Spatio-Temporal Pattern of Breast Cancer - Case Study of Southern Karnataka, India

Madhu, B; M., Srinath K.; Rajendran, Vidyalakshmi; Devi, M. Prashanthi; Ashok, N C; Balasubramanian, Somanathan

doi:10.7860/jcdr/2016/19042.7666

Cited by 8 publications

(11 citation statements)

References 4 publications

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“…Similar results were interpreted in an article showed an urban agglomeration in Mysore regions of Karnataka. [ 9 ] The present study is affirmative to incidence at high-density regions with symmetric increase in high-elevation regions on the contrary to a study by George and Mathew[ 11 ] where there is an increment in breast cancer incidence in coastal regions with low elevation and high population density. The choropleth representation showed a male predominance near town areas, whereas equal predominance is featured at a proximity to the forest zones.…”

Section: Discussionsupporting

confidence: 73%

“…[ 4 ] The present study concluded a relative risk of 0.058% of breast cancer incidence is also conclusive in other constructive spatial analysis studies. [ 9 10 11 ]…”

Section: Discussionmentioning

confidence: 99%

“…The competitive capability of spatial visualization technique presumes and predicts various association of geographic components and endemicity, apparently not possible with other traditional statistical analysis packages. [ 9 10 11 ] This calls for a spatial dataset that facilitates geospatial risk analysis to exemplify the environment risk on health.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal risk-analysis of cancer endemicity in Sulthan Bathery Taluk of Wayanad District of Kerala-A geo-informatics approach

Gory

Sinha

Saha

et al. 2018

Indian J Community Med

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Section: Discussionsupporting

confidence: 73%

“…[ 4 ] The present study concluded a relative risk of 0.058% of breast cancer incidence is also conclusive in other constructive spatial analysis studies. [ 9 10 11 ]…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal risk-analysis of cancer endemicity in Sulthan Bathery Taluk of Wayanad District of Kerala-A geo-informatics approach

Gory

Sinha

Saha

et al. 2018

Indian J Community Med

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“…Procedural advancement in mapping technologies can easily be interlinked to the physical and social phenomenon of public health and the pattern of disease, its spread and intensity in a particular area and scale of time. 11 Our present study aimed to assess the hot spot areas in Mysore district with smear positive pulmonary tuberculosis patients by implementing Arc GIS 10.2 software. This study showed that distribution of smear positive pulmonary tuberculosis cases was highest in urban areas and less in rural areas when compared to urban areas.…”

Section: Resultsmentioning

confidence: 99%

Assessment of tuberculosis spatial hotspot areas among smear positive pulmonary tuberculosis patients attending JSS: a tertiary health care centre from Mysore district, South India

Manthravadi

Anantharaj

Badveti

2019

Int J Community Med Public Health

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Background: Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. In 2017, TB caused an estimated 1.3 million deaths (range, 1.2–1.4 million) among HIV-negative people, and there were an additional 300 000 deaths from TB (range, 266 000–335 000) among HIV-positive people. The current TB program reports are often compiled and reported at higher administrative units and there is limited information about the spatial distribution of the disease. Hence, we aimed to assess the spatial distribution and hot spot areas of the disease among the patients attending a tertiary care centre in Mysore over a period of 3 years.Methods: This is a taluk based study, the spatial analysis and hot spot area identification was done by collecting the demographic data from the smear positive pulmonary tuberculosis patients attending JSS a tertiary care centre from Mysore district. Hot spot areas and areas with TB transmission are identified and estimated using GIS software tool. Distribution of TB incidence was mapped with the population density from 2016-2018.Results: Spatial mapping of smear positive tuberculosis revealed that majority of cases were recorded from Mysore city followed by T. N. Pura and Hunsur taluk regions.Conclusions: This study emphasized on finding hot spot areas and local clusters involved in TB transmission.

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“…Information on geographical patterns and temporal disease trends for different regional scales are important for the design, implementation and evaluation of CA control programs [ 13 ]. Can help to identify new hypotheses of exposure that deserve future epidemiological investigations and the with the development of better interventions and health policies [ 14 ]…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution of breast cancer mortality: Socioeconomic disparities and access to treatment in the state of Parana, Brazil

Rocha-Brischiliari

Andrade

Nihei³

et al. 2018

PLoS ONE

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IntroductionBreast cancer remains an important public health problem that is responsible for high morbidity and mortality rates, especially in developing countries.ObjectiveTo analyze the socioeconomic and access disparities related to breast cancer mortality in 399 cities in the state of Parana, Brazil.MethodsEcological, descriptive and analytical cross-sectional study based on secondary data from the Mortality Information System from 2009 to 2012 in the state of Parana. Breast cancer mortality rate was calculated considering the mortality cases and women population of each municipality, both based on women older than 20 years old. Moran global and local analyses were used to verify the presence of spatial autocorrelation and spatial regression modeling (Spatial Lag—SAR) with the purpose of analyzing the association between socioeconomic indicators, access and mortality rates for breast cancer.ResultsSignificant positive spatial autocorrelation was found for breast cancer mortality rates (I = 0.5432, p = 0.001). In the spatial regression analysis, the model explained 61% of the variance of the mortality rates for breast cancer. The mortality rate for breast cancer was negatively associated with the illiteracy rate (Coefficient = -0.0279) and positively associated with the access index (Coefficient = 12.9525).ConclusionThe lower illiteracy rate has not been sufficient to reduce the specific mortality rate by breast cancer, and the higher the score of accessibility to cancer services, the higher the specific mortality due to breast cancer. The results show that in the state of Parana, the problem is not related to a lack of education of the patients or the distance walked, but rather with the organization of services. These conclusions have important political implications on the organization and quality of the services provided for the diagnosis and treatment of breast cancer in the state of Parana.

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Spatio-Temporal Pattern of Breast Cancer - Case Study of Southern Karnataka, India

Cited by 8 publications

References 4 publications

Spatio-Temporal risk-analysis of cancer endemicity in Sulthan Bathery Taluk of Wayanad District of Kerala-A geo-informatics approach

Spatio-Temporal risk-analysis of cancer endemicity in Sulthan Bathery Taluk of Wayanad District of Kerala-A geo-informatics approach

Assessment of tuberculosis spatial hotspot areas among smear positive pulmonary tuberculosis patients attending JSS: a tertiary health care centre from Mysore district, South India

Spatial distribution of breast cancer mortality: Socioeconomic disparities and access to treatment in the state of Parana, Brazil

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