Nutrition and Behaviour Unit, School of Psychological Science, University of Bristol, Bristol, United Kingdom.
National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA.
Am J Clin Nutr. 2022 Aug 4;116(2):581-588. doi: 10.1093/ajcn/nqac112.
A possible driver of obesity is insensitivity (passive overconsumption) to food energy density (ED, kcal/g); however, it is unclear whether this insensitivity applies to all meals.
We assessed the influence of ED on energy intake (kcal) across a broad and continuous range of EDs comprised of noncovertly manipulated, real-world meals. We also allowed for the possibility that the association between energy intake and ED is nonlinear.
We completed a secondary analysis of 1519 meals which occurred in a controlled environment as part of a study conducted by Hall and colleagues to assess the effects of food ultra-processing on energy intake. To establish the generalizability of the findings, the analyses were repeated in 32,162 meals collected from free-living humans using data from the UK National Diet and Nutrition Survey (NDNS). Segmented regressions were performed to establish ED "breakpoints" at which the association between consumed meal ED and mean centered meal caloric intake (kcal) changed.
Significant breakpoints were found in both the Hall et al. data set (1.41 kcal/g) and the NDNS data set (1.75 and 2.94 kcal/g). Centered meal caloric intake did not increase linearly with consumed meal ED, and this pattern was captured by a 2-component ("volume" and "calorie content" [biologically derived from the sensing of fat, carbohydrate, and protein]) model of physical meal size (g), in which volume is the dominant signal with lower energy-dense foods and calorie content is the dominant signal with higher energy-dense foods.
These analyses reveal that, on some level, humans are sensitive to the energy content of meals and adjust meal size to minimize the acute aversive effects of overconsumption. Future research should consider the relative importance of volume and calorie-content signals, and how individual differences impact everyday dietary behavior and energy balance.
对食物能量密度（ED，每克卡路里）不敏感（被动过度摄入）可能是肥胖的一个驱动因素；然而，这种不敏感是否适用于所有餐食尚不清楚。
我们评估了 ED 对广泛且连续的 ED 范围内能量摄入（千卡）的影响，这些 ED 由非隐蔽性操纵的真实世界餐食组成。我们还考虑了能量摄入与 ED 之间的关联是非线性的可能性。
我们对 Hall 及其同事进行的一项研究中作为评估食物超加工对能量摄入影响的一部分而在受控环境中发生的 1519 餐进行了二次分析。为了确定研究结果的普遍性，我们使用来自英国国家饮食和营养调查（NDNS）的数据对 32162 餐进行了重复分析，这些餐食是在自由生活的人群中收集的。使用分段回归确定了消耗的餐食 ED 和平均中心化餐食卡路里摄入量（千卡）之间的关联发生变化的 ED“断点”。
在 Hall 等人的数据集中（1.41 千卡/克）和 NDNS 数据集中（1.75 和 2.94 千卡/克）都发现了显著的断点。中心化餐食卡路里摄入量与消耗的餐食 ED 并非呈线性增加，这种模式由物理餐食大小的 2 分量（“体积”和“卡路里含量”[由脂肪、碳水化合物和蛋白质的感知产生的生物学衍生]）模型捕获，其中体积是低能量密度食物的主要信号，而卡路里含量是高能量密度食物的主要信号。
这些分析表明，在某种程度上，人类对餐食的能量含量敏感，并调整餐食大小以最小化过度摄入的急性不适影响。未来的研究应考虑体积和卡路里含量信号的相对重要性，以及个体差异如何影响日常饮食行为和能量平衡。
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