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Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography
BACKGROUND: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regress...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2474591/ https://www.ncbi.nlm.nih.gov/pubmed/18590540 http://dx.doi.org/10.1186/1476-072X-7-32 |
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author | Mobley, Lee R Kuo, Tzy-Mey (May) Driscoll, David Clayton, Laurel Anselin, Luc |
author_facet | Mobley, Lee R Kuo, Tzy-Mey (May) Driscoll, David Clayton, Laurel Anselin, Luc |
author_sort | Mobley, Lee R |
collection | PubMed |
description | BACKGROUND: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors. RESULTS: Pooling all women across states leads to quite different conclusions than state-specific models. Commuter intensity, community acculturation, and community elderly impoverishment have significant direct impacts on mammography use which vary across states. Minorities living in isolated enclaves with others of the same race/ethnicity may be either advantaged or disadvantaged, depending upon the place studied. CONCLUSION: Careful analysis of place-specific context is essential for understanding differences across communities stemming from different causal factors. Optimal policy interventions to change behavior (improve screening rates) will be as heterogeneous as local community characteristics, so no "one size fits all" policy can improve population health. Probability modeling with correction for clustering of individuals within multilevel contexts can reveal important differences from place to place and identify key factors to inform targeting of specific communities for further study. |
format | Text |
id | pubmed-2474591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-24745912008-07-17 Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography Mobley, Lee R Kuo, Tzy-Mey (May) Driscoll, David Clayton, Laurel Anselin, Luc Int J Health Geogr Research BACKGROUND: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors. RESULTS: Pooling all women across states leads to quite different conclusions than state-specific models. Commuter intensity, community acculturation, and community elderly impoverishment have significant direct impacts on mammography use which vary across states. Minorities living in isolated enclaves with others of the same race/ethnicity may be either advantaged or disadvantaged, depending upon the place studied. CONCLUSION: Careful analysis of place-specific context is essential for understanding differences across communities stemming from different causal factors. Optimal policy interventions to change behavior (improve screening rates) will be as heterogeneous as local community characteristics, so no "one size fits all" policy can improve population health. Probability modeling with correction for clustering of individuals within multilevel contexts can reveal important differences from place to place and identify key factors to inform targeting of specific communities for further study. BioMed Central 2008-06-30 /pmc/articles/PMC2474591/ /pubmed/18590540 http://dx.doi.org/10.1186/1476-072X-7-32 Text en Copyright © 2008 Mobley et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Mobley, Lee R Kuo, Tzy-Mey (May) Driscoll, David Clayton, Laurel Anselin, Luc Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title | Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title_full | Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title_fullStr | Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title_full_unstemmed | Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title_short | Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
title_sort | heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2474591/ https://www.ncbi.nlm.nih.gov/pubmed/18590540 http://dx.doi.org/10.1186/1476-072X-7-32 |
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