scholarly journals US Army basic combat training alters the relationship between body mass index and per cent body fat

2021 ◽  
pp. bmjmilitary-2021-001936
Author(s):  
Stephen A Foulis ◽  
J M Hughes ◽  
B A Spiering ◽  
L A Walker ◽  
K I Guerriere ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Sensitivity And Specificity ◽  
Body Fat ◽  
Military Force ◽  
Us Army ◽  
Combat Training ◽  
Basic Combat Training ◽  
The Relationship

Introduction/backgroundAs a proxy for adiposity, body mass index (BMI) provides a practical public health metric to counter obesity-related disease trends. On an individual basis, BMI cannot distinguish fat and lean components of body composition. Further, the relationship between BMI and body composition may be altered in response to physical training. We investigated this dynamic relationship by examining the effect of US Army basic combat training (BCT) on the association between BMI and per cent body fat (%BF).MethodsBMI and %BF were measured at the beginning (week 1) and end (week 9) of BCT in female (n=504) and male (n=965) trainees. Height and weight were obtained for BMI, and body composition was obtained by dual X-ray absorptiometry. Sensitivity and specificity of BMI-based classification were determined at two BMI thresholds (25 kg/m2 and 27.5 kg/m2).ResultsA progressive age-related increase in fat-free mass index (FFMI) was observed, with an inflection point at age 21 years. In soldiers aged 21+, BMI of 25.0 kg/m2 predicted 33% and 29% BF in women and 23% and 20% BF in men and BMI of 27.5 kg/m2 predicted 35% and 31% BF in women and 26% and 22% BF in men, at the start and end of BCT, respectively. Sensitivity and specificity of BMI-based classification of %BF were poor. Soldiers below BMI of 20 kg/m2 had normal instead of markedly reduced %BF, reflecting especially low FFMI.ConclusionsBCT alters the BMI–%BF relationship, with lower %BF at a given BMI by the end of BCT compared with the beginning, highlighting the unreliability of BMI to try to estimate body composition. The specific BMI threshold of 25.0 kg/m2, defined as ‘overweight’, is an out-of-date metric for health and performance outcomes. To the extent that %BF reflects physical readiness, these data provide evidence of a fit and capable military force at BMI greater than 25.0 kg/m2.

scholarly journals Design and Validation of the Equation for Correction of Body Mass Index

2021 ◽  
Vol 10 (3) ◽  
pp. 400-411
Author(s):  
Abbas Farjad Pezeshk ◽  
◽  
Nader Nokhodchi ◽  
Mohammad Yousefi ◽  
Saeed Ilbeigi ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Multiple Regression ◽  
Correlation Coefficient ◽  
Body Mass ◽  
Body Fat ◽  
The Body ◽  
Spearman Correlation ◽  
Body Fat Percent ◽  
The Relationship

Background and Aims: The Body Mass Index (BMI) is considered one of the most common indexes for examining the health. The purpose of this study was the design and validation of the equations for the accuracy of BMI. Methods: In the current 419 athletic and non-athletic subjects participated in this study. Anthropometrical measurement was performed using International Standard for Anthropometry and Kinanthropometry (ISAK) protocol, and mesomorphic and endomorphic calculated based on the Heath-Carter methods. The Spearman correlation coefficient was used to determine the relationship between BMI and body fat percent, mesomorphic and endomorphic values. Multiple regressions were used to predict BMI. Results: There is a high correlation between BMI with mesomorphic and endomorphic values (P<0.01), but the correlation of BMI with mesomorphic in athletic men was higher than endomorphic (0.77 vs. 0.63). Multiple regression produces some equations for predicting mesomorphic and endomorphic, and bland Altman believes that all equations predict fatness. Conclusion: According to the results, the Equations proposed in this study could appropriately turn BMI to predict body composition so that this equation could determine higher BMI because of the higher muscular mass.

Pre-pregnancy body mass index is associated with offspring body composition in adulthood before adiposity-related disorders: a retrospective cohort

2020 ◽  
pp. 1-17
Author(s):  
Ilana Eshriqui ◽  
Angélica Marques Martins Valente ◽  
Luciana Dias Folchetti ◽  
Bianca de Almeida-Pititto ◽  
Sandra Roberta G. Ferreira
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
Retrospective Cohort ◽  
Statistical Significance ◽  
Directed Acyclic Graphs ◽  
Health Study ◽  
Appendicular Skeletal Muscle ◽  
Three Body

Abstract Objective: To investigate the association between maternal pre-pregnancy body mass index (BMI) and offspring body composition in adulthood. Design: Retrospective cohort. Undergraduates of nutrition or nutritionists were recruited at the baseline of the Nutritionists’ Health Study between 2014 and 2017. Maternal pre-pregnancy BMI and current life aspects were self-reported through online questionnaires. Three body compartments were DXA-determined. The following variables were obtained: body-fat (%), fat mass index (FMI) (kg/m2), android-to-gynoid fat ratio, visceral adipose tissue (VAT) (cm3), appendicular skeletal muscle mass index (ASMI) (kg/m2), total bone and femur mineral content (g) and density (g/cm2). Linear regression adjusted according to directed acyclic graphs recommendation was performed. Setting: São Paulo, Brazil. Participants: Healthy non-pregnant women (aged 20-45 years) (n=150). Results: Median age and BMI were 22 years (IQR=20; 29) and 22.3 kg/m2 (IQR=20.4; 25.3). Pre-pregnancy BMI≥25 kg/m2 was reported by 14.7% of mothers. In fully adjusted models, maternal pre-pregnancy BMI was associated with their daughters’ body-fat % (β=0.31; 95%CI=0.0004; 0.63), FMI (β=0.17; 95%CI=0.03; 0.30, android-to-gynoid ratio (β=0.01; 95%CI=0.004; 0.02) and VAT (β=0.09; 95%CI=0.02; 0.16), but not with total bone density (β=0.001; 95%CI=-0.003; 0.006) and content (β=7.13; 95%CI=-4.19; 18.46). Direct association with ASMI was also detected, but lost statistical significance when participants whose mothers were underweight were excluded. Conclusions: Maternal pre-pregnancy body mass index was directly associated with offspring general and visceral adiposity but seem not to be associated with bone mass. Results reinforce importance of avoiding excess of maternal adiposity, as an attempt to break the vicious cycle of obesity transmission.

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.

scholarly journals A Bayesian Sensitivity Analysis to Partition Body Mass Index Into Components of Body Composition: An Application to Head and Neck Cancer Survival

2019 ◽  
Vol 188 (11) ◽  
pp. 2031-2039
Author(s):  
Patrick T Bradshaw ◽  
Jose P Zevallos ◽  
Kathy Wisniewski ◽  
Andrew F Olshan
Keyword(s):  
Body Mass Index ◽  
Sensitivity Analysis ◽  
Body Composition ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Body Mass ◽  
Neck Cancer ◽  
Hazard Ratio ◽  
Unit Increase ◽  
The Relationship

Abstract Previous studies have suggested a “J-shaped” relationship between body mass index (BMI, calculated as weight (kg)/height (m)2) and survival among head and neck cancer (HNC) patients. However, BMI is a vague measure of body composition. To provide greater resolution, we used Bayesian sensitivity analysis, informed by external data, to model the relationship between predicted fat mass index (FMI, adipose tissue (kg)/height (m)2), lean mass index (LMI, lean tissue (kg)/height (m)2), and survival. We estimated posterior median hazard ratios and 95% credible intervals for the BMI-mortality relationship in a Bayesian framework using data from 1,180 adults in North Carolina with HNC diagnosed between 2002 and 2006. Risk factors were assessed by interview shortly after diagnosis and vital status through 2013 via the National Death Index. The relationship between BMI and all-cause mortality was convex, with a nadir at 28.6, with greater risk observed throughout the normal weight range. The sensitivity analysis indicated that this was consistent with opposing increases in risk with FMI (per unit increase, hazard ratio = 1.04 (1.00, 1.08)) and decreases with LMI (per unit increase, hazard ratio = 0.90 (0.85, 0.95)). Patterns were similar for HNC-specific mortality but associations were stronger. Measures of body composition, rather than BMI, should be considered in relation to mortality risk.

scholarly journals Prevalence of Obesity and the Relationship between the Body Mass Index and Body Fat: Cross-Sectional, Population-Based Data

PLoS ONE ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. e29580 ◽  
Author(s):  
Julie A. Pasco ◽  
Geoffrey C. Nicholson ◽  
Sharon L. Brennan ◽  
Mark A. Kotowicz
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Population Based ◽  
The Body ◽  
Cross Sectional ◽  
Prevalence Of Obesity ◽  
The Relationship

scholarly journals Despite Low Obesity Rates, Body Mass Index Under-Estimated Obesity among Russian Police Officers When Compared to Body Fat Percentage

2020 ◽  
Vol 17 (6) ◽  
pp. 1937 ◽  
Author(s):  
Katie M. Heinrich ◽  
Konstantin G. Gurevich ◽  
Anna N. Arkhangelskaia ◽  
Oleg P. Karazhelyaskov ◽  
Walker S. C. Poston
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
Police Officers ◽  
Weight Status ◽  
Bioelectrical Impedance ◽  
Accurate Method ◽  
Body Fat Percentage ◽  
Fat Percentage

In some countries, obesity rates among police officers are higher than the general public, despite physically demanding jobs. Obesity rates based on body mass index (BMI) may lack accuracy as BMI does not directly address body composition. Since data are lacking for obesity rates among Russian police officers, this study documented and compared officer obesity rates to the adult Russian population and compared the accuracy of body mass index (BMI) for obesity classification to two direct measures of body composition. Moscow region police officers (N = 182, 84% men) underwent height, weight, waist circumference (WC), and body fat percentage (BF%) bioelectrical impedance measurements during annual medical examinations. BMI-defined obesity rates were 4.6% for men and 17.2% for women, which were >3 and >1.8 times lower than Russian adults, respectively. WC-defined obesity rates were similar to BMI (3.3% for men and 10.3% for women), but BF%-defined obesity rates were much higher (22.2% for men and 55.2% for women). Although obesity rates were lower than those found among police officers in other countries, BMI alone was not a particularly accurate method for classifying weight status among Russian police officers.

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