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The concepts of life expectation, life expectation without disability, are explained. Their importance for defining a health policy and a healthcare policy is emphasized. A concrete example is given: the inequalities in life expectancy without disability follow the same pattern as the inequalities in mortality.
An increased life expectancy is associated to a nation's progress. Life expectancy at birth is 78 years in developed countries, 72 in Latin America, 70 in China, 63 in Eastern Europe and 51 in Africa. Chile is the Latin American country with the higher increment in life expectancy, reaching 75 years at birth, during the period 1990-95. A higher life expectancy is not always an advantage. People over 60 years old may survive with a burden of chronic diseases or physical and mental disability. The higher health care needs of the increasing population of elderly people is raising the costs of health care in modern nations.
OBJECTIVE: To investigate the sampling distribution and usefulness of expectation of life in comparisons of mortality at health district level or below. DESIGN: Derivation of a formula for the variance of the expectation of life, confirmation of the result and generation of the sampling distribution by Monte Carlo simulation; comparison of expectation of life with standardised mortality ratio (SMR) and other summary indices of mortality. SETTING: A health district in Trent Region, England. SUBJECTS: Routinely available mortality statistics at electoral ward level and above. MAIN RESULTS: Given reasonable and simple assumptions the sampling distribution of the expectation of life is approximately normal. Expectation of life shows a high negative correlation with SMR even if the oldest age band for the SMR is open ended. CONCLUSIONS: Where sampling error is an issue, inference concerning differences in mortality rates between populations can be based on expectation of life, which is better for illustrative purposes than SMR. The formula for the variance of the expectation of life is more complex however. If the final age band is open ended, its lower bound should be as high as possible to avoid misleading results caused by hidden differences in age structure.
Dementia-free life expectancy is a synthetic indicator of an important aspect of mental health which may have considerable use in public health decision making. Dementia expectancies were derived from senile dementia prevalence rates in Australia in 1991-1992 in conjunction with national life tables using Sullivan's method. Dementia-free life expectancy for Australian women aged 70 years was found to be 14 years within a total life expectancy of 15 years, and 11 years for men within a total life expectancy of 12 years. Between 70 and 85 years there is a constant average expectation of about one year of life expectancy with dementia. The age at which the largest number of persons with dementia is found is 82 years. Australians appear to have very similar dementia-free life expectancies to those reported in the European studies, with small differences probably due to sampling variation or to differences in case-finding methods.
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This article presents health expectancy calculations from Bulgaria for 1976-1992. The calculations are based on mortality statistics and data from a national information system from the Expert Medical Commissions on Working Capacity about loss of working capacity. Following internationally accepted terminology, the most appropriate term for the health expectancies presented here is "occupational handicap-free life expectancy' (OHFLE). Life expectancies were calculated as partial life expectancies from ages 16 to 59. Health expectancy calculations followed Sullivan's cross-sectional method with age and sex specific prevalence data on occupational handicap. Around 1985 a three- to four-fold increase in these prevalences occurred. The distribution of occupational handicaps over sexes, age groups and severity levels, however, remained fairly constant. The results show a decrease both in partial life expectancy within the age range 16-59 and in OHFLE at the age of 16 for men. For women a more or less stable partial life expectancy and a decrease in OHFLE at the age of 16 was found around 1985. The introduction of more incentives for people who successfully registered probably caused the decrease around 1985. Major social changes may have acted as confounding factors for the fluctuations after 1985. On the other hand the findings may reflect real changes in population health due to an increasing incidence in some major disease categories. The nation-wide system for assessment and registration of health related working incapacity has proved a useful source for an attempt to calculate OHFLE. Given uncertainties about the population health underlying these changes in OHFLE, however, it is recommended that health interview and health examination surveys should be considered as alternative routes for achieving a more comprehensive picture of population health in Bulgaria.
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Life-table analysis is a suitable method for evaluating the effectiveness of therapeutical approaches to and the progression of, chronic diseases. The authors performed 324 liver biopsies in patients with liver disease between 1976 and 1986. The cumulative life-table analysis of Cutler and Ederer was applied in this retrospective study. Survival rates of different groups of patients expressed as the 7-year life expectancy were as follows: toxic hepatitis 90%, steatosis hepatitis 87%, chronic persistent hepatitis 87%, nonspecific reactive hepatitis 76%, chronic active hepatitis 72%, acute alcoholic hepatitis 66%, liver cirrhosis 40%. There seems to be a correlation between the severity of histological alteration and live expectancy. A similar correlation between the inflammatory cell infiltration and life expectancy cannot be observed. The life expectancy of patients with chronic active hepatitis has significantly improved recently. Further improvement of survival of patients with liver cirrhosis can be expected only from a reduction of alcohol consumption. The results can be regarded as a reference data for life expectancy of patients with chronic liver disease in Hungary.
BACKGROUND AND METHODS: Persons of low socioeconomic status are known to have reduced life expectancy. In a study of the relation of socioeconomic status to disability-free or active life expectancy among older persons, we analyzed prospectively gathered data on 2219 blacks and 1838 whites who were 65 years of age or older in the Piedmont region of North Carolina. We defined disability as the inability to perform independently one or more basic functional activities such as walking, bathing, dressing, eating, and using the toilet. For subgroups defined by sex, race, and education, statistical models were used to estimate, for persons at each year of age, the probability of transition from not being disabled or being disabled at base line to not being disabled, being disabled, or having died one year later. These transition probabilities were then entered into increment-decrement life tables to generate estimates of total, active, and disabled life expectancy (with total life expectancy equal to active life expectancy plus disabled life expectancy). RESULTS: Sixty-five-year-old black men had a lower total life expectancy (11.4 years) and active life expectancy (10 years) than white men (total life expectancy, 12.6 years; active life expectancy, 11.2 years), although the differences were reduced after we controlled for education. The estimates for 65-year-old black women (total life expectancy, 18.7 years; active life expectancy, 15.9 years) were similar to those for white women. Black men and women 75 years old and older had higher values for total life expectancy and active life expectancy than whites, and the differences were larger after stratification for education. Education had a substantially stronger relation to total life expectancy and active life expectancy than did race. At the age of 65, those with 12 or more years of education had an active life expectancy that was 2.4 to 3.9 years longer than the values for those with less education in all the four subgroups defined by sex and race. Overall, the subgroups with longer total life expectancy and active life expectancy also lived more years with a disability. CONCLUSIONS: Among older blacks and whites, the level of education, a measure of socioeconomic status, has a greater effect than race on total life expectancy and active life expectancy.
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Mortality rates and measures of life expectancy are widely used to compare and monitor health within populations. However, there is a need to add dimensions of population health other than survival. An alternative measure, 'active life expectancy', is a way of quantifying the functional health of older adult populations and, in part, measuring quality of life. Life-table techniques are used to define the expected duration of well-being. Instead of death, the end-point of active life expectancy is loss of independence in activities of daily living. Initial studies showed that active life expectancy decreased with age, from 10 years to 4.7 years and 2.9 years, respectively, for people entering the age intervals 65-69, 80-84 and 85 years and over. Since cardiovascular disease is the major cause of disability in the older adult population, measures of active life expectancy can provide improved information about functional independence and dependence. Life tables with estimates of active life expectancy can be used as a basis for determining the needs of age cohorts of people with hypertension and other conditions.
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.
Life expectancy at birth in southern Europe is known to be greater than expected in comparison with levels of economic development. This has been attributed to the 'Mediterranean diet'. There are, however, concerns that this comparative advantage is being lost. This paper examines the factors underlying changing life expectancy in Italy since 1980. The subjects of this analysis are obtained from data on all deaths in Italy between 1980 and 1992. Change in age specific death rates is calculated from selected causes and, using the method developed by Pollard, the contribution of deaths from different causes and at different ages to changing life expectancy at birth is estimated. Between 1980 and 1992, life expectancy at birth increased by 2.70 years for men and 2.75 years for women. Death rates have fallen among children and those over 40. In contrast, death rates have increased among men aged between 20 and 39 and have increased very slightly among women aged 25-29. Falling death rates from ischaemic heart disease are continuing to contribute to increasing life expectancy. Death rates from lung and breast cancer are rising among women but are compensated for by falling death rates from other cancers. Among men, falling death rates from cancer at younger ages are being offset by increases at older ages. The rising death rate among younger men is almost entirely due to AIDS, with accidents also making a small contribution. Life expectancy in Italy has improved throughout the 1980s, largely driven by falling death rates from cardiovascular diseases. Here are, however, some worrying trends, most notably the rising death rate among young men, due almost entirely to AIDS. The changing pattern of mortality has some similarities with Spain, another Mediterranean country, but there are also important differences.
Life expectancy of males in the Slovak Republic, a small postcommunist country in Central Europe, is among the lowest in Europe due to the extremely high mortality rate in middle-aged men. The relation between male life expectancy at age 20 and several variables (i.e. ethnic structure, educational status, religious belief and economic activity) was analysed by simple regressions and by multifactorial methods in all 38 districts of Slovakia. Significant negative associations were found between male life expectancy at age 20 and ethnic structure (i.e. percent of Hungarian population), economic activity (percent of men employed in agriculture) and educational status (percent of men having only a basic education). In multifactorial analysis educational status and ethnic structure entered the model. The most dramatic health decline occurred in agricultural southern districts with high percentage of Hungarian minority and with high percentage of men with the lowest educational status. Lifestyle probably presents the background of these relations, but there is a lack of reliable data from the individual districts for a more profound analysis. More sophisticated epidemiological research projects are important for the formulation of a public health strategy in Slovakia.
In 1993 the expectation of life in the United States apparently declined slightly. Newborns could expect, on average, to live 75.4 years; for baby boys the figure was 72.0 years and for girls 78.7 years. Each of these values represents a decline of 0.3 years from the 1992 provisional expectancies prepared by the National Center for Health Statistics, and results in average future lifetime returning to the 1990-91 level. Last year's decrease in life expectation was primarily brought about by the considerable rise in the absolute number of deaths and the corresponding increase in mortality rates. Indications are that mortality increased from all major forms of death as well as from AIDS. It is estimated that there were 2,260,000 deaths in 1993 compared with the provisional count of 2,177,000 in 1992 and the final figure of 2,169,518 in 1991. Notwithstanding, projections indicate that expectation of life will continue to rise into the foreseeable future although occasional small declines are likely such as that reported for 1993.
Contrasts in life expectancy among countries are an important input for defining targets for the health service and for setting priorities for disease prevention and health promotion. In this article, the trend in life expectancy in Norway is compared with the trend in a selection of other OECD countries. Standardised measures of life expectancy were collected from WHO and OECD statistics. In 1960 Norwegians ranged among the top three countries as regards life expectancy for both women and men. In 1990 Norwegians ranged tenth for women and ninth for men. Life expectancy was two years shorter for Norwegian than for Japanese women in 1990, corresponding to a 20% surplus mortality throughout life. Similar differences were found for men. If Japanese age specific death rates are applied to the Norwegian population, this corresponds to a reduction of 9,600 deaths this year. The relatively unfavourable trend in life expectancy in Norway relative to other OECD countries raises concern, and should be considered when designing the future health policy.