Abstract ▼

In this study, we updated existing 27 Environmental Health Indicators (EHIs) in 5 areas, from published national and international statistics. By evaluating the results, we compared environmental health status at local and national scales and developed a plan to establish an environmental health mon

In this study, we updated existing 27 Environmental Health Indicators (EHIs) in 5 areas, from published national and international statistics. By evaluating the results, we compared environmental health status at local and national scales and developed a plan to establish an environmental health monitoring system using national big or large data, national health information DB, causes of death data, meteorological data and environmental monitoring data.

Compared to environmental health status with EU from 2001 to 2015, passenger transport in Korea was 1.6 times higher than in the average EU country and energy consumption per area in transportation was also 2.7 times higher than in EU. Emissions of air pollutants per area in Korea were 3 times higher, and population-weighted PM₁₀ was 2 time higher than that in EU.

For Seoul and Ulsan, emissions of air pollutants per area was 1.5 times higher in Seoul than in Ulsan in 2015. Although the population-weighted PM₁₀ levels in two areas were similar in 2015, Seoul saw a 25% drop from 2007 to 2015 while Ulsan experienced a 13% decrease in the same period. And the percentage of the population who live in the areas where the PM₁₀ levels exceed the air quality standard was 5.1% and 35% in Seoul and Ulsan, respectively.

We updated the integrated environmental health database (IEHD) with related data, and calculated the medical care utilization and admission rates for the eight diseases subject to environmental health monitoring with focusing on geographical characteristics, spatial distribution, time trend, etc. The IEHD was useful to complement existing methodologies and to monitor environmental health status.

We investigated to detect spatially significant admission care clusters of asthma, chronic obstructive pulmonary disease(COPD), circulatory disease and stroke by municipal unit (e.g. si, gun, gu). With spatial analysis, it is possible to visualize the regions of cluster using QGIS and compare the relative risk ratios by disease.

For further studies, it is required to ensure consistency of the IEHD and expand the collection of public database for environment-related diseases, and assess their environmental health effects. Furthermore, appropriate analytical methodologies need to be developed in order to clarify and prevent environmental risks.

As a results, the development and utilization of the EHIs will enable the assessment of environmental health status at local and national scales. In addition, it is expected to contribute to developing environmental health policies by identifying vulnerable sectors to environmental risks.

(출처 : Abstract 10p)

목차 Contents

• 표지 ... 1
• 목차 ... 5
• 표목차 ... 7
• 그림목차 ... 8
• Abstract ... 10
• I. 서 론 ... 13
• II. 연구내용 및 방법 ... 15
• 1. 연구내용 ... 15
• 2. 연구방법 ... 15
• III. 연구결과 및 고찰 ... 16
• 1. 환경보건 정보 산출 및 관리체계 구축 ... 16
• 가. 환경보건지표의 선정 및 산출 ... 16
• 나. 환경보건지표를 통합한 국가/지역 간 환경보건수준 분석 ... 19
• 다. 국가/공공기관 비공식 발표 자료 또는 가공자료의 활용타당성 검토 ... 24
• 2. 환경보건지표의 정책적 활용방안 검토 ... 25
• 가. EU 등 비교가능한 지표의 확인·분석 및 지표 활용을 위한 국내·외 연구동향 분석 ... 25
• 나. 환경정책 이행과 효과 분석을 위한 환경보건지표 평가 및 개선방안 검토 ... 26
• 3. 환경보건모니터링 체계에서 빅데이터 활용을 위한 기반 마련 ... 28
• 가. 환경보건통합 database 구축 ... 28
• 나. 환경보건모니터링 질환의 의료이용률 산출 ... 32
• 다. GIS 기반 의료이용 공간분석 ... 44
• IV. 결 론 ... 48
• 참 고 문 헌 ... 49
• Fact Sheet -환경보건지표 산출결과- ... 51
• 끝페이지 ... 164