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.

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.

Monaco had the highest life expectancy among both men and women worldwide as of 2024. That year, life expectancy for men and women was ** and ** years, respectively. The East Asian countries and regions, Hong Kong, Japan, South Korea, and Macao, followed. Many of the countries on the list are struggling with aging populations and a declining workforce as more people enter retirement age compared to people entering employment.

The average for 2022 based on 192 countries was 74.94 years. The highest value was in Macao: 87.98 years and the lowest value was in Nigeria: 53.97 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Life Expectancy of the World Population

The dataset from Worldometer provides a ranked list of countries based on life expectancy at birth, which represents the average number of years a newborn is expected to live under current mortality rates. It includes global, regional, and country-specific life expectancy figures, with separate data for males and females. The dataset highlights disparities in longevity across nations, with countries like Hong Kong, Japan, and South Korea having the highest life expectancies. This data serves as a key indicator of public health, quality of life, and healthcare effectiveness, offering valuable insights for policymakers, researchers, and global health organizations.

Data Analysis & Machine Learning Approaches for Life Expectancy Data

Data Analysis Approaches Life expectancy data can be analyzed using descriptive statistics (mean, variance, distribution) and correlation analysis to identify relationships with factors like GDP, healthcare, and education. Time series analysis helps track longevity trends over time, while clustering techniques (e.g., K-Means) group countries with similar patterns. Additionally, geospatial analysis can visualize regional disparities in life expectancy.

Machine Learning Models For prediction, linear and multiple regression models estimate life expectancy based on socioeconomic indicators, while polynomial regression captures non-linear trends. Decision trees and Random Forests classify countries into high- and low-life expectancy groups. Deep learning techniques like neural networks (ANNs) can model complex relationships, while LSTMs are useful for time-series forecasting.

For pattern detection, K-Means clustering groups countries based on life expectancy trends, and DBSCAN identifies anomalies. Principal Component Analysis (PCA) helps in feature selection, improving model efficiency. These methods provide insights into longevity trends, helping policymakers and researchers improve public health strategies.

Life expectancy at birth. Data based on the latest United Nations Population Division estimates.

Source: https://www.worldometers.info/demographics/life-expectancy/#countries-ranked-by-life-expectancy

The countries with the lowest life expectancy worldwide include the Nigeria, Chad, and Lesotho. As of 2023, people born in Nigeria could be expected to live only up to ** years. This is almost ** years shorter than the global life expectancy. Life expectancy The global life expectancy has gradually increased over the past couple decades, rising from **** years in 2011 to **** years in 2023. However, the years 2020 and 2021 saw a decrease in global life expectancy due to the COVID-19 pandemic. Furthermore, life expectancy can vary greatly depending on the country and region. For example, all the top 20 countries with the lowest life expectancy worldwide are in Africa. The countries with the highest life expectancy include Liechtenstein, Switzerland, and Japan. Causes of death The countries with the lowest life expectancy worldwide are all low-income or developing countries that lack health care access and treatment that more developed countries can provide. The leading causes of death in these countries therefore differ from those of middle-income and upper-income countries. The leading causes of death in low-income countries include diseases such as HIV/AIDS and malaria, as well as preterm birth complications, which do not cause substantial death in higher income countries.

The average for 2023 based on 47 countries was 75.46 years. The highest value was in Hong Kong: 85.25 years and the lowest value was in Palestine: 65.17 years. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Life Expectancy at Birth, Total for Low Income Countries (SPDYNLE00INLIC) from 1960 to 2023 about life expectancy, life, birth, and income.

Countries where people live for a long time, as a rule, provide their citizens with high-quality medical care and help them lead a healthy lifestyle. On the contrary, in countries with low life expectancy, there are usually economic difficulties, poverty and lack of access to health services.

The average for 2023 based on 7 countries was 81.78 years. The highest value was in Japan: 84.04 years and the lowest value was in the USA: 78.39 years. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Credits

This dataset was from tekkum and the original file was in xlsx format.

Context

While numerous studies have explored the factors influencing life expectancy, most have focused on demographic variables, economic indicators, and mortality rates. However, there has been limited examination of the impact of immunization coverage, health expenditures, and educational attainment on life expectancy. This study seeks to address these gaps by developing a comprehensive dataset with no missing values analyses, utilizing data from many years across 193 different countries. Key immunizations such as Hepatitis B, Polio, and Diphtheria, along with factors like GDP, schooling, and health expenditure, are included in this dataset. This approach aims to identify the most significant predictors of life expectancy, allowing countries to prioritize interventions that could most effectively improve the health and longevity of their populations.

Dataset

The success of this analysis relies heavily on the accuracy and completeness of the data. The dataset used in this project has been sourced from the Global Health Observatory (GHO) data repository of the World Health Organization (WHO), which tracks health metrics and related factors for countries worldwide. The corresponding economic data was obtained from the United Nations. From the broad range of health-related variables available, this study focuses on those that are most representative and critical to understanding life expectancy. The dataset includes data for 193 countries and has been meticulously merged into a single file containing 22 columns and 2,938 rows, representing 20 predictive variables. The variables were categorized into four main groups: Immunization-related factors, Mortality factors, Economic factors, and Social factors. Countries with a lot of missing values were excluded, and some values were generated by Bayesian Ridge.

Question

This dataset aims to answer the following key questions:

1. Do the selected predictive factors significantly impact life expectancy, and which variables are the most influential?

2. Should countries with a lower life expectancy (below 65 years) increase healthcare expenditure to improve their population's lifespan?

3. How do infant and adult mortality rates influence life expectancy across different regions?

4. What is the relationship between life expectancy and lifestyle factors such as alcohol consumption?

5. How does educational attainment, as measured by years of schooling, affect human lifespan?

6. Is there a positive or negative correlation between alcohol consumption and life expectancy?

7. What is the impact of immunization coverage on life expectancy, particularly regarding diseases like Hepatitis B, Polio, and Diphtheria?

This statistic shows the top ten countries worldwide with longest average female life expectancy at birth in 2010 and 2030. South Korea had the longest average life expectancy for females in 2030 at ***** years.

This statistic shows the top ten countries worldwide with the longest average male life expectancy at birth in 2010 and 2030. South Korea had an average male life expectancy in 2030 of ***** years.

This horizontal bar chart displays life expectancy at birth (year) by countries using the aggregation average, weighted by population. The data is about countries.

The average for 2022 based on 47 countries was 71.89 years. The highest value was in Macao: 82.75 years and the lowest value was in Afghanistan: 59.77 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Singapore had the highest life expectancy at birth of all the Southeast Asian countries in 2023, with its citizens expected to live to an average of **** years. Falling behind by almost 20 years was Myanmar, with a life expectancy of **** years old at birth as of 2023. Interestingly, Singapore made the top ten of countries with the highest average life expectancy worldwide. Increasing life expectancyLife expectancy throughout the Southeast Asian region has been rising throughout recent years, likely due to improved healthcare systems. Improvements brought about by increasing healthcare expenditures. The East Asian region also joined Southeast Asia in displaying higher life expectancies at birth, with Hong Kong and Macao all exhibiting life expectancies at birth of over 85 years old. Improved healthcare Thailand, the Philippines and Singapore are just some of the Southeast Asian governments which have released successful universal healthcare plans. As the region faces an aging population, there has been more demand for effective healthcare. Healthcare has been improving not just in the Southeast Asian region but throughout the whole Asia Pacific region, with many countries exhibiting near perfect child immunization rates, offering its citizens better healthcare from birth. With these improvements made, it does not seem surprising that life expectancy at birth has increased.

Context

Life Expectancy is a statistical measure of the average time an organism is expected to live, based on the year of its birth, current age and other demographic factors like sex. The most commonly used measure is life expectancy at birth (LEB), which can be defined in two ways. Cohort LEB is the mean length of life of a birth cohort (all individuals born in a given year) and can be computed only for cohorts born so long ago that all their members have died. Period LEB is the mean length of life of a hypothetical cohort assumed to be exposed, from birth through death, to the mortality rates observed at a given year.

Content

There is one dataset here.

global life expectancy dataset.csv

• Country Name : Name of the country
• Country Code : ISO-3 code of the name of the country
• Year[1960 - Present] : Life expectancy values in year

Acknowledgement

These datas are collected from The World Bank DataBank.

Introduction

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. It is a key metric for assessing population health.

Life expectancy has burgeoned since the advent of industrialization in the early 1900s and the world average has now more than doubled to 70 years. Yet, we still see inequality in life expectancy across and within countries. The study by Acemoglu and Johnson demonstrated the relationship between increased life expectancy and improvement in economic growth (GDP per capita), controlling for country-fixed effects [3]. In the table below, we have shown how life expectancy varies between high-income and low-income countries. However, further analysis is necessary to determine how the allocation of a country’s wealth through certain investments in healthcare, education, environmental management, and some socioeconomic factors have an overall effect in determining average life expectancy.

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The Sub-Saharan African region experiences the lowest life expectancy at birth compared to other regions over the past 3 decades. SSA countries have consistently ranked as the lowest-earning countries in terms of GDP per capita. Therefore, there is a huge scope for improvement in life expectancy in SSA countries and hence our research focuses on the 40 Sub-Saharan African (SSA) countries with the lowest GDP per capita

Research Questions

After reviewing the rich existing literature on Life Expectancy, we realized the lack of concrete research on understanding the impact of all-encompassing determinants that cover socio-economic and environmental factors for SSA countries using Panel Data techniques. Hence, we tried to address this inadequacy through our research. In this paper, we aim to have a better understanding of factors affecting life expectancy in the SSA region for an efficient policy-making process and better allocation of funds and resources in addressing the prevalence of low life expectancy in Sub-Saharan Africa. To achieve that we attempt to answer the following questions in this research:

1. What’s the Impact of Expenditure on Health and Education (% of GDP) on Life Expectancy?
2. How does the prevalence of undernourishment and communicable disease Affect Life Expectancy?
3. Do factors like corruption and unemployment rate impact life expectancy? If yes, quantify
4. Increase in CO2 emissions decrease life expectancy? Is it significant?

Data

Main sources of data - World Bank Open Data & Our World in Data

1. Country - 174 countries - list

2. Country Code - 3-letter code

3. Region - region of the world country is located in

4. IncomeGroup - country's income class

5. Year - 2000-2019 (both included)

6. Life expectancy - data

7. Prevalence of Undernourishment (% of the population) - Prevalence of undernourishment is the percentage of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normally active and healthy life

8. Carbon dioxide emissions (kiloton) - Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during the consumption of solid, liquid, and gas fuels and gas flaring

9. Health Expenditure (% of GDP) - Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT, and stocks of vaccines for emergencies or outbreaks

10. Education Expenditure (% of GDP) - General government expenditure on education (current, capital, and transfers) is expressed as a percentage of GDP. It includes expenditures funded by transfers from international sources to the government. General government usually refers to local, regional, and central governments.

11. Unemployment (% total labor force) - Unemployment refers to the % share of the labor force that is without work but available for and seeking employment

12. Corruption (CPIA rating) - Transparency, accountability, and corruption in the public sector assets the extent to which the executive can be held accountable for its use of funds and for the results of its actions by the electorate and by the legislature and judiciary, and the extent to which public employees within the executive are required to...

This horizontal bar chart displays life expectancy at birth (year) by country full name using the aggregation average, weighted by population in Micronesia. The data is about countries.

Life Expectancy at Birth, Total for Developing Countries in Europe and Central Asia was 74.79987 Number of Years in January of 2023, according to the United States Federal Reserve. Historically, Life Expectancy at Birth, Total for Developing Countries in Europe and Central Asia reached a record high of 74.79987 in January of 2023 and a record low of 54.67285 in January of 1950. Trading Economics provides the current actual value, an historical data chart and related indicators for Life Expectancy at Birth, Total for Developing Countries in Europe and Central Asia - last updated from the United States Federal Reserve on November of 2025.