Literature DB >> 24152798

Seasonal trends in restless legs symptomatology: evidence from Internet search query data.

David G Ingram1, David T Plante.   

Abstract

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.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cosinor analysis; Google trends; Restless leg syndrome; Restless legs; Seasonality; Willis-Ekbom disease

Mesh:

Year:  2013        PMID: 24152798     DOI: 10.1016/j.sleep.2013.06.016

Source DB:  PubMed          Journal:  Sleep Med        ISSN: 1389-9457            Impact factor:   3.492


  24 in total

1.  Seasonality of bruxism: evidence from Google Trends.

Authors:  Sinan Kardeş; Elif Kardeş
Journal:  Sleep Breath       Date:  2019-02-21       Impact factor: 2.816

2.  Seasonal variation in the internet searches for gout: an ecological study.

Authors:  Sinan Kardeş
Journal:  Clin Rheumatol       Date:  2018-10-29       Impact factor: 2.980

3.  Potential uses of an infodemiology approach for health-care services for rheumatology.

Authors:  Gerardo Martinez-Arroyo; Stephanie Ramos-Gomez; Elias Kaleb Rojero-Gil; Joel A Rojas-Gongora; Aldo Barajas-Ochoa; Lilia Patricia Bustamante-Montes; Jose Yañez; Cesar Ramos-Remus
Journal:  Clin Rheumatol       Date:  2018-11-17       Impact factor: 2.980

4.  Seasonal trends in tinnitus symptomatology: evidence from Internet search engine query data.

Authors:  David T Plante; David G Ingram
Journal:  Eur Arch Otorhinolaryngol       Date:  2014-09-19       Impact factor: 2.503

5.  Seasonal effects on the occurrence of nocturnal leg cramps: a prospective cohort study.

Authors:  Scott R Garrison; Colin R Dormuth; Richard L Morrow; Greg A Carney; Karim M Khan
Journal:  CMAJ       Date:  2015-01-26       Impact factor: 8.262

6.  Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data.

Authors:  David G Ingram; Camilla K Matthews; David T Plante
Journal:  Sleep Breath       Date:  2014-03-05       Impact factor: 2.816

7.  The seasonal pattern of restless legs syndrome in a sample from the Korean Health Insurance Review and Assessment Service national database.

Authors:  Seong Min Oh; Kyung-Lak Son; Seok-Jin Choi; Mi Hyun Lee; So Young Yoon; Yu Jin Lee
Journal:  J Clin Sleep Med       Date:  2021-05-01       Impact factor: 4.062

8.  The use of google trends in health care research: a systematic review.

Authors:  Sudhakar V Nuti; Brian Wayda; Isuru Ranasinghe; Sisi Wang; Rachel P Dreyer; Serene I Chen; Karthik Murugiah
Journal:  PLoS One       Date:  2014-10-22       Impact factor: 3.240

9.  Google Trends reveals increases in internet searches for insomnia during the 2019 coronavirus disease (COVID-19) global pandemic.

Authors:  Kirsi-Marja Zitting; Heidi M Lammers-van der Holst; Robin K Yuan; Wei Wang; Stuart F Quan; Jeanne F Duffy
Journal:  J Clin Sleep Med       Date:  2021-02-01       Impact factor: 4.062

10.  Detecting epidemiological relevance of adenoid hypertrophy, rhinosinusitis, and allergic rhinitis through an Internet search.

Authors:  Yingchao Yang; Xinyi Li; Qiang Ma; Zhihui Fu; Kaiming Su
Journal:  Eur Arch Otorhinolaryngol       Date:  2021-06-09       Impact factor: 3.236

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.