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 84.2 years. Around the world, females consistently have a higher average life expectancy than males, with females in Europe expected to live an average of six years longer than males on this continent. Increases in life expectancy The overall average life expectancy in OECD countries increased by 11.3 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 53 years. Life expectancy in the U.S. The life expectancy in the United States was 77.43 years as of 2022. 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 2023, the average life expectancy of the world was 70 years for men and 75 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 standard 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 2021, the countries with the highest life expectancy were Japan, Liechtenstein, Switzerland, and South Korea, all at 84 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 years.

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.

This layer contains population counts and 10 indicators of global population and maternal health by country. Layer is rendered to show the percent of married women ages 15-49 using any contraception. Data is from Population Reference Bureau's 2017 World Population Data Sheet or from their DataFinder site. Fields included are:Population, mid-2017 (reported in millions)Percent of Population Ages <15Percent of Population Ages 65+Male Life Expectancy at BirthFemale Life Expectancy at BirthTotal Fertility Rate: Children per WomanInfant Mortality Rate: Infant Deaths per 1,000 BirthsMaternal Mortality Rate: Maternal Deaths per 100,000 Births (from DataFinder, data from 2013)% Births Attended by Skilled Health Personnel (from DataFinder, year of most recent data available is different for each country, oldest is 2011)% Married Women Ages 15-49 Using Modern Contraception*% Married Women Ages 15-49 Using Any Contraception**Null values indicate that data is not available.*Modern methods include anything that requires supplies or trips to a clinic: condom, pill, injection, IUD, sterilization, etc.**Any method includes modern methods as well as abstinence, fertility awareness/cycle beads, withdrawal, and any other methods that do not require supplies or clinics.For detailed definitions, sources, and footnotes, see page 20 of PRB's 2017 World Population Data Sheet and PRB's DataFinder site.

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

The World Development Indicators from the World Bank contain over a thousand annual indicators of economic development from hundreds of countries around the world.

Here's a list of the available indicators along with a list of the available countries.

For example, this data includes the life expectancy at birth from many countries around the world:

The dataset hosted here is a slightly transformed verion of the raw files available here to facilitate analytics.

Algeria had the highest life expectancy at birth in Africa as of 2023. A newborn infant was expected to live over 77 years in the country. Cabo Verde, Tunisia, and Mauritius followed, with a life expectancy between 77 and 75 years. On the other hand, Chad registered the lowest average, at nearly 54 years. Overall, the life expectancy in Africa was almost 63 years in the same year.

(by Joseph Kerski)This map is for use in the "What is the spatial pattern of demographic variables around the world?" activity in Section 1 of the Going Places with Spatial Analysiscourse. The map contains population characteristics by country for 2013.These data come from the Population Reference Bureau's 2014 World Population Data Sheet.The Population Reference Bureau (PRB) informs people around the world about population, health, and the environment, empowering them to use that information to advance the well-being of current and future generations.PRB analyzes complex demographic data and research to provide the most objective, accurate, and up-to-date population information in a format that is easily understood by advocates, journalists, and decision makers alike.The 2014 year's data sheet has detailed information on 16 population, health, and environment indicators for more than 200 countries. For infant mortality, total fertility rate, and life expectancy, we have included data from 1970 and 2013 to show change over time. This year's special data column is on carbon emissions.For more information about how PRB compiles its data, see: https://www.prb.org/

Explore the patterns of world population in terms of total population, arithmetic density, total fertility rate, natural increase rate, life expectancy, and infant mortality rate. The GeoInquiry activity is available here.Educational standards addressed:APHG: II.A. Analyze the distribution patterns of human populations.APHG: II.B. Understand that populations grow and decline over time and space.This map is part of a Human Geography GeoInquiry activity. Learn more about GeoInquiries.

Belgian National Burden of Disease Study

Estimates of the burden of disease

Causes of death

Our estimates are based on the official causes of death database compiled by Statbel. We first map the ICD-10 codes of the underlying causes of death to the Global Burden of Disease cause list, consisting of 131 unique causes of deaths. Next, we perform a probabilistic redistribution of ill-defined deaths to specific causes, to obtain a specific cause of death for each deceased person.

Years of Life Lost

In addition to counting the number of deaths, we also calculate Years of Life Lost (YLLs) as a measure of premature mortality. YLLs correspond to the life expectancy at the age of death, and therefore give a higher weight to deaths occurring at younger ages. We calculate YLLs using the Global Burden of Disease reference life table, which represents the theoretical maximum number of years that people can expect to live.

Prevalence

Our estimates are based on the GBD cause list for morbidity by IHME. We first select for each of the 38 causes, the most suitable local data source as described in the protocol. Next, we calculate the prevalence by year, region, age, and sex, to obtain a prevalence for each of the included diseases.

Years Lived with Disability

In addition to calculating the number of prevalent cases, we also calculate Years Lived with Disability (YLDs) as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.

Disability-Adjusted Life Years

Disability-Adjusted Life Years (DALYs) are a measure of overall disease burden, representing the healthy life years lost due to morbidity and mortality. DALYs are calculated as the sum of YLLs and YLDs for each of the considered diseases.

ABSTRACT CONTEXT AND OBJECTIVE: Traffic accidents have gained prominence as one of the modern epidemics that plague the world. The objective of this study was to identify the spatial distribution of potential years of life lost (PYLL) due to accidents involving motorcycles in the state of São Paulo, Brazil. DESIGN AND SETTING: Ecological and exploratory study conducted in São Paulo. METHODS: Data on deaths among individuals aged 20-39 years due to motorcycle accidents (V20-V29 in the International Classification of Diseases, 10th revision) in the state of São Paulo in the years 2007-2011 were obtained from DATASUS. These data were stratified into a database for the 63 microregions of this state, according to where the motorcyclist lived. PYLL rates per 100,000 inhabitants were calculated. Spatial autocorrelations were estimated using the Global Moran index (IM). Thematic, Moran and Kernel maps were constructed using PYLL rates for the age groups of 20-29 and 30-39 years. The Terraview 4.2.2 software was used for the analysis. RESULTS: The PYLL rates were 486.9 for the ages of 20-29 years and 199.5 for 30-39 years. Seventeen microregions with high PYLL rates for the age group of 20-29 years were identified. There was higher density of these rates on the Kernel map of the southeastern region (covering the metropolitan region of São Paulo). There were no spatial autocorrelations between rates. CONCLUSIONS: The data presented in this study identified microregions with high accident rates involving motorcycles and microregions that deserve special attention from regional managers and traffic experts.

This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which
counts all residents regardless of legal status or citizenship--except
for refugees not permanently settled in the country of asylum, who are
generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: 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. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which
counts all residents regardless of legal status or citizenship--except
for refugees not permanently settled in the country of asylum, who are
generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: 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. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

地図(マップ)上に20歳女性の平均余命の統計データを都道府県別で色分け表示しています。過去から現在までの20歳女性の平均余命の推移も階級区分図(コロプレスマップ)で変化が見えるよう高速読込で可視化し、どの都道府県が長いかが視覚で理解できます。GeoJsonの無料ダウンロードも可能です。研究や分析レポートにお役立て下さい。

地図(マップ)上に20歳男性の平均余命の統計データを都道府県別で色分け表示しています。過去から現在までの20歳男性の平均余命の推移も階級区分図(コロプレスマップ)で変化が見えるよう高速読込で可視化し、どの都道府県が長いかが視覚で理解できます。GeoJsonの無料ダウンロードも可能です。研究や分析レポートにお役立て下さい。

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

地図(マップ)上に65歳女性の平均余命の統計データを都道府県別で色分け表示しています。過去から現在までの65歳女性の平均余命の推移も階級区分図(コロプレスマップ)で変化が見えるよう高速読込で可視化し、どの都道府県が長いかが視覚で理解できます。GeoJsonの無料ダウンロードも可能です。研究や分析レポートにお役立て下さい。

The population of Italy is getting older every year, becoming one of the oldest ones in the world. In 2024, the average age of the Italian population was 46.6 years, 3.2 years more than the average age registered in 2010. However, the age differs significantly depending on the region. According to the most recent data for 2024, the “oldest” citizens of the Italian peninsula live in the region of Liguria (average age 49.5 years), whereas the youngest inhabit Campania (44.2 years on average). Women live longer than men The difference in the average age of the population can be observed not only on a regional basis, but also between genders. In 2021, Italian women were on average roughly three years older than men. When it comes to the life expectancy, studies from 2023 confirm the longevity of Italian women. In fact, females in Italy are expected to live on average about four years longer than men. The Old Continent In 2023, Europe was the continent with the highest share of population older than 65 years. Whereas the worldwide percentage of the population over 65 years was of ten percent, the percentage of elderly people in the Old Continent reached 19 percent.