Leeds Institute for Data Analytics, Level 11 Worsley Building, Clarendon Way, University of Leeds, LeedsLS2 9JT, UK.
School of Geography, Seminary St, Woodhouse, University of Leeds, LeedsLS2 9JT, UK.
Public Health Nutr. 2023 Dec;26(12):2663-2676. doi: 10.1017/S1368980023001842. Epub 2023 Sep 6.
Scalable methods are required for population dietary monitoring. The Supermarket Transaction Records In Dietary Evaluation (STRIDE) study compares dietary estimates from supermarket transactions with an online FFQ.
Participants were recruited in four waves, accounting for seasonal dietary variation. Purchases were collected for 1 year during and 1 year prior to the study. Bland-Altman agreement and limits of agreement (LoA) were calculated for energy, sugar, fat, saturated fat, protein and sodium (absolute and relative).
This study was partnered with a large UK retailer.
Totally, 1788 participants from four UK regions were recruited from the retailer's loyalty card customer database, according to breadth and frequency of purchases. Six hundred and eighty-six participants were included for analysis.
The analysis sample were mostly female (72 %), with a mean age of 56 years (sd 13). The ratio of purchases to intakes varied depending on amounts purchased and consumed; purchases under-estimated intakes for smaller amounts on average, but over-estimated for larger amounts. For absolute measures, the LoA across households were wide, for example, for energy intake of 2000 kcal, purchases could under- or over-estimate intake by a factor of 5; values could be between 400 kcal and 10000 kcal. LoA for relative (energy-adjusted) estimates were smaller, for example, for 14 % of total energy from saturated fat, purchase estimates may be between 7 % and 27 %.
Agreement between purchases and intake was highly variable, strongest for smaller loyal households and for relative values. For some customers, relative nutrient purchases are a reasonable proxy for dietary composition indicating utility in population-level dietary research.
需要可扩展的方法来进行人群饮食监测。超市交易记录在饮食评估（STRIDE）研究中，将超市交易的饮食估计值与在线 FFQ 进行比较。
参与者分四批招募，以考虑季节性饮食变化。在研究期间和之前的一年中收集了为期一年的购买记录。为能量、糖、脂肪、饱和脂肪、蛋白质和钠（绝对值和相对值）计算了 Bland-Altman 一致性和一致性界限（LoA）。
这项研究与一家英国大型零售商合作。
根据购买的广度和频率，从零售商的忠诚度卡客户数据库中招募了来自英国四个地区的 1788 名参与者，共有 686 名参与者被纳入分析。
分析样本主要为女性（72%），平均年龄为 56 岁（标准差 13 岁）。购买量与摄入量的比例取决于购买量和消耗量；平均而言，对于较小的购买量，购买量低估了摄入量，但对于较大的购买量，购买量高估了摄入量。对于绝对值，家庭之间的 LoA 很宽，例如，对于 2000 千卡的能量摄入量，购买量可能会低估或高估摄入量的 5 倍；值可能在 400 千卡到 10000 千卡之间。相对（能量调整）估计的 LoA 较小，例如，对于饱和脂肪总能量的 14%，购买估计值可能在 7%到 27%之间。
购买量与摄入量之间的一致性差异很大，对于较小的忠实家庭和相对值来说最强。对于一些客户来说，相对营养素购买量是饮食成分的合理代表，这表明其在人群饮食研究中的实用性。
