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

Youn, Jong-Sang; Seo, Jeong-Won; Park, Wonjun; Park, SeJoon; Jeon, Ki-Joon

doi:10.3390/ijerph17144969

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

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Department of Environmental Engineering, Inha University, Incheon 22212, Korea

Department of Ophthalmology, Hallym University, Dongtan Sacred Heart Hospital, Hwaseong-si 18450, Korea

School of Industrial Management Engineering, Korea University, Seoul 02841, Korea

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Division of Energy Resources Engineering and Industrial Engineering, Kangwon National University, Chuncheon-si 24341, Korea

Authors to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2020, 17(14), 4969; https://doi.org/10.3390/ijerph17144969

Received: 4 June 2020 / Revised: 22 June 2020 / Accepted: 2 July 2020 / Published: 10 July 2020

(This article belongs to the Special Issue Advances in the Field of Human Health and Environment)

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Abstract

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 < 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 NO₂ and relative humidity are the factors impacting regional deviations in the prediction model. View Full-Text

Keywords: dry eye syndrome; air pollutants; meteorological factors; prediction model; regional deviation

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Youn, J.-S.; Seo, J.-W.; Park, W.; Park, S.; Jeon, K.-J. Prediction Model for Dry Eye Syndrome Incidence Rate Using Air Pollutants and Meteorological Factors in South Korea: Analysis of Sub-Region Deviations. Int. J. Environ. Res. Public Health 2020, 17, 4969. https://doi.org/10.3390/ijerph17144969

AMA Style

Youn J-S, Seo J-W, Park W, Park S, Jeon K-J. Prediction Model for Dry Eye Syndrome Incidence Rate Using Air Pollutants and Meteorological Factors in South Korea: Analysis of Sub-Region Deviations. International Journal of Environmental Research and Public Health. 2020; 17(14):4969. https://doi.org/10.3390/ijerph17144969

Chicago/Turabian Style

Youn, Jong-Sang, Jeong-Won Seo, Wonjun Park, SeJoon Park, and Ki-Joon Jeon. 2020. "Prediction Model for Dry Eye Syndrome Incidence Rate Using Air Pollutants and Meteorological Factors in South Korea: Analysis of Sub-Region Deviations" International Journal of Environmental Research and Public Health 17, no. 14: 4969. https://doi.org/10.3390/ijerph17144969

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

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