Rayward Anna T, Duncan Mitch J, Brown Wendy J, Plotnikoff Ronald C, Burton Nicola W
School of Medicine & Public Health, Priority Research Centre for Physical Activity and Nutrition, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, NSW 2308, Australia.
School of Medicine & Public Health, Priority Research Centre for Physical Activity and Nutrition, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, NSW 2308, Australia.
Maturitas. 2017 Aug;102:56-61. doi: 10.1016/j.maturitas.2017.05.013. Epub 2017 May 20.
This study aimed to identify how different patterns of physical activity, sleep duration and sleep quality cluster together, and to examine how the identified clusters differ in terms of socio-demographic and health characteristics.
Participants were adults from Brisbane, Australia, aged 42-72 years who reported their physical activity, sleep duration, sleep quality, socio-demographic and health characteristics in 2011 (n=5854). Two-step Cluster Analyses were used to identify clusters. Cluster differences in socio-demographic and health characteristics were examined using chi square tests (p<0.05).
Four clusters were identified: 'Poor Sleepers' (31.2%), 'Moderate Sleepers' (30.7%), 'Mixed Sleepers/Highly Active' (20.5%), and 'Excellent Sleepers/Mixed Activity' (17.6%). The 'Poor Sleepers' cluster had the highest proportion of participants with less-than-recommended sleep duration and poor sleep quality, had the poorest health characteristics and a high proportion of participants with low physical activity.
Physical activity, sleep duration and sleep quality cluster together in distinct patterns and clusters of poor behaviours are associated with poor health status. Multiple health behaviour change interventions which target both physical activity and sleep should be prioritised to improve health outcomes in mid-aged adults.
本研究旨在确定身体活动、睡眠时间和睡眠质量的不同模式是如何聚集在一起的,并研究所确定的聚类在社会人口统计学和健康特征方面有何差异。
参与者为来自澳大利亚布里斯班的42 - 72岁成年人,他们在2011年报告了自己的身体活动、睡眠时间、睡眠质量、社会人口统计学和健康特征(n = 5854)。采用两步聚类分析来识别聚类。使用卡方检验(p < 0.05)来研究聚类在社会人口统计学和健康特征方面的差异。
识别出四个聚类:“睡眠不佳者”(31.2%)、“中度睡眠者”(30.7%)、“混合睡眠者/高活动量者”(20.5%)和“优质睡眠者/混合活动者”(17.6%)。“睡眠不佳者”聚类中,睡眠时长低于推荐值且睡眠质量差的参与者比例最高,健康特征最差,身体活动量低的参与者比例也很高。
身体活动、睡眠时间和睡眠质量以不同模式聚集在一起,不良行为聚类与健康状况不佳相关。应优先开展针对身体活动和睡眠的多种健康行为改变干预措施,以改善中年成年人的健康状况。