RESUMEN
This study aimed to identify changes in clusters of lifestyle behaviours (physical activity, screen time and diet) between the ages of 7 and 14 years, and to examine socio-demographic determinants of changes. Longitudinal analyses were performed on a sample of 9339 children from the UK Millennium Cohort Study (MCS) who had complete data on behaviours of interest at age 7 (wave 4) and 14 years (wave 6). Joint Correspondence Analysis (JCA) and k-means cluster analysis were used to identify clusters of lifestyle behaviours at both time waves. Multinomial logistic regressions were used to examine the associations between socio-economic variables and changes in cluster membership. Analyses were conducted separately for boys and girls. Clusters of behaviours at age 7 and 14 years were identified as healthy, mixed or unhealthy respectively. Compared to girls, a higher proportion of boys remained in the healthier cluster over time (19.1% vs. 13.1%) or became healthier (26.4% vs. 9.36%). A higher proportion of girls changed to an unhealthier cluster (57.2% vs. 33.9%). Indicators of lower socio-economic status, such as low family income, low parental education, and not living with both parents at age 7 were associated with unhealthier changes in cluster membership. Conclusion Lifestyle behaviours cluster in children and are susceptible to change over a 7-year period, with a high proportion of boys becoming healthier and a higher proportion of girls became unhealthier. Indicators of socio-economic status appear to be important in determining changes in clusters. What is Known: ⢠Poor lifestyle behaviours (i.e. unhealthy dietary habits, low physical activity, and sedentary behaviours) tend to cluster in children and adolescents. What is New: ⢠Lifestyle behaviours cluster in children and are susceptible to changes between childhood and adolescence. Changes occur differently in boys and girls. Indicators of low socio-economic status are associated with unhealthier changes in behavioural clusters.
RESUMEN
BACKGROUND: Physical activity (PA), sedentary behaviour (SB) and diet play an important role in the physical and mental health of young people. Understanding how these behaviours cluster, and the impact of clusters on health is important for the development of public health interventions. This review examines the prevalence of clusters of PA, sedentary time, and dietary behaviours, and how clusters relate to physical and mental health indicators among children, adolescents and young adults. METHODS: Electronic (PubMed, Web of Science and Scopus) and manual searches were conducted for articles that were (i) observational studies including children, adolescents and/or young adults aged 5-24 years, (ii) examined the 'patterning', 'clustering', or 'co-existence' of each of PA, dietary behaviour and SB, and (iii) published in English up to and including July 2022. In addition to information on clustering, data on physical and mental health outcomes were extracted where reported. Included studies were assessed using the Cochrane risk of bias for observational studies. A narrative synthesis was conducted due to high heterogeneity. This review was registered with PROSPERO (CRD42021230976). RESULTS: Forty-nine cross-sectional studies and four prospective cohort studies from eighteen countries reporting data from 778,415 individual participants were included. A broad range of clusters (n = 172) were found (healthy, unhealthy, and mixed). Mixed clusters were common (n = 98), and clusters of high diet quality, low PA and high SB were more prevalent in girls, while mixed clusters of high PA, high SB and low diet quality were more prevalent in boys. Unhealthy clusters comprising low moderate to vigorous PA, low consumption of fruits and vegetables, and high screen time were prevalent, particularly in those from lower socioeconomic status families. Compared to those with healthy behavioural clusters, those with unhealthy and mixed clusters had a higher adiposity, higher risk of cardiovascular disease, poorer mental health scores, and lower cardiorespiratory fitness. CONCLUSIONS: PA, SB and diet cluster in healthy, unhealthy and mixed patterns in young people that differ across sociodemographic characteristics. Unhealthy clusters are associated with poorer health outcomes. Intervention strategies targeting un-clustering multiple unhealthy behaviours should be developed and evaluated for their impact on health outcomes.