Kipnis V, Carroll R J, Freedman L S, Li L
Biometry Branch, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA.
Am J Epidemiol. 1999 Sep 15;150(6):642-51. doi: 10.1093/oxfordjournals.aje.a010063.
Food records or 24-hour recalls are currently used to calibrate food frequency questionnaires (FFQs) and to correct disease risks for measurement error. The standard regression calibration approach requires that these reference measures contain only random within-person errors uncorrelated with errors in FFQs. Increasing evidence suggests that records/recalls are likely to be also flawed with systematic person-specific biases, so that for any individual the average of multiple replicate assessments may not converge to her/his true usual nutrient intake. The authors propose a new measurement error model to accommodate person-specific bias in the reference measure and its correlation with systematic error in the FFQ. Sensitivity analysis using calibration data from four studies demonstrates that failure to account for person-specific bias in the reference measure can often lead to substantial underestimation of the relative risk for a nutrient. These results indicate that in the absence of information on the extent of person-specific biases in reference instruments and their relation to biases in FFQs, the adequacy of the standard methods of correcting relative risks for measurement error is in question, as is the interpretation of negative findings from nutritional epidemiology such as failure to detect an important relation between fat intake and breast cancer.
食物记录或24小时膳食回顾目前被用于校准食物频率问卷（FFQ），并校正疾病风险的测量误差。标准回归校准方法要求这些参考测量仅包含与FFQ误差不相关的个体内随机误差。越来越多的证据表明，记录/回顾也可能存在特定个体的系统性偏差，因此对于任何个体而言，多次重复评估的平均值可能不会收敛于其真实的通常营养素摄入量。作者提出了一种新的测量误差模型，以适应参考测量中的特定个体偏差及其与FFQ中系统误差的相关性。使用四项研究的校准数据进行的敏感性分析表明，未能考虑参考测量中的特定个体偏差通常会导致对营养素相对风险的严重低估。这些结果表明，在缺乏关于参考工具中特定个体偏差程度及其与FFQ偏差关系的信息的情况下，校正测量误差相对风险的标准方法是否充分值得怀疑，营养流行病学中阴性结果的解释（如未能检测到脂肪摄入与乳腺癌之间的重要关系）也是如此。
