AbstractThis study attempts to answer the research question ‘Can a novel model of health information system strengthen process for conducting research to understand the effects of air pollution on
CVD in developing countries?
There is limited research output from Asia and in particular, from India on studies of the deleterious effects of air pollution on CVD. This research aimed to investigate the barriers in developing countries and proposed the use of a spatiotemporal methodology to assess the effects of air pollution on CVD by developing an application based on a GIS platform. Choosing Bangalore as a case study area, secondary data from various governmental departments that included demographic data, air pollution data and mortality data were obtained.
An Environmental Health Information system application based on GIS platform was developed specifically for Bangalore and with the characteristics of the datasets available. Data quality assessment was carried out on these datasets that resulted in the recommendation of a generalisable data quality framework to enable better data collection that will aid in strengthening health development policies. The data was analysed using spatial and non-spatial techniques. Results showed that levels of PM10 were of concern to the city with all areas having either high or critical levels of pollution. CVD deaths also were of concern contributing to almost 40% of total mortality. The potential years of life lost (PYLL), which is an estimate of the average years a person would have lived if he or she had not died prematurely was calculated for the years from 2010 to 2013; this revealed that 2.1 million person years were lost in Bangalore due to CVD alone. These potential years lost is an important factor to consider, as preventive measures taken by the Government will result in a significant economic impact on the city.
The limitations of few monitoring stations were overcome by using spatial interpolation techniques such as Inverse Distance Weighted interpolation technique. The performance of the interpolation was tested using cross-validation techniques and the results revealed that Bangalore city would benefit from increased measuring stations for PM10. The logistic regression conducted showed that pollution especially PM10 was a likely predictor of CVD in the city.
Spatial analysis was conducted and included buffering, overlay maps, queries and Hotspot analysis highlighting the zone hotspots.
The results from the research guided the development of the novel 5-I model that would assist other similar developing cities to assess the effects of air pollution on CVD. The impetus is that
based on evidence, intervention policies and programs may be implemented to inform research and practice which will ultimately have social, economic and health impact on the population.
On implementation of the model, hotspots will be identified in order to roll out interventions to priority areas and populations most at risk that will ultimately prevent millions of deaths and
enhance overall quality of life.
|Date of Award||2015|
|Supervisor||Ian Marshall (Supervisor)|