Interactions of arsenic metabolism with arsenic exposure and individual factors on diabetes occurrence: Baseline findings from Arsenic and Non-Communicable disease cohort (AsNCD) in China

The interaction between arsenic metabolism and potential modifiers on the risk of diabetes is unclear. This research aimed to investigate arsenic metabolism and diabetes prevalence and to identify the interactive effects of arsenic metabolism with some risk factors on diabetes in a Chinese population. A baseline cross-sectional survey was performed in two areas with groundwater arsenic contamination in China. Arsenic levels in water and arsenic metabolites in urine were analyzed. The proportions of each arsenic metabolite (inorganic arsenic [iAs%], monomethylarsonic acid [MMA%], and dimethylarsinic acid [DMA%]) were computed to evaluate arsenic metabolism. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between arsenic and diabetes. Interaction on the additive scale between arsenic methylation index and effect modifier was evaluated by calculating the relative excess risk due to interaction (RERI). Compared with participants in the lower tertile of MMA%, participants in the middle and upper tertiles of MMA% were less prone to diabetes (OR: 0.47 and 0.31, respectively). However, participants in the upper tertiles of urinary DMA% (OR: 3.18) were more likely to have diabetes than those participants in the lower tertiles. The stratified analyses revealed that a one-unit increase in DMA% was associated with higher odds of diabetes in females (OR: 1.06, 95% CI: 1.01, 1.11), older people (OR: 1.05, 95% CI: 1.00, 1.10), and subjects with body mass index (BMI) under 25 kg/m(2) (OR: 1.07, 95% CI: 1.01, 1.14). The additive interactions between DMA% and female gender (RERI: 0.40, 95% CI: 0.01, 11.88), DMA% and age (RERI: 0.02, 95% CI: 0.01, 8.85), as well as DMA% and BMI (RERI: 0.49, 95% CI: 0.01, 9.62), were statistically significant. In conclusion, efficient arsenic metabolism is associated with higher odds of diabetes. Urinary DMA% and individual factors interact to synergistically influence diabetes occurrence in the Chinese population. (C) 2020 Published by Elsevier Ltd.