Nutritional Statistics

Content

In this course, the student will get theoretical knowledge from lectures, and practical knowledge from data collection and statistical workshops.

This course will cover several aspects of nutritional epidemiology with a focus on the principles of dietary data collection, processing, reporting and statistical analysis. It is of interest to anyone who likes to learn more about dietary assessment, nutrient calculations, measurement of nutrient status and malnutrition, and aims to understand the specific assets of analyzing nutritional data including pattern analysis. Epidemiological principles are addressed specifically for the dietary context, including confounding, reverse causation and multi-collinearity.

Entry requirements

Prior knowledge that is needed:

• Basic knowledge in statistics (including knowledge on data distributions, tests for between-group differences, regression analysis)
• Basic knowledge of study designs (clinical trials, cohorts)
• Basic nutritional knowledge

If you do not master the above nutritional knowledge, please watch these videos for self-study beforehand:

https://www.youtube.com/watch?v=fR3NxCR9z2U
https://www.youtube.com/watch?v=kb146Y1igTQ
https://www.youtube.com/watch?v=H8WJ2KENlK0
https://www.youtube.com/watch?v=00jbG_cfGuQ
https://www.youtube.com/watch?v=TBNCqRCsSvY

Learning outcomes
The student

• has gained insight in how nutritional data is collected and can use this knowledge to choose an appropriate diet assessment method from a range of dietary questionnaires (24h-recall, food diary, Food Frequency Questionnaire) and intake biomarkers, taking into account its advantages, disadvantages and validity/reproducibility, in relation to the study design.
• is able to process the raw dietary data (handling, cleaning and calculations of the data in software packages) using food composition tables.
• is able to describe accurately the dietary intake for nutrients, food groups and food pattern approaches.
• is able to indicate and explain sources of error in the dietary data taking into account data collection, data processing, and nutrient calculations.
• is able to perform statistical analysis of the data taking into account confounding, multi-collinearity and adjustment for energy intake.
• is able to use different methods to calculate dietary patterns (pre-defined and data-driven methods), is able to analyze the relationship between dietary patterns and outcomes using regression and is able to interpret the findings.
• is able to make a critical appraisal of the findings taking into account concepts of bias, confounding, reverse causation and generalizability.

Literature for self-study

• handouts and papers from the lectures
• information and instructions from practicals
• Book: Nutritional Epidemiology, Walter Willet (Third edition, 2013)

This book is available at the RuG library as e-book. Chapters 3 and 4 are obligatory, Chapters 5 and 6 are useful to learn about the food frequency questionnaire. https://rug.on.worldcat.org/oclc/827777851

Exam (final assignment) / assessment
In principle, 100% attendance is required. Mandatory individual assignment at the end of the course, with grading.