HNH-30403 Integration of Evidence I (online)

Code last year: (HNE-30403)


Credits 3.00

Teaching methodContact hours
Knowledge clip0
Individual Paper0
Independent study0
Distance group work0
E-learning material0
Course coordinator(s)dr. ir. MC Busstra
Lecturer(s)dr. ir. A Melse-Boonstra
prof. dr. ir. P van 't Veer
dr. ir. MC Busstra
Examiner(s)dr. ir. MC Busstra

Language of instruction:


Assumed knowledge on:

DL courses HNH-28303 Introduction to Descriptive Epidemiology and HNH- 28803 Introduction to Analytical Epidemiology or HNH-24806 Introduction to Epidemiology and Public Health.
Basics of statistics.
Basic knowledge on the statistical software package R: know how to load a dataset and to do descriptive analyses (e.g means, standard deviations)


This course introduces you to the broadness of the nutritional research domain i.e. mechanistic research in vitro (cell lines), in vivo research and observational research on (human) individuals and populations.
You will focus on several approaches to integrate and judge strength of scientific evidence for a proposed causal relation between a certain (nutritional) exposure and a health outcome.
We take the ‘evidence pyramid’ as a starting point to evaluate strength of scientific evidence. The top of the evidence pyramid, the randomized controlled trial (RCT), is discussed in more detail as a ‘gold standard’ research method. This gives you a solid basis to contrast other research approaches and discuss the potential biases in various study designs.

In addition, you will study the basic statistical analyses methods to quantify intake-health associations in observational studies, as these are the associations that will be judged for their strength of evidence. For the data analysis we use the statistical data analysis software R.
Evaluating and integrating evidence from various studies is an essential skill because often you will be confronted with inconsistent research results.

A solid basis in ‘causal thinking’ and ‘causal inference’ is a prerequisite to deal with these inconsistencies both in fundamental (epidemiological) research, public health practice and policy development.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- discuss strengths and limitations of observational studies, human intervention studies and animal or cell line studies;
- show understanding of causal models (e.g. the Rothman Pie, counterfactuals, evidence pyramid, Hill criterial etc) by applying these models to specific examples of exposure-outcome associations.
- explain under which circumstances a RCT can/cannot be considered as a gold standard research approach;
- be able to quantify intake-health associations based on results of observational studies.


E-modules, knowledge clips, online group discussion & individual assignment.


- final exam: remote proctored written exam with closed questions (60%);
- group assignment: 'discuss evidence for a proposed dietary intake and health outcome' (40%);

- individual assignment (sufficient - pass)

Both components need a minimum mark of 5.5 to pass.


Petrie & Sabin, Medical statistics at a glance, (selection of chapters)
Webb & Bain, Essential Epidemiology, 2nd or 3rd edition, Ch 10
MJ. Gibney et al, Public health nutrition, 2004. Ch 11

Compulsory for: MNHNutrition and HealthMScE: Nutritional Epidemiology and Public Health6DL