Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<ul style='margin-top:20px;'>
<li>U.S. life expectancy for 2024 was <strong>79.25</strong>, a <strong>1.11% increase</strong> from 2023.</li>
<li>U.S. life expectancy for 2023 was <strong>78.39</strong>, a <strong>1.23% increase</strong> from 2022.</li>
<li>U.S. life expectancy for 2022 was <strong>77.43</strong>, a <strong>1.45% 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.
In 2021, women had an average life expectancy of ** years at birth, while men were expected to live 68.9 years. The average life expectancy worldwide dropped from 2019 to 2021, primarily due to the COVID-19 pandemic. This statistic depicts the average life expectancy at birth worldwide in 1990, 2019, and 2021, by gender.
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).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<ul style='margin-top:20px;'>
<li>World life expectancy for 2024 was <strong>73.33</strong>, a <strong>0% increase</strong> from 2023.</li>
<li>World life expectancy for 2023 was <strong>73.33</strong>, a <strong>0.49% increase</strong> from 2022.</li>
<li>World life expectancy for 2022 was <strong>72.97</strong>, a <strong>2.46% 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<ul style='margin-top:20px;'>
<li>Thailand life expectancy for 2024 was <strong>77.92</strong>, a <strong>1.97% increase</strong> from 2023.</li>
<li>Thailand life expectancy for 2023 was <strong>76.41</strong>, a <strong>1.49% increase</strong> from 2022.</li>
<li>Thailand life expectancy for 2022 was <strong>75.29</strong>, a <strong>2.98% decline</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.
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
This table contains 2754 series, with data for years 2005/2007 - 2012/2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (153 items: Canada; Newfoundland and Labrador; Eastern Regional Integrated Health Authority, Newfoundland and Labrador; Central Regional Integrated Health Authority, Newfoundland and Labrador; ...); Age group (2 items: At birth; At age 65); Sex (3 items: Both sexes; Males; Females); Characteristics (3 items: Life expectancy; Low 95% confidence interval, life expectancy; High 95% confidence interval, life expectancy).
This comparison statistic shows the difference in life expectancy of household appliances in 2011 and 2022 in the United States. The life expectancy of all household appliances has either stayed the same or declined in the last decade.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<ul style='margin-top:20px;'>
<li>U.K. life expectancy for 2024 was <strong>81.92</strong>, a <strong>0.83% increase</strong> from 2023.</li>
<li>U.K. life expectancy for 2023 was <strong>81.24</strong>, a <strong>0.28% increase</strong> from 2022.</li>
<li>U.K. life expectancy for 2022 was <strong>81.01</strong>, a <strong>0.45% 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
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.
Average expected useful life of municipally owned culture, recreation and sport facilities for all provinces and territories, by urban and rural and population size. Average expected useful life values are presented in years.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The average for 2022 based on 47 countries was 74.51 years. The highest value was in Macao: 85.38 years and the lowest value was in Afghanistan: 62.88 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Georgia: Life expectancy, in years, male: The latest value from 2022 is 66.76 years, a decline from 66.8 years in 2021. In comparison, the world average is 69.65 years, based on data from 192 countries. Historically, the average for Georgia from 1960 to 2022 is 63.85 years. The minimum value, 57.13 years, was reached in 1960 while the maximum of 68.84 years was recorded in 2017.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Macau SAR Average Life Expectancy at Birth: Male data was reported at 80.600 Year in 2018. This records an increase from the previous number of 80.300 Year for 2017. Macau SAR Average Life Expectancy at Birth: Male data is updated yearly, averaging 78.900 Year from Dec 1996 (Median) to 2018, with 23 observations. The data reached an all-time high of 80.600 Year in 2018 and a record low of 75.100 Year in 1996. Macau SAR Average Life Expectancy at Birth: Male data remains active status in CEIC and is reported by Statistics and Census Service. The data is categorized under Global Database’s Macau SAR – Table MO.G005: Life Expectancy at Birth.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The dataset contains information on various demographic and health indicators for different countries. It is organized into several columns, each providing essential information about these countries. Here's a description of each column:
1. Country: This column represents the names of different countries or regions included in the dataset. Each row corresponds to a specific country or region, and this column serves as the identifier for each entry.
2. Life Expectancy Males: This column contains data on the average life expectancy of males in each of the listed countries. Life expectancy is a crucial health indicator and provides an estimate of the average number of years a male can expect to live, given current mortality rates and health conditions.
3. Life Expectancy Females: Similar to the "Life Expectancy Males" column, this column provides data on the average life expectancy of females in the same countries. It reflects the average number of years a female can expect to live, considering the prevailing health and mortality conditions.
4. Birth Rate: The "Birth Rate" column contains information about the birth rate in each country. Birth rate is a demographic indicator that represents the number of live births per 1,000 people in a given population over a specific period, usually a year. It can provide insights into a country's population growth or decline.
5. Death Rate: This column presents data on the death rate in each of the listed countries. The death rate is another crucial demographic indicator and represents the number of deaths per 1,000 people in a population over a specific period, often a year. It helps gauge the overall health and mortality conditions within a country.
Life expectancy at birth and at age 65, by sex, on a three-year average basis.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
<ul style='margin-top:20px;'>
<li>U.S. life expectancy for 2024 was <strong>79.25</strong>, a <strong>1.11% increase</strong> from 2023.</li>
<li>U.S. life expectancy for 2023 was <strong>78.39</strong>, a <strong>1.23% increase</strong> from 2022.</li>
<li>U.S. life expectancy for 2022 was <strong>77.43</strong>, a <strong>1.45% 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.