Objective: Patients with Willis-Ekbom disease (restless legs syndrome [RLS]) frequently report seasonal worsening of their symptoms; however, seasonal patterns in this disorder have not been systematically evaluated. The purpose of our investigation was to utilize Internet search query data to test the hypothesis that restless legs symptoms vary by season, with worsening in the summer months.
Methods: Internet search query data were obtained from Google Trends. Monthly normalized search volume was determined for the term restless legs between January 2004 and December 2012. Using cosinor analysis, seasonal effects were tested for data from the United States, Australia, Germany, the United Kingdom, and Canada.
Results: Cosinor analysis revealed statistically significant seasonal effects on search queries in the United States (P=.005), Australia (P=.00007), Germany (P=.00009), and the United Kingdom (P=.003), though a trend was present in the search data from Canada (P=.098). Search queries peaked in summer months in both northern (June and July) and southern (January) hemispheres. Search query volume increased by 24-40% during summer relative to winter months across all evaluated countries.
Conclusions: Evidence from Internet search queries across a wide range of dates and geographic areas suggested a seasonality of restless legs symptomatology with a peak in summer months. Our novel finding in RLS epidemiology needs to be confirmed in additional samples, and underlying mechanisms must be elucidated.
Keywords: Cosinor analysis; Google trends; Restless leg syndrome; Restless legs; Seasonality; Willis-Ekbom disease.
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