Nationwide analysis of demographic and socioeconomic inequities in air pollution exposure in Korea, 2006–2019

BACKGROUND: Air pollution is a significant global health challenge, yet few studies have examined how the effects of exposure to environmental pollutants vary across demographic and socioeconomic groups. This study aims to investigate the distribution of air pollutants by demographics and socioeconomic status (SES), accounting for individual monthly residential mobility. METHODS: Individual annual exposures were estimated by linking monthly residential addresses to air pollutant concentrations modeled using the Community Multiscale Air Quality system. Particulate matter (≤ 10 μm, PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) from 2006 to 2019 were linked to demographic and SES indicators from the Korean National Health Insurance Service for approximately 50 million individuals annually. Exposure disparities across socioeconomic groups were assessed using ANOVA, eta-squared statistics, and generalized estimating equations. RESULTS: From 2006 to 2019, overall exposures to PM₁₀ and NO₂ declined, whereas O₃ levels increased. PM₁₀ (50.18 µg/m³) and NO₂ (25.01 ppb) concentrations were highest in adults aged 30–34 years, decreasing with age to 47.42 µg/m³ and 22.06 ppb among those aged ≥ 65 years. Conversely, O₃ exposure was lowest in the 25–29-year age group (37.58 ppb) and increased to 39.38 ppb in those aged ≥ 65 years. Eligible individuals (medical aid recipients) had the lowest exposures to PM₁₀ (45.15 µg/m³) and NO₂ (20.12 ppb) but the highest O₃ exposure (40.30 ppb). In the insured populations, self-employed individuals showed higher PM₁₀ and NO₂ exposures compared to employee-insured individuals. Higher SES groups were more likely to be in the highest tertile for PM₁₀ and NO₂ exposure (40.5% of highest-SES self-employed vs. 28.9% of lowest-SES in the high NO₂ tertile), while lower SES groups showed higher O₃ exposure. Spatially, PM₁₀ and NO₂ levels were higher in urban areas, whereas O₃ levels were elevated in rural areas. CONCLUSION: SES and demographics intersect to create distinct, pollutant-specific exposure patterns in Korea, contrasting with Western countries where lower-SES groups typically experience higher pollution exposure. By accounting for individual residential mobility, this study provides improved exposure estimates and highlights the importance of considering socioeconomic context in evaluating pollution-related health effects and developing targeted environmental policies.