• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用百度指数研究中国大陆地区干眼症的季节性、空间分布和公众关注度。

Utilizing Baidu Index to Investigate Seasonality, Spatial Distribution and Public Attention of Dry Eye Diseases in Chinese Mainland.

机构信息

Department of Ophthalmology, Peking University Third Hospital, Beijing, China.

Department of Ophthalmology, Peking University Third Hospital Yanqing Hospital, Beijing, China.

出版信息

Front Public Health. 2022 Jul 6;10:834926. doi: 10.3389/fpubh.2022.834926. eCollection 2022.

DOI:10.3389/fpubh.2022.834926
PMID:35875014
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9298962/
Abstract

PURPOSE

To explore the characteristics of spatial-temporal prevalence and public attention of dry eye diseases (DED) through Baidu Index (BI) based on infodemiology method.

METHODS

The data about BI of DED were collected from Baidu search engine using "Dry eye diseases" as keyword. The spatial and temporal distribution of DED were analyzed through timeseries data decomposition as well as spatial autocorrelation and hotspot detection of BI about DED. The most popular related words and demographic characteristics were recorded to determine the public attention of DED.

RESULTS

The trends of BI about DED in Chinese mainland had gradually increased over time with a rapid increase from 2012 to 2014 and in 2018. The results of timeseries decomposition indicated that there was seasonality in the distribution of BI about DED with the peak in winter, especially in northern regions. The geographic distribution demonstrated the search activities of DED was highest in the east of Chinese mainland while lowest in the west. The vast majority of people searching for DED were teenagers (20-29 years), with a predominance of females. Glaucoma, keratitis and conjunctivitis were the diseases most often confused with DED, and the artificial tears were the most common treatment for DED in Chinese mainland according to the BI about DED.

CONCLUSIONS

The analysis revealed the seasonality, geographic hotspots and public concern of DED through BI in Chinese mainland, which provided new insights into the epidemiology of DED.

摘要

目的

运用基于信息流行病学的百度指数(BI)探索干眼病(DED)时空流行和公众关注度的特征。

方法

使用“干眼病”作为关键词,从百度搜索引擎中收集关于 DED 的 BI 数据。通过时间序列数据分解,以及 DED 的 BI 的空间自相关和热点检测,分析 DED 的时空分布。记录最受欢迎的相关词汇和人口统计学特征,以确定 DED 的公众关注度。

结果

中国大陆 DED 的 BI 趋势随时间逐渐增加,2012 年至 2014 年和 2018 年呈快速增长。时间序列分解的结果表明,DED 的 BI 分布具有季节性,冬季高峰明显,尤其是在北方地区。地理分布显示,DED 的搜索活动以中国大陆东部最高,西部最低。搜索 DED 的绝大多数人是青少年(20-29 岁),女性居多。根据 DED 的 BI,青光眼、角膜炎和结膜炎是最常与 DED 混淆的疾病,人工泪液是中国大陆治疗 DED 的最常见方法。

结论

本研究通过中国大陆的 BI 分析揭示了 DED 的季节性、地理热点和公众关注度,为 DED 的流行病学提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/2ffbcb465a13/fpubh-10-834926-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/2408e248527e/fpubh-10-834926-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/527175e9f487/fpubh-10-834926-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/2ffbcb465a13/fpubh-10-834926-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/2408e248527e/fpubh-10-834926-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/527175e9f487/fpubh-10-834926-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d43/9298962/2ffbcb465a13/fpubh-10-834926-g0003.jpg

相似文献

1
Utilizing Baidu Index to Investigate Seasonality, Spatial Distribution and Public Attention of Dry Eye Diseases in Chinese Mainland.利用百度指数研究中国大陆地区干眼症的季节性、空间分布和公众关注度。
Front Public Health. 2022 Jul 6;10:834926. doi: 10.3389/fpubh.2022.834926. eCollection 2022.
2
Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index.利用搜索趋势分析中国大陆与 COVID-19 相关的基于网络用户的行为特征:基于热门词汇和百度指数的信息流行病学研究。
PeerJ. 2022 Nov 9;10:e14343. doi: 10.7717/peerj.14343. eCollection 2022.
3
Variations of dry eye disease prevalence by age, sex and geographic characteristics in China: a systematic review and meta-analysis.中国不同年龄、性别和地理特征人群干眼患病率的变化:系统评价和荟萃分析。
J Glob Health. 2018 Dec;8(2):020503. doi: 10.7189/jogh.08.020503.
4
Prevalence and associated risk factors of dry eye disease in 16 northern West bank towns in Palestine: a cross-sectional study.巴勒斯坦北部 16 个西岸城镇干眼症的患病率及相关危险因素:一项横断面研究。
BMC Ophthalmol. 2020 Jan 13;20(1):26. doi: 10.1186/s12886-019-1290-z.
5
Spatiotemporal distribution of migraine in China: analyses based on baidu index.中国偏头痛的时空分布:基于百度指数的分析。
BMC Public Health. 2023 Oct 10;23(1):1958. doi: 10.1186/s12889-023-16909-9.
6
Dry eye disease in the elderly in a French population-based study (the Montrachet study: Maculopathy, Optic Nerve, nuTRition, neurovAsCular and HEarT diseases): Prevalence and associated factors.法国基于人群的研究(蒙塔谢特研究:黄斑病变、视神经、营养、神经血管和心脏疾病)中的老年干眼病:患病率及相关因素。
Ocul Surf. 2018 Jan;16(1):112-119. doi: 10.1016/j.jtos.2017.09.008. Epub 2017 Sep 20.
7
Dry Eye Disease in University-based Clinics in Canada: A Retrospective Chart Review.加拿大大学诊所的干眼疾病:回顾性图表分析。
Optom Vis Sci. 2020 Nov;97(11):944-953. doi: 10.1097/OPX.0000000000001603.
8
A Novel Epidemiological Approach to Geographically Mapping Population Dry Eye Disease in the United States Through Google Trends.一种通过谷歌趋势对美国人口干眼疾病进行地理映射的新型流行病学方法。
Cornea. 2021 Mar 1;40(3):282-291. doi: 10.1097/ICO.0000000000002579.
9
Prevalence and risk factors of dry eye disease among a hospital-based population in southeast China.中国东南部某医院人群中干眼疾病的患病率及危险因素
Eye Contact Lens. 2015 Jan;41(1):44-50. doi: 10.1097/ICL.0000000000000064.
10
Using Search Trends to Analyze Web-Based Interest in Lower Urinary Tract Symptoms-Related Inquiries, Diagnoses, and Treatments in Mainland China: Infodemiology Study of Baidu Index Data.利用搜索趋势分析中国大陆与下尿路症状相关查询、诊断和治疗的网络关注度:基于百度指数数据的信息流行病学研究。
J Med Internet Res. 2021 Jul 6;23(7):e27029. doi: 10.2196/27029.

引用本文的文献

1
Spatiotemporal analysis and forecasting of public attention to China's five major religions.公众对中国五大宗教关注度的时空分析与预测
Sci Rep. 2025 Aug 8;15(1):29116. doi: 10.1038/s41598-025-15396-9.
2
Spatiotemporal distribution of migraine in China: analyses based on baidu index.中国偏头痛的时空分布:基于百度指数的分析。
BMC Public Health. 2023 Oct 10;23(1):1958. doi: 10.1186/s12889-023-16909-9.
3
Did the COVID-19 pandemic impact urticaria information-seeking behavior in China? A retrospective longitudinal study.新冠疫情是否影响了中国荨麻疹患者的信息检索行为?一项回顾性纵向研究。

本文引用的文献

1
Dry eye syndrome risk factors: A systemic review.干眼症综合征的风险因素:一项系统评价。
Saudi J Ophthalmol. 2022 Feb 18;35(2):131-139. doi: 10.4103/1319-4534.337849. eCollection 2021 Apr-Jun.
2
Trends and Seasonality of Information Searches Carried Out through Google on Nutrition and Healthy Diet in Relation to Occupational Health: Infodemiological Study.通过谷歌进行的与职业健康相关的营养和健康饮食信息搜索的趋势和季节性:信息流行病学研究。
Nutrients. 2021 Nov 28;13(12):4300. doi: 10.3390/nu13124300.
3
Using Search Trends to Analyze Web-Based Interest in Lower Urinary Tract Symptoms-Related Inquiries, Diagnoses, and Treatments in Mainland China: Infodemiology Study of Baidu Index Data.
Front Public Health. 2023 Jan 19;11:1098066. doi: 10.3389/fpubh.2023.1098066. eCollection 2023.
利用搜索趋势分析中国大陆与下尿路症状相关查询、诊断和治疗的网络关注度:基于百度指数数据的信息流行病学研究。
J Med Internet Res. 2021 Jul 6;23(7):e27029. doi: 10.2196/27029.
4
Sex and age differences in symptoms and signs of dry eye disease in a Norwegian cohort of patients.挪威患者队列中干眼疾病症状和体征的性别和年龄差异。
Ocul Surf. 2021 Jan;19:68-73. doi: 10.1016/j.jtos.2020.11.009. Epub 2020 Nov 24.
5
Why the symptoms and objective signs of dry eye disease may not correlate.为什么干眼疾病的症状和客观体征可能不相关。
J Optom. 2021 Jan-Mar;14(1):3-10. doi: 10.1016/j.optom.2020.10.002. Epub 2020 Nov 23.
6
A Novel Epidemiological Approach to Geographically Mapping Population Dry Eye Disease in the United States Through Google Trends.一种通过谷歌趋势对美国人口干眼疾病进行地理映射的新型流行病学方法。
Cornea. 2021 Mar 1;40(3):282-291. doi: 10.1097/ICO.0000000000002579.
7
Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index.新冠疫情早期的网络公众关注度:基于百度指数的信息监测研究。
JMIR Public Health Surveill. 2020 Oct 22;6(4):e23098. doi: 10.2196/23098.
8
Spatial epidemiology: An empirical framework for syndemics research.空间流行病学:综合征研究的实证框架。
Soc Sci Med. 2022 Feb;295:113352. doi: 10.1016/j.socscimed.2020.113352. Epub 2020 Sep 10.
9
Infodemiology and Infoveillance: Scoping Review.信息流行病学与信息监测:范围综述
J Med Internet Res. 2020 Apr 28;22(4):e16206. doi: 10.2196/16206.
10
Use of Google Trends to investigate loss-of-smell-related searches during the COVID-19 outbreak.利用谷歌趋势调查 COVID-19 爆发期间与嗅觉丧失相关的搜索。
Int Forum Allergy Rhinol. 2020 Jul;10(7):839-847. doi: 10.1002/alr.22580. Epub 2020 Jun 15.