Annals of Nutrition and Metabolism最新文献

Background: Quantitative measurements of liver fat contents (LFCs) by magnetic resonance imaging derived-proton density fat fraction (MRI-PDFF) are accurate but limited by availability, convenience, and expense in the surveillance of metabolic associated fatty liver (MAFLD). Insulin resistance (IR) and steatosis-associated serum indices are useful in screening for MAFLD, but their value in monitoring MAFLD with or without chronic hepatitis B virus (CHB) infection remains unclear and we aimed to evaluate these scores in predicting changes in LFC.

Methods: We conducted a prospective study between January 2015 and December 2021 with 620 consecutive participants with MAFLD (212 participants with CHB) who received a 24-week lifestyle intervention. The homeostasis model assessment of IR (HOMA-IR), HOMA2 index, glucose-insulin ratio, quantitative insulin sensitivity check index, fasting insulin resistance index, fatty liver index (FLI), hepatic steatosis index (HSI), liver fat score (LFS), visceral adiposity index, and triglycerides * glucose were calculated.

Results: When using endpoints such as LFS improvements of ≥5% or 10% or escalations of ≥5%, LFS had the highest area under the curve (AUC) values at all endpoints for MAFLD alone (0.756, 95% CI: 0.707-0.805; 0.761, 95% CI: 0.705-0.818; 0.807, 95% CI: 0.713-0.901, all p < 0.05, respectively). With CHB, the FLI (AUC = 0.750) and HIS (AUC = 0.770) exhibited the highest AUCs between the former two outcomes, respectively, but no score could predict LFC escalation of ≥5%.

Conclusion: Among IR and steatosis scores, changes in LFC through lifestyle interventions can be captured with LFS possessing moderate precision but not in those with CHB.

Background: A significant body of literature has interrogated the critical role of diet in the development and management of inflammatory bowel disease (IBD).

Summary: This review provides a summary and critical appraisal of the literature in this area, focussing on four distinct themes: nutritional epidemiology, animal and in vitro experiments, enteral nutrition, and food-based dietary therapies.

Key messages: Nutritional epidemiology and data from experiments in animals indicate that a western-type diet pattern is associated with increased risk of IBD onset. However, these findings have not been consistently replicated in the dietary management of IBD. Exclusive enteral nutrition (EEN) is the only dietary therapy with reproducible evidence of efficacy in the management of active Crohn's disease (CD). Use of EEN may also be useful for improving perioperative outcomes in CD, and as an adjuvant therapy to biologic therapy. Several dietary therapies for CD and ulcerative colitis have been proposed in the literature, but replication in well-controlled studies is needed before their routine use enters the clinical setting. Precision nutritional therapy might be an attractive therapeutic paradigm in a heterogenous disease like IBD. However, no recommendations for personalised dietary therapy can currently be made, and it is imperative we unravel the complex interplay between diet and gut inflammation before we are able to do so. Undoubtedly, diet is of critical importance in the development and management of IBD. However, the exact mechanism by which diet causes gut inflammation is still elusive, and dietary guidance is difficult to formulate.

Background: The nitrogen balance estimates a protein net difference. However, since it has a number of limitations, it is important to consider the trajectory of the nitrogen balance in the clinical course of critically ill patients.

Objectives: We herein exploratively classified the nitrogen balance trajectory using a machine learning method.

Method: This is a post hoc analysis of a single-center prospective study for the patients admitted to our Emergency and Critical Center ICU. The nitrogen balance was evaluated with 24-h urine collection from ICU days 1-10 with 9 points. K-means clustering was performed to classify the nitrogen balance trajectory. We also evaluated factors associated with uncovered clusters.

Results: Seventy-six eligible patients were included in the present study. After clustering, the nitrogen balance trajectory was classified into 4 classes. Class 1 was trajected as a negative balance over 10 days (24 patients). Class 2 had a positive conversion on day 3 or 4 (8 patients). Class 3 had a positive conversion on day 8 or 9 (28 patients). Class 4 initially had a positive balance and then converted to a negative balance (16 patients). Sepsis complication and steroid use were associated with negative nitrogen balance trajectory. Class 2 was associated with lower length of hospital stay and femoral muscle volume loss, however, frequently had frailty and sarcopenia on admission. Active nutrition therapy intention was not correlated with positive trajectory.

Conclusions: The nitrogen balance trajectory in critically ill patients may be classified into 4 classes for clinical practice. Among patients emergently admitted to the ICU, the positive conversion of the nitrogen balance might be delayed over 10 days.

Introduction: Several researchers have focused on the role of skeletal muscle in metabolic problems in recent years. We aimed to evaluate influence of sleeve gastrectomy on skeletal muscular fat infiltration determined by magnetic resonance imaging in patients with metabolic syndrome (MetS).

Methods: Sixty five MetS patients (male/female, 20/45; mean age, 35.5 years ± 6.6 [standard deviation]; age range, 22-59 years) enrolled in our study. Prior to and 1 year after sleeve gastrectomy, patients underwent routine measurement of skeletal muscular fat concentration (denoted by proton density fat fraction, PDFF) and chemical indexes. The associations of skeletal muscular fat concentration with other variables were determined using multiple linear regression analysis.

Results: Difference between skeletal muscular PDFF at baseline (4.46 ± 2.01%) and PDFF 1-year after sleeve gastrectomy (3.00 ± 1.47%) was significant. Multivariable predictors of baseline skeletal muscular PDFF by descending order of standardized coefficient were fasting serum glucose (0.459; p = 0.001), age (0.395; p < 0.001), systolic pressure (0.319; p = 0.029), insulin (0.030; p = 0.026), white cell count (0.302; p = 0.007), diastolic pressure (-0.301; p = 0.046), and total alkaline phosphatase (-0.474; p < 0.001) all at baseline. Furthermore, multivariable predictors of change in PDFF were serum total cholesterol (3.510; p < 0.001), total alkaline phosphatase (0.535; p < 0.001), estrogen (0.457; p < 0.001), diastolic pressure (0.352; p < 0.001), systolic pressure (-0.409; p < 0.001), high-density lipoprotein cholesterol (-0.719; p < 0.001), insulin (-0.774; p < 0.001), C-reactive protein (-0.900; p < 0.001), triglyceride (-1.756; p < 0.001), and low-density lipoprotein cholesterol (-2.854; p < 0.001) all at baseline.

Conclusion: Sleeve gastrectomy could alleviate myosteatosis in MetS patients during 1-year follow-up. The extent of remission on skeletal muscular fat infiltration after sleeve gastrectomy was influenced by baseline metabolic problems related to serum glucose, serum lipid, and blood pressure level.

Introduction: It has been well recognized that sarcopenia is closely related with osteoporosis, while the relationship between bone mass at different sites and muscle mass remains largely unexplored. This study aims to explore the relationship between bone mass at different sites and skeletal muscle mass in older adults.

Methods: A total of 228 patients over 65 years old were enrolled in this study, and then 180 valid participants with accessible dual-energy X-ray absorptiometry (DXA) scanning data and absence of malignant tumors, mobility disorders, serious liver and kidney disease, and cardiac insufficiency were selected (138 male and 42 female). These individuals were further divided into control group and low skeletal muscle mass index (SMI) group. DXA scanning was used to access skeletal muscle mass and bone mass. SMI or body mass index was defined as appendicular muscle mass or weight divided by squared height, respectively. Low SMI <7.0 kg/m2 in male or <5.4 kg/m2 in female was defined as low SMI; while the bone density score at or below 2.5 standard deviations (T-score) below normal peak bone values, was regarded as osteoporosis.

Results: The average age of enrolled patients was 82.72 years; the ratios of osteoporosis, low SMI, and low SMI with osteoporosis were 48.8%, 23.3%, and 15.0%, respectively. Compared with the control group, the prevalence of osteoporosis was higher, and the total bone mass and bone mass at various sites including limbs, spine, and pelvis, were all lower in low SMI group. Correlation analysis showed that SMI was positively related with total bone mass and bone mass at various sites. Covariance analysis showed that only total bone mass and appendicular bone mass decreased with decreasing SMI. After multiple adjustment, osteoporosis was positively related with the prevalence of low SMI, as evidenced by logistic regression analysis (odds ratio = 1.33, 95% confidential interval: 1.04-3.24, p = 0.045). Furthermore, compared with the highest quartile of appendicular bone mass, the lowest quartile was related with the increasing prevalence of low SMI (odds ratio = 7.29, 95% confidential interval: 1.21-67.45, p = 0.042).

Conclusion: Compared with the other sites, the bone mass reduction at limbs of older adults was positively associated with skeletal muscle loss. It may be more beneficial to increase bone mass at the limbs for improved sarcopenia prevention and therapy. Further investigations are needed to explore the effects of other confounders (e.g., energy, calcium and vitamin D intake, and physical activity) on the osteoporosis and sarcopenia in older adults.

Introduction: The life expectancy of older adults continues to increase; however, knowledge regarding their total energy requirements is lacking. This study aimed to compare the total energy expenditure (TEE) of older adults ≥80 years measured using doubly labelled water (DLW), with estimated TEE. The hypothesis was that the Mifflin, Ikeda, and Livingston equations will more closely estimate energy requirements than the commonly used Schofield equation.

Methods: Resting metabolic rate (RMR) and TEE were measured using the reference methods of indirect calorimetry and DLW, respectively. Bland-Altman plots compared measured RMR and TEE with predicted RMR using equations (Mifflin, Ikeda, Livingston, Schofield) and predicted TEE (predicted RMR × physical activity level).

Results: Twenty-one older adults (age range 80.7-90.1 years, BMI 26.1 ± 5.5 kg/m2) were included. The Schofield equation demonstrated the greatest bias from measured RMR, overestimating approximately up to double the mean difference (865 ± 662 kJ/day) compared with the three other equations. The Schofield equation exhibited the greatest bias (overestimation of 641 ± 1,066 kJ/day) compared with measured TEE. The other three equations underestimated TEE, with the least bias from Ikeda (37 ± 1,103 kJ/day), followed by Livingston (251 ± 1,108 kJ/day), and Mifflin (354 ± 1,140 kJ/day). Data are mean ± SD.

Conclusions: In older adults ≥80 years, the Ikeda, Mifflin, and Livingston equations provide closer estimates of TEE than the widely used Schofield equation. The development of nutrition guidelines therefore should consider the utilization of equations which more accurately reflect age-specific requirements.