Department of Health Professions, Faculty of Health, Psychology and Social Care, Manchester Metropolitan University, Manchester, United Kingdom.
Future Food Beacon of Excellence, University of Nottingham, Sutton Bonington, United Kingdom.
J Nutr. 2021 Apr 8;151(4):962-969. doi: 10.1093/jn/nxaa406.
Dietary assessments in research and clinical settings are largely reliant on self-reported questionnaires. It is acknowledged that these are subject to measurement error and biases and that objective approaches would be beneficial. Dietary biomarkers have been purported as a complementary approach to improve the accuracy of dietary assessments. Tentative biomarkers have been identified for many individual fruits and vegetables (FVs), but an objective total FV intake assessment tool has not been established.
To derive and validate a prediction model of total FV intake (TFVpred) to inform future biomarker studies.
Data from the National Diet and Nutrition Survey (NDNS) were used for this analysis. A modeling group (MG) consisting of participants aged >11 years from the NDNS years 5-6 was created (n = 1746). Intake data for 96 FVs were analyzed by stepwise regression to derive a model that satisfied 3 selection criteria: SEE ≤80, R2 >0.7, and ≤10 predictors. The TFVpred model was validated using comparative data from a validation group (VG) created from the NDNS years 7-8 (n = 1865). Pearson's correlation coefficients were assessed between observed and predicted values in the MG and VG. Bland-Altman plots were used to assess agreement between TFVpred estimates and total FV intake.
A TFVpred model, comprised of tomatoes, apples, carrots, bananas, pears, strawberries, and onions, satisfied the selection criteria (R2 = 0.761; SEE = 78.81). Observed and predicted total FV intake values were positively correlated in the MG (r = 0.872; P < 0.001; R2 = 0.761) and the VG (r = 0.838; P < 0.001; R2 = 0.702). In the MG and VG, 95.0% and 94.9%, respectively, of TFVpred model residuals were within the limits of agreement.
Intakes of a concise FV list can be used to predict total FV intakes in a UK population. The individual FVs included in the TFVpred model present targets for biomarker discovery aimed at objectively assessing total FV intake.
在研究和临床环境中,饮食评估在很大程度上依赖于自我报告的问卷。人们认识到,这些问卷容易受到测量误差和偏差的影响,因此采用客观的方法会更有益。饮食生物标志物已被认为是一种补充方法,可以提高饮食评估的准确性。已经确定了许多单一水果和蔬菜(FV)的暂定生物标志物,但尚未建立客观的总 FV 摄入量评估工具。
开发和验证总 FV 摄入量(TFVpred)的预测模型,为未来的生物标志物研究提供信息。
本分析使用了国家饮食与营养调查(NDNS)的数据。创建了一个包含 NDNS 第 5-6 年年龄大于 11 岁的参与者的建模组(MG)(n=1746)。通过逐步回归分析了 96 种 FV 的摄入量数据,以得出满足 3 个选择标准的模型:SEE≤80、R2>0.7 和≤10 个预测因子。使用从 NDNS 第 7-8 年创建的验证组(VG)(n=1865)中的比较数据验证了 TFVpred 模型。在 MG 和 VG 中,评估了观察值和预测值之间的 Pearson 相关系数。Bland-Altman 图用于评估 TFVpred 估计值与总 FV 摄入量之间的一致性。
由番茄、苹果、胡萝卜、香蕉、梨、草莓和洋葱组成的 TFVpred 模型满足选择标准(R2=0.761;SEE=78.81)。在 MG 和 VG 中,观察到的和预测的总 FV 摄入量值呈正相关(MG:r=0.872;P<0.001;R2=0.761;VG:r=0.838;P<0.001;R2=0.702)。在 MG 和 VG 中,TFVpred 模型残差的 95.0%和 94.9%分别在一致性限内。
简洁的 FV 清单摄入量可用于预测英国人群的总 FV 摄入量。TFVpred 模型中包含的单个 FV 是发现旨在客观评估总 FV 摄入量的生物标志物的目标。