Development and evaluation of three-stage procedures for modelling exposure patterns in epidemiological studies

与生活方式有关的各种因素的相互作用在很大程度上促进了糖尿病、肥胖症和癌症等多因素疾病的发展。3-SP是专门为解决现有数据日益复杂的问题而设计的，因为传统上用于流行病学研究的方法不能满足这一挑战。数据的日益复杂是由于近年来的技术进步使调查工具的有效性得以提高。例如，基于网络的24小时饮食召回和可穿戴式加速计现在经常被用来通过频繁重复测量来评估一段时间内的饮食摄入量和体力活动。为了基于这种具有个体内部差异的高维数据，对暴露和结果之间的关系进行适当的建模，3-SP分三个步骤进行。在第一阶段，通常的曝光量是使用考虑到个体内差异的误差校正模型得出的。这为第二阶段提供了基础，在第二阶段，使用集群模型将个人分配给暴露模式，而在第三阶段使用该模式来使用回归模型来建模这些模式与感兴趣的结果之间的关联。这种不同统计方法的多阶段组合导致了误差传播，在调查最终估计器的性质时需要考虑这一点。因此，该项目将调查在3-SP中结合不同方法得出的估计值的理论偏差和方差；此外，还将制定3-SP的应用建议，并研究其实际可行性。为此，将考虑SIMEX等纠错方法，并进行理论研究和仿真研究。将利用最近完成的IDEFICS/I家庭研究的数据，研究3-SP方法在实际应用中的可行性。这些研究提供了16,228名2至9.9岁欧洲儿童的队列数据。由于参与儿童的详细表型，这些数据为评估拟议的方法提供了一个典型的应用背景。

The interaction of various lifestyle-related factors contributes substantially to the development of multifactorial diseases such as diabetes, obesity and cancer. This project aims to develop a novel three-stage procedure (3-SP), and to investigate its properties and practical application, so as to improve the statistical analysis of the role of such factors in the development of diseases within the context of epidemiological studies. The 3-SP is specifically designed to address the growing complexity of available data, as methods traditionally employed in epidemiological studies fall short of this challenge. The growing complexity of the data is due to technical advances of recent years which enabled an increased validity of survey instruments. For instance, web-based 24-hour dietary recalls and wearable accelerometers are now routinely used to assess dietary intake and physical activity over a time period by frequent repeated measurements. To model the relation between exposure and outcome appropriately based on such high-dimensional data with intra-individual variation the 3-SP proceeds in three steps. At the first stage, the usual exposure is derived using error correction models accounting for intra-individual variation. This provides the basis for the second stage, where cluster models are used to assign individuals to exposure patterns which in turn are used at the third stage to model associations between such patterns and the outcome of interest using regression models. This multi-stage combination of different statistical methods gives rise to an error propagation which needs to be taken into account when investigating the properties of the final estimators. Furthermore, it needs to be addressed which method is most appropriate and feasible at each stage.Hence, the project will investigate the theoretical bias and the variance of estimators derived by combining different methods in the 3-SP; moreover, recommendations for the application of the 3-SP will be developed and its practical feasibility examined. To this end, error correction methods such as SIMEX will be considered, theoretical investigations and a simulation study will be conducted. The feasibility of the 3-SP methodology for practical applications will be investigated using data from the recently completed IDEFICS/I.Family studies. These studies provide cohort data on 16,228 European children aged 2 to 9.9 years. Due to the detailed phenotyping of the participating children the data offer a typical applied context for assessing the proposed methodology.