Véronique L. Karsegard

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

Comparison of Four Bioelectrical Impedance Analysis Formulas in Healthy Elderly Subjects

Background: 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. Objective: 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 (FFMDXA), in healthy elderly subjects. Methods: 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). FFMBIA was calculated by the published formulas of Deurenberg, Baumgartner, Roubenoff and Kyle and compared to FFMDXA by a Bland-Altman analysis. Results: 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 FFMBIA (Kyle) relative to FFMDXA were –3.3 and +3.3 kg for women and –3.8 and +4.3 kg for men. Conclusion: 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/m2. The other BIA formulas developed especially for the elderly are not valid in this population.

A randomized double-blind controlled study of 6 months of oral nutritional supplementation with arginine and Ω-3 fatty acids in Hiv-infected patients

OBJECTIVE To evaluate the effects of an oral nutritional supplement enriched with two potentially immunostimulant compounds (arginine and omega-3 fatty acids) on the changes in food intake, body composition, immune parameters and viraemia in HIV-infected outpatients. DESIGN Six-month prospective randomized double-blind controlled study. SETTING University hospital outpatient nutrition clinic. PATIENTS Sixty-four HIV-infected outpatients with CD4 lymphocyte count > or = 10O x 10(6)/l. INTERVENTION All patients received a daily oral nutritional supplement (606 kcal supplemented with vitamins, trace elements and minerals). In addition, half of the patients were randomized to receive 7.4 g arginine plus 1.7 g omega-3 fatty acids. MAIN OUTCOME MEASURES Disease progression measured by AIDS-defining events, CD4 and CD8 lymphocyte counts, viraemia, tumour necrosis factor soluble receptors, nutritional status determined by anthropometric, bioelectrical impedance and dietetic assessment. RESULTS Fifty-five patients completed the protocol. Compliance with and tolerance of oral nutritional supplement during the 6-month period was excellent. In both groups of patients the following were found: total energy intake was transiently increased and then returned to baseline level; nitrogen/energy intake ratio was increased throughout the study; gain of body weight and fat mass were approximately 2 and 1kg, respectively, over 6 months, and were similar in both groups. In addition, CD4 and CD8 lymphocyte counts, viraemia, tumour necrosis factor soluble receptors remained statistically unchanged and were similar in both groups. CONCLUSIONS Enrichment of an oral nutritive supplement with arginine and omega-3 fatty acids did not improve immunological parameters. However, body weight increased in both groups.

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.

Low fat-free mass as a marker of mortality in community-dwelling healthy elderly subjects

BACKGROUND low fat-free mass has been related to high mortality in patients. This study evaluated the relationship between body composition of healthy elderly subjects and mortality. METHODS in 1999, 203 older subjects underwent measurements of body composition by bioelectrical impedance analysis, Charlson co-morbidity index and estimation of energy expenditure through physical activity by a validated questionnaire. These measurements were repeated in 2002, 2005 and 2008 in all consenting subjects. Mortality data between 1999 and 2010 were retrieved from the local death registers. The relationship between mortality and the last indexes of fat and fat-free masses was analysed by multiple Cox regression models. RESULTS womens and mens data at last follow-up were: age 81.1 ± 5.9 and 80.9 ± 5.8 years, body mass index 25.3 ± 4.6 and 26.1 ± 3.4 kg/m(2), fat-free mass index 16.4 ± 1.8 and 19.3 ± 1.9 kg/m(2) and fat mass index 9.0 ± 3.2 and 6.8 ± 2.0 kg/m(2). Fifty-eight subjects died between 1999 and 2010. The fat-free mass index (hazard ratio 0.77; 95% confidence interval 0.63-0.95) but not the fat mass index, predicted mortality in addition to sex and Charlson index. The multiple Cox regression model explained 31% of the variance of mortality. CONCLUSION a low fat-free mass index is an independent risk factor of mortality in elderly subjects, healthy at the time of body composition measurement.

Body composition and all-cause mortality in subjects older than 65 y

BACKGROUND A low or high body mass index (BMI) has been associated with increased mortality risk in older subjects without taking fat mass index (FMI) and fat-free mass index (FFMI) into account. This information is essential because FMI is modulated through different healthcare strategies than is FFMI. OBJECTIVE We aimed to determine the relation between body composition and mortality in older subjects. DESIGN We included all adults ≥65 y old who were living in Switzerland and had a body-composition measurement by bioelectrical impedance analysis at the Geneva University Hospitals between 1990 and 2011. FMI and FFMI were divided into sex-specific quartiles. Quartile 1 (i.e., the reference category) corresponded to the lowest FMI or FFMI quartile. Mortality data were retrieved from the hospital database, the Geneva death register, and the Swiss National Cohort until December 2012. Comorbidities were assessed by using the Cumulative Illness Rating Scale. RESULTS Of 3181 subjects included, 766 women and 1007 men died at a mean age of 82.8 and 78.5 y, respectively. Sex-specific Cox regression models, which were used to adjust for age, BMI, smoking, ambulatory or hospitalized state, and calendar time, showed that body composition did not predict mortality in women irrespective of whether comorbidities were taken into account. In men, risk of mortality was lower with FFMI in quartiles 3 and 4 [HR: 0.78 (95% CI: 0.62, 0.98) and 0.64 (95% CI: 0.49, 0.85), respectively] but was not affected by FMI. When comorbidities were adjusted for, FFMI in quartile 4 (>19.5 kg/m(2)) still predicted a lower risk of mortality (HR: 0.72; 95% CI: 0.54, 0.96). CONCLUSIONS Low FFMI is a stronger predictor of mortality than is BMI in older men but not older women. FMI had no impact on mortality. These results suggest potential benefits of preventive interventions with the aim of maintaining muscle mass in older men. This trial was registered at clinicaltrials.gov as NCT01472679.

Bioimpedance-Derived Phase Angle and Mortality Among Older People.

BACKGROUND Phase angle measured by bioelectrical impedance analysis (BIA) may be a marker of health state. OBJECTIVE This historical cohort study of prospectively collected BIA measurements aims to investigate the link between phase angle and mortality in older people and evaluate whether a phase angle cutoff can be defined. DESIGN We included all adults aged ≥65 years who underwent a BIA measurement by the Nutriguard® device at the Geneva University Hospitals. We retrieved retrospectively the phase angle and comorbidities at the last BIA measurement and mortality until December 2012. We calculated phase angle standardized for sex, age, and body mass index (BMI), using reference values determined with the same brand of BIA device. Sex-specific and standardized phase angle were categorized into quartiles. The association of mortality with sex-specific or standardized phase angle was evaluated through univariate and multivariate Cox regression models, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. RESULTS We included 1307 (38% women) participants, among whom 628 (44% women) died. In a multivariate Cox regression model adjusted for comorbidities and setting of measurement (ambulatory vs. hospitalized), the protective effect against mortality increased progressively as the standardized phase angle quartile increased (HR 0.71 [95% CI 0.58, 0.86], 0.53 [95% CI 0.42, 0.67], and 0.32 [95% CI 0.23, 0.43]). The discriminative value of continuous standardized phase angle, assessed as the area under the ROC curve, was 0.72 (95%CI 0.70, 0.75). We could not define an acceptable phase angle cutoff for individual prediction of mortality (LK), based on sensibility and specificity values. CONCLUSIONS This study shows the association of phase angle and mortality in older patients, independent of age, sex, comorbidities, BMI categories, and setting of measurement.

Running performance in a timed city run and body composition: a cross-sectional study in over 3000 runners

OBJECTIVE The importance of body composition for running performance is unclear in the general population. The aim of this study was to evaluate whether body composition influences running speed and whether it is a better predictor of running speed than body mass index (BMI). METHODS The study included 1353 women (38.2 ± 12.1 y of age) and 1771 men (39.6 ± 12.1 y of age) who underwent, for the first time, a measurement of body composition by bioelectrical impedance analysis between 1999 and 2016, before a timed run occurring annually in Geneva. The running distances and times were converted to average speed (km/h). Body composition was expressed as sex-specific quartiles, where quartile 1 (lowest values) was the reference quartile. The relationships between speed and BMI or body composition were analyzed by multivariate linear regressions. RESULTS Multivariate regressions showed that the higher the fat mass index (FMI) quartile, the lower the running speed in women and men (all P < 0.001). In men, a fat-free mass index (FFMI) in quartile 4 (>20 kg/m2) was associated with a poor running performance (r = -0.50, P < 0.001), whereas in women, an FFMI in quartile 2 or 3 (15-16.4 kg/m2) was associated with a higher running speed (r = 0.23, P = 0.04; r = 0.28, P = 0.01, respectively). Body composition predicted speed better than BMI in women (R2 = 26.8% versus 14.4%) and men (R2 = 29.8% versus 25.4%). CONCLUSIONS Running speed is negatively associated with BMI and FMI in both sexes. Body composition is a better predictor of running performance than BMI.