Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, USA.
Stat Med. 2013 Aug 30;32(19):3314-31. doi: 10.1002/sim.5719. Epub 2013 Jan 16.
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.
受临床实验中儿童肥胖数据应用的启发，本文描述了一种多轮廓隐马尔可夫模型（HMM），该模型使用分别与青少年在学校环境中的心理社会属性、饮食摄入和能量消耗行为相关的多个时间序列的测量值。利用这些心理和行为特征，该模型从纵向数据集描绘出健康状态。此外，还使用了一个考虑到学生在学校内聚类效应的两级回归模型，来评估基于学校和社区的干预措施以及其他风险因素对健康状态随时间转变的影响。我们的研究结果表明，尽管女性学生对体重的焦虑程度很高，但她们往往会减少体育活动。这一发现适用于干预组和对照组。
