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Abstract

Background:

In Parkinson’s disease (PD) patients, the factors related to weight loss remain unclear.

Objective:

To investigate determinants of low body mass index (BMI) in PD patients.

Methods:

We identified factors associated with low BMI in PD patients in a multicenter case-control study. A total of 435 PD patients and 401 controls were included.

Results:

The mean BMI was significantly lower in PD patients than in controls (22.0±3.4 kg/m² vs. 25.4±4.3 kg/m²), with an adjusted odds ratio (AOR) of 3.072 (95% CI, 2.103–4.488; p < 0.001) for low BMI (<22 kg/m²) in PD. Compared to the high-BMI PD group (>22 kg/m²), the low-BMI PD group (<22 kg/m²) had more women; a longer disease duration; higher revised Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) II and IV scores; an increased levodopa equivalent dose (LED); and increased constipation, visual hallucination, dysphagia, dyskinesia and wearing off rates. There were no between-group differences in depression, anhedonia, apathy, sleep problems and daytime sleepiness. Multivariable analysis showed that visual hallucination (AOR, 2.408; 95% CI, 1.074–5.399; p = 0.033) and the MDS-UPDRS IV (AOR, 1.155; 95% CI, 1.058–1.260; p = 0.001) contributed to low BMI after controlling for clinical factors. In a second model, visual hallucination (AOR, 2.481; 95% CI, 1.104–5.576; p = 0.028) and dyskinesia (sum of the MDS-UPDRS 4.3–4.6) (AOR, 1.319; 95% CI, 1.043–1.668; p = 0.021) significantly contributed to low BMI.

Conclusion:

PD patients were 3 times more likely than healthy controls to have a low BMI. Motor complications, particularly dyskinesia, and visual hallucination were significantly associated with low BMI in PD patients.

Keywords

Parkinson’s disease body mass index visual hallucination dyskinesia motor complication

INTRODUCTION

In patients with Parkinson’s disease (PD), body weight fluctuates during the course of the disease, reflecting various factors, such as dysphagia, constipation, parkinsonism and other nonmotor symptoms [1, 2]. Patients with PD generally have a lower body weight than age-matched controls [3, 4]. Weight loss can precede the diagnosis of PD and worsens the symptoms related to parkinsonism and motor complications due to the increased energy expenditure [2]. In addition, appetite-regulating hormones such as ghrelin and leptin can be altered in PD patients and may play a role in body weight control [5]. Interestingly, a correlation between weight loss and reduced dopamine transporter activity in the striatum has been reported [6, 7]. In contrast, dopamine-agonist therapy [8] or deep-brain stimulation has been shown to be related to weight gain [9].

The determinants of weight loss can be different in the different stages of PD, and weight loss can have different clinical implications for each patient. However, as lower body weight can interfere with patients’ functional ability and daily activities [1], a better characterization of the determinants of lower body weight in PD patients is imperative. In this study, we analyzed the factors contributing to body mass index (BMI) in patients with PD in a multicenter case-control study.

METHODS

This study was conducted in accordance with the Declaration of Helsinki. The study was approved by the institutional review boards of the participating facilities, and written informed consent was obtained from all participants who were enrolled in the study. We performed a multicenter study, including 8 university hospitals in the Kanto region of Japan, to evaluate the nonmotor symptoms of PD patients between September 2014 and April 2016 [10 –12]. The Kanto region comprises 7 prefectures and includes the capital (Tokyo) and the greater Tokyo area, with an approximate population of 42.6 million, accounting for one-third of the entire Japanese population according to the 2010 Population Census of Japan, Preliminary Counts of the Population and Households.

Subjects

Among an initial sample of 490 patients with PD, 435 patients with PD (197 men/238 women; age, 69.8±7.8 years) and 401 age-matched controls (187 men/214 women; age, 69.2±8.6 years) were included. PD patients in our study were consecutively recruited from the participating facilities. The exclusion criteria included individuals with dementia, as defined by a Mini-Mental State Examination (MMSE) score <24 (n = 42) and individuals who were unable to answer the questionnaire or those with incomplete data of clinical information or questionnaires (n = 13). Control subjects with no history of any neurological or psychiatric diseases were recruited from among the medical staff and their friends and family.

Clinical assessment

All participants completed questionnaires on their habits and lifestyle factors, including weight and height. BMI was calculated by dividing the weight (kg) by the square of the height (m). All patients were assessed by board-certified neurologists who had experience with movement disorders. A diagnosis of PD was made according to the UK Brain Bank Clinical Diagnostic Criteria after excluding drug-induced parkinsonism, vascular parkinsonism or atypical parkinsonian syndrome with neurological examinations, a clinical history and brain imaging [13]. Disease severity was evaluated with Hoehn and Yahr (HY) staging. All PD patients were evaluated based on the Japanese version of the MDS-UPDRS part II (motor experiences of daily living), III (motor examination) and IV (motor complications) [14]. For the motor examination, 90.1% of the patients were evaluated in the on state. We divided the MDS-UPDRS part IV into a “dyskinesia score”, defined as the sum of MDS-UPDRS 4.1 and 4.2, and a “wearing off score”, defined as the sum of MDS-UPDRS 4.3, 4.4, 4.5 and 4.6. Dysphagia was evaluated with the MDS-UPDRS part II subitem 2.3 “Chewing and swallowing”. Freezing of gait was assessed by the MDS-UPDRS part III subitem 3.11 “Freezing of gait”. The clinical motor subtypes were defined using the MDS-UPDRS parts II and III: the tremor-dominant (TD) subtype (ratio ≥1.5), postural instability and gait disturbances (PIGD) subtype (ratio ≤1), and intermediate subtype (ratios >1.0 and <1.5), as described elsewhere [15]. The levodopa equivalent dose (LED) was calculated based on the previously reported conversion factors [16].

Assessment of nonmotor symptoms

The presence of visual hallucinations and falls during the past year were determined during interviews. Constipation was defined as having fewer than three bowel movements per week. Anhedonia was assessed by the Snaith-Hamilton Pleasure Scale-Japanese version (SHAPS-J) [17]. Depression was determined with the semistructured Mini International Neuropsychiatric Interview (MINI), which is based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition [18]. Apathy was defined as an apathy scale score of >16 [19]. The PD Sleep Scale (PDSS)-2, consisting of 15 individual items for PD-related nocturnal problems, was used to evaluate sleep problems [20]. Daytime sleepiness was measured by using the Japanese version of the Epworth Sleepiness Scale (ESS) [21]. The Japanese version of the REM Sleep Behavior Disorder (RBD) Screening Questionnaire (RBDSQ) was used for the evaluation of probable RBD [22].

Statistical analysis

Student’s t tests or Mann-Whitney U tests were used where appropriate to compare the continuous variables, and chi-square test was used to compare the categorical variables between PD patients and healthy controls and between the low-BMI and high-BMI groups. First, the relative risks of low BMI in PD patients compared with controls were determined with univariate and multivariable analyses (Table 2). Next, to determine the factors associated with low BMI in patients with PD, we performed a univariate logistic regression analysis with the clinical parameters in Table 3 that had a p value <0.2 (Table 4, model 1) and a multivariable logistic regression analysis that predicted low BMI with the parameters in model 1 (sex, PD duration, de novo vs treated, LED, dopamine agonist use, hallucination, dysphagia, freezing of gait, constipation, HY stage, TD/PIGD ratio, MDS-UPDRS II and MDS-UPDRS IV scores) plus age (model 2). In model 3, the dyskinesia scores (sum of the MDS-UPDRS 4.1–4.2) and wearing off scores (sum of the MDS-UPDRS 4.3–4.6) were used in place of the MDS-UPDRS IV scores. Two-tailed p values of <0.05 were considered statistically significant. IBM SPSS Statistics software version 25.0 (IBM SPSS, Inc., Tokyo, Japan) was used for statistical analyses.

Table 1

Characteristics of patients with Parkinson’s disease and controls

	N	PD patients		N	Control group		p value^a
Demographic data
Sex, female, n, %	435	238	54.7	401	214	53.4	0.696
Age, yr, m, SD	435	69.3	7.9	401	69.2	8.6	0.947
Caffeine, cups per day^b, n, %	433	2.5	2.0	401	2.5	2.0	0.667^b
Alcohol intake, n, %	435	196	45.1	401	217	54.1	0.009
Smoking, n, %	435	35	8.0	401	71	17.7	<0.001
Clinical parameters
BMI, kg/m², m, SD	435	22.0	3.4	401	25.4	4.3	<0.001
Depression, n, %	435	60	13.8	401	23	5.7	<0.001
Falls during the past year, n, %	435	136	31.3	401	16	4.0	<0.001
Constipation, n, %	435	292	76.0	401	92	22.9	<0.001
Apathy, n, %	435	203	46.7	401	91	22.7	<0.001
Anhedonia, n, %	435	105	24.1	401	42	10.5	<0.001
PDSS-2 total, score, m, SD	435	15.4	9.3	401	9.2	6.0	<0.001^b
ESS total, score, m, SD	435	8.4	5.2	401	6.1	3.5	<0.001^b
RBDSQ total, score, m, SD	435	3.9	2.8	401	1.6	1.8	<0.001^b
PD patient clinical parameters
PD duration, yr, m, SD	435	7.3	5.3	n/a
De novo, n, %	435	34	7.8	n/a
LED, mg/day, m, SD	435	487.3	359.7	n/a
Dopamine agonists, n, %	435	226	52.0	n/a
Visual hallucination, n, %	435	40	9.2	n/a
Dyskinesia score, m, SD	435	0.5	1.3	n/a
Wearing off score, m, SD	435	1.5	2.5	n/a
2.3 Chewing and swallowing score, m, SD	431	0.5	0.9	n/a
3.11 Freezing of gait score, m, SD	435	0.4	0.9	n/a
Motor subtypes, n, %				n/a
Tremor dominant	435	157	36.1	n/a
Intermediate		44	10.1	n/a
PIGD		234	53.8	n/a
HY stage, score, m, SD	433	2.3	0.7	n/a
MMSE score, m, SD	435	28.0	2.0	n/a
TD/PIGD ratio, m, SD	416	1.4	2.1	n/a
MDS-UPDRS II score, m, SD	435	12.6	9.0	n/a
MDS-UPDRS III score, m, SD	435	28.6	13.2	n/a
MDS-UPDRS IV score, m, SD	435	2.0	3.3	n/a

Data are represented as the n (number or %) or the mean±SD. Statistically significant values (p < 0.05) are shown in bold. PD, Parkinson’s disease; LED, levodopa equivalent dose; BMI, body mass index; PIGD, postural instability and gait disturbances; PDSS-2, PD Sleep Scale-2; ESS, Epworth Sleepiness Scale; RBDSQ, RBD Screening Questionnaire; HY, Hoehn and Yahr; MMSE, Mini-Mental State Examination; TD, tremor dominant; MDS-UPDRS, Movement Disorder Society Unified PD Rating Scale. Dyskinesia score = sum of MDS-UPDRS 4.1 and 4.2; Wearing off score = sum of MDS-UPDRS 4.3, 4.4, 4.5 and 4.6. ^a: Using a student’s t test or Chi-square test. ^b: Using a Mann-Whitney test.

Table 2

Relative risk of low BMI in patients with Parkinson’s disease compared with controls

	Univariate analysis			Multivariable analysis^a
	Crude OR	95% CI	p value	Adjusted OR	95% CI	p value
Sex, female vs male	1.586	1.190–2.115	0.002	1.540	1.110–2.134	0.010
Age, yr	1.027	1.009–1.046	0.004	1.023	1.002–1.044	0.028
Caffeine, cups per day^b, m, SD	1.022	0.958–1.091	0.504	1.025	0.955–1.100	0.490
Alcohol intake, n, %	0.628	0.472–0.836	0.001	0.787	0.575–1.077	0.134
Smoking, yes vs no	0.638	0.406–1.003	0.052	1.100	0.654–1.850	0.719
Depression, yes vs no	1.499	0.948–2.369	0.083	1.019	0.587–1.768	0.948
Falls during the past year, yes vs no	2.054	1.439–2.931	<0.001	1.150	0.770–1.718	0.494
Constipation, yes vs no	2.238	1.678–2.985	<0.001	1.299	0.923–1.828	0.134
Apathy, yes vs no	1.387	1.034–1.086	0.029	0.962	0.677–1.367	0.827
Anhedonia, yes vs no	1.430	0.995–2.055	0.053	1.072	0.695–1.654	0.753
PDSS-2 score	1.033	1.016–1.051	<0.001	1.001	0.979–1.022	0.949
ESS total score	1.040	1.009–1.072	0.013	1.018	0.981–1.056	0.340
RBDSQ total score	1.109	1.051–1.171	<0.001	0.990	0.924–1.060	0.774
PD patients vs control cases	3.633	2.680–4.926	<0.001	3.072	2.103–4.488	<0.001

Statistically significant values (p < 0.05) are shown in bold. Sex (male = 0, female = 1); PDSS-2, PD Sleep Scale-2; ESS, Epworth Sleepiness Scale; RBDSQ, RBD Screening Questionnaire;. a: All parameters were entered in a multivariable logistic regression analysis as follows; sex, age, caffeine, alcohol, smoking, depression, falls during the past year, constipation, apathy, anhedonia, PDSS-2, ESS and RBDSQJ score. b: Missing values (n = 2) were excluded.

Table 3

Demographic and clinical parameters of the patients with Parkinson’s disease in the low- and high-BMI groups

	Body Mass Index (BMI)
	N	Low BMI (Less than 22 kg/m²)		N	High BMI (More than 22 kg/m²)		p value^a
Demographic data
Sex, female, n, %	215	131	60.9	220	107	48.6	0.010
Age, yr, m, SD	215	69.7	8.0	220	68.8	7.7	0.220
Caffeine, cups per day, m, SD	213	2.5	2.0	220	2.4	2.0	0.302^b
Alcohol intake, n, %	215	85	39.5	220	111	50.5	0.022
Smoking, n, %	215	14	6.5	220	21	9.5	0.245
Clinical parameters
PD duration, yr, m, SD	215	7.9	5.2	220	6.8	5.3	0.008^b
De novo, n, %	215	13	6.0	220	21	9.5	0.174
LED, mg/day, m, SD	215	548.1	377.8	220	427.8	331.3	<0.001^b
Dopamine agonists, n, %	215	121	56.3	220	105	47.7	0.074
Deep-brain stimulation, n, %	215	4	1.9	220	4	1.8	1.000
Depression, n, %	215	34	15.8	220	26	11.8	0.227
Falls during the past year, n, %	215	73	34.0	220	63	28.6	0.232
Hallucination, n, %	215	29	13.5	220	11	5.0	0.002
2.3 Chewing and swallowing^c score, m, SD	213	0.6	0.9	218	0.4	0.8	0.008^b
3.11 Freezing of gait score, m, SD	215	0.5	1.0	220	0.4	0.8	0.117^b
Motor subtypes, n, %
Tremor dominant	215	74	34.4	220	83	37.7
Intermediate		19	8.8		25	11.4	0.427
PIGD		122	56.7		112	50.9
Constipation, n, %	215	154	71.6	220	138	62.7	0.048
Apathy scale ≥16, n, %	215	98	45.6	220	105	47.7	0.654
Anhedonia, n, %	215	51	23.7	220	54	24.5	0.841
PDSS-2 score, m, SD	215	16.0	9.7	220	14.8	9.0	0.215^b
ESS total score, m, SD	215	8.7	5.3	220	8.2	5.1	0.264^b
RBDSQ total score, m, SD	215	3.9	2.8	220	3.9	2.8	0.807^b
HY stage^c, m, SD	213	2.4	0.8	220	2.3	0.7	0.056
MMSE score, m, SD	215	27.9	2.1	220	28.0	2.0	0.488
TD/PIGD ratio^c, m, SD	207	1.2	1.5	209	1.7	2.5	0.130^b
MDS-UPDRS II score, m, SD	215	13.9	9.1	220	11.4	8.7	0.003
MDS-UPDRS III score, m, SD	215	29.1	13.9	220	28.1	12.7	0.451
MDS-UPDRS IV score, m, SD	215	2.8	3.9	220	1.3	2.5	<0.001^b
Dyskinesia score, m, SD	215	0.8	1.6	220	0.3	0.8	<0.001^b
Wearing off score, m, SD	215	2.0	2.8	220	1.0	2.0	<0.001^b

Data are represented as the n (number or %) or the mean±SD. Statistically significant values (p < 0.05) are shown in bold. PD, Parkinson’s disease; LED, levodopa equivalent dose; BMI, body mass index; PIGD, postural instability and gait disturbances; PDSS-2, PD Sleep Scale-2; ESS, Epworth Sleepiness Scale; RBDSQ, RBD Screening Questionnaire; HY, Hoehn and Yahr; MMSE, Mini-Mental State Examination; TD, tremor dominant; MDS-UPDRS, Movement Disorder Society Unified PD Rating Scale. Dyskinesia score = sum of MDS-UPDRS 4.1 and 4.2; Wearing off score = sum of MDS-UPDRS 4.3, 4.4, 4.5 and 4.6. a: Using Student’s t-test or chi-square test. b: Using a Mann-Whitney test. c: Missing values (Chewing and swallowing = 4, HY stage = 2, and TD/PIGD ratio = 19) were excluded.

Table 4

Predictors of low BMI in patients with Parkinson’s disease

	Model 1^a			Model 2^b			Model 3^c
Clinical parameters	Crude OR	95% CI	p value^a	Adjusted OR	95% CI	p value	Adjusted OR	95% CI	p value
Sex, female vs male	1.647	1.125–2.410	0.010	1.399	0.907–2.159	0.129	1.399	0.906–2.160	0.130
Alcohol intake, yes vs no	0.633	0.433–0.925	0.018	0.676	0.433–1.055	0.085	0.677	0.433–1.057	0.086
PD duration, yr	1.040	1.003–1.079	0.032	0.964	0.914–1.016	0.168	0.958	0.907–1.011	0.115
De novo, yes vs no	0.610	0.297–1.251	0.178	0.807	0.351–1.856	0.614	0.781	0.339–1.800	0.562
LED, mg/day	1.001	1.000–1.002	0.001	1.000	0.999–1.001	0.630	1.000	0.999–1.001	0.638
Dopamine agonists, yes vs no	1.410	0.966–2.057	0.075	1.049	0.653–1.684	0.843	1.061	0.661–1.705	0.805
Hallucination, yes vs no	2.962	1.440–6.096	0.003	2.408	1.074–5.399	0.033	2.481	1.104–5.576	0.028
2.3 Chewing and swallowing^d score	1.313	1.043–1.653	0.020	1.139	0.841–1.541	0.400	1.134	0.836–1.537	0.419
3.11 Freezing of gait score	1.187	0.957–1.473	0.119	0.980	0.741–1.296	0.886	0.984	0.742–1.303	0.908
Constipation, yes vs no	1.500	1.002–2.245	0.049	1.223	0.775–1.931	0.387	1.221	0.773–1.928	0.393
HY stage^d	1.298	0.992–1.698	0.058	0.950	0.645–1.397	0.793	0.932	0.632–1.374	0.722
TD/PIGD ratio^d	0.881	0.792–0.979	0.019	0.933	0.838–1.040	0.210	0.937	0.841–1.044	0.239
MDS-UPDRS II score	1.033	1.011–1.055	0.004	1.001	0.966–1.037	0.961	1.004	0.969–1.041	0.811
MDS-UPDRS IV score	1.157	1.084–1.235	<0.001	1.155	1.058–1.260	0.001
Dyskinesia score, m, SD	1.435	1.193–1.726	<0.001				1.319	1.043–1.668	0.021
Wearing off score, m, SD	1.185	1.089–1.289	<0.001				1.100	0.981–1.234	0.102

Statistically significant values (p < 0.05) are shown in bold. PD, Parkinson’s disease; LED, levodopa equivalent dose; HY, Hoehn and Yahr; TD, tremor dominant; PIGD, postural instability and gait disturbances; MDS-UPDRS, Movement Disorder Society Unified PD Rating Scale. Dyskinesia score = sum of MDS-UPDRS 4.1 and 2; Wearing off score = sum of MDS-UPDRS 4.3, 4.4, 4.5 and 4.6. a: Model 1 used a univariate logistic regression analysis with the clinical parameters in Table 3 with a p value <0.2. b: Model 2 used a multivariable logistic regression analysis with all variables of Model 1 including the total MDS-UPDRS IV score after adjusting for age. c: Model 3 used a multivariable logistic regression analysis with all variables of Model 1, including the subscale of the MDS-UPDRS IV score (dyskinesia and wearing off score) after adjusting for age. d: Missing values (Chewing and swallowing = 4, HY stage = 2, and TD/PIGD ratio = 19) were excluded.

RESULTS

The demographics and clinical characteristics of the PD patients and controls are shown in Table 1. The BMI was significantly lower in PD patients than in controls (22.0±3.4 kg/m² vs. 25.3±4.7 kg/m², p < 0.001). The rates of alcohol consumption (45.1% vs. 54.1%, p = 0.009) and smoking (8.0% vs. 17.7%, p < 0.001) were lower in PD patients than in controls. Caffeine consumption was similar between PD patients and controls. Depression, falls during the past year, constipation, apathy, anhedonia, sleep disturbances, daytime sleepiness and RBD symptoms were more prevalent in PD patients than in controls. The mean PD duration was 7.3±5.3 years, and the mean HY stage was 2.3±0.7. PD patients with visual hallucinations had significantly lower scores on the MMSE than did patients without visual hallucinations (27.2±2.1 vs. 28.1±2.0, p = 0.009). Table 2 shows the relative risk of low BMI in patients with PD compared with controls. The unadjusted odds ratio of low BMI (<22 kg/m²) was 3.633 (95% CI, 2.680–4.926; p < 0.001) in PD patients compared with controls. After controlling for clinical parameters, such as sex, age, alcohol intake, falls during the past year, constipation, apathy, PDSS-2 score, ESS score and RBDSQ score, the adjusted odds ratio of low BMI was 3.072 (95% CI, 2.103–4.488; p < 0.001) in PD patients compared with controls.

Among all of the PD patients, 92.2% received dopaminergic treatment, 52.0% received dopamine agonists and only 1.8% underwent deep-brain stimulation. PD patients were placed into 2 groups based on the median BMI value (22 kg/m²) (Table 3). Compared with the high-BMI group (>22 kg/m²), the low-BMI group (<22 kg/m²) had more women; a longer disease duration; higher scores on the MDS-UPDRS parts II and IV; an increased LED; and increased rates of constipation, hallucination, dysphagia, dyskinesia and wearing off. There was no difference in the MDS-UPDRS part III score or the rates of depression, anhedonia, apathy, sleep problems and daytime sleepiness between the 2 groups. In a multivariable regression model for the prediction of low BMI, visual hallucination and the MDS-UPDRS part IV score were identified as significant determinants of low BMI after adjusting for various clinical factors (Table 4, model 2). In a second model, when the MDS-UPDRS part IV was replaced with the dyskinesia score and the wearing off score, the determinants for low BMI were visual hallucination and the dyskinesia score (Table 4, model 3).

DISCUSSION

We showed that the BMI was significantly lower in patients with PD than in age- and sex-matched controls, which is in line with previous observations [3, 4]. We also demonstrated that PD patients were 3 times more likely than healthy controls to have a low BMI. In a two-group comparison based on the median BMI of the PD patients, female sex; longer disease duration; higher scores on the MDS-UPDRS part II and MDS-UPDRS part IV; and increased LED, constipation, hallucination, dysphagia, dyskinesia and wearing off were associated with low BMI. The motor aspects of the experiences of daily living (MDS-UPDRS II) were significantly impaired in the low-BMI group compared to the high-BMI group, similar to a previous study that showed that lower body weight contributed to patients’ functional ability [1]. In a study consisting of a large sample of early-treated PD patients, PD patients lost 0.6 kg per year on average, and higher age, baseline weight, female sex, higher baseline UPDRS scores, greater postural instability, dysphagia, lower cognitive scores and baseline levodopa use were the predictors for weight loss [23]. The results of that study were similar to our results except for the PIGD subtype, which was not related to low BMI in our study. The PIGD subtype has been associated with rapid progression [24], impaired cognition, autonomic and sensory symptoms, hyposmia and RBD [25]. Body weight loss has been correlated with increased energy expenditure as the disease progresses [4], which may be a result of the impact of increased motor symptoms, such as rigidity and rest tremor, and nonmotor symptoms over the course of PD. However, in our study, the MDS-UPDRS part III, psychiatric symptoms, such as depression, anhedonia and apathy, and sleep-related symptoms, such as daytime sleepiness, PD-related sleep problems and RBD, were not related to low BMI.

In a multivariable logistic regression analysis, we identified visual hallucination and the MDS-UPDRS part IV (motor complication) as the significant determinants for low BMI after adjusting for relevant clinical parameters. Furthermore, a second multivariable logistic regression model, in which the MDS-UPDRS part IV was divided into dyskinesia and wearing off scores, showed that visual hallucinations and the dyskinesia score were strong predictors for low BMI. Increased energy expenditure due to excessive involuntary movements in patients with dyskinesia likely resulted in weight loss. Bachmann et al. [26] also described an association with decreased body weight and the daily levodopa dosage per kg in PD patients with dyskinesias.

Cognitive impairment and visual hallucinations have been associated with nursing home placement [27] and weight loss [28]. In agreement with our study, Uc et al. [29] reported that the emergence of visual hallucinations was an important factor for weight loss in PD patients. Appetite can be altered in patients with visual hallucinations and may be related to concomitant cognitive impairment or late-stage complications, including infection and bone fracture. Changes in cognition related to visual hallucination may have a role in low BMI in our study. In fact, although patients with dementia, defined as MMSE < 24, were excluded in our study, patients with visual hallucinations showed significantly lower scores on the MMSE than patients without visual hallucinations. Using a cut-off of MMSE score of <26 [30] or applying more sensitive tools such as Montreal Cognitive Assessment may have included more patients with dementia.

Age-related changes in the hypothalamus in response to peripheral stimuli are involved in weight loss in elderly individuals [31]. In patients with Alzheimer disease, hypothalamic feeding dysregulation is involved in the loss of appetite and reduced food intake [32], whereas BMI was found to be negatively correlated with hippocampal volume in other studies [33]. In a pathological study of PD patients, Lewy bodies were found in more than 80% of the tuberomammillary nucleus and the lateral and posterior hypothalamic nuclei, which are involved in the control of feeding, temperature and wakefulness, suggesting that impaired hypothalamic feeding control may affect patients with PD, especially patients with advanced-stage PD [34]. Additionally, the nucleus accumbens is a key component the of reward circuity [35]. The limbic system is typically involved in late-stage PD patients, and reduced reward processing is one of the factors related to body weight loss [36]. In our study, however, the rate of anhedonia or apathy did not differ between the low- and high-BMI groups. Alternatively, visual hallucinations could result from the higher LED that the patients with a low BMI received, although the effect of the LED was not significant in the adjusted logistic regression models.

In the STRIDE-PD study, which compared the initiation of levodopa therapy with levodopa/carbidopa versus levodopa/carbidopa/entacapone, female sex was one of the predictors of both dyskinesia and wearing off, reflecting the increased L-dopa concentrations in females that result from the lower body weight of females than males [37]. In our study, the low-BMI group contained more females than the high-BMI group, but the effect of sex on low BMI was not significant in a multivariable regression model.

Surgical treatments, including deep-brain stimulation, have been associated with subsequent weight gain [9]; however, in our study, only 1.8% of patients underwent deep-brain stimulation, and this association was unlikely to have been observed. Sarcopenia, a loss of skeletal muscle mass with aging [28], and decreased fat mass [38] are both related to weight loss in PD patients. In our study, dysphagia and gastrointestinal dysfunction, such as constipation [2], which may affect body weight, were more prevalent in the low-BMI group than in the high-BMI group. While olfactory loss and constipation occur in the all stage of PD, dysphagia likely occurs in mid to advanced stage contributing to weight loss [39]. However, after adjusting for clinical factors in a logistic regression analysis (models 2 and 3), dysphagia and constipation were no longer significant predictors for low BMI. DiBaise et al. [40] reported small intestinal bacterial overgrowth was not related to weight loss in patients with PD.

A limitation of our study is that other potential factors, such as daily activity, total sleep time, energy intake and energy expenditure, longitudinal changes in body weight, hyposmia, neuroendocrine hormones (including ghrelin and leptin), bone mineral density or vitamin D, which may contribute to body weight loss, were not evaluated. In our study, the majority of patients were assessed for motor function in the on state, which could have partially affected the lack of association between low BMI and the MDS-UPDRS III.

In conclusion, the results of our study showed that PD patients were 3 times more likely than healthy controls to have a low BMI, and motor complications, particularly dyskinesia and visual hallucinations, were significantly associated with decreased BMI in PD patients. Lower BMI was related to severely disabled PD patients [41] and underweight male PD patients had significantly poorer life prognosis compared with non-underweight patients [42]. Considering negative impact of low BMI on disease progression and prognosis, we should focus more on body weight and nutrition status of patients, optimizing dopaminergic treatment and taking care of patients’ life style including regular physical exercise and food intake. Also, the clinical factors which may influence appetite, such as minor visual hallucination, should be regularly monitored in order to enhance patients’ daily activities and quality of life.

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

Footnotes

ACKNOWLEDGMENTS

The authors thank Dr. Yuji Watanabe, Dr. Takeo Matsubara, Dr. Hirotaka Sakuramoto, Ms. Sanae Tani and Ms. Kaori Soma of the Department of Neurology, Dokkyo Medical University, for their help with this study.

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Determinants of Low Body Mass Index in Patients with Parkinson’s Disease: A Multicenter Case-Control Study

Abstract

Background:

Objective:

Methods:

Results:

Conclusion:

Keywords

INTRODUCTION

METHODS

Subjects

Clinical assessment

Assessment of nonmotor symptoms

Statistical analysis

RESULTS

DISCUSSION

CONFLICT OF INTEREST

Footnotes

ACKNOWLEDGMENTS

References