A dose-response meta-analysis of chronic arsenic exposure and incident cardiovascular disease
Bibliographic record
Abstract
Consistent evidence at high levels of water arsenic (≥100 µg/l), and growing evidence at low-moderate levels (<100 µg/l), support a link with cardiovascular disease (CVD). The shape of the dose-response across low-moderate and high levels of arsenic in drinking water is uncertain and critical for risk assessment.We conducted a systematic review of general population epidemiological studies of arsenic and incident clinical CVD (all CVD, coronary heart disease (CHD) and stroke) with three or more exposure categories. In a dose-response meta-analysis, we estimated the pooled association between log-transformed water arsenic (log-linear) and restricted cubic splines of log-transformed water arsenic (non-linear) and the relative risk of each CVD endpoint.Twelve studies (pooled N = 408 945) conducted at high (N = 7) and low-moderate (N = 5) levels of water arsenic met inclusion criteria, and 11 studies were included in the meta-analysis. Compared with 10 µg/l, the estimated pooled relative risks [95% confidence interval (CI)] for 20 µg/l water arsenic, based on a log-linear model, were 1.09 (1.03, 1.14) (N = 2) for CVD incidence, 1.07 (1.01, 1.14) (N = 6) for CVD mortality, 1.11 (1.05, 1.17) (N = 4) for CHD incidence, 1.16 (1.07, 1.26) (N = 6) for CHD mortality, 1.08 (0.99, 1.17) (N = 2) for stroke incidence and 1.06 (0.93, 1.20) (N = 6) for stroke mortality. We found no evidence of non-linearity, although these tests had low statistical power.Although limited by the small number of studies, this analysis supports quantitatively including CVD in inorganic arsenic risk assessment, and strengthens the evidence for an association between arsenic and CVD across low-moderate to high levels.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".