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Stroke. 2001;32:1721-1724

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(Stroke. 2001;32:1721.)
© 2001 American Heart Association, Inc.


Original Contributions

Ankle-Brachial Index and 7-Year Ischemic Stroke Incidence

The ARIC Study

Albert W. Tsai, MPH; Aaron R. Folsom, MD; Wayne D. Rosamond, PhD Daniel W. Jones, MD

From the Division of Epidemiology (A.W.T., A.R.F.), School of Public Health, University of Minnesota (Minneapolis); Collaborative Studies Coordinating Center (W.D.R.), Department of Epidemiology, School of Public Health, University of North Carolina–Chapel Hill; and Division of Hypertension (D.W.J.), University of Mississippi Medical Center (Jackson).

Correspondence to Dr Aaron Folsom, Division of Epidemiology, School of Public Health, University of Minnesota, 1300 South 2nd St, Suite 300, Minneapolis, MN 55454. E-mail folsom{at}epi.umn.edu


*    Abstract
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Background and Purpose— Low ankle-brachial index (ABI), which is the ratio of tibial artery systolic blood pressure to brachial systolic artery pressure, is known to be a measure of lower limb peripheral artery disease as well as a marker for other cardiovascular disease events. The ability of ABI to predict incident ischemic stroke, however, is not established in population-based studies.

Methods— ABI was measured in a cohort of 14 839 black and white men and women aged 45 to 64 years. Stroke incidence was calculated during approximately 7 years of follow-up.

Results— A total of 206 incident strokes occurred. Adjusted stroke incidence rates were markedly higher for those in the lowest versus the highest categories of ABI for men, women, blacks, and whites. The proportional hazards regression model, adjusted for age, race, gender, and field center, showed an inverse linear trend between ABI and ischemic stroke incidence (P<0.0001). The lowest group (ABI <0.80) had a hazard ratio of 5.68 (95% CI 2.77 to 11.66). After adjustment for major risk factors in a multivariate model, the hazard ratio in the lowest group was elevated (1.93) but no longer statistically significant (95% CI 0.78 to 4.78). There was, however, still an indication of an overall inverse linear trend between ABI and incident stroke (P=0.03).

Conclusions— Low ABI was strongly associated with increased incidence of ischemic stroke, but the relationship was substantially reduced after adjustment for major cardiovascular risk factors.


Key Words: brachial artery • cerebral infarction • epidemiology • tibial artery


*    Introduction
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Alow ankle-brachial index (ABI), which is the ratio of posterior tibial artery systolic blood pressure (SBP) to brachial artery SBP, has long been known to be a measure of lower limb peripheral artery disease.1 Low ABI has also been shown to be a marker for other cardiovascular disease events. For example, in a previous report from the Atherosclerosis Risk In Communities (ARIC) Study, ABI was inversely associated with prevalent clinical coronary heart disease (CHD), prevalent stroke, and preclinical atherosclerosis of the carotid and popliteal arteries.2

The ability of ABI to predict incident stroke has not been firmly established. The Edinburgh Artery Study reported an adjusted relative risk of stroke of 1.98 (95% CI 1.05 to 3.77) for an ABI of <=0.9.3 In 68-year-old Swedish men, the adjusted relative risk of ischemic stroke for an ABI of <=0.9 was 2.0 (95% CI 1.1 to 3.7).4 However, the Cardiovascular Health Study found no relation between incident stroke and low ABI (<0.9).5

In the present study, we investigated the independent predictive power of a low ABI for incident clinical stroke in a population-based cohort of black and white men and women.


*    Subjects and Methods
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The ARIC study sample consisted of 15 792 men and women aged 45 to 64 years at the baseline examination and was conducted during 1987 to 1989.6 Follow-up examinations took place in 1990 through 1992 (93% return rate), 1993 through 1995 (86%), and 1996 through 1998 (80%).

Resting ankle and brachial SBPs were measured at baseline using the Dinamap 1846 SX. This automated device has high repeatability and validity compared with a Doppler probe.7 Ankle blood pressure was measured at the posterior tibial artery in 1 randomly selected leg. Two measurements, 5 to 8 minutes apart, were taken while the participant was in the prone position before a popliteal artery B-mode ultrasound scan. Brachial artery SBP was measured during the carotid ultrasound approximately every 5 minutes, usually in the right arm, with the participant in the supine position. ABI was computed by dividing the average of the 2 ankle SBP measurements by the average of the first 2 brachial readings.

Risk factor assessments have been described previously,6 including resting seated blood pressure, a sport index,8 fibrinogen and von Willebrand factor,9 and plasma lipids.10,11 Diabetes mellitus was defined as fasting glucose level of >=140 mg/dL, a nonfasting level of >=200 mg/dL, self-reported history of diabetes, or the use of any hypoglycemic agents in the past 2 weeks.

Left ventricular hypertrophy was determined with the Cornell voltage algorithm,12 as a score of >28 for men and >22 for women. Prevalent CHD was defined as reported history of a physician-diagnosed heart attack, evidence of a prior myocardial infarction by ECG, or self-report of prior coronary revascularization procedure.

Hospitalizations and deaths were ascertained by contacting ARIC study participants via telephone annually and through surveillance of death certificates and discharge lists from local hospitals.6,13 A nurse abstracted hospital records of potential stroke cases. Using symptoms, diagnostic procedures performed, and autopsy evidence, cases were classified as definite stroke, probable stroke, possible stroke of undetermined type, or no stroke by computer algorithm and by a physician reviewer.14 Differences between the computer and physician diagnoses were adjudicated by another physician. Ischemic strokes were defined as validated definite or probable embolic or thrombotic brain infarctions. Hemorrhagic strokes were excluded from this analysis.

Data Analysis
We excluded 329 (2.1%) participants with self-reported or unknown stroke history at baseline. We also excluded 624 (4.0%) participants without a satisfactory ABI index. The final sample consisted of 14 839 participants (1482 black men, 2450 black women, 5131 white men, 5776 white women).

Follow-up went from baseline until first ischemic stroke, death, lost to follow-up, or December 1996, whichever occurred first. Incidence rates, by level of ABI category, were computed from Poisson regression. Cox proportional hazards regression modeling was used to estimate hazard rates of incident ischemic stroke for categories of ABI and to adjust for potential confounding factors. Two-way interactions of ABI with gender, race, hypertension status, diabetes status, and cigarette smoking status were not found to be statistically significant. Because of the small numbers of events within gender- and race-specific strata and because no interaction was found between these variables and ABI category, gender and race groups were pooled. Linear tests for trend were performed by entering ABI into the models as a linear continuous term.


*    Results
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*Results
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A total of 206 incident ischemic strokes occurred among 14 839 participants during a median follow-up period of 7.2 years. Stroke incidence rates were markedly higher for those in the lowest versus the highest categories of ABI for men, women, blacks, and whites (Table 1). This gradient in rates was most notable, {approx}6-fold across categories, in men and whites.


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Table 1. Number of Events, Person-Years of Follow-Up, and Age–, Field Center–, and Race-Adjusted Incidence Rate of Ischemic Stroke (per 1000 Person-Years) for Various Levels of ABI by Sex, Race, and Overall in the ARIC Study

All risk factors were more prevalent in those with lower extremity arterial disease, defined as ABI of <=0.90, versus those without lower extremity arterial disease (Table 2). A consistent graded relation between risk factor levels and decreasing ABI was apparent. Persons with stroke were older and generally had a poorer cardiovascular risk profile.


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Table 2. Baseline Characteristics of Participants by Absence or Presence of Lower Extremity Arterial Disease, Category of ABI, and Incident Ischemic Stroke Status Restricted to Those Without Prevalent Stroke at Baseline in the ARIC Study

Multivariate Models
Table 3 provides the hazard rate ratios (HRs) of ischemic stroke using ABI of >1.20 as the reference category. The first model, adjusted for age, race, gender. and field center, showed an inverse linear trend between ABI and ischemic stroke incidence (P<0.0001). The lowest group (ABI <0.80) had an HR of 5.68 (95% CI 2.77 to 11.66). Lower extremity arterial disease versus no lower extremity arterial disease yielded an HR of 3.12 (95% CI 1.94 to 5.02).


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Table 3. Hazard Rate Ratios (95% CI) for Ischemic Stroke According to Lower Extremity Arterial Disease (>=0.9 Reference Group) and ABI Category (>1.20 Reference Group) in the ARIC Study

The second model added traditional risk factors and prevalent CHD to the model. After accounting for these major risk factors, the HR in the lowest group was elevated (1.92) but no longer statistically significant (95% CI 0.78 to 4.75). There was still an indication of an overall inverse linear trend between ABI and incident stroke (P=0.03).

Adjustment for other covariates in the third model did not greatly change the HR or inverse linear trend (P trend=0.06). Of the variables used in the third model, SBP, antihypertensive medication use, cigarette smoking status, pack-years of smoking, and diabetes accounted for nearly 70% of the total attenuation of the regression coefficient in a comparison of model 3 with model 1. We removed prevalent CHD in a supplemental model, but the regression coefficients for relative risk of stroke did not change significantly.

Another question that may be raised is whether knowledge of risk factors adds any predictive value after ABI level is known. To address this issue, we ran a stepwise regression model that forced ABI to remain in the model, and we calculated the statistical significance of additional risk factors. Risk factors that remained statistically significant in the model included age, gender, SBP, hypertension medication use, diabetes, current smoking, von Willebrand factor, and left ventricular hypertrophy.


*    Discussion
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowSubjects and Methods
up arrowResults
*Discussion
down arrowReferences
 
Low ABI, a subclinical marker for lower extremity arterial disease, was strongly associated with increased incidence of ischemic stroke in our population-based sample of men and women aged 45 to 64 years. Previous studies have shown that peripheral arterial disease is associated with older age, male gender, smoking, diabetes, hypertension, and hypercholesterolemia.15 These data showed that ABI is inversely related to traditional risk factors for CHD and represents a marker for atherosclerotic changes in other vascular beds. With the knowledge of this and the knowledge that prevalent CHD is a strong predictor for ischemic stroke, we thus must consider that we may be simply measuring a composite of the accumulation of CHD risk factors when looking at low ABI. Indeed, after adjustment for major stroke risk factors, the inverse linear relationship remained statistically significant, but the HRs across categories of ABI were considerably attenuated.

A limitation of the present study is that there were only 206 ischemic strokes, so we had low power for subgroup analyses. Also, ABI was measured as the average of 2 measurements in a single leg. The lowest measurements in either leg might have been used to more accurately identify decreased peripheral circulation.

The results of the stepwise regression model indicate that knowledge of some traditional stroke risk factors remains important in stroke prediction even after measurement of low ABI. ABI thus may have limited clinical use, because cardiovascular risk factors must be determined beyond knowledge of ABI to make rational decisions regarding clinical interventions. Although it may not be an effective clinical or screening tool, ABI may serve as a useful subclinical marker in epidemiological studies of cardiovascular disease.

In summary, there was a strong inverse association between ABI and ischemic stroke incidence. After adjustment for other risk factors for stroke, the relationship was substantially reduced. as might be expected if ABI is a marker of generalized atherosclerosis and the cumulative effects of risk factors. This suggests that low ABI would add little prognostic ability beyond traditional risk factors in the prediction of stroke.


*    Acknowledgments
 
The ARIC Study was funded by contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022 from the National Heart, Lung, and Blood Institute. The authors thank the staff and participants of ARIC for their valuable contributions over many years.

Received September 8, 2000; revision received January 23, 2001; accepted May 15, 2001.


*    References
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up arrowAbstract
up arrowIntroduction
up arrowSubjects and Methods
up arrowResults
up arrowDiscussion
*References
 
1. Schroll M, Munck O. Estimation of peripheral arteriosclerotic disease by ankle blood pressure measurements in a population study of 60-year-old men and women. J Chronic Dis. 1981; 34: 261–269.[Medline] [Order article via Infotrieve]

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3. Leng GC, Fowkes FG, Lee AJ, Dunbar J, Housley E, Ruckley CV. Use of ankle brachial pressure index to predict cardiovascular events and death: a cohort study. BMJ. 1996; 313: 1440–1444.[Abstract/Free Full Text]

4. Ogren M, Hedblad B, Isacsson S, Janzon L, Lindell S. Ten year cerebrovascular morbidity and mortality in 68 year old men with asymptomatic carotid stenosis. BMJ. 1995; 310: 1294–1298.[Abstract/Free Full Text]

5. Newman AB, Shemanski L, Manolio TA, Cushman M, Mittelmark M, Polak JF, Powe NR, Siscovick D. Ankle-arm index as a predictor of cardiovascular disease and mortality in the Cardiovascular Health Study. The Cardiovascular Health Study Group. Arterioscler Thromb Vasc Biol. 1999; 19: 538–545.[Abstract/Free Full Text]

6. The Atherosclerosis Risk in Communities (ARIC) Study. Design and objectives. The ARIC investigators. Am J Epidemiol. 1989; 129: 687–702.[Abstract/Free Full Text]

7. Mundt KA, Chambless LE, Burnham CB, Heiss G. Measuring ankle systolic blood pressure: validation of the Dinamap 1846 SX. Angiology. 1992; 43: 555–566.

8. Baecke JA, Burema J, Frijters JE. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr. 1982; 36: 936–942.[Abstract/Free Full Text]

9. Folsom AR, Rosamond WD, Shahar E, Cooper LS, Aleksic N, Nieto FJ, Rasmussen ML, Wu KK. Prospective study of markers of hemostatic function with risk of ischemic stroke. Circulation. 1999; 100: 736–742.[Abstract/Free Full Text]

10. Nägele U, Hägele EO, Sauer G, Wiedemann E, Lehmann P, Wahlefeld AW, Gruber W. Reagent for the enzymatic determination of serum total triglycerides with improved lipolytic efficiency. J Clin Chem Clin Biochem. 1984; 22: 165–174.[Medline] [Order article via Infotrieve]

11. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972; 18: 499–502.[Abstract]

12. Molloy TJ, Okin PM, Devereux RB, Kligfield P. Electrocardiographic detection of left ventricular hypertrophy by the simple QRS voltage-duration product. J Am Coll Cardiol. 1992; 20: 1180–1186.[Abstract]

13. White AD, Folsom AR, Chambless LE, Sharrett AR, Yang K, Conwill D, Higgins M, Williams OD, Tyroler HA. Community surveillance of coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) Study: methods and initial two years’ experience. J Clin Epidemiol. 1996; 49: 223–233.[Medline] [Order article via Infotrieve]

14. Rosamond WD, Folsom AR, Chambless LE, Wang CH, McGovern PG, Howard G, Copper LS, Shahar E. Stroke incidence and survival among middle-aged adults: 9-year follow-up of the Atherosclerosis Risk in Communities (ARIC) cohort. Stroke. 1999; 30: 736–743.[Abstract/Free Full Text]

15. Newman AB, Siscovick DS, Manolio TA, Polak J, Fried LP, Borhani NO, Wolfson SK. Ankle-arm index as a marker of atherosclerosis in the Cardiovascular Health Study. Cardiovascular Heart Study (CHS) Collaborative Research Group. Circulation. 1993; 88: 837–845.[Abstract/Free Full Text]




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