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Updated: Sep 10, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Body composition and resting metabolic rate in Parkinson's disease: A prospective cross-sectional single centre study
M K Farsana1, Shweta Prasad1, Vikram V Holla1
1Department of Neurology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Hosur Road, Bengaluru, 560029, Karnataka, India.
Introduction:
Altered body composition in Parkinson's disease (PD) is a frequent but inadequately understood manifestation with significant clinical and prognostic implications. Resting metabolic rate (RMR) is found to be higher in the postural-instability and gait-difficulty subtype of PD.
Objectives:
To study the body composition and RMR in patients with PD and to compare with healthy controls and among motor subtypes.
Methods:
This study reports an interim analysis of a prospective study of 392 patients with PD and 137 healthy controls from a tertiary care center in India. Detailed clinical evaluation was performed, including body composition measurements using bioelectric impedance based body composition monitor.
Results:
The mean age at onset and duration of illness were 48.4 ± 11.7 and 6.0 ± 4.1 years, respectively. Weight loss was reported in 12.8 % of patients. Compared to controls, PD patients had significantly lower body weight (63.4 vs 70.6 kg), BMI (24.4 vs 27.5 kg/m2), visceral fat percentage (9.8 % vs 12.3 %), and abdominal girth (92.8 vs 94.8 cm), with higher skeletal muscle percentage (26.3 % vs 25.3 %). RMR was lower in patients with dyskinesia. BMI and visceral fat negatively correlated with disease duration.
Conclusions:
The lower body weight, fat percentage, and higher skeletal muscle percentage in PD can be attributed to a negative energy balance resulting in fat loss. This finding contradicts the concept of sarcopenic obesity in PD. Lower RMR in patients with dyskinesia could be attributed to more severe disease with low body weight. These findings prompt further studies with a larger cohort for better understanding.
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