[Causal inference methods and its application in the study of health effects of air pollution].

The adverse health effects of air pollution remains a daunting public health problem globally. The research of the health effects of air pollution provides important evidence for ambient air quality standard establishments and air pollution interventions. In recent years, causal inference has been gradually introduced into the observational study of environmental epidemiology, which provides more statistical method options for the study of causal relationships between air pollution and population health effects. Controlling confounders in observational studies is a major challenge for causal inference. This study introduces the causal inference methods for the identification and control of confounding factors currently used in the study of air pollution and population health effects, in order to provide methodological reference and basis for the causal inference study of air pollution and population health effects in China.大气污染的健康危害是全球关注的公共卫生问题。大气污染与人群健康效应研究证据是环境空气质量标准与大气污染治理方案制定的重要依据。近年来，因果推断方法逐步引入到环境流行病学观察性研究中，为大气污染与人群健康效应的因果关系研究提供了更多的统计方法选择。观察性研究的复杂混杂偏倚问题是因果推断的重大挑战。本研究主要介绍了目前应用于大气污染与人群健康效应研究的混杂因素识别与控制的各因果推断方法，旨在为我国大气污染与人群健康效应因果推断研究提供方法学上的参考和依据。.