National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Educational Technology Doctoral Program, Department of Educational Studies, College of Education and Human Ecology, The Ohio State University, Columbus, OH 43210, USA.
Nutrients. 2019 Jan 8;11(1):109. doi: 10.3390/nu11010109.
The nutrient intake dataset is crucial in epidemiological studies. The latest version of the food composition database includes more types of nutrients than previous ones and can be used to obtain data on nutrient intake that could not be estimated before. Usual food consumption data were collected among 910 twins between 1969 and 1973 through dietary history interviews, and then used to calculate intake of eight types of nutrients (energy intake, carbohydrate, protein, cholesterol, total fat, and saturated, monounsaturated, and polyunsaturated fatty acids) in the National Heart, Lung, and Blood Institute Twin Study. We recalculated intakes using the food composition database updated in 2008. Several different statistical methods were used to evaluate the validity and the reliability of the recalculated intake data. Intra-class correlation coefficients between recalculated and original intake values were above 0.99 for all nutrients. ² values for regression models were above 0.90 for all nutrients except polyunsaturated fatty acids (² = 0.63). In Bland⁻Altman plots, the percentage of scattering points that outlay the mean plus or minus two standard deviations lines was less than 5% for all nutrients. The arithmetic mean percentage of quintile agreement was 78.5% and that of the extreme quintile disagreement was 0.1% for all nutrients between the two datasets. Recalculated nutrient intake data is in strong agreement with the original one, supporting the reliability of the recalculated data. It is also implied that recalculation is a cost-efficient approach to obtain the intake of nutrients unavailable at baseline.
营养素摄入量数据在流行病学研究中至关重要。最新版本的食物成分数据库包含了比以前更多类型的营养素，可用于获取以前无法估计的营养素摄入量数据。在 1969 年至 1973 年间，通过饮食史访谈收集了 910 对双胞胎的常规食物消费数据，并用于计算国立心肺血液研究所双胞胎研究中 8 种营养素（能量摄入、碳水化合物、蛋白质、胆固醇、总脂肪以及饱和、单不饱和和多不饱和脂肪酸）的摄入量。我们使用 2008 年更新的食物成分数据库重新计算了摄入量。使用了几种不同的统计方法来评估重新计算的摄入量数据的有效性和可靠性。所有营养素的重新计算摄入量与原始摄入量之间的组内相关系数均高于 0.99。除多不饱和脂肪酸（²=0.63）外，所有营养素的回归模型²值均高于 0.90。在 Bland-Altman 图中，所有营养素的散点超过均值加减两个标准差线的百分比均小于 5%。在两个数据集之间，所有营养素的五分位数一致性的算术平均值百分比为 78.5%，极端五分位数不一致性的百分比为 0.1%。重新计算的营养素摄入量数据与原始数据高度一致，支持重新计算数据的可靠性。这也意味着重新计算是一种获取基线时不可用的营养素摄入量的经济有效的方法。
