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INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

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NUTRIPERSO

Background

While infectious diseases have dramatically decreased and life expectancy has increased in many countries in recent decades, chronic diseases have sharply risen and account for 60 per cent of deaths worldwide (World Health Organization, 2010). Largely resulting from lifestyle evolution, up to 80 per cent of the incidences of heart disease, stroke and type 2 diabetes (T2D), and over one third of cancer cases could be prevented by reducing shared risk factors (WHO, 2010). According to the WHO report, if combined with actions reducing physical inactivity and tobacco use, the prevention of diet‐related risk factors could lead to an increase in average life expectancy by three to five years in high-income countries. Better prevention through more balanced diets could also contribute to improve the quality of the extra years of life, limit health expenditures related to population ageing and reduce health inequalities since there is clear evidence that the prevalence of chronic diseases is considerably higher among low-income groups.

In recognizing the importance of diet to public health, many governments and health authorities have implemented nutritional policies intended to reduce the incidence of chronic diseases. Most of these policies aim to better inform consumers about the health benefits induced by more balanced diets (Capacci et al., 2012). Based on nutritional and dietary recommendations designed for the average consumer, these policies mainly rely on generic information and awareness campaigns at national and community levels. Their impact is reported to be positive though limited (Traill et al., 2013; Capacci and Mazzochi, 2011; Shankar et al., 2013). In addition, it is likely that they increase health inequalities, since less educated individuals are less responsive to the provided information (INSERM, 2014). To overcome these limitations, public health experts are considering two types of actions. On the one hand, some interventions aim at modifying the market environment in order to facilitate healthier food choices, even by non-health-sensitive consumers (product labeling, tax policies, quality standards…). On the other hand, the effectiveness of information-based actions may be reinforced by targeting at-risk individuals and providing more personalized recommendations taking into account their particular preferences, and their social, economic, and health status.

In the last decade, several studies have been conducted on "personalized", "targeted" or “tailored” nutrition, and on the methods required to efficiently affect the food-related behavior of individuals and population groups. Initially, the concept of personalized nutrition focused on functional genetic variations, known to affect gene-nutrient metabolism. In recent times, a more encompassing definition has emerged (O’Donovan et al., 2016). The “personalized”, “targeted” or “tailored” nutrition awareness approach includes different characteristics and reference markers as tools to adapt dietary advice to specific population groups and individuals (Gibney et al., 2012). As described by Gibney and Walsh (2013), at a first level, the goal is to modulate dietary advice on the basis of the food and nutrient intake information of individuals. At a second level, tailored nutrition may also include phenotypic information on anthropometry and biochemical markers of nutritional status, thus providing adapted dietary advice to individuals or to groups of individuals sharing a common metabolic profile and a similar set of phenotypic features (Kaput 2008; Celis-Morales et al. 2015 and 2014). Lastly, in addition to diet and phenotype characteristics dietary, advice may also take into account specific genetic information (Lampe et al., 2013).

Overall, personalized nutrition relies on the assumption that by overcoming the "one-fits-all" approach, it is possible to produce more effective recommendations, as the impact of dietary recommendations on health dramatically varies according to inter‐individual differences in food behaviors and in phenotypic and genotypic characteristics. In addition, recommendations tailored to individuals may be easier to embrace by consumers than generic recommendations, and technological advances may play a key-role in collecting dietary data from consumers and providing them with personalized dietary recommendations (Harray et al., 2015; Dute et al., 2016; Stumbo, 2013), leading to cost‐effective interventions at an individual or group level.

These expectations have been partly confirmed by recent evidence suggesting that personalized nutrition may be effective. Several studies have found that tailored dietary advice is more effective than generic advice in changing dietary behaviors (Celis‐Morales et al. 2014; Ambeba et al. 2015). New technologies may be used to design efficient tailored dietary advice (Kerr et al., 2016; Burke at al., 2012; Stewart-Knox et al., 2015; Coughlin et al., 2015). In addition, consumers have been reported to be interested in personal dietary advice (Ronteltap et al., 2009; Livingston et al., 2016) with a willingness to pay for personal interventions (Roosen et al., 2008; Stewart-Knox et al., 2013; Fisher et al., 2016), provided that data confidentiality is preserved (Poinhos et al., 2014). Nevertheless, further investigation is required in order to (i) transpose generic dietary recommendations into tailored recommendations, (ii) determine under which conditions tailored nutrition can help individuals adopt long-lasting balanced diets, (iii) assess health benefits and the cost-effectiveness of such interventions, and (iv) determine to what extent tailored nutrition may affect social representations of food and health depending on social groups, and thus reinforce or curb social inequalities in health.