Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Department of Health Promotion, Education, & Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Appetite. 2018 Jan 1;120:130-135. doi: 10.1016/j.appet.2017.08.025. Epub 2017 Aug 26.
To evaluate whether knowledge of a person's eating identity (EI) can explain any additional variation in fruit and vegetable intake above and beyond that explained by food environment characteristics, perceptions of the food environment, and shopping behaviors.
Cross-sectional study.
A total of 968 adults were recruited for a telephone survey by the Survey Research Laboratory in an eight-county region in South Carolina.
The survey queried information on shopping behaviors, perceptions of the food environment, demographic and address information, fruit and vegetable intake, and EI. EI was assessed using the Eating Identity Type Inventory, a 12-item instrument that differentiates four eating identity types: healthy, emotional, meat, and picky. Statistical analyses were restricted to 819 participants with complete data.
Healthy EI and picky EI were significantly and directly related to fruit and vegetable intake, with coefficients of 0.31 (p-value<0.001) for healthy EI and -0.16 (p-value<0.001) for picky EI, whereas emotional EI (β = 0.00, p-value = 0.905) and meat EI (β = -0.04, p-value = 0.258) showed no association. Shopping frequency also directly and significantly influenced fruit and vegetable intake (β = 0.13, p-value = 0.033). With the inclusion of EI, 16.3% of the variation in fruit and vegetable intake was explained.
Perceptions and GIS-based measures of environmental factors alone do not explain a substantial amount of variation in fruit and vegetable intake. EI, especially healthy EI and picky EI, is an important, independent predictor of fruit and vegetable intake and contributes significantly to explaining the variation in fruit and vegetable intake.
评估个体的饮食身份（EI）知识是否可以在超出食物环境特征、对食物环境的感知以及购物行为所解释的范围之外，进一步解释水果和蔬菜摄入量的差异。
横断面研究。
南卡罗来纳州一个八县地区的调查研究实验室通过电话调查共招募了 968 名成年人。
调查询问了购物行为、对食物环境的感知、人口统计学和地址信息、水果和蔬菜摄入量以及 EI 信息。EI 使用 Eating Identity Type Inventory 进行评估，这是一种 12 项的工具，可区分四种饮食身份类型：健康型、情绪化型、肉食型和挑食型。统计分析仅限于 819 名具有完整数据的参与者。
健康 EI 和挑食 EI 与水果和蔬菜摄入量呈显著正相关，健康 EI 的系数为 0.31（p 值<0.001），挑食 EI 的系数为-0.16（p 值<0.001），而情绪化 EI（β=0.00，p 值=0.905）和肉食 EI（β=-0.04，p 值=0.258）则没有关联。购物频率也直接显著影响水果和蔬菜摄入量（β=0.13，p 值=0.033）。纳入 EI 后，水果和蔬菜摄入量的变异有 16.3%得到了解释。
仅通过感知和基于 GIS 的环境因素来解释水果和蔬菜摄入量的差异并不充分。EI，特别是健康 EI 和挑食 EI，是水果和蔬菜摄入量的重要独立预测因素，对解释水果和蔬菜摄入量的差异有重要贡献。
