Abstract:
Dietary and movement behaviors [physical activity (PA), sedentary behavior (SED), and sleep] occur throughout a 24-h day and involve multiple contexts. Understanding the temporal patterning of these 24-h behaviors and their contextual determinants is key to determining their combined effect on health. A scoping review was conducted to identify novel analytic methods for determining temporal behavior patterns and their contextual correlates. We searched Embase, ProQuest, and EBSCOhost databases in July 2022 to identify studies published between 1997 and 2022 on temporal patterns and their contextual correlates (e.g., locational, social, environmental, personal). We included 14 studies after title and abstract (n = 33,292) and full-text (n = 135) screening, of which 11 were published after 2018. Most studies (n = 4 in adults; n = 5 in children and adolescents), examined waking behavior patterns (i.e., both PA and SED) of which 3 also included sleep and 6 included contextual correlates. PA and diet were examined together in only 1 study of adults. Contextual correlates of dietary, PA, and sleep temporal behavior patterns were also examined. Machine learning with various clustering algorithms and model-based clustering techniques were most used to determine 24-h temporal behavior patterns. Although the included studies used a diverse range of methods, behavioral variables, and assessment periods, results showed that temporal patterns characterized by high SED and low PA were linked to poorer health outcomes, than those with low SED and high PA. This review identified temporal behavior patterns, and their contextual correlates, which were associated with adiposity and cardiometabolic disease risk, suggesting these methods hold promise for the discovery of holistic lifestyle exposures important to health. Standardized reporting of methods and patterns and multidisciplinary collaboration among nutrition, PA, and sleep researchers; statisticians; and computer scientists were identified as key pathways to advance future research on temporal behavior patterns in relation to health.
摘要:
饮食和运动行为(身体活动[PA],久坐行为[SED],和睡眠)发生在24小时的一天中,涉及多种环境。了解这些24小时行为的时间模式及其背景决定因素是确定其对健康的综合影响的关键。进行了范围审查,以确定用于确定时间行为模式及其上下文相关关系的新颖分析方法。我们搜查了Embase,2022年7月的ProQuest和EBSCOhost数据库,以确定1997年至2022年之间发表的关于时间模式及其上下文相关的研究(例如,locational,社会,环境,personal).我们在标题和摘要(n=33,292)和全文(n=135)筛选后纳入了14项研究,其中11个是在2018年之后发布的。大多数研究(成人n=4;儿童和青少年n=5),检查清醒行为模式(即,PA和SED),其中三个还包括睡眠,六个包括上下文相关因素。仅在一项成人研究中一起检查了PA和饮食。饮食的上下文相关因素,还检查了PA和睡眠时间行为模式。具有各种聚类算法和基于模型的聚类技术的机器学习最多用于确定24小时的时间行为模式。虽然纳入的研究使用了多种方法,行为变量和评估时间段,结果表明,以高SED和低PA为特征的时间模式与较差的健康结果有关,与低SED和高PA相比。这篇评论确定了时间行为模式,以及它们的上下文关联,这与肥胖和心脏代谢疾病风险相关,表明这些方法有望发现对健康重要的整体生活方式暴露。方法和模式的标准化报告以及营养学之间的多学科合作,身体活动和睡眠研究人员,统计学家,计算机科学家被确定为推进未来与健康相关的时间行为模式研究的关键途径。