» Articles » PMID: 37485030

Value of Nutritional Screening Tools Versus Anthropometric Measurements in Evaluating Nutritional Status of Children in a Low/Middle-Income Country

Overview
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: Pediatric patients in low-income countries are at a high risk of malnutrition. Numerous screening tools have been developed to detect the risk of malnutrition, including the Subjective Global Nutritional Assessment (SGNA), Pediatric Yorkhill Malnutrition Score (PYMS), Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), and Screening Tool for Risk of Nutritional Status and Growth (STRONGkids). However, anthropometry remains the main tool for assessing malnutrition. We aimed to identify the value of four nutritional screening tools versus anthropometry for evaluating the nutritional status of children.

Methods: We conducted a cross-sectional study of 1,000 children aged 1-12 years who visited the outpatient clinic of Cairo University Pediatric Hospital. Each participant was evaluated using anthropometric measurements (weight, length/height, and weight for length/height) as well as the PYMS, STAMP, STRONGkids, and SGNA screening tools. The sensitivities and specificities of these four tools were assessed using anthropometry as the gold standard.

Results: Of the patients, 1.7% were underweight, 10.2% were wasted, and 35% were stunted. STRONGkids demonstrated the highest sensitivity (79.4%) and a high specificity (80.2%) for detecting malnutrition compared with weight for height, followed by STAMP, which demonstrated lower sensitivity (73.5%) but higher specificity (81.4%). PYMS demonstrated the lowest sensitivity (66.7%) and the highest specificity (93.5%), whereas SAGA demonstrated higher sensitivity (77.5%) and lower specificity (85.4%) than PYMS.

Conclusion: The use of nutritional screening tools to evaluate the nutritional status of children is valuable and recommended as a simple and rapid method for identifying the risk of malnutrition in pediatric patients.

Citing Articles

The Validity of the Original and the Saudi-Modified Screening Tools for the Assessment of Malnutrition in Pediatrics: A Cross-Sectional Study.

Alqahtani S, Aldubayan K, Alshehri S, Almuhareb G, Mahnashi A Diagnostics (Basel). 2024; 14(20).

PMID: 39451579 PMC: 11505708. DOI: 10.3390/diagnostics14202256.


Nutritional Issues among Children with Duchenne Muscular Dystrophy-Incidence of Deficiency and Excess Body Mass.

Wernio E, Wasilewska E, Czaja-Stolc S, Sledzinska K, Wierzba J, Szlagatys-Sidorkiewicz A Nutrients. 2024; 16(13).

PMID: 38999890 PMC: 11243493. DOI: 10.3390/nu16132143.

References
1.
Joosten K, van der Velde K, Joosten P, Rutten H, Hulst J, Dulfer K . Association between nutritional status and subjective health status in chronically ill children attending special schools. Qual Life Res. 2015; 25(4):969-77. PMC: 4830861. DOI: 10.1007/s11136-015-1130-4. View

2.
Hulst J, Huysentruyt K, Joosten K . Pediatric screening tools for malnutrition: an update. Curr Opin Clin Nutr Metab Care. 2020; 23(3):203-209. DOI: 10.1097/MCO.0000000000000644. View

3.
Galera-Martinez R, Morais-Lopez A, Rivero de la Rosa M, Escartin-Madurga L, Lopez-Ruzafa E, Ros-Arnal I . Reproducibility and Inter-rater Reliability of 2 Paediatric Nutritional Screening Tools. J Pediatr Gastroenterol Nutr. 2016; 64(3):e65-e70. DOI: 10.1097/MPG.0000000000001287. View

4.
Reber E, Gomes F, Vasiloglou M, Schuetz P, Stanga Z . Nutritional Risk Screening and Assessment. J Clin Med. 2019; 8(7). PMC: 6679209. DOI: 10.3390/jcm8071065. View

5.
Aponte Borda A, Pinzon Espitia O, Aguilera Otalvaro P . [Nutritional screening in hospitalized pediatric patients: systematic review]. Nutr Hosp. 2018; 35(5):1221-1228. DOI: 10.20960/nh.1658. View