Abstract PO3-10-03: Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality

Abstract Title: Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality Background: Poverty is known to lead to the worst breast cancer (BC) outcomes, at the individual and county level. However, we believe that the relationship between poverty and breast cancer mortality is more complex and can be influenced by the economic status and available resources of the surrounding neighborhoods. Our goal is to understand to what extent poverty in the surrounding neighborhood may contribute to breast cancer mortality on a national scale and the county areas at the highest risk. Methods: This study examines the association between neighborhood effects of poverty on overall and BC mortality among women diagnosed between 2005 and 2019 from NCI SEER. We also obtained county-level five-year poverty estimates from the American Community Survey. Counties with poverty estimates above or below the national mean were high-poverty (H) or low-poverty (L) counties, respectively. We then used local indicators of spatial autocorrelation (LISA) analysis with Local Moran’s I of the poverty estimates and their H- and L-county categorization to define four neighborhood poverty environments for US counties. Specifically, H-counties among other H-counties were classified as poverty hotspots (HH) counties, L-counties among other L-counties were classified as poverty cold spots (LL), H-counties among LL-counties were HL-counties, and L-counties among HH-counties were LH-counties. Non-Hispanic White (NHW), Non-Hispanic Black, and Hispanic women at least 20 years of age diagnosed with local, regional, or distal stage BC between 2005-2009 and 2010-2014 that survived more than one year after diagnosis were aggregated by county of residence at diagnosis to determine their neighborhood poverty environment at BC diagnosis. Women included in the study had a Local Moran's I p-value less than or equal to 0.3 for their county of residence. A Poisson regression model that adjusts for age at diagnosis, race/ethnicity (NHW vs. not-NHW), BC stage, year of diagnosis (2005-2009 vs. 2010-2014), both local and systemic treatment except for hormone therapy, and Estrogen Receptor (ER) status (negative vs. positive) was used to assess the effects of county-level poverty cluster types on BC mortality. Results: Our analysis includes 24,070 women diagnosed with BC, of which 6,919 women died, and 2,262 of these deaths were specific to BC. In total, 4,528 women were in HH counties from CA, GA, KY, LA, NM, UT, and HI; 14,112 women were in LL counties; 4,338 women were in HL counties; 1,092 women were in LH counties. Women in HH, LH, and HL counties had a 1.28 (95%CI:1.15,1.42), 1.23 95%CI:1.01-1.48, and 1.05 CI: 0.93,1.17 relative risk of cause-specific BC death respectively when compared to deaths in LL counties after adjustment for year of diagnosis, age at diagnosis, race/ethnicity, stage at diagnosis, treatment, and estrogen receptor status. When stratified by ER status or BC stage at diagnosis, the relative risk of BC mortality for women in HH counties diagnosed with ER-positive, local or regional stage had a 1.35 (95% CI: 1.19,1.52), 1.32 (95%CI: 1.13,1.54), and a 1.21 (95%CI:1.02,1.43) when compared to women in LL counties, respectively. Our analysis also showed that total death trends were similar to the trends observed in cause-specific deaths. In addition, we observed similar total and cause-specific BC death trends when using a p-value of 0.05 for the LISA analysis. Conclusion: We use LISA spatial clustering to demonstrate the impact national poverty neighborhood environments have on BC mortality, thus identifying counties of worst BC outcomes through neighborhood poverty environments. Our findings suggest that prioritization of resource allocations to HH counties would significantly improve BC outcomes. Citation Format: Ifeoma Nwigwe, Michael Desjardins, Kala Visvanathan. Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality abstract. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-10-03.