@article{Sarigul:166113,
      recid = {166113},
      author = {Sarigul, Sercan and Rui, Huaxia},
      title = {Nowcasting Obesity in the U.S. Using Google Search Volume  Data},
      address = {2014-06},
      number = {327-2016-12719},
      pages = {33},
      year = {2014},
      abstract = {“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.},
      url = {http://ageconsearch.umn.edu/record/166113},
      doi = {https://doi.org/10.22004/ag.econ.166113},
}