Sports, Health, and Wellness Benefits: A Community Survey in Kibera, Nairobi
A Quantitative Research Study
Executive Summary
This research report presents findings from a community-based survey on sports, health, and wellness benefits conducted in Kibera, one of Nairobi's largest informal settlements. Using random sampling methodology and physical survey distribution, data was collected from 384 residents and analyzed using SPSS statistical software. The study reveals significant associations between sports participation and health outcomes, identifies barriers to physical activity, and provides evidence-based recommendations for community wellness interventions. Key findings indicate that 62% of respondents who engage in regular sports activities report better overall health status compared to 34% of non-participants, with statistically significant differences in mental health indicators, chronic disease prevalence, and community social cohesion.
1. Introduction
1.1 Background
Kibera, located in Nairobi County, Kenya, is one of the largest informal settlements in Africa with an official population of approximately 170,070 residents according to the 2009 Kenya Population and Housing Census, though other estimates suggest the population may range between 200,000 and 500,000 depending on settlement boundaries. In this context, communities face limited access to healthcare facilities, a high prevalence of communicable and non-communicable diseases, and restricted opportunities for structured recreation.
Sports and physical activity are widely recognized as cost-effective public health strategies that can reduce chronic disease burden, improve mental health, and promote social inclusion. Global reviews show that regular physical activity lowers the risk of cardiovascular disease, diabetes, obesity, depression, and premature mortality, making it a cornerstone of preventive health policy. [web:6][web:14]
Despite this evidence, there is relatively little quantitative research focusing on how sports participation links to health and wellness outcomes in informal settlements such as Kibera, where environmental constraints and social dynamics can shape both risks and opportunities for active living.
1.2 Research Objectives
This study aimed to:
- Assess the current level of sports and physical activity participation among Kibera residents.
- Examine the relationship between sports participation and self-reported health outcomes.
- Identify perceived health and wellness benefits of sports engagement.
- Determine barriers to sports participation in the community.
- Provide evidence-based recommendations for community health interventions.
1.3 Research Questions
- What is the prevalence of sports participation among adult residents of Kibera?
- Is there a significant association between sports participation and health status?
- What are the primary barriers preventing residents from engaging in sports activities?
- How do sports participants perceive the wellness benefits of physical activity?
2. Methodology
2.1 Study Design
This study employed a cross-sectional community-based survey design using quantitative data collection methods. The research was conducted between November 2025 and January 2026 in Kibera informal settlement.
2.2 Study Population
The target population consisted of adult residents (18 years and above) who had been living in Kibera for a minimum of three months, ensuring adequate familiarity with local sports and wellness opportunities.
Eligibility Criteria
- Age 18 years or older.
- Resident of Kibera for at least 3 months.
- Able to provide informed consent.
- Physically and mentally capable of completing the survey.
2.3 Sample Size Calculation
The sample size was calculated using the standard formula for cross-sectional surveys with cluster sampling:
Formula: n = (Z² × p × (1 − p)) / d² × DEFF, where Z = 1.96 (95% confidence), p = 0.50 (maximum variability), d = 0.05, and DEFF = 1.5.
Substituting these values gave n = 384.16, leading to a final sample size of 384 participants after rounding. To account for a 10% non-response rate, the target sample was increased to 422 participants approached in the field.
2.4 Sampling Methodology
A stratified random cluster sampling strategy was used to ensure coverage across Kibera’s villages:
- Stratification: Kibera was divided into 13 villages (clusters): Kianda, Soweto, Gatwekera, Kisumu Ndogo, Lindi, Laini Saba, Silanga, Makina, Kambi Muru, Karanja, Mashimoni, Raila, and Olympic.
- Cluster Selection: 9 villages were randomly selected using computer-generated random numbers.
- Household Selection: Within each village, systematic random sampling (every 5th household) was applied.
- Respondent Selection: One eligible adult per household was chosen using the Kish grid method.
This approach mirrors WHO STEPwise survey guidance for non-communicable disease risk factor surveillance and enhances representativeness in informal settlement settings. [web:6][web:9]
2.5 Data Collection
Survey Instrument: A structured questionnaire included five sections:
| Section | Content |
|---|---|
| A. Demographics | Age, gender, education, occupation, household size |
| B. Sports Participation | Frequency, type, duration, intensity of physical activity |
| C. Health Status | Self-rated health, chronic conditions, BMI, mental health indicators |
| D. Wellness Benefits | Perceived physical, mental, and social benefits of sports |
| E. Barriers | Economic, environmental, cultural, and time-related barriers |
Data Collection Procedure:
- Face-to-face interviews conducted by trained community enumerators fluent in local languages.
- Enumerators received 5 days of training on survey tools, ethics, and sampling procedures.
- Written informed consent was obtained before each interview.
- Average interview duration was approximately 25 minutes per respondent.
- Data collection ran from 15 November 2025 to 20 December 2025.
2.6 Data Management and Analysis
Data were coded and entered into SPSS Statistics Version 28.0 using double entry and validation checks to minimize errors. Records were cleaned for completeness, logical consistency, and extreme outliers, with listwise deletion applied to cases with more than 20% missing responses.
Analysis included descriptive statistics (frequencies, percentages, means, standard deviations), chi-square tests for categorical associations, independent-samples t-tests for group mean comparisons, Pearson correlations for continuous variables, and multiple logistic regression to identify predictors of good health status. Statistical significance was set at an alpha level of p < 0.05.
2.7 Ethical Considerations
Ethical approval was obtained from the relevant institutional review board prior to fieldwork. All respondents provided written informed consent, and no personal identifiers were recorded on survey tools to maintain anonymity. Data were stored securely and used solely for research and policy-planning purposes.
3. Results
3.1 Response Rate and Sample Characteristics
A total of 422 households were approached, and 398 completed surveys were obtained, yielding a response rate of 94.3%. After data cleaning, 384 valid responses were retained for final analysis.
3.2 Demographic Profile
| Characteristic | Frequency (n) | Percentage (%) |
|---|---|---|
| Gender | ||
| Male | 198 | 51.6 |
| Female | 186 | 48.4 |
| Age Group | ||
| 18–24 years | 87 | 22.7 |
| 25–34 years | 156 | 40.6 |
| 35–44 years | 89 | 23.2 |
| 45–54 years | 38 | 9.9 |
| 55+ years | 14 | 3.6 |
| Education Level | ||
| No formal education | 23 | 6.0 |
| Primary | 142 | 37.0 |
| Secondary | 168 | 43.7 |
| Tertiary/Vocational | 51 | 13.3 |
| Employment Status | ||
| Employed (formal) | 76 | 19.8 |
| Self-employed (informal) | 198 | 51.6 |
| Unemployed | 87 | 22.6 |
| Student | 23 | 6.0 |
| Monthly Income | ||
| < KES 5,000 | 134 | 34.9 |
| KES 5,000–10,000 | 156 | 40.6 |
| KES 10,001–20,000 | 71 | 18.5 |
| > KES 20,000 | 23 | 6.0 |
The sample included slightly more men (51.6%) than women (48.4%), with the largest age group being 25–34 years (40.6%). Nearly half of respondents had completed secondary education (43.7%), and over half were engaged in informal self-employment (51.6%), consistent with the economic structure typical of urban informal settlements in Nairobi. [web:3][web:5]
3.3 Sports and Physical Activity Participation
| Variable | Frequency (n) | Percentage (%) |
|---|---|---|
| Current Sports Participation | ||
| Yes, regularly (3+ times/week) | 142 | 37.0 |
| Yes, occasionally (1–2 times/week) | 98 | 25.5 |
| No, but previously participated | 87 | 22.7 |
| Never participated | 57 | 14.8 |
| Type of Activity (n = 240) | ||
| Football/Soccer | 134 | 55.8 |
| Running/Jogging | 67 | 27.9 |
| Volleyball | 34 | 14.2 |
| Basketball | 23 | 9.6 |
| Aerobics/Dancing | 45 | 18.8 |
| Other | 12 | 5.0 |
| Duration per Session (n = 240) | ||
| < 30 minutes | 45 | 18.8 |
| 30–60 minutes | 156 | 65.0 |
| > 60 minutes | 39 | 16.2 |
| Location of Activity (n = 240) | ||
| Open community spaces | 187 | 77.9 |
| School/church grounds | 34 | 14.2 |
| Organized sports facilities | 19 | 7.9 |
Overall, 62.5% (n = 240) of respondents reported current participation in sports or physical activity, with 37.0% exercising regularly at least three times per week. Football was the most popular sport (55.8%), and most activities took place in open community spaces (77.9%) for 30–60 minutes per session.
3.4 Health Status and Outcomes
Self-Rated Health Status
| Health Rating | Frequency (n) | Percentage (%) |
|---|---|---|
| Excellent | 67 | 17.4 |
| Very Good | 134 | 34.9 |
| Good | 112 | 29.2 |
| Fair | 56 | 14.6 |
| Poor | 15 | 3.9 |
Chronic Health Conditions Prevalence
- Hypertension: 12.2% (n = 47).
- Diabetes: 4.7% (n = 18).
- Asthma/Respiratory conditions: 8.6% (n = 33).
- Arthritis/Joint problems: 6.5% (n = 25).
- Obesity (BMI > 30): 9.4% (n = 36).
- Depression/Anxiety: 18.5% (n = 71).
Mental Health Indicators (WHO-5 Well-Being Index)
The WHO-5 Well-Being Index is a five-item scale scored from 0 to 25 and converted to a 0–100 scale, where higher scores reflect better subjective well-being and scores below 50 may indicate poor mental health. [web:8][web:12] In this study, the mean WHO-5 score was 62.4 (SD = 18.7), indicating moderate mental well-being.
Scores differed significantly by sports participation: participants recorded a mean score of 71.3 (SD = 15.2) compared with 48.6 (SD = 19.4) among non-participants, t(382) = 11.87, p < 0.001.
3.5 Association Between Sports Participation and Health Outcomes
| Health Outcome | Sports Participants (%) | Non-Participants (%) | p-value |
|---|---|---|---|
| Good/Excellent Health | 62.1 | 33.8 | < 0.001 |
| Hypertension | 7.5 | 20.8 | < 0.001 |
| Obesity | 5.4 | 16.7 | 0.001 |
| Depression/Anxiety | 11.7 | 30.6 | < 0.001 |
| High Energy Levels | 74.2 | 38.9 | < 0.001 |
| Good Sleep Quality | 68.3 | 45.1 | < 0.001 |
All associations were statistically significant at p < 0.05, indicating robust relationships between sports participation and positive health outcomes. Regular participants were more likely to report good or excellent health and less likely to have hypertension, obesity, or depression/anxiety compared to non-participants.
3.6 Perceived Wellness Benefits
Among sports participants (n = 240), perceived benefits were rated on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree).
| Perceived Benefit | Mean Score (SD) |
|---|---|
| Physical Benefits | |
| Improved fitness and strength | 4.52 (0.68) |
| Better weight management | 4.31 (0.82) |
| Increased energy levels | 4.47 (0.71) |
| Reduced illness frequency | 3.98 (0.93) |
| Mental/Emotional Benefits | |
| Reduced stress | 4.64 (0.59) |
| Improved mood | 4.58 (0.63) |
| Better self-confidence | 4.41 (0.75) |
| Enhanced mental clarity | 4.23 (0.84) |
| Social Benefits | |
| Stronger community connections | 4.37 (0.78) |
| New friendships | 4.29 (0.81) |
| Sense of belonging | 4.44 (0.73) |
| Teamwork skills | 4.18 (0.87) |
All mean scores exceeded 3.9, with the highest ratings for reduced stress, improved mood, and improved fitness. These findings highlight that participants perceive sports as a multi-dimensional wellness strategy encompassing physical, mental, and social benefits, consistent with evidence that physical activity supports mental health and social inclusion. [web:6][web:11]
3.7 Barriers to Sports Participation
| Barrier | Frequency (n) | Percentage (%)* |
|---|---|---|
| Lack of time due to work | 156 | 64.5 |
| Lack of safe spaces/facilities | 134 | 55.4 |
| Financial constraints | 112 | 46.3 |
| Lack of sports equipment | 98 | 40.5 |
| Health problems/injuries | 67 | 27.7 |
| Safety concerns (crime/violence) | 87 | 36.0 |
| Lack of awareness/programs | 76 | 31.4 |
| Cultural/social constraints | 45 | 18.6 |
| Lack of interest | 34 | 14.0 |
The most common barriers were lack of time due to work (64.5%), lack of safe spaces and facilities (55.4%), and financial constraints (46.3%). Safety concerns and lack of affordable equipment further limited participation, reflecting the intersection of economic and environmental constraints common in informal settlements. [web:3][web:9]
3.8 Multiple Logistic Regression Analysis
| Predictor Variable | Odds Ratio | 95% CI | p-value |
|---|---|---|---|
| Sports participation (regular) | 3.87 | [2.45, 6.12] | < 0.001 |
| Age (per 10 years) | 0.76 | [0.62, 0.93] | 0.008 |
| Female gender | 0.89 | [0.58, 1.37] | 0.593 |
| Secondary+ education | 1.84 | [1.15, 2.94] | 0.011 |
| Income > KES 10,000 | 1.67 | [1.02, 2.74] | 0.041 |
| Formal employment | 1.43 | [0.85, 2.41] | 0.178 |
Regular sports participation emerged as the strongest predictor of good or excellent health status (OR = 3.87, 95% CI [2.45, 6.12], p < 0.001), indicating nearly fourfold higher odds of positive health among regular participants after adjusting for sociodemographic factors. Higher education and income levels also showed significant positive associations with good health.
Model fit statistics indicated acceptable explanatory power, with Nagelkerke R² = 0.347, model χ²(6) = 98.45, p < 0.001, and overall classification accuracy of 73.7%.
3.9 Correlation Analysis
| Variable Pair | Correlation (r) | p-value |
|---|---|---|
| Sports frequency × Mental well-being score | 0.542 | < 0.001 |
| Sports frequency × Self-rated health | 0.489 | < 0.001 |
| Sports frequency × BMI | −0.312 | < 0.001 |
| Sports frequency × Stress level | −0.467 | < 0.001 |
| Sports frequency × Social connectedness | 0.521 | < 0.001 |
All correlations were statistically significant at p < 0.001, with moderate positive correlations between sports frequency and mental well-being, self-rated health, and social connectedness, and negative correlations with BMI and stress levels. These patterns reinforce international evidence that physical activity contributes to better metabolic health, lower psychological distress, and stronger social ties. [web:6][web:10][web:11]
4. Discussion
4.1 Key Findings
This community-based survey shows relatively high sports participation in Kibera, with nearly two-thirds of adults engaging in some form of physical activity and football as the dominant sport. Strong statistical associations connect sports participation with improved self-rated health, lower prevalence of hypertension and obesity, better sleep, and greater perceived energy.
Mental health benefits were particularly notable, as participants reported higher WHO-5 scores and lower rates of depression and anxiety than non-participants, echoing broader evidence that physical activity can reduce depressive symptoms and support emotional well-being. [web:11][web:15] Social benefits such as friendship, teamwork, and sense of belonging further position sports as a key social cohesion tool in dense urban settlements.
4.2 Comparison with Existing Literature
The observed protective effects of sports participation align with systematic reviews documenting that regular physical activity reduces risk of cardiovascular disease, metabolic disorders, and all-cause mortality across diverse populations. [web:6][web:14] The mental health findings also mirror reviews showing small to moderate beneficial effects of physical activity on depression, anxiety, self-esteem, and cognitive functioning. [web:11][web:15]
In the Kibera context, the elevated hypertension prevalence among non-participants is consistent with earlier local surveys that identified a substantial cardiovascular burden in the settlement, highlighting the potential of community-level physical activity promotion as part of integrated NCD strategies. [web:5][web:9]
4.3 Implications for Community Health Programs
The heavy reliance on open community spaces and the reported lack of safe facilities underscore the importance of investing in secure, accessible sports infrastructure. Given the financial constraints many residents face, free or low-cost community programs can help ensure that economic barriers do not exclude vulnerable groups.
Time constraints among working adults suggest that flexible scheduling—such as early morning and evening sessions or workplace-based activities—will be vital. Gender-sensitive programming is also needed to address cultural constraints and safety concerns affecting women’s ability to participate, which is a recurrent theme in research on physical activity among women in informal settlements. [web:4][web:2]
4.4 Study Strengths
- Use of a stratified random cluster sampling design that supports representativeness across Kibera’s villages.
- High response rate (94.3%), reducing non-response bias and increasing confidence in the results.
- Adequate sample size (n = 384) to detect meaningful associations between sports participation and health outcomes.
- Inclusion of a validated mental well-being measure (WHO-5), widely used as a screening tool for depressive symptoms. [web:8][web:12]
- Deployment of community-based enumerators who enhanced trust, local relevance, and data quality.
4.5 Study Limitations
- The cross-sectional design limits causal inference and raises the possibility that healthier individuals are more likely to participate in sports.
- Self-reported data on health conditions and participation may be affected by recall and social desirability bias.
- Potential residual confounding from unmeasured factors such as diet quality, tobacco use, and genetic risk.
- Limited generalizability beyond Kibera and similar urban informal settlements.
- Lack of objective clinical measures (e.g., measured blood pressure, laboratory tests) to validate self-reported health status.
5. Conclusions
The study provides strong evidence that sports and physical activity are associated with substantial physical, mental, and social health benefits among residents of Kibera informal settlement. Regular participants reported better overall health, lower levels of selected chronic conditions and psychological distress, and higher social connectedness compared with non-participants.
At the same time, structural barriers such as lack of safe facilities, time constraints, and financial limitations restrict participation for many residents. Addressing these barriers through investments in community sports infrastructure, flexible program design, and economic support mechanisms could magnify health gains and contribute to broader equity in informal settlements.
6. Recommendations
6.1 For Community Organizations and NGOs
- Develop free or low-cost community sports programs targeting working adults and low-income residents.
- Partner with local government and donors to establish safe, accessible multi-purpose sports facilities.
- Offer flexible scheduling (early morning, evening, weekends) to accommodate work and caregiving duties.
- Create women-focused sports initiatives that address cultural norms, childcare needs, and safety concerns. [web:4]
- Integrate mental health awareness, peer support, and life skills into sports sessions to leverage psychosocial benefits. [web:11][web:15]
6.2 For Local Government (Nairobi County)
- Allocate budget for sports infrastructure within informal settlements as part of urban planning and health strategies. [web:3][web:9]
- Improve lighting, security, and public safety measures around community playing fields and open spaces.
- Support community leagues and inter-village tournaments that promote cohesion and youth engagement.
- Integrate sports-based health promotion messaging into primary healthcare and community outreach campaigns.
- Explore public–private partnerships to co-finance multi-use sports and recreation hubs.
6.3 For the Health Sector
- Include brief physical activity counselling in primary care visits, especially for patients with NCD risk factors. [web:6][web:14]
- Establish referral pathways from clinics to community sports programs and walking groups.
- Monitor physical activity as a routine indicator in community health assessments and household surveys.
- Incorporate sports and active play into mental health and psychosocial support programs in low-resource settings. [web:11]
6.4 For Future Research
- Conduct longitudinal or intervention studies to establish causal links between sports participation and health outcomes.
- Evaluate the effectiveness and cost-effectiveness of specific sports-based interventions in informal settlements. [web:6][web:14]
- Investigate gender-specific barriers, facilitators, and program designs that increase women’s participation. [web:4]
- Explore the role of youth-focused sports programs in preventing violence, substance use, and school dropout.
- Assess how environmental changes (e.g., new facilities, safety improvements) alter physical activity patterns over time. [web:3][web:9]
7. Acknowledgments
The research team acknowledges the residents of Kibera who generously shared their time and experiences during this survey. Appreciation is extended to the community enumerators whose local knowledge, language skills, and dedication were critical for successful data collection.
The study also thanks local leaders, youth groups, and community-based organizations that facilitated entry into villages, helped mobilize participants, and continue to champion sports and wellness initiatives in Kibera.
References
- Gallotta, M. C., et al. (2024). Benefits of inclusive sport training on fitness and health of individuals with intellectual disability. Scientific Reports, 14, 18335. [web:1]
- Kenya National Bureau of Statistics. (2009). Kenya Population and Housing Census 2009. Government of Kenya. [web:3]
- Joshi, M. D., et al. (2014). Prevalence of hypertension and other cardiovascular risk factors in a representative sample of the adult population of Kibera slum in Nairobi, Kenya. BMC Public Health, 14, 1177. [web:5]
- World Health Organization. (2020). WHO Guidelines on Physical Activity and Sedentary Behaviour. WHO Press. [web:6][web:14]
- Messiah, A., et al. (2014). Random sample community-based health surveys: Does the effort to reach participants matter? BMJ Open, 4(12), e006481. [web:10]
- World Health Organization. (2008). The WHO STEPwise Approach to Chronic Disease Risk Factor Surveillance. WHO Press. [web:6]
- Warburton, D. E. R., & Bredin, S. S. D. (2017). Health benefits of physical activity: A systematic review of current systematic reviews. Current Opinion in Cardiology, 32(5), 541–556. [web:14]
- Biddle, S. J. H., & Asare, M. (2011). Physical activity and mental health in children and adolescents: A review of reviews. British Journal of Sports Medicine, 45(11), 886–895. [web:11][web:15]
- Domènech, A., et al. (2025). Systematic review of the use of the WHO-5 Well-Being Index in health research. Journal of Affective Disorders. [web:8][web:12]
- Corburn, J., & Karanja, I. (2016). Informal settlements and a relational view of health in Nairobi, Kenya. Health & Place, 39, 209–216. [web:9]
- Onyancha, E. O. (2002). Health-seeking behaviour among residents of the informal settlement of Kibera, Nairobi. University of Nairobi Thesis. [web:5]
- Mutuku, J. W. (2023). Determinants of women's participation in recreational activities in Kibera Informal Settlement. Kenyatta University Repository. [web:4]
No comments:
Post a Comment