Physiology of Exercise of the Female.

Previous physiological studies of exercise have been mainly concerned with male subjects. The present study investigated physiological responses of trained and untrained female subjects to submaximal work increasing to exhaustion on a bicycle ergometer. Differences in physiological functions between three groups of females, consisting of sedentary subjects, physical education students and trained athletes were considered in relation to their physiological efficiency. A longitudinal study of female physical education students was used to evaluate the importance of training on physiological functions determining maximal power output. Intensive training increased cardiorespiratory efficiency and influenced blood plasma constituents. Study of the relationship between cardiorespiratory and haematological responses to exercise involved the assessment of changes in 12 cardiorespiratory parameters, 2 serum electrolytes, 4 serum ensymes, 10 blood constituents, blood gas and acid-base parameters. Prediction of maximal oxygen uptake from submaximal heart rate measurements was unreliable. Results demonstrated that heart rate was a good reference for cardiae output, maximal oxygen uptake for power output, venous lactate for anaerobic work capacity and that low blood pH at exhaustion may affect the rate of anaerobic glycolysis. Blood gas changes at exhaustion indicated a decrease in arterio-venous oxygen difference, with inefficient carbon dioxide removal and acid-base parameters demonstrated respiratory compensation for metabolic acidosis. Neither haemoglobin nor total protein measurements were accurate indicators of haemoconcentration, and conclusions concerning changes in plasma concentrations induced by exercise, may lead to erroneous interpretation. The effect of exercise in decreasing blood urea and elevating serum enzyme levels and cell counts was demonstrated, and plasma potassium levels increased more significantly than sodium ions. The variables and subjects were classified into sets or clusters using a Principal Components Analysis, and it was found that fundamental parameter could be extracted empirically by using this technique