Middle-upper arm circumference for nutritional surveillance in crisis-affected populations: Development of a method.

Background: The assessment of prevalence of acute malnutrition in under-five children is widely used for the detection of nutritional emergencies, planning interventions, advocacy, and programme monitoring and evaluation. Current nutritional surveillance systems have important limitations. The aim of this thesis was to develop a new method for nutritional surveillance to assess acute malnutrition prevalence using PROBIT Methods based on Middle-Upper Arm Circumference (MUAC). Specific objectives were to: i) compare the appropriateness of MUAC versus other anthropometric measurements or indices to assess change in a population’s nutritional status; ii) Examine assumptions behind the proposed PROBIT Methods; and iii) Assess outcomes of the proposed PROBIT Methods using estimation and classification approaches. Methods: The first objective was achieved through a literature review. For the second objective, assumptions were tested on a database of 852 nutritional surveys including 668,975 children aged 6-59 months old. For the third objective, the Methods were assessed using data from 681,600 simulated surveys of eight different sizes. Results: MUAC was identified as the most appropriate anthropometric measure to detect short-term changes in the nutritional status of a population; and the main assumptions behind the proposed Methods were verified. The PROBIT methods had better precision in the estimation of acute malnutrition than the Classic Method for all sample sizes tested and a better coverage for smaller sample sizes, while having relatively little bias. The classification approach performed well with a threshold of 5% acute malnutrition. Conclusion: PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence compared to the Classic Method. Their use would require much lower sample sizes and would enable great time- and resource-savings. There is great potential in their use in surveillance systems in order to produce timely and/or locally relevant prevalence estimates of acute malnutrition and to enable a swift and well-targeted response.