title: Multi-profile hidden Markov model for mood, dietary intake, and physical activity in an intervention study of childhood obesity.
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.
authors: Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, USA. eip@wfubmc.edu
authors: E H
authors: EH
authors: Ip
authors: Q
authors: Q
authors: Zhang
authors: R
authors: R
authors: Schwartz
authors: J
authors: J
authors: Tooze
authors: X
authors: X
authors: Leng
authors: H
authors: H
authors: Han
authors: D A
authors: DA
authors: Williamson
mesh_terms: D000293:Adolescent; D000339:Affect; D004435:Eating / Q000502:physiology* / Q000523:psychology*; D004734:Energy Metabolism / Q000502:physiology; D005260:Female; D006801:Humans; D008145:Louisiana; D008390:Markov Chains; D008960:Models, Psychological; D015233:Models, Statistical; D009043:Motor Activity / Q000502:physiology*; D063766:Pediatric Obesity / Q000523:psychology / Q000628:therapy*; D012424:Rural Population; D013334:Students
keywords: childhood obesity intervention; latent Markov model; latent variable; longitudinal analysis