Motor, Psychiatric and Fatigue Features Associated with Nutritional Status and Its Effects on Quality of Life in Parkinson’s Disease Patients

OBJECTIVES: Parkinson's disease (PD) patients are more likely to develop impaired nutritional status because of the symptoms, medications and complications of the disease. However, little is known about the determinants and consequences of malnutrition in PD. This study aimed to investigate the association of motor, psychiatric and fatigue features with nutritional status as well as the effects of malnutrition on different aspects of quality of life (QoL) in PD patients. METHODS: One hundred and fifty patients with idiopathic PD (IPD) were recruited in this study. A demographic checklist, the Unified Parkinson's Disease Rating Scale (UPDRS), the Hospital Anxiety and Depression Scale (HADS) and the Fatigue Severity Scale (FSS) were completed through face-to-face interviews and clinical examinations. The health-related QoL (HRQoL) was also evaluated by means of the Parkinson's Disease Questionnaire (PDQ-39). For evaluation of nutritional status, the Mini Nutritional Assessment (MNA) questionnaire was applied together with anthropometric measurements. RESULTS: Thirty seven (25.3%) patients were at risk of malnutrition and another 3 (2.1%) were malnourished. The total score of the UPDRS scale (r =  -0.613, P<0.001) and PD duration (r =  -0.284, P = 0.002) had a significant inverse correlation with the total MNA score. The median score of the Hoehn and Yahr stage was significantly higher in PD patients with abnormal nutritional status [2.5 vs. 2.0; P<0.001]. More severe anxiety [8.8 vs. 5.9; P = 0.002], depression [9.0 vs. 3.6; P<0.001] and fatigue [5.4 vs. 4.2; P<0.001] were observed in PD patients with abnormal nutritional status. Except for stigma, all other domains of the PDQ-39 were significantly correlated with the total score of the MNA. CONCLUSION: Our study demonstrates that disease duration, severity of motor and psychiatric symptoms (depression, anxiety) and fatigue are associated with nutritional status in PD. Different aspects of the HRQoL were affected by patients' nutritional status especially the emotional well-being and mobility domains

Baseline, anthropometric and clinical characteristics of the recruited Parkinson’s disease patients (n = 150).

<p>Baseline, anthropometric and clinical characteristics of the recruited Parkinson’s disease patients (n = 150).</p

Descriptive characteristics of nutritional status (MNA), disease-related quality of life (PDQ-39), anxiety, depression (HADS) and fatigue (FSS) in Parkinson’s disease (PD) patients.

<p>Descriptive characteristics of nutritional status (MNA), disease-related quality of life (PDQ-39), anxiety, depression (HADS) and fatigue (FSS) in Parkinson’s disease (PD) patients.</p

Multivariate regression models to determine the motor and non-motor factors independently related to total score of the MNA questionnaire (model 1) and having abnormal versus normal nutritional status (model 2) in recruited Parkinson’s disease (PD) patients.

<p>In both regression models, age at the time of diagnosis, sex, weight-adjusted levodopa dosage, the score of the each part of the UPDRS scale, total UPDRS score, Hoehn & Yahr stage, Schwab & England ADL score, anxiety, depression and fatigue scores were entered as the predictor list.</p

Comparison of the mean [standard deviation (SD)] scores of different motor, psychiatric, fatigue and quality of life (PDQ-39) scales between subgroups of Parkinson’s disease (PD) patients regarding nutritional status (MNA).

<p># Values are presented as median (IQR).</p

Pearson correlation between the scores of different motor, psychiatric, fatigue and quality of life (PDQ-39) scales and nutritional status (MNA) in Parkinson’s disease (PD) patients.

<p>**Correlation is significant at the 0.01 level (2-tailed).</p><p>*Correlation is significant at the 0.05 level (2-tailed).</p

Prevalence and associated comorbidities of restless legs syndrome (RLS): Data from a large population-based door-to-door survey on 19176 adults in Tehran, Iran

<div><p>Background</p><p>Discrepancies have been reported in the prevalence rate of restless legs syndrome (RLS) among different ethnic groups and geographic populations. Furthermore, there are disagreements on determinant factors and associated comorbidities of RLS. We aimed to estimate prevalence of RLS and investigate its associated comorbid conditions and risk factors in a large population-based door-to-door survey.</p><p>Methods</p><p>Following a multistage random sampling from the households lived in 22 urban districts of Tehran, Iran, 19176 participants with ≥30 years of age were recruited. Trained surveyors filled study checklist consisting of baseline characteristics, risk factors and comorbidity profile and the International RLS Study Group (IRLSSG) diagnostic criteria through face-to-face interviews.</p><p>Results</p><p>In total, 1580 individuals were positively screened for RLS resulting in a standardized prevalence rate of 60.0/1000. There was a gradual increase in RLS prevalence by advancing age, however, sex difference disappeared after adjustment. Parkinsonism [adjusted odds’ ratio (adj-OR) = 7.4 (95% CI: 5.3–10.4)], peripheral neuropathy [adj-OR = 3.7 (95% CI: 3.3–4.1)], subjective cognitive impairment (SCI) [adj-OR = 3.1 (95% CI: 2.7–3.4)], acting out dreams [adj-OR = 2.8 (95% CI: 2.5–3.2)], hyposmia [adj-OR = 2.5 (95% CI: 2.2–2.9)], active smoking [adj-OR = 1.5 (95% CI: 1.3–1.9)] and additional number of cardiometabolic diseases associated with higher risk of RLS [adj-OR = 1.6 (95% CI: 1.2–2.3)].</p><p>Conclusion</p><p>Our findings showed that neuro-cognitive co-morbidities such as parkinsonism, peripheral neuropathy, SCI, acting out dreams and hyposmia as well as cardio-metabolic risk factors and diseases were independent determinants of RLS. It is recommended to screen individuals with either these comorbid conditions for RLS or the ones with RLS for the accompanying diseases.</p></div

Multivariate binary logistic regression models to indicate independent determinants of restless legs syndrome among those without peripheral neuropathy.

<p>Multivariate binary logistic regression models to indicate independent determinants of restless legs syndrome among those without peripheral neuropathy.</p

Multivariate binary logistic regression models to indicate independent determinants of restless legs syndrome in the entire study population.

<p>Multivariate binary logistic regression models to indicate independent determinants of restless legs syndrome in the entire study population.</p