Suppr超能文献

鉴定法国农业工人和农场主接触的农药混合物:农业与癌症(AGRICAN)队列研究的结果。

Identification of pesticide mixtures to which French agricultural workers and farm-owners are exposed: Results from the Agriculture and Cancer (AGRICAN) cohort study.

机构信息

INSERM, UMR 1086 ANTICIPE, Caen, France; Université de Caen Normandie, Caen, France.

INSERM, UMR 1086 ANTICIPE, Caen, France; Université de Caen Normandie, Caen, France; Centre de Lutte Contre le Cancer François Baclesse, avenue du Général Harris, 14076 Caen Cedex 05, France.

出版信息

Sci Total Environ. 2024 Dec 10;955:176607. doi: 10.1016/j.scitotenv.2024.176607. Epub 2024 Sep 28.

Abstract

Farmers, particularly in Europe, are exposed to multiple pesticides during their working life. Such exposures can cause adverse health outcomes. We aimed to identify the main pesticide mixtures to which French agricultural workers are exposed and to classify farmers into clusters based on their mixture exposure profile. The AGRICAN cohort includes farm-owners and farm workers enrolled from 2005 to 2007, with information on exact years of beginning and end of pesticide use on 11 crops and five livestock. We estimated duration of exposure to 390 pesticides identified with the PESTIMAT crop-exposure matrix for 16,905 male pesticide users from 1950 to 2009. We used a Sparse Non-negative Matrix Under-approximation to identify the main pesticide mixtures based on exposure duration, and then applied hierarchical agglomerative clustering to classify farmers sharing similar profiles of co-exposure to the mixtures. SNMU suggested 6 optimal numbers of mixtures (4, 7, 11, 15, 27, 38) explaining from 29 to 91 % of total variance. We selected 27 mixtures. Mixtures contained between four to 22 pesticides and mostly concerned the use of pesticides on wheat/barley, vineyards, corn, fruit and vegetables or on multiple crops together. We selected 11 clusters composed of 395 to 4521 farmers. Some had a higher proportion of individuals working on specific crops (as vineyard or corn), while others were characterized by the diversity of crops (cluster 8:"Permanent crops, potatoes and tobacco"). This is the first study to identify pesticide mixtures in farmers and to classify them into clusters based on their mixture exposure profiles. The next step will be to study the associations between pesticide mixtures and health outcomes such as prostate cancer in AGRICAN.

摘要

农民,尤其是在欧洲的农民,在工作生涯中会接触到多种农药。这种接触可能会导致不良的健康后果。我们旨在确定法国农业工人接触的主要农药混合物,并根据他们的混合物接触情况对农民进行分类。AGRICAN 队列包括 2005 年至 2007 年间登记的农场主和农场工人,有关于在 11 种作物和 5 种牲畜上开始和结束使用农药的确切年份的信息。我们使用 PESTIMAT 作物暴露矩阵估计了 1950 年至 2009 年 16905 名男性农药使用者接触 390 种农药的暴露时间。我们使用稀疏非负矩阵逼近法根据暴露时间确定主要的农药混合物,然后应用分层凝聚聚类法对具有相似混合物共同暴露情况的农民进行分类。SNMU 建议使用 6 个最佳的混合物数量(4、7、11、15、27、38),可解释总方差的 29%至 91%。我们选择了 27 种混合物。混合物中含有 4 至 22 种农药,主要涉及在小麦/大麦、葡萄园、玉米、水果和蔬菜或多种作物上使用农药。我们选择了由 395 至 4521 名农民组成的 11 个集群。其中一些集群的个体从事特定作物(如葡萄园或玉米)的比例较高,而其他集群则以作物多样性为特征(集群 8:“多年生作物、土豆和烟草”)。这是第一项识别农民中农药混合物并根据其混合物暴露情况对其进行分类的研究。下一步将在 AGRICAN 中研究农药混合物与前列腺癌等健康结果之间的关联。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验