The
variability and predictors of urinary concentrations of phthalate
metabolites in preschool-aged children have not been thoroughly examined.
Additionally, the impact of temporal changes in the use and restriction
of phthalates in children’s products has not been assessed.
Our objective was to identify demographic, behavioral, and temporal
predictors of urinary phthalate metabolite concentrations in young
children. Between 2004 and 2011, we collected up to five urine samples
from each of 296 children participating in a prospective birth cohort
during annual study visits at ages 1–5 years. We used linear
mixed models to calculate intraclass correlation coefficients (ICCs),
a measure of within-individual reproducibility, and identify demographic
predictors of urinary phthalate metabolites. We used multivariable
linear regression to examine cross-sectional relationships between
food packaging or personal care product use and phthalate metabolites
measured at age 5 years. Across annual measurements, monoethyl phthalate
exhibited the least variation (ICC = 0.38), while di-2-ethylhexyl
phthalate (ΣDEHP) metabolites exhibited the most variation (ICC
= 0.09). Concentrations changed with age, suggesting age-related changes
in phthalate exposure and perhaps metabolism. Our findings suggest
that fast food consumption may be a source of butylbenzyl phthalate
and di-isononyl phthalate (DiNP) exposure, and some personal care
products may be sources of diethyl phthalate exposure. Concentrations
of ΣDEHP metabolites decreased over the study period; however,
concentrations of DiNP metabolites increased. This finding suggests
that manufacturer practices and regulations, like the Consumer Product
Safety Improvement Act of 2008, may decrease DEHP exposure, but additional
work characterizing the nature and toxicity of replacements is critically
needed.
National Institutes of Health, United Statesdocument-id-old-9es501744vdocument-id-new-14es-2014-01744vccc-priceIntroduction
Phthalates are used
in a range of commercial products, resulting
in ubiquitous human exposure.1,2 Low molecular weight
(LMW) phthalates, such as diethyl phthalate (DEP), di-n-butyl phthalate (DnBP), and di-isobutyl phthalate (DiBP), are commonly
used as solvents in personal care products, including perfumes, lotions,
and cosmetics,3,4 and as excipients in medications.5 High molecular weight (HMW) phthalates, such
as di-2-ethylhexyl phthalate (DEHP), butyl benzyl phthalate (BBzP),
di-n-octyl phthalate (DnOP), di-isononyl phthalate (DiNP), and di-isodecyl
phthalate (DiDP), are used to add flexibility to plastics.6,7 Adults, infants, and children are routinely exposed to both LMW
and HMW phthalates from personal care products, food packaging, and
vinyl flooring.8−12
Early life exposure to phthalates may be associated with adverse
health outcomes in childhood, including obesity,13 altered neurodevelopment,14−16 and asthma or allergic
symptoms.17 However, previous epidemiological
studies have typically measured phthalate metabolites in one spot
urine sample. Because phthalate exposure is likely episodic and phthalate
metabolites have short biological half-lives, urine concentrations
can vary considerably within individuals.2,18−20 Sustained exposure could result from contact with
phthalates present in household dust, although concentrations in indoor
environments can also vary.21 Thus, phthalate
exposure misclassification is an important consideration in epidemiological
studies.
In response to growing concern about potential health
impacts of
phthalate exposure, the Consumer Product Safety Improvement Act (CPSIA)
of 2008 banned the use of several phthalates in children’s
toys and other child care articles in the United States. Specifically,
DEHP and DnBP were banned from all children’s toys, while DINP,
DIDP, and DnOP were banned from children’s toys that are more
likely to be placed in a child’s mouth.22 In addition, the patterns of phthalate use in consumer
products have changed, likely in response to concerns over the potential
toxicity of these chemicals.23
One
previous study assessed temporal variability in urinary phthalate
metabolite concentrations over a six month period among 6–10
year old minority children in New York City,2 while another assessed spot urinary metabolite concentrations among
5 and 6 year olds in Germany.24 However,
we are not aware of any studies evaluating the variability or predictors
of urinary phthalate metabolite biomarkers among toddlers or preschool
aged children. In addition, information is needed to identify potential
sources of phthalate exposure and evaluate whether regulations, like
the 2008 CPSIA, have reduced children’s phthalate exposures.
Our objective was to characterize variability in phthalate metabolite
urinary concentrations and determine if demographic, behavioral, and
temporal factors predicted urinary phthalate metabolite concentrations
in young children using a robust, longitudinal study design.
Materials
and MethodsStudy Participants
Our study sample comprised mothers
and their children participating in the Health Outcomes and Measures
of the Environment (HOME) Study, an ongoing prospective birth cohort
in Cincinnati, Ohio. Participant recruitment and eligibility criteria
have been previously described.25 Of 1263
eligible pregnant women, 468 enrolled in our study (37%) between March
2003 and January 2006. The current analysis was restricted to 327
children for whom we had at least one urinary phthalate metabolite
measurement from one of five annual visits conducted between 1 and
5 years of age. Institutional review boards at Cincinnati Children’s
Hospital Medical Center and the Centers for Disease Control and Prevention
(CDC) approved this study, and all mothers provided written informed
consent for themselves and their children prior to participation.
Urinary Phthalate Metabolite Concentrations
Children
provided urine samples during annual study visits between 2004 and
2011, which included an annual clinic visit at ages 1–5 years
and an annual home visit at ages 1–3 years. A subset of 61
participants provided urine samples at both the home and clinic visit at the 1, 2, or 3 year study visit (n = 16, 25, and 26 respectively). In our primary analyses, we gave
priority to samples collected at the clinic visit if a child provided
a urine sample at both clinic and home visits.
Prior to sample
collection, each child’s genital area was wiped with a phthalate-free
Wet Nap by their caregiver. For children who were not toilet trained,
we collected urine samples by placing a surgical insert into a clean
diaper at the beginning of the study visit. We checked the diapers
for urine at the end of the study visit. If urine was present and
the diaper was free of stool, the insert was placed into a polyethylene
urine collection cup, and urine was later expressed from the insert
with a syringe in the laboratory. For children who were in the process
of being toilet trained, a training potty was lined with inserts to
maximize urine collection. For children who were toilet trained, urine
samples were collected directly into a urine collection cup with the
aid of the child’s caregiver. All samples were refrigerated
for <24 h prior to processing and then stored at −20 °C
until shipment to the CDC, where they were stored at ≤−20
°C until analysis.
We measured 11 phthalate metabolites,
including mono-2-ethylhexyl
phthalate (MEHP), mono-2-ethyl-5-hydroxyhexyl phthalate (MEHHP), mono-2-ethyl-5-oxohexyl
phthalate (MEOHP), mono-2-ethyl-5-carboxypentyl phthalate (MECPP),
monobenzyl phthalate (MBzP), mono-3-carboxypropyl phthalate (MCPP),
monocarboxyoctyl phthalate (MCOP), monocarboxynonyl phthalate (MCNP),
monoethyl phthalate (MEP), mono-n-butyl phthalate
(MnBP), and monoisobutyl phthalate (MiBP), in urine (μg/L) using
previously described methods26 described
in detail in the Supporting Information (SI) (Text S1). We created a summary DEHP metabolite measure (∑DEHP)
by calculating the molar sum of MEHP, MEHHP, MEOHP, and MECPP. The
molar sum was calculated by dividing each metabolite concentration
by its molar mass and then summing the individual metabolite concentrations
(μmol/L). We were not able to measure MEHP, MnBP, or MiBP in
urine samples collected at 1, 2, and 3 year visits due to phthalate
contamination from the diaper inserts. Because MEHP contributed relatively
little to ∑DEHP metabolite concentrations at 4 and 5 years
of age, (Table S1, SI) the missing MEHP
values are not likely to substantively affect the ΣDEHP metabolite
summary measure from 1, 2, and 3 years of age.
Predictors of Phthalate
Concentrations
A computer-assisted
questionnaire was administered by trained research staff to collect
demographic information from participating mothers. During pregnancy,
we collected information on maternal race, maternal education, and
other sociodemographic variables. We collected data on the sex of
the child from hospital medical charts, and on the race of the child
and household income using questionnaires administered at annual visits
in early childhood. We measured serum cotinine in samples collected
at the 1, 2, and 3 year visits, which were averaged together for each
participant as a summary measure of second-hand smoke exposure over
the entire study period.
At the 5 year follow-up visit, we asked
mothers questions about their child’s use of plastic food-packaging
and personal care products. These included how often their child ate
or drank food stored or heated in plastic, fast food, or prepackaged
beverages, and if they had done so in the 48 h prior to the study
visit. We also asked if their child had used various personal care
products, including shampoo, conditioner, soap, hand sanitizer, hairspray
or gel, sunscreen, makeup, or nail polish in the 48 h prior to the
study visit.
Statistical Analysis
We did not
normalize phthalate
metabolite measurements by creatinine values (i.e., standardizing
each individual phthalate value for the creatinine concentration of
that specific sample) because changes in kidney function, muscle mass,
and other physiological factors that occur during childhood influence
urinary creatinine excretion. Thus, comparing urinary creatinine or
creatinine-normalized biomarker concentrations between a one and a
five year old may be inappropriate.27 As
an alternative, we compared methods of adjustment for urine dilution
(i.e., including creatinine as a separate covariate in regression
models) by calculating intraclass correlation coefficients (ICC) for
phthalate metabolites using three models: unadjusted for urine creatinine;
adjusted for urine creatinine; and adjusted for age-specific urine
creatinine z-score. We calculated urine creatinine z-scores separately
for each annual study visit to avoid comparing urine creatinine levels
in children of different ages.
We calculated ICCs using random
intercept linear mixed models with an unstructured covariance matrix
to estimate between- and within-subject variability of log10-transformed urinary phthalate metabolite concentrations. ICCs are
a measure of the reproducibility of a measurement within an individual,
where a value of zero indicates no reproducibility and a value of
one indicates perfect reproducibility.
We calculated ICCs for
annual phthalate metabolite measurements
over the entire study period (i.e., annual ICC), using all participants
who had phthalate measurements from at least two annual visits. We
also calculated ICCs using the subset of participants who provided
urine samples at both the home and clinic portion of the 1, 2, and
3 year visits to quantify variability over a shorter time frame (i.e.,
short-term ICC). On average, these samples were collected 13 days
apart (range 1–42 days).
We used linear mixed models
to examine associations between urinary
phthalate metabolite concentrations and demographic and temporal variables.
Demographic variables such as sex and race of the child, maternal
education, and household income, as well as mean serum cotinine were
entered as fixed effects, while child age, and creatinine or creatinine
z-scores were entered as time-varying effects. We selected covariates
based on prior knowledge and biological plausibility that they might
be associated with both phthalate exposure and the predictors under
investigation. The outcome variables were log10-transformed
phthalate metabolite concentrations in μmol/L for the ∑DEHP
summary measure and μg/L for individual phthalate metabolites.
Beta estimates were exponentiated to obtain the multiplicative difference
between groups for categorical predictors or per unit change for continuous
predictors, and are presented as percent difference with a 95% confidence
interval.
We evaluated temporal changes in phthalate exposure
by examining
children’s urinary phthalate metabolite concentrations as a
function of age and time. We examined DiNP, DiDP, and DiBP metabolites
since use of these phthalates may have increased due to changes in
manufacturer practices. We evaluated BBzP, DnBP, DEP, and DEHP metabolites
due to more extensive restrictions on certain phthalate use in children’s
products and concern over their potential toxicity.22 Specifically, the CPSIA regulations went into effect in
early 2009 and could have reduced phthalate exposure in children born
in 2005–2006 since urine samples provided at 3, 4, and 5 years
of age would have been collected after the ban was in effect. Since
participants born in 2003 would be 5 years old in 2008 and all their
samples would have been collected before the ban, we created a dichotomous
“year of birth” variable to distinguish between children
born in 2003–2004 from those born in 2005–2006. We modeled
phthalate metabolite concentrations as a function of age, year of
birth, and their product interaction (age X year of birth). This model
allowed us to compare age and calendar time-related changes in phthalate
metabolite concentrations among children born in 2005–2006,
who would have been affected by the changes in phthalate use to those
born in 2003–2004, who would have been less affected by these
changes. We controlled these analyses for sex and race of the child,
household income, maternal education, mean serum cotinine, and creatinine
z-score.
We used multivariable linear regression to examine
food packaging
and personal care product use as predictors of urinary phthalate metabolites
measured at the 5-year visit. We assessed food packaging as a predictor
of the metabolites of DEHP, DiNP (i.e., MCOP), DiDP (i.e., MCNP),
and BBzP (i.e., MBzP) in urine, as these phthalates are potential
food contaminants.28,29 Similarly, we assessed personal
care product use as predictors of MEP in urine, as DEP is the parent
phthalate found in such products.30 We
included the covariates sex, race, household income, maternal education,
mean serum cotinine, creatinine z-score, and year of birth in all
models examining food packaging or personal care use as predictors
of urinary phthalate metabolites. When modeling the use of specific
personal care products as predictors of urinary phthalate metabolites,
we additionally controlled for the total number of other personal
care products used.
Results
A total of 327 children
provided at least one urine sample during
their first 5 years of life. Of these children, 296 (n = 1050 samples) had complete covariate information on race, sex,
household income, maternal education, serum cotinine, and urine creatinine
(Table S2, SI). At age five, 190 children
provided a urine sample and had complete covariate information. All
measured phthalate metabolites were detected in greater than 99% of
urine samples with the exception of MEHP, which was detected in 79%
of urine samples. Unadjusted measures of urinary ∑DEHP metabolite
concentrations did not change with age (Table S3, Figure S1, SI). We did, however, observe age-related trends
with some individual phthalate metabolites (Figure 1, Table S3, SI). Specifically,
as child age increased, MEP concentrations decreased slightly, while
MCOP concentrations increased.
Unadjusted urinary phthalate metabolite
concentrations in HOME
Study children (μg/L). Diamond indicates arithmetic mean, whiskers
indicate minimum and maximum, edges of box indicate 25th and 75th
percentile, and middle line indicates median. One year n = 277, 2 year n = 232, 3 year n = 234, 4 year n = 170, 5 year n = 201 (All subjects with at least 1 phthalate measurement).
Variability
The reproducibility
of urinary phthalate
concentrations within individuals was low for most metabolites, with
annual ICCs ranging from 0.09 for ∑DEHP metabolites to 0.39
for MEP over the entire study period (adjusted for creatinine z-score)
(Table 1). In general, phthalate metabolite
concentrations in samples collected approximately 2 weeks apart varied
less than in annually collected samples (e.g., ∑DEHP metabolites:
short-term ICC = 0.20, annual ICC = 0.09). Among the subset of participants
with urine samples collected at both the clinic and home portion,
short-term variability was generally lower when we looked at duplicate
sample pairs separately at 1, 2, and 3 years, rather than duplicate
sample pairs from all visit years together. However, short-term ICCs
fluctuated across visits for many phthalate metabolites (e.g., MEP:
visit 1 ICC = 0.50, n = 16; visit 2 ICC = 0.33, n = 25; visit 3 ICC = 0.76, n = 27), possibly
because of the relatively small number of participants who contributed
two urine samples at more than one study visit, or they were not consistently
the same individuals from year to year. Methods for urine dilution
adjustment (unadjusted, creatinine adjusted, creatinine z-score adjusted)
did not meaningfully change our reported measures of variability (Table 1).
Intraclass Correlation
Coefficient
of HOME Study Children’s Urinary Phthalate Metabolite Concentrations
Collected (A) Annually from 1–5 Years of Age and (B) Twice
∼2 Weeks Apart at 1–3 Years of Age<xref rid="tbl1-fn2" ref-type="table-fn">a</xref>
A: annual ICCs
B: short-term
ICCs
metabolite
allb
1 year
2 years
3 yrs
allb
unadjusted
N = 283 subjects; 1,070 samplesc
N = 16 subjects
N = 25 subjects
N = 27 subjects
N = 61 subjects; 136 samplesd
∑DEHPe
0.18 (0.10, 0.27)
0.35 (0.00,
0.61)
0.27 (0.00, 0.67)
0.44 (0.00, 0.73)
0.29 (0.05, 0.49)
MBzP
0.26 (0.17, 0.35)
0.51 (0.30, 0.63)
0.14
(0.00, 0.42)
0.56 (0.29, 0.74)
0.34 (0.09,
0.54)
MCPP
0.20 (0.12, 0.29)
0.57 (0.18, 0.85)
0.29 (0.00, 0.67)
0.45 (0.00, 0.75)
0.31 (0.09, 0.49)
MCOP
0.17 (0.09, 0.26)
0.54 (0.13,
0.85)
0.00 (0.00, 0.37)
0.16 (0.00, 0.50)
0.15 (0.00, 0.33)
MCNP
0.21 (0.13, 0.29)
0.71 (0.37, 0.86)
0.20
(0.00, 0.59)
0.25 (0.00, 0.70)
0.25 (0.09,
0.41)
MEP
0.36 (0.26, 0.45)
0.30 (0.08, 0.52)
0.39 (0.15, 0.61)
0.53 (0.13, 0.79)
0.32 (0.08, 0.53)
MnBPf
0.22 (0.02, 0.43)
N/Af
N/Af
N/Af
N/Af
MiBPf
0.30 (0.10, 0.49)
N/Af
N/Af
N/Af
N/Af
Creatinine
Adjusted
∑DEHPe
0.11 (0.03, 0.19)
0.41 (0.00, 0.85)
0.24 (0.00, 0.56)
0.52
(0.16, 0.81)
0.20 (0.00, 0.41)
MBzP
0.25 (0.18, 0.35)
0.26 (0.08, 0.42)
0.25 (0.03, 0.56)
0.61 (0.35, 0.75)
0.39 (0.19, 0.57)
MCPP
0.19
(0.11, 0.27)
0.60 (0.19, 0.91)
0.60 (0.21,
0.83)
0.34 (0.00, 0.63)
0.25 (0.07, 0.43)
MCOP
0.15 (0.06, 0.24)
0.50 (0.00, 0.86)
0.00 (0.00, 0.26)
0.22
(0.00, 0.59)
0.03 (0.00, 0.20)
MCNP
0.19 (0.09, 0.27)
0.72 (0.45, 0.91)
0.28 (0.00, 0.69)
0.17 (0.00, 0.79
0.19 (0.00, 0.38)
MEP
0.35
(0.22, 0.44)
0.46 (0.29, 0.61)
0.28 (0.00,
0.72)
0.66 (0.38, 0.85)
0.29 (0.00, 0.52)
MnBPf
0.20
(0.01, 0.39)
N/Af
N/Af
N/Af
N/Af
MiBPf
0.31 (0.06, 0.50)
N/Af
N/Af
N/Af
N/Af
Creatinine
z-Score Adjusted
∑DEHPe
0.09 (0.02, 0.16)
0.46 (0.07, 0.75)
0.28 (0.00, 0.53)
0.48 (0.26, 0.67)
0.20 (0.00, 0.40)
MBzP
0.25 (0.16, 0.34)
0.39 (0.22,
0.53)
0.42 (0.20, 0.68)
0.59 (0.35, 0.79)
0.36 (0.16, 0.55)
MCPP
0.19 (0.11, 0.26)
0.64 (0.43, 0.86)
0.59
(0.32, 0.78)
0.33 (0.07, 0.53)
0.25 (0.08,
0.43)
MCOP
0.13 (0.03, 0.22)
0.47 (0.22, 0.63)
0.00 (0.00, 0.11)
0.22 (0.00, 0.40)
0.03 (0.00, 0.20)
MCNP
0.20 (0.09, 0.28)
0.61 (0.51,
0.68)
0.24 (0.00, 0.53)
0.18 (0.00, 0.66)
0.19 (0.00, 0.38)
MEP
0.39 (0.26, 0.48)
0.50 (0.36, 0.67)
0.33
(0.02, 0.69)
0.76 (0.30, 0.88)
0.33 (0.04,
0.56)
MnBPf
0.16 (0.00, 0.38)
N/Af
N/Af
N/Af
N/Af
MiBPf
0.31 (0.07, 0.50)
N/Af
N/Af
N/Af
N/Af
creatinine
0.18 (0.08, 0.28)
0.45 (0.21, 0.65)
0.03
(0.00, 0.40)
0.30 (0.00, 0.54)
0.17 (0.00,
0.34)
ICC = intraclass correlation
coefficient; N/A = not available.
Models adjusted for visit number.
All participants with at least 2
phthalate measurements, but not necessarily complete covariate information.
Some participants provided
2 urine
samples in multiple years but are counted only once in the final column.
∑DEHP= Sum of MEHP,
MEHHP,
MEOHP, and MECPP.
MnBP and
MiBP measured only at 4
and 5 years of age.
Demographic
Predictors
Race predicted select urinary
phthalate concentrations, with black children having 91% (95% CI:
64, 123) higher MEP concentrations, but 26% (95% CI: 34, 17) lower
MCPP concentrations, compared to white children after adjustment for
confounders (Table 2). Children in the “Other”
race category (Asian, Pacific Islander, or American Indian) had higher
concentrations of MEP, MnBP, and MiBP compared to white children (Table 2), although this analysis was limited by the relatively
small number of children in the “Other” category (n = 19). Higher maternal education predicted lower concentrations
of all measured phthalates, with children of mothers who were college
graduates having 10%, 33%, and 36% lower concentrations of ∑DEHP
metabolites, MBzP, and MEP, respectively, compared to children of
mothers who did not graduate from high school. Boys had 12% (95% CI:
−23, 0.3) lower urinary concentrations of MEP compared to girls.
Children’s average serum cotinine levels did not predict urinary
phthalate metabolite concentrations after adjustment for other covariates.
Adjusted Difference in HOME Study
Children’s Urinary Phthalate Concentrations at 1-5 Years of
Age According to Sociodemographic Factors or Serum Cotinine Levels
(<italic>N</italic> = 296 With a Total of 1050 Repeated Measures)<xref rid="t2fn2" ref-type="table-fn">a</xref>
∑DEHPb
MBzP
MCPP
MCOP
MCNP
MEP
MnBPc
MiBPc
variable
N (%) or mean (SD)
% differenced (95% CI)
% differenced (95% CI)
% differenced(95% CI)
% differenced (95% CI)
% differenced (95% CI)
% differenced (95% CI)
% differenced(95% CI)
% differenced(95% CI)
Child Race
non-hispanic white
194 (66)
ref.
ref.
ref.
ref.
ref.
ref.
ref.
ref.
non-hispanic black
83 (28)
–6 (−17, 7)
–6
(−19, 10)
–26 (−34, −17)
–19 (−29, 8)
–9 (−19,
1)
91 (64, 123)
–18 (−33,
1)
2 (−17, 25)
othere
19 (6)
6 (−13, 30)
–1 (−23, 26)
–2 (−18, 16)
1 (−18, 24)
12 (−6, 34)
97 (55, 152)
41 (1, 96)
53 (10, 113)
Sex
female
161 (54)
ref.
ref.
ref.
ref.
ref.
ref.
ref.
ref.
male
135 (46)
–2
(−12, 10)
12 (−3, 28)
5
(−4, 16)
–2 (−13, 10)
–4 (−13, 6)
–12 (−23, 0.3)
–18 (−32, −1)
–15
(−30, 3)
Age (% change/year)
2.94 (1.47)
–2
(−5, 1)
–2 (−6, 1)
–0.2 (−3, 3)
21 (18, 26)
–6 (−9, −4)
–11 (−14,
−7)
–24 (−34, −13)
–13 (−23, −1)
Year of Birth
born 2003–2004
142 (48)
ref.
ref.
ref.
ref.
ref.
ref.
ref.
ref.
born 2005–2006
154 (52)
–15 (−24, −6)
–18 (−27,
−6)
–3 (−11, 6)
1
(−9, 13)
–4 (−12, 5)
–18 (−28, −7)
–19 (−32, 4)
–3 (−18, 15)
Household Income(% difference/$10,000)
62,276 (40,570)
0.5 (−1, 2)
–4 (−6, −1)
0 (−2, 2)
–0.4 (−2, 2)
–1 (−2, 1)
–2 (−4,
1)
0.3 (−3, 3)
–1 (−3,
2)
Maternal Education
less than grade 12
25 (8)
ref.
ref.
ref.
ref.
ref.
ref.
ref.
ref.
high school graduate
32 (11)
4 (−12, 23)
–21 (−35,
−3)
–11 (−24, 3)
2 (−14, 22)
–17 (−28, −4)
13 (−8, 38)
–15 (−35, 12)
–26 (−44, −3)
some college
77 (26)
7 (−5, 21)
–12 (−24, 2)
–1 (−11, 10)
–0.1 (−12, 13)
–11 (−20, −1)
–14
(−26, −1)
17 (−3, 42)
–2 (−19, 19)
college graduate
162 (55)
–10 (−19, 0.1)
–33 (−41, −24)
–17 (−25, −10)
–12 (−21,
−2)
–20 (−27, −12)
–36 (−44, −28)
–9
(−23, 8)
–8 (−23, 9)
Mean Cotinine (% difference/ng/mL)
0.66 (1.97)
1 (−2, 5)
5 (−0.1, 10)
1 (−3, 4)
–2 (−5, 2)
–1 (−5, 2)
0 (−5, 5)
3 (−2, 9)
0.5 (−5, 6)
Results adjusted for all other variables
listed in Table 2 and urinary creatinine z-score.
CI= confidence interval.
∑DEHP= MEHP, MEHHP, MEOHP,
and MECPP.
MnBP and MiBP
measured only at visits
4 and 5.
% Difference =
percent difference
in geometric means compared to the reference group for categorical
variables or for a one unit increase for continuous variables.
Other race = Asian, Pacific Islander,
or American Indian.
Food Packaging
and Personal Care Products
Eating fast
food at least once per week was associated with 35% higher MCOP (95%
CI: −2, 85) and 55% higher MBzP (95% CI: 9, 123) urine concentrations
compared to eating fast food less than once per week after adjustment
for covariates (Table 3). Five year-old children
who ate foods that had been stored in plastic at least once per day
had urinary MCOP concentrations 38% higher (95% CI: −2, 96)
than those who ate such foods less than once per week, while children
who ate foods that had been heated in plastic within the past 48 h
had MCOP concentrations 34% lower than those who did not (95% CI:
−56, −0.4). Urinary concentrations of the ∑DEHP
metabolites, MCNP, MCPP (a nonspecific metabolite of HMW phthalates
and a minor metabolite of DnBP), and MBzP were not associated with
eating food stored or heated in plastic. Drinking prepackaged beverages
within the past 48 h was associated with 29% higher (95% CI: 4, 62)
urinary MCPP concentrations, but was not associated with ΣDEHP
metabolite, MCOP, MCNP, or MBzP concentrations.
Adjusted Difference in HOME Study
Children’s Urinary Phthalate Metabolite Concentrations at 5
Years of Age According to Parent-Reported Child Food Packaging Use
and Diet (<italic>N</italic> = 190)<xref rid="t3fn2" ref-type="table-fn">a</xref>
∑DEHPb (μmol/L)
MBzP (μg/L)
MCPP (μg/L)
MCOP (μg/L)
MCNP (μg/L)
variable
N (%)
% differencec (95% CI)
% differencec (95% CI)
% differencec (95% CI)
% differencec (95% CI)
% differencec (95% CI)
Food Stored in Plastic
<1/week
15 (7.9)
ref.
ref.
ref.
ref.
ref.
1–6/week
80 (42.1)
25 (1,
56)
32 (−7, 86)
11 (−12,
40)
–4 (−28, 30)
9 (−12,
35)
≥1/day
62 (32.6)
–3 (−25, 25)
28 (−14, 91)
5 (−19, 38)
38 (−2, 96)
20 (−6, 53)
Food Stored in Plastic in
Past 48 h
no
39 (20.5)
ref.
ref.
ref.
ref.
ref.
yes
113 (59.5)
–9 (−27, 13)
15 (−19, 63)
0 (−21, 26)
–7 (−32, 26)
16 (−6, 44)
Food Heated in Plastic
<1/week
93 (48.9)
ref.
ref.
ref.
ref.
ref.
≥1/week
64 (33.7)
3 (−19,
30)
–3 (−32, 40)
–4
(−24, 23)
–3 (−30, 33)
11 (−11, 39)
Food Heated in Plastic in
Past 48 h
No
127 (66.8)
ref.
ref.
ref.
ref.
ref.
Yes
25 (13.2)
–14 (−36, 14)
–25 (−53, 19)
–28 (−47,
−3)
–34 (−56, −0.4)
–20 (−40, 5)
Fast Food
<1/week
85 (44.7)
ref.
ref.
ref.
ref.
ref.
≥1/week
72 (37.9)
–1 (−22, 25)
55 (9, 123)
19 (−7, 51)
35 (−2, 85)
11 (−11, 39)
Prepackaged Beverages
<1/week
53 (27.9)
ref.
ref.
ref.
ref.
ref.
1–6/week
65 (34.2)
1 (−20,
28)
15 (−20, 67)
22 (−5,
57)
15 (−17, 60)
17 (−6,
47)
≥1/day
37 (19.5)
–17 (−36, 7)
–29 (−53, 5)
14 (−12, 48)
16 (−19, 64)
1 (−21, 29)
Prepackaged Beverages in
Past 48 h
no
68 (35.8)
ref.
ref.
ref.
ref.
ref.
yes
83 (43.7)
16 (−7, 44)
–8 (−35, 29)
29 (4, 62)
18 (−12, 57)
1 (−17, 24)
Adjusting for sex,
race of child,
household income, maternal education, mean serum cotinine, urinary
creatinine z-score and year of birth. CI = confidence interval.
∑DEHP= MEHP, MEHHP, MEOHP,
and MECPP.
% Difference
= percent difference
in geometric means compared to the reference category.
Most participants used shampoo and
various types of soap within
48 h of urine collection, but less than 15% used hairspray or hair
gel, makeup, or nail polish. Recent use of hairspray or hair gel was
associated with 63% higher urinary MEP concentrations (95% CI: 7,
148) among 5 year-old participants after adjustment for covariates,
while the use of other personal care products was not (Table S4, SI).
Temporal Trends vs Age
Increasing
age and later year
of birth (2005–2006 compared to 2003–2004) were both
associated with lower concentrations of several phthalate metabolites
after adjusting for race, sex, household income, maternal education,
serum cotinine, and creatinine z-score (Table 2). The association between birth year and ∑DEHP metabolites
changed with age, where those born in 2005–2006 had increasingly
lower relative concentrations compared to those born in 2003–2004
as they got older, although this interaction was not statistically
significant after adjustment for creatinine z-score (p = 0.24) (Figure 2, Table S5, SI). In contrast, age was positively associated
with urinary MCOP concentrations and the association between birth
year and MCOP or MCNP concentrations changed with age, such that MCOP
and MCNP concentrations were higher among children born in 2005–2006
compared to those born in 2003–2004 (p-value
for interaction <0.0001 for both metabolites) (Figure 2). For instance, compared to children born in 2003–2004,
those born in 2005–2006 had 22% lower MCOP concentrations at
one year of age, but 33% higher concentrations at five years of age
(Table S5, SI).
Geometric mean concentrations
and smoothed regression of urinary
∑DEHP metabolites and MCOP between 1 and 5 years of age among
those born between 2003 and 2004 or 2005–2006. ∑DEHP
= sum of MEHP, MEHHP, MEOHP, and MECPP. Children born in 2003–2004
provided urine samples before the CPSIA went into effect, while children
born in 2005–2006 provided their 3, 4, and 5 year urine samples
after the CPSIA went into effect.
Discussion
Our longitudinal study design allowed us
to evaluate variability
of urinary phthalate metabolite concentrations during early childhood
over both short and long-term exposure periods, as well as the effect
of policy and manufacturer related changes in phthalate use during
the study period. In addition, our cross-sectional analysis allowed
us to examine specific consumer products as sources of phthalate exposure
in preschool aged children. Our findings suggest that exposure to
certain phthalates varies during early childhood by race, maternal
education, use of personal care products such as hairspray or gel,
consumption of fast food, and possibly consumption of food stored
in specific types of packaging. Our findings also suggest that changes
in manufacturer practices due to market-forces and the CPSIA of 2008,
which restricted DEHP use in children’s products, may have
resulted in decreased exposure to DEHP among study participants. However,
urinary concentrations of MCOP, a metabolite of DiNP, increased during
this same time period.
We found that phthalate metabolite concentrations
in spot urine
samples collected approximately 2 weeks apart were weakly to moderately
correlated, while concentrations measured a year or more apart were
less correlated. Since phthalates have biological half-lives of less
than 24 h,31,32 urinary metabolite concentrations
reflect only recent exposure. However, because some phthalate exposures
are linked to routine behaviors that may vary little over short periods
of time, a single spot urine sample may be a reasonable measure of
short-term exposure to these phthalates. This may be especially true
during infancy, when dietary variation tends to be limited and personal
care product use is a routine part of child care. For example, in
a study examining phthalate exposure among infants, the significant
association between recent use of baby lotion and urinary MEP concentrations
was strongest among infants less than 8 months old.9 Our results, which indicate that urinary MCOP, MCNP, and
MCPP concentrations measured 2 weeks apart varied less among one year-olds
than older children (Table 1), are consistent
with the hypothesis that exposures become more varied as children
mature. While a single spot sample may be sufficient to characterize
exposure over a relatively narrow time window (e.g., weeks), one spot
urine sample may not adequately capture exposure over months or years,
particularly for toddlers and preschool aged children, since diet
and personal care product use, as well as physiology, change considerably
over the first five years of life. Consistent with this hypothesis,
the annual ICCs reported in the present study are generally lower,
suggesting more variability, compared to ICCs reported in a number
of studies in adult populations.18−20,33
We observed less variability (e.g., higher reproducibility)
in
urinary MEP concentrations compared to other phthalate metabolites,
consistent with previous studies.18−20,33 This may be a result of the pathways by which most young children
are exposed to the parent compound DEP. DEP is found mainly in personal
care products, which are often used regularly, but their use varies
substantially between people. In contrast, ∑DEHP metabolites
show substantial within-person variation, likely due to diet being
the primary source of exposure.
It was difficult to separate
the effects of physiological and behavioral
patterns during child development from temporal changes in phthalates
used in consumer products over the study period on measured urinary
phthalate metabolite concentrations. Because age-related physiological
changes in kidney function and muscle mass during early childhood
affect creatinine excretion,27 the use
of creatinine to adjust for urine dilution is complicated. We observed
increasing urinary creatinine concentrations from 1 to 5 years of
age (SI Figure S2) and substantially lower
ICCs when using creatinine normalization (data not shown). As children
grow older and more independent, age related changes in behavior may
also affect phthalate exposures during this time. In addition, changes
in manufacturer practices and the implementation of the CPSIA in February
of 2009 further complicated this issue. Indeed, after controlling
for urine dilution using age-specific creatinine z-scores, we detected
differences in urinary ∑DEHP metabolite concentrations between
children born in 2003–2004 and those born in 2005–2006.
For example, at five years of age, children born later had lower ∑DEHP
metabolite concentrations, a phthalate targeted by CPSIA, but higher
MCOP concentrations compared to those born earlier.
Our data
are consistent with possible increasing use of DiNP in
consumer products in recent years, although the CPSIA also placed
some restrictions on the use of this phthalate in specific children’s
products.22 It is estimated that DiNP and
DiDP make up about 33% of the U.S. plasticizer market.34 Our results suggest that changes in manufacturer
practices and the CPSIA may have played a role in reducing exposure
to some key phthalates among the target population (children), as
the later born children had lower concentrations of ∑DEHP metabolites
and MCPP (a DnOP and DnBP metabolite) at all ages. Similar decreases
in urinary phthalate metabolite concentrations, specifically DEHP
metabolites, can be seen in Europe as well.35 However, HOME study children who provided urine samples after the
CPSIA went into effect had higher MCOP and MCNP concentrations than
children providing urine samples before the CPSIA. These are metabolites
of DiNP and DiDP, respectively, which may have increased in use as
DEHP was phased out. Similar trends were recently reported among children,
adolescents, and adults in data from the National Health and Nutrition
Examination Survey (NHANES) collected from 2001 to 2010, where urinary
DEHP metabolite, MnBP, and MBzP concentrations decreased over time,
while urinary MCOP, MCNP, and MiBP concentrations increased.23 The CPSIA, which limited phthalate usage in
children’s products, would not be expected to lead to the observed
decreases in phthalate exposure among older children and adults, suggesting
that other factors, such as additional regulatory pressures and consumer-driven
market forces, may have also played a role in decreasing exposure
to specific phthalates among children, as well as adults.
We
observed higher urinary MEP concentrations among blacks and
other nonwhite children compared to whites, but similar concentrations
of most other phthalate metabolites. This finding is consistent with
observations among older children in biomonitoring studies such as
NHANES.1,36 Higher urinary phthalate concentrations
among black and other nonwhite children could be due to differences
in the frequency or type of personal care products used.
Similar
to previous studies, we observed lower urinary MEP concentrations
in males compared to females.1,6 Among five year-olds
we also observed a positive association between the use of hairspray
or gel within the past 48 h and urinary MEP concentrations and 18
of the 22 participants who reported using these products were female.
We did not see associations between the use of other personal care
products and MEP concentrations, possibly due to the small number
of participants reporting use of most products or our reliance on
maternal report of children’s exposure history. Self-reported
information is often subject to misclassification, and a mother’s
recall of their child’s experience may result in additional
misclassification. For comparison, a study of phthalate exposure among
infants found that use of baby lotion was positively associated with
urinary MEP concentrations,9 while a recent
study of 8–13 year olds reported sex-specific positive associations
between urinary MEP concentrations and deodorant, cologne or perfume,
and hair conditioner use, but not use of hair spray or gel.12
We found that consumption of fast food
more than once a week was
associated with higher urinary MBzP and MCOP concentrations, although
it is uncertain if fast food packaging, fast food itself, or both
are sources of phthalate exposure. We also observed a positive association
between urinary MCOP concentrations and eating food stored in plastic
containers, but a negative association between MCOP and eating food
that had been heated in plastic within the past 48 h. Although these
associations did not reach statistical significance, these contrasting
findings make it difficult to reach a conclusion about exposure via
plastic food packaging among this population. Our 48 h window may
have been too long to detect meaningful differences in phthalate metabolite
concentrations, and we did not collect potentially important information
such as food type and food storage time and temperature.37 In addition, we were not able to identify the
type or brand of plastic food containers used and different plastic
formulations may contain different amounts of phthalate residues.
A study evaluating predictors of phthalates among older children also
did not observe an association between maternal report of exposure
to food packaging in the previous 48 h and urinary phthalate metabolites.12 However, researchers evaluating food packaging
as a source of phthalate exposure using dietary intervention observed
a significant decrease in urinary phthalate metabolite concentrations
when participants were provided catered meals with minimal plastic
packaging.10
A major limitation of
this analysis was that we used creatinine
to adjust for urine dilution. Because kidney function and muscle mass
are changing rapidly across the age range studied here, creatinine
normalization is not an ideal method for adjustment because it could
over- or underestimate exposure at different ages. As an alternative,
we included age-specific creatinine z-scores in regression models
to adjust for urine dilution. In addition, we did not ask participants
how often their children played with toys made of plastic, the age
of these toys, mouthing behaviors, or collect other information that
would have helped us more directly examine whether the temporal trends
in certain urinary phthalate metabolites were a result of the CPSIA.
We were also not able to report concentrations of the hydrolytic monoester
metabolites MEHP, MnBP, and MiBP in urine samples collected during
visits 1, 2, or 3 due to potential contamination from diaper inserts.9 Another limitation is our modest sample size,
which limits our ability to detect associations, especially for behavioral
factors that are less accurately reported. We also do not have measures
of phthalates in participant’s indoor environments, a potential
source of exposure particularly in this age group.11,34 Phthalate concentrations in household dust can be quite high,21 and exposure through this pathway may substantially
contribute to participant’s urinary phthalate metabolite levels.38 We also did not investigate maternal use of
personal care products as a potential pathway of child phthalate exposure,
although this could be pursued in a future analysis.
In conclusion,
urinary phthalate metabolite concentrations in young
children vary over time, likely due to a combination of age related
changes in exposure and perhaps metabolism, as well as changes in
the use of phthalates in commercial products. Consistent with previous
reports in adults,29 our findings suggest
that personal care products are a source of exposure to DEP, and that
fast food consumption may be a source of exposure to DiNP and BBzP
among young children. Finally, we found that DEHP exposure may have
decreased over the course of our study, possibly in part as a result
of market forces and the CPSIA, suggesting that the regulation of
chemicals used in consumer products may be an effective method for
decreasing exposure among sensitive populations, particularly with
compounds that have a short biological half-life.
Supporting Information Available
Additional tables and figures
are available as Supporting Information as mentioned in the text.
This material is available free of charge via the Internet at http://pubs.acs.org.
Supplementary Material
es501744v_si_001.pdf
The authors
declare the following competing financial interest(s): Two coauthors
have potential conflicts of interest. Dr. Lanphear has served as an
expert witness and as a consultant to the California Attorney Generals
Office (with no compensation) and as a consultant on a US Environmental
Protection Agency research study (with compensation). Dr. Braun has
provided statistical consulting to plaintiffs in a lead poisoning
trial. The other authors declare that they have no actual or potential
competing financial interests..
Acknowledgments
This work was supported
by NIEHS grants R00 ES020346, PO1
ES11261, R01 ES014575, and R01 ES020349. We like to acknowledge the
Centers for Disease Control and Prevention (CDC) laboratory staff
who performed the analyses. Disclaimer: The findings and conclusions
in this report are those of the authors and do not necessarily represent
the official position of the Centers for Disease Control and Prevention.
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