Abstract
Background:
Aging-associated cognitive decline is greater in non-Hispanic Black (NHB) adults than non-Hispanic White (NHW) adults. An important risk factor for cognitive decline with aging is arterial stiffening, though the importance to racial variation remains poorly understood.
Objective:
We examined the association of an estimate of arterial stiffness with cognitive function in a bi-racial sample of 60–85-year-old adults (N = 3,616, 26.5% NHB) enrolled in the National Health and Nutrition Examination Survey (NHANES) between 1999–2002 and 2011–2014.
Methods:
As a measure of vascular aging, pulse wave velocity was estimated (ePWV) using an equation incorporating age and mean arterial pressure and expressed as m/s. Using the digit symbol substitution test (DSST), cognitive function was expressed as the number of correctly matched symbols (out of 133) within 120 s. Linear regression models examined associations between ePWV and DSST.
Results:
In models that adjusted for sex, education, smoking, body mass index, history of cardiovascular disease, and hypertension, ePWV was inversely associated with DSST score in NHB adults (β= –3.47, 95% CI = –3.9 to –3.0; p < 0.001) and NHW adults (β= –3.51, 95% CI = –4.4 to –2.6; p < 0.001).
Conclusion:
ePWV is inversely associated with a measure of cognitive function in older Black and White adults. ePWV may be a useful measure of vascular aging that can offer insight into cognitive aging.
As the population continues to age, the burden of dementia and its predecessor, mild cognitive impairment (MCI), is expected to increase [1]. In the U.S., non-Hispanic Black (NHB) adults have a higher risk of Alzheimer’s disease (AD) and related dementias (ADRD) compared with non-Hispanic White (NHW) Americans [2, 3], and may also have more pronounced decline in cognitive function with increasing age [4]. Factors explaining this racial disparity are not fully understood but are likely moderated by structural racism and a combination of environmental, socioeconomic, and psychosocial factors interacting with vascular risk factors [5–7].
Many clinical and research professionals contend that the decline in cognitive function with advancing age is a partial extension of cardiovascular disease (CVD), as cognitive aging has a prominent vascular component [8–10]. Thus, greater atherosclerotic-vascular burden in NHB individuals may partially contribute to racial disparities in cognitive aging [11]. With aging, the loss in extracranial large artery elasticity, and subsequent elevation in arterial stiffness, exposes the brain to high blood pressure pulsatility that causes cerebrovascular and neural damage [12]. This damage has been proposed as a mediator of the association between arterial stiffness and cognitive function [13]. Numerous cross-sectional and longitudinal studies now support a strong association between vascular aging measured as large artery stiffening and cognitive aging [14], with arterial stiffness prospectively predicting cognitive decline [15–17] and transition to dementia in older adults [18–20]. While NHB individuals have higher levels of arterial stiffness at all ages when compared to NHW individuals [21–23], whether vascular aging is associated with racial variation in cognitive aging remains poorly understood. A potential reason for this knowledge gap may reside in the lack of large-scale studies that include both measures of cognitive function and arterial stiffness.
The gold standard method for the assessment of aortic stiffness, carotid-femoral pulse wave velocity (cfPWV), requires specialized, relatively cost-prohibitive equipment and technical proficiency. As such, this measure has been largely relegated to specialized laboratory settings and research clinics and may not be feasible to perform in resource-constrained environments. cfPWV can be reasonably estimated from two commonly measured clinical variables— age and blood pressure— and we have shown that estimated pulse wave velocity (ePWV) is an independent predictor of cardiovascular and cerebrovascular events in the general population [24–26]. The ability to estimate PWV from age and blood pressure in settings where cfPWV is not measured provides an opportunity to examine vascular aging as it relates to cognitive aging at the population level in large cohort studies. Whether ePWV has construct validity as a measure of vascular aging and may offer insight into racial variation in cognitive aging is unknown.
To this end, we examined the association between ePWV as a measure of vascular aging and cognitive function in a sample of older NHB adults and NHW adults from the National Health and Nutrition Examination Survey (NHANES). Understanding racial variation in the association of ePWV with cognitive function may offer insight into cognitive health disparities.
METHODS
Study design with assessment of mortality status
Data from the 1999–2002 and 2011–2014 National Health and Nutrition Examination Survey (NHANES) were extracted. All NHANES procedures have been ethically approved by the National Center for Health Statistics review board. Prior to any data collection, participant consent was obtained from all individuals. Additional information on NHANES methodology and data collection can be obtained from the NHANES website (https://www.cdc.gov/nchs/nhanes.htm). Further, all NHANES survey response rates have been published elsewhere (https://wwwn.cdc.gov/nchs/nhanes/ResponseRates.aspx).
Participants
Specific exclusion criteria for this study included adults < 60 years of age (age range 60–85 years) and those with a history of stroke, as well as those missing cognitive function measurement, blood pressure measurement, or missing other key covariate information (see Supplementary Figure 1 flow chart).
Cognitive function
Cognitive testing was completed in NHANES respondents that were ≥60 years of age and was assessed using the digit symbol substitution test (DSST), which assesses executive functions. Respondents were instructed to draw symbols that were paired with numbers (1–9) according to a key. The number of correctly matched symbols within 120 s was summed for the DSST score (maximum score 133). The DSST is a component of the Wechsler Adult Intelligence Test and has been used in large epidemiological and clinical studies [27–29]. The DSST relies on cognitive processing speed and sustained attention and is frequently used as a sensitive and reliable measure of executive function [30]. Reference values for DSST scores across decade of life, race/ethnicity, and sex has previously been explored in detail within NHANES [31].
ePWV
Estimated pulse wave velocity was determined from the following algorithm [32]:
9.587-(0.402*age)+(4.560*0.001*(age∧2)) -(2.621*0.00001*(age∧2)*MAP)+(3.176*0.001*age*MAP)-(1.832*0.01*MAP)
In this algorithm, age was expressed in years and mean arterial pressure (MAP) was calculated as follows: [(DBP) + (0.4*(SBP-DBP))] where DBP is diastolic blood pressure and SBP is systolic blood pressure. The method used to calculate MAP is in agreement with that used by the Reference Values for Arterial Stiffness Collaboration [33] and other studies exploring the association of ePWV with clinical outcomes [32, 34]. Traditional approaches to calculate MAP rely on the “one-third” method. A form factor of 0.33 may be more appropriate for younger adults with higher SBP amplification while a form factor 0.4 may be more optimal for those with lower SBP amplification (i.e., older adults) [35]. A form factor of 0.41 has previously been shown to more closely associate with target organ damage than a traditional form factor of 0.33 [36]. Pulse pressure (PP) was calculated as SBP-DBP. Blood pressure (BP) was obtained after resting quietly in a seated position for 5 min using a stethoscope and mercury sphygmomanometer. NHANES technicians completed a thorough BP training program (Shared Care Research and Education Consulting) that involved a didactic section, audio-video observation, and measurement of BP against a certified, BP instructor. For the calculation of MAP, the average of up to 4 BP assessments was utilized. ePWV has previously been shown to be correlated with the referent measure of cfPWV (r = 0.5–0.7) and invasively measured aortic PWV (r = 0.6) in small, select-cohort studies [34, 37] and is an independent predictor of mortality in NHANES [24, 38].
Covariates
Covariates included various demographic, behavioral, and CVD risk factors that could confound the association between ePWV and cognitive function. These included age (years), sex (male/female), education (college graduate or not), blood pressure (mmHg), physician-diagnosed CVD (yes/no), hypertension (yes/no), smoking, and body mass index (BMI). We considered both the steady (MAP) and pulsatile (PP) components of blood pressure (BP) separately as both have been shown to associate with cognitive function in older adults [39, 40]. Specific details on the methodological assessment of these covariates can be found on the NHANES website (https://www.cdc.gov/nchs/nhanes.htm).
Statistical analyses
All statistical analyses were performed via complex survey analytical procedures using Stata (v.12). To account for oversampling, non-response, non-coverage, and to provide nationally representative estimates, all analyses included the use of survey sample weights, clustering and primary sampling units. Specific details on this approach can be obtained via the NHANES website (https://www.cdc.gov/nchs/tutorials/nhanes/SurveyDesign/Weighting/intro.htm).
A weighted multivariable linear regression model was used to examine the association between ePWV and DSST score. Five specific weighted models were computed: 1) unadjusted, 2) adjusted for sex and education, 3) adjusted for model 2 plus CVD, hypertension, smoking, and BMI, 4) adjusted for model 3 plus age and pulse pressure, and 5) adjusted for model 3 plus age and mean arterial pressure. We observed no concerns of multicollinearity; in the fully adjusted model, the highest individual and mean variance inflation factor, respectively, were 3.54 and 1.51. Moderation by racial group was examined by first including a main effect of race, and its cross product with ePWV, into the base model. Second, models were also explored separately by race as it is well known that NHB adults have higher vascular risk factor burden compared to NHW adults and racial differences in the association of vascular risk factors with cerebrovascular and cognitive function are well established. Thus, effect modification may still occur in the absence of an interaction [41]. An adjusted Wald test was used to examine statistical differences for continuous variables between NHB adults and NHW adults. A design-based likelihood ratio test was used for categorical variables. For all analyses, statistical significance was established as a nominal alpha of ≤0.05 for main effects and ≤0.10 for interaction effects.
RESULTS
Analyses are based on complete data from 3,616 adults (60–85 years). Supplementary Figure 1 displays our exclusion flowchart. NHB adults were younger and had lower educational attainment than NHW adults (Table 1). Compared to NHW adults, NHB adults had a higher prevalence of hypertension but a lower prevalence of overt CVD (Table 1). NHB adults also had higher BMI and SBP and were more likely to smoke (Table 1). While NHB adults had slightly lower ePWV compared to NHW adults, NHB adults had lower DSST scores compared to NHW adults (Table 1).
Characteristics of the sample (N = 3,616)
SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; DSST, Digit Symbol Substitution Test; ePWV, estimated pulse wave velocity; CI, confidence interval. An adjusted Wald test was used to examine group differences for continuous variables. A design-based likelihood ratio test was used to examine statistical differences for categorical variables.
There was an inverse association between ePWV and DSST score for both older NHB adults and NHW adults in unadjusted and partially adjusted models (Table 2, p < 0.001 for all for Models 1–3). Adjusting for PP attenuated significance for NHW adults (β= –0.04 [95% CI = –0.77 to 0.68], p = 0.79) but not for NHB adults (β= –1.32 [95% CI = –2.3 to –0.31], p = 0.01). Adjusting for MAP attenuated significance for NHB adults (β= 1.86 [95% CI = –10.9 to 14.6], p = 0.78) but not for NHW adults (β= –3.84 [95% CI = –7.7 to 0.10], p = 0.05). There was no multiplicative interaction between race and ePWV on cognition (p = 0.87), suggesting that the ePWV-cognition slope was not different across racial groups. This aligns with Supplementary Figure 2, which shows inverse parallel slopes between the two racial groups.
Multivariable linear regression evaluating the association between ePWV and DSST
Coefficients represent unstandardized coefficients, with 95% confidence intervals in parentheses followed by R2-values. Bolded values are statistically significant (p≤0.05). Model 1: unadjusted. Model 2: adjusted for sex and education. Model 3: adjusted for sex, education, CVD, hypertension, smoking, and BMI. Model 4: adjusted for sex, education, CVD, hypertension, smoking, BMI, age, and PP. Model 5: adjusted for sex, education, CVD, hypertension, smoking, BMI, age, and MAP.
DISCUSSION
This study set out to explore the association of ePWV as a measure of vascular aging with cognitive function appraised as DSST score in a nationally representative sample of older NHB and NHW adults from NHANES. ePWV predicted DSST score in both older NHB and NHW adults in unadjusted models and models adjusted for traditional CVD risk factors, history of CVD and sociodemographic characteristics, including educational attainment. There was no ePWV-by-race interaction suggesting that the strength of association between ePWV and cognitive performance was similar in older NHB and NHW adults. That is, there was no racial variation in the association between vascular aging and cognitive aging in older NHB and NHW adults. Additional separate adjustment for the steady (MAP) and pulsatile (PP) components of BP offered insight into the potential mediating role of BP on associations between vascular aging and cognitive aging. There was racial variation in the association of ePWV and DSST score when considering BP, such that adjusting for PP attenuated effects in NHW adults while adjusting for MAP attenuated effects in NHB adults. Collectively, our findings suggest that ePWV may be a useful proxy of vascular aging that offers similar insight into cognitive aging in older Black and White adults.
Our primary finding was that ePWV was similarly associated with DSST score in NHB and NHW adults from NHANES. Although Black adults in this study were slightly younger than White adults, DSST score was lower in NHB adults and ePWV was comparable between groups. By the nature of the equation used to calculate ePWV, a difference in age of 2–3 years would be expected to produce a difference in ePWV of ∼ 0.5–0.6 m/s. Thus, findings may still be taken to support a generalized hastening of vascular aging in NHB adults compared to NHW adults. Reasons for potential accelerated vascular aging in NHB individuals are unknown, but likely reflect the complex interactions of socio-demographic conditions and cumulative inequality, which have a detrimental effect on lifestyle and access to resources that promote healthy vascular aging [42]. Structural racism is a potent driver of health disparities and thus a notable harbinger of CVD [42]. Consistent with notable health disparities in socio-demographic and behavioral factors across race, NHB adults in our study had lower educational attainment, higher prevalence of smoking, higher BMI, and increased burden of hypertension. Elevated vascular risk factor burden in NHB adults may partially contribute to racial variation in white matter hyperintensity severity (a reflection of cerebral microvascular damage and ischemia) and cerebrovascular perfusion [43, 44]. This is important to note as higher white matter hyperintensity burden and cerebrovascular perfusion are associated with reduced cognitive function in African American adults but not NHW adults [45, 46]. Educational status is emerging as a potentially important moderator of the association between vascular aging and cognitive aging [47]. Vascular aging assessed as cfPWV is accelerated in those with lower educational attainment [48]. In a study by DuBose et al., cfPWV was inversely associated with cognitive function, an effect that was stronger in those with lower educational attainment (i.e., ≤ high school education). Education may help preserve cognitive “reserve” with advancing age, in a sense, maintaining cognitive function in a setting of age-associated deterioration in cerebrovascular and neural structure. Higher educational status may also be a proxy for socioeconomic status and with it a myriad of environmental structural privilege (e.g., lower neighborhood deprivation, safer spaces for exercise and physical activity, access to healthy foods, access to healthcare, etc.). Early vascular aging and longer duration of time spent with subclinical vascular dysfunction in NHB individuals may contribute to concomitant hastened target organ damage, disparately impacting cognitive function [49].
Adjustment for BP resulted in disparate effects on the association between ePWV and DSST score across race. BP has distinct steady and pulsatile profiles. The steady component (i.e., mean arterial pressure, MAP) is largely influenced by cardiac output and peripheral vascular resistance. The pulsatile component (i.e., pulse pressure, PP) reflects the integration of left ventricular systolic function, large-artery stiffness/impedance, forward wave pressure and pressure from wave reflections. Both MAP and PP are associated with cognitive function [7, 40] with racial variation noted in the cerebrovascular and cognitive effects of the distinct BP components [50, 51]. In the present study, associations between ePWV and cognitive function was significantly attenuated in NHW when considering the effect of pulse pressure, while association was significantly attenuated in NHB when considering the effect of mean arterial pressure. Our findings are largely in agreement with findings from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study whereby Black race was shown to modify the effect of MAP on cognitive decline over time but not the effect of PP [40]. Black individuals in REGARDS had significantly faster declines in cognitive function associated with higher MAP while declines in cognitive function in White individuals was more strongly associated with increases in PP [40]. We hypothesize that in NHB adults, increased MAP from vascular aging may overwhelm cerebral autoregulation with subsequent cerebral hyper-perfusion causing barotrauma and cerebrovascular damage, detrimentally affecting cognitive function [52, 53]. Conversely, in NHW adults, even though having lower MAP compared to NHB adults, hemodynamic pulsatility secondary to vascular aging may cause blood-brain barrier disruption and endothelial damage, detrimentally impacting neural and cerebrovascular structures and cognitive function [54, 55]. Although the hemodynamic pathways through which vascular aging impact cognitive function may differ by race, the end organ effect is similar. Taken together, our findings underscore the important association of BP and distinct steady and pulsatile components in affecting cognitive function in older adults.
Limitations to this study should be noted. The DSST is a commonly used cognitive test given its brevity, reliability, sensitivity, and specificity to detect presence of mild cognitive impairment as well as detect change in cognitive function with intervention. It has also been suggested that owing to its very inherent properties (i.e., a paper-pencil test that asks participants to match abstract symbols to numbers), it is not as influenced by language, culture, or education as other cognitive tests [30]. Nonetheless, the DSST as a measure of processing speed and global cognitive ability may still have implicit cultural bias that favors performance for NHW adults. This study utilized a cross-sectional design, which considers single exposures measured at one time point. As such, the study does not consider the time-varying nature of variables with aging and/or therapy or provide evidence of temporality. It should be acknowledged that history of possible dementia/dementia diagnosis was not considered in our analyses as this information was not available in NHANES cycles used herein. Since we relied on a single measure of processing speed, studies with other tests of domain-specific cognitive function are needed. Findings cannot be extended to middle-age and younger adults. Future studies may also find value from the exploration of APOɛ4 status given emerging studies noting racial variation in the association of APOE ɛ4 genotype with cognitive decline [56–58], as well as synergistic relationships between APOE ɛ4 genotype and PWV [59]. A strength of the current study is the use of a nationally representative sample of older adults.
It should be underscored that we are not suggesting ePWV as a surrogate for or replacement of cfPWV. The association between ePWV and the referent measure cfPWV has been shown to be modest (range r = 0.5–0.7), suggesting that ePWV and cfPWV are not equivocal measures [34, 37]. A measure of PWV derived solely from age and blood pressure cannot be expected to capture all individual-level alterations of the arterial system with aging (e.g., changes in intrinsic wall elastance, thickness, diameter, tortuosity) [37]. An implication of our findings suggests that ePWV can be applied to large epidemiological cohort studies that measure blood pressure. Such studies may potentially generate new hypotheses on vascular aging that can be tested in carefully designed prospective studies with more refined vascular measures.
In conclusion, we observed a similar association of ePWV with DSST score in Black and White older adults in NHANES. ePWV may hold promise as a simple vascular aging measure that offers insight into cognitive aging similarly in both Black and White older adults.
Footnotes
ACKNOWLEDGMENTS
This research benefited from grant, P30AG066583 (PI Jennifer Karas Montez), Center for Aging and Policy Studies, awarded to Syracuse University, in consortium with Cornell University and the University at Albany, by the National Institute on Aging of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
