Search PubMed⌕ Search

Biomedical subjects

S J Olshansky

Publications and source records attributed to S J Olshansky.

18 recordsLinked to original sources
PubMed2001

Heterogeneity and its biodemographic implications for longevity and mortality.

In the visible world, heterogeneity typically refers to the differences that exist among individuals in a defined population. These differences can arise from a variety of sources--biological, behavioral and social. Ever since Darwin, scientists have argued over the biological significance of differences observed at the individual, morphological, physiological, genetic, molecular and structural levels. A general consensus has been reached. Heterogeneity is ubiquitous, it is important, and it increases as observations are made at finer levels of biological resolution. Debates over the significance of heterogeneity have emerged once again as biologists and demographers work together in order to create the emerging field of biodemography. For these scientists, the debates center around the relative impact that individual heterogeneity has on population level statistics. It is argued here that in a world where the mortality barriers to long life for individuals have been dramatically weakened, the population consequences of heterogeneity are already visible and will grow in importance as biomedical technologies continue to usher progressively more people into the post-reproductive period of the lifespan.

Animals↗
PubMed1998

An interspecies prediction of the risk of radiation-induced mortality.

Mortality data for B6CF1 mice exposed to 60Co gamma rays for the duration of life were used to make quantitative predictions of age-specific mortality observed in comparably exposed beagles. Simple Kaplan-Meier survival curves for the beagles and their 95% confidence intervals were computed for each dose-rate group observed. A dose-response equation was estimated from the mortality data for mice using a proportional hazard model. The dose-response model for mice was then used to generate predicted survivorship curves at dose rates that would recreate the dose burdens observed in the beagle at comparable points within the life span of the two organisms. When these predicted survivorship curves were scaled to adjust for species differences in the life span of control animals, the predictions for the mouse fell within the confidence intervals observed for the beagle. The successful interspecies extrapolation of age-specific mortality risks for species as different as the mouse and dog enhances both the value of studies involving laboratory animals and the potential relevance of the animal studies to the prediction of health effects in humans.

Animals↗
PubMed1997

Ever since Gompertz.

In 1825 British actuary Benjamin Gompertz made a simple but important observation that a law of geometrical progression pervades large portions of different tables of mortality for humans. The simple formula he derived describing the exponential rise in death rates between sexual maturity and old age is commonly, referred to as the Gompertz equation-a formula that remains a valuable tool in demography and in other scientific disciplines. Gompertz's observation of a mathematical regularity in the life table led him to believe in the presence of a low of mortality that explained why common age patterns of death exist. This law of mortality has captured the attention of scientists for the past 170 years because it was the first among what are now several reliable empirical tools for describing the dying-out process of many living organisms during a significant portion of their life spans. In this paper we review the literature on Gompertz's law of mortality and discuss the importance of his observations and insights in light of research on aging that has taken place since then.

Aging↗
PubMed1990

In search of Methuselah: estimating the upper limits to human longevity.

Estimates of the upper limits to human longevity have important policy implications that directly affect forecasts of life expectancy, active life expectancy, population aging, and social and medical programs tied to the size and health status of the elderly population. In the past, investigators have based speculations about the upper limits of human longevity on observations of past trends in mortality. Here the estimate of the upper bound is based on hypothesized reductions in current mortality rates necessary to achieve a life expectancy at birth from 80 to 120 years and an expectation of life at age 50 from 30 to 70 years. With the use of conditional probabilities of death from complete life tables for the United States, reductions in mortality required to achieve extreme longevity (that is, 80 to 120 years) were compared with those resulting from hypothetical cures for all cardiovascular diseases, ischemic heart disease, diabetes, and cancer. Results indicate that in order for life expectancy at birth to increase from present levels to what has been referred to as the average biological limit to life (age 85), mortality rates from all causes of death would need to decline at all ages by 55%, and at ages 50 and over by 60%. Given that hypothetical cures for major degenerative diseases would reduce overall mortality by 75%, it seems highly unlikely that life expectancy at birth will exceed the age of 85.

Female↗
PubMed1988

On forecasting mortality.

Official forecasts of mortality made by the U.S. Office of the Actuary throughout this century have consistently underestimated observed mortality declines. This is due, in part, to their reliance on the static extrapolation of past trends, an atheoretical statistical method that pays scant attention to the behavioral, medical, and social factors contributing to mortality change. A "multiple cause-delay model" more realistically portrays the effects on mortality of the presence of more favorable risk factors at the population level. Such revised assumptions produce large increases in forecasts of the size of the elderly population, and have a dramatic impact on related estimates of population morbidity, disability, and health care costs.

Actuarial Analysis↗
PubMed1987

Simultaneous/multiple cause-delay (SIMCAD): an epidemiological approach to projecting mortality.

Methods being used to project mortality are based on the hypothetical elimination of one or more diseases from the population or on extrapolation from observed mortality rates. This research presents an alternative projection method based on an epidemiological theory of aging and mortality change that is consistent with recent mortality transitions. The model is founded on the observation that recent mortality declines in the United States are attributable to improved life styles and advances in the prevention and treatment of degenerative diseases and that the risk of dying from such diseases is being redistributed (or delayed) from younger to older ages. A test using U.S. mortality and population data indicates that this alternative method is promising--particularly for projecting mortality rates from major chronic degenerative diseases among populations in middle and older ages.

Adult↗
PubMed1986

The fourth stage of the epidemiologic transition: the age of delayed degenerative diseases.

Gains in longevity in the United States since the mid-nineteenth century occurred as a result of an epidemiologic transition: deaths from infectious diseases were replaced by deaths from degenerative diseases. Recent trends in cause-specific mortality suggest a distinct new stage, one of postponement of degenerative diseases. Projections based on these data must be applied cautiously; their implication for health and social policies are likely to be profound.

Actuarial Analysis↗
PubMed1985

Pursuing longevity: delay vs elimination of degenerative diseases.

Using a new model which allows for projection of mortality change resulting from preventive health care measures, prospective changes in longevity for the resident United States population in 1978 were compared with projections of longevity gains occurring under a standard single cause-elimination model. Results indicate that equal or greater gains accrue from the prevention or delay of several major degenerative diseases, than from the complete elimination of some single major degenerative diseases. Observed declines in mortality from 1960 to 1978 have resulted in gains in longevity equivalent to the successful elimination of some major degenerative diseases.

Adolescent↗
PubMed1982

Is smoker/nonsmoker segregation effective in reducing passive inhalation among nonsmokers?

Using expired carbon monoxide (CO) and a test of coordination as measures of tobacco smoke exposure in a natural environmental setting where smokers and nonsmokers were segregated, results indicate that by comparison to a control group, subjects seated in adjacent smoking/ nonsmoking environments were not only exposed to similar ambient levels of CO, but also show similar physical and physiological reactions to their exposure in the form of coordination test scores, expired CO, and blood carboxyhemoglobin. While the results may not be generalized to other tobacco smoke constituents or other environmental settings, they raise questions about the health benefits of smoker segregation which future research must address.

Adult↗
PubMedDate not supplied

A biologically motivated partitioning of mortality.

For over a century, actuaries and biologists working independently of each other have presented arguments for why total mortality needs to be partitioned into biologically meaningful subcomponents. These mortality partitions tended to overlook genetic diseases that are inherited because the partitions were motivated by a paradigm focused on aging. In this article, we combine and extend the concepts from these disciplines to develop a conceptual partitioning of total mortality into extrinsic and intrinsic causes of death. An extrinsic death is either caused or initiated by something that orginates outside the body of an individual, while an intrinsic death is either caused or initiated by processes that originate within the body. It is argued that extrinsic mortality has been a driving force in determining why we die when we do from intrinsic causes of death. This biologically motivated partitioning of mortality provides a useful perspective for researchers interested in comparative mortality analyses, the consequences of population aging, limits to human life expectancy, the progress made by the biomedical sciences against lethal diseases, and demographic models that predict the life expectancy of future populations.

Aging↗