Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements

Research output: Contribution to journalJournal articleResearchpeer-review

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Joint data analysis in nutritional epidemiology : Identification of observational studies and minimal requirements. / Pinart, Mariona; Nimptsch, Katharina; Bouwman, Jildau; Dragsted, Lars Ove; Yang, Chen; De Cock, Nathalie; Lachat, Carl; Perozzi, Giuditta; Canali, Raffaella; Lombardo, Rosario; D'Archivio, Massimo; Guillaume, Michèle; Donneau, Anne-Françoise; Jeran, Stephanie; Linseisen, Jakob; Kleiser, Christina; Nöthlings, Ute; Barbaresko, Janett; Boeing, Heiner; Stelmach-Mardas, Marta; Heuer, Thorsten; Laird, Eamon; Walton, Janette; Gasparini, Paolo; Robino, Antonietta; Castaño, Luis; Rojo-Martínez, Gemma; Merino, Jordi; Masana, Luis; Standl, Marie; Schulz, Holger; Biagi, Elena; Nurk, Eha; Matthys, Christophe; Gobbetti, Marco; de Angelis, Maria; Windler, Eberhard; Zyriax, Birgit-Christiane; Tafforeau, Jean; Pischon, Tobias.

In: Journal of Nutrition, Vol. 148, No. 2, 2018, p. 285-297.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Pinart, M, Nimptsch, K, Bouwman, J, Dragsted, LO, Yang, C, De Cock, N, Lachat, C, Perozzi, G, Canali, R, Lombardo, R, D'Archivio, M, Guillaume, M, Donneau, A-F, Jeran, S, Linseisen, J, Kleiser, C, Nöthlings, U, Barbaresko, J, Boeing, H, Stelmach-Mardas, M, Heuer, T, Laird, E, Walton, J, Gasparini, P, Robino, A, Castaño, L, Rojo-Martínez, G, Merino, J, Masana, L, Standl, M, Schulz, H, Biagi, E, Nurk, E, Matthys, C, Gobbetti, M, de Angelis, M, Windler, E, Zyriax, B-C, Tafforeau, J & Pischon, T 2018, 'Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements', Journal of Nutrition, vol. 148, no. 2, pp. 285-297. https://doi.org/10.1093/jn/nxx037

APA

Pinart, M., Nimptsch, K., Bouwman, J., Dragsted, L. O., Yang, C., De Cock, N., ... Pischon, T. (2018). Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements. Journal of Nutrition, 148(2), 285-297. https://doi.org/10.1093/jn/nxx037

Vancouver

Pinart M, Nimptsch K, Bouwman J, Dragsted LO, Yang C, De Cock N et al. Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements. Journal of Nutrition. 2018;148(2):285-297. https://doi.org/10.1093/jn/nxx037

Author

Pinart, Mariona ; Nimptsch, Katharina ; Bouwman, Jildau ; Dragsted, Lars Ove ; Yang, Chen ; De Cock, Nathalie ; Lachat, Carl ; Perozzi, Giuditta ; Canali, Raffaella ; Lombardo, Rosario ; D'Archivio, Massimo ; Guillaume, Michèle ; Donneau, Anne-Françoise ; Jeran, Stephanie ; Linseisen, Jakob ; Kleiser, Christina ; Nöthlings, Ute ; Barbaresko, Janett ; Boeing, Heiner ; Stelmach-Mardas, Marta ; Heuer, Thorsten ; Laird, Eamon ; Walton, Janette ; Gasparini, Paolo ; Robino, Antonietta ; Castaño, Luis ; Rojo-Martínez, Gemma ; Merino, Jordi ; Masana, Luis ; Standl, Marie ; Schulz, Holger ; Biagi, Elena ; Nurk, Eha ; Matthys, Christophe ; Gobbetti, Marco ; de Angelis, Maria ; Windler, Eberhard ; Zyriax, Birgit-Christiane ; Tafforeau, Jean ; Pischon, Tobias. / Joint data analysis in nutritional epidemiology : Identification of observational studies and minimal requirements. In: Journal of Nutrition. 2018 ; Vol. 148, No. 2. pp. 285-297.

Bibtex

@article{66cff4d58a324802a4e1b5cc93cd6dd5,
title = "Joint data analysis in nutritional epidemiology: Identification of observational studies and minimal requirements",
abstract = "Background: 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.Objective: 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.Methods: 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.Results: 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.Conclusions: 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.",
keywords = "Faculty of Science, Nutritional phenotype, Metadata, Data integration, Data sharing, Observational studies",
author = "Mariona Pinart and Katharina Nimptsch and Jildau Bouwman and Dragsted, {Lars Ove} and Chen Yang and {De Cock}, Nathalie and Carl Lachat and Giuditta Perozzi and Raffaella Canali and Rosario Lombardo and Massimo D'Archivio and Mich{\`e}le Guillaume and Anne-Fran{\cc}oise Donneau and Stephanie Jeran and Jakob Linseisen and Christina Kleiser and Ute N{\"o}thlings and Janett Barbaresko and Heiner Boeing and Marta Stelmach-Mardas and Thorsten Heuer and Eamon Laird and Janette Walton and Paolo Gasparini and Antonietta Robino and Luis Casta{\~n}o and Gemma Rojo-Mart{\'i}nez and Jordi Merino and Luis Masana and Marie Standl and Holger Schulz and Elena Biagi and Eha Nurk and Christophe Matthys and Marco Gobbetti and {de Angelis}, Maria and Eberhard Windler and Birgit-Christiane Zyriax and Jean Tafforeau and Tobias Pischon",
note = "CURIS 2018 NEXS 087",
year = "2018",
doi = "10.1093/jn/nxx037",
language = "English",
volume = "148",
pages = "285--297",
journal = "Journal of Nutrition",
issn = "0022-3166",
publisher = "American Society for Nutrition",
number = "2",

}

RIS

TY - JOUR

T1 - Joint data analysis in nutritional epidemiology

T2 - Identification of observational studies and minimal requirements

AU - Pinart, Mariona

AU - Nimptsch, Katharina

AU - Bouwman, Jildau

AU - Dragsted, Lars Ove

AU - Yang, Chen

AU - De Cock, Nathalie

AU - Lachat, Carl

AU - Perozzi, Giuditta

AU - Canali, Raffaella

AU - Lombardo, Rosario

AU - D'Archivio, Massimo

AU - Guillaume, Michèle

AU - Donneau, Anne-Françoise

AU - Jeran, Stephanie

AU - Linseisen, Jakob

AU - Kleiser, Christina

AU - Nöthlings, Ute

AU - Barbaresko, Janett

AU - Boeing, Heiner

AU - Stelmach-Mardas, Marta

AU - Heuer, Thorsten

AU - Laird, Eamon

AU - Walton, Janette

AU - Gasparini, Paolo

AU - Robino, Antonietta

AU - Castaño, Luis

AU - Rojo-Martínez, Gemma

AU - Merino, Jordi

AU - Masana, Luis

AU - Standl, Marie

AU - Schulz, Holger

AU - Biagi, Elena

AU - Nurk, Eha

AU - Matthys, Christophe

AU - Gobbetti, Marco

AU - de Angelis, Maria

AU - Windler, Eberhard

AU - Zyriax, Birgit-Christiane

AU - Tafforeau, Jean

AU - Pischon, Tobias

N1 - CURIS 2018 NEXS 087

PY - 2018

Y1 - 2018

N2 - Background: 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.Objective: 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.Methods: 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.Results: 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.Conclusions: 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.

AB - Background: 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.Objective: 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.Methods: 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.Results: 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.Conclusions: 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.

KW - Faculty of Science

KW - Nutritional phenotype

KW - Metadata

KW - Data integration

KW - Data sharing

KW - Observational studies

U2 - 10.1093/jn/nxx037

DO - 10.1093/jn/nxx037

M3 - Journal article

C2 - 29490094

VL - 148

SP - 285

EP - 297

JO - Journal of Nutrition

JF - Journal of Nutrition

SN - 0022-3166

IS - 2

ER -

ID: 191684143