The impacts of environmental chemicals on the decline of kidney function have been suggested by a limited number of statistical and animal studies. Thus, those exposures may be modifiable risk factors for chronic kidney disease. Some of the chemicals, such as Perfluoroalkyl acid (PFA), are pervasive throughout our environment, determining their health effects is an important public health concern. In this study, we examined cross-sectional data from the 2009–2010 cycle of the National Health and Nutrition Examination Survey (NHANES) using a statistical causal inference method-generalized propensity score method, to determine the links between concentrations of several major environmental chemicals and kidney function measured by the estimated glomerular filtration rate (eGFR). Various generalized propensity score estimation methods including Hirano-Imbens, additive spline, and a generalized additive model were compared. Among the examined environmental chemicals, each of the statistical models used associated an increase in PFA concentration with a decline in eGFR. We conclude that PFA is a modifiable risk factor for chronic kidney disease and the statistical causal method produces credible results in estimating the effect of chemical exposures on a continuous measure of kidney functions with an observational dataset.

有限的统计和动物研究表明，环境化学物质对肾功能下降的影响。因此，这些暴露可能是慢性肾脏疾病的可改变危险因素。一些化学物质，例如全氟烷基酸（PFA），在我们的整个环境中普遍存在，因此确定其健康影响是重要的公共健康问题。在这项研究中，我们使用统计因果推论方法-广义倾向评分法研究了国家健康与营养调查（NHANES）2009-2010年周期的横断面数据，以确定几种主要环境化学品的浓度之间的联系肾功能通过估计的肾小球滤过率（eGFR）来衡量。比较了各种广义倾向得分估计方法，包括平野-Imbens，加性样条和广义加性模型。在所检查的环境化学品中，使用的每种统计模型都将PFA浓度的增加与eGFR的下降联系在一起。我们得出的结论是，PFA是慢性肾脏病的一种可改变的危险因素，而统计因果方法在通过观察性数据集评估化学暴露对连续测量肾功能的影响方面产生了可信的结果。