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.

In 2023, a woman in the United States aged 65 years could expect to live another **** years on average. This number decreased in the years 2020 and 2021, after reaching a high of **** years in 2019. Nevertheless, the life expectancy of a woman aged 65 years in the United States is still higher than that of a man of that age. In 2023, a man aged 65 years could be expected to live another 18.2 years on average. Why has the life expectancy in the U.S. declined? Overall, life expectancy in the United States has declined in recent years. In 2019, the life expectancy for U.S. women was **** years, but by 2023 it had decreased to **** years. Likewise, the life expectancy for men decreased from **** years to **** years in the same period. The biggest contributors to this decline in life expectancy are the COVID-19 pandemic and the opioid epidemic. Although deaths from the COVID-19 pandemic have decreased significantly since 2022, deaths from opioid overdose continue to increase, reaching all-time highs in 2022. The leading causes of death among U.S. women The leading causes of death among women in the United States in 2022 were heart disease, cancer, stroke, and COVID-19. That year, heart disease and cancer accounted for a combined **** percent of all deaths among women, while around *** percent of deaths were due to COVID-19. The overall leading causes of death in the United States generally reflect the leading causes among women, with some slight variations. For example, Alzheimer’s disease is the ***** leading cause of death among women but the ******* leading cause of death overall in the United States.

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

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 ...).

In 2023, a 65-year-old woman in Italy had an average life expectancy of another **** years. This statistic shows the life expectancy for women at the age of ** in Italy from 2002 to 2023.

Life expectancy, healthy life expectancy and disability-free life expectancy – at birth and age 65 by sex for local areas in the UK, 2016 to 2018.

This table contains 2754 series, with data for years 2005/2007 - 2012/2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (153 items: Canada; Newfoundland and Labrador; Eastern Regional Integrated Health Authority, Newfoundland and Labrador; Central Regional Integrated Health Authority, Newfoundland and Labrador; ...);  Age group (2 items: At birth; At age 65);  Sex (3 items: Both sexes; Males; Females);  Characteristics (3 items: Life expectancy; Low 95% confidence interval, life expectancy; High 95% confidence interval, life expectancy).

Pivot table for life expectancy by sex and area type, divided by three-year intervals starting from 2001 to 2003.

Healthy life expectancy (HLE), life expectancy (LE), proportion of life spent in "Good" health and ranks for men and women at age 65 by upper tier local authority (UTLA).

In 2022, the life expectancy at birth for women born in the UK was 82.57 years, compared with 78.57 years for men. By age 65 men had a life expectancy of 18.25 years, compared with 20.76 years for women.

In 2023, men aged 65 in South Korea were expected to live an average of about ** more years, while women aged 65 were expected to live around ** more years on average. The life expectancy of the elderly population has gradually increased since the *****.

Life expectancy at birth and at age 65 for the UK and local areas in England and Wales, 1991–93 to 2011–13

Introduction

Life Expectancy Statistics: Life expectancy is the average number of years a person is expected to live based on current mortality rates in a specific population.

It is influenced by healthcare quality, lifestyle choices, economic conditions, genetics, environmental factors, and social determinants like education and public health policies.

Typically measured as life expectancy at birth, it reflects the average lifespan of a newborn. However, it can also be assessed for older ages, such as 65, to predict additional years of life.

In 2024, Trentino-South Tyrol recorded the highest life expectancy in Italy for both women and men at 65 years old. Veneto followed in the ranking with the second-highest life expectancy at 65 years. In 2020, life expectancy in Italy decreased dramatically due to the COVID-19 pandemic, which caused the largest number of deaths recorded in decades.

This table contains 3114 series, with data for years 1996 - 1996 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (173 items: Canada; Health and Community Services St. John's Region; Newfoundland and Labrador (Peer group H);Health and Community Services Eastern Region; Newfoundland and Labrador (Peer group D);Newfoundland and Labrador ...), Age group (2 items: At birth; At age 65 ...), Sex (3 items: Both sexes; Males; Females ...), Characteristics (3 items: Disability-adjusted life expectancy; Low 95% confidence interval; disability-adjusted life expectancy; High 95% confidence interval; disability-adjusted life expectancy ...).

This dataset presents the average number of years a man aged 65 can expect to live in good health, known as healthy life expectancy (HLE). It is a key measure of quality of life in later years and reflects both longevity and the prevalence of good health among older men.

Rationale Increasing healthy life expectancy at age 65 for males is a major public health objective. It highlights the importance of not only living longer but also maintaining good health and independence in later life. This indicator supports the planning of health and social care services and helps assess the impact of health inequalities and lifestyle factors on aging populations.

Numerator The numerator is derived from the number of deaths registered in the respective calendar years and the weighted prevalence of individuals reporting good or very good health, as captured by the Annual Population Survey (APS). Data are provided by the Office for National Statistics (ONS).

Denominator The denominator is based on population estimates from the 2021 Census and the APS sample, weighted to reflect local authority population totals. These data are also provided by the ONS.

Caveats Healthy life expectancy figures exclude residents of communal establishments, except for NHS housing and students in halls of residence who are included based on their parents' address. This may affect comparability in areas with large institutional populations.

External References Fingertips Public Health Profiles – Healthy Life Expectancy (Male)

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

There are two types of life tables –cohort/generational and current/period life tables. Cohort life tables are constructed using the mortality experience of the cohort and may not be useful for the cohort itself because every member of the cohort has to die before such a table can be constructed. A current or period life table uses current mortality experience applied to a cohort of births to compute the life table. On the basis of age intervals, life tables are classified as complete or abridged. A complete life table uses exact single years and an abridged life table uses age intervals. This report presents five-year age interval abridged current life tables. Computation of an abridged life table from which life expectancy is derived requires mainly population and death data by age and sex. In this report, population data consist of the 1990, 2000, and 2010 census counts of residents of each Illinois County and the city of Chicago. These data were aggregated into five-year age groups and by sex and used as denominators in computing mortality rates. The death data were received from the Illinois Center for Health Statistics (ICHS) of the Office of Health Informatics (OHI). ICHS receives these data from the Illinois Vital Records System (IVRS). Number of deaths by sex and specific age for each county were obtained from 1989 to 2011 and aggregated at county level by five-year age groups for each sex. Three-year averages were then computed for the periods 1989-1991, 1999-2001, and 2009-2011 and were used as numerators in computing mortality rates. The overall life tables were constructed using Chiang’s (1984) Method II. This method assumes a homogeneous population in which all individuals are subjected to the same force of mortality, and in which survival of an individual is independent of the survival of any other individual in the group. The method does not remove fluctuations in observed data; therefore, the 2 produced life tables exhibit more the factual mortality pattern in the actual data and less the underlying mortality picture of the populations. Margin of errors were computed to provide basis for evaluating the accuracy of the estimated life expectancies.

People in different subgroups age at different rates. Surveys containing biomarkers can be used to assess these subgroup differences. We illustrate this using hand-grip strength to produce an easily interpretable, physical-based measure that allows us to compare characteristic-based ages across educational subgroups in the United States. Hand-grip strength has been shown to be a good predictor of future mortality and morbidity, and therefore a useful indicator of population aging. Data from the Health and Retirement Survey (HRS) were used. Two education subgroups were distinguished, those with less than a high school diploma and those with more education. Regressions on hand-grip strength were run for each sex and race using age and education, their interactions and other covariates as independent variables. Ages of identical mean hand-grip strength across education groups were compared for people in the age range 60 to 80. The hand-grip strength of 65 year old white males with less education was the equivalent to that of 69.6 (68.2, 70.9) year old white men with more education, indicating that the more educated men had aged more slowly. This is a constant characteristic age, as defined in the Sanderson and Scherbov article “The characteristics approach to the measurement of population aging” published 2013 in Population and Development Review. Sixty-five year old white females with less education had the same average hand-grip strength as 69.4 (68.2, 70.7) year old white women with more education. African-American women at ages 60 and 65 with more education also aged more slowly than their less educated counterparts. African American men with more education aged at about the same rate as those with less education. This paper expands the toolkit of those interested in population aging by showing how survey data can be used to measure the differential extent of aging across subpopulations.

General health expectancy estimates by sex, at birth and age 65, for Northern Ireland by country, national deciles of area deprivation and local government districts.

IntroductionAdult male and female mortality declines in Japan have been slower than in most high-income countries since the early 1990s. This study compares Japan’s recent life expectancy trends with the more favourable trends in Australia, measures the contribution of age groups and causes of death to differences in these trends, and places the findings in the context of the countries’ risk factor transitions.MethodsThe study utilises data on deaths by age, sex and cause in Australia and Japan from 1950–2016 from the Global Burden of Disease Study. A decomposition method measures the contributions of various ages and causes to the male and female life expectancy gap and changes over four distinct phases during this period. Mortality differences by cohort are also assessed.FindingsJapan’s two-year male life expectancy advantage over Australia in the 1980s closed in the following 20 years. The trend was driven by ages 45–64 and then 65–79 years, and the cohort born in the late 1940s. Over half of Australia’s gains were from declines in ischaemic heart disease (IHD) mortality, with lung cancer, chronic respiratory disease and self-harm also contributing substantially. Since 2011 the trend has reversed again, and in 2016 Japan had a slightly higher male life expectancy. The advantage in Japanese female life expectancy widened over the period to 2.3 years in 2016. The 2016 gap was mostly from differential mortality at ages 65 years and over from IHD, chronic respiratory disease and cancers.ConclusionsThe considerable gains in Australian male life expectancy from declining non-communicable disease mortality are attributable to a range of risk factors, including declining smoking prevalence due to strong public health interventions. A recent reversal in life expectancy trends could continue because Japan has greater scope for further falls in smoking and far lower levels of obesity. Japan’s substantial female life expectancy advantage however could diminish in future because it is primarily due to lower mortality at old ages.