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Spatial Autocorrelation of Breast and Prostate Cancer in Slovakia

Cancer is one of the dominant causes of death in the Slovak population. Monitoring the course of the cancer death rate in Slovakia can be considered as a relevant subject for geographical research. Relatively little is known about the geographic distribution of breast and prostate cancer incidence i...

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Detalles Bibliográficos
Autor principal: Vilinová, Katarína
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344400/
https://www.ncbi.nlm.nih.gov/pubmed/32575748
http://dx.doi.org/10.3390/ijerph17124440
Descripción
Sumario:Cancer is one of the dominant causes of death in the Slovak population. Monitoring the course of the cancer death rate in Slovakia can be considered as a relevant subject for geographical research. Relatively little is known about the geographic distribution of breast and prostate cancer incidence in Slovakia. In the submitted paper, it is hypothesized that breast and prostate cancer in the examined territory are characterized by different intensities, incidences, and spatial differences. The spatial patterns of breast and prostate cancer in Slovakia were examined by means of spatial autocorrelation analyses with the Local Moran’s I and Anselin Local Moran’s statistics. Data on standardized death rates of breast and prostate cancer in Slovakia between 2001 and 2018 were used. Prostate cancer in men and breast cancer in women show a positive statistically significant Global Moran’s I, whose values indicate a tendency to cluster. The Anselin Local Moran’s I analysis indicates significant clusters of breast cancer in the western part of Slovakia, and prostate cancer clusters mostly in the central part of Slovakia. The findings we have obtained in this study may help us investigate further hypotheses regarding the causes and identification of spatial differences in breast and prostate cancer incidence. Our findings might stimulate further research into the possible causes which underlie the clusters.