Effects of Palm Oil Consumption on Lipid Profile among Rural Ivorian Youth
Bibliographic record
Abstract
As palm oil has been qualified as atherogen, we have studied the impact of its consumption on changes of lipid and lipoprotein profiles of young Ivorian healthy subjects living in rural areas. It is a descriptive cross-sectional analytical study of about 120 Ivorian subjects aged 18 to 30 years, including 65 regular consumers of palm oil and 55 subjects consuming that oil periodically as control subjects. Serum concentrations of triglycerides, total cholesterol, HDL, LDL cholesterols and lipoprotein (a) were measured by enzyme conventional methods. The TC serum varied not significantly in both subjects’ groups as the triglycerides and HDL-C did. In addition, 58.46% of palm oil consumers had hypoLDLemia. The serum concentration of lipoprotein (a) was not significantly elevated (p> 0.05) with consumers compared to controls: 33.85% versus 29.09%, p = 0.55. The percentage of subjects with normal serum concentrations is higher in all the studied parameters, with both that is the consumers and the controls, except LDL cholesterol, of which the percentage of subjects with a lower value is the highest (58.46% for consumers and 52.73% for controls). This study has shown that the consumption of palm oil did not alter the lipid and lipoprotein profile of the consumer, on the contrary, this consumption revealed a decrease in cholesterol levels with these subjects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".