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Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach

BACKGROUND: Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that...

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Autores principales: Terán-Hernández, Mónica, Ramis-Prieto, Rebeca, Calderón-Hernández, Jaqueline, Garrocho-Rangel, Carlos Félix, Campos-Alanís, Juan, Ávalos-Lozano, José Antonio, Aguilar-Robledo, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5041341/
https://www.ncbi.nlm.nih.gov/pubmed/27681081
http://dx.doi.org/10.1186/s12939-016-0448-z
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author Terán-Hernández, Mónica
Ramis-Prieto, Rebeca
Calderón-Hernández, Jaqueline
Garrocho-Rangel, Carlos Félix
Campos-Alanís, Juan
Ávalos-Lozano, José Antonio
Aguilar-Robledo, Miguel
author_facet Terán-Hernández, Mónica
Ramis-Prieto, Rebeca
Calderón-Hernández, Jaqueline
Garrocho-Rangel, Carlos Félix
Campos-Alanís, Juan
Ávalos-Lozano, José Antonio
Aguilar-Robledo, Miguel
author_sort Terán-Hernández, Mónica
collection PubMed
description BACKGROUND: Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that identify the main modifiable and non-modifiable CC risk factors for Mexican women. However, there are no studies that attempt to explain the residual spatial variation in CC incidence In Mexico, i.e. spatial variation that cannot be ascribed to known, spatially varying risk factors. METHODS: This paper uses a spatial statistical methodology that takes into account spatial variation in socio-economic factors and accessibility to health services, whilst allowing for residual, unexplained spatial variation in risk. To describe residual spatial variations in CC risk, we used generalised linear mixed models (GLMM) with both spatially structured and unstructured random effects, using a Bayesian approach to inference. RESULTS: The highest risk is concentrated in the southeast, where the Matlapa and Aquismón municipalities register excessive risk, with posterior probabilities greater than 0.8. The lack of coverage of Cervical Cancer-Screening Programme (CCSP) (RR 1.17, 95 % CI 1.12–1.22), Marginalisation Index (RR 1.05, 95 % CI 1.03–1.08), and lack of accessibility to health services (RR 1.01, 95 % CI 1.00–1.03) were significant covariates. CONCLUSIONS: There are substantial differences between municipalities, with high-risk areas mainly in low-resource areas lacking accessibility to health services for CC. Our results clearly indicate the presence of spatial patterns, and the relevance of the spatial analysis for public health intervention. Ignoring the spatial variability means to continue a public policy that does not tackle deficiencies in its national CCSP and to keep disadvantaging and disempowering Mexican women in regard to their health care.
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spelling pubmed-50413412016-10-05 Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach Terán-Hernández, Mónica Ramis-Prieto, Rebeca Calderón-Hernández, Jaqueline Garrocho-Rangel, Carlos Félix Campos-Alanís, Juan Ávalos-Lozano, José Antonio Aguilar-Robledo, Miguel Int J Equity Health Research BACKGROUND: Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that identify the main modifiable and non-modifiable CC risk factors for Mexican women. However, there are no studies that attempt to explain the residual spatial variation in CC incidence In Mexico, i.e. spatial variation that cannot be ascribed to known, spatially varying risk factors. METHODS: This paper uses a spatial statistical methodology that takes into account spatial variation in socio-economic factors and accessibility to health services, whilst allowing for residual, unexplained spatial variation in risk. To describe residual spatial variations in CC risk, we used generalised linear mixed models (GLMM) with both spatially structured and unstructured random effects, using a Bayesian approach to inference. RESULTS: The highest risk is concentrated in the southeast, where the Matlapa and Aquismón municipalities register excessive risk, with posterior probabilities greater than 0.8. The lack of coverage of Cervical Cancer-Screening Programme (CCSP) (RR 1.17, 95 % CI 1.12–1.22), Marginalisation Index (RR 1.05, 95 % CI 1.03–1.08), and lack of accessibility to health services (RR 1.01, 95 % CI 1.00–1.03) were significant covariates. CONCLUSIONS: There are substantial differences between municipalities, with high-risk areas mainly in low-resource areas lacking accessibility to health services for CC. Our results clearly indicate the presence of spatial patterns, and the relevance of the spatial analysis for public health intervention. Ignoring the spatial variability means to continue a public policy that does not tackle deficiencies in its national CCSP and to keep disadvantaging and disempowering Mexican women in regard to their health care. BioMed Central 2016-09-29 /pmc/articles/PMC5041341/ /pubmed/27681081 http://dx.doi.org/10.1186/s12939-016-0448-z Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Terán-Hernández, Mónica
Ramis-Prieto, Rebeca
Calderón-Hernández, Jaqueline
Garrocho-Rangel, Carlos Félix
Campos-Alanís, Juan
Ávalos-Lozano, José Antonio
Aguilar-Robledo, Miguel
Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title_full Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title_fullStr Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title_full_unstemmed Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title_short Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach
title_sort geographic variations in cervical cancer risk in san luis potosí state, mexico: a spatial statistical approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5041341/
https://www.ncbi.nlm.nih.gov/pubmed/27681081
http://dx.doi.org/10.1186/s12939-016-0448-z
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