Clusters of diet, physical activity, screen-time and sleep among adolescents and associations with 3-year change in indicators of adiposity

by Noura Alosaimi, Lauren B. Sherar, Paula Griffiths, Mark Hamer, Natalie Pearson

Background

Clusters of health behaviours could impact changes in adiposity among adolescents over time. This study examines the clustering of screen time, physical activity, dietary behaviours and sleep, and the associations with 3-year changes in indicators of adiposity.

Methods

Data from the UK’s Millennium Cohort Study were utilised when participants were aged 14 and 17 years respectively. At age 14, demographics, screen time, dietary behaviours and sleep duration were measured via self-report, and physical activity using wrist worn accelerometers. Height, weight, and percent body fat were measured at age 14 and 17 years. Behavioural clusters were determined using k-means clustering analysis, and associations with change in indicators of adiposity between age 14 and 17 years were examined using multivariate regression models.

Results

Three clusters were identified at age 14, a ‘healthy cluster’, a ‘mixed cluster’, and an ‘unhealthy cluster’ in the analytical sample of 3,065 participants (52.5% girls). The ‘unhealthy’ cluster was the most prevalent cluster among boys (53%), while the ‘healthy cluster’ was most prevalent among girls (55.9%). Adolescents in healthy clusters had a lower BMI z-score and percent body fat at age 14 compared to those in the unhealthy and mixed clusters, and maintained lower scores at age 17. Boys in the mixed and unhealthy clusters at 14 years had a lower change in BMI z-score between 14 and 17 compared to boys in the healthy cluster.

Conclusion

Adolescents in the healthy cluster had lower BMI z-scores and percent body fat at age 14 years than those in the unhealthy cluster, and they maintained this lower level at age 17. Given the upward trend in BMI during this period, this maintenance could be interpreted as a positive outcome. Further prospective research is needed to better understand these associations as well as research examining the stability of cluster membership over time.