{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T18:13:24Z","timestamp":1790446404011,"version":"4.1.0"},"reference-count":29,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,10]],"date-time":"2020-07-10T00:00:00Z","timestamp":1594339200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea Ministry of Environment","award":["2016001360005"],"award-info":[{"award-number":["2016001360005"]}]},{"DOI":"10.13039\/501100002507","name":"Kangwon National University","doi-asserted-by":"publisher","award":["2019 research grant"],"award-info":[{"award-number":["2019 research grant"]}],"id":[{"id":"10.13039\/501100002507","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R2 = 0.9443 and 0.9388, p &lt; 2.2 \u00d7 10\u221216). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO2 and relative humidity are the factors impacting regional deviations in the prediction model.<\/jats:p>","DOI":"10.3390\/ijerph17144969","type":"journal-article","created":{"date-parts":[[2020,7,10]],"date-time":"2020-07-10T09:25:28Z","timestamp":1594373128000},"page":"4969","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Prediction Model for Dry Eye Syndrome Incidence Rate Using Air Pollutants and Meteorological Factors in South Korea: Analysis of Sub-Region Deviations"],"prefix":"10.3390","volume":"17","author":[{"given":"Jong-Sang","family":"Youn","sequence":"first","affiliation":[{"name":"Department of Environmental Engineering, Inha University, Incheon 22212, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeong-Won","family":"Seo","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Hallym University, Dongtan Sacred Heart Hospital, Hwaseong-si 18450, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wonjun","family":"Park","sequence":"additional","affiliation":[{"name":"School of Industrial Management Engineering, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SeJoon","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Energy Resources Engineering and Industrial Engineering, Kangwon National University, Chuncheon-si 24341, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ki-Joon","family":"Jeon","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Inha University, Incheon 22212, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1162","DOI":"10.1097\/01.ico.0000244875.92879.1a","article-title":"Prevalence of dry eye in Bangkok, Thailand","volume":"25","author":"Lekhanont","year":"2006","journal-title":"Cornea"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1038\/eye.2010.67","article-title":"Impact of symptomatic dry eye on vision-related daily activities: The Singapore malay eye study","volume":"24","author":"Tong","year":"2010","journal-title":"Eye"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Le, Q., Zhou, X., Ge, L., Wu, L., Hong, J., and Xu, J. 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