When groups of athletes were considered separately, age, body mass, FM, and FFM were significantly associated with leptin in ET (all P < 0.05) but not in RT-athletes. Factor 1, factor 2, and SAT were significantly correlated to leptin in both groups. The magnitude of these relationships were greater in RT-athletes. Metabolic parameters were correlated to leptin only in RT-athletes (all P < 0.05).
The first model included age and estimates of adiposity. However, only %FM contributed significantly to log leptin (adj. R2 = 0.195). The next model included %FM and metabolic parameters, because metabolic parameters were associated with leptin in RT-athletes. Nonetheless, %FM had the same slope as in the previous model and remained as the main determinant. In the final model, factor 1, factor 2 and SAT were added. All estimates of subcutaneous fat were significantly associated with log leptin but only SAT remained as an independent determinant for log leptin (adj. R2 = 0.52, P < 0.0001). Because each SAT-layer was significantly correlated to log leptin, we also tested whether certain SAT-layers contribute to log leptin. The best model explained almost 50% of the variance, and included SAT-layer 6-lateral chest (adj. R2 = 0.497, P < 0.0001, not shown).
We investigated endurance- (ET) and resistance-trained (RT) athletes to study the relationship between leptin, measures of adiposity, and metabolic parameters. ET-athletes were long-distance runners and cross-country skiers, whereas RT-athletes came from different sports in which strength training is of fundamental importance. We did not rely on weight- and power-lifters or body-builders because we wanted to exclude possible downregulating effects of anabolic-steroids on leptin (8,29). Unfortunately, we did not measure testosterone, but there were no differences in leptin, glucose, insulin, and insulin resistance, indicating that the metabolic status did not differ between the two group of athletes (Table 1).
Body mass was higher in RT-athletes but not FFM. It is unlikely that differences in the water content of FFM between athletes (22) were responsible for this because total body water, extra-, and intra-cellular volume were not different between groups (data not shown). However, we measured FFM by means of impedance at a single frequency, and despite methodological concern it is also possible that the equation used (21) was not the most accurate one to predict FFM of Estonian male athletes. Another possible explanation for the finding that FFM was not greater in RT-athletes is that these subjects cannot be completely described as resistance-trained athletes because their training also included endurance exercises.
However, RT-athletes had a greater fat mass (FM), percentage FM (%FM), and overall subcutaneous fat (SAT;P = 0.052), which suggests that their greater adiposity might be due to greater SAT and (or) greater amount of visceral fat, which was not measured in the present study. We used an optical device (Lipometer) to measure the thickness of different subcutaneous fatty layers (SAT-layers) and calculated SAT by linear addition of these SAT-layers. Although this is a simple approach to calculate SAT, this might be applicable because 1) SAT-layers are distributed over the whole body and 2) because of the use of a larger number of measurement sites (N = 15) when compared with skinfolds to estimate SAT (19). However, the Lipometer measures a subcutaneous monolayer, and any comparison with skinfolds should be made with caution.
FFM was related to leptin in ET- but not RT-athletes. A greater amount of FFM contributes to leptin in male subjects (2) and in obese boys (23). The role of FFM in the regulation of leptin in humans is unclear, but regular training increases insulin sensitivity in skeletal muscle in endurance- but not resistance-athletes (26). We found a relationship between insulin, insulin resistance, and leptin in RT-athletes, perhaps reflecting some specific adaptations at the level of the FFM in response to training, which in turn could influence circulating leptin. However, we calculated insulin resistance by the fasting insulin resistance index, which is not a state of the art approach to estimating insulin resistance and sensitivity. Notwithstanding this, body mass, BMI, FM, and %FM were not correlated to leptin in RT-athletes. Because of this and, due to the significant relationship between leptin and metabolic parameters in RT-athletes, the regulation of leptin might also depend on factors at the metabolic level associated with certain training regimens.
The main influence of SAT on leptin was further confirmed by stepwise regression (Table 3). We adjusted for group differences between athletes, but SAT remained as the strongest predictor of leptin regardless of other independent determinants. A similar finding was obtained in women, in particular due to a certain mass effect of subcutaneous adipocytes on the expression rate of leptin (28). However, this is the first study which reports that SAT is an independent determinant for leptin in male athletes. Because SAT requires the measurement of 15 SAT-layers, we also tested the possibility that certain SAT-layers contribute to leptin (24,25). When SAT-layers were considered in different stepwise regression models (not shown), SAT-layer 6-lateral chest explained almost the same variance of leptin (∼50%) as SAT (52%) did. Whether this suggests that this SAT-layer from the trunk reflects SAT and (or) some kind of central fat patterning, needs to be studied in detail.
It is also possible that leptin is acutely regulated in adipocytes by surrounding hormones (20). Catecholamines were shown to suppress leptin release from differentiated human subcutaneous adipocytes, mediated via beta (1) - and beta (2) -adrenergic receptors (20). In athletes during long-term training, the definitive signal for the reduction in leptin may be linked to prolonged beta-3-adrenoceptor stimulation (27). Therefore, we cannot rule out the possibility that our findings of an independent influence of SAT on leptin in athletes is secondarily and most probably indirectly via beta-3-stimulation to SAT and (or) leptin is also acutely regulated independently from alterations in SAT. It clearly remains to be shown whether leptin is under a strong influence of SAT in ET- and RT-athletes regardless of their metabolic and hormonal status.
In conclusion, the present study shows that metabolic parameters and estimates of adiposity are associated with leptin in a sport-specific manner, and overall subcutaneous fatness was found to be the main determinant for leptin in endurance- and resistance-trained athletes.
Address for correspondence: Dr. Karl Michael Sudi, Institute for Sport Sciences, Karl-Franzens University, Mozartgasse 14, 8010 Graz, Austria; E-mail: Karl.Sudi@kfunigraz.ac.at.
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