Nutrition professionals' perception of the 'healthiness' of individual foods

OBJECTIVES: This paper describes the development of an online questionnaire for testing nutrition professionals' perceptions of the 'healthiness' of individual foods and the results of administering that questionnaire. The questionnaire was designed to produce a standard ranking of foods that can be used as a tool for testing nutrient profile models. DESIGN: The questionnaire asked respondents to categorise 40 foods (from a master list of 120) in one of six positions, ranging from less to more healthy. The 120 foods were selected to be representative of the British diet. The questionnaire was sent via email to nutrition professionals from the British Dietetic Association and the (British) Nutrition Society. RESULTS: Eight hundred and fifty responses were received. These responses were used to rank the 120 foods by the average score which they received from the nutrition professionals. A regression analysis was also carried out to examine the relationship between the scores awarded by the nutrition professionals and various features of the foods: their nutritional content, their average serving size, their frequency of consumption, whether they were drinks or foods, etc. Nearly 50% of the variance in the average scores was explained by the nutritional content of the foods. When other variables were included in the analysis the percentage of variance that was explained increased to 64%. CONCLUSIONS: The average scores of the foods produce a standard ranking, which can be used as a tool for validating and comparing nutrient profile models. The regression analysis provides some information about how nutrition professionals rank the 'healthiness' of individual foods.     

Testing nutrient profile models using data from a survey of nutrition professionals

OBJECTIVE: To compare nutrient profile models with a standard ranking of 120 foods. DESIGN: Over 700 nutrition professionals were asked to categorise 120 foods into one of six positions on the basis of their healthiness. These categorisations were used to produce a standard ranking of the 120 foods. The standard ranking was compared with the results of applying eight different nutrient profile models to the 120 foods: Models SSCg3d and WXYfm developed for the UK Food Standards Agency, the Nutritious Food Index, the Ratio of Recommended to Restricted nutrients, the Naturally Nutrient Rich score, the Australian Heart Foundation's Tick scheme, the American Heart Association's heart-check mark and the Netherlands tripartite classification model for foods. Rank correlation was assessed for continuous models, and dependence was assessed for categorical models. RESULTS: The continuous models each showed good correlation with the standard ranking (Spearman's rho = 0.6-0.8). The categorical models achieved high chi(2) results, indicating a high level of dependence between the nutrition professionals' and the models' categorisations (P < 0.001). Models SSCg3d and WXYfm achieved higher scores than the other models, implying a greater agreement with the standard ranking of foods. CONCLUSIONS: The results suggest that Models SSCg3d and WXYfm rank and categorise foods in accordance with the views of nutrition professionals.     

Quality of Fiber‐Enriched Spaghetti Containing Microbial Transglutaminase

The effects of transglutaminase (TG) on the properties of semolina dough and pasta cooking properties in durum‐only and fiber‐enriched pasta were investigated. TG was blended at levels 0, 0.05, 0.1, 0.25, 0.5, and 1% of semolina weight with semolina and semolina‐pollard (60% w/w) and semolina‐guar gum (15%) mixtures. The addition of TG increased dough maximal resistance, making the dough inextensible at >1%. Optimum effects on dough strength were obtained at 0.5% TG; this dough gave the firmest and least sticky pasta. A more extensive and thicker protein matrix was observed in the TG pasta by confocal scanning laser microscopy, indicating more cross‐links were formed, a finding supported by measuring percentage of unextracted polymeric protein. TG was unable to overcome the negative effect of 60% pollard on cooking loss or 15% guar gum on stickiness. Gluten was generally more effective than TG in restoring the properties of pastas with added fiber.     

Photonic crystal light collectors in fish retina improve vision in turbid water

Despite their diversity, vertebrate retinae are specialized to maximize either photon catch or visual acuity. Here, we describe a functional type that is optimized for neither purpose. In the retina of the elephantnose fish (Gnathonemus petersii), cone photoreceptors are grouped together within reflecting, photonic crystal-lined cups acting as macroreceptors, but rod photoreceptors are positioned behind these reflectors. This unusual arrangement matches rod and cone sensitivity for detecting color-mixed stimuli, whereas the photoreceptor grouping renders the fish insensitive to spatial noise; together, this enables more reliable flight reactions in the fish's dim and turbid habitat as compared with fish lacking this retinal specialization.     

Continental-scale effects of nutrient pollution on stream ecosystem functioning

Excessive nutrient loading is a major threat to aquatic ecosystems worldwide that leads to profound changes in aquatic biodiversity and biogeochemical processes. Systematic quantitative assessment of functional ecosystem measures for river networks is, however, lacking, especially at continental scales. Here, we narrow this gap by means of a pan-European field experiment on a fundamental ecosystem process--leaf-litter breakdown--in 100 streams across a greater than 1000-fold nutrient gradient. Dramatically slowed breakdown at both extremes of the gradient indicated strong nutrient limitation in unaffected systems, potential for strong stimulation in moderately altered systems, and inhibition in highly polluted streams. This large-scale response pattern emphasizes the need to complement established structural approaches (such as water chemistry, hydrogeomorphology, and biological diversity metrics) with functional measures (such as litter-breakdown rate, whole-system metabolism, and nutrient spiraling) for assessing ecosystem health.