APPLICATION OF THE JOINT MODELLING OF SERIAL ANTHROPOMETRIC MEASURES AND MORTALITY AMONGST CHILDREN FOLLOWING HOSPITALIZATION WITH A COINCIDENT ACUTE INFECTIOUS DISEASE IN ADDITION TO SEVERE ACUTE MALNUTRITION

Abstract

Background: Malnutrition continues to be a major health burden in developing countries. It is globally the most important risk factor for illness and death, with hundreds of millions of young children particularly affected. The mid-upper arm circumference (MUAC) and the standardized weight-for- length Z-score (WFLz) are two anthropometric measures that are used for the diagnosis of malnutrition. The two anthropometric measures have poor correlation in terms of their predictive capabilities. Design: A joint model was applied to data collected recently in a randomized, double blind, placebo-controlled trial to see which of these two anthropometric measures would be the better predictor of mortality in infants who were admitted to hospital with severe acute malnutrition and later discharged and followed up for one year. Typically longitudinal measures and event time data are modelled jointly by introducing shared random effects or by considering conditional distributions together with marginal distributions. Participants: The study population comprised of 1781 children admitted to hospital with evidence of an acute infectious disease and with severe malnutrition and who had care initiated and were stabilized. Results: Joint modelling showed that While WFLz was not significantly associated with mortality (p=0.202); MUAC had a high association with mortality (p=0.014) and was a predictor of children at risk of post-discharge mortality. Conclusion: Using joint modelling approach, MUAC was identified as superior predictor of mortality amongst children treated for complicated SAM.