American Journal of Epidemiology Vol. 153, No. 3 : 242-250
Copyright © 2001 by The Johns Hopkins University School of Hygiene and Public Health
ORIGINAL CONTRIBUTIONS |
Association between Physical Activity and Markers of Inflammation in a Healthy Elderly Population
1 Department of Pathology, College of Medicine, University of Vermont, Burlington, VT.
2 Department of Medicine, College of Medicine, University of Vermont, Burlington, VT.
3 Department of Public Health Sciences, Bowman Gray School of Medicine, Wake Forest University, Winston-Salem, NC.
4 Department of Radiology, Harvard Medical School, Boston, MA.
5 Department of Biochemistry, College of Medicine, University of Vermont, Burlington, VT.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Higher levels of physical activity are associated with lower risk of cardiovascular disease. There is growing evidence that the development of the atherosclerotic plaque is associated with inflammation. In this study, the authors investigated the cross-sectional association between physical activity and markers of inflammation in a healthy elderly population. Data obtained in 1989–1990 and 1992–1993 from the Cardiovascular Health Study, a cohort of 5,888 men and women aged
65 years, were analyzed. Concentrations of the inflammation markers–C-reactive protein, fibrinogen, Factor VIII activity, white blood cells, and albumin–were compared cross-sectionally by quartile of self-reported physical activity. Compared with persons in the lowest quartile, those in the highest quartile of physical activity had 19%, 6%, 4%, and 3% lower concentrations of C-reactive protein, white blood cells, fibrinogen, and Factor VIII activity, respectively, after adjustment for gender, the presence of cardiovascular disease, age, race, smoking, body mass index, diabetes, and hypertension. Multivariate regression models suggested that the association of higher levels of physical activity with lower levels of inflammation markers may be mediated by body mass index and glucose. There was no association between physical activity and albumin. Higher levels of physical activity were associated with lower concentrations of four out of five inflammation markers in this elderly cohort. These data suggest that increased exercise is associated with reduced inflammation. Prospective studies will be required for verification of these findings.
atherosclerosis; cardiovascular diseases; C-reactive protein; exercise; Factor VIII; fibrinogen; inflammation; leukocyte count
Abbreviations: CHS, Cardiovascular Health Study; CV, coefficient of variation.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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There is increasing evidence that the development of the atherosclerotic plaque is associated with an inflammatory process (1
–4), and that measurement of this inflammation has predictive value in determining risk for future thrombotic events. A recent meta-analysis revealed that there were moderate but statistically significant associations between four markers of inflammation–C-reactive protein, fibrinogen, albumin, and white blood cells–and coronary heart disease (5). High levels of Factor VIII activity have also been shown to be associated with atherothrombotic events in comparison with control levels (6, 7), and Factor VIII is a known acute-phase reactant (8). Ridker et al. (9) found that aspirin use decreased risk of myocardial infarction and ischemic stroke in apparently healthy men, primarily in those with the highest levels of C-reactive protein. This suggests that even a moderate reduction in inflammation may be protective.
There is evidence that physical activity may modify the inflammatory process. Cross-sectional studies of physical activity and physical fitness have shown inverse associations with levels of fibrinogen (10–14). Intervention studies have demonstrated reductions in fibrinogen (15–17) and C-reactive protein (18) when exercise groups are compared with controls, although the numbers of subjects in these latter studies have been small and few elderly subjects have been studied.
The mechanism through which physical activity may be associated with lower levels of inflammation markers is unknown. Higher levels of C-reactive protein have also been associated with obesity (19) and insulin resistance (20). Physical activity is associated with lesser degrees of central obesity (21, 22) and insulin resistance (23–25). Taking these findings together, one could speculate that physical activity may be associated with lower levels of inflammation through its inverse association with central obesity and increasing insulin resistance.
In this study, we measured the association of self-reported physical activity with several markers of inflammation in a population-based elderly cohort, using data from the Cardiovascular Health Study (CHS). Previous cross-sectional analysis of a subgroup of CHS participants with subclinical cardiovascular disease found inverse associations between exercise and fibrinogen levels in males and females and between exercise and Factor VIII activity in males (26). The markers of inflammation studied in this analysis were C-reactive protein, fibrinogen, Factor VIII activity, white blood cell count, and albumin.
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MATERIALS AND METHODS |
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Study sample
A description of the population-based design of the CHS and recruitment has been previously published (27
). The original cohort was recruited in 1989–1990 from four US communities using a defined sample of Medicare beneficiaries aged 65 years. It consisted of 5,201 participants (2,962 females and 2,239 males). An additional group made up predominantly of African Americans was added to the cohort in 1992–1993 (431 females and 256 males) (28). Eligible participants included all persons living in the household of someone sampled from Health Care Financing Administration eligibility lists who 1) were aged 65 years or older; 2) were not institutionalized; 3) expected to remain in the area for 3 years; and 4) were able to give informed consent and did not require a proxy respondent. Participants were eligible for the CHS regardless of whether they had a history of cardiovascular disease. Excluded persons included those who were wheelchair-bound and those who were receiving hospice care or treatment for cancer.
In this study, we used the full cohort for analysis (n = 5,888). Participants were classified from the baseline data as having either clinical cardiovascular disease (n = 2,051) or no cardiovascular disease (n = 3,837). Clinical disease was defined as previously described (29), with the addition of participants diagnosed with atrial fibrillation or myocardial infarction by electrocardiogram.
Baseline examination
All data were obtained from the baseline examination, which consisted of a home interview and a clinic examination. The baseline period for the original cohort was June 1989–June 1990; for the new cohort, it was June 1992–June 1993. During the home interview, information was collected on medical history, medication use, and physical activity. Information was also obtained on impairment of physical functioning. The clinic examination included a fasting blood sample, seated blood pressure and resting heart rate measurements, anthropometric measurements, assessment of ankle-brachial systolic blood pressure index, and a resting electrocardiogram. Details on the baseline examination procedures have been provided elsewhere (27).
Measurement of variables
Assessment of leisure time physical activity in the CHS has been described previously (26). During the baseline examination, participants were asked whether they had engaged in any of 15 leisure time activities in the prior 2 weeks. Participants were asked about their participation in the following activities: swimming, hiking, aerobics, tennis, jogging, racquetball, walking, gardening, mowing, raking, golfing, bicycling, dancing, calisthenics, and riding an exercise cycle. The intensity of each activity has been established and validated by the Minnesota Heart Survey (30). Participant responses regarding type of activity, frequency, and duration were used to calculate leisure time physical activity, expressed in kilocalories per week.
Blood collection occurred in the morning after an overnight fast, as previously described (27, 31). Samples were collected in ethylenediaminetetraacetic acid tubes and were sent to laboratories located close to the field centers for complete blood counts (not including differential white cell count) (32). Separation of plasma and serum occurred within 40 minutes after venipuncture; aliquots were frozen on-site at -70°C and then shipped on dry ice to the Central Blood Analysis Laboratory at the University of Vermont.
Details on quality control methods and results have been published elsewhere (31). Briefly, serum chemical analyses were performed on the Kodak Ektachem 700 Analyzer (Eastman Kodak Corporation, Rochester, New York), including analyses of albumin (coefficient of variation (CV) = 3.25 percent) and glucose (CV = 1.86 percent). Plasma lipid analyses (standardized according to the Centers for Disease Control and Prevention) were performed on an Olympus Demand system (Olympus Corporation, Lake Success, New York) and included measurement of total cholesterol, triglycerides, and high density lipoprotein cholesterol (CV = 3.56 percent). Insulin was measured in a competitive radioimmunoassay (Diagnostic Products Corporation, Malvern, Pennsylvania) (CV = 19.01 percent). Plasma fibrinogen was measured by a modification of the method of Clauss (33), using a BBL Fibrometer (Becton Dickinson, Cockeysville, Maryland; CV = 2.95 percent). The Factor VIII activity assay was performed with the Coag-A-Mate X2 instrument (Organon-Teknika, Durham, North Carolina) using factor immunodeficient plasma (Organon-Teknika) and partial thrombo-plastin (Organon-Teknika). Factor VIII activity was standardized against reference material from the World Health Organization (CV = 9.74 percent). C-reactive protein was measured using an enzyme-linked immunosorbent assay technique (34), calibrated with the World Health Organi-zation reference material (CV = 8.9 percent).
Levels of albumin, fibrinogen, white blood cells, glucose, and high density lipoprotein cholesterol were measured during two separate time periods concurrent with enrollment of the two cohorts. To adjust for possible analytical error due to this time difference, we applied a correction factor to the new cohort values, such that values for the new cohort (predominantly African Americans) were adjusted to mean values obtained for African Americans enrolled in the original cohort. C-reactive protein was measured at the same time for both cohorts. Factor VIII activity was not measured in the new cohort.
Statistical analysis
The Statistical Package for the Social Sciences (version 7.5) was used for analysis (SPSS, Inc., Chicago, Illinois). Non-normally distributed continuous variables, including C-reactive protein, white blood cell count, glucose, and high density lipoprotein cholesterol, were natural log-transformed so that parametric statistical tests could be applied. For ease of interpretation, results of non-normally distributed variables are reported as nontransformed values of the geometric means. For some analyses, the physical activity variable was divided into quartiles with the following boundaries: 1) <367.5 kcal/week (n = 1,461), 2) 367.5–<1,050 kcal/week (n = 1,461), 3) 1,050–<2,270 kcal/week (n = 1,478), and 4) 2,270 kcal/week (n = 1,468).
Initial analyses of physical activity and inflammation markers according to cardiovascular disease risk factors were performed with simple analysis of variance procedures, Pearson correlations, and 
2 tests for categorical variables.
Multivariate analysis of variance and linear regression were used to analyze these associations in more detail. Risk factors that were significantly related to physical activity and the markers of inflammation were considered as covariates in multivariate analyses and were used in multivariate modeling if they remained significant. The standardized effect size was calculated as the change in the inflammation markers associated with a 1-standard-deviation change in physical activity. We also used linear regression to explore possible mediating variables with respect to the relation between physical activity and C-reactive protein. An initial model was constructed with the natural log of C-reactive protein as the dependent variable and the natural log of physical activity as the independent variable. The following variables were then tested individually: gender, cardiovascular disease status, age, smoking history, body mass index (weight (kg)/height (m)2), fasting glucose, fasting insulin, race, and hypertension status. Variables which caused a decrease of 10 percent in the R2 of physical activity were entered into a model simultaneously. Any variables that were then nonsignificant were removed from the final model.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Results from bivariate analyses of the relations between physical activity and cardiovascular disease risk factors are shown in tables 1 and 2. Higher physical activity was associated with younger age, male gender, Caucasian race, fewer pack-years of cigarettes smoked, alcohol consumption, lower body mass index, and lower levels of fasting glucose and insulin. After stratification by gender, high density lipoprotein cholesterol (positively) and fasting insulin (negatively) were associated with physical activity in females but not in males (results not shown). These results are similar to those from a previous study of exercise in CHS participants with subclinical disease (26
). Fewer participants had clinical cardiovascular disease, hypertension, and diabetes at higher exercise levels.
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Bivariate associations between the markers of inflammation and cardiovascular disease risk factors are shown in tables 3 and 4. Age was positively correlated with fibrinogen, Factor VIII activity, and white blood cell count. Females and African Americans had higher mean values for C-reactive protein, fibrinogen, and Factor VIII activity in comparison with males and Caucasians, respectively. Higher mean values of C-reactive protein, fibrinogen, and white blood cell count were seen in current smokers compared with former and never smokers. These associations between smoking, C-reactive protein, fibrinogen, and white blood cell count are consistent with previous CHS analyses (10
, 19, 32). Mean Factor VIII activity was lower in current smokers than in never and former smokers, as has been previously demonstrated (10). High density lipoprotein cholesterol was negatively correlated with all of the markers except albumin. Compared with those without disease, participants with clinical cardiovascular disease and diabetes showed higher mean values for all markers except albumin. Alcohol consumption was inconsistently and weakly associated with inflammation markers (data not shown).
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Results from analysis of variance are shown in figures 1
–5. The adjusted mean values obtained for the inflammation markers are shown graphically by physical activity category. Each marker of inflammation was adjusted for gender, cardiovascular disease status, age, race, smoking status, diabetes status, body mass index, and hypertension. Mean values of the inflammation markers for the lowest and highest quartiles of physical activity, respectively, were as follows: C-reactive protein (mg/liter), 2.24 and 1.82 (p trend < 0.001); white blood cell count (x1,000 cells/µl), 6.37 and 5.96 (p trend < 0.001); fibrinogen (mg/dl), 329 and 317 (p trend < 0.001); Factor VIII activity (percent activity), 126 and 122 (p trend = 0.016); and albumin (g/dl), 4.008 and 4.005 (p trend = 0.840). From adjusted linear regression, the corresponding standardized effect sizes for a 1-standard-deviation change in physical activity were -0.45 mg/liter for C-reactive protein, -6.13 mg/dl for fibrinogen, -0.14 x 1,000 cells/µl for white blood cell count, -2.70 percent activity for Factor VIII activity, and 0.01 g/dl for albumin. Participants aged 72 years showed associations similar to those of participants aged <72 years (data not shown). For the prediction of inflammation variables, no significant interactions were observed between physical activity and either cardiovascular disease status, gender, or smoking.
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0.001). Note that the y axis is truncated. Numbers in bars, number of subjects in quartile.
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Using C-reactive protein as a representative inflammation marker, we employed linear regression to explore possible mediating variables. Table 5 shows that for C-reactive protein and physical activity, the greatest decrease in effect size and partial R2 was observed when body mass index was included in the model. In the final multivariate model, physical activity retained its significance, as did body mass index, glucose, and hypertension, while race did not.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The major findings of this study were: 1) physical activity as measured in the CHS was associated with significantly lower levels of markers of inflammation, including C-reactive protein, fibrinogen, Factor VIII activity, and white blood cell count; 2) these findings were independent of known cardiovascular disease risk factors; and 3) no significant association was observed between physical activity and albumin.
The differences seen with higher levels of physical activity were independent of known cardiovascular disease risk factors, as well as the presence or absence of clinical cardiovascular disease. This indicates that the observed differences were not entirely due to these participants' having fewer risk factors or having had cardiovascular disease events. Lower values of C-reactive protein, fibrinogen, Factor VIII activity, and white blood cell count were associated with higher levels of physical activity, but these associations were not of the same magnitude: Comparing the highest quartile of physical activity with the lowest, 19 percent, 6 percent, 4 percent, and 3 percent lower values were seen for C-reactive protein, white blood cell count, fibrinogen, and Factor VIII activity, respectively. C-reactive protein demonstrated strikingly lower values when the three upper exercise quartiles were compared with the lowest exercise quartile. Albumin was not associated with physical activity at all. The reason for these differences among markers is unknown. These markers are known to respond differently to proinflammatory cytokines as part of the acute-phase reaction (35); those differences may be reflected in the associations we observed. From a molecular genetic standpoint, differences in response to exercise would not be unexpected, since the genetic regulatory elements for these markers are not identical.
Albumin was the only negative acute-phase protein investigated in this analysis (a negative acute-phase reactant exhibits lower levels in the presence of inflammation), and lower levels of albumin have been associated with increased cardiovascular disease risk (36). Therefore, an association with exercise would have been demonstrated by the presence of higher albumin levels with higher levels of physical activity. However, no significant association was seen between physical activity and albumin. No differences were seen in albumin concentrations between participants with and without clinical cardiovascular disease at baseline, which calls into question the utility of albumin as a marker of the atherosclerotic process in older people (table 4). This is in contrast to the other markers of inflammation studied, which were elevated in participants with clinical cardiovascular disease compared with those without it. Because low albumin concentrations have been associated with increased risk of myocardial infarction and coronary heart disease death in studies of middle-aged people (5, 36), the relation between albumin and risk of cardiovascular disease deserves further study in the older, population-based CHS cohort.
Physical activity most likely confers cardioprotective effects through multiple mechanisms. These could include direct effects on the cardiovascular system through an increase in stroke volume (37, 38) and an increase in maximal oxygen uptake (39). Exercise also increased the dimensions of coronary arteries in an animal model (40). Long term exercise regimens seem to predispose the coagulation system toward fibrinolytic activity rather than thrombotic activity, with higher levels of tissue plasminogen activator activity and lower levels of plasminogen activator inhibitor-1 (17).
The association of physical activity with lower levels of inflammation may provide another cardioprotective mechanism, although this topic has received little prior investigation. Of the markers of inflammation we studied, the association of fibrinogen with physical activity has been investigated most often (11–13, 41). In comparison with our observations, these previous studies demonstrated similar associations between physical activity and fibrinogen levels, but they focused on the procoagulant activity of fibrinogen rather than its role in inflammation.
One current concept regarding the pathophysiologic mechanisms of the inflammation associated with atherosclerosis concerns the production of proinflammatory cytokines in response to stimuli from oxidized low density lipoproteins and macrophages associated with the atherosclerotic plaque (42, 43). The proinflammatory cytokines produced during this process include interleukin-1 ß, interleukin-6, and tumor necrosis factor-
. In vitro studies have shown that various combinations of these cytokines stimulate the production of the inflammation-sensitive proteins C-reactive protein (44), fibrinogen (45), and Factor VIII (8), as well as leukocytosis (46). Prospective studies are needed to determine whether increased activity status in older people is associated with cytokine lowering as well as changes in acute-phase protein levels.
While no causation can be inferred from a cross-sectional study, our results suggest that the association of physical activity with lower levels of inflammation may be mediated by the association of exercise with lesser degrees of central obesity and lower glucose levels. Inflammation as measured by C-reactive protein is independently correlated with obesity (19). Recent studies have shown that omental adipocytes from centrally obese individuals produce higher levels of interleukin-6 and tumor necrosis factor- than do adipocytes from controls (47, 48). In our analysis, physical activity was significantly associated with decreasing body mass index and waist:hip ratio; such associations have been reported in other studies (22, 49, 50). Waist:hip ratio is considered a measurement of central obesity (21). Taken together, these studies suggest that central obesity is associated with an increased inflammatory state, and that lesser degrees of central obesity associated with exercise could also be associated with less inflammation.
Our findings of a negative correlation between physical activity and levels of glucose are consistent with results of other studies (24, 25). Insulin resistance is associated with inflammation as measured by higher levels of C-reactive protein and interleukin-6 and lower values for albumin (51–54). Physical activity has been shown to decrease insulin resistance (24, 25), which suggests a hypothesis that improved insulin sensitivity associated with physical activity would also be associated with lower levels of inflammation.
In summary, we have identified an association between self-reported physical activity and several markers of inflammation in a cross-sectional study of the elderly. Lesser degrees of central obesity and glucose levels associated with physical activity may also be associated with these observed lower levels of inflammation. These data suggest that reduced inflammation is associated with increased exercise. Prospective studies will be required for verification of these findings.
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ACKNOWLEDGMENTS |
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This work was supported by Cardiovascular Health Study contracts NO1-HC-85079-85086, KO8-HL-03618 (M. C.), T32-HL-07594 (P. A. S.), and RO1-HL-46696 (R. P. T.) and by grants from the Office of the Dean and the Department of Pathology at the University of Vermont College of Medicine (D. F. G.).
The authors thank the investigators and staff of the Cardiovascular Health Study, especially Maureen Badger, Elaine Cornell, Florence Keating, Elizabeth Macy, Sarah Nightingale, Dr. Raymond Losito, and Adam Smiles of the Central Blood Analysis Laboratory.
Cardiovascular Health Study investigators and staff: Forsyth County, North Carolina–Bowman Gray School of Medicine, 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; EKG Reading Center, Bowman Gray School of Medicine: Kris Calhoun, Harry Calhoun, Farida Rautaharju, Pentti Rautaharju, and Loralee Robertson; Sacramento County, California–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, Maryland–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; MRI Reading Center, Johns Hopkins University: 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, Pennsylvania–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; Orange County, California–Echocardiography Reading Center (baseline), University of California, Irvine: Hoda Anton-Culver, Julius M. Gardin, Margaret Knoll, Tom Kurosaki, and Nathan Wong; Washington, DC–Echo-cardiography Reading Center (follow-up), Georgetown Medical Center: John Gottdiener, Eva Hausner, Stephen Kraus, Judy Gay, Sue Livengood, Mary Ann Yohe, and Retha Webb; Danville, Pennsylvania–Ultrasound Reading Center, Geisinger Medical Center: Daniel H. O'Leary, Joseph F. Polak, and Laurie Funk; Colchester, Vermont–Central Blood Analysis Laboratory, University of Vermont: Edwin Bovill, Elaine Cornell, Mary Cushman, and Russell P. Tracy; Tucson, Arizona–Respiratory Sciences, University of Arizona, Tucson: Paul Enright; Seattle, Washington–Coordinating Center, University of Washington, Seattle: 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; Bethesda, Maryland–National Heart, Lung, and Blood Institute Project Office: Diane E. Bild, Teri A. Manolio, Peter J. Savage, Patricia Smith, and Rachel Solomon.
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NOTES |
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Reprint requests to Dr. Russell P. Tracy, Colchester Research Facility, University of Vermont College of Medicine, 55A South Park Drive, Colchester, VT 05446 (e-mail: rtracy{at}salus.uvm.edu).
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