Comparing the geographic distribution and location characteristics of HIV-seropositive and HIV-seronegative individuals with a diagnosis of cancer living in the southeast US. (February 2018)

• Record Type: Journal Article
• Authors: Hallowell, Benjamin D.; Robb, Sara W.; Kintziger, Kristina W.
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 24(2018)
• Page Start: 11
• Page End: 18
• Publication Date: 2018-02
• Subjects: HIV -- Cancer -- Nadms -- Spatial analysis; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2017.10.002
• Languages: English
• ISSNs: 1877-5845

Abstract

Highlights: Examines the geographic distribution and location characteristics of cancer patients by HIV status in South Carolina, USA. Identified social determinates that can be used to identify areas with elevated HIV-seropositive cancer burden. These findings and methods can be used to better inform prevention, treatment, and research methods. HIV-seropositive individuals, regardless of geographic location, are at increased risk of developing cancer. Abstract: As HIV-seropositive individuals live longer, they are more likely to acquire conditions seen in the general population. Excluding AIDS-defining malignancies, HIV-seropositive individuals are more likely to develop cancer than individuals in the general population. In order to better inform future screening and prevention efforts in this population, we compared the geographic distribution and location characteristics of HIV-seropositive and HIV-seronegative cancer cases in South Carolina (SC). To do this we obtained linked HIV and cancer data from the SC enhanced HIV/AIDS Reporting System and Central Cancer Registry. Location-related information on SC residents (e.g., employment status, income levels, race of householder, and educational attainment) was obtained from the 2000 US Census. Hotspot analyses were used to analyze the geographic distribution of HIV-seropositive and HIV-seronegative cancer cases using the Getis-Ord Gi* statistic. Poisson regression analyses assessed if county demographic and geographic characteristics were associated with HIV-positive cancer case rates.