Socio-Economic Inequalities in Life Expectancy and Health Expectancy at Age 50 and over in European Countries.

2019 ◽  
Vol 68 (4) ◽  
pp. 255-288 ◽  
Author(s):  
Isabel Mosquera ◽  
Yolanda González-Rábago ◽  
Unai Martín ◽  
Amaia Bacigalupe
Keyword(s):  
Life Expectancy ◽  
Good Health ◽  
Socioeconomic Inequalities ◽  
Systematic Search ◽  
European Countries ◽  
Health Expectancy ◽  
Lower Percentage ◽  
Retirement Age ◽  
Review Of The Literature ◽  
Demographic Ageing

Abstract Based on the demographic ageing, many European governments have modified the statutory retirement age. However, in general, life expectancy (LE) and health expectancy (HE) are not uniformly distributed, being both lower among the least advantaged groups. Thus, a systematic search and review of the literature has been conducted to identify socioeconomic inequalities in LE and HE at age 50 and over in European countries. Twenty-nine studies were included in the review. Across Europe, people in a more advantaged position can expect to live longer, more years in good health and less in bad health, and therefore a lower percentage of their lives in bad health. Zusammenfassung: Sozioökonomische Ungleichheiten in der Lebens- und Gesundheitserwartung im Alter von 50 und älter in Europäischen Ländern. Erkenntnisse für die Debatte der Rentenpolitik Vor dem Hintergrund der demographischen Alterung haben viele europäische Regierungen das Renteneintrittsalter modifiziert. Allerdings sind Lebensund Gesundheitserwartungen nicht gleichmäßig verteilt, sondern sind in benachteiligten Bevölkerungsgruppen niedriger. Um sozioökonomische Ungleichheiten in der Lebens- und Gesundheitserwartung von Individuen im Alter von 50 Jahren und älter zu betrachten, wurde eine systematische Suche und Begutachtung der Literatur in den europäischen Ländern durchgeführt. Es wurden 29 Studien in der Begutachtung miteinbezogen. Es zeigt sich, dass Individuen in vorteilhaften Positionen erwarten können länger zu leben, länger gesund zu sein und weniger häufig einen schlechten Gesundheitszustand aufweisen, was der Grund dafür ist, dass sie auch einen geringeren Anteil ihrer Lebenszeit in schlechter Gesundheit verbringen.

scholarly journals Proposals to Restructure Social Security

1996 ◽  
Vol 10 (3) ◽  
pp. 67-88 ◽  
Author(s):  
Peter A Diamond
Keyword(s):  
Life Expectancy ◽  
Social Security ◽  
European Countries ◽  
Retirement Age ◽  
Retirement Savings ◽  
Partial Privatization ◽  
Trust Funds

This paper discusses five proposed changes in Social Security: indexing the normal retirement age to life expectancy (as Sweden is doing); investing part of the trust funds in private securities; partial privatization (as has been proposed by Senators Kerrey and Simpson, Sweden is doing and Mexico has done); replacing Social Security by individually mandated savings (as was done in Chile in 1981); and mandating employer provided retirement savings (as recently legislated in Australia and is effectively the case in some European countries.) The economics of Social Security and the politics of restoring (and preserving) actuarial balance are discussed.

scholarly journals On the measurement of healthy lifespan inequality

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Iñaki Permanyer ◽  
Jeroen Spijker ◽  
Amand Blanes
Keyword(s):  
Life Expectancy ◽  
Average Length ◽  
Functional Limitation ◽  
Good Health ◽  
Life Extension ◽  
Health Expectancy ◽  
Highly Educated ◽  
Low Educated ◽  
Contemporary Spain ◽  
Length Of Life

Abstract Background Current measures to monitor population health include indicators of (i) average length-of-life (life expectancy), (ii) average length-of-life spent in good health (health expectancy), and (iii) variability in length-of-life (lifespan inequality). What is lacking is an indicator measuring the extent to which healthy lifespans are unequally distributed across individuals (the so-called ‘healthy lifespan inequality’ indicators). Methods We combine information on age-specific survival with the prevalence of functional limitation or disability in Spain (2014–2017) by sex and level of education to estimate age-at-disability onset distributions. Age-, sex- and education-specific prevalence rates of adult individuals’ daily activities limitations were based on the GALI index derived from Spanish National Health Surveys held in 2014 and 2017. We measured inequality using the Gini index. Results In contemporary Spain, education differences in health expectancy are substantial and greatly exceed differences in life expectancy. The female advantage in life expectancy disappears when considering health expectancy indicators, both overall and across education groups. The highly educated exhibit lower levels of lifespan inequality, and lifespan inequality is systematically higher among men. Our new healthy lifespan inequality indicators suggest that the variability in the ages at which physical daily activity limitations start are substantially larger than the variability in the ages at which individuals die. Healthy lifespan inequality tends to decrease with increasing educational attainment, both for women and for men. The variability in ages at which physical limitations start is slightly higher for women than for men. Conclusions The suggested indicators uncover new layers of health inequality that are not traceable with currently existing approaches. Low-educated individuals tend to not only die earlier and spend a shorter portion of their lives in good health than their highly educated counterparts, but also face greater variation in the eventual time of death and in the age at which they cease enjoying good health—a multiple burden of inequality that should be taken into consideration when evaluating the performance of public health systems and in the elaboration of realistic working-life extension plans and the design of equitable pension reforms.

scholarly journals Determinants Of Healthy Ageing For Older People In European Countries – A Spatio-Temporal Approach

2017 ◽  
Vol 19 (5) ◽  
pp. 157-178 ◽  
Author(s):  
Jadwiga Suchecka ◽  
Bogusława Urbaniak
Keyword(s):  
Health Care ◽  
Economic Development ◽  
Life Expectancy ◽  
European Commission ◽  
Good Health ◽  
Healthy Ageing ◽  
European Countries ◽  
Men And Women ◽  
Active And Healthy Ageing ◽  
Life Years

The European Commission (EC) has identified active and healthy ageing (AHA) as a major societal challenge mutual to European countries. This issue has increased in importance due to the progressive ageing observed in European societies, that force authorities to take initiatives for support the activity of the elderly. One of the initiatives, widely recognised is The European Innovation Partnership on Active and Healthy Ageing, which strive to enabling EU citizens to lead healthy, active and independent lives while ageing. The positive effect of actions for the AHA will be extension of the life in good health duration of EU citizens by two years by 2020. This is an important issue, as in 2013, women who have reached the age of 65 years in UE28 were facing on average 21.3 years of further life years and only 8.6 years (on average this amounted for 40.4 % of life expectancy) accounted for living in health, whereas for males, this ratio was estimated on 8.5 years in health of the anticipated further 17.9 years (47.5% of further life duration). Life expectancy in good health in older age is influenced by many different factors, i.e. cultural, social, economic and accessibility to health services and the quality of provided treatment. The last aspect is related to both the economic development of the country and the health care system management. The significant factor that has been increasingly emphasised in documentation of World Health Organisation or European Commission, concerns the investment in public and individual health. Taking into account the multivariate impact of objective and subjective factors on life expectancy in good health of elderly, the Authors decided to conduct the multidimensional comparative analysis for EU countries, including Norway, Switzerland and Iceland as well. Among the objective factors Authors distinguished: proportion of population (men and women) aged 65 years and more, economic development of the countries measured by GDP per capita, healthy life years expectancy in absolute values for males and females at 65 years, health care expenditures in PPS per inhabitant aged 65+, whereas the group of subjective characteristics consisted of: self-perceived health for people aged 65+ and self-reported unmet needs for medical services. The article aims to investigate the relationship between the length of the further life in healthy for men and women aged 65 years and selected factors in European countries in the period 2005–2012. For this purpose, following methods were used: 1/ spatial distribution of characteristics – rates of change in selected periods: 2005 and 2012, 2/ tests for dependencies using correlograms and Spearman’s rank correlation coefficients, 3/ cluster analysis: on the basis of Ward’s methods spatial similarities (among countries) were indicated. As the source of data the Eurostat database were used.

scholarly journals Health expectancy indicators: what do they measure?

2021 ◽  
Author(s):  
Vanessa di Lego
Keyword(s):  
Life Expectancy ◽  
Information Source ◽  
Health Indicators ◽  
European Countries ◽  
World Health ◽  
Health Expectancy ◽  
Total Life Expectancy ◽  
Life Years ◽  
Z Scores ◽  
European Health

Abstract Background Health expectancy indicators aim at capturing the quality dimension of total life expectancy.; however, the underlying approach, definition of health, and information source differ considerably among the indicators available. Objective (1) Review the main concepts and approaches used to estimate health expectancy focusing on two widely used European health indicators: Health-Adjusted Life Expectancy (HALE) and Healthy Life Years (HLY); (2) identify underlying differences between the results yielded by these two indicators. Method Statistical differences between the HALE and HLY indicators by sex at ages 50, 60, and 70 were tested using pairwise and global Student´s t-tests and z-scores based on standard deviation. Data for 29 European countries were collected from the European Health Expectancy Monitoring Unit (EHEMU) information system and the World Health Organization (WHO) Global Burden of Disease Study 2016 (GBD 2016). Results The HALE indicator estimates were smoother across European countries compared with those of the HLY indicator, present a narrower sex gap in morbidity, higher z-scores compared with the average distribution across Europe, and results less sensitive to cross-national variations. Conclusion The HALE estimates indicate that morbidity is more compressed for both sexes, whereas the HLY estimates suggest that morbidity is more compressed for males but more expanded for females. These contrasting results demonstrate that health expectancy indicators should be interpreted with caution.

scholarly journals Differentiating retirement age to compensate for health differences

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Vincent Vandenberghe
Keyword(s):  
Population Aging ◽  
Good Health ◽  
European Countries ◽  
Retirement Age ◽  
Health Differences ◽  
Gender Education ◽  
The Moment ◽  
Degree Of Differentiation ◽  
High Degree ◽  
Very High

Abstract Population aging in Europe calls for an overall rise in the age of retirement. However, most observers agree that the latter should be differentiated to account for different individuals’ heterogeneous health when they grow older. This paper explores the relevance of this idea using the European Survey of Health, Ageing and Retirement in Europe (SHARE) panel data. It first quantifies the health gradient across and within each of the European countries across sociodemographic groups (i.e., Gender × Education) at typical retirement age. It then estimates the degree of retirement age differentiation that would be needed to equalize expected health at the moment of retirement. Results point at the need for a very high degree of differentiation to equalize expected health, both across and within, European countries. But the paper also shows that systematic retirement age differentiation would fail to match a significant portion of the full distribution of health status. In a world synonymous with systematic health-based retirement age differentiation, there would still be a lot of what health economists call F-mistakes ([F]ailure of treatment, i.e., no retirement for people in poor health) and E-mistakes ([E]xcessive treatment, i.e., people in good health going for retirement).

scholarly journals Investigator Initiated Clinical Trials (IICTs): A Systematic Search in Registries to Compare the Czech Republic and Portugal in Terms of Funding Policies and Scientific Outcomes

2021 ◽  
Author(s):  
C. Madeira ◽  
L. Hořavová ◽  
F. dos Santos ◽  
J. R. Batuca ◽  
K. Nebeska ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Czech Republic ◽  
Clinical Research ◽  
Systematic Search ◽  
European Countries ◽  
The Czech Republic ◽  
Research Outcomes ◽  
Funding Policies ◽  
Funding Agencies ◽  
First Time

Abstract Objectives Clinical trials provide one of the highest levels of evidence to support medical practice. Investigator initiated clinical trials (IICTs) answer relevant questions in clinical practice that may not be addressed by industry. For the first time, two European Countries are compared in terms of IICTs, respective funders and publications, envisaging to inspire others to use similar indicators to assess clinical research outcomes. Methods A retrospective systematic search of registered IICTs from 2004 to 2017, using four clinical trials registries was carried out in two European countries with similar population, GDP, HDI and medical schools but with different governmental models to fund clinical research. Each IICT was screened for sponsors, funders, type of intervention and associated publications, once completed. Results IICTs involving the Czech Republic and Portugal were n = 439 (42% with hospitals as sponsors) and n = 328 (47% with universities as sponsors), respectively. The Czech Republic and Portuguese funding agencies supported respectively 61 and 27 IICTs. Among these, trials with medicinal products represent 52% in Czech Republic and 4% in Portugal. In the first, a higher percentage of IICTs’ publications in high impact factor journals with national investigators as authors was observed, when compared to Portugal (75% vs 15%). Conclusion The better performance in clinical research by Czech Republic might be related to the existence of specific and periodic funding for clinical research, although further data are still needed to confirm this relationship. In upcoming years, the indicators used herein might be useful to tracking clinical research outcomes in these and other European countries.

scholarly journals Changing Educational Gradients in Life Expectancy With and Without Disease Among U.S. Older Adults From 2000 to 2010

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 505-505
Author(s):  
Matthew Farina ◽  
Phillip Cantu ◽  
Mark Hayward
Keyword(s):  
Older Adults ◽  
Life Expectancy ◽  
Chronic Diseases ◽  
Population Aging ◽  
Good Health ◽  
Vital Statistics ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Education Group ◽  
Education Groups

Abstract Recent research has documented increasing education inequality in life expectancy among U.S. adults; however, much is unknown about other health status changes. The objective of study is to assess how healthy and unhealthy life expectancies, as classified by common chronic diseases, has changed for older adults across education groups. Data come from the Health and Retirement Study and National Vital Statistics. We created prevalence-based life tables using the Sullivan method to assess sex-specific life expectancies for stroke, heart disease, cancer, and arthritis by education group. In general, unhealthy life expectancy increased with each condition across education groups. However, the increases in unhealthy life expectancy varied greatly. While stroke increased by half a year across education groups, life expectancy with diabetes increased by 3 to 4 years. In contrast, the evidence for healthy life expectancy provides mixed results. Across chronic diseases, healthy life expectancy decreased by 1 to 3 years for respondents without a 4-year degree. Conversely, healthy life expectancy increased for the college educated by .5 to 3 years. While previous research shows increases in life expectancy for the most educated, trends in life expectancy with chronic conditions is less positive: not all additional years are in lived in good health. In addition to documenting life expectancy changes across education groups, research assessing health of older adults should consider the changing inequality across a variety of health conditions, which will have broad implications for population aging and policy intervention.

scholarly journals Disaggregation of official demographic projections in sub-groups by education level: the neglected “composition effect” in the future path of life expectancy

Genus ◽  
2021 ◽  
Vol 77 (1) ◽  
Author(s):  
Sergio Ginebri ◽  
Carlo Lallo
Keyword(s):  
High Education ◽  
Life Expectancy ◽  
Education Level ◽  
Retirement Age ◽  
Composition Effect ◽  
Education Group ◽  
Population Forecasts ◽  
Low Education ◽  
Mortality Differential ◽  
Education Groups

AbstractWe developed an innovative method to break down official population forecasts by educational level. The mortality rates of the high education group and low education group were projected using an iterative procedure, whose starting point was the life tables by education level for Italy, based on the year 2012. We provide a set of different scenarios on the convergence/divergence of the mortality differential between the high and low education groups. In each scenario, the demographic size and the life expectancy of the two sub-groups were projected annually over the period 2018–2065. We compared the life expectancy paths in the whole population and in the sub-groups. We found that in all of our projections, population life expectancy converges to the life expectancy of the high education group. We call this feature of our outcomes the “composition effect”, and we show how highly persistent it is, even in scenarios where the mortality differential between social groups is assumed to decrease over time. In a midway scenario, where the mortality differential is assumed to follow an intermediate path between complete disappearance in year 2065 and stability at the 2012 level, and in all the scenarios with a milder convergence hypothesis, our “composition effect” prevails over the effect of convergence for men and women. For instance, assuming stability in the mortality differential, we estimated a life expectancy increase at age 65 of 2.9 and 2.6 years for men, and 3.2 and 3.1 for women, in the low and high education groups, respectively, over the whole projection period. Over the same period, Italian official projections estimate an increase of 3.7 years in life expectancy at age 65 for the whole population. Our results have relevant implications for retirement and ageing policies, in particular for those European countries that have linked statutory retirement age to variations in population life expectancies. In all the scenarios where the composition effect is not offset by a strong convergence of mortality differentials, we show that the statutory retirement age increases faster than the group-specific life expectancies, and this finding implies that the expected time spent in retirement will shrink for the whole population. This potential future outcome seems to be an unintended consequence of the indexation rule.

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