Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness | BMC Public Health

To the best of our knowledge, this is the first nationwide study to investigate the association between long-term exposure to PM_2.5 and mortality in South Korea. In this study, we found that long-term exposure to PM_2.5 was significantly associated with increased risk of non-accidental, circulatory, and respiratory mortalities. We further observed that community-level characteristics including deprivation status, medical infrastructure, and greenness could modify these associations, and the direction of this modification might not be consistent across different causes of death.

Our findings, which indicate a positive association between long-term PM_2.5 exposure and mortality, are in line with the majority of the existing epidemiological evidence. A recent systematic review and meta-analysis reported a summary risk ratio of 1.08 (95% CI 1.06, 1.09), 1.11 (95% CI 1.09, 1.14), and 1.10 (95% CI 1.03, 1.18) per 10 µg/m³ increase in long-term PM_2.5 exposure for all-cause, circulatory, and respiratory mortality, respectively (2). However, most previous studies on long-term PM_2.5 exposure and mortality have been conducted in American and European regions. The differences in observed effect sizes of PM_2.5 in the present study compared to previous studies may have resulted from methodological differences, variations in PM_2.5 concentration and composition, or distinct population characteristics.

In South Korea, only a handful of cohort-based studies have investigated the long-term exposure to PM₁₀ and mortality. One nationwide study based on NHIS-NSC version 1.0 reported positive, but statistically non-significant associations between PM₁₀ and mortality: HR (95% CI) of 1.05 (0.99, 1.11), 1.02 (0.90, 1.16), 1.19 (0.91, 1.57) per 10 µg/m³ increase in PM₁₀, for non-accidental, cardiovascular, and respiratory mortality, respectively (29). A study using Korean National Health and Nutritional Examination Survey with Mortality follow-up found positive association of PM₁₀ with circulatory mortality (HR 1.27; 95% CI 0.96, 1.66 per 10 µg/m³ increase), but not with respiratory mortality, in seven major cities in South Korea (16). To juxtapose our findings with previous studies in South Korea, we changed the exposure in our main model from PM_2.5 to PM₁₀. Consistent with earlier findings, we observed insignificant associations between PM₁₀ and mortalities: HR (95% CI) of 0.96 (0.91, 1.02), 1.09 (0.97, 1.22), 1.11 (0.95, 1.31) per 10 µg/m³ increase in PM₁₀ for non-accidental, cardiovascular, and respiratory mortality, respectively. These results suggest that exposure to PM_2.5 might pose a greater risk to human health than PM₁₀ in South Korea. PM_2.5 is capable of reaching the alveolar region of the lungs where gas exchange occurs due to its finer size, and may contain more hazardous substances, including metallic components, than larger particles (17). Further epidemiological studies focusing on PM_2.5 would be warranted in South Korea.

In the present study, we observed that circulatory mortality exhibited a higher association with longer exposure time windows of PM_2.5, while respiratory mortality was more highly associated with shorter exposure time windows of PM_2.5. Although the reasons for these differential associations remain unclear, potential explanations might lie in the different underlying biological mechanisms. The respiratory system encounters direct and immediate exposure to ambient PM_2.5, where inhaled particulates can trigger tissue damage, inflammation, and oxidative stress in the respiratory tract. On the other hand, the effects of PM_2.5 on the circulatory system are likely more indirect. For example, inflammatory mediators like cytokines, generated in the respiratory tract due to PM_2.5 exposure, can infiltrate the circulatory system and instigate distant pathophysiological changes potentially leading to pronounced cardiovascular disease (30,31,32,33). Previous studies examining the lag structure of the association between short-term exposure to PM₁₀ and mortality in South Korea reported that respiratory mortality was more affected by immediate exposure (e.g., same day), whereas effects on cardiovascular mortality were associated with more lagged and prolonged exposure (34, 35).

Regarding effect modification by community-level characteristics, we found higher effect of PM_2.5 on mortality in more deprived community, although the differences in effect estimates were statistically insignificant overall. Individual- or community-level SES, which are commonly measured by education or income, have been reported as important modifiers on the PM-mortality relationship both in short-term and long-term effects (7,8,9, 14, 15). In this study, we used the deprivation index as a more comprehensive measure of community-level SES, encapsulating multiple dimensions of deprivation, including income, education, marital status, and housing conditions. The indicators for this index were sourced from previous study by Choi et al., 2019, chosen specifically to represent local economic and social deprivation within the South Korean context. In light of this, our finding indicating elevated PM_2.5-related mortality in more deprived communities may be understood as reflecting systemic deprivation in these areas, rather than merely individual health conditions or behaviors tied to individual SES. For instance, deprived communities could face structural disadvantages such as limited access to healthcare services, inadequate infrastructure, and substandard housing conditions, which could enhance their susceptibility to the health effects of PM_2.5. Further, deprived communities may also have limited access to resources for adapting or responding to air pollution, such as air purifiers, air-conditioned spaces, and health information. Conversely, it’s possible that more deprived areas are less impacted by PM_2.5 compared to less deprived areas. For instance, areas with higher levels of deprivation might be more rural, potentially leading to lower population density and fewer sources of anthropogenic air pollution. This could result in different levels or chemical composition of PM_2.5 in these regions.

Insufficient healthcare accessibility has often been posited as a potential pathway through which low SES may modify the PM_2.5-mortality relationship, but empirical investigations into this premise have been scarce. Our study showed that communities with limited medical resources were more vulnerable to the health effects of long-term PM_2.5 exposure. Such regions may have a lower capacity to manage chronic health conditions that are exacerbated by long-term PM_2.5 exposure or a lack of timely and appropriate medical care, exacerbating the impacts of PM_2.5 on mortality. Indeed, studies have suggested an increased mortality risk associated with greater distances to hospitals (36, 37). Additionally, these communities might have limited access to preventive health measures, such as health education and screening programs, which can mitigate the harmful effects of PM_2.5 exposure. However, our findings also indicated a heightened effect of PM_2.5 on cause-specific mortalities in areas with more medical resources, although the differences were not statistically significant. One possible explanation is that areas with more medical resources could have more advanced disease detection and reporting systems, potentially resulting in a higher number of documented mortality cases associated with PM_2.5 exposure. Furthermore, areas with more medical resources might serve a population with a higher proportion of vulnerable individuals, such as the elderly or those with pre-existing health conditions, who might be seeking enhanced healthcare services. This population might be more susceptible to the effects of PM_2.5.

Modifying effects of green spaces on the relationship between PM_2.5 and mortality outcomes exhibited contrasting patterns for circulatory and respiratory causes in this study. We observed that communities with higher green space had a lower risk of circulatory mortality in association with PM_2.5, but conversely, a higher risk of respiratory mortality. Akin to these findings, a study conducted in seven major cities in South Korea found higher cardiovascular mortality associated with PM₁₀ in communities with a lower level of greenness, while the risk of PM₁₀ on non-accidental mortality was higher in greener communities (38). Several previous studies have suggested the beneficial effect of greenness in mitigating the health risk of PM exposure by fostering more opportunities for physical activity, enhancing social interactions, and reducing psychological stress levels (39,40,41). However, green space can also potentially have adverse effects on health under certain conditions. The release of allergenic pollens during peak blooming times can trigger allergies and aggravate respiratory issues. The use of pesticides in maintaining these areas may result in direct exposure or contaminate the environment. Furthermore, green spaces can emit biogenic volatile organic compounds that contribute to the formation of ground-level ozone and secondary organic aerosols, potentially worsening air quality and respiratory health. Additionally, dense vegetation can sometimes harbor vectors of diseases, such as ticks and mosquitoes, leading to an increased risk of vector-borne diseases in greener areas (42, 43). The influence of greenness on the association between PM_2.5 and mortality could be attributed to a combination of these potential mechanisms, warranting further research to untangle their intricate interactions.

Our measures for community-level characteristics come with some limitations. First, we measured indicators for the deprivation index every five years, restricting our ability to capture temporal variations in community-level SES. In addition, we could not include employment status indicators due to the data availability. These shortcomings are unlikely to significantly impacted our results because the deprivation index did not show considerable variations over time and incorporated multiple dimensions of SES that are likely to correlate closely with employment. Second, while the medical index used in our study provides a general overview of the medical resources available within a given district, it might not accurately reflect the actual healthcare accessibility experienced by the residents. It incorporates the quantity of medical personnel, hospitals, and hospital beds per capita, but it does not take into account the distribution of these resources within the districts or the potential barriers that may hinder access to these resources, such as transportation difficulties, costs, or the quality of care provided. Third, NDVI as a measure of vegetation does not reflect the different types of vegetation that could impact health differently. For example, dense forests might have different health effects compared to grasslands or urban parks. NDVI might not adequately represent pollen concentrations and their potential health impacts, as it does not account for variations in flowering times and pollen release across different types of vegetation. Furthermore, NDVI does not account for the accessibility of green spaces or their quality, both of which are important aspects of greenness that can affect health outcomes. In this study, we examined the modifying effect of each community-level characteristic independently, rather than in conjunction. Community-level variables do not account for activity patterns of study participants that would affect exposure, such as sub-community heterogeneity or movement from the community of residence to different communities for work or school. In addition. In real-world contexts, various community-level factors, including those not considered in our study, could interact with each other and consequently influence the associations between PM_2.5 and mortality. Although the correlations among the community-level factors investigated in our study were relatively weak, these factors could still exert combined effects. Thus, future research is called for, to more comprehensively understand health disparities associated with PM_2.5 exposure for various communities.

This study also has potential exposure measurement errors. We used district-level PM_2.5 concentrations since individual-level exposure measurements or individual residential addresses were not available. While we used exposure estimates for PM_2.5 from a validated model, which brings the strength of higher spatial resolution than would exposures based on air pollution monitors, these exposures are estimates there are inherent uncertainties. Our estimates are based on ambient air pollution, which do not incorporate differences in exposure patterns due to indoor air pollution, indoor/outdoor activity patterns, or occupational exposures. The modeled ambient PM_2.5 concentrations are also subject to errors arising from uncertainties in the input variables. Specifically, observed air pollution data are constrained by the coverage and density of the existing monitoring network, potentially not fully representing all areas. However, the prediction model for PM_2.5 showed excellent performance (cross-validated R²: 0.87), providing national coverage across South Korea (19). We also took into account the change in subjects’ residential locations throughout the follow-up period when assigning PM_2.5 concentrations, which further reduces potential exposure misclassification.

Lastly, while the NHIS-NSC dataset offers a large and representative sample of the South Korean population through the universal insurance coverage system and systematic stratified random sampling, not all participants could be included in our analysis. Specifically, 204,213 participants were excluded due to missing information on covariates such as smoking status and BMI (Figure S1). The characteristics of this excluded group may differ from those of the study population, introducing the possibility of selection bias. Despite these limitations, this is the first cohort study to examine the mortality effects of long-term exposure to PM_2.5 using the nationwide sample of South Korea, to the best of our knowledge. We also demonstrated the unequal effects of PM_2.5 by community-level characteristics. Our findings suggest the necessity for policy strategies to extend beyond simple mitigation of PM_2.5 levels and encompass local socio-environmental contexts. This integrated approach can help mitigate the health impacts of air pollution more effectively, promoting health equity among different communities.