The health expectancies of older Australians

Health expectancies of the states ‘Disability-free’ and ‘Disabled’ are estimated for Australian females and males aged 60 and over, both by cohort from 1980 and current for survey years 1981, 1988, 1993 and 1998. Modifications of recently developed logistic regression techniques are used rather than the standard 1971 method due to Sullivan. Results from the three later surveys are broadly similar and differ in important respects from those of the 1981 survey. Based on the last three surveys our estimates support the view that, depending on age, two-thirds or more of the increase in female life expectancy over the decade 1988–1998 is spent in the Disabled state. The situation is worse for elderly men, for whom all of the increased years of expected life are estimated to be spent in the Disabled state. The findings do not support rectangularization of the survival curve or Disability-free survival curve.     

Obtaining multistate life table distributions for highly refined subpopulations from cross-sectional data: A bayesian extension of sullivan’s method

Multistate life table methods are often used to estimate the proportion of remaining life that individuals can expect to spend in various states, such as healthy and unhealthy states. Sullivan’s method is commonly used when panels containing data on transitions are unavailable and true multistate tables cannot be generated. Sullivan’s method requires only cross-sectional mortality data and cross-sectional data indicating prevalence in states of interest. Such data often come from sample surveys, which are widely available. Although the data requirements for Sullivan’s method are minimal, the method is limited in its ability to produce estimates for subpopulations because of limited disaggregation of data in cross-sectional mortality files and small cell sizes in aggregated survey data. In this article, we develop, test, and demonstrate a method that adapts Sullivan’s approach to allow the inclusion of covariates in producing interval estimates of state expectancies for any desired subpopulation that can be specified in the cross-sectional prevalence data. The method involves a three-step process: (1) using Gibbs sampling to sample parameters from a bivariate regression model; (2) using ecological inference for producing transition probability matrices from the Gibbs samples; (3) using standard multistate calculations to convert the transition probability matrices into multistate life tables.     

Estimating Increment-Decrement Life Tables with Multiple Covariates from Panel Data: The Case of Active Life Expectancy*

A fundamental limitation of current multistate life table methodology-evident in recent estimates of active life expectancy for the elderly-is the inability to estimate tables from data on small longitudinal panels in the presence of multiple covariates (such as sex, race, and socioeconomic status). This paper presents an approach to such an estimation based on an isomorphism between the structure of the stochastic model underlying a conventional specification of the increment-decrement life table and that of Markov panel regression models for simple state spaces. We argue that Markov panel regression procedures can be used to provide smoothed or graduated group-specific estimates of transition probabilities that are more stable across short age intervals than those computed directly from sample data. We then join these estimates with increment-decrement life table methods to compute group-specific total, active, and dependent life expectancy estimates. To illustrate the methods, we describe an empirical application to the estimation of such life expectancies specific to sex, race, and education (years of school completed) for a longitudinal panel of elderly persons. We find that education extends both total life expectancy and active life expectancy. Education thus may serve as a powerful social protective mechanism delaying the onset of health problems at older ages.     

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.     

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.     

Reconstructing childhood health histories

This article provides evidence about the quality of retrospective childhood health histories given to respondents in the Health and Retirement Survey (HRS) and the Panel Study of Income Dynamics (PSID). Even though information on early life health events is critical, there is legitimate skepticism about the ability of older respondents to remember specific health problems that they had during childhood. The evidence presented in this article suggests that this view is too negative. Respondents appear to remember salient childhood events about themselves, such as the illnesses they had during childhood, quite well. Moreover, these physical and psychological childhood health events are important correlates of adult health during middle age.     

Trends in health expectancies in Australia 1981–1993

Health expectancy indices combine the mortality and morbidity experience of a population into a single composite indicator. This paper summarizes and evaluates methods for the calculation of health expectancies and presents trends in the expectation of life with disability and handicap in Australia from 1981 to 1993. Unlike other countries for which recent health expectancy time series are available, Australian results indicate that the expectation of years with disability has increased for both males and females. Possible explanations for this are examined.     

A new method for correcting under-estimation of disabled life expectancy and an application to the chinese oldest-old

This article demonstrates that disabled life expectancies that are based on conventional multistate life-table methods are significantly underestimated because of the assumption of no changes in functional status between age x and death. We present a new method to correct the bias and apply it to data from a longitudinal survey of about 9,000 oldest-old Chinese aged 80-105 collected in 1998 and 2000. In our application, the age trajectories of disability (activities of daily living--ADL), status-specific death rates, and the probabilities of transitions between ADL states of the oldest-old were investigated for the first time in a developing country. In this article, we report estimates of bias-corrected disabled and active life expectancies of the Chinese oldest-old and demonstrate patterns of large differences associated with initial status, gender, and advances in ages. Using combined information on ADL disabilities and length of having been bedridden before dying, we analyze gender and age patterns of the extent of morbidity before dying among the oldest-old and their implications for debates on the hypothesis of compression of morbidity.     

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.     

Active life expectancy estimates for the U.S. elderly population: A multidimensional continuous-mixture model of functional change applied to completed Cohorts, 1982–1996

An increment-decrement stochastic-process life table model that continuously mixes measures of functional change is developed to represent age transitions among highly refined disability states interacting simultaneously with mortality. The model is applied to data from the National Long Term Care Surveys of elderly persons in the years 1982 to 1996 to produce active life expectancy estimates based on completed-cohort life tables. At ages 65 and 85, comparisons with extant period estimates for 1990 show that our active life expectancy estimates are larger for both males and females than are extant period estimates based on coarse disability states.     

Distortions caused by nonobservation of periods of cohabitation before the latest

In retrospective studies of individual life histories, some or all of the information pertaining to periods prior to the latest event interval of interest will sometimes be left out. This simplifies data collection, and it may improve the reliability of the data actually obtained by reducing misreporting. Unfortunately, it may also introduce serious distortion in estimates based on such data. This paper investigates the extent of such distortion in a retrospective study of nonmarital cohabitation, marriage, and childbearing when information on consensual unions is restricted.     

Health profiles and profile-specific health expectancies of older women and men: The Netherlands

This study focuses on gender differences in health profiles, and examines which health profiles drive gender differences in remaining life expectancy in women and men aged 65 and over in The Netherlands. Data from the first two cycles of the Longitudinal Aging Study Amsterdam (n = 2,141 and 1,659, respectively) were used to calculate health profiles for individuals of 65-85 years. For both women and men, six profiles were found: I. cancer; II. "other" chronic diseases; III. cognitive impairment; IV. frailty or multimorbidity; V. cardiovascular diseases; and VI. good health. The further characterization of these types showed some gender differences. Remaining life expectancy for women was greater than for men in each health profile. A decomposition into health expectancies showed that both women and men could expect to live about 5 years in good health from age 66. The greatest gender differences in years spent with health problems were found for profile IV and for profile III. Their greater number of years spent in these health states have direct consequences for the type and cost of care women need.     

Parental survival data: Some results of the application of Ledermann's model life tables

Summary Ledermann's one- and two-parameter model life tables are used in order to summarize and compare adult mortality estimates derived from parental survival data, and also to link parental survival with child survival data. The Ledermann models provide an alternative to the logit model used by Brass and Hill. Examination of life tables derived from actual child and adult mortality estimates reveals that although the two types of models yield similar overall levels of mortality, they show marked differences in the estimated patterns by sex and age. It has not been possible to disentangle completely how much of this divergence is due to the models themselves and how much to inadequacies in the data available. Finally, we question whether it is always wise to establish a full life table from child and adult mortality estimates when these are based on data which refer to different periods of exposure to the risk of dying, without allowance for possible distortions resulting from mortality change.     

Child Poverty as a Determinant of Life Outcomes: Evidence from Nationwide Surveys in Japan

We attempt to examine the extent to which poverty in childhood adversely affects success in adulthood, using micro data from nationwide surveys in Japan and taking into account the recursive structure of life outcomes. We use retrospective assessments of income class at the age of 15, because longitudinal data on household income are not available. After controlling for its endogeneity, we confirm that children from poor families tend to have lower educational attainment, face higher poverty risks, and assess themselves as being less happy and as suffering from poorer health.     

How much Confidence can we have in EU-SILC? Complex Sample Designs and the Standard Error of the Europe 2020 Poverty Indicators

If estimates are based on samples, they should be accompanied by appropriate standard errors and confidence intervals. This is true for scientific research in general, and is even more important if estimates are used to inform and evaluate policy measures such as those aimed at attaining the Europe 2020 poverty reduction target. In this article I pay explicit attention to the calculation of standard errors and confidence intervals, with an application to the European Union Statistics on Income and Living Conditions (EU-SILC). The estimation of accurate standard errors requires among others good documentation and proper sample design variables in the dataset. However, this information is not always available. Therefore, I complement the existing documentation on the sample design of EU-SILC and test the effect on estimated standard errors of various simplifying assumptions with regard to the sample design. It is shown that accounting for clustering within households is of paramount importance. Although this results in many cases in a good approximation of the standard error, taking as much as possible account of the entire sample design generally leads to more accurate estimates, even if sample design variables are partially lacking. The effect is illustrated for the official Europe 2020 indicators of poverty and social exclusion and for all European countries included in the EU-SILC 2008 dataset. The findings are not only relevant for EU-SILC users, but also for users of other surveys on income and living conditions which lack accurate sample design variables.     

中国高龄老人就医及时性状况研究

基于 1 998年中国高龄老人健康长寿调查数据 ,对中国高龄老人患病能否得到及时医治的状况进行了分析。结果表明 ,高龄老人调查当时若患病 ,只有 3 7%左右的高龄老人不能得到及时医治 ;农村 (4 2 % )该比例略高于城镇 (3 0 % ) ;患病得不到及时就医的群体比较固定。LOGISTIC回归还揭示患病由家庭成员提供照料服务的高龄老人比由社会提供照料服务的高龄老人得不到及时医治的可能性小 ,与患病不能及时医治的高龄老人相比 ,患病能得到及时医治的高龄老人健康自评好的比例高 ,完全自理的比例高 ,认知健全比例高 ,疾病对日常生活妨碍比例小 ,隶属健康纯类的可能性大 ,其后死亡的可能性小 ,健康存活的可能性大。说明患病得到及时治疗对高龄老人晚年健康促进和生存具有一定的影响。     

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.     

Modeling Transition Rates Using Panel Current-Status Data: How Serious is the Bias?

Studies of disability dynamics and active life expectancy often rely on transition rates or probabilities that are estimated using panel survey data in which respondents report on current health or functional status. If respondents are contacted at intervals of one or two years, then relatively short periods of disability or recovery between surveys may be missed. Much published research that uses such data assumes that there are no unrecorded transitions, applying event-history techniques to estimate transition rates. In recent years, a different approach based on embedded Markov chains has received growing use. We assessed the performance of both approaches, using as a criterion their ability to reproduce the parameters of a “true” model based on panel data collected at one-month intervals. Neither of the widely used approaches performs particularly well, and neither is uniformly superior to the other.     

Nativity and older women's health: constructed reliance in the health and retirement study

Gender and nativity are known risk factors for physical and economic dependency. Immigrant women are particularly disadvantaged because of their greater lack of social and economic resources. In this study, we investigate how women immigrants coordinate and utilize various support systems as they approach retirement age, as well as how choices and constraints affect their physical wellbeing. Experiences throughout the life course play a role in the maintenance of health, but the pre-retirement years are particularly crucial to the establishment of patterns of reliance to be used in later life. We examine the effects of economic resources, social support, and family ties (as well as several exogenous variables) on women's physical health using data from the Health and Retirement Survey. For the women in this study, demographic characteristics, such as Hispanic ethnicity and low education are strong risk factors for poor health. Findings also indicate that reliance patterns across resource domains do not differ significantly by nativity and that both economic and familial resource access significantly lessens the risk of poor health for both native and foreign born women.