Adjusting National Health

and Nutrition Examination

Survey Sample Weights for

Women of Childbearing Age

Series 2, Number 157 May 2013
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Parker J, Branum A, Axelrad D, Cohen J. Adjusting National Health and

Nutrition Examination Survey sample weights for women of childbearing age.

National Center for Health Statistics. Vital Health Stat 2(157). 2013.

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Adjusting NHANES sample weights for women of childbearing age.

p. ; cm.— (Vital and health statistics ; Series 2, Data evaluation and methods

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I. National Center for Health Statistics (U.S.) II. Series: Vital and health
 

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DHHS publication ; No. (PHS) 2013–1357. 0276–4733
 

[DNLM: 1. National Health and Nutrition Examination Survey (U.S.) 2.
 

Fertility—United States. 3. Maternal Nutritional Physiological Phenomena—
 

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Series 2, Number 157

Adjusting National Health and

Nutrition Examination Survey

Sample Weights for Women of

Childbearing Age

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

May 2013

DHHS Publication No. 2013–1357
National Center for Health Statistics

Charles J. Rothwell, M.S., Acting Director

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

Office of Analysis and Epidemiology

Irma E. Arispe, Ph.D., Director
Contents
 

Acknowledgment ........................................................................................... v 
 

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

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

Methods .................................................................................................. 2 
 

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 
 

Adjusted Estimates ....................................................................................... 3 
 

Analysis ................................................................................................ 4 
 

Results ................................................................................................... 4 
 

Discussion ................................................................................................ 7 
 

References ................................................................................................ 8 
 

Appendix I. Calculation of Polychlorinated Biphenyls ............................................................ 19 
 

Appendix II. Means or Geometric Means for Variables, by Age Group .............................................. 20 
 

Figures

Figure 1. Means (or geometric means) of nutritional factors for women aged 16–49, by age group: National Health and
 

Nutrition Examination Survey, 1999–2008 (selected years) ......................................................... 5 
 

Figure 2. Geometric means of environmental factors for women aged 16–49, by age group: National Health and Nutrition
 

Examination Survey, 1999–2008 (selected years) ................................................................. 6 
 

Detailed Tables

1.	 Age and race distribution of women aged 16–49, by age group: National Health and Nutrition Examination Survey,
 

1999–2008......................................................................................... 11 
 

2.	 Summary statistics (weighted) for analysis variables for women aged 16–49: National Health and Nutrition
 

Examination Survey, 1999–2008 ....................................................................... 11 
 

3.	 Distribution of original and adjusted sample weight variables (unweighted statistics) for women aged 16–49: National
 

Health and Nutrition Examination Survey, 1999–2008 ..................................................... 12 
 

4.	 Correlations among original and adjusted weight variables (unweighted statistics) for women aged 16–49: National
 

Health and Nutrition Examination Survey, 1999–2008 ..................................................... 12 
 

5.	 Geometric mean and standard error for environmental variables using different adjustment methods for women aged
 

16–49: National Health and Nutrition Examination Survey, 1999–2008........................................ 13 
 

6.	 Mean (or geometric mean) and standard error for nutritional variables using different adjustment methods for women
 

aged 16–49: National Health and Nutrition Examination Survey, 1999–2008 ................................... 14 
 

7.	 Percentiles (95% confidence intervals) for environmental variables using different weight methods for women aged
 

16–49: National Health and Nutrition Examination Survey, 1999–2008........................................ 15 
 

8.	 Percentiles (95% confidence intervals) for nutritional variables using different weight methods for women aged 16–49:
 

National Health and Nutrition Examination Survey, 1999–2008 .............................................. 16 
 

9.	 Mean and standard deviation for environmental variables using different adjustment methods for women aged 16–49,
 

by race and ethnicity: National Health and Nutrition Examination Survey, 1999–2008 ........................... 17 
 

10.	 Mean (or geometric mean) and standard deviation for nutritional variables using different adjustment methods for
 

women aged 16–49, by race and ethnicity: National Health and Nutrition Examination Survey, 1999–2008 .......... 18 
 

iii
Appendix Table

Table. Means or geometric means for variables for women aged 16–49, by age group: National Health and Nutrition
 

Examination Survey, 1999–2008 ....................................................................... 20 
 

iv
Acknowledgment
 

The authors of this report gratefully

acknowledge the computer programming

assistance of Xiang Liu, M.S., of the

National Center for Health Statistics.

v
Background

Maternal risk factors have been

tabulated for women of childbearing age

using defined age ranges. However,

statistics for factors strongly related to age

may be overly influenced by values for the

youngest and oldest women in a range,

because pregnancies are most likely for

ages 20–35.

Objective

This report evaluates adjustment

methods, based on the probability of

pregnancy, for calculating estimates of risk

factors for women of childbearing age.

Methods

Adjusted and unadjusted estimates for

environmental and nutritional variables

were calculated from the 1999–2008

National Health and Nutrition Examination

Survey (NHANES) for women aged

16–49. U.S. births were used to determine

the probability of pregnancy.

Results

Adjusted and unadjusted estimates

differed for some, but not all, examined

variables. More marked differences were

observed for the environmental variables

compared with the nutritional variables.

Adjusted estimates were within about 5%

of the unadjusted estimates for the

nutritional variables. Adjusted geometric

means for lead and mercury were about

7%–10% lower, and for polychlorinated

biphenyl (or PCB) about 25% lower, than

their respective unadjusted geometric

means. With few exceptions, different

adjustment methods led to similar

estimates.

Conclusion

When calculating statistics for women

of childbearing age, the decision to adjust

for age or not to adjust appears to be

more important than the choice of

adjustment method. Although the results

suggest only small differences among

adjustment methods, approaches based

on the NHANES design and sample

weighting methodology may be the most

robust for other applications.

Keywords: NHANES • summary

measures • indicators • direct

adjustment

Adjusting National Health and

Nutrition Examination Survey

Sample Weights for Women of

Childbearing Age

by Jennifer Parker, Ph.D., and Amy Branum, Ph.D., National Center

for Health Statistics; Daniel Axelrad, M.P.P., U.S. Environmental

Protection Agency; and Jonathan Cohen, Ph.D., ICF International

Introduction
 

Conception and healthy pregnancy

depend on the health of the mother.

While studies of pregnant women can

inform their nutritional status and other

exposures, these studies cannot capture

the corresponding health status of those

who are not pregnant at the time of the

study but who may become pregnant in

the future, or those who are having

difficulty becoming pregnant. In

addition, pregnant women as a group

present many ethical and logistical

challenges to traditional medical and

epidemiologic research (1,2).

Furthermore, sample sizes for studies of

pregnant women are much lower than

for studies of women of childbearing

age, affecting statistical precision and

power. Broadening populations of

interest to women of childbearing age

can still yield important information

about various environmental and

nutritional exposures, such as vitamin D

and folate status or body burdens of

mercury and cadmium, and their impact

on pregnancy and birth outcomes. Of

the Healthy People 2020 objectives,

women of childbearing age are a target

population for three indicators related to

family planning (3) and maternal, infant,

and child health (4). A recent U.S.

Environmental Protection Agency (EPA)

report describing potential risks to

children from environmental exposures,

America’s Children and the

Environment (ACE), includes several

indicators of exposures to women of

childbearing age (5).

However, the best approach for

obtaining exposure estimates from

national samples for women of

childbearing age is unknown,

particularly when making estimates

using national complex sample surveys.

The National Health and Nutrition

Examination Survey (NHANES), for

example, collects a wide array of

examination and laboratory information

useful for describing the health of this

group. Among other design features,

NHANES data files include sample

weights for calculating nationally

representative estimates (6). However, to

define women of childbearing age, or

childbearing potential, a standard age

range (often ages 16–49) is typically

chosen. The age-range approach gives

too much ‘‘weight’’ to younger and

older women who are more commonly

represented in the overall population of

U.S. women but who are also less likely

to give birth (7,8). Consequently,

estimates based on this approach will

represent U.S. women within the age

range, but also may be influenced by

high or low values at the beginning or

end of the age range and not necessarily

represent those who are more likely to

give birth. In addition, the resulting

estimates may be sensitive to the choice

of age range—making comparisons

across analyses with different ranges

difficult—and information for women

outside the range is not used.

Page 1
Page 2 [ Series 2, No. 157

A recent journal article by Axelrad

and Cohen (9) described one approach

for handling this issue for calculating

summary statistics from NHANES.

Their objective was to evaluate methods

for producing national exposure

estimates for women of childbearing age

for a selection of the ACE indicators. In

the article, Axelrad and Cohen examined

different methods for estimating risk

factors for women of childbearing age:

a) restricting the age range to include

women more likely to have children,

and b) adjusting the NHANES

public-use sample weights using

national birth rates. They concluded that

adjusting the NHANES public-use

sample weights using birth rates

calculated by single year of age and

race and ethnicity categorized into four

groups (non-Hispanic white, nonHispanic black, Mexican American, all

other races and ethnicities) produced

reasonable estimates. This was the

approach used to calculate exposure

estimates for women of childbearing age

in the most recent ACE report (5).

To extend this work in the context

of national health survey data, two

methods for calculating estimates for

women of childbearing age are

examined using the 1999–2008

NHANES. The first method—

adjustment of the NHANES sample

weights by U.S. birth rates—reweights

the sample weights six ways, including

those used by Axelrad and Cohen (9).

For the second method—direct

standardization—estimates are derived

from the NHANES public-use sample

weights with subsequent adjustments to

standard populations defined by the

number of U.S. births. The directstandardization approach is similar to

the age standardization often used for

comparing health outcomes for two

populations with different age

distributions (10).

This report shows that estimates

calculated using different adjustment

approaches are similar. Although results

are presented for unadjusted estimates

alongside adjusted estimates, this

evaluation was not designed to

determine the conditions under which

adjustment should be done.

Nevertheless, comparisons between

unadjusted and adjusted estimates

indicate that adjustment has more of an

impact for some variables than for

others.

Methods

Data

National Health and Nutrition

Examination Survey

The NHANES program began in

the early 1960s and has been conducted

as a series of surveys focusing on

different population groups or health

topics. In 1999, the survey became a

continuous program that includes an

interview in the household followed by

a physical examination in a mobile

examination center (MEC). NHANES is

a representative cross-sectional sample

of the U.S. civilian noninstitutionalized

population that is selected using a

complex, multistage probability design.

Detailed descriptions of the NHANES

sample designs are available elsewhere

(6). Data for 1999–2008 were used for

this analysis because some of the

variables examined were not available

for later survey releases at the time of

this analysis.

Nationally representative estimates

and standard errors for reported and

measured health variables can be

calculated using the NHANES sample

weights and design variables available

from the survey (6). Different public-use

NHANES sample weights are created

for the sample participating in the

NHANES interview, the sample in the

MEC, and subsamples for some specific

survey elements (e.g., fasting blood

draws). The original NHANES

examination weights are used for this

report. Sample weights for NHANES

participants incorporate adjustments for

unequal selection probabilities and

certain types of nonresponse, as well as

an adjustment to independent estimates

(known as control totals) of population

sizes for specific age, sex, and race and

ethnicity categories. Age categories used

in the control totals covering women of

childbearing age are 16–19, 20–39, and

40–59. Race and ethnicity categories for

control totals for the 1999–2006

NHANES are non-Hispanic black,

Mexican American, and non-Hispanic

white/other (comprising all other races

and ethnicities). For the 2007–2008

NHANES, the race and ethnicity

categories are slightly different:

non-Hispanic black, Hispanic, and

non-Hispanic white/other.

Nutritional and environmental

variables—Several NHANES laboratory

variables were used in this report, many

measured in blood collected as part of

the MEC exam (11). Concentrations of

lead, total mercury, and polychlorinated

biphenyl (PCB) were measured in whole

blood using plasma mass spectrometry.

More detail on specimen collection and

laboratory methods can be found

elsewhere for lead (12), total mercury

(12), and PCB (13). Although

measurement of mercury changed over

the time period, leading to slightly

differing limits of detection (LODs), the

data have been found to be reasonably

comparable across survey releases (14).

The calculation of PCB levels was

based on multiple laboratory

measurements (15) (see Appendix I) and

follows the approach used in ACE (5).

PCB measurements were available for

NHANES 2001–2004; summary

estimates for PCB in this report are

calculated using the examination

weights created for the one-third

subsample. The three environmental

variables of lead, mercury, and PCB

were selected because of their possible

effects on infant outcomes and

childhood neurodevelopmental outcomes

(16–21), and their differing levels by

age (9,21).

Nutritional NHANES laboratory

variables included calcium, folate, iron,

and vitamin D. Iron is measured for

NHANES participants aged 3–5 years

and females aged 12–59 using a timed

end-point method (22). Vitamin D is

measured using a two-step assay

procedure (23). Calcium is measured as

part of the biochemistry profile using

indirect ion-selective electrode

methodology (24). Serum folate was

measured using radioassay (25); because

the type of radioassay changed from

1999–2006 to 2007–2008, serum folate

values are adjusted using a regression

equation provided by NHANES (25). In
Series 2, No. 157 [ Page 3

addition, body mass index [BMI =

height (meters)/weight (kilograms)2] was

analyzed (26). These variables were

chosen, in part, because pregnant

women are encouraged to consume a

threshold of these nutrients and are

monitored for weight and weight gain

throughout pregnancy.

Study population—Women aged 16

to 49 who participated in the MEC

exam in the 1999–2008 surveys were

included (Table 1). Some laboratory

measures were not available for all

years. Vitamin D was measured for

1999–2006, but the data for 2007–2008

were not available at the time of this

analysis. PCB data are available for a

one-third sample of the 2001–2002 and

2003–2004 survey releases; PCB data

from 1999–2000 were not used because

of the high frequency of samples with

values below the LOD. Some measures

were missing for some NHANES

participants (Table 2). No adjustments

for missing values were made.

Birth and population data

Birth data—U.S. natality data for

1999–2008 from the National Center for

Health Statistics (NCHS) were used to

calculate birth rates and to obtain birth

totals for the direct standardization

described below (27). The natality files

contain health and demographic

information on all births that occur in

the United States each year. During

1999–2008, approximately 3.9 million to

4.3 million births occurred annually. Of

the 4.3 million births in 2007, about

25,000 births were to mothers under age

16 (less than 0.6%) and about 500 births

to mothers over age 49 (27).

Population estimates—Civilian

noninstitutionalized population estimates

for females were used from the Current

Population Survey (CPS), estimated at

the midpoint of each NHANES data

release. These are the estimates used to

create the NHANES sample weights; for

details, see http://www.cdc.gov/nchs/

nhanes/response_rates_cps.htm (28).

These estimates are used rather than

total population estimates, which are

usually used to calculate national birth

rates (27), to better align with the

NHANES race and ethnicity domains.

Adjusted Estimates

Adjusted means and standard errors

were calculated two ways, first through

adjustment of the NHANES sample

weights and, secondly, using direct

standardization. Percentiles were

calculated using only the adjusted

sample weights because these estimates

and their standard errors are not readily

calculated using direct standardization.

NHANES sample weight

adjustment

For sample weight adjustment, the

public-use NHANES sample weights

were multiplied by birth rates calculated

for different age-group definitions, race

and ethnicity subgroups, and survey

releases. Weights were adjusted by age

and race and ethnicity because the age

distribution of births differs by race and

ethnicity. To calculate birth rates, age

was used both in single years and

categorized into seven 5-year intervals:

16–19, 20–24, 25–29, 30–34, 35–39,

40–44, and 45–49. Race and ethnicity

were categorized two ways. The first

corresponds to the categorization used

by ACE (5), with four subgroups—

Mexican American, non-Hispanic black,

non-Hispanic white, and all other races

and ethnicities. The second way

corresponds to the NHANES sampling

domains for 1999–2006, with three

subgroups—Mexican American,

non-Hispanic black, and white/other.

Birth rates were estimated by dividing

the number of births to mothers in each

age and race-and-ethnicity category by

the corresponding CPS population

estimate for females in that category.

Birth rates used in the adjustments

were calculated according to the

following six categorizations based on

the definitions above:

1.	 Single year of age

2.	 Five-year age groups

3.	 Single year of age and race and

ethnicity (four subgroups)

4.	 Single year of age and race and

ethnicity (three subgroups)

5.	 Five-year age group and race and

ethnicity (four subgroups)

6.	 Five-year age group and race and

ethnicity (three subgroups)

For each survey respondent, the

adjusted sample weight is the product of

the public-use NHANES examination

sample weight and the birth rate

corresponding to the respondent’s year

of NHANES participation, age, and race

and ethnicity.

Adj weightijkl = (NHANES sample

weightijk) * birth rateijkl

where

i corresponds to each NHANES

data release: 1999–2000,

2001–2002, 2003–2004, 2005–2006,

and 2007–2008;

j indicates age group;

k indicates race and ethnicity;

and

l indicates which of the six methods

above is used.

Direct standardization

For direct standardization, estimated

means and standard errors were

calculated for each age group using the

public-use NHANES examination

sample weights and then combined into

a standardized estimate; as noted,

percentiles and their standard errors are

less readily estimated using this

approach and were not computed. For

comparison, two standardizations were

used: births in four maternal age groups

(under age 20, 20–29, 30–39, and

40–49) and the seven 5-year age groups

(16–19, 20–24, 25–29, 30–34, 35–39,

40–44, and 45–49) detailed earlier. The

overall numbers of births for all years

combined were used for the age

adjustment, rather than for the 2-year

survey releases, for simplicity.

For an estimated mean, the overall

age-standardized mean can be calculated

as the weighted sum of the i age-group

specific means, where the weights

indicate the proportion of births in each

age group i. In applications to NHANES

and other complex surveys, age-group

specific means and variances are

obtained using methods for complex
Page 4 [ Series 2, No. 157

surveys that use the original sample

weights and design information:

_ _ x = wi

xi

The standard error follows:

� _ 2 _ se (x) = wi var (xi

)

Analysis

Before evaluating weighting

methods, the NHANES nutritional and

environmental variables were examined

to determine whether log transformation

would be appropriate. Correlations of

these variables with age were calculated

using the original public-use NHANES

examination weights. Statistical

significance of correlations was

determined using univariate regression

equations accounting for the survey

design, with each NHANES variable as

the outcome (left side) and age as the

predictor (right side) (29).

Adjusted sample weights—Next,

unweighted correlations among the

adjusted sample weights were examined,

and their unweighted summary statistics

(means, variances, and percentiles) were

inspected. Adjusted sample weights were

compared overall and by race and

ethnicity.

Adjusted estimates—Using the two

adjustment approaches described earlier,

summary statistics for the NHANES

variables were examined.

Statistics for calcium and iron were

obtained using the untransformed

variables. Summary statistics for lead,

mercury, PCB, vitamin D, folate, and

BMI were calculated using logtransformed variables to reduce the

effect of the skewness. Geometric means

and standard errors for these variables

are presented after exponentiation of the

log-transformed estimates to ease

comparisons; standard errors for these

variables were calculated using a

standard equation for geometric

variances via the delta method (30).

If ln(y) and se(ln(y)) are the estimated

mean and standard error of the natural

logarithm of Y, then the geometric mean

of Y and its standard error can be

estimated as:

gs = g * se(ln(y))

^ ln(y) g=e

œ ^

SUDAAN (31) and Stata (32)

software were used so that additional

features of the NHANES sample

design—the strata and primary sampling

units or PSUs—could be incorporated in

the estimation along with the adjusted

weights; PROC DESCRIPT (SUDAAN)

was used for direct standardization.

Percentiles were obtained using SAS

computer code used in the ‘‘Fourth

National Report on Human Exposure to

Environmental Chemicals’’ (33).

Comparisons between the

unadjusted and adjusted estimates and

among different adjustment methods

were not tested for statistical

significance because the estimates are

not independent. Consequently,

statements should be considered as

observations rather than as conclusions

of a statistical test.

Results

A total of 9,422 women aged 16–49

were eligible for this analysis (Table 1).

The number of women with data for

each analytic variable, and the weighted

correlation between each analytic

variable and age, are shown in Table 2.

Of the selected NHANES variables, the

weighted correlation between age and

PCB (log scale) was highest (0.65),

followed by the correlations between

age and lead (log scale, 0.32);

correlations between age and mercury

(log scale) and BMI (log scale) were

around 0.20. Calcium, vitamin D, and

iron were negatively correlated with age.

With the exception of folate,

correlations between the analytic

variables and age were statistically

significant (p < 0.05). Figure 1 shows

estimates for the nutrition variables, and

Figure 2 shows estimates for lead, PCB,

and mercury, by age group; the data

table for these figures is in Appendix II.

Table 3 shows unweighted

distributional statistics for the adjusted

sample weights, compared with

corresponding values for the public-use

NHANES examination sample weights.

As expected, the adjusted sample

weights are considerably smaller than

the original sample weights due to

multiplication by the birth rate. The

ranges, approximated by the differences

between the 95th and 5th percentiles,

and variability of the adjusted sample

weights, are relatively greater than those

of the original sample weights. For

example, the median of the original

sample weight is approximately

one-fourth of the corresponding 95th

percentile (about 26,000 compared with

106,000), whereas the medians of the

adjusted weights are about one-tenth of

the corresponding 95th percentiles. The

means of the adjusted weights using the

5- and single-year age adjustments were

similar. For both single- and 5-year age

adjustment, 95th percentiles and

standard deviations of adjusted sample

weights using the three NHANES

race-and-ethnicity categories were about

20% higher than those using four

race-and-ethnicity categories. The 95th

percentiles and standard deviations of

the adjusted weights using single year of

age adjustment were close to the

corresponding statistics using the 5-year

adjustment (within 1%–2%).

Correlations among the adjusted

sample weights were high, greater than

0.95 for all pairwise correlations

(Table 4). The correlations between each

of the adjusted sample weights and the

original sample weight were generally

lower, around 0.55–0.65 (Table 4).

Statistical tests for these correlations

were not done because the adjusted

sample weights are not independent.

Tables 5 and 6 show the weighted

summary statistics for the environmental

and nutritional variables, respectively,

using the different weights and

calculated using direct standardization.

For some variables, statistics using the

original sample weight were different

from those using the adjusted weights.

The effect of adjustment on the
5 

35 

40 

45 

0 

5 

A. Folate	 B. Vitamin D 

30 

25

Nanograms per milliliter 30 

25 

20 

15 

10 

Nanograms per milliliter 20 

15 

10 

5 

0 0 16–19 20–24 25–29 30–34 35–39 40–44 45–49 16–19 20–24 25–29 30–34 35–39 40–44 45–49 

Age group Age group 

NOTE: Estimates are geometric means. NOTE: Estimates are means. 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2001–2008. SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2001–2006. 

C. Body mass index	 D. Calcium 

30 12 

Kilograms per meter2

25 

20 

15 

10 

Milligrams per deciliter 10 

8 

6 

4 

2 

0 16–19 20–24 25–29 30–34 35–39 40–44 45–49 16–19 20–24 25–29 30–34 35–39 40–44 45–49 

Age group 

NOTE: Estimates are geometric means. 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 1999–2008. 

Age group 

NOTE: Estimates are means. 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 1999–2008. 

E. Iron 

80 

Micrograms per deciliter 70 

60 

50 

40 

30 

20 

10 

0 16–19 20–24 25–29 30–34 35–39 40–44 45–49 

Age group 

NOTE: Estimates are geometric means.
 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 1999–2008.
 

Series 2, No. 157 [ Page 5

Figure 1. Means (or geometric means) of nutritional factors for women aged 16–49, by age group: National Health and Nutrition Examination

Survey, 1999–2008 (selected years)
Page 6 [ Series 2, No. 157

environmental variables was more

pronounced than on the estimates of the

nutritional variables; however,

unexpectedly, the differences between

estimates calculated using the original

sample weight and the adjusted weights

were not always greater for the variables

more highly correlated with age than

those less correlated with age. For

example, the correlations between age

A. Mercury 

30–34 35–39 40–44 45–49

Age group 

16–19 20–24 25–29

Micrograms per liter 

B. Lead 

Age group 

16–19 20–24 25–29 30–34 35–39 40–44 45–49

Micrograms per deciliter 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2001–2008. 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 1999–2008. 

C. PCB 

Age group 

Nanograms per gram lipid 

NOTE: PCB is polychlorinated biphenyl. 

SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2001–2004. 

16–19 20–24 25–29 30–34 35–39 40–44 45–49

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

1.4 

0 

20 

40 

60 

80 

100 

120 

Figure 2. Geometric means of environmental factors for women aged 16–49, by age group:

National Health and Nutrition Examination Survey, 1999–2008 (selected years)

and BMI, and age and calcium, were

relatively high compared with those for

other nutritional factors (about 0.19 and

–0.09, respectively), yet the adjusted

geometric mean (BMI) and mean

(calcium) were similar to (or the same

as) unadjusted estimates. However,

adjusted geometric means for lead and

mercury were roughly 8% lower than

the unadjusted geometric means, and

adjusted geometric means for PCB were

more than one-fourth lower than the

unadjusted geometric mean.

Standard errors of the geometric

means or means for the nutritional

variables using the adjusted sample

weights were most often larger than the

corresponding standard errors calculated

using the unadjusted sample weights—

for example, about 10% larger for the

standard error for BMI and vitamin D,

and more than one-third larger for iron.

Compared with standard errors for the

geometric means using the unadjusted

sample weights, standard errors using

the adjusted sample weights were

similar for mercury, about 5% higher for

lead, and about 20% lower for PCB.

Geometric means and means

calculated using adjusted sample

weights were similar across adjustment

methods. Results from direct

standardization were similar to those for

the sample weight adjustments.

Although there were small differences,

these similarities were apparent for both

the environmental and nutritional

variables (Tables 5 and 6).

Patterns for the 85th and 95th

percentiles were similar to those for

means and geometric means for the

environmental (Table 7) and nutritional

(Table 8) variables. The 95th percentiles

for PCB using the adjusted weights are

approximately 40% lower than the 95th

percentiles using the original weights

(Table 8).

The impact of using adjusted

sample weights to obtain estimates

differed among the race-and-ethnicity

groups (Tables 9 and 10). For example,

the impact of adjustment on the

geometric mean of mercury was greater

for black than for white/other or

Mexican-American women. Estimates

generally did not vary among the

adjustment approaches within

race-and-ethnicity categories. Using race

and ethnicity to adjust the weights had a

slightly larger effect on estimates of the

environmental variables and folate for

non-Hispanic black women compared

with women in the other groups;

estimates using either the three- or

four-category race-and-ethnicity

adjustment were 2%–10% lower than

those using only age adjustment among
Series 2, No. 157 [ Page 7

non-Hispanic black women. However,

this effect was not readily apparent for

the other nutritional variables nor for the

other race-and-ethnicity subgroups.

Discussion

Several approaches were compared

for adjusting estimates of nutritional and

environmental variables to better

correspond to those women who are

most likely, based on age, to give birth.

As in Axelrad and Cohen (9), this report

demonstrates that adjustment can affect

some estimates for women aged 16–49.

However, summary statistics, including

measures of variability, were not very

sensitive to the adjustment method used.

Although it was anticipated that

adjustment would affect variables more

strongly correlated with age, this was

not fully supported by the results. For

example, the correlations with age for

mercury and BMI were similar (about

0.2); however, adjustment led to

geometric means about 7% lower for

mercury but similar for BMI (about

1.5% lower). Other factors, including

the variance of the variable, the relative

standard error of the estimate, and the

age distribution of women in the

sample, likely affect the impact of

sample weight adjustment; however,

these and other factors that may affect

the impact of adjustment were not

directly evaluated here.

Direct standardization and adjusting

sample weights led to similar results.

The similarity of estimates of means and

standard errors between these

approaches is attributable to the fact that

these calculations are mathematically

equivalent and that, in general, results

from an application would differ only

due to differences in adjustment

groupings, in the handling of missing

data, and in the populations used to

calculate birth rates. In this report,

application of the direct-standardization

method combined total births across all

survey years, whereas the sample

weights were adjusted separately for

each data release. In comparable direct

age-adjustment applications, a standard

population is generally used; currently,

populations based on year 2000

estimates are used for NCHS reports

(34). Although there is no standard

population for women of childbearing

age, using the combination of births

across years to obtain reference values

is in line with using a single-year

reference. For a particular data analysis,

any observed differences between

estimates obtained from direct

standardization using a single reference

and sample-weight adjustment using

year- or data release-specific references

could be affected by the length of the

time period for the analysis and changes

in the age distribution of births over the

time period.

The extension of the Axelrad and

Cohen paper (9) was motivated by the

question of whether an adjustment to the

sample weights more consistent with the

underlying NHANES sample design, or

using direct standardization, would be

more robust. Direct standardization

enables the user to obtain age-specific

statistics with the unmodified public-use

sample weights. It was posited that

adjustment using larger age categories,

rather than single year of age, and race

and Hispanic origin categories in line

with the NHANES design would lead to

more stable adjusted weights and, as a

result, more stable estimates of risk

factors. The NHANES sample design is

based on oversampling population

subgroups. Although the subgroups can

change over time, generally these

include specific race and Hispanic-origin

groups and age categories. The stratified

cluster design and oversampling are

intended to provide stable estimates for

selected population subgroups while

controlling for the high costs of data

collection. Very generally, sample

weights are initially calibrated based on

the probability of selection into the

sample and subsequent response. Initial

weights are further calibrated to external

population control totals based on

specific categories of age, sex, and other

characteristics, often race and ethnicity.

Weights are evaluated for extreme

values and can be trimmed to meet prior

specifications. The NHANES race

domains used in this report (nonHispanic black, Mexican American,

white/other) and broad age categories

are based on the post-stratification

categories used to calibrate the weights

to national civilian noninstitutionalized

population totals. For black and

Mexican-American women aged 16–49,

for example, the age categories are

16–19, 20–39, and 40–59; for the

white/other race group, the 20–39 and

40–59 age groups are divided into

20–29, 30–39, 40–49, and 50–59. More

detail on NHANES weights can be

found in a recent report by Curtin and

colleagues (6).

The birth rates in this report,

calculated for single-year and 5-year

groups, are more specific than the

post-stratification categories used to

calibrate the initial sample weight.

Similarly, the four race-and-ethnicity

categories used by EPA in ACE are

more specific than the three used to

calibrate the initial sample weights. For

this evaluation, summary statistics are

examined for the three NHANES

race-and-ethnicity domains but the ‘‘all

other races and ethnicities’’ group used

for ACE are not specifically examined.

On the one hand, the ‘‘all other race and

ethnicities’’ group is heterogeneous,

combining people who identify, for

example, within Asian, Pacific Islander,

and other Hispanic subgroups, so that

birth rates and subsequent inferences for

this combined group may be difficult to

interpret. On the other hand, statistics

for ‘‘all other race and ethnicities’’ may

identify potential issues for further

investigation. For example, analysis of

the NHANES data has found that

women of ‘‘all other races and

ethnicities’’ have higher blood mercury

levels than women who are white,

black, or Mexican American (35,36),

suggesting one or more of the specific

subgroups combined in the ‘‘all other

races and ethnicities’’ group is at

increased risk.

There is trade-off, known as a bias

variance trade-off, when creating sample

weights that carries over to methods for

reweighting; that is, more precise, yet

more variable, sample weights can lead

to estimates with lower bias but higher

variance. For the nutritional and

environmental factors evaluated in this

report, no patterns were observed that

suggested strong trade-offs between

using coarser (e.g, 5-year age groups

only) and more precise (e.g., single year

of age with four race-and-ethnicity
Page 8 [ Series 2, No. 157

categories) adjustments for the sample

weights.

Civilian noninstitutionalized

population estimates based on CPS

estimates were used as denominators for

the calculation of birth rates; although

the conclusions of this report were

expected to be the same, the adjusted

statistics reported in the tables could

differ slightly if different population

estimates were used. Similarly,

population estimates obtained by

summing the sample weights within the

target groups would have the advantage

of being better calibrated to NHANES

and would not require obtaining

population estimates from another

source; because the direct

standardization used counts of births,

not birth rates, using summed weights

would connect direct standardization and

sample weight adjustment more closely.

On the other hand, as the CPS

estimates, using the summed sample

weights as denominators would also

differ from the total population on

which the birth counts are based.

Methods that incorporate other factors

related to the probability of becoming

pregnant may provide better estimates.

Further, the use of population estimates

or birth counts was not considered for

estimates from single NHANES data

releases, which produce statistics with

more variability.

Direct-standardization approaches

have the advantage of being relatively

simple to implement and describe. In

addition, if the group-specific estimates

and their standard errors are available,

the adjustment does not require use of

the original data. This method relies on

external population totals and, in this

case, available counts of births by

mother’s age and other characteristics,

like race and ethnicity. Weighted

averages of the category-specific means

can be easily combined in a spreadsheet,

and variance estimates can readily

follow. In addition, the sample weights

calibrated by the survey statisticians for

public-data release remain intact.

However, care needs to be taken to

assure categories with sufficient sample

size and precision for direct

standardization. Further, directstandardization methods do not work as

easily for percentiles and other

nonparametric statistics using standard

software, so the statistical expertise

needed to obtain confidence intervals

using this approach may negate the

above-mentioned advantages of ease and

transparency.

Although little impact is shown

from the choice of adjustment methods

for the measured variables used in this

study, other uses of adjusted weights

may be more sensitive. For example,

properties were not examined of the

adjusted weights or estimates derived

from direct standardization for

subgroups defined by demographic

characteristics such as income or

education, or by other health conditions.

However, applying one of the

approaches examined here, or another

statistical method using birth rate

information, reduces the influence of

specific age ranges to define women of

childbearing age on inferences. Defining

a population using an age range can

reduce the generalizability of findings

across studies that use different ranges.

Further, fixed age ranges produce

truncated age distributions and loss of

information beyond the range.

The similarity of the estimates

obtained using different adjustment

approaches, combined with small

differences between the adjusted and

unadjusted estimates for many variables,

suggests that methods for using birth

rate information to modify statistics for

women of childbearing age in NHANES

are robust. The decision to apply an

adjustment appears to have more impact

than the actual adjustment approach.

Because the purpose of this report was

to compare possible adjustment

methods, the conditions under which

adjustment would be important were not

directly evaluated. The findings for

PCB, which is the variable most

strongly correlated with age and has a

relatively high standard error,

demonstrate the potential importance of

the decision to adjust or not adjust for

some variables.

NCHS does not currently plan to

adopt one of these reweighting methods

for regular use. A recent NCHS report

describing lead and mercury levels for

pregnant women, for example, compared

some estimates for pregnant and

nonpregnant women and used direct

standardization, as described above, to

adjust for the differing age distribution

between the two groups (37). Although

the examples shown in this report show

little impact from the choices of

adjustment on the estimates, if

adjustment is required for future

projects, NCHS will use methods

consistent with the NHANES design,

such as the coarser age categories and

race-and-ethnicity categorizations in line

with the sampling domains. Researchers

are advised to consult statistical advice

for their particular research or reporting

objectives before adjusting NHANES

sample weights.

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Series 2, No. 157 [ Page 11

Table 1. Age and race distribution of women aged 16–49, by age group: National Health and

Nutrition Examination Survey, 1999–2008

Weighted

NHANES race domain and age group (years)1 n2 percent

Non-Hispanic white/All other groups
 

16–19 .................................. 932 8.27
 

20–24 .................................. 668 11.16
 

25–29 .................................. 684 10.11
 

30–34 .................................. 675 10.88
 

35–39 .................................. 615 11.96
 

40–44 .................................. 567 12.51
 

45–49 .................................. 556 12.57
 

Non-Hispanic black
 

16–19 .................................. 746 1.55
 

20–24 .................................. 281 2.12
 

25–29 .................................. 226 1.76
 

30–34 .................................. 254 2.14
 

35–39 .................................. 231 2.04
 

40–44 .................................. 254 1.90
 

45–49 .................................. 256 2.00
 

Mexican American
 

16–19 .................................. 825 1.12
 

20–24 .................................. 381 1.72
 

25–29 .................................. 309 1.46
 

30–34 .................................. 273 1.46
 

35–39 .................................. 223 1.28
 

40–44 .................................. 268 1.13
 

45–49 .................................. 198 0.88
 

1

Categories used when designing the National Health and Nutrition Examination Survey (NHANES) sample and creating the
 

public-use sample weights for 1999–2006.
 

2

Sample sizes may be lower for some nutritional and environmental variables.
 

Table 2. Summary statistics (weighted) for analysis variables for women aged 16–49: National Health and Nutrition Examination Survey,

1999–2008

Geometric1

Standard Geometric1 standard Correlation

Variable n Mean error mean error with age2

Environmental

Mercury (μg/L) ............................. 8,830 1.50 0.06 0.87 0.03 0.20

Lead (μg/dL)............................... 8,845 1.16 0.02 0.96 0.01 0.32

PCB3 (ng/g lipid) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,164 66.02 2.13 46.54 1.78 0.65

Nutritional
 

Folate (ng/mL) ............................. 8,765 43.17 0.04 38.50 0.42 0.02 
 

Vitamin D (ng/mL) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5,472 23.80 0.37 ––– ––– –0.05 
 

Body mass index (kg/m2

). . . . . . . . . . . . . . . . . . . . . . . 9,238 27.67 0.14 26.82 0.12 0.19 
 

Calcium (mg/dL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,722 9.38 0.01 ––– ––– –0.09 
 

Iron (μg/dL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,720 81.31 0.57 71.90 0.50 –0.04 
 

– – – Data not available.

1

For left-skewed variables.

2

For variables where geometric mean is shown, the correlation is on the log scale.

3

Polychlorinated biphenyl.

NOTES: Examination weights are used from the National Health and Nutrition Examination Survey. Data reflect selected years: PCB is calculated for one-third of the sample for 2001–2004, and

vitamin D is calculated for 2001–2006. μg/L is micrograms per liter, μg/dL is micrograms per deciliter, ng/g lipid is nanograms per gram lipid, ng/mL is nanograms per milliliter, kg/m2 is kilograms per

meter2

, and mg/dL is milligrams per deciliter.
Page 12 [ Series 2, No. 157

Table 3. Distribution of original and adjusted sample weight variables (unweighted statistics) for women aged 16–49: National Health and

Nutrition Examination Survey, 1999–2008

Weight variable Mean

Standard

deviation

5th

percentile

25th

percentile Median

75th

percentile

95th

percentile

Range

(maximumminimum)

Original weight ............................. 37,788 34,546 3,414 8,327 26,229 61,058 105,916 260,381

Adjusted NHANES weight

Birth rates in 5-year age groups................... 2,229 2,961 17 266 918 2,939 8,763 30,163

Birth rates in 5-year age groups and four race and ethnicity

groups1 ................................. 2,230 2,815 18 407 913 3,168 8,384 35,862

Birth rates in 5-year age groups and three NHANES race

and ethnicity domains2 ....................... 2,317 3,349 13 309 899 2,500 10,059 34,328

Birth rates in single-year age groups................ 2,231 3,001 14 231 861 2,937 8,768 29,493

Birth rates in single-year age groups and four race and

ethnicity groups1 ........................... 2,237 2,868 15 344 884 3,134 8,440 35,640

Birth rates in single-year age groups and three NHANES

race and ethnicity domains2 .................... 2,321 3,402 13 258 828 2,558 10,166 34,138

1

Mexican American, non-Hispanic black, non-Hispanic white, and all other races and ethnicities.
 

2

Mexican American, non-Hispanic black, and non-Hispanic white/other.
 

NOTE: NHANES is National Health and Nutrition Examination Survey.
 

Table 4. Correlations among original and adjusted weight variables (unweighted statistics) for women aged 16–49: National Health and

Nutrition Examination Survey, 1999–2008

Original Adjusted Adjusted Adjusted Adjusted Adjusted Adjusted

Weight variable weight weight 1 weight 2 weight 3 weight 4 weight 5 weight 6

Original weight .................................. 1.000 0.621 0.586 0.631 0.612 0.576 0.621

Adjusted NHANES weights

Birth rates in 5-year age groups (Adjusted weight 1) ........... 0.621 1.000 0.978 0.984 0.985 0.960 0.966

Birth rates in 5-year age groups and four race and ethnicity groups1

(Adjusted weight 2) .............................. 0.586 0.978 1.000 0.977 0.965 0.983 0.961

Birth rates in 5-year age groups and three NHANES race and

ethnicity domains2 (Adjusted weight 3) .................. 0.631 0.984 0.977 1.000 0.969 0.960 0.983

Birth rates in single-year age groups (Adjusted weight 4) ........ 0.612 0.985 0.965 0.969 1.000 0.976 0.982

Birth rates in single-year age groups and four race and ethnicity

groups1 (Adjusted weight 5) ......................... 0.576 0.960 0.983 0.960 0.976 1.000 0.977

Birth rates in single-year age groups and three NHANES race and

ethnicity domains2 (Adjusted weight 6) .................. 0.621 0.966 0.961 0.983 0.982 0.977 1.000

1

Mexican American, non-Hispanic black, non-Hispanic white, and all other races and ethnicities.

2

Mexican American, non-Hispanic black, and non-Hispanic white/other.

NOTE: NHANES is National Health and Nutrition Examination Survey.
Series 2, No. 157 [ Page 13

Table 5. Geometric mean and standard error for environmental variables using different adjustment methods for women aged 16–49:

National Health and Nutrition Examination Survey, 1999–2008

Mercury (μg/L) Lead (μg/dL) PCB1 (ng/g lipid)

Geometric Geometric Geometric

Geometric standard Geometric standard Geometric standard

Method mean error mean error mean error

Original weight .............................................. 0.87 0.03 0.96 0.01 46.5 1.8

Adjusted NHANES weights

Birth rates in 5-year age groups ................................... 0.80 0.03 0.87 0.01 33.7 1.5

Birth rates in 5-year age groups and four race and ethnicity groups2 ............. 0.81 0.03 0.88 0.01 32.8 1.3

Birth rates in 5-year age groups and three NHANES race and ethnicity domains3..... 0.81 0.03 0.87 0.01 34.0 1.5

Birth rates in single-year age groups ................................ 0.81 0.03 0.87 0.01 33.5 1.5

Birth rates in single-year age groups and four race and ethnicity groups2 .......... 0.81 0.02 0.88 0.01 32.5 1.4

Birth rates in single-year age groups and three NHANES race and ethnicity domains3 . . 0.81 0.03 0.86 0.01 33.7 1.5

Direct adjustment

Four age groups4 ............................................ 0.80 0.02 0.88 0.01 34.5 1.4

Seven age groups5 ........................................... 0.80 0.02 0.87 0.01 33.8 1.4

1

Polychlorinated biphenyl (PCB) calculated for one-third sample for 2001–2004.
 

2

Mexican American, non-Hispanic black, non-Hispanic white, and all other races and ethnicities.
 

3

Mexican American, non-Hispanic black, and non-Hispanic white/other.
 

4

Under age 20, 20–29, 30–39, and 40–49.
 

5

16–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49.
 

NOTES: μg/L is micrograms per liter, μg/dL is micrograms per deciliter, and ng/g lipid is nanograms per gram lipid. NHANES is National Health and Nutrition Examination Survey.
and standard error for nutritional variables using different adjustment methods for women aged 16–49: National Health and Nutrition

Folate (ng/mL) Vitamin D1 (ng/mL) Body mass index (kg/m2) Calcium (mg/dL) Iron (μg/dL)

Geometric Geometric Geometric

Geometric standard Standard Geometric standard Standard Geometric standard

mean error Mean error mean error Mean error mean error

.................. 38.5 0.4 23.8 0.4 26.8 0.1 9.38 0.01 71.9 0.5

weights

.................. 38.4 0.5 24.3 0.4 26.4 0.1 9.38 0.01 73.2 0.7

ce and ethnicity groups2 . . . 38.1 0.4 23.7 0.4 26.5 0.1 9.38 0.01 72.7 0.7

NHANES race and ethnicity

.................. 38.7 0.5 24.9 0.4 26.3 0.1 9.38 0.01 74.1 0.7

.................. 38.4 0.5 24.3 0.4 26.5 0.1 9.38 0.01 73.2 0.7

ur race and ethnicity

.................. 38.1 0.4 23.7 0.4 26.5 0.1 9.38 0.01 72.7 0.7

ree NHANES race and

.................. 38.8 0.5 25.0 0.4 26.3 0.1 9.38 0.01 74.1 0.7

nt

.................. 38.2 0.4 24.3 0.4 26.4 0.1 9.39 0.01 73.2 0.7

.................. 38.4 0.5 24.3 0.4 26.4 0.1 9.39 0.01 73.2 0.7

nic white, and all other races and ethnicities.

Hispanic white/other.

45–49.

kilograms per meter2, mg/dL is milligrams per deciliter, and μg/dL is micrograms per deciliter. NHANES is National Health and Nutrition Examination Survey.

Page 14[ Series 2, No. 157
e intervals) for environmental variables using different weight methods for women aged 16–49: National Health and Nutrition Examination

Mercury (μg/L) Lead (μg/dL) PCB1 (ng/g lipid)

and method Percentile Lower Upper Percentile Lower Upper Percentile Lower Upper

ercentile

............................ 5.2 4.7 5.8 2.6 2.4 2.7 194.2 182.2 208.6

............................ 4.9 4.2 5.6 2.3 2.1 2.4 109.0 103.7 147.9

race and ethnicity groups2 ........... 4.9 4.2 5.6 2.4 2.2 2.5 109.0 102.8 147.9

e NHANES race and ethnicity domains3 . . . 5.0 4.2 5.8 2.3 2.1 2.4 109.0 102.8 147.9

............................ 4.9 4.2 5.6 2.3 2.1 2.4 108.7 102.8 145.3

four race and ethnicity groups2 ........ 4.9 4.1 5.6 2.3 2.2 2.5 108.7 101.7 128.7

three NHANES race and ethnicity

............................ 5.0 4.2 5.8 2.2 2.1 2.4 108.7 101.8 147.9

ercentile

............................ 2.6 2.3 2.9 1.7 1.7 1.8 115.9 103.8 128.7

............................ 2.4 2.2 2.7 1.5 1.5 1.6 77.0 67.6 88.9

race and ethnicity groups2 ........... 2.4 2.2 2.7 1.6 1.5 1.6 76.7 67.3 87.6

e NHANES race and ethnicity domains3 . . . 2.5 2.2 2.8 1.5 1.5 1.6 77.0 67.4 92.2

............................ 2.4 2.2 2.7 1.5 1.5 1.6 77.0 67.6 87.6

four race and ethnicity groups2 ........ 2.4 2.2 2.7 1.5 1.5 1.6 76.4 66.2 85.5

three NHANES race and ethnicity

............................ 2.5 2.2 2.7 1.5 1.5 1.6 77.0 66.9 88.7

-third sample for 2001–2004.

nic white, and all other races and ethnicities.

Hispanic white/other.

ograms per deciliter, and ng/g lipid is nanograms per gram lipid. NHANES is National Health and Nutrition Examination Survey.

Series 2, No. 157[ Page 15
e intervals) for nutritional variables using different weight methods for women aged 16–49: National Health and Nutrition Examination Survey,

Folate (ng/mL) Vitamin D1 (ng/mL) Body mass index (kg/m2) Calcium (mg/dL) Iron (μg/dL)

Percentile Lower Upper Percentile Lower Upper Percentile Lower Upper Percentile Lower Upper Percentile Lower Upper

.... 80.7 78.0 83.8 47 45 49 41.6 40.9 42.4 10.0 10.0 10.0 153 150 158

.... 79.3 76.6 83.7 48 46 51 41.2 40.1 42.0 10.0 9.9 10.0 159 153 162

race

.... 79.1 75.9 83.3 47 45 50 41.2 40.0 41.8 10.0 9.9 10.0 158 152 161

e

.... 80.8 76.8 85.1 49 46 51 40.8 39.6 41.6 10.0 9.9 10.0 159 154 163

.... 80.0 76.6 83.8 49 46 51 41.3 40.3 42.2 10.0 9.9 10.0 159 153 162

four

.... 79.1 75.9 83.5 47 45 50 41.3 40.2 42.0 10.0 9.9 10.0 158 152 161

three

.... 80.9 76.8 85.2 49 46 51 40.9 39.7 41.7 10.0 9.9 10.0 160 154 163

.... 61.8 60.8 63.0 38 37 39 35.2 34.7 35.7 9.8 9.7 9.8 124 121 126

.... 61.5 60.2 62.8 40 38 42 34.6 34.0 35.1 9.8 9.7 9.8 126 124 129

race

.... 61.2 59.9 62.2 39 38 41 34.7 34.1 35.1 9.7 9.7 9.8 126 123 128

e

.... 62.0 60.8 63.1 40 39 42 34.4 33.7 35.0 9.8 9.7 9.8 128 125 130

.... 61.8 60.2 62.8 40 38 42 34.8 34.1 35.3 9.7 9.7 9.8 126 124 129

four

.... 61.2 59.9 62.2 39 38 41 34.8 34.2 35.3 9.7 9.7 9.8 125 123 128

three

.... 62.0 60.8 63.3 40 39 42 34.5 33.8 35.0 9.7 9.7 9.8 127 124 130

nic white, and all other races and ethnicities.

Hispanic white/other.

kilograms per meter2, mg/dL is milligrams per deciliter, and μg/dL is micrograms per deciliter. NHANES is National Health and Nutrition Examination Survey.

Page 16[ Series 2, No. 157
Series 2, No. 157 [ Page 17

Table 9. Mean and standard deviation for environmental variables using different adjustment methods for women aged 16–49, by race and

ethnicity: National Health and Nutrition Examination Survey, 1999–2008

Mercury (μg/L) Lead (μg/dL) PCB1 (ng/g lipid)

Geometric Geometric Geometric

Geometric standard Geometric standard Geometric standard

Race and ethnicity and method mean error mean error mean error

Non-Hispanic white/All other groups

Original weight .................................... 0.87 0.03 0.93 0.01 48.8 2.3

Adjusted NHANES weights:

Birth rates in 5-year age groups ........................ 0.81 0.03 0.84 0.01 35.7 2.0

Birth rates in 5-year age groups and four race and ethnicity groups2 . . 0.84 0.03 0.85 0.01 36.8 2.1

Birth rates in 5-year age groups and three NHANES race and

ethnicity domains3 ................................ 0.82 0.03 0.84 0.01 36.7 2.1

Birth rates in single-year age groups ..................... 0.81 0.03 0.83 0.01 35.4 2.0

Birth rates in single-year age groups and four race and ethnicity

groups2....................................... 0.83 0.03 0.85 0.01 36.4 2.1

Birth rates in single-year age groups and three NHANES race and

ethnicity domains3 ................................ 0.82 0.03 0.84 0.01 36.3 2.1

Direct adjustment:

Four age groups4 ................................. 0.80 0.03 0.84 0.01 36.2 1.8

Seven age groups5 ................................ 0.80 0.03 0.83 0.01 35.2 1.8

Non-Hispanic black

Original weight .................................... 1.04 0.05 1.09 0.03 53.8 3.0

Adjusted NHANES weights:

Birth rates in 5-year age groups ........................ 0.93 0.04 0.95 0.03 36.4 2.6

Birth rates in 5-year age groups and four race and ethnicity groups2 . . 0.88 0.04 0.92 0.03 33.4 2.2

Birth rates in 5-year age groups and three NHANES race and

ethnicity domains3 ................................. 0.89 0.04 0.92 0.03 33.2 2.2

Birth rates in single-year age groups ..................... 0.94 0.04 0.94 0.03 37.0 2.7

Birth rates in single-year age groups and four race and ethnicity

groups2....................................... 0.89 0.04 0.92 0.03 33.8 2.4

Birth rates in single-year age groups and three NHANES race and

ethnicity domains3 ................................ 0.89 0.04 0.92 0.03 33.7 2.4

Direct adjustment:

Four age groups4 ................................. 0.94 0.04 0.96 0.03 38.5 2.3

Seven age groups5 ................................ 0.93 0.04 0.95 0.03 38.1 2.3

Mexican American

Original weight .................................... 0.69 0.03 1.09 0.03 25.7 1.3

Adjusted NHANES weights:

Birth rates in 5-year age groups ........................ 0.65 0.03 1.03 0.03 20.1 1.3

Birth rates in 5-year age groups and four race and ethnicity groups2 . . 0.64 0.03 1.01 0.03 19.3 1.2

Birth rates in 5-year age groups and three NHANES race and

ethnicity domains3 ................................ 0.63 0.03 1.01 0.03 19.1 1.2

Birth rates in single-year age groups ..................... 0.65 0.03 1.02 0.03 19.9 1.3

Birth rates in single-year age groups and four race and ethnicity

groups2....................................... 0.64 0.03 1.01 0.03 19.1 1.2

Birth rates in single-year age groups and three NHANES race and

ethnicity domains3 ................................ 0.63 0.03 1.01 0.03 19.0 1.2

Direct adjustment:

Four age groups4 ................................. 0.65 0.03 1.04 0.03 21.5 1.1

Seven age groups5 ................................ 0.66 0.03 1.03 0.03 20.9 1.0

1

Polychlorinated biphenyl (PCB) calculated for one-third sample for 2001–2004.
 

2

Mexican American, non-Hispanic black, non-Hispanic white, and all other races and ethnicities.
 

3

Mexican American, non-Hispanic black, and non-Hispanic white/other.
 

4

Under age 20, 20–29, 30–39, and 40–49.
 

5

16–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49.
 

NOTES: μg/L is micrograms per liter, μg/dL is micrograms per deciliter, and ng/g lipid is nanograms per gram lipid. NHANES is National Health and Nutrition Examination Survey.
and standard deviation for nutritional variables using different adjustment methods for women aged 16–49, by race and ethnicity: National

urvey, 1999–2008

Folate (ng/mL) Vitamin D1 (ng/mL) Body mass index (kg/m2) Calcium (mg/dL) Iron (μg/dL)

Geometric Geometric Geometric

Geometric standard Standard Geometric standard Standard Geometric standard

and method mean error Mean error mean error Mean error mean error

ll other groups

....................... 12.9 0.2 26.2 0.4 26.2 0.2 9.39 0.01 75.0 0.7

....................... 12.9 0.2 27.0 0.5 25.8 0.2 9.40 0.01 76.6 0.9

race and ethnicity groups2....... 12.9 0.2 26.7 0.4 25.9 0.2 9.39 0.01 76.6 0.9

e NHANES race and ethnicity

....................... 12.9 0.2 27.0 0.4 25.9 0.2 9.39 0.01 76.7 0.9

....................... 12.9 0.2 27.0 0.5 25.8 0.2 9.39 0.01 76.7 0.9

four race and ethnicity groups2.... 12.9 0.2 26.8 0.5 25.9 0.2 9.39 0.01 76.6 0.9

three NHANES race and ethnicity

....................... 12.9 0.2 27.0 0.5 25.9 0.2 9.39 0.01 76.6 0.9

....................... 12.9 0.2 26.9 0.5 25.8 0.2 9.40 0.01 76.6 0.9

....................... 12.9 0.2 27.0 0.4 25.8 0.2 9.40 0.01 76.7 0.9

c black

....................... 10.4 0.2 13.5 0.3 29.6 0.2 9.40 0.01 60.0 0.7

....................... 10.3 0.2 13.6 0.3 29.3 0.2 9.39 0.02 60.8 0.8

race and ethnicity groups2....... 10.2 0.2 13.6 0.3 28.9 0.2 9.40 0.02 61.1 0.8

e NHANES race and ethnicity

....................... 10.2 0.2 13.5 0.3 28.8 0.2 9.40 0.02 61.2 0.8

....................... 10.3 0.2 13.5 0.3 29.3 0.2 9.39 0.02 60.8 0.8

four race and ethnicity groups2.... 10.2 0.2 13.5 0.3 28.9 0.2 9.40 0.02 61.2 0.8

three NHANES race and ethnicity

....................... 10.2 0.2 13.5 0.4 28.9 0.2 9.40 0.02 61.3 0.8

....................... 10.3 0.2 13.6 0.3 29.2 0.2 9.39 0.01 60.7 0.8

....................... 10.3 0.2 13.6 0.3 29.3 0.2 9.39 0.01 60.7 0.8

erican

....................... 11.5 0.2 19.0 0.5 27.8 0.2 9.30 0.01 65.2 1.1

....................... 11.5 0.3 19.6 0.5 27.5 0.2 9.30 0.01 66.7 1.2

race and ethnicity groups2....... 11.5 0.2 19.6 0.5 27.2 0.2 9.31 0.01 66.7 1.3

e NHANES race and ethnicity

....................... 11.4 0.2 19.6 0.5 27.2 0.2 9.31 0.01 66.7 1.3

....................... 11.5 0.3 19.6 0.5 27.6 0.2 9.30 0.01 66.8 1.2

four race and ethnicity groups2.... 11.5 0.2 19.5 0.5 27.2 0.2 9.31 0.01 66.8 1.3

three NHANES race and ethnicity

....................... 11.4 0.3 19.6 0.5 27.2 0.2 9.31 0.01 66.9 1.3

....................... 11.4 0.2 19.5 0.5 27.5 0.2 9.31 0.01 66.4 1.3

....................... 11.5 0.3 19.5 0.5 27.6 0.2 9.30 0.01 66.6 1.2

Page 18[ Series 2, No. 157

nic white, and all other races and ethnicities.

Hispanic white/other.

45–49.

kilograms per meter2, mg/dL is milligrams per deciliter, and μg/dL is micrograms per deciliter. NHANES is National Health and Nutrition Examination Survey.
Series 2, No. 157 [ Page 19

Appendix I. Calculation of Polychlorinated Biphenyls

Blood serum levels of Furthermore, the PCB congeners were

polychlorinated biphenyls (PCBs) were measured in a one-third sample of the

analyzed in women of childbearing age. NHANES data, which further reduces

There are 209 possible PCBs, referred to the available sample size. Despite the

as ‘‘congeners,’’ which are defined by smaller number of measurements, serum

the number of chlorine atoms (from one PCBs are included in these analyses

to 10) and their position in the chemical because the Axelrad and Cohen analyses

structure. PCBs are lipophilic, meaning showed relatively large effects of the

that they tend to accumulate in fat. natality adjustment for this variable

Serum PCB concentrations are measured compared with blood mercury and

and expressed on a lipid-adjusted basis, serum cotinine (9).

because these values better represent the

amount of PCBs stored in the body

compared with unadjusted values. The

lipid-adjusted concentration is the

concentration of PCBs in serum divided

by the concentration of lipid in serum.

The resulting units are nanograms of

PCB per gram of lipid (ng/g lipid) in

serum.

This analysis uses the sum of four

specific congeners measured in the

National Health and Nutrition

Examination Survey (NHANES):

PCBs 118, 138, 153, and 180. The full

chemical names are: 2,3’,4,4’,5­

pentachlorophenyl; 2,2’,3,4,4’,5- and

2,3,3’,4,4’,6-hexachlorophenyl;

2,2’,4,4’,5,5’- hexachlorophenyl; and

2,2’,3,4,4’,5,5’-heptachlorophenyl,

respectively. These four congeners are

generally found at higher levels in the

environment—and in human blood

samples—than other PCB congeners.

This combination of congeners has been

used to represent PCB exposure in

epidemiological studies (15). If a

congener was measured but not detected

in a sample, a default value of the

detection limit divided by the square

root of two was assigned for purposes

of calculating the summed total. If some

but not all of the four PCB congeners

are missing, then the sum is above the

nonmissing PCB congeners.

For these analyses, serum PCB data

for the 1999–2000 cycle were not used

because the four congeners of interest

were much more frequently below the

detection limit (approximately 80% of

measurements); serum PCB data after

2004 were not available at the time of

this report. Thus, the analyses of serum

PCBs use a much narrower range of

years than the other environmental and

nutritional variables studied here.
Page 20 [ Series 2, No. 157

Appendix II. Means or Geometric Means for Variables, by Age Group

Table. Means or geometric means for variables for women aged 16–49, by age group: National Health and Nutrition Examination Survey,

1999–2008

Mercury (μg/L) Lead (μg/dL) PCB (ng/g lipid) Folate (ng/mL)

Age group (years)

Geometric

mean

Geometric

SE

Geometric

mean

Geometric

SE

Geometric

mean

Geometric

SE

Geometric

mean

Geometric

SE

16–19 ...........................

20–24 ...........................

25–29 ...........................

30–34 ...........................

35–39 ...........................

40–44 ...........................

45–49 ...........................

0.55

0.71

0.79

0.99

0.98

1.00

1.10

0.02

0.03

0.04

0.05

0.06

0.04

0.05

0.71

0.83

0.84

0.93

1.02

1.11

1.28

0.01

0.02

0.02

0.02

0.03

0.02

0.03

19.61

26.72

29.77

42.79

62.56

80.21

97.35

0.79

1.57

2.15

3.13

4.72

5.35

4.52

38.12

37.56

38.65

39.59

37.37

38.11

40.09

0.64

0.74

0.84

0.90

0.83

0.79

1.01

Vitamin D (ng/mL) Body mass index (kg/m2

) Calcium (mg/dL) Iron (μg/dL)

Age group (years) Mean SE

Geometric

mean

Geometric

SE Mean SE

Geometric

mean

Geometric

SE

16–19 ...........................

20–24 ...........................

25–29 ...........................

30–34 ...........................

35–39 ...........................

40–44 ...........................

45–49 ...........................

24.17

24.21

24.61

24.36

23.95

22.68

22.96

0.61

0.76

0.64

0.53

0.68

0.56

0.45

23.77

25.84

26.67

27.32

27.41

27.80

28.21

0.15

0.25

0.26

0.26

0.29

0.28

0.30

9.54

9.41

9.36

9.35

9.35

9.34

9.40

0.02

0.01

0.02

0.02

0.02

0.02

0.02

72.49

73.48

73.41

73.87

72.65

67.59

70.73

1.29

1.48

1.55

1.59

1.63

1.42

1.44

NOTES: μg/L is micrograms per liter, μg/dL is micrograms per deciliter, ng/g lipid is nanograms per gram lipid, ng/mL is nanograms per milliliter, kg/m2 is kilograms per meter2, and mg/dL is milligrams

per deciliter. PCB is polychlorinated biphenyl. SE is standard error.
Vital and Health Statistics

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DHHS Publication No. 2013–1357, Series 2, No. 157
 

CS238715