RT Journal Article
T1 Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements.
A1 Pinart, Mariona
A1 Nimptsch, Katharina
A1 Bouwman, Jildau
A1 Dragsted, Lars O
A1 Yang, Chen
A1 De-Cock, Nathalie
A1 Lachat, Carl
A1 Perozzi, Giuditta
A1 Canali, Raffaella
A1 Lombardo, Rosario
A1 D'Archivio, Massimo
A1 Guillaume, Michèle
A1 Donneau, Anne-Françoise
A1 Jeran, Stephanie
A1 Linseisen, Jakob
A1 Kleiser, Christina
A1 Nöthlings, Ute
A1 Barbaresko, Janett
A1 Boeing, Heiner
A1 Stelmach-Mardas, Marta
A1 Heuer, Thorsten
A1 Laird, Eamon
A1 Walton, Janette
A1 Gasparini, Paolo
A1 Robino, Antonietta
A1 Castaño, Luis
A1 Rojo-Martinez, Gemma
A1 Merino, Jordi
A1 Masana, Luis
A1 Standl, Marie
A1 Schulz, Holger
A1 Biagi, Elena
A1 Nurk, Eha
A1 Matthys, Christophe
A1 Gobbetti, Marco
A1 de-Angelis, Maria
A1 Windler, Eberhard
A1 Zyriax, Birgit-Christiane
A1 Tafforeau, Jean
A1 Pischon, Tobias
K1 Biomarkers
K1 Insulin
K1 Lipoproteins
AB Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition.
YR 2018
FD 2018
LK http://hdl.handle.net/10668/12191
UL http://hdl.handle.net/10668/12191
LA en
NO Pinart M, Nimptsch K, Bouwman J, Dragsted LO, Yang C, De Cock N, Lachat C, et al. Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements. J Nutr. 2018 Feb 1;148(2):285-297
DS RISalud
RD Apr 10, 2025