Cognitive decrement in older adults with symptomatic peripheral artery disease

Abstract

Peripheral artery disease (PAD) is highly prevalent, affecting up to 20% of people over 70 years of age. To test the hypothesis that PAD promotes the pathogenesis of vascular cognitive impairment (VCI), we compared cognitive function in older adults with symptomatic PAD and in participants without PAD who had a burden of comorbid conditions. Furthermore, we compared the cognitive function of these groups after adjusting for demographic and clinical characteristics, comorbid conditions, and cardiovascular risk factors. Participants with PAD (age: 69 ± 8 years; n = 58) and those without PAD (age: 62 ± 8 years; n = 30) were assessed on a battery of eight neuropsychological tests. The tests assessed attention and working memory, verbal memory, non-verbal memory, perceptuo-motor speed, and executive function. Participants were further characterized on demographic and clinical characteristics, comorbid conditions, cardiovascular risk factors, and ankle-brachial index. The PAD group had significantly lower neuropsychological scores than the non-PAD control group on all eight tests (P < .01). After adjusting for covariates, significantly worse scores in the PAD group persisted for verbal memory, measured by tests on logical memory-immediate recall (P = .022), and logical memory-delayed recall (P < .001), and for attention and working memory, measured by tests on digits forward (P < .001), and digits backward (P = .003). Participants with symptomatic PAD have substantially lower levels of performance on tests of attention, working memory, and verbal memory than participants without PAD independent of demographic characteristics and comorbid health burdens. These findings provide additional evidence in support of the concept that generalized accelerated vascular aging manifesting as symptomatic PAD in the peripheral circulation also affects the brain promoting the pathogenesis of VCI. These cognitive difficulties may also negatively impact symptomatic patient’s ability to understand and adhere to behavioral and medical therapies, creating a vicious cycle. We speculate that more intensive follow-up may be needed to promote adherence to therapies and monitor cognitive decline that may affect care.

Introduction

Peripheral artery disease (PAD) is highly prevalent, affecting up to 20% of people over 70 years of age and 202 million people globally [1]. Additionally, PAD is costly [2], leads to poor quality of life [3], and is associated with a high rate of all-cause and cardiovascular mortality [4].

The primary symptom of PAD is leg pain during ambulation, known as claudication [5], which leads to ambulatory dysfunction [6], impaired functional status that declines over time [7, 8], and low daily physical activity [9].

PAD is a marker of cognitive impairment and dementia [10, 11], and is associated with a greater risk for vascular cognitive impairment (VCI) [12–14]. We have previously shown that participants with symptomatic PAD have worse performance on cognitive function in the domains of nonverbal memory, concentration, executive function, perceptuo-motor speed, and manual dexterity than healthy controls free of cardiovascular risk factors and carefully screened individuals with hypertension [15]. These findings are clinically relevant because cognitive dysfunction in PAD patients is associated with functional impairment [16].

People with PAD may have cognitive dysfunction due to a high prevalence of cerebral vascular disease [17], which may impair blood supply to the brain [18]. In addition to large vessel atherosclerosis, microvascular function is also impaired in PAD, which contributes to the symptomatic manifestation of the disease [19–22]. There is increasing evidence that microvascular disease associated with PAD is a systemic phenomenon, which likely also contributes to impaired blood supply of the central nervous system [23, 24]. Importantly, cardiovascular risk factors are highly prevalent in patients with PAD [25, 26], which per se may contribute to microvascular impairment and cognitive dysfunction. Indeed, it has been shown that risk factors such as hypertension [27–30], diabetes [31–33], dyslipidemia [31, 34], obesity [35, 36], cigarette smoking [37, 38], and heightened inflammatory status [39] all negatively impact microvascular function and cognitive performance. However, it is not clear whether older individuals with PAD perform more poorly on cognitive tests compared to older individuals without PAD who have common comorbid conditions and cardiovascular risk factors. This investigation extends our previous results comparing PAD and non-PAD groups [15] by examining this issue.

The primary aim of this study was to compare cognitive function in older adults with symptomatic PAD and in participants without PAD who had a burden of comorbid conditions, with hierarchical adjustments for demographic characteristics, comorbid conditions, and cardiovascular risk factors. We hypothesized that participants with PAD would display poorer performance in domains of cognitive function which include attention, working memory, verbal memory, non-verbal memory, perceptuo-motor speed, and executive function after adjustment of demographic confounders, and that group differences would persist after further adjustment for comorbid conditions and cardiovascular risk factors.

Methods

Participants

Approval and informed consent

The procedures of this study were approved by the institutional review boards from the University of Oklahoma Health Sciences Center and by the University of Maryland, Baltimore, and written informed consent was obtained from each participant prior to beginning the investigation.

Recruitment

People who had symptomatic PAD (Fontaine Stage II and Rutherford Grade I) [5] were recruited by referrals, flyers posted in vascular laboratories and vascular clinics, and newspaper advertisements for possible enrollment into the study. People who did not have PAD were recruited via flyers posted in vascular and internal medicine clinics throughout the medical centers, and newspaper advertisements.

Medical screening through history and physical examination

Protocol

Participants were evaluated in the morning at the Clinical Research Center [40]. Participants arrived in the morning fasted, but were allowed to take their usual medications. To begin the study visit, participants completed the consent form and the Mini-Mental State Examination (MMSE) questionnaire [41]. Vital signs, demographic information, height, weight, body mass index, ankle-brachial index (ABI) [42], and waist circumference [43] were then recorded according to standard guidelines. Subsequently, participants had blood samples drawn, which were then sent to a central lab for analyses for fasting blood chemistries, including a complete metabolic panel, a lipid panel, and insulin measurement.

Participants then underwent a medical history and physical examination by study physicians, in which current medications, cardiovascular risk factors, comorbid conditions, and claudication history were recorded. Based on this battery of baseline assessments, participants were coded on cardiovascular risk factors according to standard definitions for hypertension, dyslipidemia, and diabetes, as previously described [44]. Participants were coded positive for these cardiovascular risk factors if blood pressure, cholesterol, lipid, and glucose values exceeded normal ranges, or if they were on medications to treat these risk factors. For comorbid conditions, obesity was defined as having a BMI > 30 kg/m², and abdominal obesity and metabolic syndrome were defined according to the National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III definitions [45]. Coronary artery disease was defined by having at least one of the following conditions: a history of coronary percutaneous transluminal angioplasty, coronary stents, coronary artery bypass graft, myocardial infarction, or symptoms of exertional angina. Cerebrovascular disease was defined by having one of the following conditions: a history of carotid stents, carotid endarterectomy, carotid surgery, stroke, or transient ischemic attacks (TIA) [46]. Participants with PAD were further characterized on the presence, severity, and symptoms of PAD.

Inclusion and exclusion criteria for the PAD group

Participants with symptomatic PAD were included in this study if they met the following criteria: (a) history of ambulatory leg pain, and (b) presence of PAD defined by an ABI ≤ 0.90 [47] and/or a history of lower extremity revascularization. Participants were excluded for the following conditions: (a) absence of PAD (ABI > 0.90), (b) non-compressible vessels indicated by ABI > 1.40, (c) asymptomatic PAD (Fontaine Stage I; Rutherford Grade 0) [47], (d) critical limb ischemia PAD (Fontaine Stages III and IV; Rutherford Grades II–IV) [47], (e) use of medications indicated for the treatment of claudication (cilostazol or pentoxifylline) initiated within 3 months prior to investigation, (f) history of dementia or suspected dementia (MMSE score < 24), (g) neurological diseases or other conditions that limited exercise (e.g., unstable angina, symptomatic heart failure, symptomatic cardiac dysrhythmias), (h) active cancer, and (i) end-stage renal disease defined as stage 5 chronic kidney disease [48].

Inclusion and exclusion criteria for the control group

Participants without PAD were included in this study if they met the following criteria: (a) 50 years of age or older, and (b) ABI was in the normal range between 1.00 and 1.40. Participants without PAD were excluded from this study for the following conditions: (a) ABI < 1.00, (b) non-compressible vessels indicated by ABI > 1.40, (c) history of dementia or suspected dementia (MMSE score < 24), (d) neurological diseases or other conditions that limited exercise, (e) active cancer, (f) end-stage renal disease defined as stage 5 chronic kidney disease.

Tests and measurements

Neuropsychological testing

Participants were assessed on a neuropsychological test battery, as previously described [15]. Tests were selected for previously demonstrated sensitivity to vascular diseases including hypertension, PAD, and/or stroke, and to briefly assess the following domains of cognitive function: attention, working memory, verbal and non-verbal memory, perceptuo-motor speed, and executive function.

Attention and working memory were assessed by standard administration of the digits forward and digits backward portions of the Wechsler Adult Intelligence Scale – Revised, respectively [15]. Verbal memory (immediate and 30-min delayed recall) was examined by recall of connected discourse using the Logical Memory subscale of the Wechsler Memory scale – Revised (WMS-R) [15]. Non-verbal memory (immediate and 30-min delayed recall) was evaluated by recall of geometric figures using the Visual Reproductions subscale of the WMS-R [15]. Trail Making Test Parts A and B [15] were performed to assess perceptuo-motor speed and executive function. Part A of the Trail Making Test requires participants to draw a line connecting randomly arrayed, consecutively numbered circles as quickly as possible. In Part B, participants draw a line connecting consecutively numbered and lettered circles as quickly as possible by alternating between numbers and letters (i.e., 1-A-2-B-3). In addition to perceptuo-motor speed, this test assesses mental flexibility which is a key dimension of executive function.

Six-minute walk test

Participants performed a 6-min walk test in which two cones were placed 100 ft apart in a marked corridor [49]. Trained exercise technicians supervised the test and instructed the participants to walk as many laps around the cones as possible. The total distance walked during the test was recorded.

Statistical analyses

Means and standard deviations (SD) were calculated for continuous variables, and frequencies with percentage (%) were for categorical variables. The normality assumption for continuous variables was checked based on Shapiro–Wilk tests, and natural log-transformation was implemented if the assumption was violated. Group comparisons between the PAD and control groups were performed based on two-sample t-tests or Wilcoxon rank-sum tests for continuous variables, and Pearson chi-square tests or Fisher exact tests for categorical variables, as appropriate. Univariable (unadjusted) analyses were first conducted to contrast the performance of PAD and non-PAD patients. Subsequently, multivariable logistic regressions were performed to investigate PAD influence after adjusted for demographic characteristics, comorbid conditions, and cardiovascular risk factors that included abdominal obesity, cerebrovascular disease, hypertension, dyslipidemia, diabetes, and smoking history. The adjusted P-values were obtained based on Wald tests. In addition, several statistics were calculated to summarize the results, including the partial R² values quantifying the partial correlation of determination for PAD, Akaike information criterion (AIC) for model diagnosis, and overall adjusted R² values for goodness-of-fit check. All hypothesis tests were two-sided with the significance level of 0.05. Data was analyzed using SAS 9.4 Software.

Results

As shown in Table 1, by definition, the PAD group had a significantly lower mean ABI (P < 0.01) than the control group. Additionally, the PAD group was significantly older (P < 0.01), had a lower 6-min walk distance (P < 0.01), and had higher percentage of men (P < 0.01), lower percentage of Whites (P < 0.01), and higher prevalence of comorbid conditions and cardiovascular risk factors such as smoking history (P < 0.01), hypertension (P = 0.03), dyslipidemia (P = 0.01), diabetes (P = 0.01), abdominal obesity (P = 0.04), metabolic syndrome (P < 0.01), coronary artery disease (P = 0.05), and cerebrovascular disease (P < 0.01).

Table 1.

Clinical characteristics of participants with symptomatic peripheral artery disease (PAD) and controls^a

Variables	Control group (n = 30)	PAD group (n = 58)	P value
Age (yr)	62 ± 8	69 ± 8	< .01
Weight (kg)	78.5 ± 15.7	82.1 ± 16.8	.31
Height (cm)	166.6 ± 8.0	170.3 ± 8.8	.15
Body mass index (kg/m2)	28.3 ± 5.5	28.8 ± 5.7	.72
Ankle/brachial index	1.17 ± 0.09	0.68 ± 0.26	< .01
6-min walk distance (m)	498 ± 78	369 ± 107	< .01
Sex (men)	9 (30)	44 (76)	< .01
Race (Whites)	28 (93)	36 (62)	< .01
Education (high school graduate)	29 (97)	46 (79)	.01
Smoking history	10 (33)	51 (88)	< .01
Hypertension	17 (57)	47 (81)	.03
Dyslipidemia	12 (40)	41 (71)	.01
Diabetes	6 (20)	28 (48)	.01
Obesity	10 (33)	19 (33)	.96
Abdominal obesity	8 (27)	28 (48)	.04
Metabolic syndrome	6 (20)	35 (60)	< .01
Coronary artery disease	2 (7)	12 (21)	.05
Cerebrovascular disease	0 (0)	11 (19)	< .01
Chronic obstructive pulmonary disease	2 (7)	8 (14)	.28

^aData are presented as means ± SD or n (%)

As shown in Table 2, the PAD group had significantly lower neuropsychological scores than the control group for the Logical Memory–Immediate Recall (P < 0.01), Logical Memory–Delayed Recall (P < 0.01), Visual Reproductions–Immediate Recall (P < 0.01), Visual Reproductions–Delayed Recall (P < 0.01), Digit Span Forward (P < 0.01), and Digit Span Backward (P < 0.01) tests. Furthermore, the PAD group took a significantly longer time to complete the Trail Making A (P < 0.01) and Trail Making B (P < 0.01) tasks, indicating worse performance.

Table 2.

Neuropsychological performance of participants with symptomatic peripheral artery disease (PAD) and controls^a

Variables	Control group (n = 30)	PAD group (n = 58)	P value
Logical Memory – Immediate Recall	26.2 ± 7.5	19.8 ± 7.1	< .01
Logical Memory – Delayed Recall	23.5 ± 7.7	14.5 ± 7.1	< .01
Visual Reproductions – Immediate Recall	35.5 ± 5.2	28.4 ± 7.2	< .01
Visual Reproductions – Delayed Recall	32.0 ± 7.5	22.2 ± 10.1	< .01
Digit Span Forward	10.7 ± 2.5	7.8 ± 2.8	< .01
Digit Span Backward	8.7 ± 2.8	6.4 ± 2.6	< .01
Trail Making A (s)	27.6 ± 8.4	48.8 ± 25.9	< .01b
Trail Making B (s)	90.0 ± 55.5	151.5 ± 86.0	< .01b

^aData are presented as means ± SD

^bP-value based on Fisher’s exact test

Table 3 displays multivariable regression models determining the association between PAD status and each neuropsychological performance outcome variable. Model 1 was an unadjusted model and was significant (P < 0.001) for each variable, indicating that poorer performance was associated with having PAD. Model 2 was adjusted for demographic characteristics that included age, sex, race, and education, and PAD status was significant for Logical Memory–Immediate Recall (P = 0.015), Logical Memory–Delayed Recall (P < 0.001), Visual Reproductions–Immediate Recall (P = 0.012), Digit Span Forward (P = 0.007), and Digit Span Backward (P = 0.031), indicating that lower levels of performance on these measures were associated with PAD independent of demographic characteristics. Model 3 was adjusted for the demographic characteristics in model 2 plus comorbid conditions and cardiovascular risk factors that included abdominal obesity, cerebrovascular disease, hypertension, dyslipidemia, diabetes, and smoking history. PAD status was significant for Logical Memory–Immediate Recall (P = 0.022), Logical Memory–Delayed Recall (P < 0.001), Digit Span Forward (P < 0.001), and Digit Span Backward (P = 0.003), indicating that worse performance on these variables was associated with PAD independent of all of the covariates.

Table 3.

Multivariable regression models determining the association between peripheral artery disease status (yes/no) and each neuropsychological performance outcome variable in all participants (n = 88)

Neuropsychological variables	Model	Estimate (95% CI)	Partial R2	P value	AIC	Overall adjustedR2
Logical Memory – Immediate Recall	1 2 3	− 6.47 (− 9.65, − 3.30)  − 4.97 (− 8.15, − 1.80)  − 5.66 (− 8.84, − 2.49)	0.16 0.07 0.07	< .001 .015 .022	601.2 604.3 609.8	0.16 0.18 0.29
Logical Memory – Delayed Recall	1 2 3	− 9.03 (− 12.25, − 5.81)  − 7.49 (− 10.71, − 4.27)  − 8.80 (− 12.02, − 5.58)	0.26 0.14 0.15	< .001  < .001  < .001	603.8 606.7 612.7	0.26 0.29 0.38
Visual Reproductions – Immediate Recall	1 2 3	− 7.09 (− 10.00, − 4.17)  − 4.15 (− 7.07, − 1.24)  − 2.58 (− 5.50, 0.33)	0.21 0.07 0.03	< .001 .012 .160	586.2 566.7 559.9	0.21 0.41 0.55
Visual Reproductions – Delayed Recal	1 2 3	− 9.76 (− 13.87, − 5.65)  − 4.37 (− 8.49, − 0.26)  − 2.41 (− 6.52, 1.70)	0.20 0.04 0.01	< .001 .053 .323	646.8 623.0 610.1	0.20 0.43 0.60
Digit Span Forward	1 2 3	− 2.91 (− 4.11, − 1.71)  − 2.09 (− 3.29, − 0.89)  − 3.41 (− 4.61, − 2.21)	0.21 0.08 0.19	< .001 .007  < .001	430.0 432.4 421.6	0.21 0.24 0.45
Digit Span Backward	1 2 3	− 2.42 (− 3.61, − 1.24)  − 1.61 (− 2.79, − 0.43)  − 2.64 (− 3.82, − 1.46)	0.16 0.06 0.12	< .001 .031 .003	427.5 426.6 426.2	0.16 0.22 0.37
Trail Making A (s)a	1 2 3	0.48 (0.28, 0.68) 0.19 (− 0.01, 0.39) 0.17 (− 0.03, 0.37)	0.20 0.03 0.02	< .001 .092 .187	115.5 94.3 94.4	0.20 0.41 0.52
Trail Making B (s)a	1 2 3	0.53 (0.27, 0.78) 0.16 (− 0.09, 0.42) 0.22 (− 0.04, 0.48)	0.16 0.01 0.02	< .001 .287 .203	155.8 143.3 141.4	0.16 0.32 0.46

^aNatural log transformed data. AIC, Akaike information criterion

Model 1: unadjusted

Model 2: adjusted for age, sex, race, education

Model 3: adjusted for Model 2 plus abdominal obesity, cerebrovascular disease, hypertension, dyslipidemia, diabetes, and smoking history

Discussion

A major finding was that the group with symptomatic PAD had significantly lower levels of performance on tests of attention, working memory, immediate and delayed verbal memory, and immediate non-verbal memory tests after adjustment for key demographic confounders. In contrast, differences in the performance of PAD and non-PAD patients on tests of delayed non-verbal memory, perceptuo-motor speed, and executive function were primarily attributable to demographic confounders. Furthermore, this study found that diminished performance in attention, working memory, and verbal memory among symptomatic PAD patients persisted after further adjustment for comorbid conditions and cardiovascular risk factors, indicating that PAD was independently associated with these aspects of cognitive function.

Poor neuropsychological performance of patients with PAD

Results of our current study demonstrated that participants with symptomatic PAD have significantly lower levels of performance across a variety of domains of cognitive function—attention, working memory, immediate and delayed verbal memory, and immediate non-verbal memory—than control participants without PAD after adjustment for demographic confounders. This observation agrees with most previous studies that defined participants with PAD as having either intermittent claudication [15, 50] or an ABI < 0.90 [51], but not in all studies [52]. Although the exact pattern of cognitive performance differences varies somewhat across these prior investigations, including our own [15], this is likely attributable to methodological differences among studies such as variability in control groups and adjustment variables, neuropsychological tests administered, sample size and composition, and/or use of continuous ABI rather than PAD classification.

A unique aspect of this study is that we compared the PAD and control groups on a battery of neuropsychological tests after adjusting for comorbid conditions and cardiovascular risk factors (shown in model 3) to better isolate the association between PAD and neuropsychological performance. After adjusting for comorbid conditions and cardiovascular risk factors (abdominal obesity, cerebrovascular disease, hypertension, dyslipidemia, diabetes, and smoking history), the test of non-verbal immediate recall was no longer significantly worse in the PAD group. These results support the notion that concomitant conditions frequently observed in patients with PAD may, at least in part, explain their lower levels of performance on select cognitive tests. We previously found that diastolic blood pressure, plasma glucose levels, and history of smoking were significantly associated with variability in neuropsychological test performance within the PAD group [15]. Our current study confirms this finding, as hypertension, diabetes, and smoking history were among the conditions that were selected as covariates. Furthermore, Zimmerman et al. [16] previously noted an association of lower scores on a clock drawing test with poorer functional performance within groups of PAD and non-PAD patients, relations that persisted after adjustment for various cardiovascular comorbidities and risk factors.

Interestingly, the Logical Memory-Immediate and Delayed Recall tests, and the Digit Span Forward and Backward tests remained significantly worse in the PAD group after all statistical adjustments, suggesting that PAD was associated with poorer verbal memory, attention, and working memory. These types of difficulties may have important clinical implications for those with PAD who need to understand and adhere to complex medical and/or behavioral regimens, such as increasing physical activity [53] and engaging in supervised exercise therapy. Given that the Centers for Medicare and Medicaid Services recently released a National Coverage Determination for supervised exercise therapy for patients with symptomatic PAD, our current findings on cognitive function in patients with PAD are particularly relevant to a growing number of patients who now may be referred to cardiac rehabilitation programs, which may also include a home-based component [54]. Furthermore, the current findings support previous studies which found that patients with PAD display decrements in performance on tests of verbal memory [18, 50] and attention [11, 55].

The potential mechanism for these worse cognitive function parameters in patients with PAD likely involves a reduction in cerebral perfusion, at least in part, due to atherosclerotic lesions in larger cerebral arteries. Perhaps, more importantly, there is also generalized microvascular dysfunction in PAD patients [23, 24, 56–58], likely triggered by circulating factors that elicit pro-inflammatory and pro-oxidative phenotypic changes in endothelial cells [39, 59, 60]. The high metabolic demands of the neuronal tissue are met by 600 km of microvessels in the human brain, which ensures adequate delivery of oxygen, glucose, and other nutrients and enables effective washout of metabolic by-products and maintenance of the ionic milieu. The cerebral microcirculation is also responsible for the formation of the blood–brain barrier and regulation of transport of various substances and transmigration of cells across it. Cerebromicrovascular dysfunction and microvascular damage induced by endothelial oxidative stress and inflammation have been increasingly recognized as critical contributors to the genesis of vascular cognitive impairment [35]. Further studies are needed to better understand the mechanistic role of cerebromicrovascular dysfunction in the pathogenesis of cognitive impairment in PAD patients. In particular, there is growing evidence to suggest that impairment of neurovascular coupling responses, which are responsible for moment-to-moment adjustment of cerebral blood flow to the increased metabolic needs of active neurons, is causally linked to cognitive decline [61, 62]. In that regard, neurovascular coupling responses may be impaired in patients with PAD. Future investigations should also incorporate neuroimaging to evaluate subclinical brain pathology in PAD. Although few studies are available, results to date indicate relations of PAD, peripheral vascular disease, and/or lower ABI with greater brain atrophy and its progression, and white matter lesions [63–66]. Lastly, additional studies should also determine how PAD-related microvascular dysfunction is exacerbated in advanced aging and/or modulated by the severity or the lifetime burden of various risk factors.

Limitations

There are limitations to this study. The sample sizes of the groups were relatively small, and as with many clinical studies, there may have been a self-selection bias regarding study participation, particularly for those without PAD. Individuals who agreed to participate were volunteers and may have been the most affluent. As such, they may have had the greatest interest in clinical research, the most time to spend, the best access to transportation to the research center, and the best health compared with non-volunteers. Furthermore, the results of this study are only generalizable to people with symptomatic PAD and not to individuals with different stages of PAD, such as those with asymptomatic PAD or critical limb ischemia. There are limitations associated with the design of the study. Significant differences found in the neuropsychological variables between the participants with and without PAD do not provide evidence of causality, even with statistical adjustment of covariates in multivariable models. Additionally, although our analyses were adjusted for covariates, it is possible that statistically significant findings are due to confounding variables that were not measured or to residual confounding. Several potential confounders that were not assessed include neuropsychiatric conditions that may be associated with cognitive performance, such as depression, anxiety, and chemical dependency, as well as indicators of socio-economic status beyond that of education level, such as income and occupation. There is a limitation associated with quantifying each risk factor and medication dichotomously, as this may not necessarily reflect the severity or the lifetime burden of each risk factor. There are limitations associated with the neuropsychological battery of measurements, as they provide only a sample of cognitive functions. Additionally, the specific neuropsychological tests have limitations, as they do not assess all aspects of their representative domains of function. Although these limitations exist, we believe that the findings of the present study are generalizable to a large number of participants with symptomatic PAD and older participants without PAD because of the relatively high prevalence of cardiovascular risk factors, such as hypertension, dyslipidemia, diabetes, obesity, abdominal obesity, and metabolic syndrome.

Conclusion and clinical significance

In conclusion, participants with symptomatic PAD have substantially lower levels of performance across a variety of cognitive function domains than participants without PAD. Furthermore, these decrements in attention, working memory, and verbal memory were independently associated with PAD after adjusting for both demographic characteristics and common health burdens. The clinical significance is that evaluation of cognitive function may provide insight into the planning of behavioral and medical therapies, and symptomatic patients’ ability to understand and adhere to these treatments. We speculate that attending to such cognitive challenges may require more intensive follow-up to promote adherence to these therapies and potentially minimize declines in cognitive performance in patients with symptomatic PAD.

Funding

This study was supported by grants from the National Institute on Aging (R01-AG-24296, K01-AG-00657, and P60-AG12583), a General Clinical Research Center (M01-RR-14467) sponsored by the National Center for Research Resources, by a Department of Veterans Affairs GRECC, and by the University of Maryland Claude D. Pepper Older Americans Independence Center (P60-AG-12583).

Declarations

Ethics approval

All authors have read and approved the manuscript.

Conflict of interest

The authors declare no competing interests.