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.

This statistic depicts the average life expectancy at birth worldwide in 1990 and 2019, by gender. In 2019, women had an average life expectancy of 75.9 years at birth, while men were expected to live 70.8 years.

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

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.

This statistic illustrates the life expectancy at birth in Taiwan from 1990 to 2023 with projections until 2030. In 2023, average life expectancy of Taiwanese increased to 80.23 years.

Chart and table of India life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

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 sex and racial-ethnic groups in Chicago for the years 1990, 2000 and 2010. See the full description at: https://data.cityofchicago.org/api/views/3qdj-cqb8/files/pJ3PVVyubnsS2SpGO5P5IOPtNgCJZTE3LNOeLagC3mw?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\Life Expectancy\Dataset description_LE_ Sex_Race_Ethnicity.pdf

This statistic depicts the average life expectancy at birth worldwide in 1990 and 2013, by income group. In 1990, a child born in a high income household had an average life expectancy of 75 years, while a child born in a low income household was expected to live 53 years.

Chart and table of Germany life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

Over the past 75 years, women have generally had a higher life expectancy than men by around 4-6 years. Reasons for this difference include higher susceptibility to childhood diseases among males; higher rates of accidental deaths, conflict-related deaths, and suicide among adult men; and higher prevalence of unhealthy lifestyle habits and chronic illnesses, as well as higher susceptibility to chronic diseases among men. Therefore, men not only have lower life expectancy than women overall, but also throughout each stage of life. Throughout the given period, there were notable dips in life expectancy for both sexes, including a roughly four year drop in 1960 due to China's so-called Great Leap Forward, and a 1.8 year drop due to the Covid-19 pandemic in 2021. Across the world, differences in life expectancy can vary between the sexes by large margins. In countries such as the Nordics, for example, the difference is low due to high-quality healthcare systems and access, as well as high quality diets and lifestyles. In Eastern Europe, however, the difference is over 10 years in Russia and Ukraine due to the war, although the differences were already very pronounced in this region before 2022, in large part driven by unhealthier lifestyles among men.

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 ...).

Chart and table of Kenya life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

Chart and table of Ireland life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

San Marino Life Expectancy at Birth data was reported at 80.880 Year in 2021. This records an increase from the previous number of 79.590 Year for 2020. San Marino Life Expectancy at Birth data is updated yearly, averaging 80.825 Year from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 82.990 Year in 2019 and a record low of 78.670 Year in 1990. San Marino Life Expectancy at Birth data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s San Marino – Table SM.OECD.GGI: Social: Demography: Non OECD Member: Annual.

Chart and table of Canada life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

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.

Life Expectancy: Male: Sichuan data was reported at 75.010 Year Old in 12-01-2020. This records an increase from the previous number of 72.250 Year Old for 12-01-2010. Life Expectancy: Male: Sichuan data is updated decadal, averaging 70.750 Year Old from Dec 1990 (Median) to 12-01-2020, with 4 observations. The data reached an all-time high of 75.010 Year Old in 12-01-2020 and a record low of 65.060 Year Old in 12-01-1990. Life Expectancy: Male: Sichuan data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Life Expectancy: By Region.

Chart and table of Romania life expectancy from 1950 to 2025. United Nations projections are also included through the year 2100.

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

Life Expectancy at Birth: FE: Kamchatka Territory data was reported at 70.430 Year in 2023. This records an increase from the previous number of 68.770 Year for 2022. Life Expectancy at Birth: FE: Kamchatka Territory data is updated yearly, averaging 65.750 Year from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 70.570 Year in 2019 and a record low of 60.400 Year in 1994. Life Expectancy at Birth: FE: Kamchatka Territory data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GD011: Life Expectancy at Birth: by Region.