Should We Stop Blaming Saturated Fats for Causing Coronary Heart Disease? A Systematic Review of Prospective Cohort Studies
Bibliographic record
Abstract
BACKGROUND: Coronary heart disease (CHD) is a leading cause of death worldwide. Saturated fats were known as a risk factor for CHD and dietary guidelines restrict the daily consumption of SFs. However, the association between SFs and higher risk of CHD is not clear. This systematic review includes 14 high-quality prospective cohort studies which reported the association between CHD and SFs. OBJECTIVE: This systematic review aims to examine the association between SFs intake and higher risk of CHD among prospective cohort studies.DESIGN: A systematic review was conducted for published literaure in Scopus and ProQuest during the period 2000 to 2017. Studies included if they have a prospective cohort design with follow-up more than 4 years, published in English, and provide information about the association of interest. Data were extracted and summarised into three tables.RESULTS: A total number of 14 prospective cohort studies were included in this review in which all from developed countries and half of them were from the USA. The total number of participants ranging from 501 to 344,696 in follow-up period from 4.8 to 30 years where 26,322 events of CHD and 629 CHD deaths were reported. The highest positive association HR (95%CI) was 5.17 (1.64-16.36) for CHD mortality and 1.36 (0.98-1.88) for CHD incidence. In contrast, the highest inverse association was found 0.73 (0.53-1.01) for CHD mortality and 0.62 (0.35-1.11) for CHD incidence. CONCLUSION: This systematic review suggests that SFs intake was not associated with higher incidence or mortality of CHD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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 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".