Pre-pandemic circadian phase predicts pandemic alcohol use among adolescents.

Later circadian timing during adolescence is linked to worse sleep, more severe depression and greater alcohol involvement, perhaps due to circadian misalignment imposed by early school schedules. School schedules shifted later during the COVID-19 pandemic, ostensibly reducing circadian misalignment and potentially mitigating problems with depression and alcohol. We used the pandemic as a natural experiment to test whether adolescent drinkers with later circadian timing showed improvements in sleep, depression and alcohol involvement. Participants were 42 adolescents reporting alcohol use. We assessed circadian phase via dim light melatonin onset prior to the pandemic, then conducted remote assessments of sleep, depressive symptoms and alcohol use during the pandemic. Mixed-effects models were used to test for pandemic effects, covarying for age, sex, time since baseline evaluation, and current school/work status. Adolescents with later circadian timing reported less sleep than other teens on school nights, both before and during the pandemic. Although school night sleep increased during the pandemic (F = 28.36, p < 0.001), those increases were not greater for individuals with later circadian timing. Individuals with later circadian timing reported larger increases in alcohol use than other teens during the pandemic (X2 = 36.03, p < 0.001). Depressive symptoms increased during the pandemic (X2 = 46.51, p < 0.001) but did not differ based on circadian timing. Consistent with prior reports, adolescents with later circadian timing obtained less sleep, and later school schedules facilitated increased sleep duration. Nonetheless, individuals with later circadian timing reported the sharpest increases in alcohol use, suggesting that circadian timing contributes to risk for alcohol use beyond the effects of insufficient sleep.

Activity patterns related to depression symptoms in stressed dementia caregivers.

OBJECTIVES: Self-reported activity restriction is an established correlate of depression in dementia caregivers (dCGs). It is plausible that the daily distribution of objectively measured activity is also altered in dCGs with depression symptoms; if so, such activity characteristics could provide a passively measurable marker of depression or specific times to target preventive interventions. We therefore investigated how levels of activity throughout the day differed in dCGs with and without depression symptoms, then tested whether any such differences predicted changes in symptoms 6 months later. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: We examined 56 dCGs (mean age = 71, standard deviation (SD) = 6.7; 68% female) and used clustering to identify subgroups which had distinct depression symptom levels, leveraging baseline Center for Epidemiologic Studies of Depression Scale-Revised Edition and Patient Health Questionnaire-9 (PHQ-9) measures, as well as a PHQ-9 score from 6 months later. Using wrist activity (mean recording length = 12.9 days, minimum = 6 days), we calculated average hourly activity levels and then assessed when activity levels relate to depression symptoms and changes in symptoms 6 months later. RESULTS: Clustering identified subgroups characterized by: (1) no/minimal symptoms (36%) and (2) depression symptoms (64%). After multiple comparison correction, the group of dCGs with depression symptoms was less active from 8 to 10 AM (Cohen's d ≤ -0.9). These morning activity levels predicted the degree of symptom change on the PHQ-9 6 months later (per SD unit ß = -0.8, 95% confidence interval: -1.6, -0.1, p = 0.03) independent of self-reported activity restriction and other key factors. CONCLUSIONS: These novel findings suggest that morning activity may protect dCGs from depression symptoms. Future studies should test whether helping dCGs get active in the morning influences the other features of depression in this population (i.e. insomnia, intrusive thoughts, and perceived activity restriction).

Self-reported sleep and circadian characteristics predict alcohol and cannabis use: A longitudinal analysis of the National Consortium on Alcohol and Neurodevelopment in Adolescence Study.

BACKGROUND: Growing evidence indicates that sleep characteristics predict future substance use and related problems. However, most prior studies assessed a limited range of sleep characteristics, studied a narrow age span, and included few follow-up assessments. Here, we used six annual assessments from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study, which spans adolescence and young adulthood with an accelerated longitudinal design, to examine whether multiple sleep characteristics in any year predict alcohol and cannabis use the following year. METHODS: The sample included 831 NCANDA participants (423 females; baseline age 12-21 years). Sleep variables included circadian preference, sleep quality, daytime sleepiness, the timing of midsleep (weekday/weekend), and sleep duration (weekday/weekend). Using generalized linear mixed models (logistic for cannabis; ordinal for binge severity), we tested whether each repeatedly measured sleep characteristic (years 0-4) predicted substance use (alcohol binge severity or cannabis use) the following year (years 1-5), covarying for age, sex, race, visit, parental education, and previous year's substance use. RESULTS: Greater eveningness, more daytime sleepiness, later weekend sleep timing, and shorter sleep duration (weekday/weekend) all predicted more severe alcohol binge drinking the following year. Only greater eveningness predicted a greater likelihood of any cannabis use the following year. Post-hoc stratified exploratory analyses indicated that some associations (e.g., greater eveningness and shorter weekend sleep duration) predicted binge severity only in female participants, and that middle/high school versus post-high school adolescents were more vulnerable to sleep-related risk for cannabis use. CONCLUSIONS: Our findings support the relevance of multiple sleep/circadian characteristics in the risk for future alcohol binge severity and cannabis use. Preliminary findings suggest that these risk factors vary based on developmental stage and sex. Results underscore a need for greater attention to sleep/circadian characteristics as potential risk factors for substance use in youth and may inform new avenues to prevention and intervention.

Physiological sleep measures predict time to 15-year mortality in community adults: Application of a novel machine learning framework.

Clarifying whether physiological sleep measures predict mortality could inform risk screening; however, such investigations should account for complex and potentially non-linear relationships among health risk factors. We aimed to establish the predictive utility of polysomnography (PSG)-assessed sleep measures for mortality using a novel permutation random forest (PRF) machine learning framework. Data collected from the years 1995 to present are from the Sleep Heart Health Study (SHHS; n = 5,734) and the Wisconsin Sleep Cohort Study (WSCS; n = 1,015), and include initial assessments of sleep and health, and up to 15 years of follow-up for all-cause mortality. We applied PRF models to quantify the predictive abilities of 24 measures grouped into five domains: PSG-assessed sleep (four measures), self-reported sleep (three), health (eight), health behaviours (four), and sociodemographic factors (five). A 10-fold repeated internal validation (WSCS and SHHS combined) and external validation (training in SHHS; testing in WSCS) were used to compute unbiased variable importance metrics and associated p values. We observed that health, sociodemographic factors, and PSG-assessed sleep domains predicted mortality using both external validation and repeated internal validation. The PSG-assessed sleep efficiency and the percentage of sleep time with oxygen saturation <90% were among the most predictive individual measures. Multivariable Cox regression also revealed the PSG-assessed sleep domain to be predictive, with very low sleep efficiency and high hypoxaemia conferring the highest risk. These findings, coupled with the emergence of new low-burden technologies for objectively assessing sleep and overnight oxygen saturation, suggest that consideration of physiological sleep measures may improve risk screening.

Profiles of Accelerometry-Derived Physical Activity Are Related to Perceived Physical Fatigability in Older Adults.

Physical activity (PA) is associated with greater fatigability in older adults; little is known about magnitude, shape, timing and variability of the entire 24-h rest-activity rhythm (RAR) associated with fatigability. We identified which features of the 24-h RAR pattern were independently and jointly associated with greater perceived physical fatigability (Pittsburgh Fatigability Scale, PFS, 0-50) in older adults (n = 181, 71.3 ± 6.7 years). RARs were characterized using anti-logistic extended cosine models and 4-h intervals of PA means and standard deviations across days. A K-means clustering algorithm approach identified four profiles of RAR features: "Less Active/Robust", "Earlier Risers", "More Active/Robust" and "Later RAR". Quantile regression tested associations of each RAR feature/profile on median PFS adjusted for age, sex, race, body mass index and depression symptomatology. Later rise times (up mesor; ß = 1.38, p = 0.01) and timing of midpoint of activity (acrophase; ß = 1.29, p = 0.01) were associated with higher PFS scores. Lower PA between 4 a.m. and 8 a.m. was associated with higher PFS scores (ß = -4.50, p = 0.03). "Less Active/Robust" (ß = 6.14, p = 0.01) and "Later RAR" (ß = 3.53, p = 0.01) patterns were associated with higher PFS scores compared to "Earlier Risers". Greater physical fatigability in older adults was associated with dampened, more variable, and later RARs. This work can guide development of interventions aimed at modifying RARs to reduce fatigability in older adults.

An Optimal Self-Report Physical Activity Measure for Older Adults: Does Physical Function Matter?

The authors compared two self-report measures of physical activity, the Physical Activity Scale for the Elderly (PASE) and the Community Healthy Activities Model Program for Seniors (CHAMPS), against the device-derived SenseWear Armband (SWA), to identify a recommended self-report tool to measure physical activity in older adults across physical function levels. A total of 65 community-dwelling older adults completed the PASE, CHAMPS, and seven full days of SWA wear. The authors measured physical function using the modified short physical performance battery (SPPB) and a usual-paced 6-m walk. Age- and sex-adjusted Spearman correlations showed that CHAMPS and SWA were correlated in higher functioning participants (SPPB: ρ = .33, p = .03; gait speed: ρ = .40, p = .006) and also correlated in lower functioning participants for SPPB (ρ = .70, p = .003) only. PASE and SWA were not significantly correlated across physical function. When an objective measure of physical activity is not practical, the CHAMPS questionnaire appears to capture physical activity for older adults across physical function levels.

Saturated fatty acid concentrations are predictive of insulin sensitivity and beta cell compensation in dogs.

Chronic feeding of a high fat diet (HFD) in preclinical species induces broad metabolic dysfunction characterized by body weight gain, hyperinsulinemia, dyslipidemia and impaired insulin sensitivity. The plasma lipidome is not well characterized in dogs with HFD-induced metabolic dysfunction. We therefore aimed to describe the alterations that occur in the plasma lipid composition of dogs that are fed a HFD and examine the association of these changes with the clinical signs of metabolic dysfunction. Dogs were fed a normal diet (ND) or HFD for 12 weeks. Insulin sensitivity (SI) and beta cell compensation (AIRG) were assessed through an intravenous glucose tolerance test (IVGTT) and serum biochemistry was analyzed before the introduction of HFD and again after 12 weeks of continued ND or HFD feeding. Plasma lipidomics were conducted prior to the introduction of HFD and again at week 8 in both ND and HFD-fed dogs. 12 weeks of HFD feeding resulted in impaired insulin sensitivity and increased beta cell compensation measured by SI (ND mean: 11.5 [mU/l]-1 min-1, HFD mean: 4.7 [mU/l]-1 min-1) and AIRG (ND mean: 167.0 [mU/l]min, HFD mean: 260.2 [mU/l]min), respectively, compared to dogs fed ND over the same duration. Chronic HFD feeding increased concentrations of plasma lipid species and deleterious fatty acids compared to dogs fed a ND. Saturated fatty acid (SFA) concentrations were significantly associated with fasting insulin (R2 = 0.29), SI (R2 = 0.49) and AIRG (R2 = 0.37) in all dogs after 12 weeks, irrespective of diet. Our results demonstrate that chronic HFD feeding leads to significant changes in plasma lipid composition and fatty acid concentrations associated with metabolic dysfunction. High SFA concentrations may be predictive of deteriorated insulin sensitivity in dogs.

Feeding dogs a high-fat diet induces metabolic changes similar to natural aging, including dyslipidemia, hyperinsulinemia, and peripheral insulin resistance.

OBJECTIVE: The goal of this study was to characterize changes induced by a high-fat diet in body composition, insulin levels and sensitivity, blood lipids, and other key biomarkers also associated with the metabolic dysfunction that occurs with natural aging. ANIMALS: 24 male Beagle dogs, 3 to 7 years of age, of mixed castration status. METHODS: Dogs were randomly assigned to continue twice daily feeding of the commercial adult maintenance diet (n = 12, including 2 intact) that they were previously fed or to a high-fat diet (12, including 2 intact) for 17 weeks between December 1, 2021, and April 28, 2022. Assessments included body composition (weight, body condition score, and adipose mass determined by deuterium enrichment), clinical chemistries, plasma fatty acid quantification, oral glucose tolerance test, and histology of subcutaneous and visceral adipose biopsy samples. RESULTS: The high-fat diet led to increased body weight, body condition score, fat mass and adipocyte size, hyperinsulinemia and peripheral insulin resistance, and elevations in serum lipids, including cholesterol, triglycerides, and several species of free fatty acids. Leptin levels increased in dogs fed a high-fat diet but not in control dogs. There were no significant changes in routine clinical chemistry values in either group. CLINICAL RELEVANCE: Feeding a high-fat diet for 17 weeks led to potentially deleterious changes in metabolism similar to those seen in natural aging in dogs, including hyperinsulinemia, insulin resistance, and dyslipidemia. A high-fat diet model may provide insights into the similar metabolic dysfunction that occurs during natural aging.

Body weight, gonadectomy, and other risk factors for diagnosis of osteoarthritis in companion dogs.

Objective: The aim of this study is to evaluate age, sex, body weight, breed, neuter status, and age at neutering as risk factors for diagnosis of osteoarthritis in companion dogs. Animals: Dogs seen as patients at Banfield Pet Hospital in the United States from 1998 to 2019 with a date of death in 2019. The final cohort consisted of 131,140 dogs. Methods: In this retrospective cohort study, Cox proportional hazard models were used to test for associations between osteoarthritis incidence and age at baseline, sex, maximum body weight, maximum body condition score, neuter status, and age at neutering. The same model was used to test these associations in 12 representative breeds, chosen based on breed weight and sample size. Results: Older age, higher adult body weight, gonadectomy, and younger age at gonadectomy were significantly associated with higher risks of osteoarthritis in the total cohort and in all 12 breeds evaluated. Higher body condition scores and sex were also significantly associated with osteoarthritis but with minimal effect sizes in the overall cohort, and these risk factors were not consistently significant in all breeds tested. Clinical relevance: These results will assist veterinarians in identifying dogs at higher risk for osteoarthritis and applying appropriate diagnostic, preventative, and treatment interventions. An understanding of potentially modifiable risk factors, such as body condition and neutering, will support evidence-based discussions with dog owners about risk management in individual patients.

Evaluating instruments for assessing healthspan: a multi-center cross-sectional study on health-related quality of life (HRQL) and frailty in the companion dog.

Developing valid tools that assess key determinants of canine healthspan such as frailty and health-related quality of life (HRQL) is essential to characterizing and understanding aging in dogs. Additionally, because the companion dog is an excellent translational model for humans, such tools can be applied to evaluate gerotherapeutics and investigate mechanisms underlying longevity in both dogs and humans. In this multi-center, cross-sectional study, we investigated the use of a clinical questionnaire (Canine Frailty Index; CFI; Banzato et al., 2019) to assess frailty and an owner assessment tool (VetMetrica HRQL) to evaluate HRQL in 451 adult companion dogs. Results demonstrated validity of the tools by confirming expectations that frailty score increases and HRQL scores deteriorate with age. CFI scores were significantly higher (higher frailty) and HRQL scores significantly lower (worse HRQL) in old dogs (≥ 7 years of age) compared to young dogs (≥ 2 and < 6 years of age). Body size (small < 11.3 kg (25 lbs) or large > 22.7 kg (50 lbs)) was not associated with CFI or total HRQL score. However, older, larger dogs showed faster age-related decline in HRQL scores specific to owner-reported activity and comfort. Findings suggest that the clinician-assessed CFI and owner-reported VetMetrica HRQL are useful tools to evaluate two determinants of healthspan in dogs: the accumulation of frailty and the progressive decline in quality of life. Establishing tools that operationalize the assessment of canine healthspan is critical for the advancement of geroscience and the development of gerotherapeutics that benefit both human and veterinary medicine. Graphical summary of the design, results, and conclusions of the study.

Circadian preference is associated with multiple domains of trait and state level impulsivity.

Impulsivity is a multidimensional construct with well-documented risk for substance use problems at both the trait- and state levels. A circadian preference towards eveningness has been linked to trait-level, global impulsivity, but whether this association holds true across multiple dimensions of impulsivity and whether actual sleep timing shows parallel associations with impulsivity remain unclear. Here, we extend existing literature by investigating whether eveningness is associated with multiple facets of both trait- and state-level impulsivity. We also examined these associations utilizing daily measures of sleep timing and duration and explored whether they differed by sex and/or race. All participants were moderate-to-heavy social drinkers aged 21-35. Primary analyses included 78 participants (100% White male participants: Sample 1) with circadian preference data (Composite Scale of Morningness: CSM) and sleep timing (midsleep) and duration assessed via daily self-report over 10 days. Five facets of impulsivity were assessed via the UPPS-P, both at baseline (full scale; trait-level) and up to 6 times per day over 10 days (reduced scale; state-level). Linear regression and mixed-effects models were used to examine between- and within-person associations of impulsivity with measures of circadian preference, timing, and duration, accounting for covariates. Exploratory analyses combined Sample 1 with an additional more diverse sample (Sample 2), resulting in a total of 182 participants (29.1% self-identified as Black, 29.7% as female) with daily self-report sleep timing and duration only (no circadian preference). Primary between-person models found that eveningness was associated with multiple facets of impulsivity, at trait (lack of perseverance) and state levels (negative and positive urgency, lack of perseverance, and lack of premeditation), while average midsleep and duration were generally unrelated to impulsivity. Primary within-person models largely paralleled the between-person findings. Exploratory analyses in the larger combined Samples 1 and 2 (without circadian preference) found that later midsleep timing was associated with greater mean state-level impulsivity across multiple facets, associations that may differ by race and sex. In a sample of White male participants, circadian preference for eveningness was strongly associated with multiple facets of impulsivity, at both trait- and state-levels, which may contribute to risk for substance use. Preliminary findings suggest sex and race differences in sleep-impulsivity associations, but future research with objective sleep/circadian measures in larger, more diverse samples will be important to clarify implications for sleep-focused prevention and/or treatment of substance use.

Preliminary Evidence That Circadian Alignment Predicts Neural Response to Monetary Reward in Late Adolescent Drinkers.

BACKGROUND: Robust evidence links sleep and circadian rhythm disturbances to alcohol use and alcohol-related problems, with a growing literature implicating reward-related mechanisms. However, the extant literature has been limited by cross-sectional designs, self-report or behavioral proxies for circadian timing, and samples without substantive alcohol use. Here, we employed objective measures of sleep and circadian rhythms, and an intensive prospective design, to assess whether circadian alignment predicts the neural response to reward in a sample of late adolescents reporting regular alcohol use. METHODS: Participants included 31 late adolescents (18-22 y/o; 19 female participants) reporting weekly alcohol use. Participants completed a 14-day protocol including pre- and post-weekend (Thursday and Sunday) circadian phase assessments via the dim light melatonin onset (DLMO), in counterbalanced order. Sleep-wake timing was assessed via actigraphy. Circadian alignment was operationalized as the DLMO-midsleep interval; secondary analyses considered social jet lag based on weekday-weekend differences in midsleep or DLMO. Neural response to reward (anticipation and outcome) was assessed via a monetary reward fMRI task (Friday and Monday scans). Alcohol use was assessed at baseline and via ecological momentary assessment. Mean BOLD signal was extracted from two regions-of-interest (striatum and medial prefrontal cortex, mPFC) for analyses in regression models, accounting for age, sex, racial identity, and scan order. RESULTS: In primary analyses, shorter DLMO-midsleep intervals (i.e., greater misalignment) on Thursday predicted lower striatal and mPFC responses to anticipated reward, but not reward outcome, on Friday. Lower neural (striatum and mPFC) responses to anticipated reward on Friday correlated with more binge-drinking episodes at baseline, but were not associated with alcohol use in the post-scan weekend. In secondary analyses, greater social jet lag (particularly larger weekend delays in midsleep or DLMO) was associated with lower neural responses to reward anticipation on Monday. CONCLUSION: Findings provide preliminary evidence of proximal associations between objectively determined circadian alignment and the neural response to anticipated monetary reward, which is linked in turn to patterns of problematic drinking. Replication in a larger sample and experimental designs will be important next steps to determining the extent to which circadian misalignment influences risk for alcohol involvement via alterations in reward function.

Associations between physiological and self-reported indices of emotion dysregulation across varying levels of alcohol use among individuals with and without borderline personality disorder.

Emotional functioning can be assessed across multiple levels of analysis (e.g., subjective, physiological). The degree of concordance/discordance across such indices may mark psychopathology risk. The current study assessed associations between physiological and subjective indices of emotional responding among drinkers, with (n = 39) and without (n = 42) borderline personality disorder. Subjective changes in affect were assessed by calculating difference scores on the Positive and Negative Affective Schedule, administered before and following a lab-based stress task. Physiological dysregulation was indexed by respiratory sinus arrhythmia (RSA) reactivity. We created Discordance Index scores to examine the direction and magnitude of misalignment. More frequent alcohol use was associated with greater discordance between RSA and positive affect changes (ß = -0.07, p-value = 0.009). Findings were confirmed with a response surface modeling analysis. Results highlight that individuals with greater discordance between indices of emotional responding may be at elevated risk for frequent alcohol use.

Measuring Variability in Rest-Activity Rhythms from Actigraphy with Application to Characterizing Symptoms of Depression.

The twenty-four hour sleep-wake pattern known as the rest-activity rhythm (RAR) is associated with many aspects of health and well-being. Researchers have utilized a number of interpretable, person-specific RAR measures that can be estimated from actigraphy. Actigraphs are wearable devices that dynamically record acceleration and provide indirect measures of physical activity over time. One class of useful RAR measures are those that quantify variability around a mean circadian pattern. However, current parametric and nonparametric RAR measures used by applied researchers can only quantify variability from a limited or undefined number of rhythmic sources. The primary goal of this article is to consider a new measure of RAR variability: the log-power spectrum of stochastic error around a circadian mean. This functional measure quantifies the relative contributions of variability about a circadian mean from all possibly frequencies, including weekly, daily, and high-frequency sources of variation. It can be estimated through a two-stage procedure that smooths the log-periodogram of residuals after estimating a circadian mean. The development of this measure was motivated by a study of depression in older adults and revealed that slow, rhythmic variations in activity from a circadian pattern are correlated with depression symptoms.