Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments.
Julia Mariel Wirtz BakerSonia Alejandra PouCamila NiclisEugenia HaluszkaLaura Rosana AballayPublished in: International journal of obesity (2005) (2023)
The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.
Keyphrases
- artificial intelligence
- big data
- insulin resistance
- metabolic syndrome
- weight loss
- machine learning
- electronic health record
- type diabetes
- healthcare
- deep learning
- high fat diet induced
- mental health
- drinking water
- weight gain
- health information
- adipose tissue
- data analysis
- body mass index
- social media
- network analysis