Muscle depletion and sarcopenic obesity are related to a higher morbimortality risk in chronic kidney disease (CKD). We evaluated bed-side measures/indexes associated with low muscle mass, sarcopenia, obesity, and sarcopenic obesity in CKD and proposed cutoffs for each parameter. Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People revised consensus applying dual energy X-ray absorptiometry (DXA) and hand grip strength (HGS), and obesity according to the International Society for Clinical Densitometry. Anthropometric parameters including calf (CC) and waist (WC) circumferences and WC/height (WC/H); bioelectrical impedance data including appendicular fat free mass (AFFM) and fat mass index (FMI) were assessed. ROC analysis and area under the curve (AUC) were applied for performance analyses. AFFM and CC presented the best performances for low muscle mass diagnosis–AFFM AUC for women was 0.96 and for men, 0.94, and CC AUC for women was 0.89 and for men, 0.85. FMI and WC/H were the best parameters for obesity diagnosis–FMI AUC for women was 0.99 and for men, 0.96, and WC/H AUC for women was 0.94 and for men, 0.95. The cutoffs (sensibility and specificity, respectively) for women were AFFM≤15.87 (90%; 96%), CC≤35.5 (76%; 94%), FMI>12.58 (100%; 93%), and WC/H>0.66 (91%; 84%); and for men, AFFM≤21.43 (98%; 84%), CC≤37 (88%; 69%), FMI>8.82 (93%; 88%), and WC/H>0.60 (95%; 80%). Sensibility and specificity for sarcopenia diagnosis were for AFFM+HGS in women 85% and 99% and in men, 100% and 99%; for CC+HGS in women 85% and 99% and in men, 100% and 100%; and for sarcopenic obesity were for FMI+AFFM in women 75% and 97% and in men, 75% and 95%. The tested bed-side measures/indexes presented excellent performance.

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Obesity and muscle impairment (low muscle mass or strength) are present in chronic kidney disease (CKD) and associated to worse prognosis. However, the various existing definitions for these conditions make the diagnosis variable. The aim of the study was to evaluate the agreement between diagnostic criteria for sarcopenic obesity and its components in CKD. Two hundred and sixty seven patients with CKD were included in the study. We assessed body composition by dual energy X-ray absorptiometry (DXA) and muscle function by handgrip strength (HGS); adiposity by BMI, waist circumference (WC), fat mass index (FMI), and percentage of fat mass (%FM). Diagnosis of muscle impairment was made by HGS, appendicular lean mass (ALM) and index (ALMI); obesity by BMI, WC, FMI and %FM, and sarcopenic obesity was diagnosed by concomitant presence of muscle impairment and obesity. Prevalence of muscle impairment varied from 11 to 50%, higher when low muscle mass criteria was used. Prevalence of obesity varied from 26 to 62%, higher when WC and %FM criteria was used. Prevalence of sarcopenic obesity varied from 2 to 23%. Women were more affected by sarcopenic obesity. Muscle impairment and sarcopenic obesity were more prevalent among patients on hemodialysis and obesity among non-dialysis-dependent and kidney transplant patients. The agreement was poor between muscle mass and strength criteria; substantial between FMI, BMI, and %FM and only fair between WC and the others measures; for sarcopenic obesity, varied from poor to almost perfect. Significant differences were found among the various diagnostic criteria that are used in the diagnosis of sarcopenic obesity.

Overweight, obese and chronic kidney disease patients have an altered and negative body composition being its assessment important. Bioelectrical impedance analysis is an easy-to-operate and low-cost method for this purpose. This study aimed to compare and correlate data from single- and multi-frequency bioelectrical impedance spectroscopy applied in subjects with different body sizes, adiposity, and hydration status. It was a cross-sectional study with 386 non-chronic kidney disease volunteers (body mass index from 17 to 40 kg/m2), 30 patients in peritoneal dialysis, and 95 in hemodialysis. Bioelectrical impedance, body composition, and body water data were assessed with single- and multi-frequency bioelectrical impedance spectroscopy. Differences (95% confidence interval) and agreements (Bland-Atman analyze) between devices were evaluated. The intraclass correlation coefficient was used to measure the strength of agreement and Pearson’s correlation to measure the association. Regression analyze was performed to test the association between device difference with body mass index and overhydration. The limits of agreement between devices were very large. Fat mass showed the greatest difference and the lowest intraclass and Pearson’s correlation coefficients. Pearson’s correlation varied from moderate to strong and the intraclass correlation coefficient from weak to substantial. The difference between devices were greater as body mass index increased and was worse in the extremes of water imbalance. In conclusion, data obtained with single- and multi-frequency bioelectrical impedance spectroscopy were highly correlated with poor agreement; the devices cannot be used interchangeably and the agreement between the devices was worse as body mass index and fat mass increased and in the extremes of overhydration.

Objective: The aim of this study was to evaluate the relationship of total physical activity (PA) and its different domains with sex, weight, body mass index, body composition, and resting energy expenditure (REE) among Brazilian adults. The secondary aim was to assess if the Baecke Habitual Physical Activity Questionnaire (BHPAQ) could be used to screen fat mass excess. Methods: Three hundred and sixty-six volunteers participated. PA was assessed with the BHPAQ, body composition with multifrequency bioelectrical impedance spectroscopy, and REE with indirect calorimetry. Results: Total PA and sports/exercise PA were lower in women than men. The participants most active for sports/exercise and leisure-time/locomotion PA domains had higher fat free mass and phase angle, and lower fat mass and weight than the least active subjects. The occupational PA domain was associated with higher fat mass and weight. REE was associated only with the exercise/sports PA domain. The BHPAQ could discriminate subjects with excess body fat with a 9.375 cutoff point for total PA. Conclusion: Exercise/sports and leisure-time/locomotion are PA domains associated with a better body composition. A gender gap still exists in PA, as women are less active than men. The BHPAQ could screen subjects with excess fat mass.