Protocol for the San Diego Nathan Shock Center Clinical Cohort: a new resource for studies of human aging.

INTRODUCTION: While it is well recognised that aging is a heterogeneous process, our understanding of the determinants of biological aging and its heterogeneity remains unclear. The San Diego Nathan Shock Center (SD-NSC) Clinical Cohort aims to establish a resource of biospecimens and extensive donor clinical data such as physical, cognitive and sensory function to support other studies that aim to explore the heterogeneity of normal human aging and its biological underpinnings. METHODS AND ANALYSIS: The SD-NSC Clinical Cohort is composed of 80 individuals across the adult human lifespan. Strict inclusion and exclusion criteria are implemented to minimise extrinsic factors that may impede the study of normal aging. Across three visits, participants undergo extensive phenotyping for collection of physical performance, body composition, cognitive function, sensory ability, mental health and haematological data. During these visits, we also collected biospecimens including plasma, platelets, peripheral blood mononuclear cells and fibroblasts for banking and future studies on aging. ETHICS AND DISSEMINATION: Ethics approval from the UC San Diego School of Medicine Institutional Review Board (IRB #201 141 SHOCK Center Clinical Cohort, PI: Molina) was obtained on 11 November 2020. Written informed consent is obtained from all participants after objectives and procedures of the study have been fully explained. Congruent with the goal of establishing a core resource, biological samples and clinical data are made available to the research community through the SD-NSC.

Fatness but Not Fitness Linked to BrainAge: Longitudinal Changes in Brain Aging during an Exercise Intervention.

PURPOSE: Fitness, physical activity, body composition, and sleep have all been proposed to explain differences in brain health. We hypothesized that an exercise intervention would result in improved fitness and body composition and would be associated with improved structural brain health. METHODS: In a randomized controlled trial, we studied 485 older adults who engaged in an exercise intervention ( n = 225) or a nonexercise comparison condition ( n = 260). Using magnetic resonance imaging, we estimated the physiological age of the brain (BrainAge) and derived a predicted age difference compared with chronological age (brain-predicted age difference (BrainPAD)). Aerobic capacity, physical activity, sleep, and body composition were assessed and their impact on BrainPAD explored. RESULTS: There were no significant differences between experimental groups for any variable at any time point. The intervention group gained fitness, improved body composition, and increased total sleep time but did not have significant changes in BrainPAD. Analyses of changes in BrainPAD independent of group assignment indicated significant associations with changes in body fat percentage ( r (479) = 0.154, P = 0.001), and visceral adipose tissue (VAT) ( r (478) = 0.141, P = 0.002), but not fitness ( r (406) = -0.075, P = 0.129), sleep ( r (467) range, -0.017 to 0.063; P range, 0.171 to 0.710), or physical activity ( r (471) = -0.035, P = 0.444). With linear regression, changes in body fat percentage and VAT significantly predicted changes in BrainPAD ( ß = 0.948, P = 0.003) with 1-kg change in VAT predicting 0.948 yr of change in BrainPAD. CONCLUSIONS: In cognitively normal older adults, exercise did not appear to impact BrainPAD, although it was effective in improving fitness and body composition. Changes in body composition, but not fitness, physical activity, or sleep impacted BrainPAD. These findings suggest that focus on weight control, particularly reduction of central obesity, could be an interventional target to promote healthier brains.

Elevated Pure Tone Thresholds Are Associated with Altered Microstructure in Cortical Areas Related to Auditory Processing and Attentional Allocation.

BACKGROUND: Hearing loss is associated with cognitive decline and increased risk for Alzheimer's disease, but the basis of this association is not understood. OBJECTIVE: To determine whether hearing impairment is associated with advanced brain aging or altered microstructure in areas involved with auditory and cognitive processing. METHODS: 130 participants, (mean 76.4±7.3 years; 65% women) of the Rancho Bernardo Study of Healthy Aging had a screening audiogram in 2003-2005 and brain magnetic resonance imaging in 2014-2016. Hearing ability was defined as the average pure tone threshold (PTA) at 500, 1000, 2000, and 4000 Hz in the better-hearing ear. Brain-predicted age difference (Brain-pad) was calculated as the difference between brain-predicted age based on a validated structural imaging biomarker of brain age, and chronological age. Regional diffusion metrics in temporal and frontal cortex regions were obtained from diffusion-weighted MRIs. Linear regression analyses adjusted for age, gender, education, and health-related measures. RESULTS: PTAs were not associated with brain-PAD (ß= 0.09; 95% CI: -0.084 to 0.243; p = 0.34). PTAs were associated with reduced restricted diffusion and increased free water diffusion primarily in right hemisphere temporal and frontal areas (restricted diffusion: ßs = -0.21 to -0.30; 95% CIs from -0.48 to -0.02; ps < 0.03; free water: ßs = 0.18 to 0.26; 95% CIs 0.01 to 0.438; ps < 0.04). CONCLUSIONS: Hearing impairment is not associated with advanced brain aging but is associated with differences in brain regions involved with auditory processing and attentional control. It is thus possible that increased dementia risk associated with hearing impairment arises, in part, from compensatory brain changes that may decrease resilience.

Social epidemiology of Fitbit daily steps in early adolescence.

BACKGROUND: Sociodemographic disparities in adolescent physical activity have been documented but mostly rely on self-reported data. Our objective was to examine differences in device-based step metrics, including daily step count (steps d-1), by sociodemographic factors among a diverse sample of 10-to-14-year-old adolescents in the US. METHODS: We analyzed prospective cohort data from Year 2 (2018-2020) of the Adolescent Brain Cognitive Development (ABCD) Study (N = 6460). Mixed-effects models were conducted to estimate associations of sociodemographic factors (sex, sexual orientation, race/ethnicity, household income, parental education, and parental marital status) with repeated measures of steps d-1 over the course of 21 days. RESULTS: Participants (49.6% female, 39.0% racial/ethnic minority) accumulated an average of 9095.8 steps d-1. In mixed-effects models, 1543.6 more steps d-1 were recorded for male versus female sex, Black versus White race (328.8 more steps d-1), heterosexual versus sexual minority sexual orientation (676.4 more steps d-1), >$200,000 versus <$25,000 household income (1003.3 more steps d-1), and having married/partnered parents versus unmarried/unpartnered parents (326.3 more steps d-1). We found effect modification by household income for Black adolescents and by sex for Asian adolescents. CONCLUSIONS: Given sociodemographic differences in adolescent steps d-1, physical activity guidelines should focus on key populations and adopt strategies optimized for adolescents from diverse backgrounds. IMPACT: Sociodemographic disparities in physical activity have been documented but mostly rely on self-reported data, which can be limited by reporting and prevarication bias. In this demographically diverse sample of 10-14-year-old early adolescents in the U.S., we found notable and nuanced sociodemographic disparities in Fitbit steps per day. More daily steps were recorded for male versus female sex, Black versus White race, heterosexual versus sexual minority, >$100,000 versus <$25,000 household income, and having married/partnered versus unmarried/unpartnered parents. We found effect modification by household income for Black adolescents and by sex for Asian adolescents.

Adolescent sedentary behavior and body composition in early adulthood: results from a cohort study.

BACKGROUND: This study investigates the cross-sectional and prospective associations between accelerometer-measured sedentary behavior and body composition from adolescence to early adulthood. METHODS: Data from the Santiago Longitudinal Study were analyzed (n = 212). Sedentary time was measured at age 16 years, and body composition (body mass index [BMI], waist circumference, waist-to-height ratio [WHtR], fat mass percentage, and lean mass percentage) was examined at both age 16 and 23 years. Adjusted linear regression models estimated associations between sedentary time, sedentary bout duration, and body composition, overall and by sex. RESULTS: In all analyses, mean sedentary bout duration was not associated with body composition. In cross-sectional analyses, more sedentary time during adolescence was significantly associated with lower BMI, waist circumference, WHtR, fat mass percentage, and higher lean mass percentage (p < 0.05). One standard deviation increase in daily sedentary time was prospectively associated with lower body mass index (ß = -1.22 kg/m2, 95% CI: -2.02, -0.42), waist circumference (ß = -2.39 cm, 95% CI: -4.03, -0.75), and WHtR (ß = -0.014, 95% CI: -0.024, -0.004). Sedentary time at 16 years was not associated with changes in body composition from 16 to 23 years. CONCLUSIONS: Sedentary behavior in adolescence is not adversely associated with body composition profiles in early adulthood. IMPACT: Little is known about the effect of device-measured sedentary behavior on body composition during the transition from adolescence to early adulthood. Among participants in the Santiago Longitudinal Study, more accelerometer-measured sedentary time during adolescence was associated with lower BMI, waist circumference, and waist-to-height ratio in early adulthood though point estimates were generally small in magnitude. Sedentary behavior in adolescence was not detrimentally associated with healthy body composition profiles in early adulthood. Public health interventions aimed at reducing obesity rates could consider other behaviors, such as physical activity and healthy diet, instead of sitting time.

Associations of Lean Mass, Muscular Strength, and Physical Function with Trabecular Bone Score in Older Adults.

INTRODUCTION/BACKGROUND: Trabecular bone score (TBS) is an indirect measurement of bone quality and microarchitecture determined from dual-energy X-ray absorptiometry (DXA) imaging of the lumbar spine. TBS predicts fracture risk independent of bone mass/density, suggesting this assessment of bone quality adds value to the understanding of patients' bone health. While lean mass and muscular strength have been associated with higher bone density and lower fracture risk among older adults, the literature is limited regarding the relationship of lean mass and strength with TBS. The purpose of this study was to determine associations of DXA-determined total body and trunk lean mass, maximal muscular strength, and gait speed as a measure of physical function, with TBS in 141 older adults (65-84 yr, 72.5 +/- 5.1 yr, 74% women). METHODOLOGY: Assessments included lumbar spine (L1-L4) bone density and total body and trunk lean mass by DXA, lower body (leg press) and upper body (seated row) strength by one repetition maximum tests, hand grip strength, and usual gait speed. TBS was derived from the lumbar spine DXA scan. Multivariable linear regression determined the contribution of proposed predictors to TBS. RESULTS: After adjusting for age, sex, and lumbar spine bone density, upper body strength significantly predicted TBS (unadjusted/adjusted R2= 0.16/ 0.11, ß coefficient =0.378, p=0.005), while total body lean mass index showed a trend in the expected direction (ß coefficient =0.243, p=0.053). Gait speed and grip strength were not associated with TBS (p>0.05). CONCLUSION: Maximum strength of primarily back muscles measured as the seated row appears important to bone quality as measured by TBS, independent of bone density. Additional research on exercise training targeting back strength is needed to determine its clinical utility in preventing vertebral fractures among older adults.

BrainAge of patients with severe late-life depression referred for electroconvulsive therapy.

BACKGROUND: Severe depression is associated with accelerated brain aging. BrainAge gap, the difference between predicted and observed BrainAge, was investigated in patients with late-life depression (LLD). We aimed to examine BrainAge gap in LLD and its associations with clinical characteristics indexing LLD chronicity, current severity, prior to electroconvulsive therapy (ECT) and ECT outcome. METHODS: Data was analyzed from the Mood Disorders in Elderly treated with Electroconvulsive Therapy (MODECT) study. A previously established BrainAge algorithm (BrainAge R by James Cole, (https://github.com/james-cole/brainageR)) was applied to pre-ECT T1-weighted structural MRI-scans of 42 patients who underwent ECT. RESULTS: A BrainAge gap of 1.8 years (SD = 5.5) was observed, Cohen's d = 0.3. No significant associations between BrainAge gap, number of previous episodes, current episode duration, age of onset, depression severity, psychotic symptoms or ECT outcome were observed. LIMITATIONS: Limited sample size. CONCLUSIONS: Our initial findings suggest an older BrainAge than chronological age in patients with severe LLD referred for ECT, however with high degree of variability and direction of the gap. No associations were found with clinical measures. Larger samples are needed to better understand brain aging and to evaluate the usability of BrainAge gap as potential biomarker of prognosis an treatment-response in LLD. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02667353.

Neuroimaging-Derived Predicted Brain Age and Alcohol Use Among Community-Dwelling Older Adults.

OBJECTIVES: Observational studies have suggested that moderate alcohol use is associated with reduced risk of dementia. However, the nature of this association is not understood. We investigated whether light to moderate alcohol use may be associated with slower brain aging, among a cohort of older community-dwelling adults using a biomarker of brain age based on structural neuroimaging measures. DESIGN: Cross-sectional observational study. PARTICIPANTS: Well-characterized members of a longitudinal cohort study who underwent neuroimaging. We categorized the 163 participants (mean age 76.7 ± 7.7, 60% women) into current nondrinkers, light drinkers (1-7 drinks/week) moderate drinkers (>7-14 drinks/week), or heavier drinkers (>14 drinks/week). MEASUREMENTS: We calculated brain-predicted age using structural MRIs processed with the BrainAgeR program, and calculated the difference between brain-predicted age and chronological age (brain-predicted age difference, or brain-PAD). We used analysis of variance to determine if brain-PAD differed across alcohol groups, controlling for potential confounders. RESULTS: Brain-PAD differed across alcohol groups (F[3, 150] = 4.02; p = 0.009) with heavier drinkers showing older brain-PAD than light drinkers (by about 6 years). Brain-PAD did not differ across light, moderate, and nondrinkers. Similar results were obtained after adjusting for potentially mediating health-related measures, and after excluding individuals with a history of heavier drinking. DISCUSSION: Among this sample of healthy older adults, consumption of more than 14 drinks/week was associated with a biomarker of advanced brain aging. Light and moderate drinking was not associated with slower brain aging relative to non-drinking.

Association of Physical Activity and Screen Time With Body Mass Index Among US Adolescents.

Importance: The Physical Activity Guidelines Advisory Committee Scientific Report identified important research gaps to inform future guidance for adolescents, including limited evidence on the importance of sedentary behaviors (screen time) and their interactions with physical activity for adolescent health outcomes, including overweight and obesity. Objective: To identify the independent associations of physical activity and screen time categories, and the interactions between physical activity and screen time categories, with body mass index (BMI) and overweight and obesity in adolescents. Design, Setting, and Participants: This cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) Study collected from September 10, 2018, to September 29, 2020. Data were analyzed from July 8 to December 20, 2022. A total of 5797 adolescents aged 10 to 14 years from 21 racially and ethnically diverse study sites across the US were included in the analysis. Exposures: Categories of total step count per day (with 1000 to 6000 steps per day indicating low, >6000 to 12 000 steps per day indicating medium, and >12 000 steps per day indicating high), as measured by a wearable digital device (Fitbit), and categories of self-reported screen time hours per day (with 0 to 4 hours per day indicating low, >4 to 8 hours per day indicating medium, and >8 hours per day indicating high). Main Outcomes and Measures: Participant BMI was calculated as weight in kilograms divided by height in meters squared and converted into sex- and age-specific percentiles in accordance with the Centers for Disease Control and Prevention growth curves and definitions. Individuals were classified as having overweight or obesity if their BMI was in the 85th percentile or higher for sex and age. Results: Among 5797 adolescents included in the analytic sample, 50.4% were male, 61.0% were White, 35.0% had overweight or obesity, and the mean (SD) age was 12.0 (0.6) years. Mean (SD) reported screen time use was 6.5 (5.4) hours per day, and mean (SD) overall step count was 9246.6 (3111.3) steps per day. In models including both screen time and step count, medium (risk ratio [RR], 1.24; 95% CI, 1.12-1.37) and high (RR, 1.29; 95% CI, 1.16-1.44) screen time categories were associated with higher overweight or obesity risk compared with the low screen time category. Medium (RR, 1.19; 95% CI, 1.06-1.35) and low (RR, 1.30; 95% CI, 1.11-1.51) step count categories were associated with higher overweight or obesity risk compared with the high step count category. Evidence of effect modification between screen time and step count was observed for BMI percentile. For instance, among adolescents with low screen use, medium step count was associated with a 1.55 higher BMI percentile, and low step count was associated with a 7.48 higher BMI percentile. However, among those with high screen use, step count categories did not significantly change the association with higher BMI percentile (low step count: 8.79 higher BMI percentile; medium step count: 8.76 higher BMI percentile; high step count: 8.26 higher BMI percentile). Conclusions and Relevance: In this cross-sectional study, a combination of low screen time and high step count was associated with lower BMI percentile in adolescents. These results suggest that high step count may not offset higher overweight or obesity risk for adolescents with high screen time, and low screen time may not offset higher overweight or obesity risk for adolescents with low step count. These findings addressed several research gaps identified by the Physical Activity Guidelines Advisory Committee Scientific Report and may be used to inform future screen time and physical activity guidance for adolescents.

Greater accelerometer-measured physical activity is associated with better cognition and cerebrovascular health in older adults.

OBJECTIVES: Physical activity (PA) may help maintain brain structure and function in aging. Since the intensity of PA needed to effect cognition and cerebrovascular health remains unknown, we examined associations between PA and cognition, regional white matter hyperintensities (WMH), and regional cerebral blood flow (CBF) in older adults. METHOD: Forty-three older adults without cognitive impairment underwent magnetic resonance imaging (MRI) and comprehensive neuropsychological assessment. Waist-worn accelerometers objectively measured PA for approximately one week. RESULTS: Higher time spent in moderate to vigorous PA (MVPA) was uniquely associated with better memory and executive functioning after adjusting for all light PA. Higher MVPA was also uniquely associated with lower frontal WMH volume although the finding was no longer significant after additionally adjusting for age and accelerometer wear time. MVPA was not associated with CBF. Higher time spent in all light PA was uniquely associated with higher CBF but not with cognitive performance or WMH volume. CONCLUSIONS: Engaging in PA may be beneficial for cerebrovascular health, and MVPA in particular may help preserve memory and executive function in otherwise cognitively healthy older adults. There may be differential effects of engaging in lighter PA and MVPA on MRI markers of cerebrovascular health although this needs to be confirmed in future studies with larger samples. Future randomized controlled trials that increase PA are needed to elucidate cause-effect associations between PA and cerebrovascular health.

The Independent Walking for Brain Health Intervention for Older Adults: Protocol for a Pilot Randomized Controlled Trial.

BACKGROUND: Extensive research suggests that physical activity (PA) is important for brain and cognitive health and may help to delay or prevent Alzheimer's disease and related dementias. Most PA interventions designed to improve brain health in older adults have been conducted in laboratory, gym, or group settings that require extensive resources and travel to the study site or group sessions. Research is needed to develop novel interventions that leverage mobile health (mHealth) technologies to help older adults increase their engagement in PA in free-living environments, reducing participant burden and increasing generalizability of research findings. Moreover, promoting engagement in moderate-to-vigorous PA (MVPA) may be most beneficial to brain health; thus, using mHealth to help older adults increase time spent in MVPA in free-living environments may help to offset the burden of Alzheimer's disease and related dementias and improve quality of life in older age. OBJECTIVE: We developed a novel PA intervention that leverages mHealth to help older adults achieve more minutes of MVPA independently. This pilot study was a 12-week randomized controlled trial to investigate the feasibility of providing just-in-time (JIT) feedback about PA intensity during free-living exercise sessions to help older adults meet current PA recommendations (150 minutes per week of MVPA). METHODS: Participants were eligible if they were cognitively healthy English speakers aged between 65 and 80 years without major cardiovascular, neurologic, or mental health conditions; could ambulate independently; and undergo magnetic resonance imaging. Enrollment occurred from October 2017 to March 2020. Participants randomized to the PA condition received an individualized exercise prescription and an mHealth device that provided heart rate-based JIT feedback on PA intensity, allowing them to adjust their behavior in real time to maintain MVPA during exercise sessions. Participants assigned to the healthy aging education condition received a reading prescription consisting of healthy aging topics and completed weekly quizzes based on the materials. RESULTS: In total, 44 participants were randomized to the intervention. A follow-up manuscript will describe the results of the intervention as well as discuss screening, recruitment, adverse events, and participants' opinions regarding their participation in the intervention. CONCLUSIONS: The long-term goal of this intervention is to better understand how MVPA affects brain and cognitive health in the real world and extend laboratory findings to everyday life. This pilot randomized controlled trial was conducted to determine the feasibility of using JIT heart rate zone feedback to help older adults independently increase time spent in MVPA while collecting data on the plausible mechanisms of change (frontal and medial temporal cerebral blood flow and cardiorespiratory fitness) that may affect cognition (memory and executive function) to help refine a planned stage 2 behavioral trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03058146; https://clinicaltrials.gov/ct2/show/NCT03058146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42980.

Effects of Mindfulness Training and Exercise on Cognitive Function in Older Adults: A Randomized Clinical Trial.

Importance: Episodic memory and executive function are essential aspects of cognitive functioning that decline with aging. This decline may be ameliorable with lifestyle interventions. Objective: To determine whether mindfulness-based stress reduction (MBSR), exercise, or a combination of both improve cognitive function in older adults. Design, Setting, and Participants: This 2 × 2 factorial randomized clinical trial was conducted at 2 US sites (Washington University in St Louis and University of California, San Diego). A total of 585 older adults (aged 65-84 y) with subjective cognitive concerns, but not dementia, were randomized (enrollment from November 19, 2015, to January 23, 2019; final follow-up on March 16, 2020). Interventions: Participants were randomized to undergo the following interventions: MBSR with a target of 60 minutes daily of meditation (n = 150); exercise with aerobic, strength, and functional components with a target of at least 300 minutes weekly (n = 138); combined MBSR and exercise (n = 144); or a health education control group (n = 153). Interventions lasted 18 months and consisted of group-based classes and home practice. Main Outcomes and Measures: The 2 primary outcomes were composites of episodic memory and executive function (standardized to a mean [SD] of 0 [1]; higher composite scores indicate better cognitive performance) from neuropsychological testing; the primary end point was 6 months and the secondary end point was 18 months. There were 5 reported secondary outcomes: hippocampal volume and dorsolateral prefrontal cortex thickness and surface area from structural magnetic resonance imaging and functional cognitive capacity and self-reported cognitive concerns. Results: Among 585 randomized participants (mean age, 71.5 years; 424 [72.5%] women), 568 (97.1%) completed 6 months in the trial and 475 (81.2%) completed 18 months. At 6 months, there was no significant effect of mindfulness training or exercise on episodic memory (MBSR vs no MBSR: 0.44 vs 0.48; mean difference, -0.04 points [95% CI, -0.15 to 0.07]; P = .50; exercise vs no exercise: 0.49 vs 0.42; difference, 0.07 [95% CI, -0.04 to 0.17]; P = .23) or executive function (MBSR vs no MBSR: 0.39 vs 0.31; mean difference, 0.08 points [95% CI, -0.02 to 0.19]; P = .12; exercise vs no exercise: 0.39 vs 0.32; difference, 0.07 [95% CI, -0.03 to 0.18]; P = .17) and there were no intervention effects at the secondary end point of 18 months. There was no significant interaction between mindfulness training and exercise (P = .93 for memory and P = .29 for executive function) at 6 months. Of the 5 prespecified secondary outcomes, none showed a significant improvement with either intervention compared with those not receiving the intervention. Conclusions and Relevance: Among older adults with subjective cognitive concerns, mindfulness training, exercise, or both did not result in significant differences in improvement in episodic memory or executive function at 6 months. The findings do not support the use of these interventions for improving cognition in older adults with subjective cognitive concerns. Trial Registration: ClinicalTrials.gov Identifier: NCT02665481.

Recommendations for Identifying Valid Wear for Consumer-Level Wrist-Worn Activity Trackers and Acceptability of Extended Device Deployment in Children.

BACKGROUND: Self-reported physical activity is often inaccurate. Wearable devices utilizing multiple sensors are now widespread. The aim of this study was to determine acceptability of Fitbit Charge HR for children and their families, and to determine best practices for processing its objective data. METHODS: Data were collected via Fitbit Charge HR continuously over the course of 3 weeks. Questionnaires were given to each child and their parent/guardian to determine the perceived usability of the device. Patterns of data were evaluated and best practice inclusion criteria recommended. RESULTS: Best practices were established to extract, filter, and process data to evaluate device wear, r and establish minimum wear time to evaluate behavioral patterns. This resulted in usable data available from 137 (89%) of the sample. CONCLUSIONS: Activity trackers are highly acceptable in the target population and can provide objective data over longer periods of wear. Best practice inclusion protocols that reflect physical activity in youth are provided.

Physical activity intensity is associated with cognition and functional connectivity in Parkinson's disease.

BACKGROUND: Cognitive impairment is common in Parkinson's disease (PD) and often leads to dementia, with no effective treatment. Aging studies suggest that physical activity (PA) intensity has a positive impact on cognition and enhanced functional connectivity may underlie these benefits. However, less is known in PD. This cross-sectional study examined the relationship between PA intensity, cognitive performance, and resting state functional connectivity in PD and whether PA intensity influences the relationship between functional connectivity and cognitive performance. METHODS: 96 individuals with mild-moderate PD completed a comprehensive neuropsychological battery. Intensity of PA was objectively captured over a seven-day period using a wearable device (ActiGraph). Time spent in light and moderate intensity PA was determined based on standardized actigraphy cut points. Resting-state fMRI was assessed in a subset of 50 individuals to examine brain-wide functional connectivity. RESULTS: Moderate intensity PA (MIPA), but not light PA, was associated with better global cognition, visuospatial function, memory, and executive function. Individuals who met the WHO recommendation of ≥150 min/week of MIPA demonstrated better global cognition, executive function, and visuospatial function. Resting-state functional connectivity associated with MIPA included a combination of brainstem, hippocampus, and regions in the frontal, cingulate, and parietal cortices, which showed higher connectivity across the brain in those achieving the WHO MIPA recommendation. Meeting this recommendation positively moderated the associations between identified functional connectivity and global cognition, visuospatial function, and language. CONCLUSION: Encouraging MIPA, particularly the WHO recommendation of ≥150 min of MIPA/week, may represent an important prescription for PD cognition.

Promoting Physical Activity in a Spanish-Speaking Latina Population of Low Socioeconomic Status With Chronic Neurological Disorders: Proof-of-Concept Study.

BACKGROUND: Physical activity (PA) is known to improve quality of life (QoL) as well as reduce mortality and disease progression in individuals with chronic neurological disorders. However, Latina women are less likely to participate in recommended levels of PA due to common socioeconomic barriers, including limited resources and access to exercise programs. Therefore, we developed a community-based intervention with activity monitoring and behavioral coaching to target these barriers and facilitate sustained participation in an exercise program promoting PA. OBJECTIVE: The aim of this study was to determine the feasibility and efficacy of a community-based intervention to promote PA through self-monitoring via a Fitbit and behavioral coaching among Latina participants with chronic neurological disorders. METHODS: We conducted a proof-of-concept study among 21 Spanish-speaking Latina participants recruited from the Los Angeles County and University of Southern California (LAC+USC) neurology clinic; participants enrolled in the 16-week intervention at The Wellness Center at The Historic General Hospital in Los Angeles. Demographic data were assessed at baseline. Feasibility was defined by participant attrition and Fitbit adherence. PA promotion was determined by examining change in time spent performing moderate-to-vigorous PA (MVPA) over the 16-week period. The effect of behavioral coaching was assessed by quantifying the difference in MVPA on days when coaching occurred versus on days without coaching. Change in psychometric measures (baseline vs postintervention) and medical center visits (16 weeks preintervention vs during the intervention) were also examined. RESULTS: Participants were of low socioeconomic status and acculturation. A total of 19 out of 21 (90%) participants completed the study (attrition 10%), with high Fitbit wear adherence (mean 90.31%, SD 10.12%). Time performing MVPA gradually increased by a mean of 0.16 (SD 0.23) minutes per day (P<.001), which was equivalent to an increase of approximately 18 minutes in MVPA over the course of the 16-week study period. Behavioral coaching enhanced intervention effectiveness as evidenced by a higher time spent on MVPA on days when coaching occurred via phone (37 min/day, P=.02) and in person (45.5 min/day, P=.01) relative to days without coaching (24 min/day). Participants improved their illness perception (effect size g=0.30) and self-rated QoL (effect size g=0.32). Additionally, a reduction in the number of medical center visits was observed (effect size r=0.44), and this reduction was associated with a positive change in step count during the study period (P.=04). CONCLUSIONS: Self-monitoring with behavioral coaching is a feasible community-based intervention for PA promotion among Latina women of low socioeconomic status with chronic neurological conditions. PA is known to be important for brain health in neurological conditions but remains relatively unexplored in minority populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT04820153; https://clinicaltrials.gov/ct2/show/NCT04820153.

Temporal relationships of ecological momentary mood and actigraphy-based sleep measures in bipolar disorder.

Sleep disturbances are a key feature of bipolar disorder (BD), and poor sleep has been linked to mood symptoms. Recent use of ecological momentary assessment (EMA) has allowed for nuanced exploration of the sleep-mood link; though, the scale and directionality of this relationship is still unclear. Using EMA, actigraphy, and self-reported sleep measures, this study examines the concurrent and predictive relationships between sleep and mood. Participants with BD (n = 56) wore actigraphy devices for up to 14 days and completed validated scales and daily EMA surveys about mood and sleep quality. Linear mixed models were used to examine overall and time-lagged relationships between sleep and mood variables. EMA mood ratings were correlated with validated rating scales for depression, mania, anxiety, and impulsivity. Poor self-reported sleep quality was associated with worse overall ratings of sadness and anger. Worse self-reported sleep quality was associated with greater sadness the following day. Higher daytime impulsivity was associated with worse sleep quality the following night. Exploratory analyses found relationships between worse and more variable mood (sadness, anger, and impulsivity) with worse and more variable sleep that evening (efficiency, WASO, and sleep onset time). The sample size was modest, fairly homogenous, and included mainly euthymic persons with BD. EMA-based assessments of mood and sleep are correlated with validated scale scores and provide novel insight into intra-individual variability. Further work on the complex two-way interactions between sleep and mood is needed to better understand how to improve outcomes in BD.

Social Mobile Approaches to Reducing Weight (SMART) 2.0: protocol of a randomized controlled trial among young adults in university settings.

BACKGROUND: Excess weight gain in young adulthood is associated with future weight gain and increased risk of chronic disease. Although multimodal, technology-based weight-loss interventions have the potential to promote weight loss among young adults, many interventions have limited personalization, and few have been deployed and evaluated for longer than a year. We aim to assess the effects of a highly personalized, 2-year intervention that uses popular mobile and social technologies to promote weight loss among young adults. METHODS: The Social Mobile Approaches to Reducing Weight (SMART) 2.0 Study is a 24-month parallel-group randomized controlled trial that will include 642 overweight or obese participants, aged 18-35 years, from universities and community colleges in San Diego, CA. All participants receive a wearable activity tracker, connected scale, and corresponding app. Participants randomized to one intervention group receive evidence-based information about weight loss and behavior change techniques via personalized daily text messaging (i.e., SMS/MMS), posts on social media platforms, and online groups. Participants in a second intervention group receive the aforementioned elements in addition to brief, technology-mediated health coaching. Participants in the control group receive a wearable activity tracker, connected scale, and corresponding app alone. The primary outcome is objectively measured weight in kilograms over 24 months. Secondary outcomes include anthropometric measurements; physiological measures; physical activity, diet, sleep, and psychosocial measures; and engagement with intervention modalities. Outcomes are assessed at baseline and 6, 12, 18, and 24 months. Differences between the randomized groups will be analyzed using a mixed model of repeated measures and will be based on the intent-to-treat principle. DISCUSSION: We hypothesize that both SMART 2.0 intervention groups will significantly improve weight loss compared to the control group, and the group receiving health coaching will experience the greatest improvement. We further hypothesize that differences in secondary outcomes will favor the intervention groups. There is a critical need to advance understanding of the effectiveness of multimodal, technology-based weight-loss interventions that have the potential for long-term effects and widespread dissemination among young adults. Our findings should inform the implementation of low-cost and scalable interventions for weight loss and risk-reducing health behaviors. TRIAL REGISTRATION: ClinicalTrials.gov NCT03907462 . Registered on April 9, 2019.

Community-Dwelling Older Adults and Physical Activity Recommendations: Patterns of Aerobic, Strengthening, and Balance Activities.

Though it is known that most older adults do not meet the recommended physical activity (PA) guidelines, little is known regarding their participation in balance activities or the full guidelines. Therefore, we sought to describe PA patterns among 1,352 community-dwelling older adult participants of the Adult Changes in Thought study, a longitudinal cohort study exploring dementia-related risk factors. We used a modified version of the Community Healthy Activities Model Program for Seniors questionnaire to explore PA performed and classify participants as meeting or not meeting the full guidelines or any component of the guidelines. Logistic regression was used to identify factors associated with meeting PA guidelines. Despite performing 10 hr of weekly PA, only 11% of participants met the full guidelines. Older age, greater body mass index, needing assistance with instrumental daily activities, and heart disease were associated with decreased odds of meeting PA guidelines. These results can guide interventions that address PA among older adults.

Associations Between Perceived Neighborhood Walkability and Device-Based Physical Activity and Sedentary Behavior Patterns in Older Adults.

Neighborhood walkability has been associated with self-reported sedentary behavior (SB) and self-reported and objective physical activity. However, self-reported measures of SB are inaccurate and can lead to biased estimates, and few studies have examined how associations differ by gender and age. The authors examined the relationships between perceived neighborhood walkability measured with the Physical Activity Neighborhood Environment Scale (scored 1.0-4.0) and device-based SB and physical activity in a cohort of community-dwelling older adults (N = 1,077). The authors fit linear regression models adjusting for device wear time, demographics, self-rated health, and accounting for probability of participation. The Higher Physical Activity Neighborhood Environment Scale was associated with higher steps (+676 steps/point on the Physical Activity Neighborhood Environment Scale, p = .001) and sit-to-stand transitions (+2.4 transitions/point, p = .018). Though not statistically significant, stratified analyses suggest an attenuation of effect for those aged 85 years and older and for women. Consistent with previous literature, neighborhood walkability was associated with more steps, though not with physical activity time. The neighborhood environment may also influence SB.