Associations between rice consumption, arsenic metabolism, and insulin resistance in adults without diabetes.

Abstract

Rice consumption is an important source of arsenic exposure. Little has known about the impact of rice consumption on arsenic metabolism, which is related to insulin resistance. In this study, we examined the associations between rice consumption and arsenic metabolism, and between arsenic metabolism and insulin resistance in non-diabetic U.S adults who participated in the National Health and Nutrition Examination Survey (NHANES) 2003-2016. Rice consumer was defined as ≥0.25 cups of cooked rice/day. HOMA2-IR was calculated using HOMA2 Calculator software based on participant's fasting glucose and insulin values. Urinary arsenic concentrations below limits of detection were imputed first, and then arsenic metabolism (the proportions of inorganic arsenic (iAs), monomethylarsonate (MMA), and dimethylarsinate (DMA) to their sum) were calculated (expressed as iAs%, MMA%, and DMA%). Using the leave-one-out approach, rice consumers compared with non-consumers had a 1.71% (95% CI: 1.12%, 2.29%) higher DMA% and lower MMA% when iAs% fixed; a 1.55% (95% CI: 0.45%, 2.66%) higher DMA% and lower iAs% when MMA% fixed; and a 1.62% (95% CI: 0.95%, 2.28%) higher iAs% and lower MMA% when DMA% fixed, in multivariable adjustment models. With every 10% decrease in MMA%, the geometric mean ratio of HOMA2-IR was 1.06 (95% CI:1.03,1.08) and 1.05 (95% CI:1.02, 1.09) when DMA% and iAs% was fixed, respectively; however, the associations were attenuated after adjusting for body mass index. In stratified analysis, we found that lower MMA% was associated with higher HOMA2-IR in participants with obesity: a 10% increase in iAs% with a 10% decrease in MMA% was associated with higher HOMA2-IR with the geometric mean ratio of 1.05 (95% CI: 1.01, 1.09). Our findings suggest that rice consumption may contribute to lower MMA% that was further associated with higher insulin resistance, especially in individuals with obesity. Future prospective studies are needed to confirm our results in different populations.