Chlorinated persistent organic pollutants and type 2 diabetes - A population-based study with pre- and post- diagnostic plasma samples.


Journal

Environmental research
ISSN: 1096-0953
Titre abrégé: Environ Res
Pays: Netherlands
ID NLM: 0147621

Informations de publication

Date de publication:
07 2019
Historique:
received: 18 02 2019
revised: 01 04 2019
accepted: 18 04 2019
pubmed: 29 4 2019
medline: 8 1 2020
entrez: 29 4 2019
Statut: ppublish

Résumé

Persistent organic pollutants (POPs) have been associated with type 2 diabetes (T2D), but causality is uncertain. Within longitudinal population-based data from northern Sweden, we assessed how POPs associated with T2D prospectively and cross-sectionally, and further investigated factors related to individual changes in POP concentrations. For 129 case-controls pairs matched by age, sex and date of sampling, plasma concentrations of hexachlorobenzene (HCB), dichlorodiphenyl-dichloroethylene (p,p'-DDE), dioxin-like (DL) polychlorinated biphenyl congeners (PCB-118 and PCB-156), and non-dioxin like (NDL-PCB: PCB-74, -99, -138 -153, -170, -180, -183 and PCB-187) were analyzed twice (baseline and follow-up, 9-20 years apart). The cases received their T2D diagnose between baseline and follow-up. Prospective (using baseline data) and cross-sectional (using follow-up data) odds ratios (ORs) for T2D on lipid standardized POPs (HCB, p,p'-DDE, ∑DL-PCBs, ∑NDL-PCBs) were estimated using conditional logistic regression, adjusting for body mass index (BMI) and plasma lipids. The influence of BMI, weight-change, and plasma lipids on longitudinal changes in POP concentrations were evaluated among non-diabetic individuals (n = 306). POPs were associated with T2D in both the prospective and cross-sectional assessments. Of a standard deviation increase in POPs, prospective ORs ranged 1.42 (95% CI: 0.99, 2.06) for ∑NDL-PCBs to 1.55 (95% CI: 1.01, 2.38) for HCB (p < 0.05 only for HCB), and cross-sectional ORs ranged 1.62 (95% CI: 1.13; 2.32) for p,p'-DDE to 2.06 (95% CI: 1.29, 3.28) for ∑DL-PCBs (p < 0.05 for all POPs). In analyses of non-diabetic individuals, higher baseline BMI, decreased weight and decreased plasma lipid concentrations were associated with a slower decrease of POPs. Cases had, besides a higher BMI, reduced cholesterol and weight gain at follow-up compared to controls, which can explain the higher ORs in the cross-sectional assessments. The association between POPs and T2D was confirmed, but an indication that individuals body fat history might influence POP-T2D associations weakens the epidemiological support for a causal association. It also warrants studies based on other exposure metrics than biomonitoring. In addition, we note that a cross-sectional design overestimates the ORs if T2D cases have successfully intervened on weight and/or blood lipids, as changes in these factors cause changes in POPs.

Sections du résumé

BACKGROUND
Persistent organic pollutants (POPs) have been associated with type 2 diabetes (T2D), but causality is uncertain.
OBJECTIVE
Within longitudinal population-based data from northern Sweden, we assessed how POPs associated with T2D prospectively and cross-sectionally, and further investigated factors related to individual changes in POP concentrations.
METHODS
For 129 case-controls pairs matched by age, sex and date of sampling, plasma concentrations of hexachlorobenzene (HCB), dichlorodiphenyl-dichloroethylene (p,p'-DDE), dioxin-like (DL) polychlorinated biphenyl congeners (PCB-118 and PCB-156), and non-dioxin like (NDL-PCB: PCB-74, -99, -138 -153, -170, -180, -183 and PCB-187) were analyzed twice (baseline and follow-up, 9-20 years apart). The cases received their T2D diagnose between baseline and follow-up. Prospective (using baseline data) and cross-sectional (using follow-up data) odds ratios (ORs) for T2D on lipid standardized POPs (HCB, p,p'-DDE, ∑DL-PCBs, ∑NDL-PCBs) were estimated using conditional logistic regression, adjusting for body mass index (BMI) and plasma lipids. The influence of BMI, weight-change, and plasma lipids on longitudinal changes in POP concentrations were evaluated among non-diabetic individuals (n = 306).
RESULTS
POPs were associated with T2D in both the prospective and cross-sectional assessments. Of a standard deviation increase in POPs, prospective ORs ranged 1.42 (95% CI: 0.99, 2.06) for ∑NDL-PCBs to 1.55 (95% CI: 1.01, 2.38) for HCB (p < 0.05 only for HCB), and cross-sectional ORs ranged 1.62 (95% CI: 1.13; 2.32) for p,p'-DDE to 2.06 (95% CI: 1.29, 3.28) for ∑DL-PCBs (p < 0.05 for all POPs). In analyses of non-diabetic individuals, higher baseline BMI, decreased weight and decreased plasma lipid concentrations were associated with a slower decrease of POPs. Cases had, besides a higher BMI, reduced cholesterol and weight gain at follow-up compared to controls, which can explain the higher ORs in the cross-sectional assessments.
DISCUSSION
The association between POPs and T2D was confirmed, but an indication that individuals body fat history might influence POP-T2D associations weakens the epidemiological support for a causal association. It also warrants studies based on other exposure metrics than biomonitoring. In addition, we note that a cross-sectional design overestimates the ORs if T2D cases have successfully intervened on weight and/or blood lipids, as changes in these factors cause changes in POPs.

Identifiants

pubmed: 31029940
pii: S0013-9351(19)30226-9
doi: 10.1016/j.envres.2019.04.017
pii:
doi:

Substances chimiques

Environmental Pollutants 0
Hydrocarbons, Chlorinated 0
Dichlorodiphenyl Dichloroethylene 4M7FS82U08
Polychlorinated Biphenyls DFC2HB4I0K

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

35-45

Informations de copyright

Copyright © 2019. Published by Elsevier Inc.

Auteurs

Andreas Tornevi (A)

Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden. Electronic address: andreas.tornevi@umu.se.

Johan Sommar (J)

Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden.

Panu Rantakokko (P)

Department for Health Security, Environmental Health Unit, National Institute for Health and Welfare, Kuopio, Finland.

Agneta Åkesson (A)

Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Carolina Donat-Vargas (C)

Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Hannu Kiviranta (H)

Department for Health Security, Environmental Health Unit, National Institute for Health and Welfare, Kuopio, Finland.

Olov Rolandsson (O)

Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, Umeå, Sweden.

Lars Rylander (L)

Environmental Epidemiology, Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden.

Maria Wennberg (M)

Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden.

Ingvar A Bergdahl (IA)

Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden.

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Classifications MeSH