Effects of viral upper respiratory illness on running gait.

OBJECTIVE: To determine the kinematic changes that may occur during running with a cold of known etiology and to assess the impact of select accompanying upper respiratory illness symptoms. DESIGN AND SETTING: In this nonrandomized study, subjects with colds and subjects without colds were videotaped while exercising on a treadmill. Three weeks later, the trials were repeated. SUBJECTS: Eighteen young adults (5 females, 13 males; mean age = 20.4+/- 2.4 yr) with naturally acquired moderate to severe (total symptom score) colds were screened and selected for inclusion in the illness group (ILL). A control group (CRL) of 20 subjects (2 females, 18 males) was also examined. Virologic confirmation of specific viral infections, unprecedented in this line of research, revealed that 12 of the 18 subjects in the ILL group (67%) were infected with human rhinoviruses. None of the subjects had a fever. MEASUREMENTS: All subjects exercised on a treadmill for 5 minutes at a heart rate of approximately 85% of their age-predicted maximum. Both groups were videotaped kinematically during two running trials 3 weeks apart. All subjects in the ILL group displayed upper respiratory illness symptoms for the first running trial and were asymptomatic by the second. RESULTS: We identified significant differences in mean changes between the ILL and CRL group stride lengths (p <.01), stride frequencies (p <.05), and ankle maximum angle displacement (p <.01). Mean changes in stride length (p <.03) and in stride frequency (p <.04) were larger for ILL subjects who felt feverish. CONCLUSIONS: Alterations in running gait during a rhinovirus-caused upper respiratory illness, and possibly increases in injury incidence, may be associated with feeling feverish. Gait alterations may increase injury incidence or decrease athletic performance, or both.

Evaluation of the ACSM submaximal ergometer test for estimating VO2max.

The purpose of this investigation was to assess the reliability and validity of maximal oxygen uptake estimates (ESTmax) from the ACSM submaximal cycle ergometer test. Subjects included 15 men and 15 women aged 21-54 yr who performed two submaximal tests and one maximal cycle ergometer test to determine maximal oxygen uptake (VO2max). During the submaximal tests, heart rates (HR) were recorded from a radio telemetry monitor. ESTmax was predicted for both submaximal trials by extrapolating HR to an age-predicted maximal HR. Correlation coefficient and standard error of measure (SEmeas) for ESTmax between submaximal trials were r = 0.863 and SEmeas = 0.40 l.min-1, while a t-test revealed no significant difference between trials. Although trial means were not significantly different, large variation in individual cases was evident by the high SEmeas (0.40 l.min-1) and by a large SEmeas expressed as a percentage of the mean (13%). The mean of the two ESTmax significantly overestimated measured VO2max with percent error, total error, and mean error equal to 25.7%, 0.89 l.min-1, and 0.63 l.min-1, respectively. The standard error of estimate expressed as a percentage of the mean was equal to 16% and 15% for both ESTmax. In summary, the ACSM protocol failed to be reliable as represented by the large differences found between submaximal trials. Furthermore, the protocol significantly overestimates VO2max and should not be used when an accurate assessment of VO2max is required.

Failure of predicted VO2peak to discriminate physical fitness in epidemiological studies.

Previous investigators reported that peak oxygen uptake (VO2peak) could be accurately predicted from nonexercise test variables, and that this score would be suitable for categorizing cardiorespiratory fitness (CRF) within epidemiological studies. However, the accuracy of these models has varied considerably. The purposes of this study were: 1) assess the accuracy of predicting VO2peak with a new nonexercise model, and 2) assess the utility of the predicted VO2peak for categorizing CRF in epidemiological studies. Subjects included 2,350 men and women. Cross-validated multiple regression models revealed that age, sex, resting heart rate, body weight, percentage body fat, smoking, and physical activity were significant predictors (P < 0.001) of VO2peak. The multiple regression model for relative VO2peak (ml.kg-1.min-1) had R2 = 0.733 (SEE = 5.38), whereas the model for absolute VO2peak (l.min-1) had R2 = 0.773 (SEE = 0.425). The 95% confidence intervals for the predicted VO2peak were large (+/- 10.6 ml.kg-1.min-1 and +/- 0.833 l.min-1). These results support the notion that VO2peak can be predicted from a multiple regression model devoid of exercise test variables. However, due to the extreme variability in the predicted scores, the regression models were unable to effectively distinguish CRF categories. Therefore, despite statistical success in predicting VO2peak for the nonexercise test regression models, we conclude that such models fail to provide the accuracy needed for categorizing CRF within large epidemiological cohorts where the purpose is to assess mortality risk.

Influence of metabolic control on the ventilatory threshold in adults with non insulin-dependent diabetes mellitus.

Metabolic control, as assessed by glycosylated hemoglobin (HbA1c), has been reported to have a relationship to various submaximal exercise responses. However, due to the narrow range of HbA1c and the limited exercise data from previous studies on individuals with diabetes, little support for the above statement exists in the literature. The current study assessed the relationship between HbA1c and submaximal, or ventilatory threshold (VT), and maximal exercise (VO2 peak) responses in subjects with non-insulin-dependent diabetes mellitus (NIDDM). Sixteen subjects (age = 56.5 +/- 14.4 yrs; Wt = 82.6 +/- 17.2 kg; B.M.I. = 29.5 +/- 2.7 kg.m-2) performed a ramp (20 watts.min-1) leg cycle ergometer test (GXT). Their HbA1c was 11.8 +/- 2.8% (range 6.5 to 16.6%). Breath by breath respiratory analysis was performed using a Med Graphics 2001 cart. Ventilatory threshold (VT) was determined using the V-slope method. The VT was 1,151 +/- 487 ml.min-1 or 70.2 +/- 10% VO2peak; VO2peak was 1,645 +/- 740 ml.min-1. There were no significant relationships found between HbA1c and the VO2 at the VT (r = 0.04), the % of VO2peak at the VT (r = 0.23), and the VO2peak (r = 0.17). In conclusion, metabolic control, as assessed by HbA1c, did not influence selected submaximal and maximal exercise responses in NIDDM. Therefore, exercise prescription for individuals with NIDDM may not need to consider the individual's HbA1c concentration as a modifier of their exercise response.

Predictors of over- and underachievement of age-predicted maximal heart rate.

The age-predicted maximal heart rate (PMHR) formula, 220--age, is frequently used for identifying exercise training intensity, as well as determining endpoints for submaximal exercise testing. This study was designed to identify variables discriminating those with actual maximal heart rates considerably above or below that predicted from the 220--age equation. Subjects included 2010 men and women ranging in age from 14 to 77 yr. Stepwise discriminant analysis was performed using maximal heart rate error groups as the dependent variable, and selected preexercise test characteristics as predictors. The HR error groups were based on the difference between the measured and PMHR as follows: below (> or = 15 beats.min-1 below PMHR), within (+/- 14 beats.min-1 of PMHR), and above (> or = 15 beats.min-1 above PMHR). A contrast of the below and above groups identified age, resting HR, body weight, and smoking status as predictors of group membership (P < 0.01) for both men and women. The overall canonical correlation was 0.282 and 0.294 for the men and women, respectively. Older age, higher resting HR, lower weight, and non-smoking were related to the above group, while the inverse was related to the below group. Standardized coefficients suggest that age and resting heart rate for the men, and age and smoking status for the women were the most potent variables for discriminating extreme deviations between measured and PMHR.(ABSTRACT TRUNCATED AT 250 WORDS)