High quality dietary data collection and advanced data analysis methods, as applied at the Division of Human Nutrition, are crucial for nutritional epidemiology and public health research. Developments in the fields of ICT and ‘omics’, as well as in measurement error theory and statistics, offer opportunities to improve and innovate dietary exposure assessment and can lead to efficient methods that generate valid results with impact on public policy.
There is great need for innovation to make current state-of-the-art dietary assessment future-proof for large scale epidemiological and public health research. Technological innovations have the potential to decrease measurement error and enrich the assessment with information on eating behaviour and the food environment. Diet as a whole should be increasingly studied using multi-dimensional patterns based on arrays of variables with multiple assessment methods, including objective biomarkers of intake. Opportunities should not be missed to integrate these new methods in large studies with concomitantly running validation studies.
Comparison of approaches to correct intake-health association for FFQ measurement eroor using a duplicate recovery biomarker and a duplicate 24h dietary recall as reference method
Public Health Nutrition 18 (2015)2. - ISSN 1368-9800 - p. 226 - 233.
Optimising the selection of food items for food frequency questionnaires using Mixed Integer Linear Programming
Public Health Nutrition 18 (2015)1. - ISSN 1368-9800 - p. 68 - 74.
Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study
PLoS One 9 (2014)11. - ISSN 1932-6203 - 15 p.
Large inter-individual variation in isoflavone plasma concentration limits use of isoflavone intake data for risk assessement
European Journal of Clinical Nutrition 68 (2014). - ISSN 0954-3007 - p. 1141 - 1147.
Bias in protein and potassium intake collected with 24-h recalls (EPIC-Soft) is rather comparable across European populations
European Journal of Nutrition 51 (2012)8. - ISSN 1436-6207 - p. 997 - 1010.