환경보건지표를 이용한 지역 환경보건수준 평가 사례연구
A Case Study on the Evaluation of Environmental Health Status based on Environmental Health Indicators
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초록
Objectives: This study was conducted to assess environmental health status on a local scale using environmentalhealth-related indicators. It demonstrated the possibility of using a structural equation model, a methodologicalapproach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Eachenvironmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) andobtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing theoriginal information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishingenvironmental health policies and a decision-making process. However, the availability and quality of indicators,assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should beexamined in future studies.
Abstract
Objectives: This study was conducted to assess environmental health status on a local scale using environmentalhealth-related indicators. It demonstrated the possibility of using a structural equation model, a methodologicalapproach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Eachenvironmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) andobtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing theoriginal information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishingenvironmental health policies and a decision-making process. However, the availability and quality of indicators,assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should beexamined in future studies.
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