Biomedical subjects

Ursula G Kyle

Publications and source records attributed to Ursula G Kyle.

At least 19 recordsLinked to original sources

PubMed2005

Comparison of body weight and composition measured by two different dual energy X-ray absorptiometry devices and three acquisition modes in obese women.

BACKGROUND AND AIMS: Weight measured by dual-energy X-ray (DXA) was shown to be increasingly underestimated in subjects over 75 kg compared to an electronic scale. This study compares body weight and composition measured by balance beam scale and three DXA acquisition modes in obese subjects. METHODS: In 39 obese, body weight was measured by balance beam scale, and body weight and composition by DXA Hologic QDR4500A in normal (NPM) and high power mode (HPM) (Enhanced v8.26 and v8.26* software) and DXA GE-Lunar Prodigy (v6.5 software). To ensure linearity of body weight and composition measured by the different DXA acquisitions, we also measured 13 women with a body mass index (BMI) of 25-30 kg/m(2). RESULTS: While QDR4500A HPM overestimates scale weight by about 2 kg over the whole BMI spectrum, QDR4500A NPM underestimates scale weight as a weight-dependent response (-1.7+/-1.8 kg overall, -4.1+/-1.6 kg in morbidly obese women). These results suggest switching from one mode to the other at a specific threshold, i.e. in our study a weight of 90 kg or a BMI of 34 kg/m(2). Prodigy gives weight about similar to scale (+0.5+/-0.8 kg). Both Hologic acquisition modes underestimate fat mass but overestimate lean body mass compared to Prodigy. CONCLUSIONS: The QDR4500A NPM is inappropriate in women over 90 kg. Unfortunately, the QDR4500A HPM overestimates body weight in the range of 90-150 kg. The difference between scale and Prodigy weight remains stable throughout weight ranges. To better assess their accuracies in terms of body composition, QDR4500A NPM, HPM and Prodigy should be tested against phantoms or in vivo multi-compartment models.

Absorptiometry, Photon↗

PubMed2005

Comparison of tools for nutritional assessment and screening at hospital admission: a population study.

INTRODUCTION: This population study aimed to test the sensitivity and specificity of nutritional risk index (NRI), malnutrition universal screening tool (MUST) and nutritional risk screening tool 2002 (NRS-2002) compared to subjective global assessment (SGA) and to evaluate the association between nutritional risk determined by these screening tools and length of hospital stay (LOS). METHODS: Patients (n=995) were assessed at hospital admission by four screening tools (SGA, NRI, MUST and NRS-2002). Sensitivity, specificity and predictive values were calculated to evaluate NRI, MUST and NRS-2002 compared to SGA. Multiple logistic regressions, adjusted for age, were used to estimate odds ratios (OR) and confidence interval (CI) for medium and high, compared to low risk in patients hospitalized >11, compared to 1-10 days LOS. RESULTS: The sensitivity was 62%, 61% and 43% and specificity was 93%, 76% and 89% with the NRS-2002, MUST and NRI, respectively. NRS-2002 had higher positive (85%) and negative predictive values (79%) than the MUST (65% and 76%) or NRI (76% and 66%, respectively). Patients who were severely malnourished or at high nutritional risk by SGA (OR 2.4, CI 1.5-3.9), MUST (OR 3.1, CI 2.1-4.7) and NRS-2002 (OR 2.9, CI 1.7-4.9) were significantly more likely to be hospitalized >11 days, compared to 1-10 days, than patients assessed as low risk. CONCLUSION: NRS-2002 had higher sensitivity and specificity than the MUST and NRI, compared to SGA. There was a significant association between LOS and nutritional status and risk by SGA, NRS-2002, MUST and NRI. Nutritional status and risk can be assessed by SGA, NRS-2002 and MUST in patients at hospital admission.

Anthropometry↗

PubMed2005

Clinical evaluation of hormonal stress state in medical ICU patients: a prospective blinded observational study.

OBJECTIVE: To evaluate whether classification of patients as having low, moderate, or high stress based on clinical parameters is associated with plasma levels of stress hormone. DESIGN AND SETTING: Prospective, blinded, observational study in an 18-bed medical ICU. PATIENTS: Eighty-eight consecutive patients. INTERVENTIONS: Patients were classified as low (n=28), moderate (n=33) or high stress (n=27) on days 0 and 3 of ICU stay, based on 1 point for each abnormal parameter: body temperature, heart rate, systemic arterial pressure, respiratory rate, physical agitation, presence of infection and catecholamine administration. The stress categories were: high: 4 points or more, moderate 2-3 points, low 1 point. Plasma growth hormone (GH), insulin-like growth factor 1 (IGF-1), insulin, glucagon, cortisol were measured on days 0 and 3. MEASUREMENTS AND RESULTS: Plasma cortisol and glucagon were significantly higher and IGF-1 lower in high vs. low stress patients on days 0 and 3. High stress patients were more likely to have high cortisol levels (odds ratio 5.8, confidence interval 1.8-18.9), high glucagon (8.7, 2.1-36.1), and low IGF-1 levels (5.9, 1.8-19.0) than low stress patients on day 0. Moderate stress patients were also more likely to have high cortisol and glucagon levels than low stress patients. Insulin and GH did not differ significantly. Results were similar for day 3. CONCLUSIONS: Moderate and severe stress was significantly associated with high catabolic (cortisol, glucagon) and low anabolic (IGF-1) hormone levels. The hormonal stress level in ICU patients can be estimated from simple clinical parameters during routine clinical evaluation.

Adolescent↗

PubMed2005

Body composition in patients with chronic hypercapnic respiratory failure.

STUDY OBJECTIVE: To evaluate the contribution of body composition measurements to clinical assessment in patients on home nasal positive-pressure ventilation for chronic hypercapnic respiratory failure (CHRF), and their relationship to respiratory impairment. METHODS: Patients with CHRF (restrictive lung disease (RLD), n=37; chronic obstructive pulmonary disease (COPD), n=19), during elective yearly evaluations underwent pulmonary function testing (forced expiratory volumes, arterial blood gases, maximal inspiratory and expiratory pressure (PI(max) or PE(max))), and bioelectrical impedance analysis to determine fat-free mass (FFM) index (kg/m(2)) and body fat mass index. RESULTS: When compared with age- and sex-matched healthy controls, RLD patients (OR 5.5, CI 1.9-15.6, P<0.002) and COPD (OR 5.2, CI 1.1-24.9, P=0.04) were significantly more likely to have a low FFM index. Roughly one-half of patients with RLD and one-third with COPD had abnormally low FFM index. Estimation of nutritional status by body mass index (BMI) alone clearly underestimated the prevalence of FFM index depletion. Muscle mass assessed by FFM index explained 26% of variance of PI(max) (P<0.001) and 27% of that of PE(max) (P<0.001). CONCLUSION: BMI alone clearly underestimated FFM depletion, and presence of a very high body fat mass index. Indeed, normal or high BMI can be associated with FFM depletion. Because of its relationship to respiratory muscle strength, an assessment of FFM appears to be valuable in CHRF.

Adolescent↗

PubMed2005

Increased length of hospital stay in underweight and overweight patients at hospital admission: a controlled population study.

BACKGROUND: Reduced lean tissue as well as high fat mass may be independent nutritional risk factors resulting in increased length of hospital stay (LOS). This controlled population study (1707 patients, 1707 volunteers) aimed to evaluate the association between LOS in Geneva and Berlin patients at hospital admission and high fat mass index (FMI, kg/m2) and low fat-free mass index (FFMI, kg/m2), and the respective value of body mass index (BMI) and of FFMI and FMI for nutritional assessment. METHODS: Patients (891 men, 816 women) were prospectively recruited at hospital admission and compared to gender-, age- and height-matched healthy volunteers. Fat-free mass and fat mass, determined at admission by 50 kHz-bioelectrical impedance analysis, were expressed as indices (FFMI and FMI-kg/m2) to normalize for height. Patients were classified in four groups: normal, low FFMI, high FMI, or low FFMI and high FMI. Logistic regressions were used to determine the association between body composition and LOS. RESULTS: Higher FMI and lower FFMI were found in patients at hospital admission than in sex- and age-matched healthy volunteers. Low FFMI, high FMI, and low FFMI/high FMI combined, adjusted for age, were all significantly associated with longer LOS (high FFMI: 1-5 days OR 2.4, CI 2.0-2.9; 6-10 days OR 2.3, CI 1.8-3.0; 11 days OR 2.8, CI 2.2-3.5); low FMI: 1-5 days OR 1.9, CI 1.6-2.2; 6-10 days OR 2.7, CI 2.0-3.5, 11 days OR 2.1, CI 1.7-2.7; low FFMI/high FMI: 1-5 days OR 7.8, CI 5.3-11.4; 6-10 days OR 13.6, CI 7.8-23.5, 11 days OR 11.8, CI 7.0-19.8). CONCLUSION: Increased LOS is associated with adiposity (high FMI) and low muscle mass (low FFMI). The current study shows that both depletion of lean tissue and excess of fat mass negatively affect the LOS. Finally, we found that excess fat mass reduces the sensitivity of BMI to detect nutritional depletion.

Adipose Tissue↗

PubMed2005

Does nutritional risk, as assessed by Nutritional Risk Index, increase during hospital stay? A multinational population-based study.

BACKGROUND: Progressive nutritional depletion has been reported during hospital stay. This prospective study compared the proportion of nutritional risk at hospital admission in three European countries and further evaluated nutritional risk at late versus early phase of hospitalization in one hospital. METHODS: Nutritional risk was determined in Geneva, Switzerland (n = 652), Berlin, Germany (n = 621) and Nice, France (n = 107) at hospital admission, and during hospital stay (0-100 d) in Nice (n = 527) by the Nutritional Risk Index (NRI) = (1.519 x serum albumin, g/l)+41.7 x (present weight/usual weight). NRI score of >100: no risk (NR); 97.5-100: mild risk; 83.5-97.5: moderate risk (MR); 83.5: severe risk (SR). Logistic regressions were used to determine the odds ratios (OR) between MR or SR and length of hospital stay (LOS) 16d compared to 1-15 d or nutritional assessment at 16-100 d compared to 1-15 d of hospitalization. RESULTS: Patients, assessed at hospital admission, who were hospitalized >16d were more likely (P < 0.001) to be at MR (OR 2.0, CI 1.4-3.0) or SR (OR 3.3, CI 1.7-6.2) than patients hospitalized 1-15 d. Nice patients assessed at 16-100 d were more likely (P < 0.001) to be at MR (OR 5.4, CI 2.1-14.3) and SR (OR 14.7, CI 5.4-40.0) than patients assessed at 1-15 d of hospitalization. CONCLUSIONS: The risk of MR or SR by NRI was greater in patients assessed during hospitalization than in patients assessed at hospital admission, which suggests that patients evaluated later during hospitalization are at greater risk than patients evaluated in the early phase of hospitalization. Ongoing assessment during hospitalization seems important to identify patients who are at increased risk for complications.

Analysis of Variance↗

PubMed2005

Comparison of fat-free mass and body fat in Swiss and American adults.

OBJECTIVE: No current studies have compared North American with European body composition parameters, i.e., fat-free mass (FFM), body fat (BF), and percentage of BF (%BF) in large populations. This study compared FFM, BF, and %BF values derived from two bioelectrical impedance analysis (BIA) equations (Geneva and National Health and Nutrition Examination Survey [NHANES]) in Swiss subjects and compared FFM, BF, and %BF values of white Swiss with those of white North American adults with the same BIA equations. METHODS: Healthy adults (3714 men and 3199 women), ages 20 to 79 y, in Switzerland were measured by single-frequency BIA and compared with means and standard deviations for body mass index and body composition parameters obtained from the NHANES III study (United States; n = 2538 men, 2862 women). FFM was calculated with the Geneva and NHANES equations. RESULTS: Mean FFMGENEVA values did not differ from FFMNHANES values in men but was significantly lower (-1.5 kg) in women. FFM and BF values in American men, who weighed 4.2 to 12.0 kg more than the Swiss men, were significantly higher (+2.1 to +6.0 kg and +1.5 to +6.4 kg, respectively) than those in the Swiss men. FFM and BF values in American women, who weighed 2.3 to 12.1 kg more than the Swiss women, were significantly higher (+1.3 to +2.1 kg and +4.8 to +11.8 kg, respectively, except FFM in subjects ages 20 to 29 y and BF in those ages 70 to 79 y) than FFMGENEVA values in Swiss women. FFM in American women was significantly lower (+1.3 and +1.9 kg) and non-significantly higher than FFMNHANES in Swiss women. CONCLUSION: NHANES and Geneva BIA equations estimate body composition equally well in men, but further research is necessary to determine the discrepancies in FFM between BIA equations in women. The greater weight of the American subjects yielded higher values for FFM, BF, and %BF in American than in Swiss men and women.

Adipose Tissue↗

PubMed2005

Hospital length of stay and nutritional status.

PURPOSE OF REVIEW: This review looks at the recent medical literature on the association between hospital length of stay and nutritional status. RECENT FINDINGS: Simple 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. SUMMARY: Nutritional 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.

Anthropometry↗

PubMed2004

Bioelectrical impedance analysis--part I: review of principles and methods.

The use of bioelectrical impedance analysis (BIA) is widespread both in healthy subjects and patients, but suffers from a lack of standardized method and quality control procedures. BIA allows the determination of the fat-free mass (FFM) and total body water (TBW) in subjects without significant fluid and electrolyte abnormalities, when using appropriate population, age or pathology-specific BIA equations and established procedures. Published BIA equations validated against a reference method in a sufficiently large number of subjects are presented and ranked according to the standard error of the estimate. The determination of changes in body cell mass (BCM), extra cellular (ECW) and intra cellular water (ICW) requires further research using a valid model that guarantees that ECW changes do not corrupt the ICW. The use of segmental-BIA, multifrequency BIA, or bioelectrical spectroscopy in altered hydration states also requires further research. ESPEN guidelines for the clinical use of BIA measurements are described in a paper to appear soon in Clinical Nutrition.

Body Composition↗

PubMed2004

Bioelectrical impedance analysis-part II: utilization in clinical practice.

BIA is easy, non-invasive, relatively inexpensive and can be performed in almost any subject because it is portable. Part II of these ESPEN guidelines reports results for fat-free mass (FFM), body fat (BF), body cell mass (BCM), total body water (TBW), extracellular water (ECW) and intracellular water (ICW) from various studies in healthy and ill subjects. The data suggests that BIA works well in healthy subjects and in patients with stable water and electrolytes balance with a validated BIA equation that is appropriate with regard to age, sex and race. Clinical use of BIA in subjects at extremes of BMI ranges or with abnormal hydration cannot be recommended for routine assessment of patients until further validation has proven for BIA algorithm to be accurate in such conditions. Multi-frequency- and segmental-BIA may have advantages over single-frequency BIA in these conditions, but further validation is necessary. Longitudinal follow-up of body composition by BIA is possible in subjects with BMI 16-34 kg/m(2) without abnormal hydration, but must be interpreted with caution. Further validation of BIA is necessary to understand the mechanisms for the changes observed in acute illness, altered fat/lean mass ratios, extreme heights and body shape abnormalities.

Algorithms↗

PubMed2004

Sedentarism affects body fat mass index and fat-free mass index in adults aged 18 to 98 years.

OBJECTIVE: Body mass index does not discriminate body fat from fat-free mass or determine changes in these parameters with physical activity and aging. Body fat mass index (BFMI) and fat-free mass index (FFMI) permit comparisons of subjects with different heights. This study evaluated differences in body mass index, BFMI, and FFMI in physically active and sedentary subjects younger and older than 60 y and determined the association between physical activity, age, and body composition parameters in a healthy white population between ages 18 and 98 y. METHODS: Body fat and fat-free mass were determined in healthy white men (n = 3549) and women (n = 3184), between ages 18 and 98 y, by bioelectrical impedance analysis. BFMI and FFMI (kg/m2) were calculated. Physical activity was defined as at least 3 h/wk of endurance-type activity for at least 2 mo. RESULTS: Physically active as opposed to sedentary subjects were more likely to have a low BFMI (men: odds ratio [OR], 1.4; confidence interval [CI], 0.7-2.5; women: OR 1.9, CI 1.6-2.2) and less likely to have very high BFMI (men: OR, 0.2; CI, 0.1-0.2; women: OR, 0.1; CI, 0.02-0.2), low FFMI (men: OR, 0.5; CI, 0.3-0.9; women: OR, 0.7; CI, 0.6-0.9), or very high FFMI (men: OR, 0.6; CI, 0.4-0.8; women: OR, 0.7; CI, 0.5-1.0). Compared with subjects younger than 60 y, those older than 60 y were more like to have very high BFMI (men: OR, 6.5; CI, 4.5-9.3; women: OR, 14.0; CI, 9.6-20.5), and women 60 y and older were less likely to have a low BFMI (OR, 0.4; CI, 0.2-0.5). CONCLUSIONS: A clear association was found between low physical activity or age and height-normalized body composition parameters (BFMI and FFMI) derived from bioelectrical impedance analysis. Physically active subjects were more likely to have high or very high or low FFMI. Older subjects had higher body weights and BFMI.

Adipose Tissue↗

PubMed2004

Aging, physical activity and height-normalized body composition parameters.

BACKGROUND & AIM: Regular physical activity prevents or limits weight gain, and gain in body mass index (BMI) and decreases mortality. The aims of the study in healthy adults were to determine the differences in fat-free mass index (FFMI) (kg/m(2)) and body fat mass index (BFMI) between age groups and determine the association between physical activity and FFMI and BFMI. METHODS: Caucasian men (n=3549) and women (n=3184) between 18 and 98 years, were classified as either sedentary or physically active (at least 3h per week at moderate or high-intensity level activity). FFMI and BFMI were measured by 50 kHz bioelectrical impedance analysis. RESULTS: BFMI was significantly higher (P<0.05) in sedentary than physically active subjects and the differences became progressively greater with age. The physically active subjects were significantly less likely to have a low or high FFMI (logistic regression, P<0.001), and a high or very high BFMI (P<0.001), and more likely to have low BFMI (P<0.001) compared to sedentary adults. In contrast with fat-free mass, which was lower in older subjects, the height-normalized FFMI was stable with age until 74 years and lower thereafter. Significantly higher BFMIs were noted in older subjects. CONCLUSION: Physically active subjects are less likely to have low or high FFMI, and high or very high BFMI, and more likely to have low BFMI. In contrast to common claim that fat-free mass decreases with age, we found that FFMI was stable until 74 years. The use of FFMI and BFMI permits comparison of subjects with different heights and age.

Adipose Tissue↗

PubMed2004

Nutritional assessment: lean body mass depletion at hospital admission is associated with an increased length of stay.

BACKGROUND: Low fat-free mass may be an independent risk factor for malnutrition that results in an increased length of hospital stay (LOS). OBJECTIVES: The objectives were to compare differences in fat-free mass and fat mass at hospital admission between patients and healthy control subjects and to determine the association between these differences and the LOS. DESIGN: Patients (525 men, 470 women) were prospectively recruited at hospital admission. Height-corrected fat-free mass and fat mass (fat-free-mass index or fat-mass index; in kg/m2) were determined in patients at admission by bioelectrical impedance analysis and were compared with values for sex-, age-, and height-matched control subjects. Patients were classified as well-nourished, moderately depleted, or severely depleted on the basis of a Subjective Global Assessment questionnaire and a body mass index (in kg/m2) < or > 20. RESULTS: Low fat-free mass was noted in 37% and 55.6% of patients hospitalized 1-2 d and > 12 d, respectively. The odds ratios were significant for fat-free-mass index and were higher in patients with a LOS of > 12 d [men (odds ratio: 5.6; 95% CI: 3.1, 10.4), women (4.4; 2.3, 8.7)] than in those with a LOS of 1-2 d [men (3.3; 2.2, 5.0), women (2.2; 1.6, 3.1)]. Severe nutritional depletion was significantly associated only with a LOS > 12 d. CONCLUSION: Fat-free mass and fat-free-mass index were significantly lower in patients than in control subjects. Because the fat-free-mass index is significantly associated with an increased LOS, provides nutritional assessment information that complements that from a Subjective Global Assessment questionnaire, and is a more sensitive determinant of the association of fat-free mass with LOS than is a weight loss > 10% or a body mass index < 20, it should be used to evaluate nutritional status.

Adipose Tissue↗

PubMed2004

[Simplified malnutrition screening tool: Malnutrition Universal Screening Tool (MUST)].

MUST (Malnutrition Universal Screening Tool) is a nutritional screening tool easy to use by any trained care-giver and valid for any adult patient. It considers body mass index, weight change and acute disease effect equally and determines a malnutrition risk score. If necessary, anthropometric measures may be simpliyfied by alternative methods. MUST is reliable between different healthcare settings et promotes detection and management of malnutrition during the patient medical course.

Acute Disease↗

PubMed2004

[Role of impedance measurement in nutritional screening].

Nutritional status has a prognostic value in the clinical evolution of patients who are malnourished, are becoming malnourished or are in process of being rehabilitated. The evaluation of nutritional status is based on a comprehensive approach, and includes body composition measurement by bio-impedance analysis (BIA). BIA determines the quantity of body fat-free and fat mass and has a precision around 4%. The reliability of BIA depends on the use of body composition prediction equations that are adapted to the subjects studied and on the inclusion of various anthropometric parameters (weight, height, sex, age, race, etc). BIA remains imprecise in the presence of abnormal distribution of body compartments (ascites, dialysis, lipodystrophy) or of extreme weights (cachexia, severe obesity). Multi-frequency or segmental BIA were developed to overcome hydration abnormalities and variations in body geometry. However, these techniques require further validation. This review discusses the indications and limitations of BIA.

Anthropometry↗

PubMed2003

Four-year follow-up of body compostion in lung transplant patients.

BACKGROUND: Both undernutrition and overnutrition can affect the quality of life and survival of patients with pulmonary disease and lead to quantitative and functional alterations of fat-free mass (FFM). This longitudinal study determines the changes in weight, FFM, and body fat before and up to 4 years after lung transplant (LTR). METHODS: Height, weight, and body composition measurements (bioelectrical impedance) were obtained in 37 LTR patients. FFM and body fat were measured before and at 1, 3, 6, 9, 12, 18, 24, 36, and 48 months after LTR. RESULTS: Weight changed by +16.6%, +3.2%, -0.2%, and -3.2% and FFM by +14.0%, +2.5%, -0.3%, and -1.0% during years 1, 2, 3, and 4, respectively. A diagnosis of obliterative bronchiolitis after LTR was associated with loss of body weight, FFM, and body fat, compared with stable weight or gain in weight, FFM, and body fat in obliterative bronchiolitis-negative subjects; 76.2% and 85.7%, and 28% and 38% of men and women, respectively, demonstrated low FFM at 1 month and at 2 years after LTR, respectively. The FFM change was higher (39% of weight) during year 1 than during year 2 (25%) or year 3 (21%). CONCLUSIONS: After LTR, patients gained weight, FFM, and body fat, and two-thirds reached normal levels of FFM by year 2. A weight increase resulted in an FFM increase. Contrary to studies after heart or liver transplantation, our results suggest that despite posttransplant infections and grafts rejection, LTR permits FFM recovery.

Adipose Tissue↗

PubMed2003

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.

Adipose Tissue↗

PubMed2002

Body composition in 995 acutely ill or chronically ill patients at hospital admission: a controlled population study.

OBJECTIVE: 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. SUBJECTS/SETTING: 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 DESIGN: 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. STATISTICAL ANALYSIS: Analysis of variance was used to examine differences between acutely ill and chronically ill patients and controls and between age groups. RESULTS: 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. APPLICATIONS/CONCLUSION: 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.

Acute Disease↗