The association between types of seafood intake and the risk of type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Seafood is the main source of long-chain n-3 polyunsaturated fatty acids (n-3 PUFAs) with beneficial health effects; however, findings on the association between the consumption of different types of seafood and type 2 diabetes mellitus (T2DM) are conflicting. Our objective was to perform a systematic review and meta-analysis examining the relationship between different types of fish/seafood and the risk of T2DM in adult populations. Methods: A systematic search of PubMed/Medline, Scopus, and Web of Science (ISI) databases was performed for cohort studies, published in English, before 1 September 2017. Multivariate adjusted relative risk (RR) estimates with 95% confidence intervals (CIs) for each category of seafood were pooled to examine the association. Results: Comparing the highest vs. lowest fatty fish intake categories indicated that there was a significant inverse association between the consumption of fatty fish and onset of T2DM (RR: 0.89; 95 % CI: 0.82, 0.98; I2: 0%, P = 0.54). However, after performing sensitivity analysis, we found that eliminating one study resulted in a non-significant association (RR: 0.93; 95 % CI: 0.80, 1.09). There were no significant associations between lean fish (RR: 1.03; 95% CI: 0.87, 1.22, I2: 51.0%, P = 0.08), seafood other than fish (RR: 0.95; 95% CI: 0.83, 1.10, I2: 71.2%, P = 0.002), fish products (RR: 0.96; 95% CI: 0.82, 1.13, I2:0%, P = 0.62), and fried fish (RR: 1.02; 95% CI: 0.83, 1.26, I2:71.2%, P = 0.06) and T2DM risk. Conclusion: The risk of T2DM was not associated with the intake of lean fish, seafood other than fish, and fish products. However, due to the low robustness of findings regarding protective roles of oily fish, more longitudinal studies are needed to clarify this association.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| 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 it