Cluster designs to assess the prevalence of acute malnutrition
Casey Olives, Marcello Pagano, Megan Deitchler, Bethany L. Hedt, Kari Egge and Joseph J. Valadez
Cluster sampling schemes offer both time efficient and statistically valid alternatives to the conventional methodology for assessment of acute malnutrition in emergency settings.
The study “Cluster Designs to Assess the Prevalence of Acute Malnutrition by Lot Quality Assurance Sampling: A Validation Study by Computer Simulation,” examines the classification error of three cluster designs, a 67X3, a 33X6, and a sequential sampling scheme, to assess the prevalence of acute malnutrition with LQAS. The study concludes that for independent clusters with moderate intracluster correlation, the three sampling designs maintain approximate validity for LQAS analysis of acute malnutrition prevalence.
Although the 30×30 cluster design is currently the most common sampling method used to assess the prevalence of acute malnutrition in emergency settings, the 67×3, 33×6 and sequential sampling designs provide an alternative, well-tested approach to the collection and analysis of acute malnutrition data. Comparative field studies in Ethiopia and Sudan have shown the alternative sampling designs to provide reliable and reasonably precise results and to require less time and resources in comparison to a 30×30 cluster design.
The study was funded by USAID’s Bureau for Global Health’s Office of Health, Infectious Disease and Nutrition and grants provided to the Harvard School of Public Health from the US National Institutes of Health.
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