Interventional effects of different track and field sports on human cardiovascular function indicators and physiological energy metabolism.

Abstract

Objective: To analyze the effects of different track and field events on human cardiovascular function and physiological energy metabolism.

Method: The research subjects were ordinary male students majoring in physical education at a certain university, aged between 18 and 25 years old. A total of 42 people were divided into four sub sample groups: sprint group (10 people), jump group (10 people), long-distance running group (10 people), and regular student group (12 people). The COSMED K5 portable gas metabolism analysis system was used to measure cardiopulmonary function, and key indicators such as Maximum Oxygen Uptake (VO₂max) were evaluated using a Stepwise Increasing Load Test (SILT). The two factor repeated measures ANOVA method was used to analyze the effects of different load levels and groups on cardiopulmonary function and energy metabolism.

Result: The weight, systolic blood pressure, and diastolic blood pressure of different populations were not statistically significant in a quiet state (p > 0.05). The waist to hip ratios of the short-distance and long-distance running teams were 0.75 ± 0.03 and 0.76 ± 0.03, respectively, which showed significant differences compared to ordinary students (p < 0.05). There was also a significant difference in heart rate between different track and field teams and ordinary students in a quiet state (p < 0.05). The termination load of different track and field teams varied, with the long-distance running team having the highest load (p < 0.01), followed by the jumping team. Compared with ordinary students, there was a significant difference (p < 0.05) in the termination heart rate among the sprinting, long-distance, and jumping teams. However, there was p > 0.05 in the systolic blood pressure index among the four groups of subjects. There was a significant difference (p < 0.05) in diastolic blood pressure between sprinting and jumping teams and ordinary students. In a quiet state, the energy metabolism of long-distance running teams, sprinting teams, jumping teams, and ordinary students was 1.52 ± 0.64, 1.81 ± 0.91, 1.86 ± 0.87, and 2.87 ± 0.96, respectively.

Conclusion: In a quiet state, there are significant differences in body shape and function between different track and field training teams and the general population. In a quantitative load state, long-distance runners have the strongest adaptability to load.