Relationships between period and cohort life expectancy: gaps and lags

This paper offers an empirical and analytic foundation for regarding period life expectancy as a lagged indicator of the experience of real cohorts in populations experiencing steady improvement in mortality. We find that current period life expectancy in the industrialized world applies to cohorts born some 40-50 years ago. Lags track an average age at which future years of life are being gained, in a sense that we make precise. Our findings augment Ryder's classic results on period-cohort translation.     

Relationships between period and cohort life expectancy: Gaps and lags

This paper offers an empirical and analytic foundation for regarding period life expectancy as a lagged indicator of the experience of real cohorts in populations experiencing steady improvement in mortality. We find that current period life expectancy in the industrialized world applies to cohorts born some 40–50 years ago. Lags track an average age at which future years of life are being gained, in a sense that we make precise. Our findings augment Ryder's classic results on period–cohort translation.     

Trends in senescent life expectancy

The distinction between senescent and non-senescent mortality proves to be very valuable for describing and analysing age patterns of death rates. Unfortunately, standard methods for estimating these mortality components are lacking. The first part of this paper discusses alternative methods for estimating background and senescent mortality among adults and proposes a simple approach based on death rates by causes of death. The second part examines trends in senescent life expectancy (i.e., the life expectancy implied by senescent mortality) and compares them with trends in conventional longevity indicators between 1960 and 2000 in a group of 17 developed countries with low mortality. Senescent life expectancy for females rises at an average rate of 1.54 years per decade between 1960 and 2000 in these countries. The shape of the distribution of senescent deaths by age remains relatively invariant while the entire distribution shifts over time to higher ages as longevity rises.     

Trends in life expectancy in wellbeing

Objectives: This paper describes anddiscusses trends in life expectancy inwellbeing between 1989 and 1998.Methods: Data on wellbeing by theBradburn Affect Balance Scale is obtained fromthe Netherlands Continuous Health InterviewSurveys for the calendar years from 1989 to1998. Using Sullivan's method, life expectancyin wellbeing is calculated.Results: For males at the age of 16, lifeexpectancy in wellbeing increases significantlyfrom 52.7 years in 1989 (90.1% of the totallife expectancy) to 54.4 years in 1998(90.8%). This increase is almost completelycaused by the increase in total lifeexpectancy. For females at the age of 16, lifeexpectancy in wellbeing raises significant from54.4 years in 1989 (84.1%) to 56.2 years in1998 (86.3%). This increase is almostcompletely caused by a decrease in the numberof years in a state of distress.For both males and females at the age of 65,the significant increase of life expectancy inwellbeing exceeds the increase in total lifeexpectancy and is mainly caused by the decreasein number of years in distress.Conclusion: Contrary to life expectancyin good perceived health and to disability freelife expectancy – which show a decreasing trend– the overall wellbeing of the population isincreasing. It seems that aspects in human lifethat contribute to wellbeing or quality of lifeother than physical health are gaining inimportance. This makes life expectancy inwellbeing a less appropriate instrument tomonitor changes in population health, but auseful instrument to measure population qualityof life.     

Forecasting differences in life expectancy by education

Forecasts of life expectancy (LE) have fuelled debates about the sustainability and dependability of pension and healthcare systems. Of relevance to these debates are inequalities in LE by education. In this paper, we present a method of forecasting LE for different educational groups within a population. As a basic framework we use the Li–Lee model that was developed to forecast mortality coherently for different groups. We adapted this model to distinguish between overall, sex-specific, and education-specific trends in mortality, and extrapolated these time trends in a flexible manner. We illustrate our method for the population aged 65 and over in the Netherlands, using several data sources and spanning different periods. The results suggest that LE is likely to increase for all educational groups, but that differences in LE between educational groups will widen. Sensitivity analyses illustrate the advantages of our proposed method.     

On the decomposition of life expectancy and limits to life

Life expectancy is a measure of how long people are expected to live and is widely used as a measure of human development. Variations in the measure reflect not only the process of ageing but also the impacts of such events as epidemics, wars, and economic recessions. Since 1950, the influence of these events in the most developed countries has waned and life expectancy continues to lengthen unabated. As a result, it has become more difficult to forecast long-run trends accurately, or identify possible upper limits. We present new methods for comparing past improvements in life expectancy and also future prospects, using data from five developed, low-mortality countries. We consider life expectancy in 10-year age intervals rather than over the remaining lifetime, and show how natural limits to life expectancy can be used to extrapolate trends. We discuss the implications and compare our approach with other commonly used methods.

Supplementary material for this article is available at: http://dx.doi.org/10.1080/00324728.2014.972433     

[Age-specific mortality and life expectancy].]

The author attempts to assess the degree of influence of infant mortality on average life expectancy and to develop a method to directly revise average life expectancy given a change in mortality.     

Inequality in life expectancy, functional status, and active life expectancy across selected black and white populations in the United States

We calculated population-level estimates of mortality, functional health, and active life expectancy for black and white adults living in a diverse set of 23 local areas in 1990, and nationwide. At age 16, life expectancy and active life expectancy vary across the local populations by as much as 28 and 25 years respectively. The relationship between population infirmity and longevity also varies. Rural residents outlive urban residents, but their additional years are primarily inactive. Among urban residents, those in more affluent areas outlive those in high-poverty areas. For both whites and blacks, these gains represent increases in active years. For whites alone they also reflect reductions in years spent in poor health.     

The current differential in black and white life expectancy

The 1980 National Center for Health Statistics life tables for the U.S. black and white populations reveal a difference in life expectancy of 7 years between black and white males and 6 years between black and white females. Using cause-substituted life tables, we show that a number of causes of death contribute to the difference. The largest contributors are cardiovascular disease for both sexes and homicide and cancer for males.     

On the decomposition of changes in expectation of life and differentials in life expectancy

The projection of mortality rates requires inter alia close examination of the mortality experience of a population over a long period of time and will usually also involve the analysis of mortality trends by cause of death. In two of the more important recent contributions, techniques were devised for explaining change in life expectancy in terms of mortality changes in particular age groups and by different causes of death. The approaches adopted by the authors differ, and the purpose of this article is to reconcile the two and tie the results in with those obtained by earlier writers. A new method for explaining the change in a life expectancy differential in terms of the observed changes in the mortality differentials and the observed change in overall mortality level is also described.     

Estimating Indigenous life expectancy: pitfalls with consequences

The methods used by the Australian Bureau of Statistics (ABS) to estimate life expectancies of Aboriginal and Torres Strait Islander peoples in 2009 have been controversial and require critical and sensitive analysis. The introduction by ABS of the direct method for estimating Indigenous life expectancies, based on estimated deaths and populations, has been generally welcomed. But the way this method has been applied and, in particular, death estimates used by the ABS, warrant scrutiny. These estimates were based on a first ever linkage between Indigenous deaths and census records following the 2006 census. Census-based identification was used in place of identification in the death registrations, rather than as a supplementary data source. The various national, state and regional life expectancy estimates published may have been biased upwards by this process. Because the impact of the methodology varies across Australia, regional differentials reported appear substantial but are not soundly based. The questionable ABS results are highlighted and discussed. Analysis based on more comprehensive linkage of death records in New South Wales over 5?years suggests that the ABS methods have understated Indigenous deaths and so overstated life expectancy. The effect of an alternative ABS approach is also discussed. ABS estimates published in 2009 are not necessarily definitive and may well overestimate Aboriginal and Torres Strait Islander life expectancy and underestimate the life expectancy gap. Estimates should be based on accurate estimates of deaths and population. Consultation and a thorough review are essential before the next round of estimates following the findings of the 2011 population census. Closing the Gap commitments focus on eliminating the life expectancy gap between Aboriginal and Torres Strait Islander peoples and other Australians. Life expectancy estimates need to be based on methods and data that are well understood and broadly supported. The alternative is unproductive debate about statistics rather than the range of policies and resourcing issues needed to improve Indigenous health.     

How slowing senescence translates into longer life expectancy

Mortality decline has historically been largely a result of reductions in the level of mortality at all ages. A number of leading researchers on ageing, however, suggest that the next revolution of longevity increase will be the result of slowing down the rate of ageing. In this paper, we show mathematically how varying the pace of senescence influences life expectancy. We provide a formula that holds for any baseline hazard function. Our result is analogous to Keyfitz's 'entropy' relationship for changing the level of mortality. Interestingly, the influence of the shape of the baseline schedule on the effect of senescence changes is the complement of that found for level changes. We also provide a generalized formulation that mixes level and slope effects. We illustrate the applicability of these models using recent mortality decline in Japan and the problem of period to cohort translation.     

Changes in mortality and life expectancy: Some methodological issues

Measuring and explaining the effects of mortality changes on life expectancy has been discussed for the past three decades. Different approaches have been proposed using discrete or continuous methods. Two basic ideas underlie these approaches. The first compares two different mortality schedules and quantifies the contribution of each age group to the increase in life expectancy. The second analyzes how the progress in the mortality schedule translates into progress in life expectancy. This paper discusses and compares the approaches proposed by the United Nations (1982), Arriaga (1984), Pollard (1982, 1988), and Vaupel (1986), identifying their problems, advantages, and the types of situations where each one can best be applied.     

Recent perspectives on active life expectancy for older women

This article provides a critical review of recent active life expectancy literature, describing trends of special interest to women. We review findings from leading perspectives used to study life expectancy and active life expectancy, including gender, racial and socioeconomic differences, disease-specific effects, and biodemography. We examine three competing theories of population health that frame active life expectancy research-compression of morbidity, expansion of morbidity, and dynamic equilibrium-concluding there is support for both the compression of morbidity and dynamic equilibrium theories. Policy implications for women include a greater understanding of the role of education and racial and ethnic diversity in active life trends, and an increased public policy emphasis on prevention and treatment of chronic disease, together with adoption of more healthy lifestyles.     

Atechnique for estimating life expectancy with crude vital rates

This paper describes a method of estimating life expectancy at birth on the basis of crude vital rates. The method is derived from stable population theory and it furnishes good estimates insofar as the current crude vital rates of a population are close to its intrinsic rates. This condition is generally met in closed populations which have not experienced sharp movements in fertility. The method is useful for estimating life expectancy in developing nations with good sample registration systems but for which information on age is of poor quality. It is also useful for estimating the movement of life expectancy in certain European nations in the period prior to regular census taking. There are a number of nations and regions in Europe for which long series of birth and death rates are available but for which census age counts are widely spaced.     

Global patterns of healthy life expectancy for older women

This paper focuses on patterns of healthy life expectancy for older women around the globe in the year 2000, and on the determinants of differences in disease and injury for older ages. Our study uses data from the World Health Organization for women and men in 191 countries. These data include a summary measure of population health, healthy life expectancy (HALE), which measures the number of years of life expected to be lived in good health, and a complementary measure of the loss of health (disability-adjusted life years or DALYs) due to a comprehensive set of disease and injury causes. We examine two topics in detail: (1) cross-national patterns of female-male differences in healthy life expectancy at age 60; and (2) identification of the major injury and disability causes of disability in women at older ages. Globally, the male-female gap is lower for HALE than for total life expectancy. The sex gap is highest for Russia (10.0 years) and lowest in North Africa and the Middle East, where males and females have similar levels of healthy life expectancy, and in some cases, females have lower levels of healthy life expectancy. We discuss the implications of the findings for international health policy.     

The exceptionally high life expectancy of Costa Rican nonagenarians

Robust data from a voter registry show that Costa Rican nonagenarians have an exceptionally high live expectancy. Mortality at age 90 in Costa Rica is at least 14% lower than an average of 13 high-income countries. This advantage increases with age by 1% per year. Males have an additional 12% advantage. Age-90 life expectancy for males is 4.4 years, one-half year more than any other country in the world. These estimates do not use problematic data on reported ages, but ages are computed from birth dates in the Costa Rican birth-registration ledgers. Census data con rm the exceptionally high survival of elderly Costa Ricans, especially males. Comparisons with the United States and Sweden show that the Costa Rican advantage comes mostly from reduced incidence of cardiovascular diseases, coupled with a low prevalence of obesity, as the only available explanatory risk factor. Costa Rican nonagenarians are survivors of cohorts that underwent extremely harsh health conditions when young, and their advantage might be just a heterogeneity in frailty effect that might disappear in more recent cohorts. The availability of reliable estimates for the oldest-old in low- income populations is extremely rare. These results may enlighten the debate over how harsh early-life health conditions affect older-age mortality.     

A state-based regression model for estimating substate life expectancy

Life expectancy is an important indicator of the level of mortality in a population. However, the conventional way of calculating life expectancy--constructing a life table--has rigorous data requirements. As a consequence, life expectancy data are not usually available for substate areas. In this article, a regression model for estimating life expectancy is constructed, using state-level data, and is tested against two sets of 1980 life expectancy data: (1) a nationwide sample of metropolitan areas and (2) selected cities, their suburbs, and rural counties in Ohio. An additional test shows the sensitivity of the model's accuracy to errors in one of its input data elements. The results suggest that the model should be given serious consideration for generating life expectancy estimates for substate areas.     

Gender differences in life expectancy free of impairment at older ages

This article uses data from the United Kingdom Medical Research Council Cognitive Function and Ageing study (MRC CFAS) to analyze morbidity associated with three areas of impairment. We use cognitive status, functional status, and physical illness to examine differences in the proportion of time that older women and men will spend with co-morbidity. We also analyze differences among various impairments, and investigate the relationship between missing data and sex. Women have a larger burden of impairment than men, and, by including cognitive impairment together with functional impairment, a very large impairment burden is highlighted at all ages. Policy implications of the findings from the perspective of older women in the United Kingdom are discussed.