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Breast Cancer Care of Mexican American Women in High Poverty California Neighborhoods: Protective Effects of Social and Financial Capital, Including Health.

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Presentation on theme: "Breast Cancer Care of Mexican American Women in High Poverty California Neighborhoods: Protective Effects of Social and Financial Capital, Including Health."— Presentation transcript:

1 Breast Cancer Care of Mexican American Women in High Poverty California Neighborhoods: Protective Effects of Social and Financial Capital, Including Health Insurance, in Barrios Sundus Haji-Jama, a Nancy L. Richter, a Kevin M. Gorey, a Isaac N. Luginaah, b GuangYong Zou, bc Eric J. Holowaty, d Madhan K. Balagurusamy, a & Caroline Hamm be a University of Windsor, b University of Western Ontario, c Robarts Research Institute, d University of Toronto, e Windsor Regional Cancer Center Abstract Introduction ResultsMethod Summary: Seemingly paradoxically, a very strong advantaging effect of having health insurance was observed among MA women who lived in MA barrios, neighborhoods that were also very poor. In fact, the rates of early breast cancer diagnoses, receipt of optimum treatments and survival among MA barrio residents were on par with those of NHW women who lived in the lowest poverty neighborhoods. This study’s barrios were consistent with Maas’ (2011) “gateway MA neighborhoods:” prevalent low- income & high-immigrant populations—places where social capital seems strongest & most supportive. Conclusion: Findings are consistent with the theory that more facilitative social and economic capital is available to MA women in barrios and to NHW women in more affluent neighborhoods. It is there that each respective group of women is probably best able to absorb the uncovered costs of breast cancer care. Synchrony (IS)Shared Positive AffectShared Negative Affect Cooperation.440* -.065 Assertion.458*.540** -.560** Responsibility.368.488*-.233 Self Control.451*.469*-.220 TOTAL.535**.586**-.325 HYPOTHESIS SUPPORTED HYPOTHESIS REJECTED * Significant at p <.05 ** Significant at p <.01 1.During the Great Recession prevalent poor, uninsured and underinsured populations in the United States grew to 46, 50 & 100 million people. 2.The incidence of all such risks were substantially greater among MAs than NHWs (Jargowsky, 2005). 3.Yet diverse health benefits seem to be enjoyed by those who live in Hispanic enclaves, especially in MA barrios populated by 1 st generation immigrants (Osypuk et al., 2010; Portes & Bach, 1985). 4.Though prevalently poor, MA barrios may provide relatively more instrumental social & economic supports (Markides & Coreil, 1986). 5.Studies of NHW people suggest adequate health insurance (private or Medicare) is most effective in low poverty neighborhoods, where social and economic capital abounds. 6.Research questions: Using breast cancer care as a sentinel health indicator: (1) Is health insurance less effective in high poverty neighborhoods for NHW women? And (2) Is it more effective in high poverty, barrio neighborhoods for MA women. We examined health insurance mediation of Mexican American (MA) non-Hispanic white (NHW) disparities on breast cancer care. And we hypothesized a 3-way ethnicity by poverty by health insurance interaction; 2-way poverty by health insurance interactions would differ between ethnic groups. We analyzed California registry data for 303 MA and 3,611 NHW women diagnosed between 1996 & 2000, followed until 2011. Census data categorized neighborhood poverty: high (> 30% poor) to low (< 5% poor). Barrios where 50% or more MA. MA-NHW diagnostic, treatment & survival disparities were mediated by health insurance. Advantages of health insurance were largest in low poverty neighborhoods among NHW women while among MA women they were, paradoxically, largest in high poverty, MA barrios. These findings are consistent with the theory that more facilitative social & financial capital is available to MA women in barrios and to NHW women in more affluent neighborhoods. It is there that each respective group of women is probably best able to absorb the indirect and direct, but uncovered, costs of breast cancer care. Samples Analyses For more information please contact: gorey@uwindsor.ca gorey@uwindsor.cagorey@uwindsor.ca Hypotheses Discussion Associations of Adequate Health Insurance with Breast Cancer Care & Survival : RR (95% CI) Early Diagnosis of NN Disease Mexican American women: Barrios (hi pov):RR = 1.45 (1.11, 1.90) Non-barrios: RR = 1.04 (0.91, 1.19) Non-Hispanic white women: High-poverty:RR = 1.12 (1.02, 1.23) Low-poverty: RR = 1.20 (1.06, 1.36) Received Timely RT after BCS † Mexican American women: Barrios (hi pov):RR = 1.88 (1.11, 3.10) Non-barrios: RR = 1.09 (0.87, 1.37) Non-Hispanic white women: High-poverty:RR = 1.05 (0.69, 1.60) Low-poverty:RR = 1.15 (1.07, 1.23) 8-Year Survival of Those with NN Disease Mexican American women: Barrios (hi pov):RR = 1.67 (1.13, 2.48) Non-barrios: RR = 1.38 (0.97, 1.97) Non-Hispanic white women: High poverty:RR = 1.06 (1.00, 1.13) Low poverty:RR = 1.19 (1.05, 1.34) † Radiation therapy within 6 months of breast conserving surgery. Sampling Frames: California Cancer Registry, breast cancer diagnosed 1996 to 2000, followed until 2011 High Poverty Neighborhoods Oversampled: Cases joined to census tracts (2000) High poverty tracts (> 30% poor) were oversampled So MAs & MA barrios (> 50% MA) were oversampled MA & NHW Samples: All breast cancers:303 † & 3,611 cases Node negative breast cancer: 194 † & 2,846 cases † 90% were first generation immigrants born in Mexico Breast Cancer Care & Outcome Measures: Stage at diagnosis: node –ve (NN) or node +ve (NP) Surgical & adjuvant therapies & wait times Overall & cancer-specific survival to 10 years NHW Women: Those with adequate health insurance will be diagnosed earlier, treated more effectively and survive longer in low poverty neighborhoods. MA Women: Those with adequate health insurance will be diagnosed earlier, treated more effectively and survive longer in high poverty, barrio neighborhoods. Statistical Analyses: Logistic & Cox Regression Models Odds ratios (OR), Hazard ratios (HR) & 95% confidence intervals (CI) were estimated Modest missing data were imputed from full models Practical Analyses: Age- and grade-adjusted rates per 100 reported as % Standardized rate ratios (RR) were internally adjusted Other Key Variables such as Birthplace Accounted for Through Sample Restriction or Mathematical Modeling


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