Dataset Information

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

ABSTRACT:

Study objectives

We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN).

Methods

Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age).

Results

cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST.

Conclusions

This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.

SUBMITTER: Khalsa S

PROVIDER: S-EPMC4678343 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Publications

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

Khalsa Sakh S Mayhew Stephen D SD Przezdzik Izabela I Wilson Rebecca R Hale Joanne J Goldstone Aimee A Bagary Manny M Bagshaw Andrew P AP

Sleep 20160101 1

<h4>Study objectives</h4>We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN).<h4>Methods</h4>Resting state functional magnetic resonance i ...[more]

PMID: 26414900

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Project description:BackgroundChronic inadequate sleep and frequent daytime napping may inflict deleterious health effects including weight gain, cardiometabolic and psychiatric diseases, and cancer. It is plausible that these relations may be partly influenced by the consumption of suboptimal diets.ObjectivesThe study aimed to identify potential causal links of genetically proxied longer habitual sleep duration and more frequent daytime napping on 61 dietary variables derived from an FFQ. In addition, the study aimed to assess potential bidirectional causal links between habitual sleep duration or daytime napping and macronutrient composition.MethodsGenetic variants robustly associated with habitual sleep duration and daytime napping from published genome-wide association analyses were used. Outcomes included 61 dietary variables estimated from FFQs in the UK Biobank (n = 361,194). For bidirectional associations with macronutrient composition, genetic variants associated with percentage of energy from carbohydrate, fat, and protein were used. Two-sample Mendelian randomization (MR) effects were estimated with inverse-variance weighted (IVW) analysis.ResultsIn 2-sample MR, genetically proxied longer sleep duration was associated with a 0.068 (95% CI: 0.034, 0.103) category increase in salad/raw vegetable intake [P false discovery rate (FDR) = 0.006] per hour of sleep and with "no major dietary changes in the past 5 years" (P FDR = 0.043). No associations were evident for daytime napping on dietary variables (all P FDR > 0.05). In addition, there were no bidirectional associations between habitual sleep duration or daytime napping with the relative intake of carbohydrate, fat, and protein (all P IVW > 0.05).ConclusionsIn this MR study, there was modest evidence for associations between habitual sleep duration with dietary intake and no evidence for associations between daytime napping frequency with dietary intake. These preliminary findings suggest that changes to habitual sleep duration or daytime napping frequency may have limited impact on long-term changes in dietary intake.

Project description:Study objectivesChronic sleep restriction is prevalent in the U.S. population and associated with increased morbidity and mortality. The primary reasons for reduced sleep are unknown. Using population data on time use, we sought to identify individual characteristics and behaviors associated with short sleep that could be targeted for intervention programs.DesignAnalysis of the American Time Use Survey (ATUS).SettingCross-sectional annual survey conducted by the U.S. Bureau of Labor Statistics.ParticipantsRepresentative cohort (N = 124,517) of Americans 15 years and older surveyed between 2003 and 2011.InterventionsNone.Measurements and resultsTelephone survey of activities over 24 hours. Relative to all other waking activities, paid work time was the primary waking activity exchanged for sleep. Time spent traveling, which included commuting to/ from work, and immediate pre- and post-sleep activities (socializing, grooming, watching TV) were also reciprocally related to sleep duration. With every hour that work or educational training started later in the morning, sleep time increased by approximately 20 minutes. Working multiple jobs was associated with the highest odds for sleeping ≤6 hours on weekdays (adjusted OR 1.61, 95% CI 1.44; 1.81). Self-employed respondents were less likely to be short sleepers compared to private sector employees (OR 0.83, 95% CI 0.72; 0.95). Sociodemographic characteristics associated with paid work (age 25-64, male sex, high income, and employment per se) were consistently associated with short sleep.ConclusionsU.S. population time use survey findings suggest that interventions to increase sleep time should concentrate on delaying the morning start time of work and educational activities (or making them more flexible), increasing sleep opportunities, and shortening morning and evening commute times. Reducing the need for multiple jobs may increase sleep time, but economic disincentives from working fewer hours will need to be offset. Raising awareness of the importance of sufficient sleep for health and safety may be necessary to positively influence discretionary behaviors that reduce sleep time, including television viewing and morning grooming.

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Project description:ImportanceUnderstanding the interplay between sleep duration, dietary habits, and the risk of developing type 2 diabetes (T2D) is crucial for public health and diabetes prevention strategies.ObjectiveTo investigate the associations of type of diet and duration of sleep with the development of T2D.Design, setting, and participantsData derived from the UK Biobank baseline investigation (2006-2010) were analyzed for this cohort study between May 1 and September 30, 2023. The association between sleep duration and healthy dietary patterns with the risk of T2D was investigated during a median (IQR) follow-up of 12.5 (11.8-13.2) years (end of follow-up, September 30, 2021).ExposureFor the analysis, 247 867 participants were categorized into 4 sleep duration groups: normal (7-8 hours per day), mild short (6 hours per day), moderate short (5 hours per day), and extreme short (3-4 hours per day). Their dietary habits were evaluated based on population-specific consumption of red meat, processed meat, fruits, vegetables, and fish, resulting in a healthy diet score ranging from 0 (unhealthiest) to 5 (healthiest).Main outcomes and measuresCox proportional hazards regression analysis was used to calculate hazard ratios (HRs) and 95% CIs for the development of T2D across various sleep duration groups and healthy diet scores.ResultsThe cohort comprised 247 867 participants with a mean [SD] age of 55.9 [8.1] years, of whom 52.3% were female. During the follow-up, 3.2% of participants were diagnosed with T2D based on hospital registry data. Cox regression analysis, adjusted for confounding variables, indicated a significant increase in the risk of T2D among participants with 5 hours or less of daily sleep. Individuals sleeping 5 hours per day exhibited a 1.16 adjusted HR (95% CI, 1.05-1.28), and individuals sleeping 3 to 4 hours per day exhibited a 1.41 adjusted HR (95% CI, 1.19-1.68) compared with individuals with normal sleep duration. Furthermore, individuals with the healthiest dietary patterns had a reduced risk of T2D (HR, 0.75 [95% CI, 0.63-0.88]). The association between short sleep duration and increased risk of T2D persisted even for individuals following a healthy diet, but there was no multiplicative interaction between sleep duration and healthy diet score.Conclusions and relevanceIn this cohort study involving UK residents, habitual short sleep duration was associated with increased risk of developing T2D. This association persisted even among participants who maintained a healthy diet. To validate these findings, further longitudinal studies are needed, incorporating repeated measures of sleep (including objective assessments) and dietary habits.

Dataset Information

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

Study objectives

Methods

Results

Conclusions

Publications

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

Similar Datasets

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