Changes in health, mortality, and disability and their impact on long-term care needs

The need for long-term care is driven both by the growth of the elderly population and changes in the age relations of morbidity, disability, and mortality. Data show these relations changed in the U.S. elderly population from 1982 to 1989. Chronic disability prevalence declined between the 1982 and 1989 U.S. National Long Term Care Surveys. Among those impaired, many persons using personal assistance to meet their needs shifted to the use of assisted housing and special equipment. The relation of these trends to other changes--such as the increasing educational level of the elderly population--is examined to estimate how future changes in disability and morbidity may affect the demand for long-term care. Disabilities at specific times as well as their transition rates were examined to determine how long individuals need long-term care. The analyses suggest that, while the amount of long-term care services needed will increase rapidly, the types and amounts of services used by the U.S. elderly population will undergo significant change.     

Methods for the analysis of mortality risks across heterogeneous small populations: examination of space-time gradients in cancer mortality in North Carolina counties 1970–75

A method of analyzing mortality rates in heterogeneous populations is presented. This method, appropriate for the investigation of mortality rates in small geographic areas (e.g., counties) where the forces of mobility operate to selectively “package” persons, is applied to the determination of whether a spatial west-east gradient in cancer mortality rates existed in North Carolina over the period 1970 to 1975. A significant gradient (as well as a significant temporal trend) is determined to exist in the data, though only for particular race, age and sex-specific demographic groups. Several alternate hypotheses are presented to explain the existence of the spatial gradient in these particular demographic groups.     

Black/White Differences in Health Status and Mortality Among the Elderly

Grade of membership (GOM) representations are used to characterize and compare the health status of a very heterogeneous sample of blacks and whites in an elderly cohort of 2,806 noninstitutionalized men and women living in New Haven, Connecticut. They were interviewed in 1982 as part of the Established Populations for the Epidemiologic Study of the Elderly (EPESE). Ideal profiles based on functional disabilities, chronic diseases, and selected biomedical and behavioral risk factors are constructed empirically. Each individual in the sample is represented by a set of GOM scores, interpreted as degrees of similarity of his or her health record to each of the profiles. Four profiles emerge from GOM analyses: healthy elderly, elderly with cognitive impairment, elderly with impairment in mobility function and physical performance and with selected chronic conditions, and elderly with major limitations in activities of daily living and multiple chronic conditions. Although elderly blacks and whites generally have similar configurations of profiles, there are important differences, especially when chronic conditions are related to specific types of functional impairments. Questions about and claims for black/white mortality crossovers at older ages, usually addressed with aggregate data, are examined conditional on GOM scores that correspond to diverse combinations of disabilities (or lack thereof) together with housing characteristics of cohort members (e.g., whether they live in public housing for the elderly or in owned or rented housing in the community).     

Effects of dependency among causes of death for cause elimination life table strategies

A study is made of the effects of associated causes of death, and of dependency among causes of death, by observing the relative importance of one cause of death when another is eliminated under various competing risk models. Two disease pairs, cancer and infectious disease and stroke and ischemic heart disease, are selected for analysis because they represent different types of disease dependence. Crude probabilities of death for each disease are calculated for the U.S. white male population in 1969. Next, the effects of the complementary disease in a pair are hypothetically eliminated in one of three ways: (a) a standard competing risk adjustment for cause elimination when deaths are singly caused (Chiang, 1968), (b) lethal defect-pattern of failure computations for multiply caused death when no causal order is inferred (Manton et al., 1976), and (c) relative susceptibility, computations for multiply caused deaths when causes are ordered (Wong, 1977). The paper closes with a discussion of the relative merits of the three types of adjustments.     

Methods For Comparing The Mortality Experience of Heterogeneous Populations

Methods are presented which produce Maximum Likelihood Estimates (MLE) of the degree of heterogeneity in individual mortality risks under a variety of assumptions about the age trajectory of those mortality risks. With these estimates of the degree of population heterogeneity it is possible to adjust comparisons of mortality risks across populations for the effects of population heterogeneity, differential mortality selection, and different age trajectories of the force of mortality. These methods are demonstrated by applying a variety of standard assumptions about the age trajectory of the force of mortality to the analysis of a broad range of cohort mortality data for the U.S. and Swedish populations. The estimates of the degree of heterogeneity, produced under all of the selected force of mortality models, consistently indicated a considerable degree of heterogeneity in mortality risks.     

Life table techniques for multiple-cause mortality

A lethal defect-wear model of mortality is presented which rationalizes the assumption of independent risks when death may be due to more than a single condition, Under this model, it is shown how competing risk theory and standard categorical data methods may be merged in a unified approach to the analysis of multiple-cause mortality data. The methodology is used to analyze linkages among diseases in the mortality data and evaluate the implication of the elimination of patterns of morbid states for multiple-cause mortality data from deaths occurring in 1969 in North Carolina.     

Changes in the age dependence of mortality and disability: Cohort and other determinants

Though the general trend in the United States has been toward increasing life expectancy both at birth and at age 65, the temporal rate of change in life expectancy since 1900 has been variable and often restricted to specific population groups. There have been periods during which the age- and gender-specific risks of particular causes of death have either increased or decreased. These periods partly reflect the persistent effects of population health factors on specific birth cohorts. It is important to understand the ebbs and flows of cause-specific mortality rates because general life expectancy trends are the product of interactions of multiple dynamic period and cohort factors. Consequently, we first review factors potentially affecting cohort health back to 1880 and explore how that history might affect the current and future cohort mortality risks of major chronic diseases. We then examine how those factors affect the age-specific linkage of disability and mortality in three sets of birth cohorts assessed using the 1982, 1984, and 1989 National Long Term Care Surveys and Medicare mortality data collected from 1982 to 1991. We find large changes in both mortality and disability in those cohorts. providing insights into what changes might have occurred and into what future changes might be expected.     

Health-Based Population Forecasting: Effects of Smoking on Mortality and Fertility

A microsimulation model, allowing one to forecast short- and long-term population changes conditional on the prevalence of a risk factor in a population, is presented. In this model, population changes result from the aggregation of changes in individual event histories, which, in turn, result from mortality and infertility rates recalculated in accordance with their known relative risks in population groups exposed to a risk factor. Smoking, being the most widespread and influential preventable public health risk factor, is chosen to demonstrate the abilities of the model to forecast the population effects of different hypothetical smoking prevalences. The demographic and population health effects on 20-, 50-, and 100-year projections with the current, hypothetically doubled, and hypothetically halved the current smoking prevalence are analyzed in detail. The model predicts an increase in life expectancy (0.99 year for males and 0.64 years for females), and an increase in population size (2.2-7.5% dependent on the age group) if smoking prevalence is reduced by half. Sensitivity analyses of all findings are performed. The generalization of the model to account for multiple risk factors (e.g., the simultaneous effects of alcohol consumption, obesity, and smoking) and effects on medical expenditures are discussed.     

Mortality of the chronically impaired

An analysis of the effects of diabetes and generalized atherosclerosis on death due to ischemic heart disease or stroke was conducted using multiple cause mortality statistics. Specifically, all U.S. deaths in 1969 were classified into two groups on the basis of whether diabetes or generalized atherosclerosis was mentioned anywhere on the death certificate. Then race and sex specific analyses were made of ischemic heart disease deaths (or alternately of stroke deaths) using modified life table techniques for each group (one with the specified chronic disease and one without). Comparisons were made of mortality due to the acute circulatory events (ischemic heart disease or stroke) in the two groups to determine the implications of the chronic disease for the progression of the circulatory disease events. It was found, according to expectations, that diabetes and generalized atherosclerosis play very different roles in deaths due to stroke and ischemic heart disease.     

Recent trends in multiple-caused mortality 1968 to 1982: Age and cohort components

Declines in mortality at advanced ages have been observed recently in the United States. These declines have been related to a reduction in the risk of major circulatory diseases, such as stroke and heart disease. In this paper we examine the contribution of two additional major factors in those declines. The first is the effect of conditions associated with circulatory diseases. This effect can be examined by using multiple-cause mortality data in which all conditions reported by the physician on the death certificates are recorded. The second is the contribution of cohort mortality differentials to temporal changes. If major cohort differentials are identified, we may be able to determine if recent declines in mortality are likely to continue-and to what levels. Such insights would be useful both in improving projections of the size and age structure of the U.S. elderly population and its entitlement groups and in helping to identify future patterns of needs for preventive and other health services.