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Stat Med. 2013 Aug 30;32(19):3314-31. doi: 10.1002/sim.5719. Epub 2013 Jan 16.

Multi-profile hidden Markov model for mood, dietary intake, and physical activity in an intervention study of childhood obesity.

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  • 1Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, USA.


Motivated by an application to childhood obesity data in a clinical trial, this paper describes a multi-profile hidden Markov model (HMM) that uses several temporal chains of measures respectively related to psychosocial attributes, dietary intake, and energy expenditure behaviors of adolescents in a school setting. Using these psychological and behavioral profiles, the model delineates health states from the longitudinal data set. Furthermore, a two-level regression model that takes into account the clustering effects of students within school is used to assess the effects of school-based and community-based interventions and other risk factors on the transition between health states over time. The results from our study suggest that female students tend to decrease their physical activities despite a high level of anxiety about weight. The finding is consistent across intervention and control arms.

Copyright © 2013 John Wiley & Sons, Ltd.


childhood obesity intervention; latent Markov model; latent variable; longitudinal analysis

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