Precision nutrition: hype or hope for public health interventions to reduce obesity?

Int J Epidemiol. 2019 Apr 1;48(2):332-342. doi: 10.1093/ije/dyy274.

Abstract

High-income countries are experiencing an obesity epidemic that follows a socioeconomic gradient, affecting groups of lower socioeconomic status disproportionately. Recent clinical findings have suggested new perspectives for the prevention and treatment of obesity, using personalized dietary approaches. Precision nutrition (PN), also called personalized nutrition, has been developed to deliver more preventive and practical dietary advice than 'one-size-fits-all' guidelines. With interventions becoming increasingly plausible at a large scale thanks to artificial intelligence and smartphone applications, some have begun to view PN as a novel way to deliver the right dietary intervention to the right population. We argue that large-scale PN, if taken alone, might be of limited interest from a public health perspective. Building on Geoffrey Rose's theory regarding the differences in individual and population causes of disease, we show that large-scale PN can only address some individual causes of obesity (causes of cases). This individual-centred approach is likely to have a small impact on the distribution of obesity at a population level because it ignores the population causes of obesity (causes of incidence). The latter are embedded in the populations' social, cultural, economic and political contexts that make environments obesogenic. Additionally, the most socially privileged groups in the population are the most likely to respond to large-scale PN interventions. This could have the undesirable effect of widening social inequalities in obesity. We caution public health actors that interventions based only on large-scale PN are unlikely, despite current expectations, to improve dietary intake or reduce obesity at a population level.

Keywords: Precision nutrition; obesity; obesogenic environments; personalized nutrition; population interventions; social inequalities in health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Diet*
  • Health Promotion / methods*
  • Humans
  • Obesity / prevention & control*
  • Precision Medicine*
  • Public Health Practice*
  • Socioeconomic Factors