Overview of Korean Community Health Survey

In 2008, the Korean Centers for Disease Control and Prevention (KCDC) initiated Korean Community Health Survey (KCHS), the first nationwide survey to provide data that could be used to plan, implement, monitor and evaluate community health promotion and disease prevention program. This community-based cross-sectional survey has been conducted by 253 community health centers, 36 community universities and 1,500 interviewers. The KCHS standardized questionnaire is developed jointly by KCDC staff, a working group of health indicators standardization subcommittee and 16 metropolitan cities and provinces with 253 regional sites. The KCHS was administered by trained interviewers and the quality control of KCHS was improved by introduction of computer-assisted personal interview in 2010. The questionnaire was reviewed annually so that revised and/or new questions could be added based on public health policy. The additional questions included the fixed and rotating cores, emerging issues and optional modules. The standardized questionnaire of KCHS covered a wide variety of health topics, which could be used to assess the prevalence of personal health behaviors related to causes of disease. The KCHS data allows that the differences of health issues among provinces can be directly compared. Furthermore, the provinces can use these data for their own cost-effective health interventions to improve health promotion and disease prevention.

Assessment of Applicability of Standardized Rates for Health State Comparison Among Areas: 2008 Community Health Survey / 예방의학회지

OBJECTIVES: This study shows the issues that should be considered when applying standardized rates using Community Health Survey(CHS) data. METHODS: We analyzed 2008 CHS data. In order to obtain the reliability of standardized rates, we calculated z-score and rank correlation coefficients between direct standardized rate and indirect standardized rate for 31 major indices. Especially, we assessed the change of correlations according to population composition (age and sex), and characteristics of the index. We used Mantel-Haenszel chi-square to quantify the difference of population composition. RESULTS: Among 31 major indices, 29 indices' z-score and rank correlation coefficients were over 0.9. However, regions with larger differences in population composition showed lower reliability. Low reliability was also observed for the indices specific to subgroups with small denominator such as 'permanent lesion from stroke', and the index with large regional variations in age-related differences such as 'obtaining health examinations'. CONCLUSIONS: Standardized rates may have low reliability, if comparison is made between areas with extremely large differences in population composition, or for indicies with large regional variations in age-related differences. Therefore, the special features of standardized rates should be considered when health state are compared among areas.