Evaluation of the efficacy of MUAC in the diagnosis of malnutrition in children

Objective. To evaluate the efficacy of MUAC as a screening method for the diagnosis of nutritional status of children without and with neurological pathology. Patients and methods. The study included 896 children – 506 (56.5%) boys and 309 (43.5%) girls aged 2 to 18 years (median age 12 years [7.04; 15.0]). All children were divided into two groups: group 1 included healthy children without pathology and group 2 included patients with neurological pathology (correctional group). Physical development was assessed using the WHO AnthroPlus program and compared with mid-upper arm circumference (MUAC) measurements. To evaluate the informativeness and capability of MUAC, sensitivity, specificity and accuracy scores were determined in relation to anthropometric indicators (body mass index (BMI)-for-age Z-score, weight-for-age Z-score, weight-for-height Z-score, height-for-age Z-score). The quality of the diagnostic approach was assessed by the ROC-AUC analysis. Results. The comparative analysis of qualitative data revealed statistically significant (p ≤ 0.001) differences between groups in terms of Z-score: MUAC, height-for-age, BMI-for-age. The chances of meeting a child in the correctional group with BMI-forage Z-score <-2 (=1) were 7.8 [4.11; 14.79] times higher and with height-for-age Z-score <-2 (=1) 6.33 [3.87; 10.35] times higher compared to the group of healthy children. The study identified a significant positive correlation between MUAC Z-score and BMI-for-age, weight-for-age Z-scores (p < 0.001), which was most stable with respect to MUAC Z-score <-2 and BMI-for-age Z-score <-2. Correlations were comparable across the whole sample and across groups. MUAC Z-score best corresponded to BMI-for-age Z-score (ROC-AUC = 75.3% [72.9; 77.6]% and 80.3% [76.8; 83.7]% for Z-score <-1 and <-2, respectively). The sensitivity of MUAC was 84.2% [80.6; 87.6] and 73.6% [66.7; 80.0], and specificity – 66.3% [63.3; 69.5] and 87.1% [85.2; 89.0], respectively. The ROC-AUC results indicate the capability of MUAC at the “good” and “very good” levels, which proves its informativeness. Conclusion. The MUAC method is characterized by a high level of accuracy, specificity and sensitivity. MUAC can be considered as an additional method to standard anthropometry. Its role increases when assessing the nutritional status of patients who have difficulties in determining weight and height due to the characteristics of disease. Key words: children, neurological disorders, malnutrition, nutritional status, MUAC, anthropometry