Associations of the biomarker score with incident T2D
T2D, comorbidity, cancer, cardiovascular disease, T2D, smoking status (, adiposity
PAF, RECRUITMENT, HYPERLIPIDAEMIA, SECONDARY, ADIPOSITY, REGRESSION, HYPERTENSION
In EPIC-InterAct, individual nutritional biomarkers were Winsorised at 4 standard deviations (SDs) below or above the subcohort means and were then used to calculate the biomarker score with the scoring algorithm developed as described above. The biomarker score was standardised using the means and SD and categorised into quintiles based on the distribution in the subcohort. We performed Prentice-weighted Cox regression analysis with a robust variance estimator to estimate hazard ratios (HRs) for the association between the biomarker score and incident T2D [The multivariable-adjusted model included the following covariates: age (as the underlying timescale), sex, recruitment centre, prevalent comorbidity (cancer, cardiovascular disease, hypertension, and hyperlipidaemia), family history of T2D, smoking status (never, former, and current smoker), physical activity index (inactive, moderately inactive, moderately active, and active), seasonality (sine and cosine function of the day of the year of blood draw), fasting status (<3, 3–6, >6 h), current use of vitamin or mineral supplements, marital status (single, married or cohabiting, divorced or separated, and widowed), educational attainment (none, primary school, technical or professional school, secondary school, and post-secondary school education), current employment, and in women, menopausal status (pre-, peri-, postmenopausal, and bilateral oophorectomy) and current hormone replacement therapy use. A further model was fitted with adjustment for adiposity (BMI and waist circumference as continuous variables; main analytical model). Additional models explored the effects of adjustment for biomarkers constituting the biomarker score. Continuous covariates were Winsorised at 4 SDs below or above the subcohort means. For comparison with the biomarker-based assessment, we estimated the HR for the association with incident T2D of the standardised score of self-reported Mediterranean diet using the main analytical model.We examined multiplicative interactions of the biomarker score with the following covariates: age, sex, BMI, seasonality, fasting status, use of dietary supplements, physical activity, and smoking status using the adiposity-adjusted model (excluding waist circumference for interaction by BMI) and variable specifications as outlined above. Missing covariate data were imputed by multiple imputation using chained equations in 10 datasets [To assess the potential public health impact of a feasible shift in the average population adherence to the Mediterranean diet, we modelled the population attributable fraction (PAF) [