BackgroundConcerns have been raised about the quality of reporting in nutritional epidemiology. Research reporting guidelines such as the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement can improve quality of reporting in observational studies. Herein, we propose recommendations for reporting nutritional epidemiology and dietary assessment research by extending the STROBE statement into Strengthening the Reporting of Observational Studies in Epidemiology—Nutritional Epidemiology (STROBE-nut).Methods and FindingsRecommendations for the reporting of nutritional epidemiology and dietary assessment research were developed following a systematic and consultative process, coordinated by a multidisciplinary group of 21 experts. Consensus on reporting guidelines was reached through a three-round Delphi consultation process with 53 external experts. In total, 24 recommendations for nutritional epidemiology were added to the STROBE checklist.ConclusionWhen used appropriately, reporting guidelines for nutritional epidemiology can contribute to improve reporting of observational studies with a focus on diet and health.

Concerns have been raised about the quality of reporting in nutritional epidemiology. Research reporting guidelines such as the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement can improve quality of reporting in observational studies. Herein, we propose recommendations for reporting nutritional epidemiology and dietary assessment research by extending the STROBE statement into Strengthening the Reporting of Observational Studies in Epidemiology – Nutritional Epidemiology (STROBE‐nut). Recommendations for the reporting of nutritional epidemiology and dietary assessment research were developed following a systematic and consultative process, co‐ordinated by a multidisciplinary group of 21 experts. Consensus on reporting guidelines was reached through a three‐round Delphi consultation process with 53 external experts. In total, 24 recommendations for nutritional epidemiology were added to the STROBE checklist. When used appropriately, reporting guidelines for nutritional epidemiology can contribute to improve reporting of observational studies with a focus on diet and health.

Nutritional epidemiology is an inherently complex and multifaceted research area. Dietary intake is a complex exposure and is challenging to describe and assess, and links between diet, health, and disease are difficult to ascertain. Consequently, adequate reporting is necessary to facilitate comprehension, interpretation, and generalizability of results and conclusions. The STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement is an international and collaborative initiative aiming to enhance the quality of reporting of observational studies. We previously presented a checklist of 24 reporting recommendations for the field of nutritional epidemiology, called “the STROBE-nut.” The STROBE-nut is an extension of the general STROBE statement, intended to complement the STROBE recommendations to improve and standardize the reporting in nutritional epidemiology. The aim of the present article is to explain the rationale for, and elaborate on, the STROBE-nut recommendations to enhance the clarity and to facilitate the understanding of the guidelines. Examples from the published literature are used as illustrations, and references are provided for further reading.

Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for “food and nutrition” (n = 37), “disease and specific population” (n = 100), “data description” (n = 21), “research description” (n = 35), and “supplementary (meta) data description” (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology.

Nutrition research can guide interventions to tackle the burden of diet-related diseases. Setting priorities in nutrition research, however, requires the engagement of various stakeholders with diverse insights. Consideration of what matters most in research from a scientific, social, and ethical perspective is therefore not an automatic process. Systematic ways to explicitly define and consider relevant values are largely lacking. Here, we review existing nutrition research priority-setting exercises, analyze how values are reported, and provide guidance for transparent consideration of values while setting priorities in nutrition research. Of the 27 (n = 22 peer-reviewed manuscripts and 5 grey literature documents) studies reviewed, 40.7% used a combination of different methods, 59.3% described the represented stakeholders, and 49.1% reported on follow-up activities. All priority-setting exercises were led by research groups based in high-income countries. Via an iterative qualitative content analysis, reported values were identified (n = 22 manuscripts). Three clusters of values (i.e., those related to impact, feasibility, and accountability) were identified. These values were organized in a tool to help those involved in setting research priorities systematically consider and report values. The tool was finalized through an online consultation with 7 international stakeholders. The value-oriented tool for priority setting in nutrition research identifies and presents values that are already implicitly and explicitly represented in priority-setting exercises. It provides guidance to enable explicit deliberation on research priorities from an ethical perspective. In addition, it can serve as a reporting tool to document how value-laden choices are made during priority setting and help foster the accountability of stakeholders involved.