[中国营养丰富食品指数的制定与验证]。

Run Zhang, Yifei Ouyang, Jiguo Zhang, Yanli Wei, Chang Su, Xiaofang Jia, Li Li, Jing Bai, Huijun Wang
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引用次数: 0

摘要

目的:通过基于人群的膳食质量验证,选择适用于中国居民食物特征的营养丰富食品(NRF)指标。方法:根据《中国食品成分表》和《中国食品标签营养素参考值》构建16个NRF指标,以100 g为基准进行计算。NRF指数采用中国健康与营养调查2018年收集的15个省份14068名成年居民的食物摄入数据,通过膳食质量评估指标中国优质饮食质量评分(CPDQS)对NRF指数进行验证。以CPDQS为因变量,以饲粮NRF指数评分为自变量。调整协变量后建立多元线性回归模型,以决定系数R~2最大的NRF指数作为最合适的指标。结果:回归分析显示NRF8.2指数的R~2最大,为0.16。干豆类、真菌和藻类、坚果、蔬菜、鸡蛋和水产品在NRF8.2指数中得分较高。与NRF8.2膳食指数得分较低的亚组相比,得分较高的亚组在谷物和土豆、蔬菜、水果、大豆和坚果、乳制品、鸡蛋和水产品等方面的日均摄入量较高,在畜禽肉、饮料、盐和食用油等方面的消费量较低。在营养摄入方面,NRF8.2中高亚组能量、蛋白质、维生素和矿物质的摄入量较高,脂肪和钠的摄入量较低。结论:NRF8.2指数解释了CPDQS的最大变异,是比较适合中国人群的NRF指数。
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[Development and validation of the nutrient-rich food index for China].

Objective: To select the nutrient-rich food(NRF) index applicable to the food characteristics of Chinese residents through population-based dietary quality validation.

Methods: Sixteen NRF indices were constructed based on the Chinese Food Composition Table and the Chinese Food Labelling Nutrient Reference Values, using 100 g as the base amount of food for calculation. The NRF indices were validated by the China Prime Diet Quality Score(CPDQS), a dietary quality assessment index, using food intake data collected from 14 068 adult residents in 15 provinces in 2018 under the China Health and Nutrition Survey. The CPDQS was used as the dependent variable and the dietary NRF index score was used as the independent variable. The multiple linear regression models were performed after adjusting the covariates and the NRF index with the largest coefficient of determination R~2 was used as the most appropriate index.

Results: Regression analysis showed that the R~2 of NRF8.2 index was the largest, which was 0.16. Dried legumes, fungi and algae, nuts, vegetables, eggs and aquatic products scored higher on the NRF8.2 index. The high scoring subgroups had higher average daily intakes of cereals and potatoes, vegetables, fruits, soybeans and nuts, dairy, eggs and aquatic products, as well as lower consumption of livestock and poultry meat, beverages, salt and cooking oil, compared to the low scoring subgroup on the Dietary NRF8.2 Index. In terms of nutrient intake, the medium and high NRF8.2 subgroups had relatively high intakes of energy, protein, vitamins and minerals and relatively low intakes of fat and sodium.

Conclusion: The NRF8.2 index explains the maximum variation in CPDQS and is a relatively suitable NRF index for the Chinese population.

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