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Research
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Temporal Variability and Predictors of
Urinary Bisphenol A Concentrations in Men and Women Shruthi Mahalingaiah,1 John D.
Meeker,2 Kimberly R. Pearson,3 Antonia M. Calafat,4 Xiaoyun Ye,4 John Petrozza,5 and Russ Hauser5,6 1Department
of Obstetrics and Gynecology, Brigham and Women's
Hospital, Boston, Massachusetts, USA; 2Department of
Environmental Health Sciences, University of Michigan, Ann
Arbor, Michigan, USA; 3Department of Biostatistics, Harvard School of
Public Health, Boston, Massachusetts, USA; 4Centers for
Disease Control and Prevention, Atlanta, Georgia, USA; 5The
Fertility Center, Vincent Memorial Obstetrics and Gynecology
Service, Massachusetts General Hospital, Harvard Medical
School, Boston, Massachusetts, USA; 6Department of
Environmental Health, Harvard School of Public Health, Boston,
Massachusetts, USA Abstract Background: Bisphenol A (BPA) is used to manufacture polymeric materials, such as polycarbonate plastics, and is found in a variety of consumer products. Recent data show widespread BPA exposure among the U.S. population. Objective: Our goal in the present study was to determine the temporal variability and predictors of BPA exposure. Methods: We measured urinary concentrations of BPA among male and female patients from the Massachusetts General Hospital Fertility Center. Results: Between 2004 and 2006, 217 urine samples were collected from 82 subjects: 45 women (145 samples) and 37 men (72 samples) . Of these, 24 women and men were partners and contributed 42 pairs of samples collected on the same day. Ten women became pregnant during the follow-up period. Among the 217 urine samples, the median BPA concentration was 1.20 µg/L, ranging from below the limit of detection (0.4 µg/L) to 42.6 µg/L. Age, body mass index, and sex were not significant predictors of urinary BPA concentrations. BPA urinary concentrations among pregnant women were 26% higher (–26%, +115%) than those among the same women when not pregnant (p > 0.05) . The urinary BPA concentrations of the female and male partner on the same day were correlated (r = 0.36 ; p = 0.02) . The sensitivity of classifying a subject in the highest tertile using a single urine sample was 0.64. Conclusion: We found a nonsignificant increase in urinary BPA concentrations in women while pregnant compared with nonpregnant samples from the same women. Samples collected from partners on the same day were correlated, suggesting shared sources of exposure. Finally, a single urine sample showed moderate sensitivity for predicting a subject's tertile categorization. Key words: bisphenol A, endocrine disruptors, environment, human, pregnancy. Environ Health Perspect 116: 173–178 (2008) . doi:10.1289/ehp.10605 available via http://dx.doi.org/ doi:10.1289/ehp.10605 available via http://dx.doi.org/ [Online 6 November 2007] Address correspondence to R. Hauser, Harvard School of Public Health, Department of Environmental Health, Environmental and Occupational Medicine and Epidemiology, 665 Huntington Ave., Building 1, Room 1405, Boston, MA 02115 USA. Telephone: (617) 432-3326. Fax: (617) 432-0219. E-mail: rhauser@hohp.harvard.edu We gratefully acknowledge the technical assistance of A. Bishop and J. Reidy (CDC) in measuring the urinary concentrations of BPA. This work was supported by grants ES09718 and ES00002 from the National Institute of Environmental Health Sciences, and grant OH008578 from the National Institute for Occupational Safety and Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Institute of Environmental Health Sciences, National Institutes of Health ; the National Institute for Occupational Safety and Health ; or the Centers for Disease Control and Prevention. The authors declare they have no competing financial interests. Received 27 June 2007 ; accepted 5 November 2007. |
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Bisphenol A (BPA) is used to manufacture
polymeric materials used for a variety of consumer products.
These polymers include epoxy resins that are used to line
food
cans (Kang et al. 2003), polyester-styrene (Factor 1996), and
polycarbonate plastics used for baby bottles and other
containers (Brede et al. 2003). These polymeric resins and
plastics may also be used in some dental sealants (Sasaki et
al. 2005) and fillings (Joskow et al. 2006), adhesives, protective
coatings, flame retardants (Samuelsen et al. 2001), and
water-storage tanks and supply pipes (Bae et al. 2002). BPA is
polymerized but degrades into its monomeric form over time,
which can be accelerated by heat exposure (Robeson 1985). The
monomeric form can leach from its source into adjacent
materials, such as into water or food products. Several studies
have demonstrated detectable BPA levels in packaged foods that
were contained in wrapping or cans coated with BPA
(Lopez-Cervantes and Paseiro-Losada 2003). Most human exposure
is believed to be via ingestion (Kang et al. 2006).
Recent data have shown widespread exposure
to BPA among the U.S. population. In 2,517 participants ≥ 6
years of age in the 2003–2004 National Health and Nutrition Examination
Survey (NHANES III), > 92% of urine samples had detectable
concentrations of BPA (Calafat et al. 2008). Other researchers
have also measured detectable concentrations of BPA in a
variety of human body fluids and some tissues. Of potential
concern to reproductive and developmental health end points is
the presence of BPA in follicular fluid and amniotic fluid
(Ikezuki et al. 2002), umbilical cord blood (Schonfelder et al.
2002), and breast milk (Sun et al. 2004). In studies published
as early as 1936 (Dodds and Lawson 1936), BPA has been shown
to
have estrogenic properties. These findings have been confirmed
in several subsequent studies (Hong et al. 2006; Singleton et
al.
2006). Human data on the potential health effects of BPA
exposure are limited.
Adult humans metabolize
BPA via hepatic glucuronidation and sulfation. The biologic half-life
of BPA
is
approximately 6 hr, with nearly complete urinary excretion in
24 hr (Volkel et al. 2002). Therefore, urinary BPA
concentrations primarily reflect exposures that occurred within
the last few days preceding the collection of the urine
specimen. However, because health end points of interest are
likely associated with windows of exposure consisting of time
intervals longer than a few days, information about the
temporal variability of urinary concentrations of BPA is needed
to optimize the design of exposure assessment in epidemiologic
studies. Currently, published data on the temporal variability
of urinary BPA concentrations are limited. Most studies include
only a single urine sample that may or may not reflect an
individual's long-term exposure level. Furthermore,
characteristics that may predict concentrations of BPA, such
as sex, age, and body mass index (BMI), have not been explored
in
a large sample of adult subjects.
Temporal variability in
exposure to BPA can result from changes in exposure sources,
such as diet and
product use, and from changes in BPA metabolism. Therefore, an
individual's BPA exposure depends on a variety of
factors, and it is likely that concentrations of BPA would vary
considerably over short periods, such as days. Although urinary
BPA concentrations accurately measure a person's exposure
at a single point in time, determining exposure over time
intervals of weeks or months requires multiple measurements.
Therefore, we designed the present study to examine the
temporal variability in BPA concentrations. We also explored
the ability of a single urine sample to predict an
individual's longer-term exposure, over weeks or months.
Finally, we also investigated the association of urinary BPA
concentrations with age, BMI, sex, and pregnancy status. In
regard to epidemiologic studies, this information can be used
for designing exposure assessment strategies and for adjusting
for measurement error in BPA exposure.
Subjects. Study subjects were male
and female partners seeking infertility evaluation and treatment
at the
Massachusetts General Hospital Fertility Center. They were
recruited between November 2004 and April 2006. Partners
underwent ovulation induction with timed intercourse or timed
intrauterine insemination and assisted reproductive
technologies, which included in
vitro fertilization
and intracytoplasmic sperm injection. Fertility center couples
that
conceived naturally were also enrolled. Subjects were followed
from recruitment throughout their treatment cycles until either
a live birth or the discontinuation of treatment. Biochemical
pregnancy was determined with a positive HCG (human
chorionic gonadotropin) level (> 6.0 IU/L). Clinical
intrauterine pregnancy was confirmed by the presence of a fetal
heartbeat detected by transvaginal ultrasound scan.
The study was approved by the Human
Studies Institutional Review Boards of the Massachusetts
General Hospital, Harvard School of Public Health, the Centers
for Disease Control and Prevention (CDC), and the University
of
Michigan. Subjects signed an informed consent after the study
procedures were explained and all questions were answered.
Men 18–55 years of age and women
18–45 years of age were eligible. Men who had undergone
a vasectomy were ineligible. Most study patients cited the lack
of time as the primary reason for not participating. A research
nurse administered a questionnaire to collect data on date of
birth, race/ethnicity, medical history, smoking history, and
lifestyle factors.
Urine sample collection. Both men
and women provided a spot urine sample at the time of recruitment
and at subsequent visits during
treatment cycles, as well as at post-treatment clinical
appointments. Women also collected three urine samples during
pregnancy, one during each trimester. Urine was collected in
a
nonsterile clean polypropylene container. After measuring
specific gravity (SG), the urine was divided in aliquots and
frozen at –80°C. Samples were shipped on dry ice
overnight to the CDC.
Urinary BPA measurements. We measured
the total urinary concentration of BPA (free plus conjugated species)
using online solid-phase
extraction (SPE) coupled to isotope
dilution–high-performance liquid chromatography
(HPLC)-tandem mass spectrometry (MS/MS) on a system constructed
from several HPLC Agilent 1100 modules (Agilent Technologies,
Wilmington, DE) coupled to a triple quadropole API 4000 mass
spectrometer (Applied Biosystems, Foster City, CA) (Ye et al.
2005). First, 100 µL of urine was treated with β-glucuronidase/sulfatase
(Helix pomatia, H1; Sigma Chemical Co., St. Louis, MO) to hydrolyze
the BPA-conjugated species. BPA was then retained and
concentrated on a C18 reversed-phase size-exclusion SPE column
(Merck KGaA, Germany), separated from other urine matrix
components using a pair of monolithic HPLC columns (Merck
KGaA), and detected by negative ion-atmospheric pressure
chemical ionization-MS/MS. The limit of detection (LOD) for BPA
in a 0.1-mL urine sample was 0.36 µg/L. Low-concentration
(~ 4 µg/L) and high-concentration (~ 20 µg/L)
quality control materials, prepared with pooled human urine,
were analyzed with standard, reagent blank, and unknown samples
(Ye et al. 2005). BPA concentrations < LOD were assigned a
value equal to one-half the LOD (Hornung and Reed 1990) prior
to adjustment by SG.
The first 25 urine samples collected were
analyzed for the concentration of the free species of BPA using
a method similar to the one described above, but without β-glucuronidase/sulfatase
treatment. In agreement with published reports (Volkel et al.
2002), the percentage of free BPA was essentially zero.
Therefore, for the remainder of the urine samples, we measured
only the total BPA concentration.
Figure 1. Within-couple variability shown by urinary
SG-adjusted BPA concentrations among female (diamonds and solid
lines) and male
(squares and broken lines) partners with at least two urine
samples collected on the same day (n = 11 couples).
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Table 1.
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Table 2.
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Table 3.
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Table 4.
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Several methods are used to adjust for
urine volume (Boeniger et al. 1993; Teass et al. 1993).
However, because organic compounds, such as phenols, that are
glucuronidated in the liver are eliminated by active tubular
secretion (Boeniger et al. 1993), creatinine adjustment may not
be appropriate (Teass et al. 1993). Additionally, creatinine
concentrations may be confounded by muscularity, physical
activity, urine flow, time of day, diet, and disease states
(Boeniger et al. 1993; Teass et al. 1993). For these reasons,
we used SG rather than creatinine. Urinary BPA concentrations
were normalized for dilution using the formula Pc =
Px [(1.024 – 1)/(SG – 1)],
where Pc is the SG-corrected
BPA concentration (in micrograms per liter), P is the observed
BPA concentration (in micrograms per liter), and SG is the specific
gravity of the urine sample (Boeniger et al. 1993; Teass et al.
1993).
SG was measured using a handheld refractometer (National
Instrument Company Inc., Baltimore, MD), which was calibrated
with deionized water before each measurement.
Statistical analysis. Descriptive statistics and distributions of urinary
BPA concentrations were tabulated and compared among
demographic categories. We constructed graphs to visually and
qualitatively compare BPA concentrations within and between
subjects over time. Using SAS software (version 9.1; SAS
Institute Inc., Cary, NC), mixed effects models were fit to
determine the association of urinary BPA concentrations (log10) with
age, BMI, sex, and pregnancy status. Each model included the
predictor of interest and SG as fixed effects. To account for
possible correlation of measurements, random effects were
included initially for subject, couple, and within-couple
specimen collection date. The variance component for couple was
estimated to be zero and was dropped from the models, but the
random effects for subject and within-couple collection date
were retained. Full covariate data were available for all
specimens, so information from all samples was used in the
analyses.
To explore the nature of within-couple
correlation, we regressed the geometric mean of SG-adjusted BPA
measurements from the female partner on that from the male
partner. Another analysis compared BPA measurements
(SG-adjusted and log10-transformed) of the female to those of the male
when the specimens were collected on the same date. In this
model, a random effect was included to account for a possible
correlation due to repeated measurements from the same couple.
We calculated the sensitivity,
specificity, and positive predictive value of a single urine
sample for predicting high BPA tertile by comparing predicted
and observed classifications for agreement (Hauser et al. 2004;
Meeker et al. 2005). Positive predictive value is the
probability that a person is actually in the exposure group of
interest, given that they were classified in that group based
on the single urinary BPA value that was available. BPA
tertiles were determined for the SG-adjusted BPA concentrations
among all 82 subjects. For those with more than one sample, we
used the subject's geometric mean value in the tertile
classification. A contingency table was then constructed to
display the level of agreement between each subject's
"true" tertile classification as determined by the
geometric mean value of their repeated samples and their
tertile classification predicted by each of their single repeat
samples. Only subjects with three or more urine samples (31 subjects
with a total of 149 urine samples) were included in the
contingency tables. After combining contingency tables for all
subjects with three or more samples, we calculated sensitivity,
specificity, and positive predictive value for the ability of
a
given single urine sample to classify a subject in the highest
BPA tertile.
We then calculated the sensitivity,
specificity, and positive predictive value of two urine samples
from an individual to classify subjects in the highest BPA
tertile. This analysis was limited to subjects with at least
six repeat urine samples (n = 8 subjects who contributed a total
of 67 samples). Geometric means of all possible combinations
of sample pairings
from each individual were used in the analysis as the predicted
value. The geometric mean value from all possible
within-subject combinations was then compared with the
geometric mean value of their repeated samples, used to
determine their "true" BPA tertile classification.
As above, contingency tables were then constructed. The goal of
the validity analysis was to simulate and compare the ability
of exposure assessments that involve one or two urine samples
to predict a subject's "true" longer-term
exposure.
In both of these analyses,
the single or two urine samples used to predict a subject's tertile
classification are not independent predictors of their overall
geometric mean value because they are also used to calculate
the subject's geometric mean. For instance, when we
calculated the geometric mean for subjects with three or more
urine samples, the single urine sample evaluated for its
predictive ability was included in the geometric mean
calculation for that subject. Because of this, we limited these
analyses to subjects with three (or six) or more urine samples
to minimize the structural dependence between the predicted
value based on the single sample and the "true"
observed values based on the geometric mean of that
subject's full complement of samples.
Urinary BPA concentrations were measured
in 217 samples collected from 82 subjects. On average, each
subject contributed 2.6 urine samples, ranging from 1 (n = 34
subjects) to 13 samples (n = 1 subject). Twenty-nine (13%) urine
samples had BPA concentrations < LOD. Forty-five women contributed
145 urine samples and 37 men contributed 72 specimens. Among
subjects,
24
women (93 specimens) and 24 men (53 specimens) were partners.
Of the urine samples from these 24 couples, 42 pairs of
specimens were time-matched (collected on the same day). Eleven
couples had two or more time-matched urine samples, and 10 couples
had a single time-matched urine sample. Three couples had no
time-matched urine samples.
The study subjects ranged
in age from 28 to 54 years, with a mean ± SD of 35.5 ± 4.4 years
(Table 1). Seventy subjects (85%) were Caucasian. Only five
subjects (three men and two women) were current smokers. BMI
(in kilograms per square meter) ranged from 16.5 to 44.7, with
a mean ± SD of 26.8 ± 5.8. Ten of the women
became pregnant during the follow-up period, as confirmed by
the presence of a fetal heart beat on ultrasound. One pregnancy
loss occurred.
Among the 217 urine samples,
the median BPA concentration was 1.20 µg/L (25th percentile, 0.60;
75th percentile, 2.70), with a range from < LOD of 0.4 µg/L
to 42.6 µg/L. However, because the number of urine
samples collected from subjects varied widely, subjects
contributed differentially to the median and percentiles of the
urinary BPA concentrations. For instance, a subject with four
urine samples contributed four times as many data points as a
subject with one sample. In addition, multiple urine samples
from a given subjects are not independent. To account for both
of these factors, we calculated the percentiles of the urinary
BPA distribution based on the geometric mean of the urinary BPA
concentrations for each subject with two or more urine samples
and the single urine sample concentration for subjects with one
sample (Table 2). After accounting for these factors, the
median was 1.30 µg/L (25th percentile, 0.72; 75th
percentile, 2.09). The median was slightly lower among women
(1.08 µg/L) than among men (1.40 µg/L). Urinary
concentrations unadjusted for SG (Table 2) allow for
comparisons with other study populations, because few studies
have used SG to adjust for urinary dilution.
Because spot urine
samples were collected at different times throughout the day,
we explored whether time
of day was associated with urinary SG-adjusted BPA
concentrations (Table 3). Urine samples collected before 0900
hours (time of collection ranged from 0530 to 0859 hours) had
a
median of 2.4 µg/L compared with medians of 1.92 µg/L
for samples collected from 0900 to 1159 hours, whereas samples
collected between noon and 1559 hours had a higher median of
3.24 µg/L. Median BPA then decreased to 1.62 µg/L
among samples collected after 1600 hours (range 1600 to 1830
hours).
In mixed regression analysis, there was a statistically
significant difference in geometric mean SG-adjusted BPA
concentration by time of day when urine samples were collected
(p =
0.01 for comparison of samples collected between noon and 1559
hours with those collected after 1600 hours).
Although age, BMI,
sex, and pregnancy status were not statistically significant
predictors of urinary
BPA concentrations, we found weak associations after reverse
transformation of the regression coefficients. Controlling for
SG, BPA concentrations increased by 2% [95% confidence interval
(CI), –2 to 6%) for each year age increased. To explore
associations of BMI with urinary BPA concentrations, BMI was
categorized as underweight (< 20), normal (20–24.9),
overweight (25–29.9), or obese (≥ 30).
Compared with normal BMI, underweight BMI was associated with
a 49% increase
(95% CI, –25 to 197%) in BPA concentration, overweight
BMI with an 8% increase (95% CI, –27 to 61%), and obese
BMI with a 3% decrease (95% CI, –38 to 51%). BPA
concentrations for women were 9% lower (95% CI, –35 to
28%) than those for men, and concentrations for urine samples
collected from women while pregnant were 26% higher (95% CI,
–26 to 115%) than urine samples collected from
nonpregnant women. Restricting to the 10 women who became
pregnant during follow-up, samples collected while women were
pregnant had concentrations 33% higher (95% CI, –33 to
165%) than those collected prepregnancy (n = 49 samples).
To investigate within-couple
correlation of urinary BPA concentrations, we first noted that
the
covariance parameters in the mixed-effects models were
estimated to be approximately 0.04 for subject, 0.04 for
within-couple collection date, and 0.11 for residual variance.
Because the variance component for couples had been estimated
to be zero, these numbers suggest that BPA concentrations
between partners will correlate substantially only when the
measurements are taken on the same day. As a second approach,
we used the geometric mean of SG-adjusted BPA concentrations
as
an average exposure measurement for each individual; using
ordinary linear regression, we compared the female's
geometric mean with that of her male partner (n = 24 couples).
We observed no significant association between the means (Spearman
correlation = 0.04, p = 0.84); similar results were found using
arithmetic means or arithmetic means on the log10 scale
(p =
0.92 and 0.84).
However, when female BPA concentration
(SG-adjusted and log10-transformed) on a particular
day was compared with that of her male partner on the same day
(n = 42 pairs of
day-matched, couple-matched specimens), a moderately strong
association was found (Figure 1). Using a linear mixed model
accounting for correlation from repeated observations on the
same couple by inclusion of random effects, each one unit
increase in male log10 SG-adjusted BPA urine concentration
was estimated to correspond to a 0.428 increase (95% CI, 0.110
to
0.747) in the female partner's urine BPA concentration
from the same day (Spearman correlation = 0.36; p = 0.02).
Among subjects with at least three urine
samples, the calendar time between collection of the first and
last urine samples ranged from 14 to 482 days, with a mean
(median) of 172 (150) days. The time between collection of
first and last urine samples ranged from 150 to 482 days for
subjects with at least six samples, with a mean (median) of
304
(329) days.
Sensitivity and specificity
analyses to assess the ability of one urine sample to predict
a
subject's exposure tertile are shown in Table 4. The
proportion of subjects who "truly" were in the
highest exposure tertile (top 33%), identified as those with a
single urine sample collected anytime during the
subject's participation in the study (i.e., sensitivity)
was 0.64. The proportion of subjects who "truly"
were in the lowest exposure tertiles (e.g., first and second
tertiles) and classified as such (i.e., specificity) was 0.76.
The proportion of single urine samples that classified an
individual in the highest tertile who was "truly"
classified in the highest group (i.e., positive predictive
value) was 0.63. We also calculated these measures for the
ability of two urine samples to predict an individual's
geometric mean (Table 4). When two BPA samples were used to
classify each subject, we found increases in sensitivity
(0.67), specificity (0.84), and positive predictive value
(0.85).
Apart from a small study
in Japan on five subjects (four men and one woman) (Arakawa et
al. 2004), we
report some of the first data on long-term temporal variability
of urinary BPA concentrations among a large sample of both men
and women. We found temporal within-subject variability in
urinary SG-adjusted BPA concentrations. As suggested by earlier
small studies, we also found that men had slightly higher BPA
concentrations than women. Japanese researchers reported
associations of male sex and androgen levels with higher BPA
concentrations (Takeuchi and Tsutsumi 2002; Takeuchi et al.
2004). However, Kim et al. (2003) found that BPA urine
concentrations in males and females were similar. Further
exploration of a potential sex- or androgen-related
difference in urinary BPA concentrations is needed to resolve
the inconsistencies across limited studies.
To the best of our
knowledge, the present study is the first to compare urinary
BPA concentrations in
women before and during pregnancy. Although only 10 women
contributed data, there was a nonsignificant 33% increase in
urinary concentrations of BPA during pregnancy compared with
prepregnancy. During pregnancy, there are numerous physiologic
changes that may affect BPA distribution, metabolism, and/or
clearance. For instance, the glomerular filtration rate is
increased during pregnancy, creatinine clearance increases, and
in some pregnant women, urine output increases due to increased
metabolism of antidiuretic hormone. To explore whether changes
in urinary concentrations of BPA are partially due to changes
in urine SG during pregnancy, we regressed SG on pregnancy
status, clustering by subject. The estimated SG for pregnant
women was 0.0029 higher than for nonpregnant women (95% CI, –0.0014
to 0.0071; p = 0.19). Therefore, changes in SG during
pregnancy would contribute to a slightly lower SG-adjusted BPA
concentration, rather than an increase, as we observed during
pregnancy.
Other potential explanations for
differences in urinary BPA concentrations during pregnancy
include a) changes in exposure, such as an increased use of
products or in the consumption of foods that contain BPA; b)
changes in volume of distribution and/or altered sequestration
of BPA into
different body fluid compartments, such as amniotic fluid; and
c) changes in BPA metabolism and/or excretion. Application
of physiologically
based pharmacokinetic approaches is necessary to better
understand changes in BPA dynamics during pregnancy, but it is
beyond the scope of the present report.
Because exposure to BPA is thought to be
primarily via ingestion, we hypothesized that urinary BPA
concentrations will be more similar among individuals that are
partners than those who are not partners. We found evidence
of
a moderately strong relationship between urinary BPA
concentrations in samples collected on the same day among male
and female partners. This suggests that BPA exposure occurs
through a common household lifestyle factor, most likely diet.
This finding warrants further investigation because sources
of
BPA among the general population are unclear.
Interestingly, there appeared to be a
trend in urinary BPA concentrations by the time of day when the
sample was collected. Urinary BPA concentrations were highest
in the samples collected between 1200 and 1600 hours, compared
with morning or late afternoon/evening samples. This may
reflect dietary BPA exposure during the midday meal, because
BPA has a short half-life (Volkel et al. 2002). We did not
collect data on the time of day meals or foods were consumed
throughout the day, so we are unable to confirm this directly.
We also conducted sensitivity
and specificity analyses to determine the ability of one urine sample or a pair of urine samples to predict
long-term urinary BPA concentrations over several months.
Despite the presence of temporal variability in urinary BPA
concentrations, our sensitivity and specificity analyses
suggested that a single urine sample correctly classified
subjects into the highest BPA exposure tertile based on the
geometric mean of repeat samples for that subject. However,
there were several limitations to our approach. First, because
there was no gold standard to use as the "true"
urinary BPA concentration, we relied on using the geometric
mean of repeat urine sample concentrations. How well these
geometric means represent an individual's true exposure
is unclear. Furthermore, there is structural dependency between
the "true" urinary BPA concentrations and the
single or pair of urine samples that will overinflate the
sensitivity and specificity. Second, the timing of the
collection of the repeat urine samples was not balanced. For
instance, the duration between the collection of consecutive
repeat urine samples ranged from 3 days to a year or more, but
all samples were treated equally without respect to the time
between collection. Thus, although we found that two urine
samples improved the ability to predict BPA exposure tertiles,
the preferred temporal spacing of the two samples is currently
unclear. However, based on previous work on other nonpersistent
chemicals, such as phthalates, at least 1 month between samples
is preferable when the exposure duration of interest is over
several months (Hauser et al. 2004).
Despite a much longer span of time between
the collection of the first and last urine samples among
subjects in the two-sample sensitivity analysis, the predictive
ability was increased with the collection of a second sample.
For the subset included in the two-sample sensitivity analysis
(subjects with at least six samples), the average time interval
between samples was 304 days compared with 175 days among the
group of subjects included in the one-sample sensitivity
analysis (subjects with at least three samples). Because
samples from the two-sample sensitivity analysis represent a
much wider exposure period, we would not have been surprised
by
a lack of improvement in the two-sample analysis compared to
the one-sample analysis. However, our finding of increased
predictive ability in the two-sample analysis may suggest that,
because BPA exposure is ubiquitous and likely occurs daily,
urinary concentrations exist in a relatively pseudosteady state
over the course of months or years (National Research Council
2006).
The urinary BPA concentrations
found in the present study were within the range reported from
studies
in several countries, including Japan, Korea, and the United
States. In a nonrepresentative subset of NHANES III that
included men and women between 20 and 59 years of age, the
geometric mean urinary BPA concentration was 1.33 µg/L
(Calafat et al. 2005). Among girls 6–8 years of age,
Wolff et al. (2007) reported a geometric mean of 2.0 µg/L.
Yang et al. (2003) reported a geometric mean urinary BPA
concentration of 9.54 µg/L among 73 Koreans (34 men and
39 women) In another Korean study on 15 men and 15 women, Kim
et al. (2003) reported a mean (SE) urinary BPA concentration of
2.82 µg/L (0.73) and 2.76 µg/L (0.54),
respectively, with no difference by sex. Among 48 women in
Japan, Ouchi and Watanabe (2002) reported a median urinary BPA
concentration of 1.2 µg/L, with a range of 0.2–19.1
µg/L. Comparisons across studies are difficult because
they may be confounded by differences in timing and methods
of
urine collection, containers used, analytical methods to
quantify BPA, different limits of detection, and methods for
correction of urinary dilution. Additionally, country-specific
regulations on the use of BPA and occupational exposure to BPA
may affect urinary concentrations. Countries with bans on the
use of BPA products for packaging foods may have populations
with lower urinary and serum BPA concentrations. However, we
are not aware of data showing population differences in
exposure before and after bans.
Despite within-person variability
in urinary BPA concentrations, a single sample is predictive
of
long-term exposure (over weeks to months) and provides good
sensitivity to classify individuals into tertiles in
epidemiologic studies. The addition of a second urine sample
improved this classification ability. Although we did not find
strong relationships of urinary BPA concentrations with age,
sex, BMI, and pregnancy status, these associations were
suggestive and are worthy of further follow-up. Discovery of
whether urinary concentrations increase during pregnancy,
reflecting either increased exposure or alterations in
metabolism during pregnancy, is especially important. The
correlation between urinary BPA concentrations among male and
female partners suggests that BPA exposure is shared through
diet or common residential source(s). Finally, replication of
this study in other populations, including the general
population, should be conducted to determine whether predictors
vary across populations. In addition, further work needs to be
done to determine the utility of urine samples to define an
individual's exposure level during pregnancy. |
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[References Listed in PubMed]
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