Correlates of physical activity behavior in adults: a data mining approach.

Vahid FarrahiMaisa NiemeläMikko KärmeniemiSoile PuhakkaMaarit KangasRaija KorpelainenTimo Jämsä

Published in: The international journal of behavioral nutrition and physical activity (2020)

Using data mining, we established a data-driven model composed of 36 different factors of relative importance from empirical data. This model may be used to identify subgroups for multilevel intervention allocation and design. Additionally, this study methodologically discovered an extensive set of factors that can be a basis for additional hypothesis testing in PA correlates research.

Keyphrases

electronic health record
physical activity
big data
randomized controlled trial
body mass index
machine learning
data analysis
deep learning
sleep quality