Multilevel regression for small-area estimation of mammography use in the United States, 2014
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Multilevel regression for small-area estimation of mammography use in the United States, 2014

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  • English
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    Details:

    • Alternative Title:
      Cancer Epidemiol Biomarkers Prev
    • Personal Author:
    • Description:
      Background:

      The US Preventive Services Task Force recommends biennial screening mammography for average-risk women aged 50 to 74 years. County-level information on population measures of mammography use can inform targeted intervention to reduce geographic disparities in mammography use. County-level estimates for mammography use nationwide are rarely presented.

      Methods:

      We used data from the 2014 Behavioral Risk Factor Surveillance System (BRFSS) (n=130,289 women), linked it to the American Community Survey poverty data, and fitted multilevel logistic regression models with two outcomes: mammography within the past 2 years (up-to-date); and most recent mammography 5 or more years ago or never (rarely/never). We post-stratified the data with US Census population counts to run Monte Carlo simulations. We generated county-level estimates nationally and by urban-rural county classifications. County-level prevalence estimates were aggregated into state and national estimates. We validated internal consistency between our model-based state-specific estimates and urban-rural estimates with BRFSS direct estimates using Spearman correlation coefficients and mean absolute differences.

      Results:

      Correlation coefficients were 0.94 or larger. Mean absolute differences for the 2 outcomes ranged from 0.79 to 1.03. Although 78.45% (95% CI: 77.95%—78.92%) of women nationally were up-to-date with mammography, more than half of the states had counties with >15% of women rarely/never using a mammogram, many in rural areas.

      Conclusions:

      We provided estimates for all U.S. counties and identified marked variations in mammography use. Many states and counties were far from the 2020 target (81.1%).

      Impact:

      Our results suggest a need for planning and resource allocation on a local level to increase mammography uptake.

    • Subjects:
    • Source:
      Cancer Epidemiol Biomarkers Prev. 28(1):32-40
    • Pubmed ID:
      30275116
    • Pubmed Central ID:
      PMC6343124
    • Document Type:
      Journal Article
    • Funding:
      CC999999/ImCDC/Intramural CDC HHS/United States
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    • Main Document Checksum:
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