Nutrient clustering, NOVA classification, and nutrient profiling: How do they overlap, and what do they predict about food palatability?

We compared the performance of three food categorisation metrics in predicting palatability (taste pleasantness) using a dataset of 52 foods, each rated virtually (online) by 72-224 participants familiar with the foods in question, as described in Appetite 193 (2024) 107124. The metrics were nutrient clustering, NOVA, and nutrient profiling. The first two of these metrics were developed to identify, respectively: 'hyper-palatable' foods (HPFs); and ultra-processed foods (UPFs), which are claimed to be 'made to be hyper-palatable'.

Evidence that carbohydrate-to-fat ratio and taste, but not energy density or NOVA level of processing, are determinants of food liking and food reward.

This virtual (online) study tested the common but largely untested assumptions that food energy density, level of processing (NOVA categories), and carbohydrate-to-fat (CF) ratio are key determinants of food reward. Individual participants (224 women and men, mean age 35 y, 53% with healthy weight, 43% with overweight or obesity) were randomised to one of three, within-subjects, study arms: energy density (32 foods), or level of processing (24 foods), or CF ratio (24 foods). They rated the foods for taste pleasantness (liking), desire to eat (food reward), and sweetness, saltiness, and flavour intensity (for analysis averaged as taste intensity).

Consumers' attitudes towards alternatives to conventional meat products: Expectations about taste and satisfaction, and the role of disgust.

The livestock sector has environmental, health, and animal welfare impacts. This UK-based, quantitative study aimed to elucidate consumers' valuation of alternatives to conventional meat products. In an online study, 151 meat eaters and 44 non-meat eaters were shown pictures of meat, dairy, and bakery products, including beef burger, cheese sandwich and blueberry muffin.