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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:760-767 (2005)
© 2005 The Gerontological Society of America

Association Between Physical Activity, Physical Performance, and Inflammatory Biomarkers in an Elderly Population: The InCHIANTI Study

Roberto Elosua1,2,, Benedetta Bartali3, Jose M. Ordovas1, Anna M. Corsi3, Fulvio Lauretani3, Luigi Ferrucci3,4, on Behalf of the InCHIANTI Investigators

1 Nutrition and Genomics Laboratory. Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts.
2 Lipids and Cardiovascular Epidemiology Unit, Institut Municipal d'Investigació Mèdica, Barcelona, Spain.
3 Laboratory of Clinical Epidemiology, Geriatric Department, National Institute of Research and Care on Aging, Florence, Italy.
4 Longitudinal Studies Section, Clinical Research Branch, ASTRA Unit, Harbor Hospital, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.

Address correspondence to Roberto Elosua, MD, Lipids and Cardiovascular Epidemiology Unit, Institut Municipal d'Investigació Mèdica, Dr Aiguader 80, 08003 Barcelona, Spain. E-mail: relosua{at}imim.es


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Our aim was to determine the association between physical activity and physical performance, and inflammatory biomarkers in elderly persons.

Methods. One thousand four persons aged 65 years or more, participants in a cross-sectional population-based study, were included. Interviewers collected information on self-reported physical activity during the previous year. Moreover, 841 participants performed a 400-meter walking test to assess physical performance. Plasma concentrations of inflammatory biomarkers were determined.

Results. Compared to sedentary men, men practicing light and moderate-high physical activity had a significantly lower erythrocyte sedimentation rate (–0.33 and –0.40 mm/h; p =.023 and p =.006, respectively), fibrinogen level (–43 and –39 mg/dL; p =.001 and p =.004, respectively), and logarithm of C-reactive protein (CRP) (–0.43 and –0.73 mg/L; p =.025 and p <.001, respectively), whereas only those men practicing moderate-high physical activity had a significantly lower uric acid level (–0.57 mg/dL; p =.023), log(interleukin 6) levels (–0.33 pg/mL; p =.014), and log(tumor necrosis factor-{alpha}) (–0.31 pg/mL; p =.030). In women, those practicing light and moderate-high physical activity had significantly lower uric acid (–0.45 and –0.34 mg/dL; p =.001 and p =.039, respectively) and log(interleukin 6) levels (–0.18 and –0.30 pg/mL; p =.043 and p =.004, respectively); only those women practicing moderate-high physical activity had significantly lower log(CRP) (–0.31 mg/L; p =.020). In women, when the analysis was adjusted for body mass index, the association between physical activity and CRP was no longer significant. Similar findings were observed when we carried these analyses according to physical performance.

Conclusions. Current physical activity practice and performance are associated with inflammatory biomarkers. A significant beneficial association is already observed with light physical activity practice and intermediate performance.

PHYSICAL activity is an independent protective factor against coronary heart disease (CHD) (1,2). The basis for this knowledge rests on observational studies (3), and on the beneficial effect of physical activity on traditional cardiovascular risk factors (4). However, all together, the favorable effects on cardiovascular risk factors do not account for the full beneficial effect of physical activity on cardiovascular health, suggesting that part of the observed cardioprotective effects may by mediated by other still poorly characterized mechanisms.

There is evidence of an inverse association between physical activity (5–12) and physical fitness (13–16), and C-reactive protein (CRP), fibrinogen, and white blood count (WBC). These inflammatory biomarkers, and others (such as erythrocyte sedimentation rate [ESR], albumin, and specific cytokines), have been shown to be predictors of mortality, in particular cardiovascular mortality (17), and to be associated with higher incidence and prevalence of clinical manifestation of CHD (18–23). Unfortunately, data on the relation between physical activity and/or fitness and cytokines are scanty, especially on older persons, the population most affected by the burden of cardiovascular disease.

In contrast, the question of whether physical activity or physical fitness is more important in defining health benefits is still open (24). Physical activity is any bodily movement produced by skeletal muscles that results in an expenditure of energy, whereas physical fitness refers to the ability to perform physical activities and is determined by a combination of regular activity and genetically inherited ability (25). Usually physical fitness is indirectly measured by a standardized physical performance test.

Using data from a representative elderly population, we tested the hypothesis that both self-reported physical activity and physical performance, as an indirect measure of fitness, were associated with levels of proinflammatory and antiinflammatory cytokines and other biomarkers of inflammation.


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 References
 
InCHIANTI ("Invecchiare in Chianti," aging in the Chianti area) is a study of the factors contributing to the decline of mobility in late life. The design of the study has been previously described in detail (26). In summary, InCHIANTI is a cross-sectional population-based study of persons living in two towns of the Chianti geographic area (Tuscany, Italy). The data collection started in September 1998 and was completed in March 2000.

Participants
In August 1998, 1270 persons aged 65 years or older were randomly selected from the population registry. Another 29 persons were selected randomly from those who were aged 90 years or older. Of the initial 1299 persons selected, 39 were not eligible for the study because they had already died or moved away from the area. Participation rate was very high at 91.6% (1154/1260). Participants who were not able to walk independently (n = 50) were excluded from this analysis. Finally, of these 1104 participants, 1004 had data on physical activity and at least one inflammatory biomarker (994 for fibrinogen, 1004 for interleukin 6 [IL-6] receptor), and 841 had data on physical performance and at least one inflammatory biomarker (833 for fibrinogen, 841 for uric acid). These figures represent 80% and 67% of the initial eligible population, respectively.

Laboratory Methods
Blood samples were taken in the morning after a fasting period of more than 8 hours. Serum and plasma were separated by low-speed centrifugation and stored at –80°C. WBC was determined using a hematology auto analyzer (SE 9000 DASIT; Sysmex, Kobe, Japan), and ESR was automatically determined by a DIESSE VES-Matic PC (Diagnostica Senese S.p.A., Monteriggioni, Italy). Albumin was measured by an agarose electrophoretic technique (Hydragel Protein(E) 15/30; Sebia, Issy-les-Moulineaux, France). The mean interassay coefficient of variation (CV) was 0.8%. Serum uric acid was determined by using commercial enzymatic tests (Roche Diagnostics, Mannheim, Germany) on a Roche Hitachi Modular P800 analyzer. The interassay CV was less than 2%. Plasma fibrinogen was automatically detected according to the Clauss method with an STA Fibrinogen kit (Diagnostica Stago Roche Diagnostics, Mannheim, Germany) and a Sta Stago Boehringer Mannheim analyzer.

Determination of CRP level was based on a high sensitivity enzyme-linked immunosorbent assay, a competitive immunoassay that uses purified protein and polyclonal anti-CRP antibodies. The interassay CV was {approx} 5.0%. The minimum detectable concentration was 0.03 mg/L. The average of two measures performed in each sample was used in the analysis.

A large panel of inflammatory cytokines, including several proinflammatory (interleukin 1 beta [IL-1ß], IL-6, interleukin 18 [IL-18], tumor necrosis factor alpha [TNF-{alpha}]) and antiinflammatory (interleukin 1 receptor antagonist [IL-1ra], interleukin-10 [IL-10]) cytokines (27) was also determined. The quantitative measurement of serum levels of IL-6, soluble IL-6 receptors (sIL-6R), IL-10, IL-1ß, IL-1ra, IL-18, and TNF-{alpha} was performed by enzyme-linked immunosorbent assays using commercial kits (BIOSOURCE International, Camarillo, CA). The lower detectable concentration was 0.10 pg/mL for IL-6, 8.00 pg/mL for sIL-6R, 1.00 pg/mL for IL-10, 0.01 pg/mL for IL-1ß, 4.00 pg/mL for IL-1ra, 4.50 pg/mL for IL-18, and 0.09 pg/mL for TNF-{alpha}. The mean interassay CV for IL-6, sIL-6R, TNF-{alpha}, and IL-1ß was 7.0%; it was 8.2% for IL-1ra, and 4.4% for IL-18.

Physical Activity Practice Assessment
Trained interviewers administered a structured questionnaire specifically developed for the study; the questionnaire required that the participant provide data on past and current physical activity. The details of the questionnaire have been previously reported (28). Briefly, data on current physical activity were collected by asking the following question: "Did you ever perform any sport or recreational physical activity, for at least three months, during the last year?" If the answer was affirmative, the interviewers asked the participant to specify the type of each physical activity, the number of months of practice, the number of times per month, and the number of minutes of practice each time. By combining these responses and available tables to assess the intensity of each physical activity, participants were classified as: a) inactive, including participants who were completely inactive and those who performed light intensity physical activity (i.e., walking, dancing; ≤4 Metabolic Equivalent Tax) less than 1 hour per week; b) light physical activity, including participants who performed light intensity physical activity 2–4 hours per week; c) moderate–high physical activity, including participants who performed at least light physical activity 5 hours per week or more and those who performed moderate physical activity (i.e., gymnastics, swimming; >4 Metabolic Equivalent Tax) 1–2 hours per week or more. Information about former (when participants were 20–40 and 40–60 years old) physical activity practice was recorded in the same way.

Physical Performance Evaluation
An objective assessment of physical function and performance was carried out by trained physical therapists (26). The time to walk 400 meters as fast as possible is highly correlated with maximum oxygen consumption (VO2max) in elderly people (r > 0.75) (29), and it is used in this analysis as a performance-based measure of physical fitness (30). Time was measured by using an optoelectronic system connected to a digital chronometer and a printer (Chronoprinter Tag-Heuer CR501; Zingerle Sports Timing, Bolzano, Italy). Eight hundred forty-one participants performed this test. Three groups according to tertile distribution were defined in each different age (65–74 y, 75–84 y, and ≥85 y) and sex strata: low, intermediate, and high performance. Those participants who performed the test and were not able to complete the 400 meters (n = 47) were included in the low performance group.

Other Variables
The participants were invited to the study clinic for a comprehensive evaluation of health status and anthropometrical measures conducted using standardized methods. Body mass index (BMI) was calculated as weight in kilograms divided by height (in meters squared). Presence of major chronic diseases (cardiovascular disease, CHD, stroke, peripheral artery disease), cardiovascular risk factors, and current inflammatory process (infections, bronchitis, arthritis) were ascertained by trained geriatricians according to standard algorithms that used information on medical history, drug treatments, signs and symptoms, medical documents, and hospital discharge records (31). Smoking habits were classified as follows: never smoked, former smoker, or current smoker. Intakes of alcohol, vitamin C, vitamin E, and ß-carotene were estimated using a detailed food frequency questionnaire developed and validated in the context of the European Prospective Investigation into Cancer and nutrition (EPIC) (32).

Ethics
The local ethics committee approved the protocol. All participants received a description of the study procedures and objectives, and all gave their informed consent including specific permission to use the biological samples for research purposes.

Statistical Analysis
The chi-square test was used to compare proportions between groups. Analysis of variance, for normally distributed variables, and the Kruskal-Wallis test were used to compare continuous variables between groups.

The association between physical activity and physical performance, and inflammatory biomarkers was assessed by multiple linear regression analysis. Some continuous variables (CRP, IL-6, sIL-6R, IL-10, IL-1ß, IL-1ra, IL-18, and TNF-{alpha}) were highly skewed and were log-transformed to meet the assumptions of multiple linear regression. This linear regression was not appropriate to evaluate the association between physical activity practice or performance, and IL-10. Thus, logistic regression analysis was used to determine the association between physical activity and performance, and IL-10. For this purpose, the level of IL-10 was coded as below versus above the minimum detectable level (1.00 pg/mL).

A fixed set of covariates that were clinically relevant or statistically associated with physical activity or performance and were further associated with inflammatory biomarkers (both at an alpha level of 0.10) were included in the linear regression models. BMI might be considered a confounder variable but also a factor in the causal pathway of the association between physical activity and lower inflammation. To explore this possibility, two multiple linear regression models were defined, one excluding BMI (Model 1) and one including BMI (Model 2). All the analyses were stratified by sex, and a p value less than.05 was considered to be statistically significant.


   RESULTS
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 Abstract
 Methods
 Results
Discussion
 References
 
Information about relevant clinical, anthropometrical, and behavioral characteristics of the participants and inflammatory biomarkers distribution stratified by sex is presented in Table 1. Participants with missing data for physical activity or the outcome variables (n = 100) were older (79 vs 75 years), and presented a higher proportion of inactive people (34% vs 20%) than did those participants whose data were included in the analysis (n = 1004). Participants with missing data for physical performance or the outcome variables (n = 263) were older (81 vs 74 years), and presented a higher prevalence of inactive people (47% vs 13%) and chronic cardiovascular diseases (28% vs 11%) than did those participants whose data were included in the analysis (n = 841).


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  		Table 1. Characteristics of the Participants in the Study.

 
Data on inflammatory biomarker levels according to sex and physical activity practice are presented in Table 2. Physical activity was inversely associated with WBC, ESR, fibrinogen, CRP, IL-6, and IL-1ra, and was positively associated with albumin in men and women. Moreover, physical activity was inversely associated with uric acid, sIL-6R, and IL-18 in women and with TNF-{alpha} in men.


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  		Table 2. Circulating Inflammatory Biomarker Levels According to Physical Activity Practice in Men and Women.

 
Physical performance was inversely associated with ESR and IL-6 both in men and women. Moreover, physical performance was inversely associated with CRP in men, whereas it was inversely associated with fibrinogen and IL-1ra, and positively associated with IL-1ß, in women (Table 3).


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  		Table 3. Circulating Inflammatory Biomarker Levels According to Physical Performance, as a Measure of Physical Fitness, in Men and Women.

 
Multiple linear regression analysis was performed to determine the multivariate-adjusted magnitude of the association between inflammatory biomarkers and physical activity and performance. The statistically significant associations between physical activity or performance and inflammatory biomarkers observed in men are presented in Table 4. Light and moderate–high physical activity practices were associated with lower ESR, fibrinogen, and CRP (Table 4, Model 1). The magnitude of the coefficients estimating the association of light and moderate-high physical activity compared to a sedentary state was similar for the models predicting these three inflammatory biomarkers. Only moderate-high physical activity practice was significantly associated with lower levels of uric acid, IL-6, and TNF-{alpha}. Similarly, compared to low physical performance, intermediate and high physical performance were inversely associated with ESR and CRP. High physical performance was also associated with a lower level of IL-6. When the analyses were further adjusted for BMI (Table 4, Model 2), the magnitude of the coefficients for physical activity and performance were only slightly reduced, and most of them remained significantly associated with lower levels of inflammatory biomarkers. In these models, BMI was directly associated with levels of uric acid and CRP, but it was not associated with ESR, fibrinogen, IL-6, or TNF-{alpha}. In contrast, neither physical activity nor physical performance was associated with WBC, albumin, sIL-6R, IL-1ß, IL-1ra, or IL-18.


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  		Table 4. Multiple Linear Regression Coefficients (Standard Error) of the Association Between Physical Activity Practice, Physical Performance, and Inflammatory Biomarkers in Men.

 
Results on significant associations between physical activity or performance and inflammatory biomarkers in women are presented in Table 5. Light physical activity practice was inversely associated with uric acid, fibrinogen, and IL-6; moderate-high physical activity practice was inversely associated with uric acid, CRP, and IL-6 (Table 5, Model 1). Both intermediate and high performance were inversely associated, and with a similar magnitude, with ESR. In addition, intermediate performance was inversely associated with IL-6, and high physical performance was associated with higher levels of IL-1ß and with lower levels of fibrinogen, CRP, and IL-1ra. When the analyses were further adjusted for BMI (Table 5, Model 2), the association between physical activity and performance, and CRP and IL-1ra were not further statistically significant, suggesting that changes in BMI could be a critical step in the casual pathway for these associations. In these models, BMI was directly associated with ESR, uric acid, fibrinogen, CRP, and IL-6, but it was not associated with IL-1ß and IL-1ra. In contrast, neither physical activity nor physical performance were associated with WBC, albumin, sIL-6R, IL-18, or TNF-{alpha}. We did not observe significant associations between IL-10, below or above the detectable threshold, and physical practice or performance.


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  		Table 5. Multiple Linear Regression Coefficients (Standard Error) of the Association Between Physical Activity Practice, Physical Performance, and Inflammatory Biomarkers in Women.

 
We also examined the associations between current or past physical activity practices and circulating levels of inflammatory biomarkers. Only current physical activity practice was significantly associated with a lower level of these biomarkers (Figure 1). Past light or moderate-high physical activity in participants who become currently inactive was associated with the same level of inflammatory biomarkers as in those who were inactive and remain currently inactive.



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  		Figure 1. Erythrocyte sedimentation rate, fibrinogen, C-reactive protein, and interleukin-6 mean or median, according to current and past physical activity practice

 

   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Using data obtained in an epidemiological study performed in a population-based sample, we demonstrated that physical activity and performance are associated with lower circulating levels of proinflammatory biomarkers in older men and women. Specifically, we found consistent associations between physical activity and performance, lower ESR, and lower plasma levels of fibrinogen, CRP, and IL-6. Our data confirm previous research showing that physical activity (13–20) and fitness (21–24) are inversely associated with inflammatory biomarkers such as CRP, WBC, and fibrinogen. Moreover, our study provides original contributions to the knowledge on this topic.

First, whereas most of the available evidence for an association between physical activity and lower inflammation is based on self-reported information on physical activity practice, we found that physical performance in the 400-meter walking test, which might be considered a proxy measure of fitness, was also associated with lower inflammation.

Second, most of the studies assessing the association between physical fitness and inflammatory biomarkers have been carried out in a young or middle-aged population. In our study, we also demonstrated that physical fitness is significantly associated with lower plasma levels of proinflammatory markers in the elderly population.

Third, we demonstrated that the association between physical activity and performance and inflammatory biomarkers is already observed when comparing light physical activity versus a sedentary state, or intermediate versus low performance level. We also found that current rather than past level of physical activity was associated with lower levels of inflammatory biomarkers.

Finally, in this study we tested the association between physical activity and performance and a large panel of inflammatory markers, including several proinflammatory (IL-1ß, IL-6, IL-18, and TNF-{alpha}) and antiinflammatory (IL-1ra, IL-10) cytokines (27). It has been suggested that studying only proinflammatory markers may be misleading because it does not consider the potential effect of counteractive mechanisms. However, we found no clear evidence that physical activity is associated with parallel decline in antiinflammatory cytokines, especially IL-10 and IL-1ra. These findings suggest that physical activity selectively readjusts the signaling network of cytokines toward lower levels of inflammation.

One of the strengths of this study is that we are adjusting our results for dietary antioxidant intake which has been associated with lower inflammation. In our study, IL-6 was inversely associated with vitamin C (r = –0.123), ß-carotene (r = –0.146), and vitamin E (r = –0.103) intake. It is also known that active people have a more healthy diet. In our study, more active participants presented a higher intake of these nutrients. Thus, diet may be considered a confounder. However, the results of our diet-adjusted analysis support a diet-independent association between physical activity and performance and lower levels of proinflammatory biomarkers.

The mechanism by which regular physical activity is associated with lower levels of inflammatory biomarkers is uncertain. An interesting hypothesis is that regular physical activity may forestall inflammation by reducing obesity and the percentage of visceral fat, and improving peripheral insulin receptor sensitivity (33). In fact, obesity (34) and peripheral insulin resistance (35) are directly associated with systemic inflammation. Noteworthy, in women but not in men, the association between physical activity or performance, and CRP and IL-1ra, was no longer statistically significant when BMI was included in the models, suggesting that physical activity may reduce CRP and IL-1ra through its effects on BMI.

The free radical theory of aging offers another potential explanation for our findings (36). According to this theory, reactive oxygen species generated in normal metabolic processes may cause important cell and tissue oxidative damage. In unfit individuals, subliminal injuries to myocytes due in part to reactive oxygen species and in part to unusual muscle stretching determine an inflammatory response. There is evidence, both from animal and human studies, that long-term exercise implies an increment in the mechanical resistance of myocytes to stretching, and in the endogenous antioxidant enzyme activity (37), therefore preventing excessive and self-sustained local inflammatory reaction.

The most important limitation of our study is its cross-sectional nature. The direction of the causal pathway between physical activity and lower level of inflammation remains unclear. However, some experimental studies have shown that physical activity can prospectively reduce CRP levels, other inflammatory markers (38–40), and the mononuclear cell production of atherogenic cytokines (41). Another limitation is that the participants with missing data for physical activity and/or fitness or the outcome variables were older and more inactive than were those participants whose data were included in the analyses. Nevertheless, we do not think that these differences could significantly affect the validity of the observed results.

In our study, we demonstrated that current physical activity practice and performance are associated with inflammatory biomarkers. A significant beneficial association is already observed with light physical activity practice and intermediate performance. These findings support public health recommendations suggesting that significant benefit could be already achieved with light to moderate physical activity and that "it is never too late" to become physically active.


   Acknowledgments
 
Supported by grant HL54776 by the National Heart, Lung, and Blood Institute, National Institutes of Health, and by contracts 53-K06-5-10 and 58-1950-9-001 from the U.S. Department of Agriculture Research Service. Roberto Elosua received an award from the Fulbright-Generalitat de Catalonia Program and from the Spanish Network of Cardiovascular Research Centers (RECAVA, FIS-C03/01). The InCHIANTI study was supported as a "targeted project" (ICS110.1\RS97.71) by the Italian Ministry of Health and in part by the U.S. National Institute on Aging (contracts 263_MD_9164_13 and 263_MD_821336).


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

Received October 17, 2003

Accepted January 14, 2004


   References
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 Abstract
 Methods
 Results
 Discussion
 References
 

  1. Bijnen FC, Caspersen DJ, Mosterd WL. Physical inactivity as a risk factor for coronary heart disease: a WHO and International Society and Federation of Cardiology position statement. Bull World Health Organ. 1994;72:1-4.[Medline]
  2. Fletcher GF, Blair SN, Blumenthal J, et al. Statement on exercise. Benefits and recommendations for physical activity programs for all Americans. A statement for health professionals by the Committee on exercise and cardiac rehabilitation of the Council on clinical cardiology, American Heart Association. Circulation. 1992;86:340-344.[Free Full Text]
  3. Kohl HW, III. Physical activity and cardiovascular disease: evidence for a dose response. Med Sci Sports Exerc. 2001;6:S472-S483.
  4. Thompson PD, Buchner D, Piña IL, et al. Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease. A Statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity). Circulation. 2003;107:3109-3116.[Free Full Text]
  5. Dufaux B, Order U, Geyer H, Hollman W. C-reactive protein serum concentrations in well-trained athletes. Int J Sports Med. 1984;5:102-106.[Medline]
  6. Geffken DF, Cushman M, Burke GL, Polak JF, Sakkinen PA, Tracy RP. Association between physical activity and markers of inflammation in a healthy elderly population. Am J Epidemiol. 2001;153:242-250.[Abstract/Free Full Text]
  7. Ford ES. Does exercise reduce inflammation? Physical activity and C-reactive protein among U.S. adults. Epidemiology. 2002;13:561-568.[Medline]
  8. Abramson JL, Vaccarino V. Relationship between physical activity and inflammation among apparently healthy middle-aged and older US adults. Arch Intern Med. 2002;162:1286-1292.[Abstract/Free Full Text]
  9. Wannamethee SG, Lowe GD, Whincup PH, Rumley A, Walker M, Lennon L. Physical activity and hemostatic and inflammatory variables in elderly men. Circulation. 2002;105:1785-1790.[Abstract/Free Full Text]
  10. King DE, Carek P, Mainous AG, III, Pearson WS. Inflammatory markers and exercise: differences related to exercise type. Med Sci Sports Exerc. 2003;35:575-581.[Medline]
  11. Pitsavos C, Chrysohoou C, Panagiotakos DB, et al. Association of leisure-time physical activity on inflammation markers (C-reactive protein, white cell blood count, serum amyloid A, and fibrinogen) in healthy subjects (from the ATTICA Study). Am J Cardiol. 2003;91:368-370.[Medline]
  12. Manns PJ, Williams DP, Snow CM, Wander RC. Physical activity, body fat, and serum C-reactive protein in postmenopausal women with and without hormone replacement. Am J Hum Biol. 2003;15:91-100.[Medline]
  13. Church TS, Barlow CE, Earnest CP, Kampert JB, Priest EL, Blair SN. Associations between cardiorespiratory fitness and C-reactive protein in men. Arterioscler Thromb Vasc Biol. 2002;22:1869-1876.[Abstract/Free Full Text]
  14. LaMonte MJ, Curstine JL, Yuanowitz FG, et al. Cardiorespiratory fitness and C-reactive protein among a tri-ethnic sample of women. Circulation. 2002;106:403-406.[Abstract/Free Full Text]
  15. Isasi CR, Deckelbaum RJ, Tracy RP, Starc TJ, Berglund L, Shea S. Physical fitness and C-reactive protein level in children and young adults: the Columbia University Biomarkers Study. Pediatrics. 2003;111:332-338.[Abstract/Free Full Text]
  16. Barbeau P, Litaker MS, Woods KF, et al. Hemostatic and inflammatory markers in obese youths: effects of exercise and adiposity. J Pediatr. 2002;141:415-420.[Medline]
  17. Taaffe DR, Harris TB, Ferrucci L, et al. Cross-sectional and prospective relationships of interleukin-6 and C-reactive protein with physical performance in elderly persons: MacArthur studies of successful aging. J Gerontol Med Sci. 2000;55A:M709-M715.
  18. Pradhan AD, Manson JE, Rossouw JE, et al. Inflammatory biomarkers, hormone replacement therapy, and incident coronary heart disease: prospective analysis from the Women's Health Initiative observational study. JAMA. 2002;288:980-987.[Abstract/Free Full Text]
  19. Erikssen G, Liestol K, Bjornholt JV, Stormorken H, Thaulow E, Erikssen J. Erythrocyte sedimentation rate: a possible marker of atherosclerosis and a strong predictor of coronary heart disease mortality. Eur Heart J. 2000;21:1614-1620.[Abstract/Free Full Text]
  20. Lee CD, Folsom AR, Nieto FJ, Chambless LE, Shahar E, Wolfe DA. White blood cell count and incidence of coronary heart disease and ischemic stroke and mortality from cardiovascular disease in African-American and White men and women: atherosclerosis risk in communities study. Am J Epidemiol. 2001;154:758-764.[Abstract/Free Full Text]
  21. Nelson JJ, Liao D, Sharrett AR, et al. Serum albumin level as a predictor of incident coronary heart disease: the Atherosclerosis Risk in Communities (ARIC) study. Am J Epidemiol. 2000;151:468-477.[Abstract/Free Full Text]
  22. Maresca G, Di Blasio A, Marchioli R, Di Minno G. Measuring plasma fibrinogen to predict stroke and myocardial infarction: an update. Arterioscler Thromb Vasc Biol. 1999;19:1368-1377.[Abstract/Free Full Text]
  23. Ridker PM. High-sensitivity C-reactive protein: potential adjunct for global risk assessment in the primary prevention of cardiovascular disease. Circulation. 2001;103:1813-1818.[Abstract/Free Full Text]
  24. Blair SN, Cheng Y, Holder JS. Is physical activity or physical fitness more important in defining health benefits? Med Sci Sports Exerc. 2001;33:(S6): S379-S399.[Medline]
  25. U.S. Department of Health and Human Services. Physical activity and health: a report of the Surgeon General. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion, 1996.
  26. Ferrucci L, Bandinelli S. Benvenuti E, et al., for the InCHIANTI Group. Subsystem contributing to the decline in ability to walk: bridging the gap between epidemiology and geriatric practice in the InCHIANTI Study. J Am Geriatr Soc. 2000;48:1618-1625.[Medline]
  27. von der Thusen JH, Kuiper J, van Berkel TJ, Biessen EA. Interleukins in atherosclerosis: molecular pathways and therapeutic potential. Pharmacol Rev. 2003;55:133-166.[Abstract/Free Full Text]
  28. Benvenuti E, Bandinelli S, Di Iorio A, et al. Relationship between motor behaviour in young/middle age and level of physical activity in late life. Is muscle strength in the causal pathway? In: Capodaglio P, Narici MV, eds. Advances in Rehabilitation. Pavia, Italy: Maugeri Foundation Books PI-ME Press; 2000:17–27.
  29. Simonsick EM, Newman AB, Nevitt MC, et al. Measuring higher level physical function in well-functioning older adults: expanding familiar approaches in the Health ABC study. J Gerontol Med Sci. 2001;56A:M644-M649.
  30. Simonsick EM, Montgomery PS, Newman AB, Bauer DC, Harris T. Measuring fitness in healthy older adults: the Health ABC Long Distance Corridor Walk. J Am Geriatr Soc. 2001;49:1544-1548.[Medline]
  31. Guralnik JM, Fried LP, Simonsik EM, et al., eds. The Women's Health and Aging Study: Health and Social Characteristics of Older Women With Disability. Bethesda, MD: National Institute of Aging, 1995. NIH Publ. No 95-4009.
  32. Pisani P, Faggiano F, Krogh V, et al. Relative validity and reproducibility of a food frequency dietary questionnaire for use in the Italian EPIC centres. Int J Epidemiol. 1997;26:S152-S160.[Abstract/Free Full Text]
  33. Mayer-Davis EJ, D'Agostino R, Jr, Karter AJ, et al. Intensity and amount of physical activity in relation to insulin sensitivity: the Insulin Resistance Atherosclerosis Study. JAMA. 1998;279:669-674.[Abstract/Free Full Text]
  34. Zicardi P, Nappo F, Giugliano G, et al. Reduction of inflammatory cytokine concentrations and improvement of endothelial functions in obese women after weight loss over one year. Circulation. 2002;105:804-809.[Abstract/Free Full Text]
  35. Pickup J, Mattock M, Chusney G, et al. NIDDM as a disease of the innate immune system: association of acute-phase reactants and interleukin-6 with metabolic syndrome X. Diabetologia. 1997;40:1286-1292.[Medline]
  36. Pansarasa O, Castagna L, Colombi B, et al. Age and sex differences in human skeletal muscle: role of reactive oxygen species. Free Radic Res. 2000;33:287-293.[Medline]
  37. Elosua R, Molina L, Fito M, et al. Response of oxidative stress biomarkers to a 16-week aerobic physical activity program, and to acute physical activity, in healthy young men and women. Atherosclerosis. 2003;167:327-334.[Medline]
  38. Esposito K, Pontillo A, Di Palo C, et al. Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomised trial. JAMA. 2003;289:1799-804.[Abstract/Free Full Text]
  39. Larsen AI, Aukrust P, Aarsland T, Dickstein K. Effect of aerobic training on plasma levels of tumor necrosis factor alpha in patients with heart failure. Am J Cardiol. 2001;88:805-808.[Medline]
  40. Mattusch F, Dufaux B, Heine O, et al. Reduction of the plasma concentration of C-reactive protein following nine months of endurance training. Int J Sports Med. 2000;21:21-24.[Medline]
  41. Smith JK, Dykes R, Douglas JE, et al. Long-term exercise and atherogenic activity of blood mononuclear cells in persons at risk of developing ischemic heart disease. JAMA. 1999;281:1722-1727.[Abstract/Free Full Text]



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