Errors in estimating usual sodium intake by the Kawasaki formula alter its relationship with mortality: implications for public health†
Bibliographic record
Abstract
Background: Several cohort studies with inaccurate estimates of sodium reported a J-shaped relationship with mortality. We compared various estimated sodium intakes with that measured by the gold-standard method of multiple non-consecutive 24-h urine collections and assessed their relationship with mortality. Methods: We analysed the Trials of Hypertension Prevention follow-up data. Sodium intake was assessed in four ways: (i) average measured (gold standard): mean of three to seven 24-h urinary sodium measurements during the trial periods; (ii) average estimated: mean of three to seven estimated 24-h urinary sodium excretions from sodium concentration of 24-h urine using the Kawasaki formula; (iii) first measured: 24-h urinary sodium measured at the beginning of each trial; (iv) first estimated: 24-h urinary sodium estimated from sodium concentration of the first 24-h urine using the Kawasaki formula. We included 2974 individuals aged 30-54 years with pre-hypertension, not assigned to sodium intervention. Results: During a median follow-up of 24 years, 272 deaths occurred. The average sodium intake measured by the gold-standard method was 3769 ± 1282 mg/d. The average estimated sodium over-estimated the intake by 1297 mg/d (95% confidence interval: 1267-1326). The average estimated value was systematically biased with over-estimation at lower levels and under-estimation at higher levels. The average measured sodium showed a linear relationship with mortality. The average estimated sodium appeared to show a J-shaped relationship with mortality. The first measured and the first estimated sodium both flattened the relationship. Conclusions: Accurately measured sodium intake showed a linear relationship with mortality. Inaccurately estimated sodium changed the relationship and could explain much of the paradoxical J-shaped findings reported in some cohort studies.
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 | 0.115 | 0.266 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".