[Association of urinary molybdenum levels with diabetes in adults aged 18 years and above in China].
Objective: To analyze the association of the urinary molybdenum level with diabetes in adults aged ≥18 years in China. Methods: A total of 10 893 adults aged 18-79 years were included from the first round of cross-sectional survey of China National Human Biomonitoring (2017-2018). Fasting venous blood and midcourse random urine samples were collected from them to detect the levels of serum fasting blood glucose and urinary molybdenum. Through physical examination and questionnaire survey, information about their demographic characteristics, dietary frequency, lifestyle and health status were collected. Restricted cubic spline function was used to analyze the dose-response relationship between urinary molybdenum level and the prevalence of diabetes. Multivariate logistic regression model was used to analyze the association between urinary molybdenum level and the prevalence of diabetes. Results: The weighted age of the study participants was (47.42±0.24) years, and 1 125 study participants were diagnosed with diabetes (the weighted prevalence rate: 10.72%). The weighted M(IQR) of urinary molybdenum and creatinine-corrected urinary molybdenum were 51.19 (54.87) μg/L and 48.12 (45.53) μg/g·creatinine, respectively. After adjustment for potential confounders, restricted cubic spline analysis revealed a positive linear dose-response relationship (total P=0.005, P for non-linear=0.055). The odds of diabetes increased by 15% with each 1 natural logarithm unit increase in urinary molybdenumnlevel, according to weighted multivariate logistic regression analysis, the OR was 1.15 (95%CI:1.04-1.28). Subgroup analysis revealed that the association was stronger in men, those living in rural area, and those aged 60-79 years. Conclusion: There is a positive association between the urinary molybdenum level and the prevalence of diabetes in adults in China.
Authors
Hu Hu, Li Li, Shi Shi, Ding Ding, Wu Wu, Qu Qu, Zhao Zhao, Hu Hu, Ji Ji, Li Li, Zhang Zhang, Song Song, Cai Cai, Cai Cai, Long Long, Lai Lai, Yu Yu, Ma Ma, Zhu Zhu, Shi Shi, Lyu Lyu
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