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Kenya KE: Rural Land Area data was reported at 576,333.750 sq km in 2010. This stayed constant from the previous number of 576,333.750 sq km for 2000. Kenya KE: Rural Land Area data is updated yearly, averaging 576,333.750 sq km from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 576,333.750 sq km in 2010 and a record low of 576,333.750 sq km in 2010. Kenya KE: Rural Land Area 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: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Sum;
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Rural population (% of total population) in Kenya was reported at 69.95 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Rural population - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.
The national food poverty rate in Kenya was close to ** percent as of 2022. Urban areas within the country experienced lower occurrences of food poverty, with just under ** percent, whereas rural areas had slightly more than ** percent
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Kenya KE: Rural Population: % of Total Population data was reported at 73.438 % in 2017. This records a decrease from the previous number of 73.895 % for 2016. Kenya KE: Rural Population: % of Total Population data is updated yearly, averaging 83.566 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 92.638 % in 1960 and a record low of 73.438 % in 2017. Kenya KE: Rural Population: % of Total 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. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Weighted average;
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Time series data for the statistic Rural population and country Kenya. Indicator Definition:Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.The indicator "Rural population" stands at 39.48 Million as of 12/31/2024, the highest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 1.21 percent compared to the value the year prior.The 1 year change in percent is 1.21.The 3 year change in percent is 3.73.The 5 year change in percent is 6.35.The 10 year change in percent is 14.63.The Serie's long term average value is 21.39 Million. It's latest available value, on 12/31/2024, is 84.56 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1960, to it's latest available value, on 12/31/2024, is +453.75%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is 0.0%.
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Access to electricity, rural (% of rural population) in Kenya was reported at 67.9 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Access to electricity, rural (% of rural population) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.
This dataset is the result of a phone survey set up to measure the impact of COVID-19 on rural people in Kenya. As most governments have urged the population to stay at home to slow down the transmission of the disease, the impact of COVID-19 can affect women and men in different ways: as an income shock (directly or indirectly); as a health and caring shock; as a shock of mobility (affecting access to water, food, firewood, schooling); and as a risk of increased domestic conflict and violence. To capture these various effects on household welfare, this phone survey was conducted with (around) 600 individuals randomly drawn from an existing list of phone numbers collected from previous household surveys with an equal proportion of women and men. The same individuals were also interviewed during other rounds to generate a longitudinal panel allowing to analyze the impact of COVID-19 through time.
In 2024, around ** percent of the population in Kenya lived in extreme poverty, the majority in rural areas. Those living on less than **** U.S. dollars a day in rural regions added up to around **** million, while around *** million extremely poor people resided in urban areas. During the period observed, the poverty incidence in Kenya peaked in 2022, likely due to the disruption to the country's economy caused by the coronavirus (COVID-19) pandemic.
Affordablity is the single most common barrier in Kenya for not owning a mobile phone, as stated by ** percent of respondents living in urban areas and ** percent of respondents who reside in rural areas of the country.
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Kenya KE: Rural Population data was reported at 36,498,585.000 Person in 2017. This records an increase from the previous number of 35,810,675.000 Person for 2016. Kenya KE: Rural Population data is updated yearly, averaging 18,595,106.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 36,498,585.000 Person in 2017 and a record low of 7,508,718.000 Person in 1960. Kenya KE: Rural 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. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;
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Kenya KE: Rural Population Growth data was reported at 1.903 % in 2017. This records a decrease from the previous number of 1.958 % for 2016. Kenya KE: Rural Population Growth data is updated yearly, averaging 2.906 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 3.700 % in 1982 and a record low of 1.903 % in 2017. Kenya KE: Rural Population Growth 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. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Weighted average;
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This dataset shows census data for Kenya disaggregated as follows, by:
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Kenya KE: Rural Land Area Where Elevation is Below 5 Meters data was reported at 1,381.046 sq km in 2010. This stayed constant from the previous number of 1,381.046 sq km for 2000. Kenya KE: Rural Land Area Where Elevation is Below 5 Meters data is updated yearly, averaging 1,381.046 sq km from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 1,381.046 sq km in 2010 and a record low of 1,381.046 sq km in 2010. Kenya KE: Rural Land Area Where Elevation is Below 5 Meters 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: Land Use, Protected Areas and National Wealth. Rural land area below 5m is the total rural land area in square kilometers where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Sum;
In 2022, the lowest total fertility rate was achieved among individuals residing in urban areas in Kenya, at 2.8 percent. Fertility rates in rural areas have declined considerably since 1989, from 7.1 percent to 3.9 percent in 2022. This is likely due to increased education, the use of contraception, and wanting to live a quality life.
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Kenya KE: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 0.003 % in 2010. This stayed constant from the previous number of 0.003 % for 2000. Kenya KE: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 0.003 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.003 % in 2010 and a record low of 0.003 % in 2010. Kenya KE: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area 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: Land Use, Protected Areas and National Wealth. Urban land area below 5m is the percentage of total land where the urban land elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted average;
The study includes a merged core data file from the 7 country RuralStruc surveys conducted in 2007-2008.
Areas covered in the data are selected rural areas in the following regions:
in Kenya: Bungoma, Nakuru North, Nyando
in Madagascar: Alaotra, Antsirabe, Itasy, Morondava
in Mali: Diema, Koutiala, Macina, Tominian
in Mexico: Tequisquiapan (Queretaro), Sotavento (Veracruz)
in Morocco: Chaouia, Saiss, Souss
in Nicaragua: El Cua, El Viejo, La Libertad, Muy Muy, Terrabona
in Senegal: Casamance, Mekhe, Nioro, Senegal River Delta.
For more detailed information on geographic coverage, data users can refer to the RuralStruc National Reports.
The basic unit of observation and analysis that the study describes is the rural household, with the exception of Mali.The preference for rural and not only farm households was justified by the objective of identifying more precisely agriculture's role with respect to other rural activities and sources of income. This option was not neutral, as it refers to analytical categories whose definition are more complicated than one may believe a priori, like the definition of what “rural” is, its characterization varying between countries. The Program National teams considered the following definitions for rural housholds:
-Kenya: "The household was defined as a family living together, eating together, and making farming and other household decisions as a unit"'
-Madagascar :" Le ménage est un ensemble de personnes avec ou sans lien de parenté, vivant sous le même toit ou dans la même concession, prenant leur repas ensemble ou par petits groupes, mettant une partie ou la totalité de leurs revenus en commun pour la bonne marche du groupe, et dépendant du point de vue des dépenses d'une même autorité appelée chef de ménage », le chef de ménage étant la personne reconnue comme tel par l’ensemble des membres du ménage".
-Mali : "La Loi d’Orientation Agricole (LOA), dans ses articles 10 à 28, définit ce que sont les exploitations agricoles au Mali. « L’exploitation agricole est une unité de production dans laquelle l’exploitant et/ou ses associés mettent en oeuvre un système de production agricole. Elles sont classées en deux catégories : l’exploitation agricole familiale et l’entreprise agricole. L’exploitation agricole familiale est constituée d’un ou de plusieurs membres unis librement par des liens de parenté ou des us et coutumes et exploitant en commun les facteurs de production en vue de générer des ressources sous la direction d’un des membres, désigné chef d’exploitation, qu’il soit de sexe masculin ou féminin. Le chef d’exploitation assure la maîtrise d’oeuvre et veille à l’exploitation optimale des facteurs de production. Il exerce cette activité à titre principal et représente l’exploitation dans tous les actes de la vie civile. Sont reconnus comme exerçant un métier Agricole, notamment, les agriculteurs, éleveurs, pêcheurs, exploitants forestiers".
-Maroc : "L’unité ménage renvoie au groupe domestique qui est défini comme une unité de résidence, de production et de consommation. Le plus souvent, le groupe domestique a pour noyau une famille, à laquelle peuvent s’ajouter des parents éloignés ou des « étrangers ». Il peut aussi se composer de plusieurs familles nucléaires comme il peut rassembler des personnes sans aucun lien de parenté".
-Mexico : "El Instituto Nacional de Estadística Geografía e Informática (INEGI) usa el concepto de localidad que define como “todo lugar ocupado por una vivienda o conjunto de viviendas, de las cuales al menos una está habitada. El lugar es reconocido comúnmente por un nombre dado por la ley o la costumbre”, y por otro considera que una localidad es rural cuando tiene menos de 2 500 habitantes. El INEGI define también en concepto de hogar como una “unidad doméstica [que] hace referencia a una organización estructurada a partir de lazos o redes sociales establecidas entre personas unidas o no por relaciones de parentesco, que comparten una misma vivienda y organizan en común la reproducción de la vida cotidiana a partir de un presupuesto común para la alimentación, independientemente de que se dividan otros gastos”.
-Nicaragua : "Se define hogar como el número de personas comparten una olla común. Un hogar puede estar compuesto de una o más familias. La definición oficial en Nicaragua de rural es aquel territorio que “comprenden los poblados de menos de 1000 habitantes que no reúnen las condiciones urbanísticas mínimas indicadas y la población dispersa.” INEC, 2007".
-Senegal : "Le rural se définit par opposition à l’urbain, constitué par les villes et les communes, même à dominance rurale. Au Sénégal, les populations d’une commune sont de facto considérées comme des urbains ; or, plusieurs communes sont composées à plus de la moitié par des agriculteurs. Le ménage rural se définit comme un groupe familial résidant en milieu rural au sein duquel s’organisent la production agricole et/ou non agricole, la préparation et la consommation des repas. Traditionnellement, le ménage rural se confond avec le ménage agricole ; toutefois, on note de plus en plus que la nourriture du ménage rural provient de moins en moins de la production ou des revenus tirés de l’agriculture au sens large : production agricole, élevage, pêche et foresterie. L’unité familiale de production et de consommation16 ne coïncide pas forcément avec l’unité de résidence, ker en wolof ou galle en pulaar".
For detailed information on the rationale corresponding to the definition of rural households, the data users can refer to the National Reports, available as External Resources.
The universe covered by the study includes rural households and all household members that were selected in the study areas.
Sample survey data [ssd]
With the objective of 300 to 400 surveyed households per region (i.e. between 900 and 1,200 surveys per country),the Program National teams engaged in the sampling process in two steps. The first step was the selection of the localities to be surveyed, with consideration of regions' characteristics and national team expertise. The second step was the sampling itself, which was based on existing census lists or intentionally prepared locality household lists. Then, households were selected at random, targeting a sufficient number of households per locality allowing representativeness at local level.
In the seven countries, 8,061 rural households' surveys were selected for the sample in 26 regions and 167 localities (depending on the settlement structure), and 7,269 were successfully interviewed and kept for the analysis. In Mali, the 634 household surveys (at the family farm level) were completed by 643 interviews with dependent households and 749 interviews with women.
Face-to-face [f2f]
The merged dataset was constructed from variables extracted from national datasets.
For details on questions relating to these variables, see the attached questionnaires for each country survey. Each country questionnaire was derived and adapted from a questionnaire template which was designed collectively by the RuralStruc Program Coordination team and the national teams.
The original page and question numbers for each variable is included in the variable descriptions.
Secondary editing of the data in this core dataset included:
(i) Data in local currency units (for example, incomes, prices, sales of agricultural products) were converted to international dollars ($ PPP), for comparability across national surveys. Purchasing Power Parity conversion rates were calculated using the World Bank Development Data Platform. They refer to the period January 2007 to April 2008. The conversion rates between $1 PPP and local currency units are the following: - Kenya: 34 Kenyan Shilling - Madagascar: 758.7 Ariary - Mali: 239.6 CFA Franc - Mexico: 7.3 Mexican Peso - Morocco: 4.8 Dirham - Nicaragua: 6.7 Cordoba - Senegal: 258.6 CFA Franc
(ii) Data in local currency units were converted into kilo-calories, for comparability across national surveys. In all the studied zones, diets rely primarily on cereals - at least in terms of energy. Thus, the basic cereal of each zone (or basket of cereals in the case of Mali) was used as a reference. The conversion rates between Kg of cereals and Kcal are those provided by the FAO's Food Balance Sheets (FAO 2001). The prices of cereals are those used by the RuralStruc national teams to estimate the value of self-consumption. These prices correspond with the average producer sale prices (or the median in the case of Madagascar) for the surveyed year. One will note that, in general, the farm income for the poorest households largely consists of self-consumption of cereals, which are valued, therefore, at the producer sale price. The average cereal prices and kilocalorie ratios permitted calculation of a price for units of 1000 Kcal in $PPP and then to convert the estimated monetary incomes in incomes in kilocalories equivalent. For detailed information, data users can refer to the methodological annex of the synthesis report.
(iii) Recoding of the geographical component of the household identifier
For more details on data editing, the data user should refer to the variable descriptions.
Introduction Knowledge of utilization of health services and associated factors is important in planning and delivery of interventions to improve health services coverage. We determined the prevalence and factors associated with health services utilization in a rural area of Kenya. Our findings inform the local health management in development of appropriately targeted interventions. Methods and Results We used a cluster sample survey design and interviewed household key informants on history of illness for household members and health services utilization in the preceding month. We estimated prevalence and performed random effects logistic regression to determine the influence of individual and household level factors on decisions to utilize health services. 1230/6,440 (19.1%, 95% CI: 18.3%-20.2%) household members reported an illness. Of these, 76.7% (95% CI: 74.2%-79.0%) sought healthcare in a health facility. The majority (94%) of the respondents visited dispensary-level faci...
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This dataset is about countries per year in Kenya. It has 64 rows. It features 4 columns: country, ISO 2 country code, and rural land area.
The data supporting this publication are available on the Harvard Dataverse, accessible at: https://doi.org/10.7910/DVN/UL0TEO. The data folder includes three files: (1) observations.dta, (2) sitestatistics.dta, and (3) realastmilecosts.csv In addition, we include STATA do-files that generates selected figures and tables from the article. Please note that all identifying information has been removed from this dataset. Publication: “Electrification for “Under Grid” households in Rural Kenya” Development Engineering, vol. 1, pp. 26-35 Authors: Kenneth Lee, Eric Brewer, Carson Christiano, Francis Meyo, Edward Miguel, Matthew Podolsky, Javier Rosa, Catherine Wolfram
This data describes the recovering and isolation processes of Bacteroides spp. strains from human and cattle faecal sources from rural areas in Siaya County (Kenya), and occurred between 7th and 28th of June 2018. The data also includes the detection of bacteriophages (infecting these Bacteroides spp. host strains) in conjunction with traditional faecal indicator organisms in water sources from Kisumu and Siaya County (Kenya) occurring between June 18th 2018 and June 13th 2019. Exact location (coordinates) of the sample points are also described in the data set. A microbiological technique using Bile Esculin Bacteroides (BBE) agar was used for the recovering and isolation processes of Bacteroides spp. strains. Standard ISO (7899-2, 9308-1, 10705-2 and 10705-4) techniques, such as membrane filtration and the double-agar-layer methods, were used for the detection of bacteriophages and traditional faecal indicator organisms. The purpose of data collection was to develop new markers that could identify cattle and/or human sources of faecal contamination, which could be used as part of a Microbial Source Tracking (MST) tool box. Technicians and researchers from the University of Brighton (UK), University of Southampton (UK), from the Victoria Institute for Research on Environment and Development (VIRED) (KE) and from the Kenya Medical Research Institute (KEMRI) (KE) were responsible for the collection and interpretation of data. This dataset is embargoed until 31st July 2020
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Kenya KE: Rural Land Area data was reported at 576,333.750 sq km in 2010. This stayed constant from the previous number of 576,333.750 sq km for 2000. Kenya KE: Rural Land Area data is updated yearly, averaging 576,333.750 sq km from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 576,333.750 sq km in 2010 and a record low of 576,333.750 sq km in 2010. Kenya KE: Rural Land Area 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: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Sum;