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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:607-612 (2005)
© 2005 The Gerontological Society of America

Arterial Pulse Wave Velocity as a Marker of Poor Cognitive Function in an Elderly Community-Dwelling Population

Yoshinori Fujiwara1,, Paulo H. M. Chaves2, Ryutaro Takahashi3, Hidenori Amano1, Hiroto Yoshida1, Shu Kumagai1, Koji Fujita1, Dou Gui Wang1 and Shoji Shinkai1

1 Community Health
3 Human Care Research Groups, Tokyo Metropolitan Institute of Gerontology, Japan.
2 Center on Aging and Health, The Johns Hopkins Medical Institutions, Baltimore, Maryland.

Address correspondence to Yoshinori Fujiwara, MD, PhD, Community Health Research Group, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo 173-0015, Japan. E-mail: fujiwayo{at}tmig.or.jp


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Knowledge about potentially modifiable risk factors for cognitive decline is limited at this time. The aim of this study was to determine the cross-sectional relationship between a low level of cognitive function and brachial-ankle pulse wave velocity (baPWV) in a community-dwelling elderly population.

Methods. The study population included 352 community-dwelling Japanese persons ages 70 years and older who participated in a comprehensive health examination in April 2003. None had any history of cardiovascular disease. In addition to conventional medical examinations such as blood pressure and routine blood analyses, cognitive function was tested using the Mini-Mental State Examination (MMSE), and baPWV was determined using a recently developed noninvasive and automatic arterial waveform analyzer (AT-Form). This measure, with well-established validity and reproducibility, reflects both central and peripheral arterial flow. A multivariate logistic regression model tested the possible association between poor cognitive function (an MMSE score <24) and baPWV.

Results. Poor cognitive function was independently associated with the middle tertile of baPWV (odds ratio [OR] = 9.66, 95% confidence interval [CI] = 1.15 to 80.93), age (1-year increment; OR = 1.12, 95% CI = 1.04 to 1.22), and the highest tertile of pulse pressure (OR = 4.70, 95% CI = 1.08 to 20.48) even after multivariate adjustment of data for the effects of age, educational level, and hemodynamic and metabolic antecedents of atherosclerosis.

Conclusions. A high baPWV may be a potent risk factor for poor cognitive function in an elderly community-dwelling population, and this effect is independent of another marker of arterial stiffness: pulse pressure.

Cognitive decline is an important health issue that can jeopardize the ability of older persons to live independently (1). Nonetheless, knowledge about potentially modifiable risk factors for cognitive decline remains limited. Epidemiologic studies that investigated the relationship between blood pressure and cognitive decline have suggested the following (2–11): Vascular cognitive decline is due mainly to hypoperfusion, large artery disease, and small vessel disease, with most of these problems being associated with hypertension (12). Some longitudinal studies have reported that hypertension predicts the development of Alzheimer's disease (2–4). Several population-based longitudinal studies have shown associations between cognitive decline and elevated systolic pressure (5,6), elevated diastolic pressure (7), elevations of systolic and diastolic pressures (8), high pulse pressure (9,10), and a history of hypertension (11).

However, a recent study demonstrated a U-shaped relationship between blood pressure and cognitive function (13). de la Torre and colleagues (14) summarized risk factors common to vascular cognitive decline and Alzheimer's disease, suggesting that vascular factors, including hypertension, were associated with both conditions. Thus, complex relationships may exist involving another vascular factor as yet unidentified.

Pulse wave velocity, a measure of arterial stiffness, is influenced by both structural and functional changes in the arteries (15). Recent cohort studies have identified pulse wave velocity as an independent predictor of atherosclerotic cardiovascular disease events, death from cardiovascular disease (16–18), and all-cause mortality (16), independent of age, hemodynamic factors, and conventional atherosclerotic risk factors. To our knowledge, however, the relationship between pulse wave velocity and cognitive function has not been evaluated in a community-based study.

Komai and colleagues (19) reported that 24 patients in a geriatric hospital who had vascular cognitive decline had a higher mean pulse wave velocity than did 25 patients with Alzheimer's disease. However, little is known about relationships between cognitive function and pulse wave velocity in a healthy community-dwelling elderly population. The goal of the current study was to determine the cross-sectional relationship between pulse wave velocity and poor cognitive function (Mini-Mental State Examination [MMSE] score <24) in healthy community-dwelling older persons without cardiovascular disease.


   METHODS
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 Abstract
 Methods
Results
 Discussion
 References
 
Participants
Data were collected in April 2003 as part of a comprehensive health examination conducted in Kusastu, an eastern Japanese town. Based on a long-term care insurance program launched in 2000, the Japanese Ministry of Health, Labor and Welfare is promoting comprehensive health examinations for citizens ages 70 years and older in conjunction with Kusastu Town. This preventive program offers community-dwelling elderly persons screening for medical conditions such as cardiovascular disease, and for geriatric syndromes such as cognitive decline and frequent falls (20). Of 1091 residents 70 years and older, 429 volunteered for the examinations, which were conducted during a period of 5 days at a local public health center. All of those examined were encouraged to undergo cardiovascular testing, including: measurements of brachial-ankle pulse wave velocity (baPWV), ankle-brachial pressure index, and cognitive function. A total of 412 persons consented to all tests and provided written informed consent under conditions approved by the ethics committee of Tokyo Metropolitan Institute of Gerontology. Results were analyzed for 352 of the 412 participants, excluding 60 persons who had histories of cardiovascular disease: stroke only (n = 41), ischemic heart disease only (n = 22), or both stroke and ischemic heart disease (n = 3).

Measurements
Brachial-ankle pulse wave velocity.-- The BaPWV was determined using a newly developed noninvasive and automatic waveform analyzer (AT-Form; Colin, Komaki, Japan). This method has been described in detail (21–24). Briefly, after participants rested in bed for 5 minutes in the supine position, electrocardiograms were obtained by placing electrodes on the participants' wrists. S1 and S2 heart sounds were detected by a microphone positioned on the left edge of the sternum at the fourth intercostal space. Cuffs were wrapped on both brachia and ankles and connected to a plethysmographic sensor that determines volume pulse form and an oscillometric pressure sensor. Volume waveforms for the brachium and ankle were stored for a sampling time of 10 seconds with automatic gain analysis and quality adjustment to obtain sufficient wave form data. Pressure waveforms were recorded simultaneously at 2 different sites (brachial and tibial arteries) to determine the time interval between the initial rise in the brachial and tibial waveforms ({Delta}Ta).

The distance between sampling points of baPWV was calculated automatically according to the height of the participant. The path length from the suprasternal notch to the elbow ({Delta}Da) was obtained from superficial measurements and was estimated using the equation {Delta}Da = 0.220 x H – 2.073, where H (in centimeters) is the height of the participant. The path length from the suprasternal notch to the ankle ({Delta}Db) was calculated as: {Delta}Db = (0.564 x H – 18.381) + (0.249 x H + 30.709). The following equation then provided a surrogate index of pulse wave velocity in the lower extremity: ({Delta}Db – {Delta}Da)/{Delta}Ta.

The validity and reproducibility of this equipment were well documented. The baPWV correlated well with aortic pulse wave velocity (r =.87, p <.01) obtained using the catheter method. The interobserver coefficient of variation was 2.4% and the intraobserver coefficient of variation was 5.8% in healthy participants. The interobserver coefficient of variation was 8.4% and the intraobserver coefficient of variation was 13.3% in patients with coronary heart disease (21).

Laboratory data.-- Nonfasting blood samples were collected with the participants sitting. Samples were mixed immediately with EDTA-Na2 and stored at 4°C. Within 6 hours, the plasma was separated by 15 minutes of centrifugation at 5000g and 4°C, and the samples were stored at –80°C until analysis. Blood cell counts were obtained and routine tests of biochemical markers were performed using a sequential autoanalyzer.

Physiologic data and medical histories.-- Body mass index was calculated from the participants' measured height and body mass. The casual blood pressure was determined on the right arm after 5 minutes of seated rest, the pulse pressure being calculated as the difference between systolic and diastolic readings. The ankle-brachial index was based on systolic measurements taken from the right arm and both ankles (25); separate ratios were calculated for each leg. Blood pressures and ankle-brachial indices were measured simultaneously with baPWV, using AT-Form. The community health examination files provided information on five physician-diagnosed chronic medical conditions (presence or absence for each of hypertension, hyperlipidemia, stroke, ischemic heart diseases, and diabetes mellitus), and the use of antihypertensive drugs.

Assessment of cognitive function and functional status.-- The instrumental activities of daily living were evaluated using the five-item subscale of Instrumental Self-Maintenance from the Tokyo Metropolitan Institute of Gerontology Index of Competence (26): using public transportation (bus or train), preparing meals, shopping for daily necessities, paying bills, and handling personal banking. A yes/no response to each item in the index was obtained, the total score being the sum of the five items. A functional loss reflected a lack of independence in one or more of the five items. Cognitive function was assessed using the MMSE (27); scores on this test range from 0 to 30, with higher scores indicating a better cognitive performance. Participants were separated into 2 groups: controls (MMSE ≥ 24) and persons with impaired cognition (MMSE < 24).

Other variables.-- Participant-reported ratings of health were classified as excellent, good, fair, and poor. Depressive symptoms were evaluated using the Geriatric Depression Scale (short version), with scores ranging from 0 to 15 (28,29). A depressive tendency was reported for participants who had Geriatric Depression Scale scores of 6 points or more (29). Health habits (alcohol drinking and smoking) were assessed from participant reports as current versus former or never.

Statistical Analyses
Data were expressed as means ± standard deviation or n (%) for categorical items. Differences between groups were evaluated using chi-square tests or the Fisher exact test (when the expected number was fewer than 5) for categorical items and the Kruskal-Wallis test for continuous variables. Logistic regressions modeled the bivariate association between predictor variables and the outcome measure of poor cognitive function (MMSE < 24). Multiple logistic regression analysis with forced entry evaluated the relative contributions of covariates to poor cognitive function. The model included covariates that were statistically significant along with conventional risk factors for a decreased MMSE score (30), even though the latter were not statistically significant in the bivariate logistic regression analyses. All data were analyzed using the SPSS/PC+ Statistical Software for Windows version 11.0 (SPSS, Chicago, IL). Reported probability values are two-tailed, with the level of significance set at less than.05.


   RESULTS
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 Abstract
 Methods
 Results
Discussion
 References
 
Nearly all study participants were independent in their instrumental activities of daily living: Only 3 showed dependency when walking about the house, and none needed assistance in bathing, dressing, eating, or toilet care. The participants were separated into 2 groups according to their MMSE scores (poor cognition, MMSE < 24, n = 32; control, MMSE ≥ 24, n = 320).

Table 1 summarizes the characteristics of the dichotomized groups. Participants with poor cognition were significantly older, less well educated, and had lower hemoglobin and serum albumin levels. In addition, they had higher pulse pressures and baPWV, a greater prevalence of depressive symptoms, and were more dependent in their activities of daily living compared with participants in the control group.


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  		Table 1. Characteristics of Participants Without Histories of Cardiovascular Disease by Cognitive Function Level.

 
Table 2 shows the unadjusted odds ratio for detection of as low MMSE score as seen in bivariate logistic regression analyses. For the middle (1750 to 2070 cm/s, OR = 7.12, 95% CI = 2.04 to 24.92) and highest (>2070 cm/s, OR = 3.80, 95% CI = 1.03 to 13.99) tertiles of baPWV, a 1-year increment of age (OR = 1.16, 95% CI = 1.09 to 1.24), a lowest tertile of attained education (<7 years, OR = 6.7, 95% CI = 1.50 to 30.02), second highest (160 to 179 mmHg, OR = 4.86, 95% CI = 1.01 to 23.35) and highest (≥180 mmHg, OR = 6.18, 95 % CI = 1.06 to 36.08) quartiles of systolic blood pressure, and highest tertile of pulse pressure (>70 mmHg, OR = 5.28, 95% CI = 1.70 to 16.43) were positively associated with low scores for cognitive function. Low cognitive function was less likely for those in the middle tertile of hemoglobin A1c (HbA1c) (5.1% to 5.4%, OR = 0.30, 95% CI = 0.10 to 0.86), with a high serum albumin (>4.1 mg/dl, OR = 0.47, 95% CI = 0.22 to 1.00) and a history of hyperlipidemia (OR = 0.11, 95% CI = 0.01 to 0.79).


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  		Table 2. Unadjusted Odds Ratio of Lower MMSE (<24) in Participants Without Histories of Cardiovascular Disease.

 
Table 3 summarizes statistically significant independent risk factors associated with a low MMSE score. The middle tertile of pulse wave velocity (OR = 9.66, 95% CI = 1.15 to 80.93), a 1-year increment of age (OR = 1.12, 95% CI = 1.04 to 1.22), and the highest tertile of pulse pressure (OR = 4.70, 95% CI = 1.08 to 20.48) were shown to be independent risk factors, after adjusting for the significant variables found in bivariate logistic models and conventional risk factors for a low MMSE (such as total serum cholesterol, a history of hypertension, and a history of diabetes mellitus). The middle tertile of HbA1c approached statistical significance (OR = 0.29, 95% CI = 0.08 to 1.07, p =.062).


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  		Table 3. Risk Factors Associated With Having Lower MMSE (<24) Estimated by Multiple Logistic Regression Analysis in Participants Without Histories of Cardiovascular Disease.

 

   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
In the current sample of elderly persons free of overt cardiovascular disease, higher pulse wave velocity was associated with poor cognitive function, as measured by the MMSE scale. Low scores for cognitive function were 9.7 times more prevalent among participants from the middle tertile of pulse wave velocity (1750 to 2070 cm/s), independent of all the confounding variables considered. The highest tertile of pulse wave velocity (>2070 cm/s) was also associated with poor cognitive function, but the association (OR = 3.42) was not statistically significant after adjustment of data for all confounders. This is the first report suggesting an association between pulse wave velocity and cognitive function in a community-dwelling older population.

The mechanism leading to the association between pulse wave velocity and cognitive function is unclear. However, because pulse wave velocity is a marker of functional and structural changes in the arterial vessels (15), two possible explanations can be proposed based on vessel wall pathology and the pathway of cognitive decline, leading, respectively, to vascular cognitive decline and Alzheimer's disease.

First, the arterial stiffness observed in the highest tertile of pulse wave velocities is associated with white matter lesions; these are common in vascular-related cognitive decline and are generally considered to be a consequence of chronic ischemia associated with microvessel lesions (31,32). A second explanation is based on the recent theory that the pathologic changes in the cerebral vasculature seen in Alzheimer's disease may result from cerebral hypoperfusion and ischemia as well as vascular cognitive decline, and that ischemia may lead to accumulations of amyloid precursor protein and amyloid beta, expression of presenilin genes, and an accelerated formation of free oxygen radicals, as seen in animal experiments (33). Vascular diseases caused by hypertension may lead to dysfunction in the blood–brain barrier, which could be involved in the origin and pathogenesis of neurodegenerative cognitive decline (34,35).

In the current study, pulse pressure was inversely associated with cognitive function. Many studies have documented an association between hemodynamic factors (systolic, diastolic, and pulse pressures) and cognitive function (2–11). However, few population-based studies have focused on pulse pressures (9,10). A recent study reported a U-shaped relationship between pulse pressures and the incidence of Alzheimer's disease and all dementias in a 6-year community-based longitudinal study (9). By contrast, another study reported that pulse pressures measured 4 years before clinical evaluation had a marginally significant inverse association with the risk for Alzheimer's disease (10). These inconsistent results may arise from different characteristics of the study populations, varied proportions of Alzheimer's and vascular dementias, or other unknown causes, indicating the need for further study.

Although both pulse wave velocity and pulse pressure are affected by arterial stiffness, we found that the two variables are independent markers of poor cognitive function. Quantitative information on the elastic properties of the artery can be obtained by concomitant determinations of pressure and arterial diameter. Thus, pulse wave velocity, as defined by the arterial radius and the thickness of the arterial wall, can be a direct marker of arterial stiffness (36).

A recent longitudinal study shows that pulse wave velocity is an independent predictor of fatal stroke in patients with essential hypertension who are free of cardiovascular disease after adjustment for conventional cardiovascular disease risk factors, including pulse pressure (37). Pulse pressure was also a significant predictor of stroke in univariate analyses, although this relationship disappeared after adjustment of data for age. Taken together, it may be concluded that pulse wave velocity is a better parameter than pulse pressure to predict future cerebrovascular events (stroke) and to evaluate cerebrovascular perfusion (cognitive decline).

Because the participants volunteered for the comprehensive health examination, they might be healthier than nonparticipants (20). Nonresponders would be more likely to do poorly than responders in a community-based cognitive assessment (38). A "selective survival bias" must also be considered in studies of older persons. Those with severe atherosclerosis and a high pulse wave velocity do not live to old age. These might lead to underestimation of the OR in the highest tertile of baPWV. Nevertheless, the current findings indicate that a high pulse wave velocity is a sensitive marker of cognitive impairment in the apparently healthy community-dwelling elderly who are free of cardiovascular disease, even after adjustment of the data for age, educational level, and hemodynamic or metabolic risk factors for atherosclerosis. Future studies should explore the longitudinal association between pulse wave velocity and cognitive decline in a representative sample of the older population. A longitudinal study is essential to clarify the probable value of pulse wave velocity as a means to predict the future onset of dementia.


   Acknowledgments
 
Sponsored by the Japan Arteriosclerosis Prevention Fund.

The authors thank Ms. Tsuchiya at the Public Health Center in Kusatsu for her cooperation during the study, and Dr. Linda Fried, of Johns Hopkins University, and Dr. Roy J. Shephard, Professor Emeritus at the University of Toronto, for reviewing the manuscript.


   Footnotes
 
Decision Editor: John E. Morley, MB, BCh

Received October 28, 2003

Accepted February 10, 2004


   References
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 Abstract
 Methods
 Results
 Discussion
 References
 

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