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Mapping Variation in Breast Cancer Screening: Where to Intervene?

Small geographic areas with lower mammography screening participation rates may reflect gaps in screening efforts. Our objective was to use spatial analyses to understand disparities in mammography screening use and to identify factors to increase its uptake in areas that need it in Lyon metropolita...

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Autores principales: Padilla, Cindy M., Painblanc, François, Soler-Michel, Patricia, Vieira, Veronica M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651541/
https://www.ncbi.nlm.nih.gov/pubmed/31252599
http://dx.doi.org/10.3390/ijerph16132274
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author Padilla, Cindy M.
Painblanc, François
Soler-Michel, Patricia
Vieira, Veronica M.
author_facet Padilla, Cindy M.
Painblanc, François
Soler-Michel, Patricia
Vieira, Veronica M.
author_sort Padilla, Cindy M.
collection PubMed
description Small geographic areas with lower mammography screening participation rates may reflect gaps in screening efforts. Our objective was to use spatial analyses to understand disparities in mammography screening use and to identify factors to increase its uptake in areas that need it in Lyon metropolitan area, France. Data for screened women between the ages of 50 and 74 were analyzed. Census blocks of screened and non screened women were extracted from the mammography screening programme 2015–2016 dataset. We used spatial regression models, within a generalized additive framework to determine clusters of census blocks with significantly higher prevalence of non-participation of mammography screening. Smoothed risk maps were crude and adjusted on the following covariates: deprivation index and opportunistic screening. Among 178,002 women aged 50 to 74, 49.9% received mammography screening. As hypothesized, women living in highly deprived census blocks had lower participation rates compared to less deprived blocks, 45.2% vs. 51.4% p < 0.001. Spatial analyses identified four clusters, one located in an urban area and three in suburban areas. Moreover, depending on the location of the cluster, the influence came from different variables. Knowing the impact of site-specific risk factors seems to be important for implementing an appropriate prevention intervention.
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spelling pubmed-66515412019-08-08 Mapping Variation in Breast Cancer Screening: Where to Intervene? Padilla, Cindy M. Painblanc, François Soler-Michel, Patricia Vieira, Veronica M. Int J Environ Res Public Health Article Small geographic areas with lower mammography screening participation rates may reflect gaps in screening efforts. Our objective was to use spatial analyses to understand disparities in mammography screening use and to identify factors to increase its uptake in areas that need it in Lyon metropolitan area, France. Data for screened women between the ages of 50 and 74 were analyzed. Census blocks of screened and non screened women were extracted from the mammography screening programme 2015–2016 dataset. We used spatial regression models, within a generalized additive framework to determine clusters of census blocks with significantly higher prevalence of non-participation of mammography screening. Smoothed risk maps were crude and adjusted on the following covariates: deprivation index and opportunistic screening. Among 178,002 women aged 50 to 74, 49.9% received mammography screening. As hypothesized, women living in highly deprived census blocks had lower participation rates compared to less deprived blocks, 45.2% vs. 51.4% p < 0.001. Spatial analyses identified four clusters, one located in an urban area and three in suburban areas. Moreover, depending on the location of the cluster, the influence came from different variables. Knowing the impact of site-specific risk factors seems to be important for implementing an appropriate prevention intervention. MDPI 2019-06-27 2019-07 /pmc/articles/PMC6651541/ /pubmed/31252599 http://dx.doi.org/10.3390/ijerph16132274 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Padilla, Cindy M.
Painblanc, François
Soler-Michel, Patricia
Vieira, Veronica M.
Mapping Variation in Breast Cancer Screening: Where to Intervene?
title Mapping Variation in Breast Cancer Screening: Where to Intervene?
title_full Mapping Variation in Breast Cancer Screening: Where to Intervene?
title_fullStr Mapping Variation in Breast Cancer Screening: Where to Intervene?
title_full_unstemmed Mapping Variation in Breast Cancer Screening: Where to Intervene?
title_short Mapping Variation in Breast Cancer Screening: Where to Intervene?
title_sort mapping variation in breast cancer screening: where to intervene?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651541/
https://www.ncbi.nlm.nih.gov/pubmed/31252599
http://dx.doi.org/10.3390/ijerph16132274
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