Salt Reduction Initiatives around the World – A Systematic Review of Progress towards the Global Target
Bibliographic record
Abstract
OBJECTIVE: To quantify progress with the initiation of salt reduction strategies around the world in the context of the global target to reduce population salt intake by 30% by 2025. METHODS: A systematic review of the published and grey literature was supplemented by questionnaires sent to country program leaders. Core characteristics of strategies were extracted and categorised according to a pre-defined framework. RESULTS: A total of 75 countries now have a national salt reduction strategy, more than double the number reported in a similar review done in 2010. The majority of programs are multifaceted and include industry engagement to reformulate products (n = 61), establishment of sodium content targets for foods (39), consumer education (71), front-of-pack labelling schemes (31), taxation on high-salt foods (3) and interventions in public institutions (54). Legislative action related to salt reduction such as mandatory targets, front of pack labelling, food procurement policies and taxation have been implemented in 33 countries. 12 countries have reported reductions in population salt intake, 19 reduced salt content in foods and 6 improvements in consumer knowledge, attitudes or behaviours relating to salt. CONCLUSION: The large and increasing number of countries with salt reduction strategies in place is encouraging although activity remains limited in low- and middle-income regions. The absence of a consistent approach to implementation highlights uncertainty about the elements most important to success. Rigorous evaluation of ongoing programs and initiation of salt reduction programs, particularly in low- and middle- income countries, will be vital to achieving the targeted 30% reduction in salt intake.
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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 | 0.033 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| 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".