the Journal of Nutrition, health & Aging© volume 15, Number 8, 2011
COgNitive fuNCtiON is AssOCiAteD with BODy COMpOsitiON AND NutRitiONAl Risk
Cognitive funCtion is assoCiated with body Composition and nutritional risk of geriatriC patients R. WiRth1,2,4, C. SmolineR1, C.C. SiebeR2,3, D. VolkeRt2 1. Department of internal medicine and Geriatrics, St. marien-hospital borken, borken, Germany; 2. Friedrich-Alexander-University erlangen-nuremberg, Chair of Geriatric medicine, erlangen, Germany; 3. Department of internal medicine ii, nuremberg hospital, nuremberg, Germany; 4. Corresponding author: Department of internal medicine and Geriatrics, St. marien-hospital borken, D-46325 borken, Germany, tel.: 49 2861 973410; Fax: 49 2861 9753410; e-mail: address:
[email protected]
abstract: Background: most patients with dementia lose body weight over the course of the disease. Yet it is not known whether this weight loss is predominantly in the form of fat-free mass (FFm) or fat mass (Fm), the latter of which one would expect if the weight loss were caused simply by a chronic decrease of energy intake. Objectives: to determine body composition and nutritional risk in geriatric patients and their association with cognitive function. Design: A retrospective, cross-sectional single-center database analysis. Methods: We analyzed 4,095 consecutive geriatric hospital patients for body composition, nutritional risk, need of care and cognitive function using bioelectric impedance analysis, nRS 2002, barthel index and mini mental State examination. Results: Subjects with cognitive dysfunction showed significant lower body weight, body mass index (bmi), Fm, fat mass index, FFm and fat-free mass index and a higher nRS score compared to cognitively intact subjects. mean body weight decreased 10.2%, mean Fm decreased 21.1%, mean FFm decreased 5.9% and mean nRS 2002 score increased from 2.1 to 3.0 points with increasing cognitive deterioration. A multivariate analysis revealed that cognitive dysfunction, age and female gender were all significant risk factors for a low body mass index and a low fat mass index. Age, male gender and need of care, but not cognitive dysfunction, were risk factors for a low fat-free mass index. Conclusion: Dementia patients seem to lose predominantly fat mass with weight loss. Female dementia patients are at a higher nutritional risk than male patients, presumably as a result of their different social situation in old age. that is why the nutritional state of female patients with dementia requires special attention. key words: bioelectric impedance, body composition, cognitive function, dementia, malnutrition.
introduction epidemiological studies have suggested a complex relationship between body weight and dementia. Several longitudinal studies have shown that obesity in adulthood is a risk factor for the development of dementia later in life (1). From that perspective, one would expect subjects with dementia to have a higher body mass index (bmi) than nondemented subjects. however, a lower bmi is regularly observed among demented subjects in cross-sectional studies (2, 5). this paradox highlights the fact that most patients with dementia lose substantial amounts of body weight over the course of their disease, often even preceding obvious symptoms of the disease (6, 11). this weight loss associated with dementia is associated with mortality, morbidity, disease severity and progression and poor quality of life (12, 15) and thus prompts an interesting approach for therapy. in general, unintended weight loss and malnutrition are an underestimated problem in health system and are both prevalent in geriatric patients. older subjects with weight loss and malnutrition have shown increased rates of complications, longer hospital stays, poor functional outcomes and an increased mortality rate (16, 20). A recent meta-analysis proved that the detrimental effects of malnutrition in older subjects can be partially avoided and reversed with nutritional supplementation (21). however, malnutrition in dementia patients is a special challenge, because the mechanisms of Received November 9, 2010 Accepted for publication November 10, 2010
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weight loss that occur with dementia are multifaceted and continue to remain unclear, involving both behavioral and physical aspects of the disease. only a few studies have validated effective treatment strategies for prevention and therapy of malnutrition in dementia, such as social stimulation and oral nutritional supplements (22, 24). What has not been well analyzed thus far is the question of whether the weight loss in dementia syndromes is predominantly a loss of fat mass (Fm) or fat-free mass (FFm), which might imply different consequences for effective interventions. A recent study hypothesized a reduction in lean mass early in dementia (25), which cannot be solely explained by low energy intake. however, if the weight loss in dementia patients were primarily a consequence of cognitive symptoms and therefore due to a slight decrease of energy intake, one would expect a predominant loss of fat mass to be the consequence of an often imperceptible energy imbalance. Furthermore, a previous study reported lower bmi, Fmi and FFmi in subjects with cognitive dysfunction, but did not control for cofactors such as age and gender (26), which are significant to consider because age is associated with body composition changes and one study has shown a higher risk of weight loss in dementia in female subjects (27). We conducted this data base analysis of geriatric hospitalized patients in our department to determine the association between cognitive function and anthropometry, body composition and nutritional risk, taking into account need
the Journal of Nutrition, health & Aging© volume 15, Number 8, 2011
JNhA: fRAilty AND COgNitive DeCliNe of care, age and gender. methods Study design and patients this study is a retrospective analysis of all patients consecutively admitted to the geriatric department of our tertiary teaching hospital between April 2004 and november 2009. All data were obtained from routine clinical examinations within the first three days of hospital admission. Patients without a bioelectric impedance analysis measurement were excluded from the analysis. Geriatric assessment Activities of daily living and thereby need of care was assessed according to the barthel index (28), which was performed by the responsible nurse the day of or the day after hospital admission. Cognitive function was measured by the mini mental State examination (mmSe) (29) within the first three days of admission by a specially trained occupational therapist. the results of the mmSe were grouped into four categories of cognitive dysfunction (26, 30). When the mmSe was not applicable due to severe cognitive impairment (n=154), patients were considered to have 0 points. When the mmSe was not applicable or not performed for other reasons, patients were clinically categorized by the author into one of the four groups of cognitive function according to their medical records (n=162). Fifty-nine patients with missing mmSe scores were excluded from the analysis because of severe dysphasia and the inability to establish retrospective clinical ratings of cognition.
5.1) of Data-input-Gmbh. to connect Fm and FFm with body stature, the fat mass index (Fmi) and fat-free mass index (FFmi) were calculated analogue to the bmi (Fmi = Fm(kg)/m2; FFmi = FFm(kg)/m2; Fmi + FFmi = bmi) (32, 33). A low Fmi was defined as < 4.9 kg/m2 in female subjects and < 2.5 kg/m2 in male subjects. A low FFmi was defined as < 15.1 kg/m2 in female subjects and < 17.5 kg/m2 in male subjects, according to kyle et al. (33). twenty-three patients were excluded from the analysis because the biA-software calculated a negative fat mass, which is not physiologically plausible. this is known to be a common problem in biA when assessing patients with hydration status disturbances of (34, 37). Statistics Data were analyzed using SPSS version 17 (SPSS inc, Chicago, il, USA). Descriptive statistics were used to calculate item frequency, means, standard deviation, medians and ranges. Correlation analysis was performed with Spearman’s rank correlation coefficient. the mann-Whitney test was used to compare two groups with metric data. Group comparisons of ordinal and nominal data were performed with the Chi-square test. kruskal-Wallis analysis was used when comparing multiple groups with metric data. A binary linear regression model was used to assess the simultaneous effects of cognitive dysfunction, age, gender and barthel index on the prevalence of low bmi, Fmi, FFmi and high nRS score, by using the inclusion method. A P-value of 2 points was considered to show risk of malnutrition. the nRS was not performed in all subjects, because the score was introduced into our clinical protocol two years after the start of the observation period. Bioelectric impedance analysis bioelectric impedance was performed with the biA-2000-m device of Data-input-Gmbh (Darmstadt, Germany) in a multifrequency, tetra polar technique on the right side of the body. Red Dot 2271 electrodes manufactured by 3m (neuss, Germany) were used. measurements were performed in the morning after breakfast. Fat mass (Fm) and fat-free mass (FFm) were calculated with the software nutriPlus (version 707
Subject characteristics as well as nutritional parameters of male and female participants are summarized in table 1. All items differed significantly between males and females, with the exception of barthel index, mmSe and nRS score. We found minor, but significant correlations between metric values. the bmi showed a significant correlation with age (r=-0.22; p
