Body composition and arsenic metabolism: a cross-sectional analysis in the Strong Heart Study

Abstract

Objective: The objective of this study was to evaluate the association between measures of body composition and patterns of urine arsenic metabolites in the 1989-1991 baseline visit of the Strong Heart Study, a cardiovascular disease cohort of adults recruited from rural communities in Arizona, Oklahoma, North Dakota and South Dakota.

Methods: We evaluated 3,663 Strong Heart Study participants with urine arsenic species above the limit of detection and no missing data on body mass index, % body fat and fat free mass measured by bioelectrical impedance, waist circumference and other variables. We summarized urine arsenic species patterns as the relative contribution of inorganic (iAs), methylarsonate (MMA) and dimethylarsinate (DMA) species to their sum. We modeled the associations of % arsenic species biomarkers with body mass index, % body fat, fat free mass, and waist circumference categories in unadjusted regression models and in models including all measures of body composition. We also considered adjustment for arsenic exposure and demographics.

Results: Increasing body mass index was associated with higher mean % DMA and lower mean % MMA before and after adjustment for sociodemographic variables, arsenic exposure, and for other measures of body composition. In unadjusted linear regression models, % DMA was 2.4 (2.1, 2.6) % higher per increase in body mass index category (< 25, ≥25 & <30, ≥30 & <35, ≥35 kg/m2), and % MMA was 1.6 (1.4, 1.7) % lower. Similar patterns were observed for % body fat, fat free mass, and waist circumference measures in unadjusted models and in models adjusted for potential confounders, but the associations were largely attenuated or disappeared when adjusted for body mass index.

Conclusion: Measures of body size, especially body mass index, are associated with arsenic metabolism biomarkers. The association may be related to adiposity, fat free mass or body size. Future epidemiologic studies of arsenic should consider body mass index as a potential modifier for arsenic-related health effects.

Figure 1

Maximum likelihood estimates of generalized gamma models for % arsenic species by body composition measures. The upper panel shows the crude associations of each % species with body mass index categories. The lower panel shows the residual association adjusting for categories of other body composition measures. Models allowed flexibility in location (β) and scale (σ). The % arsenic species are labeled at the marginal medians for each arsenic species.

Figure 2

Multivariate associations of body mass index and % arsenic species in urine using Dirichlet regression. The % arsenic species (% iAs, % MMA and % DMA) lie on a simplex. As body mass increases, overall metabolism shifts to greater % DMA, and the metabolism profiles are less heterogeneous across individuals within the same body mass index stratum.