Dietary sources of salt intake in adults and older people: a population-based study in a Brazilian town
Bibliographic record
Abstract
OBJECTIVE: To assess salt intake and its dietary sources using biochemical and self-report methods and to characterize salt intake according to sociodemographic and disease-related variables in a sample of the Brazilian population. DESIGN: Population-based cross-sectional survey. SETTING: Salt intake was assessed by biochemical (24 h urinary Na excretion) and self-report methods (sodium FFQ, 24 h dietary recall, seasoned-salt questionnaire, discretionary-salt questionnaire and total reported salt intake).ParticipantsAdults and older people (n 517) aged 20-80 years, living in Artur Nogueira, São Paulo, Brazil. RESULTS: Mean salt intake based on 24 h urinary Na excretion and total reported salt intake was 10·5 and 11·0 g/d, respectively; both measures were significantly correlated. Discretionary salt and seasoned salt were the most important sources of salt intake (68·2 %). Men in the study consumed more salt than women as estimated by 24 h urinary Na excretion (11·7 v. 9·6 g salt/d; P<0·0001). Participants known to be hypertensive added more salt to their meals but consumed less salty ultra-processed foods. Waist circumference in both sexes and BMI were positively correlated with salt intake estimated by 24 h urinary Na excretion. In addition, regression analysis revealed that being a young male or having a high waist circumference was a predictor of higher salt intake. CONCLUSIONS: Salt intake in this population was well above the recommended amount. The main source of salt intake came from salt added during cooking. Salt intake varied according to sex and waist circumference.
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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 | 0.001 |
| 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 | 0.000 |
| 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".