Food Sources of Sodium Intake in an Adult Mexican Population: A Sub-Analysis of the SALMEX Study
Bibliographic record
Abstract
Excessive dietary sodium intake increases blood pressure and cardiovascular risk. In Western diets, the majority of dietary sodium comes from packaged and prepared foods (≈75%); however, in Mexico there is no available data on the main food sources of dietary sodium. The main objective of this study was to identify and characterize the major food sources of dietary sodium in a sample of the Mexican Salt and Mexico (SALMEX) cohort. Adult male and female participants of the SALMEX study who provided a complete and valid three-day food record during the baseline visit were included. Overall, 950 participants (mean age 38.6 ± 10.7 years) were analyzed to determine the total sodium contributed by the main food sources of sodium identified. Mean daily sodium intake estimated by three-day food records and 24-h urinary sodium excretion was 2647.2 ± 976.9 mg/day and 3497.2 ± 1393.0, in the overall population, respectively. Processed meat was the main contributor to daily sodium intake, representing 8% of total sodium intake per capita as measured by three-day food records. When savory bread (8%) and sweet bakery goods (8%) were considered together as bread products, these were the major contributor to daily sodium intake, accounting for the 16% of total sodium intake, followed by processed meat (8%), natural cheeses (5%), and tacos (5%). These results highlight the need for public health policies focused on reducing the sodium content of processed food in Mexico.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".