The oldest-old, those 90 years and older, are the fastest growing segment of the population and the number of dementia cases at these ages will steadily increase over time. It is therefore critical to include this population in clinical research. Evidence to guide recruitment of this group is scarce. We report our experience recruiting the oldest-old to a longitudinal study of aging and dementia. Recruitment activities were grouped into four strategies: direct mailing of recruitment brochures, community outreach, earned media, and referrals. Recruitment sources were recorded based on enrollees’ self-report. Cost was estimated based on personnel time and materials. One hundred forty five new participants were enrolled over 40 months. Community outreach produced the most recruitment (33.8%) followed by earned media (21.4%), direct mail (16.6%) and referrals (15.8%). Earned media and direct mailing were most cost-effective. Local media produced more enrollment and was more cost-effective than national media.

Objective

to explore the relationship between risk of falling at age 90+ and prior physical activity at age 60-70s.

Design

population-based cohort study (The 90+ Study).

Setting

California retirement community.

Participants

of 1596 cohort members, 1536 had both falls and prior activity data. Mean age = 94 years; 78% female; 99% Caucasian.

Methods

time spent in active physical activity was self-reported in 1980s; medical history, medication, assistive devices, residence type, and falls (outcome) was collected in 2000s. Activity/fall relationships were assessed using logistic regression.

Results

falls were reported by 52% of participants, recurrent falls by 32%, and severe injury by 21% of fallers. In univariate analyses risk of falling at age 90+ was significantly related to medical history (heart disease, TIA/stroke, arthritis, vision disease, depression, dementia), medication use (hypnotics, anti-psychotics, anti-depressants), use of assistive devices (cane, walker, wheelchair), residence type (living with relatives, sheltered living), and source of information (self-report vs informant). Risks of falling and recurrent falls at age 90+ were 35-45% lower in those reporting 30+ minutes/day of active physical activity at age 60-70s compared with no activity. The odds ratio of falling was 0.65 (95% CI = 0.44-0.97) for 30-45 minutes/day and 0.64 (0.44-0.94) for 1+ hour/day adjusting for age, sex, medical history (stroke/TIA, vision disease, depression), use of assistive devices, and source of information.

Conclusions and relevance

falls are extremely common among the oldest-old and a significant proportion lead to severe injury. This work is the first to show an association between exercise at age 60-70s and lower risk of falling at age 90+.

Aging is known to have deleterious effects on cerebral white matter, yet little is known about these white matter alterations in advanced age. In this study, 94 oldest-old adults without dementia (90-103 years) underwent diffusion tensor imaging to assess relationships between chronological age and multiple measures of integrity in 18 white matter regions across the brain. Results revealed significant age-related declines in integrity in regions previously identified as being sensitive to aging in younger-old adults (corpus callosum, fornix, cingulum, external capsule). For the corpus callosum, the effect of age on genu fractional anisotropy was significantly weaker than the relationship between age and splenium fractional anisotropy. Importantly, age-related declines in white matter integrity did not differ in cognitively normal and cognitively impaired not demented oldest-old, suggesting that they were not solely driven by cognitive dysfunction or preclinical dementia in this advanced age group. Instead, white matter in these regions appears to remain vulnerable to normal aging processes through the 10th decade of life.

Background: The oldest-old (≥85 years) have the highest rates of dementia. However, because of pronounced brain atrophy, standard neuroimaging programs face unique challenges in this cohort. Here, using data from both The 90+ Study and Alzheimer’s Disease Neuroimaging Initiative (ADNI), we report the prevalence of errors when processing brain MRIs from oldest-old participants using standard approaches and present some strategies for ameliorating these issues. Method: First, we analyzed image quality issues and segmentation errors (FreeSurfer) for the last available scans by age-groups (oldest-old, ≥85 years, vs younger-old, 55 to 85 years) in ADNI. Second, we evaluated the utility of an age-specific template (the 90+ T1w Template) for realigning MRIs from the oldest-old compared to a standard template (Montreal Neurological Institute T1w template, MNI) using linear and nonlinear registration (FSL) and evaluating alignment quality using visual and deformation (Jacobian) measures for oldest-old participants (≥90 years) in both The 90+ Study and ADNI. Lastly, we evaluated whether stringent preprocessing (bias field removal, denoising, brain extraction, intensity normalization using Computational Anatomy Toolbox (CAT12)) helped reduce FreeSurfer segmentation errors in frontal, parietal, and temporal regions in MRIs from the oldest-old. Comparisons were performed using Chi-square tests. Result: In ADNI data (Table-1), MRIs from oldest-old participants (∼10% of cohort) were around twice as likely to have image quality issues (20% vs 13%, P<0.001) and brain segmentation errors (45% vs 29%, P<0.001) compared to younger-old participants. Figure-1 shows a histogram of image quality issues and segmentation errors, which become more common with greater age. Compared to the MNI template, MRIs from participants aged 90 and older from both The 90+ Study (N=163, Table-2) and ADNI (N=75) had fewer registration errors (∼5% vs ∼23%, P<0.001 for all) and less severe deformation when using the 90+ T1w Template (Figure-2). Our proposed preprocessing pipeline (see Figure-3 for example) roughly halved segmentation errors in the oldest-old (P<0.001 for all regions, Figure-4). Conclusion: Our results show that adapting pipelines specifically for processing brain MRIs of oldest-old participants minimizes errors, enabling more effective use of neuroimaging to study neural correlates of neurodegeneration and dementia in this important portion of our aging population.

Purpose: To analyze the relationship between blood pressure (BP) variables, including circadian pattern, and cognition in 90+ year-olds. Methods: Twenty-four hour ambulatory BP monitoring was completed on 121 participants drawn from a longitudinal study of aging and dementia in the oldest-old. Various measures of BP and its variability, including nocturnal dipping, were calculated. Each person was given both a neuropsychological test battery covering different cognitive domains and a neurological examination to determine cognitive status. Seventy-one participants had a brain magnetic resonance imaging (MRI) scan. Results: Participants ranged in age from 90 to 102 years (mean = 93), about two-thirds were female, and nearly 80% had at least some college education. Mean nocturnal dips differed significantly between cognitively normal (n = 97) and impaired individuals (n = 24), with cognitively normal participants having on average greater nocturnal dips [6.6% vs. 1.3%, p = 0.006 for systolic BP (SBP); 11% vs. 4.4%, p = 0.002 for diastolic BP (DBP)]. Nocturnal dips were also related to performance on select cognitive test scores (especially those related to language, recent memory and visual-spatial ability), with individuals who performed below previously established median norms having significantly smaller nocturnal dips (both SBP and DBP) than those above the median. DBP reverse dippers had larger mean white matter hyperintensities (WMH as percent of total brain volume; 1.7% vs. 1.2%, 1.1% and 1.0% in extreme dippers, dippers, non-dippers) and a greater proportion had lobar cerebral microbleeds (CMBs; 44% vs. 0%, 7%, 16%, p < 0.05). Impaired participants had higher mean WMH than those with normal cognition (1.6% vs. 1.0% p = 0.03) and more tended to have CMB (31% vs. 20%, p = n.s.). Conclusion: These findings suggest that cognitive dysfunction is associated with dysregulation in the normal circadian BP pattern. Further study is warranted of the potential role of WHM and CMB as mediators of this association.

Background

The goal of this study was to examine cross-sectional and longitudinal associations between cognitive performance and beta amyloid (Aβ) load determined by florbetapir F18 positron emission tomography (PET) in nondemented oldest-old.

Methods

Thirteen nondemented (normal or cognitively impaired nondemented) participants (median age, 94.2 years) from The 90+ Study underwent florbetapir-PET scanning within 3 months of baseline neuropsychological testing. Amyloid load was measured with a semi-automated quantitative analysis of average cortical-to-cerebellar standardized uptake value ratio (SUVr) and a visual interpretation (Aβ- or Aβ+). Neuropsychological testing was repeated every 6 months.

Results

At baseline, SUVr correlated significantly with tests of global cognition and memory. During follow-up (median, 1.5 years), the Aβ+ group had steeper declines on most cognitive tests, particularly global cognitive measures.

Conclusion

This preliminary study suggests that greater amyloid load is associated with poorer cognition and faster cognitive decline in nondemented oldest-old. Amyloid load may identify individuals at increased risk of developing Alzheimer's disease.