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- Research Methods and Procedures
Objective: This study investigated the relationship between physical activity and the obesity-related inflammatory markers C-reactive protein, interleukin-6, and soluble tumor necrosis factor receptors (sTNF-Rs) 1 and 2. Furthermore, we examined the relationship between physical activity and insulin sensitivity (insulin, C-peptide, and hemoglobin A1c levels) and whether inflammatory markers mediate this association.
Research Methods and Procedures: Biomarkers were measured in 405 healthy men and 454 healthy women from two large ongoing prospective studies. Information about physical activity and other variables was assessed by questionnaires.
Results: After adjustment for other predictors of inflammation, physical activity was inversely associated with plasma levels of sTNF-R1, sTNF-R2, interleukin-6, and C-reactive protein (p = 0.07, p = 0.004, p = 0.04, and p = 0.009). After further adjustment for BMI and leptin, as a surrogate for fat mass, most of these associations were no longer significant. Physical activity was also inversely related to insulin and C-peptide levels (p = 0.008 and p < 0.001); however, in contrast to BMI and leptin, levels of inflammatory markers explained only very little of this inverse relationship.
Discussion: These results suggest that frequent physical activity is associated with lower systemic inflammation and improved insulin sensitivity. These associations can partially be explained by a lower degree of obesity in physically active subjects. Although inflammatory markers may mediate obesity-dependent effects of physical activity on inflammatory related diseases such as type 2 diabetes or coronary heart disease, our study suggests that they do not directly account for the beneficial effects of physical activity on insulin resistance.
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- Research Methods and Procedures
Physical activity improves insulin sensitivity and reduces the risk of type 2 diabetes and coronary heart disease (CHD)1 (1, 2, 3, 4); however, the mechanisms for these benefits are not completely understood. Obesity-related inflammatory markers may be important mediators in the pathophysiology of these diseases. Thus, the expression of interleukin-6 (IL-6), tumor necrosis factor (TNF)-α, and soluble TNF receptors (sTNF-Rs) from adipose tissue is increased in obese subjects (5, 6), and plasma levels of these cytokines and C-reactive protein (CRP) are associated with BMI and insulin resistance (7, 8, 9). Furthermore, these biomarkers are important risk factors for CHD and type 2 diabetes (10, 11, 12, 13). Thus, these data suggest the hypothesis that physical activity, which leads to a decrease in obesity, may reduce adipose-derived inflammatory markers and lower the risk of chronic diseases.
Results from several cross-sectional studies suggest that higher levels of physical activity are associated with lower CRP levels (14, 15, 16, 17, 18); however, only limited data are available on the association between leisure-time physical activity and IL-6, TNF-α, or sTNF-R in humans. One smaller study (18) found a reduction in TNF-α production by blood mononuclear cells after a 6-month exercise program in 43 healthy volunteers.
The aim of the present study was to investigate the relationship between physical activity and the obesity-related inflammatory markers sTNF-R1, sTNF-R2, IL-6, and CRP. Furthermore, we examine the relationship between physical activity and measures of insulin sensitivity [insulin, C-peptide, and hemoglobin A1c (HbA1c) levels] and whether inflammatory markers mediate this association.
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Table 1 shows the biomarker levels that we measured for the present study in men, in women, and in the combined cohort. Plasma levels of sTNF-R1, sTNF-R2, and leptin were generally higher in women, whereas IL-6 and CRP concentrations were comparable between the two groups. HbA1c, insulin, and c-peptide levels were slightly higher in men.
Table 1. Biomarker levels in men, women, and in the combined cohort (mean ± SD)
|Biomarker||Men (n = 405)||Women (n = 454)||Total (n = 859)|
|sTNF-R1 (pg/mL)||932 ± 235||1004 ± 217||970 ± 229|
|sTNF-R2 (pg/mL)||1414 ± 392||2117 ± 430||1785 ± 541|
|IL-6 (pg/mL)||1.55 ± 2.17||1.53 ± 2.27||1.54 ± 2.23|
|CRP (mg/L)||1.88 ± 3.03||1.74 ± 4.29||1.81 ± 3.75|
|Leptin (ng/mL)||6.58 ± 4.48||15.58 ± 11.44||11.31 ± 9.92|
|HbA1c (%)||5.73 ± 0.68||5.24 ± 0.19||5.47 ± 0.55|
|Insulin (μU/mL)*||12.66 ± 8.93||11.36 ± 6.71||11.81 ± 7.58|
|C-peptide (ng/mL)*||2.05 ± 1.14||1.92 ± 0.91||1.96 ± 0.96|
The age-standardized characteristics and biomarker levels of the study subjects according to quintiles of physical activity are presented in Table 2. Men were more active, older, had higher body mass indices, consumed more alcohol, and had a higher energy intake than women. In both men and women, participants with higher physical activity had lower body mass indices and higher alcohol and energy but lower fat intake compared to those with lower physical activity.
Table 2. Characteristics of the study population by quintile of physical activity (N = 859)*
| ||Men Quintile|
|Median physical activity (MET-hrs/week)||4.9||16.0||29.1||49.5||86.0|
|Current smoker (%)||9.4||4.8||3.7||0.8||6.2|
|Alcohol intake (g/d)||23.4||22.5||20.8||23.0||23.8|
|Total calories (kcal/d)||2008||2020||2200||2183||2226|
|Total fat (% energy)||30.2||29.1||28.8||30.0||28.8|
|EPA + DHA (% energy)||0.11||0.11||0.15||0.15||0.15|
|Intake of NSAID (%)||39.0||43.5||49.4||47.3||49.2|
| ||Women Quintile|
|Median physical activity (MET-hrs/week)||2.4||8.0||15.1||24.7||51.9|
|Current smoker (%)||8.0||6.7||10.2||7.0||7.1|
|Alcohol intake (g/d)||10.3||9.7||12.4||12.2||12.3|
|Total calories (kcal/d)||1810||1907||1817||1931||1850|
|Total fat (% energy)||30.9||28.9||28.3||27.5||26.7|
|EPA + DHA (% energy)||0.08||0.06||0.07||0.04||0.10|
|Intake of NSAID (%)||42.5||50.1||49.7||55.9||50.4|
In both groups, individuals with higher physical activity had lower plasma levels of sTNF-R1, sTNF-R2, IL-6, CRP, and leptin. Thus, levels of inflammatory markers in men in the highest quintile of physical activity compared with men in the lowest quintile of physical activity were 5%, 9%, 13%, and 25% lower for sTNF-R1, sTNF-R2, IL-6, and CRP, respectively; the comparison values among women in the two quintile categories were 5%, 4%, 7%, and 68% lower, respectively. Insulin and c-peptide levels were also lower in subjects with higher physical activity.
Because the association between physical activity and the biomarkers may be, in part, mediated by body weight, we next analyzed the association between BMI and inflammatory markers and leptin. As expected, leptin was correlated with BMI (Spearman age-adjusted partial correlation coefficient: men, r = 0.62, p < 0.001; women, r = 0.73, p < 0.001; combined age- and sex-adjusted, r = 0.65, p < 0.001). IL-6 and CRP were moderately correlated with BMI (men, r = 0.24, p < 0.001 and 0.35, p < 0.001, respectively; women, r = 0.27, p < 0.001, and r = 0.48, p < 0.001, respectively; combined, r = 0.26, p < 0.001, and r = 0.45, p < 0.001, respectively), whereas the relationship was somewhat lower for sTNF-R1 (men, r = 0.10, p = 0.04; women, r = 0.15, p = 0.001; combined, r = 0.14, p < 0.001) and sTNF-R2 (men, r = −0.01, p = 0.88; women, r = 0.13, p = 0.005; combined, r = 0.09, p = 0.01).
Table 3 shows the association between physical activity and inflammatory markers and leptin levels, adjusted for other potential predictors of inflammation as absolute and relative changes in biomarker levels associated with an increase in physical activity of 20 MET-hrs/week. These associations were generally comparable between men and women (data not shown). Without adjustment for BMI, there were significant inverse relationships between physical activity and plasma levels of sTNF-R2 (p = 0.004), IL-6 (p = 0.04), and CRP (p = 0.009), but less so for sTNF-R1 (p = 0.07). Thus, subjects running 4 or more hours per week had ∼4% lower sTNF-R1 and sTNF-R2 levels, 6% lower IL-6 levels, and 49% lower CRP levels than those running less than 0.5 hours per week. Adjustment for BMI reduced the association of physical activity on these inflammatory markers (Table 3). After further adjustment for leptin, as a surrogate for fat mass, only the association between sTNF-R2 and physical activity remained significant. When we restricted the analyses to vigorous physical activity, the effect estimates became somewhat stronger in the base model without BMI adjustment (data not shown). However, adjustment for BMI, and especially leptin, again substantially reduced the effect estimates. When both vigorous and nonvigorous physical activity were included in one model to control for each variable, the effect estimates for both variables were not substantially different (data not shown).
Table 3. Association between physical activity and obesity-related inflammatory markers and leptin levels in men and women (N = 859), with and without adjustment for BMI and leptin
| || ||Model|
|Biomarker||Change*||Base model†||Base model + BMI||Base model + BMI + leptin|
We also assessed the association between hours of television watching and these biomarkers to determine whether measures of a sedentary lifestyle were important predictors of inflammation (data not shown). In the BMI-unadjusted model, hours of television watching were significantly associated with sTNF-R1 and leptin; however, after adjustment for BMI, none of these associations was statistically significant. Results were similar in men and women (data not shown).
Physical activity was inversely associated with plasma insulin (p = 0.008) and c-peptide levels (p < 0.001, Table 4). These associations were not significantly different between men and women (data not shown). Adjustment for the soluble TNF receptors, IL-6, or CRP slightly weakened these relationships. In contrast, adjustment for BMI and leptin markedly reduced these effect estimates.
Table 4. Association between physical activity and HbA1c, insulin, and c-peptide levels with and without further adjustment for different inflammatory markers (IM) (including sTNF-R1, sTNF-R2, IL-6, and CRP), BMI, and leptin, in men and women (N = 859)
| || ||Model|
|Biomarker||Change*||Base model†||Base model + sTNF-R1 + sTNF-R2||Base model + IL-6||Base model + CRP||Base model + BMI||Base model + BMI + leptin||Base model + BMI + leptin + IM|
| ||% (relative)||0.13||0.15||0.13||0.18||0.26||0.46||0.46|
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In this cross-sectional study, we observed statistically significant inverse associations between physical activity and plasma levels of obesity-related inflammatory markers. Further adjustment for BMI and leptin, as a surrogate for fat mass, weakened these associations, suggesting that the beneficial association between physical activity and inflammation is partially due to less body fat in subjects with higher levels of physical activity. These results extend further the findings that frequent physical activity is associated with lower systemic inflammation and higher insulin sensitivity. Furthermore, we found that in contrast to fat mass, inflammatory markers explained only very little of the inverse association between physical activity and insulin markers.
Our results of an inverse association between physical activity and insulin status are in line with intervention and population studies reporting beneficial effects of physical activity on insulin sensitivity and on the prevention of type 2 diabetes (1, 2, 3). Similarly, several studies have shown that physical activity is associated with a lower risk of CHD (for review, see Ref. (4)). However, the mechanisms responsible for these effects are only poorly understood. A few cross-sectional studies have reported that physical activity is associated with lower levels of inflammatory markers such as fibrinogen (14, 15, 17, 22, 33, 34, 35, 36, 37, 38), blood leukocytes (14, 15, 17), and CRP (14, 15, 17). However, not all studies have controlled adequately for potential confounders, and some included persons with known existing chronic disease, which may preclude patients from being active. Several of these studies (14, 15, 17) found physical activity inversely associated with inflammatory markers even after adjustment for BMI. However, although BMI is widely used to measure adiposity, it may not perfectly reflect body fat mass (39). Thus, it was recently shown that leptin is a better surrogate for body composition (40). In line with this observation, we found that adjustment for leptin levels had a larger impact on the association between physical activity and biomarkers than controlling for BMI alone (Tables 3and 4). Thus, adjustment for BMI and leptin reduced the association of physical activity with inflammatory markers by 75% for sTNF-R1, by 62% for CRP, by 25% for sTNF-R2, and by 14% for IL-6, and for insulin and c-peptide by 49% and 60%, respectively, suggesting that body fat may partially mediate some of these associations. Of course, it should be noted that these cross-sectional observations cannot prove causation.
CRP is the principal downstream mediator of the acute phase response and is primarily secreted by the liver in response to TNF-α or IL-6 stimuli (41). Although CRP has been widely used clinically to measure inflammation, its biological significance is less clear. CRP can bind to damaged tissue, to nuclear antigens, and to certain pathogens. It activates complement, binds to Fc receptors, and acts as an opsonin for pathogens (41). Plasma levels of CRP have been shown to be associated with adiposity and insulin resistance (8) and are reduced after weight loss (42). However, whether elevated CRP levels are an epiphenomenon of insulin resistance or play a causative role remains speculative. Nevertheless, elevated plasma CRP levels are an important risk factor for type 2 diabetes (13) and cardiovascular disease (10) and, therefore, highlight the importance of examining preventive measures which decrease CRP levels.
TNF-α, its soluble receptors, and IL-6 are considered to play an important role in the pathophysiology of insulin resistance, type 2 diabetes, and CHD. TNF-α can mediate insulin resistance through indirect and direct effects, including increased free fatty acid oxidation, inhibition of glucose transporter protein GLUT4, reduced autophosphorylation of the insulin receptor, modifications of insulin receptor substrates, or reduced glucose-stimulated insulin release by pancreatic β-cells (5, 43). The soluble TNF receptors are derived by proteolytic cleavage from the TNF cell surface receptors after induction by TNF or other cytokines such as IL-6, IL-1β, or IL-2, have a longer half-life, and are detected with a higher sensitivity than TNF (44, 45). The biological function of these soluble receptors is not entirely clear, and it was suggested that by binding to TNF they might attenuate its bioactivity (44). However, other studies have shown that the soluble receptors promote formation of complexes, which preserve the active trimeric form of TNF and, thus, prevent the decay of TNF into inactive monomeric forms (46, 47). Therefore, the receptors may serve as binding proteins and/or as a slow release reservoir for TNF, thereby prolonging its half-life (48). Clinically, the soluble TNF receptors are excellent indicators of inflammatory processes (for review, see Refs. (44, 45)) and are associated with obesity, insulin resistance, CHD, and angina severity (12, 49). Plasma TNF levels also have been shown to reflect disease intensity in chronic heart failure (50), and, interestingly, recent studies confirmed that the soluble TNF receptors were more predictive of the disease status in heart failure than TNF itself (51, 52). The possible causative role of IL-6 in the pathophysiology of insulin resistance comes from several lines of evidence. As noted above, IL-6 concentrations have been found to be correlated with adiposity and insulin resistance in previous studies (6, 9), and weight loss—accompanied by improvement of insulin sensitivity—is associated with a reduction of IL-6 levels (53). IL-6 also has been shown to increase basal intracellular calcium, which negatively modulates insulin-mediated stimulation of GLUT4-dependent glucose transport (54), and infusion of recombinant IL-6 has been shown to increase plasma glucose levels in animals and humans (55, 56). Furthermore, plasma IL-6 levels predict subsequent development of type 2 diabetes independent of body weight (13), and it has also been shown that IL-6 is an important predictor of CHD (10, 11). Our study shows an inverse association between physical activity and the soluble TNF receptors, IL-6 and CRP levels, suggesting that regular physical activity reduces these obesity-related inflammatory markers, partially through the effects of physical activity on body weight. However, although inflammatory markers may mediate the obesity-dependent effects of physical activity on type 2 diabetes and CHD, our study suggests that they do not directly account for the beneficial effects of physical activity on insulin resistance.
In our age-standardized analysis, we observed lower sTNF receptors levels in men compared with women. We cannot exclude the possibility that these differences are partially due to gender differences in kidney function because sTNF receptor levels may depend on renal function and tend to increase with renal impairment (44, 45); however, kidney function is not likely associated with physical activity. Furthermore, we cannot rule out the possibility that slight differences in our blood collection procedures (different anticoagulants) or the use of different kits to determine the soluble TNF receptor levels are responsible for the differences in the absolute levels of sTNF-R between men and women. However, any potential bias between men and women should not affect our main analysis because we adjusted for sex, and the main results were similar in the male and female strata.
Our study has some limitations. The cross-sectional design complicates the drawing of causal inferences, and a single assessment of a biochemical indicator, especially acute-phase inflammatory markers, may be susceptible to short-term variation, which would bias the results toward the null. However, the biomarkers of inflammation we measured are reasonable stable over time (see above). Physical activity measured in this study represents the average exposure over the year previous to the blood drawing (24, 29). Measurement error from using self-reported lifestyle variables and dietary intake is relatively small (20, 24) and likely does not bias our results because reporting error is not likely associated with the biological measurements. The HPFS and the NHS2 do not represent random samples of the U.S. population; therefore, lifestyle and dietary patterns may not reflect those of the general population. However, the biological relationship between lifestyle and dietary factors and the biomarkers found in this study should be similar to men and women in general. Because the ranges of anthropometric parameters and the biological measures are quite broad and comparable with those of the general population, the associations found in this study most likely are generalizable to men and women of this age range.
In summary, we found physical activity inversely associated with obesity-related inflammatory markers. These results extend further the findings that frequent physical activity is associated with lower risk of systemic inflammation. Our study proposes one possible mechanism for the beneficial effects of physical activity on type 2 diabetes and CHD described in the literature and suggests that these effects are partially mediated by a reduction of fat mass. Furthermore, although inflammatory markers may mediate the obesity-dependent effects of physical activity on type 2 diabetes and CHD, our study suggests that they do not directly account for the beneficial effects of physical activity on insulin resistance.