Population-level interventions in government jurisdictions for dietary sodium reduction: a Cochrane Review
Bibliographic record
Abstract
Background: Worldwide, excessive salt consumption is common and is a leading cause of high blood pressure. Our objectives were to assess the overall and differential impact (by social and economic indicators) of population-level interventions for dietary sodium reduction in government jurisdictions worldwide. Methods: This is a Cochrane systematic review. We searched nine peer-reviewed databases, seven grey literature resources and contacted national programme leaders. We appraised studies using an adapted version of the Cochrane risk of bias tool. To assess impact, we computed the mean change in salt intake (g/day) from before to after intervention. Results: Fifteen initiatives met the inclusion criteria and 10 provided sufficient data for quantitative analysis of impact. Of these, five showed a mean decrease in salt intake from before to after intervention including: China, Finland (Kuopio area), France, Ireland and the UK. When the sample was constrained to the seven initiatives that were multicomponent and incorporated activities of a structural nature (e.g. procurement policy), most (4/7) showed a mean decrease in salt intake. A reduction in salt intake was more apparent among men than women. There was insufficient information to assess differential impact by other social and economic axes. Although many initiatives had methodological strengths, all scored as having a high risk of bias reflecting the observational design. Study heterogeneity was high, reflecting different contexts and initiative characteristics. Conclusions: Population-level dietary sodium reduction initiatives have the potential to reduce dietary salt intake, especially if they are multicomponent and incorporate intervention activities of a structural nature. It is important to consider data infrastructure to permit monitoring of these initiatives.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".