ArticleBMC cancer2021
Geospatial analysis, web-based mapping and determinants of prostate cancer incidence in Georgia counties: evidence from the 2012-2016 SEER data.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 18 citations in OpenAlex.
- The Geography of Cancer: Regional Disparities in the Incidence of Prostate Cancer in Puerto Rico, 2016-2022.Journal of racial and ethnic health disparities · 2026Article
- Spatial variability in the association of ambient PMEnvironment international · 2026Article
- Bayesian spatio-temporal modeling and prediction of malaria cases in Tanzania mainland (2016-2023): unveiling associations with climate and intervention factors.International journal of health geographics · 2025Article
- Bayesian spatiotemporal modelling and mapping of malaria risk among children under five years of age in Ghana.BMC infectious diseases · 2025Article
- Geographical variability in cancer incidence explained by the socioeconomic environment: an example of lung cancer in northwestern France.Journal of epidemiology and community health · 2025Article
- Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016-2021.Malaria journal · 2024Article
- Bayesian Disease Mapping to Identify High-Risk Population for Oral Cancer: A Retrospective Spatiotemporal Analysis.International journal of dentistry · 2023Article
- Article
- Health Burdens and SES in Alabama: Using Geographic Information System to Examine Prostate Cancer Health Disparity.Cancers · 2022Article
- Spatio-temporal variations in neonatal mortality rates in Ghana: An application of hierarchical Bayesian methods.PLOS global public health · 2022Article
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Authors and funding
3 authors at 2 institutions in 3 countries.
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Abstract
backgroundProstate cancer (CaP) cases are high in the United States. According to the American Cancer Society, there are an estimated number of 174,650 CaP new cases in 2019. The estimated number of deaths from CaP in 2019 is 31,620, making CaP the second leading cause of cancer deaths among American men with lung cancer been the first. Our goal is to estimate and map prostate cancer relative risk, with the ultimate goal of identifying counties at higher risk where interventions and further research can be targeted.
methodsThe 2012-2016 Surveillance, Epidemiology, and End Results (SEER) Program data was used in this study. Analyses were conducted on 159 Georgia counties. The outcome variable is incident prostate cancer. We employed a Bayesian geospatial model to investigate both measured and unmeasured spatial risk factors for prostate cancer. We visualised the risk of prostate cancer by mapping the predicted relative risk and exceedance probabilities. We finally developed interactive web-based maps to guide optimal policy formulation and intervention strategies.
resultsNumber of persons above age 65 years and below poverty, higher median family income, number of foreign born and unemployed were risk factors independently associated with prostate cancer risk in the non-spatial model. Except for the number of foreign born, all these risk factors were also significant in the spatial model with the same direction of effects. Substantial geographical variations in prostate cancer incidence were found in the study. The predicted mean relative risk was 1.20 with a range of 0.53 to 2.92. Individuals residing in Towns, Clay, Union, Putnam, Quitman, and Greene counties were at increased risk of prostate cancer incidence while those residing in Chattahoochee were at the lowest risk of prostate cancer incidence.
conclusionOur results can be used as an effective tool in the identification of counties that require targeted interventions and further research by program managers and policy makers as part of an overall strategy in reducing the prostate cancer burden in Georgia State and the United States as a whole.
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