Johan P Mackenbach1, José Rubio Valverde2, Matthias Bopp3, Henrik Brønnum-Hansen4, Patrick Deboosere5, Ramune Kalediene6, Katalin Kovács7, Mall Leinsalu8, Pekka Martikainen9, Gwenn Menvielle10, Enrique Regidor11, Wilma J Nusselder2. 1. Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands. Electronic address: j.mackenbach@erasmusmc.nl. 2. Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands. 3. Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland. 4. Department of Public Health, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark. 5. Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium. 6. Lithuanian University of Health Sciences, Kaunas, Lithuania. 7. Hungarian Demographic Research Institute, Budapest, Hungary. 8. Stockholm Centre for Health and Social Change, Södertörn University, Stockholm, Sweden; Department of Epidemiology and Biostatistics, National Institute for Health Development, Tallinn, Estonia. 9. Department of Sociology, University of Helsinki, Helsnki, Finland. 10. INSERM, Sorbonne Universités, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France. 11. Department of Public Health & Maternal and Child Health, Faculty of Medicine, Universidad Complutense de Madrid, Madrid, Spain; CIBER Epidemiologí y Salud Püblica, Madrid, Spain.
Abstract
BACKGROUND: Socioeconomic inequalities in longevity have been found in all European countries. We aimed to assess which determinants make the largest contribution to these inequalities. METHODS: We did an international comparative study of inequalities in risk factors for shorter life expectancy in Europe. We collected register-based mortality data and survey-based risk factor data from 15 European countries. We calculated partial life expectancies between the ages of 35 years and 80 years by education and gender and determined the effect on mortality of changing the prevalence of eight risk factors-father with a manual occupation, low income, few social contacts, smoking, high alcohol consumption, high bodyweight, low physical exercise, and low fruit and vegetable consumption-among people with a low level of education to that among people with a high level of education (upward levelling scenario), using population attributable fractions. FINDINGS: In all countries, a substantial gap existed in partial life expectancy between people with low and high levels of education, of 2·3-8·2 years among men and 0·6-4·5 years among women. The risk factors contributing most to the gap in life expectancy were smoking (19·8% among men and 18·9% among women), low income (9·7% and 13·4%), and high bodyweight (7·7% and 11·7%), but large differences existed between countries in the contribution of risk factors. Sensitivity analyses using the prevalence of risk factors in the most favourable country (best practice scenario) showed that the potential for reducing the gap might be considerably smaller. The results were also sensitive to varying assumptions about the mortality risks associated with each risk factor. INTERPRETATION: Smoking, low income, and high bodyweight are quantitatively important entry points for policies to reduce educational inequalities in life expectancy in most European countries, but priorities differ between countries. A substantial reduction of inequalities in life expectancy requires policy actions on a broad range of health determinants. FUNDING: European Commission and Network for Studies on Pensions, Aging, and Retirement.
BACKGROUND: Socioeconomic inequalities in longevity have been found in all European countries. We aimed to assess which determinants make the largest contribution to these inequalities. METHODS: We did an international comparative study of inequalities in risk factors for shorter life expectancy in Europe. We collected register-based mortality data and survey-based risk factor data from 15 European countries. We calculated partial life expectancies between the ages of 35 years and 80 years by education and gender and determined the effect on mortality of changing the prevalence of eight risk factors-father with a manual occupation, low income, few social contacts, smoking, high alcohol consumption, high bodyweight, low physical exercise, and low fruit and vegetable consumption-among people with a low level of education to that among people with a high level of education (upward levelling scenario), using population attributable fractions. FINDINGS: In all countries, a substantial gap existed in partial life expectancy between people with low and high levels of education, of 2·3-8·2 years among men and 0·6-4·5 years among women. The risk factors contributing most to the gap in life expectancy were smoking (19·8% among men and 18·9% among women), low income (9·7% and 13·4%), and high bodyweight (7·7% and 11·7%), but large differences existed between countries in the contribution of risk factors. Sensitivity analyses using the prevalence of risk factors in the most favourable country (best practice scenario) showed that the potential for reducing the gap might be considerably smaller. The results were also sensitive to varying assumptions about the mortality risks associated with each risk factor. INTERPRETATION: Smoking, low income, and high bodyweight are quantitatively important entry points for policies to reduce educational inequalities in life expectancy in most European countries, but priorities differ between countries. A substantial reduction of inequalities in life expectancy requires policy actions on a broad range of health determinants. FUNDING: European Commission and Network for Studies on Pensions, Aging, and Retirement.
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Authors: Paolo Vineis; Mauricio Avendano-Pabon; Henrique Barros; Mel Bartley; Cristian Carmeli; Luca Carra; Marc Chadeau-Hyam; Giuseppe Costa; Cyrille Delpierre; Angelo D'Errico; Silvia Fraga; Graham Giles; Marcel Goldberg; Michelle Kelly-Irving; Mika Kivimaki; Benoit Lepage; Thierry Lang; Richard Layte; Frances MacGuire; Johan P Mackenbach; Michael Marmot; Cathal McCrory; Roger L Milne; Peter Muennig; Wilma Nusselder; Dusan Petrovic; Silvia Polidoro; Fulvio Ricceri; Oliver Robinson; Silvia Stringhini; Marie Zins Journal: Front Public Health Date: 2020-05-12
Authors: Wilma J Nusselder; José Rubio Valverde; Matthias Bopp; Henrik Brønnum-Hansen; Patrick Deboosere; Ramune Kalediene; Katalin Kovács; Mall Leinsalu; Pekka Martikainen; Gwenn Menvielle; Enrique Regidor; Bodgan Wojtyniak; Johan P Mackenbach Journal: Eur J Public Health Date: 2021-07-13 Impact factor: 3.367
Authors: Mariana Haeberer; Inmaculada León-Gómez; Beatriz Pérez-Gómez; María Téllez-Plaza; Mónica Pérez-Ríos; Anna Schiaffino; Fernando Rodríguez-Artalejo; Iñaki Galán Journal: PLoS One Date: 2020-09-28 Impact factor: 3.240