ABSTRACT
INTRODUCTION: Spatio-ecological study of disease provides a framework to study the interaction of genetic, environmental, social, cultural and behavioural factors on people's health. The occurrence and interaction of these factors are different in different places, giving rise to distinct geographic or spatial variation. Diseases like breast cancer have variation both spatially and temporally. Public health practitioners can use Geographic Information System (GIS) as a visualization tool to effectively present geographic phenomenon and depict it in maps that might remain otherwise undiscovered in tabular form. AIM: To demonstrate how GIS can be used to understand and communicate breast cancer data through spatial visualization techniques. OBJECTIVES: (i) To visualize the Spatial Distribution of Breast cancer incidences by a point map. (ii) To visualize the Temporal distribution of breast cancer incidences by thematic maps for the study period of 2007 -2011. MATERIALS AND METHODS: Total 1090 breast cancer case records collected for the year 2007-2012 were segregated taluk wise for the 29 taluks and geocoded using the address of the patient, creating a point map. ArcGIS 10.2 software was used to prepare thematic map of breast cancer cases. The taluk wise aggregated breast cancer incidence from the year 2007 to 2011 was then attributed into polygon map representing taluks (Base Map). Natural break data classification technique was used to classify the breast cancer incidence data and breast cancer incidences were classified as low, moderate, high and very high. RESULTS: Spatial distribution of breast cancer incidences using thematic mapping methods high incidences were reported in MY_ T24 (Hunsur), MY_ T25 (KR Nagar), MY_27 (Nanjangud), CH_T1 (Chamrajnagar) and CH-T2 (Gundlupet). Temporal maps prepared for the study from 2007 to 2011 showed that Mysore Taluk had very high Incidence level and the same was observed throughout the study period. The taluks which have high and moderate intensities seem to be fluctuating. However, 25 taluks do not fall into very high category during the study period. Taluks such Gundlupet (CH_T2), K R Nagar (MY_T25), Kollegal (CH_T3) have been observed to enter high intensity category during the year 2011 from moderate intensity. It is also observed that Nanjangud (MY_T27) is in high intensity category throughout the study period which might be due to its proximity to Mysore urban. CONCLUSION: Analysis of Breast Cancer in southern Karnataka using GIS has revealed that urban areas of Mysore has the highest risk of breast cancer and the temporal trends reveal that even rural areas with moderate risk are moving towards high risk areas.
ABSTRACT
BACKGROUND: Metabolic syndrome is a cluster of clinical and metabolic abnormalities. In diabetics, other components of metabolic syndrome are an added risk factor for cardiovascular disease and all these cause mortality. Epidemiological transition is happening all over the world and tribes are not spared either. Identifying the extent of metabolic syndrome and its components in diabetics is vital for the prevention of cardiovascular diseases and other morbidities. OBJECTIVE: To estimate the prevalence of Metabolic Syndrome among diabetics and pre-diabetics of Jenu Kuruba tribe and compare the mean values of various components of metabolic syndrome among diabetics and pre-diabetics. METHODS: A community based cross sectional study was carried out among 7500 Jenu Kuruba tribal population in two phases. In phase I, total of 7500 subjects were screened for diabetes and hypertension and in phase II, a total of 249 diabetics and 310 pre-diabetics were identified and evaluated for metabolic syndrome. RESULTS: Prevalence of metabolic syndrome was estimated using NCEP ATP-III criteria. Metabolic syndrome was found in 84 (33.7%) of diabetics and 113 (36.4%) of pre-diabetic study subjects. Metabolic syndrome was highest in the 41-50 year age group. Lipid parameters such as total cholesterol, triglycerides and VLDL were significantly higher and HDL levels were significantly lower among subjects with metabolic syndrome as compared to subjects without metabolic syndrome. CONCLUSIONS: One third of diabetics and pre-diabetics had definable metabolic syndrome. Dyslipidemia is a significant component of metabolic syndrome. Epidemiological transitions are happening among Jenu Kuruba tribes and non-communicable diseases are on the raise among them.
