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dc.contributor.authorSchwinger, Catherineen_US
dc.contributor.authorFadnes, Lars Thoreen_US
dc.contributor.authorVan den Broeck, Janen_US
dc.date.accessioned2016-06-20T11:45:57Z
dc.date.available2016-06-20T11:45:57Z
dc.date.issued2016
dc.PublishedAmerican Journal of Clinical Nutrition 2016, 103(3):801-807eng
dc.identifier.issn1938-3207
dc.identifier.issn0002-9165
dc.identifier.urihttps://hdl.handle.net/1956/12139
dc.description.abstractBackground: Growth assessment based on the WHO child growth velocity standards can potentially be used to predict adverse health outcomes. Nevertheless, there are very few studies on growth velocity to predict mortality. Objectives: We aimed to determine the ability of various growth velocity measures to predict child death within 3 mo and to compare it with those of attained growth measures. Design: Data from 5657 children <5 y old who were enrolled in a cohort study in the Democratic Republic of Congo were used. Children were measured up to 6 times in 3-mo intervals, and 246 (4.3%) children died during the study period. Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for weight and length velocity z scores and 3-mo changes in midupper arm circumference (MUAC). We used receiver operating characteristic (ROC) curves to present balance in sensitivity and specificity to predict child death. Results: GEE models showed that children had an exponential increase in the risk of dying with decreasing growth velocity in all 4 indexes (1.2- to 2.4-fold for every unit decrease). A length and weight velocity z score of <−3 was associated with an 11.8- and a 7.9-fold increase, respectively, in the RR of death in the subsequent 3-mo period (95% CIs: 3.9, 35.5, and 3.9, 16.2, respectively). Weight and length velocity z scores had better predictive abilities [area under the ROC curves (AUCs) of 0.67 and 0.69] than did weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score <−2), the AUC of weight velocity z scores was 0.87. Absolute MUAC performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value. Conclusion: Although repeated growth measures are slightly more complex to implement, their superiority in mortality-predictive abilities suggests that these could be used more for identifying children at increased risk of death.en_US
dc.language.isoengeng
dc.publisherAmerican Society for Nutritioneng
dc.relation.ispartof<a href="http://hdl.handle.net/1956/17271" target="blank"> Growth velocity of young children in two low-resource settings. Patterns and abilities to predict negative health outcomes</a>
dc.rightsThis is an open access article distributed under the CC-BY licenseeng
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/eng
dc.subjectanthropometryeng
dc.subjectlongitudinal growtheng
dc.subjectMortalityeng
dc.subjectpredictioneng
dc.subjectWHO growth velocity standardseng
dc.titleUsing Growth velocity to predict child mortalityen_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2016-04-05T09:44:59Z
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright The Authors.
dc.identifier.doihttps://doi.org/10.3945/ajcn.115.118679
dc.identifier.cristin1334785
dc.subject.nsiVDP::Medisinske Fag: 700::Helsefag: 800en_US


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