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  • 1
    Publication Date: 1980-11-01
    Print ISSN: 0003-2697
    Electronic ISSN: 1096-0309
    Topics: Biology , Chemistry and Pharmacology
    Published by Elsevier
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  • 2
    Publication Date: 2019-07-19
    Description: The physical activity guidelines (PAG) established by the US Dept. of Health and Human Services in 2008 is consistent with a rating of 〉/= 6 on the 11-point NASA Physical Activity Status Scale (PASS). Wier, et. al. developed non-exercise models for estimating VO2(sub max) from a combination of PASS, age, gender and either waist girth (WG) (R = 0.810, SEE= 4.799 ml/kg/min), %Fat (R = 0. 817, SEE = 4.716 ml/kg/min) or BMI (R = 0.802, SEE = 4.900 ml . kg-1. min -1 ). PURPOSE: to develop non-exercise models to estimate VO2max from age, gender, body composition (WG, %Fat, BMI) and PASS dichotomized at meets or does not meet the PAG (PAG-PASS), and to compare the accuracy of the PAG-PASS models with the models using the 11-point PASS. METHODS: 2417 men and 384 women were measured for VO2max by indirect calorimetry (RER 〉1.1); age (yr), gender by M = 1, W = 0; WG at the umbilicus; %fat by skin-folds, BMI by weight (kg) divided by height squared (m 2 ) , and PAGPASS by PASS 〈 6 = 0 and =/〉 6 = 1. RESULTS: Three models were developed by multiple regression to estimate VO2(sub max) from age, gender, PAG-PASS and either WG (R = 0.790, SEE=5.019 ml/kg/min), %FAT (R= 0.080, SEE = 4.915 ml/kg/min) or BMI (R = 0.777, SEE = 5.162ml/kg/min). Cross-validation by the PRESS technique confirmed these statistics. Simple correlations between measured VO2(sub max) and estimates from the PAG-PASS models with WG, %Fat and BMI were 0.790, 0.800 and 0.777, minimally different from the correlations obtained with the PASS models (0.810, 0.810, and 0.802). PAG-PASS and PASS model constant errors were also similar: 〈 1 ml/kg/min for subsamples of age, gender, PASS and for VO2(sub max) between 30 and 50 ml/kg/min (70% of the sample) but 〉 1 ml/kg/min for VO2(sub max) 〈30 and 〉50 ml/kg/min. CONCLUSIONS: Non-exercise models using the combined effects of age, gender, body composition and the dichotomized PAG-PASS provide estimates of VO2(sub max) that are accurate for most adults, and the accuracy of these models are similar to previously published models using the 11-point PASS.
    Keywords: Aerospace Medicine
    Type: JSC-CN-19092 , ACSM Annual Meeting; Jun 02, 2010 - Jun 05, 2010; Baltimore, MD; United States
    Format: text
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  • 3
    Publication Date: 2019-07-13
    Description: VO2max is associated with many factors, including age, gender, physical activity, and body composition. It is popularly believed that habitual smoking lowers aerobic fitness. PURPOSE: to determine the effect of habitual smoking on VO2max after controlling for age, gender, activity and BMI. METHODS: 2374 men and 375 women employed at the NASA/Johnson Space Center were measured for VO2max by indirect calorimetry (RER〉=1.1), activity by the 11 point (0-10) NASA Physical Activity Status Scale (PASS), BMI and smoking pack-yrs (packs day*y of smoking). Age was recorded in years and gender was coded as M=1, W=0. Pack.y was made a categorical variable consisting of four levels as follows: Never Smoked (0), Light (1-10), Regular (11-20), Heavy (〉20). Group differences were verified by ANOVA. A General Linear Models (GLM) was used to develop two models to examine the relationship of smoking behavior on VO2max. GLM #1(without smoking) determined the combined effects of age, gender, PASS and BMI on VO2max. GLM #2 (with smoking) determined the added effects of smoking (pack.y groupings) on VO2max after controlling for age, gender, PASS and BMI. Constant errors (CE) were calculated to compare the accuracy of the two models for estimating the VO2max of the smoking subgroups. RESULTS: ANOVA affirmed the mean VO2max of each pack.y grouping decreased significantly (p〈0.01) as the level of smoking exposure increased. GLM #1 showed that age, gender, PASS and BMI were independently related with VO2max (R2 = 0.642, SEE = 4.90, p〈0.001). The added pack.y variables in GLM #2 were statistically significant (R2 change = 0.7%, p〈0.01). Post hoc analysis showed that compared to Never Smoked, the effects on VO2max from Light and Regular smoking habits were -0.83 and -0.85 ml.kg- 1.min-1 respectively (p〈0.05). The effect of Heavy smoking on VO2max was -2.56 ml.kg- 1.min-1 (p〈0.001). The CE s of each smoking group in GLM #2 was smaller than the CE s of the smoking group counterparts in GLM #1. CONCLUSIONS: After accounting for the effects of gender, age, PASS and BMI the effect of habitual smoking on reducing VO2max is minimal, about 0.85 ml/kg/min, until the habit exceeds 20 pack.y at which point an additional decrease of 1.71 ml/kg/min is noted. Adding pack.y data improves the accuracy of predicting the VO2max of smokers.
    Keywords: Aerospace Medicine
    Type: ACSM''s 55th Annual Meeting; May 28, 2008 - May 31, 2008; Indianapolis, IN; United States
    Format: application/pdf
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