Authors: Brun, J.F. | Bouchahda, C. | Chaze, D. | Aïssa Benhaddad, A. | Micallef, J.P. | Mercier, J.
Article Type:
Research Article
Abstract:
The paradox of hematocrit in exercise physiology is that artificially increasing it by autotransfusion or erythropoietin doping improves VO2 max and performance, while in normal conditions there is a strong negative correlation between hematocrit and fitness, due to a training‐induced “autohemodilution”. We aimed at investigating: (a) which is the physiological range of hematocrit in highly trained professional footballers; (b) what are the characteristics of athletes with high vs low hematocrit? We determined in 77 healthy male footballers the physiological range (mean±sd) of hematocrit: 42.3±2.74, (range −2σ/+2σ=36.8–47.8%) thus defining boundaries of quintiles of distribution for this parameter: 40, 41.6, 42.9,
…44.6. In another sample of 42 male footballers we compared three groups: lowest quintile (n=8), highest quintile (n=5) and the three middle quintiles considered together (n=29). Athletes in the lowest quintile compared to those in the four other quintiles had a lower value of blood viscosity (−8%, p<0.01) but this difference disappeared after correction for hematocrit. These subjects with low hematocrit had also higher values of the following parameters: aerobic working capacity (p<0.01); isometric adductor strength (p=0.02); crossover point of carbohydrate oxidation (70% carbohydrates/30% lipids) (p<0.05); insulin like growth factor binding protein 1 (p<0.0001). Athletes in the highest quintile had higher red cell aggregability (Myrenne index “M1” 8.45±0.38 vs 6.82±0.62, p<0.04) and a higher disaggregability threshold γD (72.6±22.63 vs 44.49±1.37, p<0.01) and a lower percentage of water in fat‐free mass (p<0.02). On the whole sample hematocrit was negatively correlated with aerobic working capacity (W170 r=−0.329, p=0.007; Wmax (% of expected value) r=−0.552, p=0.008; VO2 max (% of expected value) r=−0.543, p=0.009) and with ferritin (r=−0.33, p=0.031), and positively correlated with the overtraining score (r=0.352, p=0.019) which was in turn negatively correlated with ferritin r=−0.312, p=0.02). Besides, hematocrit behaves as a major determinant of blood viscosity (correlation with blood viscosity r=0.997, p<10−7 ) and erythrocyte disaggregability γD (r=0.384, p=0.03), but the hematocrit/viscosity ratio (h/η index of O2 delivery) remains maintained almost constant over the range of values studied. These results show that (a) physiological values of hematocrit in these athletes are comprised between 36 and 48%; (b) “low” hematocrit (<40%) was associated with a higher aerobic capacity; (c) subjects with the higher hematocrits (>44.6%) were frequently overtrained and/or iron‐deficient, and their blood viscosity (and red cell disaggregability) tended to be increased.
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Keywords: Hematocrit, blood viscosity, hemorheology, erythrocyte deformability, human, male, exercise training, overtraining, body fluids, lipid oxidation, glucose oxidation
Citation: Clinical Hemorheology and Microcirculation,
vol. 22, no. 4, pp. 287-303, 2000
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