Abstract
Background
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.
Methods
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.
Results
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.
Conclusions
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.
Plain Language Summary
Ultra-processed foods now make up a large part of young children’s diets and are linked to poorer physical and mental health. However, it remains unclear why some children consume more ultra-processed foods than others. Using data from over 2,400 Canadian preschoolers, we examined how family habits and neighbourhood environments together shape children’s ultra-processed food intake. We found that children ate more ultra-processed foods when their parents consumed more of these foods, when screen time was higher, and when families lived in areas with limited access to fresh food markets or longer travel times to work. Altogether, these findings show that early-life diet is shaped by both family and the environment children grow up in. Effective policies must therefore go beyond individual choices to improve food environments and support healthy childhood development.
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Data availability
Data described in the manuscript will be made available upon request pending approval from CHILD’s Access and Publication Committee and the CHILD Study National Coordinating Center. Researchers interested in collaborating on a project and accessing CHILD Cohort Study data should contact the Study’s National Coordinating Center (NCC) to discuss their needs before initiating a formal request. To contact the NCC, please email child@mcmaster.ca. A list of variables available in the CHILD Cohort Study is available at https://childstudy.ca/for-researchers/study-data/. More information about data access for the CHILD Cohort Study can be found at https://childstudy.ca/for-researchers/data-access/. Source data for figures are provided as Supplementary Data.
Code availability
The analytic code can be made available upon request.
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Acknowledgements
We would like to express gratitude to the research team at the CHILD Cohort Study, all participating families for making this article possible, and the Canadian Urban Environmental Health Research Consortium (CANUE) for enabling access to Employment metrics, indexed to DMTI Spatial Inc. This work was funded by CIHR Project Grant (#197857) and the University of Toronto CIHR Pathway Grant. The CHILD Cohort Study was funded by the Canadian Institutes of Health Research (CIHR) and the Allergy, Genes and Environment (AllerGen) Network of Centers of Excellence (NCE), GENOME CANADA. SS is supported by the European Union’s Horizon Europe Research and Innovation Programme under the Marie Sklodowska-Curie Post-doctoral Fellowship Grant Agreement (#101109136) (URBANE). MBA is supported by a Tier 2 Canada Research Chair in Early Nutrition and the Developmental Origins of Health and Disease. PJM is supported by Women’s and Children’s Health Research Institute. KM is supported by CIHR and Heart and Stroke. These entities had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
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K.M. designed and managed this project. The CHILD Study Founding team (P.S., T.J.M., P.J.M., and S.E.T.) conceived the CHILD cohort design, managed study recruitment and oversaw clinical assessments of study participants. S.M. and Z.H.C. mapped all food items into the NOVA groups. S.M. and Z.H.C. conducted all the statistical analyses. Z.L., S.S., and K.M. advised on the statistical approaches. J.R.B. conceived CANUE and facilitated data linkage to CHILD. S.M., Z.H.C., and K.M. interpreted the data and draughted the manuscript. All authors, S.M., Z.H.C., Z.L., S.S., M.R.L., M.B.A., P.J.M., T.J.M., P.S., S.E.T., J.R.B., and K.M. provided feedback and approved the final version. S.M. and Z.H.C. have full access to the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
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Mousavi, S., Chen, Z.H., Lu, Z. et al. Multilevel predictors of ultra-processed food intake in Canadian preschoolers. Commun Med (2026). https://doi.org/10.1038/s43856-026-01473-1
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DOI: https://doi.org/10.1038/s43856-026-01473-1
