Department of Nutrition, University of California, Davis, Davis, CA 95616 United States; Center for Nutrition in Schools, University of California, Davis, Davis, CA 95616 United States.
Department of Human Ecology, University of California, Davis, Davis, CA 95616 United States.
Appetite. 2018 Jan 1;120:196-204. doi: 10.1016/j.appet.2017.08.037. Epub 2017 Sep 9.
Although increasing attention is placed on the quality of foods in children's packed lunches, few studies have examined the capacity of observational methods to reliably determine both what is selected and consumed from these lunches. The objective of this project was to assess the feasibility and inter-rater reliability of digital imaging for determining selection and consumption from students' packed lunches, by adapting approaches previously applied to school lunches. Study 1 assessed feasibility and reliability of data collection among a sample of packed lunches (n = 155), while Study 2 further examined reliability in a larger sample of packed (n = 386) as well as school (n = 583) lunches. Based on the results from Study 1, it was feasible to collect and code most items in packed lunch images; missing data were most commonly attributed to packaging that limited visibility of contents. Across both studies, there was satisfactory reliability for determining food types selected, quantities selected, and quantities consumed in the eight food categories examined (weighted kappa coefficients 0.68-0.97 for packed lunches, 0.74-0.97 for school lunches), with lowest reliability for estimating condiments and meats/meat alternatives in packed lunches. In extending methods predominately applied to school lunches, these findings demonstrate the capacity of digital imaging for the objective estimation of selection and consumption from both school and packed lunches.
虽然越来越多的人关注儿童携带的午餐食品质量,但很少有研究检验观察法在可靠确定这些午餐中选择和食用的食物方面的能力。本项目的目的是评估数字成像技术用于确定学生携带的午餐中选择和食用食物的可行性和评分者间可靠性,方法是改编先前用于学校午餐的方法。研究 1 在 155 份携带的午餐样本中评估了数据收集的可行性和可靠性,而研究 2 则进一步在更大的携带(n=386)和学校(n=583)午餐样本中检验了可靠性。根据研究 1 的结果,收集和对携带午餐图像中的大多数项目进行编码是可行的;数据缺失最常见的原因是包装限制了对内容的可见性。在这两项研究中,在所研究的 8 个食物类别中,确定选择的食物类型、选择的数量和食用的数量都具有令人满意的可靠性(携带午餐的加权 Kappa 系数为 0.68-0.97,学校午餐为 0.74-0.97),对包装食品和肉类/肉类替代品的估计可靠性最低。通过扩展主要应用于学校午餐的方法,这些发现表明数字成像技术具有从学校和携带午餐中客观估计选择和食用食物的能力。