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자료유형
학술저널
저자정보
기지선 (서울대학교) 김호 (서울대학교)
저널정보
한국역학회 Epidemiology and Health Epidemiology and Health Vol.41
발행연도
2019.1
수록면
1 - 10 (10page)

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OBJECTIVES: In South Korea, there are two nationwide health surveys conducted by the Korea Centers for Disease Control and Prevention: the Korea Community Health Survey (KCHS) and Korea National Health and Nutrition Examination Survey (KNHANES). The two surveys are directly comparable, as they have the same target population with some common items, and because both surveys are used in various analyses, identifying the similarities and disparities between the two surveys would promote their appropriate use. Therefore, this study aimed to compare the estimates of six variables in KCHS and eight variables in KNHANES over a six-year period and compare time series stability of region-specific and sex- and age-specific subgroup estimates. METHODS: Data from adults aged 19 years or older in the 2010-2015 KCHS and KNHANES were examined to analyze the differences of estimates and 95% confidence interval for self-rated health, current smoking rate, monthly drinking rate, hypertension diagnosis rate, diabetes diagnosis rate, obesity prevalence, hypertension prevalence, and diabetes prevalence. The variables were then clustered into subgroups by city as well as sex and age to assess the time series stability of the estimates based on mean square error. RESULTS: With the exception of self-rated health, the estimates taken based on questionnaires, namely current smoking rate, monthly drinking rate, hypertension diagnosis rate, and diabetes diagnosis rate, only differed by less than 1.0%p for both KCHS and KNHANES. However, for KNHANES, estimates taken from physical examination data, namely obesity prevalence, hypertension prevalence, and diabetes prevalence, differed by 1.9-8.4%p, which was greater than the gap in the estimates taken from questionnaires. KCHS had a greater time series stability for subgroup estimates than KNHANES. CONCLUSIONS: When using the data from KCHS and KNHANES, the data should be selected and used based on the purpose of analysis and policy and in consideration of the various differences between the two data.

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