ABSTRACT
Objetivo: Presentar la metodología seguida en el diseño y la implementación de un índice de privación por sección censal, y describir la situación socioeconómica en España en 2011. Método: La unidad de análisis fue la sección censal (N=35.960). Los datos proceden del Censo de Población y Viviendas de 2011. Teniendo en cuenta el carácter muestral del censo y las limitaciones normativas de confidencialidad de datos, las variables se calcularon indirectamente usando los complementarios de las variables disponibles. Se efectuaron comprobaciones para asegurar su fiabilidad. En la selección de indicadores se consideró la comparabilidad con el índice MEDEA y se exploró la incorporación de nueva información. Se elaboró un índice de privación mediante análisis de componentes principales. Se realizó un análisis de sensibilidad del índice en ámbitos urbanos y en el resto de los territorios. Resultados: Con la información censal se elaboraron 22 indicadores para 35.917 secciones censales. El índice de privación se basó en seis indicadores: población trabajadora manual, población asalariada eventual, desempleo, personas de 16 y más años y de 16 a 29 años con instrucción insuficiente, y viviendas principales sin acceso a Internet. El mapa de España muestra un eje decreciente de privación de suroeste a nordeste. Conclusiones: Se ha aprovechado sistemáticamente la información socioeconómica del censo de 2011 por sección censal. El índice elaborado, similar al MEDEA, facilitará el estudio actualizado de las desigualdades en salud para toda España después de la crisis económica iniciada en 2008. (AU)
Objective: To present the methodology used in the design and implementation of a deprivation index by enumeration district, and to describe the socioeconomic situation of Spain in 2011.Method: The unit of analysis was the enumeration district (N=35,960). Data came from the 2011 Population and Housing Census of Spain. Given both the sampling nature of the Census and the regulatory limitations of data confidentiality, variables were calculated indirectly by using the complement of the available variables. Checks were made to ensure reliability. The selection of the indicators took into account comparability with the MEDEA index. The inclusion of additional information was explored. A deprivation index was built using Principal Component Analysis. Sensitivity analysis of the index was performed for urban areas and the rest of the regions. Results: Using the census information, 22 indicators were calculated for 35,917 enumeration districts. The deprivation index was based on six indicators: manual and temporary workers, unemployment, insufficient education overall and in young people (aged 16 to 29 years), and dwellings without access to the internet. The map of Spain shows a gradient of decreasing deprivation from south-west to north-east. Conclusions: The socioeconomic information of the 2011 census by enumeration district was used systematically. The drafted index, similar to the MEDEA, will facilitate the updated study of health inequalities for Spain overall following the economic recession that began in 2008. (AU)
Subject(s)
Humans , Male , Female , Adolescent , Young Adult , Health Status Disparities , Censuses , Unemployment , Spain , Cross-Sectional Studies , Socioeconomic Factors , Reproducibility of ResultsABSTRACT
La incidencia y la mortalidad brindan información sobre la carga de la morbilidad del cáncer y los años potenciales de vida perdidos debido al cáncer. Se ha desarrollado el Índice de Privación (IP) como una medida estandarizada para medir la privación socioeconómica en España a nivel de sección censal. Además, se puede combinar la información del IP con variables ecológicas poblacionales y los datos de los Estudios Europeos de Alta Resolución en Cáncer. El objetivo de este estudio es caracterizar las desigualdades socioeconómicas en la incidencia, el exceso de mortalidad, la mortalidad prematura y la supervivencia neta para tres de los cánceres más incidentes (pulmón, colon-recto y mama) en España usando el IP. Este estudio nacional multinivel de base poblacional evaluará el impacto de las desigualdades socioeconómicas. Se usarán el análisis espacial, la modelización multinivel, la supervivencia neta y la evaluación del impacto económico. Los resultados serán útiles para el apoyo a la toma de decisiones y la planificación y la gestión de intervenciones en salud pública destinadas a reducir el impacto de las desigualdades socioeconómicas en el diagnóstico y el pronóstico de los pacientes de cáncer en España. (AU)
Incidence and mortality provide information on the burden of cancer morbidity and the potential years of life lost due to cancer. The Spanish Deprivation Index (SDI) has been developed as a standardized measure to study socioeconomic deprivation in Spain at the census tract level. In addition, SDI information can be combined with ecological variables at the population level and data from the High-Resolution European Studies in Cancer. The aim of this study is to characterize socioeconomic inequalities in incidence, excess mortality, premature mortality and net survival for three of the most incident cancers (lung, colon-rectum and breast) in Spain using the SDI. This national population-based study will assess the impact of socioeconomic inequalities using a multilevel modelling approach. Spatial analysis, multilevel modeling, net survival and economic impact assessment will be used. The results will be useful for supporting decision-making, planning, and management of public health interventions aimed at reducing the impact of socioeconomic inequalities in the diagnosis and prognosis of cancer patients in Spain. (AU)
Subject(s)
Humans , Neoplasms/epidemiology , Neoplasms/mortality , Health Status Disparities , Spain/epidemiology , Socioeconomic Factors , IncidenceABSTRACT
OBJECTIVE: To present the methodology used in the design and implementation of a deprivation index by enumeration district, and to describe the socioeconomic situation of Spain in 2011. METHOD: The unit of analysis was the enumeration district (N=35,960). Data came from the 2011 Population and Housing Census of Spain. Given both the sampling nature of the Census and the regulatory limitations of data confidentiality, variables were calculated indirectly by using the complement of the available variables. Checks were made to ensure reliability. The selection of the indicators took into account comparability with the MEDEA index. The inclusion of additional information was explored. A deprivation index was built using Principal Component Analysis. Sensitivity analysis of the index was performed for urban areas and the rest of the regions. RESULTS: Using the census information, 22 indicators were calculated for 35,917 enumeration districts. The deprivation index was based on six indicators: manual and temporary workers, unemployment, insufficient education overall and in young people (aged 16 to 29 years), and dwellings without access to the internet. The map of Spain shows a gradient of decreasing deprivation from south-west to north-east. CONCLUSIONS: The socioeconomic information of the 2011 census by enumeration district was used systematically. The drafted index, similar to the MEDEA, will facilitate the updated study of health inequalities for Spain overall following the economic recession that began in 2008.
Subject(s)
Censuses , Unemployment , Adolescent , Humans , Reproducibility of Results , Socioeconomic Factors , SpainABSTRACT
Incidence and mortality provide information on the burden of cancer morbidity and the potential years of life lost due to cancer. The Spanish Deprivation Index (SDI) has been developed as a standardized measure to study socioeconomic deprivation in Spain at the census tract level. In addition, SDI information can be combined with ecological variables at the population level and data from the High-Resolution European Studies in Cancer. The aim of this study is to characterize socioeconomic inequalities in incidence, excess mortality, premature mortality and net survival for three of the most incident cancers (lung, colon-rectum and breast) in Spain using the SDI. This national population-based study will assess the impact of socioeconomic inequalities using a multilevel modelling approach. Spatial analysis, multilevel modeling, net survival and economic impact assessment will be used. The results will be useful for supporting decision-making, planning, and management of public health interventions aimed at reducing the impact of socioeconomic inequalities in the diagnosis and prognosis of cancer patients in Spain.
Subject(s)
Health Status Disparities , Neoplasms , Humans , Incidence , Mortality , Neoplasms/epidemiology , Socioeconomic Factors , Spain/epidemiologyABSTRACT
OBJECTIVE: To build a deprivation index for the assignation of the budgets of the primary healthcare teams in Catalonia (Spain) valid for both urban and rural environments and updatable with greater frequency than indices built from census variables. METHOD: Starting from a review of the most common deprivation indices, variables were selected from sources that allow frequent updating and are representative at the territorial level of primary care. The correlations were calculated between the chosen variables and variables of need for healthcare and morbidity. principal components analysis was applied. Finally, the correlations of the index built with the MEDEA index and with variables of use of healthcare resources and morbidity was calculated stratifying by geographical dispersion. RESULTS: The variables of income, occupation and education are the ones with the highest correlation with the need for healthcare and morbidity. The composed socioeconomic index (CSI) ranges from -.01 to 5.68, with an average value of 2.60 and a standard deviation of .91. The correlation between the CSI and the MEDEA index is .89. The CSI correlates with use for healthcare in both urban and rural environments, although in rural environments the association is lower. CONCLUSIONS: The CSI was built with data that allow frequent updating and was integrated in the model for allocating resources to primary healthcare starting in 2017.
