Department of Statistics, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138, USA; email:
Annu Rev Public Health. 2019 Apr 1;40:23-43. doi: 10.1146/annurev-publhealth-040218-044048. Epub 2019 Jan 11.
The field of environmental health has been dominated by modeling associations, especially by regressing an observed outcome on a linear or nonlinear function of observed covariates. Readers interested in advances in policies for improving environmental health are, however, expecting to be informed about health effects resulting from, or more explicitly caused by, environmental exposures. The quantification of health impacts resulting from the removal of environmental exposures involves causal statements. Therefore, when possible, causal inference frameworks should be considered for analyzing the effects of environmental exposures on health outcomes.
环境卫生领域一直以模型研究为主，特别是将观察到的结果与观察到的协变量的线性或非线性函数进行回归。然而，关注改善环境卫生政策进展的读者期望了解环境暴露导致或更明确地由环境暴露引起的健康影响。量化消除环境暴露对健康的影响涉及因果关系陈述。因此，在可能的情况下，应考虑使用因果推理框架来分析环境暴露对健康结果的影响。
