Wang Wei, Cheung Sing-Hang, Cheung Shu Fai, Sun Rong Wei, Hui C Harry, Ma Ho Yin Derek, Lau Esther Yuet Ying
Department of Psychology, The Education University of Hong Kong, Tai Po, New Territories, Hong Kong SAR, China.
Analytics\Assessment Research Centre, The Education University of Hong Kong, Tai Po, New Territories, Hong Kong SAR, China.
Sleep. 2025 Apr 11;48(4). doi: 10.1093/sleep/zsaf021.
To shed light on understanding sleep duration trajectories (SDTs) using different classification methods and their outcomes, this study aimed to (1) identify common SDTs among different age groups, (2) investigate the alignment versus differences between SDTs identification by group-based trajectory modeling (GBTM) and clinical standards, and (3) examine the impacts of SDTs on health outcomes.
A systematic literature search from four databases yielded 34 longitudinal SDT studies with GBTM analyses spanning three or more data waves. Apart from the proportion meta-analysis, a three-level meta-analysis was conducted with 14 of the studies that examined the association between SDT groups and health outcomes. Assessment of study quality was performed using the Guidelines for Reporting on Latent Trajectory Studies checklist.
Qualitative analysis identified four age-related SDT classes based on longitudinal trends: "persistent sleepers," "increase sleepers," "decrease sleepers," and "variable sleepers." Meta-analysis also showed differential proportions of "GBTM-defined shortest sleepers" across age groups and sample regions, as well as significant discrepancies in the prevalence of short sleep identified by clinical standards (=50% vs. 15% per GBTM). Overall, SDTs predicted emotional and behavioral outcomes, neurocognitive problems, and physical health (OR = 1.538, p < 0.001), in GBTM-defined "short," "fluctuating," "long," and "decreasing" sleepers as compared to the "adequate" group. The effects were stronger in adolescents and in datasets with more waves.
The identification of the GBTM-defined "short," "fluctuating," "long," and "decreasing" SDT groups and their associations with various health outcomes supported longitudinal investigations, as well as the development of interventions focusing on both the length and stability of sleep durations, especially in younger populations. Study registration: PROSPERO registration number CRD42023412201.
为了通过使用不同的分类方法及其结果来深入了解睡眠时长轨迹（SDTs），本研究旨在：（1）确定不同年龄组中的常见SDTs；（2）调查基于群体轨迹建模（GBTM）识别的SDTs与临床标准之间的一致性与差异；（3）研究SDTs对健康结果的影响。
从四个数据库进行的系统文献检索产生了34项纵向SDT研究，这些研究采用了GBTM分析，跨越三个或更多数据波。除了比例荟萃分析外，对其中14项研究进行了三级荟萃分析，这些研究考察了SDT组与健康结果之间的关联。使用《潜在轨迹研究报告指南》清单对研究质量进行评估。
定性分析根据纵向趋势确定了四类与年龄相关的SDT：“持续睡眠者”、“睡眠增加者”、“睡眠减少者”和“睡眠多变者”。荟萃分析还显示，不同年龄组和样本区域中“GBTM定义的最短睡眠者”的比例存在差异，以及临床标准确定的短睡眠患病率存在显著差异（临床标准为50%，而GBTM为15%）。总体而言，与“充足”组相比，在GBTM定义的“短”、“波动”、“长”和“减少”睡眠者中，SDTs预测了情绪和行为结果、神经认知问题以及身体健康（OR = 1.538，p < 0.001）。在青少年和数据波更多的数据集中，这些影响更强。
识别GBTM定义的“短”、“波动”、“长”和“减少”SDT组及其与各种健康结果的关联，支持了纵向研究以及针对睡眠时长的长度和稳定性的干预措施的开发，特别是在年轻人群中。研究注册：PROSPERO注册号CRD42023412201。
