Measurement error adjustment in essential fatty acid intake from a food frequency questionnaire: alternative approaches and methods
Measurement error adjustment in essential fatty acid intake from a food frequency questionnaire: alternative approaches and methods
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DOI：
10.1186/1471-2288-7-41
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发表时间：
2007-09-14
影响因子：
4
通讯作者：
Heiss, Gerardo
中科院分区：
文献类型：
--
作者：
Beydoun, May A.;Kaufman, Jay S.;Heiss, Gerardo
背景资料：我们的目的是评估食物频率问卷中必需脂肪酸摄入量的测量误差程度，以及校正这种误差对logistic模型中比值比的精度和偏倚的影响。为了评估这些影响，并说明的目的，替代的方法和手段被用来与二进制的认知下降的结果，在口头fluency.Methods：使用社区动脉粥样硬化风险（ARIC）的研究，我们进行了敏感性分析。7，814例50岁或以上的受试者基线时的易出错检查-访视1脂肪酸摄入量（1987-89）-在访视2（1990-92）和访视4（1996-98）之间有关于认知下降的完整数据。我们感兴趣的二元结果是语言流畅性的临床显著下降。点估计值和95%置信区间之间的天真和测量误差调整的比值比下降，每SD增加脂肪酸摄入量的能量%。探索了两种调整方法：（A）针对生物标志物（胆固醇酯和磷脂中的血浆脂肪酸）的外部验证和（B）访视2和3时的内部重复测量。两者之间的主要区别在于，方法B对结构模型中缺乏误差相关性做出了更强的假设。此外，我们还比较了回归校准（RCAL）和模拟外推（SIMEX）的结果。最后，使用结构方程模型，我们估计衰减因子与每一个膳食暴露，以评估在一个双变量的情况下回归校准的logistic regression model.Results的测量误差程度和结论：衰减因子的方法A小于B，表明在膳食暴露的测量误差较大。与浓度生物标志物（方法A）不同，重复测量（方法B）可能会由于较大的标准误差而导致不精确的比值比。使用SIMEX而不是RCAL模型往往会保持优势比的精度。我们发现，在许多情况下，在天真的优势比偏向零。与SIMEX相比，RCAL倾向于校正更大量的效应偏倚，特别是对于方法A。
Background: We aimed at assessing the degree of measurement error in essential fatty acid intakes from a food frequency questionnaire and the impact of correcting for such an error on precision and bias of odds ratios in logistic models. To assess these impacts, and for illustrative purposes, alternative approaches and methods were used with the binary outcome of cognitive decline in verbal fluency.Methods: Using the Atherosclerosis Risk in Communities (ARIC) study, we conducted a sensitivity analysis. The error-prone exposure-visit 1 fatty acid intake (1987-89) - was available for 7,814 subjects 50 years or older at baseline with complete data on cognitive decline between visits 2 (1990-92) and 4 (1996-98). Our binary outcome of interest was clinically significant decline in verbal fluency. Point estimates and 95% confidence intervals were compared between naive and measurement-error adjusted odds ratios of decline with every SD increase in fatty acid intake as % of energy. Two approaches were explored for adjustment: (A) External validation against biomarkers (plasma fatty acids in cholesteryl esters and phospholipids) and (B) Internal repeat measurements at visits 2 and 3. The main difference between the two is that Approach B makes a stronger assumption regarding lack of error correlations in the structural model. Additionally, we compared results from regression calibration (RCAL) to those from simulation extrapolation (SIMEX). Finally, using structural equations modeling, we estimated attenuation factors associated with each dietary exposure to assess degree of measurement error in a bivariate scenario for regression calibration of logistic regression model.Results and conclusion: Attenuation factors for Approach A were smaller than B, suggesting a larger amount of measurement error in the dietary exposure. Replicate measures (Approach B) unlike concentration biomarkers (Approach A) may lead to imprecise odds ratios due to larger standard errors. Using SIMEX rather than RCAL models tends to preserve precision of odds ratios. We found in many cases that bias in naive odds ratios was towards the null. RCAL tended to correct for a larger amount of effect bias than SIMEX, particularly for Approach A.