Composite Index of Anthropometric Failure to Assess Malnutrition in Low-and Middle-Income Countries Across Africa, Asia, and Europe: A State-of-the-Art Review

Godana Arero Dassie^*

• Adama General Hospital and Medical College, Adama, Ethiopia

The Composite Index of Anthropometric Failure (CIAF) provides a comprehensive framework for assessing malnutrition by combining multiple anthropometric measures into one metric. Traditional indicators like stunting, wasting, and underweight are often used in isolation, underestimating the true malnutrition burden. Limited research has explored CIAF's application, particularly in low-and middle-income countries (LMICs) where malnutrition is most prevalent.Objective: To critically examine the evolution, methodologies, applications, and implications of CIAF in assessing malnutrition in LMICs.Method: A comprehensive search was conducted using PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2019 and 2024. Search terms included "Composite Index of Anthropometric Failure," "malnutrition," and "anthropometric measures in low-and middle-income countries." Inclusion criteria focused on studies applying the CIAF framework in LMICs, excluding studies from high-income countries or those lacking detailed methodology. Extracted data included study objectives, population characteristics, methodologies, CIAF prevalence rates, and comparisons with traditional indicators. A critical appraisal checklist assessed study validity, reliability, and relevance to enhance evidence-based decision-making.Results: CIAF offers a holistic measure by capturing multiple forms of anthropometric failure, enabling better identification of children with overlapping nutritional deficits. Studies across LMICs demonstrate CIAF's utility in highlighting regional disparities, informing policies, and guiding interventions. CIAF also reveals correlations between malnutrition and factors like socioeconomic status, maternal education, and healthcare access. Despite its advantages, challenges such as data availability and interpretation persist, necessitating further research.CIAF effectively captures multiple anthropometric failures, offering a more complete assessment of malnutrition. Its application in LMICs highlights regional disparities and socioeconomic gaps, guiding targeted interventions. However, data limitations and interpretation challenges require further study to enhance its global utility.