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At least 19 recordsLinked to original sources
PubMed1999

[Physio-social activities and active life expectancy, life expectancy in Japanese elderly].

PURPOSE: Incidence of loss of activity and death in elderly people living at home were investigated to attempt to determine their relationship to physio-social activities in elderly. METHOD: This longitudinal study of life expectancy and active life expectancies is a thirty-six months follow up study. Loss of activities were classified as follows: Long term (over six months) treatment at home, long term (over six months) admission to hospital or intermediate institute for the elderly, admission to nursing home, and death. Subjects were persons living at home in Ogi, Saga prefecture, aged 70 years or older not requiring help in active daily living (ambulating, bathing, dressing, discharging, eating). RESULTS: 6,274 (male = 2,383, female = 3,891) subjects were followed for thirty six months, and 178 people experienced long term treatment at home, 310 people had long term admission to a hospital or intermediate institute for elderly, 28 people were admitted to a nursing home and 449 people experienced death. The main results were as follows: (1) From the Cox proportional hazards model using the likelihood-ratio method of survival and active life loss, significant hazard ratios for reduction active life expectancy for male were found for age, disability score for ADL, speech disorder, inconvenient bathroom design, with attention to health, and daily activity were associated with extension of active life expectancy. Age, disability score for ADL, speech disorder, inconvenient bathroom design were associated with reduced life expecting, while, attention to health, choosing to undergo regular health examinations, and daily were associated with increased activity in life expectancy. (2) Hazard ratios for reduction active life expectancy for females were age, disability score for ADL, defect of memory deficits, inconvenient design for hallway and stairs. Participating in health examinations, Purpose in life were associated with life expectancy increase. For females were age, disability score for ADL, speech disorder, inconvenient design of bathroom were associated with decrease in life expectancy, while having a person in life was associated with increase in life expectancy. DISCUSSION: Relationship between physio-social activities in elderly is a significant factor in many studies on elderly health. This study suggests that age, disability score for ADL, inconvenient for housing design, active health behavior, daily activities, and Losing a sense of worth in living, affect active life expectancy and life expectancy.

Activities of Daily Living↗
PubMed1998

[Active life expectancy, life expectancy and ADL in Japanese elderly].

The purpose of the present Study is to analyze the incidence of loss of active life and death rates over a 36 month period in elderly people living a home, to attempt to determine relationships of index of ADL for bed ridden elderly to incidence and expectancies of active life loss, for life and active life. The definition of loss of activities was as follows: Long term (over six months) medication at home, long term (over six months) admission to hospital or intermediate institute for elderly, admission to nursing home or death. Subjects were 6,883 people living at home in Ogi, Sage prefecture, aged 70 years or older. A total of 6,753 people could be followed up for thirty six months, with 287 people having long term medication at home, 389 people having long term admission in hospital or intermediate institute for elderly, 45 people were admission to nursing home and of these groups defined as experiencing, 490 people were died of all subjects, 746 deaths were observed. The main results were as follows: (1) Annual mortality rate was 5.4% for males, 3.0% for females, and annual rate of active life loss was 7.1% for males, 6.0% for females. Life expectancy for the 70-74 year group was 13.7 years for male, 17.9 years for female, and active life expectancy for the 70-74 year group was 12.0 year for males, 13.9 years for females. The difference between life expectancy and active life expectancy was 1.7 years for male, 4.2 years for female, which can be considered the average length of term requiring care. (2) From the relation between scale of active daily living for the handicapped elderly and the life expectancies of life and active life by Cox proportional hazard model analysis of survival, controlling for age and sex, five categories of classification for active daily living for a handicapped elderly were developed: 1-very healthy with abilities for using transportation (train and bus); 2-abilities of moving in the neighborhood by oneself; 3-abilities of moving in the neighborhood with help; 4-Chair-bound, 5-Bed-bound.

Activities of Daily Living↗
PubMed1989

A state-based regression model for estimating substate life expectancy.

Life expectancy is an important indicator of the level of mortality in a population. However, the conventional way of calculating life expectancy--constructing a life table--has rigorous data requirements. As a consequence, life expectancy data are not usually available for substate areas. In this article, a regression model for estimating life expectancy is constructed, using state-level data, and is tested against two sets of 1980 life expectancy data: (1) a nationwide sample of metropolitan areas and (2) selected cities, their suburbs, and rural counties in Ohio. An additional test shows the sensitivity of the model's accuracy to errors in one of its input data elements. The results suggest that the model should be given serious consideration for generating life expectancy estimates for substate areas.

Demography↗
PubMed1993

[Social determinants of life expectancy].

"Life expectancy and mortality increasingly are analyzed in the context of social factors. This study analyzes the impact of social position, marital status, and religious confession on cohort life expectancy. The analysis is based on [German data from the] Socio-Economic Panel Survey, wherein proxy-interviewee's parents have been used to estimate cohort mortality. Results confirm a lower mortality risk of the upper classes and of married persons. However, as opposed to other studies, Catholics do not have a lower, but even a higher mortality risk." (SUMMARY IN ENG)

Cohort Studies↗
PubMedDate not supplied

Oral contraceptives and life expectancy.

Life expectancy for women in the United States is 77.34 years; women who take oral contraceptives (OCs) for five years before the age of 30 can expect to live about four days longer. This is due primarily to protection against ovarian and endometrial cancers. For women taking pills for five years in their thirties there is a maximum loss of 18 days on the average that is attributable to OC use, and for women over 45 this rises to 80 days. The decreased life expectancy is due mainly to the increased mortality from myocardial infarction and stroke. This is substantially less than life lost due to use of a variety of other substances, most notably tobacco.

Adolescent↗
PubMed1996

[Male life expectancy and prolongation of life expectancy were lowest in small towns in Japan].

The relationship between size of population and life expectancy of residents was investigated in 652 cities in Japan, using municipal life tables for 1985 and 1990. The following findings were seen: 1) Population size and life expectancy Life expectancy of males at age 0, 20 and 40 was lowest in small towns with a population less than 30,000 (except for age 40 in 1985), and highest in cities with a population of 70,000-199,999 in 1985 and 1990. Life expectancy of females at age 0, 20, 40 and 65 did not significantly vary with size of population in 1985 and 1990. 2) Population size and prolongation of life expectancy (1985-1990) Life expectancy was prolonged in males by 1.02, 0.88, 0.86 and 0.66 years at age 0, 20, 40 and 65, respectively. The prolongation of life expectancy of males at age 0, 20 and 40 was smallest in small towns with a population less than 30,000. Life expectancy was prolonged in females by 1.41, 1.32, 1.29 and 1.12 years at age 0, 20, 40 and 65, respectively. The prolongation of life expectancy was shortest at birth for females who lived in cities with a population of 50,000-59,999. 3) Socioeconomic factors and prolongation of life expectancy The prolongation of life expectancy of males was related to the entrance rate for high school and inversely related to the unemployment rate. The prolongation of life expectancy of females was not related to any of the socioeconomic factors studied.

Adult↗
PubMed1988

On the decomposition of changes in expectation of life and differentials in life expectancy.

The projection of mortality rates requires inter alia close examination of the mortality experience of a population over a long period of time and will usually also involve the analysis of mortality trends by cause of death. In two of the more important recent contributions, techniques were devised for explaining change in life expectancy in terms of mortality changes in particular age groups and by different causes of death. The approaches adopted by the authors differ, and the purpose of this article is to reconcile the two and tie the results in with those obtained by earlier writers. A new method for explaining the change in a life expectancy differential in terms of the observed changes in the mortality differentials and the observed change in overall mortality level is also described.

Adolescent↗
PubMed1992

Does increased life expectancy imply active life expectancy?

From Danish results, it is argued that longer life need not imply worse health. If we as individuals and society will prevent the "pawnbroker-diseases," increase access to geriatric rehabilitation, and supply necessary services in an individualised way, most added years can be active years. The following conclusions are drawn: In the first decades after the year 2000, morbidity, disability and mortality will be postponed, but treatment will be more important for prolongation of life than prevention. Therefore, the net result will be extension of morbidity. The next question is how severe disability will be among the increased number of people who have a disease, but are not dying from it. The elderly will be more healthy in the future, but the prevalence of chronic disabling diseases may not change, or may even increase. That is because healthy men and women can postpone disability and death until higher ages (successful aging), but some elderly persons live with premature disabling diseases, which might have killed them some decades ago. When elderly people make the transition from autonomy to dependence in the course of a disease, it is possible by early geriatric intervention and rehabilitation to restore them to functional levels and provide them with more active years. It is possible to disseminate geriatric rehabilitation to a much wider population of elderly with multipathology and social problems. In this way, disability can be overcome in a higher fraction of diseased elderly.(ABSTRACT TRUNCATED AT 250 WORDS)

Activities of Daily Living↗
PubMed1997

Achievement domain and life expectancies in Japanese civilization.

Previous studies have found that the expected life span of eminent personalities may vary systematically according to the domain of achievement. The current investigation examines this phenomenon more closely by 1) introducing methodological controls for potential gender and cohort artifacts, 2) adding substantive predictors (e.g., suicide and homicide) that provide clues regarding the substantive basis for the differences, 3) scrutinizing a greater variety of achievement domains in both creativity and leadership, and 4) using a non-Western sample of historical figures (1,632 Japanese born between 450 and 1883 A.D.). Multiple regression analyses revealed domain contrasts in life expectancy (e.g., the shorter life spans of fiction authors and political figures, but the longer life spans of religious leaders and sword makers). In addition, the analyses helped decipher the extent to which these domain differences were due to violent death or to the stress of occupying high positions of power.

Achievement↗
PubMed1997

Regional patterns of disability-free life expectancy and disability-adjusted life expectancy: global Burden of Disease Study.

BACKGROUND: Information on non-fatal health outcomes of disease and injury has been largely neglected in health planning because of the conceptual and definitional complexity of measuring morbidity and disability in populations. One of our major objectives was to quantify disability for inclusion in health policy debates. We analysed these health outcomes in terms of disability-free life expectancy (DFLE) and disability-adjusted life expectancy (DALE). METHODS: Published and unpublished data were systematically reviewed to estimate the incidence, prevalence, and duration of 483 disabling sequelae of 107 diseases and injuries. To ensure internal consistency of these estimates, a software programme (DISMOD) was applied many times until consistent parameters were identified. The severity of disability, on a scale of 0 (perfect health) to 1 (death), was measured in a deliberate manner by the person-trade-off method. Spearman's and Pearson's correlation coefficients were used to measure disability weights among groups. Prevalence of seven classes of disability was back-calculated from the distribution of each disabling sequela across disabilities. Prevalence for each class of disability for different age-sex groups was used to calculate seven forms of DFLE and DALE based on Sullivan's method. FINDINGS: Prevalence of most disability classes is highest in sub-Saharan Africa and lowest in established market economies. Low-severity disabilities (class I and class II) are the most common. The expectation at birth of class I disability ranges from 6.5 years in established market economies to 14.7 years in sub-Saharan Africa, and for class II disabilities, from 8.5-18.4 years. DFLE varies significantly among regions: DFLE for class I disabilities at birth ranges from 9.9 years in sub-Saharan Africa to 47.7 years in established market economies for females and DFLE for class V disabilities ranges from 43.4 years for men in sub-Saharan Africa to 74.8 years for women in established market economies. The proportion of expected life span at birth lived with disability adjusted for severity, varies from about 8% in established market economies to 15% in sub-Saharan Africa, with little difference between men and women. In high-income regions, nearly 90% of expected disability is due to non-communicable diseases and most of the remainder to injuries. In poorer regions, almost half of expected disability is due to communicable diseases and injuries. INTERPRETATION: The higher proportion of lifespan spent disabled in high-mortality populations is consistent with the compression of morbidity hypothesis. The threshold definition of disability used substantially affects the results of DFLE, DALE, which incorporates severity weights for disabilities, is a useful summary measure of the burden of disability and mortality.

Adolescent↗
PubMed2003

Obesity in adulthood and its consequences for life expectancy: a life-table analysis.

BACKGROUND: Overweight and obesity in adulthood are linked to an increased risk for death and disease. Their potential effect on life expectancy and premature death has not yet been described. OBJECTIVE: To analyze reductions in life expectancy and increases in premature death associated with overweight and obesity at 40 years of age. DESIGN: Prospective cohort study. SETTING: The Framingham Heart Study with follow-up from 1948 to 1990. PARTICIPANTS: 3457 Framingham Heart Study participants who were 30 to 49 years of age at baseline. MEASUREMENTS: Mortality rates specific for age and body mass index group (normal weight, overweight, or obese at baseline) were derived within sex and smoking status strata. Life expectancy and the probability of death before 70 years of age were analyzed by using life tables. RESULTS: Large decreases in life expectancy were associated with overweight and obesity. Forty-year-old female nonsmokers lost 3.3 years and 40-year-old male nonsmokers lost 3.1 years of life expectancy because of overweight. Forty-year-old female nonsmokers lost 7.1 years and 40-year-old male nonsmokers lost 5.8 years because of obesity. Obese female smokers lost 7.2 years and obese male smokers lost 6.7 years of life expectancy compared with normal-weight smokers. Obese female smokers lost 13.3 years and obese male smokers lost 13.7 years compared with normal-weight nonsmokers. Body mass index at ages 30 to 49 years predicted mortality after ages 50 to 69 years, even after adjustment for body mass index at age 50 to 69 years. CONCLUSIONS: Obesity and overweight in adulthood are associated with large decreases in life expectancy and increases in early mortality. These decreases are similar to those seen with smoking. Obesity in adulthood is a powerful predictor of death at older ages. Because of the increasing prevalence of obesity, more efficient prevention and treatment should become high priorities in public health.

Adult↗
PubMed2001

Inequality in life expectancy, functional status, and active life expectancy across selected black and white populations in the United States.

We calculated population-level estimates of mortality, functional health, and active life expectancy for black and white adults living in a diverse set of 23 local areas in 1990, and nationwide. At age 16, life expectancy and active life expectancy vary across the local populations by as much as 28 and 25 years respectively. The relationship between population infirmity and longevity also varies. Rural residents outlive urban residents, but their additional years are primarily inactive. Among urban residents, those in more affluent areas outlive those in high-poverty areas. For both whites and blacks, these gains represent increases in active years. For whites alone they also reflect reductions in years spent in poor health.

Activities of Daily Living↗
PubMed1991

Expected gains in life expectancy from various coronary heart disease risk factor modifications.

BACKGROUND: Despite much evidence that modifying risk factors for coronary heart disease can decrease morbidity and mortality, little is known about the impact of risk-factor modification on life expectancy. METHODS AND RESULTS: We used the Coronary Heart Disease Policy Model, a state-transition computer simulation of the US population, to forecast potential gains in life expectancy from risk-factor modification for the cohort of Americans turning age 35 in 1990. Among 35-year-old men, we projected that the population-wide increase in life expectancy would be about 1.1 years from strict blood pressure control, 0.8 years from smoking cessation, 0.7 years from reduction of serum cholesterol to 200 mg/dl, and about 0.6 years from weight loss to ideal body weight. For women, reducing cholesterol to 200 mg/dl would have the greatest estimated impact-a gain of 0.8 years-whereas smoking cessation, blood pressure control, or weight loss would yield population-wide gains of 0.7, 0.4, and 0.4 years, respectively. Gains for 35-year-old individuals having a given risk factor are greater. We estimate that, on average, male smokers would gain 2.3 years from quitting smoking; males with hypertension would gain 1.1-5.3 years from reducing their diastolic blood pressure to 88 mm Hg; men with serum cholesterol levels exceeding 200 mg/dl would gain 0.5-4.2 years from lowering their serum cholesterol level to 200 mg/dl; and overweight men would gain an average of 0.7-1.7 years from achieving ideal body weight. Corresponding projected gains for at-risk women are 2.8 years from quitting smoking, 0.9-5.7 years from lowering blood pressure, 0.4-6.3 years from decreasing serum cholesterol, and 0.5-1.1 years from losing weight. Eliminating coronary heart disease mortality is estimated to extend the average life expectancy of a 35-year-old man by 3.1 years and a 35-year-old woman by 3.3 years. CONCLUSIONS: Population-wide gains in life expectancy from single risk-factor modifications are modest, but gains to individuals at risk can be more substantial.

Adult↗
PubMedDate not supplied

Mixed life expectancy changes.

Life expectancy for the U.S. total population was essentially unchanged in 1995 from the prior year. However, analysis by sex reveals that males experienced longevity enhancements across the age spectrum. In fact, average remaining future lifetime for men established new record highs or remained at peak levels at every age. In 1995 expectation of life at birth was 75.7 years for the total population, 72.4 years for boys and 78.8 years for girls. At individual ages, women's average remaining lifetime has hardly changed since 1990, whereas men under age 75 have gained around 0.5 years between 1990 and 1995. In 1995 the infant mortality rate established another all-time low, namely 7.6 per 1,000 live births; this marks the 33rd consecutive year of annual declines.

Adolescent↗
PubMed1996

[Sex differential in life expectancy at birth in Japan: (2) trends in sex differential in life expectancy at birth from 1920 to 1990].

Sex differentials in life expectancy at birth in Japan are analyzed for the period 1920 to 1990. The results show that there was a general increase in differences in mortality by sex over time. "The sex differential in age-specific death rate in 0-4 year age group (particularly age 0) explained most of the sex differential in life expectancy at birth before 1947. After 1950, the age group of 60-79 played a major role in the sex differential in life expectancy at birth. It is noteworthy that female mortality exceeded male mortality in age groups of 2-41 before 1930. Consequently, excess of female mortality reduced the sex differential in life expectancy at birth at that period. As for the sex differential in mortality rates by causes of death, tuberculosis, pregnancy and childbirth related disease exerted a great influence...before 1940. Recently, malignant neoplasms, heart diseases, cerebrovascular diseases, and accidents [have] become leading contributors to the sex differentials in life expectancy at birth." (SUMMARY IN ENG)

Age Factors↗