4&in BS I 1p '54' KENYA NATIONAL BUREAU OF STATISTICS ?15: Keeping you informed 26319 Mame] Peym? atlm anleJ Jaws mg .4 a 1.4% Analjytijcalj depart: an Urbanizatijgn V/Qllume A a?t 2019 Kenya Population and Housing Census ?Counting Our People for Sustainable Development and Devolution of Services? Analytical Report on Urbanization Volume IX KNBS KENYA NATIONAL BUREAU OF STATISTICS Ami: Jitokeze Uhesabike! April, 2022 Published by: Kenya National Bureau of Statistics Real Towers, Upper Hill PO. BOX 30266 - 00100 Nairobi, Kenya Tel: +254-20-3317583 +254-20-3317612 +254-20-3317586 Email: info@knbs.or.ke directorgeneral@knbs.or.ke Facebook: @Kenya National Bureau of Statistics Twitter: Website: 2022 Kenya National Bureau of Statistics ISBN: 978-9914-9986-3-4 Published 2022 All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording or other electronic or mechanical methods, without the prior written permission of the Bureau except in the brief quotations embodied in reviews and certain other non-commercial uses permitted by the copyright laws Table of Contents Table of Contents i List of Tables List of Figures iv List of Abbreviations Foreword Vi Acknowledgement Vii Urbanization at a Glance Executive Summary ix Chapter 1: Introduction 1 1.1. Background Information- 1 1.2. Objectives of the 2019 Census 1 1.3. Overview of Analytical Report on Urbanization 2 1.4. Methodology 3 Definition of Terms and Key Concept 4 Chapter 2: Levels and Trends in Urbanization 6 2.1. Urbanization Trends in Kenya 6 2.2. Population by Urban Centres 6 2.3. Population of Urban Centres by Population Size Category 7 2.4. Population of Nairobi City 9 2.5. Population of Mombasa 9 2.6. Population of Nairobi City Region 10 2.7. Urban Population by County 13 2.8. Urban Primacy in Kenya 15 Chapter 3: Demographic and Socio-Economic Characteristics of the Urban Population 16 3.1. Urban Population by Age and Sex 16 3.2. Urban Population by Education Status 17 3.3. Urban Population by Economic Activity 19 3.4. Urban Population Living with Disability 21 Chapter 4: Housing Conditions and Amenities of the Urban Population 23 4.1. Tenure Status 23 4.2. Housing Conditions 24 4.3. Main Source of Water 26 4.4. Main Mode of Human and Solid Waste Disposal 28 4.5. Main Type of Cooking and Lighting Fuel 30 Chapter 5: Population of Urban Informal Settlements 33 5.1. Urban Informal Settlements Population 33 5.2. Economic Characteristics of Urban Informal Settlements Population 34 5.3. Housing Characteristics of Urban Informal Settlements 35 5.4. Main Source of Water in Urban Informal Settlements 35 5.5. Main Mode of Human and Solid Waste Disposal in Urban Informal Settlements 36 5.6. Main Type of Coking and Lighting Fuel in Urban Informal Settlements 36 Chapter 6: Summary of Key Findings and Recommendations 39 6.1. Summary of Key Findings 39 6.2. Recommendations 40 References 41 Appendices 42 Appendix 1: Questionnaires 42 Appendix 2: Population by Urban Centre, 20 19 48 Appendix 3: Population of Nairobi City by Location, 20 19 55 Appendix 4: Population of Mombasa by Location, 2019 57 Appendix 5: Contributors to the 2019 Kenya Population and Housing Census Monographs 58 ii List of Tables Table 1. 1: Summary of Census Counts in Kenya, 1897-2019 1 Table 2.1 Urbanization Trends in Kenya, 1948-2019 6 Table 2.2: Population by Major Urban Centres, 2019 7 Table 2.3 Urban Population by Size Category of Urban Centres, 1962-2019 7 Table 2.4: Population of Nairobi City, 1948-2019 9 Table 2.5: Population of Mombasa, 1948-2019 10 Table 2.6: Population of Nairobi City Region, 2019 11 Table 2.7: Urban Population by County, 2019 13 Table 3.1 Sex Ratios by Major Urban Centres, 1979-2019 17 Table 3.2: Highest Level of Education Completed for Population Aged 3 Years and Above by Major Urban Centres, 2019 18 Table 3.3: Economic Activity by Major Urban Centres, 2019 20 Table 3.4: Main Employer by Major Urban Centres, 2019 21 Table 3.5: Population Aged 5 Years and Above Living with Disability by Major Urban Centres, 2019 22 Table 3.6: Population of Street Persons by Urban Centres, 2019 22 Table 4.1: Tenure Status by Major Urban Centres, 2019 24 Table 4.2: Dominant Roof, Wall and Floor Material by Major Urban Centres, 2019 26 Table 4.3: Main Source of Water by Major Urban Centres, 2019 28 Table: 4.4: Main Mode of Human and Solid Waste Disposal by Major Urban Centres, 2019 30 Table 4.5: Main Type of Cooking and Lighting Fuel by Major Urban Centres, 2019 32 Table 5.1: Informal Settlements Population by Urban Centres, 2019 33 Table 5.2: Informal Settlements Population in Nairobi City, 2019 34 Table 5.3: Informal Settlements Population in Mombasa, 2019 34 Table 5.4 Economic Characteristics of Urban Informal Settlements Population, 2009 35 Table 5.5 Housing Characteristics of Urban Informal Settlements, 2009 35 List of Figures Figure 2.1: Spatial Distribution of Urban Centres by Category 8 Figure 2.2: Nairobi City Region, 2019 12 Figure 2.3: Per cent Urban Population by County, 2019 14 Figure 2.4: 11-City Primacy Index in Kenya, 1948-2019 15 Figure 3.1: Urban Population by Age and Sex, 2019 16 Figure 3.2 Ratios of Urban Population in Kenya, 1979-2019 17 Figure 3.3: Highest Level of Education Completed for Urban Population Aged 3+ Years, 2019 18 Figure 3.4: Proportion of Adult Population Having No Education by Major Urban Centres, 2019 19 Figure 3.5: Economic Activity of Urban Population in Kenya, 2019 19 Figure 3.6: Main Employer of Urban Working Population, 2019 21 Figure 4.1: Tenure Status in Urban Kenya, 2019 23 Figure 4.2: Dominant Roof Material in Urban Kenya, 2019 25 Figure 4.3: Dominant Wall Material in Urban Kenya, 2019 25 Figure 4.4: Dominant Floor Material in Urban Kenya, 2019 26 Figure 4.5: Main Source of Water in Urban Kenya, 2019 27 Figure 4.6: Main Mode of Human Waste Disposal in Urban Kenya, 2019 29 Figure 4.7: Main Mode of Solid Waste Disposal in Urban Kenya, 2019 29 Figure 4.8: Main Type of Cooking Fuel in Urban Kenya, 2019 31 Figure 4.9: Main Type of Lighting Fuel in Urban Kenya, 2019 3 1 Figure 5.1: Main Source of Water in Urban Informal Settlements, 2019 36 Figure 5.2: Main Mode of Human Waste Disposal in Urban Informal Settlements, 2019 37 Figure 5.3: Main Mode of Solid Waste Disposal in Urban Informal Settlements, 2019 37 Figure 5.4: Main Type of Cooking Fuel in Urban Informal Settlements, 2019 38 Figure 5.5: Main Type of Lighting in Urban Informal Settlements, 2019 38 iv AFDB AICS ASAL CBO CSPro DfID EA FBO GIS GPS ICT KENSUP KFI KNBS KPHC LPG LPG MDGs MTP NGOs ONS-UK SDGs SIDA SPSS UN UNDP UNECA UNFPA UNICEF UNRCO UNSD US USAID VIP WHO African Development Bank Italian Agency for Development Cooperation Arid and Semi-Arid Land Community-Based Organization Census and Survey Processing System Department for International Development Enumeration Area Faith-Based Organization Geographic Information System Global Positioning System Information Communication Technology Kenya Slum Upgrading Programme Keying From Image Kenya national Bureau of Statistics Kenya Population and Housing Census Liquefied Petroleum Gas Liquefied petroleum gas Millennium Development Goals Medium Term Plan Non-Governmental Organizations Office of National Statistics United Kingdom Sustainable Development Goals Swedish International Development Agency Statistical Package for the Social Sciences United Nations United Nations Development Programme United Nations Economic Commission for Africa United Nations Population Fund United Nations Children Fund United Nations Resident Coordinator's Office United Nations Statistical Division United States United States Agency for International Development Ventilation Improved Pit latrine World Health Organization Foreword The 2019 Kenya Population and Housing Census (KPHC) was conducted from the night of 24th/25th to 31St August 2019 and followed the United Nations principles and recommendations for conducting the 2020 round of censuses. The theme of the Census was ?Counting Our People for Sustainable Development and Devolution of Services?. This resonated very well with Kenya?s development agenda -Vision 2030 and the Big Four, as well as other regional and international development initiatives such as the Sustainable Development Goals (SDGs) and the African Union Agenda 2063. The main objective was to provide the Government and other stakeholders with essential information for evaluating policies and easing planning and budgeting processes. The first set of the census reports (basic volumes I-IV) were released in a record 6 months after enumeration. The second set of the census reports covers the thematic areas of: Fertility and Nuptiality; Mortality; Migration; Education and Training; Youth and Adolescents; Information and Communication Technology; Housing Conditions, Amenities and Household Assets; Gender Dimensions; Older and Vulnerable Population; Urbanization; Disability; Household and Family Dynamics; Labour Force Dynamics; Agriculture; Population Dynamics and Population Projections. This monograph presents information on levels, trends and patterns of urbanization with a View of providing useful data for formulating appropriate and sustainable policies on urbanization. As is the case in other Sub-Saharan countries, urbanization is inevitable and managing its emerging trends and patterns constitutes a challenge. The urban population has increased to 14.8 million people in 2019 from 12.0 million people in 2009. The proportion of urban population to the total population has, however, reduced from 31.3 per cent in 2009 to 31.2 per cent in 2019. The information in this monograph provides valuable programmatic evidence to policymakers for use in the formulation of policies and plans explicitly intended to achieve SDG targets. The report not only adds knowledge but also serves as a foundation for assessment, reporting and eventually monitoring achievement of SD Gs by 2030, Vision 2030, formulation of MTP IV, County Integrated Development Plans, and other sector-specific plans. Specifically, the evidence is expected to contribute immensely towards measuring and monitoring SD Gs numbers 6, 7 and 11 that are related to social sector outcomes with special focus on urbanization. On behalf of the Government, Iwish to thank the staff, management and Board of Directors of the Kenya National Bureau of Statistics as well as the authors for their contribution towards the preparation of this report. I further wish to extend special thanks to our development partners, especially UNFPA, UNICEF, UN?Women, WHO and UNDP under the coordination of UN Resident Coordinators? Office and all the other stakeholders who were involved in the process for their technical and financial support. HON (AMB) UKUR YATANI, EGH CABINET SECRETARY THE NATIONAL TREASURY AND PLANNING vi Acknowledgement The 2019 Kenya Population and Housing Census (KPHC) was implemented under the provisions of the Constitution of Kenya, 2010 and the Statistics Act, 2006. The census was the sixth to be conducted in Kenya since independence and the first that was fully digitized, where the latest technology was embraced. This monograph is among the set of 16 such reports, addressing various topical areas regarding the demographic, social, and economic profiles of the Kenyan population. The 2019 KPHC implementation process was accomplished through a concerted effort of various government ministries, departments, agencies, International and local organizations and individuals who assisted during preparation, collection, compilation, processing, analyzing and publishing the results. Kenya National Bureau of Statistics (KNBS), on behalf of the Government, takes this opportunity to sincerely thank all those who participated in the preparation of this report. The Bureau is indebted to all the organs of government, the private sector, and the general public for the overwhelming support and participation that led to the successful implementation of the 2019 Census. Special gratitude goes to United Nations Population Fund United Nations Entity for Gender Equality and the Empowerment of Women (UN Women); United Nations Children?s Fund United Nations Economic Commission for Africa World Health Organization (WHO) and United Nations Development Programme (UNDP) under the coordination of UN Resident Coordinators? Office African Development Bank Statistics Sweden,- Office of National Statistics, United Kingdom (ONS-UK) and Italian Agency for Development Cooperation (AICS) for their immense support. I also recognize the census personnel (coordinators, content and ICT supervisors, enumerators, Village elders and security) for the role they played in the overall success of the 2019 KPHC. 51mm XL MACDONALD G. OBUDHO, MBS DIRECTOR GENERAL KENYA NATIONAL BUREAU OF STATISTICS vii Urbanization at a Glance Urban population 14.8 million Population of Nairobi 4.3 million Population of ombasa 1.2 million Population of urban street persons 14,587 Population of urban informal settlements 1 million Number of urban centres 372 Urban seX ratio 98 Urban growth rate 2.10% Proportion of urban population to total population 31.20% Proportion of urban population living in urban informal settlements 6.90% Proportion of urban adult population with no education 13.20% Proportion of urban population working 45% Proportion of urban population seeking work 10.80% Proportion of urban population working in the informal sector 34.40% Proportion of urban population living with disability 1.40% Per cent of urban households living in own house 21.30% Per cent of urban households with access to improved source of water 78.90% Per cent of urban households with access to main sewer 24.60% Per cent of urban households with access to county government solid waste disposal services 15.30% Per cent of urban households with access to clean energy for cooking 55.30% Per cent of urban households with access to electricity for lighting 88.60% Executive Summary Based on the 2019 Kenya Population and Housing Census data, this Monograph provides data and information on the urban population in Kenya. It is divided into six chapters as follows. Chapter 1 provides an overview on census background, methodology and defines key concepts and terms. Chapter 2 contains urbanization trends in Kenya,- population by urban centres and population size category; population of Nairobi City, Mombasa and Nairobi City Region; urban population by county,- and urban primacy in Kenya. In chapter 3, there are selected characteristics of the urban population in terms of age and sex, education status, economic activity, population living with disability and population of street persons. Chapter 4 thereafter highlights selected housing characteristics of the urban population in terms of tenure status, housing conditions, main source of water, main mode of human and solid waste disposal and main Wpe of cooking and lighting fuel. Chapter 5 finally provides information on urban informal settlements population. Lastly, chapter 6 highlights the summary of key findings and recommendations. The urban population has increased from 12 million people recorded in 2009 to 14.8 million people in 2019. The proportion of urban population to the total population has, however, reduced from 31.9 per cent in 2009 to 31.2 per cent in 2019. Similarly, the urban growth rate has significantly dropped from a high of 7.9 per cent in 2009 to a low of 2.1 per cent in 2019. The Sex Ratio indicates a gradual reduction in the selective dominance of males in the urban centres. The proportion of unemployed urban population is relatively small, while the informal sector plays a significant role in providing urban employment. Most households in urban Kenya live in individual rental dwelling units with a large majority having access to improved sources of water and electricity for lighting. The proportion of urban households having access to main sewer, piped water in the house and county government solid waste management services is still low. Furthermore, more than half of the urban households use unclean sources of energy for cooking. The proportion of urban population living in informal settlements has significantly reduced from 15 per cent in 2009 to 6.9 per cent in 2019. The urban informal settlements population continue to be disproportionately concentrated in Nairobi. There seems to be no significant differences between the characteristics of urban informal settlements population with the general trends of Kenya?s urban population. However, most households in the urban informal settlements tend to live in dwelling units with non-durable wall materials they rely on water vendors and piped water from elsewhere rather than from individual connections) and use unclean energy sources for cooking. The monograph gives a wide range of recommendations that can be used to guide Kenya?s urban growth and development. Chapter 1: Introduction 1 .1 . Background Information- A population Census is a total process of collecting, compiling, evaluating, analysing and publishing or otherwise disseminating demographic, economic, and social data pertaining, at a specified time, to all persons in a country or in a well-delimited part of a country. It is Vital for effective national development planning because it provides detailed bench-mark data on all population characteristics. 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 defacto basis with the midnight of 24th/25th August as the reference point. The Censuses have been implemented under the United Nations (UN) Principles and Recommendations for conducting Population and Housing Censuses. Table 1.1 presents Census results since 1897. Table l. 1: Summary of Census Counts in Kenya, 1897-2019 Year Population (millions) 1897 2.5 1948 5.4 1962 8.6 1969 10.9 1979 15.3 1989 21.4 1999 28.5 2009 37.7 20 19 47.6 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. The theme for the Census was ?Counting Our Peoplefor Sustainable Development and Devolution of Services?. 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: 0 Population size, composition, and spatial distribution,- 0 Levels of fertility, mortality and migration; 0 Educational attainment,- 0 Household composition; 0 Rate and pattern of urbanization; 0 Size and deployment of the labour force; 0 Distribution of persons with disability; 0 Housing conditions and availability of household amenities; and 0 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 a geo-spatial database; and benchmark for agricultural Censuses surveys. 1 .3. Overview of Analytical Report on Urbanization Urbanization is inevitable and managing its trends and patterns has inherent challenges. The ideal scenario is to move from chaotic to sustainable urban centres and cities, provided that good policies and strategies are adopted, investments mobilized, stakeholder participation secured, good governance practiced and human development recognized. As such, there is need to support sustainable urban development with adequate and relevant data on urbanization. The Main Objective of the 2019 Kenya Population and Housing Census Analytical Report on Urbanization is to provide data and information on the urban population in Kenya. The specific objectives are: 1. To determine the Level and Trends of Urbanization in 2019. 2. To analyze the Demographic and Socio-Economic Characteristics of the Urban Population in 2019. 3. To determine the Housing Conditions and Amenities of the Urban Population in 2019. 4. To describe the Characteristics of Urban Informal Settlements Population in 2019. 5. To provide Global and National Sustainable Urban Development Indicators. Policies and Development Indicators Related to Urbanization Inadequate implementation of the national urban development policy in Kenya presents a major challenge in achieving sustainable urban development. Policies and strategies related to urban development have, for a long time, been formulated within the framework of broader national and or sectoral development plans and policies, as well as various Acts of Parliament. Kenya?s Vision 2030 aims to transform Kenya into a newly-industrializing, middle-income country providing a high quality of life to all its citizens in a clean and secure environment (Kenya 2007). The vision recognizes that Kenya is moving towards a predominantly urban population and should plan for high qualiW urban livelihoods. Part of the Vision?s goals are to achieve integrated regional and urban planning and management; increase access to safe water and sanitation in urban areas; facilitate access to adequate housing; and improve the lives of slum dwellers (Kenya 2008). Table 1.2 presents some of the Sustainable Development Goals (SDGs) indicators that can be derived from this Analytical Report. These are proportion of urban population living in informal settlements or inadequate housing; proportion of urban solid waste regularly collected (SDG 11) proportion of population using safely managed drinking water services; proportion of population using safely managed sanitation services (SDG 6) proportion of population with access to electricity; and proportion of population with primary reliance on clean fuels (SDG 7). Table 1.2: Related Sustainable Development Goals and Targets SD Targets Indicators Goal 1 1: Make cities and human settlements inclusive, safe, resilient and sustainable Ensure access for all to adequate, safe and affordable housing and basic services Proportion of urban population living in informal settlements or inadequate Reduce the adverse per capita environmental impact of cities, including by paying special attention to air qualiw and municipal and other waste management housing Proportion of urban solid waste regularly collected Goal 6: Ensure availability and sustainable manageme nt of water and sanitation for all Achieve universal and equitable access to safe and affordable drinking water for all Proportion of population using safely managed drinking water services Achieve access to adequate and equitable sanitation and hygiene for all Proportion of population using safely managed sanitation services Goal 7: Ensure access to affordable, reliable, sustainable and modern energy for all Ensure universal access to affordable, reliable and modern energy Proportion of population with access to electricity Proportion of population with primary reliance on clean fuels 1 .4. Methodology 1.4.1. 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?s history to use mobile technology in the capture and transmission of data for both cartographic mapping and enumeration. During mapping, the GPS coordinates for homesteads, households and other points of interests within the locality were collected using the mobile devices with an accuracy of plus or minus 5 Meters. The enumeration area (EA) maps were developed using Arc GIS Sofmare on a background of aerial photographs and satellite imageries that were not more than six months old from the date of the field cartographic data collection. The EA maps were then uploaded into the tablets assembled by two local universities to facilitate the 2019 Census enumeration exercise. 1.4.2. Recruitment and Training Recruitment of Census personnel who included supervisors (both content and ICT) and 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 .4.3. Enumeration The Census enumeration was preceded by enumeration area (EA) boundary identification and pre-enumeration listing of households in each EA for two days prior to the Census night. The pre- enumeration listing exercise helped in gauging the expected workload during the seven days of enumeration and also in monitoring the level of coverage as enumeration progressed. The actual enumeration took place from the night of 24th/25th August 2019 and ended on 31St August 2019. A mop-up exercise was conducted on 1St and 2nd September 2019. Special populations were strictly enumerated on the night of 24th/25th August 2019. The 2019 Census adopted the defacto approach where all persons within the boundaries of Kenya were enumerated 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. 1.4.4. Data Transmission and Storage Data collected by enumerators using mobile devices (tablets) were subsequently transmitted to a central server. The data were before transmission and backed up in off-site locations. 1 .4.5. Data Processing Editing of the Census data was guided by the United Nations Handbook on Population and Housing Census Editing. The data were processed using Stata and SPSS software's. 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 geopolitical units. 1 .4.6. Quality Assurance Quality assurance was integrated into 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 the 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. 1.5. Definition of Terms and Key Concept Informal Settlements: These are urban settlements characterized by poor structural quality of housing,- lack of formal basic services and infrastructure; and lack of securiW of tenure. In most cases, they are located in geographically and environmentally hazardous areas. Rural: This is a large and isolated part of an open or agricultural country with relatively low population concentrations and whose predominant economic activity is agriculture Urbanization: This is the process of concentration of a country?s national population into settlements designated as urban centres. Urban centre: This is a built-up and compact human settlement with a population of at least 2,000 people. An urban centre may be classified as a market centre, town, municipality or city. Urban centres are also service centres that provide goods and services to both the resident and surrounding population. As such, an urban centre may constitute some trading centres with less than 2,000 people. Household: Is a person or a group of persons who reside in the same homestead or compound but not necessarily in the same dwelling unit. They have the same cooking arrangement and are answerable to the same household head. For purpose of 2019 KPHC, households were categorized into conventional and non-conventional. Conventional were the ordinary households while non-conventional households referred to people live together but cannot be said to belong to ?ordinary? households. Examples were students in boarding schools and colleges, hospital in- patients, people in police cells, guests in hotels, or prison inmates, outdoor sleepers, nuns, brothers in a monastery and other religious organizations with some institution-like living arrangements. Chapter 2: Levels and Trends in Urbanization This Chapter presents the levels and trends in urbanization in Kenya. The Chapter provides data and information on urbanization trends in Kenya; population by urban centres; population of urban centres by population size category; population of Nairobi City; population of Mombasa; population of Nairobi Region; urban population by county; and urban primacy in Kenya. 2.1 . Urbanization Trends in Kenya Table 2.1 shows the trends of urbanization in Kenya between 1948 and 2019. The number of urban centres has increased from 17 in 1948 to 139 in 1989 and to 372 in 2019. As the number of urban centres increased, the population of Kenyans living in the urban centres also increased from 285,000 in 1948 to 3.8 million in 1989 and to 14.8 million in 2019. The proportion of Kenyans living in urban centres is still relatively low. The percentage of urban population to the total population has gradually increased from 5.3 per cent in 1948 to 18.1 per cent in 1989 and to 31.2 per cent in 2019. In all censuses, the urban population has been disproportionately concentrated in Nairobi and Mombasa. The growth of urban centres both in numbers and population accelerated immediately after independence, when Africans were allowed to migrate to towns without any legal and administrative restrictions. This explains the high urban growth rates in 1969, 1979 and 1989, largely a consequence of rural-urban migration. As the population become more urbanized, the urban growth rate declined from a peak of 7.7 per cent in 1979 to 2.1 per cent in 2019. However, in 2009 the urban growth rate rose to a high of 7.9 per cent. Table 2.1 Urbanization Trends in Kenya, 1948-2019 Year Total population No. of urban centres Urban population Percentage 0f urban to total Intercens al growth population rate (per cent) 1948 5,407,599 17 285,000 5.3 - 1962 8,636,263 34 747,651 8.7 6.9 1969 10,956,501 47 1,076,908 9.8 5.2 1979 15,327,061 91 2,315,696 15.1 7.7 1989 21,443,636 139 3,878,697 18.1 5.2 1999 28,485,869 180 5,429,790 19.1 3.4 2009 37,724,850 230 12,023,570 31.9 7.9 2019 47,564,299 372 14,835,425 31.2 2.1 2.2. Population by Urban Centres In 2019, there were 372 urban centres in Kenya. Table 2.2 presents the population of major urban centres with a population size of more than 150,000 people in 2019. These urban centres contribute more than half of the total urban population of Kenya in 2019. Nairobi City leads the urban hierarchy with a population of 4.3 million people, representing 29.6 per cent of the total urban population in Kenya. Nairobi City is followed by Mombasa with a population of 1.2 million people. Mombasa is followed by Nakuru, Ruiru, Eldoret, Kisumu and Kikuyu each with a population of more than 300,000 people. The other major urban centres in the urban hierarchy are Thika, Naivasha, Karuri, Ongata Rongai, Kitale, Juja and Kitengela. Seven of the 14 major urban centres, namely Ruiru, Kikuyu, Thika, Karuri, Ongata Rongai,]uja and Kitengela are in close proximiw to Nairobi City. Table 2.2: Population by Major Urban Centres, 2019 Percentage of total Urban centre Population urban population Nairobi City 4,395,749 29.6 Mombasa 1,208,112 8.1 Nakuru 570,614 3.8 Ruiru 490,035 3.3 Eldoret 475,659 3.2 Kisumu 397,853 2.7 Kikuyu 323,825 2.2 Thika 251,360 1.7 Naivasha 198,399 1.3 Karuri 194,289 1.3 Ongata Rongai 172,516 1.2 Kitale 162, 1 54 1.1 Juja 155,999 1.1 Kitengela 154,327 1 Appendix 2 presents Population by Urban Centres in 2019 2.3. Population of Urban Centres by Population Size Category Table 2.3 demonstrates that the numbers and populations of small and medium-size urban centres have shown an upward trend over the years and is expected to do so in future. Mombasa has joined Nairobi City in the category of urban centres with a population of over 1 million people. Small urban centres are considered to be those with a population of less than 10,000 people, while medium-size urban centres have a population of more than 10,000 but less than 100,000 people. In 2019, the number of small urban centres increased to 160 with a total population of 753,873 people. On the other hand, the number of medium-size urban centres rose to 126 with a total population of 3.8 million people. Figure 2.1 shows the spatial distribution of urban centres in 2019 by population size category. Table 2.3 Urban Population by Size Category of Urban Centres, 1962-2019 Category of urban centres bypopulation size Year 1 million and over 100,000-999,999 10,000-99,999 2,000-9,999 No. Population No. Population No. Population No. Population 1962 0 0 2 523,075 5 105,712 27 118,864 1969 2 756,359 9 79,267 36 153,282 1979 6 1,321,566 24 717,855 64 276,275 1989 1 1,324,570 5 1,046,588 40 1,080,726 93 426,813 1999 1 2,083,509 4 1,214,927 62 1,508,180 113 623,174 2009 1 3,109,861 22 4,617,114 97 3,665,486 110 631,109 2019 2 5,603,861 20 4,533,035 126 3,856,072 160 753,873 No.2 Numb er of urban centres Ethiopia Ma rsabit West Pokot Isiolo . Somalla Garissa Tana River Tanzania 130 I Kilifi Taita 1TaQeta I Indian Ocean Number - 2010 - 9999 10000 - 99999 0 100000 - 999999 . 1000000 - 4395749 County Boundary Water Bodies Figure 2. 1: Spatial Distribution of Urban Centres by Category 2.4. Population of Nairobi City Nairobi was first established injune 1899 as a Transportation and Administrative Centre. Nairobi grew to become a Township in 1900 and the Capital of Kenya in 1905. In 1919, Nairobi was elevated into a Municipality and finally, in March 1950, Nairobi became a City. According to Table 2.4, Nairobi?s Population has increased from 119,000 people in 1948 to 1.3 million in 1989 and to 4.3 million in 2019. The emerging importance of small and medium-size urban centres has reduced Nairobi?s dominance in the urban hierarchy. As such, Nairobi?s share of the total urban population declined from a high of 47 per cent in 1969 to 29.6 per cent in 2019. Nairobi?s growth rate increased considerably after independence because of its attractiveness to African migrants. The growth rate increased from 4.6 per cent in 1962 to 12.2 per cent in 1969. However, from 1979 to 2019, Nairobi has been growing at a sustained and constant rate of a little less than 5 per cent a year. In 2009, Nairobi?s population growth rate reduced further to 3.5 per cent. Table 2.4: Population of Nairobi City, 1948?2019 Nairobi City population Percentage of total Intercensal growth Year (?000) urban population rate (per cent) 1948 119 41.7 1962 227 33.8 4.6 1969 506 47 12.2 1979 828 35.7 4.9 1989 1,325 34.1 4.7 1999 2,083 38.4 4.5 2009 3,100 25.9 3.8 2019 4,396 29.6 3.5 Appendix 3 presents Population of Nairobi City by Location in 2019 Administratively, Nairobi City has 11 Administrative Sub-Counties (Dagoretti, Embakasi, Kamukunji, Kasarani, Kibra, Lang'ata, Makadara, Mathare, Njiru, Starehe and Westlands) with 73 administrative locations. Mukuru Kwa Njenga Location has the highest population of 242,879 people. It is followed by Embakasi (178,313), Kariobangi South (142,625), Umoja (140,181), Kasarani (138,098), Savannah (124,848), Kayole (118,713), Imara Daima (118,511), Kangemi (116,700) and Huruma (113,009). These administrative Locations are located in the densely populated sub-counties in the East of Nairobi namely,- Embakasi, Kasarani, Mathare and Njiru sub-counties. However, Kangemi is in Westlands Sub-County. 2.5. Population of Mombasa Mombasa is a Coastal as well as a Port ciW. It is the oldest and second largest city in Kenya. According to Table 2.5, the population of Mombasa has increased from 84,000 people in 1948 to 462,000 in 1989 and to 1.2 million in 2019. Mombasa has joined Nairobi City in the category of urban centres with a population of over 1 million people. Like Nairobi, Mombasa?s share of the total urban population declined from a high of 29.7 per cent in 1948 to 8.1 per cent in 2019. The growth rate has also shown a decreasing trend from 5.5 per cent to 2.7 per cent in 2019. Administratively, Mombasa has 6 administrative sub-counties (Changamwe, Jomvu, Kisauni, Likoni, Mvita and Nyali) with 22 administrative locations. The administrative locations with more than 100,000 people are Kisauni (168,139), Likoni (163,245), Bamburi (123,731) and Miritini 101,988). These locations are located in Kisauni,]omvu and Likoni sub counties of Mombasa. Table 2.5: Population of Mombasa, 1948-2019 Mombasa population Percentage of total Intercensal growth Year (?000) urban population rate (per cent) 1948 84 29.7 1962 180 24 5.5 1969 247 22.9 4.5 1979 341 14.7 3.2 1989 462 1 1.9 3 1999 665 12.4 3.7 2009 925 7.7 3.4 2019 1,208 8.1 2.7 Appendix 4 presents Population of Mombasa by Location in 2019 2.6. Population of Nairobi City Region Table 2.6 presents the population of Nairobi City Region. The spatial extent of Nairobi City Region is geographically defined to include Nairobi City and the neighbouring parts of Kiarnbu, Machakos, Muranga, Makueni and Kajiado counties (Figure 2.2). The urban population of Nairobi Region is, therefore, the total population of all the urban centres in the region. These are Nairobi City; Githiga, Githunguri, lkinu, Juja, Karuri, Kawaida, Kiambu, Kikuyu, Limuru, Ngewa, Rironi, Ruiru, Thika, Ting'ang?a (in Kiambu County) Athi River, Githunguri, Kangundo, Kathiani, Machakos, Makutano (Kyumbi), Mlolongo, Nguluni, Oldonyo Sabuk, Tala (in Machakos County) Muranga (in Thika County) Salama (in Makueni County) Isinya, Kajiado, Kiserian, Kitengela, Ngong, and Ongata Rongai (in Kajiado County). As such, the total urban population of Nairobi City Region is 7 million people. 10 Table 2.6: Population of Nairobi City Region, 2019 County Spatial extent Total Population Urban population Nairobi City Nairobi City County 4,395,749 4,395,749 Kiambu Limuru, Kikuyu, Kabete, Kiambaa, Kiambu, Githunguri, Ruiru, Juj a, Thika West and Thika East Sub-Counties 2,050,068 1,688,963 Machakos Athi River, Kalama, Machakos, Kathiani, Kangundo and Matungulu Sub- Counties 918,780 387,979 Muranga Samuru Division in Gatanga Sub-County 8,910 2,459 Makueni Malili Division in Mukaa Sub-County 41,616 1,905 Kaj iado Kajiado North and Isinya Sub-Counties,- Central and Enkorika Divisions in Kajiado Central Sub-County; Mashuru Division in Mashuru Sub-County,- and Kiserian and Kibiko Locations in Kajiado West Sub?County 645,560 540,501 TOTAL 8,060,683 7,017,556 11 Murang'a Kiambu Nairobi City Kajiado County Boundary - Nairobi City County - Nairobi City Region - Metropolitan Counties Machakos Figure 2.2: Nairobi City Region, 20 19 12 2.7. Urban Population by County Table 2.7 shows the urban population of the 47 counties in Kenya as well as the proportion of urban population to the county population (Figure 2.3). Demographic, social, economic and political variables have impacted greatly on urbanization process in Kenya, resulting in varied county urbanization levels and trends. Nairobi and Mombasa are the most urbanized counties in Kenya, with their entire population being urban. Nairobi and Mombasa are followed by Kiambu (70.6% urban) and Kajiado (55.7% urban). On the other hand, Kitui, Elgeyo-Marakwet and Bomet are the least urbanized counties each with less than 5 per cent urban population. Table 2.7: Urban Population by County, 2019 Percentage of Percentage of County Urban urban to County Urban urban to county Population county Population population population Nairobi City 4,395,749 100 Kwale 126,414 14.6 Mombasa 1,208,112 100 Busia 113,731 12.7 Kiambu 1,705,921 70.6 Embu 75,919 12.5 Kajiado 622,533 55.7 Kisii 151,395 12 Nakuru 1,046,938 48.4 Bungoma 190,096 11.4 Isiolo 125,645 46.9 Baringo 75,288 11.3 Uasin Gishu 510,146 43.9 Murang'a 118,436 11.2 Kisumu 440,788 38.2 Kericho 93,506 10.4 Mandera 270,444 31.2 Nyandarua 66,533 10.4 Machakos 413,953 29.1 Homabay 113,069 10 Taita-Taveta 93,764 27.5 Kakamega 185,318 9.9 Lamu 39,489 27.4 Vihiga 58,376 9.9 Kilifi 393,804 27.1 Meru 138,887 9 Garissa 210,850 25.1 Narok 100,327 8.7 Tana River 78,000 24.7 Siaya 85,371 8.6 Laikipia 127,355 24.6 Tharaka-Nithi 32,739 8.3 Marsabit 107,239 23.3 Nyamira 50,131 8.3 Waj ir 177,148 22.7 Makueni 77,067 7.8 Kirinyaga 136,218 22.3 Nandi 59,479 6.7 Nyeri 150,739 19.9 West Pokot 31,839 5.1 Trans Nzoia 178,711 18 Kitui 54,017 4.8 Elgeyo? Turkana 140,741 15.2 20,573 4.5 Marakwet Samburu 47,131 15.2 Bomet 27,966 3.2 Migori 167,530 15 13 Ethiopia Isiolo Tanzania Percent I 30?15 116-29 :130?45 46-60 =61-100 7 County Boundary 0 65 130 Water Bodies I I 260 Km Somalia Indian Ocean Figure 2.3: Per cent Urban Population by County, 2019 14 1.22 Primacy Index 1.09 0.89 0.81 1948 1962 1969 1979 0.94 1989 0.99 1999 1.03 0.98 2009 2019 75+ 70 - 74 65 - 69 60 - 64 55 - 59 50 - 54 45 - 49 40 - 44 35 - 39 30 - 34 25 - 29 20 - 24 15 - 19 10 - 14 5-9 0-4 1,500,000 1,000,000 500,000 Male Female 500,000 1,000,000 1,500,000 other hand, those with very low sex ratios are Sega (78), Migwani (77), Kijabe (77), Ragengni (76), Holo (76), Kwisero (74) and Kibingoti (721979 1989 1999 2009 I 2019 Figure 3.2 Sex Ratios of Urban Population in Kenya, 1979?20 19 Table 3.1 Sex Ratios by Major Urban Centres, 1979-2019 Urban centre 1979 1989 1999 2009 2019 Nairobi 138 132 115 104 99 Mombasa 121 125 117 106 102 Nakuru 123 116 105 100 97 Ruiru 135 136 107 100 95 Eldoret 134 122 108 101 99 Kisumu 104 108 102 97 96 Kikuyu 118 113 96 94 Thika 136 122 111 101 96 Naivasha 142 108 102 101 100 Karuri 100 99 95 Ongata Rongai 122 92 97 Kitale 123 119 101 99 Juja 103 98 Kitengela 104 96 ata not available /Appendix 2 provides the sex ratios for all urban centres in 2009 3.2. Urban Population by Education Status Figure 3.3 presents the proportion of urban population aged 3 years and above who have completed various levels of education. Educational attainment is a good indicator of socio- economic development and the capacity of a population to participate in development activities. Ideally, it is an index that re?ects the stock of highly educated and skilled labour force in a country. more than half of the population under consideration had attained secondary education and above, while 7.8 per cent had not attained any level of education. Table 3.2 presents the highest level of education completed for population aged 3 years and above by major urban centres. There is no significant variation between these urban centres. 17 Percentage of Urban Population Aged 3+ Years 37.6 40 35 31.5 30 25 20 15 11.9 7.8 10 7.0 3.7 5 0 None Pre-Primary Primary Secondary Middle Level Training University Percentage of Adult Urban Population 15 13.6 10 6.7 7.9 7.7 5.1 4.4 5 7.1 6.8 5.9 5.7 4.5 6.3 4.9 0 Nairobi City Mombasa Nakuru Ruiru Eldoret Kisumu Kikuyu Thika Karuri Naivasha Ongata Rongai Juja Kitengela Percentage of Urban Population Aged 5+ Years 50 45 44.1 45 40 35 30 25 20 15 10.8 10 5 0 Working Seeking work/No work available Persons outside the labour force Table 3.3: Economic Activity by Major Urban Centres, 20 19 Seeking Persons work 0 Working outside the work Urban centre labour force available (Percentage ofpopulation aged 5+ years) Nairobi City 47.2 11.4 41.4 Mombasa 40.1 14.1 45.8 Nakuru 46.6 8.1 45.3 Ruiru 50.1 9.6 40.3 Eldoret 42.9 10.3 46.8 Kisumu 42.7 8.2 49.1 Kikuyu 52.8 8.5 38.7 Thika 49.3 8.9 41.8 Naivasha 51.7 7.6 40.8 Karuri 51 10.1 38.9 Ongata Rongai 46.1 10.8 43.1 Kitale 42 7.8 50.2 Juja 48.2 10.2 41.6 Kitengela 49.1 13.7 37.2 A further analysis of the working population reveals that the private sector is the major employer of 43.4 per cent of the working urban population (Figure 3.6). This is followed by the informal sector, employing 34.4 per cent of the working urban population. This implies that the informal sector contributes a significant proportion to the employed population in urban centres. Employment in the public sector is very minimal at 10.2 per cent of the working urban population. Engagement in agricultural activities, be it in an urban centre or in the rural areas, is emerging as an important livelihood source and economic activity in urban Kenya. Those engaged in agricultural activities were 11.9 per cent of the working urban population. Several empirical studies Show that an increasing number of the urban poor in sub-Saharan Africa depend on urban farming as well as rural livelihood sources rural farming). Table 3.4 presents main employer by major urban centres. Nairobi, Mombasa, Naivasha and Kitengela have more than half of their working population employed in the private sector. Ruiru and Kisumu have relatively higher proportion of working population employed in the informal sector. Nakuru, Eldoret, Kikuyu and Kitale have more than 15 per cent of their working population engaged in agricultural activities. 20 Percentage of Urban Working Population 50 43.4 40 34.4 30 20 11.9 10.2 10 0 Public sector Public sector Private sector Private sector Informal sector Informal sector Small scale agriculture/ pastrolist activities Small scale agriculture/ pastrolist activities Table 3.5: Population Aged 5 Years and Above Living with Disability by Major Urban Centres, 2019 Percentage of . Population population Populatlon Urban centre living with aged 5+ years aged 5+ years disability livingwith disability KENYA (Urban) 1 2,787,247 179,344 1.4 Nairobi City 3,813,745 42,620 1.1 Mombasa 1,043,429 14,226 1.4 Nakuru 492,027 7,564 1.5 Ruiru 428,020 5,537 1.3 Eldoret 409,536 5,371 1.3 Kisumu 341,285 8,138 2.4 Kikuyu 285,100 5,577 2 Thika 216,580 3,024 1.4 Naivasha 168,978 2,394 1.4 Karuri 170,389 2,898 1.7 Ongata Rongai 150,462 1,767 1.2 Kitale 138,647 1,984 1.4 Juja 136,533 1,952 1.4 Kitengela 132,724 951 0.7 3.5 Population of Street Persons in Urban Centres Street persons are a social concern in major urban centres. Table 3.6 presents the population of street persons by major urban centres. According to the 2019 Kenya Population and Housing Census data, Kenya had a total of 14,587 street persons in urban centres. Nairobi and Mombasa have higher numbers of street persons. It is also notable that in all the urban centres, there are more male street persons than female. Table 3.6: Population of Street Persons by Urban Centres, 2019 Total Male Female KENYA (Urban) 14,587 13,076 1,507 Nairobi City 6,743 6,062 679 Mombasa 1,809 1,579 230 Eldoret 637 586 5 1 Nakuru 343 304 39 Kitale 276 272 4 Kisumu 267 222 45 Ruiru 235 205 30 Kisii 226 2 1 5 1 1 Ahero 172 81 91 Kakamega 158 157 1 Lodwar 15 1 137 14 Meru 146 141 5 Kitengela 140 116 24 Ngong 133 129 Nanyuki 1 12 106 Thika 1 12 105 Ongata Rongai 112 92 20 22 Rented -… 0.3 Rented - Individual 70.3 Rented -… 5.2 Rented - Local Authority 1.2 Rented - Government 1.7 Own House 21.3 0 20 40 Percentage of Households 60 80 Table 4.1: Tenure Status by Major Urban Centres, 2019 Rented Parastatal/ Own House Local Individual Urban centre Government Authority Company rental units (Percentage ofhouseholds) Nairobi City 9.3 1.9 1.6 7.5 79.3 Mombasa 21 - 0.3 3.3 75.4 Nakuru 35.8 0.4 2.6 - 61.2 Ruiru 57.7 3.1 0.7 1 37.5 Eldoret 14 - 0.3 1 84.7 Kisumu 17.7 - - 0.3 82 Kikuyu 32.9 2.7 0.1 0.1 63.9 Thika 38.2 - 8.6 - 53.2 Naivasha 29 0.1 1.8 1.8 67.2 Karuri 25 1.2 - 4.4 69.3 Ongata Rongai 37.6 0.8 - - 53.7 Kitale 52.3 0.4 0.4 1.4 45.5 Juja 54.3 0.3 - 2.9 42 Kitengela 26.1 2.4 1.2 1.9 68.3 The percentages exclude housing rented or provided from FB 0, NGO, Church/ Temple/ Mosque 4.2. Housing Conditions This section highlights house conditions in urban Kenya in terms of dominant roof material (Figure 4.2), dominant wall material (Figure 4.3) and dominant ?oor material (Figure 4.4) of households main dwelling unit (see also Table 4.2). The following trends can be summarized about housing conditions: Nine out of every ten households in urban Kenya live in dwelling units with durable roof material, the most dominant being iron sheets and concrete/ cement Durable roof material include iron sheets, asbestos sheets, concrete cement, tiles, decra/ versatile, and shingles. Non-durable roof material include grass thatch/twigs, makuti thatch, dung/mud, tin cans, canvas tents, and nylon cartons cardboard. Seven out often households in urban Kenya live in dwelling units with durable wall material, the most dominant being concrete concrete block/ precast wall and stone with lime cement Durable wall material include concrete/ concrete blocks/precast wall, stone with lime/ cement, bricks, timber, and prefabricated panels. Non-durable wall material include cane/ palm/ trunks, grass/ reeds, mud/cow dung, plywood/ cardboard, offcuts/ reused wood/ wood planks, canvas/ tents, nylon/ cartons, stone with mud, covered adobe, uncovered adobe, and iron sheets. Eight out of ten households in urban Kenya live in dwelling units with durable ?oor material, the most dominant being concrete cement/ tarrazo and ceramic tiles Durable ?oor material include wood planks shingles timber, parquet/ polished wood, Vinyl/ asphalt strips, ceramic tiles, concrete/ cement/ terrazzo, and wall to wall carpet. Non-durable ?oor material include earth/ sand, dung, and palm bamboo. 24 Shingles 0.1 Nylon/Cartons/Cardboard 0.1 Decra/Versatile 0.9 Tiles 2.3 Concrete/Cement 20.1 Asbestos sheet 2.2 Tin cans 0.1 Iron sheets 73.2 Dung/mud 0.1 Makuti thatch 0.5 Grass thatch/twigs 0.6 0 20 Timber Bricks Stone with lime/cement Concrete/Concrete blocks/Precast wall Iron sheets Off cuts/Reused wood/Wood planks Plywood/Cardboard Uncovered adobe Covered adobe Stone with mud Mud/cow dung Grass/reeds Cane/palm/trunks 40 60 Percentage of Households 80 2.3 8.5 29.9 31.9 15.3 0.7 0.3 0.4 2.2 2.4 5.5 0.4 0.2 0 10 20 30 Percentage of Households 40 Wall to wall Carpet 2.8 Concrete/ Cement/Terrazo 63.3 Ceramic tiles 20.6 Vinyl or asphalt strips 0.3 Parquet or polished wood 0.7 Wood planks/ shingles/timber 0.4 Dung 1.4 Earth/sand 10.6 0 20 40 Percentage of Households 60 80 Public tap/Standpipe 15.6 Water Vendor 16.7 Rain/Harvested water 2.0 Bottled water 6.7 Piped to yard/plot 24.0 Piped into dwelling 18.1 Borehole/Tube well 6.8 Unprotected Well 0.5 Protected Well 4.0 Unprotected Spring 0.3 Protected Spring 1.8 Stream/River 2.6 Lake 0.3 Dam 0.5 Pond 0.2 0 10 20 Percentage of Households 30 Table 4.3: Main Source of Water by Major Urban Centres, 2019 Improved source Unimproved Urban centre ofwater source ofwater (Percentage ofhouseholds) KENYA (Urban) 78.9 21.1 Nairobi City 84.3 15.7 Mombasa 55.6 44.4 Nakuru 89.9 10.1 Ruiru 85 15 Eldoret 92.7 7.3 Kisumu 82.8 17.2 Kikuyu 86.4 1 3.6 Thika 96.3 3.7 Naivasha 64.7 35.3 Karuri 87.8 12.2 Ongata Rongai 80.7 19.3 Kitale 88.2 1 1.8 Juj a 86.2 1 3.8 Kitengela 49.3 50.7 4.4. Main Mode of Human and Solid Waste Disposal Urban households have access to a wide range of main mode of human waste disposal (Figure 4.6) and main mode of solid waste disposal (Figure 4.7; see also Table 4.4). The following trends can be summarized about main mode of human solid waste disposal: Nine out of every ten households in urban Kenya have access to improved human waste disposal systems. Improved human waste disposal systems include main sewer, septic tank, cess pool, VIP pit latrine, pit latrine covered, and bio-septic tank/biodigester. Unimproved human waste disposal systems include pit latrine uncovered, bucket latrine, and open defecation. Among the major urban centres, Kitale has a relatively higher proportion of its population using unimproved solid waste disposal systems. Connection to main sewer is generally low in most urban centres. At the national level, only 24.6 per cent of the households are connected to main sewer, while 21.1 per cent rely on septic tanks and 0.6 per cent on cess pool. A significant number of households in urban Kenya rely on pit latrines, be it VIP covered or uncovered Nine out of every ten households in urban Kenya have access to improved solid waste disposal systems. Improved solid waste disposal systems include collected by counW government; collected by CBOs, Youth Groups, collected by private company; dumped in the latrine; burnt in open; buried; compost pit; and burnt in a pit. Unimproved solid waste disposal systems include dumped in the compound; and dumped in the street/ vacant plot/ drain/ waterways. 28 Bio-septic tank/Biodigester 0.3 Bush 0.8 Bucket latrine 1.2 Pit Latrine uncovered 4.4 Pit latrine covered 34.4 VIP Pit Latrin 12.5 Cess pool 0.6 Septic tank 21.1 Main Sewer 24.6 0 10 20 30 40 Percentage of Households Burnt in a pit 10.1 Compost pit 7.8 Buried 0.8 Burnt in open 16.5 Dumped in the Latrine 2.5 Dumped in the street/vacant plot/drain/waterways 4.4 Dumped in the compound 3.2 Collected by private company 21.8 Collected by Community Association(CBOs Youth… 17.5 Collected by County Government 15.3 0 10 20 Percentage of Households 30 Table: 4.4: Main Mode of Human and Solid Waste Disposal by Major Urban Centres, 2019 Human waste disposal system I Solid waste disposal system Urban centre (Percentage of households) Improved Unimproved Improved Unimproved KENYA (Urban) 93.6 6.4 92.5 7.5 Nairobi City 96.5 3.5 88.5 9.3 Mombasa 91.2 8.8 86.1 9.1 Nakuru 95.4 4.6 93 3.6 Ruiru 96 4 92.6 4.8 Eldoret 94.8 5.2 86 4.7 Kisumu 90.3 9.7 82.5 6.6 Kikuyu 97.5 2.5 92.8 2.6 Thika 97.4 2.6 88.8 7.2 Naivasha 92.6 7.4 91.6 3.6 Karuri 96.7 3.3 87 4.7 Ongata Rongai 94.3 5.7 93.4 2.7 Kitale 92.5 7.5 52.1 11.6 Juja 95.3 4.7 89.7 6.8 Kitengela 94.4 5.6 96.6 1.4 4.5. Main Type of Cooking and Lighting Fuel Figures 4.8 and 4.9 presents urban households? main type of cooking fuel and main type of lighting fuel, respectively (see also Table 4.5). The following trends can be summarized about main type of cooking and lighting fuel: A significant proportion of urban households depend on unclean cooking fuel. Clean cooking fuel include electricity, LPG (gas), biogas, and solar. Unclean cooking fuels include firewood, charcoal, and paraffin. The use of unclean cooking fuel is generally higher in Mombasa, Kisumu and Kitale. LPG (gas) tend to be preferred for cooking than use of electricity. Nine out of every Ten households in urban Kenya have access to clean lighting fuel. Clean lighting fuels include mains electricity, gas lamp, solar, torch/spotlight-solar charged, torch/ spot light-dry cells, battery (car/ charged) generator (diesel/ petrol) and biogas. Unclean cooking fuels include paraffin pressure lamp, paraffin lantern, paraffin tin lamp, wood, and candle. 3O 60 Percentage of Households 53.0 40 17.7 17.7 20 9.3 1.6 0.7 0 Electricity Paraffin Battery(Car/Charged) LPG (gas) Biogas Firewood Charcoal 0.1 Candle 1.8 Torch/Spot light-Dry cells 0.7 Torch/Spotlight-Solar Charged 0.7 Solar 2.4 Wood 0.3 Gas Lamp 0.1 Paraffin Tin lamp 2.7 Paraffin Lantern 2.2 Paraffin Pressure lamp 0.2 Mains Electricity 88.6 0 20 40 60 Percentage of Households 80 100 Table 4.5: Main Type of Cooking and Lighting Fuel by Major Urban Centres, 2019 Type of cooking fuel I Type of lighting fuel Urban centre (Percentage of households) Clean Unclean Clean Unclean KENYA (Urban) 55.3 44.7 92.8 7.2 Nairobi City 70.1 29.9 97.1 2.9 Mombasa 40 60 88.5 11.5 Nakuru 51.7 48.3 94.8 5.2 Ruiru 80.1 19.9 96.6 3.4 Eldoret 44.9 55.1 93.6 6.4 Kisumu 39.6 60.4 90.6 9.4 Kikuyu 68.2 31.8 96.2 3.8 Thika 77.7 22.3 96.1 3.9 Naivasha 60.4 39.6 94.6 5.4 Karuri 67.3 32.7 96.3 3.7 Ongata Rongai 77.2 22.8 96.6 3.4 Kitale 27.6 72.4 84.8 15.2 Iuja 77 23 95.5 4.5 Kitengela 75.3 24.7 95.7 4.3 32 Chapter 5: Population of Urban Informal Settlements This Chapter presents selected characteristics of urban informal settlements. The Chapter provides data and information on urban informal settlements population,- economic characteristics of urban informal settlements population; housing characteristics of urban informal settlements,- main source of water in urban informal settlements,- main mode of human and solid waste disposal in urban informal settlements; and main Wpe of cooking and lighting fuel in urban informal settlements. 5.1. Urban Informal Settlements Population According to the 2019 Kenya Population and Housing Census data, the total urban population living in informal settlements is 1,016,913 (Table 5.1). This represents 6.9 per cent of the total urban population. These informal settlements were located in 19 out of the 372 urban centres in Kenya as shown in Table 5.1. Nairobi contributes a disproportionately larger share of the total urban informal settlements? population in the country, followed by Kisumu and Mombasa. Table 5.1: Informal Settlements Population by Urban Centres, 2019 Informal Percentage of total Urban Centre settlements urban informal Population settlements population KENYA (Urban) 1,016,913 6.9 Nairobi City 813, 848 80 Kisumu 85,314 8.4 Mombasa 32,387 3.2 Athi River 27,680 2.7 Naivasha 12,694 1.2 Thjka 11,963 1.2 Wote 6,975 0.7 Kitui 6,111 0.6 Nakuru 5,136 0.5 V01 4,527 0.4 Nyeri 3,975 0.4 Narok 1,659 0.2 Kitale 1,058 0.1 Kikuyu 866 0.1 Kakamega 844 0.1 Meru 685 0.1 Lodwar 419 Embu 390 Machakos 382 According to Table 5.2 a large proportion of Nairobi?s informal settlements population is found in Embakasi Kibra Kasarani and Mathare sub-counties. These are administrative areas that house the known informal settlements in Nairobi such Kibra, Mathare, Mukuru and Korogocho. The rest of the sub-counties in Nairobi have very low proportions of informal settlements population. In Mombasa, informal settlements population 33 was recorded in three out of the siX sub-counties (Table 5.3). These are Jomvu, MVita and Nyali sub-counties. Changamwe, Kisauni and Likoni sub-counties did not record any informal settlements population. The informal settlements population was largely concentrated in Jomvu and Mvita sub-counties, in comparison to Nyali. Table 5.2: Informal Settlements Population in Nairobi City, 2019 Percentage of Administrative Informal informal sub-county settlements settlements population population in Nairobi Embakasi 199,678 24.5 Kibra 134,389 16.5 Kasarani 101,004 12.4 Mathare 81,278 10 Kamukunji 79,073 9.7 Starehe 64,751 Lang'ata 48,835 Makadara 44,364 5.5 Njiru 37,956 4.7 Westlands 19,445 2.4 Dagoretti 3,075 0.4 Table 5.3: Informal Settlements Population in Mombasa, 2019 Percentage of informal Administrative Informal settlements settlements population sub-county population in Mombasa Iomvu 15,068 46.5 MVita 13,096 40.4 Nyali 4,223 13 5.2. Economic Characteristics of Urban Informal Settlements Population Table 5.4 presents the Economic Characteristics of urban informal settlements population in terms of the highest level of education completed (for those aged 3 years and above), economic activity (for those aged 5 years and above) and main employer (for those working). There seems to be no significant differences with the general trends of Kenya?s urban population. However, urban informal settlements population tend to have higher proportions of people with primary level of education and below, as well as those engaged in informal sector employment. Nationally, 56.9 per cent of the urban informal settlements population had attained primary level of education and below, 45.4 per cent were engaged in gainful employment working) and 45.3 per cent were employed in the informal sector. 34 Table 5.4 Economic Characteristics of Urban Informal Settlements Population, 2009 Percentage of settlements? category population Urban centre Highest level of education Economic activity Main employer completed years old) years old) Primary and Secondary and Looking for Public Informal Working below above work sector sector KENYA (Urban) 56.9 43.1 45.4 14 5.2 45.3 Nairobi 56.4 43.6 45.1 14.9 4.7 46.4 Kisumu 55.5 44.5 41.8 8.9 7.1 46.5 Mombasa 65.9 34.1 46.3 14.6 5.9 41.3 5.3. Housing Characteristics of Urban Informal Settlements Table 5.5 presents the Housing Characteristics of urban informal settlements in terms of tenure status and dominant roof, wall and ?oor material of the dwelling units. There seems to be no significant differences with the general trends of Kenya?s urban population. Informal settlements are also characterized by high proportions of households living in individual rental units with durable roof (89.6% iron sheets) and ?oor (73.9% cement) materials. However, most of the dwelling units are characterized by non-durable wall materials. The common wall materials are iron sheets concrete/ concrete blocks/precast wall stone with lime/ cement and mud/cow dung Nationally, 85.4 per cent of the informal settlement?s households live in individual rental units, 99.6 per cent live in dwelling units with durable roof material, 33.7 per cent live in dwelling units with durable wall material, and 82.4 per cent live in dwelling units with durable ?oor material. Table 5.5 Housing Characteristics of Urban Informal Settlements, 2009 Percentage of urban settlements? households Urban centre Tenure status Housing condition Durable Individual Durable roof Durable wall Own house ?oor rental unit material material material KENYA (Urban) 8.8 85.4 99.6 33.7 82.4 Nairobi 7.6 86.2 99.6 29.2 83.1 Kisumu 13 83.2 99.8 55.3 81.8 Mombasa 15 81.1 98.8 36.3 68 5.4. Main Source of Water in Urban Informal Settlements Generally, informal settlements are also characterized by high proportions of households having access to improved water sources. However, as shown in Figure 5.1, the main sources of water in urban informal settlements are public tap stand pipe piped water to yard/ plot and water vendors Only 6 per cent of the households in the urban informal settlements had access to piped water in the house. The sourcing of water from elsewhere, as well 35 as reliance on water vendors has been documented to increase the cost of water in urban informal settlements. PublictapIStandpine 38-5 WaterVendor 23-? Raianaruestedwater I 0.2 Bottledwater I 1.3 27-2 Piped intodwelling 6.0 BoreholefTuhe well I 1.2 Unprotected Well 0.0 Protected Well I 0.4 Unprotected Spring 0.1 Protected Spring I 0.8 StreamlRiuer I 0.4 Lake 0.1 Dam 0.1 Pond 0.1 0 10 20 30 40 Percentage of Huseholds Figure 5. 1: Main Source of Water in Urban Informal Settlements, 2019 5.5. Main Mode of Human and Solid Waste Disposal in Urban Informal Settlements Generally, nine out of every ten households in the urban informal settlements have access to improved human waste disposal system, while six out of every ten households have access to improved solid waste disposal system. The main modes of human waste disposal systems in urban informal settlements are use of covered pit latrines, main sewer, use of VIP latrine and use of septic tank (Figure 5.2). On the other hand, the main modes of solid waste disposal systems in urban informal settlements are use of youth groups and faith-based organizations, dumping, waste is collected by county government, use of private company and burning of waste (Figure 5.3). 5.6. Main Type of Coking and Lighting Fuel in Urban Informal Settlements On average, only 36.1 per cent of the households in urban informal settlements use clean energy for cooking. As shown in Figure 5.4, the main types of cooking fuel in urban informal settlements are paraffin, LPG (gas) and charcoal. more than half of the households use paraffin, 32.3 per cent use LPG (gas), while 9.5 per cent use charcoal. Electricity is largely used for lighting and therefore, the main mode of lighting (Figure 5.5). 36 Bio-septic tankaiodigester I 0.3 Bush I 0.4 Bucket Iatrine - 3.5 Pit Latrine uncovered - 5.8 Cess pool I 0.7 36.7 10.6 0 10 20 30 40 Percentage of Households Figure 5.2: Main Mode of Human Waste Disposal in Urban Informal Settlements, 20 9 Bumt in a pit Compost pit Buried Burnt in open Dumped in the Latrine Dumped in the streetfvacant plotfdrainfwaterways Dumped in the compound Collected by private company Collected by Community AssociationlCBOs Youth Groups Faith based organizations) Collected by County Government Percentage of Households Figure 5.3: Main Mode of Solid Waste Disposal in Urban Informal Settlements, 20 19 37 EG- 53.0 01 I a. I 32.3 Percentage of Households Electricity Paraffin LPG {gas} Biogas Firewood Charcoal Figure 5.4: Main Type of Cooking Fuel in Urban Informal Settlements, 2019 Candle I 3.3 TorohfSpuotlight-Dripr cells 0.2 Charged 0.2 Solar I 0.5 Paraffin Tin lamp I 3.1 Paraffin Lantern I 2.2 Paraffin Pressurelamp 100 Percentage of Households Figure 5.5: Main Type of Lighting in Urban Informal Settlements, 2019 38 Chapter 6: Summary of Key Findings and Recommendations This Chapter highlights the summary of key findings and recommendations in the context of emerging indicators that could be relevant to existing and proposed development programmes and policies in urban Kenya. Particularly important are the Sustainable Development Goals (SDGS) and Kenya?s Vision 2030. 6.1 . Summary of Key Findings Levels and Trends in Urbanization The urban population has increased from 12 million people in 2009 to 14.8 million people in 2019. The proportion of urban population to the total population has, however, reduced from 31.9 per cent in 2009 to 31.2 per cent in 2019. Similarly, the urban growth rate has significantly dropped from a high of 7.9 per cent in 2009 to a low of 2.1 per cent in 2019. Even then, a further analysis by county and urban centres reveals varied levels and trends in urbanization. In other words, demographic, social, economic and political variables have impacted greatly on urbanization process in Kenya, resulting in varied counW urbanization levels and trends. While Nairobi continues to have the largest share of the urban population, the importance of small and medium-size urban centres is beginning to emerge in the urban hierarchy. Demographic Characteristics of the Urban Population Kenya?s urban population is gradually being dominated by male and female youth aged behzveen 20-34 years (youth bulge). The sex ratio of 98 is a general indication that there are more females than males in most of the urban centres in Kenya. more than half of the urban population have attained secondary education and above, while 13.2 per cent of the adult population living in urban centres had no education. The proportion of unemployed urban population is relatively small, while the private sector and informal sector play a significant role in providing urban employment. The population of people aged 5 years and above living with disability is relatively low. The same applies to the population of street persons. Housing Characteristics of the Urban Population House ownership is still minimal in urban Kenya with only 21.3 per cent of the households living in own house. In other words, most households in urban Kenya live in individual rental dwelling units. A large proportion of urban households live in dwelling units with durable roof, wall and ?oor materials. Similarly, majority of the households have access to improved sources of water, improved human waste disposal systems, improved solid waste disposal systems, and electricity for lighting. However, the proportion of urban households having access to main sewer, piped water in the house and county government solid waste management services is still low. Furthermore, more than half of the urban households use unclean sources of energy for cooking. Population of Urban Informal Settlements The proportion of urban population living in informal settlements has significantly reduced from 15 per cent in 2009 to 6.9 per cent in 2019. The urban informal settlements population continue to be disproportionately concentrated in Nairobi. There seems to be no significant differences between the characteristics of urban informal settlements population with the general trends of Kenya?s urban population. However, most households in the urban informal settlements tend to 39 live in dwelling units with non-durable wall materials; they rely on water vendors and piped water from elsewhere rather than from individual connections) and use unclean energy sources for cooking. 6.2. 1. Recommendations The definition of what constitutes an urban area varies from one country to another. For the purposes of future censuses, there is need for a clearer definition of what constitutes rural, urban and urban informal settlements. In addition, there is need for well defined and measurable indicators for delimiting urban informal settlements. Given the levels, trends and patterns of urbanization process in Kenya, there is need for implementation of the National Urban Policy (2016) to guide urban development country- wide. In addition, the policy should aim at guiding county-based urbanization processes by reducing risks and maximizing opportunities offered by urban growth. The country should enact an urban development law to anchor the many segmented parts of urbanization issues captured in many diferent legislations. There is no doubt that small and medium-size urban centres will continue to grow and absorb a larger proportion of the urban population. There is need to plan for the spatial growth and development of these urban centres as well as strengthen their governance capacities through increased capacity building and infrastructure investements. The growth of Nairobi City has spilled over to the adjacent urban centres. Other large urban centres will gradually experience the same. There is need to encourage area-wide metropolitan planning and governance, including fastracking the formation of the proposed metropolis regions of Kenya. Urban centres are central places where people converge on a daily basis. They serve not only the urban residents but also the population living around the urban centre. However, the day time population of urban centres is hardly captured in population censuses, yet it is important for planning purposes. There is need to capture and plan for the day-time population in urban areas. Improving the conditions of informal settlements in the three cities of Nairobi, Mombasa and Kisumu should be encouraged, while at the same time controlling further growth of these settlements in other urban centres. One way of achieving sustainable urban development is through generating, collecting and analyzing accurate and reliable urban-area specific data which can better inform local and national decision-making processes. 40 References Kenya, Government of (2012), 2009 Kenya Population and Housing Census: Analytical Report on Urbanization Volume Nairobi: Kenya National Bureau of Statistics. Kenya, Government of (1996), Kenya Population Census 1989: Analytical Report Volume VI on Migration and Urbanisation. Nairobi: Central Bureau of Statistics/ Ministry of Finance of Planning. Kenya, Government of (2004), Kenya Population and Housing Census 1999: Analytical Report Volume VI on Migration and Urbanisation. Nairobi: Central Bureau of Statistics/ Ministry of Finance of Planning. Kenya, Government of (2008), Kenya Vision 2030: FirstMedium-Terni Plan, 2008-2012. Nairobi: Ministry of State for Planning, National Development and Vision 2030. Kenya, Government of (2007), Kenya Vision 2030. Nairobi: Ministry of Planning and National Development/ National Economic and Social Council. 41 42 (CONFIDENTIAL) Republic of Kenya Population and Housing Census - 24th/ 25th August 2019 A :5 ?3.21122 ??qringyut x'rifbnm'd Appendix 1 REPUBLIC Sub-County [:lj Divisionljj lowtion E11 Sub-LomonDD E.A.Typa EA Status Household No :13: Household Type Structure No. D:l:l Males: [Um Females: Others: Total Household Papulotlon: Line Relationship Sex Age Date of Birth Line Usual E?mieily/ Religion Marital Birth Previous Duration of Reason (or Number Number member Nationality Status l'la ce Residence Residence migration Orphanho otl Particulars of All Live Births of oth er Quest Particulars of last Live Births lonnalr es (0-34) (0-35] mild] umeiuuhddisnot alive, when didth: Mum: mum of Whatis Wlutu How oldis Wnatis 3 Whatis Wnatis Wherewas Where was 4mm) Why am is Howmany How many How many How many Wnauwasyour 1m Mm :11 Wlmwas 5:31:52? mild in? eathpersonwhosplm dam linznumhzr usual move rod-i: oath: :urmir duldrzuhavzyvu rhildraihavr thildhom? diesncof relan'onslup to sex? birth? of member of religion 7 hum? living in County? plat: of: rsidam: hiologtal biologioal you our home born: alive who youhomz alive alive ?our? this thild/ (NAM E>'s tins (AYPLIUBLE August 2018? fa?lzr mother alive? this Ev: who have died? . [h?drzni? hinlogira] household? TO AGE 12 alive? alive? household? mother AND Aoom August, 2019 in this household? (Record two norms q/auch person, yuungand old, starting wi 01 the hood of the household.) 215 where I . a health . 2:53;? For [5??de if data oflurthis Farihty if data of Is as unknown Code notknowntode Kmya,or $333,;iy: "95"for mouth "59"{or mouth and 31mm "on" roulmy rode, birth, rod: mm and ?9999' for ym. 3 '9999' for year. 5 if outside . and year of birth. BIOLOGICAL Kmyal nomms Dram!? NOTINTHE -?l?E-Elm? lldatz of Eagodundu? movementis not 1 year, wriu write formant): and '9999'rmym, Appendices [The rod: in (The rode in is proud: is providz (The rodelist Related is provided.) Sen?al N1 Di continuation form: (1-. ?an (Tobe asked at pusans .331 2 years a share.5de a1 pagans Aged 5 yum and above Except (r43) hrpusms Aged 3 Years and Above "1"?th "wand? (In ?k?d persons ?ed 5 yum ?d mm) (Hz) (MS) (Ms) LSeeing, 2.Hun'ng, Bdeing ar sail-(u! 6. awn i even if using climbing all Communican'?! Has dime) am or dnssinp using his/bu mm usual 1 5 - imamham im- amp)! ?m in a mulls? any hah?nn'm wm?nv. 1mm wm': a: SM/Pam/Gadg mum Wl-lid: Humane: imitation mung mm of (mum und "standing - lun'mb'nn 43 lzla-M lie-um: Va-aame 2=Y5v5ane Ya-alut 2:75am dilicuhy dil?zuky many hi?hs belwun 24/08/2018 and inmis howl-ma 24/03/2019 [1m 12 months}? betwun 24/08/20? and 24/03/20? [Ian Iran?supnms til-28) MW Maia?: Roam Haw many Haw Inn-y mm): ?mug mam damaevm In?: die within? )la- Malaky v: mm: d?nmy Ye-alatal mmlsonhe homebokl {unused lo the bud oilhis Tam-e Sm?! Mail llwel'ng um a: 15mm- ma ?Mum: Han Raul haviehld campy 7 or Ming unduslood? V: nan: Y=?s sex? birthday? CountryI'County of birth? current (Record age in completed years Countrinounty using two digits. if under 1 year, of residence? 1=Male record if 95 years and 2: Female above, code (Code list (Code list 3=Other provided) provided111111111 UU UM ll?i i?H?i 47 KN Bs KENYA NATI ONAL ovum [aging you informed REPUBLIC OF KENYA POPULATION AND HOUSING CENSUS 24?h /25?h AUGUST 20l9 CONFIDENTIAL SHORT QUESTIONNAIRE FOR STREET County Sub-county Division ED: Location Sub-Location EA Number Name of the street Code Line Name SEX AGE in COUNTRY OF BIRTH NATIONALITY INO (List at least two I. Male 3. Other Completed years What is Nationality/Ethnicity? names) 2. Female 4. Not Stated TOTAL: MALES FEMALES OTHER UNSPECIFIED SEX TOTAL Appendix 2: Population by Urban Centre, 2019 Urban centre Population Sex ratio Nairobi City 4,395,749 99 Mombasa 1,208,112 102 Nakuru 570,614 97 Ruiru 490,035 95 Eldoret 475,659 99 Kisumu 397,853 96 Kikuyu 323,825 94 Thika 251,360 96 Naivasha 198,399 100 Karuri 194,289 95 Ongata Rongai 172,516 97 Kitale 162,154 99 Juja 155,999 98 Kitengela 154,327 96 Kiambu 147,826 92 Garissa 141,936 101 Mlolongo 136,266 103 Malindi 119,825 94 Kisii 115,511 98 Mandera 114,718 110 Kakamega 107,205 100 Ngong 102,718 97 Mtwapa 90,670 94 Wajir 90,092 114 Lodwar 82,927 100 Limuru 81,305 98 Athi River 81,286 102 Meru 80,169 99 Nyeri 80,069 97 Isiolo 78,630 97 Ukunda 77,679 100 Kiserian 76,897 96 Kili? 74,260 93 Nanyuki 72,810 100 Busia 71,864 95 Migori 71,661 91 Bungorna 68,022 94 Narok 65,415 100 Embu 64,974 96 Machakos 63,761 96 Githunguri 63,308 95 E1 Wak 60,707 85 Gilgil 60,690 105 Nyahururu 60,486 96 Kimilili 56,048 94 Kericho 53,774 110 Voi 53,345 100 Wanguru 51,718 92 Habaswein 49,597 120 Moyale 47,850 102 M010 46,682 94 Homa Bay 44,942 91 Kenol 44,083 93 48 Urban centre Population Sex ratio Masalani 43,631 118 Murang'a 43,330 95 Webuye 42,642 95 Njoro 42,167 96 Kapsabet 41,997 100 Mumias 41,942 91 Marsabit 36,289 108 Rhamu 35,644 107 Siaya 33,133 92 Mariakani 31,708 96 Maralal 31,350 102 Kerugoya 30,045 93 Kitui 29,062 96 Makutano 28,467 93 Elburgon 28,359 101 Watarnu 27,853 101 Lamu 26,429 103 Kajiado 24,678 101 Nyamira 24,475 93 Isebania 23,891 94 Madogo 23,721 98 Karatina 23,552 89 Kakuma 22,978 110 Lafey 22,882 89 Bondo 22,694 89 Kabarnet 22,474 95 Chuka 22,378 95 Kehancha 22,188 95 Maua 22,114 94 Taveta 22,018 98 Takaba 21,519 100 Eldama Ravine 21,382 96 Hola 20,910 97 Mai Mahiu 20,823 98 Rongo 20,686 88 Oyugis 19,946 87 Wote 19,724 101 Emali 18,323 106 Gar-Batula 17,442 107 Mbale 17,401 90 Mwingi 17,023 92 Awendo 16,815 98 Kiminini 16,557 93 Moi's Bridge 16,355 94 Mazeras 16,253 96 Malaba 15,581 95 Makindu 15,038 104 Banisa 14,974 107 Msambweni 14,944 95 Namanga 14,921 103 Mbita 14,916 92 Isinya 14,429 102 Bute 14,108 107 Kawaida 14,028 95 Kagio 13,961 82 49 Urban centre Population Sex ratio Bura 13,649 105 Suneka 13,404 88 Litein 13,401 98 Mogotio 13,366 94 Luanda 13,319 91 Ol Kalou 13,232 98 Rumuruti 13,052 105 Lokichar 12,675 113 Chavakali 12,674 92 Item 12,630 94 Makutano (Kyumbi) 12,395 115 Eldas 12,270 118 Port Victoria 12,194 94 Vipingo 12,183 102 Matuu 12,073 89 Majengo 11,908 94 Modogashe 11,818 104 Mau Narok 11,806 97 Ahero 11,798 84 Ijara 11,792 159 Bomet 11,760 105 Lokichoggio 11,626 104 Dadaab 11,524 131 Tala 11,442 94 Sagana 11,203 95 Kinna 11,175 106 Merti 10,990 107 Gongoni 10,978 93 Keroka 10,881 90 Kilgoris 10,838 95 Matunda 10,807 93 Githunguri 10,606 91 Timau 10,570 95 Loitoktok 10,568 95 Kainuk 10,535 102 Subukia 10,343 92 Sindo 10,285 90 Kangundo 10,258 99 Kimana 10,110 93 Kwale 10,063 94 Chwele 9,797 85 Mwatate 9,570 93 Salgaa 9,446 99 Marigat 9,398 93 Kutus 9,143 94 Sultan Hamud 8,718 92 Maragua 8,593 87 Kibwezi 8,139 95 Rodi Kopany 8,121 86 Naro Moru 8,097 94 Nandi Hills 8,032 98 Usenge 7,975 92 Gatundu 7,944 87 Giriftu 7,935 120 Brooke Bond 7,896 100 50 Urban centre Population Sex ratio IL Bissil 7,811 96 Mairo Inya 7,691 91 801010 7,683 105 Nkubu 7,674 85 Chogoria 7,603 97 Butere 7,596 86 Shianda 7,502 85 Sori 7,365 89 Muhoroni 7,204 103 Garsen 7,164 93 Marereni 7,085 92 Kapsokwony 7,077 94 Ugunja 7,060 88 Kaloleni 7,015 90 Sondu 6,869 92 Kimbirnbi 6,825 89 Maseno 6,771 120 Othaya 6,650 8 1 Mukurweini 6,508 92 Mwisho wa Rami 6,499 101 Bura East 6,496 119 Kangema 6,424 95 Kendu Bay 6,064 93 Ting'ang'a 6,057 87 Lolgorian 6,051 99 Kijauri 5,993 95 Chaka 5,970 93 Mp eketoni 5,956 96 Kinango 5,925 85 Mtito Andei 5,626 142 Ololunga 5,609 97 Githiga 5,565 98 Rironi 5,544 90 Ndundori 5,392 96 Chebilat 5,373 102 Laare 5,358 98 Engineer 5,324 89 Loiyangalani 5,193 82 North Horr 5,177 116 Maji Mazuri 5,138 106 Malava 5,131 89 Katito 5,098 87 Awasi 5,052 89 Laisamis 5,047 115 Nairagie Ngare 4,954 97 Runyenjes 4,943 95 Muhuri Bay 4,924 92 Musoriot 4,916 93 Kinamba 4,890 91 Keringet 4,774 100 Ndhiwa 4,762 85 Timboroa 4,744 99 Burnt Forest 4,739 101 Maungu 4,713 98 Kebirigo 4,711 89 51 Urban centre Population Sex ratio Kapsowar 4,709 95 Illasit 4,631 88 Jua Kali 4,621 89 Archers Post 4,620 106 Wamba 4,580 100 Samburu 4,454 87 Isineti 4,437 99 Cheptais 4,414 92 Kimende 4,355 90 Ndunyu Njeru 4,354 96 Siakago 4,315 93 Kathiani 4,304 92 Baragoi 4,253 96 Mokowe 4,249 114 Sotik 4,194 113 Amagoro 4,182 91 Sega 4,172 78 Wundanyi 4,118 102 Kangari 4,096 88 Nyandiwa Beach 4,033 94 Kiganjo 4,009 140 Nambale 3,993 82 Serem 3,984 93 Njabini 3,929 95 Mackinon Road 3,901 110 Ogembo 3 ,901 86 Khayega 3,892 89 Rombo 3,854 98 Mosocho 3,823 91 Kiriaini 3,779 85 Ndori 3,770 80 Kagumo 3,673 86 Masii 3,651 91 Funyula 3,645 85 Magonga 3,628 92 Mweiga 3,608 93 Nyangusu 3,590 86 Kapsoit 3,545 109 Magena 3,501 89 Ntulele 3,390 90 Ortum 3,372 97 Oldonyo Sabuk 3,353 97 Mitunguu 3,293 94 Kikima 3,269 92 Yala 3,237 89 Kapcherop 3,234 92 Bahati 3,180 93 Mulot 3,149 99 Londian 3,148 98 Tarbaj 3,146 103 Chepsion 3,096 99 Kianyaga 2,973 80 Rabuor 2,942 93 Kithimani 2,923 95 Tabaka 2,910 82 52 Urban centre Population Sex ratio Total 2,893 98 Faza 2,855 105 Olenguruone 2,787 106 Kampi Ya Moto 2,775 89 Marimanti 2,758 102 Endarasha 2,743 92 Kiboko 2,708 115 Kenyenya 2,698 97 Kipini 2,656 101 Kinungi 2,573 89 Turbo 2,559 95 Lunga Lunga 2,536 89 Ikinu 2,532 89 Masimba 2,504 103 Kapkatet 2,484 112 Ngewa 2,451 94 Wiyumiririe 2,448 82 Saba Saba 2,438 86 Kabati 2,420 82 Sikuta Marmar 2,328 96 Karuga 2,301 108 Kesses 2,293 91 Nunguni 2,266 96 Kasuku 2,209 86 Wamunyu 2,190 90 Muchorwi 2,162 92 Kiirua 2,158 84 Makutano 2,146 95 Ewuaso Kedong 2,144 113 Oljoro Orok 2,116 94 Rongai 2,096 97 Sirisia 2,096 90 Baraton 2,043 95 Kijabe 2,026 77 Bamba 2,010 84 Piai 1,991 99 Naishi 1,956 95 Magadi 1,950 183 Gatarakwa 1,930 95 Salama 1,905 109 Ndaragwa 1,877 95 Maeli Tisai 1,874 114 Kabazi 1,864 88 Kangeta 1,828 97 Mogogosiek 1,822 110 Tenwek Hospital 1,821 80 Sipili 1,807 98 Kiunduani 1,806 95 Mwala 1,793 90 Kamwangi 1,776 82 Mutomo 1,751 101 Kyuso 1,722 85 Kathonzweni 1,709 85 Turi 1,669 98 Butali 1,667 92 53 Urban centre Population Sex ratio Mikinduri 1,664 93 Igoji 1,651 90 Kandara 1,638 85 Nguluni 1,606 82 Makuyu 1,596 92 Kabiyet 1,581 91 Narosura 1,559 100 Cheptiret 1,544 100 Sigomere 1,527 85 Miharati 1,508 91 Kibingoti 1,502 72 Kuresoi 1,491 96 Shamata 1,457 93 H010 1,436 76 Ewaso Ngiro 1,394 103 Kibirichia 1,376 93 Katangi 1,368 89 Masinga 1,362 98 Ukwala 1,346 89 Makutano 1,3 18 97 Longisa 1,295 80 Kiptagich 1,260 100 Kipkelion 1,179 1 02 Lumakanda 1,166 86 Tseikuru 1,110 92 Silibwet 1,092 117 Masimba 1,077 90 Baricho 1,047 104 Mutuati 1,032 115 Bangale 961 95 Migwani 929 77 Amukura 927 83 Kiritiri 921 94 Bumula 906 82 Kabartonjo 878 113 Gede 876 86 Kambaa 857 102 Kiangai 8 19 82 Kwisero 786 74 Kanyuambora 766 93 Chemilil 748 114 Kabaa 614 99 Ragengni 457 76 Matayos 439 84 54 Appendix 3: Population of Nairobi City by Location, 2019 Location Population Percentage of Nairobi population Dagoretti Sub-County Gatina 63,520 1.4 Kawangware 91,438 2.1 Ngando 49,913 1.1 Riruta 86,588 2.0 Kabiria 27,018 0.6 Mutuini 22,962 0.5 Ruthimitu 19,422 0.4 Uthiru 32,363 0.7 Waithaka 40,832 0.9 Embakasi Sub-County Embakasi 178,313 4.1 Mukuru Kwa Njenga 242,879 5.5 Imara Daima 118,511 2.7 Kayole 118,713 2.7 Komarock 65,132 1.5 Savannah 124,848 2.8 Umoja 140,181 3.2 Kamukunji Sub-County Airbase 40,102 0.9 Eastleigh North 44,760 1.0 Eastleigh South 67,554 1.5 Kiambiu 45,958 1.0 Uhuru 27,328 0.6 Pumwani 19,742 0.4 Shaurimoyo 22,704 0.5 Kasarani Sub-County Githurai 84,007 1.9 Kahawa West 82,811 1.9 Zimmerman 49,519 1.1 Baba Dogo 71,248 1.6 Kariobangi North 46,325 1.1 Korogocho 36,891 0.8 Kasarani 138,098 3.1 Mwiki 60,757 1.4 Roysambu 85,464 1.9 Ruaraka 90,925 2.1 Utalii 34,426 0.8 Kibra Sub-County Kibera 64,749 1.5 Sarangombe 55,291 1.3 Laini Saba 29,605 0.7 GolfCourse 7,606 0.2 Kenyatta 9,394 0.2 Woodley 19,098 0.4 Lang'ata Sub-County Karen 13,546 0.3 Lang'ata 21,629 0.5 Highrise 39,335 0.9 Mugumoini 58,258 1.3 Nairobi West 64,661 1.5 Makadara Sub-County Bahati 29,985 0.7 55 Location Population Percentage of Nairobi population Makadara 47,702 1.1 Makongeni 29,993 0.7 Maringo 38,761 0.9 Viwandani 43,055 1.0 Mathare Sub-County Huruma 113,009 2.6 Mathare 93,480 2.1 Njiru Sub-County Dandora 93,159 2.1 DandoraI 8: 11 59,792 1.4 Kariobangi South 142,625 3.2 Kayole North 70,428 1.6 Mihang'o 60,341 1.4 Njiru 94,470 2.1 Kamulu 33,343 0.8 Ruai 72,111 1.6 Starehe Sub-County Kamukunji 10,953 0.2 Ngara 31,110 0.7 Starehe 11,022 0.3 Kariokor 18,827 0.4 Pangani 35,984 0.8 Landmawe 36,901 0.8 Mukuru Nyayo 65,499 1.5 Westlands Sub-County Highridge 61,871 1.4 Parklands 13,639 0.3 Kangemi 116,700 2.7 Kitisuru 33,643 0.8 Kileleshwa 32,500 0.7 Kilimani 50,422 1.1 56 Appendix 4: Population of Mombasa by Location, 20 19 Location Population Percentage of Mombasa population Changamwe Sub-County Chaani 38,785 3.2 Changamwe 9,032 0.7 Kwa Hola 18,568 1.5 Port Reitz 65,488 5.4 Jomvu Sub-County Mikindani 61,398 5.1 Miritini 101,988 8.4 Kisauni Sub-County Bamburi 123,731 10.2 Kisauni 168,139 13.9 Likoni Sub-Count)7 Likoni 163,245 13.5 Mtongwe 33,032 2.7 Shikaadabu 54,060 4.5 Mvita Sub-County Ganjoni 17,369 1.4 Majengo 38,107 3.2 Mwembe Tayari 8,968 0.7 Old Town 19,467 1.6 Railway 5,952 0.5 Tononoka 27,966 2.3 Tudor 36,282 3.0 Nyali Sub-County Frere Town 50,297 4.2 Kadzandani 55,169 4.6 Kongowea 65,757 5.4 Maweni 45,312 3.8 57 Appendix 5: Contributors to the 2019 Kenya Population and Housing Census Monographs Name and Institution Role Mr. Macdonald Obudho, MBS Director General, Kenya National Bureau of Statistics Mr. Abdulkadir Amin Awes, Kenya National Bureau of Statistics Mr. Collins Omondi, OGW Kenya National Bureau of Statistics Mr. Benjamin Avusevwa Kenya National Bureau of Statistics Mr. Robert Nderitu, OGW Kenya National Bureau of Statistics Ms. Anne M. Mburu, HSC Kenya National Bureau of Statistics Mr. Samuel Ogola Kenya National Bureau of Statistics Prof. Alfred Agwanda, MBS UniversiW of Nairobi Mr. Ben 0.]arabi UniversiW of Nairobi Mr. James Ng?ang?a, HSC Kenya National Bureau of Statistics Ms. Vivianne Nyarunda, HSC Kenya National Bureau of Statistics Mr. Elias Nyaga Kenya National Bureau of Statistics Mr. Michael Musyoka, HSC Kenya National Bureau of Statistics Makau Kenya National Bureau of Statistics Mr. Paul Waweru, HSC Kenya National Bureau of Statistics National Census Coordinator Deputy National Census Coordinator Technical Coordinator Technical Coordinator Technical Coordinator Technical Coordinator Technical Coordinator Lead Author - all Monographs Lead Author - all Monographs Census Project Manager/ Author, Urbanization Author, Labour Gender Dimensions Author, Older Vulnerable Populations/ Population Projections Author, Fertility/ Gender Dimensions/ Population Dynamics Population Projections Author, Migration Population Dynamics Population Projections Author, Fertility/ Population Projections/ Data Processing/ Formatting 58 Ms. Priscilla Ndayara Kenya National Bureau of Statistics Mr. Andrew A. Imbwaga, HSC Kenya National Bureau of Statistics Ms. Schola Kingi Kenya National Bureau of Statistics Ms. Leah Wambugu Kenya National Bureau of Statistics Mr.]ames Munguti Kenya National Bureau of Statistics Ms. Rosemary Kong?ani Kenya National Bureau of Statistics Ms. Caroline Gatwiri Kenya National Bureau of Statistics Mr. Francis Kundu National Council for Population and Development Mrs. Judy Kilobi Otieno Civil Registration Services Dr. Andrew Mutuku UniversiW of Nairobi Mr. Lewis Ngari Kenya National Bureau of Statistics Mr. Godfrey Otieno Kenya National Bureau of Statistics Mr. Peter Wanjohi Kenya National Bureau of Statistics Mr. Robert Buluma Kenya National Bureau of Statistics Mr. Stanley Wambua Kenya National Bureau of Statistics Author, Migration Author, Mortality and Health Population Dynamics/ Gender Dimensions/ Population Projections Author, Mortality and Health Gender Dimensions Population Dynamics Population Projections Author, Mortality and Health Author, Household and Family Dynamics Author, Older and Vulnerable Population Author, Gender Dimensions/ Household and Family Dynamics/ Population Dynamics/ Population Projections Author, Older and Vulnerable Population Author, Youth and Adolescents Author, Youth and Adolescents Reviewer,- Population Dynamics, Households Family Dynamics Author, Youth and Adolescents Gender Dimensions Author, Education and Training/ Gender Dimensions/ Population Dynamics/ Population Projections/ Disability Author, Education and Training/ Labour Dynamics Author, Disability/ Gender Dimensions Author, Disability/ Gender Dimensions 59 Ms. Renice Bunde Kenya National Bureau of Statistics Ms. Winnie Kemunto Kenya National Bureau of Statistics Mr.]ohn Mburu Kenya National Bureau of Statistics Mr.]oseph Kibor State Department for Livestock Development Mr. Rogers Mumo Kenya National Bureau of Statistics Mr. Alphonse Orang'o Kenya National Bureau of Statistics Mr. Jim Kirimi Kenya National Bureau of Statistics Ms. Tabitha Wambui Kenya National Bureau of Statistics Mr. Paul K. Samoei Kenya National Bureau of Statistics Ms. Linah Ngumba Kenya National Bureau of Statistics Mrs. Rosemary Bowen Kenya National Bureau of Statistics Mr. Kenneth Malakwen Communications AuthoriW of Kenya Dr. George Odipo University of Nairobi Dr. Samuel Wakibi University of Nairobi Prof. Sam Owuor University of Nairobi Dr. Isaiah Bwila, OGW Ministry of Interior Coordination of National Government Author, Disability/ Gender Dimensions/ Population Dynamics/ Population Projections Author, Disability Author, Agriculture Author, Agriculture Author, Agriculture Formatting Author, Agriculture Author, Housing Conditions, Amenities and Household Assets/ Population Projections Author, Housing Conditions, Amenities and Household Assets Author, Housing Conditions, Amenities and Household Assets Author, Gender Dimensions Author, ICT Author, ICT Author, Migration Author, Older and Vulnerable Population Author, Urbanization Author, Older and Vulnerable Population 60 Prof. George Orwa Bomet University College Dr. Caroline Odhiambo Dr. Francis Kiarie JKUAT University Prof. Owiti Kakumu University of Nairobi Prof. Antony Waititu JKUAT University Ms. Verity Mganga State Department for Gender Mr. Caneble Oganga UN Women KNBS Ms. Maureen Gitonga UN Women Ms. Dinah Mutinda UNFPA Ms Tabitha Weru Kenya National Bureau of Statistics Ms Monicah Karanja Kenya National Bureau of Statistics Mr. Tom Dienya State Departments for Agriculture Ms.]ane Kioko State Departments for Agriculture Ms Jane Njeru State Departments for Agriculture Mr. Stephen Ndegwa Fisheries Authority and the Blue Economy Mr Alex Lukwenda State Departments for Fisheries Dr. Anne Khasakhala UniversiW of Nairobi Author, Education and Training Author, Education and Training Author, Education and Training Author, Housing Conditions, Amenities and Household Assets Author, Disability Author, Gender Dimensions Author, Gender Dimensions Data Processing Author, Gender Dimensions Author, Gender Dimensions Author, Agriculture Author, Agriculture Author, Agriculture Author, Agriculture Author, Agriculture Author, Agriculture Author, Agriculture Peer Reviewer, Adolescents Youth/ Gender Dimensions 61 Prof. Kimani Murungaru UniversiW of Nairobi Prof. Lawrence lkamari UniversiW of Nairobi Dr. Daniel Mutegi State Department for Housing and Urban Development Mr. Sebastian Owanga UniversiW of Nairobi Dr. Edwin Oyaro Ondieki UniversiW of Nairobi Mr. Peter Musakhi Ministry of Devolution and ASAL Dr. Wanjiru Gichuhi University of Nairobi Dr. Owen Nyang'oro University of Nairobi Ms. Mary Muyonga University of Nairobi Mr. Peter Nyakwara National Council for Population and Development Dr. Owuor Olunga University of Nairobi Dr.]acob Omolo Kenyatta University Dr.]onathan Nzuma University of Nairobi Ms. Katunge Kiilu Kenya National Bureau of Statistics Dr. Dennis Shilabukha UniversiW of Nairobi Mr. Paul Kuria National Gender and EqualiW Commission Peer Reviewer/ Fertility Nuptiality Peer Reviewer/ Mortality Health Peer Reviewer/ Urbanization Peer Reviewer/ Education Peer Reviewer/ Housing Conditions, Amenities and Household Assets Peer Reviewer/ Disability Peer Reviewer/ Older Vulnerable Population Peer Reviewer/ ICT Peer Reviewer/ Migration Peer Reviewer/ Migration Peer Reviewer, Gender Dimensions Peer Reviewer, Labour Dynamics Peer Reviewer, Agriculture Overall Editor Editor, Gender Dimensions Editor, Gender Dimensions 62 Mr. Mutua Kakinyi Kenya National Bureau of Statistics Mr.]ob Mose Kenya National Bureau of Statistics Mr. Benson Karugu Kenya National Bureau of Statistics Mr. Maurice Kamau Kenya National Bureau of Statistics Mr. Silas Mulwa Kenya National Bureau of Statistics Mr. Anthony Makau Kenya National Bureau of Statistics Ms. Yvonne Chebet Kenya National Bureau of Statistics Mr. Silvester Mwendwa Kenya National Bureau of Statistics Mrs. Hellen Wanyoike Kenya National Bureau of Statistics Mr. Peter Muthama Kenya National Bureau of Statistics Mr. David Alunga Kenya National Bureau of Statistics Mr. Godfrey Ndeng'e UNICEF Mr. Jacob Ochieng UNICEF Mr. Ezekiel Ngure UNFPA Mr. Peter Nyongesa, OGW Monitoring and Evaluation Department Mr. Omondi Omenya, OGW The National Treasury Data Processing Data Processing/ Author, Education and Training/ Population Projections Population Dynamics/ Gender Dimensions Data Processing Information and Communication Technology Formatting Formatting Formatting Formatting Cartography and Author, Urbanization Cartography and GIS Cartography and GIS Technical Support Technical Support Technical Support Data Processing Data Processing 63 64 Kenya National Bureau of Statistics Real Towers, Hospital Road P.O Box 30266-00100 Nairobi, Kenya Tel: (+254) 3317583/6 Fax:(+254) 20 3315977 Email: directorgeneral@knbs.or.ke Website: www.knbs.or.ke Kenya National Bureau of Statistics (Kenya Stats) @KNBStats