Spatial analysis of chronic obstructive pulmonary disease and its risk factors in an urban area of Trivandrum, Kerala, India.

Background: Chronic obstructive pulmonary disease (COPD) is the second leading cause of death in India. The objective of this study was to map COPD cases and its risk factors and to determine the association between them using geographic information system (GIS) in a semi-urban area of Trivandrum, South India. Materials and Methods: This community-based cross-sectional, descriptive study (n = 494) was conducted in a subcenter area of a primary health center. Location was mapped and COPD population screener questionnaire was administered to all the study subjects enrolled by census method. Lifetime firewood exposure (person-hours) and tobacco smoking were enquired and distance from road was mapped using portable differential global positioning system. The association with COPD was assessed by kriging and hotspot analysis using ArcGIS software. Results: The prevalence of COPD (6.5%) was comparable to national prevalence estimates. Spatial maps showed COPD case clustering in areas with higher firewood exposure, greater smoking exposure, and in households with closer proximity to local roads. A particular high-risk cluster was obtained which had a significant association with all the risk factors. Conclusion: GIS technology is useful in identification of spatial clustering of COPD cases and its environmental risk factors, making it an important tool for targeted interventions for COPD.

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

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.