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.

Abstract

The aim of this study was to evaluate the exposure profiles and predictors for solar greenhouse workers to chemical mixtures. 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. 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. This study provided important insights into the exposure characteristics and predictive factors of chemical mixtures among solar greenhouse workers.