Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore

被引:0
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作者
Chinnaswamy, Anitha K. [1 ]
Balisane, Hewa [2 ]
Nguyen, Quynh T. [2 ,3 ]
Naguib, Raouf N.G. [2 ,3 ]
Trodd, Nigel [4 ]
Marshall, Ian M. [1 ]
Yaacob, Norlaily [1 ]
Santos, Gil Nonato [5 ]
Vallar, Edgar A. [5 ]
Galvez, Maria Cecilia D. [5 ]
Shaker, Mohyi H. [6 ]
Wickramasinghe, Nilmini [7 ]
Ton, Tuan Nghia [8 ]
机构
[1] Faculty of Engineering and Computing, Coventry University, United Kingdom
[2] Faculty of Science, Soran University, Kurdistan Regional Government, Iraq
[3] BIOCORE Research and Consultancy International, United Kingdom
[4] Faculty of Business, Environment and Society, Coventry University, United Kingdom
[5] Physics Department, De La Salle University, Philippines
[6] Ecology and Environment, Inc., United States
[7] Epworth HealthCare Deakin University, Australia
[8] Environmental Health Unit, World Health Organization Representative Office, Viet Nam
关键词
Air pollution - Cardiology - Geographic information systems - Diseases - Information use;
D O I
10.1504/IJIQ.2015.071690
中图分类号
学科分类号
摘要
Cardiovascular disease (CVD) is the world's number one cause of mortality. Research in recent years has begun to illustrate a significant association between CVD and air pollution. As most of these studies employed traditional statistics, cross-sectional or meta-analysis methods, a study undertaken by the authors was designed to investigate how a geographical information system (GIS) could be used to develop a more efficient spatio-temporal method of analysis than the currently existing methods mainly based on statistical inference. Using Bangalore, India, as a case study, demographic, environmental and CVD mortality data was sought from the city. However, critical deficiencies in the quality of the environmental data and mortality records were identified and quantified. This paper discusses the shortcomings in the quality of mortality data, together with the development of a framework based on WHO guidelines to improve the defects, henceforth considerably improving data quality. Copyright © 2015 Inderscience Enterprises Ltd.
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页码:64 / 81
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