The total population in Kenya was forecast to continuously increase between 2024 and 2029 by in total 4.6 million people (+8.77 percent). After the tenth consecutive increasing year, the total population is estimated to reach 57.04 million people and therefore a new peak in 2029. Notably, the total population was continuously increasing over the past years.This indicator describes the total population in the country at hand. This total population of the country consists of all persons falling within the scope of the census.Find more key insights for the total population in countries like Burundi, Seychelles, and Mozambique.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Kenya data available from WorldPop here.

The dataset contains Population and Household statistics for the years 2009 and 2016 as well as the enumeration areas.The dataset was provided by Kenya National Bureau of Statistics (KNBS).

Chart and table of Kenya population from 1950 to 2025. United Nations projections are also included through the year 2100.

As of 2024, the median age in Kenya reached 19.9 years. The indicator has been increasing in the country, which indicates declining fertility rates and/or improvements in life expectancy. In 2015, the median age in Kenya stood by 17.9 years.

While the East African region, including Kenya, is one of first regions believed to have modern humans inhabit it, population growth in the region remained slow to non-existent throughout the 19th century; in the past hundred years, however, Kenya’s population has seen an exponential increase in size, going from 2.65 million in 1920, to an estimated 53.77 million in 2020.

Along with this population growth, Kenya has seen rapid urbanization and industrialization, particularly in recent decades. The metropolitan area of Kenya’s capital, Nairobi, with an estimated population of 9.35 million in 2020, now contains on its own over three and a half times the population of the entire country just a century earlier.

Kenya KE: Population: Female: Ages 30-34: % of Female Population data was reported at 7.536 % in 2017. This records an increase from the previous number of 7.507 % for 2016. Kenya KE: Population: Female: Ages 30-34: % of Female Population data is updated yearly, averaging 5.866 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.536 % in 2017 and a record low of 4.488 % in 1975. Kenya KE: Population: Female: Ages 30-34: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 30 to 34 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

This statistic shows the total population of Kenya from 2013 to 2023 by gender. In 2023, Kenya's female population amounted to approximately 27.82 million, while the male population amounted to approximately 27.52 million inhabitants.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.


Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):

- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019).

Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the United Nations Children's Fund ( UNICEF ) - Population Modelling for use in Routine Health Planning and Monitoring project (contract no. 43335861). Projects partners included the Kenya Unicef Regional and Country Offices, WorldPop research group at the University of Southampton and the Center for International Earth Science Information Network CIESIN in the Columbia Climate School at Columbia University. Assane Gadiaga (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Thomas Abbott supported the covariates processing work, as well as Christopher Lloyd, particularly for the processing of residential/non-residential building footprints. In-country engagements were done by Benard Mitto, Justine Dowden (CIESIN) and Maria Muniz (Unicef). Using the 2009 and 2019 census data from the Kenya’s National Bureau of Statistics (KNBS), the US Census Bureau released the census-based total population projections, population by age and sex and digital sub-counties boundaries. Duygu Cihan helped in the preparation of these input population data. Attila N Lazar, Edith Darin and Heather Chamberlain advised on the modelling procedure. The work was overseen by Attila N Lazar and Andy J Tatem.

For further details, please, read the Release Statement.

Release content

1. KEN_population_v1_0_gridded.tif
2. KEN_population_v1_0_agesex.zip
3. KEN_population_v1_0_mastergrid.tif

Recommended citations

Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. Census disaggregated gridded population estimates for Kenya (2021), version 1.0 University of Southampton. doi:10.5258/SOTON/WP00747

License

These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License, specified in legal code. Contact release[at]worldpop.org for more information.

The authors followed rigorous procedures designed to ensure that the used data, the applied method and thus the results are appropriate and of reasonable quality. If users encounter apparent errors or misstatements, they should contact WorldPop at release[at]worldpop.org.

WorldPop, University of Southampton, and their sponsors offer these data on a "where is, as is" basis; do not offer an express or implied warranty of any kind; do not guarantee the quality, applicability, accuracy, reliability or completeness of any data provided; and shall not be liable for incidental, consequential, or special damages arising out of the use of any data that they offer.

This statistic shows the age structure in Kenya from 2013 to 2023. In 2023, about 37.22 percent of Kenya's total population were aged 0 to 14 years.

Population ages 15-64, female (% of female population) in Kenya was reported at 59.72 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Population ages 15-64, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Population ages 15-64, female in Kenya was reported at 16614458 Persons in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Population ages 15-64, female - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system. The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Kenya KE: Population: as % of Total: Male: Aged 15-64 data was reported at 56.522 % in 2017. This records an increase from the previous number of 56.147 % for 2016. Kenya KE: Population: as % of Total: Male: Aged 15-64 data is updated yearly, averaging 48.868 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 56.522 % in 2017 and a record low of 46.680 % in 1982. Kenya KE: Population: as % of Total: Male: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 15 to 64 as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Geographic coverage

National

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Population ages 35-39, female (% of female population) in Kenya was reported at 6.1952 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Population ages 35-39, female (% of female population) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

This dataset shows census data for Kenya disaggregated as follows, by:

• Urban or rural areas and sex
• Age
• Education levels
• Employment levels

Abstract

The Population and Housing Census 1979, has been done after a ten year period the previous one being in 1969. it is a de jure analysis of Kenyan households covering all individuals present.

Geographic coverage

it covers the whole country

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646