On the measurement of healthy lifespan inequality

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.

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Healthy life expectancy in Brazil: applying the Sullivan method

Cadernos de Saúde Pública ◽

10.1590/s0102-311x2005000700002 ◽

2005 ◽

Vol 21 (suppl 1) ◽

pp. S7-S18 ◽

Cited By ~ 27

Author(s):

Dalia Elena Romero ◽

Iúri da Costa Leite ◽

Célia Landmann Szwarcwald

Keyword(s):

Life Expectancy ◽

Functional Limitation ◽

Good Health ◽

World Health ◽

Healthy Life Expectancy ◽

State Of Health ◽

World Health Survey ◽

Healthy Life ◽

Mortality And Morbidity ◽

Sullivan Method

The objective of this study is to present the method proposed by Sullivan and to estimate the healthy life expectancy using different measures of state of health, based on information from the World Health Survey carried out in Brazil in 2003. By combining information on mortality and morbidity into a unique indicator, simple to calculate and easy to interpret, the Sullivan method is currently the one most commonly used for estimating healthy life expectancy. The results show higher number of healthy years lost if there is a long-term disease or disability that limits daily activities, regardless of the difficulty in performing such activities or the severity of the functional limitations. The two measures of healthy life expectancy adjusted by the severity of functional limitation show results very similar to estimates based on the perception of state of health, especially in advanced age. It was also observed, for all measures used, that the proportion of healthy years lost increases significantly with age and that, although females have higher life expectancy than males, they live proportionally less years in good health.

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Narrowing sex differences in life expectancy: regional variations, 1971-1991

Canadian Studies in Population ◽

10.25336/p6130b ◽

2001 ◽

Vol 28 (1) ◽

pp. 89 ◽

Cited By ~ 6

Author(s):

Frank Trovato ◽

N. M. Lalu

Keyword(s):

Sex Differences ◽

Life Expectancy ◽

Gender Gap ◽

Prince Edward Island ◽

Causes Of Death ◽

Average Length ◽

Decomposition Analysis ◽

Relative Contribution ◽

Life Expectancy At Birth ◽

Length Of Life

A number of industrialized nations have recently experienced some degrees of constriction in their long-standing sex differentials in life expectancy at birth. In this study we examine this phenomenon in the context of Canada’s regions between 1971 and 1991: Atlantic (Newfoundland, Nova Scotia, New Brunswick, Prince Edward Island); Quebec, Ontario, and the West (Manitoba, Saskatchewan, Alberta, British Columbia, Yukon and Northwest Territories). Decomposition analysis based on multiple decrement life tables is applied to address three questions: (1) Are there regional differentials in the degree of narrowing in the sex gap in life expectancy? (2) What is the relative contribution of major causes of death to observed sex differences in average length of life within and across regions? (3) How do the contributions of cause-of-death components vary across regions to either widen or narrow the sex gap in survival? It is shown that the magnitude of the sex gap is not uniform across the regions, though the differences are not large. The most important contributors to a narrowing of the sex gap in life expectancy are heart disease and external types of mortality (i.e., accidents, violence, and suicide), followed by lung cancer and other types of chronic conditions. In substantive terms these results indicate that over time men have been making sufficient gains in these causes of death as to narrow some of the gender gap in overall survival. Regions show similarity in these effects.

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Longevity and Education: A Demographic Perspective

Gerontology ◽

10.1159/000438901 ◽

2015 ◽

Vol 62 (3) ◽

pp. 253-262 ◽

Cited By ~ 10

Author(s):

Domantas Jasilionis ◽

Vladimir M. Shkolnikov

Keyword(s):

Life Expectancy ◽

Best Practice ◽

National Level ◽

Population Level ◽

Reliable Data ◽

Human Longevity ◽

Evidence Based ◽

Highly Educated ◽

Level Statistics ◽

Length Of Life

In the second half of the 20th century, the advances in human longevity observed have been accompanied by an increase in the disparities between countries and regions. Education is one of the strongest predictors of life expectancy. Studies have shown that both relative and absolute mortality differences by education within countries have been increasing, even in the most developed and egalitarian countries. It is possible to assume that groups of highly educated people who systematically display life expectancy levels which are higher than the observed best practice (record) life expectancy at the national level are vanguards who are leading the way toward a lengthening of life for the remaining population groups. This evidence based on population-level statistics and exploring an important single factor could inspire further discussion about the possibilities for extending human length of life at the national level. However, more comprehensive and reliable data covering a larger number of countries and more covariates are needed for understanding health effects of education and prospects of human longevity.

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

Sozialer Fortschritt ◽

10.3790/sfo.68.4.255 ◽

2019 ◽

Vol 68 (4) ◽

pp. 255-288 ◽

Cited By ~ 2

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.

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Life expectancy at birth and life disparity: an assessment of sex differentials in mortality in India

International Journal of Population Studies ◽

10.18063/ijps.2016.01.005 ◽

2016 ◽

Vol 2 ◽

Cited By ~ 3

Author(s):

Akansha Singh ◽

Laishram Ladusingh

Keyword(s):

Life Expectancy ◽

Rural Areas ◽

Urban Areas ◽

Average Length ◽

Adult Mortality ◽

Life Tables ◽

Life Expectancy At Birth ◽

Replacement Algorithm ◽

Sex Differentials ◽

Length Of Life

This study aims to examine the sex differentials in life expectancy at birth and life disparity, and to estimate the age-specific contribution of the differences for India and its major states. Life dispari-ty measures the variation in the distribution of deaths, and life expectancy at birth measures the average length of life. Complete life tables generated from death rates and abridged life tables of the Sample Reg-istration System in India from 1970–1975 to 2006–2010 were used to fulfill the research goals. Stepwise replacement algorithm was used for the decomposition of sex differences in life expectancy at birth and in life disparity. The results indicate that the increase in life expectancy at birth and decline in life disparity was higher for females. The sex differential was more prominent in urban areas than in rural areas. A ma-jority of the states in India experienced changes in the direction and magnitude of sex differentials in life expectancy at birth and life disparity from 1970–1975 to 2006–2010. The sex differentials in life expec-tancy at birth and life disparity in 1970–1975 were primarily attributed to child mortality, whereas the sex differentials in recent decades were attributed to adult mortality.

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Reflection on modern methods: cause of death decomposition of cohort survival comparisons

International Journal of Epidemiology ◽

10.1093/ije/dyz276 ◽

2020 ◽

Vol 49 (5) ◽

pp. 1712-1718

Author(s):

Vladimir Canudas-Romo ◽

Tim Adair ◽

Stefano Mazzuco

Keyword(s):

Life Expectancy ◽

Time Trends ◽

Causes Of Death ◽

Average Length ◽

Major Contributor ◽

Cross Sectional ◽

Disease Mortality ◽

Modern Methods ◽

Length Of Life ◽

Cross Sectional Average

Abstract Life expectancy is most commonly measured for a period (corresponding to mortality within a given year) or for a specific birth cohort. Although widely used, period and cohort life expectancy have limitations as their time-trends often show disparities and can mask the historical mortality experience of all cohorts present at a given time. The truncated cross-sectional average length of life, or TCAL, is a period measure including all available cohort mortality information, irrespective of whether all cohort members have died. It is particularly useful for comparing cohort mortality between populations. This study extends TCAL by disentangling causes of death contributions. The strength of the approach is that it allows identification of mortality differences in cohorts with members still alive, as well as identification of which ages and causes of death contribute to mortality differentials between populations. Application of the method to Japan shows that over the period 1950–2014 a major contributor to TCAL differences with other high-longevity countries was its lower cardiovascular disease mortality.

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

Innovation in Aging ◽

10.1093/geroni/igaa057.1630 ◽

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.

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