Dose–response relationship between multiple trace elements and risk of all-cause mortality: a prospective cohort study

Author:

Zhao Shaohua,Wang Shaohua,Yang Xiaorong,Shen Lin

Abstract

ObjectivesWe aimed to prospectively investigate the independent and combined relationship between trace elements concentrations [blood (selenium, manganese), serum (copper, zinc), and urine (cobalt, molybdenum, tin, strontium, iodine)] and all-cause mortality.MethodsThis study included 5,412 individuals with demographical, examination, and laboratory data from the National Health and Nutrition Examination Survey. Three statistical models, including Cox proportional hazards models, restricted cubic spline models, and Bayesian kernel machine regression (BKMR) models, were conducted to estimate the longitudinal relationship between trace elements and all-cause mortality.ResultsThere were 356 deaths documented with a median follow-up time of 70 months. In the single-exposure model, the results showed that compared with the lowest quartile, the adjusted hazard ratios (HRs) of mortality for the highest quartile of selenium, manganese, and strontium were 0.47 (95% CI: 0.28–0.79), 1.57 (95% CI: 1.14–2.14), and 0.47 (95% CI: 0.26–0.86), respectively. A nonlinear relationship between zinc, cobalt and mortality was also observed. Furthermore, a significant overall effect of mixtures of trace elements on all-cause mortality was identified, especially when the mixture was at the 60th percentile or lower.ConclusionThe association of multiple trace elements with all-cause mortality was identified in this study. It is recommended that healthcare providers and relevant public health agencies should strengthen the surveillance and management of trace elements. Emphasis should be placed on monitoring the sources of trace elements such as the body, food, and environment. More population studies and animal experiments should be conducted to identify the underlying mechanisms.

Publisher

Frontiers Media SA

Subject

Nutrition and Dietetics,Endocrinology, Diabetes and Metabolism,Food Science

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