TY - JOUR
T1 - Spatial epidemiology of dry eye disease
T2 - Findings from South Korea
AU - Um, Sun Bi
AU - Kim, Na H.
AU - Lee, Hyung K.
AU - Song, Jong S.
AU - Kim, Hyeon C.
N1 - Funding Information:
Thanks are extended to the different national agencies of South Korea (Korea Centers for Disease Control and Prevention and the National Climate Data Service System) for providing their data for this manuscript. The authors gratefully acknowledge the support by a grant from the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HI13C0055).
Publisher Copyright:
© 2014 Um et al.; licensee BioMed Central Ltd.
PY - 2014/8/15
Y1 - 2014/8/15
N2 - Background: DED 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.Methods: We 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.Results: Among 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.Conclusion: Our findings suggest that prevalence of DED can be affected by the degree of urbanization and environmental factors such as humidity and sunshine duration.
AB - Background: DED 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.Methods: We 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.Results: Among 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.Conclusion: Our findings suggest that prevalence of DED can be affected by the degree of urbanization and environmental factors such as humidity and sunshine duration.
KW - Air pollutants
KW - Dry eye disease
KW - Meteorological factors
KW - Prevalence
KW - Spatial epidemiology
UR - http://www.scopus.com/inward/record.url?scp=84910059316&partnerID=8YFLogxK
U2 - 10.1186/1476-072X-13-31
DO - 10.1186/1476-072X-13-31
M3 - Article
C2 - 25128034
AN - SCOPUS:84910059316
SN - 1476-072X
VL - 13
JO - International Journal of Health Geographics
JF - International Journal of Health Geographics
IS - 1
M1 - 31
ER -
