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Dioxins and polychlorinated biphenyls (PCBs) are toxic, endocrine disruptors and persistent chemicals for which the main exposure source is diet due to their bioaccumulation and biomagnification in food chains. Cohort studies in the general populations have reported inconsistent associations between these chemicals in serum/plasma and mortality. Our objective was to study the association between dietary intake of 17 dioxins and 35 PCBs and all-cause, cancer-specific and cardiovascular-specific mortalities were assessed in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Dietary intake of dioxins and PCBs was assessed combining EPIC food consumption data with European food contamination data provided by the European Food Safety Authority. We applied multivariable Cox regressions. The analysis included 451,390 adults (mean ± SD age:51.1 ± 9.7 years) with 46,627 deaths and a median follow-up of 17.4 years (IQR = 15.2–19.1). A U-shaped non-linear association with all-cause mortality for dietary intake of dioxins (Pnon-linearity<0.0001), DL-PCB (Pnon-linearity = 0.0001), and NDL-PCBs (Pnon-linearity<0.01) was observed. For example, the hazard ratios (95%Confidance interval) for all-cause mortality obtained with the spline model was equal to 1.03 (1.02–1.05) for low levels of intake to dioxins (7 pg TEQ/day), 0.93 (0.90–0.96) for moderate levels of intake (25 pg TEQ/day), while for high levels of intake (55 pg TEQ/day) it was 1.03 (0.97–1.09). Intake of dioxins, DL-PCBs and NDL-PCBs was not associated with cardiovascular mortality. There was no association between intakes of dioxins and cancer mortality, but a U-shaped association was observed for intake of DL-PCBs and intakes of NDL-PCBs and cancer mortality. The PCBs and dioxins are known to have endocrine disrupting properties which can lead to non-monotonic dose responses. These results need to be interpreted with caution and further studies are needed to better clarify the associa, Dioxins and polychlorinated biphenyls (PCBs) are toxic, endocrine disruptors and persistent chemicals for which the main exposure source is diet due to their bioaccumulation and biomagnification in food chains. Cohort studies in the general populations have reported inconsistent associations between these chemicals in serum/plasma and mortality. Our objective was to study the association between dietary intake of 17 dioxins and 35 PCBs and all-cause, cancer-specific and cardiovascular-specific mortalities were assessed in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Dietary intake of dioxins and PCBs was assessed combining EPIC food consumption data with European food contamination data provided by the European Food Safety Authority. We applied multivariable Cox regressions. The analysis included 451,390 adults (mean ± SD age:51.1 ± 9.7 years) with 46,627 deaths and a median follow-up of 17.4 years (IQR = 15.2–19.1). A U-shaped non-linear association with all-cause mortality for dietary intake of dioxins (Pnon-linearity<0.0001), DL-PCB (Pnon-linearity = 0.0001), and NDL-PCBs (Pnon-linearity<0.01) was observed. For example, the hazard ratios (95%Confidance interval) for all-cause mortality obtained with the spline model was equal to 1.03 (1.02–1.05) for low levels of intake to dioxins (7 pg TEQ/day), 0.93 (0.90–0.96) for moderate levels of intake (25 pg TEQ/day), while for high levels of intake (55 pg TEQ/day) it was 1.03 (0.97–1.09). Intake of dioxins, DL-PCBs and NDL-PCBs was not associated with cardiovascular mortality. There was no association between intakes of dioxins and cancer mortality, but a U-shaped association was observed for intake of DL-PCBs and intakes of NDL-PCBs and cancer mortality. The PCBs and dioxins are known to have endocrine disrupting properties which can lead to non-monotonic dose responses. These results need to be interpreted with caution and further studies are

Of the thousands of per- and polyfluoroalkyl substances (PFAS) known to exist, only a small fraction (≤1%) are commonly monitored in humans. This discrepancy has led to concerns that human exposure may be underestimated. Here, we address this problem by applying a comprehensive fluorine mass balance (FMB) approach, including total fluorine (TF), extractable organic fluorine (EOF), total oxidizable precursors (TOP), and selected target PFAS, to human serum samples collected over a period of 28 years (1986, 2007, and 2015) in Tromsø, Norway. While concentrations of TF did not change between sampling years, EOF was significantly higher in 1986 compared to 2007 and 2015. The ∑12PFAS concentrations were highest in 2007 compared to 1986 and 2015, and unidentified EOF (UEOF) decreased from 1986 (46%) to 2007 (10%) and then increased in 2015 (37%). While TF and EOF were not influenced by sex, women had higher UEOF compared to men, opposite to target PFAS. This is the first FMB in human serum to include TOP, and it suggests that precursors with >4 perfluorinated carbon atoms make a minor contribution to EOF (0–4%). Additional tools are therefore needed to identify substances contributing to the UEOF in human serum.

Background: Previous studies have reported associations between certain persistent organic pollutants (POPs) and type 2 diabetes mellitus (T2DM). Polybrominated diphenyl ethers (PBDEs) are a class of POPs that are found in increasing concentrations in humans. Although obesity is a known risk factor for T2DM and PBDEs are fat-soluble, very few studies have investigated associations between PBDEs and T2DM. No longitudinal studies have assessed associations between repeated measurements of PBDE and T2DM in the same individuals and compared time trends of PBDEs in T2DM cases and controls. Objectives: To investigate associations between pre- and post-diagnostic measurements of PBDEs and T2DM and to compare time trends of PBDEs in T2DM cases and controls. Methods: Questionnaire data and serum samples from participants in the Tromsø Study were used to conduct a longitudinal nested case-control study among 116 T2DM cases and 139 controls. All included study participants had three pre-diagnostic blood samples (collected before T2DM diagnosis in cases), and up to two post-diagnostic samples after T2DM diagnosis. We used logistic regression models to investigate pre- and post-diagnostic associations between PBDEs and T2DM, and linear mixed-effect models to assess time trends of PBDEs in T2DM cases and controls. Results: We observed no substantial pre- or post-diagnostic associations between any of the PBDEs and T2DM, except for BDE-154 at one of the post-diagnostic time-points (OR = 1.65, 95% CI: 1.00, 2.71). The overall time trends of PBDE concentrations were similar for cases and controls. Discussion: The study did not support PBDEs increasing the odds of T2DM, prior to or after T2DM diagnosis. T2DM status did not influence the time trends of PBDE concentrations.

Background: Positive associations have been reported between persistent organic pollutants (POPs) and type 2 diabetes mellitus (T2DM); however, causality has not been established. Over the last decades, environmental exposure to legacy POPs has decreased, complicating epidemiological studies. In addition, physiological risk factors for T2DM may also influence POP concentrations, contributing to a complex network of factors that could impact associations with T2DM. Longitudinal studies on this topic are lacking, and few have assessed prospective and cross-sectional associations between repeated POP measurements and T2DM in the same individuals, which may shed light on causality. Objectives: To compare longitudinal trends in concentrations of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in T2DM cases and controls, and to examine prospective and cross-sectional associations between PCBs, OCPs and T2DM at different time-points before and after T2DM diagnosis in cases. Methods: We conducted a longitudinal, nested case-control study (1986–2016) of 116 T2DM cases and 139 controls from the Tromsø Study. All participants had three blood samples collected before T2DM diagnosis in cases, and up to two samples thereafter. We used linear mixed-effect models to assess temporal changes of POPs within and between T2DM cases and controls, and logistic regression models to investigate the associations between different POPs and T2DM at different time-points. Results: PCBs, trans-nonachlor, cis-nonachlor, oxychlordane, cis-heptachlor epoxide, p,p’-DDE, and p,p’-DDT declined more slowly in cases than controls, whereas β-HCH and HCB declined similarly in both groups. Most POPs showed positive associations between both pre- and post-diagnostic concentrations and T2DM, though effect estimates were imprecise. These associations were most consistent for cis-heptachlor epoxide. Discussion: The observed positive associations between certain POPs and T2DM may be becaus

BACKGROUND: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. METHODS: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case-control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; <1st tertile) and metabolically unhealthy (MU; ≥1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW); body mass index (BMI)<25 kg/m2 or waist circumference (WC)<80 cm or waist-to-hip ratio (WHR)<0.8) and overweight (OW; BMI≥25 kg/m2 or WC≥80 cm or WHR≥0.8) status, generating four phenotype groups for each anthropometric measure: (i) MH/NW, (ii) MH/OW, (iii) MU/NW, and (iv) MU/OW. RESULTS: In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW [ORWC, 1.48; 95% confidence interval (CI), 1.05-2.10 and ORWHR, 1.68; 95% CI, 1.21-2.35] and MU/OW (ORBMI, 2.38; 95% CI, 1.73-3.27; ORWC, 2.69; 95% CI, 1.92-3.77 and ORWHR, 1.83; 95% CI, 1.32-2.54). MH/OW individuals were also at increased endometrial cancer risk compared with MH/NW individuals (ORWC, 1.94; 95% CI, 1.24-3.04). CONCLUSIONS: Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, OW status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity-related pathways are relevant for the development of this cancer beyond insulin. IMPACT: Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se.