Longitudinal associations between facets of sleep and adiposity in youth

Association between weekend catch-up sleep and depression of the United States population from 2017 to 2018: A cross-sectional study

Insufficient sleep on weekdays has become a societal norm, and studies have shown that sleep deprivation increases the risk of depression. Although individuals often resort to weekend catch-up sleep (CUS) as a compensatory measure, the present evidence supporting its efficacy in mitigating the risk of depression is limited. This article attempts to explore the relationship between CUS and depression. In this study, a total of 5510 participants were included, characterized into two groups: nondepressed (n = 5051) and depressed (n = 459), with data extracted from the National Health and Nutrition Examination Survey (NHANES). Compared with people without CUS, those practicing CUS exhibited a significantly lower risk of depression (OR = 0.81, P = 0.048). In subgroup analysis, this reduction effect was only observed in males (OR = 0.70, 95 % CI 0.05 to 0.99, P = 0.04), middle-aged (>40, ≤60) (OR: 0.57, 95 % CI: 0.40 to 0.81, P = 0.002), married or living with parents (OR: 0.61, 95 % CI: 0.44 to 0.86, P = 0.004), groups with three or more family members (OR: 0.69, 95 % CI: 0.52 to 0.93, P = 0.01), and individuals without alcohol intake (OR: 0.24,95 % CI: 0.09 to 0.67, P = 0.006). Therefore, in the realm of depression treatment, doctors may consider advising patients to get adequate sleep on weekends as part of their overall treatment plan. At the same time, individuals can also choose weekend sleep as a proactive strategy for regulating their psychological status.

Associations of actigraphy-assessed sleep variables with adiposity and serum cardiometabolic outcomes in emerging adults

This study assessed associations of actigraphy-assessed sleep with adiposity and serum cardiometabolic outcomes in emerging adults, and whether sex and race modified these associations. Data on 147 emerging adults (age = 19.4 ± 1.3 years; body mass index = 26.4 ± 7.0 kg m-2 ; 59% female; 65% White) from RIGHT Track Health were used. Actigraphy-based sleep measures included sleep duration, sleep efficiency, sleep timing midpoint, day-to-day sleep duration and sleep timing midpoint variability. Combined sleep duration and sleep timing behaviours were also derived (early-bed/late-rise, early-bed/early-rise, late-bed/late-rise, late-bed/early-rise). Outcomes included body mass index and BodPod-assessed fat mass index, fasting serum leptin, C-reactive protein, and homeostatic model assessment-insulin resistance. Sleep duration was 5.4 h per night. We noted an inverse association between sleep duration and homeostatic model assessment-insulin resistance. The early-bed/early-rise group had greater body mass index, C-reactive protein and homeostatic model assessment-insulin resistance compared with the early-bed/late-rise group (referent). Sex modified associations of sleep efficiency with C-reactive protein; stratified results revealed positive association between sleep efficiency and C-reactive protein in males, but not females. Race modified associations of sleep duration with body mass index and leptin, and of sleep duration variability with C-reactive protein. Stratified analyses revealed inverse associations between sleep duration with body mass index and leptin in Black, multiracial/other race individuals only. Positive association between sleep duration variability and C-reactive protein was noted in White individuals only. Shorter sleep duration, particularly when combined with earlier sleep timing, is associated with greater adiposity and serum cardiometabolic outcomes. Additional studies are needed to assess individual- and contextual-level factors that may contribute to sex and race differences in sleep health and cardiometabolic risk in emerging adults.

Social jetlag and obesity: A systematic review and meta-analysis

Social jetlag, the weekly variation in sleep timing, is proposed to contribute to increased obesity risk, potentially because of the misalignment of behavioral cycles relative to the endogenous circadian timing system. This systematic review and meta-analysis aim to determine the association between social jetlag and adiposity-related measures using observational studies. We reviewed 477 references, of which 43 studies met inclusion criteria with a total sample size of 231,648. There was a positive association between social jetlag and body mass index (correlation coefficient [r]: 0.12; 95%CI, 0.07, 0.17; P < 0.001; I2  = 94.99%), fat mass (r: 0.10; 95%CI, 0.05, 0.15; P < 0.001; I2  = 0.00%), fat mass index (fat mass divided by height in meter squared, β: 0.14 kg/m2 ; 95%CI, 0.05, 0.23; P < 0.001; I2  = 56.50%), percent of body fat (r: 0.37; 95%CI, 0.33, 0.41; P < 0.001; I2  = 96.17%), waist circumference (r: 0.15; 95%CI, 0.06, 0.24; P = 0.001; I2  = 90.83%), and the risk of having overweight/obesity (odds ratio: 1.20; 95%CI, 1.02, 1.140; P = 0.039; I2  = 98.25%). Social jetlag is positively and consistently associated with multiple obesity-related anthropometric measures. Further studies are needed to test causality, underlying mechanisms, and whether obesity interventions based on increasing regularity of the sleep/wake cycle can aid in the battle against the obesity pandemic.

Accelerometry-assessed sleep clusters and cardiometabolic risk factors in adolescents

OBJECTIVE

This study aimed to identify sleep clusters based on objective multidimensional sleep characteristics and test their associations with adolescent cardiometabolic health.

METHODS

The authors included 1090 participants aged 14.3 to 16.4 years (mean = 15.2 years) who wore 7-day accelerometers during the 15-year follow-up of the German Infant Study on the influence of Nutrition Intervention PLUS environmental and genetic influences on allergy development (GINIplus) and the Influence of Lifestyle factors on the development of the Immune System and Allergies in East and West Germany (LISA) birth cohorts. K-means cluster analysis was performed across 12 sleep characteristics reflecting sleep quantity, quality, schedule, variability, and regularity. Cardiometabolic risk factors included fat mass index (FMI), blood pressure, triglycerides, high-density lipoprotein cholesterol, high-sensitivity C-reactive protein, and insulin resistance (n = 505). Linear and logistic regression models were examined.

RESULTS

Five sleep clusters were identified: good sleep (n = 337); delayed sleep phase (n = 244); sleep irregularity and variability (n = 108); fragmented sleep (n = 313); and prolonged sleep latency (n = 88). The "prolonged sleep latency" cluster was associated with increased sex-scaled FMI (β = 0.39, 95% CI: 0.15-0.62) compared with the "good sleep" cluster. The "sleep irregularity and variability" cluster was associated with increased odds of high triglycerides only in male individuals (odds ratio: 9.50, 95% CI: 3.22-28.07), but this finding was not confirmed in linear models.

CONCLUSIONS

The prolonged sleep latency cluster was associated with higher FMI in adolescents, whereas the sleep irregularity and variability cluster was specifically linked to elevated triglycerides (≥1.7 mmol/L) in male individuals.

Age, sex and race distribution of accelerometer-derived sleep variability in US school-aged children and adults

Sleep variability (e.g. intra-individual variabilities in sleep duration or sleep timing, social jetlag, and catch-up sleep) is an important factor impacting health and mortality. However, limited information is available on the distribution of these sleep parameters across the human life span. We aimed to provide distribution of sleep variability related parameters across lifespan by sex and race in a national representative sample from the U.S. population. The study included 9981 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, who had 4-7 days of valid 24-h accelerometer recording with at least one day obtained during weekend (Friday or Saturday night). Of the study participants, 43% showed ≥ 60 min sleep duration standard deviation (SD), 51% experienced ≥ 60 min catch-up sleep, 20% showed ≥ 60 min sleep midpoint SD, and 43% experienced ≥ 60 min social jetlag. American youth and young adults averaged greater sleep variability compared to other age groups. Non-Hispanic Blacks showed greater sleep variability in all parameters compared to other racial groups. There was a main effect of sex on sleep midpoint SD and social jetlag with males averaging slightly more than females. Our study provides important observations on sleep variability parameters of residents of the United States by using objectively measured sleep patterns and will provide unique insights for personalized advice on sleep hygiene.

Obesogenic sleep patterns among Chinese preschool children: A latent profile and transition analysis of the association sleep patterns and obesity risk

OBJECTIVE

This paper utilized a person-centered approach to examine whether sleep patterns on school and free days are associated with obesity risk in preschool children aged 3-6 years.

METHODS

The cross-sectional analysis included 204 children from the Wuhan Healthy Start Project with valid sleep data in at least four consecutive days gathered via Actigraph GT3X+. Based on three domains of sleep duration, sleep onset, and sleep offset, we used latent profile analysis to identify distinct sleep patterns on school and free days separately. Additionally, we conducted latent transition analysis to explore the probabilities of sleep patterns transitions between school and free days. The multivariate logistic regression model investigated the associations of sleep patterns with overweight/obesity (OWO) (BMI ≥ age- and sex-specific 85th percentile) and abdominal obesity (AO) (WC ≥ age- and sex-specific 75th percentile).

RESULTS

Two sleep patterns were identified for school days: "EL-sc" (early-to-sleep/longer-duration) (n = 119; 58.3%) and "LS-sc" (late-to-sleep/shorter-duration) (n = 85; 41.7%). Similarly, "LES-fr" (late-to-sleep/early-to-wake/shorter-duration) (n = 118; 57.8%) and "ELL-fr" (early-to-sleep/late-to-wake/longer-duration) (n = 86; 42.2%) patterns were identified for free days. LTA categorized the participants into four distinct transition groups, i.e., "EL-sc→ELL-fr" (32.9%), "EL-sc→LES-fr" (24.0%), "LS-sc→LES-fr" (33.8%), and "LS-sc→ELL-fr" (9.3%). Compared with the "ELsc→ELL-fr", the "LS-sc→LES-fr" had a higher risk of OWO (AOR 4.76; 95% CI: 1.39-20.33) and AO (AOR, 2.78; 95% CI, 1.21-6.62), respectively. Neither "EL-sc→LES-fr" (AOR, 1.11; 95% CI, 0.14-6.67) nor "LS-sc→ELL-fr" (AOR, 0.74; 95% CI, 0.03-6.14) was significantly associated with OWO. Likewise, no significant association was observed for "EL-sc→LES-fr" (AOR, 0.96; 95% CI, 0.35-2.62) and "LS-sc→ELL-fr" (AOR, 0.56; 95% CI, 0.11-2.18) with AO.

CONCLUSIONS

"LS-sc→LES-fr" pattern is significantly associated with an increased risk of general and abdominal obesity, indicating its obesogenic nature. Furthermore, although not statistically associated with obesity outcomes, "LS-sc→ELL-fr" and "EL-sc→LES-fr" patterns exhibit a semi-obesogenic characteristic. In addition, we identified a concerning trend that preschool children are at risk of transitioning to and persisting in sleep patterns characterized by delayed and shorter sleep. These findings underscore the importance of implementing interventions and strategies to address sleep patterns as a crucial step to minimize the risk of obesity.

Age, sex and race distribution of accelerometer-derived sleep variability in US school-aged children and adults

Background

Sleep variability (e.g. intra-individual variabilities in sleep duration or sleep timing, social jetlag, and catch-up sleep) is an important factor impacting health and mortality. However, limited information is available on the distribution of these sleep parameters across the human life span. We aimed to provide distribution of sleep variability related parameters across lifespan by sex and race in a national representative sample from the U.S. population.

Methods

The study included 9,799 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, who had at least 3 days of valid sleep parameters with at least one day obtained during weekend (Friday or Saturday night). These were calculated from 7-day 24-h accelerometer recordings.

Results

Of the study participants, 43% showed ≥ 60 minutes sleep duration standard deviation (SD), 51% experienced ≥ 60 minutes catch-up sleep, 20% showed ≥ 60 minutes midpoint of sleep SD, and 43% experienced ≥ 60 minutes social jetlag. American youth and young adults averaged greater sleep variability compared to other age groups. Non-Hispanic Blacks showed greater sleep variability in all parameters compared to other racial groups. There was a main effect of sex on sleep midpoint SD and social jetlag with males averaging slightly more than females.

Conclusion

Our study provides important observations on sleep irregularity parameters of residents of the United States by using objectively measured sleep patterns and will provide unique insights for personalized advice on sleep hygiene.

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.

Changes in sleep duration and sleep difficulties from adolescence to young adulthood and the risk of obesity: Bidirectional evidence in the GINIplus and LISA studies

OBJECTIVE

This study aimed to assess the association of changes in sleep behaviors from adolescence to young adulthood with the risk of overweight/obesity, and the reverse relationship.

METHODS

Data of 1978 participants was obtained from the 15- and 20-year follow-ups of the GINIplus and LISA birth cohorts. Insufficient sleep was defined as reported sleep duration <8 h for adolescents, <7 h for adults, and sleep difficulties as reported having sleeping difficulties. Logistic regression models were used to assess bidirectional associations of changes in insufficient sleep and sleep difficulties with overweight/obesity. The polygenic risk scores (PRS) for body mass index (BMI) was tested in a sub-sample (n = 918).

RESULTS

Compared with sufficient sleep in both adolescence and young adulthood, insufficient sleep only in young adulthood was associated with an increased risk of overweight/obesity (odds ratio = 1.85, 95%confidence interval = [1.27-2.69]). Compared with no sleep difficulties at both time-points, only persistent sleep difficulties was associated with a higher risk of overweight/obesity (2.15 [1.22-3.77]). The PRS for BMI was associated with overweight/obesity (1.41 [1.17-1.70]), but no significant gene-sleep interaction effect was observed. Reversely, only persistent overweight/obesity was associated with increased risks of insufficient sleep (1.81 [1.21-2.70]), and sleep difficulties (1.77 [1.18-2.66]), respectively.

CONCLUSIONS

Insufficient sleep only presented a cross-sectional association with overweight/obesity in young adulthood, while long-term sleep difficulties from adolescence to young adulthood was associated with young adult overweight/obesity. Reversely, long-term overweight/obesity from adolescence to young adulthood was associated with insufficient sleep and sleep difficulties in young adulthood.

Association between Sleep, Sedentary Time, Physical Activity, and Adiposity in Adolescents: A Prospective Observational Study

PURPOSE

This study aimed to examine the effects of substituting sedentary time with sleep or physical activity on adiposity in a longitudinal sample of adolescents.

METHODS

Adolescents (10-16 yr) were recruited for a prospective observational cohort. Parents and adolescents reported demographic characteristics and pubertal development. Accelerometry was used to measure sleep, physical activity, and sedentary time. Adiposity was quantified with imaging techniques. Isotemporal substitution modeling was conducted to examine the effect of substituting 10 min of sedentary time with sleep or differing intensities of physical activity. Results were stratified by sex and race and adjusted for covariates.

RESULTS

A total of 217 adolescents provided complete measures at both baseline and 2 yr later (58.1% White, 51.8% girls; 12.9 ± 1.9 yr at baseline). Sleep was negatively related to adiposity 2 yr later when considering other movement behaviors, but substituting baseline sedentary time with sleep was not related to future adiposity ( P > 0.05). In boys and non-White adolescents, substituting sedentary time with vigorous-intensity physical activity was related to lower adiposity 2 yr later ( P < 0.05). Substituting sedentary time for moderate- to vigorous-intensity physical activity was not associated with future adiposity.

CONCLUSIONS

Substituting sedentary time with vigorous-intensity physical activity was related to lower adiposity in later adolescence in certain groups. Opportunities to promote an adequate balance of sleep, sedentary time, and physical activity in all adolescents are encouraged for optimal development.