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Background Life expectancy at birth (LE) has been calculated for states and counties. LE estimates at these levels mask health disparities in local communities. There are no nationwide estimates at the sub-county level. We present a stepwise approach for calculating LE using census tracts in New York state to identify health disparities. Methods Our study included 2751 census tracts in New York state, but excluded New York City. We used population data from the 2010 United States Census and 2008–2010 mortality data from the state health department. Tracts were assigned to 99.97% of the deaths. We removed tracts which had a majority of people living in group quarters. Deaths in these tracts are often recorded elsewhere. Of the remaining 2679 tracts, 6.6% of the tracts had standard errors ≥ 2 years. A geographic aggregation tool was used to aggregate tracts with fewer than 60 deaths, and then aggregate areas that had standard errors of ≥ 2 years. Results Aggregation resulted in a 9.9% reduction in the number of areas. Tracts with

Fundamento. Describir las desigualdades en mortalidad en Logroño y Pamplona, ciudades del norte de España, utilizando un indicador de privación socioeconómica por secciones censales. Métodos. Para geocodificar la residencia de los fallecidos en base a las unidades censales se utilizó la dirección postal del Boletín Estadístico de Defunción y en su defecto la del Padrón Municipal o Tarjeta Sanitaria. Las variables socioeconómicas que componen el índice de privación se obtuvieron del Censo de Población y Vivienda de 2001. Se agruparon las secciones censales por quintiles de menor a mayor privación socioeconómica y se calcularon tasas ajustadas para la mortalidad total y para una lista de causas por sexo, grupo de edad (0-64, ≥ 65) y quintil del índice de privación socioeconómico. Resultados. La comparación de la mortalidad de las zonas con menor privación socioeconómica respecto a zonas geográficas con mayor privación mostró en ambas ciudades una mayor mortalidad principalmente entre los hombres menores de 65 años. En este subgrupo se observó un gradiente positivo entre la mortalidad y el índice de privación. Las zonas situadas en el quintil de mayor privación alcanzaron un riesgo relativo (RR) de 1,61 (IC 95%, 1,33-1,92) en Pamplona y de 1,77 (IC 95%, 1,55-2,01) en Logroño. Las mujeres menores de 65 años mostraron un RR de 1,44 (IC 95%, 1,18-1,74) y de 1,48 (IC 95%, 1,10-1,95) en las zonas situadas en el quintil de mayor privación de Pamplona y Logroño, respectivamente. Conclusiones. El estudio evidenció desigualdades en mortalidad asociadas a la privación socioeconómica en las ciudades de Logroño y Pamplona. También mostró la utilidad de los indicadores socioeconómicos y de mortalidad a nivel de área pequeña para identificar desigualdades en salud Background. The objective of this study was to describe inequalities in mortality in the cities of Logroño and Pamplona, using a socioeconomic privation index by census tract. Methods. Deaths were geocoded using the mailing address of the Death Statistics Bulletin and, in its absence, that of the Spanish Municipal Register or the Spanish Health Card. The socioeconomic variables used to construct the deprivation index were obtained from the Spanish Population and Housing Census of 2001. Census tracts were grouped by socioeconomic deprivation quintiles. In each quintile, age-adjusted mortality rates were computed by sex and age group (0-64, ≥ 65). Results. In both cities, higher mortality rates were observed in the geographical areas with higher socio-economic deprivation. This was particularly evident among men under 65 for whom a positive gradient between mortality and the deprivation index was observed. The areas with higher deprivation reached a relative risk (RR) of 1.61 (CI 95%, 1, 33-1, 92) and 1.77 (CI 95%, 1, 55-2 01) in Pamplona and Logroño respectively. Among women under 65, a RR of 1.44 (CI 95%, 1, 18-1, 74) and 1.48 (CI 95%, 1, 10-1, 95) were shown for the most depressed areas of Pamplona and Logroño respectively. Conclusions. The study highlighted inequalities in mortality associated with socioeconomic deprivation in the cities of Logroño and Pamplona. Also showed was the utility of analysing socio-economic indicators and mortality by small areas in order to identify inequality in health

Background: While research continues into indicators such as preventable and amenable mortality in order to evaluate quality, access, and equity in the healthcare, it is also necessary to continue identifying the areas of greatest risk owing to these causes of death in urban areas of large cities, where a large part of the population is concentrated, in order to carry out specific actions and reduce inequalities in mortality. This study describes inequalities in amenable mortality in relation to socioeconomic status in small urban areas, and analyses their evolution over the course of the periods 1996–99, 2000–2003 and 2004–2007 in three major cities in the Spanish Mediterranean coast (Alicante, Castellón, and Valencia). Methods: All deaths attributed to amenable causes were analysed among non-institutionalised residents in the three cities studied over the course of the study periods. Census tracts for the cities were grouped into 3 socioeconomic status levels, from higher to lower levels of deprivation, using 5 indicators obtained from the 2001 Spanish Population Census. For each city, the relative risks of death were estimated between socioeconomic status levels using Poisson’s Regression models, adjusted for age and study period, and distinguishing between genders. Results: Amenable mortality contributes significantly to general mortality (around 10%, higher among men), having decreased over time in the three cities studied for men and women. In the three cities studied, with a high degree of consistency, it has been seen that the risks of mortality are greater in areas of higher deprivation, and that these excesses have not significantly modified over time. Conclusions: Although amenable mortality decreases over the time period studied, the socioeconomic inequalities observed are maintained in the three cities. Areas have been identified that display excesses in amenable mortality, potentially attributable to differences in the healthcare system, associated with areas of greater deprivation. Action must be taken in these areas of greater inequality in order to reduce the health inequalities detected. The causes behind socioeconomic inequalities in amenable mortality must be studied in depth. This work was partly supported by the FIS-FEDER projects PI040170 and PI080330.

Fundamento. Describir las desigualdades en mortalidad en Logroño y Pamplona, ciudades del norte de España, utilizando un indicador de privación socioeconómica por secciones censales. Métodos. Para geocodificar la residencia de los fallecidos en base a las unidades censales se utilizó la dirección postal del Boletín Estadístico de Defunción y en su defecto la del Padrón Municipal o Tarjeta Sanitaria. Las variables socioeconómicas que componen el índice de privación se obtuvieron del Censo de Población y Vivienda de 2001. Se agruparon las secciones censales por quintiles de menor a mayor privación socioeconómica y se calcularon tasas ajustadas para la mortalidad total y para una lista de causas por sexo, grupo de edad (0-64, ≥ 65) y quintil del índice de privación socioeconómico. Resultados. La comparación de la mortalidad de las zonas con menor privación socioeconómica respecto a zonas geográficas con mayor privación mostró en ambas ciudades una mayor mortalidad principalmente entre los hombres menores de 65 años. En este subgrupo se observó un gradiente positivo entre la mortalidad y el índice de privación. Las zonas situadas en el quintil de mayor privación alcanzaron un riesgo relativo (RR) de 1,61 (IC 95%, 1,33-1,92) en Pamplona y de 1,77 (IC 95%, 1,55-2,01) en Logroño. Las mujeres menores de 65 años mostraron un RR de 1,44 (IC 95%, 1,18-1,74) y de 1,48 (IC 95%, 1,10-1,95) en las zonas situadas en el quintil de mayor privación de Pamplona y Logroño, respectivamente. Conclusiones. El estudio evidenció desigualdades en mortalidad asociadas a la privación socioeconómica en las ciudades de Logroño y Pamplona. También mostró la utilidad de los indicadores socioeconómicos y de mortalidad a nivel de área pequeña para identificar desigualdades en salud. Background. The objective of this study was to describe inequalities in mortality in the cities of Logroño and Pamplona, using a socioeconomic privation index by census tract. Methods. Deaths were geocoded using the mailing address of the Death Statistics Bulletin and, in its absence, that of the Spanish Municipal Register or the Spanish Health Card. The socioeconomic variables used to construct the deprivation index were obtained from the Spanish Population and Housing Census of 2001. Census tracts were grouped by socioeconomic deprivation quintiles. In each quintile, age-adjusted mortality rates were computed by sex and age group (0-64, ≥ 65). Results. In both cities, higher mortality rates were observed in the geographical areas with higher socio-economic deprivation. This was particularly evident among men under 65 for whom a positive gradient between mortality and the deprivation index was observed. The areas with higher deprivation reached a relative risk (RR) of 1.61 (CI 95%, 1, 33-1, 92) and 1.77 (CI 95%, 1, 55-2 01) in Pamplona and Logroño respectively. Among women under 65, a RR of 1.44 (CI 95%, 1, 18-1, 74) and 1.48 (CI 95%, 1, 10-1, 95) were shown for the most depressed areas of Pamplona and Logroño respectively. Conclusions. The study highlighted inequalities in mortality associated with socioeconomic deprivation in the cities of Logroño and Pamplona. Also showed was the utility of analysing socio-economic indicators and mortality by small areas in order to identify inequality in health.

Introduction: Little is known about the influence of individual debts on health inequalities in Germany. Studies front English-language countries have shown that indebtedness is a great burden in every-day life that leads to mental stress and is related to negative health outcomes. Our paper, for the first time, analyses the role of indebtedness oil mortality in Germany. Methods: Using ecological level data of Germany's 439 administrative districts, we assessed the role of unemployment, income, educational level, population density, regional prosperity, number of hospital beds and of the independent effect of indebtedness on mortality. The variance explained by indebtedness was determined by means of multiple linear regression models. Data were provided by the Federal Statistical Office of Germany and Schufa Holding AG. Results: Indebtedness and unemployment are moderately correlated. Even so, a significant independent effect of indebtedness on mortality can be shown. Indebtedness contributes to the explanation of health inequalities and, together with other socioeconomic factors and the federal state, explains 59% of the variance in age-standardised district level mortality. Indebtedness explains 6% of variance. Conclusion: For the first time in Germany, this study shows that indebtedness not only influences population health as a result of low income or unemployment but also has ail independent, albeit rather shall, effect. Studies focussing oil social inequity and health should further examine the role of indebtedness and also include an analysis oil the individual level.

Objetivos: Describir las desigualdades socioeconómicas en la mortalidad en la Comunidad Autónoma del País Vasco, utilizando datos de mortalidad y socioeconómicos por secciones censales. Métodos: Los datos sobre las defunciones y sobre la población fueron obtenidos del Instituto Vasco de Estadística. Se asignó a cada defunción las características socioeconómicas de su sección censal y se construyó un índice de privación que combinaba cuatro indicadores socioeconómicos. Se estimaron tasas de mortalidad ajustadas por edad para cada quintil del índice de privación por sexo, grupo de edad (0-64, ≥ 65 años) y causa de defunción. Mediante modelos de regresión de Poisson se estimaron las razones de tasas ajustadas por edad y el exceso de mortalidad atribuible a las desigualdades. Resultados: La mortalidad mostró un gradiente según el índice de privación en ambos sexos, siendo la mortalidad mayor en las secciones más desfavorecidas. Las mayores desigualdades se observaron en los varones menores de 65 años. Un 9,3 y un 4,9% de las defunciones en los varones y en las mujeres, respectivamente, fueron atribuibles a las desigualdades socioeconómicas. La importancia relativa de las causas de muerte fue distinta según la medida de desigualdad utilizada, y destacaron las causas relacionadas con los estilos de vida. Conclusiones: Este estudio ilustra la utilidad de los datos por sección censal para describir las desigualdades en la mortalidad y para identificar prioridades de intervención. Objectives: To describe socioeconomic inequalities in mortality in the Basque Country, using mortality and socioeconomic data by census sections. Methods: Mortality and population data were obtained from the Basque Institute of Statistics. Socioeconomic characteristics of the census sections were assigned to each death and a deprivation index combining information from four socioeconomic indicators was computed. Age-adjusted mortality rates by sex, age group (0-64 ≥ 65) and cause of death were calculated for each quintile of the deprivation index. Poisson regression models were fitted to estimate age-adjusted rate ratios and excess mortality attributable to inequalities. Results: Mortality showed a gradient according to the deprivation index in men and women. Mortality was greater in the most deprived sections. Mortality inequalities were observed in men younger than 65 years. A total of 9.3% of deaths in men and 4.9% of those in women were attributable to socioeconomic inequalities. The relative importance of the cause of death differed according to the inequality measure used. Lifestyle-related causes of death were notable. Conclusion: This study illustrates the potential utility of census section socioeconomic indicators both to describe socioeconomic inequalities in mortality and to identify priorities for interventions.

ResumenObjetivosDescribir las desigualdades socioeconómicas en la mortalidad en la Comunidad Autónoma del País Vasco, utilizando datos de mortalidad y socioeconómicos por secciones censales.MétodosLos datos sobre las defunciones y sobre la población fueron obtenidos del Instituto Vasco de Estadística. Se asignó a cada defunción las características socioeconómicas de su sección censal y se construyó un índice de privación que combinaba cuatro indicadores socioeconómicos. Se estimaron tasas de mortalidad ajustadas por edad para cada quintil del índice de privación por sexo, grupo de edad (0-64, ≥ 65 años) y causa de defunción. Mediante modelos de regresión de Poisson se estimaron las razones de tasas ajustadas por edad y el exceso de mortalidad atribuible a las desigualdades.ResultadosLa mortalidad mostró un gradiente según el índice de privación en ambos sexos, siendo la mortalidad mayor en las secciones más desfavorecidas. Las mayores desigualdades se observaron en los varones menores de 65 años. Un 9,3 y un 4,9% de las defunciones en los varones y en las mujeres, respectivamente, fueron atribuibles a las desigualdades socioeconómicas. La importancia relativa de las causas de muerte fue distinta según la medida de desigualdad utilizada, y destacaron las causas relacionadas con los estilos de vida.ConclusionesEste estudio ilustra la utilidad de los datos por sección censal para describir las desigualdades en la mortalidad y para identificar prioridades de intervención.AbstractObjectivesTo describe socioeconomic inequalities in mortality in the Basque Country, using mortality and socioeconomic data by census sections.MethodsMortality and population data were obtained from the Basque Institute of Statistics. Socioeconomic characteristics of the census sections were assigned to each death and a deprivation index combining information from four socioeconomic indicators was computed. Age-adjusted mortality rates by sex, age group (0-64 ≥ 65) and cause of death were calculated for each quintile of the deprivation index. Poisson regression models were fitted to estimate age-adjusted rate ratios and excess mortality attributable to inequalities.ResultsMortality showed a gradient according to the deprivation index in men and women. Mortality was greater in the most deprived sections. Mortality inequalities were observed in men younger than 65 years. A total of 9.3% of deaths in men and 4.9% of those in women were attributable to socioeconomic inequalities. The relative importance of the cause of death differed according to the inequality measure used. Lifestyle-related causes of death were notable.ConclusionThis study illustrates the potential utility of census section socioeconomic indicators both to describe socioeconomic inequalities in mortality and to identify priorities for interventions.