BACKGROUND & AIMS: Sufficient protein intake is of great importance in hemodialysis (HD) patients, especially for maintaining muscle mass. Daily protein needs are generally estimated using bodyweight (BW), in which individual differences in body composition are not accounted for. As body protein mass is best represented by fat free mass (FFM), there is a rationale to apply FFM instead of BW. The agreement between both estimations is unclear. Therefore, the aim of this study is to compare protein needs based on either FFM or BW in HD patients.METHODS: Protein needs were estimated in 115 HD patients by three different equations; FFM, BW and BW adjusted for low or high BMI. FFM was measured by multi-frequency bioelectrical impedance spectroscopy and considered the reference method. Estimations of FFM x 1.5 g/kg and FFM x 1.9 g/kg were compared with (adjusted)BW x 1.2 and x 1.5, respectively. Differences were assessed with repeated measures ANOVA and Bland-Altman plots.RESULTS: Mean protein needs estimated by (adjusted)BW were higher compared to those based on FFM, across all BMI categories (P < 0.01) and most explicitly in obese patients. In females with BMI >30, protein needs were 69 ± 17.4 g/day higher based on BW and 45 ± 9.3 g/day higher based on BMI adjusted BW, compared to FFM. In males with BMI >30, protein needs were 51 ± 20.4 g/day and 23 ± 20.9 g/day higher compared to FFM, respectively.CONCLUSIONS: Our data show large differences and possible overestimations of protein needs when comparing BW to FFM. We emphasize the importance of more research and discussion on this topic.
Background & aims: Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. Methods: This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. Results: 110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Conclusions: Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. Trial registration: ClinicalTrials.gov (NCT02555670).
OBJECTIVE: To examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases.DESIGN: Prospective cohort study.SETTING AND PARTICIPANTS: The Nurses' Health Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366).MAIN EXPOSURES: Five low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%).MAIN OUTCOME: Life expectancy free of diabetes, cardiovascular diseases, and cancer.RESULTS: The life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50.CONCLUSION: Adherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.
