Differences in workday sleep fragmentation,rest-activity cycle,sleep quality,and activity level among nurses working different shifts

ABSTRACT

Schedule changes associated with rotating shifts can interfere with the circadian rhythms of nurses and thereby affect their sleep duration, sleep quality, work efficiency, and work performance. The objectives of this study was to investigate differences in workday sleep fragmentation, rest-activity cycle, sleep quality, and activity level among nurses working different shifts. After filling out a basic information questionnaire and completing the Pittsburgh Sleep Quality Index (PSQI) questionnaire, participants were asked to wear an actigraph and keep sleep records for seven consecutive days. Data pertaining to wake after sleep onset (WASO), 24-hour autocorrelation coefficient (r24), and daytime activity mean was collected in order to investigate workday sleep fragmentation, rest-activity cycle, and daytime activity level. We obtained complete questionnaires and data from 191 nurses. Day- and evening-shift nurses had more regular workday rest-activity cycles than did night-shift nurses (F = 51.26, p < .001). After controlling for r24 coefficients, we determined that nurses who experienced greater workday sleep fragmentation had higher PSQI scores (β = .18, p = .008). After controlling for WASO times, we determined that nurses who had more regular rest-activity cycles on workdays had lower PSQI scores (β = – .16, p = .036). After controlling for shift type and WASO times, we determined that nurses with higher PSQI scores displayed lower activity levels (β = – .21, p = .015) and those with higher r24 coefficients displayed higher activity levels (β = .18, p = .040) on workdays. We then examined the causal path relationships. Among the shifts, only the day-shift nurses had a higher r24 (β = ?.59, p < .001) than did the night-shift nurses; WASO exerted a significant impact on PSQI scores (β = .20, p = .002); r24 had a significant and negative influence on PSQI scores (β = ?.38, p < .001), and PSQI scores significantly and negatively influenced workday activity levels (β = ?.20, p = .006). This study determined that day- and evening-shift nurses enjoyed more regular and consistent rest-activity cycles than did night-shift nurses; nurses with greater workday sleep fragmentation and/or more irregular rest-activity cycles experienced poorer sleep quality; and nurses suffering from poorer sleep quality displayed lower daytime activity levels on workdays.     

Sleep quality and visuospatial performance in rotating shifts workers from a petrochemical company

Working rotating shifts may cause poorer sleep quality and, consequently, negatively affect visuospatial performance. However, studies linking sleep and visuospatial perception show conflicting results and are infrequent with regard to shift workers in their working environment. We evaluated the connection between sleep quality and visuospatial perception in 16 workers on rotating shifts from a petrochemical company (aged 29–53 years), using the Rey Complex Figure Test, the Sleep Diary, the Pittsburgh Sleep Quality Index (PSQI) and the Psychomotor Vigilance Test. The PSQI data indicated poor sleep quality. Two of the participants had low visuospatial performance, and reaction time was slower at the end of the night shift. Better sleep quality was associated with better visuospatial performance in the day shift (rho = 0.66, p < 0.05) and on days off. The results suggest that a good sleep quality may be associated with better visuospatial performance.     

Effects of Cognitive Behavioral Therapy on Insomnia of Maintenance Hemodialysis Patients

The objective of the study was to evaluate the effects of cognitive behavioral therapy [sleep-related behavior modification and progressive muscle relaxation on insomnia of maintenance hemodialysis (MHD) patients] on improving insomnia of MHD patients. 103 MHD patients complicated with insomnia were randomly assigned to treatment (n = 52) and control (n = 51) groups. The control group was treated with conventional hemodialysis, and the treatment group was additionally treated with cognitive behavioral therapy for 3 months (sleep-related behavior modification and progressive muscle relaxation). All cases were assessed by Symptom Checklist 90 (SCL-90) and Pittsburgh Sleep Quality Index (PSQI) before and 2, 4, 6, 8, 10, and 12 weeks after treatment. Fifty-one patients in the treatment group and 47 patients in the control group completed the experiments. After treatment, the total mean scores were (1.94 ± 0.50/2.29 ± 0.31); scores of somatization, depression, anxiety, hostility, and additional items were (1.87 ± 0.58/2.56 ± 0.26), (2.25 ± 0.80/2.79 ± 0.50), (1.79 ± 0.26/2.37 ± 0.34), (1.71 ± 0.46/2.25 ± 0.43), and (1.91 ± 0.67/2.26 ± 0.59) in SCL-90, respectively. The total scores for PSQI were (12.63 ± 2.27/16.40 ± 2.16); scores of subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, hypnotics, and daytime dysfunction which were (1.98 ± 0.76/2.57 ± 0.58), (1.75 ± 0.59/2.60 ± 0.50), (2.10 ± 0.50/2.62 ± 0.53), (2.06 ± 0.47/2.57 ± 0.54), (2.04 ± 0.69/2.45 ± 0.72), (1.02 ± 0.79/1.51 ± 0.98), and (1.69 ± 0.55/2.09 ± 0.58), respectively, were significantly lower in the treatment group compared with the control group. However, there were no significant differences in the scores of factors of obsessive–compulsive (2.26 ± 0.62/2.32 ± 0.38), interpersonal sensitivity (2.23 ± 0.64/2.43 ± 0.47), phobic anxiety (1.98 ± 0.62/2.01 ± 0.67), paranoid ideation (1.55 ± 0.43/1.69 ± 0.39), and psychoticism (1.57 ± 0.46/1.66 ± 0.49). The conclusion is that sleep-related behavior modification in combination with progressive muscle relaxation effectively improved the mental state and sleep quality of MHD patients with insomnia.     

Construct Validity and Factor Structure of the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale in a Multi-National Study of African,South East Asian and South American College Students

Background

The Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) are questionnaires used to assess sleep quality and excessive daytime sleepiness in clinical and population-based studies. The present study aimed to evaluate the construct validity and factor structure of the PSQI and ESS questionnaires among young adults in four countries (Chile, Ethiopia, Peru and Thailand).

Methods

A cross-sectional study was conducted among 8,481 undergraduate students. Students were invited to complete a self-administered questionnaire that collected information about lifestyle, demographic, and sleep characteristics. In each country, the construct validity and factorial structures of PSQI and ESS questionnaires were tested through exploratory and confirmatory factor analyses (EFA and CFA).

Results

The largest component-total correlation coefficient for sleep quality as assessed using PSQI was noted in Chile (r = 0.71) while the smallest component-total correlation coefficient was noted for sleep medication use in Peru (r = 0.28). The largest component-total correlation coefficient for excessive daytime sleepiness as assessed using ESS was found for item 1 (sitting/reading) in Chile (r = 0.65) while the lowest item-total correlation was observed for item 6 (sitting and talking to someone) in Thailand (r = 0.35). Using both EFA and CFA a two-factor model was found for PSQI questionnaire in Chile, Ethiopia and Thailand while a three-factor model was found for Peru. For the ESS questionnaire, we noted two factors for all four countries

Conclusion

Overall, we documented cross-cultural comparability of sleep quality and excessive daytime sleepiness measures using the PSQI and ESS questionnaires among Asian, South American and African young adults. Although both the PSQI and ESS were originally developed as single-factor questionnaires, the results of our EFA and CFA revealed the multi- dimensionality of the scales suggesting limited usefulness of the global PSQI and ESS scores to assess sleep quality and excessive daytime sleepiness.     

Intra-individual variability in the sleep of senior and junior rugby league athletes during the competitive season

This study examined the sleep intra-individual variability (IIV) of rugby league athletes across senior and junior levels during one week of the competitive season. Forty-five rugby league athletes across elite senior, sub-elite senior and elite junior levels each wore actigraphy monitors for seven days during the competitive season, and completed a subjective sleep diary each morning upon waking. Linear mixed models were used to assess differences in sleep measures between playing levels. Intra-individual standard deviations for each sleep measure were calculated for each athlete to determine their respective IIV, allowing differences in IIV between groups to be assessed. Elite junior athletes went to bed later (ES = 0.94 ± 0.50, p < 0.05) and woke later than elite senior athletes (ES = 0.94 ± 0.40, p < 0.05), while also displaying greater IIV when considering time in bed (ES = 1.14 ± 0.60, p < 0.05) and sleep duration (ES = 1.53 ± 0.64, p < 0.05) compared with elite senior athletes. Similarly, IIV was more pronounced in elite junior players for time in bed (ES = 0.88 ± 0.60, p < 0.05) and sleep duration (ES = 1.03 ± 0.64, p < 0.05) compared with sub-elite senior athletes. Despite this, elite junior athletes still obtained sufficient sleep duration, efficiency and quality. The outcomes of this investigation show a distinct difference in the habitual sleep-wake patterns of senior and junior rugby league athletes, and show how sleep IIV differs between playing levels in rugby league.     

Persistence of social jetlag and sleep disruption in healthy young adults

Sleep disruption has been associated with increased risks for several major chronic diseases that develop over decades. Differences in sleep/wake timing between work and free days can result in the development of social jetlag (SJL), a chronic misalignment between a person’s preferred sleep/wake schedule and sleep/wake timing imposed by his/her work schedule. Only a few studies have examined the persistence of SJL or sleep disruption over time. This prospective investigation examined SJL and sleep characteristics over a 2-year period to evaluate whether SJL or poor sleep were chronic conditions during the study period. SJL and sleep measures (total sleep time [TST], sleep onset latency [SOL], wake after sleep onset [WASO]), and sleep efficiency [SE]), were derived from armband monitoring among 390 healthy men and women 21–35 years old. Participants wore the armband for periods of 4–10 days at 6-month intervals during the follow-up period (N = 1431 repeated observations).

The consistency of SJL or sleep disruption over time was analyzed using generalized linear mixed models (GLMMs) for repeated measures. Repeated measures latent class analysis (RMLCA) was then used to identify subgroups among the study participants with different sleep trajectories over time. Individuals in each latent group were compared using GLMMs to identify personal characteristics that differed among the latent groups.

Minor changes in mean SJL, chronotype, or TST were observed over time, whereas no statistically significant changes in SOL, WASO, or SE were observed during the study period. The RMLCA identified two groups of SJL that remained consistent throughout the study (low SJL, mean ± SE: 0.4 ± 0.04 h, 42% of the study population; and high SJL, 1.4 ± 0.03 h, 58%). Those in the SJL group with higher values tended to be employed and have an evening chronotype.

Similarly, two distinct subgroups were observed for SOL, WASO, and SE; one group with a pattern suggesting disrupted sleep over time, and another with a consistently normal sleep pattern. Analyses of TST identified three latent groups with relatively short (5.6 ± 1.0 h, 21%), intermediate (6.5 ± 1.0 h, 44%), and long (7.3 ± 1.0 h, 36%) sleep durations, all with temporally stable, linear trajectories. The results from this study suggest that sleep disturbances among young adults can persist over a 2 year period. Latent groups with poor sleep tended to be male, African American, lower income, and have an evening chronotype relative to those with more normal sleep characteristics. Characterizing the persistence of sleep disruption over time and its contributing factors could be important for understanding the role of poor sleep as a chronic disease risk factor.     

Association between Personality Traits and Sleep Quality in Young Korean Women

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women.     

The association between self‐reported sleep quality and overweight in a Chinese population

Objective:

Sleep quality and obesity are associated with type 2 diabetes, hypertension, and metabolic syndrome. However, there is limited research on the association between sleep quality and obesity, and thus the aim of this study is to investigate this relationship in a Chinese population.

Design and Methods:

Subjects were recruited from the Prevention Health Center of National Cheng Kung University Hospital. Anthropometric data and metabolic parameters were measured. Being overweight or obese was defined according to the recommendations of the Department of Health in Taiwan. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI).

Results:

Of the total 2,803 subjects, 1,059 were classified as normal weight, 1,127 were overweight, and 617 were obese. The global PSQI score were 6.30 ± 2.56, 6.61 ± 2.96, and 7.02 ± 2.95 in subjects who were normal weight, overweight, and obese, respectively (test for trend, P < 0.001). Of the variables tested in the multivariate linear regression model, female gender, being overweight, obesity, sleep duration, and alcohol drinking were significantly associated with global PSQI scores, and in the multivariate logistic regression model, female gender, being overweight, obesity, and sleep duration were independent predictors of poor sleepers after controlling for age, gender, BMI or different weight statuses, sleep duration, alcohol drinking, smoking, habitual exercise, hypertension, newly diagnosed diabetes, total cholesterol, high‐density lipoprotein, triglyceride, estimated glomerular filtration rate, and alanine aminotransferase.

Conclusions:

In conclusion, female gender, being overweight, obesity, and sleep duration were associated with poor sleep quality independent of cardiometabolic risk factors. In clinical practice, subjects who are obese, or even only overweight, should be evaluated for the presence of sleep disturbance.     

The effects of depression,anxiety and sleep disturbances on cognitive impairment in patients with chronic obstructive pulmonary disease

The purpose of this study was to investigate the effects of depression, anxiety and sleep disturbances on cognitive functions in chronic obstructive pulmonary disease (COPD) patients. In this prospective case-control study, demographic data, smoking history, depression, anxiety, sleep quality and cognitive status of 48 COPD patients and 36 healthy volunteers aged 40–90 years were recorded. The Beck depression inventory (BDI), the Beck anxiety inventory (BAI), and Pittsburgh Sleep Quality Index (PSQI) were used to assess depression, anxiety and sleep quality, respectively in COPD patients. Cognitive performance was studied by the mini-mental state examination. The mean age of patients with COPD was 65.3 ± 9.4 years, and disease duration was 9.6 ± 7.8 years. Male sex ratio, smoking, BDI score, BAI score, total PSQI score, sleep latency, sleep duration, average use of sleep aids and sleep disturbances in patients with COPD were significantly higher than the control group (p < 0.05). When cognitive impairment was compared by age, FVC, FEV, FEV/FVC, PEF values and smoking, no statistically significant relationship was found (p > 0.05). A statistically significant relationship was established between cognitive impairment and severity of disease, presence of anxiety, presence of depression and sleep quality. In our study, we found that sleep disorders, depression and anxiety comorbid with COPD increased cognitive impairment as well as the severity of disease. We believe that this finding is important in terms of reducing the risk of cognitive impairment, preventing misdiagnosis and treatment of the aforementioned comorbid diseases.     

Psychometric properties of the Russian version of the Composite Scale of Morningness

Morningness–eveningness preference is commonly measured by questionnaires, such as the Composite Scale of Morningness (CSM). Purpose of our study was to assess the Russian translation of the CSM and provide psychometric properties of this scale. Participants (N = 406) were students from high schools and university in Petrozavodsk. Mean age was 20.47 ± 3.66 with a range of 12–38 years. Mean CSM scores were 31.43 ± 6.32, with a range from 14 to 50. Internal reliability, as measured by Cronbach’s α, was 0.823. There was no negative correlation among the items. The reliability of 0.82 is good and fits into previous work done with the CSM in many different countries. The factor structure appears as a two-factor structure based on parallel analysis and a three-factor structure based on the eigenvalue greater than one criterion. We suggest retaining the two-factor structure, one factor could be labelled as morning affect and the other one as self-assessment/activity planning. Construct validity was checked with the MCTQ and showed that the correlations between midpoint of sleep and CSM are comparable to other studies.     

Chronotype and depressive symptoms in students: An investigation of possible mechanisms

ABSTRACT

Individuals with an evening chronotype are at increased risk of experiencing emotional problems, including depressive symptoms. However, the mechanisms underlying these associations remain unclear. The present study aimed to determine whether poor sleep quality, substance use and cognitive emotion regulation difficulties – which have been implicated in the etiology of depression – mediate the relationship between chronotype and depressive symptoms in a student sample, which was assessed cross-sectionally and after 1 year. A total of 742 Dutch students (75% women, mean age 21.4 ± 2.9 years) completed the Quick Inventory of Depressive Symptomatology, the Morningness-Eveningness Questionnaire, the Pittsburgh Sleep Quality Index, a questionnaire assessing alcohol, caffeine, tobacco and cannabis use, the Cognitive Emotion Regulation Questionnaire and the Behavioral Inhibition/Activation Scale. A subsample (n = 115) was assessed 1 year later with the same questionnaires. Cross-sectional analyses showed that evening chronotype was associated with more depressive symptoms, adjusted for age and gender (β = ?0.082, p = 0.028). The relationship between eveningness and depressive symptoms was mediated by sleep quality, alcohol consumption and the cognitive emotion regulation strategies of self-blame and positive reappraisal. In longitudinal analyses, eveningness at baseline predicted more depressive symptoms at follow-up, adjusted for age and gender (β = ?0.29, p = 0.002); after additional adjustment for baseline depressive symptoms, chronotype remained a significant predictor of depressive symptoms at T2 (β = ?0.16, t = ?2.01, p = 0.047). Only poor sleep quality at follow-up was a significant mediator of this relationship. Even though the effect is small in terms of explained variance, eveningness is related to depressive symptoms and this relationship is mediated by poor sleep quality, also in a prospective design. Self-blame and reduced positive reappraisal are correlated with eveningness. Further research is needed to assess the efficacy of chronotherapeutic interventions for the prevention of depression, in addition to sleep education and cognitive approaches.     

Using 3D finite element models verified the importance of callus material and microstructure in biomechanics restoration during bone defect repair

Background: There is lack of further observations on the microstructure and material property of callus during bone defect healing and the relationships between callus properties and the mechanical strength. Methods: Femur bone defect model was created in rabbits and harvested CT data to reconstruct finite element models at 1 and 2 months. Three types of assumed finite element models were compared to study the callus properties, which assumed the material elastic property as heterogeneous (R-model), homogenous (H-model) or did not change from 1 to 2 months (U-model). Results: The apparent elastic moduli increased at 2 months (from 355.58 ± 132.67 to 1139.30 ± 967.43 MPa) in R-models. But there was no significant difference in apparent elastic moduli between R-models (355.58 ± 132.67 and 1139.30 ± 967.43 MPa) and H-models (344.79 ± 138.73 and 1001.52 ± 692.12 MPa) in 1 and 2 months. A significant difference of apparent elastic moduli was found between the R-model (1139.30 ± 967.43 MPa) and U-model group (207.15 ± 64.60 MPa) in 2 months. Conclusions: This study showed that the callus structure stability remodeled overtime to achieve a more effective structure, while the material quality of callus tissue is a very important factor for callus strength. At the meantime, this study showed an evidence that the material heterogeneity maybe not as important as it is in bone fracture model.     

A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues

In mammalian ventricular cardiomyocytes, invaginations of the surface membrane form the transverse tubular system (T-system), which consists of transverse tubules (TTs) that align with sarcomeres and Z-lines as well as longitudinal tubules (LTs) that are present between Z-lines in some species. In many cardiac disease etiologies, the T-system is perturbed, which is believed to promote spatially heterogeneous, dyssynchronous Ca²⁺ release and inefficient contraction. In general, T-system characterization approaches have been directed primarily at isolated cells and do not detect subcellular T-system heterogeneity. Here, we present MatchedMyo, a matched-filter-based algorithm for subcellular T-system characterization in isolated cardiomyocytes and millimeter-scale myocardial sections. The algorithm utilizes “filters” representative of TTs, LTs, and T-system absence. Application of the algorithm to cardiomyocytes isolated from rat disease models of myocardial infarction (MI), dilated cardiomyopathy induced via aortic banding, and sham surgery confirmed and quantified heterogeneous T-system structure and remodeling. Cardiomyocytes from post-MI hearts exhibited increasing T-system disarray as proximity to the infarct increased. We found significant (p < 0.05, Welch’s t-test) increases in LT density within cardiomyocytes proximal to the infarct (12 ± 3%, data reported as mean ± SD, n = 3) versus sham (4 ± 2%, n = 5), but not distal to the infarct (7 ± 1%, n = 3). The algorithm also detected decreases in TTs within 5° of the myocyte minor axis for isolated aortic banding (36 ± 9%, n = 3) and MI cardiomyocytes located intermediate (37 $\pm$ 4%, n = 3) and proximal (34 ± 4%, n = 3) to the infarct versus sham (57 ± 12%, n = 5). Application of bootstrapping to rabbit MI tissue revealed distal sections comprised 18.9 ± 1.0% TTs, whereas proximal sections comprised 10.1 ± 0.8% TTs (p < 0.05), a 46.6% decrease. The matched-filter approach therefore provides a robust and scalable technique for T-system characterization from isolated cells through millimeter-scale myocardial sections.     

Accuracy of PurePulse photoplethysmography technology of Fitbit Charge 2 for assessment of heart rate during sleep

Elevated asleep heart rate (HR) is a risk factor for cardiovascular disease and other-cause morbidity and mortality. We assessed the accuracy of Fitbit Inc. PurePulse® photoplethysmography with reference to three-lead electrocardiography (ECG) in determining HR during sleep. HR of 35 (17 female) healthy adults 25.1 ± 10.6 years of age (mean ± SD) was continuously recorded throughout a single night of sleep. There was no significant difference in asleep HR mean (0.09 beats per minute [bpm], P = 0.426) between Fitbit photoplethysmography and ECG; plus, there was excellent intraclass correlation (0.998) and narrow Bland–Altman agreement range (2.67 bpm). The regression analysis of Bland–Altman plot of mean asleep HR indicates Fitbit tends to slightly overestimate reference values in the lower range of HR (HR < 50 bpm) by 0.51 bpm and slightly underestimate reference values in the higher range of HR (HR > 80 bpm) by 0.63 bpm. Mixed model analysis of epoch-by-epoch (5-min epochs) asleep HR showed significant “U” shape trend (P < 0.001) in amount of Fitbit error (absolute amount of difference between ECG and Fitbit values regardless of overestimation or underestimation) in regard to HR, i.e. smaller error in the medium range of HR (60–80 bpm) and slightly larger error for lower (<60 bpm) and higher (>80 bpm) ranges of HR. However, effect of age, body mass index, gender, and subjective sleep quality measured by Pittsburgh sleep quality index (good/poor sleepers) on error in estimating HR by the Fitbit method was not significant. It is concluded that Fitbit photoplethysmography suitably tracks HR during sleep in healthy young adults.     

Sleep duration and social jetlag are independently associated with anxious symptoms in adolescents

Although short total sleep time (TST) is associated with increased anxious symptoms in adolescents, it is unknown whether social jetlag, a misalignment between sleep timing on the weekend and school week, is independently associated with anxious symptoms. In the current study, sleep timing, anxious symptoms, and demographic information were assessed from 3097 adolescents (48% female, mean ± SD age 15.59 ± .77 years) from the age 15 wave of the Fragile Families and Child Wellbeing Study. Social jetlag was calculated as the absolute value of the midpoint of sleep on the weekend minus the midpoint of sleep during the school week. Anxious symptoms were measured through the 6-item anxiety subscale of the Brief Symptom Inventory 18. We assessed associations between sleep variables and anxious symptoms using multiple linear regression. Adjusted analyses controlled for sex, race/ethnicity, age in years, body mass index percentile, number of other children below the age of 18 in the household, and primary caregiver (PCG) married/cohabiting with youth’s biological parent, PCG employment status, PCG household income and PCG education level. In fully adjusted models (R² = .034), school night TST (b = ?.04, ?R² = .005, p < .001) was negatively associated with anxiety symptoms, while social jetlag (b = .04, ?R² = .009, p < .001) was positively and independently associated with anxiety symptoms. Findings indicate small associations of school night TST and social jetlag with anxious symptoms. Thus, maintenance of optimal emotional health in adolescents may require both sufficient sleep duration and regularity of sleep timing across the week.     

Melatonin ingestion after exhaustive late-evening exercise improves sleep quality and quantity,and short-term performances in teenage athletes

ABSTRACT

The present study aimed to explore the effects of a single 10-mg dose of melatonin (MEL) administration after exhaustive late-evening exercise on sleep quality and quantity, and short-term physical and cognitive performances in healthy teenagers. Ten male adolescent athletes (mean ± SD, age = 15.4 ± 0.3 years, body-mass = 60.68 ± 5.7 kg, height = 167.9 ± 6.9 cm and BMI = 21.21 ± 2.5) performed two test sessions separated by at least one week. During each session, participants completed the Yo-Yo intermittent-recovery-test level-1 (YYIRT-1) at ~20:00 h. Then, sleep polysomnography was recorded from 22:15 min to 07:00 h, after a double blind randomized order administration of a single 10-mg tablet of MEL (MEL-10 mg) or Placebo (PLA). The following morning, Hooper wellness index was administered and the participants performed the Choice Reaction Time (CRT) test, the Zazzo test and some short-term physical exercises (YYIRT-1, vertical and horizontal Jumps (VJ; HJ), Hand grip strength (HG), and five-jump test (5-JT)). Evening total distance covered in the YYIRT-1 did not change during the two conditions (p > 0.05). Total sleep time (Δ = 24.55 mn; p < 0.001), sleep efficiency (Δ = 4.47%; p < 0.001), stage-3 sleep (N3 sleep) (Δ = 1.73%; p < 0.05) and rapid-eye-movement sleep (Δ = 2.15%; p < 0.001) were significantly higher with MEL in comparison with PLA. Moreover, sleep-onset-latency (Δ = –8.45mn; p < 0.001), total time of nocturnal awakenings after sleep-onset (NA) (Δ = –11 mn; p < 0.001), stage-1 sleep (N1 sleep) (Δ = –1.7%; p < 0.001) and stage-2 sleep (N2 sleep) (Δ = ?1.9%; p < 0.05) durations were lower with MEL. The Hooper index showed a better subjective sleep quality, a decrease of the subjective perception of fatigue and a reduced level of muscle soreness with MEL. Moreover, MEL improved speed and performance but not inaccuracy during the Zazzo test. CRT was faster with MEL. Morning YYIRT-1 (Δ = 82 m; p < 0.001) and 5-JT (Δ = 0.08 m; p < 0.05) performances were significantly higher with MEL in comparison with PLA. In contrast, HG, VJ and HJ performances did not change during the two conditions (p > 0.05). The administration of a single dose of MEL-10 mg after strenuous late-evening exercise improved sleep quality and quantity, selective attention, subjective assessment of the general wellness state, and some short-term physical performances the following morning in healthy teenagers.     

Adaptation of the Morningness–Eveningness Stability Scale improved (MESSi) into Turkish

Morningness–eveningness is an individual difference that is related with various traits such as behavioral problems, personality, and health. The aim of the current study is to adopt the Morningness–Eveningness Stability Scale improved (MESSi) which is a novel assessment tool that consists of subscales of morning affect (MA), eveningness (EV), and distinctness (DI) into Turkish. Concurrent validity of the MESSi along with Big five inventory (BIG-5), Subjective alertness level, Pittsburg Sleep Quality Index (PSQI), Positive and Negative Affect Schedule (PANAS) were analyzed. The scale was administered to 1,076 high school and university students aged 14–47 years (M = 19.49, SD = 3.53). The explanatory factor analysis (EFA) and confirmatory factor analysis (CFA) revealed the three-factor structure of MESSi. According to the concurrent validity result of the MESSi with BIG-5, conscientiousness was found to correlate positively with MA and negatively with EV. Also, extraversion showed a negative correlation with DI and positive correlation with MA. Furthermore, the subjective alertness rating results showed that MA was positively related to alertness in the morning hours and negatively in the evening hours. Also, sleep quality-related results showed that EV and DI are positively related to total PSQI scores and negatively related to MA. In addition, concerning positive affect (PA) and negative affect (NA), MA was positively related with PA and negatively with NA, while DI was negatively related with PA and positively with NA. In overall, MESSi is a valid and reliable instrument and can be used in Turkish students.     

糖尿病足患者睡眠质量与疲劳程度的调查研究

目的:调查糖尿病足(diabetic foot,DF)患者的睡眠质量与疲劳程度,并分析其相关性。方法:选取105例糖尿病足患者,采用人口数据统计表调查患者的一般情况,匹兹堡睡眠质量指数量(PSQI)评估患者的睡眠质量,Piper疲劳量表(PFS)评估患者的疲劳程度,并通过pearson检测分析其相关性。结果:人口统计数据显示,56%的DF患者年龄在41岁以上,64.8%女性,82.9%已婚,48.6%小学学历,39%病程3年或更长的时间。PSQI的平均总得分为(8.17±3.02),PFS量表总分为(6.38±2.18),睡眠质量与疲劳度总得分之间呈显著正相关,相关系数r=0.622(P0.05)。结论:DF患者的睡眠质量较差,大多出现中度疲劳,二者之间呈正相关,应加强对DF患者的睡眠质量与疲劳的护理。     

Evening chronotype is associated with poor cardiovascular health and adverse health behaviors in a diverse population of women

ABSTRACT

Chronotype reflects time of day preferences for performing daily activities. Previous research within Asian and European cohorts indicates evening chronotype is associated with elevated cardiometabolic risk. However, evidence is limited from population-based US cohorts, particularly among women in whom evening chronotype prevalence may become higher after middle-age, coinciding with life stages associated with higher cardiovascular disease (CVD) risk. This cross-sectional study evaluated associations of chronotype with overall cardiovascular health (CVH), health behaviors, and cardiometabolic risk factors among 506 women (mean age = 37 ± 16y, 62% racial/ethnic minority) in the American Heart Association (AHA)’s Go Red for Women Strategically-Focused Research Network cohort at Columbia University (New York City, NY, USA). Chronotype was assessed using the validated Morningness-Eveningness Questionnaire (MEQ) and categorized as “evening”, “intermediate”, and “morning” chronotypes. Health behaviors (diet, physical activity, and sleep) were assessed using validated questionnaires. Anthropometrics, clinical blood pressure, and blood biomarkers were assessed at the clinic visit. CVH was evaluated using the AHA Life’s Simple 7 (LS7) metrics; LS7 scores of 0–8 and 9–14 were considered indicative of poor and moderate-to-high CVH, respectively. Linear and logistic regression models adjusted for age, race/ethnicity, education, health insurance, and menopausal status were used to examine associations of MEQ scores and chronotype categories with overall CVH, clinical cardiometabolic risk factors, and health behaviors. Overall, 13% of women identified as evening chronotypes, while 55% and 32% reported being intermediate and morning types. In linear models, higher MEQ scores were associated with higher AHA LS7 scores (β(SE) = 0.02(0.01); p = .014), indicative of more favorable CVH, and with health behaviors not included in the LS7. Higher MEQ scores were also associated with lower Pittsburgh Sleep Quality Index, i.e. better sleep quality, (β(SE) = ?0.07(0.02), p < .0001), lower insomnia severity (β(SE) = ?0.14(0.01), p < .0001), shorter time to fall asleep (β(SE) = ?0.28(0.14), p = .044), and less sedentary time (β(SE) = ?0.11(0.03), p = .001). In logistic regression models, evening chronotype, compared to intermediate/morning type, was associated with higher odds of having poor CVH (OR(95%CI):2.41(1.20–4.85)), not meeting AHA diet (OR(95%CI):2.89(1.59–5.23)) and physical activity guidelines (OR(95%CI):1.78(1.03–3.07)), and having short sleep (OR(95%CI):2.15(1.24–3.73)) or insomnia (OR(95%CI):2.69(1.53–4.75)). The evening type compared to morning type was also associated with being a current smoker (OR(95%CI):2.14(1.02–4.52)) and having poor sleep quality (OR(95%CI:2.35(1.27–4.37)) and long sleep onset latency (OR(95%CI:1.89(1.00–3.56)). In our cohort of women, evening chronotype was related to poor CVH, likely driven by its influence on health behaviors. These findings, although warranting confirmation prospectively in other populations, suggest chronotype is an important factor to consider and possibly target when designing lifestyle interventions for CVD prevention.