scholarly journals The Anthropometric Generalization of the Body Mass Index

Author(s):  
alexandru godescu

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 “social physics” [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]…[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

Author(s):  
Katie M. Heinrich ◽  
Konstantin G. Gurevich ◽  
Anna N. Arkhangelskaia ◽  
Oleg P. Karazhelyaskov ◽  
Walker S. C. Poston

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.


2021 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Suci Eka Putri ◽  
Adelina Irmayani Lubis

Body mass index (BMI) is to monitor nutritional status adults, especially those related to deficiency and overweight. Body fat percentage can describe the risk of degenerative diseases.This study was conducted to measure the relationship between BMI and body fat percentage. Methods An analytical study was conducted to 41 male and 51 female participant from Universitas Teuku Umar. The body weight was measured using scales, whereas the body height was measured using microtoise. The body fat percentage was measured using Karada Scan. The BMI was calculated by dividing the body weight in kilogram divided by body height in meter square. Data was collected from 16-18th February 2021 and analyzed by Pearson’s correlation test. The results showed BMI underweight, normal, and overweight were 10,9, 57,6, and 31,5. High body fat percentage in men were 75,6% and in women were 35,5%. There is a relationship between the nutritional status of the women group and the body fat percentage with p-value is obtained = 0.021. Furthermore, for men, there is no relationship between nutritional status in the men group and the body fat percentage. There is a relationship between nutritional status and body fat percentage in women. Among this population, BMI can still be used to determine body fat percentage


Author(s):  
Stevo POPOVIC ◽  
Boris BANJEVIC ◽  
Bojan MASANOVIC ◽  
Dusko BJELICA

Background: The body composition and physical fitness of members of the army is always a relevant topic for research, since the level of defense and security of people and material goods in a specific territory in many ways depends on the level of ability of the army. However, members of the armed forces are a heterogeneous group, typified by different abilities, characteristics, but also everyday needs, and the trend of changing body composition and reducing physical fitness is a current issue that has not bypassed this population either. Therefore, this study aimed to determine possible differences in body composition indicators that could appear between members of the Army of Montenegro of different military specialties. Methods: The sample of respondents included 240 Montenegrin male soldiers (32.5yr±9.5), who were measured at the sports dispensaries within the barracks of Montenegrin Army around the country in the spring of 2020, was classified into eight numerically equal subsamples according to their military specialty. The sample of variables included five anthropometric measures, which were necessary to calculate two derived body composition indicators: Body Mass Index (BMI) and Body Fat Percentage (FAT %). Using the one-way ANOVA and Post Hoc test with Taki’s model, the variables were analyzed. Results: It was determined that the body composition of Montenegrin soldiers shows a certain peculiarity compared to other national military corps, while there are differences in body composition indicators between members of the Montenegrin Army of different military specialties. Conclusion: This fact dramatically strengthens the issues of Montenegrin distinctive regarding body composition, both in general terms and in terms of distinctive within specific professional vocations.  


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ewa Jednacz ◽  
Lidia Rutkowska-Sak

The study was aimed to evaluate cardiovascular risk parameters, body mass index (BMI) centiles for sex and age, and body fat percentage using the electric bioimpedance method in children with juvenile idiopathic arthritis (JIA). 30 children with JIA participated in the study. A control group included 20 children. Patients were well matched for the age and sex. The body mass and body fat percentage were determined using the segmental body composition analyser; the BMI centiles were determined. All patients had the following parameters determined: lipid profile, hsCRP, homocysteine, and IL-6. The intima media thickness (IMT) was measured. Patients with JIA had significantly lower body weight, BMI, and the BMI centile compared to the control group. The IL-6 levels were significantly higher in patients with JIA compared to the control group. There were no differences between two groups with regard to the lipid profile, % content of the fat tissue, homocysteine levels, hsCRP, and IMT. Further studies are necessary to search for reasons for lower BMI and BMI centile in children with JIA and to attempt to answer the question of whether lower BMI increases the cardiovascular risk in these patients, similarly as in patients with rheumatoid arthritis (RA).


Author(s):  
Alexandru Godescu

The Body Mass Index (BMI) formula has been developed by Belgian mathematician Adolphe Quetelet and published in 1840 [1] as a law of nature and society, based on statistics about the weight and height of the population of that time, the first part of the 19th century. He called it “social physics”. From then, for nearly two centuries, the BMI had been the most important formula describing the normal relations and ratio of weight to the square of the height for humans. The problem arises if the BMI formula, developed in the first part of the 19th century is still good today when the type of work people perform is very different? In modern times, most people are less muscular than at the time when the BMI was developed because they do not work physically as heavy as at that time. In many cases, the Body Mass index can predict mortality, morbidity and illness but not always, for example cases such as (a) the obesity paradox for some cardiovascular problems and (b) the U shape mortality paradox as well as (c) false positive obesity diagnostic in regard to people who are strong and muscular, have low body fat percentage but are classified as obese by the BMI and (d) cases where BMI is normal but people have an “obese metabolism” (e) BMI normal but high fat percentage. The objective is to develop a formula good for all body types, a formula that makes the difference between fat and non-fat body weight such as muscle and body frame and quantifies the effect of strength and fitness, which BMI does not. Another objective is to develop a formula to predict the health risks and fitness status of people, better than BMI. The first generalizations of BMI using anthropometric metrics could be found in [2], where I discuss and analyze many formulae, developed, tested, and simulated by me, using similar new methods, accounting for body shape, physical shape and body function, making the difference between muscle mass and fat, fat and non fat body weight. Nearly all formulae and methods developed and proposed in this new model are new, never published before. Many experiments published before, in highly cited papers show that grip strength and muscle strength is a predictor of health, mortality, morbidity, endocrine and metabolic disease outside the BMI and anthropometric measures. The purpose of my formula is to explain the outcome of those experiments and create a formula which predicts these experiments [21-41].


2021 ◽  
Vol 5 (3) ◽  
pp. 242
Author(s):  
Nurul Hikma ◽  
Zakiyatul Faizah ◽  
Rize Budi Amalia

AbstractBackground: The menstrual cycle can be said to be normal if the interval is between 21-35 days. The prevalence rates associated with menstrual cycle disorders were found in the range of 15.8-89.5. Nutritional status is one of the factors that cause menstrual cycle disorders, where nutritional status can be determined using body mass index and measuring the percentage of fat in the body. The purpose of this study was to determine the relationship between nutritional status and the menstrual cycle using the literature review method. The formulation of the problem in this research is determined by PICO, namely: "is there a relationship between nutritional status and menstrual cycle disorders?". A total of 749 literary works obtained from the Google Scholar, Science Direct, PubMed and ProQuest databases were used as a literature review source, where in screening the literature the inclusion and exclusion criteria were seen, which had previously been determined so that finally six literatures were reviewed. Results: The cause of menstrual cycle disorders has been found in adolescents with an average value of 18.4-37.8 and the percentage of body fat between 12.80-34.80. Conclusion: Based on all literature that has been reviewed, it can be concluded that menstrual cycle disorders have a significant relationship with body mass index and body fat percentage.


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