SIMEX for correction of dietary exposure effects with Box‐Cox transformed data

SIMEX for correction of dietary exposure effects with Box‐Cox transformed data
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SIMEX 通过 BoxâCox 转换数据校正饮食暴露影响

DOI:
10.1002/bimj.201900066
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发表时间:
2020
影响因子:
1.7
通讯作者:
Pigeot I on behalf of the I.Family consortium
Pigeot I on behalf of the I.Family consortium
中科院分区:
生物学3区
文献类型:
--
作者:
Intemann T;Mehlig K;De Henauw S;Siani A;Constantinou T;Moreno LA;Molnár D;Veidebaum T;Pigeot I on behalf of the I.Family consortium

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对饮食数据,尤其是 24 小时饮食回忆 (24HDR) 数据进行建模是一项挑战。在调查暴露与结果之间的关联时,忽略固有测量误差 (ME) 会导致效应估计出现偏差。我们提出了一种适应模拟外推(SIMEX)算法来对饮食暴露进行建模。为此,我们利用 NCI 方法的 ME 模型,其中假设 Box-Cox 变换量表上报告的摄入量的误差呈正态分布,并且假设原始量表上的无偏回忆。根据 SIMEX 算法,生成具有附加 ME 的观测数据的重新测量,以便估计 ME 水平与最终效果估计之间的关联。随后,这种关联被外推到零 ME 的情况以获得校正的估计。我们证明所提出的方法满足 SIMEX 方法的关键属性,即如果 ME 方差收敛到零,则生成数据的 MSE 将收敛到零。此外,该方法还应用于 I.Family 研究的真实 24HDR 数据,以纠正盐和酒精摄入对血压的影响。在模拟研究中,将该方法与 NCI 方法进行比较,导致在某些情况下具有较小的 MSE 或较小的偏差的效果估计。此外,我们发现我们的方法信息更丰富且更易于实施。因此,我们得出的结论是,所提出的方法有助于促进营养流行病学中 ME 校正方法的传播。
Modelling dietary data, and especially 24‐hr dietary recall (24HDR) data, is a challenge. Ignoring the inherent measurement error (ME) leads to biased effect estimates when the association between an exposure and an outcome is investigated. We propose an adapted simulation extrapolation (SIMEX) algorithm for modelling dietary exposures. For this purpose, we exploit the ME model of the NCI method where we assume the assumption of normally distributed errors of the reported intake on the Box‐Cox transformed scale and of unbiased recalls on the original scale. According to the SIMEX algorithm, remeasurements of the observed data with additional ME are generated in order to estimate the association between the level of ME and the resulting effect estimate. Subsequently, this association is extrapolated to the case of zero ME to obtain the corrected estimate. We show that the proposed method fulfils the key property of the SIMEX approach, that is, that the MSE of the generated data will converge to zero if the ME variance converges to zero. Furthermore, the method is applied to real 24HDR data of the I.Family study to correct the effects of salt and alcohol intake on blood pressure. In a simulation study, the method is compared with the NCI method resulting in effect estimates with either smaller MSE or smaller bias in certain situations. In addition, we found our method to be more informative and easier to implement. Therefore, we conclude that the proposed method is useful to promote the dissemination of ME correction methods in nutritional epidemiology.
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