T5.1/5.2 Use Cases “Nutritional Epidemiology” and “Epidemiology of chronic diseases”

T5.1/5.2 Use Cases “Nutritional Epidemiology” and “Epidemiology of chronic diseases”


The Use Cases “Nutritional epidemiology” and “Epidemiology of chronic diseases” were chosen to showcase complex exposition and outcome data from the epidemiological research area. The complexity in nutritional data mainly results from a variety of dietary assessment instruments, which were chosen depending on the research questions in the studies. This is resulting in varying methods within and between studies and in distinct granularity of detail for the assessed research data (e.g. frequencies vs. intake amount; covered observation periods). Additionally, different dimensions of nutritional data can be analysed: either in more aggregated forms like meal- and dietary patterns, on the level of food groups and food items, or on the level of macro- and micronutrients. For the research data on chronic diseases, similar complexity is introduced by different assessment methods (self-report to medical diagnosis) and the use of different versions regarding the disease classification system by the WHO (ICD-10 vs. ICD-11).

The epidemiological studies in Germany are also characterised by this heterogeneity in the research data, such as the German National Cohort (GNC), EPIC-Potsdam, EPIC-Heidelberg, KORA and SHIP. The efforts to standardise and harmonise the assessed research data and the immediate implementation of developed services in NFDI4Health will provide a huge advantage for the overall research field in Germany.

Based on typical research questions in the respective research areas, scientists of the Use Cases 5.1 “Nutritional Epidemiology” and 5.2 “Epidemiology of chronic diseases” will work on the development of services regarding data standardisation and harmonisation, which will be provided later for the whole research community.

Pilot studies

The following 3 pilot studies for data standardisation and harmonisation in epidemiological studies are ongoing:

1. Systematic investigation of methodological limitations in the derivation of dietary patterns 

Contact: Dr. Franziska Jannasch

Even though numerous exploratorily derived dietary patterns have been generated in the last two decades, there was no comprehensive investigation of methodological constraints, like the influence of different energy adjustment techniques or different levels of granularity, when condensing food items into food groups, on the resulting pattern composition. Furthermore, for simplified dietary patterns, which can be useful in multi-centre analyses, the systematic investigation of different cut-offs for factor loadings on pattern composition and the comparison with the original dietary patterns are useful analyses to conduct.

2.Association of dietary sugar intake and body composition

Contact: Dr. Ines Perrar

The association of added or free sugar intakes with the development of overweight has been discussed for many years. In 2022, European Food Safety Authority (EFSA) published an update on their "Tolerable upper intake level for dietary sugars", in which they state that it is not possible to set a recommendation due to major research gaps. Pooled analyses examining the impact of sugar intake on the development of obesity and non-communicable diseases are desired. Therefore, in addition to the collection of metadata and standards for data harmonisation, a pooled representative study on the level of sugar intake (e.g., total, added and/or free sugars) as well as its main sources (e.g., SSB, juices, sweets) of children, adolescents and adults in Germany and its association with body composition (e.g., BMI) will be conducted. If available, biomarker data (e.g., urinary sugar excretion) may also be considered.

3. Association of dietary sugar intake and glycaemic load with chronic disease risk 

Contact: Tracy B. Osei

In Germany, chronic diseases represent 89% of the total disease burden, half of which come from cardiovascular diseases (CVD), type 2 diabetes (T2D), and cancer. While dietary sugar intake has been hypothesised to affect chronic disease risk, existing studies vary widely in the definitions of sugar or sugar-containing foods and the chronic diseases studied, highlighting the importance of discerning between types of sugar and knowledge gaps for some chronic diseases. Furthermore, most of the evidence related to dietary sugar intake stems from studies in non-German populations. Using federated data analyses, we aim to examine the associations of simple sugars intake, sugar-sweetened beverage intake, and glycaemic load with chronic disease risk jointly in multiple German population-based prospective observational studies. Our findings will provide disease risk estimates for various chronic diseases in a diverse German population. 

Due to the different level of detail for the assessment and actual availability of nutrient data in the underlying databases, most of the participating studies in our Use Cases are not able to provide detailed information on the exposition of sugar intake. Hence, the two pilot studies investigating the association between sugar intake and body composition and the association with glycaemic load and chronic diseases will be merged into one pilot study. The respective research questions will now focus only on the intake of sugar-rich food (sweets, soft drinks, juices).

In NFDI4Health, data standardisation and harmonisation will be performed based on the Maelstrom harmonisation procedures, which were adapted to the current pilot project needs. From this, the following steps emerge for the projects:

First, metadata collection is performed on the study- and resource-descriptive level via the NFDI4Health German Central Health Study Hub, as well as the collection of metadata describing research data necessary for our pilot studies according to the Maelstrom metadata schema (Step 1 of the maelstrom harmonisation guidelines). At the same time, the OPAL/ DataSHIELD installation and configuration is carried out. DataSHIELD is an infrastructure, which enables the remote and non-disclosive analysis of sensitive research data. A Standard Operating Procedure (SOP) for installing and configuring Opal/DataSHIELD for the NFDI4Health consortium is published here: Github-opal-datashield-sop. Once all the necessary metadata have been collected and the DataSHIELD infrastructure has been installed, the harmonisation can start.
To support the participating studies, a harmonisation protocol was created and published on Github: Github-data-harmonisation-protocol. After harmonisation, the analysis of the research question is performed and harmonised metadata will be made available for re-use.


Schwedhelm C, Nimptsch K, Ahrens W, Hasselhorn HM, Jöckel KH, Katzke V, Kluttig A, Linkohr B, Mikolajczyk R, Nöthlings U, Perrar I, Peters A, Schmidt CO, Schmidt B, Schulze M, Stang A, Zeeb H, Pischon T. Chronic disease outcome metadata from German observational studies – public availability and FAIR principles. Scientific Data. 2023; 10, 868. https://doi.org/10.1038/s41597-023-02726-7

Schwedhelm C, Nimptsch K, Pischon T, Jannasch F, Schulze M, Perrar I, Nöthlings U. Data harmonisation protocol for pilot studies in Use Case 5.1 ‘Nutritional Epidemiology’ and 5.2 ‘Epidemiology of Chronic diseases’. 2023. https://github.com/nfdi4health/data-harmonisation-protocol/wiki
Siampani SM, Schwedhelm C, Nimptsch K, Pischon T. Standard Operating Procedure for Installation and Configuration of Opal DataSHIELD in NFDI4Health. 2023. https://github.com/nfdi4health/opal-datashield-sop/wiki


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Prof. Dr. Matthias Schulze

Measure-Lead: T5.1 “Use case ‘Nutritional epidemiology’”
E-Mail: mschulze@dife.de
Phone: +49 (0)33 200 88 - 2434

German Institute of Human Nutrition Potsdam-Rehbruecke
Arthur-Scheunert-Allee 114-116
14558 Nuthetal 

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Prof. Dr. Ute Nöthlings

Measure-Lead T5.1 “Use case ‘Nutritional epidemiology'”
E-Mail: noethlings@uni-bonn.de
Phone: +49 (0)228 73 60490

University of Bonn,
Institute for Nutrition and Food Sciences
Fiedrich-Hirzebruch-Allee 7
53115 Bonn

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Prof. Dr. Tobias Pischon

Measure-Lead T5.2 “Use case ‘Epidemiology of chronic diseases’”
E-Mail: tobias.pischon@mdc-berlin.de
Phone: +49 (0)30 9406-4563

Max Delbrück Center for Molecular Medicine
Robert-Rössle-Straße 10
13125 Berlin, Deutschland

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Prof. Dr. Hajo Zeeb

Measure-Lead T5.2 “Use case ‘Epidemiology of chronic diseases’”
E-Mail: zeeb@leibniz-bips.de
Phone: +49 (0)421 218-56-902

Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH
Achterstraße 30
D-28359 Bremen

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