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Background: In observational studies, older adults with insufficient or deficient serum vitamin D levels are at higher risk of cardiovascular disease (CVD), but randomized trials have failed to demonstrate reduction in CVD risk from vitamin D supplementation. This is possibly because the doses of vitamin D supplements tested were too low. Objective: To determine if higher doses of vitamin D supplementation lower high sensitivity cardiac troponin level (hs-cTnI) and N-terminal pro b-type natriuretic peptide (NT-proBNP), markers of subclinical CVD. Methods: The Study to Understand Fall Reduction and Vitamin D in You (STURDY) was a double-blind, randomized, response-adaptive trial that tested the effects of 4 doses of vitamin D3 supplementation (200, 1000, 2000, and 4000 IU/day) on fall risk in adults aged ≥70 years old with low serum 25-hydroxyvitamin D levels (10-29 ng/ml). Hs-cTnI and NT-proBNP levels were measured at baseline and at 3-, 12- and 24-month follow-up visits. For analysis, participants were divided into low (200 IU/day) and high dose (1000+ IU/day) vitamin D treatment groups. The effects of vitamin D dose on hs-cTnI and NT-proBNP were assessed via mixed effects tobit models. Results: Among 688 participants (mean age of 77 ± 5 years, 44% were women, and 18% were Black), 50.7% were in the high-dose treatment group (1000+ IU/day). Hs-cTnI increased in both the low and high dose groups by 5.1% and 5.8%, respectively; likewise, NT-proBNP increased in both groups by 11.3% and 9.3%, respectively ( Figure). Compared to the low-dose group, high-dose vitamin D treatment did not affect hs-cTnI (1.7 % difference; 95% CI: -5.3, 9.3) or NT-proBNP (-1.8 % difference; 95% CI: -9.3, 6.3). Conclusions: Compared to low dose vitamin D supplementation, a higher dose did not affect markers of subclinical CVD in older adults with low serum vitamin D levels. These findings do not support higher doses of vitamin D as an intervention to reduce the risk of CVD in this population.

ObjectiveDue to the long prodromal period for dementia pathology, approaches are needed to detect cases before clinically recognizable symptoms are apparent, by which time it is likely too late to intervene. This study contrasted two theoretically-based algorithms for classifying early cognitive impairment (ECI) in adults aged ≥50 enrolled in the Baltimore Longitudinal Study of Aging.MethodTwo ECI algorithms were defined as poor performance (1 standard deviation [SD] below age-, sex-, race-, and education-specific means) in: (1) Card Rotations or California Verbal Learning Test (CVLT) immediate recall and (2) ≥1 (out of 2) memory or ≥3 (out of 6) non- memory tests. We evaluated concurrent criterion validity against consensus diagnoses of mild cognitive impairment (MCI) or dementia and global cognitive scores using receiver operating characteristic (ROC) curve analysis. Predictive criterion validity was evaluated using Cox proportional hazards models to examine the associations between algorithmic status and future adjudicated MCI/dementia.ResultsAmong 1,851 participants (mean age=65.2±11.8 years, 50% women, 74% white), the two ECI algorithms yielded comparably moderate concurrent criterion validity with adjudicated MCI/dementia. For predictive criterion validity, the algorithm based on impairment in Card Rotations or CVLT immediate recall was the better predictor of MCI/dementia (HR=3.53, 95%CI: 1.59-7.84) over 12.3 follow-up years.ConclusionsImpairment in visuospatial ability or memory may be capable of detecting early cognitive changes in the preclinical phase among cognitively normal individuals.

Background: There is inconsistent evidence on the optimal time after standing to assess orthostatic hypotension (OH). Objectives: To characterize the timing of OH after standing in older adults and the fall risk associated with OH at specific times. Methods: We performed a secondary analysis of the Study to Understand Fall Reduction and Vitamin D in You (STURDY). Blood pressure (BP) was measured in the supine position. Participants stood upright and underwent 6 standing BP measurements: 3 (M1-M3) immediately after standing, and 3 (M4-M6) after 3 minutes of standing. OH was defined as a decrease from supine systolic BP (SBP) of 20 or supine diastolic BP (DBP) of 10 mm Hg. We used generalized estimating equations to characterize changes in SBP, DBP, and OH over time. We used Cox models to examine the relationship between OH at each time point and subsequent falls. Results: There were 425 falls among 491 adults with 6,055 BP measurements and a median follow-up of 275 days. SBP/DBP decreased by a mean 9.5/2.6 mm Hg immediately after standing (M1) vs. 2.2/0.9 about 5 minutes after standing (M6). OH was observed in 32% of assessments at M1, and only 16% at M5 and M6 ( Table ). Only OH at M5 (Hazard Ratio = 1.84 [95% confidence interval = 1.17, 2.91]) and M6 (1.85 [1.03, 2.91]) predicted higher fall risk among individual time points. However, average OH from early (M1-3) and late (M4-6) measurements, respectively, also predicted higher fall risk (M1-3 = 1.65 [1.08, 2.52]; M4-6 = 1.73 [1.03, 2.91]). Conclusions: OH was most prevalent immediately after standing, but most informative for fall risk in late and average measurements. Multiple standing BP measurements may improve the clinical assessment of OH.

The benefits of routine engagement in physical activity (PA) on vascular health are well established; lesser known is whether vascular health associates with accelerometry-based daily patterns of PA in mid-to-late life. Using linear regression models adjusted for demographics and comorbidities, we modeled the cross-sectional associations between ankle brachial index (ABI) and PA patterns (diurnal activity and activity fragmentation) in 7,848 HCHS/SOL participants (45.5% men, 56.4±0.2 years). Compared to those with normal ABI (1.0-1.4), those with low ABI (≤0.9) had more fragmented daily activity (B=1.0%, SE=0.4, p=.04); primarily between 12 and 8 PM (B=1.66%, SE=0.55, p

This study hypothesized that perceived fatigability, fatigue standardized to walking, would better discriminate mortality risk than general fatigue symptoms. We leveraged perceived fatigability, self-reported tiredness, self-reported low energy and mortality data from 1,112 participants aged ≥50 years. Hazard ratios (HRs) of all-cause mortality (198 [17.8%] events) by either z-scored fatigability, tiredness, and energy level were estimated using Cox proportional hazards models. Model discrimination was compared using Harrell’s C-statistics (C). After full covariate adjustment, 1 SD higher perceived fatigability, tiredness and low energy level were associated with higher mortality risk (HR=1.20, 95% confidence interval [CI]:1.05-1.37; HR=1.28, 95% CI:1.11-1.48; HR=1.26, 95% CI:1.10-1.45, respectively). The model for perceived fatigability (C=0.8039) had comparable discrimination to tiredness (C=0.8085,p=0.26) and low energy level (C=0.8067,p=0.41). While perceived fatigability was associated with higher mortality risk, it did not exhibit superior ability to discriminate mortality risk than self-reported fatigue symptoms among persons in mid-to-late life.

Researchers often prefer different accelerometers for measurement of sleep and physical activity (PA) in older adults, but wearing multiple accelerometers increases costs and participant burden. We tested the hypothesis that the Actiwatch-2, commonly used to measure sleep, and the ActiGraph GT9X Link, commonly used to measure PA, yield comparable sleep parameters among 331 participants (aged 71+/-14 years, 50.5% women) who wore them simultaneously for 7+/-1.6 nights in the BLSA. Compared to the Actiwatch-2, the ActiGraph estimated 50% greater wake after sleep onset, 89% longer wake bout length, 18% lower sleep fragmentation index (SFI), 5% lower total sleep time (TST) and 5% higher sleep efficiency. Yet, despite yielding different absolute values of TST and SFI, the devices generated similar between-person (relative) differences in TST and SFI. These devices may only be interchangeable for measurement of some relative sleep parameters in older adults. Studies with both devices and gold-standard polysomnography are needed.

β-amyloid is a hallmark of Alzheimer’s disease and can be measured in vivo by PET imaging. Whether PiB+ (elevated β-amyloid) individuals exhibit distinct physical activity patterns throughout the day (i.e., activity amount or fragmentation) is unknown. Using data from 125 BLSA participants (56-95 years) with PET imaging and ≥3 days of wrist accelerometry, we examined associations between PiB status and activity patterns daily and during 6-hour time blocks using multivariable linear regression models. Modification by age was also examined. Daily total activity counts and activity fragmentation did not differ by PiB status (p=0.34 and p=0.70, respectively). Yet, per each additional year of age, PiB+ individuals were more active during early morning (p=0.04) and evening (p=0.029) but trended towards less active in mid-morning (p=0.069) than PiB- individuals. Though replication of findings is needed, older PiB+ participants appeared more active in the late evening/early morning, possibly reflecting altered sleep-time, agitation, or restlessness.

Age-related sensory impairment, such as loss in vision or hearing, have been linked to poor brain health. Yet, the relationship between co-occurring sensory impairments and brain volumes remains unclear. We used cross-sectional sensory and brain imaging data from 208 cognitively normal participants of the Baltimore Longitudinal Study of Aging (mean age 72 years; 59% women). Sensory impairments were separately identified with vision, hearing, smell, proprioception, and vestibular function testing. Brain imaging volumes were derived using an automated multi-atlas approach. Multiple linear regression models were used to estimate brain volumetric differences by number of sensory impairments (0-5) or by multisensory impairment status (MSI; ≥2 impairments). For every one additional sensory impairment, there was lower volume in the orbitofrontal gyrus (beta=0.35 cc [SE=0.17], p=0.04) but higher volumes in the caudate (0.14 cc [0.05], p=0.006) and putamen (0.13 cc [0.06], p=0.043). Participants with MSI (versus no MSI) had lower volumes in superior frontal gyrus (-1.01 cc [=0.34], p=0.003), lower orbitofrontal gyrus (-0.91 cc [0.38], p=0.018), superior parietal lobe (0.68 cc [0.27], p=0.011), and precuneus (-0.74 cc [0.35], p=0.038), but similar volumes in the caudate (p=0.12) and putamen (p=0.14). A negative relationship between MSI and brain volume across multiple regions was largely observed yet our exploratory findings raise the possibility that MSI is associated with compensatory maintenance of brain volume structures in the basal ganglia. Future directions include replication of these findings in other studies and longitudinal analyses to determine how MSI relates to brain atrophy.

The Apolipoprotein-ε4 (APOE-ε4) genotype is associated with earlier onset and greater risk of β-amyloid deposition, but whether APOE-ε4 status is associated with physical activity amount or fragmentation remains unclear. In 563 BLSA participants aged 55-97 years with APOE-ε4 and ≥3 days of wrist accelerometry data, multivariable linear regression models were fitted to estimate differences in activity amount (daily or by 6-hour time blocks) or fragmentation by APOE-ε4 status and to test whether age modifies these effects. Overall, daily activity amount and fragmentation did not differ by APOE-ε4 status (p=0.28 and p=0.93, respectively). Yet, age significantly modified the APOE-ε4 effect. Per each additional year of age, APOE-ε4 carriers had less activity during early morning (12:00-6:00AM) than non-carriers (p=0.035). This association was non-significant among the oldest-old (p=0.697 at age 80 years, p=0.347 at age 90 years), suggesting possible decreases in the predictive power of APOE-ε4 with increasing age.

Physical activity and sleep are well-established predictors of health and longevity with aging. Wrist accelerometers, that produce high-frequency time series data, capture multiple aspects of daily physical activity and sleep 24-hours/day. Historically, the majority of accelerometry-based activity research has employed summary metrics to understand the associations of total daily physical activity and sleep with physical and cognitive health. Although these measures are important for understanding conformity with physical activity and sleep recommendations, they underutilize the potential of these data. Further, the summary metrics may differ by accelerometer type/brand, making it difficult to translate results across device types and studies. This symposium will examine the associations between accelerometry-derived physical activity and various aging-related health outcomes, and compare the measurement properties of two commonly used accelerometers for measuring sleep. Ms. Marino will discuss the association of physical activity volume and fragmentation with the presence of the Apolipoprotein-ε4 genotype in the Baltimore Longitudinal Study of Aging (BLSA), overall and by time of day. Dr. Wanigatunga will present evidence on the association of physical activity patterns with beta amyloid plaques in the BLSA. Dr. Schrack will present the association of physical activity fragmentation and diurnal patterns with peripheral artery disease in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Finally, Ms. Liu will compare measurement of sleep variables derived from two commonly used accelerometers. Collectively, these presentations highlight ways to utilize the richness of accelerometry data to illuminate more sensitive associations between movement and health outcomes to advance prevention science and promote health aging.

Higher energetic cost of walking per unit distance has been linked to many adverse health outcomes in older adults. Aging-related changes in gait characteristics have been postulated to contribute to energetic inefficiency, but previous studies focused on younger adults, and/or examined only a few gait characteristics. In the Baltimore Longitudinal Study of Aging, 507 older adults ≥50 years (72.3±9.8 years, 48.3% women, 48.3% black) without stroke and Parkinson disease had concurrent measurements of usual-paced gait characteristics using 3D motion analysis and energetic cost of walking using indirect calorimetry during a 2.5-min usual-paced overground walk. We tested the associations of the mean and the coefficient of variance (CV) of cadence (steps/min), swing time (ms), double support time (ms), stance time (ms), step time (ms), step length (cm), and step width (cm) with energetic cost of walking using linear regression models, adjusting for demographics, body composition, comorbidities, and gait speed. We found that a 5-cm shorter step length was associated with 0.40 ml/kg/100m higher cost of walking (p< 0.001). A 1% higher CV in swing time and 1% lower CV in step width was associated with 0.152 ml/kg/100m higher (p=0.044) and 0.023 ml/kg/100m lower (p=0.022) cost of walking, respectively. Our results suggest that mean step length and variability in swing time and step width could potentially contribute to the rising cost of walking in older adults. Future longitudinal studies are needed to understand whether changes in gait variability can predict increased energetic cost of walking and can be intervened to preserve energy efficiency.

Background/aim:Cost-efficient methods are essential for successful participant recruitment in clinical trials. Patient portal messages are an emerging means of recruiting potentially eligible patients into trials. We assessed the response rate and complaint rate from direct-to-patient, targeted recruitment through patient portals of an electronic medical record for a clinical trial, and compared response rates by differences in message content.Methods:The Study to Understand Fall Reduction and Vitamin D in You (STURDY) trial is a National Institutes of Health–sponsored, community-based study of vitamin D supplementation for fall prevention in older adults conducted at Johns Hopkins. Potential participants were identified using the Epic electronic medical record at the Johns Hopkins Health System based on age (≥70 years), ZIP code (30-mile radius of study site), and prior activation of a patient portal account. We prepared a shorter message and a longer message. Both had basic information about study participation, but the longer message also contained information about the significance of the study and a personal invitation from the STURDY principal investigator. The Hopkins Institutional Review Board did not require prior consent from the patient or their providers. We calculated the response rate and tracked the number of complaints and requests for removal from future messages. We also determined response rate according to message content.Results:Of the 5.5 million individuals receiving care at the Johns Hopkins Health System, a sample of 6896 met our inclusion criteria and were sent one patient portal recruitment message between 6 April 2017 and 3 August 2017. Assessment of enrollment by this method ended on 1 December 2017. There were 116 patients who expressed interest in the study (response rate: 1.7%). Twelve (0.2%) recipients were randomized. There were two complaints (0.03%) and one request to unsubscribe from future recruitment messages (0.01%). Response rate was higher with the longer message than the shorter message (2.1% vs 1.2%; p = 0.005).Conclusion:Patient portal messages inviting seniors to participate in a randomized controlled trial resulted in a response rate similar to commercial email marketing and resulted in very few complaints or opt-out requests. Furthermore, a longer message with more content enhanced response rate. Recruitment through patient portals might be an effective strategy to enroll trial participants.

Low physical activity (PA) is a common phenotype of frailty, but whether disengagement of daily lifestyle PA signals impending frailty remains unexplored. Using STURDY (Study to Understand Fall Reduction and Vitamin D in You) data from 499 robust/prefrail adults (mean age=76 + 5 years; 42% women), we examined whether accelerometer patterns (activity counts/day, active minutes/day, and activity fragmentation) were prospectively associated with incident frailty over 2 years of follow-up; 48 (10%) participants developed frailty. In Discrete-Cox hazard models adjusted for demographics, medical conditions, and device wear days, every 30 min/day higher baseline active time, 100,000 more activity counts/day, and 1% lower activity fragmentation was associated with a 13% (p=0.003), 10% (p=0.001), and 8% (p

Motor and sensory impairments are linked with dementia risk, but whether there is a joint effect of deficits in motor and sensory function is unknown. We analyzed 649 BLSA participants (aged 72±11 years; 55% women; 68% white) who had concurrent baseline 6-meter usual gait speed and sensory function (vision, hearing) between 2012-2019. Mild cognitive impairment (MCI) and dementia were adjudicated during an average follow-up of 3 years. We examined the association between baseline gait speed, z-scored sensory function, and a gait*sensory interaction with risk of MCI/dementia using Cox proportional hazard models, adjusted for demographics and chronic conditions. Each .01 m/s faster baseline gait was associated with a reduced risk (HR:0.98 (0.96-0.99)) of MCI/dementia, and each 1 SD higher in hearing and vision z-score was associated with an increased risk (HR:1.84 (1.1-3.1)) increased risk. The was no significant interaction, suggesting motor and sensory impairments may be independently associated with MCI/dementia risk.

Perceived fatigability is linked to declining physical and cognitive performance, yet whether fatigability reflects early subclinical change in brain structure is unknown. Using mixed effects models, we assessed the longitudinal association of 3T MRI-derived brain volumes with perceived fatigability after a 5-min treadmill walk (0.67 m/s, 0% grade) using the Borg Rating of Perceived Exertion scale (range 6-20) in 802 BLSA participants (age 68.2+/-12.4 years, 45% men 66% White). In models adjusted for intracranial volume, demographics, chronic conditions, and CESD score, declining gray matter volumes in the frontal (β=-0.01) and temporal (β=-0.02) lobes, as well as the hippocampus (β=-0.25), precuneus (β=-0.10) and thalamus (β=-0.19) were associated with higher fatigability. Larger ventricular volumes were also associated with higher fatigability (β=0.02). Brain atrophy, particularly in gray matter and the hippocampal region, is longitudinally associated with increased fatigability in cognitively normal older adults, making it a potential marker of brain atrophy.

Higher energetic costs for mobility are associated with slow and declining gait speed. Slow gait is linked to cognitive decline and Alzheimer’s disease (AD), but the physiological underpinnings are note well-understood. We investigated the cross-sectional association between the energetic cost of walking and amyloid status (+/-) in 174 cognitively unimpaired men and women (52%) aged 78.5±8.6 years. The energetic cost of walking was assessed as the average oxygen consumption (VO2) during 2.5 minutes of customary-paced overground walking. Amyloid status was determined from 11C-Pittsburgh compound B (PiB) positron emission tomography (PET) imaging. Average energetic cost of walking was .169±.0379 ml/kg/m and 30% of the sample was PiB+. In logistic regression adjusted for demographics, APOE-e4, body composition and comorbidities, each 0.01ml/kg/m higher energy cost was associated with 12% increased odds of being PiB+ (OR=1.12; 95% CI:1.01-1.24). Inefficient walking may be a clinically meaningful physiological indicator of emerging AD-related pathology.

Regular and sufficient amounts of physical activity (PA) are significant in increasing health benefits and mitigating health risks. Given the growing popularity of wrist-worn devices across all age groups, a rigorous evaluation for recognizing hallmark measures of physical activities and estimating energy expenditure is needed to compare their accuracy across the lifespan. The goal of the study was to build machine learning models to recognizing the hallmark measures of PA and estimating energy expenditure (EE), and to test the hypothesis that model performance varies across age-group: young [20-50 years], middle (50-70 years], and old (70-89 years]. Participants (n = 253, 62% women, aged 20-89 years old) performed a battery of 33 daily activities in a standardized laboratory setting while wearing a portable metabolic unit to measure EE that was used to gauge metabolic intensity. Participants also wore a Tri-axial accelerometer on the right wrist. Results from random forests algorithm were quite accurate at recognizing PA type; the F1-Score range across age groups was: sedentary [0.955 – 0.973], locomotion [0.942 – 0.964], and lifestyle [0.913 – 0.949]. Recognizing PA intensity resulted in lower performance; the F1-Score range across age groups was: sedentary [0.919 – 0.947], light [0.813 – 0.828], and moderate [0.846–0.875]. The root mean square error range was [0.835–1.009] for the estimation of EE. The F1-Score range for recognizing individual PAs was [0.263–0.784]. In conclusion, machine learning models used to represent accelerometry data are robust to age differences and a generalizable approach might be sufficient to utilize in accelerometer-based wearables.

Physical performance is associated with cognitive function in later life, but few studies have examined the prospective association of physical performance with incident dementia. We studied 4539 community-dwelling National Health and Aging Trends Study (NHATS) participants aged ≥65 years with data on demographics and the Short Physical Performance Battery (SPPB) in 2011, who were followed through 2014. Our outcome was dementia diagnosis from a validated NHATS algorithm. We applied survey weights to make results nationally representative and performed Cox regression analyses. After adjustment for potential confounders, lower baseline SPPB scores were associated with incident dementia (HR=1.68, p < 0.01). Slower gait speed was the SPPB component most strongly associated with incident dementia (HR=1.21, p < 0.01). We found that poorer physical performance was linked to incident dementia in a cohort of older adults. More research is needed to examine the effect of improving physical performance on the prevention of dementia.

Physical activity especially at moderate-to-vigorous intensity may preserve brain structure in old age. However, current findings are cross-sectional and rely on absolute intensity. This study aimed to examine whether relative or absolute vigorous-intensity physical activity (VPA) predicts brain microstructural changes. We analyzed 260 initially cognitively normal and well-functioning participants(age=70.5yrs) who had VPA data via ActiHeart and longitudinal brain microstructure by DTI(follow-up=3.7yrs). Associations of VPA with microstructural changes were examined using linear mixed-effects models, adjusted for demographics. Each SD higher relative VPA defined by heart rate reserve (i.e. 21 min/day) was significantly associated with less decline in memory-related microstructural integrity, including mean diffusivity of entorhinal cortex and parahippocampal gyrus and fractional anisotropy of uncinate fasciculus and cingulum-hippocampal part, and not executive/motor-related microstructure. Absolute VPA was not associated with microstructural markers. Among well-functioning older adults, participating in VPA defined by heart rate reserve may predict less brain microstructural decline in memory-related areas.