Prediction Model for Dry Eye Syndrome Incidence Rate Using Air Pollutants and Meteorological Factors in South Korea: Analysis of Sub-Region Deviations

Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM(10), NO(2), SO(2), O(3), 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 incidenc...

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Detalles Bibliográficos
Autores principales: Youn, Jong-Sang, Seo, Jeong-Won, Park, Wonjun, Park, SeJoon, Jeon, Ki-Joon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399894/
https://www.ncbi.nlm.nih.gov/pubmed/32664192
http://dx.doi.org/10.3390/ijerph17144969
Descripción
Sumario:Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM(10), NO(2), SO(2), O(3), 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 (R(2) = 0.9443 and 0.9388, p < 2.2 × 10(−16)). 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 NO(2) and relative humidity are the factors impacting regional deviations in the prediction model.

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