Links between sleep and body mass index in bipolar disorders: An exploratory study

2015 ◽  
Vol 30 (1) ◽  
pp. 89-93 ◽  
Author(s):  
C. Boudebesse ◽  
P.-A. Geoffroy ◽  
C. Henry ◽  
A. Germain ◽  
J. Scott ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Bipolar Disorders ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Cross Sectional ◽  
Sleep Parameters

AbstractStudy objectives:Obesity and excess bodyweight are highly prevalent in individuals with bipolar disorders (BD) and are associated with adverse consequences. Multiple factors may explain increased bodyweight in BD including side effects of psychotropic medications, and reduced physical activity. Research in the general population demonstrates that sleep disturbances may also contribute to metabolic burden. We present a cross-sectional study of the associations between body mass index (BMI) and sleep parameters in patients with BD as compared with healthy controls (HC).Methods:Twenty-six French outpatients with remitted BD and 29 HC with a similar BMI completed a 21-day study of sleep parameters using objective (actigraphy) and subjective (PSQI: Pittsburgh Sleep Quality Index) assessments.Results:In BD cases, but not in HC, higher BMI was significantly correlated with lower sleep efficiency (P = 0.009) and with several other sleep parameters: shorter total sleep time (P = 0.01), longer sleep onset latency (P = 0.05), higher fragmentation index (P = 0.008), higher inter-day variability (P = 0.05) and higher PSQI total score (P = 0.004).Conclusions:The findings suggest a link between a high BMI and several sleep disturbances in BD, including lower sleep efficiency. Physiological mechanisms in BD cases may include an exaggeration of phenomena observed in non-clinical populations. However, larger scale studies are required to clarify the links between metabolic and sleep-wake cycle disturbances in BD.

scholarly journals Delayed Lactogenesis II is Associated With Lower Sleep Efficiency and Greater Variation in Nightly Sleep Duration in the Third Trimester

2019 ◽  
Vol 35 (4) ◽  
pp. 713-724
Author(s):  
Theresa Casey ◽  
Hui Sun ◽  
Helen J. Burgess ◽  
Jennifer Crodian ◽  
Shelley Dowden ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Blood Glucose ◽  
Sleep Duration ◽  
Body Mass ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Delayed Onset ◽  
Wrist Actigraphy

Background: Metabolic and hormonal disturbances are associated with sleep disturbances and delayed onset of lactogenesis II. Research aims: The aim of this study was to measure sleep using wrist actigraphy during gestation weeks 22 and 32 to determine if sleep characteristics were associated with blood glucose, body mass index, gestational related disease, delayed onset of lactogenesis II, or work schedule. Methods: Demographic data were collected at study intake from primiparous women who wore a wrist actigraph during gestation weeks 22 ( n = 50) and 32 ( n = 44). Start and end sleep time, total nighttime sleep, sleep efficiency, wake after sleep onset, and sleep fragmentation were measured. Night to night variability was assessed with the root mean square of successive difference. Blood glucose levels, body mass index, and gestational disease data were abstracted from medical charts. Timing of lactogenesis II was determined by survey. Results: Between gestation week 22 and 32, sleep efficiency decreased and fragmentation increased ( p < .05). During gestation week 32, blood glucose was negatively correlated with sleep duration, and positively related to fragmentation ( p < .05). Women who experienced delayed lactogenesis II had lower sleep efficiency and greater fragmentation ( p < .05), and greater night-to-night variability in sleep start and end time, efficiency, and duration during gestation week 32 ( p < .05). Conclusion: Women with better sleep efficiency and more stable nightly sleep time are less likely to experience delayed onset of lactogenesis II. Interventions to improve sleep may improve maternal health and breastfeeding adequacy.

scholarly journals Does Sars-Cov-2 Threaten Our Dreams? Effect of Quarantine on Sleep Quality and Body Mass Index

2020 ◽  
Author(s):  
Luigi Barrea ◽  
Gabriella Pugliese ◽  
Lydia Framondi ◽  
Rossana Di Matteo ◽  
Daniela Laudisio ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Sleep Quality ◽  
Body Mass ◽  
Sleep Disturbances ◽  
Statistical Significance ◽  
Sleep Onset ◽  
Lifestyle Changes ◽  
Sleep Onset Latency ◽  
Smart Working

Abstract Background: COVID 19- related quarantine led to a sudden and radical lifestyle changes, in particular in eating habits. Objectives of the study were to investigate the effect of quarantine on sleep quality (SQ) and body mass index (BMI), and if change in SQ was related to working modalities.Materials: We enrolled 121 adults (age 44.9±13.3 years and 35.5% males). Anthropometric parameters, working modalities and physical activity were studied. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI). At baseline, the enrolled subjects were assessed in outpatient clinic and after 40 days of quarantine/lockdown by phone interview. Results: Overall, 49.6% of the subjects were good sleepers (PSQI < 5) at the baseline and significantly decreased after quarantine (p<0.001). In detail, sleep onset latency (p<0.001), sleep efficiency (p=0.03), sleep disturbances (p<0.001), and daytime dysfunction (p<0.001) significantly worsened. There was also a significant increase in BMI values in normal weight (p=0.023), in subjects grade I (p=0.027) and II obesity (p=0.020). In all cohort, physical activity was significantly increased (p=0.004). However, analyzing the data according gender difference, males significantly increased physical activity compared to females in which there was only a trend without reaching statistical significance (46.5% vs 74.4%; p=0.015 and 50.0% vs 64.1%, p=0.106; in males and females, respectively). Also, smart working activity resulted in a significant worsening of SQ, particularly in males (p<0.001). Conclusions: Quarantine was associated to a worsening of SQ, particularly in males doing smart working, and to an increase in BMI values.

scholarly journals Does Sars-Cov-2 threaten our dreams? Effect of Quarantine on Sleep Quality and Body Mass Index

2020 ◽  
Author(s):  
Luigi Barrea ◽  
Gabriella Pugliese ◽  
Lydia Framondi ◽  
Rossana Di Matteo ◽  
Daniela Laudisio ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Sleep Quality ◽  
Body Mass ◽  
Sleep Disturbances ◽  
Statistical Significance ◽  
Sleep Onset ◽  
Lifestyle Changes ◽  
Sleep Onset Latency ◽  
Smart Working

Abstract Background: COVID 19- related quarantine led to a sudden and radical lifestyle changes, in particular in eating habits. Objectives of the study were to investigate the effect of quarantine on sleep quality (SQ) and body mass index (BMI), and if change in SQ was related to working modalities.Materials: We enrolled 121 adults (age 44.9±13.3 years and 35.5% males). Anthropometric parameters, working modalities and physical activity were studied. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI) questionnaire. At baseline, the enrolled subjects were assessed in outpatient clinic and after 40 days of quarantine/lockdown by phone interview. Results: Overall, 49.6% of the subjects were good sleepers (PSQI < 5) at the baseline and significantly decreased after quarantine (p<0.001). In detail, sleep onset latency (p<0.001), sleep efficiency (p=0.03), sleep disturbances (p<0.001), and daytime dysfunction (p<0.001) significantly worsened. There was also a significant increase in BMI values in normal weight (p=0.023), in subjects grade I (p=0.027) and II obesity (p=0.020). In all cohort, physical activity was significantly decreased (p=0.004). However, analyzing the data according gender difference, males significantly decreased physical activity as well as females in which there was only a trend without reaching statistical significance (53.5% vs 25.6%; p=0.015 and 50.0% vs 35.9%, p=0.106; in males and females, respectively). In addition, smart working activity resulted in a significant worsening of SQ, particularly in males (p<0.001). Conclusions: Quarantine was associated to a worsening of SQ, particularly in males doing smart working, and to an increase in BMI values.

Mindfulness and Behaviour Therapy for Insomnia: An Assessment of Treatment Effect in a Sleep Disorders Clinic Population with Insomnia

2020 ◽  
pp. 1-15
Author(s):  
Allie Peters ◽  
John Reece ◽  
Hailey Meaklim ◽  
Moira Junge ◽  
David Cunnington ◽  
...  
Keyword(s):  
Sleep Disorders ◽  
Treatment Effect ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Health Concern ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Subjective Sleep ◽  
Sleep Parameters

Abstract Insomnia is a common major health concern, which causes significant distress and disruption in a person's life. The objective of this paper was to evaluate a 6-week version of Mindfulness-Based Therapy for Insomnia (MBTI) in a sample of people attending a sleep disorders clinic with insomnia, including those with comorbidities. Thirty participants who met the DSM-IV-TR diagnosis of insomnia participated in a 6-week group intervention. Outcome measures were a daily sleep diary and actigraphy during pre-treatment and follow-up, along with subjective sleep outcomes collected at baseline, end-of-treatment, and 3-month follow-up. Trend analyses showed that MBTI was associated with a large decrease in insomnia severity (p < .001), with indications of maintenance of treatment effect. There were significant improvements in objective sleep parameters, including sleep onset latency (p = .005), sleep efficiency (p = .033), and wake after sleep onset (p = .018). Significant improvements in subjective sleep parameters were also observed for sleep efficiency (p = .005) and wake after sleep onset (p < .001). Overall, this study indicated that MBTI can be successfully delivered in a sleep disorders clinic environment, with evidence of treatment effect for both objective and subjective measures of sleep.

scholarly journals The Cycle of Daily Stress and Sleep: Sleep Measurement Matters

2020 ◽  
Author(s):  
Danica C Slavish ◽  
Justin Asbee ◽  
Kirti Veeramachaneni ◽  
Brett A Messman ◽  
Bella Scott ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Multilevel Models ◽  
Single Channel ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Daily Stress ◽  
Sleep Diaries ◽  
Sleep Measurement

Abstract Background Disturbed sleep can be a cause and a consequence of elevated stress. Yet intensive longitudinal studies have revealed that sleep assessed via diaries and actigraphy is inconsistently associated with daily stress. Purpose We expanded this research by examining daily associations between sleep and stress using a threefold approach to assess sleep: sleep diaries, actigraphy, and ambulatory single-channel electroencephalography (EEG). Methods Participants were 80 adults (mean age = 32.65 years, 63% female) who completed 7 days of stressor and sleep assessments. Multilevel models were used to examine bidirectional associations between occurrence and severity of daily stress with diary-, actigraphy-, and EEG-determined sleep parameters (e.g., total sleep time [TST], sleep efficiency, and sleep onset latency, and wake after sleep onset [WASO]). Results Participants reported at least one stressor 37% of days. Days with a stressor were associated with a 14.4-min reduction in actigraphy-determined TST (β = −0.24, p = 0.030), but not with other actigraphy, diary, or EEG sleep measures. Nights with greater sleep diary-determined WASO were associated with greater next-day stressor severity (β = 0.01, p = 0.026); no other diary, actigraphy, or EEG sleep measures were associated with next-day stressor occurrence or severity. Conclusions Daily stress and sleep disturbances occurred in a bidirectional fashion, though specific results varied by sleep measurement technique and sleep parameter. Together, our results highlight that the type of sleep measurement matters for examining associations with daily stress. We urge future researchers to treat sleep diaries, actigraphy, and EEG as complementary—not redundant—sleep measurement approaches.

scholarly journals Study of correlation between perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography before and after antidepressant therapy

2020 ◽  
Vol 8 (7) ◽  
pp. 2551
Author(s):  
Ganesh Ingole ◽  
Harpreet S. Dhillon ◽  
Bhupendra Yadav
Keyword(s):  
Sleep Disturbances ◽  
Total Sleep Time ◽  
Antidepressant Treatment ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Architecture ◽  
Wake Time ◽  
Depressed Patients ◽  
Before And After

Background: A prospective cohort study to correlate perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography (PSG) before and after antidepressant therapy.Methods: Patients were recruited into the study after applying strict inclusion and exclusion criterion to rule out other comorbidities which could influence sleep. A diagnosis of Depressive episode was made based on ICD-10 DCR. Psychometry, in the form of Beck Depressive inventory (BDI) and HAMD (Hamilton depression rating scale) insomnia subscale was applied on Day 1 of admission. Patients were subjected to sleep study on Day 03 of admission with Polysomnography. Patients were started on antidepressant treatment post Polysomnography. An adequate trial of antidepressants for 08 weeks was administered and BDI score ≤09 was taken as remission. Polysomnography was repeated post remission. Statistical analysis was performed using Kruskal Wallis test and Pearson correlation coefficient.Results: The results showed positive (improvement) polysomnographic findings in terms of total sleep time, sleep efficiency, wake after sleep onset, percentage wake time and these findings were statistically significant. HAM-D Insomnia subscale was found to correlate with total sleep time, sleep efficiency, wake after sleep onset, total wake time and N2 Stage percentage.Conclusions: Antidepressant treatment effectively improves sleep architecture in Depressive disorder and HAM-D Insomnia subscale correlates with objective findings of total sleep time, sleep efficiency, wake after sleep onset, total wake time and duration of N2 stage of NREM.

312 Associations Between Sleep Regularity and Body Mass Index: Findings from a Prospective Study of First-Year College Students

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A124-A125
Author(s):  
Patricia Wong ◽  
David Barker ◽  
Caroline Gredvig-Ardito ◽  
Mary Carskadon
Keyword(s):  
College Students ◽  
Body Mass Index ◽  
Prospective Study ◽  
Body Mass ◽  
Sleep Onset ◽  
First Year ◽  
Sleep Onset Latency ◽  
Wake Time ◽  
First Year College ◽  
First Year College Students

Abstract Introduction College students often experience irregular sleep timing, short sleep duration, and weight gain. Using data from a large, prospective study on sleep in first-year college students, we examined whether students’ sleep regularity index (SRI; Phillips et al., 2017) was associated with body mass index (BMI) and BMI change (∆BMI) during the first nine weeks of their college semester. Methods Analyses included data from 583 students (mean age = 18.7± 0.5 years; 59% Female; 48% non-White) who had their height and weight assessed at the start of classes (T1) and end (T2) of nine weeks. ∆BMI was calculated as the difference between T2 and T1, with a positive value indicating an increase in BMI. Throughout the semester, participants completed on-line daily sleep diaries that included bedtime, wake-time, sleep onset latency, and wake after sleep onset for the previous major sleep episode and daytime naps. Based on this data, total sleep time (TST) was calculated as time spent asleep between bedtime and wake-time, and SRI was calculated by comparing participants’ sleep/wake states across adjacent 24-hour periods. Average SRI reflects participants’ sleep regularity (0 (random) to 100 (perfect regularity)) across the study. Data were analyzed with hierarchical linear regressions that controlled for sex and average TST. Results Average SRI was 74.1±8.7 (range 25.7–91.6). Average BMI at T1 was 22.0±3.5; 6% of participants were underweight (BMI less than 18.5), 6% overweight (≥25 and &lt;30) and 3% obese (≥30). Greater BMI at T1 was correlated with less ∆BMI by T2 (r=-.16, p&lt;.001). On average, participants gained 1.8±2.4kg (range: -7.2–11.4); 6% of participants lost ≥2kg, 39% gained 2-5kg, 8% gained more than 5kg. Average TST was not significantly correlated with BMI or ∆BMI. Lower SRI was associated with greater BMI at T1 (B= -.06 [95% CI: -.09– -.02], p=.001) but less ∆BMI (B= .01 [.002–.018], p=.018). Conclusion We found that lower sleep-wake regularity associated with greater baseline BMI but less BMI increase during the initial transition to college. Given that the majority of our participants were normal weight young adults, our findings may indicate that sleep regularity associates with healthy growth in this population. Support (if any) R01MH079179, T32MH019927(P.W.)

Anxiety, Obsessive-Compulsive, and Related Disorders

2020 ◽  
pp. 318-336
Author(s):  
Bruce Rohrs ◽  
Benjamen Gangewere ◽  
Alicia Kaplan ◽  
Amit Chopra
Keyword(s):  
Anxiety Disorders ◽  
Sleep Disturbance ◽  
Sleep Disturbances ◽  
Sleep Problems ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Limited Evidence ◽  
Obsessive Compulsive ◽  
Psychotherapeutic Interventions

Despite its common comorbidity, sleep disturbance is often underrecognized and undertreated in individuals with anxiety disorders. Compared to mood disorders, sleep disturbance in this population is less well studied except for panic disorder and generalized anxiety disorder. Some evidence suggests a bidirectional link between anxiety disorders and sleep disturbance. Polysomnography findings point to some commonalities across anxiety disorders, including longer sleep onset latency, reduced total sleep time, and reduced sleep efficiency. The underlying biological mechanisms linking anxiety disorders and sleep disturbance are still unclear. However, there is limited evidence suggesting a connection between impaired executive functioning due to sleep problems and failure to inhibit anxiety related thoughts and feelings. Cortisol irregularities and disruption in the serotonergic system may also play a role. Evidence suggests that anxiety sensitivity is a transdiagnostic factor that contributes to both anxiety disorders and sleep disturbance. Further research is warranted to elucidate common biological and psychological factors underlying sleep disturbances and anxiety disorders. There is an imminent need to systematically assess the impact of sleep disturbance on symptom severity and treatment outcomes in anxiety, obsessive-compulsive, and related disorders. Limited evidence is available for medications and targeted psychotherapeutic interventions for management of sleep disturbance thus warranting the development of robust sleep interventions to achieve optimal clinical outcomes in this patient population.

scholarly journals Self-administered electroencephalography-based sleep assessment: compliance and perceived feasibility in children and adults

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Jesper Pedersen ◽  
Martin Gillies Banke Rasmussen ◽  
Line Grønholt Olesen ◽  
Peter Lund Kristensen ◽  
Anders Grøntved
Keyword(s):  
A Priori ◽  
Pilot Trial ◽  
Sleep Onset ◽  
Sleep Time ◽  
Secondary Outcome ◽  
Sleep Onset Latency ◽  
Assessment Protocol ◽  
Sleep Assessment ◽  
Sleep Parameters

Abstract Background Sleep is a crucial part of our lives and insufficient sleep has been linked to several health disorders in both children and adults. However, most studies are based on single night laboratory polysomnography, actigraphy, or sleep diaries. The primary aim of this study was to evaluate compliance to and perceived feasibility of the Zmachine insight+ for assessment of habitual sleep parameters in a sample of children and adults for six nights. The secondary aim was to report sleep parameters derived from the Zmachine. Methods We analyzed data from 12 families who participated in the SCREENS pilot trial (2018–2019). Children (n=14) and adults (n=19) had to undergo three nights of EEG-based sleep assessment at baseline and follow-up. We assessed compliance to the sleep assessment protocol and summarized perceived feasibility in children and adults. Summary estimates were computed for total sleep time, sleep onset latency, wake after sleep onset, light sleep, deep sleep, and rapid eye movement sleep. Results Compliance to the sleep assessment protocol was high with 92.9 and 89.4% of children and adults meeting the a priori specified compliance goal of at least two out of three nights of complete sleep data at both baseline and follow-up. In general, the protocol was perceived as feasible, with low prevalence of sleep disruption and only minor issues, e.g. difficulties with removing sensors. Results on sleep parameters indicate large within group variation. Conclusions Our findings support the use of a self-administered EEG-based habitual sleep assessment protocol, including multiple days of measurement, in children and adults. Trial registration Cilinicaltrials.gov: NCT03788525 [Secondary outcome measures; Retrospectively registered; 27th December, 2018].

scholarly journals Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 5993
Author(s):  
Mahnoosh Kholghi ◽  
Claire M. Ellender ◽  
Qing Zhang ◽  
Yang Gao ◽  
Liesel Higgins ◽  
...  
Keyword(s):  
Older Adults ◽  
Time Course ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Community Dwelling ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Short Sleep Duration

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019–February 2020) and during (March–May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84–85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.

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