Reformulation strategies to reduce the energy, salt, sugar, total fat, and saturated fat content of packaged food are one means to improve the food offer and facilitate healthier food choices. In Germany, the "National Reduction and Innovation Strategy for Sugar, Fats, and Salt", which runs from 2019 to 2025, is accompanied by a yearly product monitoring of packaged food. The product monitoring focuses on food categories with a major contribution to dietary intake of sugar, total and saturated fat, and salt, and on products targeted at children. Nutrition labelling information taken from manufacturer's websites serves as the primary data source and is collected manually. Analyses include the current energy, salt, sugar, total fat, and saturated fat content as well as changes of energy and nutrient content over time at the level of food categories and subcategories. Monitoring results are presented on a yearly basis for the comprehensive product range and, for selected product categories, for top-selling products. Differences in data collection and evaluation methods and limited information about the approaches taken by others hinder the comparison with further national monitoring approaches in Europe. Ongoing research projects related to the German monitoring of packaged food seek to a) automate the German data collection and b) harmonize the monitoring across Europe.

Plant-based meat substitutes (PBMS) are becoming increasingly popular due to growing concerns about health, animal welfare, and environmental issues associated with animal-based foods. The aim of this study was to compare the declared energy and nutrient contents of PBMS with corresponding meat products and sausages available on the German market. Mandatory nutrition labelling data of 424 PBMS and 1026 meat products and sausages, surveyed in 2021 and 2020, respectively, as part of the German national monitoring of packaged food were used to test for differences in energy and nutrient contents. Principal component analysis (PCA) was used to describe characteristics in the energy and nutrient contents. The comparison showed that most of the PBMS subcategories had significantly lower contents of fat and saturated fat but higher contents of carbohydrate and sugar than corresponding meat subcategories. For salt, the only striking difference was that PBMS salamis had lower salt content than meat salamis. Overall, the PCA revealed protein as a main characteristic for most PBMS categories, with the protein content being equivalent to or, in most protein-based PBMS, even higher than in the corresponding meat products. The wide nutrient content ranges within subcategories, especially for salt, reveal the need and potential for reformulation.

The figures for the proportion of vegetarian and vegan diets in the German population vary considerably. To investigate the reasons for this, representative studies of adults from the period 2005-2022 were analyzed. In the 38 surveys identified, the proportions ranged from 0.96% to 11.2% for vegetarian diets and from 0% to 3.2% for vegan diets, with an increase over time. Higher proportions of vegetarian diets are found, especially when the data are not clearly differentiated from those for pescetarian and flexitarian diets. To ensure robust and comparable data, future studies should be designed in particular to ensure that dietary habits are clearly recorded using clearly defined answer options, and that control questions on consumption allow for correction of self-classifications.

Objectives: To investigate nutrition knowledge in the German population, its determinants and its association with food consumption. Methods: Data were obtained from the NEMONIT study (2014/15, n = 1,505, participants' age: 22–80 years). Nutrition knowledge was measured using the consumer nutrition knowledge scale (CoNKS) in a computer-assisted telephone interview. Two 24-h recalls were conducted to assess food consumption, which was evaluated using the Healthy Eating Index-NVS II. Results: Areas for knowledge enhancement were the understanding of health benefits of fruit and vegetable consumption, the concept of a balanced diet and saturated fatty acids. Nutrition knowledge was higher among females, younger and high socio-economic status participants. Correlations between nutrition knowledge and a favorable diet were significant but low. Analyses of types of nutrition knowledge yielded similar results for procedural knowledge and knowledge on nutrients but not for knowledge on calories. Conclusions: Areas for knowledge enhancement were identified, but an increase in nutrition knowledge alone seems unlikely to result in large improvements of dietary behavior.

The aim of the present study was to determine whether the association between body mass index (BMI) and the intake of macronutrients varies along the BMI distribution of German adults. Based on a sample of 9214 men and women aged 18-80 years from the representative cross-sectional German National Nutrition Survey (NVS) II, quantile regression was used to investigate the association between BMI and the intake of macronutrients independent of energy intake and other predictors. In both sexes, BMI was positively associated with the intake of total protein and animal protein over its entire range and negatively associated with vegetable protein. A negative association between BMI and the intake of polysaccharides was found along the entire range of BMI in men. There was a weak negative association between BMI and the intake of total fat and saturated fatty acids observed in normal-weight-range women only. In conclusion, the association between BMI and the intake of macronutrients varies along the BMI range. Animal protein intake is positively associated with BMI independent of energy intake in both sexes whereas only in men an inverse association of polysaccharide intake with BMI was shown.

AbstractIntroductionA comparison of means of food consumption assessed by three different dietary assessment methods (diet history interviews [DHI], 24h-recalls [24HR] and weighing food records [WR]) used in the German National Nutrition Survey (NVS) II showed higher consumption means in 7 out of 18 food groups for DHI compared to 24HR and WR. Especially for food groups perceived as socially desirable such as fruit and vegetable means were highest for DHI. In the following, it is examined whether differences in fruit and vegetable consumption assessed by three different dietary assessment methods are related to sex, age, body mass index (BMI) or socio economic status (SES).MethodsA subgroup of 677 participants of the NVS II (2005–2007, 14–80 years of age) completed all three dietary assessment methods. DHI covered the food consumption of the past month, 24HR of the previous day and WR two times four days. Body height and weight were measured. SES was defined as an index based on the household income, employment status of the household's principle earner, and education level of the participant. The Multiple Source Method was applied to estimate population distributions of usual intakes based on two 24HR. Confidence intervals were calculated on basis of bootstrapping samples. Differences are considered to be significant if confidence intervals do not overlap.ResultsFor vegetable consumption, all subgroups regarding sex (male, female), age (14–18 years, 19–24 years, 25–34 years, 51–64 years, 65 years and older), body mass index (< 25 kg/m2, 25–30 kg/m2, > 30 kg/m2) and SES (5 groups from 1 = lower to 5 = upper SES) showed higher means for DHI compared to 24HR and WR. For fruit consumption, in almost all subgroups higher means for DHI compared to 24HR and WR could be found, except for the age group 19–24 years and the lowest SES group.DiscussionThe results show that higher means in fruit and vegetable consumption assessed by DHI compared to 24HR and WR are independent of sex, age, BMI and SES. A reason why socially desirable foods like fruit or vegetables are stated in higher amounts by DHI may be the enormous cognitive task of participants necessary to estimate quantities and frequencies over the long period of time covered by DHI.

Glyphosate (N-[phosphonomethyl]-glycine) is the most widely used herbicide worldwide. Due to health concerns about glyphosate exposure, its continued use is controversially discussed. Biomonitoring is an important tool in safety evaluation and this study aimed to determine exposure to glyphosate and its metabolite AMPA, in association with food consumption data, in participants of the cross-sectional KarMeN study (Germany). Glyphosate and AMPA levels were measured in 24-h urine samples from study participants (n = 301). For safety evaluation, the intake of glyphosate and AMPA was calculated based on urinary concentrations and checked against the EU acceptable daily intake (ADI) value for glyphosate. Urinary excretion of glyphosate and/or AMPA was correlated with food consumption data. 8.3% of the participants (n = 25) exhibited quantifiable concentrations (> 0.2 µg/L) of glyphosate and/or AMPA in their urine. In 66.5% of the samples, neither glyphosate (< 0.05 µg/L) nor AMPA (< 0.09 µg/L) was detected. The remaining subjects (n = 76) showed traces of glyphosate and/or AMPA. The calculated glyphosate and/or AMPA intake was far below the ADI of glyphosate. Significant, positive associations between urinary glyphosate excretion and consumption of pulses, or urinary AMPA excretion and mushroom intake were observed. Despite the widespread use of glyphosate, the exposure of the KarMeN population to glyphosate and AMPA was found to be very low. Based on the current risk assessment of glyphosate by EFSA, such exposure levels are not expected to pose any risk to human health. The detected associations with consuming certain foods are in line with reports on glyphosate and AMPA residues in food.

SCOPE:The human volatilome has gained high interest for the discovery of potential biomarkers of diseases. However, knowledge about the diet as a crucial factor affecting the volatilome is scarce. Therefore, the search for disease biomarkers, as well as the potential use of volatiles as dietary markers is so far limited. The aim of this study is to investigate the association of the diet with the urinary volatilome with the special task to find potential markers of coffee consumption in 24 h urine samples from the Karlsruhe Metabolomics and Nutrition (KarMeN) study.METHODS AND RESULTS:Acidified urine samples are analyzed using an approach combining headspace solid phase microextraction (HS-SPME) sampling with untargeted GC×GC-MS. Overall, 138 reliably occurring volatiles are detected. To account for the unequally concentrated urine samples, results of six different commonly used normalization methods are compared. Statistical analysis evidences six potential markers of coffee consumption, the most promising being 3,4-dimethyl-2,5-furandione. A correlation analysis between the 24 h dietary recall data and the urinary volatilome reveals further promising associations.CONCLUSION:The human urinary volatilome is highly affected by the diet, enabling access to a high level of information about potential diet-related biomarkers. Therefore, it is a very promising source for further investigations on dietary markers.

This dataset contains the underlying research data for the paper: Merz, B.; Frommherz, L.; Rist, M.J.; Kulling, S.E.; Bub, A.; Watzl, B. Dietary Pattern and Plasma BCAA-Variations in Healthy Men and Women—Results from the KarMeN Study. Nutrients 2018, 10, 623. The tab-delimeted data file contains information of participants from the Karlsruhe Metabolomics and Nutrition (KarMeN) Study including descriptive metadata, plasma amino acid concentrations assessed via liquid chromatography–mass spectrometry, information on current dietary intake (food group level) assessed via 24h recall and information on habitual dietary intake (food group level and selected macronutrients) calculated with the NCI method. The dataset also includes an annotation file that is providing additional information such as unit, decoding of used abbreviations and a description of the included food groups.

ABSTRACT Background Although sugars and sugar derivatives are an important class of metabolites involved in many physiologic processes, there is limited knowledge on their occurrence and pattern in biofluids. Objective Our aim was to obtain a comprehensive urinary sugar profile of healthy participants and to demonstrate the wide applicability and usefulness of this sugar profiling approach for nutritional as well as clinical studies. Design In the cross-sectional KarMeN study, the 24-h urine samples of 301 healthy participants on an unrestricted diet, assessed via a 24-h recall, were analyzed by a newly developed semitargeted gas chromatography–mass spectrometry (GC-MS) profiling method that enables the detection of known and unknown sugar compounds. Statistical analyses were performed with respect to associations of sex and diet with the urinary sugar profile. Results In total, 40 known and 15 unknown sugar compounds were detected in human urine, ranging from mono- and disaccharides, polyols, and sugar acids to currently unknown sugar-like compounds. A number of rarely analyzed sugars were found in urine samples. Maltose was found in statistically higher concentrations in the urine of women compared with men and was also associated with menopausal status. Further, a number of individual sugar compounds associated with the consumption of specific foods, such as avocado, or food groups, such as alcoholic beverages and dairy products, were identified. Conclusions We here provide data on the complex nature of the sugar profile in human urine, of which some compounds may have the potential to serve as dietary markers or early disease biomarkers. Thus, comprehensive urinary sugar profiling not only has the potential to increase our knowledge of host sugar metabolism, but can also reveal new dietary markers after consumption of individual food items, and may lead to the identification of early disease biomarkers in the future. The KarMeN study was registered at drks.de as DRKS00004890.

Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles.In the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study 301 healthy men and women aged 18-80 years were recruited. Participants were characterized in detail applying standard operating procedures for all measurements including anthropometric, clinical, and functional parameters. Fasting blood and 24 h urine samples were analyzed by targeted and untargeted metabolomics approaches, namely by mass spectrometry coupled to one-or comprehensive two-dimensional gas chromatography or liquid chromatography, and by nuclear magnetic resonance spectroscopy. This yielded in total more than 400 analytes in plasma and over 500 analytes in urine. Predictive modelling was applied on the metabolomics data set using different machine learning algorithms.Based on metabolite profiles from urine and plasma, it was possible to identify metabolite patterns which classify participants according to sex with > 90% accuracy. Plasma metabolites important for the correct classification included creatinine, branched-chain amino acids, and sarcosine. Prediction of age was also possible based on metabolite profiles for men and women, separately. Several metabolites important for this prediction could be identified including choline in plasma and sedoheptulose in urine. For women, classification according to their menopausal status was possible from metabolome data with > 80% accuracy.The metabolite profile of human urine and plasma allows the prediction of sex and age with high accuracy, which means that sex and age are associated with a discriminatory metabolite signature in healthy humans and therefore should always be considered in metabolomics studies.

OBJECTIVE:The objective of the study was to identify predictors of BMI in German adults by considering the BMI distribution and to determine whether the association between BMI and its predictors varies along the BMI distribution.METHODS:The sample included 9,214 adults aged 18-80 years from the German National Nutrition Survey II (NVS II). Quantile regression analyses were conducted to examine the association between BMI and the following predictors: age, sports activities, socio-economic status (SES), healthy eating index-NVS II (HEI-NVS II), dietary knowledge, sleeping duration and energy intake as well as status of smoking, partner relationship and self-reported health.RESULTS:Age, SES, self-reported health status, sports activities and energy intake were the strongest predictors of BMI. The important outcome of this study is that the association between BMI and its predictors varies along the BMI distribution. Especially, energy intake, health status and SES were marginally associated with BMI in normal-weight subjects; this relationships became stronger in the range of overweight, and were strongest in the range of obesity.CONCLUSIONS:Predictors of BMI and the strength of these associations vary across the BMI distribution in German adults. Consequently, to identify predictors of BMI, the entire BMI distribution should be considered.

AbstractObjectiveTo characterise German vitamin and mineral supplement users differentiated by their motives for supplement use.DesignData were obtained from the German National Nutrition Monitoring (2010/11) via two 24 h dietary recalls and a telephone interview. Motive-based subgroups of supplement users were identified by factor and cluster analysis. Sociodemographic, lifestyle, health and dietary characteristics and supplement use were examined. Differences were analysed using χ2 tests, logistic and linear regression models.SettingGermany, nationwide.SubjectsIndividuals (n 1589) aged 18–80 years.ResultsThree motive-based subgroups were identified: a ‘Prevention’ subgroup (n 324), characterised by the motive to prevent nutrient deficiencies; a ‘Prevention and additional benefits’ subgroup (n 166), characterised by motives to prevent health problems and improve well-being and performance; and a ‘Treatment’ subgroup (n 136), characterised by motives to treat nutrient deficiencies or diseases. Members of the two prevention subgroups had a higher Healthy Eating Index score and tended to be more physically active than non-users. Those in the ‘Prevention and additional benefits’ subgroup supplemented with a greater number of micronutrients. Members of the ‘Treatment’ subgroup tended to be older and have a lower self-reported health status than non-users, and supplemented with a smaller number of micronutrients.ConclusionsThe majority of supplement users take supplements for preventive purposes and they are more health conscious than non-users of supplements due to their concerns about developing health problems. Those supplementing for treatment purposes may have underlying health indications and may be more likely to benefit from supplementation than those supplementing for preventive purposes.

Comparison of food consumption, nutrient intake and underreporting of diet history interviews, 24-h recalls and weighed food records to gain further insight into specific strength and limitations of each method and to support the choice of the adequate dietary assessment method.

The aim of this article is to demonstrate the complexity of nutritional behavior and to increase understanding of this complex phenomenon. We developed a cause-effect model based on current literature, expert consultation, and instruments dealing with complexity. It presents factors from all dimensions of nutrition and their direct causal relationships with specification of direction, strength, and type. Including the interplay of all relationships, the model reveals cause-effect chains, feedback loops, multicausalities, and side effects. Analyses based on the model can further enhance understanding of nutritional behavior and help identify starting points for measures to modify food consumption.

Background The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible. Objective The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and1H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics. Methods Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,1H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods. Results The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway. Conclusions We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and1H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study. Trial Registration German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx)