The anthropometric generalization of the Body Mass Index (Preprint)

2020 ◽  
Author(s):  
Alexandru Godescu
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Experimental Research ◽  
Large Body ◽  
The Body ◽  
Fat Free Mass ◽  
Physical Work ◽  
Healthy Weight ◽  
Quantification Theory ◽  
Highly Cited

BACKGROUND While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. OBJECTIVE Develop a generalization of the body mass index explaining the results of a number of highly cited research papers showing how fat distribution and muscle strength are predictors or mortality, morbidity, ill health, loss of function METHODS In essence, my method is theoretic, to develop a formula explaining highly cited experimental research. It is like theoretical physics, developing a formula to explain important experiments and building a theory to generalize the body mass index. I use also data and perform numerical simulation of the formulae RESULTS My formulae explain the causality in the important experiments in medicine and sport cited by me. the formulae can be used to develop new experiments CONCLUSIONS I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

Body Image, Body Mass Index, and Body Composition: In Young Adults

2012 ◽  
Vol 73 (2) ◽  
pp. 78-83 ◽  
Author(s):  
Veronica M. Streeter ◽  
Robin R. Milhausen ◽  
Andrea C. Buchholz
Keyword(s):  
Body Mass Index ◽  
Body Image ◽  
Young Adults ◽  
Body Composition ◽  
Body Mass ◽  
Body Esteem ◽  
The Body ◽  
Fat Free Mass ◽  
Healthy Weight ◽  
External Attribution

Purpose: Associations were examined between body image and body mass index (BMI) in comparison with body composition in healthy weight, overweight, and obese young adults. Methods: Weight and height were determined, and the percentage of fat mass (%FM) and percentage of fat-free mass (%FFM) were measured by dual energy X-ray absorptiometry in 75 male and 87 female young adults (21.1 ± 1.9 years; 25.2 ± 4.4 kg/m2 [mean ± standard deviation]). Body image was measured using the three subscales Weight Esteem, Appearance Esteem, and External Attribution of the Body-Esteem Scale for Adolescents and Adults (BESAA). Results: Body mass index and %FM were highly correlated (r for males = 0.74, r for females = 0.82; both p<0.001), and were inversely associated with body image, particularly Weight Esteem. After adjustment for physical activity, BMI and %FM (and %FFM, although in the opposite direction) were associated with each BESAA subscale: %FM, %FFM, and BMI explained 12% to14% of the variance in Appearance Esteem for both sexes, 33% to 41% in Weight Esteem in women and 16% to 18% in men, and 8% to 10% in External Attribution in women (all p<0.05) and <5% for men (NS). Conclusions: Clinicians should be aware that as their clients’ BMI and %FM increase, body image decreases, particularly in women.

scholarly journals Hubungan IMT (Indeks Massa Tubuh) dengan Ketahanan (Endurance) Kardiorespirasi pada Mahasiswa Pendidikan Dokter Unand 2009-2012

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Reny Jayusfani ◽  
Afriwardi Afriwardi ◽  
Eti Yerizel
Keyword(s):  
Body Mass Index ◽  
Medical Student ◽  
Linear Regression ◽  
Body Mass ◽  
The Body ◽  
Physical Work ◽  
Physical Work Capacity ◽  
Cross Sectional ◽  
Average Maximum ◽  
Cardiorespiratory Endurance

AbstrakSaat ini terjadi peningkatan kelebihan berat badan terutama pada generasi muda disebabkan oleh diet yang tidak tepat dan gaya hidup yang tidak aktif. Peningkatan berat badan ini akan berakibat pada penurunan daya tahan kardiorespirasi hingga berdampak pada kapasitas kerja fisik. Tujuan penelitian ini adalah untuk menentukan hubungan Indeks Massa Tubuh (IMT) dengan ketahanan kardiorespirasi pada mahasiswa FK Unand. Penelitian dilakukan pada mahasiswa FK Unand Padang dari Desember 2012 sampai Februari 2013. Studi observasional analitik ini menggunakan desain cross sectional study dengan jumlah subjek 30 orang. Ketahanan kardiorespirasi didapat dengan menghitung nilai VO2maks menggunakan tes ergometer sepeda metode Astrand 6 minute cycle test. Dilakukan pengukuran berat badan dan tinggi badan. Analisis statistik yang digunakan adalah uji regresi linear sederhana. Hasil penelitian menemukan bahwa rerata IMT 23,2 ± 5,1 dan rerata volume oksigen maksimal 39,5 ± 12,1. Uji regresi linear menunjukkan terdapat hubungan antara IMT dengan ketahanan kardiorespirasi dengan tingkat hubungan sedang (r=0,567, p<0,05) dengan pengaruh sebesar 32,1% (R2=0,321) dan persamaan regresi yang didapat adalah Y=70,827 – 1,349X. Kesimpulan hasil studi ini adalah semakin tinggi indeks massa tubuh semakin rendah ketahanan kardiorespirasi.Kata kunci: volume oksigen maksimal, indeks massa tubuh, ketahanan kardiorespirasi AbstractNowadays, there are many cases about increasing the weight of body, especially at younger generation. It is caused by anappropriate diet and inactive lifestyle. Increasing of weight will cause declining of cardiorespiratory endurance. So that, it will impact on physical work capacity. The objective of this study was to determine the relationship between cardiorespiratory with Body Mass Index (BMI) in medical student of Andalas University.The research was done on medical student of Andalas University Padang in December 2012 until February 2012. This research used observational study with cross sectional design study. The subject of this research were 30 people. Cardiorespiratory endurance was obtained by calculate the value of VO2max. This measurement used ergometer bicycle with the method was using Astrand 6 minute cycle test. This test measured the weight and height body. Statistical analysis was simple linear regression. The result found that the average of BMI is 23.2 ± 5.1 and an average maximum oxygen volume is 39.5 ± 12.1. Linear regression found that there is a moderate significant effect between BMI and cardiorespiratory endurance (r=0.567, p <0.05) with the effect about 32.1% (R2 = 0.321) and the regression equation was Y = 70.827 to 1.349 X.In conclusion, the subjects have average cardiorespiratory endurance level and normal body mass index. If the body of mass index is higher, the cardiorespiratory endurance

scholarly journals Age relative height, weight and body mass index percentiles of children in Jos, North-Central Nigeria

2021 ◽  
Vol 12 (8) ◽  
pp. 149-154
Author(s):  
Ovayoza O. Mosugu ◽  
Francis Shinku ◽  
Jacob C. Nyam ◽  
Emmanuel S. Mador
Keyword(s):  
Body Mass Index ◽  
Childhood Obesity ◽  
Body Mass ◽  
Weight Status ◽  
Body Height ◽  
Mean Value ◽  
The Body ◽  
Healthy Weight ◽  
North Central ◽  
The Mean

Background: Interpretation of body mass index in children is quite different from that in adults which use standard weight status categories that are the same for all ages and for both men and women. Aims and Objective: The study was aimed at determining the prevalence of childhood obesity in Jos. Materials and Methods: A total of 371 children were enrolled in the study. Weight was taken with only light clothing and without foot wears. Height obtained without head-gears or shoes and the measuring flat tops pressed down to avoid errors due to tall hair. Body mass index were calculated for each subject as ratio of body weight to body height. All data were analyzed statistically and separately for different ages and the mean values for height against age, weight against age, height against weight and BMI for age was obtained with centiles of absolute deviations from the mean. Results: The age of the studied population ranged from 3 – 14 years with mean of 8.4 ± 2.8. Height of the children on the other hand ranged from 0.9 – 1.64 meters with mean value of 1.26 ± 0.15 and their weight ranged from 10 – 76 kg with mean value of 25.6 ± 9.2. Out of the 371 children studied, 14 (3.8%) were found to be underweight, 302 (81.4%) had healthy weight while 41 (11%) were at risk of overweight and 14 (3.8%) were overweight. In addition, the body mass index of girls was found to be significantly higher than those of boys at 12 and 13 years only. Conclusion: It is concluded that the prevalence of childhood obesity is high in Jos, North-central Nigeria.

scholarly journals Estimación del riesgo cardiovascular por composición corporal total

2017 ◽  
Vol 4 (1) ◽  
pp. 22-27
Author(s):  
Oscar Medina ◽  
Juan Manuel Sarmiento ◽  
Larry Quinn ◽  
Sonia Merlano ◽  
Fabian Antonio Dávila ◽  
...  
Keyword(s):  
Heart Failure ◽  
Body Mass Index ◽  
Body Composition ◽  
Waist Circumference ◽  
Body Mass ◽  
Cross Sectional Study ◽  
Rehabilitation Program ◽  
The Body ◽  
Fat Free Mass ◽  
Cross Sectional

Introducción: La obesidad y la adiposidad están relacionadas con el aumento del riesgo cardiovascular. El índice de masa corporal (IMC) y el perímetro abdominal son las variables antropométricas más utilizadas para evaluar su magnitud. El presente estudio busca establecer la relación entre desenlaces cardiometabólicos y la adiposidad medida con Absorciometría Dual por rayos X (DXA), así como el rendimiento diagnóstico de la misma contra la medición de las variables antropométricas convencionales. Materiales y métodos: Se realizó un estudio observacional de corte transversal; se calcularon las variables antropométricas y de composición corporal para 60 pacientes en programa de rehabilitación cardiaca fase II. Resultados: Existió mayor prevalencia de obesidad por IMC y adiposidad en mujeres que en hombres (p=0,01 y 0,048). La curva ROC encontró que el rendimiento del perímetro abdominal es solo 65% y el del IMC del 65,6% para el diagnóstico de adiposidad. Se encontraron relaciones significativas entre porcentaje de masa grasa elevado y la enfermedad coronaria (OR: 1,9 p= 0,042); el IMC aumentado con la hipertensión arterial (OR: 3,0 p= 0,0334) y el LDL > 70 mg/dl (OR: 0,4 p= 0,0178); el perímetro abdominal aumentado con la falla cardiaca (OR: 0,58 p=0,0382); la TMB baja con la hipertensión arterial (OR: 1,70 p= 0,046) y finalmente el IIRME disminuido con el LDL > 70 mg/dl y la falla cardiaca (OR: 0,4 p= 0,0178 y OR 1,96 p=0,078, respectivamente).Conclusiones: La suma de la medición de las variables antropométricas y de composición corporal por DXA ofrece información valiosa para el estudio y estimación del riesgo cardiovascular y metabólico de los pacientes. Abstract Introduction: Obesity and adiposity are associated with increased cardiovascular risk. The body mass index (BMI) and waist circumference are the most anthropometric variables used to assess their magnitude. This study aims to establish the relationship between adiposity and cardiometabolic outcomes measured by Dual X-ray Absorptiometry (DXA) as well as the diagnostic performance of the latter against the measurement of the conventional anthropometric variables. Materials and methods: An observational cross-sectional study was conducted; anthropometric and body composition variables for 60 patients in cardiac rehabilitation program phase II were calculated. Results: There was a higher prevalence of obesity by BMI and adiposity in women than in men (p = 0.01 and 0.048). The ROC curve found that the performance is only 65% for waist circumference and 65.6% for BMI for the diagnosis of adiposity. Significant correlations between high percentage of fat mass and coronary heart disease (OR: 1.9 p = 0.042) were found; as well as for increased BMI with hypertension (OR: 3.0 p = 0.0334) and LDL> 70mg/dl (OR: 0.4 p = 0.0178); increased waist circumference with heart failure (OR: 0.58 p = 0.0382); low basal metabolic rate (BMR) with hypertension (OR: 1.70 p = 0.046) and finally the decreased fat free mass index (FFMI) with LDL>70mg/dl and heart failure (OR: 0.4 p = 0.0178 and OR: 1.96 p = 0.078 respectively). Conclusions: The addition of body composition variables by DXA and anthropometric variables, provides valuable information for the study and estimation of cardiovascular and metabolic risk. Key Words: Obesity; DEXA Scans; Coronary Disease; BodyComposition; Body Mass Index; Adiposity.

The Body Mass Index of Blacks and Whites in the United States during the Nineteenth Century

2011 ◽  
Vol 42 (3) ◽  
pp. 371-391 ◽  
Author(s):  
Scott Alan Carson
Keyword(s):  
United States ◽  
Nineteenth Century ◽  
Body Mass Index ◽  
Body Mass ◽  
Rural Areas ◽  
Urban Areas ◽  
The United States ◽  
The Body ◽  
Healthy Weight ◽  
Blacks And Whites

Body mass index (bmi) values reflect the net balance between nutrition, work effort, and calories consumed to fight disease. Nineteenth-century prison records in the United States demonstrate that the bmi values of blacks and whites were distributed symmetrically; neither underweight nor obese individuals were common among the working class. bmi values declined throughout the nineteenth century. By modern standards, however, nineteenth-century bmis were in healthy weight ranges, though the biological living standards in rural areas exceeded those in urban areas. The increase in bmis during the twentieth century did not have its origin in the nineteenth century.

scholarly journals TRUNK BODY MASS INDEX: A NEW REFERENCE FOR THE ASSESSMENT OF BODY MASS DISTRIBUTION

2018 ◽  
Vol 31 (1) ◽  
Author(s):  
Mariane TAKESIAN ◽  
Marco Aurelio SANTO ◽  
Alexandre Vieira GADDUCCI ◽  
Gabriela Correia de Faria SANTARÉM ◽  
Julia GREVE ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Mass Distribution ◽  
Fat Mass ◽  
Preoperative Evaluation ◽  
Fat Distribution ◽  
The Body ◽  
Fat Free Mass ◽  
Super Obesity ◽  
Obesity Class

ABSTRACT Background: Body mass index (BMI) has some limitations for nutritional diagnosis since it does not represent an accurate measure of body fat and it is unable to identify predominant fat distribution. Aim: To develop a BMI based on the ratio of trunk mass and height. Methods: Fifty-seven patients in preoperative evaluation to bariatric surgery were evaluated. The preoperative anthropometric evaluation assessed weight, height and BMI. The body composition was evaluated by bioimpedance, obtaining the trunk fat free mass and fat mass, and trunk height. Trunk BMI (tBMI) was calculated by the sum of the measurements of the trunk fat free mass (tFFM) and trunk fat mass (tFM) in kg, divided by the trunk height squared (m2)). The calculation of the trunk fat BMI (tfBMI) was calculated by tFM, in kg, divided by the trunk height squared (m2)). For the correction and adjustment of the tBMI and tfBMI, it was calculated the relation between trunk extension and height, multiplying by the obtained indexes. Results: The mean data was: weight 125.3±19.5 kg, height 1.63±0.1 m, BMI was 47±5 kg/m2) and trunk height was 0.52±0,1 m, tFFM was 29.05±4,8 kg, tFM was 27.2±3.7 kg, trunk mass index was 66.6±10.3 kg/m², and trunk fat was 32.3±5.8 kg/m². In 93% of the patients there was an increase in obesity class using the tBMI. In patients with grade III obesity the tBMI reclassified to super obesity in 72% of patients and to super-super obesity in 24% of the patients. Conclusion: The trunk BMI is simple and allows a new reference for the evaluation of the body mass distribution, and therefore a new reclassification of the obesity class, evidencing the severity of obesity in a more objectively way.

scholarly journals COMPARISON OF PERCEIVED WEIGHT AS IDEAL AGAINST IDEAL BODY WEIGHT FORMULAS AND BODY MASS INDEX OF 22 KG/M2 IN YOUNG ADULT WOMEN.

2018 ◽  
Vol 17 (1) ◽  
pp. 7-15
Author(s):  
Erik Ramirez López ◽  
Debbie Puente Hernández ◽  
Nohemí Liliana Negrete López ◽  
Araceli Serna-Gutiérrez ◽  
Zuli Calderón Ramos ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Ideal Body Weight ◽  
The Body ◽  
Adult Women ◽  
Healthy Weight ◽  
Frame Size ◽  
Perceived Weight ◽  
Ideal Body

SUMMARYIntroduction: Formulas of ideal body weight (IBW) including the body mass index (BMI) of 22 kg/m2 are used under the assumption to provide a healthy weight. Objective: We compare the perceived ideal body weight (PIBW) with the calculated IBW by formulas and the BMI of 22. Methods: We recruited 705 women (20-25 y). Six common formulas and 2 published equations by our team were used. Results: Group regression analysis determined that including the frame size improves the agreement of formulas of Robinson et al, Hammond and Hamwi with the PIBW (p>0.05). Individually, the concordance analysis (higher % of differences <2 kg: PIBW - IBW by formula), determined that for a measured BMI <20, only the Faspyn 1 formula needs to be adjusted by frame size; while Robinson et al, Hammond, Tokunaga (BMI of 22), Faspyn 2 (BMI of 22) and Broca, are equivalent with the PIBW in different intervals of BMI. Conclusions: According to the BMI perceived as overweight (23.8 kg/m2) and perceived as ideal (21.1 kg/m2), caution is suggested when using the IBW formulas for BMI of 22 as a diagnosis. The IBW formulas and BMI of 22 does not necessarily represent a desirable or aesthetic weight. Comparación del peso percibido como ideal con fórmulas de peso ideal y el IMC de 22 kg/m2 en mujeres jóvenes.RESUMEN Introducción: El peso ideal calculado con fórmulas (PIF) y con el índice de masa corporal (IMC) de 22 kg/m2 se emplea bajo el supuesto de proporcionar un peso saludable o estético. Objetivo: Comparar el peso percibido como ideal (PPI) contra el PIF y del IMC de 22. Métodos: Se reclutaron 705 mujeres (20-25 años). Empleamos seis fórmulas comunes y 2 publicadas previamente. Resultados: El análisis de regresión grupal determinó que incluir la complexión corporal mejora la concordancia de las fórmulas de Robinson et al, Hammond y Hamwi con el PPI (p>0.05). Individualmente, el análisis de concordancia (porcentaje mayor de diferencias <2 kg: PPI-PIF), determinó que para un IMC <20 kg/m2 solo la fórmula de Faspyn 1 debe ajustarse por la complexión corporal, mientras que las fórmulas de Robinson et al, Hammond, Tokunaga (IMC de 22), Faspyn 2 (IMC de 22) y Broca, son equivalentes con el PPI en diferentes intervalos de IMC. Conclusiones: de acuerdo con el IMC percibido como sobrepeso (23.8 kg/m2) y percibido como ideal (21.1 kg/m2), las fórmulas de peso ideal y el IMC de 22 deben ser usados con precaución en el diagnóstico de peso ideal ya que no necesariamente representan un peso deseable o estético. 

scholarly journals The Anthropometric Generalization of the Body Mass Index

2020 ◽  
Author(s):  
alexandru godescu
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
The Body ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
The Difference ◽  
The 19Th Century ◽  
Highly Cited

The classic Body Mass Index, (BMI), developed in the 19th century by the Belgian mathematician Adolphe Quetelet [1] is an important indicator of the risk of death, of obesity, of negative health consequences, body fat percentage and of the shape of the body. While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers [2][3][4][5][9][25] that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. The BMI was developed as a law of natural sciences and &ldquo;social physics&rdquo; [1], as it was called then, before the middle of the 19th century, and it had been used from the 70s for medical purposes, to detect obesity and the risk of mortality [6][7]. The BMI has a huge importance for modern society, affected by an obesity epidemic [8]. BMI has applications in medicine, sport medicine, sport, fitness, bodybuilding, insurance, nutrition, pharmacology. The main limitation of the BMI is that it does not account for body composition including non fat body mass such as muscles, joints, body frame and makes no difference between fat and non fat components of the body weight. The body composition and the proportion of fat and muscles make a difference in health outcomes [12][13][14][25][26][27][35][36][37] [38][39][40][41][42][43][44]&hellip;[100]. Body composition makes a difference also in the level of sport performance for athletes of every level. In nearly two centuries since the Body Mass Index was developed, no formula had been successfully developed to account for body composition and make the difference between muscle and fat in a consistent way. This can be considered a longstanding open problem of major importance for society. The objective of this analysis is to develop new formulae taking into account the health implication of body composition measured through indirect, simple indicators and making the difference between muscles and fat, healthy and non healthy metabolism. The formulae developed in this article are the only formula to successfully generalize BMI and make this difference. I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. No other formula generalized the BMI to make the difference between fat and a large frame and muscles has ever been published in nearly two centuries since the BMI formula had been developed. The formulae I developed explain and generalize the conclusions of a large number of highly cited empirical experiments cited in the reference section. [35][36][37][38][38][39] [40][42][43][44]..[100] Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

scholarly journals Accuracy of Different Indexes of Body Composition and Adiposity in Identifying Metabolic Syndrome in Adult Subjects with Prader-Willi Syndrome

2020 ◽  
Vol 9 (6) ◽  
pp. 1646 ◽  
Author(s):  
Giorgio Radetti ◽  
Antonio Fanolla ◽  
Fiorenzo Lupi ◽  
Alessandro Sartorio ◽  
Graziano Grugni
Keyword(s):  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Area Under The Curve ◽  
Threshold Value ◽  
The Body ◽  
Fat Free Mass ◽  
Prader Willi Syndrome ◽  
Better Than

(1) Objective: To compare the accuracy of different indexes of adiposity and/or body composition in identifying metabolic syndrome (MetS) in adult patients suffering from Prader‒Willi syndrome (PWS). (2) Study Design: One hundred and twenty PWS patients (69 females and 51 males), aged 29.1 ± 9.4 years, body mass index (BMI) 36.7 ± 9.9, were evaluated. The following indexes were assessed in each subject: body mass index (BMI), fat-free mass index (FFMI), fat mass index (FMI), tri-ponderal mass index (TMI), waist-to-height ratio (WtHR) and the body mass fat index (BMFI), which adjusts the BMI for the percentage of body fat and waist circumference. Thereafter, a threshold value adjusted for age and sex, which could identify MetS, was calculated for each index. (3) Results: A significant correlation was found among all indexes (p < 0.0001 for all). However, when the area under the curve (AUC) was compared, BMFI performed better than FMI (p < 0.05) and BMI better than TMI (p < 0.05), but only in females. (4) Conclusions: Besides small differences, all the indexes taken into consideration seem to have the same ability to identify MetS in adults with PWS. Consequently, the most easily calculated index, i.e., BMI, should be considered as the best choice. The use of thresholds appropriate for sex and age can further improve its accuracy.

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