000166113 001__ 166113
000166113 005__ 20210819131359.0
000166113 0247_ $$2doi$$a10.22004/ag.econ.166113
000166113 037__ $$a327-2016-12719
000166113 041__ $$aeng
000166113 245__ $$aNowcasting Obesity in the U.S. Using Google Search Volume Data
000166113 260__ $$c2014-06
000166113 269__ $$a2014-06
000166113 300__ $$a33
000166113 336__ $$aConference Paper/ Presentation
000166113 520__ $$a“Googling” is now ubiquitous in our society. We typically start searching on Google before we
make purchase decisions or when we have interest in certain topics. Aggregating these search
data can provide us with real-time and possibly accurate information on people's behavior. In
fact, Google keeps tracks of all the search queries and has accumulated a tremendous amount of
information about people's interest at the society level. It currently provides search volume data
of keywords for different regions and time intervals on its free and public service of Google
Trends. An interesting and hot research area is how to exploit the Google Search volume data in
innovative ways to benefit our society. This paper aims to reveal the connection between obesity
prevalence and people’s online search behavior in the United States by combining data from
Google Trends and data from Behavioral Risk Factor Surveillance System (BRFSS) which is
updated by the Centers for Disease Control and Prevention (CDC) annually. We first handselected
keywords that are associated to people's life style and used panel data model to study
association between search pattern and obesity level. We found significant correlation power of
those keywords with Body Mass Index (BMI) level and results suggest great promise of the idea
of obesity monitoring through real-time Google Trends data. We believe this is an important
finding and is particularly attractive for government health institutions and private businesses
such as insurance companies etc.
000166113 546__ $$aEnglish
000166113 650__ $$aFood Consumption/Nutrition/Food Safety
000166113 650__ $$aHealth Economics and Policy
000166113 700__ $$aSarigul, Sercan
000166113 700__ $$aRui, Huaxia
000166113 8564_ $$955a3469e-0a65-47db-8571-47eddc11450a$$s1089926$$uhttps://ageconsearch.umn.edu/record/166113/files/AAEA_Sercan_Sarigul.pdf
000166113 887__ $$ahttp://purl.umn.edu/166113
000166113 909CO $$ooai:ageconsearch.umn.edu:166113$$pGLOBAL_SET
000166113 912__ $$nSubmitted by Mallory Pagel (pagel107@umn.edu) on 2014-04-17T17:22:48Z
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  Previous issue date: 2014-04-03
000166113 913__ $$aLicense granted by Mallory Pagel (pagel107@umn.edu) on 2014-04-17T17:14:13Z (GMT):

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000166113 980__ $$a327
000166113 982__ $$gAgricultural and Applied Economics Association>2014 AAEA/EAAE/CAES Joint Symposium: Social Networks, Social Media and the Economics of Food, May 29-30, 2014, Montreal, Canada