Abstract

Malnutrition refers to deficiencies, excesses or imbalances in a person’s intake of energy and/or nutrients. The burden of childhood malnutrition in developing countries continues to rise posing significant obstacle to achievement of better child health interventions. Several factors are involved in causation of malnutrition with Arid and Semi-Arid lands greatly affected as a result of erratic weather patterns, droughts, conflicts, poor access to health services and food among others. This study aims at investigating the risk factors for child malnutrition in North Rift Arid and semi-Arid lands (ASAL) counties of Kenya based on the 2014 Demographic and Health survey (DHS) data.
The main objective of the study was to determine and model various causal factors of malnutrition in ASAL areas of North Rift Kenya. Specifically (i) to determine the predictors of child malnutrition in the North Rift arid and semi-arid lands (ASAL) counties of Kenya (ii) to determine the level of influence of risk factors and (iii) Assess vulnerability to malnutrition using the DHS data and other causal Factors.
Secondary analysis of 2014 Kenya Demographic and health survey data was conducted for the study area comprising of 2,278 children living in 151 clusters. The percentage of malnourished children in each cluster was computed based on the anthropometric z scores. Independent variables were various household level and environmental factors extracted at cluster level. Predictors of malnutrition were analysed using spatial lag model taking into account the spatial dependence in the datasets.
Results obtained show significant predictors to be temperature, place of delivery, Enhanced Vegetation Index (EVI), poverty index, Illiteracy and drinking sources of water with strongest association observed between malnutrition and Temperature. A 1-unit increase in temperature was associated with 31% increase in malnutrition. Most constituencies in Turkana County are highly vulnerable to malnutrition based on factors significantly associated with malnutrition in ASAL Areas with Turkana North, central & South Constituencies most vulnerable. Areas of Samburu North bordering Turkana East constituency are also vulnerable and Eastern parts of Samburu East constituency. Most parts of Baringo, West pokot, Western parts of Turkana County and Laikipia counties recorded low to medium vulnerability.
Temperature variation, EVI were observed to be likely drivers of malnutrition in ASAL areas. Spatial modelling of these factors better informs on specific areas to be targeted in nutrition based programmes.

Keywords: Malnutrition; Vulnerability; Spatial modelling; EVI; ASAL