Association of magnesium intake with type 2 diabetes and total stroke: an updated systematic review and meta-analysis
Bibliographic record
Abstract
Objective The detailed associations between type 2 diabetes (T2D) and total stroke and magnesium intake as well as the dose–response trend should be updated in a timely manner. Design Systematic review and meta-analyses. Data sources PubMed, Embase, Cochrane Library, Web of Science and ClinicalTrials.gov were rigorously searched from inception to 15 March 2019. Eligibility criteria Prospective cohort studies investigating these two diseases were included. Data synthesis Relative risk (RR) and 95% CI in random effects models as well as absolute risk (AR) were pooled to calculate the risk of T2D and stroke. Methodological quality was assessed by the Newcastle-Ottawa Scale. Results Forty-one studies involving 53 cohorts were included. The magnitude of the risk was significantly reduced by 22% for T2D (RR 0.78 (95% CI 0.75 to 0.81); p<0.001; AR reduction 0.120%), 11% for total stroke (RR 0.89 (95% CI 0.83 to 0.94); p<0.001; AR reduction 0.281%) and 12% for ischaemic stroke (RR 0.88 (95% CI 0.81 to 0.95); p=0.001; AR reduction 0.246%) when comparing the highest magnesium intake to the lowest. The inverse association still existed when studies on T2D were adjusted for cereal fibre (RR 0.79; p<0.001) and those on total stroke were adjusted for calcium (RR 0.89; p=0.040). Subgroup analyses suggested that the risk for total and ischaemic stroke was significantly decreased in females, participants with ≥25 mg/m 2 body mass index and those with ≥12-year follow-up; the reduced risk in Asians was not as notable as that in North American and European populations. Conclusions Magnesium intake has significantly inverse associations with T2D and total stroke in a dose-dependent manner. Feasible magnesium-rich dietary patterns may be highly beneficial for specific populations and could be highlighted in the primary T2D and total stroke prevention strategies disseminated to the public. PROSPERO registration number CRD42018092690.
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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 | 0.002 | 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) | 0.001 | 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 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".