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Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Womens+Health+Issues 2016 ; 26 (2): 201-7 Nephropedia Template TP
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Area-level socioeconomic inequalities in the use of mammography screening: A multilevel analysis of the Health of Houston Survey #MMPMID26809487
Calo WA; Vernon SW; Lairson DR; Linder SH
Womens Health Issues 2016[Mar]; 26 (2): 201-7 PMID26809487show ga
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?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?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. quartile 1: OR=0.50; 95% CI: 0.30?0.85), Hispanic composition (quartile 3 vs. quartile 1: OR=0.54; 95% CI: 0.32?0.90), and crowding (quartile 4 vs. quartile 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.