Impact of urinary sodium excretion on the prevalence and incidence of metabolic syndrome: a population-based study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association of metabolic syndrome (MetS) risk with 24-hour urinary sodium excretion (24hUNaE) estimated from spot urine samples. DESIGN: Serial cross-sectional studies were conducted, and those with multiple repeated examinations were used to assess the MetS incidence risk. SETTING AND PARTICIPANTS: A health check-up programme was conducted between 2018 and 2021 and enrolled 59 292 participants to evaluate the relationship between MetS risk and 24hUNaE in the Third Xiangya Hospital, Changsha, China. Among these participants, 9550 had at least two physical examinations during this period, which were used to evaluate the association of a new occurrence of MetS with 24hUNaE. OUTCOMES: Guidelines for the prevention and treatment of dyslipidaemia in Chinese adults (revised in 2016) were used to define prevalent and incident MetS. RESULTS: The prevalence of MetS was 19.3% at the first check-up; among individuals aged ≤55 years, the risk was higher in men than women, while among older individuals, a similar prevalence was observed in both sexes. A significant increase in MetS prevalence was observed per unit increase in 24hUNaE (adjusted OR (AOR) 1.11; 95% CI 1.09 to 1.13), especially for the prevalence of central obesity and elevated blood pressure. Additionally, 27.4% of the participants among the 7842 participants without MetS at the first check-up (male vs female: 37.3% vs 12.9%) were found to have a new occurrence of MetS at the second, third and/or fourth check-ups. A 25% increase in MetS incidence was observed per unit increase in 24hUNaE (95% CI 1.19 to 1.32), which was more prominent in the participants with a new occurrence of central obesity and elevated fasting blood glucose. CONCLUSIONS: Although the prevalence of MetS seemed stable, new occurrences of MetS remained high, which might result in MetS recurrence. The influence of sodium intake on MetS development is probably attributed to the increase in blood pressure and central obesity, but a new occurrence of MetS may develop through elevated blood glucose and central obesity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".