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Arteriosclerosis, Thrombosis, and Vascular Biology. 1997;17:2167-2176

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(Arteriosclerosis, Thrombosis, and Vascular Biology. 1997;17:2167-2176.)
© 1997 American Heart Association, Inc.

Articles

Lifetime Smoking Exposure Affects the Association of C-Reactive Protein with Cardiovascular Disease Risk Factors and Subclinical Disease in Healthy Elderly Subjects

Russell P. Tracy; Bruce M. Psaty; Elizabeth Macy; Edwin G. Bovill; Mary Cushman; Elaine S. Cornell; ; Lewis H. Kuller

From the Departments of Pathology and Biochemistry (R.P.T.), Pathology (E.M., E.G.B., E.S.C.), Medicine and Pathology (M.C.), University of Vermont, Colchester, the Departments of Epidemiology and Health Services and Medicine (B.M.P.), University of Washington, Seattle, and the Departments of Epidemiology and Medicine (L.H.K.), University of Pittsburgh, Penn.

Correspondence and reprint requests to Russell P. Tracy, University of Vermont, Aquatec Bldg, T205, 55A S. Park Drive, Colchester, VT 05446. Email: rtracy{at}salus.uvm.edu


*    Abstract
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Abstract Blood levels of C-reactive protein (CRP), a marker of inflammation, are related to cardiovascular disease risk. To determine cross-sectional correlates in the elderly, we measured CRP in 400 men and women older than 65 years and free of clinical cardiovascular disease at baseline as part of the Cardiovascular Health Study. Only 2% of the values were greater than 10 mg/L, the cut-point usually used to identify inflammation. CRP levels appeared tightly regulated, since there were strong bivariate correlations between CRP and the following: inflammation-sensitive proteins such as fibrinogen (r=.52); measures of fibrinolysis such as plasmin-antiplasmin complex (r=.23); pack-years of smoking (r=.30); and body mass index (r=.24; all P values<=.001). The association with pack-years was independent of the length of time since cessation of smoking. CRP levels were also associated with coagulation factors VIIc, IXc, and Xc; HDL cholesterol (negative) and triglyceride; diabetes status; diuretic use; ECG abnormalities; and level of exercise. Because of effect modification, two multiple linear regression prediction models were developed for CRP, one each for never smokers and ever smokers. An a priori physiologic model was used to guide these analyses, which disallowed the use of other inflammation-sensitive variables such as fibrinogen. In never smokers, the independent predictors were body mass index (+), diabetes status (+), plasmin-antiplasmin complex (+), and the presence of ECG abnormalities (+); this model predicted 15% of the CRP population variance. In ever smokers, the predictors were body mass index (+), plasmin-antiplasmin complex (+), pack-years of smoking (+), HDL cholesterol (-), and ankle-arm blood pressure index (-); this model predicted 42% of the population variance. We conclude that levels of CRP in the healthy elderly are tightly regulated and reflect lifetime exposure to smoking as well as level of obesity, ongoing level of fibrinolysis, diabetes status, and level of subclinical atherothrombotic disease. Moreover, exposure to smoking affects the relation of CRP to these other factors.


Key Words: atherosclerosis • thrombosis • fibrinolysis • inflammation • acute-phase proteins


*    Introduction
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 *Introduction
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It is becoming apparent that inflammation is associated with atherosclerosis and the resulting thrombosis (atherothrombosis). This association with CVD is complex in nature. There are data to link inflammation with the formation of very early lesions, such as fatty streaks,1 the attachment of monocytes to damaged endothelium,2 3 and the active thrombotic process that accompanies plaque rupture.4 5 However, although it seems likely that some aspects of the inflammation may contribute to the atherothrombotic process, there is also evidence that some inflammatory responses may dampen it.6

The serum level of CRP is used clinically as an indicator of inflammation.7 When used in this way, relatively high values have the greatest diagnostic utility, since the combination of a relatively small within-subject variance and relatively large between-subjects variance limits the usefulness of healthy reference ranges in detecting early low-level inflammation,8 9 and the changes in CRP after significant acute inflammation are generally large, up to several hundredfold.7

Elevations in CRP have been shown to be positively associated with acute MI and sudden cardiac-related death in patients with unstable angina, linking inflammation and acute coronary events.10 11 12 Recently, we (L.K., R.T.) have extended these studies to show that in middle-aged men13 and elderly women14 free of prevalent CVD, higher CRP levels are associated with incident CVD events. In the study of middle-aged men, the association of CRP with CVD events, extending over 5 to 17 years of follow-up, was primarily seen in those men who were smokers; and in one previous study, smoking was associated with higher CRP levels.15 However, to date there have been no population-based studies examining the associations of CRP with other variables known to be related to CVD risk.

In the current study, we measured CRP in 400 subjects free of clinically recognized CVD, a subset of a well-defined, healthy elderly cohort in the CHS.16 We examined cross-sectional associations of CRP with other CVD risk factors and measures of prevalent subclinical disease such as carotid atherosclerosis defined by ultrasonography.


*    Methods
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Cardiovascular Health Study
The CHS has been described in detail.16 After the study was approved by all relevant institutional review boards, participants were recruited with informed consent, and examinations were performed from May 1989 to June 1990. The four CHS field centers were in Forsyth County, NC; Washington County, Md; Sacramento County, Calif; and, Pittsburgh, Penn. Participants were identified by random sampling from Medicare eligibility lists.17 For the present study, we obtained a sample of 400 CHS participants free of prevalent clinical CVD at baseline. A stratified random sample was selected, with 40 participants in each of 10 sex-age groups. Some analyses had slightly fewer than 400 data points, since data on every variable was not available on every participant.

The baseline examination consisted of an interview, a physical examination with several blood measurements, and an assessment of CVD status. Information was collected on blood pressure, anthropomorphic characteristics, and medical and lifestyle histories including a comprehensive assessment of medications. Blood samples were analyzed at the central laboratory, the Laboratory for Clinical Biochemistry Research at the University of Vermont, Burlington Vt. The general laboratory design and the quality assurance procedures and results have been published.18 Other measurements include AAI,19 carotid ultrasonography,20 echocardiography21 and resting 12-lead ECG.

Definitions
The definition of borderline hypertension was a random zero seated systolic blood pressure (average of five measurements) between 140 and 159 mm Hg or, if systolic was <140 mm Hg, an average diastolic between 90 and 94 mm Hg. Hypertension was defined as an average systolic >=160 mm Hg or, if the systolic was <160 mm Hg, an average diastolic >=95 mm Hg, or the use of hypertension medications. Abnormal glucose tolerance was defined as impaired (fasting glucose <140 mg/dL and 2-hour post-glucose challenge between 140 and 199 mg/dL) or diabetes (fasting glucose >=140 mg/dL or 2-hour post-glucose challenge >=200 mg/dL, or self-reported diabetes, or if the participant was taking either insulin or oral hypoglycemic medication). Smoking was defined as never, former, or current; no restrictions were placed on the time since cessation of smoking for the former smoker category. Responses to years since cessation of smoking were based on the participants' recall. Obesity was defined as BMI (in units of kg/m2) over 130% of the ideal for sex and age. Exercise level, classified as none, low, moderate and high, was based on questionnaire responses.16 Sitting systolic blood pressure was used to calculate the AAI, with a value <0.9 considered abnormal.19 Abnormal ECG results and the use of the ECG to define the left ventricular mass have been described.22 Ultrasound methods and quality control are described in detail elsewhere.20

Clinical coronary heart disease at entry to the study was defined by the following: (1) self-reported myocardial infarction, angina, or use of nitroglycerin; (2) definite myocardial infarction by resting ECG using the Minnesota code23 ; or (3) self-reported history of coronary angioplasty or coronary artery bypass graft. Cerebrovascular disease was defined as self-reported stroke, transient ischemic attack, or carotid endarterectomy. Peripheral vascular disease was defined as self-reported intermittent claudication or history of peripheral artery angioplasty or bypass surgery.

Blood Measurements
We (M.C., E.S.C., E.G.B., R.T.) have described blood collection in detail.18 Briefly, blood was collected after fasting with minimal tourniquet time. Along with serum and both citrated and EDTA plasma, we collected blood in a special coagulation collection tube (SCAT-1; Haematologic Technologies, Inc., Essex Junction, Vt) that contained, at final concentration in blood, 4.5 mmol/L of EDTA, 150 KIU/mL of aprotinin, and 20 mmol/L of D-Phe-Pro-Arg chloromethyl ketone.24 CRP was measured by in-house competitive immunoassay (antibodies and antigens from Calbiochem, La Jolla, Calif) with an interassay CV (all subsequent CVs are also interassay CVs) of 8.9%.25 {alpha}1-Acid glycoprotein was also measured with an in-house immunoassay with reagents from Calbiochem, using SCAT-1 plasma, with a CV of 7.9%. Lipid assays (under Centers for Disease Control and Prevention certification) and general chemistries were performed using EDTA plasma and serum respectively, as previously reported.18 Lipoprotein(a) was measured in SCAT-1 plasma with a specific immunoassay26 (reagents kindly donated by Dr. Wai-Le Wong of Genentech), with a CV of 7.5%. Fibrinogen, factor VII, and factor VIII were measured using citrate plasma as previously described.18 27 Factor IX and factor X were measured in citrate plasma using one-stage clot-rate assays and the Diagnostica Stago ST4 instrument, according to the manufacturer's recommendations,28 with CVs of 5.8 and 4.7%, respectively. Tissue-type plasminogen activator, PAI-1, PAP, tissue-type plasminogen activator/PAI-1 complex, and the fibrin fragment D-dimer were measured by enzyme-linked immunoabsorbent assays, with reagents kindly provided by Drs. D. Collen and P. Declerk, Leuven, Belgium.29 30 31 32 33 34 The CVs for control samples in these assays were, respectively: 5.2, 8.4, 3.0, 14.3, and 12.7%. With the exception of PAI-1, which was measured in citrate plasma,35 these assays were performed with SCAT-1 plasma. Plasminogen36 and antithrombin III were measured by rate chromogenic assays in citrate plasma, with CVs of 3.6 and 5.0%, respectively. Protein C and protein S were measured in SCAT-1 plasma using in-house immunoassays, with CVs of 2.0 and 9.9%, respectively.37 38 F1-2 was measured with an enzyme-linked immunosorbent assay (Baxter-Dade, Miami, Fla) in SCAT-1 plasma with a CV of 9.3%. This assay has excellent correlation with another F1-2 assay (Berhing Diagnostics, Inc., Westwood, Mass), with a Pearson coefficient of 0.92 (P<.0001). FPA was measured on fibrinogen-free SCAT-1 plasma by a double antibody competition radioimmunoassay (Byk-Sangtec Diagnostica, Dietzenbach, Germany). Fibrinogen was extracted with bentonite.39 The postextraction CV was 8.4%; the total CV for the assay, including extraction, was approximately 25%.39 Despite the relatively high CV, the FPA assay remains the single best choice for estimating thrombin activity. Recent studies indicate that FPA levels are useful in epidemiological settings.40 Complete blood counts were performed at a designated local laboratory near each field center site.

Statistical Analyses
SPSS for Windows41 was used for all analyses. The data set used was distributed version 1.0, from the CHS Coordinating Center. The distribution of CRP in our sample was determined to be nonnormal. A natural log transformation achieved normality, so ln-CRP values were used for statistical analyses. Bivariate associations of ln-CRP with CVD risk factors and other biochemical measurements were estimated using the Pearson correlation coefficient or, for categorical variables, analysis of variance. The significance level was set at P<=.01. Since there were strong interactions between smoking status and a number of other variables, all analyses were done on the full group as well as on subgroups stratified on smoking status. Due to the small number of current smokers (n=33), we combined current smokers and former smokers (n=147) into a single group of ever smokers. We compared known CVD risk factors between former smokers and current smokers; the only variable that was significantly different was BMI: former smokers, 26.3; current smokers, 23.5; P=.001. We also ran our final multivariate model in both the ever smoker and the former smoker groups. Formal testing for effect modification was done using the SPSS MANOVA feature, which reports a significance for the selected interaction terms.

Step-wise multivariate linear regression models were developed to predict ln-CRP as tests of the independence of associations. P<=.05 was used to assess significance. We started with general variables such as age and sex, then added indices of disease and lipids, and then thrombosis and fibrinolysis measures. Fibrinolysis and thrombosis markers such as PAP levels and fibrinopeptide A levels were considered for inclusion into the models since we propose that thrombosis and subsequent fibrinolysis are most likely in the causal pathway; however, static levels of coagulation factors, eg, fibrinogen, and certain other variables were not appropriate for the model since they appear to be coregulated, at least to a certain extent, with CRP through mediators of inflammation. Diabetes status was used in the models instead of fasting or 2-hour glucose or insulin because preliminary analyses showed stronger associations with CRP for diabetes status. Pack-years was the variable used to represent smoking in the regression models. Since approximately half of the population has a value of 0 for pack-years (never smokers), we ended up with two "final models": one for never smokers (without pack-years as an independent variable) and one for ever smokers.

Age and sex were not significant in either model when the models were developed as described. As a final step, we forced age and sex into the final models since many variables were significantly associated with age and sex in bivariate analyses.

We calculated the effect ratio for each variable that remained in the final models, as described previously.42 The effect ratio is the percentage of an SD change in ln-CRP "explained" by a 1-SD change in continuous predictor variables or a one-category change in categorical variables. In this way, the effect sizes of the variables may be more easily compared.


*    Results
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Distributions
The characteristics of this sample of the CHS cohort have been published.43 The average age of both the men and women was 77 years. Although free of clinical CVD at baseline, more than 25% of the men and more than 15% of the women had major ECG abnormalities. More than 35% of the men and more than 30% of the women had carotid stenosis greater than 24%. Approximately 14% of the women used hormone replacement therapy. Only about 10% of the men and 7% of the women were current smokers, but almost 50% of the men and a quarter of the women were former smokers.

The distributions of CRP for men and women (Fig 1Down) are similar, skewed high and characterized by relatively few individuals (four men, five women) with values greater than 10 mg/L, the value commonly used to represent clinically relevant inflammation.44 The 5 to 95 percentile range for men was 0.26 to 5.75 mg/L, and 0.21 to 7.26 mg/L for women. An association of CRP values with smoking status has been suggested,15 and Fig 1Down illustrates the distributions when men and women are combined and the values stratified on smoking status, ie, ever smokers and never smokers. Again, the distributions are very similar, with 5 to 95 percentile ranges of 0.26 to 7.54 mg/L and 0.19 to 6.70 mg/L for ever smokers and never smokers, respectively.



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  		Figure 1. Distributions of CRP in a healthy elderly population. Clockwise, from upper right left: women, men, ever smokers, never smokers. Relatively few individuals have CRP values >10 mg/L, the usually accepted cut-off for inflammation values in parentheses.

Associations with CVD Risk Factors
Table 1Down illustrates correlations between ln-CRP and other continuous variables, and Table 2Down illustrates associations with categorical variables. Men and women had similar values. Age also was not associated with ln-CRP. Although smoking status per se was not significantly associated with ln-CRP, there was a relatively strong association of ln-CRP and pack-years among ever smokers. In a separate analysis, there were no significant differences in ln-CRP levels between never, former, and current smokers; however, the number of current smokers was small.


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  		Table 1. Correlations Between ln-CRP and Continuous Variables in Healthy Elderly Persons Free of Clinical CVD


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  		Table 2. Unadjusted Mean Values for CRP, Stratified on Categorical Variable Status, in Healthy Elderly Persons Free of Clinical CVD

Pack-years and years since cessation were highly negatively correlated (R=-.49). In a multiple regression model, pack-years was significant whereas years since cessation was not. A formal test of interaction between pack-years and years since cessation was not significant (P=.17).

To further evaluate the relationship of ln-CRP to smoking, we stratified our sample of former smokers based on tertiles of years since cessation of smoking, then within each stratum, stratified on tertiles of pack-years of smoking and calculated mean values for ln-CRP. The results are shown in Fig 2Down. Although the number of subjects in each cell is small, the relationship of ln-CRP to number of pack-years within each stratum of years since cessation appears consistent. Taken all together, our data support the hypothesis that CRP is primarily related to lifetime exposure of smoking (pack-years) and not to years since cessation of smoking.



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  		Figure 2. Mean values for Ln-CRP, stratified by pack-years of smoking and years since cessation of smoking. We first stratified the CHS sample based on tertiles of years since cessation of smoking. The mid-point values for the three strata are shown: 10, 22 and 41 years. We next stratified on tertiles of pack-years of smoking, with each of the first strata. The mid-point values are shown for each of the resulting nine strata. The numbers above each bar are the number of values within each stratum.

To illustrate the interaction of smoking with other variables, mean values for CRP (and for ln-CRP, data not shown) were actually greater in women than in men among never smokers, whereas the opposite was true among ever smokers (Fig 3Down, P=.04 for interaction term). A similar weak interaction (P=.08) existed for the relationship of CRP to obesity (Table 2Up and Fig 3Down): The significantly greater CRP values in obese subjects of the full group was primarily due to greater values in the obese never smokers. However, the bivariate correlation of ln-CRP to BMI was the same in ever smokers as in never smokers (Table 1Up).



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  		Figure 3. Mean values for CRP in sex, diabetes, and obesity subgroups, stratified by smoking status. The dark bars indicate never smokers, and the open bars indicate ever smokers. Normal, normal glucose tolerance; IGT, impaired glucose tolerance; DM, diabetes mellitus. The significance for the interaction terms for sex, diabetes, and obesity were P=.04, P=.006, and P=.08, respectively.

The association of CRP to diabetes status (Fig 3Up and Table 2Up) or serum glucose (both fasting and after a 2-hour oral glucose tolerance test; Table 1Up) was also strongly affected by smoking status, with significant associations observed only in the never smokers (P=.006 for interaction term for diabetes status). ln-CRP was not associated with cholesterol (Table 1Up) or LDL cholesterol (data not shown) but was associated with HDL cholesterol (-) and, weakly, with fasting triglyceride (+).

Associations with Other Variables
ln-CRP showed several strong positive associations with procoagulant factors (Table 1Up) including factor VIIc, factor VIIIc, factor IXc, and factor Xc. With the exception of factor VIIc, these associations were approximately the same in the never smokers and ever smokers. Factor VIIc was more strongly associated with CRP in the never smokers. Several measures of fibrinolysis were positively correlated with ln-CRP. In particular, the associations with t-PA, PAP (a measure of plasmin production), and the fibrin fragment D-dimer (plasmin activity) were stronger in ever smokers than in never smokers (P=.04 for interaction term for PAP).

Although only nine of approximately 400 subjects (<3%) had CRP values greater than the generally accepted cutoff for inflammation, ln-CRP showed significant correlations to other known markers of inflammation, including fibrinogen, {alpha}1-acid glycoprotein, albumin (-), and white cell count. All of these associations were stronger in the ever smoker subgroup than in the never smoker group. ln-CRP was not associated with aspirin or nonsteroidal antiinflammatory drug use, nor with postmenopausal estrogen use in women. However, there was a significant association with diuretic use (-).

Associations with Subclinical Disease Variables
ln-CRP was not significantly associated with left ventricle ejection fraction, left ventricular mass, or carotid atherosclerosis in this healthy population. However, in ever smokers, ln-CRP was associated with AAI as a measure of peripheral vascular disease (Table 1Up) and relatively weakly associated with ECG abnormalities (minor) in never smokers.

Multivariate Models Predicting ln-CRP
We began the step-wise multivariate model for never smokers with age and gender. After BMI and diabetes status entered the model, neither age nor gender was significant. The presence of minor ECG abnormalities was included, but not HDL or triglycerides. PAP entered the model as a measure of fibrinolysis. Other measures of fibrinolysis, eg, the fibrin fragment D-dimer, could be used in place of PAP but with less statistical significance. Our final model for never smokers contained BMI, diabetes, minor ECG abnormalities, and PAP (Table 3Down, Fig 4Down).


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  		Table 3. Multivariate Linear Regression Models Predicting Ln-CRP



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  		Figure 4. Effect ratios calculated from the final multiple linear regression models predicting ln-CRP. The effect ratio is the fraction of an SD change in ln-CRP "explained" by a 1-SD change in a continuous predictor variable, or a one-category change in a categorical variable, multiplied by 100%. Data are represented as the calculated effect ratio ±95% confidence intervals. PAP, plasmin-antiplasmin complex; DM, glucose tolerance status as either normal, impaired glucose tolerance, or diabetic; ECG, presence or absence of minor ECG abnormalities; AAI, ankle-arm blood pressure index. X-N, variables present in the final model for never smokers; X-F+C, variables present in the final model for former plus current (ever) smokers.

The model for ever smokers began with age, gender, pack-years of smoking, and BMI, with BMI, pack-years, and age remaining in the model at this stage. With pack-years in the model, years since cessation of smoking was not significant. Diabetes did not enter the model, but AAI did. ln-FPA entered the model but became nonsignificant, along with age, as soon as PAP entered. (In a separate analysis, age and PAP were significantly associated with a Pearson coefficient of .29; P<=.0001.) HDL also entered this model, but triglycerides, diuretic use, uric acid, creatinine, and forced expiratory volume in 1 second, FEV1 did not. Our final model contained BMI, pack-years, AAI, PAP, and HDL (Table 3Up). In Fig 4Up, it can be seen that PAP is a significantly stronger predictor in ever smokers compared with never smokers, and that of the final predictors in ever smokers, PAP explains the greatest proportion of the ln-CRP distribution. When run with former smokers only, the model was essentially unchanged except for a slight decrease in the coefficient and significance of AAI (new P=.11).

None of the predictor variables became nonsignificant when age and sex were forced into the final models. In the model for never smokers, age was significantly associated with ln-CRP (-) when entered this way, and the overall R2 was increased slightly to .185. In the model for ever smokers, neither age nor sex was significant, and there was virtually no change in the overall R2.


*    Discussion
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 *Discussion
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In general, elevated levels of CRP are useful in detecting and monitoring infections, postoperative complications, and the effectiveness of treatment in the course of various diseases, when inflammation is in some way involved.7 44 45 46 The cell biology of CRP has been established, and IL-6 appears to play a major role in regulating the production of CRP.47 It has been reported that other proinflammatory cytokines may play important roles as well.48 Along with immunological activity, alternative pathways for IL-6-mediated CRP production may include fibrinolytic activity, since fibrin degradation products can stimulate monocyte production of IL-6.49 50

Recently, CRP levels have been used in population studies of CVD. The European Concerted Action on Thrombosis and Disability (ECAT) Angina Pectoris Study Group reported that in subjects with angina pectoris, baseline CRP correlated with several markers of coagulation and fibrinolysis activity as well as white cell count, suggesting an association of a low grade inflammation with atherothrombosis.12 On follow-up, the baseline CRP level was positively associated with MI and sudden cardiac-related death. Liuzzo et al measured CRP and serum amyloid A (another marker of inflammation) in subjects with chronic stable angina, unstable angina, and MI on presentation at the hospital.11 The CRP levels were highest in the subjects who went on to develop MI, followed by those who had only unstable angina. We have recently reported that CRP levels are predictive of incident CVD events in middle-aged men who are free of prevalent clinical CVD at baseline13 and in elderly women who have subclinical CVD.51 Therefore, it is important to understand the cross-sectional correlates of CRP.

Strengths of the current study include the removal of prevalent clinical CVD as a potential confounder; a carefully designed parent study with appropriate blood collection and storage procedures; a comprehensive battery of measurements related to lipids, coagulation, and fibrinolysis; and assessment of independence through multivariate analyses. The major weaknesses of this study are its cross-sectional nature and its limited generalizability due to selection criteria of the parent study and this substudy.

Distribution of CRP Levels
The distribution of CRP in this healthy population of elderly subjects reflected the almost complete absence of clinical inflammation in this group, with very few CRP values greater than 10 mg/L (9/399 or 2% overall). We observed no significant association with age. The strong associations with other inflammation-sensitive proteins, eg, fibrinogen, provide evidence that CRP levels within the healthy reference range are tightly regulated, most likely by IL-6 levels.47 We25 (E.M., R.P.T.) and others52 have recently analyzed CRP biovariability and found it to be characterized by relatively small within-person variability and relatively large between-persons variability, in the absence of clinically apparent inflammation.

Relation of CRP to Smoking
Despite the powerful effect modification of smoking status, there was no significant association of CRP values with smoking status itself, although CRP was strongly related to lifetime smoking exposure. Although CRP was associated with years since cessation of smoking, this association was not significant when the category pack-years was included in a model. In addition, in our stratified analysis, it appeared that even when the individuals had stopped smoking for 30 years or more, CRP was still associated with pack-years. These findings suggest the hypothesis that if smoking is in the causal pathway for CRP, some smoking effects may persist over long periods of time.

When looking at correlates, we examined smoking for effect modifications since we had seen a large interaction of smoking with incident events in middle-aged men.13 Smoking status had a significant effect on the associations of gender, obesity, and diabetes status with CRP, consistent with an hypothesis that smoking causes a chronic, increased inflammatory response, especially in the absence of other mitigating factors. In support of this, we have recently observed very high values for the inflammation-sensitive protein fibrinogen in normal and diabetic North American Indians, with the strongest correlate being albuminuria (R.T. et al, manuscript in review). Interestingly, smoking did not have a strong association with fibrinogen, and fibrinogen was not an independent risk factor for prevalent disease in these.53

The mechanism for the hypothesized long-lasting inflammatory effect of smoking is unknown but could be linked to the development of atherothrombotic plaque at sites of vessel wall damage. This suggestion is supported by the associations of CRP with several measures of subclinical CVD in the current study and the recent reports linking CVD with inflammation-associated cell adhesion molecules and selectins.54 55 56 57 58

We were able to develop a model in ever smokers that explained almost three times as much of the population variance as in never smokers, even though the distributions of CRP in these two groups were very similar (Fig 1Up). The effect of including pack-years made up a large share of this difference. In addition, the effect size of the fibrinolysis variable was much larger in the ever smokers compared with the never smokers. This is consistent with our finding in bivariate analysis of stronger correlations of both PAP and the fibrin fragment D-dimer with CRP in ever smokers, and it suggests that damage associated with smoking may have long-term consequences with respect to thrombotic activity and concomitant plasmin generation.

The relatively strong association of BMI and CRP (Tables 1Up and 3Up) was unexpected and is unexplained at this time. However, we found CRP associated with BMI in another study,59 and in the Women's Healthy Lifestyle Project, we observed that weight loss was associated with a decrease in CRP (E. Meilahn, personal communication, 1996). Recently, we observed that moderate weight loss, independent of diet changes, also was associated with a decrease in PAI-1, another acute-phase protein.60 The mechanism is unclear but may be related to diet- and/or exercise-mediated changes in triglyceride levels since in this study CRP was correlated to triglycerides, and we have observed similar correlations for fibrinogen43 and PAI-1 (M.C., manuscript in preparation) in CHS.

CRP was strongly associated with a variety of measures of procoagulant activity and fibrinolysis in both bivariate and multivariate models. We believe that these associations fall into two categories: (1) associations that are the result of the inflammation caused by underlying subclinical atherothrombotic disease, including those with ambient levels of acute-phase factors such as fibrinogen, factor VIIIc, and PAI-1; (2) associations between CRP and factors that reflect an ongoing process such as thrombin generation (prothrombin fragment 1-2) or plasmin generation (PAP). We hypothesize that these processes contribute to the inflammation of CVD, possibly through monocyte IL-6 production in the presence of fibrin degradation products, which are the inevitable result of coagulation and fibrinolysis.50 In fact, CRP itself may be procoagulant, through its ability to stimulate monocyte tissue factor expression.61

In conclusion, levels of CRP in the healthy elderly indicate little clinical inflammation. However, these levels appear to be tightly regulated, with relatively strong associations with other inflammation-sensitive proteins, eg, fibrinogen, as well as BMI, fibrinolytic activity, glucose tolerance status, and some measures of subclinical CVD. Lifetime exposure to smoking, even in those who have stopped smoking, is strongly associated with CRP and affects the association of CRP with other variables. Our data suggest that some effects of smoking may persist for many years after cessation.


*    Selected Abbreviations and Acronyms
 
AAI = ankle-arm blood pressure index
BMI = body mass index
CHS = Cardiovascular Health Study
CRP = C-reactive protein
CV = coefficient of variation
CVD = cardiovascular disease
FPA = fibrinopeptide A
IL-6 = interleukin-6
ln-CRP = natural log-transformed CRP
MI = myocardial infarction
PAI-1 = plasminogen activator inhibitor
PAP = plasmin-antiplasmin complex


*    Acknowledgments
 
This work was supported by grant RO1 HL-46696 (R.P.T.) from the National Heart, Lung, and Blood Institute (NHLBI) and by NHLBI contracts NO1-HC-85079 through -85086. Dr. Cushman was supported by US Public Health Service training grant T3207594. We thank Drs. Collen and DeClerck of Leuven, Belgium, for their kind gift of reagents for the fibrinolysis immunoassays, and Dr. Wai-Le Wong of Genentech (South San Francisco, Calif) for reagents to assay lipoprotein(a). We also thank the investigators and staff of the Cardiovascular Health Study: Forsyth County, NC-Bowman Gray School of Medicine of Wake Forest University: Gregory L. Burke, Alan Elster, Walter H. Ettinger, Curt D. Furberg, Edward Haponik, Gerardo Heiss, Dalane Kitzman, H. Sidney Klopfenstein, Margie Lamb, David S. Lefkowitz, Mary F. Lyles, Maurice B. Mittelmark, Cathy Nunn, Ward Riley, Grethe S. Tell, James F. Toole, and Beverly Tucker; Bowman Gray School of Medicine EKG Reading Center: Kris Calhoun, Harry Calhoun, Farida Rautaharju, Pentti Rautaharju, and Loralee Robertson; Sacramento County, Calif—University of California, Davis: William Bommer, Charles Bernick, Andrew Duxbury, Mary Haan, Calvin Hirsch, Paul Kellerman, Lawrence Laslett, Marshall Lee, Virginia Poirier, John Robbins, Marc Schenker, and Nemat Borhani; Washington County, Md—The Johns Hopkins University: M. Jan Busby-Whitehead, Joyce Chabot, George W. Comstock, Linda P. Fried, Joel G. Hill, Steven J. Kittner, Shiriki Kumanyika, David Levine, Joao A. Lima, Neil R. Powe, Thomas R. Price, Jeff Williamson, Moyses Szklo, and Melvyn Tockman; Washington County, Md—The Johns Hopkins University MRI Reading Center: R. Nick Bryan, Carolyn C. Meltzer, Douglas Fellows, Melanie Hawkins, Patrice Holtz, Michael Kraut, Grace Lee, Larry Schertz, Earl P. Steinberg, Scott Wells, Linda Wilkins, and Nancy C. Yue; Allegheny County, Penn—University of Pittsburgh: Diane G. Ives, Charles A. Jungreis, Laurie Knepper, Lewis H. Kuller, Elaine Meilahn, Peg Meyer, Roberta Moyer, Anne Newman, Richard Schulz, Vivienne E. Smith, and Sidney K. Wolfson; University of California, Irvine, Echocardiography Reading Center (Baseline): Hoda Anton-Culver, Julius M. Gardin, Margaret Knoll, Tom Kurosaki, and Nathan Wong; Washington, DC—Georgetown Medical Center Echocardiography Reading Center (Follow-Up): John Gottdiener, Eva Hausner, Stephen Kraus, Judy Gay, Sue Livengood, Mary Ann Yohe, and Retha Webb; Geisinger Medical Center Ultrasound Reading Center: Daniel H. O'Leary, Joseph F. Polak, and Laurie Funk; University of Arizona, Tucson, Respiratory Sciences: Paul Enright; University of Washington, Seattle, Coordinating Center: Alice Arnold, Annette L. Fitzpatrick, Bonnie K. Lind, Richard A. Kronmal, Bruce M. Psaty, David S. Siscovick, Lynn Shemanski, Lloyd Fisher, Will Longstreth, Patricia W. Wahl, David Yanez, Paula Diehr, and Maryann McBurnie; National Heart, Lung, and Blood Institute Project Office, Bethesda, Md: Diane E. Bild, Teri A. Manolio, Peter J. Savage, Patricia Smith, and Rachel Solomon.

Received August 23, 1996; accepted March 5, 1997.


*    References
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 *References
 

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