Associations between empirically derived dietary patterns and cardiovascular risk factors among older adult men
Bibliographic record
Abstract
Abstract: Cardiovascular disease (CVD) remains the leading cause of death globally, and epidemiological studies have suggested a link between diet and cardiometabolic risk. Currently, the prevalence of CVD is rapidly increasing with an aging population and continues to contribute to the growing economic and public health burden. However, there is limited evidence available regarding dietary patterns and cardiometabolic risk factors in older adults. We conducted a cross-sectional study to assess dietary patterns and cardiometabolic risk factors in males ≥60 years. Factor analysis identified a “healthy” diet and an “unhealthy” diet as the two primary dietary patterns. Multivariable logistic regression was used for estimating the associations of identified dietary patterns and cardiometabolic risk factors including anthropometric measures, blood pressure, glycemic biomarkers, lipid profile, and inflammatory biomarkers. A healthy dietary pattern was significantly associated with decreased odds of high serum fasting blood sugar (FBS) (OR: 0.32; 95% CI: 0.15–0.67; P trend =0.002), but increased odds of high serum low-density lipoprotein cholesterol (LDL-C) (OR: 1.82; 95% CI: 1.02–3.24; P trend =0.04). In comparison, an unhealthy diet was associated with increased odds of obesity (OR: 2.33; 95% CI: 1.31–4.15; P trend =0.004) and high LDL-C (OR: 2.00; 95% CI: 1.10–2.61; P trend =0.02). Thus, in older adults, adherence to an unhealthy dietary pattern has a significant impact on clinically relevant risk factors for cardiometabolic risk.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".