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<p>This research presents an empirical analysis of the association between ambient air quality and mental health outcomes within the police force of Henan Province, China. It utilizes Air Quality Index (AQI) data from all 28 cities in the province, along with mental health survey data obtained from a sample of 40,790 officers using the 12-item General Health Questionnaire (GHQ-12). The analysis employs spatial econometric modeling to investigate these associations. The results demonstrate significant spatial autocorrelation in both air pollution levels and mental health risks, with cities exhibiting higher AQI values and elevated GHQ positivity rates showing pronounced spatial clustering. Estimates from a Spatial Durbin Model confirm a significant association between local air quality and mental health among police officers. Furthermore, the results indicate that air quality in neighboring areas is also correlated with the mental health risk levels of officers in a given locale. These findings point to both local and regional pollution exposure as significant correlates of psychological well-being among police officers, a group that experiences high levels of occupational exposure. The study underscores the need for inter-regional environmental policy coordination and the integration of mental health support into occupational health frameworks, particularly for public safety personnel in heavily polluted regions.</p>

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The relationship between air pollution and police officers’ mental health: an empirical analysis based on spatial econometric models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月29日

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  • Xiupan Teng

摘要

This research presents an empirical analysis of the association between ambient air quality and mental health outcomes within the police force of Henan Province, China. It utilizes Air Quality Index (AQI) data from all 28 cities in the province, along with mental health survey data obtained from a sample of 40,790 officers using the 12-item General Health Questionnaire (GHQ-12). The analysis employs spatial econometric modeling to investigate these associations. The results demonstrate significant spatial autocorrelation in both air pollution levels and mental health risks, with cities exhibiting higher AQI values and elevated GHQ positivity rates showing pronounced spatial clustering. Estimates from a Spatial Durbin Model confirm a significant association between local air quality and mental health among police officers. Furthermore, the results indicate that air quality in neighboring areas is also correlated with the mental health risk levels of officers in a given locale. These findings point to both local and regional pollution exposure as significant correlates of psychological well-being among police officers, a group that experiences high levels of occupational exposure. The study underscores the need for inter-regional environmental policy coordination and the integration of mental health support into occupational health frameworks, particularly for public safety personnel in heavily polluted regions.