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PubMed1994

Mortality in sickle cell disease. Life expectancy and risk factors for early death.

BACKGROUND: Information on life expectancy and risk factors for early death among patients with sickle cell disease (sickle cell anemia, sickle cell-hemoglobin C disease, and the sickle cell-beta-thalassemias) is needed to counsel patients, target therapy, and design clinical trials. METHODS: We followed 3764 patients who ranged from birth to 66 years of age at enrollment to determine the life expectancy and calculate the median age at death. In addition, we investigated the circumstances of death for all 209 adult patients who died during the study, and used proportional-hazards regression analysis to identify risk factors for early death among 964 adults with sickle cell anemia who were followed for at least two years. RESULTS: Among children and adults with sickle cell anemia (homozygous for sickle hemoglobin), the median age at death was 42 years for males and 48 years for females. Among those with sickle cell-hemoglobin C disease, the median age at death was 60 years for males and 68 years for females. Among adults with sickle cell disease, 18 percent of the deaths occurred in patients with overt organ failure, predominantly renal. Thirty-three percent were clinically free of organ failure but died during an acute sickle crisis (78 percent had pain, the chest syndrome, or both; 22 percent had stroke). Modeling revealed that in patients with sickle cell anemia, the acute chest syndrome, renal failure, seizures, a base-line white-cell count above 15,000 cells per cubic millimeter, and a low level of fetal hemoglobin were associated with an increased risk of early death. CONCLUSIONS: Fifty percent of patients with sickle cell anemia survived beyond the fifth decade. A large proportion of those who died had no overt chronic organ failure but died during an acute episode of pain, chest syndrome, or stroke. Early mortality was highest among patients whose disease was symptomatic. A high level of fetal hemoglobin predicted improved survival and is probably a reliable childhood forecaster of adult life expectancy.

Adult↗
PubMed2006

Disability life expectancy for the elderly, city of Sao Paulo, Brazil, 2000: gender and educational differences.

There is evidence that 'health life expectancy' (expected number of years to be lived in health) differs by socioeconomic status. Time spent in health or disability plays a critical role in the use of health care services. The objective of this study was to estimate 'disability life expectancy' by age, gender and education attainment for the elderly of the city of São Paulo, Brazil, in the year 2000. Data came from the SABE database, population censuses and mortality statistics (SEADE Foundation). Life expectancy with disability was calculated using Sullivan's method on the basis of the current probability of death and prevalence of disability by educational level. The prevalence of disability increased with age, for both sexes and both levels of educational attainment studied. Men showed a lower prevalence of disability, in general, and persons with lower educational attainment showed a higher prevalence of disability. Regarding life expectancy, women could expect to live longer than men, with and without disability. For both sexes, the percentage of life expectancy lived with disability decreased with increasing educational attainment. With increasing educational attainment, the sex differences in the percentage of remaining years to be lived with disability increased for most ages. Finally, the percentage of remaining years to be lived with disability increased with age for males and females, except for males with high educational attainment between the ages 70-75 and 75-80. The results may serve as a guide for public policies in the country, since health problems faced by older persons, such as disability, are the result of a number of past experiences during their life-times, such as health care, housing conditions, hygiene practices and education. Education influences health behaviours and is related, to some extent, to all these factors. Therefore, improvements in education for the disadvantaged may improve health.

Activities of Daily Living↗
PubMed1991

Socioeconomic determinants of white and black males' life expectancy differentials, 1980.

Epidemiological transition theory suggests that two population existing under disparate socioeconomic conditions would have different life expectancies as the result of cause-of-death differences. The effect of racial socioeconomic differentials on the total racial life expectancy differential are examined as they act through specific cause-of-death differentials. Results suggest that residential isolation of blacks has a strong effect on the total life expectancy differential as it acts through the racial homicide differential. The racial unemployment difference also has a strong effect on the total differential as it acts through the racial heart disease differential. Implications of the findings for reducing life expectancy differentials are discussed.

Black or African American↗
PubMed2005

Is poor life expectancy a predictive factor in the progression of primary open angle glaucoma?

AIM: To investigate the disease progression and final visual outcome of glaucoma patients with poor life expectancy, compared to matched patients with a longer life expectancy. METHOD: Visual fields at diagnosis and at the last ophthalmic appointment before death were analysed for glaucoma patients referred between 1991 and 1995, and deceased before the end of 2001. These patients were matched to the patients living beyond 2001. Functional vision was also assessed, and classified as better than the NHS partial sighted criteria. RESULTS: A total of 61 deceased patients were identified, resulting in 40 matched pairs. In all, 6.5% of the patients with poor life expectancy progressed from functional vision to beyond partial sighted criteria, and none of the matched patients progressed to this extent. At final assessment an association between poor life expectancy and progression beyond functional vision was found existing (P = 0.02), with a lesser association at diagnosis (P = 0.06). Visual field scores of the matched pairs who had test results available for both initial and final assessment (n = 23 pairs) showed no statistically significant difference between the two groups at diagnosis (P = 0.52); However, a significant difference at final the assessment did exist (P = 0.042). No difference between the initial (off medication) intraocular pressures (IOPs) was found (P = 0.82). At the final assessment a significant difference existed (P = 0.025), with the surviving group having a higher final mean pressure (15.9 mmHg, SD 2.8, vs 18.3 mmHg, SD 4.9). CONCLUSION: Patients with poor life expectancy progressed more than the matched surviving patients, when measured from an initially similar position, despite better IOP control.

Aged↗
PubMed1999

[Active life expectancy in Germany].

Using the method of multistate life-tables, the article presents results on active life expectancy on the basis of the German Socio-Economic Panel Survey (SOEP). Different determinants of mortality and morbidity are revealed by event-history analysis. Results show that men live a greater proportion of their lives without disability than do women. Results on the association between mortality/morbidity and socio-economic factors suggest that studies which usually focussed either on mortality or on morbidity cannot fully explain differences in active life expectancy.

Adult↗
PubMed2006

Causes of inequality in life expectancy between Indigenous and non-Indigenous people in the Northern Territory, 1981-2000: a decomposition analysis.

OBJECTIVE: To identify the causes of the gap in life expectancy between Indigenous and non-Indigenous populations of the Northern Territory and how the causes have evolved over time. DESIGN AND SETTING: Analysis of NT death data over four 5-year periods, 1 January 1981 to 31 December 2000 inclusive. A decomposition method using discrete approximations (Vaupel and Romo) was applied to abridged life tables for the Indigenous and non-Indigenous populations of the NT. MAIN OUTCOME MEASURES: Contribution of causes of death, grouped according to global burden of disease groups and categories, to the life expectancy gap. RESULTS: The gap between the life expectancy of Indigenous and non-Indigenous people in the NT did not appear to narrow over time, but there was a marked shift in the causes of the gap. In terms of disease groups, the contribution of communicable diseases, maternal, perinatal and nutritional conditions halved during the 20 years to 2000. Meanwhile, the contribution of non-communicable diseases and conditions increased markedly. The contribution of injuries remained static. In terms of disease categories, the contribution of infectious diseases, respiratory infections and respiratory diseases declined considerably; however, these gains were offset by significantly larger increases in the contribution of cardiovascular diseases and diabetes for Indigenous women and cardiovascular diseases, cancers and digestive diseases for Indigenous men. CONCLUSIONS: The main contributors to the gap in life expectancy between the Indigenous and non-Indigenous populations were non-communicable diseases and conditions, which are more prevalent in ageing populations. With the life expectancy of Indigenous people in the NT expected to improve, it is important that public health initiatives remain focused on preventing and managing chronic diseases.

Cause of Death↗
PubMed2002

Changing life expectancy in Romania after the transition.

BACKGROUND: While Poland, Hungary, and the Czech Republic have seen impressive gains in life expectancy in the 1990s, Romania has not. In contrast with the other countries, there has been very little research on the causes of the pattern of mortality seen in Romania. OBJECTIVES: To describe the trends in life expectancy at birth in Romania after the political transition in 1989 and to evaluate the contribution of deaths from different causes and different ages to these changes. METHODS: Decomposition of life expectancy by age and cause of death using routine data on mortality for the years 1990, 1996, and 1998; comparison of death rates by age, sex, and cause of death. RESULTS: Romania has experienced an overall decline of 1.71 years of life expectancy at birth from 1990 to 1996 in men and 0.54 years in women. The major contribution to this decline was an increase in mortality from cardiovascular diseases and diseases of the digestive system, in particular cirrhosis, among the middle aged and elderly. The recovery observed in 1998, of 1.12 years in men and 0.89 years in women, was mainly caused by a reduction in deaths from cardiovascular disease in the middle aged and elderly. Infant and early childhood mortality fell throughout the period but there was an increase of approximately 40% in mortality at age 5-9 that was almost entirely attributable to AIDS. CONCLUSION: This is the first Romanian study that describes the evolution of life expectancy after transition. Romania may at last be beginning to follow the path of improving adult mortality seen in the early 1990s in some of its neighbours. It has, however, been unique in eastern Europe in experiencing increasing childhood mortality. This is attributable to an epidemic of paediatric AIDS, consequent on the tragically inappropriate policies adopted in the 1980s.

Acquired Immunodeficiency Syndrome↗
PubMed1991

Life expectancies of cigarette smokers and nonsmokers in the United States.

This research employs the National Health Interview and the National Mortality Followback Surveys to calculate life expectancies by age and sex for white nonsmokers, former smokers, and current smokers in the United States in 1986. In general, life expectancies are higher for never smokers than for former smokers, and higher for former smokers than for current smokers. Heavy smokers have lower life expectancies than persons with all other smoking statuses; indeed, compared to never smokers, heavy smokers at age 25 can expect at least a 25% shorter life. Gender differences in life expectancies were found to persist even with the elimination of smoking. Differences in life expectancy by sex thus appear to be due, in part, to cigarette smoking, but also to occupational, environmental, and sociodemographic factors.

Adult↗
PubMed1999

Smoking, physical activity, and active life expectancy.

The effect of smoking and physical activity on active and disabled life expectancy was estimated using data from the Established Populations for Epidemiologic Studies of the Elderly (EPESE). Population-based samples of persons aged > or = 65 years from the East Boston, Massachusetts, New Haven, Connecticut, and Iowa sites of the EPESE were assessed at baseline between 1981 and 1983 and followed for mortality and disability over six annual follow-ups. A total of 8,604 persons without disability at baseline were classified as "ever" or "never" smokers and doing "low," "moderate," or "high" level physical activity. Active and disabled life expectancies were estimated using a Markov chain model. Compared with smokers, men and women nonsmokers survived 1.6-3.9 and 1.6-3.6 years longer, respectively, depending on level of physical activity. When smokers were disabled and close to death, most nonsmokers were still nondisabled. Physical activity, from low to moderate to high, was significantly associated with more years of life expectancy in both smokers (9.5, 10.5, 12.9 years in men and 11.1, 12.6, 15.3 years in women at age 65) and nonsmokers (11.0, 14.4, 16.2 years in men and 12.7, 16.2, 18.4 years in women at age 65). Higher physical activity was associated with fewer years of disability prior to death. These findings provide strong and explicit evidence that refraining from smoking and doing regular physical activity predict a long and healthy life.

Aged↗
PubMed2006

Modeling predicted that tobacco control policies targeted at lower educated will reduce the differences in life expectancy.

BACKGROUND AND OBJECTIVE: To estimate the effects of reducing the prevalence of smoking in lower educated groups on educational differences in life expectancy. METHODS: A dynamic Markov-type multistate transition model estimated the effects on life expectancy of two scenarios. A "maximum scenario" where educational differences in prevalence of smoking disappear immediately, and a "policy target-scenario" where difference in prevalence of smoking is halved over a 20-year period. The two scenarios were compared to a reference scenario, where smoking prevalences do not change. Five Dutch cohort studies, involving over 67,000 participants aged 20 to 90 years, provided relative mortality risks by educational level, and smoking habits were assessed using national data of more than 120,000 persons. RESULTS: In the reference scenario, the difference in life expectancy at age 40 between highest and lowest educated groups was 5.1 years for men and 2.7 years for women. In the "maximum scenario" these differences were reduced to 3.6 years for men and 1.7 years for women (reduction approximately 30%), and in the "policy target-scenario" differences were 4.7 years for men and 2.4 years for women (reduction approximately 10%). CONCLUSION: Theoretically, educational differences in life expectancy would be reduced by 30% at maximum, if variations in smoking prevalence were eliminated completely. In practice, tobacco control policies that are targeted at the lower educated may reduce the differences in life expectancy by approximately 10%.

Adult↗
PubMed2005

Life expectancy in a birth cohort of Boxers followed up from weaning to 10 years of age.

OBJECTIVE: To determine mortality rate over time, risk factors for death, and heritability of life expectancy in Boxers. ANIMALS: 1,733 purebred Boxers born in The Netherlands between January 1994 and March 1995. PROCEDURE: Dogs were followed up from weaning (ie, 49 days of age) to 10 years of age through use of a written questionnaire sent to owners every 6 months. Mortality rate over time, risk factors potentially associated with death, and heritability of life expectancy were examined by use of a proportional hazards model based on the Weibull distribution. RESULTS: stimated mortality rate during the 10-year study period for this birth cohort of Boxers was 45%. The probability of surviving to 5 years of age was 88%; the probability of surviving to 10 years of age was 55%. Estimated effective heritability of life expectancy was 0.076, meaning that in this population, an estimated 76% of the observed variation in life expectancy could be attributed to genetic differences among dogs that were passed from parents to their offspring. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that cumulative incidence of death from weaning to 10 years of age among this birth cohort of Boxers was 45%. The estimated heritability of life expectancy suggested that life expectancy can be improved by use of selective breeding.

Animals↗
PubMed1986

Life expectancy of kibbutz members.

Data are presented demonstrating that the life expectancy (LE) of kibbutz members--both men and women--is higher than that of the overall Jewish population in Israel. Closer inspection of the death rates at various ages reveals that, from age thirty, those of kibbutz women are lower than those of the Jewish population. Although those of kibbutz men are actually higher until age forty-nine, nevertheless the LE of kibbutz members (based on death rates) surpasses that of Jews in Israel. These data add to and support other research findings illustrating the more positive mental health and well-being found among kibbutz members than among other comparative populations. Similarly, the factors contributing to kibbutz members' life expectancy evolve from this quality of life, especially as this quality of life affects old age.

Culture↗
PubMed1997

[Changing life expectancy in the 1980's. Why was Denmark different from Sweden?].

The aim of the present study was to identify the contribution from specific causes of death to the changes in life expectancy at birth in Denmark relative to Sweden in different age groups during the 1980s and to compare the difference in life expectancy between the two countries in 1990. Mortality data from WHO mortality tapes grouped in smaller series of clinically meaningful categories were used to calculate the contribution of each of these categories at each ten year age group to the difference in life expectancy at birth in each country between 1979 and 1990 and between the two countries. During the period from 1979 to 1990 life expectancy increased in both Denmark and Sweden. However, Sweden experienced the greatest increase in life expectancy (more than two years) while it increased less than one year in Denmark. In both countries a decrease in cardiovascular disease mortality contributed most to the increase in life expectancy among males as well as females. Both among males and females the less favourable development in Denmark was mainly caused by differences in mortality trends related to cardio-vascular diseases, respiratory and non-respiratory cancer. Over a short period of time two Nordic countries experienced remarkable, but different changes in mortality. These findings suggest that mortality rates are sensitive to even minor differences in social and cultural factors across countries and over short time periods.

Adolescent↗
PubMed1997

Life expectancy in England: variations and trends by gender, health authority, and level of deprivation.

STUDY OBJECTIVES: To investigate variations and trends in life expectancy in English district health authorities in relation to gender and Jarman deprivation level. DESIGN: Mortality data for English health authorities from 1984-94, compiled by the Office for National Statistics, were assessed conventionally and using life table techniques. SETTING: District health authorities in England. MAIN OUTCOME MEASURES: Life expectancies in the 105 DHAs in relation to rank, to gender, and to deprivation category based on the census based Jarman score. CONCLUSIONS: Differences in life expectancy had widened over the decade and prosperous areas with greatest longevity had seen the largest gains. In most deprived areas improvements in life expectancy were negligible. The greatest gender differences in life expectancy were also seen in deprived areas.

Aged↗
PubMed1998

Life expectancy of adults with cerebral palsy.

To determine the predictors of mortality and find the life expectancies of adults with cerebral palsy (CP), data on 24,768 individuals aged 15 years and over who received services in California between January 1980 and December 1995 were analyzed. Multivariate statistical methods to identify mortality predictors, and actuarial methods to determine corresponding life expectancies were used. The key predictors were lack of basic functional skills: mobility and feeding. Adults lacking these skills had much reduced life expectancies, as short as 11 years for the worst functioning groups. By contrast, survival of high-functioning adults was close to that of the general population. The influence on survival of cognitive skills, type of CP, and other factors appears to be expressed largely through their effect on basic functioning. Life expectancies of adults of a given age can differ by 40 years or more, according to their functional level.

Activities of Daily Living↗
PubMedDate not supplied

Black-white inequalities in mortality and life expectancy, 1933-1999: implications for healthy people 2010.

OBJECTIVES: Optimistic predictions for the Healthy People 2010 goals of eliminating racial/ethnic disparities in health have been made based on absolute improvements in life expectancy and mortality. This study sought to determine whether there is evidence of relative improvement (a more valid measure of inequality) in life expectancy and mortality, and whether such improvement, if demonstrated, predicts future success in eliminating disparities. METHODS: Historical data from the National Center for Health Statistics and the Census Bureau were used to predict future trends in relative mortality and life expectancy, employing an Autoregressive Integrated Moving Average (ARIMA) model. Excess mortality and time lags in mortality and life expectancy for blacks relative to whites were also estimated. RESULTS: Based on data for 1945 to 1999, forecasts for relative black:white age-adjusted, all-cause mortality and white:black life expectancy at birth showed trends toward increasing disparities. From 1979, when the Healthy People initiative began, to 1998, the black:white ratio of age-adjusted, gender-specific mortality increased for all but one of nine causes of death that accounted for 83.4% of all US mortality in 1998. From 1980 to 1998, average numbers of excess deaths per day among American blacks relative to whites increased by 20%. American blacks experienced 4.3 to 4.5 million premature deaths relative to whites in 1940-1999. CONCLUSIONS: The rationale that underlies the optimistic Healthy People 2010 forecasts, that future success can be built on a foundation of past success, is not supported when relative measures of inequality are used. There has been no sustained decrease in black-white inequalities in age-adjusted mortality or life expectancy at birth at the national level since 1945. Without fundamental changes, most probably related to the ways medical and public health practitioners are trained, evaluated, and compensated for prevention-related activities, as well as further research on translating the findings of prevention studies into clinical practice, it is likely that simply reducing disparities in access to care and/or medical treatment will be insufficient. Millions of premature deaths will continue to occur among African Americans.

Adolescent↗
PubMedDate not supplied

Life expectancy by employment status, income, and education in the National Longitudinal Mortality Study.

Based on data from the National Longitudinal Mortality Study for 1979-85, life expectancies are estimated for white men and white women by education, by family income, and by employment status. Life expectancy varies directly with amount of schooling and with family income. Differences in life expectancy at age 25 between the highest and the lowest levels of education completed were about 6 years for white men and about 5 years for white women. For family income, differences between the highest and the lowest income groups were about 10 years for white men and 4.3 years for white women. The largest differences in life expectancy were between employment categories. At age 25, white men in the labor force lived on average about 12 more years than those not in the labor force, and white women lived on average about 9 more years. For those who were unable to work compared with those in the labor force, the difference for white men was about 20 years; for white women, 29 years. Results in this study showed much the same differentials in life expectancy for education as the earlier Kitagawa-Hauser study.

Adult↗
PubMed1989

[Estimating the value of disability-free life expectancy for western countries in the last decade. How can this new health status indicator be used?].

Disability-free life expectancy (DFLE) is an indicator of the mean duration of life in good health, based on the measurement of mortality combined with the measurement of disability. To date, some experimental calculations have been carried out mainly in Canada, England, France, the Netherlands and the United States of America. Taking these studies as a whole, disability-free life expectancy in the last decade can be estimated at about 59 years for men and about 63 years for women. The share of years of disability within life expectancy ranges from 11% to 27%. The calculations show that women suffer disability for a greater part of their life expectancy than men. The calculations also reveal social inequalities in health. Health authorities in Western countries are showing increasing interest in this indicator today. The main points in its favour are its simplicity in practice, its usefulness for determining objectives, allocating resources, measuring the success or failure of health policies, assessing current needs and defining future scenarios.

Aged↗