Prevalence of Malnutrition in a Group of Institutionalized Psychogeriatric Patients Using Different Diagnostic Criteria.

Malnutrition (MN) is a highly prevalent condition in the elderly. It is associated with functional impairment, disability, frailty, and sarcopenia. The aim was to analyze the capacity of GLIM and ESPEN criteria to diagnose MN in a sample of institutionalized psychogeriatric patients. Clinical and anthropometric data were collected in a cross-sectional study. Patients' frailty, dependence, functional capacity, MNA, hand-grip strength (HS), and sarcopenia were evaluated. Body composition (BC) was estimated by conventional bioimpedance analysis. MN diagnosis was established using the ESPEN and the GLIM criteria based on fat-free mass index (GLIM-FFMI), appendicular skeletal muscle mass index (GLIM-ASMMI), skeletal muscle mass index (GLIM-SMMI), and HS (mGLIM). Ninety-two patients (57.6% men; mean age: 79.4 years) were studied. Depending on the diagnosis criteria, MN prevalence was between 25% (ESPEN) and 41.3% (GLIM-SMMI). Agreement between ESPEN and all GLIM criteria was poor, but it was excellent between all GLIM criteria (kappa > 0.8). Phenotypic criteria carried more weight in the diagnosis of MN than etiological ones. Depending on the parameter used, the prevalence of reduced muscle mass was notably different. Differences in BMI, BC, inflammation, and albumin are detected by the GLIM-FFMI criteria in the MN and non-MN subjects. Also, this criterion is the only one that identified differences in phase angle (PhA) between these groups. In the elderly, PhA can be very useful to monitor nutritional status.

Phase Angle as a Prognostic Indicator of Survival in Institutionalized Psychogeriatric Patients.

Phase angle (PhA) has been evidenced to be a useful survival indicator and predictor of morbi-mortality in different pathologies, but not in psychogeriatric patients. The aim of this study was to evaluate the clinical utility of PhA as a prognostic indicator of survival in a group of institutionalized psychogeriatric patients. A survival study was conducted on 157 patients (46.5% dementia, 43.9% schizophrenia). Functional impairment stage, frailty, dependence, malnutrition (MNA), comorbidity, polypharmacy, BMI, and waist circumference were registered. Body composition was analyzed using a 50-kHz whole-body BIA; PhA was recorded. The association between mortality and standardized-PhA was evaluated through univariate and multivariate Cox regression models and ROC-curve. The risk of death decreased when Z-PhA, BMI, and MNA were higher. Mortality increases with age, frailty, and dependence. The risk of death was statistically significantly lower (56.5%) in patients with schizophrenia vs. dementia (89%). The Z-PhA cut-off point was -0.81 (Sensitivity:0.75; Specificity:0.60). Mortality risk was multiplied by 1.09 in subjects with a Z-PhA < -0.81, regardless of age, presence of dementia, and BMI. PhA presented a remarkable clinical utility as an independent indicator of survival in psychogeriatric patients. Moreover, it could be useful to detect disease-related malnutrition and to identify subjects eligible for an early clinical approach.

Body mass index and waist circumference are not good surrogate indicators of adiposity in psychogeriatric patients.

OBJECTIVE: to assess the utility of body mass index (BMI) and waist circumference (WC) as surrogate indicators of adiposity with respect to the total body fat estimated with bioimpedance analysis in psychogeriatric patients. METHODS: Anthropometric and hand-to-foot bioimpedance measurements were performed according to standard procedures in a sample of 128 psychogeriatric patients (87 males, 41 females). WC cutoffs proposed by the International Diabetes Federation were used to define abdominal obesity. Z-scores of fat and fat-free mass indices (Z-FMI and Z-FFMI) were calculated. RESULTS: Males with WC values below the cutoff were normal weight, and showed normal levels of FM and low FFM (Z-FFMI below 1.5 SD). Males with WC values above the cutoff were overweight, showed high levels of FM (Z-FMI: 1.34 SD) and a slight depletion of FFM (Z-FFMI: -0.59 SD). In females with WC values below the cutoff, BMI was close to 20 kg/m(2) and both FM and FFM were depleted (Z-FMI: -0.7 SD; Z-FFMI: -1.76 SD). In females with WC above the cutoff, the average BMI was 25.6 kg/m(2) , Z-FMI was 0.48 SD, and Z-FFMI was -0.56 SD. CONCLUSIONS: Our results indicate that it is necessary to establish age and sex-specific BMI and WC cutoffs, and also highlight the importance of focusing on body composition analysis to ensure an accurate nutritional diagnosis in older-adults and in psychogeriatric patients.

Bioimpedance vector analysis and conventional bioimpedance to assess body composition in older adults with dementia.

OBJECTIVE: Although dementia and nutritional status have been shown to be strongly associated, differences in body composition (BC) among older people with dementia have not yet been firmly established. The aim of this study was to assess BC through conventional and vector bioimpedance analysis (BIA and BIVA, respectively) in a sample of institutionalized older men with and without dementia, in order to detect dementia-related BC changes. METHODS: Forty-one institutionalized men ages ≥ 65 y (23 without dementia [CG] and 18 with dementia [DG]) were measured with BIA and interpreted with BIVA and predictive equations. RESULTS: Age (74.4 and 75.7 y) and body mass index (22.5 and 23.6 kg/m(2)) were similar for DG and CG, respectively. Resistance and ratio of resistance to height did not differ significantly between the two groups. Reactance and ratio of reactance to height were 21.2% and 20.4% lower in DG than in CG. Phase angle was significantly lower in DG (mean = 4.0; 95% confidence interval [CI], 3.6°-4.3°) than in CG (mean = 4.7; 95% CI, 4.3°-5.1°). Mean fat mass index (6 and 7 kg/m(2)), and mean fat-free mass index (16.4 and 16.6 kg/m(2)) were similar in both groups. BIVA showed a significant downward migration of the ellipse in DG with respect to CG (T(2) = 15.1; P < 0.01). CONCLUSION: Conventional BIA showed no significant differences in BC between DG and CG, although reactance and ratio of reactance to height were about 21% lower in DG. Nevertheless, a body cell mass depletion and an increase in the ratio of extracellular to intracellular water were identified in DG using BIVA. BIVA reflects dementia-related changes in BC better than BIA.

Specific bioelectrical impedance vector analysis (BIVA) is more accurate than classic BIVA to detect changes in body composition and in nutritional status in institutionalised elderly with dementia.

BACKGROUND: A new analytical variation of bioelectrical impedance vector analysis (BIVA), called specific BIVA, has shown to be more accurate in detecting changes in fat mass than classic BIVA. OBJECTIVE: To compare classic and specific BIVA in order to identify which is more strongly associated with psycho-functional and nutritional indicators in a group of institutionalised elderly patients with dementia. SUBJECTS AND METHODS: Cross-sectional study. Fifty-four patients (34 women, 20 men) with dementia in moderately severe to very severe stages and aged 60-95years underwent geriatric nutritional assessment, including body mass index calculations, the Mini Nutritional Assessment, the Geriatric Nutritional Risk Index, and whole body composition analysis. RESULTS: With specific BIVA (unlike with classic BIVA), significant differences were found between women with moderately severe and very severe dementia. In the BIVA conducted for body mass index, the confidence ellipses produced with the classic BIVA approach were highly overlapping; but with specific BIVA, significant differences were observed between the women in different nutritional categories (malnutrition, risk of malnutrition, normal weight and obesity). On the other hand, both approaches distinguished malnourished women from those who were at risk of malnutrition, according to the Mini Nutritional Assessment; and men with a moderate-high risk of malnutrition from men with no risk, on the basis of the Geriatric Nutritional Risk Index. CONCLUSION: Overall, the findings of the present study suggest that specific BIVA is more effective than classic BIVA in identifying bioelectrical changes associated with psycho-functional and nutritional indicators in institutionalised elderly with dementia.