Periodic leg movements during sleep and cognitive functioning in the older 
general population

Marchi, Nicola Andrea; Peci, Arton; Haba-Rubio, José; Solelhac, Geoffroy; Bayon, Virginie; Berger, Mathieu; Vollenweider, Peter; Marques-Vidal, Pedro; von Gunten, Armin; Strippoli, Marie-Pierre Françoise; Preisig, Martin; Draganski, Bogdan; Heinzer, Raphael

doi:10.1016/j.sleep.2023.07.011

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Periodic leg movements during sleep and cognitive functioning in the older general population

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Draganski, Bogdan
Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Marchi, N. A., Peci, A., Haba-Rubio, J., Solelhac, G., Bayon, V., Berger, M., et al. (2023). Periodic leg movements during sleep and cognitive functioning in the older general population. Sleep Medicine, 109, 197-201. doi:10.1016/j.sleep.2023.07.011.

Cite as: https://hdl.handle.net/21.11116/0000-000D-75B6-2

Abstract

Objective
The current evidence of a relationship between periodic leg movements during sleep (PLMS) and cognitive functioning is limited and inconsistent. This cross-sectional study assessed associations between PLMS and cognitive functioning among community-dwelling older adults.

Methods
We included community-dwelling older adults who underwent a polysomnography and a cognitive assessment. The PLMS index (PLMI) and PLMS arousal index (PLMAI) were categorized into tertiles: PLMI <5/h (reference), 5–29.9/h, ≥30/h; and PLMAI <1/h (reference), 1–4.9/h, ≥5/h. The cognitive assessment consisted of ten scores covering the main cognitive domains: global cognition, processing speed, executive function, language, episodic verbal memory, and visuospatial function. Associations between PLMI, PLMAI, and cognitive scores were assessed using regression unadjusted and adjusted models.

Results
A total of 579 individuals without dementia were included (mean age: 71.5 ± 4.4 years; men 45.4%). The number of participants in the high-PLMI categories, 5–29.9/h and ≥30/h, was 185 (32.0%) and 171 (29.5%), respectively. Participants in the high-PLMI categories showed no significant difference compared to the reference group regarding their cognitive performance according to the unadjusted and adjusted models. Similarly, we found no association between PLMAI severity and cognitive functioning.

Conclusions
This study shows no cross-sectional association between PLMS severity and cognitive functioning among community-dwelling older adults. However, given the paucity of data in this field, further studies are needed to clarify the relationship between PLMS and cognitive functioning.