Disability and Mortality Among the Oldest-Old: Implications for Current and Future Health and Long-term Care Service Needs
Citation: Manton, Kenneth G., Soldo (1992) Disability and Mortality Among the Oldest-Old: Implications for Current and Future Health and Long-term Care Service Needs.
Sorry about this seemingly useless description. I wasn't sure exactly what to include since there were pages and pages of this stuff, but it seems like it could pretty much be boiled down to this: Not all elderly are the same in terms of health status and health care needs. It appears that one can define a few groups within the elderly population that are more similar according to health characteristics including an older, pretty health group, a younger quite un-healthy group, an older, seriously ill group (maybe with dementia or something), and a couple of other groups in between.... There are a number of current aging trends in the US that are historically unique: (1) the rapid growth of the oldest old; (2) increases in life expectancy at advanced ages; (3) the predominance of women at advanced ages; and (4) reduction in the age-specific mortality rates of certain major chronic degenerative diseases (e.g., stroke, ischemic heart disease). In this paper, individual health changes at advanced ages are assessed using a broad range of vital statistics, epidemiological, and longitudinal study data. A general model of health changes based upon cohort and life-course perspectives is presented. Manton and Soldo also examine the implications of changes in the health of the oldest old for social and health policy. The model of health changes at advanced ages is represented by a series of survival curves for morbidity, disability and mortality (probability of survival) one inside the other. First, the model is used to examine different perspectives on health changes at advanced ages. One perspective, argued by Strehler (1975) is that as life expectancy reaches its maximum limit, interventions would increase the productive/active life span, but time spent with a chronic disease or disabled would remain the same. In contrast, Gruenberg (1977) and Kramer (1981) suggest that increases in life expectancy will lead only to further increases of time spent diseased or disabled; the onset of morbidity and disability would remain the same while the mortality curve would shift to the right. Similarly, Golini and Egidi (1984) found evidence that for increases in the prevalence of chronic degenerative diseases. More optimistically, Fries (1980, 1983), as we all know, argued for the possibility of the compression of morbidity as we reach the limits of life expectancy. However, Feldman (1982) and Schneider and Guralnik (1988) found little insufficient for such health improvements. Finally, Riley and Bond (1983) found both a high degree of individual variability in rates of aging changes and maintenance of certain physiological functions, even into the 80s. This suggests that all 3 curves can be moved and that, for example, an appropriate allocation of resources can compress the morbid and disabled period, but not with an absolutely fixed mortality curve. This is also represented in Manton's (1982) dynamic equilibrium of morbidity and mortality. A second use of the survival curve model is as a measure or index of health status in elderly populations that summarizes the cross-sectional relation of morbidity, disability, and mortality. A third use of the model is as a device to weight actuarial calculations, not only for changes in life expectancy but also for changes in the portion of life expectancy spent in health states with different health-service needs. The next few sections of the paper treat the vital statistics and epidemiological evidence on the individual components of mortality, morbidity, and disability. Regarding mortality, Manton and Soldo ask if the survival curve has rectangularized. The answer to that question is yes if one examines the entire curve from birth; however, the apparent rectangularization seems more a function of mortality rates at early ages, having reached low levels relative to the mortality rates among the elderly, than of the mortality changes observed at advanced ages. Moreover, at advanced ages, not only has the standard deviation at age of death been constant, the distribution has shifted significantly upward. Regarding morbidity, using data from the Duke Longitudinal Study of Aging (1955-1976), Manton and Soldo use a special analysis (Grade of Membership (GoM) seems sort of like factor analysis) to identify sub-populations that have similar physiological characteristics, demographic attributes, and responses to physical measurements as they relate to morbidity. The groups are originally defined (and are created as a result of the analysis) on physical health and intellectual status; however, there are within-group similarities based on other characteristics, such as age, survival time, and social status. They found a subgroup among the extreme elderly (i.e., mean age over 80) who were healthy and unimpaired and a frail extreme elderly group with multiple chronic diseases (i.e., diabetes, hypertension, dementia, arteriosclerosis) and several functional impairments. They also tended to find a young sub-population (mean age in mid-70s) with severe acute illness and high rates of service use who had short survival. Regarding disability, using data from the 1982 and 1984 National Long Term Care Study (NLTCS), they constructed a scale of disability from items on ADL and IADL limitations. There appears to be stability in disability rates in the community at later ages; however, this is due to mortality and institutionalization of highly disabled persons. Manton and Soldo project an increase in individuals with IADL and ADL limitations from 2000 to 2040. The greatest growth will be among unmarried females aged 75 and older. Manton and Soldo performed other GoM analyses of the NLTCS sample to identify sub-populations (one set based on sociodemographic factors and functional limitations, the other set composed of the institutionalized population based on diagnosis) who represent different target populations in order to evaluate the effect of policy options on the required service mix. Although chronic disease morbidity is most likely to be associated with functional disability among the oldest old, the correlation between age and either morbidity of disability is not sufficiently strong to warrant use of the age group 85+ as a proxy for service need in a population. For these groups, the process of selective survivorship may have already claimed persons most vulnerable to the chronic degenerative diseases that are associated with the highest levels of service need. Targeting services, then, requires identifying groups that manifest a consistent pattern of both need and service use. Using the groups created from the GoM analysis of NLTCS data described above, Manton and Soldo found that the health service profile of each group is appropriate to the group's health status/need profile. At low levels of functional dependence, the need for assistance is most likely to be satisfied in a community setting through the informal caregiving of family, friends, and neighbors. The sources of informal care are quite different by sex and marital status. Men are more dependent on their spouses for informal care. Women receive more care from offspring and relatives. With age, the likelihood of formal-care services increases as it does with increasing disability. Regarding costs of community services (for individual who are not institutionalized but receive formal care), monthly out-of-pocket expenses are greatest for those over age 85. In fact, for persons aged 85+ at the highest and next-to-highest disability levels, expenses are greater than the average for all ages combined. Manton and Soldo apply the health model described above to different types of long-term care service. First, morbidity sets in, then disability, then individuals receive informal care only, then formal and informal care, then institutionalization, then mortality. This model shows that as the population ages, the disabled will not only be older and possibly require more service, but informal care providers also are more likely to be elderly themselves.