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International Journal of Health Geographics

, 13:31

First Online: 15 August 2014Received: 31 May 2014Accepted: 11 August 2014DOI: 10.1186-1476-072X-13-31

Cite this article as: Um, SB., Kim, N.H., Lee, H.K. et al. Int J Health Geogr 2014 13: 31. doi:10.1186-1476-072X-13-31

Abstract

BackgroundDED rate maps from diverse regions may allow us to understand world-wide spreading pattern of the disease. Only few studies compared the prevalence of DED between geographical regions in non-spatial context. Therefore, we examined the spatial epidemiological pattern of DED prevalence in South Korea using a nationally representative sample.

MethodsWe analyzed 16,431 Korean adults aged 30 years or older of the 5th Korea National Health and Nutrition Examination Survey. DED was defined as previously diagnosed by an ophthalmologist as well as symptoms experienced. Multiple logistic regression analysis was used to assess the spatial pattern in the prevalence of DED, and effects of environmental factors.

ResultsAmong seven metropolitan cities and nine provinces, three metropolitan cities located in the southeast of Korea revealed the highest prevalence of DED. After adjusting for sex, age and survey year, people living in urban areas had higher risk of having DED. Adjusted odds ratio for having previously diagnosed DED was 1.677 95% CI 1.299-2.166 for metropolitan cities and 1.580 95% CI 1.215-2.055 for other cities compared to rural areas. Corresponding odds ratio for presenting DED symptoms was 1.388 95% CI 1.090-1.766 for metropolitan cities and 1.271 95% CI 0.999-1.617 for other cities. Lower humidity and longer sunshine duration were significantly associated with DED. Among air pollutants, SO2 was associated with DED, while NO2, O3, CO, and PM10 were not.

ConclusionOur findings suggest that prevalence of DED can be affected by the degree of urbanization and environmental factors such as humidity and sunshine duration.

KeywordsAir pollutants Dry eye disease Meteorological factors Prevalence Spatial epidemiology AbbreviationsCIConfidence interval

DEDDry eye disease

KCDCKorea center for disease control and prevention

KNHANESKorea national health and nutrition examination survey

OROdds ratio

SDStandard deviation.

Electronic supplementary materialThe online version of this article doi:10.1186-1476-072X-13-31 contains supplementary material, which is available to authorized users.

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Autor: Sun-Bi Um - Na Hyun Kim - Hyung Keun Lee - Jong Suk Song - Hyeon Chang Kim

Fuente: https://link.springer.com/







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