Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS) · 2026
Association between urine metal exposure and sleep quality among Zhuang ethnic postmenopausal women in China.
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Lu Peini, Luo Dan, Lei Lidi, Chen Yingrong, Xu Xuemei, Wei Gangjie, Huang Xuanqian, Huang Dongping, Su Li, Qiu Xiaoqiang, Zeng Xiaoyun, Liu Shun
Аннотация
BACKGROUND: Previous studies have explored the effects of metal exposure on sleep indifferent age groups, but few have examined the effects in postmenopausal women. The study was aimed to investigate the single and mixed effects of exposure to 22 metals on sleep quality in postmenopausal women.
METHODS: The baseline data of 1914 postmenopausal women were extracted from the Prospective Cohort of Chronic Diseases in Guangxi Ethnic Minority Natural Population in China. Concentrations of 22 metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality in postmenopausal women. The binary logistic regression model was used to analyze the effect of single metals exposure on the risk of poor sleep quality and quantile g-computation regression model was applied to assess the mixed effects of multiple metals exposure.
RESULTS: Among the 1914 participants,736(38.5%) had poor sleep quality. In single-metal analyses, only manganese showed a positive association with poor sleep quality before multiple comparison correction (continuous variable, adjusted OR=1.21,95%CI:1.03-1.41), but this did not remain significant after false discovery rate (FDR) correction. Similarly, quartile-based analyses showed nominally positive associations for Mn (Q2:OR=1.51,95%CI:1.16-1.98,Q4:OR=1.41, 95%CI:1.07-1.85), Zn (Q2:OR=1.40, 95%CI:1.07-1.83), Ca (Q3:OR=1.36,95%CI:1.04-1.77), and Mo (Q3:OR=1.30, 95%CI:1.00-1.70), but none remained significant after FDR correction. However, the qgcomp mixture analysis revealed that exposure to the essential metal mixture was significantly associated with poor sleep quality (OR=1.23, 95%CI:1.05-1.44), with Mn, Zn, Ca, and Mo as the main positive contributors.
CONCLUSION: No single metal remained significantly associated with poor sleep quality after FDR correction, whereas the essential metal mixture showed a significant positive association, with Mn identified as the primary contributor. Associations for Ca, Zn, and Mo were observed only in specific quartiles with non-monotonic patterns and should therefore be considered exploratory. These findings highlight the importance of mixture-based approaches in environmental health research. Further longitudinal studies, animal experiments, and cell-based investigations are warranted to validate these findings.
METHODS: The baseline data of 1914 postmenopausal women were extracted from the Prospective Cohort of Chronic Diseases in Guangxi Ethnic Minority Natural Population in China. Concentrations of 22 metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality in postmenopausal women. The binary logistic regression model was used to analyze the effect of single metals exposure on the risk of poor sleep quality and quantile g-computation regression model was applied to assess the mixed effects of multiple metals exposure.
RESULTS: Among the 1914 participants,736(38.5%) had poor sleep quality. In single-metal analyses, only manganese showed a positive association with poor sleep quality before multiple comparison correction (continuous variable, adjusted OR=1.21,95%CI:1.03-1.41), but this did not remain significant after false discovery rate (FDR) correction. Similarly, quartile-based analyses showed nominally positive associations for Mn (Q2:OR=1.51,95%CI:1.16-1.98,Q4:OR=1.41, 95%CI:1.07-1.85), Zn (Q2:OR=1.40, 95%CI:1.07-1.83), Ca (Q3:OR=1.36,95%CI:1.04-1.77), and Mo (Q3:OR=1.30, 95%CI:1.00-1.70), but none remained significant after FDR correction. However, the qgcomp mixture analysis revealed that exposure to the essential metal mixture was significantly associated with poor sleep quality (OR=1.23, 95%CI:1.05-1.44), with Mn, Zn, Ca, and Mo as the main positive contributors.
CONCLUSION: No single metal remained significantly associated with poor sleep quality after FDR correction, whereas the essential metal mixture showed a significant positive association, with Mn identified as the primary contributor. Associations for Ca, Zn, and Mo were observed only in specific quartiles with non-monotonic patterns and should therefore be considered exploratory. These findings highlight the importance of mixture-based approaches in environmental health research. Further longitudinal studies, animal experiments, and cell-based investigations are warranted to validate these findings.