Literature DB >> 33323223

A big-data approach to producing descriptive anthropometric references: a feasibility and validation study of paediatric growth charts.

Barbara Heude1, Pauline Scherdel2, Andreas Werner3, Morgane Le Guern1, Nathalie Gelbert4, Déborah Walther1, Michel Arnould5, Marc Bellaïche6, Bertrand Chevallier7, Jacques Cheymol8, Emmanuel Jobez9, Sylvie N'Guyen10, Christine Pietrement11, Rachel Reynaud12, Jean-François Salaün13, Babak Khoshnood14, Jennifer Zeitlin14, Jean Maccario15, Gérard Breart14, Jean-Christophe Thalabard16, Marie-Aline Charles1, Jérémie Botton17, Bruno Frandji18, Martin Chalumeau19.   

Abstract

BACKGROUND: Both national and WHO growth charts have been found to be poorly calibrated with the physical growth of children in many countries. We aimed to generate new national growth charts for French children in the context of huge datasets of physical growth measurements routinely collected by office-based health practitioners.
METHODS: We recruited 32 randomly sampled primary care paediatricians and ten volunteer general practitioners from across the French metropolitan territory who used the same electronic medical records software, from which we extracted all physical growth data for the paediatric patients, with anonymisation. We included measurements from all children born from Jan 1, 1990, and aged 1 month to 18 years by Feb 8, 2018, with birthweight greater than 2500 g, to which an automated process of data cleaning developed to detect and delete measurement or transcription errors was applied. Growth charts for weight and height were derived by using generalised additive models for location, scale, and shape with the Box-Cox power exponential distribution. We compared the new charts to WHO growth charts and existing French national growth charts, and validated our charts using growth data from recent national cross-sectional surveys.
FINDINGS: After data cleaning, we included 1 458 468 height and 1 690 340 weight measurements from 238 102 children. When compared with the existing French national and WHO growth charts, all height SD and weight percentile curves for the new growth charts were distinctly above those for the existing French national growth charts, as early as age 1 month, with an average difference of -0·75 SD for height and -0·50 SD for weight for both sexes. Comparison with national cross-sectional surveys showed satisfactory calibration, with generally good fit for children aged 5-6 years and 10-11 years in height and weight and small differences at age 14-15 years.
INTERPRETATION: We successfully produced calibrated paediatric growth charts by using a novel big-data approach applied to data routinely collected in clinical practice that could be used in many fields other than anthropometry. FUNDING: The French Ministry of Health; Laboratoires Guigoz-General Pediatrics section of the French Society of Pediatrics-Pediatric Epidemiological Research Group; and the French Association for Ambulatory Pediatrics.
Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

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Year:  2019        PMID: 33323223     DOI: 10.1016/S2589-7500(19)30149-9

Source DB:  PubMed          Journal:  Lancet Digit Health        ISSN: 2589-7500


  7 in total

1.  Head circumference from birth to five years in France: New national reference charts and comparison to WHO standards.

Authors:  Manon Bergerat; Barbara Heude; Marion Taine; Sylvie Nguyen The Tich; Andreas Werner; Bruno Frandji; Thomas Blauwblomme; Dorin Sumanaru; Marie-Aline Charles; Martin Chalumeau; Pauline Scherdel
Journal:  Lancet Reg Health Eur       Date:  2021-05-05

2.  Growth charts in FGFR2- and FGFR3-related faciocraniosynostoses.

Authors:  Caroline Ea; Quentin Hennocq; Arnaud Picard; Michel Polak; Corinne Collet; Laurence Legeai-Mallet; Éric Arnaud; Giovanna Paternoster; Roman Hossein Khonsari
Journal:  Bone Rep       Date:  2022-03-26

3.  Brain charts for the human lifespan.

Authors:  R A I Bethlehem; J Seidlitz; S R White; J W Vogel; K M Anderson; C Adamson; S Adler; G S Alexopoulos; E Anagnostou; A Areces-Gonzalez; D E Astle; B Auyeung; M Ayub; J Bae; G Ball; S Baron-Cohen; R Beare; S A Bedford; V Benegal; F Beyer; J Blangero; M Blesa Cábez; J P Boardman; M Borzage; J F Bosch-Bayard; N Bourke; V D Calhoun; M M Chakravarty; C Chen; C Chertavian; G Chetelat; Y S Chong; J H Cole; A Corvin; M Costantino; E Courchesne; F Crivello; V L Cropley; J Crosbie; N Crossley; M Delarue; R Delorme; S Desrivieres; G A Devenyi; M A Di Biase; R Dolan; K A Donald; G Donohoe; K Dunlop; A D Edwards; J T Elison; C T Ellis; J A Elman; L Eyler; D A Fair; E Feczko; P C Fletcher; P Fonagy; C E Franz; L Galan-Garcia; A Gholipour; J Giedd; J H Gilmore; D C Glahn; I M Goodyer; P E Grant; N A Groenewold; F M Gunning; R E Gur; R C Gur; C F Hammill; O Hansson; T Hedden; A Heinz; R N Henson; K Heuer; J Hoare; B Holla; A J Holmes; R Holt; H Huang; K Im; J Ipser; C R Jack; A P Jackowski; T Jia; K A Johnson; P B Jones; D T Jones; R S Kahn; H Karlsson; L Karlsson; R Kawashima; E A Kelley; S Kern; K W Kim; M G Kitzbichler; W S Kremen; F Lalonde; B Landeau; S Lee; J Lerch; J D Lewis; J Li; W Liao; C Liston; M V Lombardo; J Lv; C Lynch; T T Mallard; M Marcelis; R D Markello; S R Mathias; B Mazoyer; P McGuire; M J Meaney; A Mechelli; N Medic; B Misic; S E Morgan; D Mothersill; J Nigg; M Q W Ong; C Ortinau; R Ossenkoppele; M Ouyang; L Palaniyappan; L Paly; P M Pan; C Pantelis; M M Park; T Paus; Z Pausova; D Paz-Linares; A Pichet Binette; K Pierce; X Qian; J Qiu; A Qiu; A Raznahan; T Rittman; A Rodrigue; C K Rollins; R Romero-Garcia; L Ronan; M D Rosenberg; D H Rowitch; G A Salum; T D Satterthwaite; H L Schaare; R J Schachar; A P Schultz; G Schumann; M Schöll; D Sharp; R T Shinohara; I Skoog; C D Smyser; R A Sperling; D J Stein; A Stolicyn; J Suckling; G Sullivan; Y Taki; B Thyreau; R Toro; N Traut; K A Tsvetanov; N B Turk-Browne; J J Tuulari; C Tzourio; É Vachon-Presseau; M J Valdes-Sosa; P A Valdes-Sosa; S L Valk; T van Amelsvoort; S N Vandekar; L Vasung; L W Victoria; S Villeneuve; A Villringer; P E Vértes; K Wagstyl; Y S Wang; S K Warfield; V Warrier; E Westman; M L Westwater; H C Whalley; A V Witte; N Yang; B Yeo; H Yun; A Zalesky; H J Zar; A Zettergren; J H Zhou; H Ziauddeen; A Zugman; X N Zuo; E T Bullmore; A F Alexander-Bloch
Journal:  Nature       Date:  2022-04-06       Impact factor: 69.504

4.  Measuring growth: descriptive or prescriptive?

Authors:  James A Berkley
Journal:  Lancet Digit Health       Date:  2019-11-07

5.  Sample size and sample composition for constructing growth reference centiles.

Authors:  T J Cole
Journal:  Stat Methods Med Res       Date:  2020-10-12       Impact factor: 3.021

6.  The legacy of a standard of normality in child nutrition research.

Authors:  Austin Sandler
Journal:  SSM Popul Health       Date:  2021-07-06

Review 7.  Influential Usage of Big Data and Artificial Intelligence in Healthcare.

Authors:  Yan Cheng Yang; Saad Ul Islam; Asra Noor; Sadia Khan; Waseem Afsar; Shah Nazir
Journal:  Comput Math Methods Med       Date:  2021-09-06       Impact factor: 2.238

  7 in total

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