Active Life Expectancy. Introduction

Introduction.Active life expectancy (ALE) is a useful, and increasingly used, concept for measuring the combined health, func­tional, and longevity status of relatively long-lived national populations. It has recently received emphasis as a public health measure for cross-national comparisons ofthe health of economically developed countries by, for example, the World Health Organization (Robine and Michel, 2004).

This was, in part, because health policy analysts became concerned that life expectancy in developed countries might continue to increase, not primarily because of improved health, but rather due to increasingly expensive medical interventions that possibly were increasing the length of life spent in disabled life states at later ages with poor quality of health and impaired function.

This concern emerged most strongly in the United States in the early 1980s because actuaries at the Social Security Administration (SSA) had failed to anticipate the renewed acceleration of the increase in overall life expec­tancy in the United States starting in 1969 after significant declines in male life expectancy due to increased cardio­vascular disease mortality rates had been observed from 1954 to 1968. This was because the SSA actuarial fore­casting models were based on extrapolations of prior long­term (e.g., 10-year) cause-specific national mortality trends.

Thus, when U.S. male mortality started to increase in 1954 due to increased circulatory disease risks, a trend that continued to 1968, their cause-specific mortality projections in the early 1970s, based primarily on that 14-year period of adverse male mortality experience, suggested that life expectancy would not increase further in the United States as a result of having reached what some demographic researchers believed was the biological upper bound to human life expectancy (Myers, 1981). This occurred despite U.S. female’s life expectancy continuing to increase over the same period.

In 1982, sufficient new positive U.S. male mortality experience (e.g., from 1969 to 1980) had accumulated to suggest, in contrast to the prior SSA projections, that continuing future reductions in adult male morta­lity would be likely and, therefore, future increases in life expectancy. As a consequence, it became necessary to consider how to change the normal retirement age (then 65) for the income-support component of the U.S. Social Security program to preserve the long-term (75-year) fiscal integrity of the SSA trust fund.

Although the evidence on U.S. life expectancy increases after 1968 was strong and consistent, there did not exist sufficient data on the direction and magnitude of the longitudinal correlation of disability and morbidity trends with those life expectancy increases to confidently determine the quality of life and level of functioning in the increasing number of years expected to be lived at ever more advanced ages (e.g., at ages 65 and above) (Feldman, 1983).

This concern was supported by a number of public health researchers who argued that it was the intrinsic nature ofmodern industrial society (e.g., due to social stress and environmental pollution) to increase the prevalence of chronic diseases. They viewed modern industrial society as incapable of mounting effective public health responses to chronic disease pandemics or to modulate the effects of those chronic health problems on functioning at later ages (e.g., Kramer, 1980; Gruenberg, 1977).

These pessimistic arguments, however, were also based on insufficient longi­tudinal national morbidity and health data and thus were speculative. For example, many examples were taken from the mental health arena, where disease definition and diag­nosis are often difficult and ambiguous. One set of argu­ments was based on the increased survival of persons with certain genetic disorders to reproductive age because of medical advances (e.g., the improved surgical repair of cardiac anomalies in persons afflicted with Down’s syn­drome (Greunberg, 1977)). This, it was argued, would serve to increase the future prevalence of these genetic syndromes and their health and functional sequelae.

In contrast, other authors (e.g., Fries, 1980) suggested that by appropriately targeting preventative measures (e.g., exercise and nutrition programs) to the general elderly population - and rehabilitation services to the disabled elderly - the period of life expected to be spent without chronic disability could increase faster than total life expec­tancy.

This beneficial state of population health dynamics was called ‘‘morbidity compression’’ (Fries, 1980). Fries, however, continued to assume that the upper bound for life expectancy was biologically fixed. Manton (1989) argued, in his dynamic equilibrium model, that the cor­relation of disability-free and total life expectancy was not genetically fixed but modifiable through appropriate public health policy supported by biomedical research intended to improve clinical and rehabilitative interven­tions in disablement processes and chronic morbidity at late ages.

Recent analyses (Manton et al., 2006b) tend to support the dynamic equilibrium model in that active life expectancy continues to increase faster than overall life expectancy.

A different, but equally optimistic, argument suggested that modern societies had indeed evolved in ways that would better support the genetic constitution of humans by modifying many social, environmental, and medical conditions.

This complex dynamic situation, labeled by Professor Robert Fogel of the University of Chicago ‘‘techno-physiological’’ evolution, reflects both improve­ment in nutrition and environmental quality (e.g., water treatment), which, by increasing body size and strength, led to increased economic productivity and reduced health problems through rapid modification of technol­ogy and environmental quality. In such conditions, health improvements occurred far more rapidly than they could have if changes were solely dependent on genetic selection operating over multiple biological generations.

Fogel’s formulations were, fortunately, empirically veri­fiable by using data on the health of Union army soldiers both at enlistment in the Civil War (the Gould sample) and later, when Civil War veterans applied for pensions from 1900 to 1910. The health of Union army veterans could be compared, for example, with veterans of World War II as assessed in national health surveys such as the National Health Interview Surveys (NHIS) and the National Health Nutrition and Examination Survey (NHANES) in the late 1980s and early 1990s. It was found that many chronic diseases (e.g., CVD) and chronic disability declined 6% over prevalence per decade in most of the twentieth century.

Associated with these trends, body mass index (BMI) increased as life expectancy increased. Fogel argued that increases in BMI reflected better health as a result of improved nutrition and water quality and reductions in caloric expenditures directed to fighting acute and chronic effects of infectious diseases.

The rate of improve­ment in health and functioning, in multiple analyses of the National Long Term Care Surveys for 1982 to 2004, was observed to accelerate starting in 1982 - results confirmed both in other national surveys (e.g., the Medicare Current Beneficiary Survey (MCBS), the Health and Retirement Survey (HRS), and the NHIS) and in Medicare expendi­ture and service use files longitudinally linked to the 49 000 sample persons from the six National Long Term Care Surveys (NLTCS).

In contrast, recent increases in BMI were argued by Lakdawalla and others (2005) to represent a potential health risk for the future U.S. elderly population by causing increas es in disabili ty prevalence (e.g., as early as 2012 to 2015), although the most recent available data (i.e., the 2004 NLTCS; Manton et al, 2006a) do not yet show such adverse health effects. Indeed, recent analyses of the relation of BMI to mortality and morbidity by Flegal and other researchers at the U.S. Center for Dis ease Control suggested prior estimates of the health and mortality effects of elevated BM I had been overestimated because of a failure to use recent data reflecting large improve­ments in the medical management of such obesity-related risk factors as hypertension, hypercholesterolemia, and elevated blood glucose. Rand researchers, in a com­prehensive report to the CMS actuaries, also did not find a significa nt relation of elevated BMI to Medicare expenditures to at least 2030.

Since it was argued that there were insufficient data on disability and morb idity in 1980 to evaluate the longitudi­nal correlation of age trends in the prevalence of disability and longevity, it was decided in 1982 by Congress and the Greenspan Commission to conservatively increase the SSA normal retirement age by only two year s (from age 65 to 67) starting in 2000, with the increase to be phased in gradually by 2020. No corresponding changes were pro­posed for the Medicare entitl ement age, which was left at age 65. A number of Euro pean countries an d Japan have begun to con sider similar changes.

In Britain, an increase in the normal retireme nt age to 67, with a further increase to age 69 in 2050, is being considered. It has be en suggested that pension benefits in Japan be restricted to a fixed proportion of the total population. To maintain pension coverage for 17% of the Japanese popu lation would require, with current Japanese mortality, incr easing the normal retirement age to 73.2 years.

It is thus of interest that recent U.S. Bureau of Labor Statistics projections of labor force participation rates at ages 65+ from 2004 to 2014 suggest there will be significant future increases in the economic activity of the U.S. elderly population.

A number of economists suggest that increased labor force activity in the United States at later ages may be stimulated by the transition from defined-benefit pension programs to joint individual-enterprise savings pension programs such as 401(k) systems (defined contribution pensions), in which benefits continue to increase as long as one continues to work and pay into the system.