Depressive symptoms and circadian activity rhythm disturbances in community-dwelling older women

Sleep Deficiency in the Elderly

With aging, there are normative changes to sleep physiology and circadian rhythmicity that may predispose older adults to sleep deficiency, whereas many health-related and psychosocial/behavioral factors may precipitate sleep deficiency. In this article, we describe age-related changes to sleep and describe how the health-related and psychosocial/behavioral factors typical of aging may converge in older adults to increase the risk for sleep deficiency. Next, we review the consequences of sleep deficiency in older adults, focusing specifically on important age-related outcomes, including mortality, cognition, depression, and physical function. Finally, we review treatments for sleep deficiency, highlighting safe and effective nonpharmacologic interventions.

Sleep Deficiency in Obstructive Sleep Apnea

Sleep deficiency in patients with obstructive sleep apnea (OSA) includes abnormal quality, timing and duration of sleep, and the presence of other comorbid conditions. These include insomnia, circadian misalignment disorders, and periodic limb movements of sleep, among others. The co-occurrence of these conditions with OSA likely plays a role in pathogenesis, clinical presentation, and management of OSA. Considering these conditions and their treatment in evaluating sleep deficiency in OSA may help improve patient outcomes. However, future research is needed to understand the intersection between OSA and these disorders.

Actigraphic monitoring of sleep and circadian rest-activity rhythm in individuals with major depressive disorder or depressive symptoms: A meta-analysis

BACKGROUND

Disrupted sleep and rest-activity pattern are common clinical features in depressed individuals. This meta-analysis compared sleep and circadian rest-activity rhythms in people with major depressive disorder (MDD) or depressive symptoms and healthy controls.

METHODS

Eligible studies were identified in five databases up to December 2023. The search yielded 53 studies with a total of 11,115 participants, including 4000 depressed participants and 7115 healthy controls.

RESULTS

Pooled meta-analyses demonstrated that depressed individuals have significantly longer sleep latency (SMD = 0.23, 95 % CI: 0.12 to 0.33) and wake time after sleep onset (SMD = 0.37, 95 % CI: 0.22 to 0.52), lower sleep efficiency (SMD = -0.41, 95 % CI: -0.56 to -0.25), more nocturnal awakenings (SMD = 0.58, 95 % CI: 0.29 to 0.88), lower MESOR (SMD = -0.54, 95 % CI: -0.81 to -0.28), amplitude (SMD = -0.33, 95 % CI: -0.57 to -0.09), and interdaily stability (SMD = -0.17, 95 % CI: -0.28 to -0.05), less daytime (SMD = -0.79, 95 % CI: -1.08 to -0.49) and total activities (SMD = -0.89, 95 % CI: -1.28 to -0.50) when compared with healthy controls.

LIMITATIONS

Most of the included studies reported separate sleep and activity parameters instead of 24-hour rest-activity rhythms. The variabilities among actigraphy devices and the types of participants recruited also impede precise comparisons.

CONCLUSIONS

The findings emerging from this study offered a better understanding of sleep and rest-activity rhythm in individuals with MDD or depressive symptoms. Future studies could advocate for deriving objective, distinctive 24-hour rest-activity profiles contributing to the risk of depression.

PROSPERO REGISTRATION NUMBER

CRD42021259780.

Rest-Activity Rhythm Phenotypes in Adults with Epilepsy and Intellectual Disability

Objective

Sleep and rest-activity rhythms (RARs) are perturbed in many forms of neuropsychiatric illness. In this study, we applied wrist actigraphy to describe the extent of RAR perturbations in adults with epilepsy and intellectual disability ("E+ID"), using a cross-sectional case-control design. We examined whether RAR phenotypes correlated with epilepsy severity, deficits in adaptive function and/or comorbid psychopathology.

Methods

Primary caregivers of E+ID adults provided informed consent during routine ambulatory clinic visits and were asked to complete standardized surveys of overall epilepsy severity (GASE, Global Assessment of Severity of Epilepsy), adaptive function (ABAS-3, Adaptive Behavior Assessment System-3) and psychopathology (ABCL, Adult Behavior Checklist). Caregivers were also asked to ensure that subjects wore an Actiwatch-2 device continuously on their nondominant wrist for at least ten days. From recorded actograms, we calculated RAR amplitude, acrophase, robustness, intradaily variability (IV), interdaily stability (IS) and estimates of sleep quantity and timing. We compared these RAR metrics against those from (i) a previously published cohort of adults with epilepsy without ID (E-ID), and (ii) a cohort of age- and sex-matched intellectually able subjects measured within the Study of Latinos (SOL) Ancillary actigraphy study (SOL). Within E+ID subjects, we applied k-means analysis to divide subjects into three actigraphically distinct clusters.

Results

46 E+ID subjects (median age 26 [20-68], 47% female) provided a median recording duration of 11 days [range 6-27]. Surveys reflected low to extremely low levels of adaptive function (ABAS3 General Adaptive Composite score: median 50 [49-75]), and low/subclinical levels of psychopathology (ABCL total score: median 54.5 [25-67]). Compared with E-ID (n=57) and SOL (n=156) cohorts, E+ID subjects displayed significantly lower RAR amplitude, robustness and IS, with significantly higher IV and total daily sleep. K-means clustering of E+ID subjects recognized an intermediate cluster "B", with RAR values indistinguishable to E-ID. Cluster "A" subjects displayed pronounced hypoactivity and hypersomnia with high rates of rhythm fragmentation, while cluster "C" subjects featured hyper-robust and high amplitude RARs. All three clusters were similar in age, body mass index, antiseizure medication (ASM) polytherapy, ABAS3 and ABCL scores. We qualitatively describe RAR examples from all three clusters.

Interpretation

We show that adults with epilepsy and intellectual disability display a wide spectrum of RAR phenotypes that do not neatly correlate with measures of adaptive function or epilepsy severity. Prospective studies are necessary to determine whether continuous actigraphic monitoring can sensitively capture changes in chronobiological health that may arise with disease progression, iatrogenesis (e.g., ASM toxicity) or acute health deteriorations (e.g., seizure exacerbation, pneumonia). Similar long-term data is necessary to recognize whether behavioral interventions targeted to 'normalize' RARs may promote improvements in adaptive function and therapy engagement.

Prevalence of sleep disorders in geriatrics: an exploratory study using sleep questionnaires

OBJECTIVES

This study aimed to investigate the prevalence of sleep problems in older subjects, considering sex and age differences.

METHODS

Subjects admitted to a geriatrics clinic underwent a medical visit and completed a battery of questionnaires assessing sleep quality, insomnia, sleep apnea risk, excessive daytime sleepiness (EDS), restless legs syndrome (RLS), chronotype, depression and global cognition.

RESULTS

Fifty-eight subjects (58.6 % women, mean age 77.36±6.07) were included. The most predominant sleep-related complaint was poor sleep quality (36.2 %), followed by sleep apnea risk (34.5 %), insomnia symptoms (25.9 %), EDS (15.5 %) and RLS (12.1 %). Older women reported more insomnia, poorer sleep quality and depressive symptoms than males. Patients aged ≥ 75 years old had more comorbidities and higher sleep apnea risk compared to those under 75 years old.

CONCLUSIONS

Sleep problems are frequent in older adults, requiring their screening and treatment for possibly improving well-being and reduce the burden of neuropsychiatric and medical comorbidities.

Exploring actigraphy as a digital phenotyping measure: A study on differentiating psychomotor agitation and retardation in depression

INTRODUCTION

Psychomotor activity stands out as a crucial symptom in characterizing behaviors associated with depression. This study aims to explore the potential of actigraphy as a tool for digital phenotyping in characterizing symptoms of psychomotor agitation and retardation, which are clinically challenging dimensions to capture, in patients diagnosed with major depressive episode (MDE) according to DSM-5 criteria.

METHODS

We compared rest-activity circadian rhythm biomarkers measured by the Motion Watch 8 actigraphy between 58 (78.4%) patients with MDE and psychomotor retardation (PMR), and 16 (21.6%) patients with MDE and psychomotor agitation (PMA), according to DSM-5 criteria.

RESULTS

Actigraphy allowed to objectively report PMA through heightened activity over a 24-h period, while PMR manifests as reduced activity during the most active 10 h. Lower rest-activity rhythm (RAR) amplitude in PMR was accompanied by increased irregularities in intra- and inter-day rhythms. Interestingly, actigraphy emerges as an objective tool to measure the characteristics of the active and rest periods, free from the confounding effects of sleep disturbances. Indeed, no differences in sleep disturbances were identified between patients exhibiting psychomotor agitation and those displaying PMR.

CONCLUSION

Digital phenotyping through actigraphy may aid in distinguishing psychomotor retardation and psychomotor agitation allowing for a more precise characterization of the depression phenotype. When integrated with clinical assessment, measurements from actigraphy could offer additional insights into activity rhythms alongside subjective assessments and hold the potential to augment existing clinical decision-making processes in psychiatry.

Depressive symptom screening in elderly by passive sensing data of smartphones or smartwatches: A systematic review

BACKGROUND

The elderly is commonly susceptible to depression, the symptoms for which may overlap with natural aging or other illnesses, and therefore miss being captured by routine screening questionnaires. Passive sensing data have been promoted as a tool for depressive symptoms detection though there is still limited evidence on its usage in the elderly. Therefore, this study aims to review current knowledge on the use of passive sensing data via smartphones and smartwatches in depressive symptom screening for the elderly.

METHOD

The search of literature was performed in PubMed, IEEE Xplore digital library, and PsycINFO. Literature investigating the use of passive sensing data to screen, monitor, and/or predict depressive symptoms in the elderly (aged 60 and above) via smartphones and/or wrist-worn wearables was included for initial screening. Studies in English from international journals published between January 2012 to September 2022 were included. The reviewed studies were further analyzed by a narrative analysis.

RESULTS

The majority of 21 included studies were conducted in Western countries with a few in Asia and Australia. Most studies adopted a cohort study design (n = 12), followed by cross-sectional design (n = 7) and a case-control design (n = 2). The most popular passive sensing data was related to sleep and physical activity using an actigraphy. Sleep characteristics, such as prolonged wakefulness after sleep onset, along with lower levels of physical activity, exhibited a significant association with depression. However, cohort studies expressed concerns regarding data quality stemming from incomplete follow-up and potential confounding effects.

CONCLUSION

Passive sensing data, such as sleep, and physical activity parameters should be promoted for depressive symptoms detection. However, the validity, reliability, feasibility, and privacy concerns still need further exploration.

Sleep-wake behavioral characteristics associated with depression symptoms: findings from the Multi-Ethnic Study of Atherosclerosis

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.

Stability and Volatility of Human Rest-Activity Rhythms: Insights from Very Long Actograms (VLAs)

Importance

Wrist-worn activity monitors provide biomarkers of health by non-obtrusively measuring the timing and amount of rest and physical activity (rest-activity rhythms, RARs). The morphology and robustness of RARs vary by age, gender, and sociodemographic factors, and are perturbed in various chronic illnesses. However, these are cross-sectionally derived associations from recordings lasting 4-10 days, providing little insights into how RARs vary with time.

Objective

To describe how RAR parameters can vary or evolve with time (~months).

Design Setting and Participants

48 very long actograms ("VLAs", ≥90 days in duration) were identified from subjects enrolled in the STAGES (Stanford Technology, Analytics and Genomics in Sleep) study, a prospective cross-sectional, multi-site assessment of individuals > 13 years of age that required diagnostic polysomnography to address a sleep complaint. A single 3-year long VLA (author GD) is also described.

Exposures/Intervention

None planned.

Main Outcomes and Measures

For each VLA, we assessed the following parameters in 14-day windows: circadian/ultradian spectrum, pseudo-F statistic ("F"), cosinor amplitude, intradaily variability, interdaily stability, acrophase and estimates of "sleep" and non-wearing.

Results

Included STAGES subjects (n = 48, 30 female) had a median age of 51, BMI of 29.4kg/m2, Epworth Sleepiness Scale score (ESS) of 10/24 and a median recording duration of 120 days. We observed marked within-subject undulations in all six RAR parameters, with many subjects displaying ultradian rhythms of activity that waxed and waned in intensity. When appraised at the group level (nomothetic), averaged RAR parameters remained remarkably stable over a ~4 month recording period. Cohort-level deficits in average RAR robustness associated with unemployment or high BMI (>29.4) also remained stable over time.

Conclusions and Relevance

Through an exemplary set of months-long wrist actigraphy recordings, this study quantitatively depicts the longitudinal stability and dynamic range of human rest-activity rhythms. We propose that continuous and long-term actigraphy may have broad potential as a holistic, transdiagnostic and ecologically valid monitoring biomarker of changes in chronobiological health. Prospective recordings from willing subjects will be necessary to precisely define contexts of use.

24 h Rest/Activity Rhythms in Older Adults with Memory Impairment: Associations with Cognitive Performance and Depressive Symptomatology

Little is known about links of circadian rhythm alterations with neuropsychiatric symptoms and cognition in memory impaired older adults. Associations of actigraphic rest/activity rhythms (RAR) with depressive symptoms and cognition are examined using function-on-scalar regression (FOSR). Forty-four older adults with memory impairment (mean: 76.84 ± 8.15 years; 40.9% female) completed 6.37 ± 0.93 days of actigraphy, the Beck depression inventory-II (BDI-II), mini-mental state examination (MMSE) and consortium to establish a registry for Alzheimer's disease (CERAD) delayed word recall. FOSR models with BDI-II, MMSE, or CERAD as individual predictors adjusted for demographics (Models A1-A3) and all three predictors and demographics (Model B). In Model B, higher BDI-II scores are associated with greater activity from 12:00-11:50 a.m., 2:10-5:50 p.m., 8:40-9:40 p.m., 11:20-12:00 a.m., higher CERAD scores with greater activity from 9:20-10:00 p.m., and higher MMSE scores with greater activity from 5:50-10:50 a.m. and 12:40-5:00 p.m. Greater depressive symptomatology is associated with greater activity in midafternoon, evening, and overnight into midday; better delayed recall with greater late evening activity; and higher global cognitive performance with greater morning and afternoon activity (Model B). Time-of-day specific RAR alterations may affect mood and cognitive performance in this population.

Sleep Deficiency in Obstructive Sleep Apnea

Sleep deficiency in patients with obstructive sleep apnea includes abnormal quality, timing, and duration of sleep, and the presence of other comorbid conditions. These include insomnia, circadian misalignment disorders, and periodic limb movements of sleep. The co-occurrence of these conditions with obstructive sleep apnea likely plays a role in the pathogenesis, clinical presentation, and management of obstructive sleep apnea. Considering these conditions and their treatment in evaluating sleep deficiency in obstructive sleep apnea may help to improve patient outcomes. However, future research is needed to understand the intersection between obstructive sleep apnea and these disorders.

Sleep Deficiency in the Elderly

With aging, there are normative changes to sleep physiology and circadian rhythmicity that may predispose older adults to sleep deficiency, whereas many health-related and psychosocial/behavioral factors may precipitate sleep deficiency. In this article, we describe age-related changes to sleep and describe how the health-related and psychosocial/behavioral factors typical of aging may converge in older adults to increase the risk for sleep deficiency. Next, we review the consequences of sleep deficiency in older adults, focusing specifically on important age-related outcomes, including mortality, cognition, depression, and physical function. Finally, we review treatments for sleep deficiency, highlighting safe and effective nonpharmacologic interventions.

Digital Biomarkers for Depression Screening With Wearable Devices: Cross-sectional Study With Machine Learning Modeling

Background

Depression is a prevalent mental disorder that is undiagnosed and untreated in half of all cases. Wearable activity trackers collect fine-grained sensor data characterizing the behavior and physiology of users (ie, digital biomarkers), which could be used for timely, unobtrusive, and scalable depression screening.

Objective

The aim of this study was to examine the predictive ability of digital biomarkers, based on sensor data from consumer-grade wearables, to detect risk of depression in a working population.

Methods

This was a cross-sectional study of 290 healthy working adults. Participants wore Fitbit Charge 2 devices for 14 consecutive days and completed a health survey, including screening for depressive symptoms using the 9-item Patient Health Questionnaire (PHQ-9), at baseline and 2 weeks later. We extracted a range of known and novel digital biomarkers characterizing physical activity, sleep patterns, and circadian rhythms from wearables using steps, heart rate, energy expenditure, and sleep data. Associations between severity of depressive symptoms and digital biomarkers were examined with Spearman correlation and multiple regression analyses adjusted for potential confounders, including sociodemographic characteristics, alcohol consumption, smoking, self-rated health, subjective sleep characteristics, and loneliness. Supervised machine learning with statistically selected digital biomarkers was used to predict risk of depression (ie, symptom severity and screening status). We used varying cutoff scores from an acceptable PHQ-9 score range to define the depression group and different subsamples for classification, while the set of statistically selected digital biomarkers remained the same. For the performance evaluation, we used k-fold cross-validation and obtained accuracy measures from the holdout folds.

Results

A total of 267 participants were included in the analysis. The mean age of the participants was 33 (SD 8.6, range 21-64) years. Out of 267 participants, there was a mild female bias displayed (n=170, 63.7%). The majority of the participants were Chinese (n=211, 79.0%), single (n=163, 61.0%), and had a university degree (n=238, 89.1%). We found that a greater severity of depressive symptoms was robustly associated with greater variation of nighttime heart rate between 2 AM and 4 AM and between 4 AM and 6 AM; it was also associated with lower regularity of weekday circadian rhythms based on steps and estimated with nonparametric measures of interdaily stability and autocorrelation as well as fewer steps-based daily peaks. Despite several reliable associations, our evidence showed limited ability of digital biomarkers to detect depression in the whole sample of working adults. However, in balanced and contrasted subsamples comprised of depressed and healthy participants with no risk of depression (ie, no or minimal depressive symptoms), the model achieved an accuracy of 80%, a sensitivity of 82%, and a specificity of 78% in detecting subjects at high risk of depression.

Conclusions

Digital biomarkers that have been discovered and are based on behavioral and physiological data from consumer wearables could detect increased risk of depression and have the potential to assist in depression screening, yet current evidence shows limited predictive ability. Machine learning models combining these digital biomarkers could discriminate between individuals with a high risk of depression and individuals with no risk.

The role of circadian rhythms in Obstructive Sleep Apnea symptoms and novel targets for treatment

Obstructive Sleep Apnea (OSA) is a common disorder that is associated with disability, premature mortality and lost quality of life. Excessive daytime sleepiness and depressive symptoms confer a great portion of the disability and lost quality of life associated with the disorder. While showing robust rates of response and symptoms resolutions, current treatments aimed at correcting the respiratory disturbances are not universally successful and a non-negligible proportion of patients who are correctly using available therapies do not experience symptomatic relief, suggesting that mechanisms beyond the respiratory disturbances may be involved in the pathogenesis of symptoms. A growing body of literature concerning animal and human models suggests that the sleep and respiratory disturbances commonly seen in OSA, namely sleep fragmentation, partial sleep deprivation, intermittent hypoxia, can promote shifts in circadian rhythms ultimately leading to misalignment between sleep-wake rhythms and the internal clock, as well as desynchrony amongst peripheral clocks and peripheral and central clock. This manuscript reviews the current evidence in support of a circadian disturbance underlying OSA symptomatology and proposes new applications for existing chronotherapeutic interventions with the potential for improving symptoms and quality of life for those patients that do not find symptomatic relief with currently available treatments.

Irregular sleep-wake patterns in older adults with current or remitted depression

BACKGROUND

Disturbed sleep and irregular sleep-wake patterns have been associated with poor outcomes in older adults. Sleep regularity however has not been studied in a sample with current or remitted major depression.

METHODS

138 participants (63.8±8.6 years; n=27 current major depression, n=64 remitted, and n=47 healthy controls) were monitored using wrist-worn actigraphy. The Sleep Regularity Index (SRI), sleep-wake fragmentation and stability, sleep onset and offset timing, number of awakenings and measures from cosinor analysis were computed.

RESULTS

Compared with controls, older adults with current depression had lower SRI (p < 0.01), lower relative amplitude (p < 0.05), and higher activity during sleeping and post-midnight hours (p < 0.05). Older adults with remitted depression displayed lower activity during the day (p < 0.05), showed reduced average activity and lower amplitude than controls. Total sleep time, sleep timing, and number of awakenings did not differ between groups. All groups differed significantly in self-reported sleep quality and depression severity.

LIMITATIONS

Longitudinal studies which examine how sleep-wake patterns change based on depressive episode recency, severity and how medications may influence these patterns are needed.

CONCLUSIONS

Older adults with current or remitted major depression do not differ from controls on traditional sleep metrics but do report poor quality sleep and show differences in sleep regularity and rest-activity patterns. Reducing the risk of poor outcomes in both groups may be aided by interventions that help promote sleep regularity and increased activity.

Screening for Depression in Daily Life: Development and External Validation of a Prediction Model Based on Actigraphy and Experience Sampling Method

Background

In many countries, depressed individuals often first visit primary care settings for consultation, but a considerable number of clinically depressed patients remain unidentified. Introducing additional screening tools may facilitate the diagnostic process.

Objective

This study aimed to examine whether experience sampling method (ESM)-based measures of depressive affect and behaviors can discriminate depressed from nondepressed individuals. In addition, the added value of actigraphy-based measures was examined.

Methods

We used data from 2 samples to develop and validate prediction models. The development data set included 14 days of ESM and continuous actigraphy of currently depressed (n=43) and nondepressed individuals (n=82). The validation data set included 30 days of ESM and continuous actigraphy of currently depressed (n=27) and nondepressed individuals (n=27). Backward stepwise logistic regression analysis was applied to build the prediction models. Performance of the models was assessed with goodness-of-fit indices, calibration curves, and discriminative ability (area under the receiver operating characteristic curve [AUC]).

Results

In the development data set, the discriminative ability was good for the actigraphy model (AUC=0.790) and excellent for both the ESM (AUC=0.991) and the combined-domains model (AUC=0.993). In the validation data set, the discriminative ability was reasonable for the actigraphy model (AUC=0.648) and excellent for both the ESM (AUC=0.891) and the combined-domains model (AUC=0.892).

Conclusions

ESM is a good diagnostic predictor and is easy to calculate, and it therefore holds promise for implementation in clinical practice. Actigraphy shows no added value to ESM as a diagnostic predictor but might still be useful when ESM use is restricted.

Level and timing of physical activity during normal daily life in depressed and non-depressed individuals

Engaging in physical activity is known to reduce depressive symptoms. However, little is known which behavioral factors are relevant, and how patterns of activity change during depressive episodes. We expected that compared to controls, in depressed individuals the level of activity would be lower, the amplitude of 24-h-actigraphy profiles more dampened and daytime activities would start later. We used 14-day continuous-actigraphy data from participants in the Netherlands Study of Depression and Anxiety (NESDA) who participated in an ambulatory assessment study. Participants with a depression diagnosis in the past 6 months (n = 58) or its subsample with acute depression (DSM diagnosis in the past 1 month, n = 43) were compared to controls without diagnoses (n = 63). Depression was diagnosed with a diagnostic interview. Actigraphy-derived variables were activity mean levels (MESOR), the difference between peak and mean level (amplitude) and the timing of the activity peak (acrophase), which were estimated with cosinor analysis. Compared to the control group, both depression groups (total: B = -0.003, p = 0.033; acute: B = -0.004, p = 0.005) had lower levels of physical activity. Amplitude was also dampened, but in the acute depression group only (total: B = -0.002, p = 0.065; acute: B = -0.003, p = 0.011). Similarly, the timing of activity was marginally significant towards a later timing of activity in the acute, but not total depression group (total: B = 0.206, p = 0.398; acute: B = 0.405, p = 0.084). In conclusion, our findings may be relevant for understanding how different aspects of activity (level and timing) contribute to depression. Further prospective research is needed to disentangle the direction of the association between depression and daily rest-activity rhythms.

Characterizing Behavioral Activity Rhythms in Older Adults Using Actigraphy

Wrist actigraphy has been used to assess sleep in older adult populations for nearly half a century. Over the years, the continuous raw activity data derived from actigraphy has been used for the characterization of factors beyond sleep/wake such as physical activity patterns and circadian rhythms. Behavioral activity rhythms (BAR) are useful to describe individual daily behavioral patterns beyond sleep and wake, which represent important and meaningful clinical outcomes. This paper reviews common rhythmometric approaches and summarizes the available data from the use of these different approaches in older adult populations. We further consider a new approach developed in our laboratory designed to provide graphical characterization of BAR for the observed behavioral phenomenon of activity patterns across time. We illustrate the application of this new approach using actigraphy data collected from a well-characterized sample of older adults (age 60+) with osteoarthritis (OA) pain and insomnia. Generalized additive models (GAM) were implemented to fit smoothed nonlinear curves to log-transformed aggregated actigraphy-derived activity measurements. This approach demonstrated an overall strong model fit (R2 = 0.82, SD = 0.09) and was able to provide meaningful outcome measures allowing for graphical and parameterized characterization of the observed activity patterns within this sample.

Assessment of Circadian Rhythms

Circadian rhythms are observed in most physiologic functions across a variety of species and are controlled by a master pacemaker in the brain called the suprachiasmatic nucleus. The complex nature of the circadian system and the impact of circadian disruption on sleep, health, and well-being support the need to assess internal circadian timing in the clinical setting. The ability to assess circadian rhythms and the degree of circadian disruption can help in categorizing subtypes or even new circadian rhythm disorders and aid in the clinical management of the these disorders.

Circadian Preference as a Moderator of Depression Outcome Following Cognitive Behavioral Therapy for Insomnia Plus Antidepressant Medications: A Report From the TRIAD Study

STUDY OBJECTIVES

We previously presented results from a randomized controlled trial that examined the effects of antidepressant medication plus cognitive behavioral therapy for insomnia (CBT-I) among patients with major depressive disorder (MDD) and insomnia. The current secondary analysis aims to examine whether circadian preference moderated the reduction in depression and insomnia symptom severity during this trial.

METHODS

A total of 139 adult participants with MDD and insomnia disorder were treated with antidepressant medication and randomized to receive 7 sessions of CBT-I or a control therapy (CTRL). Circadian preference (eveningness) was measured using the Composite Scale of Morningness (CSM). Depression symptom severity was assessed using the Hamilton Depression Rating Scale (HDRS); insomnia symptom severity was assessed using the Insomnia Severity Inventory (ISI). The moderating role of circadian preference on changes in HRSD and ISI was assessed via latent growth models within the framework of structural equation modeling.

RESULTS

Greater evening preference was associated with smaller reduction in HDRS (P = .03) from baseline to week 6 across treatment groups. The interaction between CSM and treatment group was also significant (P = .02), indicating that participants with greater evening preference in the CTRL group had significantly smaller HDRS reduction than those with greater evening preference in the CBT-I group. Circadian preference did not share significant associations with ISI (all P > .30).

CONCLUSIONS

Individuals with MDD and insomnia who have an evening preference are at increased risk for poor response to pharmacological depression treatment augmented with either CBT-I or CTRL behavioral insomnia treatment. However, evening types have better depression outcomes when treated with CBT-I than with CTRL for insomnia.

The effect of night shift on sleep quality and depressive symptoms among Chinese nurses

PURPOSE

Night shift is associated with adverse physical and psychological health outcomes such as poor sleep quality and depressive symptoms. We aimed to compare sleep quality as well as depressive symptoms in nurses working night shifts to those working day shifts only and explore the association between sleep quality and depressive symptoms among nurses.

PATIENTS AND METHODS

Eight hundred sixty-five nurses were enrolled in the current study. Sleep quality and depressive symptoms among nurses were evaluated by the Pittsburgh Sleep Quality Index (PSQI) and Hospital Anxiety and Depressive Disorders Rating Scale (HADS), respectively.

RESULTS

PSQI and HADS scores were both significantly higher in the nurses working night shifts (P<0.05) than in those working day shifts only. Besides, there was a positive correlation between PSQI and HADS scores. Binary logistic regression showed that night shift and poor sleep quality were independent risk factors of depressive symptoms among nurses.

CONCLUSION

Higher rates of depression among Chinese nurses working night shifts may be associated with poor sleep quality induced by night shift.

Impact of Poor Sleep on Physical and Mental Health in Older Women

Many aspects of sleep and circadian rhythms change as people age. Older adults usually experience decrease in sleep duration and efficiency, increase in sleep latency and fragmentation, high prevalence of sleep disorders, and weakened rest-activity rhythms. Research evidence suggests that women are more likely to report aging-related sleep problems. This review presents epidemiologic and clinical evidence on the relationships between sleep deficiency and physical and mental outcomes in older women, explores potential mechanisms underlying such relationships, points out gaps in the literature that warrant future investigations, and considers implications in clinical and public health settings.

Rest-activity rhythm profiles associated with manic-hypomanic and depressive symptoms

Rest-activity rhythm (RAR) disturbances are associated with mood disorders. But there remains a need to identify the particular RAR profiles associated with psychiatric symptom dimensions. Establishing such profiles would support the development of tools that track the 24-h sleep-wake phenotypes signaling clinical heterogeneity. We used data-driven clustering to identify RAR profiles in 145 adults aged 36-82 years (mean = 60, standard deviation = 9). Then we evaluated psychiatric symptom dimensions (including positive and negative affect, depressive, manic-hypomanic, panic-agoraphobic, and substance use symptoms) associated with these empirically-derived RAR profiles. Clustering identified three sub-groups characterized, on average, by: (1) earlier and more robust RARs ("earlier/robust," n = 55, 38%); (2) later and irregular RARs ("later/irregular," n = 31, 21%); and (3) later RARs and a narrower active period ("later/narrower," n = 59, 41%). Compared with the "earlier/robust" group: the "later/irregular" group had higher levels of lifetime manic-hypomanic symptoms (β (standard error) = 0.80 (0.22) higher standardized symptom units, p = 0.0004) and lifetime depression symptoms (β (standard error) = 0.73 (0.21) higher standardized symptom units, p = 0.0009); the "later/narrower" group had more lifetime depression symptoms (β (standard error) = 0.48 (0.18) higher standardized symptom units, p = 0.0076). These associations persisted after adjustments for sleep continuity and duration, suggesting that RARs are distinct behavioral correlates of clinical heterogeneity. Longitudinal studies are needed to confirm whether RAR characteristics contribute to the risk of manic and/or depressive episodes, and whether they reflect the consequences of psychiatric disturbance (e.g., on quality of life or disability). Opportunities to monitor or intervene on objectively-assessed RARs could facilitate better mental health related outcomes.

Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK Biobank

BACKGROUND

Disruption of sleep and circadian rhythmicity is a core feature of mood disorders and might be associated with increased susceptibility to such disorders. Previous studies in this area have used subjective reports of activity and sleep patterns, but the availability of accelerometer-based data from UK Biobank participants permits the derivation and analysis of new, objectively ascertained circadian rhythmicity parameters. We examined associations between objectively assessed circadian rhythmicity and mental health and wellbeing phenotypes, including lifetime history of mood disorder.

METHODS

UK residents aged 37-73 years were recruited into the UK Biobank general population cohort from 2006 to 2010. We used data from a subset of participants whose activity levels were recorded by wearing a wrist-worn accelerometer for 7 days. From these data, we derived a circadian relative amplitude variable, which is a measure of the extent to which circadian rhythmicity of rest-activity cycles is disrupted. In the same sample, we examined cross-sectional associations between low relative amplitude and mood disorder, wellbeing, and cognitive variables using a series of regression models. Our final model adjusted for age and season at the time that accelerometry started, sex, ethnic origin, Townsend deprivation score, smoking status, alcohol intake, educational attainment, overall mean acceleration recorded by accelerometry, body-mass index, and a binary measure of childhood trauma.

FINDINGS

We included 91 105 participants with accelerometery data collected between 2013 and 2015 in our analyses. A one-quintile reduction in relative amplitude was associated with increased risk of lifetime major depressive disorder (odds ratio [OR] 1·06, 95% CI 1·04-1·08) and lifetime bipolar disorder (1·11, 1·03-1·20), as well as with greater mood instability (1·02, 1·01-1·04), higher neuroticism scores (incident rate ratio 1·01, 1·01-1·02), more subjective loneliness (OR 1·09, 1·07-1·11), lower happiness (0·91, 0·90-0·93), lower health satisfaction (0·90, 0·89-0·91), and slower reaction times (linear regression coefficient 1·75, 1·05-2·45). These associations were independent of demographic, lifestyle, education, and overall activity confounders.

INTERPRETATION

Circadian disruption is reliably associated with various adverse mental health and wellbeing outcomes, including major depressive disorder and bipolar disorder. Lower relative amplitude might be linked to increased susceptibility to mood disorders.

FUNDING

Lister Institute of Preventive Medicine.

Rest-activity rhythm and sleep characteristics associated with depression symptom severity in strained dementia caregivers

Depression is associated with disturbances to sleep and the 24-h sleep-wake pattern (known as the rest-activity rhythm: RAR). However, there remains a need to identify the specific sleep/RAR correlates of depression symptom severity in population subgroups, such as strained dementia caregivers, who are at elevated risk for major depressive disorder. We assessed the cross-sectional associations of sleep/RARs with non-sleep depression symptom severity among 57 (mean age: 74 years, standard deviation: 7.4) strained dementia caregivers who were currently without clinical depression. We derived sleep measures from polysomnography and actigraphy, modelled RARs using a sigmoidally transformed cosine curve and measured non-sleep depression symptom severity using the Hamilton Depression Rating Scale (HRDS) with sleep items removed. The following sleep-wake measures were associated with greater depression symptom severity (absolute Spearman's correlations ranged from 0.23 to 0.32): more time awake after sleep onset (WASO), higher RAR middle level (mesor), relatively shorter active periods (alpha), earlier evening settling time (down-mesor) and less steep RARs (beta). In multivariable analysis, high WASO and low RAR beta were associated independently with depression symptom severity. Predicted non-sleep HDRS means (95% confidence intervals) in caregivers with and without these characteristics were: normal WASO/beta = 3.7 (2.3-5.0), high WASO/normal beta = 5.5 (3.5-7.6), normal WASO/low beta = 6.3 (3.6-8.9) and high WASO/low beta = 8.1 (5.3-10.9). Thus, in our sample of strained caregivers, greater sleep fragmentation (WASO) and less sustained/sharply segregated resting and active periods (low RAR beta) correlate uniquely with depression symptom severity. Longitudinal studies are needed to establish whether these independent sleep-wake correlates of depression symptoms explain heightened depression risk in dementia caregivers.

Sex Differences in the Relationship Between Depressive Symptoms and Actigraphic Assessments of Sleep and Rest-Activity Rhythms in a Population-Based Sample

OBJECTIVE

Depression is often associated with disruptions in sleep and circadian rhythms. We aimed to confirm these relationships via actigraphic assessment in a large, population-based sample and test whether sex moderates these relationships.

METHODS

A total of 418 participants (age = 35-85 years, mean [standard deviation] = 57.04 [11.47]) completed questionnaires and 1 week of actigraphy, used to calculate sleep and rest-activity statistics including mesor (mean activity level), amplitude (height of rhythm), and acrophase (time of day that rhythm peaks).

RESULTS

Depressive symptoms, assessed via Center for Epidemiologic Studies Depression Scale, were associated with disrupted sleep and rest-activity rhythms. Furthermore, men demonstrated longer sleep onset latency (SOL, B = -13.28, p < .001), longer wake time after sleep onset (B = -6.26, p < .01), lower sleep efficiency (B = 5.91, p < .001), and lower total sleep time (TST, B = 33.16, p < .001) than women. Sex moderated the relationship between depression and SOL, TST, mesor, and amplitude; sex-stratified models revealed that higher depression scores were associated with greater SOL (B = 1.05, p < .001) and less TST (B = -0.87, p < .10) for women with higher depressive symptoms, but lower mesor (B = -1.75, p < .01) and amplitude (B = -1.94, p < .01) for men with higher depressive symptoms.

CONCLUSIONS

Depressive symptoms were related to disrupted sleep continuity and rest-activity rhythms in this population-based sample; however, these relationships differed by sex. Women with greater depressive symptoms exhibited difficulty with sleep continuity, whereas men with greater depressive symptoms demonstrated disruption throughout the 24-hour rhythm.

Opportunities for clinical applications of rest-activity rhythms in detecting and preventing mood disorders

PURPOSE OF REVIEW

Rest-activity rhythm (RAR) measurements may aid in the detection of depression risk and serve as an important target for depression prevention. This review evaluates the strength of current evidence supporting these potential applications.

RECENT FINDINGS

Depression is associated with lower activity levels, that is less regularly patterned, and potentially shifted earlier or later in the day. Specific RAR patterns (combinations of several RAR characteristics) in patients with clinical depression may be unique or partially shared across disorders. Longitudinal research is limited but provides initial evidence that multiple distinct RAR patterns are associated with the risk of developing depression symptoms.

SUMMARY

RAR measures provide a comprehensive and objective assessment of depression's behavioral manifestations, and therefore may be useful as monitoring tool, providing additional information to help clinicians tailor behavioral treatments to specific patients. RARs also appear to contribute to depression risk and may be an important target for depression prevention. But research has not established valid predictive metrics using RARs to diagnose depression or detect depression risk. Future research should prioritize establishing the specific RAR patterns related to depression risk in high-risk groups, and should seek to place this risk within the known psychosocial and neurobiological risk architecture of depression.

Latent activity rhythm disturbance sub-groups and longitudinal change in depression symptoms among older men

Activity rhythm disturbances and depression often co-occur among older adults. However, little is known about how activity rhythm disturbances themselves co-occur, or how disturbances to multiple aspects of the activity rhythm relate to depression over time. In this study, we performed a Latent Class Analysis to derive sub-groups of older men [total n = 2933, mean age = 76.28, standard deviation (SD) = 5.48] who shared similar patterns of activity rhythm disturbances (defined as extreme values of modeled activity rhythm parameters). We found eight sub-groups with distinct combinations of activity rhythm disturbances: one had all normative activity rhythm parameters (32.09%), one had only lower activity (10.06%), three had earlier activity (totaling 26.96%) and three had later activity (totaling 30.89%). Groups with similar timing were distinguished depending on whether the relative length of the active period was shorter and/or if the activity rhythm had lesser amplitude/robustness. We next examined whether the derived activity rhythm sub-groups were associated with different rates of change in depression symptom levels over an average of 5.5 (0.52 SD) follow-up years. The sub-group with lower activity only had faster increases in depressive symptoms over time (compared with the group with normative rhythm parameters), but this association was accounted for by adjustments for concurrently assessed health status covariates. Independent of these covariates, we found that four activity rhythm disturbance sub-groups experienced faster depressive symptom increases (compared with the normative sub-group): These included all three sub-groups that had later activity timing and one sub-group that had earlier activity timing plus a shorter active period and a dampened rhythm. Low activity rhythm height/robustness with normal timing therefore may mark depression risk that is attributable to co-occurring disease processes; in contrast, having late or combined early/compressed/dampened activity rhythms may independently contribute to depression symptom development. Our findings suggest that activity rhythm-related depression risk is heterogeneous, and may be detected when multiple aspects of rhythm timing are delayed or when early timing is accompanied by compressed/dampened activity rhythms. Future studies should consider how distinct combinations of altered activity rhythm timing and height/robustness develop and conjointly determine health risks. Further research is also needed to determine whether/how activity rhythms can be modified to improve depression outcomes.

Associations of PER3 and RORA Circadian Gene Polymorphisms and Depressive Symptoms in Older Adults

BACKGROUND

Depressive symptoms are common in older adults and associated with poor outcomes. Although circadian genes have been implicated in depression, the relationship between circadian genes and depressive symptoms in older adults is unclear.

METHODS

A cross-sectional genetic association study of 529 single nucleotide polymorphisms (SNPs) representing 30 candidate circadian genes was performed in two population-based cohorts: the Osteoporotic Fractures in Men Study (MrOS; N=270, age: 76.58±5.61 years) and the Study of Osteoporotic Fractures (SOF) in women (N=1740, 84.05±3.53 years) and a meta-analysis was performed. Depressive symptoms were assessed with the Geriatric Depression Scale categorizing participants as having none-few symptoms (0-2), some depressive symptoms (>2 to <6), or many depressive symptoms (≥6).

RESULTS

We found associations meeting multiple testing criteria for significance between the PER3 intronic SNP rs12137927 and decreased odds of reporting "some depressive symptoms" in the SOF sample (odds ratio [OR]: 0.61, 95% confidence interval [CI]: 0.48-0.78, df=1, Wald χ2=-4.04, p=0.000054) and the meta-analysis (OR: 0.61, CI: 0.48-0.78, z=-4.04, p=0.000054) and between the PER3 intronic SNPs rs228644 (OR: 0.74, CI: 0.63-0.86, z=3.82, p=0.00013) and rs228682 (OR: 0.74, CI: 0.86-0.63, z=3.81, p=0.00014) and decreased odds of reporting "some depressive symptoms" in the meta-analysis compared to endorsing none-few depressive symptoms. The RORA intronic SNP rs11632098 was associated with greater odds of reporting "many depressive symptoms" (OR: 2.16, CI: 1.45-3.23, df=1, Wald χ2=3.76, p=0.000168) in the men. In the meta-analysis the association was attenuated and nominally significant (OR: 1.63, CI: 1.24-2.16, z=3.45, p=0.00056).

CONCLUSION

PER3 and RORA may play important roles in the development of depressive symptoms in older adults.

24-HOUR ACTIVITY RHYTHM AND SLEEP DISTURBANCES IN DEPRESSION AND ANXIETY: A POPULATION-BASED STUDY OF MIDDLE-AGED AND OLDER PERSONS

BACKGROUND

Disturbed circadian rhythms have been associated with depression and anxiety, but it is unclear if disturbances in the 24-hr activity rhythm and sleep are independently and specifically related to these disorders.

METHODS

In 1,714 middle-aged and elderly participants of the Rotterdam Study, we collected actigraphy recordings of at least 96 hr (138 ± 14 hr, mean ± standard deviation). Activity rhythms were quantified calculating the fragmentation of the rhythm, stability of the rhythm over days, and timing of the rhythm. Total sleep time, sleep onset latency, and wake after sleep onset were also estimated with actigraphy. Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression scale, persons with clinically relevant depressive symptoms were interviewed to diagnose DSM-IV-depressive disorder. Anxiety disorders were determined with the Munich version of the Composite International Diagnostic Interview.

RESULTS

More fragmented rhythms were associated with clinically relevant depressive symptoms (odds ratio (OR): 1.27, 95% confidence interval (CI): 1.04;1.54) and anxiety disorders (OR: 1.39, 95% CI: 1.14;1.70) after covariate adjustment. Less stable rhythms, longer sleep onset latency, and more wake after sleep onset were related to clinically relevant depressive symptoms or anxiety disorders only if not adjusted for covariates and other activity rhythm and sleep indicators.

CONCLUSIONS

Our study in middle-aged and elderly persons suggests that fragmentation of the 24-hr activity rhythm is associated with depression and anxiety. Moreover, this association also largely accounts for the effect of disturbed sleep on these psychiatric disorders.

A rest-activity biomarker to predict response to SSRIs in major depressive disorder

Most adults with Major Depressive Disorder (MDD) will not experience a remission with the first antidepressant trial. No practical biomarkers presently exist to predict responsiveness to antidepressants. Herein we report pilot data for a rest-activity biomarker of antidepressant response. Fifty-eight medication-free adults with MDD underwent a week-long collection of actigraphic data before beginning a 9 week open label trial of fluoxetine, coupled with blinded randomized assignment to eszopiclone/placebo. Depression severity was repeatedly measured with the Hamilton Rating Scale for Depression (HRSD). Baseline actigraphic data was analyzed with functional data analysis to create smoothed 24-h curves of activity. The time of the lowest point of activity (the bathyphase) was calculated for each patient, as well the mean difference between bedtime and the bathyphase (BBD). At the end of treatment, patients were characterized as treatment responders (50% reduction in HRSD) or non-responders, and receiver operating curves were calculated to find the optimal cut point of the BBD for prediction of treatment response. The best cut point for BBD was at 260.2 min, resulting in an effect size of 1.45, and with a positive predictive value of 0.75 and a negative predictive value of 0.88. We conclude that actigraphically-determined measures of rest-activity patterns show promise as potential biomarker predictors of antidepressant response. However, this conclusion is based upon a small number of patients who received only one choice of antidepressant, for a single trial. Replication with a larger sample is needed.

Circadian rest-activity rhythms predict future increases in depressive symptoms among community-dwelling older men

OBJECTIVE

Circadian rest-activity rhythms (CARs) have been cross-sectionally associated with depressive symptoms, although no longitudinal research has examined whether CARs are a risk factor for developing depressive symptoms.

METHODS

We examined associations of CARs (measured with actigraphy over a mean of 4.8 days) with depressive symptoms (measured with the Geriatric Depression Scale) among 2,892 community-dwelling older men (mean age: 76.2 ± 5.5 years) from the MrOS Sleep Study who were without cognitive impairment. Among 2,124 men with minimal (0-2) symptoms at baseline, we assessed associations between CAR parameters and increases to mild (3-5) or clinically significant (≥6) symptoms after an average of 1.2 (±0.32) years.

RESULTS

Cross-sectional associations between rhythm height parameters were independent of chronic diseases, lifestyle, sleep, and self-reported physical activity covariates. For example, men in the lowest mesor quartile had twice the adjusted odds (adjusted odds ratio [AOR]: 2.04, 95% confidence interval [CI]: 1.36-3.04, p = 0.0005) of having prevalent clinically significant symptoms (compared to minimal). Longitudinally, low CAR robustness (being in the lowest quartile of the pseudo-F statistic) was independently associated with increasing odds of developing symptoms (i.e., AOR for having clinically significant depressive symptoms at follow-up = 2.58, 95% CI: 1.11-5.99, p = 0.03).

CONCLUSION

CAR disturbances are indicative of depressive symptomology. Low CAR robustness may independently contribute to the risk of worsening depression symptomology.