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Maija Huttunen-Lenz,1 Sylvia Hansen,1 Pia Christensen,2 Thomas Meinert Larsen,2 Finn Sandø-Pedersen,2 Mathijs Drummen,3 Tanja C Adam,3 Ian A Macdonald,4,5 Moira A Taylor,5 J Alfredo Martinez,6–8 Santiago Navas-Carretero,6–8 Svetoslav Handjiev,9 Sally D Poppitt,10 Marta P Silvestre,10 Mikael Fogelholm,11 Kirsi H Pietiläinen,12,13 Jennie Brand-Miller,14 Agnes AM Berendsen,15 Anne Raben,2 Wolfgang Schlicht1 1Department of Exercise and Health Sciences, University of Stuttgart, Stuttgart, Germany; 2Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark; 3Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, the Netherlands; 4MRC/ARUK Centre for Musculoskeletal Ageing Research, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, School of Life Sciences, University of Nottingham, Nottingham, UK; 5School of Life Sciences, University of Nottingham Medical School, Nottingham, UK; 6Center for Nutrition Research at the University of Navarra, Pamplona, Spain; 7Madrid Institute of Advanced Studies (IMDEA Food), Madrid, Spain; 8Biomedical Research Centre Network in Physiopathology of Obesity and Nutrition (CIBERobn), Carlos III Institute, Madrid, Spain; 9Department of Pharmacology and Toxicology, Medical University – Sofia, Sofia, Bulgaria; 10Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, New Zealand; 11Department of Food and Nutrition, University of Helsinki, Helsinki, Finland; 12Obesity Research Unit, Research Program Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland; 13Abdominal Center, Endocrinology, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland; 14Charles Perkins Centre and School of Life and Environmental Biosciences, University of Sydney, Camperdown, NSW, Australia; 15Division of Human Nutrition & Health, Wageningen University & Research, Wageningen, the Netherlands Purpose: Onset of type 2 diabetes (T2D) is often gradual and preceded by impaired glucose homeostasis. Lifestyle interventions including weight loss and physical activity may reduce the risk of developing T2D, but adherence to a lifestyle change is challenging. As part of an international T2D prevention trial (PREVIEW), a behavior change intervention supported participants in achieving a healthier diet and physically active lifestyle. Here, our aim was to explore the influence of this behavioral program (PREMIT) on social-cognitive variables during an 8-week weight loss phase. Methods: PREVIEW consisted of an initial weight loss, Phase I, followed by a weight-­maintenance, Phase II, for those achieving the 8-week weight loss target of ≥ 8% from initial bodyweight. Overweight and obese (BMI ≥25 kg/m2) individuals aged 25 to 70 years with confirmed pre-diabetes were enrolled. Uni- and multivariate statistical methods were deployed to explore differences in intentions, self-efficacy, and outcome expectancies between those who achieved the target weight loss (“achievers”) and those who did not (“non-achievers”). Results: At the beginning of Phase I, no significant differences in intentions, self-efficacy and outcome expectancies between “achievers” (1,857) and “non-achievers” (163) were found. “Non-achievers” tended to be younger, live with child/ren, and attended the PREMIT sessions less frequently. At the end of Phase I, “achievers” reported higher intentions (healthy eating χ2(1)=2.57; P

BACKGROUND/OBJECTIVES: High consumption of meat has been linked with the risk for obesity and chronic diseases. This could partly be explained by the association between meat and lower-quality diet. We studied whether high intake of red and processed meat was associated with lower-quality dietary habits, assessed against selected nutrients, other food groups and total diet. Moreover, we studied whether meat consumption was associated with obesity, after adjustment for all identified associations between meat and food consumption. SUBJECTS/METHODS: The nationally representative cross-sectional study population consisted of 2190 Finnish men and 2530 women, aged 25-74 years. Food consumption over the previous 12 months was assessed using a validated 131-item Food Frequency Questionnaire. Associations between nutrients, foods, a modified Baltic Sea Diet Score and meat consumption (quintile classification) were analysed using linear regression. The models were adjusted for age and energy intake and additionally for education, physical activity and smoking. RESULTS: High consumption of red and processed meat was inversely associated with fruits, whole grain and nuts, and positively with potatoes, oil and coffee in both sexes. Results separately for the two types of meat were essentially similar. In a linear regression analysis, high consumption of meat was positively associated with body mass index in both men and women, even when using a model adjusted for all foods with a significant association with meat consumption in both sexes identified in this study. CONCLUSIONS: The association between meat consumption and a lower-quality diet may complicate studies on meat and health. European Journal of Clinical Nutrition (2015) 69, 1060-1065;doi: 10.1038/ejcn.2015.63; published online 13 May 2015, INTRODUCTION Consumption of red and processed meat (hereafter the general term 'meat' in this manuscript refers to red and processed meat, but excluding poultry) is increasing globally, most markedly in [...]

A placebo-controlled, randomized, double-blind study of the influence of treatment and dose duration of low-dose iron supplementation in 64 non-pregnant, premenopausal women with iron-depletion revealed that after a month's treatment, concentration of serum ferritin was the same as or greater than that achieved by high-dose inorganic supplementation. While both the 9 and 27 mg doses of iron resulted in correction of slight iron deficiency anaemia, only the 27 mg dose increased iron stores.