Abstract
This study investigates whether older adults diagnosed with the apathy, gait impairment, and executive dysfunction (AGED) triad, frequently associated with cerebrovascular disease and confounded with depression, have earlier dementia onset. We followed 322 community-dwelling older individuals (mean age 72.0 ± 6.4 years; 58.3% women) free of dementia at baseline for up to 9 years. The AGED triad was identified when gait slowness (< 1 m/s), apathy (assessed by Geriatric Depression Scale-3A with ≥ 2 items), and executive dysfunction (assessed by the 75th percentile of Trail Making Test-part B by age range) were simultaneously present. Incident dementia was diagnosed using the clinical dementia rating scale. Over the 9-year follow-up (mean 45.1 ± 28.6 months), 44 participants (13.6%) converted to dementia. Sixteen participants (5.0%) were diagnosed with AGED triad + and showed a significantly higher risk of earlier conversion to dementia compared with AGED triad- (hazard ratio = 5.08, 95%CI 2.16–11.97; p = 0.0001), as well as to those with only one AGED factor or fewer AGED factors. Hypertension and diabetes were 2 and 3 times more prevalent, respectively, in individuals with AGED triad + . These findings suggest that the AGED triad serves as a simplified and effective behavioral marker for accelerated progression to dementia.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11357-024-01372-0.
Keywords: Dementia, Vascular risk factors, Gait slowness, Apathy, Executive function
Background
The world population is rapidly aging. As a consequence of this phenomenon, the number of older adults living with dementia will grow at faster rates within the next decades [1]. This poses significant challenges to public healthcare systems that will have to allocate exponential amounts of resources to diagnose, prevent, and treat dementia. Hence, there is an urgent need to identify simpler and cost-effective behavioral markers of poorer brain health that would indicate early onset of dementia, especially markers linked with modifiable risk factors.
Hypertension, diabetes, high cholesterol, smoking, and obesity are prevalent modifiable risk factors associated with the presence of cerebrovascular disease[2–8]. Besides genetic factors, these modifiable risk factors have the potential to disrupt brain networks that regulate affective, motor, and cognitive dysfunctions [9–11]. As an example, apathy (e.g., the lack of interest and avoidant behaviors), gait impairment (e.g., gait slowness) and executive dysfunction (e.g. slow cognitive processing), the AGED triad factors, are separately considered risk factors for incident dementia but often occur jointly, especially in individuals with cerebrovascular disease[12, 13]. Moreover, AGED triad factors are usually confounded with depression; however, an aging phenotype of this triad has been described to be associated with vascular risk factors including hypertension and diabetes [12, 13]. It has been [14] recently proposed that the AGED triad can be a behavioral manifestation of extensive brain damage, specifically in frontal and subcortical brain regions, caused by insidious vascular damage. Moreover, AGED triad factors are associated with accelerated progress to dementia an indicative of poorer brain health. Brain health encompasses a myriad of functional and structural brain changes that culminate into behavioral manifestations (e.g., affective, motor and cognitive) [15, 16]. Therefore, AGED triad may have important implications for clinical practices particularly because of its simplicity and potential to detect brain neurodegeneration through behavioral changes. The recognition of this phenotype is clinically useful because vascular risk factors are treatable and preventable although their impact on brain function is more difficult to estimate. Hence, the AGED triad could be a simplified way to assess one’s brain health and predisposition for earlier dementia onset. This hypothesis, however, has not been empirically tested yet.
The first aim of this study was to investigate whether AGED triad would predict earlier conversion to dementia compared with those not manifesting the triad. The second aim was to examine whether presence of AGED triad (i.e., AGED triad +) would predict dementia onset earlier than individuals manifesting none, one and two of the AGED triad factors (i.e. apathy, gait and executive dysfunction). We postulate that older individuals clinically diagnosed with AGED triad + at baseline would have the highest risk of accelerated dementia onset during the follow-up compared with individuals without AGED triad + (i.e., AGED triad-) and individuals presenting none, one, and two of the AGED factors.
Methods
Study participants
Participants were part of the Gait and Brain Study (Trial Registration clinicaltrials.gov: NCT03020381), an ongoing prospective cohort study designed to determine whether quantitative gait deficits can predict incident cognitive and mobility decline and progression to dementia among community-dwelling older adults. Design and logistics have been described in detail elsewhere [17]. Ethics approval was obtained from the University of Western Ontario (London, Ontario, Canada) Health Sciences Research ethics board, and written informed consent was obtained from participants at enrollment (REB# 7162). After written consent was obtained, participants underwent a comprehensive baseline evaluation and subsequent face-to-face assessments every 6 months for up to 9 years. For this analysis, participants were required to have at least two assessments, including the baseline visit. All participants were community-living adults meeting the following inclusion criteria: age 65 years and older, able to walk 10 m independently without a gait aid, and the absence of dementia using criteria from the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) [18]. Exclusion criteria included the lack of English proficiency that would affect performance in neuropsychological tests, any neurologic disorder with residual motor deficits (e.g., stroke), Parkinson’s disease/Parkinsonism (i.e., bradykinesia, rigidity and tremor), uncontrolled/severe pain, and musculoskeletal disorders of lower limbs (e.g., severe osteoarthritis or history of knee/hip replacement) affecting gait performance at clinical examination. Data collection occurred between July 2010 and July 2023. Medical and Cognitive Assessments Sociodemographic characteristics, comorbidities, chronic medications, physical activity level, history of falls, and basic and instrumental activities of daily living were collected using standardized questionnaires during face-to-face interviews (Table 1). Participants were recruited from the community through advertisements (e.g., website and posters) and referrals from physicians.
Table 1.
Participants’ characteristics included in each group
| AGED triad- (N = 306) |
AGED triad + (N = 16) |
Total (N = 322) |
p-value | |
|---|---|---|---|---|
| Age in years, mean (SD) | 72.00 (± 6.51) | 72.81 (± 5.58) | 72.04 (± 6.46) | 0.49 |
| Years of education, mean (SD) | 14.87 (± 3.22) | 13.40 (± 2.62) | 14.80 (± 3.20) | 0.05 |
| Women, N (%) | 179 (58.50%) | 9 (56.25%) | 188 (58.39%) | 1 |
| Height in cm, mean (SD) | 166.3 (± 8.87) | 169.0 (± 9.73) | 166.4 (± 8.92) | 0.27 |
| Weight in Kg, mean (SD) | 77.46 (± 17.28) | 85.81 (± 17.49) | 77.88 (± 17.36) | 0.05 |
| BMI in Kg/m2, mean (SD) | 27.96 (± 5.44) | 29.84 (± 4.30) | 28.05 (± 5.40) | 0.07 |
| Systolic blood pressure in mmHg, mean (SD) | 136.4 (± 17.21) | 135.6 (± 20.83) | 136.3 (± 17.37) | 0.57 |
| Diastolic blood pressure in mmHg, mean (SD) | 78.80 (± 11.75) | 81.31 (± 18.03) | 78.93 (± 12.11) | 0.95 |
| MMSE (0–30), mean (SD) | 27.70 (± 2.16) | 26.94 (± 2.35) | 27.67 (± 2.17) | 0.11 |
| MoCA (0-–0), mean (SD) | 24.82 (± 3.33) | 22.81 (± 3.27) | 24.72 (± 3.35) | 0.01 |
| GDS-15 (0–15), mean (SD) | 2.137 (± 2.35) | 5.938 (± 2.35) | 2.32 (± 2.49) | < 0.001 |
| Trail Making Test-part A (0–180), mean (SD) | 38.33 (± 14.60) | 54.83 (± 13.75) | 39.15 (± 14.98) | < 0.001 |
| Trail Making Test-part B (0–300), mean (SD) | 100.7 (± 53.11) | 201.3 (± 70.43) | 105.7 (± 58.23) | < 0.001 |
| Digit span forward (0–16), mean (SD) | 10.11 (± 2.18) | 10.38 (± 2.27) | 10.12 (± 2.18) | 0.72 |
| Digit span backward (0–14), mean (SD) | 6.38 (± 2.11) | 4.56 (± 2.22) | 6.29 (± 2.15) | < 0.001 |
| Letter number sequence (0–21), mean (SD) | 8.83 (± 2.69) | 7.43 (± 3.01) | 8.764 (± 2.72) | 0.042 |
| RAVLT (0–15), mean (SD) | 7.20 (± 4.06) | 4.37 (± 3.00) | 7.067 (± 4.06) | 0.005 |
| BNT (0–15), mean (SD) | 14.00 (± 1.37) | 13.75 (± 1.34) | 13.99 (± 1.37) | 0.37 |
| FAB (0–18), mean (SD) | 15.95 (± 1.68) | 14.38 (± 2.39) | 15.87 (± 1.75) | 0.004 |
| PASE (0–700), mean (SD) | 117.9 (± 60.25) | 92.99 (± 53.50) | 116.6 (± 60.10) | 0.10 |
| SPPB (0–12), mean (SD) | 9.88 (± 2.02) | 6.68 (± 2.33) | 9.72 (± 2.15) | < 0.001 |
| Number of medications, mean (SD) | 6.97 (± 4.44) | 9.18 (± 4.47) | 7.08 (± 4.46) | 0.04 |
| Number of comorbidities, mean (SD) | 5.02 (± 2.60) | 6.18 (± 1.55) | 5.08 (± 2.57) | 0.01 |
| TIA, N (%) | 25 (8.17%) | 2 (12.50%) | 27 (8.39%) | 0.63 |
| Gait speed in cm/s, mean (SD) | 116.3 (± 21.78) | 81.12 (± 18.46) | 114.5 (± 22.92) | < 0.001 |
| Converted to dementia, N (%) | 35 (11.44%) | 9 (56.25%) | 44 (13.66%) | < 0.001 |
| Days to convert to dementia, mean (SD) | 1343 (± 840.9) | 712.5 (± 720.6) | 1312 (± 845.5) | 0.001 |
MMSE, Mini-Mental State Exam; MoCA, Montreal Cognitive Assessment; DS, Geriatric Depression Scale; RAVLT, Rey Auditory Verbal Learning Test; BNT, Boston naming test; FAB, Frontal Assessment Battery; SPPB, Short Physical Performance Battery; PASE, Physical Activity Scale for the Elderly; TIA, transient ischemic attack; BMI, body mass index; SD, standard deviation. Only 1 participant who converted to dementia from the AGED triad had partial covariates
Medical, gait, and cognitive assessments
Sociodemographic characteristics, comorbidities, chronic medications, physical activity level, history of falls, and basic and instrumental activities of daily living were collected using standardized questionnaires during face-to-face interviews (Table 1). Study clinicians performed a physical examination including a neurological examination on all participants. Global cognition was assessed by using the Montreal Cognitive Assessment [19] (MoCA), with alternative test versions used in consecutive assessments to avoid potential learning effects. The Clinical Dementia Rating (CDR) scale [20] was also performed at all visits. Executive function was assessed using Trail Making Test-part B [21], verbal episodic memory using the Rey Auditory Verbal Learning Test [22], attention using the Digit Span Test [23] (forward and backward), attention/working memory using the Letter-Number Sequencing [24], and language/naming using the Boston Naming Test [25]. Modifiable risk factors were detected through structured baseline face-to-face interviews. Hypertension, diabetes and dyslipidemia were ascertained by examining participant’s prescriptions and power charts. Obesity was detected during the face-to-face interview through the relationship between height and weight (i.e., body mass index > 30 kg/m2). Smoking history was solely ascertained through the following question: “Do you smoke?”.
Dementia diagnosis ascertainment (outcome)
Incident dementia was the main end point as determined by a clinician investigator during follow-up visits per Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) [18] criteria and when Clinical Dementia Rating increased to a score of 1 or higher [20]. At the time of diagnosis, clinicians were blinded to baseline gait or baseline neuropsychological test scores. The type of dementia was established using standardized clinical criteria for Alzheimer’s disease dementia [26], frontotemporal dementia [27], Lewy body dementia [28], and vascular dementia [29]. Participants were reassessed after 6 months to confirm dementia status and subtype.
AGED triad + ascertainment (predictor)
The AGED triad diagnosis was ascertained when all three factors (i.e., apathy, gait slowness, and executive dysfunction) were present in the participant. The presence of apathy was defined using three apathy items from the Geriatric Depression Scale [30] (GDS-3A) [31]: (i) Have you dropped many of your activities and interests?; (ii) Do you prefer to stay at home, rather than going out and doing new things?; and (iii) Do you feel full of energy? Significant presence of apathy was defined if GDS-3A ≥ 2 (Table 2).
Table 2.
Distribution of each component and diagnosis by AGED triad status
| AGED triad- (N = 306) |
AGED triad + (N = 16) |
Overall (N = 322) |
|
|---|---|---|---|
| Executive dysfunction | 65 (21.2%) | 16 (100%) | 81 (25.2%) |
| Gait impairment | 63 (20.6%) | 16 (100%) | 79 (24.5%) |
| Apathy | 66 (21.6%) | 16 (100%) | 82 (25.5%) |
| AGED triad factor number | |||
| 0 (none) | 156 (51.0%) | 0 (0%) | 156 (48.4%) |
| 1 (single) | 106 (34.6%) | 0 (0%) | 106 (32.9%) |
| 2 (dyad) | 44 (14.4%) | 0 (0%) | 44 (13.7%) |
| 3 (triad) | 0 (0%) | 16 (100%) | 16 (5.0%) |
| Only one AGED factor | |||
| None | 156 (51.0%) | 0 (0%) | 156 (48.4%) |
| Executive dysfunction only | 35 (11.4%) | 0 (0%) | 35 (10.9%) |
| Gait slowness only | 31 (10.1%) | 0 (0%) | 31 (9.6%) |
| Apathy only | 40 (13.1%) | 0 (0%) | 40 (12.4%) |
Gait slowness was defined by using the walking speed cutoff of < 1 m/s [32]. Gait speed was assessed using an electronic walkway (Zeno walkway, 600 cm long × 64 cm wide × 0.5 cm high; CIR Systems Inc; PKmass software) that provides data to assess both spatial and temporal gait parameters. Start and end points were marked on the floor 1 m from either walkway end to avoid recording acceleration and deceleration phases. Each participant performed 1 practice trial walking on the walkway. Participants were instructed to walk at their usual pace in a quiet, well-lit room wearing appropriate footwear and without the use of any mobility aids and only stop when they reached the line on the floor placed at 1 m from the electronic walkway’s edge. Only the average of the first three consecutive usual/single-task gait trials were analyzed for this study.
Executive dysfunction was defined using the 4th quartile (> 75th percentile)[33] of the TMT-B completion time stratified by age range, i.e., > 106.53 s (65 to 75 years of age) and > 143.4 s (75 to 85 years of age) in the Gait & Brain Study cohort. Participants were instructed by a trained research assistant to draw a line going from a number to a letter in the numerical and alphabetical order, always alternating between a number and a letter, starting at number 1 and finishing at number 13 without lifting the pencil from the paper (e.g., 1-A-2-B-3-C-4-D…). Participants were allowed 5 min to complete the test; and if they were unable to finish in 5 min, then a time of 300 s was assigned to the participant’s test.
Covariates
Five potential confounders of the association between AGED triad + and incident dementia were selected as covariates in this study. We included age, sex, years of education (until highest degree), global cognition (i.e., MoCA 0–30), and the total number of comorbidities (sum of 17 eligible comorbidities) recorded at baseline visit. These variables were entered as covariates in all Cox-regression models (see Tables 3, 4, and 5).
Table 3.
Comparisons between AGED triad + vs. AGED triad- using Cox-regression model
| Beta | HR | SE | z | p-value | Lower 95%CI | Upper 95%CI | |
|---|---|---|---|---|---|---|---|
| AGED triad + | 1.62 | 5.08 | 0.43 | 3.72 | 0.0001 | 2.16 | 11.97 |
| AGED triad- [reference] | - | - | - | - | - | - | - |
| Age | 0.07 | 1.08 | 0.03 | 2.48 | 0.01 | 1.01 | 1.14 |
| Sex | − 0.04 | 0.95 | 0.34 | − 0.12 | 0.9 | 0.48 | 1.89 |
| Years of education | − 0.1 | 0.9 | 0.05 | − 1.77 | 0.07 | 0.8 | 1.01 |
| MoCA | − 0.27 | 0.76 | 0.04 | − 5.88 | 0.000000003 | 0.69 | 0.83 |
| Total number of comorbidities | 0.02 | 1.02 | 0.07 | 0.28 | 0.77 | 0.88 | 1.17 |
321 entered in the analysis, number of events = 43. Bold p-values indicate statistically significant association between AGED triad and risk of earlier conversion to dementia compared with the reference group
SE Standard error, HR Hazard Ratio, CI confidence intervals from HR
Table 4.
Comparisons between AGED triad + vs each AGED triad factor
| Beta | HR | SE | z | p-value | Lower 95%CI | Upper 95%CI | |
|---|---|---|---|---|---|---|---|
| No AGED factors [reference] | - | - | - | - | - | - | - |
| Executive Dysfunction only | 2.23 | 9.36 | 0.68 | 3.25 | 0.001 | 2.43 | 36.1 |
| Gait only | 2.4 | 11.07 | 0.68 | 3.51 | 0.0004 | 2.9 | 42.27 |
| Apathy only | 0.89 | 2.44 | 0.87 | 1.01 | 0.30 | 0.43 | 13.69 |
| Triad (all 3 AGED factors) | 3.59 | 36.58 | 0.72 | 4.94 | 0.0000007 | 8.77 | 152.47 |
| Age | 0.08 | 1.08 | 0.04 | 2.08 | 0.03 | 1 | 1.17 |
| Sex | − 0.12 | 0.88 | 0.43 | − 0.28 | 0.77 | 0.37 | 2.07 |
| Years of education | − 0.03 | 0.96 | 0.06 | − 0.54 | 0.58 | 0.84 | 1.09 |
| MoCA | − 0.19 | 0.82 | 0.05 | − 3.4 | 0.0006 | 0.73 | 0.92 |
| Total number of comorbidities | − 0.05 | 0.94 | 0.09 | − 0.6 | 0.54 | 0.79 | 1.12 |
HR Hazard ratios, SE standard error, CI confidence intervals from HR. This analysis included 277, number of events = 31 (45 participants removed due to presence of two AGED factors). Bold p-values indicate statistically significant association between AGED triad and risk of earlier conversion to dementia compared with the reference group
Table 5.
Comparisons between AGED triad + vs. the number of AGED triad factors (0, 1, or 2)
| beta | HR | SE | z | p-value | Lower 95%CI | Upper 95%CI | |
|---|---|---|---|---|---|---|---|
| None [reference] | - | - | - | - | - | - | |
| 1 AGED factor (single) | 1.96 | 7.16 | 0.57 | 3.39 | 0.0006 | 2.29 | 22.31 |
| 2 AGED factors (dyad) | 2.35 | 10.54 | 0.62 | 3.78 | 0.0001 | 3.11 | 35.7 |
| 3 AGED factors (triad) | 3.4 | 30.07 | 0.68 | 4.96 | 0.0000006 | 7.84 | 115.26 |
| Age | 0.07 | 1.08 | 0.03 | 2.39 | 0.01 | 1.01 | 1.15 |
| Sex | − 0.27 | 0.75 | 0.36 | − 0.75 | 0.44 | 0.37 | 1.55 |
| Years of education | − 0.1 | 0.89 | 0.05 | − 1.9 | 0.05 | 0.8 | 1 |
| MoCA | − 0.21 | 0.8 | 0.04 | − 4.65 | 0.000003 | 0.73 | 0.88 |
| Total number of comorbidities | − 0.07 | 0.92 | 0.07 | − 1 | 0.31 | 0.79 | 1.07 |
321 entered in the analysis, number of events = 43. Bold p-values indicate statistically significant association between AGED triad and risk of earlier conversion to dementia compared with the reference group
SE Standard error, HR Hazard Ratio, CI confidence intervals from HR
Statistical analysis
We used mean, standard deviation, and percentages to describe sociodemographic, functional, medical, physical and cognitive aspects of the AGED triad + and AGED triad- groups (Table 1). Cox-regression models were used to compare the dementia onset risk between AGED triad + and AGED triad-. Time-to-event (i.e., dementia conversion onset) was calculated using the date when the conversion to dementia was ascertained during the follow-up relative to baseline visit (i.e., time-to-event = dementia conversion date − baseline visit date). Conversion to dementia (dichotomous) and time-to-event (continuous) were then entered in all Cox-regression models for risk (i.e., hazard ratios) comparisons. Two additional Cox-regression models were created to compare the risk of earlier dementia onset between AGED triad + and individuals presenting only one AGED factor (i.e., apathy, gait slowness, or executive dysfunction), as well as to compare individuals with fewer AGED factors (i.e., 0, 1, or 2 factors). A minimum number of six dementia events per independent variable assured statistical stability of Cox-regression models [34]. The same approach has been used in previous longitudinal analyses in the same cohort [17, 35]. Kruskal–Wallis tests were applied to compare the percentage of individuals with one or more modifiable vascular risk factors associated with risk of dementia selected for our study [36] in each group (supplementary Tables 1 and 2). A binomial regression model was used to determine the odds of AGED triad + membership (dependent variable) compared with AGED triad-, for each one of the five eligible modifiable vascular risk factors (independent variable) in our study (supplementary Table 3). Statistically significant differences were accepted whenever a p ≤ 0.05 was achieved. Analyses were performed in the R software Project for Statistical Computing v. 4.3.1 (www.R-project.org).
Results
From 450 participants available in the Gait & Brain dataset, at the moment of the data extraction period, only 322 had follow-up on dementia conversion (mean of 45.12 ± 8.6 months; 6 to 108 months). Sixteen participants (5.0%) were classified as AGED triad + (i.e., concomitant presence of apathy, gait slowness, and executive dysfunction) at baseline. Full characterization of the AGED triad + and – are described in Table 1. In brief, AGED triad + were older, had more comorbidities and had poorer cognitive and physical functions. According with our criteria for AGED factors, there were 82 participants (24.5%) with executive dysfunction, 81 participants (25.2%) with apathy, and 79 (24.5%) with gait slowness. A group of participants had only one (single) or two (dyad) AGED triad factors as follows: 40 (13.1%) individuals had apathy only; 31 (10.1%) had gait slowness only; 35 (11.4%) had executive dysfunction only; 106 (34.6%) had only one AGED triad factor (AGED single); and 44 (13.7%) had two AGED triad factors only (AGED dyad) (Table 2).
A total of 44 participants (13.6%) converted to dementia with annual dementia incidence rate of 3.8% (see supplementary material for calculations) or 38 person per 1000-year; however, 1 participant in the AGED triad- group who converted to dementia could not be included in the final analysis because of missing data for covariates totalizing 43 participants who converted to dementia included in the final analysis. In this study a total of 32 participants were clinically diagnosed with Alzheimer’s disease, 2 were clinically diagnosed with the Alzheimer’s disease frontal variant, 2 were clinically diagnosed with mixed dementia, 1 was clinically diagnosed with Frontotemporal dementia, 4 were clinically diagnosed with vascular dementia, 1 was clinically diagnosed with Lewy body dementia, and 2 had undefined dementia category (Supplementary Table 5).
Nine participants (56.25%) in the AGED triad + converted to dementia against 35 participants (11.14%) in the AGED triad-. Overall, one (2.5%) case of conversion to dementia was observed in individuals with apathy only, 7 (23.3%) in individuals with gait slowness only, and 7 (23.3%) in individuals with executive dysfunction only. A total of 15 (15%) participants with AGED single (i.e., only one AGED factor) and 13 (31.0%) with AGED dyad (i.e. only two AGED factors) converted to dementia, whereas 6 (3.7%) participants that did not present any AGED factors (i.e., no AGED factors) converted to dementia.
AGED triad and dementia onset
Cox-regression model adjusted for potential confounders estimated hazard ratios (HR) for dementia onset in individuals with AGED triad + compared with AGED triad- (see Table 3 and Fig. 1 for details). This model revealed that AGED triad + had a significant higher risk of earlier conversion to dementia compared with AGED triad- (adjusted HR = 5.08, 95%CI 2.16 to 11.97, p < 0.001). When AGED triad- was broken down into apathy, gait slowness, and executive dysfunction, the model showed that the individuals with the AGED triad + remained with the highest risk of early dementia onset (adjusted HR 36.58, 95%CI 8.77 to 152.47, p < 0.0001) compared with none AGED factors, followed by gait slowness (adjusted HR 11.07, 95%CI 2.9 to 42.27, p = 0.0004), executive dysfunction (adjusted HR 9.36, 95%CI 2.43 to 36.1, p = 0.001), and apathy (adjusted HR 2.44, 95%CI 0.43 to 13.69, p = 0.30) (see Table 4 and Fig. 2 for details).
Fig. 1.
Hazard ratios plots with survival tables showing the cumulative risk of dementia over time
Fig. 2.
Hazard ratios plots with survival tables showing the cumulative risk of dementia over time in individuals with none (reference group), Executive dysfunction only, Gait slowness only, Apathy only or all three AGED factors (triad)
Another Cox-regression model revealed an additive contribution of AGED factors to earlier dementia onset risk. This analysis showed that the risk of earlier dementia onset increased if individuals presented 1 to 3 AGED factors compared with zero AGED factors as follows: no AGED single (adjusted HR 7.16, 95%CI 2.29 to 23.31, p = 0.006); AGED dyad (adjusted HR 10.54, 95%CI 3.11 to 35.7, p = 0.0001); and AGED triad + (adjusted HR 30.07, 95%CI 7.84 to 115.26, p = 0.0000006) (Table 5 and Fig. 3 for details).
Fig. 3.
Hazard ratios plots with survival tables showing the cumulative risk of dementia over time in individuals with none, one (single), two (dyad) or three (triad) AGED factors
Association between AGED triad and modifiable vascular risk factors
From the five modifiable vascular risk factors selected for this study, only smoking history was not more prevalent in AGED triad + compared with AGED triad- (supplementary Table 1 for details). There was a higher prevalence of participants presenting more than 2, out of 5, modifiable vascular risk factors (i.e., high vascular risk burden) compared with AGED triad- (37.5% vs. 24.5%, respectively, supplementary Table 1). The prevalence of hypertension, diabetes, and high vascular risk burden linearly increased from none to three AGED factors (supplementary Table 2). Hypertension, obesity, and high cholesterol also increase the odds of AGED triad + membership although not statistically significant (p > 0.08). Noteworthy, high VRF burden (> 2 risk factors) and hypertension were significantly more prevalent in participants with obesity (46.4%, p < 0.001 and 55.1%, p = 0.02, respectively) than in non-obese participants (not shown in tables).
The binomial logistic regression adjusted for age, sex, MoCA, and years of education revealed that diabetes was the only VRF that significantly increased the odds of an AGED triad + membership (OR, 3.06; 95%CI 0.97, 8.93, p = 0.05). Despite not statistically significant, having more than two VRFs, hypertension, obesity, and high cholesterol also increased the odds of an AGED triad + membership (supplementary Table 3 for details).
Discussion
Our study demonstrated that individuals with the AGED triad + are at a higher risk of earlier onset of dementia compared with individuals who had the AGED triad- or present fewer AGED factors (i.e., none, single and dyad). Aligned with findings from a previous study [12], our results also showed that AGED triad + is significantly associated with greater burden of vascular risk factors (> 2), specifically hypertension and diabetes, thus suggesting that AGED triad would be a behavioral manifestation of insidious vascular changes on brain function.
This study empirically confirms that AGED triad could be a marker of earlier onset of dementia in older adults. Gait slowness only was the second strongest predictor of dementia, after AGED triad + , followed by executive dysfunction only and apathy only. Noteworthy, gait slowness and executive dysfunction had very similar onset risk, and both nearly threefold higher than apathy’s risk. This result could be explained by the fact that both gait slowness [37] and executive dysfunction [38] share common brain substrates, specifically smaller prefrontal brain volumes. It is possible that gait slowness would, therefore, represent a certain stage of executive dysfunction since gait demands cognitive resources for its optimum functioning [39, 40]. Therefore, gait slowness and executive dysfunction may be both a marker of more advanced prefrontal atrophy which would signal faster progression to dementia.
Our study also demonstrated an additive effect of AGED factors for dementia risk as that the presence of each additional AGED factor would accelerate risk of dementia onset. This additive effect of AGED factors aligns with a previous study demonstrating that older individuals with both cognitive and gait declines (dual decline) had higher risk of earlier conversion to dementia compared with only one decline (single decline) [35, 41]. Furthermore, our results also suggest that presence of an AGED factor would be a sign of vascular brain damage (see Table 4 for details) resulting from the insidious presence of hypertension and diabetes. In alignment with previous studies [12, 13], hypertension and diabetes had the strongest association with AGED triad + . Notably, diabetes has been associated with all dementia subtypes due to increased predisposition to microvascular lesions in white matter, amyloid deposition, hypoperfusion, and inflammation in patients with diabetes, which can accelerate neuronal death [42, 43]. Moreover, hypertension and diabetes may have greater insidious impact in frontal and subcortical regions [44, 45], potentially explaining its higher prevalence in the AGED triad + compared with fewer AGED triad factors in our study. We speculate, therefore, that the presence of an AGED factor signals the extension of cortical and subcortical impairments.
Compared with a previous study [12], ours showed a much lower AGED triad + prevalence (17% vs. 5.0% respectively). This lower prevalence in our study could be partially explained by the lower number of individuals with 80 years of age and older enrolled since AGED triad is more prevalent in older than younger participants and/or a less diverse population highly educated population. Notably, we could not find a significant association between apathy and dementia onset perhaps because apathy is not as strong as the depression score to indicate affective disorder in older people. It is important to mention that our decision to include apathy instead of depression, as an AGED factor, is because apathy is positively associated with both depression and dementia, and therefore, it would simplify the detection of affective dysfunction (i.e., depression or depressive symptoms) by using only three questions compared with 15 or 30 questions with sensitive information from the Geriatric Depression Rating Scale (GDS). It is also possible that our study is not statistically powered to find significant associations between apathy and dementia since a meta-analysis [46] revealed a significant association between apathy and incidental dementia but only in individuals with subjective cognitive impairment and mild cognitive impairment, whereas in individuals with normal cognition, this association was protective (i.e., lower dementia risk). A similar subgroup analysis in our study was not possible due to limited sample size. Future studies should replicate our findings in larger samples with different cognitive statuses.
From a mechanistic perspective, the association between AGED triad + and dementia could be due to damaged neural networks that modulate attention, complex thinking, and motor control largely located in frontal and subcortical brain regions. Vascular insults in white matter and/or decreased blood supply to brain regions (i.e., hypoperfusion) would likely affect brain networks and/or amplify current pathology decreasing processing speed and the individual’s global cognitive capacity [9]. This can limit the individual’s ability to perform activities of daily living at the usual level or independently. These potential mechanisms should be further investigated in future studies.
It is possible that AGED triad + is too stringent as a marker of accelerated cognitive decline given its low prevalence with high dementia incidence among participants with this phenotype. We want to reinforce, however, that our study is not seeking to replace the MCI diagnosis battery; instead, our intention is to demonstrate that individuals with AGED triad phenotype progress very rapidly to dementia and that the number of AGED triad factors may be a sign of rapid brain deterioration or dementia risk. Due to the elevated risk of dementia demonstrated by AGED triad individuals and the simplicity of AGED triad detection, it would be important that older individuals have the triad components tested frequently, particularly those who present 2 or more vascular risk factors. The AGED triad assessment can provide not only insights regarding an individual’s cognitive decline, but it can also help monitor the impact of vascular risk factors management. This aspect should be confirmed in future clinical trials.
Limitations
Our study has several strengths, including an extensive assessment battery for sample characterization, the control of several potential confounders, and the long follow-up to detect incidental dementia. However, important limitations should be acknowledged. Quantitative techniques were used to measure gait speed, which can be a limitation to wide clinical applicability although gait speed can be reliably measured with stopwatch using the same walking protocol [47]. We were unable to determine a potential causal-effect relationship between AGED triad + and cerebrovascular function (e.g., brain vessels blood pressure) and/or morphological brain changes over time (e.g., micro bleedings). Brain imaging analyses of participants’ cortical and subcortical regions [14] would strengthen cause-effects arguments of cognitive decline associated with cerebrovascular disease and dementia etiology. Future studies should address these limitations to better understand the mechanisms of the associations between AGED triad and future dementia onset. We acknowledge that a larger and more diverse sample including more participants with history of stroke or TIA may potentially yield different results including an association between AGED triad and vascular dementia since the AGED triad is associated with more vascular risk factors. It is also important to acknowledge that there are other dementia modifiable risk factors including fewer years of education, sedentarism, hearing loss, and depression that could also be potentially linked with the AGED triad and therefore those should be investigated in future studies.
Conclusion
Older adults presenting with the AGED triad phenotype are at a higher risk of earlier conversion to dementia showing a summative effect of the triad factors. The AGED triad construct may assist detection of older adults at higher risk of dementia and point to vascular risk factors that can be modified or prevented.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to express our gratitude to all participants from the Gait & Brain Study.
Funding
Dr. Montero-Odasso’s program in Gait and Brain Health is supported by grants from the Canadian Institutes of Health Research CIHR (MOP211220; PJT 153100), the Ontario Ministry of Research and Innovation (ER11 − 08 − 101), the Ontario Neurodegenerative Diseases Research Initiative (OBI34739), the Canadian Consortium on Neurodegeneration in Aging (FRNCNA137794), the Weston Family Foundation (BH210118), and the University of Western Ontario Department of Medicine’s Program of Experimental Medicine Research Award (POEM768915). He is the first recipient of the Schulich School of Medicine and Dentistry’s Schulich Clinician-Scientist Award.
Data Availability
Data from the Gait & Brain Study may be available upon request.
Declarations
Ethics approval
Participants involved in this study provided informed consent. The study was conducted in accordance with Helsinki Declaration and Institutional ethical standards.
Conflict of interest
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Nichols E, Steinmetz JD, Vollset SE, Fukutaki K, Chalek J, Abd-Allah F, et al. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Heal. 2022 10.1016/S2468-2667(21)00249-8 [DOI] [PMC free article] [PubMed]
- 2.Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020 10.1016/S0140-6736(20)30367-6 [DOI] [PMC free article] [PubMed]
- 3.Viswanathan A, Rocca WA, Tzourio C. Vascular risk factors and dementia: how to move forward? Neurology. 2009. 10.1212/01.wnl.0000341271.90478.8e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Montero-Odasso M, Ismail Z, Livingston G. One third of dementia cases can be prevented within the next 25 years by tackling risk factors. The case “for” and “against.” Alzheimer’s Res Ther. 2020 10.1186/s13195-020-00646-x [DOI] [PMC free article] [PubMed]
- 5.Takeda S, Rakugi H, Morishita R. Roles of vascular risk factors in the pathogenesis of dementia. Hypertens Res. 2020. 10.1038/s41440-019-0357-9. [DOI] [PubMed] [Google Scholar]
- 6.Sahathevan R, Brodtmann A, Donnan GA. Dementia, stroke, and vascular risk factors; a review. Int J Stroke. 2012. 10.1111/j.1747-4949.2011.00731.x. [DOI] [PubMed] [Google Scholar]
- 7.Hachinski V. Dementia: paradigm shifting into high gear. Alzheimer’s Dement. 2019. 10.1016/j.jalz.2019.01.006. [DOI] [PubMed] [Google Scholar]
- 8.Chen V, Ning H, Allen N, Kershaw K, Khan S, Lloyd-Jones DM, et al. Lifetime risks for hypertension by contemporary guidelines in African American and white men and women. JAMA Cardiol. 2019. 10.1001/jamacardio.2019.0529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Prins ND, Scheltens P. White matter hyperintensities, cognitive impairment and dementia: An update. Nat Rev Neurol. 2015. 10.1038/nrneurol.2015.10. [DOI] [PubMed] [Google Scholar]
- 10.Gothe F, Enache D, Wahlund LO, Winblad B, Crisby M, Lokk J, et al. Cerebrovascular diseases and depression: epidemiology, mechanisms and treatment. Panminerva Med. 2012;54(3):161–70. [PubMed] [Google Scholar]
- 11.Willey JZ, Scarmeas N, Provenzano FA, Luchsinger JA, Mayeux R, Brickman AM. White matter hyperintensity volume and impaired mobility among older adults. J Neurol. 2013;260(3):884–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hajjar I, Yang F, Sorond F, Jones RN, Milberg W, Cupples LA, et al. A novel aging phenotype of slow gait, impaired executive function, and depressive symptoms: relationship to blood pressure and other cardiovascular risks. J Gerontol A Biol Sci Med Sci. 2009;64(9):994–1001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hajjar I, Quach L, Yang F, Chaves PH, Newman AB, Mukamal K, et al. Hypertension, white matter hyperintensities, and concurrent impairments in mobility, cognition, and mood: the Cardiovascular Health Study. Circulation. 2011;123(8):858–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Hachinski V, Finger E, Pieruccini-Faria F, Montero-Odasso M. The apathy, gait impairment, and executive dysfunction (AGED) triad vascular variant. Alzheimer’s Dement. 2022. 10.1002/alz.12637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Wang Y, Pan Y, Li H. What is brain health and why is it important? BMJ. 2020. 10.1136/bmj.m3683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Zou L, Herold F, Cheval B, Wheeler MJ, Pindus DM, Erickson KI, et al. Sedentary behavior and lifespan brain health. Trends Cogn Sci. 2024. 10.1016/j.tics.2024.02.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Montero-Odasso MM, Sarquis-Adamson Y, Speechley M, Borrie MJ, Hachinski VC, Wells J, et al. Association of dual-task gait with incident dementia in mild cognitive impairment: results from the gait and brain study. JAMA Neurol. 2017;74(7):857–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text revision. Washington, DC: American Psychiatric Association; 2000.
- 19.Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9. [DOI] [PubMed] [Google Scholar]
- 20.Morris JC, Ernesto C, Schafer K, Coats M, Leon S, Sano M, et al. Clinical dementia rating training and reliability in multicenter studies: the Alzheimer’s Disease Cooperative Study experience. Neurology. 1997;48(6):1508–10. [DOI] [PubMed] [Google Scholar]
- 21.Reitan RM. Trail making test results for normal and brain-damaged children. Percept Mot Ski. 1971;33(2):575–81. [DOI] [PubMed] [Google Scholar]
- 22.Rosenberg SJ, Ryan JJ, Prifitera A. Rey Auditory-Verbal Learning Test performance of patients with and without memory impairment. J Clin Psychol. 1984;40(3):785–7. [DOI] [PubMed] [Google Scholar]
- 23.Blackburn HL, Benton AL. Revised administration and scoring of the digit span test. J Consult Psychol. 1957;21(2):139–43. [DOI] [PubMed] [Google Scholar]
- 24.Crowe SF. Does the letter number sequencing task measure anything more than digit span? Assessment. 2000. 10.1177/107319110000700202. [DOI] [PubMed] [Google Scholar]
- 25.Kaplan E, Goodglass H, Weintraub S. Boston naming test. The Clin Neuropsychol. 2001.
- 26.McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS—ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology. 2011. 10.1212/01.wnl.0000400650.92875.cf. [DOI] [PubMed] [Google Scholar]
- 27.Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011. 10.1093/brain/awr179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.McKeith IG. Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): Report of the Consortium on DLB International Workshop. J Alzheimer’s Dis. 2006. 10.3233/jad-2006-9s347. [DOI] [PubMed] [Google Scholar]
- 29.Chui HC, Victoroff JI, Margolin M, Jagust W, Shankle R, Katzman R. Criteria for the diagnosis of ischemic vascular dementia proposed by the state of California Alzheimer’s disease diagnostic and treatment centers. Neurology. 1992. 10.1212/wnl.42.3.473. [DOI] [PubMed] [Google Scholar]
- 30.Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37–49. [DOI] [PubMed] [Google Scholar]
- 31.Bertens AS, Moonen JEF, de Waal MWM, Foster-Dingley JC, de Ruijter W, Gussekloo J, et al. Validity of the three apathy items of the geriatric depression scale (GDS-3A) in measuring apathy in older persons. Int J Geriatr Psychiatry. 2017. 10.1002/gps.4484. [DOI] [PubMed] [Google Scholar]
- 32.Studenski S. Bradypedia: is gait speed ready for clinical use? J Nutr Heal Aging. 2009. 10.1007/s12603-009-0245-0. [DOI] [PubMed] [Google Scholar]
- 33.Strauss EA, Sherman EMS, Spreen O. Compendium of Neuropsychological Tests: administration, norms, and commentary. 3rd ed. New York: Oxfor University Press; 1998. [Google Scholar]
- 34.Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol. 2007;165(6):710–8. [DOI] [PubMed] [Google Scholar]
- 35.Montero-Odasso M, Speechley M, Muir-Hunter SW, Pieruccini-Faria F, Sarquis-Adamson Y, Hachinski V, et al. Dual decline in gait speed and cognition is associated with future dementia: evidence for a phenotype. Age Ageing. 2020;49(6):995–1002. 10.1093/ageing/afaa106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Gottesman RF, Schneider ALC, Zhou Y, Coresh J, Green E, Gupta N, et al. Association between midlife vascular risk factors and estimated brain amyloid deposition. JAMA - J Am Med Assoc. 2017. 10.1001/jama.2017.3090. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Wilson J, Allcock L, Mc Ardle R, Taylor JP, Rochester L. The neural correlates of discrete gait characteristics in ageing: a structured review. Neurosci Biobehav Rev. 2019. 10.1016/j.neubiorev.2018.12.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Yuan P, Raz N. Prefrontal cortex and executive functions in healthy adults: a meta-analysis of structural neuroimaging studies. Neurosci Biobehav Rev. 2014. 10.1016/j.neubiorev.2014.02.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Callisaya ML, Blizzard CL, Wood AG, Thrift AG, Wardill T, Srikanth VK. Longitudinal relationships between cognitive decline and gait slowing: the Tasmanian study of cognition and gait. J Gerontol Ser A-Biol Sci Med Sci. 2015;70(10):1226–32. [DOI] [PubMed] [Google Scholar]
- 40.Watson NL, Rosano C, Boudreau RM, Simonsick EM, Ferrucci L, Sutton-Tyrrell K, et al. Executive function, memory, and gait speed decline in well-functioning older adults. J Gerontol Ser A, Biol Sci Med Sci. 2010;65(10):1093–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Verghese J, Annweiler C, Ayers E, Barzilai N, Beauchet O, Bennett DA, et al. Motoric cognitive risk syndrome: multicountry prevalence and dementia risk. Neurology. 2014;83(8):718–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Iadecola C. Hypertension and dementia. Hypertension. 2014. 10.1161/HYPERTENSIONAHA.114.03040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Iadecola C. Sugar and Alzheimer’s disease: a bittersweet truth. Nat Neurosci. 2015. 10.1038/nn.3986. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Flint AJ, Eastwood MR. Frontal lobe syndrome and depression in old age. J Geriatr Psychiatry Neurol. 1988. 10.1177/089198878800100110. [DOI] [PubMed] [Google Scholar]
- 45.Kuo HK, Sorond F, Iloputaife I, Gagnon M, Milberg W, Lipsitz LA. Effect of blood pressure on cognitive functions in elderly persons. Journals Gerontol - Ser A Biol Sci Med Sci. 2004. 10.1093/gerona/59.11.1191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Van Dalen JW, Van Wanrooij LL, Moll Van Charante EP, Brayne C, Van Gool WA, Richard E. Association of apathy with risk of incident dementia: a systematic review and meta-analysis. JAMA Psychiatry. 2018;75(10):1012. 10.1001/jamapsychiatry.2018.1877. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Montero-Odasso M, Sarquis-Adamson Y, Song HY, Bray NW, Pieruccini-Faria F, Speechley M. Polypharmacy, gait performance, and falls in community-dwelling older adults. Results from the Gait and Brain Study. J Am Geriatr Soc. 2019 10.1111/jgs.15774 [DOI] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data from the Gait & Brain Study may be available upon request.