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Sleep Jun 2022Sleep plays a significant role in the mental and physical development of children. Emerging evidence in animals and human adults indicates a relationship between sleep...
Sleep plays a significant role in the mental and physical development of children. Emerging evidence in animals and human adults indicates a relationship between sleep and the gut microbiota; however, it is unclear whether the sleep of preschoolers during a key developmental period, associates with features of their gut microbiota. The objective of this study was to assess the relationship between sleep and gut microbiota in preschool-aged children (4.37 ± 0.48 years, n = 143). Sleep measures included total night-time sleep (TST), sleep efficiency (SE), and wake-time after sleep onset (WASO) assessed using actigraphy. Beta-diversity differences between children with low and high TST (p = .048) suggest gut microbiota community differences. Particularly, relative abundance of Bifidobacterium was higher in the high TST group and Bacteroides, was higher in children who had greater SE and less WASO (LDA score >2). In contrast, some Lachnospiraceae members including Blautia and Coprococcus 1 were associated with shorter night-time sleep duration and less efficiency, respectively. We also found a group of fecal metabolites, including specific neuroactive compounds and immunomodulating metabolites were associated with greater sleep efficiency and less time awake at night. Notably, tryptophan and its metabolizing products were higher in children who had higher SE or lower WASO (LDA score >2); concentration of propionate was higher in children with less WASO (p = .036). Overall, our results reveal a novel association between sleep and gut microbiota in preschool-aged children. Longer night-time sleep and greater sleep efficiency were associated with specific commensal bacteria that may regulate sleep through modulating neurotransmitter metabolism and the immune system.
Topics: Actigraphy; Child, Preschool; Gastrointestinal Microbiome; Humans; Polysomnography; Sleep; Wakefulness
PubMed: 35037059
DOI: 10.1093/sleep/zsac020 -
Movement Disorders : Official Journal... Jan 2023Isolated rapid-eye-movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle-aged and...
BACKGROUND
Isolated rapid-eye-movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle-aged and older adults; however, accurate ambulatory diagnostic methods are not available. Questionnaires lack specificity in nonclinical populations. Wrist actigraphy can detect characteristic features in individuals with RBD; however, high-frequency actigraphy has been rarely used.
OBJECTIVE
The aim was to develop a machine learning classifier using high-frequency (1-second resolution) actigraphy and a short patient survey for detecting iRBD with high accuracy and precision.
METHODS
The method involved analysis of home actigraphy data (for seven nights and more) and a nine-item questionnaire (RBD Innsbruck inventory and three synucleinopathy prodromes of subjective hyposmia, constipation, and orthostatic dizziness) in a data set comprising 42 patients with iRBD, 21 sleep clinic patients with other sleep disorders, and 21 community controls.
RESULTS
The actigraphy classifier achieved 95.2% (95% confidence interval [CI]: 88.3-98.7) sensitivity and 90.9% (95% CI: 82.1-95.8) precision. The questionnaire classifier achieved 90.6% accuracy and 92.7% precision, exceeding the performance of the Innsbruck RBD Inventory and prodromal questionnaire alone. Concordant predictions between actigraphy and questionnaire reached a specificity and precision of 100% (95% CI: 95.7-100.0) with 88.1% sensitivity (95% CI: 79.2-94.1) and outperformed any combination of actigraphy and a single question on RBD or prodromal symptoms.
CONCLUSIONS
Actigraphy detected iRBD with high accuracy in a mixed clinical and community cohort. This cost-effective fully remote procedure can be used to diagnose iRBD in specialty outpatient settings and has potential for large-scale screening of iRBD in the general population. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Topics: Middle Aged; Humans; Aged; Actigraphy; Parkinson Disease; Synucleinopathies; REM Sleep Behavior Disorder; Surveys and Questionnaires; Sleep
PubMed: 36258659
DOI: 10.1002/mds.29249 -
Behavioral Sleep Medicine 2020A growing body of work supports linear associations between sleep and socioemotional adjustment in adolescence. However, associations between sleep and adjustment are...
BACKGROUND & OBJECTIVES
A growing body of work supports linear associations between sleep and socioemotional adjustment in adolescence. However, associations between sleep and adjustment are not necessarily linear and investigations of nonlinear effects are scarce. This study examined linear and nonlinear relations between several sleep-wake parameters and externalizing behavior and internalizing symptoms in adolescence, and assessed the role of adolescent sex as a moderator of effects.
PARTICIPANTS
Participants were high school students ( = 180; age = 17.49, = .62; 59% female; 68% White/European American, 32% Black/African American) from a wide range of socio-economic backgrounds living in semirural communities and small towns in Alabama.
METHODS
Sleep-wake parameters were indexed by actigraphy-derived sleep minutes and adolescents' reports on morningness-eveningness (circadian preference), sleep-wake problems (sleep quality), and sleepiness. Adolescents completed questionnaires on externalizing behaviors and internalizing symptoms.
RESULTS
Controlling for sleep duration, a higher preference for eveningness and poor sleep quality were associated in a linear fashion with increased externalizing and internalizing symptoms. Nonlinear relations between sleepiness and internalizing symptoms emerged with pronounced sex-related effects, including somewhat delayed accelerating relations for males and rapidly accelerating associations that tended to plateau for females.
CONCLUSIONS
Results illustrate the importance of examining multiple sleep-wake and adjustment variables as well as linear and nonlinear associations.
Topics: Actigraphy; Adolescent; Adolescent Behavior; Female; Humans; Male; Sleep Initiation and Maintenance Disorders; Social Adjustment
PubMed: 31537121
DOI: 10.1080/15402002.2019.1665049 -
International Journal of Environmental... Aug 2019Various accelerometers have been used in research measuring physical activity (PA) and sedentary behavior (SB). This study compared two triaxial accelerometers-Active... (Comparative Study)
Comparative Study
Various accelerometers have been used in research measuring physical activity (PA) and sedentary behavior (SB). This study compared two triaxial accelerometers-Active style Pro (ASP) and ActiGraph (AG)-in measuring PA and SB during work and nonwork days in free-living conditions. A total of 50 working participants simultaneously wore these two accelerometers on one work day and one nonwork day. The difference and agreement between the ASP and AG were analyzed using paired -tests, Bland-Altman plots, and intraclass coefficients, respectively. Correction factors were provided by linear regression analysis. The agreement in intraclass coefficients was high among all PA intensities between ASP and AG. SB in the AG vertical axis was approximately 103 min greater than ASP. Regarding moderate-to-vigorous-intensity PA (MVPA), ASP had the greatest amount, followed by AG. There were significant differences in all variables among these devices across all day classifications, except for SB between ASP and AG vector magnitude. The correction factors decreased the differences of SB and MVPA. PA time differed significantly between ASP and AG. However, SB and MVPA differences between these two devices can be decreased using correction factors, which are useful methods for public health researchers.
Topics: Actigraphy; Adult; Exercise; Female; Health Surveys; Humans; Japan; Male; Middle Aged; Reproducibility of Results; Sedentary Behavior
PubMed: 31450754
DOI: 10.3390/ijerph16173065 -
Parkinsonism & Related Disorders Jul 2021Step counts represent a straight-forward method of measuring physical activity in adults with Parkinson's disease (PD). The present study examined the absolute and...
INTRODUCTION
Step counts represent a straight-forward method of measuring physical activity in adults with Parkinson's disease (PD). The present study examined the absolute and relative accuracy and precision of a wrist-worn research-grade accelerometer (i.e., ActiGraph GT3X+) for measuring step counts during over-ground and treadmill walking in adults with PD and controls without PD.
METHODS
Participants (PD: n = 29; controls: n = 31) wore two ActiGraph GT3X + accelerometers, one on each wrist, and completed an over-ground walking bout followed by a treadmill walking bout at the same speed. Step counts were measured manually using a hand-held tally counter. Accuracy and precision were based on absolute and relative metrics.
RESULTS
The ActiGraph GT3X + underestimated step counts in both participants with PD (4.7-11% error) and controls without PD (8.8-17% error), with a greater discrepancy in controls. The ActiGraph GT3X + provided more accurate and precise estimates of step counts when placed on the more affected wrist and non-dominant wrist for participants with PD and controls, respectively, and was more accurate and precise during over-ground walking compared with treadmill walking for both groups.
CONCLUSIONS
Our results suggest that placement of the device (i.e., dominant vs. non-dominant), type of activity (i.e., over-ground vs. treadmill walking), and presence of clinical conditions may impact the accuracy and precision of data when using the research-grade ActiGraph GT3X + accelerometer for measuring step counts.
Topics: Actigraphy; Aged; Female; Humans; Male; Middle Aged; Parkinson Disease; Walking; Wearable Electronic Devices; Wrist
PubMed: 34171566
DOI: 10.1016/j.parkreldis.2021.06.009 -
Journal of Medical Internet Research Dec 2020In many countries, depressed individuals often first visit primary care settings for consultation, but a considerable number of clinically depressed patients remain...
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.
Topics: Actigraphy; Activities of Daily Living; Adolescent; Adult; Aged; Depression; Female; Humans; Male; Mass Screening; Middle Aged; Research Design; Young Adult
PubMed: 33258783
DOI: 10.2196/22634 -
Sensors (Basel, Switzerland) Jan 2020Wrist 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... (Review)
Review
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 (R = 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.
Topics: Actigraphy; Aged; Circadian Rhythm; Female; Human Activities; Humans; Male; Middle Aged; Signal Processing, Computer-Assisted; Sleep
PubMed: 31963889
DOI: 10.3390/s20020549 -
Medicine and Science in Sports and... Jan 2020This study aimed to determine the validity of existing methods to estimate sedentary behavior (SB) under free-living conditions using ActiGraph GT3X+ accelerometers (AG).
PURPOSE
This study aimed to determine the validity of existing methods to estimate sedentary behavior (SB) under free-living conditions using ActiGraph GT3X+ accelerometers (AG).
METHODS
Forty-eight young (18-25 yr) adults wore an AG on the right hip and nondominant wrist and were video recorded during four 1-h sessions in free-living settings (home, community, school, and exercise). Direct observation videos were coded for postural orientation, activity type (e.g., walking), and METs derived from the Compendium of Physical Activities, which served as the criterion measure of SB (sitting or lying posture, <1.5 METs). Thirteen methods using cut points from vertical counts per minute (CPM), counts per 15-s (CP15s), and vector magnitude (VM) counts (e.g., CPM1853VM), raw acceleration and arm angle (sedentary sphere), Euclidean norm minus one (ENMO) corrected for gravity (mg) thresholds, uni- or triaxial sojourn hybrid machine learning models (Soj1x and Soj3x), random forest (RF), and decision tree (TR) models were used to estimate SB minutes from AG data. Method bias, mean absolute percent error, and their 95% confidence intervals were estimated using repeated-measures linear mixed models.
RESULTS
On average, participants spent 34.1 min per session in SB. CPM100, CPM150, Soj1x, and Soj3x were the only methods to accurately estimate SB from the hip. Sedentary sphere and ENMO44.8 overestimated SB by 3.9 and 6.1 min, respectively, whereas the remaining wrist methods underestimated SB (range, 9.5-2.5 min). In general, mean absolute percent error was lower using hip methods compared with wrist methods.
CONCLUSION
Accurate group-level estimates of SB from a hip-worn AG can be achieved using either simpler count-based approaches (CPM100 and CPM150) or machine learning models (Soj1x and Soj3x). Wrist methods did not provide accurate or precise estimates of SB. The development of large open-source free-living calibration data sets may lead to improvements in SB estimates.
Topics: Actigraphy; Adolescent; Adult; Fitness Trackers; Hip; Humans; Posture; Reproducibility of Results; Sedentary Behavior; Video Recording; Wrist; Young Adult
PubMed: 31343523
DOI: 10.1249/MSS.0000000000002099 -
Medicine Sep 2021To investigate fatigue, health-related quality of life (HR-QOL), and sleep quality in women with primary Sjogren syndrome (pSS) or rheumatoid arthritis (RA) as compared... (Observational Study)
Observational Study
Cross-sectional assessment of sleep and fatigue in middle-aged Japanese women with primary Sjogren syndrome or rheumatoid arthritis using self-reports and wrist actigraphy.
To investigate fatigue, health-related quality of life (HR-QOL), and sleep quality in women with primary Sjogren syndrome (pSS) or rheumatoid arthritis (RA) as compared with healthy controls using self-reports and wrist actigraphy.In this cross-sectional observational study, we evaluated a total of 25 patients (aged 40-75 years) with pSS, 10 with RA, and 17 healthy control subjects living in Japan. The HR-QOL was assessed using the Short Form-36. Fatigue was evaluated using the Short Form-36 vitality score, visual analog scale (VAS) for fatigue, and 2 questionnaire items using scores based on a 4-point Likert scale. Sleep quality was measured using the Japanese version of the Pittsburgh Sleep Quality Index, VAS for sleep quality, and wrist actigraphy for 14 days.Patients with pSS reported severer fatigue and lower HR-QOL than healthy controls, especially in mental health. Based on the Pittsburgh Sleep Quality Index score, 56% of the patients with pSS were poor sleepers, which was higher than healthy controls (29.4%). Furthermore, the patients with pSS scored significantly lower on the VAS for sleep quality than healthy controls (40.5 vs 63.7, P = .001). Although subjective assessments revealed slight sleep disturbances in patients with pSS, wrist actigraphy revealed no differences when compared with healthy controls for total sleep time (421.8 minutes vs 426.5 minutes), sleep efficiency (95.2% vs 96.4%), number of awakenings (1.4 vs 0.9), and wake after sleep onset (22.4 minutes vs 16.1 minutes). Poor subjective sleep quality was associated with enhanced fatigue. However, sleep efficiency, as determined by actigraphy, was not associated with fatigue. Notably, the patients with RA and healthy controls did not differ significantly in terms of fatigue or sleep quality, although patients with RA experienced more nocturnal awakenings than healthy controls (1.7 vs 0.9, P = .04).Patients with pSS experience severe fatigue, poor HR-QOL, and sleep disturbances, which are associated with fatigue. However, wrist actigraphy did not reveal differences in sleep quality, suggesting that it may not be an appropriate measure of sleep in patients with pSS.
Topics: Actigraphy; Adult; Aged; Arthritis, Rheumatoid; Cross-Sectional Studies; Fatigue; Female; Humans; Japan; Male; Middle Aged; Monitoring, Physiologic; Quality of Life; Self Report; Sjogren's Syndrome; Sleep; Surveys and Questionnaires; Wrist
PubMed: 34664865
DOI: 10.1097/MD.0000000000027233 -
Journal of Psychiatric Research Jul 2023The aims of this study were to investigate the associations of major depressive disorder (MDD) and its subtypes (atypical, melancholic, combined, unspecified) with...
The aims of this study were to investigate the associations of major depressive disorder (MDD) and its subtypes (atypical, melancholic, combined, unspecified) with actigraphy-derived measures of sleep, physical activity and circadian rhythms; and test the potentially mediating role of sleep, physical activity and circadian rhythms in the well-established associations of the atypical MDD subtype with Body Mass Index (BMI) and the metabolic syndrome (MeS). The sample consisted of 2317 participants recruited from an urban area, who underwent comprehensive somatic and psychiatric evaluations. MDD and its subtypes were assessed via semi-structured diagnostic interviews. Sleep, physical activity and circadian rhythms were measured using actigraphy. MDD and its subtypes were associated with several actigraphy-derived variables, including later sleep midpoint, low physical activity, low inter-daily stability and larger intra-individual variability of sleep duration and relative amplitude. Sleep midpoint and physical activity fulfilled criteria for partial mediation of the association between atypical MDD and BMI, and physical activity also for partial mediation of the association between atypical MDD and MeS. Our findings confirm associations of MDD and its atypical subtype with sleep and physical activity, which are likely to partially mediate the associations of atypical MDD with BMI and MeS, although most of these associations are not explained by sleep and activity variables. This highlights the need to consider atypical MDD, sleep and sedentary behavior as cardiovascular risk factors.
Topics: Humans; Depressive Disorder, Major; Depression; Cardiovascular Diseases; Risk Factors; Sleep; Metabolic Syndrome; Heart Disease Risk Factors; Circadian Rhythm; Actigraphy
PubMed: 37253320
DOI: 10.1016/j.jpsychires.2023.05.042