The beneficial effects of exercise training on traditional cardiovascular risk factors explain approximately half of the risk reduction associated with exercise (34). The unexplained benefit may be attributable, in part, to the direct protective effects of exercise on the vasculature, a concept recently called vascular conditioning (28). In this regard, it is commonly accepted that repeated episodes of elevated blood flow and, consequently, shear stress represent a primary physiological signal for vascular adaptations to exercise training (31). The vascular effects of chronic exercise may include structural (e.g., arterial remodeling) and functional adaptations (21,30), the latter involving phenotypic alterations of vascular endothelial and smooth muscle cells, resulting in changes in vasomotor function.
In humans, the most common noninvasive methodology to evaluate endothelium-dependent dilation is flow-mediated dilation (FMD), a noninvasive technique introduced by Celermajer et al. (6) in 1992. In brief, the brachial artery vasodilator response to an elevation in shear stress after a transient period of forearm ischemia is assessed via high-resolution ultrasound. Peak percent FMD from baseline diameter is reported as the index of endothelial function/health. As proposed in earlier animal and human studies, a recent comprehensive meta-analysis concluded that brachial artery FMD is, at least in part, nitric oxide mediated (18). In addition, the brachial artery response to exogenous nitric oxide donors, i.e., nitrate-mediated dilation (NMD), can be used to assess endothelium-independent dilation, thus providing information on the function of the underlying vascular smooth muscle (8). The assessment of FMD has become popular in clinical studies because it strongly predicts cardiovascular events in patients with established cardiovascular disease and in asymptomatic patients, independently of other traditional risk factors including aging (25,42).
Although it may be intuitive to expect a larger FMD response in athletes because of chronic exercise training, the evidence on this matter is far from conclusive (16,33). In fact, Green et al. (20) recently reported similar or even decreased FMD in enlarged conduit arteries of young elite athletes compared with that in age-matched controls. The publication of this report stimulated the present meta-analysis. It has been proposed that long-term training may result in the enlargement of conduit arteries, which in turn could reduce (normalize) the effect of shear stress on the endothelium and thus diminish the stimulus for FMD enhancement in athletes (20,30). Alternative explanations for the discrepant FMD results in athletes may lie in the inherent limitations of cross-sectional comparisons and the small sample sizes of previous individual studies (1,3,12–14,20,23,27,29,32,36,37,40,44–46,49,50,56,59,60). In addition, longitudinal studies have been predominantly based on relatively short- to medium-term training interventions, hence plausibly assessing incomplete vascular adaptations (53). It has also been proposed that many chronic diseases associated with aging are largely caused by the decline in physical activity and not by aging per se (5,28,34). Certainly, current research in animals and humans suggests that “vascular aging” is preventable with physical activity (4,10,22,30,51). The study on master athletes has been proposed as an optimal model to determine the effects of successful aging due to lifelong exercise training (10). Accordingly, we performed a meta-analysis procedure to systematically review available FMD studies comparing young and master athletes against corresponding age-matched control subjects.
The review is reported according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group guidelines (55).
Data sources and searches
Our systematic search included MEDLINE, Cochrane, Scopus, and Web of Science since their inceptions until July 2013. We used combinations of the subject headings “athletes,” “highly trained,” “endothelial function,” “flow-mediated dilation,” “vasodilation,” and “vasoreactivity” (see Figure, Supplemental Digital Content 1, https://links.lww.com/MSS/A389, MEDLINE search strategy). We also performed hand searching in reference citations of identified reviews and original research articles selected for full-text retrieval.
To be included in the analysis, an observational report had to 1) assess FMD in long-term–trained subjects considered as athletes and 2) include a group of age-matched controls. In the event of multiple publications pertaining to the same research, the first published or more comprehensive study was included. Inclusion of studies was not limited by publication status or language. Study selection was performed independently and in duplicate by two investigators (D. M.) and (C. D.). Discrepancies on inclusion/exclusion were solved by consensus or through consultation with a third reviewer (G. W.).
Data extraction and quality assessment
The following variables were extracted into a preformatted spreadsheet: authors, year of publication, characteristics of study participants (number, gender, age, height, weight, body mass index (BMI), systolic blood pressure (SBP), and diastolic blood pressure (DBP)), exercise training characteristics (type of training, sport, primary trained limb, hours per day, frequency, hours per week, and years of training), and vascular variables (cuff placement, occlusion time, baseline brachial diameter, peak brachial diameter, continuous or single ultrasound scan of peak brachial diameter, time to peak brachial diameter, hyperemic shear rate, FMD, and NMD). The presence of concomitant cardiovascular disease and smoking status were also determined. In addition, if data were unclear or were not available in the published reports, we contacted the corresponding and/or first author by e-mail to request this information. A systematic appraisal of quality for observational research (SAQOR) (47) previously applied in meta-analysis of observational studies evaluating vascular function (54) was performed to provide assessment of study quality. The SAQOR was adjusted to assess 1) the athlete sample, 2) the control group, 3) quality of FMD measurement, 4) confounding variables, and 5) data. Overall, the SAQOR was scored out of 16, quality deemed better with a greater score (see Table, Supplemental Digital Content 2, https://links.lww.com/MSS/A389, quality assessment of studies included in the meta-analysis). Data extraction and quality assessment were performed independently and in duplicate by two investigators (D. M.) and (C. D.). Discrepancies were solved by consensus or through consultation with a third reviewer (G. W.).
Data synthesis and analysis
The meta-analysis and statistical analyses were performed using the Review Manager software (RevMan 5.2; Cochrane Collaboration, Oxford, United Kingdom) and Comprehensive Meta-analysis software (version 2; Biostat, Inc., Englewood, NJ). The primary outcome was the standardized mean difference (SMD) in FMD between athletes and control groups. SMD summary statistic allowed us to standardize FMD and NMD values obtained using relatively different procedures to reduce the methodology-related variability in the meta-analysis. Each SMD was weighted according to the inverse variance method (24), and they were pooled with a random effects model (9).
Heterogeneity between studies was assessed using the chi-square test for heterogeneity and I2 statistics. Potential moderating factors were evaluated by subgroup analysis comparing studies grouped by dichotomous or continuous variables potentially influencing arterial parameters. Median values of continuous variables were used as cutoff values for grouping studies. Meta-regression analysis was performed to further explore the variables that best predicted the SMD in FMD between athletes and control groups. In all meta-regression models, studies were weighted by the inverse variance of the dependent variable (24). Potential moderating factors were entered as independent variables in regression models, with the SMD in FMD between athletes and control groups as the dependent variable. Publication bias was evaluated by estimating the Begg and Mazumdar rank correlation test and the Egger weighted regression test (11). A P value of less than 0.05 was considered statistically significant.
Study selection and characteristics
The flow diagram of the process of study selection is shown in Figure 1. The search on MEDLINE, Cochrane, Scopus, and Web of Science and manual review of articles cited in the identified and related publications retrieved 578 articles, 231 remaining after duplicate removal. Of these, 177 were excluded because they were irrelevant to our present meta-analysis (n = 54), did not report vascular function (n = 44), were review articles, guidelines, or letters (n = 37), did not have a control group (n = 28), were animal studies (n = 8), or were meeting abstracts (n = 6). We obtained and reviewed the full text of the remaining 54 articles and excluded 32 for the following reasons: microvascular studies (n = 15), other populations (n = 10), no report of endothelial function (n = 5), duplicate data (n = 2) (43,48), or no standard FMD methodology (n = 1) (39). Finally, 21 articles were included in the meta-analysis. Five of these 21 articles presented a single control group independently compared with two or more athlete subgroups (1,20,37,40,59); thus, the control group of each of these articles was divided into equivalent parts so that the total numbers added up to the original size of the control group, and athlete subgroups were then evaluated as individual studies (24). Moreover, one article presented young and master athletes independently compared with age-matched counterparts; thus, they were evaluated as two individual studies (13).
Table 1 shows the main characteristics of the resulting 29 studies, comprising 530 athletes and 376 age-matched control subjects, ranging from 15 to 102 in sample size. Twenty-one studies involved young athletes (<40 yr), whereas 8 studies involved master athletes (>;50 yr). Twenty-two studies comprised male subjects, three studies comprised female subjects (23,32,44), and four studies comprised female and male subjects (37,56,60). The mean clinical characteristics of all subjects in the included studies ranged from 20 to 75 yr for age, 164 to 188 cm for height, 56 to 93 kg for weight, 19.6 to 27.5 kg·m−2 for BMI, 104 to 134 mm Hg for SBP, and 60 to 82 mm Hg for DBP. Regarding training characteristics of athletes (Table 2), 24 studies included endurance-trained athletes, three studies included strength-trained athletes (1,40,60), and two studies included endurance- and strength-trained athletes (20,36), for a total of 452 endurance-trained athletes, 49 strength-trained athletes, and 29 endurance- and strength-trained athletes. With respect to the (primarily) trained limb, 20 studies included lower limb-trained athletes, five studies included upper and lower limb-trained athletes (1,20,40,60), and four studies included upper limb-trained athletes (20,36,37,59).
Arterial endothelial function
FMD was determined in the included studies in the brachial artery, according to widely used methodological references in the last two decades (6,8,57). Considering the effect of the menstrual cycle phase on FMD (61), studies with a subject pool composed of 50% or more premenopausal females (32,37,44) performed FMD during the early follicular phase in athletes and control women (32,37,44). With regard to technical variations in the FMD procedure (Table 2), 24 studies reported forearm cuff placement and five studies applied upper arm cuff placement (3,32,45,46,50). As for the duration of blood flow occlusion, 23 studies used a 5-min period, whereas six studies reported periods between 4 and 5 min (1,23,27,44,50,56). Peak brachial diameter after cuff deflation (i.e., during hyperemia) was determined via continuous ultrasound scan in 20 studies (1,3,12–14,20,27,36,40,49,50,59,60) and single time point(s) ultrasound scan in seven studies (23,29,32,44–46,56), and one study did not report such information (37). Time to peak brachial diameter after cuff deflation was reported in one study (3). Shear rate parameters were reported in 15 studies (1,20,36,37,40,46,49,59), eight of which presented peak shear rate after cuff deflation (1,37,40,46) and seven presented area under the curve of shear rate until time of peak brachial diameter (20,36,49,59). Baseline brachial diameter ranged from 3.2 to 5.4 mm in the included studies. After data pooling, the meta-analysis revealed that baseline brachial diameter was increased in athletes compared with that in control groups (mean difference, 0.30 mm; P < 0.0001) (Fig. 2). With regard to FMD, values ranged from 1.1% to 17.1% in the included studies. After data pooling, FMD was higher in athletes than that in control groups (SMD, 0.48; P = 0.008) (Fig. 3). In contrast, after data pooling, there was no significant difference between athletes and control groups in NMD (SMD, 0.05; P = 0.72). Significant heterogeneity was found in brachial artery diameter (I2 = 53%; P = 0.001), FMD (I2 = 82%; P < 0.00001), and NMD meta-analysis (I2 = 50%; P = 0.006).
Subgroup and meta-regression analyses
Subgroup analyses were conducted to study heterogeneity of differences in brachial artery parameters between athletes and control groups according to potential moderating factors. Studies in young athletes (<40 yr) presented increased baseline brachial diameter (17 studies; mean difference, 0.40 mm; P < 0.00001) and similar FMD (21 studies; SMD, 0.27; P = 0.22) compared with those in controls (Figs. 2 and 3). In contrast, studies on master athletes (>;50 yr) showed similar baseline brachial diameter (eight studies; mean difference, 0.04 mm; P = 0.69) and increased FMD (eight studies; SMD, 0.99; P = 0.0005) compared with those in controls (Figs. 2 and 3). NMD followed the same pattern of differences as that of FMD between athletes and controls in young and master subjects (Fig. 4). Significant subgroup differences in baseline brachial diameter, FMD, and NMD were found when studies in young and master athletes were grouped and compared with each other (P = 0.003, P = 0.045, and P = 0.04, respectively) (Figs. 2, 3, and 4).
Studies in young athletes were analyzed separately (see Table, Supplemental Digital Content 3, https://links.lww.com/MSS/A389, subgroup analyses of the SMD in FMD between young athletes (<40 yr) and control subjects). The SMD in FMD between young athletes and control groups was significantly lower in studies on subjects ≥23.24 yr than that in subjects <23.24 yr (P = 0.01). Moreover, studies published in 2010 onward differed from those published before 2010 (P = 0.003). No other potential moderating factor (number, gender, height, weight, BMI, SBP, DBP, type of training, sport, primary trained limb, training hours per week, cuff placement, occlusion time, baseline brachial diameter, continuous or single ultrasound scan of peak brachial diameter, hyperemic shear rate, and methodological quality) significantly influenced FMD results in subgroup analyses in young athletes. In meta-regression, age was not significantly associated with SMD in FMD between young athletes and control groups. A significant positive association was found between SMD in NMD and SMD in FMD between young athletes and control groups (B = 1.18, P = 0.00002). Likewise, the difference in height between young athletes and control groups was inversely associated with SMD in FMD between young athletes and control groups (B = −0.19, P = 0.03). In addition, year of publication of studies was inversely associated with SMD in FMD between young athletes and control groups (B = −0.17, P = 0.01).
In studies on master athletes, there was no potential moderating factor significantly influencing FMD results in subgroup analyses (see Table, Supplemental Digital Content 4, https://links.lww.com/MSS/A389, subgroup analyses of the SMD in FMD between master athletes (>;50 yr) and control subjects), although it has to be noted that three potential moderating factors (sport, volume of training, and hyperemic shear rate) were not evaluated because of scarcity of data. In meta-regression, an inverse association was detected between the difference in SBP between master athletes and control groups and SMD in FMD between master athletes and control groups (B = −0.09, P = 0.009).
Quality assessment and potential bias
The quality of the studies, according to a previously validated scale (47,54), was moderate to high. The mean score was 12.8 ± 1.8 out of a possible 16 points (see Table, Supplemental Digital Content 2, https://links.lww.com/MSS/A389, quality assessment of studies included in the meta-analysis). As for the evaluation of potential bias, the Begg and Mazumdar rank correlation test for SMD in FMD in all studies included in the meta-analysis suggested the absence of significant publication bias (P = 0.27). The Egger significance test also showed no significant publication bias (P = 0.43).
In this systematic review and meta-analysis, we pooled and analyzed data from 29 studies comparing FMD of the brachial artery in 530 athletes and 376 control subjects. The main finding of this analysis is that master athletes (>;40 yr of age) but not young athletes (<40 yr of age) had a greater FMD and enhanced smooth muscle function (i.e., NMD) compared with those of age-matched control subjects. These data support the idea that high levels of exercise training can attenuate age-related decline in vascular function.
The observation that differences in vascular function between athletes and age-matched control subjects are found in older but not in young individuals could suggest that the vasculature is not amendable to improvements in vascular function with long-term training, unless impairment is present. That is, when vascular function is near optimal levels, as in the healthy arteries of young subjects, improvements may not occur as a result of a “ceiling effect.” (19,26,38). In contrast, augmented vascular function associated with exercise training may be present in aged arteries where there is “room” for improvement. An alternative explanation for these age-dependent differences in vascular function between athletes and control subjects may be related to differences in baseline brachial artery diameter, as previously proposed by Green et al. (20). Indeed, we found that greater FMD and NMD in master athletes versus those in controls were accompanied by a lack of difference in brachial artery diameter, whereas lack of difference in FMD and NMD in young athletes versus that in controls was accompanied by greater brachial artery diameter in athletes. The finding of an inverse relation between arterial diameter and vascular function is not new (58). In fact, the recognition that artery size can influence the FMD response has prompted recent efforts to statistically normalize FMD to baseline arterial diameter (2). Furthermore, increased baseline brachial diameter might result in decreased shear rate during reactive hyperemia, thus reducing the stimulus for FMD (41). In the present study, young athletes had a larger diameter versus that of young control subjects but hyperemic shear rate did not influence FMD results (see Table, Supplemental Digital Content 3, https://links.lww.com/MSS/A389, subgroup analyses of the SMD in FMD between young athletes (<40 yr) and control subjects). However, not all studies reported shear rate parameters, and of those, several reported the peak shear rate rather than the area under the curve of the shear rate until the time of peak diameter assessment (the latter is recommended as a superior characterization) (57). Therefore, it remains possible that a lower shear rate could have contributed to the “unenhanced” FMD in the young athletes. In older athletes, any role of shear rate in the enhanced FMD response relative to that in controls is unclear because of the scarcity of shear rate data. In addition, given that NMD followed the same pattern as that of FMD and the two were correlated in our analysis, age-related differences in FMD between athletes and control subjects could be, to a certain degree, the result of divergence in smooth muscle function.
An interesting observation of this study was the distinct age-related change of conduit artery size and function in athletes and control subjects. There was a twofold greater age-related difference in FMD in control subjects (weighted mean of 8.17% in young vs 3.38% in older subjects) relative to that in athletes (weighted mean of 8.58% in young vs 6.31% in older subjects). The magnitude of the age-related difference in FMD can be considered clinically relevant because a 1% increase in FMD was associated with up to 13% reduction of cardiovascular events in low-risk and high-risk populations (25,42). On the other hand, the age-related difference in baseline brachial diameter was fivefold greater in control subjects (weighted mean of 4.49 mm in young vs 4.75 mm in older subjects) relative to that in athletes (weighted mean of 4.69 mm in young vs 4.74 mm in older subjects). Taken together, this study suggests an age-related increase in baseline brachial diameter and decrease in FMD, particularly marked in control subjects. In this regard, aging per se has been previously associated with pathological expansive arterial remodeling of the brachial artery (7), reduced shear rate (7), and lower FMD (52). We speculate that in athletes, a less pronounced age-related pathological expansive arterial remodeling may contribute to an attenuated decline in FMD at old age. A question that remains to be addressed is this: if both exercise training and aging cause artery enlargement, why was the combination of the two not associated with larger artery diameter in master athletes relative to that in age-matched controls? Perhaps, there is a ceiling effect and/or an interactive effect of aging and exercise on artery remodeling that requires further experimental investigation.
There are a few limitations in the present meta-analysis that deserve attention. First, the training load experienced by athletes could not be assessed with accuracy. Nevertheless, it can be assumed that young athletes were exposed to higher training loads than those in master athletes. This expected difference in training loads between age groups should be considered in light of previous studies noting that high-intensity, but not mild or moderate, training is associated with increased oxidative stress and a lack of improved endothelium-dependent vasodilation in healthy adults (15). Second, it should be noted that all studies included in this meta-analysis involved measurements performed at the brachial artery. Thus, these findings cannot be applied to other vasculatures. Third, the majority of studies included in the meta-analysis involved (primarily lower limb trained) endurance athletes. However, a small number of studies were composed of strength-trained or racket athletes. Inclusion of these few studies could be considered a limitation, given that vascular adaptations may be specific to the exercise training modality (17,48). However, when pooled and analyzed separately, the SMD in FMD between athletes and controls was not significantly different in studies in strength-trained or racket athletes compared with that in studies in endurance-trained or nonracket athletes, respectively (see Table Supplemental Digital Content 3, https://links.lww.com/MSS/A389, subgroup analyses of the SMD in FMD between young athletes (<40 yr) and control subjects). This suggests that the effects of these different types of training on FMD were similar, although the small number of these studies limits our ability to make definitive modality-specific conclusions. Fourth, endothelial function adaptations may be dependent on variations in training characteristics of periodized training programs commonly followed by athletes to reach peak performance at particular time points during the competitive season. Consequently, the time point at which athletes were assessed could be considered a potential moderating factor, albeit not investigated in this meta-analysis.
Additional limitations to this meta-analysis reside in the fact that cross-sectional comparisons may be misleading when addressing the question of the effect of exercise training (35). Nonetheless, a comprehensive evaluation of the sources of heterogeneity was performed through subgroup and meta-regression analyses. Likewise, considering that our primary outcome was the SMD in FMD between athletes and control groups, we used the difference in study variables between athletes and control groups instead of athlete study variables to search for further moderating factors with accuracy. By these analyses, heterogeneity could be partially explained by differences between athletes and control subjects related to some clinical characteristics, in view of the inverse associations detected between the difference in height or SBP between athletes and control groups and SMD in FMD between athletes and control groups. In addition, we found an association between SMD in FMD in studies in young athletes and the year of publication, which suggests the presence of publication bias in these studies. However, the two tests used to assess potential bias, the Begg and Mazumdar correlation test and the Egger significance test, did not detect significant publication bias (P = 0.27 and P = 0.43, respectively). In this regard, a statistical artifact may result from the division of articles presenting a single control group independently compared with two or more athlete subgroups into several studies (24), which could explain the effect of year of publication on FMD outcomes. Finally, the methodological quality of the included studies was relatively high, particularly when compared with that of a previous meta-analysis of observational studies evaluating brachial artery FMD in a clinical population (54).
The current meta-analysis provides evidence that master athletes but not young athletes exhibit greater FMD compared with that in age-matched control individuals. In addition, we found an enlargement of the brachial artery with aging, with no differences between master athletes and age-matched controls. In contrast, a greater artery diameter was found in young athletes compared with that in their counterparts. Further research is needed to elucidate whether age-dependent differences in FMD between athletes and nonathletes are evidences of a protective effect of high levels of exercise training on arterial aging or an observation that is exclusively dependent on differences in artery size.
The authors have no financial relationships to disclose relevant to this article. The authors have no conflicts of interest to disclose.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Agrotou S, Karatzi K, Papamichael C, et al. Effects of chronic anaerobic training on markers of sub-clinical atherosclerosis. Hellenic J Cardiol
. 2013; 54 (3): 178–85.
2. Atkinson G, Batterham AM, Thijssen DH, Green DJ. A new approach to improve the specificity of flow-mediated dilation for indicating endothelial function in cardiovascular research. J Hypertens
. 2013; 31 (2): 287–91.
3. Ballard KD, Miller JJ, Robinson JH, Olive JL. Aerobic capacity and postprandial flow mediated dilation. Int J Exerc Sci
. 2008; 1 (4): 163–76.
4. Black MA, Cable NT, Thijssen DH, Green DJ. Impact of age, sex, and exercise on brachial artery flow-mediated dilatation. Am J Physiol Heart Circ Physiol
. 2009; 297 (3): H1109–16.
5. Blair SN, Morris JN. Healthy hearts—and the universal benefits of being physically active: physical activity and health. Ann Epidemiol
. 2009; 19 (4): 253–6.
6. Celermajer DS, Sorensen KE, Gooch VM, et al. Non-invasive detection of endothelial dysfunction in children and adults at risk of atherosclerosis. Lancet
. 1992; 340 (8828): 1111–5.
7. Chung WB, Hamburg NM, Holbrook M, et al. The brachial artery remodels to maintain local shear stress despite the presence of cardiovascular risk factors. Arterioscler Thromb Vasc Biol
. 2009; 29 (4): 606–12.
8. Corretti MC, Anderson TJ, Benjamin EJ, et al. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. J Am Coll Cardiol
. 2002; 39 (2): 257–65.
9. DerSimonian R, Laird N. Meta-analysis
in clinical trials. Control Clin Trials
. 1986; 7 (3): 177–88.
10. DeVan AE, Seals DR. Vascular health in the ageing athlete. Exp Physiol
. 2012; 97 (3): 305–10.
11. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis
detected by a simple, graphical test. BMJ
. 1997; 315 (7109): 629–34.
12. Florescu M, Stoicescu C, Magda S, et al. “Supranormal” cardiac function in athletes related to better arterial and endothelial function. Echocardiography
. 2010; 27 (6): 659–67.
13. Franzoni F, Ghiadoni L, Galetta F, et al. Physical activity, plasma antioxidant capacity, and endothelium-dependent vasodilation in young and older men. Am J Hypertens
. 2005; 18 (4 Pt 1): 510–6.
14. Galetta F, Franzoni F, Plantinga Y, et al. Ambulatory blood pressure monitoring and endothelium-dependent vasodilation in the elderly athletes. Biomed Pharmacother
. 2006; 60 (8): 443–7.
15. Goto C, Higashi Y, Kimura M, et al. Effect of different intensities of exercise on endothelium-dependent vasodilation in humans: role of endothelium-dependent nitric oxide and oxidative stress. Circulation
. 2003; 108 (5): 530–5.
16. Green D. Enhanced conduit artery flow-mediated dilation in elite athletes: false or reality? Author reply. Med Sci Sports Exerc
. 2013; 45 (6): 1220.
17. Green DJ, Bilsborough W, Naylor LH, et al. Comparison of forearm blood flow responses to incremental handgrip and cycle ergometer exercise: relative contribution of nitric oxide. J Physiol
. 2005; 562 (Pt 2): 617–28.
18. Green DJ, Dawson EA, Groenewoud HM, Jones H, Thijssen DH. Is flow-mediated dilation nitric oxide mediated?: a meta-analysis
. 2014; 63 (2): 376–82.
19. Green DJ, Maiorana A, O’Driscoll G, Taylor R. Effect of exercise training on endothelium-derived nitric oxide function in humans. J Physiol
. 2004; 561 (Pt 1): 1–25.
20. Green DJ, Rowley N, Spence A, et al. Why isn’t flow-mediated dilation enhanced in athletes? Med Sci Sports Exerc
. 2013; 45 (1): 75–82.
21. Green DJ, Spence A, Rowley N, Thijssen DH, Naylor LH. Vascular adaptation in athletes: is there an ‘athlete’s artery’? Exp Physiol
. 2012; 97 (3): 295–304.
22. Green DJ, Swart A, Exterkate A, et al. Impact of age, sex and exercise on brachial and popliteal artery remodelling in humans. Atherosclerosis
. 2010; 210 (2): 525–30.
23. Hagmar M, Eriksson MJ, Lindholm C, Schenck-Gustafsson K, Hirschberg AL. Endothelial function in post-menopausal former elite athletes. Clin J Sport Med
. 2006; 16 (3): 247–52.
24. Higgins JPT, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]
. The Cochrane Collaboration; 2011. Available from: www.cochrane-handbook.org
. Accessed 25 August 2013.
25. Inaba Y, Chen JA, Bergmann SR. Prediction of future cardiovascular outcomes by flow-mediated vasodilatation of brachial artery: a meta-analysis
. Int J Cardiovasc Imaging
. 2010; 26 (6): 631–40.
26. Jasperse JL, Laughlin MH. Endothelial function and exercise training: evidence from studies using animal models. Med Sci Sports Exerc
. 2006; 38 (3): 445–54.
27. Jensen-Urstad K, Bouvier F, Jensen-Urstad M. Preserved vascular reactivity in elderly male athletes. Scand J Med Sci Sports
. 1999; 9 (2): 88–91.
28. Joyner MJ, Green DJ. Exercise protects the cardiovascular system: effects beyond traditional risk factors. J Physiol
. 2009; 587 (Pt 23): 5551–8.
29. Kasikcioglu E, Oflaz H, Kasikcioglu HA, Kayserilioglu A, Umman S, Meric M. Endothelial flow-mediated dilatation and exercise capacity in highly trained endurance athletes. Tohoku J Exp Med
. 2005; 205 (1): 45–51.
30. Laughlin MH. Endothelium-mediated control of coronary vascular tone after chronic exercise training. Med Sci Sports Exerc
. 1995; 27 (8): 1135–44.
31. Laughlin MH, Newcomer SC, Bender SB. Importance of hemodynamic forces as signals for exercise-induced changes in endothelial cell phenotype. J Appl Physiol (1985)
. 2008; 104 (3): 588–600.
32. Moe IT, Hoven H, Hetland EV, Rognmo O, Slørdahl SA. Endothelial function in highly endurance-trained and sedentary, healthy young women. Vasc Med
. 2005; 10 (2): 97–102.
33. Montero D, Obert P, Walther G. Enhanced conduit artery flow-mediated dilation in elite athletes: false or reality? [corrected]. Med Sci Sports Exerc
. 2013; 45 (6): 1219.
34. Mora S, Cook N, Buring JE, Ridker PM, Lee IM. Physical activity and reduced risk of cardiovascular events: potential mediating mechanisms. Circulation
. 2007; 116 (19): 2110–8.
35. Naylor LH, George K, O’Driscoll G, Green DJ. The athlete’s heart: a contemporary appraisal of the ‘Morganroth hypothesis’. Sports Med
. 2008; 38 (1): 69–90.
36. Naylor LH, O’Driscoll G, Fitzsimons M, Arnolda LF, Green DJ. Effects of training resumption on conduit arterial diameter in elite rowers. Med Sci Sports Exerc
. 2006; 38 (1): 86–92.
37. Nualnim N, Barnes JN, Tarumi T, Renzi CP, Tanaka H. Comparison of central artery elasticity in swimmers, runners, and the sedentary. Am J Cardiol
. 2011; 107 (5): 783–7.
38. Padilla J, Newcomer SC, Simmons GH, Kreutzer KV, Laughlin MH. Long-term exercise training does not alter brachial and femoral artery vasomotor function and endothelial phenotype in healthy pigs. Am J Physiol Heart Circ Physiol
. 2010; 299 (2): H379–85.
39. Petersen SE, Wiesmann F, Hudsmith LE, et al. Functional and structural vascular remodeling in elite rowers assessed by cardiovascular magnetic resonance. J Am Coll Cardiol
. 2006; 48 (4): 790–7.
40. Phillips SA, Das E, Wang J, Pritchard K, Gutterman DD. Resistance and aerobic exercise protects against acute endothelial impairment induced by a single exposure to hypertension during exertion. J Appl Physiol (1985)
. 2011; 110 (4): 1013–20.
41. Pyke KE, Tschakovsky ME. Peak vs. total reactive hyperemia: which determines the magnitude of flow-mediated dilation? J Appl Physiol (1985)
. 2007; 102 (4): 1510–9.
42. Ras RT, Streppel MT, Draijer R, Zock PL. Flow-mediated dilation and cardiovascular risk prediction: a systematic review with meta-analysis
. Int J Cardiol
. 2013; 168 (1): 344–51.
43. Rickenlund A, Eriksson MJ, Schenck-Gustafsson K, Hirschberg AL. Amenorrhea in female athletes is associated with endothelial dysfunction and unfavorable lipid profile. J Clin Endocrinol Metab
. 2005; 90 (3): 1354–9.
44. Rickenlund A, Eriksson MJ, Schenck-Gustafsson K, Hirschberg AL. Oral contraceptives improve endothelial function in amenorrheic athletes. J Clin Endocrinol Metab
. 2005; 90 (6): 3162–7.
45. Rinder MR, Spina RJ, Ehsani AA. Enhanced endothelium-dependent vasodilation in older endurance-trained men. J Appl Physiol (1985)
. 2000; 88 (2): 761–6.
46. Rognmo O, Bjornstad TH, Kahrs C, et al. Endothelial function in highly endurance-trained men: effects of acute exercise. J Strength Cond Res
. 2008; 22 (2): 535–42.
47. Ross LE, Grigoriadis S, Mamisashvili L, et al. Quality assessment of observational studies in psychiatry: an example from perinatal psychiatric research. Int J Methods Psychiatr Res
. 2011; 20 (4): 224–34.
48. Rowley NJ, Dawson EA, Birk GK, et al. Exercise and arterial adaptation in humans: uncoupling localized and systemic effects. J Appl Physiol (1985)
. 2011; 110 (5): 1190–5.
49. Rowley NJ, Green DJ, George K, et al. Peripheral vascular structure and function in hypertrophic cardiomyopathy. Br J Sports Med
. 2012; 46: 98–103.
50. Rywik TM, Blackman MR, Yataco AR, et al. Enhanced endothelial vasoreactivity in endurance-trained older men. J Appl Physiol (1985)
. 1999; 87 (6): 2136–42.
51. Sindler AL, Reyes R, Chen B, et al. Age and exercise training alter signaling through reactive oxygen species in the endothelium of skeletal muscle arterioles. J Appl Physiol (1985)
. 2013; 114 (5): 681–93.
52. Skaug EA, Aspenes ST, Oldervoll L, et al. Age and gender differences of endothelial function in 4739 healthy adults: the HUNT3 Fitness Study. Eur J Prev Cardiol
. 2013; 20 (4): 531–40.
53. Spence AL, Carter HH, Naylor LH, Green DJ. A prospective randomized longitudinal study involving 6 months of endurance or resistance exercise. Conduit artery adaptation in humans. J Physiol
. 2013; 591 (Pt 5): 1265–75.
54. Sprung VS, Atkinson G, Cuthbertson DJ, et al. Endothelial function measured using flow-mediated dilation in polycystic ovary syndrome: a meta-analysis
of the observational studies. Clin Endocrinol (Oxf)
. 2013; 78 (3): 438–46.
55. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis
of observational studies in epidemiology: a proposal for reporting. Meta-analysis
of observational studies in epidemiology (MOOSE) group. JAMA
. 2000; 283 (15): 2008–12.
56. Tanriverdi H, Evrengul H, Tanriverdi S, et al. Improved endothelium dependent vasodilation in endurance athletes and its relation with ACE I/D polymorphism. Circ J
. 2005; 69 (9): 1105–10.
57. Thijssen DH, Black MA, Pyke KE, et al. Assessment of flow-mediated dilation in humans: a methodological and physiological guideline. Am J Physiol Heart Circ Physiol
. 2011; 300 (1): H2–12.
58. Thijssen DH, Dawson EA, Black MA, Hopman MT, Cable NT, Green DJ. Heterogeneity in conduit artery function in humans: impact of arterial size. Am J Physiol Heart Circ Physiol
. 2008; 295 (5): H1927–34.
59. Walther G, Nottin S, Karpoff L, Pérez-Martin A, Dauzat M, Obert P. Flow-mediated dilation and exercise-induced hyperaemia in highly trained athletes: comparison of the upper and lower limb vasculature. Acta Physiol (Oxf)
. 2008; 193 (2): 139–50.
60. Welsch MA, Blalock P, Credeur DP, Parish TR. Comparison of brachial artery vasoreactivity in elite power athletes and age-matched controls. PLoS One
. 2013; 8 (1).
61. Williams MR, Westerman RA, Kingwell BA, et al. Variations in endothelial function and arterial compliance during the menstrual cycle. J Clin Endocrinol Metab
. 2001; 86 (11): 5389–95.