PREVALENCE AND PREDICTORS OF VITAMIN A DEFICIENCY AMONG INFANTS IN WESTERN KENYA USING A CROSS-SECTIONAL ANALYSIS

Vitamin A (VA) deficiency (VAD) is a major nutritional public health problem among children under-5-years-old in the developing world including Kenya. A community-based cross-sectional survey among 1,630 children (aged 6-23 mos) was undertaken in Western Kenya. A questionnaire was administered to collect demographic, socio-economic and dietary intake information. Prevalence of low retinol-binding protein (RBP) concentrations was assessed using Dried Blood Spot (DBS) methodology. Analysis of RBP was carried out using rapid enzyme immunoassay (EIA) and C-reactive protein (CRP) was carried out using enzyme linked immunosorbent assay (ELISA) to estimate VA and sub-clinical inflammation statuses, respectively. Values were adjusted for influence of inflammation using CRP (CRP >5 mg/L) and population prevalence of VAD (RBP <0.825 μmol/L, biologically equivalent to 0.70 μmol/L retinol) estimated. Anthropometric data gave three indices: stunting, wasting and underweight—all of which took age and sex into consideration. Mean (geometric± SD) concentration of RBP was adequate (1.56±0.79μmol/L) but the inflammation-adjusted mean (±SE) prevalence of VAD was high (20.1±1.1%) in this population. The level of CRP was within normal range (1.06±4.95 mg/L) whilst 18.4±0.9% of the children had subclinical inflammation (CRP>5 mg/L). Intake of VA capsule (VAC) by a child was a predictor of VAD with children who have not taken VA during the past 1 year prior to the survey having a 30% increased risk of VAD (OR (CI): 1.3 (1.1-1.7); p=0.025. Additionally, age of the child was a predictor with older children (18-23 mos) having a 30 % increased risk of VAD (OR (CI): 1.3 (1.1-1.9); p=0.035); the caretaker’s knowledge on VA and nutrition was also a predictor of VAD with children whose caretaker’s had poor knowledge having a 40 % increased risk of VAD (OR (CI): 1.4 (1.0-1.9); p=0.027. A child’s district of residence was also a significant predictor of VAD. Prevalence of VAD in this sample of infants was high. Predictors of VAD included child intake of VAC in the last 1 year before the survey, older children, children whose caretakers had poor VA and nutritional knowledge and a child’s district of residence. There is a need to improve knowledge on nutrition and VA of caretakers; undertake a targeted VAC distribution, particularly in children older than 1 year and above and use a sustainable food-based intervention in the areas with severe VAD.

ASSESSING THE DETERMINANTS OF TISSUE CULTURE BANANA ADOPTION IN WESTERN KENYA

In this study cross-section data was used to analyze the effect of farmers’ demographic, socioeconomic and institutional setting, market access and physical attributes on the probability and intensity of tissue culture banana (TCB) adoption. The study was carried out between July 2011 and November 2011. Both descriptive (mean, variance, promotions) and regression analysis were used in the analysis. A double hurdle regression model was fitted on the data. Using multistage sampling technique, four counties and eight sub-locations were randomly selected. Using random sampling technique, three hundred and thirty farmers were selected from a list of banana households in the selected sub-locations. The adoption level of tissue culture banana (TCB) was about 32%. The results also revealed that the likelihood of TCB adoption was significantly influenced by: availability of TCB planting material, proportion of banana income to the total farm income, per capita household expenditure and the location of the farmer in Kisii County; while those that significantly influenced the intensity of TCB adoption were: occupation of farmers, family size, labour source, farm size, soil fertility, availability/access of TCB plantlets to farmers, distance to banana market, use of manure in planting banana, access to agricultural extension services and index of TCB/non-TCB banana cultivar attributes which were scored by farmers. Compared to West Pokot County, farmers located in Bungoma County are more significantly and likely to adopt TCB technology. Therefore, the results of the study suggest that the probability of adoption and intensity of the use of TCB should be enhanced. This can be done by taking cognizance of these variables in order to meet the priority needs of the smallholder farmers who were the target group. This would lead to alleviating banana shortage in the region for enhanced food security. Subsequently, actors along the banana value chain are encouraged to target the intervention strategies based on the identified farmer, farm and institutional characteristics for enhanced impact on food provision. Opening up more TCB multiplication centres in different regions will make farmers access the TCB technology for enhanced impact on the target population.

DETERMINANTS OF THE ADOPTION OF INTEGRATED SOIL FERTILITY MANAGEMENT TECHNOLOGIES IN MBALE DIVISION, KENYA

The agro-climatic conditions in western Kenya present the region as a food surplus area yet people are still reliant on food imports, with the region registering high poverty levels. Depletion of soil fertility and the resulting decline in agricultural productivity in Mbale division has led to many attempts to develop and popularize Integrated Soil Fertility Management (ISFM) technologies that could restore soil fertility. These technologies bridge the gap between high external inputs and extreme forms of traditional low external input agriculture. Some of the ISFM components used by farmers are organic and inorganic inputs and improved seeds. However, the adoption of these technologies is low. The study aimed to examine the factors that influence the adoption of ISFM technologies by smallholder farmers in Mbale division, Kenya. The study was conducted in 9 sub-locations in Mbale division. Purposive sampling was used in selecting the 80 farmers to get the data based on a farm-household survey. Self-administered questionnaires were used to collect data on the determinants of the adoption of ISFM technologies from the sampled farmers in the study area. The study sought to answer the research question: What factors influence the uptake of ISFM technologies by farmers in Mbale division? The hypothesis tested was that the adoption of ISFM technologies is not influenced by age, education, extension services, labour, off-farm income and farm size. Data was analyzed using descriptive statistics. Cross tabulation was used for examining the relationship between categorical (nominal or ordinal) variables, and the bivariate correlations procedure was used to compute the pair wise associations between scale or ordinal variables. Probit regression was used to predict the socio-economic factors influencing the adoption of ISFM technologies among smallholder farmers. Results of the study indicated that education of household head, membership in social groups, age of the household head, off-farm income and farm size were the variables that significantly influenced the adoption of ISFM technologies. The findings show that there is need for a more pro-poor focused approach to achieve sustainable soil fertility management among smallholder farmers. The findings will help farmers, extension officers, researchers and donors in identifying region-specific entry points that can help in developing innovative ISFM technologies.