scholarly journals Gap in life expectancy at age 30 by sex and educational level, 2012 (or latest year)

2015 ◽  
Keyword(s):  
Life Expectancy ◽  
Educational Level

Persistent social inequality in life expectancy and disability-free life expectancy: Outlook for a differential pension age in Denmark?

2016 ◽  
Vol 45 (4) ◽  
pp. 459-462 ◽  
Author(s):  
Henrik Brønnum-Hansen ◽  
Mette Lindholm Eriksen ◽  
Karen Andersen-Ranberg ◽  
Bernard Jeune
Keyword(s):  
Life Expectancy ◽  
Social Inequality ◽  
Educational Level ◽  
Average Life Expectancy ◽  
Men And Women ◽  
Level Of Education ◽  
Disability Free Life Expectancy ◽  
Low Levels ◽  
Pension Age ◽  
Old Men

Aims: The state old-age pension in Denmark increases to keep pace with the projected increase in average life expectancy (LE) without any regard to the social gap in LE and expected lifetime in good health. The purpose of this study was to compare changes in LE and disability-free life expectancy (DFLE) between groups of Danes with high, medium and low levels of education. Methods: Nationwide register data on education and mortality were combined with data from the Surveys of Health, Ageing and Retirement in Europe (SHARE) surveys in 2006–2007, 2010–2011 and 2013–2014 and the DFLE by educational level was estimated by Sullivan’s method for each of these three time points. Results: Between 2006–2007 and 2013–2014, LE among 65-year-old men and women with a low educational level increased by 1.3 and 1.0 years, respectively, and by 1.4 and 1.3 years for highly educated men and women. The gap in LE between people with high and low levels of education remained more than 2 years. In 2006–2007, 65-year-old men with a high level of education could expect 3.2 more years without disability than men of the same age with a low level of education. In 2013–2014, the difference was 2.9 years. For women, the results were 3.7 and 3.4 years, respectively. Conclusions: With the persistent social inequality in LE of more than 2 years and the continuous gap between high and low educational groups in DFLE of about 3 years, a differential pension age is recommended.

scholarly journals Rising Educational Levels Contribute to Compression of Morbidity. A Multi-State Life Table Analysis of the Netherlands 1995-2015

2002 ◽  
pp. 77-96
Author(s):  
E. Kunst Anton ◽  
M. A. Joung Inez ◽  
J. Nusselder Wilma ◽  
W. N. Looman Caspar ◽  
P. Mackenbach Johan
Keyword(s):  
Life Expectancy ◽  
Educational Level ◽  
Total Population ◽  
The Elderly ◽  
Transition Rates ◽  
Compression Of Morbidity ◽  
Increase Life Expectancy ◽  
Male Population ◽  
Educational Levels ◽  
Table Analysis

Objective: This paper assesses whether the future rise in educational levels of theelderly may not only increase life expectancy (LE) but also at the same timecontribute to a reduction in life expectancy with disability (LED).Methods: For each educational level, LE and LED were estimated from multi-statelife tables with a disabled and non-disabled state. Basic transition rates wereestimated from regression analysis of data of a Dutch longitudinal study. The resultsper educational level were aggregated to the total population for the years 1995,2005 and 2015.Results: In 1995, men in the highest educational level had a 0.9 years longerLE and a 5.4 years shorter LED than men in the lowest level. Differences amongwomen were larger (2.0 and 8.3 years). Due to rising educational levels between1995 and 2015, LE for the total male population would increase by 0.2 years whileLED would decrease by 0.5 years. A larger effect was observed for women(0.2 and 1.5 years).Conclusion: Rising educational levels of the elderly are likely to contribute to acompression of morbidity over the next decades, especially among women.

scholarly journals Trends in remaining life expectancy at retirement age (65 years) by educational level in Norway 1961-2009

2012 ◽  
Vol 22 (2) ◽  
Author(s):  
Joakim Oliu Moe ◽  
Ólöf Anna Steingrímsdóttir ◽  
Bjørn Heine Strand ◽  
Øyvind Næss
Keyword(s):  
Life Expectancy ◽  
Educational Level ◽  
Least Square ◽  
Remaining Life ◽  
Individual Level ◽  
Level Data ◽  
Life Years ◽  
Educational Groups ◽  
Remaining Life Expectancy ◽  
The Difference

<p><em><strong>Background</strong></em>: Over the last half a century education based inequalities in life expectancy have increased in younger populations, but our knowledge of long-term trends in old-age life expectancy differentials is sparse. We investigated the trends in remaining life expectancy at age 65 (e65) according to education in Norway for the period 1961-2009.</p><p><em><strong>Methods</strong></em>: This was a register-based population study including all Norwegian residents aged 65 years and older. Individual-level data were provided by the Central Population Registry and the National Educational Database. We classified education into higher and lower education and constructed one life table for each calendar year, sex, and educational group. We tested for trends using weighted least square regression models.</p><p><em><strong>Results</strong></em>: e65 increased over the observation period for all educational groups, but the difference in e65 increased by 0.060 life years per calendar year in men and 0.025 life years per calendar year in women (P &lt; 0.001). The increase in e65 in less-educated men slowed in the 1980s and 1990s, whereas e65 in less-educated women decelerated from the 1980s, and significantly so from 2001 (P = 0.029).</p><p><em><strong>Conclusions</strong></em>: Educational-based inequalities in e65 increased over the last half century. The increase seems to be temporal in men and might be ongoing in women. Increasing inequalities in e65 challenge public health policy and will become increasingly important in the ageing societies of the future. In addition, they imply increasing deviation from the overall life expectancy of the population, which forms the basis of the recently implemented adjustment of pension levels according to life expectancy. Divergent trends in e65 according to educational level may also have implications for future demographic projections.</p>

scholarly journals Health inequalities in the Netherlands: trends in quality-adjusted life expectancy (QALE) by educational level

2016 ◽  
Vol 26 (5) ◽  
pp. 794-799 ◽  
Author(s):  
Maria Gheorghe ◽  
Parida Wubulihasimu ◽  
Frederik Peters ◽  
Wilma Nusselder ◽  
Pieter H.M. Van Baal
Keyword(s):  
Life Expectancy ◽  
The Netherlands ◽  
Health Inequalities ◽  
Educational Level ◽  
Quality Adjusted Life

scholarly journals Spatial inequalities in life expectancy related to educational level in the urban context of Rome

2017 ◽  
Vol 27 (suppl_3) ◽  
Author(s):  
C De Vito ◽  
G Migliara ◽  
LM Salvatori ◽  
M Marceca ◽  
L Paglione
Keyword(s):  
Life Expectancy ◽  
Educational Level ◽  
Urban Context ◽  
Spatial Inequalities

scholarly journals Socioeconomic Position Across the Life Course and Trends in Disability-Free Life Expectancy in Australia

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 641-641
Author(s):  
Kim Kiely ◽  
Richard Tawiah ◽  
Carol Jagger ◽  
Kaarin Anstey
Keyword(s):  
Life Expectancy ◽  
Life Course ◽  
Social Mobility ◽  
Educational Level ◽  
Early Life ◽  
Low Education ◽  
Disability Free Life Expectancy ◽  
Lower Education ◽  
Years Lived With Disability ◽  
The Life Course

Abstract There has been little investigation of how life-course social mobility is linked to Disability-Free Life Expectancy (DFLE). We report novel analysis of the HILDA survey examining how DFLE trends differs by three markers of socio-economic position (SEP): early-life (educational attainment), midlife (occupational level), and late-life (area-disadvantage). All women, irrespective of their educational level, gained years with disability (Age 65: Low education=1.5 and High education=2.5 years). Similar results were obtained by level of occupation, but women with low occupation showed small declines in LE (-0.8 years), all being losses in DFLE. Only women in the most advantaged areas gained DFLE. For men, higher levels of any marker of SEP were associated with DFLE gains that were larger than, or comparable to, gains in years lived with disability, although lower education was associated only with gains in years lived with disability. DFLE trends differ by SEP marker more in women than men.

Shorter Lives with Poor Health: The Toll on Spain’s Less Educated Population

2021 ◽  
pp. 1-4
Author(s):  
Amand Blanes ◽  
Sergi Trias-Llimós
Keyword(s):  
Life Expectancy ◽  
Educational Level ◽  
Social Inequalities ◽  
High Educational Level ◽  
Inequalities In Health ◽  
The Social ◽  
Low Levels ◽  
Health And Mortality ◽  
High Educational

More than three years separate life expectancy at the age of 30 in more educated groups compared with those with low levels of education. Recent decades have seen considerable advances in the longevity of the Spanish population but these improvements mask the persistence of significant inequalities in health and mortality. Socioeconomic level is a discriminating factor in the health status of individuals throughout their lives and education is one of the most frequently used indicators in studies on social inequalities in health and mortality. In addition to being an indirect variable of the socioeconomic situation, educational level largely conditions the lifestyles and health preferences of individuals as well as their use of the resources of the social and healthcare system. In this issue of Perspectives Demogràfiques, we discuss the present-day differences in health and mortality in Spain according to educational level. These inequalities can be summarised as a threefold penalisation of less educated individuals in comparison with those with a high educational level: a) lower life expectancy; b) greater inequality in age at death; and c) a smaller proportion of years with quality of life.

Appreciations for the Role of Sensors in Everyday Life Against the Aging Population

2021 ◽  
pp. 246-270
Author(s):  
Adriana Elena Micsa
Keyword(s):  
Life Expectancy ◽  
Social Security ◽  
Everyday Life ◽  
Detailed Analysis ◽  
Educational Level ◽  
Daily Life ◽  
Aging Population ◽  
Mortality Rates ◽  
Modern Equipment

The focus of this chapter is on the sensor within an aging population. The study involves a detailed analysis of applications with sensors and the effects of their use in the basic sectors of society, such as economic, educational, medical, social security system, social, and cultural activities. After a faithful presentation of the notion of sensor, the work makes a foray into contemporary technical history starting with the appearance of sensors, selects and appreciates some characteristic and edifying parameters of daily life from the beginning of the period of using the sensors; these parameters refer to living standards, health standards, mortality rates, life expectancy, birth rate, occupations by sex and age, educational level of individuals, employment, degree of development of a professions, the interest of the population for a certain type of product, and the tendency to use modern equipment by fields of activity by geographical areas.

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