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Abstract B02: Recreational physical activity, sedentary time and the incidence of colorectal polyps in a screening population for colon cancer

2017· article· en· W2744757432 on OpenAlexaffabout
Darren R. Brenner, Demetra Yannitsos, Matthew T. Warkentin, Eileen Shaw, Nigel T. Brockton, S. Elizabeth McGregor, Susanna Town, Robert J. Hilsden

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2017
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineColorectal cancerOdds ratioColonoscopyPopulationInternal medicineIncidence (geometry)CancerLogistic regressionSittingDemographyEnvironmental healthPathology

Abstract

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Abstract Background: Despite the consistent association between regular recreational moderate to vigorous physical activity (rMVPA) and reduced risk of colorectal cancer (CRC), few studies have examined the effect of physical activity on carcinogenic development by examining colorectal adenomas (polyps). Furthermore, even fewer studies have examined the impact of sedentary behavior/time (ST) on the development of polyps. In this study we examined the associations between rMVPA and ST and the presence, number and type of colorectal polyps in a population undergoing screening for colorectal cancer in Calgary, Alberta, Canada. Methods: A cross-sectional study of 2,499 individuals undergoing colonoscopy at the Forzani & MacPhail Colon Cancer Screening Centre in Calgary, Canada was conducted. Physical activity levels and ST were characterized using hours of rMVPA, meeting cancer prevention recommendations (≥150 mins/wk of rMVPA) and hours of ST using self-reported data from the Long Form International Physical Activity Questionnaire. Unconditional logistic regression models were used to estimate the crude and adjusted odds ratios (OR) for presence of polyps associated with rMVP and ST. Results: Crude estimates for meeting cancer prevention guidelines (ORunadj=0.83, 95% CI: 0.70-0.98) and increasing rMVPA (ORunadj=0.75, 95% CI: 0.60-0.93 for 1-3 hrs/wk vs. 0) were associated with lower odds of having ≥1 polyp at screening. Effect estimates were attenuated in adjusted models. Threshold effects were observed for ST with significant associations observed for up to 20 hours/week of sitting time (ORadj per hour sitting=1.05, 95% CI: 1.01-1.09). Associations were strongest for rMVPA among females (ORadj=0.68, 95% CI: 0.48-0.97 for 1-3 hrs/wk vs. 0) and for ST among males (ORadj=1.74, 95% CI: 1.06-2.86 for 14-35hrs/wk of ST vs. 0-14 hrs/wk) Conclusions: In this large population undergoing colonoscopy screening for colorectal cancer, rMVPA was associated with reduced prevalence of polyps at screening, particularly among females. Even low amounts of regular ST (2-5hrs/day) were associated with the presence of polyps, particularly among males. Strategies aimed at reducing the amount of pre-carcinogenic colon lesions should combine increasing rMVPA and reducing ST. Citation Format: Darren R. Brenner, Demetra H. Yannitsos, Matthew Warkentin, Eileen Shaw, Nigel T. Brockton, S. Elizabeth McGregor, Susanna Town, Robert J. Hilsden. Recreational physical activity, sedentary time and the incidence of colorectal polyps in a screening population for colon cancer. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B02.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.498
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.415
Teacher spread0.351 · 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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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