IDEFICS/I.Family - Cohort Dataset

The IDEFICS/I.Family Cohort Dataset includes all data collected and derived for this cohort. These were collected at waves T0-T2 (IDEFICS), T3/T4 (I.Family) and T5 (I.Family follow-up). The dataset contains extensive information on anthropometry, health, demographics, physical activity (including accelerometer measurements), dietary behaviour (including food frequency questionnaire and 24-hour dietary recall), laboratory parameters analysed from urine, saliva, blood and stool samples, results of fMRI examinations, neurological tests and data from kindergartens and schools. The data were collected using various questionnaires and surveys or measured using standardised procedures.

The participants were between 2 and 9 years old at baseline (T0) and between 11 and 27 years old at wave T5. In the T3 wave, also siblings and parents of the children from T0/T1 were included.

Further information on the studies and the study content can be found under “Related Resources” (see below). From there, you will be forwarded to the individual entries of the IDEFICS and I.Family study. Detailed information on available variables can be found in the variable catalog which is linked in the data dictionaries:
https://mica.covid19.studyhub.nfdi4health.de/search#lists?type=datasets&query=variable(limit(0,20),in(Mica_variable.datasetId,(string:2982,string:2985,string:2976,string:2983,string:2981,string:2984,string:2987,string:2986))),dataset(limit(0,20))

IDEFICS/I.Family队列数据集包含为本队列收集及衍生的全部数据。该数据集覆盖T0至T2波次（IDEFICS研究）、T3至T4波次（I.Family研究）以及T5波次（I.Family随访研究）的采集工作。数据集涵盖人体测量学、健康状况、人口统计学特征、身体活动（含加速度计测量数据）、饮食行为（含食物频率问卷与24小时膳食回顾数据）、对尿液、唾液、血液及粪便样本分析得到的实验室检测指标、功能磁共振成像（fMRI, functional magnetic resonance imaging）检查结果、神经学测试结果，以及来自幼儿园与学校的相关数据。上述数据通过各类问卷与调研收集，或采用标准化流程完成测量。

研究参与者在基线（T0波次）时年龄为2至9岁，在T5波次时年龄为11至27岁。在T3波次调研中，还纳入了T0/T1波次受访儿童的兄弟姐妹及其父母。

关于本研究及研究内容的更多信息可参见“相关资源”（见下文），点击后将跳转至IDEFICS与I.Family研究的独立条目。关于可用变量的详细信息可查阅数据字典中链接的变量目录：https://mica.covid19.studyhub.nfdi4health.de/search#lists?type=datasets&query=variable(limit(0,20),in(Mica_variable.datasetId,(string:2982,string:2985,string:2976,string:2983,string:2981,string:2984,string:2987,string:2986))),dataset(limit(0,20))