Delay discounting and response disinhibition moderate associations between actigraphically measured sleep parameters and body mass index

Changes in the sleeping habits of Japanese university students during the COVID-19 pandemic: a 3-year follow-up study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has greatly changed our daily life. Owing to the imposed restrictions, many educational facilities have introduced remote teaching. This study aims to clarify the association between remote teaching and Japanese university students' sleeping habits.

METHODS

The participants were medical students at Aichi Medical University. We used data from an ongoing longitudinal sleeping habits survey. For the participants who enrolled in the university during 2018-2020, multilevel analyses of sleep duration during weekdays and weekends across 3 years were conducted, adjusting for sex, grade, place of stay, sleep problems and lifestyle habits.

RESULTS

Among the students enrolled in the university, the data of 677 in 2018, 657 in 2019, and 398 in 2020 was available for analysis. The mean sleep duration during weekdays (in minutes) was 407.6 ± 60.3 in 2018, 406.9 ± 63.0 in 2019, and 417.3 ± 80.9 in 2020. The mean sleep duration during weekends (in minutes) was 494.5 ± 82.5 in 2018, 488.3 ± 87.9 in 2019, and 462.3 ± 96.4 in 2020. Multilevel analysis conducted for the 684 participants who enrolled during 2018-2020 showed that sleep duration during weekdays was associated with the place of stay and survey year. Moreover, students reported significantly longer sleep duration during weekdays in 2020 than in 2019, but no significant difference in sleep duration was found between 2018 and 2019. The other multilevel analysis found sleep duration during weekends to be associated with the survey year, sex and always doing something before going to bed. Sleep duration during weekends was shorter in 2020 than in 2019 and longer for male students and students who always do something before going to bed. Ten students were reported to have a delayed sleep phase in 2020.

CONCLUSIONS

Students' sleep duration increased during weekdays and decreased during weekends in 2020. This difference could be explained by the COVID-19 pandemic and the introduction of remote teaching.

Intertemporal Decision-making and Risk Decision-making Among Habitual Nappers Under Nap Sleep Restriction: A Study from ERP and Time-frequency

Sleep restriction affects people's decision-making behavior. Nap restriction is a vital subtopic within sleep restriction research. In this study, we used EEG to investigate the impact of nap sleep restriction on intertemporal decision-making (Study 1) and decision-making across risky outcomes (Study 2) from ERP and time-frequency perspectives. Study 1 found that habitual nappers restricting their naps felt more inclined to choose immediate, small rewards over delayed, large rewards in an intertemporal decision-making task. P200s, P300s, and LPP in our nap-restriction group were significantly higher than those in the normal nap group. Time-frequency results showed that the delta band (1 ~ 4 Hz) power of the restricted nap group was significantly higher than that of the normal nap group. In Study 2, the nap-restriction group was more likely to choose risky options. P200s, N2s, and P300s in the nap deprivation group were significantly higher than in the normal nap group. Time-frequency results also found that the beta band (11 ~ 15 Hz) power of the restricted nap group was significantly lower than that of the normal nap group. The habitual nappers became more impulsive after nap restriction and evinced altered perceptions of time. The time cost of the LL (larger-later) option was perceived to be too high when making intertemporal decisions, and their expectation of reward heightened when making risky decisions-believing that they had a higher probability of receiving a reward. This study provided electrophysiological evidence for the dynamic processing of intertemporal decision-making, risky decision-making, and the characteristics of nerve concussions for habitual nappers.

Irregular sleep and cardiometabolic risk: Clinical evidence and mechanisms

Sleep regularity is an essential part of the multidimensional sleep health framework. The phenomenon of irregular sleep patterns is widespread in contemporary lifestyles. This review synthesizes clinical evidence to summarize the measures of sleep regularity and discusses the role of different sleep regularity indicators in developing cardiometabolic diseases (coronary heart disease, hypertension, obesity, and diabetes). Existing literature has proposed several measurements to assess sleep regularity, mainly including the standard deviation (SD) of sleep duration and timing, sleep regularity index (SRI), interdaily stability (IS), and social jetlag (SJL). Evidence on associations between sleep variability and cardiometabolic diseases varies depending on the measure used to characterize variability in sleep. Current studies have identified a robust association between SRI and cardiometabolic diseases. In comparison, the association between other metrics of sleep regularity and cardiometabolic diseases was mixed. Meanwhile, the associations of sleep variability with cardiometabolic diseases differ across the population. SD of sleep characteristics or IS may be more consistently associated with HbA1c in patients with diabetes compared with the general population. The association between SJL and hypertension for patients with diabetes was more accordant than in the general population. Interestingly, the age-stratified association between SJL and metabolic factors was observed in the present studies. Furthermore, the relevant literature was reviewed to generalize the potential mechanisms through which irregular sleep increases cardiometabolic risk, including circadian dysfunction, inflammation, autonomic dysfunction, hypothalamic-pituitary-adrenal (HPA) axis disorder, and gut dysbiosis. Health-related practitioners should give more attention to the role of sleep regularity on human cardiometabolic in the future.

Associations between sleep variability and cardiometabolic health: A systematic review

This review explored the associations between sleep variability and cardiometabolic health. It was performed following PRISMA guidelines. We identified 63 studies. Forty-one studies examined the association between sleep variability and body composition, with 29 examined body mass index (BMI). Thirteen studies used social jet lag (SJL), n = 30,519, with nine reporting a null association. Eight studies used variability in sleep duration (n = 33,029), with five reporting a correlation with BMI. Fourteen studies (n = 133,403) focused on overweight/obesity; significant associations with sleep variability were found in 11 (n = 120,168). Sleep variability was associated with weight gain (seven studies; n = 79,522). Twenty-three studies examined glucose outcomes. The association with hemoglobin A1c (16 studies, n = 11,755) differed depending on populations, while associations with diabetes or glucose were mixed, and none were seen with insulin resistance (five studies; n = 6416). Sixteen studies examined cardiovascular-related outcomes, with inconsistent results. Overall significant associations were found in five studies focusing on metabolic syndrome (n = 7413). In summary, sleep variability was likely associated with obesity, weight gain, and metabolic syndrome. It might be associated with hemoglobin A1c in people with type 1 diabetes. The associations with other outcomes were mixed. This review highlighted the possible association between sleep variability and cardiometabolic health.

Daytime napping and cardiovascular risk factors, cardiovascular disease, and mortality: A systematic review

Associations between night sleep duration and cardiovascular risk factors in adults have been well documented. However, the associations for daytime napping remain unclear. In this review, six databases were searched for eligible publications to April 8, 2022. A total of 11 articles were identified for umbrella review on the association of daytime napping with diabetes, metabolic syndrome (MetS), cardiovascular disease (CVD), and mortality in adults, 97 for systematic review on the association with CVD and several CVD risk factors. Our umbrella review showed that the associations of daytime napping with diabetes, MetS, CVD, and mortality in most meta-analyses were mainly supported by weak or suggestive evidence. Our systematic review showed that long daytime napping (≥1 h/d) was associated with higher odds of several CVD risk factors, CVD, and mortality, but no significant association was found between short daytime napping and most of the abovementioned outcomes. Our dose-response meta-analyses showed that daytime napping <30 min/d was not significantly associated with higher odds of most CVD risk factors and CVD among young and middle-aged adults. However, among older adults aged >60 years, we observed significant dose-response associations of daytime napping with higher odds of diabetes, dyslipidemia, MetS, and mortality starting from 0 min/d.

Temporal discounting as a candidate behavioral marker of obesity

Although obesity is a result of processes operating at multiple levels, most forms result from decision-making behavior. The aim of this review was to examine the candidacy of temporal discounting (TD) (i.e. the reduction in the value of a reinforcer as a function of the delay to its receipt) as a behavioral marker of obesity. For this purpose, we assessed whether TD has the ability to: identify risk for obesity development, diagnose obesity, track obesity progression, predict treatment prognosis/outcomes, and measure treatment effectiveness. Three databases (Pubmed, PsycINFO, and Web of Science) were searched using a combination of terms related to TD and obesity. A total of 153 papers were reviewed. Several areas show strong evidence of TD's predictive utility as a behavioral marker of obesity (e.g., distinguishing obese from non obese). However, other areas have limited and/or mixed evidence (e.g., predicting weight change). Given the positive relationship for TD in the majority of domains examined, further consideration for TD as a behavioral marker of obesity is warranted.

Variability of Sleep and Relations to Body Weight Among First-Year College Students

BACKGROUND

Existing research suggests that greater sleep variability may increase risk for weight gain. College often marks a transition to a less consistent daily schedule, which may adversely impact sleep routines and further increase risk for weight gain. The current study is among the first to explore relations between nighttime sleep variability and daytime sleep (napping) and body weight among first-year college students.

METHODS

Using daily diary methods, first-year college students (N = 307; 84.7% female) self-reported their sleep for seven days. Several indices were created to capture sleep variability for reported bedtime, wake time, and sleep duration, including weekday versus weekend differences (WvW), day to day differences (D2D), and overall standard deviation (SD). Napping was also assessed. Based on body mass index (BMI), individuals were categorized as underweight, healthy weight, overweight, and obese.

RESULTS

Across indices, students' sleep varied over an hour on average across the week. Hierarchical regressions revealed that greater differences in wake time D2D, wake time SD, and sleep duration WvW were all associated with higher BMI, after accounting for gender, depressive symptoms, and sleep duration. Longer napping was also associated with higher BMI, using the same covariates. Finally, greater sleep variability was reported by overweight and obese than healthy weight individuals.

CONCLUSION

These findings suggest that sleep variability, particularly wake times and napping may be important modifiable sleep behaviors to investigate in future studies. More longitudinal research is needed to explore relations between multiple facets of sleep variability and weight gain, including possible mechanisms.

Association between Sleep Timing and Weight Status among 14- to 19-Year-Old Adolescents in Wuhan, China

This study examined the cross-sectional and longitudinal association of sleep timing with weight status in 14- to 19-year-old adolescents in Wuhan, China. A prospective school-based study was conducted in Wuhan, China between 28 May and 29 September 2019. Data on sociodemographic information, academic performance, diet, mental health status, physical activity, sleep characteristics, body weight, and height were collected. A linear regression model and binary logistic regression model were performed. A total of 1194 adolescents were included in the analysis. Adolescents who woke up before 05:45 had higher body mass index (BMI) Z-score (odds ratio (OR) with 95% confidence interval (CI) = 1.28 (1.05, 1.57), p = 0.02) and higher odds of overweight/obesity (odds ratio (OR) with 95% confidence interval (CI) = 1.74 (1.10, 2.76), p = 0.02) at baseline after fully adjustment for covariates, compared with those who woke up after 05:45. Longitudinal data showed a nonsignificant association between waking up time and change in BMI Z-score (p = 0.18). No association of bedtime with weight status was observed in this sample after full adjustment (p > 0.1). Earlier waking up time might contribute to overweight and obesity in adolescents; however, more data are needed to test and elucidate this relationship.

Irregular sleep and event schedules are associated with poorer self-reported well-being in US college students

STUDY OBJECTIVES

Sleep regularity, in addition to duration and timing, is predictive of daily variations in well-being. One possible contributor to changes in these sleep dimensions are early morning scheduled events. We applied a composite metric-the Composite Phase Deviation (CPD)-to assess mistiming and irregularity of both sleep and event schedules to examine their relationship with self-reported well-being in US college students.

METHODS

Daily well-being, actigraphy, and timing of sleep and first scheduled events (academic/exercise/other) were collected for approximately 30 days from 223 US college students (37% females) between 2013 and 2016. Participants rated well-being daily upon awakening on five scales: Sleepy-Alert, Sad-Happy, Sluggish-Energetic, Sick-Healthy, and Stressed-Calm. A longitudinal growth model with time-varying covariates was used to assess relationships between sleep variables (i.e. CPDSleep, sleep duration, and midsleep time) and daily and average well-being. Cluster analysis was used to examine relationships between CPD for sleep vs. event schedules.

RESULTS

CPD for sleep was a significant predictor of average well-being (e.g. Stressed-Calm: b = -6.3, p < 0.01), whereas sleep duration was a significant predictor of daily well-being (Stressed-Calm, b = 1.0, p < 0.001). Although cluster analysis revealed no systematic relationship between CPD for sleep vs. event schedules (i.e. more mistimed/irregular events were not associated with more mistimed/irregular sleep), they interacted upon well-being: the poorest well-being was reported by students for whom both sleep and event schedules were mistimed and irregular.

CONCLUSIONS

Sleep regularity and duration may be risk factors for lower well-being in college students. Stabilizing sleep and/or event schedules may help improve well-being.

CLINICAL TRIAL REGISTRATION

NCT02846077.

Actigraphy-Derived Daily Rest-Activity Patterns and Body Mass Index in Community-Dwelling Adults

Study Objectives

To examine associations between 24-hour rest-activity patterns and body mass index (BMI) among community-dwelling US adults. Rest-activity patterns provide a field method to study exposures related to circadian rhythms.

Methods

Adults (N = 578) wore an actigraph on their nondominant wrist for 7 days. Intradaily variability and interdaily stability (IS), M10 (most active 10-hours), L5 (least active 5-hours), and relative amplitude (RA) were derived using nonparametric rhythm analysis. Mesor, acrophase, and amplitude were calculated from log-transformed count data using the parametric cosinor approach.

Results

Participants were 80% female and mean (standard deviation) age was 52 (15) years. Participants with higher BMI had lower values for magnitude, RA, IS, total sleep time (TST), and sleep efficiency. In multivariable analyses, less robust 24-hour rest-activity patterns as represented by lower RA were consistently associated with higher BMI: comparing the bottom quintile (least robust) to the top quintile (most robust 24-hour rest-activity pattern) of RA, BMI was 3-kg/m2 higher (p = .02). Associations were similar in magnitude to an hour less of TST (1-kg/m2 higher BMI) or a 10% decrease in sleep efficiency (2-kg/m2 higher BMI), and independent of age, sex, race, education, and the duration of rest and/or activity.

Conclusions

Lower RA, reflecting both higher night activity and lower daytime activity, was associated with higher BMI. Independent of the duration of rest or activity during the day or night, 24-hour rest, and activity patterns from actigraphy provide aggregated measures of activity that associate with BMI in community-dwelling adults.

Archetypes of human cognition defined by time preference for reward and their brain correlates: An evolutionary trade-off approach

Biological systems carry out multiple tasks in their lifetime, which, in the course of evolution, may lead to trade-offs. In fact phenotypes (different species, individuals within a species, circuits, bacteria, proteins, etc.) cannot be optimal at all tasks, and, according to Pareto optimality theory, lay into a well-defined geometrical distribution (polygons and/or polyhedrons) in the space of traits. The vertices of this distribution contain archetypes, namely phenotypes that are specialists at one of the tasks, whereas phenotypes toward the center of the geometrical distribution show average performance across tasks. We applied this theory to the variability of cognitive and behavioral scores measured in 1206 individuals from the Human Connectome Project. Among all possible combinations of pairs of traits, we found the best fit to Pareto optimality when individuals were plotted in the trait-space of time preferences for reward, evaluated with the Delay Discounting Task (DDT). The DDT measures subjects' preference in choosing either immediate smaller rewards or delayed larger rewards. Time preference for reward was described by a triangular distribution in which each of the three vertices included individuals who used a particular strategy to discount reward. These archetypes accounted for variability on many cognitive, personality, and socioeconomic status variables, as well as differences in brain structure and functional connectivity, with only a weak influence of genetics. In summary, time preference for reward reflects a core variable that biases human phenotypes via natural and cultural selection.

Daily associations between objective sleep and consumption of highly palatable food in free-living conditions

OBJECTIVES

Prior studies have shown that individuals with shorter sleep duration and later sleep timing consume more highly palatable food (HPF). It is unclear if this relationship exists at the within-individual level, e.g. if sleeping less or later on one night is associated with greater HPF consumption in the following day in naturalistic environments. This study examined the daily associations between naturalistic sleep and HPF consumption.

METHODS

Data were obtained from 78 healthy young adults (age = 20.38 [SD = 2.40] years). Participants carried a wrist actigraph and completed daily diaries tracking food consumption and covariates for seven consecutive days. Data were analysed using mixed models.

RESULTS

Individuals with later bedtime were less likely to consume HPF at breakfast in the following day (odds ratio, OR [between] = 0.55 [0.44, 0.70], p < 0.001). This association was also significant at the within-individual level (OR (within) = 0.85 [0.74, 0.97], p = 0.016) - sleeping later on one night was associated with 15% decrease in the odds of consuming HPF at breakfast in the following day. Individual with later wake time had greater likelihood of consuming HPF at dinner (OR = 1.34 [1.03, 1.75], p = 0.027).

CONCLUSIONS

Sleep schedules characterized by later bedtimes and later wake times were associated with lower HPF consumption earlier in the following day but greater HPF consumption later in the day. This pattern of energy intake might mediate the association between sleep and the risk of obesity.

Naps Do Not Change Delay Discounting Behavior in Young Adults

When offered a choice of $40 today or $50 later, many would choose the immediate reward over the greater delayed reward. Such behavior is a result of future gains being discounted such that their value is rendered less than that of the immediate gain. Extreme discounting behaviors are associated with impulsivity and addiction. Given recent evidence of sleep's role in decision making, we tested the hypothesis that sleep would reduce delayed discounting behavior. Twenty young adults (M = 20.19 years, SD = 0.98 years; 6 males) performed a hypothetical delay discounting task, making a series of choices between an immediate reward (from $0 to $50) or a larger reward ($50) available at a delay of 2, 4, 8, 14, or 22 weeks. Participants performed the task before and after a mid-day nap, and before and after an equivalent interval of wake (within subject, order counterbalanced, wake, and sleep conditions separated by 1 week). As expected, indifference points decreased with longer delays both prior to and following the nap/wake interval. However, the impact of a nap interval on discounting did not differ from the impact of a wake interval. Thus, while sleep has been shown to play an active role in some financial decision-making tasks, a nap is not sufficient to change delay discounting behavior.

Transforming Life: A Broad View of the Developmental Origins of Health and Disease Concept from an Ecological Justice Perspective

The influential scientist Rene J. Dubos (1901–1982) conducted groundbreaking studies concerning early-life environmental exposures (e.g., diet, social interactions, commensal microbiota, housing conditions) and adult disease. However, Dubos looked beyond the scientific focus on disease, arguing that “mere survival is not enough”. He defined mental health as fulfilling human potential, and expressed concerns about urbanization occurring in tandem with disappearing access to natural environments (and elements found within them); thus modernity could interfere with health via “missing exposures”. With the advantage of emerging research involving green space, the microbiome, biodiversity and positive psychology, we discuss ecological justice in the dysbiosphere and the forces—financial inequity, voids in public policy, marketing and otherwise—that interfere with the fundamental rights of children to thrive in a healthy urban ecosystem and learn respect for the natural environment. We emphasize health within the developmental origins of health and disease (DOHaD) rubric and suggest that greater focus on positive exposures might uncover mechanisms of resiliency that contribute to maximizing human potential. We will entrain our perspective to socioeconomic disadvantage in developed nations and what we have described as “grey space”; this is a mental as much as a physical environment, a space that serves to insidiously reinforce unhealthy behavior, compromise positive psychological outlook and, ultimately, trans-generational health. It is a dwelling place that cannot be fixed with encephalobiotics or the drug-class known as psychobiotics.