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International Journal of Nursing Practice 2014; ••: ••–••
CLINICAL PAPER
Factors contributing to malnutrition in patients with Parkinson’s disease Sung R Kim RN PhD Assistant Professor, College of Nursing, Chonbuk National University, Jeonju, Korea
Sun J Chung MD PhD Associate Professor, Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
Sung-Hee Yoo RN PhD Assistant Professor, College of Nursing, Chonnam National University, Gwangju, Korea
Accepted for publication November 2014 Kim SR, Chung SJ, Yoo SH. International Journal of Nursing Practice 2014; ••: ••–•• Factors contributing to malnutrition in patients with Parkinson’s disease Our objective in this study was to evaluate the nutritional status and to identify clinical, psychosocial, and nutritional factors contributing to malnutrition in Korean patients with Parkinson’s disease. We used a descriptive, cross-sectional study design. Of 102 enrolled patients, 26 (25.5%) were malnourished and 27 (26.5%) were at risk of malnutrition based on Mini-Nutritional Assessment scores. Malnutrition was related to activity of daily living score, Hoehn and Yahr stage, duration of levodopa therapy, Beck Depression Inventory and Spielberger’s Anxiety Inventory scores, body weight, body weight at onset of Parkinson’s disease, and body mass index. On multiple logistic regression analysis, anxiety score, duration of levodopa therapy, body weight at onset of Parkinson’s disease, and loss of body weight were significant factors predicting malnutrition in Parkinson’s disease patients. Therefore, nutritional assessment, including psychological evaluation, is required for Parkinson’s disease patients to facilitate interdisciplinary nutritional intervention for malnourished patients. Key words: malnutrition, nutritional status, Parkinson’s disorder.
INTRODUCTION Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by dopaminergic neuronal loss.1 Patients with PD experience not only neurological motor symptoms including tremor, rigidity and bradykinesia but also health-related problems including depression, dementia, fatigue and constipation.2 Malnutrition has also been recognized as an important problem in PD patients.2,3 Correspondence: Sung-Hee Yoo, College of Nursing, Chonnam National University, 160 Baekseo-ro, Dong-gu, Gwangju 501-746, Korea. Email: [email protected] doi:10.1111/ijn.12377
Malnutrition is generally defined as an underweight BMI less than 18.50 kg/m2 in adults, according to the WHO classification.4 Previous studies have shown that PD patients have a lower body weight and body mass index (BMI) than healthy controls5–7 and also are at increased risk of developing malnutrition than age-matched controls.8 The prevalence of malnutrition in PD patients has been reported to range from 0 to 24%, and the malnutrition risk from 3 to 60% based on various nutritional parameters and definitions.8–11 Although the true extent of malnutrition in the PD population remains unclear, a not inconsiderable proportion of patients have a nutritional problem. © 2014 Wiley Publishing Asia Pty Ltd
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Nutritional assessment can be performed by assessing hematologic parameters such as albumin or prealbumin levels, anthropometric parameters such as body mass index (BMI) and body weight, and using nutritional assessment tools to assess dietary habits and general status.12 The mini-nutritional assessment (MNA) tool is one of the most widely used tools for nutritional assessment in clinical and research settings, because it can evaluate neuropsychological health and morbidity as well as anthropometric parameters and dietary habits, and has been validated in elderly patients.13 Therefore, nutritional assessment using this validated tool is essential for PD patients. Several factors might contribute to the high prevalence of malnutrition in PD patients. The first factor is related to motor symptoms. Bradykinesia, rigidity and gait disturbance cause some patients to experience difficulty in performing the activities of daily living (ADL) such as shopping, preparing and eating or swallowing food independently11,14 These types of disabilities might also be caused by levodopa-related motor complications such as dyskinesia.7,8,15 The second factor is related to psychosocial and cognitive factors. Depression, anxiety and dementia have been found to contribute to lowered food intake and weight loss in the elderly,16–18 and such symptoms are present at a higher incidence in PD patients than in controls.19,20 The last factor is related to medications that are used to manage PD, which can have side effects such as nausea, vomiting, loss of appetite and change of taste.8,21–23 Although multiple factors might contribute to malnutrition in PD patients, only a few of these factors have been examined in previous studies.5,7,9,10,23 Therefore, a comprehensive study examining all potential factors is needed to identity factors that significantly affect malnutrition in PD patients. Because malnutrition leads to poorer quality of life and worse health outcomes, such as higher mortality and prolonged length of hospital stay,8 evaluation of the nutritional status of PD patients and determination of the factors that contribute to malnutrition in PD patients are particularly relevant.
Aims Our aims in the current study were to describe the nutritional status of Korean patients with PD and to identify clinical, psychosocial and nutritional factors that predicted malnutrition in these patients. © 2014 Wiley Publishing Asia Pty Ltd
METHODS Design This was an observational study with a cross-sectional design.
Participants Subjects were recruited from a single tertiary university hospital in Seoul, Korea, and convenience sampling was used to select subjects. We included patients (i) who were over 20 years of age, (ii) who had PD based on the United Kingdom Parkinson’s Disease Society Brain Bank criteria as the primary diagnosis,24 and (iii) who had no other major health problems that could influence nutritional status such as active cancer, infection, inflammation, liver failure, or renal failure. We excluded patients with atypical Parkinsonism or secondary Parkinsonism. We enrolled a total of 102 patients in the current study.
Measurement of nutritional status Mini-Nutritional Assessment (MNA)
Nutritional status was measured using the MNA tool.25 The MNA is widely used to assess nutritional status and has been validated in various settings,13 including in elderly Korean patients.26 MNA is highly sensitive (96%) and specific (98%).13,27 The MNA is an 18-item questionnaire comprising anthropometric measurements, general status including swallowing function, dietary habits and self-perception of health and nutrition states.13 MNA scores range from 0 to 30 points; a higher score indicates a healthier nutritional status. Based on the final MNA scores, we classified the nutritional status of subjects ‘good’ (≥ 24 points), at ‘risk of malnutrition’ (17–23.5 points), or ‘malnourished’ (< 17 points).13,25 In this study, we defined patients with a good nutritional status and those at risk of malnutrition into the non-malnutrition group, whereas malnourished patients were defined to the malnutrition group.
Beck Depression Inventory (BDI) Depression was measured using the Beck Depression Inventory (BDI) with self-rating scales,28,29 which is one of the most commonly used tools for assessment of depression.30 Its reliability and validity have been validated in Korean patients.30,31 The BDI includes 21 questions and BDI scores range from 0 to 63. Higher scores indicate greater depression. Cronbach’s alpha value for the BDI was 0.90 in the current study.
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Spielberger’s Anxiety Inventory (SAI)
Data collection
Anxiety was measured using the Korean version of SAI.32,33 This is a well-established scale that has been used extensively in research and clinical practice.34,35 SAI includes 20 questions and SAI scores range from 20 to 80. Higher scores indicate greater anxiety. Cronbach’s alpha value for the SAI was 0.95 in the current study.
Between March and September 2012, we enrolled subjects who provided written informed consent. Subjects were informed of the aims and procedures of the current study by clinical nurse specialists. Patients who agreed to face-to-face interviews had their body weight and BMI measured and were administered a structured questionnaire that they completed together with a spouse or family member. Following the interviews, we confirmed patient information using medical records.
Mini-Mental State Examination (MMSE) Korean version of the MMSE (K-MMSE) was used to measure the cognitive function of patients.36 Sensitivity for detecting dementia with the K-MMSE has been reported to range from 0.70 to 0.83.37 K-MMSE scores range from 0 to 30. Higher scores indicate greater cognitive function.
Other variables We examined various clinical and nutritional variables using a structured questionnaire. The clinical characteristics of age of onset of PD, disease duration, duration of levodopa therapy, daily levodopa equivalent dose (LED), presence of motor fluctuation and dyskinesia, Hoehn and Yahr stage, and the Schwab and England ADL score were assessed. We assessed nutritional characteristics in detail including MNA; anthropometric parameters such as current body weight, body weight at onset of PD, weight loss and body mass index (BMI); biochemical parameters such as serum albumin and total protein; and presence of symptoms potentially affecting oral intake by PD medication such as constipation, nausea and vomiting, and dyspepsia. Current body weight and BMI were measured using an automatic fatness measuring system (G-tec, G-tec International, Uijungbu, South Korea). Subjects were assigned to one of four categories based on BMI values according to WHO recommendations for Asian populations.38 Weight loss was calculated as the difference between weight at onset of PD and current weight based on a review of electronic medical records. In addition, serum protein and albumin levels were assessed as biochemical parameters. Serum total protein was classified based on a cut-off of 6.2 g/dL and serum albumin on a cut-off of 3.5 g/ dL.39 We defined constipation as bowel action less than three times weekly,40 whereas we defined dyspepsia as gastrointestinal discomfort after taking PD medication based on subjective sensations of bloating, burning and gas in the bowels.22
Analysis Statistical analyses were conducted using SPSS version 20.0 (IBM SPSS Statistics, SPSS Inc., Chicago, IL). All data are expressed as numbers (percentages), means ± SD (standard deviations), or medians (ranges). To compare clinical, psychosocial and nutritional characteristics between the malnutrition and non-malnutrition group, we used the chi-square test, t-test or Mann–Whitney U-test as appropriate, and we used the Kolmogorov– Smirnov test to analyze the normality of continuous variables. To identify independent predictors of malnutrition, we performed multiple logistic regression analysis and calculated odds ratios (ORs) and 95% confidence intervals (CIs). Hosmer–Lemeshow test was used to assess goodness-of-fit. A two-tailed P value less than 0.05 was considered statistically significant.
Ethical considerations The current study was approved by the Institutional Review Board (IRB) of Asan Medical Center in Korea. We obtained written informed consent from all subjects or their legal representatives. Subjects were allowed to voluntarily withdraw their informed consent and their personal data were kept strictly confidential throughout the study.
RESULTS Demographic, clinical and psychosocial characteristics Of the 102 patients included in this study, 57 (55.9%) were female. Age ranged from 31 to 81 years (mean ± SD, 61.2 ± 10.1 years), and the median disease duration was 9 years (range, 1–24 years). Median Hoehn and Yahr stage was 2 (range, 0–5). Mean K-MMSE, BDI, and SAI scores were 25.7 ± 3.7, 14.7 ± 10.8, and 44.6 ± 11.1, respectively. © 2014 Wiley Publishing Asia Pty Ltd
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Nutritional status and characteristics Nutritional characteristics are summarized in detail in Table 1. Twenty-six (25.5%) of the 102 patients were categorized as malnourished whereas 27 (26.5%) patients were considered at risk of malnutrition based on the MNA results. Fifty-eight (56.8%) patients had experienced weight loss. Mean BMI of all PD patients was 23.2 ± 3.7 kg/m2 and seven patients (6.9%) were underweight (BMI < 18.5 kg/m2). Mean serum total protein and albumin levels were 6.6 ± 0.5 and 4.0 ± 0.4 g/dl (range, 5.3–7.7 g/dl and 3.0–5.9 g/dl), respectively.
Demographic, clinical, psychosocial, and nutritional characteristics related to malnutrition Differences in demographic, clinical, psychosocial, and nutritional characteristics between the two groups are presented in Table 2. Table 1 Nutritional characteristics of PD patients (n = 102) Variables
n (%) or mean ± SD
MNA Good status (≥ 24) Risk of malnutrition (17–23.5) Malnutrition (< 17) Body weight (kg) Body weight at disease onset (kg) Weight loss
21.4 ± 6.2 49 (48.0%) 27 (26.5%) 26 (25.5%) 58.7 ± 9.4 61.7 ± 9.4 58 (56.9%) 7.2 ± 4.7 23.2 ± 3.7 7 (6.9%) 44 (43.1%) 40 (39.2%) 11 (10.8%) 6.6 ± 0.5 21 (21.4%) 77 (78.6%) 4.0 ± 0.4 8 (7.8%) 90 (88.2%) 55 (53.9%) 12 (11.8%) 16 (15.7%)
BMI (kg/m2) < 18.5 18.5 ≤ BMI < 23 23 ≤ BMI < 27.5 ≥ 27.5 Protein (g/dl), (n = 98) < 6.2 ≥ 6.2 Albumin (g/dl), (n = 98) < 3.5 ≥ 3.5 Constipation Nausea & vomiting Dyspepsia
Range
4.5–29.0
40.5–83.0 42.0–93.8 1.0–20.0 14.4–34.2
5.3–7.7
3.0–5.9
PD, Parkinson’s disease; SD, standard deviation; MNA, mininutritional assessment; LED, levodopa equivalent dose; K-MMSE, Korean mini mental status examination; BMI, body mass index.
© 2014 Wiley Publishing Asia Pty Ltd
In the malnutrition group, the age of onset of PD was significantly higher than that in the non-malnutrition group (55.6 ± 9.5 years vs. 49.6 ± 11.8 years, respectively) (P = 0.020), and Schwab and England ADL score was significantly lower in the malnutrition group (P < 0.001). However, the duration of levodopa therapy was significantly shorter in the malnutrition group (P = 0.038). Hoehn and Yahr stage was significantly correlated with the degree of malnutrition according to MNA score (P = 0.017). BDI and SAI scores were significantly higher in the malnutrition group than the non-malnutrition group (P = 0.009 and P < 0.001, respectively). Among nutritional parameters, body weight, body weight at disease onset, and BMI were significantly lower in the malnutrition group than the non-malnutrition group (P < 0.001, P = 0.009, and P < 0.001, respectively), whereas weight loss was higher in the malnutrition group than the non-malnutrition group (P < 0.001). Moreover, we found a significant correlation between malnutrition and nausea and vomiting (P = 0.048) and dyspepsia (P = 0.001) related to anti-PD medication. However, clinical factors such as sex, age, disease duration, daily levodopa equivalent dose (LED), motor fluctuation, dyskinesia, K-MMSE score, and levels of visceral proteins such as serum total protein and albumin were not related to malnutrition.
Factors predicting malnutrition in patients with PD Multiple logistic regression analysis revealed that anxiety score (OR = 1.124, 95% CI: 1.003–1.261, P = 0.044), duration of levodopa therapy (OR = 0.666, 95% CI: 0.460–0.962, P = 0.030), body weight at onset of PD (OR = 0.709, 95% CI: 0.544–0.925, P = 0.011), and weight loss (OR = 2.972, 95% CI: 1.366–6.464, P = 0.006) were significant factors predicting malnutrition (Table 3).
DISCUSSION The results of our study indicate that the prevalence of malnourishment in patients with PD is high, and that the psychological factor of anxiety, as well as duration of levodopa treatment, initial weight at diagnosis, and weight change after PD onset are independent predictors of malnutrition. A strength of our study is that we examined all potential contributing factors, including nutritional symptoms related with anti-PD medication,
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Table 2 Comparison of clinical, psychosocial, and nutritional characteristics between the malnutrition group and the non-malnutrition group Variables
Clinical characteristics Sex (Female) Age (years) Age at onset (years) Disease duration (years) Hoehn & Yahr stage 0 1 2 3 4 5 ADL (%) Duration of levodopa Therapy (years) LED (mg/day) Motor fluctuation No Yes, but not disabling Yes, disabling Dyskinesia No Yes, but not disabling Yes, disabling K-MMSE Psychosocial characteristics Depression Anxiety Nutritional characteristics Body weight (kg) Body weight at PD onset (kg) BMI (kg/m2) < 18.5 18.5 ≤ BMI < 23 23 ≤ BMI < 27.5 ≥ 27.5 Weight loss (kg) Protein (g/dl) Albumin (g/dl) Constipation Nausea & vomiting Dyspepsia
Malnutrition (n = 26)
Non-malnutrition (n = 76)
18 (69.2%) 64.5 ± 8.6 55.6 ± 9.5 8.7 ± 5.3
39 (51.3%) 60.1 ± 10.4 49.6 ± 11.8 10.6 ± 6.2
0 3 (11.5%) 10 (38.5%) 5 (19.2%) 5 (19.2%) 3 (11.5%) 63.9 ± 26.1 6.5 ± 4.4 614.1 ± 311.9 (n = 25) 9 (36.0%) 8 (32.0%) 8 (32.0%) (n = 25) 9 (36.0%) 11 (44.0%) 5 (20.0%) 24.4 ± 3.6
2 (2.6%) 5 (6.6%) 46 (60.5%) 16 (21.1%) 7 (9.2%) 0 84.7 ± 11.9 9.3 ± 6.1 788.5 ± 497.7 (n = 76) 22 (28.9%) 32 (42.1%) 22 (28.9%) (n = 76) 27 (35.5%) 34 (44.7%) 15 (19.7%) 26.1 ± 3.6
23.7 ± 10.6 52.3 ± 12.3
11.6 ± 9.1 42.2 ± 9.6
50.8 ± 6.3 57.5 ± 8.5 20.2 ± 2.6 6 (23.1%) 17 (65.4%) 3 (11.5%) 0 22 (84.6%) 7.4 ± 5.0 6.6 ± 0.4 4.0 ± 0.6 14 (53.8%) 6 (23.1%) 10 (38.5%)
61.4 ± 8.8 63.1 ± 9.3 24.3 ± 3.4 1 (1.3%) 27 (35.5%) 37 (48.7%) 11 (14.5%) 36 (47.4%) 3.1 ± 4.6 6.6 ± 0.5 3.9 ± 0.3 41 (53.9%) 6 (7.9%) 6 (7.9%)
t or z or χ2
P value
0.169 1.968 2.360 −1.338 13.463
0.112 0.052 0.020* 0.114† 0.017*
−3.930 −2.468 −1.643 0.849
< 0.001** 0.038†* 0.384† 0.654
0.004
0.998
−2.036
0.083†
4.682 3.654
0.009†* < 0.001**
−5.629 −2.655 −5.612 27.951
< 0.001** 0.009* < 0 .001** < 0.001**
10.957 3.992 −0.161 0.629 0.000 4.302 13.686
0.001* < 0.001†** 0.873 0.401† 0.993 0.048* 0.001**
* P < 0.05; ** P < 0.001; †Mann–Whitney U-test. ADL, activities of daily living; LED, levodopa equivalent dose; K-MMSE, Koreanmini mental status examination; BMI, body mass index.
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Table 3 Predictors of malnutrition in PD patients Variables
Odds ratio
95% CI
P value
Anxiety Duration of levodopa therapy Body weight at onset of PD Weight loss
1.124 0.666 0.709 2.972
1.003–1.261 0.460–0.962 0.544–0.925 1.366–6.464
0.044* 0.030* 0.011* 0.006*
* P < 0.05, Hosmer–Lemeshow goodness-of-fit test showed χ2 = 1.56 (P = .980). PD, Parkinson’s disease; CI, confidence interval.
clinical and psychological factors, and various nutritional parameters, to determine independent predictors of malnutrition. The prevalence of malnutrition was 25.5% and the risk of malnutrition was 26.5%, indicating that more than half of the subjects (52%) had nutritional problems. This result is largely consistent with those reported in previous studies based on MNA assessment.8,23 Our results indicate that PD patients are therefore more likely to be undernourished than hemodialysis patients (56.5%)41 or patients with other chronic diseases, such as chronic obstructive pulmonary disease (30.7%).42 This result highlights the necessity of performed nutritional assessments in all PD patients, given that patients at risk of malnutrition might become malnourished.43 We found that although K-MMSE scores were lower in the malnutrition group than in the non-malnutrition group (24.4 ± 3.6 vs. 26.1 ± 3.6, respectively), these scores were not statistically correlated with malnutrition, a finding similar to that reported in previous studies.7,8 However, because cognitive function has been shown to be associated with malnutrition in other populations,44 including Alzheimer’s disease patients,45 further studies are warranted to elucidate the correlation between cognitive function and nutritional status in patients with PD. Because PD is a neurodegenerative disorder, disease duration and disease severity are positively associated with each other, and both might be negatively associated with nutritional status. We found an association between malnutrition and a higher Hoehn and Yahr stage, as described in previous studies,6,8 but no association between malnutrition and PD duration. It is therefore unclear whether PD duration is associated with malnutrition, because previous studies have reported findings that conflict with © 2014 Wiley Publishing Asia Pty Ltd
those of the current study;6,7,23 further studies are needed to address this issue. Our results suggest that disease severity might be a more important factor than disease duration for predicting malnutrition in PD patients. It is well known that depression and anxiety are psychological factors associated with malnutrition,16,18 consistent with our results. In particular, we found that anxiety was an independent predictor of malnutrition after adjusting for all other factors in our study. Anxiety is a frequent emotional symptom in PD patients and is associated with motor symptoms, such as severe gait problems, dyskinesia, and off symptoms.46 Anxiety might worsen nutritional status through exacerbated neurologic symptoms and might affect appetite and food intake. Until recently, medication was the main treatment strategy in patients with high levels of anxiety.47 However, cognitive behavior therapy and exercise are gaining popularity as effective approaches to treat anxiety in PD patients.48,49 Thus, a multi-dimensional intervention strategy might alleviate anxiety and improve nutritional status in PD patients. Other nutritional parameters were also significantly different between the malnutrition and non-malnutrition groups. We used albumin as a biochemical parameter to investigate cross-sectional nutritional state in PD patients, not temporal changes, because albumin is known to be a good predictor of poor clinical outcomes in various diseases50,51 and has a longer half-life than prealbumin or transferrin. However, the albumin results did not reflect the MNA results in our study. This was consistent with previous findings that the serum albumin was not a reliable indicator for nutritional assessment in patients with chronic diseases.52 In addition, we also measured the BMI as an anthropometric parameter, but the proportion of underweight individuals according to the WHO BMI classification showed a discrepancy with the incidence of malnutrition according to the MNA. It was also consistent with previous findings performed in elderly patients and patients with cancer.53–55 We believe that these results might be due to each nutritional parameter (such as anthropometric, biochemical, and global assessment tools) reflecting a different clinical process.56 Nevertheless, the MNA considers various nutritional parameters including food intake by appetite or swallowing difficulty, anthropometric measurements including weight loss, and physical and mental functions, and malnutrition and nonmalnutrition groups classified by the MNA showed a difference in clinical and psychological factors reported in
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previous studies, symptoms affecting oral intake, and other nutritional factors excluding biochemical parameters. Therefore, we believe that the MNA is a useful tool for nutritional assessment in patients with PD as a chronic disease. We recommend assessing the nutritional state of PD patients using a validated tool and identifying risk factors for poor nutrition. Moreover, for patients at risk of malnutrition, as well as those with malnutrition, various individual interventions such as diet modification and nutritional supplements, education, stress relief, regulation of symptoms affecting poor oral intake, and dietary consultation should be considered in both research settings and clinical practice.
CONCLUSIONS Our study revealed that more than half of patients with PD had nutritional problems, and that anxiety, duration of levodopa therapy, body weight at onset of PD, and weight loss were factors that contributed significantly to the development of malnutrition in PD patients. Therefore, appropriate nutritional assessment, including psychological evaluation, should be conducted regularly in PD patients, and a multidisciplinary approach involving various nutritional interventions should be considered for undernourished patients.
ACKNOWLEDGEMENTS No research funding or any other financial support was received for this study. None of the authors have any conflicts of interest to declare.
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21 Marcason W. What are the primary nutritional issues for a patient with Parkinson’s disease? Journal of the American Dietetic Association 2009; 109: 1316. 22 Pfeiffer RF. Gastrointestinal dysfunction in Parkinson’s disease. Lancet Neurology 2003; 2: 107–116. 23 Wang G, Wan Y, Cheng Q et al. Malnutrition and associated factors in Chinese patients with Parkinson’s disease: Results from a pilot investigation. Parkinsonism and Related Disorders 2010; 16: 119–123. 24 Gibb WR, Lees AJ. The relevance of the lewy body to the pathogenesis of idiopathic Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry 1988; 51: 745–752. 25 Guigoz Y, Vellas B, Garry PJ. Mini nutritional assessment: A practical assessment tool for grading the nutritional state of elderly patients. Facts and Research in Gerontology 1994; 4 (Suppl. 2): 15–59. 26 Kim EJ, Yoon YH, Kim WH, Lee KL, Park JM. The clinical significance of the mini-nutritional assessment and the scored patient-generated subjective global assessment in elderly patients with stroke. Annals of Rehabilitation Medicine 2013; 37: 66–71. 27 Vellas B, Guigoz Y, Garry PJ et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition (Burbank, Los Angeles County, Calif.) 1999; 15: 116–122. 28 Beck AT. Depression: Clinical, Experimental and Theoretical Aspects. New York, USA: Harper & Row, 1967. 29 Lee YH, Song JY. A study of the reliability and the validity of the BDI, SDS, and MMPI-D scales. Korean Journal of Clinical Psychology 1991; 10: 98–113. 30 Kil SY, Oh WO, Koo BJ, Suk MH. Relationship between depression and health-related quality of life in older Korean patients with chronic obstructive pulmonary disease. Journal of Clinical Nursing 2010; 19: 1307–1314. 31 Jo SA, Park MH, Jo I, Ryu SH, Han C. Usefulness of Beck Depression Inventory (BDI) in the Korean elderly population. International Journal of Geriatric Psychiatry 2007; 22: 218–223. 32 Kim JT, Shin DK. A study based on the standardization of the STAI for Korea. New Medical Journal 1978; 21: 69–75. 33 Spielberger CD. Anxiety; State-Trait Process: Stress and Anxiety. New York, NY, USA: Joan Wiley & Sons, 1975. 34 Ju HO, McElmurry BJ, Park CG, McCreary L, Kim M, Kim EJ. Anxiety and uncertainty in Korean mothers of children with febrile convulsion: Cross-sectional survey. Journal of Clinical Nursing 2011; 20: 1490–1497. 35 Luo YY. Effects of written plus oral information vs. oral information alone on precolonoscopy anxiety. Journal of Clinical Nursing 2013; 22: 817–827. 36 Kwon YC, Park J. Korean version of mini-mental state examination (MMSE-K) part I: Development of the test for the elderly. Journal of the Korean Neuropsychiatric Association 1989; 28: 125–135.
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37 Kang Y, Na DL, Hahn S. A validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients. Journal of Korean Neurological Assocication 1997; 15: 300–308. 38 WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363: 157–163. 39 Stosovic MD, Naumovic RT, Stanojevic M, Simic-Ogrizovic SP, Jovanovic DB, Djukanovic LD. Could the level of serum albumin be a method for assessing malnutrition in hemodialysis patients? Nutrition in Clinical Practice 2011; 26: 607–613. 40 Chaudhuri KR, Martinez-Martin P, Brown RG et al. The metric properties of a novel non-motor symptoms scale for Parkinson’s disease: Results from an international pilot study. Movement Disorders 2007; 22: 1901–1911. 41 Tsai AC, Chang MZ. Long-form but not short-form MiniNutritional Assessment is appropriate for grading nutritional risk of patients on hemodialysis: A cross-sectional study. International Journal of Nursing Studies 2011; 48: 1429–1435. 42 Battaglia S, Spatafora M, Paglino G et al. Ageing and COPD affect different domains of nutritional status: The ECCE study. The European Respiratory Journal 2011; 37: 1340– 1345. 43 Yoo SH, Kim JS, Kwon SU et al. Undernutrition as a predictor of poor clinical outcomes in acute ischemic stroke patients. Archives of Neurology 2008; 65: 39–43. 44 Fagerström C, Palmqvist R, Carlsson J, Hellström Y. Malnutrition and cognitive impairment among people 60 years of age and above living in regular housing and in special housing in Sweden: A population-based cohort study. International Journal of Nursing Studies 2011; 48: 863–871. 45 Gillette Guyonnet S, Abellan Van Kan G, Alix E et al. IANA (International Academy on Nutrition and Aging) Expert Group: Weight loss and Alzheimer’s disease. The Journal of Nutrition, Health & Aging 2007; 11: 38–48. 46 Leentjens AF, Dujardin K, Marsh L et al. Anxiety rating scales in Parkinson’s disease: Critique and recommendations. Movement Disorders 2008; 23: 2015–2025. 47 Nègre-Pagès L, Grandjean H, Lapeyre-Mestre M et al. Anxious and depressive symptoms in Parkinson’s disease: The French cross-sectionnal DoPaMiP study. Movement Disorders 2010; 25: 157–166. 48 Pachana NA, Egan SJ, Laidlaw K et al. Clinical issues in the treatment of anxiety and depression in older adults with Parkinson’s disease. Movement Disorders 2013; 28: 1930– 1934. 49 van der Kolk NM, King LA. Effects of exercise on mobility in people with Parkinson’s disease. Movement Disorders 2013; 28: 1587–1596. 50 Akdag I, Yilmaz Y, Kahvecioglu S et al. Clinical value of the malnutrition-inflammation-atherosclerosis syndrome
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for long-term prediction of cardiovascular mortality in patients with end-stage renal disease: A 5-year prospective study. Nephron. Clinical Practice 2008; 108: c99– c105. 51 Di Fiore F, Lecleire S, Pop D et al. Baseline nutritional status is predictive of response to treatment and survival in patients treated by definitive chemoradiotherapy for a locally advanced esophageal cancer. The American Journal of Gastroenterology 2007; 102: 2557–2563. 52 Baron M, Hudson M, Steele R, Canadian Scleroderma Research Group (CSRG). Is serum albumin a marker of malnutrition in chronic disease? The scleroderma paradigm. Journal of the American College of Nutrition 2010; 29: 144– 151. 53 Laky B, Janda M, Cleghorn G, Obermair A. Comparison of different nutritional assessments and body-composition measurements in detecting malnutrition among gynecologic
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cancer patients. American Journal of Clinical Nutrition 2008; 87: 1678–1685. 54 Isenring E, Cross G, Daniels L, Kellett E, Koczwara B. Validity of the malnutrition screening tool as an effective predictor of nutritional risk in oncology outpatients receiving chemotherapy. Supportive Care in Cancer 2006; 14: 1152– 1156. 55 Slee A, Birch D, Stokoe D. A comparison of the malnutrition screening tools, MUST, MNA and bioelectrical impedance assessment in frail older hospital patients. Clinical Nutrition. Published Online: May 02, 2014. doi: 10.1016/ j.clnu.2014.04.013. 56 Covinsky KE, Covinsky MH, Palmer RM, Sehgal AR. Serum albumin concentration and clinical assessments of nutritional status in hospitalized older people: Different sides of different coins? Journal of the American Geriatrics Society 2002; 50: 631–637.
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International Journal of Nursing Practice 2014; ••: ••–••
CLINICAL PAPER
Factors contributing to malnutrition in patients with Parkinson’s disease Sung R Kim RN PhD Assistant Professor, College of Nursing, Chonbuk National University, Jeonju, Korea
Sun J Chung MD PhD Associate Professor, Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
Sung-Hee Yoo RN PhD Assistant Professor, College of Nursing, Chonnam National University, Gwangju, Korea
Accepted for publication November 2014 Kim SR, Chung SJ, Yoo SH. International Journal of Nursing Practice 2014; ••: ••–•• Factors contributing to malnutrition in patients with Parkinson’s disease Our objective in this study was to evaluate the nutritional status and to identify clinical, psychosocial, and nutritional factors contributing to malnutrition in Korean patients with Parkinson’s disease. We used a descriptive, cross-sectional study design. Of 102 enrolled patients, 26 (25.5%) were malnourished and 27 (26.5%) were at risk of malnutrition based on Mini-Nutritional Assessment scores. Malnutrition was related to activity of daily living score, Hoehn and Yahr stage, duration of levodopa therapy, Beck Depression Inventory and Spielberger’s Anxiety Inventory scores, body weight, body weight at onset of Parkinson’s disease, and body mass index. On multiple logistic regression analysis, anxiety score, duration of levodopa therapy, body weight at onset of Parkinson’s disease, and loss of body weight were significant factors predicting malnutrition in Parkinson’s disease patients. Therefore, nutritional assessment, including psychological evaluation, is required for Parkinson’s disease patients to facilitate interdisciplinary nutritional intervention for malnourished patients. Key words: malnutrition, nutritional status, Parkinson’s disorder.
INTRODUCTION Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by dopaminergic neuronal loss.1 Patients with PD experience not only neurological motor symptoms including tremor, rigidity and bradykinesia but also health-related problems including depression, dementia, fatigue and constipation.2 Malnutrition has also been recognized as an important problem in PD patients.2,3 Correspondence: Sung-Hee Yoo, College of Nursing, Chonnam National University, 160 Baekseo-ro, Dong-gu, Gwangju 501-746, Korea. Email: [email protected] doi:10.1111/ijn.12377
Malnutrition is generally defined as an underweight BMI less than 18.50 kg/m2 in adults, according to the WHO classification.4 Previous studies have shown that PD patients have a lower body weight and body mass index (BMI) than healthy controls5–7 and also are at increased risk of developing malnutrition than age-matched controls.8 The prevalence of malnutrition in PD patients has been reported to range from 0 to 24%, and the malnutrition risk from 3 to 60% based on various nutritional parameters and definitions.8–11 Although the true extent of malnutrition in the PD population remains unclear, a not inconsiderable proportion of patients have a nutritional problem. © 2014 Wiley Publishing Asia Pty Ltd
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Nutritional assessment can be performed by assessing hematologic parameters such as albumin or prealbumin levels, anthropometric parameters such as body mass index (BMI) and body weight, and using nutritional assessment tools to assess dietary habits and general status.12 The mini-nutritional assessment (MNA) tool is one of the most widely used tools for nutritional assessment in clinical and research settings, because it can evaluate neuropsychological health and morbidity as well as anthropometric parameters and dietary habits, and has been validated in elderly patients.13 Therefore, nutritional assessment using this validated tool is essential for PD patients. Several factors might contribute to the high prevalence of malnutrition in PD patients. The first factor is related to motor symptoms. Bradykinesia, rigidity and gait disturbance cause some patients to experience difficulty in performing the activities of daily living (ADL) such as shopping, preparing and eating or swallowing food independently11,14 These types of disabilities might also be caused by levodopa-related motor complications such as dyskinesia.7,8,15 The second factor is related to psychosocial and cognitive factors. Depression, anxiety and dementia have been found to contribute to lowered food intake and weight loss in the elderly,16–18 and such symptoms are present at a higher incidence in PD patients than in controls.19,20 The last factor is related to medications that are used to manage PD, which can have side effects such as nausea, vomiting, loss of appetite and change of taste.8,21–23 Although multiple factors might contribute to malnutrition in PD patients, only a few of these factors have been examined in previous studies.5,7,9,10,23 Therefore, a comprehensive study examining all potential factors is needed to identity factors that significantly affect malnutrition in PD patients. Because malnutrition leads to poorer quality of life and worse health outcomes, such as higher mortality and prolonged length of hospital stay,8 evaluation of the nutritional status of PD patients and determination of the factors that contribute to malnutrition in PD patients are particularly relevant.
Aims Our aims in the current study were to describe the nutritional status of Korean patients with PD and to identify clinical, psychosocial and nutritional factors that predicted malnutrition in these patients. © 2014 Wiley Publishing Asia Pty Ltd
METHODS Design This was an observational study with a cross-sectional design.
Participants Subjects were recruited from a single tertiary university hospital in Seoul, Korea, and convenience sampling was used to select subjects. We included patients (i) who were over 20 years of age, (ii) who had PD based on the United Kingdom Parkinson’s Disease Society Brain Bank criteria as the primary diagnosis,24 and (iii) who had no other major health problems that could influence nutritional status such as active cancer, infection, inflammation, liver failure, or renal failure. We excluded patients with atypical Parkinsonism or secondary Parkinsonism. We enrolled a total of 102 patients in the current study.
Measurement of nutritional status Mini-Nutritional Assessment (MNA)
Nutritional status was measured using the MNA tool.25 The MNA is widely used to assess nutritional status and has been validated in various settings,13 including in elderly Korean patients.26 MNA is highly sensitive (96%) and specific (98%).13,27 The MNA is an 18-item questionnaire comprising anthropometric measurements, general status including swallowing function, dietary habits and self-perception of health and nutrition states.13 MNA scores range from 0 to 30 points; a higher score indicates a healthier nutritional status. Based on the final MNA scores, we classified the nutritional status of subjects ‘good’ (≥ 24 points), at ‘risk of malnutrition’ (17–23.5 points), or ‘malnourished’ (< 17 points).13,25 In this study, we defined patients with a good nutritional status and those at risk of malnutrition into the non-malnutrition group, whereas malnourished patients were defined to the malnutrition group.
Beck Depression Inventory (BDI) Depression was measured using the Beck Depression Inventory (BDI) with self-rating scales,28,29 which is one of the most commonly used tools for assessment of depression.30 Its reliability and validity have been validated in Korean patients.30,31 The BDI includes 21 questions and BDI scores range from 0 to 63. Higher scores indicate greater depression. Cronbach’s alpha value for the BDI was 0.90 in the current study.
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Spielberger’s Anxiety Inventory (SAI)
Data collection
Anxiety was measured using the Korean version of SAI.32,33 This is a well-established scale that has been used extensively in research and clinical practice.34,35 SAI includes 20 questions and SAI scores range from 20 to 80. Higher scores indicate greater anxiety. Cronbach’s alpha value for the SAI was 0.95 in the current study.
Between March and September 2012, we enrolled subjects who provided written informed consent. Subjects were informed of the aims and procedures of the current study by clinical nurse specialists. Patients who agreed to face-to-face interviews had their body weight and BMI measured and were administered a structured questionnaire that they completed together with a spouse or family member. Following the interviews, we confirmed patient information using medical records.
Mini-Mental State Examination (MMSE) Korean version of the MMSE (K-MMSE) was used to measure the cognitive function of patients.36 Sensitivity for detecting dementia with the K-MMSE has been reported to range from 0.70 to 0.83.37 K-MMSE scores range from 0 to 30. Higher scores indicate greater cognitive function.
Other variables We examined various clinical and nutritional variables using a structured questionnaire. The clinical characteristics of age of onset of PD, disease duration, duration of levodopa therapy, daily levodopa equivalent dose (LED), presence of motor fluctuation and dyskinesia, Hoehn and Yahr stage, and the Schwab and England ADL score were assessed. We assessed nutritional characteristics in detail including MNA; anthropometric parameters such as current body weight, body weight at onset of PD, weight loss and body mass index (BMI); biochemical parameters such as serum albumin and total protein; and presence of symptoms potentially affecting oral intake by PD medication such as constipation, nausea and vomiting, and dyspepsia. Current body weight and BMI were measured using an automatic fatness measuring system (G-tec, G-tec International, Uijungbu, South Korea). Subjects were assigned to one of four categories based on BMI values according to WHO recommendations for Asian populations.38 Weight loss was calculated as the difference between weight at onset of PD and current weight based on a review of electronic medical records. In addition, serum protein and albumin levels were assessed as biochemical parameters. Serum total protein was classified based on a cut-off of 6.2 g/dL and serum albumin on a cut-off of 3.5 g/ dL.39 We defined constipation as bowel action less than three times weekly,40 whereas we defined dyspepsia as gastrointestinal discomfort after taking PD medication based on subjective sensations of bloating, burning and gas in the bowels.22
Analysis Statistical analyses were conducted using SPSS version 20.0 (IBM SPSS Statistics, SPSS Inc., Chicago, IL). All data are expressed as numbers (percentages), means ± SD (standard deviations), or medians (ranges). To compare clinical, psychosocial and nutritional characteristics between the malnutrition and non-malnutrition group, we used the chi-square test, t-test or Mann–Whitney U-test as appropriate, and we used the Kolmogorov– Smirnov test to analyze the normality of continuous variables. To identify independent predictors of malnutrition, we performed multiple logistic regression analysis and calculated odds ratios (ORs) and 95% confidence intervals (CIs). Hosmer–Lemeshow test was used to assess goodness-of-fit. A two-tailed P value less than 0.05 was considered statistically significant.
Ethical considerations The current study was approved by the Institutional Review Board (IRB) of Asan Medical Center in Korea. We obtained written informed consent from all subjects or their legal representatives. Subjects were allowed to voluntarily withdraw their informed consent and their personal data were kept strictly confidential throughout the study.
RESULTS Demographic, clinical and psychosocial characteristics Of the 102 patients included in this study, 57 (55.9%) were female. Age ranged from 31 to 81 years (mean ± SD, 61.2 ± 10.1 years), and the median disease duration was 9 years (range, 1–24 years). Median Hoehn and Yahr stage was 2 (range, 0–5). Mean K-MMSE, BDI, and SAI scores were 25.7 ± 3.7, 14.7 ± 10.8, and 44.6 ± 11.1, respectively. © 2014 Wiley Publishing Asia Pty Ltd
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Nutritional status and characteristics Nutritional characteristics are summarized in detail in Table 1. Twenty-six (25.5%) of the 102 patients were categorized as malnourished whereas 27 (26.5%) patients were considered at risk of malnutrition based on the MNA results. Fifty-eight (56.8%) patients had experienced weight loss. Mean BMI of all PD patients was 23.2 ± 3.7 kg/m2 and seven patients (6.9%) were underweight (BMI < 18.5 kg/m2). Mean serum total protein and albumin levels were 6.6 ± 0.5 and 4.0 ± 0.4 g/dl (range, 5.3–7.7 g/dl and 3.0–5.9 g/dl), respectively.
Demographic, clinical, psychosocial, and nutritional characteristics related to malnutrition Differences in demographic, clinical, psychosocial, and nutritional characteristics between the two groups are presented in Table 2. Table 1 Nutritional characteristics of PD patients (n = 102) Variables
n (%) or mean ± SD
MNA Good status (≥ 24) Risk of malnutrition (17–23.5) Malnutrition (< 17) Body weight (kg) Body weight at disease onset (kg) Weight loss
21.4 ± 6.2 49 (48.0%) 27 (26.5%) 26 (25.5%) 58.7 ± 9.4 61.7 ± 9.4 58 (56.9%) 7.2 ± 4.7 23.2 ± 3.7 7 (6.9%) 44 (43.1%) 40 (39.2%) 11 (10.8%) 6.6 ± 0.5 21 (21.4%) 77 (78.6%) 4.0 ± 0.4 8 (7.8%) 90 (88.2%) 55 (53.9%) 12 (11.8%) 16 (15.7%)
BMI (kg/m2) < 18.5 18.5 ≤ BMI < 23 23 ≤ BMI < 27.5 ≥ 27.5 Protein (g/dl), (n = 98) < 6.2 ≥ 6.2 Albumin (g/dl), (n = 98) < 3.5 ≥ 3.5 Constipation Nausea & vomiting Dyspepsia
Range
4.5–29.0
40.5–83.0 42.0–93.8 1.0–20.0 14.4–34.2
5.3–7.7
3.0–5.9
PD, Parkinson’s disease; SD, standard deviation; MNA, mininutritional assessment; LED, levodopa equivalent dose; K-MMSE, Korean mini mental status examination; BMI, body mass index.
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In the malnutrition group, the age of onset of PD was significantly higher than that in the non-malnutrition group (55.6 ± 9.5 years vs. 49.6 ± 11.8 years, respectively) (P = 0.020), and Schwab and England ADL score was significantly lower in the malnutrition group (P < 0.001). However, the duration of levodopa therapy was significantly shorter in the malnutrition group (P = 0.038). Hoehn and Yahr stage was significantly correlated with the degree of malnutrition according to MNA score (P = 0.017). BDI and SAI scores were significantly higher in the malnutrition group than the non-malnutrition group (P = 0.009 and P < 0.001, respectively). Among nutritional parameters, body weight, body weight at disease onset, and BMI were significantly lower in the malnutrition group than the non-malnutrition group (P < 0.001, P = 0.009, and P < 0.001, respectively), whereas weight loss was higher in the malnutrition group than the non-malnutrition group (P < 0.001). Moreover, we found a significant correlation between malnutrition and nausea and vomiting (P = 0.048) and dyspepsia (P = 0.001) related to anti-PD medication. However, clinical factors such as sex, age, disease duration, daily levodopa equivalent dose (LED), motor fluctuation, dyskinesia, K-MMSE score, and levels of visceral proteins such as serum total protein and albumin were not related to malnutrition.
Factors predicting malnutrition in patients with PD Multiple logistic regression analysis revealed that anxiety score (OR = 1.124, 95% CI: 1.003–1.261, P = 0.044), duration of levodopa therapy (OR = 0.666, 95% CI: 0.460–0.962, P = 0.030), body weight at onset of PD (OR = 0.709, 95% CI: 0.544–0.925, P = 0.011), and weight loss (OR = 2.972, 95% CI: 1.366–6.464, P = 0.006) were significant factors predicting malnutrition (Table 3).
DISCUSSION The results of our study indicate that the prevalence of malnourishment in patients with PD is high, and that the psychological factor of anxiety, as well as duration of levodopa treatment, initial weight at diagnosis, and weight change after PD onset are independent predictors of malnutrition. A strength of our study is that we examined all potential contributing factors, including nutritional symptoms related with anti-PD medication,
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Table 2 Comparison of clinical, psychosocial, and nutritional characteristics between the malnutrition group and the non-malnutrition group Variables
Clinical characteristics Sex (Female) Age (years) Age at onset (years) Disease duration (years) Hoehn & Yahr stage 0 1 2 3 4 5 ADL (%) Duration of levodopa Therapy (years) LED (mg/day) Motor fluctuation No Yes, but not disabling Yes, disabling Dyskinesia No Yes, but not disabling Yes, disabling K-MMSE Psychosocial characteristics Depression Anxiety Nutritional characteristics Body weight (kg) Body weight at PD onset (kg) BMI (kg/m2) < 18.5 18.5 ≤ BMI < 23 23 ≤ BMI < 27.5 ≥ 27.5 Weight loss (kg) Protein (g/dl) Albumin (g/dl) Constipation Nausea & vomiting Dyspepsia
Malnutrition (n = 26)
Non-malnutrition (n = 76)
18 (69.2%) 64.5 ± 8.6 55.6 ± 9.5 8.7 ± 5.3
39 (51.3%) 60.1 ± 10.4 49.6 ± 11.8 10.6 ± 6.2
0 3 (11.5%) 10 (38.5%) 5 (19.2%) 5 (19.2%) 3 (11.5%) 63.9 ± 26.1 6.5 ± 4.4 614.1 ± 311.9 (n = 25) 9 (36.0%) 8 (32.0%) 8 (32.0%) (n = 25) 9 (36.0%) 11 (44.0%) 5 (20.0%) 24.4 ± 3.6
2 (2.6%) 5 (6.6%) 46 (60.5%) 16 (21.1%) 7 (9.2%) 0 84.7 ± 11.9 9.3 ± 6.1 788.5 ± 497.7 (n = 76) 22 (28.9%) 32 (42.1%) 22 (28.9%) (n = 76) 27 (35.5%) 34 (44.7%) 15 (19.7%) 26.1 ± 3.6
23.7 ± 10.6 52.3 ± 12.3
11.6 ± 9.1 42.2 ± 9.6
50.8 ± 6.3 57.5 ± 8.5 20.2 ± 2.6 6 (23.1%) 17 (65.4%) 3 (11.5%) 0 22 (84.6%) 7.4 ± 5.0 6.6 ± 0.4 4.0 ± 0.6 14 (53.8%) 6 (23.1%) 10 (38.5%)
61.4 ± 8.8 63.1 ± 9.3 24.3 ± 3.4 1 (1.3%) 27 (35.5%) 37 (48.7%) 11 (14.5%) 36 (47.4%) 3.1 ± 4.6 6.6 ± 0.5 3.9 ± 0.3 41 (53.9%) 6 (7.9%) 6 (7.9%)
t or z or χ2
P value
0.169 1.968 2.360 −1.338 13.463
0.112 0.052 0.020* 0.114† 0.017*
−3.930 −2.468 −1.643 0.849
< 0.001** 0.038†* 0.384† 0.654
0.004
0.998
−2.036
0.083†
4.682 3.654
0.009†* < 0.001**
−5.629 −2.655 −5.612 27.951
< 0.001** 0.009* < 0 .001** < 0.001**
10.957 3.992 −0.161 0.629 0.000 4.302 13.686
0.001* < 0.001†** 0.873 0.401† 0.993 0.048* 0.001**
* P < 0.05; ** P < 0.001; †Mann–Whitney U-test. ADL, activities of daily living; LED, levodopa equivalent dose; K-MMSE, Koreanmini mental status examination; BMI, body mass index.
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Table 3 Predictors of malnutrition in PD patients Variables
Odds ratio
95% CI
P value
Anxiety Duration of levodopa therapy Body weight at onset of PD Weight loss
1.124 0.666 0.709 2.972
1.003–1.261 0.460–0.962 0.544–0.925 1.366–6.464
0.044* 0.030* 0.011* 0.006*
* P < 0.05, Hosmer–Lemeshow goodness-of-fit test showed χ2 = 1.56 (P = .980). PD, Parkinson’s disease; CI, confidence interval.
clinical and psychological factors, and various nutritional parameters, to determine independent predictors of malnutrition. The prevalence of malnutrition was 25.5% and the risk of malnutrition was 26.5%, indicating that more than half of the subjects (52%) had nutritional problems. This result is largely consistent with those reported in previous studies based on MNA assessment.8,23 Our results indicate that PD patients are therefore more likely to be undernourished than hemodialysis patients (56.5%)41 or patients with other chronic diseases, such as chronic obstructive pulmonary disease (30.7%).42 This result highlights the necessity of performed nutritional assessments in all PD patients, given that patients at risk of malnutrition might become malnourished.43 We found that although K-MMSE scores were lower in the malnutrition group than in the non-malnutrition group (24.4 ± 3.6 vs. 26.1 ± 3.6, respectively), these scores were not statistically correlated with malnutrition, a finding similar to that reported in previous studies.7,8 However, because cognitive function has been shown to be associated with malnutrition in other populations,44 including Alzheimer’s disease patients,45 further studies are warranted to elucidate the correlation between cognitive function and nutritional status in patients with PD. Because PD is a neurodegenerative disorder, disease duration and disease severity are positively associated with each other, and both might be negatively associated with nutritional status. We found an association between malnutrition and a higher Hoehn and Yahr stage, as described in previous studies,6,8 but no association between malnutrition and PD duration. It is therefore unclear whether PD duration is associated with malnutrition, because previous studies have reported findings that conflict with © 2014 Wiley Publishing Asia Pty Ltd
those of the current study;6,7,23 further studies are needed to address this issue. Our results suggest that disease severity might be a more important factor than disease duration for predicting malnutrition in PD patients. It is well known that depression and anxiety are psychological factors associated with malnutrition,16,18 consistent with our results. In particular, we found that anxiety was an independent predictor of malnutrition after adjusting for all other factors in our study. Anxiety is a frequent emotional symptom in PD patients and is associated with motor symptoms, such as severe gait problems, dyskinesia, and off symptoms.46 Anxiety might worsen nutritional status through exacerbated neurologic symptoms and might affect appetite and food intake. Until recently, medication was the main treatment strategy in patients with high levels of anxiety.47 However, cognitive behavior therapy and exercise are gaining popularity as effective approaches to treat anxiety in PD patients.48,49 Thus, a multi-dimensional intervention strategy might alleviate anxiety and improve nutritional status in PD patients. Other nutritional parameters were also significantly different between the malnutrition and non-malnutrition groups. We used albumin as a biochemical parameter to investigate cross-sectional nutritional state in PD patients, not temporal changes, because albumin is known to be a good predictor of poor clinical outcomes in various diseases50,51 and has a longer half-life than prealbumin or transferrin. However, the albumin results did not reflect the MNA results in our study. This was consistent with previous findings that the serum albumin was not a reliable indicator for nutritional assessment in patients with chronic diseases.52 In addition, we also measured the BMI as an anthropometric parameter, but the proportion of underweight individuals according to the WHO BMI classification showed a discrepancy with the incidence of malnutrition according to the MNA. It was also consistent with previous findings performed in elderly patients and patients with cancer.53–55 We believe that these results might be due to each nutritional parameter (such as anthropometric, biochemical, and global assessment tools) reflecting a different clinical process.56 Nevertheless, the MNA considers various nutritional parameters including food intake by appetite or swallowing difficulty, anthropometric measurements including weight loss, and physical and mental functions, and malnutrition and nonmalnutrition groups classified by the MNA showed a difference in clinical and psychological factors reported in
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previous studies, symptoms affecting oral intake, and other nutritional factors excluding biochemical parameters. Therefore, we believe that the MNA is a useful tool for nutritional assessment in patients with PD as a chronic disease. We recommend assessing the nutritional state of PD patients using a validated tool and identifying risk factors for poor nutrition. Moreover, for patients at risk of malnutrition, as well as those with malnutrition, various individual interventions such as diet modification and nutritional supplements, education, stress relief, regulation of symptoms affecting poor oral intake, and dietary consultation should be considered in both research settings and clinical practice.
CONCLUSIONS Our study revealed that more than half of patients with PD had nutritional problems, and that anxiety, duration of levodopa therapy, body weight at onset of PD, and weight loss were factors that contributed significantly to the development of malnutrition in PD patients. Therefore, appropriate nutritional assessment, including psychological evaluation, should be conducted regularly in PD patients, and a multidisciplinary approach involving various nutritional interventions should be considered for undernourished patients.
ACKNOWLEDGEMENTS No research funding or any other financial support was received for this study. None of the authors have any conflicts of interest to declare.
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