Causal inference methods and its application in the study of health effects of air pollution
10.3760/cma.j.cn112150-20201113-01367
- VernacularTitle:因果推断方法在大气污染与人群健康效应研究中的应用
- Author:
Xiaofen XIE
1
;
Huan XU
;
Jialong WU
;
Bing GUO
;
Xiong XIAO
;
Junmin ZHOU
;
Shujuan YANG
;
Xing ZHAO
Author Information
1. 四川大学华西公共卫生学院 华西第四医院，成都 610041
- Keywords:
Causality;
Air pollution;
Confounding factors (epidemiology)
- From:
Chinese Journal of Preventive Medicine
2021;55(11):1364-1370
- CountryChina
- Language:Chinese
-
Abstract:
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.
