Department of Environmental Engineering, Inha University, Incheon 22212, Korea.
Department of Ophthalmology, Hallym University, Dongtan Sacred Heart Hospital, Hwaseong-si 18450, Korea.
Int J Environ Res Public Health. 2020 Jul 10;17(14):4969. doi: 10.3390/ijerph17144969.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM, NO, SO, O, 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 = 0.9443 and 0.9388, < 2.2 × 10). 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 and relative humidity are the factors impacting regional deviations in the prediction model.
在这里，我们利用空气污染物（PM、NO、SO、O 和 CO）、气象因素（温度、湿度和风速）、人口率和临床数据，为韩国开发了一种干眼症综合征（DES）发病率预测模型。预测模型很好地拟合了发病率（R = 0.9443 和 0.9388，<2.2×10）。为了分析区域偏差，我们将门诊数据、空气污染物和气象因素按 16 个行政区（七个大都市区和九个州）进行分类。我们的结果证实，NO 和相对湿度是影响预测模型中区域偏差的因素。
