ArticlePloS one2019
An ecological approach to monitor geographic disparities in cancer outcomes.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Opportunities, challenges, and future directions for simulation modeling the effects of structural racism on cancer mortality in the United States: a scoping review.Journal of the National Cancer Institute. Monographs · 2023Article
- The Use of Area-Level Socioeconomic Indices in Evaluating Cancer Care Delivery: A Scoping Review.Annals of surgical oncology · 2023Article
- A retrospective cohort study of cutaneous squamous cell carcinoma of the scalp: features of disease and influence of sociodemographic factors on outcomes.Irish journal of medical science · 2022Article
- A new proactive virtual resource center navigation model identifies patient risk factors to reduce barriers to cancer care during the COVID-19 pandemic.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundArea-level indices are widely used to assess the impact of socio-environmental characteristics on cancer outcomes. While area-level measures of socioeconomic status (SES) have been previously used in cancer settings, fewer studies have focused on evaluating the impact of area-level health services supply (HSS) characteristics on cancer outcomes. Moreover, there is significant variation in the methods and constructs used to create area-level indices.
methodsIn this study, we introduced a psychometrically-induced, reproducible approach to develop area-level HSS and SES indices. We assessed the utility of these indices in detecting the effects of area-level characteristics on prostate, breast, and lung cancer incidence and stage at diagnosis in the US. The information on county-level SES and HSS characteristics were extracted from US Census, County Business Patterns data and Area Health Resource Files. The Surveillance, Epidemiology, and End Results database was used to identify individuals diagnosed with cancer from 2010 to 2012. SES and HSS indices were developed and linked to 3-year age-adjusted cancer incidence rates. SES and HSS indices empirically summarized the level of employment, education, poverty and income, and the availability of health care facilities and health professionals within counties.
resultsSES and HSS models demonstrated good fit (TLI = 0.98 and 0.96, respectively) and internal consistency (alpha = 0.85 and 0.95, respectively). Increasing SES and HSS were associated with increasing prostate and breast cancer and decreasing lung cancer incidence rates. The results varied by stage at diagnosis and race.
conclusionComposite county-level measures of SES and HSS were effective in ranking counties and detecting gradients in cancer incidence and stage at diagnosis. Thus, these measures provide valuable tools for monitoring geographic disparities in cancer outcomes.
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