Breakfast quality and cardiometabolic risk profiles in an upper middle-aged German population.

BACKGROUND/OBJECTIVES: Little is known about relation of overall breakfast quality with cardiometabolic risk factors. Therefore, this study aimed to explore sex-specific associations between breakfast quality and cardiometabolic risk profiles in a sample of an upper middle-aged German population. SUBJECTS/METHODS: Cardiometabolic profiles of 339 men and 329 women were cross-sectionally assessed using an overall biomarker score (BScore), glycated hemoglobin (HbA1c), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), blood pressure, body mass index (BMI) and waist circumference (WC). Overall breakfast quality was assessed by using (i) an a-priori defined breakfast quality score (BQS) and (ii) data-driven breakfast patterns based on principal component analysis (PCA). Multiple linear regression models for association of breakfast quality with all outcomes were adjusted for all potential confounders including overall diet quality. RESULTS: After adjustment for all potential confounders the BQS was inversely associated with the BScore (regression beta with 95% Confidence Interval: -0.29 (052-0.06)) and HbA1c (-0.12 (-0.21, -0.04)) in men; whereas no such associations were observed in women. Four breakfast (B) patterns were identified: B-processed-food pattern, B-cereal pattern, B-high fat pattern and B-dairy & cereal pattern. The B-processed-food pattern was positively associated with HbA1c (0.09(0.01, 0.18)), BMI (0.16 (0.06, 0.26)), and WC (0.17 (0.8, 0.26)) in men, and BMI (0.13 (0.1, 0.25)) and WC (0.11(0.01.0.22)) in women. The B-cereal pattern was inversely associated with BScore (-0.23 (-0.45, -0.01)) and BMI (-0.11 (-0.20, -0.01)) in men and WC(-0.16 (-0.27, -0.05)) in women. The B-dairy & cereal pattern was also inversely associated with BScore (-0.26 (-0.48, -0.04)) in men but not in women. CONCLUSIONS: The overall breakfast quality was cross-sectionally associated with a healthier cardiometabolic profile, especially in upper-middle age men, independent of overall dietary quality. Such analyses should be supplemented by studies investigating the circadian sequence of food intake and metabolic consequences including hard disease endpoints.

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 (ΔQ4-Q1)=-1.7 mg/dl; women: ΔQ4-Q1=-3.6 mg/dl), so did fitness (men: ΔQ4-Q1=-1.2 ml/kg/min; women: ΔQ4-Q1=-0.9 ml/kg/min). Direct relations with total/low density lipoprotein cholesterol in men were not changed by misreporting (ΔQ4-Q1 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 (ΔQ4-Q1=-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.