2026-06-14T03:29:13Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/48332024-11-18T12:24:19Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19608

00925njm 22002777a 4500 dc Terán-Hernández, Mónica author Ramis, Rebeca author Calderón-Hernández, Jaqueline author Garrocho-Rangel, Carlos Félix author Campos-Alanís, Juan author Ávalos-Lozano, José Antonio author Aguilar-Robledo, Miguel author 2016-09-29 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. Int J Equity Health. 2016;15(1):161 10.1186/s12939-016-0448-z 1475-9276 International Journal for Equity in Health 27681081 http://hdl.handle.net/20.500.12105/4833 Spatial analysis Bayesian approach Cervical cancer Generalised lineal mixed models San Luis Potosí México Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach