0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessIntroduction: There is limited evidence on the association between long-term consumption of ultra-processed foods (UPF) and the risk of type 2 diabetes (T2D), among the U.S population. The overall strength of this association has also not been established. Hypothesis: Higher intake of UPF is associated with a higher risk of T2D in U.S. adults. The pooled risk estimates from published literature reinforce the positive relationship between the UPF intakes and T2D. Methods: We first assessed this relationship among 71,871 women from the Nurses’ Health Study (NHS, 1984-2016), 87,918 women from NHSII (1991-2017), and 38,847 men from the Health Professionals Follow-up Study (HPFS, 1986-2016) who were all free of T2D at baseline. Diet was assessed using food frequency questionnaires, every 2-4 years. UPF were categorized according to the Nova classification. Information on incident cases of T2D was obtained through follow-up questionnaires every 2 years. The association between UPF intake and incident T2D was examined using Cox proportional hazards models. Second, after conducting a systematic review of prospective cohort studies, risk estimates from all included cohorts were pooled in a random-effects, dose-response, meta-analysis to assess nonlinearity of the association between total UPF intake and T2D risk. Finally, the strength of the meta-evidence was assessed using NutriGrade. Results: During 5,187,678 person-years of follow-up across the three cohorts, 19,503 T2D cases were documented. The pooled multivariable-adjusted hazard ratios (HRs) for T2D between the extreme quintiles of total UPF intake (% of grams/day), was 1.36 (95% confidence interval (CI): 1.29, 1.44; P trend <0.0001). This relationship was driven by intakes of ultra-processed animal-based products, ready-to-eat mixed dishes and artificially- and sugar-sweetened beverages. Ultra-processed cereals and ultra-processed dark breads and whole-grain breads were inversely associated with T2D risk. In the meta-analysis (7 risk estimates, 415,554 participants and 21,932 T2D cases), a significant positive dose-response association between total UPF intake and T2D was observed (P=0.90 for non-linearity): a 10% increase in total UPF intake (% grams from UPF/day) was associated with a 10% higher risk of T2D (95%CI: 8%, 12%; I 2 =23.1%; P heterogeneity =0.25). Per NutriGrade, the evidence supporting the positive relationship between total UPF intake and T2D was of high quality. Conclusions: High quality evidence shows that total UPF consumption is associated with higher risk of T2D, although not all individual foods classified as ultra-processed were associated with a higher risk in these U.S. cohorts.
Zhangling Chen, Neha Khandpur, Clémence Desjardins, Carlos Augusto Monteiro, Sinara Laurini Rossato, Teresa T. Fung, JoAnn E. Manson, Walter C. Willett, Eric B. Rimm, Frank B Hu, Qi Sun, Jean‐Philippe Drouin‐Chartier (2023). Abstract MP56: Intake of Ultra-Processed Foods is Associated With an Increase in Risk for Type Two Diabetes: Results From Three U.S. Cohort Studies and a Meta-Analysis. , 147(Suppl_1), DOI: https://doi.org/10.1161/circ.147.suppl_1.mp56.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
12
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1161/circ.147.suppl_1.mp56
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access