Unlocking Healthy Food Preferences of Older Adults: A Fuzzy Clustering Approach

Population aging is a global phenomenon with significant social and economic implications, making healthy eating crucial for maintaining physical and mental health. This study investigates the factors influencing healthy food choices of a sample of 334 Italian older adults by considering cognitive, informative and emotional factors into established theoretical frameworks. Regression analysis and fuzzy clustering were employed to understand the antecedents of healthy food choices and to identify distinct sub-groups of older adults. Three clusters were identified. The Light-healthy group would benefit from efforts to improve the taste and accessibility of healthy foods, while the Health-conscious segment would be more influenced by information emphasising the functional benefits of a healthy diet. Finally, the Unhealthy group requires targeted educational efforts to improve their overall knowledge and trust in healthy food. Implications emerge, especially for companies aimed at fostering healthy eating habits and well-being among this population.