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Adverse effects of meteorological factors and air pollutants on dry eye disease: a hospital-based retrospective cohort study.
Choi, Yun-Hee; Song, Myung-Sun; Lee, Yunjin; Paik, Hae Jung; Song, Jong Suk; Choi, Yoon-Hyeong; Kim, Dong Hyun.
Afiliación
  • Choi YH; Department of Ophthalmology, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
  • Song MS; School of Health and Environmental Science, Korea University, Seoul, South Korea.
  • Lee Y; Department of Ophthalmology, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
  • Paik HJ; Department of Ophthalmology, Gachon University College of Medicine, Gil Medical Center, Incheon, South Korea.
  • Song JS; Department of Ophthalmology, Gachon University College of Medicine, Gil Medical Center, Incheon, South Korea.
  • Choi YH; Department of Ophthalmology, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
  • Kim DH; School of Health and Environmental Science, Korea University, Seoul, South Korea. yoonchoi@korea.ac.kr.
Sci Rep ; 14(1): 17776, 2024 08 01.
Article en En | MEDLINE | ID: mdl-39090167
ABSTRACT
Although previous studies have suggested that meteorological factors and air pollutants can cause dry eye disease (DED), few clinical cohort studies have determined the individual and combined effects of these factors on DED. We investigated the effects of meteorological factors (humidity and temperature) and air pollutants [particles with a diameter ≤ 2.5 µ m (PM2.5), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO)] on DED. A retrospective cohort study was conducted on 53 DED patients. DED was evaluated by Symptom Assessment in Dry Eye (SANDE), tear secretion, tear film break-up time (TBUT), ocular staining score (OSS), and tear osmolarity. To explore the individual, non-linear, and joint associations between meteorological factors, air pollutants, and DED parameters, we used generalized linear mixed model (GLMM) and Bayesian kernel machine regression (BKMR). After adjusting for all covariates, lower relative humidity or temperature was associated with a higher SANDE (p < 0.05). Higher PM2.5, O3, and NO2 levels were associated with higher SANDE and tear osmolarity (p < 0.05). Higher O3 levels were associated with lower tear secretion and TBUT, whereas higher NO2 levels were associated with higher OSS (p < 0.05). BKMR analyses indicated that a mixture of meteorological factors and air pollutants was significantly associated with increased SANDE, OSS, tear osmolarity, and decreased tear secretion.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Síndromes de Ojo Seco / Contaminantes Atmosféricos Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Síndromes de Ojo Seco / Contaminantes Atmosféricos Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Reino Unido