Over the past 160 years, life expectancy (from birth) in the United States has risen from 39.4 years in 1860, to 78.9 years in 2020. One of the major reasons for the overall increase of life expectancy in the last two centuries is the fact that the infant and child mortality rates have decreased by so much during this time. Medical advancements, fewer wars and improved living standards also mean that people are living longer than they did in previous centuries.

Despite this overall increase, the life expectancy dropped three times since 1860; from 1865 to 1870 during the American Civil War, from 1915 to 1920 during the First World War and following Spanish Flu epidemic, and it has dropped again between 2015 and now. The reason for the most recent drop in life expectancy is not a result of any specific event, but has been attributed to negative societal trends, such as unbalanced diets and sedentary lifestyles, high medical costs, and increasing rates of suicide and drug use.

A global phenomenon, known as the demographic transition, has seen life expectancy from birth increase rapidly over the past two centuries. In pre-industrial societies, the average life expectancy was around 24 years, and it is believed that this was the case throughout most of history, and in all regions. The demographic transition then began in the industrial societies of Europe, North America, and the West Pacific around the turn of the 19th century, and life expectancy rose accordingly. Latin America was the next region to follow, before Africa and most Asian populations saw their life expectancy rise throughout the 20th century.

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org.

This dataset gives the average life expectancy and corresponding confidence intervals for each Chicago community area for the years 1990, 2000 and 2010. See the full description at: https://data.cityofchicago.org/api/views/qjr3-bm53/files/AAu4x8SCRz_bnQb8SVUyAXdd913TMObSYj6V40cR6p8?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\Life Expectancy\Dataset description - LE by community area.pdf

Throughout most of history, average life expectancy from birth was fairly consistent across the globe, at around 24 years. A major contributor to this was high rates of infant and child mortality; those who survived into adulthood could expect to live to their 50s or 60s, yet pandemics, food instability, and conflict did cause regular spikes in mortality across the entire population. Gradually, from the 16th to 19th centuries, there was some growth in more developed societies, due to improvements in agriculture, infrastructure, and medical knowledge. However, the most significant change came with the introduction of vaccination and other medical advances in the 1800s, which saw a sharp decline in child mortality and the onset of the demographic transition. This phenomenon began in more developed countries in the 1800s, before spreading to Latin America, Asia, and (later) Africa in the 1900s. As the majority of the world's population lives in countries considered to be "less developed", this figure is much closer to the global average. However, today, there is a considerable difference in life expectancies across these countries, ranging from 84.7 years in Japan to 53 years in the Central African Republic.

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 17 more years on average. Women aged 65 years can expect to live around 19.7 more years on average.

Life expectancy in the U.S.

As of 2021, the average life expectancy at birth in the United States was 76.33 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 2019, a woman in the U.S. could be expected to live up to 79.3 years.

Leading causes of death

The leading causes of death in the United States include heart disease, cancer, unintentional injuries, chronic lower respiratory diseases and cerebrovascular diseases. However, heart disease and cancer account for around 38 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.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

China life expectancy for 2025 is 77.81, a 0.22% increase from 2024.

<ul style='margin-top:20px;'>

<li>China life expectancy for 2024 was <strong>77.64</strong>, a <strong>0.22% increase</strong> from 2023.</li>
<li>China life expectancy for 2023 was <strong>77.47</strong>, a <strong>0.22% increase</strong> from 2022.</li>
<li>China life expectancy for 2022 was <strong>77.30</strong>, a <strong>0.22% increase</strong> from 2021.</li>
</ul>Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

Alcobendas City Council. Evolution of the average age of the population. Data since 2006.

Average life expectancy excluding death from a specific cause by single year of age (from 1996)

Life expectancy in the United Kingdom was below 39 years in the year 1765, and over the course of the next two and a half centuries, it is expected to have increased by more than double, to 81.1 by the year 2020. Although life expectancy has generally increased throughout the UK's history, there were several times where the rate deviated from its previous trajectory. These changes were the result of smallpox epidemics in the late eighteenth and early nineteenth centuries, new sanitary and medical advancements throughout time (such as compulsory vaccination), and the First world War and Spanish Flu epidemic in the 1910s.

Greece life expectancy for 2025 is 83.10, a 0.18% increase from 2024.

<ul style='margin-top:20px;'>

<li>Greece life expectancy for 2024 was <strong>82.95</strong>, a <strong>1.74% increase</strong> from 2023.</li>
<li>Greece life expectancy for 2023 was <strong>81.54</strong>, a <strong>0.93% increase</strong> from 2022.</li>
<li>Greece life expectancy for 2022 was <strong>80.79</strong>, a <strong>0.88% increase</strong> from 2021.</li>
</ul>Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

Poland life expectancy for 2025 is 79.60, a 0.21% increase from 2024.

<ul style='margin-top:20px;'>

<li>Poland life expectancy for 2024 was <strong>79.43</strong>, a <strong>0.21% increase</strong> from 2023.</li>
<li>Poland life expectancy for 2023 was <strong>79.27</strong>, a <strong>0.2% increase</strong> from 2022.</li>
<li>Poland life expectancy for 2022 was <strong>79.11</strong>, a <strong>0.21% increase</strong> from 2021.</li>
</ul>Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

Egypt life expectancy for 2025 is 72.85, a 0.21% increase from 2024.

<ul style='margin-top:20px;'>

<li>Egypt life expectancy for 2024 was <strong>72.69</strong>, a <strong>1.48% increase</strong> from 2023.</li>
<li>Egypt life expectancy for 2023 was <strong>71.63</strong>, a <strong>0.88% increase</strong> from 2022.</li>
<li>Egypt life expectancy for 2022 was <strong>71.01</strong>, a <strong>2.95% increase</strong> from 2021.</li>
</ul>Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

The content has some words in Chinese, I can help you with the translation if you would like that.

It is only in the past two centuries where demographics and the development of human populations has emerged as a subject in its own right, as industrialization and improvements in medicine gave way to exponential growth of the world's population. There are very few known demographic studies conducted before the 1800s, which means that modern scholars have had to use a variety of documents from centuries gone by, along with archeological and anthropological studies, to try and gain a better understanding of the world's demographic development. Genealogical records One such method is the study of genealogical records from the past; luckily, there are many genealogies relating to European families that date back as far as medieval times. Unfortunately, however, all of these studies relate to families in the upper and elite classes; this is not entirely representative of the overall population as these families had a much higher standard of living and were less susceptible to famine or malnutrition than the average person (although elites were more likely to die during times of war). Nonetheless, there is much to be learned from this data. Impact of the Black Death In the centuries between 1200 and 1745, English male aristocrats who made it to their 21st birthday were generally expected to live to an age between 62 and 72 years old. The only century where life expectancy among this group was much lower was in the 1300s, where the Black Death caused life expectancy among adult English noblemen to drop to just 45 years. Experts assume that the pre-plague population of England was somewhere between four and seven million people in the thirteenth century, and just two million in the fourteenth century, meaning that Britain lost at least half of its population due to the plague. Although the plague only peaked in England for approximately eighteen months, between 1348 and 1350, it devastated the entire population, and further outbreaks in the following decades caused life expectancy in the decade to drop further. The bubonic plague did return to England sporadically until the mid-seventeenth century, although life expectancy among English male aristocrats rose again in the centuries following the worst outbreak, and even peaked at more than 71 years in the first half of the sixteenth century.

Albania Population: Average: Age 35 to 39 data was reported at 179.750 Person th in 2022. This records an increase from the previous number of 177.710 Person th for 2021. Albania Population: Average: Age 35 to 39 data is updated yearly, averaging 176.315 Person th from Dec 2001 (Median) to 2022, with 22 observations. The data reached an all-time high of 216.905 Person th in 2001 and a record low of 161.921 Person th in 2015. Albania Population: Average: Age 35 to 39 data remains active status in CEIC and is reported by Institute of Statistics. The data is categorized under Global Database’s Albania – Table AL.G001: Population: by Gender and Age Group.

1) demographic traitsthese data are published data of age-specific mortality rates, age-specific lengths or weights, length and age at maturity, fecundity-length relationships, and egg size for 84 populations from 49 species of primarily commercial teleost fishes. the populations included are those for which all the life history traits under study have been estimated over a period shorter than 10 years. traits were estimated from within the ten year window or averaged across it when data were available. only studies in which reference population, sample size, techniques used for ageing fish and counting eggs, and models used for estimating mortality were reported are included. when only a size or age range was available, the midpoint between the extreme values was used.raw data were converted into seven demographic traits:- time-to-5%-survival (t.05): the time elapsed from sexual maturity until 95% of a cohort is dead. t.05 fwas estimated from an exponential mortality model, based on total mortality coefficients estimated by virtual population analysis (age-structured model) in most cases or cohort analysis or catch curves.- length-at-5%-survival (l.05). in fishes, adult size is difficult to measure because of their indeterminate growth. adult size reported here is length at time-to-5%-survival. - age at sexual maturity (tm): median age at maturity was estimated directly from the data or by fitting a logistic curve to age-specific proportion mature data. when only an age range was available, the midpoint between minimum and maximum is reported. - length at sexual maturity (lm): median length at maturity was estimated as age at maturity. - slope of the fecundity-length relationship (fb): fish fecundity, defined as the number of eggs present in the ovaries immediately before spawning, is known to increase intraspecifically with the size of females. this increase is usually described by a power-law f = alb. the exponent of this relationship, b (slope of the log-log fecundity-length regression), accounts for the increase in fecundity with size.- fecundity at maturity (fm): fecundity in the year of maturity was estimated from length at maturity, the fecundity-length relationship and the number of spawning bouts per year for batch spawners. - egg volume (egg): when information on egg size was unavailable in specific papers, values were borrowed from other studies, using the following criteria in the descending order: from the same period, the same population, the same species. in five species of perciformes no estimate was available for any population, thus egg volume was estimated from other species of the same family.2) fishing pressurethree types of environments with low, moderate and high fishing pressure were defined.- to scale the pressure exerted by fishing to the natural population turn-over, it was expressed as the ratio of fishing mortality to natural mortality rates (f/m). data were gathered from the literature together with demographic traits. authors use the following methods to estimate natural mortality rates: intercept of a regression of total mortality on fishing effort, linear relationship known between estimates of natural mortality, growth parameters and the temperature, or multispecies models. fishing mortality rates were estimated from virtual population analysis or cohort analysis, or as the difference between total and natural mortality. three levels of fishing pressure were defined: low fishing pressure (fishing mortality lower than natural mortality, f/m < 1), intermediate (1 <= f/m < 2) and high (f/m >= 2).

Retirement Age Men in the United States increased to 66.83 Years in 2025 from 66.67 Years in 2024. This dataset provides - United States Retirement Age Men - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Motor Vehicles Registration: Estimated Average Age: Non Freight Carrying Trucks: South Australia data was reported at 15.200 Year in 2021. This records an increase from the previous number of 15.193 Year for 2020. Motor Vehicles Registration: Estimated Average Age: Non Freight Carrying Trucks: South Australia data is updated yearly, averaging 14.900 Year from Jan 2001 (Median) to 2021, with 21 observations. The data reached an all-time high of 15.200 Year in 2021 and a record low of 14.200 Year in 2001. Motor Vehicles Registration: Estimated Average Age: Non Freight Carrying Trucks: South Australia data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.TA004: Motor Vehicles Registration: Estimated Average Age: by Type and State (Discontinued).

The life expectancy of men at birth in the United States saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 75.8 years. However, 2023 marked the second consecutive increase of the life expectancy. Life expectancy at birth refers to the number of years the average newborn is expected to live, providing that mortality patterns at the time of birth do not change thereafter.Find more statistics on other topics about the United States with key insights such as total fertility rate, infant mortality rate, and total life expectancy at birth.