scholarly journals Grip Strength Generalization of the Body Mass Index

2020 ◽  
Author(s):  
Alexandru Godescu
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Grip Strength ◽  
19Th Century ◽  
Body Mass ◽  
Fat Body ◽  
The Body ◽  
Fat Percentage ◽  
The Difference ◽  
The 19Th Century

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].

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 “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

scholarly journals The Relationship Between Body Mass Index with Body Fat Percentage of Participants EXPO 2021 Universitas Teuku Umar

2021 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Suci Eka Putri ◽  
Adelina Irmayani Lubis
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Nutritional Status ◽  
Body Mass ◽  
Body Fat ◽  
Body Height ◽  
The Body ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
The Relationship

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

scholarly journals Biometric Measures, Body Score and Body Mass Index Evaluation in Wild Coatis (Nasua Nasua) Living in the South-Central Region of São Paulo State, Brazil

2019 ◽  
Vol 47 (1) ◽  
Author(s):  
Barbara Sardela Ferro ◽  
Alícia Giolo Hippólito ◽  
Maria Cristina Reis Castiglioni ◽  
José Ivaldo De Siqueira Silva Junior ◽  
Carlos Roberto Teixeira ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Body Condition ◽  
Body Condition Score ◽  
The Body ◽  
Abdominal Circumference ◽  
Fat Percentage ◽  
Nasua Nasua ◽  
Condition Score

Background: Coatis (Nasua nasua) have easy interaction with man, besides being sociable and curious animals. The proximity to urbanized areas encourages them to intake food from anthropogenic sources, and it can change their eating habits and make them prone to obesity. The body condition evaluates the animals’ energetic status and measures variations in their body fat reserves. There are direct-invasive methods and indirect methods that rely on size and body mass to evaluate the body condition, like body condition score and body mass index. Thus, the aim of the present study was to assess different methods to determine the body condition of wild coatis (Nasua nasua) living in urban areas.Materials, Methods & Results: Sixteen (16) wild coatis (Nasua nasua), nine females and seven males, were captured at Faculty of Veterinary Medicine and Animal Science (FMVZ) of São Paulo State University, Botucatu, in pitfalls. The animals were anesthetized with ketamine and midazolam and subjected to biometric evaluation after physical exams proved normal. The following variables were analyzed: body weight, body condition score (BCS) based on the five-point scale for dogs, thoracic and abdominal circumference, height at the withers, spine length and distance from the patella to the calcaneus. Two body mass index (BMI) were calculated from these data, one was based on dogs (BMI1) and another one on cats (BMI2), as well as the body fat percentage (%BF). Results showed that 25% of the assessed coatis were overweight. Body weight, thoracic and abdominal circumference, height at the withers, spine length and distance from the patella to the calcaneus were significantly higher in males than in females and the other assessed parameters did not present differences between sexes. The correlation between fat percentage and body weight was significant, and that between fat percentage and BCS was not. There was closer correlation between BMI2 and body weight, and BCS, than between BMI1 and these two parameters.Discussion: Anthropogenic interactions could change the body condition of these animals and make them prone to obesity, since their body condition scores were altered. With regard to the nutritional body condition, although males were bigger than females, the measures did not show significant differences between them. Results of this parameter varied in different studies with coatis, some studies have shown that males have body mass 1/3 higher than that of females and others have not recorded any difference between sexes. Fat percentage estimated through the metrics used in cats is not a good method when it is applied alone in body condition evaluations. A study that has correlated body mass, body condition score, body fat estimates, body mass index and abdominal circumference recorded positive results between these two evaluation methods. Such finding corroborated with the present study, but it was differed from it in abdominal circumference, which did not correlate to the two body mass indices and to body fat percentage. Therefore, it is possible saying that there is biometric difference between male and female coatis. The body condition score adopted for dogs was efficient for coatis (Nasua nasua), as well as the body mass index used for dogs and cats – the one used for cats was even more efficient. The proximity wild coatis (Nasua nasua) have to humans could change the body condition of these animals and make them prone to obesity.

scholarly journals Effects of Triphala on Lipid and Glucose Profiles and Anthropometric Parameters: A Systematic Review

2021 ◽  
Vol 26 ◽  
pp. 2515690X2110110
Author(s):  
Wiraphol Phimarn ◽  
Bunleu Sungthong ◽  
Hiroyuki Itabe
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Blood Glucose ◽  
Waist Circumference ◽  
Lipid Profile ◽  
Body Mass ◽  
The Body ◽  
Current Evidence ◽  
Diabetic Patients ◽  
Anthropometric Parameters

Aim. The efficacy of triphala on lipid profile, blood glucose and anthropometric parameters and its safety were assessed. Methods. Databases such as PubMed, ScienceDirect, Web of Science, and Thai Library Integrated System (ThaiLIS) were systematically searched to review current evidence of randomized controlled trials (RCT) on triphala. RCTs investigating the safety and efficacy of triphala on lipid profile, blood glucose and anthropometric parameters were included. Study selection, data extraction, and quality assessment were performed independently by 2 authors. Results. Twelve studies on a total of 749 patients were included. The triphala-treated groups showed significantly reduced low-density lipoprotein-cholesterol, total cholesterol and triglyceride in 6 studies. Five RCTs demonstrated triphala-treated groups led to statistically significant decrease in body weight, body mass index and waist circumference of obese patients. Moreover, triphala significantly decreased fasting blood glucose level in diabetic patients but not in people without diabetes. No serious adverse event associated with triphala was reported during treatment. Conclusions. This review summarized a current evidence to show triphala might improve the lipid profile, blood glucose, the body weight, body mass index and waist circumference under certain conditions. However, large well-designed RCTs are required to confirm this conclusion.

Asociación entre la composición corporal y la condición física en estudiantes de grado sexto, pertenecientes a la institución educativa moderna de Tuluá, Colombia año 2019 (Association between body composition and the physical condition in sixth grade st

Retos ◽  
2020 ◽  
pp. 539-546
Author(s):  
Luis Hebert Palma Pulido ◽  
Carlos Hernán Méndez Díaz ◽  
Alfonso Cespedes Manrrique ◽  
Jorge Andrés Castro Mejía ◽  
Alejandro Viveros Restrepo ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Fat Mass ◽  
Physical Condition ◽  
Pearson Correlation ◽  
Sixth Grade ◽  
The Body ◽  
Fat Percentage ◽  
Cardiovascular Capacity

 El siguiente estudio, tuvo como finalidad, determinar la correlación entre la composición corporal y la condición física en niños de sexto grado de la Institución Educativa de Tuluá, Colombia. El estudio fue no experimental, descriptivo y de alcance correlacional. La valoración de la composición corporal, se realizó mediante el índice de masa corporal y el porcentaje de grasa (fórmula de Slaughter y Lohmann). La condición física, se determinó por medio de la batería Fitnessgram. La muestra fue de 193 niños y niñas, entre ocho y 12 años. Los resultados se determinaron, por medio de estadísticos descriptivos y correlación de Pearson. Estos resultados, evidenciaron una r=-0,52 y -0,72 para niño y niña respectivamente, entre el porcentaje de grasa y la capacidad cardiovascular. Las correlaciones entre el índice de masa corporal y peso corporal, con el porcentaje de grasa fueron, r=0,59 niña 0,76 y niño y r=0,46 niña y 0,67 niño respectivamente, indicando que, a mayor masa corporal mayor grasa. La correlación entre masa grasa y el test de barra fija fue inversa, pero no alta, r=-0,23 y -0,24, sin embaro, cuando este test se correlacionó con el índice de masa corporal, dicha correlación fue mayor, r=-0,57 y -0,78, reflejando que, la masa corporal, afectó la resistencia en la barra. La flexibilidad y agilidad, no se alteraron por la masa grasa, r < 0,20. Como conclusión, se evidencia que, la masa grasa puede disminuir la capacidad cardiovascular y resistencia a la fuerza, sin embargo, la flexibilidad y la velocidad-agilidad pueden no alterarse.  Abstract. The following study aimed at determining the correlation between body composition and physical condition in sixth grade students from the high school Institución Educativa Moderna in Tuluá, Colombia. It was carried as a non-experimental, descriptive, and correlational study. The assessment of body composition was carried out using the body mass index and the fat percentage based on Slaughter and Lohmann formula. Physical condition was determined by using the Fitnessgram battery. The sample consisted of 193 boys and girls, around eight and 12 years old. The results were determined by means of descriptive statistics and Pearson correlation. These results showed r = -0.52 and -0.72 for boys and girls respectively, after correlating the percentage of fat and cardiovascular capacity. The correlation of their body mass index and their body weight, towards the percentage of fat were: r = 0.59 girl, 0.76 boy and r = 0.46 girl and 0.67 boy respectively, indicating that, the higher the body mass the higher the increase of fat. The correlation between fat mass and the fixed bar test was inverse, but not high: r = -0.23 and -0.24. However, when this test was correlated with the body mass index, that correlation was higher: r = -0.57 and -0.78, reflecting that the body mass affected the resistance at the bar. Flexibility and agility were not altered by fat mass: r <0.20. In conclusion, it is evidenced that fat mass can decrease cardiovascular capacity and resistance to strength, however, flexibility and speed-agility may not be altered.

Clinical Observations on Laser Acupuncture in Simple Obesity Therapy

2010 ◽  
Vol 38 (05) ◽  
pp. 861-867 ◽  
Author(s):  
Wen-Long Hu ◽  
Chih-Hao Chang ◽  
Yu-Chiang Hung
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Therapeutic Effect ◽  
Body Mass ◽  
The Body ◽  
Laser Acupuncture ◽  
Acupuncture Points ◽  
Percent Reduction ◽  
Simple Obesity ◽  
Restrictive Diet

A previous study has shown that laser acupuncture is a useful healing method for the treatment of visceral postmenopausal obesity in combination with a low-calorie diet. We observe and evaluate the therapeutic effect of laser acupuncture in subjects of simple obesity with a non-restrictive diet protocol. Subjects included 73 women and 22 men with simple obesity and body mass indices ≥ 27 kg/m2. Daily energy intake recommendations for obese females and males were 1620.0 and 1894.2 kcal in average, respectively. The gallium aluminum arsenide Handylaser Trion was used to apply 0.25 J of energy to each of the following acupuncture points three times per week for four consecutive weeks: Stomach, Hunger, ST25, ST28, ST40, SP15, and CV9. The subjects' body weights and body mass indices were recorded before treatment, and four weeks after treatment, and the percent reduction in each parameter was calculated. Statistically significant reductions in body weight and body mass index were detected after four weeks of treatment. The mean reduction and mean percent reduction in body weight were 3.17 kg and 3.80% (p < 0.0001), respectively. The corresponding values for the body mass index were 1.22 kg/m2 and 3.78% (p < 0.0001), respectively. We concluded that laser acupuncture was found to exert a therapeutic effect on simple obesity by reducing both body weight and body mass index. Moreover, subjects showed good compliance with this comfortable and non-restrictive diet protocol.

scholarly journals The effects of three-week fasting diet on blood pressure, lipid profile and glucoregulation in extremely obese patients

2007 ◽  
Vol 135 (7-8) ◽  
pp. 440-446 ◽  
Author(s):  
Biljana Beleslin ◽  
Jasmina Ciric ◽  
Milos Zarkovic ◽  
Zorana Penezic ◽  
Svetlana Vujovic ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Body Weight ◽  
Insulin Sensitivity ◽  
Lipid Profile ◽  
Body Mass ◽  
Glucose Intolerance ◽  
The Body ◽  
Obese Patients

Introduction Obesity is often accompanied by a number of complications including diabetes mellitus and cardiovascular diseases. Elevated blood pressure and lipids, as well as deterioration of glucoregulation are attributed, as the most significant factors, to development of diabetes mellitus and cardiovascular complications in obese patients. Objective The aim of our study was to evaluate the effects of a fasting diet on blood pressure, lipid profile and glucoregulatory parameters. Method We included 110 patients (33 male and 77 female; mean age 35?1 years, body weight 131.7?2.6 kg, body mass index 45.4?0.8 kg/m2) who were hospitalized for three weeks for the treatment of extreme obesity with the fasting diet. At the beginning, during, and at the end of this period, we evaluated changes in blood pressure, lipid profile, as well as parameters of glucoregulation including glycaemia, insulinaemia, and insulin sensitivity by HOMA. Oral glucose tolerance test (OGTT) was performed in all patients at the beginning and at the end of the fasting diet. Results During the fasting diet, the body weight decreased from 131.7?2.6 kg to 117.7?2.4 kg (p<0.001), the body mass index decreased from 45.4?0.8 kg/m2 to 40.8?0.8 kg/m2 (p<0.001), and both systolic and diastolic blood pressure significantly declined (143?2 vs. 132?2 mm Hg, p<0.001; 92?2 vs. 85?2 mm Hg, p<0.001). In addition, the fasting diet produced a significant decrease in total cholesterol, LDL cholesterol, triglycerides, as well as basal glycaemia and insulinaemia (p<0.001) Before the fasting diet, OGTT was normal in 76% of patients, whereas 21% of patients showed glucose intolerance, and 4% of patients diabetes mellitus. After the fasting diet, OGTT was normal in 88% of patients, whereas 12% of patients still had signs of glucose intolerance (p<0.05). In addition, insulin resistance significantly (p<0.05) increased from 54?6% to 89?13% after the fasting diet. Conclusion The three-week fasting diet in extremely obese patients produced a significant decrease and normalization of blood pressure, decrease in lipids, and improvement in glucoregulation including the increase in insulin sensitivity.

scholarly journals Relationship between Body Mass Index (BMI) and Anemia Among Adolescent Indonesian Girls (Analysis of The Indonesia Family Life Survey 5th Data)

2021 ◽  
Vol 5 (4) ◽  
pp. 347
Author(s):  
Rieza Enggardany ◽  
Lucia Yovita Hendrati ◽  
Noran Naqiah Hairi
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Nutritional Status ◽  
Body Mass ◽  
Young Women ◽  
Family Life ◽  
The Body ◽  
Normal Body Mass Index ◽  
Measurement Results ◽  
Prevalence Of Anemia

ABSTRACTBackground: Anemia is a condition characterized by low levels of hemoglobin (Hb) from normal limits. Anemia is still a public health problem. Data states that the prevalence of anemia in Indonesia in 2013 was 21.7%, with the number of sufferers known to be higher in women than men. The prevalence of anemia in the age range 15 to 24 years was 18.4%. Nutritional status shows the balance of nutrients due to the consumption, absorption, and use of nutrients that come from food in the body. A person's nutritional status can be said to be deficient if the body lacks intake of one or more essential nutrients for the body. One of the indicators for assessing a person's nutritional status is the Body Mass Index (BMI). Inadequate nutritional status will affect the nutritional status of iron in a person' s body so that it can be interpreted that nutritional status is one of the factors of anemia. Consuming foods with good nutritional value, especially foods that contain high iron will also affect the nutritional status of these adolescents so that the risk of suffering from anemia will decrease.Objective: This study aims to analyze the relationship between body mass index and anemia among young women in Indonesia.Methods: This study is a cross-sectional study. The data used are secondary data from the Indonesian Family Life Survey (IFLS) 5. The population of this study was all Indonesians who participated in IFLS 5. The sample used in this study amounted to 3,525 respondents. IInclusion criteria of this study included female, aged 10-18 years, unmarried, having complete data regarding body weight, height and hemoglobin measurement results. If data related to the measurement results of hemoglobin, body weight, height are incomplete, they will be excluded.The statistical test was used is a chi-square test.Results: There was a relationship between Body Mass Index (BMI) and anemia among young women in Indonesia (p = 0.034 <0.05).Based on the odd ratio analysis using the normal Body Mass Index (BMI) group as a comparison, it is known that young women with underweight BMI categories have a 1.198 greater risk of experiencing anemia than girls with normal BMI categories.Conclusion: There is a relationship between BMI and anemia in adolescent girls. It is important for young women to always pay attention to daily iron intake by eating foods that are rich in iron or taking blood-booster tablets (TTD) to avoid anemia.

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