ArticleInternational journal of environmental research and public health2025
A Geospatial Analysis of the Lung Cancer Burden in Philadelphia, Using Pennsylvania Cancer Registry Data from 2008-2017.
Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Geospatial Analysis of Accredited Lung Cancer Screening Facilities in Florida Reveals Suboptimal Alignment with High-Risk Populations.Cancer research communications · 2026Article
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7 authors.
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Abstract
(1) Background: Lung cancer is the deadliest and second most prevalent cancer in Pennsylvania (PA), and African American patients are disproportionately affected. Lung cancer morbidity and mortality in Philadelphia County are among the highest in PA. Geographic information systems (GIS) are useful to explore geospatial variations in the cancer burden and risk factors. Therefore, we used GIS to analyze the lung cancer burden in Philadelphia to assess which areas of the city have the highest morbidity and mortality, identify potential clusters, and determine which census tract-level characteristics were associated with higher tract-level cancer burden. (2) Methods: Using secondary data from the Pennsylvania Cancer Registry, age-adjusted standardized incidence and mortality ratios (SIR and SMR) were calculated by census tract, and choropleth maps were created to visualize geographic variations in the disease burden. Two geostatistical methods were used to determine the presence of lung cancer clusters. Multivariable regression analyses were performed to identify which census-tract level characteristics correlated with a higher lung cancer burden. (3) Results: Three distinct geographical lung cancer clusters were identified. After controlling for demographics and other covariates, adult smoking prevalence, prevalence of chronic obstructive pulmonary disease, and percentage of residential addresses vacant were positively associated with higher lung cancer SIR and SMR. (4) Conclusions: Our findings may inform cancer control efforts within the region and guide future municipal-level GIS analyses of the lung cancer burden.
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