Pasta Consumption and Cardiometabolic Risks in Older Adults with Overweight/Obesity: A Longitudinal Analysis
Bibliographic record
Abstract
Objective Low Glycemic Index (GI) diets improve cardiometabolic risk (CMR) specifically in those with insulin resistance. However, the prospective association between pasta (a low GI staple) consumption and CMR is unclear. We evaluated the longitudinal association of pasta consumption with CMR (after 2 y: body weight, body mass index (BMI), waist circumference (WC), blood pressure (BP); after 1 y: fasting blood glucose, HbA1c, HDL-cholesterol and triglycerides) in ∼6000 older adults (50% women) at high CMR.Methods Consumption of pasta and other staples were determined as the cumulative average of reported intakes at baseline and annual follow-up visits from food frequency questionnaires and defined as energy-adjusted (residuals) and the number of daily servings. Longitudinal association between pasta consumption and CMR was assessed in PREDIMED-Plus participants (Trail registry number: ISRCTN89898870).Results Mean (SD) dry pasta intake was 9(7) g/d at Year 1 and 8(6) g/d at Year 2. In linear regression models, higher pasta intake was associated with greater 2 y decreases in body weight, BMI and WC. When fully adjusted, every additional serving of pasta was associated with significantly greater 2 y decreases in body weight (−2.23(−3.47, −0.98 kg), BMI (−0.86(−1.27, −0.34 kg/m2) and WC (−1.92 (−3.46, −0.38 cm). There was no evidence of association with other outcomes. Additionally, substituting equivalent servings of pasta for white bread or white rice or potato was significantly associated with greater 2 y decreases in body weight and BMI. Replacing white bread with pasta was associated with higher 2 y reductions in WC. Replacing potato with pasta was associated with improvements in diastolic BP and HDL-cholesterol. Conclusions: Equivalent serving substitutions of white bread/white rice/potato with pasta may help reduce CMR in older Mediterranean adults with overweight/obesity. While such substitutions are feasible where pasta consumption aligns with the local gastronomic culture, the feasibility and potential CMR benefit of such interventions should be confirmed in other populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".