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.

Causality; Air pollution; Confounding factors (epidemiology)