Abstract P221: Intake of Ultra-Processed Foods in Relation to Cardiovascular Disease Incidence in US Men and Women With Diabetes Mellitus
Bibliographic record
Abstract
Introduction: Recent evidence suggests that intake of ultra-processed foods (UPF) is related to unfavorable cardio-metabolic risk profiles among generally healthy populations. However, evidence on the relationship between UPF intake and cardiovascular disease (CVD) among patients with type 2 diabetes (T2D) is lacking. Hypothesis: We assessed the hypothesis that higher intake of dietary UPF is associated with higher risks of CVD among individuals with T2D. Methods: We prospectively followed 13,272 men and women participating in the Health Professionals Follow-Up Study (HPFS) and Nurses’ Health Study (NHS) with T2D at baseline and during follow-up (HPFS: 1986-2018; NHS: 1980-2014). Diet was repeatedly assessed using validated food frequency questionnaires every 2-4 years. UPF were categorized according to the Nova classification. CVD was defined as fatal and non-fatal coronary heart disease (CHD) (including nonfatal myocardial infarction, coronary artery bypass graft surgery, and coronary angioplasty and stent) and fatal and non-fatal stroke. Associations of UPF consumption with risks of CVD were assessed using Cox regression. Results: During 165,761 person-years of follow-up, 1,826 total CHD and 529 total stroke were identified and confirmed. After adjusting for demographics, lifestyle, medical history, dietary factors, and diabetes medication use, higher total intake of UPF was associated with higher risk of CHD. The multivariable-adjusted HRs (95% CIs) were 1.20 (1.02, 1.43) ( P trend = 0.03) when comparing the highest and lowest quintiles (Q5 vs. Q1) or 1.03 (1.01, 1.04) for each 1 serving/day increment of UPF. No association between UPF intake and risk of stroke was observed (Q5 vs. Q1: 0.92 (0.67, 1.24)). These results were consistent across subgroups in analyses stratified by age, sex, BMI, diet quality, physical activity, smoking, diabetes medication use, or diabetes duration. In addition, compared with participants who had a stable or decreased consumption of UPF (≤0 change in UPF) from pre- to post-diabetes diagnosis, participants who increased consumption of UPF (>0 increment of UPF intake) after diabetes diagnosis had a 15% (1%, 31%) higher risk of CHD. Conclusions: Among participants with T2D, higher dietary UPF consumption was associated with a higher risk of CHD, but not stroke. These results provide further support for the current recommendations to limit UPF consumption for the prevention of CHD among patients with diabetes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".