Background : As the physical and mental health hazards of air pollution become increasingly severe, efforts to establish response systems are intensifying both domestically and internationally. Globally, the disease burden of mental disorders continue...
Background : As the physical and mental health hazards of air pollution become increasingly severe, efforts to establish response systems are intensifying both domestically and internationally. Globally, the disease burden of mental disorders continues to rise. South Korea maintains one of the highest suicide rates among OECD countries, and the prevalence of depression has also surged sharply in recent years. Air pollution is known to cause mental health problems such as suicide and depression through biological pathways, and it also affects mental health through complex interactions with various socioeconomic factors. However, existing studies have primarily analyzed the effects of short-term exposure to air pollution or individual-level impacts. Research analyzing the effects of long-term exposure and interactions with regional characteristics at the city, county, and district level across all of Korea is currently lacking.
Objectives : This study aimed to evaluate the impact of long-term exposure to air pollution on regional mental health levels using Korean city/county/district-level panel data, and to identify the moderating effects of regional characteristics such as health behaviors, healthcare accessibility, and socioeconomic status. It seeks to provide policy evidence for enhancing community mental health and improving health equity.
Methods : The study included 206 cities, counties, and districts in Korea, excluding areas that did not meet the criteria for calculating air pollution statistics. The independent variables were the annual average concentrations of three air pollutants (PM10, PM2.5, NO2), and the dependent variables were three regional-level mental health indicators (number of suicide deaths, prevalence of depressive symptoms, prevalence of perceived stress). Covariates included regional environmental and spatiotemporal indicators (annual mean temperature, year, latitude, longitude), health behaviors (obesity rate, healthy lifestyle practice rate), healthcare utilization (unmet medical needs rate), and socioeconomic indicators (sex ratio, elderly population ratio, population density, fiscal self-sufficiency rate). The statistical analysis method employed a Generalized Linear Mixed Model (GLMM) assuming a Poisson distribution when the dependent variable was suicide deaths. For the prevalence of depression and perceived stress rates, a Linear Mixed Model (LMM) was used.
Results : It was confirmed that when PM10 and PM2.5 increase by one quartile range, the risk of suicide mortality increases by 1.035 times (95% CI: 1.013, 1.059) and 1.022 times (95% CI: 1.001, 1.044), respectively. Furthermore, when PM10 and PM2.5 increased by one quartile range, the prevalence of experiencing depression increased by 0.484 percentage points (95% CI: 0.216, 0.753) and 0.308 percentage points (95% CI: 0.045, 0.570), respectively. Conversely, while the perceived stress rate increased by 0.589 percentage points (95% CI: 0.112, 1.066) when PM10 increased by one quartile range, PM2.5 and NO2 showed no significant association with the perceived stress rate. Among regional characteristics, the health-conscious lifestyle practice rate emerged as a factor significantly mitigating the mental health impact of air pollution. The lag effect analysis revealed that PM10 showed a significant positive association with perceived stress rates at the three-year average exposure (Lag0-2). For PM2.5, the effect size on suicide mortality risk and depression experience rate was greater at Lag0-2 compared to exposure in the current year (Lag0).
Conclusion : PM10 and PM2.5 were significantly associated with community-level mental health, and regional characteristics were found to moderate the magnitude of these associations. These findings suggest that air pollution should be considered as an environmental factor in mental health policy development and that tailored interventions reflecting regional characteristics are necessary.