다중 영향 및 환경정의를 고려한 지역 환경보건수준 평가 사례연구
A Case Study on the Evaluation of Environmental Health Status Focused on Multiple Impact and Environmental Justice
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Objectives: Based on the concept of environmental justice, we developed an evaluation model for setting and adopting the direction of environmental health policy using environmental health indicators and statistics from the local governments of Seoul, including environmentally susceptible populations. Methods: We selected a total of 20 variables based on data officially released from national and local governments. After the classification of these variables into the five components of environmental pressure, environmental status, environmental disease, sensitive population, and socioeconomic status, a basic model was constructed to calculate the relative scores of the local governments. Results: The cumulative impact scores for assessment of environmental health status were similar to those of the environmental pressure and status components. The highest five cumulative impact scores fell between 114 and 147. Local government A reported the highest scores and had high environmental pressure, environmental status and socioeconomic status. In addition, the evaluation of the other four local governments indicated that they exhibited above average scores for environmental pressure and environmental status, two did so for environmental disease, and four for sensitive population. Conclusion: We constructed a model to evaluate the environmental health status of the local governments of Seoul based on cumulative impact scores under the concept of environmental justice. As an approach for studying environmentally vulnerable areas through relative ranking, this model was feasible for policy-setting. In addition, this approach would be an analytically useful tool for decision-makers.
Abstract
Objectives: Based on the concept of environmental justice, we developed an evaluation model for setting and adopting the direction of environmental health policy using environmental health indicators and statistics from the local governments of Seoul, including environmentally susceptible populations. Methods: We selected a total of 20 variables based on data officially released from national and local governments. After the classification of these variables into the five components of environmental pressure, environmental status, environmental disease, sensitive population, and socioeconomic status, a basic model was constructed to calculate the relative scores of the local governments. Results: The cumulative impact scores for assessment of environmental health status were similar to those of the environmental pressure and status components. The highest five cumulative impact scores fell between 114 and 147. Local government A reported the highest scores and had high environmental pressure, environmental status and socioeconomic status. In addition, the evaluation of the other four local governments indicated that they exhibited above average scores for environmental pressure and environmental status, two did so for environmental disease, and four for sensitive population. Conclusion: We constructed a model to evaluate the environmental health status of the local governments of Seoul based on cumulative impact scores under the concept of environmental justice. As an approach for studying environmentally vulnerable areas through relative ranking, this model was feasible for policy-setting. In addition, this approach would be an analytically useful tool for decision-makers.
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