Validation of the web-based self-administered 24-h dietary recall myfood24-Germany: comparison with a weighed dietary record and biomarkers

Purpose We aimed to validate myfood24-Germany, a web-based 24-h dietary recall (24HDR), by comparing its performance with a weighed dietary record (WDR) and biomarkers. Methods 97 adults (77% female) completed a 3-day WDR with a 24-h urine collection on day 3, followed by at least one 24HDR with myfood24-Germany (corresponding to day 3 of the WDR). Intake of energy and 32 nutrients assessed by myfood24-Germany and the WDR for the same day were compared (method comparison). Intakes of protein and potassium assessed by myfood24-Germany/WDR were compared with intake estimated from urinary biomarkers for protein and potassium (biomarker comparison). Results In the method comparison, significant correlations were found for energy and all tested nutrients (range 0.45–0.87). There was no significant difference between both methods in the assessed mean energy and macronutrient intake. However, myfood24-Germany underestimated mean intake of 15 nutrients. In the biomarker comparison, protein intake reported by myfood24-Germany/WDR was on average 10%/8% lower than estimated by biomarker. There was no significant difference in mean potassium intake assessed by myfood24-Germany/WDR and biomarker. However, a shared bias in the assessment of potassium intake was observed for both instruments. Concordance correlation coefficients (pc) and weighted Kappa coefficients (κ) confirmed good agreement with the biomarker estimates for myfood24-Germany/WDR in case of protein (pc = 0.58/0.66, κ = 0.51/0.53) and moderate agreement in case of potassium (pc = 0.44/0.51; κ = 0.30/0.33). Conclusion Our results suggest that myfood24-Germany is of comparable validity to traditional dietary assessment methods

Changing dietary patterns is necessary to improve the sustainability of Western diets from a One Health perspective

Western diets are associated with multiple environmental impacts and risks to human health. European countries are gradually taking action towards the Farm to Fork Strategy, embracing a Life Cycle Assessment (LCA) perspective to promote the sustainability of food production and consumption. Although LCA enables the comprehensive assessment of environmental impacts, diet-related human health and animal welfare impacts are often underrepresented. This study proposes integrating additional indicators into LCA to evaluate the sustainability of diets under the One Health (OH) approach, which holistically considers interlinked complex health issues between humans, animals and the environment. Human health loss is estimated according to risk factors for non-communicable diseases; while animal welfare is measured as animal life years suffered, loss of animal lives and loss of morally-adjusted animal lives. The extended LCA framework is applied to men and women's reference diets in the German federal state of North Rhine-Westphalia (NRW); compared to three optimized dietary scenarios under nutritional constraints: 1) the national dietary guidelines, 2) a vegan diet (VD) and 3) a Mediterranean diet (MD). Men's reference diet causes greater impacts than women's across OH dimensions due to the higher food consumption, especially of ready-to-eat meals, sausages, meat, and sweetened and alcoholic beverages. Both reference diets are associated with risk factors for cardiovascular diseases, diabetes, stroke and neoplasms. Besides meat, consumption of honey, fish and seafood has the greatest impact on animal welfare, because of the high number of individuals involved. Alternative diets improve the sustainability of food consumption in NRW, although trade-offs arise: MD worsens animal suffering due to the higher fish intake; water use increases in both VD and MD due the higher intake of nuts and vegetables. Results highlight the importance of including animal welfare and human health indicators in LCA to better elucidate the potential impacts of diets characterized by the high intake of animal products, from a OH perspective

Optimised diets for achieving One Health: A pilot study in the Rhine-Ruhr Metropolis in Germany

Dietary changes are needed to align the global food systems with the planetary boundaries and contribute to Sustainable Development Goals. We employed a Life Cycle Assessment (LCA) framework, extended with indicators on human health and animal welfare, to assess 2020 food consumption data of a pilot sample collected through an online survey in the Rhine-Ruhr Metropolis (Germany). Feasible optimisation scenarios representing alternative sustainable choices towards overarching environmental, societal and policy goals were explored. Meat and meat products contributed most to overall environmental impacts (e.g., climate change, terrestrial acidification), and fish and seafood to animal welfare loss (e.g., animal lives lost, animal life years suffered). Sodium intake was the most contributing risk factor for life minutes lost. The combined optimisation scenario reduces 55% of greenhouse gas emissions, improves human health indicators by 25% and reduces animal welfare loss substantially (by 52-97%). This is possible with a shift towards flexitarian and vegetarian dietary scenarios. These optimisations deliver improvements across One Health dimensions with marginal changes in dietary scenarios and align with the sustainability goals of the EU Green Deal. Working with regional data can offer advantages in obtaining more realistic baseline dietary information to promote localised dietary shifts. While this research has limitations regarding sample representativeness, it can serve as a case study to encourage sustainable consumption in the Rhine-Ruhr region

Non-fasting lipids and risk of cardiovascular disease in patients with diabetes mellitus

The aim of this study was to examine the effect of postprandial time on the associations and predictive value of non-fasting lipid levels and cardiovascular disease risk in participants with diabetes. This study was conducted among 1,337 participants with diabetes from the Dutch and German (Potsdam) contributions to the European Prospective Investigation into Cancer and Nutrition. At baseline, total cholesterol, LDL- and HDL-cholesterol and triacylglycerol concentrations were measured and the ratio of total cholesterol/HDL-cholesterol was calculated. Participants were followed for incidence of cardiovascular disease. Lipid concentrations changed minimally with increasing postprandial time, except for triacylglycerol which was elevated just after a meal and declined over time (1.86 at 0.1 h to 1.33 at >6 h, p for trend <0.001). During a mean follow-up of 8 years, 116 cardiovascular events were documented. After adjustment for potential confounders, triacylglycerol (HR for third tertile compared with first tertile (HR(t)₃(to)₁), 1.73 [95% CI 1.04, 2.87]), HDL-cholesterol (HR(t)₃(to)₁, 0.41 [95% CI 0.23, 0.72]) and total cholesterol/HDL-cholesterol ratio (HR(t)₃(to)₁, 1.65 [95% CI 0.95, 2.85]) were associated with cardiovascular disease, independent of postprandial time. Cardiovascular disease risk prediction using the UK Prospective Diabetes Study risk engine was not affected by postprandial time. Postprandial time did not affect associations between lipid concentrations and cardiovascular disease risk in patients with diabetes, nor did it influence prediction of cardiovascular disease. Therefore, it may not be necessary to use fasting blood samples to determine lipid concentrations for cardiovascular disease risk prediction in patients with diabete

External validation of the UK Prospective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes

Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engine for predicting cardiovascular risk in patients with type 2 diabetes, although validation studies showed moderate performance. The methods used in these validation studies were diverse, however, and sometimes insufficient. Hence, we assessed the discrimination and calibration of the UKPDS risk engine to predict 4, 5, 6 and 8 year cardiovascular risk in patients with type 2 diabetes. The cohort included 1,622 patients with type 2 diabetes. During a mean follow-up of 8 years, patients were followed for incidence of CHD and cardiovascular disease (CVD). Discrimination and calibration were assessed for 4, 5, 6 and 8 year risk. Discrimination was examined using the c-statistic and calibration by visually inspecting calibration plots and calculating the Hosmer-Lemeshow χ(2) statistic. The UKPDS risk engine showed moderate to poor discrimination for both CHD and CVD (c-statistic of 0.66 for both 5 year CHD and CVD risks), and an overestimation of the risk (224% and 112%). The calibration of the UKPDS risk engine was slightly better for patients with type 2 diabetes who had been diagnosed with diabetes more than 10 years ago compared with patients diagnosed more recently, particularly for 4 and 5 year predicted CVD and CHD risks. Discrimination for these periods was still moderate to poor. We observed that the UKPDS risk engine overestimates CHD and CVD risk. The discriminative ability of this model is moderate, irrespective of various subgroup analyses. To enhance the prediction of CVD in patients with type 2 diabetes, this model should be update