Association of drinking water salinity with elevated blood pressure and risk of hypertension among coastal and other populations: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
BACKGROUND: The link between drinking water salinity and increased blood pressure and hypertension risk among coastal and other populations remains unclear. To investigate this, we performed a systematic review and meta-analysis of observational studies on drinking water salinity and cardiovascular outcomes. METHODS: We systematically searched MEDLINE, Embase and Web of Science for relevant studies published until 10 May 2025. Observational studies reporting on the association between sodium in drinking water and systolic/diastolic blood pressure (SBP/DBP), hypertension, coronary heart disease (CHD), stroke and composite cardiovascular outcomes were prespecified to be included. We assessed study quality using the Newcastle-Ottawa Scale and performed random effects meta-analysis. RESULTS: We identified 27 observational studies (involving 74 063 unique participants from 7 countries), 15 of which included coastal populations. Comparing higher versus lower drinking water salinity, the mean differences were 3.22 mm Hg (95% CI 1.11 to 5.33) for SBP and 2.82 mm Hg (95% CI 1.44 to 4.20) for DBP. The pooled OR for hypertension, comparing higher versus lower water salinity, was 1.26 (95% CI 1.07 to 1.48). These associations were generally consistent across subgroups but were statistically significant for studies conducted in coastal populations and for those published after 2000. However, we found an insufficient number of studies with reliable data on CHD or stroke outcomes. CONCLUSIONS: Higher drinking water salinity is associated with an elevated risk of blood pressure and hypertension, especially among coastal populations. More research is needed to examine connections with CHD and stroke, and to create strategies to counter salinity's effects, particularly in climate-vulnerable coastal areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".