{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T21:37:11Z","timestamp":1772833031453,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2019,6,7]],"date-time":"2019-06-07T00:00:00Z","timestamp":1559865600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["aspenjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nut in Clin Prac"],"published-print":{"date-parts":[[2020,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Anthropometric <jats:italic>z<\/jats:italic>\u2010scores used commonly for diagnosis and determining degree of malnutrition, specifically body mass index (BMIz), weight\u2010for\u2010length (WLz), and mid\u2010upper 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This was a 2\u2010year, prospective single\u2010center study of children \u226418 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\u2010based classification.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Sixty\u2010one dietitians enrolled 10,401 patients with distributions of <jats:italic>z<\/jats:italic>\u2010scores for weight (\u22120.5\u00a0\u00b1\u00a01.9), length (\u22120.8\u00a0\u00b1\u00a01.6), BMI or WL (\u22120.1\u00a0\u00b1\u00a01.8), and MUAC (\u22120.4\u00a0\u00b1\u00a01.5), 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\u2010 and manually\u2010based refinement of thresholds result in mixed improvements and can be explored by the reader with the associated supplement.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ncp.10324","type":"journal-article","created":{"date-parts":[[2019,6,8]],"date-time":"2019-06-08T00:03:09Z","timestamp":1559952189000},"page":"344-352","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Examining Mid\u2010Upper Arm Circumference Malnutrition <i>z<\/i>\u2010Score Thresholds"],"prefix":"10.1002","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1725-2322","authenticated-orcid":false,"given":"Karen","family":"Stephens","sequence":"first","affiliation":[{"name":"Nutrition Services Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meike","family":"Orlick","sequence":"additional","affiliation":[{"name":"Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shannon","family":"Beattie","sequence":"additional","affiliation":[{"name":"Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Audrey","family":"Snell","sequence":"additional","affiliation":[{"name":"Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kim","family":"Munsterman","sequence":"additional","affiliation":[{"name":"Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leah","family":"Oladitan","sequence":"additional","affiliation":[{"name":"Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susan","family":"Abdel\u2010Rahman","sequence":"additional","affiliation":[{"name":"UMKC School of Medicine  Kansas City Missouri USA"},{"name":"Innovation in Health Care Delivery Children's Research Institute  Kansas City Missouri USA"},{"name":"Section of Therapeutic Innovation Children's Mercy Hospital  Kansas City Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,6,7]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"Malnutrition in Children \u2013 UNICEF DATA.https:\/\/data.unicef.org\/topic\/nutrition\/malnutrition\/. 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