Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements

Pinart, Mariona; Nimptsch, Katharina; Bouwman, Jildau; Dragsted, Lars Ove; Yang, Chen; Cock, Nathalie De; 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, Éamon; Walton, Janette; Gasparini, Paolo; Robino, Antonietta; Castaño, Luís; Rojo‐Martínez, Gemma; Merino, Jordi; Standl, Marie; Schulz, Holger; Biagi, Elena; Nurk, Eha; Matthys, Christophe; Gobbetti, Marco; Angelis, Maria De; Windler, E.; Zyriax, BC; Tafforeau, Jean; Pischon, Tobias

doi:10.1093/jn/nxx037

Cited by 15 publications

(19 citation statements)

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“…When fully achieved, integrated analysis will lead to new discoveries and maximize use of public funds. In ENPADASI, this problem was broadly dealt with from both legal and technical aspects, and a recommendation on minimal information to be added as metadata to studies to boost integration capacity has been developed [ 19 ]. The identification of minimal requirements, essential to connect existing and future study (meta) databases, facilitates data exchange and data interpretation, helping to increase the robustness of results from future joint data analysis in nutritional epidemiology [ 31 ].…”

Section: Resultsmentioning

confidence: 99%

“…The ONS was developed within the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium [ 17 ], which joins scientists from 51 research centers in nine countries of Europe with the common effort to handle and make available big nutritional data through the open access nutritional database Data Sharing In Nutrition (DASH-IN) [ 17 , 18 ]. DASH-IN is a distributed pan-European infrastructure and supports the storage of both interventional and observational studies and provides the tools for distributed management and search and analysis of the data [ 19 ]. The development of this infrastructure requires an ontology to harmonize biochemical, genetic, clinical, and nutritional concepts typically found in intervention and observational studies.…”

Section: Introductionmentioning

confidence: 99%

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ONS: an ontology for a standardized description of interventions and observational studies in nutrition

et al. 2018

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BackgroundThe multidisciplinary nature of nutrition research is one of its main strengths. At the same time, however, it presents a major obstacle to integrate data analysis, especially for the terminological and semantic interpretations that specific research fields or communities are used to. To date, a proper ontology to structure and formalize the concepts used for the description of nutritional studies is still lacking.ResultsWe have developed the Ontology for Nutritional Studies (ONS) by harmonizing selected pre-existing de facto ontologies with novel health and nutritional terminology classifications. The ONS is the result of a scholarly consensus of 51 research centers in nine European countries. The ontology classes and relations are commonly encountered while conducting, storing, harmonizing, integrating, describing, and searching nutritional studies. The ONS facilitates the description and specification of complex nutritional studies as demonstrated with two application scenarios.ConclusionsThe ONS is the first systematic effort to provide a solid and extensible formal ontology framework for nutritional studies. Integration of new information can be easily achieved by the addition of extra modules (i.e., nutrigenomics, metabolomics, nutrikinetics, and quality appraisal). The ONS provides a unified and standardized terminology for nutritional studies as a resource for nutrition researchers who might not necessarily be familiar with ontologies and standardization concepts.Electronic supplementary materialThe online version of this article (10.1186/s12263-018-0601-y) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ONS: an ontology for a standardized description of interventions and observational studies in nutrition

et al. 2018

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“…By combining a standardized inventory of the different aspects of dietary behavior with a standardized inventory of the ways to assess these aspects, empirical research in the area of nutrition can be more easily compared and pooled. Arguably the most extensive effort to date in the field of nutrition stems from the ENPADASI research project ( Pinart et al, 2018 ), which aims to develop an all-encompassing ontology of all aspects related to nutrition (food components, foods, the diet, the individual, the health, and the diseases). The ontology currently comprises of tens of thousands of entries describing different constructs and the relations between them.…”

Section: Discussionmentioning

confidence: 99%

“…For example, a recent development involves the creation of ontologies [a method for systematically assessing and registering the properties of concepts or constructs within a certain domain, as well as the interrelations between these phenomena ( Groß et al, 2016 ; Larsen and Bong, 2016 ; Larsen et al, 2017 )] to facilitate knowledge accumulation, synthesis and integration. Ontologies have been developed both within nutrition-related research [e.g., the Ontology for Nutritional Studies from the ENPADASI project ( Pinart et al, 2018 ) and the development of the standardized STROBE-nut statement aimed at strengthening reporting of nutritional epidemiological studies ( Lachat et al, 2016 )] as well as in other scientific domains (e.g., Cimino and Zhu, 2006 ; The Gene Ontology Consortium, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Dietary Behavior: An Interdisciplinary Conceptual Analysis and Taxonomy

et al. 2018

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Background: Dietary behavior encompasses many aspects, terms for which are used inconsistently across different disciplines and research traditions. This hampers communication and comparison across disciplines and impedes the development of a cumulative science. We describe the conceptual analysis of the fuzzy umbrella concept “dietary behavior” and present the development of an interdisciplinary taxonomy of dietary behavior.Methods: A four-phase multi-method approach was employed. Input was provided by 76 scholars involved in an international research project focusing on the determinants of dietary behavior. Input was collected from the scholars via an online mind mapping procedure. After structuring, condensing, and categorizing this input into a compact taxonomy, the result was presented to all scholars, discussed extensively, and adapted. A second revision round was then conducted among a core working group.Results: A total of 145 distinct entries were made in the original mind mapping procedure. The subsequent steps allowed us to reduce and condense the taxonomy into a final product consisting of 34 terms organized into three main categories: Food Choice, Eating Behavior, and Dietary Intake/Nutrition. In a live discussion session attended by 50 of the scholars involved in the development of the taxonomy, it was judged to adequately reflect their input and to be a valid and useful starting point for interdisciplinary understanding and collaboration.Conclusion: The current taxonomy can be used as a tool to facilitate understanding and cooperation between different disciplines investigating dietary behavior, which may contribute to a more successful approach to tackling the complex public health challenges faced by the field. The taxonomy need not be viewed as a final product, but can continue to grow in depth and width as additional experts provide their input.

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“…For a while now, there has been a call for data sharing across the sector; from funding agency to industry and academia. Provision of raw data, as precious as it is, allows future investigators the opportunity to reanalyze and test newer hypotheses towards clinical medicine outcomes [9], as well as cementing diet and disease relationships [10]. The EJCN, and other like-minded journals, support this move by requesting authors to make their data available on a publically accessible website, or have in place an approach for researchers to request such information.…”

Section: Quality Manuscriptsmentioning

confidence: 99%