Comparing Three Approaches to Salt Intake Assessment Among Lactating Women in Rural Cambodia
Bibliographic record
Abstract
Monitoring population salt intake is a critical component of implementing salt fortification programs. In Cambodia, salt is being considered as a vehicle for thiamine fortification to prevent infantile beriberi among breastfed infants. However, salt intake among lactating mothers is not known. The gold standard for assessing sodium intake is repeat 24-hr urinary sodium concentrations. This method has logistical barriers, especially in low-resource settings, and other methods have not been trialed in this population. Here we compare three methods of assessing salt intake in lactating Cambodian women: repeat 24-hr urinary sodium concentrations (USC), repeat 12-hr observed weighed intake records (OWIR), and household salt disappearance (HSD). Data from trial: NCT03616288. Salt intake was assessed using the three methods in a subsample of lactating women (n = 104) between 8 and 22 weeks postpartum. Women were asked to collect two 24-hour urine samples within 7 days. Repeat 12-hr OWIR were collected from women. Household salt disappearance was recorded fortnightly, and was divided by the number of household members to estimate individual intakes. Descriptive household salt use was also recorded. Differences in estimated salt intake from each method were compared using a Kruskal-Wallis test. Mean (95%CI) estimated salt intakes from repeat 24-hr USC, repeat 12-hr OWIR, and HSD were: 9.0 (8.3, 9.8) g/day, 9.1 (7.9, 10.3) g/day, and 10.9 (9.8, 11.9) g/day, respectively. Estimated intakes from HSD were significantly higher than both 24-hr USC (p = 0.009) and 12-hr OWIR (p = 0.002). Estimated intakes from 24-hr USC and 12-hr OWIR were not statistically different (p = 0.6). Salt was being used for purposes other than consumption, such as cleaning fish and vegetables, in 26% of fortnightly visits. Repeat 24-hr USC and 12-hr OWIR are both acceptable and logistically feasible methods of salt intake assessment among lactating women in rural Cambodia. While HSD is a less resource-intensive approach, this method over-estimated salt intake. Salt being used for purposes other than consumption may contribute to over-estimation using this method. Bill & Melinda Gates Foundation, New York Academy of Sciences, Canadian Institutes of Health Research, Research Nova Scotia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".