scholarly journals Development of an Easy-to-Use Prediction Equation for Body Fat Percentage Based on BMI in Overweight and Obese Lebanese Adults

Diagnostics ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 728
Author(s):  
Leila Itani ◽  
Hana Tannir ◽  
Dana El Masri ◽  
Dima Kreidieh ◽  
Marwan El Ghoch
Keyword(s):  
Body Fat ◽  
Model Building ◽  
Clinical Importance ◽  
Training Sample ◽  
Prediction Equation ◽  
Accurate Estimation ◽  
Body Fat Percentage ◽  
Validation Sample ◽  
Fat Percentage ◽  
Prediction Bias

An accurate estimation of body fat percentage (BF%) in patients who are overweight or obese is of clinical importance. In this study, we aimed to develop an easy-to-use BF% predictive equation based on body mass index (BMI) suitable for individuals in this population. A simplified prediction equation was developed and evaluated for validity using anthropometric measurements from 375 adults of both genders who were overweight or obese. Measurements were taken in the outpatient clinic of the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). A total of 238 participants were used for model building (training sample) and another 137 participants were used for evaluating validity (validation sample). The final predicted model included BMI and sex, with non-significant prediction bias in BF% of −0.017 ± 3.86% (p = 0.946, Cohen’s d = 0.004). Moreover, a Pearson’s correlation between measured and predicted BF% was strongly significant (r = 0.84, p < 0.05). We are presenting a model that accurately predicted BF% in 61% of the validation sample with an absolute percent error less than 10% and non-significant prediction bias (−0.028 ± 4.67%). We suggest the following equations: BF% females = 0.624 × BMI + 21.835 and BF% males = 1.050 × BMI − 4.001 for accurate BF% estimation in patients who are overweight or obese in a clinical setting in Lebanon.

scholarly journals ESTIMATING BODY FAT PERCENTAGE THROUGH BODY MASS INDEX AND HANDGRIP STRENGTH IN MIDDLE AND OLDER-AGED ASIAN ADULTS

2022 ◽  
pp. 92
Author(s):  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Handgrip Strength ◽  
Prediction Equation ◽  
Whole Body ◽  
Body Fat Percentage ◽  
Prediction Equations ◽  
Middle Aged ◽  
Fat Percentage

Objectives: To determine the ability of handgrip strength combined with body mass index (BMI, kg/m2) to estimate body fat percentage (BF%) in middle-aged and older Asian adults. Methods: Middle-aged and older Asian adults (n=459, males=197) were randomly divided into a validation and model development group (n=303) and cross-validation group (n=156). A whole-body scan using dual energy x-ray absorptiometry measured BF%. Bland-Altman plots, standard error of the estimates, total errors and mean absolute errors were used to compare prediction equations. Stepwise regression analysis was used to determine a new prediction equation for middle-aged and older Asian adults. Right and left handgrip strength, age, sex and BMI were included in the analysis. Results: A previously developed prediction equation that included handgrip strength poorly predicted BF% in our current sample with the mean difference being -6.0 ± 4.2%. Predicted BF% values were significantly lower than measured BF% values (22.7% vs. 28.7%, p<0.05). A new prediction equation was developed that included sex, BMI, left handgrip strength and age. Validation of the new equation revealed a constant error of 0.2 ± 3.9% with there being no significant difference between measured and predicted BF% (28.2% vs. 28.5%, p=0.467). Previously developed BF% equations using BMI, but not handgrip strength, had similar constant errors and mean absolute errors compared to the new prediction equation. Conclusion: Handgrip strength does not appear to improve the estimation of body fat percentage from BMI prediction equations in middle and older-aged Asian adults.

A Prediction Equation for Estimating Body Fat Percentage Using Readily Accessible Measures: A Multivariate Study of 200 Adult Women

1998 ◽  
Vol 12 (4) ◽  
pp. 229-236 ◽  
Author(s):  
Larry A. Tucker ◽  
Denise S. Demers ◽  
K. Patrick Kelly
Keyword(s):  
Body Fat ◽  
White Women ◽  
Age Groups ◽  
Prediction Equation ◽  
Average Weight ◽  
Body Fat Percentage ◽  
Adult Women ◽  
Fat Percentage ◽  
Cross Sectional ◽  
Wide Range

Purpose. This study was conducted to develop a regression equation that accurately estimates body fat percentage using relatively easy and inexpensive methods that do not require women to remove clothing. Design. A cross-sectional design was employed. Setting. All data were collected at the University. Subjects. Subjects were 200 white women ages 20 to 65 years. The sample was equally distributed across four age groups, 20–29, 30–39, 40–49, and 50–65, and within each age group, one-third of the women were lean, one-third were of average weight, and one-third were obese. Measures. Subjects were hydrostatically weighed and participated in a variety of anthropometric and lifestyle assessments, including skinfolds, circumferences, and questionnaire responses. Results. The full regression model included six measures: hip circumference, triceps skinfold (observed and quadratic), age (quadratic), self-reported physical activity, and calf skinfold (quadratic). This equation accounted for 81 % of the variance in body weight measured by hydrostatic weighing (SEE = 3.5%). A simpler, five-variable equation was also formed that did not include the calf skinfold assessment (R2 = .800, SEE = 3.6%). Conclusions. The prediction equations in this study afford accurate and relatively easy and inexpensive means of estimating body fat percentage in a wide range of white women without having them remove their clothing.

scholarly journals Which Body Density Equations Calculate Body Fat Percentage Better in Olympic Wrestlers?—Comparison Study with Air Displacement Plethysmography

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 707
Author(s):  
Aslı Devrim-Lanpir ◽  
Ebru Arslanoğlu Badem ◽  
Hatice Işık ◽  
Aslıhan Nefes Çakar ◽  
Banu Kabak ◽  
...  
Keyword(s):  
Body Mass ◽  
Body Fat ◽  
Prediction Equation ◽  
Field Application ◽  
Body Fat Percentage ◽  
Male Body ◽  
Prediction Equations ◽  
Fat Percentage ◽  
Air Displacement Plethysmography ◽  
Specific Prediction

Although skinfold-derived equations seem to be practical for field application in estimating body fat percentage (BF%) and minimum body mass in Olympic wrestlers, prediction equations applied first need to be cross-validated in Olympic wrestlers to define the best prediction equation. This study aimed to evaluate the most accurate field method to predict BF% in Olympic wrestlers compared to BF% estimated by air displacement plethysmography (ADP). Sixty-one male (body mass 72.4 ± 13.5 kg; height 170.3 ± 7.0 cm; body mass index (BMI) 24.9 ± 3.5 kg.m−2; BF% 8.5 ± 4.9%) and twenty-five female wrestlers (body mass 60.3 ± 9.9 kg; height 161.3 ± 7.1 cm; BMI 23.1 ± 2.5 kg.m−2; BF% 18.7 ± 4.7%) undertook body composition assessments including ADP and nine-site skinfold measurements. Correlations, bias, limits of agreement, and standardized differences between alterations in BF% measured by ADP and other prediction equations were evaluated to validate measures, and multiple regression analyses to develop an Olympic wrestlers-specific prediction formula. The Stewart and Hannan equation for male wrestlers and the Durnin and Womersley equation for female wrestlers provided the most accurate BF% compared to the measured BF% by ADP, with the lowest bias and presented no significant differences between the measured and predicted BF%. A new prediction equation was developed using only abdominal skinfold and sex as variables, predicting 83.2% of the variance. The findings suggest the use of the new wrestler-specific prediction equation proposed in the study as a valid and accurate alternative to ADP to quantify BF% among Olympic wrestlers.

Subjective Sleep Debt Is Correlated with Body Fat Percentage Independent of Sleep Duration

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1675-P
Author(s):  
XIAO TAN ◽  
CHRISTIAN BENEDICT
Keyword(s):  
Sleep Duration ◽  
Body Fat ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Subjective Sleep ◽  
Sleep Debt

Comparison of the Effect of Soy protein and Whey protein on Body Composition: A Meta-Analysis of Randomized Clinical Trials

2021 ◽  
pp. 1-27
Author(s):  
Masoome Piri Damaghi ◽  
Atieh Mirzababaei ◽  
Sajjad Moradi ◽  
Elnaz Daneshzad ◽  
Atefeh Tavakoli ◽  
...  
Keyword(s):  
Body Composition ◽  
Whey Protein ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Soy Protein ◽  
Protein Supplementation ◽  
Body Fat Percentage ◽  
Fat Percentage

Abstract Background: Essential amino acids (EAAs) promote the process of regulating muscle synthesis. Thus, whey protein that contains higher amounts of EAA can have a considerable effect on modifying muscle synthesis. However, there is insufficient evidence regarding the effect of soy and whey protein supplementation on body composition. Thus, we sought to perform a meta-analysis of published Randomized Clinical Trials that examined the effect of whey protein supplementation and soy protein supplementation on body composition (lean body mass, fat mass, body mass and body fat percentage) in adults. Methods: We searched PubMed, Scopus, and Google Scholar, up to August 2020, for all relevant published articles assessing soy protein supplementation and whey protein supplementation on body composition parameters. We included all Randomized Clinical Trials that investigated the effect of whey protein supplementation and soy protein supplementation on body composition in adults. Pooled means and standard deviations (SD) were calculated using random-effects models. Subgroup analysis was applied to discern possible sources of heterogeneity. Results: After excluding non-relevant articles, 10 studies, with 596 participants, remained in this study. We found a significant increase in lean body mass after whey protein supplementation weighted mean difference (WMD: 0.91; 95% CI: 0.15, 1.67. P= 0.019). Subgroup analysis, for whey protein, indicated that there was a significant increase in lean body mass in individuals concomitant to exercise (WMD: 1.24; 95% CI: 0.47, 2.00; P= 0.001). There was a significant increase in lean body mass in individuals who received 12 or less weeks of whey protein (WMD: 1.91; 95% CI: 1.18, 2.63; P<0.0001). We observed no significant change between whey protein supplementation and body mass, fat mass, and body fat percentage. We found no significant change between soy protein supplementation and lean body mass, body mass, fat mass, and body fat percentage. Subgroup analysis for soy protein indicated there was a significant increase in lean body mass in individuals who supplemented for 12 or less weeks with soy protein (WMD: 1.48; 95% CI: 1.07, 1.89; P< 0.0001). Conclusion: Whey protein supplementation significantly improved body composition via increases in lean body mass, without influencing fat mass, body mass, and body fat percentage.

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