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. 2018 Nov 9;104(4):1293–1303. doi: 10.1210/jc.2018-01522

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This article has been published under the terms of the Creative Commons Attribution License (CC BY; https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s).

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Figure 1. — Association of demographic, lifestyle, dietary variables, or circulating biomarkers with plasma 25(OH)D metabolites in the EPIC-InterAct subcohort. The estimates in the figure represent standardized differences in individual 25(OH)D metabolites (in SD unit) per 1 standardized unit/category difference in each demographic, lifestyle, dietary factor, or circulating biomarker. Linear regression or Tobit regression was used to obtain the country-specific estimates of association (except for latitude due to limited study centers in some countries, or 25(OH)D₂ due to limited sample size), which were combined across countries using random-effects meta-analysis. Only associations that were significant (P < 0.05) for at least one metabolite are presented. Estimates for other variables and covariates included in the models are presented in an online repository (7). Results are from complete case analysis, with n = 11,369 for each of the nonepimeric 25(OH)D₃, 3-epi-25(OH)D₃, and 25(OH)D₂. GGT, γ-glutamyltransferase; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids.