveys is known 

to be underreported (4). Further, even 

when accurately reported, the status at 

interview does not capture the coverage 

throughout childhood. Medicaid claims 

data are limited to information obtained 

for billing purposes, and detailed claims 

are not always available for enrollees in 

managed care programs (1,5). As a result, 

Medicaid enrollment and claims alone do 

not provide sufficient information for all 

health studies.

Using NHIS linked to Medicaid 

Analytic eXtract (MAX) data, this 

report illustrates the ability of these 

linked data to assess health outcomes of 

children whose births, occurring during 

1999–2001, were covered by Medicaid 

and who participated in the 1999–2005 

NHIS during early childhood. Medicaid 

coverage at birth is captured in MAX 

data, based on maternal enrollment in 

Medicaid at the time of delivery. Unlike 

other surveys, NHIS collects identifying 

information from multiple members 

of the household, which enabled the 

identification of children enrolled in 

Medicaid at birth using their mothers’ 

Medicaid information for this report. 

Selected demographic and health 

characteristics available from NHIS for 

identified children are shown.

Methods

Data sources: NHIS–MAX 

linked data

Each year since 1957, NCHS 

has administered NHIS, a nationally 

representative, cross-sectional health 

survey of the civilian noninstitutionalized 

population. The design is a multistage 

sample with primary sampling units of 

counties or adjacent counties, secondary 

sampling units of clusters of houses, and 

tertiary sampling units of households 

and persons within households. Detailed 

descriptions of the NHIS sample design 

are described elsewhere (6). For the 

NHIS years included in this report, 

household response rates for NHIS range 

from a low of 86.5% in 2005 to a high of 

89.6% in 2002.

Medicaid eligibility and claims files 

are submitted individually by each state 

to the Medicaid Statistical Information 

System (MSIS). An extract of these 

files, the MAX files, is then created for 

research purposes by CMS (7). The MAX 

files contain information on Medicaid 

eligibility and claims. Data from the 

Children’s Health Insurance Program 

(CHIP) are included for only some states 

in the MAX files. Births covered by 

CHIP, as noted in the MAX files, are not 

included in this analysis.

This report uses the most recent 

linked data available at the time it was 

written. Data from the 1994–2005 

NHIS and 1999–2009 MAX files 

were linked following an established 

algorithm described elsewhere (1). In 

brief, NHIS linkage-eligible participants 

were identified as those who did not 

refuse to provide their Social Security 

number (SSN) or health insurance 

claim number, had sufficient personally 

identifiable information (PII), and had 

an SSN verified by the Social Security 

Administration (SSA) Enumeration 

Verification System. CMS provided the 

person summary and claims files from 

MAX for linkage-eligible participants 

with SSA-verified SSNs that matched. A 

2015 NCHS report provided information 

on the linkage and MAX files, including 

match rates (1).

The NCHS Ethics Review Board 

(ERB) approved the data linkage of NHIS 

files with MAX files. No additional ERB 

approval was required by NCHS for this 

analysis. The linked NHIS–MAX files are 

restricted use and available to users in the 

NCHS Research Data Center.

For the 1999–2005 NHIS, the survey 

years for this analysis, the percentage of 

persons eligible for linkage in the whole 

sample ranged from 56.2% in 2002 to 

45.3% in 2005 with an overall linkage to 

MAX of 13.6% to 16.5%, respectively 

(3) (Table 4).

Target sample

The target sample comprised 

children aged 0–4 years born 1999–2001 

and enrolled in Medicaid at birth at the 

time of the 1999–2005 NHIS interview. 

Selecting these years of MAX data to 

identify Medicaid births ensured that 

the possible age range of the 1999–2005 

NHIS child participants was 0–4 

years. However, inpatient claims for 

childbirth are for the mother, not the 

child. Consequently, to identify children 

enrolled in Medicaid at birth, it was 

necessary to identify inpatient claims for 

childbirth from their mothers.

The sample of mothers comprised 

1999–2005 NHIS linkage-eligible female 

participants aged 16–49 who lived in 

the same household of a 1999–2005 

NHIS child aged 0–4 years (as indicated 

above), and were identified using the 

variable (MOTHER) from the record of 

the child’s mother available on NHIS. 

Mothers who were not linkage eligible 

(and their children), based on criteria 

described previously, were excluded 
National Health Statistics Reports  Number 109  April 02, 2018 Page 3

from this study. Dates recorded in 

MAX correspond to the beginning and 

ending dates of the hospital service for 

the claim; no specific date of birth is 

recorded. Because of this, and since the 

exact date of birth on NHIS was missing 

for nearly 10% of children during these 

survey years, linkage based on time of 

birth was performed as follows: Children 

were classified as enrolled in Medicaid at 

birth if their mothers successfully linked 

to a childbirth claim in the Medicaid 

MAX files, and the dates provided on 

that claim were consistent with a birth 

corresponding to the child’s date of birth 

or age reported at the time of NHIS 

interview. Children whose mothers did 

not successfully link with a retrospective 

birth covered by Medicaid, for any 

reason, were classified as having a 

non-Medicaid covered birth. However, it 

is possible that some of these births may 

have been covered by Medicaid.

Demographic and health 

variables

Other than Medicaid status at birth, 

all sociodemographic and health-related 

data described in this report come 

from NHIS data in the linked file and 

were collected from an adult who was 

knowledgeable about the child within the 

Family Core questionnaire.

Sociodemographic factors included 

the race and Hispanic origin of the child 

(i.e., Hispanic, non-Hispanic white, 

non-Hispanic black, non-Hispanic other, 

or multiple-race groups) and poverty 

status defined using family income 

as a percentage of the federal poverty 

threshold from the family questionnaire 

(i.e., below 100%, 100%–149%, 

150%–199%, and at or above 200% 

of the poverty threshold). Single 

imputations for race and Hispanic origin 

(https://www.cdc.gov/nchs/nhis/rhoi/

rhoi_faq.htm) and multiple imputations 

for family income are included in NHIS 

data files and are used in this analysis 

(8,9). As states have varying income 

eligibility requirements, poverty status 

is particularly relevant to examining 

Medicaid coverage. Additional variables 

included maternal education (i.e., no high 

school diploma, high school diploma or 

General Educational Development high 

school equivalency diploma [GED], and 

more than a high school education) and 

the child’s age at the time of interview 

(i.e., 0, 1–2, and 3–4 years).

State of residence at the time of 

interview was classified according to 

the U.S. census region (i.e., Northeast, 

Midwest, South, and West) (9). 

Urban–rural classification of county of 

residence was based on the 2006 NCHS 

Urban–Rural Classification Scheme for 

Counties (10) as follows: large central 

metropolitan counties (counties in 

metropolitan statistical areas [MSAs] of 

1 million or more population that contain 

the entire population of the largest 

principal city of the MSA, are completely 

contained in the largest principal city 

of the MSA, or contain at least 250,000 

residents of any principal city of the 

MSA); large fringe metropolitan counties 

(counties in MSAs of 1 million or more 

population that do not qualify as large 

central); medium metropolitan counties 

(counties in MSAs of 250,000 to 999,999 

population); and a combined category 

comprising small metropolitan counties 

(counties within MSAs comprising a 

population of 50,000–250,000), counties 

within micropolitan areas (areas of 

at least 10,000 but less than 50,000 

population), and noncore counties (all 

other areas) (10). For tabulations, the 

combined category (small metropolitan, 

micropolitan, and noncore) is referred to 

as rural.

Health insurance coverage for the 

child at the time of NHIS interview 

was categorized as any private, public 

(including Medicaid, State Children’s 

Health Insurance Program, and other 

government-based insurance), and none. 

The child’s respondent-reported health 

status was categorized as excellent or 

very good, good, and fair or poor. The 

child having an unmet medical need due 

to cost in the last 12 months was assessed 

by the family respondent’s answer to the 

following questions within the Family 

Core questionnaire: “During the past 12 

months, has medical care been delayed 

for {person} because of worry about the 

cost?” and “During the past 12 months, 

was there any time when {person} 

needed medical care, but did not get it 

because {person} couldn’t afford it?”

Analyses

Percentage estimates and 

corresponding 95% Clopper–Pearson 

confidence intervals are shown for all 

sociodemographic, geographic, and 

health variables.

Health status, health insurance, 

and unmet health care need due to cost 

were examined by the child and family 

demographic characteristics described 

above due to their known relationships 

with health and Medicaid enrollment 

(3,5,11) and by the geographic factors 

described above, as geography is known 

to be related to access to health care and 

sociodemographic factors, such as race 

and Hispanic origin (12). Chi-square tests 

were used to assess overall associations 

between child and family characteristics 

and health-related characteristics. 

Associations with statistical significance 

levels less than 0.05 were identified.

The child survey participant was the 

unit of analysis for all tabulations. While 

a mother may have multiple children 

in NHIS, maternal characteristics, 

such as educational attainment, are 

treated as other household-level 

characteristics, such as poverty status. 

Analyses do not account for the 

correlation of maternal characteristics 

between children belonging to the 

same household (approximately 5% 

of all identified eligible children, see 

Results and the Figure). Three children 

were missing information on family 

income, 20 were missing information on 

maternal education, and 7 were missing 

information on health insurance and were 

dropped from corresponding tabulations. 

A total of 31 children had addresses 

that could not be geocoded and were 

excluded from tabulations for region and 

urbanization.

Unless otherwise stated, all 

percentage estimates were weighted. 

The 1999–2005 NHIS sample weights 

for children were adjusted to account 

for missing Medicaid birth status for 

the children with mothers who were 

not linkage eligible. More specifically, 

the sample weights for children with 

Medicaid birth status were inflated 

to account for the sample weights for 

children with missing information 

on Medicaid birth status. A marginal 

calibration model with the child’s race 
Page 4 National Health Statistics Reports  Number 109  April 02, 2018

and Hispanic origin, age, and sex was 

used. This model produced adjusted 

sample weights for the children with 

Medicaid birth status that approximate 

the original weighted distributions of 

these factors among all children. The 

sum of the adjusted sample weights is the 

same as the sum of the original sample 

weights.

SAS System for Windows, release 

9.4 (SAS Institute, Inc., Cary, N.C.), 

and SUDAAN, release 11.0.1 (RTI 

International, Research Triangle Park, 

N.C.), were used for all analyses to

account for the complex design of the

sample. Design-based sample variances

were estimated using Taylor series

linearization.

Results

The Figure is a flowchart of the 

analytic sample selection process. Of 

the total 189,041 children aged 0–17 

years who participated in the 1999–2005 

NHIS, 20,649 were aged 0–4 years and 

born between 1999 and 2001. Using 

information collected about familial 

relationships during the family NHIS 

interview (4), a mother was identified 

in the household for 19,479 of these 

children. In total, 17,099 females aged 

16–49 who participated in the 1999–2005 

NHIS were identified in the survey as 

the biological mother of at least one 

of the 19,479 children. The 19,479 

children were paired to the 17,099 

mothers (mothers may have been paired 

to more than one child). The mother 

was linkage eligible in 10,687 of the 

19,479 pairs (54.9%). Of these pairs for 

which the mother was linkage eligible, 

2,492 children (23.3%) were born the 

same year that their mothers had a 

Medicaid-covered birth. As described 

previously, these children were classified 

as having been a Medicaid-covered 

birth. Of these, 134 mothers (5.0%) had 

more than one child represented in the 

1999–2005 NHIS whose births were 

covered by Medicaid. The children in 

the remaining 8,195 pairs either had 

mothers who were not linked to the 

MAX files or were linked but did not 

have a Medicaid-covered birth in their 

birth year. These children are classified 

as not enrolled in Medicaid at birth or a 

non-Medicaid birth.

Demographic, geographic, 

and health variables

Among the children enrolled in 

Medicaid at birth, 20.0% were under 

1 year of age, 42.5% were aged 1–2 

years, and 37.4% were aged 3–4 

years at the time of interview. Nearly 

one-half (48.8%) of the children were 

non-Hispanic white, 24.8% were 

non-Hispanic black, and 22.7% were 

Hispanic. At the time of interview, the 

majority of the children were below 

200% of the federal poverty threshold 

(79.6%) and 45.2% were below 100%. 

Most children had mothers with no high 

school diploma (40.1%), 30.0% had 

mothers with a high school diploma or 

GED, and 29.9% had mothers with more 

than a high school education. A total of 

37.8% of the children lived in rural areas 

and 48.9% lived in the South (Table 1).

Seven in 10 children aged 0–4 

years enrolled in Medicaid at birth were 

covered by public insurance at the time of 

interview (69.9%), 18.7% were covered 

by private health insurance, and 11.4% 

were uninsured (Table 1). The majority of 

children were reported to be in excellent 

or very good health (79.1%), 18.5% were 

reported to be in good health, and 2.4% 

were reported to be in fair or poor health 

1

Mother may be included in more than one mother–child pair. 2

Based on mother’s linkage-eligibility status.

 NOTE: NHIS is National Health Interview Survey and MAX is Medicaid Analytic eXtract data.

1999–2005 NHIS women aged

16–49 years with at least one 

child born during 1999–2001

(n = 17,099)

Children whose mothers

participated in

1999–2005 NHIS

(n = 19,479)

NHIS mother–child1 pairs

(n = 19,479) 

Linkage-ineligible2

mother–child pair

(n = 8,792)

Linkage-eligible2

mother–child pair

(n = 10,687)

Mothers did not link

to a MAX birth

(n = 8,195)

Mothers linked

to a MAX birth

(n = 2,492)

Children aged 0–4 and

born during 1999–2001

(n = 20,649)

1999–2005 NHIS children

aged 0–17 years

(n = 189,041)

Figure. Analytic sample selection process to identify mothers with and without Medicaid 

births using the 1999–2005 National Health Interview Survey linked to 1999–2001
National Health Statistics Reports  Number 109  April 02, 2018 Page 5

at the time of the interview (Table 1). 

One in 20 children had an unmet medical 

need due to cost at the time of interview 

(4.7%) (Table 1).

Health insurance coverage at the 

time of interview differed by the age of 

the child at the time of interview, race 

and Hispanic origin, poverty status, and 

maternal education. Health insurance 

coverage did not differ with the urban–

rural classification of the county of 

residence, but it differed by region 

(Table 2).

Respondent-reported health status 

did not differ with the age of the child 

or region of residence at the time of 

the interview. However, it significantly 

differed by race and Hispanic origin, 

poverty status, maternal education, and 

the urban–rural classification of county of 

residence (Table 3).

Having an unmet need due to cost 

differed by maternal education but did 

not differ by the age of the child at the 

time of interview or the child’s race 

and Hispanic origin or poverty status 

(Table 4). In addition, unmet need due to 

cost was not associated with the region 

or the rural–urban classification of the 

county of residence (Table 4).

Discussion

This report illustrates how 

NHIS–MAX linked data can be used to 

identify Medicaid-covered births among 

children participating in a national health 

survey at 0–4 years of age. The report 

also investigates health outcomes using 

information collected in NHIS.

While NHIS and MAX data can be 

used separately to examine some health 

conditions for children in the Medicaid 

program, not all children who were 

covered by Medicaid at birth remain in 

Medicaid throughout childhood, and not 

all children in the Medicaid program at 

the time of survey participation were 

enrolled at birth. Importantly, NHIS 

undercounts Medicaid enrollment 

(4), does not capture retrospective 

Medicaid enrollment, or collect detailed 

information on health care delivered 

by Medicaid providers. MAX data are 

compiled for billing purposes and do 

not include information on risk factors 

related to health. Use of these linked 

data expands the analytic capabilities of 

both files.

For illustration, this report describes 

three general health outcomes from 

NHIS for children who had a Medicaidcovered birth: health insurance status, 

general health status, and unmet health 

care need due to cost. With the additional 

linking of more recent NHIS data to 

earlier MAX files, health outcomes for 

older age groups, including outcomes 

more common among older children, 

could also be studied using this approach. 

While not included in this report, this 

approach can also be used to investigate 

later health-related outcomes among 

women participating in NHIS who had a 

Medicaid-covered birth. NHIS collects 

information on multiple household 

members, unlike other NCHS population 

health surveys, which enabled the 

identification of Medicaid coverage at 

birth for child survey participants, as 

described in this report. However, the 

collection of PII for linkage, linkage 

eligibility, and linkage algorithms change 

over time and should be considered when 

conducting similar analyses with later 

surveys and linkages (13).

The approach described in this report 

is subject to the following considerations: 

First, NHIS child participants were paired 

with women in the same household who 

had a birth documented in the MAX 

files corresponding to their date of 

birth. It is possible that some children 

had mothers with births covered by 

Medicaid but were not identified in the 

MAX files. Children with Medicaidcovered births who were not identified 

by NCHS’ procedures may include those 

covered by CHIP, children who were 

adopted or those from foster homes, 

and children with mothers who had 

inaccurate matching information. Second, 

Medicaid birth status could not be 

determined for children whose mothers 

were not linkage eligible (mothers who 

were not linkage eligible could not be 

linked to MAX files). Incomplete data 

due to linkage ineligibility may lead to 

biased estimates. Although the children’s 

sample weights for the tabulations in this 

report were calibrated to approximate 

national age, race and Hispanic origin, 

and sex distributions among children 

for these survey years, there could be 

other factors related to the availability of 

Medicaid birth status, which was based 

on the mother’s linkage eligibility and 

not included in the adjustment model 

that could affect the inferences; other 

approaches for adjusting weights or 

analyzing data to address this potential 

bias could be used. Third, since income 

eligibility requirements for Medicaid 

receipt vary by state, Medicaid eligibility 

does not apply uniformly among those 

selected at the national level to participate 

in the survey, and mothers may or 

may not have met the requirements 

for Medicaid eligibility at the time of 

birth, depending on the state in which 

the birth occurred. As a result, some of 

the children who were not identified as 

enrolled in Medicaid at birth may have 

been enrolled in Medicaid had their 

mothers lived in a different state based on 

income eligibility requirements. As with 

other analyses of MAX data, these state 

differences could affect some research 

questions addressed by the linked NHIS–

MAX data.

In summary, NHIS–MAX linked 

data may be used to assess relationships 

between health status and Medicaid 

coverage at birth among children sampled 

in NHIS. This data source could be used 

for analyses that may inform policy 

analysts and others who are interested in 

data that allow examination of the health 

of children and mothers after a Medicaidcovered birth. With additional years of 

linked NHIS data, this analysis could 

provide an example for future assessment 

of health outcomes for children enrolled 

in Medicaid at birth during 1999–2001 as 

the children grow older.

References

1. Golden C, Driscoll AK, Simon AE, Judson

DH, Miller EA, Parker JD. Linkage

of NCHS population health surveys

to administrative records from Social

Security Administration and Centers for

Medicare & Medicaid Services. National

Center for Health Statistics. Vital Health

Stat 1(58). 2015.

2. Martin JA, Hamilton BE, Osterman MJK,

Driscoll AK, Drake P. Births: Final data

for 2016. National Vital Statistics Reports;

vol 67 no 1. Hyattsville, MD: National

Center for Health Statistics. 2018.
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3. Simon AE, Driscoll A, Gorina Y, Parker

JD, Schoendorf KC. A longitudinal

view of child enrollment in Medicaid.

Pediatrics 132(4):656–62. 2013.

4. Mirel LB, Simon AE, Golden C, Duran

CR, Schoendorf KC. Concordance

between survey report of Medicaid

enrollment and linked Medicaid

administrative records in two national

studies. National Health Statistics Reports;

no 72. Hyattsville, MD: National Center

for Health Statistics. 2014.

5. Lloyd PC, Simon AE, Parker JD.

Characteristics of children in Medicaid

managed care and Medicaid fee-forservice, 2003–2005. National Health

Statistics Reports; no 80. Hyattsville,

MD: National Center for Health Statistics.

2015.

6. Botman SL, Moore TF, Moriarity CL,

Parsons VL. Design and estimation for

the National Health Interview Survey,

1995–2004. National Center for Health

Statistics. Vital Health Stat 2(130). 2000.

7. Centers for Medicare & Medicaid

Services. Medicaid Analytic eXtract

(MAX) general information. Available

from: https://www.medicaid.gov/

medicaid/data-and-systems/macbis/max/

index.html.

8. Schenker N, Raghunathan TE, Chiu P-L,

Makuc DM, Zhang G, Cohen AJ. Multiple

imputation of missing income data in the

National Health Interview Survey. J Am

Stat Assoc 101(475):924–33. 2016.

9. U.S. Census Bureau. Census regions and

divisions of the United States. Available

from: https://www2.census.gov/geo/pdfs/

maps-data/maps/reference/us_regdiv.pdf.

10. Ingram DD, Franco SJ. 2013 NCHS

urban–rural classification scheme for

counties. National Center for Health

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health care for children. Health Serv Res

37(1):173–86. 2002.

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Health, United States, 2001 with urban

and rural health chartbook. Hyattsville,

MD. 2001.

13. Miller DM, Gindi RM, Parker JD.

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Characteristics of National Health

Interview Survey participants who

refuse record linkage. Presented at: Joint

Statistical Meeting. Miami, FL: American

Statistical Association. 2011.
National Health Statistics Reports  Number 109  April 02, 2018 Page 7

Table 1. Percent distribution of child and family characteristics of children with 

Medicaid-covered births at the time of interview, 1999–2005

Characteristic

95% confidence interval

Percent1 Lower Upper

Age (years)

0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.0 18.4 21.8

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.5 40.4 44.7

3–4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37.4 35.3 39.6

Race and Hispanic origin

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.7 20.5 25.1

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.8 45.9 51.7

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.8 22.5 27.2

Non-Hispanic other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 2.8 4.8

Poverty status as a percentage of poverty threshold

Less than 100% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.2 43.0 47.5

100%–149% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.2 19.4 23.1

150%–199% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 11.8 14.8

200% and greater. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.4 18.5 22.4

Maternal education

No high school diploma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40.1 37.9 42.4

High school or GED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30.0 28.0 32.0

More than high school education . . . . . . . . . . . . . . . . . . . . . . . . . . 29.9 27.8 32.1

Urban–rural classification of county of residence2

Large central metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.2 21.8 26.7

Large fringe metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 13.0 17.0

Medium metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.2 19.8 26.9

Rural. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37.8 33.9 41.8

U.S. census region

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.0 12.0 16.3

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.0 20.6 25.7

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.9 46.1 51.8

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.0 12.6 15.5

Health insurance coverage

Private. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 16.8 20.7

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.9 67.6 72.2

Uninsured . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 10.0 13.0

Respondent-reported health status

Very good or excellent health . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  79.1 77.2 80.9

Good. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.5 16.8 20.3

Fair or poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 1.8 3.2

Unmet medical need due to cost . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 3.9 5.7

1

Percentages may not add to 100 due to rounding. 

2

2013 National Center for Health Statistics Urban–Rural Classification Scheme for Counties (see reference 10 in the report).

NOTES: Child and family variables were obtained from the National Health Interview Survey (NHIS) at the time of interview.

GED is General Educational Development high school equivalency diploma.

SOURCE: 1999–2004 NHIS linked to Medicaid Analytic eXtract data.
Page 8 National Health Statistics Reports  Number 109  April 02, 2018

Table 2. Child and family characteristics of children with Medicaid-covered births, by child’s health insurance status at the time of interview, 

1999–2005

Private health 

insurance

95% confidence 

interval

Public health 

insurance

95% confidence 

interval

No health 

insurance 

95% confidence 

interval

Characteristic Lower Upper Lower Upper Lower Upper

Age (years)1

0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.6 10.1 18.1 77.7 73.0 81.7 8.7 6.5 11.5

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.0 15.4 20.8 70.3 66.6 73.7 11.8 9.6 14.4

3–4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3 18.1 24.8 66.9 63.1 70.4 11.9 9.5 14.7

Race and Hispanic origin1

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.9 10.0 16.5 70.1 65.6 74.2 17.0 13.9 20.7

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . . . . . . . 22.5 19.6 25.6 67.5 64.1 70.6 10.1 8.2 12.3

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 11.5 17.5 78.8 75.1 82.0 7.0 5.1 9.4

Non-Hispanic other. . . . . . . . . . . . . . . . . . . . . . . . . . . 24.8 12.2 41.7 56.9 39.3 73.4 18.3 8.8 31.7

Poverty status as a percentage 

of poverty threshold1

Less than 100% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 3.6 6.4 85.8 83.2 88.0 9.4 7.5 11.6

100%–149% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 11.7 19.1 72.3 66.9 77.1 12.7 9.6 16.6

150%–199% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.2 21.1 32.0 59.3 53.1 65.3 14.5 10.9 19.1

200% and greater . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.9 41.9 52.0 41.6 36.9 46.4 11.5 8.5 15.4

Maternal education1

No high school diploma . . . . . . . . . . . . . . . . . . . . . . . 9.8 7.9 12.1 76.4 73.1 79.5 13.7 11.3 16.7

High school or GED . . . . . . . . . . . . . . . . . . . . . . . . . . 20.5 17.3 24.2 70.0 66.1 73.6 9.5 7.2 12.4

More than high school education . . . . . . . . . . . . . . . . 27.3 23.5 31.5 63.7 59.7 67.5 9.0 6.9 11.6

Urban–rural classification of 

county of residence2

Large central metropolitan . . . . . . . . . . . . . . . . . . . . . 17.1 13.7 21.1 70.6 66.0 74.8 12.4 9.5 15.9

Large fringe metropolitan . . . . . . . . . . . . . . . . . . . . . . 24.0 18.9 29.9 66.0 60.5 72.1 9.5 6.4 13.4

Medium metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . 15.7 12.4 19.7 74.8 69.8 78.3 10.0 7.2 13.4

Rural. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 15.7 22.2 69.5 65.5 73.2 11.8 9.6 14.6

U.S. census region1

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.8 11.3 21.5 77.1 70.7 82.5 7.1 4.5 10.5

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.3 18.5 26.5 69.0 64.7 73.0 8.8 6.2 12.0

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3 14.7 20.1 70.9 67.0 73.6 12.4 10.2 14.9

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 14.0 24.4 66.2 59.9 72.0 15.1 11.4 19.8

1

Statistically significant association between health insurance coverage at the time of interview and characteristic (p < 0.05). 2

2013 National Center for Health Statistics Urban–Rural Classification Scheme for Counties (see reference 10 in the report).

NOTES: Child and family variables were obtained from the National Health Interview Survey (NHIS) at the time of interview. GED is General Educational Development high school equivalency diploma. 

SOURCE: 1999–2004 NHIS linked to Medicaid Analytic eXtract data.
National Health Statistics Reports  Number 109  April 02, 2018 Page 9

Table 3. Child and family characteristics of children with Medicaid-covered births, by reported health status at the time of interview, 

1999–2005

Excellent or 

very good

95% confidence 

interval

Good

95% confidence 

interval

Fair or poor

95% confidence 

interval

Characteristic Lower Upper Lower Upper Lower Upper

Age (years)

0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.8 75.6 83.5 18.0 14.5 22.1 2.2 1.1 3.9

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.5 75.8 81.0 18.7 16.5 21.2 2.8 1.8 4.1

3–4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.4 76.2 82.3 18.5 15.6 21.6 2.1 1.2 3.4

Race and Hispanic origin1

Hispanic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.4 73.8 80.6 20.2 17.1 23.7 2.4 1.3 4.1

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . . . . . . . 82.9 79.9 85.6 15.8 13.1 18.9 1.3 0.7 2.2

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . . . . . . . 73.5 70.2 76.6 22.3 19.5 25.4 4.2 2.7 6.1

Non-Hispanic other. . . . . . . . . . . . . . . . . . . . . . . . . . . 76.7 64.5 86.3 18.0 9.6 29.5 5.3 1.2 14.5

Poverty status as a percentage 

of poverty threshold1

Less than 100% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74.7 71.6 77.5 22.0 19.4 24.8 3.4 2.3 4.8

100%–149% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.2 73.0 81.0 19.3 15.8 23.4 3.5 2.0 5.5

150%–199% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.9 77.6 87.1 16.3 12.1 21.5 0.9 0.2 2.6

200% and greater. . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.5 84.6 91.4 11.4 8.5 15.2 0.2 0.0 1.1

Maternal education1

No high school diploma . . . . . . . . . . . . . . . . . . . . . . . 74.3 71.1 77.2 22.9 19.9 26.1 2.8 1.9 4.1

High school or GED. . . . . . . . . . . . . . . . . . . . . . . . . . 79.4 75.7 82.6 18.3 15.2 21.9 2.3 1.3 3.7

More than high school education . . . . . . . . . . . . . . . . 85.6 82.7 88.1 12.6 10.2 15.6 1.8 0.9 3.1

Urban–rural classification of 

county of residence1,2

Large central metropolitan . . . . . . . . . . . . . . . . . . . . . 76.0 72.3 79.3 20.5 17.6 23.9 3.5 1.9 5.9

Large fringe metropolitan. . . . . . . . . . . . . . . . . . . . . . 84.1 79.3 88.0 14.1 10.4 18.8 1.8 0.7 4.0

Medium metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . 75.0 70.2 79.3 23.0 19.0 27.6 2.0 1.0 3.5

Rural. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.3 78.1 84.0 16.5 13.8 19.5 2.3 1.3 3.6

U.S. census region

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.9 73.7 83.3 17.3 13.0 22.6 3.8 1.6 7.6

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.4 73.0 81.3 20.2 16.6 24.3 2.4 1.2 4.3

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.9 77.1 82.4 18.1 15.7 20.8 2.0 1.3 3.0

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.2 73.6 82.2 19.3 15.4 23.9 2.5 1.1 4.8

1

Statistically significant association between health status at the time of interview and characteristic (p < 0.05). 2

2013 National Center for Health Statistics Urban–Rural Classification Scheme for Counties (see reference 10 in the report).

NOTES: Child and family variables were obtained from the National Health Interview Survey (NHIS) at the time of interview. GED is General Educational Development high school equivalency diploma.

SOURCE: 1999–2004 NHIS linked to Medicaid Analytic eXtract data.
Page 10 National Health Statistics Reports  Number 109  April 02, 2018

Table 4. Child and family characteristics of children with Medicaid-covered births, by unmet health care need due to cost at the time of 

interview, 1999–2005

Unmet need

95% confidence interval

No unmet need

95% confidence interval

Characteristic Lower Upper Lower Upper

Age (years)

0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 1.7 4.9 97.0 95.2 98.3

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.0 3.6 6.6 95.0 93.4 96.4

3–4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 3.9 7.2 94.6 92.8 96.1

Race and Hispanic origin

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 2.9 6.6 95.5 93.4 97.1

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 3.9 6.9 94.7 93.1 96.1

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 2.5 5.6 96.2 94.4 97.5

Non-Hispanic other. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 0.8 16.9 94.7 83.1 99.2

Poverty status as a percentage of poverty threshold 

Less than 100% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 3.2 6.1 95.5 94.0 96.8

100%–149% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 2.9 6.7 95.5 93.3 97.1

150%–199% . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0 4.4 10.4 93.0 89.6 95.6

200% and greater. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 2.3 6.6 95.9 93.4 97.7

Maternal education1

No high school diploma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 3.1 6.1 95.6 93.9 96.9

High school or GED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 2.1 5.0 96.7 95.0 97.9

More than high school education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 4.9 8.9 93.3 91.1 95.1

Urban–rural classification of county of residence2

Large central metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 3.6 7.3 94.7 92.7 96.4

Large fringe metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 4.1 9.5 93.6 90.5 95.9

Medium metropolitan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 1.9 5.6 96.6 94.4 98.1

Rural. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 3.0 6.2 95.6 93.8 97.1

U.S. census region

Northeast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 1.2 5.5 97.2 94.5 98.8

Midwest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 3.4 7.6 94.8 92.4 96.6

South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 3.2 6.1 95.5 93.9 96.9

West . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 4.1 9.1 93.8 90.9 96.0

1

Statistically significant association between unmet health care need due to cost at the time of interview and characteristic (p < 0.05). 2

2013 National Center for Health Statistics Urban–Rural Classification Scheme for Counties (see reference 10 in the report).

NOTES: Child and family variables were obtained from the National Health Interview Survey (NHIS) at the time of interview. GED is General Educational Development high school equivalency diploma.

SOURCE: 1999–2004 NHIS linked to Medicaid Analytic eXtract data.
National Health Statistics Reports  Number 109  April 02, 2018

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Suggested citation

Lloyd PC, Driscoll AK, Simon AE, Parker JD. 

Use of the National Health Interview Survey 

linked to Medicaid Analytic eXtract data to 

identify children with Medicaid-covered births. 

National Health Statistics Reports; no 109. 

Hyattsville, MD: National Center for Health 

Statistics. 2018.

Copyright information

All material appearing in this report is in 

the public domain and may be reproduced 

or copied without permission; citation as to 

source, however, is appreciated. 

National Center for Health Statistics

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

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

for Science

Office of Analysis and Epidemiology

Irma E. Arispe, Ph.D., Director

Makram Talih, Ph.D., Associate Director for 

Science

Acknowledgments

The authors would like to thank the editors and graphic designers in the Office of Information Services at the National Center for Health Statistics 

(NCHS). The authors would also like to thank Amy Branum, Deputy Associate Director for Science at NCHS; Makram Talih, Associate Director for 

Science in the Office of Analysis and Epidemiology at NCHS; and Lisa Mirel, Chief of the Special Projects Branch at NCHS, for valuable input on 

this report.