Public Health Nutrition (Sep 2023)

Cross-sectional and prospective associations between behavioural patterns and adiposity in school-aged children

  • Ninoshka J D’Souza,
  • Katherine Downing,
  • Miaobing Zheng,
  • Gavin Abbott,
  • Sandrine Lioret,
  • Karen J Campbell,
  • Kylie D Hesketh

DOI
https://doi.org/10.1017/S136898002300112X
Journal volume & issue
Vol. 26
pp. 1840 – 1849

Abstract

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Abstract Objective: Behavioural patterns are important in understanding the synergistic effect of multiple health behaviours on childhood adiposity. Most previous evidence assessing associations between patterns and adiposity were cross-sectional and investigated two or three behaviour domains within patterns. This study aimed to identify behavioural patterns comprising four behaviour domains and investigate associations with adiposity risk in children. Design: Parent-report and accelerometry data were used to capture daily dietary, physical activity, sedentary behaviour and sleep data. Variables were standardised and included in the latent profile analysis to derive behavioural patterns. Trained researchers measured children’s height, weight and waist circumference using standardised protocols. Associations of patterns and adiposity measures were tested using multiple linear regression. Setting: Melbourne, Australia. Participants: A total of 337 children followed up at 6–8 years (T2) and 9–11 years (T3). Results: Three patterns derived at 6–8 years were broadly identified to be healthy, unhealthy and mixed patterns. Patterns at 9–11 years were dissimilar except for the unhealthy pattern. Individual behaviours characterising the patterns varied over time. No significant cross-sectional or prospective associations were observed with adiposity at both time points; however, children displaying the unhealthy pattern had higher adiposity measures than other patterns. Conclusion: Three non-identical patterns were identified at 6–8 and 9–11 years. The individual behaviours that characterised patterns (dominant behaviours) at both ages are possible drivers of the patterns obtained and could explain the lack of associations with adiposity. Identifying individual behaviour pattern drivers and strategic intervention are key to maintain and prevent the decline of healthy patterns.

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