Understanding Socio-Demographic Factors Among Community Health Volunteers in Nyandarua County, Kenya

Community health volunteers (CHVs) operate as volunteers at the community level where they live. Their needs assessment has been forgotten since 2006 when their recruitment started and therefore their personal data is lacking or inadequate. General profiling of CHVs is a common gap yet their profiles impact community health. This study assessed their socio-demographic factors in a cross-sectional descriptive method using self-administered questionnaires. The sample size, n= 348 (N=1,390) was determined through the Yamane formula with a CI of 95%. Data collected from randomly selected (n=30) community health units (CHUs) from all wards with a response rate of 92% (n=320) indicated that 61% were female, 91.9% were beyond 35 years old and 57% had secondary education. The married was 73.7% and 67.7% had worked 11 years or more while farmers were 88.4%. Daily incomes for 57.1% was below poverty (Ksh 200). After expert-pretesting self-administered questionnaire data was collected during a monthly dialogue meeting and analysed through Microsoft Excel before being presented in figures. Results indicated that their socio-demographic conditions were wanting. It was recommended that the County government of Nyandarua should solve gender inequality, improve succession management and tap job experiences from long-serving CHVs. Additionally, giving farming inputs support as a motivation and a gateway to self-reliance together with income generating activities (IGAs) supporting poverty eradication besides giving timely and reasonable stipends for improving their livelihoods as a boost to community health. This study potentially contributed to the profiling of CHVs as a baseline for designing effective community health programs. It suggests that their backgrounds are likely to be responsible for some health system gaps because the expectancy theory predicts that effects come from causes. However, this hypothesis was recommended for a future inferential study.