BackgroundFront of pack food labels or signpost labels are currently widely discussed as means to help consumers to make informed food choices. It is hoped that more informed food choices will result in an overall healthier diet. There is only limited evidence, as to which format of a food label is best understood by consumers, helps them best to differentiate between more or less healthy food and whether these changes in perceived healthiness result in changes of food choice.MethodsIn a randomised experimental study in Hamburg/Germany 420 adult subjects were exposed to one of five experimental conditions: (1) a simple "healthy choice" tick, (2) a multiple traffic light label, (3) a monochrome Guideline Daily Amount (GDA) label, (4) a coloured GDA label and (5) a "no label" condition. In the first task they had to identify the healthier food items in 28 pair-wise comparisons of foods from different food groups. In the second task they were asked to select food portions from a range of foods to compose a one-day's consumption. Differences between means were analysed using ANOVAs.ResultsTask I: Experimental conditions differed significantly in the number of correct decisions (p < 0.001). In the condition "no label" subjects had least correct decisions (20.2 ± 3.2), in the traffic light condition most correct decisions were made (24.8 ± 2.4). Task II: Envisaged daily food consumption did not differ significantly between the experimental conditions.ConclusionDifferent food label formats differ in the understanding of consumers. The current study shows, that German adults profit most from the multiple traffic light labels. Perceived healthiness of foods is influenced by this label format most often. Nevertheless, such changes in perceived healthiness are unlikely to influence food choice and consumption. Attempts to establish the informed consumer with the hope that informed choices will be healthier choices are unlikely to change consumer behaviour and will not result in the desired contribution to the prevention of obesity and diet related diseases.

Weight management is a dynamic process, with a pre-treatment phase, a treatment (including process) phase and post-treatment maintenance, and where relapse is possible during both the treatment and maintenance.Variability in the statistical power of the studies concerned, heterogeneity in the definitions, the complexity of obesity and treatment success, the constructs and measures used to predict weight loss maintenance, and an appreciation of who, and how many people achieve it, make prediction difficult.In models of weight loss or maintenance: (i) predictors explain up to 20-30% of the variance; (ii) many predictors are the sum of several small constituent variables, each accounting for a smaller proportion of the variance; (iii) correlational or predictive relationships differ across study populations; (iv) interindividual variability in predictors and correlates of outcomes is high; (v) most of the variance remains unexplained.Greater standardisation of predictive constructs and outcome measures, in more clearly defined study populations, tracked longitudinally, is needed better to predict who sustains weight loss.Treatments need to develop a more individualised approach that is sensitive to patients' needs and individual differences, which requires measuring and predicting patterns of intra-individual behaviour variations associated weight loss and its maintenance. This information will help people shape behaviour change solutions to their own lifestyle needs.3

Objective: Two subscales for the Eating Inventory (Three-Factor Eating Questionnaire) are developed and validated: Rigid and Flexible control of eating behavior. Method: Study I is an analysis of questionnaire data and a 7-day food diary of 54,517 participants in a computer-assisted weight reduction program. Study II is a study of 85 subjects used to develop a final item pool. Study III is a questionnaire survey of a random sample (N = 1,838) from the West German population aged 14 years and above used to validate the developed subscales. Results: Rigid control is associated with higher scores of Disinhibition, with higher body mass index (BMI), and more frequent and more severe binge eating episodes. Flexible control is associated with lower Disinhibition, lower BMI, less frequent and less severe binge eating episodes, lower self-reported energy intake, and a higher probability of successful weight reduction during the 1-year weight reduction program. Discussion: Rigid and flexible control represent distinct aspects of restraint having different relations to disturbed eating patterns and successful weight control.

No abstract

No abstract