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

This statistic depicts the average life expectancy at the age of 60 worldwide in 1990 and 2013, by income group. In 2013, a person aged 60 from a high income household had a life expectancy of 23 more years, while a person of the same age from a low income household was expected to live 17 more years.

Age-Adjusted Death Rates

Death Rates and Life Expectancy in the United States, 2011-2013

By Health [source]

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How to use the dataset

In order to use this dataset, start by selecting a particular set of variables to investigate. You can choose from Measure Names (e.g., Death Rates or Life Expectancy), Race (e.g., All Races), Sex (Male/Female) and Year (2011-2013). Once you have selected your desired variables, you can begin analyzing the data by looking at mortality rates and life expectancy averages amongst different populations in the United States over time.

You may also wish to perform more detailed analyses such as identifying trends or examining correlations between features, regional disparities in mortality rates or changes in average life expectancies over time. If so, you can do so by creating line graphs plotted against one or more independent variables such as Race and Sex to see how demographics impact these statistics overall and on a yearly basis using the Year variable computed from July 1st 2010 estimates

Research Ideas

• Analyzing mortality and life expectancy trends among certain races and sexes over time.
• Examining the effects of different socioeconomic factors on death rates and life expectancies.
• Making predictions about future mortality rates and average life expectancies with machine learning algorithms

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: rows.csv | Column name | Description | |:----------------------------|:----------------------------------------------------------------------| | Measure Names | The type of measure being reported. (String) | | Race | The race of the population being reported. (String) | | Sex | The gender of the population being reported. (String) | | Year | The year the data was collected. (Integer) | | Average Life Expectancy | The average life expectancy of the population being reported. (Float) | | Mortality | The mortality rate of the population being reported. (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Health.

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.

Over the last two observations, the life expectancy has significantly increased in all gender groups Comparing the two different gender groups for the year 2023, the 'life expectancy of women at birth' leads the ranking with 78.73 years. Contrastingly, 'life expectancy of men at birth' is ranked last, with 68.04 years. Their difference, compared to life expectancy of women at birth, lies at 10.69 years. Life expectancy at birth refers to the number of years the average newborn is expected to live, providing that mortality patterns at the time of birth do not change thereafter.Find further similar statistics for other countries or regions like Thailand and Brunei.

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.

The life expectancy of women at birth in the United States saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 81.1 years. However, 2023 marked the second consecutive increase of the life expectancy. Life expectancy at birth refers to the number of years that the average newborn can expect to live, providing that mortality patterns at the time of their birth do not change thereafter.Find more statistics on other topics about the United States with key insights such as infant mortality rate, total life expectancy at birth, and total fertility rate.

Life Expectancy at Birth: Mexico City data was reported at 76.325 Year in 2018. This records an increase from the previous number of 76.220 Year for 2017. Life Expectancy at Birth: Mexico City data is updated yearly, averaging 72.400 Year from Dec 1970 (Median) to 2018, with 49 observations. The data reached an all-time high of 76.385 Year in 2013 and a record low of 62.130 Year in 1970. Life Expectancy at Birth: Mexico City data remains active status in CEIC and is reported by National Population Council. The data is categorized under Global Database’s Mexico – Table MX.G006: Life Expectancy at Birth: by State.

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).

On average, women live almost 6 years more than men in France. In 2023, female life expectancy at birth in France reached **** years compared to ** years for males. In 2021, life expectancy in France, regardless of gender, was ***** years. Thus, France is one of the countries in the world with the highest life expectancy. Women outlive men According to the source, there are differences in life expectancy between men and women in France. In 2004, female life expectancy in France was ****, compared to **** years for males. Since then, life expectancy for both genders has been evolving similarly. When life expectancy decreased slightly in 2015, it affected both men and women. Similarly, when life expectancy increased. But one aspect remained the same: male life expectancy remains lower than female life expectancy. This difference has been seen not only in France. In Europe, females are expected to live longer than men in every region. While women in France have a longer life expectancy, they are also expected to have a higher number of healthy life years. In 2013, a study from Eurostat showed that French women had several expected healthy years of ****, compared to ** years for men. An aging population Like other Western countries, France has an aging population. French citizens aged 65 years and older are now more than the French aged from 0 to 14 years old. The median age of the population in the country has been increasing since the nineties, while the share of seniors reached almost ** percent of the population in 2013.

This statistic shows the male average life expectancy at birth in Macao from 2013 to 2023. In 2023, a new born male child in Macao had an average life expectancy of 80.3 years.

In 2023, the total life expectancy at birth in Norway remained nearly unchanged at around 83.11 years. Life expectancy at birth refers to the expected lifespan of the average newborn, providing that mortality patterns at the time of birth in the given region do not change thereafter.Find more statistics on other topics about Norway with key insights such as death rate, infant mortality rate, and total fertility rate.

The average number of years a newborn can expect to live, assuming he or she experiences the currently prevailing rates of death through their lifespan. Source: Baltimore City Health Department Years Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

The average number of years a newborn can expect to live, assuming he or she experiences the currently prevailing rates of death through their lifespan. Source: Baltimore City Health Department Years Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

In 2023, the total life expectancy at birth in Russia remained nearly unchanged at around 73.25 years. Nevertheless, 2023 still represents a peak in the life expectancy at birth in Russia. These figures refer to the expected lifespan of the average newborn in a given country or region, providing that mortality patterns at the time of birth remain constant thereafter.Find more statistics on other topics about Russia with key insights such as infant mortality rate, death rate, and total fertility rate.

Greenland GL: Life Expectancy at Birth: Total data was reported at 71.830 Year in 2013. This records an increase from the previous number of 71.299 Year for 2012. Greenland GL: Life Expectancy at Birth: Total data is updated yearly, averaging 65.783 Year from Dec 1978 (Median) to 2013, with 36 observations. The data reached an all-time high of 71.830 Year in 2013 and a record low of 63.075 Year in 1981. Greenland GL: Life Expectancy at Birth: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Greenland – Table GL.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, or derived from male and female life expectancy at birth from sources such as: (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;

Greenland GL: Life Expectancy at Birth: Male data was reported at 69.650 Year in 2013. This records an increase from the previous number of 69.060 Year for 2012. Greenland GL: Life Expectancy at Birth: Male data is updated yearly, averaging 63.300 Year from Dec 1978 (Median) to 2013, with 36 observations. The data reached an all-time high of 69.650 Year in 2013 and a record low of 59.470 Year in 1981. Greenland GL: 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 Greenland – Table GL.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 number of years a newborn can expect to live, assuming he or she experiences the currently prevailing rates of death through their lifespan. Source: Baltimore City Health Department Years Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018

Romania RO: Life Expectancy at Birth: Male data was reported at 71.500 Year in 2016. This stayed constant from the previous number of 71.500 Year for 2015. Romania RO: Life Expectancy at Birth: Male data is updated yearly, averaging 66.700 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 71.600 Year in 2013 and a record low of 63.860 Year in 1960. Romania RO: 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 Romania – Table RO.World Bank: 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;

Pivot table for healthy life expectancy by sex and area type, divided by three-year intervals starting from 2011 to 2013.