Population-based cohort studies allow the assessment of exposure-outcome relationships and potential confounders, as well as numerous other variables of potential interest.¹ Given their nature and design, population-based cohort studies generally enable evaluation of multiple hypotheses, some defined a priori whereas others are suggested during the course or at the end of the study.¹ In particular, having data repeatedly and longitudinally collected on cohort members allows the testing and generation of new hypotheses such as predictors of events and disease/state incidence determination and its trends over time, in addition to the testing of multiple associations (in both cross-sectional and longitudinal manners). Additionally, the estimation of distributions and prevalence rates of relevant variables and the calculation of population-attributable risks can be performed, as well as data confirmation for external validation and reproducibility.²

中文翻译：

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队列简介：STANISLAS队列的第四次访问的原理和设计：来自法国南锡地区的家族纵向人口队列

基于人群的队列研究可以评估暴露-结果关系和潜在的混杂因素，以及许多其他可能引起关注的变量。¹基于人群的队列研究，由于其性质和设计，通常可以评估多种假设，其中一些假设是先验的，而其他建议则是在研究过程中或研究结束时提出的。^1个特别是，通过重复和纵向收集队列成员的数据，不仅可以测试和生成新的假设，例如事件和疾病/状态发生率的预测因子的确定以及其随时间推移的趋势，还可以测试多个关联（在两个交叉领域中，截面和纵向方式）。另外，可以进行相关变量的分布和流行率的估计以及人口归因风险的计算，以及用于外部验证和可再现性的数据确认。^2个