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Body Composition

Body Composition refers to the relative amounts of fat, bone, water, and muscle in the human body.
Accurate assessment of body composition is crucial for optimizing health, fitness, and athletic performance.
PubCompare.ai is a powerful AI-driven platform that helps researchers and practitioners easily locate the most effective body composition optimization protocols from scientific literature, pre-prints, and patents.
With intelligent comparison tools, PubCompare.ai enhances research accuracy and provides the most effective solutions for your body composition needs.
Experince the future of body composition optimization today.

Most cited protocols related to «Body Composition»

1
Measuring Body Composition with DEXA and BIA
Total body fat mass and total bone-free lean mass (kg) were acquired from total body scans using fan-beamed dual-energy x-ray absorptiometry (Hologic, Waltham, MA or Lunar, Madison, WI) using standardized protocols (35 (link),36 (link)). Appendicular lean mass (ALM) was the sum of lean mass from both arms and legs. Participants missing lean mass measurements for an arm or leg were excluded. The validity and reproducibility of dual-energy x-ray absorptiometry have been reported previously. In Invecchiare in Chianti, body composition was measured using peripheral quantitative computed tomography of the calf. For Invecchiare in Chianti, estimated ALM was available only in men and was derived from equations from Osteoporotic Fractures in Men Study that included height, weight, waist circumference, fat area, muscle area, and muscle density. In Age, Gene/Environment Susceptibility-Reykjavik Study, body composition was measured with bioelectrical impedance (Xitron Hydra ECF/ICF Bio-Impedance Spectrum Analyzer).
Studenski S.A., Peters K.W., Alley D.E., Cawthon P.M., McLean R.R., Harris T.B., Ferrucci L., Guralnik J.M., Fragala M.S., Kenny A.M., Kiel D.P., Kritchevsky S.B., Shardell M.D., Dam T.T, & Vassileva M.T. (2014). The FNIH Sarcopenia Project: Rationale, Study Description, Conference Recommendations, and Final Estimates. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 69(5), 547-558.
Publication 2014
Bioelectrical Impedance Body Composition Body Fat Bone Density Dual-Energy X-Ray Absorptiometry Fracture, Bone Genetic Predisposition to Disease Hydra Muscle Tissue Silver Waist Circumference Whole Body Imaging X-Ray Computed Tomography
2
Mathematical Model for Growth and Metabolism

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Publication 2013
Acclimatization Adolescent Adult Body Composition Body Weight Child Energy Metabolism Food Human Body Macronutrient Metabolism Physical Examination Physiological Processes Resting Metabolic Rate
3
Nonalcoholic Steatohepatitis Therapeutic Trial
The trial design and rationale for the PIVENS trial have been described previously.16 (link) This trial focused on adults without diabetes who had nonalcoholic steatohepatitis. Adults with diabetes were excluded because it was unclear whether they would have the same responses to therapy as would adults without diabetes and because it was possible that changes in antidiabetic therapy might confound the analysis of data both from subjects with diabetes and from those without diabetes. All subjects underwent a liver biopsy within 6 months before randomization.
Steatohepatitis was categorized as absent, possible, or definite.17 (link) Disease activity was assessed with the use of the nonalcoholic fatty liver disease activity score, which is based on a standardized grading system for steatosis (on a scale of 0 to 3), lobular inflammation (on a scale of 0 to 3), and hepatocellular ballooning (on a scale of 0 to 2), with higher scores indicating increasing severity).17 (link) The specific inclusion criteria were definite or possible steatohepatitis with an activity score of 5 or more, or definite steatohepatitis (confirmed by two pathologists) with an activity score of 4. A score of at least 1 for hepatocellular ballooning was required in all cases. Although eligibility was determined by the pathologist at each site from an assessment of tissue sections prepared locally, the final analysis was based on review by a pathology committee of deeper cuts, prepared centrally, from the biopsy specimens obtained at baseline and at the end of treatment. Members of the pathology committee who performed the final analysis were unaware of the study-group assignments.
Exclusion criteria were alcohol consumption of more than 20 g per day in the case of women and more than 30 g per day in the case of men for at least 3 consecutive months during the previous 5 years, as assessed with the use of the Lifetime Drinking History questionnaire of Skinner et al.18 (link) and the self-administered Alcohol Use and Disorders Identification Test (AUDIT).19 (link) Subjects were also excluded if they had cirrhosis, hepatitis C or other liver diseases, or heart failure (New York Heart Association class II to IV), or if they were receiving drugs known to cause steatohepatitis.
Both at the initial evaluation and at the completion of treatment 96 weeks later, subjects underwent an assessment of body weight, height, and waist and hip circumferences, and blood samples were obtained for routine biochemical tests and assessment of fasting levels of lipids, glucose, and insulin. Body composition was assessed with the use of dual-energy x-ray absorptiometry. The Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) was administered for the assessment of quality of life.
Sanyal A.J., Chalasani N., Kowdley K.V., McCullough A., Diehl A.M., Bass N.M., Neuschwander-Tetri B.A., Lavine J.E., Tonascia J., Unalp A., Natta M.V., Clark J., Brunt E.M., Kleiner D.E., Hoofnagle J.H, & Robuck P.R. (2010). Pioglitazone, Vitamin E, or Placebo for Nonalcoholic Steatohepatitis. The New England journal of medicine, 362(18), 1675-1685.
Publication 2010
Adult Antidiabetics Biopsy BLOOD Body Composition Body Weight Committee Members Congestive Heart Failure Diabetes Mellitus Dual-Energy X-Ray Absorptiometry Eligibility Determination Glucose Heart Hepatitis C virus Inflammation Insulin Lipids Liver Liver Cirrhosis Liver Diseases Non-alcoholic Fatty Liver Disease Nonalcoholic Steatohepatitis Pathologists Pharmaceutical Preparations Steatohepatitis Tissues Woman
4
Genomic Epidemiology of Cardiovascular Traits
Data from 62,266 participants from the following eleven studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium [3] (link) were included in this joint calling experiment and study descriptions were published previously: Age, Gene/Environment, Susceptibility-Reykjavik (AGES) Study [8] (link), Atherosclerosis Risk in Communities (ARIC) Study [9] (link), Cardiac Arrest Blood Study (CABS) [10] (link), Cardiovascular Health Study (CHS) [11] (link), [12] (link), Coronary Artery Risk Development in Young Adults (CARDIA) [13] (link), [14] (link), Multi-Ethnic Study of Atherosclerosis (MESA) [15] (link), Family Heart Study (FamHS) [16] (link), Framingham Heart Study (FHS) [17] (link), Health, Aging, and Body Composition (HABC) Study [18] (link), Jackson Heart Study (JHS) [19] , and the Rotterdam Study (RS) [20] –[23] (link). In addition, we genotyped 96 unrelated HapMap samples (48 CEU and 48 YRI) with each cohort and the list of sample IDs are available as a reference on the CHARGE exome chip public website.
Grove M.L., Yu B., Cochran B.J., Haritunians T., Bis J.C., Taylor K.D., Hansen M., Borecki I.B., Cupples L.A., Fornage M., Gudnason V., Harris T.B., Kathiresan S., Kraaij R., Launer L.J., Levy D., Liu Y., Mosley T., Peloso G.M., Psaty B.M., Rich S.S., Rivadeneira F., Siscovick D.S., Smith A.V., Uitterlinden A., van Duijn C.M., Wilson J.G., O’Donnell C.J., Rotter J.I, & Boerwinkle E. (2013). Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium. PLoS ONE, 8(7), e68095.
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Publication 2013
Artery, Coronary Atherosclerosis BLOOD Body Composition Cardiac Arrest Cardiovascular System DNA Chips Exome Genes Genome HapMap Heart Joints Susceptibility, Disease Young Adult
5
Bioimpedance Spectroscopy for Fluid Assessment in Hemodialysis
Body composition and hydration state were assessed with a portable whole body bioimpedance spectroscopy device (BCM—Fresenius Medical Care D GmbH). The BCM measures the impedance spectroscopy at 50 frequencies. Measurements were performed before the start of the HD treatment with the patient sitting relaxed in the dialysis chair. Electrodes were attached to one hand and one foot on the same side of the body. All measurements were performed by one trained nurse—no failure of measurement especially due to possible electrical interference was recorded. The fluid volumes extracellular (ECW), intracellular (ICW) and total body water (TBW) were determined using the approach described by Moissl [17 (link)]. The hydration status, lean tissue mass (LTM) and fat mass were calculated based on a physiologic tissue model described by Chamney [25 (link)]. To facilitate the comparison between patients, the hydration state was normalized to the ECW (ΔHS = HS/ECW). The patient population was divided into a hyperhydrated and a normohydrated groups using a cutoff of 15% for the relative hydration status (ΔHS > 15%). The definition of hyperhydration for ΔHS > 15% is based on the work described by Wabel et al. [26 (link)]. The boundary of ΔHS > 15% represents the highest quartile of the measured population. The normohydrated group also included patients with mild overhydration (6,8% < ΔHS ≤ 15%), and these patient groups were not separated for further analysis. LTM and Fat were normalized to the body surface area to obtain lean tissue index (LTI = LTM/height2) and fat tissue index (FTI = Fat/height2). The values for LTI and FTI were compared to an age- and gender-matched reference population (n = 1248) [27 (link)]. Values below the 10th percentile of the reference population were regarded as clinically significant. It has been demonstrated in studies in HD patients that the reproducibility of the used BIS device [coefficient of variation (CVECW = 2.6%; CVTBW = 2.6%)] is far superior to the reproducibility of clinical measurements like the blood pressure (CVBPsyspre = 8.5%; CVBPsyspost = 15.7%) [28 (link)]. Therefore, only one BCM measurement was performed, while the blood pressure was averaged for six consecutive dialysis treatments as described by Agarwal [29 (link)].
The hydration status at the end of the treatments (HSpost) was calculated by subtracting the UFV from the hydration status at the start of the treatment (HSpre).
Wizemann V., Wabel P., Chamney P., Zaluska W., Moissl U., Rode C., Malecka-Masalska T, & Marcelli D. (2009). The mortality risk of overhydration in haemodialysis patients. Nephrology Dialysis Transplantation, 24(5), 1574-1579.
Publication 2009
Blood Pressure Body Composition Body Surface Area Dialysis Dielectric Spectroscopy Electricity Foot Gender Human Body Medical Devices Nurses Patients physiology Protoplasm Spectrum Analysis Tissues Water, Body Water Intoxication

Most recents protocols related to «Body Composition»

1
Tracking Body Composition Changes with Aging
Changes in body composition are a normal part of ageing and often occur simultaneously with declines in physical function. Anthropometric measurements were made to provide a quantitative measure of body composition, obesity and body fat distribution that is related to overall health status and can be tracked over time. Standing height and weight were measured using standard techniques, BMI was computed as weight/height2 (kg/m2).
Waist and hip measurements were recorded using a SECA measuring tape. The waist was measured midway between the iliac crest and the costal margin (lower rib) while the hip circumference was measured at the widest circumference over the buttocks and below the iliac crest. Measurements were repeated twice. Waist-to-hip ratio was calculated as a measure of body fat distribution which is an important indicator of risk of cardiovascular disease [9 (link)]. Percentage body fat was also measured using the Bodystat 1500 MDD body composition analyser. This measures the amount of lean and fat mass that makes up total body weight.
Neville C.E., Young I.S., Kee F., Hogg R.E., Scott A., Burns F., Woodside J.V, & McGuinness B. (2023). Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA): health assessment protocol, participant profile and patterns of participation. BMC Public Health, 23, 466.
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Publication 2023
Body Composition Body Fat Body Weight Buttocks Costal Arch Iliac Crest Measure, Body Obesity Physical Examination Waist-Hip Ratio
2
Sarcopenia in Heart Failure Patients
Seventy-seven patients aged ≥ 65 years old with similar diet and environmental conditions in the Second Xiangya Hospital of Central South University were enrolled in this study. Patients were classified into the following 3 categories: 33 HF patients without sarcopenia (HF group), 29 HF patients with sarcopenia (SHF group), and 15 control individuals (Control group). Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 Guidelines (Chen et al., 2020 (link)). Low skeletal muscle mass was defined as muscle mass < 7.0 kg/m2 (male) or < 5.7 kg/m2 (female) by bioelectrical impedance analysis using the InBodyS10 body composition analyzer (Chen et al., 2014 (link)). Low muscle strength was defined as handgrip strength <28 kg for male and <18 kg for female. Criteria for low physical performance is a 6-m walk speed < 1 m/s. Sarcopenia was defined as low muscle mass plus either diminished muscle strength or physical performance. Exclude subjects included recurrent diarrhea or constipation, unusual dietary habits (vegetarians), edema, those with tumors, diabetes, intestinal inflammation, irritable bowel syndrome, history of intestinal surgery, being treated with antibiotics or probiotics within 1 month. Demographic characteristics and clinical laboratory examinations were documented for all patients. The study was approved by the local Ethics Committee of the Second Xiangya Hospital of Central South University. Written informed consent was obtained from all participants. This study was conducted under the Declaration of Helsinki.
Peng J., Gong H., Lyu X., Liu Y., Li S., Tan S., Dong L, & Zhang X. (2023). Characteristics of the fecal microbiome and metabolome in older patients with heart failure and sarcopenia. Frontiers in Cellular and Infection Microbiology, 13, 1127041.
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Publication 2023
Antibiotics, Antitubercular Asian Persons Bioelectrical Impedance Body Composition Clinical Laboratory Services Constipation Diabetes Mellitus Diarrhea Edema Inflammation Intestines Irritable Bowel Syndrome Males Muscle Strength Muscle Tissue Neoplasms Operative Surgical Procedures Patients Performance, Physical Physical Examination Probiotics Regional Ethics Committees Sarcopenia Skeletal Muscles Therapy, Diet Vegetarians Woman
3
Assessing Sarcopenia and Myosteatosis Using CT Scans
CT scans within 1 month prior to TACE or in the first post-TACE were selected to measure body composition. Pre-TACE scans were preferentially chosen. When these were unavailable, the earliest post-TACE scans were used in the study. The CT images at the level of the third lumbar vertebra (L3) were carefully chosen and archived as Digital Imaging and Communications in Medicine (DICOM) data. All DICOM data calculated body composition using in-house software developed by MATLAB (The MathWorks, Natick, MA, USA) and freeware Python 3.6.13 (Anaconda, Inc.), to generate the measurement model based on neural network architecture also known as UNet. The valid accuracy of the model was 99.17% and validity of the intersect over union co-efficiency was 89.40%17 (link).
The L3 skeletal muscle index (SMI) is used to identify sarcopenia and is calculated by dividing the cross-sectional area of the muscle by the square of the patient's height (cm2/m2). Sarcopenia was defined as SMI ≤ 36.2 cm2/m2 and ≤ 29.6 cm2/m2 for males and females, respectively11 (link). The areas of the abdominal wall and back muscles were used to calculate the SMD based on the areas of the pixels with attenuation between − 29 and + 150 HU. Myosteatosis was defined as SMD ≤ 44.4 HU or ≤ 39.3 HU in males and females, respectively11 (link). In addition, patients were classified into four groups according to their sarcopenia and myosteatosis status (Group A—neither sarcopenia nor myosteatosis, Group B—sarcopenia without myosteatosis, Group C—myosteatosis without sarcopenia, and Group D—sarcopenia with myosteatosis).
Bannangkoon K., Hongsakul K., Tubtawee T., Ina N, & Chichareon P. (2023). Association of myosteatosis with treatment response and survival in patients with hepatocellular carcinoma undergoing chemoembolization: a retrospective cohort study. Scientific Reports, 13, 3978.
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Publication 2023
ADAM17 protein, human Anaconda Body Composition Females Males Muscle, Back Muscle Tissue Patients Pharmaceutical Preparations Python Radionuclide Imaging Sarcopenia Skeletal Muscles Vertebrae, Lumbar Wall, Abdominal X-Ray Computed Tomography
4
Analyzing Mouse Body Composition using Echo MRI
The body composition of mice was analysed using an Echo MRI 3-in-1 scanner (Echo MRI, Houston, TX, USA).
Thompson D., Mahmood S., Morrice N., Kamli-Salino S., Dekeryte R., Hoffmann P.A., Doherty M.K., Whitfield P.D., Delibegović M, & Mody N. (2023). Fenretinide inhibits obesity and fatty liver disease but induces Smpd3 to increase serum ceramides and worsen atherosclerosis in LDLR−/− mice. Scientific Reports, 13, 3937.
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Publication 2023
Body Composition ECHO protocol Mice, House
5
Whole-Body Composition Evaluation by NMR
Body composition, including whole-body fat mass and lean mass, were analyzed by a nuclear magnetic resonance system (Body Composition Analyzer QMR06-090H, Niumag Corporation, Shanghai, China).
Zhang X., Wang L., Wang Y., He L., Xu D., Yan E., Guo J., Ma C., Zhang P, & Yin J. (2023). Lack of adipocyte IP3R1 reduces diet-induced obesity and greatly improves whole-body glucose homeostasis. Cell Death Discovery, 9, 87.
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Publication 2023
Body Composition Body Fat Magnetic Resonance Imaging

Top products related to «Body Composition»

1
Lunar idxa by GE Healthcare
Sourced in United States, United Kingdom, Japan, Germany, Belgium, Denmark
The Lunar iDXA is a dual-energy X-ray absorptiometry (DXA) system used for the measurement of bone mineral density and body composition. It provides accurate and precise assessments of bone, lean, and fat mass.
2
Lunar prodigy by GE Healthcare
Sourced in United States, United Kingdom, Germany, Belgium, Japan, Morocco
The Lunar Prodigy is a bone densitometry system designed for the assessment of bone mineral density (BMD) and body composition. It utilizes dual-energy X-ray absorptiometry (DXA) technology to provide accurate and reproducible measurements.
3
Bc 418ma by Tanita
Sourced in Japan, United Kingdom, Germany, United States, Netherlands
The BC-418MA is a body composition analyzer that measures body weight, body fat percentage, and other body composition parameters. It uses bioelectrical impedance analysis (BIA) technology to provide detailed information about an individual's body composition.
4
Bodpod by Cosmed
Sourced in United States, Italy, Germany
The BodPod is a lab instrument used to measure body composition. It utilizes air displacement plethysmography to determine an individual's body volume, from which their body density and body composition can be calculated.
5
Echomri by Echo Medical Systems
Sourced in United States
The EchoMRI is a laboratory equipment product designed for medical imaging. It utilizes magnetic resonance imaging (MRI) technology to capture detailed images of the body's internal structures.
6
Bc 418 by Tanita
Sourced in Japan, United States, Germany, United Kingdom
The BC-418 is a body composition analyzer that measures body weight, body fat percentage, and other body composition metrics through bioelectrical impedance analysis. It provides accurate and reliable data for health and fitness assessments.
7
Qdr 4500a by Hologic
Sourced in United States, United Kingdom, New Zealand
The QDR 4500A is a dual-energy X-ray absorptiometry (DXA) system designed for bone density measurements. It is a diagnostic medical device used to assess bone mineral density (BMD) and evaluate the risk of osteoporosis.
8
Stadiometer by Seca
Sourced in Germany, United Kingdom, United States, Japan, Jamaica, Switzerland, Brazil
A stadiometer is a medical device used to measure a person's height. It consists of a vertical scale, typically marked in centimeters or inches, with a horizontal headpiece that can be lowered to rest on top of the person's head, allowing for an accurate measurement of their stature.
9
Discovery a by Hologic
Sourced in United States, United Kingdom, New Zealand
The Discovery A is a laboratory equipment product designed for molecular diagnostic testing. It is a compact, automated system that performs nucleic acid extraction, amplification, and detection. The Discovery A is capable of processing multiple sample types and is intended for use in clinical and research laboratories.
10
Lunar prodigy advance by GE Healthcare
Sourced in United States, United Kingdom, Italy, Belgium, Germany
The Lunar Prodigy Advance is a dual-energy X-ray absorptiometry (DXA) system designed for bone mineral density (BMD) assessment. It utilizes low-dose X-rays to measure the bone density of the spine, hip, and other skeletal sites. The system provides precise and reproducible measurements to aid in the diagnosis and management of osteoporosis and other bone-related conditions.

More about "Body Composition"

Body composition refers to the relative proportions of fat, bone, water, and muscle in the human body.
Accurate assessment of body composition is crucial for optimizing health, fitness, and athletic performance.
Key techniques for measuring body composition include Lunar iDXA, Lunar Prodigy, BC-418MA, BodPod, EchoMRI, BC-418, QDR 4500A, Stadiometer, and Discovery A.
These advanced tools provide detailed insights into an individual's body makeup, allowing for personalized fitness and nutrition planning.
By understanding your body composition, you can make informed decisions to achieve your desired physique, whether it's building muscle, reducing fat, or maintaining a healthy balance.
PubCompare.ai is a powerful AI-driven platform that helps researchers and practitioners easily locate the most effective body composition optimization protocols from scientific literature, pre-prints, and patents.
With intelligent comparison tools, PubCompare.ai enhances research accuracy and provides the most effective solutions for your body composition needs.
Experience the future of body composition optimization today and take control of your health and fitness journey.