Cargando…
The spatial distribution of health vulnerability to heat waves in Guangdong Province, China
BACKGROUND: International literature has illustrated that the health impacts of heat waves vary according to differences in the spatial variability of high temperatures and the social and economic characteristics of populations and communities. However, to date there have been few studies that quant...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Co-Action Publishing
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212080/ https://www.ncbi.nlm.nih.gov/pubmed/25361724 http://dx.doi.org/10.3402/gha.v7.25051 |
_version_ | 1782341645791920128 |
---|---|
author | Zhu, Qi Liu, Tao Lin, Hualiang Xiao, Jianpeng Luo, Yuan Zeng, Weilin Zeng, Siqing Wei, Yao Chu, Cordia Baum, Scott Du, Yaodong Ma, Wenjun |
author_facet | Zhu, Qi Liu, Tao Lin, Hualiang Xiao, Jianpeng Luo, Yuan Zeng, Weilin Zeng, Siqing Wei, Yao Chu, Cordia Baum, Scott Du, Yaodong Ma, Wenjun |
author_sort | Zhu, Qi |
collection | PubMed |
description | BACKGROUND: International literature has illustrated that the health impacts of heat waves vary according to differences in the spatial variability of high temperatures and the social and economic characteristics of populations and communities. However, to date there have been few studies that quantitatively assess the health vulnerability to heat waves in China. OBJECTIVES: To assess the spatial distribution of health vulnerability to heat waves in Guangdong Province, China. METHODS: A vulnerability framework including dimensions of exposure, sensitivity, and adaptive capacity was employed. The last two dimensions were called social vulnerability. An indicator pool was proposed with reference to relevant literatures, local context provided by relevant local stakeholder experts, and data availability. An analytic hierarchy process (AHP) and a principal component analysis were used to determine the weight of indicators. A multiplicative vulnerability index (VI) was constructed for each district/county of Guangdong province, China. RESULTS: A total of 13 items (two for exposure, six for sensitivity, and five for adaptive capacity) were proposed to assess vulnerability. The results of an AHP revealed that the average VI in Guangdong Province was 0.26 with the highest in the Lianzhou and Liannan counties of Qingyuan (VI=0.50) and the lowest in the Yantian district of Shenzhen (VI=0.08). Vulnerability was gradiently distributed with higher levels in northern inland regions and lower levels in southern coastal regions. In the principal component analysis, three components were isolated from the 11 social vulnerability indicators. The estimated vulnerability had a similar distribution pattern with that estimated by AHP (Intraclass correlation coefficient (ICC)=0.98, p<0.01). CONCLUSIONS: Health vulnerability to heat waves in Guangdong Province had a distinct spatial distribution, with higher levels in northern inland regions than that in the southern coastal regions. |
format | Online Article Text |
id | pubmed-4212080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Co-Action Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-42120802014-11-17 The spatial distribution of health vulnerability to heat waves in Guangdong Province, China Zhu, Qi Liu, Tao Lin, Hualiang Xiao, Jianpeng Luo, Yuan Zeng, Weilin Zeng, Siqing Wei, Yao Chu, Cordia Baum, Scott Du, Yaodong Ma, Wenjun Glob Health Action Original Article BACKGROUND: International literature has illustrated that the health impacts of heat waves vary according to differences in the spatial variability of high temperatures and the social and economic characteristics of populations and communities. However, to date there have been few studies that quantitatively assess the health vulnerability to heat waves in China. OBJECTIVES: To assess the spatial distribution of health vulnerability to heat waves in Guangdong Province, China. METHODS: A vulnerability framework including dimensions of exposure, sensitivity, and adaptive capacity was employed. The last two dimensions were called social vulnerability. An indicator pool was proposed with reference to relevant literatures, local context provided by relevant local stakeholder experts, and data availability. An analytic hierarchy process (AHP) and a principal component analysis were used to determine the weight of indicators. A multiplicative vulnerability index (VI) was constructed for each district/county of Guangdong province, China. RESULTS: A total of 13 items (two for exposure, six for sensitivity, and five for adaptive capacity) were proposed to assess vulnerability. The results of an AHP revealed that the average VI in Guangdong Province was 0.26 with the highest in the Lianzhou and Liannan counties of Qingyuan (VI=0.50) and the lowest in the Yantian district of Shenzhen (VI=0.08). Vulnerability was gradiently distributed with higher levels in northern inland regions and lower levels in southern coastal regions. In the principal component analysis, three components were isolated from the 11 social vulnerability indicators. The estimated vulnerability had a similar distribution pattern with that estimated by AHP (Intraclass correlation coefficient (ICC)=0.98, p<0.01). CONCLUSIONS: Health vulnerability to heat waves in Guangdong Province had a distinct spatial distribution, with higher levels in northern inland regions than that in the southern coastal regions. Co-Action Publishing 2014-10-21 /pmc/articles/PMC4212080/ /pubmed/25361724 http://dx.doi.org/10.3402/gha.v7.25051 Text en © 2014 Qi Zhu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Zhu, Qi Liu, Tao Lin, Hualiang Xiao, Jianpeng Luo, Yuan Zeng, Weilin Zeng, Siqing Wei, Yao Chu, Cordia Baum, Scott Du, Yaodong Ma, Wenjun The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title | The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title_full | The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title_fullStr | The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title_full_unstemmed | The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title_short | The spatial distribution of health vulnerability to heat waves in Guangdong Province, China |
title_sort | spatial distribution of health vulnerability to heat waves in guangdong province, china |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212080/ https://www.ncbi.nlm.nih.gov/pubmed/25361724 http://dx.doi.org/10.3402/gha.v7.25051 |
work_keys_str_mv | AT zhuqi thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT liutao thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT linhualiang thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT xiaojianpeng thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT luoyuan thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT zengweilin thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT zengsiqing thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT weiyao thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT chucordia thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT baumscott thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT duyaodong thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT mawenjun thespatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT zhuqi spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT liutao spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT linhualiang spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT xiaojianpeng spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT luoyuan spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT zengweilin spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT zengsiqing spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT weiyao spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT chucordia spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT baumscott spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT duyaodong spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina AT mawenjun spatialdistributionofhealthvulnerabilitytoheatwavesinguangdongprovincechina |