Optimisation of children z-score calculation based on new statistical techniques

Antonio Martinez-Millana, Jessie M Hulst, Mieke Boon, Peter Witters, Carlos Fernandez-Llatas, Ines Asseiceira, Joaquin Calvo-Lerma, Ignacio Basagoiti, Vicente Traver, Kris De Boeck and Carmen Ribes-Koninckx

PLOS ONE, 2018, vol. 13, issue 12, 1-13

Abstract: Background: Expressing anthropometric parameters (height, weight, BMI) as z-score is a key principle in the clinical assessment of children and adolescents. The Centre for Disease Control and Prevention (CDC) growth charts and the CDC-LMS method for z-score calculation are widely used to assess growth and nutritional status, though they can be imprecise in some percentiles. Objective: To improve the accuracy of z-score calculation by revising the statistical method using the original data used to develop current z-score calculators. Design: A Gaussian Process Regressions (GPR) was designed and internally validated. Z-scores for weight-for-age (WFA), height-for-age (HFA) and BMI-for-age (BMIFA) were compared with WHO and CDC-LMS methods in 1) standard z-score cut-off points, 2) simulated population of 3000 children and 3) real observations 212 children aged 2 to 18 yo. Results: GPR yielded more accurate calculation of z-scores for standard cut-off points (p

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0208362

DOI: 10.1371/journal.pone.0208362

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