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Record W4324139902 · doi:10.1161/circ.147.suppl_1.p521

Abstract P521: Association Between Dietary Phytosterols and Risk of Cardiovascular Disease Mortality in US Adults: Findings From the Third National Health and Nutrition Examination Survey (NHANES III), 1988-1994

2023· article· en· W4324139902 on OpenAlexaffabout
Julianah O. Oguntala, Andreea Zurbau, Meaghan E Kavanagh, Andrea J. Glenn, Laura Chiavaroli, Tauseef Khan, Sonia Blanco Meija, David J.A. Jenkins, Cyril W.C. Kendall, John L. Sievenpiper

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsNational Health and Nutrition Examination SurveyMedicinePhytosterolNational Death IndexEnvironmental healthPopulationDiseaseDemographyGerontologyInternal medicineConfidence intervalFood scienceBiology

Abstract

fetched live from OpenAlex

Introduction: Phytosterols (plant sterols) are naturally occurring components of plant food sources, including vegetable oils, nuts, cereals and legumes. Their chemical structure impedes intestinal cholesterol absorption and regular consumption has been related to lower serum low-density cholesterol (LDL-C), a causal risk factor for cardiovascular disease (CVD). The association between dietary plant sterol intake and CVD has yet to be determined. Objective: We aimed to examine the association of phytosterol consumption in the diet with cardiovascular mortality in US adults the National Health & Nutrition Examination Survey III (NHANES III), 1988-1994. Methods: We conducted a prospective cohort analysis on National Health and Nutrition Examination Survey (NHANES, 1988-1994 [III]), linked with the National Death Index mortality data (2015) to associate dietary phytosterol intake from 24h dietary recall data with CVD mortality. We included 13,004 adults aged ≥20 years who were non-pregnant, free of CVD at baseline and completed ≥1 24h dietary recall with plausible caloric intake data. We excluded individuals with death occurring within 1 year of baseline. We created a database quantifying the phytosterol content of foods in the 24h dietary recall data and estimated usual intake by quintiles using the NCI method. We determined the risk function by regression calibration and estimated CVD mortality risk between the 10 th (Q1) and 90 th (Q5) percentiles of usual intake. Data was adjusted for sex, age, smoking status and ethnicity. Results: Over a mean±SD follow-up period of 21.2±5.1y, 949 CVD deaths occurred in a population with a mean±SD age of 44.2±14.3y, BMI 26.7±4.7 kg/m 2 and mean dietary plant sterol usual intake of 272.3 mg/day. The top sources of dietary phytosterols were from potatoes 23%), wheat and other grains (21%) and beans, legumes and nuts (13%). Mean usual intake plant intake in the 10 th (Q1) and 90 th (Q5) percentiles of the population was 150.1 and 414.0 mg/day. The estimated relative risk for CVD mortality between Q1 (ref) and Q5 was 0.972 (p<0.05). Conclusions: Preliminary analyses suggest a CVD death risk reduction of 2.8% in the highest versus lowest intakes of dietary plant sterols in the US population. We plan to expand the multivariable model to include the Healthy Eating Index (diet quality) and assess stratification by healthful and unhealthful sources of phytosterols and linear and non-linear dose response analyses to determine the robustness of the association. OSF Registration: osf.io/da4sg Funding: Amgen Scholars Program, Canadian Institutes of Health Research (CIHR), Banting and Best Diabetes Centre (BBDC), Toronto 3D Knowledge Synthesis and Clinical Trials foundation

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.046
GPT teacher head0.290
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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