{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T05:04:55Z","timestamp":1790831095814,"version":"4.1.0"},"reference-count":63,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010731","name":"Faculty of Medicine, Chiang Mai University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010731","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Seasonal haze pollution in Thailand exposes populations to recurrent fine particulate matter (PM\u2082.\u2085), yet its health impacts are unequally distributed, reflecting disparities in education, social vulnerability, and protective capacity. This study examined the associations of educational attainment, sociodemographic, lifestyle, protective behaviors, and environmental factors with acute health symptoms during the haze season.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A nationwide cross-sectional study was conducted between January and April 2025 among 3,916 adults across Thailand. Data were collected through standardized interviews assessing sociodemographic characteristics, protective behaviors, and acute health symptoms. Provincial PM\u2082.\u2085 concentrations were obtained from satellite-based monitoring data. Latent class analysis was used to identify protective behavioral phenotypes, and mixed-effects multivariable logistic regression models were applied to evaluate determinants of health symptoms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Mean monthly PM\u2082.\u2085 concentrations exceeded international guideline values throughout the study period. Respiratory symptoms were the most prevalent (80.7%), followed by eye (52.8%), dermatological (48.7%), and neurological symptoms (33.1%). Three behavioral phenotypes were identified: compliers (33.4%), non-compliers (48.6%), and a neutral group (18.0%). Higher PM\u2082.\u2085 exposure was independently associated with increased odds of respiratory and dermatological symptoms. Compared with compliers, non-compliers and neutral participants had significantly higher odds of respiratory and neurological symptoms. Female sex, younger age, comorbidity, alcohol consumption, urban or suburban residence, and lack of village health volunteer engagement were also associated with elevated symptom risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Higher ambient PM\u2082.\u2085 exposure, non-compliant protective behavioral phenotypes were associated with increased odds of acute health symptoms, highlighting persistent social inequalities in vulnerability to haze pollution. Equity-oriented public health strategies that strengthen community health resources, promote protective behaviors, and address educational disparities may help reduce unequal vulnerability to air pollution.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1899785","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:50:22Z","timestamp":1790830222000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Health inequalities in PM\u2082.\u2085-related symptoms during Thailand\u2019s haze season: the role of education, sociodemographic, lifestyle, protective behaviors, and environmental factors"],"prefix":"10.3389","volume":"14","author":[{"given":"Nalin","family":"Sittitoon","sequence":"first","affiliation":[{"name":"School of Environmental Health, Institute of Public Health, Suranaree University of Technology","place":["Nakhon Ratchasima, Thailand"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wuttipat","family":"Kiratipaisarl","sequence":"additional","affiliation":[{"name":"Department of Community Medicine, Faculty of Medicine, Chiang Mai University","place":["Chiang Mai, Thailand"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ratana","family":"Sapbamrer","sequence":"additional","affiliation":[{"name":"Department of Community Medicine, Faculty of Medicine, Chiang Mai University","place":["Chiang Mai, Thailand"]},{"name":"Environmental and Occupational Medicine Excellence Center (EnOMEC), Faculty of Medicine, Chiang Mai University","place":["Chiang Mai, Thailand"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"120613","DOI":"10.1016\/j.atmosenv.2024.120613","article-title":"Understanding the seasonal dynamics of surface PM\u2082.\u2085 mass 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