Multilevel predictors of ultra-processed food intake in Canadian preschoolers

Ultra-processed foods (UPF) dominate modern food systems and contribute significantly to early-life diets. However, the multilevel predictors of UPF consumption in early childhood, from family factors to neighbourhood environments, remain underexplored.

We leveraged data from a subset of the Canadian CHILD Cohort Study (n = 2,411), to assess UPF intake in three-years-old children using the NOVA classification system. A machine-learning variable selection algorithm and mixed-effect models identified independent predictors of UPF spanning family behaviours to neighbourhood environments.

Here we show parental factors including prenatal maternal UPF intake (β = 2.8 % daily energy from UPF, [95%CI 2.3,3.2]) and greater paternal adherence to a Western-like dietary pattern (β = 1.1, [95%CI 0.6,1.6]) are associated with higher UPF intake. Other factors such as shorter breastfeeding duration, longer daily screen time, and having older siblings are also associated with a higher proportion of daily energy intake from UPF at three years of age (all p-values < 0.05). In contrast, children residing in neighbourhoods with better access to employment opportunities (β = -1.9, [95%CI -3.0,-0.9]) and higher density of fresh food markets (β = -2.0, [95%CI -3.4,-0.5]) are associated with lower proportion of daily energy intake from UPFs.

These findings indicate that the early childhood UPF intake reflects the convergence of family behaviours and structural features of the built environment. Interventions to reduce UPF intake must go beyond individual food choice and address food systems design, including how the interrelated factors of daily time demands, travel distance requirements and public infrastructure constrain access to healthier options that shape children's diet.