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Record W4387868619 · doi:10.1016/j.canep.2023.102454

The association of the healthy eating index with risk of colorectal cancers (overall and by subsite) among Canadians

2023· article· en· W4387868619 on OpenAlexaffabout
Rhonda Arthur, Victoria A. Kirsh, Thomas E. Rohan

Bibliographic record

VenueCancer Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsOntario Institute for Cancer Research
FundersAlbert Einstein College of Medicine, Yeshiva University
KeywordsMedicineColorectal cancerHazard ratioInternal medicineProportional hazards modelCohortBody mass indexCohort studyCancerLower riskGastroenterologyOncologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Healthy dietary patterns characterized by high intake of fruits and vegetables, grains/cereals, and lean meat/fish, and low intake of red/processed meats and refined carbohydrates, have been shown to be associated with reduced risk of colorectal cancer, but evidence regarding their association with colorectal cancer subsites is limited. Hence, this study was conducted to assess the association of a healthy dietary pattern, as reflected in the Healthy Eating Index (HEI) (a composite score based on consumption of various food groups), with risk of colorectal cancer, overall and by subsite. METHODS: We conducted a case-cohort study in the Canadian Study of Diet, Lifestyle and Health (CSDLH). The study included all cases of incident colorectal cancer in the entire cohort, and an age-stratified subcohort of 3185 women and 2622 men. Cox regression models were used to estimate hazard ratios (HR) for the association between the HEI and the risk of colorectal cancer, overall and by subsite. We also assessed the association by sex and by selected metabolic factors. RESULTS: For both sexes combined, the highest quintile of the HEI score was inversely associated with risk of colorectal cancer, colon cancer and proximal colon cancer (HR: 0.65; 95% CI: 0. 49-0.85, HR: 0.60, 95% CI: 0.44-0.83 and HR: 0.54, 95% CI: 0.35-0.85, respectively). However, these associations were mostly observed among men (HR: 0.56; 95% CI: 0.38-0.81, HR: 0.44, 95% CI: 0.28-0.69 and HR: 0.26; 95% CI: 0.12-0.56, for colorectal cancer, colon cancer and proximal colon cancer, respectively; p-interactions=0.029, 0.032 and 0.063, respectively). An inverse association was also observed between the HEI and risk of colorectal cancer among normal weight participants, overweight/obese participants, non-smokers, non-alcohol drinkers and participants who were physically inactive. CONCLUSION: A healthy dietary pattern may reduce risk of colorectal cancer, particularly among men.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.016
GPT teacher head0.298
Teacher spread0.282 · 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.

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

Citations5
Published2023
Admission routes2
Has abstractyes

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