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Objective: Although traumatic brain injury (TBI) and posttraumatic epilepsy (PTE) are common, there are no prospective models quantifying individual epilepsy risk after moderate-to-severe TBI (msTBI). We generated parsimonious prediction models to quantify individual epilepsy risk between acute inpatient rehabilitation for individuals 2 years after msTBI., Methods: We used data from 6089 prospectively enrolled participants (≥16 years) in the TBI Model Systems National Database. Of these, 4126 individuals had complete seizure data collected over a 2-year period post-injury. We performed a case-complete analysis to generate multiple prediction models using least absolute shrinkage and selection operator logistic regression. Baseline predictors were used to assess 2-year seizure risk (Model 1). Then a 2-year seizure risk was assessed excluding the acute care variables (Model 2). In addition, we generated prognostic models predicting new/recurrent seizures during Year 2 post-msTBI (Model 3) and predicting new seizures only during Year 2 (Model 4). We assessed model sensitivity when keeping specificity ≥.60, area under the receiver-operating characteristic curve (AUROC), and AUROC model performance through 5-fold cross-validation (CV)., Results: Model 1 (73.8% men, 44.1 ± 19.7 years, 76.1% moderate TBI) had a model sensitivity = 76.00% and average AUROC = .73 ± .02 in 5-fold CV. Model 2 had a model sensitivity = 72.16% and average AUROC = .70 ± .02 in 5-fold CV. Model 3 had a sensitivity = 86.63% and average AUROC = .84 ± .03 in 5-fold CV. Model 4 had a sensitivity = 73.68% and average AUROC = .67 ± .03 in 5-fold CV. Cranial surgeries, acute care seizures, intracranial fragments, and traumatic hemorrhages were consistent predictors across all models. Demographic and mental health variables contributed to some models. Simulated, clinical examples model individual PTE predictions., Significance: Using information available, acute-care, and year-1 post-injury data, parsimonious quantitative epilepsy prediction models following msTBI may facilitate timely evidence-based PTE prognostication within a 2-year period. We developed interactive web-based tools for testing prediction model external validity among independent cohorts. Individualized PTE risk may inform clinical trial development/design and clinical decision support tools for this population., (© 2024 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Objectives: Many sleep-wake behaviors have been associated with cognition. We examined a panel of sleep-wake/activity characteristics to determine which are most robustly related to having low cognitive performance in midlife. Secondarily, we evaluate the predictive utility of sleep-wake measures to screen for low cognitive performance., Methods: The outcome was low cognitive performance defined as being >1 standard deviation below average age/sex/education internally normalized composite cognitive performance levels assessed in the Hispanic Community Health Study/Study of Latinos. Analyses included 1006 individuals who had sufficient sleep-wake measurements about 2years later (mean age=54.9, standard deviation= 5.1; 68.82% female). We evaluated associations of 31 sleep-wake variables with low cognitive performance using separate logistic regressions., Results: In individual models, the strongest sleep-wake correlates of low cognitive performance were measures of weaker and unstable 24-hour rhythms; greater 24-hour fragmentation; longer time-in-bed; and lower rhythm amplitude. One standard deviation worse on these sleep-wake factors was associated with ∼20%-30% greater odds of having low cognitive performance. In an internally cross-validated prediction model, the independent correlates of low cognitive performance were: lower Sleep Regularity Index scores; lower pseudo-F statistics (modellability of 24-hour rhythms); lower activity rhythm amplitude; and greater time in bed. Area under the curve was low/moderate (64%) indicating poor predictive utility., Conclusion: The strongest sleep-wake behavioral correlates of low cognitive performance were measures of longer time-in-bed and irregular/weak rhythms. These sleep-wake assessments were not useful to identify previous low cognitive performance. Given their potential modifiability, experimental trials could test if targeting midlife time-in-bed and/or irregular rhythms influences cognition., (Copyright © 2024 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging data play an important role in the advancement of science. Imaging data that measure brain function are usually multivariate high-density longitudinal data and are heterogeneous across both imaging sources and subjects, which lead to various statistical and computational challenges. In this article, we propose a group-based method to cluster a collection of multivariate high-density longitudinal data via a Bayesian mixture of smoothing splines. Our method assumes each multivariate high-density longitudinal trajectory is a mixture of multiple components with different mixing weights. Time-independent covariates are assumed to be associated with the mixture components and are incorporated via logistic weights of a mixture-of-experts model. We formulate this approach under a fully Bayesian framework using Gibbs sampling where the number of components is selected based on a deviance information criterion. The proposed method is compared to existing methods via simulation studies and is applied to a study on functional near-infrared spectroscopy, which aims to understand infant emotional reactivity and recovery from stress. The results reveal distinct patterns of brain activity, as well as associations between these patterns and selected covariates., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. [br]For permissions, please e-mail: journals.permissions@oup.com.)

Low power is a problem in many fields, as underpowered studies that find a statistically significant result will exaggerate the magnitude of the observed effect size. We quantified the statistical power and magnitude error of studies of epilepsy surgery outcomes. The median power across all studies was 14%. Studies with a median sample size or less (n<=56) and a statistically significant result exaggerated the true effect size by a factor of 5.4 (median odds ratio 9.3 vs. median true odds ratio 1.7), while the Bayesian estimate of the odds ratio only exaggerated the true effect size by a factor of 1.6 (2.7 vs. 1.7). We conclude that Bayesian estimation of odds ratio attenuates the exaggeration of significant effect sizes in underpowered studies. This approach could help improve patient counseling about the chance of seizure freedom after epilepsy surgery., Competing Interests: DISCLOSURE OF CONFLICTS OF INTEREST N.P.P. has served as a paid consultant for DIXI Medical USA, who manufactures products used in the workup for epilepsy surgery. The terms of this arrangement have been reviewed and approved by Emory University in accordance with its conflict-of-interest policies. A.S.D, V.R. and R.T.K. have no conflicts of interest to disclose.

Study Objectives: To help prioritize target/groups for experimental intervention studies, we characterized cross-sectional associations between 24-hour sleep-wake measures and depression symptoms, and evaluated if similar sleep-wake-depression relationships existed in people with and without higher insomnia severity., Methods: Participants had ≥3 days of actigraphy data (n = 1884; mean age = 68.6/SD = 9.1; 54.1% female). We extracted 18 sleep, activity, timing, rhythmicity, and fragmentation measures from actigraphy. We used individual and multivariable regressions with the outcome of clinically significant depression symptoms (Center for Epidemiologic Studies Depression Scale ≥ 16). We conducted sensitivity analyses in people with higher insomnia severity (top quartile of the Women's Health Initiative Insomnia Rating Scale total score)., Results: From separate models in the overall sample, the odds of having depression symptoms were higher with: later timing (e.g. activity onset time odds ratio [OR]/1 SD = 1.32; 95% confidence interval [CI]: 1.16 to 1.50), lower rhythmicity (e.g. pseudo-F OR/1 SD = 0.75; 95% CI: 0.66 to 0.85), less activity (e.g. amplitude OR/1 SD = 0.83; 95% CI: 0.72 to 0.95), and worse insomnia (OR/1 SD = 1.48, 95% CI: 1.31 to 1.68). In multivariable models conducted among people with lower insomnia severity, later timing, lower rhythmicity, and higher insomnia severity were independent correlates of depression. In people with higher insomnia symptom severity, measures of later timing were most strongly associated with depression symptoms., Conclusions: These correlative observations suggest that experimental studies are warranted to test if: broadly promoting 24-hour sleep-wake functioning reduces depression even in people without severe insomnia, and if advancing timing leads to depression symptom reductions in people with insomnia., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Perform a secondary analysis examining the efficacy of the Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C) for depression symptom responses, and explore changes in potential target mechanisms., Design: Secondary analysis of a randomized controlled trial with convenience age subsamples (younger (20-49 year; n = 52) versus and older (50-71 years; n = 35))., Setting: Community mental health clinics., Participants: Eighty-seven adults with serious mental illness., Intervention: TranS-C versus treatment as usual (TAU)., Measurements: Outcomes were depression symptoms (Quick Inventory of Depression Symptoms), insomnia symptoms (Insomnia Severity Index), and objective sleep-wake rhythm measures (interdaily stability and relative amplitude)., Results: Depression response rates (≥50% symptom reductions) were higher in the TranS-C (35.0%) than the TAU (8.8%) group 6-months postintervention (χ 2 = 10.3, p = 0.001). There was a medium effect of TranS-C versus TAU on depression symptoms 6-months postintervention (Cohen's d = -0.40, 95% confidence interval (CI): -0.81, 0.01). In both age groups, there were large treatment effects on insomnia symptoms post-treatment (Cohen's d >0.90). In the older subsample, there were additionally medium treatment effects on post-treatment interdaily stability (Cohen's d = 0.60, 95% CI: -0.11, 1.61). Post-treatment reductions in insomnia symptoms correlated with depression symptom reduction 6-months later in the younger subsample (Spearman rho = 0.59, n = 20, p = 0.008). In older adults, postintervention increases in interdaily stability correlated with depression symptom reductions 6-months later (Spearman rho = -0.52, n = 15, p = 0.049)., Conclusion: Confirmatory trials are needed, given the low age-specific sample sizes here, to determine if TranS -C's produces durable depression responses by increasing sleep-wake rhythm stability in older adults and improving insomnia symptoms in younger adults., Brief Article Summary: The authors evaluated preliminary efficacy of a behavioral intervention that targets sleep/sleep-wake rhythms, the Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C), for depression symptoms in people with serious mental illness. TranS-C was associated with higher depression response rates than treatment as usual 6-months postintervention. The degree of depression symptom response 6-months later was related to the degree of treatment phase improvements in interdaily stability (in older adults) and reduction in insomnia severity (in younger adults). A pragmatic nonpharmacologic intervention, the Transdiagnostic Intervention for Sleep and Circadian Dysfunction, has preliminary efficacy for improving sleep-wake factors and depression symptoms., Competing Interests: DISCLOSURES This analysis was supported in part byR21MH120511. The trial was supported byR01MH120147andR01MH105513. Dr. Allison G. Harvey has received research support from theNational Institutes of Health, theNational Institute of Child Health and Human Development, and book royalties fromAmerican Psychological Association, Guilford Press, andOxford University Press. Dr. McCall receives payments as a scientific advisor to Idorsia and Carelon, and royalty payments fromWolters Kluwer. He receives research support fromThe George Institute., (Copyright © 2023 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Objective: To identify 1) complicated grief symptom clusters among acutely-bereaved older adults who have lost a spouse to COVID-19 and 2) if spousal death due to COVID-19 increased risk of developing probable PGD METHODS: Eighty adults participating in a randomized controlled trial for depression prevention (mean age [± SD] = 70.4 [6.6]) completed the Inventory of Complicated Grief, every 3 months over a maximum of 15 months. Twenty-four percent (n = 19) of participants lost a spouse to COVID-19; 76% (n = 61) lost a spouse to other causes of death. Adjusted linear regression examined the associations between COVID-19 bereavement and six symptom clusters: yearning and preoccupation, anger and bitterness, shock and disbelief, estrangement from others, hallucinations, and behavior change., Results: Compared to the non-COVID-19 group, the COVID-19 bereaved group reported greater shock and disbelief, hallucinations of the deceased, and estrangement from others. COVID-19 death was also associated with higher risk for probable prolonged grief disorder (PGD) at 12 months (odds ratio = 4.38, p = 0.027)., Conclusions: Older adults who have lost a spouse to COVID-19 present with specific symptoms of distress and may eventually require clinical care for PGD., (Copyright © 2023 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Animal-based research is essential to the study of sepsis pathophysiology, diagnostics, and therapeutics. However, animal models of sepsis are often associated with high mortality because of the difficulty in predicting imminent death based on premortem assessment of the animals. The use of validated visual scoring would allow researchers to systematically identify humane endpoints but visual approaches require high interobserver agreement for accurate results. The objective of this study was to establish a scoring system for mice undergoing cecal ligation and puncture (CLP)-induced sepsis based on 3 visual parameters: respiratory status, activity and response to stimulus (ASR), and eye appearance, with scores ranging from 0 to 3. In the first study, we evaluated interobserver agreement. Veterinary and investigative staff assessed 283 mice with CLP and had substantial to near-perfect agreement for all 3 parameters as evaluated using weighted Cohen κ statistic. The second study assessed the ability of the scoring system and temperature to predict death. The scoring system and subcutaneous transpond- ers were used to monitor C57BL/6J mice ( n = 80, male and female) until death or for 7 days after CLP. Results showed that the scoring system discriminates between surviving ( n = 26) and nonsurviving ( n = 54) septic mice. The scoring system was accurate in predicting death, with an AUC of 0.8997. The sensitivity and specificity of the ASR parameter were 96% and 92%, respectively, and for the eye parameter were 94% and 73%. A sum of the ASR and eye scores that was 5 or more was also predictive of death. Temperature was a quantitative predictor, with sensitivity and specificity of 93% and 92%, respectively. This scoring system refines the CLP model by allowing identification of humane endpoints and avoidance of spontaneous death.

Shift workers experience poor sleep and dysregulated cardiac autonomic function during sleep. However, it is unknown if this dysregulation persists into retirement, potentially accelerating the age-associated risk for adverse cardiovascular outcomes. Using sleep deprivation as a physiological challenge to cardiovascular autonomic function, we compared heart rate (HR) and high-frequency heart rate variability (HF-HRV) during baseline and recovery sleep following sleep deprivation between retired night shift and day workers. Participants were retired night shift (N = 33) and day workers (N = 37) equated on age (mean [standard deviation] = 68.0 [5.6] years), sex (47% female), race/ethnicity (86% White), and body mass index. Participants completed a 60-h lab protocol including one night of baseline polysomnography-monitored sleep, followed by 36 h of sleep deprivation and one night of recovery sleep. Continuously recorded HR was used to calculate HF-HRV. Linear mixed models compared HR and HF-HRV during non-rapid eye movement (NREM) and REM sleep between groups during baseline and recovery nights. Groups did not differ on HR or HF-HRV during NREM or REM sleep (ps > .05) and did not show differential responses to sleep deprivation. In the full sample, HR increased and HF-HRV decreased from baseline to recovery during NREM (ps < .05) and REM (ps < .01). Both groups exhibited cardiovascular autonomic changes during recovery sleep following 36 h of sleep deprivation. Sleep deprivation appears to induce cardiovascular autonomic changes that persist into recovery sleep in older adults, regardless of shift work history., (© 2023 Society for Psychophysiological Research.)

Study Objectives: Shift work is associated with compromised cognitive function, and with chronic exposure, may place shift workers at elevated risk for dementia. However, evidence of cognitive impairment among former night shift workers is mixed, possibly due to inconsistencies regarding retirement status, work history classification, and cognitive assessments. To address these limitations, this study compared neurocognitive function between retired night shift workers and retired day workers using a well-characterized sample and a rigorous neurocognitive test battery., Methods: Participants (N = 61; mean age: 67.9 ± 4.7 years; 61% females; 13% non-white) were 31 retired day workers and 30 retired night shift workers equated on age, sex, race/ethnicity, premorbid IQ, years retired, and diary-assessed habitual sleep characteristics. Participants completed a neurocognitive battery assessing six cognitive domains (language, visuospatial ability, attention, immediate and delayed memory, executive function) and self-reported cognitive function. Linear regression models compared groups on individual cognitive domains, adjusting for age, sex, race/ethnicity, education level, and habitual sleep quality., Results: Retired night shift workers scored lower than retired day workers on attention (B = -0.38, 95% CI [-0.75, -0.02], p = .040) and executive function (B = -0.55, 95% CI [-0.92, -0.17], p = .005). In post hoc analyses, attention and executive function were unrelated to diary-assessed habitual sleep characteristics (disruption, timing, and irregularity) in retired night shift workers., Conclusions: The observed cognitive weaknesses in retired night shift workers may suggest increased risk for future dementia. Retired night shift workers should be followed to determine whether observed weaknesses progress., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics., Methods: Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) ( n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report., Results: After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed., Conclusions: There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.

Nocturia (waking to void) is prevalent among older adults. Disruption of the well-described circadian rhythm in urine production with higher nighttime urine output is its most common cause. In young adults, their circadian rhythm is modulated by the 24-h secretory pattern of hormones that regulate salt and water excretion, including antidiuretic hormone (ADH), renin, angiotensin, aldosterone, and atrial natriuretic peptide (ANP). The pattern of hormone secretion is less clear in older adults. We investigated the effect of sleep on the 24-h secretion of these hormones in healthy older adults. Thirteen participants aged ≥65 yr old underwent two 24-h protocols at a clinical research center 6 wk apart. The first used a habitual wake-sleep protocol, and the second used a constant routine protocol that removed the influence of sleep, posture, and diet. To assess hormonal rhythms, plasma was collected at 8:00 am, 12:00 pm, 4:00 pm, and every 30 min from 7:00 pm to 7:00 am. A mixed-effects regression model was used to compare subject-specific and mean trajectories of hormone secretion under the two conditions. ADH, aldosterone, and ANP showed a diurnal rhythm that peaked during sleep in the wake-sleep protocol. These nighttime elevations were significantly attenuated within subjects during the constant routine. We conclude that sleep has a masking effect on circadian rhythm amplitude of ADH, aldosterone, and ANP: the amplitude of each is increased in the presence of sleep and reduced in the absence of sleep. Disrupted sleep could potentially alter nighttime urine output in healthy older adults via this mechanism. NEW & NOTEWORTHY Nocturia (waking to void) is the most common cause of sleep interruption among older adults, and increased nighttime urine production is its primary etiology. We showed that in healthy older adults sleep affects the 24-h secretory rhythm of hormones that regulate salt-water balance, which potentially alters nighttime urine output. Further studies are needed to elucidate the impact of chronic insomnia on the secretory rhythms of these hormones.

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 β = -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).

Background: Consistent evidence from retrospective reports and case registry studies indicates that a history of depression is a major risk factor for depression in the peripartum period. However, longitudinal studies with racially and socioeconomically diverse samples of young mothers are lacking, and little is known about developmental patterns of depression across the lifespan that can inform preventive interventions., Methods: Young primiparous mothers ( n = 399, 13-25 years, 81% Black) were recruited from a population-based prospective study that began in childhood. Women reported on depression symptoms for at least 3 years prior to their pregnancy, during pregnancy, and at 4 months postpartum. Linear regression models were used to estimate change in pre-pregnancy depression severity and to evaluate associations between patterns of lifetime history and postpartum depression symptoms., Results: Results revealed high levels of continuity in depression from pregnancy to postpartum, and across multiple years pre-pregnancy to postpartum. Overall, depression severity leading up to pregnancy decreased over time, but patterns of worsening or improving symptoms were not associated with depression severity in the postpartum period. Instead, area under the pre-pregnancy trajectory curve, representing cumulative lifetime depression burden, was uniquely associated with postpartum depression after adjusting for prenatal depression severity., Conclusions: Depression in the postpartum period should be considered within a lifespan perspective of risk that accumulates before conception. Clinical screening and early interventions are needed in adolescence and young adulthood to prevent the onset and persistence of depressive symptoms that could have long-term implications for peripartum health.

Many studies collect functional data from multiple subjects that have both multilevel and multivariate structures. An example of such data comes from popular neuroscience experiments where participants' brain activity is recorded using modalities such as electroencephalography and summarized as power within multiple time-varying frequency bands within multiple electrodes, or brain regions. Summarizing the joint variation across multiple frequency bands for both whole-brain variability between subjects, as well as location-variation within subjects, can help to explain neural reactions to stimuli. This article introduces a novel approach to conducting interpretable principal components analysis on multilevel multivariate functional data that decomposes total variation into subject-level and replicate-within-subject-level (i.e., electrode-level) variation and provides interpretable components that can be both sparse among variates (e.g., frequency bands) and have localized support over time within each frequency band. Smoothness is achieved through a roughness penalty, while sparsity and localization of components are achieved by solving an innovative rank-one based convex optimization problem with block Frobenius and matrix $L&#95;1$-norm-based penalties. The method is used to analyze data from a study to better understand reactions to emotional information in individuals with histories of trauma and the symptom of dissociation, revealing new neurophysiological insights into how subject- and electrode-level brain activity are associated with these phenomena. Supplementary materials for this article are available online., (© The Author 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Coronary heart disease is a leading cause of death and disability. Although psychological stress has been identified as an important potential contributor, mechanisms by which stress increases risk of heart disease and mortality are not fully understood. The purpose of this study was to assess mechanisms by which stress acts through the brain and heart to confer increased CHD risk., Methods: Coronary Heart Disease patients (N=10) underwent cardiac imaging with [Tc-99m] sestamibi single photon emission tomography at rest and during a public speaking mental stress task. Patients returned for a second day and underwent positron emission tomography imaging of the brain, heart, bone marrow, aorta (indicating inflammation) and subcutaneous adipose tissue, after injection of [ 18 F]2-fluoro-2-deoxyglucose for assessment of glucose uptake followed mental stress. Patients with (N=4) and without (N=6) mental stress-induced myocardial ischemia were compared for glucose uptake in brain, heart, adipose tissue and aorta with mental stress., Results: Patients with mental stress-induced ischemia showed a pattern of increased uptake in the heart, medial prefrontal cortex, and adipose tissue with stress. In the heart disease group as a whole, activity increase with stress in the medial prefrontal brain and amygdala correlated with stress-induced increases in spleen (r=0.69, p=0.038; and r=0.69, p=0.04 respectfully). Stress-induced frontal lobe increased uptake correlated with stress-induced aorta uptake (r=0.71, p=0.016). Activity in insula and medial prefrontal cortex was correlated with post-stress activity in bone marrow and adipose tissue. Activity in other brain areas not implicated in stress did not show similar correlations. Increases in medial prefrontal activity with stress correlated with increased cardiac glucose uptake with stress, suggestive of myocardial ischemia (r=0.85, p=0.004)., Conclusions: These findings suggest a link between brain response to stress in key areas mediating emotion and peripheral organs involved in inflammation and hematopoietic activity, as well as myocardial ischemia, in Coronary Heart Disease patients., Competing Interests: Conflict: The authors have no conflicts of interest to declare in reference to this research.

Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technology that uses low levels of nonionizing light in the range of red and near-infrared to record changes in the optical absorption and scattering of the underlying tissue that can be used to infer blood flow and oxygen changes during brain activity. The challenges and difficulties of reconstructing spatial images of hemoglobin changes from fNIRS data are mainly caused by the illposed nature of the optical inverse model., Aim: We describe a Bayesian approach combining several lasso-based regularizations to apply anatomy-prior information to solving the inverse model., Approach: We built a Bayesian hierarchical model to solve the Bayesian adaptive fused sparse overlapping group lasso (Ba-FSOGL) model. The method is evaluated and validated using simulation and experimental datasets., Results: We apply this approach to the simulation and experimental datasets to reconstruct a known brain activity. The reconstructed images and statistical plots are shown., Conclusion: We discuss the adaptation of this method to fNIRS data and demonstrate that this approach provides accurate image reconstruction with a low false-positive rate, through numerical simulations and application to experimental data collected during motor and sensory tasks., (© 2023 The Authors.)

The time-varying frequency characteristics of many biomedical time series contain important scientific information. However, the high-dimensional nature of the time-varying power spectrum as a surface in time and frequency limits its direct use by applied researchers and clinicians for elucidating complex mechanisms. In this article, we introduce a new approach to time-frequency analysis that decomposes the time-varying power spectrum in to orthogonal rank-one layers in time and frequency to provide a parsimonious representation that illustrates relationships between power at different times and frequencies. The approach can be used in fully nonparametric analyses or in semiparametric analyses that account for exogenous information and time-varying covariates. An estimation procedure is formulated within a penalized reduced-rank regression framework that provides estimates of layers that are interpretable as power localized within time blocks and frequency bands. Empirical properties of the procedure are illustrated in simulation studies and its practical use is demonstrated through an analysis of heart rate variability during sleep., (© 2021 The International Biometric Society.)

Background: Despite the high prevalence of depression and disruption to 24-h sleep-wake routines following the death of a spouse in late-life, no bereavement interventions have been developed to re-entrain a regular sleep-wake routine among older widow(er)s. We describe the rationale and methodology of the NIH-funded WELL Study (Widowed Elders' Lifestyle after Loss), a randomized controlled trial (RCT) comparing the efficacy of a digital health intervention (DHI) to enhanced usual care (EUC) arm for reducing depression symptoms in older spousally-bereaved adults., Methods: We will randomize approximately 200 recently bereaved (<12 months) adults aged 60+ years to one of two 12-week interventions: digital monitoring of the timing and regularity of sleep, meals, and physical activity plus weekly motivational health coaching; or enhanced usual care consisting of weekly telephone calls and similar assessment schedules. Participants will complete self-report and clinical assessments at baseline, post-intervention, and 3-, 6-, and 12-months post-intervention, and objective actigraphic assessments of their 24-h rest-activity rhythm (RAR) at baseline and 1-, 2-, and 3-months during the intervention. The primary outcome is change in depression symptoms burden (using the Hamilton Rating Scale for Depression) from pre- to post-intervention and over 12 months of follow-up., Discussion: WELL Study findings will inform the development of widely generalizable and scalable technology-based interventions to support bereaved spouses in community-based settings. Clinical http://Trials.gov Identifier: NCT04016896., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2022 Elsevier Inc. All rights reserved.)

Importance: Evidence regarding the nature and prevalence of 24-hour activity pattern phenotypes in older adults, especially those related to depression symptoms and cognition, is needed to guide the development of targeted mechanism research and behavioral interventions., Objectives: To identify subgroups of older adults with similar 24-hour activity rhythm characteristics and characterize associated depression symptoms and cognitive performance., Design, Setting, and Participants: From January to March 2022, a cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination and Survey (NHANES) accelerometer study was conducted. The NHANES used a multistage probability sample that was designed to be representative of noninstitutionalized adults in the US. The main analysis included participants 65 years or older who had accelerometer and depression measures weighted to represent approximately 32 million older adults., Exposures: Latent profile analysis identified subgroups with similar 24-hour activity pattern characteristics as measured using extended-cosine and nonparametric methods., Main Outcomes and Measures: Covariate-adjusted sample-weighted regressions assessed associations of subgroup membership with (1) depression symptoms defined as 9-Item Patient Health Questionnaire (PHQ-9) scores of 10 or greater (PHQ-9) and (2) having at least psychometric mild cognitive impairment (p-MCI) defined as scoring less than 1 SD below the mean on a composite cognitive performance score., Results: The actual clustering sample size was 1800 (weighted: mean [SD] age, 72.9 [7.3] years; 57% female participants). Clustering identified 4 subgroups: (1) 677 earlier rising/robust (37.6%), (2) 587 shorter active period/less modelable (32.6%), (3) 177 shorter active period/very weak (9.8%), and (4) 359 later settling/very weak (20.0%). The prevalence of a PHQ-9 score of 10 or greater differed significantly across groups (cluster 1, 3.5%; cluster 2, 4.7%; cluster 3, 7.5%; cluster 4, 9.0%; χ2 P = .004). The prevalence of having at least p-MCI differed significantly across groups (cluster 1, 7.2%; cluster 2, 12.0%; cluster 3, 21.0%; cluster 4, 18.0%; χ2 P &lt; .001). Five of 9 depression symptoms differed significantly across subgroups., Conclusions and Relevance: In this cross-sectional study, findings indicate that approximately 1 in 5 older adults in the US may be classified in a subgroup with weak activity patterns and later settling, and approximately 1 in 10 may be classified in a subgroup with weak patterns and shorter active duration. Future research is needed to investigate the biologic processes related to these behavioral phenotypes, including why earlier and robust activity patterns appear protective, and whether modifying disrupted patterns improves outcomes.

Study Objectives: We examined whether homeostatic sleep drive and circadian rhythmicity differ in older adults with insomnia (OAI) compared to older good sleepers (GS)., Methods: OAI (n = 37) and GS (n = 30) participated in a 60-h in-lab study with sleep deprivation and constant routine paradigms. Homeostatic sleep drive was assessed by examining the effect of sleep deprivation on delta EEG power and theta EEG power, and repeated sleep latency tests. Circadian rhythm was assessed with salivary melatonin (phase and amplitude), core body temperature (phase, amplitude, and mesor), and sleep latency during a constant routine paradigm. Mixed models were used to assess interactions of group (OAS vs GS) with homeostatic sleep and circadian effects., Results: Compared to GS, OAI showed a greater linear increase in waking theta power during sleep deprivation, but the two groups did not show differential responses to sleep deprivation in delta EEG, or in repeated sleep latency tests. The two groups did not differ in circadian phase or amplitude of melatonin or core body temperature rhythms. OAI had a significantly elevated core body temperature mesor compared to GS., Conclusions: Homeostatic response to sleep deprivation was intact in OAI compared to GS; theta EEG power suggested a greater homeostatic response in OAI. Circadian rhythm amplitude and phase were similar in OAI compared to GS. Elevated body temperature mesor in OAI may indicate elevated physiological arousal. These findings suggest that effective treatments for insomnia in older adults may leverage intact sleep and circadian regulatory mechanisms, rather than repair defective sleep and circadian regulation., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Ambulatory blood pressure monitoring (ABPM) increases restlessness during adults' sleep in laboratory settings, but there is little evidence of an association among adolescents or in naturalistic environments. This study examined activity levels before and after blood pressure cuff inflation during sleep to determine whether and for how long ABPM increased restlessness during sleep in healthy adolescents., Methods: Two hundred thirty-four healthy adolescents (mean age = 15.72 [1.30] years; 54% female; 57% Black) completed two consecutive nights of hourly ABPM and wrist-worn actigraphy. Activity counts during sleep, averaged across 5-minute bins, were compared in the 20 minutes before and after blood pressure cuff inflation using a four-level mixed model (bins within hours within nights within participants). Interactions of bin with night, sex, and race were examined. Covariates included age, sex, and race., Results: Activity counts in the 5-minute bin immediately after cuff inflation were 10% to 14% higher than all other bins before ( p < .001) and after ( p < .001) cuff inflation. This effect differed by night and sex, as activity levels during 5-minute post-cuff inflation were elevated only on night 1 ( p values < .001) and only in female participants ( p values < .001). Effects did not differ by race., Conclusions: Cuff inflation during ABPM briefly increased adolescent female participants' restlessness during sleep. Habituation occurred after one night, so two nights of ABPM may minimize impact on sleep. If only one night of ABPM is feasible, excluding 5 minutes of actigraphy data after each cuff inflation may accommodate the impact of ABPM on restlessness during sleep., (Copyright © 2022 by the American Psychosomatic Society.)

Introduction: Sleep disturbance is associated with autonomic dysregulation, but the temporal directionality of this relationship remains uncertain. The objective of this study was to evaluate the temporal relationships between objectively measured sleep disturbance and daytime or nighttime autonomic dysregulation in a co-twin control study., Methods: A total of 68 members (34 pairs) of the Vietnam Era Twin Registry were studied. Twins underwent 7-day in-home actigraphy to derive objective measures of sleep disturbance. Autonomic function indexed by heart rate variability (HRV) was obtained using 7-day ECG monitoring with a wearable patch. Multivariable vector autoregressive models with Granger causality tests were used to examine the temporal directionality of the association between daytime and nighttime HRV and sleep metrics, within twin pairs, using 7-day collected ECG data., Results: Twins were all male, mostly white (96%), with mean (SD) age of 69 (2) years. Higher daytime HRV across multiple domains was bidirectionally associated with longer total sleep time and lower wake after sleep onset; these temporal dynamics were extended to a window of 48 h. In contrast, there was no association between nighttime HRV and sleep measures in subsequent nights, or between sleep measures from previous nights and subsequent nighttime HRV., Conclusions: Daytime, but not nighttime, autonomic function indexed by HRV has bidirectional associations with several sleep dimensions. Dysfunctions in autonomic regulation during wakefulness can lead to subsequent shorter sleep duration and worse sleep continuity, and vice versa, and their influence on each other may extend beyond 24 h., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Studies of human movement usually collect data from multiple repetitions of a task and use the average of all movement trials to approximate the typical kinematics or kinetics pattern for each individual. Few studies report the expected accuracy of these estimated mean kinematics or kinetics waveforms for each individual. The purpose of this study is to demonstrate how simultaneous confidence bands, which is an approach to quantify uncertainty across an entire waveform based on limited data, can be used to calculate margin of error (MOE) for waveforms. Bilateral plantar pressure data were collected from 70 participants as they walked over 4 surfaces for an average of at least 300 steps per surface. The relationship between MOE and the number of steps included in the analysis was calculated using simultaneous confidence bands, and 3 methods commonly used for pointwise estimates: intraclass correlation, sequential averaging, and T-based MOE. The conventional pointwise approaches underestimated the number of trials required to estimate biomechanical waveforms within a desired MOE. Simultaneous confidence bands are an objective approach to more accurately estimate the relationship between the number of trials collected and the MOE in estimating typical biomechanical waveforms.

In the opioid research, predicting the risk of overdose or other adverse outcomes from opioid prescription patterns can help health professionals identify high-risk individuals. Challenges may arise in modeling the exposure-time-response association if the intensity, duration, and timing of exposure vary among subjects, and if exposures have a cumulative or latency effect on the risk. Further challenges may arise when the data involve competing risks, where subjects may fail from one of multiple events and failure from one precludes the risk of experiencing others. In this study, we proposed a competing risks regression model via subdistribution hazards to directly estimate the association between longitudinal patterns of opioid exposure and cumulative incidence of opioid overdose. The model incorporated weighted cumulative effects of the exposure and used penalized splines in the partial likelihood equation to estimate the weights flexibly. The proposed model is able to distinguish different opioid prescription patterns even though these patterns have the same overall intensity during the study period. Performance of the model was evaluated through simulation.

Studies of epilepsy surgery outcomes are often small and thus underpowered to reach statistically valid conclusions. We hypothesized that ordinal logistic regression would have greater statistical power than binary logistic regression when analyzing epilepsy surgery outcomes. We reviewed 10 manuscripts included in a recent meta-analysis which found that mesial temporal sclerosis (MTS) predicted better surgical outcomes after a stereotactic laser amygdalohippocampectomy (SLAH). We extracted data from 239 patients from eight studies that reported four discrete Engel surgical outcomes after SLAH, stratified by the presence or absence of MTS. The rate of freedom from disabling seizures (Engel I) was 64.3% (110/171) for patients with MTS compared to 44.1% (30/68) without MTS. The statistical power to detect MTS as a predictor for better surgical outcome after a SLAH was 29% using ordinal regression, which was significantly more than the 13% power using binary logistic regression (paired t-test, P < .001). Only 120 patients are needed for this example to achieve 80% power to detect MTS as a predictor using ordinal regression, compared to 210 patients that are needed to achieve 80% power using binary logistic regression. Ordinal regression should be considered when analyzing ordinal outcomes (such as Engel surgical outcomes), especially for datasets with small sample sizes., (© 2022 The Authors. Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Study Objectives: Polysomnography (PSG) is considered the "gold standard" for assessing sleep, but cost and burden limit its use. Although wrist actigraphy and self-report diaries are feasible alternatives to PSG, few studies have compared all three modalities concurrently across multiple nights in the home to assess their relative validity across multiple sleep outcomes. This study compared sleep duration and continuity measured by PSG, actigraphy, and sleep diaries and examined moderation by race/ethnicity., Methods: Participants from the Study of Women's Health Across the Nation (SWAN) Sleep Study included 323 White ( n = 147), African American ( n = 120), and Chinese ( n = 56) middle-aged community-dwelling women (mean age: 51 years, range: 48-57). PSG, wrist actigraphy (AW-64; Philips Respironics, McMurray, PA), and sleep diaries were collected concurrently in participants' homes over three consecutive nights. Multivariable repeated-measures linear models compared time in bed (TIB), total sleep time (TST), sleep efficiency (SE), sleep latency (SL), and wake after sleep onset (WASO) across modalities., Results: Actigraphy and PSG produced similar estimates of sleep duration and efficiency. Diaries yielded higher estimates of TIB, TST, and SE versus PSG and actigraphy, and lower estimates of SL and WASO versus PSG. Diary SL was shorter than PSG SL only among White women, and diary WASO was lower than PSG and actigraphy WASO among African American versus White women., Conclusions: Given concordance with PSG, actigraphy may be preferred as an alternative to PSG for measuring sleep in the home. Future research should consider racial/ethnic differences in diary-reported sleep continuity., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society.)

Objectives: Management of spontaneous pneumomediastinum in the pediatric population is highly variable. There are limited data on the use of diagnostic tests and the need for admission. Our objectives were to characterize the management of pediatric spontaneous pneumomediastinum, determine the diagnostic yield of advanced imaging, and describe the patients' outcomes., Methods: This is a retrospective cohort study of all patients presenting to a single tertiary pediatric emergency department between January 2008 and February 2015 diagnosed with pneumomediastinum. Patients were identified using 2 complementary strategies: International Classification of Diseases, Ninth Revision billing codes and a keyword search of the hospital radiology database., Results: We identified 183 patients with spontaneous pneumomediastinum. The mean age was 12.8 ± 4.8 years. Diagnosis was established by chest radiograph (CXR) in 165 (90%) patients, chest computed tomography in 15 (8%), neck imaging in 2 (1%), and abdominal imaging in 1. After diagnosis, many patients underwent additional studies: repeat CXR (99, 54%), chest computed tomography (53, 29%), esophagram (45, 25%), and laryngoscopy (15, 8%). Seventy-eight percent of patients (n = 142) were admitted with a median length of stay of 27 hours (18.4-45.6 hours). Six patients returned to the emergency department within 96 hours for persistent chest pain; 2 were admitted, and 1 was found to have worsening pneumomediastinum on CXR. We performed a secondary analysis on 3 key subgroups: primary spontaneous pneumomediastinum (64, 35%), secondary gastrointestinal-associated pneumomediastinum (31, 17%), and secondary respiratory-associated pneumomediastinum (88, 48%). No patients in the study received an invasive intervention for pneumomediastinum. In all patients, further studies did not yield additional diagnostic information., Conclusions: Our data suggest that patients with spontaneous pneumomediastinum who are clinically well appearing can be managed conservatively with clinical observation, avoiding exposure to radiation and invasive procedures., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The science of stress exposure and health in humans has been hampered by differences in operational definitions of exposures and approaches to defining timing, leading to results that lack consistency and specificity. In the present study we aim to empirically derive variability in type, timing and chronicity of stress exposure for Black and White females using prospectively collected data in the Pittsburgh Girls Study (PGS)., Methods: The PGS is an ongoing 20-year longitudinal, community-based study. In this paper we focused on annual caregiver reports of three domains of stress: subsistence (e.g., resource strain, overcrowding); safety (e.g., community violence, inter-adult aggression), and caregiving (e.g., separation, maternal depression) from early childhood through adolescence. Z-scores were used to conduct a finite mixture model-based latent class trajectory analysis. Model fit was compared using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). We examined differences in timing and chronicity of stress exposure between Black and White girls., Results: Distinct trajectory groups characterized by differential timing and chronicity of stress exposure were observed across all stress domains. Six trajectories characterized subsistence and safety stress, and five characterized caregiving stress. Variability in initial level, chronicity, and magnitude and timing of change was observed within and across domains of stressors. Race differences also varied across the domains: race differences in timing and chronicity were most pronounced for the subsistence and safety domains, whereas Black and White girls had similar levels of exposure to caregiving stress., Conclusions: Substantial variability in timing and chronicity was observed within and across stress domains. Modeling specific domains and dimensions of stress exposure is likely important in testing associations between exposure and health; such specificity may lead to more effective deployment of preventive interventions based on stress exposure., (© 2021 The Authors.)

Severe worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults., (© 2021. The Author(s).)

Background: Depressive symptoms and sleep disturbances disproportionately affect midlife women. While there may be a bidirectional association, few studies have examined whether depressive symptoms are longitudinally associated with subsequent sleep. Sleep is typically considered unidimensional, despite emerging evidence that multidimensional sleep health provides novel information on the sleep-health link., Purpose: The current study examined whether higher depressive symptoms were longitudinally associated with poorer multidimensional sleep health., Method: Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale across six to nine annual assessments in 302 midlife women from the Study of Women's Health Across the Nation. Six months after their last assessment, actigraphy (mean ± standard deviation = 29.3 ± 6.9 days) and self-report were used to assess sleep health components: efficiency, duration, mid-sleep timing, regularity, alertness, and satisfaction, which were dichotomized and summed to create a composite multidimensional sleep health score. Mixed-effects models were used to evaluate the longitudinal associations between depressive symptoms and multidimensional sleep health, as well as individual sleep health components, adjusting for covariates. Exploratory analyses stratified models by race/ethnicity., Results: Higher depressive symptoms were associated with subsequent poorer multidimensional sleep health (p < .0.001) and lower alertness (p < .0001) and satisfaction with sleep (p < .0001)., Conclusions: Our finding that higher average depressive symptoms were associated longitudinally with actigraphy-measured poorer sleep health in midlife women is novel and converges with the larger body of evidence that these two common symptoms are strongly associated. The bidirectional relationship between these two prevalent symptoms needs to be studied in prospective longitudinal studies., (© Society of Behavioral Medicine 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: A lack of "morningness" predicts greater depression symptom severity over time, including in a vulnerable group of older adults: family dementia caregivers (dCGs). Evidence regarding the neurobiological basis of these correlations is needed to guide future research towards biomarker-informed detection and prevention approaches. We therefore primarily aimed to identify simple resting-state biomarkers that correlated with a lack of "morningness" in dCGs., Method: We examined 54 dCGs (mean age = 70, range: 61-84; 70% female) of whom 40% were definite "morning types" according to Composite Scale of Morningness (CSM). Using a 7 Tesla resting-state sequence, we compared the functional connectivity of nodes in networks previously implicated in depression (fronto-parietal, default mode, limbic, and salience) between caregivers who were and were not "morning types.", Results: Correcting for voxel-wise comparisons, "morning-type" dCGs had less amygdala-posterior cingulate connectivity (Cohen's d = -1.3), which statistically mediated ~32% of the association between the degree of "morningness" and lower depression severity. Post hoc analyses of CSM items found significant correlations, with both amygdala-posterior cingulate FC and depression severity, for 4/6 items pertaining to difficulty, 2/5 items pertaining to preference, and 0/2 items pertaining to typical patterns., Discussion: Prior research shows that amygdala-posterior cingulate connectivity increases when allocating attention to peripheral aspects of negative emotional stimuli. As such, difficulty with morning activation may relate to the ongoing direction of focus around distressing content; in contrast, morning activity participation may serve to limit focus on distress. Replication and experimental studies are required to confirm these associations and their modifiability., (© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Life stressors during pregnancy can disrupt maternal stress regulation and negatively impact offspring health. Despite the important role of cardiac vagal control (e.g., heart rate variability; HRV) in stress regulation, few studies have investigated how life stressors and emotional support influence vagal control during pregnancy. This study aimed to (a) characterize patterns of cardiac vagal control in response to a stressor administered in pregnancy, and (b) examine the effects of life stress and emotional support on vagal control during rest, reactivity, and recovery. Participants included 191 pregnant women (79% Black; 21% White) living in an urban U.S. city (73% receiving public assistance). Heart rate (HR) and HRV (indexed by RMSSD) were recorded continually during the preparation, task, and recovery periods of the Trier Social Stress Test (TSST). Participants reported recent life stressors (e.g., relationship problems, financial hardship) and emotional support. Piecewise growth curve modeling was used to model rates of reactivity and recovery, adjusting for gestational age at time of assessment and recent health problems. Life stress predicted greater HR and HRV reactivity to the TSST as well as greater HRV recovery (vagal rebound). However, associations were only evident for women reporting high emotional support. Results suggest that pregnant women living with frequent life stressors may exhibit more rapid autonomic responses to acute stress, including more rapid vagal rebound after stressors, potentially reflecting physiological adaptation to anticipated high-stress environments; emotional support may enhance these responses. Studies are needed to investigate long-term health outcomes related to this stress response pattern., (© 2021 Society for Psychophysiological Research.)

Background: Relative activity deficits found in people with (verses without) depression symptoms/disorders may accumulate uniformly throughout the day, or they may tend to be expressed at specific times. Evidence for the latter would suggest times when behavioral approaches are most needed to reduce depression and its health consequences., Methods: We performed a secondary-data analysis of participants who contributed valid accelerometer data at the 2005-2006 National Health and Nutrition Examination Survey (n=4390). Participants were categorized according to the Patient Health Questionnaire-9 standard cut-point of ≥10 (i.e., people with versus without clinically significant depression symptoms). Average levels of accelerometer-measured activity in two-hour bins were the dependent variable in mixed models testing if the relationship between depression status and activity level differed by time of day; and if any such relations varied by age group (18-29 years, 30-44 years, 45-59 years, and 60+ years)., Results: In adults over the age of 30, people with depression symptoms had generally lower levels of activity across the day, but these effects were most markedly pronounced in the morning hours. We found no differences in activity levels associated with prevalent depression symptoms among people 18-30 years of age., Limitations: Core aspects of depression pathophysiology that produce these different activity patterns and confer their effects on mood were not measured., Conclusions: In adults 30 years and older, efforts to ameliorate relative activity deficits associated with depression may benefit from considering the apparently outsized role of inactivity that occurs in the morning., (Copyright © 2021. Published by Elsevier B.V.)

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; β = 1.38, p = 0.01) and timing of midpoint of activity (acrophase; β = 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 (β = -4.50, p = 0.03). "Less Active/Robust" (β = 6.14, p = 0.01) and "Later RAR" (β = 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.

This article introduces a nonparametric approach to spectral analysis of a high-dimensional multivariate nonstationary time series. The procedure is based on a novel frequency-domain factor model that provides a flexible yet parsimonious representation of spectral matrices from a large number of simultaneously observed time series. Real and imaginary parts of the factor loading matrices are modeled independently using a prior that is formulated from the tensor product of penalized splines and multiplicative gamma process shrinkage priors, allowing for infinitely many factors with loadings increasingly shrunk towards zero as the column index increases. Formulated in a fully Bayesian framework, the time series is adaptively partitioned into approximately stationary segments, where both the number and locations of partition points are assumed unknown. Stochastic approximation Monte Carlo (SAMC) techniques are used to accommodate the unknown number of segments, and a conditional Whittle likelihood-based Gibbs sampler is developed for efficient sampling within segments. By averaging over the distribution of partitions, the proposed method can approximate both abrupt and slowly varying changes in spectral matrices. Performance of the proposed model is evaluated by extensive simulations and demonstrated through the analysis of high-density electroencephalography.

The evening chronotype is strongly associated with greater alcohol use, though mechanisms underlying this association are not well understood. The current study evaluated emotion regulation as a potential mechanism linking evening chronotype and alcohol use. Participants were 81 undergraduate students. Chronotype was assessed using the Composite Scale of Morningness (CSM). Alcohol use disorder severity was assessed using the Alcohol Use Disorder Identification Test (AUDIT). Participants recorded daily sleep patterns using an online diary for seven days. Participants then completed a standardized laboratory emotion regulation task. Self-reported affect, high-frequency heart rate variability (HF-HRV), and pre-ejection period (PEP) were measured throughout the task. Sleep duration on non-free days (defined as days when sleep was restricted by morning obligations such as work or school) was evaluated as a moderator. Thirty-one evening chronotypes (CSM scores ≤ 26) were compared to 50 non-evening chronotypes (CSM scores >26). Evening chronotypes reported significantly greater symptoms of alcohol use disorder ( F = 4.399, p = .039). In the full sample, emotion regulation was successful for altering affective but not autonomic reactivity to emotional stimuli. There were no chronotype differences in self-reported affect, HF-HRV, or PEP during the emotion regulation task. Longer sleep duration on non-free days was associated with increased HF-HRV during negative emotion regulation among non-evening chronotypes. Moderated mediation revealed that emotion regulation did not mediate the association between evening chronotype and alcohol use, irrespective of sleep duration on non-free days. This study is consistent with the literature on chronotype and substance use, demonstrating that undergraduate evening chronotypes endorse greater severity of alcohol use disorder. Given that emotion regulation did not successfully alter autonomic reactivity to emotional stimuli, emotion regulation as a potential mechanism linking chronotype and alcohol use remains inconclusive. Longer sleep duration appears to be protective for non-evening chronotypes in terms of parasympathetic control during the regulation of negative emotions.

Objectives: The association between sleep and adiposity (indexed by body mass index or waist-to-hip ratio) has typically been evaluated using a single dimension of self-reported sleep. However, other dimensions and behavioral measures of sleep may also be associated with adiposity. This study evaluated whether multidimensional sleep health calculated from actigraphy and self-report was longitudinally associated with adiposity in a sample of midlife women who have a high prevalence of sleep disturbances and adiposity., Design: Longitudinal study with 11-14 years of follow-up time between the sleep health assessment and body mass index / waist-to-hip ratio measurements., Participants: Two hundred and twenty-one midlife women enrolled in the Study of Women's Health Across the Nation Sleep Study., Measurements: Multidimensional sleep health was quantified using actigraphy (M[SD] = 29.1[7.2] nights) measures of sleep efficiency, midpoint, duration, regularity, and self-report measures of alertness and satisfaction. Each component was dichotomized and summed; higher values indicated better sleep health. Height, body weight, and waist and hip circumference were measured at the sleep study and at follow-up. Linear regression models were used to assess associations between sleep health and adiposity, adjusting for demographic and menopausal covariates., Results: There was no substantial within-person change in adiposity over time. Better sleep health was cross-sectionally and longitudinally associated with lower adiposity in unadjusted, but not in adjusted, models. Individual sleep health components were not associated with adiposity after adjustment., Conclusion: We did not observe cross-sectional or longitudinal associations between multidimensional sleep health and adiposity. The sleep-adiposity link may be weaker in midlife adults than in other age groups., (Copyright © 2020 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose: Physical activity has been associated with several individual dimensions of sleep. However, the association between physical activity and sleep health, a construct that emphasizes the multidimensional nature of sleep, has not been explored. This analysis examined the relationship between physical activity and a composite measure of sleep health., Methods: A total of 114 adults (66% female, 60.3 ± 9.2 years) were included in the analyses. Participants reported daily light-intensity physical activity (LPA) and moderate- and vigorous-intensity physical activity (MVPA) via diary, while wearing a pedometer (Omron HJ-720ITC) to measure daily steps. Sleep health was measured using the RU&#95;SATED questionnaire, which addresses regularity of sleep patterns, satisfaction with sleep, daytime alertness, and sleep timing, efficiency, and duration. Multiple linear regression, binary logistic regression, and analysis of covariance (ANCOVA) were utilized for analyses., Results: Mean sleep health score was 9.6 ± 2.4 (0 [poor]-12 [good]). Participants reported 62.9 ± 66.0 and 51.2 ± 51.2 min/day of LPA and MVPA, respectively, and took 5585.5 ± 2806.7 steps/day. Greater MVPA was associated with better sleep health (β = 0.27, P = 0.005) and sleep health scores differed between those reporting < 30 min/day and ≥ 60 min/day of MVPA (P = 0.004). Greater MVPA was associated with higher odds of having good sleep satisfaction (OR = 1.58 [1.14-2.20], P < 0.01), timing (OR = 2.07 [1.24-3.46], P < 0.01), and duration (OR = 1.48 [1.02-2.18], P = 0.04). Pedometer-based physical activity and LPA were not related to sleep health or its individual dimensions., Conclusions: In middle- to older-aged adults, higher-intensity activity, but not lower-intensity or volume of activity, was associated with greater sleep health. These data suggest that physical activity intensity may be important for sleep health.

Background: Moderate to heavy alcohol use during pregnancy (≥3 drinks/occasion) is linked to a range of adverse offspring outcomes. Prior studies suggest that adolescent and young adult mothers may be particularly vulnerable to these risky drinking behaviors during and after pregnancy. This study used latent class growth analysis (LCGA) to examine changes in risky drinking from prepregnancy to postpregnancy and identified prepregnancy predictors representing cognitive and social factors to inform prevention., Methods: Participants included 432 adolescent and young adult mothers (aged 13 to 24; 78% Black) assessed annually since childhood in the Pittsburgh Girls Study. Participants prospectively reported frequency of risky drinking (≥3 drinks/occasion) in the year of pregnancy and 2 years before and after pregnancy, as well as social-cognitive risk factors for drinking (alcohol expectancies, drinking motives, caregiver, and peer alcohol use)., Results: Approximately 11% of young mothers in this community-based sample engaged in risky drinking at least once a month during the year of pregnancy, with greater frequency observed for young adult (vs. adolescent) mothers. LCGA revealed 4 risky drinking trajectories across the perinatal period, including 3 relatively stable trajectories (low, moderate, and high frequency) and 1 distinct trajectory ("postpartum initiators") characterized by increased risky drinking post-childbirth. Peer alcohol use during and after pregnancy distinguished higher risk from lower risk trajectories, controlling for age, race, and age of drinking onset. Exposure to caregiver alcohol use and prepregnancy coping motives for drinking also elevated risk, but only for mothers who became pregnant in early adulthood (vs. adolescence)., Conclusions: Adolescent and young adult mothers show heterogeneous risky drinking trajectories from prepregnancy to postpregnancy. Pregnant women in the transitional age of early adulthood who report exposure to caregiver alcohol use, more friends who drink, and coping motives for drinking may have elevated risk for moderate-heavy drinking during the perinatal period and may benefit from targeted intervention., (© 2020 by the Research Society on Alcoholism.)

Objective: We sought to determine whether the aspects of white matter connectivity implicated in major depression also relate to mild depressive symptoms in family dementia caregivers (dCGs)., Methods: Forty-one dCGs (average age=69 years, standard deviation=6.4) underwent a 7 Tesla 64-direction (12-minute) diffusion-weighted imaging sequence. We compared the fractional anisotropy (FA) of 11 white matter features between dCGs with (n=20) and without (n=21) depressive symptoms (Patient Health Questionnaire-9 scores ≥5)., Results: Caregivers reporting depression symptoms had lower FA in tracts connecting to the posterior cingulate cortex (Cohen's d = -0.9) and connecting dorsolateral prefrontal with rostral cingulate regions (Cohen's d = -1.2)., Conclusions: Posterior cingulate and dorsolateral prefrontal-to-rostral cingulate white matter, implicated in prior studies of major depression, appear relevant to mild depression in dCGs., (Copyright © 2019 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

The time-varying power spectrum of a time series process is a bivariate function that quantifies the magnitude of oscillations at different frequencies and times. To obtain low-dimensional, parsimonious measures from this functional parameter, applied researchers consider collapsed measures of power within local bands that partition the frequency space. Frequency bands commonly used in the scientific literature were historically derived, but they are not guaranteed to be optimal or justified for adequately summarizing information from a given time series process under current study. There is a dearth of methods for empirically constructing statistically optimal bands for a given signal. The goal of this article is to provide a standardized, unifying approach for deriving and analyzing customized frequency bands. A consistent, frequency-domain, iterative cumulative sum based scanning procedure is formulated to identify frequency bands that best preserve nonstationary information. A formal hypothesis testing procedure is also developed to test which, if any, frequency bands remain stationary. The proposed method is used to analyze heart rate variability of a patient during sleep and uncovers a refined partition of frequency bands that best summarize the time-varying power spectrum.

Predicting clinical variables from whole-brain neuroimages is a high-dimensional problem that can potentially benefit from feature selection or extraction. Penalized regression is a popular embedded feature selection method for high-dimensional data. For neuroimaging applications, spatial regularization using the ℓ 1 or ℓ 2 norm of the image gradient has shown good performance, yielding smooth solutions in spatially contiguous brain regions. Enormous resources have been devoted to establishing structural and functional brain connectivity networks that can be used to define spatially distributed yet related groups of voxels. We propose using the fused sparse group lasso (FSGL) penalty to encourage structured, sparse, and interpretable solutions by incorporating prior information about spatial and group structure among voxels. We present optimization steps for FSGL penalized regression using the alternating direction method of multipliers algorithm. With simulation studies and in application to real functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange, we demonstrate conditions under which fusion and group penalty terms together outperform either of them alone., (© 2019 The International Biometric Society.)

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.