Youth Unemployment and Crime Rates in Mathare Sub-County, Nairobi County, Kenya

Youth unemployment remains a major global challenge and is strongly linked to rising levels of criminality, particularly in informal urban settlements. This study examined the relationship between youth unemployment and criminality in Mathare Sub-County, Nairobi, Kenya. The research was guided by Strain Theory and Social Learning Theory to explain how socioeconomic pressures influence youth involvement in crime.
The study employed a survey research design using both quantitative and qualitative approaches. Data were collected from youths aged 18–35 years through questionnaires and interview guides. Quantitative data were analyzed using SPSS, while qualitative data were analyzed through thematic content analysis.
The findings indicated a strong association between youth unemployment and increased crime rates in the Mathare informal settlement. Many respondents lacked stable income and employment opportunities, exposing them to extreme poverty and making criminal activities such as robbery, drug trafficking, and prostitution alternative survival strategies. High unemployment also increased frustration, idle time, and exposure to delinquent peer groups.
The study concludes that youth unemployment is a key driver of criminal activity in informal settlements. It recommends youth-focused education and skills training, fair recruitment practices, economic empowerment programs, and job creation policies as essential strategies for reducing unemployment and crime among youths.

CRIMINOLOGY

1. Agnew, R. (1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1), 47–88. https://doi.org/10.1111/j.1745-9125.1992.tb01093 [Google Scholar] [Crossref]

2. Adebayo, A. (2013). Youth unemployment and crime in Nigeria: Anexus implications for national development. International Journal of Sociology and Anthropology, 59–350. [Google Scholar] [Crossref]

3. Ajaegbu, O. (2012). Rising youth unemployment and violent crimes in Nigeria. American Journal of Social Issues and Humanities, 87–99. [Google Scholar] [Crossref]

4. Akers, R. L. (2002). A social learning theory of crime. In F. T. Cullen & R. Agnew (Eds.), Criminological theories: Bridging the past to the future (pp. 135–143). [Google Scholar] [Crossref]

5. Akers, R. L., & Jensen, G. F. (2017). The empirical status of social learning theory of crime and deviance: The past, present, and future. In Taking stock (pp. 37–76). Routledge. [Google Scholar] [Crossref]

6. Bausman, K., & Goe, W. (2004). An examination of the link between employment volatility and the spatial distribution of property crime rates. American Journal of Economics and Sociology, 665–696. [Google Scholar] [Crossref]

7. Burton, V. S., Jr., & Cullen, F. T. (1992). The empirical status of strain theory. Journal of Crime and Justice, 15(2), 1–30. [Google Scholar] [Crossref]

8. Buonanno, P., & Montolio, D. (2008). Identifying socio-economic and demographic determinants of crime across Spanish provinces. International Review of Law and Economics, 89–97. [Google Scholar] [Crossref]

9. Calvo, A., Antoni, V., & Zenou, Y. (2007). Strong and weak ties in employment and crime. Journal of Public Economics, 203–233. [Google Scholar] [Crossref]

10. Creswell, J., & Clark, P. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications. [Google Scholar] [Crossref]

11. Johnson, B., & Christensen, L. (2010). Educational research: Quantitative, qualitative, and mixed approaches (4th ed.). Sage Publications. [Google Scholar] [Crossref]

12. Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4th ed.). Wadsworth/Thomson Learning. [Google Scholar] [Crossref]

13. KNBS (Kenya National Bureau of Statistics). (2009). 2009 Kenya population and housing census: Population distribution by administrative units. Government. [Google Scholar] [Crossref]

14. Merton, R. K. (1938). Social structure and anomie. American Sociological Review, 3(5), 672–682. https://doi.org/10.2307/2084686 [Google Scholar] [Crossref]

15. NPS (National Police Service, Kenya). (2016). Crime statistics report 2016. National Police Service. [Google Scholar] [Crossref]

16. Pratt, T. C., Cullen, F. T., Sellers, C. S., Winfree, L. T., Madensen, T. D., Daigle, L. E., & Gau, J. M. (2010). The empirical status of social learning theory: A meta-analysis. Justice Quarterly, 27(6), 765–802. [Google Scholar] [Crossref]

17. Robinson, P. H. (2005). Corporate crime, elites, and white-collar offenders: Strain and opportunity in the contemporary United States. Journal of Contemporary Criminal Justice, 21(3), 190–204. https://doi.org/10.1177/1043986205277418 [Google Scholar] [Crossref]

18. Winfree, L. T., Jr., Backström, T., & Mays, G. L. (1994). Social learning theory and delinquency: Integrating theory and research. Journal of Research in Crime and Delinquency, 31(3), 299–322. [Google Scholar] [Crossref]

19. Wu, D., & Wu, Z. (2012). Crime, inequality and unemployment in England and Wales. Applied Economics, 44(29), 3765–3775. https://hdl.handle.net/10.1080/00036846.2011.581217 [Google Scholar] [Crossref]

• Occupational Culture in Relation to Job Satisfaction and Work Performance among Police
• Inmates' Character Reformation and Recidivism in Nigeria: A Study of Okaka Correctional Facility, Yenagoa, Bayelsa State.
• Life World of Former Female Basic Internal Security Operations Course (BISOC) Trainees
• Efficacy of Fingerprint and Facial Recognition in Enhancing National Security in Kenya
• No More Catcalling: Awareness of College of Criminal Justice Education Students on Republic Act 11313 Also Known as Safe Spaces Act