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•Overall body composition in this cohort of patients with spinal cord injuries did not change significantly after injury and during rehabilitation.•Subgroup analysis revealed body composition changes differed by the level and severity of neurologic injury.•Changes in energy and protein intake post-injury were not associated with changes in body composition. [Display omitted] Spinal cord injury (SCI) is associated with low muscle mass and adiposity, however, to our knowledge, few studies have monitored the trajectory of changes over time. This study aimed to evaluate the timing, rate, magnitude, and site-specific changes in body composition and related changes in diet after SCI. We assessed 39 patients with SCI. The analysis included five women. Of the participants, 51% had American Spinal Injury Association Impairment Scale (AIS) criteria A/B (motor complete) injuries, 18% had AIS C (sensory/motor incomplete) injuries, and 31% had AIS D (motor incomplete) injuries. The mean age of the patients was 43.2 y. They were 48.1 d post-injury and had their weight, diet, and body composition (bioimpedance spectroscopy) assessed every 2 wk. No significant linear changes were observed for any body composition measure. Total body fat mass (FM) changed 0.01 kg/2 wk when fitted to a quadratic model (P = 0.004), decreasing to week 15 and returning to baseline at week 28. Subgroup analysis revealed that arm lean tissue mass (LTM) increased in paraplegic versus tetraplegic participants (0.05 versus –0.01 kg/2 wk, P = 0.007). Participants with AIS A/B injuries lost FM (–0.17 kg; P = 0.010), whereas those with AIS C injuries gained appendicular LTM (ALTM; 0.15 kg; P = 0.017) and leg LTM (0.12 kg; P = 0.008) every 2 wk. Body composition remained stable in the AIS D group. Mean fortnightly changes were greater in the AIS A/B group than the C group for weight (mean difference –0.30 kg; P = 0.021), FM (–0.25 kg; P = 0.002), and leg LTM (–0.11 kg; P = 0.021) and AIS A/B versus D for FM (–0.42 kg; P = 0.013). Baseline energy and protein intakes were 2150 kcal (±741) and 102 g (±40) and decreased by 21.5 kcal (P = 0.016) and 1.3 g (P = 0.004) every 2 wk but were not associated with body composition changes. Neurologic level and severity of SCI, but not changes in diet, were the main determinants of heterogeneous body composition changes.

The study of human body composition covers many fields, from clinical assessment to sports performance. Humans manifest different traits that set limitations in model estimation. This investigation aimed to (i) provide sport-specific densities for reducing biological variation in body composition assessment, and (ii) develop new regression models for body volume and density estimation by field applications. Thirty elite basketball players (16.84 ± 1.15 years; 188.48 ± 6.74 cm; 82.66 ± 12.23 kg) with a mean of 10.48 years of sport experience underwent anthropometric, bio-impedance (BIA) and air-displacement plethysmography (ADP) evaluations. Many models accounting for body fat percentage (BF) used the measured body mass (BM), volume (BV) and density (d) to analyse adipose and fat-free tissues. A new model payable for all players encompassed BF, with low error propagation (3.4% of BM). In addition, two new methods estimated BV by anthropometry (R 2  = 0.96, RMSE = 2.9%) or BIA (R 2  = 0.81, RMSE = 4.56%), with a high degree of precision (97.8 and 86.8%) and accuracy (100 and 99.6%). Body composition requires rigorous speculation, advanced instruments and high costs that could lead investigators to omit relevant concepts and produce estimation biases. Specific and easier methods may enhance its applicability.

In chronic kidney disease it is hypothesised that the association between loss of lean tissue mass (LLTM) and mortality is purely a function of multimorbidity. We conducted a systematic review in CKD patients to quantify the strength of association between LLTM and mortality or frailty surrogates, including hospitalisation and quality of life (QoL). Muscle mass was estimated using different whole-body bioimpedance methods (BI-MM). Searches of electronic databases identified 132 studies for inclusion (147542 dialysis patients; 15378 CKD G3−5 patients; 356 kidney transplant recipients [KTR], with 14429 deaths). From 67 studies reporting unadjusted analyses, 52 (78%) demonstrated associations between LLTM and mortality. In 80 studies reporting analyses adjusting for age, sex, and multimorbidity, 59 (74% overall: 74, 67 and 100% in dialysis, CKD, and KTR studies respectively) reported an association. Meta-analysis of dialysis studies reporting adjusted survival analyses found each degree decrease in phase angle or a lean tissue index < 10th percentile was associated with a 92 and 49% higher hazard of mortality respectively. In studies reporting hospitalisation and QoL measures, 63 and 76% reported associations with BI-MM respectively. In conclusion, having accounted for multimorbidity, LLTM remained associated with mortality and frailty surrogates in CKD, irrespective of the BI-MM method used.

Malnutrition and lean tissue loss are common in dialysis patients and are linked to increased morbidity and mortality. Lean Tissue Index (LTI), a measure of muscle mass adjusted for height, offers an objective assessment of nutritional status. However, its relationship with conventional nutritional markers remains poorly defined. We conducted a retrospective analysis of 365 adult dialysis patients from multiple centers. Baseline data included anthropometrics, body composition (LTI), and nutritional biomarkers: albumin, prealbumin, Geriatric Nutritional Risk Index (GNRI), normalized protein catabolic rate, phosphate, and potassium. Correlation analysis (Pearson/Spearman), multivariate linear regression, and comparative analysis based on LTI classification (LTI2: low vs. high) were performed to evaluate the associations between LTI and nutritional parameters. Mean age was 70.2 ± 13.3 y; 64.9% were male. The mean LTI was 12.29 ± 3.32 kg/m². LTI showed strong positive correlation with weight (r = 0.85) and moderate associations with albumin (r = 0.50) and GNRI (r = 0.55). Multivariate analysis revealed weight (β = 0.144, P < 0.001), serum albumin (β = 0.241, P = 0.001), prealbumin (β = 0.046, P = 0.015), and potassium (β = 0.800, P < 0.001) levels as independent predictors of LTI. GNRI was inversely associated with LTI (β = −0.170, P < 0.001). Patients in the high-LTI group had significantly higher weight, albumin, prealbumin, and GNRI (all P < 0.05), but no significant differences in normalized protein catabolic rate, phosphate, or potassium. LTI is strongly associated with conventional nutritional markers, particularly body weight and serum proteins. While GNRI correlates with LTI, it may reflect broader nutritional reserves rather than lean mass specifically. These findings underscore the importance of integrating body composition measurements into routine nutritional assessment in dialysis care. •Lean tissue index (LTI) correlates strongly with body weight and serum albumin.•GNRI showed an unexpected inverse association with LTI in adjusted analysis.•Prealbumin, albumin, and weight are independent predictors of lean mass.•Nutritional markers like nPCR and phosphate had limited value in predicting LTI.•Body composition analysis adds value to routine nutrition assessment in dialysis.

Controversy exists about the maximum amount of protein that can be utilized for lean tissue-building purposes in a single meal for those involved in regimented resistance training. It has been proposed that muscle protein synthesis is maximized in young adults with an intake of ~ 20–25 g of a high-quality protein; anything above this amount is believed to be oxidized for energy or transaminated to form urea and other organic acids. However, these findings are specific to the provision of fast-digesting proteins without the addition of other macronutrients. Consumption of slower-acting protein sources, particularly when consumed in combination with other macronutrients, would delay absorption and thus conceivably enhance the utilization of the constituent amino acids. The purpose of this paper was twofold: 1) to objectively review the literature in an effort to determine an upper anabolic threshold for per-meal protein intake; 2) draw relevant conclusions based on the current data so as to elucidate guidelines for per-meal daily protein distribution to optimize lean tissue accretion. Both acute and long-term studies on the topic were evaluated and their findings placed into context with respect to per-meal utilization of protein and the associated implications to distribution of protein feedings across the course of a day. The preponderance of data indicate that while consumption of higher protein doses (> 20 g) results in greater AA oxidation, this is not the fate for all the additional ingested AAs as some are utilized for tissue-building purposes. Based on the current evidence, we conclude that to maximize anabolism one should consume protein at a target intake of 0.4 g/kg/meal across a minimum of four meals in order to reach a minimum of 1.6 g/kg/day. Using the upper daily intake of 2.2 g/kg/day reported in the literature spread out over the same four meals would necessitate a maximum of 0.55 g/kg/meal.

With expanding kidney transplantation programs, remaining hemodialysis patients are more likely to have a high comorbidity burden and may therefore be more prone to lose muscle mass. Our aim was to analyze risk factors for muscle loss in hemodialysis patients with high comorbidity. Fifty-four chronic hemodialysis patients (Charlson Comorbidity Index 9.0 ± 3.4) were followed for 20 weeks using 4-weekly measurements of lean tissue mass, intracellular water, and body cell mass (proxies for muscle mass), handgrip strength (HGS), and biochemical parameters. Mixed models were used to analyze covariate effects on LTM. LTM (−6.4 kg, interquartile range [IQR] −8.1 to −4.8), HGS (−1.9 kg, IQR −3.1 to −0.7), intracellular water (−2.11 L, IQR −2.9 to −1.4) and body cell mass (−4.30 kg, IQR −5.9 to −2.9) decreased in all patients. Conversely, adipose tissue mass increased (4.5 kg, IQR 2.7 to 6.2), resulting in no significant change in body weight (−0.5 kg, IQR −1.0 to 0.1). Independent risk factors for LTM loss over time were male sex (−0.26 kg/week, 95% CI −0.33 to −0.19), C-reactive protein above median (−0.1 kg/week, 95% CI −0.2 to −0.001), and baseline lean tissue index ≥10th percentile (−1.6 kg/week, 95% CI −2.1 to −1.0). Age, dialysis vintage, serum albumin, comorbidity index, and diabetes did not significantly affect LTM loss over time. In this cohort with high comorbidity, we found universal and prominent muscle loss, which was further accelerated by male sex and inflammation. Stable body weight may mask muscle loss because of concurrent fat gain. Our data emphasize the need to assess body composition in all hemodialysis patients and call for studies to analyze whether intervention with nutrition or exercise may curtail muscle loss in the most vulnerable hemodialysis patients.

Background/purposeMetabolic associated fatty liver disease (MAFLD) is the commonest cause of chronic liver disease, which is associated with obesity and diabetes. However, it also occurs in lean individuals especially in Asian populations.MethodsThe participants of Tzu Chi MAFLD cohort (TCMC) including health controls or MAFLD patients were enrolled. MAFLD was defined as fatty liver in imaging without hepatitis B virus, hepatitis C virus infection, drug, alcohol or other known causes of chronic liver disease. Lean MAFLD was defined as MAFLD in lean subjects (BMI < 23 kg/m2). ResultsA total of 880 subjects were included for final analysis. Of 394 MAFLD patients, 65 (16.5%) patients were diagnosed as lean MAFLD. Lean MAFLD patients were elder, higher percentage of female gender, lower ALT, diastolic blood pressure, triglyceride, and waist circumference but higher HDL than non-lean MAFLD patients. Using binary regression analysis, elder age and lower waist circumference were associated with lean MAFLD. Compared with lean healthy controls, lean MAFLD patients had higher BMI, waist circumference, and percentage of hypertension. In body composition, fatty tissue index (FTI), lean tissue index (LTI) ,and total body water (TBW) were lower in lean MAFLD than non-lean MAFLD patients; but they were comparable with lean healthy controls.ConclusionsThe prevalence of lean MAFLD was 16.5% in this study population and it was higher in elder age, especially of female subjects. Lean MAFLD patients had different metabolic profiles compared with lean healthy controls, but different body composition compared with non-lean MAFLD patients.

Objectives Low back pain is the largest contributor to disability worldwide. The role of body composition as a risk factor for back pain remains unclear. Our aim was to examine the relationship between fat mass and fat distribution on back pain intensity and disability using validated tools over 3 years. Methods Participants (aged 25–60 years) were assessed at baseline using dual-energy X-ray absorptiometry (DXA) to measure body composition. All participants completed the Chronic Pain Grade Scale at baseline and 3-year follow-up. Of the 150 participants, 123 (82%) completed the follow-up. Results Higher baseline body mass index (BMI) and fat mass (total, trunk, upper limb, lower limb, android, and gynoid) were all associated with high intensity back pain at either baseline and/or follow-up (total fat mass: multivariable OR 1.05, 95% CI 1.01–1.09, p  < 0.001). There were similar findings for all fat mass measures and high levels of back disability. A higher android to gynoid ratio was associated with high intensity back pain (multivariable OR 1.04, 95% CI 1.01–1.08, p  = 0.009). There were no associations between lean mass and back pain. Conclusions This cohort study provides evidence for the important role of fat mass, specifically android fat relative to gynoid fat, on back pain and disability.

Purpose Athletes cycle between exercise and recovery. Exercise invokes changes in total body water from thermal sweating, muscle and hepatic glycogen depletion and metabolic water loss. Recovery from exercise results in rehydration, substrate repletion, and possible glycogen supercompensation. Such changes may corrupt the measurement of hydrated tissues, such as lean tissue mass (LTM), by dual-energy X-ray absorptiometry (DXA). The purpose of this study was to determine the effect of exercise and thermal dehydration and subsequent glycogen supercompensation on DXA-based measurement of body composition. Methods Twelve active adult (18–29 years) males exercised at 70% V O 2max on a cycle ergometer in a thermal environment (30 °C) to induce a 2.5% reduction in body mass. Participants subsequently underwent a glycogen supercompensation phase, whereby a high carbohydrate diet (8–12 g/kg body mass/day) was consumed for a 48-h period. Whole-body DXA measurement was performed at baseline, following exercise and supercompensation. Results Following exercise, mean body mass decreased by −1.93 kg (95% CI −2.3, −1.5), while total LTM decreased by −1.69 kg (−2.4, −1.0). Supercompensation induced a mean body mass increase of 2.53 kg (2.0, 3.1) and a total LTM increase of 2.36 kg (1.8, 2.9). No change in total fat mass or bone mineral content was observed at any timepoint. Conclusions Training regimens that typically induce dehydration and nutrition regimens that involve carbohydrate loading can result in apparent changes to LTM measurement by DXA. Accurate measurement of LTM in athletes requires strict observation of hydration and glycogen status to prevent manipulation of results.

Muscle wasting is common and is associated with increased morbidity and mortality in patients with chronic kidney disease (CKD). However, factors associated with decreased muscle mass in CKD patients are seldom reported. We performed a cross-sectional study of 326 patients (age 65.8 ± 13.3 years) with stage 3–5 CKD who were not yet on dialysis. Muscle mass was determined using the Body Composition Monitor (BCM), a multifrequency bioimpedance spectroscopy device, and was expressed as the lean tissue index (LTI, lean tissue mass/height2). An LTI of less than 10% of the normal value (low LTI) indicates muscle wasting. Patients with low LTI (n = 40) tended to be diabetic, had significantly higher fat tissue index, urine protein creatinine ratio, and interleukin-6 and tumor necrosis factor-α levels, but had significantly lower serum albumin and hemoglobin levels compared with those with normal LTI. In multivariate linear regression analysis, age, sex, cardiovascular disease, and interleukin-6 were independently associated with LTI. Additionally, diabetes mellitus remained an independent predictor of muscle wasting according to low LTI by multivariate logistic regression analysis. We conclude that LTI has important clinical correlations. Determination of LTI may aid in clinical assessment by helping to identify muscle wasting among patients with stage 3–5 CKD.