Abstract:
Malnutrition is the leading cause of child morbidity and mortality in Nigeria. Children are
said to be stunted, wasted, and underweight if their height-for-age, weight-for-height, and weightfor-
age z-score falls below the threshold of the World Health Organisation median growth standards
respectively. Predicting the prevalence of childhood malnutrition has been by region which in the
real sense could be misleading as variation occurs even at smaller units. This study makes use
of point referenced data from the 2013 Nigeria Demographic and Health Survey to predict the
prevalence of malnutrition in the forms of stunting, wasting, and underweight for every location
in Nigeria, thus, avoiding issues of generalisation. The computational cost of obtaining model
parameters was reduced by employing the stochastic partial differential equation approach, which
allows the continuously indexed Gaussian field of the underlying spatial process to be represented
by a Gaussian Markov random field. Inferences was based on integrated nested Laplace approximation
method of Bayesian computing. Results show that children that resides in urban area
offer all forms of malnutrition than their counterparts in rural areas, though, the estimates for
stunting and wasting are insignificant. Female children are 20.4%, 13%, and 19.9% less likely to
be stunted, wasted, and underweight respectively compared to male children. Results also show
that children are prone to malnutrition at the early months of their life and older mothers have
better nourished children. The predicted maps showing the prevalence and spatial distribution
of malnutrition indicate that there exists huge variation in the nutritional status of children that
live within the same geographical settings. In particular, there is uneven distribution of stunting
among children living in Ondo state, while wasting and underweight were unevenly distributed
among children from Borno and Nasarawa states respectively.
