Sami dietary habits and the risk of cardiometabolic disease: a systematic review
Bibliographic record
Abstract
This systematic literary review investigates if an association between Sami dietary habits and cardiometabolic outcomes exists, and examines the dietary characteristics and cardiometabolic status of the Sami population. Included were all articles assessing Sami dietary habits and cardiometabolic disease or risk factors. Embase, Medline and SweMed were searched on 26 September 2019 and articles were screened for eligibility in October 2019. Data were extracted according to Moose Guidelines and the Newcastle Ottawa Scale (NOS) was used to assess risk of bias. The initial search generated 4,195 articles in total. Nine articles met all inclusion criteria. Two were cohort studies and seven were cross-sectional. Rating by NOS ranked from 2/7 to 8/9 stars. The studies were largely descriptive and only few had results regarding a direct association between Sami dietary habits and cardiometabolic outcomes. The findings demonstrated no association between consumption of certain Sami food items and blood-lipids or mortality from CVD/CHD. A higher intake of fat, protein, reindeer-meat and coffee and a slightly lower blood pressure and mortality from CVD/CHD was seen among Sami compared with non-Sami. The limited amount and descriptive nature of the eligible articles indicate that resaerch within the fielt is limited. Thus, additional longitudinal studies are suggested.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".