This statistic shows average life expectancy at birth in Sub-Saharan Africa from 2013 to 2023. Sub-Saharan Africa includes almost all countries south of the Sahara desert. In 2023, the average life expectancy at birth in Sub-Saharan Africa was 62.6 years.

Graph and download economic data for Life Expectancy at Birth, Total: All Income Levels for Sub-Saharan Africa (SPDYNLE00INSSF) from 1960 to 2023 about Sub-Saharan Africa, life expectancy, life, birth, and income.

Tunisia had the highest projected life expectancy at birth in Africa as of 2025. A newborn infant was expected to live about 77 years in the country. Algeria, Cabo Verde, Morocco, and Mauritius followed, with a life expectancy between 77 and 75 years. On the other hand, Nigeria registered the lowest average, at 54.8 years. Overall, the life expectancy in Africa was just over 64 years in the same year.

Historical dataset showing Sub-Saharan Africa life expectancy by year from 1950 to 2025.

The average for 2022 based on 47 countries was 64.57 years. The highest value was in Cape Verde: 79.01 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.

For those born in 2024, the average life expectancy at birth across Africa was 62 years for men and 66 years for women. The average life expectancy globally was 71 years for men and 76 years for women in mid-2024. Additional information on life expectancy in Africa With the exception of North Africa where life expectancy is around the worldwide average for men and women, life expectancy across all African regions paints a negative picture. Comparison of life expectancy by continent shows the gap in average life expectancy between Africa and other continents. Africa trails Asia, the continent with the second lowest average life expectancy, by 10 years for men and 11 years for women. Life expectancy in Africa is the lowest globally Moreover, countries from across the African regions dominate the list of countries with the lowest life expectancy worldwide. Nigeria and Chad had the lowest life expectancy for those born in 2024 for women and men, respectively. However, there is reason for hope despite the low life expectancy rates in many African countries. The Human Development index rating in Sub-Saharan Africa has increased significantly from nearly 0.44 to 0.57 between 2000 and 2023, demonstrating an improvement in quality of life and, as a result, greater access to vital services that allow people to live longer lives. One such improvement has been successful efforts to reduce the rate of aids infection and research into combating its effects. The number of new HIV infections across sub-Saharan Africa has decreased from over 1.3 million in 2015 to close to 650,000 in 2024. However, the sub-region still accounts for 50 percent of the total new HIV infections.

Life expectancy from birth in Africa was just over 37 years in 1950. As a wave of independence movements and decolonization swept the continent between the 1950s and early 1970s, life expectancy rose greatly in Africa; particularly due to improvements and control over medical services, better sanitation and the widespread promotion of vaccinations in the continent resulted in a sharp decrease in child mortality; one of the most significant reasons for Africa’s low life expectancy rates. Life expectancy in the continent would continue to steadily increase for much of the second half of the 20th century; however, life expectancy would slow down in the latter half of the 1980s, as the HIV/AIDS epidemic quickly grew to become one of the leading causes of death in the continent. After hovering around the low-fifties in the 1980s to and 1990s, life expectancy would begin to rise again at the turn of the millennium, and is estimated to be over 64 years in 2023.

United States - Life Expectancy at Birth, Total for Developing Countries in Sub-Saharan Africa was 62.60174 Number of Years in January of 2023, according to the United States Federal Reserve. Historically, United States - Life Expectancy at Birth, Total for Developing Countries in Sub-Saharan Africa reached a record high of 62.60174 in January of 2023 and a record low of 36.17255 in January of 1950. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Life Expectancy at Birth, Total for Developing Countries in Sub-Saharan Africa - last updated from the United States Federal Reserve on November of 2025.

The average for 2022 based on 47 countries was 60.12 years. The highest value was in the Seychelles: 71.8 years and the lowest value was in Lesotho: 50.32 years. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

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...

For most of the world, throughout most of human history, the average life expectancy from birth was around 24. This figure fluctuated greatly depending on the time or region, and was higher than 24 in most individual years, but factors such as pandemics, famines, and conflicts caused regular spikes in mortality and reduced life expectancy. Child mortality The most significant difference between historical mortality rates and modern figures is that child and infant mortality was so high in pre-industrial times; before the introduction of vaccination, water treatment, and other medical knowledge or technologies, women would have around seven children throughout their lifetime, but around half of these would not make it to adulthood. Accurate, historical figures for infant mortality are difficult to ascertain, as it was so prevalent, it took place in the home, and was rarely recorded in censuses; however, figures from this source suggest that the rate was around 300 deaths per 1,000 live births in some years, meaning that almost one in three infants did not make it to their first birthday in certain periods. For those who survived to adolescence, they could expect to live into their forties or fifties on average. Modern figures It was not until the eradication of plague and improvements in housing and infrastructure in recent centuries where life expectancy began to rise in some parts of Europe, before industrialization and medical advances led to the onset of the demographic transition across the world. Today, global life expectancy from birth is roughly three times higher than in pre-industrial times, at almost 73 years. It is higher still in more demographically and economically developed countries; life expectancy is over 82 years in the three European countries shown, and over 84 in Japan. For the least developed countries, mostly found in Sub-Saharan Africa, life expectancy from birth can be as low as 53 years.

Context

Life expectancy at birth is a key metric reflecting the average number of years a person can expect to live from birth, considering current mortality rates. Across the globe, life expectancy varies widely due to factors such as healthcare access, socio-economic conditions, and lifestyle choices. Developed nations often boast higher life expectancies, typically ranging from 75 to 85 years, owing to advanced healthcare systems and improved living standards. In contrast, developing nations often face shorter life expectancies, frequently falling below 70 years, largely due to inadequate healthcare infrastructure and prevailing socio-economic challenges. These disparities underscore the critical importance of global efforts to enhance healthcare access and address socio-economic inequalities.

Content

This dataset comprises historical information encompassing various indicators concerning Life Expectancy at Birth on a global scale. The dataset prominently features: ISO3, Country, Continent, Hemisphere, Human Development Groups, UNDP Developing Regions, HDI Rank (2021), and Life Expectancy at Birth from 1990 to 2021.

Dataset Glossary (Column-wise)

• ISO3 - ISO3 for the Country/Territory
• Country - Name of the Country/Territory
• Continent - Name of the Continent
• Hemisphere - Name of the Hemisphere
• Human Development Groups - Human Development Groups
• UNDP Developing Regions - UNDP Developing Regions
• HDI Rank (2021) - Human Development Index Rank for 2021
• Life Expectancy at Birth from 1990 - 2021 - Life Expectancy at Birth from year 1990 to 2021 (32 Columns.)

Data Dictionary

• UNDP Developing Regions:
  • SSA - Sub-Saharan Africa
  • LAC - Latin America and the Caribbean
  • EAP - East Asia and the Pacific
  • AS - Arab States
  • ECA - Europe and Central Asia
  • SA - South Asia

Structure of the Dataset

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Acknowledgement

This Dataset is created from Human Development Reports. This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

Cover Photo by: Image by Freepik

Thumbnail by: Image by Quality of life icons created by Paul J. - Flaticon

Additional file 3.

lep Life expectancy at birth, total (years) lepf Life expectancy at birth, female (years) lepm Life expectancy at birth, male (years) mmat Maternal mortality ratio (modeled estimate, per 100,000 live births) minf Mortality rate, infant (per 1,000 live births) mun5 Mortality rate, under-5 (per 1,000 live births) hep Current health expenditure per capita, PPP (current international $) ghep Domestic general government health expenditure per capita, PPP (current international $) phep Domestic private health expenditure per capita, PPP (current international $) hout Health outcomes co2 Carbon emission kt per capita ecft Ecological footprint ccn Control of Corruption: Estimate ge Government Effectiveness: Estimate rqv Regulatory Quality: Estimate insq Institutional Quality

Female life expectancy is forecast to increase in every world region from 2023 to 2050, underlining the challenges of an aging population in several countries. Australia and New Zealand were forecast to have the highest female life expectancy at birth in 2050, reaching **** years. On the other hand, Sub-Saharan Africa was forecast to have the lowest, below 70 years.

Background: For decades, health targeted aid in the form of development assistance for health has been an important source of financing health sectors in developing countries. Health sectors in Sub Saharan countries in general and Ethiopia in particular, are even more heavily reliant upon donors. Consequently, a more audible donors support to health sectors was seen during the last four decades, consistent with the donor's response to the global goal of Alma-Ata declaration of "health for all by the year 2000" through primary health care in 1978. Ever since, a massive surge of development assistance for health has followed the out gone of the 2015 United Nations Millennium Declaration Goals in which three out of the eight goals were directly related to health. In spite of the long history of health targeted aid, with an ever increasing volumes, there is an increasing controversy on the extent to which health targeted aid is producing the intended health outcomes in the recipient countries. Despite the vast empirical literatures considering the effect of foreign development aid on economic growth of the recipient countries, systematic evidence that health sector targeted aid improves health outcomes is relatively scarce. The main contribution of this study is, therefore, to present a comprehensive country level, and cross-country evidences on the effect of development assistance for health on health outcomes. Objectives: The overall objective of this study was to analyze the effect of development assistance for health on health outcomes in Ethiopia, and in Sub Saharan Africa. Methods: For the Ethiopian (country level) study, a dynamic time series data analytic approach was employed. A retrospective sample of 36-year observations from 1978 to 2013 was analyzed using an econometric technique - vector error correction model. Beside including time dependency between the variables of interest and allowing for stochastic trends, the model provides valuable information on the existence of long-run and short-run relationships among the variables under study. Furthermore, to estimate the co-integrating relations and the other parameters in the model, the standard procedure of Johansen's approach was used. While development assistance for health expenditure was used as an explanatory variable of interest, life expectancy at birth was used as a dependent variable for the fact that it has long been used with or without mortality measures as health status indicators in the literatures.In the Sub Saharan Africa (cross-country level) study, a dynamic panel data analytic approach was employed using fixed effect, random effect, and the first difference-generalized method of moments estimators in the period confined to the year 1995-2013 over the cross section of 43 SSA countries. While development assistance for health expenditure was used as an explanatory variable of interest here again, infant mortality rate was used for health status measure done for its advantage over other mortality measures in cross-country studies. Results: In Ethiopia, the immediate one and two prior year of development assistance for health was shown to have a significant positive effect on life expectancy at birth. Other things being equal, an increase of development assistance for health expenditure per capita by 1% leads to an improvement in life expectancy at birth by about 0.026 years (P=0.000) in the immediate year following the period, and 0.008 years following the immediate prior two years period (P= 0.025). Similarly, in Sub-Saharan Africa, development assistance for health was found to have a strong negative effect on the reduction of infant mortality rate. The estimates of the study result indicated that during the covered period of study, in the region, a 1% increase in development assistance for health expenditure, which is far less than 10 cents per capita at the mean level, saves the life of two infants per 1000 live births (P=0.000). Conclusion: Contrary to the views of health aid skeptics, this study indicates strong favorable effect of development assistance for health sector in improving health status of people in Sub Saharan Africa in general and the Ethiopia in particular. Recommendations: The policy implication of the current findings is that development assistance for health sector should continue as an interim necessity means. However, domestic health financing system should also be sought, as the targeted countries cannot rely upon external resources continuously for improving the health status of the population. At the same time, the current development assistance stakeholders assumption of targeting facility based primary health care provision should be augmented by a more strong parallel strategy of improving socioeconomic status of the population that promotes sustainable improvement of health status in the targeted countries.

BackgroundEpilepsy is a major public health issue worldwide, often leading to physical and cognitive impairments that limit employment, independence, and social interaction. Health-related quality of life (HRQoL) is a crucial outcome in the treatment of chronic epilepsy as it is linked to reduced independence, treatment challenges, and lower life expectancy. HRQoL serves as an important health indicator for assessing the impact of the disease on daily living activities.ObjectiveThis study aimed to estimate the mean score of health-related quality of life (HRQoL) and factors associated with lower HRQoL in people living with epilepsy (PLWE) in sub-Saharan African (SSA) countries.MethodsA comprehensive literature search was conducted using PubMed, Cochrane Library, Scopus, and Google Scholar databases. This review has been registered with PROSPERO (CRD42024620363). The eligibility criteria were established, and this review included cross-sectional and observational studies assessing HRQOL in PLWE in SSA countries, published in English from the inception of databases through November 2024. The pooled HRQoL was reported as the mean score with accompanying 95% confidence intervals. Finally, publication bias was evaluated using a funnel plot and Egger’s regression test.ResultsThe pooled mean score of HRQoL among PLWE in SSA was 63.79 (95% CI: 59.75–67.84%). Owing to significant heterogeneity across the studies, a random-effects model was utilized for the meta-analysis (I2 = 98.96%, p 

In 2023, there were around 211 million children aged 0-4 years in Africa. In total, the population aged 17 years and younger amounted to approximately 680 million. In contrast, only approximately 52 million individuals were aged 65 years and older as of the same year. The youngest continent in the world Africa is the continent with the youngest population worldwide. As of 2024, around 40 percent of the population in Sub-Saharan Africa was aged 15 years and younger, compared to a global average of 25 percent. Although the median age on the continent has been increasing annually, it remains low at around 20 years. There are several reasons behind the low median age. One factor is the low life expectancy at birth: On average, the male and female populations in Africa live between 61 and 65 years, respectively. In addition, poor healthcare on the continent leads to high mortality, also among children and newborns, while the high fertility rate contributes to lowering the median age. Cross-country demographic differences Africa’s demographic characteristics are not uniform across the continent. The age structure of the population differs significantly from one country to another. For instance, Niger and Uganda have the lowest median age in Africa, at 15.1 and 16.1 years, respectively. Not surprisingly, these countries also register a high crude birth rate. On the other hand, North Africa is the region recording the highest life expectancy at birth, with Tunisia and Algeria leading the ranking in 2025.

FGLS estimates of the relationship between Carbon, GDPpcap, Life, POP, and Energy in Sub-Saharan Africa, Middle East and North Africa, and Europe and Central Asia.

Context

Life expectancy at birth is defined as the average number of years that a newborn could expect to live if he or she were to pass through life subject to the age-specific mortality rates of a given period. The years are from 1950 to 2018.

Content

For regional- and global-level data pre-1950, data from a study by Riley was used, which draws from over 700 sources to estimate life expectancy at birth from 1800 to 2001.

Riley estimated life expectancy before 1800, which he calls "the pre-health transition period". "Health transitions began in different countries in different periods, as early as the 1770s in Denmark and as late as the 1970s in some countries of sub-Saharan Africa". As such, for the sake of consistency, we have assigned the period before the health transition to the year 1770. "The life expectancy values employed are averages of estimates for the period before the beginning of the transitions for countries within that region. ... This period has presumably the weakest basis, the largest margin of error, and the simplest method of deriving an estimate."

For country-level data pre-1950, Clio Infra's dataset was used, compiled by Zijdeman and Ribeira da Silva (2015).

For country-, regional- and global-level data post-1950, data published by the United Nations Population Division was used, since they are updated every year. This is possible because Riley writes that "for 1950-2001, I have drawn life expectancy estimates chiefly from various sources provided by the United Nations, the World Bank’s World Development Indicators, and the Human Mortality Database".

For the Americas from 1950-2015, the population-weighted average of Northern America and Latin America and the Caribbean was taken, using UN Population Division estimates of population size.

Acknowledgements

Life expectancy:

Data publisher's source: https://www.lifetable.de/RileyBib.pdf Data published by: James C. Riley (2005) – Estimates of Regional and Global Life Expectancy, 1800–2001. Issue Population and Development Review. Population and Development Review. Volume 31, Issue 3, pages 537–543, September 2005., Zijdeman, Richard; Ribeira da Silva, Filipa, 2015, "Life Expectancy at Birth (Total)", http://hdl.handle.net/10622/LKYT53, IISH Dataverse, V1, and UN Population Division (2019) Link: https://datasets.socialhistory.org/dataset.xhtml?persistentId=hdl:10622/LKYT53, http://onlinelibrary.wiley.com/doi/10.1111/j.1728-4457.2005.00083.x/epdf, https://population.un.org/wpp/Download/Standard/Population/ Dataset: https://ourworldindata.org/life-expectancy

GDP per capita:

Data publisher's source: The Maddison Project Database is based on the work of many researchers that have produced estimates of economic growth for individual countries. Data published by: Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update”. Link: https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 Dataset: https://ourworldindata.org/life-expectancy

Inspiration

The life expectancy vs GDP per capita analysis.