{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T13:52:11Z","timestamp":1772545931683,"version":"3.50.1"},"reference-count":33,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2024,5,23]],"date-time":"2024-05-23T00:00:00Z","timestamp":1716422400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Maternal &amp; Child Nutrition"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Post\u2010natal growth influences short\u2010 and long\u2010term preterm infant outcomes. Different growth charts, such as the Fenton Growth Chart (FGC) and INTERGROWTH\u201021st Preterm Post\u2010natal Growth Standards (IG\u2010PPGS), describe different growth curves and targets. This study compares FGC\u2010 and IG\u2010PPGS\u2010derived weight\u2010for\u2010postmenstrual age <jats:italic>z<\/jats:italic>\u2010score (WZ) up to 50 weeks postmenstrual age (PMA50) for predicting 1\u2010year anthropometry in 321 South African preterm infants. The change in WZ from birth to PMA50 (\u0394WZ, calculated using FGC and IG\u2010PPGS) was correlated to age\u2010corrected 1\u2010year anthropometric z\u2010scores for weight\u2010for\u2010age (WAZ), length\u2010for\u2010age (LAZ), weight\u2010for\u2010length (WLZ) and BMI\u2010for\u2010age (BMIZ), and categorically compared with rates of underweight (WAZ\u2009&lt;\u2009\u22122), stunting (LAZ\u2009&lt;\u2009\u22122), wasting (WLZ\u2009&lt;\u2009\u22122) and overweight (BMIZ\u2009&gt;\u2009+\u20092). Multivariable analyses explored the effects of other early\u2010life exposures on malnutrition risk. At PMA50, mean WZ was significantly higher on IG\u2010PPGS (\u22120.56\u2009\u00b1\u20091.52) than FGC (\u22120.90\u2009\u00b1\u20091.52; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001), but \u0394WZ was similar (IG\u2010PPGS \u22120.26\u2009\u00b1\u20091.23, FGC \u22120.11\u2009\u00b1\u20091.14; <jats:italic>p<\/jats:italic>\u2009=\u20090.153). Statistically significant \u0394WZ differences emerged among small\u2010for\u2010gestational age infants (FGC \u22120.38\u2009\u00b1\u20091.22 vs. IG\u2010PPGS \u22120.01\u2009\u00b1\u20091.30; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001) and appropriate\u2010for\u2010gestational age infants (FGC\u2009+\u20090.02\u2009\u00b1\u20091.08, IG\u2010PPGS \u22120.39\u2009\u00b1\u20091.18; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). Correlation coefficients of \u0394WZ with WAZ, LAZ, WLZ and BMIZ were low (<jats:italic>r<\/jats:italic>\u2009&lt;\u20090.45), though higher for FGC than IG\u2010PPGS. Compared with IG\u2010PPGS, \u0394WZ\u2009&lt;\u2009\u22121 on FGC predicted larger percentages of underweight (42% vs. 36%) and wasting (43% vs. 39%) and equal percentages of stunting (33%), while \u0394WZ\u2009&gt;\u2009+\u20091 predicted larger percentages overweight (57% vs. 38%). Both charts performed similarly in multivariable analysis. Differences between FGC and IG\u2010PPGS are less apparent when considering \u0394WZ, highlighting the importance of assessing growth as change over time, irrespective of growth chart.<\/jats:p>","DOI":"10.1111\/mcn.13663","type":"journal-article","created":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T03:45:38Z","timestamp":1716522338000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Infant growth by INTERGROWTH\u201021st and Fenton Growth Charts: Predicting 1\u2010year anthropometry in South African preterm infants"],"prefix":"10.1111","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3175-7340","authenticated-orcid":false,"given":"Sanja","family":"Nel","sequence":"first","affiliation":[{"name":"Department of Human Nutrition University of Pretoria Pretoria South Africa"},{"name":"Research Centre for Maternal, Fetal, Newborn &amp; Child Health Care Strategies University of Pretoria  Atteridgeville South Africa"},{"name":"South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit  Atteridgeville South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6339-1040","authenticated-orcid":false,"given":"Ute Dagmar","family":"Feucht","sequence":"additional","affiliation":[{"name":"Research Centre for Maternal, Fetal, Newborn &amp; Child Health Care Strategies University of Pretoria  Atteridgeville South Africa"},{"name":"South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit  Atteridgeville South Africa"},{"name":"Department of Paediatrics University of Pretoria  Pretoria South Africa"},{"name":"Tshwane District Health Services Gauteng Department of Health  Pretoria South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8861-4466","authenticated-orcid":false,"given":"Tanita","family":"Botha","sequence":"additional","affiliation":[{"name":"Research Centre for Maternal, Fetal, Newborn &amp; Child Health Care Strategies University of Pretoria  Atteridgeville South Africa"},{"name":"South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit  Atteridgeville South Africa"},{"name":"Department of Statistics University of Pretoria  Pretoria South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1140-5065","authenticated-orcid":false,"given":"Friedeburg Anna Maria","family":"Wenhold","sequence":"additional","affiliation":[{"name":"Department of Human Nutrition University of Pretoria Pretoria South Africa"},{"name":"Research Centre for Maternal, Fetal, Newborn &amp; Child Health Care Strategies University of Pretoria  Atteridgeville South Africa"},{"name":"South African Medical Research Council (SA MRC) Maternal and Infant Health Care Strategies Unit  Atteridgeville South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2024,5,23]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1201\/9780429258589"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(23)00354-9"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1590\/1984-0462\/2021\/39\/2019245"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1159\/000271911"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/nu12071941"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyt109"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1542\/neo.21-2-e98"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpeds.2020.05.063"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/pr.2016.26"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2431-13-59"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2021.690788"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00431-020-03796-0"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12887-017-0946-1"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1093\/ajcn\/nqac051"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1017\/S2040174415001403"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10995-020-02988-2"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00431-020-03613-8"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/mcn.13359"},{"key":"e_1_2_10_20_1","unstructured":"National Department of Health Statistics South Africa & South African Medical Research Council. 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