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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 &lt; 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.

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