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

各种与生活方式有关的因素的相互作用在很大程度上促进了糖尿病、肥胖和癌症等多因素疾病的发展。本项目旨在开发一种新的三阶段程序（3-SP），并研究其性质和实际应用，以便在流行病学研究的背景下改进这些因素在疾病发展中的作用的统计分析。3-SP是专门为解决现有数据日益复杂的问题而设计的，因为流行病学研究中传统使用的方法无法应对这一挑战。数据的日益复杂是由于近年来技术的进步使调查工具的有效性得到提高。例如，基于网络的24小时饮食回顾和可穿戴加速计现在通常用于通过频繁重复测量来评估一段时间内的饮食摄入量和身体活动。为了根据这种具有个体内部差异的高维数据适当地模拟暴露与结果之间的关系，3-SP分三个步骤进行。在第一阶段，通常的暴露是使用误差修正模型来计算个体内部的变化。这为第二阶段提供了基础，其中集群模型用于将个体分配到暴露模式，然后在第三阶段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会产生误差传播，在研究最终估计器的性质时需要考虑到这一点。此外，需要解决在每个阶段哪种方法是最合适和可行的。因此，该项目将研究3-SP中结合不同方法得出的估计量的理论偏差和方差；此外，还将就3-SP的应用提出建议，并审查其实际可行性。为此，将考虑SIMEX等纠错方法，并进行理论调查和模拟研究。将利用最近完成的IDEFICS/I的数据调查3-SP方法在实际应用中的可行性。家庭研究。这些研究提供了16228名2至9.9岁的欧洲儿童的队列数据。由于参与儿童的详细表型，这些数据为评估所提出的方法提供了典型的应用背景。

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.