Resistance Exercise Modify Cardiovascular Responses of Professors During Teaching and Sleep

Overview

Both work activity and reduced nocturnal dipping of blood pressure are related to increased cardiovascular risk. The aim of the present study was to assess the hemodynamic and autonomic responses of university professors during teaching and sleeping times after different resistance exercise intensities. Ten normotensive professors (33.6±3.4 years, 82.4±12.4 kg; 177.0±7.5 cm) randomly underwent control and resistance exercise before initiating their daily activities. Resistance exercise consisted of a circuit training lasting 40min at 40% and 80% of one repetition maximum test. Systolic blood pressure and diastolic blood pressure as well as heart rate variability indicators in the time and frequency domains (Low Frequency, High Frequency, Low Frequency:High Frequency ratio) were evaluated on resting and 24 hours after the sessions. The average day-time, night-time and nocturnal blood pressure fall of systolic blood pressure and diastolic blood pressure were calculated.

Experimental Procedure To test the hypothesis of the present study, after the evaluation of anthropometric characteristics, an interview covering medical history and habits of daily living and a strength assessment using the one maximum repetition test, consisting of another three distinct experimental sessions for a period of seven days each and always at the same time of the day and in random order, were applied to university professors. The interventions during each experimental session consisted of resistance exercise with intensities of 40% one maximum repetition (low intensity), 80% one maximum repetition (high intensity) and control without exercise. Before and 24 hours after the different interventions, with emphasis on the teaching and sleeping hours of the university professors, the hemodynamic and cardiac autonomic responses were examined. Experimental Sessions The participants were told to avoid the intake of alcohol and caffeine in the 24 hours prior to the experimental sessions. In addition, for this same period, the participants were asked to not perform moderate or vigorous physical activity. The experimental sessions were performed in random order and were separated by a period of seven days each, from 9 to 10 am. All sessions were performed on days the professor taught class, which occurred during the university's night period, between 7 and 10 pm. In the three experimental sessions, the professor taught the same class and the same subject. Pre-intervention: Before each intervention, the individuals remained seated in the laboratory for a period of 20 minutes in a quiet room without interference from noise and with a room temperature between 22-24ºC. During this period, every 5 minutes, blood pressure measurements were obtained, and the R-R intervals (the elapsed time between two consecutive R waves between cardiac cycles) were continuously recorded. The mean blood pressure and indicators of heart rate variability based on the R-R interval records were considered for the pre-intervention resting period. Intervention: The resistance exercise intensities were defined based on previous studies. These studies found that both low intensity (40% one maximum repetition) and high intensity (80% one maximum repetition) resistance exercise sessions promoted positive blood pressure responses at periods subsequent to their execution in normotensive individuals. The low intensity and high intensity resistance exercise and control sessions lasted 40 minutes each. For sessions with resistance exercise, three circuits with 7 exercises each were performed in the same sequence of the one maximum repetition test. For low intensity and high intensity, 16 and 8 repetitions were performed for each exercise, with an interval of 60 and 90 seconds between exercises, respectively, and 120 seconds between circuits. The duration of repetition in the exercises, both at low intensity and high intensity, was 3 seconds - 1 second in the concentric phase and 2 seconds in the eccentric phase of the movement. In the control session, the participants remained seated in a comfortable chair in the same environment of the resistance exercise sessions. Post-intervention: When the intervention periods were completed, the participants were allowed to bathe for subsequent installation of the equipment for hemodynamic and cardiac autonomic assessment. The blood pressure monitoring was performed in the subsequent 24 hours, every 15 minutes during the day and every 30 minutes during the night. The R-R interval records were continuously obtained in the subsequent 24 hours. At the end of the 24 hours period, the volunteers returned to the laboratory for removal of the measuring equipment. In the ambulatory blood pressure monitoring, the tests were considered valid when records occurred with more than 80% validity. Hemodynamic and Autonomic Evaluation All participants were instructed to maintain their daily eating routine on the day of the hemodynamic and autonomic evaluation. A Meditech Ambulatory Blood Pressure Monitoring-04, properly validated, was used for the hemodynamic assessment of systolic blood pressure and diastolic blood pressure in the pre- and post-intervention periods. A Polar® RS800CX frequency meter (Electo Oy, Kempele, Finland), also with demonstrated validity and reproducibility, was used for the cardiac autonomic assessment during the same period. The autonomic indicators examined were 1) linear methods in the time domain from absolute mean records of the R-R interval; and 2) methods in the frequency domain by spectral analysis through Fast Fourier Transform, including low frequency power (0.04/0.15 Hz) in normalized units as a marker of sympathetic activity, high frequency power (0.15/0.40 Hz) in normalized units as a marker of vagal activity, and the low frequency:high frequency ratio as a marker of the sympathetic-vagal balance. All indicators are described by the European Society of Cardiology, and all analyses were performed using the software Kubios Heart Rate Variability Analysis version 2.0 (Biosignal Laboratory, University of Kuopio, Finland). All variables were analyzed pre-intervention and for 24 hours post-intervention. In addition, the day time and night time periods were adopted to calculate, from the systolic blood pressures and diastolic blood pressures, the mean blood pressure during the day time (wakefulness) and night time (sleep) hours. The percentage of nocturnal blood pressure fall was calculated from the percentage of blood pressure reduction during night-time compared to day time (night time:day time ratio). The morning blood pressure surge that corresponds to the morning increase in blood pressure and is calculated according to the difference between morning pressure (the average blood pressure during the 2 hours after awakening) and the lowest night time blood pressure (the average of the lowest blood pressure and the 2 readings immediately preceding and after the lowest value) were also analyzed. Statistical Analysis Descriptive statistics with means and standard deviations or standards error of means were adopted. All variables are presented in absolute variations (Δ = the difference between the baseline and various times after session). Mathematical procedures to calculate the percentage blood pressure fall and morning blood pressure surge were performed. Data normality was verified through an exploratory analysis using the Shapiro-Wilk test. Two-way repeated-measures analysis of variance was applied, reporting "F-ratio" and "p-value" to check the main interaction effects of time by session (time\*session) and of time (time). When statistically significant effects were found, a post-hoc Tukey test was adopted for multiple comparisons, and the "p" values were reported. Initially, the variable low-frequency:high-frequency ratio had a non-normal distribution; however, the natural logarithmic transformation was performed for scale adjustments to meet the normal distribution model. The significance level used in the study was p\<0.05, and the software programs used were BioEstat v. 5.3 and Statistica® v. 7.0.