William A Calo1, Sally W Vernon2, David R Lairson3, Stephen H Linder4. 1. Department of Management, Policy and Community Health, The University of Texas School of Public Health, Houston, Texas. Electronic address: wacalo@live.unc.edu. 2. Center for Health Promotion and Prevention Research, The University of Texas School of Public Health, Houston, Texas. 3. Center for Health Services Research, The University of Texas School of Public Health, Houston, Texas. 4. Institute for Health Policy, The University of Texas School of Public Health, Houston, Texas.
Abstract
BACKGROUND: An emerging literature reports that women who reside in socioeconomically deprived communities are less likely to adhere to mammography screening. This study explored associations between area-level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas. METHODS: We conducted a cross-sectional, multilevel study linking individual-level data from the 2010 Health of Houston Survey and contextual data from the U.S. Census. Women ages 40 to 74 years (n = 1,541) were included in the analyses. We examined tract-level poverty, unemployment, education, Hispanic and Black composition, female-headed householder families, and crowding as contextual measures. Using multilevel logistic regression modeling, we compared most disadvantaged tracts (quartiles 2-4) to the most advantaged tract (quartile 1). RESULTS: Overall, 64% of the sample was adherent to mammography screening. Screening rates were lower (p < .05) among Hispanics, those foreign born, women aged 40 to 49 years, and those with low educational attainment, unemployed, and without health insurance coverage. Women living in areas with high levels of poverty (quartile 2 vs. 1: odds ratio [OR], 0.50; 95% CI, 0.30-0.85), Hispanic composition (quartile 3 vs. 1: OR, 0.54; 95% CI, 0.32-0.90), and crowding (quartile 4 vs. 1: OR, 0.53; 95% CI, 0.29-0.96) were less likely to have up-to-date mammography screening, net of individual-level factors. CONCLUSION: Our findings highlight the importance of examining area-level socioeconomic inequalities in mammography screening. The study represents an advance on previous research because we examined multiple area measures, controlled for key individual-level covariates, used data aggregated at the tract level, and accounted for the nested structure of the data.
BACKGROUND: An emerging literature reports that women who reside in socioeconomically deprived communities are less likely to adhere to mammography screening. This study explored associations between area-level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas. METHODS: We conducted a cross-sectional, multilevel study linking individual-level data from the 2010 Health of Houston Survey and contextual data from the U.S. Census. Women ages 40 to 74 years (n = 1,541) were included in the analyses. We examined tract-level poverty, unemployment, education, Hispanic and Black composition, female-headed householder families, and crowding as contextual measures. Using multilevel logistic regression modeling, we compared most disadvantaged tracts (quartiles 2-4) to the most advantaged tract (quartile 1). RESULTS: Overall, 64% of the sample was adherent to mammography screening. Screening rates were lower (p < .05) among Hispanics, those foreign born, women aged 40 to 49 years, and those with low educational attainment, unemployed, and without health insurance coverage. Women living in areas with high levels of poverty (quartile 2 vs. 1: odds ratio [OR], 0.50; 95% CI, 0.30-0.85), Hispanic composition (quartile 3 vs. 1: OR, 0.54; 95% CI, 0.32-0.90), and crowding (quartile 4 vs. 1: OR, 0.53; 95% CI, 0.29-0.96) were less likely to have up-to-date mammography screening, net of individual-level factors. CONCLUSION: Our findings highlight the importance of examining area-level socioeconomic inequalities in mammography screening. The study represents an advance on previous research because we examined multiple area measures, controlled for key individual-level covariates, used data aggregated at the tract level, and accounted for the nested structure of the data.
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