Salt Intakes, Knowledge, and Behavior in Samoa: Monitoring Salt‐Consumption Patterns Through the World Health Organization's Surveillance of Noncommunicable Disease Risk Factors (<scp>STEPS</scp>)
Bibliographic record
Abstract
This project measured population salt intake in Samoa by integrating urinary sodium analysis into the World Health Organization's (WHO's) STEPwise approach to surveillance of noncommunicable disease risk factors (STEPS). A subsample of the Samoan Ministry of Health's 2013 STEPS Survey collected 24-hour and spot urine samples and completed questions on salt-related behaviors. Complete urine samples were available for 293 participants. Overall, weighted mean population 24-hour urine excretion of salt was 7.09 g (standard error 0.19) to 7.63 g (standard error 0.27) for men and 6.39 g (standard error 0.14) for women (P=.0014). Salt intake increased with body mass index (P=.0004), and people who added salt at the table had 1.5 g higher salt intakes than those who did not add salt (P=.0422). A total of 70% of the population had urinary excretion values above the 5 g/d cutoff recommended by the WHO. A reduction of 30% (2 g) would reduce average population salt intake to 5 g/d, in line with WHO recommendations. While challenging, integration of salt monitoring into STEPS provides clear logistical and cost benefits and the lessons communicated here can help inform future programs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".