Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore
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 undert...
Saved in:
Main Authors: | , , , , , , , , , , , , |
---|---|
Format: | text |
Published: |
Animo Repository
2015
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1532 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2531/type/native/viewcontent |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
id |
oai:animorepository.dlsu.edu.ph:faculty_research-2531 |
---|---|
record_format |
eprints |
spelling |
oai:animorepository.dlsu.edu.ph:faculty_research-25312022-05-11T02:45:28Z Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore Chinnaswamy, Anitha K. Balisane, Hewa Nguyen, Quynh T. Naguib, Raouf N. G. Trodd, Nigel Marshall, Ian M. Yaacob, Norlaily Santos, Gil Nonato C. Vallar, Edgar A. Galvez, Maria Cecilia D. Shaker, Mohyi H. Wickramasinghe, Nilmini Ton, Tuan Nghia 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. 2015-01-01T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1532 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2531/type/native/viewcontent Faculty Research Work Animo Repository Cardiovascular system—Diseases—Mortality--India Cardiovascular system—Diseases—Mortality—Geographic information systems--India Cardiovascular Diseases |
institution |
De La Salle University |
building |
De La Salle University Library |
continent |
Asia |
country |
Philippines Philippines |
content_provider |
De La Salle University Library |
collection |
DLSU Institutional Repository |
topic |
Cardiovascular system—Diseases—Mortality--India Cardiovascular system—Diseases—Mortality—Geographic information systems--India Cardiovascular Diseases |
spellingShingle |
Cardiovascular system—Diseases—Mortality--India Cardiovascular system—Diseases—Mortality—Geographic information systems--India Cardiovascular Diseases Chinnaswamy, Anitha K. Balisane, Hewa Nguyen, Quynh T. Naguib, Raouf N. G. Trodd, Nigel Marshall, Ian M. Yaacob, Norlaily Santos, Gil Nonato C. Vallar, Edgar A. Galvez, Maria Cecilia D. Shaker, Mohyi H. Wickramasinghe, Nilmini Ton, Tuan Nghia Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
description |
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. |
format |
text |
author |
Chinnaswamy, Anitha K. Balisane, Hewa Nguyen, Quynh T. Naguib, Raouf N. G. Trodd, Nigel Marshall, Ian M. Yaacob, Norlaily Santos, Gil Nonato C. Vallar, Edgar A. Galvez, Maria Cecilia D. Shaker, Mohyi H. Wickramasinghe, Nilmini Ton, Tuan Nghia |
author_facet |
Chinnaswamy, Anitha K. Balisane, Hewa Nguyen, Quynh T. Naguib, Raouf N. G. Trodd, Nigel Marshall, Ian M. Yaacob, Norlaily Santos, Gil Nonato C. Vallar, Edgar A. Galvez, Maria Cecilia D. Shaker, Mohyi H. Wickramasinghe, Nilmini Ton, Tuan Nghia |
author_sort |
Chinnaswamy, Anitha K. |
title |
Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
title_short |
Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
title_full |
Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
title_fullStr |
Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
title_full_unstemmed |
Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore |
title_sort |
data quality issues in the gis modelling of air pollution and cardiovascular mortality in bangalore |
publisher |
Animo Repository |
publishDate |
2015 |
url |
https://animorepository.dlsu.edu.ph/faculty_research/1532 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2531/type/native/viewcontent |
_version_ |
1733052802035351552 |