Unscrambling the relations of egg and meat consumption with type 2 diabetes risk.

Background: Meat intake is associated with increased risk of type 2 diabetes (T2D). It is not clear if egg intake is associated with T2D risk because purported associations may be due to concurrent consumption of eggs with meat. Objective: Our aim was to differentiate any associations between meat and egg consumption and the risk of T2D. Design: In this longitudinal study, 55,851 participants of the Adventist Health Study 2 who were free of diabetes provided demographic, anthropometric, and dietary data at baseline. Meat and egg intakes were assessed with a validated quantitative food-frequency questionnaire. Responses to 2 follow-up questionnaires determined incident T2D cases. Multivariate-adjusted logistic regression was used to determine relations between meat and egg intake and incident T2D. Results: T2D cases identified during a mean 5.3 y of follow-up totaled 2772. Meat intake of >0 to <25 g/d, ≥25 to <70 g/d, and ≥70 g/d significantly increased the risk of T2D compared with no meat intake (OR: 1.29; 95% CI: 1.16, 1.44; OR: 1.42; 95% CI: 1.25, 1.61; and OR: 1.65; 95% CI: 1.39, 1.96, respectively; P-trend < 0.0001). Egg intake compared with no egg intake was not associated with T2D risk. A significant meat-egg interaction (P = 0.019) showed that within every category of egg intake, there was an incremental rise in T2D risk as meat intake increased. However, within categories of meat intake, increasing egg intake did not increase the risk of T2D except among nonmeat-eaters consuming ≥5 eggs/wk (OR: 1.52; 95% CI: 1.09, 2.12). Conclusions: Meat consumption, but not egg consumption, is independently associated with T2D risk. Egg intake seems not to increase T2D risk further with meat intake. Our findings suggest that the purported egg-T2D risk relation in US populations may be biased due to failure to investigate egg-meat interactions. Further investigations are needed to ascertain T2D risk among nonmeat-eaters with high egg intakes.

Validating polyphenol intake estimates from a food-frequency questionnaire by using repeated 24-h dietary recalls and a unique method-of-triads approach with 2 biomarkers.

Background: The assessment of polyphenol intake in free-living subjects is challenging, mostly because of the difficulty in accurately measuring phenolic content and the wide presence of phenolics in foods.Objective: The aims of this study were to evaluate the validity of polyphenol intake estimated from food-frequency questionnaires (FFQs) by using the mean of 6 measurements of a 24-h dietary recall (24-HR) as a reference and to apply a unique method-of-triads approach to assess validity coefficients (VCs) between latent "true" dietary estimates, total urinary polyphenol (TUP) excretion, and a surrogate biomarker (plasma carotenoids).Design: Dietary intake data from 899 adults of the Adventist Health Study 2 (AHS-2; 43% blacks and 67% women) were obtained. Pearson correlation coefficients (r), corrected for attenuation from within-person variation in the recalls, were calculated between 24-HRs and FFQs and between 24-HRs and TUPs. VCs and 95% CIs between true intake and polyphenol intakes from FFQs, 24-HRs, and the biomarkers TUPs and plasma carotenoids were calculated.Results: Mean ± SD polyphenol intakes were 717 ± 646 mg/d from FFQs and 402 ± 345 mg/d from 24-HRs. The total polyphenol intake from 24-HRs was correlated with FFQs in crude (r = 0.51, P < 0.001) and deattenuated (r = 0.63; 95% CI: 0.61, 0.69) models. In the triad model, the VC between the FFQs and theoretical true intake was 0.46 (95% CI: 0.20, 0.93) and between 24-HRs and true intake was 0.61 (95% CI: 0.38, 1.00).Conclusions: The AHS-2 FFQ is a reasonable indicator of total polyphenol intake in the AHS-2 cohort. Urinary polyphenol excretion is limited by genetic variance, metabolism, and bioavailability and should be used in addition to rather than as a replacement for dietary intake assessment.