scholarly journals The Relationship Between Maximal Oxygen Intake, Body Fat and Bone Marker Measurements in Different Sports Branches

2017 ◽  
Vol 4 (3) ◽  
pp. 58-71
Author(s):  
SERAP DEMİR ◽  
Armağan Aytuğ Yürük
Keyword(s):  
Body Fat ◽  
Bone Marker ◽  
Oxygen Intake ◽  
Maximal Oxygen Intake ◽  
The Relationship

Limitations to prediction of maximal oxygen intake

1964 ◽  
Vol 19 (5) ◽  
pp. 919-927 ◽  
Author(s):  
Loring B. Rowell ◽  
Henry L. Taylor ◽  
Yang Wang
Keyword(s):  
Metabolic Rate ◽  
Pulse Rate ◽  
Oxygen Intake ◽  
Physical Conditioning ◽  
Maximal Oxygen Intake ◽  
Before And After ◽  
Normal Men ◽  
Accuracy Of Prediction ◽  
Relationship Of ◽  
The Relationship

The predictability of maximal O2 intake (max Vo2) was studied in four groups of normal men, 18–24 years of age. Prediction of max Vo2 was made from pulse rate and Vo2 at a single submaximal workload at an ambient temperature of 78 F by use of the nomogram of Åstrand and Ryhming (1954) and underestimated actual max Vo2 by 27 ± 7% and 14 ± 7% in a sedentary group, before and after 2frac12–3 months of physical training, and by 5.6 ȁ 4% in a group of ten endurance athletes. Accuracy of prediction in all groups varied with approximation of pulse rate to 128 beats/min at 50% of max Vo2. Nonspecific stresses increased predictive errors in all groups. Constants b (slope) and A (intercept) in the regression equation Vo2 = bP – A (where P is pulse rate), were determined from Vo2 and pulse measured at four submaximal workloads requiring 13–28 ml O2/kg min. Prediction of max Vo2 by extrapolation of the slope to maximal pulse rate resulted in underestimation of 700–800 ml O2/min. Removal of 14% of circulating hemoglobin decreased max Vo2 by 4% but there was no change in pulse rates or predicted max Vo2. The relationship of RQ to V22 during work provided no reliable basis for prediction of max Vo2. exercise pulse rate, oxygen intake, relationship; pulse rate, oxygen intake relationship in exercise; metabolic rate, maximal aerobic prediction of; aerobic metabolic rate, maximal, prediction of; phlebotomy, effect on maximal oxygen intake, pulse rate; blood loss, effect on maximal oxygen intake, pulse rate; training, effect on maximal oxygen intake, pulse rates; physical conditioning, effect on maximal oxygen intake, pulse rates Submitted on October 4, 1963

Investigating the relationship between insulin resistance and adipose tissue in a randomized Tehrani population

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jalaledin Mirzay Razzaz ◽  
Hossein Moameri ◽  
Zahra Akbarzadeh ◽  
Mohammad Ariya ◽  
Seyed ali Hosseini ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Adipose Tissue ◽  
Body Fat ◽  
Odds Ratio ◽  
Cross Sectional Study ◽  
Model Assessment ◽  
Fasting Insulin ◽  
Cross Sectional ◽  
Body Fat Percent ◽  
The Relationship

Abstract Objectives Insulin resistance is the most common metabolic change associated with obesity. The present study aimed to investigate the relationship between insulin resistance and body composition especially adipose tissue in a randomized Tehrani population. Methods This study used data of 2,160 individuals registered in a cross-sectional study on were randomly selected from among subjects who were referred to nutrition counseling clinic in Tehran, from April 2016 to September 2017. Insulin resistance was calculated by homeostasis model assessment formula. The odds ratio (95% CI) was calculated using logistic regression models. Results The mean age of the men was 39 (±10) and women were 41 (±11) (the age ranged from 20 to 50 years). The risk of increased HOMA-IR was 1.03 (95% CI: 1.01–1.04) for an increase in one percent of Body fat, and 1.03 (95% CI: 1.00–1.05) for an increase in one percent of Trunk fat. Moreover, the odds ratio of FBS for an increase in one unit of Body fat percent and Trunk fat percent increased by 1.05 (adjusted odds ratio [95% CI: 1.03, 1.06]) and 1.05 (95% CI: 1.02, 1.08). Also, the risk of increased Fasting Insulin was 1.05 (95% CI: 1.03–1.07) for an increase in one unit of Body fat percent, and 1.05 (95% CI: 1.02–1.08) for an increase in one unit of Trunk fat percent. Conclusions The findings of the present study showed that there was a significant relationship between HOMA-IR, Fasting blood sugar, Fasting Insulin, and 2 h Insulin with percent of Body fat, percent of Trunk fat.

The relationship between plasma leptin concentrations and the distribution of body fat in crossbred steers

2003 ◽  
Vol 74 (2) ◽  
pp. 95-100 ◽  
Author(s):  
Tomoya YAMADA ◽  
Shin-Ichi KAWAKAMI ◽  
Naoto NAKANISHI
Keyword(s):  
Body Fat ◽  
Plasma Leptin ◽  
The Relationship

scholarly journals Body mass index as a measure of body fatness: age- and sex-specific prediction formulas

1991 ◽  
Vol 65 (2) ◽  
pp. 105-114 ◽  
Author(s):  
Paul Deurenberg ◽  
Jan A. Weststrate ◽  
Jaap C. Seidell
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Prediction Error ◽  
Bioelectrical Impedance ◽  
Skinfold Thickness ◽  
Fat Percentage ◽  
Wide Range ◽  
The Relationship ◽  
Age And Sex

In 1229 subjects, 521 males and 708 females, with a wide range in body mass index (BMI; 13.9–40.9 kg/m2), and an age range of 7–83 years, body composition was determined by densitometry and anthropometry. The relationship between densitometrically-determined body fat percentage (BF%) and BMI, taking age and sex (males =1, females = 0) into account, was analysed. For children aged 15 years and younger, the relationship differed from that in adults, due to the height-related increase in BMI in children. In children the BF% could be predicted by the formula BF% = 1.51xBMI–0.70xage–3.6xsex+1.4 (R2 0.38, SE of estimate (see) 4.4% BF%). In adults the prediction formula was: BF% = 1.20xBMI+0.23xage−10.8xsex–5.4 (R2 0.79, see = 4.1% BF%). Internal and external cross-validation of the prediction formulas showed that they gave valid estimates of body fat in males and females at all ages. In obese subjects however, the prediction formulas slightly overestimated the BF%. The prediction error is comparable to the prediction error obtained with other methods of estimating BF%, such as skinfold thickness measurements or bioelectrical impedance.

Examining the Relationship Between Physical Activity Intensity and Adiposity in Young Women

2015 ◽  
Vol 12 (6) ◽  
pp. 764-769 ◽  
Author(s):  
Bruce W. Bailey ◽  
Pamela Borup ◽  
James D. LeCheminant ◽  
Larry A. Tucker ◽  
Jacob Bromley
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Body Fat ◽  
Young Women ◽  
Physical Activity Intensity ◽  
Fat Percentage ◽  
Bod Pod ◽  
Activity Intensity ◽  
Objectively Measured ◽  
The Relationship

Background:The purpose of this study was to assess the relationship between intensity of physical activity (PA) and body composition in 343 young women.Methods:Physical activity was objectively measured using accelerometers worn for 7 days in women 17 to 25 years. Body composition was assessed using the BOD POD.Results:Young women who spent less than 30 minutes a week performing vigorous PA had significantly higher body fat percentages than women who performed more than 30 minutes of vigorous PA per week (F = 4.54, P = .0113). Young women who spent less than 30 minutes per day in moderate to vigorous PA (MVPA) had significantly higher body fat percentages than those who obtained more than 30 minutes per day of MVPA (F = 7.47, P = .0066). Accumulating more than 90 minutes of MVPA per day was associated with the lowest percent body fat. For every 10 minutes spent in MVPA per day, the odds of having a body fat percentage above 32% decreased by 29% (P = .0002).Conclusion:Vigorous PA and MVPA are associated with lower adiposity. Young women should be encouraged to accumulate at least 30 minutes of MVPA per day, however getting more than 90 minutes a day is predictive of even lower levels of adiposity.

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