East Africa is one of the fastest urbanizing areas in the whole continent. From 2000 to 2018, urbanization in the region grew by 4.5 percent. Uganda and Burundi had the fastest urban growth rates, at six and 5.7 percent, respectively. In contrast, Djibouti's urban population expanded by 1.6 percent. Even though, the country was still the most urbanized in East Africa, with a share of close to 78 percent of urban population, in 2018.

As of 2023, Eastern Africa was the region with the largest population in Africa, with around *** million inhabitants. On the contrary, Southern Africa was the least populous area and counted approximately ** million people. In 2021, the total population of the African continent exceeded **** billion.

This interactive map presents demographic data for East African countries, showing population size, fertility, mortality, migration rates, and projections up to 2050. By combining statistics with geographic locations, the map helps users explore spatial variations, compare country profiles, and understand future population challenges across the region.

As of 2018, more than 60 million people were living in urban areas in East Africa. Ethiopia was the country with the largest urban residents in the region, in terms of absolute numbers, roughly 23 million. In its turn, in Djibouti, 760 thousand people lived in urban areas by the same period. Even though, the country was the most urbanized in East Africa, with a share of 78 percent of urban population, in 2018.

Around 65 million people are expected to be living in urban areas in East Africa, by 2020. The region is one of the fastest urbanizing in the entire continent. In ten years, there were nearly 20 million more urban residents, as the total amount was 43 million in 2010. Djibouti is the most urbanized country in East Africa, with a share of approximately 78 percent of urban population, in 2018. In absolute numbers, Ethiopia has the largest number of urban residents, roughly 23 million.

Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: German East Africa (Tanganyka)

This dataset is about countries per year in Eastern Africa. It has 1,088 rows. It features 3 columns: country, and population.

Graph and download economic data for Population ages 65 and above for Developing Countries in Middle East and North Africa (SPPOP65UPTOZSMNA) from 1960 to 2024 about North Africa, Middle East, 65-years +, and population.

This dataset is about countries in Eastern Africa. It has 17 rows. It features 2 columns including urban population.

Population characteristics of adults in rural East Africa based on weighted SEARCH-CKD participants.

In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable. The Afrobarometer surveys did not include data on the BMI of adults nor weights for children. Here, the reported times the household went without food in the year were used prior to the date the survey was conducted as vulnerability indicator. The study area of households vulnerability included: rural, urban and total population. This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata. This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.

This dataset is about countries in Eastern Africa. It has 17 rows. It features 3 columns: region, and population.

Graph and download economic data for Population Growth: All Income Levels for Middle East and North Africa (SPPOPGROWMEA) from 1961 to 2024 about North Africa, Middle East, income, population, and rate.

Vulnerable population identified by the nutritional status of women (BMI) as indicator for food security, in sample of households in East Africa study area. Data based on DHS and MICS surveys. In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable. This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata. This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.

Vulnerable population identified by the prevalence of diseases (malaria, cough and diarrhea) as indicator for food security, in sample of households in East Africa study area. Data based on DHS and MICS surveys. In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age and weight for height) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable. This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata. This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.

Actual value and historical data chart for Kenya Population Ages 65 And Above Male Percent Of Total

Major Towns by PopulationTowns in Kenya: Kenya’s capital city is Nairobi. It is the largest city in East Africa and the region’s Financial, Communication and Diplomatic Capital. In Kenya there are only three incorporated cities but there are numerous municipalities and towns with significant urban populations. Two of the cities, Nairobi and Mombasa are cities whose county borders run the same as their city limits, so in a way they could be thought of as City-CountiesNairobi is the only city in the world with a game park. Nairobi National Park is a preserved ecosystem where you can view wildlife in its natural habitat. Hotels, airlines and numerous tour firms and agencies offer tour packages for both domestic and foreign tourists visiting Nairobi and the park. The tourism industry provides direct employment to thousands of Nairobi residents.

In 2025, life expectancy at birth in East Africa was higher than the African average of 64 years for the majority of countries in the region. The Seychelles had the highest in the region at around 74 years, whereas Somalia had the lowest life expectancy at about 54 years.

This horizontal bar chart displays population (people) by country using the aggregation sum in Eastern Africa. The data is about countries per year.

South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data was reported at 531,545.000 Person in 2018. This records a decrease from the previous number of 568,062.743 Person for 2017. South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data is updated yearly, averaging 620,146.947 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 671,734.772 Person in 2009 and a record low of 482,541.064 Person in 2001. South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G004: Population: Mid Year: by Province, Age and Sex.