Potential support ratios: Cohort versus period perspectives

The ‘prospective potential support ratio’ has been proposed by researchers as a measure that accurately quantifies the burden of ageing, by identifying the fraction of a population that has passed a certain measure of longevity, for example, 17?years of life expectancy. Nevertheless, the prospective potential support ratio usually focuses on the current mortality schedule, or period life expectancy. Instead, in this paper we look at the actual mortality experienced by cohorts in a population, using cohort life tables. We analyse differences between the two perspectives using mortality models, historical data, and forecasted data. Cohort life expectancy takes future mortality improvements into account, unlike period life expectancy, leading to a higher prospective potential support ratio. Our results indicate that using cohort instead of period life expectancy returns around 0.5 extra younger people per older person among the analysed countries. We discuss the policy implications implied by our cohort measures.     

Steep increase in best-practice cohort life expectancy

We analyze trends in best-practice life expectancy among female cohorts born from 1870 to 1950. Cohorts experience declining rather than constant death rates, and cohort life expectancy usually exceeds period life expectancy. Unobserved mortality rates in non-extinct cohorts are estimated using the Lee-Carter model for mortality in 1960–2008. Best-practice cohort and period life expectancies increased nearly linearly. Across cohorts born from 1870 to 1920 the annual increase in cohort length of life was 0.43 years. Across calendar years from 1870 to 2008, the annual increase was 0.28 years. Cohort life expectancy increased from 53.7 years in the 1870 cohort to 83.8 years in the 1950 cohort. The corresponding cohort/period longevity gap increased from 1.2 to 10.3 years. Among younger cohorts, survival to advanced ages is substantially higher than could have been anticipated by period mortality regimes when these cohorts were young or middle-aged. A large proportion of the additional expected years of life are being lived at ages 65 and older. This substantially changes the balance between the stages of the life cycle.     

Relating Changes in Life Expectancy to Changes in Mortality

I address the problem of what can be said of changes in mortality rates, if one knows how life expectancies change. I note a general formula relating life expectancies in different ages to mortality and prove that if mortality changes over time following a proportional-hazard model, then there is a one-to-one correspondence between life expectancy at birth and mortality rates. Extensions and an application of these results to the analysis of mortality change are presented.     

Using Subjective Expectations to Forecast Longevity: Do Survey Respondents Know Something We Don’t Know?

Old-age mortality is notoriously difficult to predict because it requires not only an understanding of the process of senescence-which is influenced by genetic, environmental, and behavioral factors-but also a prediction of how these factors will evolve. In this paper I argue that individuals are uniquely qualified to predict their own mortality based on their own genetic background, as well as environmental and behavioral risk factors that are often known only to the individual. Given this private information, individuals form expectations about survival probabilities that may provide additional information to demographers and policymakers in their challenge to predict mortality. From expectations data from the 1992 Health and Retirement Study (HRS), I construct subjective, cohort life tables that are shown to predict the unusual direction of revisions to U.S. life expectancy by gender between 1992 and 2004: that is, for these cohorts, the Social Security Actuary (SSA) raised male life expectancy in 2004 and at the same lowered female life expectancy, narrowing the gender gap in longevity by 25% over this period. Further, although the subjective life expectancies for men appear to be roughly in line with the 2004 life tables, the subjective expectations of women suggest that female life expectancies estimated by the SSA might still be on the high side.     

Diet,mortality and life expectancy: a cross national analysis

"There are numerous reasons why mortality and life expectancy vary between countries. Epidemiological studies seem to indicate that dietary variations may be among them. A sample of 51 countries studied with data from the International Comparisons Project and other sources, shows that after controlling for nutrient intake, consumption of medical goods and services, income distribution, weather, and literacy, countries with more meat and poultry in their diet have lower life expectancies after age five. The results for infant mortality and child death between one and five indicate that a more animal-intensive diet may be actually beneficial, especially if fish consumption is increased and meat and poultry consumption reduced."     

The momentum of mortality change

Mortality change is not usually assigned much importance as a source of population growth when future population trends are discussed. Yet it can make a significant contribution to population momentum. In populations that have experienced mortality change, cohort survivorship will continue varying for some time even if period mortality rates become constant. This continuing change in cohort survivorship can create a significant degree of mortality-induced population change, a process we call the ‘momentum of mortality change’. The momentum of mortality change can be estimated by taking the ratio of e ₀ (the period life expectancy at birth) to CAL (the cross-sectional average length of life) for a given year. In industrialized nations, the momentum of mortality change can attenuate the negative effect on population growth of declining fertility or sustained below-replacement fertility. In India, where population momentum has a value of 1.436, the momentum of mortality change is the greatest contributor to its value.     

Probabilistic population projections for countries with generalized HIV/AIDS epidemics

In 2015, the United Nations (UN) issued probabilistic population projections for all countries up to 2100, by simulating future levels of total fertility and life expectancy and combining the results using a standard cohort component projection method. For the 40 countries with generalized HIV/AIDS epidemics, the mortality projections used the Spectrum/Estimation and Projection Package (EPP) model, a complex, multistate model designed for short-term projections of policy-relevant quantities for the epidemic. We propose a simpler approach that is more compatible with existing UN projection methods for other countries. Changes in life expectancy are projected probabilistically using a simple time series regression and then converted to age- and sex-specific mortality rates using model life tables designed for countries with HIV/AIDS epidemics. These are then input to the cohort component method, as for other countries. The method performed well in an out-of-sample cross-validation experiment. It gives similar short-run projections to Spectrum/EPP, while being simpler and avoiding multistate modelling.     

Mortality in Quebec during the nineteenth century: from the state to the cities

The aim of this paper is to explore mortality in Quebec during the nineteenth century from a demographic perspective. During the nineteenth century, there was excess urban mortality in various countries; in order to identify such mortality differentials, we compared mortality indicators for the province of Quebec and then for the urban areas of Montreal and Quebec City. Using data from various studies, we produced life tables and compared life expectancies. We show that at different times during the nineteenth century, spatial variations in mortality levels across the province of Quebec and its urban areas were significant. According to the data we analyzed, mortality is undoubtedly higher in urban areas even though a convergence in trends took place towards the end of the century, resulting in an overall reduction in mortality. Also, exploring life expectancies within a cohort approach at times of fast-changing mortality patterns has proved to be instructive. Life expectancy estimates based on a cross-sectional approach were systematically lower than those resulting from a cohort-specific one. Trends diverged to a greater extent beginning with the 1870 cohort, reflecting the improvements made from that point on to World War II. Since current mortality levels are substantially determined by the cumulative effects of past behaviour specific to each generation, it is quite obvious that mortality analysis will reveal its true meaning only with the help of cohort life tables.     

Change in disability-free life expectancy for Americans 70 years old and older*

In this article, we examine changes in life expectancy free of disability using longitudinal data collected from 1984 through 2000 from two cohorts who composed the Longitudinal Studies of Aging I and II. Life expectancies with and without ADL and/or IADL disability are calculated using a Markov-based multistate life table approach. At age 70, disability-free life expectancy increased over a 10-year period by 0.6 of a year in the later cohort, which was the same as the increase in total life expectancy, both increases marginally statistically significant. The average length of expected life with IADL and ADL disability did not change. Changes in disability-free life expectancy resulted from decreases in disability incidence and increases in the incidence of recovery from disability across the two survey cohorts. Age-specific mortality among the ADL disabled declined significantly in the later cohort after age 80. Mortality for the IADL disabled and the nondisabled did not change significantly. Those with ADL disability at age 70 experienced substantial increases in both total life expectancy and disability-free life expectancy. These results indicate the importance of efforts both to prevent and delay disability and to promote recovery from disability for increasing life expectancy without disability. Results also indicate that while reductions in incidence and increases in recovery work to decrease population prevalence of disability, declining mortality among the disabled has been a force toward increasing disability prevalence.     

European Perspectives on Healthy Aging in Women

SUMMARY

Using data from the 1994 European Community Household Panel, we compare active life expectancy differentials at age 65 years between women and men in 12 European countries. We seek to explain the extent to which differences are a reflection of gender differentials in life expectancy at 65 years or reflect differences in active life expectancy earlier in life. Considerable variation in the gender differentials in both total and active life expectancies at age 65 years exist within Europe, with some countries experiencing 20% lower life expectancy at age 65 years for men compared to women. Some evidence was found to suggest that gender differentials in active life expectancy may continue from younger ages through to later life.     

Diet,mortality and life expectancy A cross national analysis

There are numerous reasons why mortality and life expectancy vary between countries. Epidemiological studies seem to indicate that dictary variations may be among them. A sample of 51 countries studied with data from the International Comparisons Project and other sources, shows that after controlling for nutrient intake, consumption of medical goods and services, income distribution, weather, and literacy, countries with more meat and poultry in their diet have lower life expectancies after age five. The results for infant mortality and child death between one and five indicate that a more animal-intensive diet may be actually be beneficial, especially if fish consumption is increased and meat and poultry consumption reduced.I thank Jere Behrman, David Crawford, Anil Deolalikar, the Managing Editor, two anonymous referees, and especially Samuel Preston for valuable comments, and Alan Heston and Robert Summers for being generous with their time and their data. Financial support was provided by a Compton Foundation Fellowship. All errors remain my responsibility.     

Increment–Decrement Life Table Estimates of Happy Life Expectancy for the U.S. Population

Using large nationally representative longitudinal data on changes in happiness and mortality and multivariate increment–decrement life tables, we assess length of quality life through cohort estimates of happy life expectancies. We examine population-based and status-based life expectancies in absolute term of years and relative term of proportions. We find that happy life expectancies exceed unhappy life expectancies in both absolute and relative terms for the overall population and population in each state of happiness at any given age. Being happy (as opposed to unhappy) at any age brings a longer life and more of the future life spent in happiness. We also examine social differentials in the estimates of happy life expectancy at each age by sex, race, and education. The educational gap in happy life expectancies is larger than the sex and race gaps. For the better educated, longer life consists of a longer happy life and shorter unhappy life in both years and proportions and regardless of happy or unhappy status at any given age.     

Changing Life Expectancy and Health Expectancy Among Russian Adults: Results from the Past 20 Years

The decade following the collapse of the Soviet Union was characterized by wide fluctuations in Russian mortality rates, but since the early 2000s, life expectancy has improved progressively. Recent upturns in longevity have promoted policy debates over extending the retirement age in the country. However, whether observed gains in life expectancy are accompanied by improving health remains to be addressed. Using data from the 1994–2014 Russian Longitudinal Monitoring Survey of the Higher School of Economics, this study investigates trends over 20 years in healthy life expectancy (HLE) and illness-free life expectancy (IFLE) for men and women at adult ages. Analyses using the Sullivan method show that men and women at adult ages have experienced large increases in health expectancies during the post-Soviet period. Increases in HLE exceeded increases in total life expectancy for both genders. Further, health expectancies have evolved over time through cycles of increases and decreases, just like life expectancy. These results suggest increases in good-quality years among men and women at working ages, offering support for changing the official retirement age. The extent of the change in the retirement age, however, needs to be carefully considered, given that, despite recent improvements, the health expectancy of the Russian population still remains low.     

Truncated cross-sectional average length of life: A measure for comparing the mortality history of cohorts

Period life expectancies are commonly used to compare populations, but these correspond to simple juxtapositions of current mortality levels. In order to construct life expectancies for cohorts, a complete historical series of mortality rates is needed, and these are available for only a subset of developed countries. The truncated cross-sectional average length of life (TCAL) is a new measure that captures historical information about all cohorts present at a given moment and is not limited to countries with complete cohort mortality data. The value of TCAL depends on the rates used to complete the cohort series, but differences between TCALs of two populations remain similar irrespective of the data used to complete the cohort series. This result is illustrated by a comparison of TCALs for the US with those for Denmark, Japan, and other high-longevity countries. Specific cohorts that account for most of the disparity in mortality between the populations are identified.

Supplementary material for this article is available at: http://dx.doi.org/10.1080/00324728.2015.1019955     

The momentum of mortality change

Mortality change is not usually assigned much importance as a source of population growth when future population trends are discussed. Yet it can make a significant contribution to population momentum. In populations that have experienced mortality change, cohort survivorship will continue varying for some time even if period mortality rates become constant. This continuing change in cohort survivorship can create a significant degree of mortality-induced population change, a process we call the 'momentum of mortality change'. The momentum of mortality change can be estimated by taking the ratio of e0 (the period life expectancy at birth) to CAL (the cross-sectional average length of life) for a given year. In industrialized nations, the momentum of mortality change can attenuate the negative effect on population growth of declining fertility or sustained below-replacement fertility. In India, where population momentum has a value of 1.436, the momentum of mortality change is the greatest contributor to its value.     

Modeling and Forecasting Health Expectancy: Theoretical Framework and Application

Life expectancy continues to grow in most Western countries; however, a major remaining question is whether longer life expectancy will be associated with more or fewer life years spent with poor health. Therefore, complementing forecasts of life expectancy with forecasts of health expectancies is useful. To forecast health expectancy, an extension of the stochastic extrapolative models developed for forecasting total life expectancy could be applied, but instead of projecting total mortality and using regular life tables, one could project transition probabilities between health states simultaneously and use multistate life table methods. In this article, we present a theoretical framework for a multistate life table model in which the transition probabilities depend on age and calendar time. The goal of our study is to describe a model that projects transition probabilities by the Lee-Carter method, and to illustrate how it can be used to forecast future health expectancy with prediction intervals around the estimates. We applied the method to data on the Dutch population aged 55 and older, and projected transition probabilities until 2030 to obtain forecasts of life expectancy, disability-free life expectancy, and probability of compression of disability.     

“人均预期寿命提高1岁”的实证研究

温家宝总理在政府工作报告中首次提出十二五时期"人均预期寿命提高1岁"的目标。本文在生命表数据基础上,通过计算平均预期寿命贡献率并进行相关分析与回归分析后得出:我国目前平均预期寿命虽然已高于绝大多数发展中国家,但其绝对增速正逐渐放慢。而降低60～90岁年龄段老年人口死亡率、提高居民消费水平、缩小家庭规模、迁移有条件的离退休老人到低海拔地区养老是实现人均预期寿命提高1岁目标的有效路径。     

Lifespan Dispersion in Times of Life Expectancy Fluctuation: The Case of Central and Eastern Europe

Central and Eastern Europe (CEE) have experienced considerable instability in mortality since the 1960s. Long periods of stagnating life expectancy were followed by rapid increases in life expectancy and, in some cases, even more rapid declines, before more recent periods of improvement. These trends have been well documented, but to date, no study has comprehensively explored trends in lifespan variation. We improved such analyses by incorporating life disparity as a health indicator alongside life expectancy, examining trends since the 1960s for 12 countries from the region. Generally, life disparity was high and fluctuated strongly over the period. For nearly 30 of these years, life expectancy and life disparity varied independently of each other, largely because mortality trends ran in opposite directions over different ages. Furthermore, we quantified the impact of large classes of diseases on life disparity trends since 1994 using a newly harmonized cause-of-death time series for eight countries in the region. Mortality patterns in CEE countries were heterogeneous and ran counter to the common patterns observed in most developed countries. They contribute to the discussion about life expectancy disparity by showing that expansion/compression levels do not necessarily mean lower/higher life expectancy or mortality deterioration/improvements.     

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.     

Measuring and explaining the change in life expectancies

A set of new indices for interpreting change in life expectancies, as well as a technique for explaining change in life expectancies by change in mortality at each age group are presented in the paper. The indices, as well as the new technique for explaining the differences in life expectancies, have been tested and examples using United States life tables are presented. The technique for explaining life expectancy differentials can be used for analyzing change in mortality or mortality differentials by sex, ethnicity, region, or any other subpopulations. The technique can be applied to life expectancies at birth or temporary life expectancies between any desirable ages.