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Published on: August 30, 2013
Using small-area estimation to describe county-level disparities in mammography
Karen L Schneider1, Kate L Lapane, Melissa A Clark
1Department of Community Health, Brown University, Providence, Rhode Island, USA. kschneider@jsi.com
Preventing Chronic Disease
|September 17, 2009
Summary
Geographic disparities in mammography use exist across U.S. counties. Small-area estimation reveals lower prevalence among nonwhite women and younger age groups, highlighting the need for targeted interventions.
Area of Science:
- Public Health
- Epidemiology
- Health Services Research
Background:
- Mammography prevalence studies typically analyze data at national and state levels.
- Substate-level analysis is crucial for effective breast cancer control.
- Geographic disparities in mammography use remain underexplored at the county level.
Purpose of the Study:
- To evaluate geographic disparities in mammography use across U.S. counties.
- To identify variations in mammography prevalence at a substate level.
- To inform targeted breast cancer screening interventions.
Main Methods:
- Employed synthetic regression, a small-area estimation technique.
- Utilized data from the 2000 Behavioral Risk Factor Surveillance System (BRFSS), 2000 Census, Area Resource File, and FDA mammography facility data.
- Generated county-level mammography prevalence estimates for women aged 40-79, stratified by race and age group.
Main Results:
- Significant geographic variation in mammography use was observed at the county level.
- Nonwhite women exhibited the lowest prevalence and widest range of county-level estimates.
- Younger women (40-49) had lower prevalence, while older women (65-79) showed the greatest variation.
Conclusions:
- Small-area estimation using BRFSS data is effective for county-level mammography surveillance.
- This method accurately documents geographic disparities and spatial distribution of mammography use.
- Future interventions should address county-level variations, prioritizing underserved populations.
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