World Aquaculture Safari 2025

June 24 - 27, 2025

Kampala, Uganda

Add To Calendar 27/06/2025 15:30:0027/06/2025 15:50:00Africa/CairoWorld Aquaculture Safari 2025DATA DRIVEN INSIGHTS INTO ENHANCING AQUACULTURE PRODUCTIVITY AND INCOME: THE ROLE OF SOCIO-DEMOGRAPHIC FACTORS, FARM AND MARKET CHARACTERISTICS IN KENYABujagali HallThe World Aquaculture Societyjohnc@was.orgfalseDD/MM/YYYYanrl65yqlzh3g1q0dme13067

DATA DRIVEN INSIGHTS INTO ENHANCING AQUACULTURE PRODUCTIVITY AND INCOME: THE ROLE OF SOCIO-DEMOGRAPHIC FACTORS, FARM AND MARKET CHARACTERISTICS IN KENYA

Horace Owiti2*, Michael Waweru1, Steve Ogega1, Hezron Awandu2, Derrick Onyango2, Patrick Otuo2, Nimo Jamal1, Fonda Jane Awuor2, Mary Opiyo3, Domitila Kyule3 and Sammy Macaria1

 

1Aquaculture Business Development Programme, PO BOX 904 - 10100, Nyeri, Kenya

2Kenya Marine and Fisheries Research Institute, Kisumu Research Centre, PO BOX 1881 - 40100, Kisumu, Kenya

3Kenya Marine and Fisheries Research Institute, Sagana Aquaculture Research Centre, PO BOX 451-10230 Sagana, KENYA Kenya

*Corresponding author:  howiti@kmfri.go.ke

 



in Africa, particularly as capture fisheries decline due to overexploitation, pollution, and climate change. In Kenya, the Aquaculture Business Development Programme (ABDP) has been a major public investment aimed at enhancing fish production and income among smallholder farmers. However, despite standardized inputs and training across counties, disparities in productivity and income persist, suggesting that other underlying factors may be influencing outcomes. This study investigates the influence of socio-demographic factors, farm characteristics, and market access on aquaculture productivity (kg) and income (USD) among 927 smallholder farmers across 15 counties participating in ABDP. The objective was to determine which human and contextual factors most significantly impact production and sales outcomes in a standardized aquaculture intervention. Data were collected using structured digital surveys administered via Kobo Toolbox, and analyzed using log-log linear regression models to interpret elasticities and significance of multiple predictors. Key findings reveal that education, fish species, variable input costs, and regional location significantly influenced both production and income levels. For instance, a 1% increase in variable input costs was associated with a 2.8% increase in fish production and a 9.4% increase in income. Farmers in Western Kenya exhibited higher productivity than those in Central/Eastern regions, while those selling to institutional and hotel markets achieved higher incomes. Socio-demographic factors such as gender and household size had limited direct influence on outcomes when controlling for other variables. These results suggest that beyond input provisioning, aquaculture outcomes are shaped by market dynamics, farmer knowledge, and regional conditions. We recommend strengthening farmer education, tailoring regional interventions, and enhancing access to high-value markets through inclusive value chains. Policy shifts towards differentiated support based on farmer profiles and location could improve aquaculture’s contribution to food security and rural livelihoods in Kenya.

Keywords: Aquaculture productivity, socio-demographic factors, smallholder farmers, market access.