Evidence map›Paper›PMID 41654761›Full record

ArticleBMC public health2026

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

So Yeon Kim, Sun Ju Nam Goung, Yoon-Hee Kang, Soontae Kim, Seoung Yeon Heo, Min Ji Koo, Jaiyong Kim, Kyoung Sook Jeong

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

So Yeon KimHealth Information & Environmental Big Data Center, Wonju Severance Christian Hospital, Yonsei University, Wonju, Republic of Korea.ORCID http://orcid.org/0009-0009-2616-4584
Sun Ju Nam GoungHealth Information & Environmental Big Data Center, Wonju Severance Christian Hospital, Yonsei University, Wonju, Republic of Korea.ORCID http://orcid.org/0009-0004-0360-5416
Yoon-Hee KangEnvironmental Institute, Ajou University, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0002-1198-934X
Soontae KimDepartment of Environmental and Safety Engineering, Ajou University, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0003-1770-0989
Seoung Yeon HeoHealth Information & Environmental Big Data Center, Wonju Severance Christian Hospital, Yonsei University, Wonju, Republic of Korea.ORCID http://orcid.org/0009-0001-1333-5630
Min Ji KooDepartment of Artificial Intelligence, National Health Insurance Service, 32, Geongang-ro, 26464, Wonju, Republic of Korea.ORCID http://orcid.org/0000-0001-5990-1354
Jaiyong Kim *Department of Big Data Management, National Health Insurance Service, 32, Geongang-ro, Wonju, 26464, Republic of Korea. dockjy2@gmail.com.ORCID http://orcid.org/0000-0003-0985-7871
Kyoung Sook Jeong *Institute of Occupational & Environmental Medicine, Yonsei University, Wonju, Republic of Korea. jeongks@yonsei.ac.kr.ORCID http://orcid.org/0000-0002-6897-8289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAir 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.

methodsIndividual 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.

resultsFrom 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.

conclusionSES 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.

Indexed as

Air PollutionEnvironmental ExposureAdolescentAdultAgedAir PollutantsChildChild, PreschoolFemaleHumansMaleMiddle AgedNitrogen DioxideOzoneParticulate MatterRepublic of KoreaAir PollutantsNitrogen DioxideOzoneParticulate MatterAir pollutantsInequalityLong-term exposureSocioeconomic status

Identifiers

PMID41654761
PMCPMC12977947

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.