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2019 Kenya Population and Housing Census: Volume IV

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VOLUME IV

DISTRIBUTION OF POPULATION BY

SOCIO-ECONOMIC CHARACTERISTICS


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Kenya National Bureau of Statistics P.O Box 30266-00100

Nairobi

Tel. +254-20-3317583/6/8 E-mail: [email protected]

or

[email protected]

Website: http://www.knbs.or.ke

ISBN: 978-9966-102-11-9 All Rights Reserved Copyright©2019 Extracts may be published if the source is duly acknowledged

mailto:[email protected]


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Kenya Counties


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ABOUT KNBS

The Kenya National Bureau of Statistics (KNBS) is the principal agency of the Government for collecting, analysing and disseminating statistical data, and the custodian of official statistical information. The Bureau is also responsible for the co-ordination of the National Statistical System (NSS) in the country. The functions of KNBS as defined in the Statistics (Amendment) Act, 2019 are:

• Planning, authorising, coordinating and supervising all official statistical programmes undertaken within the NSS;

• Establishing standards and ensuring the use of best practices and methods in the production and dissemination of statistical information across the NSS;

• Collecting, compiling, analysing, abstracting and disseminating statistical information;

• Conducting the Population and Housing Census every ten years, and such other censuses and surveys as the Board may determine;

• Maintaining a comprehensive and reliable national socio-economic database;

• Developing and maintaining sampling frames of the Bureau;

• Collaborating with and assisting the county governments or any institutions in the production of official statistics;

• Providing technical advice on statistics to other state entities;

• Promoting co-ordination among producers, users and suppliers of official statistics by forming appropriate sector committees; and

• Designating statistics produced by national statistical system as official statistics on being satisfied that the necessary criteria have been followed.

The KNBS has an elaborate infrastructure for data collection across the country. This includes, a County Statistical Office in each of the 47 counties, two sampling frames for implementation of censuses and surveys and various databases for socio-economic statistical information. The Bureau collects various statistical information on monthly, quarterly, semi-annually and annual basis. Ad hoc surveys and studies are also carried out to gather information on specific indicators. Some of the statistical products of the Bureau include; Consumer Price Index (CPI), Leading Economic Indicators report, Quarterly Gross Domestic Product (GDP), Quarterly Producer Price Index (PPI), Quarterly Balance of Payment, Annual Economic Survey Report and Annual Statistical Abstract. The Bureau also provides statistical information to regional and international organisations. The KNBS maintains various platforms through which products and statistical information are disseminated.

The Bureau provides information for monitoring the country’s development agenda as well as internationally agreed initiatives such as Sustainable Development Goals (SDGs). In undertaking its mandate, the Bureau is guided by a Vision, Mission and Core Values.


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Vision

“To be a global leader in the provision of quality statistical services”

Mission “To provide, manage and promote quality statistical services through utilization of best practices for evidence-based decision making”.

Core Values

• P-Professionalism: The Bureau will strictly abide by professional considerations, including scientific principles and ethics on methods, standards and procedures for provision of quality statistical services.

• I-Integrity: The Bureau will adhere to the principles of good governance to ensure transparency and accountability in undertaking its programmes and activities.

• C-Confidentiality: The Bureau will treat all information provided by stakeholders with strict confidentiality and use it exclusively for statistical purposes

• C-Customer Focus: The Bureau commits itself to align its programmes to the expectations of its stakeholders and attaining the highest standards in service delivery.

• I-Innovation: The Bureau will continuously embrace creativity and innovation for value-addition in its business processes.

• T-Teamwork: The Bureau will embrace teamwork in pursuing timely attainment of targeted results at all levels, through coordination and networking.


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FOREWORD

The 2019 Kenya Population and Housing Census (KPHC) was the eighth to be conducted

in Kenya since 1948 and was conducted from the night of 24th/25th to 31st August2019.

It was implemented under the provisions of the Constitution of Kenya, 2010 and the

Statistics (Amendment) Act, 2019. It also followed the United Nations Principles and

Recommendations for conducting the 2020 round of censuses, including adoption of

technology. Indeed, the country leveraged on technology to capture data during

cartographic mapping, enumeration and data transmission, making the 2019 KPHC the

first paperless census to be conducted in Kenya.

The theme for the census was “Counting Our People for Sustainable Development and

Devolution of Services”. The theme resonates well with Kenya’s development agenda -

Vision 2030 and the Big Four, as well as other regional and international development

initiatives including the Sustainable Development Goals (SDGs) and the African Union

Agenda 2063. The information contained herein responds to the ever-increasing

demand for official statistics and provides benchmark information for other statistical

development and infrastructure, particularly for the devolved units of governance.

The 2019 KPHC Volume IV Report is the fourth in the series of census publications. It

presents the distribution of population by socio-economic characteristics. These are:

education; labour participation; housing conditions and amenities; agriculture and

livestock; disability; religion and ethnicity; Information and Communication Technology

(ICT); and ownership of household assets. Further work is ongoing to produce in-depth

analytical thematic reports on the Census.

The Bureau is indebted to all the organs of government, the private sector and the public

for the overwhelming support and participation in implementing the Census. Special

gratitude goes to United Nations Population Fund (UNFPA); United Nations Children’s

Fund (UNICEF); United Nations Economic Commission for Africa (UNECA); African

Development Bank (AfDB); Statistics Sweden; and Office of National Statistics United

Kingdom (ONS-UK) for their support. I also recognise the census personnel who played

a key role in the overall success of the 2019 KPHC.

Stakeholders are encouraged to utilize the information in this report effectively.

Zachary Mwangi

Director General, KNBS


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Table of Contents ABOUT KNBS ..................................................................................................................... vi

FOREWORD ..................................................................................................................... viii

List of Tables ...................................................................................................................... xi

ACRONYMS AND ABBREVIATIONS ............................................................................... xiii

SYMBOLS AND CONVENTIONS USED .......................................................................... xiii

CHAPTER 1: INTRODUCTION ........................................................................................... 1

1.1. Background Information ....................................................................................... 1

1.2. Objectives of the 2019 Census .............................................................................. 1

1.3. Theme of the 2019 Census .................................................................................... 2

1.4. Implementation of the 2019 Census .................................................................... 2

1.4.1 Legal Framework ...................................................................................................................... 2

1.4.2 Census Management Structure ............................................................................................... 2

1.4.3 Use of Technology .................................................................................................................... 3

1.4.4 Cartographic Mapping ............................................................................................................ 3

1.4.5 Census Questionnaires............................................................................................................. 3

1.4.6 Pilot and Pre-tests ..................................................................................................................... 4

1.4.7 Publicity and Advocacy .............................................................................................................. 4

1.4.8 Recruitment and Training ....................................................................................................... 4

1.4.9 Enumeration ............................................................................................................................. 4

1.4.10 Data Transmission and Storage .................................................................................................. 5

1.5. Data Processing ...................................................................................................... 5

1.6. Quality Assurance .................................................................................................. 5

1.7. Definition of Key Concepts .................................................................................... 5

1.8. Constraints and Challenges ................................................................................... 6

1.9. List of Counties and Sub-Counties ........................................................................ 7

CHAPTER 2: CENSUS RESULTS ........................................................................................ 10

2.1 Summary Findings ............................................................................................ 10

2.1.1 Sub-Locations with No Data.................................................................................................. 10

2.1.2 Education ................................................................................................................................ 10

2.1.3 Activity Status ......................................................................................................................... 11

2.1.4 Housing Conditions and Amenities ...................................................................................... 11

2.1.5 Agriculture .............................................................................................................................. 12

2.1.6 Disability ................................................................................................................................. 12

2.1.7 Religious and Ethnic Affiliation ............................................................................................ 12

2.1.8 Information and Communication Technology (ICT) .......................................................... 12


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2.1.9 Ownership of Household Assets ........................................................................................... 13

LIST OF CONTRIBUTORS ............................................................................................... 473

APPENDICES: QUESTIONNAIRES ................................................................................... 476


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List of Tables

Table 1. 1: Summary of Census Counts in Kenya.............................................................................................. 6

Table 2. 1: Sub-locations with no People on the Census Night by Status/Reason.......................................... 10

Table2.2: Distribution of Population Aged 3 Years and Above by School Attendance Status, Area of Residence, Sex, County and SubCounty.............................................................................................................. 14 Table 2.3: Distribution of Population Aged 3 Years and Above Currently Attending School/ Learning Institution by Education Level, Area of Residence, Sex, County and Sub-County.......................................... 44 Table 2.4: Distribution of Population Aged 3 Years and Above by Highest Level of Education Reached, Area of Residence, Sex, County and Sub-County............................................................................................... 75 Table 2.5: Distribution of Population Aged 3 Years and Above by Highest Level of Education Completed, Area of Residence, Sex, County and Sub-County............................................................................................... 106 Table 2.6a: Distribution of Population Aged 3 Years and Above by School Attendance Status, Sex and Special Age Groups............................................................................................................................................... 137 Table 2.6b: Distribution of Population Aged 3 Years and Above by School Attendance Status, Sex, Special Age Groups and County.......................................................................................................................... 138 Table 2.7: Distribution of Population Aged 15 years and Above by Sex and Main Training Acquired and Qualified for.......................................................................................................................................................... 160 Table 2.8a: Distribution of Population Aged 5 Years and above by Activity Status, Sex, County and Sub-County.................................................................................................................................................................... 162 Table 2.8b: Distribution of Urban Population Aged 5 Years and above by Activity Status, Sex, County and Sub-County.................................................................................................................................................... 183 Table 2.8c: Distribution of Rural Population Aged 5 Years and above by Activity Status, Sex, County and Sub-County............................................................................................................................................................ 207 Table 2.9a: Distribution of Population Aged 5 years and above by Activity Status, Broad Age Groups and County............................................................................................................................................................ 227 Table 2.9b: Distribution of Rural Population Aged 5 years and above by Activity Status, Broad Age Groups and County.............................................................................................................................................. 233 Table 2.9c: Distribution of Urban Population Aged 5 years and above by Activity Status, Broad Age Groups and County.............................................................................................................................................. 239 Table 2.10: Distribution of Households and Tenure Status of Main Dwelling Unit by Area of Residence, County and Sub-County....................................................................................................................................... 245 Table 2.11a: Distribution of Households Owning the Main Dwelling Unit by Mode of Acquisition, Area of Residence, County and Sub-County................................................................................................................ 252 Table 2.11b: Distribution of Households Renting/Provided with their Main Tenure Status of Main Dwelling Unit by Provider, Area of Residence, County and Sub-County...................................................................................... 259 Table 2.12: Percentage Distribution of Conventional Households by Dominant Roofing Material of Main Dwelling Unit, Area of Residence, County and Sub-County.................................................................. 265 Table 2.13: Percentage Distribution of Conventional Households by Dominant Wall Material of Main Dwelling Unit, Area of Residence, County and Sub-County............................................................................ 277 Table 2.14: Percentage Distribution of Conventional Households by Dominant Floor Material of the Main Dwelling Unit, Area of Residence, County and Sub County................................................................... 287 Table 2.15: Percentage Distribution of Conventional Households by Main Source of Drinking Water, Area of Residence, County and Sub-County....................................................................................................... 300 Table 2.16: Percentage Distribution of Conventional Households by Main Mode of Human Waste Disposal, Area of Residence, County and Sub-County...................................................................................... 310 Table 2.17: Percentage Distribution of Conventional Households by Main Mode of Solid Waste Disposal, Area of Residence, County and Sub-County...................................................................................... 317 Table 2.18: Percentage Distribution of Conventional Households by Main Type of Cooking Fuel, Area of Residence, County and Sub-County.................................................................................................................... 330 Table 2.19: Percentage Distribution of Conventional Households by Main Type of Lighting Fuel, Area of Residence, County and Sub-County.................................................................................................................... 337 Table 2.20: Distribution of households practicing Agriculture, Fishing and Irrigation by County and Sub County........................................................................................................................................................... 350

Table 2.21: Distribution of Households Growing Permanent Crops by Type and County............................ 356

Table 2.22: Distribution of Households Growing Other Crops by Type, County and Sub County............... 357

Table 2.23: Distribution of Households Rearing Livestock and Fish by County and Sub County................. 366


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Table 2.24: Distribution of Livestock population by type, Fish Ponds and Fish Cages by County and Sub County.................................................................................................................................................................... 376 Table 2.25: Distribution of area (hectares) of Agricultural land and Farming Households by purpose of production, County and Sub-County.................................................................................................................. 387 Table 2.26: Distribution of Population aged 5 years and above by Disability Status, Sex1, Area of Residence, County and Sub-County.................................................................................................................... 394 Table 2.27: Distribution of Persons with Disability by Type of Disability, Sex1, Area of Residence, County and Sub County...................................................................................................................................... 405 Table 2.28: Distribution of Persons with Albinism by Sex1, Area of Residence, County and Sub County.................................................................................................................................................................... 414

Table 2.29: Population of Street Persons/Outdoor Sleepers by Sex1, Area of Residence and County......... 421

Table 2.30: Distribution of Population by Religious Affiliation and County.................................................. 322

Table 2.31: Distribution of Population by Ethnicity/Nationality..................................................................... 423

Table 2.32: Distribution of Population Age 3 years and Above Owning a Mobile Phone by Area of Residence, Sex, County and Sub County............................................................................................................. 424 Table 2.33: Distribution of Population Age 3 Years and Above Using Internet and Computer/Laptop/Tablet by Area of Residence, Sex, County and Sub-County............................................. 432 Table 2.34: Distribution of Population age 15 years and above who Searched and Bought Goods and Services Online by Area of Residence, Sex, County and Sub-County.............................................................. 442 Table 2.35: Distribution of Population Age 3 years and Above who owned and used Selected ICT Equipment and Service by Age, Area of Residence and County....................................................................... 449 Table 2.36: Percentage Distribution of Conventional Households by Ownership of Selected Household Assets by Area of Residence, County and Sub County....................................................................................... 462

Table 2.37: Births in the Last 12 months* by place of Occurrence and County............................................. 469

Table 2.38: Births in the Last 5 Years* by place of Occurrence and County.................................................. 470

Table 2.39: Notified Births in the Last 12 months by County.......................................................................... 471

Table 2.40: Notified Births in the Last 5 Years by County................................................................................ 472


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ACRONYMS AND ABBREVIATIONS

CCC County Census Committees

CSPro Census and Survey Processing system

EA Enumeration Area

Esri Environmental Systems Research Institute

GPS Geographical Positioning System

ICT Information and Communication Technology

KNBS Kenya National Bureau of Statistics

KPHC Kenya Population and Housing Census

NGOs Non-Governmental Organisations

NSS National Statistical System

ODK Open Data Kit

SCCCs Sub-County Census Committees

SDGs Sustainable Development Goals

SPSS Statistical Package for Social Sciences

UN United Nations

SYMBOLS AND CONVENTIONS USED

The following symbols have been used in this publication

“ _ ” Means Nil

“ .. ” Means Negligible Rounding of Figures: In tables where figures have been rounded to the nearest final digit, there may be an apparent slight discrepancy between the sum of the constituent items and the total as shown.


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CHAPTER 1: INTRODUCTION

1.1. Background Information

The first known population census in Kenya was conducted in 1897 and was basically

a headcount. This was followed by the 1948 census that focused on non-natives. A

complete census that enumerated 8.6 million persons was conducted in 1962 and was

used to set up political and administrative structures. The first post-independence

census was undertaken in 1969 and enumerated 10.9 million persons. Since then, the

country has conducted decennial Population and Housing Censuses on a de facto basis with the midnight of 24th/25th August as the reference point. The censuses have been

implemented in accordance with the United Nations (UN) Principles and

Recommendations for conducting population and housing censuses. Table 1.1

presents census results since 1897.

Table 1. 1: Summary of Census Counts in Kenya

Year Population (millions)

1897 2.5

1948 5.4

1962 8.6

1969 10.9

1979 15.3

1989 21.4

1999

28.7

2009 37.7

2019 47.6

1.2. Objectives of the 2019 Census

The main objective of the 2019 KPHC was to collect information on the size,

composition, distribution and socio-economic characteristics of the population. The

specific objectives were to ascertain the following:

▪ Population size, composition, and spatial distribution; ▪ Levels of fertility, mortality and migration; ▪ Educational attainment; ▪ Household composition; ▪ Rate and pattern of urbanization; ▪ Size and deployment of labour force; ▪ Distribution of persons with disability;


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▪ Housing conditions and availability of household amenities; and ▪ Agricultural indicators to inform the creation of an agriculture sampling frame

This information will be used in planning, budgeting and programming for important

services; future policy formulation, resource allocation; creation of administrative and

political units; monitoring and evaluation of programmes and projects; research;

development of a master household sampling frame; development of geo-spatial

database; and benchmark for agricultural census/surveys.

1.3. Theme of the 2019 Census

The theme of the census was “Counting Our People for Sustainable Development and

Devolution of Services”. This is in response to the demand for statistical information

for implementation of Kenya’s development agenda such as the Big Four and Vision

2030, and other global initiatives including the Sustainable Development Goals

(SDGs).

1.4. Implementation of the 2019 Census

1.4.1 Legal Framework

The 2019 Kenya Population and Housing Census was conducted under the provisions

of the Constitution of Kenya, 2010 (Fourth Schedule Part 1 Item 11), the Statistics

(Amendment) Act, 2019 and the Statistics (Census of Population) Order, 2018 - Legal

Notice No. 205 and the Cabinet Memorandum of May 2017 on the implementation

of the 2019 population and housing census process.

1.4.2 Census Management Structure Various committees were established and operationalized at both national and county

levels to manage the census process. These committees drew their membership from

various stakeholders namely; government departments and agencies, private sector,

learning institutions, religious organizations, and Non-Governmental Organisations

(NGOs).The National Census Steering Committee spearheaded the implementation

process and provided policy direction such as approving all the census guidelines,

strategies and mobilization of resources. Coordination of the processes was

undertaken by the National Census Coordination Committee. The Technical Working

Committee was responsible for all the technical aspects of the census, which included

development of the instruments and ensuring adherence to quality assurance

guidelines.

http://www.brookings.edu/research/interactives/2013/kenya-resource-sharing


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At the county level, the County Census Committees (CCCs) and Sub-County Census

Committees (SCCCs) were established to oversee implementation of the 2019 census

activities, such as recruitment of personnel, procurement of training venues and

logistical arrangements for transport and security at their respective levels. These

committees were instrumental in rallying public participation for the census.

1.4.3 Use of Technology Kenya adopted the use of mobile technology to collect data during the 2019 census as

recommended by the UN for the 2020 round of censuses. This was the first census in

Kenya to use mobile technology in the capture and transmission of data for both

cartographic mapping and enumeration. The mobile devices (tablets) used for data

collection were assembled by local universities.

1.4.4 Cartographic Mapping The implementation of preparatory activities for the 2019 KPHC started in early 2016

with cartographic mapping exercise. The process involved delineation of the country

into small geographical units known as Enumeration Areas (EAs). The EAs were used

in determining the number of census personnel required as well as in ensuring total

coverage during enumeration. The use of modern technologies in the entire census

cartographic mapping was embraced, as per the UN recommendations for countries

undertaking the 2020 round of population and housing censuses. Smart phones and tablets

embedded with Geographical Positioning System (GPS) were used to pick coordinates for

homesteads, households and other points of interest. Satellite imageries and aerial

photographs were used to prepare maps for rural and urban areas, respectively. Open Data

Kit (ODK), Esri Survey 123 applications were used during field mapping while ArcGIS was

used during digitization and map production. Sub-location and EA maps generated based on

administrative boundaries, were then uploaded onto mobile devices for use during the

enumeration exercise.

1.4.5 Census Questionnaires The census questionnaires and manuals were developed through a consultative

process spearheaded by the Technical Working Committee comprising of various

stakeholders. A mobile data capture system was designed based on the paper

questionnaire. These were uploaded onto the mobile devices for data collection and

transmission. Five sets of questionnaires (one main and four short) were developed to

cover the conventional population and special population (travellers, outdoor

sleepers, individuals in hotels, lodges, schools and, hospitals and emigrants). The main

questionnaire had additional questions on crop farming, fishing, aquaculture,

registration of births and deaths and e-commerce. A third sex marker for intersex


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was also introduced. Further, a detailed set of questions on disability was included as

recommended by the Washington Group.

1.4.6 Pilot and Pre-tests A Pilot Census was conducted in August 2018, a year prior to actual enumeration as

per the UN recommendation, followed by two pre-tests undertaken in April and May

2019. This was meant to assess the preparedness for the actual enumeration in terms

of logistics, map accuracy, content and flow of questions, data capture application and

data transmission. Lessons learnt provided crucial input in the finalization of the tools

and implementation strategies.

1.4.7 Publicity and Advocacy Publicity and advocacy campaigns were done in all parts of the country through

various channels, including; print media, national and local radio stations, mobile

telephony, television stations and road shows. A call/contact centre was established

with a toll-free line to respond to queries raised by the field teams and the public. One

of the key activities was the launch of the census enumeration countdown by His

Excellency the President of the Republic of Kenya, a week prior to census enumeration

exercise.

1.4.8 Recruitment and Training Recruitment of census personnel who included 2,467 ICT supervisors, 22,268 content

supervisors and 138,572 enumerators was undertaken by the County and Sub-County

Census Committees through a competitive process. The training of these personnel

was conducted in a cascaded manner from the training of trainers to the training of

enumerators. The training for various cadres was conducted for seven days for each

cadre. These trainings were sequentially conducted between 14th July and 20th August

2019.

1.4.9 Enumeration

The main census enumeration was preceded by EA boundary identification and pre-

enumeration listing of households in each EA for two days on 22nd and 23rdAugust

2019. The pre-enumeration listing exercise helped in gauging the expected

workload during the seven days of enumeration and also help in monitoring the level

of coverage as enumeration progressed.

The actual enumeration took place from the night of 24th/25thAugust 2019 and

ended on 31st August 2019. A mop-up exercise was conducted on 1stand


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2ndSeptember 2019. The special population was strictly enumerated on the night of

24th/25th August 2019. The 2019 Census adopted the de facto approach where all persons within the boundary of Kenya were enumerating depending on where they

spent (or were found on) the census night. The canvasser method of enumeration,

where information for each individual or household is collected and recorded by a

trained census official designated to perform the tasks in the assigned area, was used.

1.4.10 Data Transmission and Storage Data was collected by enumerators using mobile devices (tablets) and subsequently

transmitted to a central server. The data was encrypted prior to transmission and was

backed up in off-site locations.

1.5. Data Processing Editing of the census data was guided by the United Nations Handbook on Population

and Housing Census editing. The data was processed using CSPro, Stata and SPSS

software. In addition, validation checks were done to ensure that all EAs, aligned to

administrative boundaries, were accounted for in the dataset. Outputs were generated

based on administrative and geo-political units.

1.6. Quality Assurance Quality assurance was integrated in all phases of the census process. Comprehensive

guidelines were developed and shared with census personnel. Field supervision

followed a three-tier structure to ensure adequate support, real-time response to

emerging issues, and feedback during data collection. In addition, enumeration

reporting schedules and control forms were used to facilitate monitoring of activities.

Field monitoring teams oversaw technical, logistical and administrative aspects of

enumeration in each region. Further, independent observers, drawn from the

international community and national statistics offices across Africa monitored and

observed the 2019 census enumeration process.

1.7. Definition of Key Concepts

Household: Refers to a person or group of persons who reside in the same

homestead/compound but not necessarily in the same dwelling unit, have same

cooking arrangements, and are answerable to the same household head.

Group Quarters: For the purposes of this census, group quarters refer to persons

enumerated in collective living quarters such as army barracks and hostels in

learning institutions.


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Household Head: This is the most responsible/respected member of the household

(as at the census night) who makes key decisions in the household on a day to day

basis, and whose authority is recognized by all members of the household.

Dwelling Unit: This is a place of abode or residence occupied by one or more households, usually with a private entrance.

Enumeration Area (EA): This is a designated area with an average of 100 households, but may vary from 50 to 149 households depending on the population density, terrain, and/or vastness of the area concerned. An EA may be a village, group of villages or part of a village, and is so delineated to be conveniently covered by an enumerator.

De Facto Census: One that enumerates all persons depending on where they spend

(or are found on) the census night.

Age: The number of years/months that a person has lived as at the census reference

night

Area: The extent of a surface enclosed within a specified boundary, usually expressed

in square kilometres.

Density: Refers to number of persons per square kilometre, obtained by dividing the

enumerated persons by the size of the land area in a given area, expressed in square

kilometres.

Sex: Refers to the biological condition or characteristics of being male, female or

intersex.

1.8. Constraints and Challenges

• Boundary disputes in some of the administrative units slowed the pace of

mapping.

• Poor network connectivity in some areas hampered the real time transmission of

data to the central server.


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1.9. List of Counties and Sub-Counties COUNTY

CODE

COUNTY NAME SUB-COUNTY

CODE

SUB-COUNTY

NAME

COUNTY

CODE


CODE

SUB-COUNTY

NAME

1 MOMBASA 101 CHANGAMWE 12 MERU 1201 BUURI EAST1 MOMBASA 102 JOMVU 12 MERU 1202 BUURI WEST1 MOMBASA 103 KISAUNI 12 MERU 1203 IGEMBE CENTRAL1 MOMBASA 104 LIKONI 12 MERU 1204 IGEMBE NORTH1 MOMBASA 105 MVITA 12 MERU 1205 IGEMBE SOUTH1 MOMBASA 106 NYALI 12 MERU 1206 IMENTI NORTH2 KWALE 201 KINANGO 12 MERU 1207 IMENTI SOUTH2 KWALE 202 LUNGA LUNGA 12 MERU 1208 MERU CENTRAL2 KWALE 203 MATUGA 12 MERU 1209 TIGANIA CENTRAL2 KWALE 204 MSAMBWENI 12 MERU 1210 TIGANIA EAST2 KWALE 205 SAMBURU 12 MERU 1211 TIGANIA WEST3 KILIFI 301 CHONYI 13 THARAKA-NITHI 1301 IGAMBANG'OMBE3 KILIFI 302 GANZE 13 THARAKA-NITHI 1302 MAARA3 KILIFI 303 KALOLENI 13 THARAKA-NITHI 1303 MERU SOUTH3 KILIFI 304 KAUMA 13 THARAKA-NITHI 1304 THARAKA NORTH3 KILIFI 305 KILIFI NORTH 13 THARAKA-NITHI 1305 THARAKA SOUTH3 KILIFI 306 KILIFI SOUTH 14 EMBU 1401 EMBU EAST3 KILIFI 307 MAGARINI 14 EMBU 1402 EMBU NORTH3 KILIFI 308 MALINDI 14 EMBU 1403 EMBU WEST3 KILIFI 309 RABAI 14 EMBU 1404 MBEERE SOUTH4 TANA RIVER 401 TANA DELTA 14 EMBU 1405 MBEERE NORTH4 TANA RIVER 402 TANA NORTH 15 KITUI 1501 IKUTHA4 TANA RIVER 403 TANA RIVER 15 KITUI 1502 KATULANI5 LAMU 501 LAMU EAST 15 KITUI 1503 KISASI5 LAMU 502 LAMU WEST 15 KITUI 1504 KITUI CENTRAL6 TAITA/TAVETA 601 MWATATE 15 KITUI 1505 KITUI WEST6 TAITA/TAVETA 602 TAITA 15 KITUI 1506 KYUSO6 TAITA/TAVETA 603 TAVETA 15 KITUI 1507 LOWER YATTA6 TAITA/TAVETA 604 VOI 15 KITUI 1508 MATINYANI7 GARISSA 701 BALAMBALA 15 KITUI 1509 MIGWANI7 GARISSA 702 DADAAB 15 KITUI 1510 MUMONI7 GARISSA 703 FAFI 15 KITUI 1511 MUTITU7 GARISSA 704 GARISSA 15 KITUI 1512 MUTITU NORTH7 GARISSA 705 HULUGHO 15 KITUI 1513 MUTOMO7 GARISSA 706 IJARA 15 KITUI 1514 MWINGI CENTRAL7 GARISSA 707 LAGDERA 15 KITUI 1515 MWINGI EAST8 WAJIR 801 BUNA 15 KITUI 1516 NZAMBANI8 WAJIR 802 ELDAS 15 KITUI 1517 THAGICU8 WAJIR 803 HABASWEIN 15 KITUI 1518 TSEIKURU8 WAJIR 804 TARBAJ 16 MACHAKOS 1601 ATHI RIVER8 WAJIR 805 WAJIR EAST 16 MACHAKOS 1602 KALAMA8 WAJIR 806 WAJIR NORTH 16 MACHAKOS 1603 KANGUNDO8 WAJIR 807 WAJIR SOUTH 16 MACHAKOS 1604 KATHIANI8 WAJIR 808 WAJIR WEST 16 MACHAKOS 1605 MACHAKOS9 MANDERA 901 MANDERA WEST 16 MACHAKOS 1606 MASINGA9 MANDERA 902 BANISA 16 MACHAKOS 1607 MATUNGULU9 MANDERA 903 KOTULO 16 MACHAKOS 1608 MWALA9 MANDERA 904 LAFEY 16 MACHAKOS 1609 YATTA9 MANDERA 905 MANDERA CENTRAL 17 MAKUENI 1701 KATHONZWENI9 MANDERA 906 MANDERA EAST 17 MAKUENI 1702 KIBWEZI9 MANDERA 907 MANDERA NORTH 17 MAKUENI 1703 KILUNGU

10 MARSABIT 1001 LOIYANGALANI 17 MAKUENI 1704 MAKINDU10 MARSABIT 1002 MARSABIT CENTRAL 17 MAKUENI 1705 MAKUENI10 MARSABIT 1003 MARSABIT NORTH 17 MAKUENI 1706 MBOONI EAST10 MARSABIT 1004 MARSABIT SOUTH 17 MAKUENI 1707 MBOONI WEST10 MARSABIT 1005 MOYALE 17 MAKUENI 1708 MUKAA10 MARSABIT 1006 NORTH HORR 17 MAKUENI 1709 NZAUI10 MARSABIT 1007 SOLOLO 18 NYANDARUA 1801 KINANGOP11 ISIOLO 1101 GARBATULLA 18 NYANDARUA 1802 NYANDARUA SOUTH11 ISIOLO 1102 ISIOLO 18 NYANDARUA 1803 MIRANGINE11 ISIOLO 1103 MERTI 18 NYANDARUA 1804 KIPIPIRI


8

COUNTY

CODE


CODE

SUB-COUNTY

NAME

COUNTY

CODE


CODE

SUB-COUNTY

NAME

18 NYANDARUA 1805 NYANDARUA CENTRAL 28 ELGEYO/MARAKWET 2801 KEIYO NORTH18 NYANDARUA 1806 NYANDARUA WEST 28 ELGEYO/MARAKWET 2802 KEIYO SOUTH18 NYANDARUA 1807 NYANDARUA NORTH 28 ELGEYO/MARAKWET 2803 MARAKWET EAST19 NYERI 1901 TETU 28 ELGEYO/MARAKWET 2804 MARAKWET WEST19 NYERI 1902 KIENI EAST 29 NANDI 2901 CHESUMEI19 NYERI 1903 KIENI WEST 29 NANDI 2902 NANDI CENTRAL19 NYERI 1904 MATHIRA EAST 29 NANDI 2903 NANDI EAST19 NYERI 1905 MATHIRA WEST 29 NANDI 2904 NANDI NORTH19 NYERI 1906 NYERI SOUTH 29 NANDI 2905 NANDI SOUTH19 NYERI 1907 MUKURWE-INI 29 NANDI 2906 TINDERET19 NYERI 1908 NYERI CENTRAL 30 BARINGO 3001 BARINGO CENTRAL20 KIRINYAGA 2001 KIRINYAGA CENTRAL 30 BARINGO 3002 BARINGO NORTH20 KIRINYAGA 2002 KIRINYAGA EAST 30 BARINGO 3003 EAST POKOT20 KIRINYAGA 2003 KIRINYAGA WEST 30 BARINGO 3004 KOIBATEK20 KIRINYAGA 2004 MWEA EAST 30 BARINGO 3005 MARIGAT20 KIRINYAGA 2005 MWEA WEST 30 BARINGO 3006 MOGOTIO21 MURANG'A 2101 MURANG'A EAST 30 BARINGO 3007 TIATY EAST21 MURANG'A 2102 KANGEMA 30 BARINGO 3008 LAKE BARINGO21 MURANG'A 2103 MATHIOYA 31 LAIKIPIA 3101 LAIKIPIA CENTRAL21 MURANG'A 2104 KAHURO 31 LAIKIPIA 3102 LAIKIPIA EAST21 MURANG'A 2105 MURANG'A SOUTH 31 LAIKIPIA 3103 LAIKIPIA NORTH21 MURANG'A 2106 GATANGA 31 LAIKIPIA 3104 LAIKIPIA WEST21 MURANG'A 2107 KIGUMO 31 LAIKIPIA 3105 NYAHURURU21 MURANG'A 2108 KANDARA 32 NAKURU 3201 GILGIL22 KIAMBU 2201 GATUNDU NORTH 32 NAKURU 3202 KURESOI NORTH22 KIAMBU 2202 GATUNDU SOUTH 32 NAKURU 3203 KURESOI SOUTH22 KIAMBU 2203 GITHUNGURI 32 NAKURU 3204 MOLO22 KIAMBU 2204 JUJA 32 NAKURU 3205 NAIVASHA22 KIAMBU 2205 KABETE 32 NAKURU 3206 NAKURU EAST22 KIAMBU 2206 KIAMBAA 32 NAKURU 3207 NAKURU NORTH22 KIAMBU 2207 KIAMBU 32 NAKURU 3208 NAKURU WEST22 KIAMBU 2208 KIKUYU 32 NAKURU 3209 NJORO22 KIAMBU 2209 LARI 32 NAKURU 3210 RONGAI22 KIAMBU 2210 LIMURU 32 NAKURU 3211 SUBUKIA22 KIAMBU 2211 RUIRU 33 NAROK 3301 NAROK EAST22 KIAMBU 2212 THIKA EAST 33 NAROK 3302 NAROK NORTH22 KIAMBU 2213 THIKA WEST 33 NAROK 3303 NAROK SOUTH23 TURKANA 2301 KIBISH 33 NAROK 3304 NAROK WEST23 TURKANA 2302 LOIMA 33 NAROK 3305 TRANS MARA EAST23 TURKANA 2303 TURKANA CENTRAL 33 NAROK 3306 TRANS MARA WEST23 TURKANA 2304 TURKANA EAST 34 KAJIADO 3401 ISINYA23 TURKANA 2305 TURKANA NORTH 34 KAJIADO 3402 KAJIADO CENTRAL23 TURKANA 2306 TURKANA SOUTH 34 KAJIADO 3403 KAJIADO NORTH23 TURKANA 2307 TURKANA WEST 34 KAJIADO 3404 KAJIADO WEST24 WEST POKOT 2401 KIPKOMO 34 KAJIADO 3405 LOITOKITOK24 WEST POKOT 2402 POKOT CENTRAL 34 KAJIADO 3406 MASHUURU24 WEST POKOT 2403 POKOT NORTH 35 KERICHO 3501 BELGUT24 WEST POKOT 2404 POKOT SOUTH 35 KERICHO 3502 BURETI24 WEST POKOT 2405 WEST POKOT 35 KERICHO 3503 KERICHO EAST25 SAMBURU 2501 SAMBURU CENTRAL 35 KERICHO 3504 KIPKELION25 SAMBURU 2502 SAMBURU EAST 35 KERICHO 3505 LONDIANI25 SAMBURU 2503 SAMBURU NORTH 35 KERICHO 3506 SOIN SIGOWET26 TRANS NZOIA 2601 TRANS NZOIA WEST 36 BOMET 3601 BOMET EAST26 TRANS NZOIA 2602 TRANS NZOIA EAST 36 BOMET 3602 CHEPALUNGU26 TRANS NZOIA 2603 KWANZA 36 BOMET 3603 KONOIN26 TRANS NZOIA 2604 ENDEBESS 36 BOMET 3604 SOTIK26 TRANS NZOIA 2605 KIMININI 36 BOMET 3605 BOMET CENTRAL27 UASIN GISHU 2701 AINABKOI 37 KAKAMEGA 3701 BUTERE27 UASIN GISHU 2702 KAPSERET 37 KAKAMEGA 3702 KAKAMEGA CENTRAL27 UASIN GISHU 2703 KESSES 37 KAKAMEGA 3703 KAKAMEGA EAST27 UASIN GISHU 2704 MOIBEN 37 KAKAMEGA 3704 KAKAMEGA NORTH27 UASIN GISHU 2705 SOY 37 KAKAMEGA 3705 KAKAMEGA SOUTH27 UASIN GISHU 2706 TURBO 37 KAKAMEGA 3706 KHWISERO


9

COUNTY

CODE


CODE

SUB-COUNTY

NAME

COUNTY

CODE


CODE

SUB-COUNTY

NAME

37 KAKAMEGA 3707 LIKUYANI 43 HOMA BAY 4301 HOMA BAY37 KAKAMEGA 3708 LUGARI 43 HOMA BAY 4302 NDHIWA37 KAKAMEGA 3709 MATETE 43 HOMA BAY 4303 RACHUONYO NORTH37 KAKAMEGA 3710 MATUNGU 43 HOMA BAY 4304 RACHUONYO EAST37 KAKAMEGA 3711 MUMIAS EAST 43 HOMA BAY 4305 RACHUONYO SOUTH37 KAKAMEGA 3712 MUMIAS WEST 43 HOMA BAY 4306 RANGWE37 KAKAMEGA 3713 NAVAKHOLO 43 HOMA BAY 4307 SUBA NORTH38 VIHIGA 3801 EMUHAYA 43 HOMA BAY 4308 SUBA SOUTH38 VIHIGA 3802 VIHIGA 44 MIGORI 4401 AWENDO38 VIHIGA 3803 SABATIA 44 MIGORI 4402 KURIA EAST38 VIHIGA 3804 LUANDA 44 MIGORI 4403 KURIA WEST38 VIHIGA 3805 HAMISI 44 MIGORI 4404 NYATIKE39 BUNGOMA 3901 BUMULA 44 MIGORI 4405 RONGO39 BUNGOMA 3902 BUNGOMA CENTRAL 44 MIGORI 4406 SUNA EAST39 BUNGOMA 3903 BUNGOMA EAST 44 MIGORI 4407 SUNA WEST39 BUNGOMA 3904 BUNGOMA NORTH 44 MIGORI 4408 URIRI39 BUNGOMA 3905 BUNGOMA SOUTH 45 KISII 4501 ETAGO39 BUNGOMA 3906 CHEPTAIS 45 KISII 4502 GUCHA39 BUNGOMA 3907 KIMILILI 45 KISII 4503 GUCHA SOUTH39 BUNGOMA 3909 BUNGOMA WEST 45 KISII 4504 KENYENYA39 BUNGOMA 3910 TONGAREN 45 KISII 4505 KISII CENTRAL39 BUNGOMA 3911 WEBUYE WEST 45 KISII 4506 KISII SOUTH39 BUNGOMA 3912 MT ELGON FOREST 45 KISII 4507 KITUTU CENTRAL40 BUSIA 4001 BUNYALA 45 KISII 4508 MARANI40 BUSIA 4002 BUSIA 45 KISII 4509 MASABA SOUTH40 BUSIA 4003 BUTULA 45 KISII 4510 NYAMACHE40 BUSIA 4004 NAMBALE 45 KISII 4511 SAMETA40 BUSIA 4005 SAMIA 46 NYAMIRA 4601 BORABU40 BUSIA 4006 TESO NORTH 46 NYAMIRA 4602 MANGA40 BUSIA 4007 TESO SOUTH 46 NYAMIRA 4603 MASABA NORTH41 SIAYA 4101 SIAYA 46 NYAMIRA 4604 NYAMIRA NORTH41 SIAYA 4102 GEM 46 NYAMIRA 4605 NYAMIRA SOUTH41 SIAYA 4103 UGENYA 47 NAIROBI CITY 4701 DAGORETTI41 SIAYA 4104 UGUNJA 47 NAIROBI CITY 4702 EMBAKASI41 SIAYA 4105 BONDO 47 NAIROBI CITY 4703 KAMUKUNJI41 SIAYA 4106 RARIEDA 47 NAIROBI CITY 4704 KASARANI42 KISUMU 4201 KISUMU EAST 47 NAIROBI CITY 4705 KIBRA42 KISUMU 4202 KISUMU CENTRAL 47 NAIROBI CITY 4706 LANG'ATA42 KISUMU 4203 KISUMU WEST 47 NAIROBI CITY 4707 MAKADARA42 KISUMU 4204 SEME 47 NAIROBI CITY 4708 MATHARE42 KISUMU 4205 MUHORONI 47 NAIROBI CITY 4709 NJIRU42 KISUMU 4206 NYANDO 47 NAIROBI CITY 4710 STAREHE42 KISUMU 4207 NYAKACH 47 NAIROBI CITY 4711 WESTLANDS


10

CHAPTER 2: CENSUS RESULTS

2.1 Summary Findings 2.1.1 Sub-Locations with No Data A number of sub-locations had no enumerated population on the census night. Table

2.1 shows the specific sub-locations and reasons for no population.

Table 2. 1: Sub-locations with no People on the Census Night by Status/Reason

County Sub-Location Status/Reason

Makueni Tsavo East National Park National Park

Kiambu Aberdare Forest Forest Area

Turkana Parkati Population migrated in search of water

Nandi Nandi South Forest Forest Area

Nandi North Tinderet Forest Forest Area

Nandi Nandi South Forest Forest Area

Baringo Lake Bogoria Lake

Baringo Lake Baringo Lake

Nakuru Mau Forest Forest Area

Kericho Mau Forest Forest Area

Kericho Tinderet Forest Forest Area

Bomet Mau Forest Forest Area

Kakamega Kakamega East Forest Forest Area

2.1.2 Education The 2019 census collected data on formal and non-formal schooling in order to

determine the educational attainment of population aged 3 years and above. Tables

2.2, 2.3, 2.4, 2.5, 2.6a and 2.6b provide the distribution of population aged 3 years

and above by school attendance status, schooling level, highest level of education

reached and completed, disaggregated by sex, county and sub-county. Table 2.7

shows the distribution of population aged 15 years and above by main training

acquired and qualified for, by sex and county.

A total of 17.8 million individuals reported that they were at school/learning

institution; 11.6 million left school/learning institution after completion; 6.9 million

left school/learning institution before completion; and 7.1 million had never been to

school.

The data shows that 10.0 million people were attending primary school; 3.4 million

were attending secondary school while 3.3 million were attending pre-primary

school. Those attending middle level college/technical training education were about

500 thousand and those attending university education were 471 thousand. Majority


11

of respondents had attained primary education, followed by secondary education.

Persons with university education were 1.3 million.

2.1.3 Activity Status Information on the activity status for all individuals aged five years and above for the

seven days preceding the census reference night is presented in Tables 2.8a, 2.8b,

2.8c, 2.9a, 2.9b and 2.9c.

The results show that the economically active population was 22.3 million,

comprising the working (19.7 million) and those seeking work (2.6 million). Females

accounted for 50.2 per cent of the total working population. The proportion of males

in the urban areas that reported having worked was 50.4 per cent compared to 40.6

per cent of females. A total of 18.9 million individuals were outside the labour force

during the reference period. There were 10.1 million youth aged 18-34 years and

4.1 million youth aged 15-24 years in the labour force.

2.1.4 Housing Conditions and Amenities

The proportion of households owning the main dwelling unit they occupied was 61.3

per cent while those occupying rented/provided dwelling units were 38.7 per cent.

Majority (93.9 per cent) of the owned dwelling units were constructed, 3.3 per cent

were inherited and 2.8 per cent were purchased.

The 2019 KPHC data shows that 80.3 per cent of the households occupied dwelling

units that had iron sheet as the main roofing material followed by concrete/cement at

8.2 per cent. The dominant material used for wall construction was mud/cow dung

at 27.5 per cent followed by stone with lime/cement at 16.5 per cent. Dwelling units

with concrete walls accounted for 16.3 per cent of the total. The predominant floor

material was concrete/cement accounting for 43.7 per cent followed by earth/sand

floors at 30.0 per cent.

More than a third (34.2 per cent) of households in the country relied on piped water

as a source of drinking water. More than half (51.2 per cent) of households use

covered pit latrine as a sanitation facility. The most common mode of solid waste

disposal was burning in the open, used by 27.1 per cent of the households.

Firewood was the most commonly used type of cooking fuel reported by 55.1 per cent

of the households followed by Liquefied Petroleum Gas (LPG) at 23.9 per cent. Slightly

over half (50.4 per cent) of households reported using electricity mains as a source of

lighting fuel followed by solar (19.3 per cent).


12

2.1.5 Agriculture

Statistics on agriculture from Kenya Population and Housing Census (KPHC 2019) are

presented in Tables 2.19 to 2.24. Total agricultural land operated by households stood

at 10.3 million hectares, equivalent to 17.5 per cent of the total land area in the

country. Of the total enumerated households, 6.4 million were practicing agriculture.

Households growing crops were 5.6 million while those practicing irrigation were

369,679. In total, 5.1 million households were engaged in maize cultivation followed

by 3.6 million cultivating beans.

Livestock keeping was practiced by 4.7 million households while aquaculture and

fishing activities were practiced by 29,325 and 109,640 households, respectively.

2.1.6 Disability Questions on the six domains of disability (visual, hearing, mobility, cognition, self-care and communication) were asked of persons aged five years and above while that of albinism was administered to everyone.

Tables2.25 to 2.27 present information on disability. The results show that 918,270

people aged 5 years and above had a disability. More females (523,883) than males

(394,330) had disabilities. The common types of disability were mobility (385,417)

followed by visual (333,520). A total of 9,729 persons had albinism.

2.1.7 Religious and Ethnic Affiliation Tables 2.29 and 2.30 presents the distribution of the population by religious and

ethnic affiliation, respectively. The data shows that majority (85.5 per cent) of the

population are Christians with Protestants, Catholics and Evangelical churches

accounting for 33.4,20.6, and 20.4 per cent, respectively. Muslims accounted for 11

per cent of the entire population. The five most populous ethnic affiliations were

Kikuyu, Luhya, Kalenjin, Luo and Kamba while the five least populous were Dahalo,

El Molo, Konso, Gosha and Wayyu.

2.1.8 Information and Communication Technology (ICT) Information on ownership and usage of selected ICT equipment and services is

presented in Tables 2.31 to 2.34. The KPHC results show that 20,694,315 of

individuals aged 3 years and above owned a mobile phone. More females

(10,425,040) than males (10,268,651) owned a mobile phone.


13

The data also shows that 22.6 per cent of individuals aged 3 years and above used

internet while 10.4 per cent used a computer. The proportion of population aged 15

years and above who searched and bought goods and services online was 4.3 per cent.

2.1.9 Ownership of Household Assets A functional television set was the popular household asset owned by 40.7 per cent of

households, with households in urban areas accounting for a larger share (62.5 per

cent) compared to those in rural areas (26.9 per cent). Approximately 9 per cent of

households owned a motorcycle. A larger share of the rural households (10.8 per cent)

than urban (6.7 per cent) owned a motor cycle.

Table 2.2: Distribution of Population Age 3 Years and Above by School Attendance Status, Area of Residence, Sex, County and Sub-County

Total* Not Stated

Number Number per cent Number per cent Number per cent Number per cent Number per cent Number

KENYA 43,739,906 17,780,277 40.7 11,568,544 26.4 6,854,538 15.7 7,120,542 16.3 406,887 0.9 9,118

Rural 30,253,083 12,922,660 42.7 6,023,054 19.9 5,088,656 16.8 5,940,009 19.6 273,416 0.9 5,288

Urban 13,486,823 4,857,617 36.0 5,545,490 41.1 1,765,882 13.1 1,180,533 8.8 133,471 1.0 3,830

Male 21,574,077 9,040,318 41.9 5,910,664 27.4 3,172,382 14.7 3,223,856 14.9 222,301 1.0 4,556

Female 22,164,531 8,739,524 39.4 5,657,565 25.5 3,681,910 16.6 3,896,417 17.6 184,558 0.8 4,557

Intersex 1,298 435 33.5 315 24.3 246 19.0 269 20.7 28 2.2 5

MOMBASA 1,100,173 378,423 34.4 457,603 41.6 153,982 14.0 101,097 9.2 8,817 0.8 251

Male 552,476 189,490 34.3 243,173 44.0 74,382 13.5 40,253 7.3 5,043 0.9 135

Female 547,681 188,930 34.5 214,424 39.2 79,596 14.5 60,843 11.1 3,772 0.7 116

CHANGAMWE 121,334 39,032 32.2 58,097 47.9 16,205 13.4 6,940 5.7 1,048 0.9 12

Male 63,184 19,482 30.8 31,918 50.5 8,157 12.9 2,976 4.7 647 1.0 4

Female 58,150 19,550 33.6 26,179 45.0 8,048 13.8 3,964 6.8 401 0.7 8

JOMVU 149,699 51,892 34.7 64,235 42.9 19,430 13.0 13,416 9.0 698 0.5 28

Male 75,931 26,020 34.3 34,362 45.3 9,689 12.8 5,424 7.1 422 0.6 14

Female 73,765 25,872 35.1 29,872 40.5 9,739 13.2 7,992 10.8 276 0.4 14

KISAUNI 263,742 95,844 36.3 102,940 39.0 37,450 14.2 25,182 9.5 2,257 0.9 69

Male 131,351 48,136 36.6 54,063 41.2 18,051 13.7 9,748 7.4 1,315 1.0 38

Female 132,388 47,707 36.0 48,876 36.9 19,399 14.7 15,434 11.7 941 0.7 31

LIKONI 228,472 79,083 34.6 90,079 39.4 34,337 15.0 23,434 10.3 1,516 0.7 23

Male 115,784 39,336 34.0 49,230 42.5 16,522 14.3 9,784 8.5 897 0.8 15

Female 112,685 39,746 35.3 40,849 36.3 17,814 15.8 13,650 12.1 618 0.5 8

MVITA 138,927 46,714 33.6 54,731 39.4 18,229 13.1 17,745 12.8 1,441 1.0 67

Male 66,589 23,515 35.3 27,476 41.3 8,307 12.5 6,515 9.8 736 1.1 40

Female 72,336 23,198 32.1 27,255 37.7 9,922 13.7 11,229 15.5 705 1.0 27

NYALI 197,999 65,858 33.3 87,521 44.2 28,331 14.3 14,380 7.3 1,857 0.9 52

Male 99,637 33,001 33.1 46,124 46.3 13,656 13.7 5,806 5.8 1,026 1.0 24

Female 98,357 32,857 33.4 41,393 42.1 14,674 14.9 8,574 8.7 831 0.8 28

KWALE 783,189 334,612 42.7 152,178 19.4 98,811 12.6 192,001 24.5 5,418 0.7 169

Male 382,538 171,696 44.9 83,012 21.7 49,352 12.9 75,281 19.7 3,108 0.8 89

Female 400,636 162,911 40.7 69,162 17.3 49,457 12.3 116,716 29.1 2,310 0.6 80

KINANGO 84,534 38,765 45.9 9,817 11.6 9,969 11.8 25,594 30.3 372 0.4 17

Male 40,445 20,011 49.5 5,412 13.4 5,040 12.5 9,783 24.2 192 0.5 7

Female 44,088 18,753 42.5 4,405 10.0 4,929 11.2 15,811 35.9 180 0.4 10

LUNGA LUNGA 180,056 76,787 42.6 22,030 12.2 23,394 13.0 55,779 31.0 2,056 1.1 10

Male 87,893 39,663 45.1 12,198 13.9 12,070 13.7 22,798 25.9 1,158 1.3 6

Female 92,161 37,124 40.3 9,831 10.7 11,324 12.3 32,980 35.8 898 1.0 4

Don't Know County/ Sub-County

At School/ Learning Institution Left School/ Learning Institution

After Completion

Left School/ Learning Institution

Before Completion

Never Been to School/ Learning

Institution

14


Total* Not Stated




After Completion


Before Completion


Institution

MATUGA 177,675 76,734 43.2 40,378 22.7 22,561 12.7 37,190 20.9 771 0.4 41

Male 87,377 39,476 45.2 21,744 24.9 11,056 12.7 14,610 16.7 469 0.5 22

Female 90,296 37,257 41.3 18,633 20.6 11,505 12.7 22,580 25.0 302 0.3 19

MSAMBWENI 159,936 61,075 38.2 52,123 32.6 22,798 14.3 22,665 14.2 1,245 0.8 30

Male 80,181 30,868 38.5 28,037 35.0 11,099 13.8 9,381 11.7 777 1.0 19

Female 79,752 30,206 37.9 24,085 30.2 11,698 14.7 13,284 16.7 468 0.6 11

SAMBURU 180,988 81,251 44.9 27,830 15.4 20,089 11.1 50,773 28.1 974 0.5 71

Male 86,642 41,678 48.1 15,621 18.0 10,087 11.6 18,709 21.6 512 0.6 35

Female 94,339 39,571 41.9 12,208 12.9 10,001 10.6 32,061 34.0 462 0.5 36

KILIFI 1,323,664 605,776 45.8 282,538 21.3 175,199 13.2 250,280 18.9 9,634 0.7 237

Male 636,891 308,926 48.5 154,263 24.2 86,075 13.5 82,303 12.9 5,214 0.8 110

Female 686,754 296,841 43.2 128,273 18.7 89,122 13.0 167,972 24.5 4,420 0.6 126

CHONYI 57,246 28,875 50.4 8,612 15.0 7,410 12.9 12,060 21.1 289 0.5 -

Male 26,917 14,936 55.5 4,814 17.9 3,513 13.1 3,509 13.0 145 0.5 -

Female 30,328 13,938 46.0 3,798 12.5 3,897 12.8 8,551 28.2 144 0.5 -

GANZE 131,101 67,193 51.3 14,842 11.3 13,191 10.1 35,066 26.7 761 0.6 48

Male 60,552 34,222 56.5 7,843 13.0 6,804 11.2 11,272 18.6 391 0.6 20

Female 70,546 32,969 46.7 6,999 9.9 6,387 9.1 23,793 33.7 370 0.5 28

KALOLENI 176,734 80,964 45.8 32,710 18.5 20,914 11.8 40,720 23.0 1,369 0.8 57

Male 83,996 41,402 49.3 17,946 21.4 10,588 12.6 13,331 15.9 705 0.8 24

Female 92,733 39,559 42.7 14,764 15.9 10,326 11.1 27,388 29.5 664 0.7 32

KAUMA 20,821 10,969 52.7 3,354 16.1 1,753 8.4 4,517 21.7 228 1.1 -

Male 10,054 5,659 56.3 2,004 19.9 865 8.6 1,421 14.1 105 1.0 -

Female 10,767 5,310 49.3 1,350 12.5 888 8.2 3,096 28.8 123 1.1 -

KILIFI NORTH 162,990 72,834 44.7 40,268 24.7 24,984 15.3 23,855 14.6 1,040 0.6 9

Male 78,763 36,930 46.9 21,544 27.4 12,190 15.5 7,498 9.5 597 0.8 4

Female 84,225 35,902 42.6 18,724 22.2 12,794 15.2 16,357 19.4 443 0.5 5

KILIFI SOUTH 187,663 76,984 41.0 53,927 28.7 28,002 14.9 26,646 14.2 2,092 1.1 12

Male 91,863 39,007 42.5 29,022 31.6 13,465 14.7 9,225 10.0 1,137 1.2 7

Female 95,799 37,977 39.6 24,904 26.0 14,537 15.2 17,421 18.2 955 1.0 5

MAGARINI 174,553 86,722 49.7 24,896 14.3 22,469 12.9 39,884 22.8 562 0.3 20

Male 84,429 44,425 52.6 14,412 17.1 11,450 13.6 13,822 16.4 307 0.4 13

Female 90,124 42,297 46.9 10,484 11.6 11,019 12.2 26,062 28.9 255 0.3 7

MALINDI 301,205 132,098 43.9 76,156 25.3 43,748 14.5 46,878 15.6 2,241 0.7 84

Male 146,545 67,256 45.9 41,483 28.3 21,034 14.4 15,451 10.5 1,282 0.9 39

Female 154,653 64,841 41.9 34,672 22.4 22,712 14.7 31,424 20.3 959 0.6 45

RABAI 111,351 49,137 44.1 27,773 24.9 12,728 11.4 20,654 18.5 1,052 0.9 7

Male 53,772 25,089 46.7 15,195 28.3 6,166 11.5 6,774 12.6 545 1.0 3

Female 57,579 24,048 41.8 12,578 21.8 6,562 11.4 13,880 24.1 507 0.9 4

15


Total* Not Stated




After Completion


Before Completion


Institution

TANA RIVER 284,605 95,997 33.7 32,815 11.5 29,062 10.2 125,160 44.0 1,445 0.5 126

Male 142,087 50,470 35.5 19,351 13.6 14,502 10.2 56,872 40.0 835 0.6 57

Female 142,516 45,527 31.9 13,464 9.4 14,560 10.2 68,287 47.9 609 0.4 69

TANA DELTA 99,792 38,308 38.4 11,589 11.6 10,687 10.7 38,778 38.9 384 0.4 46

Male 50,066 19,808 39.6 6,810 13.6 5,371 10.7 17,832 35.6 229 0.5 16

Female 49,726 18,500 37.2 4,779 9.6 5,316 10.7 20,946 42.1 155 0.3 30

TANA NORTH 105,495 28,681 27.2 10,250 9.7 7,843 7.4 57,968 54.9 724 0.7 29

Male 53,199 15,776 29.7 6,284 11.8 4,254 8.0 26,472 49.8 396 0.7 17

Female 52,294 12,905 24.7 3,966 7.6 3,589 6.9 31,495 60.2 327 0.6 12

TANA RIVER 79,318 29,008 36.6 10,976 13.8 10,532 13.3 28,414 35.8 337 0.4 51

Male 38,822 14,886 38.3 6,257 16.1 4,877 12.6 12,568 32.4 210 0.5 24

Female 40,496 14,122 34.9 4,719 11.7 5,655 14.0 15,846 39.1 127 0.3 27

LAMU 130,991 50,249 38.4 30,833 23.5 22,762 17.4 26,325 20.1 786 0.6 36

Male 69,111 25,969 37.6 18,933 27.4 11,830 17.1 11,888 17.2 472 0.7 19

Female 61,877 24,278 39.2 11,899 19.2 10,932 17.7 14,437 23.3 314 0.5 17

LAMU EAST 20,637 7,592 36.8 4,029 19.5 4,189 20.3 4,745 23.0 82 0.4 -

Male 10,805 3,866 35.8 2,599 24.1 2,164 20.0 2,112 19.5 64 0.6 -

Female 9,832 3,726 37.9 1,430 14.5 2,025 20.6 2,633 26.8 18 0.2 -

LAMU WEST 110,354 42,657 38.7 26,804 24.3 18,573 16.8 21,580 19.6 704 0.6 36

Male 58,306 22,103 37.9 16,334 28.0 9,666 16.6 9,776 16.8 408 0.7 19

Female 52,045 20,552 39.5 10,469 20.1 8,907 17.1 11,804 22.7 296 0.6 17

TAITA/TAVETA 312,593 116,381 37.2 118,731 38.0 47,998 15.4 28,128 9.0 1,286 0.4 69

Male 158,230 59,272 37.5 63,137 39.9 23,804 15.0 11,239 7.1 744 0.5 34

Female 154,357 57,108 37.0 55,594 36.0 24,190 15.7 16,888 10.9 542 0.4 35

MWATATE 76,078 28,635 37.6 27,675 36.4 12,851 16.9 6,765 8.9 143 0.2 9

Male 38,672 14,632 37.8 14,867 38.4 6,443 16.7 2,638 6.8 87 0.2 5

Female 37,404 14,002 37.4 12,808 34.2 6,408 17.1 4,126 11.0 56 0.1 4

TAITA 52,345 19,302 36.9 22,153 42.3 6,632 12.7 4,059 7.8 197 0.4 2

Male 26,495 9,800 37.0 11,852 44.7 3,242 12.2 1,503 5.7 98 0.4 -

Female 25,850 9,502 36.8 10,301 39.8 3,390 13.1 2,556 9.9 99 0.4 2

TAVETA 82,789 31,879 38.5 25,884 31.3 15,410 18.6 9,009 10.9 585 0.7 22

Male 42,548 16,342 38.4 13,891 32.6 7,929 18.6 4,016 9.4 361 0.8

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2019 Kenya Population and Housing Census: Volume IV › wp-content › uploads › 2020 › 06 › ... · 2019 Kenya Population and Housing Census: Volume IV viii FOREWORD The 2019