Chen Tian, Liu Xiaohua, Zhang Jianghua, Wang Lulu, Su Jin, Jing Tao, Xiao Ping
State Environmental Protection Key Laboratory of the Assessment of Effects of Emerging Pollutants on Environmental and Human Health, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China; Department of Environmental Health, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Shanghai Minhang Center for Disease Control and Prevention, Shanghai, China.
Chemosphere. 2024 Mar;351:141194. doi: 10.1016/j.chemosphere.2024.141194. Epub 2024 Jan 11.
Epidemiological studies have related exposure to pesticides to increased risk of diabetes. However, few studies have evaluated the health effects of mixed pesticides exposure, especially in an elderly population. Here, we utilized gas chromatography-tandem mass spectrometry to quantify the levels of 39 pesticides in 4 categories in a Chinese elderly population. Then we used general linear models to explore the association between individual pesticide exposure and type 2 diabetes mellitus (T2DM). Restricted cubic spline (RCS) models were fitted to identify potential non-linearities between those associations. Furthermore, stratified analysis by gender was conducted to explore the gender-specific associations. Finally, we used weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the effects of mixed exposure to 39 pesticides. The results showed that exposure to pesticides was associated with high risk of T2DM, with β-Hexachlorocyclohexane (β-BHC) and oxadiazon being the most significant independent contributors, which was pronounced among elderly women. Moreover, the association of β-BHC and oxadiazon with T2DM was linear. These indicated that it is an urgent need to take practical measures to control these harmful pesticides.
流行病学研究表明，接触农药会增加患糖尿病的风险。然而，很少有研究评估混合农药接触对健康的影响，尤其是在老年人群中。在此，我们利用气相色谱-串联质谱法对中国老年人群中4类39种农药的含量进行了定量分析。然后，我们使用一般线性模型来探讨个体农药接触与2型糖尿病（T2DM）之间的关联。采用限制立方样条（RCS）模型来识别这些关联之间潜在的非线性关系。此外，我们还进行了按性别分层的分析，以探讨特定性别的关联。最后，我们使用加权分位数和（WQS）回归、基于分位数的g计算（qgcomp）和贝叶斯核机器回归（BKMR）来评估39种农药混合接触的影响。结果表明，接触农药与患T2DM的高风险相关，其中β-六氯环己烷（β-BHC）和恶草酮是最显著的独立影响因素，在老年女性中尤为明显。此外，β-BHC和恶草酮与T2DM的关联呈线性。这些结果表明，迫切需要采取切实措施来控制这些有害农药。
