The portfolio dietary pattern and risk of cardiovascular disease mortality during 1988–2019 in US adults: a prospective cohort study
Bibliographic record
Abstract
Background The Portfolio Diet, a dietary pattern of cholesterol-lowering foods, has been shown to reduce cardiovascular disease (CVD) risk factors in clinical trials and lower CVD risk in observational cohorts of mainly white men and women. However, evidence on mortality outcomes in diverse populations is limited. Objective To examine the association of the Portfolio dietary pattern with CVD mortality in a racially diverse cohort. Methods A total of 14,835 US adults from the National Health and Nutrition Examination Survey, NHANES (1988–1994), were included. Diet was assessed by a 24-h dietary recall which was supplemented with a food frequency questionnaire at baseline using the Portfolio Diet Score (PDS), with positive points for nuts, plant protein, viscous fiber, phytosterols, and plant monounsaturated fatty acid sources, and negative points for foods high in saturated fat and cholesterol (range, 6–30 points). The primary outcome was CVD mortality. Other mortality outcomes included coronary heart disease (CHD), stroke, and all-cause mortality. Results During 22 years of follow-up, 2300 CVD deaths, including 1887 CHD deaths, 413 stroke deaths, and 6238 all-cause deaths were documented. Greater adherence was inversely associated with risk factors including blood lipids, glycemia, and inflammation. Treated as a continuous variable, an increase in PDS by 8 points was associated with a 12% (hazard ratio 0.88 [95% confidence intervals:0.78, 0.99]), 14% (0.86 [0.78, 0.96]), and 12% (0.88 [0.82, 0.95]) lower risk of CVD, CHD, and all-cause mortality after adjustments for known CVD risk factors. Comparing the highest to lowest tertiles of the PDS, higher PDS was associated with 16% (0.84 [0.73, 0.98]), 18% (0.82 [0.72, 0.95]) and 14% (0.86 [0.78, 0.96]) lower risk of CVD, CHD, and all-cause mortality, respectively. As part of exploratory analyses, an interaction between PDS and race/ethnicity was observed, emphasizing the necessity of future research involving underserved groups. Conclusions Among a national cohort of racially diverse adults in the US, greater adherence to the Portfolio dietary pattern was inversely and prospectively associated with CVD, CHD, and all-cause mortality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".