SAFER HEALTHIER PEOPLE TM 

Monitoring the 

Nation's Health 

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Center for Health Statistics 

National Health and Nutrition 

Examination Survey: Estimation 

Procedures, 2011–2014

Vital and Health StatisticsSeries 2, Number 177 January 2018
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Chen TC, Parker JD, Clark J, Shin HC, Rammon JR, Burt VL. National Health and 

Nutrition Examination Survey: Estimation procedures, 2011–2014. National Center 

for Health Statistics. Vital Health Stat 2(177). 2018.

Library of Congress Cataloging-in-Publication Data

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

Title: National health and nutrition examination survey: Estimation 

 procedures, 2011-2014.

Other titles: Estimation procedures, 2011-2014 | Vital and health statistics. 

 Series 2, Data evaluation and methods research ; no. 177. | DHHS 

 publication ; no. 2018-1377. 0276-4733

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

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

 Health Statistics, January 2018. | Series: Vital and health statistics, 

 series 2, data evaluation and methods research ; number 177 | Series: DHHS 

 pub ; number 2018-1377 | Includes bibliographical references.

Identifiers: LCCN 2017057351| ISBN 9780840606860 (pbk.) | ISBN 0840606869 

 (pbk.)

Subjects: | MESH: National Health and Nutrition Examination Survey (U.S.) | 

 Health Surveys | Nutrition Surveys | Body Weight | Sampling Studies | 

 Statistics as Topic | United States

Classification: LCC RA407.3 | NLM W2 A N148vb no.177 2018 | DDC 

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Vital and Health Statistics

Series 2, Number 177

National Health and Nutrition 

Examination Survey: Estimation 

Procedures, 2011–2014

Data Evaluation and Methods Research

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

National Center for Health Statistics

Hyattsville, Maryland 

January 2018 

DHHS Publication No. 2018–1377
National Center for Health Statistics

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

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

Division of Health and Nutrition Examination Surveys

Kathryn S. Porter, M.D., M.S., Director

Ryne Paulose-Ram, Ph.D., Associate Director for Science
iii

Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

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

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

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

Weighting the Sample Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Calculating Base Weights. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Nonresponse Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Trimming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Poststratification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Computing Final Weights. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

NHANES National Youth Fitness Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Subsample Weights. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Combining Survey Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Variance Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Variance Units for Publicly Released Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Restricted Data Access in the NCHS Research Data Center . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Appendix I. Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Appendix II. Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Text Table

Table. Sampling subdomains classified by race and Hispanic origin, income, sex, and age: 

National Health and Nutrition Examination Survey, 2011–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Appendix Tables

I. Final sampling rates and base weights: National Health and Nutrition Examination Survey, 2011–2014 . . . . . . . . . . 13

II. Variables used in forming nonresponse adjustment cells for weighting interview samples:

National Health and Nutrition Examination Survey, 2011–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

III. Variables used in forming nonresponse adjustment cells for weighting mobile examination center 

examination samples: National Health and Nutrition Examination Survey, 2011–2014 . . . . . . . . . . . . . . . . . . . 16

IV. Most common survey sample weights and their appropriate use: National Health and

Nutrition Examination Survey, 2011–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
iv

Acknowledgments

The authors gratefully acknowledge 

the assistance of Michele Chiappa, 

Ryne Paulose-Ram, and Kathryn Porter 

in the preparation of this report.
Page 1 

Introduction

The National Health and Nutrition 

Examination Survey (NHANES) is one 

of a series of health-related programs 

conducted by the National Center for 

Health Statistics (NCHS) to provide 

information on the health and nutritional 

status of the noninstitutionalized civilian 

resident population of the United States. 

This information is used to estimate 

the prevalence of various diseases and 

conditions and to provide information for 

use in planning health policy.

NHANES is unique in collecting 

person-level demographic, health, 

and nutrition information from 

personal interviews (interview) and a 

standardized physical examination in 

a mobile examination center (MEC). 

The examination includes objective 

measures of health status, including 

height, weight, blood pressure, and the 

collection of blood and urine specimens 

for laboratory testing. In 2012, NCHS 

also conducted the NHANES National 

Youth Fitness Survey (NNYFS) to collect 

data on physical activity and fitness 

levels for U.S. children aged 3–15 years. 

NNYFS was designed to use the same 

primary and secondary sampling units as 

NHANES during 2012.

The specific NHANES sample 

designs, including specifications 

for clustering, stratification, and 

oversampling population subgroups, 

have changed over time. Since 1999, the 

principal sample design has consisted of 

multiyear, stratified, clustered four-stage 

samples, with 2-year data releases. The 

sample design for NHANES 2011–2014 

is fully described in the “National Health 

and Nutrition Examnation Survey: 

Sample Design, 2011–2014” (1). Designs 

for earlier continuous NHANES are 

described in previous reports (2,3). 

Two key changes in the design of 

NHANES 2011–2014 compared with 

NHANES 2007–2010 were the addition 

of an oversample of non-Hispanic Asian 

persons and the use of state-level health 

rankings to form sampling strata.

“The National Health and Nutrition 

Examination Survey: Estimation 

Procedures, 2007–2010” (4) describes 

the methods that were used to construct 

sample weights and variance units for 

NHANES 2007–2010. It also provides 

information for the user on combining 

survey cycles, sample weights for 

subsamples, and using the strata and 

primary sampling unit information 

(variance units) provided on public-use 

files for variance estimation. Additional 

information for conducting data analysis 

can be found in the NHANES analytic 

guidelines (5).

This report describes the 

construction of sample weights and 

variance units for NHANES 2011–2014, 

updating the NHANES 2007–2010 

estimation procedures. The “Sample 

Design Summary” section summarizes 

the sample design specifications for 

NHANES 2011–2014. The “Weighting 

the Sample Data” section describes 

the creation of sample weights for 

the NHANES 2011–2014 sample 

and subsamples, with a focus on how 

NHANES 2011–2014 sample design 

features affect the sample weights. 

The “Variance Estimation” section 

describes the variance units on the 

National Health and Nutrition 

Examination Survey: Estimation 

Procedures, 2011–2014

by Te-Ching Chen, Ph.D., and Jennifer D. Parker, Ph.D., National 

Center for Health Statistics; Jason Clark, M.S., Westat; and Hee-Choon 

Shin, Ph.D., Jennifer R. Rammon, M.S., and Vicki L. Burt, Sc.M., R.N., 

National Center for Health Statistics

Background

The purpose of the National Health 

and Nutrition Examination Survey 

(NHANES) is to produce national 

estimates representative of the total 

noninstitutionalized civilian U.S. 

population. The sample for NHANES 

is selected using a complex, fourstage sample design. NHANES 

sample weights are used by analysts 

to produce estimates of the healthrelated statistics that would have 

been obtained if the entire sampling 

frame (i.e., the noninstitutionalized 

civilian U.S. population) had been 

surveyed.

Sampling errors should be 

calculated for all survey estimates 

to aid in determining their statistical 

reliability. For complex sample 

surveys, exact mathematical 

formulas for variance estimates 

that fully incorporate the sample 

design are usually not available. 

Variance approximation procedures 

are required in order to provide 

reasonable, approximately unbiased, 

and design-consistent estimates of 

variance.

Objective 

This report describes the methods 

used to create NHANES 2011–2014 

sample weights and variance units for 

the public-use data files, including 

sample weights for selected 

subsamples, such as the fasting 

subsample. The impacts of sample 

design changes on estimation for 

NHANES 2011–2014 and the addition 

of the NHANES National Youth Fitness 

Survey (NNYFS) 2012 are described. 

Approaches that data users can 

employ to modify sample weights 

when combining survey cycles or 

when combining subsamples are also 

included.

Keywords: sampling • weighting •

variance estimation • mobile 

examination center (MEC) 

Abstract
Page 2  Series 2, No. 177

public-use data files and appropriate 

variance estimation methods for analysis. 

Appendix I provides a glossary of 

terms and Appendix II contains tables 

of supporting material. For additional 

information regarding the calculation of 

NHANES sample weights, please refer 

to the NHANES 2007–2010 Estimation 

Procedures (4).

Additional documentation of 

the survey content, data collection 

procedures, and methods for assessing 

nonsampling errors is provided elsewhere 

(see https://www.cdc.gov/nchs/nhanes.

htm).

Sample Design 

Summary

The NHANES sample represents the 

noninstitutionalized civilian population 

residing in the 50 states and the District 

of Columbia. Since 1999, the sample 

design has consisted of multiyear, 

stratified, clustered four-stage samples, 

with 2-year data releases. The NHANES 

sample is drawn in four stages: primary 

sampling units (PSUs, counties or 

combinations of adjacent counties), 

segments within PSUs (census blocks or 

combinations of blocks), dwelling units 

(DUs, households) within segments, and 

individuals within households. PSUs are 

sampled from all U.S. counties.

The population subgroups chosen 

for oversampling directly determine 

the sampling domains used to select 

the sample at all stages. The specific 

NHANES sample designs, including 

specifications for clustering, stratification, 

and oversampling population subgroups, 

have changed over time. The set of 

domains for which specified reliability 

was desired in NHANES 2011–2014 

consisted of sex-age groups for Hispanic 

persons, non-Hispanic black persons and 

non-Hispanic non-black Asian (referred 

to as NH Asian) persons, and incomesex-age groups for the remainder of 

the U.S. population. Specifically, the 

oversampled subgroups in the 2011–2014 

survey were:

1. Hispanic persons

2. Non-Hispanic black persons

3. Non-Hispanic, non-black Asian 

persons

4. Non-Hispanic white persons and 

persons of other races and ethnicities 

at or below 130 percent of the federal 

poverty level

5. Non-Hispanic white persons and 

persons of other races and ethnicities 

aged 80 and over.

Race and Hispanic-origin domains 

used in the sample design and sample 

weight creation differ from the categories 

used in variables on publicly released 

data files (e.g., RIDRETH3 and 

RIDRETH1 for NHANES 2011–2014). 

Race and Hispanic-origin information 

used for sampling is based on census 

population estimates and obtained from 

the household screener to determine 

eligibility for inclusion in the survey. 

The released race and Hispanic-origin 

variable is based on survey response. In 

addition to response differences between 

screening (provided by the household 

reference person) and interview 

(provided by the sampled person [SP] or 

proxy), the released variable RIDRETH3 

includes only single-race categories 

for the non-Hispanic white, black, and 

Asian groups, with all SPs reporting 

multi-race groups coded into the “other 

races, including multiracial” category. 

In contrast, when collecting race and 

ethnicity information at screening for 

NHANES 2011–2014, the black category 

included persons reporting non-Hispanic 

black as a single race or in combination 

with other races, including Asian, and 

the Asian screening category included 

non-Hispanic Asian persons as a single 

race and in combination with other races, 

except black.

Table lists the set of sampling 

domains in NHANES 2011–2014. 

Although data are released in 2-year 

cycles, at least 4 years of data must be 

combined to obtain an acceptable level 

of reliability for most of the sampling 

domains given in Table. To create 

estimates for 2-year samples, domains 

must be collapsed to produce adequate 

sample sizes for analysis.

NHANES PSUs are selected with 

probabilities proportionate to size (PPS), 

where each PSU’s measure of size (MOS) 

is determined by criteria established in 

advance for obtaining health estimates for 

subgroups determined by age group, sex, 

race and Hispanic origin, and income. 

The MOS is a weighted average of 

population counts, where the “weights” 

are calculated to give relatively higher 

probabilities of selection to PSUs with 

higher proportions of individuals within 

the subgroups chosen for oversampling. 

For NHANES 2011–2014, the MOS 

“weights” were calculated to give 

relatively higher probabilities of selection 

to PSUs with higher proportions of black, 

Hispanic, Asian or low-income white and 

other persons. In comparison, the PSU 

MOS used for NHANES 2007–2010 

gave higher weight to PSUs with higher 

proportions of black, Hispanic, or lowincome white and other persons. The 

sampling rates for each subdomain are 

listed in Table I (Appendix II).

Some counties have a MOS large 

enough that they are selected with 

certainty (certainty PSU, often referred 

to as self-representing or SR). The 

remaining counties are referred to as 

noncertainty PSUs (non-self-representing 

or NSR). The certainty PSUs are 

removed from the county frame prior 

to noncertainty PSU selection. The 

noncertainty PSUs are divided into strata 

prior to selection.

The stratification scheme for 

NHANES 2011–2014, as for NHANES 

2007–2010, included state groups, 

major strata, and minor strata levels. 

Unlike NHANES 2007–2010 where 

state groups were formed using the 

four census regions (Northwest, South, 

Midwest, and West), state groups for 

NHANES 2011–2014 were formed 

using several state-level health-related 

variables: death rate, infant mortality 

rate, percentage of adults with high 

blood pressure, percentage of adults 

overweight or obese, percentage of adults 

with poor nutrition, and percentage of 

adults who smoke; state-level health 

statistics were available from vital 

statistics (6,7) and the Behavioral Risk 

Factor Surveillance System (8,9). There 

were five state groups for NHANES 

2011–2014, including a separate state 

group for California. The NHANES 

2011–2014 design defined California 

as a separate state group because of 
Series 2, No. 177  Page 3 

interest in multiyear estimates for 

California. For detailed information 

about NHANES’ California samples, 

sample weights and analytic issues, 

please see “National Health and Nutrition 

Examination Survey: California and Los 

Angeles County, Estimation Methods and 

Analytic considerations, 1999–2006 and 

2007–2014” (10).

Each of the five state groups had 

two or three major strata for a total of 13 

major strata. There were four minor strata 

in each major stratum for a total of 52 

minor strata. The NHANES 2011–2014 

sample had one noncertainty PSU per 

minor stratum for the 4-year sample and 

two noncertainty PSUs per major stratum 

for each 2-year sample, one each year. 

NHANES 2011–2014 surveyed a total of 

60 PSUs, including 8 certainty PSUs.

For survey operational purposes, the 

sample is designed to have approximately 

equal sample size per PSU. Noncertainty 

PSUs have 24 segments. Certainty PSUs 

may have any number of segments to 

ensure appropriate representation in the 

sample. In addition, some large certainty 

PSUs can be treated as multiple study 

locations with varying numbers of 

segments in each location.

Weighting the Sample 

Data

Weighting of the NHANES data 

produces estimates representative of 

the U.S. noninstitutionalized civilian 

resident population. The weighting of 

sample data permits analysts to produce 

estimates of the statistics that would 

have been obtained if the entire eligible 

population had been surveyed. Sample 

weights can be considered measures 

of the number of persons in the target 

population represented by the particular 

sampled participant. Weighting takes into 

account several features of the survey: 

the differential probabilities of selection 

for the sampling domains, survey 

nonresponse, and differences between the 

final sample distribution and the target 

population distribution. Each of the three 

levels of data collection for NHANES 

(screening, interview, examination) has a 

response rate. As a result, sample weights 

are calculated for each level of data 

collection.

The NHANES sample weighting 

is carried out in three steps. The first 

step involves the computation of stage 

base weights to compensate for unequal 

probabilities of selection. The second 

step adjusts for nonresponse to reduce 

the potential bias. In the third step, the 

sample weights are poststratified to the 

reference population. Poststratification 

is used to compensate for possible 

inadequacies in the eligible population 

and to reduce variances in the estimation 

procedure. The nonresponse and 

poststratification steps are performed at 

each level of data collection: the screener, 

interview, and examination. The new 

weight for each step in the adjustment 

is the product of the weight before the 

adjustment and the adjustment factor of 

the step. 

Adjustment factors are calculated 

within adjustment cells defined by 

characteristics available for both sample 

participants and nonrespondents at that 

step. Because available information 

differs for each step, adjustment cells 

differ for each step.

Calculating Base Weights

The initial weight for each sampled 

participant within a sampling domain is 

the same for all other participants in that 

domain and is equal to the inverse of the 

sampling rate (rk) within the sampling 

domain. For NHANES 2011–2014, the 

initial weights were adjusted to account 

for: 1) the proportion of DUs released 

in a PSU ( fi(release)), 2) the proportion of 

deselected DUs in a PSU ( fi(diesel)), and 

3) the number of years in the sample

 ( fi(year)). At screening, not all DUs 

can be screened and not all of those 

screened include eligible SPs. As a result, 

NHANES’ samples are drawn much 

larger than the target sample sizes to get 

enough eligible persons at the screening 

stage. The first two adjustments account 

for the selection probability for the 

released and deselected DUs.

The three base weight adjustment 

factors are described below. The base 

weights are calculated as the product of 

Table. Sampling subdomains classified by race and Hispanic origin, income, sex, and age: 

National Health and Nutrition Examination Survey, 2011–2014

Non-Hispanic white and other

Sex-age

Non-Hispanic

black Hispanic

Non-Hispanic,

non-black, 

Asian

Non-lowincome Low-income1

Males and females, 

age (years)

Under 1 Under 1 Under 1 Under 1 Under 1

1–2 1–2 1–2 1–2 1–2

3–5 3–5 3–5 3–5 3–5

Males, age (years) 6–11 6–11 6–11 6–11 6–11

12–19 12–19 12–19 12–19 12–19

20–39 20–39 20–39 20–29 20–29

... ... ... 30–39 30–39

40–49 40–49 40–49 40–49 40-49

50–59 50–59 50–59 50–59 50–59

60 and over 60 and over 60 and over 60–69 60–69

... ... ... 70–79 70–79

... ... ... 80 and over 80 and over

Females, age (years) 6–11 6–11 6–11 6–11 6–11

12–19 12–19 12–19 12–19 12–19

20–39 20–39 20–39 20–29 20–29

... ... ... 30–39 30–39

40–49 40–49 40–49 40–49 40–49

50–59 50–59 50–59 50–59 50–59

60 and over 60 and over 60 and over 60–69 60–69

... ... ... 70–79 70–79

... ... ... 80 and over 80 and over

... Category not applicable.

1

Persons living at or below 130% of the federal poverty level.

SOURCE: NCHS, National Health and Nutrition Examination Survey, 2011–2014.
Page 4  Series 2, No. 177

the initial weights and the three 

adjustment factors.

For NHANES 2007–2010, segment 

sizes and probability of housing unit 

selection were increased for years 

2008–2010 to reach the target number 

of identified sampled participants. Base 

weights were also adjusted for this 

increase. For NHANES 2011–2014, the 

segment sizes were not changed after the 

survey began so the additional adjustment 

factor used for NHANES 2007–2010 

(for the increased segment sizes) was not 

needed.

Adjustment for number of 

sampled DUs released to 

the field

In each study location, a larger 

sample than needed is deliberately drawn, 

and smaller subsamples are released for 

screening with the objective of obtaining 

a relatively fixed sample size of 

completed examinations. For NHANES 

2011–2014, the selected sample in each 

study location was 80% more than was 

expected to be needed, but the actual 

sample released varied depending on the 

characteristics of the location. To adjust 

for this approach, a subsample factor is 

calculated for each study location as the 

inverse of the proportion of sampled DUs 

released for screening (Ri). 

Adjustment for deselection of 

released DUs

When the expected number of 

sampled participants from released DUs 

exceeds the target sample size for the 

study location, some of the DUs from the 

released sets that have not been screened 

are randomly deselected to keep the 

sample size near the target. To account 

for the deselection, a deselection factor is 

applied to the remaining DUs that have 

been released but not screened. This 

factor is calculated as the inverse of the 

proportion of released but not screened 

Wi(base) = 1 

rk

( fi(release) fi(desel) fi(year)) [1]

[2]

1

Ri

fi(release) = 

DUs that were not deselected (1 – Di).

Adjustment for number of years 

in the sample

NHANES 2011–2014 is a 4-year 

sample design. Operationally, this means 

that the selected sample of 60 locations 

on which the sampling rates were based 

was implemented over 4 years. Fifteen 

of the locations were allocated to each 

single-year sample, with 30 locations 

included in each 2-year public-use data 

release cycle. Each single-year and 2-year 

sample is nationally representative; 

single-year data are restricted use and 

available from the NCHS Research Data 

Center (RDC).

As a result of the 4-year sample 

design, the initial base weights calculated 

from the original sampling rates 

correspond to 4-year samples. These 

original base weights are based on the 

sampling probabilities and, as a result, 

pertain to the 4-year sample prior to its 

implementation. This means that the 

original base weights sum to a national 

population estimate. To produce weights 

that sum to national population totals for 

single-year and 2-year samples, 

adjustment factors are needed. For 

example, to create the 2-year sample 

weights for NHANES 2011–2012 and 

NHANES 2013–2014 released on the 

public-use files, the 4-year base weights 

were multiplied by two to account for the 

2-year selection (the number of years in 

the design divided by the number of years 

in the sample, 4 / 2 = 2). 

Nonresponse Adjustment

If every selected household was 

screened, and every selected person 

agreed to complete the interview and 

the examination, weighted estimates 

using the base weights described in the 

“Calculating Base Weights” section 

would be approximately unbiased 

estimates of characteristics for the 

noninstitutionalized civilian U.S. 

population. However, some of the 

fi(desel) = 1

1 − Di

[3]

fi(year) = Number of years in sample

4

[4]

selected households are not screened, 

some of the SPs who are screened refuse 

to be interviewed, and some of the 

interviewed sampled participants refuse 

the examination. To reduce the potential 

for nonresponse bias, sample weights 

are adjusted for nonresponse at each 

stage of the survey (screener, interview, 

examination). The amount of information 

that can be used for these adjustments 

increases at each progressive stage; only 

the sampling information is available 

at the screener stage, while personspecific information from the interview is 

available to adjust examination weights.

The nonresponse adjustment 

procedure consists of computing 

adjustment factors, 

and applying these to the survey weights 

as 

wi(NR) = wi(base) fi(NR) [6]

separately within nonresponse cells, 

where nonresponse cells are defined by 

categorical characteristics known for both 

survey participants and nonresponders. 

Since little is known about 

households that do not complete the 

screener, the adjustment cells at the 

screening stage are just the segments, 

with the assumption that households in 

the same segment are similar. For the 

interview and examination nonresponse 

adjustments, a classification program is 

used to identify available variables most 

highly related to response propensity. 

Different variables are identified to form 

adjustment cells for the following age 

groups: 0–5 years, 6–19 years, 20–59 

years, and 60 years and over. Variables 

used to form the nonresponse adjustment 

cells for interview and examination 

weights are listed in Tables II and III in 

Appendix II.

Nonresponse adjustment reduces 

bias if response rates and survey 

characteristics vary from cell to cell and 

if survey participants and nonrespondents 

sharing the same characteristics are in the 

same cell.

[5]

Sum of base weights in 

the adjustment cell

Sum of base weights of 

the respondents in 

the adjustment cell

fi(NR) =
Series 2, No. 177  Page 5 

An effect of nonresponse adjustment 

is that it increases the variability of the 

weights, which in turn increases the 

variance of estimates obtained from the 

data. When the nonresponse adjustment 

cells contain a sufficient number of cases 

and the adjustment factors are not too 

large, the effect on variances is modest. 

A large adjustment factor in a cell is 

usually the result of the small number 

of survey participants in that cell. To 

avoid having nonresponse adjustments 

based on very small sample sizes, or 

having large nonresponse adjustment 

factors, nonresponse adjustment cells 

can be collapsed to form larger cells. As 

with prior NHANES samples, cells with 

fewer than 30 respondents were collapsed 

to create larger cells in NHANES 

2011–2012 and NHANES 2013–2014. 

Due to increasing nonresponse to the 

interview, larger adjustment factors than 

in previous NHANES samples were 

allowed, with most cells having factors 

less than 2. By comparison, for NHANES 

2007–2010, all nonresponse adjustment 

factors were less than 1.65.

Trimming

Weight-trimming procedures are 

considered to reduce the impact of 

any extreme weights on estimation. 

Nonresponse adjustment can contribute 

to extreme weights. Extreme weights 

may also occur when units are sampled 

to yield fixed sample sizes within a PSU. 

Even a few unexpectedly large weights 

can seriously inflate the variance of 

survey estimates. However, trimming 

sample weights may introduce estimation 

bias, so trimming is not automatically 

used for all sample weights. The impacts 

of trimming on both variance and bias are 

considered when deciding whether or not 

to trim weights.

For NHANES 2011–2014, trimming 

was not performed for either the 

NHANES 2011–2012 or the NHANES 

2013–2014 2-year sample weights, but it 

was employed for the NHANES-NNYFS 

2011–2012 sample weights.

To determine whether or not to 

trim weights for samples (or subsets of 

samples), the distribution of weights 

within each sampling domain is 

inspected. A threshold is defined as 

three times the sampling domain mean, 

and extreme weights that exceed this 

threshold are identified. The values of 

these extreme weights are reduced to the 

threshold, and the weights of all cases in 

the sampling domain are adjusted so that 

the sum of the weights in each sampling 

domain equals the corresponding 

weighted sum prior to trimming. 

Trimmed sample weights are 

calculated as follows. Let ti

 be the weight 

after trimming for SP i. It is defined as

Then the trimming factor, fi(TR) , is 

calculated as

where nb is the sample size of the bth

race-Hispanic origin-income-sex-age 

sampling domain and 

wi(TR) = wi(NR) fi(TR). [9]

Poststratification

The final step in the weighting 

procedure for each survey stage is 

poststratification to known population 

totals. Poststratification compensates 

for undercoverage or overcoverage of 

certain demographic groups and for any 

residual differential nonresponse among 

these groups. Poststratification, like 

nonresponse adjustment, is done at the 

screening, interview, and examination 

stages. 

As mentioned above, a participant’s 

sample weight represents the number 

of persons with similar characteristics 

in the target population. The sum of all 

participants’ weights in a race-ethnicityage-sex demographic subgroup could be 

considered as the total number of persons 

NHANES participants represented for 

this particular demographic subgroup. 

Poststratification adjusts the individual 

sample weights so that the sum of the 

sample weights within a demographic 

subgroup equals the population from an 

independent source for that demographic 

subgroup. 

ti = {threshold, otherwise.

w if i(NR), wi(NR) is ≤ threshold [7]

fi(TR) = [8] wi(NR)

ti wi(NR)

ti

∑nb

i = 1

∑nb

i = 1

×

Similar to the adjustment factors for 

earlier steps, poststratification involves 

applying a ratio adjustment to the survey 

weights. In this step, the denominator of 

the adjustment factor for a particular 

demographic subgroup is the sum of the 

nonresponse-adjusted sample weights 

from the nonresponse adjustment step 

within the demographic subgroup, and 

the numerator Nc is the reference 

population control total for the 

demographic subgroup.

The poststratified weights are then 

calculated as 

wi(PS) = wi(NR) fi(PS) [11]

If trimming was performed, the 

poststratification adjustments factor fi(PS)

and poststratification weights wi(PS) were 

calculated from trimmed weights instead 

of nonresponse adjusted weights. 

For NHANES 2011–2012 and 

NHANES 2013–2014, the Census 

Bureau’s 2011 and 2013 1-year American 

Community Survey (ACS) were used, 

respectively, as the source for the 

reference noninstitutionalized civilian 

population totals for each demographic 

subgroup. Though earlier NHANES 

cycles used the Current Population 

Survey (CPS) to obtain population 

control totals (11), beginning in 2011, 

ACS was used to calibrate the weights. 

Since Asian sampling domains were 

introduced in the 2011–2014 sample 

design, ACS was considered to provide 

more accurate NHANES estimates. 

CPS, for example, does not produce 

separate estimates for non-Hispanic 

Asians persons. The ACS population 

counts have been adjusted to match the 

Census Bureau best estimates of the total 

noninstitutionalized civilian population 

of the United States, including those not 

counted in surveys or in the most recent 

decennial census. Poststratification using 

ACS, therefore, brings the weighted 

totals up to the level of the presumed 

total noninstitutionalized civilian 

population in the United States. Detailed 

reports for these two population surveys 

[10]

fi(PS) = Nc

Sum of nonresponse 

adjusted weights of 

the demographic subgroup
Page 6  Series 2, No. 177

are available from the Census Bureau 

website (11,12).

A major effect of poststratification 

is that it implicitly imputes survey 

characteristics for persons missed 

by the survey due to errors in the 

sampling frame and adjusts for residual 

nonresponse not previously corrected. 

The underlying assumption for 

poststratification is that missed persons 

not covered by the survey have the same 

distribution of characteristics as surveyed 

persons within the poststratification 

cells. This assumption is obviously an 

oversimplification; the missed persons 

are likely to be different. However, 

in the absence of information on the 

characteristics of the missed persons, 

poststratification is a technique available 

for reducing bias due to undercoverage 

and residual nonresponse.

Computing Final Weights

The final sample weight for each 

sampled participant at each stage is 

calculated as the product of the base 

weight, the nonresponse adjustment, the 

trimming adjustment (if needed), and the 

poststratification adjustment. That is,

The final screening weight was 

calculated as the product of the base 

weight, the adjustment factors for 

nonresponse, trimming (if needed), and 

poststratification for screen stage. 

The final weights from the screener 

stage are the base weights for the 

interview stage, and the final interview 

weight was calculated as the product of 

the screen weight, adjustment factors of 

nonresponse, trimming (if needed), and 

poststratification for interview stage. 

[12] wi, stage = wi, (base,stage) fi, (NR,stage) 

fi, (TR,stage) fi, (PS,stage)

[13]

wi, screen = wi, base fi, (NR,screen) 

fi, (TR,screen) fi, (PS,screen)

[14] = wi, base fi(NR,screen) 

wi, interview = wi, screen fi, (NR,interview) 

fi,(TR,interview) fi, (PS,interview)

fi, (TR,screen) fi, (PS,screen) 

fi, (NR,interview) fi, (TR,interview) 

fi, (PS,interview)

The final weights from the interview 

stage are the base weights for the MEC 

examination stage, and the final MEC 

examination weight was calculated as the 

product of the interview weight, 

adjustment factors for nonresponse, 

trimming (if needed), and 

poststratification for examine stage. 

and was calculated as

The interview weight should be used 

for analyses of data from the household 

interview only, when no variables from 

the examination are included. The 

examination weights should be used for 

analyses of data from the examination 

(including the MEC interview and some 

laboratory data) or in conjunction with 

the household interview data. In addition, 

there are special survey components 

and subsamples that require further 

adjustment of the examination weights 

due to specific inclusion criteria (e.g., 

morning fasting sample). Componentspecific special weights, if needed, are 

released with the data for the component 

and described in the component’s 

documention. See the “Subsample 

Weights” section for more details and 

Table IV in Appendix II for a list of 

the weights and usages for NHANES 

2011–2014.

NHANES National Youth 

Fitness Survey

In 2012, NCHS also conducted 

the NHANES National Youth Fitness 

Survey (NNYFS) to collect data on 

physical activity and fitness levels 

for U.S. children aged 3–15 years. 

NNYFS was designed to use the same 

primary and secondary sampling units 

as NHANES during 2012, and to 

produce approximately equal sample 

sizes of children aged 3–15 per PSU. 

The segments were enlarged to ensure 

there were enough DUs for both surveys. 

[15] wi, MEC = wi, interview fi, (NR,MEC) 

fi, (TR,MEC) fi, (PS,MEC)

[16]

wi, MEC = wi, base fi, (NR,screen) fi, (TR,screen) 

fi, (PS,screen) fi, (NR,interview) 

fi, (TR,interview) fi, (PS,interview) 

fi(NR,MEC) fi, (TR,MEC) 

fi, (PS,MEC)

NNYFS has six sex-age domains: boys 

aged 3–5 years, girls aged 3–5 years, 

boys aged 6–11 years, girls aged 6–11 

years, boys aged 12–15 years, and girls 

aged 12–15 years. In addition, some 

survey content was collected in the same 

manner in both surveys. Therefore, it 

is possible to combine the samples to 

increase sample sizes for common survey 

content collected in 2012.

Sample weights for the combined 

NHANES-NNYFS 2012 sample 

were created using a composite of the 

sample weights of the two surveys. 

NHANES 2011 was fielded before 

the changes were implemented to 

make NHANES 2012 and NNYFS 

2012 more comparable; therefore, a 

much smaller set of NHANES 2011 

questionnaire and examination items 

are able to be combined with NNYFS 

2012 as compared with NHANES 2012. 

Nevertheless, it is possible to combine 

NNYFS 2012 with NHANES 2011–2012 

for the limited items available for both 

years. Sample weights for the combined 

NHANES-NNYFS 2011–2012 sample 

were created using a composite of the 

sample weights of the two surveys.

The weights for the combined 

sample started with the final interview 

and examination weights for NHANES 

2012 and NNYFS 2012. The initial 

combined survey weights were calculated 

as the final sample weights of each 

survey times the proportion of the 

effective sample size of the combined 

sample for each of six sex-age group 

domains described. The initial combined 

sample weights were poststratified 

as described in the “Postratification” 

section, with the denominators equal to 

the sum of the initial combined weights.

To produce sample weights for the 

combined NHANES-NNYFS 2011–2012 

sample, the sample weights for NHANES 

2011 and the final combined sample 

weights for the NHANES-NNYFS 2012 

were divided by 2. The weights for the 

combined sample were then reviewed 

and trimmed of extreme weights. After 

trimming, the interview and examination 

weights for the combined sample were 

poststratified to population totals from the 

2011 ACS.
Series 2, No. 177  Page 7 

Data from the NNYFS 2012 sample 

are released to the public. Data from 

either of the combined files are available 

only through the NCHS RDC 

(https://www.cdc.gov/rdc/). See 

“Restricted Data Access in the NCHS 

Research Data Center” section for 

detailed information on accessing 

restricted data. See the NNYFS website 

for specific information about NNYFS 

restricted data files (available from: 

https://wwwn.cdc.gov/nchs/nhanes/

search/nnyfsdata.aspx?Component=NonPublic). For more detailed information 

on the combined NHANES-NNYFS 

weights, see “National Health and 

Nutrition Examination Survey: National 

Youth Fitness Survey Estimation 

Procedures, 2012” (https://www.cdc.gov/

nchs/data/series/sr_02/sr02_168.pdf). 

For more information on the NNYFS 

survey design, implementation, and data 

analysis, and the combined NHANES 

2011–2012 and NNYFS 2012 sample, 

see “National Health and Nutrition 

Examination Survey: National Youth 

Fitness Survey Plan, Operations, and 

Analysis, 2012” (13).

Subsample Weights

Some laboratory or examination 

components are done on a subsample 

of NHANES participants. For example, 

some but not all participants aged 12 

years and over are selected to give blood 

samples for testing for lead and mercury 

in blood. The subsamples selected for 

these components are chosen at random 

with a specified sampling fraction (e.g., 

one-half of this examined age group), 

according to the protocol for that 

component. Each subsample is selected 

to be a nationally representative sample 

of the target population and has its 

own designated sample weight, which 

accounts for the additional probability of 

selection into the subsample component, 

as well as any additional nonresponse to 

the component.

These subsample weights are 

included in the respective data files. 

Because these weights differ from the 

examination weights, subsample weights 

must be used for statistical estimation of 

measures collected only in that sample 

and for analyses that include those 

measures (see Table IV in Appendix II

for a list of special component sample 

weights and information regarding their 

appropriate use). See the respective 

survey protocol and documentation 

for more detail on the laboratory tests 

or health measurements done on a 

subsample of participants (available 

from: https://www.cdc.gov/nchs/nhanes.

htm).

There are caveats when trying 

to combine data sets with subsample 

weights. Some subsamples, like the three 

environmental subsamples, are mutually 

exclusive and cannot be combined 

together in the same data release cycle 

or across cycles, since weights are not 

available for each group. On the other 

hand, certain combinations of subsamples 

have some overlap, for example, each 

of the three environmental subsamples 

has overlap with the fasting subsample. 

These could be combined within the 

same data release cycle. These could 

also be combined across cycles if the 

overlapping sample is adequate, and there 

are no differences in the estimates across 

the cycles. However, NHANES does 

not provide sample weights for these 

combined data sets.

To combine two or more subsamples 

for analysis, random overlap is needed 

between the subsamples and appropriate 

weights need to be recalculated. While 

there are no specific recommendations 

regarding how to create combined sample 

weights for overlapping subsamples, 

there are calibration approaches to 

adjusting weights available within the 

SUDAAN software, with the procedures 

WTADJUST and WTADJX (14,15). 

Adjustments to create sample weights 

for overlapping subsamples can be 

made by adjusting the sample weights 

to match population totals within 

adjustment cells defined by race and 

Hispanic origin, sex, and age group, 

demographic characteristics present in 

both subsamples. Additional adjustments 

specific to the analysis may also be made 

to the sample weights using characterstics 

common to both subsamples. The 

selection and categorization of the 

variables used for adjustment will depend 

on the size of the combined sample and 

the purpose of the analysis. Since the 

overlapping subsamples are typically 

small, coarser adjustment cells than those 

used for the original sample weights 

creation are often required.

Note that sample weight adjustments 

using the public-use data files would 

use one of the released race and 

Hispanic-origin variables (RIDRETH3 

or RIDRETH1) available on the file for 

the calculations. As described earlier, 

sample weights created by NCHS use the 

sampling race and ethnicity information.

Although 24-hour dietary recall is 

not considered a subsample, participants 

who completed this component have 

special weights that incorporate day 

of the week of recall. If an analyst is 

interested in combining this file with 

a subsample and interested in how 

day-to-day variation in diet relates to 

the information in the subsample, new 

weights need to be created. Weights could 

be calculated by starting with the dietary 

weights and adjusting for subsample 

participation. If day-to-day variation in 

diet is not analytically important, the 

subsample weights could be used without 

adjustment.

Combining Survey Cycles

Two-year sample weights are 

provided on public-use files for 

NHANES 2011–2012 and 2013–2014. To 

combine these cycles to produce 4-year 

estimates, a new 4-year weight can be 

calculated by dividing the 2-year weights 

by 2, the number of 2-year cycles. Sixyear weights can similarly be created 

for 2009–2014 estimates, or any three 

combined survey cycles for 2001–2002 

or later, by dividing the 2-year weights 

for each cycle by 3. Other years of data 

can continue to be added, using these 

same methods. When 1999–2000 data are 

included, first double the 4-year weights 

for 1999–2002, then divide all the 

weights by the number of 2-year cycles. 

However, as a result of sample 

design changes initiated in 2011, it is 

important to consider changes in race 

and Hispanic-origin sampling and the 

corresponding variables on the publicuse files when calculating estimates 

based on data from combined cycles 
Page 8  Series 2, No. 177

that overlap 2011, such as the 6-year 

period 2009–2014. RIDRETH3 was 

created to account for the non-Hispanic 

Asian category starting in 2011 and 

is not available on public-use files for 

earlier cycles. Prior to 2011, Asian 

participants were grouped in the “nonHispanic white and other” category for 

sampling and the “other race, including 

multiracial” race category for race and 

Hispanic-origin variables on public-use 

files. Therefore, for combined data sets 

that use cycles prior to and after 2011, 

non-Hispanic Asian cannot be a separate 

race and Hispanic-origin category and 

participants in this group should be 

added to the “Other” category. Similarly, 

estimates from combined cycles should 

only be made for the total Hispanic 

subgroup from 2007 onward. Additional 

information for race and Hispanic-origin 

changes over time and combining sample 

weights can be found in the NHANES 

analytic guidelines (5).

When adjusting the sample weights 

to combine data for multiple survey 

cycles, the sum of combined weights will 

be reasonably close to an independent 

estimate of the U.S. noninstitutionalized 

civilian population at the midpoint of 

the combined interval. The estimate 

from combined years of data will be 

the average over the time period. Using 

multiple cycles to create combined 

estimates is useful for increasing sample 

sizes, particularly for analysis of rare 

events and small subgroups. However, 

estimation using combined cycles is 

based on the assumption that there are no 

differences in the estimates across cycles, 

including increasing or decreasing trends, 

other than observed differences due to 

random variation.

Variance Estimation

This section introduces designbased methods of variance estimation 

for complex sample survey data and 

describes the creation of variables 

necessary for variance estimation on the 

public- and restricted-use data files for 

the NHANES 2011–2014 samples.

Sampling errors should be calculated 

for all survey estimates to aid in 

determining the statistical reliability of 

those estimates. For complex sample 

surveys, exact mathematical formulas 

for variance estimates are not available. 

Variance approximation procedures 

are necessary to provide reasonable, 

approximately unbiased, and designconsistent estimates of variance. These 

routines require special software that 

account for the survey design. Standard 

statistical software routines that assume 

a simple random sample should not 

be used for computing variances for 

NHANES. Although each 2-year sample 

is nationally representative, it is selected 

from only 30 PSUs.

This small number of PSUs 

sometimes poses challenges for variance 

estimation. First, the sample sizes for 

some specific race-Hispanic originincome-sex-age subdomains may be 

small. Second, with a small number 

of PSUs, direct design-based variance 

estimates may be unstable for some 

measures.

Two variance approximation 

procedures that account for the 

complex sample design and allow for 

the computation of design effects are 

replication methods and Taylor series 

linearization. Replication methods 

provide a general means for estimating 

variances for the types of complex 

sample designs and weighting procedures 

usually encountered in practice. The basic 

idea behind the replication approach is 

to select subsamples repeatedly from the 

whole sample, to calculate the statistic 

of interest for each of these subsamples 

(or “replicates”), and then to use the 

variability among these replicate statistics 

to estimate the variance of the fullsample statistic. The jackknife and Fay’s 

adjusted balanced repeated replication 

(Fay’s BRR) methods are two common 

procedures for deriving replicates from 

a full sample. The jackknife procedure 

drops a small part of the sample in each 

replicate and adjusts the weights for the 

sample that is retained. Fay’s BRR retains 

the entire sample in each replicate, but 

adjusts the weights so that part of the 

sample has increased weights and part of 

the sample has decreased weights (16).

For the linearization approach, 

nonlinear estimates are approximated 

by linear estimates for the purpose 

of variance estimation. The linear 

approximation is derived by taking the 

first-order Taylor series approximation 

for the estimator. Standard variance 

estimation methods for linear statistics 

are then used to estimate the variance 

of the linearized estimator. Currently, 

NCHS recommends using Taylor series 

linearization for variance estimation in 

analyses of NHANES data for 2-year 

cycles or combined cycles and replication 

methods for single-year data. Replication 

methods are also recommended for use 

with the California NHANES data files 

(10). SUDAAN, Stata, R, and SAS 

survey procedures can be used to obtain 

variance estimates by these methods.

Variance Units for Publicly 

Released Data

Noncertainty PSUs are grouped 

into major strata defined by state-level 

health-related variables as discussed 

in the “Sample Design Summary” 

section. In any 2-year sample there are 

two PSUs sampled from each stratum. 

These strata are used as variance strata 

to estimate sampling error in the Taylor 

series linearization approach. Within each 

variance stratum, the two sampled PSUs 

are generally defined as variance units. 

Certainty PSUs are not selected within 

strata. Variance strata for these PSUs are 

formed based on the relative size of the 

PSU compared with the other PSUs. As 

a result, some of these variance strata 

may have one PSU split into multiple 

variance units, while other variance strata 

may comprise three PSUs for variance 

estimation, depending on the number and 

size of the certainty locations that year.

The small number of PSUs in a 

2-year NHANES sample, geographic 

data and other characteristics of the 

geographic area on the data files, as 

well as local publicity campaigns while 

the survey is in the field, all pose a 

risk for data disclosure. As a result, 

masked variance units (MVUs) are 

provided for use with the public-use 

data files to reduce the chance of an 

intruder being able to match PSUs in 

the sample to PSUs in the geographic 

areas, while minimizing the bias in the 
Series 2, No. 177  Page 9 

variance caused by altering the PSU 

structure. Collectively, MVUs (pseudoPSUs) formed by the noncertainty and 

certainty locations can be used for 

variance estimations and to estimate 

sampling error. Though they are not the 

“true” design PSUs, the pseudo-PSUs 

produce variance estimates that closely 

approximate the variances that would 

have been estimated using the true design 

PSUs. MVUs have been created for all 

2-year survey cycles from NHANES 

1999–2000 through 2013–2014 and can 

be used for analyzing any 2-year data set 

or any combined 4- to 16-year data set. 

Analysts can compute replicate weights 

for variance estimation based on MVUs.

Restricted Data Access in 

the NCHS Research Data 

Center

For the current sample design, 

NHANES data are released to the public 

in 2-year data cycles. In addition to 

public-use data files, there are special 

data sets that are available only through 

the NCHS RDC. These include data sets 

with (a) data items that were collected 

from a single-year sample or collected 

for any time period other than a publicrelease 2-year cycle (identified as such 

in the component description, e.g., the 

single-year 24-hour urine data [17]), (b) 

data merged geographically to some other 

contextual data files (often supplied by 

the data user), and (c) data items that 

are determined to be too sensitive or too 

detailed to be released to the public due 

to confidentiality restrictions. NHANES 

data linked with administrative data (e.g., 

Medicare, Medicaid or Children’s Health 

Insurance Program, and Social Security 

Adminisitration data) are only available 

in the RDC.

Some of these data files have 

special sample weights that should be 

used when these nonpublic data sets 

are analyzed within the confines of the 

RDC environment. For example, single 

calendar-year data files have single-year 

interview and examination weights. 

These single-year sample weights can be 

combined with sample weights provided 

on the 2-year public-use file to create 

3-year sample weights. All single-year 

sample weights were calculated in 

the same manner as the public-use 

2-year sample weights described in the 

“Weighting the Sample Data” section. 

If a special data file involves 

subsampling, then special subsample 

weights were created for that file that 

reflect the number of calendar years in 

the data file and the rate of subsampling. 

For all special data files, appropriate 

documentation is provided in the RDC to 

describe the necessary sample weights.

Unmasked PSU and variance stratum 

codes (which differ from the MVU codes 

provided for the public-use files) can 

be provided for variance estimation for 

restricted data files in the RDC. These 

unmasked variance codes are necessary 

for studies that use geographically 

defined variables or for studies that 

geographically merge NHANES with 

external data sets. In addition, Fay’s BRR 

weights for 2-year data and jackknife 

weights for single-year data with 

unmasked variance units are available in 

the RDC. If replication methods are to be 

used for combined survey years or cycles 

with unmasked variance units, replicate 

weights must be computed by the analyst 

in the RDC. Providing the unmasked 

PSU and stratum codes poses no 

disclosure risk because of the restrictions 

of the RDC. Further, any subnational 

estimate that is generated from an 

RDC analysis must be reviewed and 

approved by NCHS staff to protect the 

confidentiality of sampled participants.

More information on the RDC 

and lists of commonly used restricted 

NHANES data files and variables are 

available from the NCHS website 

at: https://www.cdc.gov/rdc/. Other 

restricted variables not listed here may 

be available upon request. Information 

on proposals for use of stored specimens 

is available from: https://www.cdc.gov/

nchs/nhanes/biospecimens/biospecimens.

htm.

Summary

This report describes the methods 

used to create NHANES 2011–2014 

sample weights and variance units for the 

public use data files, including sample 

weights for selected subsamples, such 

as the fasting subsample. The impacts of 

sample design changes on estimation for 

NHANES 2011–2014 and the addition 

of the NNYFS 2012 are described. 

Approaches that data users can employ to 

modify sample weights when combining 

survey cycles or when combining 

subsamples are also included.

References

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VL, Mohadjer LK. National Health 

and Nutrition Examination Survey: 

Sample design, 2011–2014. National 

Center for Health Statistics. Vital 

Health Stat 2(162). 2014. Available 

from: https://www.cdc.gov/nchs/

data/series/sr_02/sr02_162.pdf.

2. Curtin LR, Mohadjer LK, 

Dohrmann SM, Montaquila JM, 

Kruszon-Moran D, Mirel LB, et al. 

The National Health and Nutrition 

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Dohrmann SM, Curtin LR. National 

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VL. National Health and Nutrition 

Examination Survey: California and 

Los Angeles County, estimation 

methods and analytic considerations, 

1999–2006 and 2007–2014. National 

Center for Health Statistics. Vital 

Health Stat 2(173). 2017. Available 

from: https://www.cdc.gov/nchs/

data/series/sr_02/sr02_173.pdf.

11. U.S. Census Bureau. Current 

population survey design and 

methodology technical paper (66). 

2006. Available from: 

https://www.census.gov/

prod/2006pubs/tp-66.pdf.

12. U.S. Census Bureau. Design 

and methodology American 

Community Survey. 2009. Available 

from: https://www.census.gov/

content/dam/Census/library/

publications/2010/acs/acs_design_

methodology.pdf.

13. Borrud L, Chiappa M, Burt V, 

Gahche J, Zipf G, Dohrmann SM, 

Johnson CL. National Health and 

Nutrition Examination Survey: 

National Youth Fitness Survey plan, 

operations, and analysis, 2012. 

National Center for Health Statistics. 

Vital Health Stat 2(163). 2014. 

Available from: https://www.cdc.

gov/nchs/data/series/sr_02/sr02_163.

pdf.

14. Brown GG. Survey weight 

adjustment using PROC 

WTADJUST from SUDAAN V10. 

In: American Association for Public 

Opinion Research 2010 conference.

Available from: https://www.rti.org/

sites/default/files/resources/aapor10_

brown_poster.pdf.

15. RTI International. SUDAAN 

(Release 11.1) [computer software]. 

2017. Available from: 

http://sudaansupport.rti.org/sudaan/

page.cfm?obj=A4FF532B-5056-

B100-31D5BDEAEF4181A2.

16. Judkins DR. Fay’s method for 

variance estimation. J Off Stat 

6(3):223–39. 1990.

17. National Center for Health Statistics. 

National Health and Nutrition 

Examination Survey 2014–2014 

data documentation, codebook, 

and frequencies. 24-Hour urine 

collection data processing—First 

collection. Available from: 

https://wwwn.cdc.gov/Nchs/Nhanes/

limited_access/UR1_H_R.htm.
Series 2, No. 177  Page 11 

Appendix I. Glossary

Demographic subgroup—A 

demographic group defined by race and 

Hispanic origin, age, and sex, which 

might be a single or a combination of 

multiple sample domains. 

Domain—A demographic group 

of analytic interest (analytic domain). 

Analytic domains may also be sampling 

domains if a sample design is created 

to meet goals for those specific 

demographic groups. For the National 

Health and Nutrition Examination 

Survey (NHANES), sampling domains 

are defined by race and Hispanic origin, 

income, age, and sex. See Sampling 

domain. 

Dwelling unit (DU)—Also "housing 

unit." A house, apartment, mobile home 

or trailer, group of rooms, or single room 

occupied as separate living quarters or, 

if vacant, intended for occupancy as 

separate living quarters. Separate living 

quarters are those in which the occupants 

live separately from other individuals in 

the building and which have direct access 

from outside the building or through a 

common hall. In this report, the term 

generally means those DUs that are 

eligible for the survey (i.e., excluding 

institutional group quarters), or that could 

become eligible (e.g., vacant at the time 

of sampling, but could be occupied once 

screening begins). 

Household—All the persons who 

occupy a housing unit as their usual place 

of residence. 

Masked variance units (MVUs)—A 

collection of secondary sampling units 

aggregated into groups for the purpose 

of variance estimation and designed 

to prevent disclosure of the identity of 

the selected primary sampling units 

(PSUs). For NHANES, rather than 

using the units as sampled, some pseudo 

units are created. The resulting units 

produce variance estimates that closely 

approximate the "true" design variance 

estimates. MVUs have been created for 

all 2-year survey cycles from NHANES 

1999–2000 through 2013–2014. They can 

also be used for analyzing any combined 

4-, 6-, or 8-year data set.

Measure of size (MOS)—A value 

assigned to every sampling unit in a 

sample selection, usually a count of 

units associated with the elements to 

be selected. For NHANES, the MOS 

is actually a weighted average of 

estimates of population counts for the 

race-Hispanic-origin-income groups of 

interest.

National Center for Health Statistics 

(NCHS)—As the nation’s principal 

health statistics agency, NCHS designs, 

develops, and maintains a number of 

systems that produce data related to 

demographic and health concerns. These 

include data on registered births and 

deaths collected through the National 

Vital Statistics System, and data collected 

by the National Health Interview Survey, 

NHANES, the National Health Care 

Surveys, and the National Survey of 

Family Growth, among others. NCHS is 

part of the Centers for Disease Control 

and Prevention, an operating division 

of the U.S. Department of Health and 

Human Services. 

Noninstitutionalized civilian 

population—Includes all people living 

in households and noninstitutional group 

quarters who are not active members of 

the military. This is the target population 

for NHANES. 

Primary sampling unit (PSU)—The 

first-stage selection unit in a multistage 

area probability sample. In NHANES, 

PSUs are counties or groups of counties 

in the United States. Some PSUs are 

so large that they are selected into the 

survey with a probability of one. These 

are referred to as PSUs selected with 

certainty ("certainty PSUs" or often 

referred to as self-representing PSU 

[SR PSU]); all other PSUs are selected 

without certainty (noncertainty PSUs 

[NSR PSU]). 

Probability proportionate to size 

(PPS) sampling—In this method, the 

probability of selecting any unit varies 

with the size of the unit, giving larger 

units a greater probability of selection 

and smaller units a lower probability. 

NHANES uses PPS sampling in the 

selection of PSUs and Secondary 

sampling unit (SSUs).

Public-use data file—An electronic 

data set containing respondent records 

from a survey with a subset of variables 

collected in the survey that have been 

reviewed by analysts within NCHS to 

ensure that respondent identities are 

protected. NCHS disseminates these files 

to encourage public use of the survey 

data.

Race and Hispanic origin—Unless 

otherwise specified, the phrase (race and 

Hispanic origin) in this report is used as 

it was used in NHANES sample selection 

and sample weight construction. It refers 

to Hispanic, non-Hispanic black, nonHispanic, and non-black Asian persons, 

and a fourth group that includes nonHispanic white and all other persons.

Replicates—Subsamples selected 

repeatedly from a sample used in some 

variance estimation approaches. With 

these approaches, the statistic of interest 

is calculated for each subsample, and the 

variability among the replicate statistics 

is used to estimate the variance of the 

full-sample statistic. The jackknife and 

balanced repeated replication (BRR) 

methods are two common procedures for 

the derivation of replicates from a full 

sample. The BRR method was used in 

the creation of replicate weights for most 

of the NHANES 2011–2014 multiyear 

samples. 

Respondent—A person selected into 

a sample who agrees to participate in 

all aspects of the survey. In NHANES, 

persons agreeing to complete the in-home 

interview are considered "interview 

respondents." Persons agreeing to 

complete both the in-home interview and 

an examination in a mobile examination 

center (MEC) are considered "MEC 

respondents." 

Response rate—The number of 

survey respondents divided by the 

number of persons selected into the 

sample. The response rates in this report 

are MEC response rates—calculated 

as the number of people receiving 

examinations in the MEC divided by the 

total number of people sampled. 
Page 12  Series 2, No. 177

Restricted-use data file—An 

electronic data set of survey respondent 

records containing some information 

that may, if released to the public, risk 

disclosing individual survey respondents. 

These data are available only through 

the NCHS Research Data Center. These 

include data sets with (a) data items 

collected from single year); (b) data 

geographically linked to other contextual 

data files (often supplied by the data 

user); or (c) data items determined to be 

too sensitive or too detailed to be released 

to the public due to confidentiality 

restrictions.

Sample weight—The estimated 

number of persons in the target 

population that an NHANES respondent 

represents. For example, if a man in 

the sample represents 12,000 men in 

his race-Hispanic-origin-income-age 

subdomain, then his sample weight is 

12,000. The NHANES sample weights 

were adjusted for different sampling rates 

(of the race-Hispanic-origin-income-sexage groups), different response rates, and 

different coverage rates among persons 

in the sample, so that accurate national 

estimates could be made from the sample. 

The product of all of these adjustments 

is sometimes called the “final” sample 

weight.

Sampling domain—NHANES 2011–

2014 included 87 sampling domains, 

which were defined by race and Hispanic 

origin, income, age, and sex. Every 

person in the NHANES target population 

can be classified into exactly one of the 

87 sampling domains. See Domain. 

Sampling rate—The rate at which a 

unit is selected from a sampling frame. 

For NHANES, the rates required for 

sampling persons in the race-Hispanicorigin-income-sex-age domains were 

designed to achieve the designated 

number of MEC examinations in each of 

those domains. The sampling rates are the 

driving force in all stages of sampling.

Screener—An interview (usually 

short) containing a set of questions asked 

of a household member to determine 

whether the household contains anyone 

eligible for the survey. In NHANES, 

the screener consisted of compiling 

a household roster and collecting the 

income level of the household and the 

race and Hispanic origin, age, and sex 

of all household members. In NHANES, 

only persons aged 18 and over can 

answer the screener.

Screening—The process of 

conducting, or attempting to conduct, 

the screener interview in selected DUs. 

Occupied DUs (households) are screened 

using the screener. Other units can also 

be screened; the process for these units 

is simply verification that they are either 

vacant or not DUs. See Screener.

Secondary sampling unit—The 

second-stage selection unit in a 

multistage area probability sample. For 

NHANES, these are typically referred to 

as “segments;” see Segment.

Segment—A group of housing units 

located near each other, all of which 

were considered for selection into the 

sample. For NHANES, segments consist 

of a census block, or group of blocks, 

and their selection makes up the second 

stage of sampling. Within each segment, 

a sample of DUs was selected. 

Stratification (or strata)—The 

partitioning of a population of sampling 

units into mutually exclusive categories 

(strata). Typically, stratification is used 

to increase the precision of survey 

estimates for subpopulations important 

to the survey's objectives. To select 

the PSUs fielded in 2011–2014, PSUs 

were stratified based on health status, 

metropolitan statistical area status, and 

various population demographics. 

Study location—The set of segments 

within a PSU that were fielded together, 

with all MEC examinations conducted 

at the same physical location. The 

distinction between a PSU and a study 

location is necessary because some large 

certainty PSUs were divided into multiple 

study locations and fielded at different 

times.

Target population—The 

population to be described by estimates 

from the survey. In NHANES, the 

target population is the resident 

noninstitutionalized civilian population 

of the United States, which excludes all 

persons in supervised care or custody 

in institutional settings, all active-duty 

military personnel, active-duty family 

members living overseas, and any other 

persons residing outside the 50 states and 

the District of Columbia. 

Undercoverage—The result of 

failing to include all of the target 

population within the sampling frame. 

Variance—A measure of the 

dispersion of a set of numbers. In this 

report, the variance is specifically the 

sample variance, which is a measure 

of the variation of a statistic, such as a 

proportion or a mean, calculated as a 

function of the sampling design and the 

population parameter being estimated. 

Many common statistical software 

packages compute "population variances" 

by default; these may underestimate the 

sampling variance because they do not 

incorporate any effects of having taken 

a sample instead of collecting data from 

every person in the full population. 

Estimating the variance in NHANES 

requires special statistical software, as 

discussed in this report. 

Variance stratum—The cluster of 

variance units used when forming a 

replicate for variance estimation. For 

NHANES, the PSU sampling strata 

usually correspond to the variance strata. 

Variance unit—A collection of 

secondary sampling units aggregated 

into groups and excluded when forming 

a replicate for variance estimation. 

For NHANES, an entire PSU usually 

corresponds to a variance unit.

Weight—See Sample weight.
Series 2, No. 177  Page 13 

Appendix II. Tables

Table I. Final sampling rates and base weights: National Health and Nutrition Examination Survey, 2011–2014

2011–2012 2013–20141

Race and Hispanic-origin-income-sex-age sampling domain2

Numerator of 

sampling rate3 Base weight

Numerator of 

sampling rate4 Base weight

Non-Hispanic black

Male and female:

Under 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.82 1,748.32 1.00 1,890.34

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.58 2,471.85 0.76 2,471.85

Male:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.58 2,458.66 0.77 2,458.66

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.45 3,159.91 0.60 3,159.91

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.26 5,491.79 0.34 5,491.79

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.31 4,588.14 0.41 4,588.14

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.34 4,201.29 0.45 4,201.29

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.70 2,037.30 0.93 2,037.30

Female:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.62 2,319.15 0.82 2,319.15

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.45 3,212.60 0.59 3,212.60

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.21 6,887.17 0.27 6,887.17

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.25 5,647.05 0.33 5,647.05

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.30 4,740.20 0.40 4,740.20

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.50 2,861.99 0.66 2,861.99

Hispanic

Male and female:

Under 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.98 1,458.48 1.00 1,890.34

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.51 2,829.21 0.68 2,769.02

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.38 3,798.67 0.51 3,678.71

Male:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.37 3,858.13 0.51 3,736.30

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.29 4,870.33 0.41 4,667.40

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.16 8,821.38 0.23 8,197.64

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.19 7,696.97 0.28 6,680.39

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.26 5,460.40 0.38 4,925.07

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.69 2,064.02 0.94 2,020.57

Female:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.38 3,775.37 0.52 3,656.15

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.31 4,619.96 0.43 4,427.46

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.15 9,676.17 0.21 8,902.08

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.18 7,785.45 0.28 6,757.18

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.26 5,539.49 0.38 4,996.40

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.56 2,544.90 0.76 2,491.33

Non-Hispanic, non-black Asian

Male and female:

Under 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

Male:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.44 3,270.54 0.58 3,270.54

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.62 2,295.99 0.82 2,295.99

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.68 2,093.59 0.90 2,093.59

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

Female:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.93 1,540.84 1.00 1,890.34

20–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.47 3,068.76 0.62 3,068.76

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.58 2,449.97 0.77 2,449.97

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.63 2,283.92 0.83 2,283.92

60 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

See footnotes at end of table.
Page 14  Series 2, No. 177

Table I. Final sampling rates and base weights: National Health and Nutrition Examination Survey, 2011–2014—Con.

2011–2012 2013–20141

Race and Hispanic-origin-income-sex-age sampling domain2

Numerator of 

sampling rate3 Base weight

Numerator of 

sampling rate4 Base weight

Non-Hispanic white or other, low-income

Male and female:

Under 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.90 1,589.94 1.00 1,890.34

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.40 3,575.80 0.55 3,464.05

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.32 4,442.21 0.44 4,303.39

Male:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.35 4,058.72 0.48 3,931.88

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.29 4,979.74 0.39 4,824.12

20–29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.23 6,088.01 0.33 5,729.90

30–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.44 3,276.56 0.59 3,177.27

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.34 4,190.58 0.47 4,063.59

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.33 4,276.60 0.46 4,147.01

60–69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.38 3,734.97 0.52 3,621.79

70–79 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.70 2,055.29 0.95 1,993.01

80 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.00 1,430.08 1.00 1,890.34

Female:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.37 3,848.80 0.51 3,728.53

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.27 5,309.69 0.38 4,987.89

20–29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.16 8,770.22 0.24 8,018.48

30–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.26 5,563.59 0.36 5,236.32

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.27 5,261.14 0.38 4,951.67

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.29 4,941.72 0.39 4,791.97

60–69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.26 5,554.53 0.36 5,227.79

70–79 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.35 4,074.04 0.48 3,950.58

80 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.49 2,925.40 0.67 2,836.75

Non-Hispanic white or other, non-low-income

Male and female:

Under 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.38 3,749.62 0.53 3,562.14

1–2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.20 7,201.28 0.29 6,620.53

3–5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.13 11,066.36 0.19 9,704.34

Male:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.13 10,981.69 0.20 9,630.10

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.09 16,419.59 0.14 13,564.01

20–29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.07 19,355.25 0.12 15,538.73

30–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.08 16,858.95 0.14 13,926.96

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.07 19,422.44 0.12 15,592.66

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.06 22,809.90 0.11 17,810.47

60–69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.08 17,190.55 0.13 14,200.89

70–79 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.16 9,218.96 0.23 8,210.64

80 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.33 4,282.86 0.46 4,068.72

Female:

6–11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.13 10,768.92 0.20 9,443.51

12–19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.09 15,367.79 0.15 12,881.82

20–29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.08 18,803.49 0.12 15,311.41

30–39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.08 17,365.14 0.13 14,345.11

40–49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.07 21,833.52 0.11 17,048.09

50–59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.06 24,990.82 0.10 18,993.03

60–69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.09 16,761.14 0.14 13,846.16

70–79 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.16 9,182.40 0.23 8,178.08

80 and over. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.29 4,959.41 0.41 4,634.20

1

Sampling rates for 2013–2014 sample were increased to account for reduced screening amounts.

2

Age in years.

3

Corresponds to a 180% sample; sampling rates may be calculated by dividing the numerator by 1,430.

4

Corresponds to a 180% sample; sampling rates may be calculated by dividing the numerator by 1,890.

SOURCE: NCHS, National Health and Nutrition Examination Survey, 2011–2014.
Series 2, No. 177  Page 15 

Table II. Variables used in forming nonresponse adjustment cells for weighting interview samples: National Health and Nutrition 

Examination Survey, 2011–2014

Order and categories of variables cross-classified to form nonresponse adjustment cells

Variables considered for nonresponse, by age group 2011–2012 2013–2014

0–5 years

Race and ethnicity of sampled person 1. Hispanic, non-Hispanic black, other 6. Hispanic, non-Hispanic black, Asian, other

Urbanicity 2. Urban, suburban, rural ...

Census region 3. Northeast, Midwest, South, West 3. Northeast, Midwest, South, West

Health-based state groups used for sampling strata 4. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

5. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

Household size 5. 1–4, 5–6, 7 or more 4. 1–2, 3–4, 5–6, 7 or more

Tract-level median income (by quartile) ... 1. First quartile, second, third, fourth

Sex of household reference person ... 2. Male, female

6–19 years

Race and ethnicity of sampled person 1. Hispanic, non-Hispanic black, other 1. Hispanic, non-Hispanic black, Asian, other

Urbanicity 2. Nonrural, rural ...

Census region 3. Northeast, all others 7. Northeast, Midwest, South, West

Number of sampled persons in household 4. 1–2, 3, 4, 5 or more 3. 1–4, 5 or more

Sex of household reference person 5. Male, female 8. Male, female

Health-based state groups used for sampling strata 6. Most healthy states including California, 

second-and third-most healthy states, fourthmost

4. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

Household size ... 2. 1–2, 3–4, 5–6, 7 or more

Tract-level percentage of the population aged 25 and over 

with a college education or higher 

... 5. First quartile, second, third, fourth

Tract-level median age ... 6. First quartile, second, third, fourth

20–59 years

Race and ethnicity of sampled person 1. Hispanic, non-Hispanic black, other 5. Hispanic, non-Hispanic black, Asian, other

Urbanicity 2. Urban, nonUrban ...

Census region 3. Midwest, South, other 3. Northeast, Midwest, South, West

Health-based state groups used for sampling strata 4. Most healthy states including California, 

second-and third-most healthy states, fourthmost

4. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

Household size 5. 1–2, 3–4, 5–6, 7 or more ...

Number of sampled persons in household 6. 1–2, 3, 4, 5 or more 2. 1–4, 5 or more

Sex of sampled person 7. Male, female 8. Male, female

Presence of a sampled person under age 16 in household 8. Yes, no ...

Tract-level median income ... 1. First quartile, second, third, fourth

Sex of household reference person ... 6. Male, female

Tract-level percentage of the population born in the United States ... 7. First quartile, second, third, fourth

Number of sampled persons combined with presence of 

a sampled person under age 16 in household 

... 9. One person under age 16, one person aged 16 

and over, more than one person under age 

16, more than one person aged 16 and over, 

mixed ages

Tract-level percentage of the population aged 25 and over 

with a college education or higher 

... 10. First quartile, second, third, fourth

60 years and over

Urbanicity 1. Urban, suburban, rural ...

Race and ethnicity of sampled person 2. Non-Hispanic non-black non-Asian (white), 

other

6. Hispanic, non-Hispanic black, Asian, other

Number of sampled persons in household 3. 1, 2, 3–5, 6 or more 3. 1–2, 3 or more

Household size 4. 1–2, 3 or more ...

Sex of household reference person 5. Male, female ...

Census region 6. Northeast, Midwest, South, West 2. Northeast, Midwest, South, West

Health-based state groups used for sampling strata 7. Most healthy states including California, 

second-and third-most healthy states, 

fourth-most

7. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

Tract-level percentage of the population that is 

Asian alone or in combination 

... 1. First quartile, second, third, fourth

Tract-level percentage of the population aged 25 and over 

with a college education or higher 

... 4. First quartile, second, third, fourth

Tract-level median income ... 5. First quartile, second, third, fourth

... Category not applicable.

SOURCE: NCHS, National Health and Nutrition Examination Survey, 2011–2014.
Page 16  Series 2, No. 177

Table III. Variables used in forming nonresponse adjustment cells for weighting mobile examination center samples: National Health and 

Nutrition Examination Survey, 2011–2014

Order and categories of variables cross-classified to form nonresponse adjustment cells

Variables considered for nonresponse, by age group 2011–2012 2013–2014

0–5 years

Number of sampled persons in household 1. 1, more than 1 ...

Presence of a sampled person over age 16 in household 2. Yes, no ...

Household size 3. 1–4, 5–6, 7 or more ...

Census region ... 1. Northeast, Midwest, South, West

Race and ethnicity of sampled person ... 2. Hispanic, non-Hispanic black, Asian, other

Sex of household reference person ... 3. Male, female

6–19 years

Highest level of education in household 1. Less than high school, high school, more 

than high school

...

Sex of household reference person 2. Male, female ...

Health-based state groups used for sampling strata 3. Most healthy states, California, second-most 

healthy states, third-most, fourth-most

...

Number of sampled persons in household ... 1. 1–3, 4 or more

Home ownership ... 2. Own, rent, some other arrangement

Tract-level median income ... 3. First quartile, second, third, fourth

Tract-level percentage of the population born in the United States ... 4. First quartile, second, third, fourth

20–59 years

Census region 1. Northeast, Midwest, South, West ...

Home ownership 2. Own, other 2. Own, rent, some other arrangement

Number of sampled persons in household 3. 1, more than 1 ...

Presence of a sampled person under age 16 in household 4. Yes, no ...

Highest level of education for sampled person 5. Less than high school, high school, more 

than high school

...

Household size 6. 1–2, 3–4, 5–6, 7 or more ...

Self-reported health 7. Excellent/very good/good, fair/poor ...

Number of sampled persons combined with presence of 

a sampled person under age 16 in household 

... 1. One person under age 16, one person aged 

16 and over, more than one person under 

age 16, more than one person aged 16 and 

over, mixed ages

Highest level of education in household ... 3. Less than high school, high school, more 

than high school

Sex of household reference person ... 4. Male, female

Race and ethnicity of sampled person ... 5. Hispanic, non-Hispanic black, Asian, other

60 years and over

Census region 1. Northeast, Midwest, South, West ...

Highest level of education in household 2. Less than high school, high school, more 

than high school

...

Home ownership ... 1. Own, rent, some other arrangement

Tract-level percentage of the population aged 25 and over 

with a college education or higher 

... 2. First quartile, second, third, fourth

Tract-level median age ... 3. First quartile, second, third, fourth

... Category not applicable.

SOURCE: NCHS, National Health and Nutrition Examination Survey, 2011–2014.
Series 2, No. 177  Page 17 

Table IV. Most common survey samples weights and their appropriate use: National Health and Nutrition Examination Survey, 2011–2014

Sample weights Application Notes

Full samples

Interview weights (WTINT2YR) Use when analyzing data from the home interview only. Do 

not use if the analysis includes variables that were also 

collected on examined persons in the mobile examination 

center (MEC).

Examination weights (WTMEC2YR) Use when analyzing data from the MEC examination. Do 

not use if the analysis includes variables collected as 

part of one of the dietary interviews or part of one of the 

subsamples (e.g., fasting or environmental).

Dietary Day 1 sample weights (WTDRD1) Use when analyzing data from sample with completed Day 

1 24-hour dietary recall or the Flexible Consumer Behavior 

Survey telephone follow-up module.

Instead of adjusting for 7 days of the week in addition 

to race and ethnicity and age groups like in NHANES 

2011–2012, NHANES 2013–2014 Day 1 dietary weights 

were adjusted based on race and ethnicity, age groups, 

and four categories of the day of the week (weekdays, 

Fridays, Saturdays, and Sundays).

Dietary Day 1 and Day 2 completed sample 

(WTDR2D) 

Use when analyzing data from the smaller sample with 2 

days of completed 24-hour dietary recall. 

Dietary 2-day sample weights were adjusted based on race 

and ethnicity, age groups, and Day 1 and Day 2 weekdayweekend categories.

One-half subsamples

Blood metals one-half subsample weights 

(WTSH2YR) 

Use when analyzing blood lead, cadmium, total mercury, 

selenium, and manganese, etc. (blood metals). 

Blood metals one-half subsample weights are only for 

aged 12 and over for 2013–2014. MEC weights should be 

used for children aged 1–11 in 2013–2014 and all ages in 

2011–2012. 

Fasting subsample weights (WTSAF2YR) Use when analyzing the plasma fasting glucose, insulin 

levels, triglycerides, and low-density lipoprotein cholesterol 

(lipids) only for examined persons assigned to and meeting 

the criteria for the fasting subsample.

Fasting subsample weights are for participants aged 12 

and over who were examined in a morning session and 

fasted 8–23 hours. Diagnosed diabetes is a separate 

poststratification category (to the interview weights).

Oral glucose tolerance test (OGTT) 

subsample weights (WTSOG2YR) 

Use when analyzing only OGTT glucose levels or OGTT 

glucose levels with other data such as insulin or fasting 

levels for examined persons assigned to and meeting the 

criteria for the OGTT.

OGTT subsample weights are for participants aged 12 and 

over who were examined in a morning session, fasted 

9–23 hours, and had valid glucose test results, except for 

women stating they were pregnant. Women stating that 

they were not pregnant, but were later determined to be 

pregnant from laboratory results, were eligible and are 

included. Diagnosed diabetics were not given the OGTT, 

but nonpregnant diagnosed diabetics are included in the 

OGTT file with a weight equal to their fasting weight.

Volatile organic compound (VOC) subsample 

weights (WTSVOC2Y) 

Use when analyzing data from volatile organic compound 

one-half laboratory subsample for examined persons 

assigned to and meeting the criteria for this subsample.

VOC subsample weights are for partcipants aged 12 and 

over. For 2013–2014, WTSVOC2Y equals to WTSH2YR 

for participants aged 12 and over.

VOC smoking weights (WTSVS2YR) Use when analyzing the VOC smoking special sample. VOC smoking weights are for participants in the VOC 

subsample plus current smokers. Current smokers 

were identified based on the smoking questions asked 

to all participants aged 20 and over for 2011–2012 and 

participants aged 18 and over for 2013–2014.

See footnotes at end of table.
Page 18  Series 2, No. 177

Table IV. Most common survey samples weights and their appropriate use: National Health and Nutrition Examination Survey, 

2011–2014—Con.

Sample weights Application Notes

One-third subsamples

Environmental chemicals A weights 

(WTSA2YR)

Use when analyzing data from the one-third laboratory 

environmental subsample A for examined persons 

assigned to and meeting the criteria for this subsample.

Environmental subsample A, B, C weights are each for a 

one-third subsample of examined partcipants aged 6 and 

over. Participants are assigned to one of the three mutually 

exclusive one-third environmental subsamples based on 

the sampling scheme. The analytes in each of the three 

subsamples are varied depending on what is included in 

the cycle. The names Subsample A, Subsample B, and 

Subsample C are for convenience and not representative 

of any ordering. The proper subsample weights attached 

in the data set should be used to analyze. As the same 

analytes might be in different subsamples, it is important to 

check the weight.

Environmental chemicals B weights 

(WTSB2YR) 

Use when analyzing data from the one-third laboratory 

environmental subsample B for examined persons 

assigned to and meeting the criteria for this subsample.

See Environmental chemicals A weights.

Environmental chemicals C weights 

(WTSC2YR) 

Use when analyzing data from the one-third laboratory 

environmental subsample C for examined persons 

assigned to and meeting the criteria for this subsample.

See Environmental chemicals A weights.

Smoking weights (WTFSM) Use when analyzing the smoking special sample. These weights apply to the participants in environmental 

chemicals subsample A plus all examined adults who were 

current smokers. Current smokers were identified based 

on the smoking questions asked to all participants aged 20 

and over for 2011–2012, and participants aged 18 and over 

for 2013–2014.

Special single-year sample 

(Research Data Center only)

NHANES-NNYFS 2012 interview weights 

(WTINT) 

Use when analyzing data from the home interview for the 

combined NHANES-NNYFS 2012 sample only.

These weights apply to children aged 3–15 years who 

participated in either NHANES or NNYFS in 2012. 

NHANES-NNYFS 2012 MEC weights 

(WTMEC) 

Use when analyzing data from the MEC examination for 

the combined NHANES-NNYFS 2012 sample only. 

These weights apply to children aged 3–15 years who 

participated in either NHANES or NNYFS in 2012. 

24-hour urine (2014) (WT1YUR) Use when analyzing the 24-hour urine collection sample. These weights apply to a one-half sample from NHANES 

2014 examined adults aged 20–69. Jackknife and Fay’s 

balanced repeated replication weights are also available 

for variance estimations.

NOTES: NHANES is National Health and Nutrition Examination Survey. NNYFS is NHANES National Youth Fitness Survey.

SOURCE: NCHS, National Health and Nutrition Examination Survey, 2011–2014.
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