100+ datasets found
  1. M

    U.S. Life Expectancy (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
    + more versions
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    MACROTRENDS (2025). U.S. Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/usa/united-states/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Dec 31, 2025
    Area covered
    United States
    Description

    Historical chart and dataset showing U.S. life expectancy by year from 1950 to 2025.

  2. Life expectancy at birth worldwide 1950-2100

    • statista.com
    • ai-chatbox.pro
    Updated Mar 26, 2025
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    Statista (2025). Life expectancy at birth worldwide 1950-2100 [Dataset]. https://www.statista.com/statistics/805060/life-expectancy-at-birth-worldwide/
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    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Global life expectancy at birth has risen significantly since the mid-1900s, from roughly 46 years in 1950 to 73.2 years in 2023. Post-COVID-19 projections There was a drop of 1.7 years during the COVID-19 pandemic, between 2019 and 2021, however, figures resumed upon their previous trajectory the following year due to the implementation of vaccination campaigns and the lower severity of later strains of the virus. By the end of the century it is believed that global life expectancy from birth will reach 82 years, although growth will slow in the coming decades as many of the more-populous Asian countries reach demographic maturity. However, there is still expected to be a wide gap between various regions at the end of the 2100s, with the Europe and North America expected to have life expectancies around 90 years, whereas Sub-Saharan Africa is predicted to be in the low-70s. The Great Leap Forward While a decrease of one year during the COVID-19 pandemic may appear insignificant, this is the largest decline in life expectancy since the "Great Leap Forward" in China in 1958, which caused global life expectancy to fall by almost four years between by 1960. The "Great Leap Forward" was a series of modernizing reforms, which sought to rapidly transition China's agrarian economy into an industrial economy, but mismanagement led to tens of millions of deaths through famine and disease.

  3. M

    World Life Expectancy (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). World Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/wld/world/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Dec 31, 2025
    Area covered
    World, World
    Description

    Historical chart and dataset showing World life expectancy by year from 1950 to 2025.

  4. C

    Public Health Statistics - Life Expectancy By Community Area - Historical

    • data.cityofchicago.org
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated Jun 16, 2014
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    Vital statistics files produced by the Illinois Department of Public Health (IDPH) (2014). Public Health Statistics - Life Expectancy By Community Area - Historical [Dataset]. https://data.cityofchicago.org/widgets/qjr3-bm53
    Explore at:
    application/rssxml, json, xml, tsv, application/rdfxml, csvAvailable download formats
    Dataset updated
    Jun 16, 2014
    Dataset authored and provided by
    Vital statistics files produced by the Illinois Department of Public Health (IDPH)
    Description

    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

  5. Global life expectancy at birth by gender 1950-2100

    • statista.com
    Updated Feb 25, 2025
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    Statista (2025). Global life expectancy at birth by gender 1950-2100 [Dataset]. https://www.statista.com/statistics/673420/projected-global-life-expectancy/
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    Dataset updated
    Feb 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    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.

  6. M

    Life Expectancy Statistics 2025 By Health Progress

    • media.market.us
    Updated Jan 14, 2025
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    Market.us Media (2025). Life Expectancy Statistics 2025 By Health Progress [Dataset]. https://media.market.us/life-expectancy-statistics/
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    Dataset updated
    Jan 14, 2025
    Dataset authored and provided by
    Market.us Media
    License

    https://media.market.us/privacy-policyhttps://media.market.us/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    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.

    https://media.market.us/wp-content/uploads/2024/12/life-expectancy-statistics.png" alt="Life Expectancy Statistics" class="wp-image-27483">

  7. Life expectancy in North America 2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Life expectancy in North America 2022 [Dataset]. https://www.statista.com/statistics/274513/life-expectancy-in-north-america/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    North America
    Description

    This statistic shows the average life expectancy in North America for those born in 2022, by gender and region. In Canada, the average life expectancy was 80 years for males and 84 years for females.

    Life expectancy in North America

    Of those considered in this statistic, the life expectancy of female Canadian infants born in 2021 was the longest, at 84 years. Female infants born in America that year had a similarly high life expectancy of 81 years. Male infants, meanwhile, had lower life expectancies of 80 years (Canada) and 76 years (USA).

    Compare this to the worldwide life expectancy for babies born in 2021: 75 years for women and 71 years for men. Of continents worldwide, North America ranks equal first in terms of life expectancy of (77 years for men and 81 years for women). Life expectancy is lowest in Africa at just 63 years and 66 years for males and females respectively. Japan is the country with the highest life expectancy worldwide for babies born in 2020.

    Life expectancy is calculated according to current mortality rates of the population in question. Global variations in life expectancy are caused by differences in medical care, public health and diet, and reflect global inequalities in economic circumstances. Africa’s low life expectancy, for example, can be attributed in part to the AIDS epidemic. In 2019, around 72,000 people died of AIDS in South Africa, the largest amount worldwide. Nigeria, Tanzania and India were also high on the list of countries ranked by AIDS deaths that year. Likewise, Africa has by far the highest rate of mortality by communicable disease (i.e. AIDS, neglected tropics diseases, malaria and tuberculosis).

  8. Life expectancy by continent and gender 2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Life expectancy by continent and gender 2024 [Dataset]. https://www.statista.com/statistics/270861/life-expectancy-by-continent/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    In 2024, the average life expectancy in the world was 71 years for men and 76 years for women. The lowest life expectancies were found in Africa, while Oceania and Europe had the highest. What is life expectancy?Life expectancy is defined as a statistical measure of how long a person may live, based on demographic factors such as gender, current age, and most importantly the year of their birth. The most commonly used measure of life expectancy is life expectancy at birth or at age zero. The calculation is based on the assumption that mortality rates at each age were to remain constant in the future. Life expectancy has changed drastically over time, especially during the past 200 years. In the early 20th century, the average life expectancy at birth in the developed world stood at 31 years. It has grown to an average of 70 and 75 years for males and females respectively, and is expected to keep on growing with advances in medical treatment and living standards continuing. Highest and lowest life expectancy worldwide Life expectancy still varies greatly between different regions and countries of the world. The biggest impact on life expectancy is the quality of public health, medical care, and diet. As of 2022, the countries with the highest life expectancy were Japan, Liechtenstein, Switzerland, and Australia, all at 84–83 years. Most of the countries with the lowest life expectancy are mostly African countries. The ranking was led by the Chad, Nigeria, and Lesotho with 53–54 years.

  9. M

    Thailand Life Expectancy (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). Thailand Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/tha/thailand/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Dec 31, 2025
    Area covered
    Thailand
    Description

    Historical chart and dataset showing Thailand life expectancy by year from 1950 to 2025.

  10. T

    Vital Signs: Life Expectancy – by county

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Mar 22, 2017
    + more versions
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    State of California, Department of Health: Death Records (2017). Vital Signs: Life Expectancy – by county [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Life-Expectancy-by-county/g26a-g4jw
    Explore at:
    csv, application/rdfxml, tsv, json, application/rssxml, xmlAvailable download formats
    Dataset updated
    Mar 22, 2017
    Dataset authored and provided by
    State of California, Department of Health: Death Records
    Description

    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/

    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. 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 https://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). 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. In this way, the original 305 Bay Area Zip codes were reduced to 218 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.

  11. M

    China Life Expectancy 1950-2025

    • macrotrends.net
    csv
    Updated May 31, 2025
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    MACROTRENDS (2025). China Life Expectancy 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/chn/china/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Jun 2, 2025
    Area covered
    China
    Description
    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.
    
  12. T

    Vital Signs: Life Expectancy – Bay Area

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Mar 22, 2017
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    State of California, Department of Health: Death Records (2017). Vital Signs: Life Expectancy – Bay Area [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Life-Expectancy-Bay-Area/emjt-svg9
    Explore at:
    xml, csv, tsv, application/rssxml, json, application/rdfxmlAvailable download formats
    Dataset updated
    Mar 22, 2017
    Dataset authored and provided by
    State of California, Department of Health: Death Records
    Area covered
    San Francisco Bay Area
    Description

    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/

    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. 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 https://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). 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. In this way, the original 305 Bay Area Zip codes were reduced to 218 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.

  13. Life expectancy in selected countries 2023

    • statista.com
    • ai-chatbox.pro
    Updated Apr 15, 2020
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    Statista (2020). Life expectancy in selected countries 2023 [Dataset]. https://www.statista.com/statistics/236583/global-life-expectancy-by-country/
    Explore at:
    Dataset updated
    Apr 15, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of 2023, the countries with the highest life expectancy included Switzerland, Japan, and Spain. As of that time, a new-born child in Switzerland could expect to live an average of **** years. Around the world, females consistently have a higher average life expectancy than males, with females in Europe expected to live an average of *** years longer than males on this continent. Increases in life expectancy The overall average life expectancy in OECD countries increased by **** years from 1970 to 2019. The countries that saw the largest increases included Turkey, India, and South Korea. The life expectancy at birth in Turkey increased an astonishing 24.4 years over this period. The countries with the lowest life expectancy worldwide as of 2022 were Chad, Lesotho, and Nigeria, where a newborn could be expected to live an average of ** years. Life expectancy in the U.S. The life expectancy in the United States was ***** years as of 2023. Shockingly, the life expectancy in the United States has decreased in recent years, while it continues to increase in other similarly developed countries. The COVID-19 pandemic and increasing rates of suicide and drug overdose deaths from the opioid epidemic have been cited as reasons for this decrease.

  14. M

    Africa Life Expectancy (1950-2025)

    • macrotrends.net
    csv
    Updated May 31, 2025
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    MACROTRENDS (2025). Africa Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/afr/africa/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 31, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Africa
    Description
    Africa life expectancy for 2025 is 64.64, a 0.41% increase from 2024.
    <ul style='margin-top:20px;'>
    
    <li>Africa life expectancy for 2024 was <strong>64.38</strong>, a <strong>0.41% increase</strong> from 2023.</li>
    <li>Africa life expectancy for 2023 was <strong>64.11</strong>, a <strong>0.45% increase</strong> from 2022.</li>
    <li>Africa life expectancy for 2022 was <strong>63.82</strong>, a <strong>0.46% 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.
    
  15. F

    Life Expectancy at Birth, Total for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 16, 2025
    + more versions
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    (2025). Life Expectancy at Birth, Total for the United States [Dataset]. https://fred.stlouisfed.org/series/SPDYNLE00INUSA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 16, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Life Expectancy at Birth, Total for the United States (SPDYNLE00INUSA) from 1960 to 2023 about life expectancy, life, birth, and USA.

  16. M

    Japan Life Expectancy 1950-2025

    • macrotrends.net
    csv
    Updated Apr 30, 2025
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    MACROTRENDS (2025). Japan Life Expectancy 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/jpn/japan/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - May 30, 2025
    Area covered
    Japan
    Description
    Japan life expectancy for 2025 is 85.27, a 0.14% increase from 2024.
    <ul style='margin-top:20px;'>
    
    <li>Japan life expectancy for 2024 was <strong>85.15</strong>, a <strong>0.14% increase</strong> from 2023.</li>
    <li>Japan life expectancy for 2023 was <strong>85.03</strong>, a <strong>0.14% increase</strong> from 2022.</li>
    <li>Japan life expectancy for 2022 was <strong>84.91</strong>, a <strong>0.14% 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.
    
  17. Life Expectancy 1960 to present (Global)

    • kaggle.com
    Updated Mar 13, 2025
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    Frederick Salazar Sanchez (2025). Life Expectancy 1960 to present (Global) [Dataset]. https://www.kaggle.com/datasets/fredericksalazar/life-expectancy-1960-to-present-global
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 13, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Frederick Salazar Sanchez
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    PLEASE if you use or like this dataset UPVOTE 👁️

    This dataset offers a detailed historical record of global life expectancy, covering data from 1960 to the present. It is meticulously curated to enable deep analysis of trends and gender disparities in life expectancy worldwide.

    Dataset Structure & Key Columns:

    Country Code (🔤): Unique identifier for each country.

    Country Name (🌍): Official name of the country.

    Region (🌐): Broad geographical area (e.g., Asia, Europe, Africa).

    Sub-Region (🗺️): More specific regional classification within the broader region.

    Intermediate Region (🔍): Additional granular geographical grouping when applicable.

    Year (📅): The specific year to which the data pertains.

    Life Expectancy for Women (👩‍⚕️): Average years a woman is expected to live in that country and year.

    Life Expectancy for Men (👨‍⚕️): Average years a man is expected to live in that country and year.

    Context & Use Cases:

    This dataset is a rich resource for exploring long-term trends in global health and demography. By comparing life expectancy data over decades, researchers can:

    Analyze Time Series Trends: Forecast future changes in life expectancy and evaluate the impact of health interventions over time.

    Study Gender Disparities: Investigate the differences between life expectancy for women and men, providing insights into social, economic, and healthcare factors influencing these trends.

    Regional & Sub-Regional Analysis: Compare and contrast life expectancy across various regions and sub-regions to understand geographical disparities and their underlying causes.

    Support Public Policy Research: Inform policymakers by linking life expectancy trends with public health policies, socioeconomic developments, and other key indicators.

    Educational & Data Science Applications: Serve as a comprehensive teaching tool for courses on public health, global development, and data analysis, as well as for Kaggle competitions and projects.

    With its detailed, structured format and broad temporal coverage, this dataset is ideal for anyone looking to gain a nuanced understanding of global health trends and to drive impactful analyses in public health, social sciences, and beyond.

    Feel free to ask for further customizations or additional details as needed!

  18. M

    Italy Life Expectancy (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). Italy Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/ita/italy/life-expectancy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Dec 31, 2025
    Area covered
    Italy
    Description

    Historical chart and dataset showing Italy life expectancy by year from 1950 to 2025.

  19. Life expectancy at birth and at age 65, by province and territory,...

    • www150.statcan.gc.ca
    • datasets.ai
    • +5more
    Updated Dec 6, 2017
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    Government of Canada, Statistics Canada (2017). Life expectancy at birth and at age 65, by province and territory, three-year average [Dataset]. http://doi.org/10.25318/1310040901-eng
    Explore at:
    Dataset updated
    Dec 6, 2017
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

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

  20. Life expectancy and other elements of the complete life table, three-year...

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +2more
    Updated Dec 4, 2024
    + more versions
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    Government of Canada, Statistics Canada (2024). Life expectancy and other elements of the complete life table, three-year estimates, Canada, all provinces except Prince Edward Island [Dataset]. http://doi.org/10.25318/1310011401-eng
    Explore at:
    Dataset updated
    Dec 4, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Government of Canadahttp://www.gg.ca/
    Area covered
    Canada
    Description

    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).

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
MACROTRENDS (2025). U.S. Life Expectancy (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/usa/united-states/life-expectancy

U.S. Life Expectancy (1950-2025)

U.S. Life Expectancy (1950-2025)

Explore at:
8 scholarly articles cite this dataset (View in Google Scholar)
csvAvailable download formats
Dataset updated
Jun 30, 2025
Dataset authored and provided by
MACROTRENDS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 1, 1950 - Dec 31, 2025
Area covered
United States
Description

Historical chart and dataset showing U.S. life expectancy by year from 1950 to 2025.

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