Diet is recognised as one modifiable lifestyle factor for ischaemic heart disease (IHD). We aimed at investigating the associations between adherence to the Danish Food-Based Dietary Guidelines (FBDG) indicated by a Dietary Quality Index (DQI) and selected cardiometabolic risk factors in a cross-sectional study with 219 Danish adult participants (59 %women; age 31–65years) with a minimum of one self-rated risk marker of IHD. Information regarding diet was obtained using web-based dietary assessment software and adherence to the Danish FBDG was expressed by a DQI calculated from 5 food and nutrient indicators (whole grain, fish, fruit and vegetables, energy from saturated fat and from added sugar). Background information, blood samples and anthropometrics were collected and blood pressure was measured. Linear regression analyses were used to evaluate the association between DQI and cardiometabolic risk factors. DQI was inversely associated with LDL:HDL ratio and TAG (−0·089 per unit; 95 % CI −0·177, −0·002 and −5 % per unit; 95 % CI −9, 0, respectively) and positively associated with HDL-cholesterol (0·047 mmol/l per unit; 95 % CI 0·007, 0·088). For men, DQI was inversely associated with BMI (−3 %per unit; 95 % CI −5, −1), trunk fat (−1 % per unit; 95 % CI −2, −1), high-sensitivity C-reactive protein (−30 % per unit; 95 % CI −41, −16 %), HbA1c (−0·09 % per unit; 95 % CI −0·14, −0·04), insulin (−13 % per unit; 95 % CI −19, −7) and homoeostatic model assessment-insulin resistance (−14 % per unit; 95 % CI −21, −7). In women, DQI was positively associated with systolic blood pressure (2·6 mmHg per unit; 95 % CI 0·6, 4·6). In conclusion, higher adherence to the current Danish FBDG was associated with a more beneficial cardiometabolic risk profile in a Danish adult population with a minimum of one self-rated risk factor for IHD.

Subjective energy intake (sEI) is often misreported, providing unreliable estimates of energy consumed. Therefore, relating sEI data to health outcomes is difficult. Recently, Börnhorst et al. compared various methods to correct sEI-based energy intake estimates. They criticised approaches that categorise participants as under-reporters, plausible reporters and over-reporters based on the sEI:total energy expenditure (TEE) ratio, and thereafter use these categories as statistical covariates or exclusion criteria. Instead, they recommended using external predictors of sEI misreporting as statistical covariates. We sought to confirm and extend these findings. Using a sample of 190 adolescent boys (mean age=14), we demonstrated that dual-energy X-ray absorptiometry-measured fat-free mass is strongly associated with objective energy intake data (onsite weighted breakfast), but the association with sEI (previous 3-d dietary interview) is weak. Comparing sEI with TEE revealed that sEI was mostly under-reported (74 %). Interestingly, statistically controlling for dietary reporting groups or restricting samples to plausible reporters created a stronger-than-expected association between fat-free mass and sEI. However, the association was an artifact caused by selection bias – that is, data re-sampling and simulations showed that these methods overestimated the effect size because fat-free mass was related to sEI both directly and indirectly via TEE. A more realistic association between sEI and fat-free mass was obtained when the model included common predictors of misreporting (e.g. BMI, restraint). To conclude, restricting sEI data only to plausible reporters can cause selection bias and inflated associations in later analyses. Therefore, we further support statistically correcting sEI data in nutritional analyses. The script for running simulations is provided.

The aim of the present study was to establish whether the characteristics of members of a large national birth cohort study who submitted diet diaries with implausibly low-energy intake differed from those whose recorded energy intake was more plausible. Survey members (n 1898) recorded their diets in a 7d diary in household measures. Those whose reported energy intake (EI) as 'a fraction of their estimated BMR was less than 1·10, here termed low-energy reporters (LER) but often called under-reporters, constituted 20·6% of the study population. None of the variables describing dietary, smoking or exercise behaviour bore a significant relationship with low EI/BMR (<1·10), neither did those describing region of residence, subjective adequacy of income, current social class, social relations or the social environment of the subjects. Results of logistic regression analysis showed that the only independently significant characteristic for men was higher BMI. In women, in addition to higher BMI, having been overweight or obese as an adult independently, but less significantly, predicted low EI/BMR, while membership as a child of social class III (non-manual), having more children in the household and having a paid job marginally but independently decreased the probability of reporting low EI/BMR. Submission of a diary with EI/BMR < 1·10 7 years earlier in the same survey was an even more powerful predictor of current low EI/BMR than higher BMI in both sexes. The average reported diet-composition of LER was more micronutrient- and protein-rich than that of the others, indicating different dietary, or diet-recording, behaviour in this group of subjects. LER are not a random sample of the survey population, and their characteristics, definable to some extent, put them at risk for lower health status. Although EI/BMR cut-off points can be used to identify LER, the problem of how to use their data is still unresolved.