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PP37 Growth pattern of White British and Pakistani children in the Born in Bradford (BiB) cohort: a latent growth modelling approach
  1. TF Mebrahtu1,
  2. RG Feltbower1,
  3. ES Petherick2,
  4. RC Parslow1
  1. 1Division of Epidemiology and Biostatistics, School of Medicine, University of Leeds, Leeds, UK
  2. 2Data and Research Team, Bradford Institute of Health Research, Bradford, UK


Background Childhood growth patterns have been proposed as a key predictor of health during childhood and adult life. In earlier studies however, the statistical methodologies employed failed to uncover the more subtle patterns in growth trajectories.

Methods Study participants were 1364 singleton term children, 602 White British (293 boys and 309 girls), and 762 Pakistani (368 boys and 394 girls) drawn from a subset of children (the BiB1000) participating in the prospective Born in Bradford birth cohort study based in Bradford, UK. Weights were measured at 0, 1, 3, 6, 12, 18, 24, and 36 months. Age- and sex-specific standardised weight scores (SDS) were derived according to World Health Organisation recommendations. We investigated the growth trajectories of children using Latent Growth Modelling, a method which allows us to describe life-course growth patterns.

Results On average, Pakistani children were 190 grams lighter than White British children at birth. Although there was no difference in the change in weight in the first three months, Pakistani children showed faster growth than White British children between 3 and 32 months of age. Based on our Growth Mixture Models (GMM) results, the BiB1000 children had three distinct growth patterns: ‘normal growers’ (95.9%), ‘fast growers’ (2.5%) and ‘slow growers’ (1.6%). The Pakistani children were more likely to be in either the ‘fast’ (OR=1.17; 95% CI: 0.35, 103.0) or ‘slow growers’ (OR=13.36; 95% CI: 0.15, 1186.0) class than the White British, although these ethnic differences were not statistically significant.

Conclusion In this growth study we have identified that the population of BiB1000 children have three distinct growth patterns. These growth patterns may provide greater insight in predicting the risk of childhood or early adulthood diseases in life-course studies.

  • childhood growth trajectories
  • latent growth modelling

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