The Impact of Particulate Matter on Outdoor Activity and Mental Health: A Matching Approach

Abstract

Exposure to air pollution affects human activity and health. Particularly, in Asian countries, the influence of particulate matter on humans has received wide attention. However, there is still a lack of research about the effects of particulate matter on human outdoor activities and mental health. Therefore, we aimed to explore the association between exposure to particulate matter with a diameter of less than 10 µm (PM10) and outdoor activity along with mental health in South Korea where issues caused by particulate matter increasingly have social and economic impacts. We examined this relationship by combining the physical and habitual factors of approximately 100,000 people in 2015 from the Korean National Health Survey. To measure each individual's exposure to particulate matter, we computed the total hours exposed to a high PM10 concentration (>80 μg/m³) in a given district one month before the survey was conducted. After dividing all districts into six groups according to the exposed level of the high PM10, we applied the propensity score-weighting method to control for observable background characteristics. We then estimated the impact of the high PM10 on outdoor activity and mental health between the weighted individuals in each group. Our main findings suggest that the impact of PM10 on outdoor activity and stress shows an inverted-U shaped function, which is counterintuitive. Specifically, both outdoor activity and stress levels tend to be worsened when the exposure time to a high PM10 (>80 μg/m³) was more than 20 h. Related policy implications are discussed.

Keywords: mental health; outdoor activity; particulate matter; propensity score.

Figure 1

Research framework and the focus of this study. Note: An increase of particulate matter (PM) exerts an influence on outdoor activity and mental health. This is the locus of our study, as represented by the solid and bolded arrows. Outdoor physical activities and mental health affect a variety of diseases and mortality rates.

Figure 2

The method to calculate the total hour count of high PM10 exposure. Note: The x-axis denotes day, and the y-axis denotes the level of PM10. Each dot denotes an hourly level of PM10, so 24 dots are shown in each day. The red dots indicate that the level of PM for the time was higher than 80 µg/m³ between 1 August 2015, and 31 August 2015.

Figure 3

Propensity scores across groups.

Figure 4

Absolute standardized differences across all groups.

Figure 5

The estimated coefficient indicating the number of days that the participant walked at least 10 min per week. Note: The error bar indicates the 95% confidence interval of each coefficient.

Figure 6

The estimated coefficient indicating self-reported mental stress (Likert 4 scale: 1, strong to 4, less likely) across the six groups. Note: The error bar indicates the 95% confidence interval of each coefficient.

Figure 7

U-shape association between high PM10 exposure hours and focal outcomes. Note: The coefficients on x and x² is from the coefficients on high PM10 hours and high PM10 hours X² in Table 5.