TY  - JOUR
AU  - Knueppel, S.*
AU  - Clemens, M.*
AU  - Conrad, J.*
AU  - Gastell, S.*
AU  - Michels, K.*
AU  - Leitzmann, M.*
AU  - Krist, L.*
AU  - Pischon, T.*
AU  - Krause, G.*
AU  - Ahrens, W.*
AU  - Ebert, N.*
AU  - Joeckel, K.*
AU  - Kluttig, A.*
AU  - Obi, N.*
AU  - Kaaks, R.*
AU  - Lieb, W.*
AU  - Schipf, S.*
AU  - Brenner, H.*
AU  - Heuer, T.*
AU  - Harttig, U.*
AU  - Linseisen, J.
AU  - Nöethlings, U.*
AU  - Boeing, H.*
C1  - 59751
C2  - 49035
CY  - Edinburgh Bldg, Shaftesbury Rd, Cb2 8ru Cambridge, England
SP  - E85-E85
TI  - Dietary assessment in the German National Cohort (GNC).
JO  - Proc. Nutr. Soc.
VL  - 79
IS  - OCE2
PB  - Cambridge Univ Press
PY  - 2020
SN  - 0029-6651
ER  - 

TY  - JOUR
AU  - Meisinger, C.
AU  - Rospleszcz, S.
AU  - Wintermeyer, E.*
AU  - Lorbeer, R.*
AU  - Thorand, B.
AU  - Bamberg, F.*
AU  - Peters, A.
AU  - Schlett, C.*
AU  - Linseisen, J.
C1  - 59748
C2  - 49033
CY  - Edinburgh Bldg, Shaftesbury Rd, Cb2 8ru Cambridge, England
SP  - E654-E654
TI  - Association between dietary fat intake and MRI-determined visceral, subcutaneous, or hepatic fat in men and women from the general population.
JO  - Proc. Nutr. Soc.
VL  - 79
IS  - OCE2
PB  - Cambridge Univ Press
PY  - 2020
SN  - 0029-6651
ER  - 

TY  - JOUR
AU  - Riedl, A.
AU  - Wawro, N.
AU  - Meisinger, C.
AU  - Peters, A.
AU  - Rathmann, W.*
AU  - Koenig, W.*
AU  - Daniel, H.*
AU  - Hauner, H*
AU  - Brennan, L.*
AU  - Linseisen, J.
C1  - 59749
C2  - 49034
CY  - Edinburgh Bldg, Shaftesbury Rd, Cb2 8ru Cambridge, England
SP  - E380-E380
TI  - Validation of metabotypes identified in an Irish population in the German KORA FF4 study.
JO  - Proc. Nutr. Soc.
VL  - 79
IS  - OCE2
PB  - Cambridge Univ Press
PY  - 2020
SN  - 0029-6651
ER  - 

TY  - JOUR
AB  - © 2017 The Authors. FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health.
AU  - Brouwer-Brolsma, E.M.*
AU  - Brennan, L.*
AU  - Drevon, C.A.*
AU  - van Kranen, H.J.*
AU  - Manach, C.*
AU  - Dragsted, L.O.*
AU  - Roche, H.M.*
AU  - Andres-Lacueva, C.*
AU  - Bakker, S.J.L.*
AU  - Bouwman, J.*
AU  - Capozzi, F.*
AU  - De Saeger, S.*
AU  - Gundersen, T.E.*
AU  - Kolehmainen, M.*
AU  - Kulling, S.E.*
AU  - Landberg, R.*
AU  - Linseisen, J.
AU  - Mattivi, F.*
AU  - Mensink, R.P.*
AU  - Scaccini, C.*
AU  - Skurk, T.*
AU  - Tetens, I.*
AU  - Vergeres, G.*
AU  - Wishart, D.S.*
AU  - Scalbert, A.*
AU  - Feskens, E.J.M.*
C1  - 52352
C2  - 43922
CY  - Cambridge
SP  - 619-627
TI  - Combining traditional dietary assessment methods with novel metabolomics techniques: Present efforts by the Food Biomarker Alliance.
JO  - Proc. Nutr. Soc.
VL  - 76
IS  - 4
PB  - Cambridge Univ Press
PY  - 2017
SN  - 0029-6651
ER  - 

TY  - JOUR
AB  - Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.
AU  - Leng, G.*
AU  - Adan, R.A.H.*
AU  - Belot, M.*
AU  - Brunstrom, J.M.*
AU  - de Graaf, K.*
AU  - Dickson, S.L.*
AU  - Hare, T.*
AU  - Maier, S.*
AU  - Menzies, J.*
AU  - Preissl, H.
AU  - Reisch, L.A.*
AU  - Rogers, P.J.*
AU  - Smeets, P.A.M.*
C1  - 50125
C2  - 42209
CY  - Cambridge
SP  - 316-327
TI  - The determinants of food choice.
JO  - Proc. Nutr. Soc.
VL  - 76
IS  - 3
PB  - Cambridge Univ Press
PY  - 2016
SN  - 0029-6651
ER  - 

TY  - JOUR
AB  - Meat is a food rich in protein, minerals such as iron and zinc as well as a variety of vitamins, in particular B vitamins. However, the content of cholesterol and saturated fat is higher than in some other food groups. Processed meat is defined as products usually made of red meat that are cured, salted or smoked (e.g. ham or bacon) in order to improve the durability of the food and/or to improve colour and taste, and often contain a high amount of minced fatty tissue (e.g. sausages). Hence, high consumption of processed foods may lead to an increased intake of saturated fats, cholesterol, salt, nitrite, haem iron, polycyclic aromatic hydrocarbons, and, depending upon the chosen food preparation method, also heterocyclic amines. Several large cohort studies have shown that a high consumption of processed (red) meat is related to increased overall and cause-specific mortality. A meta-analysis of nine cohort studies observed a higher mortality among high consumers of processed red meat (relative risk (RR) = 1·23; 95 % CI 1·17, 1·28, top v. bottom consumption category), but not unprocessed red meat (RR = 1·10; 95 % CI 0·98, 1·22). Similar associations were reported in a second meta-analysis. All studies argue that plausible mechanisms are available linking processed meat consumption and risk of chronic diseases such as CVD, diabetes mellitus or some types of cancer. However, the results of meta-analyses do show some degree of heterogeneity between studies, and it has to be taken into account that individuals with low red or processed meat consumption tend to have a healthier lifestyle in general. Hence, substantial residual confounding cannot be excluded. Information from other types of studies in man is needed to support a causal role of processed meat in the aetiology of chronic diseases, e.g. studies using the Mendelian randomisation approach.
AU  - Rohrmann, S.*
AU  - Linseisen, J.
C1  - 47461
C2  - 40570
CY  - Cambridge
SP  - 233-241
TI  - Processed meat: The real villain?
JO  - Proc. Nutr. Soc.
VL  - 75
IS  - 3
PB  - Cambridge Univ Press
PY  - 2016
SN  - 0029-6651
ER  -