Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore
by Anitha K. Chinnaswamy; Hewa Balisane; Quynh T. Nguyen; Raouf N.G. Naguib; Nigel Trodd; Ian M. Marshall; Norlaily Yaacob; Gil Nonato Santos; Edgar A. Vallar; Maria Cecilia D. Galvez; Mohyi H. Shaker; Nilmini Wickramasinghe; Tuan Nghia Ton
International Journal of Information Quality (IJIQ), Vol. 4, No. 1, 2015

Abstract: 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.

Online publication date: Mon, 14-Sep-2015

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