Frailty is characterized by diminished resilience to stressor events. It is associated with adverse future health outcomes and impedes healthy aging. The circadian system orchestrates ~24-h rhythms in bodily functions in synchrony with the day-night cycle, and disturbed circadian regulation plays an important role in many age-related health consequences. We investigated prospective associations of circadian disturbances with incident frailty in over 1000 older adults who had been followed annually for up to 16 years. We found that decreased rhythm strength, reduced stability, or increased variation were associated with a higher risk of incident frailty and faster progress of frailty over time. Perturbed circadian rest-activity rhythms may be an early sign or risk factor for frailty in older adults.

Background: Disturbed sleep patterns are common among older adults and may contribute to cognitive and physical declines. However, evidence for the relationship between sleep duration and cognitive frailty, a concept combining physical frailty and cognitive impairment in older adults, is lacking. Objective: This study aimed to examine the associations of sleep duration and its changes with cognitive frailty. Methods: We analyzed data from the 2008‐2018 waves of the Chinese Longitudinal Healthy Longevity Survey. Cognitive frailty was rendered based on the modified Fried frailty phenotype and Mini-Mental State Examination. Sleep duration was categorized as short (9 h). We examined the association of sleep duration with cognitive frailty status at baseline using logistic regressions and with the future incidence of cognitive frailty using Cox proportional hazards models. Restricted cubic splines were used to explore potential nonlinear associations. Results: Among 11,303 participants, 1298 (11.5%) had cognitive frailty at baseline. Compared to participants who had moderate sleep duration, the odds of having cognitive frailty were higher in those with long sleep duration (odds ratio 1.71, 95% CI 1.48‐1.97; P<.001). A J-shaped association between sleep duration and cognitive frailty was also observed (P<.001). Additionally, during a mean follow-up of 6.7 (SD 2.6) years among 5201 participants who were not cognitively frail at baseline, 521 (10%) participants developed cognitive frailty. A higher risk of cognitive frailty was observed in participants with long sleep duration (hazard ratio 1.32, 95% CI 1.07‐1.62; P=.008). Conclusions: Long sleep duration was associated with cognitive frailly in older Chinese adults. These findings provide insights into the relationship between sleep duration and cognitive frailty, with potential implications for public health policies and clinical practice.

Background: Circadian function is altered with aging, leading to changes in the ∼24‐h rhythms of behavior and physiology. Based on circadian rest‐activity rhythms (CRAR), we previously constructed a biological age biomarker to characterize the aging profile of circadian function—circadian age (CircAge)—in older adults (>65 years) and showed its association with risk of Alzheimer’s dementia. Here, we constructed CircAge in middle‐to‐older‐aged adults and tested whether it predicts all‐cause dementia.Method: Participants from the UK Biobank with valid actigraphy data were studied (n = ∼97,000; 42‐78 years old). We developed a machine‐learning‐based regression model with 23 CRAR features derived from actigraphy (using cosinor, nonparametric, uniform‐phase‐empirical‐mode‐decomposition, and detrended‐fluctuation analyses). The fitting target was chronological age (ChrAge), and the prediction output was defined as CircAge. Model parameters were optimized using cross validation on 47,234 participants not performing shift work and without mental/behavioral or nervous system diseases. The optimized model was applied to all dementia‐free participants with valid CRAR (n = 80,805) to obtain their CircAge.Result: CircAge was 1.03±0.01 years older per one‐year older in ChrAge that explained ∼25% of the variance of CircAge (p<0.0001). Male sex, European ethnicity, or having mental/behavioral/nervous system diseases were associated with a greater CircAge (all p<0.0001). We compared CircAge of current shift workers (n = 6,389) with that of matched non‐shift workers to examine whether CircAge captures CRAR perturbations and found that CircAge of current shift workers was 1.1±0.2 years greater (p<0.0001) than non‐shift workers. We then associated the difference between CircAge and ChrAge (DCC, = CircAge‐ChrAge) to incident all‐cause dementia using a Cox proportional hazards model adjusting for ChrAge, sex, ethnic groups, mental/behavioral diseases, and nervous system diseases. Results showed that greater DCC predicted higher adjusted risk of all‐cause dementia (n = 451): each decade higher DCC corresponding to a 1.10‐fold higher risk (95% CI: 1.02‐1.18; p = 0.009).Conclusion: CRAR patterns can be translated into a biological aging biomarker for circadian function (CircAge), and greater CircAge than ChrAge is independently associated with risk of dementia in middle‐to‐older‐aged adults. Future studies are warranted to examine the use of CircAge (and/or in combination with other risk markers) for identifying at‐risk individuals in a clinical setting.

Background: Delirium is a common neurological complication in older adults after a major illness or surgery and is characterized by acute dysfunction in cognition, attention, and awareness. Once diagnosed, it is associated with an increased risk for dementia. Frailty is an age‐related syndrome and is associated with poorer postoperative outcomes, and is an emerging risk factor for delirium. The current study aimed to examine the association between frailty and delirium risk in middle‐ to older‐aged adults.Method: We examined frailty and incident delirium in 389,040 UK Biobank participants (38‐73 years old; 178,377 females) were hospitalized at least once during follow‐up. Frailty at baseline was assessed using two validated measures: (1) frailty phenotype (FP) that is identified when three or more of the following five criteria were fulfilled: self‐reported weight loss, exhaustion, low physical activity, slow walking pace, and low grip strength; (2) frailty index (FI: range 0‐1) that is calculated from 49 items covering health, presence of diseases and disabilities, and mental well‐being (FI score ≥0.24 indicating frailty). A new onset of delirium was obtained from hospitalization records using ICD‐10 F05 coding. Cox proportional hazards models assessed the association between frailty and delirium.Result: At baseline, 4.3% (15,311/359,979) and 5.2% (20,061/389,040) were identified as frail cases using FP and FI, respectively. The participants had been followed for a median of 12 years, with 6,710 newly developed delirium cases. Compared with non‐frail participants based on FP, participants with frailty were at a higher risk for delirium after adjusting for age, sex, ethnicity, and education (Hazard ratio [HR] = 3.22, 95% CI = 2.97‐3.49, p<0.0001). Similar results were observed based on FI, i.e., frail participants had an adjusted HR of 2.79 (95% CI = 2.59‐3.00, p<0.0001) for delirium compared with non‐frail participants. These observations were consistent after further adjusting for social economic status, body mass index, sleep duration, smoking, and alcohol consumption (HR = 2.48, 95% CI = 2.28‐2.70 for FP; HR = 2.17, 95% CI = 2.01‐2.35 for FI, both p values <0.0001).Conclusion: Frailty predicted delirium in middle‐ to older‐aged adults. Assessment and management of frailty may help with risk stratifications for delirium.