scholarly journals The impact of adjustment of a weight-height index (W/H2) for frame size on the prediction of body fatness

1985 ◽  
Vol 54 (2) ◽  
pp. 335-342 ◽  
Author(s):  
Maartje A. Rookus ◽  
Jan Burema ◽  
Paul Deurenberg ◽  
Wilhelmina A. M. Van Der Wiel-Wetzels
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Body Height ◽  
The Body ◽  
Frame Size ◽  
Body Fatness ◽  
Percentage Of Body Fat ◽  
Body Diameter ◽  
The Impact

1. The impact of frame-size categories in weight-height tables was studied by comparing the efficiency of the body-mass index (weight/height2 (W/H2)) and weight adjusted for body-height and a body-diameter, W/(H2Dp), in predicting body fatness.2. Body-weight, body-height, six body-diameters and four skinfold thicknesses were measured in ninety-five men and seventy women, aged between 23 and 35 years. Percentage of body fat was calculated from skinfold thicknesses using regression equations according to Durnin & Womersley (1974).3. The inclusion of a body-diameter increased the explained variation of body fatness from 57% to 62% (knee) and 63% (shoulder) in men and from 63% to 69% (knee) in women.4. It can be concluded that in the present population the efficiency of the prediction of percentage of body fat was not improved markedly by the inclusion of a body-diameter in the body-mass index, thus giving no support for the inclusion of frame-size categories in weight-height tables.

scholarly journals Factors Predicting the Response to a Vitamin D-Fortified Milk in Healthy Postmenopausal Women

Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2641 ◽  
Author(s):  
Rebeca Reyes-Garcia ◽  
Antonia Garcia-Martin ◽  
Santiago Palacios ◽  
Nancy Salas ◽  
Nicolas Mendoza ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Vitamin D ◽  
Postmenopausal Women ◽  
Body Mass ◽  
Body Fat ◽  
Dietary Intervention ◽  
The Body ◽  
Hydroxyvitamin D ◽  
Percentage Of Body Fat ◽  
Fortified Milk

Background: Milk products fortified with vitamin D may constitute an alternative to pharmacological supplements for reaching the optimal levels of serum 25-hydroxyvitamin D [25(OH)D]. Our aim was to analyze the response of serum 25(OH)D and its predictive factors in postmenopausal healthy women after a dietary intervention with a milk fortified with vitamin D and calcium. Methods: We designed a prospective study including 305 healthy postmenopausal women who consumed a fortified milk with calcium (900 mg/500 mL) and vitamin D3 (600 IU/500 mL) daily for 24 months. Results: The 25(OH)D concentrations at 24 months were correlated to weight, to body mass index, to the percentage of fat, triglycerides and to baseline 25(OH)D levels. We found significant differences in the levels of 25(OH)D at 24 months according to baseline 25(OH)D levels (p < 0.001) and body mass index (p = 0.019) expressed at quartiles. Multivariate analysis showed an association between levels of 25(OH)D after the intervention and at baseline 25(OH)D (Beta = 0.47, p < 0.001) and percentage of body fat (Beta = −0.227, p = 0.049), regardless of the body mass index. Conclusions: In healthy postmenopausal women, the improvement in 25(OH)D after an intervention with a fortified milk for 24 months depends mainly on the baseline levels of serum 25(OH)D and on the percentage of body fat.

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 Body fatness, relative weight and frame size in young adults

1982 ◽  
Vol 48 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Jos A. H. Baecke ◽  
Jan Burema ◽  
Paul Deurenberg
Keyword(s):  
Body Weight ◽  
Body Fat ◽  
Body Height ◽  
Age Groups ◽  
Relative Weight ◽  
Regression Equations ◽  
Frame Size ◽  
Body Fatness ◽  
Percentage Of Body Fat ◽  
Skinfold Measurements

1. Body-weight, body height, knee width, wrist width and skinfold measurements were made on males (n 139) and females (n 167) in three age-groups (20–22, 25–27 and 30–32 years). Percentage of body fal was calculated from skinfold thicknesses using regression equations according to Durnin & Womersley (1974), Three indices of relative weight were calculated: W/H2, W/Hp and W/Ŵ, where W is body-weight, H is body height, p is the exponent that made the index of relative weight independent of height and W is the weight, estimated from body height and frame size.2. The standard error of the estimate of body-weight was only reduced by 5% in males and by 13% in females when, in addition to body height, knee width was taken into account.The addition of wrist width did not improve the accuracy of estimation of body-weight in either sex. Therefore in further analyses W was estimated from body height and knee width. In the present population the exponent p was 1·7 in males and 1·6 in females.3. The correlations between the percentage of body fat and the indices, W/H2, W/HP, and W/Ŵ, were all very similar, being approximately 0·8 in both sexes.4. A positive relationship was observed between percentage of body fat and knee width in females, which may be explained by an artifact of measurement.5. In conclusion it can be stated that the accuracy of estimation of percentage of body fat was not improved when the index of relative weight was adjusted for knee width or wrist width in the present population. The W/H2was the most preferable of the three indices which were calculated.

scholarly journals Using body mass index ignores the intensive training of elite special force personnel

2019 ◽  
Vol 244 (11) ◽  
pp. 873-879 ◽  
Author(s):  
Erwin Tafeit ◽  
Gerhard Cvirn ◽  
Manfred Lamprecht ◽  
Markus Hohensinn ◽  
Reinhard Moeller ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Muscle Mass ◽  
Body Mass ◽  
Body Fat ◽  
Task Force ◽  
Large Body ◽  
Overweight And Obesity ◽  
The Body ◽  
Body Fatness ◽  
Intensive Training

Body mass index is a common and well-known measure in daily life. A body mass index higher than 25 is assumed to be an indicator for overweight and obesity and a high amount of total body fat. But body mass index overestimates body fat in subjects with high muscle mass and underestimates it in persons with a low lean body mass, especially in elderly and diseased persons. In the present study, we investigate the performance of the body mass index as a measure of body fatness and its ability to distinguish between well-trained and untrained subjects. Twenty-one well-trained male members of a police task force named “Cobra” and 38 non-active controls, matched by age, weight and height were participants of the study. The age range of these subjects was between 30 and 45 years. Subcutaneous adipose tissue thicknesses and body fat distributions were measured non-invasively by an optical device named the “Lipometer.” Statistics were performed with SPSS. We found that the body mass index did not show a difference between the two groups, whereas all Lipometer results were able to discriminate significantly between the trained and untrained subjects. Furthermore, the receiver operating characteristic curve analysis was calculated and all Lipometer measurements provided significant results up to a correct classification of all subjects of 86.4%, which was for the lateral thigh body site. In conclusion, the body mass index was not able to recognize the difference between trained and untrained participants, while body fat distribution measured with the Lipometer was able to distinguish more clearly the large body fat differences between these two groups. Impact statement Body mass index (BMI) is a common measure of body fatness but overestimates body fat in subjects with high muscle mass. We have developed previously a device named “Lipometer,” an alternative way to measure body fatness. We show herein that the Lipometer is able to distinguish more clearly (than the BMI) the large body fat differences between well-trained and untrained subjects. Thus, the Lipometer is superior to BMI with respect to body fat measurements.

scholarly journals Body Mass Index, Multi-Morbidity, and COVID-19 Risk Factors as Predictors of Severe COVID-19 Outcomes

2021 ◽  
Vol 12 ◽  
pp. 215013272110185
Author(s):  
Sanjeev Nanda ◽  
Audry S. Chacin Suarez ◽  
Loren Toussaint ◽  
Ann Vincent ◽  
Karen M. Fischer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Hospital Admission ◽  
Body Mass ◽  
Risk Score ◽  
The Body ◽  
Risk Scores ◽  
Nasopharyngeal Swab ◽  
Morbidity Score ◽  
The Impact

Purpose The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes. Patients Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Measures Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death. Results Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes. Conclusion Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

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

scholarly journals The Impact of Nutritional Status and Body Mass Index on Rehabilitation Outcomes in Patients Receiving Home-Based Medical Care

2020 ◽  
Vol 3 (2) ◽  
pp. 15
Author(s):  
Kanako Eiwa ◽  
Naomi Nakayama ◽  
Yumi Takami ◽  
Shuko Iwasaki ◽  
Yoshinori Hino ◽  
...  
Keyword(s):  
Body Mass Index ◽  
At Risk ◽  
Nutritional Status ◽  
Medical Care ◽  
Body Mass ◽  
Functional Independence ◽  
The Body ◽  
Rehabilitation Outcomes ◽  
Home Based ◽  
The Impact

Background: Home-based medical care is expanding rapidly in Japan.Objectives: We aimed to identify the factors associated with outcomes of therapy in patients receiving home-visit rehabilitation.Methods: One hundred twenty-one patients receiving home-based rehabilitation were investigated. Nutritional status was assessed by the Mini Nutritional Assessment Short Form (MNA-SF). The Functional Independence Measure (FIM) was employed to assess the activities of daily living (ADL). The body mass index (BMI), medical history, and orthopedic disease-related pain were also recorded. The primary outcome was the improvement in FIM scores in one year.Results: A total of 19 (17%) patients were malnourished and 58 (48%) were at risk of malnutrition. Malnourished patients had a lower FIM score at initiation than those at risk of malnutrition or with normal nutritional status. Only changes in patients’ BMI and MNA-SF scores over one year were significantly associated with improved FIM scores (p = 0.0079 and p = 0.0049, respectively). No association was noted with the other factors.Conclusions: This is the first report to demonstrate that changes in MNA-SF scores and BMI are significantly associated with rehabilitation outcomes in home-based care. Nutritional management is essential along with rehabilitation to improve ADL in the long-term home care setting.

scholarly journals Prevalence of Obesity and the Relationship between the Body Mass Index and Body Fat: Cross-Sectional, Population-Based Data

PLoS ONE ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. e29580 ◽  
Author(s):  
Julie A. Pasco ◽  
Geoffrey C. Nicholson ◽  
Sharon L. Brennan ◽  
Mark A. Kotowicz
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Population Based ◽  
The Body ◽  
Cross Sectional ◽  
Prevalence Of Obesity ◽  
The Relationship
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