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A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Författare och institution:
N. Assi (-); A. Moskal (-); N. Slimani (-); V. Viallon (-); V. Chajès (-); H. Freisling (-); S. Monni (-); S. Knueppel (-); J. Förster (-); E.W. Weiderpass (-); L. Luján-Barroso (-); P. Amiano (-); E. Ardánaz (-); E. Molina Montes (-); D. Salmerón (-); J.R. Quirós (-); A.H. Olsen (-); A. Tjønneland (-); C.C. Dahm (-); K. Overvad (-); L. Dossus (-); A. Fournier (-); L. Baglietto (-); R.T. Fortner (-); R.J. Kaaks (-); A.D. Trichopoulou (-); C. Bamia (-); P. Orfanos (-); M. Santucci de Magistris (-); G. Masala (-); C. Agnoli (-); F. Ricceri (-); R. Tumino (-); H.B.A.S. Bueno-de-Mesquita (-); M.F. Bakker (-); P.H.M. Peeters (-); G. Skeie (-); T. Br̈aaten (-); Anna Winkvist (Institutionen för medicin, avdelningen för invärtesmedicin och klinisk nutrition); I. Johansson (-); K.T.T. Khaw (-); N.J. Wareham (-); T. Key (-); R.C. Travis (-); J.A. Schmidt (-); M.A. Merritt (-); E.B. Riboli (-); I. Romieu (-); P. Ferrari (-)
Publicerad i:
Public Health Nutrition, 19 ( 2 ) s. 242-254
Artikel, refereegranskad vetenskaplig
Sammanfattning (abstract):
Copyright © The Authors 2015 Objective: Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. Design: Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. Setting: The European Prospective Investigation into Cancer and Nutrition (EPIC). Subjects: Women (n 334 850) from the EPIC study. Results: The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, P trend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, P trend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, P trend<0·01). Conclusions: TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
Hälsovetenskaper ->
Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ->
Hälsovetenskaper ->
Breast cancer , European Prospective Investigationinto Cancer and Nutrition , Nutrient patterns , Principal component analysis , Treelet transform
Postens nummer:
Posten skapad:
2015-04-29 10:19
Posten ändrad:
2016-04-28 15:59

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