Language Trajectories of Children Born Very Preterm and Full Term from Early to Late Childhood

Thi-Nhu-Ngoc Nguyen, Megan Spencer-Smith, Kristina M. Haebich, Alice Burnett, Shannon E. Scratch, Jeanie L.Y. Cheong, Lex W. Doyle, Joshua F. Wiley, Peter J. Anderson

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)


Objective: To identify distinct language trajectories of children born very preterm and full term from 2 to 13 years of age and examine predictors for the identified trajectories. Study design: A cohort of 224 children born very preterm and 77 full term controls recruited at birth were followed up at ages 2, 5, 7, and 13 years. The number of distinct language trajectories was examined using latent growth mixture modeling allowing for linear and quadratic time trends. Potential predictors in the neonatal period (eg, birth group, sex, and medical risk) and at 2 years (ie, social risk and use of allied health services) for the language trajectories were tested using multinomial logistic regression. Results: Five distinct language trajectories were identified across childhood: stable normal (32% of study cohort), resilient development showing catch-up (36%), precocious language skills (7%), stable low (17%), and high-risk (5%) development. The very preterm group was 8 times more likely to have a language trajectory that represented poorer language development compared with full term controls (very preterm, 40%; full term, 6%). Greater social risk and use of allied health services were associated with poorer language development. Conclusions: Variable language trajectories were observed, with a substantial proportion of children born very preterm exhibiting adverse language development. These findings highlight the need for monitoring language skills in children born very preterm before school entry and across middle childhood.

Original languageEnglish
Pages (from-to)86-91
Number of pages6
JournalJournal of Pediatrics
Publication statusPublished - Nov 2018


  • early predictors
  • language development
  • latent growth mixture modelling

Cite this