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BACKGROUND: This study focused on the relationship between adiposity and Rest-Activity Rhythms (RAR), utilizing both parametric cosine-based models and non-parametric algorithms. The emphasis was on the impact of varying measurement periods (7-28 days) on this relationship. METHODS: We retrieved actigraphy data from two datasets, encompassing a diverse cohort recruited from an obesity outpatient clinic and a workplace health promotion program. Participants were required to wear a research-grade wrist actigraphy device continuously for a minimum of four weeks. The final dataset included 115 individuals (mean age 40.7 ± 9.5 years, 51 % female). We employed both parametric and non-parametric methods to quantify RAR using six standard variables. Additionally, the study evaluated the correlations between three key adiposity indices - Body Mass Index (BMI), Visceral Adipose Tissue (VAT) area, and Body Fat Percentage (BF%) - and circadian rhythm indicators, controlling for factors like physical activity, age, and gender. RESULTS: The obesity group displayed a significantly lower relative amplitude (RA) as per non-parametric algorithm findings, with a decreased amplitude noted in the parametric algorithm analysis, in comparison to the overweight and control groups. The relationship between circadian rhythm indicators and adiposity metrics over 7- to 28-day periods was examined. A notable negative correlation was observed between RA and both BMI and VAT, while correlation coefficients between adiposity indicators and non-parametric circadian parameters increased with extended durations of actigraphy data. Specifically, RA over a 28-day period was significantly correlated with BF%, a trend not seen in the 7-day measurement (p = 0.094) in multivariate linear regression. The strength of the correlation between BF% and 28-day RA was more pronounced than that in the 7-day period (p = 0.044). However, replacing RA with amplitude as per parametric cosinor fitting yielded no significant correlations for any of the measurement periods. CONCLUSION: The study concludes that a 28-day measurement period more effectively captures the link between disrupted circadian rhythms and adiposity. Non-parametric algorithms, in particular, were more effective in characterizing disrupted circadian rhythms, especially when extending the measurement period beyond the standard 7 days.
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BACKGROUND: Circadian rhythm disruptions are a common concern for poststroke patients undergoing rehabilitation and might negatively impact their functional outcomes. OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
Asunto(s)
Ritmo Circadiano , Descanso , Rehabilitación de Accidente Cerebrovascular , Accidente Cerebrovascular , Humanos , Femenino , Masculino , Persona de Mediana Edad , Anciano , Rehabilitación de Accidente Cerebrovascular/métodos , Accidente Cerebrovascular/fisiopatología , Accidente Cerebrovascular/complicaciones , Ritmo Circadiano/fisiología , Actigrafía/métodos , Estudios de Casos y ControlesRESUMEN
OBJECTIVE: Rest-activity rhythm is an essential behavior for human health. However, the association between rest-activity rhythm and atherosclerotic cardiovascular disease (ASCVD) risk remains unclear. Therefore, this study aimed to elucidate the association. METHODS: This study included 87,039 participants from the UK Biobank who had 7-day accelerometry data and were free of ASCVD at baseline. Relative amplitude was calculated as the difference between the most active continuous 10-h period (M10) and the least active continuous 5-h period (L5) in 24 h, and lower relative amplitude indicated the disruption of rest-activity rhythm. Cox proportional hazard model was used to examine the association of relative amplitude with ASCVD. Further, the linear association between relative amplitude and arterial stiffness measurements, including arterial stiffness index (ASI) and carotid intima-media thickness (cIMT), was examined. RESULTS: During a mean follow-up period of 6.80 ± 1.10 years, 2798 ASCVD cases were identified. A dose-response relationship was observed between relative amplitude and ASCVD risk (P for trend<0.001). The adjusted hazard ratio, for the highest vs the lowest quintile of relative amplitude, was 1.54 (95 % confidence interval: 1.31, 1.79). Further, we found significant association of lower relative amplitude with ASI and cIMT. The onset timing of M10 at ≤06:00, 09:00, 10:00, or ≥11:00, as opposed to the reference time of 07:00, was associated with higher ASCVD risk. CONCLUSIONS: Low rest-activity rhythm amplitude was associated with a higher risk of ASCVD. Rest-activity rhythm amplitude may provide a method to identify individuals at risk of ASCVD in public health and clinical practice.