Biomonitoring: Bisphenol A
Methods
Indicator
B11. Bisphenol A in women ages 16 to 49 years: Median and 95th percentile concentrations in
urine, 2003-2016.
B12. Bisphenol A in children ages 6 to 17 years: Median and 95th percentile concentrations in
urine, 2003-2016.
Summary
Since the 1970s, the National Center for Health Statistics, a division of the Centers for Disease
Control and Prevention, has conducted the National Health and Nutrition Examination Surveys
(NHANES), a series of U.S. national surveys of the health and nutrition status of the non-
institutionalized civilian population. The National Center for Environmental Health at CDC
measures environmental chemicals in blood and urine samples collected from NHANES
participants.1 This indicator uses urine measurements of bisphenol A (BP A) in women ages 16 to
49 years and children ages 6 to 17 years from 2003-2016.
Indicator B11 is the trend in the median and 95th percentile concentrations of BP A for women
ages 16 to 49 for 2003-2016. The median is the estimated concentration such that 50% of all
non-institutionalized civilian women ages 16 to 49 years have a BPA concentration below this
level; the population distribution was adjusted by age-specific birth rates to reflect exposures to
women who are pregnant or may become pregnant. The 95th percentile is the estimated
concentration such that 95% of all non-institutionalized civilian women ages 16 to 49 years have
a BPA concentration below this level. Indicator B12 is the trend in the median and 95th percentile
concentrations of BPA for children ages 6 to 17 years for 2003-2016.
Supplementary Tables: Table B1 la presents the median concentration of BPA for women ages
16 to 49 years for 2013-2016, stratified both by race/ethnicity and family income. Table B1 lb
presents the 95th percentile concentration of BPA for women ages 16 to 49 years for 2013-2016,
stratified both by race/ethnicity and family income. Table B12a presents the median
concentration of BPA for children ages 6 to 17 years for2013-2016, stratified both by
race/ethnicity and family income. Table B12b presents the 95th percentile concentration of BPA
for children ages 6 to 17 years in 2013-2016, stratified both by race/ethnicity and family income.
Table B12c presents the median and 95th percentile concentrations of BPA for children ages 6 to
17 in 2013-2016, stratified by age. The survey data were weighted to account for over-sampling,
non-response, and non-coverage.
1 Centers for Disease Control and Prevention. 2009. Fourth National Report on Human Exposure to Environmental
Chemicals. Atlanta. GA. Available at: www.cdc.gov/exposurereport.
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Data Summary
Indicator Bll. Bisphenol A in women ages 16 to 49 years: Median and 95th percentile concentrations in urine, 2003-2016.
Data
Urine BPA
Years
2003-2004
2005-2006
2007-2008
2009-
2010
2011-2012
2013-2014
2015-2016
Limits of Detection (|ig/L)*
0.4
0.4
0.4
0.4
0.4
0.2
0.2
Number of Values
627
634
589
618
542
612
585
Number of Non-Missing
Values**
611 (97%)
616 (97%)
571 (97%)
608
(98%)
536 (99%)
600 (98%)
564 (96%)
Number of Missing Values**
16 (3%)
18(3%)
18(3%)
10 (2%)
6 (1%)
12 (2%)
21 (4%)
Percentage Below Limit of
Detection***
5
8
4
8
11
6
8
* The Limit of Detection (LOD) is defined as the level at which the measurement has a 95% probability of being greater than zero.
**Non-missing values include those below the analytical LOD, which are reported as LOD/V2. Missing values are the number of sampled women ages 16 to 49 years in the
Mobile Examination Center (MEC) sub-sample that have no value reported for the particular variable used in calculating the indicator.
"This percentage is survey-weighted using the NHANES MEC survey weights for the given period and is weighted by age-specific birth rates.
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Indicator B12. Bisphenol A in children ages 6 to 17 years: Median and 95th percentile concentrations in urine, 2003-2016.
Data
Urine BPA
Years
2003-2004
2005-2006
2007-2008
2009-2010
2011-2012
2013-2014
2015-2016
Limits of Detection
(ng/L)*
0.4
0.4
0.4
0.4
0.4
0.2
0.2
Number of Values
884
927
714
743
706
789
789
Number of Non-Missing
Values**
852 (96%)
896 (97%)
690 (97%)
727 (98%)
689 (98%)
750 (95%)
742 (94%)
Number of Missing
Values**
32 (4%)
31 (3%)
24 (3%)
16 (2%)
17(2%)
39 (5%)
47 (6%)
Percentage Below Limit of
Detection***
3
4
3
8
10
2
3
* The Limit of Detection (LOD) is defined as the level at which the measurement has a 95% probability of being greater than zero.
**Non-missing values include those below the analytical LOD, which are reported as LOD/V2. Missing values are the number of sampled children ages 6 to 17 years in the Mobile
Examination Center (MEC) sub-sample that have no value reported for the particular variable used in calculating the indicator.
"This percentage is survey-weighted using the NHANES MEC survey weights for the given period.
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National Health and Nutrition Examination Surveys (NHANES)
Since the 1970s, the National Center for Health Statistics, a division of the Centers for Disease
Control and Prevention, has conducted the National Health and Nutrition Examination Surveys
(NHANES), a series of U.S. national surveys of the health and nutrition status of the non-
institutionalized civilian population. The National Center for Environmental Health at CDC
measures environmental chemicals in blood and urine samples collected from NHANES
participants. This indicator uses urine BPA measurements from NHANES 2003-2004, 2005-
2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016 in women ages 16 to 49
and children ages 6 to 17. The NHANES data were obtained from the NHANES website:
http://www.cdc.gov/nchs/nhanes.htm. Following the CDC recommended approach, values below
the analytical limit of detection (LOD) were replaced by LOD/V2."
The NHANES use a complex multi-stage, stratified, clustered sampling design. Certain
demographic groups were deliberately over-sampled, including Mexican Americans, Blacks,
and, from 2007 onwards, All Hispanics, to increase the reliability and precision of estimates of
health status indicators for these population subgroups. The publicly released data includes
survey weights to adjust for the over-sampling, non-response, and non-coverage. The statistical
analyses used the applicable MEC sub-sample survey weights (WTC2YR for 2003-2004,
WTSB2YR for 2005-2006, 2007-2008, 2009-2010, 2013-2014, 2015-2016, and WTA2YR for
2011-2012) to re-adjust the urine BPA data to represent the national population.
Age-Specific Birth Rates
In addition to the NHANES MEC survey weights, the data for women ages 16 to 49 were also
weighted by the birth rate for women of the given age and race/ethnicity, to estimate prenatal
exposures. Thus, the overall weight in each two-year period is the product of the NHANES
survey weight and the total number of births in the two calendar years for the given age and
race/ethnicity, divided by twice the corresponding population of women at the midpoint of the
two-year period:111
Adjusted Survey Weight =
MEC survey weight x U.S. Births (NHANES cycle, age, race/ethnicity) /
{Number of years in NHANES cycle x U.S. Women (NHANES cycle midpoint, age,
race/ethnicity)}.
II See Hornung RW, Reed LD. 1990. Estimation of average concentration in the presence of nondetectable values.
Applied Occupational and Environmental Hygiene 5:46-51.
III Axelrad, D. A., Cohen, J. 2011. Calculating summary statistics for population chemical biomonitoring in women of
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Race/Ethnicity and Family Income
For these indicators, the percentiles were calculated for demographic strata defined by the
combination of race/ethnicity and family income.
The family income was characterized based on the INDFMPIR variable, which is the ratio of the
family income to the poverty level. The National Center for Health Statistics used the U.S.
Census Bureau Current Population Survey definition of a "family" as "a group of two people or
more (one of whom is the householder) related by birth, marriage, or adoption and residing
together" to group household members into family units, and the corresponding family income
for the respondent was obtained during the interview. The U.S. Census Bureau defines annual
poverty level money thresholds varying by family size and composition. The poverty income
ratio (PIR) is the family income divided by the poverty level for that family. Family income was
stratified into the following groups:
• Below Poverty Level: PIR < 1
• Above Poverty Level: PIR > 1
• Unknown Income: PIR is missing
For the four-year period 2013-2016, the weighted percentage of women ages 16 to 49 years with
unknown income was 7% and the weighted percentage of children ages 6 to 17 years with
unknown income was 6%.
Race/ethnicity was characterized using the RIDRETH1 variable. The possible values of this
variable are:
• 1. Mexican American
• 2. Other Hispanic
• 3. Non-Hispanic White
• 4. Non-Hispanic Black
• 5. Other Race - Including Multi-racial
• Missing
Category 5 includes: all non-Hispanic single race responses other than White or Black; and
multi-racial responses.
For this indicator, the RIDRETH1 categories 2, 5, and missing were combined into a single "All
Other Races/Ethnicities" category. This produced the following categories:
• White non-Hispanic: RIDRETH1 = 3
• Black non-Hispanic: RIDRETH1 = 4
• Mexican American: RIDRETH1 = 1
• All Other Races/Ethnicities: RIDRETH1 = 2 or 5 or missing
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The "All Other Races/Ethnicities" category includes multiracial persons and individuals whose
racial or ethnic identity is not White non-Hispanic, Black non-Hispanic, or Mexican American.
Except for non-Mexican American Hispanics in 2007-2016 and Asian non-Hispanics in 2011-
2016, persons of "All Other Races/Ethnicities" are selected into the survey with a probability
that is very much lower than White non-Hispanic, Black non-Hispanic and Mexican American
individuals, and as a group they are not representative of all other race and ethnicities in the
United States.
Calculation of Indicator
Indicator B11 is the median and 95th percentile for urine BPA in women ages 16 to 49 years,
stratified by NHANES survey cycle. The median for women ages 16 to 49 is the estimated
concentration such that 50% of all non-institutionalized civilian women ages 16 to 49 years
during the survey period have urine BPA concentrations below this level. The 95th percentile for
women ages 16 to 49 is the estimated concentration such that 95% of all non-institutionalized
civilian women ages 16 to 49 years during the survey period have urine BPA concentrations
below this level. To adjust the NHANES data to represent prenatal exposures, the data for each
woman surveyed was multiplied by the estimated number of births per woman of the given age
and race/ethnicity. Indicator B12 is the median and 95th percentile for urine BPA in children ages
6 to 17 years, stratified by NHANES survey cycle. The birth rate adjustment was not applied to
children ages 6 to 17.
Table B1 la presents the median for urine BPA in women of ages 16 to 49 years in 2013-2016,
stratified by race/ethnicity and family income. Table B1 lb presents the 95th percentile for urine
BPA in women ages 16 to 49 years in 2013-2016, stratified by race/ethnicity and family income.
Table B12a presents the median for urine BPA in children ages 6 to 17 years in 2013-2016,
stratified by race/ethnicity and family income. Table B12b presents the 95th percentile for urine
BPA in children ages 6 to 17 years in 2013-2016, stratified by race/ethnicity and family income.
Table B12c presents the median concentration of BPA for children ages 6 to 17 in 2013-2016,
stratified by age.
To simply demonstrate the calculations, we will use the NHANES 2009-2010 urine BPA values
for women ages 16 to 49 years of all race/ethnicities and all incomes as an example. We have
rounded all the numbers to make the calculations easier:
We begin with all the non-missing NHANES 2009-2010 urine BPA values for women ages 16 to
49 years. Assume for the sake of simplicity that valid BPA data were available for every sampled
woman. Each sampled woman has an associated annual survey weight that estimates the annual
number of U.S. women represented by that sampled woman. For 2009-2010, the associated
annual survey weight for each woman is defined as WTSB2YR. Each sampled woman also has
an associated birth rate giving the numbers of annual births per woman of the given age, race,
and ethnicity. The product of the annual survey weight and the birth rate estimates the annual
number of U.S. births represented by that sampled woman which we will refer to as the adjusted
survey weight. For example, the lowest urine BPA measurement for a woman between 16 and 49
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years of age is 0.3 |ig/L with an annual survey weight of 380,000, a birth rate of 0.0002, and thus
an adjusted survey weight of 80, and so represents 80 births. The total of the adjusted survey
weights for the sampled women equals 4 million, the total number of annual U.S. births to
women ages 16 to 49 years. The second lowest measurement is also 0.3 |ig/L with an adjusted
survey weight of 22,000, and so represents another 22,000 U.S. births. The highest measurement
is 965 |ig/L with an adjusted survey weight of 500, and so represents another 500 U.S. births.
To calculate the median, we can use the adjusted survey weights to expand the data to the entire
U.S. population of births to women ages 16 to 49. We have 80 values of 0.3 |ig/L from the
lowest measurement, 22,000 values of 0.3 |ig/L from the second lowest measurement, and so on,
up to 500 values of 965 |ig/L from the highest measurement. Arranging these 4 million values in
increasing order, the 2 millionth value is 2.1 |ig/L. Since half of the values are below 2.1 and half
of the values are above 2.1, the median equals 2.1 |ig/L. To calculate the 95th percentile, note that
95% of 4 million equals 3.8 million. The 3.8 millionth value is 9.7 |ig/L. Since 95% of the values
are below 9.7, the 95th percentile equals 9.7 |ig/L.
The calculations need to consider that urine BPA measurements were not available for every
respondent and need to use exact rather than rounded numbers. There were urine BPA
measurements for only 608 of the 618 sampled women ages 16 to 49 years. The adjusted survey
weights for all 618 sampled women add up to 4.29 million, the U.S. population of births to
women ages 16 to 49. The adjusted survey weights for the 608 sampled women with urine BPA
data add up to 4.26 million. Thus, the available data represent 4.26 million values and so
represent 99% of the U.S. population of births. The median and 95th percentiles are given by the
2.13 millionth (50% of 4.26 million) and 4.05 millionth (95% of 4.26 million) U.S. birth's value.
These calculations assume that the sampled women with valid urine BPA data are representative
of women giving birth without valid urine BPA data. The calculations also assume that the
sampled women are representative of women that actually gave birth in 2009-2010, since
NHANES information on pregnancy and births was not incorporated into the analysis.
Equations
These percentile calculations can also be given as the following mathematical equations, which
are based on the default percentile calculation formulas from Statistical Analysis System (SAS®)
software. Exclude all missing urine BPA values. Suppose there are n women of ages 16 to 49
years with valid urine BPA values. Arrange the urine BPA concentrations in increasing order
(including tied values) so that the lowest concentration is x(l) with an adjusted survey weight of
w(l), the second lowest concentration is x(2) with an adjusted survey weight of w(2), ..., and the
highest concentration is x(n) with an adjusted survey weight of w(n).
1. Sum all the adjusted survey weights to get the total weight W:
W = E[1 < i < n] w(i)
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2. Find the largest number i so that the total of the weights for the i lowest values is less than or
equal to W/2.
E[j < i] w(j) < W/2 < E[j < i + 1] w(j)
3. Calculate the median using the results of the second step. We either have
E[j < i] w(j) = W/2 < E[j < i + 1] w(j)
or
E[j < i] w(j) < W/2 < E[j < i + 1] w(j)
In the first case we define the median as the average of the i'th and i + l'th values:
Median = [x(i) + x(i + l)]/2 if S[j < i] w(j) = W/2
In the second case we define the median as the i + l'th value:
Median = x(i + 1) if E[j < i] w(j) < W/2
(The estimated median does not depend upon how the tied values of x(j) are ordered).
A similar calculation applies to the 95th percentile. The first step to calculate the sum of the
weights, W, is the same. In the second step, find the largest number i so that the total of the
weights for the i lowest values is less than or equal to 0.95W.
E[j < i] w(j) < 0.95W < E[j < i + 1] w(j)
In the third step we calculate the 95th percentile using the results of the second step. We either
have
E[j < i] w(j) = 0.95W < E[j < i + 1] w(j)
or
E[j < i] w(j) < 0.95W < E[j < i + 1] w(j)
In the first case we define the 95th percentile as the average of the i'th and i + l'th values:
95th Percentile = [x(i) + x(i + l)]/2 if S[j < i] w(j) = 0.95W
In the second case we define the 95th percentile as the i + l'th value:
95th Percentile = x(i + 1) if E[j < i] w(j) < 0.95W
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Relative Standard Error
The uncertainties of the median and 95th percentile values were calculated using a revised
version of the CDC method given in CDC 2005,1V Appendix C, and the SAS® program provided
by CDC. The method uses the Clopper-Pearson binomial confidence intervals adapted for
complex surveys by Korn and Graubard (see Korn and Graubard, 1999,v p. 65). The following
text is a revised version of the Appendix C. For the birth rate adjusted calculations for women
ages 16 to 49, the sample weight is adjusted by multiplying by the age-specific birth rate.
Step 1: Use SAS® Proc Univariate to obtain a point estimate Psas of the percentile value. Use the Weight
option to assign the exact correct sample weight for each chemical result.
Step 2: Use SUDAAN® Proc Descript with Taylor Linearization DESIGN = WR (i.e.,
sampling with replacement) and the proper sampling weight to estimate the proportion (p) of subjects with
results less than and not equal to the percentile estimate Psas obtained in Step 1 and to obtain the standard
error (sep) associated with this proportion estimate. Compute the degrees-of-freedom adjusted effective
sample size
ndf = ( tnum/ tdenom )2 p (l - p) / (sep 2)
where tnUm and tdenom are 0.975 critical values of the Student's t distribution with degrees of freedom
equal to the sample size minus 1 and the number of primary sampling units (PSUs) minus the number of
strata, respectively. Note: the degrees of freedom for tdenom can vary with the demographic sub-group of
interest.
Step 3: After obtaining an estimate of p (i.e., the proportion obtained in Step 2), compute the Clopper-
Pearson 95% confidence interval (PL(x,ndf), Pu(x,ndf)) as follows:
PL(x,ndf) = ViFvi,v2 (0.025)/(v2 + ViFvi,v2(0.025))
Pu(x,ndf) = v3FV3,v4 (0.975)/(v4 + v3FV3,v4(0.975))
where x is equal to p times ndf, vi = 2x, V2 = 2(ndf - x + 1), v3 = 2(x + 1), V4 = 2(ndf - x), and Fdi,d2(P) is
the (3 quantile of an F distribution with dl and d2 degrees of freedom. (Note: If ndf is greater than the
actual sample size or if p is equal to zero, then the actual sample size should be used.) This step will
produce a lower and an upper limit for the estimated proportion obtained in Step 2.
Step 4: Use SAS® Proc Univariate (again using the Weight option to assign weights) to determine the
chemical percentile values Pcdc, LCdc and UCdc that correspond to the proportion p obtained in Step 2 and
its lower and upper limits obtained in Step 3. Do not round the values of p and the lower and upper limits.
For example, if p = 0.4832, then Pcdc is the 48.32'th percentile value of the chemical. The alternative
percentile estimates Pcdc and Psas are not necessarily equal.
Step 5: Use the confidence interval from Step 4 to estimate the standard error of the estimated percentile
Pcdc:
IV CDC Third National Report on Human Exposure to Environmental Chemicals. 2005
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Standard Error (PCdc) = (UCdc - LCDc) / (2tdenom)
Step 6: Use the estimated percentile Pcdc and the standard error from Step 4 to estimate the relative
standard error of the estimated percentile Pcdc:
Relative Standard Error (%) = [Standard Error (Pcdc) / Pcdc] x 100%
The tabulated estimated percentile is the value of Psas given in Step 1. The relative standard error is given
in Step 6, using Pcdc and its standard error.
The relative standard error depends upon the survey design. For this purpose, the public release
version of NHANES includes the variables SDMVSTRA and SDMVPSU, which are the Masked
Variance Unit pseudo-stratum and pseudo-primary sampling unit (pseudo-PSU). For
approximate variance estimation, the survey design can be approximated as being a stratified
random sample with replacement of the pseudo-PSUs from each pseudo-stratum; the true stratum
and PSU variables are not provided in the public release version to protect confidentiality. If the
relative standard error is too high, then the estimated percentile will not be accurately estimated.
Furthermore, if the degrees of freedom (from Step 2) are too low, then the relative standard error
will be less accurately estimated and thus may be underestimated. For these reasons, percentiles
with high relative standard errors or with low degrees of freedom are unstable or unreliable.
Percentiles with a relative standard error less than 30% and with 12 or more degrees of freedom
were treated as being reliable and were tabulated. Percentiles with a relative standard error that is
30% or greater but less than 40% and with 12 or more degrees of freedom were treated as being
unstable; these values were tabulated but were flagged to be interpreted with caution. Percentiles
with a relative standard error less than 40% and with between 7 and 11 degrees of freedom were
also treated as being unstable; these values were tabulated but were flagged to be interpreted
with caution. Percentiles with a relative standard error that is 40% or greater, or without an
estimated relative standard error, or with 6 or less degrees of freedom, were treated as being
unreliable; these values were not tabulated and were flagged as having a large uncertainty.
Questions and Comments
Questions regarding these methods, and suggestions to improve the description of the methods,
are welcome. Please use the "Contact Us" link at the bottom of any page in the America's
Children and the Environment website.
Statistical Comparisons
Statistical analyses of the percentiles were used to determine whether the differences between
percentiles for different demographic groups were statistically significant. For these analyses, the
percentiles and their standard errors were calculated for each combination of age group, sex (in
the cases of children), income group (below poverty, at or above poverty, unknown income), and
race/ethnicity group using the method described in the "Relative Standard Error" section. In the
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notation of that section, the percentile and standard error are the values of Pcdc and Standard
Error (Pcdc), respectively. These calculated standard errors account for the survey weighting and
design and, for women, for the age-specific birth rate.
Using a weighted linear regression model, the percentile was assumed to be the sum of
explanatory terms for age, sex, income and/or race/ethnicity and a random error term; the error
terms were assumed to be approximately independent and normally distributed with a mean of
zero and a variance equal to the square of the standard error. In this model, the weight is the
inverse of the variance, so that percentiles with larger standard errors are given less of a
statistical weight in the fitted regression model. Using this model, the difference in the value of a
percentile between different demographic groups is statistically significant if the difference
between the corresponding sums of explanatory terms is statistically significantly different from
zero. A p-value at or below 0.05 implies that the difference is statistically significant at the 5%
significance level. No adjustment is made for multiple comparisons.
For each type of comparison, we present unadjusted and adjusted analyses. The unadjusted
analyses directly compare a percentile between different demographic groups. The adjusted
analyses add other demographic explanatory variables to the statistical model and use the
statistical model to account for the possible confounding effects of these other demographic
variables. For example, the unadjusted race/ethnicity comparisons use and compare the
percentiles between different race/ethnicity pairs. The adjusted race/ethnicity comparisons use
the percentiles for each age/sex/income/race/ethnicity combination. The adjusted analyses add
age, sex, and income terms to the statistical model and compare the percentiles between different
race/ethnicity pairs after accounting for the effects of the other demographic variables. For
example, if White non-Hispanics tend to have higher family incomes than Black non-Hispanics,
and if the urine BPA level strongly depends on family income only, then the unadjusted
differences between these two race/ethnicity groups would be significant but the adjusted
difference (taking into account income) would not be significant.
Comparisons between pairs of race/ethnicity groups are shown in Table 1 for women ages 16 to
49 years and in Table 4 for children ages 6 to 17 years. Comparisons between income groups are
shown in Table 2 for women ages 16 to 49 years and in Table 5 for children ages 6 to 17 years.
In Tables 1 and 4, for the unadjusted "All incomes" comparisons, the only explanatory variables
are terms for each race/ethnicity group. For these unadjusted comparisons, the statistical tests
compare the percentiles for each pair of race/ethnicity groups. For the adjusted "All incomes
(adjusted for age, sex, income)" comparisons, the explanatory variables are terms for each
race/ethnicity group together with terms for each age, sex (for children), and income group. For
these adjusted comparisons, the statistical test compares the pair of race/ethnicity groups after
accounting for any differences in the age, sex for children), and income distributions between the
race/ethnicity groups. The adjustment for sex is applicable only for children, and thus appears
only in Tables 4, 5 and 6.
In Tables 1 and 4, for the unadjusted "Below Poverty Level" and "At or Above Poverty Level"
comparisons, the only explanatory variables are terms for each of the twelve
race/ethnicity/income combinations (combinations of four race/ethnicity groups and three
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non-Hispanics below the poverty level with Black non-Hispanics below the poverty level. The
same set of explanatory variables are used in Tables 2 and 5 for the unadjusted comparisons
between one race/ethnicity group below the poverty level and the same race/ethnicity group at or
above the poverty level. The corresponding adjusted analyses include extra explanatory variables
for age and sex (for children), so that race/ethnicity/income groups are compared after
accounting for any differences due to age or sex. Although these comparisons only involve the
two income groups with known incomes, these statistical models were fitted to all three income
groups (including those with unknown income) to make a more general, better fitting model; this
approach has no impact on the unadjusted p-values but has a small impact on the adjusted p-
values. Also, in Tables 2 and 5, the unadjusted p-value for the population "All" compares the
percentiles for women ages 16 to 49 years or children ages 6 to 17 years below poverty level
with those at or above poverty level, using the explanatory variables for the two income groups
(below poverty, at or above poverty), excluding those with unknown income. The adjusted p-
value includes adjustment terms for age, sex (for children), and race/ethnicity in the model.
Additional comparisons are shown in Table 3 for women ages 16 to 49 years and in Table 6 for
children ages 6 to 17 years. Comparisons are shown for differences between children's age
groups, between those below poverty and those at or above poverty, and for changes over time
(trends). The Against = "age" unadjusted p-value compares the percentiles between children in
different age groups, using the explanatory variables for the age groups. The adjusted p-value
includes adjustment terms for sex (for children), race/ethnicity, and income in the model. The
Against = "income" unadjusted p-value compares the percentiles for those below poverty level
with those at or above poverty level, using the explanatory variables for the two income groups
(below poverty, at or above poverty). The adjusted p-value includes adjustment terms for age,
sex (for children), and race/ethnicity in the model. The Against = "year" p-value examines
whether the linear trend in the percentiles is statistically significant (using the percentiles for
each NHANES period regressed against the midpoint of that period); the adjusted model for
trend adjusts for demographic changes in the populations from year to year by including terms
for age, sex (for children), income, and race/ethnicity. The adjustment for sex is applicable only
for children, and thus appears only in Table 6.
For women, the age groups used were 16-19, 20-24, 25-29, 30-39, and 40-49. For children, the
age groups used were 6-10, 11-15, and 16-17.
For more details on these statistical analyses, see the memorandum by Cohen (2010).V1
vl Cohen, J. 2010. Selected statistical methods for testing for trends and comparing years or demographic groups in
ACE NHIS and NHANES indicators. Memorandum submitted to Dan Axelrad, EPA, 21 March, 2010.
America's Children and the Environment
Updated October 2021
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Biomonitoring: Bisphenol A
Table 1. Statistical significance tests comparing the percentiles of BP A in women ages 16 to 49 years, between pairs of race/ethnicity
groups, for 2013-2016.
P-VALUES
At or
All
Below
Above
First
Second
incomes
(adjusted
Below
Poverty
Level
At or
Above
Poverty
Level
Variable
Percentile
race/ethnicity
group
race/ethnicity
group*
All
incomes
for age,
income)
Poverty
Level
(adjusted
for age)
Poverty
Level
(adjusted
for age)
BPA
50
White non-
Hispanic
Black non-
Hispanic
<0.001
<0.001
0.094
0.002
<0.001
0.001
BPA
50
White non-
Hispanic
Mexican
American
0.159
<0.001
0.342
<0.001
0.479
0.232
BPA
50
White non-
Hispanic
Other
0.101
0.041
0.114
0.884
0.411
0.108
BPA
50
Black non-
Hispanic
Mexican
American
0.011
<0.001
0.449
0.388
0.032
0.037
BPA
50
Black non-
Hispanic
Other
<0.001
<0.001
<0.001
0.025
<0.001
<0.001
BPA
50
Mexican
American
Other
0.014
<0.001
0.001
0.004
0.275
0.020
BPA
95
White non-
Hispanic
Black non-
Hispanic
0.236
0.022
0.787
0.139
0.015
<0.001
BPA
95
White non-
Hispanic
Mexican
American
0.193
0.632
1.000
0.007
0.243
0.760
BPA
95
White non-
Hispanic
Other
0.812
0.256
0.046
0.001
0.686
<0.001
BPA
95
Black non-
Hispanic
Mexican
American
0.029
<0.001
0.862
0.106
0.002
<0.001
BPA
95
Black non-
Hispanic
Other
0.198
<0.001
0.126
0.012
0.015
0.115
BPA
95
Mexican
American
Other
0.327
0.328
0.396
0.340
0.542
<0.001
* "Other" represents the "All Other Races/Ethnicities" category, which includes all other races and ethnicities not specified, together with those individuals who report more than one race.
America's Children and the Environment
Updated October 2021
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Biomonitoring: Bisphenol A
Table 2. Statistical significance tests comparing the percentiles of BP A in women ages 16 to 49 years, between those below poverty
level and those at or above poverty level, for 2013-2016.
P-Values for difference between income levels
Variable
Percentile
Population*
Unadjusted
Adjusted (for age)**
BPA
50
All
0.002
0.532
BPA
50
White non-Hispanic
0.350
0.054
BPA
50
Black non-Hispanic
0.317
0.749
BPA
50
Mexican American
0.093
0.019
BPA
50
Other
0.235
0.723
BPA
95
All
0.482
0.918
BPA
95
White non-Hispanic
0.473
<0.001
BPA
95
Black non-Hispanic
0.412
0.001
BPA
95
Mexican American
0.426
0.013
BPA
95
Other
0.434
<0.001
* "Other" represents the "All Other Races/Ethnicities" category, which includes all other races and ethnicities not specified, together with those individuals who report more than one race.
** Comparison for "All" is adjusted for age and race/ethnicity; comparisons for race/ethnicity categories are adjusted for age.
Table 3. Other statistical significance tests comparing the percentiles of BP A in women ages 16 to 49 years, for 2013-2016 (trends for
2003-2016).
P-VALUES
Variable
Percentile
From
To
Against
Unadjusted
Adjusted*
BPA
50
2013
2016
income
0.002
0.532
BPA
50
2003
2016
year
<0.001
<0.001
BPA
95
2013
2016
income
0.482
0.918
BPA
95
2003
2016
year
0.003
<0.001
*For Against = "income," the comparison is between those below the poverty level and those at or above the poverty level, and the p-values are adjusted for age and race/ethnicity.
For Against = "year" the comparison is the trend over different years, and the p-values are adjusted for age, race/ethnicity, and income.
America's Children and the Environment
Updated October 2021
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Biomonitoring: Bisphenol A
Table 4. Statistical significance tests comparing the percentiles of BP A in children ages 6 to 17 years, between pairs of race/ethnicity
groups, for 2013-2016.
P-VALUES
Variable
Percentile
First
race/ethnicity
group
Second
race/ethnicity
group*
All
incomes
All
incomes
(adjusted
for age,
income)
Below
Poverty
Level
Below
Poverty
Level
(adjusted
for age)
At or
Above
Poverty
Level
At or
Above
Poverty
Level
(adjusted
for age)
BPA
50
White non-
Hispanic
Black non-
Hispanic
0.013
<0.001
0.492
0.002
0.081
0.010
BPA
50
White non-
Hispanic
Mexican
American
0.327
0.082
0.196
0.946
0.137
0.013
BPA
50
White non-
Hispanic
Other
0.332
<0.001
0.582
0.015
0.028
<0.001
BPA
50
Black non-
Hispanic
Mexican
American
0.001
<0.001
0.133
0.003
0.003
<0.001
BPA
50
Black non-
Hispanic
Other
0.001
<0.001
0.288
<0.001
0.001
<0.001
BPA
50
Mexican
American
Other
1.000
0.074
0.469
0.043
0.459
0.052
BPA
95
White non-
Hispanic
Black non-
Hispanic
0.101
0.050
0.297
<0.001
0.930
0.178
BPA
95
White non-
Hispanic
Mexican
American
0.937
0.009
0.496
<0.001
0.821
0.004
BPA
95
White non-
Hispanic
Other
0.458
<0.001
0.243
<0.001
0.005
0.847
BPA
95
Black non-
Hispanic
Mexican
American
0.126
<0.001
0.547
<0.001
0.831
<0.001
BPA
95
Black non-
Hispanic
Other
0.010
<0.001
0.799
<0.001
0.157
<0.001
BPA
95
Mexican
American
Other
0.418
0.026
0.428
<0.001
0.024
<0.001
* "Other" represents the "All Other Races/Ethnicities" category, which includes all other races and ethnicities not specified, together with those individuals who report more than one race.
America's Children and the Environment
Updated October 2021
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Biomonitoring: Bisphenol A
Table 5. Statistical significance tests comparing the percentiles of BP A in children ages 6 to 17 years, between those below poverty
level and those at or above poverty level, for 2013-2016.
P-Values for difference between income levels
Variable
Percentile
Population*
Unadjusted
Adjusted (for age,
sex)**
BPA
50
All
1.000
0.069
BPA
50
White non-Hispanic
0.552
0.034
BPA
50
Black non-Hispanic
1.000
0.754
BPA
50
Mexican American
0.395
0.920
BPA
50
Other
0.050
0.251
BPA
95
All
0.675
0.003
BPA
95
White non-Hispanic
0.213
0.019
BPA
95
Black non-Hispanic
0.877
0.663
BPA
95
Mexican American
0.500
<0.001
BPA
95
Other
0.087
<0.001
* "Other" represents the "All Other Races/Ethnicities" category, which includes all other races and ethnicities not specified, together with those individuals who report more than one race.
** Comparison for "All" is adjusted for age, sex, and race/ethnicity; comparisons for race/ethnicity categories are adjusted for age and sex.
Table 6. Other statistical significance tests comparing the percentiles of BP A in children ages 6 to 17 years, for 2013-2016 (trends for
2003-2016).
P-VALUES
Variable
Percentile
From
To
Against
Unadjusted
Adjusted*
BPA
50
2013
2016
age
0.586
0.009
BPA
50
2013
2016
income
1.000
0.069
BPA
50
2003
2016
year
<0.001
<0.001
BPA
95
2013
2016
age
0.694
<0.001
BPA
95
2013
2016
income
0.675
0.003
BPA
95
2003
2016
year
<0.001
<0.001
*For Against = "age," the comparison is between the age groups 6-10, 11-15, and 16-17 years, and the p-values are adjusted for sex, race/ethnicity, and income.
For Against = "income," the comparison is between those below the poverty level and those at or above the poverty level, and the p-values are adjusted for age, sex, and race/ethnicity.
For Against = "year" the comparison is the trend over different years, and the p-values are adjusted for age, sex, race/ethnicity, and income.
America's Children and the Environment
Updated October 2021
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Biomonitoring: Bisphenol A
Data Files
The following files are needed to calculate this indicator. The files together with the survey
documentation and SAS® programs for reading in the data are available at the NHANES
website: http://www.cdc.gov/nchs/nhanes/nhanes questionnaires.htm.
• NHANES 2003-2004: Demographic file democ.xpt. Environmental Phenols laboratory
file 124eph_c.xpt. The demographic file demo c.xpt is a SAS® transport file that
contains the subject identifier (SEQN), age (RIDAGEYR), sex (RIAGENDR),
race/ethnicity (RIDRETH1), poverty income ratio (INDFMPIR), pseudo-stratum
(SDMVSTRA) and the pseudo-PSU (SDMVPSU). The Environmental Phenols
laboratory file 124eph_c.xpt contains SEQN, urine BPA (URXBPH), the BPA non-detect
comment code (URDBPHLC), and the two-year Mobile Examination Center (MEC) sub-
sample C weight (WTSC2YR). The two files are merged using the common variable
SEQN.
• NHANES 2005-2006: Demographic file demod.xpt. Environmental Phenols and
Parabens laboratory file ephd.xpt. The demographic file demo d.xpt is a SAS®
transport file that contains the subject identifier (SEQN), age (RIDAGEYR), sex
(RIAGENDR), race/ethnicity (RIDRETH1), poverty income ratio (INDFMPIR), pseudo-
stratum (SDMVSTRA) and the pseudo-PSU (SDMVPSU). The Environmental Phenols
and Parabens laboratory file eph d.xpt contains SEQN, urine BPA (URXBPH), the BPA
non-detect comment code (URDBPHLC), urine creatinine (URXUCR) and the two-year
MEC sub-sample B weight (WTSB2YR). The two files are merged using the common
variable SEQN.
• NHANES 2007-2008: Demographic file demoe.xpt. Environmental Phenols laboratory
file ephe.xpt. The demographic file demo e.xpt is a SAS® transport file that contains
the subject identifier (SEQN), age (RIDAGEYR), sex (RIAGENDR), race/ethnicity
(RIDRETH1), poverty income ratio (INDFMPIR), pseudo-stratum (SDMVSTRA) and
the pseudo-PSU (SDMVPSU). The Environmental Phenols laboratory file eph e.xpt
contains SEQN, urine BPA (URXBPH), the BPA non-detect comment code
(URDBPHLC), and the two-year MEC sub-sample B weight (WTSB2YR). The two files
are merged using the common variable SEQN. Note that these files were downloaded in
October 2011 and so include the corrected subsample weights released in September
2011.
• NHANES 2009-2010: Demographic file demof.xpt. Environmental Phenols laboratory
file ephf.xpt. The demographic file demo f.xpt is a SAS® transport file that contains the
subject identifier (SEQN), age (RIDAGEYR), sex (RIAGENDR), race/ethnicity
(RIDRETH1), poverty income ratio (INDFMPIR), pseudo-stratum (SDMVSTRA) and
the pseudo-PSU (SDMVPSU). The Environmental Phenols laboratory file eph f.xpt
contains SEQN, urine BPA (URXBPH), the BPA non-detect comment code
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Updated October 2021
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Biomonitoring: Bisphenol A
(URDBPHLC), and the two-year MEC sub-sample B weight (WTSB2YR). The two files
are merged using the common variable SEQN.
• NHANES 2011-2012: Demographic file demog.xpt. Environmental Phenols & Parabens
laboratory file eph g.xpt. The demographic file demo g.xpt is a SAS® transport file that
contains the subject identifier (SEQN), age (RIDAGEYR), sex (RIAGENDR),
race/ethnicity (RIDRETH1), poverty income ratio (INDFMPIR), pseudo-stratum
(SDMVSTRA) and the pseudo-PSU (SDMVPSU). The Environmental Phenols &
Parabens laboratory file eph g.xpt contains SEQN, urine BPA (URXBPH), the BPA non-
detect comment code (URDBPHLC), and the two-year MEC sub-sample A weight
(WTSA2YR). The two files are merged using the common variable SEQN.
• NHANES 2013-2014: Demographic file demoh.xpt. Personal Care and Consumer
Product Chemicals and Metabolites laboratory file ephpph.xpt. The demographic file
demo h.xpt is a SAS® transport file that contains the subject identifier (SEQN), age
(RIDAGEYR), sex (RIAGENDR), race/ethnicity (RIDRETH1), poverty income ratio
(INDFMPIR), pseudo-stratum (SDMVSTRA) and the pseudo-PSU (SDMVPSU). The
Personal Care and Consumer Product Chemicals and Metabolites laboratory file
ephpp h.xpt contains SEQN, urine BPA (URXBPH), the BPA non-detect comment code
(URDBPHLC), and the two-year MEC sub-sample B weight (WTSB2YR). The two files
are merged using the common variable SEQN.
• NHANES 2015-2016: Demographic file demoi.xpt. Personal Care and Consumer
Product Chemicals and Metabolites laboratory file ephppi.xpt. The demographic file
demo i.xpt is a SAS® transport file that contains the subject identifier (SEQN), age
(RIDAGEYR), sex (RIAGENDR), race/ethnicity (RIDRETH1), poverty income ratio
(INDFMPIR), pseudo-stratum (SDMVSTRA) and the pseudo-PSU (SDMVPSU). The
Personal Care and Consumer Product Chemicals and Metabolites laboratory file
ephpp i.xpt contains SEQN, urine BPA (URXBPH), the BPA non-detect comment code
(URDBPHLC), and the two-year MEC sub-sample B weight (WTSB2YR). The two files
are merged using the common variable SEQN.
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