Osteoporotic Fractures In Men Study Research Articles

Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs.

Vertebral compression fractures may indicate osteoporosis but are underdiagnosed and underreported by radiologists. We have developed an ensemble of vertebral body (VB) segmentation models for lateral radiographs as a critical component of an automated, opportunistic screening tool. Our goal is to detect the approximate location of thoracic and lumbar VBs, including fractured vertebra, on lateral radiographs. The Osteoporotic Fractures in Men Study (MrOS) data set includes spine radiographs of 5994 men aged ≥65 years from 6 clinical centers. Two segmentation models, U-Net and Mask-RCNN (Region-based Convolutional Neural Network), were independently trained on the MrOS data set retrospectively, and an ensemble was created by combining them. Primary performance metrics for VB detection success included precision, recall, and F1 score for object detection on a held-out test set. Intersection over union (IoU) and Dice coefficient were also calculated as secondary metrics of performance for the test set. A separate external data set from a quaternary health care enterprise was acquired to test generalizability, comprising diagnostic clinical radiographs from men and women aged ≥65 years. The trained models achieved F1 score of U-Net = 83.42%, Mask-RCNN = 86.30%, and ensemble = 88.34% in detecting all VBs, and F1 score of U-Net = 87.88%, Mask-RCNN = 92.31%, and ensemble = 97.14% in detecting severely fractured vertebrae. The trained models achieved an average IoU per VB of 0.759 for U-Net and 0.709 for Mask-RCNN. The trained models achieved F1 score of U-Net = 81.11%, Mask-RCNN = 79.24%, and ensemble = 87.72% in detecting all VBs in the external data set. An ensemble model combining predictions from U-Net and Mask-RCNN resulted in the best performance in detecting VBs on lateral radiographs and generalized well to an external data set. This model could be a key component of a pipeline to detect fractures on all vertebrae in a radiograph in an automated, opportunistic screening tool under development.

Fall Trajectories in Older Men: Trajectories of Change by Age and Predictors for Future Fall Risk.

Very little is known about specific trajectories or patterns of falls over time. Using the well-characterized cohort of the Osteoporotic Fractures in Men Study (MrOS), we classified individuals by fall trajectories across age and identified predictors of group assignment based on characteristics at baseline. Using an analysis sample of 5976 MrOS participants and 15 years of follow-up data on incident falls, we used group-based trajectory models (PROC TRAJ in SAS) to identify trajectories of change. We assessed the association of baseline characteristics with group assignment using one-way analysis of variance (ANOVA) and chi-square tests. Multivariable logistic regression was used to analyze the outcome of the high risk fall trajectory groups compared to the low risk groups. Changes in rates of falls were relatively constant or increasing with five distinct groups identified. Mean posterior probabilities for all five trajectories were similar and consistently above 0.8 indicating reasonable model fit. Among the five fall trajectory groups, two were deemed high risk, those with steeply increasing fall risk and persistently high fall risk. Factors associated with fall risk included body mass index, use of central nervous agents, prior history of diabetes and Parkinson's disease, back pain, grip strength, and physical and mental health scores. Two distinct groups of high fall risk individuals were identified among five trajectory groups, those with steeply increasing fall risk and persistently high fall risk. Statistically significant characteristics for group assignment suggest that future fall risk of older men may be predictable at baseline.

Power-law properties of nocturnal arrhythmia avalanches: A novel marker for incident cardiovascular events

BackgroundBursting nonsustained cardiac arrhythmia events are a common observation during sleep. ObjectivesThe purpose of this study was to investigate the hypothesis that nocturnal arrhythmia episode durations could follow a power law, whose exponent could predict long-term clinical outcomes. MethodsWe defined “nocturnal arrhythmia avalanche” (NAA) as any instance of a drop in electrocardiographic (ECG) template-matched R-R intervals ≥30% of R-R baseline, followed by a return to 90% of baseline. We studied NAA in ECG recordings obtained from the Sleep Heart Health Study (SHHS), Osteoporotic Fractures in Men Study (MrOS) Study, and Multi-Ethnic Study of Atherosclerosis (MESA). The association of nocturnal arrhythmia durations with a power-law distribution was evaluated and the association of derived power-law exponents (α) with major adverse cardiovascular (CV) events and mortality assessed with multivariable Cox regression. ResultsA total of 9176 participants were studied. NAA episodes distribution was consistent with power-law vs comparator distributions in all datasets studied (positive log likelihood ratio of power-law vs exponential in MESA: 83%; SHHS: 69%; MrOS: 81%; power-law vs log-normal in MESA: 95%; SHHS: 35%; MrOS: 64%). The NAA power-law exponent (α) showed a significant association of with adverse CV outcomes (association with CV mortality: SHHS hazard ratio 1.39 [1.07–1.79], P = .012; MrOS hazard ratio 1.42 [1.02–1.94], P = .039; association with CV events: MESA HR 3.46 [1.46–8.21], P = .005) in multivariable Cox regression, after adjusting for conventional CV risk factors and nocturnal ectopic rate. ConclusionThe NAA power-law exponent is a reproducible, predictive marker for incident CV events and mortality.

Long-term Trajectories of Low Back Pain in Older Men: A Prospective Cohort Study With 10-Year Analysis of the Osteoporotic Fractures in Men Study.

Although low back pain (LBP) may persist or recur over time, few studies have evaluated the individual course of LBP over a long-term period, particularly among older adults. Based on data from the longitudinal Osteoporotic Fractures in Men (MrOS) Study, we aimed to identify and describe different LBP trajectories in older men and characterize members in each trajectory group. A total of 5 976 community-dwelling men (mean age = 74.2) enrolled at 6 U.S. sites were analyzed. Participants self-reported LBP (yes/no) every 4 months for a maximum of 10 years. Latent class growth modeling was performed to identify unique LBP trajectory groups that explained variation in the LBP data. The association of baseline characteristics with trajectory group membership was assessed using univariable and multivariable multinominal logistic regression. A 5-class solution was chosen; no/rare LBP (n = 2 442/40.9%), low frequency-stable LBP (n = 1 040/17.4%), low frequency-increasing LBP (n = 719/12%), moderate frequency-decreasing LBP (n = 745/12.5%), and high frequency-stable LBP (n = 1 030/17.2%). History of falls (OR = 1.52), history of LBP (OR = 6.37), higher physical impairment (OR = 1.51-2.85), and worse psychological function (OR = 1.41-1.62) at baseline were all associated with worse LBP trajectory groups in this sample of older men. These findings present an opportunity for targeted interventions and/or management to older men with worse or increasing LBP trajectories and associated modifiable risk factors to reduce the impact of LBP and improve quality of life.

Predictive value of sarcopenia components for all-cause mortality: findings from population-based cohorts

BackgroundLow grip strength and gait speed are associated with mortality. However, investigation of the additional mortality risk explained by these measures, over and above other factors, is limited.AimWe examined whether grip strength and gait speed improve discriminative capacity for mortality over and above more readily obtainable clinical risk factors.MethodsParticipants from the Health, Aging and Body Composition Study, Osteoporotic Fractures in Men Study, and the Hertfordshire Cohort Study were analysed. Appendicular lean mass (ALM) was ascertained using DXA; muscle strength by grip dynamometry; and usual gait speed over 2.4–6 m. Verified deaths were recorded. Associations between sarcopenia components and mortality were examined using Cox regression with cohort as a random effect; discriminative capacity was assessed using Harrell’s Concordance Index (C-index).ResultsMean (SD) age of participants (n = 8362) was 73.8(5.1) years; 5231(62.6%) died during a median follow-up time of 13.3 years. Grip strength (hazard ratio (95% CI) per SD decrease: 1.14 (1.10,1.19)) and gait speed (1.21 (1.17,1.26)), but not ALM index (1.01 (0.95,1.06)), were associated with mortality in mutually-adjusted models after accounting for age, sex, BMI, smoking status, alcohol consumption, physical activity, ethnicity, education, history of fractures and falls, femoral neck bone mineral density (BMD), self-rated health, cognitive function and number of comorbidities. However, a model containing only age and sex as exposures gave a C-index (95% CI) of 0.65(0.64,0.66), which only increased to 0.67(0.67,0.68) after inclusion of grip strength and gait speed.ConclusionsGrip strength and gait speed may generate only modest adjunctive risk information for mortality compared with other more readily obtainable risk factors.

Associations between longitudinal changes in sleep stages and risk of cognitive decline in older men.

To investigate the relationships between longitudinal changes in sleep stages and the risk of cognitive decline in older men. This study included 978 community-dwelling older men who participated in the first (2003-2005) and second (2009-2012) sleep ancillary study visits of the Osteoporotic Fractures in Men Study. We examined the longitudinal changes in sleep stages at the initial and follow-up visits, and the association with concurrent clinically relevant cognitive decline during the 6.5-year follow-up. Men with low to moderate (quartile 2, Q2) and moderate increase (Q3) in N1 sleep percentage had a reduced risk of cognitive decline on the modified mini-mental state examination compared to those with a substantial increase (Q4) in N1 sleep percentage. Additionally, men who experienced a low to moderate (Q2) increase in N1 sleep percentage had a lower risk of cognitive decline on the Trails B compared with men in the reference group (Q4). Furthermore, men with the most pronounced reduction (Q1) in N2 sleep percentage had a significantly higher risk of cognitive decline on the Trails B compared to those in the reference group (Q4). No significant association was found between changes in N3 and rapid eye movement sleep and the risk of cognitive decline. Our results suggested that a relatively lower increase in N1 sleep showed a reduced risk of cognitive decline. However, a pronounced decrease in N2 sleep was associated with concurrent cognitive decline. These findings may help identify older men at risk of clinically relevant cognitive decline.

0866 Prevalence of Obesity in Obstructive Sleep Apnea Within a Large Community-based Cohort of Middle-aged/Older Adults

Abstract Introduction Obesity is a well-known risk factor for obstructive sleep apnea (OSA), gaining interest due to the global rise in obesity and novel obesity drugs. The rationale behind this lies in the role of obesity in the pathophysiology of OSA. However, many OSA patients are non-obese, and the association between obesity and OSA may vary by age and sex. Past population studies largely reported the prevalence of OSA according to different obesity categories. In this study, we sought to determine the prevalence of obesity across different levels of OSA severity, age, and sex. Methods The analytic sample included individuals with OSA from the Sleep Heart Health Study (SHHS). OSA severity was quantified using the apnea-hypopnea index (AHI4; apneas plus hypopneas with at least 4% oxygen desaturation per hour). Individuals were stratified by the severity of OSA (mild: 5≤AHI4< 15; moderate: 15≤AHI4< 30; severe: AHI4≥30 events/hour), body mass index (BMI), age, and sex. Results A total of 2950 of 5749 participants in SHHS had OSA (AHI4≥5 events/hour; 1729/788/433 mild/moderate/severe). Of these, 40.6% were female; mean±SD age was 65.3±10.7 years; and median [interquartile range] BMI was 28.8 [25.8; 32.3] kg/m2. For those with any OSA, 60.6% were non-obese (BMI< 30 kg/m2) and 39.4% were obese (BMI≥30 kg/m2). Across OSA severities, 34.1% of mild, 42.6% of moderate and 54.3% of severe OSA were obese. A greater proportion of younger adults (< 65 years) with OSA were obese (48.3%) than older adults (≥65 years) with OSA (30.9%). In older adults 26.7% of mild, 34.5% of moderate and 40.3%of severe OSA were obese. Finally, a greater proportion of females with OSA were obese (43.6%) than males with OSA (36.5%). Conclusion The majority of middle-aged/older adults with OSA are non-obese. The association between obesity and OSA varies by age and sex, with a higher prevalence of obesity in younger adults and in females with OSA. Additional analyses of data from the Multi-Ethnic Study of Atherosclerosis, the Osteoporotic Fractures in Men study, and the HypnoLaus study are being conducted to establish the association between OSA and obesity within other community-based samples. Support (if any) NHLBI R01HL153874, R35HL135818 and unrestricted grant support from Apnimed.

Association of Disrupted Delta Wave Activity During Sleep With Long-Term Cardiovascular Disease and Mortality

BackgroundDelta wave activity is a prominent feature of deep sleep, which is significantly associated with sleep quality. ObjectivesThe authors hypothesized that delta wave activity disruption during sleep could predict long-term cardiovascular disease (CVD) and CVD mortality risk. MethodsThe authors used a comprehensive power spectral entropy-based method to assess delta wave activity during sleep based on overnight polysomnograms in 4,058 participants in the SHHS (Sleep Heart Health Study) and 2,193 participants in the MrOS (Osteoporotic Fractures in Men Study) Sleep study. ResultsDuring 11.0 ± 2.8 years of follow-up in SHHS, 729 participants had incident CVD and 192 participants died due to CVD. During 15.5 ± 4.4 years of follow-up in MrOS, 547 participants had incident CVD, and 391 died due to CVD. In multivariable Cox regression models, lower delta wave entropy during sleep was associated with higher risk of coronary heart disease (SHHS: HR: 1.46; 95% CI: 1.02-2.06; P = 0.03; MrOS: HR: 1.79; 95% CI: 1.17-2.73; P < 0.01), CVD (SHHS: HR: 1.60; 95% CI: 1.21-2.11; P < 0.01; MrOS: HR: 1.43; 95% CI: 1.00-2.05; P = 0.05), and CVD mortality (SHHS: HR: 1.94; 95% CI: 1.18-3.18; P < 0.01; MrOS: HR: 1.66; 95% CI: 1.12-2.47; P = 0.01) after adjusting for covariates. The Shapley Additive Explanations method indicates that low delta wave entropy was more predictive of coronary heart disease, CVD, and CVD mortality risks than conventional sleep parameters. ConclusionsThe results suggest that delta wave activity disruption during sleep may be a useful metric to identify those at increased risk for CVD and CVD mortality.

A protocol for the prospective study of urinary cadmium with risk of fracture, bone loss, and muscle loss.

Cadmium (Cd) is a heavy metal and natural element found in soil and crops with increasing concentrations linked to phosphate fertilizers and sewage sludge applied to crop lands. A large fraction of older US men and woman have documented Cd exposure. Cd exposure has proven health concerns such as risk of lung cancer from inhalation and impaired renal function; however, growing evidence suggests it also influences bone and muscle health. Given that low levels of Cd could affect bone and muscle, we have designed prospective studies using the two largest and most detailed US studies of bone health in older men and women: the Osteoporotic Fractures in Men Study and the Study of Osteoporotic Fractures. We are investigating the association of urinary cadmium (U-Cd), as a surrogate for long-term Cd exposure, with bone and muscle health. Building off suggestive evidence from mechanistic and cross-sectional studies, this will be the first well-powered prospective study of incident fracture outcomes, bone loss, and muscle loss in relation to U-Cd, an established biomarker of long-term Cd exposure. The following is a proposed protocol for the intended study; if successful, the proposed studies could be influential in directing future US policy to decrease Cd exposure in the US population similar to recent policies adopted by the European Union to limit Cd in fertilizers.

PROSPECTIVE MULTI-OMIC ANALYSIS OF HUMAN LONGEVITY COHORTS IDENTIFIES ANALYTE NETWORKS ASSOCIATED WITH LONGEVITY

Abstract Serum based biomarkers of longevity have long been sought to explain the mechanisms of healthy aging and longevity. Using a 1:3 case cohort design, the Longevity Consortium has produced untargeted mass spectrometry based proteomic and metabolomic datasets from serum of four cohorts with longevity status, defined as those that reached the age corresponding to the 98th percentile of survival using sex specific and birth cohort specific survival percentiles. The cohorts are the Osteoporotic Fractures in Men study, the Study of Osteoporotic Fractures, the Health, Aging, and Body Composition Study, and the Cardiovascular Health Study. In this study, we integrate metabolomics and proteomics using machine learning and system biology approaches to construct multi-omic signatures predictive of longevity and healthy aging. We identify networks enriched for biomarkers previously shown to be associated with longevity such as apolipoproteins, along with novel associations, and we further compare with our findings in a mouse omics LC dataset of molecular changes induced by life-extending interventions. We show substantial differences between male and female longevity networks. The study highlights the effectiveness of using integrative systems biology methods to capture the heterogeneity of underlying molecular aging phenotypes, in order to generate a robust signature of longevity. The identified biomarker signatures may have significant implications for the development of personalized interventions aimed at promoting healthy aging and preventing age-related diseases.

Association of sleep timing with all-cause and cardiovascular mortality: the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study.

Previous studies have highlighted the importance of sleep patterns for human health. This study aimed to investigate the association of sleep timing with all-cause and cardiovascular disease mortality. Participants were screened from two cohort studies: the Sleep Heart Health Study (SHHS; n = 4,824) and the Osteoporotic Fractures in Men Study (n = 2,658). Sleep timing, including bedtime and wake-up time, was obtained from sleep habit questionnaires at baseline. The sleep midpoint was defined as the halfway point between the bedtime and wake-up time. Restricted cubic splines and Cox proportional hazards regression analyses were used to examine the association between sleep timing and mortality. We observed a U-shaped association between bedtime and all-cause mortality in both the SHHS and Osteoporotic Fractures in Men Study groups. Specifically, bedtime at 11:00 pm and waking up at 7:00 am was the nadir for all-cause and cardiovascular disease mortality risks. Individuals with late bedtime (> 12:00 am) had an increased risk of all-cause mortality in SHHS (hazard ratio 1.53, 95% confidence interval 1.28-1.84) and Osteoporotic Fractures in Men Study (hazard ratio 1.27, 95% confidence interval 1.01-1.58). In the SHHS, late wake-up time (> 8:00 am) was associated with increased all-cause mortality (hazard ratio 1.39, 95% confidence interval 1.13-1.72). No significant association was found between wake-up time and cardiovascular disease mortality. Delaying sleep midpoint (> 4:00 am) was also significantly associated with all-cause mortality in the SHHS and Osteoporotic Fractures in Men Study. Sleep timing is associated with all-cause and cardiovascular disease mortality. Our findings highlight the importance of appropriate sleep timing in reducing mortality risk. Ma M, Fan Y, Peng Y, etal. Association of sleep timing with all-cause and cardiovascular mortality: the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study. J Clin Sleep Med. 2024;20(4):545-553.

Polysomnography derived sleep metrics and cognition in the Sleep and Dementia Consortium (SDC): a study of 5 population‐based cohorts

AbstractBackgroundGood sleep is essential for health, yet the role of sleep in dementia risk is incompletely understood. The Sleep and Dementia Consortium (SDC) was established to study associations between polysomnography (PSG)‐derived sleep metrics and the risk of dementia and related cognitive and brain MRI endophenotypes. This study presents the associations of sleep architecture and obstructive sleep apnea (OSA) with cognitive function across participating cohorts.MethodThe SDC curates data from five population‐based cohorts with methodologically consistent, overnight, home‐based PSG and neuropsychological assessments over 5 years of follow‐up. Cohorts include the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Osteoporotic Fractures in Men Study (MrOS), and Study of Osteoporotic Fractures (SOF). Global cognitive composite scores were derived from principal component analysis as the primary outcome. All sleep metrics were harmonized centrally and then distributed to the participating cohorts for cohort‐specific analysis using linear regression; study‐level estimates were pooled in random effects meta‐analyses. Results are adjusted for demographic variables, the time interval between the PSG and neuropsychological assessment (0‐5 years), body mass index, antidepressant use, and sedative medication use.ResultThe mean age of the cohorts ranged from 58 to 89 years (Figure 1) with a pooled sample of 5,946 participants. As shown in Figure 2, across cohorts, higher REM sleep percentage (pooled β±SE = 0.49±0.18 per % increase; p = 0.008) and Sleep Maintenance Efficiency (pooled β±SE = 0.08±0.03 per % increase; p = 0.01) were associated with better global cognition whereas OSA (Apnea‐hypopnea index [AHI] ≥ 5) was associated with worse global cognition (pooled β±SE = ‐0.06±0.02 vs. AHI&lt;5; p = 0.03). Differences in N3 sleep were not associated with cognition.ConclusionBetter sleep consolidation and higher REM sleep percentage were associated with better cognition whereas OSA was associated with worse cognition over 5‐years follow‐up. The role of interventions to improve sleep for maintaining cognitive function and potentially reduce dementia risk requires investigation.

Functional Interactions of Low‐density Electroencephalography During Sleep Cycles to Detect Alzheimer’s Disease

AbstractBackgroundAlzheimer’s disease (AD) causes disruption in the collective dynamics of the brain activities which can be captured by analyzing the functional interactions between electroencephalographic (EEG) signals in different regions of the brain. To better assess the AD‐related changes in the interactions, one possible approach is to increase the EEG electrode density for better spatial information. Alternatively, high order interactions within the fluctuations of low‐density EEG — a concept of the multivariate information theory — may better reveal complex EEG interactions and can be used to detect AD‐related changes in brain activities. This study is aimed to demonstrate this conceptual approach using machine learning.MethodWe analyzed overnight 4‐channel EEG recordings (left central, right central, left mastoid, and right mastoid) in the polysomnography (PSG) data collected from 28 older men in the Osteoporotic Fractures in Men Study (MrOS). 14 participants reported a history of clinical diagnosis of AD while the other 14 did not. Groups were matched in age and education. Each of 30‐second epochs of the PSG recording was scored as wake, N1, N2, N3, or rapid eye movement sleep according to the established guideline. Features based on low (2) and high order (3‐4) interactions between electrodes, i.e., total correlation (TC), dual total correlation (DTC), O‐information (O) and S‐information (S), were extracted from raw and band‐passed filtered data (δ: 0.5‐4 Hz, θ: 4‐8 Hz, α: 8‐12 Hz, β: 12‐30 Hz, γl: 30‐40 Hz, γh: 40‐100 Hz) within each wake/sleep stage. The optimal set of features was identified using a cross‐validated random forest classifier to maximize the group discrimination.ResultAD was discriminated from control with an average area under the receiver operating characteristic curve of 0.90±0.05 using just 3 features: O (triplet) measured in the γh band within wake stage, DTC (triplet) of raw EEG within N1 stage, and TC (pairwise) in the δ band within N1 stage.ConclusionThis proof‐of‐concept study shows the possibility of using low‐density sleep EEG to detect AD. This method might be useful for screening people with risk of AD in ambulatory setting.

Breaking Up Sedentary Time Reduces Recurrent Fall Risk, but Not Incident Fracture Risk in Older Men.

Apart from physical activity volume, frequent breaks from sedentary bouts and active bouts may differentially reduce fall and fracture risk. We assessed the longitudinal relationship between frequency of breaks from time spent sedentary and frequency of active bouts with recurrent falls and fractures. The sample included 2918 men aged 79.0 ± 5.1 years with free-living activity (SenseWear Armband) at the Osteoporotic Fractures in Men Study (MrOS) year 7 (2007-2009) visit. Men were divided into quartiles by the number of breaks from sedentary bouts (sedentary bout: 5+ minutes sedentary; <1.5 metabolic equivalents of task [METS]) and separately by active bout frequency (active bout: 5+ minutes of activity; ≥1.5 METS). Recurrent falls (2+ falls/year) and fractures were ascertained by self-report; fractures were radiographically confirmed. Generalized estimating equations estimated the recurrent fall odds, with restricted cubic splines applied to assess nonlinear relationships. Cox proportional hazards models estimated fracture risk. Over 4 years of follow-up after year 7, 1025 (35.1%) men were fallers. Over 8.40 ± 4.10 years of follow-up, 640 (21.9%) men experienced a fracture. There was a significant nonlinear U-shaped relationship between number of breaks from sedentary bouts and recurrent falls (p < 0.001); compared with men with few breaks from sedentary bouts (1.4-<13.6), the odds of recurrent falls were lower with a moderate number (13.6-<17.0, odds ratio [OR] = 0.82, 95% confidence interval [CI] 0.66, 1.01; 17.0-<20.4, OR = 0.79, 95% CI 0.64, 0.99), but not with the highest number of breaks from sedentary bouts (20.4-34.6, OR = 1.01, 95% CI 0.81, 1.27). Results remained borderline significant after adjusting for total sedentary time. Men with the highest compared with the lowest number of breaks from sedentary bouts had a lower fracture risk, but the association was attenuated after adjustment for total sedentary time. No associations were observed for active bout frequency. In conclusion, breaking up extended periods of sedentary time reduces fall risk regardless of total sedentary time. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.

Sleep Architecture, Obstructive Sleep Apnea, and Cognitive Function in Adults

Good sleep is essential for health, yet associations between sleep and dementia risk remain incompletely understood. The Sleep and Dementia Consortium was established to study associations between polysomnography (PSG)-derived sleep and the risk of dementia and related cognitive and brain magnetic resonance imaging endophenotypes. To investigate association of sleep architecture and obstructive sleep apnea (OSA) with cognitive function in the Sleep and Dementia Consortium. The Sleep and Dementia Consortium curated data from 5 population-based cohorts across the US with methodologically consistent, overnight, home-based type II PSG and neuropsychological assessments over 5 years of follow-up: the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, Framingham Heart Study (FHS), Osteoporotic Fractures in Men Study, and Study of Osteoporotic Fractures. Sleep metrics were harmonized centrally and then distributed to participating cohorts for cohort-specific analysis using linear regression; study-level estimates were pooled in random effects meta-analyses. Results were adjusted for demographic variables, the time between PSG and neuropsychological assessment (0-5 years), body mass index, antidepressant use, and sedative use. There were 5946 participants included in the pooled analyses without stroke or dementia. Data were analyzed from March 2020 to June 2023. Measures of sleep architecture and OSA derived from in-home PSG. The main outcomes were global cognitive composite z scores derived from principal component analysis, with cognitive domains investigated as secondary outcomes. Higher scores indicated better performance. Across cohorts, 5946 adults (1875 females [31.5%]; mean age range, 58-89 years) were included. The median (IQR) wake after sleep onset time ranged from 44 (27-73) to 101 (66-147) minutes, and the prevalence of moderate to severe OSA ranged from 16.9% to 28.9%. Across cohorts, higher sleep maintenance efficiency (pooled β per 1% increase, 0.08; 95% CI, 0.03 to 0.14; P < .01) and lower wake after sleep onset (pooled β per 1-min increase, -0.07; 95% CI, -0.13 to -0.01 per 1-min increase; P = .02) were associated with better global cognition. Mild to severe OSA (apnea-hypopnea index [AHI] ≥5) was associated with poorer global cognition (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .01) vs AHI less than 5; comparable results were found for moderate to severe OSA (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .02) vs AHI less than 5. Differences in sleep stages were not associated with cognition. This study found that better sleep consolidation and the absence of OSA were associated with better global cognition over 5 years of follow-up. These findings suggest that the role of interventions to improve sleep for maintaining cognitive function requires investigation.

Interactions Between HR-pQCT Bone Density and D3 Cr Muscle Mass (or HR-pQCT Bone Structure and HR-pQCT Muscle Density) in Predicting Fractures: The Osteoporotic Fractures in Men Study.

We examined if an interaction exists between bone and muscle in predicting fractures in older men. Prospective data from the Osteoporotic Fractures in Men study was used to build Cox proportional hazards models. Predictors included HR-pQCT total volumetric BMD (Tt.BMD), trabecular BMD (Tb.BMD), cortical BMD (Ct.BMD) and cortical area (Ct.Ar) at distal radius/tibia, HR-pQCT muscle volume and density (diaphyseal tibia), D3 -creatine dilution (D3 Cr) muscle mass, and grip strength and leg force, analyzed as continuous variables and as quartiles. Incident fractures were self-reported every 4 months via questionnaires and centrally adjudicated by physician review of radiology reports. Potential confounders (demographics, comorbidities, lifestyle factors, etc.) were considered. A total of 1353 men (mean age 84.2 ± 4.0 years, 92.7% white) were followed for 6.03 ± 2.11 years. In the unadjusted (continuous) model, there were no interactions (p > 0.05) between any muscle variable (D3 Cr muscle mass, muscle volume, muscle density, grip strength or leg force) and Tt.BMD at distal radius/tibia for fractures (all: n = 182-302; nonvertebral: n = 149-254; vertebral: n = 27-45). No consistent interactions were observed when interchanging Tt.BMD for Tb.BMD/Ct.BMD or for Ct.Ar (bone structure) at the distal radius/tibia in the unadjusted (continuous) models. Compared with men in quartiles (Q) 2-4 of D3 Cr muscle mass and Q2-4 of distal tibia Tt.BMD, men in Q1 of both had increased risk for all fractures (hazard ratio (HR) = 2.00; 95% confidence interval [CI] 1.24-3.23, p = 0.005) and nonvertebral fractures (HR = 2.10; 95% CI 1.25-3.52, p < 0.001) in the multivariable-adjusted model. Confidence intervals overlapped (p > 0.05) when visually inspecting other quartile groups in the multivariable-adjusted model. In this prospective cohort study of older men, there was no consistent interactions between bone and muscle variables on fracture risk. Larger sample sizes and longer follow-up may be needed to clarify if there is an interaction between bone and muscle on fracture risk in men. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

0052 A Novel Biomarker of Alzheimer’s Disease Based on High-order Interactions of Low-density Electroencephalography

Abstract Introduction Alzheimer’s disease (AD) causes disruptions in brain functions, which can be tracked by proper analysis of electroencephalography (EEG). Current efforts to understand the impact of AD on brain activity have leveraged the development of high-density EEG. Alternatively, we propose that AD can be discriminated from healthy controls (HC) by analyzing low-density EEG sleep recordings with nonlinear measures that capture functional interactions beyond pairwise such as the total correlation (TC), dual total correlation (DTC), O-information (O) and S-information (S). Methods We analyzed overnight polysomnography data with 4 EEG channels (left central, right central, left mastoid, and right mastoid) of 28 older men (14 with a self-reported history of clinical diagnosis of AD and 14 HC, matched in age and education) in the Osteoporotic Fractures in Men Study (MrOS) obtained from the National Sleep Research Resource (NSRR). Each 30-second epoch was scored as wake (W), N1, N2, N3, or rapid eye movement. Features based on low (2) and high order (3-4) interactions between electrodes (TC, DTC, O, and S) were extracted from raw and band-pass filtered data within each wake/sleep stage. Finally, a feature selection algorithm provided the optimal subset of features that maximizes the discrimination between conditions. Results AD was discriminated from HC with an average area under the receiver operating characteristic curve of 0.90±0.05 using just 3 features: O (triplet) measured within W stage in the high γ band (40-100 Hz), DTC (triplet) for raw N1 data, and TC (pairwise) in the δ band (0.5-4 Hz) within N stages. Conclusion State-of-the-art analysis of high-order interactions can maximize the discrimination of AD using a low-density sleep EEG set-up. The potential of these features to capture the physiopathology of AD and its impact on brain function should be further confirmed using larger samples. Support (if any) National Institutes of Health (RF1AG059867, RF1AG064312, R01AG057234); ANID/FONDECYT Regular (1210195 and 1210176 and 1220995); Alzheimer’s Association (SG-20-725707). MrOS Sleep Study was supported by R01 HL071194, R01HL070848, R01HL070847, R01HL070842, R01HL070841, R01HL070837, R01HL070838, and R01HL070839. The NSRR was supported by R24HL114473, 75N92019R002.

0130 Reduced Entropy in EEG During Rapid Eye Movement Sleep in Men with Depression

Abstract Introduction Depression is an increasingly prevalent mental health condition. Patients with depression have disrupted rapid eye movement (REM) sleep as characterized by shortened REM latency, increased REM sleep duration, and increased REM density. However, it is unknown whether the dynamic patterns of EEG within REM episodes are altered in these patients. Here we investigated the complexity of EEG during REM sleep using the analysis of irregularity on multiple temporal time scales and compared the difference in such a nonlinear property of EEG between patients with depression and controls. Methods We analyzed the overnight EEG recordings (256 Hz) collected from the left central channel in 19 older men with depression and 19 age-matched otherwise healthy control men in the Osteoporotic Fractures in Men Study (MrOS) obtained from the National Sleep Research Resource (NSRR). To quantify the irregularity/complexity in EEG fluctuations during REM, a Multiscale Entropy (MSE) analysis was performed on each 30-second epoch to calculate the entropy at different time scales between ~0.004 and ~0.078 seconds (i.e., 1/256, 2/256, …, 20/256 seconds). Results As compared to control men, men with depression had significantly lower entropy values at multiple time scales between 0.023-0.031 seconds (time scale =6/256 second: 0.363□0.008 [SE] for depression, 0.408□0.009 for controls; time scale =7/256 second: 0.295□0.009 for depression, 0.342□0.008 for controls; time scale =8/256 second: 0.225□0.009 for depression, 0.269□0.008 for controls; all FDR-adjusted P-values&amp;lt; 0.001), indicating reduced temporal irregularity/complexity in EEG fluctuations. The differences were not statistically significant at smaller or larger time scales. Conclusion EEG complexity/irregularity within REM sleep were altered in patients with depression. Our results indicate the capability of MSE analysis in capturing important complexity features of EEG fluctuations, which might be missed using those entropy algorithms focused on EEG fluctuations at a single time scale. Support (if any) RF1AG059867, RF1AG064312. The National Heart, Lung, and Blood Institute provided funding for the ancillary MrOS Sleep Study, "Outcomes of Sleep Disorders in Older Men," under the following grant numbers: R01 HL071194, R01 HL070848, R01 HL070847, R01 HL070842, R01 HL070841, R01 HL070837, R01 HL070838, and R01 HL070839. The NSRR was supported by the National Heart, Lung, and Blood Institute (R24 HL114473, 75N92019R002).

Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis.

There is uncertainty on best approaches for defining apnea-hypopnea events. To clarify the contributions of desaturation vs arousal to defining hypopneas, we examined the associations of events with desaturation (≥ 3%) but not arousal (apnea-hypopnea index [AHI]≥3%Only) vs events with arousals but no desaturation (AHIArOnly) with obstructive sleep apnea-related comorbidities and incident cardiovascular disease across multiple cohorts. In the Sleep Heart Health Study (n = 5,473), the Multi-Ethnic Study of Atherosclerosis (n = 1,904), and the Osteoporotic Fractures in Men Study (n = 2,685), we examined the independent associations of AHI≥3%Only and AHIArOnly with hypertension, diabetes, and daytime sleepiness, and incident cardiovascular disease. After adjusting for covariates and AHI based on events with electroencephalogram arousal (regardless of desaturation), AHI≥3%Only was associated with hypertension in Sleep Heart Health Study (odds ratio: 1.12; 95% confidence interval: 1.04,1.21), per 1 standard deviation increase). Similar associations were observed in the Multi-Ethnic Study of Atherosclerosis and Osteoporotic Fractures in Men Study, as well as for associations with diabetes (odds ratio: 1.30; 1.09,1.54, and 1.25; 1.07,1.47, respectively), sleepiness (odds ratio: 1.19; 1.00,1.41; and 1.17; 1.01-1.35), and incident cardiovascular disease (hazard ratio: 1.37; 1.05,1.77 and 1.14; 1.00,1.29). In contrast, after adjusting for events with desaturation (regardless of arousal), AHIArOnly was unassociated with these outcomes. In Sleep Heart Health Study, greater baseline obstructive sleep apnea severity was associated with a reduction in arousal frequency over 5 years (P < .0001). In middle-aged and older individuals, addition of events with arousals does not improve the strength of associations with comorbidities or incident cardiovascular disease. Research is needed to understand generalizability to younger individuals and the mechanistic role of arousals in obstructive sleep apnea. Azarbarzin A, Sands SA, Han S, etal. Relevance of cortical arousals for risk stratification in sleep apnea: a 3 cohort analysis. J Clin Sleep Med. 2023;19(8):1475-1484.

Role of Perceived Physical and Mental Fatigability Severity on Prospective, Recurrent, and Injurious Fall Risk in OlderMen.

Falls occur annually in 25% of adults aged ≥65years. Fall-related injuries are increasing, highlighting the need to identify modifiable risk factors. Role of fatigability on prospective, recurrent, and injurious fall risk was examined in 1740 men aged 77-101years in the Osteoporotic Fractures in Men Study. The 10-item Pittsburgh Fatigability Scale measured perceived physical and mental fatigability (0-50/subscale) at Year 14 (2014-16); established cut-points identified men with more severe perceived physical (≥15, 55.7%), more severe mental (≥13, 23.7%) fatigability, or having both (22.8%). Prospective, recurrent (≥2), and injurious falls were captured by triannual questionnaires ≥1year after fatigability assessment; risk of any fall was estimated with Poisson generalized estimating equations, and likelihood of recurrent/injurious falls with logistic regression. Models adjusted for age, health conditions, and other confounders. Men with more severe physical fatigability had a 20% (p=.03) increased fall risk compared with men with less physical fatigability, with increased odds of recurrent and injurious falls, 37% (p=.04) and 35% (p=.035), respectively. Men with both more severe physical and mental fatigability had a 24% increased risk of a prospective fall (p=.026), and 44% (p=.045) increased odds of recurrent falling compared with men with less severe physical and mental fatigability. Mental fatigability alone was not associated with fall risk. Additional adjustment for previous fall history attenuated associations. More severe fatigability may be an early indicator to identify men at high risk for falls. Our findings warrant replication in women, as they have higher rates of fatigability and prospective falls.