Relationship between Vitamin D Insufficiency, Lipid Profile and Atherogenic Indices in Healthy Women Aged 18–50 Years
Bibliographic record
Abstract
Although vitamin D insufficiency has been correlated with an increased risk of cardiovascular disease (CVD), there are few data on the association between 25-hydroxyvitamin D (25(OH)D) and atherogenic indices predictive of CVD. This study investigated the relationship of vitamin D status with lipid profile and atherogenic indices in adult women in Morocco. Three hundred women aged 18 to 50 years from Meknes were included. Fasting 25(OH)D and lipid concentrations were assayed by a one-step electrochemiluminescence-based immunoassay and an enzymatic method, respectively. Atherogenic indices (atherogenic index of plasma (AIP), atherogenic coefficient (AC), non-HDL cholesterol (non-HDL-C), Castelli risk indices I and II (CRI-I and II), and CHOLIndex (CI)) were calculated using conventional lipid parameters. Logistic regression models and operating characteristic curve (ROC) analysis were used to assess the relationship of the variables and estimate the threshold of 25(OH)D levels associated with high atherogenic indices. 25(OH) D below 20 ng/mL was significantly associated with an enhanced risk of hypertriglyceridemia and elevated values of AIP, AC, non-HDL-C, and CRI-I with an OR (95% CI) of 4.904 (1.856–12.959), 3.637 (2.149–6.158), 3.589 (1.673–7.700), 2.074 (1.215–3.540), and 2.481 (1.481–4.123), respectively. According to the ROC analysis, the likelihood of hypertriglyceridemia and high values of AIP, AC, non-HDL-C, and CRI-I were associated with 25(OH)D thresholds ≤15.15 ng/mL, ≤17.5 ng/mL, ≤19.8 ng/mL, ≤20.1 ng/mL, and ≤19.5 ng/mL, respectively, all p < 0.01. Based on the atherogenic indices, this study indicates that vitamin D below 20 ng/mL may increase the risk of cardiovascular disease in adult women. Additional health measures are essential to raise awareness among women and health professionals of preventing and controlling cardiovascular risk factors, particularly among young individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".