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Associations between urinary metals and kidney stones in the Miao population of Guizhou
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Cheng CHEN, Yu-xin ZHANG, Shen-yan WU, Yi-li SHEN, Yu-xin HU, Feng HONG
Modern Preventive Medicine | 2024, 51(2) : 366 - 373
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Modern Preventive Medicine | 2024, 51(2): 366-373
Clinical Medicine and Prevention
Associations between urinary metals and kidney stones in the Miao population of Guizhou
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Cheng CHEN, Yu-xin ZHANG, Shen-yan WU, Yi-li SHEN, Yu-xin HU, Feng HONG
Affiliations
  • School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
Published: 2024-01-25 doi: 10.20043/j.cnki.MPM.202306249
Outline
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Objective

To discuss the correlation between urinary metal elements and kidney stones in Miao population in Guizhou Province since there are few studies on the association between urine metal concentration and the risk of kidney stones in ethnic minorities.

Methods

In this study, 3 933 Miao people were sampled from the cohort database of natural populations living in ethnic minority areas in southwest China, and the concentrations of urine metals(arsenic, cadmium, cobalt, chromium, copper, iron, mercury, lithium, manganese, molybdenum, nickel, lead, strontium, vanadium and zinc) were detected by inductively coupled plasma mass spectrometry. The urinary metal concentration was divided into four groups: Q1, Q2, Q3 and Q4, and the relationship between the exposure of a single metal to the risk of kidney stones was analyzed by binary logistic regression model, and the dose-response relationship between the concentration of monometals and the risk of kidney stones was explored by restriction cubic spline.

Results

The detection rate of kidney stones of Miao ethnic group in Guizhou Province was 20.59%, the detection rate of male was 18.27%, and the detection rate of female was 22.02%. The results of the binary logistic regression model showed that when the covariate was not adjusted. In Miao women, after adjusting the covariate, the Q1 exposure group was used as the reference, and the chromium Q4 group(OR=0.534, 95% CI: 0.337-0.846) was used. Lead Q3 group(OR=0.546, 95% CI: 0.400-0.745); Lead Q4 group(OR=0.657, 95% CI: 0.482-0.895) was negatively correlated with the risk of kidney stones. In Miao men, after adjusting for covariates, manganese Q4 group(OR=1.911, 95% CI: 1.274-2.867) was positively correlated with the risk of kidney stones. Further restriction cubic spline analysis showed that there was a dose-response relationship between urine chromium and the risk of kidney stones in Miao women(P<0.05). There was no dose-response relationship between urine lead and the risk of kidney stones(P>0.05), and in Miao men, there was a dose-response relationship between urinary manganese and the risk of kidney stones(P<0.05).

Conclusion

Heavy metals in urine affect kidney stones which supports the view that metal exposure plays a role in the development of kidney stones.

Urine metal concentration  /  Kidney stone  /  Miao ethnic group
Cheng CHEN, Yu-xin ZHANG, Shen-yan WU, Yi-li SHEN, Yu-xin HU, Feng HONG. Associations between urinary metals and kidney stones in the Miao population of Guizhou[J]. Modern Preventive Medicine, 2024 , 51 (2) : 366 -373 . DOI: 10.20043/j.cnki.MPM.202306249
Year 2024 volume 51 Issue 2
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doi: 10.20043/j.cnki.MPM.202306249
  • Receive Date:2023-06-13
  • Online Date:2026-03-19
  • Published:2024-01-25
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  • Received:2023-06-13
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    School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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