Spatial Distribution and Predictors of Vitamin A Deficiency among Infants 6-23 Months in Bungoma and Busia Counties, Kenya

Abstract

The study determined the prevalence and geospatial distribution of vitamin A deficiency among children aged 6-23 months in Busia and Bungoma counties. Analysis of spatial patterns using spatial indices and geographical visualizations of the presence and absence of significant high and low values of VAD was done. ArcGIS and GeoDa 1.6 were used for spatial analysis. A null hypothesis of spatial randomness was tested at a level of significance α=0.005 against the thought of Spatial Autocorrelation (SA). It was rejected giving a strong evidence of significant spatial patterns of VAD distribution in Bungoma and Busia. Local Indicators of Spatial Association were used to assess levels of local clustering. Regression analysis was conducted to model the most significant prediction equation for a set of 12 covariates. Exploratory Spatial Data Analysis was conducted followed by Ordinary Least Squares Regression (OLSR) on the predictor variables. Dependent variable was VAD while spatial and demographic variables were the independent variables. The results of OLSR were scrutinized by a set test diagnostic for the existence of spatial dependence (Lagrange Multiplier diagnostics). Analysis of Moran’s Index in Bungoma and Busia revealed heavy clustering of High-High (MI≥0.9). Lower parts of Bungoma and Busia showed heavy clustering of Low-Low values of VAD (MI≥0.9). Spatial error model yielded varying levels of coefficients with diverse spatial and non-spatial independent variables at α≤0.005 with a sensitivity of 999 permutations and λ=0.381. OLSR identified length of crop growing period, distance to health facilities and towns as the most significant spatial predictors of VAD.