Description of Module “Nutritional Epidemiology”

Overview

There is considerable heterogeneity in the methods used to assess and operationalise dietary questionnaires, dietary recalls, dietary record, diet history questionnaires) are applied. Second, the specific design of assessment instruments varies, to some extent reflecting the variation in regional dietary behaviour. Third, dietary intake is characterised by different levels (e.g., meal intake, dietary pattern, dietary intake) and corresponding dimensions (e.g., food intake, nutrient intake) and subdimensions (e.g., specific nutrients). Hence, this heterogeneity has often per se impeded attempts to synthesize results from different studies and also attempts to do cross-study analyses. To overcome these limitations, the Use Case “Nutritional epidemiology” will implement the data infrastructure developed in NFDI4Health in the context of nutritional epidemiological studies to facilitate population-based research on dietary factors and their association to health-related outcomes. A central element is to help researchers with the discovery (Findability) of existing data from observational studies related to the assessment of nutritional behaviour (exposure), by making studies clearly and persistently identifiable and providing those specific metadata, which help researchers to decide on the suitability of studies to answer their research questions.

Scenario

Planning of an analysis across many studies to answer the research question: How is sugar intake associated with body composition? A researcher aims to close the current research gap on the association between sugar intake and body composition. Since he has a relatively small sample size in his own study, but needs a bigger sample to gain enough statistical power for his planned analyses, he wants to get an overview on other studies with the respective data to ask them for a collaboration. In particular for the data on sugar intake, he would need to know, if a similar dietary assessment instrument was applied, so that the data would be comparable across the studies with regards to the referring time frame (usual intake ~ previous year) or the granularity of information on inquired food and drink items. Furthermore, he would like to check the reliability and validity of the applied instruments to evaluate the compatibility of the derived dietary intake data. Consequently, an extension of the core metadata scheme by a specific module describing dietary assessment in detail, is inevitable.

Authors (with affiliations) of the Nutritional Epidemiology Module

• Franziska Jannasch, German Institute of Human Nutrition Potsdam-Rehbrücke
• Matthias Schulze, German Institute of Human Nutrition Potsdam-Rehbrücke