The good life: living for health and a life without risks? On a prominent script of nutrigenomics

Br J Nutr. 2009 Feb;101(3):307-16. doi: 10.1017/S0007114508076253. Epub 2008 Oct 2.


Like all scientific innovations, nutrigenomics develops through a constant interplay with society. Normative assumptions, embedded in the way researchers formulate strands of nutrigenomics research, affect this interplay. These assumptions may influence norms and values on food and health in our society. To discuss the possible pros and cons of a society with nutrigenomics, we need to reflect ethically on assumptions rooted in nutrigenomics research. To begin with, we analysed a set of scientific journal articles and explicated three normative assumptions embedded in the present nutrigenomics research. First, values regarding food are exclusively explained in terms of disease prevention. Health is therefore a state preceding a sum of possible diseases. Second, it is assumed that health should be explained as an interaction between food and genes. Health is minimised to quantifiable health risks and disease prevention through food-gene interactions. The third assumption is that disease prevention by minimisation of risks is in the hands of the individual and that personal risks, revealed either through tests or belonging to a risk group, will play a large role in disease prevention. Together, these assumptions suggest that the good life (a life worth living, with the means to flourish and thrive) is equated with a healthy life. Our thesis is that these three normative assumptions of nutrigenomics may strengthen the concerns related to healthism, health anxiety, time frames and individual responsibilities for health. We reflect on these ethical issues by confronting them in a thought experiment with alternative, philosophical, views of the good life.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Diet
  • Food Technology
  • Health Status*
  • Humans
  • Nutrigenomics / ethics
  • Nutrigenomics / standards*
  • Research Design
  • Risk