Early-life exposure to multiple persistent organic pollutants and metals and birth weight: Pooled analysis in four Flemish birth cohorts

Exploring the levels of persistent organic pollutants in umbilical cord blood and their connection to gestational age and birth weights in Şanlıurfa, Turkey

BACKGROUND

Controversy surrounds the impact of persistent organic pollutants (POPs) on fetal development. This study aimed to investigate levels of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in umbilical cord blood from Şanlıurfa mothers in Turkey, exploring associations with gestational age and birth weight.

METHODS

Participants included voluntary mothers pregnant with a single fetus, providing details on maternal factors. Cord blood samples were collected immediately after delivery. Samples were extracted with a modified QuEChERS method, and OCPs (17 pesticides) and PCBs (11 congeners) compound levels were analyzed with a gas chromatograph/mass spectrometry. Detection frequencies and levels of POPs by single pollutant type and pollutant groups were calculated and compared according to gestational duration and birth weight. We used partial least squares discriminant analysis to identify the key chemicals and distinguish their respective statuses.

RESULTS

Among 120 infants, 35 were preterm but appropriate for gestational age, 35 were term but small for gestational age (SGA), and 50 were term and appropriate for gestational age (AGA). Beta HCH, Oxy-Chlordan, and PCB 28, were not detected in cord blood samples. Half of the samples contained at least 4 types of OCPs, with a median OCP level of 38.44 ng/g. Among the DDT, 2,4'-DDE was found at the highest concentration in cord plasma samples. The PCB congeners with a frequency exceeding 50% were ranked in the following order: 151, 149, 138, 146. The median level of ∑PCBs was 5.93 ng/g. Male infants born at term with SGA status exhibited lower levels of ∑DDTs, ∑OCPs compared to male infants born preterm or at term with AGA status. Di-ortho-substituted PCBs and hexachlorinated PCBs were higher in male infants born at term with SGA status than male infants born preterm with AGA status.

CONCLUSION

Overall, exposure to DDT and PCBs demonstrates varying effects depending on gestational duration and birth weight, with exposure levels also differing by gender. This underscores the necessity for studies across diverse populations that investigate the combined effects of multiple pollutant exposures on gestational age, birth weight, and gender simultaneously.

Exposure to metal mixtures and adverse pregnancy and birth outcomes: A systematic review

BACKGROUND

Prenatal exposure to metal mixtures is associated with adverse pregnancy and birth outcomes like low birth weight, preterm birth, and small for gestational age. However, prior studies have used individual metal analysis, lacking real-life exposure scenarios.

OBJECTIVES

This systematic review aims to evaluate the strength and consistency of the association between metal mixtures and pregnancy and birth outcomes, identify research gaps, and inform future studies and policies in this area.

METHODS

The review adhered to the updated Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) checklist, along with the guidelines for conducting systematic reviews and meta-analyses of observational studies of etiology (COSMOS-E). Our data collection involved searching the PubMed, MEDLINE, and SCOPUS databases. We utilized inclusion criteria to identify relevant studies. These chosen studies underwent thorough screening and data extraction procedures. Methodological quality evaluations were conducted using the NOS framework for cohort and case-control studies, and the AXIS tool for cross-sectional studies.

RESULTS

The review included 34 epidemiological studies, half of which focused on birth weight, and the others investigated neonate size, preterm birth, small for gestational age, miscarriage, and placental characteristics. The findings revealed significant associations between metal mixtures (including mercury (Hg), nickel (Ni), arsenic (As), cadmium (Cd), manganese (Mn), cobalt (Co), lead (Pb), zinc (Zn), barium (Ba), cesium (Cs), copper (Cu), selenium (Se), and chromium (Cr)) and adverse pregnancy and birth outcomes, demonstrating diverse effects and potential interactions.

CONCLUSION

In conclusion, this review consistently establishes connections between metal exposure during pregnancy and adverse consequences for birth weight, gestational age, and other vital birth-related metrics. This review further demonstrates the need to apply mixture methods with caution but also shows that they can be superior to traditional approaches. Further research is warranted to deeper understand the underlying mechanisms and to develop effective strategies for mitigating the potential risks associated with metal mixture exposure during pregnancy.

Prenatal Exposure to Multiple Endocrine-Disrupting Chemicals and Childhood BMI Trajectories in the INMA Cohort Study

BACKGROUND

Prenatal exposure to endocrine-disrupting chemicals (EDCs) may disrupt normal fetal and postnatal growth. Studies have mainly focused on individual aspects of growth at specific time points using single chemical exposure models. However, humans are exposed to multiple EDCs simultaneously, and growth is a dynamic process.

OBJECTIVE

The objective of this study was to evaluate the associations between prenatal exposure to EDCs and children's body mass index (BMI) growth trajectories using single exposure and mixture modeling approaches.

METHODS

Using data from the INfancia y Medio Ambiente (INMA) Spanish birth cohort (n = 1,911 ), prenatal exposure to persistent chemicals [hexachlorobenzene (HCB), 4-4'-dichlorodiphenyldichloroethylene (DDE), polychlorinated biphenyls (PCB-138, -150, and -180), 4 perfluoroalkyl substances (PFAS)] and nonpersistent chemicals (8 phthalate metabolites, 7 phenols) was assessed using blood and spot urine concentrations. BMI growth trajectories were calculated from birth to 9 years of age using latent class growth analysis. Multinomial regression was used to assess associations for single exposures, and Bayesian weighted quantile sum (BWQS) regression was used to evaluate the EDC mixture's association with child growth trajectories.

RESULTS

In single exposure models exposure to HCB, DDE, PCBs, and perfluorononanoic acid (PFNA) were associated with increased risk of belonging to a trajectory of lower birth size followed by accelerated BMI gain by 19%-32%, compared with a trajectory of average birth size and subsequent slower BMI gain [e.g., relative risk ratio (RRR) per doubling in DDE concentration = 1.19 (95% CI: 1.05, 1.35); RRR for PFNA = 1.32 (95% CI: 1.05, 1.66)]. HCB and DDE exposure were also associated with higher probability of belonging to a trajectory of higher birth size and accelerated BMI gain. Results from the BWQS regression showed the mixture was positively associated with increased odds of belonging to a BMI trajectory of lower birth size and accelerated BMI gain (odds ratio per 1-quantile increase of the mixture = 1.70 ; credible interval: 1.03, 2.61), with HCB, DDE, and PCBs contributing the most.

DISCUSSION

This study provides evidence that prenatal EDC exposure, particularly persistent EDCs, may lead to BMI trajectories in childhood characterized by accelerated BMI gain. Given that accelerated growth is linked to a higher disease risk in later life, continued research is important. https://doi.org/10.1289/EHP11103.

Metals and per- and polyfluoroalkyl substances mixtures and birth outcomes in the New Hampshire Birth Cohort Study: Beyond single-class mixture approaches

We aimed to investigate the joint, class-specific, and individual impacts of (i) PFAS, (ii) toxic metals and metalloids (referred to collectively as "metals"), and (iii) essential elements on birth outcomes in a prospective pregnancy cohort using both established and recent mixture modeling approaches. Participants included 537 mother-child pairs from the New Hampshire Birth Cohort Study. Concentrations of 6 metals and 5 PFAS were measured in maternal toenail clippings and plasma, respectively. Birth weight, birth length, and head circumference at birth were abstracted from medical records. Joint, index-wise, and individual associations of the metals and PFAS concentrations with birth outcomes were evaluated using Bayesian Kernel Machine Regression (BKMR) and Bayesian Multiple Index Models (BMIM). After controlling for potential confounders, the metals-PFAS mixture was associated with a larger head circumference at birth, which was driven by manganese. When using BKMR, the difference in the head circumference z-score when changing manganese from its 25th to 75th percentiles while holding all other mixture components at their medians was 0.22 standard deviations (95% posterior credible interval [CI]: -0.02, 0.46). When using BMIM, the posterior mean of index weight estimates assigned to manganese for head circumference z-score was 0.72 (95% CI: 0, 0.99). Prenatal exposure to the metals-PFAS mixture was not associated with birth weight or birth length by either BKMR or BMIM. Using both traditional and new mixture modeling approaches, prenatal exposure to manganese was associated with a larger head circumference at birth after accounting for exposure to PFAS and multiple toxic and essential metals.

Identification of Real-Life Mixtures Using Human Biomonitoring Data: A Proof of Concept Study

Human health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called "communities", within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments.

Mixtures of environmental contaminants and diabetes

BACKGROUND

Many studies have been published on the relationships between different environmental contaminants and diabetes. In these studies, the environmental contaminants have most often been evaluated one by one, but in real life we are exposed to a mixture of contaminants that interact with each other.

OBJECTIVE

The major aim of this study was to see if a mixture of contaminants could improve the prediction of incident diabetes, using machine learning.

METHODS

In the Prospective Investigation of the Vasculature in Uppsala (PIVUS) study (988 men and women aged 70 years), circulating levels of 42 contaminants from several chemical classes were measured at baseline. Incident diabetes was followed for 15 years. Six different machine-learning models were used to predict prevalent diabetes (n = 115). The variables with top importance were thereafter used to predict incident diabetes (n = 83).

RESULTS

Boosted regression trees performed best regarding prediction of prevalent diabetes (area under the ROC-curve = 0.70). Following removal of correlated contaminants, the addition of nine selected contaminants (Cd, Pb, Trans-nonachlor the phthalate MiBP, Hg, Ni, PCB126, PCB169 and PFOS) resulted in a significant improvement of 6.0 % of the ROC curve (from 0.66 to 0.72, p = 0.018) regarding incident diabetes (n = 51) compared with a baseline model including sex and BMI when the first 5 years of the follow-up was used. No such improvement in prediction was seen over 15 years follow-up. The single contaminant being most closely related to incident diabetes over 5 years was Nickel (odds ratio 1.44 for a SD change, 95 % CI 1.05-1.95, p = 0.022).

CONCLUSION

This study supports the view that machine learning was useful in finding a mixture of important contaminants that improved prediction of incident diabetes. This improvement in prediction was seen only during the first 5 years of follow-up.

Prenatal exposure to persistent organic pollutants and changes in infant growth and childhood growth trajectories

BACKGROUND

Children are born with a burden of persistent organic pollutants (POPs) which may have endocrine disrupting properties and have been postulated to contribute to the rise in childhood obesity. The current evidence is equivocal, which may partly because many studies investigate the effects at one time point during childhood. We assessed associations between prenatal exposure to POPs and growth during infancy and childhood.

METHODS

We used data from two Belgian cohorts with cord blood measurements of five organochlorines [(dichlorodiphenyldichloroethylene (p,p'-DDE), hexachlorobenzene (HCB), polychlorinated biphenyls (PCB-138, -150, -180)] (N = 1418) and two perfluoroalkyl substances [perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS)] (N = 346). We assessed infant growth, defined as body mass index (BMI) z-score change between birth and 2 years, and childhood growth, characterized as BMI trajectory from birth to 8 years. To evaluate associations between POP exposures and infant growth, we applied a multi-pollutant approach, using penalized elastic net regression with stability selection, controlling for covariates. To evaluate associations with childhood growth, we used single-pollutant linear mixed models with random effects for child individual, parametrized using a natural cubic spline formulation.

RESULTS

PCB-153 was associated with increased and p,p'-DDE with decreased infant growth, although these results were imprecise. No clear association between any of the exposures and longer-term childhood growth trajectories was observed. We did not find evidence of effect modification by child sex.

CONCLUSION

Our results suggest that prenatal exposure to PCB-153 and p,p'-DDE may affect infant growth in the first two years, with no evidence of more persistent effects.

Exposure to flame retardants in European children - Results from the HBM4EU aligned studies

Many legacy and emerging flame retardants (FRs) have adverse human and environmental health effects. This study reports legacy and emerging FRs in children from nine European countries from the HBM4EU aligned studies. Studies from Belgium, Czech Republic, Germany, Denmark, France, Greece, Slovenia, Slovakia, and Norway conducted between 2014 and 2021 provided data on FRs in blood and urine from 2136 children. All samples were collected and analyzed in alignment with the HBM4EU protocols. Ten halogenated FRs were quantified in blood, and four organophosphate flame retardants (OPFR) metabolites quantified in urine. Hexabromocyclododecane (HBCDD) and decabromodiphenyl ethane (DBDPE) were infrequently detected (<16% of samples). BDE-47 was quantified in blood from Greece, France, and Norway, with France (0.36 ng/g lipid) having the highest concentrations. BDE-153 and -209 were detected in <40% of samples. Dechlorane Plus (DP) was quantified in blood from four countries, with notably high median concentrations of 16 ng/g lipid in Slovenian children. OPFR metabolites had a higher detection frequency than other halogenated FRs. Diphenyl phosphate (DPHP) was quantified in 99% of samples across 8 countries at levels ∼5 times higher than other OPFR metabolites (highest median in Slovenia of 2.43 ng/g lipid). FR concentrations were associated with lifestyle factors such as cleaning frequency, employment status of the father of the household, and renovation status of the house, among others. The concentrations of BDE-47 in children from this study were similar to or lower than FRs found in adult matrices in previous studies, suggesting lower recent exposure and effectiveness of PBDE restrictions.

Early-life chemical exposome and gut microbiome development: African research perspectives within a global environmental health context

The gut microbiome of neonates, infants, and toddlers (NITs) is very dynamic, and only begins to stabilize towards the third year of life. Within this period, exposure to xenobiotics may perturb the gut environment, thereby driving or contributing to microbial dysbiosis, which may negatively impact health into adulthood. Despite exposure of NITs globally, but especially in Africa, to copious amounts and types of xenobiotics - such as mycotoxins, pesticide residues, and heavy metals - little is known about their influence on the early-life microbiome or their effects on acute or long-term health. Within the African context, the influence of fermented foods, herbal mixtures, and the delivery environment on the early-life microbiome are often neglected, despite being potentially important factors that influence the microbiome. Consequently, data on in-depth understanding of the microbiome-exposome interactions is lacking in African cohorts. Collecting and evaluating such data is important because exposome-induced gut dysbiosis could potentially favor disease progression.

Comprehensive suspect screening for the identification of contaminants of emerging concern in urine of Flemish adolescents by liquid chromatography high-resolution mass spectrometry

The increasing human exposure to contaminants of emerging concern (CECs) cannot be fully assessed by targeted biomonitoring methods alone as these are limited to a subset of known analytes. On the contrary, suspect screening approaches based on liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) allow the simultaneous detection of a high number of CECs and/or their (predicted) metabolites leading to a more comprehensive assessment of possible human exposure to these compounds. Within this study, 83 urine samples of Flemish adolescents (47 males, 36 females) collected in the frame of the 4th cycle of the Flemish Environment and Health Study (FLEHS IV) were selected with the aim of including a high and a low exposure group based on the overall exposure of 45 known contaminants. Samples were analyzed using a previously developed method involving a suspect screening approach to annotate CECs and their metabolites. The applied suspect list contained a total of >12,500 CECs and their known and predicted metabolites resulting from metabolization reactions, such as hydroxylation, glucuronidation and methylation. In total, 63 compounds were annotated at a confidence level of 3 or better, with most of the detected compounds not included in current biomonitoring programs. 5 out of the 63 compounds could be assigned with confidence level 2. Five compounds could unequivocally be identified (confidence level 1) through the comparison with reference standards. Personal care products were the main detected compound class (42% of detected compounds). Additionally, a detailed literature search indicated potential toxic effects for several of the detected CECs. Lastly, in the urine samples, a significantly higher number (p < 0.05) of compounds was detected in the high exposure group as opposed to the low exposure group. This difference could only be observed between high and low exposure load samples of female participants (p < 0.01).

Gestational exposure to PCB-118 impairs placental angiogenesis and fetal growth

Maternal exposure to polychlorinated biphenyls (PCBs) results in adverse effects on fetal development. However, the underlying mechanism has not been sufficiently explored in respect to particular PCBs. Placental angiogenesis plays a crucial role in feto-maternal substances transportation and fetal development. The present study was conducted to investigate the effects of prenatal PCB118 exposure on placental angiogenesis and fetal growth. The pregnant dam received PCB118 at environmentally relevant doses (0, 20, or 100 μg/kg/day) intragastrically from gestational day (GD) 7.5-18.5 to establish an in vivo model. Compared with the control group, the fetal body and placental weights of the PCB118 (100 μg/kg/day) group were significantly decreased and the intrauterine growth retardation (IUGR) rates were increased both in the female and male fetus. Furthermore, we found that placental histology was significantly impaired and the number of blood vessels was decreased in the PCB118 group. Additionally, gestational exposure to PCB118 caused anomalous mRNA expression of the genes in the placenta regarding angiogenesis. These findings indicate that PCB118 may contribute to the occurrence of IUGR by provoking placental angiogenesis dysfunction. This study clarified the adverse effects and potential mechanism of prenatal PCBs exposure on fetal growth, providing a new theoretical and experimental basis for future treatment and prevention.

Endocrine disruptor hexachlorobenzene induces cell migration and invasion, and enhances aromatase expression levels in human endometrial stromal cells

Endometriosis is the presence and growth of endometrial tissue outside of the uterus. Previous studies have suggested that endocrine disrupting chemicals such as organochlorine pesticides could be a risk factor for endometriosis. Hexachlorobenzene (HCB) is a weak ligand of the aryl hydrocarbon receptor (AhR) and promotes metalloproteinase and cyclooxygenase-2 (COX-2) expression, as well as, c-Src activation in human endometrial stromal cells (T-HESC) and in rat endometriosis model. Our aim was to evaluate the effect of HCB exposure on oestrogen receptor (ER) ɑ and β, progesterone receptor (PR) and aromatase expression, as well as, on cell migration and invasion in T-HESC and primary cultures of endometrial stromal cells from eutopic endometria of control subjects (ESC). Results show that HCB increases ERɑ and aromatase protein levels and reduces PR content in both T-HESC and ESC. However, the pesticide only increases ERβ expression in ESC, without changes in T-HESC. Moreover, cell migration and invasion are promoted by pesticide exposure involving the AhR, c-Src, COX-2 and ER pathways in T-HESC. HCB also triggers ERɑ activation via phosphorylation in Y537 through AhR/c-Src pathway. Our results provide experimental evidence that HCB induces alterations associated with endometriosis, suggesting that these mechanisms could contribute to pesticide exposure-induced endometriosis development.

Quantitative assessment of multiple pesticides in silicone wristbands of children/guardian pairs living in agricultural areas in South Africa

Little is known about personal and time-integrated exposure to past and current used pesticides in agricultural areas and within-family exposure similarities. We aimed to assess exposure to pesticides using silicone wristbands in child/guardian pairs living on farms and in villages within two agricultural areas in South Africa. Using silicone wristbands, we quantified 21 pesticides in child/guardian pairs in 38 households over six days in 2018. Levels (in ng/g wristband) of pesticides and their transformation products (12 current-use pesticides and nine organochlorine pesticides) were measured using GC-MS/MS. We assessed the correlation between pesticide levels and between household members using Spearman correlation coefficients (r_s). Multivariable generalized least squares (GLS) models, using household id as intercept, were used to determine level of agreement between household members, exposure differences between children and guardians and exposure predictors (study area, household location [farm vs. village] and household pesticide use). We detected 16 pesticides with highest detection frequencies for deltamethrin (89%), chlorpyrifos (78%), boscalid (56%), cypermethrin (55%), and p,p'-DDT (48%). Most wristbands (92%) contained two or more pesticides (median seven (range one to 12)). Children had higher concentrations than guardians for four pesticides. Correlation between the pesticide levels were in most cases moderate (rs 0.30-0.68) and stronger in children than in guardians. Five pesticides showed moderate to strong correlation between household members, with the strongest correlation for boscalid (r_s 0.84). Exposure differences between the two agricultural areas were observed for chlorpyrifos, diazinon, prothiofos, cypermethrin, boscalid, p,p'-DDT and p,p'-DDE and within areas for cypermethrin. We showed that for several pesticides children had higher exposure levels than guardians. The positive correlations observed for child/guardian pairs living in the same household suggest non-occupational shared exposure pathways in these communities.

Performance of urine, blood, and integrated metal biomarkers in relation to birth outcomes in a mixture setting

BACKGROUND

Studies on the health effects of metal mixtures typically utilize biomarkers measured in a single biological medium, such as blood or urine. However, the ability to evaluate mixture effects are limited by the uncertainty whether a unified medium can fully capture exposure for each metal. Therefore, it is important to compare and assess metal mixtures measured in different media in epidemiology studies.

OBJECTIVES

The aim of this study was to examine the mixture predictive performance of urine and blood metal biomarkers and integrated multi-media biomarkers in association with birth outcomes.

METHODS

In our analysis of 847 women from the Puerto Rico PROTECT Cohort, we measured 10 essential and non-essential metals in repeated and paired samples of urine and blood during pregnancy. For each metal, we integrated exposure estimates from paired urine and blood biomarkers into multi-media biomarkers (MMBs), using intraclass-correlation coefficient (ICC) and weighted quantile sum (WQS) approaches. Using Ridge regressions, four separate Environmental risk scores (ERSs) for metals in urine, blood, MMBICC, and MMBWQS were computed as a weighted sum of the 10 metal concentrations. We then examined associations between urine, blood, and multi-media biomarker ERSs and birth outcomes using linear and logistic regressions, adjusting for maternal age, maternal education, pre-pregnancy body mass index (BMI), and second-hand smoke exposure. The performance of each ERS was evaluated with continuous and tertile estimates and 95% confidence intervals of the odds ratio of preterm birth using area under the curve (AUC).

RESULTS

Pb was the most important contributor of blood ERS as well as the two integrated multi-media biomarker ERSs. Individuals with high ERS (3rd tertile) showed increased odds of preterm birth compared to individuals with low ERS (1st tertile), with 2.8-fold (95% CI, 1.49 to 5.40) for urine (specific gravity corrected); 3.2- fold (95% CI, 1.68 to 6.25) for blood; 3.9-fold (95% CI, 1.72 to 8.66) for multi-media biomarkers composed using ICC; and 5.2-fold (95% CI, 2.34 to 11.42) for multi-media biomarkers composed using WQS. The four ERSs had comparable predictive performances (AUC ranging from 0.64 to 0.68) when urine is examined with specific gravity corrected concentrations.

CONCLUSIONS

Within a practical metal panel, measuring metals in either urine or blood may be an equally good approach to evaluate the metals as a mixture. Applications in practical study design require validation of these methods with other cohorts, larger panels of metals and within the context of other adverse health effects of interest.

Praegnatio Perturbatio-Impact of Endocrine-Disrupting Chemicals

The burden of adverse pregnancy outcomes such as preterm birth and low birth weight is considerable across the world. Several risk factors for adverse pregnancy outcomes have been identified. One risk factor for adverse pregnancy outcomes receiving considerable attention in recent years is gestational exposure to endocrine-disrupting chemicals (EDCs). Humans are exposed to a multitude of environmental chemicals with known endocrine-disrupting properties, and evidence suggests exposure to these EDCs have the potential to disrupt the maternal-fetal environment culminating in adverse pregnancy and birth outcomes. This review addresses the impact of maternal and fetal exposure to environmental EDCs of natural and man-made chemicals in disrupting the maternal-fetal milieu in human leading to adverse pregnancy and birth outcomes-a risk factor for adult-onset noncommunicable diseases, the role lifestyle and environmental factors play in mitigating or amplifying the effects of EDCs, the underlying mechanisms and mediators involved, and the research directions on which to focus future investigations to help alleviate the adverse effects of EDC exposure.

Network Analysis to Identify Communities Among Multiple Exposure Biomarkers Measured at Birth in Three Flemish General Population Samples

Introduction: Humans are exposed to multiple environmental chemicals via different sources resulting in complex real-life exposure patterns. Insight into these patterns is important for applications such as linkage to health effects and (mixture) risk assessment. By providing internal exposure levels of (metabolites of) chemicals, biomonitoring studies can provide snapshots of exposure patterns and factors that drive them. Presentation of biomonitoring data in networks facilitates the detection of such exposure patterns and allows for the systematic comparison of observed exposure patterns between datasets and strata within datasets. Methods: We demonstrate the use of network techniques in human biomonitoring data from cord blood samples collected in three campaigns of the Flemish Environment and Health Studies (FLEHS) (sampling years resp. 2002-2004, 2008-2009, and 2013-2014). Measured biomarkers were multiple organochlorine compounds, PFAS and metals. Comparative network analysis (CNA) was conducted to systematically compare networks between sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Results: Network techniques offered an intuitive approach to visualize complex correlation structures within human biomonitoring data. The identification of groups of highly connected biomarkers, "communities," within these networks highlighted which biomarkers should be considered collectively in the analysis and interpretation of epidemiological studies or in the design of toxicological mixture studies. Network analyses demonstrated in our example to which extent biomarker networks and its communities changed across the sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Conclusion: Network analysis is a data-driven and intuitive screening method when dealing with multiple exposure biomarkers, which can easily be upscaled to high dimensional HBM datasets, and can inform mixture risk assessment approaches.