Chinese Interest in Thyroid Related Diseases: Evidence from Baidu Index

Chinese Interest in Thyroid Related Diseases: Evidence from Baidu Index | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chinese Interest in Thyroid Related Diseases: Evidence from Baidu Index Zhao-ya Fan, Yuan-lin Mou, Qian Hu, Ruo-yun Yin, Lei Tang, Fan Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1190514/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Common thyroid diseases are hyperthyroidism, hypothyroidism, thyroiditis, thyroid tumor and so on. Baidu is currently the most widely used online search tool in China, has developed an internet search trends collection and analysis tool called the Baidu Index. The aim of the present study was to understand the trend and characteristics of public’s online attention to thyroid diseases, and to explore the value of Baidu Index in monitoring online retrieval behavior of thyroid related information. Methods: Taking the period from January 1, 2011 to December 31, 2019 as the time range into consideration, we used the big data analysis tool of Baidu Index and took “thyroid nodules”, “thyroid cancer”, “thyroiditis” “hyperthyroidism” and “hypothyroidism” as the keywords, the data of “search index” and “media index” were recorded on a weekly basis, and all information were aggregated into quarterly and annual to generate the final data which was carried out for secondary analysis. Pearson correlation analysis was used to analyze the correlation between the search index of keywords and the year. One-way Analysis of Variance was used to analyze the differences between search index and media index. Results: Among the five keywords, thyroid nodule search index had the highest growth rate (640%), followed by thyroid cancer (298%). The media’s attention to thyroid diseases had been declining year by year. Unlike the public’s attention, the media index of hyperthyroidism was significantly higher than other keywords. Conclusion: Over the past nine years, the public's attention to thyroid related diseases has been increasing gradually. Baidu Index is an effective tool to track the health information query behavior of Chinese internet users, which can provide a cost-effective supplement to traditional monitoring system. Other Public Policy Health Policy Baidu Index media search engines thyroid diseases Figures Figure 1 Figure 2 Background Thyroid diseases (TDs) are a category of non-communicable disease that are easy to neglected, misdiagnosed and poorly managed ( 1 ). At both ends of the spectrum, inadequate or excessive iodine intake can lead to thyroid disorders ( 2 ). China was an iodine deficient country with a high prevalence of iodine deficiency disorders ( 3 ), and in 1996, China implemented Universal Salt Iodization (USI) legislation nationally. During the 20 years of USI enactment, China has experienced excessive iodine intake (defined as median urine iodine concentration (UIC) ≥ 300 µg/L) for 5 years (1996-2001), more than adequate iodine intake (defined as median UIC from 200 to 299 µg/L) for 10 years (2002-2011), and adequate iodine intake (defined as median UIC from 100 to 199 µg/L) for 5 years (2012-2016) ( 4 ). Since TDs are a health care and socio-economic burden in China, there has been increased interest in research on TDs intervention and prevention ( 5 – 7 ). The development of the internet has greatly changed people’s lives, especially the expansion of search engines, which has further enhanced the value of the internet as a tool for life, learning and work. According to the 47th Statistical Report on Internet Development in China, there were approximately 989 million internet users in China by the end of December 2020, and the internet penetration rate reached 70.4% ( 8 ). It was estimated that the utilization rate of search engine among netizens was about 81.3%. 77.3% of users could find the information they need through this service. Baidu search accounted for 90.9% of search engine users, ranking first ( 9 ). Through the analysis of these online search trend data, it is possible to reflect the pattern of health information search behavior and interest of internet users on population level. This study used the Baidu Index data platform to obtain data and conduct secondary analysis in order to understand the characteristics of public attention to TDs, information search behavior and the trend of media attention, to explored the value of internet search data in monitoring online information search behavior. Methods Data from Baidu Index The data from Baidu Index ( http://index.baidu.com/Helper/?tpl=helpandword=#pdesc ) was used. Baidu Index is a big data sharing platform constructed by massive user behavior information, which shows the search trend of the selected keywords, gain insight into the changes in the needs of netizens, monitor the trend of media public opinion, and locate the characteristics of users. The platform can provide data such as search index, demand map, information index, media index and population attributes. The data used in this study included: 1) search index: the data based on the search volume of netizens in Baidu, with keywords as statistical objects, scientifically analyze and calculate the weighted search frequency of each keyword in Baidu web search. 2) media index: the number of news reported by major internet media related to keywords and included by Baidu News Channel. 3) annual netizen search rate: search index/annual number of netizens (the annual number of netizens comes from the Statistical Report on Internet Development in that year). The keyword “thyroid” was searched through the demand map of Baidu Index platform, and the weekly keyword demand map was collected in December 2019. The keywords related to TDs with the highest demand were selected: “thyroid nodule”, “thyroid cancer”, “thyroiditis”, “hyperthyroidism” and “hypothyroidism”. The two nouns of non-thyroid related diseases: “what are the symptoms of thyroid” and “thyroid function” were excluded. The search index and media index for each keyword from January 1, 2011 to December 31, 2019 were obtained, a total of nine complete years. At the same time, due to the limitations of Baidu Index tools and the needs of research and analysis, this study recorded the data of search index and media index with weekly as the smallest unit, and summarized them to the quarter and year as the basis for subsequent data analysis. Statistical methods We added up the five keyword search indexes of each year to get the annual search index; the differences of annual search index, quarterly search index and annual media index of each keyword were analyzed by one-way ANOVA; the correlation between search index and year was analyzed by Pearson correlation analysis. After drawing the scatter plot and the regression line of the netizens' search rate in each year, the covariance analysis was conducted to test the statistical difference of the slope of the regression line among each group. P <0.05 (two-tailed) was considered statistically significant. Microsoft Office Excel 365 (Microsoft, Redmond, WA, USA) and SPSS version 20.0 (SPSS, Inc., Chicago, IL, USA) were used to draw figures, and all statistics analyses were performed with SPSS. Results Changes in search index Over the past nine years, the sum of the annual search index of each keyword showed an upward trend and was positively correlated with the year (Pearson’s correlation=0.983, P <0.001).The Figure 1 showed the changing trend of the annual search index. Each keyword was also positively correlated with the year (thyroid nodule: Pearson’s correlation=0.981, P <0.001, thyroid cancer: Pearson’s correlation=0.956, P <0.001, thyroiditis: Pearson’s correlation=0.934, P <0.001, hyperthyroidism: Pearson’s correlation=0.784, P =0.012; hypothyroidism: Pearson’s correlation=0.954, P <0.001). In terms of search index growth, the absolute increase of thyroid nodule search index was the highest (4236537), followed by hyperthyroidism (1845562). The growth rate of thyroid nodule was the highest (640%), followed by thyroid cancer (298%). The changes of each search index over the nine years and their correlation with years were represented in Table 1 . Table 1 Basic situation and correlation analysis of search index from 2011 to 2019 Keywords 2011 2012 2013 2014 2015 2016 2017 2018 2019 Increment Increment rate (%) Correlation coefficient P Thyroid nodule 662208 964825 1140236 1808814 3122765 3425706 4071499 4034230 4898745 4236537 640 0.981 <0.001 Thyroid cancer 388935 561461 677555 712290 723164 877078 1007796 1297074 1549871 1160936 298 0.956 <0.001 Thyroiditis 221298 293053 344820 357781 348763 378601 409109 429130 421535 200237 90 0.934 <0.001 Hyperthyroidism 1402019 3027818 2150914 2536677 2670551 3136113 3393895 3258544 3247581 1845562 132 0.784 0.012 Hypothyroidism 402925 585253 564211 642715 748042 934890 1338790 1377319 1330711 927786 230 0.954 <0.001 Annual search index 3077385 5432410 4877736 6058277 7613285 8752388 10221089 10396297 11448443 8371058 272 0.983 <0.001 Using the least-significant difference method, we found that there was a statistical difference between the search index of thyroid nodule and thyroid cancer, thyroiditis and hypothyroidism ( P <0.001), and between hyperthyroidism and thyroid cancer, thyroiditis and hypothyroidism ( P <0.001). However, there was no statistical difference between thyroid nodule and hyperthyroidism ( P =0.838). The search index of thyroid nodule surpassed that of hyperthyroidism for the first time in April 2015 and was higher than that of hyperthyroidism for four consecutive years; the search index of thyroid nodule and hyperthyroidism was always higher than that of the other three keywords in nine years. The specific results were shown in Table 2 . Table 2 Multiple comparisons between keywords (search index) Keywords P 95% CI Thyroid nodule Thyroid cancer <0.001 1058300.69 2571433.53 Thyroiditis <0.001 1568426.69 3081559.53 Hyperthyroidism 0.838 -833797.98 679334.87 Hypothyroidism <0.001 1043897.13 2557029.98 Thyroid cancer Thyroiditis 0.181 -246440.42 1266692.42 Hyperthyroidism <0.001 -2648665.09 -1135532.24 Hypothyroidism 0.969 -770969.98 742162.87 Thyroiditis Hyperthyroidism <0.001 -3158791.09 -1645658.24 Hypothyroidism 0.169 -1281095.98 232036.87 Hyperthyroidism Hypothyroidism <0.001 1121128.69 2634261.53 As shown in Figure 2 ,in the past nine years, the annual search rate of netizens showed an upward trend, and the regression linear slope of the five keywords was all greater than 0. The results of the covariance analysis showed that there was a statistical difference in the linear regression slope between different groups (F=16.876, P <0.001). Changes in media index Unlike the keywords search index, the media index showed a downward trend in nine years (Pearson’s correlation=-0.835, P =0.005). The Table 3 showed the changes in the media index for each keyword over the nine years. Among them, the media index of hyperthyroidism was statistically different from that of thyroid nodule ( P =0.039), thyroiditis ( P <0.001), and hypothyroidism ( P =0.010). The relationship between other keywords were shown in Table 4 . Table 3 Basic situation of media index from 2011 to 2019 Keywords 2011 2012 2013 2014 2015 2016 2017 2018 2019 Thyroid nodule 327 662 322 1336 638 201 170 134 250 Thyroid cancer 624 1382 371 481 651 445 204 199 218 Thyroiditis 173 282 129 280 13 0 0 0 0 Hyperthyroidism 1818 1237 1442 1960 672 380 126 120 190 Hypothyroidism 739 523 232 784 385 118 67 67 76 Media index 3681 4086 2496 4841 2359 1144 567 520 734 Table 4 Multiple comparisons between keywords (media index) Keywords P 95% CI Thyroid nodule Thyroid cancer 0.772 -471.04 352.15 Thyroiditis 0.092 -60.15 763.04 Hyperthyroidism 0.039 -845.49 -22.29 Hypothyroidism 0.570 -295.04 528.15 Thyroid cancer Thyroiditis 0.050 -0.71 822.49 Hyperthyroidism 0.073 -786.04 37.15 Hypothyroidism 0.393 -235.60 587.60 Thyroiditis Hyperthyroidism <0.001 -1196.93 -373.73 Hypothyroidism 0.256 -646.49 176.71 Hyperthyroidism Hypothyroidism 0.010 138.85 962.04 Discussion The results of this study showed that public attention to TDs had increased in the past nine years, but there were differences in different diseases. The attention of thyroid nodule and hyperthyroidism was significantly higher than that of hypothyroidism, thyroid cancer and thyroiditis, and the growth rate of thyroid nodule search index was more than twice that of the second place. Although all keywords showed an upward trend, the rising trend of thyroid nodule was more obvious than the other four keywords. This might be related to the increased in the prevalence of thyroid nodule in recent years ( 10 ). The incidence of thyroid nodules was insidious,and most patients were asymptomatic in the early stage, and patients were more likely to inquire relevant information on their own after detecting discomfort ( 11 ). As the largest search tool in China, Baidu’s search results can reflect people's needs well. The disease prediction product jointly developed by Baidu and the Chinese Center for Disease Control and Prevention can provide real-time data on infectious diseases ( 12 ). At the same time, it can also be used to predict the epidemic trend of diseases, as a powerful complement to the traditional detection system ( 13 ). Baidu Index has not been used for TDs related research in China. Our study is the first attempt to explore the behavior and interest of Chinese netizens in TDs, confirming the potential of using online search trend data to represent the real situation of TDs patients in China. For the media index part, the results showed that the media’s attention to the hyperthyroidism was higher than other keywords. This suggested that the media had pushed and reported more information about hyperthyroidism to the public in the past nine years. Overall, the media attention of TDs was on the decline. The reason might be related to the rapid development of the internet, the scattered news points, the shortage of media practitioners and the declined in the number of media concerned about TDs. Despite the huge medical expenditure imposed on China by TDs ( 14 ), due to China's vast territory and large population, it is difficult to evaluate the true prevalence rate of TDs and to understand the characteristics and needs of TDs patients. With the wide application of the internet and the increasing reliance of the public on search engines as the main way to query health information, some online digital diseases surveillance tools has been explored in recent years ( 15 – 17 ). As a query tool, search engine can provide sensitive information on the disease before the diagnosis of the disease is reported, thus improving disease control. Internet big data has a broad application prospect in the medical field, which may be a supplement and an expansion of the current clinical and epidemiological data. Today, with the rapid development of the internet services and search engines, combined with network data analysis can be regarded as an auxiliary means of traditional disease monitoring. Limitations This study also has several limitations. First, we only focused on the attention of Baidu search engine users to TDs, without considering the public attention on other search engines or social media, which can only reflect part of the public’s attention to TDs. Second, there might be sampling biases in Baidu Index. Although the internet penetration rate in China had been greatly improved, the characteristics of internet users were obviously skewed to those with higher socioeconomic level and better educated segments. Third, Baidu Index algorithm has not been made public. Conclusion Between 2011 and 2019, the online search rate of TDs maintained a sustained growth while the media index showed a downward trend. The Baidu Index can be used to track Chinese netizens' online behavior and interest in TDs. This may help to improve our understanding of the incidence of disease, patient education and the use of online resources. Internet search trend data is a valuable source for monitoring the search behavior of TDs-related information. It can be used as an exploratory tool to better understand the characteristics and preferences of patients and provide a scientific evidence for the control and prevention of TDs in China. Abbreviations TDs:Thyroid diseases USI:Universal Salt Iodization Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The data analyzed in this study are availiable in Baidu Index Data Platform (http://index.baidu.com/Helper/?tpl=helpandword=#pdesc) Competing interests The authors declare that they have no competing interests Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions All authors contributed to the study conception and design. The manuscript writing for the original draft and data analysis were completed by Zhao-ya Fan. Yuan-lin Mou and Qian Hu gave the paper revision and format adjustment work. The rest of the authors gave the paper revision and grammar editing work. Ruo-yun Yin and Lei Tang gave the entire process technical and paper writing guidance support. All authors read and approved the final manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Disclosure The author reports no conflicts of interest in this work. References Fualal J, Ehrenkranz J. Access, availability, and infrastructure deficiency: The current management of thyroid disease in the developing world. Rev Endocr Metab Dis. 2016;17:583–89. doi: 10.1007/s11154-016-9376-x Zimmermann MB, Boelaert K. Iodine deficiency and thyroid disorders. Lancet. Diabetes Endocrinol. 2015;3:286–95. doi: 10.1016/S2213-8587(14)70225-6 Ma T, Guo J, Wang F. The epidemiology of iodine-deficiency diseases in China. Am J Clinical Nutrition . 1993;57(2):264S-66S. doi: 10.1093/ajcn/57.2.264S Li Y, Di Teng, Ba J, Chen B, Du J, He L, et al. Efficacy and safety of long-term universal salt iodization on thyroid disorders: epidemiological evidence from 31 provinces of mainland China. Thyroid . 2020;30:568–79. doi: 10.1089/thy.2019.0067 Shan Z, Chen L, Lian X, Liu C, Shi B, Shi L, et al. The iodine status and prevalence of thyroid disorders after introduction of mandatory universal salt iodization for 16 years in China: A cross-sectional study in 10 cities. Thyroid . 2016;26:1125–30. doi: 10.1089/thy.2015.0613 Liang Z, Xu C, Luo Y. Association of iodized salt with goiter prevalence in Chinese populations: a continuity analysis over time. Mil Med Res . 2017;4:8. doi: 10.1186/s40779-017-0118-5 Gu F, Ding G, Lou X, Wang X, Mo Z, Zhu W, et al. Incidence of thyroid diseases in Zhejiang Province, China, after 15 years of salt iodization. J Trace Elem Med Bio. 2016;36:57–64. doi: 10.1016/j.jtemb.2016.04.003 China Internet Network Information Center (CNNIC). The 47th China Statistical Report on Internet Development. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm . Accessed 14 February 2021. China Internet Network Information Center (CNNIC). China statistical report on search engine, 2019. (2019). http://www.cnnic.cn/hlwfzyj/hlwxzbg/ssbg/201910/t20191025_70843.htm . Accessed 14 February 2021. Yu CC, Wang Q. An initial analysis on thyroid nodules prevalence and influencing factors of Chinese healthy adults in 2008-2014. J Environ Health. 2016;33:440–43. doi: 10.16241/j.cnki.1001-5914.2016.05.016 Zou B, Wang X, Sun L, Zhou Y, Chen ZT. Prevalence of Thyroid Nodules in Health Checkups and Its Relationship with Metabolic Diseases. Chin Gen Pract . 2020;23:2423–28. doi: 10.12114/j.issn.1007-9572.2020.00.089 Li K, Liu ML, Feng Y, Ning CY, Ou WD, Sun J, et al. Using Baidu Search Engine to Monitor AIDS Epidemics Inform for Targeted intervention of HIV/AIDS in China. Sci Rep . 2019;9:320. doi: 10.1038/s41598-018-35685-w Chen SY. Big data applications and practices of Baidu. Big Data Res . 2015;1:104–14. Xie DY, Wang Q, Li C, Wang Z, Song CY. Analysis of the Influencing Factors of Hospitalization Expense of Patients with Thyroid Carcinoma in a Hospital. China Health Insurance. 2018:46–50. doi: 10.19546/j.issn.1674-3830.2018.1.011 Tu BZ, Wei LF, Jia YY, Qian J. Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index. BMC Infect Dis . 2021;21:98. doi: 10.1186/s12879-020-05740-x Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The use of google trends in health care research: a systematic review. Plos One. 2014;9:e109583. doi: 10.1371/journal.pone.0109583 Gluskin RT, Johansson MA, Santillana M, Brownstein JS. Evaluation of Internet-based dengue query data: Google Dengue Trends. PloS Negl Trop Dis . 2014;8:e2713. doi: 10.1371/journal.pntd.000271 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1190514","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":72860082,"identity":"6a6a1ee2-541a-4348-9934-3ceaea63c678","order_by":0,"name":"Zhao-ya Fan","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhao-ya","middleName":"","lastName":"Fan","suffix":""},{"id":72860083,"identity":"2a1decb1-bee8-43a6-ab72-0056b4c6a153","order_by":1,"name":"Yuan-lin Mou","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuan-lin","middleName":"","lastName":"Mou","suffix":""},{"id":72860084,"identity":"4567d838-125c-4f9c-b1bc-9b71fede5d0b","order_by":2,"name":"Qian Hu","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Hu","suffix":""},{"id":72860085,"identity":"1a8b710f-d6cb-443d-a95f-a028602119ae","order_by":3,"name":"Ruo-yun Yin","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ruo-yun","middleName":"","lastName":"Yin","suffix":""},{"id":72860086,"identity":"58254348-0820-48c2-a418-add79ff45d9b","order_by":4,"name":"Lei Tang","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Tang","suffix":""},{"id":72860087,"identity":"b34e2de9-94a6-4292-949b-258c6496bc46","order_by":5,"name":"Fan Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAq0lEQVRIiWNgGAWjYFACxgYQKcfG3n6ANC3GfDxnEkizK3GehIMBcUr5pZsbP7zNOZzeJsGQwPCjYhthLZJzDjZLzt12OLdNuvEAY8+Z24S1GNxIbGPmBWmROZDAzNhGhBZ7qJZ0NokEA+K0GEhAtCQQr0XiDtgv6YZtwEA+SJRf+Ge3P/zwdpu1vHx7+8EHPyqI0MIgAcQ8UPYBItSjaRkFo2AUjIJRgBUAAMYLPCupLjmYAAAAAElFTkSuQmCC","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2021-12-21 03:59:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1190514/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1190514/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16847165,"identity":"6e5e8589-b4d3-4230-aea8-6eb604a58a58","added_by":"auto","created_at":"2021-12-29 19:25:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93575,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the annual search index\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1190514/v1/5e796de490b3a03dc4ff3c6a.png"},{"id":16847166,"identity":"ecbcc8c8-9001-4afd-a1b3-88dff2ab4806","added_by":"auto","created_at":"2021-12-29 19:25:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112730,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of annual netizen search rate\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1190514/v1/09f542a2efcead9347ffc74d.png"},{"id":16847167,"identity":"7dc078f5-5aff-44f1-870f-10ec7b044c38","added_by":"auto","created_at":"2021-12-29 19:25:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":438623,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1190514/v1/7cfbdc1c-d19d-4875-9580-357feab93d83.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eChinese Interest in Thyroid Related Diseases: Evidence from Baidu Index\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eThyroid diseases (TDs) are a category of non-communicable disease that are easy to neglected, misdiagnosed and poorly managed (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). At both ends of the spectrum, inadequate or excessive iodine intake can lead to thyroid disorders (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). China was an iodine deficient country with a high prevalence of iodine deficiency disorders (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), and in 1996, China implemented Universal Salt Iodization (USI) legislation nationally. During the 20 years of USI enactment, China has experienced excessive iodine intake (defined as median urine iodine concentration (UIC) \u0026ge; 300 \u0026micro;g/L) for 5 years (1996-2001), more than adequate iodine intake (defined as median UIC from 200 to 299 \u0026micro;g/L) for 10 years (2002-2011), and adequate iodine intake (defined as median UIC from 100 to 199 \u0026micro;g/L) for 5 years (2012-2016) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Since TDs are a health care and socio-economic burden in China, there has been increased interest in research on TDs intervention and prevention (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe development of the internet has greatly changed people\u0026rsquo;s lives, especially the expansion of search engines, which has further enhanced the value of the internet as a tool for life, learning and work. According to the 47th Statistical Report on Internet Development in China, there were approximately 989 million internet users in China by the end of December 2020, and the internet penetration rate reached 70.4% (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). It was estimated that the utilization rate of search engine among netizens was about 81.3%. 77.3% of users could find the information they need through this service. Baidu search accounted for 90.9% of search engine users, ranking first (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Through the analysis of these online search trend data, it is possible to reflect the pattern of health information search behavior and interest of internet users on population level.\u003c/p\u003e \u003cp\u003eThis study used the Baidu Index data platform to obtain data and conduct secondary analysis in order to understand the characteristics of public attention to TDs, information search behavior and the trend of media attention, to explored the value of internet search data in monitoring online information search behavior.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData from Baidu Index\u003c/h2\u003e \u003cp\u003eThe data from Baidu Index (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://index.baidu.com/Helper/?tpl=helpandword=#pdesc\u003c/span\u003e\u003c/span\u003e) was used. Baidu Index is a big data sharing platform constructed by massive user behavior information, which shows the search trend of the selected keywords, gain insight into the changes in the needs of netizens, monitor the trend of media public opinion, and locate the characteristics of users. The platform can provide data such as search index, demand map, information index, media index and population attributes.\u003c/p\u003e \u003cp\u003eThe data used in this study included: 1) search index: the data based on the search volume of netizens in Baidu, with keywords as statistical objects, scientifically analyze and calculate the weighted search frequency of each keyword in Baidu web search. 2) media index: the number of news reported by major internet media related to keywords and included by Baidu News Channel. 3) annual netizen search rate: search index/annual number of netizens (the annual number of netizens comes from the Statistical Report on Internet Development in that year).\u003c/p\u003e \u003cp\u003eThe keyword \u0026ldquo;thyroid\u0026rdquo; was searched through the demand map of Baidu Index platform, and the weekly keyword demand map was collected in December 2019. The keywords related to TDs with the highest demand were selected: \u0026ldquo;thyroid nodule\u0026rdquo;, \u0026ldquo;thyroid cancer\u0026rdquo;, \u0026ldquo;thyroiditis\u0026rdquo;, \u0026ldquo;hyperthyroidism\u0026rdquo; and \u0026ldquo;hypothyroidism\u0026rdquo;. The two nouns of non-thyroid related diseases: \u0026ldquo;what are the symptoms of thyroid\u0026rdquo; and \u0026ldquo;thyroid function\u0026rdquo; were excluded. The search index and media index for each keyword from January 1, 2011 to December 31, 2019 were obtained, a total of nine complete years. At the same time, due to the limitations of Baidu Index tools and the needs of research and analysis, this study recorded the data of search index and media index with weekly as the smallest unit, and summarized them to the quarter and year as the basis for subsequent data analysis.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eWe added up the five keyword search indexes of each year to get the annual search index; the differences of annual search index, quarterly search index and annual media index of each keyword were analyzed by one-way ANOVA; the correlation between search index and year was analyzed by Pearson correlation analysis. After drawing the scatter plot and the regression line of the netizens' search rate in each year, the covariance analysis was conducted to test the statistical difference of the slope of the regression line among each group. \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 (two-tailed) was considered statistically significant. Microsoft Office Excel 365 (Microsoft, Redmond, WA, USA) and SPSS version 20.0 (SPSS, Inc., Chicago, IL, USA) were used to draw figures, and all statistics analyses were performed with SPSS.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003eChanges in search index\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eOver the past nine years, the sum of the annual search index of each keyword showed an upward trend and was positively correlated with the year (Pearson\u0026rsquo;s correlation=0.983, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001).The Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e showed the changing trend of the annual search index. Each keyword was also positively correlated with the year (thyroid nodule: Pearson\u0026rsquo;s correlation=0.981, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, thyroid cancer: Pearson\u0026rsquo;s correlation=0.956, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, thyroiditis: Pearson\u0026rsquo;s correlation=0.934, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, hyperthyroidism: Pearson\u0026rsquo;s correlation=0.784, \u003cem\u003eP\u003c/em\u003e=0.012; hypothyroidism: Pearson\u0026rsquo;s correlation=0.954, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). In terms of search index growth, the absolute increase of thyroid nodule search index was the highest (4236537), followed by hyperthyroidism (1845562). The growth rate of thyroid nodule was the highest (640%), followed by thyroid cancer (298%). The changes of each search index over the nine years and their correlation with years were represented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBasic situation and correlation analysis of search index from 2011 to 2019\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"14\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKeywords\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncrement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncrement rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCorrelation coefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e662208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e964825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1140236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1808814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3122765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3425706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4071499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4034230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4898745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4236537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e388935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e561461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e677555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e712290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e723164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e877078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1007796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1297074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1549871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1160936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e221298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e293053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e344820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e357781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e348763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e378601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e409109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e429130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e421535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1402019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3027818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2150914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2536677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2670551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3136113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3393895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3258544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3247581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1845562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e402925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e585253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e564211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e642715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e748042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e934890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1338790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1377319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1330711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e927786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnual search index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3077385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5432410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4877736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6058277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7613285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8752388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10221089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10396297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11448443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8371058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eUsing the least-significant difference method, we found that there was a statistical difference between the search index of thyroid nodule and thyroid cancer, thyroiditis and hypothyroidism (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), and between hyperthyroidism and thyroid cancer, thyroiditis and hypothyroidism (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). However, there was no statistical difference between thyroid nodule and hyperthyroidism (\u003cem\u003eP\u003c/em\u003e=0.838). The search index of thyroid nodule surpassed that of hyperthyroidism for the first time in April 2015 and was higher than that of hyperthyroidism for four consecutive years; the search index of thyroid nodule and hyperthyroidism was always higher than that of the other three keywords in nine years. The specific results were shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultiple comparisons between keywords (search index)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKeywords\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1058300.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2571433.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1568426.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3081559.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-833797.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e679334.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1043897.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2557029.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-246440.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1266692.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2648665.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1135532.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-770969.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e742162.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3158791.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1645658.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1281095.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e232036.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1121128.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2634261.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs shown in Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e,in the past nine years, the annual search rate of netizens showed an upward trend, and the regression linear slope of the five keywords was all greater than 0. The results of the covariance analysis showed that there was a statistical difference in the linear regression slope between different groups (F=16.876, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003eChanges in media index\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eUnlike the keywords search index, the media index showed a downward trend in nine years (Pearson\u0026rsquo;s correlation=-0.835, \u003cem\u003eP\u003c/em\u003e=0.005). The Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e showed the changes in the media index for each keyword over the nine years. Among them, the media index of hyperthyroidism was statistically different from that of thyroid nodule (\u003cem\u003eP\u003c/em\u003e=0.039), thyroiditis (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), and hypothyroidism (\u003cem\u003eP\u003c/em\u003e=0.010). The relationship between other keywords were shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBasic situation of media index from 2011 to 2019\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKeywords\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e218\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedia index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultiple comparisons between keywords (media index)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKeywords\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-471.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e352.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-60.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e763.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-845.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-22.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-295.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e528.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroid cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e822.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-786.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-235.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e587.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyroiditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1196.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-373.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-646.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e176.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperthyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e138.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e962.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study showed that public attention to TDs had increased in the past nine years, but there were differences in different diseases. The attention of thyroid nodule and hyperthyroidism was significantly higher than that of hypothyroidism, thyroid cancer and thyroiditis, and the growth rate of thyroid nodule search index was more than twice that of the second place. Although all keywords showed an upward trend, the rising trend of thyroid nodule was more obvious than the other four keywords. This might be related to the increased in the prevalence of thyroid nodule in recent years (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The incidence of thyroid nodules was insidious,and most patients were asymptomatic in the early stage, and patients were more likely to inquire relevant information on their own after detecting discomfort (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). As the largest search tool in China, Baidu\u0026rsquo;s search results can reflect people's needs well. The disease prediction product jointly developed by Baidu and the Chinese Center for Disease Control and Prevention can provide real-time data on infectious diseases (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). At the same time, it can also be used to predict the epidemic trend of diseases, as a powerful complement to the traditional detection system (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Baidu Index has not been used for TDs related research in China. Our study is the first attempt to explore the behavior and interest of Chinese netizens in TDs, confirming the potential of using online search trend data to represent the real situation of TDs patients in China.\u003c/p\u003e \u003cp\u003eFor the media index part, the results showed that the media\u0026rsquo;s attention to the hyperthyroidism was higher than other keywords. This suggested that the media had pushed and reported more information about hyperthyroidism to the public in the past nine years. Overall, the media attention of TDs was on the decline. The reason might be related to the rapid development of the internet, the scattered news points, the shortage of media practitioners and the declined in the number of media concerned about TDs.\u003c/p\u003e \u003cp\u003eDespite the huge medical expenditure imposed on China by TDs (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), due to China's vast territory and large population, it is difficult to evaluate the true prevalence rate of TDs and to understand the characteristics and needs of TDs patients. With the wide application of the internet and the increasing reliance of the public on search engines as the main way to query health information, some online digital diseases surveillance tools has been explored in recent years (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). As a query tool, search engine can provide sensitive information on the disease before the diagnosis of the disease is reported, thus improving disease control. Internet big data has a broad application prospect in the medical field, which may be a supplement and an expansion of the current clinical and epidemiological data. Today, with the rapid development of the internet services and search engines, combined with network data analysis can be regarded as an auxiliary means of traditional disease monitoring.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eLimitations\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThis study also has several limitations. First, we only focused on the attention of Baidu search engine users to TDs, without considering the public attention on other search engines or social media, which can only reflect part of the public\u0026rsquo;s attention to TDs. Second, there might be sampling biases in Baidu Index. Although the internet penetration rate in China had been greatly improved, the characteristics of internet users were obviously skewed to those with higher socioeconomic level and better educated segments. Third, Baidu Index algorithm has not been made public.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBetween 2011 and 2019, the online search rate of TDs maintained a sustained growth while the media index showed a downward trend. The Baidu Index can be used to track Chinese netizens' online behavior and interest in TDs. This may help to improve our understanding of the incidence of disease, patient education and the use of online resources. Internet search trend data is a valuable source for monitoring the search behavior of TDs-related information. It can be used as an exploratory tool to better understand the characteristics and preferences of patients and provide a scientific evidence for the control and prevention of TDs in China.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTDs:Thyroid diseases\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUSI:Universal Salt Iodization\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analyzed in this study are availiable in Baidu Index Data Platform (http://index.baidu.com/Helper/?tpl=helpandword=#pdesc)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. The manuscript writing for the original draft and data analysis were completed by Zhao-ya Fan.\u0026nbsp;Yuan-lin Mou\u0026nbsp;and Qian Hu gave the paper revision and format adjustment work. The rest of the authors gave the paper revision and grammar editing work. Ruo-yun Yin and Lei Tang gave the entire process technical and paper writing guidance support. All authors read and approved the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch1\u003eDisclosure\u003c/h1\u003e\n\u003cp\u003eThe author reports no conflicts of interest in this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFualal J, Ehrenkranz J. Access, availability, and infrastructure deficiency: The current management of thyroid disease in the developing world. \u003cem\u003eRev Endocr Metab Dis.\u003c/em\u003e 2016;17:583\u0026ndash;89. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11154-016-9376-x\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimmermann MB, Boelaert K. Iodine deficiency and thyroid disorders. \u003cem\u003eLancet. Diabetes Endocrinol.\u003c/em\u003e 2015;3:286\u0026ndash;95. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2213-8587(14)70225-6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa T, Guo J, Wang F. The epidemiology of iodine-deficiency diseases in China. \u003cem\u003eAm J Clinical Nutrition\u003c/em\u003e. 1993;57(2):264S-66S. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ajcn/57.2.264S\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Di Teng, Ba J, Chen B, Du J, He L, et al. Efficacy and safety of long-term universal salt iodization on thyroid disorders: epidemiological evidence from 31 provinces of mainland China. \u003cem\u003eThyroid\u003c/em\u003e. 2020;30:568\u0026ndash;79. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/thy.2019.0067\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShan Z, Chen L, Lian X, Liu C, Shi B, Shi L, et al. The iodine status and prevalence of thyroid disorders after introduction of mandatory universal salt iodization for 16 years in China: A cross-sectional study in 10 cities. \u003cem\u003eThyroid\u003c/em\u003e. 2016;26:1125\u0026ndash;30. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/thy.2015.0613\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang Z, Xu C, Luo Y. Association of iodized salt with goiter prevalence in Chinese populations: a continuity analysis over time. \u003cem\u003eMil Med Res\u003c/em\u003e. 2017;4:8. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40779-017-0118-5\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu F, Ding G, Lou X, Wang X, Mo Z, Zhu W, et al. Incidence of thyroid diseases in Zhejiang Province, China, after 15 years of salt iodization. \u003cem\u003eJ Trace Elem Med Bio.\u003c/em\u003e 2016;36:57\u0026ndash;64. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jtemb.2016.04.003\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChina Internet Network Information Center (CNNIC). The 47th China Statistical Report on Internet Development. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203_71361.htm\u003c/span\u003e\u003c/span\u003e. Accessed 14 February 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChina Internet Network Information Center (CNNIC). China statistical report on search engine, 2019. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cnnic.cn/hlwfzyj/hlwxzbg/ssbg/201910/t20191025_70843.htm\u003c/span\u003e\u003c/span\u003e. Accessed 14 February 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu CC, Wang Q. An initial analysis on thyroid nodules prevalence and influencing factors of Chinese healthy adults in 2008-2014. \u003cem\u003eJ Environ Health.\u003c/em\u003e 2016;33:440\u0026ndash;43. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16241/j.cnki.1001-5914.2016.05.016\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou B, Wang X, Sun L, Zhou Y, Chen ZT. Prevalence of Thyroid Nodules in Health Checkups and Its Relationship with Metabolic Diseases. \u003cem\u003eChin Gen Pract\u003c/em\u003e. 2020;23:2423\u0026ndash;28. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12114/j.issn.1007-9572.2020.00.089\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi K, Liu ML, Feng Y, Ning CY, Ou WD, Sun J, et al. Using Baidu Search Engine to Monitor AIDS Epidemics Inform for Targeted intervention of HIV/AIDS in China. \u003cem\u003eSci Rep\u003c/em\u003e. 2019;9:320. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-018-35685-w\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen SY. Big data applications and practices of Baidu. \u003cem\u003eBig Data Res\u003c/em\u003e. 2015;1:104\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie DY, Wang Q, Li C, Wang Z, Song CY. Analysis of the Influencing Factors of Hospitalization Expense of Patients with Thyroid Carcinoma in a Hospital. \u003cem\u003eChina Health Insurance.\u003c/em\u003e 2018:46\u0026ndash;50. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19546/j.issn.1674-3830.2018.1.011\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTu BZ, Wei LF, Jia YY, Qian J. Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: \u0026ndash; evidence from Baidu index. \u003cem\u003eBMC Infect Dis\u003c/em\u003e. 2021;21:98. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12879-020-05740-x\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The use of google trends in health care research: a systematic review. \u003cem\u003ePlos One.\u003c/em\u003e 2014;9:e109583. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0109583\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGluskin RT, Johansson MA, Santillana M, Brownstein JS. Evaluation of Internet-based dengue query data: Google Dengue Trends. \u003cem\u003ePloS Negl Trop Dis\u003c/em\u003e. 2014;8:e2713. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pntd.000271\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Baidu Index, media, search engines, thyroid diseases","lastPublishedDoi":"10.21203/rs.3.rs-1190514/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1190514/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCommon thyroid diseases are hyperthyroidism, hypothyroidism, thyroiditis, thyroid tumor and so on. Baidu is currently the most widely used online search tool in China, has developed an internet search trends collection and analysis tool called the Baidu Index. The aim of the present study was to understand the trend and characteristics of public’s online attention to thyroid diseases, and to explore the value of Baidu Index in monitoring online retrieval behavior of thyroid related information.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eTaking the period from January 1, 2011 to December 31, 2019 as the time range into consideration, we used the big data analysis tool of Baidu Index and took “thyroid nodules”, “thyroid cancer”, “thyroiditis” “hyperthyroidism” and “hypothyroidism” as the keywords, the data of “search index” and “media index” were recorded on a weekly basis, and all information were aggregated into quarterly and annual to generate the final data which was carried out for secondary analysis. Pearson correlation analysis was used to analyze the correlation between the search index of keywords and the year. One-way Analysis of Variance was used to analyze the differences between\u0026nbsp;search index and media index.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong the five keywords, thyroid nodule search index had the highest growth rate (640%), followed by thyroid cancer (298%). The media’s attention to thyroid diseases had been declining year by year. Unlike the public’s attention, the media index of hyperthyroidism was significantly higher than other keywords.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOver the past nine years, the public's attention to thyroid related diseases has been increasing gradually. Baidu Index is an effective tool to track the health information query behavior of Chinese internet users, which can provide a cost-effective supplement to traditional monitoring system.\u003c/p\u003e","manuscriptTitle":"Chinese Interest in Thyroid Related Diseases: Evidence from Baidu Index","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-12-29 19:25:53","doi":"10.21203/rs.3.rs-1190514/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-07-11T03:26:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-07-08T10:20:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f93165d2-b682-448a-a469-1966d4ea3cbb","date":"2022-06-28T09:32:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-06-13T06:53:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"599718d5-a677-4843-9c20-85000d698048","date":"2022-06-03T17:12:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-03-28T17:35:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-02-09T23:26:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-12-28T08:52:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-12-28T08:43:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-12-21T03:57:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fb7be271-703c-4b08-8a51-51fb20aa309c","owner":[],"postedDate":"December 29th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":9429029,"name":"Other Public Policy"},{"id":9429030,"name":"Health Policy"}],"tags":[],"updatedAt":"2022-09-27T04:44:22+00:00","versionOfRecord":[],"versionCreatedAt":"2021-12-29 19:25:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1190514","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1190514","identity":"rs-1190514","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}