Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, L8L 2X2, Canada; Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, L8S 4L8, Canada.
Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, L8L 2X2, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, L8S 4L8, Canada.
Nutr Res. 2023 Nov;119:109-118. doi: 10.1016/j.nutres.2023.09.001. Epub 2023 Sep 7.
Reliable information on dietary trends is essential. We compared individual-level dietary estimates for total energy, carbohydrate, fat, and protein intake over time with national supply data from the Global Expanded Nutrient Supply Model (186 paired estimates from 1961 to 2011, 18 countries). We hypothesized that supply data would overestimate individual measures and that the two measures would be weakly correlated. Individual- and supply-level estimates were compared using Spearman correlation coefficients and linear mixed-effect models were used to estimate the differences between measures. Overall, the correlations between individual- and supply-level measures were moderate for energy (r = 0.34) and carbohydrate (r = 0.39), strong for fat (r = 0.85), and protein (r = 0.69). Trends in total energy measured by individual-level surveys and total energy supply were positively correlated in 38.9% of countries, whereas trends in macronutrients aligned between estimates in most countries. Supply-level dietary data overestimated individual-level intakes, especially in higher income countries in Europe and in the United States. In the United States, supply-level data exceeded individual-level estimates by 26.3% to 29.9% for energy, carbohydrate, and fat, whereas protein estimates were similar between measures. In Europe, supply-level estimates overestimated individual-level intake by 19.9% for energy, 17.0% for carbohydrate, 13.7% for fat, and 7.7% for protein, whereas estimates for energy and macronutrients were similar in Asia. In Asia and lower income countries, our findings generally support the use of supply-level data in the absence of individual-level data, though this finding may be related to smaller sample size and differences in underlying national statistics that inform supply data.
有关饮食趋势的可靠信息至关重要。我们将个体层面的总能量、碳水化合物、脂肪和蛋白质摄入的饮食估计值与来自全球扩展营养供应模型的国家供应数据(186 对来自 1961 年至 2011 年的估计值,18 个国家)进行了比较。我们假设供应数据会高估个体测量值,并且这两种测量值相关性较弱。使用 Spearman 相关系数比较个体和供应水平的估计值,并使用线性混合效应模型来估计两种测量值之间的差异。总体而言,个体水平和供应水平的测量值之间的相关性在能量(r=0.34)和碳水化合物(r=0.39)方面为中度,在脂肪(r=0.85)和蛋白质(r=0.69)方面为强。个体水平调查测量的总能量趋势与总能量供应趋势在 38.9%的国家中呈正相关,而大多数国家的估计值中宏量营养素趋势是一致的。供应层面的饮食数据高估了个体层面的摄入量,尤其是在欧洲和美国等收入较高的国家。在美国,能量、碳水化合物和脂肪的供应层面数据比个体层面估计值高出 26.3%至 29.9%,而蛋白质估计值在两种测量值之间相似。在欧洲,能量供应估计值高估了个体层面的摄入量 19.9%,碳水化合物为 17.0%,脂肪为 13.7%,蛋白质为 7.7%,而能量和宏量营养素的估计值在亚洲相似。在亚洲和低收入国家,我们的研究结果普遍支持在缺乏个体层面数据的情况下使用供应层面的数据,尽管这一发现可能与样本量较小以及影响供应数据的国家统计数据的差异有关。