The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences

Background Wearable heart rate (HR) monitors collect minute-level HR continuously across days, yet these data are commonly reduced to scalars such as resting HR (RHR) and heart rate reserve (HRR), defined as the difference between maximum HR and RHR. This discards two dimensions of within-day HR dynamics: how HR range varies across the day and the magnitude and duration of individual HR rises and declines. We introduce diurnal heart rate range (dHRR), a time-of-day-specific measure of HR range across repeated days, and heart rate excursions (HREs), individual HR rises and declines characterized by amplitude and duration. Methods We analyzed minute-level HR from 750 participants in the Baltimore Longitudinal Study of Aging (mean [SD] age, 66 [12] years). We estimated the 5th, 50th, and 95th HR percentiles at each minute of the 24-hour cycle across repeated days, defining diurnal HR (dHR) as the median curve and dHRR as the 95th minus 5th percentile curve. A moving-average algorithm segmented HR into HREs. Function-on-scalar regression modeled dHR and dHRR by age, sex,and BMI across the day; local polynomial regression examined age and sex differences in HRR and HREs. Results Conventional HRR decreased with age, indicating a smaller overall observed HR range. Age-related differences in dHR varied substantially across the day: between ages 40 and 80, fitted dHR was approximately 2 bpm lower at 3:00 AM but 8 bpm lower at 6:00 PM. dHRR showed that this contraction was not uniform across the day: the evening peak near 6:00 PM at younger ages was largely absent by age 70, while the morning peak shifted from approximately 9:00 AM toward noon. At the event level, HREs showed two parallel age-related changes: between ages 40 and 80, mean excursion amplitude decreased from approximately 40 to 32 bpm, while mean excursion duration increased from approximately 90 to 104 minutes. Conclusions Aging was characterized by a smaller global HR range, compression and reorganization of HR range across the day, and smaller, longer-lasting HREs. dHRR and HREs provide complementary views of the diurnal organization and event-level dynamics of wearable HR and are implemented in the open-source ihr R package.

Background: Frailty is a prominent risk factor for dementia. Early detection of at-risk individuals may enable intervention to prevent or slow dementia pathology. Blood-based biomarker discovery could offer a path for early detection of frailty and cognitive decline. Methods: Older adults at risk of dementia underwent comprehensive multi-disciplinary assessment at the Healthy Brain Ageing (HBA) clinic, including geriatric, neurophysiological and mood evaluations, in addition to providing a fasted blood sample. Clinical data were used to calculate a deficit accumulation frailty index (FI) score. Additional cohorts attended either one (n=118) or two (n=73) subsequent visits over an average period of 4 years. Untargeted metabolomics was performed on plasma samples, and metabolites were clustered by similarity. Linear regression was used to assess association of clusters with FI. Finally, change in plasma abundance over time was assessed. Results: At assessment, participants had a mean (SD) age of 68.10 (8.07) years; 72.2% were female. Hierarchical clustering identified 10 clusters of metabolites, of which 6 were significantly associated with FI (p<0.05) at baseline and contained similar classes of metabolite. Differential abundance analysis found unique temporal regulation of metabolite abundance in each cluster, but across clusters severity of frailty impacted direction of change in plasma abundance over time. Conclusions: Frailty index was associated with carboxylic acids and derivatives, fatty acyls and organooxygen compounds across multiple clusters, and a large number of lipids were linked to frailty score, potentially implicating dysregulation of energy metabolism in the pathophysiology of frailty and forming a panel of predictive biomarkers of at risk patients.

Background Heart rate fragmentation (HRF) has emerged as a novel marker of sinoatrial instability and neuroautonomic dysregulation and is a predictor of incident cardiovascular disease (CVD) events and cardiovascular mortality. Leveraging heart rate fragmentation as a novel measure may help us better understand the prognostic significance of physical activity. Physical activity (PA) patterns are multidimensional and difficult to study holistically, however. We sought to examine for novel PA clusters in a cohort of veteran men and evaluate their prognostic significance based on their associations with neuroautonomic dysregulation. Methods In this cross-sectional study, we examined 602 male veterans from the Vietnam Era Twins Study of Electrophysiology in Posttraumatic Stress Disorder (VETS-EP) who were enrolled between 2022 and 2026. Accelerometry data were used to derive physical activity parameters across 6 domains: volume, sedentary behavior, intensity, diurnal pattern, fragmentation, and variability. Heart rate fragmentation was assessed using percentage of inflection points (PIP), inverse average length of segments (IALS), percentage of short segments (PSS), and percentage of alternating segments (PAS). Gaussian mixture models were used to derive digital phenotypes of physical activity, and associations with heart rate fragmentation were assessed using linear mixed models. Results Participants had a mean age of 73.8 {+/-} 2.9 years and 93.2% reported White race. Two overlapping phenotypes of physical activity patterns were identified: a compact-early phenotype, characterized by earlier activity timing and slightly greater overall activity, and a diffuse-late phenotype, characterized by later activity timing and greater heterogeneity in activity volume. In fully adjusted models, the diffuse-late phenotype was associated with higher PIP, the primary outcome ({beta}: 1.199, 95% CI: 0.034 to 2.363, p-value: 0.044), and higher IALS ({beta}: 0.01210, 95% CI: 0.00048 to 0.02373, p-value: 0.041), but not PSS or PAS, compared with the compact-early phenotype. Conclusions In older male veterans, Gaussian mixture model phenotyping identified two overlapping physical activity phenotypes, differing mainly in diurnal timing and in the dispersion of overall activity, that were associated with modest differences in heart rate fragmentation. These phenotypes provide a framework for capturing complex physical activity patterns. Future prospective studies representing diverse populations are needed to validate such phenotypes.

The effects of older age on the oxidation of energy substrates (carbohydrates, fats) over 24 hr and during activities of daily living (ADL) may have substantial implications for metabolic health. To examine this issue, we evaluated age-related differences in substrate oxidation for 24 hr and periods of sleep, ADLs, and a 30-min treadmill walk (30MTW, 1.3m{middle dot}s^-1) in 17 young (29 {+/-} 5 yr, mean {+/-} SD, 6F) and 16 older (72 {+/-} 5, 8F) healthy active adults. Oxygen consumption (&VdotO2) and carbon dioxide production were measured using a 32,500 L room calorimeter to quantify substrate oxidation, which was normalized to body mass (kJ{middle dot}kg^-1) and total energy expenditure (%). Separately, &VdotO2peak was measured during an incremental treadmill test to exhaustion. &VdotO2peak (ml{middle dot}kg^-1{middle dot}min^-1) was lower in older adults compared with young adults. Older adults oxidized fewer carbohydrates than young over 24 hr (kJ{middle dot}kg^-1, %), sleep (kJ{middle dot}kg^-1), and ADLs (kJ{middle dot}kg^-1, %); and fat oxidation was greater in older than young over 24 hr (kJ{middle dot}kg^-1, %) and ADLs (kJ{middle dot}kg^-1, %). Carbohydrate oxidation did not differ by group during the 30MTW (kJ{middle dot}kg^-1, %), but fat oxidation was greater in older (kJ{middle dot}kg^-1) despite their walking at a greater relative intensity. These results indicate that older adults derived oxidative energy differently than young over 24 hr and during daily tasks. The lower carbohydrate and greater fat contribution to daily energy requirements may be meaningful in the development of metabolic disease in older adults.

Study objectives: Aging is associated with increased sleep complaints and changes in sleep architecture, microstructure and rest-activity rhythms. Meditation-based interventions have shown benefits on subjective sleep quality, but their effects on objective sleep parameters remain largely underexplored. This study investigated the effects of an 18-month meditation intervention on sleep combining subjective (questionnaires) and objective (polysomnography and actigraphy) measures in older adults. Methods: A total of 120 cognitively unimpaired older adults ([&ge;]65 y) with minimal sleep complaint completed questionnaires, one week of actigraphy and in-home polysomnography at baseline, and again 18 months later. Following the baseline visit, participants were randomly assigned to one of 3 groups: meditation training, non-native language training (active control), or passive control. Group-by-visit interactions were examined using mixed-effects models for sleep questionnaires, actigraphy-derived metrics, sleep architecture and microstructure, including slow waves, spindles, and spectral power. Results: Compared to the passive control group only, meditation training was associated with greater ease of morning awakening (p=0.04). No significant intervention effects were observed for any other sleep parameter, including actigraphy- and polysomnography-derived measures. These findings remained unchanged after adjustment for depressive symptoms and trait anxiety. Conclusion: In cognitively unimpaired older adults, this 18-month meditation intervention yielded only limited improvements in subjective sleep assessment. Meditation may therefore have subtle effects on self-reported sleep quality in this healthy older population, although no effects on objective sleep measures were detected. Future studies should examine whether adapting the content, intensity, or timing of meditation practice and enrolling populations with clinically meaningful sleep disturbances or psychoaffective symptoms may yield greater benefits.

Background Attentional control declines with normal aging, yet the role of modifiable lifestyle factors in accelerating this decline remains incompletely characterised in large, diverse populations. We examined associations between four modifiable risk factors (smoking intensity, alcohol binge drinking, social satisfaction and blood pressure) and sustained attention performance in 13,866 adults drawn from the All of Us Research Program. Methods Cognitive performance was assessed using the Gradual-Onset Continuous Performance Task (GradCPT). A composite cognitive efficiency score was derived via principal component analysis of four GradCPT metrics: d' (perceptual sensitivity), response criterion, median reaction time and reaction time variability. Associations between cognitive efficiency and each risk factor were examined using multiple linear regression adjusted for age, sex and race/ethnicity. Effect sizes were expressed as age-equivalent years of cognitive aging (age-equivalent years = regression coefficient for the risk factor divided by the regression coefficient for age) to aid clinical interpretation. Results GradCPT performance declined progressively with age (p < 0.001). Social satisfaction emerged as the strongest lifestyle predictor: low social satisfaction was associated with approximately 5.8 additional age-equivalent years of cognitive aging relative to high social satisfaction. Smoking showed a dose-response pattern, with heavy smokers (> 20 cigarettes/day) exhibiting an approximately 5-year age-equivalent deficit versus never-smokers. Stage 2 hypertension showed a modest, non-significant negative association. Binge drinking showed limited significant associations, likely complicated by survivor and abstainer biases. Bootstrapped analyses of combined exposures showed that combinations of risk factors, particularly those involving low social satisfaction, produced larger cognitive deficits than expected under an additive model. Conclusions These findings support an interactive rather than a purely additive model of lifestyle-related cognitive vulnerability and highlight the GradCPT as a subclinical measure of attention-based cognitive risk in non-clinical populations. Keywords Cognitive aging, Sustained attention, GradCPT, Modifiable risk factors, Social isolation, Smoking, Hypertension, All of Us Research Program

Background: Circadian syndrome (CircS) comprises metabolic abnormalities, short sleep, and depressive symptoms, and is associated with cardiovascular, liver, and lung diseases and mortality; evidence on digestive disease is scarce. We assessed its association with incident non-neoplastic digestive disease in Chinese adults. Methods: In this prospective analysis of the China Health and Retirement Longitudinal Study (CHARLS), we included 2011 baseline participants aged >=45 years free of digestive disease, with follow-up to 2018. CircS (>=4 of 7 components) was analysed as a continuous score and as a binary exposure. Cox models estimated hazard ratios (HRs) adjusting for demographic factors, BMI, smoking, and alcohol use. We did dose-response, component, subgroup, and sensitivity analyses; hs-CRP mediation was explored. Findings: 907 (19.0%) of 4 771 participants developed digestive disease over a median 84 months. Each additional CircS component raised the risk by 9.1% (HR 1.091, 95% CI 1.041-1.144, P<0.001); CircS positivity (36.1%) was associated with a 25.7% higher risk (HR 1.257, 1.084-1.456, P=0.002). Risk rose approximately linearly to about 70% higher at 5-7 components. Short sleep (HR 1.178, 1.017-1.365) and depressive symptoms (HR 1.570, 1.367-1.803) were the only independently associated components; no metabolic component was associated. Results were robust across sensitivity analyses; hs-CRP did not mediate the association. Interpretation: CircS is associated with incident non-neoplastic digestive disease, driven by its circadian-emotional rather than metabolic components. Sleep and mood may be targets for prevention. Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Keywords: circadian syndrome; digestive diseases; cohort study; sleep; depression; brain-gut axis

Objectives: To evaluate change in physical function and probable sarcopenia following a 36-week community multicomponent exercise programme (Vivifrail model) across two consecutive cycles, and to assess the consistency of this change between cohorts. Study design: Quasi-experimental, single-arm, repeated-measures service evaluation. Ninety-two older adults (2025-2026 cohort; mean age 75.9 years, 88.0% women) completed baseline and post-intervention assessments; an independent 2024-2025 cohort (n = 86) was analysed jointly for replication (n = 178). Main outcome measures: Short Physical Performance Battery (SPPB) score (primary); Timed Up and Go (TUG), handgrip strength, 6-metre walk time and Mini-Mental State Examination (MMSE) (secondary); probable sarcopenia (EWGSOP2), SPPB-based frailty category, and a fall-risk indicator computed identically in both cohorts. Results: SPPB improved by a mean of 1.33 points (Cohen's d = 0.96; p < .001), with concordant improvement in all four secondary outcomes (all q < .005). 72.8% reached the substantial minimal clinically important difference. Probable sarcopenia fell from 17.4% to 5.4% (p = .006), and frailty category shifted toward higher functional levels (p < .001). Effect sizes were consistent between cohorts for SPPB, handgrip and 6-metre walk; the Time x Cohort interaction was significant for TUG only. In the pooled sample, elevated fall risk fell from 19.7% to 11.2% (p = .002). Conclusions: A 36-week multicomponent exercise programme was associated with clinically meaningful, reproducible improvement in physical function and a reduction in probable sarcopenia across two independent cohorts. The single-arm design precludes causal inference.

Background: Associations of sleep duration and insomnia symptoms with cognitive decline are inconsistent, and whether they represent modifiable risk factors or early manifestations of neurodegeneration may depend on life stage. We examined how sleep-cognition associations vary with age (44 to >90 years). Methods: We studied 16,884 participants from three cohorts with harmonised measures. In the English Longitudinal Study of Ageing (ELSA: n=9,473, median age 64, range 50 to >=90), linear mixed-effects models examined age-specific differences in cognitive change (recall and fluency) associated with sleep duration, difficulty falling asleep, nocturnal awakenings, incorporating sleep-by-age-by-time interactions, with initial adjustment for sociodemographic factors and further adjustment for health and lifestyle factors. Sleep characteristics showing consistent age-dependent associations in ELSA were further evaluated in Whitehall II (n=5,580, median age 55, range 44 to 68) and the Rush Memory and Aging Project (MAP: n=1,831, median age 80, range 53 to 102). Findings: In ELSA, difficulty falling asleep >=1 time/week (vs <1 time/week) was associated with less favourable 5-year change in recall at age 50 (difference -0.12 SD, 95% CI -0.20 to -0.04), with the association attenuating and reversing towards more favourable change at older ages (p-interaction=0.009 [linear], 0.016 [quadratic]). These persisted after further adjustment for health and lifestyle factors. Short sleep (<=6 h) showed similar patterns that attenuated after further adjustment. Similar age gradients were observed for difficulty falling asleep in Whitehall II and MAP. There was no evidence of age modification on long sleep and nocturnal awakenings. Interpretation: The cognitive implications of sleep disturbances vary by life stage. In midlife, difficulty falling asleep was associated with faster cognitive decline, supporting its role as a modifiable risk factor. In advanced age, the reversal is consistent with diminished arousal capacity accompanying prodromal dementia. Funding: US National Institute on Aging

Background: Mitochondrial dysfunction is a hallmark of ageing and is implicated in the pathogenesis of sarcopenia. Genetically confirmed mitochondrial disease provides a biologically definitive model of impaired oxidative phosphorylation against which novel functional assessments can be validated. We investigated whether a brief, submaximal, non-ischaemic intermittent isometric handgrip exercise protocol combined with Near Infra-Red Spectroscopy (NIRS) could detect distinct muscle oxygenation signatures in mitochondrial disease and sarcopenia. Methods: Adults with genetically confirmed mitochondrial disease (n=10, 7 female) and group-matched controls (n=19, 11 female), underwent assessment of maximal grip force, handgrip relaxation kinetics and a 3-minute intermittent submaximal isometric handgrip test (40% maximal voluntary contraction, 1Hz contraction/relaxation) with continuous force recording at 2000Hz and simultaneous NIRS. Findings were compared with 23 community-dwelling older adults from the Muscle Ageing and Sarcopenia Study (MASS) Lifecourse cohort (n=23, 13 female) including seven with probable or confirmed sarcopenia according to European Working Group on Sarcopenia in Older People (EWGSOP2) criteria. Results: Participants with mitochondrial disease demonstrated an attenuated reduction in tissue saturation index (TSI) during exercise compared with controls (TSI % {middle dot} s150-180s: -59.9 {+/-} 94.5 vs -175.1 {+/-} 128.4; p=0.02). Total haemoglobin (THb) responses did not differ between groups (p=0.10). In contrast, participants with probable or confirmed sarcopenia showed exaggerated reduction in TSI compared with non-sarcopenic participants (TSI % {middle dot} s150-180s: -256.5 {+/-} 146.0 vs -121.2 {+/-} 95.2; p=0.05), while THb responses remained similar. The association between sarcopenia and TSI differed by sex (interaction coefficient -240, p=0.016), with greater TSI reductions observed in males with sarcopenia. Differences in TSI between mitochondrial disease and control groups were independent of age and sex. No statistically significant associations were observed between THb responses and age, sex or force production. Conclusions: A brief, non-ischaemic handgrip exercise protocol combined with NIRS identified divergent muscle oxygenation responses in mitochondrial disease and sarcopenia. The attenuated TSI response observed in genetically confirmed mitochondrial disease is consistent with impaired oxygen utilisation secondary to defective oxidative phosphorylation, whereas the exaggerated TSI reduction observed in sarcopenia suggests a distinct physiological mechanism, potentially involving impaired oxygen delivery, reduced muscle efficiency, or both. This portable and non-invasive approach has significant potential as a physiological biomarker for mechanistic studies and clinical trials in ageing and neuromuscular disease. More broadly, our findings demonstrate how biologically defined rare diseases can provide a powerful framework for interpreting mechanisms in common heterogeneous age-related conditions.

Neuropsychiatric symptoms (NPS) are highly prevalent in Mild Cognitive Impairment (MCI), conceptualized as an intermediate clinical state between normal aging and dementia. Although neuroimaging studies have reported associations between NPS and brain alterations in MCI, longitudinal evidence on NPS and their relationship with multimodal MRI measures remains limited. We aimed to investigate (1) longitudinal changes in NPS, volumetric assessment and measurement of regional cerebral blood flow (CBF) within the medial temporal lobe (MTL); (2) associations between longitudinal changes in MRI measures and NPS; (3) whether baseline MRI measures predicted longitudinal changes in NPS. Thirty individuals with MCI aged over 65 years were recruited, of whom eighteen followed up for a mean period of 29 {+/-} 8.9 months. There were significant reductions in total grey matter and white matter volumes, together with volume loss in the bilateral hippocampus, bilateral parahippocampal gyrus and right entorhinal cortex (pFDR[&le;]0.05) over the follow up period. Volume loss in the right parahippocampal gyrus was associated with increase in aggression (pFDR<0.01), and CBF increase in the right hippocampus and parahippocampal gyrus was associated with worsening in agitation (pFDR<0.01). Furthermore, lower baseline volume of the right entorhinal cortex was associated with increase in aggression, and lower baseline CBF in the right hippocampus and parahippocampal gyrus was associated with worsening of agitation (pFDR<0.05). Our findings highlight the importance of identifying NPS in individuals with MCI and the role of structural and perfusion MRI measures as promising biomarkers for monitoring disease progression and improving risk prediction of conversion to dementia.

Biological aging, the decline in physiological resilience that increases our vulnerability to disease and death as we grow older, can be measured from standard clinical-laboratory panels. Measurement of biological aging from laboratory data embedded in electronic health records (EHRs) could enhance precision healthcare. However, suitability of EHR-embedded laboratory records for this purpose is uncertain. We evaluated feasibility of EHR biological age measurement in a cohort of n=4,313 cardiothoracic-surgery patients at a large US Hospital and tested whether measured biological aging was associated with patient outcomes. Patients who were biologically older prior to surgery more often died or experienced adverse outcomes as compared to those measured to be biologically younger. Postoperative biological-aging trajectories were associated with length of intensive-care-unit (ICU) stays and in-hospital death. EHR laboratory data provide an opportunity for scalable implementation of biological aging measurement within healthcare systems, with potential to enhance patient monitoring and risk stratification.

Although physical activity is associated with better physical functioning, the effects of initiating regular physical activity among older adults with persistent inactivity remain unclear. We conducted a sequential target trial emulation using Health and Retirement Study (HRS) data to estimate the effect of physical activity initiation versus noninitiation on incident mobility difficulty. Participants were included in the analysis if they were aged [&ge;]65 years at the previous wave, reported no regular physical activity at the previous two waves, and had no mobility, activities of daily living (ADL), or instrumental activities of daily living (IADL) difficulties at baseline. Stabilized inverse probability of treatment weighting was applied to adjust for measured confounding. Weighted cumulative incidence was then estimated with death treated as a competing event, and risk differences were calculated at approximately 2, 4, and 6 years. At 2 years, the cumulative incidence of mobility difficulty was 32.75% among initiators and 39.73% among noninitiators, with a risk difference of -6.98 percentage points (95% CI, -13.11 to -0.88). At 4 and 6 years, risk differences were -2.90 percentage points (95% CI, -9.77 to 4.29) and -5.44 percentage points (95% CI, -12.27 to 1.99), respectively. Initiating regular moderate or vigorous physical activity was associated with a lower risk of incident mobility difficulty at approximately 2 years among older adults with persistent inactivity. This difference was less evident at later follow-up, and no clear differences were observed for incident ADL or IADL difficulty.

Age-related decline in skeletal muscle function, often manifesting as slower gait speed, contributes significantly to frailty and loss of independence. To uncover the molecular basis of this decline, we investigated coordinated changes across the transcriptome, miRNome, and methylome in vastus lateralis muscle from female vervet monkeys (Chlorocebus aethiops sabaeus), contrasting middle-aged animals with normal gait speed versus older animals with declining gait speed. Through multi-omics integration, we identified a molecular signature that sharply distinguishes these two groups. This signature involves key regulatory molecules, including miR-181a-5p, miR-320b and miR-425 control of SYNCRIP, miR-193b-3p regulation of MCL1 and PLAU, as well as a multi-omic regulatory network governing ZNF274 and ANP32E gene expression, and altered levels of mRNAs such as VEZT. Functional annotation implicates miRNA signatures with inverse expression of their mRNA targets operating within systems of skeletal muscle biology, metabolism, and potential immune-inflammation mechanisms. Collectively, these findings reveal an interconnected network of epigenetic, post-transcriptional, and transcriptional alterations associated with impaired muscle function during aging. This molecular signature provides novel insights into potential mechanisms driving sarcopenia and highlights specific molecules as potential targets for interventions aimed at preserving muscle health.

Sleep disturbances compromise cognition, and overall physical and mental health; however, animal models of these effects remain limited, and typically impose more extreme disturbances than those experienced by humans. Here, we use behavioural interventions in mice to model two common types of sleep disruption: (1) sleep displacement associated with shiftwork and (2) sleep fragmentation associated with aging and disease. C57BL6/J mice were subjected to either a sleep deprivation protocol (n = 8, females = 4) or a fragmentation protocol (n = 8, females = 4), in which they were completely deprived of sleep or awoken every 2 min respectively, for 12 hours during their typical rest phase (lights-on) across 7 consecutive days. Age-matched control mice (n = 14, females = 7) remained undisturbed in their home cages. Activity during the 12-hour active phase was recorded via infrared motion sensors. After protocol completion, mice were injected with bromodeoxyuridine (BrdU, 200mg/kg) 2 hours prior to brain and blood collection; hippocampal neurogenesis and plasma corticosterone were then assessed. Results show that the sleep deprivation and fragmentation protocols had different, dynamic effects on behaviour; sleep deprivation was associated with an accumulating sleep need, operationalized as progressively reduced locomotor activity across the week, whereas fragmentation produced only an acute reduction of locomotor activity. Cell proliferation rates and corticosterone did not differ from controls. These protocols provide a foundation for future research into the mechanistic links between shiftwork and sleep fragmentation on health and cognition.

Reduced visibility is a common contributor to falls in older adults, but the neural processes that support safe locomotion under low lighting are not well established. In this study, 22 young (mean age = 22.5) and 20 older (mean age = 70.9) adults walked along a pathway under bright, ambient and dark lighting conditions while stepping over expected and unexpected obstacles projected on the floor. Mobile electroencephalography (EEG), combined with motion capture, was used to quantify spectral power changes during obstacle crossing preparation and the post-crossing phases, relative to a standing baseline. We identified that reduced lighting conditions elicited a widespread increase in cortical engagement, predominantly in the alpha band, during both preparation and reset phases. Obstacle negotiation recruited a distributed sensorimotor network, with reduced theta-alpha-beta desynchronisation during preparation and a robust post-movement beta rebound during the post-crossing reset phase. Expectation effects were modest, with unexpected obstacles inducing greater transient alpha-beta desynchronisation relative to expected obstacles, suggesting additional cortical resources are recruited under uncertainty. Age effects were minimal and limited to reduced frontal alpha desynchronisation in older adults compared to young adults during the preparation phase, possibly reflecting differences in walking speed rather than differences in neural control. In conclusion, environmental features such as low lighting and obstacle presence exert a stronger influence on cortical dynamics during walking than age and expectation effects alone. This provides a foundation for future work examining how these processes may differ in older adults at increased risk of falls.

Postmenopausal women are vulnerable to metabolic dysfunction. Compelling evidence suggests this is because they lack the protective effects of estrogens. We have shown that circulating estrogens regulate daily eating and activity rhythms in female mice and protect them from obesity and metabolic dysfunction. However, few studies have investigated whether postmenopausal women have disrupted eating and sleep-activity rhythms that could contribute to metabolic dysfunction. The purpose of this cross-sectional study was to investigate the relationship between sleep and eating rhythms and metabolic risk in postmenopausal women with overweight or obesity. Seven days of sleep and food intake behavior data were collected from postmenopausal women with overweight or obesity. Sleep timing was assessed using wrist-worn actigraphy and sleep logs. First and last calorie intake times were collected daily using text messaging. Visceral adipose tissue (DXA), insulin resistance (Matsuda index), blood pressure, and triglycerides were analyzed as markers of metabolic risk. In 122 postmenopausal women (mean {+/-} SD: 58.1 {+/-} 3.6 yr, 33.2 {+/-} 5.2 kg/m2 BMI), we found that later sleep onset was associated with greater visceral adipose tissue (p=0.0007), but not insulin resistance, blood pressure, or triglycerides. Next, we used a random forest model to quantify the relative contributions of sleep and meal timing variables to predict visceral adipose tissue. The top predictors of visceral adipose tissue were time of sleep onset, sleep duration, and time of last caloric intake. These data suggest that interventions that advance sleep onset may reduce metabolic risk in postmenopausal women.

Importance: Long-term exposure to higher average air pollutant concentrations is associated with poorer cognitive health, but annual averages can obscure substantial differences in day-to-day exposure. Whether recurrent high pollution days are associated with long-term cognitive aging trajectories among people with similar overall air pollution exposure is unclear. Objective: To determine whether the annual number of days exceeding World Health Organization daily guideline values for nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) is associated with subsequent cognitive decline after accounting for annual mean air pollutant exposure. Design: Prospective cohort study using data from waves 1-10 (2002-03 to 2021-23) of the English Longitudinal Study of Ageing. Setting: Population-based cohort of community-dwelling adults in England. Participants: 12,235 adults aged 50+ years at analytic baseline. Exposures: Number of days exceeding World Health Organization daily guideline values ('exceedance days') for NO2, PM2.5, and PM10, derived from residence-linked environmental estimates during the calendar year preceding the analytic baseline. Main Outcomes and Measures: Baseline cognitive performance and model-estimated 14-year cognitive decline (corresponding to the 75th percentile of follow-up duration) in episodic memory and verbal fluency. Results: Exceedance days were not associated with baseline memory or verbal fluency after adjustment for annual mean air pollutant exposure. More NO2 exceedance days were associated with faster cognitive decline: comparing the 75th percentile with the median of NO2 exceedance days, the difference in 14-year decline was -0.09 SD (95% CI, -0.17 to -0.01; p = 0.02) for memory and -0.10 SD (95% CI, -0.19 to 0.00; p = 0.04) for fluency. PM2.5 and PM10 exceedance days were not associated with cognitive decline. Conclusions and Relevance: In this cohort study of older adults, a higher number of NO2 exceedance days was associated with faster subsequent cognitive decline after adjustment for annual mean air pollutant exposure. This suggests that daily exposure to high NO2 concentrations may be related to accelerated cognitive aging even when offset by lower exposure on other days, potentially providing a new rationale for identifying and prioritizing areas with recurrent high NO2 exposure and the local emission sources contributing to it.

Background. Blood-based biological age clocks predict mortality well, but they are statistical composites. They do not say which physiological systems make a person biologically older, and they cannot say how an intervention would move the clock or whether moving it would change risk. Methods. We built IQN-BIOAGE-01, a quantitative systems pharmacology (QSP) model of mortality-referenced biological age. A systemic senescent load follows saturating-removal stochastic dynamics and drives eight latent organ/hallmark axes, which are observed through 13 routine blood, blood pressure and body size measurements. Death is the first passage of the load over a threshold lowered by poor organ reserve, and biological age (BAmech) is the age at which the reference population has the same 10year risk. The model was calibrated on NHANES III (14,049 adults; 2,736 deaths in 20 years) and tested on a locked NHANES IV 1999 2010 holdout (24,650 adults; 1,867 deaths). Two later versions were accepted or rejected by rules written before their validation results. We confronted the inflammation axis with three anti-inflammatory outcome trials, audited common implementations of the comparator clock, and locked a registration-ready external validation. Results. On the hold-out, Harrell's C was 0.842 for BAmech, 0.842 for PhenoAge and 0.823 for chronological age. The hazard ratio per SD of the biological age gap was 1.55 (1.48 1.62) for BAemech and 1.45 (1.40 1.50) for PhenoAge. Risk ordering transferred across eras (calibration slope 1.01 1.03), but absolute 10year risk was overpredicted (10.4% against 7.4% observed); life-table recalibration moved observed-to-expected from 0.72 to 0.81. The inflammation axis carried most of the gap. A joint re-estimate did not converge and a converged, biological-variation-anchored version narrowly failed its pre-written identifiability criterion, so v1.0 remains the locked primary. The outcome evidence available so far, chiefly topline results from one anti-inflammatory trial, suggested that only a small fraction of a pharmacological CRP fall may carry the risk implied by the model's cross-sectional structure (posterior median pass-through 0.22). Common software implementations of PhenoAge differed from the published formula by 0.7 2.0 years. Conclusions. A mechanistic model can match a leading statistical blood clock in discrimination while adding an organ-level decomposition, explicit statements of what the data can and cannot identify, and a structure in which interventions can be simulated. Because inflammation dominates blood-based biological age while lowering CRP with drugs may carry little of the implied risk, a change in a blood clock should not be read as a change in mortality risk without outcome evidence. Validation is Tier 1 (internal and temporal, within one survey programme); the external test is locked and awaiting data access.

Objective This study aimed to develop and validate a predictive model for sleep disorders in young and middle-aged adults with anemia, providing evidence for early identification, risk stratification, and individualized sleep management. Methods Data in the NHANES were analyzed and randomly divided into development and validation cohorts. LASSO regression was used to screen optimal predictors in the development cohort, followed by univariate and multivariate logistic regression to identify independent predictors and construct a nomogram. Model performance was evaluated using receiver operating characteristic curves, calibration curves, Brier scores, and decision curve analysis. Results The weighted prevalence of sleep disorders among young and middle-aged adults with anemia was 10.19%. Multivariate logistic regression identified seven independent predictors: sex, monocyte count, asthma, overweight, arthritis, congestive heart failure, and hypertension. The model showed good discrimination, with area under the curve values of 0.817 in the development cohort and 0.791 in the validation cohort. Calibration was satisfactory, with Brier scores of 0.074 and 0.075, respectively. Decision curve analysis indicated favorable clinical net benefit in both cohorts. Conclusion The proposed predictive model demonstrated good discrimination, calibration, and may help healthcare providers identify young and middle-aged adults with anemia who are at high risk for sleep disorders.