Basavegowda Madhu1, Kenkere Marulaiah Srinath2, Vidyalakshmi Rajendran3, Marimuthu Prashanthi Devi4, Nagaralu Channabasappa Ashok5, Somanathan Balasubramanian6. 1. Associate Professor, Department of Community Medicine, JSS University , Mysuru, Karnataka, India . 2. Associate Professor, Department of Medicine, JSS Medical College and Hospital, JSS University , Mysuru, Karnataka, India . 3. Research Scholar, Department of Environmental Management, Bharathidasan University , Trichy, Tamil Nadu, India . 4. Assistant Professor, Department of Environmental Management, Bharathidasan University , Trichy, Tamil Nadu, India . 5. Professor, Department of Community Medicine, JSS University , Mysuru, Karnataka, India . 6. Dean, Faculty of Life Sciences and Director Research, JSS University , Mysuru, Karnataka, India .
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.
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.
Entities:
Keywords:
Health geographic information system (Health-GIS); Population at Risk; Risk areas; Spatial analysis; Spatio-temporal trends; Thematic mapping
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