Associations of geriatric nutrition risk index and other nutritional risk-related indexes with sarcopenia presence and their value in sarcopenia diagnosis

Triceps skinfold thickness trajectories and the risk of all-cause mortality: A prospective cohort study

BACKGROUND

The measurement of triceps skinfold (TSF) thickness serves as a noninvasive metric for evaluating subcutaneous fat distribution. Despite its clinical utility, the TSF thickness trajectories and their correlation with overall mortality have not been thoroughly investigated.

AIM

To explore TSF thickness trajectories of Chinese adults and to examine their associations with all-cause mortality.

METHODS

This study encompassed a cohort of 14747 adults sourced from the China Health and Nutrition Survey. Latent class trajectory modeling was employed to identify distinct trajectories of TSF thickness. Subjects were classified into subgroups reflective of their respective TSF thickness trajectory. We utilized multivariate Cox regression analyses and mediation examinations to explore the link between TSF thickness trajectory and overall mortality, including contributory factors.

RESULTS

Upon adjustment for multiple confounding factors, we discerned that males in the 'Class 2: Thin-stable' and 'Class 3: Thin-moderate' TSF thickness trajectories exhibited a markedly reduced risk of mortality from all causes in comparison to the 'Class 1: Extremely thin' subgroup. In the mediation analyses, the Geriatric Nutritional Risk Index was found to be a partial intermediary in the relationship between TSF thickness trajectories and mortality. For females, a lower TSF thickness pattern was significantly predictive of elevated all-cause mortality risk exclusively within the non-elderly cohort.

CONCLUSION

In males and non-elderly females, lower TSF thickness trajectories are significantly predictive of heightened mortality risk, independent of single-point TSF thickness, body mass index, and waist circumference.

Geriatric nutrition risk index: a more powerful index identifying muscle mass loss in patients with rheumatoid arthritis

OBJECTIVE

To explore the association of geriatric nutrition risk index (GNRI), a traditional albumin-body weight calculation, with myopenia in patients with rheumatoid arthritis (RA) and compare its ability to identify myopenia with protein indicators.

METHODS

This cross-sectional study was carried out based on a Chinese RA cohort. Clinical data and protein indicators (including albumin, globulin, albumin to globulin ratio, prealbumin, hemoglobin) were collected. GNRI was estimated by serum albumin and body weight. Myopenia was indicated as muscle mass loss measured by bioelectric impedance analysis.

RESULTS

There were 789 RA patients included with mean age 52.6 ± 12.6 years and 77.6% female. There were 41.3%, 18.0%, 27.5%, 13.2% patients with no (GNRI > 98), low (GNRI 92 to ≤ 98), moderate (GNRI 82 to < 92), and major nutrition-related risk (GNRI < 82). There were 406 (51.5%) RA patients with myopenia, RA patients with major nutrition-related risk had the highest prevalence of myopenia (87.5% vs. 73.3% vs. 50.0% vs. 26.1%). Multivariate logistic analysis showed that compared with no risk, RA patients with low (OR = 3.23, 95% CI: 1.86-5.61), moderate (OR = 9.56, 95% CI: 5.70-16.01), and major nutrition-related risk (OR = 28.91, 95% CI: 13.54-61.71) were associated with higher prevalence of myopenia. Receiver operating characteristic curves showed that GNRI (AUC = 0.79) performed a better identifiable ability toward myopenia than serum albumin (AUC = 0.66) or others indicators (AUC range 0.59 to 0.65), respectively.

CONCLUSION

GNRI, an objective and convenient albumin-weight index, may be preferable for identifying myopenia in RA patients. Key Points • We firstly elucidated the association of GNRI with muscle mass loss among RA patients, and compared its ability to identify muscle mass loss with serum albumin or other protein indicators. • Major nutrition-related risk identified by GNRI showed the highest risk of muscle mass loss, GNRI demonstrated a greater ability to identify myopenia in RA patients. which indicated GNRI was an objective and convenient albumin-weight index to identify myopenia in RA patients.

Prevalence of Four Sarcopenia Criteria in Older Patients with Cancer, and Their Predictive Value for 6-Month Mortality: The NutriAgeCancer National Prospective Cohort Study

Older cancer patients have an elevated risk of sarcopenia. The aim was to estimate the prevalence of four criteria for sarcopenia case finding, assessment, diagnosis, and severity determination: abnormal strength, assistance with walking, rising from a chair, climbing stairs, and falls (SARC-F), low hand-grip strength (HGS), low arm circumference (AC, a muscle mass proxy), and low physical performance (PP). Sarcopenia (low HGS and AC) and severe sarcopenia (low HGS, AC, and PP) and their predictive values for 6-month mortality were estimated in the whole population and by metastatic status. We analyzed data from the NutriAgeCancer French nationwide study of cancer patients aged ≥70 referred for geriatric assessment before anti-cancer treatment. We performed Cox proportional hazards analysis for each criterion separately and all criteria combined. Overall, 781 patients from 41 geriatric oncology clinics were included (mean age: 83.1; females: 53%; main cancer types: digestive (29%) and breast (17%); metastases: 42%). The prevalence of abnormal SARC-F, low HGS, a low AC, low PP, sarcopenia, and severe sarcopenia were, respectively, 35.5%, 44.6%, 44.7%, 35.2%, 24.5%, and 11.7%. An abnormal SARC-F and/or low HGS, sarcopenia, and severe sarcopenia were associated with 6-month mortality in patients with metastases (adjusted hazard ratios [95% confidence interval]: 2.72 [1.34-5.49], 3.16 [1.48-6.75] and 6.41 [2.5-16.5], respectively). Sarcopenia was strongly predictive of 6-month mortality in patients with metastatic cancer.

Challenges in the Management of Sarcopenia in the Primary Care Setting: A Scoping Review

BACKGROUND

Sarcopenia is a disease associated with the loss of muscle mass, strength, and function. It affects the elderly in various ways, such as reduced mobility, compromising their daily activities, and even deteriorating metabolic health. Primary care serves as the first point of contact for patients and plays an important role in health promotion and disease prevention. Hence, this review is conducted to identify the challenges in the management of sarcopenia in the primary care setting.

METHOD

In December 2022, a scoping review was conducted using PubMed, SCOPUS, Web of Science, and a manual search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. We used articles that have been written in English, and relevant articles were then screened, duplicates were removed, eligibility criteria were applied, and studies that met the criteria were reviewed. The keywords challenges, management, sarcopenia, and primary care were included.

RESULT

The initial search generated 280 publications, and 11 articles were included after inclusion and exclusion criteria for this review. In this review, challenges in the management of sarcopenia in a primary care setting are reviewed based on the screening and diagnosis.

CONCLUSIONS

With an increasing aging population, it is important to understand the challenges in the management of sarcopenia in a primary care setting. Identification of elderly at risk of sarcopenia, followed by referring the affected elderly for confirmation of the diagnosis, is essential to preventing the adverse health effects. The initiation of treatment that comprises resistance exercise training and nutrition should not be delayed, as they are salient in the management of sarcopenia.

A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study

Background

There are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.

Objective

We investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.

Methods

This was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.

Results

In 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72-17.2), P < 0.001. The superiority of GNRI as compared to albumin and CONUT for detecting sarcopenia was also observed in the subclasses of men, women, body mass index (BMI) < 22, and BMI ≥ 22.

Conclusions

Results showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.

Transitional Dynamics of Sarcopenia and Associations of Nutritional Indices with State Transitions in Chinese aged ≥ 50

OBJECTIVES

Sarcopenia's temporal profile can be regarded as a dynamic process with distinct states, in which malnutrition plays an important role. This study aimed to address two research gaps: sarcopenia's transitional dynamics and associations of nutritional indices with state transitions in community-dwelling Chinese adults aged 50 and older.

DESIGN

A prospective population-based cohort study.

SETTING

Community-based setting in western China.

PARTICIPANTS

The analytic sample included data from 1910 participants aged ≥ 50 in the West China Health and Aging Trend study between 2018-2022.

MEASUREMENTS

We defined three states: the initial normal state (normal muscle strength, physical performance and muscle mass), the worst sarcopenia state (low muscle mass plus low muscle strength and/or low physical performance) and the intermediate subclinical state (the other scenarios). The relevant measurement methods and cut-off points were based on the 2019 AWGS consensus. Using a continuous-time multistate Markov model, we calculated probabilities of transitions between different states over 1, 2 and 4 years; we also examined associations between nutritional indices and transitions, including body mass index (BMI), calf circumference (CC), mid-arm circumference (MAC), triceps skinfold thickness (TST), albumin (ALB), geriatric nutrition risk index (GNRI), vitamin D (VitD) and prealbumin (PA).

RESULTS

For individuals in the normal state, their probabilities of remaining stable versus progressing to a subclinical state were 53.4% versus 42.1% at 2 years, and 40.6% versus 49.0% at 4 years. In the subclinical population, their 2- and 4-year chances were 60.2% and 51.2% for maintaining this state, 11.8% and 16.2% for developing sarcopenia, 28.0% and 32.6% for reverting to normal. For sarcopenic individuals, the likelihood of staying stable versus retrogressing to the subclinical state were 67.0% versus 26.3% at 2 years, and 48.3% versus 36.3% at 4 years. Increased BMI, CC, MAC, TST, ALB, GNRI and PA correlated with reversion from the subclinical state, among which increased TST, ALB and PA were also paralleled with reversion from sarcopenia, while decreased BMI, CC, MAC, TST and GNRI were associated with progression to sarcopenia. VitD was not significantly associated with any transitions.

CONCLUSION

This study reveals how sarcopenia changes over time in a Chinese population. It also highlights the usefulness of simple and cost-effective nutritional status indices for indicating state transitions, which can help identify individuals at risk of sarcopenia and guide targeted interventions within the optimal time window.

Patterns of Muscle-Related Risk Factors for Sarcopenia in Older Mexican Women

Early detriment in the muscle mass quantity, quality, and functionality, determined by calf circumference (CC), phase angle (PA), gait time (GT), and grip strength (GSt), may be considered a risk factor for sarcopenia. Patterns derived from these parameters could timely identify an early stage of this disease. Thus, the present work aims to identify those patterns of muscle-related parameters and their association with sarcopenia in a cohort of older Mexican women with neural network analysis. Methods: Information from the functional decline patterns at the end of life, related factors, and associated costs study was used. A self-organizing map was used to analyze the information. A SOM is an unsupervised machine learning technique that projects input variables on a low-dimensional hexagonal grid that can be effectively utilized to visualize and explore properties of the data allowing to cluster individuals with similar age, GT, GSt, CC, and PA. An unadjusted logistic regression model assessed the probability of having sarcopenia given a particular cluster. Results: 250 women were evaluated. Mean age was 68.54 ± 5.99, sarcopenia was present in 31 (12.4%). Clusters 1 and 2 had similar GT, GSt, and CC values. Moreover, in cluster 1, women were older with higher PA values (p < 0.001). From cluster 3 upward, there is a trend of worse scores for every variable. Moreover, 100% of the participants in cluster 6 have sarcopenia (p < 0.001). Women in clusters 4 and 5 were 19.29 and 90 respectively, times more likely to develop sarcopenia than those from cluster 2 (p < 0.01). Conclusions: The joint use of age, GSt, GT, CC, and PA is strongly associated with the probability women have of presenting sarcopenia.

Anthropometric Indices as Predictive Screening Tools for Obesity in Adults; The Need to Define Sex-Specific Cut-Off Points for Anthropometric Indices

Due to the lack of full agreement as to the best indicators for obesity diagnosis and type, the aim of this study was to assess the comparative classification capabilities with the use of BIA results and selected anthropometric indices in individuals aged 20–60 years. This was a cross-sectional observational study among 368 Caucasian subjects aged 20–60 years. Body size and four skinfolds measurement were taken. To assess individual body composition, the bioelectrical impedance (BIA) method was applied. The results of fat mass (FM, kg) and fat-free mass (FFM, kg) were taken to calculate FM/FFM, fat mass index (FMI), and fat free mass index (FFMI). Receiver-operating characteristic (ROC) curve analysis was employed to compare the predictive power of different anthropometric indices in differentiating the classification of obesity in adults. The results of this study demonstrated and confirmed the need to change the approach to commonly used indicators such as BMI (body mass index) or WHtR (waist-to-height ratio), which should lead to the establishment of new criteria for the diagnosis of obesity that will also be sex-specific, in the adult population. The measurement of body fat content should become a generally accepted indicator for effective diagnosis, as well as for screening, of obesity.