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Mismatch between perceived family and individual chronotype and their association with sleep-wake patterns.

ABSTRACT: While social zeitgebers are known to shape diurnal preference, little research has been devoted to determining the contribution of the familiar group chronotype as social zeitgeber on individual circadian rhythms and sleep-wake patterns in adult subjects. The current study aimed to examine the matching between perceived family chronotype and individual chronotype and their relationship with sleep-wake patterns on weekdays and weekends, diurnal subjective somnolence, and substance consumption. Nine hundred and forty-two Colombian adults completed the Composite Scale of Morningness, the Epworth Sleepiness Scale, and responded to a questionnaire about circadian preferences of their family nucleus. We found evidence of a mismatch between perceived family and individual chronotype, mainly for morning-type individuals (Cohen's Kappa = -0.231; p < 0.001). This mismatch was associated with diurnal subjective somnolence (β = 0.073; p < 0.001) and specific sleep-wake patterns (p < 0.01). In addition, subjects with evening-type families showed higher caffeine and alcohol consumption (p < 0.001). To our knowledge, this is the first study to assess and report the mismatching between perceived family and individual chronotypes, and it adds to the existing body of knowledge regarding the influence of social zeitgebers on circadian rhythms. This is particularly relevant since mismatching between circadian physiology and environmental cues have been shown to lead to diverse pathologies.

SUBMITTER: Pereira-Morales AJ

PROVIDER: S-EPMC6494859 | biostudies-other | 2019 May

REPOSITORIES: biostudies-other

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Mismatch between perceived family and individual chronotype and their association with sleep-wake patterns.

Pereira-Morales Angela J AJ Adan Ana A Casiraghi Leandro P LP Camargo Andrés A

Scientific reports 20190501 1

While social zeitgebers are known to shape diurnal preference, little research has been devoted to determining the contribution of the familiar group chronotype as social zeitgeber on individual circadian rhythms and sleep-wake patterns in adult subjects. The current study aimed to examine the matching between perceived family chronotype and individual chronotype and their relationship with sleep-wake patterns on weekdays and weekends, diurnal subjective somnolence, and substance consumption. Ni ...[more]

PMID: 31043644

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Project description:BackgroundDifferentiating nonwear time from sleep and wake times is essential for the estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale data sets, an automatic method of identifying these three different states is required. Therefore, we developed a classification algorithm to determine nonwear, sleep and wake periods from accelerometer data. Our work aimed to (I) develop a new pattern recognition algorithm for identifying nonwear periods from actigraphy data based on the influence of respiration rate on the power spectrum of the acceleration signal and implement it in an automatic classification algorithm for nonwear/sleep/wake states; (II) address motion artifacts that occur during nonwear periods and are known to cause misclassification of these periods; (III) adjust the algorithm depending on the sensor position (wrist, chest); and (IV) validate the algorithm on both healthy individuals and patients with sleep disorders.MethodsThe study involved 98 participants who wore wrist and chest acceleration sensors for one day of measurements. They spent one night in the sleep laboratory and continued to wear the sensors outside of the laboratory for the remainder of the day. The results of the classification algorithm were compared to those of the reference source: polysomnography for wake/sleep and manual annotations for nonwear/wear classification.ResultsThe median kappa values for the two locations were 0.83 (wrist) and 0.84 (chest). The level of agreement did not vary significantly by sleep health (good sleepers vs. subjects with sleep disorders) (p = 0.348, p = 0.118) or by sex (p = 0.442, p = 0.456). The intraclass correlation coefficients of nonwear total time between the reference and the algorithm were 0.92 and 0.97 with the outliers and 0.95 and 0.98 after the outliers were removed for the wrist and chest, respectively. There was no evidence of an association between the mean difference (and 95% limits of agreement) and the mean of the two methods for either sensor position (wrist p = 0.110, chest p = 0.164), and the mean differences (algorithm minus reference) were 5.11 [95% LoA -15.4-25.7] and 1.32 [95% LoA -9.59-12.24] min/day, respectively, after the outliers were removed.DiscussionWe studied the influence of the respiration wave on the power spectrum of the acceleration signal for the differentiation of nonwear periods from sleep and wake periods. The algorithm combined both spectral analysis of the acceleration signal and rescoring. Based on the Bland-Altman analysis, the chest-worn accelerometer showed better results than the wrist-worn accelerometer.

Dataset Information

Mismatch between perceived family and individual chronotype and their association with sleep-wake patterns.

Publications

Mismatch between perceived family and individual chronotype and their association with sleep-wake patterns.

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