Identifying the causal effects of long-term exposure to PM2.5 and ground surface ozone on individual medical costs in China—evidence from a representative longitudinal nationwide cohort

Abstract

Abstract Background There is little evidence on whether PM2.5 and ground surface ozone have consistent effects on increased individual medical costs, and there is a lack of evidence on causality in developing countries. Methods This study utilized balanced panel data from 2014, 2016, and 2018 waves of the Chinese Family Panel Study. The Tobit model was developed within a counterfactual causal inference framework, combined with a correlated random effects and control function approach (Tobit-CRE-CF), to explore the causal relationship between long-term exposure to air pollution and medical costs. We also explored whether different air pollutants exhibit comparable effects. Results This study encompassed 8928 participants and assessed various benchmark models, highlighting the potential biases from failing to account for air pollution endogeneity or overlooking respondents without medical costs. Using the Tobit-CRE-CF model, significant effects of air pollutants on increased individual medical costs were identified. Specifically, margin effects for PM2.5 and ground-level ozone signifying that a unit increase in PM2.5 and ground-level ozone results in increased total medical costs of 199.144 and 75.145 RMB for individuals who incurred fees in the previous year, respectively. Conclusions The results imply that long-term exposure to air pollutants contributes to increased medical costs for individuals, offering valuable insights for policymakers aiming to mitigate air pollution’s consequences.

Keywords

• Air pollution
• Medical costs
• Causal models
• Tobit model
• China