scholarly journals The Relationship between Alcohol Hangover Severity, Sleep and Cognitive Performance; a Naturalistic Study

2021 ◽  
Vol 10 (23) ◽  
pp. 5691
Author(s):  
Elizabeth Ayre ◽  
Andrew Scholey ◽  
David White ◽  
Grant J. Devilly ◽  
Jordy Kaufman ◽  
...  

Alcohol hangover (AH) has been associated with poor sleep due to the negative effects of alcohol intoxication on sleep quantity and sleep quality. The aim of the current study was to further explore the relationship between AH severity and sleep using a naturalistic study design. A further aim was to determine whether quantitative aspects of sleep were a mediating influence on the relationship between AH severity and cognitive performance. As part of the naturalistic study design, 99 drinkers were recruited following a night of drinking in an Australian state capital, with breath alcohol concentration (BrAC) measured as participants were leaving the entertainment district. The following morning at home, participants answered online questions regarding their drinking behaviour on the previous evening, current AH symptoms and sleep quality. Participants also completed an online version of the Trail-Making Test B (TMT-B) to assess cognitive performance. The findings reveal the duration of nightly awakenings to be negatively related to six individual AH symptoms as well as overall AH severity. The number of nightly awakenings, sleep quality and total sleep time correlated with four AH symptoms including overall AH severity. Total AH severity accounted for a moderate amount of variance (11%) in the time to complete the TMT-B. These findings confirm that alcohol consumption negatively affects sleep, which is related to higher next-day hangover severity ratings and poorer cognitive performance.

2017 ◽  
pp. 125-130
Author(s):  
Minh Tam Nguyen ◽  
Phuc Thanh Nhan Nguyen ◽  
Thi Thuy Hang Nguyen

The increasing use of smartphone among young people is creating negative effects and is an important public health problem in many countries. Smartphone abuse and addiction may cause physical and psychological disorders among users. However, the awarenes on this issue has been inadequate due to lacking of evidence. Objectives: To describe the current situation of smartphone using among students at highschools and universities in Hue city and to examine the relationship between smartphone using and sleep disturbances and psychological disstress among participants. Methods: A cross-sectional study with a randomly selected sample of 1,150 students at highschools and universities in Hue city. SAS-SV scale was used to evaluate phone addiction status, K10 scale was used for psychological distress assessment and PSQI scale was used to examine the sleep quality. Results: The proportion of students at highschools and universities having smartphones was 78.0%. The rate of smartphone addiction among high school students was 49.1% and that among university students was 43.7%. There was 57.3% of high school students had poor sleep quality, and that of university students was 51.6%. There was a statistically significant association between smartphone addiction and sleep disturbances and psychological disstress among participants (p <0.05). Conclusion: The prevalence of smartphone addiction among students at highschools and universities is alarming and is related to sleep disturbances and psychological disstress among participants. There is a strong call to develop intervention to help students to aware and manage the use of smartphone effectively.


SLEEP ◽  
2021 ◽  
Author(s):  
Jessica Nicolazzo ◽  
Katharine Xu ◽  
Alexandra Lavale ◽  
Rachel Buckley ◽  
Nawaf Yassi ◽  
...  

Abstract Study objectives To examine if sleep symptomatology was associated with subjective cognitive concerns or objective cognitive performance in a dementia-free community-based sample. Methods A total of 1421 middle-aged participants (mean±standard deviation = 57±7; 77% female) from the Healthy Brain Project completed the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth Sleepiness Scale (ESS) to measure sleep quality, insomnia symptom severity, and daytime sleepiness, respectively. Participants were classified as having no sleep symptomatology (normal scores on each sleep measure), moderate sleep symptomatology (abnormal scores on one sleep measure), or high sleep symptomatology (abnormal scores on at least two sleep measures), using established cut-off values. Analysis of covariance was used to compare objective cognitive function (Cogstate Brief Battery) and subjective cognitive concerns (Modified Cognitive Function Instrument) across groups. Results Following adjustments for age, sex, education, mood, and vascular risk factors, persons classified as having high sleep symptomatology, versus none, displayed more subjective cognitive concerns (d=0.24) but no differences in objective cognitive performance (d=0.00-0.18). Subjective cognitive concerns modified the association between sleep symptomatology and psychomotor function. The strength of the relationship between high sleep symptomatology (versus none) and psychomotor function was significantly greater in persons with high as compared with low cognitive concerns (β±SE =-0.37±0.16; p=0.02). Conclusions More severe sleep symptomatology was associated with greater subjective cognitive concerns. Persons reporting high levels of sleep symptomatology may be more likely to display poorer objective cognitive function in the presence of subjective cognitive concerns.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1017.2-1018
Author(s):  
N. Kelly ◽  
E. Hawkins ◽  
H. O’leary ◽  
K. Quinn ◽  
G. Murphy ◽  
...  

Background:Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory condition that affects 0.5% of the adult population worldwide (1). Sedentary behavior (SB) is any waking behavior characterized by an energy expenditure of ≤1.5 METs (metabolic equivalent) and a sitting or reclining posture, e.g. computer use (2) and has a negative impact on health in the RA population (3). Sleep is an important health behavior, but sleep quality is an issue for people living with RA (4, 5). Poor sleep quality is associated with low levels of physical activity in RA (4) however the association between SB and sleep in people who have RA has not been examined previously.Objectives:The aim of this study was to investigate the relationship between SB and sleep in people who have RA.Methods:A cross-sectional study was conducted. Patients were recruited from rheumatology clinics in a large acute public hospital serving a mix of urban and rural populations. Inclusion criteria were diagnosis of RA by a rheumatologist according to the American College of Rheumatology criteria age ≥ 18 and ≤ 80 years; ability to mobilize independently or aided by a stick; and to understand written and spoken English. Demographic data on age, gender, disease duration and medication were recorded. Pain and fatigue were measured by the Visual Analogue Scale (VAS), anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS), and sleep quality was assessed using the Pittsburgh Sleep Quality Index. SB was measured using the ActivPAL4™ activity monitor, over a 7-day wear period. Descriptive statistics were calculated to describe participant characteristics. Relationships between clinical characteristics and SB were examined using Pearson’s correlation coefficients and regression analyses.Results:N=76 participants enrolled in the study with valid data provided by N=72 participants. Mean age of participants was 61.5years (SD10.6) and the majority 63% (n = 47) were female. Participant mean disease duration was 17.8years (SD10.9). Mean SB time was 533.7 (SD100.1) minutes (8.9 hours per day/59.9% of waking hours). Mean sleep quality score was 7.2 (SD5.0) (Table 1). Correlation analysis and regression analysis found no significant correlation between sleep quality and SB variables. Regression analysis demonstrated positive statistical associations for SB time and body mass index (p-value=0.03846, R2 = 0.05143), SB time and pain VAS (p-value=0.009261, R2 = 0.07987), SB time and HADS (p-value = 0.009721, R2 = 0.08097) and SB time and HADSD (p-value = 0.01932, R2 = 0.0643).Conclusion:We found high levels of sedentary behavior and poor sleep quality in people who have RA, however no statistically significant relationship was found in this study. Future research should further explore the complex associations between sedentary behavior and sleep quality in people who have RA.References:[1]Carmona L, et al. Rheumatoid arthritis. Best Pract Res Clin Rheumatol 2010;24:733–745.[2]Anon. Letter to the editor: standardized use of the terms “sedentary” and “sedentary behaviours”. Appl Physiol Nutr Metab = Physiol Appl Nutr Metab 2012;37:540–542.[3]Fenton, S.A.M. et al. Sedentary behaviour is associated with increased long-term cardiovascular risk in patients with rheumatoid arthritis independently of moderate-to-vigorous physical activity. BMC Musculoskelet Disord 18, 131 (2017).[4]McKenna S, et al. Sleep and physical activity: a cross-sectional objective profile of people with rheumatoid arthritis. Rheumatol Int. 2018 May;38(5):845-853.[5]Grabovac, I., et al. 2018. Sleep quality in patients with rheumatoid arthritis and associations with pain, disability, disease duration, and activity. Journal of clinical medicine, 7(10)336.Table 1.Sleep quality in people who have RASleep variableBed Time N(%) before 10pm13(18%) 10pm-12pm43 (60%) after 12pm16 (22%)Hours Sleep mean(SD)6.56 (1.54)Fall Asleep minutes mean(SD)33.3(27.7)Night Waking N(%)45(63%)Self-Rate Sleep mean(SD)2.74 (0.90)Hours Sleep mean(SD)6.56 (1.54)Disclosure of Interests:None declared


2020 ◽  
Vol 10 (9) ◽  
pp. 3282
Author(s):  
Angela Shin-Yu Lien ◽  
Yi-Der Jiang ◽  
Jia-Ling Tsai ◽  
Jawl-Shan Hwang ◽  
Wei-Chao Lin

Fatigue and poor sleep quality are the most common clinical complaints of people with diabetes mellitus (DM). These complaints are early signs of DM and are closely related to diabetic control and the presence of complications, which lead to a decline in the quality of life. Therefore, an accurate measurement of the relationship between fatigue, sleep status, and the complication of DM nephropathy could lead to a specific definition of fatigue and an appropriate medical treatment. This study recruited 307 people with Type 2 diabetes from two medical centers in Northern Taiwan through a questionnaire survey and a retrospective investigation of medical records. In an attempt to identify the related factors and accurately predict diabetic nephropathy, we applied hybrid research methods, integrated biostatistics, and feature selection methods in data mining and machine learning to compare and verify the results. Consequently, the results demonstrated that patients with diabetic nephropathy have a higher fatigue level and Charlson comorbidity index (CCI) score than without neuropathy, the presence of neuropathy leads to poor sleep quality, lower quality of life, and poor metabolism. Furthermore, by considering feature selection in selecting representative features or variables, we achieved consistence results with a support vector machine (SVM) classifier and merely ten representative factors and a prediction accuracy as high as 74% in predicting the presence of diabetic nephropathy.


2021 ◽  
Vol 8 ◽  
Author(s):  
Yangyang Hui ◽  
Xiaoyu Wang ◽  
Zihan Yu ◽  
Hongjuan Feng ◽  
Chaoqun Li ◽  
...  

Both sleep–wake disturbance and malnutrition are common in cirrhosis and might be associated with similar adverse outcomes, such as impaired health-related quality of life, hepatic encephalopathy, and sarcopenia, but there is no study investigating the relationship between these two. We aimed to explore the relationship between sleep–wake disturbance [estimated by the Pittsburgh Sleep Quality Index (PSQI)] and malnutrition risk [estimated by the Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT)]. About 150 patients with cirrhosis were prospectively recruited. The nutritional risk is classified as low (0 points), moderate (1 point), and high (2–7 points) according to the RFH-NPT score. A global PSQI &gt;5 indicated poor sleepers. Furthermore, multivariate linear regression analyses were performed to determine the relationship between sleep–wake disturbance and malnutrition. The median PSQI was seven, and RFH-NPT was two in the entire cohort, with 60.67 and 56.67% rated as poor sleep quality and high malnutrition risk, respectively. Patients with cirrhosis with poor sleep quality had significantly higher RFH-NPT score (3 vs. 1, P = 0.007). Our multivariate analyses indicated that male patients (β = 0.279, P &lt; 0.001), ascites (β = 0.210, P = 0.016), and PSQI (β = 0.262, P = 0.001) were independent predictors of malnutrition. In addition, the differences regarding PSQI score were more significant in male patients, as well as those &gt;65 years or with Child-Turcotte-Pugh class A/B (CTP-A/B) or the median model for end-stage liver disease (MELD) &lt;15. Taken together, the sleep–wake disturbance is strongly correlated with high malnutrition risk in patients with cirrhosis. Given sleep–wake disturbance is remediable, it is tempting to incorporate therapies to reverse poor sleep quality for improving nutritional status in patients with cirrhosis.


2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Mutia Annisa ◽  
Dwi Nurviyandari Kusuma Wati

<p class="AbstractContent"><strong>Objective:</strong> Elderly are at risk of poor slepp quality and other health problems due to reduced sleep satisfaction. The objective of this study was to explore the association between sleep hygiene and sleep quality in elderly.</p><p class="AbstractContent"><strong>Methods: </strong>This was a descriptive study with cross sectional design. The study was conducted in four elderly care institutions in Jakarta, Indonesia, involving a purposive sample of 103 elderly aged 60 to 111 years old. Data were collected using Sleep Hygiene Index (SHI) and Pittsburgh Sleep Quality Index (PSQI).</p><p class="AbstractContent"><strong>Results:</strong> Over half of the residents had poor sleep hygiene (51.5%) and more than three quarter (81.6%) had poor sleep quality. The study revealed that there was a highly significant relationship between sleep hygiene and sleep quality (p = 0.001). The study also showed that those with poor sleep hygiene were 7.834 times more likely to have poor sleep quality.<strong></strong></p><p class="AbstractContent"><strong>Conclusion: </strong>Nurses need to include interventions that may address residents’ sleep problems. They also need to promote sleep hygiene and improve residents’ sleep quality.<strong></strong></p><strong>Keywords: </strong>elderly, institution, sleep hygiene, sleep quality


2020 ◽  
Vol 11 ◽  
Author(s):  
Jinru Liu ◽  
Lin Zhu ◽  
Conghui Liu

This study examined the mediating roles of both positive and negative affects in the relationship between sleep quality and self-control. A sample of 1,507 Chinese adults (37% men; mean age = 32.5 years) completed self-report questionnaires measuring sleep quality, positive and negative emotions, and self-control. Poor sleep quality was positively correlated with negative affect and negatively correlated with positive affect and self-control. Positive affect was positively correlated with self-control, while negative affect was negatively correlated with self-control. Both positive and negative affects significantly mediated the relationship between sleep quality and self-control. Improving individuals’ sleep qualities may lead to more positive emotions and less negative emotion, and these mood changes may increase resources for self-control. Regulating positive and negative affects may reduce the negative effects of poor sleep quality on self-control.


2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Momoko Kitazawa ◽  
Michitaka Yoshimura ◽  
Hidefumi Hitokoto ◽  
Yuka Sato-Fujimoto ◽  
Mayu Murata ◽  
...  

Abstract Background Besides research on psychiatric diseases related to problematic Internet use (PIU), a growing number of studies focus on the impact of Internet on subjective well-being (SWB). However, in previous studies on the relationship between PIU and SWB, there is little data for Japanese people specifically, and there is a lack of consideration for differences in perception of happiness due to cultural differences. Therefore, we aimed to clarify how happiness is interdependent on PIU measures, with a focus on how the concept of happiness is interpreted among Japanese people, and specifically among Japanese university students. Methods A paper-based survey was conducted with 1258 Japanese university students. Respondents were asked to fill out self-report scales regarding their happiness using the Interdependent Happiness Scale (IHS). The relationship between IHS and Internet use (Japanese version of the Internet addiction test, JIAT), use of social networking services, as well as social function and sleep quality (Pittsburgh Sleep Quality Index, PSQI) were sought using multiple regression analyses. Results Based on multiple regression analyses, the following factors related positively to IHS: female gender and the number of Twitter followers. Conversely, the following factors related negatively to IHS: poor sleep, high- PIU, and the number of times the subject skipped a whole day of school. Conclusions It was shown that there was a significant negative correlation between Japanese youths’ happiness and PIU. Since epidemiological research on happiness that reflects the cultural background is still scarce, we believe future studies shall accumulate similar evidence in this regard.


SLEEP ◽  
2020 ◽  
Author(s):  
Andrea L Harris ◽  
Nicole E Carmona ◽  
Taryn G Moss ◽  
Colleen E Carney

Abstract Study Objectives There is mixed evidence for the relationship between poor sleep and daytime fatigue, and some have suggested that fatigue is simply caused by lack of sleep. Although retrospective measures of insomnia and fatigue tend to correlate, other studies fail to demonstrate a link between objectively disturbed sleep and fatigue. The current study prospectively explored the relationship between sleep and fatigue among those with and without insomnia disorder. Methods Participants meeting Research Diagnostic Criteria for insomnia disorder (n = 33) or normal sleepers (n = 32) completed the Consensus Sleep Diary (CSD) and daily fatigue ratings for 2 weeks. Baseline questionnaires evaluated cognitive factors including unhelpful beliefs about sleep and rumination about fatigue. Hierarchical linear modeling tested the within- and between-participant relationships between sleep quality, total sleep time, and daily fatigue ratings. Mediation analyses tested if cognitive factors mediated the relationship between insomnia and fatigue. Results Self-reported nightly sleep quality significantly predicted subsequent daily fatigue ratings. Total sleep time was a significant predictor of fatigue within, but not between, participants. Unhelpful sleep beliefs and rumination about fatigue mediated the relationship between insomnia and fatigue reporting. Conclusions The results suggest that perception of sleep plays an important role in predicting reports of daytime fatigue. These findings could be used in treatment to help shift the focus away from total sleep times, and instead, focus on challenging maladaptive sleep-related cognitions to change fatigue perception.


2019 ◽  
Vol 31 (06) ◽  
pp. 779-788 ◽  
Author(s):  
Sonya Kaur ◽  
Nikhil Banerjee ◽  
Michelle Miranda ◽  
Mitchell Slugh ◽  
Ni Sun-Suslow ◽  
...  

ABSTRACTObjectives:Frailty is associated with cognitive decline in older adults. However, the mechanisms explaining this relationship are poorly understood. We hypothesized that sleep quality may mediate the relationship between frailty and cognition.Participants:154 participants aged between 50-90 years (mean = 69.1 years, SD = 9.2 years) from the McKnight Brain Registry were included.Measurements:Participants underwent a full neuropsychological evaluation, frailty and subjective sleep quality assessments. Direct relationships between frailty and cognitive function were assessed using linear regression models. Statistical mediation of these relationships by sleep quality was assessed using nonparametric bootstrapping procedures.Results:Frailty severity predicted weaker executive function (B = −2.77, β = −0.30, 95% CI = −4.05 – −1.29) and processing speed (B = −1.57, β = −0.17, 95% CI = −3.10 – −0.16). Poor sleep quality predicted poorer executive function (B = −0.47, β = −0.21, 95% CI = −0.79 – −0.08), processing speed (B = −0.64, β = −0.28, 95% CI = −0.98 – −0.31), learning (B = −0.42, β = −0.19, 95% CI = −0.76 – −0.05) and delayed recall (B = −0.41, β = −0.16, 95% CI = −0.80 – −0.31). Poor sleep quality mediated the relationships between frailty severity and executive function (B = −0.66, β = −0.07, 95% CI = −1.48 – −0.39), learning (B = −0.85, β = −0.07, 95% CI = −1.85 – −0.12), delayed recall (B = −0.47, β = −0.08, 95% CI = −2.12 – −0.39) and processing speed (B = −0.90, β = −0.09, 95% CI = −1.85 – −0.20).Conclusions:Relationships between frailty severity and several cognitive outcomes were significantly mediated by poor sleep quality. Interventions to improve sleep quality may be promising avenues to prevent cognitive decline in frail older adults.


Sign in / Sign up

Export Citation Format

Share Document