Profiles and Predictor of Pesticide and Metal Mixtures in Urine Among Solar Greenhouse Workers: Findings From the Measures of Environment and the Health Outcomes Study.
{"title":"Profiles and Predictor of Pesticide and Metal Mixtures in Urine Among Solar Greenhouse Workers: Findings From the Measures of Environment and the Health Outcomes Study.","authors":"Siyuan Wang, Jianjian Su, Xin Song, Binshuo Hu, Yanan Pan, Xiaowen Ding, Xiaodong Liu, Chunguang Ding, Tian Chen, Xiaojun Zhu, Huadong Xu, Tenglong Yan","doi":"10.1097/JOM.0000000000003317","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to evaluate the exposure profiles and predictors for solar greenhouse workers to chemical mixtures.</p><p><strong>Methods: </strong>Two hundred eighty-one solar greenhouse workers in China were included in this study. Six pesticides and 14 metals in urine were determined using chromatography-mass spectrometry. Pearson correlation, k-means clustering, and principal component analysis were used.</p><p><strong>Results: </strong>The Pearson correlation coefficient showed that the correlation between similar chemicals was stronger than that between different types of chemicals. The k-means clustering showed that the female workers and multiple greenhouse workers had significantly higher chemical concentrations. The principal component analysis results showed that six principal components explain over 50% of the data variance, each dominated by specific chemicals.</p><p><strong>Conclusion: </strong>This study provided important insights into the exposure characteristics and predictive factors of chemical mixtures among solar greenhouse workers.</p>","PeriodicalId":94100,"journal":{"name":"Journal of occupational and environmental medicine","volume":" ","pages":"e219-e226"},"PeriodicalIF":1.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of occupational and environmental medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/JOM.0000000000003317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/16 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: The aim of this study was to evaluate the exposure profiles and predictors for solar greenhouse workers to chemical mixtures.
Methods: Two hundred eighty-one solar greenhouse workers in China were included in this study. Six pesticides and 14 metals in urine were determined using chromatography-mass spectrometry. Pearson correlation, k-means clustering, and principal component analysis were used.
Results: The Pearson correlation coefficient showed that the correlation between similar chemicals was stronger than that between different types of chemicals. The k-means clustering showed that the female workers and multiple greenhouse workers had significantly higher chemical concentrations. The principal component analysis results showed that six principal components explain over 50% of the data variance, each dominated by specific chemicals.
Conclusion: This study provided important insights into the exposure characteristics and predictive factors of chemical mixtures among solar greenhouse workers.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
