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      Inequalities in life expectancy by educational level and its decomposition in Barcelona, 2004-2018 Translated title: Desigualdades en la esperanza de vida por nivel educativo y su descomposición en Barcelona, 2004-2018

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          Abstract

          Abstract Objective: To analyse the gap in life expectancy by educational level in the city of Barcelona from 2004 to 2018 and to decompose this gap by age and causes of death. Method: We computed abridged life tables at the age of 25 years by sex from 2004 to 2018 using standard methods. Educational level was categorised in two groups (lower secondary or less vs. upper secondary or higher education). The life expectancy gap was further decomposed by age and by causes of death based in Arriaga's method in 5-year age blocks up to the age of ≥ 90 years and broad causes of death using ICD-10 codes. Results: The life expectancy gap at 25 years by educational level oscillated without trend at around 3.08 years for men and 1.93 years for women. Decomposition by age showed a favourable significant shift in the contribution to this gap from young to older ages for men, with few changes for women. Decomposition by causes of death showed that the diseases concentrating the largest share of the contribution were neoplasms and respiratory and circulatory disease. There was a significant downward trend in external causes for men and in infectious diseases for both men and women but a significant upward trend for respiratory disease for both sexes. Conclusions: The stability of the life expectancy gap by educational level during the period analysed resulted from a combination of divergent trends by age and causes of death among high and low educational levels.

          Translated abstract

          Resumen Objetivo: Analizar la brecha en la esperanza de vida por nivel educativo en la ciudad de Barcelona desde 2004 hasta 2018, y descomponer esta brecha por edad y causas de muerte. Método: Se calcularon tablas de vida abreviadas a la edad de 25 años por sexo desde 2004 hasta 2018 utilizando métodos estándar. El nivel educativo se clasificó en dos grupos: secundaria inferior o menor frente a secundaria superior o educación superior. La brecha de la esperanza de vida se descompuso además por edad y por causas de muerte según el método de Arriaga en bloques de edad de 5 años hasta la edad de ≥90 años y causas amplias de muerte utilizando los códigos de la CIE-10. Resultados: La brecha de la esperanza de vida a los 25 años por nivel educativo osciló sin tendencia en torno a los 3,08 años para los hombres y 1,93 años para las mujeres. La descomposición por edad mostró un cambio favorable a esta brecha desde las edades jóvenes a las mayores en los hombres, con pocos cambios en las mujeres. La descomposición por causas de muerte mostró una mayor contribución de las neoplasias y las enfermedades respiratorias y circulatorias. Hubo una tendencia a la baja en las causas externas en los hombres, y en las enfermedades infecciosas tanto en los hombres como en las mujeres, pero al alza en las enfermedades respiratorias para ambos sexos. Conclusiones: La estabilidad de la brecha de la esperanza de vida por nivel educativo durante el periodo analizado fue el resultado de una combinación de tendencias divergentes por edad y causas de muerte entre los niveles educativos altos y bajos.

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          Socioeconomic Inequalities in Health in 22 European Countries

          Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care. Copyright 2008 Massachusetts Medical Society.
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            Changes in mortality inequalities over two decades: register based study of European countries

            Objective To determine whether government efforts in reducing inequalities in health in European countries have actually made a difference to mortality inequalities by socioeconomic group. Design Register based study. Data source Mortality data by level of education and occupational class in the period 1990-2010, usually collected in a census linked longitudinal study design. We compared changes in mortality between the lowest and highest socioeconomic groups, and calculated their effect on absolute and relative inequalities in mortality (measured as rate differences and rate ratios, respectively). Setting All European countries for which data on socioeconomic inequalities in mortality were available for the approximate period between years 1990 and 2010. These included Finland, Norway, Sweden, Scotland, England and Wales (data applied to both together), France, Switzerland, Spain (Barcelona), Italy (Turin), Slovenia, and Lithuania. Results Substantial mortality declines occurred in lower socioeconomic groups in most European countries covered by this study. Relative inequalities in mortality widened almost universally, because percentage declines were usually smaller in lower socioeconomic groups. However, as absolute declines were often smaller in higher socioeconomic groups, absolute inequalities narrowed by up to 35%, particularly among men. Narrowing was partly driven by ischaemic heart disease, smoking related causes, and causes amenable to medical intervention. Progress in reducing absolute inequalities was greatest in Spain (Barcelona), Scotland, England and Wales, and Italy (Turin), and absent in Finland and Norway. More detailed studies preferably using individual level data are necessary to identify the causes of these variations. Conclusions Over the past two decades, trends in inequalities in mortality have been more favourable in most European countries than is commonly assumed. Absolute inequalities have decreased in several countries, probably more as a side effect of population wide behavioural changes and improvements in prevention and treatment, than as an effect of policies explicitly aimed at reducing health inequalities.
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              Measuring and explaining the change in life expectancies.

              A set of new indices for interpreting change in life expectancies, as well as a technique for explaining change in life expectancies by change in mortality at each age group are presented in the paper. The indices, as well as the new technique for explaining the differences in life expectancies, have been tested and examples using United States life tables are presented. The technique for explaining life expectancy differentials can be used for analyzing change in mortality or mortality differentials by sex, ethnicity, region, or any other subpopulations. The technique can be applied to life expectancies at birth or temporary life expectancies between any desirable ages.
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                Author and article information

                Journal
                gs
                Gaceta Sanitaria
                Gac Sanit
                Sociedad Española de Salud Pública y Administración Sanitaria (SESPAS) (Barcelona, Barcelona, Spain )
                0213-9111
                December 2022
                : 36
                : 6
                : 520-525
                Affiliations
                [2] Barcelona orgnameInstitut d'Investigació Biomèdica (IIB Sant Pau) Spain
                [4] Barcelona Cataluña orgnameUniversitat Pompeu Fabra orgdiv1Facultat de Ciències de la Salut i de la Vida orgdiv2Departament de Cièncias Experimentales i de la Salut Spain
                [1] Barcelona orgnameAgència de Salut Pública de Barcelona (ASBP) Spain
                [3] Madrid orgnameCIBER de Epidemiología y Salud Pública (CIBERESP) Spain
                Article
                S0213-91112022000600007 S0213-9111(22)03600600007
                10.1016/j.gaceta.2021.11.008
                35337685
                1d1bb651-92dd-4857-82a9-4759c8809cca

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 22 August 2021
                : 29 November 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 31, Pages: 6
                Product

                SciELO Spain

                Categories
                Original Articles

                Socioeconomic factors,Mortality,Life expectancy,Mortalidad,Factores socioeconómicos,Esperanza de vida

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