College of Public Health, University of South Florida, Tampa, USA.
Cancer Causes Control. 2022 Sep;33(9):1155-1160. doi: 10.1007/s10552-022-01607-5. Epub 2022 Jul 23.
Examining spatial distribution of colorectal cancer (CRC) incidence or mortality is helpful for developing cancer control and prevention programs or for generating hypotheses. Such an investigation involves describing the spatial variation of risk factors for CRC and identifying hotspots. The aim of this study is to identify county-level risk factors that may be associated with the incidence of CRC and to map hotspots for CRC in Florida.
County-level CRC cases, recorded in 2018, were obtained from the Florida Department of Health, Division of Public Health Statistics & Performance Management (DPHSM). Data on county-level risk factors were also obtained from the same source. We used Bayesian spatial models for relative incidence rates and produced posterior predictive that indicates excess risk (hotspots) for CRC.
The county-level unadjusted incidence rates range from .462 to 3.142. After fitting a Bayesian spatial model to the data, the results show that a decreasing risk of CRC is strongly associated with an increasing median income, higher percentage of Black population, and higher percentage of sedentary life at county level. Using exceedance probability, it is also observed that there are clustering and hotspots of high CRC incidence rates in Charlotte County in South Florida, Hernando, Sumter and Seminole counties in central Florida and Union and Washington counties in north Florida.
Among few county-level variables that significantly explained the spatial variation of CRC, income disparity may need more attention for resource allocation and developing preventive intervention in high-risk areas for CRC.
研究结直肠癌(CRC)发病率或死亡率的空间分布有助于制定癌症防控计划或提出假设。这种研究包括描述 CRC 的危险因素的空间变化,并确定热点。本研究的目的是确定与 CRC 发病率相关的县级危险因素,并绘制佛罗里达州 CRC 的热点图。
从佛罗里达州卫生署公共卫生统计与绩效管理部(DPHSM)获得 2018 年记录的县级 CRC 病例。还从同一来源获得了县级危险因素数据。我们使用贝叶斯空间模型来计算相对发病率,并生成表示 CRC 超额风险(热点)的后验预测值。
县级未经调整的发病率范围从 0.462 到 3.142。在对数据进行贝叶斯空间模型拟合后,结果表明 CRC 风险降低与县级中位数收入增加、黑人群体比例增加和久坐生活方式比例增加强烈相关。使用超出概率,还观察到南佛罗里达州夏洛特县、中佛罗里达州 Hernando、Sumter 和 Seminole 县以及北佛罗里达州 Union 和 Washington 县的 CRC 发病率存在聚类和热点。
在几个显著解释 CRC 空间变异的县级变量中,收入差距可能需要更多关注,以便在高风险地区为 CRC 分配资源和制定预防干预措施。