Dietary Sodium Intake and Risk of Cardiovascular Disease: A Systematic Review and Dose-Response Meta-Analysis
Bibliographic record
Abstract
Dietary sodium intake has received considerable attention as a potential risk factor of cardiovascular disease. However, evidence on the dose-response association between dietary sodium intake and cardiovascular disease risk is unclear. Embase and PubMed were searched from their inception to 17 August 2020 and studies that examined the association between sodium intake and cardiovascular disease in adolescents were not included in this review. We conducted a meta-analysis to estimate the effect of high sodium intake using a random effects model. The Newcastle-Ottawa Scale assessment was performed. A random-effects dose-response model was used to estimate the linear and nonlinear dose-response relationships. Subgroup analyses and meta-regression were conducted to explain the observed heterogeneity. We identified 36 reports, which included a total of 616,905 participants, and 20 of these reports were also used for a dose-response meta-analysis. Compared with individuals with low sodium intake, individuals with high sodium intake had a higher adjusted risk of cardiovascular disease (Rate ratio: 1.19, 95% confidence intervals = 1.08-1.30). Our findings suggest that there is a significant linear relationship between dietary sodium intake and cardiovascular disease risk. The risk of cardiovascular disease increased up to 6% for every 1 g increase in dietary sodium intake. A low-sodium diet should be encouraged and education regarding reduced sodium intake should be provided.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".