Correlation and interaction between urinary metals level and diabetes: A cross sectional study of community-dwelling elderly

It has been reported that metal exposure is associated with the risk of diabetes, but the results are inconsistent. The relationship between diabetes and a single metal might be attenuated or strengthened due to the complex interactions of metals and the chronic diseases comorbidity (especially in the elderly). However, the evidence of multiple metal exposure effect in participants with diabetes only is limited, particularly in the elderly. This cross-sectional study used a case-control method, involving 188 diabetes patients and 376 healthy participants aimed to evaluate the potential relationships between the concentrations of 9 metals in urine and the risk of diabetes and to access the interactive effects of metals in Chinese community-dwelling elderly. The urine levels of 9 metals (cobalt, zinc, copper, arsenic, molybdenum, cadmium, tellurium, thallium, lead) were detected by inductively coupled plasma mass spectrometry (ICP-MS) in 564 adults recruited from Yinchuan Community Health Service Center (Yinchuan, China). During the baseline survey, the demographic information of the subjects was collected through questionnaire survey, the indexes such as blood pressure, blood lipid and liver function were measured through physical examination. Logistic regression and restricted cubic spline (RCS) analysis were used to explore the associations and dose–response relationships of urine metals with diabetes. To the analysis of multi-metal exposures and diabetes risk, weighted quantile sum (WQS) regression model and the Bayesian Kernel machine regression (BKMR) model were applied. The concentrations of cobalt, zinc, copper, arsenic, molybdenum, cadmium, tellurium, thallium, and lead were higher in the diabetes group ( p