Korean J Sports Med KJSM The Korean Journal of Sports Medicine 1226-3729 2288-6028 The Korean Society of Sports Medicine 10.5763/kjsm.2019.37.4.155 Clinical Article Clinical Sports Medicine Achilles Tendon Injury and Seasonal Variation: An Analysis Using Google Trends https://orcid.org/0000-0002-5460-8420 Cha Yun-Sik https://orcid.org/0000-0002-8594-5745 Hwang Seok-Min https://orcid.org/0000-0003-2116-6918 Yang Pei-Jiun Department of Orthopedic Surgery, Seoul Red Cross Hospital, Seoul, Korea. Correspondence: Seok-Min Hwang. Department of Orthopedic Surgery, Seoul Red Cross Hospital, 9 Saemunan-ro, Jongno-gu, Seoul 03181, Korea. Tel: +82-2-2002-8000, Fax: +82-2-2002-8855, gulpae@naver.com 12 2019 06 12 2019 37 4 155 161 23 08 2019 14 10 2019 19 10 2019 Copyright © 2019 The Korean Society of Sports Medicine 2019 The Korean Society of Sports Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Purpose

Achilles tendon injury is one of the most common sports-related injuries. Several studies suggest that Achilles tendon injury is associated with seasonal variation. The purpose of this study is to determine the relationship between seasonal variations and Achilles tendon injury through Google Trends (GT) and to evaluate the correlation between GT and actual data.

 Methods

We identified three articles through PubMed database as control group. The experimental group (GT group) was collected from GT by setting the same conditions as the control group. For GT group, we use the search terms related to the Achilles tendon injury. The exploration period was set from January 1, 2004 to December 31, 2018.

 Results

There is approximately more than 90% (p<0.05) correlation between GT group and control group. The incidences of Ontario were the highest in the summer. Those of New York and Vancouver were higher in spring compared to those of Ontario.

 Conclusion

Our study implies that there is significant seasonal variation for Achilles tendon injury. Most of these injuries seem to occur in spring and summer. Also, there is a significant relationship between GT data and actual data. If the data from GT can be analyzed properly, these approach methods will be useful for epidemiological research.

 Achilles tendon Big data Incidence Seasons

No potential conflict of interest relevant to this article was reported.

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The bar graph showing the area comparison of percentages with that Google Trends [GT] and Actual [A]. (A) In Ontario, the volumes of seasonal variations are as follows: spring (GT, 27.6%; A, 24.3%), summer (GT, 35.7%; A, 33.9%), fall (GT, 20.3%; A, 23.4%), winter (GT, 16.5%; A, 18.5%). (B) The values for New York are: spring (GT, 29.4%; A, 31.8%), summer (GT, 28.1%; A, 28.6%), fall (GT, 20.3%; A, 15.9%), winter (GT, 22.2%; A, 23.7%). (C) The values for Vancouver are: spring (GT, 30.1%; A, 29.7%), summer (GT, 25.9%; A, 26.2%), fall (GT, 20.9%; A, 21.9%), winter (GT, 23.1%; A, 22.3%). The threshold of significance is adjusted at p<0.05. Time series plots for the relative search volume in the Ontario, New York, and Vancouver from January 1, 2004 to December 31, 2018. (A) Ontario (µ<sub>MAX</sub>, 54.77/yr; R<sup>2</sup>, 0.66; p<0.05). (B) New York (µ<sub>MAX</sub>, 49.99/yr; R<sup>2</sup>, 0.68; p<0.05). (C) Vancouver (µ<sub>MAX</sub>, 5.82/yr; R<sup>2</sup>, 0.02; p=0.63). Correlation with actual data

R: correlation coefficient.

*p<0.05.

 High and low point month of searching frequency

*Numeric values correspond to months as follows: January=1, February=2, March=3, April=4, May=5, June=6, July=7, August=8, September=9, October=10, November=11, and December=12; high point month was maximum search frequency; low point month was minimal search frequency; †p<0.025.