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 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 dataset presents life expectancy at birth estimates based on annual complete period life tables for each of the 50 states and the District of Columbia (D.C.) in 2020 for the total, male and female populations.

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.

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.

Life expectancy at birth for males and females for Middle Layer Super Output Areas (MSOAs), Leicester: 2016 to 2020The average number of years a person would expect to live based on contemporary mortality rates.For a particular area and time period, it is an estimate of the average number of years a newborn baby would survive if he or she experienced the age-specific mortality rates for that area and time period throughout his or her life.Life expectancy figures have been calculated based on death registrations between 2016 to 2020, which includes the first wave and part of the second wave of the coronavirus (COVID-19) pandemic.

This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

In 1875, the average person born in Chile could expect to live to the age of 32 years, a figure that would remain largely stagnante throughout the late 19th and early 20th century, as the country’s Parliamentary era would see relatively little change in the day to day lives of the country’s citizens. Outside of two dips in 1910 and 1920, the latter primarily driven by the 1918 Spanish Flu epidemic. Life expectancy would see two sharp increases following the end of the First World War; the first in the 1920s, and the most dramatic in the early 1950s.

The first of these spikes, under President Ibáñez del Campo, can be attributed primarily to large increases in spending on public healthcare and improvements in public sanitation by the Campo administration. The second and larger spike, under President González Videla, can be attributed to a combination of mass immunization and vaccination, and the implementation of a national health care system, drastically cutting child mortality in the country. As a result of these reforms, life expectancy in Chile would more than double in just thirty years, rising from just over 33 years in 1925 to 69 years by 1955. Following the end of the Videla administration in 1952, life expectancy would continue to rise in Chile, as increasing urbanization, and the successful eradication of many childhood diseases would see both child and overall mortality decline. This rise has continued even into the 21st century, and as a result, life expectancy in Chile rose to over 78 years by the end of the century, and in 2020, it is estimated that the average person born in Chile will live to over 82 years old, the highest in South America.

Life expectancy in India was 25.4 in the year 1800, and over the course of the next 220 years, it has increased to almost 70. Between 1800 and 1920, life expectancy in India remained in the mid to low twenties, with the largest declines coming in the 1870s and 1910s; this was because of the Great Famine of 1876-1878, and the Spanish Flu Pandemic of 1918-1919, both of which were responsible for the deaths of up to six and seventeen million Indians respectively; as well as the presence of other endemic diseases in the region, such as smallpox. From 1920 onwards, India's life expectancy has consistently increased, but it is still below the global average.

Data for Figures and Tables in "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 data in the figures and tables published in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

50-e0diffT.csv

• Figure 1: Life expectancy changes 2019/20 and 2020/21 across countries. The countries areordered by increasing cumulative life expectancy losses since 2019. Grey dots indicate theaverage annual LE changes over the years 2015 through 2019.

51-arriagaT.csv

• Figure 2: Age contributions to life expectancy changes since 2019 separated for 2020 and 2021.

52-sexdiff.csv

• Figure 3: Change in the female life expectancy advantage from 2019 through 2021. Muted colorsindicate non-significant changes.

53-e0diffcodT.csv

• Figure 4:Life expectancy deficit in 2021 decomposed into contributions by age and cause of death. LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

54-tab_arriaga.csv

• Table 1: Months of life expectancy (LE) changes and deficits (labelled ES) since the start of thepandemic attributed to age-specific mortality changes (labelled AT). LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

Chart and table of India 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.

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE), Slope Index of Inequality (SII) and range by national deprivation deciles using the Index of Multiple Deprivation 2015 for data periods from 2011 to 2013 to 2015 to 2017, and the Index of Multiple Deprivation 2019 for data periods from 2016 to 2018 to 2018 to 2020: England, 2011 to 2013 to 2018 to 2020.

China Life Expectancy: Male data was reported at 75.370 Year Old in 2020. This records an increase from the previous number of 73.640 Year Old for 2015. China Life Expectancy: Male data is updated yearly, averaging 70.830 Year Old from Dec 1981 (Median) to 2020, with 7 observations. The data reached an all-time high of 75.370 Year Old in 2020 and a record low of 66.280 Year Old in 1981. China Life Expectancy: Male 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.

This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the 2020 County Health Rankings page about Life Expectancy:"Life Expectancy is an AverageLife Expectancy measures the average number of years from birth a person can expect to live, according to the current mortality experience (age-specific death rates) of the population. Life Expectancy takes into account the number of deaths in a given time period and the average number of people at risk of dying during that period, allowing us to compare data across counties with different population sizes.Life Expectancy is Age-AdjustedAge is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. Life Expectancy is age-adjusted in order to fairly compare counties with differing age structures.What Deaths Count Toward Life Expectancy?Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, that death is attributed to his/her home county.Some Data are SuppressedA missing value is reported for counties with fewer than 5,000 population-years-at-risk in the time frame.Measure LimitationsLife Expectancy includes mortality of all age groups in a population instead of focusing just on premature deaths and thus can be dominated by deaths of the elderly.[1] This could draw attention to areas with higher mortality rates among the oldest segment of the population, where there may be little that can be done to change chronic health problems that have developed over many years. However, this captures the burden of chronic disease in a population better than premature death measures.[2]Furthermore, the calculation of life expectancy is complex and not easy to communicate. Methodologically, it can produce misleading results caused by hidden differences in age structure, is sensitive to infant and child mortality, and tends to be overestimated in small populations."Click on the map to see a breakdown by race/ethnicity in the pop-up: Full details about this measureThere are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.Data from County Health Rankings 2020 (in this layer and referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World

This multi-scale map shows life expectancy - a widely-used measure of health and mortality. From the County Health Rankings page about Life Expectancy:"Life Expectancy is an AverageLife Expectancy measures the average number of years from birth a person can expect to live, according to the current mortality experience (age-specific death rates) of the population. Life Expectancy takes into account the number of deaths in a given time period and the average number of people at risk of dying during that period, allowing us to compare data across counties with different population sizes.Life Expectancy is Age-AdjustedAge is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. Life Expectancy is age-adjusted in order to fairly compare counties with differing age structures.What Deaths Count Toward Life Expectancy?Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, that death is attributed to his/her home county.Some Data are SuppressedA missing value is reported for counties with fewer than 5,000 population-years-at-risk in the time frame.Measure LimitationsLife Expectancy includes mortality of all age groups in a population instead of focusing just on premature deaths and thus can be dominated by deaths of the elderly.[1] This could draw attention to areas with higher mortality rates among the oldest segment of the population, where there may be little that can be done to change chronic health problems that have developed over many years. However, this captures the burden of chronic disease in a population better than premature death measures.[2]Furthermore, the calculation of life expectancy is complex and not easy to communicate. Methodologically, it can produce misleading results caused by hidden differences in age structure, is sensitive to infant and child mortality, and tends to be overestimated in small populations."Breakdown by race/ethnicity in pop-up: (This map has been updated with new data, so figures may vary from those in this image.)There are many factors that play into life expectancy: rates of noncommunicable diseases such as cancer, diabetes, and obesity, prevalence of tobacco use, prevalence of domestic violence, and many more.Proven strategies to improve life expectancy and health in general A database of dozens of strategies can be found at County Health Rankings' What Works for Health site, sorted by Health Behaviors, Clinical Care, Social & Economic Factors, and Physical Environment. Policies and Programs listed here have been evaluated as to their effectiveness. For example, consumer-directed health plans received an evidence rating of "mixed evidence" whereas cultural competence training for health care professionals received a rating of "scientifically supported." Data from County Health Rankings (layer referenced below), available for nation, state, and county, and available in ArcGIS Living Atlas of the World.

Period life expectancy by age and sex. Each life table is based on population estimates, births and deaths for a single year.

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.

Life Expectancy: Anhui data was reported at 77.960 Year Old in 12-01-2020. This records an increase from the previous number of 75.080 Year Old for 12-01-2010. Life Expectancy: Anhui data is updated decadal, averaging 73.465 Year Old from Dec 1990 (Median) to 12-01-2020, with 4 observations. The data reached an all-time high of 77.960 Year Old in 12-01-2020 and a record low of 69.480 Year Old in 12-01-1990. Life Expectancy: Anhui 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.

The average number of additional years a man or woman aged 75 can be expected to live if they continue to live in the same place and the death rates in their area remain the same for the rest of their life. To ensure that the NHS is held to account for doing all that it can to prevent avoidable deaths in older people. This indicator captures all persons aged 75 and over. A correction was made to this indicator on the 6th March 2019 due to errors found in the data. The confidence intervals for females in the region breakdown for the 2015-17 time period were displayed the wrong way round and some of the upper intervals were rounded incorrectly. These have now been corrected. A further correction was made to this indicator on the 21st May 2020. For 2015-17, The population numbers presented within the local authority (LA) breakdown for females were found to be incorrect for three LAs. The affected LAs were Redcar and Cleveland (E06000003), Norwich (E07000148) and Redbridge (E09000026). These have now been corrected. The indicator value and confidence intervals for all three LAs were unaffected by the error. Legacy unique identifier: P01728