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dc.rights.licenseopenen_US
dc.contributor.authorIMAMURA, F.
dc.contributor.authorFRETTS, A.
dc.contributor.authorMARKLUND, M.
dc.contributor.authorARDISSON KORAT, A. V.
dc.contributor.authorYANG, W. S.
dc.contributor.authorLANKINEN, M.
dc.contributor.authorQURESHI, W.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorHELMER, Catherine
dc.contributor.authorCHEN, T. A.
dc.contributor.authorWONG, K.
dc.contributor.authorBASSETT, J. K.
dc.contributor.authorMURPHY, R.
dc.contributor.authorTINTLE, N.
dc.contributor.authorYU, C. I.
dc.contributor.authorBROUWER, I. A.
dc.contributor.authorCHIEN, K. L.
dc.contributor.authorFRAZIER-WOOD, A. C.
dc.contributor.authorDEL GOBBO, L. C.
dc.contributor.authorDJOUSSE, L.
dc.contributor.authorGELEIJNSE, J. M.
dc.contributor.authorGILES, G. G.
dc.contributor.authorDE GOEDE, J.
dc.contributor.authorGUDNASON, V.
dc.contributor.authorHARRIS, W. S.
dc.contributor.authorHODGE, A.
dc.contributor.authorHU, F.
dc.contributor.authorKOULMAN, A.
dc.contributor.authorLAAKSO, M.
dc.contributor.authorLIND, L.
dc.contributor.authorLIN, H. J.
dc.contributor.authorMCKNIGHT, B.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorRAJAOBELINA, Kalina
dc.contributor.authorRISERUS, U.
dc.contributor.authorROBINSON, J. G.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorSAMIERI, Cecilia
dc.contributor.authorSISCOVICK, D. S.
dc.contributor.authorSOEDAMAH-MUTHU, S. S.
dc.contributor.authorSOTOODEHNIA, N.
dc.contributor.authorSUN, Q.
dc.contributor.authorTSAI, M. Y.
dc.contributor.authorUUSITUPA, M.
dc.contributor.authorWAGENKNECHT, L. E.
dc.contributor.authorWAREHAM, N. J.
dc.contributor.authorWU, J. H.
dc.contributor.authorMICHA, R.
dc.contributor.authorFOROUHI, N. G.
dc.contributor.authorLEMAITRE, R. N.
dc.contributor.authorMOZAFFARIAN, D.
dc.contributor.authorFATTY, Acids
dc.date.accessioned2020-11-17T11:14:22Z
dc.date.available2020-11-17T11:14:22Z
dc.date.issued2018-10
dc.identifier.issn1549-1676 (Electronic) 1549-1277 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/14066
dc.description.abstractEnBACKGROUND: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). METHODS AND FINDINGS: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. CONCLUSIONS: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subject.enLEHA
dc.title.enFatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies
dc.title.alternativePLoS Meden_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1371/journal.pmed.1002670en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed30303968en_US
bordeaux.journalPLoS Medicineen_US
bordeaux.pagee1002670en_US
bordeaux.volume15en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.issue10en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamLEHA_BPH
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03165486
hal.version1
hal.date.transferred2021-03-10T15:34:21Z
hal.exporttrue
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