Role of Geographic Information System in Assessing Determinants of Cardiovascular Disease: An Experience From a Low- and Middle-Income Country

Abstract

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the world. The determinants of CVD in an urban population using conventional and geographic information system techniques were attempted as a community-based census-type cross-sectional study in Kerala, India, among 1649 individuals residing in 452 households. Sociodemographic details, risk factor exposures, and self-reported disease prevalence were determined. Location of houses, wells from which subjects drew drinking water, and distances of the house from the outer road (proxy for air pollution) were mapped using differential global positioning system and pH of water samples determined. Prevalence of CVD was 5.8%. Significant predictors of CVD were male gender, diabetes mellitus, hypertension, and hypothyroidism. Statistically significant spatial association was found between CVD and groundwater pH. Geographic information system technology is useful in identification of spatial clustering and disease hotspots for designing preventive strategies targeting CVD.

mHealth Technology Translation in a Limited Resources Community—Process, Challenges, and Lessons Learned From a Limited Resources Community of Chiang Mai Province, Thailand

“…First, GIS technology can increase understanding of how and where health care services are accessed, leading to more targeted plans to address coverage and access issues [2] , [3] . Second, interactive maps produced using GIS techniques are useful for monitoring the live spread of diseases in the population by strengthening disease surveillance, examining disease risk factors, and planning and evaluating interventions [4] , [5] . Third, GIS can also aid the development of community profiles, giving healthcare workers knowledge of demographic, economic, healthcare, and lifestyle characteristics of the population as well as information about exposure to potential environmental hazards [2] , [6] – [8] .…”

Exploring urban health inequities: the example of non-communicable disease prevention in Indore, India

“…When these have been included, the results were not significant (Thankappan et al 2010, Rooban et al 2012). Neighborhood differences in risk were found for individual NCDs in Bhopal, India, as well as the states of Rajasthan and Kerala (Gupta et al 2018, Valamparampil et al 2018, Banerjee et al 2020.…”