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.
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Our Population Density Grid Dataset for Eastern Africa offers detailed, grid-based insights into the distribution of population across cities, towns, and rural areas. Free to explore and visualize, this dataset provides an invaluable resource for businesses and researchers looking to understand demographic patterns and optimize their location-based strategies.
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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 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.
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This horizontal bar chart displays population (people) by region using the aggregation sum in Eastern Africa. The data is about countries.
Roughly two out of ten people in East Africa are expected to live in urban areas in 2020. The region is one of the fastest urbanizing in the continent. In 1960, seven percent of East Africa was urbanized, while it was 24 percent in 2020. In absolute numbers, the number of urban residents jumped from three million to 65 million in the period, and Ethiopia is the country with more residents in urban areas, roughly 23 million.
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This horizontal bar chart displays urban population (people) by countries using the aggregation sum in Eastern Africa. The data is about countries.
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.
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Graph and download economic data for Population Growth for Developing Countries in Middle East and North Africa (SPPOPGROWMNA) from 1961 to 2024 about North Africa, Middle East, population, and rate.
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Graph and download economic data for Population, Total for Developing Countries in Middle East and North Africa (SPPOPTOTLMNA) from 1960 to 2024 about North Africa, Middle East, and population.
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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.
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This horizontal bar chart displays population (people) by country using the aggregation sum in Eastern Africa. The data is about countries per year.
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This dataset is about countries in Eastern Africa. It has 17 rows. It features 3 columns: continent, and urban population.
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South Africa Population: Mid Year: Eastern Cape: 25 to 29 Years data was reported at 527,548.000 Person in 2018. This records a decrease from the previous number of 545,041.268 Person for 2017. South Africa Population: Mid Year: Eastern Cape: 25 to 29 Years data is updated yearly, averaging 496,672.607 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 552,071.094 Person in 2014 and a record low of 378,182.286 Person in 2001. South Africa Population: Mid Year: Eastern Cape: 25 to 29 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.
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.
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South Africa Population: Mid Year: Eastern Cape: Female: 30 to 34 Years data was reported at 253,490.000 Person in 2018. This records a decrease from the previous number of 256,329.937 Person for 2017. South Africa Population: Mid Year: Eastern Cape: Female: 30 to 34 Years data is updated yearly, averaging 203,092.154 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 256,329.937 Person in 2017 and a record low of 192,141.391 Person in 2008. South Africa Population: Mid Year: Eastern Cape: Female: 30 to 34 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.
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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.
Data publication: 2013-08-01
Supplemental Information:
ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).
ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.
The project focused on the following specific objectives:
Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;
Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;
Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;
Suggest and analyse new suited adaptation strategies, focused on local needs;
Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;
Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.
The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.
Contact points:
Metadata Contact: FAO-Data
Resource Contact: Lia van Wesenbeeck
Resource Contact: Ben Sonneveld
Resource constraints:
copyright
Online resources:
BMI <16, % of population - Distribution in sample of households in East Africa
BMI 16-18.3, % of population - Distribution in sample of households in East Africa
BMI 18.3-18.6, % of population - Distribution in sample of households in East Africa
BMI >18.6, % of population - Distribution in sample of households in East Africa
CLIMAFRICA – Climate change predictions in Sub-Saharan Africa: impacts and adaptations
In 2022, the East African countries with the highest share of the population with access to electricity were in Mauritius and the Seychelles, at 100 percent. Comoros followed, with almost ** percent of residents having a connection to the grid. On the other hand, Burundi and South Sudan had the lowest share with **** percent and *** percent, respectively.
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This horizontal bar chart displays male population (people) by countries using the aggregation sum in Eastern Africa. The data is about countries.
In 2018, roughly 23 percent of the population in East Africa were living in urban areas. The most urbanized country was Djibouti (78 percent), while Burundi was the least urbanized (13 percent). In absolute numbers, Ethiopia had the largest number of urban residents, approximately 23 million.
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.