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Examining Mid‐Upper Arm Circumference Malnutrition z ‐Score Thresholds
Author(s) -
Stephens Karen,
Orlick Meike,
Beattie Shan,
Snell Audrey,
Munsterman Kim,
Oladitan Leah,
AbdelRahman Susan
Publication year - 2020
Publication title -
nutrition in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.725
H-Index - 71
eISSN - 1941-2452
pISSN - 0884-5336
DOI - 10.1002/ncp.10324
Subject(s) - medicine , malnutrition , anthropometry , overnutrition , body mass index , pediatrics , circumference , population , standard score , prospective cohort study , environmental health , statistics , surgery , geometry , mathematics
Background Anthropometric z ‐scores used commonly for diagnosis and determining degree of malnutrition, specifically body mass index (BMIz), weight‐for‐length (WLz), and mid‐upper arm circumference (MUACz), are not wholly concordant, yet the proposed thresholds for classification are identical. This study was designed to critically examine MUACz thresholds and their ability to correctly classify nutrition status. Methods This was a 2‐year, prospective single‐center study of children ≤18 years seen by registered dietitians within a large pediatric institution. The sensitivity, specificity, and predictive performance of the malnutrition classification thresholds were estimated against clinician‐based classification. Results Sixty‐one dietitians enrolled 10,401 patients with distributions of z ‐scores for weight (−0.5 ± 1.9), length (−0.8 ± 1.6), BMI or WL (−0.1 ± 1.8), and MUAC (−0.4 ± 1.5), suggesting participants were smaller and shorter than the reference U.S. population. Distributions of MUACz were broad and overlapped between nutrition classification groups, an observation that extended to BMIz and WLz as well. Consequently, existing thresholds do not accurately classify 100% of children. Misclassification rates increase, with increasing severity ranging from 8% in children with no malnutrition to 71% in children with severe malnutrition. Algorithm‐ and manually‐based refinement of thresholds result in mixed improvements and can be explored by the reader with the associated supplement. Conclusion The sensitivity of proposed MUACz thresholds systematically decreases with increasing severity of malnutrition and will require optimization if we aim to limit the number of children at risk of misclassification. Indicators for overnutrition remain to be addressed but are explored herein.