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.

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.

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).

The average for 2022 based on 12 countries was 72.9 years. The highest value was in Chile: 79.52 years and the lowest value was in Bolivia: 64.93 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Abstract

The Health Inequality Project uses big data to measure differences in life expectancy by income across areas and identify strategies to improve health outcomes for low-income Americans.

Section 7

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution. Both race-adjusted and unadjusted estimates are reported.

Source

Section 13

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution separately by year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 6

This dataset was created on 2020-01-10 18:53:00.508 by merging multiple datasets together. The source datasets for this version were:

Commuting Zone Life Expectancy Estimates by year: CZ-level by-year life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy: Commuting zone (CZ)-level life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy Trends: CZ-level estimates of trends in life expectancy for men and women, by income quartile

Commuting Zone Characteristics: CZ-level characteristics

Commuting Zone Life Expectancy for larger populations: CZ-level life expectancy estimates for men and women, by income ventile

Section 15

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by state of residence and year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 11

This table reports US mortality rates by gender, age, year and household income percentile. Household incomes are measured two years prior to the mortality rate for mortality rates at ages 40-63, and at age 61 for mortality rates at ages 64-76. The “lag” variable indicates the number of years between measurement of income and mortality.

Observations with 1 or 2 deaths have been masked: all mortality rates that reflect only 1 or 2 deaths have been recoded to reflect 3 deaths

Source

Section 3

This table reports coefficients and standard errors from regressions of life expectancy estimates for men and women at age 40 for each quartile of the national income distribution on calendar year by commuting zone of residence. Only the slope coefficient, representing the average increase or decrease in life expectancy per year, is reported. Trend estimates for both race-adjusted and unadjusted life expectancies are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 9

This table reports life expectancy estimates at age 40 for Males and Females for all countries. Source: World Health Organization, accessed at: http://apps.who.int/gho/athena/

Source

Section 10

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by county of residence. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for counties with populations larger than 25,000 only

Source

Section 2

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by commuting zone of residence and year. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 8

This table reports US population and death counts by age, year, and sex from various sources. Counts labelled “dm1” are derived from the Social Security Administration Data Master 1 file. Counts labelled “irs” are derived from tax data. Counts labelled “cdc” are derived from NCHS life tables.

Source

Section 12

This table reports numerous county characteristics, compiled from various sources. These characteristics are described in the county life expectancy table.

Two variables constructed by the Cen

The average for 2022 based on 24 countries was 77.36 years. The highest value was in Bermuda: 84.51 years and the lowest value was in Haiti: 66.7 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.

30-lt_input.csv

Life table input data.

id: unique row identifier

region_iso: iso3166-2 region codes

sex: Male, Female, Total

year: iso year

age_start: start of age group

age_width: width of age group, Inf for age_start 100, otherwise 1

nweeks_year: number of weeks in that year, 52 or 53

death_total: number of deaths by any cause

population_py: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)

death_total_nweeksmiss: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)

death_total_minnageraw: the minimum number of age-groups in the raw input data within this region-sex-year stratum

death_total_maxnageraw: the maximum number of age-groups in the raw input data within this region-sex-year stratum

death_total_minopenageraw: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_maxopenageraw: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_source: source of the all-cause death data

death_total_prop_q1: observed proportion of deaths in first quarter of year

death_total_prop_q2: observed proportion of deaths in second quarter of year

death_total_prop_q3: observed proportion of deaths in third quarter of year

death_total_prop_q4: observed proportion of deaths in fourth quarter of year

death_expected_prop_q1: expected proportion of deaths in first quarter of year

death_expected_prop_q2: expected proportion of deaths in second quarter of year

death_expected_prop_q3: expected proportion of deaths in third quarter of year

death_expected_prop_q4: expected proportion of deaths in fourth quarter of year

population_midyear: midyear population (July 1st)

population_source: source of the population count/exposure data

death_covid: number of deaths due to covid

death_covid_date: number of deaths due to covid as of

death_covid_nageraw: the number of age groups in the covid input data

ex_wpp_estimate: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year

ex_hmd_estimate: life expectancy estimates from the Human Mortality Database

nmx_hmd_estimate: death rate estimates from the Human Mortality Database

nmx_cntfc: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

source:

STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)

ONS for GB-EAW pre 2020

CDC for US pre 2020

STMF:

harmonized to single ages via pclm

pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110

smoothing parameters estimated via BIC grid search seperately for every pclm iteration

last age group set to [110,111)

ages 100:110+ are then summed into 100+ to be consistent with mid-year population information

deaths in unknown weeks are considered; deaths in unknown ages are not considered

ONS:

data already in single ages

ages 100:105+ are summed into 100+ to be consistent with mid-year population information

PCLM smoothing applied to for consistency reasons

CDC:

The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

source:

for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019

for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100

mid-year population

mid-year population translated into exposures:

if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates

if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

source: COVerAGE-DB (https://osf.io/mpwjq/)

the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

source:

World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019

Human Mortality Database (https://mortality.org/), single year and age tables

Japan had the highest life expectancy at birth of the G7 countries between 2000 and 2025, reaching **. On the other hand, life expectancy in the United States was ***** years, the only one of the seven where it was below 80. Life expectancy dropped in all G7 countries following the COVID-19 pandemic.

The average for 2022 based on 7 countries was 81.52 years. The highest value was in Japan: 84 years and the lowest value was in the USA: 77.43 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

As of 2023, the countries with the highest life expectancy included Liechtenstein, Switzerland, and Japan. In Japan, a person could expect to live up to around ** years. In general, the life expectancy for females is higher than that of males, with lifestyle choices and genetics the two major determining factors of life expectancy. Life expectancy worldwide The overall life expectancy worldwide has increased since the development of modern medicine and technology. In 2011, the global life expectancy was **** years. By 2023, it had increased to **** years. However, the years 2020 and 2021 saw a decline in global life expectancy due to the COVID-19 pandemic. Furthermore, not every country has seen a substantial increase in life expectancy. In Nigeria, for example, the life expectancy is only ** years, almost ***years shorter than the global average. In addition to Nigeria, the countries with the shortest life expectancy include Chad, Lesotho, and the Central African Republic. Life expectancy in the U.S. In the United States, life expectancy at birth is currently ***** years. Life expectancy in the U.S. generally increases every year, however, over the past decade, life expectancy has seen some surprising decreases. The major contributing factors to this drop have been the ongoing opioid epidemic, which claimed around ****** lives in 2022 alone, and the COVID-19 pandemic.

Objective Gains in life expectancy have faltered in several high-income countries in recent years. We aim to compare life expectancy trends in Scotland to those seen internationally, and to assess the timing of any recent changes in mortality trends for Scotland. Setting Austria, Croatia, Czech Republic, Denmark, England & Wales, Estonia, France, Germany, Hungary, Iceland, Israel, Japan, Korea, Latvia, Lithuania, Netherlands, Northern Ireland, Poland, Scotland, Slovakia, Spain, Sweden, Switzerland, USA. Methods We used life expectancy data from the Human Mortality Database (HMD) to calculate the mean annual life expectancy change for 24 high-income countries over five-year periods from 1992 to 2016, and the change for Scotland for five-year periods from 1857 to 2016. One- and two-break segmented regression models were applied to mortality data from National Records of Scotland (NRS) to identify turning points in age-standardised mortality trends between 1990 and 2018. Results In 2012-2016 life expectancies in Scotland increased by 2.5 weeks/year for females and 4.5 weeks/year for males, the smallest gains of any period since the early 1970s. The improvements in life expectancy in 2012-2016 were smallest among females (<2.0 weeks/year) in Northern Ireland, Iceland, England & Wales and the USA and among males (<5.0 weeks/year) in Iceland, USA, England & Wales and Scotland. Japan, Korea, and countries of Eastern Europe have seen substantial gains in the same period. The best estimate of when mortality rates changed to a slower rate of improvement in Scotland was the year to 2012 Q4 for males and the year to 2014 Q2 for females. Conclusion Life expectancy improvement has stalled across many, but not all, high income countries. The recent change in the mortality trend in Scotland occurred within the period 2012-2014. Further research is required to understand these trends, but governments must also take timely action on plausible contributors. Description of methods used for collection/generation of data: The HMD has a detailed methods protocol available here: https://www.mortality.org/Public/Docs/MethodsProtocol.pdf The ONS and NRS also have similar methods for ensuring data consistency and quality assurance. Methods for processing the data: The segmented regression was conducted using the 'segmented' package in R. The recommended references to this package and its approach are here: Vito M. R. Muggeo (2003). Estimating regression models with unknown break-points. Statistics in Medicine, 22, 3055-3071. Vito M. R. Muggeo (2008). segmented: an R Package to Fit Regression Models with Broken-Line Relationships. R News, 8/1, 20-25. URL https://cran.r-project.org/doc/Rnews/. Vito M. R. Muggeo (2016). Testing with a nuisance parameter present only under the alternative: a score-based approach with application to segmented modelling. J of Statistical Computation and Simulation, 86, 3059-3067. Vito M. R. Muggeo (2017). Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach. Australian & New Zealand Journal of Statistics, 59, 311-322. Software- or Instrument-specific information needed to interpret the data, including software and hardware version numbers: The analyses were conducted in R version 3.6.1 and Microsoft Excel 2013. Please see README.txt for further information HMD international_updated Jan 2019.xlsx Comprises 20 worksheets, of which 14 contain data. These data are arranged by country and by year. Missing data codes: "" The tab 'contents and sources' provides descriptions of the data source and contents of each sheet. HMD Scotland time trend analysis.xlsx Comprises 5 worksheets, including a combination of data and charts. The sheet 'contents' describes the data source and contents of other sheets. The variables include year, life expectancy, and various measures of change in life expectancy Missing data codes: "" Segmented regression chart.xlsx Comprises 2 worksheets, 'Data' and 'Chart'. Variables within the 'data' worksheet include: Year 4 quarter rolling period ending Female observed mortality rate Female predicted by one-break model Female predicted by two-break model Male observed mortality rate Male predicted by one-break model Male predicted by two-break model Chart breakpoint indicator Missing data codes: (blank space) Summary findings from segmented regression.xlsx Excel workbook containing table 1 of paper 'summary of results of segmented regression by population group and model/test'

Ukraine UA: Life Expectancy at Birth: Male data was reported at 66.730 Year in 2016. This records an increase from the previous number of 66.370 Year for 2015. Ukraine UA: Life Expectancy at Birth: Male data is updated yearly, averaging 65.186 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 66.878 Year in 1966 and a record low of 61.400 Year in 1996. Ukraine UA: Life Expectancy at Birth: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Health Statistics. 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.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

The average for 2022 based on 11 countries was 81.87 years. The highest value was in Japan: 84 years and the lowest value was in the USA: 77.43 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Men born in Chad have the lowest life expectancy in the world as of 2024, reaching only 53 years. The lowest life expectancy for women in the world in 2024 was for girls born in Nigeria, with only 55 years. Except for Afghanistan, all the countries with the lowest life expectancy in the world are in Africa.

Tunisia had the highest life expectancy at birth in Africa as of 2025. A newborn infant was expected to live about 77 years in the country. Algeria, Cabo Verde, Morocco, and Mauritius followed, with a life expectancy between 77 and 75 years. On the other hand, Nigeria registered the lowest average, at 54.8 years. Overall, the life expectancy in Africa was just over 64 years in the same year.

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.

In 2024, the average life expectancy for those born in more developed countries was 76 years for men and 82 years for women. On the other hand, the respective numbers for men and women born in the least developed countries were 64 and 69 years. Improved health care has lead to higher life expectancy Life expectancy is the measure of how long a person is expected to live. Life expectancy varies worldwide and involves many factors such as diet, gender, and environment. As medical care has improved over the years, life expectancy has increased worldwide. Introduction to health care such as vaccines has significantly improved the lives of millions of people worldwide. The average worldwide life expectancy at birth has steadily increased since 2007, but dropped during the COVID-19 pandemic in 2020 and 2021. Life expectancy worldwide More developed countries tend to have higher life expectancies, for a multitude of reasons. Health care infrastructure and quality of life tend to be higher in more developed countries, as is access to clean water and food. Africa was the continent that had the lowest life expectancy for both men and women in 2023, while Oceania had the highest for men and Europe and Oceania had the highest for women.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

For most of the world, throughout most of human history, the average life expectancy from birth was around 24. This figure fluctuated greatly depending on the time or region, and was higher than 24 in most individual years, but factors such as pandemics, famines, and conflicts caused regular spikes in mortality and reduced life expectancy. Child mortality The most significant difference between historical mortality rates and modern figures is that child and infant mortality was so high in pre-industrial times; before the introduction of vaccination, water treatment, and other medical knowledge or technologies, women would have around seven children throughout their lifetime, but around half of these would not make it to adulthood. Accurate, historical figures for infant mortality are difficult to ascertain, as it was so prevalent, it took place in the home, and was rarely recorded in censuses; however, figures from this source suggest that the rate was around 300 deaths per 1,000 live births in some years, meaning that almost one in three infants did not make it to their first birthday in certain periods. For those who survived to adolescence, they could expect to live into their forties or fifties on average. Modern figures It was not until the eradication of plague and improvements in housing and infrastructure in recent centuries where life expectancy began to rise in some parts of Europe, before industrialization and medical advances led to the onset of the demographic transition across the world. Today, global life expectancy from birth is roughly three times higher than in pre-industrial times, at almost 73 years. It is higher still in more demographically and economically developed countries; life expectancy is over 82 years in the three European countries shown, and over 84 in Japan. For the least developed countries, mostly found in Sub-Saharan Africa, life expectancy from birth can be as low as 53 years.

This statistic shows the 20 countries * with the lowest infant mortality rate in 2024. An estimated 1.5 out of 1,000 live births died in the first year of life in Slovenia and Singapore in 2024. Infant mortality Infant mortality rates are often used as an indicator of the health and well-being of a nation. Monaco, Iceland, and Japan are among the top three countries with the lowest infant mortality rates with around 2 infant deaths per 1,000 infants within their first year of life. Generally, the countries with the lowest infant mortality also have some of the highest average life expectancy figures. Additionally, the countries with the highest density of physicians and doctors also generally report low infant mortality. Yet, many different factors contribute to differing rates, including the overall income of a country, health spending per capita, a mother’s level of education, environmental conditions, and medical infrastructure, to name a few. This creates a lot of variation concerning the level of childbirth and infant care around the world. The countries with the highest rates of infant mortality include Afghanistan, Mali, and Somalia. These countries experience around 100 infant deaths per 1,000 infants in their first year of life. While the reasons for high rates of infant mortality are numerous, the leading causes of death for children under the year five around the world are Pneumonia, Diarrhea, and Prematurity.