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Association between Geriatric Nutrition Risk Index and The Presence of Sarcopenia in People with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

ABSTRACT: The aim of this cross-sectional study was to examine the association between the geriatric nutritional risk index (GNRI) and the prevalence of sarcopenia in people with type 2 diabetes (T2DM). Having both low handgrip strength (<28 kg for men and <18 kg for women) and low skeletal muscle mass index (<7.0 kg/m² for men and <5.7 kg/m² for women) was diagnosed as sarcopenia. GNRI was estimated by the formula as below: GNRI = (1.489 × serum albumin level [g/L]) + (41.7 × [current body weight (kg)/ideal body weight (kg)]). Participants were dichotomized on the basis of their GNRI scores (GNRI < 98, low; or GNRI ≥ 98, high). Among 526 people (301 men and 225 women) with T2DM, the proportions of participants with sarcopenia and low GNRI were 12.7% (n = 67/526) and 5.1% (n = 27/526), respectively. The proportion of sarcopenia in participants with low-GNRI was higher than that with high GNRI (44.4% [n = 12/27] vs. 11.0% [n = 55/499], p < 0.001). The GNRI showed positive correlations with handgrip strength (r = 0.232, p < 0.001) and skeletal muscle mass index (r = 0.514, p < 0.001). Moreover, low GNRI was related to the prevalence of sarcopenia (adjusted odds ratio, 4.88 [95% confidence interval: 1.88-12.7], p = 0.001). The GNRI, as a continuous variable, was also related to the prevalence of sarcopenia (adjusted odds ratio, 0.89 [95% confidence interval: 0.86-0.93], p < 0.001). The present study revealed that low GNRI was related to the prevalence of sarcopenia.

SUBMITTER: Takahashi F

PROVIDER: S-EPMC8618310 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveStandard modalities recommended for sarcopenia diagnosis may be unavailable in primary care settings. We aimed to comprehensively evaluate and compare associations of some better popularized nutritional risk-related indexes with sarcopenia presence and their value in sarcopenia diagnosis in community-dwelling middle-aged and elderly adults, including geriatric nutrition risk index (GNRI), albumin (ALB), calf circumference (CC), mid-arm circumference (MAC), triceps skinfold thickness (TST) and body mass index (BMI).MethodsBased on the West China Health and Aging Trend study, the current study included participants aged 50 or older who were recruited in 2018. Sarcopenia-related assessment and diagnosis were in line with Asian Working Group for Sarcopenia 2019. For each single index, we assessed its association with sarcopenia presence by univariate and multivariate logistic regression analysis; we also computed diagnostic measures including the area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, accuracy at the optimal cut-off value determined according to Youden's index.ResultsA total of 3829 subjects were included, consisting of 516 and 3313 subjects in the sarcopenia and non-sarcopenia groups, respectively. Regarding the risk for sarcopenia presence, the fully adjusted odds ratios of GNRI, ALB, CC, MAC, TST and BMI per standard deviation decrease were 2.95 (95% CI 2.51-3.47, P < 0.001), 1.01 (95% CI 0.90-1.15, P = 0.816), 4.56 (95% CI 3.82-5.44, P < 0.001), 4.24 (95% CI 3.56-5.05, P < 0.001), 1.67 (95% CI 1.92-1.45, P < 0.001) and 4.09 (95% CI 3.41-4.91, P < 0.001), respectively. Regarding the value in sarcopenia diagnosis in the entire study population, their AUCs could be ordered as MAC (0.85, 95% CI 0.83-0.86) > GNRI (0.80, 95% CI 0.78-0.82), CC (0.83, 95% CI 0.81-0.85), BMI (0.81, 95% CI 0.79-0.83) > TST (0.72, 95% CI 0.70-0.74) > ALB (0.62, 95% CI 0.60-0.65). At the relevant optimal cut-off values, the sensitivity was the highest for CC (0.83, 95% CI 0.80-0.87) and MAC (0.80, 95% CI 0.77-0.84), while GNRI showed the highest specificity (0.79, 95% CI 0.78-0.81) and accuracy (0.78, 95% 0.76-0.79).ConclusionOverall diagnostic performance was the best for MAC, followed by GNRI, CC, BMI, and the worst for TST, ALB in distinguishing sarcopenia from non-sarcopenia in middle-aged and elderly adults in community-based settings. CC or MAC might do better in reducing missed diagnosis, while GNRI was superior in reducing misdiagnosis.

Project description:BackgroundHypoglycemia occurs in an appreciable number of individuals with type 2 diabetes mellitus (T2DM) who are receiving glycemic therapy. Iatrogenic hypoglycemia induces not only complications but also a substantial medical expense. Intervention for relevant risk factors may help avert severe hypoglycemia and enhance quality of life in at-risk individuals. This study investigates the relationship between body mass index (BMI) and plasma glucose concentration during iatrogenic hypoglycemia in people with T2DM.MethodsEnrollment criteria were people above 20 years of age, with existing diagnosis of T2DM, a documented plasma glucose level ≤70 mg/dL, and acute cognitive impairment requiring hospitalization. Participants were classified into two groups according to their BMI. Specifically, lower BMI subgroup denotes individuals whose BMI fall within lower half of the study population, and vice versa. Plasma glucose concentration, length of hospital stay, and serum electrolyte level at hospitalization were compared between these BMI subgroups. Moreover, multivariate regression analysis was performed to identify covariates associated with plasma glucose level during iatrogenic hypoglycemia.ResultsThis study enrolled 107 participants for whom 54 were assigned to a higher BMI subgroup and the remainder to a lower BMI subgroup. People with lower BMI harbored substantially reduced plasma glucose concentration during iatrogenic hypoglycemia compared to those with higher BMI (30.1 ± 9.6 mg/dL vs. 38.4 ± 12.3 mg/dL, P < 0.001). Nonetheless, the length of stay (6.2 ± 4.6 days vs. 5.7 ± 4.0 days, P = 0.77) and serum potassium level (3.7 ± 0.9 meq/L vs. 3.9 ± 0.8 meq/L, P = 0.14) were comparable between subgroups. Multivariate regression analysis identified BMI as a determinant of plasma glucose concentration in diabetic individuals with iatrogenic hypoglycemia (β coefficient: 0.72, P = 0.008).DiscussionIn individuals with T2DM who experience severe iatrogenic hypoglycemia, BMI influences the plasma glucose level at hospitalization. People with lower BMI harbored appreciably reduced plasma glucose concentration relative to their higher BMI counterparts. In lower weight people, therefore, appropriate dosing of antidiabetic medications, frequent self-monitoring of blood glucose level and adequate nutritional support may help avert more severe hypoglycemia. Overall, BMI potentially influences the severity of iatrogenic hypoglycemia in people with T2DM.

Project description:BackgroundPrevious studies investigating the association between the geriatric nutrition risk index (GNRI) and sarcopenia either lacked longitudinal evidence or narrowly focused on specific populations.AimsWe aimed to reveal longitudinal associations of GNRI with sarcopenia risk in community-dwelling Chinese. We also investigated interaction effects of potential factors on such associations.MethodsWe included participants aged ≥ 50 years with sufficient data from the WCHAT study who did not have sarcopenia at baseline and completed sarcopenia assessment during follow-up. GNRI was calculated according to the formula based on serum albumin, height and weight. Sarcopenia was diagnosed according to the 2019 AWGS consensus. Longitudinal associations between GNRI and sarcopenia were estimated by logistic regression with GNRI as either a continuous or categorical variable by tertiles, using generalized estimating equations (GEE) as sensitivity analyses. Subgroup analyses by potential covariates were conducted to detect interaction effects.ResultsA total of 1907 participants without baseline sarcopenia were finally included, of whom 327 (17.1%) developed incident sarcopenia during 5-year follow-up. After controlling for confounders, sarcopenia risk decreased with each one standard deviation increase in GNRI (ORadjusted=0.36, 95% CI 0.31-0.43), and it also decreased successively from the lowest (< 111.2) through middle (111.2-117.7) to the highest (≥ 117.8) tertile of the GNRI level (P for trend < 0.001). Similar results were yielded by GEE. Such associations generally remained robust across subgroups with distinct characteristics, while significant differences were observed between different age groups (≥ 65 vs. <65 years) (interaction P-value < 0.05).ConclusionGNRI is longitudinally associated with sarcopenia risk with possibly age-specific differences in association magnitude, which holds implications for policymakers to conduct population-based risk assessment.

Project description:OBJECTIVES:To establish healthcare professionals' (HCPs) views about clinical roles, and the barriers and enablers to delivery of diabetes care for people with severe mental illness (SMI). DESIGN:Cross-sectional, postal and online survey. SETTING:Trusts within the National Health Service, mental health and diabetes charities, and professional bodies. PARTICIPANTS:HCPs who care for people with type 2 diabetes mellitus (T2DM) and/or SMI in the UK. PRIMARY AND SECONDARY OUTCOME MEASURES:The barriers, enablers and experiences of delivering T2DM care for people with SMI, informed by the Theoretical Domains Framework. RESULTS:Respondents were 273 HCPs, primarily mental health nurses (33.7%) and psychiatrists (32.2%). Only 25% of respondents had received training in managing T2DM in people with SMI. Univariate analysis found that mental health professionals felt responsible for significantly fewer recommended diabetes care standards than physical health professionals (P<0.001). For those seeing diabetes care as part of their role, the significant barriers to its delivery in the multiple regression analyses were a lack of knowledge (P=0.003); a need for training in communication and negotiation skills (P=0.04); a lack of optimism about the health of their clients (P=0.04) and their ability to manage T2DM in people with SMI (P=0.003); the threat of being disciplined (P=0.02); fear of working with people with a mental health condition (P=0.01); a lack of service user engagement (P=0.006); and a need for incentives (P=0.04). The significant enablers were an understanding of the need to tailor treatments (P=0.04) and goals (P=0.02) for people with SMI. CONCLUSIONS:This survey indicates that despite current guidelines, diabetes care in mental health settings remains peripheral. Even when diabetes care is perceived as part of an HCP's role, various individual and organisational barriers to delivering recommended T2DM care standards to people with SMI are experienced.

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Association between Geriatric Nutrition Risk Index and The Presence of Sarcopenia in People with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

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