Comparison of 24‐hour urine and 24‐hour diet recall for estimating dietary sodium intake in populations: A systematic review and meta‐analysis
Bibliographic record
Abstract
This systematic literature review and meta-analysis examined whether 24-hour diet recall is a valid way to measure mean population sodium intake compared with the gold standard 24-hour urinary assessment. The authors searched electronic databases MEDLINE, Embase, and Scopus using pre-defined terms. Studies were eligible for inclusion if they assessed adult humans in free-living settings, and if they included group means for 24-hour diet recall and 24-hour urinary collection of sodium intake in the same participants. Studies that included populations with an active disease state that might interfere with normal sodium metabolism were excluded. Results of 28 studies are included in the meta-analysis. Overall, 24-hour diet recall underestimated population mean sodium intake by an average of 607 mg per day compared to the 24-hour urine collection. The difference between measures from 24-hour urine and 24-hour diet recall was smaller in studies conducted in high-income countries, in studies where multiple-pass methods of 24-hour diet recall were reported and where urine was validated for completeness. Higher quality studies also reported smaller differences between measures than lower quality studies. Monitoring of population sodium intake with 24-hour urinary excretion remains the most accurate method of assessment. Twenty-four-hour diet recall tends to underestimate intake, although high-quality 24-hour diet recall improves accuracy, and may be used if 24-hour urine is not feasible.
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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 | 0.022 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.044 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".