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本文引用的文献

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2
Discrepancies between subjective and objective sleep assessments revealed by in-home electroencephalography during real-world sleep.在现实睡眠期间通过家庭脑电图揭示的主观和客观睡眠评估之间的差异。
Proc Natl Acad Sci U S A. 2025 Jan 21;122(3):e2412895121. doi: 10.1073/pnas.2412895121. Epub 2025 Jan 16.
3
Social epidemiology of Fitbit daily steps in early adolescence.青少年早期 Fitbit 日常步数的社会流行病学研究。
Pediatr Res. 2023 Nov;94(5):1838-1844. doi: 10.1038/s41390-023-02700-4. Epub 2023 Jun 23.
4
Validation of the Munich Chronotype Questionnaire (MCTQ) in Chinese college freshmen based on questionnaires and actigraphy.基于问卷和活动记录仪对中国大学新生的慕尼黑时间类型问卷(MCTQ)进行验证。
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5
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6
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8
Accuracy of Wristband Fitbit Models in Assessing Sleep: Systematic Review and Meta-Analysis.腕部 Fitbit 型号设备评估睡眠的准确性:系统评价与荟萃分析
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9
Chronotype, Social Jet Lag, and Cardiometabolic Risk Factors in Early Adolescence.青少年早期的昼夜节律类型、社会时差与心血管代谢风险因素
JAMA Pediatr. 2019 Nov 1;173(11):1049-1057. doi: 10.1001/jamapediatrics.2019.3089.
10
Chronotype and Social Jetlag: A (Self-) Critical Review.昼夜节律类型与社会时差:一篇(自我)批判性综述。
Biology (Basel). 2019 Jul 12;8(3):54. doi: 10.3390/biology8030054.

检验睡眠主观与客观测量之间的一致性:慕尼黑昼夜节律问卷与Fitbit得出的睡眠指标的比较

Examining the Agreement Between Subjective and Objective Measures of Sleep: A Comparison of Munich Chronotype Questionnaire and Fitbit-Derived Sleep Metrics.

作者信息

Rohr Kayla E, Thomas Michael L, McCarthy Michael J, Meruelo Alejandro D

机构信息

University of California, San Diego, La Jolla, California, USA.

Colorado State University, Fort Collins, Colorado, USA.

出版信息

J Sleep Res. 2025 Apr 9:e70065. doi: 10.1111/jsr.70065.

DOI:10.1111/jsr.70065
PMID:40205758
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12353032/
Abstract

Understanding the relationship between subjective and objective sleep measures is essential for evaluating their agreement and utility. This study compared Munich Chronotype Questionnaire (MCTQ) and Fitbit metrics for sleep duration, sleep midpoint and social jetlag in 5252 participants from the Adolescent Brain Cognitive Development (ABCD) study. Linear and nonlinear models assessed relationships between Fitbit-derived and MCTQ-reported metrics, whilst moderation analyses examined the influence of age, sex, household income and BMI. A sensitivity analysis compared results pre- and post-COVID-19 to assess pandemic-related effects (pre-COVID n = 4451). Correlations were weak to moderate: r = 0.15-0.21 for sleep duration, r = 0.37-0.42 for sleep midpoint, and r = 0.12-0.16 for social jetlag. Quadratic and LOESS models confirmed nonlinear trends for sleep midpoint, with greater Fitbit-MCTQ divergence at extreme morningness or eveningness. Fitbit classified 63.2% of participants as having insufficient sleep, compared to 39.45% with MCTQ, suggesting Fitbit underestimates sleep duration. Bland-Altman plots confirmed MCTQ overestimation, especially for shorter sleepers. BMI was significantly associated with sleep duration and social jetlag, with higher BMI linked to shorter sleep and greater variability. Household income and BMI moderated specific sleep metrics, whilst age and sex did not significantly moderate any metric. Sensitivity analyses showed consistent results across pre- and post-COVID periods. Findings highlight stronger agreement for sleep midpoint than for sleep duration or social jetlag, with methodological differences driving discrepancies. The consistency across demographics and time periods supports the complementary use of Fitbit and MCTQ for adolescent sleep assessment.

摘要

了解主观和客观睡眠测量之间的关系对于评估它们的一致性和实用性至关重要。本研究比较了慕尼黑时间类型问卷(MCTQ)和Fitbit指标在青少年大脑认知发展(ABCD)研究的5252名参与者中的睡眠时间、睡眠中点和社会时差。线性和非线性模型评估了Fitbit得出的指标与MCTQ报告的指标之间的关系,同时调节分析考察了年龄、性别、家庭收入和体重指数(BMI)的影响。一项敏感性分析比较了新冠疫情前和后的结果,以评估与疫情相关的影响(新冠疫情前n = 4451)。相关性为弱到中度:睡眠时间的r = 0.15 - 0.21,睡眠中点的r = 0.37 - 0.42,社会时差的r = 0.12 - 0.16。二次模型和局部加权散点平滑(LOESS)模型证实了睡眠中点的非线性趋势,在极端早型或晚型时Fitbit与MCTQ的差异更大。Fitbit将63.2%的参与者归类为睡眠不足,而MCTQ的这一比例为39.45%,表明Fitbit低估了睡眠时间。布兰德 - 奥特曼图证实了MCTQ的高估,尤其是对于睡眠时间较短的人。BMI与睡眠时间和社会时差显著相关,BMI越高,睡眠时间越短且变异性越大。家庭收入和BMI调节了特定的睡眠指标,而年龄和性别对任何指标均无显著调节作用。敏感性分析显示新冠疫情前后的结果一致。研究结果突出表明,睡眠中点的一致性比睡眠时间或社会时差更强,方法学差异导致了差异。不同人口统计学特征和时间段的一致性支持将Fitbit和MCTQ互补用于青少年睡眠评估。