Risk variables for the development of obesity and type 2 diabetes
van der Meer, Tom
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10.33612/diss.170143787
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2021
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Chapter seven
Temporal exposure and consistency of endocrine
disrupting chemicals in a longitudinal study of
individuals with impaired fasting glucose
Thomas P. van der Meer, Ming K. Chung, Martijn van Faassen, Konstantinos C. Makris, André P. van Beek, Ido P. Kema,
Bruce H.R. Wolffenbuttel, Jana V. van Vliet-Ostaptchouk, Chirag J. Patel
Abstract
Background
Endocrine disrupting chemicals (EDCs) include non-persistent exogenous substances such as parabens, bisphenols and phthalates which have been associated with a range of metabolic disorders and disease. It is unclear if exposure remains consistent over time. We investigated change in indicators of EDC exposure between 2009 and 2016 and assessed its consistency between and within individuals over a median follow-up time of 47 months in a sample of Dutch individuals.
Methods
Of 500 Dutch individuals, two 24 hour urine samples were analysed for 5 parabens, 3 bisphenols and 13 metabolites of in total 8 different phthalates. We calculated per-year differences using meta-analysis and assessed temporal correlations between and within individuals using Spearman correlation coefficients, intra-class correlation coefficients (ICC) and kappa-statistics.
Results
We found a secular decrease in concentrations of methyl, ethyl, propyl and n-butyl paraben, bisphenol A, and metabolites of di-ethyl phthalate (DEP), di-butyl phthalate (DBP), di-(2-ethyl-hexyl) phthalate (DEHP), and butylbenzyl phthalate (DBzP) which varied from 8 to 96% (ethyl paraben, propyl paraben) between 2009 and 2016. Within-person temporal correlations were highest for parabens (ICC: 0.34 to 0.40) and poorest for bisphenols (ICC: 0.15 to 0.23). For phthalate metabolites, correlations decreased most between time periods (ICC < 48 months: 0.22 to 0.39; ≥ 48 months: -0.05 to 0.32). When categorizing EDC concentrations, 33 to 54% of individuals remained in the lowest or highest category and temporal correlations were similar to continuous measurements.
Conclusions
Exposure to most EDCs decreased between 2009 and 2016 in a sample of individuals with impaired fasting glucose from the Dutch population. Temporal consistency was generally poor. The inconsistency in disease associations may be influenced by individual-level or temporal variation exhibited by EDCs. Our findings call for the need for repeated measurements of EDCs in observational studies before and during at-risk temporal windows for the disease.
7
Introduction
Parabens, bisphenols and phthalates are man-made substances that can be found in a wide variety of everyday products (e.g. food, personal care products and plastics), leading to ubiquitous exposure in humans (1–4). Because of their estrogenic and/or anti-androgenic activity, these chemicals are hypothesized to disrupt the endocrine system and therefore have been labelled as “Endocrine Disrupting Chemicals” (EDCs). Exposure to these EDCs has been associated with chronic diseases such as obesity, type 2 diabetes, infertility and cancer (5,6). Most of these studies rely on a single measurement to indicate chronic exposure and do not take the stability of these EDCs into account. Lack of consideration of time-related phenomena may lead to inconsistencies in associations between EDCs and disease.
Regulatory limits have been introduced for EDCs over the past decades (7,8). These regulations, together with a rise in consumer awareness has led to a general decrease in EDC exposures in several European countries and the US (1–3). However, there is limited information available on the temporal change in the body burden of EDC concentrations over recent years. Moreover, biomonitoring studies as described above use cross-sectional designs which make it impossible to evaluate changes in exposure within individuals.
Further, parabens, bisphenols and phthalates are all quickly metabolized and excreted from the human body. Because of half-life times of less than 24 hour (24h) (9–11), these EDCs are non-persistent. Due to their non-persistent nature, the consistency of these chemicals has been a subject of debate with a recent review showing a wide range of within-person variability (12). Inconsistencies may be caused by high variability over time, but also the medium (e.g. serum, spot urine) and/or small sample sizes. More important, studies investigating EDC consistency often focus on a follow-up period of weeks to months, while association studies require assessment of disease development over years. Furthermore, studies often investigate associations between categorized EDCs and disease (e.g. first quartile versus fourth quartile) in an attempt to “reduce” noise or investigate non-linear associations. Very little is known about the potential benefits (and pitfalls) of EDC categorization in the face of temporal inconsistency.
In short, it is unclear (a) how ubiquitous exposure levels change over time and (b) how consistent exposures remain over the course of multiple years. Here, we aimed to assess the prospective changes in adult exposure to a wide range of a mixture of parabens, bisphenols and phthalate metabolites in the Netherlands between 2009 and 2016 as measured in 24h urine samples. Using repeated measurements, we investigated temporal correlations of EDCs both within and between individuals over a time period relevant for clinical studies and assessed the change in correlations between different lengths of follow-up. Finally, we assessed the potential benefits of exposure categorization.
Materials and Methods
Study population
This study consisted of 500 native Dutch subjects with impaired fasting glucose (i.e. fasted glucose 6.1 to 7.0 mmol/l) from the Lifelines study. Individuals were selected based on their glycaemic status (i.e. fasting glucose: 6.1 to 7.0 mmol/l) and the availability of urine samples. Baseline urine samples were collected between January 2009 and December 2013. A second urine sample was collected between January 2014 and December 2015. Lifelines is a multi-disciplinary prospective population-based cohort study conducted in and representative for the north of the Netherlands (13,14). The LifeLines Cohort Study is conducted in accordance with the Declaration of Helsinki and the research code of the University Medical Center Groningen (UMCG). Before study entrance, participants signed an informed consent. The study was approved by the UMCG medical ethics review committee.
Biochemical measurements
Containers for 24h urine collection were accompanied by oral and written instructions and samples. The total 24h urine volume was measured from the collected containers. Next, urine was homogenized after which a sample was taken and stored at -80°C. Methyl paraben (MeP), ethyl paraben (EtP), propyl paraben (PrP), n-butyl paraben (n-BuP) and benzyl paraben (BzP), BPA, BPF and BPS and phthalate metabolites mono-methyl phthalate (MMP), ethyl phthalate (MEP), iso-butyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), mono-(2-ethylhexyl) phthalate (MEHP), mono-n-hexyl phthalate (MnHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono-benzyl phthalate (MBzP), mono-iso-nonyl phthalate (MiNP), mono-hydroxy-iso-nonyl phthalate (MHiNP), and mono-iso-decyl phthalate (MiDP) were analysed in 24h urine samples using offline isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/ MS) technology, for which the full analytical methods have been described elsewhere
(15). The limit of detection (LOD) was calculated as 3.3*S0 / b, where S0 is the standard
deviation of the response and b the slope of the calibration curve (16). The limit of quantification (LOQ) was determined by analysing six different samples with progressively lower concentrations on six different days. The LOQ was set where the imprecision was ≤ 20% and the signal to noise ratio was > 10 on all days. Urinary concentrations of total excreted EDCs per 24h (ng/24h) were calculated by multiplying the measured EDCs (ng/ mL) by the total urinary 24h volume (mL). This way, we corrected for dilution as a result of differences in urine volume.
Statistical analysis
We assessed the consistency of exposure to EDCs by I) examining trends in per-year exposure, II) assessing the robustness of correlations between EDCs and III) investigating inter- and intra-person correlations of EDCs between baseline and follow-up.
7
To investigate the temporal stability of EDCs, we calculated the proportion ofsamples detected above the LOD, median concentrations and distribution for each EDC at baseline and at follow-up. Solely EDCs which were detected above LOD in at least 33% of the samples were selected for subsequent analysis. Samples which were detected below the LOD were imputed with the LOD divided by the square root of 2 (“LOD/√2”) (17), after which we grouped concentrations per year of urine collection. To account for
a right-skewed distribution, we transformed EDC concentrations with a log10 for statistical
analysis. We tested differences in exposure within individuals using linear mixed effect models. In R, our model is specified:
(1) lme(EDC ~ time + (1|ID), data = data).
Differences in exposure over time were modelled using meta-regression approach. Again, in R:
(2) rma(yi = mean, sei = sem, mods = ~ year, data = data, control = list(maxiter = 10000))
In which sem stands for standard error of the mean. Second, we assessed how EDC concentrations were correlated with each other by calculating Spearman correlation coefficients between EDCs at both baseline and follow-up and examined whether the correlations remained consistent over time by comparing correlations found between baseline EDCs to those found at follow-up. Third, we investigated the temporal correlations of EDC exposure between individuals independent of temporal trends by calculating the Spearman correlation coefficients between baseline and follow-up. In addition, we assessed the within-person temporal correlation of EDCs over time by calculating intraclass coefficients (ICC) with a random effect for individuals.
As many studies which focus on disease associations categorize EDC exposure (e.g. highest concentration quartile versus lowest concentration quartile), we categorized all EDCs which were detected above LOD in at least 75% of the samples at both timepoints into quartiles. First, we assessed agreement and cross-over from one category to another over time while sticking to the cut-offs based on baseline measurements. Next, we repeated the analysis after recategorizing follow-up measurements independent of baseline categories, and tested cross-over by calculating kappa statistics. To examine the effect of time interval between baseline and follow-up measurements on temporal correlations, we calculated Spearman correlation coefficients, ICCs and Kappa statistics while stratifying for time interval (i.e. <48 months; ≥48 months).
This study was conducted in a population at-risk for metabolic diseases, which may impact the representativeness of the results. Therefore, we investigated how two levels of potential confounding variables affected our results: a) age and sex, and b) age, sex,
body mass index (BMI; categorized as: normal weight [<25 kg/m2], overweight [25-30 kg/ m2] or obese [>30kg/m2]) and smoking status (categorized as: never smoker, ex-smoker, and current smoker). For both categories, the healthiest level was set as reference (i.e. normal weight, never smoker). We added these variables as fixed effects in our model that assessed differences in exposure within individuals. Also, we calculated partial Spearman correlation adjusting for the variables mentioned above. Further, we conducted a sensitivity analysis in which we excluded all individuals with a body mass index (BMI) of
30 kg/m2 or higher.
We performed all analyses using the R project software (version: 3.5.2) (18).
Results
The study population consisted of slightly more males (60%) with a mean age of 53 years at baseline. The largest proportion was overweight (48%) and ex-smoker (46%) (Supplementary table 1). The median time difference between baseline and follow-up was 47 months (interquartile range: 39 to 55 months; maximum: 85 months).
Temporal trends of endocrine disrupting chemical exposure
Urinary excretions of EDCs are reported in Table 1. The phenols MeP and EtP, and BPA were detected in at least 75% of the samples at both baseline and follow-up measurements, as were the phthalates MEP, MiBP, MnBP, MEHP, MEHHP, MEOHP, MECPP and MBzP (≥ 99%). BzP, BPS, MiNP and MiDP were detected in at most 18% of the samples and were therefore excluded from subsequent analysis. Within-person excretions decreased over time for all EDCs (p ≤ 0.006) but BPF, MMP and MnHP (p > 0.05). When analysing excretions per year (Figure 1), we observed a similar decline in all EDC excretions except for BPF, MMP, and MnHP. Between 2009 and 2016, median concentrations decreased with 8 to 96% for parabens (EtP, PrP, respectively), 50% for BPA, and 34 to 66% for phthalates (MEP, MEHP, respectively; Supplementary Table 2). For some parabens (i.e. MeP, PrP, n-BuP) a large decrease in excretions was detected between 2010 and 2011, whereas BPA and phthalate metabolites appeared to decline more gradually over time. Excretions per
year are presented in Supplementary Table 3, and log10-transformed excretions used for
the meta-regression analyses are depicted in Supplementary Figure 1.
Correlations between exposure to endocrine disrupting chemicals
Figure 2a shows Spearman correlations between EDC excretions at both baseline (lower triangle) and follow-up (upper triangle). Correlations between phenol excretions in general remained consistent over time and were strong for MeP with EtP and PrP (r: 0.50 to 0.71). n-BuP was correlated stronger with MeP, EtP and PrP at follow-up (r: 0.48 to 0.59) compared to baseline (0.36 to 0.38). For phthalates, we found the strongest consistent correlations between MEHHP, MEOHP and MECPP (r: 0.86 to 0.96), which were all to a lesser extent correlated with MEHP (r: 0.60 to 0.68). MinBP and MnBP were moderately correlated at
7
Ta b le 1 . N um b er o f de te ct ion s, c on cen tr at ion a nd d is tr ib ut ion o f en do cr in e d is ru p tin g c hem ic al s. Abbr eviation LOD Baseline (µg/24h) Follow-up (µg/24h) p-value >LOD (n (%)) Median [IQR] >LOD (n (%)) Median [IQR] Parabens methyl paraben MeP 0.14 500 (100) 12.25 (2.74; 44.84) 500 (100) 4.81 (1.71; 22.81) <0.0001 ethyl paraben EtP 0.09 470 (94) 1.2 (0.35; 5.54) 449 (90) 0.76 (0.24; 2.75) 0.0014 pr opyl paraben PrP 0.07 377 (75) 1.18 (0.08; 9.36) 286 (57) 0.21 (<LOD; 2.27) <0.0001 n-butyl paraben n-BuP 0.06 278 (56) 0.07 (<LOD; 0.41) 178 (36) <LOD (<LOD; 0.09) <0.0001 benzyl paraben BzP 0.07 15 (3)<LOD (<LOD; <LOD)
8 (2)
<LOD (<LOD; <LOD)
Bisphenols bisphenol A B PA 0.22 399 (80) 1.1 (0.31; 2.41) 379 (76) 0.77 (0.22; 1.72) 0.0055 bisphenol F BPF 0.23 276 (55) 0.29 (<LOD; 0.81) 263 (53) 0.25 (<LOD; 0.77) 0.8860 bisphenol S BPS 0.06 65 (13)
<LOD (<LOD; <LOD)
88 (18)
<LOD (<LOD; <LOD)
Phthalates mono-methyl phthalate MMP 0.43 351 (70) 0.96 (<LOD; 2.02) 311 (62) 0.78 (<LOD; 1.83) 0.9193 mono-ethyl phthalate MEP 0.35 500 (100) 50.46 (19.76; 148.62) 500 (100) 31.46 (14; 81.08) <0.0001 mono-iso-butyl phthalate MiBP 0.33 500 (100) 19.93 (12.2; 34.55) 500 (100) 13.77 (8.59; 22.41) <0.0001 mono-n-butyl phthalate MnBP 0.22 500 (100) 16.42 (10.46; 25.54) 500 (100) 12.53 (7.83; 18.95) <0.0001 mono-n-hexyl phthalate MnHP 0.12 288 (58) 0.08 (<LOD; 0.14) 230 (46) <LOD (<LOD; 0.11) 0.0620 mono-(2-ethylhexyl) phthalate MEHP 0.07 500 (100) 2.19 (1.34; 3.72) 493 (99) 1.28 (0.75; 2.23) <0.0001 mono-(2-ethyl-5-hydr oxyhexyl) phthalate MEHHP 0.11 500 (100) 8.81 (6.14; 13.67) 500 (100) 5.83 (3.95; 8.62) <0.0001 mono-(2-ethyl-5-oxohexyl) phthalate MEOHP 0.09 500 (100) 5.19 (3.61; 8.29) 500 (100) 3.52 (2.42; 5.41) <0.0001 mono-(2-ethyl-5-carboxypentyl) phthalate MECPP 0.25 500 (100) 9.03 (6.31; 13.99) 500 (100) 5.75 (3.88; 9.07) <0.0001 mono-benzyl phthalate MBzP 0.22 500 (100) 3.73 (2.28; 6.48) 496 (99) 2.02 (1.22; 4.09) <0.0001 mono-iso-nonyl phthalate MiNP 0.10 3 (1)
<LOD (<LOD; <LOD)
1 (0)
<LOD (<LOD; <LOD)
mono-iso-decyl phthalate
MiDP
0.31
5 (1)
<LOD (<LOD; <LOD)
4 (1)
<LOD (<LOD; <LOD)
Abbr
eviations: LOD, limit of detection; IQR, inter
-quartile range. LODs ar
e expr
essed as ng/mL. Urinary concentrations of total excr
eted EDCs per 24h (µg/24h) wer
e calculated by multiplying the measur ed EDCs (ng/mL) by the
total urinary 24h volume (mL) and dividing
the result by a factor 1000. W ithin-person dif fer ences wer e
calculated using linear mixed ef
fect models:
“lme(EDC ~ time + (1|ID), data = data)”
Figur
e 1.
Yearly excr
etions of urinary endocrine disrupting chemicals. Y
early phenol and phthalate excr
etions (µg/24 hour) ar e expr essed as median [inter quartile range]. The
dotted line depicts
the
end of baseline sample collection (2009 - 2014), and
the
beginning of follow-up sample collection
(2014 - 2016).
The
p-values show whether
the
change in EDC excr
etion changes significantly over time. Full names of abbr
eviations ar
e shown in T
7
both timepoints (r: 0.44, 0.40, baseline, follow-up). When comparing correlations of EDCsbetween baseline and follow-up (Figure 2b), we found the phenol MeP to consistently correlate with EtP and PrP (r: 0.31 to 0.34) and PrP to be consistently correlated with n-BuP (r: 0.31, 0.32). All Spearman correlation coefficients are described in Supplementary Table 4.
Temporal correlations of endocrine disrupting chemical exposure
Next, we assessed the consistency of parabens, bisphenols and phthalates over time. In the total population, we detected moderate between-person temporal correlations (Figure 2b, Figure 3a) for MeP, EtP, PrP and n-BuP (Spearman’s rho: 0.38 to 0.49), and BPA and BPF (Spearman’s rho: 0.19, 0.21). This was reflected by the within-person temporal correlations (Figure 3b), which we found to be significant for all parabens (ICC: 0.34 to 0.40) but not for BPA and BPF (0.15, 0.23, respectively). For phthalates, between-person temporal correlations were moderate for MiBP, MnBP, MEHP, and MBzP (Spearman’s rho: 0.43 to 0.55). Of these phthalates, within-person temporal correlations were in agreement for MiBP, MEHP and MnBP (ICC: 0.32 to 0.37), and lower for MBzP (ICC: 0.25). We observed weak between-person (Spearman’s rho: 0.29 to 0.37) and weak within-person temporal correlations (0.09 to 0.24) for MEP, MnHP, MEHHP, MEOHP and MECPP. Though being weakly correlated between persons (r: 0.33), MMP showed a consistent within-person correlation (ICC: 0.35). All temporal correlation coefficients are reported in Supplementary table 5.
Temporal correlations of categorized endocrine disrupting chemical exposure
When categorizing EDC exposure into quartiles based on baseline cut-off points, at follow-up we observed a 1.2 to 2.5-fold increase of the lowest quartile (BPA, MEOHP) and a 1.5 to 3.1-fold decrease of the highest quartile (BPA, MEHHP; Figure 4a). When categorizing baseline and follow-up EDC excretions independent of each other, we observed a large proportion of cross-over between exposure quartiles (Figure 4b): Specifically, a total of 32 to 43% of the individuals remained in their respective category (MEHHP, MEOHP; MiBP, respectively), with 44 to 54% (MEHHP, MEOHP; MiBP, MnBP) and 33 to 54% (MEHHP, MEOHP, BPA; MEHP) remaining in respectively lowest and highest quartile. Information on changes in quartile composition are documented in Supplementary table 6.
Difference in temporal correlations between less and greater than four
year follow-up
As consistency has been shown to decrease over time, we compared correlation coefficients for repeated measurements with an interval of less than 48 months (n = 260) with those which had an interval of at least 48 months (n = 240). For parabens, we observed correlations to increase over time for MeP (Spearman’s rho: +30%, ICC: +11%, kappa: +28%), and to remain stable for EtP. Between-person correlations remained similar for PrP and n-BuP (Spearman’s rho: -5%, +13%), but ICCs decreased over time (-22%, -35%). Bisphenol correlations decreased when continuous (Spearman’s rho: -33%, -24%;
Figur
e 2.
Corr
elations between endocrine disrupting chemicals at dif
fer
ent timepoints. Abbr
eviations: EDCs, endocrine disrupting chemicals. A.) Spear
man
corr
elation coef
ficients of EDCs at baseline (lower triangle) and follow-up (upper triangle). At places wher
e
the
colouring is symmetrical acr
oss the diagonal, corr elations ar e r obust acr
oss time. B.) Spear
man corr
elation coef
ficients of EDCs at baseline versus those at follow-up.
The
diagonal depicts coef
ficients
between
the
baseline and follow-up of
the
same chemicals. Full names of EDC abbr
eviations ar
e shown in T
7
ICC: -39%, -43%, BPA, BPS, respectively), but BPA correlations remained similar when categorized. Regarding phthalates, a longer interval between measurements impacted all correlation coefficients for MMP and MEP between -10% and -24%. Though a similar decrease was observed for the between-person and categorized correlation coefficients of MiBP, MnBP and MEHP, the ICC showed a larger decline (-46% to -50%). Coefficients for MnHP, MEHHP, MEOHP, MECPP, and MBzP varied between -32% and -51% for between-Figure 3. Consistency of endocrine disrupting chemicals over different timeframes. A.) Spearman rank-order correlation coefficients to show between-person temporal correlation, which is independent of the general decrease of exposure to endocrine disrupting chemicals as depicted in Figure 1. B.) Intraclass correlation coefficients of endocrine disrupting chemicals to show temporal correlation within individuals of absolute exposure values. C.) Kappa of endocrine disrupting chemicals to show temporal correlation after categorization of the data into quartiles. Parabens are coloured purple, bisphenols blue, low molecular weight phthalates green and high molecular weight phthalates red. Full names of EDC abbreviations are shown in Table 1.
Figure 4. Consistency of categorized endocrine disrupting chemicals. A.) Endocrine disrupting chemical exposure groups categorized in quartiles based on baseline cut-off values. The sizes of the categories at follow-up show the proportion in which concentrations at follow-up would be categorized based on baseline exposure measurements. The observed size increase of the lowest category is in line with the decreasing trend in EDC exposures as depicted in Figure 1. B.) Endocrine disrupting chemical exposure groups categorized in quartiles based on the cut-off values at their respective timepoint, leading to an equal distribution of individuals over the quartiles. The coloured bands express the proportion of individuals which are categorized in that respective quartile at baseline that relocate to a category at follow-up. The category labelled “1” (purple) represents the lowest exposure category, whereas the “4” (red) represents the highest exposure quartile. Full names of EDC abbreviations are shown in Table 1.
7
person and categorized correlation coefficients, and between -76% and -123% forwithin-person correlations.
Sensitivity analysis
We found within-person changes in exposure to remain similar when we adjusted for potential confounding variables (Supplementary table 2). Further, we observed that adjusting for age, sex, BMI and smoking status did not affect the Spearman correlation with more than 0.10 points between the EDCs measured at baseline (Supplementary figure 2). When we adjusted the model focusing on EDCs measured at follow-up we found that correlation coefficients became less strong between n-BuP and MeP (Rho: 0.51 to 0.39), and PrP (0.33 to 0.17). Correlation coefficients changed direction between BPF and MeP, PrP and n-BuP and remained minor (-0.01 to 0.04). We next looked at the impact of age, sex, BMI and smoking status on the Spearman correlations between the same EDCs measured at different timepoints (Supplementary figure 3). All adjusted correlation coefficients remained within 0.10 point of their unadjusted coefficient. Changes were largest for MeP (0.46 to 0.37) and PrP (0.38 to 0.29).
In total, 181 individuals had a BMI of at least 30 kg/m2 and were therefore excluded
from the sensitivity analysis. Within-person changes in exposure remained similar for all EDCs but BPA (1.85 [0.62; 3.69] to 1.44 [0.50; 3.08], p = 0.076). On the other hand, when assessing exposure per year BPA showed significant decrease over time (p = 0.037), as did MnHP (p = 0.031). Correlation patterns between EDCs remained similar compared to the full study population, as did the temporal correlation coefficients (data not shown).
Discussion
Here, we used 24h urine samples to assess the exposure of a wide mixture of non-persistent EDCs in Dutch adults between 2009 and 2016. We investigated the consistency between EDCs over different time intervals leveraging individual samples taken at baseline and follow-up. Further, we investigated the effect of categorization on the stability of EDC exposure values.
Secular decrease in endocrine disrupting chemical exposure from 2009 to
2016
Over the past decades, exposure to parabens, bisphenols and phthalates have been monitored through surveillance programs such as the National Health and Nutrition Examination Survey (NHANES, US), and the German Environmental Specimen Bank (ESB). Though some studies have reported exposures without the help of biomonitoring programs (e.g. Denmark), this data is unavailable for most countries including the Netherlands. In the current study, we observed a decrease in exposure for all parabens between 2009 and 2016. Between 2010 and 2011, we observed an especially steep decline in exposure for MeP, PrP and n-BuP. The ESB did not report data on parabens for 2011, but they did observe
a reduction in exposure gradient in median concentrations for EtP and PrP (1.8- and 2.2-fold decrease), but not MeP (1.3-fold increase) between 2009 and 2012 (1). In 2010, Denmark banned the use of PrP and BuP in cosmetic products for children under three years (7). Though this regulation did not include MeP and did not apply to the Netherlands, it might have led to changes in the production of Western-European based products. We observed another decline in paraben exposure between 2014 and 2015 that has, to the best of our knowledge, not been reported by other studies before. This decrease could be another result of legislation: As of April 2014, the European Parliament banned the use of iso-PrP, iso-BuP, and BzP in cosmetic products, next to allowing maximum concentrations of 0.19% for BuP and PrP, and 0.8% for combined parabens (7). In contrast to Europe, parabens are not regulated in the USA (19), potentially limiting the representativeness of this data to other countries.
We observed a declining gradient in BPA exposure over time. Several studies showed a similar trend in the USA, in which median concentrations decreased 1.5- to 5.8-fold (20–22). For Swedish mothers, an annual decrease of 9.8% (±4.3, p = 0.029) was observed (23), which was similar to Danish young men that showed an average decrease of 10% per year, (3). BPA concentrations remained similar over time in a Canadian population (1.1 to 1.2 ng/ml) and increased from 0.7 to 1.1 ng/ml in Korea (21). We found the strongest decline in exposure between 2014 and 2015, in which the European Union reduced the tolerable daily intake (TDI) for BPA from 50 to 4 µg/kg body weight/day (24). In contrast, we observed BPF concentrations to remain stable over time, in line with studies from the USA and Denmark (3,20), while concentrations showed an increasing gradient of 20% change per year (±7.6, p = 0.003) in Sweden (23).
Regarding phthalates, we observed a decreasing gradient in exposure to the DEHP metabolites MEHP, MEHHP, MEOHP and MECPP, the DBP metabolites MiBP and MnBP, and the BBP metabolite MBzP. Other studies showed a similar trend in Danish (average yearly decreases of 7.2 to 16%, all p < 0.0001) and Swedish study populations (14 to 17% decrease per year, all p < 0.001) (3,23). Moreover, median concentrations of MEHP, MiBP, MnBP and MBzP decreased 1.7- to 2.8-fold between 2009 and 2015 in a German study performed by the ESB (2). In contrast to parabens and bisphenols, this gradient was more constant. This might be due to the implementation of multiple different regulations over time focussed on different products such as children’s toys (8), foodstuffs (25), cosmetics (26), and electronic devices (27), which have been gradually become active over the years and will continue to until 2021. In addition, concentrations of the metabolite for DEP showed a declining gradient over time, in line with Danish and Swedish studies which showed a yearly decrease of 16 and 9.8%, respectively (3,23). The DMP metabolite MMP remained stable. Though some studies reported decreases over time, absolute concentrations were in the same range (i.e. 1.4 µg/L versus 1.9 to 2.8 µg/L) (2,3).
Parabens, bisphenols, and phthalates are mainly used as plasticizers or preservatives, and sources of exposure described in literature include food- and personal care products. Therefore, it would be of interest to investigate whether the use or consumption of
7
specific products is associated with exposure. However, in current study data on the useof personal care products is unavailable. Though we did have data on the consumption of a large variety of food products, the packaging and way of preparation of these products was unknown. For example, we do have an indication of how much carrots an individual ate over the past month, but not whether these were freshly picked and paper-wrapped at a farm or bought canned from the supermarket. As shown previously, the packaging of products and use of cooking utensils can heavily impact exposure to EDCs (28). Therefore, specific sources of exposure should be investigated in studies designed for that purpose.
Co-exposure and correlation patterns between different endocrine
disrupting chemicals
We observed strong correlation patterns between several parabens at baseline that remained consistent at follow-up. As parabens have been shown to be more effective as antimicrobial agents when combined, they are often used as a mixture of several different parabens (29). Most phthalates showed correlations to some extent, with strong correlations between DEHP metabolites. MEHP showed a less strong correlation compared to other DEHP metabolites, which may be explained by abiotic hydrolysis of DEHP which naturally occurs in the environment (30).
The EDCs of interest have been associated with a wide range of demographic variables such as age, sex, obesity, and smoking status, and association analysis therefore often adjust for these variables (31–33). Here, we found that these variables had a small impact on our findings. This may be due to the use of repeated measurements in the same individual. Further, our study population consisted of individuals with impaired fasting glucose. Although obesity and smoking status varied between individuals, this may have led to uniformity within the population.
Lack of consistency of endocrine disrupting chemical exposure over time
We investigated a mixture of EDCs that have half-lives of less than 24h (9–11). Combined with the wide applications of these chemicals, exposure and thus urinary concentrations are susceptible for variation. A recent review showed a wide range of within-person temporal correlations, also known as reproducibility, in spot urine samples, which were in mostly poor (i.e. ICC <0.40) (12). In general, paraben ICCs were reported to be higher than other EDCs (12). To the best of our knowledge, this is the first study to assess within-person temporal correlations of parabens over the course of more than one year. Compared to studies investigating shorter time intervals, we found similar correlation coefficients. This is in line with the stability we observed between samples with a short (i.e. < 48 months) and a longer time interval (i.e. ≥ 48 months) and implies that paraben exposure remains relatively consistent over longer time periods. For BPA, studies investigating spot urine samples over an interval up to several months reported very poor within-person temporal correlations (12). This results was confirmed in another study investigating BPA in spot urine over a period up to three years (ICC 12 to 25 months: 0.23 [0.06; 0.60]; 25 to 36
months: 0.06 [0.00; 0.94]) (34). The within-person temporal correlations we found for BPA was similar to that of the first interval of Townsend and colleagues, but remained stable over a much longer period of time (i.e. 48 months) potentially due to our use of 24h urine samples; The use of 24h urine samples appeared to improve within-person temporal correlation for BPA (ICC: 0.39) over two seasons (35). Yet, after a time period of more than 48 months correlation coefficients also deteriorated in 24h urine, stressing the importance of repeated measurements in BPA-focussed research. To the best of our knowledge, we are the first to report the temporal correlation of BPF, which appeared to be in the same range as BPA. So far, few studies have investigated the temporal correlations of phthalates over a time period of longer than one year (34,36). Townsend and colleagues included spot- and morning urine samples of 40 individuals from the US with an one to three year interval (34). We observed similar ICCs for most phthalates (i.e. MEP, MiBP, MnBP, MBzP, MECPP), whereas DEHP metabolites differed. Startling and colleagues included spot urine samples of 100 individuals from Shanghai with a two to eight year interval, and reported lower ICCs for all phthalates (36). As we observed a decrease in within-person correlations over time, this may explain differences between studies. In this study, we observed higher between-person compared to the within-person correlation coefficients, which can be explained by the general decrease of phthalate concentrations over time. This is in line with the drop in within-person correlations between time intervals, and further stresses the need for repeated measurements.
Consistency of categorized or grouped endocrine disrupting chemical
exposure
It is common to categorize continuous EDC concentrations and compare EDC exposure groups in association studies. The similarity between the Spearman correlation coefficients and the weighted kappa statistics indicates that categorizing EDCs does not lead to better temporal correlation. Further, we found that about half of the individuals categorized in the highest or lowest quartile did not remain in their respective category after categorization based on a second measurement. Therefore, categorization severely reduces the dimension of the data (i.e. four groups instead of continuous values) while not increasing consistency and should therefore be avoided.
Conclusion
We found that exposure to BPA and most parabens and phthalates have decreased between 2009 and 2016, of which some may be attributed to the introduction of European legislation. Further, the consistency of 24h urine samples deteriorated over the course of years that reflects both the short half-life of these indicators of exposure and lifestyle changes over a 7-year span. Therefore, repeated measurements of non-persistent EDCs are strongly recommended in clinical studies. Last, categorization of EDC measurements does not improve consistency and should be avoided.
7
Acknowledgments
The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centres delivering data to Lifelines, and all the study participants. We thank Irene van der Kooi-Wijbenga for her contribution to the technical measurements. JVvVO was supported by a Diabetes Funds Junior Fellowship from the Dutch Diabetes Research Foundation (project no. 2013.81.1673). CJP had financial support from the National Institutes of Health (grant R01AI127250) for the submitted work. The authors declare no conflict of interest.
Competing Financial Interests and study approval
JVvVO was supported by a Diabetes Funds Junior Fellowship from the Dutch Diabetes Research Foundation (project no. 2013.81.1673). CJP had financial support from the National Institutes of Health (grant R01AI127250) for the submitted work. All other authors declare they have no actual or potential competing financial interests. The authors declare no conflict of interest. The Medical Ethics committee of the University Medical Center Groningen approved the study, and all participants gave written informed consent.
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7
Supplementary table 1. Baseline population characteristicsNumber of individuals 500
Age (years) 53.4 (10.3)
Sex (female) 201 (40%)
Body mass index (BMI)
Normal weight (20-24.9 kg/m2) 77 (15%) Overweight (25-29.9 kg/m2) 242 (48%) Obese (≥30 kg/m2) 181 (36%) Smoking status Never smoker 181 (36%) Ex-smoker 230 (46%) Current smoker 89 (18%)
Characteristics are displayed as mean (SD) or number (%). BMI categories do not add up to 100% due to rounding.
Su p p lement ar y t ab le 2 . W it hi n-p er so n c ha ng e i n e xp o su re t o E nd o cr in e D is ru p tin g C he m ic al s a ft er a d ju st in g f o r p ot en tia l c o nf o un d in g v ar ia b le s. Abbr eviation Metabolite
Concentration (median [IQR])
p-value Baseline Follow-up Model 1 Model 2 Model 3 MeP methyl paraben 22.2 (5.12; 82.1) 7.45 (3.09; 39.8) 7.48E-15 1.40E-14 1.70E-14 EtP ethyl paraben 2.13 (0.59; 10.3) 1.40 (0.40; 5.16) 0.001417 0.001831 0.001636 PrP pr opyl paraben 2.24 (0.15; 16.6) 0.37 (0.10; 3.81) 9.04E-06 2.38E-06 1.27E-06 n-BuP n-butyl paraben 0.14 (0.08; 0.74) 0.10 (0.07; 0.16) 9.12E-07 6.13E-07 1.27E-06 B PA bisphenol A 1.85 (0.58; 4.00) 1.36 (0.46; 2.98) 0.005527 0.005613 0.004715 BPF bisphenol F 0.51 (0.32; 1.56) 0.48 (0.32; 1.35) 0.886029 0.808514 0.81768 MMP mono-methyl phthalate 1.73 (0.77; 3.53) 1.35 (0.70; 3.12) 0.919314 0.881261 0.861374 MEP mono-ethyl phthalate 92.1 (36.3; 263) 57.9 (25.1; 144) 1.10E-08 1.16E-08 3.53E-09 MiBP mono-iso-butyl phthalate 36.4 (24.7; 55.3) 24.7 (17.7; 36.0) 6.77E-32 6.98E-32 5.03E-32 MnBP mono-n-butyl phthalate 29.6 (20.9; 43.7) 21.3 (14.7; 33.5) 1.07E-18 1.09E-18 4.84E-19 MEHP mono-(2-ethylhexyl) phthalate 4.20 (2.45; 6.45) 2.24 (1.36; 3.71) 2.64E-45 2.08E-45 1.03E-44 MnHP mono-n-hexyl phthalate 0.15 (0.10; 0.24) 0.13 (0.09; 0.19) 0.062043 0.062707 0.079088 MEHHP mono-(2-ethyl-5-hydr oxyhexyl) phthalate 16.0 (11.6; 23.2) 9.94 (7.40; 14.6) 3.92E-35 4.71E-35 5.03E-34 MEOHP mono-(2-ethyl-5-oxohexyl) phthalate 9.88 (6.99; 13. 7) 6.07 (4.56; 8.86) 1.06E-33 1.11E-33 1.61E-32 MECPP mono-(2-ethyl-5-carboxypentyl) phthalate 17.0 (11.7; 23.2) 10.3 (7.35; 15.2) 3.56E-37 3.54E-37 4.87E-36 MBzP mono-benzyl phthalate 6.84 (4.32; 11.1) 3.57 (2.21; 6.72) 2.03E-38 1.96E-38 1.28E-37
Urinary concentrations of total excr
eted EDCs per 24h (µg/24h) wer
e calculated by multiplying
the
measur
ed EDCs (ng/mL) by
the
total urinary 24h volume (mL) and
dividing the result by a factor 1000. W ithin-person dif fer ences wer e calculated using linear mixed ef fect models: “lme(EDC ~ time + (1|ID), data = data)”. Potentially confounding variables wer e added as fixed ef fect. Model
1: No confounding variables; Model 2:
age + sex; Model 3: age
+ sex + body
7
S uppl em ent ar y f ig ur e 1 . E x cr et ion s pe r y ea r, w it h log 10 -t ran sf o rm ed E D C ex cr et io n s. Y ear ly ex cr et io n s o f l o g10 -t ran sf o rm ed E D C s ar e ex p re ssed as m ed ian [ in te rq u ar ti le r an g e] . T he do tte d l ine de pi ct s t he e nd of ba se line sa m pl e col le ct io n ( 20 09 2014) , a n d t he b eg inni ng of f o ll ow -up s am pl e c o ll ec ti on (2014 2016) . Th e p -v al u es w er e cal cu la ted u si n g m et a-reg ressi o n ana ly si s a nd show w he the r the c ha ng e i n E D C e xc re ti o n c ha ng es s ig ni fi ca nt ly ov er t im e. For fu ll n am es of a bbr ev ia te d c he m ic al s, s ee T abl e 1. Supplementary figur e 1. Excretions per year
, with log
10
-transfor
med EDC excr
etions. Y early excr etions of log 10 -transfor med EDCs ar e expr essed as median [inter quartile range]. The dotted line depicts the end of baseline sample collection (2009 - 2014), and the beginning of follow-up sample collection (2014 - 2016). The p -values wer
e calculated using meta-r
egr
ession analysis and show whether
the
change in EDC excr
etion changes significantly over time. For full
names of abbr
eviated chemicals, see T
Supplementary table 3. Urinary 24-hour excretions of phenols and phthalates per year. 2009 (n = 90) 2010 (n = 129) 2011 (n = 114) 2012 (n = 96) 2013 (n = 71) 2014 (n = 247) 2015 (n =138) 2016 (n = 115) p-trend Change (%) Phenols MeP 31.1 (8.73; 97.8) 34.3 (6.69; 95.2) 14.4 (4.13; 76.2) 17.3 (3.76; 62.6) 10.8 (2.99; 47.1) 9.75 (3.45; 48.2) 6.06 (2.45; 26.1) 7.26 (3.25; 31.6) <0.001 -77 EtP 1.85 (0.73; 8.46) 3.13 (0.92; 14.9) 2.36 (0.69; 9.69) 1.89 (0.49; 10.0) 1.13 (0.40; 5.29) 1.72 (0.49; 5.44) 0.88 (0.32; 2.81) 1.70 (0.46; 6.60) 0.004 -8 PrP 6.07 (0.72; 32.2) 3.38 (0.39; 23.2) 1.40 (0.13; 10.7) 1.63 (0.12; 9.35) 0.52 (0.11; 6.46) 0.76 (0.11; 5.97) 0.14 (0.10; 2.32) 0.27 (0.09; 3.49) <0.001 -96 n-BuP 0.20 (0.10; 0.88) 0.27 (0.10; 1.69) 0.10 (0.07; 0.72) 0.11 (0.08; 0.54) 0.14 (0.08; 0.25) 0.10 (0.07; 0.18) 0.10 (0.07; 0.16) 0.09 (0.07; 0.13) <0.001 -55 BPA 2.32 (0.95; 4.26) 2.28 (0.96; 4.20) 1.70 (0.45; 3.56) 1.35 (0.63; 3.38) 1.83 (0.48; 5.04) 1.75 (0.64; 3.40) 0.94 (0.42; 2.41) 1.16 (0.42; 2.03) 0.001 -50 BPF 0.49 (0.32; 1.39) 0.68 (0.37; 2.04) 0.46 (0.30; 1.31) 0.50 (0.34; 1.85) 0.45 (0.29; 0.96) 0.57 (0.32; 1.32) 0.44 (0.33; 1.11) 0.46 (0.30; 1.67) 0.481 -6 Phthalates MMP 1.20 (0.69; 2.52) 2.43 (0.92; 5.55) 1.83 (0.82; 3.51) 1.38 (0.66; 3.45) 1.58 (0.87; 2.48) 1.56 (0.72; 3.81) 1.07 (0.68; 2.18) 1.13 (0.68; 2.53) 0.164 -6 MEP 111 (36.3; 300) 92.2 (50.4; 303) 112 (36.2; 353) 83.0 (27.6; 183) 82.0 (28.6; 209) 60.6 (29.9; 142) 45.9 (22.7; 121) 72.9 (25.5; 156) <0.001 -34 MiBP 42.9 (27.9; 71.7) 42.5 (29.2; 57.9) 32.5 (23.4; 47.5) 32.2 (20.6; 54.1) 29.7 (21.0; 44.1) 25.2 (18.4; 36.6) 24.1 (17.8; 33.7) 23.0 (16.5; 36.8) <0.001 -46 MnBP 33.4 (25.6; 51.5) 32.0 (23.2; 49.0) 28.0 (20.3; 43.5) 26.8 (19.7; 41.7) 25.8 (19.7; 35.5) 23.8 (16.0; 35.2) 20.5 (14.0; 34.3) 19.1 (13.5; 31.3) <0.001 -43 MnHP 0.15 (0.09; 0.22) 0.19 (0.12; 0.34) 0.17 (0.12; 0.27) 0.12 (0.09; 0.18) 0.12 (0.09; 0.16) 0.13 (0.09; 0.18) 0.12 (0.09; 0.18) 0.13 (0.09; 0.24) 0.078 -13 MEHP 4.98 (3.63; 7.15) 4.94 (3.07; 7.65) 3.72 (2.20; 5.62) 3.31 (2.04; 4.87) 3.44 (1.77; 5.17) 2.64 (1.76; 4.45) 2.04 (1.29; 3.22) 1.68 (0.92; 2.99) <0.001 -66 MEHHP 21.1 (15.5; 28.7) 18.7 (12.4; 25.7) 16.0 (11.5; 22.4) 13.1 (10.3; 19.0) 12.9 (9.22; 18.8) 10.4 (7.81; 16.2) 9.64 (7.23; 15.0) 9.11 (7.05; 12.2) <0.001 -57 MEOHP 13.2 (9.66; 17.7) 11.3 (7.95; 15.5) 9.45 (6.80; 12.9) 8.16 (6.10; 11.1) 8.05 (5.38; 11.3) 6.44 (4.88; 9.81) 6.03 (4.33; 8.81) 5.54 (4.11; 7.45) <0.001 -58 MECPP 21.4 (16.9; 28.1) 18.3 (13.7; 26.6) 15.8 (11.0; 20.8) 13.9 (10.2; 18.8) 12.5 (9.40; 18.8) 11.4 (8.28; 16.8) 10.2 (6.88; 14.0) 8.17 (7.08; 12.6) <0.001 -62 MBzP 8.81 (5.65; 13.2) 7.63 (4.82; 12.1) 5.94 (4.31; 11.2) 5.92 (3.67; 9.28) 5.61 (3.43; 7.99) 4.00 (2.38; 7.88) 3.50 (2.14; 5.83) 3.11 (1.98; 4.99) <0.001 -65
Solely chemicals which were detected above the limit of detection (LOD) for > 33% of the samples were included. Values with a detection LOD were imputed with “LOD/√2”. To account for dilution, raw concentrations (ng/ml) were multiplied by urine volume leading to total excretions (µg/24h). Medians and interquartile ranges were calculated
for each year. p-values for linear trend (p-trend) were calculated by modelling the median concentration of each year as a continuous variable. The change between 2009 and 2016 was calculated as: “(median2016 – median2009)
7
Supplementary table 3. Urinary 24-hour excretions of phenols and phthalates per year.2009 (n = 90) 2010 (n = 129) 2011 (n = 114) 2012 (n = 96) 2013 (n = 71) 2014 (n = 247) 2015 (n =138) 2016 (n = 115) p-trend Change (%) Phenols MeP 31.1 (8.73; 97.8) 34.3 (6.69; 95.2) 14.4 (4.13; 76.2) 17.3 (3.76; 62.6) 10.8 (2.99; 47.1) 9.75 (3.45; 48.2) 6.06 (2.45; 26.1) 7.26 (3.25; 31.6) <0.001 -77 EtP 1.85 (0.73; 8.46) 3.13 (0.92; 14.9) 2.36 (0.69; 9.69) 1.89 (0.49; 10.0) 1.13 (0.40; 5.29) 1.72 (0.49; 5.44) 0.88 (0.32; 2.81) 1.70 (0.46; 6.60) 0.004 -8 PrP 6.07 (0.72; 32.2) 3.38 (0.39; 23.2) 1.40 (0.13; 10.7) 1.63 (0.12; 9.35) 0.52 (0.11; 6.46) 0.76 (0.11; 5.97) 0.14 (0.10; 2.32) 0.27 (0.09; 3.49) <0.001 -96 n-BuP 0.20 (0.10; 0.88) 0.27 (0.10; 1.69) 0.10 (0.07; 0.72) 0.11 (0.08; 0.54) 0.14 (0.08; 0.25) 0.10 (0.07; 0.18) 0.10 (0.07; 0.16) 0.09 (0.07; 0.13) <0.001 -55 BPA 2.32 (0.95; 4.26) 2.28 (0.96; 4.20) 1.70 (0.45; 3.56) 1.35 (0.63; 3.38) 1.83 (0.48; 5.04) 1.75 (0.64; 3.40) 0.94 (0.42; 2.41) 1.16 (0.42; 2.03) 0.001 -50 BPF 0.49 (0.32; 1.39) 0.68 (0.37; 2.04) 0.46 (0.30; 1.31) 0.50 (0.34; 1.85) 0.45 (0.29; 0.96) 0.57 (0.32; 1.32) 0.44 (0.33; 1.11) 0.46 (0.30; 1.67) 0.481 -6 Phthalates MMP 1.20 (0.69; 2.52) 2.43 (0.92; 5.55) 1.83 (0.82; 3.51) 1.38 (0.66; 3.45) 1.58 (0.87; 2.48) 1.56 (0.72; 3.81) 1.07 (0.68; 2.18) 1.13 (0.68; 2.53) 0.164 -6 MEP 111 (36.3; 300) 92.2 (50.4; 303) 112 (36.2; 353) 83.0 (27.6; 183) 82.0 (28.6; 209) 60.6 (29.9; 142) 45.9 (22.7; 121) 72.9 (25.5; 156) <0.001 -34 MiBP 42.9 (27.9; 71.7) 42.5 (29.2; 57.9) 32.5 (23.4; 47.5) 32.2 (20.6; 54.1) 29.7 (21.0; 44.1) 25.2 (18.4; 36.6) 24.1 (17.8; 33.7) 23.0 (16.5; 36.8) <0.001 -46 MnBP 33.4 (25.6; 51.5) 32.0 (23.2; 49.0) 28.0 (20.3; 43.5) 26.8 (19.7; 41.7) 25.8 (19.7; 35.5) 23.8 (16.0; 35.2) 20.5 (14.0; 34.3) 19.1 (13.5; 31.3) <0.001 -43 MnHP 0.15 (0.09; 0.22) 0.19 (0.12; 0.34) 0.17 (0.12; 0.27) 0.12 (0.09; 0.18) 0.12 (0.09; 0.16) 0.13 (0.09; 0.18) 0.12 (0.09; 0.18) 0.13 (0.09; 0.24) 0.078 -13 MEHP 4.98 (3.63; 7.15) 4.94 (3.07; 7.65) 3.72 (2.20; 5.62) 3.31 (2.04; 4.87) 3.44 (1.77; 5.17) 2.64 (1.76; 4.45) 2.04 (1.29; 3.22) 1.68 (0.92; 2.99) <0.001 -66 MEHHP 21.1 (15.5; 28.7) 18.7 (12.4; 25.7) 16.0 (11.5; 22.4) 13.1 (10.3; 19.0) 12.9 (9.22; 18.8) 10.4 (7.81; 16.2) 9.64 (7.23; 15.0) 9.11 (7.05; 12.2) <0.001 -57 MEOHP 13.2 (9.66; 17.7) 11.3 (7.95; 15.5) 9.45 (6.80; 12.9) 8.16 (6.10; 11.1) 8.05 (5.38; 11.3) 6.44 (4.88; 9.81) 6.03 (4.33; 8.81) 5.54 (4.11; 7.45) <0.001 -58 MECPP 21.4 (16.9; 28.1) 18.3 (13.7; 26.6) 15.8 (11.0; 20.8) 13.9 (10.2; 18.8) 12.5 (9.40; 18.8) 11.4 (8.28; 16.8) 10.2 (6.88; 14.0) 8.17 (7.08; 12.6) <0.001 -62 MBzP 8.81 (5.65; 13.2) 7.63 (4.82; 12.1) 5.94 (4.31; 11.2) 5.92 (3.67; 9.28) 5.61 (3.43; 7.99) 4.00 (2.38; 7.88) 3.50 (2.14; 5.83) 3.11 (1.98; 4.99) <0.001 -65
Solely chemicals which were detected above the limit of detection (LOD) for > 33% of the samples were included. Values with a detection LOD were imputed with “LOD/√2”. To account for dilution, raw concentrations (ng/ml) were multiplied by urine volume leading to total excretions (µg/24h). Medians and interquartile ranges were calculated
for each year. p-values for linear trend (p-trend) were calculated by modelling the median concentration of each year as a continuous variable. The change between 2009 and 2016 was calculated as: “(median2016 – median2009)
Su p p lement ar y t ab le 4 a. C o rr el at io n p at te rn s b et w ee n p he no ls a nd p ht ha la te s a t b as el in e a nd a t f o llo w -u p . MeP EtP PrP n-BuP B PA BPF MMP MEP MiBP MnBP MEHP MnHP MEHHP MEOHP MECPP MBzP MeP 1 0.57 0.7 0.27 0.08 0.02 -0.01 0.02 0.01 0.07 0.04 0.04 0.14 0.14 0.14 -0.01 EtP 0.5 1 0.32 0.28 0.14 0.09 0.01 -0.01 -0.04 0.06 -0.01 0.12 0.07 0.07 0.08 -0.01 PrP 0.49 0.14 1 0.1 -0.03 -0.03 -0.01 0 0.02 0.08 0.05 -0.05 0.16 0.17 0.17 0 n-BuP 0.3 0.23 0.16 1 0.01 0.11 0.01 0 -0.02 0.06 0.03 -0.07 0.18 0.15 0.18 0 B PA -0.01 0 0.01 -0.02 1 -0.02 -0.01 -0.01 0 -0.03 0.06 0.13 0.11 0.13 0.08 0.02 BPF 0 0.03 -0.05 -0.02 -0.04 1 0 0.15 0.13 -0.01 -0.02 -0.08 -0.02 -0.03 -0.02 0.05 MMP -0.05 0.03 -0.03 -0.06 -0.02 -0.06 1 0.01 0.06 -0.02 0.03 0.08 0.05 0.04 0.08 -0.01 MEP 0.04 0.02 0.01 -0.03 -0.01 -0.03 0.11 1 0.03 0.07 0.03 0.03 0.12 0.12 0.11 0.02 MiBP 0.04 0 -0.02 0 -0.03 -0.05 0.04 0.09 1 0.09 0.14 0.03 0.18 0.19 0.21 0.04 MnBP 0.04 0.14 0.15 -0.02 0.01 0.03 -0.03 0 0.01 1 0.15 0 0.45 0.42 0.39 0.01 MEHP 0.13 0.1 0.13 0.66 0.01 -0.03 0.06 0.08 0.09 0.03 1 0.17 0.55 0.57 0.55 0.05 MnHP -0.06 -0.04 -0.05 -0.03 0.02 -0.01 -0.04 0.02 0.01 0 -0.01 1 0.12 0.12 0.1 0.06 MEHHP 0.2 0.15 0.1 0.81 0 -0.02 0.03 0.03 0.06 0 0.69 0 1 0.98 0.93 0.03 MEOHP 0.18 0.13 0.1 0.75 0 -0.02 0.03 0.02 0.07 0 0.7 0 0.98 1 0.95 0.04 MECPP 0.17 0.12 0.09 0.72 0.01 -0.04 0.03 0.03 0.08 0 0.69 0 0.96 0.98 1 0.04 MBzP 0.01 -0.03 0.1 0.09 0.01 0.01 0.08 0.08 0.2 0 0.07 -0.03 0.06 0.07 0.07 1 Pearson corr
elation between baseline phenols and phthalates ar
e depicted in
the
upper triangle, wher
eas corr
elations between follow-up chemicals ar
e shown in
the
lower triangle. Full names of
the
abbr
eviated chemicals ar
7
Su p p lement ar y t ab le 4 b . C o rr el at io n p at te rn s b et w ee n p he no ls a nd p ht ha la te s a t b as el in e v er su s f o llo w -u p . MeP EtP PrP n-BuP B PA BPF MMP MEP MiBP MnBP MEHP MnHP MEHHP MEOHP MECPP MBzP MeP 0.3 0.26 0.2 0.32 0.03 -0.02 0.06 -0.02 0.01 -0.01 0.21 0.04 0.35 0.35 0.33 -0.07 EtP 0.15 0.33 0.11 -0.07 0 -0.01 0.09 -0.02 -0.04 0.02 0.02 0 0.02 0.04 0.05 -0.09 PrP 0.23 0.11 0.23 0.44 0.07 -0.05 -0.01 -0.04 0 -0.03 0.31 -0.05 0.49 0.5 0.49 -0.03 n-BuP 0.15 0.03 0.11 0.03 0.01 -0.06 -0.06 -0.02 -0.03 -0.02 0.04 -0.06 0 -0.01 0 -0.07 B PA 0.05 0.24 -0.09 0.01 -0.01 -0.02 -0.03 -0.04 0.33 -0.01 -0.05 0.04 -0.04 -0.03 -0.03 -0.05 BPF 0.07 0.02 0.05 -0.04 0.01 0.16 -0.02 -0.03 0.03 -0.02 -0.01 0.07 -0.01 -0.01 -0.02 0.08 MMP -0.01 0 0.02 -0.03 -0.01 -0.03 0.23 0.02 0.08 -0.01 -0.05 -0.06 -0.01 -0.01 0 0.09 MEP 0.05 0.01 -0.01 0.01 -0.01 0 0.2 0.13 0 0 -0.05 -0.01 0 0 0 0 MiBP 0.04 0.01 -0.03 -0.02 -0.02 0.37 0.02 0.01 0.22 0.03 0.05 0.11 0.03 0.03 0.04 0.11 MnBP 0.06 0.08 0.09 -0.03 0 -0.03 -0.04 0.04 0.03 0.41 0.01 -0.02 0.01 0 0 0.21 MEHP 0 0.03 0.02 0.04 0.01 -0.06 0.23 0.01 0.05 0.05 0.32 -0.04 0.09 0.1 0.08 0 MnHP -0.01 0.08 0.01 0 -0.03 0.07 0.16 -0.01 0 0.01 0.03 0.05 0.05 0.04 0.04 0.03 MEHHP 0 0.04 -0.01 0 -0.02 -0.06 0.24 -0.04 0.09 0.01 0.08 -0.04 0.09 0.07 0.06 0.01 MEOHP -0.01 0.05 0 0 -0.03 -0.07 0.21 -0.05 0.12 0.02 0.1 -0.05 0.1 0.11 0.1 0.01 MECPP 0.01 0.05 0 -0.01 -0.02 -0.09 0.26 -0.04 0.1 0.03 0.09 -0.04 0.08 0.09 0.12 0.02 MBzP -0.02 -0.01 -0.02 0.15 0 -0.01 0.05 -0.02 -0.01 -0.01 0.02 -0.01 0.02 0.03 0.02 0.08 Pearson correlations between phenols and phthalates at baseline and follow-up. Full names of
the
abbr
eviated chemicals ar
Supplementary table 5a. Spearman correlation coefficients between baseline and follow-up measurements
Metabolite <48 months ≥48 months Total
MeP 0.4 (0.29; 0.49) 0.52 (0.42; 0.61) 0.46 (0.39; 0.53) EtP 0.4 (0.28; 0.51) 0.4 (0.28; 0.5) 0.4 (0.32; 0.48) PrP 0.39 (0.23; 0.53) 0.37 (0.22; 0.51) 0.38 (0.27; 0.48) n-BuP 0.39 (0.18; 0.56) 0.44 (0.2; 0.63) 0.49 (0.35; 0.61) BPA 0.21 (0.06; 0.36) 0.14 (-0.01; 0.29) 0.19 (0.08; 0.29) BPF 0.25 (0.02; 0.45) 0.19 (-0.03; 0.39) 0.21 (0.05; 0.35) MMP 0.37 (0.21; 0.51) 0.29 (0.11; 0.44) 0.33 (0.22; 0.44) MEP 0.33 (0.22; 0.44) 0.25 (0.13; 0.37) 0.3 (0.21; 0.37) MiBP 0.6 (0.52; 0.67) 0.46 (0.35; 0.55) 0.52 (0.46; 0.58) MnBP 0.5 (0.4; 0.59) 0.41 (0.3; 0.51) 0.46 (0.38; 0.52) MEHP 0.57 (0.48; 0.65) 0.53 (0.43; 0.61) 0.55 (0.48; 0.61) MnHP 0.43 (0.25; 0.58) 0.21 (0; 0.4) 0.32 (0.19; 0.44) MEHHP 0.39 (0.28; 0.49) 0.22 (0.1; 0.34) 0.3 (0.22; 0.38) MEOHP 0.38 (0.27; 0.48) 0.22 (0.1; 0.34) 0.29 (0.2; 0.37) MECPP 0.47 (0.37; 0.56) 0.28 (0.16; 0.39) 0.37 (0.29; 0.44) MBzP 0.5 (0.41; 0.59) 0.34 (0.22; 0.45) 0.43 (0.35; 0.5)
Spearman correlation coefficients between endocrine disrupting chemicals at baseline and at follow-up were calculated after stratifying for time to follow-up (<48 months versus ≥48 months) and in total. These coefficients are rank-order based, and thus not affected by the general decrease in EDC exposure we observed over time. Full names of the abbreviated chemicals are shown in table 1.
Supplementary table 5b. Intraclass correlation coefficients between baseline and follow-up measurements
Metabolite <48 months ≥48 months Total
MeP 0.38 (0.27; 0.48) 0.42 (0.31; 0.52) 0.4 (0.32; 0.47) EtP 0.39 (0.27; 0.49) 0.39 (0.27; 0.5) 0.39 (0.31; 0.47) PrP 0.37 (0.21; 0.52) 0.29 (0.13; 0.44) 0.34 (0.22; 0.44) n-BuP 0.4 (0.2; 0.57) 0.26 (0; 0.49) 0.37 (0.21; 0.5) BPA 0.18 (0.03; 0.32) 0.11 (-0.04; 0.26) 0.15 (0.04; 0.25) BPF 0.3 (0.08; 0.49) 0.17 (-0.04; 0.38) 0.23 (0.08; 0.38) MMP 0.39 (0.23; 0.53) 0.32 (0.15; 0.47) 0.35 (0.24; 0.46) MEP 0.27 (0.15; 0.38) 0.21 (0.08; 0.32) 0.24 (0.15; 0.32) MiBP 0.48 (0.39; 0.57) 0.21 (0.09; 0.33) 0.34 (0.26; 0.41) MnBP 0.46 (0.36; 0.55) 0.25 (0.12; 0.36) 0.37 (0.29; 0.44) MEHP 0.42 (0.32; 0.52) 0.21 (0.09; 0.33) 0.32 (0.24; 0.4) MnHP 0.34 (0.15; 0.51) 0.08 (-0.13; 0.28) 0.18 (0.04; 0.32) MEHHP 0.22 (0.1; 0.34) -0.05 (-0.17; 0.08) 0.09 (0; 0.18) MEOHP 0.23 (0.11; 0.34) -0.02 (-0.15; 0.1) 0.10 (0.01; 0.19) MECPP 0.29 (0.17; 0.39) 0.04 (-0.09; 0.17) 0.16 (0.07; 0.24) MBzP 0.44 (0.34; 0.53) 0.07 (-0.05; 0.2) 0.25 (0.17; 0.33)
Intraclass correlation coefficients between endocrine disrupting chemicals at baseline and at follow-up were calculated after stratifying for time to follow-up (<48 months versus ≥48 months) and in total. These coefficients present the within-person reproducibility of the compounds. Full names of the abbreviated chemicals are shown in table 1.
7
Supplementary table 5c. Kappa statistics between categorized baseline and follow-up measurements.Metabolite <48 months ≥48 months Total
MeP 0.36 (0.25; 0.47) 0.46 (0.36; 0.56) 0.44 (0.37; 0.52) EtP 0.37 (0.26; 0.48) 0.37 (0.25; 0.49) 0.4 (0.32; 0.48) BPA 0.23 (0.11; 0.35) 0.23 (0.1; 0.35) 0.25 (0.17; 0.34) MEP 0.3 (0.18; 0.41) 0.27 (0.14; 0.39) 0.28 (0.19; 0.36) MiBP 0.55 (0.46; 0.64) 0.43 (0.32; 0.53) 0.48 (0.41; 0.55) MnBP 0.47 (0.36; 0.57) 0.39 (0.26; 0.51) 0.44 (0.36; 0.51) MEHP 0.54 (0.45; 0.63) 0.58 (0.49; 0.67) 0.54 (0.47; 0.61) MEHHP 0.34 (0.23; 0.45) 0.22 (0.1; 0.34) 0.29 (0.21; 0.37) MEOHP 0.36 (0.25; 0.47) 0.22 (0.09; 0.34) 0.26 (0.18; 0.34) MECPP 0.45 (0.35; 0.55) 0.27 (0.15; 0.39) 0.34 (0.26; 0.42) MBzP 0.49 (0.4; 0.58) 0.33 (0.21; 0.44) 0.41 (0.33; 0.48)
Kappa statistics coefficients between endocrine disrupting chemicals at baseline and at follow-up were calculated after stratifying for time to follow-up (<48 months versus ≥48 months) and in total. Kappa statistics were calculated after categorizing the endocrine disrupting chemicals into four quartiles based on exposure, and thus depict the reproducibility of categorized chemicals. Full names of the abbreviated chemicals are shown in table 1.
Supplementary table 6a. Consistency of endocrine disrupting chemicals after categorization based on baseline exposure.
Metabolite
Number of categories change Remains
0 1 2 3 Lowest Highest MeP 194 (39) 191 (38) 89 (18) 26 (5) 86 (69) 39 (31) EtP 199 (40) 193 (39) 74 (15) 34 (7) 74 (59) 42 (34) BPA 187 (37) 181 (36) 86 (17) 46 (9) 64 (51) 33 (26) MEP 173 (35) 184 (37) 103 (21) 40 (8) 71 (57) 24 (19) MiBP 182 (36) 192 (38) 93 (19) 33 (7) 100 (80) 32 (26) MnBP 184 (37) 182 (36) 97 (19) 37 (7) 93 (74) 35 (28) MEHP 182 (36) 192 (38) 95 (19) 31 (6) 105 (84) 30 (24) MEHHP 154 (31) 166 (33) 115 (23) 65 (13) 99 (79) 14 (11) MEOHP 144 (29) 175 (35) 116 (23) 65 (13) 97 (78) 14 (11) MECPP 147 (29) 187 (37) 109 (22) 57 (11) 96 (77) 12 (10) MBzP 186 (37) 165 (33) 99 (20) 50 (10) 99 (79) 39 (31)
Individuals are categorized into four quartiles based on the cut-off values of baseline exposure. The first columns express the number individuals (and percentage) which change categories. Zero remain in the same category, whereas three shifts from the highest exposure category to the lowest exposure category, or the other way around. The last two columns show the number of individuals (percentage) which were categorized in the lowest and highest exposure category, respectively, and remain in the same category based on their follow-up measurement. Full names of the abbreviated chemicals are shown in table 1.
Supplementary table 6b. Consistency of endocrine disrupting chemicals after independent categorization based on exposure at both timepoints.
Metabolite
Number of categories change Remains
0 1 2 3 Lowest Highest MeP 194 (39) 210 (42) 76 (15) 20 (4) 62 (50) 63 (50) EtP 209 (42) 185 (37) 77 (15) 29 (6) 62 (50) 60 (48) BPA 183 (37) 192 (38) 77 (15) 48 (10) 59 (47) 41 (33) MEP 184 (37) 181 (36) 98 (20) 37 (7) 59 (47) 43 (34) MiBP 213 (43) 193 (39) 79 (16) 15 (3) 68 (54) 62 (50) MnBP 212 (42) 191 (38) 72 (14) 25 (5) 67 (54) 64 (51) MEHP 224 (45) 200 (40) 62 (12) 14 (3) 73 (58) 68 (54) MEHHP 159 (32) 209 (42) 103 (21) 29 (6) 55 (44) 41 (33) MEOHP 160 (32) 203 (41) 102 (20) 35 (7) 55 (44) 41 (33) MECPP 171 (34) 208 (42) 95 (19) 26 (5) 58 (46) 45 (36) MBzP 194 (39) 199 (40) 84 (17) 23 (5) 61 (49) 55 (44)
Individuals are categorized into four quartiles based on the cut-off values of baseline exposure and follow-up exposure independent of each other, leading to four groups of 125 individuals at both baseline and follow-up. The first columns express the number individuals (and percentage) which change categories. Zero remain in the same category, whereas three shifts from the highest exposure category to the lowest exposure category, or the other way around. The last two columns show the number of individuals (percentage) which were categorized in the lowest and highest exposure category, respectively, and remain in the same category based on their follow-up measurement. Full names of the abbreviated chemicals are shown in table 1.
7
Su ppl em en ta ry fi gu re 2. C or re la tio ns b et w ee n e nd oc rin e d isr up tin g c he m ic als e xp os ur e at bas el in e a nd ex po su re at fo llo w -up . A bbr ev ia tion s: B M I, body m as s i nde x. Sp ear m an co rrel at io n co ef fic ien ts o f en do cr in e d isr up tin g ch em ical s ( ED Cs) at b as el in e ( lo w er tr ian gl e) and fol lo w -up (uppe r t ria ng le ). A ) d ep ic ts u nad ju sted c or re la tio n co ef fic ien ts, w he reas B ) sh ow s p ar tia l co rr el at io n co ef fic ien ts ad ju sted fo r ag e an d se x an d co ef fici en ts d isp lay ed in C ) a re a dj ust ed fo r ag e, sex , B MI an d sm ok in g st at us . A t p lac es w he re th e co lo ur in g i s sy m m et rica l acr oss th e d iag on al , co rr el at io ns a re r ob ust acr oss tim e. B MI w as ca teg or iz ed a s n or m al w ei gh t ( ref er en ce ), o ver w ei gh t an d o be se; S m ok in g st at us w as cat eg or iz ed as nev er sm ok er (r ef er en ce ), ev er -sm ok er an d cu rren t sm ok er . F ul l na m es of E D C a bbr ev ia tions a re show n i n S upp le m ent ar y t ab le 2. Supplementary figur e 2. Corr elations between endocrine disrupting chemicals exposur e at baseline and exposur e at follow-up. Abbr eviations: BMI, bodymass index. Spear
man corr
elation coef
ficients of endocrine disrupting chemicals (EDCs) at baseline (lower triangle) and follow-up (upper triangle). A) depicts
unadjusted corr
elation coef
ficients, wher
eas B) shows partial corr
elation coef
ficients adjusted for age and sex and coef
ficients displayed in C) ar
e adjusted for
age, sex, BMI and smoking status. At places wher
e
the
colouring is symmetrical acr
oss the diagonal, corr elations ar e r obust acr
oss time. BMI was categorized
as nor
mal weight (r
efer
ence), overweight and obese; Smoking status was categorized as never smoker (r
efer
ence), ever
-smoker and curr
ent smoker
. Full
names of EDC abbr
eviations ar
Suppl em ent ar y f ig ur e 3 . C or re la tio ns b et w een en do cr in e d isr up tin g ch em ica ls exp os ur e at b as el in e v er su s ex po su re at fo llo w -up A bbr ev ia tion s: B M I, body m as s i nde x. Sp ear m an co rrel at io n co ef fic ien ts o f E D Cs at b ase lin e v er su s t ho se at fo llo w -up. A ) de pi ct s una dj us te d co rrel at io n c oef fici en ts, w her ea s B ) sh ow s p ar tia l co rre lat io n co ef fici en ts ad ju sted fo r ag e a nd se x an d co ef fici en ts di sp lay ed in C ) ar e ad ju st ed fo r ag e, s ex, B M I a nd s m ok ing s ta tus . T he d ia gona l de pi ct s c oe ffi ci en ts be tw ee n t he b as el ine a nd fol low -u p o f t he sam e ch em ical s. BMI w as cat eg or iz ed as no rm al w ei gh t ( re fer en ce ), o ver w ei gh t a nd o bes e; S m ok in g st at us w as ca teg or iz ed a s n ev er sm ok er (r ef er en ce ), e ve r-s m ok er a nd cu rren t sm ok er . F ul l n am es of E D C a bb re vi at ion s a re show n i n S up pl em ent ar y t ab le 2. Supplementary figur e 3. Corr
elations between endocrine disrupting chemicals exposur
e at baseline versus exposur
e at follow-up. Abbr
eviations: BMI,
body mass index. Spear
man corr
elation coef
ficients of EDCs at baseline versus those at follow-up. A) depicts unadjusted corr
elation coef
ficients, wher
eas
B) shows partial corr
elation coef
ficients adjusted for age and sex and coef
ficients displayed in C) ar
e adjusted for age, sex, BMI and smoking status.
The
diagonal depicts coef
ficients between
the
baseline and follow-up of
the
same chemicals. BMI was categorized as nor
mal weight (r efer ence), overweight and obese; Smoking status was categorized as never smoker (refer ence), ever -smoker and curr ent smoker . Full names of EDC abbr eviations ar e shown in Supplementary table 2.
