Blood Concentrations of Persistent Organic Pollutants and Unhealthy Metabolic Phenotypes in Normal-Weight, Overweight, and Obese Individuals

Abstract

Factors underlying metabolic phenotypes, such as the metabolically healthy but obese phenotype, remain unclear. Differences in metabolic phenotypes-particularly, among individuals with a similar body mass index-could be related to concentrations of persistent organic pollutants (POPs). To our knowledge, no studies have analyzed POPs and metabolic phenotypes in normal-weight persons. We investigated the relationships between serum concentrations of POPs and metabolic phenotypes in 860 normal-weight, overweight, and obese participants in the 2002 Catalan Health Interview Survey (Spain). POP concentrations were significantly higher in metabolically unhealthy than in metabolically healthy individuals. In models adjusting for body mass index and other confounders, hexachlorobenzene, β-hexachlorocyclohexane, and polychlorinated biphenyls were associated with the unhealthy metabolic phenotype and metabolic syndrome. Among normal-weight individuals, the adjusted prevalence ratio of having an unhealthy phenotype for the upper category of the sum of orders of the 6 mentioned POPs (all individually associated with metabolic phenotypes) was 4.1 (95% confidence interval: 1.7, 10.0). Among overweight and obese individuals, the corresponding prevalence ratio for the sum of polychlorinated biphenyls was 1.4 (95% confidence interval: 1.0, 1.8). Our results supported the hypothesis that POP concentrations are associated with unhealthy metabolic phenotypes, not only in obese and overweight individuals but also (and probably more strongly) in normal-weight individuals.

Polychlorinated biphenyl serum levels, thyroid hormones and endocrine and metabolic diseases in people living in a highly polluted area in North Italy: A population-based study

“…The Anniston community survey showed a positive association between serum PCB levels and self-referred diabetes prevalence, but the association was found in females only and was imprecise in older people, who however had the highest PCB serum levels (Silverstone et al., 2012). PCB serum concentration was positively associated with diabetes, prediabetes and unhealthy metabolic pattern also in a cross-sectional study in a Spanish general population, with a stronger association in normal-weight than overweight-obese subjects (Gasull et al., 2012, 2017). In another cross-sectional study in a Native American population, however, an association was found between diabetes and only low-chlorinated PCB congeners, which are the most volatile congeners, suggesting that the main route of exposure was inhalation (Aminov et al., 2016).…”

“…PCBs have been classified as endocrine disruptors because they can interact with several functions of endocrine system, particularly the thyroid and reproductive organs (El Majidi et al., 2014). Various studies have also found that PCBs are associated with diabetes, insulin resistance and unhealthy metabolic phonotype (Kuo et al., 2013; Taylor et al., 2013; Gasull et al., 2017), and cardiovascular diseases, particularly hypertension (Everett et al., 2008, 2011). However, current evidence on the role of PCBs as determinants of endocrine, metabolic or cardiovascular disease is still inconclusive (Warner et al., 2013; Lee et al., 2014; Henríquez-Hernández et al., 2017; Benson et al., 2018), Brescia is a highly industrialized town in North Italy where a chemical factory produced PCBs from 1938 to 1984 (CTS , 2003).…”

Plasma concentrations of persistent organic pollutants and pancreatic cancer risk

“…These observations argue against the need to condition on total lipids, BMI or smoking. 16 , 21 Nevertheless, to explore alternative scenarios, in some instances we also used lipid-corrected POPs or further conditioned on BMI or smoking.…”

“…Whereas matching factors included age, date and time of the day of blood collection, and fasting status, results are coherent with the notion that exposure misclassification is lower and the comparison of POP measures between cases and controls more accurate among participants who fast longer or have normal weight. 1 , 9 , 13 , 15 , 16 …”

“…To assess exposure to multiple compounds, we computed: (i) the sum of all 10 PCBs; (ii) the sum of four PCBs; (iii) the sum of orders of the six OC pesticides quantified in ≥90% of participants; and (iv) the sum of orders of the 16 POPs quantified in ≥90% of participants ( Table 1 ). 1 , 16 We computed the number of POPs detected in each person at high concentrations (nPhc) by adding the number of POPs (out of the 16 POPs quantified in ≥90% of participants) whose plasma concentrations were equal to or greater than a selected cut-off point, as percentile 75. 17 …”