The association between 24-hour activity, sedentary and sleep compositions and mental health in Australian adults: a cross-sectional study.

Rachel G Curtis, Dot Dumuid, Hamish McCabe, Ben Singh, Ty Ferguson, Carol Maher
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Abstract

Background: Physical activity, sedentary behaviour, and sleep are key components to health and well-being. Compositional data analysis of activity data overcomes the limitations of traditional statistical approaches and comprehensively assesses the association of all activities throughout a 24-hour day. Few studies have used compositional analysis to explore associations between movement behaviours and mental health. This study examined the association between 24-hour activity compositions and mental health in middle-aged Australian adults.

Methods: This study used cross-sectional data from participants (n = 322; mean age 40.4 years; 58.1% female; 47.8% university degree; 84.8% partnered) in the longitudinal Annual Rhythms in Adults' lifestyle and health study (Adelaide, Australia). Activity composition (sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity) was derived using 24-hour Fitbit accelerometry from the first month of participation (December). Mental health outcomes (depression, anxiety, and stress) were obtained from the Depression Anxiety Stress Scale 21-item short-form (DASS-21). The associations between activity composition (conveyed as isometric log ratios) and DASS-21 scores were examined using compositional multi-level linear regression models with a random intercept for clustering of individuals within families. Using the compositional time reallocation model, expected differences in mental health were examined for hypothetical time reallocations between individual activities.

Results: Favourable associations were observed when time (15 min) was reallocated to light physical activity from sleep (depression: -0.31 [95% CI=-0.57: -0.06]; anxiety: -0.20 [95% CI=-0.37: -0.03] and from sedentary behaviour (depression: -0.29 [95% CI=-0.46: -0.13]; anxiety: -0.14 [95% CI=-0.25: -0.03]; stress: -0.16 [95% CI=-0.31: -0.01]). Detrimental associations were observed when time was reallocated away from light physical activity to sleep (depression: 0.32 [95% CI = 0.07: 0.58]; anxiety: 0.20 [95% CI = 0.03: 0.37]) and to sedentary behaviour (depression: 0.30 [95% CI = 0.13: 0.48); anxiety: 0.15 [95% CI = 0.03: 0.26]; stress: 0.17 [95% CI = 0.01: 0.32]). There were no associations when time was allocated to or from moderate-to-vigorous physical activity.

Conclusion: The way adults spend their time across a 24-hour day is associated with their mental health. Spending more time in light physical activity appears favourable if this time is taken from sleep and sedentary behaviour. These findings provide support for "move more, sit less" public health messages.

Trial registration: This study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123) on the 16/10/2019.

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澳大利亚成年人24小时活动、久坐和睡眠成分与心理健康之间的关系:一项横断面研究
背景:身体活动、久坐行为和睡眠是健康和幸福的关键组成部分。活动数据的组成数据分析克服了传统统计方法的局限性,全面评估了全天24小时内所有活动的关联。很少有研究使用成分分析来探索运动行为与心理健康之间的关系。本研究调查了澳大利亚中年成年人24小时活动组成与心理健康之间的关系。方法:本研究采用来自参与者的横断面数据(n = 322;平均年龄40.4岁;58.1%的女性;47.8%大学学历;84.8%的伴侣)在成人生活方式和健康研究(澳大利亚阿德莱德)的纵向年度节律中。从参与的第一个月(12月)开始,使用24小时Fitbit加速度计计算活动组成(睡眠、久坐行为、轻度体育活动和中度至剧烈体育活动)。心理健康结果(抑郁、焦虑和压力)通过抑郁焦虑压力量表21项短表(DASS-21)获得。活动组成(以等长对数比率表示)与DASS-21分数之间的关系使用具有家庭内个体聚类随机截距的组成多层级线性回归模型进行了检验。利用组合时间再分配模型,对个体活动之间假设的时间再分配的心理健康预期差异进行了检验。结果:当睡眠时间(15分钟)重新分配给轻度体力活动时,观察到有利的关联(抑郁:-0.31 [95% CI=-0.57: -0.06];焦虑:-0.20 [95% CI=-0.37: -0.03]和久坐行为(抑郁:-0.29 [95% CI=-0.46: -0.13]);焦虑:-0.14 [95% CI=-0.25: -0.03];压力:-0.16 [95% CI=-0.31: -0.01])。当将时间从轻体力活动重新分配到睡眠时,观察到有害的关联(抑郁:0.32 [95% CI = 0.07: 0.58];焦虑:0.20 [95% CI = 0.03: 0.37])和久坐行为(抑郁:0.30 [95% CI = 0.13: 0.48);焦虑:0.15 [95% CI = 0.03: 0.26];应激:0.17 [95% CI = 0.01: 0.32])。当时间被分配到中度到剧烈的体育活动时,没有任何关联。结论:成年人度过24小时的方式与他们的心理健康有关。花更多的时间进行轻微的体育活动似乎是有益的,如果这些时间是从睡眠和久坐的行为中剔除的话。这些发现为“多动,少坐”的公共卫生信息提供了支持。试验注册:本研究于2019年10月16日在澳大利亚新西兰临床试验注册中心(试验ID: ACTRN12619001430123)前瞻性注册。
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