Added Sugar, Sugar-Sweetened Beverages, and Artificially Sweetened Beverages and Risk of Cardiovascular Disease: Findings from the Women’s Health Initiative and a Network Meta-Analysis of Prospective Studies
Bibliographic record
Abstract
Much remains unknown about the role of added sugar in relation to cardiovascular disease (CVD) and the relative contributions of sugar-sweetened beverages (SSB) or artificially sweetened beverages (ASB) to CVD risk. Among the 109,034 women who participated in Women's Health Initiative, we assessed average intakes of added sugar, SSB and ASB, and conducted Cox regression to estimate the hazard ratios (HRs) and their 95% confidence intervals for CVD risk. The consistency of findings was compared to a network meta-analysis of all available cohorts. During an average of 17.4 years of follow-up, 11,597 cases of total CVD (nonfatal myocardial infarction, coronary heart disease (CHD) death, stroke, coronary revascularization, and/or incident heart failure) were confirmed. Added sugar as % energy intake daily (%EAS) at ≥15.0% was positively associated with total CVD (HR = 1.08 [1.01, 1.15]) and CHD (HR = 1.20 [1.09, 1.32]). There was also a higher risk of total CVD associated with ≥1 serving of SSB intake per day (HR = 1.29 [1.17, 1.42]), CHD (1.35 [1.16, 1.57]), and total stroke (1.30 [1.10, 1.53]). Similarly, ASB intake was associated with an increased risk of CVD (1.14 [1.03, 1.26]) and stroke (1.24 [1.04, 1.48]). According to the network meta-analysis, there was a large amount of heterogeneity across studies, showing no consistent pattern implicating added sugar, ASB, or SSB in CVD outcomes. A diet containing %EAS ≥15.0% and consuming ≥1 serving of SSB or ASB may be associated with a higher CVD incidence. The relative contribution of added sugar, SSB, and ASB to CVD risk warrants further investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".