| Literature DB >> 23322318 |
E H Ip1, Q Zhang, R Schwartz, J Tooze, X Leng, H Han, D A Williamson.
Abstract
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.Entities:
Keywords: childhood obesity intervention; latent Markov model; latent variable; longitudinal analysis
Mesh:
Year: 2013 PMID: 23322318 PMCID: PMC3710544 DOI: 10.1002/sim.5719
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373