Static in vitro digestion model adapted to the general older adult population: an INFOGEST international consensus | Static in vitro digestion model adapted to the general older adult population: an INFOGEST international consensus

Understanding the mechanisms of food digestion is of paramount importance to determine the effect foods have on human health. Significant knowledge on the fate of food during digestion has been generated in healthy adults due to the development of physiologically-relevant in vitro digestion models. However, it appears that the performance of the oro-gastrointestinal tract is affected by ageing and that a model simulating the digestive conditions found in a younger adult (<65 years) is not relevant for an older adult (>65 years). The objectives of the present paper were: (1) to conduct an exhaustive literature search to find data on the physiological parameters of the older adult oro-gastrointestinal tract, (2) to define the parameters of an in vitro digestion model adapted to the older adult. International experts have discussed all the parameters during a dedicated workshop organized within the INFOGEST network. Data on food bolus properties collected in the older adult were gathered, including food particle size found in older adult boluses. In the stomach and small intestine, data suggest that significant physiological changes are observed between younger and older adults. In the latter, the rate of gastric emptying is slowed down, the pH of the stomach content is higher, the amount of secretions and thus the hydrolytic activities of gastric and intestinal digestive enzymes are reduced and the concentration of bile salts lower. The consensus in vitro digestion model of the older adult proposed here will allow significant progress to be made in understanding the fate of food in this specific population, facilitating the development of foods adapted to their nutritional needs. Nevertheless, better foundational data when available and further refinement of the parameters will be needed to implement the proposed model in the future.

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