Kenya
- Overview
- Obesity prevalence
- Trends over time
- Population breakdowns
- Drivers
- Comorbidities
- Health systems
- Policies
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National obesity risk *7.5/10This is a composite ‘obesity risk’ score (out of 10, the highest risk) based on obesity prevalence, rate of increase, likelihood of meeting the 2025 target, treatment indicator and childhood stunting levels.Childhood obesity risk *4/11This is a ‘risk score’ for each country’s likelihood of having or acquiring a major childhood obesity problem during the 2020s, taking account of current prevalence levels and risk for future obesity (based on stunting among infants, maternal obesity, maternal smoking, and breastfeeding rates).
* Based on estimated data. For more information see Publications
Obesity prevalence
Trends over time
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The report card collates all the most-recent graphics for this country. If you would like to produce a custom report based on selected graphics, just tap the Add to custom PDF button below the graphics you would like to use.Population breakdowns
Drivers
Comorbidities
Health systems
Obesity prevalence
Adults, 2015
| Survey type: | Measured |
| Age: | 18-69 |
| Sample size: | 6000 |
| Area covered: | National |
| References: | Non Communicable Diseases Risk Factors STEPS Survey Kenya 2015 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey Kenya 2014 |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2008-2009
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 7548 |
| Area covered: | National |
| References: | Demographic Health Survey 2009 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2003
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 7047 |
| Area covered: | National (MACRO) |
| References: | Kenya Demographic Health Survey 2003 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 1993
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 3294 |
| References: | Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Children, 2011-2013
| Survey type: | Measured |
| Age: | 9-11 |
| Sample size: | 563 |
| Area covered: | Regional |
| References: | Muthuri SK, Wachira LJ, Onywera VO, Tremblay MS. Correlates of objectively measured overweight/obesity and physical activity in Kenyan school children: results from ISCOLE-Kenya. BMC Public Health. 2014;14:436. Published 2014 May 9. doi:10.1186/1471-2458-14-436 |
| Notes: | Nairobi NB Small sample size |
| Cutoffs: | WHO |
% Adults living with obesity, 1993-2014
| Survey type: | Measured |
| References: | 1993: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2003: Kenya Demographic Health Survey 2003 2008: Demographic Health Survey 2009 2014: Demographic Health Survey Kenya 2014 |
| Notes: | Adults 15-49 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
% Adults living with obesity, 1993-2014
| Survey type: | Measured |
| References: | 1993: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2003: Kenya Demographic Health Survey 2003 2008: Demographic Health Survey 2009 2014: Demographic Health Survey Kenya 2014 |
| Notes: | Adults 15-49 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
Overweight/obesity by education
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey Kenya 2014 |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2003
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 7047 |
| References: | Demographic Health Survey, Kenya 2003 |
| Notes: | Ever married women aged 15-49 years |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Overweight/obesity by age
Women, 2014
| Survey type: | Measured |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey Kenya 2014 |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2003
| Survey type: | Measured |
| Sample size: | 7047 |
| References: | Demographic Health Survey, Kenya 2003 |
| Notes: | Ever married women aged 15-49 years |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Overweight/obesity by region
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey, Kenya 2014 |
| Notes: | Includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey Kenya 2014 |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2003
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 7047 |
| References: | Demographic Health Survey, Kenya 2003 |
| Notes: | Ever married women aged 15-49 years |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Overweight/obesity by socio-economic group
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 13143 |
| Area covered: | National |
| References: | Demographic Health Survey Kenya 2014 |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2003
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 7047 |
| References: | Demographic Health Survey, Kenya 2003 |
| Notes: | Ever married women aged 15-49 years |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Insufficient physical activity
Adults, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Men, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Women, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Children, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Boys, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Girls, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Children, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Boys, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Girls, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Estimated per capita fruit intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita fruit intake (g/day) |
Estimated per-capita processed meat intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita processed meat intake (g per day) |
Estimated per capita whole grains intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita whole grains intake (g/day) |
Mental health - depression disorders
Adults, 2015
| References: | Prevalence data from Global Burden of Disease study 2015 (http://ghdx.healthdata.org) published in: Depression and Other Common Mental Disorders: Global Health Estimates. Geneva:World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO. |
| Definitions: | % of population with depression disorders |
Mental health - anxiety disorders
Adults, 2015
| References: | Prevalence data from Global Burden of Disease study 2015 (http://ghdx.healthdata.org) published in: Depression and Other Common Mental Disorders: Global Health Estimates. Geneva:World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO. |
| Definitions: | % of population with anxiety disorders |
Oesophageal cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, oesophagus, adults ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, oesophagus, adults ages 20+. ASR (World) per 100,000 |
Breast cancer
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, breast, females, ages 20+. ASR (World) per 100,000 |
Colorectal cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, colorectum, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, colorectum, adults, ages 20+. ASR (World) per 100,000 |
Pancreatic cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, pancreas, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, pancreas, adults, ages 20+. ASR (World) per 100,000 |
Gallbladder cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, gallbladder, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, gallbladder, adults, ages 20+. ASR (World) per 100,000 |
Kidney cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, kidney, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, kidney, adults, ages 20+. ASR (World) per 100,000 |
Cancer of the uterus
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, cervix uteri, females, ages 20+. ASR (World) per 100,000 |
Raised blood pressure
Adults, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Men, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Women, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Raised cholesterol
Adults, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Men, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Women, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Raised fasting blood glucose
Men, 2014
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A869?lang=en |
| Definitions: | Age Standardised % raised fasting blood glucose (>= 7.0 mmol/L or on medication). |
Women, 2014
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A869?lang=en |
| Definitions: | Age Standardised % raised fasting blood glucose (>= 7.0 mmol/L or on medication). |
Diabetes prevalence
Adults, 2019
| Age: | 20-79 |
| References: | Reproduced with kind permission International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels,Belgium: 2019. Available at: https://www.diabetesatlas.org |
| Definitions: | Diabetes age-adjusted comparative prevalence (%). |
Adults, 2017
| References: | Reproduced with kind permission of IDF, International Diabetes Federation. IDF Diabetes Atlas, 8th edition. Brussels, Belgium: International Diabetes Federation, 2017. http://www.diabetesatlas.org |
| Definitions: | Diabetes age-adjusted comparative prevalence (%). |
Health systems
Economic classification: Lower Middle Income
Health systems summary
Kenya has a devolved healthcare system that can be split into three subsystems; the public sector, the commercial private sector and the faith-based sector. Most Kenyans receive healthcare from the underfunded public sector that has suffered in recent years from successive nurse and doctor strikes, a shortage of health workers and corruption. There is a mandatory national hospital insurance fund for formal sector workers that is optional for informal workers.
Currently, healthcare is financed through a combination of insurance, government funding, donor funding and out of pocket (OOP) payments. Both public and private facilities charge user fees with some exceptions such as certain facilities and age groups. It is estimated that OOP payments by individuals and donor funding make up 26.1% and 23.4% of total health expenditure respectively, indicating a precarious financial situation that offers inadequate financial protection. Kenya has committed to reforming its health financing by 2022 in order to achieve universal health coverage.
Indicators
| Where is the country’s government in the journey towards defining ‘Obesity as a disease’? | No |
| Where is the country’s healthcare provider in the journey towards defining ‘Obesity as a disease’? | No |
| Is there specialist training available dedicated to the training of health professionals to prevent, diagnose, treat and manage obesity? | No |
| Have any taxes or subsidies been put in place to protect/assist/inform the population around obesity? | No |
| Are there adequate numbers of trained health professionals in specialties relevant to obesity in urban areas? | No |
| Are there adequate numbers of trained health professionals in specialties relevant to obesity in rural areas? | No |
| Are there any obesity-specific recommendations or guidelines published for adults? | Not known |
| Are there any obesity-specific recommendations or guidelines published for children? | Not known |
| In practice, how is obesity treatment largely funded? | Out of pocket |
Summary of stakeholder feedback
Obesity is not yet considered to be a disease in Kenya. Rather, it is considered a lifestyle condition and by some, a symbol of wealth and success to be celebrated. Stakeholders reported that obesity is not yet a priority as a result of these perceptions and the continued challenges of communicable diseases. It is noted that there are some positive developments however, such as the development of healthy food guidelines for children and the training and deployment of nutritionists.
It appears that obesity is only treated when comorbidities and complications have developed. Any treatment received is then paid for out of pocket by the individuals, typically in the private sector. Overall, treatment options are limited in urban areas, and are even worse in rural areas. In the few instances where one living with obesity enters the health system, they tend to leave the system with their obesity unaddressed because of the lack of obesity-specific care pathways and policies.
Stakeholders stressed that there are inadequate numbers of obesity specialists in both urban and rural areas. There is no specialist obesity training available, but it appears that there is also a lack of general training available. This lack of training contributes to the high numbers of individuals leaving the system with their obesity untreated.
There were conflicting responses on the presence of obesity management guidelines. One stakeholder reported that a set had been developed but were poorly disseminated. Others were not aware of the existence of any guidelines.
Based on interviews/survey returns from 5 stakeholders
Last updated: June 2020
