Human biomonitoring and exposure risk assessment to phthalates, parabens, benzophenone-3, bisphenols and triclosan in the adult population of Kinshasa, Democratic Republic of Congo (D.R.C): a cross-sectional study

Human biomonitoring and exposure risk assessment to phthalates, parabens, benzophenone-3, bisphenols and triclosan in the adult population of Kinshasa, Democratic Republic of Congo (D.R.C): a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Human biomonitoring and exposure risk assessment to phthalates, parabens, benzophenone-3, bisphenols and triclosan in the adult population of Kinshasa, Democratic Republic of Congo (D.R.C): a cross-sectional study Trésor Bayebila Menanzambi, Catherine Pirard, Cédric Ilunga wa Kabuaya, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8473872/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background : Phthalates, parabens, benzophenone-3, bisphenols and triclosan are among the contaminants suspected of being involved in several hormone-related pathologies. In developing countries, weak regulations and lack of a precise monitoring plan lead to exposures that could be much worse than in developed countries. The objectives of this study were to evaluate the level of exposure of the adult population of Kinshasa (D.R.C) to these compounds and to assess the health risk induced by these pollutants. Methods : Concentrations of four parabens, nine phthalate metabolites, two non-phthalate plasticizers, benzophenone-3, three bisphenols and triclosan were assessed in the urine of 145 volunteers recruited in Kinshasa. Measurements were performed using a liquid or a gas chromatography coupled to a mass spectrometer. Results : Detected in more than 95% of the samples with median concentrations in bracket, methylparaben (MeP) (62.6 µg/L), mono-n-butyl phthalate (MnBP) (78.1 µg/L) and bisphenol-A (BPA) (1.54 µg/L) were the most abundant compounds for parabens, phthalates metabolites and bisphenols, respectively. Globally, the current exposure seemed to be much higher for some phthalates and parabens compared to Western countries. For some phthalates, a non-neglectable part of the population studied exceeded human biomonitoring guidance values proposed by the HBM4EU consortium, meaning that they are expected to be more susceptible to reproductive disorders due to environmental exposure. Conclusion : The exposure of the population of Kinshasa to these pollutants merits consideration, as it constitutes a genuine public health concern. To enhance the protection of the population and its ecosystem, regulatory measures must be implemented and large-scale studies conducted. urinary pollutants phthalates parabens bisphenols triclosan benzophenone-3 adult population Kinshasa Figures Figure 1 Figure 2 Text box 1. Contributions to the Literature The first large-scale biomonitoring study of non-persistent organic pollutants in the general adult population of the DRC and particularly, in Kinshasa; The compounds investigated are widely used in the production of everyday items and are currently being investigated for their potential negative impact on human and environmental health; The study provides reliable environmental data that highlights the urgent need for measures to restore environmental balance. Background For decades, humans have been synthetizing a growing number of chemicals used in agriculture, chemical or plastic industries, food production, pharmaceutical and cosmetics, and more. These chemicals have beneficial effects on human life, including increased agricultural yield, protection against or treatment of diseases, and the production of inexpensive and durable everyday products. Phthalates, for example, are a group of compounds that make plastics more flexible and help certain cosmetics to penetrate the skin [ 1 ]. Parabens are widely used as preservatives in perishable products [ 2 ]. Benzophenone-3, an ultraviolet filter, is added to body care products to enhance skin protection, prevent photoaging, and reduce the risk of skin cancer [ 3 ]. Bisphenols are essential monomers used to manufacture polymerized plastics (polycarbonates) and epoxy resins. They are found in cans, baby bottles, plastic toys and clear water bottles. Triclosan is an antimicrobial agent that is often added to personal care products [ 4 ]. However, despite the benefits these compounds provide to human health and well-being, many of these compounds are suspected of being harmful to humans and biodiversity by acting as endocrine disruptors. They are thought to be implicated in the rising prevalence of various hormone-related pathologies including, but not limited to, fertility disorders [ 5 – 7 ], metabolic pathologies [ 8 , 9 ], and cancers of the endocrine glands [ 10 , 11 ]. Consequently, regulatory agencies such as the European Food Safety Authority (EFSA) and the U.S. Environmental Protection Agency (US EPA) have classified some of these molecules, including phthalates and bisphenols, as substances of very high concern [ 12 , 13 ]. On the other hand, the number of morbidity and mortality cases linked to chronic hormonal diseases is constantly rising in the Democratic Republic of the Congo (D.R.C). For example, cases of thyroid cancer have doubled in recent decades [ 14 , 15 ]. According to the International Diabetes Federation, the incidence of type 2 diabetes in the D.R.C has increased from 3.1% of the adult population in 2011 to 7.7% in 2024, and would be one of the causes of underdevelopment [ 16 ]. In light of the rising incidence of these endocrine-related pathologies, the question of the implication of the population’s exposure to pollutants in the DRC could be reasonably raised. To answer to this question, the first step is to accurately evaluate the exposure of the population of the D.R.C to potentially toxic compounds. Over time, a reduction in human exposure to some of these compounds has been observed in Europe and the United States, following the enhancement of regulatory measures implemented since the 2000s [ 12 , 17 – 19 ]. However, in developing countries such like D.R.C, weak regulations and a lack of a precise monitoring plans result in the unrestricted addition of these compounds to many everyday items. This leads to exposures that could be much worse than in developed countries [ 20 , 21 ]. Additionally, the absence of an effective waste management policy coupled with the tropical climate would facilitate the accumulation of these substances in various environmental compartments, threatening ecosystems and human health [ 22 ]. Unlike some other African countries such as South Africa, Egypt, Nigeria, Tunisia, Ghana, etc., which have data on non-persistent pollutants in environmental and biological matrices, the D.R.C lags behind in this area [ 22 – 24 ] although the use of these compounds in everyday items is expected to be extensive. There are several reasons for this delay, including a lack of specialized laboratories in the country, limited international funding, and a failure to address this issue in national health priorities. To begin to fill this gap, we conducted in 2019 a pilot study based on 15 volunteers recruited among the adult population in Kinshasa, and observed particularly high levels of parabens, benzophenone-3, triclosan, bisphenol A, and some phthalate metabolites in their urine [ 25 ]. The aim of the present study is to confirm these results by measuring levels of these pollutants in the urine of a larger cohort of adults recruited in Kinshasa and to assess their exposure risk. For this purpose, 145 volunteers were recruited between 2022 and 2023, and 4 parabens, 9 phthalate metabolites, 2 non-phthalate plasticizers, 3 bisphenols, benzophenone-3 and triclosan were measured in spot urine samples. This is the first large-scale biomonitoring study of non-persistent organic pollutants in the general adult population of the D.R.C and particularly, in Kinshasa. Methods Volunteer recruitment and sample collection The study was carried out in Kinshasa, the capital of the Democratic Republic of the Congo (D.R.C), and targeted adults aged 18 and over. The participants were stratified into five age groups: 18–29, 30–39, 40–49, 50–59, and ≥ 60 years. Outreach sites and recruitment process were previously described in Bayebila et al., 2025 [ 26 ]. Between November 2022 and January 2023, 145 volunteers, ranging in age from 18 to 80, were recruited from across the city (Fig. 1 ). Volunteers were asked to provide a random urine spot in the morning, either fasting or not. The sample was collected in a polypropylene vial after the volunteer completed a form providing information on their lifestyle and anthropometric measurements. The samples were then placed in an isothermal box and transported to the Physical Chemistry and Biopharmaceutics Laboratory at the Faculty of Pharmaceutical Sciences of the University of Kinshasa. There, the samples were stored at -20°C, before being sent to the Clinical, Forensic and Environmental Toxicology Laboratory at the University of Liège (Belgium) for chemical analysis. Chemical analysis The concentrations of four parabens, namely, methylparaben (MeP), ethylparaben (EtP), propylparaben (PrP) and n-butylparaben (nBP), nine phthalate metabolites, namely, monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), mono-2-ethylhexyl phthalate (MEHP), mono-2-ethyl-5-hydroxyhexyl phthalate (5-OH-MEHP), mono-2-ethyl-5-oxohexyl phthalate (5-oxo-MEHP), 7-carboxy octyl phthalate (7-cxOP), 6-hydroxypropylheptyl phthalate (6-OH-PrHpP), and monobenzyl phthalate (MBzP), two non-phthalate plasticizers (substitutes for phthalates), namely, cyclohexane-1,2-dicarboxylate-mono-(7-hydroxy-4-methyl)octyl ester (OH-MINCH) and cyclohexane-1,2-dicarboxylate-mono-(7carboxylate-4-methyl)heptyl ester (cx-MINCH), and benzophenone-3 (BP-3) were measured in urine according to the method extensively described in Dewalque et al., 2014 [ 27 ]. In brief, after enzymatic beta-glucuronidase hydrolysis of the samples, the samples were extracted on a solid-phase extraction Bond Elut Certify cartridge 10cc (130 mg) from Agilent. After evaporation and reconstitution in a mixture of mobile phases (acetic acid (0.1%) in water/acetic acid (0.1%) in acetonitrile), the samples were analyzed on a liquid chromatography Acquity UPLC system coupled to a mass spectrometer Quattro Premier XE (Waters, Milford, MA, USA). Bisphenols (namely, bisphenol-A (BPA), bisphenol-F (BPF), bisphenol-Z (BPZ)) and triclosan (TCS) contaminations were assessed using an Agilent 7890A GC/ 7000A GC Triple Quad mass spectrometer (Agilent Technologies, California, USA). The sample preparation encompassed a simultaneous double enzymatic hydrolysis with beta-glucuronidase and sulfatase, followed by an extraction on solid phase cartridge (Oasis HLB, 60 mg, 3 cc from Waters) and subsequent a liquid/liquid extraction. After the evaporation of the organic phase, extracts were derivatized using N-methyl-N-trimethylsilyl trifluoroacetamide before injection on GC-MS/MS apparatus. This method was extensively detailed in Pirard et Charlier 2022 [ 17 ]. Quality assurance The analytical methods used for this study were previously validated according to the total error approach [ 28 , 29 ]. The limits of quantification (LOQ) for each pollutant are gathered in Table 1 and were defined as the smallest concentrations measurable in samples with a total error not exceeding 30%. Materials from previous external quality controls were included in each batch of samples (G-EQUAS from the Out-Patient Clinic for Occupational, Social and Environmental Medicine of the University Erlangen-Nuremberg, for all investigated pollutants and OSEQAS from the Institut national de santé publique Québec, for bisphenols and triclosan). Each sequence also contained a procedural blank. Table 1 Descriptive statistics of non-persistent organic pollutants in urine Pollutant LOQ (µg/L) DF (%) Mean SD GM P25 P50 P75 P95 Range Parabens MeP 2.00 99 282 1021 59.9 15.2 62.6 216 853 <LOQ – 11,442 EtP 0.30 44 2.80 8.60 0.401 <LOQ <LOQ 1.20 12.5 <LOQ − 66.1 PrP 0.36 95 84.7 194 10.1 1.50 7.50 52.8 439 <LOQ – 1365 nBP 6.00 6 <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ <LOQ − 6.51 Phthalates MEP 0.94 99 373 1,053 74.8 25.4 61.3 229 1,59 <LOQ – 7,194 MnBP 0.99 100 105 105 70.1 41.8 78.1 143 270 2.31–815 MiBP 1.23 99 26.4 24.5 17.7 10.6 17.1 32.2 79.9 <LOQ – 115 MEHP 0.62 95 7.10 25.1 3.20 1.40 3.10 5.90 16.4 <LOQ – 294 5-oxo-MEHP 0.53 99 15.5 79.3 6.40 3.50 6.30 10.8 21.9 <LOQ – 955 5-OH-MEHP 0.43 100 30.1 175 11.2 6.01 11.4 19.4 44.7 0.601- 2,108 Sum of DEHP metabolites* 52.8 278 21.9 12.6 21.5 36.3 81.5 1.74–3,357 MBzP 0.61 51 1.40 5.90 0.701 <LOQ <LOQ 1.10 3.20 <LOQ − 69.9 7-cxOP 2.00 68 4.10 3.80 3.10 1.40 2.90 5.10 9.20 <LOQ − 31.7 6-OH-PrHpP 2.00 6 <LOQ 2.80 <LOQ <LOQ <LOQ <LOQ 2.50 <LOQ – 30.4 OH-MINCH 2.00 6 <LOQ 1.50 <LOQ <LOQ <LOQ <LOQ 2.15 <LOQ – 12.2 cx-MINCH 2.00 6 <LOQ 1.20 <LOQ <LOQ <LOQ <LOQ 2.30 <LOQ – 10.2 Benzophenone BP-3 0.20 96 2.60 4.30 1.50 0.701 1.40 2.80 7.01 <LOQ − 37.5 Bisphenols BPA 0.29 98 2.91 6.48 1.63 0.971 1.54 2.32 8.33 <LOQ – 55.9 BPF 0.07 69 0.265 0.789 0.134 <LOQ 0.130 0.235 0.667 <LOQ – 8.95 BPZ 0.06 10 <LOQ 0.06 <LOQ <LOQ <LOQ <LOQ 0.0919 <LOQ – 0.483 Triclosan TCS 0.33 100 158 379 53.2 24.6 50.2 125 499 1.55–3,152 *Sum of DEHP metabolites = MEHP + 5-oxo-MEHP + 5-OH-MEHP; LOQ: Limit of Quantification; DF: Detection Frequency; SD: Standard Deviation; GM: Geometric Mean. Statistical analysis Statistical analyses were performed to identify parameters associated with levels of contamination. Prior to statistical analysis, contaminant levels below the LOQ were replaced by the LOQ multiplied by the detection frequency (DF) of the compound in our population. Contaminants with a DF below 70% were dichotomized (detected vs. not detected). Pollutant concentrations were not normally distributed (Shapiro-Wilk test < 0.05), therefore non-parametric tests (Kruskal-Wallis, Mann-Whitney) and Spearman correlation were used for quantitative variables. For categorical variables and pollutants with DF < 70%, chi-squared test was used. Principal component analysis (PCA) was used to investigate the correlation between quantitative variables and to gain insight into common sources of exposure. P-value ≤ 0.05 was considered significant. RStudio, Rcmdr software (version 3.6.3., CRAN) and Excel 2013 (Microsoft, Redmond, WA) were used for statistical processing of data. Exposure risk assessment One of the main objectives of this study was to evaluate the health risks associated with exposure to pollutants among the population of Kinshasa. To accomplish this, we compared urinary pollutant levels measured in our population with reference levels provided by scientific authorities and working groups. The European Initiative HBM4EU provided human biomonitoring guidance values (HBM-GVs) for BPA, MnBP, MiBP and the sum of 5-oxo-MEHP and 5-OH-MEHP [ 30 , 31 ]. These HBM-GVs are defined as the concentration in a biological matrix (i.e. urine) at and below which negative health effects are not expected based on the current knowledge. We then compared urinary concentrations of these compounds in our cohort to the corresponding HBM-GVs proposed by Apel et al., 2023 [ 30 ]. A human biomonitoring value I (German HBM-I value are similar to HBM-GV from HBM4EU) was also proposed by the German Human Biomonitoring Commission for TCS [ 32 ]. To the best of our knowledge, no HBM-GV or associated threshold is available for parabens. Nevertheless, in 2004, the European Food Safety Authority (EFSA) established an Acceptable Daily Intake (ADI) of 0–10 mg/kg body weight per day (mg/kg bw/day) for the sum of MeP and EtP. Therefore, for each volunteer in our study, we calculated an estimated daily intake (EDI) based on the formula proposed by Ma et al., 2013 [ 33 ]: $$\:EDI=\frac{50\times\:{C}_{i}\times\:\text{V}}{BW}$$ where C i is the sum of the urinary concentrations of MeP and EtP (µg/L), V(L/day) is the daily urine excretion rate (a value of 1.7 L/day was used for adults) and BW (kg) is the body weight of each participant. We then compared the EDIs with the ADI provided by the EFSA. Results Table 1 shows the detection frequencies (%), the limits of quantification of the methods used and the descriptive statistical parameters for each pollutant, all of which are expressed in µg/L. The sociodemographic characteristics of the population under study were previously reported in Bayebila et al. (2025) [ 26 ]. Overall, males were overrepresented, accounting for 64.1% of the sample. The mean age was 36.9 years (range 18–80 years) and the mean BMI was 25.6 kg/m² (range 15.6–43.0 kg/m²). High participation rates were seen among adults aged 18–29 (42.8%), drivers (13.8%) and residents of the Funa district (33.1%). Further details can be found in Table 2 . Table 2 Socio-demographic characteristics of the studied population Total (%) Men (%) Women (%) All 145 (100) 93 (64.1) 52 (35.9) Age (years) Mean 36.9 36.4 37.9 SD 15.7 15.7 15.7 Median 33.0 32.0 34.0 P25 24.0 23.0 25.8 P75 46.0 46.0 48.5 Range 18.0–80.0 18.0–74.0 18.0–80.0 Age categories 18–29 years 62 (42.8) 41 (28.3) 21 (14.5) 30–39 years 28 (19.3) 19 (13.1) 9 (6.20) 40–49 years 23 (15.8) 14 (9.65) 9 (6.20) 50–59 years 14 (9.66) 6 (4.14) 8 (5.52) ≥ 60 years 18 (12.4) 13 (8.96) 5 (3.45) BMI (kg/m²) Mean 25.6 25.0 26.6 SD 4.92 4.59 5.35 Median 25.3 25.0 25.7 P25 22.1 21.9 23.3 P75 28.0 26.9 29.1 Range 15.6–43.0 15.6–39.6 16.0–43.0 ˂18.5 7 (4.83) 6 (4.14) 1 (0.69) 18.5–24.9 63 (43.4) 41 (28.2) 22 (15.2) 25.0-29.9 52 (35.9) 34 (23.5) 18 (12.4) ≥ 30 23 (15.9) 12 (8.27) 11 (7.59) Activities Drivers 20 (13.8) 20 (13.8) 0 (0.0) Teachers 19 (13.1) 14 (9.7) 5 (3.4) Traders 16 (11.0) 9 (6.2) 7 (4.8) Students 16 (11.0) 11 (7.6) 5 (3.4) Medical staff 16 (11.0) 6 (4.1) 10 (6.9) Others 58 (40.0) 33 (22.8) 25 (17.2) Feed 24 hours before sampling No 8 (5.5) 5 (3.4) 3 (2.1) Vegetables 24 (16.6) 14 (9.7) 10 (6.9) Vegetables and meat 69 (47.6) 46 (31.7) 23 (15.9) Meat 35 (24.1) 22 (15.2) 13 (8.9) Others 9 (6.2) 6 (4.1) 3 (2.1) Area of residence Tshangu 29 (20.0) 19 (13.1) 10 (6.9) Mont Amba 47 (32.4) 36 (24.8) 11 (7.6) Funa 48 (33.1) 25 (17.2) 23 (15.9) Lukunga 21 (14.5) 13 (9.0) 8 (5.5) BMI : Body Mass Index Table 3 shows the levels of urinary non-persistent organic pollutants in different populations worldwide. Figure 2 and Table 4 respectively present the PCA results for assessing the correlation between pollutants and differences in contamination within Kinshasa's adult population according to certain studied variables. The results for the entire set of chemicals and variables are reported in full in the supplementary materials (Tables S1, S2 and S3). Table 5 summarises the results of the risk assessment linked to exposure to the pollutants investigated. Table 3 Levels of urinary non-persistent organic pollutants in different populations worldwide Population Year of collection Pollutants median values (µg/L) Reference Phthalates MEP MnBP MiBP MEHP 5-OH-MEHP 5-oxo-MEHP Belgium, adult population, N = 92 2018 20.4 11.8 - <LOQ 2.89 1.92 [ 17 ] Danish, Young population, N = 100 2017 23.9 20.9 23.1 1.09 5.64 3.81 [ 12 ] Korea, adult population, N = 3787 2015–2017 25.3 - - 13.7 - [ 9 ] USA, adult population, N = 1862 2017–2018 29.9 9.6 7.4 0.9 4.6 3.1 NHANES 2017-18 German, children and adolescents, N = 2256 2014–2017 23.1 21.0 26.2 1.5 11.1 7.7 [ 18 ] Kinshasa (DRC), adult population , N = 145 2022–2023 61.3 78.1 17.0 3.1 11.4 6.30 This study Parabens MeP PrP EtP Belgium, adult population, N = 92 2018 3.56 <LOQ 0.58 [ 17 ] Korea, adult population, N = 3781 2015–2017 34.6 2.1 36.2 [ 9 ] Sichuan (China), non-occupational population, N = 986 2021 10.1 0.55 0.70 [ 34 ] Nantong city (eastern China), general population, N = 104 2020 3.28* 0.19* 0.45* [ 35 ] Suizhou and Beijing (China), general population, N = 203 2018–2019 7.83 0.614 0.248 [ 36 ] Spain, breastfeeding mothers, N = 180 2015 17.7* [ 37 ] India, young adult women from Assam, N = 52 2020 108 37.1 0.11 [ 38 ] Kinshasa (DRC), adult population , N = 145 2022–2023 62.6 7.5 <LOQ This study Benzophenone BP-3 Belgium, adult population, N = 261 2013 1.3 [ 39 ] Tunisia, women, N = 34 2012 1.73 [ 40 ] Sichuan (China), non-occupational population, N = 986 2021 0.10 [ 34 ] Nantong city (eastern China), general population, N = 104 2020 0.103* [ 35 ] Kinshasa (DRC), adult population , N = 145 2022–2023 1.40 This study Bisphenols BPA BPF BPZ Belgium, adult population, N = 90 2018 0.79 0.12 < LOQ [ 17 ] Korea, adult population, N = 3780 2015–2017 1.3 [ 9 ] Nantong city (eastern China), general population, N = 104 2020 0.398* 0.584* 0.024* [ 35 ] Shenyang, (northeastern China), women, N = 111 2020–2021 4.33 2.86 [ 41 ] Spain, breastfeeding mothers, N = 180 2015 0.927* 0.042* [ 37 ] India, young adult women from Assam, N = 52 2020 < LOQ < LOQ 0.40 [ 38 ] Nigeria, Ota University students, N = 73 ? 2.052 [ 42 ] Kinshasa (DRC), adult population , N = 145 2022–2023 1.54 0.13 < LOQ This study Triclosan TCS China, Sichuan, general adult population, N = 986 2021 10.58 [ 34 ] China, Shenzhen, general adult population, N = 1163 2017 3.67 [ 43 ] China, Guangzhou, general adult population, N = 299 2018–2019 0.737 [ 44 ] Spain, Barcelona, pregnant women, N = 546 2018–2021 0.8 [ 45 ] USA, adult population, N = 1829 2015–2016 3.1 NHANES 2015–2016 Iran, Tehran, pregnant women, N = 189 2019–2020 14.08 [ 46 ] Mexico, low- or middle-income adult women, N = 91 2017–2019 58.8 [ 47 ] Belgium, general population, N = 131 2011 2.24 [ 4 ] Kinshasa (DRC), adult population , N = 145 2022–2023 50.2 This study * : Geometric mean; LOQ: Limit of Quantification Table 4: contamination of the Kinshasa population according to some studied variables Variable Pollutant Median (µg/L) P-value Sex Males Females MeP 35.5 136 0.002 PrP 5.14 16.1 0.010 MEHP 3.99 2.45 0.016 5-OH-MEHP 13.1 8.89 0.003 BP-3 1.16 2.31 0.002 BPA 1.66 1.22 0.029 Area of residence Tshangu Mont Amba Funa Lukunga EtP 0.84 0.22 0.13 0.13 0.016 7-cxOP 3.80 2.24 3.77 2.13 0.037 BPF 0.0968 0.188 0.0897 0.130 0.017 BMI <18.5 18.5-24.9 25.0-29.9 ≥30 MEP 10.1 37.9 90.2 87.6 0.029 Activities Drivers Teachers Traders Student Medical staff Others MiBP 28.1 7.47 23.4 24.3 15.7 17.6 <0.001 MnBP 98.9 27.3 75.7 132 87.3 80.5 <0.001 5-OH-MEHP 19.4 4.16 13.5 12.1 12.7 9.86 <0.001 5-oxo-MEHP 11.1 2.80 6.45 6.65 8.35 5.42 <0.001 Age 18-29 years 30-39 years 40-49 years 50-59 years ≥60 years MiBP 17.0 15.9 26.6 13.5 9.12 0.011 MnBP 84.6 84.8 82.1 55.3 46.5 0.006 BMI : Body Mass Index Table 5 Summary of the exposure risk assessment to pollutants Chemical compounds Reference levels for adults Number of participants exceeding the threshold Urine concentration MnBP 190 µg/L 22 (15%) ∑5-OH-MEHP, 5-oxo-MEHP 500 µg/L 1 (0.7%) MiBP 230 µg/L 0 (0%) BPA 230 µg/L 0 (0%) TCS 3,000 µg/L 1 (0.7%) Tolerable daily intake ∑MeP, EtP 10 mg/kg bw/day 1 (0.7%) Discussion Phthalate metabolites and non-phthalate plasticizers All phthalate metabolites were detected in more than 95% of the samples, except for MBzP (51%) and 7-cxOP (68%). Non-phthalate plasticizers were detected in only 6% of the samples, with concentrations ranging from below the LOQ to 12.2 µg/L, unlike in countries with established regulations on legacy phthalates, where detection of non-phthalate plasticizer alternatives in biological fluids is constantly increasing [ 17 , 19 ], this indicates a very low level of these alternatives in items sold in Kinshasa. The highest median concentrations (Table 1 ) were measured for MnBP (median: 78.1 µg/L, range: 2.31–815 µg/L), followed by MEP (median: 61.3 µg/L, range: <LOQ-7,194 µg/L), and the sum of the di-2-ethylhexyl phthalate (DEHP) metabolites (sum of MEHP + 5-OH-MEHP + 5-oxo-MEHP) (median: 21.5 µg/L, range: 1.74-3,357 µg/L). These levels are consistent with those reported in our 2019 pilot study [ 25 ], suggesting that these molecules are still present in personal care products, as well as in the food packaging, pharmaceutical and cosmetic products sold in the city although they are banned or restricted in several countries [ 17 ]. We reviewed the literature to highlight studies measuring urinary levels of phthalate metabolites in populations recruited in 2015 or later. Over the past decade, phthalate metabolites contamination has been assessed in adult populations in Belgium [ 17 ], Denmark [ 12 ], and Korea [ 9 ], as well as in German children and adolescents [ 18 ]. Finally, we extracted median urinary phthalate concentrations in adults from the National Health and Nutrition Examination Survey (NHANES) dataset. As shown in Table 3 , the MEP levels measured in our cohort are two to three times higher than those reported in developed countries over the past 10 years and the MnBP levels are also several times higher in our population than in other recent cohorts, suggesting the presence of their respective parent compounds, diethyl phthalate and di-n-butyl phthalate, in perfumes, cosmetics and nail polishes sold in Kinshasa. The levels of MiBP and DEHP metabolites are similar to the high levels reported in Denmark, Korea and Germany. Overall, we can conclude that the Kinshasa inhabitants are more exposed to phthalates than individuals from the Western countries. This is likely due to the lack of Congolese legislation on these products, leaving the population exposed. Table 4 shows the significant differences in contamination according to the variables studied in our population. Men, particularly drivers, showed higher levels of DEHP metabolite contamination (Table 4). DEHP (a high-molecular-weight phthalate) was commonly used in food and beverage packaging, as well as in plastics in interior car coatings. The use of this compound is now restricted in Western countries, but not in D.R.C [ 48 , 49 ]. Therefore, food packaging in D.R.C are probably contaminated. Furthermore, most vehicles in Kinshasa are old, secondhand cars imported from Western countries or Asia. Drivers are likely exposed to DEHP through their vehicles, which were produced in countries and/or at times when DEHP was not restricted. Drivers, students, and people aged 18–49, showed relatively high levels of MiBP and MnBP contamination, likely due to their frequent use of cosmetics and nail polishes as they belong to a category that includes young people, a potential user group for body care products (Table 4; p-value < 0.05). Furthermore, overweight and obese adults showed higher levels of MEP contamination (Table 4; p < 0.05), this observation is quite surprising since diethylphthalate is usually associated to cosmetic use and not eating habits. As women are the primary users of cosmetic products, they are therefore usually more exposed to low-molecular-weight phthalates such as diethyl phthalate, di-n-butyl phthalate and di-iso-butyl phthalate. However, this study found that contamination levels of these compounds were the same for both sexes (see supplementary material: Table S1 ), a finding that warrants further investigation in the Kinshasa market. Parabens More than 95% of the samples tested positive for MeP and PrP, with median concentrations of 62.6 µg/L and 7.50 µg/L, respectively. Conversely, nBP and EtP were detected in 6% and 44% of the samples, respectively (Table 1 ). The levels of MeP and PrP contamination observed in this study are significantly lower than those highlighted in the 2019 pilot study [ 25 ]. However, because the sample size in the present study has increased almost tenfold, the current estimates are likely more accurate. Table 3 reports the median levels of parabens measured in some cohorts recruited after 2014. The MeP and PrP contamination observed in the adult population of Kinshasa is several times higher (up to one order of magnitude) than in Belgian [ 17 ], Korean [ 9 ], Spanish [ 37 ], and Chinese [ 34 , 35 ] populations. On the other hand, the level of parabens measured in another developing country (i.e. India) were significantly higher than those highlighted in our study [ 38 ]. In Europe, the use of parabens is strictly regulated. PrP use in food is banned, and maximum concentrations of MeP and EtP are established (Regulation (EU) 1129/2011). MeP, EtP, PrP, and nBP are authorized for use in cosmetics, but the European Commission has imposed maximum thresholds (Regulation (EU) 1004/2014). Such legislation is unavailable in the D.R.C; therefore, cosmetics, food and pharmaceutical products sold in Kinshasa may contain high amounts of these toxic substances, which probably explains the high levels measured in the urine of our volunteers. Paraben contamination was consistent across all studied variables (see supplementary material), except for gender and area of residence (Table 4). Women were found to be relatively more contaminated than men by MeP and PrP, potentially due to the presence of these molecules in personal care products (Table 4; P-value < 0.05), as observed in several worldwide studies [ 39 , 50 ]. For EtP, the inhabitants of Tshangu were relatively more exposed than residents of other districts, this observation is surprising and warrants further investigations. Benzophenone-3 Benzophenone-3 was detected in 96% of the samples, with a median concentration of 1.40 µg/L and concentration values ranging from < LOQ to 37.5 µg/L (Table 1 ). The current median level in the Kinshasa inhabitants is one order of magnitude higher than in the Chinese population [ 34 , 35 ], though it is similar to levels in the Belgian adult population [ 39 ] and Tunisian women [ 40 ]. Similar to what has been observed for parabens, women had higher contamination levels of BP-3 than men (Table 3 ; P-value < 0.05), this observation is likely due to women's more frequent use of cosmetics. The BP-3 contamination observed in this study is also significantly lower than that highlighted in the 2019 pilot study, but the present study's estimates are better than those in the previous study which involved a limited number of volunteers. Bisphenols Bisphenols Z, F, and A were detected in 10%, 69%, and 98% of the samples, respectively. The highest median value was found for BPA (1.54 µg/L, range: <LOQ-55.9 µg/L), followed by BPF (0.13 µg/L, range: <LOQ-8.95 µg/L) (see Table 1 ). Bisphenol A is one of the most studied endocrine-disrupting compounds. Exposure to this compound has been assessed in many populations worldwide. For example, Acevedo et al., 2025 [ 51 ] conducted an extensive review of epidemiological studies performed in Asia, Latin America, Australia, and Africa. Table 3 shows some examples of the median (or geometric mean) BPA concentrations measured in the urine of recently recruited adult cohorts. The adult population of Kinshasa exhibited slightly higher BPA contamination than the Belgian [ 17 ], Spanish [ 37 ], and Korean [ 9 ] populations. The median BPF level in Kinshasa is similar to those observed in Belgium [ 17 ] and higher than those reported in Spain [ 37 ]. In China, urinary levels of BPA measured in different cohorts vary greatly: Xu et al., 2022 [ 35 ] reported a geometric mean of 0.398 µg/L in a general population cohort recruited in Nantong (eastern China). This level is four times lower than those reported in the present study. Conversely, Zhang et al., 2024 [ 41 ] observed a far higher median concentration (4.33 µg/L) in a population of adult women from Shenyang (northeastern China). The BPF concentrations in these two Chinese cohorts were also very different (0.584 µg/L in Xu et al., 2022, and 2.86 µg/L in Zhang et al., 2024) and were several times higher than those in the Kinshasa population. There is a lower difference in bisphenol contamination between the population of Kinshasa and that of developed countries than we observed for phthalate metabolites and parabens. However, it will be interesting to observe the trend in the coming years. In Western countries, the use of BPA is declining due to increasingly restrictive regulations, while alternatives like BPF are being used more frequently. This is reflected in the decline of concentrations of BPA measured in the urine of volunteers in Europe and the US [ 17 , 51 ]. Conversely, an increasing trend in urinary BPA concentration has been observed in Australia, Asia, and Latin America, while any trend could be identified in Africa due to the too few existing data from this continent [ 51 ]. Only seven studies assessed the urine concentration of bisphenols in cohorts recruited in Africa: our pilot study, three performed in Egypt [ 52 – 54 ], one in Tunisia [ 40 ], one in Ghana [ 55 ] and one in Nigeria [ 42 ]. All these studies involved a relatively low number of individuals (from 15 to 73 volunteers). In the study with the largest cohort [ 42 ], the median BPA concentration was 2.052 µg/L but it was determined with an ELISA kit which hampers comparison with our results obtained to a GC-MS apparatus. The small number of studies, involving limited number of volunteers and the use of less reliable analytical methods in some works underscores again the urgent need for studies in low- and middle-income countries in Africa and highlights the relevance of the data collected in the present study. In Kinshasa, men showed significantly higher levels of BPA than women (Table 4; p < 0.05), and Mont Amba inhabitants had higher BPF levels (Table 4; p < 0.05) than those in other districts. These observations could be explained by dietary habits, as men are more likely to consume food and beverages stored in contaminated packaging [ 10 ]. The median BPA level in the present study is similar to those highlighted in our pilot study (1.36 µg/L). Triclosan Triclosan (TCS) was detected in all analyzed samples, with a median value of 50.2 µg/L and contamination ranging from 1.55 to 3,152 µg/L (see Table 1 ). We reviewed the literature for studies measuring TCS in the urine of adult volunteers recruited in 2015 or later. Some examples of cohorts are presented in Table 3 . The levels measured vary greatly from one cohort to another, even within the same country. For example, the median concentrations measured in China range from 0.737 µg/L in Guangzhou [ 44 ] to 10.58 µg/L in Sichuan [ 34 ]. Except for the Mexican cohort by Zamora et al., 2023 [ 47 ], the highest level of TCS measured in last decade was 14.08 µg/L in Iranian pregnant women [ 46 ]. This suggests that TCS contamination in Kinshasa is several times higher than in most other populations worldwide (our median concentration is 50.2 µg/L). The only other study that highlights a similar (and slightly higher) level of contamination is the work of Zamora et al., 2023 [ 47 ], which explored the concentrations of several non-persistent pollutants in the urine of low- or middle-income Mexican women. The exceptional nature of exposure to TCS in Kinshasa indicates that self-care products sold in the city are likely highly contaminated with this compound. This underscores the urgent need for strict regulations in the D.R.C. Regardless of the variable studied, no difference in TCS concentration was observed between the groups (Table 4; p > 0.05). The high levels of TCS highlighted in the present study were not surprising regarding the concentrations previously measured during our pilot study (median level: 40.1 µg/L). Exposure risk assessment to EDCs in the adult population of Kinshasa Our results demonstrate that the population of Kinshasa is highly exposed to non-persistent organic pollutants, especially compared to inhabitants of developed countries. All of the compounds measured in our study are potential endocrine disruptors; therefore, the associated health risks of this high exposure could be significant in the capital of the D.R.C. To evaluate this risk, we compared the concentrations measured in our volunteers to thresholds proposed in the literature. First, the HBM4EU consortium proposed an HBM-GV of 190 µg/L for MnBP [ 30 ]. In our cohort, 15% of individuals had a urinary MnBP concentration above this threshold (Table 5 ). This HBM-GV is derived from a rat study highlighting the negative impact of di-n-butyl phthalate (the parent compound of MnBP) exposure on sexual system development. Moreover this compound is known to interfere with the activation of sexual steroid hormone receptors and could thus disrupt reproductive system homeostasis [ 56 ]. Furthermore, one volunteer exceeded the HBM-GV proposed for the sum of 5-oxo-MEHP and 5-OH-MEHP (500 µg/L) (see Table 5 ). This threshold was also determined based on a study that examined the effects of DEHP on the reproductive system [ 30 ]. This compound is also capable of interfering with sexual steroid receptors [ 56 ]. Therefore, based on these results, we can conclude that a significant percentage of the Kinshasa population is susceptible to reproductive disorders due to exposure to phthalates. However, none of the volunteers exceeded the HBM-GV proposed for MiBP (230 µg/L) [ 30 ]. None of our volunteers exceeded the HBM-GV of 230 µg/L for BPA proposed by HBM4EU (Table 5 ) [ 31 ]. The HBM-GV is based on the tolerable daily intake (TDI) of 4 µg/kg bw/day established by the EFSA in 2015. However, in 2021, the EFSA published a re-evaluation of this TDI for consultation. The EFSA proposed a new TDI of 0.04 ng/kg bw/day. If this new TDI is adopted, the HBM-GV would need to be reduced by a factor of 10 5 , resulting in a new value of 2.3 ng/L [ 30 ]. With this new HBM-GV, a high proportion of individuals in our cohort but also in virtually every population worldwide will be considered at risk. This will be consistent with the ample evidences of BPA toxicity, notably due to its estrogenic potential [ 57 ]. Although the level of TCS contamination measured in our cohort is very high compared to other populations worldwide, only one of our volunteers exceeds the HBM-I value of 3,000 µg/L proposed by Apel et al. 2017 [ 32 ], based on the hematotoxicity (Table 5 ). Finally, we calculated the EDI for parabens (the sum of MeP and EtP), and only one volunteer exceeded the tolerable daily intake (TDI) of 10 mg/kg bw/day proposed by the European Food Safety Authority (EFSA), thus he should be considered at risk for impaired reproductive function (Table 5 ). Several volunteers had urine concentrations of some compounds that exceeded the thresholds associated with health risks, though most individuals were below these limits. Nevertheless, we must consider that we are all simultaneously exposed to numerous potentially toxic compounds that can act in an additive or synergistic manner. Therefore, although already significant, the percentage of Kinshasa's population exposed to toxic levels of non-persistent pollutants could be worse than if we consider the pollutants individually. Correlation between parameters Principal component analysis was used to evaluate the relationships between the various quantitative variables. Strong correlations were observed among all phthalate metabolites (MEP, MiBP, MnBP, MEHP, 5-oxo-MEHP and 5-OH-MEHP) and TCS, BP3 and BPA, meaning that they have similar sources of exposure, likely plastic packaging and personal care products sold in the city. Additionally, MeP and PrP were strongly correlated, indicating that they are potentially used in combination in food and pharmaceutical products (Fig. 2 ). Strengths and limitations of the study This study provides the first data in D.R.C on the exposure of a large population to several different environmental non-persistent pollutants, larger than our 2019 initial pilot study. However, despite the selection strategy used for the recruitment, is the population could still not be considered as fully representative of the city's entire population, let alone that of the Democratic Republic of the Congo (D.R.C). A cohort of 150 volunteers could hardly be expected to be fully representative of a city with a population of around 17.7 million inhabitants, spread over a large geographical area and with very different socio-demographic characteristics. We could not compare the concentration of each pollutant with HBM or TDI values because these reference levels were missing from the literature. Furthermore, no scientific organization has proposed a health risk threshold that accounts for simultaneous exposure to multiple pollutants. Therefore, our evaluation of the health risks associated with non-persistent pollutants in Kinshasa is incomplete. Another limitation of our study is that we only used one random urine sample. Due to the short half-life of the studied compounds and the significant temporal variability in urinary concentrations, using 24-hour urine samples or repeated sampling would be more suitable options for accurately assessing the population’s exposure to these compounds in Kinshasa [ 58 ]. Conclusion Notwithstanding the limitations of our study, the results of our work shed light on the high exposure of the inhabitants of Kinshasa to non-persistent pollutants. The presence of these various compounds in the population of Kinshasa merits particular attention from the Congolese people and authorities, as they are implicated in various hormonal pathologies. These substances are present in many everyday items, including packaging, cosmetics, food and pharmaceuticals. The high levels detected reflect the population's actual exposure, and the results obtained mostly highlight greater contamination compared to other populations on international scale. Although the exposure to these various endocrine disruptors was most often below certain toxicological reference values, it always poses a serious public health risk due to the potential additive or synergic effects of these compounds present simultaneously in the organism. Thus, eliminating or replacing these toxic products with healthier alternatives in the Congolese market will contribute to achieving the Sustainable Development Goals by 2030, which are a set of 17 global objectives adopted by the United Nations to strike a better balance between humans and the ecosystem [ 59 ]. This will require good synergy between public authorities, companies, and university researchers for continuous monitoring and the implementation of regulatory measures, as in Western countries. Consumers must also be committed to choosing the right products. Abbreviations D.R.C Democratic Republic of Congo US EPA U.S. Environmental Protection Agency EFSA European Food Safety Authority HBM-GVs human biomonitoring guidance values ADI Acceptable Daily Intake EDI estimated daily intake nPOPs non-Persistent organic pollutants LOQ Limit of Quantification DF Detection Frequency GM Geometric Mean SD Standard Deviation PCA Principal Component Analysis SPE Solid Phase Extraction GC-MS Gas Chromatography coupled to Mass Spectrometry LC-MS Liquid Chromatography coupled to Mass Spectrometry BMI Body Mass Index HBM Human Biomonitoring ELISA enzyme-linked immunosorbent assay MeP methylparaben EtP ethylparaben PrP propylparaben MEP monoethyl phthalate MnBP mono-n-butyl phthalate MiBP mono-isobutyl phthalate MEHP mono-2-ethylhexyl phthalate 5-OH-MEHP mono-2-ethyl-5-hydroxyhexyl phthalate 5-oxo-MEHP mono-2-ethyl-5-oxohexyl phthalate BP-3 benzophenone-3 TCS triclosan BPA bisphenol-A BPF bisphenol-F BPZ bisphenol-Z. Declarations Ethics approval and consent to participate Ethical approval for this study was conducted by the National Health Ethics Committee in the Democratic Republic of Congo (401/CNES/BN/PMMF/2022). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. All participants were informed about the purpose of the study, assured of confidentiality, and provided written consent prior to participation. Participation was voluntary, and respondents could withdraw at any time without consequence. Consent for publication Not applicable Availability of data and materials Availability of the data is guaranteed by the authors upon request. Competing interests The authors declare that there is no competing interest regarding the publication of this paper. Funding ARES-CCD (Académie de Recherche et d’Enseignement Supérieur-Commission de la Coopération au Développement) was the funding agent of this study. Authors’ contributions TB and PD drafted the manuscript and performed the statistical analysis. CP, CI, AM, MM, JN, RM, JM and CC conceived of the study and participated in its design and coordination and helped to draft the manuscript. All the authors read, commented the draft versions and approved the final manuscript. Acknowledgments We would like to express our deep gratitude to the “ARES-CCD” (Académie de Recherche et d’Enseignement Supérieur-Commission de la Coopération au Développement) for the support provided to TB. Thanks also to all the study participants and D.R.C health authorities for their commitment to this investigation. References Dewalque L, Pirard C, Vandepaer S, Charlier C. Temporal variability of urinary concentrations of phthalate metabolites, parabens and benzophenone-3 in a Belgian adult population. Environ Res. 2015;142:414–23. https://doi.org/10.1016/j.envres.2015.07.015 . Wei F, Mortimer M, Cheng H, Sang N, Guo L-H. Parabens as chemicals of emerging concern in the environment and humans: A review. Sci Total Environ. 2021;778:146150. https://doi.org/10.1016/j.scitotenv.2021.146150 . Mustieles V, Balogh RK, Axelstad M, Montazeri P, Márquez S, Vrijheid M, et al. Benzophenone-3: Comprehensive review of the toxicological and human evidence with meta-analysis of human biomonitoring studies. Environ Int. 2023;173:107739. https://doi.org/10.1016/j.envint.2023.107739 . Pirard C, Sagot C, Deville M, Dubois N, Charlier C. Urinary levels of bisphenol A, triclosan and 4-nonylphenol in a general Belgian population. Environ Int. 2012;48:78–83. https://doi.org/10.1016/j.envint.2012.07.003 . Axelsson J, Rylander L, Rignell-Hydbom A, Jönsson BAG, Lindh CH, Giwercman A. Phthalate exposure and reproductive parameters in young men from the general Swedish population. Environ Int. 2015;85:54–60. https://doi.org/10.1016/j.envint.2015.07.005 . Mínguez-Alarcón L, Bellavia A, Gaskins AJ, Chavarro JE, Ford JB, Souter I, et al. Paternal mixtures of urinary concentrations of phthalate metabolites, bisphenol A and parabens in relation to pregnancy outcomes among couples attending a fertility center. Environ Int. 2021;146:106171. https://doi.org/10.1016/j.envint.2020.106171 . Srnovršnik T, Virant-Klun I, Pinter B. Polycystic Ovary Syndrome and Endocrine Disruptors (Bisphenols, Parabens, and Triclosan)—A. Syst Rev Life. 2023;13:138. https://doi.org/10.3390/life13010138 . Zhu X, Yin T, Yue X, Liao S, Cheang I, Zhu Q, et al. Association of urinary phthalate metabolites with cardiovascular disease among the general adult population. Environ Res. 2021;202:111764. https://doi.org/10.1016/j.envres.2021.111764 . Lee I, Park YJ, Kim MJ, Kim S, Choi S, Park J, et al. Associations of urinary concentrations of phthalate metabolites, bisphenol A, and parabens with obesity and diabetes mellitus in a Korean adult population: Korean National Environmental Health Survey (KoNEHS) 2015–2017. Environ Int. 2021;146:106227. https://doi.org/10.1016/j.envint.2020.106227 . Choi JY, Lee J, Huh D-A, Moon KW. Urinary bisphenol concentrations and its association with metabolic disorders in the US and Korean populations. Environ Pollut. 2022;295:118679. https://doi.org/10.1016/j.envpol.2021.118679 . Moreno-Gómez-Toledano R, Vélez-Vélez E, Arenas MI, Saura M, Bosch RJ. Association between urinary concentrations of bisphenol A substitutes and diabetes in adults. World J Diabetes. 2022;13:521–31. https://doi.org/10.4239/wjd.v13.i7.521 . Frederiksen H, Nielsen O, Koch HM, Skakkebaek NE, Juul A, Jørgensen N, et al. Changes in urinary excretion of phthalates, phthalate substitutes, bisphenols and other polychlorinated and phenolic substances in young Danish men; 2009–2017. Int J Hyg Environ Health. 2020;223:93–105. https://doi.org/10.1016/j.ijheh.2019.10.002 . Colorado-Yohar SM, Castillo-González AC, Sánchez-Meca J, Rubio-Aparicio M, Sánchez-Rodríguez D, Salamanca-Fernández E, et al. Concentrations of bisphenol-A in adults from the general population: A systematic review and meta-analysis. Sci Total Environ. 2021;775:145755. https://doi.org/10.1016/j.scitotenv.2021.145755 . Bukasa Kakamba J, Sabbah N, Bayauli P, Massicard M, Bidingija J, Nkodila A, et al. Thyroid cancer in the Democratic Republic of the Congo: Frequency and risk factors. Ann Endocrinol. 2021;82:606–12. https://doi.org/10.1016/j.ando.2021.09.002 . Bukasa-Kakamba J, Bangolo A, Bayauli P, Mbunga Kilola B, Iyese F, Nkodila A, et al. Proportion of thyroid cancer and other cancers in the democratic republic of Congo. World J Exp Med. 2023;13:17–27. https://doi.org/10.5493/wjem.v13.i3.17 . Home R, diabetes, with L, FAQs A. accessed October 31, Contact, IDF Diabetes Atlas n.d. https://diabetesatlas.org/ (2024). Pirard C, Charlier C. Urinary levels of parabens, phthalate metabolites, bisphenol A and plasticizer alternatives in a Belgian population: Time trend or impact of an awareness campaign? Environ Res. 2022;214:113852. https://doi.org/10.1016/j.envres.2022.113852 . Schwedler G, Rucic E, Lange R, Conrad A, Koch HM, Pälmke C, et al. Phthalate metabolites in urine of children and adolescents in Germany. Human biomonitoring results of the German Environmental Survey GerES V, 2014–2017. Int J Hyg Environ Health. 2020;225:113444. https://doi.org/10.1016/j.ijheh.2019.113444 . Vogel N, Frederiksen H, Lange R, Jørgensen N, Koch HM, Weber T, et al. Urinary excretion of phthalates and the substitutes DINCH and DEHTP in Danish young men and German young adults between 2000 and 2017 – A time trend analysis. Int J Hyg Environ Health. 2023;248:114080. https://doi.org/10.1016/j.ijheh.2022.114080 . Baluka SA, Rumbeiha WK. Bisphenol A and food safety: Lessons from developed to developing countries. Food Chem Toxicol. 2016;92:58–63. https://doi.org/10.1016/j.fct.2016.03.025 . Zakari-Jiya A, Frazzoli C, Obasi CN, Babatunde BB, Patrick-Iwuanyanwu KC, Orisakwe OE. Pharmaceutical and personal care products as emerging environmental contaminants in Nigeria: A systematic review. Environ Toxicol Pharmacol. 2022;94:103914. https://doi.org/10.1016/j.etap.2022.103914 . Pouokam GB, Ajaezi GC, Mantovani A, Orisakwe OE, Frazzoli C. Use of Bisphenol A-containing baby bottles in Cameroon and Nigeria and possible risk management and mitigation measures: community as milestone for prevention. Sci Total Environ. 2014;481:296–302. https://doi.org/10.1016/j.scitotenv.2014.02.026 . Rotimi OA, Olawole TD, De Campos OC, Adelani IB, Rotimi SO. Bisphenol A in Africa: A review of environmental and biological levels. Sci Total Environ. 2021;764:142854. https://doi.org/10.1016/j.scitotenv.2020.142854 . Jebara A, Albergamo A, Rando R, Potortì AG, Lo Turco V, Mansour HB, et al. Phthalates and non-phthalate plasticizers in Tunisian marine samples: Occurrence, spatial distribution and seasonal variation. Mar Pollut Bull. 2021;163:111967. https://doi.org/10.1016/j.marpolbul.2021.111967 . Bayebila Menanzambi T, Dufour P, Pirard C, Nsangu J, Mufusama J-P, Mbinze Kindenge J, et al. Bio-surveillance of environmental pollutants in the population of Kinshasa, Democratic Republic of Congo (DRC): a small pilot study. Arch Public Health. 2021;79:197. https://doi.org/10.1186/s13690-021-00717-x . Bayebila Menanzambi T, Pirard C, Ilunga wa Kabuaya C, Malolo L-CM, Makola MM, Kule-Koto FK, et al. Current exposure to environmental pollutants in the general adult population of Kinshasa, Democratic Republic of Congo (DRC): A cross-sectional study. Int J Hyg Environ Health. 2025;263:114479. https://doi.org/10.1016/j.ijheh.2024.114479 . Dewalque L, Pirard C, Dubois N, Charlier C. Simultaneous determination of some phthalate metabolites, parabens and benzophenone-3 in urine by ultra high pressure liquid chromatography tandem mass spectrometry. J Chromatogr B. 2014;949–950:37–47. https://doi.org/10.1016/j.jchromb.2014.01.002 . Hubert Ph, Nguyen-Huu J-J, Boulanger B, Chapuzet E, Chiap P, Cohen N, et al. Harmonization of strategies for the validation of quantitative analytical procedures: A SFSTP proposal—part I. J Pharm Biomed Anal. 2004;36:579–86. https://doi.org/10.1016/j.jpba.2004.07.027 . Dubois N, Paccou AP, De Backer BG, Charlier CJ. Validation of the Quantitative Determination of Tetrahydrocannabinol and Its Two Major Metabolites in Plasma by Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry According to the Total Error Approach*. J Anal Toxicol. 2012;36:25–9. https://doi.org/10.1093/jat/bkr009 . Apel P, Lamkarkach F, Lange R, Sissoko F, David M, Rousselle C, et al. Human biomonitoring guidance values (HBM-GVs) for priority substances under the HBM4EU initiative - New values derivation for deltamethrin and cyfluthrin and overall results. Int J Hyg Environ Health. 2023;248:114097. https://doi.org/10.1016/j.ijheh.2022.114097 . Ougier E, Zeman F, Antignac J-P, Rousselle C, Lange R, Kolossa-Gehring M, et al. Human biomonitoring initiative (HBM4EU): Human biomonitoring guidance values (HBM-GVs) derived for bisphenol A. Environ Int. 2021;154:106563. https://doi.org/10.1016/j.envint.2021.106563 . Apel P, Angerer J, Wilhelm M, Kolossa-Gehring M. New HBM values for emerging substances, inventory of reference and HBM values in force, and working principles of the German Human Biomonitoring Commission. Int J Hyg Environ Health. 2017;220:152–66. https://doi.org/10.1016/j.ijheh.2016.09.007 . Ma W-L, Wang L, Guo Y, Liu L-Y, Qi H, Zhu N-Z, et al. Urinary Concentrations of Parabens in Chinese Young Adults: Implications for Human Exposure. Arch Environ Contam Toxicol. 2013;65:611–8. https://doi.org/10.1007/s00244-013-9924-2 . Zheng Y, Zhang L, Xiang Q, Li J, Yao Y, Sun H, et al. Human exposure characteristics of pharmaceutical and personal care product chemicals and associations with dietary habits. Sci Total Environ. 2024;939:173540. https://doi.org/10.1016/j.scitotenv.2024.173540 . Xu L, Hu Y, Zhu Q, Liao C, Jiang G. Several typical endocrine-disrupting chemicals in human urine from general population in China: Regional and demographic-related differences in exposure risk. J Hazard Mater. 2022;424:127489. https://doi.org/10.1016/j.jhazmat.2021.127489 . Wang Y, Li G, Zhu Q, Liao C. Occurrence of parabens, triclosan and triclocarban in paired human urine and indoor dust from two typical cities in China and its implications for human exposure. Sci Total Environ. 2021;786:147485. https://doi.org/10.1016/j.scitotenv.2021.147485 . Sanchis Y, Coscollà C, Corpas-Burgos F, Vento M, Gormaz M, Yusà V. Biomonitoring of bisphenols A, F, S and parabens in urine of breastfeeding mothers: Exposure and risk assessment. Environ Res. 2020;185:109481. https://doi.org/10.1016/j.envres.2020.109481 . Jala A, Varghese B, Dutta R, Adela R, Borkar RM. Levels of parabens and bisphenols in personal care products and urinary concentrations in Indian young adult women: Implications for human exposure and health risk assessment. Chemosphere. 2022;297:134028. https://doi.org/10.1016/j.chemosphere.2022.134028 . Dewalque L, Pirard C, Charlier C. Measurement of Urinary Biomarkers of Parabens, Benzophenone-3, and Phthalates in a Belgian Population. BioMed Res Int. 2014. https://doi.org/10.1155/2014/649314 . Jiménez-Díaz I, Artacho-Cordón F, Vela-Soria F, Belhassen H, Arrebola JP, Fernández MF, et al. Urinary levels of bisphenol A, benzophenones and parabens in Tunisian women: A pilot study. Sci Total Environ. 2016;562:81–8. https://doi.org/10.1016/j.scitotenv.2016.03.203 . Zhang N, Zhao Y, Zhai L, Bai Y, Wei W, Sun Q, et al. Urinary concentrations of bisphenol A and its alternatives: Potential predictors of and associations with antral follicle count among women from an infertility clinic in Northern China. Environ Res. 2024;249:118433. https://doi.org/10.1016/j.envres.2024.118433 . Olawole TD, De Campos OC, Adelani IB, Rotimi OA, Rotimi SO, Goodrich JM. Bisphenol A Associated Epigenetic Changes in Young Adults in Ota, Nigeria. Environ. Mol. Mutagen., vol. 63, WILEY 111 RIVER ST, HOBOKEN 07030 – 5774, NJ USA; 2022, pp. 105–6. Yang D, Kong S, Wang F, Tse LA, Tang Z, Zhao Y, et al. Urinary triclosan in south China adults and implications for human exposure. Environ Pollut. 2021;286:117561. https://doi.org/10.1016/j.envpol.2021.117561 . Liao Q, Huang H, Zhang X, Ma X, Peng J, Zhang Z, et al. Assessment of health risk and dose-effect of DNA oxidative damage for the thirty chemicals mixture of parabens, triclosan, benzophenones, and phthalate esters. Chemosphere. 2022;308:136394. https://doi.org/10.1016/j.chemosphere.2022.136394 . Jedynak P, Bustamante M, Rolland M, Mustieles V, Thomsen C, Sakhi AK, et al. Prenatal Exposure to Synthetic Phenols Assessed in Multiple Urine Samples and Dysregulation of Steroid Hormone Homeostasis in Two European Cohorts. Environ Health Perspect. 2025;133:057011. https://doi.org/10.1289/EHP15117 . Jamal A, Rastkari N, Dehghaniathar R, Nodehi RN, Nasseri S, Kashani H, et al. Prenatal urinary concentrations of environmental phenols and birth outcomes in the mother-infant pairs of Tehran Environment and Neurodevelopmental Disorders (TEND) cohort study. Environ Res. 2020;184:109331. https://doi.org/10.1016/j.envres.2020.109331 . Zamora AN, Peterson KE, Goodrich JM, Téllez-Rojo MM, Song PXK, Meeker JD, et al. Associations between exposure to phthalates, phenols, and parabens with objective and subjective measures of sleep health among Mexican women in midlife: a cross-sectional and retrospective analysis. Environ Sci Pollut Res Int. 2023;30:65544–57. https://doi.org/10.1007/s11356-023-26833-5 . Rowdhwal SSS, Chen J. Toxic Effects of Di-2-ethylhexyl Phthalate: An Overview. BioMed Res Int. 2018;2018:1750368. https://doi.org/10.1155/2018/1750368 . Schettler T. Human exposure to phthalates via consumer products. Int J Androl. 2006;29:134–9. https://doi.org/10.1111/j.1365-2605.2005.00567.x . discussion 181–185. Kang H-S, Kyung M-S, Ko A, Park J-H, Hwang M-S, Kwon J-E, et al. Urinary concentrations of parabens and their association with demographic factors: A population-based cross-sectional study. Environ Res. 2016;146:245–51. https://doi.org/10.1016/j.envres.2015.12.032 . Acevedo JM, Kahn LG, Pierce KA, Carrasco A, Rosenberg MS, Trasande L. Temporal and geographic variability of bisphenol levels in humans: A systematic review and meta-analysis of international biomonitoring data. Environ Res. 2025;264:120341. https://doi.org/10.1016/j.envres.2024.120341 . Nahar MS, Soliman AS, Colacino JA, Calafat AM, Battige K, Hablas A, et al. Urinary bisphenol A concentrations in girls from rural and urban Egypt: a pilot study. Environ Health. 2012;11:20. https://doi.org/10.1186/1476-069X-11-20 . Omran GA, Gaber HD, Mostafa NAM, Abdel-Gaber RM, Salah EA. Potential hazards of bisphenol A exposure to semen quality and sperm DNA integrity among infertile men. Reprod Toxicol. 2018;81:188–95. https://doi.org/10.1016/j.reprotox.2018.08.010 . Youssef MM, El-Din E, AbuShady MM, El-Baroudy NR, Abd El Hamid TA, Armaneus AF, et al. Urinary bisphenol A concentrations in relation to asthma in a sample of Egyptian children. Hum Exp Toxicol. 2018;37:1180–6. https://doi.org/10.1177/0960327118758150 . Karalius VP, Harbison JE, Plange-Rhule J, van Breemen RB, Li G, Huang K, et al. Bisphenol A (BPA) Found in Humans and Water in Three Geographic Regions with Distinctly Different Levels of Economic Development. Environ Health Insights. 2014;8:1–3. https://doi.org/10.4137/EHI.S13130 . Engel A, Buhrke T, Imber F, Jessel S, Seidel A, Völkel W, et al. Agonistic and antagonistic effects of phthalates and their urinary metabolites on the steroid hormone receptors ERα, ERβ, and AR. Toxicol Lett. 2017;277:54–63. https://doi.org/10.1016/j.toxlet.2017.05.028 . Cull ME, Winn LM. Bisphenol A and its potential mechanism of action for reproductive toxicity. Toxicology. 2025;511:154040. https://doi.org/10.1016/j.tox.2024.154040 . Morgan MK, Nash M, Barr DB, Starr JM, Clifton MS, Sobus JR. Distribution, variability, and predictors of urinary bisphenol A levels in 50 North Carolina adults over a six-week monitoring period. Environ Int. 2018;112:85–99. https://doi.org/10.1016/j.envint.2017.12.014 . NCD Countdown 2030: pathways to achieving Sustainable Development Goal target 3.4. Lancet Lond Engl 2020;396:918–34. https://doi.org/10.1016/S0140-6736(20)31761-X Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Feb, 2026 Reviews received at journal 16 Feb, 2026 Reviews received at journal 02 Feb, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers agreed at journal 15 Jan, 2026 Reviewers invited by journal 15 Jan, 2026 Editor assigned by journal 06 Jan, 2026 Submission checks completed at journal 06 Jan, 2026 First submitted to journal 29 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8473872","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":575170646,"identity":"0e36c99a-f29a-484d-b98b-f44ad1dc3290","order_by":0,"name":"Trésor Bayebila 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10:57:26","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":256434,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8473872/v1/2c38b01b99aafe330baa55ea.html"},{"id":100674135,"identity":"d051eb5c-97bf-4968-89c0-6d5e60353079","added_by":"auto","created_at":"2026-01-20 10:57:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139779,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical location of study area (C) in D.R.C (B) and Africa (A)\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8473872/v1/7be4fe131b4b0594ba37782d.jpg"},{"id":100674409,"identity":"ea6800b2-84d0-49c6-8415-2f382b946adc","added_by":"auto","created_at":"2026-01-20 10:59:21","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60115,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) graph of variables\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8473872/v1/d4c04efa819ea8c4686f7b8d.jpg"},{"id":100679919,"identity":"ca8cb73e-e1f2-47b2-a576-252f0b8b2600","added_by":"auto","created_at":"2026-01-20 11:51:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2095801,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8473872/v1/8cc747c4-b42f-4da8-ae73-e43a189596a0.pdf"},{"id":100674433,"identity":"bfe88cb6-3675-4680-b567-536b4f4870d4","added_by":"auto","created_at":"2026-01-20 10:59:41","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42264,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8473872/v1/8e157c6095ac15004be2e8ba.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Human biomonitoring and exposure risk assessment to phthalates, parabens, benzophenone-3, bisphenols and triclosan in the adult population of Kinshasa, Democratic Republic of Congo (D.R.C): a cross-sectional study","fulltext":[{"header":"Text box 1. Contributions to the Literature","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cul\u003e\n \u003cli\u003eThe first large-scale biomonitoring study of non-persistent organic pollutants in the general adult population of the DRC and particularly, in Kinshasa;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cul\u003e\n \u003cli\u003eThe compounds investigated are widely used in the production of everyday items and are currently being investigated for their potential negative impact on human and environmental health;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cul\u003e\n \u003cli\u003eThe study provides reliable environmental data that highlights the urgent need for measures to restore environmental balance.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Background","content":"\u003cp\u003eFor decades, humans have been synthetizing a growing number of chemicals used in agriculture, chemical or plastic industries, food production, pharmaceutical and cosmetics, and more. These chemicals have beneficial effects on human life, including increased agricultural yield, protection against or treatment of diseases, and the production of inexpensive and durable everyday products. Phthalates, for example, are a group of compounds that make plastics more flexible and help certain cosmetics to penetrate the skin [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Parabens are widely used as preservatives in perishable products [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Benzophenone-3, an ultraviolet filter, is added to body care products to enhance skin protection, prevent photoaging, and reduce the risk of skin cancer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Bisphenols are essential monomers used to manufacture polymerized plastics (polycarbonates) and epoxy resins. They are found in cans, baby bottles, plastic toys and clear water bottles. Triclosan is an antimicrobial agent that is often added to personal care products [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, despite the benefits these compounds provide to human health and well-being, many of these compounds are suspected of being harmful to humans and biodiversity by acting as endocrine disruptors. They are thought to be implicated in the rising prevalence of various hormone-related pathologies including, but not limited to, fertility disorders [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], metabolic pathologies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and cancers of the endocrine glands [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, regulatory agencies such as the European Food Safety Authority (EFSA) and the U.S. Environmental Protection Agency (US EPA) have classified some of these molecules, including phthalates and bisphenols, as substances of very high concern [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, the number of morbidity and mortality cases linked to chronic hormonal diseases is constantly rising in the Democratic Republic of the Congo (D.R.C). For example, cases of thyroid cancer have doubled in recent decades [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to the International Diabetes Federation, the incidence of type 2 diabetes in the D.R.C has increased from 3.1% of the adult population in 2011 to 7.7% in 2024, and would be one of the causes of underdevelopment [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In light of the rising incidence of these endocrine-related pathologies, the question of the implication of the population\u0026rsquo;s exposure to pollutants in the DRC could be reasonably raised. To answer to this question, the first step is to accurately evaluate the exposure of the population of the D.R.C to potentially toxic compounds.\u003c/p\u003e \u003cp\u003eOver time, a reduction in human exposure to some of these compounds has been observed in Europe and the United States, following the enhancement of regulatory measures implemented since the 2000s [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, in developing countries such like D.R.C, weak regulations and a lack of a precise monitoring plans result in the unrestricted addition of these compounds to many everyday items. This leads to exposures that could be much worse than in developed countries [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, the absence of an effective waste management policy coupled with the tropical climate would facilitate the accumulation of these substances in various environmental compartments, threatening ecosystems and human health [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnlike some other African countries such as South Africa, Egypt, Nigeria, Tunisia, Ghana, etc., which have data on non-persistent pollutants in environmental and biological matrices, the D.R.C lags behind in this area [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] although the use of these compounds in everyday items is expected to be extensive. There are several reasons for this delay, including a lack of specialized laboratories in the country, limited international funding, and a failure to address this issue in national health priorities.\u003c/p\u003e \u003cp\u003eTo begin to fill this gap, we conducted in 2019 a pilot study based on 15 volunteers recruited among the adult population in Kinshasa, and observed particularly high levels of parabens, benzophenone-3, triclosan, bisphenol A, and some phthalate metabolites in their urine [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The aim of the present study is to confirm these results by measuring levels of these pollutants in the urine of a larger cohort of adults recruited in Kinshasa and to assess their exposure risk. For this purpose, 145 volunteers were recruited between 2022 and 2023, and 4 parabens, 9 phthalate metabolites, 2 non-phthalate plasticizers, 3 bisphenols, benzophenone-3 and triclosan were measured in spot urine samples. This is the first large-scale biomonitoring study of non-persistent organic pollutants in the general adult population of the D.R.C and particularly, in Kinshasa.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eVolunteer recruitment and sample collection\u003c/p\u003e \u003cp\u003eThe study was carried out in Kinshasa, the capital of the Democratic Republic of the Congo (D.R.C), and targeted adults aged 18 and over. The participants were stratified into five age groups: 18\u0026ndash;29, 30\u0026ndash;39, 40\u0026ndash;49, 50\u0026ndash;59, and \u0026ge;\u0026thinsp;60 years. Outreach sites and recruitment process were previously described in Bayebila et al., 2025 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Between November 2022 and January 2023, 145 volunteers, ranging in age from 18 to 80, were recruited from across the city (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVolunteers were asked to provide a random urine spot in the morning, either fasting or not. The sample was collected in a polypropylene vial after the volunteer completed a form providing information on their lifestyle and anthropometric measurements. The samples were then placed in an isothermal box and transported to the Physical Chemistry and Biopharmaceutics Laboratory at the Faculty of Pharmaceutical Sciences of the University of Kinshasa. There, the samples were stored at -20\u0026deg;C, before being sent to the Clinical, Forensic and Environmental Toxicology Laboratory at the University of Li\u0026egrave;ge (Belgium) for chemical analysis.\u003c/p\u003e \u003cp\u003eChemical analysis\u003c/p\u003e \u003cp\u003eThe concentrations of four parabens, namely, methylparaben (MeP), ethylparaben (EtP), propylparaben (PrP) and n-butylparaben (nBP), nine phthalate metabolites, namely, monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), mono-2-ethylhexyl phthalate (MEHP), mono-2-ethyl-5-hydroxyhexyl phthalate (5-OH-MEHP), mono-2-ethyl-5-oxohexyl phthalate (5-oxo-MEHP), 7-carboxy octyl phthalate (7-cxOP), 6-hydroxypropylheptyl phthalate (6-OH-PrHpP), and monobenzyl phthalate (MBzP), two non-phthalate plasticizers (substitutes for phthalates), namely, cyclohexane-1,2-dicarboxylate-mono-(7-hydroxy-4-methyl)octyl ester (OH-MINCH) and cyclohexane-1,2-dicarboxylate-mono-(7carboxylate-4-methyl)heptyl ester (cx-MINCH), and benzophenone-3 (BP-3) were measured in urine according to the method extensively described in Dewalque et al., 2014 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In brief, after enzymatic beta-glucuronidase hydrolysis of the samples, the samples were extracted on a solid-phase extraction Bond Elut Certify cartridge 10cc (130 mg) from Agilent. After evaporation and reconstitution in a mixture of mobile phases (acetic acid (0.1%) in water/acetic acid (0.1%) in acetonitrile), the samples were analyzed on a liquid chromatography Acquity UPLC system coupled to a mass spectrometer Quattro Premier XE (Waters, Milford, MA, USA).\u003c/p\u003e \u003cp\u003eBisphenols (namely, bisphenol-A (BPA), bisphenol-F (BPF), bisphenol-Z (BPZ)) and triclosan (TCS) contaminations were assessed using an Agilent 7890A GC/ 7000A GC Triple Quad mass spectrometer (Agilent Technologies, California, USA). The sample preparation encompassed a simultaneous double enzymatic hydrolysis with beta-glucuronidase and sulfatase, followed by an extraction on solid phase cartridge (Oasis HLB, 60 mg, 3 cc from Waters) and subsequent a liquid/liquid extraction. After the evaporation of the organic phase, extracts were derivatized using N-methyl-N-trimethylsilyl trifluoroacetamide before injection on GC-MS/MS apparatus. This method was extensively detailed in Pirard et Charlier 2022 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQuality assurance\u003c/p\u003e \u003cp\u003eThe analytical methods used for this study were previously validated according to the total error approach [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The limits of quantification (LOQ) for each pollutant are gathered in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and were defined as the smallest concentrations measurable in samples with a total error not exceeding 30%. Materials from previous external quality controls were included in each batch of samples (G-EQUAS from the Out-Patient Clinic for Occupational, Social and Environmental Medicine of the University Erlangen-Nuremberg, for all investigated pollutants and OSEQAS from the Institut national de sant\u0026eacute; publique Qu\u0026eacute;bec, for bisphenols and triclosan). Each sequence also contained a procedural blank.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of non-persistent organic pollutants in urine\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePollutant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLOQ (\u0026micro;g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDF (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP95\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eParabens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e62.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 11,442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e 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\u003cp\u003ePrP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e7.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 1365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026minus;\u0026thinsp;6.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePhthalates\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMEP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e61.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 7,194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMnBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e78.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.31\u0026ndash;815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e17.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-oxo-MEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e6.30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-OH-MEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e11.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.601- 2,108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum of DEHP metabolites*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e21.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e81.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.74\u0026ndash;3,357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMBzP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026minus;\u0026thinsp;69.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-cxOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e68\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2.90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026minus;\u0026thinsp;31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-OH-PrHpP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 30.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOH-MINCH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 12.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecx-MINCH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBenzophenone\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026minus;\u0026thinsp;37.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBisphenols\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e98\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 55.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.130\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 8.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBPZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;LOQ \u0026ndash; 0.483\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTriclosan\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e50.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.55\u0026ndash;3,152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e*Sum of DEHP metabolites\u0026thinsp;=\u0026thinsp;MEHP\u0026thinsp;+\u0026thinsp;5-oxo-MEHP\u0026thinsp;+\u0026thinsp;5-OH-MEHP; LOQ: Limit of Quantification; DF: Detection Frequency; SD: Standard Deviation; GM: Geometric Mean.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed to identify parameters associated with levels of contamination. Prior to statistical analysis, contaminant levels below the LOQ were replaced by the LOQ multiplied by the detection frequency (DF) of the compound in our population. Contaminants with a DF below 70% were dichotomized (detected vs. not detected). Pollutant concentrations were not normally distributed (Shapiro-Wilk test\u0026thinsp;\u0026lt;\u0026thinsp;0.05), therefore non-parametric tests (Kruskal-Wallis, Mann-Whitney) and Spearman correlation were used for quantitative variables. For categorical variables and pollutants with DF\u0026thinsp;\u0026lt;\u0026thinsp;70%, chi-squared test was used. Principal component analysis (PCA) was used to investigate the correlation between quantitative variables and to gain insight into common sources of exposure. P-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant. RStudio, Rcmdr software (version 3.6.3., CRAN) and Excel 2013 (Microsoft, Redmond, WA) were used for statistical processing of data.\u003c/p\u003e \u003cp\u003eExposure risk assessment\u003c/p\u003e \u003cp\u003eOne of the main objectives of this study was to evaluate the health risks associated with exposure to pollutants among the population of Kinshasa. To accomplish this, we compared urinary pollutant levels measured in our population with reference levels provided by scientific authorities and working groups. The European Initiative HBM4EU provided human biomonitoring guidance values (HBM-GVs) for BPA, MnBP, MiBP and the sum of 5-oxo-MEHP and 5-OH-MEHP [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These HBM-GVs are defined as the concentration in a biological matrix (i.e. urine) at and below which negative health effects are not expected based on the current knowledge. We then compared urinary concentrations of these compounds in our cohort to the corresponding HBM-GVs proposed by Apel et al., 2023 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A human biomonitoring value I (German HBM-I value are similar to HBM-GV from HBM4EU) was also proposed by the German Human Biomonitoring Commission for TCS [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, no HBM-GV or associated threshold is available for parabens. Nevertheless, in 2004, the European Food Safety Authority (EFSA) established an Acceptable Daily Intake (ADI) of 0\u0026ndash;10 mg/kg body weight per day (mg/kg bw/day) for the sum of MeP and EtP. Therefore, for each volunteer in our study, we calculated an estimated daily intake (EDI) based on the formula proposed by Ma et al., 2013 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:EDI=\\frac{50\\times\\:{C}_{i}\\times\\:\\text{V}}{BW}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere C\u003csub\u003ei\u003c/sub\u003e is the sum of the urinary concentrations of MeP and EtP (\u0026micro;g/L), V(L/day) is the daily urine excretion rate (a value of 1.7 L/day was used for adults) and BW (kg) is the body weight of each participant. We then compared the EDIs with the ADI provided by the EFSA.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the detection frequencies (%), the limits of quantification of the methods used and the descriptive statistical parameters for each pollutant, all of which are expressed in \u0026micro;g/L. The sociodemographic characteristics of the population under study were previously reported in Bayebila et al. (2025) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Overall, males were overrepresented, accounting for 64.1% of the sample. The mean age was 36.9 years (range 18\u0026ndash;80 years) and the mean BMI was 25.6 kg/m\u0026sup2; (range 15.6\u0026ndash;43.0 kg/m\u0026sup2;). High participation rates were seen among adults aged 18\u0026ndash;29 (42.8%), drivers (13.8%) and residents of the Funa district (33.1%). Further details can be found in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the studied population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMen (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWomen (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAll\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (35.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.0\u0026ndash;80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0\u0026ndash;74.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.0\u0026ndash;80.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge categories\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (14.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (6.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (6.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (9.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (5.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (8.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (3.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6\u0026ndash;43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6\u0026ndash;39.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.0\u0026ndash;43.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e˂18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.5\u0026ndash;24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (15.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0-29.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (12.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (8.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (7.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActivities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrivers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTeachers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedical staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFeed 24 hours before sampling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVegetables and meat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (8.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArea of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTshangu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMont Amba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLukunga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI : Body Mass Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the levels of urinary non-persistent organic pollutants in different populations worldwide. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;4 respectively present the PCA results for assessing the correlation between pollutants and differences in contamination within Kinshasa's adult population according to certain studied variables. The results for the entire set of chemicals and variables are reported in full in the supplementary materials (Tables S1, S2 and S3). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarises the results of the risk assessment linked to exposure to the pollutants investigated.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevels of urinary non-persistent organic pollutants in different populations worldwide\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear of collection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003ePollutants median values (\u0026micro;g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ePhthalates\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMEP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMnBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMiBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5-OH-MEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5-oxo-MEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium, adult population, N\u0026thinsp;=\u0026thinsp;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDanish, Young population, N\u0026thinsp;=\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKorea, adult population, N\u0026thinsp;=\u0026thinsp;3787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSA, adult population, N\u0026thinsp;=\u0026thinsp;1862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNHANES 2017-18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGerman, children and adolescents, N\u0026thinsp;=\u0026thinsp;2256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2014\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinshasa (DRC), adult population\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2022\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e61.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e78.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e17.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e6.30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eParabens\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEtP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium, adult population, N\u0026thinsp;=\u0026thinsp;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKorea, adult population, N\u0026thinsp;=\u0026thinsp;3781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSichuan (China), non-occupational population, N\u0026thinsp;=\u0026thinsp;986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNantong city (eastern China), general population, N\u0026thinsp;=\u0026thinsp;104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.28*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuizhou and Beijing (China), general population, N\u0026thinsp;=\u0026thinsp;203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain, breastfeeding mothers, N\u0026thinsp;=\u0026thinsp;180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndia, young adult women from Assam, N\u0026thinsp;=\u0026thinsp;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinshasa (DRC), adult population\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2022\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e62.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eBenzophenone\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eBP-3\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium, adult population, N\u0026thinsp;=\u0026thinsp;261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTunisia, women, N\u0026thinsp;=\u0026thinsp;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSichuan (China), non-occupational population, N\u0026thinsp;=\u0026thinsp;986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNantong city (eastern China), general population, N\u0026thinsp;=\u0026thinsp;104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.103*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinshasa (DRC), adult population\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2022\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eBisphenols\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBPZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium, adult population, N\u0026thinsp;=\u0026thinsp;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt; LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKorea, adult population, N\u0026thinsp;=\u0026thinsp;3780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNantong city (eastern China), general population, N\u0026thinsp;=\u0026thinsp;104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.398*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.584*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShenyang, (northeastern China), women, N\u0026thinsp;=\u0026thinsp;111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain, breastfeeding mothers, N\u0026thinsp;=\u0026thinsp;180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.927*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.042*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndia, young adult women from Assam, N\u0026thinsp;=\u0026thinsp;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt; LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; LOQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNigeria, Ota University students, N\u0026thinsp;=\u0026thinsp;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinshasa (DRC), adult population\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2022\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt; LOQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eTriclosan\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina, Sichuan, general adult population, N\u0026thinsp;=\u0026thinsp;986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina, Shenzhen, general adult population, N\u0026thinsp;=\u0026thinsp;1163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina, Guangzhou, general adult population, N\u0026thinsp;=\u0026thinsp;299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain, Barcelona, pregnant women, N\u0026thinsp;=\u0026thinsp;546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSA, adult population, N\u0026thinsp;=\u0026thinsp;1829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNHANES 2015\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIran, Tehran, pregnant women, N\u0026thinsp;=\u0026thinsp;189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexico, low- or middle-income adult women, N\u0026thinsp;=\u0026thinsp;91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium, general population, N\u0026thinsp;=\u0026thinsp;131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinshasa (DRC), adult population\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2022\u0026ndash;2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003e*\u003c/b\u003e: Geometric mean; LOQ: Limit of Quantification\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"699\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 510px;\"\u003e\n \u003cp\u003eTable 4: contamination of the Kinshasa population according to some studied variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePollutant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 437px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (\u0026micro;g/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSex\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMeP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePrP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMEHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5-OH-MEHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eBP-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eBPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.029\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eArea of residence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTshangu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMont Amba\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFuna\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLukunga\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eEtP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e7-cxOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eBPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.0968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e0.0897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBMI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.5-24.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.0-29.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMEP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e37.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e90.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e87.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.029\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eActivities\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrivers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeachers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical staff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOthers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMiBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e28.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMnBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e75.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e87.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e80.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5-OH-MEHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5-oxo-MEHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-29 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30-39 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40-49 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50-59 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;60 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMiBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMnBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 73px;\"\u003e\n \u003cp\u003e84.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e84.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e82.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e55.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e46.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eBMI : Body Mass Index\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the exposure risk assessment to pollutants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemical compounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference levels for adults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of participants exceeding the threshold\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrine concentration\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMnBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum;5-OH-MEHP, 5-oxo-MEHP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,000 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTolerable daily intake\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum;MeP, EtP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 mg/kg bw/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePhthalate metabolites and non-phthalate plasticizers\u003c/p\u003e \u003cp\u003eAll phthalate metabolites were detected in more than 95% of the samples, except for MBzP (51%) and 7-cxOP (68%). Non-phthalate plasticizers were detected in only 6% of the samples, with concentrations ranging from below the LOQ to 12.2 \u0026micro;g/L, unlike in countries with established regulations on legacy phthalates, where detection of non-phthalate plasticizer alternatives in biological fluids is constantly increasing [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], this indicates a very low level of these alternatives in items sold in Kinshasa. The highest median concentrations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were measured for MnBP (median: 78.1 \u0026micro;g/L, range: 2.31\u0026ndash;815 \u0026micro;g/L), followed by MEP (median: 61.3 \u0026micro;g/L, range: \u0026lt;LOQ-7,194 \u0026micro;g/L), and the sum of the di-2-ethylhexyl phthalate (DEHP) metabolites (sum of MEHP\u0026thinsp;+\u0026thinsp;5-OH-MEHP\u0026thinsp;+\u0026thinsp;5-oxo-MEHP) (median: 21.5 \u0026micro;g/L, range: 1.74-3,357 \u0026micro;g/L). These levels are consistent with those reported in our 2019 pilot study [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], suggesting that these molecules are still present in personal care products, as well as in the food packaging, pharmaceutical and cosmetic products sold in the city although they are banned or restricted in several countries [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe reviewed the literature to highlight studies measuring urinary levels of phthalate metabolites in populations recruited in 2015 or later. Over the past decade, phthalate metabolites contamination has been assessed in adult populations in Belgium [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Denmark [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and Korea [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], as well as in German children and adolescents [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Finally, we extracted median urinary phthalate concentrations in adults from the National Health and Nutrition Examination Survey (NHANES) dataset. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the MEP levels measured in our cohort are two to three times higher than those reported in developed countries over the past 10 years and the MnBP levels are also several times higher in our population than in other recent cohorts, suggesting the presence of their respective parent compounds, diethyl phthalate and di-n-butyl phthalate, in perfumes, cosmetics and nail polishes sold in Kinshasa. The levels of MiBP and DEHP metabolites are similar to the high levels reported in Denmark, Korea and Germany. Overall, we can conclude that the Kinshasa inhabitants are more exposed to phthalates than individuals from the Western countries. This is likely due to the lack of Congolese legislation on these products, leaving the population exposed.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;4 shows the significant differences in contamination according to the variables studied in our population. Men, particularly drivers, showed higher levels of DEHP metabolite contamination (Table\u0026nbsp;4). DEHP (a high-molecular-weight phthalate) was commonly used in food and beverage packaging, as well as in plastics in interior car coatings. The use of this compound is now restricted in Western countries, but not in D.R.C [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Therefore, food packaging in D.R.C are probably contaminated. Furthermore, most vehicles in Kinshasa are old, secondhand cars imported from Western countries or Asia. Drivers are likely exposed to DEHP through their vehicles, which were produced in countries and/or at times when DEHP was not restricted. Drivers, students, and people aged 18\u0026ndash;49, showed relatively high levels of MiBP and MnBP contamination, likely due to their frequent use of cosmetics and nail polishes as they belong to a category that includes young people, a potential user group for body care products (Table\u0026nbsp;4; p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, overweight and obese adults showed higher levels of MEP contamination (Table\u0026nbsp;4; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), this observation is quite surprising since diethylphthalate is usually associated to cosmetic use and not eating habits.\u003c/p\u003e \u003cp\u003eAs women are the primary users of cosmetic products, they are therefore usually more exposed to low-molecular-weight phthalates such as diethyl phthalate, di-n-butyl phthalate and di-iso-butyl phthalate. However, this study found that contamination levels of these compounds were the same for both sexes (see supplementary material: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), a finding that warrants further investigation in the Kinshasa market.\u003c/p\u003e \u003cp\u003eParabens\u003c/p\u003e \u003cp\u003eMore than 95% of the samples tested positive for MeP and PrP, with median concentrations of 62.6 \u0026micro;g/L and 7.50 \u0026micro;g/L, respectively. Conversely, nBP and EtP were detected in 6% and 44% of the samples, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The levels of MeP and PrP contamination observed in this study are significantly lower than those highlighted in the 2019 pilot study [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, because the sample size in the present study has increased almost tenfold, the current estimates are likely more accurate.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reports the median levels of parabens measured in some cohorts recruited after 2014. The MeP and PrP contamination observed in the adult population of Kinshasa is several times higher (up to one order of magnitude) than in Belgian [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Korean [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], Spanish [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and Chinese [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] populations. On the other hand, the level of parabens measured in another developing country (i.e. India) were significantly higher than those highlighted in our study [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In Europe, the use of parabens is strictly regulated. PrP use in food is banned, and maximum concentrations of MeP and EtP are established (Regulation (EU) 1129/2011). MeP, EtP, PrP, and nBP are authorized for use in cosmetics, but the European Commission has imposed maximum thresholds (Regulation (EU) 1004/2014). Such legislation is unavailable in the D.R.C; therefore, cosmetics, food and pharmaceutical products sold in Kinshasa may contain high amounts of these toxic substances, which probably explains the high levels measured in the urine of our volunteers.\u003c/p\u003e \u003cp\u003eParaben contamination was consistent across all studied variables (see supplementary material), except for gender and area of residence (Table\u0026nbsp;4). Women were found to be relatively more contaminated than men by MeP and PrP, potentially due to the presence of these molecules in personal care products (Table\u0026nbsp;4; P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as observed in several worldwide studies [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. For EtP, the inhabitants of Tshangu were relatively more exposed than residents of other districts, this observation is surprising and warrants further investigations.\u003c/p\u003e \u003cp\u003eBenzophenone-3\u003c/p\u003e \u003cp\u003eBenzophenone-3 was detected in 96% of the samples, with a median concentration of 1.40 \u0026micro;g/L and concentration values ranging from \u0026lt;\u0026thinsp;LOQ to 37.5 \u0026micro;g/L (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The current median level in the Kinshasa inhabitants is one order of magnitude higher than in the Chinese population [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], though it is similar to levels in the Belgian adult population [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and Tunisian women [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Similar to what has been observed for parabens, women had higher contamination levels of BP-3 than men (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), this observation is likely due to women's more frequent use of cosmetics. The BP-3 contamination observed in this study is also significantly lower than that highlighted in the 2019 pilot study, but the present study's estimates are better than those in the previous study which involved a limited number of volunteers.\u003c/p\u003e \u003cp\u003eBisphenols\u003c/p\u003e \u003cp\u003eBisphenols Z, F, and A were detected in 10%, 69%, and 98% of the samples, respectively. The highest median value was found for BPA (1.54 \u0026micro;g/L, range: \u0026lt;LOQ-55.9 \u0026micro;g/L), followed by BPF (0.13 \u0026micro;g/L, range: \u0026lt;LOQ-8.95 \u0026micro;g/L) (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Bisphenol A is one of the most studied endocrine-disrupting compounds. Exposure to this compound has been assessed in many populations worldwide. For example, Acevedo et al., 2025 [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] conducted an extensive review of epidemiological studies performed in Asia, Latin America, Australia, and Africa. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows some examples of the median (or geometric mean) BPA concentrations measured in the urine of recently recruited adult cohorts. The adult population of Kinshasa exhibited slightly higher BPA contamination than the Belgian [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Spanish [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and Korean [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] populations. The median BPF level in Kinshasa is similar to those observed in Belgium [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and higher than those reported in Spain [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In China, urinary levels of BPA measured in different cohorts vary greatly: Xu et al., 2022 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported a geometric mean of 0.398 \u0026micro;g/L in a general population cohort recruited in Nantong (eastern China). This level is four times lower than those reported in the present study. Conversely, Zhang et al., 2024 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] observed a far higher median concentration (4.33 \u0026micro;g/L) in a population of adult women from Shenyang (northeastern China). The BPF concentrations in these two Chinese cohorts were also very different (0.584 \u0026micro;g/L in Xu et al., 2022, and 2.86 \u0026micro;g/L in Zhang et al., 2024) and were several times higher than those in the Kinshasa population. There is a lower difference in bisphenol contamination between the population of Kinshasa and that of developed countries than we observed for phthalate metabolites and parabens. However, it will be interesting to observe the trend in the coming years. In Western countries, the use of BPA is declining due to increasingly restrictive regulations, while alternatives like BPF are being used more frequently. This is reflected in the decline of concentrations of BPA measured in the urine of volunteers in Europe and the US [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Conversely, an increasing trend in urinary BPA concentration has been observed in Australia, Asia, and Latin America, while any trend could be identified in Africa due to the too few existing data from this continent [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Only seven studies assessed the urine concentration of bisphenols in cohorts recruited in Africa: our pilot study, three performed in Egypt [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], one in Tunisia [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], one in Ghana [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and one in Nigeria [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. All these studies involved a relatively low number of individuals (from 15 to 73 volunteers). In the study with the largest cohort [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], the median BPA concentration was 2.052 \u0026micro;g/L but it was determined with an ELISA kit which hampers comparison with our results obtained to a GC-MS apparatus. The small number of studies, involving limited number of volunteers and the use of less reliable analytical methods in some works underscores again the urgent need for studies in low- and middle-income countries in Africa and highlights the relevance of the data collected in the present study.\u003c/p\u003e \u003cp\u003eIn Kinshasa, men showed significantly higher levels of BPA than women (Table\u0026nbsp;4; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and Mont Amba inhabitants had higher BPF levels (Table\u0026nbsp;4; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than those in other districts. These observations could be explained by dietary habits, as men are more likely to consume food and beverages stored in contaminated packaging [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The median BPA level in the present study is similar to those highlighted in our pilot study (1.36 \u0026micro;g/L).\u003c/p\u003e \u003cp\u003eTriclosan\u003c/p\u003e \u003cp\u003eTriclosan (TCS) was detected in all analyzed samples, with a median value of 50.2 \u0026micro;g/L and contamination ranging from 1.55 to 3,152 \u0026micro;g/L (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We reviewed the literature for studies measuring TCS in the urine of adult volunteers recruited in 2015 or later. Some examples of cohorts are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The levels measured vary greatly from one cohort to another, even within the same country. For example, the median concentrations measured in China range from 0.737 \u0026micro;g/L in Guangzhou [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] to 10.58 \u0026micro;g/L in Sichuan [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Except for the Mexican cohort by Zamora et al., 2023 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], the highest level of TCS measured in last decade was 14.08 \u0026micro;g/L in Iranian pregnant women [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This suggests that TCS contamination in Kinshasa is several times higher than in most other populations worldwide (our median concentration is 50.2 \u0026micro;g/L). The only other study that highlights a similar (and slightly higher) level of contamination is the work of Zamora et al., 2023 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], which explored the concentrations of several non-persistent pollutants in the urine of low- or middle-income Mexican women. The exceptional nature of exposure to TCS in Kinshasa indicates that self-care products sold in the city are likely highly contaminated with this compound. This underscores the urgent need for strict regulations in the D.R.C. Regardless of the variable studied, no difference in TCS concentration was observed between the groups (Table\u0026nbsp;4; p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The high levels of TCS highlighted in the present study were not surprising regarding the concentrations previously measured during our pilot study (median level: 40.1 \u0026micro;g/L).\u003c/p\u003e \u003cp\u003eExposure risk assessment to EDCs in the adult population of Kinshasa\u003c/p\u003e \u003cp\u003eOur results demonstrate that the population of Kinshasa is highly exposed to non-persistent organic pollutants, especially compared to inhabitants of developed countries. All of the compounds measured in our study are potential endocrine disruptors; therefore, the associated health risks of this high exposure could be significant in the capital of the D.R.C. To evaluate this risk, we compared the concentrations measured in our volunteers to thresholds proposed in the literature.\u003c/p\u003e \u003cp\u003eFirst, the HBM4EU consortium proposed an HBM-GV of 190 \u0026micro;g/L for MnBP [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our cohort, 15% of individuals had a urinary MnBP concentration above this threshold (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This HBM-GV is derived from a rat study highlighting the negative impact of di-n-butyl phthalate (the parent compound of MnBP) exposure on sexual system development. Moreover this compound is known to interfere with the activation of sexual steroid hormone receptors and could thus disrupt reproductive system homeostasis [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Furthermore, one volunteer exceeded the HBM-GV proposed for the sum of 5-oxo-MEHP and 5-OH-MEHP (500 \u0026micro;g/L) (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This threshold was also determined based on a study that examined the effects of DEHP on the reproductive system [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This compound is also capable of interfering with sexual steroid receptors [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Therefore, based on these results, we can conclude that a significant percentage of the Kinshasa population is susceptible to reproductive disorders due to exposure to phthalates. However, none of the volunteers exceeded the HBM-GV proposed for MiBP (230 \u0026micro;g/L) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNone of our volunteers exceeded the HBM-GV of 230 \u0026micro;g/L for BPA proposed by HBM4EU (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The HBM-GV is based on the tolerable daily intake (TDI) of 4 \u0026micro;g/kg bw/day established by the EFSA in 2015. However, in 2021, the EFSA published a re-evaluation of this TDI for consultation. The EFSA proposed a new TDI of 0.04 ng/kg bw/day. If this new TDI is adopted, the HBM-GV would need to be reduced by a factor of 10\u003csup\u003e5\u003c/sup\u003e, resulting in a new value of 2.3 ng/L [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. With this new HBM-GV, a high proportion of individuals in our cohort but also in virtually every population worldwide will be considered at risk. This will be consistent with the ample evidences of BPA toxicity, notably due to its estrogenic potential [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the level of TCS contamination measured in our cohort is very high compared to other populations worldwide, only one of our volunteers exceeds the HBM-I value of 3,000 \u0026micro;g/L proposed by Apel et al. 2017 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], based on the hematotoxicity (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, we calculated the EDI for parabens (the sum of MeP and EtP), and only one volunteer exceeded the tolerable daily intake (TDI) of 10 mg/kg bw/day proposed by the European Food Safety Authority (EFSA), thus he should be considered at risk for impaired reproductive function (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral volunteers had urine concentrations of some compounds that exceeded the thresholds associated with health risks, though most individuals were below these limits. Nevertheless, we must consider that we are all simultaneously exposed to numerous potentially toxic compounds that can act in an additive or synergistic manner. Therefore, although already significant, the percentage of Kinshasa's population exposed to toxic levels of non-persistent pollutants could be worse than if we consider the pollutants individually.\u003c/p\u003e \u003cp\u003eCorrelation between parameters\u003c/p\u003e \u003cp\u003ePrincipal component analysis was used to evaluate the relationships between the various quantitative variables. Strong correlations were observed among all phthalate metabolites (MEP, MiBP, MnBP, MEHP, 5-oxo-MEHP and 5-OH-MEHP) and TCS, BP3 and BPA, meaning that they have similar sources of exposure, likely plastic packaging and personal care products sold in the city. Additionally, MeP and PrP were strongly correlated, indicating that they are potentially used in combination in food and pharmaceutical products (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStrengths and limitations of the study\u003c/p\u003e \u003cp\u003eThis study provides the first data in D.R.C on the exposure of a large population to several different environmental non-persistent pollutants, larger than our 2019 initial pilot study. However, despite the selection strategy used for the recruitment, is the population could still not be considered as fully representative of the city's entire population, let alone that of the Democratic Republic of the Congo (D.R.C). A cohort of 150 volunteers could hardly be expected to be fully representative of a city with a population of around 17.7\u0026nbsp;million inhabitants, spread over a large geographical area and with very different socio-demographic characteristics.\u003c/p\u003e \u003cp\u003eWe could not compare the concentration of each pollutant with HBM or TDI values because these reference levels were missing from the literature. Furthermore, no scientific organization has proposed a health risk threshold that accounts for simultaneous exposure to multiple pollutants. Therefore, our evaluation of the health risks associated with non-persistent pollutants in Kinshasa is incomplete.\u003c/p\u003e \u003cp\u003eAnother limitation of our study is that we only used one random urine sample. Due to the short half-life of the studied compounds and the significant temporal variability in urinary concentrations, using 24-hour urine samples or repeated sampling would be more suitable options for accurately assessing the population\u0026rsquo;s exposure to these compounds in Kinshasa [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNotwithstanding the limitations of our study, the results of our work shed light on the high exposure of the inhabitants of Kinshasa to non-persistent pollutants. The presence of these various compounds in the population of Kinshasa merits particular attention from the Congolese people and authorities, as they are implicated in various hormonal pathologies. These substances are present in many everyday items, including packaging, cosmetics, food and pharmaceuticals. The high levels detected reflect the population's actual exposure, and the results obtained mostly highlight greater contamination compared to other populations on international scale.\u003c/p\u003e \u003cp\u003eAlthough the exposure to these various endocrine disruptors was most often below certain toxicological reference values, it always poses a serious public health risk due to the potential additive or synergic effects of these compounds present simultaneously in the organism. Thus, eliminating or replacing these toxic products with healthier alternatives in the Congolese market will contribute to achieving the Sustainable Development Goals by 2030, which are a set of 17 global objectives adopted by the United Nations to strike a better balance between humans and the ecosystem [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This will require good synergy between public authorities, companies, and university researchers for continuous monitoring and the implementation of regulatory measures, as in Western countries. Consumers must also be committed to choosing the right products.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eD.R.C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDemocratic Republic of Congo\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUS EPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eU.S. Environmental Protection Agency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEFSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Food Safety Authority\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHBM-GVs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehuman biomonitoring guidance values\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcceptable Daily Intake\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eestimated daily intake\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003enPOPs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-Persistent organic pollutants\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLimit of Quantification\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDetection Frequency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeometric Mean\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrincipal Component Analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSolid Phase Extraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGC-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGas Chromatography coupled to Mass Spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLC-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLiquid Chromatography coupled to Mass Spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Biomonitoring\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eenzyme-linked immunosorbent assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMeP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethylparaben\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEtP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eethylparaben\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePrP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epropylparaben\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emonoethyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMnBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emono-n-butyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMiBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emono-isobutyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEHP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emono-2-ethylhexyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-OH-MEHP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emono-2-ethyl-5-hydroxyhexyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-oxo-MEHP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emono-2-ethyl-5-oxohexyl phthalate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBP-3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebenzophenone-3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etriclosan\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebisphenol-A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBPF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebisphenol-F\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBPZ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebisphenol-Z.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was conducted by the National Health Ethics Committee in the Democratic Republic of Congo (401/CNES/BN/PMMF/2022). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. All participants were informed about the purpose of the study, assured of confidentiality, and provided written consent prior to participation. Participation was voluntary, and respondents could withdraw at any time without consequence.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAvailability of the data is guaranteed by the authors upon request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no competing interest regarding the publication of this paper.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eARES-CCD (Acad\u0026eacute;mie de Recherche et d\u0026rsquo;Enseignement Sup\u0026eacute;rieur-Commission de la Coop\u0026eacute;ration au D\u0026eacute;veloppement) was the funding agent of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTB and PD drafted the manuscript and performed the statistical analysis. CP, CI, AM, MM, JN, RM, JM and CC conceived of the study and participated in its design and coordination and helped to draft the manuscript. \u0026nbsp;All the authors read, commented the draft versions and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to express our deep gratitude to the \u0026ldquo;ARES-CCD\u0026rdquo; (Acad\u0026eacute;mie de Recherche et d\u0026rsquo;Enseignement Sup\u0026eacute;rieur-Commission de la Coop\u0026eacute;ration au D\u0026eacute;veloppement) for the support provided to TB. Thanks also to all the study participants and D.R.C health authorities for their commitment to this investigation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDewalque L, Pirard C, Vandepaer S, Charlier C. Temporal variability of urinary concentrations of phthalate metabolites, parabens and benzophenone-3 in a Belgian adult population. Environ Res. 2015;142:414\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2015.07.015\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2015.07.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei F, Mortimer M, Cheng H, Sang N, Guo L-H. Parabens as chemicals of emerging concern in the environment and humans: A review. Sci Total Environ. 2021;778:146150. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2021.146150\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.146150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMustieles V, Balogh RK, Axelstad M, Montazeri P, M\u0026aacute;rquez S, Vrijheid M, et al. Benzophenone-3: Comprehensive review of the toxicological and human evidence with meta-analysis of human biomonitoring studies. Environ Int. 2023;173:107739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2023.107739\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2023.107739\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePirard C, Sagot C, Deville M, Dubois N, Charlier C. Urinary levels of bisphenol A, triclosan and 4-nonylphenol in a general Belgian population. Environ Int. 2012;48:78\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2012.07.003\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2012.07.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAxelsson J, Rylander L, Rignell-Hydbom A, J\u0026ouml;nsson BAG, Lindh CH, Giwercman A. Phthalate exposure and reproductive parameters in young men from the general Swedish population. Environ Int. 2015;85:54\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2015.07.005\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2015.07.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026iacute;nguez-Alarc\u0026oacute;n L, Bellavia A, Gaskins AJ, Chavarro JE, Ford JB, Souter I, et al. Paternal mixtures of urinary concentrations of phthalate metabolites, bisphenol A and parabens in relation to pregnancy outcomes among couples attending a fertility center. Environ Int. 2021;146:106171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2020.106171\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2020.106171\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrnovršnik T, Virant-Klun I, Pinter B. Polycystic Ovary Syndrome and Endocrine Disruptors (Bisphenols, Parabens, and Triclosan)\u0026mdash;A. Syst Rev Life. 2023;13:138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/life13010138\u003c/span\u003e\u003cspan address=\"10.3390/life13010138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu X, Yin T, Yue X, Liao S, Cheang I, Zhu Q, et al. Association of urinary phthalate metabolites with cardiovascular disease among the general adult population. Environ Res. 2021;202:111764. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2021.111764\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2021.111764\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee I, Park YJ, Kim MJ, Kim S, Choi S, Park J, et al. Associations of urinary concentrations of phthalate metabolites, bisphenol A, and parabens with obesity and diabetes mellitus in a Korean adult population: Korean National Environmental Health Survey (KoNEHS) 2015\u0026ndash;2017. Environ Int. 2021;146:106227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2020.106227\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2020.106227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi JY, Lee J, Huh D-A, Moon KW. Urinary bisphenol concentrations and its association with metabolic disorders in the US and Korean populations. Environ Pollut. 2022;295:118679. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envpol.2021.118679\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2021.118679\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoreno-G\u0026oacute;mez-Toledano R, V\u0026eacute;lez-V\u0026eacute;lez E, Arenas MI, Saura M, Bosch RJ. Association between urinary concentrations of bisphenol A substitutes and diabetes in adults. World J Diabetes. 2022;13:521\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4239/wjd.v13.i7.521\u003c/span\u003e\u003cspan address=\"10.4239/wjd.v13.i7.521\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrederiksen H, Nielsen O, Koch HM, Skakkebaek NE, Juul A, J\u0026oslash;rgensen N, et al. Changes in urinary excretion of phthalates, phthalate substitutes, bisphenols and other polychlorinated and phenolic substances in young Danish men; 2009\u0026ndash;2017. Int J Hyg Environ Health. 2020;223:93\u0026ndash;105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2019.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2019.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColorado-Yohar SM, Castillo-Gonz\u0026aacute;lez AC, S\u0026aacute;nchez-Meca J, Rubio-Aparicio M, S\u0026aacute;nchez-Rodr\u0026iacute;guez D, Salamanca-Fern\u0026aacute;ndez E, et al. Concentrations of bisphenol-A in adults from the general population: A systematic review and meta-analysis. Sci Total Environ. 2021;775:145755. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2021.145755\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.145755\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBukasa Kakamba J, Sabbah N, Bayauli P, Massicard M, Bidingija J, Nkodila A, et al. Thyroid cancer in the Democratic Republic of the Congo: Frequency and risk factors. Ann Endocrinol. 2021;82:606\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ando.2021.09.002\u003c/span\u003e\u003cspan address=\"10.1016/j.ando.2021.09.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBukasa-Kakamba J, Bangolo A, Bayauli P, Mbunga Kilola B, Iyese F, Nkodila A, et al. Proportion of thyroid cancer and other cancers in the democratic republic of Congo. World J Exp Med. 2023;13:17\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5493/wjem.v13.i3.17\u003c/span\u003e\u003cspan address=\"10.5493/wjem.v13.i3.17\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHome R, diabetes, with L, FAQs A. accessed October 31, Contact, IDF Diabetes Atlas n.d. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetesatlas.org/\u003c/span\u003e\u003cspan address=\"https://diabetesatlas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePirard C, Charlier C. Urinary levels of parabens, phthalate metabolites, bisphenol A and plasticizer alternatives in a Belgian population: Time trend or impact of an awareness campaign? Environ Res. 2022;214:113852. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2022.113852\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2022.113852\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwedler G, Rucic E, Lange R, Conrad A, Koch HM, P\u0026auml;lmke C, et al. Phthalate metabolites in urine of children and adolescents in Germany. Human biomonitoring results of the German Environmental Survey GerES V, 2014\u0026ndash;2017. Int J Hyg Environ Health. 2020;225:113444. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2019.113444\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2019.113444\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVogel N, Frederiksen H, Lange R, J\u0026oslash;rgensen N, Koch HM, Weber T, et al. Urinary excretion of phthalates and the substitutes DINCH and DEHTP in Danish young men and German young adults between 2000 and 2017 \u0026ndash; A time trend analysis. Int J Hyg Environ Health. 2023;248:114080. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2022.114080\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2022.114080\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaluka SA, Rumbeiha WK. Bisphenol A and food safety: Lessons from developed to developing countries. Food Chem Toxicol. 2016;92:58\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fct.2016.03.025\u003c/span\u003e\u003cspan address=\"10.1016/j.fct.2016.03.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZakari-Jiya A, Frazzoli C, Obasi CN, Babatunde BB, Patrick-Iwuanyanwu KC, Orisakwe OE. Pharmaceutical and personal care products as emerging environmental contaminants in Nigeria: A systematic review. Environ Toxicol Pharmacol. 2022;94:103914. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.etap.2022.103914\u003c/span\u003e\u003cspan address=\"10.1016/j.etap.2022.103914\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePouokam GB, Ajaezi GC, Mantovani A, Orisakwe OE, Frazzoli C. Use of Bisphenol A-containing baby bottles in Cameroon and Nigeria and possible risk management and mitigation measures: community as milestone for prevention. Sci Total Environ. 2014;481:296\u0026ndash;302. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2014.02.026\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2014.02.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRotimi OA, Olawole TD, De Campos OC, Adelani IB, Rotimi SO. Bisphenol A in Africa: A review of environmental and biological levels. Sci Total Environ. 2021;764:142854. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2020.142854\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2020.142854\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJebara A, Albergamo A, Rando R, Potort\u0026igrave; AG, Lo Turco V, Mansour HB, et al. Phthalates and non-phthalate plasticizers in Tunisian marine samples: Occurrence, spatial distribution and seasonal variation. Mar Pollut Bull. 2021;163:111967. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.marpolbul.2021.111967\u003c/span\u003e\u003cspan address=\"10.1016/j.marpolbul.2021.111967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayebila Menanzambi T, Dufour P, Pirard C, Nsangu J, Mufusama J-P, Mbinze Kindenge J, et al. Bio-surveillance of environmental pollutants in the population of Kinshasa, Democratic Republic of Congo (DRC): a small pilot study. Arch Public Health. 2021;79:197. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13690-021-00717-x\u003c/span\u003e\u003cspan address=\"10.1186/s13690-021-00717-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayebila Menanzambi T, Pirard C, Ilunga wa Kabuaya C, Malolo L-CM, Makola MM, Kule-Koto FK, et al. Current exposure to environmental pollutants in the general adult population of Kinshasa, Democratic Republic of Congo (DRC): A cross-sectional study. Int J Hyg Environ Health. 2025;263:114479. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2024.114479\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2024.114479\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDewalque L, Pirard C, Dubois N, Charlier C. Simultaneous determination of some phthalate metabolites, parabens and benzophenone-3 in urine by ultra high pressure liquid chromatography tandem mass spectrometry. J Chromatogr B. 2014;949\u0026ndash;950:37\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jchromb.2014.01.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jchromb.2014.01.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert Ph, Nguyen-Huu J-J, Boulanger B, Chapuzet E, Chiap P, Cohen N, et al. Harmonization of strategies for the validation of quantitative analytical procedures: A SFSTP proposal\u0026mdash;part I. J Pharm Biomed Anal. 2004;36:579\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jpba.2004.07.027\u003c/span\u003e\u003cspan address=\"10.1016/j.jpba.2004.07.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubois N, Paccou AP, De Backer BG, Charlier CJ. Validation of the Quantitative Determination of Tetrahydrocannabinol and Its Two Major Metabolites in Plasma by Ultra-High-Performance Liquid Chromatography\u0026ndash;Tandem Mass Spectrometry According to the Total Error Approach*. J Anal Toxicol. 2012;36:25\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jat/bkr009\u003c/span\u003e\u003cspan address=\"10.1093/jat/bkr009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApel P, Lamkarkach F, Lange R, Sissoko F, David M, Rousselle C, et al. Human biomonitoring guidance values (HBM-GVs) for priority substances under the HBM4EU initiative - New values derivation for deltamethrin and cyfluthrin and overall results. Int J Hyg Environ Health. 2023;248:114097. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2022.114097\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2022.114097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOugier E, Zeman F, Antignac J-P, Rousselle C, Lange R, Kolossa-Gehring M, et al. Human biomonitoring initiative (HBM4EU): Human biomonitoring guidance values (HBM-GVs) derived for bisphenol A. Environ Int. 2021;154:106563. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2021.106563\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2021.106563\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApel P, Angerer J, Wilhelm M, Kolossa-Gehring M. New HBM values for emerging substances, inventory of reference and HBM values in force, and working principles of the German Human Biomonitoring Commission. Int J Hyg Environ Health. 2017;220:152\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijheh.2016.09.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ijheh.2016.09.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa W-L, Wang L, Guo Y, Liu L-Y, Qi H, Zhu N-Z, et al. Urinary Concentrations of Parabens in Chinese Young Adults: Implications for Human Exposure. Arch Environ Contam Toxicol. 2013;65:611\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00244-013-9924-2\u003c/span\u003e\u003cspan address=\"10.1007/s00244-013-9924-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Y, Zhang L, Xiang Q, Li J, Yao Y, Sun H, et al. Human exposure characteristics of pharmaceutical and personal care product chemicals and associations with dietary habits. Sci Total Environ. 2024;939:173540. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2024.173540\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2024.173540\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu L, Hu Y, Zhu Q, Liao C, Jiang G. Several typical endocrine-disrupting chemicals in human urine from general population in China: Regional and demographic-related differences in exposure risk. J Hazard Mater. 2022;424:127489. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jhazmat.2021.127489\u003c/span\u003e\u003cspan address=\"10.1016/j.jhazmat.2021.127489\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Li G, Zhu Q, Liao C. Occurrence of parabens, triclosan and triclocarban in paired human urine and indoor dust from two typical cities in China and its implications for human exposure. Sci Total Environ. 2021;786:147485. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2021.147485\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2021.147485\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanchis Y, Coscoll\u0026agrave; C, Corpas-Burgos F, Vento M, Gormaz M, Yus\u0026agrave; V. Biomonitoring of bisphenols A, F, S and parabens in urine of breastfeeding mothers: Exposure and risk assessment. Environ Res. 2020;185:109481. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2020.109481\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2020.109481\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJala A, Varghese B, Dutta R, Adela R, Borkar RM. Levels of parabens and bisphenols in personal care products and urinary concentrations in Indian young adult women: Implications for human exposure and health risk assessment. Chemosphere. 2022;297:134028. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chemosphere.2022.134028\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2022.134028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDewalque L, Pirard C, Charlier C. Measurement of Urinary Biomarkers of Parabens, Benzophenone-3, and Phthalates in a Belgian Population. BioMed Res Int. 2014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1155/2014/649314\u003c/span\u003e\u003cspan address=\"10.1155/2014/649314\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJim\u0026eacute;nez-D\u0026iacute;az I, Artacho-Cord\u0026oacute;n F, Vela-Soria F, Belhassen H, Arrebola JP, Fern\u0026aacute;ndez MF, et al. Urinary levels of bisphenol A, benzophenones and parabens in Tunisian women: A pilot study. Sci Total Environ. 2016;562:81\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2016.03.203\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2016.03.203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang N, Zhao Y, Zhai L, Bai Y, Wei W, Sun Q, et al. Urinary concentrations of bisphenol A and its alternatives: Potential predictors of and associations with antral follicle count among women from an infertility clinic in Northern China. Environ Res. 2024;249:118433. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2024.118433\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2024.118433\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlawole TD, De Campos OC, Adelani IB, Rotimi OA, Rotimi SO, Goodrich JM. Bisphenol A Associated Epigenetic Changes in Young Adults in Ota, Nigeria. Environ. Mol. Mutagen., vol. 63, WILEY 111 RIVER ST, HOBOKEN 07030\u0026thinsp;\u0026ndash;\u0026thinsp;5774, NJ USA; 2022, pp. 105\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang D, Kong S, Wang F, Tse LA, Tang Z, Zhao Y, et al. Urinary triclosan in south China adults and implications for human exposure. Environ Pollut. 2021;286:117561. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envpol.2021.117561\u003c/span\u003e\u003cspan address=\"10.1016/j.envpol.2021.117561\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao Q, Huang H, Zhang X, Ma X, Peng J, Zhang Z, et al. Assessment of health risk and dose-effect of DNA oxidative damage for the thirty chemicals mixture of parabens, triclosan, benzophenones, and phthalate esters. Chemosphere. 2022;308:136394. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chemosphere.2022.136394\u003c/span\u003e\u003cspan address=\"10.1016/j.chemosphere.2022.136394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJedynak P, Bustamante M, Rolland M, Mustieles V, Thomsen C, Sakhi AK, et al. Prenatal Exposure to Synthetic Phenols Assessed in Multiple Urine Samples and Dysregulation of Steroid Hormone Homeostasis in Two European Cohorts. Environ Health Perspect. 2025;133:057011. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1289/EHP15117\u003c/span\u003e\u003cspan address=\"10.1289/EHP15117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJamal A, Rastkari N, Dehghaniathar R, Nodehi RN, Nasseri S, Kashani H, et al. Prenatal urinary concentrations of environmental phenols and birth outcomes in the mother-infant pairs of Tehran Environment and Neurodevelopmental Disorders (TEND) cohort study. Environ Res. 2020;184:109331. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2020.109331\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2020.109331\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZamora AN, Peterson KE, Goodrich JM, T\u0026eacute;llez-Rojo MM, Song PXK, Meeker JD, et al. Associations between exposure to phthalates, phenols, and parabens with objective and subjective measures of sleep health among Mexican women in midlife: a cross-sectional and retrospective analysis. Environ Sci Pollut Res Int. 2023;30:65544\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11356-023-26833-5\u003c/span\u003e\u003cspan address=\"10.1007/s11356-023-26833-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRowdhwal SSS, Chen J. Toxic Effects of Di-2-ethylhexyl Phthalate: An Overview. BioMed Res Int. 2018;2018:1750368. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1155/2018/1750368\u003c/span\u003e\u003cspan address=\"10.1155/2018/1750368\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchettler T. Human exposure to phthalates via consumer products. Int J Androl. 2006;29:134\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2605.2005.00567.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2605.2005.00567.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. discussion 181\u0026ndash;185.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang H-S, Kyung M-S, Ko A, Park J-H, Hwang M-S, Kwon J-E, et al. Urinary concentrations of parabens and their association with demographic factors: A population-based cross-sectional study. Environ Res. 2016;146:245\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2015.12.032\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2015.12.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAcevedo JM, Kahn LG, Pierce KA, Carrasco A, Rosenberg MS, Trasande L. Temporal and geographic variability of bisphenol levels in humans: A systematic review and meta-analysis of international biomonitoring data. Environ Res. 2025;264:120341. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2024.120341\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2024.120341\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNahar MS, Soliman AS, Colacino JA, Calafat AM, Battige K, Hablas A, et al. Urinary bisphenol A concentrations in girls from rural and urban Egypt: a pilot study. Environ Health. 2012;11:20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1476-069X-11-20\u003c/span\u003e\u003cspan address=\"10.1186/1476-069X-11-20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmran GA, Gaber HD, Mostafa NAM, Abdel-Gaber RM, Salah EA. Potential hazards of bisphenol A exposure to semen quality and sperm DNA integrity among infertile men. Reprod Toxicol. 2018;81:188\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.reprotox.2018.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.reprotox.2018.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoussef MM, El-Din E, AbuShady MM, El-Baroudy NR, Abd El Hamid TA, Armaneus AF, et al. Urinary bisphenol A concentrations in relation to asthma in a sample of Egyptian children. Hum Exp Toxicol. 2018;37:1180\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0960327118758150\u003c/span\u003e\u003cspan address=\"10.1177/0960327118758150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaralius VP, Harbison JE, Plange-Rhule J, van Breemen RB, Li G, Huang K, et al. Bisphenol A (BPA) Found in Humans and Water in Three Geographic Regions with Distinctly Different Levels of Economic Development. Environ Health Insights. 2014;8:1\u0026ndash;3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4137/EHI.S13130\u003c/span\u003e\u003cspan address=\"10.4137/EHI.S13130\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEngel A, Buhrke T, Imber F, Jessel S, Seidel A, V\u0026ouml;lkel W, et al. Agonistic and antagonistic effects of phthalates and their urinary metabolites on the steroid hormone receptors ERα, ERβ, and AR. Toxicol Lett. 2017;277:54\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.toxlet.2017.05.028\u003c/span\u003e\u003cspan address=\"10.1016/j.toxlet.2017.05.028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCull ME, Winn LM. Bisphenol A and its potential mechanism of action for reproductive toxicity. Toxicology. 2025;511:154040. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tox.2024.154040\u003c/span\u003e\u003cspan address=\"10.1016/j.tox.2024.154040\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorgan MK, Nash M, Barr DB, Starr JM, Clifton MS, Sobus JR. Distribution, variability, and predictors of urinary bisphenol A levels in 50 North Carolina adults over a six-week monitoring period. Environ Int. 2018;112:85\u0026ndash;99. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2017.12.014\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2017.12.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNCD Countdown 2030: pathways to achieving Sustainable Development Goal target 3.4. Lancet Lond Engl 2020;396:918\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(20)31761-X\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(20)31761-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"urinary pollutants, phthalates, parabens, bisphenols, triclosan, benzophenone-3, adult population, Kinshasa","lastPublishedDoi":"10.21203/rs.3.rs-8473872/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8473872/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Phthalates, parabens, benzophenone-3, bisphenols and triclosan are among the contaminants suspected of being involved in several hormone-related pathologies. In developing countries, weak regulations and lack of a precise monitoring plan lead to exposures that could be much worse than in developed countries. The objectives of this study were to evaluate the level of exposure of the adult population of Kinshasa (D.R.C) to these compounds and to assess the health risk induced by these pollutants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Concentrations of four parabens, nine phthalate metabolites, two non-phthalate plasticizers, benzophenone-3, three bisphenols and triclosan were assessed in the urine of 145 volunteers recruited in Kinshasa. Measurements were performed using a liquid or a gas chromatography coupled to a mass spectrometer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Detected in more than 95% of the samples with median concentrations in bracket, methylparaben (MeP) (62.6 µg/L), mono-n-butyl phthalate (MnBP) (78.1 µg/L) and bisphenol-A (BPA) (1.54 µg/L) were the most abundant compounds for parabens, phthalates metabolites and bisphenols, respectively. Globally, the current exposure seemed to be much higher for some phthalates and parabens compared to Western countries. For some phthalates, a non-neglectable part of the population studied exceeded human biomonitoring guidance values proposed by the HBM4EU consortium, meaning that they are expected to be more susceptible to reproductive disorders due to environmental exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The exposure of the population of Kinshasa to these pollutants merits consideration, as it constitutes a genuine public health concern. To enhance the protection of the population and its ecosystem, regulatory measures must be implemented and large-scale studies conducted.\u003c/p\u003e","manuscriptTitle":"Human biomonitoring and exposure risk assessment to phthalates, parabens, benzophenone-3, bisphenols and triclosan in the adult population of Kinshasa, Democratic Republic of Congo (D.R.C): a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 09:30:23","doi":"10.21203/rs.3.rs-8473872/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-16T14:46:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T07:24:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-02T16:19:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215157121503577764070989020574380039233","date":"2026-01-21T10:45:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238792254893825097976704825321091452746","date":"2026-01-15T15:55:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-15T14:57:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-06T14:28:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-06T14:27:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Public Health","date":"2025-12-29T14:19:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8c69708d-03c1-4d1e-bfd8-ccdf067c0a7b","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-25T16:08:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-20 09:30:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8473872","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8473872","identity":"rs-8473872","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}