Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS) · 2025
Association of multi-metal exposure with hyperuricemia in middle-aged and older adults: A cross-sectional study in rural Guangxi, China.
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Guan Qinyi, Teng Kaisheng, Liu Qiumei, Wu Songju, Luo Lei, Zhao Linhai, Rong Jiahui, Jin Wenjia, Zhang Tiantian, Xiaoting Mo, Jiansheng Cai, Zhang Zhiyong, Qin Jian
Аннотация
BACKGROUND: Hyperuricemia constitutes a significant global public health concern, particularly among the elderly, and is associated with environmental factors such as metal exposure. In China, the predominant focus of existing research has been on urban populations, which leaves the relationship between hyperuricemia and ecological exposures in rural populations inadequately explored. This study investigates the association between hyperuricemia and exposure to multiple metals among elderly residents in rural China.
METHODS: Cross-sectional survey data were collected from middle-aged and elderly individuals residing in Yao Autonomous County of Gongcheng, Guangxi, China, from 2018 to 2019. The analytical techniques employed included least absolute shrinkage and selection operator (LASSO) regression, binary logistic regression and Bayesian kernel machine regression (BKMR) to examine the association between exposure to multi-metal mixtures and hyperuricemia.
RESULTS: Logistic regression results indicated a negative association between magnesium (OR=0.634, 95 % CI=0.476-0.867, Q3) and hyperuricemia, while iron, nickel, strontium, molybdenum, and tin were positively associated with hyperuricemia (all P < 0.05). The Bayesian kernel machine regression analysis revealed a significant overall positive correlation between hyperuricemia and plasma polymetallic mixtures, with notable contributions from Sr (PIP=0.991) and Fe (PIP=0.749), particularly when all metals were at their respective 50th percentiles. Exposure-response relationships were consistent with the logistic regression results. Plasma Sr was positively correlated with hyperuricemia at different levels of other metals (p25, p50, p75).
CONCLUSION: This study suggests that exposure to multi-metal mixtures is positively associated with hyperuricemia, with Sr and Fe being the most significant contributors.
METHODS: Cross-sectional survey data were collected from middle-aged and elderly individuals residing in Yao Autonomous County of Gongcheng, Guangxi, China, from 2018 to 2019. The analytical techniques employed included least absolute shrinkage and selection operator (LASSO) regression, binary logistic regression and Bayesian kernel machine regression (BKMR) to examine the association between exposure to multi-metal mixtures and hyperuricemia.
RESULTS: Logistic regression results indicated a negative association between magnesium (OR=0.634, 95 % CI=0.476-0.867, Q3) and hyperuricemia, while iron, nickel, strontium, molybdenum, and tin were positively associated with hyperuricemia (all P < 0.05). The Bayesian kernel machine regression analysis revealed a significant overall positive correlation between hyperuricemia and plasma polymetallic mixtures, with notable contributions from Sr (PIP=0.991) and Fe (PIP=0.749), particularly when all metals were at their respective 50th percentiles. Exposure-response relationships were consistent with the logistic regression results. Plasma Sr was positively correlated with hyperuricemia at different levels of other metals (p25, p50, p75).
CONCLUSION: This study suggests that exposure to multi-metal mixtures is positively associated with hyperuricemia, with Sr and Fe being the most significant contributors.