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Arteriosclerosis, Thrombosis, and Vascular Biology. 1995;15:1269-1279

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(Arteriosclerosis, Thrombosis, and Vascular Biology. 1995;15:1269-1279.)
© 1995 American Heart Association, Inc.

Articles

Fibrinogen and Factor VIII, but Not Factor VII, Are Associated With Measures of Subclinical Cardiovascular Disease in the Elderly

Results From the Cardiovascular Health Study

Russell P. Tracy; Edwin G. Bovill; David Yanez; Bruce M. Psaty; Linda P. Fried; Gerardo Heiss; Marshal Lee; Joseph F. Polak; Peter J. Savage; for the Cardiovascular Health Study Investigators

From the Departments of Pathology (R.P.T., E.G.B.) and Biochemistry (R.P.T.), University of Vermont, Colchester; the Departments of Biostatistics (D.Y.) and of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle; the Departments of Medicine and Epidemiology, The Johns Hopkins University, Baltimore, Md (L.P.F.); the Department of Epidemiology, University of North Carolina, Chapel Hill (G.H.); the Department of Medicine, University of California, Davis (M.L.); the Department of Radiology, Brigham and Women's Hospital, Boston, Mass (J.F.P.); and the Epidemiology and Biometry Program, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Md (P.J.S.).

Correspondence to Russell P. Tracy, PhD, Department of Pathology, University of Vermont, Aquatec Bldg, Room T205, 55A S Park Dr, Colchester, VT 05446.


*    Abstract
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 *Abstract
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Abstract No studies have examined the associations of coagulation factor levels with measures of subclinical cardiovascular disease (CVD) in the elderly. The Cardiovascular Health Study (CHS) is a prospective, population-based cohort study of CVD in persons older than 65 years. At the baseline examination, we measured fibrinogen, factor VII, and factor VIII levels in 5024 of the 5201 participants of the CHS and examined the associations of these coagulation factors with measures of subclinical CVD in a cross-sectional analysis. Subclinical CVD measures were based on electrocardiography, carotid ultrasonography, echocardiography, and ankle-arm blood pressure measurements (AAI). For analyses, we used the full cohort as well as two mutually exclusive subgroups: those with prevalent clinical CVD at baseline and those without. Fibrinogen and to a lesser extent factor VIII showed positive associations with a variety of subclinical CVD measures. In age-adjusted analyses, fibrinogen and factor VIII were significantly associated with 8 of 10 measures. In multivariate analyses, fibrinogen was significantly associated with carotid artery stenosis, internal (but not common) carotid artery wall thickness, and AAI. Factor VIII was associated with abnormal wall motion and AAI in the full cohort only. Factor VII was not consistently associated with subclinical disease measures. In bivariate analyses that included data from all three groups, there were 5 positive subclinical disease associations and 5 negative associations for factor VII. In multivariate analyses, there were no significant associations between factor VII and subclinical CVD in the full cohort or in either subgroup. We conclude that in these cross-sectional analyses, fibrinogen and to a lesser extent factor VIII are associated with subclinical CVD in the elderly, even in those without symptoms or a history of clinical CVD. Factor VII, however, was not associated with subclinical CVD in the elderly.


Key Words: cardiovascular disease • blood coagulation factors • elderly • risk factors


*    Introduction
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 *Introduction
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More than 80% of the individuals affected by CVD in the United States are 65 years or older,1 yet little is known about the relationships between "traditional" risk factors and disease in this group. The CHS was designed to explore such relationships. Recently, evidence has been mounting that plasma coagulation factors are risk factors for CVD in middle-aged populations. Meade and coworkers,2 3 as part of the NPHS, have demonstrated that fibrinogen and factor VII, and to a lesser extent factor VIII, are predictors of ischemic heart disease and that the magnitude of this association is approximately the same as that between cholesterol and ischemic heart disease. The finding that fibrinogen is an independent risk factor has been supported by several other longitudinal studies,4 5 6 7 8 whereas data concerning factor VII have been developed primarily in cross-sectional studies.9 10 11 12 13 To date, virtually all results are consistent with the hypothesis that measures of coagulation, possibly as estimates of thrombotic potential, are predictors of CVD in middle-aged men and women.

In the aforementioned studies, there have been very few participants older than 65 years. In the two studies that examined the issue of fibrinogen and older age, the NPHS and the Framingham Study, fibrinogen was associated with CVD risk in older men in the Framingham Study in the initial analysis,7 but was found to be less so in a later analysis,8 whereas fibrinogen was reported to be unassociated with CVD risk in men older than 65 years in the NPHS.3

Since the careful studies of DeWood et al,14 most investigators believe that thrombosis is important as the precipitating event of acute ischemic disease in CVD. However, recent evidence has pointed to an additional role for thrombosis as a major factor in atherosclerotic plaque growth.15 16 17 In any case, the question of the relationship between coagulation factors, whose plasma levels may be related to thrombotic potential, and CVD risk is important in the elderly: while many elderly have atherosclerosis, some individuals appear able to avoid major ischemic events. It is possible that risk factors in the middle-aged, which may more often relate to atherogenesis, may become less important in the elderly, while measures of thrombotic potential may become more important as age increases.18

We have recently reported the distributions of fibrinogen, factor VII, and factor VIII levels in the elderly population of the CHS and the relations of these coagulation factors to age, race, and sex.19 A second recent CHS report demonstrated that fibrinogen, and to a lesser degree factor VIII, was associated with a global "index" of subclinical disease, but factor VII was not.20 In this article we report the associations of these coagulation factors to specific measures of subclinical CVD in the full cohort as well as in those with and without prevalent, clinical CVD at baseline. A report of the correlates of fibrinogen, factor VII, and factor VIII is in preparation (M. Cushman MD, et al, 1995, unpublished data).


*    Methods
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 *Methods
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CHS Design and Cohort
A description of the CHS design and methods has been published.21 There are four field centers in the CHS: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and, Pittsburgh, Pa. Each field center recruited approximately equal numbers of participants, for a total of 5201. All participants gave informed consent, and all relevant institutional committees on human research approved the study. The initial examination was conducted from June 1989 to June 1990. All participants were 65 years of age or older at the time of contact, with an age range of 65 to 100 years. More than one third of the participants were at least 75 years old. The major exclusion criteria were being institutionalized, being wheel-chair bound, currently under treatment for cancer, and planning to move from the area within 3 years. Of those contacted and eligible, 57% agreed to participate. Those who were ineligible or who refused to participate were more likely to be older, of lower income and education, unmarried, and to have limited physical activity.22

Participants answered standardized questionnaires that included medical history, quality of life, social support, personal health habits, and diet. Information on medication use was also collected,23 as were data on physical activity.24 The clinical exam included measures of anthropometry, blood pressure,25 26 ECG,27 carotid ultrasonography,28 echocardiography,29 and blood chemistry profiles,30 including an oral glucose tolerance test. Elevated blood pressure was defined as either "borderline" (systolic blood pressure measured while the subject was seated by random-zero sphygmomanometry [mean of five measurements; the "random" aspect decreases bias] between 140 and 159 mm Hg or mean diastolic blood pressure between 90 and 94 mm Hg) or "hypertension" (mean systolic blood pressure >=160 mm Hg, mean diastolic blood pressure >=95 mm Hg, or use of antihypertensive medications). Abnormal glucose tolerance was defined as "impaired" (fasting glucose <140 mg/dL and 2-hour postload glucose between 140 and 199 mg/dL) or "diabetes" (fasting glucose >=140 mg/dL, 2-hour postload glucose >=200 mg/dL, self-reported diabetes, or use of either insulin or oral hypoglycemic medications).31 "Smoking" was defined as "never," "former," or "current"; no restrictions were placed on the time since cessation of smoking for the "former" category.

The entire CHS cohort comprised 5201 individuals. For this study, 177 individuals were considered ineligible due to missing data or warfarin use, leaving 5024 eligible participants (97%). For analytical purposes, in addition to the those eligible from the full cohort, two mutually exclusive subgroups were defined: those with prevalent, clinical CVD at baseline (clinical CVD subgroup) and those without it (clinical CVD–free subgroup). The prevalent-disease subgroup consisted of those individuals who had any of the following characteristics: definite, possible, or unreported (ie, discovered during the examination) myocardial infarction, angina, stroke, transient ischemic attacks, congestive heart failure, or claudication; past coronary artery angioplasty, carotid endarterectomy, coronary artery bypass surgery, lower-extremity angioplasty, or pacemaker implantation; or rheumatic disease–related valve dysfunction. This subgroup consisted of 1672 of the 5024 eligible participants (33%). All other eligible participants (3352, or 67%) were designated as the clinical CVD–free subgroup. All statistical analyses were performed on these two subgroups as well as on the full cohort.

Measures of Subclinical Disease
Blood pressure (measured while the subject was seated) was used to calculate the AAI, with a value <0.9 considered abnormal.32 In the multivariate models, AAI was used as a continuous variable. Twelve-lead resting ECGs were obtained for all participants; abnormal ECG results and use of the ECG to define LVM have been described.27 For dichotomized analyses, an LVM value >80th percentile (sex specific) was considered abnormal. Ultrasound and quality control methods have been described in detail elsewhere.28 Duplex ultrasonography of the carotid arteries was performed, and results were expressed either as percent stenosis or as CCA or ICA wall thickness. Stenosis is reported as percentage of the arterial lumen occluded. For dichotomized analyses, stenosis in either the ICA or CCA >25% was considered abnormal. In the ANOVA model, the larger percent stenosis of the CCA or ICA was used to establish six strata: <1%, 1% through 24%, 25% through 49%, 50% through 74%, 75% through 99%, and 100%. Wall thickness values were used in both dichotomized (>80th percentile considered abnormal) and multivariate (continuous) models. M-mode, two-dimensional, and Doppler echocardiography was performed, with results expressed as either normal or abnormal LVEF, normal or abnormal wall motion, and LAD as described elsewhere.29 Wall motion and LVEF were used only in dichotomized analyses; LAD was used in both dichotomized (>80th percentile considered abnormal) and multivariate (continuous) models.

Blood Measurements
Methods of phlebotomy, sample handling, and shipment to the central laboratory at the University of Vermont, as well as the results of our quality-assurance programs, have been described.30 Plasma prepared with EDTA was used for analysis of lipids (cholesterol, HDL cholesterol, and triglycerides); citrated plasma kept at 4°C during preparation was used for fibrinogen and factor VIII measurements, and citrated plasma kept at room temperature (to avoid cold activation33 ) was used for factor VII assays. Separation of serum or plasma occurred within 30 to 40 minutes of venipuncture. Aliquots were frozen on-site to -70°C and shipped in batch to the central laboratory at the University of Vermont.

Serum insulin was measured by solid-phase radioimmunoassay using serum-based standards (Diagnostic Products), and glucose was measured using a Kodak Ektachem 700 Analyzer (Eastman Kodak). Fasting lipids were measured on an Olympus Demand system (Olympus Corp) that had been standardized in the Centers for Disease Control and Prevention Lipid Standardization program. LDL cholesterol was estimated using the Friedewald formula.34

Plasma fibrinogen, reported in milligrams per deciliter, was measured as the rate of clot formation by a semiautomated, modified Clauss method35 using a BBL Fibrometer (Becton-Dickinson). We used the Data-Fi fibrinogen calibration reference plasma (Baxter Healthcare Corp) as our standard. Results were confirmed by participation in the College of American Pathologists' comprehensive coagulation quality-assurance program and by assaying the CAP Fibrinogen Reference material. During the course of the study, internal-reference plasma samples were used to assess reproducibility of results. The mean monthly CV for our fibrinogen control plasma was 3.09%.

Assays for factor VII, reported as percent of a normal plasma pool, were performed with a Coag-A-Mate X2 instrument (Organon Teknika) using factor VII–immunodeficient plasma (Baxter-Dade) and the human placental thromboplastin Thromborel S (Behring). Standardization was performed by assaying reference plasma from the World Health Organization.36 The mean monthly CV for the factor VII assay was 5.31%.

Assays for factor VIII, also reported as percent of a normal plasma pool, were performed by using the Coag-A-Mate, factor VIII–immunodeficient plasma, and partial thromboplastin reagent from Organon Teknika. Standardization was done to World Health Organization reference plasma.37 The mean monthly CV for the factor VIII assay was 9.67%.

Statistical Analyses
All analyses were performed on microcomputers using the SPSS statistical packages.38 The first analyses for the full cohort and both subgroups were {chi}2 analyses of the demographic frequency data in Table 1Down. Then we performed ANOVA comparisons of age-adjusted mean values for the coagulation factors in those with and without positive results for the 10 measures of subclinical CVD: LAD, LVM, maximum left or right CCA stenosis, maximum left or right ICA stenosis (>80th or <80th percentile), wall motion, LVEF, ECG (normal or abnormal); AAI (<=0.9 or >0.9 in either leg), maximum stenosis in either the left or right CCA or ICA (>25% or not), and any of the above (in the disease-free subgroup only). Although a relatively large number of comparisons were made (n=84), the significance level was established at P<=.05 because we were using this analysis as a "screen" and wanted to include as many associations as possible. Measures of subclinical disease that were associated with significant differences in any of the age-adjusted coagulation factors in the clinical CVD–free subgroup were used in multivariate models to explore these associations more fully. The maximum stenosis variable, available as an ordered, discrete variable with six levels, was used in an ANOVA model in which the coagulation factor of interest was the dependent variable. The coagulation factor of interest was also used as a continuous variable in univariate and multiple linear regression models to predict the subclinical disease measure. The association of factor VIII with abnormal wall motion, a dichotomous variable ("normal" or "borderline" in one category and "abnormal" in the other), was explored by multiple logistic regression. The covariates in all multivariate analyses were the known CVD risk factors: age; sex; height; weight; smoking status; levels of LDL cholesterol, HDL cholesterol, fasting glucose; and systolic and diastolic blood pressures. There are three models for each subclinical CVD measure, corresponding to the full cohort and the clinical CVD and clinical CVD–free subgroups.


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  		Table 1. Demographic Data of the Full Cohort, the Subgroup With Prevalent CVD, and the CVD-Free Subgroup

To estimate the effect of coagulation factors in the multivariate models, we calculated a value that we called the "effect ratio." To calculate this value, we estimated the change in the predicted subclinical disease measure associated with a 1-SD change in the coagulation factor of interest. We then divided this number by a value equal to 1 SD for each predicted variable. Therefore, the effect ratio is the fraction of a 1-SD change in the disease variable that can be "explained" by a 1-SD change in the coagulation variable. In this way the effect sizes of the coagulation variables can be more easily compared.


*    Results
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 up arrowIntroduction
 up arrowMethods
 *Results
down arrowDiscussion
 down arrowReferences
 
Demographics
The distributions of fibrinogen, factor VII, and factor VIII have been published, and all three are slightly skewed toward the high end.19 The CHS cohort was divided into two mutually exclusive subgroups as described earlier in this report. Table 1Up describes several sex-stratified demographic variables for the full cohort as well as the two subgroups. {chi}2 analyses of the frequencies in each category that compare groups indicated that men were not different with respect to age, race, or weight but were different with respect to the other risk factor variables (P<=.05). As expected, the differences were always in the direction of the clinical CVD subgroup having a greater proportion of men in the "worse" risk factor category compared with the clinical CVD–free subgroup and the full cohort. The three groups of women showed the same pattern, except they did not differ with respect to smoking status.

ANOVA Analyses
Table 2Down lists the age-adjusted mean values for fibrinogen, factor VII, and factor VIII stratified by the 10 indicators of subclinical CVD, in the full cohort as well as the clinical CVD subgroup and the clinical CVD–free subgroup. Fig 1Down illustrates the difference in mean values (value for those with subclinical disease minus the value for those without) for the three coagulation factors in the clinical CVD–free subgroup.


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  		Table 2. Age-Adjusted Mean Values for Fibrinogen (Fib), Factor VII (FVII), and Factor VIII (FVIII), by Dichotomized Subclinical Disease Variables, for the CVD-Free Subgroup, the CVD Subgroup, and Full Cohort



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  		Figure 1. Bar graphs showing association of fibrinogen (top), factor VII (middle), and factor VIII (bottom) with measures of subclinical disease in those CHS participants free of prevalent CVD. Age-adjusted mean values for those without subclinical CVD were subtracted from those with subclinical CVD (Table 2Up) within each disease category, using data from the clinical CVD–free subgroup. The difference was then graphed above each disease category. Abn Wall indicates abnormal wall motion; Abn Ejc, abnormal left ventricular ejection fraction; Sten >25%, carotid artery stenosis >25% lumen occlusion; cWT >80%, CCA wall thickness >80th percentile; iWT >80%, ICA wall thickness >80th percentile; ECG Abn, ECG abnormality; Any, any of the above conditions. *P<=.001 and #P<=.01 by ANOVA.

Fibrinogen showed a consistent, positive association with all 10 measures of subclinical disease when all three groups were considered (Table 2Up). Fibrinogen was significantly associated with 8 of the 10 measures of subclinical disease in at least one of the three groups. In the clinical CVD–free subgroup, fibrinogen level was significantly associated with stenosis, CCA and ICA wall thickness, and AAI (Table 2Up and Fig 1Up). Factor VIII showed a similar pattern of association: 9 of 10 associations were positive in at least one group; 8 of 10 positive associations were statistically significant in at least one group; and there were 3 positive, significant associations in the clinical CVD–free subgroup. Compared with the results for fibrinogen, there were fewer associations with ultrasound-based measures and more associations with echocardiographic measures (Table 2Up and Fig 1Up).

Factor VII, in contrast, showed no consistent pattern. When all three groups were considered, factor VII was positively associated with 5 measures (3 significant associations) and negatively associated with 5 (3 significant associations). In the clinical CVD–free subgroup, there were 2 significant associations, both positive: LVM and CCA wall thickness (Table 2Up and Fig 1Up).

Multivariate Analyses
Multivariate analyses were based on results from the clinical CVD–free subgroup, as we anticipated less confounding due to the absence of prevalent, clinical CVD. Fig 2Down illustrates the mean values for fibrinogen in all three participant groups after adjustment for a variety of other CVD risk factors and stratified by percent stenosis. Data for factor VII and factor VIII are also shown for comparison purposes, although three factors were not associated with percent stenosis in the bivariate analyses. Fibrinogen was associated with percent stenosis in a graded, positive manner in all three groups, whereas the other two variables were not.



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  		Figure 2. Bar graphs showing association of fibrinogen (top), factor VII (middle), and factor VIII (bottom) with carotid artery stenosis in multivariate analysis. CHS participants were grouped on the basis of the level of stenosis in the carotid arteries as described in text. Mean values for fibrinogen, factor VII, and factor VIII were calculated with an ANOVA model that included the following covariates: age; sex; height; weight; smoking status; levels of LDL cholesterol, HDL cholesterol, and fasting glucose; and systolic and diastolic blood pressures. Data are shown for the clinical CVD–free subgroup (open bars), the clinical CVD subgroup (shaded bars), and the full cohort (filled bars). Within each group for ANOVA analyses: P<=.001 for fibrinogen and P=NS for factors VII and VIII; for trend analyses (in each of the three groups): P<=.001 for fibrinogen and P=NS for factors VII and VIII.

Tables 3Down, 4Down, and 5Down show the results of multiple linear regression models that were designed to determine whether the coagulation factors were significantly associated with the subclinical disease measures in multivariate analysis. Table 3Down shows the results for fibrinogen and three subclinical disease measures: CCA wall thickness, ICA wall thickness, and AAI. For CCA wall thickness, fibrinogen was significant in the bivariate model but not significant in any group in the multivariate models. However, for ICA wall thickness, fibrinogen was significant in all three groups in multivariate models. Fibrinogen was also strongly associated in multivariate models with AAI in all three groups.


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  		Table 3. Multiple Regression Analysis of the Relation Between Fibrinogen and CCA and ICA Wall Thickness and AAI in the Elderly


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  		Table 4. Multiple Regression Analysis of the Relation Between Factor VII and CCA Wall Thickness and LVM in the Elderly


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  		Table 5. Multiple Regression Analysis of the Relation Between Factor VIII and AAI and LAD in the Elderly

Although factor VII was associated with CCA wall thickness in the ANOVA analysis, there was no significant association in the regression models (Table 4Up). There was also no significant association between factor VII and LVM in the multivariate regression models.

As shown in Table 5Up, factor VIII retained significant although weak associations with AAI and LAD in the multivariate regression models in the full cohort but not in the two subgroups. Table 6Down illustrates the association of factor VIII with abnormal wall motion in logistic regression models. Factor VIII was significantly and independently associated with abnormal wall motion in the clinical CVD subgroup and in the full cohort.


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  		Table 6. Logistic Regression Analysis of the Relation Between Factor VIII and Abnormal Wall Motion in the Elderly

Fig 3Down illustrates the effect ratios, as described in "Methods," for the multiple regression models and the odds ratios (which compare values for factor VIII at the 25th and 75th percentiles) for the wall motion logistic regression models. The significant positive association of fibrinogen with CCA wall thickness was essentially removed by adjustment for other risk factors, whereas adjustment had little effect on the associations of fibrinogen with ICA wall thickness and AAI. A change in fibrinogen level equivalent in magnitude to a 1-SD change in fibrinogen distribution was associated with a change of approximately 5% of an SD in wall thickness and 10% of an SD in AAI. Adjustment for other risk factors removed any significant association between factor VII and CCA wall thickness and LVM and any significant association with factor VIII in the clinical CVD–free subgroup. However, adjustment did not completely remove the associations between factor VIII and AAI in the full cohort, with a change in factor VIII equivalent to 1 SD in the factor VIII distribution associated with a change in AAI equivalent to 4% of an SD. On the basis of logistic regression models, the odds ratio for abnormal wall motion (ie, the 75th percentile versus the 25th percentile for factor VIII) was approximately 1.2 to 1.3.



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  		Figure 3. Plots showing effect and odds ratios and confidence intervals (C.I.) for fibrinogen (top), factor VII (middle), and factor VIII (bottom) with respect to measures of subclinical disease. Using data from Tables 3Up, 4Up, and 5Up, we estimated the change in the predicted subclinical disease measure associated with a 1-SD change in the coagulation factor. We then divided this number by a value equal to 1 SD for each predicted variable. Therefore, effect ratio is the fraction of a 1-SD change in the disease variable "explained" by a 1-SD change in the coagulation variable. Odds ratios are also displayed for factor VIII, which were calculated by using the difference between the 25th and 75th percentile factor VIII values for abnormal wall motion, as described in Table 6Up. DIS (-) indicates clinical CVD–free subgroup, no covariates; DIS (-) adj, clinical CVD–free subgroup, adjusted for covariates; DIS (+) adj, clinical CVD subgroup, adjusted; FULL adj, full cohort, adjusted. Covariates used in the models were age; sex; height; weight; smoking status; levels of LDL cholesterol, HDL cholesterol, triglycerides, and fasting glucose; and systolic and diastolic blood pressures.


*    Discussion
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 up arrowIntroduction
 up arrowMethods
 up arrowResults
 *Discussion
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The primary result of this cross-sectional study is that fibrinogen is independently associated with measures of subclinical CVD, even when individuals with prevalent clinical CVD were excluded from analysis. In addition, factor VIII exhibited significant associations with AAI and wall motion abnormalities in multivariate analysis. Factor VII was not significantly associated with any measure of subclinical disease in multivariate analysis. The unique features of this study include the use of a variety of measures of subclinical disease and subgroup analyses of those with and without prevalent CVD. This study is also strengthened by the participation of the large number of community-dwelling elderly and extensive validation of clinical histories. The primary limitation of this study is the use of cross-sectional data.

Fibrinogen
In prospective studies, there is evidence that both supports7 and rejects3 8 the hypothesis that fibrinogen is associated with CVD in the elderly. However, fibrinogen has been shown to be associated with prevalent and incident CVD in various studies of middle-aged people.2 4 5 6 7 8 The nature of this association remains unclear. Plasma fibrinogen levels are responsive to pro-inflammatory, cytokine-mediated regulation39 and therefore, may reflect ongoing tissue damage associated with atherothrombosis. However, there are several potential mechanisms by which increased fibrinogen levels may cause increased atherothrombosis, including increased platelet cross-linking,40 increased fibrin formation,41 increased blood viscosity,6 42 and decreased fibrinolysis (M. Nesheim, PhD, 1995, personal communication). Smith et al43 44 have suggested that fibrinogen might be important even in the early atherogenic processes. We have recently suggested that atherothrombotic disease might upregulate fibrinogen levels and that this in turn might lead to more disease through one or more of the mechanisms mentioned above.18 45 The role of genetics in regulating fibrinogen levels is unclear; some studies suggest a prominent role,46 47 while other studies have found little evidence for genetic regulation.48 49

In simple age-adjusted analyses, fibrinogen showed extensive associations with several measures of subclinical CVD. On the basis of these analyses, we explored three disease measures derived from ultrasonographic data and one based on AAI. Use of ultrasonographic estimates of carotid atherosclerosis to approximate coronary atherothrombotic disease has been validated in several studies.50 Our finding that fibrinogen was associated with carotid artery wall thickness in the elderly, even in those in the clinical CVD–free subgroup, supports our preliminary results51 and those of others in middle-aged subjects.52 53 These associations remained even after adjustment for a variety of CVD risk factors, including smoking, age, and race, all of which are important correlates of fibrinogen. This finding is consistent with the notion that fibrinogen plays an important role in the causal pathway for atherosclerosis or that significant "inflammation" accompanies asymptomatic atherosclerosis.

In previous studies of the middle-aged, atherosclerosis severity was estimated by using measures of intimal-medial thickening that averaged several views of ICAs and CCAs.52 We separately analyzed data for the CCAs and ICAs. The association of fibrinogen with wall thickness was stronger for the ICA than for the CCA. The segment of ICA that was used for analysis is adjacent to the carotid artery bifurcation and hence, may be subject to greater rheological stress than the segment of CCA used for analysis. Any increase in blood viscosity caused by increased fibrinogen levels may have a greater effect in the ICA than in the CCA. This notion is consistent with reports that atherosclerotic disease is greater in the ICA than in the CCA.54 55 We also report a strong, independent association between fibrinogen and carotid artery stenosis, even in the clinical CVD–free subgroup. This association with stenosis, taken together with the results concerning wall thickness, supports the position that fibrinogen is an important marker of atherosclerotic disease.

The association of fibrinogen with AAI in the clinical CVD–free subgroup supports this position. AAI is believed to be a marker for generalized atherosclerosis as well as peripheral vascular disease56 57 and has been extensively evaluated in the CHS population.32 In a manner similar to the association of fibrinogen with ultrasound variables, the association of AAI with fibrinogen in this cross-sectional study may reflect the presence of an inflammatory atherosclerotic process, a causal effect of elevated fibrinogen, or both. Also, as pointed out by Ernst and Resch58 and others,6 59 the importance of the rheological effect of fibrinogen must be established. Prospective studies from the CHS should help us understand these relations more clearly.

Factor VII
Factor VII has not been previously studied in the elderly general population. Unlike fibrinogen, factor VII has not been consistently associated with CVD in the middle-aged. In one prospective study, the NPHS, factor VII was a strong, independent predictor of incident CVD.2 Also, cross-sectional data indicate that higher factor VII values are found in young adults at risk for CVD60 ; subjects with hypertriglyceridemia,9 hypercholesterolemia, or mixed hyperlipidemia61 ; male survivors of myocardial infarction11 ; and subjects at risk for thromboembolic disease.62 However, another prospective study failed to find a significant association between factor VII and incident CVD,13 and one large, cross-sectional study also failed to associate factor VII with prevalent CVD in middle-aged individuals.52

In the present study, we failed to identify any consistent association of factor VII with subclinical measures of CVD. In simple age-adjusted analyses, mean factor VII values were both higher and lower in the presence of various measures of subclinical disease. For the two measures studied in more detail, ie, LVM and CCA wall thickness, although bivariate analysis of means indicated that factor VII values were higher in the presence of disease, the regression analyses done initially without adjustment indicated negative associations. After adjustment, no significant association remained. These results lend support to the position that factor VII may not be a risk factor for CVD.

However, this position must be approached cautiously. One striking feature of factor VII is that there are many different assay "methods" available.63 We used a clot-rate, one-stage factor VII assay that utilized human-derived reagents. However, other investigators, the NPHS group in particular, used assays that employed bovine reagents, at least in part. It is well known that the origin of assay reagents and many other factors influence the factor VII assay. In fact, Miller et al64 have argued that the type of assay used may partly explain the differences between studies. However, this possibility remains to be verified.

Factor VII, unlike fibrinogen and factor VIII, is known to be associated with dietary fat intake,65 66 67 68 and dietary fat intake is a potential confounder in these analyses. However, because fasting lipid levels are only weakly associated with dietary fat, adjustment for this potential confounder is difficult. It is important to establish the role of factor VII in CVD, as factor VII levels can be modified to a greater degree than fibrinogen levels by behavioral changes, such as dietary modification.

Factor VIII
In age-adjusted analyses of the clinical CVD–free subgroup, factor VIII was significantly associated with LAD, abnormal wall motion, and AAI. The overall pattern was essentially positive (ie, higher mean values in disease) but less pronounced than that for fibrinogen (Fig 1Up). In multivariate analyses, significant associations of factor VIII were found with AAI in the full cohort, which remained even after adjustment for other risk factors, and with wall motion abnormalities in all but the adjusted clinical CVD–free subgroup model. The AAI results confirm the study described by Folsom et al52 in a middle-aged population. The wall motion results are a new finding and suggest a role for factor VIII as a key procoagulant. However, although factor VIII is a key procoagulant enzymatic cofactor, it is also an inflammation-responsive plasma protein like fibrinogen. Therefore, analysis of factor VIII as a risk factor has the same uncertainties concerning causality as does analysis of fibrinogen. There is some evidence, although less convincing than that for fibrinogen, to support the idea that factor VIII is a CVD risk factor. The NPHS group observed a positive but nonsignificant association with incident CVD,2 3 69 and we reported in preliminary analysis an association with prevalent cerebrovascular disease.51 Others have also reported associations of factor VIII with incident CVD in vascular disease patients.70 However, while the key role played by factor VIII in the assembly of the enzymatic complex responsible for factor X activation cannot be denied, support for the position that factor VIII is an important CVD risk factor in the general population must await studies of incident disease.

Summary
It is becoming well established that fibrinogen is a risk factor for CVD in middle-aged populations. There are some data that have linked hemostatic factors to subclinical CVD in the middle-aged, and the present study extends these associations to include the elderly by using a comprehensive array of subclinical CVD measures. Fibrinogen and to a lesser extent factor VIII were associated with subclinical disease in a variety of forms; the associations for factor VII were weaker and less consistent. Prospective data from the CHS will shed further light on the associations of coagulation factors with CVD in older people.


*    Selected Abbreviations and Acronyms
 
AAI = ankle-arm index
CCA = common carotid artery
CHS = Cardiovascular Health Study
CV(s) = coefficient(s) of variation
CVD = cardiovascular disease
ECG = electrocardiogram(s), electrocardiography
ICA = internal carotid artery
LAD = left atrial dimension
LVEF = left ventricular ejection fraction
LVM = left ventricular mass
NPHS = Northwick Park Heart Study


*    Acknowledgments
 
This study was supported by contracts NO1-HC-85079 through 85086 from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health, Bethesda, Md. The authors would like to thank Florence Keating, Maureen Kennedy, and Elaine Cornell for their excellent technical assistance. Also, our CHS colleagues are gratefully acknowledged: Forsyth County, North Carolina—Bowman Gray School of Medicine of Wake Forest University: Gregory L. Burke, Marie E. Cody, R. Gale Cruise, Walter H. Ettinger, Curt D. Furberg, Gerardo Heiss, H. Sidney Klopfenstein, David S. Lefkowitz, Mary F. Lyles, Maurice B. Mittelmark, Grethe S. Tell, and James F. Toole; Sacramento County, California—University of California, Davis: William Bommer, Marshall Lee, John Robbins, and Mark Schenker; Washington County, Maryland—The Johns Hopkins University: R. Nick Bryan, Trudy L. Bush, Joyce Chabot, George W. Comstock, Linda P. Fried, Pearl S. German, Joel Hill, Steve Kittner, Shiriki Kumanyika, Neil R. Powe, Thomas R. Price, Robert Rock, and Moyses Szklo; Allegheny County, Pennsylvania—University of Pittsburgh: Janet Bonk, Lewis H. Kuller, Bett McLaughlin, Peg Meyer, Anne Newman, Trevor J. Orchard, Gale H. Rutan, Richard Schulz, Vivienne E. Smith, and Sidney K. Wolfson; Echocardiography Reading Center—University of California, Irvine: Hoda Anton-Culver, Julius M. Gardin, Margaret Knoll, Tom Kurosaki, and Nathan Wong; Ultrasound Reading Center—New England Deaconess Hospital: Daniel H. O'Leary, Joseph F. Polak, and Jeffrey Potter; Central Blood Analysis Laboratory—University of Vermont: Edwin Bovill, Elaine Cornell, Paula Howard, and Russell P. Tracy; Pulmonary Function Reading Center—Mayo Clinic and Foundation: Paul Enright and Sheila Toogood; Electrocardiography Reading Center—University of Alberta, Edmonton: Paula Priest, Farida Rautaharju, and Pentti Rautaharju; Coordinating Center—University of Washington, Seattle: Nemat O. Borhani, Annette L. Fitzpatrick, Bonnie K. Lind, Richard A. Kronmal, Bruce M. Psaty, David S. Siscovick, and Patricia W. Wahl; NHLBI Project Office: Diane E. Bild, Teri A. Manolio, Peter J. Savage, and Patricia Smith.


*    Footnotes
 
Reprint requests to CHS Coordinating Center, Century Sq, Suite 2025, 1501 Fourth Ave, Seattle WA 98101.

Participating institutions and principal staff are listed in the "Acknowledgments."

Received April 14, 1995; accepted July 3, 1995.


*    References
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 *References
 

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