This table contains mortality indicators by sex for Canada and all provinces except Prince Edward Island. These indicators are derived from three-year complete life tables. Mortality indicators derived from single-year life tables are also available (table 13-10-0837). For Prince Edward Island, Yukon, the Northwest Territories and Nunavut, mortality indicators derived from three-year abridged life tables are available (table 13-10-0140).

Period life expectancy by age and sex for the UK. Each national life table is based on population estimates, births and deaths for a period of three consecutive years. Tables are published annually.

ABSTRACT This study aimed to set upper and lower bounds for the expected present value of whole life annuities and whole life insurance policies from incomplete mortality data, generalizing previous results on life expectancy. Since its inception, in the 17th century, actuarial science has been devoted to the study of annuities and insurance plans. Thus, setting intervals that provide an initial idea about the cost of these products using incomplete mortality data represents a theoretical contribution to the area and this may have major applications in markets lacking historical records or those having little reliability of mortality data, as well as in new markets still poorly explored. For both the continuous and discrete cases, upper and lower bounds were constructed for the expected present value of whole life annuities and whole life insurance policies, contracted by a person currently aged x, based on information about the expected present value of these respective financial products subscribed to by a person of age x + n and the probability that an individual of age x survives to at least age x + n. Through the bounds of a continuous annuity, in an environment where the instantaneous interest rate is equal to zero, the results shown also set bounds for the complete life expectancy, which implies that the contribution of this research generalizes previous results in the literature. It was also found that, for both annuities and insurance plans, the length of constructed intervals increases as the data gap size increases and it decreases as the survival curve becomes more rectangular. Illustratively, bounds for life expectancy at 40 and 60 years of age, for the 10 municipalities showing the highest life expectancy at birth in Brazil in 2010, were constructed by using data available in the Atlas of Human Development in Brazil.

Period life expectancy by age and sex. Each life table is based on population estimates, births and deaths for a single year.

This table contains mortality indicators for Canada and provinces for the period 1980/1982 to 2013/2015. Complete mortality tables are available for men, women and both sexes combined.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

This study examines occupation-based differences in life expectancy and the extent to which health accounts for these differences. Twentyseven-year survival follow-up data were used from the Dutch population-based Longitudinal Aging Study Amsterdam (n = 2,531), initial ages 55–85 years. Occupation was based on longest-held job. Results show that the non-skilled general, technical and transport domains had an up to 3.5-year shorter life expectancy than the academic professions, accounting for the compositional characteristics age and gender. Statutory retirement age could be made to vary accordingly, by allowing a proportionally greater pension build-up in the shorter-lived domains. Health accounted for a substantial portion of the longevity difference, ranging from 20 to 66%, depending on the health indicator. Thus, health differences between occupational domains today can be used as a means to tailor retirement ages to individuals’ risks of longevity. These data provide a proof of principle for the development of an actuarially fair method to determine statutory retirement ages.

The life expectancy for men aged 65 years in the U.S. has gradually increased since the 1960s. Now men in the United States aged 65 can expect to live 18.2 more years on average. Women aged 65 years can expect to live around 20.7 more years on average. Life expectancy in the U.S. As of 2023, the average life expectancy at birth in the United States was 78.39 years. Life expectancy in the U.S. had steadily increased for many years but has recently dropped slightly. Women consistently have a higher life expectancy than men but have also seen a slight decrease. As of 2023, a woman in the U.S. could be expected to live up to 81.1 years. Leading causes of death The leading causes of death in the United States include heart disease, cancer, unintentional injuries, and cerebrovascular diseases. However, heart disease and cancer account for around 42 percent of all deaths. Although heart disease and cancer are the leading causes of death for both men and women, there are slight variations in the leading causes of death. For example, unintentional injury and suicide account for a larger portion of deaths among men than they do among women.

Regression analysis of subjective healthy life expectancy, subjective life expectancy and subjective life years with disability by gender.

Exposure to ambient fine particulate matter (PM2.5) air pollution is a major risk for premature death. Here, we systematically quantify the global impact of PM2.5 on life expectancy. Using data from the Global Burden of Disease project and actuarial standard life table methods, we estimate global and national decrements in life expectancy that can be attributed to ambient PM2.5 for 185 countries. In 2016, PM2.5 exposure reduced average global life expectancy at birth by ∼1 year with reductions of ∼1.2–1.9 years in polluted countries of Asia and Africa. If PM2.5 in all countries met the World Health Organization Air Quality Guideline (10 μg m–3), we estimate life expectancy could increase by a population-weighted median of 0.6 year (interquartile range of 0.2–1.0 year), a benefit of a magnitude similar to that of eradicating lung and breast cancer. Because background disease rates modulate the effect of air pollution on life expectancy, high age-specific rates of cardiovascular disease in many polluted low- and middle-income countries amplify the impact of PM2.5 on survival. Our analysis adds to prior research by illustrating how mortality from air pollution substantially reduces human longevity.

Life expectancy at birth and at age 65, by sex, on a three-year average basis.

Period life expectancy by age and sex for Scotland. Each national life table is based on population estimates, births and deaths for a period of three consecutive years. Tables are published annually.

Distribution of key explanatory variables.

1. The assumption that reproductive effort decreases somatic state, accelerating ageing, is central to our understanding of life-history variation. Maximal reproductive effort early in life is predicted to be maladaptive by accelerating ageing disproportionally, decreasing fitness.
2. Optimality theory predicts that reproductive effort is restrained early in life to balance the fitness contribution of reproduction against the survival cost induced by the reproductive effort. When adaptive, the level of reproductive restraint is predicted to be inversely linked to the remaining life-expectancy, potentially resulting in a terminal effort in the last period of reproduction.
3. Experimental tests of the reproductive restraint hypothesis require manipulation of somatic state and subsequent investigation of reproductive effort and residual lifespan. To our knowledge the available evidence remains inconclusive, and hence reproductive restraint remains to be demonstrated.
4. We modulated somati...

The demonstration of life span plasticity in natural populations would provide a powerful test of evolutionary theories of senescence. Plastic senescence is not easily explained by mutation accumulation or antagonistic pleiotropy but is a corollary of the disposable soma theory. The life span differences among castes of the eusocial Hymenoptera are potentially some of the most striking and extreme examples of life span plasticity. Although these differences are often assumed to be plastic, this has never been demonstrated conclusively because differences in life span may be caused by the proximate effects of different levels of environmental hazard experienced by castes. Here age-dependent and age-independent components of instantaneous mortality rates of the honey bee (Apis mellifera) were estimated from published life tables for natural and seminatural populations to determine whether differences in life span between queens and workers and between different types of workers are indeed plastic. These differences in life span were found to be due to differences in the rate of actuarial senescence, which correlate positively with the rate of extrinsic mortality, in accordance with the central prediction of evolutionary theories of senescence. Although all three evolutionary theories of senescence could in principle explain such plastic senescence, given differential gene expression between castes or life stages, only the disposable soma theory adequately explains the adaptive regulation of somatic maintenance in response to different environmental conditions that appears to underlie life span plasticity.