Endline Survey Dataset on Agricultural Practices, Dietary Diversity, Socio-Economic Indicators, and Household Decision-Making in Vihiga County, Kenya (2020)

Termote, C.; Aluso, L.O.; Akingbemisilu, T.H. (2025) Endline Survey Dataset on Agricultural Practices, Dietary Diversity, Socio-Economic Indicators, and Household Decision-Making in Vihiga County, Kenya (2020). https://doi.org/10.7910/DVN/NHXOIS

This dataset originates from an endline survey conducted in Vihiga County, Kenya, between November and December 2020, as part of the project titled "Improving access to and benefits from a wealth of diverse seeds to support on-farm biodiversity for healthy people in resilient landscapes." The survey aimed to assess the outcomes of agricultural and nutritional interventions implemented in the study area, building on the baseline conducted in 2018. The dataset includes detailed information on demographic and socio-economic characteristics, household income, market access, wealth profiles, household food security, dietary changes, maternal nutritional knowledge, and attitudes and . Additionally, it captures household agricultural practices, including the adoption of climate-smart technologies, social seed networks for traditional leafy vegetables and legumes, smart poultry farming practices and household decision-making among women. Quantitative 24-hour dietary recall data for women and children was also collected to assess dietary diversity and nutritional adequacy. The survey targeted households across intervention and comparison sublocations, capturing the perspectives of direct beneficiaries, indirect beneficiaries, and non-beneficiaries. The principal investigators sought to address critical questions such as: i) How have dietary diversity and nutritional practices evolved since the baseline survey? ii) What impact have the agricultural and nutrition interventions had on household food security and resilience? iii) How do household decision-making dynamics, particularly among women, influence agricultural and nutritional outcomes? iv) What are the differences in outcomes between households in intervention and comparison areas? v) This dataset offers a comprehensive view of the study area's agricultural, nutritional, and socio-economic landscape, providing valuable insights for evaluating the project's long-term impact. Methodology:The endline data was collected through a survey conducted in Vihiga County, Kenya, from November to December 2020. The study employed a quasi-randomized study design, sampling households from three categories: proposed intervention areas (198 households), comparison areas (200 households), and areas with prior interventions conducted before this baseline study (64 households). In total, 462 households were sampled. Including the previously intervened areas aimed to assess differences over time between these areas and the newly selected intervention areas. Households were eligible if they included at least one woman of reproductive age (15–49 years) and a child aged 6–23 months. In the intervention sublocations, 31 direct beneficiary households were purposively included from the newly intervention site to evaluate differences between participants directly involved in the agricultural and nutritional interventions and non-participants. The survey utilized structured data collection tools, including a household questionnaire capturing demographic and socio-economic characteristics, household income, market access, food security, wealth profiles, agricultural practices, and maternal nutritional knowledge; a section on household decision-making, focusing on women's roles and dynamics in decision-making processes; a 24-hour dietary recall for women and children, collected over two non-consecutive days to assess dietary diversity and adequacy, with the second recall conducted for over 50% of the sample. Data collection was conducted by trained enumerators using the KoBo Toolbox for digital data capture. The dietary recall remained paper-based, with data digitized for analysis. Rigorous cleaning and validation processes were applied to ensure data accuracy and reliability. The endline dataset serves as a critical resource for assessing the long-term impacts of interventions targeting agricultural practices, nutrition education, and household resilience, with a specific focus on women's roles in household decision-making.