Identifying the patterns of ultra-processed food consumption and their characteristics in the UK adults using the UK National Diet and Nutritional Surveys 2008/09 to 2018/19.

Objective: To identify the dietary patterns of ultra-processed food (UPF) consumption in the UK adults, and to explore their nutritional characteristics and associated demographic and socioeconomic factors.

Design: UPF-based dietary patterns were identified using weighted principal component analysis and k-means cluster analysis on UPFs intakes (identified using Nova classification) from the cross-sectional NDNS data (2008-2019). Weighted multivariable logistic regression models were employed to identify the demographic and socioeconomic factors associated with the patterns.

Setting: United Kingdom.

Participants: 8,347 adults (≥ 18y).

Results: UPFs accounted for 54% of total energy intake in the UK adult diet. Three distinct UPF-clusters were identified, labelled as "Sweet Foods," "Fast Foods," and "Traditional Foods" based on their predominant food intakes. Older participants (>68 years) were more likely to adhere to the "Sweet Foods" pattern (OR: 2.39; 95% CI: 1.99-2.87) and less likely to be part of the "Fast Foods" pattern (OR: 0.47; 95% CI: 0.40-0.55) compared to younger individuals (< 29). Participants in lower occupations were less likely to adhere to the "Fast Foods" pattern than participants in the higher occupations (OR: 0.82; 95% CI: 0.72-0.94) while being more likely to adhere to the "Traditional Foods" pattern (OR: 1.23; 95% CI: 1.06-1.43).

Conclusions: The UK diet was dominated by UPF products. Our analysis identified three distinct UPF dietary patterns with varying nutritional quality, influenced by key demographic and social factors. These findings provide valuable insights into the determinants of UPF consumption and highlight which population groups are more likely to consume certain types of UPFs.