Abstract:
Abstract: In the developing world today, nutritional and epidemiological transitions are key contributors to
the continuous existence of undernutrition and overnutrition, often resulting in concurrent forms of
malnutrition in a child –double burden malnutrition (DBM). The complex phenomenon occasions a unique
challenge to international health organizations and governments. Many studies have focused on the household
and community DBM with only a few of them examining the individual-level DBM. With data extracted from
the Demographic and Health Survey (DHS) – 2015, we extend the knowledge space by systematically and
empirically testing how child sex, child age, residence, maternal education, household wealth scale, and access
to improved water and sanitation affect the likelihood of observing the DBM in an under-5 child. A weighted
sample of 21,896 children aged 0-59 months was used in the analysis, using WHO (2006) child growth
standards in which children whose height-for-age z-scores are less than -2 standard deviations are classified
as stunted. Those whose weight-for-height z-scores are above +2 standard deviations are treated as
overweight/obese. Bivariate and multivariate logistic regression were differently used and the findings were
that (i) female children are less likely to experience DBM than their male counterparts; (ii) living in the rural
settings increases the odds of occurrence of DBM in a child; (iii) children born to higher-educated mothers
are less likely to experience DBM; (iv) higher-wealth households are less likely to observe DBM in a child;
and (v) households with access to improved water and sanitation are less likely to observe DBM in a child.
Interventions should be structured to target the specific groups of children who are simultaneously wasted and
stunted because they are more exposed to the associated health risks.
Keywords: Stunting, overweight/obese, double burden of malnutrition, overnutrition, undernutrition
Abbreviations: DBM, Double Burden of Malnutrition; WHO, World Health Organization; DHS, Demographic
and Health Survey; KDHS, Kenya Demographic and Health Survey; KNBS, Kenya National Bureau of
Statistics; ICF, WASH, Water, Sanitation, and Hygiene
