Leveraging Google Trends to investigate the global public interest in rheumatoid arthritis

  • Guo-Cui Wu
  • Sha-Sha Tao
  • Chan-Na Zhao
  • Yan-Mei Mao
  • Qian Wu
  • Yi-Lin Dan
  • Hai-Feng PanEmail author
Public Health


This study aims to investigate the global public interest in rheumatoid arthritis by evaluating search term popularity changes of the disease over a decade. Google Trends was applied to retrieve search popularity scores for the term ‘rheumatoid arthritis’ between January 2004 and December 2017, utilizing the category of “health”. Overall, relative searches volume for rheumatoid arthritis steadily decreased from January 2004 to December 2010, and then slowly rose from January 2011 to December 2017. There were significant seasonal variations in relative searches volume for the term ‘rheumatoid arthritis’ (Amplitude = 3.11; Phase: Month = 4.3; Low point: Month = 10.3; p < 0.025). Relative searches volume peaked in April and reached the lowest level in October. The top 11 rising topics were scleroderma, Anna Marchesini, C-reaction protein, osteoarthritis, arthritis, joint pain, autoimmune disease, rheumatoid factor, rheumatology, methotrexate, and systemic lupus erythematosus, ranking from high to low by relative growth of topic regarding rheumatoid arthritis. In conclusion, the evidence from Google Trends analysis demonstrates a significant seasonal variation in rheumatoid arthritis, with a peak in April. In addition, the top rising search queries are beneficial for physicians to search the Internet themselves for websites that provide high-quality information to recommend to their patients.


Google Trends Global public interest Rheumatoid arthritis Seasonality 


Author contribution

GCW, SST, CNZ, YMM, and HFP conceptualized the study, participated in the study design, and revised the manuscript. GCW and CNZ wrote the manuscript. QW and YLD collected the data, conducted the statistical analysis, and revised the manuscript. All authors read and approved the final manuscript.


The Doctoral research Grant from Anhui Medical University (XJ201712), and the scientific research grant from Anhui Medical University (2017xkj010) and the National Natural Science Foundation of China (81872687).

Compliance with ethical standards

Conflicts of interest

All authors declare that they have no conflict of interest.


  1. 1.
    Fazal SA, Khan M, Nishi SE, Alam F, Zarin N, Bari MT, Ashraf GM (2018) A clinical update and global economic burden of rheumatoid arthritis. Endocr Metab Immune Disord Drug Targets 18(2):98–109. CrossRefGoogle Scholar
  2. 2.
    Burska A, Boissinot M, Ponchel F (2014) Cytokines as biomarkers in rheumatoid arthritis. Mediators Inflamm 2014:545493. Google Scholar
  3. 3.
    Cross M, Smith E, Hoy D, Carmona L, Wolfe F, Vos T, Williams B, Gabriel S, Lassere M, Johns N, Buchbinder R, Woolf A, March L (2014) The global burden of rheumatoid arthritis: estimates from the global burden of disease 2010 study. Ann Rheum Dis 73(7):1316–1322. CrossRefGoogle Scholar
  4. 4.
    van der Vaart R, Drossaert CH, Taal E, van de Laar MA (2011) Patient preferences for a hospital-based rheumatology Interactive Health Communication Application and factors associated with these preferences. Rheumatology (Oxford) 50(9):1618–1626. CrossRefGoogle Scholar
  5. 5.
    Bundorf MK, Wagner TH, Singer SJ, Baker LC (2006) Who searches the Internet for health information? Health Serv Res 41(3 Pt 1):819–836. CrossRefGoogle Scholar
  6. 6.
    Baker L, Wagner TH, Singer S, Bundorf MK (2003) Use of the Internet and e-mail for health care information: results from a national survey. JAMA 289(18):2400–2406. CrossRefGoogle Scholar
  7. 7.
    NetMarketShare (2018) Search engine market share. Accessed 21 June 2018
  8. 8.
    Cervellin G, Comelli I, Lippi G (2017) Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings. J Epidemiol Glob Health 7(3):185–189. CrossRefGoogle Scholar
  9. 9.
    Brigo F, Trinka E (2015) Google search behavior for status epilepticus. Epilepsy Behav 49:146–149. CrossRefGoogle Scholar
  10. 10.
    Schootman M, Toor A, Cavazos-Rehg P, Jeffe DB, McQueen A, Eberth J, Davidson NO (2015) The utility of Google Trends data to examine interest in cancer screening. BMJ Open 5(6):e006678. CrossRefGoogle Scholar
  11. 11.
    Solano P, Ustulin M, Pizzorno E, Vichi M, Pompili M, Serafini G, Amore M (2016) A Google-based approach for monitoring suicide risk. Psychiatry Res 246:581–586. CrossRefGoogle Scholar
  12. 12.
    Rossignol L, Pelat C, Lambert B, Flahault A, Chartier-Kastler E, Hanslik T (2013) A method to assess seasonality of urinary tract infections based on medication sales and google trends. PLoS One 8(10):e76020. CrossRefGoogle Scholar
  13. 13.
    Jellison SS, Bibens M, Checketts J, Vassar M (2018) Using Google Trends to assess global public interest in osteoarthritis. Rheumatol Int 38(11):2133–2136. CrossRefGoogle Scholar
  14. 14.
    Barnett AG, Baker P, Dobson AJ (2012) Analysing seasonal data. R J 4(1):5–10. CrossRefGoogle Scholar
  15. 15.
    Barnett AG, Baker P (2018) Seasonal analysis of health data. R package version 0:3-5. Accessed 06 Dec 2018
  16. 16.
    Abhishek A, Doherty M, Kuo CF, Mallen CD, Zhang W, Grainge MJ (2017) Rheumatoid arthritis is getting less frequent-results of a nationwide population-based cohort study. Rheumatology (Oxford) 56(5):736–744. Google Scholar
  17. 17.
    Jacobsson LT, Hanson RL, Knowler WC, Pillemer S, Pettitt DJ, McCance DR, Bennett PH (1994) Decreasing incidence and prevalence of rheumatoid arthritis in Pima Indians over a 25-year period. Arthritis Rheum 37(8):1158–1165. CrossRefGoogle Scholar
  18. 18.
    Doran MF, Pond GR, Crowson CS, O’Fallon WM, Gabriel SE (2002) Trends in incidence and mortality in rheumatoid arthritis in Rochester, Minnesota, over a 40-year period. Arthritis Rheum 46(3):625–631. CrossRefGoogle Scholar
  19. 19.
    Azevedo R, Bernardes M, Fonseca J, Lima A (2015) Smartphone application for rheumatoid arthritis self-management: cross-sectional study revealed the usefulness, willingness to use and patients’ needs. Rheumatol Int 35(10):1675–1685. CrossRefGoogle Scholar
  20. 20.
    Castillo-Ortiz JD, de Jesus Valdivia-Nuno J, Ramirez-Gomez A, Garagarza-Mariscal H, Gallegos-Rios C, Flores-Hernandez G, Hernandez-Sanchez L, Brambila-Barba V, Castaneda-Sanchez JJ, Barajas-Ochoa Z, Suarez-Rico A, Sanchez-Gonzalez JM, Ramos-Remus C (2016) Fifteen-year trend in information on the World Wide Web for patients with rheumatoid arthritis: evolving, but opportunities for improvement remain. Rheumatol Int 36(9):1281–1289. CrossRefGoogle Scholar
  21. 21.
    Iikuni N, Nakajima A, Inoue E, Tanaka E, Okamoto H, Hara M, Tomatsu T, Kamatani N, Yamanaka H (2007) What’s in season for rheumatoid arthritis patients? Seasonal fluctuations in disease activity. Rheumatology (Oxford) 46(5):846–848. CrossRefGoogle Scholar
  22. 22.
    Feldthusen C, Grimby-Ekman A, Forsblad-d’Elia H, Jacobsson L, Mannerkorpi K (2016) Seasonal variations in fatigue in persons with rheumatoid arthritis: a longitudinal study. BMC Musculoskelet Disord 17:59. CrossRefGoogle Scholar
  23. 23.
    Szucs G, Szekanecz Z, Zilahi E, Kapitany A, Barath S, Szamosi S, Vegvari A, Szabo Z, Szanto S, Czirjak L, Gyorgy Kiss C (2007) Systemic sclerosis-rheumatoid arthritis overlap syndrome: a unique combination of features suggests a distinct genetic, serological and clinical entity. Rheumatology (Oxford) 46(6):989–993. CrossRefGoogle Scholar
  24. 24.
    Pope JE (2002) Scleroderma overlap syndromes. Curr Opin Rheumatol 14(6):704–710. CrossRefGoogle Scholar
  25. 25.
    Clements PJ, Allanore Y, Khanna D, Singh M, Furst DE (2012) Arthritis in systemic sclerosis: systematic review of the literature and suggestions for the performance of future clinical trials in systemic sclerosis arthritis. Semin Arthritis Rheum 41(6):801–814. CrossRefGoogle Scholar
  26. 26.
    Horimoto AM, da Costa IP (2016) Overlap between systemic sclerosis and rheumatoid arthritis: a distinct clinical entity? Rev Bras Reumatol Engl Ed 56(4):287–298. CrossRefGoogle Scholar
  27. 27.
    Mahroum N, Bragazzi NL, Sharif K, Gianfredi V, Nucci D, Rosselli R, Brigo F, Adawi M, Amital H, Watad A (2018) Leveraging Google Trends, Twitter, and Wikipedia to investigate the impact of a celebrity’s death from rheumatoid arthritis. J Clin Rheumatol 24(4):188–192. CrossRefGoogle Scholar
  28. 28.
    Vogt B, Fuhrnrohr B, Muller R, Sheriff A (2007) CRP and the disposal of dying cells: consequences for systemic lupus erythematosus and rheumatoid arthritis. Autoimmunity 40(4):295–298. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of NursingAnhui Medical UniversityHefeiChina
  2. 2.Department of Epidemiology and Biostatistics, School of Public HealthAnhui Medical UniversityHefeiChina
  3. 3.Anhui Province Key Laboratory of Major Autoimmune DiseasesHefeiChina

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