Implausible results in human nutrition research

BMJ 2013; 347 doi: https://doi.org/10.1136/bmj.f6698 (Published 14 November 2013) Cite this as: BMJ 2013;347:f6698

Re: Implausible results in human nutrition research

The massive problem of implausible results is not limited to nutritional epidemiology [1]. It concerns the whole field of observational epidemiology [2].

One overlooked reason is that epidemiology has not yet moved beyond correlation. Indeed, our increasing ability to gather large amount of data and our growing confidence to conduct highly complex (multi-variable, multi-level, etc) analyses have let us think that we had solved issues of selection bias or of confounding in observational studies [3].

Having an explicit causal reasoning, notably thanks to recent developments in causal thinking [4, 5], may help observational epidemiology move beyond correlation.

1. Ioannidis JPA. Implausible results in human nutrition research. BMJ 2013; 347:f6698
2. Taubes G. Epidemiolgy faces its limits. Science 1995; 269:164-9.
3. Chiolero A. Big data in epidemiology: too big to fail? Epidemiology 2013; 24(6):938-9.
4. Hernán MA, Hernández-Díaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epidemiol 2002; 155(2):176-84.
5. Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med 2007; 26(1):20-36.

Competing interests: No competing interests

17 November 2013
Chiolero Arnaud
epidemiologist, senior lecturer
IUMSP, Lausanne University Hospital
1010 Lausanne, Switzerland