Cancer Prevention Research Center, University of Rhode Island, USA.
Eat Behav. 2013 Aug;14(3):255-62. doi: 10.1016/j.eatbeh.2013.01.014. Epub 2013 Mar 1.
Longitudinal predictors of dietary behavior change are important and in need of study. This secondary data analysis combined primary data across three randomized trials to examine transtheoretical model (TTM) and specific dietary predictors of successful dietary change at 12 and 24 months separately in treatment and control groups (N = 4178). The treatment group received three TTM-tailored print interventions over 12 months between 1995 and 2000. Chi-square and MANOVA analyses were used to examine baseline predictors of dietary outcome at 12 and 24 months. Last, a multivariable logistic regression was conducted with all baseline variables included. Across all analyses in both treatment and control groups, the most robust predictors of successful change were for TTM-tailored treatment group, preparation stage of change, and increased use of dietary behavior variables such as moderating fat intake, substitution of lower fat foods, and increasing intake of healthful foods. These results provide strong evidence for treatment, stage and behavioral dietary severity effects predicting dietary behavior change over time, and for targeting these variables with the strongest relationships to outcome in interventions, such as TTM-tailored dietary interventions.
纵向预测饮食行为改变很重要,需要进行研究。本二次数据分析结合了三项随机试验的原始数据,分别在治疗组和对照组中(N=4178),在 12 个月和 24 个月时检查跨理论模型(TTM)和特定饮食预测因子对成功饮食改变的影响。治疗组在 1995 年至 2000 年期间接受了三次 TTM 定制的印刷干预,共 12 个月。采用卡方检验和 MANOVA 分析来检验 12 个月和 24 个月时饮食结果的基线预测因子。最后,使用所有基线变量进行多变量逻辑回归分析。在治疗组和对照组的所有分析中,成功改变的最有力预测因子是 TTM 定制治疗组、改变的准备阶段,以及增加使用饮食行为变量,如调节脂肪摄入、用低脂肪食物替代和增加健康食品的摄入。这些结果为治疗、阶段和行为饮食严重程度预测饮食行为随时间的变化提供了强有力的证据,并为以与结果最相关的变量为目标提供了依据,如 TTM 定制的饮食干预。