Yale School of Public Health, Yale University, New Haven, CT, USA.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
J Expo Sci Environ Epidemiol. 2019 Apr;29(3):344-357. doi: 10.1038/s41370-018-0088-z. Epub 2018 Oct 30.
Residents of agricultural areas experience pesticide exposures from sources other than direct agricultural work. We developed a quantitative, active ingredient-specific algorithm for cumulative (adult, married lifetime) non-occupational pesticide exposure intensity for spouses of farmers who applied pesticides in the Agricultural Health Study (AHS). The algorithm addressed three exposure pathways: take-home, agricultural drift, and residential pesticide use. Pathway-specific equations combined (i) weights derived from previous meta-analyses of published pesticide exposure data and (ii) information from the questionnaire on frequency and duration of pesticide use by applicators, home proximity to treated fields, residential pesticide usage (e.g., termite treatments), and spouse's off-farm employment (proxy for time at home). The residential use equation also incorporated a published probability matrix that documented the likelihood active ingredients were used in home pest treatment products. We illustrate use of these equations by calculating exposure intensities for the insecticide chlorpyrifos and herbicide atrazine for 19,959 spouses. Non-zero estimates for ≥1 pathway were found for 78% and 77% of spouses for chlorpyrifos and atrazine, respectively. Variability in exposed spouses' intensity estimates was observed for both pesticides, with 75th to 25th percentile ratios ranging from 7.1 to 7.3 for take-home, 6.5 to 8.5 for drift, 2.4 to 2.8 for residential use, and 3.8 to 7.0 for the summed pathways. Take-home and drift estimates were highly correlated (≥0.98), but were not correlated with residential use (0.01‒0.02). This algorithm represents an important advancement in quantifying non-occupational pesticide relative exposure differences and will facilitate improved etiologic analyses in the AHS spouses. The algorithm could be adapted to studies with similar information.
农业地区的居民会接触到除直接农业工作以外的其他来源的农药。我们为参加农业健康研究(AHS)的农民配偶(他们使用农药)开发了一种定量的、针对活性成分的、累积(成人、已婚终生)非职业性农药接触强度的算法。该算法解决了三条暴露途径:携带回家、农业飘移和住宅农药使用。特定途径的方程结合了:(i) 来自之前关于已发表的农药暴露数据的荟萃分析的权重,以及 (ii) 问卷中关于施药者使用农药的频率和持续时间、家庭与施药农田的接近程度、住宅农药使用(例如,白蚁处理)以及配偶的非农就业(家庭时间的替代指标)的信息。住宅使用方程还纳入了一份已发表的概率矩阵,该矩阵记录了活性成分在家庭害虫处理产品中使用的可能性。我们通过计算 19959 名配偶的杀虫剂毒死蜱和除草剂莠去津的暴露强度来举例说明这些方程的使用。对于毒死蜱和莠去津,分别有 78%和 77%的配偶在至少一条途径中有非零估计值。对于这两种农药,暴露配偶的强度估计值都存在差异,从 75%到 25%的比值范围分别为 7.1 到 7.3(携带回家)、6.5 到 8.5(飘移)、2.4 到 2.8(住宅使用)以及 3.8 到 7.0(总和)。携带回家和飘移的估计值高度相关(≥0.98),但与住宅使用不相关(0.01-0.02)。该算法在量化非职业性农药相对暴露差异方面是一个重要的进步,将有助于改善 AHS 配偶的病因分析。该算法可以适用于具有类似信息的研究。