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Body composition measurements: Interpretation finally made easy for clinical use
Abstract
This review presents the latest clinical applications of bioelectrical impedance analysis. It discusses the evaluation of nutritional status by using fat-free mass and body fat, percentiles of fat-free mass and body fat, height-normalized fat-free mass and body fat mass indices and a resistance/reactance vector graph.
Fat-free mass and body fat can be used to evaluate nutritional status by comparing individuals or groups of individuals with themselves or with reference values. Percentile distributions are also useful in determining whether individuals or groups fall within the population range. Percentile ranks can also be used to define nutritional depletion and obesity. The use of the fat-free mass and body fat mass indices has the advantage of compensating for differences in body height. The use of low, normal, high and very high fat-free mass and body fat mass indices ranges that correspond to underweight, normal, overweight and obese body mass index categories further aid in the nutritional assessment process. With vector bioelectrical impedance analysis, an individual impedance vector is compared with the 50, 75, and 95% tolerance ellipses calculated in the reference, healthy population, allowing evaluation in any clinical condition. More accurate estimates of conventional bioelectrical impedance analysis equations might be obtained in individuals with a normal impedance vector.
The assessment of fat-free mass and body fat provides valuable information about changes in body composition with weight gain or loss and physical activity, and during ageing. The use of percentiles and height-normalized fat-free mass and body fat permit the classification of patients as under or overnourished.
... The analysis of body composition in community clinical settings often relies on BIA due its affordability, relatively safe usage and general portability. Electrical impedance generated via BIA provides the means to estimate body cell mass through the reactance (Xc) and total body water through the resistance (R) [55,56]. Importantly, the calculation of FFM using BIA requires the use of validated equations that account for age, health status and racial/ethnic background [52,55,57]. ...
... Electrical impedance generated via BIA provides the means to estimate body cell mass through the reactance (Xc) and total body water through the resistance (R) [55,56]. Importantly, the calculation of FFM using BIA requires the use of validated equations that account for age, health status and racial/ethnic background [52,55,57]. Given that BIA is dependent on tissue-specific conductivity, altered states of hydration and chronic fluid imbalances adversely affect the accuracy and reliability of the body composition estimates [55,58]. ...
... Importantly, the calculation of FFM using BIA requires the use of validated equations that account for age, health status and racial/ethnic background [52,55,57]. Given that BIA is dependent on tissue-specific conductivity, altered states of hydration and chronic fluid imbalances adversely affect the accuracy and reliability of the body composition estimates [55,58]. Therefore limitations to using BIA to assess post-exercise adaptations in people with CKD may be associated with peripheral edema, changes in diuretic use and the timing of hemodialysis procedures in those with ESRD. ...
Skeletal muscle wasting has gained interest as a primary consequence of chronic kidney disease (CKD) due to the relationship between skeletal muscle mass, mortality and major adverse cardiovascular events in this population. The combination of reductions in physical function, skeletal muscle performance and skeletal muscle mass places individuals with CKD at greater risk of sarcopenia. Therefore the monitoring of skeletal muscle composition and function may provide clinical insight into disease progression. Dual-energy X-ray absorptiometry and bioelectrical impedance analysis are frequently used to estimate body composition in people with CKD within clinical research environments, however, their translation into clinical practice has been limited. Proxy measures of skeletal muscle quality can be obtained using diagnostic ultrasound, providing a cost-effective and accessible imaging modality to aid further clinical research regarding changes in muscle composition. Clinicians and practitioners should evaluate the strengths and limitations of the available technology to determine which devices are most appropriate given their respective circumstances. Progressive resistance exercise has been shown to improve skeletal muscle hypertrophy of the lower extremities, muscular strength and health-related quality of life in end-stage renal disease, with limited evidence available in CKD predialysis. Fundamental principles (i.e. specificity, overload, variation, reversibility, individuality) can be used in the development of more advanced programs focused on improving specific neuromuscular and functional outcomes. Future research is needed to determine the applicability of skeletal muscle monitoring in clinical settings and the feasibility and efficacy of more advanced resistance exercise approaches in those with CKD predialysis.
... Several studies have shown that, when using BIA equations developed in different populations to which it is going to be applied, the result has been inconsistent [16][17][18]. It is relevant, then, to join the international recommendations, which establish that the equation selected to predict body fat mass should be the most appropriate for the group of subjects to be studied [19]. ...
... Some of the questions that BIA has, is that the prediction equations used to estimate body compartments are based on mathematical models developed by statistical procedures and on assumptions about relations or inter compartimental constants; Such as hydration of lean tissue (73%); variable that may change depending on various factors such as age, sex and ethnicity of the individuals evaluated [27]. Further; that these equations have been formulated using reference samples to population groups of the Caucasus; which have particular characteristics; and therefore when applied to different population groups exhibit an inaccurate behavior [16][17][18]28]. ...
... A second reason that may justify the lack of significant differences between the two measurements (% FM BIA and% FM formula) is that the BIA methodology presents limitations inherent to the principles on which it is based, assuming that the explorations must be performed Under certain standardized conditions; makes the results dependent on the population in which they are performed [16,17,43]. ...
... The body mass index (BMI) was obtained and calculated using self-reported weight and height measures. A BMI ranging from 18.5 to 25.0 is considered healthy (Kyle, Piccoli, and Pichard, 2003). The BMI is grouped into BMI < 18.5 indicating "underweight"; BMI 18.5-24.9 ...
... indicating "normal weight"; BMI 25-29.9 indicating "overweight"; and BMI > 30 indicating "obesity" (Kyle, Piccoli, and Pichard, 2003). ...
... Multiple logistic regression analyses were performed to estimate odds ratios (ORs) with 95% confidence intervals (95%CI) of anthropometric and body composition measures as the independent variables for the presence of CVRFs as the dependent variable. Three models were fitted for each measurement by three cut-off points: model 1 in agreement with the cut-off points from current guidelines for WC (≥80 cm in women and ≥94 cm in men), BF% (≥35% in women and ≥25% in men), BMI (≥25 kg/m 2 in both gender), FMI (≥8.2 kg/m 2 in women and ≥5.2 kg/m 2 in men), and FFMI (≤15 kg/m 2 in women and ≤17 kg/m 2 in men) [23][24][25]; model 2 consistent with the 50th percentile cut-off points; and model 3 according to the average of optimal cut-off points determined by the Youden index from ROC curves. All models were adjusted by age. ...
... Our results showed that, compared to all anthropometric and body composition measures, high BMI showed the greatest odds of high TG in women, as well as high WC in men, when cut-off values from current guidelines were included in the logistic regression model [23,24]. When these cut-off points were replaced by those obtained in the present study from the 50th percentile and from the average of ROC curves, high BMI still significantly increased the risk of high TG in women more than the other anthropometric and body composition measures. ...
The study aimed to identify accurate cut-off points for waist circumference (WC), body fat percentage (BF%), body mass index (BMI), fat mass index (FMI), and fat-free mass index (FFMI), and to determine their effective accuracy to predict cardiovascular risk factors (CVRFs) among Mexican young adults. A cross-sectional study was conducted among 1730 Mexican young adults. Adiposity measures and CVRFs were assessed under fasting conditions. The optimal cut-off points were assessed using the receiver operating characteristic curve (ROC). Age-adjusted odds ratios (OR) were used to assess the associations between anthropometric measurements and CVRFs. The cut-off values found, in females and males, respectively, for high WC (≥72.3 and ≥84.9), high BF% (≥30 and ≥22.6), high BMI (≥23.7 and ≥24.4), high FMI (≥7.1 and ≥5.5), and low FFMI (≤16 and ≤18.9) differ from those set by current guidelines. High BMI in women, and high FMI in men, assessed by the 50th percentile, had the best discriminatory power in detecting CVRFs, especially high triglycerides (OR: 3.07, CI: 2.21–4.27 and OR: 3.05, CI: 2.28–4.08, respectively). Therefore, these results suggest that BMI and FMI measures should be used to improve the screening of CVRFs in Mexican young adults.
... Recently, there has been growing interest in bioelectrical impedance analysis (BIA), which is a safe, non-invasive, and inexpensive bedside method for assessing body composition (10). The operating principle uses the empirical regression equation to measure resistance, which is mainly determined by the intracellular and extracellular fluid, and reactance, which is produced by the double layer of the cell membranes (11,12). ...
... Phase angle (PhA), another raw parameter of BIA, is calculated from the original data resistive resistance (R) and capacitive reactance (Xc) by the formula arctangent (Xc/R) × 180 • /π at a frequency of 50 kHz (Figure 1), and this measure is less affected by body fluid distribution (10,12,13). Previous studies have shown that PhA is positively correlated with cell membrane integrity and cell function. ...
Sarcopenia is commonly defined as the age-related loss of muscle mass and function and may be caused by several factors, such as genetics, environmental conditions, lifestyle, drug use, and, in particular, comorbidities. People with pre-existing conditions are more likely to develop sarcopenia and subsequently have a less favorable prognosis. Recently, phase angle (PhA), which is derived from bioelectrical impedance analysis (BIA), has received a great deal of attention, and numerous studies have been carried out to examine the relationship between PhA and sarcopenia in different conditions. Based on these studies, we expect that PhA could be used as a potential marker for sarcopenia in the future.
... In the current study, FFMI and FMI defined nutritional status (Table 1). Using this definition, individuals with any BMI may be at potential nutritional risk due to decreased FFMI or high FMI (Kyle, Piccoli, et al., 2003;Kyle, Schutz, et al., 2003). ...
... Despite that FFMI and FMI reference values correspond to BMI values (Kyle, Piccoli, et al., 2003;Kyle, Schutz, et al., 2003) more patients were at increased nutritional risk when defined with the body composition measures (18% at admission; 10% after 4 weeks) compared to the definition with BMI (6% at admission; 4% after 4 weeks) in the current study. This may be due to the unequal graduation of malnutrition severity or in particular, that low FFMI rather than BMI is related to increased health risks and mortality (Kyle, Schutz, et al., 2003). ...
Aim:
To illuminate using body composition measurements for malnutrition measured by Bio Impedance Analysis (BIA), as opposed to body mass index (BMI), and discuss benefits and burdens for fundamental nursing care.
Design:
A second analysis of a prospective, descriptive cohort study, targeting fundamental nursing care elements.
Methods:
This postevaluation study explored data from a prospective, descriptive cohort study, which consecutively included 92 patients admitted for neurorehabilitation care. Measures of nutritional status were BMI and FFMI. Chi-Square test and Multivariable logistic regression were used.
Results:
Body composition measures rather than BMI contributed to target individual nutritional nursing care as this measure detected more patients at potential risk of malnutrition and indicated minor changes in the nutritional state. Transitions from being malnourished to a normal nutritional status occurred in 29% using the BMI definition while it was the case in 40% of individuals with malnutrition defined by the body composition.
... kg/m 2 , and obese, when C30.0 kg/m 2 [7]. As BMI is not sensitive to body fat content, body composition measurements such as lean body mass index (LBMI) and body fat mass (BFM) are usually preferred for obtaining an exact evaluation of nutritional status of the patient [8]. LBMI in men is defined as low when B16.6 kg/m 2 and normal when C16.7 kg/m 2 . ...
... LBMI in men is defined as low when B16.6 kg/m 2 and normal when C16.7 kg/m 2 . In women, LBMI is defined as low when B14.5 kg/m 2 and normal when C14.6 kg/m 2 [8]. Unlike BMI, adequate data is not available regarding the effects of pre-transplant LBMI and BFM on the outcome HSCT. ...
Patients with impaired nutritional status may show increased risk of hematopoietic stem cell transplan-tation (HSCT)-related complications. This study was conducted to determine whether body mass index (BMI) and other body composition parameters, such as lean body mass index (LBMI) and body fat mass (BFM), are associated with early post-transplantation toxicity and mortality in allogeneic HSCT recipients. The records of 71 patients diagnosed with acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML), or myelodysplastic leukemia (MDS) who had undergone allogeneic HSCT with a conditioning regimen of busulfan-cyclophosphamide (Bu-Cy), between September 2003 and January 2009 at the Stem Cell Transplantation Unit of Gazi University Hospital were retrospectively evaluated. BMI was found to be negatively correlated with the NCI grade of mucositis, cardiotoxicity, emesis, and hyperglycemia, and with the number of erythrocyte transfusions. LBMI was also negatively correlated with the number of erythrocyte transfusions, cardiotoxicity, emesis, and hyperglycemia. BFM was negatively correlated with the day of neutrophil engraftment, and NCI grade of mu-cositis. Nutritional status did not have an impact on overall survival (OS), progression-free survival (PFS), or 100-day transplant related mortality (TRM).
... kg/m 2 , and obese, when C30.0 kg/m 2 [7]. As BMI is not sensitive to body fat content, body composition measurements such as lean body mass index (LBMI) and body fat mass (BFM) are usually preferred for obtaining an exact evaluation of nutritional status of the patient [8]. LBMI in men is defined as low when B16.6 kg/m 2 and normal when C16.7 kg/m 2 . ...
... LBMI in men is defined as low when B16.6 kg/m 2 and normal when C16.7 kg/m 2 . In women, LBMI is defined as low when B14.5 kg/m 2 and normal when C14.6 kg/m 2 [8]. Unlike BMI, adequate data is not available regarding the effects of pre-transplant LBMI and BFM on the outcome HSCT. ...
Patients with impaired nutritional status may show increased risk of hematopoietic stem cell transplan-tation (HSCT)-related complications. This study was conducted to determine whether body mass index (BMI) and other body composition parameters, such as lean body mass index (LBMI) and body fat mass (BFM), are associated with early post-transplantation toxicity and mortality in allogeneic HSCT recipients. The records of 71 patients diagnosed with acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML), or myelodysplastic leukemia (MDS) who had undergone allogeneic HSCT with a conditioning regimen of busulfan-cyclophosphamide (Bu-Cy), between September 2003 and January 2009 at the Stem Cell Transplantation Unit of Gazi University Hospital were retrospectively evaluated. BMI was found to be negatively correlated with the NCI grade of mucositis, cardiotoxicity, emesis, and hyperglycemia, and with the number of erythrocyte transfusions. LBMI was also negatively correlated with the number of erythrocyte transfusions, cardiotoxicity, emesis, and hyperglycemia. BFM was negatively correlated with the day of neutrophil engraftment, and NCI grade of mu-cositis. Nutritional status did not have an impact on overall survival (OS), progression-free survival (PFS), or 100-day transplant related mortality (TRM).
... Bioelectrical impedance analysis (BIA) is a technique suitable for use in clinical routine given it is a noninvasive and portable method, enabling to evaluate body fat as well as other body composition components such as lean mass. [16][17][18] Bioelectrical impedance analysis uses alternating electric current to generate two raw parameters: resistance (R), which represents the pure opposition to the electrical flow, and reactance (Xc), representing the resistive effect due to capacitance produced by tissue interfaces and cell membranes. Both, R and Xc, are useful to estimate phase angle (PhA), which is directly calculated as arc-tangent (Xc/R) × 180°/Pi. ...
... Additionally, validated and specific predictive equations using R and/ or Xc values provide accurate estimates of body fat, fat-free mass, BCM, and total body water. [19][20][21] The use of BIA is recommended for healthy subjects and patients with stable water and electrolytes, [16][17][18] including renal transplant recipients (RTR). 22,23 Renal transplantation is the treatment of choice for most patients with end-stage chronic kidney disease. ...
Obesity is associated with increased risk of cardiovascular disease (CVD). Body mass index (BMI) is the most used parameter for obesity screening. However, the evaluation of CVD risk in overweight individuals should include the assessment of body fat distribution and body composition. Renal transplant recipients (RTR) have a high CVD risk and frequently present weight gain and loss of lean mass. The aim of this study was to evaluate body fat distribution and body composition in overweight RTR. This cross‐sectional study was conducted with 86 RTR and 86 hypertensive individuals (comparison group;CG) presenting BMI 25‐35Kg/m2 and 45‐70years. Anthropometric evaluation included BMI, waist circumference, waist‐to‐height ratio and a body shape index. Body composition was evaluated with bioelectrical impedance analysis (BIA). Glomerular filtration rate was estimated (eGFR) by CKD‐EPI equation. RTR group (RTRG) and CG presented similar age and BMI. RTRG compared to CG, presented lower percentage of women and eGFR; higher central adiposity; and lower values of reactance, intracellular water, body cell mass and phase angle, more consistently observed in women. This study suggests that overweight RTR present higher abdominal adiposity and impairment in BIA parameters that are sensitive indicators of impaired membrane integrity, water distribution and body cell mass. This article is protected by copyright. All rights reserved.
... The use of direct bio-impedance data has been suggested by different authors and this is based on the electrical measurements used and the different properties of the cell membranes which are said to vary depending on the hydration status, its integrity and composition which changes depending on the health status of the individual [150]. Direct bioelectrical impedance analysis data like: phase angle, resistance and reactance normalized for height in R/Xc graphs are used in assessing the clinical and nutritional status of individuals in relation to their body fat and lean mass [151]. ...
... This could hinder the participation and engagement of PLHIV and malnourished adults in strenuous and labour intensive activities like digging, ploughing, pruning hence their inability to effectively have adequate food supplies for themselves and their family members. As mentioned previously, the use of raw bio impedance parameters has been suggested to counter the difficulties associated with getting comparable predictive equations for populations being studied and getting the required conditions of hydration status which may not be met especially due to body composition changes during sickness [150][151][152][153]. body cell mass and cell integrity [39,174]. ...
Background and study objectives: Studies done to assess the prevalence and interaction of malnutrition, dietary practices, and food security among HIV positive refugees in Uganda are limited. There is also little information about the use of direct Bioelectrical Impedance Analysis (BIA) parameters for assessing or monitoring body composition among HIV positive adults in resource poor settings. The overarching goals for my study were: to assess the prevalence of HIV-related food insecurity and malnutrition, describe the body composition of HIV positive adults, and investigate the potential utility of using BIA parameters as prognostic indicators among HIV positive refugee adults. / Study methods and data collected: First, I conducted a cross-sectional study involving 368 HIV positive and 368 HIV negative adults recruited from two refugee settlements. Secondly, I conducted a prospective observational longitudinal study following up for 16 weeks 74 malnourished HIV positive adults who were attending a nutritional rehabilitation clinic as part of their routine HIV treatment and care. Data was collected on: the demographic characteristics and socioeconomic status of the participants; Individual Dietary Diversity and Household Food Insecurity; anthropometric indices; and Hand Grip Strength. I also collected bioelectrical impedance data – and used phase angle, resistance, reactance and bioelectrical impedance vector analysis – to assess the body composition of the participants. / Key results from the two studies: Overall, 57% of participants were food insecure with those from Nakivale being worse affected compared to those from Kyaka settlement – 75% and 38% of participants respectively. Multivariable regression indicated that HIV infection was not a risk factor to food insecurity but the participants’ location significantly affected their food security status. 13% of the participants were underweight with those who were HIV positive more affected than those who were HIV negative – 15.2% compared to 10.3% respectively. HIV infection was found to be a risk factor for being underweight (BMI≤18.49kg/m2) with those infected with HIV being nearly three times of becoming underweight. Underweight male and female participants had significantly lower BIA values for phase angle, and reactance and resistance normalized for height. Malnourished HIV positive adults gained over 1.60kg of weight and 5Kg force for Hand Grip Strength during the 16 weeks of nutritional rehabilitation; males gained more weight and HGS compared to female participants. Phase angle, reactance and resistance normalized for height also increased during the 16 weeks of follow up but female participants had lower values. / Conclusion: Food insecurity and malnutrition are high among refugees in these areas of Uganda but due to a range of causes on top of HIV infection. Nutritional supplementation of malnourished HIV positive adults improves their nutritional status and BIA parameters. However, the gender variations observed need to be explored further.
... 현장에서 매우 중요하다 (Siervogel, et al., 2003;Wang, Pierson, & Heymsfield, 1992, Wells, 2001 , , 2007;, 2011;Ellis, 2000;Houtkooper, Lohman, Going, & Howell, 1996;Kyle, et al., 2003;Piccoli 2010;Piccoli, et al., 1995;Wang, et al., 1992). Kyle, et al., 2003;Piccoli, 2010;Piccoli, et al., 1995). ...
... 현장에서 매우 중요하다 (Siervogel, et al., 2003;Wang, Pierson, & Heymsfield, 1992, Wells, 2001 , , 2007;, 2011;Ellis, 2000;Houtkooper, Lohman, Going, & Howell, 1996;Kyle, et al., 2003;Piccoli 2010;Piccoli, et al., 1995;Wang, et al., 1992). Kyle, et al., 2003;Piccoli, 2010;Piccoli, et al., 1995). ...
... Body composition in this context refers to the amount and distribution of fat, bone, water, and muscle in an individual, which can be assessed through a variety of methods (Wells & Fewtrell, 2006). Body composition is often used to further understand and interpret health outcomes (Wells & Fewtrell, 2006;Kyle et al., 2003); individuals with higher body fat percentages are often at a higher risk for cardiovascular disease, type 2 diabetes, and some cancers (Holmes & Racette, 2021). Body composition also influences thermoregulation; higher muscle mass offers more insulation against heat loss during cold exposure (Payne et al., 2018). ...
There is considerable evidence that differences in patterns of habitual activity influence the distribution of skeletal tissue within the human skeleton, but little is known about variation in soft tissue. This thesis examines body composition and surface scan data from runners, swimmers, and a ‘recreational control’ population to investigate differences in the properties of limb segment surface areas and volumes, muscle mass, and fat mass. It also explores the relationship between activity and aging through the examination of body composition and volumetric measurements in older-adult habitual swimmers. The findings show that resulting limb segment properties support assumptions of running as a lower-limb dominant and swimming as an upper limb dominant activity. Habitual swimming also displays a positive effect on the preservation of skeletal muscle mass across the life course. This thesis suggests non-impact loading results in demonstrable differences in body morphology, emphasizing the importance of activity throughout the life course.
... Only the st− th percentile of exposure is shown. mortality risk has been shown previously among individuals with and without heart diseases (18)(19)(20) and hospitalized patients (21)(22)(23). However, to the best of our knowledge, no previous studies have examined if a measured change over time in PhA may be predictive of a future increased risk of early overall mortality or cardiovascular disease. ...
Introduction
Phase angle (PhA, degrees), measured via bioimpedance (BIA, 50 kHz), is an index that has been used as an indicator of nutritional status and mortality in several clinical situations. This study aimed to determine the relationship between 6-year changes in PhA and total mortality as well as the risk of incident morbidity and mortality from cardiovascular disease (CVD) and coronary heart disease (CHD) during 18 years of follow-up among otherwise healthy adults.
Methods
A random subset (n = 1,987) of 35–65 years old men and women was examined at the baseline in 1987/1988 and 6 years later in 1993/1994. Measures included weight, height, and whole-body BIA, from which PhA was calculated. Information on lifestyle was obtained through a questionnaire. The associations between 6-year PhA changes (ΔPhA) and incident CVD and CHD were assessed by Cox proportional hazard models. The median value of ΔPhA was used as the reference value. The hazard ratio (HR) model and confidence intervals (CIs) of incident CVD and CHD were used according to the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ΔPhA.
Results
During 18 years of follow-up, 205 women and 289 men died. A higher risk of both total mortality and incident CVD was present below the 50th percentile (Δ = −0.85°). The highest risk was observed below the 5th percentile (ΔPhA = −2.60°) in relation to total mortality (HR: 1.55; 95% CI: 1.10–2.19) and incident CVD (HR: 1.52; 95% CI: 1.16–2.00).
Discussion
The larger the decrease in PhA, the higher the risk of early mortality and incident CVD over the subsequent 18 years. PhA is a reliable and easy measure that may help identify those apparently healthy individuals who may be at increased risk of future CVD or dying prematurely. More studies are needed to confirm our results before it can be definitively concluded that PhA changes can improve clinical risk prediction.
... Body composition values can then be interpreted either on the basis of absolute values, which allows longitudinal follow-up of the same patient, or on the basis of percentiles, which allows comparison with the body composition of subjects of the same age and sex, below the 10 percentile are strongly associated with undernutrition [27,28]. Thus, measurement of LM by bioelectrical impedancemetry is a sensitive parameter for the diagnosis of undernutrition [29]. ...
Undernutrition is one of the major problems of public health, frequent in the extreme ages of life where its evaluation is often difficult. It most often leads to tissue loss with deleterious functional consequences. Aging is a persistent decline in the age-specific fitness components of an organism due to internal physiological deterioration. As a result of physiological changes, the nutritional status of the elderly can deteriorate rapidly and affect all steps of eating, from the sensation perceived when food is put into the mouth to the metabolism of nutrients. This can lead to protein-energy under-nutrition in this population. Anthropometric, biophysical and biological measurements allowing the quantification of undernutrition, the evaluation of its severity. This narrative review focuses on the importance of recognizing, preventing and treating under-nutrition in the elderly as part of management strategies in order to limit the morbid consequences in this vulnerable population.
... Отсутствие лучевой нагрузки в свою очередь дает возможность проводить исследование в динамике гораздо чаще 1 раза в год и тем самым контролировать ход лечения (табл. 2) [35][36][37][38][39][40]. ...
... Looking beyond the scope of nutritional support, quantifying LBM and fat mass might be helpful in dosing of other medication, and provide information on preadmission status, possibly with important consequences for decisions regarding treatment options and treatment limitations. Also, the use of percentiles and height-normalized LBM and body fat permit the classification of patients as under or over nourished (10)(11)(12). Anthropometric studies in patients admitted to the intensive care unit are considered one of the best methods of assessment (6,(13)(14)(15). Evaluation of the nutritional status of children is performed by calculating the Z score based on the World Health Organization (WHO) recommendations or the Centers for Disease Control and Prevention (CDC) guidelines, which includes weight versus age, weight versus height, head circumference (for children younger than 2 years), body mass index (for children over 2 years). ...
Context: Children admitted to the intensive care unit are at risk of malnutrition, mainly due to chronic diseases they are suffering from. These patients require a different nutritional diet regimen from those in a normal or stable disease state due to change in metabolism under the stress of diseases. Methods: According to the SIGN guideline based on evidence, first, articles matching our criteria were extracted from the literature, and then the strength of evidence was evaluated. Finally, a summary of statements consisting of details regarding the strength of evidence and recommendation level was reviewed by 12 experts, and two-round surveys were accomplished according to the Delphi method to reach a consensus. Results: 27 statements in 5 categories with strength of evidence, grade of recommendations, and expert opinions are summarized. Conclusions: Rapid nutritional assessment, judging patients with malnutrition or at risk of malnutrition, fast intervention with early enteral nutrition, reaching the protein and energy goals under the supervision of an expert registered dietitian, and persistent monitoring with minimizing the time of fasting are some of the key components of proper nutrition management based on evidence found in the literature.
... Created in the 1980s, DXA was first approved in clinical practice for assessment of fracture risk (1988) and is currently one of the main tools for the detection of osteoporosis through analysis of lumbar spine, femur, and forearm bone mineral density [83]. Over the last decades, the use of DXA has expanded to include accurate and precise total body assessment and body composition analysis based on the three-compartment model-lean mass, fat (or body fat) mass, and bone mass [67,84]-and to become the reference method for in vivo evaluation of body composition in clinical practice [85,86]. ...
Objective
To review the technical aspects of body composition assessment by dual-energy X-ray absorptiometry (DXA) and other methods based on the most recent scientific evidence.
Materials and methods
This Official Position is a result of efforts by the Scientific Committee of the Brazilian Association of Bone Assessment and Metabolism ( Associação Brasileira de Avaliação Óssea e Osteometabolismo , ABRASSO) and health care professionals with expertise in body composition assessment who were invited to contribute to the preparation of this document. The authors searched current databases for relevant publications. In this first part of the Official Position, the authors discuss the different methods and parameters used for body composition assessment, general principles of DXA, and aspects of the acquisition and analysis of DXA scans.
Conclusion
Considering aspects of accuracy, precision, cost, duration, and ability to evaluate all three compartments, DXA is considered the gold-standard method for body composition assessment, particularly for the evaluation of fat mass. In order to ensure reliable, adequate, and reproducible DXA reports, great attention is required regarding quality control procedures, preparation, removal of external artifacts, imaging acquisition, and data analysis and interpretation.
... 7,8 In addition, the nutritional status deficit and the depletion of lean mass presented by the critically ill cancer patient are closely related to a decrease in the response to treatment, the quality of life, and functional capacity, increasing the risk of infections, hospitalization time, and death occurrence. 9 However, no data was found regarding the association between nutritional risk, critical illness and cancer. ...
... Even back then, various parameters were used, such as gender, age, weight, and the person's reaction and body composition. [26]. ...
—Bioelectrical impedance (BIA) is a painless,
non-invasive, and easily portable technique that may
clarify how the human body is operational. Body
composition (BC) assessment is commonly established
as a clinical technique for evaluating and estimating
disease status. BIA has been applied to assess the mass
distribution and water compartments in the BC. BIA
has several parameters: fat mass, fat-free mass, total
body water, phase angle, and body mass index; these
parameters show the body distributions. Thus, BIA
could beneficially predict the patient’s status.
However, more studies need to improve validity and
reliability, according to these aspects. The purpose of
this review was to briefly theoretical procedures of
numerous compartments models of body composition.
... Он легко определяется с помощью биоэлект рического импедансного анализа. Более сложным методиками являются 2 энергетическое рентгенов ское исследование и метод изотопного разведения дейтерия или бромида [394][395][396][397][398][399][400]. Статистическое частотное распределение установлено для каждого из них. ...
... LBM is the sum of all lean tissues and excluding bone whereas FFM includes bone mineral content and lean tissues [25]. Muscle mass could be estimated using body imaging techniques such as DXA scans, bioelectrical impedance analysis (BIA) or anthropometric measures [26,27]. With anthropometry, estimation of muscle mass is based on the measurements of mid-upper arm circumference (MUAC) and triceps skinfold (TSF) thickness and calculation of the mid-upper arm muscle circumference [26]. ...
Background & Aims
Omega-3 polyunsaturated fatty acid (PUFA) supplementation has been proposed as a potential therapy for cancer-related malnutrition, which affects up to 70% of patients with cancer. The aim of this systematic review and meta-analysis was to examine the effects of oral omega-3 PUFA supplementation on muscle maintenance, quality of life, body weight and treatment-related toxicities in patients with cancer.
Methods
Randomised controlled trials in patients with cancer aged >18 years were retrieved from 5 electronic databases: MEDLINE (via PubMed), EMBASE, CENTRAL, CINAHL (via EBSCOhost), and Web of Science, from database inception until 31st of December 2019. The quality of included studies was assessed using the Cochrane risk of bias tool. Trials supplementing ≥600 mg/d omega-3 PUFA (oral capsules, pure fish oil or oral nutritional supplements) compared with a control intervention for ≥3 weeks were included. Meta-analyses were performed in RevMan to determine the mean differences (MD) in muscle mass, quality of life and body weight, and odds ratio (OR) for the incidence of treatment-related toxicities between omega-3 PUFA and control groups with 95% confidence intervals (CI) and I² for heterogeneity.
Results
We included 31 publications in patients with various types of cancers and degrees of malnutrition. The Cochrane risk of bias tool graded most trials as ‘unclear’ or ‘high’ risk of bias. Meta-analyses showed no significant difference between omega-3 PUFA supplements and control intervention on muscle mass, quality of life and body weight. Oral omega-3 PUFA supplements reduced the likelihood of developing chemotherapy-induced peripheral neuropathy (OR: 0.20; 95% CI: 0.10-0.40; p<0.001; I²=0%).
Conclusion
This systematic review and meta-analysis indicates that oral omega-3 PUFA supplementation does not improve muscle maintenance, quality of life or body weight in patients with cancer, but may reduce the incidence of chemotherapy-induced peripheral neuropathy. Well-designed large-scale randomised controlled trials in homogenous patient cohorts are required to confirm these findings.
... In recent humans, a body composition with a high percentage of fat mass is frequently associated with an increased probability of cardiovascular and metabolic diseases (Kyle et al., 2003). The Middle Pleistocene hominins might have been partially protected from the negative effects of increased fat deposits by certain metabolic adaptations and their high levels of daily physical activity. ...
During the mid-Middle Pleistocene MIS 14 to MIS 11, humans spread through Western Europe from the Mediterranean peninsulas to the sub-Arctic region, and they did so not only during the warm periods but also during the glacial stages. In doing so, they were exposed to harsh environmental conditions, including low or extremely low temperatures. Here we review the distribution of archeological assemblages in Western Europe from MIS 14 to MIS 11 and obtain estimates of the climatic conditions at those localities. Estimates of the mean annual temperature, mean winter and summer temperatures, and the lowest temperature of the coldest month for each locality were obtained from the Oscillayers database. Our results show that hominins endured cold exposure not only during the glacial stages but also during the interglacials, with winter temperatures below 0 C at many localities. The efficacy of the main physiological and behavioral adaptations that might have been used by the Middle Pleistocene hominins to cope with low temperatures is evaluated using a simple heat-loss model. Our results suggest that physiological and anatomical adaptations alone, such as increasing basal metabolic rate and subcu-taneous adipose tissue, were not enough to tolerate the low winter temperatures of Western Europe, even during the MIS 13 and MIS 11 interglacials. In contrast, the use of a simple fur bed cover appears to have been an extremely effective response to low temperatures. We suggest that advanced fire production and control technology were not necessary for the colonization of northern Europe during MIS 14 and MIS 12. We propose that Middle Pleistocene European populations were able to endure the low temperatures of those glacial stages combining anatomical and physiological adaptations with behavioral responses, such as the use of shelter and simple fur clothes.
... LBM is the sum of all lean tissues and excluding bone whereas FFM includes bone mineral content and lean tissues [25]. Muscle mass could be estimated using body imaging techniques such as DXA scans, bioelectrical impedance analysis (BIA) or anthropometric measures [26,27]. With anthropometry, estimation of muscle mass is based on the measurements of mid-upper arm circumference (MUAC) and triceps skinfold (TSF) thickness and calculation of the mid-upper arm muscle circumference [26]. ...
... Changes in body composition are the reliable indicator of the nutritional and health status of individuals (Kyle, Antoniob, & Claudea, 2003). The regular monitoring of anthropometric body composition variables among the ageing population is beneficial for healthy ageing and to assess whether benefits of healthcare facilities are reaching the elderly class or not. ...
The present study was conducted to find out the changes in anthropometric measurements with advancing age among elderly males living in old-age homes and those living in family. Cross-sectional data on anthropometric measurements and other general information were obtained for 400 male subjects (200 living in old-age homes and 200 living with family) ageing 60 years and above, and data were collected from various districts in Punjab. Height decreased non-significantly and sitting height decreased significantly ( p = 0.03) from 60 years to ≥80 years of age in both the groups of elderly males. Weight decreased significantly among the elderly males residing in old-age homes ( p < 0.001). Biceps ( p = 0.03) and thigh skinfold ( p = 0.009) thicknesses decreased significantly only among elderly residing in old-age homes. Abdominal ( p = 0.01) and supra-iliac ( p = 0.01) skinfold thickness measurements decreased significantly among elderly residing with their families. Circumference measurements on limbs decreased significantly ( p < 0.01) among both the groups of elderly (except upper arm circumference among elderly residing with their families). Abdominal circumference decreased significantly ( p = 0.04) among the elderly males residing with their families. Elderly residing in old-age homes retained more abdominal subcutaneous fat mass and lost more appendicular fat mass as compared with those residing with their families. Elderly residing with their families lost lesser appendicular muscle mass as compared with their counterpart’s elderly residing in old-age homes.
... To compare body components between the analyzed groups, we used the bioimpedance method, which allows an estimation of lean body mass (free fat mass) and body fat content [27][28][29]. In our study, body mass, LBM, and BMI values were comparable between CTD and control groups. ...
Peroxisome proliferator-activated receptors (PPAR gamma-2) and beta-3-adrenergic receptors (ADRB3) are involved in the risk of hypertension. But their exact role in blood pressure modulation in patients with connective tissue diseases (CTD) is still not well defined. In this study, 104 patients with CTD and 103 gender- and age-matched controls were genotyped for Pro12Ala and C1431T polymorphisms of the PPAR gamma-2 gene and Trp64Arg polymorphism of the ADRB gene. Anthropometric and biochemical measurements were evaluated, followed by genotyping using TaqMan® SNP genotyping assays and polymerase chain reaction-restriction fragment length polymorphism. The prevalence of analyzed genotypes and alleles was comparable between patients with CTD and the control group, as well as hypertensive and normotensive subjects. Patients with CTD have lower body fat and higher body water amount, serum glucose, and triglyceride (TG) levels. Hypertensive subjects are older and have higher body mass, BMI, waist circumference (WC), body water content, glucose, and TG concentration. The multivariate analysis revealed that hypertensive subjects with Ala12/X or Trp64Trp have higher body mass and WC when compared to normotensive subjects. Trp64Trp polymorphism was also characterized by a higher TG level, while T1431/X subjects had higher WC. The presence of CTD, visceral fat distribution, and increased age are the predictors of hypertension development. Hypertensive patients with CTD and Trp64Trp polymorphism have an increased risk of visceral obesity development and metabolic complications, which in turn affects the value of blood pressure. In addition, either Ala12/X or T1431/X predicts the visceral body fat distribution in hypertensive subjects.
... Total body weight depends on the body water mass [29], protein mass [30] and bone mass [31], in addition to fat mass [32]. Values are expressed as Mean ± S.E.M. n = 5 "p<0.05 ...
Plant fats are low in saturated fats but high in unsaturated fats compared to animal fats, and are supposedly less obesogenic. This study compared the obesogenic effects of plant and animal derived fatty diets in Wistar rats. Rats of each gender were divided into three dietary (standard chow (SC), high fat diet rich in animal fat (HFDaf) and a high fat diet rich in plant fat (HFDpf)) groups of ten each and fed for 17 weeks. Anthropometric, Adiposity and nutritive variables were assessed using standard methods. Comparing HFDpf to HFDaf: Abdominal circumference (AC),initial feed intaken (IFI), final feed intake(FFI), final body weight (FBW), white adipose tissue (WAT) were increased but brown adipose tissue (BAT) decreased in male rats fed with HFDpf; also, there were increased body length, IFI, FFI but decreased AC, FBW, BAT in female rats fed with HFDpf. Comparing male to female rats: Thoracic circumference, IFI, FFI, energy intake were increased while Adiposity index decreased across diet groups in male rats; the AC, FBW increased while WAT, BAT decreased in HFDpf fed group, also, BAT was increased but AC, FBW decreased in HFDaf fed group in male rats. Palatability and high feed efficiency of consumed diets were more associated with obesogenic risk than just the level of saturation. Therefore, Obesogenic effects of fatty diets in both genders is more dependent on the quantity (amount) of fatty diet consumed than the dietary fat composition alone.
... Bioelectrical impedance analysis (BIA) is more accurate than body mass index and most other anthropometric measures in assessing body composition [34]. When compared to more advanced measures, BIA is less expensive, less invasive, and easier to use [34,35]. ...
Background: Being overweight or obese is one of the most harmful risk factors to the health of a population. The cause of obesity is complex and multifactorial, but the primary cause is a nutrient poor diet. Despite excess intake of calories, obese individuals commonly have a lack of phytonutrients. Phytonutrients such as chlorophyll, carotenoids, and anthocyanins have all been shown to have anti-obesity effects. National data shows that states in with the lowest intakes of fruit and vegetable intake also have higher obesity rates. The data available depicts that a low fruit and vegetable intake, thus low phytonutrient intake, is correlated with excess adiposity.
Methods: Fifty subjects from Thibodaux, Louisiana were randomly selected to participate. Three 24-hour food recalls were used to calculate phytonutrient content of the diets using the phytonutrient index. A food frequency questionnaire was also administered to determine intake of specific phytonutrients (carotenoids, anthocyanins, and carotenoids). Body adiposity was measured using body mass index (BMI), waist circumference, and fat percentage. Pearson correlation was used to assess correlations between phytonutrient index and body adiposity measures. Analysis of variance (ANOVA) with post-hoc tests was used to determine differences in PI and phytonutrient intakes among the BMI, waist circumference and percent body fat groups.
Results: Participants who met healthy standards for BMI, waist circumference, and fat percentage all averaged much higher PI scores compared to those classified as obese/overweight. The data showed a strong inverse relationship between PI and BMI (r = -0.753, p = 0.00), waist circumference (r = -0.730, p = 0.00), and body fat percentage (r = -0.701, p = 0.00). Higher weekly intakes of chlorophyll, carotenoid, and anthocyanin rich foods had better body composition in comparison to those who consumed less (p
... Several physiological and pathological factors may contribute to BIVA results, and interpretation may be challenging, nevertheless, longer and shorter vectors indicate, respectively, dehydration and hyperhydration [7], while vectors falling left of the major axis are associated with a higher cell mass compared to those falling on the right. As shown in Fig. 1, higher resistance (p < 0.001) and reactance (p = 0.001), as well as longer vectors falling on the right of the major axis were observed in NI paediatrics compared to controls, suggesting an impaired hydration status. ...
Dehydration is common and frequently under-diagnosed in chronic malnourished children, leading to life-threatening conditions. In this pilot study we applied bioimpedance vector analysis (BIVA) to determine hydration status in 52 neurologically impaired (NI) paediatric patients (14.08 ± 5.32). Clinical and biochemical data were used to define malnutrition and dehydration. Body composition analysis and hydration were also assessed by BIVA and we considered 143 normal-weight healthy subjects (15.0 ± 1.7), as controls for hydration status assessment. BIVA revealed a pathological hydration status in NI children, showing higher resistance (p < 0.001) and reactance values (p = 0.001) compared to controls. No differences in reactance and resistance were detected between well-nourished and under-nourished subjects. Four patients out of 52 showed mild signs of dehydration; no severe dehydration was detected. Laboratory data, suggestive for dehydration, were similar in well-nourished and under-nourished NI subjects. In conclusion, in our sample of NI paediatrics, dehydration according to clinical signs and laboratory data was under-diagnosed. BIVA showed specific bioelectrical characteristics that could be compatible with impaired hydration status. Further studies are necessary to confirm that BIVA may an applicable tool for defining dehydration status and guiding rehydration in NI children.
... However, BIA has been extensively used for this assessment in COPD patients because it is practical, simple and reliable when using a validated equation to assess patients with stable water and electrolyte balance. 10,49 For the present study, a validated prediction equation specific for patients with COPD was used. 16 However, it is not possible to affirm that the hydric status did not interfere in the measurements, although the protocol was standardised and all subjects had body composition measurements assessed at the same conditions. ...
Background/objectives:
Abnormal body composition is an independent determinant of COPD outcomes. To date, it is already known that patient stratification into body composition phenotypes are associated with important outcomes, such as exercise capacity and inflammation, but there are no data comparing physical activity and muscle strength among these phenotypes. Thus, the aim of this study was to compare clinical characteristics and physical function in patients with COPD stratified into body composition phenotypes.
Subjects/methods:
Two-hundred and seventy stable COPD patients were classified according to the 10th and 90th percentiles of sex-age-BMI-specific reference values for fat-free and fat mass indexes into four groups: Normal body composition (NBC), Obese, Sarcopenic, and Sarcopenic-obese (SO). Patients underwent assessment of exercise capacity, peripheral and respiratory muscle strength, physical activity, dyspnea severity, functional status, and symptoms of anxiety and depression.
Results:
The prevalence of patients classified as NBC, Obese, Sarcopenic, and SO was 39%, 13%, 21%, or 27%, respectively. SO presented lower 6MWT compared with NBC (P < 0.05). Sarcopenic and SO groups presented worse muscle strength compared with NBC (P < 0.05). Sarcopenic group presented more time in moderate-to-vigorous physical activity compared to all other groups (P < 0.05) and less sedentary time when compared with NBC and obese groups (P < 0.05). There were no differences regarding dyspnea severity, functional status, and symptoms of anxiety and depression (P > 0.16). Sarcopenic and SO groups had, respectively, 7.8 [95% CI: 1.6-37.7] and 9.5 [2.2-41.7] times higher odds to have a 6MWT equal or lower to 350 meters.
Conclusions:
Body composition phenotypes are associated with physical function in patients with COPD. Sarcopenic-obese patients were the most impaired.
... In the meantime, the classification of overweight based on BMI in some age groups coincided with higher values of LBM in both men and women. This finding demonstrates one of the shortcomings of classifying nutritional status based only on the weight/height relation, since it does not distinguish body compartments, and may lead to misinterpretations 2,19 . ...
Objective:
Body's lean mass compartment is a strong predictor of morbidity and mortality risk in various clinical conditions. This paper proposes a simple and easily applied reference table for lean body mass (LBM) and lean body mass index (LBMI) for the Italian population.
Patients and methods:
Retrospective analysis of a database containing anthropometric and DXA body composition measurements obtained from a cross-sectional study conducted between 2002 and 2009 with Italian individuals. Parametric and nonparametric tests were performed using R 3.1.1 and SPSS 22.0 software packages.
Results:
The 3712 study participants, 37.3% men and 62.7% women, aging from 18 to 88 years. Individuals with normal weight, overweight and obesity were evenly distributed in the sample. LBM and LBMI measures were significantly higher in males. In both genders, there was a significant and progressive decline in these measures associated with aging. Significant differences in LBMI between genders were found in all age groups except for individuals over 75 years.
Conclusions:
Based on the participants LBM profile, a reference table for LBM values was proposed. This reference will be useful to detect changes in the LBM compartment of individuals from the South Central Region of Italy, supporting health professionals during the process of diagnosing sarcopenia.
... Even small changes in body fat percentage can be a major influence on the ability to perform anaerobic movements (Inacio et al., 2011). Assessment of body composition can provide valuable information about changes that the athlete observes throughout the season (Kyle et al., 2003). Moreover, incorrectly assessing body composition can cause difficulties in giving a proper nutrition plan because of the pressure to reach a target body fat value (Fink & Mikesky, 2015). ...
The aim of this study is to investigate the effects of static and Warm-Up Protocols On Fitness Component and body fat percentage of athletes in different branches. In this study, 50 (25 female and 25 male) athletes from Mersin University High School of Physical Education and Sports volleyball, football, basketball, wrestling and handball branches were formed the sample group of the research. The anthropometric characteristics of the individuals Height and weight measurements were made to determine and body fat percentages were determined by Bioelectrical Impedance Analysis. As engine performance tests, Vertical jump test, Sprint performance test (20m), sit-reach flexibility test were applied. One-way analysis of variance (ANOVA) was performed to determine whether there was a statistically significant difference between measurements. Data was tested for normality with the "Kolmogorov Smirnov Test". Kruskall Wallis tests were used for comparison among five groups. According to our findings no significant difference was observed between the male branches in terms of body fat percentage (%BF). Female soccer players were found to have the least body fat percentage when compared to other branches (p <0.01). Static and dynamic warming protocols it was found to have an effect statistically significant (p <0.05, P <0.001) in sit-reach flexibility, vertical jump and speed test values of athletes in different branches. As a result; it has been found that the static and dynamic warming protocolshave different effects in terms of the different sports branches and motor performance parameters. When both male and female performance values were examined, dynamic heating was found to be more dominant. It can be said that the physical and physiological values of the athletes are directly related to the performance of being suitable for the sports branch involved. For this reason, the use of warming protocols is recommended with regard to the results of the study presented here
... Even small changes in body fat percentage can be a major influence on the ability to perform anaerobic movements (Inacio et al., 2011). Assessment of body composition can provide valuable information about changes that the athlete observes throughout the season (Kyle et al., 2003). Moreover, incorrectly assessing body composition can cause difficulties in giving a proper nutrition plan because of the pressure to reach a target body fat value (Fink & Mikesky, 2015). ...
The aim of this study is to investigate the effects of static and Warm-Up Protocols On Fitness Component and body fat percentage of athletes in different branches. In this study, 50 (25 female and 25 male) athletes from Mersin University High School of Physical Education and Sports volleyball, football, basketball, wrestling and handball branches were formed the sample group of the research. The anthropometric characteristics of the individuals Height and weight measurements were made to determine and body fat percentages were determined by Bioelectrical Impedance Analysis. As engine performance tests, Vertical jump test, Sprint performance test (20m), sit-reach flexibility test were applied. One-way analysis of variance (ANOVA) was performed to determine whether there was a statistically significant difference between measurements. Data was tested for normality with the "Kolmogorov Smirnov Test". Kruskall Wallis tests were used for comparison among five groups. According to our findings no significant difference was observed between the male branches in terms of body fat percentage (%BF). Female soccer players were found to have the least body fat percentage when compared to other branches (p <0.01). Static and dynamic warming protocols it was found to have an effect statistically significant (p <0.05, P <0.001) in sit-reach flexibility, vertical jump and speed test values of athletes in different branches. As a result; it has been found that the static and dynamic warming protocolshave different effects in terms of the different sports branches and motor performance parameters. When both male and female performance values were examined, dynamic heating was found to be more dominant. It can be said that the physical and physiological values of the athletes are directly related to the performance of being suitable for the sports branch involved. For this reason, the use of warming protocols is recommended with regard to the results of the study presented here
... Females with a percentage of body fat ≥32% and males with a body fat percentage ≥25% are classified as having obesity (H-group). Classification by body fat percentage was chosen as a more specific measure of adiposity than the more commonly used proxy measure of Body Mass Index (BMI), which does not differentiate between fat and lean tissue (Kyle, Piccoli, & Pichard, 2003;Shah & Braverman, 2012). Body fat percentage has been shown to be of importance in food reward (Stice & Yokum, 2016). ...
We developed a smart phone application to measure participants' food-reward perceptions and eating behavior in their naturalistic environment. Intensity ratings (0 - not at all to 10 - very strongly) of perceived anticipation of food (wanting) and food enjoyment at endpoint of intake (liking) were recorded as they occurred over a period of 14 days. Moreover, food craving trait, implicit and explicit attitude towards healthy food, and body composition were assessed. 53 participants provided complete data. Participants were classified by percentage of body fat; 33 participants with lower body fat (L-group) and 20 with higher body fat (H-group; ≥25% body fat for males and ≥32% for females). L-group participants reported 6.34 (2.00) food wanting events per day, whereas H-group participants recorded significantly fewer food wanting events (5.07 (1.42)); both groups resisted about the same percentage of wanting events (L-group: 29.2 (15.5)%; H-group 27.3 (12.8)%). Perceived intensity ratings were significantly different within the L-group in the order liking (7.65 (0.81)) > un-resisted wanting (leading to eating) (7.00 (1.01)) > resisted wanting (not leading to eating) (6.02 (1.72)) but not in the H-group. Liking scores (L-group: 7.65 (0.81); H-group: 7.14 (1.04)) were significantly higher in L-group than in H-group after controlling for age. Our results show that individuals with higher percentage of body fat show less food enjoyment after intake and reveal no differentiation in intensity ratings of perceived anticipatory and consummatory food reward. These results are consistent with a hypothesized reward deficiency among individuals with higher percentage of body fat.
... Assumptions for good predictive models of body composition recommend that models should be proposed for a wider clinical application [30], make valid assumptions in relations between the components [28], i.e., if relations between FFM, FM and TBW are constant for all ages. Some equations proposed are more well-founded descriptions and specific to predict only one component [31], or restricted age range [32]. ...
Background/Purpose: Anthropometric models remain appropriate alternatives to estimate body composition of peripubertal populations. However, body composition assessment in children is not an easy task, since the relationship between body components during growth is not constant as in adults (Lohman, Hingle, & Going, 2013). The traditional models do not consider other body components that undergo major changes during
growth spurt, with restrictions to a multicompartimental approach as a quantitative growth. DXA has great potential to determine pediatric body composition in more than one component (three compartmental model; 3-C), but has limited use in field settings.
Thus, the purpose of this study was to propose and validate an anthropometric model for simultaneous estimation of lean soft tissue (LST), bone mineral content (BMC) and fat mass (FM) in girls, from a multivariate approach of densitometric technique, as the criterion method. Method: The study followed a cross-sectional design and a sample of 84 girls (7–17 years old) was defined by chronological age and maturity offset. The girls were healthy with no medical condition, without body parts amputated, no use of drugs or not under medical treatment that could affect metabolism, appetite or growth. Whole total and regional DXA body scan were performed with components defined (LST, BMC and FM) and considered as dependent variables. Twenty-one anthropometric measures were recorded as independent variables, including body mass, height, and skinfold measurements. Their maturity offset was determined by gender-specific regression to predict the years for Peak Height Velocity (PHV). Analysis/Results: From a multivariate regression analysis, an anthropometric multicompartmental model was obtained with only four predictive measurements: body weight (BW); supra-iliac skinfold (SiSk); horizontal abdominal skinfold (HaSk); contracted arm circumference (CaCi) with high coefficients of determination and low estimation errors (LST = 0.6662657 BW—0.
2157279 SiSk—0.2069373 HaSk + 0.3411678 CaCi—1.8504187; BMC = 0.0222185 BW—0.1001097 SiSk—0.0064539 HaSk—0.0084785 CaCi + 0.3733974 and FM = 0.3645630 BW + 0.1000325 SiSk—0.2888978 HaSk—0.4752146 CaCi + 2.8461916). The crossvalidation was confirmed through the sum of squares of residuals (PRESS) method, presenting accurate coefficients (Q2PRESS from 0.81 to 0.93) and reduced error
reliability (SPRESS from 0.01 to 0.30). Conclusions: The goal of this study to develop and
validate an anthropometric predictive model to simultaneously estimate LST, BMC and FM, was achieved. These models provide a practical, low cost, and reliable tool in assessing body composition of a female pediatric population. These models can be used to determine and monitor body growth in peripubertal girls, either to assess health indicators (i.e., overweight control, obesity and the associated risks), or improve sports performance (i.e., body adequacy and physical preparation for sports). The internal validation method PRESS (Holiday, Ballard & McKeown, 1995) confirms the effectiveness of the model in predicting the body components with high internal validity, with high coefficients of determination and low prediction errors. These models are a valid alternative to estimate body composition in girls and can be applied in nonclinical or field settings.
... Assumptions for good predictive models of body composition recommend that models should be proposed for a wider clinical application [30], make valid assumptions in relations between the components [28], i.e., if relations between FFM, FM and TBW are constant for all ages. Some equations proposed are more well-founded descriptions and specific to predict only one component [31], or restricted age range [32]. ...
Background
Anthropometric models remain appropriate alternatives to estimate body composition of peripubertal populations. However, these traditional models do not consider other body components that undergo major changes during peripubertal growth spurt, with restrictions to a multicompartimental approach as a quantitative growth. DXA has great potential to determine pediatric body composition in more than one component (3-C), but has limited use in field settings. Thus, the aim of this study was to propose and validate an anthropometric model for simultaneous estimation of lean soft tissue (LST), bone mineral content (BMC) and fat mass (FM) in healthy girls, from a multivariate approach of densitometric technique, as the criterion method. MethodsA sample of 84 Brazilian girls (7-17 years) was defined by chronological age and maturity offset. Whole total and regional DXA body scan were performed and, the components were defined (LST, BMC and FM) and considered as dependent variables. Twenty-one anthropometric measures were recorded as independent variables. From a multivariate regression, an anthropometric multicompartmental model was obtained. ResultsIt was possible to predict DXA body components with only four predictive measurements: body weight (BW); supra-iliac skinfold (SiSk); horizontal abdominal skinfold (HaSk) and contracted arm circumference (CaCi) with high coefficients of determination and low estimation errors (LST = 0.6662657 BW - 0. 2157279 SiSk - 0.2069373 HaSk + 0.3411678 CaCi - 1.8504187; BMC = 0.0222185 BW - 0.1001097 SiSk - 0.0064539 HaSk - 0.0084785 CaCi + 0.3733974 and FM = 0.3645630 BW + 0.1000325 SiSk - 0.2888978 HaSk - 0.4752146 CaCi + 2.8461916). The cross-validation was confirmed through the sum of squares of residuals (PRESS) method, presenting accurate coefficients (Q2PRESS from 0.81 to 0.93) and reduced error reliability (SPRESS from 0.01 to 0.30). Conclusions
When sophisticated instruments are not available, this model provides valid estimates of multicompartmental body composition of girls in healthy Brazilian pediatric populations.
Aim: This study (1) compared skeletal muscle mass (SMM) and muscle strength in familial Mediterranean fever (FMF) patients with those of healthy controls (HCs) and (2) investigated the association of SMM and muscle strength with disease severity and quality of life (QOL). Materials and Methods: This study included 31 FMF patients and 30 matched HCs. Disease severity was evaluated using the International Severity Scoring System for FMF (ISSF). Body composition parameters were measured using a bioelectrical impedance analysis. Grip and pinch strengths were calculated for muscle strength. Health status was assessed with Short Form 36 (SF-36). Results: The all-body composition parameters of the FMF patients, including SMM, were similar to those of the HCs, with significantly lower grip and pinch strengths. All SF-36 scores of the FMF patients were significantly lower than those of the HCs. Positive correlations were observed between muscle-related indices and pinch strength for some SF-36 domains. Conclusion: Muscle- or fat-related indices were similar among adult patients with FMF and the HCs. In contrast, patients with FMF had a poorer health-related QOL and lower grip and pinch strengths than the HCs. Further studies are needed to determine the clinical significance of these correlations in patients with FMF.
Background
In terms of assessing obesity-associated risk, quantification of visceral adipose tissue (VAT) has become increasingly important in risk assessment for cardiovascular and metabolic diseases. However, differences exist in the accuracy of various modalities, with a lack of up-to-date comparison with three-dimensional whole volume assessment.
Aims
Using CT or MRI three-dimensional whole volume VAT as a reference, we evaluated the correlation of various commonly used modalities and techniques namely body impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA) as well as single slice CT to establish how these methods compare.
Methods
We designed the study in two parts. First, we performed an intra-individual comparison of the 4558 participants from the UK Biobank cohorts with matching data of MRI abdominal body composition, DXA with VAT estimation, and BIA. Second, we evaluated 174 CT scans from the publicly available dataset to assess the correlation of the commonly used single-slice technique compared to three-dimensional VAT volume.
Results
Across the UK Biobank cohort, the DXA-derived VAT measurement correlated better (R ² 0.94, p<0.0001) than BIA (R ² 0.49, p<0.0001) with reference three-dimensional volume on MRI. However, DXA-derived VAT correlation was worse for participants with a BMI of < 20 (R ² = 0.62, p=0.0013). A commonly used single slice method on CT demonstrated a modest correlation (R ² between 0.51 – 0.64), with best values at L3- and L4 (R ² L3 = 0.63, p<0.0001; L4 = 0.64, p<0.0001) compared to reference three-dimensional volume. Combining multiple slices yielded a better correlation, with a strong correlation when L2-L3 levels were combined (R ² = 0.92, p<0.0001).
Conclusion
When deployed at scale, DXA-derived VAT volume measurement shows excellent correlation with three-dimensional volume on MRI based on the UK Biobank cohort. Whereas a single slice CT technique demonstrated moderate correlation with three-dimensional volume on CT, with a stronger correlation achieved when multiple levels were combined.
The aim of this study is to know the various parameters of the body, their range and their importance in analyzing the different illness present in the body. The body parameters vary according to male, female, height, weight and lifestyle. Different methods are proposed by researchers for studying the body parameters. The electrical bio-impedance method is the most used method for the evaluation of body parameters since it is noninvasive, easy to use, inexpensive and safe on the human body. The electrical bio-impedance method is further used in two ways: single-frequency and multi-frequency bio-impedance analysis-based instruments. In this paper, both single-frequency and multi-frequency bio-impedance analysis-based instruments applications used for the measurement of different body parameters are discussed in detail. Different body parameter such as fat mass, water component, electrical body parameters are explained in detail here and their range for healthy and unhealthy persons are also summarized here. This paper presents the detail illustration of important body parts.
Children with cancer require adequate nutritional support to prevent malnutrition. This study investigated the impact of chemotherapy on anthropometrical status and body composition during the first six months of treatment. Anthropometrical status and body composition were measured at diagnosis, utilizing standardized protocols and validated S10 InBody bio-electrical impedance (BIA) measurements and compared to subsequent consecutive monthly follow-up measurements to plot changes over time during the first six months. Statistical significance was defined as p < 0.05. Forty-three newly diagnosed children (median age 4 years, IQR: 2.0-7.6; male-female ratio 1:0.9; 53% haematological malignancies and 47% solid tumors) were included. Prevalence of malnutrition varied, with under-nutrition 14% (mid-upper arm circumference (MUAC)/body mass index (BMI)), over-nutrition 9.3% (BMI) and stunting 7% at diagnosis. MUAC (14%) identified fewer participants with underlying muscle store depletion than BIA (41.8%). Chemotherapy exposure acutely exacerbated existing nutritional depletion during the first two months after diagnosis for all variables except fat mass (FM), with contrary effects on cancer type. Haematological malignancies had rapid increases in weight, BMI and FM. All patients had an acute loss of skeletal muscle mass. Nutritional improvement experienced by all cancer types during month two to three of treatment resulted in catch-up growth, with a significant increase in weight (chi2=40.43, p < 0.001), height (chi2=53.79, p < 0.001), BMI (chi2=16.32, p < 0.005), fat free mass (chi2=23.69, p < 0.003) and skeletal muscle mass (chi2=24.19, p < 0.001) after six months. Monthly nutritional assessments, including advanced body composition measurements, are essential to provide timely nutritional interventions to overcome the acute decline in nutritional reserves observed during the first two months of chemotherapy exposure.
Background: Imatinib mesylate (IM) is the treatment of choice in patients with chronic myeloid leukemia (CML). Among its nonhematological adverse events, water retention is the most common, together with weight gain. However, no thorough description of the body composition in these patients has been informed. Therefore, our purpose was to evaluate the nutritional status, body composition and handgrip-strength in patients with CML treated with IM. Methods: We conducted a cross-sectional study in 78 patients (n = 48 men, 30 women) with chronic myeloid leukemia in the chronic (82%) or accelerated (18%) phases. We assessed body mass index (BMI), body composition by bioelectrical impedance, performed vector analysis through Bioelectrical Impedance Vector Analysis, and handgrip-strength measurement in patients with at least 3 months of IM treatment. Hematocrit and hemoglobin values were collected from the medical charts. Results: BMI was within the normal range in 28.2%, indicated overweight in 39.7% and obesity in 30.8%. According to BIVA, 25.6% of the patients were muscle-depleted and were older (p = 0.006) and received lower doses of IM (p < 0.001). Conclusions: In patients with CML with ≥3 months of IM treatment muscular depletion is frequent and is related to lower doses of IM.
Background and purpose
A femoral neck fracture (FNF) may have long-term effects on the patient's function, also in patients younger than 70 years. These long-term effects are not well described, since most studies have short follow-ups. The aim of this study was to investigate clinical outcome by performance-based functional tests, hand grip strength, and hip function in different subgroups. The secondary aim was to study surgical complications, bone mineral density (BMD) and occurrence of sarcopenia 10 years after a FNF.
Patients and methods
A prospective multicenter study with a 10-year follow-up of patients aged 20-69 years with a FNF treated with internal fixation (IF). Five-times sit-to-stand test (5TSST), 4-m walking speed test, hand grip strength (HGS) and Harris Hip Score (HHS) were performed.
A radiographic examination of the hip was performed and re-operations were registered. Bone mineral density (BMD) at the hip, spine and total body composition were assessed with dual energy x-ray absorptiometry (DXA). Present sarcopenia was determined by the combination of reduced functional performance and low fat-free mass index (FFMI).
Results
A total of 58 patients were included. 5TSTS was normal in 45% of the patients and old age was associated with poorer performance (p<0.001). 76% of the study population had a normal speed gait and likewise, old age (p=0.005) and walking aids (p=0.001) were associated with poor performance. HGS was normal in 82% of the men and 64% of the women. HHS showed that 85% had a good/excellent function. A major re-operation was performed in 34% of the patients with displaced FNF and in 20% of patients with non-displaced FNF. 74% displayed osteopenia and 12% osteoporosis. 17% of the men and 38% of the women had sarcopenia.
Interpretation
The majority of patients less than 70 years of age with a FNF treated with IF, had normal functional tests, muscle strength and a good hip function ten years post-operatively. However, one in ten had osteoporosis, and one third was sarcopenic which indicate the importance of encouraging regular muscle preserving resistance training after hip fracture.
A densitometria óssea (DO) é o método de escolha e o mais amplamente usado, acurado e preciso para avaliação quantitativa da densidade mineral óssea (DMO), diagnóstico e rastreamento de baixa massa óssea para idade/osteopenia/osteoporose, bem como identificação de indivíduos com maior risco de fratura por fragilidade e monitorização da massa óssea, relacionada à própria doença ou ao tratamento instituído. Assim, esta revisão se propõe a discutir as peculiaridades técnicas da metodologia, bem como enumerar os detalhes da aquisição, análise e problemas/artefatos envolvidos com a interpretação clínica do exame. Unitermos: Densitometria óssea. Aquisição. Análise. Osteoporose. Composição corporal. Interpretação clínica.
Sarcopenia is a disease affecting muscle strength, muscle quantity/quality, and physical performance. Since the bioelectrical impedance analysis (BIA) is accessible in the clinical practice, its use may be helpful to estimate, from its BIA parameters [resistance (R/H), reactance (Xc/H), and phase angle (PA)], the components for sarcopenia diagnosis, muscle mass, and strength. We aimed to investigate the association between BIA parameters and measures of muscle mass and strength. A cross-sectional analysis was performed in 51 older adults assessed for the sarcopenia outcomes [Appendicular Skeletal Muscle Mass Index (ASMMI) from DXA and Handgrip Strength (HGS) from dynamometry] and predictors [BIA parameters (R/H, Xc/H, and phase angle)], anthropometric measures, physical activity, and demographic data (age and sex). Sarcopenia was classified according to the EWGSOP2. Association between the outcomes and predictors was analysed by correlation tests and linear regression models, adjusted by sex and age. A total of 17.65% of participants were classified with probable sarcopenia and 9.8% were diagnosed for sarcopenia. Significant negative correlations were found between ASMMI and HGS and R/H and Xc/H, in all participants. Regression models detected statistically significant association between ASMMI and R/H (B = −0.013, p <0.001) and Xc/H (B= −0.08, p= <0.01), adjusted for age and sex. We found significant associations between BIA raw parameters (R/H and Xc/H) and muscle mass assessed by ASMMI. More robust studies are necessary to determine the efficacy of raw BIA parameters to predict sarcopenia in older adults through predictive equations.
Background & Aims
Change in hydration is common in children with severe acute malnutrition (SAM) including during treatment, but is difficult to assess. We investigated the utility of bio-electrical impedance vector analysis (BIVA), a quick non-invasive method, for indexing hydration during treatment.
Methods
We studied 350 children 0·5-14 years of age with SAM (mid-upper arm circumference <11·0 cm or weight-for-height <70% of median, and/or nutritional oedema) admitted to a hospital nutrition unit, but excluded medically unstable patients. Weight, height (H), resistance (R), reactance (Xc) and phase angle (PA) were measured and oedema assessed. Similar data were collected from 120 healthy infants and preschool/school children for comparison. Means of height-adjusted vectors (R/H, Xc/H) from SAM children were interpreted using tolerance and confidence ellipses of corresponding parameters from the healthy children.
Results
SAM children with oedema were less wasted than those without (p< 0·001), but had BIVA parameters that differed more from those of healthy children (P<0·05) than those non-oedematous. Initially, both oedematous and non-oedematous SAM children had mean vectors outside the reference 95% tolerance ellipse. During treatment, mean vectors migrated differently in the two SAM groups, indicating fluid loss in oedematous patients, and tissue accretion in non-oedematous patients. At admission, R/H was lower (oedematous) or higher (non-oedematous) among children who died than those who exited the hospital alive.
Conclusions
BIVA can be used in children with SAM to distinguish tissue-vs. hydration-related weight changes during treatment, and also identify children at high risk of death enabling early clinical interventions.
This study investigated psycho-physiological factors as predictors of sport prominence and excellence among student-athletes in Southwestern, Nigeria. Psychological factors are goal setting and self-efficacy, while physiological factors are muscular strength.. muscular endurance and body composition. Expost-facto research design was used for the study. Purposive sampling technique was used to select 1604 university athletes' matriculated students who have represented the institutions in NUGA. The instruments used were Goal Setting in Sport Questionnaire (GSTSQ), Sport Se(f Confidence Questionnaire (SSCQ). TCHPER.SD Children/Youth Fitness Test. Five hypotheses were tested at 0.05 level of significance. Data were analysed using inferential statistic of regression. The combined effect of the independent variables (both psychological and physiological factors) yielded coefficient of R2: 0.43 and 0.46 respectively and this translated into 43% and 46% of the total variance on sport prominence and excellence. The F-value (F (3, 600) = 25.49. P< 0.05) was found to be significant. Four out of five independent variables tested had significant contributions (P< 0.05): goal setting (β = .18. t=6.68). self-efficacy (β =.058. t= 2.79), muscular strength (β =.06, t=2.07) and muscular endurance (β = .19, t=6.94) to sport prominence and excellence. However, body composition had no significant contribution. Based on the result of the findings. it was recommended that both psychological and physiological factors intervention support be given student-athletes in order to enhance sport performance, prominence and excellence.
Objectives:
The aims of this study were to develop and validate a resting energy expenditure (REE) predictive equation in a cohort of patients on dialysis and to test the accuracy of two previously developed specific equations to estimate REE of these patients.
Methods:
A database with REE measured by indirect calorimetry (IC) of 189 patients on hemodialysis and peritoneal dialysis was used to develop and validate the new equation. The sample including only patients on hemodialysis (n = 131) was used to test the accuracy of the specific REE dialysis equations by Vilar and Byham-Gray.
Results:
Multiple regression analysis generated two equations: REE (kcal/d) = 957.02 - 8.08 × age + 11.07 × body weight + 136.4 (if men) (R2 = 0.515) (1) REE (kcal/d) = 624.6-4.8 × age + 20.6 × fat-free, ass-fat-free mass-8.65 (if men) (R2 = 0.512) (2) In the validation group, REE by both equations did not differ from the REE measured by IC. No bias was found in the Bland-Altman analysis and the intraclass correlation coefficient and P20 test showed good reliability with measured REE. Vilar's equation overestimated REE; whereas REE generated by Byham-Gray's equation did not differ from measured REE. Proportional and systematic biases were significant for both equations.
Conclusions:
The new equations developed showed good accuracy and can be valuable to estimate energy needs of patients on dialysis. Byham-Gray's and Vilar's equations presented low to moderate performance to estimate REE of the patients on dialysis.
Conditions affecting metabolism, such as disease and aging, alter body fat mass and lean body mass. In recent studies, it has been emphasized that the calculation of the body weight and BMI values of individuals is not sufficient in determining the underlying causes about the body weight related physiological or psychological problems. It is essential to assess the body composition besides measuring body weight and height. Even in evaluating health risks recent studies held on fat free mass index (FFMI).
Background and aims:
Body composition is important as a marker of both current and future health status. Bioelectrical impedance analysis (BIA) is a simple and accurate method for estimating body composition in field, clinical and research settings, if standard protocol procedures are followed. However, BIA requires population-specific equations since applicability of existing equations to diverse populations has been questioned. This study aimed to derive predictive equations for Total Body Water (TBW), Fat Free Mass (FFM) and Fat Mass (FM) determinations with BIA and anthropometric measurements in a population of children and adolescents aged 8-19 years in Uganda.
Methods:
A cross-sectional study was conducted among 203 children and adolescents aged 8-19 years attending schools in Kampala district (also referred to as Kampala city since the city is conterminous with the district), Uganda through a two-stage cluster sample design. Deuterium dilution method (DDM) was used as the reference measure while BIA and anthropometric measures were used to create the new body composition prediction equations through multivariate regression.
Results:
The new prediction equations explained 88%, 87% and 71% of the variance in TBW, FFM % and of FM respectively with no statistical shrinkage upon cross-validation. The linear regression models proposed in this study were well adjusted with respect to TBW, FFM and FM. Log of TBW obtained by DDM = 0.0129 × Impedance index + 0.0055 × Age + 0.0049 Waist Circumference + 0.1219Ht2 + 2.0388. Log of FFM obtained by DDM = 0.0197 × FFM obtained by BIA - 0.0181 sex code - 0.00055 × Impedance + 3.1761. Log of FM obtained by DDM = 0.0634 × FM obtained by BIA - 0.1881 sex code + 0.0252 × Weight + 0.5273.
Conclusion:
The use of these equations for more accurate body composition assessment may facilitate identification of effective intervention strategies to prevent or combat overweight and obesity among children and adolescents. They may also assist in treatment of conditions where more accurate information on body composition measures is required.
The evaluation of the total body composition by discriminating its different components is a very useful tool in clinical practice. Bioelectrical impedance analysis (BIA) has become a good tool for this assessment. The technique relies upon electrical properties of the body that were described since 1871 and has the possibility of estimating extracellular fluid/intracellular fluid volume ratio. Changes in this ratio underlie many critical clinical conditions and diseases. In this chapter, its principles, assumptions, and clinical uses in its various modalities are described.
Kidney International aims to inform the renal researcher and practicing nephrologists on all aspects of renal research. Clinical and basic renal research, commentaries, The Renal Consult, Nephrology sans Frontieres, minireviews, reviews, Nephrology Images, Journal Club. Published weekly online and twice a month in print.
To describe differences in the 22 y mortality risk associated with body mass index (BMI), body fat or fat-free mass, in order to examine if the differential health consequences of fat and fat-free mass may be responsible for elevated mortality rates at both high and low BMI.
Prospective cohort study, a 22 y follow-up.
General community. The study of men born in 1913, Gothenburg.
787 men aged 60 y.
Number and time of total deaths from 1973 to 1995.
The risk of dying was a linear function of percentage fat and fat-free mass, and increased from a relative risk of 1.00 in men belonging to the lowest fifth to 1.4 (95% confidence interval 1.11-1.99) in men in the highest fifth of percentage fat mass. For BMI the lowest risk was observed for men belonging to the middle fifth of BMI. When the relative risk was set at 1.00 for subjects belonging to the middle fifth of BMI the risk associated with the low BMI fifth was 1.3 (95% confidence interval 0.94-1.68) and that with the highest fifth was 1. 5 (95% confidence interval 1.09-1.96). Analyses including both body fat and fat-free mass showed that total mortality was a linear increasing function of high fat and low fat-free mass.
The apparent U-shaped association between BMI and total mortality may be the result of compound risk functions from body fat and fat-free mass. International Journal of Obesity (2000)24, 33-37
Bioelectrical-impedance spectroscopy (BIS) is a very attractive method for body composition measurements in a clinical setting. However, validation studies often yield different results. This can partly be explained by the different approaches used to transform measured resistance values into body compartments.
The aim of this study was to compare the linear regression (LR) method with the Hanai Mixture theory (HM). Secondly, the effect of degree of overweight on the accuracy of BIS was analysed.
In 90 people (10 M, 80 F; body mass index (BMI) 23-62 kg/m2) total body water (TBW) and extracellular water (ECW) were measured by deuterium and NaBr dilution methods, respectively, and by BIS. Resistance values of ECW (R(ECW)) and TBW (R(TBW)) were used for volume calculations. Data of half the group were used for LR based on L2/R (L = length, R = resistance) to predict TBW and ECW and to calculate the constants used in the HM (kECW), k(p)). Prediction equations and constants were cross-validated in Group 2.
Bland and Altman analysis showed that the LR method underestimated TBW by 1.1 l (P < 0.005) and ECW by 1.1 l (P < 0.005). The HM approach underestimated ECW by 0.8 l (P < 0.005). The correlations with the dilution methods and the SEEs for TBW and ECW were comparable for the two approaches. The prediction error of BIS for TBW and ECW correlated with BMI. The constant kECW, and the specific resistivities of the ECW and intracellular water (ICW) pECW and pICW were also correlated with BMI.
The mixture approach is slightly more accurate than linear regression, but not sensitive enough for clinical use. The constants used in the HM model are not constants in a population with a wide variation in degree of overweight. The physical causes of the correlation between BMI and constants used in the model should be studied further in order to optimize the mixture model.
To study the relationship between body fat percentage and body mass index (BMI) in three different ethnic groups in Singapore (Chinese, Malays and Indians) in order to evaluate the validity of the BMI cut-off points for obesity.
Cross-sectional study.
Two-hundred and ninety-one subjects, purposively selected to ensure adequate representation of range of age and BMI of the general adult population, with almost equal numbers from each ethnic and gender group.
Body weight, body height, sitting height, wrist and femoral widths, skinfold thicknesses, total body water by deuterium oxide dilution, densitometry with Bodpod(R) and bone mineral content with Hologic(R) QDR-4500. Body fat percentage was calculated using a four-compartment model.
Compared with body fat percentage (BF%) obtained using the reference method, BF% for the Singaporean Chinese, Malays and Indians were under-predicted by BMI, sex and age when an equation developed in a Caucasian population was used. The mean prediction error ranged from 2.7% to 5.6% body fat. The BMI/BF% relationship was also different among the three Singaporean groups, with Indians having the highest BF% and Chinese the lowest for the same BMI. These differences could be ascribed to differences in body build. It was also found that for the same amount of body fat as Caucasians who have a body mass index (BMI) of 30 kg/m2 (cut-off for obesity as defined by WHO), the BMI cut-off points for obesity would have to be about 27 kg/m2 for Chinese and Malays and 26 kg/m2 for Indians.
The results show that the relationship between BF% and BMI is different between Singaporeans and Caucasians and also among the three ethnic groups in Singapore. If obesity is regarded as an excess of body fat and not as an excess of weight (increased BMI), the cut-off points for obesity in Singapore based on the BMI would need to be lowered. This would have immense public health implications in terms of policy related to obesity prevention and management.
We used bioelectrical impedance analysis (BIA) as an exploratory tool to monitor the changes in body composition induced by a short-term (3-wk) weight reduction (energy-restricted diet, moderate aerobic exercise conditioning and psychological counselling) in 175 highly obese subjects (body mass index, BMI=41.7+/-5.8 kg/m2). The decrease in weight and BMI after the weight reduction program was 3.4% (geometric mean, p<0.0001) and 3.7+/-1.3 kg/m2 (mean+/-SD, p<0.0001), respectively. Bioelectrical impedance (Z) increased of about the same value at each of the measured frequencies (from 6+/-10% at 5 kHz to 5+/-9% at 100 kHz, mean+/-SD, p<0.0001). A statistically significant increase in Z5:Z100 was also seen (p<0.0001), but its clinical significance is questionable owing to its low absolute value (<1%). Taken together, these data suggest that no clinically relevant change in body water distribution occurred in our subjects as a result of the weight reduction program. However, the changes in Z did not satisfactorily predict the changes in anthropometric dimensions despite the evidence of a substantial association between Z and anthropometry both before and after the weight reduction program. Thus, accurate predictions of body composition changes in obese subjects may require more than two BIA measurements so as to have a better description of the weight-losing process.
The body water changes indicated by bioelectric impedance analysis (BIA) and body weight were studied in 12 patients admitted to hospital for acute treatment of congestive heart failure (NYHA-class II-III). BIA was performed at the time of admittance and on the third day by using a multifrequency technique, which allows simultaneous estimation of the total body water (TBW) and the extracellular fluid (ECF) and intracellular fluid (ICF) volumes. The body weight at admittance was 85+/-20 kg. Body weight correlated with the body water compartments (r - 0.9, p<0.001). From day 1 to day 3, the body weight decreased by 2.9+/-1.7 kg. BIA estimated the corresponding reductions of the physiological body fluid spaces to 3.2+/-2.4 L (TBW), 2.7+/-1.6 L (ECF) and 0.5+/-3.2 L (ICF). These results indicate that diuretic treatment for acute congestive heart failure mainly lowers the ECF volume. However, changes in body weight correlated poorly with changes in TBW, r=-0.11. We conclude that, although BIA corresponded well to the weight changes at the group level, a poor correlation in individual patients suggests that BIA is not a suitable tool to monitor the fluid balance in patients with acute congestive heart failure undergoing diuretic treatment.
Changes of body composition occur with aging and influence health status. Thus accurate methods for measuring fat-free mass (FFM) in the elderly are essential.
The purpose of this study was to compare FFM obtained by three bioelectrical impedance analysis (BIA) published formulas specific for the elderly and one equation intended for all age groups, with FFM derived from dual-energy X-ray absorptiometry (FFM(DXA)), in healthy elderly subjects.
Healthy Caucasian subjects over 65 years (106 women, age 75 +/- 6.2, body mass index 25.2 +/- 4.1 and 100 men, age 74.6 +/- 6.6, body mass index 25.8 +/- 3.0) were measured by DXA (Hologic QDR-4500) and BIA (Xitron, 50 kHz). FFM(BIA) was calculated by the published formulas of Deurenberg, Baumgartner, Roubenoff and Kyle and compared to FFM(DXA) by a Bland-Altman analysis.
The Deurenberg and Roubenoff BIA formulas underestimated FFM compared to DXA by -7.1 and -2.9 kg in women and -6.7 and -2.3 kg in men, respectively. The Baumgartner formula overestimated FFM by 4.3 kg in women and 1.4 kg in men. The Kyle formula showed differences of 0.0 kg in women and 0.2 kg in men, and the limits of agreement of FFM(BIA (Kyle)) relative to FFM(DXA) were -3.3 and +3.3 kg for women and -3.8 and +4.3 kg for men.
The Kyle BIA formula accurately predicts FFM in elderly Swiss subjects between 65 and 94 years, with a body mass index of 17 to 34.9 kg/m(2). The other BIA formulas developed especially for the elderly are not valid in this population.
Body weight, weight changes and BMI are easily obtainable indicators of nutritional status, but they do not provide information on the amount of fat-free and fat masses. The purpose of the present study was to determine if fat-free mass (FFM) and fat mass were depleted in patients with normal BMI or serum albumin at hospital admission. A group of 995 consecutive patients were evaluated for malnutrition by BMI, serum albumin, and 50 kHz bioelectrical impedance analysis and compared with 995 healthy adults, matched for age and height, and then compared with FFM and fat mass percentiles previously determined in 5225 healthy adults. A BMI of <or=20 kg/m2 was noted in 17.3 % of patients and serum albumin of <or=35 g/l was found in 14.9 % of patients. In contrast, 31 % of all patients were below the tenth percentile for FFM, compared with 10.1 % of controls (chi2, P=0.0001), while 73 % of patients with BMI <or=20 kg/m2 and 31 % of patients with BMI 20-24.9 kg/m2 fell below the tenth percentile for FFM. Furthermore, the FFM was lower in patients than controls and the differences with age in FFM (lower) and fat mass (higher) were greater in patients than in controls. BMI and albumin significantly underestimated the prevalence of malnutrition in patients at hospital admission compared with body composition measurements. Optimal nutritional assessment should therefore include objective measurement of FFM and fat mass.
To describe a method to obtain a profile of the duration and intensity (speed) of walking periods over 24 hours in women under free-living conditions.
A new method based on accelerometry was designed for analyzing walking activity. In order to take into account inter-individual variability of acceleration, an individual calibration process was used. Different experiments were performed to highlight the variability of acceleration vs walking speed relationship, to analyze the speed prediction accuracy of the method, and to test the assessment of walking distance and duration over 24-h.
Twenty-eight women were studied (mean+/-s.d.) age: 39.3+/-8.9 y; body mass: 79.7+/-11.1 kg; body height: 162.9+/-5.4 cm; and body mass index (BMI) 30.0+/-3.8 kg/m(2).
Accelerometer output was significantly correlated with speed during treadmill walking (r=0.95, P<0.01), and short unconstrained walks (r=0.86, P<0.01), although with a large inter-individual variation of the regression parameters. By using individual calibration, it was possible to predict walking speed on a standard urban circuit (predicted vs measured r=0.93, P<0.01, s.e.e.=0.51 km/h). In the free-living experiment, women spent on average 79.9+/-36.0 (range: 31.7-168.2) min/day in displacement activities, from which discontinuous short walking activities represented about 2/3 and continuous ones 1/3. Total walking distance averaged 2.1+/-1.2 (range: 0.4-4.7) km/day. It was performed at an average speed of 5.0+/-0.5 (range: 4.1-6.0) km/h.
An accelerometer measuring the anteroposterior acceleration of the body can estimate walking speed together with the pattern, intensity and duration of daily walking activity.
Bioelectrical impedance spectroscopy (BIS) is an attractive method for measuring body composition because it is noninvasive, simple, and cheap. The effect of obesity on the accuracy of impedance measurements has been recognized for some time, but no conclusive explanations or ways to correct the measurement errors have been published. We studied the effect of the composition of weight loss on the accuracy of BIS to measure changes in body fluid volumes during severe weight loss. Within subjects the effect of variable losses of fat mass was studied.
In 10 morbidly obese female subjects who underwent gastric reduction surgery, changes in total body water (TBW) and extracellular water (ECW) were monitored for 1 year by deuterium (Deu) and bromide (Br) dilution and by BIS. Measurements were performed before the operation and after 2 weeks, 3 months, and 1 year. Extrapolated resistance values of extracellular (Recw) and intracellular water (Ricw) were used in mixture equations for calculating the corresponding fluid volumes.
After 1 year, weight decreased by 53 kg, TBW (Deu) loss was 8.7 L, and ECW (Br) loss was 4.3 L. Comparison of BIS with reference methods for measuring all possible changes over 6 time-intervals revealed a mean overestimation of TBW (2.4 L, SD = 2.9) and ECW (0.74 L, SD = 2.6) losses by BIS. Overestimation increased significantly with increasing fat losses, expressed as percentage fat of the weight loss and as change in triceps skinfolds. Measured changes in Recw and Ricw were less than expected for an ideal agreement between dilution methods and mixture equations.
BIS with the use of mixture equations overestimates fluid losses during weight loss. The error is associated with the amount of fat loss. The large contribution of the factor weight in the mixture equations is likely to be responsible. The assumptions of mixture theory are not valid in obesity.
To test the impact of body build factors on the validity of impedance-based body composition predictions across (ethnic) population groups and to study the suitability of segmental impedance measurements.
Cross-sectional observational study.
Ministry of Health and School of Physical Education, Nanyang Technological University, Singapore.
A total of 291 female and male Chinese, Malays and Indian Singaporeans, aged 18-69, body mass index (BMI) 16.0-40.2 kg/ m2.
Anthropometric parameters were measured in addition to impedance (100 kHz) of the total body, arms and legs. Impedance indexes were calculated as height2/impedance. Arm length (span) and leg length (sitting height), wrist and knee width were measured from which body build indices were calculated. Total body water (TBW) was measured using deuterium oxide dilution. Extra cellular water (ECW) was measured using bromide dilution. Body fat percentage was determined using a chemical four-compartment model.
The bias of TBW predicted from total body impedance index (bias: measured minus predicted TBW) was different among the three ethnic groups, TBW being significantly underestimated in Indians compared to Chinese and Malays. This bias was found to be dependent on body water distribution (ECW/TBW) and parameters of body build, mainly relative (to height) arm length. After correcting for differences in body water distribution and body build parameters the differences in bias across the ethnic groups disappeared. The impedance index using total body impedance was better correlated with TBW than the impedance index of arm or leg impedance, even after corrections for body build parameters.
The study shows that ethnic-specific bias of impedance-based prediction formulas for body composition is due mainly to differences in body build among the ethnic groups. This means that the use of 'general' prediction equations across different (ethnic) population groups without prior testing of their validity should be avoided. Total body impedance has higher predictive value than segmental impedance.
Background: Changes in body composition in men and women occur with age, but these changes are affected by numerous covariate factors.
Objective: The study examined patterns of change in body composition and determined the effects of long-term patterns of change in physical activity in older men and women and in menopausal status and estrogen use in women.
Design: Serial measures of height, weight, body mass index (BMI), total body fat (BF), percentage BF, and fat-free mass (FFM) from underwater weighing of 102 men and 108 women enrolled in the Fels Longitudinal Study were analyzed. Physical activity levels and menopausal status were included as covariates.
Results: There were significant age-related decreases in FFM and height and increases in total BF, percentage BF, weight, and BMI. Physical activity was associated with decreases in total BF, percentage BF, weight, and BMI in men and were associated with increases in FFM and decreases in total BF and percentage BF in women. Postmenopausal women had significantly higher total BF and percentage BF than did pre- and perimenopausal women. The longer the time since menopause the greater were the increases in weight, BMI, total BF, and percentage BF; however, estrogen use attenuated these increases.
Conclusions: Low FFM can be improved by increased physical activity. The effects of an intervention program on body composition can be masked if only body weight or BMI is measured. The effects of physical activity were more profound in postmenopausal than in premenopausal women, and estrogen use had beneficial effects on body composition.
In patients undergoing hemodialysis (HD) cyclic body fluid changes are estimated by body weight variations, which may be misleading. Conventional bioelectrical impedance analysis (BIA) produces biased estimates of fluids in HD due to the assumption of constant tissue hydration. We used an assumption-free assessment of hydration based on direct measurements of the impedance vector. The impedance vector (standard BIA at 50 kHz frequency) was measured in 1367 HD patients, ages 16 to 89 years with BMI 17 to 31 kg/m2, 1116 asymptomatic (680 M and 436 F), and 251 with recurrent HD hypotension (118 M and 133 F) before and after two HD sessions (thrice weekly bicarbonate dialysis, 210 to 240 min) removing 2.7 kg fluid. The vector distribution of HD patients was compared to 726 healthy subjects with the same age and BMI range. Individual vector measurements (resistance and reactance components) were plotted on the gender specific 50th, 75th and 95th percentiles of the vector distribution in the healthy population (reference tolerance ellipses) as a resistance-reactance graph (RXc graph). The wet-dry weight cycling of HD patients was represented on the resistance-reactance plane with a definite, cyclical, backward-forward displacement of the impedance vector. The vectors of patients with HD hypotension were less steep and more often shifted to the right, out of the reference 75% tolerance ellipse, than asymptomatic patients. A wet-dry weight prescription, based on BIA indications, would bring the vectors of patients back into the 75% reference ellipse, where tissue electrical conductivity is restored. Whether HD patients with vector cycling within the normal third quartile ellipse have better outcome awaits confirmation by longitudinal evaluation.
This study assessed the effects of changes in skin temperature on multifrequency bioimpedance analysis (MF-BIA) and on the prediction of body water compartments. Skin temperature (baseline 29.3 +/- 2.1 degrees C) of six healthy adults was raised over 50 min to 35.8 +/- 0.6 degrees C, followed by cooling for 20 min to 26.9 +/- 1.3 degrees C, by using an external heating and cooling blanket. MF-BIA was measured at both distal (conventional) and proximal electrode placements. Both distal and proximal impedance varied inversely with a change in skin temperature across all frequencies (5-500 kHz). The change in proximal impedance per degree centigrade change in skin surface temperature was approximately 60% of distal impedance. The change in measured impedance at 50 kHz erroneously increased predicted total body water (TBW) by 2.6 +/- 0.9 liters (P < 0.001) and underpredicted fat mass by 3.3 +/- 1.3 kg (P < 0.0001). Computer modeling of the MF-BIA data indicated changes in predicted water compartments with temperature modifications; however, the ratio of extracellular water (ECW) to TBW did not significantly change (P < 0.4). This change in impedance was not due to a change in the movement of water of the ECW compartment and thus probably represents a change in cutaneous impedance of the skin. Controlled ambient and skin temperatures should be included in the standardization of BIA measurements. The error in predicted TBW is < 1% within an ambient temperature range of 22.3 to 27.7 degrees C (72.1-81.9 degrees F).
Nutrition assessment is important during chronic respiratory insufficiency to evaluate the level of malnutrition or obesity and should include body composition measurements. The appreciation of fat-free and fat reserves in patients with chronic respiratory insufficiency can aid in designing an adapted nutritional support, e.g., nutritional support in malnutrition and food restriction in obesity. The purpose of the present study was to cross-validate fat-free and fat mass obtained by various bioelectric impedance (BIA) formulas with the fat-free and fat mass measured by dual-energy X-ray absorptiometry (DXA) and determine the formulas that are best suited to predict the fat-free and fat mass for a group of patients with severe chronic respiratory insufficiency. Seventy-five patients (15 women and 60 men) with chronic obstructive and restrictive respiratory insufficiency aged 45-86 y were included in this study. Body composition was calculated according to 13 different BIA formulas for women and 12 for men and compared with DXA. Because of the variability, calculated as 2 standard deviations, of +/- 5.0 kg fat-free mass for women and +/- 6.4 kg for men for the best predictive formula, the use of the various existing BIA formulas was considered not clinically relevant. Therefore disease-specific formulas for patients with chronic respiratory insufficiency should be developed to improve the prediction of fat-free and fat mass by BIA in these patients.
Changes in body composition in men and women occur with age, but these changes are affected by numerous covariate factors.
The study examined patterns of change in body composition and determined the effects of long-term patterns of change in physical activity in older men and women and in menopausal status and estrogen use in women.
Serial measures of height, weight, body mass index (BMI), total body fat (BF), percentage BF, and fat-free mass (FFM) from underwater weighing of 102 men and 108 women enrolled in the Fels Longitudinal Study were analyzed. Physical activity levels and menopausal status were included as covariates.
There were significant age-related decreases in FFM and height and increases in total BF, percentage BF, weight, and BMI. Physical activity was associated with decreases in total BF, percentage BF, weight, and BMI in men and were associated with increases in FFM and decreases in total BF and percentage BF in women. Postmenopausal women had significantly higher total BF and percentage BF than did pre- and perimenopausal women. The longer the time since menopause the greater were the increases in weight, BMI, total BF, and percentage BF; however, estrogen use attenuated these increases.
Low FFM can be improved by increased physical activity. The effects of an intervention program on body composition can be masked if only body weight or BMI is measured. The effects of physical activity were more profound in postmenopausal than in premenopausal women, and estrogen use had beneficial effects on body composition.
To assess the relationship between central venous pressure values and bioelectrical impedance vector analysis (BIVA), which may be used as complementary methods in the bedside monitoring of fluid status.
Cross-sectional evaluation of a consecutive sample.
Intensive care unit of a university hospital.
One hundred and twenty-one consecutive Caucasian, adult patients of either gender, for whom routine central venous pressure measurements were available.
None.
Central venous pressure values and impedance vector components (i.e., resistance and reactance) were determined simultaneously. Total body water predictions were obtained from regression equations according to either conventional bioimpedance analysis or anthropometry (Watson and Hume formulas). Variability of total body water predictions was unacceptable for clinical purposes. Central venous pressure values significantly and inversely correlated with individual impedance vector components (r2 = .28 and r2 = .27 with resistance and reactance, respectively), and with both vector components together (R2 = .31). Patients were classified in three groups according to their central venous pressure value: low (0 to 3 mm Hg); medium (4 to 12 mm Hg); and high (13 to 20 mm Hg). Three BIVA patterns were considered: vectors within the target (reference) 75% tolerance ellipse (normal tissue hydration); long vectors out of the upper pole of the target (dehydration); and short vectors out of the lower pole of the target (fluid overload). The agreement between BIVA and central venous pressure indications was good in the high central venous pressure group (93% short vectors), moderate in the medium central venous pressure group (35% normal vectors), and poor in low central venous pressure group (10% long vectors).
Central venous pressure values correlated with direct impedance measurements more than with total body water predictions. Whereas central venous pressure values >12 mm Hg were associated with shorter impedance vectors in 93% of patients, indicating fluid overload, central venous pressure values <3 mm Hg were associated with long impedance vectors in only 10% of patients, indicating tissue dehydration. The combined evaluation of intensive care unit patients by BIVA and central venous pressure may be useful in therapy planning, particularly in those with low central venous pressure in whom reduced, preserved, or increased tissue fluid content can be detected by BIVA.
To describe the relation between body composition and age measured by dual-energy X-ray absorptiometry (DXA) in healthy Japanese adults.
Cross-sectional study.
The subjects were 2411 healthy Japanese adults (males 625, females 1786, age 20--79 y) who attended the Fukuoka Health Promotion Center, Fukuoka, Japan for health check-up. Body composition was determined by DXA (QDR-2000, Hologic) for the whole body and three anatomical regions of arms, legs and trunk.
The mean values of body mass index (BMI) and percentage fat mass (%FM) were 23.2+/-3.1 (s.d.) kg/m(2) and 21.8+/-6.8% for males and 22.1+/-3.3 kg/m(2) and 32.0+/-7.5% for females, respectively. For males, curvilinear relations with the peaks in their forties or fifties were seen for the variables associated adiposity, ie BMI, waist and hip circumference, waist-hip ratio, total or regional fat mass (FM), %FM and ratio of trunk FM to leg FM. For females, most of these variables increased linearly in older subjects. Lean mass (LM), bone mineral content (BMC) and bone mineral density (BMD) of the whole body and appendicular LM were relatively constant until the forties and then decreased in both sexes. The rates of decrease in the total or appendicular LM were larger for males than for females, whereas those in BMC or BMD were larger for females than for males.
This study presents the first detailed data on body composition in Japanese, which may be useful when comparing with populations of different racial and ethnic backgrounds and studying ill subjects.
Fat-free mass (FFM) and fat mass (FM) are important in the evaluation of nutritional status. Bioelectrical impedance analysis (BIA) is a simple, reproducible method used to determine FFM and FM. Because normal values for FFM and FM have not yet been established in adults aged 15 to 98 y, its use is limited in the evaluation of nutritional status. The aims of this study were to determine reference values for FFM, FM, and percentage of FM by BIA in a white population of healthy adults, observe their differences with age, and develop percentile distributions for these parameters between ages 15 and 98 y.
Whole-body resistance and reactance of 2735 healthy white men and 2490 healthy white women, aged 15 to 98 y, was determined by 50-kHz BIA, with four skin electrodes on the right hand and foot. FFM and FM were calculated by a previously validated, single BIA formula and analyzed for age decades.
Mean FFM peaked in 35- to 44-y-old men and 45- to 54-y-old women and declined thereafter. Mean FFM was 8.9 kg or 14.8% lower in men older than 85 y than in men 35 to 44 y old and 6.2 kg or 14.3% lower in women older than 85 y than in women 45 to 54 y old. Mean FM and percentage of FM increased progressively in men and women between ages 15 and 98 y. The results suggested that the greater weight noted in older subjects is due to larger FM.
The percentile data presented serve as reference to evaluate deviations from normal values of FFM and FM in healthy adult men and women at a given age.
Bioelectrical impedance measurements were collected in the Third National Health and Nutrition Examination Survey (NHANES III), but their results have not been published. In the NHANES III population, resistance (R) and reactance (Xc) values at 50-kHz frequency were obtained with a Valhalla Scientific meter (model 1990B; San Diego, CA, USA). The RXc graph method was used to identify bivariate pattern distributions of mean vectors (95% confidence ellipses by sex, race, age, and body mass index [BMI]), and individual impedance vectors (50%, 75%, and 95% tolerance ellipses). Data from 10 222 adults (5261 men and 4961 women) formed 90 four-way classification groups, with two sexes, three races or ethnicities (non-Hispanic white, non-Hispanic black, Mexican American), five age classes (20-29, 30-39, 40-49, 50-59, and 60-69 y), and three BMI classes (19-24.9, 25-29.9, and 30-34.9 kg/m 2). Sex, race or ethnicity, BMI and age, in decreasing order, influenced the vector distribution pattern. Mean vectors in women were significantly longer than those in men. Within each sex, the mean vector of non-Hispanic white subjects was shorter and with a smaller phase angle than that of corresponding BMIs from the two other race/ethnic populations. Tolerance ellipses were calculated from sex- and race-specific reference populations 20 to 69 y old and 19 ≤ BMI < 30 kg/m 2 (8022 subjects, 4226 men and 3796 women). After transformation of impedance vector components into bivariate Z scores (standardized deviates, as differences from the mean divided by the standard deviation of the reference population), we constructed one standard, reference, RXc-score graph (50%, 75%, and 95% tolerance ellipses) that can be used with any analyzer in any population. The pattern of impedance vector distribution and reference bivariate intervals for the individual impedance vector are presented for comparative studies (free software at E-mail: [email protected]
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This study aims to examine the association between various measures of adiposity and all-cause mortality in Swedish middle-aged and older men and women and, additionally, to describe the influences of age and sex on these associations.
A prospective analysis was performed in a cohort of 10,902 men and 16,814 women ages 45 to 73 years who participated in the Malmö Diet and Cancer Study in Sweden. Baseline examinations took place between 1991 and 1996, and 982 deaths were documented during an average follow-up of 5.7 years. All-cause mortality was related to the following variables measured at baseline: body mass index (BMI), percentage of body fat, lean body mass (LBM), and waist-to-hip ratio (WHR), with adjustment for age and selected covariates. Body composition data were derived from bioelectrical impedance analysis.
The association between percentage of body fat and mortality was modified by age, particularly in women. For instance, fatness was associated with excess mortality in the younger women but with reduced mortality in the older women. Weaker associations were seen for BMI than for percentage of body fat in both sexes. Placement in the top quintiles of waist-to-hip ratio, independent of overall body fat, was a stronger predictor of mortality in women than in men. The observed associations could not be explained by bias from early death or antecedent disease.
The findings reveal sex and age differences for the effects of adiposity and WHR on mortality and indicate the importance of considering direct measures of adiposity, as opposed to BMI, when describing obesity-related mortality risks.
Body weight and body mass index are easily obtainable indicators of nutrition status but do not provide information on changes in fat-free mass (FFM) and fat mass with age. In this prospective controlled study, we investigated whether body composition measurements were useful in identifying moderately or severely depleted patients, as judged by the Subjective Global Assessment at hospital admission. In addition, the subjects were grouped by age (< or =60 and >60 y) to determine whether there was an effect of aging on the prevalence of malnutrition.
Nine hundred ninety-five consecutive patients were evaluated for malnutrition by body mass index, serum albumin, Subjective Global Assessment, and 50-kHz bioelectrical impedance analysis and compared with 995 age- and height-matched healthy volunteers for FFM and fat mass.
A body mass index less than 20 kg/m(2) was found in 17.3% of patients. Low albumin (< or =34.9 g/L) was found in 14.9% of all patients and 23.7% of those older than 60 y. In contrast, 23.1% and 38.3% of all patients were severely and moderately depleted, respectively, according to the Subjective Global Assessment. FFM was significantly lower in severely depleted men and women and moderately depleted women (P < or = 0.001), and fat mass was significantly higher (P < or = 0.05) in well-nourished patients than in volunteers. Patients older than 60 y had lower FFM and higher fat mass than did patients 60 y or younger or volunteers (P < or = 0.001).
The prevalence of malnutrition was greater in patients older than 60 y than in those 60 y and younger. Patients classified as severely depleted according to the Subjective Global Assessment were depleted of FFM. Body composition measurement can help to identify patients with low FFM and high fat mass.
To determine reference values for fat-free mass index (FFMI) and fat mass index (FMI) in a large Caucasian group of apparently healthy subjects, as a function of age and gender and to develop percentile distribution for these two parameters.
Cross-sectional study in which bioelectrical impedance analysis (50 kHz) was measured (using tetrapolar electrodes and cross-validated formulae by dual-energy X-ray absorptiometry in order to calculate FFMI (fat-free mass/height squared) and FMI (fat mass/height squared).
A total of 5635 apparently healthy adults from a mixed non-randomly selected Caucasian population in Switzerland (2986 men and 2649 women), varying in age from 24 to 98 y.
The median FFMI (18-34 y) were 18.9 kg/m(2) in young males and 15.4 kg/m(2) in young females. No difference with age in males and a modest increase in females were observed. The median FMI was 4.0 kg/m(2) in males and 5.5 kg/m(2) in females. From young to elderly age categories, FMI progressively rose by an average of 55% in males and 62% in females, compared to an increase in body mass index (BMI) of 9 and 19% respectively.
Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner. In contrast to BMI, similar reference ranges seems to be utilizable for FFMI with advancing age, in particular in men.
To determine if fat-free mass and fat mass in acutely ill and chronically ill patients differed from healthy controls at hospital admission and if prevalence of malnutrition differed by body mass index (BMI) or fat-free mass percentile.
995 consecutive patients 15 to 100 years of age admitted to the hospital were measured in the hospital admission center and compared with 995 healthy age- and height-matched subjects
Cross-sectional study. Fat-free mass, fat mass, and percentage fat mass were determined by 50 kHz bioelectrical impedance analysis. Prevalence of malnutrition was determined by BMI < or = 20 kg/m2 or fat-free mass in the 10th percentile.
Analysis of variance was used to examine differences between acutely ill and chronically ill patients and controls and between age groups.
Fat-free mass was significantly lower in patients than controls (P< or = .05), and the difference with age in fat-free mass in patients was greater than the age-related difference in the controls. A higher percentage fat mass was found in spite of lower BMI in chronically ill patients older than 55 years. Among participants, 25% of acutely ill and 37.3% of chronically ill patients fell below fat-free mass in the 10th percentile, compared with 15.6% of acutely ill and 18.9% of chronically ill patients falling below BMI < or = 20 kg/m2.
Weight and BMI do not evaluate body compartments and therefore do not reveal if weight changes result in loss of fat-free mass or gain in fat mass. In spite of minimal differences in BMI between patients and controls, we found that fat-free mass was lower and fat mass was higher in acutely ill and chronically ill patients than controls. The objective measurement of body composition, as part of a comprehensive nutritional assessment, helps to identify subjects who have low fat-free mass or high fat mass.
Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI.
FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated.
FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively.
BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.
We evaluated the performance of different prediction equations to estimate fat-free mass (FFM) from bioelectrical impedance analysis (BIA) in the elderly.
This study was based on 106 (51 male and 55 female) free-living 75-y-old subjects who participated in the Göteborg part of the Nordic Research on Ageing (NORA) study during 1991 and 1992. FFM predicted from BIA (FFM(GOT)) was validated against FFM estimated from measurements of total body water and total body potassium (FFM(REF)). FFM was calculated from BIA prediction equations for the elderly developed by Deurenberg et al. (FFM(WAG)) and Roubenoff et al. (FFM(FHS)). FFM also was calculated from an equation developed in subjects with a wide age range by Kyle et al. (FFM(GEN)). Bland-Altman analysis was performed to compare FFM(REF) with FFM(GOT), FFM(WAG), FFM(FHS), and FFM(GEN), respectively. FFM(GOT) also was compared with FFM derived from these published equations.
Compared with FFM(REF), the FFM(FHS) and FFM(WAG) underestimated FFM by 2.6 and 7.9 kg in males and 4.2 and 9 kg in females, respectively. The FFM(GEN) underestimated FFM in females by 1.3 kg but not in males (mean difference, -0.04 kg). FFM calculated from the BIA equation developed in this population (FFM(GOT)) neither underestimated nor overestimated FFM as compared with FFM(REF), as expected. The differences between FFM(GOT) and FFMs predicted from these equations were of the same magnitude as that observed with FFM(REF).
Different prediction equations produced different values for FFM. The age-specific equations developed in other populations underestimated FFM, whereas FFM(GEN) produced an unbiased estimate of FFM in males but not in females. Thus, the BIA prediction equation needs to be developed and validated in the population under study.
Multicenter study determines prevalence of low fat-free mass and high fat mass at hospital admission.
- Kyle
Kyle UG, Pirlich M, Schuetz T, et al. Multicenter study determines prevalence
of low fat-free mass and high fat mass at hospital admission. Clin Nutr 2002;
21:11.