Summary
Physical activity and body composition show a typical pattern over the lifecycle. Fat‐free mass and physical performance generally peak in early adulthood. Here, evidence for a relation ...between physical activity changes over the life span and the development of sarcopenic obesity is presented. Activity‐induced energy expenditure increases with body size and physical activity during growth. The physical activity level, calculated by expressing total energy expenditure as a multiple of resting energy expenditure, gradually increases from early age to adulthood to decrease again in old age. Habitual physical activity has a significant effect on growth of fat‐free mass during adolescence and thus on peak fat‐free mass and physical performance in early adulthood. Older subjects have a lower fat‐free mass and lower physical activity levels but there is no association, suggesting physical activity does not protect against loss of lean body mass at higher age. Prevention of sarcopenic obesity starts with a physically active lifestyle to develop a healthy peak fat‐free mass and subsequent prevention of excess fat gain. The change from a physically active to a more sedentary routine in later life requires restriction of energy intake to maintain energy balance.
Summary
Postbariatric loss of muscle tissue could negatively affect long‐term health due to its role in various bodily processes, such as metabolism and functional capacity. This meta‐analysis aimed ...to unravel time‐dependent changes in the magnitude and progress of lean body mass (LBM), fat‐free mass (FFM), and skeletal muscle mass (SMM) loss following bariatric surgery. A systematic literature search was conducted in Pubmed, Embase, and Web of Science. Fifty‐nine studies assessed LBM (n = 37), FFM (n = 20), or SMM (n = 3) preoperatively and ≥1 time points postsurgery. Random‐effects meta‐analyses were performed to determine pooled loss per outcome parameter and follow‐up time point. At 12‐month postsurgery, pooled LBM loss was −8.13 kg 95%CI −9.01; −7.26. FFM loss and SMM loss were −8.23 kg 95%CI −10.74; −5.73 and −3.18 kg 95%CI −5.64; −0.71, respectively. About 55% of 12‐month LBM loss occurred within 3‐month postsurgery, followed by a more gradual decrease up to 12 months. Similar patterns were seen for FFM and SMM. In conclusion, >8 kg of LBM and FFM loss was observed within 1‐year postsurgery. LBM, FFM, and SMM were predominantly lost within 3‐month postsurgery, highlighting that interventions to mitigate such losses should be implemented perioperatively.
The Global Leadership Initiative on Malnutrition (GLIM) has suggested a process for the diagnosis of malnutrition. The process consists of applying an existing screening tool for malnutrition ...screening, followed by malnutrition diagnostics, and finally categorization of malnutrition severity (moderate or severe) according to specific GLIM criteria. However, it is not known how well the GLIM process agrees with other diagnostic tools used in the current clinical practice. The aim of this study was to validate the GLIM process against the Patient Generated-Subjective Global Assessment (PG-SGA) when different screening tools were applied in the screening step of the GLIM process.
Colorectal cancer (CRC) patients from the ongoing CRC-NORDIET study were included. For the GLIM process, the patients were first screened for malnutrition using either 1) Nutritional risk screening, first 4 questions (NRS-2002-4Q), 2) Malnutrition Screening Tool (MST), 3) Malnutrition Universal Screening Tool (MUST) or 4) the PG-SGA short form (PG-SGA-SF). The GLIM malnutrition diagnosis was then based on combining the result from each of the screening methods with the etiological and phenotypic GLIM-criteria including weight loss, BMI and fat free mass. In parallel, the patients were diagnosed using the PG-SGA methodology categorizing the patients into either A: well nourished, B: moderately malnourished or C: severely malnourished. The four different GLIM based diagnoses were then validated against the diagnosis obtained by the PG-SGA tool. Sensitivity, specificity and positive predictive value (PPV) were calculated to evaluate validity.
In total, 426 patients were included (mean age: 66, ±8 years) at a mean time of 166 (±56) days after surgery. The GLIM diagnosis based on the four different screening tools identified 10–24% of the patients to be malnourished, of which 3–8% were severely malnourished. The PG-SGA method categorized 15% as moderately malnourished (PG-SGA: category B) and no patients as severely malnourished (PG-SGA: category C). The agreement between the PG-SGA and GLIM process was in general low, but differed according to the tools: PG-SGA SF (sensitivity 47%, PPV 71%), MST (sensitivity 56%, PPV 47%), NRS-2002-4Q (sensitivity 63%, PPV 53%) and MUST (sensitivity 53%, PPV 34%).
In this cross-sectional study of patients with CRC, the concordance between the GLIM-criteria and PG-SGA depended on the screening tool used in the GLIM process. Malnutrition frequency based on the GLIM process schould be reported with and without the use of a screening tool.
This study investigated the effects of a relatively high‐ versus moderate‐volume resistance training program on changes in lean mass during caloric restriction. Thirty‐eight resistance‐trained males ...were randomized to perform either a high‐volume (HVG; 5 sets/exercise) or a moderate‐volume (MVG; 3 sets/exercise) resistance training program. Both groups were supervised during lower body training. Participants consumed 30 kcal/kg for 6 weeks after 1 week of weight maintenance (45 kcal/kg), with protein intake fixed at 2.8 g/kg fat‐free mass. Muscle thickness of the m. rectus femoris, body composition, contractile properties, stiffness, mood, and sleep status were assessed at pre‐, mid‐, and post‐study. No significant group × time interaction was observed for muscle thickness of the m. rectus femoris at 50% (∆ post‐pre 0.36 ± 0.93 mm vs. ∆ −0.01 ± 1.59 mm; p = 0.226) and 75% length (∆ −0.32 ± 1.12 mm vs. ∆ 0.08 ± 1.14 mm; p = 0.151), contractility, sleep, and mood in the HVG and MVG, respectively. Body mass (HVG: ∆ −1.69 ± 1.12 kg vs. MVG: ∆ −1.76 ± 1.76 kg) and lean mass (∆ −0.51 ± 2.30 kg vs. ∆ −0.92 ± 1.59 kg) decreased significantly in both groups (p = 0.022), with no between‐group difference detected (p = 0.966). High‐volume resistance training appears to have neither an advantage nor disadvantage over moderate‐volume resistance training in terms of maintaining lean mass or muscle thickness. Given that both groups increased volume load and maintained muscle contractility, sleep quality, and mood, either moderate or higher training volumes conceivably can be employed by resistance‐trained individuals to preserve muscle during periods of moderate caloric restriction.
Background
Understanding how blood alcohol concentrations (BAC) achieved after drinking are determined is critical to predicting alcohol exposure to the brain and other organs and alcohol's effects. ...However, predicting end‐organ exposures is challenging, as there is wide variation in BAC achieved after drinking a specified volume of alcohol. This variation is partly due to differences in body composition and alcohol elimination rates (AER), but there are limited data on how obesity affects AER. Here, we assess associations between obesity, fat‐free mass (FFM), and AER in women and examine whether bariatric surgeries, which are linked to an increased risk of alcohol misuse, affect these associations.
Methods
We analyzed data from three studies that used similar intravenous alcohol clamping procedures to estimate AER in 143 women (21 to 64 years old) with a wide range of body mass index (BMI; 18.5 to 48.4 kg/m2). Body composition was measured in a subgroup using dual‐energy X‐ray absorptiometry (n = 42) or Bioimpedance (n = 60), and 19 of the women underwent bariatric surgery 2.1 ± 0.3 years before participation. We analyzed data using multiple linear regression analyses.
Results
Obesity and older age were associated with a faster AER (BMI: rs = 0.70 and age: rs = 0.61, both p < 0.001). Compared to women with normal weight, AER was 52% faster (95% Confidence Interval: 42% to 61%) in women with obesity. However, BMI lost predictive value when adding fat‐free mass (FFM) to the regression model. Age, FFM, and its interaction explained 72% of individual variance in AER (F (4, 97) = 64.3, p < 0.001). AER was faster in women with higher FFM, particularly women in the top tertile of age. After controlling for FFM and age, bariatric surgery was not associated with differences in AER (p = 0.74).
Conclusions
Obesity is associated with a faster AER, but this association is mediated by an obesity‐related increase in FFM, particularly in older women. Previous findings of a reduced alcohol clearance following bariatric surgery compared with prior to surgery are likely explained by a reduction in FFM post‐surgery.
Using the intravenous alcohol clamp method to estimate alcohol elimination rates (AER) in 143 women, we show here that obesity was associated with 52% faster AER. However, this association depended on an obesity‐related increase in fat‐free mass (FFM), a good predictor of lean liver volume. Age and FFM explained 72% of individual variations in AER. Bariatric surgeries, which remarkably increase the bioavailability of ingested alcohol and the risk for alcohol misuse, were not associated with differences in AER.
Reliable and valid body composition assessment is important in both clinical and research settings. A multitude of methods and techniques for body composition measurement exist, all with inherent ...problems, whether in measurement methodology or in the assumptions upon which they are based. This review is focused on currently applied methods for in vivo measurement of body composition, including densitometry, bioimpedance analysis, dual-energy X-ray absorptiometry, computed tomography (CT), magnetic resonance techniques and anthropometry. Multicompartment models including quantification of trace elements by in vivo neutron activation analysis, which are regarded as gold standard methods, are also summarized. The choice of a specific method or combination of methods for a particular study depends on various considerations including accuracy, precision, subject acceptability, convenience, cost and radiation exposure. The relative advantages and disadvantages of each method are discussed with these considerations in mind.
Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN ...displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex‐specific GWAS in a healthy and medication‐free subsample of the UK Biobank (n = 155,961), identifying 77 genome‐wide significant loci associated with body fat percentage (BF%) and 174 with fat‐free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue‐associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p < .0001, δ = −0.17), suggesting that the female preponderance in AN may, in part, be explained by sex‐specific anthropometric and metabolic genetic factors increasing liability to AN.
The total preparation for a bodybuilding competition basically involves two phases, the preparation phase, and the pre-competition phase, in which both tend to add up on average 32 weeks. During the ...pre-contest phase, bodybuilding athletes maintain a negative energy balance both by lower energy intake from the diet and by the longer time dedicated to training, to try reducing the body fat percentage, fat-free mass (FFM) maintenance and to present a dense and dry physique on stage in the competition day. Therefore, this work tries to bring a correlation explanation between a greater caloric deficit applied to the bodybuilding athlete during his preparation with the variation in fat free mass between the preparation and pre-contest phases. This way, open the question: “could greater caloric deficits in the bodybuilding athlete's dietary intake be closely correlated with negative changes in fat-free mass for stage performance?”
The author searched PubMed and ScienceDirect databases for recent studies involving the food consumption of bodybuilders when preparing for competition using the keywords “bodybuilding”, “diet” and “preparation”. 16 results were obtained from ScienceDirect and 8 from PubMed. Two cross-sectional studies and two case studies involved the evaluation of the food consumption of forty-four male athletes practicing bodybuilding over eighteen years of age during their preparation that lasted from 5 to 32 weeks. Participants' diet was monitored by self-report. The studies were selected and observationally evaluated by the author regarding the size of the variation in the energy intake and its possible correlation with the variation in the fat-free mass from the beginning of the preparation until the day of the competition.
Of the four studies, the greatest average variation in energy intake (final minus initial) exceeded 1700 kcal and the smallest did not reach even 300 kcal. On the other hand, the study with the longest preparation time had the greatest loss of body weight even without applying the greatest energy variation between the studies in table 1 yet had the greatest fat-free mass loss with a worse result than the study with the shortest preparation time.
Observationally, higher caloric deficits in the bodybuilding athlete's food intake cannot closely correlated with negative changes in fat-free mass for the stage presentation.
Background and purpose
To establish the utility of venous creatinine as a biomarker to monitor loss of fat‐free mass in patients with amyotrophic lateral sclerosis (ALS).
Methods
In this multicenter ...natural history study, body composition and venous creatinine were assessed in 107 patients with ALS and 52 healthy controls. Longitudinal patterns of venous creatinine and its association with the risk of death during follow‐up were determined in a cohort of patients with ALS from Australia (n = 69) and the Netherlands (n = 38).
Results
The mean levels of venous creatinine were 75.78 ± 11.15 μmol/L for controls, 70.25 ± 12.81 μmol/L for Australian patients, and 59.95 ± 14.62 μmol/L for Dutch patients with ALS. The relationship between measures of venous creatinine and fat‐free mass was similar between all groups (r = 0.36, p < 0.001). Within patients, fat‐free mass declined by 0.31 (95% confidence interval CI: 0.22–0.40) kg/month, and venous creatinine declined by 0.52 (95% CI: 0.38–0.66) μmol/L/month, with a longitudinal correlation of 0.57 (95% CI: 0.35–0.76, p < 0.001). Lower levels of venous creatinine were associated with increased risk for earlier death in patients with ALS (hazard ratio = 0.94, 95% CI: 0.90–0.98, p = 0.007).
Conclusions
Venous creatinine is decreased in ALS and declines alongside a decline in fat‐free mass over the course of the disease, and may serve as a practical marker to monitor the change of fat‐free mass in patients with ALS. This could inform clinical care and provide an alternative endpoint for the evaluation of therapeutic interventions that focus on slowing the loss of fat‐free mass and disease progression in ALS.
Creatinine is a potential biomarker for amyotrophic lateral sclerosis (ALS). This case‐control study was conducted across two centers in Australia and the Netherlands, contrasting venous creatinine levels with the change in fat‐free mass and disease progression in patients with ALS. Observations confirm that creatinine can be used to infer changes in fat‐free mass and confirm the utility of creatinine as a predictor for disease progression and survival.
PDF
