The influence of adjustment for energy misreporting on relations of cake and cookie intake with cardiometabolic disease risk factors.

BACKGROUND/OBJECTIVES: Previous cohort studies elucidated unexpected inverse relations of cake and cookie (CC) consumption with chronic disease risk. We assessed CC intake in relation to cardiometabolic disease risk factors in a well-phenotyped population with emphasis on misreporting as the potential driving force behind inverse relations.

SUBJECTS/METHODS: In a cross-sectional EPIC-Potsdam sub-study individual usual CC intake was modeled by combining 24 h recall and food frequency questionnaire data. Cardiometabolic risk factors were anthropometry, blood lipids, blood pressure (BP), physical activity and fitness. Analysis of covariance models adjusted for (i) age/education/lifestyle and (ii) additionally for energy misreporting (ratio of energy intake over energy expenditure) were used to compute mean values of risk factors for quartiles of CC intake.

RESULTS

Adjustment for misreporting had considerable impact on relations of CC intake. Initial inverse links with anthropometry were reversed to direct associations. Misreporting adjustment also nullified inverse relations with triglycerides and with total cholesterol in women. Negligible associations with high density lipoprotein cholesterol turned inverse (men: cross-quartile difference (Δ)=-1.7 mg/dl; women: Δ=-3.6 mg/dl), so did fitness (men: Δ=-1.2 ml/kg/min; women: Δ=-0.9 ml/kg/min). Direct relations with total/low density lipoprotein cholesterol in men were not changed by misreporting (Δ max. 7.5 or 11.3 mg/dl). Reduced BP was observed in females with increased CC intake; only systolic BP remained relevant after misreporting adjustment (Δ=-4.6 mmHg).

CONCLUSIONS

The strong impact of energy misreporting on relations of CC intake with risk factors emphasizes a careful analysis and interpretation of nutritional data. We showed that apparent favorable relations of CC intake changed with a different model specification, highlighting proper modeling considerations when analyzing diet-disease relations.