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PubMed2002

Recent perspectives on active life expectancy for older women.

This article provides a critical review of recent active life expectancy literature, describing trends of special interest to women. We review findings from leading perspectives used to study life expectancy and active life expectancy, including gender, racial and socioeconomic differences, disease-specific effects, and biodemography. We examine three competing theories of population health that frame active life expectancy research-compression of morbidity, expansion of morbidity, and dynamic equilibrium-concluding there is support for both the compression of morbidity and dynamic equilibrium theories. Policy implications for women include a greater understanding of the role of education and racial and ethnic diversity in active life trends, and an increased public policy emphasis on prevention and treatment of chronic disease, together with adoption of more healthy lifestyles.

Activities of Daily Living↗
PubMed1992

Measurement and utilization of healthy life expectancy: conceptual issues.

The periodic calculation of healthy life expectancies permits the evaluation of the impact of new health policies at a given moment, as well as the assessment of trends under changing health conditions. In spite of their apparent simplicity, the results obtained will have to be interpreted by experts. Useful reference values can be provided by international comparisons. However, several choices remain to be made, such as (i) the types of morbidity and disability data to be associated with mortality data; (ii) the multiple indicators available; (iii) the type of observations to be recorded, i.e., "abilities" or "performances"; (iv) whether or not the recovery of lost functions should be considered; (v) the mode of computation, i.e., life expectancy before the first morbid event or global healthy life expectancy; and (vi) the determination of thresholds based on either relative or absolute criteria.

Activities of Daily Living↗
PubMed2001

Life expectancies among survivors of acute cerebrovascular disease.

BACKGROUND AND PURPOSE: Stroke survivors represent a large group of persons for whom age-differentiated life expectancy tables do not exist. Such tables are vital for many purposes. The aim of the present study was to estimate age- and sex-specific life expectancies among individuals who have survived the acute phase (1 month) of a cerebrovascular disease (CVD). METHODS: All patients who were registered with the Swedish National Hospital Discharge Registry with an admission for CVD (ICD codes 430 to 438) between January 1, 1989, and November 30, 1993, and were alive at the end of 1993 (N=103 591) were followed for mortality rates in 1994. The same was done for 1983. Actuarial analyses were used to convert death rates into life expectancies. RESULTS: Life expectancy among CVD survivors increased with time (1983 versus 1994): 22.9% for men (95% CI 18.3% to 27.6%) and 12.9% for women (95% CI 9.1% to 16.6%). The life expectancy ratio in 1983 between CVD survivors and the general population was 0.571 (95% CI 0.533 to 0.590) for men and 0.578 (95% CI 0.562 to 0.592) for women. In 1994, the corresponding ratios were 0.641 (95% CI 0.629 to 0.654) and 0.611 (95% CI 0.601 to 0.622). The life expectancy ratios between female and male survivors were 1.28 (95% CI 1.23 to 1.34) in 1983 and 1.18 (95% CI 1.15 to 1.21) in 1994. The prognosis for survivors who experienced occlusion and stenosis of the precerebral arteries was better than that for survivors of an intracerebral hemorrhage (P=4.4E-4) or occlusion of cerebral arteries (P=3.8E-8). CONCLUSIONS: Although the prognosis has improved for all ages, stroke survivors still constitute a large group of persons with a low life expectancy compared with the general population.

Acute Disease↗
PubMed2002

Family relationships, social support and subjective life expectancy.

Do supportive personal relationships increase subjective life expectancy? The objective existence of family relationships and the subjective sense of having someone to call on in need may increase the length of life a person expects by creating assurance about the future, by reinforcing healthy habits, and by improving current health. Using the 1995 Aging, Status, and Sense of Control representative sample of 2,037 Americans ages 18-95, we find that having adult children and surviving parents increases the length of life one expects, but young children in the home does not, and marriage only contributes years of life expected for older men. People expect to live longer when they report high levels of emotional support, and the association is mediated entirely by the perception that one has someone to call on when one is sick. People with informal health support expect to live longer than those without it, and this is especially true for persons with physical impairments. Although informal health practices shape subjective life expectancy, they explain little of the effects of supportive relationships. People who smoke, drink heavily, and have poor nutritional habits expect shorter lives, and those who walk and exercise expect longer lives. Better current health is associated with higher subjective life expectancy, but it does not explain the impact of supportive relationships. Most of the impact of supportive relationships appears to be a direct result of projected security about the future. Feeling that you have someone who would care for you if sick appears to increase the sense of security about surviving future health crises, thereby increasing one's perceived inventory of the essential property--life itself.

Adolescent↗
PubMed2003

Monitoring health inequalities: life expectancy and small area deprivation in New Zealand.

BACKGROUND: Socioeconomic and ethnic inequalities in health are of great concern, and life expectancy provides a readily understood means of monitoring such inequalities. The objectives of this study are to (1) measure life expectancy by socioeconomic deprivation and ethnicity, and (2) describe trends in the deprivation gradient in life expectancy since the mid-1990s. METHODS: Three years of national mortality data have been combined with mid-point population denominators to produce life tables within nationally determined levels of small area deprivation (NZDep96) for three ethnic group: European, Mäori and Pacific peoples. This process has been repeated for the periods 1995-97, 1996-98, 1997-99 and 1998-2000. RESULTS: There was a strong relationship between increasing small area deprivation and decreasing life expectancy. Through the mid- to late 1990s, males living in the most deprived small areas in New Zealand experienced life expectancies at birth approximately nine years less than their counterparts living in the least deprived areas; for females the corresponding difference was under seven years.Mäori and Pacific life expectancies at birth were lower than those of Europeans at each level of deprivation.Over the study period (1995-2000) the gradient in life expectancy across deprivation deciles remained stable. CONCLUSION: Small area deprivation analyses of life expectancy could be repeated routinely at regular intervals, which would provide a useful approach to monitoring trends in socioeconomic, geographic, ethnic and gender inequalities in mortality.

Journal Article↗
PubMed2004

[Methodological basics of prognosticating the life expectancy of population in big cities].

The reasons of high mortality and of low life expectancy among Russian citizens as well as their sharp fluctuations observed in the 90-ies were explained differently by researchers, however, no attempt was made to analyze the impact made by a huge inflow of immigrant from the republics of the former USSR and "close abroad" in any case studies. In this paper we point at the fact that the mortality statistics and life expectancy in Moscow were influenced, at least for as long as 12 years, by a systemic error, which made the mortality index higher and the life expectancy lower, among Muscovites, due to overestimates of the absolute number of died Muscovites and to underestimates of the city residents. The 2001 life expectancy of men and women in Moscow calculated on the basis of data, from which non-residents who died in the capital were deleted, was 64.7 and 75.0, respectively, but not 61.7 and 73.5 as represented by the official statistics. The maximum negative effect of death cases of non-residents exerted on the life expectancy coincides with the overall mortality peak value in Moscow: life expectancy of Muscovites for 1994 estimated without accounting of the mortality rate for non-residents turned out to be 3.2 years higher for men and 1.5 years higher for women. Supposedly, the Russian mortality statistics is not nation-wide in line with the actual state of affairs. However, the influence of the discussed systemic error in Russia's regions can be expected to be less pronounced since the level of immigration in Moscow is most probably by far higher.

Data Collection↗
PubMed1999

Life expectancy in Central and Eastern European countries and newly independent states of the former Soviet Union: changes by gender.

AIM: To examine changes in life expectancy at birth for countries in Central and Eastern Europe (CEE) and the Newly Independent States of the former Soviet Union (NIS) for the period 1989-1996. Differences in the change by gender were examined and several factors which likely bear on the changes were discussed. Methods. Data from the WHO Health for All European Data Base were used to determine changes in life expectancy and selected economic factors for CEE and NIS countries. RESULTS: Changes in life expectancy varied by gender in both CEE and the NIS, with the difference increasing for the two groups during the period with the largest increase occurring in the NIS. Both male and female life expectancy declined, with male life expectancy dropping at a more rapid rate. In 1994, the year in which most, but not all countries, reached a low point, life expectancy for males had declined below 60 years for two countries. CONCLUSIONS: The most striking point about the decline in life expectancies was the short period in which the declines occurred, especially in the NIS. It is not possible to determine the exact cause for the changes, but there are likely multiple reasons. It is not completely clear why the decline in life expectancy was greater for males, although the linkage between economic and behavioral and lifestyle factors appear to have some association. Further research is necessary to determine why effects by gender vary so greatly and whether the negative outcomes are a short-term anomaly or will persist.

Asia, Central↗
PubMed2005

[On Hendrikje van Andel-Schipper and other remarkable developments in the life expectancy of the Dutch population].

The Netherlands was home to the oldest living individual in the world, Mrs. Hendrikje van Andel-Schipper, until she died at the age of 115 years on 30 August 2005. She illustrated the remarkable increase in centenarians in many European countries resulting from substantial increases in life expectancy at birth. In 2004, life expectancy at birth in the Netherlands reached a record high of 76.9 years for men and 81.4 years for women. These developments raise important questions on the potential for further increases in life expectancy. Based on an extrapolation of recent trends in cause-specific mortality, Netherlands Statistics predicts an increase in life expectancy of 2 to 3 years in the half-century between 2004 and 2050. Experts are deeply divided about the prospects for further increases in life expectancy. Some have argued that such estimates are too optimistic because, for example, the obesity epidemic might even reduce average life expectancy in the future. Others consider these estimates too pessimistic because, for example, previous estimates of limits to life expectancy have almost always been surpassed. Even relatively modest increases in life expectancy at birth, however, will pose important challenges to health care, social services and pension arrangements.

Aged↗
PubMed1997

Absence of health insurance is associated with decreased life expectancy in patients with cystic fibrosis.

Life expectancy for individuals with cystic fibrosis (CF) has increased dramatically in the last 30 yr, but it is unclear whether the improved survival has applied equally to individuals with different health insurance status. We developed a retrospective inception cohort of all 189 patients with CF born 1/1/55 to 12/31/70 who had at least one hospitalization at a university referral center. The median survival for patients with CF who were without health insurance was 6.1 yr compared with 20.5 yr for those with Medicaid and 20.5 yr for those with private insurance. Using multivariate Cox regression, health insurance and increased socioeconomic status were independently associated with longer survival. The adjusted relative risk of death was greater for the absence of health insurance than for factors previously shown to predict mortality in individuals with CF (female sex and presentation with meconium ileus). In summary, the absence of health insurance was associated with increased mortality rate in children with CF and was a stronger predictor of mortality than variables previously shown to be associated with mortality for CF. If increasing numbers of children with CF lose health insurance coverage, our results suggest that their life expectancy will decrease dramatically.

Adult↗
PubMed1982

Changes in life expectancy in the United States due to declines in mortality, 1968-1975.

This study examines the gains in life expectancy for four race/sex groups of the US population between 1968 and 1975. An increase of 2.3 years in life expectancy at birth and 1.7 years in life expectancy at age 45 years has occurred for all race/sex groups combined. The added years of life for the normal working ages (15-70 years) is only 0.6 years for the total US population, 0.3 years for white females, 0.6 years for white males, 1.5 years for nonwhite males, and 1.7 years for nonwhite females. The relative contribution of the five leading causes of death to this gain varies at different ages. For example, more than 50% of the increase in life expectancy at age 45 years was due to a lower mortality rate in diseases of the heart which is still the leading cause of death among each of the race/sex groups. Other contributions to the increase in life expectancy at age 45 years are: cerebrovascular diseases, 16%; accidents, 6%; influenza and pneumonia, 7%; and all other causes, 16%. The increase in the malignant neoplasms mortality rate had a negative effect, -2%, on the gain of life expectancy.

Accidents↗
PubMed1994

Should years lost always be equated with life expectancy?

BACKGROUND: The 'years lost' by a person dying prematurely from some cause is usually equated with life expectancy at the age of death derived from a life table for either the general population or a population in which the cause does not operate. It is suggested that this procedure may not always be valid. METHODS: The calculation of years lost by individuals dying prematurely from smoking-related deaths is taken as an example using data from the American Cancer Society Cancer Prevention Study (ACS CPS II) and from Peto et al. An alternative hypothesis, whereby smoking advances the age of death by an amount considerably less than the life expectancy, is examined. RESULTS: It is shown that when smoking-related deaths are removed from the ACS CPS II data, the life expectancy of the smokers is still less than that of the non-smokers. Secondly, it is demonstrated that, if the alternative hypothesis is used to predict a survival curve in the absence of smoking, it would be incorrect to equate years lost with life expectancy calculated from that curve. CONCLUSIONS: Years lost cannot automatically be equated with life expectancy. In the case of smoking, estimates of years lost must still be subject to considerable uncertainty. Further research is needed to see if smokers dying at a given age have comparable physical and social characteristics to all smokers living at that age.

Adult↗
PubMed1992

The relationship between life expectancy and socioeconomic status in Arkansas: 1970 and 1990.

Life Expectancy at Birth is estimated for county populations in Arkansas in 1970, 1980 and 1990. Counties are grouped into quintiles at each time point according to the percent of persons below the poverty level. Comparisons are made between mean life expectancy in the highest and lowest socioeconomic group at each point in time as well as between the same group at 1970 and 1990. It is hypothesized that the high socioeconomic populations will experience an increase in mean life expectancy over the low socioeconomic populations between 1970 and 1990. Statistical analysis supports the hypothesis. These findings conform to those from earlier research in Ohio and may reflect a continuing deterioration in the relative standard of living of lower income groups in the United States subsequent to 1970.

Adolescent↗
PubMed2004

Healthy life expectancy--an important indicator for health policy development in Lithuania.

UNLABELLED: The aim of the study was to assess the changes in healthy life expectancy of the Lithuanian population between the years 1997 and 2001 and to explore the differentials of this combined mortality and subjective health measure in males and females. MATERIAL AND METHODS: The data about the Lithuanian population and the deceased were available from the Lithuanian Department of Statistics, life tables for 1997 and 2001 were created and life expectancy estimated. The method presented first by D. F. Sullivan was applied for the assessment of healthy life expectancy. The data on self-perceived health of the Lithuanian population were acquired from the surveys of the health behavior of a randomly selected sample of the adult population of Lithuania, carried out by the Lithuanian Center for Health Education. RESULTS: Healthy life expectancy at birth increased from 52.7 in males and 52.6 in females in 1997 up to 53.7 in males and 55.3 in females in 2001. The proportion of healthy life expectancy in the total life expectancy at birth increased both in males and in females. Though the total life expectancy of males is 10-11 years shorter, females are expected to spend considerably more years in poor health, even though some positive changes were observed. CONCLUSION: Increasing healthy life expectancy reflects improving health of Lithuanian population. This integrated health indicator should be periodically assessed and used for development health strategies to promote health in Lithuania.

Adolescent↗
PubMed1987

Increase in life expectancy at birth in Japan: some implications for variable patterns of decrease in mortality.

"The characteristics of the increase in life expectancy at birth...in Japan were analyzed using the life tables of developed countries in which the values of [life expectancy at birth] were almost the same. When the decrease in age-specific probability of dying...and its contribution to total gain in [life expectancy at birth] in Japan were compared to those of other developed countries, the decline in [age-specific probability of dying] in prime, middle and old age groups accounts for much of the change; the decrease in this variable for males aged 50 years and over accounted for 35% of the recent increase in [life expectancy at birth]. Well-organized medical care and public services are discussed in relation to this unique and unusually rapid increase in [life expectancy at birth] for the Japanese population."

Age Factors↗
PubMed2002

The ethics of life expectancy.

Some ethical dilemmas in health care, such as over the use of age as a criterion of patient selection, appeal to the notion of life expectancy. However, some features of this concept have not been discussed. Here I look in turn at two aspects: one positive--our expectation of further life--and the other negative--the loss of potential life brought about by death. The most common method of determining this loss, by counting only the period of time between death and some particular age, implies that those who die at ages not far from that one are regarded as losing very little potential life, while those who die at greater ages are regarded as losing none at all. This approach has methodological advantages but ethical disadvantages, in that it fails to correspond to our strong belief that anyone who dies is losing some period of life that he or she would otherwise have had. The normative role of life expectancy expressed in the 'fair innings' attitude arises from a particular historical situation: not the increase of life expectancy in modern societies, but a related narrowing in the distribution of projected life spans. Since life expectancy is really a representation of existing patterns of mortality, which in turn are determined by many influences, including the present allocation of health resources, it should not be taken as a prediction, and still less as a statement of entitlement.

Age Factors↗
PubMedDate not supplied

Life expectancy in Germany: possible reasons for the increasing gap between East and West Germany.

The current life expectancy of East and West Germans is different. After the late 1980s, life expectancy at birth in both regions, which was comparable in the early 1950s, became almost three years lower in East Germany. Life-table calculations of German birth cohorts since 1900 revealed that a difference between the groups in cardiovascular disease prevalence was associated with the difference in life expectancy. Whereas migration, environmental pollution, and health-care differences accounted for only a small part of the gap, evidence emerged that lifestyle and social patterns may have caused the less favourable trend in cardiovascular disease. The life-expectancy curve has flattened in East Germany while continuously increasing in West Germany. During the 1960s and 1970s, such opposite trends were due to steeply increasing blood-pressure and cholesterol levels in East Germany and more favourable social development in West Germany--a better average social class (higher educational levels and a lower proportion of working-class individuals), a higher gross national product, and a higher proportion of GNP spent on health. Both the cardiovascular-risk-factor trends and the social gradient have contributed to the gap between the populations of East and West Germany in life expectancy.

Adult↗
PubMed1990

Early natural menopause and the duration of postmenopausal life. Findings from a mathematical model of life expectancy.

Menopause marks the beginning of a stage of life characterized by an increased susceptibility to diseases such as coronary heart disease and osteoporosis. It was therefore hypothesized that early age at natural menopause would lengthen the duration of the postmenopausal stage of life and thereby result in an earlier age at death. This study investigated the relations between age at natural menopause, duration of postmenopausal life (ie, life expectancy at menopause), and age at death (ie, age at menopause plus life expectancy at menopause). Data were derived from a study of 5,287 naturally postmenopausal Seventh-day Adventists observed during 1976-1982. Life expectancy was estimated by a mathematical model that used mortality ratios from the study and mortality rates from the US general population. For natural menopause before the age of 47 years, each one-year decrease in age at menopause was associated with a 0.53-year increase in postmenopausal life (P = .04) and a 0.47-year decrease in the age at death (P = .04). For natural menopause at the age of 47 years and older, however, each one-year decrease in age at menopause was associated with a 0.99-year increase in postmenopausal life (P = .03) and only a 0.01-year decrease in the age at death (P = .85). Overall, these findings argue against the possibility that the association between age at menopause and age at death in this study was due to the relation of age at menopause to the duration of postmenopausal life.

Aged↗
PubMedDate not supplied

Inaccuracies in estimates of life expectancies of patients with bronchial cancer in clinical decision making.

Approximations of life expectancy in clinical decision making frequently assume constant disease-specific ("excess") mortality hazards over age at diagnosis and over time from diagnosis. This assumption is inconsistent with the longer relative survival of younger patients with bladder cancer and with the declines in mortality hazards from bladder and breast cancers over time from diagnosis. To estimate the error that may result from these assumptions, the authors derived excess mortality hazards from the Surveillance, Epidemiology and End Result (SEER) tumor registry for bronchial cancers stratified by age at diagnosis and time from diagnosis. They compared the life expectancies calculated by a model using an average constant annual cancer-specific mortality hazard over time from diagnosis with those calculated using data-derived cancer-specific annual mortality hazards that varied as a function of time from diagnosis. For younger patients with less advanced disease, the constant-average-mortality model underestimated life expectancies by up to 50% relative to those predicted by the time-variant model. For those over 75 years old at diagnosis, and for all patients with advanced disease, the constant-average-mortality model overestimated life expectancies by up to 65% relative to those predicted by the time-variant model. The authors conclude that predictions of life expectancy with bronchial cancer, and probably with other neoplasms, are limited by the widespread use of oversimplified methods of calculation and by the lack of data describing mortality hazards as a function of time from diagnosis.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗