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Development of a Conjunctivitis Outpatient Rate Prediction Model Incorporating Ambient Ozone and Meteorological Factors in South Korea
Ozone (O(3)) is a commonly known air pollutant that causes adverse health effects. This study developed a multi-level prediction model for conjunctivitis in outpatients due to exposure to O(3) by using 3 years of ambient O(3) data, meteorological data, and hospital data in Seoul, South Korea. We con...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189411/ https://www.ncbi.nlm.nih.gov/pubmed/30356707 http://dx.doi.org/10.3389/fphar.2018.01135 |
Sumario: | Ozone (O(3)) is a commonly known air pollutant that causes adverse health effects. This study developed a multi-level prediction model for conjunctivitis in outpatients due to exposure to O(3) by using 3 years of ambient O(3) data, meteorological data, and hospital data in Seoul, South Korea. We confirmed that the rate of conjunctivitis in outpatients (conjunctivitis outpatient rate) was highly correlated with O(3) (R(2) = 0.49), temperature (R(2) = 0.72), and relative humidity (R(2) = 0.29). A multi-level regression model for the conjunctivitis outpatient rate was well-developed, on the basis of sex and age, by adding statistical factors. This model will contribute to the prediction of conjunctivitis outpatient rate for each sex and age, using O(3) and meteorological data. |
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