Across the globe, dietary habits include the consumption of foods and drinks between main meals. Although often described as "snacks" or "snacking," there is no scientific consensus of what constitutes a snack, either as an eating occasion or as a snack food. Nonetheless, food-based dietary guidelines, compiled at national or regional levels by governments, learned societies, and health organizations, frequently refer to snacking habits and desirable or undesirable snack food choices. This review aims to provide a comprehensive snapshot of snacking recommendations worldwide. From a search of 207 countries and organizations, 49 countries and 7 regional or global organizations were identified that referred to snacks, snack foods, or snacking. A total of 136 snacking-specific recommendations or examples were identified, which varied in nature whereby some provided advice on the quality of the snack food choice and others focused on the frequency or energy and nutrient composition of such snacks. Guidelines varied in terms of the detail of foods and drinks identified, wherein some recommendations focused only on foods or food categories to include (e.g., fruit or dairy) or to exclude (e.g., processed foods), whereas other recommendations made reference to both. Both individual foods (e.g., apples) and food categories (e.g., fruit) were mentioned. Reasons or rationales to support the snacking choices were less frequently identified and varied across regions. It is hoped that this analysis will stimulate discussion on the need for a consensus in the scientific community and beyond with regard to snacking. An agreed-upon definition of snacks, snacking, and snack foods could be used to inform a number of stakeholders and ultimately help consumers adhere to healthful diets as defined locally.

BackgroundSnacking patterns and increased consumption of high fat/sugar food items (HFS) have been proposed as components of an adverse food environment; yet again no clear guidance is available to define their 'optimal' intake. Methods: A systematic literature search was conducted to identify existing recommendations on the consumption of HFS food items and snacks as well as reports documenting the actual consumption patterns in various countries worldwide. Nutritionists from 10 countries were also contacted to provide with a translation of recommendations published in languages other than English. Results: Overall, recommendations on snacking and HFS food items were available in 30 countries. Advice on the consumption of snacks was available in 9 countries suggesting they provide 10‐30% of energy intake (EI). Epidemiological data, on the other hand, shows that currently the percentage of energy obtained from snacks differs substantially between countries and is in the majority of the cases higher than recommended (17.4‐39.8%). Energy contribution of snacks Country Recommendation Target population Reported intake Population Spain 10‐15% EI General Sweden 20% EI General United Kingdom 20% EI General 17.4‐22.7% EI (15.7‐29.6% EI) Adults (Children) Brazil 15% EI General 21% EI General Chile 20% EI Adults USA 10% EI Children 18.4‐20.3% EI (17.0‐23.8% EI) Adults (Children) Italy 10‐14% EI Children Mexico 30% EI Children Canada ‐ ‐ 16.6‐26.5% EI (26.2‐29.6%EI) Adults (Children) Australia ‐ ‐ 28%EI Adults Belgium ‐ ‐ 20‐24% EI General Estonia ‐ ‐ 7% EI Children Finland ‐ ‐ 36.1‐39.8% EI Adults HFS food items were referred to in 25 recommendations but were rarely expressed quantitatively and if so they were highly variable. Consumption patterns are highly different among countries (7‐30.3%) with inconsistencies in the definition of HFS food items being one of the sources of heterogeneity. Energy contribution of HFS food items Country Recommendation Target population Reported intake Population Spain &9occasionally&9 General ‐ ‐ Sweden 13‐14% EI Adults ‐ ‐ United Kingdom &9small amounts&9 General 12.8‐16.2% EI Children Brazil &9avoid&9 General 7% EI General* USA 120‐330Kcal (100‐500 Kcal) General (Children) 11% EI Children Italy &9limit&9 General ‐ ‐ Mexico &9limit General 5.8% EI Adults Canada &9avoid&9 General 18.2‐22.5% EI Children Ireland ‐ ‐ 17.9% EI Children Netherlands &9reduce&9 Adults 15% EI General Australia &9limited&9 Adults 11.1‐15.8% EI General Iran ‐ ‐ 30.3% EI Children* Lebanon ‐ ‐ 6% EI Adults* France &9reduce&9 General ‐ ‐ Denmark &9limit&9 General ‐ ‐ Austria one serving/d General ‐ ‐ Switzerland one serving/day Adults ‐ ‐ Germany &9sparingly&9 General ‐ ‐ Belgium &9occasionally&9 General ‐ ‐ New Zealand &9limit&9 (once/week) General (Children) ‐ ‐ South Africa &9special occasions&9 General ‐ ‐ India &9limit&9 General ‐ ‐ Japan &9moderate General ‐ ‐ Vietnam &9limited&9 General ‐ ‐ Philippines &9limit&9 General ‐ ‐ Saudi Arabia &9limit&9 General ‐ ‐ Singapore added sugars <10% EI General ‐ ‐ South Korea 185‐225 kcal General ‐ ‐ Discussion: Current advice on snacking and the consumption of HFS food items is limited and inconclusive. Based on the recommendations available and the relevant consumption data, reducing energy intake from snacks to 蠄20% EI and limiting HFS food items could improve dietary habits while being aligned with current advice from various bodies.

BackgroundFew nutrient profiling (NP) models have been specifically developed for reformulation purposes.ObjectiveTo compare how the NNPS and Ofcom NP models, respectively designed for reformulation and regulation purposes, classified foods consumed in the US.MethodsThe across‐the‐board Ofcom and the category‐specific NNPS models were applied to all ice creams, pizzas, soups, and yogurts of the USDA SR27 database. Both models have a dichotomous Yes/No outcome. Classification of foods across categories was assessed using chi2 tests. Agreement between the systems was assessed using the kappa statistic, for all foods and by category.ResultsOverall, and in all categories but pizzas, more foods were classified 'Yes' by the Ofcom than by the NNPS (Table). Contrary to the NNPS (p‐chi2=0.59), the Ofcom classified differently the four categories (p<0.01): all yogurts were classified 'Yes' while most pizzas were 'No'. Across all foods, agreement was relatively low between the two systems; it was higher for ice creams and pizzas.Table: Classification of foods according to the NNPS and Ofcom nutrient profiling systems (USDA SR27 data) Food category n % Yes, NNPS % Yes, Ofcom Kappa‐statistic Ice Creams 43 16 28 0.54 Pizzas 75 23 15 0.30 Soups 282 25 72 0.06 Yogurts 25 28 100 N/A Total 425 24 59 0.13 ConclusionIn the assessed food categories, the NNPS model was more inclined to promote reformulation than the Ofcom model. Further research is needed to assess other food categories in which manufactured goods are predominant in the food environment. Confirmatory investigations should focus on food environment from other regions, or for specific target populations.

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BackgroundNutrient profiling (NP) has been mainly used for regulation or food labeling purposes; few systems have been proposed to track food reformulation across a wide range of manufactured foodsObjectiveTo present a category‐specific NP model, the NF score, which aim is to facilitate the tracking of nutritional characteristics of foods; and to show examples of NF score implementationMethodsThe NF score is calculated as an unweighted average of common (energy, added sugars, fructose, sodium, and total, saturated, and trans fats) and category‐specific (e.g. calcium for dairy products, fiber for breads) nutrient ratios (R) calculated per serving: NF score=Average R. For nutrients to limit, R=content/criteria; for nutrients to encourage R=criteria/content. The criteria are category‐specific and linked to public health recommendations, target population (children or adults), and to the role of the food category in the diet. If the food content for one nutrient does not reach the criteria (i.e. R>1), then all Rs蠄1 are set to 1, to ensure that a nutritional weakness cannot be compensated for. Any score above 2 is capped at 2. The final NF score, ranging from 0 to 2, is reversed for a more intuitive reading; any score below 1 indicates that the food has at least one nutritional weakness.ResultsThe NF score was used to assess the evolution of nutritional characteristics of reformulated foods. For all the examples but one, there was an improvement of the NF score (Figure). Improvements for the Cereal bar, Sugar candies, and Pepperoni pizza were also linked to a reduced serving size.imageConclusionsThe NF score allows for a sensitive tracking of food reformulation. Testing the NF score in standard food composition databases should highlight how effective the NF score could be in improving the food environment.