Abstract
Objectives
People with Parkinson's disease (PD) are at higher risk of malnutrition due to PD symptoms and pharmacotherapy side effects. When pharmacotherapy is no longer effective for symptom control, deep-brain stimulation (DBS) surgery may be considered. The aim of this study was to assess the nutritional status of people with PD who may be at higher risk of malnutrition related to unsatisfactory symptom management with optimised medical therapy.
Design
This was an observational study using a convenience sample.
Setting
Participants were seen during their hospital admission for their deep brain stimulation surgery.
Participants
People with PD scheduled for DBS surgery were recruited from a Brisbane neurological clinic (n=15).
Measurements
The Patient-Generated Subjective Global Assessment (PG-SGA), weight, height and body composition were assessed to determine nutritional status.
Results
Six participants (40%) were classified as moderately malnourished (SGA-B). Eight participants (53%) reported previous unintentional weight loss (average loss of 13%). On average, participants classified as well-nourished (SGA-A) were younger, had shorter disease durations, lower PG-SGA scores, higher body mass (BMI) and fat free mass indices (FFMI) when compared to malnourished participants (SGA-B). Five participants had previously received dietetic advice but only one in relation to unintentional weight loss.
Conclusion
Malnutrition remains unrecognised and untreated in this group despite unintentional weight loss and presence of nutrition impact symptoms. Improving nutritional status prior to surgery may improve surgical outcomes.
Key words: Nutritional status, Parkinson's disease, deep brain stimulation, malnutrition, prevalence
Background
Malnutrition, or protein-energy under-nutrition, is associated with lower quality of life and poorer health outcomes (1., 2., 3.). Significantly lower body weight and body mass indices (BMI) (4) and higher rates of unintentional weight loss (5, 6) have been found in people with Parkinson’s disease (PD) compared to age-matched controls. More severe disease symptoms may result in higher amounts of weight loss and a greater risk of malnutrition (5., 6., 7.).
The clinical motor characteristics of PD can impair functional ability, (8) result in an inability to shop, cook, and feed independently and increase the risk of malnutrition (9). Many PD non-motor symptoms have been found to contribute to decreased food intake and subsequent weight loss in the elderly and in people with PD (6, 10, 11).
Side effects of anti-parkinsonian medication include nausea, vomiting and weight loss. Higher intakes of levodopa have been associated with lower BMIs (12) as well as ‘off’ periods which are associated with prolonged levodopa use resulting in more pronounced PD symptoms (13). Levodopa-induced dyskinesias can further impair function (14) and increase energy expenditure (15, 16).
When medical therapy is no longer effectively controlling PD symptoms, deep-brain stimulation (DBS) surgery may be considered (17). Uncontrolled symptoms and the side effects of increased medication, present in patients eligible for DBS surgery, may further increase the risk of malnutrition in this group.
Therefore, the aim of this pilot study was to assess the nutritional status of people with PD who may be at higher risk of malnutrition related to unsatisfactory symptom management with optimised medical therapy.
Methods
Twenty community-dwelling patients clinically diagnosed with idiopathic PD and scheduled for bilateral subthalamic nucleus deep-brain stimulation surgery (STN-DBS) between 30 March and 2 June 2010 were contacted from a neurology clinic in Queensland, Australia resulting in a convenience sample of 18 participants. Informed written consent was obtained as per protocol approved by the UnitingCare Health and Queensland University of Technology Human Research Ethics Committees.
Questionnaires, including demographics information; current medications; the Scale for Outcomes of Parkinson’s disease–Autonomic (SCOPA-AUT) (18) and Modified Constipation Assessment Scale (MCAS), (19) were completed prior to the data collection visit.
Participants were interviewed either prior to or during hospital admission. The Patient-Generated Subjective Global Assessment (PG-SGA) (20) was performed by a dietitian to assess nutritional status. The PG-SGA is a nutrition assessment tool previously used to assess nutritional status in community-dwelling elderly, (21) oncology patients, (22) and patients with chronic kidney disease (23). The PG-SGA consists of a medical history (recent changes in weight, nutrition impact symptoms (lack of appetite, nausea/vomiting, changes in smell and taste, constipation, dry mouth, mouth sores, early satiety, pain, difficulties swallowing), food intake, functional capacity, components of metabolic stress) and physical examination of fat and muscle stores. A number of the nutrition impact factors included in the PG-SGA, such as nausea, pain, lack of appetite, dysphagia, changes in smell and taste and constipation are also symptoms associated with PD. The PG-SGA provides an additive score with a higher score indicating a greater risk of malnutrition. It also includes the Subjective Global Assessment (SGA), a global rating of nutritional status, categorising patients as SGA-A (well nourished), SGA-B (moderately malnourished) or SGA-C (severely malnourished).
Body weight was measured to the nearest 0.1kg (Tanita HD-316, Japan) in light clothing, without shoes. All participants were able to stand independently; therefore standing height was measured to the nearest 0.1cm, without shoes. BMI was calculated (body weight(kg)/(height in metres)2). Mid-arm circumference (MAC) was measured at the mid-point between the acromion and the olecranon process on the non-dominant arm. Waist circumference was measured at the mid-point between the iliac crest and the lower rib. Body composition was assessed using bioelectrical impedance spectroscopy (BIS) (ImpediMed Imp SFB7, Brisbane, Australia) after removing all metal objects and lying supine for at least 5 minutes. The measurements were taken in the bioimpedance spectroscopy mode over a range of 4-1000 kHz, and the estimates of fat and fat free mass (kg, %) provided by the ImpediMed were used. Fat free mass index (FFMI) was calculated as fat mass(kg)/((height in metres)2).
The WHO BMI categories were initially used to classify participants as underweight (BMI<18.5kg/m2), normal weight (BMI 18.5-24.99kg/m2) and overweight/obese (BMI
≥25.0kg/m2). Participants were then categorised by BMI according to age. Participants younger than 65 years of age were classified according to the WHO BMI categories. Participants aged 65 years and older were classified as underweight with BMI <23.5kg/m2, normal weight with BMI 23.5-27.5kg/m2, and overweight/obese with BMI ≥27.5kg/m2 (24).
Statistical analysis was completed using SPSS Version 17 (SPSS Inc., Chicago, IL, USA). Variables were compared between SGA-A and SGA-B classifications only as no one was classified as SGA-C. Non-parametric Mann Whitney U tests were used to assess differences between groups due to the small sample size. Therefore all values are reported as median (range). Statistical significance was set at p<0.05.
Results
Eighteen of the twenty PD patients eligible agreed to participate but subsequently 2 withdrew due to anxiety relating to the procedure and 1 person withdrew due to spousal disapproval of research projects. Median age of the fifteen participants (11 male) was 68.0 years (range 42.0-78.0). Self-reported median length of disease was 6.75 (range 0.5 - 24.0) years while self-reported median length of time since symptom onset was 10.0 (range 2.0 - 30.0) years.
Using the World Health Organisation (WHO) BMI cut-offs, none of the participants were classified as underweight. Nine were in the normal weight range, four were overweight, and two were obese. Using the age-specific categories, five were underweight, six were in the normal weight range, and four were overweight or obese. Five participants (33%) had previously received dietetic advice from a dietitian or nutritionist: only one for unintentional weight loss.
Eight participants (53%) reported unintentional weight loss since PD diagnosis (Table 1) for an average 13% (range: 4-24%) of original body weight lost. Those who lost weight unintentionally were significantly older, (U=5.5,z=-2.62,p<.01) and had significantly lower BMIs, (U=4.0,z=-2.78,p<.01) and MACs, (U=2.0,z=-2.88,p<.01), than those who did not report losing weight unintentionally. Differences between the groups are reported in Table 1. The median waist circumference, fat free mass index (FFMI), SCOPA-AUT and MCAS scores were also lower in those with unintentional weight loss, but this did not reach significance. All of those with unintentional weight loss had BMIs that fell within the healthy weight range according to the WHO.
Table 1.
Characteristics of the 15 Parkinson’s disease participants compared between weight loser groups and between SGA classifications
| Unintentional | Weight Loss | SGA Classification | ||
|---|---|---|---|---|
| Yes (n=8) Median (range) | No (n=7) Median (range) | A (Well-nourished) (n=9) Median (range) | B (Moderately malnourished) (n=6) Median (range) | |
| Age (years) PD Duration (years) Years since symptom onset BMI (kg/m2) MAC (cm) Waist circumference (cm) FFMI (kg/m2) PG-SGA score SCOPA-AUT MCAS | 72.5 (64.0 - 78.0)* 8.0 (0.5 - 20.0) 10.0 (2.0 - 30.0) 22.8 (19.5 - 25.2)* 28.0 (23.0 - 31.6)* 84.5 (74.0 - 107.5) 16.3 (12.9 - 19.9) 4 (3 - 11) 21 (8 - 33) 4 (0 - 6) | 63.0 (42.0 - 69.0)* 5.5 (3.0 - 24.0) 10.0 (6.0 - 24.0) 28.6 (23.5 - 34.4)* 32.0 (28.6 - 34.0)* 103.0 (75.5 - 122.0) 19.2 (14.0 - 23.4) 5 (1 - 12) 27 (11 - 38) 5 (0 - 8) | 68.0 (42.0 - 78.0) 7.25 (3.0 - 24.0) 9.75 (6.0 - 24.0) 25.6 (22.2 - 34.4)* 29.5 (26.2 - 34.0) 96.0 (74.0 - 122.0) 19.2 (13.9 - 23.4) 4 (1 - 12) 23 (8 - 29) 2 (0 - 8) | 68.0 (48.0 - 77.0) 5.5 (0.5 - 20.0) 10.0 (2.0 - 30.0) 23.0 (19.5 - 25.2)* 28.5 (23.0 - 31.8) 84.5 (77.3 - 107.5) 17.7 (12.9 - 18.4) 6.5 (3 - 11) 23 (16 - 38) 4 (0 - 8) |
Statistically significant difference between the groups based on Mann Whitney U tests (p<0.05). Abbreviations: BMI=body mass index, FFMI=fat free mass index, MAC=mid-arm circumference, MCAS=Modified Constipation Assessment Scale, PD=Parkinson’s disease, PG-SGA=Patient-Generated Subjective Global Assessment, SCOPA-AUT=Scale for Outcomes of Parkinson’s Disease - Autonomic
Six participants (40%) were classified as moderately malnourished (SGA-B) (Table 1). BMIs for the SGA-B group were significantly lower than those for the SGA-A group, (U=10.5,z=-1.95,p=.05). The SGA-B group had a median BMI within the WHO healthy weight range, and the SGA-A group had a median BMI within the WHO overweight range. According to the age-specific categories, two of the SGA-A participants (22%) had BMIs in the underweight range, three (33%) were in the normal weight range, and four (44%) were overweight or obese while three of the SGA-B participants (50%) had BMIs in the underweight range and another three (50%) had BMIs in the normal weight range. Participants classified as SGA-A had larger mid-arm circumferences (MAC) and waist circumferences, higher median FFMI and lower PG-SGA scores than the SGA-B group. The SGA-A participants reported better bowel function on the MCAS than the SGA-B participants.
Of the nutrition impact symptoms listed on the PG-SGA, 12 of the participants listed at least one as affecting their food intake over the previous 2 weeks. Seven (58%) listed constipation. Early satiety, things tasting funny or having no taste, dry mouth and problems swallowing each affected 3 (25%) people while lack of appetite, diarrhoea, nausea, and lack of smell each affected 2 (17%) people.
Discussion
A higher percentage of the current sample in the current study was malnourished according to SGA classification than has been previously reported in people with PD when classified using a nutrition assessment tool (25, 26). In addition, the majority reported previous clinically significant unintentional weight loss resulting in significantly lower nutritional status parameters.
Protein-energy malnutrition is associated with a lower quality of life and poorer health outcomes. Our results demonstrate that the prevalence of malnutrition in this group is high with 40% of the participants classified as malnourished. Comparatively, on an international level, the prevalence of malnutrition in community-dwelling older adults is 3-11% (21, 27, 28) while the prevalence of malnutrition in Parkinson’s disease has been reported to be between 0-2% (25, 26). In addition, in the current study, 53% of the participants reported significant amounts of weight loss since diagnosis. In a previous study by Abbott, et al (1992) (29), 52% of participants reported experiencing unintentional weight loss, similar to the percentage found in the current study, nearly 20 years later. As with other at-risk groups, malnutrition remains under-recognised and untreated in people with PD despite the fact that unintentional weight loss and low body weights have been reported for decades.
The increasing global prevalence of overweight and obesity may contribute to the lack of recognition of malnutrition. Historically BMI has been the tool of choice to identify health risks based on body weight. BMI is a measure of body size or mass and alone is not sensitive enough to recognise small yet clinically-significant weight loss (30) where the weight loss may result in significant loss of lean body mass but does not result in a BMI classification change. People can be at risk of malnutrition or malnourished and be classified as overweight or obese according to BMI (sarcopenic obesity). Nor can BMI detect changes in nutrition impact symptoms which may lead to weight loss. Therefore, it is important to take into account recent weight loss, loss of appetite and changes in eating habits when identifying someone at risk of malnutrition. The PG-SGA as a nutrition assessment tool does take into account weight loss, changes in food intake and functional status. It also captures the nutrition impact symptoms that are present in Parkinson’s disease such as nausea, pain, lack of appetite, dysphagia, changes in smell and taste and constipation.
Research to date has focused on how DBS affects weight post-surgery, particularly weight gain. This is the first study to report nutritional status prior to undergoing DBS. Not surprisingly, the rate of malnutrition in this group is higher than that reported previously (0-2%) (25, 26) for people with PD; however, given the small sample size, this may not generalise to the entire PD population eligible for DBS. This could also be due to the fact that different nutrition assessment tools have been used.
Also, due to the small sample size, statistically significant differences between the groups could not be established despite the fact that trends were identified. If a similar study were to be carried out in a larger sample, those differences may become statistically significant.
Screening can and should occur for everyone who is at an increased risk of malnutrition using simple tools such as the Malnutrition Screening Tool (MST) (31) or the revised Mini Nutritional Assessment Short Form (MNA-SF) (32) which require minimal training and are widely available. If a person is screened at risk of malnutrition, appropriate referrals can be made to nutrition health care professionals for a full assessment and any subsequent nutrition care. Ensuring adequate nutritional status prior to surgery may improve outcomes following the surgery.
Conclusions
The current study highlights the fact that malnutrition is more prevalent in this group of people with PD eligible for surgery than it is in the wider PD population and also in community-dwelling adults. However, this has gone largely unrecognised. The relationships between appropriate nutrition care, positive health outcomes and lower health care costs in older adults have been well established (33). Nutrition support in malnourished patients undergoing various forms of surgery results in improved surgical outcomes. While the effects on surgeries such as DBS surgery have not been studied, it is possible that improving nutritional status prior to DBS may improve post-surgery outcomes.
Competing interests: Participants were recruited from Professor Silburn’s neurology clinic. There are no other conflicts of interest to report for any of the authors.
Acknowledgments
We thank all of the participants for their time in this study at a rather stressful time. We also thank the staff of Neurosciences Queensland for their help in recruitment and scheduling.
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