Sweetened beverages and cardiovascular outcomes: an umbrella review of mortality and health outcomes
Bibliographic record
Abstract
BACKGROUND: The increasing intake of sugar-sweetened (SSBs) and artificially sweetened beverages (ASBs) raises concerns over their potential impact on cardiovascular health. This umbrella meta-analysis examines their association with cardiovascular outcomes, synthesizing existing evidence comprehensively. METHODS: A systematic search was conducted across PubMed, Scopus, Web of Science, and Google Scholar databases, covering studies published up to November 2024. Eligible meta-analyses were synthesized using a random-effects model to calculate pooled effect sizes and 95% confidence intervals. Subgroup and sensitivity analyses were performed, and the methodological quality of studies was evaluated using AMSTAR 2 tools. RESULTS: Nineteen meta-analyses encompassing 67 datasets met the inclusion criteria. ASB consumption was associated with a 10% increased risk of mortality (RR: 1.10; 95% CI: 1.07 to 1.12), including an 8% increased risk of cardiovascular disease (CVD) mortality (RR: 1.08; 95% CI: 1.05 to 1.11). SSB intake was linked to a 9% higher overall mortality risk (RR: 1.09; 95% CI: 1.07 to 1.11) and a 10% increased CVD mortality risk (RR: 1.10; 95% CI: 1.07 to 1.13). Additional cardiovascular risks associated with both beverages included hypertension (RR range: 1.12-1.19), coronary heart disease (RR range: 1.09-1.20), metabolic syndrome (RR range: 1.19-1.31), and stroke (RR range: 1.06-1.25). CONCLUSION: The results underscore a clear link between the intake of sweetened beverages and elevated risks of mortality and major cardiovascular outcomes, suggesting an urgent need to reduce their consumption as part of public health initiatives. Targeted strategies, including consumer education and policy interventions, may help mitigate these risks and improve cardiovascular health outcomes.
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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 | 0.017 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".