Evaluation of age-standardized cancer burden in western Tamil Nadu, India

Background: The burden of cancer is growing globally and is one of the top leading causes of death. Information on cancer patterns is essential for effective planning of cancer control interventions. Aims and Objectives: The present cross sectional study aims to explore the patterns and trends of the cancer incidences in the western regions of Tamil Nadu, India including Coimbatore, Erode, Tiruppur, Salem, Namakkal and Nilgiris. Materials and Methods: A sum of 14392 cancer cases were recorded from the hospital based cancer registries of Coimbatore district. The cancer cases were segregated district-wise for specific cancer sites and the age-standardized incident rates were calculated for different age groups. Results: Coimbatore district recorded the highest number of incidences among all districts. Among all age-groups the adults aged 50-74 carry the highest burden of cancer. Among men, head and neck and gastrointestinal cancers are predominant while among women, breast and gynecological cancers are high. The age-standardized incidence rates were found to be higher in Coimbatore and least in Salem. Conclusion: Through this study, it is observed that Coimbatore district is under major threat and needs further investigation of risk factors for implementing optimized treatment and prevention strategies for reducing the adverse effects of cancer

Evaluation of age-standardized cancer burden in western Tamil Nadu, India

Background: The burden of cancer is growing globally and is one of the top leading causes of death. Information on cancer patterns is essential for effective planning of cancer control interventions. Aims and Objectives: The present cross sectional study aims to explore the patterns and trends of the cancer incidences in the western regions of Tamil Nadu, India including Coimbatore, Erode, Tiruppur, Salem, Namakkal and Nilgiris. Materials and Methods: A sum of 14392 cancer cases were recorded from the hospital based cancer registries of Coimbatore district. The cancer cases were segregated district-wise for specific cancer sites and the age-standardized incident rates were calculated for different age groups. Results: Coimbatore district recorded the highest number of incidences among all districts. Among all age-groups the adults aged 50-74 carry the highest burden of cancer. Among men, head and neck and gastrointestinal cancers are predominant while among women, breast and gynecological cancers are high. The age-standardized incidence rates were found to be higher in Coimbatore and least in Salem. Conclusion: Through this study, it is observed that Coimbatore district is under major threat and needs further investigation of risk factors for implementing optimized treatment and prevention strategies for reducing the adverse effects of cancer

Probability mapping to determine the spatial risk pattern of acute gastroenteritis in Coimbatore District, India, using Geographic Information Systems (GIS)

Background: Maps show well the spatial configuration of information. Considerable effort is devoted to the development of geographical information systems (GIS) that increase understanding of public health problems and in particular to collaborate efforts among clinicians, epidemiologists, ecologists, and geographers to map and forecast disease risk. Objectives: Small populations tend to give rise to the most extreme disease rates, even if the actual rates are similar across the areas. Such situations will follow the decision-maker′s attention on these areas when they scrutinize the map for decision making or resource allocation. As an alternative, maps can be prepared using P-values (probabilistic values). Materials and Methods: The statistical significance of rates rather than the rates themselves are used to map the results. The incidence rates calculated for each village from 2000 to 2009 is used to estimate λ, the expected number of cases in the study area. The obtained results are mapped using Arc GIS 10.0. Results: The likelihood of infections from low to high is depicted in the map and it is observed that five villages namely, Odanthurai, Coimbatore Corporation, Ikkaraiboluvampatti, Puliakulam, and Pollachi Corporation are more likely to have significantly high incidences. Conclusion: In the probability map, some of the areas with exceptionally high or low rates disappear. These are typically small unpopulated areas, whose rates are unstable due to the small numbers problem. The probability map shows more specific regions of relative risks and expected outcomes