Changing mortality and morbidity rates and the health status and life expectancy of the older population

This paper demonstrates the consequences of changes in mortality and health transition rates for changes in both health status life expectancy and the prevalence of health problems in the older population. A five-state multistate life table for the mid-1980s provides the baseline for estimating the effect of differing mortality and morbidity schedules. Results show that improving mortality alone implies increases in both the years and the proportion of dependent life; improving morbidity alone reduces both the years and the proportion of dependent life. Improving mortality alone leads to a higher prevalence of dependent individuals in the life table population; improving morbidity alone leads to a lower percentage of individuals with problems in functioning.     

Voting status life tables for the United States, 1968–1980

Using current and retrospective voting data from the November Current Population Surveys of Presidential election years, this study modifies and applies demographic accounting and increment-decrement life table methods to construct voting status life tables for three recent election periods. The paper shows how to combine a continuously occurring process (mortality) with a process that is active only at discrete times (voting transitions) within a multistate life table. Empirical results pertain to the number of Presidential elections an individual is expected to vote in at ages 0 and 18, the typical life course pattern of transitions between voting and not voting statuses, sex and race differentials, changes across the three election periods, and cohort effects.     

The impact of heterogeneity in individual frailty on the dynamics of mortality

Life table methods are developed for populations whose members differ in their endowment for longevity. Unlike standard methods, which ignore such heterogeneity, these methods use different calculations to construct cohort, period, and individual life tables. The results imply that standard methods overestimate current life expectancy and potential gains in life expectancy from health and safety interventions, while underestimating rates of individual aging, past progress in reducing mortality, and mortality differentials between pairs of populations. Calculations based on Swedish mortality data suggest that these errors may be important, especially in old age.     

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.     

Estimating internal migration from incomplete data using model multiregional life tables

A principal feature of current methods of estimating demographic measures from incomplete data is the use of model life tables that approximate the mortality of a region for which reliable mortality data are unavailable. Observed decennial rates of survivorship may be used to identify out of a set of such model life tables one that best matches the observed data. This paper introduces the concept of a modelmultiregional life table and outlines a procedure for selecting an appropriate one using place-of-birth-by-residence data.     

Proportional hazards life table models: an illustrative analysis of socio-demographic influences on marriage dissolution in the United States

The proportional hazards life table is a recently developed approach to the analysis of survival data when mortality risks vary among individuals. It assumes that at a given age (or duration since the start of a life) the force of mortality is a constant (specific to that age) multiplied by a proportionality factor which is determined by the characteristics of the individual and does not change unless these covariates do. In this paper, the method is reviewed for the case where the covariates are fixed at the start of the lifetime and illustrated by an application to marital dissolution in the United States.     

Life table construction on the basis of two enumerations of a closed population

The author demonstrates that an accurate detailed life table that represents average mortality experience between two censuses can be constructed if the censuses provide accurate records of the single-year age distribution of a closed population. This life table can begin at age zero if accurate data on the annual number of births during the inter-censal period are available; otherwise the first age in the life table must equal the duration of time between the censuses. "The estimation technique involves the calculation of the number of persons attaining each age during the period between the censuses and the determination of the average rate of increase in the number at each individual age. The success of the technique comes from the use of interpolation to calculate how many in each cohort attain each exact age the cohort passes through between the censuses." The estimation technique is tested using two alternative methods of interpolation. Some illustrations based on data for Sweden and China are included.     

Estimating Mortality Level for Small Populations: An Evaluation of a Pair of Two-Census Methods

A pair of two-census methods of estimating mortality levels are tested with simulated census data. The populations considered range in size from 250 to 1500 individuals of each sex; censuses were taken at intervals of five and ten years. In general, the methods are resistant to bias, and yield variances similar in magnitude to those obtained using vital registration data and life table techniques for censored data. The two-census methods represent a substantial improvement over the techniques of mortality estimation previously available for small populations, since two reliable censuses are more likely to be available for these populations than complete vital registration.     

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.     

Racial inequality in active life among adult americans

Is a shorter life with more years lived in poor health a defining attribute of the life cycle of disadvantaged groups? Based on the J990 5% Public Use Microdata Survey, we develop life table models of healthy (or active) life for the major racial groups, by sex, in the United States. The analysis underscores the complexity of the relationship between morbidity and mortality in the population. For Asians, longer life is associated with fewer years lived in poor health. In contrast, Native Americans’ relatively longer lives are accompanied by extended periods of chronic health problems. of all racial groups, blacks live the fewest years, and they live a high proportion of those years with a chronic health problem. Hispanics also live substantially fewer years, yet the period of life they spend with a health problem is relatively compressed. Racial differences in the link between morbidity and mortality point to the importance of investigating how chronic diseases and disease prevention and treatment are related to active life across the population subgroups.     

The Association Between Individual Income and Remaining Life Expectancy at the Age of 65 in the Netherlands

This article quantifies the association between individual income and remaining life expectancy at the statutory retirement age (65) in the Netherlands. For this purpose, we estimate a mortality risk model using a large administrative data set that covers the 1996–2007 period. Besides age and marital status, the model includes as covariates individual and spouse’s income as well as a random individual specific effect. It thus allows for dynamic selection based on both observed and unobserved characteristics. We find that conditional on marital status, individual income is about equally strong and negatively associated with mortality risk for men and women and that spouse’s income is only weakly associated with mortality risk for women. For both men and women, we quantify remaining life expectancy at age 65 for low-income individuals as approximately 2.5 years less than that for high-income individuals.     

The four-parameter logit life table system

Summary Brass's model life table system, which is a two parameter system based on the logit transformation of survivorship values, has been widely and successfully used to describe age patterns of mortality in many populations. As more reliable information has become available for populations with mortality patterns which differ in important ways from the assumed standard pattern of mortality, a more flexible model system is needed. This paper shows how Brass's system can be expanded into a four-parameter model, and evaluates the performance of the new system by examining how well it can fit observed life table data.     

A simple model for linking life tables by survival mortality ratios

Patterns of variation in mortality can be studied by measuring changes in selected life table functions. A model is proposed in which the rate of change over time in the life table survivorship probability at any age has been assumed as proportional to the product of its own value and its complementary probability or the probability of dying by that age, where the proportion is the same for all ages and depends only on the time duration between successive life tables. The end result is that the logit functions of the survivorship probabilities at two points in time are linearly related with a slope of one. The projecting power of the model has been tested by using U.S. life tables for the years 1950 and 1970 as well as Coale and Demeny's regional model life tables. In the latter case, the model produced surprisingly close matches even when the expectations of life differed by as much as 20 years.     

Using quality of life information to set priorities in health policy

Health care has as primary objectives extending life expectancy and improving quality of life in years prior to death. This paper offers a General Health Policy Model as a method for quantifying these outcomes. The model adjusts life expectancy for diminished quality of life, which is measured using a standardized instrument known as the Quality of Well-being (QWB) scale. The Well-year or Quality Adjusted Life Year (QALY) results from these analyses and serves as a single quantitative expression of health benefit. QALY units integrate side effects and benefits of treatment by combining into a single number, mortality, morbidity, and duration of each health state. Examples show the application of the model relevant to a variety of medical and public health problems, including diabetes, arthritis, AIDS, neonatal circumcision, and tobacco tax. It is suggested that the General Health Policy Model has advantages for guiding both individual and public health decisions.     

Causes of Male Excess Mortality: Insights from Cloistered Populations

The degree to which biological factors contribute to the existence and the widening of mortality differences by sex remains unclear. To address this question, a mortality analysis for the years 1890 to 1995 was performed comparing mortality data on more than 11,000 Catholic nuns and monks in Bavarian communities living in very nearly identical behavioral and environmental conditions with life table data for the general German population. While the mortality differences between women and men in the general German population increased considerably after World War II, they remained almost constant among the members of Bavarian religious orders during the entire observation period, with slight advantages for nuns. Thus, the higher differences observable in the general population cannot be attributed to biological factors. The different trends in sex‐specific mortality between the general and the cloistered populations are caused exclusively by men in the general population who were unable to follow the trend in mortality reduction of women, nuns, and especially monks. Under the special environmental conditions of nuns and monks, biological factors appear to confer a maximum survival advantage for women of no more than one year in remaining life expectancy at young adult ages.     

Estimates of mortality from infant mortality rates

Estimates of mortality rates and expectation of life at birth, using infant mortality rates, are examined on the basis of 150 life tables for both sexes. Least squares linear estimates are given as well as estimates of their variances. Model life table calculations, as proposed by the U.N. Population Branch, are then compared with these unbiased minimum variance estimates and shown to overestimate the expectation of life by more than two years on the average, and to be at most 68% efficient. Though better estimates are provided in this paper, their variance is still so large as to cast doubt on the practical usefulness of anv estimates based exclusively on infant mortality rates.     

The use of mortality time series data to produce hypothetical morbidity distributions and project mortality trends

It is difficult to obtain direct empirical estimates of chronic disease prevalence in the U.S. population. The available estimates are usually derived from epidemiological studies of selected populations. In this paper we present strategies for estimating morbidity distributions in the national population using auxiliary biomedical evidence and theory to estimate transitions to morbidity states from a cohort mortality time series. We present computational methods which employ these estimates of morbid state transitions to produce life table functions for both primary (morbidity) and secondary (mortality) decrements. These methods are illustrated using data on stomach cancer mortality for nine white male cohorts, aged 30 to 70 in 1950, observed for a 28-year period (1950 to 1977).     

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.     

The Changing Shape of Soviet Mortality, 1958–1985: An Evaluation of Old and New Evidence

Changes in mortality in the Soviet Union have attracted the attention of both scholars and the popular media. After a hiatus of more than ten years, the government of the Soviet Union has released data on mortality for the 1980s, which allow assessment of recent changes. The new life table for 1984–85 shows that mortality of Soviet females has improved at ages below 45 and deteriorated above that age since the last age-specific mortality data were published in the early 1970s, while mortality of males has improved at ages below 25 and deteriorated above that age. At the same time, the official mortality rates for persons aged 60 and over in 1958–59, 1968–71, and 1984–85 are implausibly low. Poor-quality data at the older ages, particularly in rural areas and the less developed regions of the country, contributed to these low mortality rates of the old. As data quality has improved with time, the reported mortality rates at old ages have increased. Adjustment of the official data for error, especially above age 60, shows that whereas the reported value of e₀ for males fell by 1.5 years between 1958–59 and 1984–85, the actual value probably fell by no more than 0.5 years; the corresponding figures for females were a reported rise of one year, and an actual rise of at least two years. Examination of these Soviet data illustrates how important consideration of error in mortality statistics of the old can be in understanding mortality trends.     

Recent trends in mortality in Australia—an analysis of the causes of death through the application of life table techniques

The paper examines the post-1971 reduction in Australian mortality in light of data on causes of death. Multiple-decrement life tables for eleven leading causes of death by sex are calculated and the incidence of each cause of death is presented in terms of the values of the life table functions. The study found that in the overall decline in mortality over the last 20 years significant changes occurred in the contribution of the various causes to total mortality. Among the three leading causes of death, heart disease, malignant neoplasms (cancer), and cerebrovascular disease (stroke), mortality rates due to neoplasms increased and those of the other two causes decreased. The sex-age-cause-specific incidence of mortality changed and the median age at death increased for all causes except for deaths due to motor-vehicle accidents for both sexes and suicide for males. The paper also deciphers the gains in the expectation of life at birth over various time periods and the sex-differentials in the expectation of life at birth at a point in time in terms of the contributions made by the various sex-age-cause-specific mortality rates.