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Multicenter Study

Adherence to predefined dietary patterns and incident type 2 diabetes in European populations: EPIC-InterAct Study

InterAct Consortium. Diabetologia. 2014 Feb.

Abstract

Aims/hypothesis: Few studies have investigated the relationship between predefined dietary patterns and type 2 diabetes incidence; little is known about the generalisability of these associations. We aimed to assess the association between predefined dietary patterns and type 2 diabetes risk in European populations.

Methods: From among a case-cohort of 12,403 incident diabetes cases and 16,154 subcohort members nested within the prospective European Prospective Investigation into Cancer and Nutrition study, we used data on 9,682 cases and 12,595 subcohort participants from seven countries. Habitual dietary intake was assessed at baseline with country-specific dietary questionnaires. Two diet-quality scores (alternative Healthy Eating Index [aHEI], Dietary Approaches to Stop Hypertension [DASH] score) and three reduced rank regression (RRR)-derived dietary-pattern scores were constructed. Country-specific HRs were calculated and combined using a random-effects meta-analysis.

Results: After multivariable adjustment, including body size, the aHEI and DASH scores were not significantly associated with diabetes, although for the aHEI there was a tendency towards an inverse association in countries with higher mean age. We observed inverse associations of the three RRR-derived dietary-pattern scores with diabetes: HRs (95% CIs) for a 1-SD difference were 0.91 (0.86, 0.96), 0.92 (0.84, 1.01) and 0.87 (0.82, 0.92). Random-effects meta-analyses revealed heterogeneity between countries that was explainable by differences in the age of participants or the distribution of dietary intake.

Conclusions/interpretation: Adherence to specific RRR-derived dietary patterns, commonly characterised by high intake of fruits or vegetables and low intake of processed meat, sugar-sweetened beverages and refined grains, may lower type 2 diabetes risk.

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Figures

Fig. 1
Fig. 1
Construction of the EPIC-InterAct case-cohort study and the study population for the present analysis. T2D, type 2 diabetes
Fig. 2
Fig. 2
HRs (95% CIs) for developing type 2 diabetes for a 1-SD increment in the dietary-pattern scores (a, AHEI; b, DASH; c, RRR1; d, RRR2; e, RRR3) stratified by country and meta-analysed using a random-effects model, EPIC-InterAct study (n = 21,616). Note that the scale of the x-axis is non-linear. Model 4 adjustments were applied (stratified by age and study centre [applicable for country-specific analyses only] and adjusted for sex, physical activity, smoking status, education, total energy intake, BMI and waist circumference). In (d) the German study population is labelled ‘Heidelberg’ because Potsdam was excluded since it was used in the derivation of RRR2

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