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A novel, efficient method for estimating the prevalence of acute malnutrition in resource-constrained and

Severine Frison1, Marko Kerac1, Francesco Checchi1

  • 1Department of Population Health, London School of Hygiene and Tropical Medicine (LSHTM), London, United Kingdom.

Plos One
|November 2, 2017
PubMed

Insights

PROBIT methods offer a more precise and resource-efficient way to estimate acute malnutrition in children using Middle-Upper Arm Circumference (MUAC). These methods require smaller sample sizes, enabling faster and more targeted public health responses.

Area of Science:

  • Public Health Nutrition
  • Statistical Modeling
  • Child Health Monitoring

Background:

  • Acute malnutrition assessment in children under five is crucial for emergency detection, intervention planning, and monitoring.
  • Middle-Upper Arm Circumference (MUAC) is a key indicator for estimating acute malnutrition prevalence.
  • Traditional methods may require large sample sizes, impacting timeliness and resource allocation.

Purpose of the Study:

  • To evaluate the performance of PROBIT Methods for estimating acute malnutrition prevalence using MUAC.
  • To compare PROBIT Methods against the classic method in terms of precision, bias, and coverage.
  • To determine the efficiency of PROBIT Methods concerning required sample sizes.

Main Methods:

  • Assessed two PROBIT Method variations: Method I (sample mean, database SD) and Method II (sample mean and SD).
  • Simulated 100 surveys for eight sample sizes, generating 681,600 total simulated surveys from 852 datasets.
  • Analyzed performance based on precision, coverage, and bias in estimating acute malnutrition prevalence.

Main Results:

  • PROBIT methods demonstrated superior performance compared to the classic method, even with small sample sizes (n=50).
  • Achieved better precision and coverage across all sample sizes, with minimal bias.
  • Accurately classified malnutrition prevalence at a 5% threshold; both PROBIT methods yielded similar results.

Conclusions:

  • PROBIT Methods offer a significant advantage for MUAC-based acute malnutrition assessment.
  • Reduced sample size requirements lead to substantial time and resource savings.
  • Enables timely and locally relevant prevalence estimates for improved response strategies.
Abstract

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