The taste of Parkinson's: How food choices reflect nutritional health

Abstract

Introduction

Underweight is common in Parkinson's disease (PD), particularly in advanced stages, and is linked to malnutrition and poorer outcomes. Understanding dietary habits and nutritional status may help identify vulnerable patients.

Objective

To examine dietary habits and their associations with clinical characteristics in underweight versus normal-to-overweight individuals with PD.

Methods

This cross-sectional study included 70 patients with PD attending a tertiary movement disorders centre. Demographic and clinical data were obtained through interviews and medical records. Disease severity was assessed using the Hoehn & Yahr scale and the Unified Parkinson's Disease Rating Scale (UPDRS Part III and IV). Nutritional status was screened using the Mini Nutritional Assessment–Short Form (MNA-SF). Dietary habits were evaluated using a culturally adapted Thai PD dietary questionnaire, and a dietitian estimated daily caloric and fluid intake. Participants were categorized by body mass index as underweight (<18.5) or normal-to-overweight (≥18.5). Group comparisons and logistic regression analyses were performed.

Results

Underweight patients more often consumed soft or liquid diets and had a higher prevalence of dysphagia. They reported less varied diets with lower meat and vegetable intake, although caloric and fluid intake were similar between groups. Underweight participants had lower MNA-SF scores (p < 0.001) and greater motor complications, including higher UPDRS Part IV scores (p = 0.015). Female gender (OR 18.51), dysphagia (OR 5.97), and dyskinesia (OR 2.03) were independently associated with underweight status.

Conclusion

Underweight in PD is associated with female gender, dysphagia, and dyskinesia. Early nutritional screening and management of dysphagia and motor complications may improve outcomes.

Plain language summary

Parkinson's disease (PD) patients often lose weight, particularly as the disease progresses. Being underweight can increase the risk of malnutrition, infections, and poorer quality of life. This study aimed to examine differences in eating habits, food choices, and health problems between underweight PD patients and those with normal-to-overweight PD groups. Seventy PD patients participated in this study. Information on health status, disease severity, and nutritional condition was collected through interviews and medical records. Patients completed a questionnaire on their eating habits, food preferences, and fluid intake over the past week. A dietitian estimated their daily calorie and water intake. Based on body weight, patients were divided into two groups: underweight and normal-to-overweight. Compared with the normal-to-overweight group, underweight patients showed distinct differences in both eating habits and health status. They were more likely to experience dysphagia and to consume soft or liquid foods. They consumed less red meat and vegetables and more milk, and they ate certain foods, such as desserts, less often. Although their total calorie and fluid intake were similar to those of the other group, the underweight group had poorer overall nutritional status. The findings suggest that underweight status in PD is associated with female gender, dysphagia, and dyskinesia. However, this study identifies associations rather than establishing cause-and-effect relationships. Early screening for eating issues, careful medication adjustment, and personalised nutritional support may help improve nutritional status, health outcomes, and quality of life in PD patients at risk of being underweight.

Keywords

food habits Parkinson's disease malnutrition dysphagia dietary intervention

Introduction

Being underweight is an essential problem for Parkinson's disease (PD).¹ Weight loss and being underweight have significant impacts on the disease progression and patient's quality of life, such as increasing risk of malnutrition, muscle wasting and frailty, and even higher risk of complications.^1,2 Gastrointestinal (GI) dysfunctions are widespread in PD, and PD patients frequently experience dysphagia, constipation, and gastroparesis, all of which worsen as the disease progresses into advanced stages.^3,4 Dysphagia may pose patients at a serious risk, such as choking, aspiration pneumonia, and malnutrition.^5,6 Constipation is common and leads to discomfort, bloating, and appetite loss, further reducing dietary intake.^7,8 Moreover, decreased water intake in PD correlated with greater constipation severity,^9,10 and may lead to dehydration or serious consequences.¹¹ Gastroparesis usually contributes to nausea, vomiting, and early satiety, making it difficult for patients to consume adequate nutrition.⁸ These several gastrointestinal problems significantly impair a patient's ability to maintain adequate nutrition, leading to reduced intake, malnutrition, and increased aspiration risk.^12,13

Balancing energy expenditure and dietary energy intake is required to maintain a suitable body weight.¹⁴ Weight loss results from a negative energy balance, in which energy expenditure exceeds energy intake.¹⁵ Occurrence of weight loss in PD has been associated with malnutrition and several issues that can worsen the patient's quality of life, especially in an advanced stage of the disease.¹⁶ PD patients with underweight status, determined using body mass index (BMI < 18.5), often experience more pronounced motor and non-motor symptoms, including severe dysphagia, reduced mobility, fatigue, depression, and cognitive impairment.¹⁶ These patients frequently struggle to maintain adequate nutritional intake due to dysphagia, early satiety, bloating, and gastroparesis.¹⁷ Their restricted dietary intake can lead to malnutrition, muscle wasting, and further deterioration in physical strength and mobility.¹⁸ On the other hand, normal-to-overweight patients (BMI > 18.5) may not face the same immediate risk of malnutrition. However, they may still experience problems with significant gastrointestinal dysfunctions, such as gastrointestinal reflux disease (GERD), dyspepsia, and irritable bowel syndrome.^19,20

The relationship between body composition and disease progression highlights the need for a deeper understanding of how underweight versus normal-to-overweight PD patients manage their dietary needs. However, few studies have examined the intersection of body weight, dysphagia, and culturally specific dietary patterns in PD. In addition, there is limited targeted research on dietary habits, food preferences, hydration, and nutritional status among PD patients, particularly when comparing different body types. This knowledge gap may contribute to increased risks of malnutrition and aspiration.

To address this gap, the present study explores dietary habits and food preferences among PD patients using a newly developed Thai dietary habits questionnaire. The questionnaire assessed food intake, flavour preferences, gastrointestinal symptoms, seasoning use, and food and fluid consumption over the previous seven days, with a specific focus on comparing underweight and normal-to-overweight individuals. The study also evaluated the relationship between dietary habits and health status by integrating standardized clinical assessments, including Hoehn & Yahr staging (H&Y), the Unified Parkinson's Disease Rating Scale (UPDRS), dysphagia evaluation, and nutritional screening using the Mini Nutritional Assessment–Short Form (MNA-SF). By clarifying these relationships, this study aims to support more personalized dietary guidance tailored to the distinct needs of underweight and normal-to-overweight PD patients.

Methods

This cross-sectional observational study was conducted among 70 Thai patients with PD at the Chulalongkorn Centre of Excellence for Parkinson's Disease and Related Disorders (ChulaPD, www.chulapd.org) in Bangkok, Thailand. The study aimed to assess dietary habits and their association with clinical outcomes, including mobility, dysphagia, and gastrointestinal symptoms. Ethical approval was obtained from the Faculty of Medicine Ethics Committee at Chulalongkorn University, and informed consent was obtained from all participants before the study. The IRB number of this study is IRB 0933/66.

Study population

Seventy PD patients were recruited for this study with a consecutive sampling method from the consecutive patients attending the centre. Inclusion criteria included a confirmed diagnosis of PD by a movement disorder neurologist, the ability to participate in interviews and clinical assessments, and consent to provide dietary and clinical information. Patients with severe cognitive impairments or any other neurodegenerative diseases that could interfere with dietary assessments were excluded.

Demographic and clinical data collection

Demographic and clinical data were collected through structured interviews and patient records. Data collected included disease duration (in years), weight (kg), height (cm), body mass index (BMI), gender, and the presence of comorbidities such as hypertension, diabetes, or cardiovascular disease. BMI was calculated as weight (kg)/height (m²) and used to categorize patients into two groups: underweight (BMI < 18.5) and normal-to-overweight (BMI ≥ 18.5). Additionally, detailed medical histories and medication use were recorded, particularly those related to PD management, as medications could affect nutritional intake and gastrointestinal function.

Questionnaire development and validation

The Thai Parkinson's Disease Dietary Habits Questionnaire was newly developed for this study to assess dietary patterns, food intake characteristics, nutritional status, and eating-related factors relevant to individuals with Parkinson's disease (PD). The questionnaire was developed collaboratively by movement disorder neurologists (OP and RB), PD nurse specialists (KS and NR), and a dietitian (NS). Item generation was informed by clinical experience, established dietary assessment frameworks, and factors known to influence nutritional status, gastrointestinal symptoms, and swallowing function in PD.

Instrument structure and content

The questionnaire was designed to evaluate dietary intake over the preceding seven days. It comprised 43 sections with a total of 118 items organised into five major domains:

Demographic and clinical information (such as age, gender, disease duration, comorbidities, mobility status, and dysphagia)

Dietary patterns and food consistency (regular, soft, or liquid diets)

Frequency and portion size of key food groups (vegetables, fruits, grains, meats, poultry, fish, dairy products, nuts, and snacks)

Fluid intake and beverage consumption (including water, milk, coffee, tea, juice, and sweetened or carbonated drinks)

Eating preferences and meal preparation practices, such as seasoning habits, preferred food temperature, and cooking methods

A key feature of the questionnaire was its cultural adaptation to Thai dietary practices. Content was informed by national dietary guidelines, typical Thai meal structures, and commonly consumed foods such as rice-based dishes, noodles, soups, tropical fruits, and traditional condiments (e.g., fish sauce, chilli, vinegar, and sugar). Portion sizes were expressed using culturally familiar household measures (e.g., ladles, cups, and spoons). In addition to traditional Thai foods, the questionnaire incorporated modern and Western-influenced dietary patterns increasingly common in Thailand, including milk, chocolate, bakery products, and processed foods, to capture contemporary dietary behaviours across different generations and socioeconomic groups.

The questionnaire also assessed gastrointestinal and eating-related symptoms frequently associated with PD, including choking, dysphagia, constipation, bloating, nausea, and vomiting. Dysphagia severity was determined based on self-reported swallowing difficulties, choking frequency, and the need for dietary modification (e.g., soft or liquid diets). Mobility status was categorised as fully independent, limited mobility, or wheelchair dependent.

Completion time was approximately 30 min. Reported food quantities were reviewed by a certified dietitian (NS) to estimate daily caloric intake. A seven-day recall period was selected to minimise recall bias while reflecting habitual dietary patterns.

Content validation and pilot testing

Content validity was established through a multidisciplinary expert panel review comprising two physicians with expertise in PD management, one registered nurse, and one dietitian. Panel members evaluated item relevance, comprehensiveness, clarity, and clinical applicability. For formal content validation, the Item–Objective Congruence (IOC) index was used; the mean IOC value exceeded 0.6 across all items, indicating acceptable content validity. Iterative revisions were implemented based on expert feedback.

Pilot testing was subsequently conducted with a small group of patients with PD to assess feasibility, comprehension, and response burden. Minor modifications to wording and formatting were made to improve clarity and usability.

Conceptual framework and psychometric considerations

The questionnaire primarily consists of independent descriptive items assessing multiple domains of dietary behavior rather than items designed to measure a single latent construct. This approach aligns with structured dietary assessment instruments and food frequency questionnaire (FFQ)-style tools, where emphasis is placed on content validity, clinical relevance, and accurate capture of habitual intake rather than internal consistency reliability across heterogeneous items.^21,22 Accordingly, internal consistency measures such as Cronbach's alpha were not calculated, as such metrics are generally appropriate for psychometric scales assessing a unified construct. In contrast, multidimensional dietary indices are not expected to demonstrate high inter-item correlations.²³

Detailed descriptions of the questionnaire and validation procedures are provided in Supplementary Data 1 and 2.

Clinical assessment

Disease severity was evaluated using the Hoehn and Yahr (H&Y) staging. Motor and functional status were assessed using the Unified Parkinson's Disease Rating Scale-motor section (UPDRS Part III). Motor complications were assessed using the Unified Parkinson's Disease Rating Scale – motor complications (UPDRS Part IV). Greater score of UPDRS represented for greater disease severity. Dysphagia was evaluated by a physician during the clinical examination using standardized clinical judgment based on patient-reported symptoms and observational findings.

Nutritional status was screened using the Mini Nutritional Assessment – Short Form (MNA-SF), a validated tool for identifying malnutrition risk in clinical populations, with range score between 0–14 points by a lower score represent for malnutrition, and a higher score represent for normal nutritional status. Participants were categorized according to established scoring criteria as following malnutrition (0–7 points), at risk of malnutrition (8–11 points), and normal nutritional status (12–14 points).

These standardized clinical assessments were incorporated to improve objective evaluation of disease severity, functional impairment, and nutritional risk.

Statistical analysis

Statistical analysis was performed to identify significant differences between the underweight and normal-to-overweight groups across several parameters, including dietary habits, mobility, dysphagia severity, and gastrointestinal symptoms. Descriptive statistics (mean, standard deviation, frequency, and percentage) were used to summarise the data. The two groups were compared using an independent t-test or Mann-Whitney U test for continuous variables (e.g., BMI, disease duration) and chi-square tests or Fisher's Exact Test for categorical variables (e.g., preferred diet consistency, presence of dysphagia). Additional analyses were performed incorporating clinical severity variables, including H&Y staging, UPDRS, dysphagia status, and MNA-SF classification to explore associations between dietary habits and clinical characteristics. Moreover, Logistic regression analysis was conducted using a stepwise logistic regression model with the Wald Forward selection method to determine associations between BMI categories and clinical outcomes, including age, gender, disease duration, eating and gastrointestinal problems, seasoning, and types of food consumption. All analyses were performed using SPSS software version 23. A p-value of <0.05 was considered statistically significant.

Results

The demographic data and clinical characteristics of all PD patients

The demographic data and clinical characteristics of the 70 PD patients are summarised in Table 1. The mean values and standard deviation (SD) are as follows: the patients’ current age is 65.61 ± 12.58 years (range 26–94), with an average disease duration of 10.21 ± 6.70 years (range 2–32). The average weight of the patients is 58.06 ± 13.04 kg (range 33–95), and their average height is 161.10 ± 8.63 cm (range 134–180), resulting in a mean BMI of 22.20 ± 3.79 (range 14.48–33.06). Of the 70 patients, 33 (47.1%) are female. Based on BMI, 13 (18.6%) are underweight, while the remaining 57 (81.4%) are normal-to-overweight. For mobility, 43 patients (61.4%) are independent, 22 (31.4%) have limited mobility, and 5 (7.1%) rely on a wheelchair.

Table 1.

Demographic and clinical data of 70 PD patients, including information about their health and dietary habits.

Items	Mean ± SD	Min – max
Patients’ current age	65.61 ± 12.58	26–94
Disease duration	10.21 ± 6.70	2–32
Weight (kg)	58.06 ± 13.04	33–95
Height (cm)	161.10 ± 8.63	134–180
BMI	22.20 ± 3.79	14.48–33.06
Female gender	33 (47.1%)
Hoehn & Yahr staging	3.52 ± 0.76	2.0–5.0
Total UPDRS Part III during on stage	27.47 ± 13.22	8–59
Total UPDRS Part IV	6.04 ± 2.87	0–13
UPDRS Part IV dyskinesias	1.93 ± 1.65	0–8
UPDRS Part IV clinical fluctuations	2.49 ± 1.29	0–5
UPDRS Part IV other complications	1.63 ± 0.57	0–3
Mini Nutritional Assessment - Short Form	10.43 ± 2.42	5–14
MNA interpretation	Malnutrition 8 (11.4%)
	At risk of malnutrition 35 (50%)
	Normal nutritional status 27 (38.6%)
Levodopa equivalent dosage	932.41 ± 466.88	150–2245
BMI classification	Underweight 13 (18.6%)
	Healthy weight 44 (62.9%)
	Overweight 11 (15.7%)
	Obesity (class 1) 2 (2.9%)
Having no other diseases	40 (57.1%)
Hypertension	9 (12.9%)
Diabetes	8 (11.4%)
Dyslipidemia	2 (2.9%)
Stroke	3 (4.3%)
Heart diseases	4 (5.7%)
Thyroid disease	3 (4.3%)
Cancer	4 (5.7%)
Self-body figure perception	Very thin 4 (5.7%), Thin 17 (24.3%), Normal 38 (54.3%), overweight 9 (12.9%), Very overweight 2 (2.9%)
Weight changes over the part 6 months	Stable 40 (57.1%), Weight loss 14 (20.0%), Weight gain 15 (21.4%), Uncertain 1 (1.4%)
Preferred diet	Regular 55 (78.6%), Soft diet 12 (7.1%), Liquid diet 3 (4.3%)
Amount of food	Normal intake 47 (67.1%), Less intake 13 (18.6%), More intake 10 (14.3%)
Choking	26 (37.1%)
Swallowing difficulty/dysphagia	19 (27.1%)
Using feeding tube	7 (10.0%)
GI: flatulence	10 (14.3%)
GI: diarrhea	4 (5.7%)
GI: constipation	45 (64.3%)
GI: nausea	5 (7.1%)
GI: vomit	3 (4.3%)
Mobility status	Independent 43 (61.4%)
	limited mobility 22 (31.4%)
	Wheel-chair 5 (7.1%)
Favorite flavor	Sour 8 (11.4%), Sweet 13 (18.6%), Salty 4 (5.7%), Spicy 4 (5.7%), Bitter 0 (0%), Umami 41 (58.6%)
Favorite flavor
Less favorite flavor	Sour 9 (12.9%), Sweet 5 (7.1%), Salty 10 (14.3%), Spicy 12 (17.1%), Bitter 30 (42.9%), Umami 4 (5.7%)
Less favorite flavor
Preferred food temperature	Cold 13 (18.6%)
	Room temperature 18 (25.7%)
	Mild hot 31 (44.3%)
	Hot 8 (11.4%)
When eating your favorite food, how do you feel?	Normal intake 31 (44.3%)
	More intake 31 (44.3%)
	Less intake 8 (11.4%)
Cooking	No, I buy it from the shop 30 (42.9%)
Cooking	Home cooking 40 (57.1%)
Add seasoning	15 (21.4%) – Salty, sweet, sour, spicy
Red wine	3 (4.3%)
White wine	1 (1.4%)
Beer	4 (5.7%)
Weekly consumption of vegetable	67 (95.7%)
Weekly consumption of meat	65 (92.9%)
Weekly consumption of poultry	60 (85.7%)
Weekly consumption of fish	61 (87.1%)
Weekly consumption of milk	45 (64.3%)
Weekly consumption of yogurt	25 (35.7%)
Weekly consumption of cream	16 (22.9%)
Weekly consumption of cheese	9 (12.9%)
Weekly consumption of berry fruits	20 (28.6%)
Weekly consumption of avocado	12 (17.1%)
Weekly consumption of fast-food	15 (21.4%)
Weekly consumption of ice-cream	35 (50.0%)
Weekly consumption of pie	15 (21.4%)
Weekly consumption of chocolate	14 (20.0%)
Weekly consumption of candy	13 (18.6%)
Weekly consumption of frozen foods	16 (22.9%)
Daily consumption of fruit	66 (94.3%)
Daily consumption of wholegrains	23 (32.9%)
Daily consumption of sugar-free drink	70 (100%)
Daily consumption of sugar-added drink	25 (35.7%)
Daily consumption of olive oil	12 (17.1%)
Daily consumption of oral fluid less than 1.5 L	31 (44.3%)
Amount of vegetable in past 7 days (gram)	220.71 ± 211.02	0–1200
Amount of red meat in past 7 days (gram)	398.57 ± 386.79	0–3000
Amount of poultry in past 7 days (gram)	282.85 ± 185.69	0–1000
Amount of fish in past 7 days (gram)	434.29 ± 326.54	0–1000
Amount of milk in past 7 days (mL)	388.57 ± 673.15	0–4000
Amount of drinking water in 1 day (mL)	1231.43 ± 692.72	200–5000
Amount of oral fluid intake in 1 day (mL)	1532.65 ± 818.96	271.43–5071.43
Total calorie intake per day (Kcal)	1484.77 ± 619.17	729.00–3118.00

UPDRS: Unified Parkinson's Disease Rating Scale; BMI: Body Mass Index.

The mean levodopa equivalent daily dose was 932.41 ± 466.88 mg (range 150–2245 mg). The mean Hoehn & Yahr staging was 3.52 ± 0.76 (range 2.0–5.0), indicating moderate disease severity among participants. Motor examination during the “on” stage demonstrated a mean UPDRS Part III score of 27.47 ± 13.22 (range 8–59). Motor complications, assessed using UPDRS Part IV, had a mean total score of 6.04 ± 2.87 (range 0–13). Among the subcomponents, UPDRS Part IV dyskinesias sub-score averaged 1.93 ± 1.65 (range 0–8), clinical fluctuations averaged 2.49 ± 1.29 (range 0–5), and other complications averaged 1.63 ± 0.57 (range 0–3). Nutritional status, assessed by the MNA-SF, had a mean score of 10.43 ± 2.42 (range 5–14). Based on MNA-SF interpretation, 8 participants (11.4%) were classified as malnourished, 35 (50%) were at risk of malnutrition, and 27 (38.6%) had normal nutritional status.

Regarding body image perception, 4 patients (5.7%) perceive themselves as very thin, 17 (24.3%) as thin, 38 (54.3%) as normal, 9 (12.9%) as overweight, and 2 (2.9%) as very overweight. Over the past 6 months, 40 patients (57.1%) reported stable weight, 14 (20.0%) reported weight loss, 15 (21.4%) reported weight gain, and 1 (1.4%) was uncertain. The majority of patients (55, 78.6%) prefer a regular diet, while 12 (7.1%) opt for a soft diet, and 3 (4.3%) prefer a liquid diet. In terms of gastrointestinal (GI) symptoms, 26 patients (37.1%) experienced choking, 19 (27.1%) had dysphagia, and 7 (10.0%) used a feeding tube. Other reported GI symptoms include flatulence in 10 patients (14.3%), diarrhea in 4 patients (5.7%), constipation in 45 patients (64.3%), nausea in 5 patients (7.1%), and vomiting in 3 patients (4.3%).

In terms of flavour preferences, 8 patients (11.4%) prefer sour, 13 (18.6%) favor sweet, 4 (5.7%) prefer salty, 4 (5.7%) prefer spicy, and 41 (58.6%) prefer umami, while none favor bitter. Conversely, the least favorite flavors include bitter for 30 patients (42.9%), spicy for 12 patients (17.1%), salty for 10 patients (14.3%), sour for 9 patients (12.9%), sweet for 5 patients (7.1%), and umami for 4 patients (5.7%). When considering preferred food temperature, 13 patients (18.6%) prefer cold food, 18 (25.7%) prefer room temperature food, 31 (44.3%) prefer mildly hot food, and 8 (11.4%) prefer hot food. When asked how they feel when eating their favorite food, 31 patients (44.3%) report normal intake, 31 (44.3%) more intake than usual, and 8 (11.4%) less intake than usual. As for cooking habits, 30 patients (42.9%) buy food from shops, while 40 (57.1%) cook at home. Finally, 15 patients (21.4%) report adding seasoning to their food, whether salty, sweet, sour, or spicy. Overall, PD patients in this study reported that sweet was their most favorite flavor, preferred a mild hot temperature, and showed a greater tendency to consume larger amounts when eating their favorite foods.

The comparison in demographic data and clinical characteristics between the underweight and the normal-to-overweight groups

From Table 2, the study identified significant differences between the underweight and normal-to-overweight groups. Compared with patients with normal-to-overweight BMI, underweight PD patients demonstrated several distinct clinical characteristics. The underweight group had a significantly higher proportion of female participants (84.6% vs 38.6%, p = 0.003). The underweight group had a significantly lower BMI (p < 0.001) compared to the normal-to-overweight group and a higher percentage of females (p = 0.003). They likely preferred a soft or liquid diet (p = 0.004) and exhibited a higher prevalence of dysphagia (p = 0.023). Dysphagia was more frequently observed among underweight patients, suggesting a potential association between dysphagia-related symptoms and lower nutritional status. Nutritional screening using the Mini Nutritional Assessment – Short Form (MNA-SF) further confirmed poorer nutritional status in the underweight group (8.08 ± 2.02 vs 10.96 ± 2.19, p < 0.001).

Table 2.

Comparison in demographic data and clinical characteristics between underweight and normal-to-overweight groups.

Items	Underweight (n = 13)	Normal-to-overweight (n = 57)	p-value
Patients’ current age	65.54 ± 15.25	65.63 ± 12.05	0.892
Disease duration	11.54 ± 6.62	9.90 ± 6.74	0.331
Weight (kg)	42.10 ± 4.94	61.71 ± 11.48	<0.001*
Height (cm)	156.56 ± 5.30	162.14 ± 8.94	0.007*
BMI	17.14 ± 1.36	23.36 ± 3.16	<0.001*
Female gender	11 (84.6%)	22 (38.6%)	0.003*
Hoehn &Yahr staging	3.46 ± 0.78	3.54 ± 0.77	0.967
Total UPDRS Part III during on stage	28.85 ± 13.57	27.16 ± 13.24	0.511
Total UPDRS Part IV	7.62 ± 1.81	5.68 ± 2.96	0.015*
UPDRS Part IV dyskinesias	2.85 ± 1.14	1.72 ± 1.69	0.014*
UPDRS Part IV clinical fluctuations	3.00 ± 1.16	2.37 ± 1.30	0.079
UPDRS Part IV other complications	1.77 ± 0.44	1.60 ± 0.59	0.279
Mini Nutritional Assessment – Short Form	8.08 ± 2.02	10.96 ± 2.19	<0.001
MNA interpretation	Malnutrition 6 (46.2%)	Malnutrition 2 (3.5%)	<0.001
	At risk of malnutrition 7 (53.8%)	At risk of malnutrition 28 (49.1%)
	Normal nutritional status 0 (0%)	Normal nutritional status 27 (47.4%)
Levodopa equivalent dosage	948.35 ± 419.17	928.77 ± 480.47	0.706
Preferred diet	Regular 6 (46.2%)	Regular 49 (86.0%)	0.004*
	Soft diet 5 (38.5%)	Soft diet 7 (12.3%)
	Liquid diet 2 (15.4%)	Liquid diet 1 (1.8%)
Self-body figure perception	Very thin 3 (23.1%), Thin 7 (53.8%), Normal 3 (23.1%), overweight 0 (0%), Very overweight 0 (0%)	Very thin 1 (1.8%), Thin 10 (17.5%), Normal 35 (61.4%), overweight 9 (15.8%), Very overweight 2 (3.5%)	0.001*
Weight changes	Stable 6 (46.2%), Weight loss 5 (38.5%), Weight gain 2 (15.4%), Uncertain 0 (0%)	Stable 34 (59.6%), Weight loss 9 (15.8%), Weight gain 13 (22.8%), Uncertain 1 (1.8%)	0.313
Choking	5 (38.5%)	21 (36.8%)	0.576
Swallowing difficulty/dysphagia	7 (53.8%)	12 (21.1%)	0.023*
Using feeding tube	2 (15.4%)	5 (8.8%)	0.386
GI: flatulence	1(7.7%)	9 (15.8%)	0.404
GI: diarrhea	1(7.7%)	3 (5.3%)	0.569
GI: constipation	10 (76.9%)	35 (61.4%)	0.235
GI: nausea	1 (7.7%)	4 (7.0%)	0.654
GI: vomit	0 (0.0%)	3 (5.3%)	0.535
Mobility status	Independent 5 (38.5%)	Independent 38 (66.7%)	0.001*
	Limited mobility 4 (30.8%)	Limited mobility 18 (31.6%)
	Wheel-chair 4 (30.8%)	Wheel-chair 1 (1.8%)
Favorite flavor	Sour 3 (23.1%)	Sour 5 (8.8%)	0.547
	Sweet 2 (15.4%)	Sweet 11 (19.3%)
	Salty 0 (0%)	Salty 4 (7.0%)
	Spicy 1 (7.7%)	Spicy 3 (5.3%)
	Bitter 0 (0%)	Bitter 0 (0%)
	Umami 7 (53.8%)	Umami 34 (59.6%)
Less favorite flavor	Sour 2 (%)15.4	Sour 7 (12.3%)	0.758
	Sweet 0 (0%)	Sweet 5 (8.8%)
	Salty 2 (15.4%)	Salty 8 (14.0%)
	Spicy 2 (15.4%)	Spicy 10 (17.5%)
	Bitter 7 (53.8%)	Bitter 23 (40.4%)
	Umami 0 (0%)	Umami 4 (7.0%)
Preferred food temperature	Cold 1 (7.7%)	Cold 12 (121.1%)	0.704
	Room temperature 4 (30.8%)	Room temperature 14 (24.6%)
	Mild hot 6 (46.2%)	Mild hot 25 (43.9%)
	Hot 2 (15.4%)	Hot 6 (10.5%)
When eating your favorite food, how do you feel?	Normal intake 6 (46.2%)	Normal intake 25 (43.9%)	0.547
	More intake 6 (46.2%)	More intake 25 (43.9%)
	Less intake 1 (7.7%)	Less intake 7 (12.3%)
Cooking	No, I buy it from the shop 34 (30.8%)	No, I buy it from the shop 26 (45.6%)	0.448
Cooking	Home cooking 9 (69.2%)	Home cooking 31 (54.4%)	0.448
Add seasoning	2 (15.4%) – Salty, sweet, sour, spicy	13 (22.8%) – Salty, sweet, sour, spicy	0.556
Red wine	1 (7.7%)	2 (3.5%)	0.465
White wine	0 (0%)	1 (1.8%)	0.814
Weekly consumption of vegetable	11 (84.6%)	56 (98.2%)	0.029*
Weekly consumption of meat	11 (84.6%)	54 (94.7%)	0.230
Weekly consumption of poultry	3 (23.1%)	7 (12.3%)	0.271
Weekly consumption of fish	11 (84.6%)	50 (87.7%)	0.531
Weekly consumption of milk	10 (76.9%)	35 (61.4%)	0.235
Weekly consumption of yogurt	3 (23.1%)	22 (38.6%)	0.235
Weekly consumption of cream	2 (15.4%)	14 (24.6%)	0.469
Weekly consumption of cheese	1 (7.7%)	8 (14.0%)	0.538
Weekly consumption of berry fruits	1 (7.7%)	19 (33.3%)	0.059
Weekly consumption of avocado	1 (7.7%)	11 (19.3%)	0.292
Weekly consumption of fast-food	3 (23.1%)	12 (21.1%)	0.872
Weekly consumption of ice-cream	5 (38.5%)	30 (52.6%)	0.356
Weekly consumption of pie	0 (0%)	15 (26.3%)	0.031*
Weekly consumption of chocolate	0 (0%)	14 (24.6%)	0.040*
Weekly consumption of candy	1 (7.7%)	12 (21.1%)	0.245
Weekly consumption of frozen foods	2 (15.4%)	14 (24.6%)	0.381
Daily consumption of fruit	12 (92.3%)	54 (94.7%)	0.569
Daily consumption of wholegrains	6 (46.2%)	17 (29.8%)	0.209
Daily consumption of sugar-free drink	13 (100%)	57 (100%)	na
Daily consumption of sugar-added drink	5 (38.5%)	20 (35.1%)	0.528
Daily consumption of olive oil	2 (15.4%)	10 (17.5%)	0.609
Daily consumption of oral fluid less than 1.5 L	7 (53.8%)	32 (56.1%)	0.560
Amount of vegetable in past 7 days (gram)	201.92 ± 217.09	225.00 ± 211.34	0.342
Amount of red meat in past 7 days (gram)	250.00 ± 151.38	432.45 ± 414.95	0.026*
Amount of poultry in past 7 days (gram)	246.15 ± 185.36	291.23 ± 186.39	0.539
Amount of fish in past 7 days (gram)	469.23 ± 396.62	426.31 ± 311.98	0.988
Amount of milk in past 7 days (mL)	969.23 ± 1349.31	256.14 ± 268.44	0.045*
Amount of drinking water in 1 day (mL)	1053.84 ± 377.74	1271.93 ± 742.76	0.411
Amount of oral fluid intake in 1 day (mL)	1700.00 ± 1136.41	1494.48 ± 735.99	0.856
Total calorie intake per day (Kcal)	1731.23 ± 789.06	1428.56 ± 567.12	0.156

Statistical analysis was performed using Chi-square or Fisher's Exact test or Mann-Whitney U test as appropriate. *; the asterisk represented p-value <0.05 which was considered statistically significance. UPDRS: Unified Parkinson's Disease Rating Scale; BMI: Body Mass Index.

Regarding mobility, the underweight group had significantly less independence in daily life (p = 0.001). In addition, measures of motor complications were also significantly different between groups. Specifically, underweight patients exhibited higher total UPDRS Part IV scores (7.62 ± 1.81 vs 5.68 ± 2.96, p = 0.015) and higher UPDRS Part IV dyskinesias sub-scores (2.85 ± 1.14 vs 1.72 ± 1.69, p = 0.014), indicating greater motor complications related to treatment. However, no significant differences were observed in H&Y stage (p = 0.967) or total UPDRS Part III scores between groups (p = 0.511).

Figure 1.

Food consumption patterns in underweight vs. normal-to-overweight participants. This figure compares the normal-to-overweight group, underweight participants reported significantly lower weekly red meat intake and significantly higher milk consumption.

Regarding the amount of food consumption, compared to the normal-to-overweight group, the underweight group showed a lower amount in weekly consumption of red meat (250.00 ± 151.38 vs. 432.45 ± 414.95 grams; p = 0.026), and a greater amount in weekly consumption of milk (969.23 ± 1349.31 vs. 256.14 ± 268.44 grams; p = 0.045) (Figure 1). Also, the underweight group had a lower weekly frequency of vegetables (p = 0.029), pie (p = 0.031), and chocolate (p = 0.040) than their normal-to-overweight counterparts. However, there are no differences between groups in terms of volume of drinking water per day (1053.84 ± 377.74 vs. 1271.93 ± 742.76 mL, p = 0.411), total oral fluid intake per day (1700.00 ± 1136.41 vs. 1494.48 ± 735.99 mL, p = 0.856), or total caloric intake per day (1731.23 ± 789.06 vs. 1428.56 ± 567.12 kcal, p = 0.156). Moreover, our study shows that the underweight group tends to use less seasoning than the normal-to-overweight group. Overall, underweight patients were more likely to suffer from dysphagia and reduced mobility. Their dietary preferences leaned towards softer, more easily digestible foods, increased milk intake, and less red meat consumption, and they reported more serious gastrointestinal problems. On the other hand, the underweight group displayed less varied dietary intake. However, they still drank appropriate water and had no significant dehydration-related issues.

Identification of predictors and odds ratios Exp(B) for determining the likelihood of becoming an underweight patient

Multivariable logistic regression analysis was performed to identify factors independently associated with underweight status in PD patients. Female gender, dysphagia, and UPDRS Part IV dyskinesia sub-scores were identified as significant predictors. Female gender was strongly associated with underweight status (odds ratio [OR] = 18.51, 95% confidence interval [CI] 2.74–125.16, p = 0.003). Patients reporting dysphagia or swallowing difficulty also had higher odds of being underweight (OR = 5.97, 95% CI 1.23–28.92, p = 0.026). Additionally, higher UPDRS Part IV dyskinesias sub-score were independently associated with underweight status (OR = 2.03, 95% CI 1.13–3.68, p = 0.018). The overall regression model was statistically significant (Omnibus test χ² = 5.36, p = 0.021). The Nagelkerke R² value was 0.45, suggesting moderate explanatory power. The Hosmer–Lemeshow goodness-of-fit test indicated adequate model fit (p = 0.950) (Table 3).

Table 3.

Predictors and odds ratios (Exp (B)) for determining the likelihood of becoming an underweight PD patient.

Predictors	Exp (B)	p-value
Female gender	18.51 (95%CI 2.74–125.16)	0.003*
Eating problems – swallowing difficulty	5.97 (95%CI 1.23–28.92)	0.026*
UPDRS Part IV dyskinesias sub-score	2.03 (95%CI 1.13–3.68)	0.018*
Model summary
Omnibus tests of Model coefficients: Chi-square	5.36	0.021
Nagelkerke R Square	0.45
Hosmer and Lemeshow Test	0.950

*: statistically significant; Percentage of variance was determined by the pseudo R-square from the Nagelkerke R-square model. Nagelkerke R square - An approximate measure of the proportion of explained variation. Hosmer and Lemeshow Test – The goodness of fit in logistic regression model.

Factors: female gender, swallowing difficulty, UPDRS Part III, UPDRS Part IV, and presence of GI symptoms.

Discussion

This study provides novel insights into the dietary habits of people with PD in Thailand. It identified significant differences between underweight and normal-to-overweight individuals with PD, highlighting important clinical and nutritional distinctions. Moreover, underweight patients showed reduced dietary variety despite similar caloric intake to normal-to-overweight groups, which may be explained by three possible factors, including (1) Gender-related vulnerabilities (especially in females), (2) Dyskinesia increasing energy needs and favoring energy-dense foods, and (3) Dysphagia limiting safe food textures as follows.

The higher proportion of female patients among the underweight group may reflect gender-specific differences in body composition, metabolic reserve, or disease-related weight trajectories. Women generally have lower baseline muscle mass and energy reserves, which may increase susceptibility to weight loss when faced with increased metabolic demands or feeding difficulties. Also, recent evidence suggested that female PD patients were more likely to have dyskinesia than male PD patients.^24,25 Hormonal, behavioral, and body-composition factors may also contribute, though further investigation is required.

The association between higher UPDRS Part IV dyskinesias sub- score and underweight status is biologically plausible. Dyskinesia represents a hyperkinetic state characterized by involuntary movements that may increase resting energy expenditure and caloric requirements. A previous study suggested that excessive motor activity and levodopa-induced dyskinesia can contribute to negative energy balance, thereby predisposing patients to weight loss.¹⁶ Additionally, dyskinesia may interfere with meal preparation and eating efficiency, prolong feeding time, and reduce effective caloric intake.²⁶

Dysphagia emerged as another independent factor associated with underweight status.²⁷ Dysphagia is common in PD due to impaired oropharyngeal motor control and reduced coordination of the swallowing musculature. Dysphagia also contributes to poor nutritional status and subsequent weight loss, a common complication in advanced PD that can markedly affect food intake and dietary choices.⁴ Patients with swallowing impairment may avoid certain food textures, reduce overall intake, or experience anxiety during meals, which can further contribute to inadequate nutrition. Our findings further indicate that the underweight group's lower preference for a regular diet, higher incidence of dysphagia, and reduced red-meat consumption may reflect imbalanced nutritional patterns, underscoring the complex interplay between nutrition and disease progression.^4,28 Underweight patients tended to choose softer, easier-to-swallow foods, which can limit their ability to maintain a nutritionally adequate diet.¹⁷ Consistently, these individuals consumed less red meat, vegetables, pie, and chocolate than the normal-to-overweight group. Finally, the coexistence of dysphagia and dyskinesia may amplify nutritional vulnerability by simultaneously increasing energy expenditure while limiting intake, which is usually found in the advanced stage of PD.²⁷ Taken together, these findings support a multifactorial model in which dyskinesia, dysphagia, and individual patient characteristics interact to influence nutritional status in PD. Early recognition of dyskinesia and dysphagia may therefore represent important opportunities for targeted nutritional assessment and intervention. Together, these three factors may restrict food choices even when total caloric intake is adequate, as showed in our study.

Interestingly, chocolate intake has previously been associated with PD. Studies have reported that individuals with PD tend to consume more chocolate than healthy controls, possibly due to its content of biogenic amines, such as β-phenylethylamine and methylxanthines, which can cross the blood–brain barrier and modestly enhance dopaminergic neurotransmission.²⁹ Controlled studies have suggested that dark chocolate, which is rich in polyphenols and antioxidants, may transiently enhance motor function and reduce fatigue in people with Parkinson's disease. However, findings across clinical trials remain inconsistent.^30,31 In addition, recent evidence proposes that chocolate may modulate the gut–brain axis, particularly when combined with probiotics, offering potential benefits for both dopaminergic activity and gastrointestinal health.³² In the context of our study, the lower frequency of chocolate consumption amongst underweight participants may therefore reflect both reduced caloric intake and avoidance of dense or sweet foods, rather than the potential therapeutic use observed in other populations.

Poor flavour perception may further contribute to weight loss and malnutrition in PD.³³ This issue aligns with our finding that the underweight group used less seasoning than the normal-to-overweight group. Another important finding is the significant reduction in mobility and independence amongst those in the underweight group. It is often associated with higher motor scores, including H&Y staging and UPDRS.² Reduced mobility can exacerbate nutritional deficiencies, as patients with limited independence may be unable to prepare food or access a diverse range of food options.^6,34 In contrast, the normal-to-overweight group, who reported fewer digestive issues and a more varied diet, may have better preserved functional abilities, allowing them to maintain a broader range of dietary choices, as observed in a previous study.¹⁹ Moreover, although the underweight group consumed a less varied diet, they still drank an appropriate amount of water, suggesting awareness of hydration needs despite challenges in maintaining adequate caloric intake.

Beyond nutrition, low body weight in PD has been consistently linked to reduced bone mineral density and an increased risk of osteoporosis and fractures, particularly hip fractures.^35–37 Factors such as reduced muscle mass, vitamin D deficiency, and decreased mobility contribute to bone fragility in this population. Women with PD are particularly vulnerable, as hormonal changes combined with low body mass and physical inactivity can accelerate bone loss.³⁸ Furthermore, chronic levodopa therapy may also influence bone metabolism through altered homocysteine levels and vitamin B12 depletion.³⁹ Together, these findings underscore the need for integrated nutritional and musculoskeletal assessments in underweight PD patients to reduce the risk of fractures and improve overall quality of life. Together, these findings underscore the importance of integrated nutritional, musculoskeletal, and fracture-risk assessments in underweight patients with PD, in line with the 2024 UK National Osteoporosis Guideline, which now explicitly recognises PD as a clinical risk factor for osteoporosis and fragility fractures.⁴⁰ The guideline emphasises the combined use of the Fracture Risk Assessment Tool (FRAX), mobility evaluation, and nutritional optimisation to guide early interventions aimed at reducing fracture risk and maintaining functional independence.

Overall, our findings suggest that underweight PD patients represent a more vulnerable group with distinct nutritional and clinical challenges. Their reduced food intake, limited dietary preferences, dysphagia, and high prevalence of dyskinesia underscore the need for targeted dietary interventions.^17,41 Meanwhile, the normal-to-overweight group's more varied diet and fewer digestive complications suggest a more stable nutritional status and higher independence.¹⁹ However, obesity also carries risks, including GI symptoms and potentially faster motor progression in early PD.¹⁹ These contrasts highlight the dietitian's role in providing individualized nutritional care for PD patients at all stages of the disease. The lower dietary variety among underweight PD patients, despite comparable caloric intake to the normal-to-overweight group, may be influenced by the higher prevalence of dyskinesia and dysphagia in this subgroup. Motor complications and dysphagia can restrict the range of tolerated foods, leading patients to rely on a narrower selection of easily consumed or softer foods.

Additionally, the higher proportion of female patients may contribute to differences in food preferences, portioning, or dietary behaviors. Together, these factors may reduce dietary diversity without necessarily affecting total energy intake. Therefore, dietitians should be part of the multidisciplinary team managing advanced PD, playing a crucial role in optimizing nutrition to support overall health, medication effectiveness, and symptom management.⁴² Dietitians are integral to personalizing nutritional care plans that adapt to the evolving needs of patients with advanced PD. Based on our findings, dietitians may also recommend preparing food tailored to PD patients’ preferences to encourage greater consumption, for example, adding sweetness with sugar substitutes or serving food at a mildly warm temperature.

Dietitians evaluate the nutritional status of PD patients by assessing weight, muscle mass, and dietary intake to identify malnutrition or unintentional weight loss, which are common in advanced PD.⁴² The key roles of dietitians include, firstly, nutritional assessment and monitoring by ensuring adequate calorie, protein, and vitamin intake, especially regarding vitamins B and D.^39,43 Secondly, re-check for any medication and food interactions and provide supplement recommendations and strategies to address the side effects of medications, such as nausea, constipation, or orthostatic hypotension.⁴² Thirdly, symptom-specific nutritional support, such as constipation management, before sending patients for further consultation,⁴⁴ and suggesting a healthier dietary pattern rich in protein sources such as poultry, fish, and plant-based protein, including the Mediterranean diet.⁴⁵ For those with unintentional weight loss, the dietitian can recommend calorie-dense, nutrient-rich foods or supplements to help maintain weight. Also, for those with weight gain, a dietitian can guide on portion control and balanced diets early in cases of reduced activity levels. Fourthly, being a part of the multidisciplinary team (MDT) for collaboration and supporting patient and caregiver education. However, involving dietitians may not be practical in all cases, especially in countries where they are not widely available. Furthermore, no standardized appraisal methods and management strategies for weight loss and malnutrition can be easily applied to PD.¹⁶

To the best of our knowledge, a consensus has been reached on the nutritional management of PD, defining the specific role of dietitians and strategies for managing various nutrition-related symptoms.⁴⁴ Therefore, an early screening tool, either for a questionnaire or scale, such as in this study, we newly developed a Thai dietary habits questionnaire, specifically designed to assess the nutritional patterns of PD patients, that may help identify the contributing factors of weight loss and malnutrition in PD and possibly offer an effectively kick-start proper managing patients with nutritional issues before dietitian referral. Based on our findings, patients at the highest risk of being underweight include women and those experiencing dysphagia.

A key strength of this study is the use of a newly developed Thai Dietary Habits Questionnaire to provide comprehensive data on food intake, flavour preferences, GI symptoms, and seasoning use over the past seven days, reflecting Thai dietary patterns. The inclusion of standardized clinical assessments, including H&Y staging, UPDRS scores, dysphagia status, and MNA-SF nutritional screening, strengthens the interpretation of our findings by integrating objective measures of disease severity and functional status. Previous studies relying solely on questionnaire-based data may be limited by subjective bias; therefore, the addition of validated clinical scales in the present study enhances methodological rigor and supports the clinical relevance of the observed associations between dietary habits and health outcomes. Additionally, classifying patients into underweight and normal-to-overweight groups based on BMI enabled targeted statistical comparisons, revealing significant differences in dietary and health-related outcomes. These easily interpretable findings can help physicians better interpret patients’ symptoms and facilitate the early diagnosis of those at risk of malnutrition. It is also important to acknowledge differing perspectives on body image between physicians and dietitians/nutritionists (Figure 2). Physicians often underdiagnose malnutrition,⁴⁶ while dietitians or nutritionists may be more accurate in their initial assessment, using tools to stratify nutritional status into categories such as underweight, normal, overweight, and obesity type I-III.^47,48 Therefore, the classification used in this study is valuable in supporting physicians to manage patients’ nutritional care more effectively.

Figure 2.

Differences in body image perception between physicians and dietitians/nutritionists. This figure shows that physicians use broad BMI categories, typically identifying individuals only as thin, normal, or overweight. In contrast, dietitians and nutritionists use more detailed ones, distinguishing across a broader range of categories, including underweight, normal weight, overweight, and obesity classes I–III. This contrast highlights the more limited perceptual range among physicians compared with the more refined classification used by dietitians/nutritionists.

This study has several limitations. First, the relatively small number of underweight participants (n = 13) may limit statistical power and reduce the generalizability of the results. Second, the study was conducted at a single centre, which may introduce institutional or regional biases and restrict the generalizability of the findings to other PD populations. Third, the questionnaire used was developed within a Thai cultural context and primarily focused on locally consumed foods. However, this may limit the generalizability of the findings to non-Thai populations. Therefore, the inclusion of modern and Western-influenced foods, such as milk, chocolate, and processed foods, ensured a broader representation of contemporary eating habits and improved their applicability beyond traditional Thai diets. Fourth, the cross-sectional design prevents causal inference and provides only a snapshot of dietary habits and health status at a single point in time, precluding causal inferences regarding the relationship between dietary habits and disease progression and clinical outcomes; findings should be interpreted as associative rather than causal. Fifth, the absence of bone health assessments, such as bone mineral density or fracture history, is particularly relevant in underweight and less mobile PD patients, where osteoporosis and fracture risk are common interrelated issues. Finally, the study was conducted within a Thai population, and dietary patterns can vary across regions and cultural contexts, with distinct food practices in different areas. Therefore, the generalizability of these results to other populations may be restricted. Additionally, reliance on self-reported dietary data may have introduced recall bias and subjective misreporting, as patients might not accurately recall or quantify their food intake and symptoms. Future research should employ longitudinal or multi-centre study designs to track changes in nutritional status, dysphagia progression, bone health, and mobility. Interventional studies incorporating targeted nutritional programmes, dysphagia management, and multidisciplinary care models would provide valuable evidence for improving clinical and nutritional outcomes in underweight PD patients.

Conclusion

This study highlights the distinct nutritional and clinical characteristics of underweight individuals with PD, underscoring the multifactorial nature of malnutrition in this population. Underweight PD patients experienced significantly greater difficulties with dysphagia and motor complications, especially with dyskinesia, both of which contributed to limited food variety and lower intake of key nutrients such as red meat and vegetables. Despite maintaining adequate hydration, their dietary patterns reflected compensatory adaptations to dysphagia rather than balanced nutritional choices.

Female gender, dysphagia, and dyskinesia emerged as key risk factors for being underweight, emphasising the importance of early identification of at-risk groups through systematic screening and targeted interventions. These findings reinforce the critical need for MDT nutritional management, involving dietitians, physicians, and rehabilitation specialists, to address dysphagia, mobility limitations, and nutrient deficiencies simultaneously.

Furthermore, integrating culturally adapted dietary assessment tools, such as the Thai Parkinson's Disease Dietary Habits Questionnaire, provides valuable insight into the intersection of traditional and modern eating patterns among people with PD in Thailand. Such tools can facilitate early nutritional assessment and guide personalised dietary strategies tailored to both cultural context and disease stage.

Future research should examine longitudinal changes in nutritional status, bone health, and functional mobility to understand how dietary patterns evolve over the course of disease progression. Interventional studies combining nutritional optimisation, dysphagia management, and musculoskeletal assessment, consistent with recent UK osteoporosis and fracture-risk guidelines, may offer a path toward improving both nutritional outcomes and quality of life for people living with PD.

Supplemental Material

sj-docx-1-pkn-10.1177_1877718X261445952 - Supplemental material for The taste of Parkinson's: How food choices reflect nutritional health

Supplemental material, sj-docx-1-pkn-10.1177_1877718X261445952 for The taste of Parkinson's: How food choices reflect nutritional health by Onanong Phokaewvarangkul, Narumol Sukmueng, Panthitra Kuwattanasuchati, Kanyawat Sanyawut, Naruemon Rattanapitak and Roongroj Bhidayasiri in Journal of Parkinson's Disease

Supplemental Material

sj-docx-2-pkn-10.1177_1877718X261445952 - Supplemental material for The taste of Parkinson's: How food choices reflect nutritional health

Supplemental material, sj-docx-2-pkn-10.1177_1877718X261445952 for The taste of Parkinson's: How food choices reflect nutritional health by Onanong Phokaewvarangkul, Narumol Sukmueng, Panthitra Kuwattanasuchati, Kanyawat Sanyawut, Naruemon Rattanapitak and Roongroj Bhidayasiri in Journal of Parkinson's Disease

Footnotes

Acknowledgements

This study was supported by multiple funding bodies: the Thailand Science Research and Innovation (TSRI, Programme Management Unit for Competitiveness, C01F670185), the National Economic and Social Development Council of Thailand, Thailand Centre of Excellence for Life Sciences (TC (ERP) 31/2568), the National Research Council of Thailand (N42A680591, N35E680087), and Chulalongkorn University (Ratchadapiseksompotch Fund, Faculty of Medicine (RA-MF-22/69) and Centre of Excellence Grant (CE68_028_3000_004)).

ORCID iDs

Roongroj Bhidayasiri

Onanong Phokaewvarangkul

Narumol Sukmueng

Panthitra Kuwattanasuchati

Kanyawat Sanyawut

Roongroj Bhidayasiri

Ethical consideration

Ethical approval was obtained from the Faculty of Medicine Ethics Committee at Chulalongkorn University, and informed consent was obtained from all participants before the study. The IRB number of this study is IRB 0933/66.

Consent to participate

Written informed consent was obtained from every patient.

Contributors

OP, NS, PK, KS, NR, and RB contributed to the study conception, design, and methodology. OP, NS, and PK contributed to the study analysis. OP contributed to writing the first draft. NS, PK, KS, NR, and RB contributed to the review and editing of the first draft. RB supervised the final draft, and all authors have approved the final manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported through the generous support of multiple funding bodies: the Thailand Science Research and Innovation (TSRI, Programme Management Unit for Competitiveness, C01F670185), the National Economic and Social Development Council of Thailand, Thailand Centre of Excellence for Life Sciences (TC (ERP) 31/2568), the National Research Council of Thailand (N42A680591, N35E680087), and Chulalongkorn University (CE68_028_3000_004).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The data supporting the main finding of this study are available on request from the corresponding author. Due to individuals’ privacy and ethical restrictions, these data are not publicly available.

Supplemental material

Supplemental material for this article is available online.

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