Motivation and Behaviour Research Program, Institute for Positive Psychology and Education, Faculty of Health Sciences, Australian Catholic University, Street: Level 10, 33 Berry Street, North Sydney NSW 2060, PO Box 968, Sydney, 2059, Australia.
ARC Centre of Excellence for Children and Families over the Life Course (Life Course Centre), Institute for Social Science Research, The University of Queensland, Brisbane, Australia.
Int J Behav Nutr Phys Act. 2019 Jul 8;16(1):55. doi: 10.1186/s12966-019-0816-3.
Understanding the early roots of physical activity and sedentary behaviors is critical to developing intervention programs that promote healthy lifestyle habits in infants and children. There is, however, no evidence on how these behaviors cluster and develop together during early childhood. The aim of this study was to identify single and joint longitudinal trajectories in physical activity and screen time amongst children aged 0 to 9 years, their social-demographic predictors and their prospective health-related quality-of-life and socio-emotional outcomes.
Three waves of data from The Longitudinal Study of Australian Children, a national study tracking two cohorts every 2 years (B-cohort, 0-5 years, n = 4,164; K-cohort, 4-9 years, n = 3,974) were analysed. Growth mixture modelling was applied to longitudinal time-use diary data to identify joint trajectories in children's physical activity and screen time over Waves 1-3. Key socio-demographic variables measured at Wave 1 were used to predict membership in different trajectories. The prospective consequences (at Wave 3) of time-use trajectories on health-related quality-of-life and socio-emotional outcomes were assessed.
Three physical-activity/screen-time trajectories were identified for both cohorts: Cluster-A-children who maintained low levels of physical activity and screen time (∽50% of the sample), Cluster-B-children who progressively increased physical activity and maintained low screen-time levels (∽25%), and Cluster-C-children who maintained low physical-activity levels and increased screen time (∽25%). Children in Cluster-B experienced the best health-related quality-of-life and socio-emotional outcomes, while those in Cluster-C experienced the worst. Children who were female, Indigenous, from non-English-speaking backgrounds, not living with two biological parents, in more affluent households and neighbourhoods, without siblings and with parents with poor mental health were at greater risk of falling into Cluster-A or Cluster-C.
Our findings identified which children are most at-risk of falling into time-use trajectories that lead to poor health-related quality-of-life and socio-emotional outcomes later in life, increasing our ability to monitor, detect and prevent these suboptimal behaviours prior to their onset.
了解身体活动和久坐行为的早期根源对于制定干预计划以促进婴儿和儿童养成健康的生活习惯至关重要。然而，目前尚不清楚这些行为在幼儿期是如何一起聚集和发展的。本研究的目的是确定 0 至 9 岁儿童的身体活动和屏幕时间的单一和联合纵向轨迹，及其社会人口学预测因素，以及他们的预期健康相关生活质量和社会情感结果。
使用来自澳大利亚儿童纵向研究的三个时间点的数据，这是一项跟踪两个队列每两年一次（B 队列，0-5 岁，n=4164；K 队列，4-9 岁，n=3974）的全国性研究。对纵向时间使用日记数据应用增长混合建模，以确定儿童身体活动和屏幕时间在第 1 波至第 3 波的联合轨迹。在第 1 波测量的关键社会人口学变量用于预测不同轨迹的成员身份。评估时间使用轨迹对健康相关生活质量和社会情感结果的预期后果（在第 3 波）。
两个队列都确定了三种身体活动/屏幕时间轨迹：A 类儿童保持低水平的身体活动和屏幕时间（约 50%的样本），B 类儿童逐渐增加身体活动并保持低屏幕时间水平（约 25%），和 C 类儿童保持低身体活动水平并增加屏幕时间（约 25%）。B 类儿童的健康相关生活质量和社会情感结果最好，而 C 类儿童的结果最差。女性、土著人、非英语背景、不与两个亲生父母同住、家庭和社区更富裕、没有兄弟姐妹和父母心理健康状况不佳的儿童，更有可能落入 A 类或 C 类。
我们的研究结果确定了哪些儿童最有可能陷入导致生命后期健康相关生活质量和社会情感结果不佳的时间使用轨迹，从而提高了我们在这些次优行为发生之前监测、发现和预防这些行为的能力。
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