Individuals may perceive personalized dietary advice as more relevant and motivational than national guidelines. Personal preference and food cost are factors that can affect consumer decisions. The objective of this study was to present a method for modelling and analysing the trade-off between deviation from preference and food cost for optimized personalized dietary recommendations. Quadratic programming was applied to minimize deviation from fish preference and cost simultaneously with different weights on the cost for 3,016 Danish adults (whose dietary intake and body weight were recorded in a national dietary survey). Model constraints included recommendations for eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and vitamin D and tolerable levels for methyl mercury, dioxins, and polychlorinated biphenyls (dl-PCBs). When only minimizing deviation from preference, 50% of the study population should be recommended to increase fish intake, 48% should be suggested to maintain current consumption, and 2%, should be suggested to decrease fish consumption. When only minimizing cost, the vast majority (99%) should be recommended to only consume herring, which is the least-expensive fish species. By minimizing deviation from preference and cost simultaneously with different weights on the cost, personalized optimal trade-off curves between deviation from fish intake preference and fish cost could be generated for each individual in our study population, except for 22 individuals (0.7%) whose contaminant background exposure was too high. In the future, the method of this paper could be applied in the personal communication of healthy and safe food recommendations that fit the preferences of individual consumers.
- optimal trade-off curve
- personal food preference
- personalized intake recommendations
- quadratic programming