Intradaily Variability Research Articles

Sleep Fragmentation Despite Intact Rest-Activity Patterns in Premanifest Huntington's disease: An Actigraphy Study

ObjectiveSleep research in Huntington’s disease (HD) has primarily focused on manifest HD, with significantly less attention given to premanifest HD (Pre-HD). Therefore, we investigated sleep and rest-activity patterns in people with Pre-HD versus healthy controls (HC). MethodsWe conducted a cross-sectional study including 36 Pre-HD and 48 HC participants. Pre-HD participants were stratified into three groups according to their proximity to estimated diagnosis, using a cytosine-adenine-guanine (CAG) and current age-based predictive model: NEAR (<9 years to diagnosis), MID (9-15 years to diagnosis) and FAR (>15 years to diagnosis). Sleep and rest-activity patterns were assessed using wrist-worn actigraphy, a sleep diary, and sleep questionnaires. ResultsNEAR and MID groups experienced higher fragmentation index than HC and FAR groups. NEAR and MID groups also exhibited greater WASO than the FAR group. NEAR and MID groups showed lower intra-daily variability (IV) than HC and FAR groups, with the NEAR group also being more active in the most active 10 hours (M10). Groups did not differ on subjective sleep measures, inter-daily stability (IS), sleep regularity index, relative amplitude, or amount of activity in the least active five hours (L5). Considering all Pre-HD participants, fewer years to diagnosis, higher CAG-age-product (CAP) scores (a measure of cumulative exposure to the HD-causing gene mutation) and larger CAG repeat lengths correlated with higher WASO, fragmentation index, L5, IS, and lower sleep efficiency and IV. Higher CAP score correlated with higher M10. ConclusionsDespite intact rest-activity patterns and similar subjective sleep quality to HC, greater sleep fragmentation is a prominent and early feature in Pre-HD. Therefore, reducing sleep fragmentation may be a potential target for sleep intervention in HD. Longitudinal studies using larger samples are needed to assess sleep across the disease spectrum and its impact on clinical outcomes, like cognition.

Abstract 4136762: Association Between Circadian Rest/Activity Rhythms and Incident Dementia in Older Adults: The Atherosclerosis Risk in Communities (ARIC) Study

Introduction: Alterations in circadian rest/activity rhythms (RARs) are common among older adults. RARs can be derived from accelerometry data and are routinely used as proxy measures. Evidence suggests that altered (e.g., fragmented, delayed) RARs may be risk factors for dementia. However, results have been mixed. Using data from the ARIC Study, a community-based cohort, we assessed the association between RARs and incident dementia. Methods: ARIC participants without dementia who wore the Zio XT ECG Patch in 2016-17 for &gt; 3 days were included. RARs were obtained from an accelerometer within the Zio XT ECG Patch and measures of interdaily stability (IS; consistency), intradaily variability (IV; fragmentation), and relative amplitude (RA; strength) were derived. Dementia cases were identified through 2020 using in-person and phone-based cognitive assessments, hospitalization discharge codes, or death certificates. Cox proportional hazards models were used. Results: Of the 2,183 participants (mean [SD] age 79 [4.5] years, 58% female, 24% identified as Black), 176 (8%) developed dementia. Median follow-up time was 3 years and mean Zio XT ECG Patch wear time was 12 days. After multivariable adjustment, lower RA and higher IV were associated with incident dementia (HRs [95% CIs] per 1-SD increment: 0.65 [0.56-0.76], 1.19 [1.02-1.38]). No significant association between IS and dementia was noted; however, there was an interaction by race (p=0.03). Stratified results were not significant, but effect estimates were in opposite directions: (HRs [95% CIs] per 1-SD increment in IS: 0.78 [0.59-1.02] in Black participants and 1.17 [0.96-1.41] in white participants, respectively). No interactions by sex or APOEε4 were noted (p&gt;0.10). Conclusion: In this community-based cohort of older adults, weaker circadian rhythm strength and fragmentation were associated with dementia risk. The association between IS and dementia may differ by race; however, this needs to be further examined in future research. Overall, measures of circadian RARs may be risk factors for dementia. Additional research is warranted to determine whether they can be novel targets for dementia prevention.

Disrupted rest-activity circadian rhythms are associated with all-cause mortality in patients with chronic kidney diseases

ABSTRACT Circadian rhythms are important biological contributors to health. Rest activity rhythms (RAR) are emerging as biomarkers of circadian behavior that are associated with chronic disease when abnormal. RAR have not yet been characterized in chronic kidney diseases (CKD). Leveraging the National Health and Nutrition Examination Survey (2011–2014), patients with CKD (n = 1114; Mean [95% CI]: Age, 50 [58–61] y; 52% female) were compared with non-CKD individuals (n = 5885; Age, 47 [46–48] y; 52% female). Actigraphy data were processed for RAR parameters including rhythmic strength (amplitude), the rhythm adjusted mean (mesor), the timing of peak activity (acrophase), activity regularity (inter-daily stability), and activity fragmentation (intra-daily variability). Cox regression was performed to assess RAR parameters for the prediction of all-cause mortality. Compared to non-CKD adults, patients with CKD had a lower rhythmic amplitude and mesor, and exhibited greater fragmentation and less day-to-day stability in RAR (ps < 0.001). Among CKD patients, a lower rhythmic amplitude (HR [95% CI]: 0.88 [0.82–0.96]; p < 0.001), a lower rhythm adjusted mean (0.87 [0.81–0.95]; p = 0.002), and a higher daily activity fragmentation (1.87 [1.10–3.18]; p = 0.023) were associated with an increased risk of all-cause mortality. Patients with CKD showed dampened rhythmic amplitudes and greater fragmentation of activity that were associated with a higher risk of all-cause mortality. These findings demonstrate a relationship between circadian disruption and prognosis in patients with CKD.

Reliable measures of rest-activity rhythm fragmentation: how many days are needed?

BackgroundA more fragmented, less stable rest-activity rhythm (RAR) is emerging as a risk factor for health. Accelerometer devices are increasingly used to measure RAR fragmentation using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probabilities (TP), self-similarity parameter (α), and activity balance index (ABI). These metrics were proposed in the context of long period of wear but, in real life, non-wear might introduce measurement bias. This study aims to determine the minimum number of valid days to obtain reliable fragmentation metrics.MethodsWrist-worn accelerometer data were drawn from the Whitehall accelerometer sub-study (age: 60 to 83 years) to simulate different non-wear patterns. Pseudo-simulated data with different numbers of valid days (one to seven), defined as < 1/3 of non-wear during both day and night periods, and with omission or imputation of non-wear periods were compared against complete data using intraclass correlation coefficient (ICC) and mean absolute percent error (MAPE).ResultsFive days with valid data (97.8% of participants) and omission of non-wear periods allowed an ICC ≥ 0.75 and MAPE ≤ 15%, acceptable cut points for reliability, for IS and ABI; this number was lower for TPs (two-three days), α and IV (four days). Overall, imputation of data did not provide better estimates. Findings were consistent across age and sex groups.ConclusionsThe number of days of wrist accelerometer data with at least 2/3 of wear time for both day and night periods varies from two (TPs) to five (IS, ABI) days for reliable RAR measures among older adults.

Associations between rest–activity/light-exposure rhythm characteristics and depression in United States adults: A population-based study

This cross-sectional study investigated the association between 24-hour rest-activity rhythm (RAR), light exposure rhythm (LER), and depression symptoms in American adults, using data from the National Health and Nutrition Examination Survey (2011–2014, N = 6852). RAR and LER characteristics were derived from a 24-hour activity recorder and analyzed using the extended cosine model, focusing on intradaily variability (IV), interdaily stability (IS), and relative amplitude (RA). Depression was assessed via the Patient Health Questionnaire-9 (PHQ-9).Multiple logistic and linear regression models showed that higher IV in RAR and LER were associated with increased depression risk (RAR-IV OR = 1.92 [95 % CI: 0.89–4.13]; LER-IV OR = 2.5 [1.45–4.30]), while higher IS and RA in both rhythms were linked to lower depression risk (RAR-IS OR = 0.22 [0.10–0.48], RAR-RA OR = 0.20 [0.11–0.37], LER-IS OR = 0.22 [0.10–0.49], LER-RA OR = 0.29 [0.15–0.56]). Participants in the highest tertile for IS and RA had a significantly lower depression risk compared to the lowest tertile. Subgroup analyses indicated interactions between age and RAR-IV, gender and LER-IV, and BMI and LER-RA (p-interaction < 0.05). Disruptions in RAR and LER are positively associated with depression, emphasizing the need for rhythm regulation interventions considering age, gender, and BMI factors.

Association between rest-activity rhythm and diabetic retinopathy among US middle-age and older diabetic adults.

The disruption of circadian rhythm has been reported to aggravate the progression of diabetic retinopathy (DR). Rest-activity rhythm (RAR) is a widely used method for measuring individual circadian time influencing behavior. In this study, we sought to explore the potential association between RAR and the risk of DR. Diabetic participants aged over 40 from 2011-2014 National Health and Nutrition Examination Survey (NHANES) were enrolled. Data from the wearable device ActiGraph GT3X was used to generate RAR metrics, including interdaily stability (IS), intradaily variability (IV), most active 10-hour period (M10), least active 5-hour period (L5), and Relative amplitude (RA). Weighted multivariable logistic regression analysis and restricted cubic spline analysis were conducted to examine the association between RAR metrics and DR risk. Sensitivity analysis was also conducted to examine the robustness of the findings. An unsupervised K-means clustering analysis was conducted to identify patterns in IV and M10. A total of 1,096 diabetic participants were enrolled, with a DR prevalence of 20.53%. The mean age of participants was 62.3 years, with 49.57% being male. After adjusting covariates, IV was positively associated with DR (β: 3.527, 95%CI: 1.371-9.073). Compared with the lowest quintile of IV, the highest quintile of IV had 136% higher odds of DR. In contrast, M10 was negatively associated with DR (β: 0.902, 95%CI: 0.828-0.982), with participants in the highest M10 quintile showing 48.8% lower odds of DR. Restricted cubic spline analysis confirmed that these associations were linear. Meanwhile, sensitivity analysis confirmed the robustness. K-means clustering identified three distinct clusters, with participants in Cluster C (high-IV, low-M10) had a significantly higher risk of DR comparing with Cluster A (low-IV, high-M10). A more fragmented rhythm and lower peak activity level might be associated with an increased risk of DR. These findings indicate that maintaining a more rhythmic sleep-activity behavior might mitigate the development of DR. Further research is necessary to establish causality and understand the underlying mechanisms, and focus on whether interventions designed to enhance daily rhythm stability and increase diurnal activity level can effectively mitigate the risk of progression of DR.

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

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. 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. 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. 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.

Sleep During the COVID-19 Pandemic: Longitudinal Observational Study Combining Multisensor Data With Questionnaires.

The COVID-19 pandemic prompted various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often lack a comprehensive perspective that considers other factors, such as seasonal variations and physical activity (PA), which can also influence sleep. This study aims to longitudinally examine the detailed changes in sleep patterns among working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables: (1) demographics; (2) sleep-related habits; (3) PA behaviors; and external factors, including (4) pandemic-specific constraints and (5) seasonal variations during the study period. We recruited working adults in Finland for a 1-year study (June 2021-June 2022) conducted during the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by participants, as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the Stringency Index for Finland at various points in time to estimate the degree of pandemic-related lockdown restrictions during the study period. We applied linear mixed models to examine changes in sleep patterns during this late stage of the pandemic and their association with the 5 sets of variables. The sleep patterns of 27,350 nights from 112 working adults were analyzed. Stricter pandemic measures were associated with an increase in total sleep time (TST) (β=.003, 95% CI 0.001-0.005; P<.001) and a delay in midsleep (MS) (β=.02, 95% CI 0.02-0.03; P<.001). Individuals who tend to snooze exhibited greater variability in both TST (β=.15, 95% CI 0.05-0.27; P=.006) and MS (β=.17, 95% CI 0.03-0.31; P=.01). Occupational differences in sleep pattern were observed, with service staff experiencing longer TST (β=.37, 95% CI 0.14-0.61; P=.004) and lower variability in TST (β=-.15, 95% CI -0.27 to -0.05; P<.001). Engaging in PA later in the day was associated with longer TST (β=.03, 95% CI 0.02-0.04; P<.001) and less variability in TST (β=-.01, 95% CI -0.02 to 0.00; P=.02). Higher intradaily variability in rest activity rhythm was associated with shorter TST (β=-.26, 95% CI -0.29 to -0.23; P<.001), earlier MS (β=-.29, 95% CI -0.33 to -0.26; P<.001), and reduced variability in TST (β=-.16, 95% CI -0.23 to -0.09; P<.001). Our study provided a comprehensive view of the factors affecting sleep patterns during the late stage of the pandemic. As we navigate the future of work after the pandemic, understanding how work arrangements, lifestyle choices, and sleep quality interact will be crucial for optimizing well-being and performance in the workforce.

Associations between Aircraft Noise, Sleep, and Sleep-Wake Cycle: Actimetric Data from the UK Biobank Cohort near Four Major Airports.

Nighttime aircraft noise may affect people's sleep, yet large-scale evidence using objective and subjective measures remains limited. Our aim was to investigate associations between nighttime aircraft noise exposure and objectively measured sleep disturbance using a large UK cohort. We used data from 105,770 UK Biobank cohort participants exposed and unexposed to aircraft noise who lived in 44 local authority districts near 4 international airports in England. We used a generalized linear regression model to examine cross-sectional associations between aircraft noise (23:00 hours-07:00 hours) and 7-d actimetric measures collected 2013-2015 (). We also used Logit and generalized estimating equations models to examine associations between and self-reported sleep measures at enrollment (2006-2010) and follow-up (2012-2013). This approach allowed us to compare and contrast the results and support potential future meta-analyses on noise-related sleep disturbance. Cross-sectional analyses of actimetric data suggested sleep disturbance associated with , showing higher level of movements during the least active continuous 8-h time period [: 0.12 milligravitational units; 95% confidence interval (CI): 0.013, 0.23]. We also saw disrupted sleep-wake cycles as indicated by index scores of lower relative amplitude (: ; 95% CI: , ), poorer interdaily stability (: ; 95% CI: , ), and greater intradaily variability (: 0.021; 95% CI: 0.019, 0.023), comparing dB with dB. Repeated cross-sectional analyses found a 52% higher odds of more frequent daytime dozing [odds ratio (OR) ; 95% CI: 1.32, 1.75] for dB in comparison with dB, whereas the likelihood for more frequent sleeplessness was more uncertain (; 95% CI: 0.92, 1.39). Higher effect sizes were seen in preidentified vulnerable groups, including individuals of age and those with diabetes or dementia. Individuals exposed to higher levels of aircraft noise experienced objectively higher levels of sleep disturbance and changes in sleep-wake cycle. https://doi.org/10.1289/EHP14156.

The association between maternal sleep and circadian rhythms during pregnancy and infant sleep and socioemotional outcomes.

Studies have established that maternal sleep and circadian rhythm disturbances during pregnancy are associated with poor prenatal and perinatal outcomes for mothers and offspring. However, little work has explored its effects on infant sleep or socioemotional outcomes. The current study examined the relationship between maternal sleep and circadian rhythm disturbances during pregnancy and infant sleep and socioemotional outcomes in a diverse sample of N = 193 mothers and their infants (51% White; 52% Female; Mage = 11.95months). Maternal sleep and circadian rhythms during pregnancy were assessed using self-reports and actigraphy. Mothers reported on infants' sleep and socioemotional outcomes when infants were one year old. When controlling for infant sex, age, gestational age at birth, family income-to-needs ratios, and maternal depression, mothers who reported more sleep problems during pregnancy had infants with more sleep disturbances when they were one year old. Moreover, mothers who had later sleep timing (i.e., went to bed and woke up later, measured via actigraphy) during pregnancy had infants with more dysregulation (e.g., increased feeding difficulties, sensory sensitivities) and externalizing problems, and mothers with increased intra-daily variability in rest-activity rhythms (as measured via actigraphy) had infants with more externalizing problems. Findings suggest that maternal sleep and circadian rhythm disturbances during pregnancy may be a risk factor for infant sleep problems and socioemotional difficulties.

Variability in sleep architecture and alterations in circadian rhythms in patients with acute cerebral infarction accompanied by sleep-disordered breathing.

To continuously and dynamically monitor the sleep status of patients in the acute phase of cerebral infarction, and to investigate the characteristics of acute cerebral infarction(ACI)associated with sleep-disordered breathing (SDB), variations in sleep structure, and changes in sleep circadian rhythms. Patients with ACI within 48h of onset who were admitted to the Department of Neurology at Kailuan General Hospital from November 2020 to December 2022 were selected. Detailed baseline information such as age, gender, smoking history, drinking history, were recorded for the selected participants. From the beginning of their hospitalization, the selected participants were monitored for their sleep status continuously for 5 days using the Intelligent Mattress-based Sleep Monitoring Platform System(IMSMPS). Based on the heart rate data obtained from the monitoring, the interdaily stability (IS) and intradaily variability (IV) of the sleep circadian rhythm were calculated. 1,367 patients with ACI were selected. Monitoring results over 5 days indicated 147 cases (10.75%) without SDB, and 1,220 cases (89.25%) with SDB. Among the group with SDB, there were 248 cases (18.14%) with continuous mild SDB, 395 cases (28.90%) with moderate SDB, 295 cases (21.58%) with severe SDB, and 282 cases (20.63%) that fluctuated between different severity levels. Within this fluctuating group, 152 cases (53.90%) fluctuated between two severity levels, 120 cases (42.55%) between three levels, and 10 cases (3.55%) among all four levels. There were statistically significant differences (P < 0.05) in the sleep latency, sleep efficiency, non-rapid eye movement stages 1-2, rapid eye movement, proportion of non-rapid eye movement, proportion of rapid eye movement, wake after sleep onset, time out of bed, number of awakenings, respiratory variability index, and heart rate variability index among patients with ACI monitored from day 1 to 5. However, other monitored sleep structure parameters did not show statistically significant differences (P > 0.05). The coefficient of variation for all sleep monitoring parameters ranged between 14.54 and 36.57%. The IV in the SDB group was higher than in the group without SDB (P < 0.05), and the IS was lower than in the group without SDB (P < 0.05). Patients in the acute phase of cerebral infarction have a high probability of accompanying SDB. The sleep structure of these patients shows significant variability based on the onset time of the stroke, and some patients experience fluctuations among different severity levels of SDB. ACI accompanied by SDB can further reduce the IS of a patient's sleep circadian rhythm and increase its IV.

Rest-Activity Rhythm Differences in Acute Rehabilitation Between Poststroke Patients and Non-Brain Disease Controls: Comparative Study.

Circadian rhythm disruptions are a common concern for poststroke patients undergoing rehabilitation and might negatively impact their functional outcomes. Our research aimed to uncover unique patterns and disruptions specific to poststroke rehabilitation patients and identify potential differences in specific rest-activity rhythm indicators when compared to inpatient controls with non-brain-related lesions, such as patients with spinal cord injuries. We obtained a 7-day recording with a wearable actigraphy device from 25 poststroke patients (n=9, 36% women; median age 56, IQR 46-71) and 25 age- and gender-matched inpatient control participants (n=15, 60% women; median age 57, IQR 46.5-68.5). To assess circadian rhythm, we used a nonparametric method to calculate key rest-activity rhythm indicators-relative amplitude, interdaily stability, and intradaily variability. Relative amplitude, quantifying rest-activity rhythm amplitude while considering daily variations and unbalanced amplitudes, was calculated as the ratio of the difference between the most active 10 continuous hours and the least active 5 continuous hours to the sum of these 10 and 5 continuous hours. We also examined the clinical correlations between rest-activity rhythm indicators and delirium screening tools, such as the 4 A's Test and the Barthel Index, which assess delirium and activities of daily living. Patients who had a stroke had higher least active 5-hour values compared to the control group (median 4.29, IQR 2.88-6.49 vs median 1.84, IQR 0.67-4.34; P=.008). The most active 10-hour values showed no significant differences between the groups (stroke group: median 38.92, IQR 14.60-40.87; control group: median 31.18, IQR 18.02-46.84; P=.93). The stroke group presented a lower relative amplitude compared to the control group (median 0.74, IQR 0.57-0.85 vs median 0.88, IQR 0.71-0.96; P=.009). Further analysis revealed no significant differences in other rest-activity rhythm metrics between the two groups. Among the patients who had a stroke, a negative correlation was observed between the 4 A's Test scores and relative amplitude (ρ=-0.41; P=.045). Across all participants, positive correlations emerged between the Barthel Index scores and both interdaily stability (ρ=0.34; P=.02) and the most active 10-hour value (ρ=0.42; P=.002). This study highlights the relevance of circadian rhythm disruptions in poststroke rehabilitation and provides insights into potential diagnostic and prognostic implications for rest-activity rhythm indicators as digital biomarkers.

Sleep, 24-Hour Activity Rhythms, and Subsequent Amyloid-β Pathology

Sleep disturbances are common among older adults and have been associated with the development of Alzheimer disease (AD), such as amyloid-β (Aβ) pathology. For effective AD prevention, it is essential to pinpoint the specific disturbances in sleep and the underlying 24-hour activity rhythms that confer the highest risk of Aβ deposition. To determine the associations of 24-hour activity rhythms and sleep with Aβ deposition in adults without dementia, to evaluate whether disrupted 24-hour activity and sleep may precede Aβ deposition, and to assess the role of the apolipoprotein E ε4 (APOE4) genotype. This was an observational cohort study using data from the Rotterdam Study. Of 639 participants without dementia who underwent Aβ positron emission tomography (PET) from September 2018 to November 2021, 319 were included in the current study. Exclusion criteria were no APOE genotyping and no valid actigraphy data at the baseline visits from 2004 to 2006 or from 2012 to 2014. The mean (SD) follow-up was 7.8 (2.4) years. Data were analyzed from March 2023 to April 2024. Actigraphy (7 days and nights, objective sleep, and 24-hour activity rhythms), sleep diaries (self-reported sleep), Aβ42/40, phosphorylated tau (p-tau)181 and p-tau217 plasma assays, 18F-florbetaben PET (mean standard uptake value ratio [SUVR] in a large cortical region of interest), and APOE4 genotype. Association of objective and self-reported sleep and 24-hour activity rhythms at baseline with brain Aβ PET burden at follow-up. The mean (range) age in the study population was 61.5 (48-80) years at baseline and 69.2 (60-88) years at follow-up; 150 (47%) were women. Higher intradaily variability at baseline, an indicator of fragmented 24-hour activity rhythms, was associated with higher Aβ PET burden at follow-up (β, 0.15; bootstrapped 95% CI, 0.04 to 0.26; bootstrapped P = .02, false discovery rate [FDR] P = .048). APOE genotype modified this association, which was stronger in APOE4 carriers (β, 0.38; bootstrapped 95% CI, 0.05 to 0.64; bootstrapped P = .03) compared to noncarriers (β, 0.07; bootstrapped 95% CI, -0.04 to 0.18; bootstrapped P = .19). The findings remained largely similar after excluding participants with AD pathology at baseline, suggesting that a fragmented 24-hour activity rhythm may have preceded Aβ deposition. No other objective or self-reported measure of sleep was associated with Aβ. Among community-dwelling adults included in this study, higher fragmentation of the 24-hour activity rhythms was associated with greater subsequent Aβ burden, especially in APOE4 carriers. These results suggest that rest-activity fragmentation could represent a modifiable risk factor for AD.

Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index (ABI) metric, a transformation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}, and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}. Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical use in a large dataset.

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study.

The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

Behavioral-Social Rhythms and Cardiovascular Disease Risk in Retired Night Shift Workers and Retired Day Workers.

Stability in the timing of key daily routine behaviors such as working/doing housework, sleeping, eating, and engaging in social interactions (i.e., behavioral-social rhythms) contributes to health. This study examined whether behavioral-social rhythms were associated with cardiovascular disease (CVD) risk factors in retired night shift workers and retired day workers and explored whether past night shift work exposure moderated this association. A total of 154 retired older adults participated in this study. Multiple logistic regression models were used to examine associations between behavioral-social rhythms and CVD risk factors. Independent variables included Social Rhythm Metric (SRM)-5 score and actigraphy rest-activity rhythm intradaily variability (IV) and interdaily stability (IS). Dependent variables were metabolic syndrome prevalence and its five individual components. More regular behavioral-social rhythms were associated with lower odds of prevalent metabolic syndrome (SRM: odds ratio [OR] = 0.57, 95% confidence interval [CI] = 0.35-0.88; IV: OR = 4.00, 95% CI = 1.86-8.58; IS: OR = 0.42, 95% CI = 0.24-0.73) and two of its individual components: body mass index (SRM: OR = 0.56, 95% CI = 0.37-0.85; IV: OR = 2.84, 95% CI = 1.59-5.07; IS: OR = 0.42, 95% CI = 0.26-0.68) and high-density lipoprotein cholesterol (SRM: OR = 0.49, 95% CI = 0.30-0.80; IV: OR = 2.49, 95% CI = 1.25-4.96; IS: OR = 0.35, 95% CI = 0.19-0.66). Past shift work history did not moderate the association between behavioral-social rhythms and metabolic syndrome. Behavioral-social rhythms were related to CVD risk factors in retired adults regardless of prior night shift work exposure. Older retired workers may benefit from education and interventions aiming to increase behavioral-social rhythm regularity.

Objectively assessed sleep quality parameters in Multiple Sclerosis at home: Association to disease, disease severity and physical activity

BackgroundMultiple Sclerosis (MS) is a chronic inflammatory autoimmune, neurodegenerative disease that affects regular mobility and leads predominantly to physical disability. Poor sleep quality, commonly reported in MS patients, impacts their physical activity (PA). Accelerometers monitor 24-h activity patterns, offering insights into disease progression in daily life. ObjectiveTo test if the sleep quality variables of MS patients, as assessed with wrist-worn accelerometers, differ from those of controls and are associated with PA and disease severity variables. MethodsSeven-day raw accelerometer data collected from 40 MS patients and 24 controls was processed using an open-source GGIR package, from which variables of sleep quality (sleep efficiency, wake after sleep onset (WASO), sleep regularity index (SRI), intradaily variability (IV)) and PA (of different intensities: inactivity, light (LPA), moderate (MPA), vigorous (VPA)) were analyzed. The variables were compared between the two study groups and in MS patients, correlation tested associations among the variables of sleep quality, PA, and disease severity (assessed with the Expanded Disability Status Scale, EDSS). ResultsSleep efficiency was the only variable that differed significantly between MS patients and controls (lower in MS, p = 0.01). Both SRI (positively) and IV (negatively) correlated with the time spent in LPA and MPA. WASO correlated negatively with inactivity. ConclusionThis is one of the few studies with a wrist-worn accelerometer that shows a difference in sleep efficiency between MS patients and controls and, in MS, an association of sleep quality variables with PA variables.

Associations of 24-Hour Rest-Activity Rhythm Fragmentation, Cognitive Decline, and Postmortem Locus Coeruleus Hypopigmentation in Alzheimer's Disease.

While studies suggested that locus coeruleus (LC) neurodegeneration contributes to sleep-wake dysregulation in Alzheimer's disease (AD), the association between LC integrity and circadian rest-activity patterns remains unknown. Here, we investigated the relationships between 24-hour rest-activity rhythms, cognitive trajectories, and autopsy-derived LC integrity in older adults with and without cortical AD neuropathology. This retrospective study leveraged multi-modal data from participants of the longitudinal clinical-pathological Rush Memory and Aging Project. Indices of 24-hour rest-activity rhythm fragmentation (intradaily variability) and stability (interdaily stability) were extracted from annual actigraphic recordings, and cognitive trajectories were computed from annual cognitive evaluations. At autopsy, LC neurodegeneration was determined by the presence of hypopigmentation, and cortical AD neuropathology was assessed. Contributions of comorbid pathologies (Lewy bodies, cerebrovascular pathology) were evaluated. Among the 388 cases included in the study sample (age at death = 92.1 ± 5.9 years; 273 women), 98 (25.3%) displayed LC hypopigmentation, and 251 (64.7%) exhibited cortical AD neuropathology. Logistic regression models showed that higher rest-activity rhythm fragmentation, measured up to ~7.1 years before death, was associated with increased risk to display LC neurodegeneration at autopsy (odds ratio [OR] = 1.46, 95% confidence interval [CI95%]: 1.16-1.84, pBONF = 0.004), particularly in individuals with cortical AD neuropathology (OR = 1.56, CI95%: 1.15-2.15, pBONF = 0.03) and independently of comorbid pathologies. In addition, longitudinal increases in rest-activity rhythm fragmentation partially mediated the association between LC neurodegeneration and cognitive decline (estimate = -0.011, CI95%: -0.023--0.002, pBONF = 0.03). These findings highlight the LC as a neurobiological correlate of sleep-wake dysregulation in AD, and further underscore the clinical relevance of monitoring rest-activity patterns for improved detection of at-risk individuals. ANN NEUROL 2024;95:653-664.

Is rest-activity rhythm prospectively associated with all-cause mortality in older people regardless of sleep and physical activity level? The 'Como Vai?' Cohort study.

This study aims to test the association of rest-activity rhythm (intradaily variability and interdaily stability) with all-cause mortality in an older adult cohort in Brazil. It also assesses whether the amount of time spent at each intensity level (i.e., physical activity and nocturnal sleep) interferes with this association. This cohort study started in 2014 with older adults (≥60 years). We investigated deaths from all causes that occurred until April 2017. Rest-activity rhythm variables were obtained using accelerometry at baseline. Intradaily variability indicates higher rhythm fragmentation, while interdaily stability indicates higher rhythm stability. Cox proportional-hazard models were used to test the associations controlling for confounders. Among the 1451 older adults interviewed in 2014, 965 presented valid accelerometry data. During the follow-up period, 80 individuals died. After adjusting the analysis for sociodemographic, smoking, morbidity score, and number of medicines, an increase of one standard deviation in interdaily stability decreased 26% the risk of death. The adjustment for total sleep time and inactivity did not change this association. On the other hand, the association was no longer significant after adjusting for overall physical activity and moderate to vigorous physical activity. Rest-activity rhythm pattern was not associated with mortality when physical activity was considered, possibly because this pattern could be driven by regular exercise. Promoting physical activity remains a relevant strategy to improve population health.

Associations of Circadian Rest-Activity Rhythms With Affect and Cognition in Community-Dwelling Stroke Survivors: An Ambulatory Assessment Study

Background Rest-activity rhythm (RAR) is a modifiable behavioral factor associated with affect and cognition. Identifying RAR characteristics associated with affect and cognition among stroke survivors provides insight into preventing poststroke affective and cognitive impairment. Objective To examine the associations of RAR characteristics with affect and cognition among community-dwelling stroke survivors. Methods Forty participants with mild stroke (mean age = 52.8; 42.5% female; 55% White) reported their affect and cognitive complaints using ecological momentary assessment and wore an accelerometer for 7 consecutive days and completed the National Institutes of Health Toolbox Cognition Battery. RAR characteristics were extracted using parametric and non-parametric approaches. Multivariable linear regressions were used to identify RAR characteristics associated with affect and cognition. Results Later onset of rest (B = 0.45; P = .008) and activity (B = 0.36; P = .041) were positively associated with depressed affect. These associations were reversed for cheerful effect (rest onset: B = −0.42; P = .017; activity onset: B = −0.39; P = .033). Cheerful affect was also positively associated with relative amplitude (ie, distinctions in activity levels between rest and activity; B = .39; P = .030). Intra-daily variability (ie, RAR fragmentation; B = 0.35; P = .042) and later onset of activity (B = .36; P = .048) were positively associated with cognitive complaints. Less erratic RAR was positively associated with fluid cognition (B = 0.29; P = .036); RAR fragmentation was positively associated with crystallized cognition (B = 0.39; P = .015). Conclusions We identified RAR correlates of affect and cognition among stroke survivors, highlighting the value of managing RAR and sleep in stroke rehabilitation. Future studies should test whether advancing the onset of rest and activity, promoting a regular active lifestyle, and improving rest and sleep in the nighttime protect stroke survivors from affective and cognitive impairment.