CHARACTERIZING THE LIFESTYLE ENGAGEMENT OF OLDER ADULTS: IMPLICATIONS FOR COGNITIVE FUNCTIONING, PHYSICAL FRAILTY, AND FUTURE INTERVENTIONS

Background: Active life-expectancies post-retirement have increased, allowing for new opportunities for cognitive, social, and physical engagement to mitigate later-life health outcomes. The question remains as to how we use information about older adults’ lifestyle engagement to predict health outcomes and deploy interventions. Here we characterized qualitatively-distinct lifestyle engagement groups of older adults, and examined whether they had differential risk for cognitive and physical outcomes. Method: Data come from the Ginkgo Evaluation of Memory Study (N=3,069). Data collection occurred from September 2000 and April 2008. Participants were assessed up to 7.5 years. Baseline activities were measured using the Lifestyle Activity Questionnaire. We conducted latent class analysis to group individuals by their activity response patterns, and examined their risk of dementia using discrete-time proportional hazards modeling. Dementia was screened for every six months and clinically-adjudicated. We then examined whether the lifestyle engagement groups also had differential changes in domain-specific cognition and physical frailty criteria using mixed effects modeling. All models were adjusted for baseline age, sex, race, education, study site, treatment group, medical comorbidities, and depressive symptoms. Results: A 4-class model adequately characterized lifestyle engagement in the current sample. The Social Intellectual (22%) and Intellectual (18%) groups had high engagement in intellectual activities, whereas the Social Intellectual and Social groups (32%) had high engagement in social institutional activities. The Least Active group (28%) had lower engagement in most activities and had the highest risk of incident dementia. We found that the Social Intellectual group had higher baseline performance across cognitive domains, as well as attenuated declines in memory. Finally, we found that the Social Intellectual group had lower risk of prevalent slow gait compared to all groups, and lower risk of prevalent exhaustion compared to the Least Active group. Implications: Older adults who were highly active in intellectual and social institutional activities had the lowest risk of poor health outcomes. Behavioral interventions should aim to supplement an individual’s current lifestyle to encourage broad engagement in cognitively- and socially-enriching activities. Future group-level interventions can specifically target the activity types that are meaningful to older adults to facilitate adherence and enjoyment of health-promoting behaviors

Dual Roles of Fitness and Fatigability in the Life Space Mobility of Older Adults

Background: Cardiorespiratory fitness and fatigability are interrelated components of physical capacity that may jointly facilitate movement within one’s living environment (life-space mobility). We examined whether fitness and perceived fatigability, and the interaction between them, were associated with life-space mobility in a well-characterized cohort of older adults. Methods: Participants were from the preliminary data release of the Study of Muscle, Mobility, and Aging (SOMMA) baseline cohort (N=387, Mage=76.4±5.0, 57% women). Life Space Assessment scores (range: 0-120) incorporated level, frequency, and assistance used for life-space mobility (Mean=82.7±18.8). Fitness was measured as VO2peak (Mean=19.5±4.2 mL/kg/min) from symptom-limited treadmill testing. Fatigability cut-points included: 1) Borg Rating of Perceived Exertion (RPE) ≥10 after a steady-state treadmill test, 2) the Pittsburgh Fatigability Scale (PFS) Physical ≥15, and 3) PFS Mental ≥13. Linear regressions were adjusted for demographic, lifestyle, and health confounders. Results: The relationship between fitness and life-space mobility was nonlinear, where those within the lower range of fitness scores (VO2peak≤18) had 2.2-point greater life-space scores per 1-mL/kg/min greater VO2peak (95% CI: 0.68, 3.67, p=.005). The association was not significant for the upper range of fitness scores (VO2peak>18). Participants with higher fatigability on all measures (RPE≥10, PFS Physical≥15, PFS Mental≥13) had a 7.6-point lower mean life-space score (95% CI: -13.84, -1.34) after adjusting for demographics, but this was not significant after further adjusting for lifestyle and health factors. There was potential moderation of the fitness-life-space relationship by fatigability, where associations within the lower fitness range (VO2peak≤18) were only significant for those with RPE≥10 (B=3.3, 95% CI: 1.06, 5.53, p-interaction=.078). Conclusion: Fitness may primarily limit life-space mobility if it falls below a critical threshold, where older individuals may need to operate closer to their maximum aerobic capacity to traverse their daily environments. Higher fatigability may moderate this relationship, as those with both low fitness and high fatigability had the lowest life-space scores. Public health interventions that target this high-risk group may mitigate further functional declines resulting from life-space constriction

Relationship Between Personality Measures and Perceived Mental Fatigability.

OBJECTIVE: Examine the association between personality measures and perceived mental fatigability. METHODS: We performed a cross-sectional analysis in N=1670 men, age 84.3±4.1 years. Multivariable linear regression models were used to examine the covariate adjusted association between personality measures (conscientiousness, optimism, goal reengagement, and goal disengagement) and perceived mental fatigability (measured with the validated 10-item Pittsburgh Fatigability Scale, PFS). RESULTS: One standard deviation lower conscientiousness (β=-0.91, p<.0001) and optimism (β=-0.63, p<.0001), and higher goal reengagement (β=0.51, p=.01) scores were independently associated with higher PFS Mental scores adjusted for age, cognitive function, self-reported health status, depressive symptoms, sleep disturbance, physical activity, and goal disengagement. DISCUSSION: Lower conscientiousness, optimism, and higher goal reengagement were linked with more severe perceived mental fatigability in older men. Personality traits may potentially contribute to early risk assessment for fatigability in later life. Future work should be longitudinal in nature and include personality assessments to confirm the temporality of the relationships observed

Neural correlates of working memory training: Evidence for plasticity in older adults.

Brain activity typically increases with increasing working memory (WM) load, regardless of age, before reaching an apparent ceiling. However, older adults exhibit greater brain activity and reach ceiling at lower loads than younger adults, possibly reflecting compensation at lower loads and dysfunction at higher loads. We hypothesized that WM training would bolster neural efficiency, such that the activation peak would shift towards higher memory loads after training. Pre-training, older adults showed greater recruitment of the WM network than younger adults across all loads, with decline at the highest load. Ten days of adaptive training on a verbal WM task improved performance and led to greater brain responsiveness at higher loads for both groups. For older adults the activation peak shifted rightward towards higher loads. Finally, training increased task-related functional connectivity in older adults, both within the WM network and between this task-positive network and the task-negative/default-mode network. These results provide new evidence for functional plasticity with training in older adults and identify a potential signature of improvement at the neural level

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

BACKGROUND: Falls occur annually in 25% of adults aged ≥65 years. Fall-related injuries are increasing, highlighting the need to identify modifiable risk factors. METHODS: Role of fatigability on prospective, recurrent, and injurious fall risk was examined in 1 740 men aged 77-101 years 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 ≥1 year 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. RESULTS: 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. CONCLUSIONS: 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

Changes in Objectively Measured Physical Activity Are Associated With Perceived Physical and Mental Fatigability in Older Men.

BackgroundLower physical activity (PA) is associated with greater perceived fatigability, a person-centered outcome. The association between change in PA and fatigability with advanced age has yet to be established.MethodsCommunity-dwelling older men (N = 1 113, age = 84.1 ± 3.9 years at Year 14) had free-living PA assessed using SenseWear Armband prospectively at Year 7 (2007-2009) and Year 14 (2014-2016) of Osteoporotic Fractures in Men Study, a longitudinal cohort established in 2000 (baseline). We categorized percent changes in PA into groups (large decline → large increase) for 4 metrics: step count, light intensity PA (LIPA, metabolic equivalents [METs] >1.5 to <3.0), moderate-to-vigorous PA (MVPA, METs ≥ 3.0), and sedentary behavior (SB, METs ≤ 1.5, excluding sleep). Perceived physical and mental fatigability were measured (Year 14) with the Pittsburgh Fatigability Scale (PFS, higher score = greater fatigability; range = 0-50). Associations between each metric of percent changes in PA and fatigability were examined using linear regression, adjusted for demographics, change in health conditions, and Year 7 step count or total PA (METs > 1.5).ResultsMen declined 2 336 ± 2 546 (34%) steps/d, 24 ± 31 (25%) LIPA min/d, 33 ± 58 (19%) MVPA min/d, and increased 40 ± 107 (6%) SB min/d over 7.2 ± 0.7 years. Compared to large decline (% change less than -50%), those that maintained or increased step count had 3-8 points lower PFS Physical scores; those who maintained or increased LIPA and MVPA had 2-3 and 2-4 points lower PFS Physical scores, respectively (all p ≤ .01). Associations were similar, but smaller, for PFS Mental scores.ConclusionOlder men who maintained or increased PA had lower fatigability, independent of initial PA. Our findings inform the types and doses of PA that should be targeted to reduce fatigability in older adults

Age differences in functional network reconfiguration with working memory training

Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10- days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task- related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default- mode network for younger adults, it enhanced efficiency within a task- specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default- mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between- network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training.We examined how working memory (WM) training affects the integration and modularity of functional networks in older and younger adults. Younger adults increase network segregation with training, suggesting more automated processing. Older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/1/hbm25337.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/2/hbm25337-sup-0001-supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/3/hbm25337_am.pd

Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA) and 20 older adults (OA) were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of cognitive transfer in both younger and older adults