Addressing Challenges with the Categorization of Foods Processed at Home: A Pilot Methodology to Inform Consumer-Facing Guidance

Abstract

The objective of this study was to inform consumer-facing dietary guidance by (1) adapting the current University of North Carolina at Chapel Hill (UNC) food processing framework to include a home processing (HP) component and (2) pilot testing the adapted version using a nationally representative sample of foods consumed in the U.S. The UNC framework was adapted to include guidelines for categorizing home-prepared (HP) foods. The original UNC and adapted HP frameworks were used to code dietary recalls from a random sample of National Health and Nutrition Examination Survey (2015–2016 cycle) participants (n = 100; ages 2–80 years). Percent changes between the UNC and HP adapted frameworks for each processing category were calculated using Microsoft Excel, version 16.23. Participants were 56% female, 35% non-Hispanic white (mean age = 31.3 ± 23.8). There were 1,376 foods with 651 unique foods reported. Using the HP compared to the UNC framework, unprocessed/minimally processed foods declined by 11.7% (UNC: 31.0% vs. HP: 27.4%); basic processed foods increased by 116.8% (UNC: 8.2% vs. HP: 17.8%); moderately processed foods increased by 16.3% (UNC: 14.2% vs. HP: 16.6%); and highly processed foods decreased by 17.8% (UNC: 46.5% vs. HP: 38.2%). Home-prepared foods should be considered as distinct from industrially produced foods when coding dietary data by processing category. This has implications for consumer-facing dietary guidance that incorporates processing level as an indicator of diet quality.

Keywords

• dietary guidance
• food processing
• food classification systems
• processing
• ultra-processed
• NOVA