Role of environmental chemicals in diabetes and obesity: a National Toxicology Program workshop review

Abstract

Background: There has been increasing interest in the concept that exposures to environmental chemicals may be contributing factors to the epidemics of diabetes and obesity. On 11-13 January 2011, the National Institute of Environmental Health Sciences (NIEHS) Division of the National Toxicology Program (NTP) organized a workshop to evaluate the current state of the science on these topics of increasing public health concern.

Objective: The main objective of the workshop was to develop recommendations for a research agenda after completing a critical analysis of the literature for humans and experimental animals exposed to certain environmental chemicals. The environmental exposures considered at the workshop were arsenic, persistent organic pollutants, maternal smoking/nicotine, organotins, phthalates, bisphenol A, and pesticides. High-throughput screening data from Toxicology in the 21st Century (Tox21) were also considered as a way to evaluate potential cellular pathways and generate -hypotheses for testing which and how certain chemicals might perturb biological processes related to diabetes and obesity.

Conclusions: Overall, the review of the existing literature identified linkages between several of the environmental exposures and type 2 diabetes. There was also support for the "developmental obesogen" hypothesis, which suggests that chemical exposures may increase the risk of obesity by altering the differentiation of adipocytes or the development of neural circuits that regulate feeding behavior. The effects may be most apparent when the developmental exposure is combined with consumption of a high-calorie, high-carbohydrate, or high-fat diet later in life. Research on environmental chemical exposures and type 1 diabetes was very limited. This lack of research was considered a critical data gap. In this workshop review, we outline the major themes that emerged from the workshop and discuss activities that NIEHS/NTP is undertaking to address research recommendations. This review also serves as an introduction to an upcoming series of articles that review the literature regarding specific exposures and outcomes in more detail.

Figure 1

Association between maternal smoking during pregnancy and overweight/obesity in offspring. Studies are grouped by study design and then sorted by health outcome (overweight or obesity); studies are presented alphabetically by author within the health outcome categories. Abbreviations and symbols: ♀, female; ♂, male; AK Nat, Alaskan native; ALSPAC, Avon Longitudinal Study of Parents and Children; Am Ind, American Indian; adj OR, adjusted odds ratio; BBC, British Birth Cohort; CI, confidence interval; CESAR, Central European Study on Air Pollution and Respiratory Health; CLASS, Children’s Lifestyle and School Performance study; CPP, Collaborative Perinatal Project; GDM, gestational diabetes mellitus; Gen R, Generation R study; OH, Ohio; MA, Massachusetts; milt serv, military service; nat’l, national; NCDS, National Child Development Study; NLSY, National Longitudinal Survey of Youth; PedNSS, Pediatric Nutrition Surveillance System; prev OR, prevalence odds ratio; WI, Wisconsin; WIC, Women, Infants, and Children program. ^aRisk estimates for bracketed statistics (i.e., [crude prev OR]) calculated based on data presented in the paper using open source epidemiology statistics software OpenEpi (Dean et al. 2011).

Figure 2

Association between arsenic and diabetes in areas of relatively high exposures (> 150 ppm drinking water). Studies are sorted by quality of the diagnostic from worse to better. Abbreviations: adj PR, adjusted prevalence ratio; As, arsenic; avg., average; CC, case–control; CEI, cumulative exposure index; CS, cross-sectional; FBG, fasting blood glucose; HEALS, Health Effects of Arsenic Longitudinal Study; OGTT, oral glucose tolerance test; Pros, prospective; Qn, quintile; Retro, retrospective; RR, relative risk; SMR, standardized mortality ratio; WA, Washington State. ^aCalculated based on data presented using open source epidemiology statistics software OpenEpi (Dean et al. 2011) for Nabi et al. (2005) and Tsai et al. (1999) or as estimated by Navas-Acien et al. (2006) for Tollestrup et al. (2003).

Figure 3

Association between PCBs and diabetes. Studies are grouped by study design and then sorted alphabetically by first author within each study design category. Abbreviations: CARDIA, Coronary Artery Risk Development in Young Adults; CS, cross-sectional; FBG, fasting blood glucose; IDR, incidence density ratio; IRR, incidence rate ratio; LOD, limit of detection; med, median; MI, Michigan; ND, not detected; NHANES, National Health and Nutrition Examination Survey; PBB, polybrominated biphenyl; Q, quartile; T, tertile; TEQ, toxic equivalency; WHILA, Women’s Health in the Lund Area; ww, wet weight.