Ursula G. Kyle

Single Prediction Equation for Bioelectrical Impedance Analysis in Adults Aged 20 -94 Years

Existing equations for bioelectrical impedance analysis (BIA) are of limited use when subjects age or become overweight because these equations were developed in young, normal-weight subjects and are not valid in elderly or overweight people. The purpose of this study was to validate a single BIA equation in healthy white subjects aged 22--94 y with a body mass index between 17.0 and 33.8 kg/m(2). Healthy subjects (202 men and 141 women) aged 20--94 y were measured by two methods: fat-free mass (FFM) was measured by dual-energy x-ray absorptiometry (Hologic QDR-4500) and by a bioelectrical impedance analyzer (Xitron 4000B). Validity of BIA was assessed by double cross validation. Because correlations were high (r = 0.986--0.987) and prediction errors low, a single equation was developed using all subjects, as follows: FFM = -4.104 + (0.518 x height(2)/resistance) + (0.231 x weight) + (0.130 x reactance) + (4.229 x sex: men = 1, women = 0). FFM predicted with dual-energy x-ray absorptiometry was 54.0 +/- 10.7 kg. BIA-predicted FFM was 54.0 +/- 10.5 kg (r = 0.986, standard error of the estimate = 1.72 kg, technical error = 1.74 kg). In conclusion, the new Geneva BIA equation was valid for prediction of FFM in healthy adults aged 22--94 y with body mass indexes between 17.0 and 33.8 kg/m(2). Inclusion of reactance in the single prediction equation appeared to be essential for use of BIA equations in populations with large variations in age or body mass.

Fat-free and fat mass percentiles in 5225 healthy subjects aged 15 to 98 years

OBJECTIVES 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.

Age-related differences in fat-free mass, skeletal muscle, body cell mass and fat mass between 18 and 94 years.

Objective: To determine (1) lean and fat body compartments, reflected by fat-free mass (FFM), appendicular skeletal muscle mass (ASMM), body cell mass (BCM), total body potassium (TBK), fat mass and percentage fat mass, and their differences between age groups in healthy, physically active subjects from 18 to 94 y of age; and (2) if the rate of decrease in any one of the parameters by age might be accelerated compared to others.Methods: A total of 433 healthy ambulatory Caucasians (253 men and 180 women) aged 18–94 y were measured by dual-energy X-ray absorptiometry (DXA) and whole body scintillation counter (TBK counter) using a large sodium iodide crystal (203 mm diameter).Results: The ASMM change (−16.4 and −12.3% in men and women, respectively) in >75 y-old compared to 18 to 34-y-old subjects was greater than the FFM change (−11.8 and −9.7% in men and women, respectively) and this suggests that skeletal muscle mass decrease in older subjects was proportionally greater than non-skeletal muscle mass. BCM (−25.1 and −23.2% in men and women, respectively) and TBK differences were greater than the differences in FFM or ASMM suggesting altered composition of FFM in older subjects. Women had lower peak FFM, ASMM, BCM and TBK than men.Conclusions: The decline in FFM, ASMM, BCM and TBK is accelerated in men and women after 60 y of age and FFM, ASMM, BCM and TBK are significantly lower than in younger subjects. Fat mass continued to increase until around 75 y.Sponsorship: Foundation Nutrition 2000Plus, Geneva, Switzerland.European Journal of Clinical Nutrition (2001) 55, 663–672

Body composition interpretation. Contributions of the fat-free mass index and the body fat mass index.

OBJECTIVE 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. METHODS 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. RESULTS 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. CONCLUSION 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.

Total body mass, fat mass, fat-free mass, and skeletal muscle in older people: cross-sectional differences in 60-year-old persons.

OBJECTIVES: To evaluate body composition parameters, including fat‐free mass (FFM), appendicular skeletal muscle mass (ASMM), relative skeletal muscle mass (RSM) index, body cell mass (BCM), BCM index, total body potassium (TBK), fat mass, percentage fat mass (FM), and their differences between age groups and to evaluate the frequency of sarcopenia in healthy older subjects

Dual-energy X-ray absorptiometry and body composition: differences between devices and comparison with reference methods.

Body composition measurements provide essential information for assessing and monitoring nutrition state.1 Some researchers use underwater weighing or potassium counting as reference methods for total body composition. However, these methods assume a constant density and potassium content of lean body mass (LBM), which may not be true, and measure only two compartments, fat (FM) and LBM.2 A multicompartment approach combining different technologies that measure bone, mineral, muscle and water is preferable and currently considered the gold standard.3 Nevertheless, its high costs, long duration, and the potential intolerance of patients limit its use in clinical routine. Thus, other methods, especially dual-energy x-ray absorptiometry (DXA), have been investigated. Although the original purpose of DXA was to determine bone mineral density, recent devices measure total and regional body composition of three compartments, fat and lean soft tissues and bone mineral.4 This editorial focuses on the advantages and limitations of DXA and the differences in total and regional body compositions. In this article, the combination of lean soft tissue and bone mineral is referred to as LBM.

Hospital length of stay and nutritional status.

Purpose of reviewThis review looks at the recent medical literature on the association between hospital length of stay and nutritional status. Recent findingsSimple anthropometric parameters underestimate the nutritional risk in hospitalized patients. The Malnutrition Universal Screening Tool and Nutritional Risk Screening are simple screening tools that identify patients who require further monitoring. Recent weight loss appears to be the most important single indicator of nutritional status. Body composition measurements identify patients with muscle mass depletion and excess body fat, both of which are significantly associated with increased length of stay. The Subjective Global Assessment is useful at detecting patients with established malnutrition and the Mini Nutritional Assessment for the elderly is useful at detecting patients who need preventive nutritional measures. The Nutritional Risk Index, which incorporates albumin and weight loss, appears to capture both nutritional risk and poor clinical outcome. SummaryNutritional risk is associated with the length of stay in hospital. The choice of nutritional screening and assessment tools depends on the type of institution (university hospital versus community hospital), the patient populations (acute care versus intermediary care; general hospital versus elderly population) and the resources available.

The Dutch Famine of 1944-1945: a pathophysiological model of long-term consequences of wasting disease.

Purpose of reviewThe tragic circumstances of the Dutch Hunger Winter of 1944–1945 created a unique opportunity to study the relation between exposure to prenatal famine and health in adult life. This review addresses the literature on the effects of maternal malnutrition during the different periods of gestation and childhood on health in adult life. Recent findingsExposure to famine during gestation resulted in increases in impaired glucose tolerance, obesity, coronary heart disease, atherogenic lipid profile, hypertension, microalbuminuria, schizophrenia, antisocial personality and affective disorders. Exposure to famine during childhood resulted in changes in reproductive function, earlier menopause, changes in insulin-like growth factor-I and increases in breast cancer. SummaryExposure to famine during gestation and childhood has life-long effects on health, and these effects vary depending on the timing of exposure as well as evolution of the recovery period.

Reference values of fat-free and fat masses by bioelectrical impedance analysis in 3393 healthy subjects

Determination of fat-free mass (FFM) and fat mass (FM) is of considerable interest in the evaluation of nutritional status. In recent years, bioelectrical impedance analysis (BIA) has emerged as a simple, reproducible method used for the evaluation of FFM and FM, but the lack of reference values reduces its utility to evaluate nutritional status. The aim of this study was to determine reference values for FFM, FM, and %FM by BIA in a white population of healthy subjects, to observe the changes in these values with age, and to develop percentile distributions for these parameters. Whole-body resistance of 1838 healthy white men and 1555 women, aged 15-64 y, was determined by using four skin electrodes on the right hand and foot. FFM and FM were calculated according to formulas validated for the subject groups and analyzed for age decades. This is the first study to present BIA-determined age- and sex-specific percentiles for FFM, FM, and %FM for healthy subjects, aged 15-64 y. Mean FM and %FM increased progressively in men and after age 45 y in women. The results suggest that any weight gain noted with age is due to a gain in FM. In conclusion, the data presented as percentiles can serve as reference to evaluate the normality of body composition of healthy and ill subject groups at a given age.

Body composition measurements: interpretation finally made easy for clinical use.

Purpose of review 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. Recent findings 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. Summary 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.