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Evidence from big data in obesity research: international case studies
[journal article]
Abstract Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of 'big data' presents... view more
Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of 'big data' presents a potential solution to this challenge. Big data is defined by Delphi consensus as: always digital, has a large sample size, and a large volume or variety or velocity of variables that require additional computing power (Vogel et al. Int J Obes. 2019). 'Additional computing power' introduces the concept of big data analytics. The aim of this paper is to showcase international research case studies presented during a seminar series held by the Economic and Social Research Council (ESRC) Strategic Network for Obesity in the UK. These are intended to provide an in-depth view of how big data can be used in obesity research, and the specific benefits, limitations and challenges encountered.... view less
Keywords
adipositas; demographic factors; cause; data quality; data capture; health behavior; social factors; physical exercise
Classification
Medicine, Social Medicine
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Big Data
Document language
English
Publication Year
2020
Page/Pages
p. 1028-1040
Journal
International Journal of Obesity, 44 (2020)
DOI
https://doi.org/10.1038/s41366-020-0532-8
ISSN
1476-5497
Status
Postprint; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications