Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore 169857, Singapore.
Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore.
Nutrients. 2020 Jul 20;12(7):2158. doi: 10.3390/nu12072158.
The rising prevalence of non-communicable diseases has brought attention to the importance of consuming a healthy diet. One strategy to improve diet quality is through front-of-pack (FOP) nutrition labels. Taking advantage of an online grocery store, we allowed consumers to choose the FOP labels they preferred, and combined this information with real-time feedback on the overall nutritional quality of the shopping basket. We hypothesized that these dynamic food labels with real-time feedback (DFLF) would improve nutritional quality of food purchases. This trial followed a two-arm (no-label control and DFLF) crossover design with 125 participants exposed to each condition once in random order via an online grocery store. A first difference regression model allowed for estimating the unbiased effect of the DFLF on diet quality, measured by the weighted average Nutri-Score (ranging 1 to 5) per serving (primary) and changes in select nutrients and calories. The mean weighted Nutri-Score was 0.4 (12.6%) higher in the DFLF arm (CI: [0.2, 0.6]) relative to the control. The DFLF also decreased the amount of sugar per serving by 0.9 g (CI: [-1.7, -0.0]) and total sugar per shop by 169.5 g (CI: [-284.5, -54.5]). The DFLF features significantly improved nutrition quality relative to no labelling, as measured by average Nutri-Score values. These results shed light on the considerable potential of the online shopping environment to improve diet quality through customization and real time feedback.
非传染性疾病的患病率不断上升，使人们开始关注健康饮食的重要性。改善饮食质量的一种策略是使用前置（FOP）营养标签。我们利用一家在线杂货店，让消费者选择他们喜欢的 FOP 标签，并将这些信息与购物篮整体营养质量的实时反馈相结合。我们假设这些具有实时反馈的动态食品标签（DFLF）将改善食品购买的营养质量。这项试验采用了两臂（无标签对照和 DFLF）交叉设计，125 名参与者通过在线杂货店随机顺序各暴露于一种条件一次。首次差异回归模型允许估计 DFLF 对饮食质量的无偏影响，通过每份食物的加权平均 Nutri-Score（范围为 1 到 5）来衡量（主要）以及选择营养素和卡路里的变化。DFLF 组每份食物的加权 Nutri-Score 平均高出 0.4（12.6%）（CI：[0.2，0.6]）。DFLF 还使每份糖的含量减少了 0.9 克（CI：[-1.7，-0.0]），每笔购物的总糖含量减少了 169.5 克（CI：[-284.5，-54.5]）。与无标签相比，DFLF 的特征在于平均 Nutri-Score 值显示出营养质量的显著改善。这些结果表明，在线购物环境具有通过定制和实时反馈来改善饮食质量的巨大潜力。
