To identify the relative contributions and importance of modifiable fitness and demographic variables to cognitive performance in a cohort of healthy older adults.

Metrics of modifiable fitness (gait speed, respiratory function, grip strength, and body mass index (BMI)) and cognition (executive function, episodic memory, and processing speed) were assessed in 619 older adults from the Health and Retirement Study 2016 wave (mean age = 74.9, sd = 6.9; mean education = 13.4 years, sd = 2.6; 42% female). General linear models were employed to assess the contribution of modifiable fitness variables in predicting three domains of cognition: executive function, episodic memory, and processing speed. Demographics (age, sex, education, time between appointments, and a chronic disease score) were entered as covariates for each model. Relative importance metrics were computed for all variables in each model using Lindeman, Merenda, and Gold (lmg) analysis, a technique which decomposes a given model’s explained variance to describe the average contribution of each predictor variable, independent of its position in the linear model.

When all variables were entered into the general linear model, demographic and modifiable fitness variables explained 35%, 24%, and 26% of the variance in executive function, episodic memory, and processing speed, respectively (all three models were significant, p <0.001). Age, education, respiratory function, and walking speed had higher relative importance values (all lmgs > 1.8) compared to BMI, grip strength, and other covariates in all three models (all lmgs < 1.3). Gender was also relatively important in the executive function (lmg = 4.2) and episodic memory models (lmg = 5.0). Of the modifiable fitness variables, walking speed and respiratory function had the greatest lmg values (5.8 and 6.4 respectively) in the executive function model, similar to demographic variables age (lmg = 6.0) and education (lmg = 8.9). When demographic variables were entered as covariates, modifiable fitness variables collectively accounted for an additional 9.7%, 6.3%, and 6.0% variance in the executive function, episodic memory, and processing speed models respectively (all three models were significant, p <0.001).

Our findings indicate that walking speed and respiratory function are of similar importance compared to “traditional” demographic variables such as age and education in predicting cognitive performance in a cohort of healthy older adults. Moreover, modifiable fitness variables accounted for unique variance in executive function, episodic memory, and processing speed after accounting for age and education. Modifiable fitness variables explained the most unique variance in executive function. These results extend the current literature by demonstrating that modifiable fitness variables, even when assessed with brief and relatively coarse measures of physical performance, may be useful in predicting cognitive function. Moreover, the results highlight the need to assess metrics of cognitive reserve, such as education, as well as modifiable fitness variables and their respective roles in accounting for cognitive performance. The data further suggest that relative contributions of physical performance metrics may vary by cognitive domain in healthy older adults.

Accurately interpreting change in cognitive functioning is an essential aspect of clinical care for older adults. Several approaches to identifying ‘true’ cognitive change in a single cognitive measure are available (e.g., reliable change methods, regression-based norms); however, neuropsychologists in clinical settings often rely on simple score differences rather than advanced analytical procedures especially since they examine multiple test performances. This study sought to establish quick-reference normative criteria to help neuropsychologists identify how frequently significant change occurs across multiple cognitive measures in cognitively normal older adults.

Data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants were 401 older adults who were classified as cognitively normal at baseline and at 24-month follow-up. In ADNI, these clinical classifications are made separately from the assessment of cognitive performance, including cognitive change. The sample was 50.1% female, 93.5% non-Hispanic White, 4.0% non-Hispanic Black, 1.5% Asian American, and 1.0% other race/ethnicity, with a mean age of 76.0 years (SD = 4.9). Mean education was 16.4 years (SD = 2.7). The cognitive battery included: Boston Naming Test, Category Fluency Test, Trails A & B, Clock Drawing Test, and Auditory Verbal Learning Test, Trial 1-5 Total and Delayed Recall. Change scores between baseline performance and 24-month follow-up were calculated for each measure. The natural distribution of change scores was examined for each measure and cut points representing the 5th and 10th percentile were applied to each distribution to classify participants who exhibited substantial declines in performance on a given measure. We then examined the multivariate frequency of statistically rare change scores for each individual.

As expected in a normal sample, overall cognitive performance was generally stable between baseline and 24-month followup. Across cognitive measures, 43.6% of participants had at least one change score fall below the 10th percentile in the distribution of change scores, and 21.9% had at least one score below the 5th percentile. 13.0% of participants had two or more change scores that fell below the 10th percentile, in comparison to 4.5% with two or more below the 5th percentile. 3.2% of participants had three or more change scores below the 10th percentile, versus 0.5% of participants who had three change scores below the 5th percentile.

Among cognitively normal older adults assessed twice at a 24-month interval with a battery of seven measures, it was not uncommon for an individual to have at least one score fall below the 10th percentile (43% of the sample) or even the 5th percentile (21%) in the natural distribution of change scores. However, only 3.2% of normals had more than two declines in test performance below the 10th percentile, and less than 1% of the sample at more than one change score at the 5th percentile. This suggests that individuals who exhibit more multivariate changes in performance than these standards are likely experiencing an abnormal rate of cognitive decline. Our findings provide a preliminary quick-reference approach to identifying clinically significant cognitive change. Future studies will explore additional batteries and examine multivariate frequencies of change in clinical populations.

Given the aging population, there are significant public health benefits to delaying the onset of Alzheimer’s disease (AD) in individuals at risk. However, adherence to health behaviors (e.g., diet, exercise, sleep hygiene) is low in the general population. The Health Belief Model proposes that beliefs such as perceived threat of disease, perceived benefits and barriers to behavior change, and cues to action are mediators of behavior change. The aim of this study was to gain additional information on current health behaviors and beliefs for individuals at risk for developing AD. This information can then be used to inform behavioral interventions and individualized strategies to improve health behaviors that may reduce AD risk or delay symptom onset.

Surveys were sent to the Rhode Island AD Prevention Registry, which is enriched for at-risk, cognitively normal adults (i.e., majority with a family history and/or an APOE e4 allele). A total of 177 individuals participated in this study. Participants were 68% female; 93% Caucasian and non-Hispanic; mean age of 69.2; 74% with family history of dementia; 40% with subjective memory decline. The survey included measures from the Science of Behavior Change (SoBC) Research Network to measure specific health belief factors, including individual AD risk, perceived future time remaining in one’s life, generalized self-efficacy, deferment of gratification, consideration of future consequences as well as dementia risk awareness and a total risk score for dementia calculated from a combination demographic, health and lifestyle behaviors.

Participants who were older had higher scores for dementia risk (r=0.78), lower future time perspective (r=-0.33), and lower generalized self-efficacy (r=-0.31) (all at p<0.001). Higher education correlated with higher consideration of future consequences (r=-.31, p<0.001) and lower overall dementia risk score (r=-0.23, p=0.006). Of all scales examined, only generalized self-efficacy had a significant linear relationship to both frequency (r2=0.06) and duration (r2=0.08) of weekly physical activity (p<0.001). Total dementia risk score also had significant linear relationships (r2=0.19) with future time perspective (p<0.001) and generalized self-efficacy (p=0.48).

Overall, individuals who rated themselves higher in self-efficacy were more likely to exercise more frequently and for a longer duration. Individuals who had lower overall risk for dementia due to both demographic and behavioral factors were more likely to endorse higher self-efficacy and more perceived time remaining in their lives. Increasing self-efficacy and targeting perceived future time limitations may be key areas to increase motivation and participation in behavioral strategies to reduce AD risk. Developing individual profiles based on these scales may further allow for individually tailored intervention opportunities.

On traditional pattern separation tasks, older adults perform worse than younger adults when identifying similar objects but perform equally well when recognizing repeated objects. When objects are superimposed on semantically related scenes, older adults are influenced by the context to a greater degree than younger adults, leading to errors when identifying similar objects. However, in everyday life, people rarely need to differentiate between two perceptually similar objects. Therefore, we developed a task using short stories to represent similar events people may experience in daily life. Our goal was to investigate the influence of context, detail-type, and age on memory performance.

Twenty-one older and 18 younger adults listened to 20 short stories taking place in either a coffee shop or library, each paired with a unique picture (i.e., context). Participants were asked to imagine the story taking place within the picture. Approximately 20 minutes later, participants answered a yes/no question about a detail from a story superimposed on different contexts. The different context conditions were (1) the same picture from the original story, (2) a similar picture (i.e., a different library or coffee shop picture), (3) a dissimilar picture (i.e., a library picture instead of a coffee shop picture), or (4) a control using a Fourier-transform (FT) image without any spatial-context information. Questions either asked about an identical or similar detail from the story.

Correct answers were analyzed using a 4x2x2 repeated measures ANOVA including context (same, similar, dissimilar, and FT), detail type (identical and similar), and age (younger and older adults). Overall, younger adults were more accurate than older adults, F(1,37)=23.4, p<0.001. However, surprisingly, the context and detail-type made no difference in accuracy, (F’s<1.1) A similar model was used to analyze reaction times. Younger adults were faster than older adults, F(1,37)=23.4, p<0.001. Participants of both ages were faster at correctly responding to the identical detail than the similar detail, F(1,114)=62.87, p<0.001. Context also impacted reaction time, F(3,114)=7.97, p<0.001. All participants were faster while viewing same and similar contexts compared to both the dissimilar and FT contexts (t(39)’s>2.20, p’s<0.05).

We did not find the kinds of age-related effects normally observed on traditional pattern separation tasks. Although younger adults performed better overall, older adults were not any worse when responding to a similar detail compared to an identical detail, which is inconsistent with performance on pattern separation tasks where older adults perform worse when identifying similar objects compared to younger adults. Additionally, older and younger adults were influenced by context in the same way. Previous studies from our laboratory demonstrated that older adults are biased toward the context when recognizing similar objects, but the context in this paradigm did not differentially influence accuracy for either older or younger adults. Potentially, this task relies on more semantic similarity rather than the perceptual similarity of objects. Semantic similarity from the short stories may incorporate more information to better orthogonalize similar memories, rendering retrieval less susceptible to interference.

Subjective cognitive decline (SCD, i.e., perceived cognitive decline without neuropsychological deficits) is associated with Alzheimer’s disease pathology and increased risk for cognitive impairment but is heterogenous in etiology and has been linked to other factors including personality and depression. Mental wellbeing (i.e., the perception and functioning of social, emotional, and health-related aspects of one’s life) has been associated with subjective memory complaints, but its relationship with other subjective cognitive domains is poorly understood. Further characterizing the relationship between mental wellbeing and SCD could refine understanding of SCD and inform development of interventions that prevent progression to objective cognitive decline. This study aimed to describe the relationship between mental wellbeing and subjective decline in multiple cognitive domains and examine whether this relationship differs between older adults with normal cognition and those with mild cognitive impairment (MCI).

Community-dwelling older adults (normal: n = 58, Mage = 73.7±5.6; MCI: n = 43, Mage = 75.9±6.1) completed the Everyday Cognition scale, a validated self-report measure of SCD, and the RAND-36 Health Survey, a validated self-report measure of health-related quality of life which includes a mental wellbeing subscale. Spearman’s rank correlations were conducted between self-reported mental wellbeing and each self-reported cognitive domain (i.e., memory, language, visuospatial, and executive function) for the Normal Cognition and MCI groups.

Worse mental wellbeing was associated with worse subjective language and executive function in the normal group, rs(56) = -.42, p =.001; rs(56) = -.37, p =.005, but not for the MCI group, rs(41) = -.23, p =.15; rs(41) = -.12, p =.46. Worse mental wellbeing was associated with worse subjective visuospatial function in the MCI group, rs(41) = -.39, p =.009, but not in the normal group, rs(56) = -.11, p =.39. For both groups, worse mental wellbeing was associated with worse subjective memory, rs(56) = -.45, p < .001; rs(41) = -.37, p =.02. While this correlation was greater in the normal group, the difference was not significant (z = 0.38, p =.71).

These results suggest that perceptions of mental wellbeing are related to perceptions of cognitive decline in multiple domains, and that the specific domains involved differ between normal and MCI groups. The differential associations may mean perception of specific cognitive domains more strongly affect mental wellbeing, or mental wellbeing more acutely influences perception of those domains. The overall observed relationship between SCD and mental wellbeing may have several explanations: the impact of broader health perceptions may extend to cognitive perception, behavioral changes associated with poor wellbeing may reduce subjective cognitive function, or worse subjective cognitive function may lead to negative experiences of wellbeing. Future longitudinal investigation could inform causal inferences. The more limited associations between mental wellbeing and SCD among MCI individuals may point to the role of decreased self-awareness (due to cognitive impairment) precluding detection of subtle changes in cognition or wellbeing. This study highlights the importance of better understanding mental wellbeing in experiences of SCD in both normal and MCI older adults to improve cognitive and mental health outcomes.

Processing speed declines with age and is a strong predictor of age-related cognitive decline in other domains, and in predicting who will need help with tasks of daily living in later years. Higher cardiorespiratory fitness (CRF) reflects better cardiopulmonary health and is related to maintenance of processing speed and cognition into late life. On the other hand, white matter lesions (WML) are reflective of age-related brain network disconnections from damage to white matter tracts in the brain. Lower CRF and higher WML burden have each been related to poorer cognitive performance. Although higher CRF provides a protective effect on cognition, the combined effects of CRF and WML on processing speed have yet to be determined. Specifically, whether CRF and WML independently affect processing speed or if WML moderates the effect of CRF on processing speed is yet to be established. We predicted WML may moderate CRF benefits on cognitive aging if CRF-related cognitive benefits are weakened by high WML load. Here, we test this question with the gold-standard measure of CRF, maximal exercise oxygen uptake (relative VO2 max, mL/kg/min) during a graded exercise test, and a validated neuropsychological measure of processing speed, the Digit Symbol Substitution Test (DSST).

CRF, DSST scores, and WML volumes of cognitively normal adults (n=91) aged 55-80 years were included in this analysis. The WML data was corrected for total intracranial volume and was log transformed. A linear regression model included the number of accurately completed items on the DSST as the dependent variable and age, sex, relative VO2 max, WML volumes and the interaction between relative VO2 max and WML volume as the predictor variables.

Main effects of age, sex, VO2 max and WML volume on the DSST were observed. Greater age, higher WML volume, and lower relative VO2 max were associated with poorer performance on the DSST. In addition, females (n=55) performed better than males (n=36) on the DSST. No significant interaction was observed between VO2 max and WML volume on DSST scores.

Our results show that 1) WML and relative VO2 max independently contribute to processing speed performance in older adults as measured by the DSST, and 2) WML do not moderate the relation between VO2 max and the DSST. Strengths of this study include gold-standard measurement of CRF and WML volumes as predictors of performance on the DSST in older adults. Further research is warranted to understand how vascular aging and brain health indicators interactively or interdependently impact cognition in aging.

Alzheimer’s disease (AD) pathophysiology, including β-amyloid (Aβ), can be appreciated with molecular PET imaging. Among older adults, the distribution of Aβ standard uptake value ratios (SUVR) is typically bimodal and a diagnostic cut is applied to define those who are amyloid ‘positive’ and ‘negative’. However, it is unclear whether the dynamic range of SUVRs in amyloid positive and negative individuals is meaningful and associated with cognition. Previous work by Insel and colleagues (2020) used screening data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) trial to demonstrate subtle associations between a cortical summary SUVR and cognition, particularly on the Free and Cued Selective Reminding Test (FCSRT). We followed up this study to determine the extent to which regional SUVR is associated with performance on the FCSRT in amyloid positive and negative participants screened for participation in the A4 study.

We accessed regional Aβ SUVR, including anterior cingulate, posterior cingulate, parietal, precuneus, temporal, and medial/orbital frontal regions, along with FCSRT15 and demographic data from 4492 A4 participants at screening. Participants were coded as amyloid positive (n=1329; 30%) or amyloid negative (n=3169; 70%) based on a summary SUVR of greater than or equal to 1.15. We used separate general linear models to examine the association of total or regional SUVR, amyloid positivity status, and the interaction of SUVR and amyloid status with FCSRT scores. We compared model fits across regions with the Akaike Information Criterion (AIC). We ran post hoc correlational analyses examining the relationship between SUVR and FCSRT scores stratified by amyloid status in the case of significant interactions. Results were similar with and without demographic adjustment.

There was a significant interaction of summary and all regional SUVR with FCSRT scores in addition to main effects of amyloid positivity. In all models, there were small negative associations between SUVR and memory in amyloid positive individuals. For amyloid negative individuals, there was a significant and very small negative association between SUVR and FCSRT scores only in the parietal lobes and precuneus regions. Model fits were generally similar across the different analyses.

In this sample of individuals screened for a secondary prevention trial of AD, there were consistent associations between Aβ SUVR in all regions and memory for those considered amyloid positive. However, for individuals considered amyloid negative, there were only very small associations between SUVR and memory in parietal and precuneus regions. We conclude that the dynamic range of amyloid may be relevant among those with diagnostic evidence of amyloidosis, but that subtle Aβ accumulation in posterior regions may relate to declining memory in “subthreshold” states.

Prior work suggests financial exploitation vulnerability may be an early behavioral manifestation of Alzheimer’s disease (AD). Brain morphometric measures of the parahippocampal gyrus and entorhinal cortex have been shown to be sensitive to early AD progression. We hypothesized that perceived financial exploitation vulnerability may be associated with morphometric measures of the parahippocampal gyrus and entorhinal cortex in cognitively unimpaired older adults. We secondarily investigated the association of morphometric measures with neuropsychological measures.

The sample consisted of 39 cognitively unimpaired older adults (mean age = 68.74 ± 6.43, mean education = 16.87 ± 2.35, 77% female). Cognitive impairment was screened using the telephone version of the Montreal Cognitive Assessment (MoCA) and the cut-off was 21 for study participation. Perceived financial exploitation vulnerability was characterized using a 6-item self-report measure derived from the contextual items of the Lichtenberg Financial Rating Scale. Neuropsychological measures included the CVLT-II Long Delay Free Recall (verbal memory), Benson Complex Figure Recall (visual memory), and Verbal Fluency: Phonemic Test from the Alzheimer’s Disease Centers’ Uniform Data Set (UDS) version 3. Brain images were collected on a 7 Tesla Siemens Magnetom with the following parameters: TE=2.95ms, TR=2200ms, 240 sagittal slices, acquired voxel size (avs)=0.7mm x 0.7mm x 0.7mm. Structural brain images were processed using FreeSurfer version 7.2.0. Cortical thickness and volume measures were generated using the Killiany/Desikian parcellation atlas. Regions were averaged across hemispheres to obtain a single value for each region. Volume measures were adjusted for intracranial volume. Bivariate analyses were conducted to assess relationships between each outcome variable and potential confounders (age, sex, and education). Linear regression models were adjusted for any covariates significantly associated with the outcome variable (none for perceived financial exploitation vulnerability; sex and age for verbal memory; education for visual memory; sex for verbal fluency).

Smaller entorhinal cortex volume (β = -1275.14, SE = 582.79, p < 0.05) and lower parahippocampal gyrus thickness (β = -3.37, SE = 1.57, p < 0.05) were significantly associated with greater perceived financial exploitation vulnerability. Lower entorhinal cortex thickness was marginally associated with greater perceived financial exploitation vulnerability (β = -2.03, SE = 1.11, p = 0.08). Higher parahippocampal gyrus thickness was associated with better verbal fluency (β = 17.66, SE = 7.01, p < 0.05). Higher entorhinal cortex thickness was associated with better visual memory (β = 4.71, SE = 1.73, p < 0.05). No significant associations were observed between structural brain measures and verbal memory.

These results suggest smaller entorhinal cortex volume and lower parahippocampal gyrus thickness are associated with higher perceived financial exploitation vulnerability in cognitively normal older adults. Additionally, parahippocampal gyrus thickness appears to be associated with verbal fluency abilities while entorhinal cortex thickness appears to be associated with visual memory. Taken together, these findings lend support to the notion that financial exploitation vulnerability may serve as an early behavioral manifestation of preclinical AD. Longitudinal studies are needed to better understand the temporal nature of these relationships.

The ability to generate, plan for, and follow through with goals is essential to everyday functioning. Compared to young adults, cognitively normal older adults have more difficulty on a variety of cognitive functions that contribute to goal setting and follow through. However, how these age-related cognitive differences impact real-world goal planning and success remains unclear. In the current study, we aimed to better understand the impact of older age on everyday goal planning and success.

Cognitively normal young adults (18-35 years, n= 57) and older adults (60-80 years, n= 49) participated in a 10-day 2-session study. In the first session, participants described 4 real-world goals that they hoped to pursue in the next 10 days. These goals were subjectively rated for personal significance, significance to others, and vividness, and goal descriptions were objectively scored for temporal, spatial, and event specificity, among other measures. Ten days later, participants rated the degree to which they planned for and made progress in their real-world goals since session one. Older adults also completed a battery of neuropsychological tests.

Some key results are as follows. Relative to the young adults, cognitively normal older adults described real-world goals which navigated smaller spaces (p=0.01) and that they perceived as more important to other people (p=0.03). Older adults also planned more during the 10-day window (p<0.001). There was not a statistically significant age group difference, however, in real-world goal progress (p=0.65). Nonetheless, among older participants, goal progress was related to higher mental processing speed as shown by the Trail Making Test Part A (r=0.36, p=0.02) and the creation of goals confined to specific temporal periods (r=0.35, p=0.01). Older participants who scored lower on the Rey Complex Figure Test (RCFT) long delay recall trial reported that their goals were more like ones that they had set in the past (r= -0.34, p=0.02), and higher episodic memory as shown by the RCFT was associated with more spatially specific goals (r=0.32, p=0.02), as well as a greater use of implementation intentions in goal descriptions(r=0.35, p=0.02).

Although older adults tend to show decline in several cognitive domains relevant to goal setting, we found that cognitively normal older adults did not make significantly less progress toward a series of real-world goals over a 10-day window. However, relative to young adults, older adults tended to pursue goals which were more important to others, as well as goals that involved navigating smaller spaces. Older adults also appear to rely on planning more than young adults to make progress toward their goals. These findings reveal age group differences in the quality of goals and individual differences in goal success among older adults. They are also in line with prior research suggesting that cognitive aging effects may be more subtle in real-world contexts.

The vascular depression hypothesis posits that there is a relationship between vascular disease and geriatric depressive symptoms. Black Americans are at higher risk for cardiovascular disease (CVD) than their White counterparts. However, it is not fully understood whether risk for CVD or potentially related neurovascular changes have a differential relationship in Black and White Americans. We investigated differences in the relationships between white matter hyperintensities, risk for CVD, and depressive symptoms in Black and White older adults.

Participants were derived from the National Alzheimer Coordinating Center database. Black (N = 120) and White (N = 120) participants were matched on age, sex, and education. White matter hyperintensity (WMH) and CVD burden data (sum of vascular conditions) on 320 individuals were analyzed (mean age = 75.9; 69.4% female). Age, sex, race, and education were included as covariates in separate regression models in which WMH and CVD burden predicted scores on the 15-item Geriatric Depression Scale (GDS-15). Follow-up stratified analyses were conducted to explore the relationship between WMH and CVD burden on GDS scores in the Black and White samples.

Lower WMH volume and higher CVD burden were associated with higher GDS scores in the total sample. Analyses stratified by race showed a positive effect of CVD burden on GDS scores only for the Black sample and a trend effect of WMH on GDS scores only for the White sample, with higher WMH volume associated with lower rather than higher GDS scores.

These findings are consistent with previous research showing that WMH and CVD burden are related to depression in older adults. Contrary to expectation, WMH had a negative trend association with GDS scores in the White sample. Findings also suggest that different etiologies may play a role in the clinical presentation of depression in Black and White Americans. Additional research is needed to further explore the relationships among CVD, its neural correlates, and depressive symptoms in diverse samples.

Drawing on the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS), this study aimed to investigate the direct and indirect associations between vascular risk factors/cardiovascular disease (CVD), pharmacological treatment (of CVD), and white matter hyperintensity (WMH) burden on overall cognition and decline trajectories in a cognitively diverse sample of older adults.

Participants were 1,049 cognitively diverse older adults drawn from a larger NACC data repository of 22,684 participants whose data was frozen as of December 2019. The subsample included only participants who were aged 60-97 (56.7% women) who completed at least one post-baseline neuropsychological evaluation, had medication data, and both T1 and FLAIR neuroimaging scans. Cognitive composites (Memory, Attention, Executive Function, Language) were derived factor analytically using harmonized data. Baseline WMH volumes were quantified using UBO Detector. Baseline health screening and medication data was used to determine overall CVD burden and total medication. Longitudinal latent growth curve models were estimated adjusting for demographics.

More CVD medication was associated with greater CVD burden; however, no direct effects of medication were found on any of the cognitive composites or WMH volume. While no direct effects of CVD burden on cognition (overall or rate of decline) were observed, instead we found that greater CVD burden had small, but significant, negative indirect effects on Memory, Attention, Executive Functioning and Language (all p’s < .01) after controlling for CVD medication use. Whole brain WMH volume served as the mediator of this relationship, as it did for an indirect effect of baseline CVD on 6-year rate of decline in Memory and Executive function.

Findings from this study were generally consistent with previous literature and extend extant knowledge regarding the direct and indirect associations between CVD burden, pharmacological treatment, and neuropathology of presumed vascular origin on cognitive decline trajectories in an older adult sample. Results reveal the subtle importance of CVD risk factors on late life cognition even after accounting for treatment and WHM volume and highlight the need for additional research to determine sensitive windows of opportunity for intervention.

This study aimed to determine how modifiable risk factors, such as physical exercise and social support, and non-modifiable risk factors, such as genetic risk may affect cognitive function over time in older adults. As well, the study explored how changes in modifiable risk factors (i.e., increase in exercise) may affect cognitive function over time. This research question was shaped with the help of a patient partner team.

The study used UK Biobank data, and patient partners were involved in shaping research questions/goals. The UK Biobank study had participants complete comprehensive baseline assessments (2006-2010), with subgroups also completing repeat assessments (2012-2013), imaging assessments (2014-ongoing) and/or repeat imaging assessments (2019-ongoing; i.e., 2-4 data points per participant). Age, sex, education, ethnicity, and apolipoprotein E (APOE) e4 status (at least one e4 allele present) data were collected at baseline. Employment, physical activity, social support, and recent depressive symptom data were collected across timepoints. A Fluid intelligence score was obtained at each timepoint via a series of thirteen 1-pt. reasoning tasks (range: 0-13). Participants who did not complete cognitive testing at baseline and at least one other time point, and those with neurological conditions or events (e.g., stroke, epilepsy, dementia) were excluded (final N=17,409).

Multi-Level Modeling (with Maximum Likelihood) was utilized, with fluid intelligence as the primary outcome measure. We ran Model 1: fully unconditioned, Model 2: with time predictor in years (baseline= 0), and Model 3: with baseline physical activity, social support and APOE e-4 predictors and covariates (mean-centered as appropriate), time-varying physical activity and social support predictors, and interaction terms. Nonsignificant interaction terms were trimmed from Model 3 to facilitate interpretation.

Model 1 was significant (p<.001) with an intraclass correlation (ICC) of 0.64, suggesting that 64% of the total variance in fluid intelligence in this sample is due to interindividual differences. Model 2 revealed that the average fluid intelligence score at baseline mean age (55.85) was 6.79 and significantly decreased with each year increase since baseline. Results from Model 3 (trimmed) revealed that being male, white, and having at least a university degree were associated with higher score at baseline, while being older and having more recent depressive symptoms were associated with lower scores. Higher social support quality was associated with higher scores while higher social support quantity was associated with lower scores at baseline; however, higher social support quantity at baseline was associated with less decline in scores over time. Surprisingly, having at least one e4 allele was associated with higher scores. Engaging in more moderate physical activity was associated with lower scores at baseline, however, individuals who increased the length of their moderate physical activity sessions over time showed higher timepoint-specific fluid intelligence scores. Additional significant interactions will be elaborated.

Results suggest that increases in the length of moderate physical activity exercise sessions were associated with better cognitive function over time. Having better social support quality was also associated with better cognitive function, while higher social support quantity was associated with less cognitive decline over time. These findings suggest that positive lifestyle changes in older adulthood may slow cognitive decline.

Human imagination is a complex system that allows us to form images or concepts in the mind that are not present to the senses. Research on imagination has been heavily influenced by the idea that humans store two distinct types of long-term memory: episodic and semantic memory. This theoretical distinction is particularly important in the context of aging, where older adults show reduced episodic memory compared to semantic memory (Levine et al., 2002). However, recent work has shown that these two memories are not as distinct as once thought (Renoult et al., 2019; Irish & Vatansever, 2020), suggesting a need to either refine the relationship between these concepts, or the concepts themselves.

Here, we apply a broader framework for imagination to the autobiographical memories of older adults. Introduced by Andrews-Hanna & Grilli (2021), memory and future thoughts can be understood as the outcome of the collaboration between two representational forms of imagination: the mind’s mind and the mind’s eye. The mind’s mind is described as a high-level, abstract form of imagination accompanied by a verbal representational form, and the mind’s eye is described as a contextually-specific, image-based form of imagination. In the present study, we examine whether this broader framework for understanding imaginative thought can a) explain some of the established age-related changes in episodic and semantic memory, and b) extend beyond existing research to offer new ways to conceptualize autobiographical memory in aging.

In this study, we introduce a novel scoring protocol distinguishing mind’s eye from mind’s mind forms of imagination and apply this protocol to the autobiographical memories of eighty-two cognitively normal older adults. Participants were instructed to retrieve unique autobiographical events, and to focus on describing event-specific details. All data were scored both with our new scoring protocol as well as the Autobiographical Interview scoring protocol from Levine et al. (2002).

Our novel scoring protocol demonstrated high inter-rater reliability across two raters for both mind’s mind (0.95) and mind’s eye (0.96) details. First, we show that the proportion of mind’s mind and mind’s eye details on average are significantly different, with an increased proportion of mind’s eye details. Second, we find that both mind’s eye detail production and mind’s mind detail production is significantly reduced with age, whereas only internal details decline across age when scored with the Autobiographical Interview scoring procedure.

The new scoring protocol suggests that both mind’s mind and mind’s eye details undergo change with age, a finding that shares similarities and differences with results from the Autobiographical Interview scoring technique. Taken together, our results hint at a more elaborate set of detail types forming autobiographical memories that change with age, with implications for understanding episodic and semantic memory.

The relation between depressed mood and functional difficulties in older adults has been demonstrated in studies using self-report measures and has been interpreted as evidence for low mood negatively impacting everyday functional abilities. However, few studies have directly examined the relation between mood and everyday function using performance-based tests. This study included a standardized, performance-based measure of everyday action (Naturalistic Action Task, NAT) to test the prediction that report of depression symptoms are associated with self-report and performance-based tests of everyday function. Associations with anxiety symptoms and motivation/grit and everyday function also were explored.

68 older adults without dementia were screened and recruited (n = 55, M age = 74.21, SD= 6.80, age range = 65 to 98) from the community and completed self-report measures of depression symptoms (GDS), anxiety (GAI), motivation (Short Grit-S), and everyday functioning (FAQ). Participants also performed the NAT, which requires completion of a breakfast and lunch task and is scored for task accomplishment, errors (micro-errors, overt, motor), and total time. Additionally, an informant also reported on the participant’s everyday function. Spearman correlations were performed and results showing a medium effect size or greater are reported.

Participant mood (GDS) was associated with self-reported function (FAQ; r =.45) but not performance-based measures of everyday function (NAT). Self-reported anxiety and motivation were not meaningfully associated with either self-reported or performance-based everyday function. Participant self-report (FAQ) and informant report of participant’s function (IFAQ) supported the validity of performance-based assessment as both were meaningfully associated with NAT performance (FAQ x NAT overt errors r = .34; I-FAQ x NAT micro-errors r = .34; I-FAQ x NAT motor errors r = .49).

Mood, but not anxiety or motivation, was associated with self-reported everyday function but not performance-based function. When considered alongside the meaningful relations between self/informant-report of function and everyday task performance, results suggest mood does not impact everyday function abilities in community-dwelling older adults without dementia. We suggest that frameworks to be reconceptualized to consider the potential for mild functional difficulties to negatively impact mood in older adults without dementia. Additionally, interventions and compensatory strategies designed to improve everyday function should examine the impact on mood outcomes.

Individuals with major depressive disorder (MDD) are observed to have reduced plasma nitrate levels and plasma nitric oxide (NO) metabolites (Chrapko et al., 2004; Garcia et al., 2011). Endothelial cell dependent dilation of vascular smooth muscle function has been observed to be blunted in adults with Major Depressive Disorder (MDD) and mediated by NO-dependent dilation (Greaney et al., 2019). Certain vegetables and fruits are particularly high in dietary nitrates, which is reduced to nitric oxide in the stomach, entering intravascular circulation, and acting as a potent dilator, blood pressure reducing, and vasoprotective substance (Webb et al., 2008). In older adults, dietary nitrates which are found in certain vegetables and fruits (e.g., green leafy vegetables) is shown to increase cerebral blood perfusion in frontal lobe white matter between the dorsolateral prefrontal and anterior cingulate cortex, regions particularly implicated in cognitive functioning (Presley et al., 2011). Recently, Morris et al. (2018) observed that in older adults from the Memory and Aging Project (MAP), the highest quintile of dietary nitrate intake was associated with slower cognitive decline than that of the lowest quintile of nitrate intake. Although viewing the extremes of dietary nitrate intake reveals valuable information, the present study investigated the association of all levels of dietary nitrate intake with cognition and depression among older adults in the same MAP dataset.

The sample included 461 community dwelling older adults (Mage=80; Medu =14.9, 74% female) from the MAP study (Bennett et al., 2012). The measures used for the present study include: the Center for Epidemiological Studies Depression Scale (CESD, depression), a neuropsychological battery (global cognition, perceptual organization and semantic memory), and a dietary nutrient analysis of the food frequency questionnaire (FFQ, nitrate).

Using Pearson correlations we observed that increased dietary nitrate intake was associated with increased global cognition (r(458) = .100, p = .031), perceptual organization (r(448) = .095, p = .04) and semantic memory (r(453) = .142, p = .002). Furthermore, we observed that dietary nitrate intake was associated with lower depression severity (r(459) = -.132, p = .004).

The present study’s results revealed that in a sample of community dwelling older adults, eating more nitrate rich foods is not only associated with improved cognition similar to findings of Morris et al. (2018), it is also associated with lower levels of depression. This further extends the Morris et al. (2018) study by suggesting that it is not only those older adults who eat the highest quantity of nitrate rich foods that can benefit from higher levels of nitrate intake. Overall, this study reveals that older adults who increase their dietary nitrate intake may improve their mood and thinking ability.

Understanding healthcare information is an important aspect in managing one’s own needs and navigating a complex healthcare system. Health numeracy and literacy reflect the ability to understand and apply information conveyed numerically (i.e., graphs, statistics, proportions, etc.) and written/verbally (i.e., treatment instructions, appointments, diagnostic results) to communicate with healthcare providers, understand one’s medical condition(s) and treatment plan, and participate in informed medical decision-making. Cognitive impairment has been shown to impact one’s ability to understand complex medical information. The purpose of this study is to explore the relationship between the degree of cognitive impairment and one’s ability to perform on measures of health numeracy and literacy.

This cross-sectional study included data from 38 adult clinical patients referred for neuropsychological evaluation for primary memory complaints at an urban, public Midwestern academic medical center. All patients were administered a standardized neurocognitive battery that included the Montreal Cognitive Assessment (MoCA), as well as measures of both health numeracy (Numeracy Understanding of Medicine Instrument-Short Version [NUMI-SF]) and health literacy (Short Assessment of Health Literacy-English [SAHL-E]). The sample was 58% female and 60% Black/40% White. Mean age was 65 (SD=9.4) and mean education was 14.4 years (SD=2.5). The sample was further split into three groups based on cognitive diagnosis determined by comprehensive neuropsychological assessment (i.e., No Diagnosis [34%]; Mild Cognitive Impairment [MCI; 29%]; Dementia [34%]).Groups were well matched and did not statistically differ in premorbid intellectual functioning (F=1.96, p=.157; No Diagnosis, M=100, SD=7.92; MCI, M=99, SD=8.87; Dementia, M=94, SD=7.72) ANOVAs were conducted to evaluate differences between clinical groups on the MoCA, NUMI-SF, and SAHL-E. Multiple regressions were then conducted to determine the association of MoCA scores with NUMI-SF and SAHL-E performance.

As expected, the Dementia group performed significantly below both the No Diagnosis and MCI groups on the MoCA (F=19.92, p<.001) with a large effect (ηp2=.540). Significant differences were also found on the NUM-SF (F=5.90, p>.05) and on the SAHL-E (F=6.20, p>.05) with large effects (ηp2=.258 and ηp2=.267, respectively). Regression found that MoCA performance did not predict performance on the NUMI-SF and SAHL-E in the No Diagnosis group (F=2.30, p=.809) or the MCI group (F=1.31, p=.321). Conversely, the MoCA significantly predicted performance on the NUMI-SF and SAHL-E for the Dementia (F=15.59, p=.001) group.

Degree of cognitive impairment is associated with understanding of health numeracy and literacy information, with patients diagnosed with dementia performing most poorly on these measures. Patients with normal cognitive functioning demonstrated a significantly better understanding of health numeracy and health literacy. This study supports the notion that as cognitive functioning diminishes, incremental support is necessary for patients to understand medical information pertaining to their continued care and medical decision-making, particularly as it relates to both numerical and written information.

Cognitive reserve and health-related fitness are associated with favorable cognitive aging, but Black/African American older adults are underrepresented in extant research. Our objective was to explore the relative contributions and predictive value of cognitive reserve and health-related fitness metrics on cognitive performance at baseline and cognitive status at a 4-year follow up in a large sample of Black/African American older adults.

Participants aged 65 years and older from the Health and Retirement Study (HRS) who identified as Black/African American and completed baseline and follow-up interviews (including physical, health, and cognitive assessments) were included in the study. The final sample included 321 Black/African American older adults (mean age = 72.8; sd = 4.8; mean years of education = 12.3; sd = 2.9; mean body mass index (BMI) = 29.1; sd = 5.2; 60.4% identified as female). A cross-sectional analysis of relative importance – a measure of partitioned variance controlling for collinearity and model order – was first used to explore predictor variables and inform the hierarchical model order. Next, hierarchical multiple regression was used to examine cross-sectional relationships between cognitive reserve (years of education), health-related fitness variables (grip strength, lung capacity, gait speed, BMI), and global cognition. Multiple logistic regression was used to examine prospective relationships between predictors and longitudinal cognitive status (maintainers versus decliners). Control variables in all models included age, gender identity, and a chronic disease index score.

Cross-sectional relative importance analyses identified years of education and gait speed as important predictors of global cognition. The cross-sectional hierarchical regression model explained 33% of variance in baseline global cognition. Education was the strongest predictor of cognitive performance (β = 0.48, p < 0.001). Holding all other variables constant, gait speed was significantly associated with baseline cognitive performance and accounted for a significant additional amount of explained variance (ΔR = 0.01, p = 0.032). In a prospective analysis dividing the sample into cognitive maintainers and decliners, a single additional year of formal education increased chances of being classified as a cognitive maintainer (OR = 1.30, 95% CI = 1.17-1.45). There were no significant relationships between rate of change in health-related fitness and rate of change in cognition.

Education, a proxy for cognitive reserve, was a robust predictor of global cognition at baseline and was associated with increased odds of maintaining cognitive ability at 4-year follow up in Black/African American older adults. Of the physical performance metrics, gait speed was associated with cognitive performance at baseline. The lack of observed association between other fitness variables and cognition may be attributable to the brief assessment procedures implemented in this large-scale study.

Mind-wandering is defined as a spontaneous shift of attention away from the external environment to inner thoughts. With mind-wandering being a ubiquitous phenomenon, there has been increasing interest in examining the role these spontaneous, and often unintentional, thought processes may have for metrics of cognitive and psychological health. However, much of this literature is mired with inconsistencies, potentially stemming from the use of variegated experimental methods and quantification of mind-wandering through different metrics. For example, mind-wandering has been investigated through endorsement of self-report probes embedded in tasks of sustained attention, with participants asking to endorse whether they were engaging in task-unrelated thoughts or task-related, but evaluative thoughts about the task (task-related interference). Other studies have instead focused on behavioral metrics of task performance, like omission and commission errors, the variability in response time (RTCV), and speeding or slowing prior to errors to quantify mind-wandering. In this study, employing a large sample of older adults, and implementing the novel technique of partial least squares regression, we examined the combined and simultaneous effect of different mind-wandering metrics in explaining variance in fluid cognition and psychological health in older adults.

One hundred and fifty older adults with normal cognition or mild cognitive impairment were administered a Go/No-Go Task (GNG) with embedded mind-wandering probes, the Conners CPT-3, the NIH Toolbox-Cognition Battery, and the WHO Quality of Life Assessment Brief Version at baseline in a clinical trial examining the impact of two mind-body interventions on aging. Based on previous research, the following variables were considered behavioral measures of mind-wandering: quantity of omission and commission errors, RTCV, pre-error speeding, and post-error slowing. Percentage of self-reported task-related interference (i.e. evaluating current performance) and task-unrelated thoughts were included as self-report measures of mind-wandering. These mind-wandering measures, along with demographic variables (age, sex, and education), were regressed using Partial Least Squares Regression to determine the impact of mind-wandering measures on fluid cognition (NIHT-CB) and perceived psychological well-being (WHOQOL-BBREF). Validation tests were completed to assess model fit.

A single latent factor explained 26% of the variance in fluid cognition (p=0.0001). Higher levels of age, errors of omission on both tasks, and task-related interference were all associated with worse fluid cognition, whereas task-unrelated thoughts were associated with better fluid cognition.

A two-factor latent model explained 12% of the variance in perceived psychological well-being (p=0.0004). Age and task-unrelated thoughts were positively associated with psychological well-being. In contrast, errors of omission on both tasks, response time variability on the CPT, and task-related interference were negatively associated with perceived psychological well-being.

Mind-wandering is associated with fluid cognition and perceived psychological well-being in older adults. Select behavioral measures were better than self-report measures at linking mind-wandering to fluid cognition and perceived psychological well-being. Interestingly task-unrelated thoughts, but not task-related interference, was positively associated with fluid cognition, supporting the cognitive resource-based account of mind-wandering. The result of our study provides novel insights into differential relationships between various metrics of mind-wandering and cognitive and psychological health.

Certain contextual factors, including non-restorative sleep (Niermeyer & Suchy, 2020), sleep deprivation (Lim & Dinges, 2010), burdensome emotion regulation (Franchow & Suchy, 2017), and pain interference (Boselie, Vancleef, & Peters, 2016) have been shown to contribute to temporary declines in executive functioning (EF). Contextually-induced decrements in EF in turn have been associated with temporary decrements in performance of instrumental activities of daily living (IADLs) among healthy older adults (Brothers & Suchy, 2021; Suchy et al., 2020; Niermeyer & Suchy 2020). Furthermore, some evidence suggests that higher variability in levels of contextual factors across days (i.e., deviations from routine) may contribute to IADL lapses above and beyond average, albeit high, levels of these contextual burdens (Bielak, Mogle, & Sliwinksi, 2019; Brothers & Suchy, 2021). Taken together, these findings highlight the importance of accounting for transient contextual burdens when assessing EF and IADL abilities in older adults.

Poor sleep quality has been associated with poor IADL performance (Fung et al., 2012; Holfeld & Ruthing, 2012) when assessed in a single visit. However, the potential contributions of variable sleep quantity and quality on IADL performance have not been assessed in healthy older adults using longitudinal methods. Accordingly, the aim of this study was to examine the impact of fluctuations in sleep quantity and quality, assessed daily, above and beyond average levels, on at-home IADL performance across 18 days in a group of community-dwelling older adults.

Fifty-two non-demented community-dwelling older adults (M age = 69 years, 65% female) completed 18 days of at-home IADL tasks, as well as daily ecological momentary assessment (EMA) measures of EF, sleep hours, and restfulness questions. An 18-day mean EMA EF score was computed controlling for practice effects. Mean levels of and variability in EMA sleep hours and EMA restfulness ratings were computed. IADL scores were computed for timeliness and accuracy across the 18 days.

A series of hierarchical linear regressions were run using separate IADL timeliness and accuracy as the dependent variable. In the first step, demographics (age, sex, education) were entered. Then, EMA EF was entered, followed by mean EMA sleep hours and EMA mean restfulness, and lastly, variability in EMA sleep hours and EMA restfulness. EMA EF was found to significantly predict both IADL accuracy (B = .46, p = .001) and timeliness (B = .45, p = .005). Variability in EMA sleep hours (B = .40, p = .008) and restfulness (B = -.29, p = .043) both predicted IADL accuracy beyond other variables, while mean levels did not. Additionally, variability in sleep hours and restfulness substantially improved the prediction of IADL accuracy above and beyond other variables in the model, accounting for an additional 16% of variance (F (2) = 3.80, ∆ R2 = .16, p = .006). Neither mean levels of or variability in sleep hours or restfulness predicted IADL timeliness.

Results suggest that greater fluctuations in the amount and quality of sleep across days may render healthy older adults more susceptible to lapses in daily functioning abilities, particularly the accuracy with which IADL tasks are completed.

Although health problems are often a natural consequence of aging, many older adults struggle to manage their health care problems. Health literacy refers to the ability to access, process, and use health information to make appropriate decisions to promote good overall health. Low levels of health literacy are associated with a host of negative outcomes such as less efficient use of healthcare services, higher healthcare costs, increased mortality, and poorer self-rated health. In those with medical conditions (e.g., diabetes), lower health literacy is linked with higher levels of depression. It is important to investigate whether mental health is linked to health literacy as understanding these links has the potential to identify those at risk for negative outcomes and thus implement protective strategies. Therefore, the current study sought to determine the extent to which various mental health constructs such as happiness, well-being, anxiety and depression are related to health literacy in a community-based sample of cognitively healthy individuals. We hypothesized that higher levels of health literacy would be associated with higher self-reported well-being, happiness, and lower anxiety and depression.

Design - Cross-sectional, prospective study. Setting - Community-based. 93 individuals were included with mean age=59.02 years (SD=15.12) and mean education=15.70 (SD=2.39). 60% were women, the majority were White (55%) while 38% were Black and 7% belonged to other races; 90% were non-Hispanic.

Health Literacy - Health literacy was measured by an 8-item instrument in the Rush Memory and Aging Project that examined the participant’s understanding of health care, treatment, and related behaviors. Happiness - Happiness was measured by 5 items from the Satisfaction with Life Scale using a 7-point scale (1 = strongly agree; 7 = strongly disagree). Higher scores indicated lower levels of happiness. Well-being - Well-being was measured with an 18-item instrument from the Rush Memory and Aging project, with higher scores indicating better well-being. Statistics: Bivariate correlations between age, education, and mental health measures and health literacy were examined.

Higher level of health literacy was significantly associated with age (r = .282 p = .009) and education (r = .228 p = .039). Contrary to our hypothesis, health literacy was not significantly associated with happiness (r = .002 p = .987), well-being (r = .037 p = .742), depression (r = .005 p = .962) or anxiety (r = -.064 p = .568). Even after controlling for age and education, these associations remained significant.

Higher level of healthy literacy was associated with older age and higher level of education. However, no significant association was found between health literacy and mental health measures of happiness, well-being, depression, and anxiety in cognitively healthy individuals, even after controlling for demographics. The lack of such associations in this study was unexpected and suggests that other factors such as the presence of health conditions (e.g., diabetes, cancer) might critically contribute to such associations. Future studies should examine these associations in a larger context to better understand how to promote healthy self-care behaviors.