Cluster Designs to Assess the Prevalence of Acute Malnutrition by Lot Quality Assurance Sampling: A Validation Study by Computer Simulation (2009)

A large sample size is generally required to assess acute malnutrition via a population-based survey. This is true even when Lot Quality Assurance Sampling (LQAS), an otherwise time- and cost-efficient method, is used. Cluster sampling, or sampling observations in batches, offers an alternative to the large simple random sample size that would typically be needed for LQAS analysis.

Although the 30 x 30 cluster design is currently the most common sampling method used to assess the prevalence of acute malnutrition in emergency settings, the 67 x 3, 33 x 6, and sequential sampling designs provide alternative, well-tested approaches.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 x 30 cluster design. This study concludes that for independent clusters with moderate intracluster correlation the three sampling designs maintain approximate validity for LQAS analysis of acute malnutrition prevalence.

The study was funded by the United States Agency for International Development’s (USAID) Office of Health, Infectious Diseases, and Nutrition in the Bureau for Global Health and grants provided to the Harvard School of Public Health from the National Institutes of Health.

The article is available at no cost from the Journal of the Royal Statistical Society website.