scholarly journals Body mass index: a measure of fatness or leanness?

1995 ◽  
Vol 73 (4) ◽  
pp. 507-516 ◽  
Author(s):  
Alan M. Nevill ◽  
Roger L. Holder
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Normal Range ◽  
Percentage Body Fat ◽  
Distributional Properties ◽  
Two Indices ◽  
The Relationship

The relationship between body fat and stature-adjusted weight indices was explored. Assuming the term height2 is a valid indicator of a subject's lean body mass, height2/weight was shown to be an accurate measure of percentage lean body mass and, as such, a better predictor of percentage body fat than the traditional body mass index (BMI; weight/height2). The name, lean body mass index (LBMI), is proposed for the index height2/weight. These assumptions were confirmed empirically using the results from the Allied Dunbar National Fitness Survey (ADNFS). Using simple allometric modelling, the term heightp explained 74% of the variance in lean body mass compared with less than 40% in body weight. For the majority of ADNFS subjects the fitted exponent from both analyses was approximately p = 2, the only exception being the female subjects aged 55 years and over, where the exponent was found to be significantly less than 2. Using estimates of percentage body fat as the dependent variable, regression analysis was able to confirm that LBMI was empirically, as well as theoretically, superior to the traditional BMI. Finally, when the distributional properties of the two indices were compared, BMI was positively skewed and hence deviated considerably from a normal distribution. In contrast, LBMI was found to be both symmetric and normally distributed. When height and weight are recorded in centimetres and kilograms respectively, the suggested working normal range for LBMI is 300–500 with the median at 400.

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 Influence of adiposity and fatigue on the scapular muscle recruitment order

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7175
Author(s):  
Guillermo Mendez-Rebolledo ◽  
Eduardo Guzman-Muñoz ◽  
Rodrigo Ramírez-Campillo ◽  
Pablo Valdés-Badilla ◽  
Carlos Cruz-Montecinos ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Body Fat ◽  
Skinfold Thickness ◽  
The Body ◽  
Excess Body Weight ◽  
Onset Latency ◽  
Percentage Body Fat ◽  
Recruitment Order

Background Several authors have indicated that excess body weight can modify the electromyographic (EMG) amplitude due to the accumulation of subcutaneous fat. This accumulation of adipose tissue around the muscle would affect the metabolic capacity during functional activities. On the other hand, some authors have not observed differences in the myoelectric manifestations of fatigue between normal weight and obese people. Furthermore, these manifestations have not been investigated regarding EMG onset latency, which indicates a pattern of muscle activation between different muscles. The objective of this study was to determine whether an increase in body weight, skinfolds, and muscle fatigue modify the trapezius and serratus anterior (SA) onset latencies and to determine the scapular muscle recruitment order in fatigue and excess body weight conditions. Methods This cross-sectional study was carried out in a university laboratory. The participants were randomly assigned to the no-fatigue group (17 participants) or the fatigue (17 participants) group. The body mass index, skinfold thickness (axillary, pectoral, and subscapular), and percentage of body fat were measured. In addition, the onset latency of the scapular muscles [lower trapezius (LT), middle trapezius (MT), upper trapezius (UT), and SA] was assessed by surface EMG during the performance of a voluntary arm raise task. A multiple linear regression model was adjusted and analyzed for the additive combination of the variables, percentage body fat, skinfold thickness, and fatigue. The differences in onset latency between the scapular muscles were analyzed using a three-way repeated measure analysis of variance. In all the tests, an alpha level <0.05 was considered statistically significant. Results For the MT, LT, and SA onset latencies, the body mass index was associated with a delayed onset latency when it was adjusted for the additive combination of percentage of body fat, skinfold thickness, and fatigue. Of these adjustment factors, the subscapular skinfold thickness (R2 = 0.51; β = 10.7; p = 0.001) and fatigue (R2 = 0.86; β = 95.4; p = 0.001) primarily contributed to the increase in SA onset latency. A significant muscle ×body mass index ×fatigue interaction (F = 4.182; p = 0.008) was observed. In the fatigue/excess body weight condition, the UT was activated significantly earlier than the other three scapular muscles (p < 0.001) and SA activation was significantly delayed compared to LT (p < 0.001). Discussion Excess body weight, adjusted for skinfold thickness (axillary and subscapular) and fatigue, increases the onset latency of the MT, LT, and SA muscles and modifies the recruitment order of scapular muscles. In fact, the scapular stabilizing muscles (MT, LT, and SA) increase their onset latency in comparison to the UT muscle. These results were not observed when excess body weight was considered as an individual variable or when adjusted by the percentage body fat.

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.

Prevalence of obesity using the body mass index and equivalent age- and sex-specific thresholds for percentage body fat mass

2013 ◽  
Vol 7 ◽  
pp. e93
Author(s):  
Julie A. Pasco ◽  
Haslinda Gould ◽  
Kara L. Holloway ◽  
Amelia G. Dobbins ◽  
Mark A. Kotowicz ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
The Body ◽  
Body Fat Mass ◽  
Percentage Body Fat ◽  
Equivalent Age ◽  
Prevalence Of Obesity ◽  
Age And Sex

Serum leptin levels and energy expenditure in normal weight women

1998 ◽  
Vol 76 (2) ◽  
pp. 237-241 ◽  
Author(s):  
L J Martin ◽  
PJH Jones ◽  
R V Considine ◽  
W Su ◽  
N F Boyd ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Food Intake ◽  
Energy Expenditure ◽  
Body Mass ◽  
Body Fat ◽  
Positive Association ◽  
Normal Weight ◽  
Serum Leptin ◽  
Percentage Body Fat ◽  
Healthy Humans

To investigate whether circulating leptin levels are associated with energy expenditure in healthy humans, doubly labeled water energy measurements and food intake assessment were carried out in 27 women (mean age, 48.6 years; weight, 61.9 kg; body mass index, 23.2). Energy expenditure was determined over 13 days. Food intake was measured by 7-day food records. Leptin was measured by radioimmunoassay. Leptin level was strongly associated with percentage body fat (r = 0.59; p < 0.001), fat mass (r = 0.60; p < 0.001), and body mass index (r = 0.41; p = 0.03), but no correlation was observed with energy expenditure (r = 0.02; p = 0.93). After controlling for percentage body fat, a positive association of leptin level with energy expenditure of marginal significance (p = 0.06) was observed. There were no significant univariate associations of age, physical activity, lean body mass, height, or dietary variables with leptin level. When controlling for body fat, a significant positive correlation was observed for percent energy from carbohydrate and negative correlations with dietary fat and alcohol intake. These findings confirm previous associations between leptin and body fat content and suggest a relationship between serum leptin and energy expenditure level in healthy humans.Key words: leptin, energy expenditure, body composition, diet.

scholarly journals Paternal body mass index before conception associated with offspring's birth weight in Chinese population: a prospective study

2021 ◽  
Author(s):  
Renying Xu ◽  
Weixiu Zhao ◽  
Tao Tan ◽  
Haojie Li ◽  
Yanping Wan
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Birth Weight ◽  
Body Mass ◽  
Sensitivity Analyses ◽  
Gestational Weight ◽  
A Prospective Study ◽  
The Relationship ◽  
Multivariable Adjustment ◽  
Chinese Mother

Whether paternal epigenetic information of nutrition might be inherited by their offspring remained unknown. evaluate the relationship between preconception paternal body weight and their offspring's birth weight in 1,810 Chinese mother-father-baby trios. Information on paternal and maternal preconception body weight and height was collected via a self-reported questionnaire. Birth weight was collected from medical records. Paternal preconception body weight was associated with offspring's birth weight (p trend=0.02) after multivariable adjustment. Each standard deviation increment of paternal body mass index was associated with an additional 29.6 g increase of birth weight (95% confident interval: 5.7g, 53.5g). The association was more pronounced in male neonates, and neonates with overweight mothers, and with mothers who gained excessive gestational weight, compared to their counterparts (all p interaction<0.05). Sensitivity analyses showed similar pattern to that of the main analysis. Paternal preconception body weight was associated with birth weight of their offspring.

scholarly journals Cardiorespiratory Fitness in University Level Volleyball Players and its Correlation with Body Fat

2020 ◽  
Vol 27 (3) ◽  
pp. 15-19
Author(s):  
Archana Khanna ◽  
Ankita Singh ◽  
Bhanu Pratap Singh ◽  
Faiz Khan
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Cardiorespiratory Fitness ◽  
Body Fat ◽  
Vigorous Physical Activity ◽  
Step Test ◽  
Male And Female ◽  
Percentage Body Fat ◽  
Volleyball Players ◽  
University Level

Abstract Introduction. The present study was aimed to compare the cardiorespiratory fitness levels (VO2max) between university level male and female volleyball players and to find its correlation with percentage body fat. Material and Methods. In the present cross-sectional study, male and female volleyball players (n = 15 each) aged 18-25 years were randomly selected from Teerthanker Mahaveer University, Moradabad, India. An equal number of sedentary individuals were also selected who did not indulge in any vigorous physical activity or training. Body height, body weight, body mass index (BMI), % lean body mass of players and sedentary individuals were recorded using standard methods. Percentage body fat was calculated using the sum of four skinfolds and VO2max was recorded using Queen’s college step test. Data were analysed using SPSS software version 20.0. Unpaired t-test was used for comparison between players and sedentary individuals and two-way ANOVA was used to examine interaction of status (active players and sedentary individuals) and gender on VO2max. Results. Players had higher mean values for % lean body mass and VO2max. Statistically, highly significant differences (p < 0.05) were observed between male and female players for all variables except BMI. Players had better cardiorespiratory fitness (VO2max) as compared to their sedentary counterparts. Conclusions. Significant differences exist between players and sedentary individuals for percentage body fat and percentage lean body mass. Cardiorespiratory fitness of players is negatively correlated with percentage body fat. Players have higher VO2max as compared to their sedentary counterparts.

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