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谷歌趋势在监测心血管疾病方面的效用不断增加。

Increasing utility of Google Trends in monitoring cardiovascular disease.

作者信息

Senecal Conor, Mahowald Madeline, Lerman Lilach, Lopes-Jimenez Francisco, Lerman Amir

机构信息

Department of Cardiovascular Diseases, Mayo Clinic and College of Medicine, USA.

Department of Internal Medicine, Division of Nephrology Mayo Clinic and College of Medicine, USA.

出版信息

Digit Health. 2021 Sep 28;7:20552076211033420. doi: 10.1177/20552076211033420. eCollection 2021 Jan-Dec.

DOI:10.1177/20552076211033420
PMID:34873449
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8642777/
Abstract

INTRODUCTION

Cardiovascular disease is the most common cause of morbidity and mortality in the United States. Patients are increasingly using internet search to find health-related information, including searches for cardiovascular diseases and risk factors. We sought to evaluate the change in the state by state correlation of cardiovascular disease and risk factors with Google Trends search volumes.

METHODS

Data on cardiovascular disease hospitalizations and risk factor prevalence were obtained from the publically available Centers for Disease Control and Prevention website from 2006 to 2018. Google Trends data were obtained for matching conditions and time periods. Simple linear regression was performed to evaluate for an increase in correlation over time.

RESULTS

Hospitalizations for six separate cardiovascular disease conditions showed moderate to strong correlation with online search data in the last period studied (heart failure (0.58,  < .001), atrial fibrillation (0.57,  < .001), coronary heart disease (0.58,  < .001), myocardial infarction (0.70,  < .001), stroke (0.62,  < .001), cardiac dysrhythmia (0.46,  < .001)) in the United States. All diseases studied showed a positive increase in correlation throughout the time period studied ( < .05). All five of the cardiovascular risk factors studied showed strong correlation with online search data; diabetes ( = 0.78,  < .001), cigarette use ( = 0.79,  < .001), hypertension ( = 0.81,  < .001), high cholesterol ( = 0.59,  < .001), and obesity ( = 0.80,  < .001) in the United States. Three of the five risk factors showed an increasing correlation over time.

CONCLUSION

The prevalence of and hospitalizations for cardiovascular conditions in the United States strongly correlate with online search volumes in the United States when analyzed by state. This relationship has progressively strengthened or been strong and stable over recent years for these conditions. Google Trends represents an increasingly valuable tool for evaluating the burden of cardiovascular disease and risk factors in the United States.

摘要

引言

心血管疾病是美国发病和死亡的最常见原因。患者越来越多地通过互联网搜索来查找与健康相关的信息,包括搜索心血管疾病及其危险因素。我们试图评估心血管疾病及危险因素与谷歌趋势搜索量的州与州之间相关性的变化。

方法

2006年至2018年心血管疾病住院治疗及危险因素患病率的数据来自可公开获取的疾病控制与预防中心网站。获取了相匹配疾病和时间段的谷歌趋势数据。进行简单线性回归以评估随时间相关性的增加情况。

结果

在所研究的最后阶段,六种不同心血管疾病的住院治疗情况与在线搜索数据显示出中度至高度相关性(美国心力衰竭(0.58,<0.001)、心房颤动(0.57,<0.001)、冠心病(0.58,<0.001)、心肌梗死(0.70,<0.001)、中风(0.62,<0.001)、心律失常(0.46,<0.001))。在所研究的整个时间段内,所有研究的疾病相关性均呈正向增加(<0.05)。所研究的五个心血管危险因素均与在线搜索数据显示出高度相关性;美国的糖尿病(=0.78,<0.001)、吸烟(=0.79,<0.001)、高血压(=0.81,<0.001)、高胆固醇(=0.59,<0.001)和肥胖(=0.80,<0.001)。五个危险因素中的三个随时间相关性增加。

结论

按州分析时,美国心血管疾病的患病率及住院治疗情况与美国在线搜索量密切相关。近年来,这些疾病的这种关系逐渐增强或一直很强且稳定。谷歌趋势是评估美国心血管疾病负担及危险因素的一种越来越有价值的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/0d50c7d89c3e/10.1177_20552076211033420-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/54d0b2005491/10.1177_20552076211033420-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/567e18de5051/10.1177_20552076211033420-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/345a24206061/10.1177_20552076211033420-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/0d50c7d89c3e/10.1177_20552076211033420-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/54d0b2005491/10.1177_20552076211033420-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/567e18de5051/10.1177_20552076211033420-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/345a24206061/10.1177_20552076211033420-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ce3/8642777/0d50c7d89c3e/10.1177_20552076211033420-fig4.jpg

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