Zhai Junya, Ma Baihui, Lyu Quanjun, Guo Lijun, Khatun Pipasha, Liang Rui, Cong Minghua, Kong Yongxia
Department of Clinical Nutrition, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou450008, People's Republic of China.
Department of Nutrition, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People's Republic of China.
Public Health Nutr. 2022 Mar 25;25(6):1-9. doi: 10.1017/S1368980022000465.
A family of nutrient-rich food (NRF) indices was validated against the mean adequacy ratio (MAR) and their associations with obesity were tested.
Cross-sectional study. NRF indices include nutrients to encourage ranging from 6-11 (protein; fibre; vitamin A, vitamin C, vitamin E and vitamin B12; Ca; Fe; K; Mg; Zn) and two nutrients to limit (saturated fat and Na), described as NRFn.2 (where n 6-11), based on reference amount of 100 g or 100 kcal using the NRF index family of algorithms. The percentage of variation in MAR (R2) was the criteria of index performance. Logistic regression models were applied to predict the association between NRF index and obesity.
Three communities in Zhengzhou city, Henan province, China.
A total of 656 adults were recruited from Henan as the subjects.
The NRF9·2 index, based on nine beneficial nutrients and two nutrients to limit, using the algorithm based on sums and 100 kcal, had the higher R2 values (R2 = 0·232). The OR for overweight (defined by BMI) in the 4th quartile (Q4) v. the 1st quartile (Q1) of the NRF9·2 index was 0·61 (95 % CI = 0·37, 0·98) after multiple adjustments.
NRF9·2 index using the algorithm based on sums and 100 kcal gave the best predicted model for diet quality. NRF9·2 index score was associated with overweight defined by BMI, but it was not associated with central obesity. The NRF9·2 index is a valid tool to assess the overall diet quality among adults in Henan province of China.
对一系列富含营养食物(NRF)指数与平均充足率(MAR)进行验证,并测试它们与肥胖的关联。
横断面研究。NRF指数包括6 - 11种鼓励摄入的营养素(蛋白质、纤维、维生素A、维生素C、维生素E、维生素B12、钙、铁、钾、镁、锌)和2种限制摄入的营养素(饱和脂肪和钠),基于100克或100千卡的参考量,使用NRF指数算法家族描述为NRFn.2(其中n = 6 - 11)。MAR的变异百分比(R2)是指数性能的标准。应用逻辑回归模型预测NRF指数与肥胖之间的关联。
中国河南省郑州市的三个社区。
共招募了656名来自河南的成年人作为研究对象。
基于9种有益营养素和2种限制营养素,使用基于总和及100千卡的算法得出的NRF9·2指数具有较高的R2值(R2 = 0·232)。在进行多次调整后,NRF9·2指数第四四分位数(Q4)相对于第一四分位数(Q1)的超重(由BMI定义)的比值比(OR)为0·61(95%置信区间 = 0·37,0·98)。
使用基于总和及100千卡算法的NRF9·2指数为饮食质量提供了最佳预测模型。NRF9·2指数得分与BMI定义的超重相关,但与中心性肥胖无关。NRF9·2指数是评估中国河南省成年人总体饮食质量的有效工具。