McIntire Russell K, Senter Katherine, Shusted Christine, Yearwood Rickisa, Barta Julie, Keith Scott W, Zeigler-Johnson Charnita
College of Health, Lehigh University, Bethlehem, PA 18015, USA.
College of Population Health, Thomas Jefferson University, Philadelphia, PA 19107, USA.
Int J Environ Res Public Health. 2025 Mar 20;22(3):455. doi: 10.3390/ijerph22030455.
(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.
(1) 背景:肺癌是宾夕法尼亚州(PA)最致命且第二常见的癌症,非裔美国患者受其影响的比例过高。费城县的肺癌发病率和死亡率在宾夕法尼亚州位居前列。地理信息系统(GIS)有助于探索癌症负担和风险因素的地理空间差异。因此,我们使用GIS分析费城的肺癌负担,以评估该市哪些区域的发病率和死亡率最高,识别潜在的聚集区,并确定哪些普查区层面的特征与更高的普查区层面癌症负担相关。(2) 方法:利用宾夕法尼亚癌症登记处的二手数据,按普查区计算年龄调整后的标准化发病率和死亡率(SIR和SMR),并创建分级统计图以直观显示疾病负担的地理差异。使用两种地理统计方法来确定肺癌聚集区的存在。进行多变量回归分析以确定哪些普查区层面的特征与更高的肺癌负担相关。(3) 结果:识别出三个不同的地理肺癌聚集区。在控制人口统计学和其他协变量后,成人吸烟率、慢性阻塞性肺疾病患病率和住宅空置率与更高的肺癌SIR和SMR呈正相关。(4) 结论:我们的研究结果可为该地区的癌症控制工作提供信息,并指导未来市级层面关于肺癌负担的GIS分析。