The obesity epidemic is still one of the greatest challenges in Public Health. Its complex aetiology hampers identification of determinants beyond the classical model of energy balance. The “chemical obesogenic” and “metabolic disruptor” hypotheses support an important role of xenobiotic chemicals on obesity and metabolic diseases, particularly those provided by food. Specifically, food additives and contaminants from food processing and packaging are of particular interest due to the increased exposure in the last decades. These chemicals can act as obesogens/metabolic disruptors by; dysregulation of the endocrine function, alteration of the hormonal control of appetite and satiety, shifting energy balance and basal metabolic rate, influencing adipocytes function, and/or glucose-insulin metabolism. Additionally, by influencing insulin resistance and inflammatory processes, these compounds may also exert an effect on cognitive function.
Previous studies were performed mainly in vitro or in animal models, and few were developed in human population sets using longitudinal approaches. One of the methodological challenges in this area of research is to assess exposure to these food chemicals in large epidemiologic studies. The use of detailed individual food consumption data description, according to European standards, and the development of predictive models of assessment could partly solve these constraints.
This project will allow to describe the exposure to these contaminants using previously collected information of dietary intake from a representative sample of the Portuguese population (the national nutrition and physical activity survey, IAN-AF 2015-2016) and to develop predictive statistical models to improve estimation of exposure by additionally using biomarkers of exposure in urinary samples. Also, it intends to increase knowledge on the influence of these chemicals on adiposity and cognitive function from childhood to adolescence, trying to understand common metabolic pathways, using a longitudinal approach with data from a population-based birth cohort – Generation XXI.
Objectives achievement is assured by sustained background knowledge of researchers from areas of nutrition, psychology, food toxicology and mathematics, and by their large experience in methodological aspects of dietary assessment and on conducting cohort studies. This project benefits from early work of the team that developed a software for dietary assessment (eAT24) which integrates the food classification and description system FoodEx2 and an extensive food composition data which allows for better exposure assessment. Also, using longitudinal data and the use of complex statistical models are strengths for obtaining better evidence for developing public policies to reduce exposure to adverse food compounds and to support the definition of risk management actions.
Funding approved by the Competitiveness and Internationalization Operational Program in its FEDER component, by the Foundation for Science and Technology, I.P.
