School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, NSW 2308, Australia; Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, University Drive, Callaghan, NSW 2308, Australia.
School of Science and Health, Western Sydney University, Penrith, NSW 2751, Australia.
Prev Med. 2019 Jan;118:295-303. doi: 10.1016/j.ypmed.2018.11.017. Epub 2018 Nov 23.
Diet quality, physical activity, alcohol use, smoking, sleep and sitting-time are behaviors known to influence health. The aims of this study were to identify how these behaviors co-occur to form distinct health-behavior patterns, and to investigate the relationship between these patterns, and mental and self-rated health. Members of the Australian 10,000 Steps project were invited to participate in an online survey in November-December 2011. The participants self-reported demographic and behavioral characteristics (fruit and vegetable intake, fast food, soft drink and alcohol consumption, smoking, physical activity, sitting-time and sleep), frequency of mental distress and self-rated health. Latent Class Analysis was used to identify health-behavior patterns. Latent class regression was used to examine relationships between behavior patterns, mental and self-rated health, and socio-demographic and economic factors. Data were analyzed in October 2017. Complete datasets were obtained from 10,638 participants. Four latent classes were identified, characterized by 'Low-Risk Behavior', 'Poor Sleep, Low-Risk Daytime Behavior', 'Sound Sleep, High-Risk Daytime Behavior' and 'High-Risk Behavior'. The latter two classes, both characterized by high-risk daytime behaviors, were associated with poor self-rated health. Participants in classes with high-risk daytime behaviors were more likely to be younger, non-partnered, non-university educated, from lower income households and work longer hours. Classes characterized by poor sleep quality were associated with higher frequency of mental distress. Findings suggest that experiencing poor sleep is partly independent of daytime behaviors, demographic and socioeconomic factors, but has a strong association with mental health.
饮食质量、身体活动、饮酒、吸烟、睡眠和久坐时间是已知会影响健康的行为。本研究旨在确定这些行为如何共同出现，形成不同的健康行为模式，并探讨这些模式与心理健康和自评健康之间的关系。澳大利亚 10000 步项目的成员被邀请参加 2011 年 11 月至 12 月的在线调查。参与者自我报告了人口统计学和行为特征（水果和蔬菜摄入量、快餐、软饮料和酒精消费、吸烟、身体活动、久坐时间和睡眠）、精神困扰和自评健康的频率。潜在类别分析用于识别健康行为模式。潜在类别回归用于检验行为模式、精神和自评健康与社会人口和经济因素之间的关系。数据分析于 2017 年 10 月进行。从 10638 名参与者中获得了完整的数据集。确定了四个潜在类别，分别为“低风险行为”、“睡眠不佳，日间行为低风险”、“睡眠良好，日间行为高风险”和“高风险行为”。后两种行为模式均具有高风险的日间行为，与自评健康状况不佳有关。具有高风险日间行为的参与者更年轻、未婚、未受过大学教育、来自低收入家庭、工作时间更长。睡眠质量差的类别与更高的精神困扰频率有关。研究结果表明，睡眠质量差部分独立于日间行为、人口统计学和社会经济因素，但与心理健康密切相关。
