Progress on sodium reduction in South Korea
Bibliographic record
Abstract
INTRODUCTION: 4000 mg/day, twice the recommended upper limit. METHODS: In 2012, South Korea implemented its National Plan to Reduce Sodium Intake, with a goal of reducing population sodium consumption by 20%, to 3900 mg/day, by 2020. The plan included five key components: (1) a consumer awareness campaign designed to change food consumption behaviours; (2) increased availability of low-sodium foods at schools and worksites; (3) increased availability of low-sodium meals in restaurants; (4) voluntary reformulation of processed foods to lower sodium content; and (5) development of low-sodium recipes for food prepared at home. Monitoring and evaluation included tracking sodium intake and sources of dietary sodium using the Korea National Health and Nutrition Examination Survey. RESULTS: By 2014, South Korea had reduced dietary sodium consumption among adults by 23.7% compared to a survey conducted in 2010 prior to implementation of a nationwide salt reduction campaign that used this comprehensive, multipronged approach. The reductions in sodium intake were accompanied by reductions in population blood pressure and hypertension prevalence. Although causal associations between the sodium reduction programme and reduced sodium intake cannot be made, the declines occurred with the introduction of the programme. CONCLUSION: Multicomponent interventions have great potential to reduce population sodium intake. Lessons learnt from South Korea could be applied to other countries and are likely very relevant to other Asian countries with similar food sources and consumption profiles.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".