(OR21-03-25) Ultra-Processed Foods Are Not All Alike: A Novel, Objective Approach to Differentiate Among Processed Foods Including Those Classified As NOVA 4

Objectives: Develop the WISEcode UPF™ (Wc-UPF), a data driven nuanced and objective approach to distinguish among all processed foods. Compare Wc-UPF to NOVA, particularly NOVA 4/ultra-processed, across the dataset and within select grocery categories.

Methods: A database of 100,243 commercial foods (5,041 ingredients) was used. The Wc-UPF score was based on three components (higher = more processed): i) number of processed ingredients, weighted based on processing and health risks; ii) percent energy from added sugars; iii) a penalty for ingredients with significant health concerns. All foods were also classified per NOVA criteria. Also, the distribution of foods based on NOVA classification and Wc-UPF levels were compared in 7 (of the 138) Doordash™ grocery categories (bagels, condiments, dressing, easy heat, ice cream, tortillas & wraps, yogurts), a total of 9,545 foods.

Results: Of the 100,243 commercial foods, 3.3% were classified as NOVA 1, 0.3% as NOVA 2, 1.3% as NOVA 3, and 95.1% as NOVA 4. Five levels emerged from the raw Wc-UPF scores: minimal (0–3), light (4–6), moderate (7–10), ultra (11–15), super-ultra ( >15). Combining ultra and super-ultra captured what are commonly referred to as ultra-processed foods. The distribution across the 5 Wc-UPF levels from minimal to super-ultra was somewhat uniform, at 19.6%, 15.6%, 22.5%, 19.7% and 22.6% respectively. Additionally, Wc-UPF scores pointed to a range of processing levels within NOVA 4 ultra-processed: combining ultra and super-ultra levels captured 44.7% of the foods, with minimal, light and moderate levels being 15.7%, 16.4% and 23.2% respectively. Of the 9,545 foods in the 7 Doordash™ grocery categories assessed, all but 18 foods were classified as NOVA 4. However, Wc-UPF levels varied widely between food categories, yogurt having the fewest ultra and super-ultra foods (12.4% of 1,810 products) while ice cream had the highest (71.3% of 4,037 products).

Conclusions: Wc-UPF and the dataset underpinning its development offer a high resolution approach that differentiates among ultra-processed foods, likely having important implications for health. This tool can support research into the health impact of processed foods, assist in product development, and help regulators establish evidence-based policies.

Funding Sources: WISEcode, LLC funded all work.