Letizia Galasso

Chronotype influences activity circadian rhythm and sleep: differences in sleep quality between weekdays and weekend.

Several studies have shown the differences among chronotypes in the circadian rhythm of different physiological variables. Individuals show variation in their preference for the daily timing of activity; additionally, there is an association between chronotype and sleep duration/sleep complaints. Few studies have investigated sleep quality during the week days and weekends in relation to the circadian typology using self-assessment questionnaires or actigraphy. The purpose of this study was to use actigraphy to assess the relationship between the three chronotypes and the circadian rhythm of activity levels and to determine whether sleep parameters respond differently with respect to time (weekdays versus the weekend) in Morning-types (M-types), Neither-types (N-types) and Evening-types (E-types). The morningness–eveningness questionnaire (MEQ) was administered to 502 college students to determine their chronotypes. Fifty subjects (16 M-types, 15 N-types and 19 E-types) were recruited to undergo a 7-days monitoring period with an actigraph (Actiwacth® actometers, CNT, Cambridge, UK) to evaluate their sleep parameters and the circadian rhythm of their activity levels. To compare the amplitude and the acrophase among the three chronotypes, we used a one-way ANOVA followed by the Tukey–Kramer post-hoc test. To compare the Midline Estimating Statistic of Rhythm (MESOR) among the three chronotypes, we used a Kruskal–Wallis non-parametric test followed by pairwise comparisons that were performed using Dunn’s procedure with a Bonferroni correction for multiple comparisons. The analysis of each sleep parameter was conducted using the mixed ANOVA procedure. The results showed that the chronotype was influenced by sex (χ2 with p = 0.011) and the photoperiod at birth (χ2 with p < 0.05). Though the MESOR and amplitude of the activity levels were not different among the three chronotypes, the acrophases compared by the ANOVA post-hoc test were significantly different (p < 0.001). The ANOVA post-hoc test revealed the presence of a significant difference (p < 0.001) between the M-types (14:32 h) and E-types (16:53 h). There was also a significant interaction between the chronotype and four sleep parameters: Sleep end, Assumed Sleep, Immobility Time and Sleep Efficiency. Sleep Efficiency showed the same patterns as did Assumed Sleep and Immobility Time: the Sleep Efficiency of the E-types was poorer than that of the M- and N-types during weekdays (77.9% ± 7.0 versus 84.1% ± 4.9 and 84.1% ± 5.2) but was similar to that measured in the M- and N-types during the weekend. Sleep Latency and Movement and Fragmentation Index were not different among the three chronotypes and did not change on the weekend compared with weekdays. This study highlights two key findings: first, we observed that the circadian rhythm of activity levels was influenced by the chronotype; second, the chronotype had a significant effect on sleep parameters: the E-types had a reduced sleep quality and quantity compared with the M- and N-types during weekdays, whereas the E-types reached the same levels as the other chronotypes during the weekends. These findings suggest that E-types accumulate a sleep deficit during weekdays due to social and academic commitments and that they recover from this deficit during “free days” on the weekend.

Sleep quality and high intensity interval training at two different times of day: A crossover study on the influence of the chronotype in male collegiate soccer players

ABSTRACT The influence of the chronotype on the sleep quality in male collegiate soccer players in response to acute high intensity interval training (HIIT) performed at two different times of day was evaluated. The sleep quality was poorer in the morning-type than in the evening-type players after the evening HIIT session, whereas no significant changes in the sleep quality of the two chronotypes after the morning HIIT session was observed. The results suggest that an athlete’s chronotype should be taken into account when scheduling training sessions and to promote faster recovery processes.

Protective Effect of Aerobic Physical Activity on Sleep Behavior in Breast Cancer Survivors

Hypotheses. Sleep disorders are associated with an increased risk of cancer, including breast cancer (BC). Physical activity (PA) can produce beneficial effects on sleep. Study design. We designed a randomized controlled trial to test the effect of 3 months of physical activity on sleep and circadian rhythm activity level evaluated by actigraphy. Methods. 40 BC women, aged 35-70 years, were randomized into an intervention (IG) and a control group (CG). IG performed a 3 month of aerobic exercise. At baseline and after 3 months, the following parameters were evaluated both for IG and CG: anthropometric and body composition measurements, energy expenditure and motion level; sleep parameters (Actual Sleep Time-AST, Actual Wake Time-AWT, Sleep Efficiency-SE, Sleep Latency-SL, Mean Activity Score-MAS, Movement and Fragmentation Index-MFI and Immobility Time-IT) and activity level circadian rhythm using the Actigraph Actiwatch. Results. The CG showed a deterioration of sleep, whereas the IG showed a stable pattern. In the CG the SE, AST and IT decreased and the AWT, SL, MAS and MFI increased. In the IG, the SE, IT, AWT, SL, and MAS showed no changes and AST and MFI showed a less pronounced change in the IG than in the CG. The rhythmometric analysis revealed a significant circadian rhythm in two groups. After 3 months of PA, IG showed reduced fat mass %, while CG had improved weight and BMI. Conclusion. Physical activity may be beneficial against sleep disruption. Indeed, PA prevented sleep worsening in IG. PA can represent an integrative intervention therapy able to modify sleep behaviour.

Predicting the actigraphy-based acrophase using the Morningness–Eveningness Questionnaire (MEQ) in college students of North Italy

ABSTRACT Actigraphy is the reference objective method to measure circadian rhythmicity. One simpler subjective approach to assess the circadian typology is the Morningness–Eveningness Questionnaire (MEQ) by Horne and Ostberg. In this study, we compared the MEQ score against the actigraphy-based circadian parameters MESOR, amplitude and acrophase in a sample of 54 students of the University of Milan in Northern Italy. MEQ and the acrophase resulted strongly and inversely associated (r = −0.84, p < 0.0001), and their relationship exhibited a clear-cut linear trend. We thus used linear regression to develop an equation enabling us to predict the value of the acrophase from the MEQ score. The parameters of the regression model were precisely estimated, with the slope of the regression line being significantly different from 0 (p < 0.0001). The best-fit linear equation was: acrophase (min) = 1238.7–5.49·MEQ, indicating that each additional point in the MEQ score corresponded to a shortening of the acrophase of approximately 5 min. The coefficient of determination, R2, was 0.70. The residuals were evenly distributed and did not show any systematic pattern, thus indicating that the linear model yielded a good, balanced prediction of the acrophase throughout the range of the MEQ score. In particular, the model was able to accurately predict the mean values of the acrophase in the three chronotypes (Morning-, Neither-, and Evening-types) in which the study subjects were categorized. Both the confidence and prediction limits associated to the regression line were calculated, thus providing an assessment of the uncertainty associated with the prediction of the model. In particular, the size of the two-sided prediction limits for the acrophase was about ±100 min in the midrange of the MEQ score. Finally, k-fold cross-validation showed that both the model’s predictive ability on new data and the model’s stability to changes in the data set used for parameter estimation were good. In conclusion, the actigraphy-based acrophase can be predicted using the MEQ score in a population of college students of North Italy.

If the Morning-Evening Questionnaire (MEQ) is able to predict the actigraphy-based acrophase, how does its reduced, five-item version (rMEQ) perform?

Dear Editor, We have recently shown that the score yielded by the Morning-Evening Questionnaire (MEQ) (Horne & Ostberg, 1976) can be used to predict the acrophase measured by actigraphy in a sample of 54 college students of North Italy (Roveda et al., 2017). The MEQ score was very well correlated with the acrophase (r = 0.84, p < 0.001), and the linear regression equation linking the MEQ score to the acrophase is: acrophase = 1238.7–5.49·MEQ, thus indicating that a one-point increase in the MEQ score is accompanied, on average, by a decrease of approximately 5 min in the acrophase. Since the online publication of the article, we were contacted by potential users of this equation who do not have at their disposal theMEQ score, but only its reduced version (rMEQ) based on 5 over 19 items (Adan & Almiral, 1991). These inquiries motivated the present follow-up which is aimed to address the following questions. If the MEQ score is capable of satisfactorily predicting the acrophase, what is the performance of its shorter version rMEQ? Does the predictive ability of rMEQ remain good enough or the loss of information inherent in the item reduction take its toll? Such questions are clearly relevant for the investigators planning to use a questionnairebased approach to gain insight into the acrophase. Therefore, we returned to the original database (Roveda et al., 2017; Vitale et al., 2015) and calculated the rMEQ with 5 items, whose numbers in the MEQ were 1, 7, 10, 18, and 19 (Adan & Almiral, 1991). The rMEQ score was 13.8 ± 4.5 (mean ± SD, n = 54). Then, the exact same regression analysis procedures were applied as previously described (Roveda et al., 2017) so that a new linear equation was generated enabling the rMEQ to predict the acrophase. The scattergram of the data together with the best-fit regression line is showed in Figure 1. The equation of the regression line is: acrophase = 1182.4–16.24·rMEQ. The slope of the regression line (−16.24 min per unit of rMEQ) was significantly different from 0 (p < 0.001). Its value indicates that a one-point increase in the rMEQ score was accompanied, on average, by a decrease of approximately 16 min in the acrophase. Pearson’s r was 0.79 (p < 0.001), and thus only slightly lower than the value r = 0.84 that measured the strength of the relationship between theMEQ and the acrophase (Roveda et al., 2017). If we make reference to the coefficient of determination (i.e., R), the MEQ explained 70% of the variability present in the acrophase, while rMEQ explained 62%. All in all, the performance of the rMEQ was reasonably good. This is probably related with the fact that rMEQ has been proven to be a very good measure of circadian typology (Adan & Almiral, 1991; Adan & Natale, 2002; Adan et al., 2012; Chelminski et al., 2000; Di Milia et al. 2013; Natale et al., 2006). As pointed out by Adan et al. in their review paper (Adan et al., 2012), many authors have reported an elevated degree of agreement between MEQ and rMEQ, with Pearson’s correlation coefficient ranging from satisfying to excellent (0.69–0.90). In our study, the demonstrated correlation was excellent (r = 0.95, p < 0.001), probably because our sample consisted of college students having a very restricted age range (mean age ± SD was 22.1 ±

Rest-activity circadian rhythm and sleep quality in patients with binge eating disorder

ABSTRACT Recent findings suggest that altered rest-activity circadian rhythms (RARs) are associated with a compromised health status. RARs abnormalities have been observed also in several pathological conditions, such as cardiovascular, neurological, and cancer diseases. Binge eating disorder (BED) is the most common eating disorder, with a prevalence of 3.5% in women and 2% in men. BED and its associate obesity and motor inactivity could induce RARs disruption and have negative consequences on health-related quality of life. However, the circadian RARs and sleep behavior in patients with BED has been so far assessed only by questionnaires. Therefore, the purpose of this study was to determine RARs and sleep parameters by actigraphy in patients with BED compared to a body mass index-matched control group (Ctrl). Sixteen participants (eight obese women with and eight obese women without BED diagnosis) were recruited to undergo 5-day monitoring period by actigraphy (MotionWatch 8®, CamNtech, Cambridge, UK) to evaluate RARs and sleep parameters. In order to determine the RARs, the actigraphic data were analyzed using the single cosinor method. The rhythmometric parameters of activity levels (MESOR, amplitude and acrophase) were then processed with the population mean cosinor. The Actiwatch Sleep Analysis Software (Cambridge Neurotecnology, Cambridge, UK) evaluated the sleep patterns. In each participant, we considered seven sleep parameters (sleep onset: S-on; sleep offset: S-off; sleep duration: SD; sleep latency: SL; movement and fragmentation index: MFI; immobility time: IT; sleep efficiency: SE) calculated over a period of five nights. The population mean cosinor applied to BED and Ctrl revealed the presence of a significant circadian rhythm in both groups (p < 0.001). The MESOR (170.0 vs 301.6 a.c., in BED and Ctrl, respectively; p < 0.01) and amplitude (157.66 vs 238.19 a.c., in BED and Ctrl, respectively p < 0.05) differed significantly between the two groups. Acrophase was not different between BED and Ctrl, as well as all sleep parameters. Both groups displayed a low level of sleep quality (SE 80.7% and 75.7% in BED and Ctrl, respectively). These data provided the first actigraphy-based evidence of RARs disruption and sleep behavior disorder in patients with BED. However, while sleep disorders could be reasonably ascribed to overweight/obesity and the related lower daily physical activity, RARs disruption in this pathology should be ascribed to factors other than reduced physical activity. The circadian timing approach can represent a novel potential tool in the treatment of patients with eating disorders. These data provide exploratory evidence of behavioral association in a small population of patients that, if confirmed in a wider number of subjects and across different populations, may lead to a revision and enhancement of interventions in BED patients.

The circadian typology: the role of physical activity and melatonin

Circadian rhythms influence our daily behavior. Individuals display preferences for activity at certain time of day and this circadian phenotype can be summarized with the concept of “chronotype” or circadian typology (CT). The chronotypes differ in the timing of many physiological and psychological variables. Individuals with an early circadian phase are morning-types (M-types), those with a delayed circadian phase are evening-types (E-types), and those with an intermediate circadian phase are neither-types (N-types). Nevertheless, the propensity toward morning or evening preferences can vary during the life. In particular, adolescence can represent a crucial time in which the sleep–wake cycle tends to become delayed. The circadian rhythm desynchronization is common in modern society and lead to negative health effects, not only for physical health, but also for cognitive and affective function. One of the most important variables that show a defined circadian rhythm is melatonin; human melatonin levels increase at night, but the acrophase of melatonin occurs earlier in M-type than in E-type. Aim of this review, after providing a description of the methods for detecting the CT, analyzes the propensity toward morning or evening preferences in different life periods and the interactions between melatonin and physiological functions associated to physical activity. Exercise, performed in morning or in evening sessions, can adjust circadian rhythm, supporting its application as a treatment for the circadian rhythm desynchronization, for example, resulting from jet lag or shift work. Interindividual differences should also be taken into account in case of changes of the circadian rhythms parameters of different variables that can influence health also in relation to sport.

Rest-Activity circadian Rhythms and Body Mass Index In women with metabolic syndrome

The metabolic syndrome is a complex of interrelated risk factors such as abdominal obesity, high blood pressure, dyslipidemia and high fasting glycemia. These risk factors expose the subject to cardiovascular diseases and type 2 diabetes mellitus. Furthermore, it has been shown that there is a correlation between circadian rhythms and metabolic syndrome. The circadian rhythms produce 24-hour oscillations of several physiological variables and any irregularity of these rhythms exposes the subject to an increased risk of metabolic syndrome [1]. Aim of the study was to investigate a possible direct correlation between Rest-Activity circadian Rhythms (RARs) and Body Mass Index (BMI) in subjects with metabolic syndrome. We recruited 52 adult women with metabolic syndrome in care at Fondazione IRCCS, Istituto Nazionale Tumori. All participants underwent a continuous 7-day actigraphic monitoring to detect the RARs. Subsequently, they were subdivided into 3 groups referring to their BMI: group 1, with BMI between 25 and 30 (n=18), group 2, with BMI between 30 and 35 (n=27), and group 3 with BMI >35 (n=8). All data were analyzed by single cosinor method to obtain MESOR (M), amplitude (A) and acrophase (O) for each subject. Then, on these values we applied the mean cosinor method to evaluate the parameters M, A and O for each group. We found statistically significant differences for MESOR (M group 1: 269.8 vs M group 2: 226.9; p< .05) and amplitude (A group 1: 212.1 vs A group 2: 171.8; p< .05) between group 1 and 2 by Hotelling test. These results show a trend to have an inverse correlation between BMI and MESOR, and BMI and amplitude.

“Muoversi in equilibrio” project: effects on balance capacity in Binge Eating Disorder

Patients with Binge Eating Disorder (BED) are characterized by the consumption of a large amount of food in a short period of time, accompanied by a perceived sense of loss of control over the eating episode. Although obesity is not a DSM-V criterion for BED, there is a strong association between BED, obesity and physical inactivity [1]. In this study we evaluated if a structured physical activity program influences static and dynamic balance in BED patients. For the study we recruited 18 BED patients, 15 females and 3 males, aged 53.1 ± 14.9 (mean ± SD). Subjects physically/pathologically unable in doing physical activity were excluded. The participants, in addition to medical treatment, performed a physical activity program for 6 months. The exercise session consists on aerobic, balance and strength activity performed in four weekly sessions of 90 minutes. In basal conditions and after 6 months were assessed: One Legged Stance Test to evaluate the static balance and Star Excursion Balance Test for the dynamic balance. The comparison between baseline and after 6 months results showed a significant improvement for either motor skills tests: OLST dx-sx (t Student p<.001) and SEBT dx-sx (t Student p<.01). The addition of exercise training in the traditional treatment for BED patients constitutes a novel potential therapeutic approach in eating disorder.

The student academic performance in Anatomy is related to Circadian Typology

In human species, circadian rhythmic expression differs among individuals and may be classified with the concept of Circadian Typology (CT), which consists of three chronotypes: i) Morning-type (M-types), subjects that go to bed early and wake up early and achieve their peak of mental and physical performance in the early part of the day; ii) Evening-type (E-types), subjects that go to bed and wake up late, and perform at their best toward the end of the day, during evening hours; iii) Neither-type (N-types), subjects that show intermediate characteristics between the previous samples. Circadian preferences may change during the life span and can influence academic and sport performance and job activities [1]. We collected data considering 427 students, 294 males and 133 females (age 18-25 years), attending the School of Sport Science, University of Milan. All participants compiled the Morningness-Eveningness Questionnaire (MEQ) for the assessment of chronotype; subsequently they have been evaluated taking into consideration their anatomy test marks. The chronotype distribution of the students was: 44 M-types, 280 N-types and 103 E-types. For M-types, the result in Anatomy exam was significantly higher compared to Evening-types (p< .01). Even the comparison between M-types and N-types showed a significant difference (p< .01). Instead, the performance for E- and N-types was similar. The present results provide a clear indication of a better academic performance for M-types students compared to E-types referring to Anatomy exam. In this way, the italian academic organization seems to be less favorable for E-types.