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Record W4402126601 · doi:10.1016/j.lana.2024.100859

Ultra-processed foods and cardiovascular disease: analysis of three large US prospective cohorts and a systematic review and meta-analysis of prospective cohort studies

2024· review· en· W4402126601 on OpenAlexaboutno aff
Kenny Mendoza-Herrera, Stephanie A. Smith‐Warner, Sinara Laurini Rossato, Neha Khandpur, JoAnn E. Manson, Eric B. Rimm, Kenneth J. Mukamal, Walter C. Willett, Μolin Wang, Frank B. Hu, Josiemer Mattei, Qi Sun

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2024
Typereview
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
FundersPan American Health OrganizationNational Institutes of HealthFundación México en HarvardConsejo Nacional de Ciencia y Tecnología
KeywordsMedicineProspective cohort studyHazard ratioFunnel plotMeta-analysisCohort studyPublication biasInternal medicineStroke (engine)Nurses' Health StudyCohortConfidence interval

Abstract

fetched live from OpenAlex

Background: Prospective associations between total and groups of ultra-processed foods (UPF) and cardiovascular disease (CVD) remained to be characterised. Our aim was to assess the association of total and group-specific UPF intakes with CVD, coronary heart disease (CHD), and stroke in three large prospective cohorts of US adults. Additionally, we conducted a systematic review and meta-analyses on the existing evidence on the associations of total UPF intake with these outcomes. Methods: = 40,409). Cox regression estimated cohort-specific associations of total and group-specific UPF intake with risk of CVD (cases = 16,800), CHD (cases = 10,401), and stroke (cases = 6758), subsequently pooled through fixed-effect models. Random-effects meta-analyses pooled existing prospective findings on the UPF-CVD association identified on Medline and Embase up to April 5, 2024, without language restrictions. Risk of bias was assessed with the Newcastle-Ottawa Scale, funnel plots, and Egger's tests, and meta-evidence was evaluated using NutriGrade. Findings: The baseline mean (SD) age was 50.8 years (7.2) for the NHS, 36.7 years (4.6) for the NHSII, and 53.4 years (9.6) for the HPFS. The proportion of participants of White race was 97.7% in the NHS, 96.4% in the NHSII, and 94.9% in the HPFS. Among the three cohorts, multivariable-adjusted hazard ratios [HRs (95% CIs)] for CVD, CHD, and stroke for the highest (vs. lowest) total UPF intake quintile were 1.11 (1.06-1.16), 1.16 (1.09-1.24), and 1.04 (0.96-1.12), respectively. UPF groups demonstrated divergent associations. Sugar-/artificially-sweetened drinks and processed meats were associated with higher CVD risk, whereas inverse associations were observed for bread/cold cereals, yoghurt/dairy desserts, and savoury snacks. Meta-analysing 22 prospective studies showed that total UPF intake at the highest category (vs. lowest) was associated with 17% (11%-24%), 23% (12%-34%), and 9% (3%-15%) higher CVD, CHD, and stroke risk. Meta-evidence quality was high for CHD, moderate for CVD, and low for stroke. Interpretation: Total UPF intake was adversely associated with CVD and CHD risk in US adults, corroborated by prospective studies from multiple countries, also suggesting a small excess stroke risk. Nutritional advice for cardiovascular health should consider differential consequences of group-specific UPF. Replication is needed in racially/ethnically-diverse populations. Funding: National Institutes of Health (NIH) grants supported the NHS, NHSII, and HPFS.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.435
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0230.003
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.175
GPT teacher head0.436
Teacher spread0.262 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations75
Published2024
Admission routes1
Has abstractyes

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