Abstract
Background
Parkinson’s disease (PD) is a neurodegenerative disorder characterised by motor and non-motor symptoms that impact quality of daily life, including diet and sleep. However, relatively little is known about dietary intake and quality in people with PD (PwP). Lifestyle factors, and how they relate to diet, are also insufficiently understood.
The aims of this study were to investigate dietary intake and quality, sleep and quality of life in PwP, and to explore the relationships between these factors.
Methods
Forty-five community-dwelling participants with PD (n = 45) were recruited to this cross-sectional study through the Cork Parkinson’s Association, Ireland. Dietary intake was assessed using the EPIC food frequency questionnaire, and diet quality was assessed using the Healthy Diet Indicator. Dietary intakes were compared to Irish RDAs for adults > 65 years. Sleep duration and quality were subjectively measured using the PD Sleep Scale and Pittsburgh sleep quality index and objectively measured by actigraphy in a subset of participants (n = 27). QOL was measured using the validated PDQ-39 questionnaire.
Results
Energy intake in PwP was significantly higher than that of the general population (2013 vs 1755 kcal/d, p = 0.01), despite their lower mean BMI (25.9 vs 27.7 kg/m2, p = 0.02). Intakes of carbohydrate, protein and fruits and vegetables were significantly higher in PwP compared to recommended and population intakes (all p < 0.01), but fibre intake was significantly lower than recommended (17.3 vs 25 g/d, p \(\le\) 0.05). Seventy-eight percent of participants had poor dietary quality, and poor sleep quality was associated with poor QOL.
Conclusions
Carbohydrates, protein, fruit and vegetable intakes were greater in PwP than population norms, but overall diet quality was low. Interventions to improve dietary and lifestyle factors may improve health and QOL in PwP.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Parkinson’s disease (PD) is a progressive neurodegenerative disorder affecting approximately 1% of the global population aged over 65 years [1]. Genetic and environmental risk factors are implicated in its aetiology [2]. Neuropathological hallmarks of PD include the progressive degeneration of midbrain dopaminergic neurons, which leads to loss of striatal dopamine levels and consequent motor impairments including rigidity, resting tremor and bradykinesia [2]. Additionally, intracellular accumulation of alpha-synuclein protein, in inclusions known as Lewy bodies that spread through the nervous system, contributes to non-motor PD symptoms including cognitive impairment, sleep disturbance, gastrointestinal dysfunction, dysphagia and depression [3]. Dopamine replacement pharmacotherapy is the mainstay treatment for PD, and clinical guidelines increasingly call for multi-disciplinary care for the management of motor and non-motor symptoms [4]. Side effects of long-term treatment, as well as natural disease progression, can lead to adverse consequences including impaired nutritional status and increased risk of malnutrition [5].
Unintended weight loss and reduced body mass index have been observed in PD cohorts, often despite increased energy intake [6]. The prevalence (0–24%) and risk (3–60%) of malnutrition amongst people with PD (PwP) varies, but aetiologically, symptoms such as constipation, dysphagia, olfactory dysfunction and appetite suppression can impact food intake, whilst involuntary motors symptoms increase energy expenditure, increasing the risk of malnutrition [5].
Studies investigating the impact of different dietary regimens on PD, notably the Mediterranean [7] and ketogenic diets [8] as well as bioactive compounds [9], are underway. However, an understanding of current dietary intake amongst PwP also warrants further research particularly given the conflicting data. Excessive carbohydrate intake amongst newly diagnosed PwP [10, 11], as well as a preference for sweet foods [12], has been reported. Data regarding protein intake is discordant; some studies have reported inadequate protein intakes [10, 12, 13], whilst others reported excessive protein intake compared to non-PD controls [13] and compared to recommended daily allowances [10]. Adherence to a protein redistribution diet, which is used to maximise absorption of levodopa, has also been shown to lead to low protein intake in this population [14]. However, there is some controversy regarding the data [15], and it has been reported that reduced protein intake may affect QOL [16].
Sleep disturbances occur in up to 98% of PwP, affecting both duration and quality of sleep as well as impacting daytime wakefulness [17]. In healthy populations, a bi-directional relationship between sleep quality and quantity, and diet, has been posited. Observational and experimental data indicate that inadequate sleep duration and quality adversely impact dietary intake [18, 19], and vice versa [20]. Inadequate sleep duration is associated with higher intakes of fat and protein [18, 21], whilst the impact on carbohydrate intake remains conflicted [22]. Additionally, overall dietary quality (DQ) is also adversely affected by sleep disturbances. Higher intakes of snacks, energy-dense foods [23, 24], confectionary [25] and sugar-sweetened drinks [24], as well as lower intakes of fruit, vegetables and wholegrains [26, 27], have been associated with inadequate sleep. A large observational study reported that poor sleep quality is significantly associated with greater energy intake and poor DQ, whilst good sleep quality significantly associated with Mediterranean diet adherence, which is indicative of better DQ [28]. Consequently, the preference for sweet foods, higher energy and lower protein intakes that are observed in PD patients may be influenced by sleep disturbances; therefore, the relationship between sleep and diet in PwP warrants further investigation. However, sleep studies should be interpreted with caution, as the majority are based on self-reported sleep and dietary intake and are thus open to response bias and misreporting. Additionally, controlled experimental and cross-sectional studies do not reflect habitual sleep, or the effects of chronic sleep debt.
Dietary intake and quality are associated with quality of life (QOL) [29], and, in PD, reduced QOL is commonplace [30]. Poor nutritional status and reduced QOL have been reported in PD [31], and a 6-week nutrition intervention for PwP at risk of, or experiencing, malnutrition significantly improved QOL [16]. In the Memory and Aging Project, a longitudinal cohort of elderly adults, the MIND dietary pattern (a combination of the dietary approaches used to prevent hypertension (DASH) and the Mediterranean diet) was shown to reduce the risk of developing PD, and to slow PD progression. The Mediterranean diet was observed to reduce the risk of disease progression, but no protective effect was observed with the DASH diet alone [32]. In other neurodegenerative disorders, positive correlations between greater intakes of fruit, vegetables and healthy fats (indicative of good DQ), and greater adherence to a Mediterranean diet, are associated with improved better QOL [31, 33, 34]. A systematic review found that better DQ or adherence to the Mediterranean diet in older adults with or at risk of chronic disease is positively associated with a better QOL [27]. Additionally, the MIND dietary pattern has been shown to be protective against risk of cognitive decline [35] and Alzheimer’s disease [36]. Given that PD is predominantly a disease of later life, these findings may be relevant to PwP, and they warrant further investigation.
As outlined, sleep disturbances and reduced QOL are prevalent in PD, and whilst little is known about diet intake and quality in PD, diet may affect QOL and, potentially, sleep. Understanding these interconnecting factors may inform tailored management strategies for PwP. Therefore, the aim of this study is to characterise dietary intake in a population of community-dwelling, free-living PwP in Ireland and to explore the relationship between dietary quality, sleep quality and QOL in this population.
Methods
Study design
A cross-sectional observational design was used to investigate DI, sleep quality and QOL in a free-living community population with PD. Associations between DI, sleep quality and QOL were explored. Ethical approval was granted by the Clinical Research Ethics Committee of the Cork Teaching Hospitals and University College Cork, Ireland.
Sample
A convenience sample of n = 45 community-dwelling adults (aged ≥ 18 years) diagnosed with PD in accordance with the Queen Square London Brain Bank Criteria [37] was recruited between 2016 and 2018 from the Cork Parkinson’s Association, Ireland. Participants were provided with an information leaflet outlining details of the study, and informed consent was obtained from each participant. Participants under aged 18 years, those with PD diagnosis ≤ 6 months prior to study initiation, students, non-English speakers, pregnant women, prisoners, BMI ≤ 18 kg/m2 or unexplained weight loss (> 10% in the previous 6 months) were excluded. Participants who were illiterate or had cognitive impairment that would limit the ability to give informed consent were also excluded.
Study variables
Demographic, anthropometric, dietary intake, sleep and QOL data were self-reported. Validated questionnaires were used. Participants completed hardcopies of the questionnaires during home and or clinic visits; questionnaires were self-completed, with assistance provided by the research team as needed. Data collection was carried out by a trained researcher within participants’ homes for approximately 45–60 min per visit.
Dietary intake and quality
Dietary intake (DI) was determined using the European Prospective Investigation of Cancer (EPIC)-Norfolk Food Frequency Questionnaire (FFQ), a validated and widely used dietary assessment method [38] previously used in PD [10] which measures habitual food intake during the previous year. The full EPIC-FFQ methodology has been described elsewhere [38]. Briefly, the EPIC-FFQ has two sections: part one includes a list of 130 food items, of which usual consumption is indicated from nine frequencies (never or less than once/month to up to six times/day), part two includes additional questions to determine specific intakes of milk, cereal and fat. FFQs were analysed using FFQ EPIC and Nutrition Tool for Analysis (FETA, Windows, version 2.53) [39] to obtain daily EI, macronutrient and micronutrient data. If the frequencies of ≥ 10 food items were missing, the FFQ was considered incomplete and excluded from analysis. Analysed DI data was compared to the National Adult Nutrition Survey (NANS) (Irish Universities Nutrition Alliance (IUNA), 2011) and the RDAs for Ireland [40,41,42] and used to determine DQ. Mean dietary intakes amongst PwP were compared to Irish RDAs for adults > 65 years of age.
The Healthy Diet Index (HDI) was used to determine DQ as it was based upon nutritional recommendations closer to the population studied [43] and provided an objective analysis. Bertenez et al. [44] described recent updates to the original HDI [45] that represent current dietary guidelines for chronic disease. The HDI includes seven nutrients/food groups, each scored dichotomously with a value of 1 or 0 (Table 1). Dichotomous variables were summed to give an HDI score between 0 and 7; higher scores demonstrate better DQ.
Sleep assessment
Sleep duration, latency and disturbance were objectively measured using actigraphy, a non-invasive, validated method for monitoring rest and activity cycles [46]. Participants wore an actigraph (Actigraph, Pensacola, FL, USA) on the non-dominant wrist for 7 days to track sleep and activity.
Sleep quality was also measured subjectively using three validated, self-report questionnaires: the Parkinson’s Disease Sleep Scale (PDSS), the PDSS-2 [47, 48] and the Pittsburgh Sleep Quality Index (PSQI) [49]. Participants with 310% missing data were excluded from analysis.
The PDSS and PDSS-2 assess nocturnal symptoms associated with PD during the previous week. The questionnaires consist of 15 questions; each question is rated on a 10-point (PDSS) or 5-point Likert scale (PDSS-2). PDSS scores were collapsed into a 5-point Likert scale for analysis and to align with the more contemporary PDSS-2 scoring system. Scores for each question were summed ranging from 0 (no disturbance) to 60 (maximum disturbance) [48]. A score ≥ 18 suggests clinically relevant poor sleep quality [50].
The PSQI questionnaire measures sleep quality over the previous month and consists of 10 questions, nine completed by the participant and one by a bed partner/roommate. The PSQI has seven components: sleep quality, latency, duration, disturbances, medication, habitual sleep efficiency and daytime dysfunction, each scored between 0 and 3. Scores of participant-completed questions were summed to give a total score ranging 0–21. A score ≥ 5 suggests poor sleep quality [49].
Quality of life
QOL was measured using the PD questionnaire-39 item (PDQ-39), a reliable and validated self-reported measure to assess health-related QOL over the previous month [51]. It consists of 39 questions assessing eight domains: mobility, emotional well-being, stigma, social support, cognition, communication, activities of daily living and bodily discomfort. Each question was scored on a 5-point Likert scale from 0 (never) to 4 (always). Scores for each question were summed to obtain a total PDQ-39 score; lower scores indicate better QOL. Domains were individually scored (sum of each item in the domain divided by maximum possible score within the domain/questions answered (for missing data)) ranging from 0 to 100. PDQ-39 summary index scores were calculated (sum of domain scores divided by eight) to provide a standardised QOL score [51].
Statistical analysis
Descriptive statistics were used to characterise the population. For outcomes data, Shapiro–Wilk tests were used to determine normality in each variable analysed. A one-sample t test was used to compare DI data to RDAs and population intakes, and a paired samples t test was used to compare self-reported and objective sleep duration and latency. Pearson’s correlations were used to compare sleep quality, DQ and QOL scores of normally distributed variables; Spearman’s correlations were used for non-normally distributed variables. Correlations were unmatched pairs. Data are reported as means ± standard deviation (SD) unless otherwise specified. Statistical significance is reported as p < 0.05. SPSS (version 25) was used for statistical analysis.
Results
Participant characteristics
The sample consisted of n = 45 adults with a PD diagnosis. Twelve participants were removed due to incomplete dietary, sleep and/or QOL questionnaires; one participant was removed as an outlier. Thirty-three participants (19 male, 14 female) were included in the analysis; mean age was 69 $$\pm $$ 9 years, and mean BMI was 25.9 $$\pm $$ 3.9 kg/m2 (Table 2).
Dietary intake and quality
Mean DIs were compared to Irish RDAs for adults > 65 years of age (Table 3). EIs were similar to SACN (2011) recommendations; however, saturated fat, protein, salt, calcium, vitamin b12 and fruits and vegetable intakes were all significantly higher than the RDA, whilst fibre and vitamin D were significantly lower. Carbohydrate and fat intakes were within recommended ranges [36, 37]. There is no RDA for alcohol. Compared to general population intakes (IUNA, 2011) (Table 3), intakes of energy, carbohydrate, protein, salt and fruits and vegetables were significantly greater in PwP, whereas intake of vitamin D was significantly lower. Fibre, alcohol and vitamin B12 intakes were similar to the general population. No data were recorded for saturated fat in the NANS (IUNA, 2011). The majority of the participants had poor diet quality (n = 26). No difference in diet quality was observed between males and females (male 1.58 ± 1.1 min vs female 2.21 ± 0.9 min, t(− 1.804), p = 0.81).
Sleep and quality of life
Sleep quality, sleep duration and QOL data are reported in Table 4. Mean sleep quality score, as assessed by PSQI, was 9 ± 5 and, as assessed by PDSS-2, was 22.2 ± 13, indicating that overall sleep quality was poor (35 and 318, PSQI and PDSS-2, respectively).
Objective sleep duration, measured by actigraphy (~ 7.5 \(\pm\) 1.4 h), was in line with current recommendations (7–8 h) [52]. However, self-reported sleep duration (~ 6.0 \(\pm\) 1.4 h) was significantly lower than objective sleep duration (t = − 4.54, p ≤ 0.01). Similarly, self-reported sleep latency (24.77 \(\pm\) 26.10 min) was significantly greater than objectively recorded sleep latency (11.08 \(\pm\) 9.60 min) (t = 2.61, p < 0.02) (Table 5). There were no significant sex differences in sleep duration (PSQI-derived sleep duration: male 371 ± 79.9 min vs female 364.1 ± 92.9 min, t(0.203), p = 0.841; actigraphy sleep duration: male 463.1 ± 74.2 min vs female 97.2 ± 29.3 min, t(0.639), p = 0.495). There were no significant sex differences in sleep latency (PSQI-derived sleep latency: male 28 ± 30.7 min vs female 19.9 ± 14.3 min, t(0.822), p = 0.419; actigraphy sleep latency: male 9.8 ± 9 min vs female 12.8 ± 10.6 min, t(− 0.786), p = 0.439).
Table 6 shows the associations between sleep quality, DQ and QOL using Spearman’s and Pearson’s correlation where appropriate. No correlation was found between sleep quality assessed by PDSS-2 or PSQI and DQ. PDSS-2 and PSQI total score showed no significant association between sleep quality and DQ (r = − 0.260, p = 0.18 and rs = − 0.229, p = 0.22 respectively). Similarly, there was no significant association between QOL, as measured by PDQ-39 total score or the summary index, and DQ (r = − 0.122, p = 0.52 and r = − 0.152, p = 0.42 respectively). A significant moderate positive correlation was found between both measures of sleep quality, PDSS-2 and PSQI total scores (rs = 0.455, p = 0.02).
A significant positive association was found between QOL, as measured by PDQ-39 summary index and sleep quality using both PDSS-2 and PSQI total score (r = 0.432, p = 0.03 and rs = 0.532, p ≤ 0.01 respectively). Similar correlations were reported when the PDQ-39 total score and PDSS-2 total score were used (rs = 0.499, p = 0.01). There was an insignificant trend towards a moderate positive association between PDQ-39 and PSQI total score (r = 0.350, p = 0.08).
Analysis of individual domains of QOL that compose the PDQ-39 found significant moderate positive associations between the emotional well-being (rs = 0.433, p = 0.02 and rs = 0.447, p = 0.02), cognition (rs = 0.490, p = 0.01 and r = 0.429, p = 0.03) and bodily discomfort (rs = 0.635, p ≤ 0.01 and r = 0.417, p = 0.03) domains and sleep quality as measured by PDSS-2 and PSQI, respectively. A significant moderate positive association was also found between activities of daily living and PDSS-2 (rs = 0.463, p = 0.01).
Discussion
This study aimed to characterise DI in a population of community-dwelling, free-living people with PD in Ireland, and to explore the relationships between DQ, sleep quality and QOL. Significant differences were observed between DIs in PwP compared to RDAs for Ireland and for the general population of the same age. The PD population had low DQ overall and significantly higher intakes of energy, carbohydrates, and fruit and vegetables, compared to the general population, whilst showing significantly lower fibre intake. Contradictions between carbohydrate, fruits and vegetables and fibre intake could be due to misreporting in the FFQ or to the small sample size. The free sugar intake in PwP was significantly higher than the RDA, whilst vitamin D intake was significantly lower, highlighting the potential need for vitamin D supplementation in this cohort. Consistent with current literature [53, 54], sleep quality was clinically poor as identified by two measures of sleep quality, PSQI and PDSS-2. Habitual sleep efficiency and sleep disturbance were the most affected domains as assessed on the PSQI. QOL was moderate in this cohort of PwP, with mobility, activities of daily living, cognition and bodily discomfort being the most affected domains.
Contrary to previous studies on healthy populations [26, 28, 29], DQ was not found to be associated with sleep quality or QOL in PD. However, poor sleep quality was significantly associated with reduced QOL, particularly in activities of daily living, emotional well-being, cognition and bodily discomfort domains.
Energy intake was similar to SACN (2011) recommendations, but significantly higher than population intakes (2127 vs 1755 kcal) despite a lower mean BMI amongst PwP (25.9 kg/m2) compared to the mean population BMI (27.7 kg/m2) (IUNA, 2011). This is consistent with existing literature [13, 55] and could be due to an increase in EE in PD, related to motor symptoms and treatment complications, suggesting that EIs are unable to compensate for increased requirements. However, Marczewska and colleagues reported no significant difference in EI or BMI in PwP compared to spouse controls, although it is expected that intakes of PwP and spouses would be similar [10]. In this population of PD patients, mean daily protein intake (1.22 g/kg/d) was significantly higher than the RDA (0.75 g/kg) and population intakes (1.02 g/kg), which is consistent with the research of Barichella et al. (2017) and Marczewska et al. (2006), both of whom also reported significant positive associations between protein intake, disease duration and higher levodopa doses [10, 13]. Protein-restricted diets have been proposed to reduce progression of PD and to affect the therapeutic efficiency of levodopa [15]. Barichella and colleagues [13] reported that protein intake of 10 g in excess of the RDA is associated with increased levodopa dose. Whilst no medication data is available for the participants in our study, future research should consider whether intakes such as that reported (1.22 g/kg/d) affect medication use and disease progression.
The percentage of energy intake from carbohydrate was significantly higher in this cohort of PwP than in the healthy population, though it was within the RDA, which supports previous research by Ådén et al. (2011) and Marczewska et al. (2006) [10, 11]. Estimated intake of free sugars was significantly higher than the recommended intake. This could potentially be related to the preference for sweet foods by PwP, as reported by Aiello et al., (2015) although it should be noted that unvalidated questionnaires were used in that study [12]. Preference for sweet food is theorised to be due to excessive dopamine neurotransmission related to PD treatment [56], although data from human studies is lacking.
In PwP, the percentage of energy obtained from fat intake was also within the RDA and similar to population intakes. This is consistent with dietary fat intake, assessed using the EPIC FFQ, from a cross-sectional study of 45 Italian PwP and their spouses [10]. In contrast, Barichella (2017) reported intakes of higher fat and saturated fat in PwP compared to controls. These differences in the literature could be due to the different FFQs used to measure DI. In the current study, the percentage of energy from saturated fat and free sugar intake was significantly higher than recommended, and fibre intake was lower than recommended; both of these are indicative of poor dietary quality. Indeed, 78% of participants were found to have poor overall DQ. Currently there is a lack of research exploring DQ in PD, but these findings suggest that there may be an opportunity for dietary management strategies to improve DQ in this cohort of patients.
Limitations of this study are recognised and include the small sample size which limits generalisability, the cross-sectional nature of the data which does not reflect longitudinal changes and the absence of data on medication use. Further, the EPIC FFQ was originally developed for the prospective investigation in cancer trial but, despite this, has been used previously in PD cohorts [10]. FFQ approaches for dietary assessment are regularly used in studies with PwP; however, shorter validated tools would be a welcome addition to the field, particularly given the potential impact of PD symptoms on the completion of longer FFQ which commonly contain in excess of 100 food items. Whilst the limitations of the existing data are acknowledged, this is the first study to investigate the relationship between DQ, QOL and sleep quality in a cohort of PD patients. It found no correlation between DQ and sleep quality, as assessed by two independent measures, PDSS-2 and PSQI. Evidence from previous studies on populations of healthy adults showed that poor sleep quality is significantly associated with lower DQ [57, 58]. However, these studies did not use validated tools to measure sleep quality, and so the results should be interpretated with that consideration. This study should encourage further work in the area, particularly research focused on individuals living well in the community, and interventions to address lifestyle factors to improve overall health and QOL in PwP.
Abbreviations
- BMI:
-
Body mass index
- DI:
-
Dietary intake
- DQS:
-
Dietary quality
- DQS:
-
Dietary quality score
- EE:
-
Energy expenditure
- EI:
-
Energy intake
- EFSA:
-
European Food Safety Authority
- EPIC:
-
European Prospective Investigation of Cancer
- FETA:
-
FFQ EPIC and Nutrition Tool for Analysis
- FFQ:
-
Food Frequency Questionnaire
- FSAI:
-
Food Safety Authority of Ireland
- HDI:
-
Healthy Diet Indicator
- IUNA:
-
Irish Universities Nutrition Alliance
- NANS:
-
National Adult Nutrition Survey
- PD:
-
Parkinson’s disease
- PDSS:
-
Parkinson’s disease Sleep Scale
- PDSS-2:
-
Parkinson’s disease Sleep Scale-2
- PDQ-39:
-
Parkinson’s disease questionnaire-39 item
- PSQI:
-
Pittsburgh Sleep Quality Index
- PwP:
-
People with Parkinson’s disease
- QOL:
-
Quality of life
- RDA:
-
Recommended daily allowance
- SACN:
-
Scientific Advisory Committee on Nutrition
- WHO:
-
World Health Organisation
References
de Lau LM, Breteler MM (2006) Epidemiology of Parkinson’s disease. Lancet Neurol 5(6):525–535
Kalia LV, Lang AE (2015) Parkinson’s disease. The Lancet 386(9996):896–912
Pfeiffer RF (2016) Non-motor symptoms in Parkinson’s disease. Parkinsonism Relat Disord 1(22):S119–S122
Overview (2021) Parkinson’s disease in adults | Guidance | NICE. NICE. Available from: https://www.nice.org.uk/guidance/ng71
Best practice guidance for dietitians on the nutritional management of Parkinson’s FINAL.pdf (2021) Available from: https://www.parkinsons.org.uk/sites/default/files/2021-02/Best%20practice%20guidance%20for%20dietitians%20on%20the%20nutritional%20management%20of%20Parkinson%27s%20FINAL.pdf
Ma K, Xiong N, Shen Y et al (2018) Weight loss and malnutrition in patients with Parkinson’s disease: current knowledge and future prospects. Front Aging Neurosci 10:1
Rusch C, Beke M, Tucciarone L et al (2021) Effect of a Mediterranean diet intervention on gastrointestinal function in Parkinson’s disease (the MEDI-PD study): study protocol for a randomised controlled trial. BMJ Open 11(9):e053336
Koh S, Dupuis N, Auvin S (2020) Ketogenic diet and neuroinflammation. Epilepsy Res 1(167):106454
Aryal S, Skinner T, Bridges B, Weber JT (2020) The pathology of Parkinson’s disease and potential benefit of dietary polyphenols. Molecules 25(19):4382
Marczewska A, De Notaris R, Sieri S et al (2006) Protein intake in Parkinsonian patients using the EPIC food frequency questionnaire. Mov Disord 21(8):1229–1231
Ådén E, Carlsson M, Poortvliet E et al (2011) Dietary intake and olfactory function in patients with newly diagnosed Parkinson’s disease: a case-control study. Nutr Neurosci 14(1):25–31
Aiello M, Eleopra R, Rumiati RI (2015) Body weight and food intake in Parkinson’s disease. A review of the association to non-motor symptoms. Appetite 84:204–11
Barichella M, Cereda E, Cassani E et al (2017) Dietary habits and neurological features of Parkinson’s disease patients: implications for practice. Clin Nutr 36(4):1054–1061
Barichella M, Cereda E, Pezzoli G (2009) Major nutritional issues in the management of Parkinson’s disease. Mov Disord 24(13):1881–1892
Wang L, Xiong N, Huang J et al (2017) Protein-restricted diets for ameliorating motor fluctuations in Parkinson’s disease. Front Aging Neurosci 28(9):206
Ongun N (2018) Does nutritional status affect Parkinson’s Disease features and quality of life? PLoS ONE 13(10):e0205100
Stefani A, Högl B (2020) Sleep in Parkinson’s disease. Neuropsychopharmacology 45(1):121–128
St-Onge MP, Roberts AL, Chen J et al (2011) Short sleep duration increases energy intakes but does not change energy expenditure in normal-weight individuals123. Am J Clin Nutr 94(2):410–416
St-Onge MP, Roberts A, Shechter A, Choudhury AR (2016) Fiber and saturated fat are associated with sleep arousals and slow wave sleep. J Clin Sleep Med 12(01):19–24
Godos J, Grosso G, Castellano S et al (2021) Association between diet and sleep quality: a systematic review. Sleep Med Rev 1(57):101430
Grandner MA, Kripke DF, Naidoo N, Langer RD (2010) Relationships among dietary nutrients and subjective sleep, objective sleep, and napping in women. Sleep Med 11(2):180
Fenton S, Burrows TL, Skinner JA, Duncan MJ (2021) The influence of sleep health on dietary intake: a systematic review and meta-analysis of intervention studies. J Hum Nutr Diet 34(2):273–285
Chaput JP (2014) Sleep patterns, diet quality and energy balance. Physiol Behav 134(C):86–91
Dashti HS, Scheer FA, Jacques PF et al (2015) Short sleep duration and dietary intake: epidemiologic evidence, mechanisms, and health implications12. Adv Nutr 6(6):648–659
Katagiri R, Asakura K, Kobayashi S, Suga H (2014) Low intake of vegetables, high intake of confectionary, and unhealthy eating habits are associated with poor sleep quality among middle-age female Japanese workers. J Occup Health 56:359–368
Mossavar-Rahmani Y, Weng J, Wang R et al (2017) Actigraphic sleep measures and diet quality in the Hispanic Community Health Study/Study of Latinos Sueño ancillary study. J Sleep Res 26(6):739–746
Katagiri R, Asakura K, Kobayashi S et al (2014) The Three-generation Study of Women on Diets and Health Study Group. Low intake of vegetables, high intake of confectionary, and unhealthy eating habits are associated with poor sleep quality among middle-aged female Japanese workers. J Occup Health 56(5):359–68
Mamalaki E, Anastasiou CA, Ntanasi E et al (2018) Associations between the mediterranean diet and sleep in older adults: results from the hellenic longitudinal investigation of aging and diet study. Geriatr Gerontol Int 18(11):1543–1548
Govindaraju T, Sahle BW, McCaffrey TA et al (2018) Dietary patterns and quality of life in older adults: a systematic review. Nutrients 10(8):971
Duncan GW, Khoo TK, Yarnall AJ et al (2014) Health-related quality of life in early Parkinson’s disease: the impact of nonmotor symptoms. Mov Disord 29(2):195–202
Sheard JM, Ash S, Mellick GD et al (2014) Improved nutritional status is related to improved quality of life in Parkinson’s disease. BMC Neurol 14(1):212
Agarwal P, Wang Y, Buchman AS et al (2018) MIND diet associated with reduced incidence and delayed progression of parkinsonism in old age. J Nutr Health Aging 22(10):1211–1215
Hadgkiss EJ, Jelinek GA, Weiland TJ et al (2015) The association of diet with quality of life, disability, and relapse rate in an international sample of people with multiple sclerosis. Nutr Neurosci 18(3):125–136
Rivadeneyra J, Cubo E, Gil C et al (2016) Factors associated with Mediterranean diet adherence in Huntington’s disease. Clin Nutr ESPEN 1(12):e7-13
Morris MC, Tangney CC, Wang Y et al (2015) MIND diet slows cognitive decline with aging. Alzheimers Dement J Alzheimers Assoc 11(9):1015–1022
Morris MC, Tangney CC, Wang Y et al (2015) MIND diet associated with reduced incidence of Alzheimer’s disease. Alzheimers Dement J Alzheimers Assoc 11(9):1007–1014
Hughes AJ, Daniel SE, Kilford L, Lees AJ (1992) Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry 55(3):181–184
McKeown NM, Day NE, Welch AA et al (2001) Use of biological markers to validate self-reported dietary intake in a random sample of the European Prospective Investigation into Cancer United Kingdom Norfolk cohort. Am J Clin Nutr 74(2):188–196
Mulligan AA, Luben RN, Bhaniani A et al (2014) A new tool for converting food frequency questionnaire data into nutrient and food group values: FETA research methods and availability. BMJ Open 4(3):e004503
Authority (EFSA) (2017) EFS Dietary reference values for nutrients summary report. EFSA Support Publ 14(12):e15121E
Ireland (FSAI) (1999) FSA of. Recommended dietary allowances for Ireland: 1999 / Food Safety Authority of Ireland. Available from: https://www.lenus.ie/handle/10147/44808
Scientific Advisory Committee on Nutrition (SACN) (2011) Dietary reference values for energy
Weltgesundheitsorganisation, FAO (edit)(2003) Diet, nutrition, and the prevention of chronic diseases: report of a WHO-FAO Expert Consultation; [Joint WHO-FAO Expert Consultation on Diet, Nutrition, and the Prevention of Chronic Diseases, 2002, Geneva, Switzerland]. Geneva: World Health Organization 149 p. (WHO technical report series)
Berentzen NE, Beulens JW, Hoevenaar-Blom MP et al (2013) Adherence to the WHO’s healthy diet indicator and overall cancer risk in the EPIC-NL cohort. PLoS ONE 8(8):e70535
Huijbregts P, Feskens E, Räsänen L et al (1997) Dietary pattern and 20 year mortality in elderly men in Finland, Italy, and The Netherlands: longitudinal cohort study. BMJ 315(7099):13–17
Quante M, Kaplan ER, Cailler M et al (2018) Actigraphy-based sleep estimation in adolescents and adults: a comparison with polysomnography using two scoring algorithms. Nat Sci Sleep 10:13–20
Chaudhuri K, Pal S, DiMarco A et al (2002) The Parkinson’s disease sleep scale: a new instrument for assessing sleep and nocturnal disability in Parkinson’s disease. J Neurol Neurosurg Psychiatry 73(6):629–635
Trenkwalder C, Kohnen R, Högl B et al (2011) Parkinson’s disease sleep scale—validation of the revised version PDSS-2. Mov Disord 26(4):644–652
Spira AP, Beaudreau SA, Stone KL et al (2012) Reliability and validity of the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale in older men. J Gerontol A Biol Sci Med Sci 67A(4):433–439
Muntean ML, Benes H, Sixel-Döring F et al (2016) Clinically relevant cut-off values for the Parkinson’s Disease Sleep Scale-2 (PDSS-2): a validation study. Sleep Med 1(24):87–92
Jenkinson C, Fitzpatrick R, Peto V et al (1997) The Parkinson’s Disease Questionnaire (PDQ-39): development and validation of a Parkinson’s disease summary index score. Age Ageing 26(5):353–357
Hirshkowitz M, Whiton K, Albert SM et al (2015) National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health 1(1):40–43
Arnaldi D, Cordano C, De Carli F et al (2016) Parkinson’s Disease Sleep Scale 2: application in an Italian population. Neurol Sci 37(2):283–288
Chen L, Liu C, Ye Z, Wang B, He S (2018) Assessment of sleep quality using cardiopulmonary coupling analysis in patients with Parkinson’s disease. Brain Behav 8(5):e00970
van der Marck MA, Dicke HC, Uc EY et al (2012) Body mass index in Parkinson’s disease: a meta-analysis. Parkinsonism Relat Disord 18(3):263–267
Miwa H, Kondo T (2008) Alteration of eating behaviors in patients with Parkinson’s disease: possibly overlooked? Neurocase 14(6):480–484
Štefan L, Radman I, Podnar H, Vrgoč G (2018) Sleep duration and sleep quality associated with dietary index in free-living very old adults. Nutrients 10(11):1748
Stern JH, Grant AS, Thomson CA et al (2014) Short sleep duration is associated with decreased serum leptin, increased energy intake, and decreased diet quality in postmenopausal women. Obes Silver Spring Md 22(5):E55-61
Acknowledgements
This work was kindly supported by the Cork Parkinson’s Association and its members.
Funding
Open Access funding provided by the IReL Consortium.
Author information
Authors and Affiliations
Contributions
This study was designed by AMS, GWOK and MOK. PM, SA and AMS obtained ethical approval, undertook data collection and data analysis. DD undertook data entry and developed the analysis plan. MOK and DD undertook statistical analysis. DD, MOK and GWOK and AS wrote the manuscript. The final manuscript was edited and approved by all authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Dunk, D., Mulryan, P., Affonso, S. et al. Diet quality, sleep and quality of life in Parkinson’s disease: a cross-sectional study. Ir J Med Sci 192, 1371–1380 (2023). https://doi.org/10.1007/s11845-022-03144-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11845-022-03144-1