Geographic and racial disparities in breast cancer-related outcomes in Georgia.
Ontology highlight
ABSTRACT: Objective
To measure the effects of race/ethnicity, area measures of socioeconomic status (SES) and geographic residency status, and health care supply (HCS) characteristics on breast cancer (BC)-related outcomes.Data sources/study setting
Female patients in Georgia diagnosed with BC in the years 2000-2009.Study design
Multilevel regression analysis with adjustment for variables at the county, census tract (CT), and individual level. The county represents the spatial unit of analysis for HCS. SES and geographic residency status were grouped at the CT level.Principal findings
Even after controlling for area-level characteristics, racial and ethnic minority women suffered an unequal BC burden. Despite inferior outcomes for disease stage and receipt of treatment, Hispanics had a marginally significant decreased risk of death compared with non-Hispanics. Higher CT poverty was associated with worse BC-related outcomes. Residing in small, isolated rural areas increased the odds of receiving surgery, decreased the odds of receiving radiotherapy, and decreased the risk of death. A higher per-capita availability of BC care physicians was significantly associated with decreased risk of death.Conclusions
Race/ethnicity and area-level measures of SES, geographic residency status, and HCS contribute to disparities in BC-related outcomes.
SUBMITTER: Markossian TW
PROVIDER: S-EPMC3976183 | biostudies-literature | 2014 Apr
REPOSITORIES: biostudies-literature
Publications
Geographic and racial disparities in breast cancer-related outcomes in Georgia.
Markossian Talar W TW Hines Robin B RB Bayakly Rana R
Health services research 20130801 2
<h4>Objective</h4>To measure the effects of race/ethnicity, area measures of socioeconomic status (SES) and geographic residency status, and health care supply (HCS) characteristics on breast cancer (BC)-related outcomes.<h4>Data sources/study setting</h4>Female patients in Georgia diagnosed with BC in the years 2000-2009.<h4>Study design</h4>Multilevel regression analysis with adjustment for variables at the county, census tract (CT), and individual level. The county represents the spatial unit ...[more]
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