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.

Dietary Energy Density is Associated with Body Mass Index and Fat Mass in Early Adulthood

2019 ◽  
pp. 105477381988319
Author(s):  
María Correa-Rodríguez ◽  
Emilio González-Jiménez ◽  
Ángel Fernández-Aparicio ◽  
Jose Luis Gómez-Urquiza ◽  
Jacqueline Schmidt-RioValle ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Young Adults ◽  
Body Composition ◽  
Energy Density ◽  
Body Mass ◽  
Fat Mass ◽  
Fat Free Mass ◽  
Dietary Energy ◽  
Mass Percent ◽  
Dietary Energy Density

A cross-sectional study was conducted to investigate the association between body composition parameters as well as body mass index (BMI), and dietary energy density in a population of 538 young adults. Fat mass, fat mass percent, fat-free mass, and visceral fat were measured using a body composition analyzer. Daily energy intake was assessed using a 72-hr diet recall, and dietary energy density was calculated. Significant differences in dietary energy density among underweight, normal-weight and overweight/obesity young adults were identified ( M = 1.42, SD = 0.26 vs. M = 1.52, SD = 0.46 vs. M = 1.66, SD = 0.53, p = .002). Dietary energy density was associated with BMI (β = .961; CI 95% = 0.335, 1.586; p = .0030), fat mass percent (β = 1.921; CI 95% = 0.707, 3.135; p = .002), and fat mass (β = 2.146; CI 95% = 0.827, 3.466; p = .001). Dietary energy density might be considered as an important aspect in the obesity nutritional education programs in young people.

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 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

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.

scholarly journals Gender Differences in Body Image Misperception According to Body Mass Index, Physical Activity, and Health Concern among Korean University Students

2019 ◽  
Vol 15 (1) ◽  
pp. e1-e9 ◽  
Author(s):  
Woo-Suk Chung ◽  
Ki Ok Shin ◽  
Ju Yong Bae
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Gender Differences ◽  
Body Image ◽  
University Students ◽  
Body Mass ◽  
The Body ◽  
Health Concern ◽  
Healthy Weight ◽  
Image Perception

Background and Objective The purpose of this study was to investigate the gender differences in body image misperception, analyzed according to the body-mass index (BMI), physical activity, and health concern among Korean university students. Material and Methods Three-hundred-and-thirty-nine students participated. Body image misperception was examined through data on subjective body image perception and differences in the measured BMI. Results A total of 45.9% of the male students perceived their body shape measurements to be lower and 18.9% of the female students perceived them to be higher than the actual values. Body image misperception, according to the BMI, significant differences by gender were observed in the underweight (p < .045), standard weight (p < .000), and overweight groups (p < .000). For body image misperception, according to the amount of physical activity, significant differences by gender were observed in the inactivity (p < .001), minimum activity (p < .000), and health-enhancing activity groups (p < .000); significant differences by gender were also observed in the low health concern (p < .000) and high health concern groups (p < .000). Conclusion The prevalence of body image misperception was high, and the degree of misperception varies by gender. Therefore, educational efforts to reduce instances of body image misperception are needed for healthy weight management, and these efforts should take into consideration the gender differences.

scholarly journals Seasonal and Longitudinal Changes in Body Composition by Sport-Position in NCAA Division I Basketball Athletes

Sports ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 85 ◽  
Author(s):  
Jennifer Fields ◽  
Justin Merrigan ◽  
Jason White ◽  
Margaret Jones
Keyword(s):  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Ncaa Division I ◽  
The Body ◽  
Fat Free Mass ◽  
Strength And Conditioning ◽  
Air Displacement Plethysmography ◽  
Within Subjects

The purpose of this study was to assess the body composition of male and female basketball athletes (n = 323) across season, year, and sport-position using air displacement plethysmography. An independent sample t-test assessed sport-position differences. An analysis of variance was used to assess within-subjects across season (pre-season, in-season, and off-season), and academic year (freshman, sophomore, and junior). For both men and women basketball (MBB, WBB) athletes, guards had the lowest body fat, fat mass, fat free mass, and body mass. No seasonal differences were observed in MBB, but following in-season play for WBB, a reduction of (p = 0.03) in fat free mass (FFM) was observed. Across years, MBB showed an increase in FFM from freshman to sophomore year, yet remained unchanged through junior year. For WBB across years, no differences occurred for body mass (BM), body fat (BF%), and fat mass (FM), yet FFM increased from sophomore to junior year (p = 0.009). Sport-position differences exist in MBB and WBB: Guards were found to be smaller and leaner than forwards. Due to the importance of body composition (BC) on athletic performance, along with seasonal and longitudinal shifts in BC, strength and conditioning practitioners should periodically assess athletes BC to ensure preservation of FFM. Training and nutrition programming can then be adjusted in response to changes in BC.

scholarly journals Agreement and association between different indicators of body image and body mass index in adolescents

2014 ◽  
Vol 17 (3) ◽  
pp. 747-760 ◽  
Author(s):  
Carla Fernandez dos Santos ◽  
Inês Rugani Ribeiro de Castro ◽  
Letícia de Oliveira Cardoso ◽  
Letícia Ferreira Tavares
Keyword(s):  
Body Mass Index ◽  
Body Image ◽  
Nutritional Status ◽  
Body Mass ◽  
Private Schools ◽  
Weighted Kappa ◽  
Continuous Variable ◽  
The Body ◽  
Kappa Statistics ◽  
Image Variables

The aim of the study was to examine the correlation among different indicators of body image; between each one of these and nutritional status; and the association of these indicators with the Body Mass Index (BMI) of adolescents. A random sample of 152 students from public and private schools in the city of Rio de Janeiro, Brazil, was studied. On four occasions, two silhouette scales and two questions regarding the opinion of the student about his/her body and weight were applied and weight and height were measured. The BMI was examined both as a continuous and as a categorical variable. The agreement between the variables was analyzed using the quadratic weighted Kappa statistics. The association between body image variables and BMI was examined by the comparison among median, mean, standard deviation and 95% confidence interval of BMI for each category of the body image variables. In general, the correlation among the body image variables ranged from reasonable to good; between these and the variable nutritional status, correlation ranged from regular to reasonable. Best results were observed among boys and students from private schools. All body image variables showed good discriminatory power for BMI, when it was analyzed as a continuous variable, even when controlling for potential confounders. The question about body seems to be better than that about weight to compose the questionnaire of a surveillance system for risk and protective factors for adolescent health.

Relationships Between the Body Mass Index and Body Composition

1996 ◽  
Vol 4 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Rita I. Wellens ◽  
Alex F. Roche ◽  
Harry J. Khamis ◽  
Andrew S. Jackson ◽  
Michael L. Pollock ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
The Body

scholarly journals Perception of Body Image and Dietary Habit Among Adults Aged 20–45 Years at Sunyani Metropolis

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 277-277
Author(s):  
Jacob Setorglo ◽  
Philip Narteh Gorleku ◽  
Kyei Roselyn ◽  
Kingsley Kwadwo Asare Pereko
Keyword(s):  
Body Mass Index ◽  
Body Image ◽  
Body Size ◽  
Body Mass ◽  
Who Classification ◽  
The Body ◽  
World Health ◽  
Outcome Variable ◽  
Sugar Consumption ◽  
Normal Body

Abstract Objectives The study assessed the body size perception of respondents against the WHO body mass index and related the body sizes to fat and sugar consumption among 20–45-year-old adults. Methods The study design was a descriptive cross-sectional survey which involved 200 respondents aged 20–45 years, sampled conveniently. at Sunyani. Data on socio-demographic, fat and sugar consumption, anthropometry (weight in kg, height in cm) were collected. The weight and height data were later converted into body mass index using the World Health Organisation (WHO) classification. Sugar and fat intakes were measured by dietary food based assessment. (Analysis was done using IBM SPSS version 25. Proportions were presented for categorical values. Chi square test of association was used to determine relationship between the independent and the dependent outcome variable. Statistical significant was set at and P &lt; 0.05. Results The mean age of the respondents was 35 years. About 35.0% of respondents were males and the rest 65.0% females. Sugar and fat consumption among the respondents were within the recommended dietary allowances. Although 75% of respondents had normal body mass index (kg/m2) and 21% were obese based on the WHO classification, Majority (43.0%) of them perceived their body weights were normal. About 48.1% perceived they are either obese or had normal body size. There was no statistically significant association between respondents’ perceived body image and socio-demographic characteristics except for marital status (X2 = 8.82, P = 0.044). There was no statistically significant association between body image perception and dietary intake of fat and sugar. Conclusions There is great disparity in the perception of respondents body image compared to the WHO classification and married women and men are more particular about how they look. Dietary components studied do not have any association with body image. Funding Sources None.

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