Neighborhood-Level Factors Contribute to Disparities in Hepatocellular Carcinoma Incidence in Texas,Clinical Gastroenterology and Hepatology

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Neighborhood-Level Factors Contribute to Disparities in Hepatocellular Carcinoma Incidence in Texas
Clinical Gastroenterology and Hepatology ( IF 11.6 ) Pub Date : 2022-08-04 , DOI: 10.1016/j.cgh.2022.06.031
Abiodun O Oluyomi ₁ , Hashem B El-Serag ₂ , Adegboyega Olayode ₃ , Aaron P Thrift ₄

Affiliation

Background and Aims

Texas has the highest hepatocellular carcinoma (HCC) incidence rates in the continental United States, but these rates vary by race-ethnicity. We examined racial-ethnic disparities through a geospatial analysis of the social determinants of health.

Methods

Using data from the Texas Cancer Registry, we assembled 11,547 HCC cases diagnosed between 2011 and 2015 into Texas’s census tracts geographic units. Twenty-nine neighborhood measures representing demographics and socioeconomic, and employment domains were retrieved from the U.S. Census Bureau. We performed a series of aspatial and spatially weighted regression models to identify neighborhood-level characteristics associated with HCC risk.

Results

We found positive associations between HCC and proportion of population in census tracts that are Black or African American, Hispanic, over 60 years of age, in the construction industry, and in the service occupation but an inverse association with the proportion of population employed in the agricultural industry. The magnitude of these associations varied across Texas census tracts.

Conclusions

We found evidence that neighborhood-level factors are differentially associated with variations in HCC incidence across Texas. Our findings reinforce existing knowledge about HCC risk factors and expose others, including neighborhood-level employment status.

中文翻译：

社区层面的因素导致德克萨斯州肝细胞癌发病率的差异

背景和目标

德克萨斯州的肝细胞癌 (HCC) 发病率是美国大陆最高的，但这些发病率因种族而异。我们通过对健康的社会决定因素进行地理空间分析来研究种族差异。

方法

利用德克萨斯州癌症登记处的数据，我们将 2011 年至 2015 年间诊断的 11,547 例 HCC 病例汇总到德克萨斯州人口普查区地理单元中。从美国人口普查局检索了代表人口统计、社会经济和就业领域的 29 个社区指标。我们执行了一系列空间和空间加权回归模型来识别与 HCC 风险相关的社区级特征。