Ibacache Francisca, Northstone Kate, Zou Mengxuan, Johnson Laura
Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, United Kingdom.
Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, United Kingdom.
Am J Clin Nutr. 2025 Mar;121(3):685-694. doi: 10.1016/j.ajcnut.2025.01.012. Epub 2025 Jan 11.
The precision of recorded eating times directly affects the estimation of eating architecture, that is, size, timing, and frequency of eating. The impact of imprecise timing on estimates and associations of eating architecture with health remains unclear.
We compared eating architecture variables derived from precise with those of broad timing methods and examined associations with anthropometric-related and diet-related outcomes.
Cross-sectional data came from 3-d diet diaries of 7-y-old children in the Avon Longitudinal Study of Parents and Children. We derived mean size, timing, and frequency of eating, using exact times (precise, n = 4855) and midpoint meal slot times (broad, n = 7285). Intraclass correlation coefficients (ICCs) estimated agreement between methods. Bland-Altman analysis determined mean difference and limits of agreement (LOAs). Correlations (95% CIs) estimated associations between eating architecture variables and anthropometric-related or diet-related traits.
Agreement varied from moderate to excellent for size (ICC: 0.75), last or first time (ICC: 0.80 or 0.58), and frequency (ICC: 0.43) of eating occasions. Broad times underestimated eating frequency (2.2 times/d; LOA: -1, 5) and overestimated size (83 g; LOA: -179, 13), last time (50 min; LOA: -142, 42), intermeal intervals (68 min; LOA: -126, -11), and eating window (49 min; LOA: -161, 63). Directions of eating architecture intercorrelations were consistent regardless of time precision but varied in magnitude, for example, larger eating occasion size correlated with lower eating frequency but was stronger with precise time (r = -0.54; 95% CI: -0.56, -0.52; r = -0.24; 95% CI: -0.27, -0.22). Correlations with anthropometric-related and diet-related outcomes were also directionally consistent.
Precise timing improves the estimation of eating architecture. Differences in estimation will affect descriptions of children's eating habits and possibly dietary guidance. However, consistent directional associations across timing methods suggest that broad times could provide a pragmatic method for investigating eating architecture associations in large samples.
记录进食时间的精确性直接影响对进食结构的估计，即进食的量、时间和频率。进食时间不精确对进食结构估计以及与健康关系的影响尚不清楚。
我们比较了精确计时法与宽泛计时法得出的进食结构变量，并研究了其与人体测量相关及饮食相关结果的关联。
横断面数据来自阿冯父母与儿童纵向研究中7岁儿童的3天饮食日记。我们采用精确时间（精确计时法，n = 4855）和餐次中点时间（宽泛计时法，n = 7285）得出进食的平均量、时间和频率。组内相关系数（ICC）估计两种方法之间的一致性。Bland-Altman分析确定平均差异和一致性界限（LOA）。相关性分析（95%置信区间）估计进食结构变量与人体测量相关或饮食相关特征之间的关联。
进食次数的量（ICC：0.75）、最后或首次进食时间（ICC：0.80或0.58）以及频率（ICC：0.43）的一致性从中度到优不等。宽泛计时法低估了进食频率（2.2次/天；LOA：-1，5），高估了进食量（83克；LOA：-179，13）、最后进食时间（50分钟；LOA：-142，42）、餐间间隔（68分钟；LOA：-126，-11）和进食窗口（49分钟；LOA：-161，63）。无论时间精确性如何，进食结构相互关联的方向是一致的，但程度有所不同，例如，进食量越大与进食频率越低相关，但精确计时法下这种相关性更强（r = -0.54；95%置信区间：-0.56，-0.52；r = -（此处原文有误，应为0.24）；95%置信区间：-0.27，-0.22）。与人体测量相关和饮食相关结果的相关性在方向上也一致。
精确计时可改善对进食结构的估计。估计差异会影响对儿童饮食习惯的描述，可能还会影响饮食指导。然而，不同计时方法之间一致的方向关联表明，宽泛计时法可为在大样本中研究进食结构关联提供一种实用方法。
