Abstract
Background
The high availability and marketing of unhealthy foods has contributed to unhealthy diets. Unhealthy diets are a major risk factor for a range of non-communicable diseases (NCDs). However, the availability and marketing of pre-packaged foods haven’t been assessed in Senegal. Nutrient profiling models have been developed to identify less healthy foods that could be subject to marketing restrictions, particularly when targeted at children. The aim of this study was to assess the nutritional quality and on-pack promotion of pre-packaged food sold in major supermarkets in Senegal using the Nutrient Profile Model for the WHO African Region (NPM-WHO/AR), the Nutri-Score labelling system and the NOVA classification.
Methods
A cross-sectional survey was conducted in two major supermarkets in Dakar between August and September 2021. Data were collected for all pre-packaged foods, with the exception of the fresh food and alcoholic beverages categories. Pre-packaged foods were classified into fifteen food categories and five beverage categories according to the NPM-WHO/AR, with the exception of the categories “fresh and frozen meat, fish and sea food” and “fresh and frozen fruits and vegetables, legumes and tubers”. Nutritional information was extracted from product labels and products were evaluated using 3 classification systems: NPM-WHO/AR, Nova classification as an indicator of the degree of food processing and Nutri-Score, a nutritional labelling system based on a 5-colour scale from dark green to red, associated with letters ranging from A (high nutritional quality) to E (low nutritional quality), established according to nutritional value and fruits, vegetables and legumes content. Depending on the classification system used, foods were rated on the basis of the nutritional information declared as relevant for this rating. Thus, 5,542 products were evaluated for their nutritional composition, 5,280 products were evaluated according to the NPM-WHO/AR and 5,407 products were evaluated according to both the Nutri-Score and the Nova classification. A pre-packaged food was classified as “non-permitted” to be marketed to children if the content of defined nutrients exceeded the threshold set in the model for the corresponding product category. Data analysis was performed using RStudio.
Results
Ultra-processed foods (71.1%) and processed foods (18.8%) were the most common in Senegalese supermarkets. According to the Nutri-Score, pre-packaged foods were most frequently classified as Nutri-Score D (24.4%) and Nutri-Score E (22.1%). Almost 63.3% of the products were classified as non-permitted to be marketed to children according to the NPM-WHO/AR. Of these foods, 12.5% had on-pack promotions. Non-permitted foods to be marketed to children with the highest number of on-pack promotions were “breakfast cereals” (50.0%), “chocolate and sugar confectionery” (31.3%), “milk and dairy based drinks” (28.1%) and “cakes, sweet biscuits and pastries” (17.7%). However, the comparison between the NPM-WHO/AR and the Nutri-Score showed that some NPM-WHO/AR prohibited foods were classified into Nutri-Score A and B.
Conclusions
This study shows that pre-packaged foods available in major supermarkets in Senegal are predominantly non-permitted to be marketed to children. In the context of increasing levels of obesity and diet-related NCDs, effective policies should be established to regulate the promotion of these foods.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-22295-1.
Keywords: Pre-packaged foods, Nutritional quality, On-pack promotion, Supermarkets, Senegal
Background
Unhealthy diets are one of the main risk factors for a range of non-communicable diseases (NCDs), such as obesity, cardiovascular diseases, diabetes mellitus, chronic respiratory diseases and various types of cancer [1, 2]. The aforementioned NCDs are responsible for 45% of premature deaths in Senegal [3]. Although obesity is more common in high-income countries, it has increased in many low-and middle-income countries, particularly among urban populations [4]. According to the Global Nutrition Report (2021), 15.1% of adult women and 4.8% of adult men in Senegal were living with obesity in 2019. At the same time, the prevalence of overweight and obesity in children and adolescents aged 5–19 years are estimated to affect 11.7% of boys and 6% of girls.
In recent decades, diets have undergone tremendous changes due to the modernization of food systems. This has resulted in an increase in the availability and affordability of ultra-processed foods and beverages (UPFs), which are often high in energy, fat, saturated fat, added sugars, salt and/or sodium [5–7]. Globally and in Africa, the food supply is increasingly dominated by UPFs products [8]. Due to the evidence linking UPFs to poor diet quality, pre-packaged foods manufacturers are collectively considered a major driver of the NCDs epidemic [9]. Scientific evidence supports the overconsumption of UPFs in the development of obesity and NCDs [10–14]. Among the various factors contributing to overweight, obesity and diet-related diseases, the promotion of UPFs has been shown to have a negative impact, particularly among children [15]. Aggressive marketing of such foods, often accompanied by health and nutrition claims, can obscure potential harms and drive and distort consumer demand. Research has shown that the majority of products advertised to children and adolescents are of low nutritional value [16].
Together, these factors shape policy and public opinion on NCDs prevention. An important way to improve health and prevent obesity and NCDs is to focus on reducing associated risk factors [17]. Policies that alter the food environments can influence consumer behaviors towards healthy food choices and/or incentivize food manufacturers to improve the nutritional quality of their products. A range of priority actions have been recommended by WHO, including government regulations, such as mandatory sugar limits in foods; fiscal policies, such as taxes on beverages with added sugars; food marketing regulations, such as mandatory nutrient declaration by manufacturers; and promotion of healthier foods for infants and young children. However, governments are generally not taking a comprehensive approach in this area and policy measures are limited [18, 19]. In 2004, WHO recommended that the food industry limit the levels of critical nutrients in their pre-packaged food and introduce new products with better nutritional quality to ensure that consumers can access healthy food choices through manufacturers’ product portfolios [20]. In direct response, some leading companies have reported some improvements in their product portfolios through self-regulation, but most are not taking strong measures, pointing towards the need for government regulations. Nutrient profiling systems have been developed as a method of assessing the nutritional quality of foods and beverages according to their energy content and nutrient composition, and underpin a wide range of food policies, including food reformulation, food labelling, child-directed marketing restrictions and school nutrition standards [21, 22]. The WHO has developed a nutrient profile model for the African Region to support countries in controlling obesogenic food environments and promoting healthy diets, with a focus on protecting children from marketing of unhealthy foods and non-alcoholic beverages. Specific thresholds for energy and critical nutrients are defined for each major food category according to their recommended dietary targets for the prevention of obesity and related NCDs, as well as guidelines for sugar and salt. Non-compliance (intake above the threshold) for a single nutrient makes the food or beverage unsuitable for advertising to children.
However, no studies have examined the healthfulness of products available on the market through major supermarkets in Senegal. Therefore, the objective of this study was to assess the nutritional quality and on-pack promotion of pre-packaged foods sold in major supermarkets in Senegal, using the WHO Nutrient Profile Model for the African Region (NPM-WHO/AR), the Nutri-Score labelling system and the NOVA classification.
Methods
Study design
A cross-sectional survey was conducted between August and September 2021 in two large supermarket chains (Auchan and Exclusive) in Dakar, the capital city in which the largest urban population in Senegal is concentrated. These chains are among the most frequented by the Senegalese population, given the wide range of products available. With thirty-five (35) stores and one drive, Auchan is the uncontested leader of modern food retailing in Senegal. The methodological framework proposed by INFORMAS (International Network for Food and Obesity/non-communicable diseases, Research, Monitoring and Action Support) to assess nutritional composition and food promotion [23, 24] was used in the conceptualization of this study.
Data collection
Data collection was carried out by 6 interviewers, 5 of whom were nutritionists. The interviewers were initially trained on two consecutive days on the data collection tool and also took part in a pre-test of the tool. Only pre-packaged food and non-alcoholic beverages were collected in the stores. Data were collected using a tablet with the Open Data Kit collect (ODK). All sides of packaged food products were photographed to capture all the information on the package. Product-related information was collected separately using a questionnaire. For each packaged product, data collected included the product name, brand and nutritional information (energy density, carbohydrates, total sugars, protein, fat, saturated fat, trans fat, salt and sodium content). The nutrient information was collected per 100 g or 100 ml of each product from the nutrient declarations on the product labels. As the nutritional composition of the same food in a different pack size remains unchanged, only one format (pack size) of the same product was recorded. However, all flavours of the same food brand were collected. Each product was sampled only once and the barcode was checked to see if it had been found already elsewhere in the other supermarket. In addition, where the nutritional composition of the food was presented by portion or by net weight or volume of the food, additional calculations were made to find the equivalent for 100 g/ml of the food.
Promotional features and premium offers observed on product packaging were also recorded. These promotional aspects included: mascots (cartoon characters, brand mascots, superheroes), licensed characters (e.g., Barbie), celebrities, drawings or text related to children or their characteristics, primes (physical or virtual gifts for children such as games on the packaging or online games), price discount, game contest, bonus, etc.).
Food categorization
All pre-packaged foods in supermarkets were included, with the exception of unpackaged fresh foods and alcoholic beverages. Pre-packaged foods were classified into fifteen (15) food categories and five (5) beverage subcategories according to the NPM-WHO/AR (excluding the categories “Fresh and frozen meat, fish and seafood” and “Fresh and frozen fruit and vegetables, pulses and tubers”). The following categories and subcategories “Food for special dietary uses” (infants’ formula and dietary supplements), “Herbs and spices”, “Sugar, honey and related products”, “Salt and monosodium glutamate” were excluded from all analyses as they are not included in the NPM-WHO/AR.
The categories and sub-categories included in this study were 1a) Cakes, sweet biscuits and pastries, 1b) Bread and crisp bread, 2a) Savoury snacks Potato, cereal or starch-based 2b) Processed nuts, edible seeds, 3) Beverages, 4) Breakfast cereals, 5) Chocolate and sugar confectionery, 6) Cheese, 7) Yoghurt, ice cream and sorbets, 8) Flan, custard, 9) Ready-made and convenience foods, 10) Butter, oils and emulsions, 11) Pasta, noodles, rice, 12) Processed meats, 13) Processed fish and seafood products, 14) Processed fruits and vegetables, 15) Sauces, dips and dressings. The category ‘‘Beverages’’ is disaggregated into 5 sub-categories, including “Juices”, “Milk and dairy based drinks”, “Energy drinks”, “Coffee, tea, herbal infusions” and “Cereals, legumes, grain beverages”. The description of the food categories is shown in Table S1.
Pre-packaged foods assessed across each classification system
Depending on the classification system used, foods were evaluated on the basis of the declaration of nutritional information deemed relevant for this assessment. Figure 1 shows the number of pre-packaged foods evaluated in each classification system after applying the inclusion and exclusion criteria.
Fig. 1.
Flowchart of sample size representing initial and final number dataset that used in the present study
Assessment of nutritional quality of pre-packaged food
According to extent of processing
After analyzing each component in the ingredient list, all pre-packaged foods were categorized into four (4) groups according to their level of processing, as defined by the NOVA classification system: (1) unprocessed or minimally processed foods; (2) processed culinary ingredients; (3) processed foods (PFs); and (4) ultra-processed foods (UPFs) [25].
According to nutrient and energy values
The calories, fat, saturated fat, total sugars, salt and sodium content of the products per 100 g or 100 ml were examined. Medians and interquartile ranges were calculated for energy and nutrient content by category and subcategory.
According to the Nutri-Score
The nutritional quality of the foods was determined using the official Nutri-Score 2021 calculation tool provided by the French National Health Agency. Nutri-Score is a front-of-pack nutritional label applied in various countries in Europe that translates the nutritional quality of a product into a five-letter code A, B, C, D and E, with each letter corresponding to a different colour (group A includes scores between −15 and −1, group B between 0 and 2, group C between 3 and 10, group D between 11 and 18 and group E between 19 and 40). The letters A and B correspond to products with a high nutritional profile, while the letters D and E correspond to products with a low nutritional profile. The Nutri-Score system assigns a series of positive and negative points to each product based on its energy and nutrient content and the ingredients used in its manufacture [saturated fat, sugar, sodium, fibre, protein and fruits, vegetables, legumes and nuts (FVLN)] per 100 g or 100 ml, with slight variations for beverages and oils or solid fats. Positive points are given for the amounts of elements that should be limited, including energy, total sugars, saturated fat and sodium (0 to 10 positive points for each). Negative points are then assigned for the amount of elements that should be encouraged, including FVLN, fibre and protein (0 to 5 negative points for each).
The Nutri-Score is calculated based on the values provided in the Nutrition Facts table. The first step was to select the category to which the product belongs (generally cheese, added fats or beverages). The nutritional values of the product were then entered: calories (KJ), saturated fat (g), sugar (g), protein (g), fibre (g) and salt (g). Sodium values were given in mg. In the specific case of beverages, the first step was to indicate whether the product was a water by selecting “YES” or “NO” from the drop-down menu. However, only natural waters fall into this category. Flavoured waters (with or without sweeteners) were considered as sweetened beverages.
According to the Nutrient Profile Model for the WHO African region
Nutrient profiling was used to classify foods according to their nutrient composition. This study used the NPM-WHO/AR to assess the nutritional quality of pre-packaged foods. The nutrients for which thresholds have been set are total fat, saturated fat, total sugars, added sugars, sodium and energy, taking into account the nutrients that should be limited according to their relevance for the category. Unless otherwise stated, a food is considered to be “excessive” in one or more critical nutrients if its relative content is higher than the corresponding maximum level recommended in the salt or sugar guidelines and the WHO population nutrient intake targets.
The respective thresholds in the Nutrient Profile Model were used to determine the proportion of packaged foods that exceeded the criteria overall and in each food category. A pre-packaged food was classified as “non-permitted” to be marketed to children if the content of any defined nutrient exceeded the threshold set in the model for the corresponding product category, and in such a case, the pre-packaged food was classified as “permitted” to be marketed to children.
Statistical analyses
Energy, fat, saturated fat, total sugars, salt and sodium were analyzed per 100 g or 100 ml. Medians and interquartile ranges were calculated for energy and nutrient content by category and subcategory. Nutrient profiling was carried out on the products with nutrient values for the thresholds set in the model. The availability of “permitted” and “non-permitted” foods to be marketed to children was also calculated overall and by category.
The relationship between the two categorical variables classifying foods, NOVA and Nutri-Score, was described by simple correspondence analysis. Data analyses were performed using RStudio version 2022.07.2.
Results
Degree of processing pre-packaged foods by food categories
A total of 1,037 products (16.1%) for which the list of ingredients and/or the nutritional values were not provided, were excluded from this analysis. The degree of processing analysis was carried out on 5,407 pre-packaged foods and is presented by each food category in Table 1. The category with the highest proportion of products was “Beverages” (19.3%), followed by “Bread and bakery products” (14.3%) and “Processed fruits, vegetables and legumes” (11.9%).
Table 1.
Degree of processing of pre-packaged foods by category
| Food categories | n (%) | Unprocessed food n (%) |
Processed culinary ingredient | PFs n (%) |
UPFs n (%) |
|---|---|---|---|---|---|
| Bread and bakery products | |||||
| a) Cakes, sweet biscuits and pastries | 746 | 3 (0.4) | 0 (0.0) | 1 (0.1) | 742 (99.5) |
| b) Bread and crisp bread | 125 | 5 (4.0) | 0 (0.0) | 6 (4.8) | 114 (91.2) |
| Savoury snack foods | |||||
| a) Savoury snacks Potato, cereal or starch-based | 235 | 41 (17.4) | 0 (0.0) | 10 (4.3) | 184 (78.3) |
| b) Processed nuts, edible seeds | 67 | 34 (50.7) | 0 (0.0) | 15 (22.4) | 18 (26.9) |
| Beverages | |||||
| a) Juices | 295 | 34 (11.5) | 0 (0.0) | 129 (43.7) | 132 (44.7) |
| b) Milk and dairy based drinks | 74 | 22 (29.7) | 0 (0.0) | 2 (2.7) | 50 (67.6) |
| c) Energy drink | 314 | 6 (1.9) | 0 (0.0) | 31 (9.9) | 277 (88.2) |
| d) Coffee, tea, herbal infusion | 149 | 36 (24.2) | 0 (0.0) | 33 (22.1) | 80 (53.7) |
| e) Cereal, legumes, grain beverages | 32 | 0 (0.0) | 0 (0.0) | 4 (12.5) | 28 (87.5) |
| Breakfast cereals | 112 | 14 (12.5) | 0 (0.0) | 29 (25.9) | 69 (61.6) |
| Chocolate and sugar confectionery | 432 | 0 (0.0) | 0 (0.0) | 1 (0.2) | 431 (99.8) |
| Cheese | 110 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 110 (100.0) |
| Frozen yoghurt, ice cream and sorbets | 125 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 125 (100.0) |
| Flan, custard, yoghurt | 112 | 2 (1.8) | 0 (0.0) | 1 (0.9) | 109 (97.3) |
| Ready-made and convenience foods | 377 | 0 (0.0) | 0 (0.0) | 86 (22.8) | 291 (77.2) |
| Butter, oils and emulsions | 53 | 0 (0.0) | 42 (79.2) | 0 (0.0) | 11 (20.8) |
| Pasta, noodles, rice | 450 | 225 (50.0) | 0 (0.0) | 28 (6.2) | 197 (43.8) |
| Processed meats | 174 | 4 (2.3) | 0 (0.0) | 24 (13.8) | 146 (83.9) |
| Processed fish and seafood products | 233 | 3 (1.3) | 0 (0.0) | 156 (67.0) | 74 (31.8) |
| Processed fruits, vegetables and legumes | 679 | 72 (10.6) | 2 (0.3) | 347 (51.1) | 258 (38.0) |
| Sauces, dips and dressings | 513 | 1 (0.2) | 0 (0.0) | 114 (22.2) | 398 (77.6) |
| All | 5 407 | 502 (9.3) | 44 (0.8) | 1 017 (18.8) | 3 844 (71.1) |
n represents products with both Nutrition Information Panel (NIP) and ingredient list by food category
Our results show that the majority of the pre-packaged foods were classified as UPFs and PFs according to the NOVA classification. The proportions of UPFs and PFs were 71.1% and 18.8%, respectively. Minimally processed foods were most frequently observed in the categories “pasta, noodles, rice” (50.0%) and “processed nuts, edible seeds” (50.7%). High proportions of PFs were observed in the categories “processed fish and seafood products” (67.0%), “processed fruits, vegetables and legumes” (51.1%) and “juices” (43.7%). The highest proportions of UPFs were found in the categories “cheese” and “frozen yoghurt, ice cream and sorbet”, where 100% of the products were ultra-processed, followed by “chocolate and sugar confectionery” (99.8%) and “cakes, sweet biscuits and pastries” (99.5%). Conversely, lower proportions of UPFs were found in the categories “butter, oils and emulsions (20.8%), “processed nuts, edible seeds” (26.9%) and “processed fish and seafood products” (31.8%).
Median energy and nutrient values by food categories
Of the 6,444 products, 902 (14.0%) did not provide nutritional information on their packaging and were excluded from the nutrient analysis. As the nutrient data were not normally distributed, the median (IQR) of the energy, total fat, saturated fat, total sugar, salt and sodium content was calculated for each category. The median energy and nutrient values by category are shown in Table 2.
Table 2.
Median values of energy, total fat, saturated fat, total sugar, salt and sodium per 100 g or 100 ml
| Foods categories | Number of productsa | Energy (Kcal/100 g) |
Total Fat (g/100 g) |
Saturated fat (g/100 g) |
Total sugar (g/100 g) |
Salt (g/100 g) |
Sodium (g/100 g) |
|---|---|---|---|---|---|---|---|
| Bread and bakery products | |||||||
| a) Cakes, sweet biscuits, pastries | 748 | 468 [431–499] | 19 [13–24] | 8.3 [3.5–13] | 29.3 [21.3–35.3] | 0.6 [0.4–0.8] | 0.2 [0.1–0.3] |
| b) Bread and crisp bread | 128 | 384 [348–402] | 4,9 [2.4–8.7] | 0.6 [0.4–2.2] | 6.4 [2.1–10.0] | 1.1 [0.4–1.6] | 0.7 [0.1–1.1] |
| Savoury snack foods | |||||||
| a) Savoury snacks Potato, cereal | 236 | 504 [474.5–539] | 27 [21–33] | 5.3 [2.5–13] | 2.8 [1.4–5.6] | 1.6 [1.3–2.1] | 0.7 [0.5–0.9] |
| b) Processed nuts, edible seeds | 68 | 565 [499.4–609.8] | 47.8 [34.8–53.1] | 5.3 [4.1–6.5] | 5.0 [4.7–9] | 0.1 [0.0–1.0] | 0.3 [0.0–0.8] |
| Beverages | |||||||
| a) Fruit and vegetables juices | 309 | 47 [41–52] | 0 [0–0.5] | 0 [0–0.1] | 10.5 [8.7–12] | 0.0 [0.0–0.0] | 0.0 [0.0–0.01] |
| b) Milk and dairy based drinks | 90 | 66.1 [46.3–162] | 3.5 [1.5–8] | 2.2 [0.8–4.2] | 5 [4.8–10.3] | 0.1 [0.1–0.2] | 0.0 [0.0–0.1] |
| c) Energy drink | 315 | 47 [28.7–287.8] | 0.1 [0–0.5] | 0.1 [0–0.1] | 9.8 [4.9–70] | 0.0 [0.0–0.1] | 0.01 [0.0–0.02] |
| d) Coffee, tea, herbal infusion | 158 | 26 [2–356] | 0.2 [0–2.1] | 0.0 [0–0.9] | 3.4 [0.0–9.5] | 0.0 [0.0–0.2] | 0 [0–0.1] |
| e) Cereal, legumes, grain beverages | 32 | 42 [25–39.3] | 1.5 [1.2–1.9] | 0.3 [0.1–0.3] | 3.3 [1.9–4.5] | 0.1 [0.1–0.1] | - |
| Breakfast cereals | 113 | 386 [375–422] | 4,1 [1.9–11.7] | 0.9 [0.5–2.5] | 19.2 [12.3–25] | 0.4 [0.2–0.8] | 0.1 [0.0–0.3] |
| Chocolate and sugar confectionery | 433 | 410.4 [351–532.2] | 8.9 [0.5–31] | 4.7 [0.1–16] | 53.1 [42.7–62] | 0.1 [0.0–0.3] | 0.0 [0.0–0.1] |
| Cheese | 122 | 316 [255–366] | 27 [21–30] | 17.3 [13.4–20] | 0.6 [0.3–3] | 1.5 [1.1–2.1] | 0.4 [0.4–0.7] |
| Frozen yoghurt, ice cream and sorbets | 125 | 211 [125.8–282.8] | 11 [1.5–18] | 7.4 [1–11] | 24 [17.3–27] | 0.0 [0.1–0.2] | - |
| Flan, custard | 113 | 303 [135–369] | 3,4 [1.4–23.7] | 2 [0.1–20] | 11 [3.1–23] | 0.1 [0.1–0.2] | 0.0 [0.0–0.1] |
| Ready-made and convenience foods | 377 | 134.5 [90–240] | 5.0 [2.8–10] | 1.5 [0.7–3.3] | 1.9 [0.9–3.3] | 0.9 [0.7–1.3] | 0.4 [0.3–2.0] |
| Butter, oils and emulsions | 72 | 884.3 [744–900] | 99 [82–100] | 13.7 [10.9–16.5] | 0.6 [0.5–3.4] | 0.0 [0.0–0.5] | 0.4 [0.4–0.4] |
| Pasta, noodles, rice | 488 | 356 [349–369] | 2 [1.5–4.1] | 0.4 [0.3–1.2] | 2.7 [0.6–3.7] | 0.0 [0.0–0.7] | 0.0 [0.0–0.1] |
| Processed meats | 175 | 264 [207.2–346.5] | 20.2 [14.8–30] | 7.8 [5.2–11.6] | 0.7 [0.5–1.1] | 2.5 [1.7–4.0] | 0.7 [0.6–0.8] |
| Processed fish and seafood products | 234 | 201 [137–244] | 12.3 [6.9–17.1] | 2.5 [1–3.5] | 0.5 [0.5–1.1] | 1 [0.9–1.2] | 0.5 [0.4–1.1] |
| Processed fruits, vegetables, legumes | 692 | 64 [29–165] | 0.5 [0.3–1] | 0.1 [0.1–0.3] | 3.4 [0.9–12] | 0.5 [0.0–0.7] | 0.3 [0.1–0.9] |
| Sauces, dips and dressings | 514 | 151.9 [73–304.8] | 4.5 [0.6–24.0] | 0.7 [0.1–3.7] | 5.5 [2.7–11.3] | 1.8 [1.0–4] | 1.8 [1.0–6.3] |
| All foods | 5542 | 284 [80–416] | 4.4 [0.5–19.4] | 1.3 [0.1–6.0] | 5.6 [1.5–25.0] | 0.9 [0.5–1.5] | 0.1 [0.0–0.5] |
aNumber of products with nutritional information. Median (IQR) values are presented per sub-category for 100g or 100ml of packaged food. IQR Interquartile range
The results show that the energy and nutrient values varied significantly by food category. The top 5 food categories with the highest energy density per 100 g were “butter, oils and emulsions” (median 884.3 kcal [744–900]), “processed nuts, edible seeds” (565 kcal [499.4–609.8]), “savoury snacks Potato, cereal or starch-based” (504 kcal [474.5–539]), “cakes, sweet biscuits and pastries” (468 kcal [431–499]), and “chocolate and sugar confectionery” (410.4 kcal [351–532.2]). For total fat, the highest median values were found in the category “butter, oils and emulsions” (99 g/100 g [82–100]), followed by “processed nuts, edible seeds” (47.8 g/100 g [34.8–53.1]) and “cheese” (27 g/100 g [21–30]). The median values for saturated fat were mainly higher in the category “cheese” (17.3 g [13.4–20]), followed by “butter, oils and emulsions” (13.7 g [10.9–16.5]), “cakes, sweet biscuits and pastries” (8.3 g [3.5–13]) and “processed meats” (7.8 g [5.2–11.6]).
The highest contents of total sugar were found in “chocolate and sugar confectionery” (53.1 g/100 g [42.7–62]), “cakes, sweet biscuits and pastries” (29.3 g/100 g [21.3–35.3]), “frozen yoghurt, ice cream and sorbets” (24 g/100 g [17.3–27]). and “breakfast cereals” (19.2 g/100 g [12.3–25]). The highest salt levels were found in “processed meats” (2.5 g [1.7–4.0]), “sauces, dips and dressings” (1.8 g [1–0.4]), “savoury snacks Potato, cereal or starch-based” (1.6 g [1.3–2.1]) and “cheese” (1.5 g [1.1–2.1]).
However, the following 3 categories: “cakes, sweet biscuits and pastries”, “savoury snack foods” and “chocolate and sugar confectionery” had excessive levels of at least three nutrients.
For sodium, the median values were mostly higher in the categories “sauces, dips and dressings” (1.8 g/100 g [1.0–6.3]), and for “processed meats” and “bread and crisp bread” (0.7 g/100 g each).
Nutritional quality according to the Nutri-Score labelling system
The nutritional quality according to the Nutri-Score by food category is shown in Table 3. The results are displayed for foods with both the ingredients list and the nutritional values. According to the Nutri-Score, the most common category was D (24.4%), followed by E and A with 22.1% and 20.9% respectively.
Table 3.
Distribution of each foods category according to Nutri-Score
| Foods categories | n (%) | Nutri-Score A n (%) |
Nutri-Score B n (%) |
Nutri-Score C n (%) |
Nutri-Score D n (%) |
Nutri-Score E n (%) |
|---|---|---|---|---|---|---|
| Bread and bakery products | ||||||
| a) Cakes, sweet biscuits and pastries | 746 (95.4) | 9 (0.1) | 50 (5.5) | 97 (11.5) | 216 (16.4) | 374 (31.2) |
| b) Bread and crisp bread | 125 (89.9) | 29 (2.6) | 23 (2.5) | 30 (3.5) | 37 (2.8) | 6 (0.5) |
| Savoury snack foods | ||||||
| a) Savoury snacks Potato, cereal or starch-based | 235 (80.5) | 2 (2.6) | 9 (1.0) | 48 (5.7) | 102 (7.7) | 74 (6.2) |
| b) Processed nuts, edible seeds | 67 (69.1) | 4 (0.4) | 8 (0.9) | 28 (3.3) | 24 (1.8) | 3 (0.3) |
| Beverages | ||||||
| a) Juices | 295 (85.3) | 0 (0.0) | 2 (0.2) | 12 (1.4) | 61 (4.6) | 219 (0.2) |
| b) Milk and dairy based drinks | 74 (74.7) | 18 (1.6) | 26 (2.9) | 13 (1.5) | 10 (0.8) | 7 (0.6) |
| c) Energy drink | 314 (91.5) | 8 (0.7) | 22 (0.2) | 28 (3.3) | 54 (4.1) | 201 (16.8) |
| d) Coffee, tea, herbal infusion | 149 (35.0) | 0 (0.0) | 37 (4.1) | 30 (3.5) | 25 (1.9) | 54 (4.5) |
| e) Cereal, legumes, grain beverages | 32 (100.0) | 7 (0.6) | 25 (2.7) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| Breakfast cereals | 112 (99.1) | 24 (2.1) | 21 (2.3) | 50 (5.9) | 16 (1.2) | 1 (0.1) |
| Chocolate and sugar confectionery | 432 (95.4) | 10 (0.9) | 38 (4.2) | 15 (1.8) | 173 (13.1) | 195 (16.3) |
| Cheese | 110 (80.3) | 3 (0.3) | 0 (0.0) | 6 (0.7) | 84 (6.4) | 16 (1.4) |
| Frozen yoghurt, ice cream and sorbets | 125 (71.8) | 3 (0.3) | 0 (0.0) | 6 (0.7) | 84 (6.4) | 16 (1.3) |
| Flan, custard, yoghurt | 112 (70.9) | 3 (0.3) | 15 (1.6) | 28 (3.3) | 65 (4.9) | 2 (0.2) |
| Ready-made and convenience foods | 377 (95.9) | 206 (18.2) | 113 (12.4) | 23 (2.7) | 30 (2.3) | 6 (0.5) |
| Butter, oils and emulsions | 53 (55.2) | 0 (0.0) | 1 (0.1) | 12 (1.4) | 33 (2.5) | 8 (0.7) |
| Pasta, noodles, rice | 450 (86.5) | 325 (28.7) | 76 (8.4) | 30 (3.5) | 12 (0.9) | 4 (0.3) |
| Processed meats | 174 (70.2) | 16 (1.4) | 32 (3.5) | 40 (4.7) | 84 (6.4) | 1 (0.1) |
| Processed fish and seafood products | 233 (89.3) | 138 (12.2) | 71 (7.8) | 12 (1.4) | 13 (1.0) | 0 (0.0) |
| Processed fruits, vegetables and legumes | 679 (88.3) | 219 (19.4) | 206 (22.6) | 125 (14.7) | 130 (9.8) | 4 (0.3) |
| Sauces, dips and dressings | 513 (90.6) | 100 (8.8) | 117 (12.9) | 189 (22.3) | 104 (7.9) | 3 (0.3) |
| All | 5 407 | 1131 (20.9) | 910 (16.8) | 847 (15.7) | 1 320 (24.4) | 1 197 (22.1) |
The food categories that most represented Nutri-Score group A were “pasta, noodles, rices” (28.7%), followed by “processed fruits, vegetables and legumes” (19.4%) and “ready meals and convenience foods” (18.2%). For Nutri-Score B, the most common categories were “processed fruits, vegetables and legumes” (22.6%), followed by “sauces, dips and dressings” (12.9%) and “ready-made and convenience foods” (12.4%). Nutri-Score C was more represented in the “sauces, dips and dressings” category (22.3%). Nutri-Score D and E were more represented in the categories “cakes, sweet biscuits and pastries” and “chocolate and sugar confectionery”.
Proportion of products not meeting energy and nutrient content according to NPM-WHO/AR
The proportion of packaged foods exceeding the threshold set in the nutrient profile model is shown in Table 4. Overall, the results show that exceeding the threshold was most common for total sugars and energy (almost 90% of non-compliant products), followed by non-compliance for total fat (approximately 50% of non-compliant products). The proportion of non-compliant products for more than one nutrient was more pronounced for “savoury snacks Potato, cereal or starch-based”, followed by “cakes, sweet biscuits and pastries” and “processed meats”. Overall, 100% of the products were non-compliant for energy in the category “savoury snacks potato, cereal”. For total sugars, approximately 95% of products were non-compliant in the categories “yoghurt, ice cream and sorbets” and “energy drinks”. For fat and saturated fat, non-compliance was more pronounced for “savoury snacks Potato, cereal or starch-based” (95.8% of non-compliant products for fat) and “processed meats” (almost 93% of non-compliant products for fat and saturated fat).
Table 4.
Compliance with the WHO Nutrient Profile thresholds
| Foods categories | N | Mention energy (n) |
Non-Compliant products n (%) |
Mention fat (n) |
Non-Compliant products n (%) |
Mention saturated fat (n) |
Non-Compliant products n (%) |
Mention total sugar |
Non-Compliant products n (%) |
Mention sodium (n) |
Non-Compliant products n (%) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Bread and bakery products | |||||||||||
| a) Cakes, sweet biscuits and pastries | 748 | 747 | 709 (94.9) | 748 | 654 (87.4) | 713 | - | 723 | 641 (88.7) | 139 | 55 (39.6) |
| b) Bread and crisp bread | 128 | 125 | - | 128 | 35 (27.3) | 103 | - | 106 | 55 (51.9) | 24 | 14 (58.3) |
| Savoury snack foods | |||||||||||
| a) Savoury snacks Potato, cereal or starch-based | 236 | 236 | 236 (100) | 236 | 226 (95.8) | 220 | - | 277 | - | 65 | 64 (98.5) |
| b) Processed nuts, edible seeds | 68 | 68 | - | 68 | - | 55 | - | 61 | - | 17 | 12 (70.6) |
| Beverages | |||||||||||
| a) Juices | 309 | 308 | - | 295 | - | 260 | - | 267 | 232 (86.9) | 78 | 3 (3.8) |
| b) Milk and dairy based drinks | 90 | 86 | - | 90 | 32 (35.5) | 63 | - | 64 | - | 20 | |
| c) Energy drink | 315 | 314 | - | 273 | - | 212 | - | 287 | 273 (95.1) | 59 | 4 (6.8) |
| d) Coffee, tea, herbal infusion | 158 | 153 | - | 149 | - | 126 | - | 133 | 101 (75.9) | 30 | |
| e) Cereal, legumes, grain beverages | 32 | 32 | - | 32 | - | 32 | - | 32 | 2 (6.3) | 0 | - |
| Breakfast cereals | 113 | 113 | - | 113 | 28 (24.8) | 113 | - | 113 | 89 (78.8) | 7 | 2 (28.6) |
| Chocolate and sugar confectionery | 433 | 432 | 396 (91.7) | 431 | 218 (50.6) | 418 | - | 419 | 376 (89.7) | 73 | |
| Cheese | 122 | 121 | - | 121 | 96 (79.3) | 119 | - | 119 | - | 3 | 1 (33.3) |
| Yoghurt, ice cream and sorbets | 125 | 125 | 59 (47.2) | 125 | 83 (66.4) | 109 | - | 113 | 108 (95.6) | 4 | 4 (100) |
| Flan, custard | 113 | 98 | 70 (71.4) | 97 | 52 (53.6) | 101 | - | 97 | 50 (51.5) | 7 | 1 (14.3) |
| Ready-made and convenience foods | 377 | 377 | - | 377 | 65 (17.2) | 377 | 89 (23.6) | 376 | 37 (9.8) | 16 | 11 (68.7) |
| Butter, oils and emulsions | 72 | 72 | - | 72 | - | 67 | 8 (11.9) | 30 | - | 1 | 1 (100) |
| Pasta, noodles, rice | 488 | 483 | - | 486 | 151 (31.1) | 444 | - | 450 | - | 41 | 8 (19.5) |
| Processed meats | 175 | 174 | - | 173 | 162 (93.6) | 163 | 153 (93.9) | 163 | - | 11 | 10 (90.9) |
| Processed fish and seafood products | 234 | 234 | - | 234 | 170 (72.6) | 234 | 83 (35.5) | 156 | - | 7 | 5 (71.4) |
| Processed fruits, vegetables and legumes | 692 | 691 | - | 640 | 80 (12.5) | 519 | - | 618 | - | 55 | 22 (40.0) |
| Sauces, dips and dressings | 514 | 514 | - | 514 | 208 (40.5) | 477 | - | 482 | - | 73 | 65 (89.0) |
| All | 5542 | 5 415 | 1 470 (89.1) | 5 311 | 2 260 (49.9) | 4 820 | 333 (39.6) | 5275 | 2 531 (89.7) | 726 | 277 (45.9) |
(-) indicate that thresholds have not been defined for the nutrient in the category or no products to perform nutritional profiling
Proportion of permitted and non-permitted products to be marketed to children by food category
The proportion of permitted and non-permitted products to be marketed to children by food category is presented in Table 5. The results showed that almost 63.3% of the foods were classified as “non-permitted” to be marketed to children. The top 5 categories and sub-categories with the highest proportion of “permitted foods” according to the criteria set by the NPM-WHO/AR were “cereal, legumes and grain beverages” (93.8%), followed by “butter, oils and emulsions” (88.1%), “processed fruits, vegetables and legumes” (87.5%), “ready-made and convenience foods” (71.2%) and “pasta, noodles, rice” (68.9%). In contrast, the top 5 categories and sub-categories with the highest proportion of non-permitted foods to be marketed to children were “savoury snacks Potato, cereal or starch-based” (100%), “cakes, sweet biscuits and pastries” (98.5%), “energy drinks” (98.2%), “processed meats” (96.4%) and “yoghurt, ice cream and sorbets” (95.8%).
Table 5.
Proportion of permitted and non-permitted products to be marketed to children according to NPM-WHO/AR by food category
| Foods categories | N | n | Permitted products n (%) |
Non-permitted products n (%) |
p-value |
|---|---|---|---|---|---|
| Bread and bakery products | |||||
| a) Cakes, sweet biscuits and pastries | 748 | 747 | 11 (1.5) | 736 (98.5) | < 0.001 |
| b) Bread and crisp bread | 128 | 106 | 51 (48.1) | 55 (51.9) | 0.697 |
| Savoury snack foods | |||||
| a) Savoury snacks Potato, cereal or starch-based | 236 | 236 | 0 (0.0) | 236 (100.0) | < 0.001 |
| b) Processed nuts, edible seeds | 68 | 17 | 5 (29.4) | 12 (70.6) | 0.089 |
| Beverages | |||||
| a) Juices | 309 | 267 | 35 (13.1) | 232 (86.9) | < 0.001 |
| b) Milk and dairy based drinks | 90 | 90 | 58 (64.4) | 32 (35.6) | 0.006 |
| c) Energy drink | 315 | 286 | 13 (1.8) | 273 (98.2) | < 0.001 |
| d) Coffee, tea, herbal infusion | 158 | 134 | 33 (24.6) | 101 (75.4) | < 0.001 |
| e) Cereal, legumes, grain beverages | 32 | 32 | 30 (93.8) | 2 (6.2) | < 0.001 |
| Breakfast cereals | 113 | 113 | 24 (21.2) | 89 (78.8) | < 0.001 |
| Chocolate and sugar confectionery | 433 | 431 | 28 (6.5) | 403 (93.5) | < 0.001 |
| Cheese | 122 | 121 | 25 (20.7) | 96 (79.3) | < 0.001 |
| Yoghurt, ice cream and sorbets | 125 | 119 | 5 (4.2) | 114 (95.8) | < 0.001 |
| Flan, custard | 113 | 97 | 25 (25.8) | 72 (74.2) | < 0.001 |
| Ready-made and convenience foods | 377 | 378 | 269 (71.2) | 109 (28.8) | < 0.001 |
| Butter, oils and emulsions | 72 | 67 | 59 (88.1) | 8 (11.9) | < 0.001 |
| Pasta, noodles, rice | 488 | 486 | 335 (68.9) | 151 (31.1) | < 0.001 |
| Processed meats | 175 | 169 | 6 (3.5) | 163 (96.4) | < 0.001 |
| Processed fish and seafood products | 234 | 234 | 62 (26.5) | 172 (73.5) | < 0.001 |
| Processed fruits, vegetables and legumes | 692 | 639 | 559 (87.5) | 80 (12.5) | < 0.001 |
| Sauces, dips and dressings | 514 | 511 | 303 (59.3) | 208 (40.7) | < 0.001 |
| All | 5 542 | 5 280 (95.3) | 1 936 (36.7) | 3 344 (63.3) | < 0.001 |
The non-permitted and permitted foods to be marketed to children according to the different Nutri-Score categories are shown in Table 6. The results also showed that most of the non-permitted foods were classified respectively in Nutri-Score E (35.3%), followed by Nutri-Score D (31.1%) and Nutri-Score C (16.2%). In addition, most of the permitted foods were respectively classified in Nutri-Score A (40.7%), Nutri-Score B (27.3%) and Nutri-Score C (13.0%). Nevertheless, it should be noted that almost half of the permitted foods were also rated Nutri-Score A.
Table 6.
Cross-frequency table between Nutri-Score and NPM-WHO/AR for permitted and non-permitted foods to be marketed to children
| Foods categories | Permitted foods to be marketed to children | Non-permitted foods to be marketed to children | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | Nutri-Score A | Nutri-Score B | Nutri-Score C | Nutri-Score D | Nutri-Score E | p-value | n | Nutri-Score A | Nutri-Score B | Nutri-Score C | Nutri-Score D | Nutri-Score E | p-value | |
| Bread and bakery products | ||||||||||||||
| a) Cakes, sweet biscuits and pastries | 11 | 0 (0.0) | 2 (18.2) | 9 (81.8) | 0 (0.0) | 0 (0.0) | < 0.001 | 736 | 9 (1.2) | 48 (6.5) | 87 (11.8) | 217 (29.5) | 375 (50.9) | < 0.001 |
| b) Bread and crisp bread | 51 | 24 (47.1) | 7 (13.7) | 6 (11.8) | 14 (27.4) | 0 (0.0) | < 0.001 | 55 | 5 (9.1) | 11 (20.0) | 20 (36.4) | 14 (25.5) | 5 (9.1) | 0.005 |
| Savoury snack foods | ||||||||||||||
| a) Savoury snacks Potato, cereal | 0 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | - | 236 | 2 (0.8) | 9 (3.8) | 49 (20.8) | 102 (43.2) | 74 (31.3) | < 0.001 |
| b) Processed nuts, edible seeds | 5 | 0 (0.0) | 0 (0.0) | 2 (40.0) | 3 (60.0) | 0 (0.0) | 0.09 | 12 | 0 (0.0) | 0 (0.0) | 3 (25.0) | 8 (66.7) | 1 (8.3) | < 0.001 |
| Beverages | ||||||||||||||
| a) Juices | 35 | 0 (0.0) | 1 (2.9) | 8 (22.8) | 21 (60.0) | 5 (14.3) | < 0.001 | 232 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 8 (3.4) | 224 (96.6) | < 0.001 |
| b) Milk and dairy based drinks | 58 | 18 (31.0) | 30 (51.7) | 7 (12.1) | 3 (5.2) | 0 (0.0) | < 0.001 | 32 | 5 (15.6) | 7 (21.9) | 6 (18.7) | 7 (21.9) | 7 (21.9) | 0.973 |
| c) Energy drink | 13 | 0 (0.0) | 10 (76.9) | 1 (7.7) | 0 (0.0) | 2 (15.4) | < 0.001 | 273 | 8 (2.9) | 10 (3.7) | 23 (8.4) | 43 (15.7) | 189 (69.2) | < 0.001 |
| d) Coffee, tea, herbal infusion | 33 | 0 (0.0) | 28 (84.8) | 3 (9.1) | 1 (3.0) | 1 (3.0) | < 0.001 | 101 | 0 (0.0) | 0 (0.0) | 29 (28.7) | 19 (18.8) | 53 (52.5) | < 0.001 |
| e) Cereal, legumes, grain beverages | 30 | 7 (23.3) | 23 (76.7) | 0 (0.0) | 0 (0.0) | 0 (0.0) | < 0.001 | 2 | 0 (0.0) | 2 (100.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | - |
| Breakfast cereals | 24 | 15 (62.5) | 4 (16.7) | 4 (16.7) | 1 (4.2) | 0 (0.0) | < 0.001 | 89 | 10 (11.2) | 17 (19.1) | 46 (51.7) | 15 (16.8) | 1 (1.1) | < 0.001 |
| Chocolate and sugar confectionery | 28 | 1 (3.6) | 23 (82.1) | 4 (14.3) | 0 (0.0) | 0 (0.0) | < 0.001 | 403 | 8 (2.0) | 15 (3.7) | 11 (2.5) | 174 (40.4) | 195 (48.4) | < 0.001 |
| Cheese | 25 | 1 (4.0) | 0 (0.0) | 6 (24.0) | 15 (60.0) | 3 (12.0) | < 0.001 | 96 | 2 (2.1) | 0 (0.0) | 0 (0.0) | 81 (84.4) | 13 (13.5) | < 0.001 |
| Yoghurt, ice cream and sorbets | 5 | 2 (40.0) | 1 (20.0) | 1 (20.0) | 1 (20.0) | 0 (0.0) | 0.735 | 114 | 0 (0.0) | 15 (13.1) | 34 (29.8) | 46 (40.3) | 19 (16.6) | < 0.001 |
| Flan, custard | 25 | 1 (4.0) | 4 (16.0) | 20 (80.0) | 0 (0.0) | 0 (0.0) | < 0.001 | 72 | 0 (0.0) | 2 (2.8) | 3 (4.2) | 65 (90.3) | 2 (2.8) | < 0.001 |
| Ready-made and convenience foods | 269 | 192 (71.4) | 70 (26.0) | 4 (1.5) | 3 (1.1) | 0 (0.0) | < 0.001 | 109 | 14 (12.8) | 43 (39.4) | 19 (17.4) | 27 (24.8) | 6 (4.5) | < 0.001 |
| Butter, oils and emulsions | 59 | 0 (0.0) | 3 (5.1) | 9 (15.2) | 46 (78.0) | 1 (1.7) | < 0.001 | 8 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 8 (100.0) | < 0.001 |
| Pasta, noodles, rice | 335 | 289 (86.3) | 39 (11.6) | 6 (1.8) | 1 (0.3) | 0 (0.0) | < 0.001 | 151 | 66 (43.7) | 44 (29.1) | 26 (17.2) | 11 (7.3) | 4 (2.6) | < 0.001 |
| Processed meat | 6 | 6 (100.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0.001 | 163 | 8 (4.9) | 31 (19.0) | 40 (24.5) | 83 (50.9) | 1 (0.6) | < 0.001 |
| Processed fish and seafood products | 62 | 55 (88.7) | 5 (8.1) | 0 (0.0) | 2 (3.2) | 0 (0.0) | < 0.001 | 172 | 83 (48.3) | 65 (37.8) | 12 (6.9) | 12 (6.9) | 0 (0.0) | < 0.001 |
| Processed fruits, vegetables and legumes | 559 | 217 (38.8) | 178 (31.8) | 79 (14.1) | 84 (15.0) | 1 (0.2) | < 0.001 | 80 | 1 (1.2) | 4 (5.0) | 28 (35.0) | 43 (53.7) | 4 (5.0) | < 0.001 |
| Sauces, dips and dressing | 303 | 77 (25.4) | 101 (33.3) | 83 (27.4) | 40 (13.2) | 2 (0.7) | < 0.001 | 208 | 21 (10.9) | 15 (7.2) | 107 (51.4) | 64 (30.8) | 1 (0.4) | < 0.001 |
| All | 1 936 | 905 (46.7) | 529 (27.3) | 252 (13.1) | 235 (12.1) | 15 (0.8) | 3 344 | 242 (7.3) | 338 (10.1) | 543 (16.2) | 1 039 (31.1) | 1 182 (35.3) | ||
Cross frequency table between Nutri-Score and NOVA classification
The cross-frequency table between Nutri-Score and NOVA classification is shown in Table 7. Ultra-processed foods were most prevalent regardless of Nutri-Score, ranging from 9.8% in Nutri-Score A to 21.0% in Nutri-Score D.
Table 7.
Cross-frequency table between Nutri-Score and NOVA classification
| Nutri-Score | n (%) |
Unprocessed foods n (%) |
Processed culinary ingredients n (%) |
PFs n (%) |
UPFs n (%) |
|---|---|---|---|---|---|
| Nutri-Score A | 1131 (20.9) | 274 (5.1)*** | 0 (0.0) | 328 (6.0)*** | 529 (9.8) |
| Nutri-Score B | 910 (16.8) | 84 (1.6) | 3 (0.1) | 271 (5.0) | 552 (10.2) |
| Nutri-Score C | 847 (15.7) | 54 (1.0) | 6 (0.1) | 165 (3.0) | 622 (11.5) |
| Nutri-Score D | 1320 (24.4) | 35 (0.6) | 30 (0.6)*** | 119 (2.2) | 1 136 (21.0)*** |
| Nutri-Score E | 1199 (22.2) | 55 (1.0) | 6 (0.1) | 138 (2.6) | 1 000 (18.5) |
| All | 5 407 | 502 (9.3) | 45 (0.9) | 1 021 (18.8) | 3 839 (71.0) |
Statistically significant at p < 0.05; *** corresponds to a value of p < 0.001
In addition, 50% of the PFs were classified as Nutri-Score A or Nutri-Score B, while almost 50% of the UPFs were classified as Nutri-Score A, Nutri-Score B or Nutri-Score C (Fig. 2).
Fig. 2.
Boxplot showing the Nutri-Score values according to the different food processing categories. The lower limit of the box indicates the 25th percentile, the line inside the box marks the median and the upper limit of the box indicates the 75th percentile. Whiskers (error bars) at the top and bottom of the box indicate the lower limit (25th percentile—1.5* (inter-quartile range)) and the upper limit (75th percentile + 1.5* (inter-quartile range)). The circles are individual outliers
Proportion of permitted and non-permitted foods to be marketed to children with on-pack promotion
The proportions of permitted and non-permitted products with on-pack promotions by food category are shown in Table 8. The results showed that the non-permitted foods to be marketed to children were the ones with the most on-pack promotions (12.5% vs. 4.6%).
Table 8.
Proportion of permitted and non-permitted foods to be marketed to children with on-pack promotion
| Foods categories | Permitted foods | Non-permitted foods | |||
|---|---|---|---|---|---|
| N |
with on-pack promotion n (%) |
N |
with on-pack promotion n (%) |
p-value | |
| Bread and bakery products | |||||
| a) Cakes, sweet biscuits and pastries | 11 | 0 (0.0) | 736 | 130 (17.7) | 0.163 |
| b) Bread and crisp bread | 51 | 3 (5.9) | 55 | 7 (12.7) | 0.251 |
| Savoury snack foods | |||||
| a) Savoury snacks Potato, cereal or starch-based | 0 | 0 (0.0) | 236 | 41 (17.4) | - |
| b) Processed nuts, edible seeds | 5 | 0 (0.0) | 12 | 0 (0.0) | - |
| Beverages | |||||
| a) Juices | 35 | 1 (2.8) | 232 | 6 (2.6) | 0.926 |
| b) Milk and dairy based drinks | 58 | 8 (13.8) | 32 | 9 (28.1) | 0.134 |
| c) Energy drink | 13 | 2 (15.4) | 273 | 7 (2.6) | 0.01 |
| d) Coffee, tea, herbal infusion | 33 | 1 (3.0) | 101 | 6 (5.9) | 0.525 |
| e) Cereal, legumes, grain beverages | 30 | 0 (0.0) | 2 | 0 (0.0) | - |
| Breakfast cereals | 24 | 10 (41.7) | 89 | 45 (50.6) | 0.579 |
| Chocolate and sugar confectionery | 28 | 0 (0.0) | 403 | 126 (31.3) | 0.003 |
| Cheese | 25 | 7 (28.0) | 96 | 4 (4.2) | 0.000 |
| Yoghurt, ice cream and sorbets | 5 | 0 (0.0) | 114 | 9 (7.9) | 0.529 |
| Flan, custard | 25 | 4 (16.0) | 72 | 10 (13.8) | 0.810 |
| Ready-made and convenience foods | 269 | 3 (1.1) | 109 | 0 (0.0) | 0.270 |
| Butter, oils and emulsions | 59 | 0 (0.0) | 8 | 0 (0.0) | - |
| Pasta, noodles, rice | 335 | 23 (6.9) | 151 | 14 (9.3) | 0.373 |
| Processed meats | 6 | 1 (16.7) | 163 | 4 (2.4) | 0.046 |
| Processed fish and seafood products | 62 | 0 (0.0) | 172 | 1 (0.6) | 0.548 |
| Processed fruits, vegetables and legumes | 559 | 23 (4.1) | 80 | 0 (0.0) | 0.069 |
| Sauces, dips and dressings | 303 | 4 (1.3) | 208 | 0 (0.0) | 0.097 |
| All | 1 936 | 90 (4.6) | 3 344 | 419 (12.5) | < 0.001 |
Statistically significant at p < 0.05
Discussion
This study was the first to analyze the nutritional quality and on-pack marketing of pre-packaged foods available in major supermarkets in Dakar, Senegal, using the NOVA classification, the Nutri-Score labelling system and the Nutrient Profile Model for the WHO African Region. This study was conducted on a sample of 5,542 pre-packaged foods and non-alcoholic beverages classified into 15 main categories and 9 sub-categories according to the NPM-WHO/AR.
In this study, most of the pre-packaged foods were ultra-processed foods and beverages (711%), highlighting that the majority of pre-packaged products involve UPFs, which is in line with previous studies [26, 27]. These foods are generally of poor nutritional quality (high in saturated fat, sugar, salt and low in micronutrients and fibre) and are likely to contain additives with health risks. Poor diet quality is a major risk factor for the onset and development of NCDs [28]. Preventive nutrition policies are an important public health issue for these diseases. The top 3 categories with the highest UPFs are “chocolate and sugar confectionery” (99.8%), followed by “cakes, sweet biscuits and pastries” (99.5%) and “frozen yoghurt, ice cream and sorbets” (97.2%). This is alarming given the negative impact of over-consumption of ultra-processed foods and beverages, particularly through the development of chronic NCDs. Meta-analyses have shown that the consumption of UPFs is associated with an increased risk of overweight, obesity, cardiometabolic diseases and cancer in adults, and with metabolic syndrome in adolescents and dyslipidemia in children [2, 29, 30]. In view of the current challenges, we need to move towards urgent and effective public health measures. It is essential to create an environment conducive to better nutrition by implementing policies that promote quality products. A fiscal policy aimed at improving eating habits would be an essential means of reducing the consumption of these unhealthy foods. Taxes influence consumption behaviors, especially when applied to sweetened beverages, which is a key factor in the fight against obesity and diabetes [31]. These taxes can also encourage the food industry to improve the nutritional quality of their products.
In our study, the majority of pre-packaged foods were classified in Nutri-Score D (24.4%) and Nutri-Score E (22.1%) and contained a significant percentage of UPFs, ranging from 21.0% for Nutri-Score D and 18.5% for Nutri-Score E. These results are in line with those reported by [32, 33]. However, the majority of the products examined were imported and manufactured by large multinational companies that have committed to voluntary reformulation of their products. This leaves one perplexed, given the many declarations of nutritional commitments and policies by these food companies. Recent reports show that consumption of foods ranked lower on the Nutri-Score scale is associated with an increased risk of cardiovascular disease [34] and mortality [35]. Interventions should be implemented to make products of better nutritional quality more visible in supermarkets and, conversely, products with a Nutri-Score D or E less visible.
In this study, approximately 20% of the products in the two healthiest Nutri-Score classes (Nutri-Score A and B) were UPFs. This may be explained by the fact that although the Nutri-Score algorithm includes nutrients and elements whose consumption has an impact on health, it does not include other aspects of food that are likely to have an impact on health, such as the presence of additives (colorings, preservatives, emulsifiers, flavor enhancers, sweeteners, etc.). Adding these elements to the Nutri-Score rating could improve the ability to classify/discriminate between healthy and unhealthy items.
In this study, nutritional profiling was performed on 95% of the products for which nutritional information was provided and the results showed that 63.3% did not meet the criteria of the WHO Nutrient Profile Model. These results are similar to those reported by Frank et al. [36] in South Africa and Vergeer et al. [37] on food products available on the Canadian market. Li et al. [38] also reported a higher proportion of non-compliant foods (90%) for the WHO Western Pacific Region NPM (WPHO NPM). In light of these findings, the fact that nearly 63% of products do not meet the model criteria indicates that these products contain high levels of nutrients of concern, particularly saturated fat, sugar and/or sodium. Unhealthy diets high in saturated fat, sugar and sodium are associated with obesity, high blood pressure and chronic diseases such as heart disease, cerebrovascular accidents and type 2 diabetes [39]. Reformulation of pre-packaged foods is essential to address this issue and is an effective way to improve the food supply. The need to improve product nutrition labelling is also crucial and interpretative nutrition labelling could be an effective way to help consumers make quick and informed choices, and underlies to motivate manufacturers to develop products with lower levels of the nutrients that contribute to chronic disease.
This study showed that the majority of non-permitted foods to be marketed to children were classified in the Nutri-Score groups C, D, and E (82.6%). However, a more detailed examination of the food categories showed that the Nutri-Score would have classified 52.2% and 85.5% of non-permitted foods “ready-made and convenience foods” and “processed fish and seafood products” respectively in Nutri-Score groups A and B. This result suggests a slight discrepancy between the two classification systems, even though both are based on the nutritional composition of foods. This could be explained by the fact that the Nutri-Score system includes fibre, protein and FVNL (fruits, vegetables, nuts and legumes) in its classification. For example, in the “processed fish and seafood products” category, the protein content of fish means that some packaged foods are healthy according to the Nutri-Score, without any indication of high saturated fat content. Nevertheless, the results of this study also showed that the Nutri-Score would classify 74% of the permitted foods to be marketed to children according to NPM-WHO/AR in Nutri-Score groups A and B. However, the research carried out by Richonnet et al. [27] on French market reported a higher proportion (almost 95%), thus highlighting the consistency between the two classification systems.
In an operational context, front-of-pack nutrition labelling systems make it easier for consumers to understand nutritional information, enabling them to make better food choices. The Nutri-Score could be adopted, as this logo reflects the nutritional quality of products and not only encourages manufacturers to offer better quality products, but also encourages the public to make healthier choices. The government should take action to make this nutritional logo mandatory on the front of products as a public health tool to guide consumers in their food choices in order to prevent chronic diseases. However, the Nutri-Score currently only applies to packaged foods and many foods products are not labelled. Therefore, other public health measures need to be implemented in addition, such as strengthening the nutritional labelling of products by making it mandatory to include other information deemed relevant to consumers, in particular the content of nutritional components and the processing degree of products. Joint initiatives are needed, in particular campaigns to raise awareness and educate the public about nutrition and the impact of food choices on health, including the importance of good eating habits.
Our results showed a significant proportion of UPFs in the permitted foods according to the WHO nutrient profiling. This result may suggest that high-processed foods do not always have a mediocre nutritional composition, as highlighted by other authors [40].
In this study, 12.5% of promotional characters were displayed on the packaging of non-permitted foods according to NPM-WHO/AR. The most common promotional characters used were cartoon characters and premium offers with a strong appeal to children, strategies known to influence children under 12 years of age, particularly in their choices, preferences and eating habits. International research has shown that children’s exposure to unhealthy foods and beverages contributes to preferences for unhealthy foods and beverages [41]. Through this aggressive marketing, children are more likely to be exposed to products with low nutritional value. Unhealthy foods in childhood have an impact on obesity, dental caries and taste preferences in later life [42, 43]. Implementing marketing restrictions that protect children should be a priority. The Senegalese government should establish solid, comprehensive regulations based on the WHO’s nutrient profile model to define which foods should not be marketed in order to protect children’s health.
The limitations of this study were that only around 80% of foods declared their nutritional composition and, on the other hand, foods in certain categories did not declare their content of specific nutrients for which thresholds have been defined in the NPM-WHO/AR, although nutritional information was displayed on the packaging. This study was based on the previous version of the Nutri-Score tool for assessing the nutritional quality of pre-packaged foods. The current version would have placed more foods in Nutri-Score categories C, D or E as the revised, slightly stricter Nutri-Score calculation changes the score for certain product categories. For example, under the old calculation, some breakfast cereals would have been Nutri-Score A, but under the new algorithm these would have been downgraded to Nutri-Score C (the tightening of the criteria removes positive points for protein, but also takes more account of sugar and salt content). Under the new Nutri-Score, cereal have received more negative points for sugar and salt and less positive points for protein and fiber; and the presence of sweeteners in beverages is taken into account. This study was limited to data on pre-packaged foods available in two hypermarkets in the Senegalese capital. Consequently, it could not shed light on the nutritional quality of food available on the Senegalese market as whole (given that chains such as Casino and Utile promote their own brand products although the most identified products are also sold in the aforementioned chains; but also had a significant market share).
Conclusion
This study reports that pre-packaged foods available in major supermarkets in Senegal are predominantly non-permitted to be marketed to children and are widely promoted. Policies should be implemented to incentivize the reformulation of pre-packaged foods in the context of increasing levels of obesity and diet-related NCDs. Government should strengthen nutrition labelling of foods so that consumers have relevant information to guide their food choices. Other public health measures, such as restrictions on marketing targeting to children, need to be implemented alongside.
Our study shows wide variation in the agreement of the nutritional assessment between the three classification systems (NOVA, Nutri-Score and NPM-WHO/AR). Nutritional profiling is an important tool that can help define and monitor policies actions to improve the healthiness of products. The Senegalese government could rely on the NPM-WHO/AR to define which foods are permitted or not for marketing to children. Furthermore, in order to implement a front-of-pack labelling system in Senegal (whether Nutri-Score or another system), it would be important as a priori, to make nutrition declarations mandatory on the back of product packaging, subsequently to facilitate the calculation of scores supporting the chosen front-of-pack nutritional labelling system.
Supplementary Information
Supplementary Material 1: Table S1. Description of the foods categories according to WHO Nutrient Profile Model for African region. * Table S2. Distribution of each foods category according to Nutri-Score.
Acknowledgements
The authors would like to grateful to Aude Ranchon Nguyen Huu: catering Director Auchan Retail Senegal, Amadou Diallo: Director Hypermarket Auchan Mermoz, Aida Mbernard and M. Ndiaye for granting access to their stores. Our gratitude extends to collaborating students for their contribution to data collection.
Abbreviations
- INFORMAS
International Network for Food and Obesity/non-communicable diseases, Research, Monitoring and Action Support
- IQR
Interquartile range
- FVNL
Fruits, Vegetable, Nuts and Legumes
- NCDs
Non-Communicable Diseases
- NIP
Nutrition Information Panel
- NPM
Nutrient Profile Model
- ODK
Open Data Kit
- PFs
Processed foods
- UPFs
Ultra-Processed foods
- SpF
Santé Publique France
- WHO
World Health Organization
- NPM-WHO/AR
Nutrient Profile Model by WHO for African region
Authors’ contributions
A.D. is the principal investigator of the study and successful funding application. Y.O., M.H.F. and A.D. designed the study. Y.O. and F.F. carried out data collection in supermarkets; M.H.F. supervised data collection; Y.O. performed statistical analysis; M.H.F., and A.D. corrected and validated data analysis; Y.O., M.H.F. and A.D. drafted the manuscript with inputs from G.S., N.I.D., B.S. and S.V. All authors reviewed the manuscript.
Funding
This research was funded by International Development Research Centre (IDRC) through INFORMAS 2.0 "Towards harmonized indicators for measuring progress on creating healthy and sustainable food systems project" (Ref 109472) and PROMESS "Policies evaluation and development of multisectoral strategies to promote healthy and sustainable food environments in francophone West Africa" (Ref 109416). IDRC had no role in the design, analysis or drafting of this article.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Hypermarkets Directors and Managers provided informed consent to Laboratoire de Recherche en Nutrition et Alimentation Humaine (LARNAH) to participate in this study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.World Health Organization. WHO Regional Committee for Europe resolution on an action plan for the prevention and control of noncommunicable diseases in the WHO European region. Copenhagen: WHO Regional Office for Europe; 2016. [Google Scholar]
- 2.Fiolet T, Srour B, Sellem L, Kesse-Guyot E, Allès B, Méjean C, Deschasaux M, Fassier P, Latino-Martiel P, Beslay M, et al. Comsumption of ultra-processed foods and cancer risk: results from NutriNet-Santé prospective cohort. BMJ. 2018;360:k322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Noncommunicable diseases progress monitor 2022. Geneva: World Health Organization; 2022.
- 4.World Health Organization. Diet, nutrition and the prevention of chronic diseases. World Health Organ Tech Rep Ser. 2003;916:1–149. [PubMed] [Google Scholar]
- 5.Baker P, Friel S. Processed foods and the nutrition transition: evidence from Asia. Obes Rev. 2014;15:564–77. [DOI] [PubMed] [Google Scholar]
- 6.Adjei AP, Amevinya GS, Quarpong W, Tandoh A, Aryeetey R, Holdsworth M, Agyemang C, Zotor F, Laar ME, Mensah K, Addo P, Laryea D, Asiki G, Sellen D, Vandevijvere S, Laar A. Availability of healthy and unhealthy foods in modern retail outlets located in selected districts of Greater Accra Region, Ghana. Front Public Health. 2022;10:922447. 10.3389/fpubh.2022.922447. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Popkin BM, Ng SW. The nutrition transition to a stage of high obesity and noncommunicable disease prevalence dominated by ultra-processed foods is not inevitable. Obes Rev. 2022;23(1):e13366. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Monteiro CA, Moubarac JC, Cannon G, Ng SW, Popkin B. Ultra-processed products are becoming dominant in the global food system. Obes Rev. 2013;14 Suppl 2:21–8. 10.1111/obr.12107. PMID: 24102801. [DOI] [PubMed] [Google Scholar]
- 9.Stuckler D, Nestle M. Big food, food systems, and global health. PLoS Med. 2012;9(6):e1001242. 10.1371/journal.pmed.1001242. Epub 2012 Jun 19. PMID: 22723746; PMCID: PMC3378592. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Popkin BM. The nutrition transition: an overview of world patterns of change. Nutr Rev. 2004;62(7 Pt 2):S140–3. [DOI] [PubMed] [Google Scholar]
- 11.Hawkes C, Jewell J, Allen K. A food policy package for healthy diets and the prevention of obesity and diet-related non-communicable diseases: the NOURISHING framework. Obes Rev. 2013;14(Suppl 2):159–68. [DOI] [PubMed] [Google Scholar]
- 12.Louzada ML, Baraldi LG, Steele LM, Martins AP, Canellla DS, Moubarac JC, Levy RB, Cannon G, Afshin A, Imamura F, et al. Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev Med. 2015;81:9–15. [DOI] [PubMed] [Google Scholar]
- 13.Julia C, Martinez L, Alles B, Touvier M, Hercberg S, Mejean C, Kesse-Guyot E. Contribution of ultra-processed foods in the diet of adults from the French NutriNet-Sante study. Public Health Nutr. 2018;21:27–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Moradi S, Entezari MH, Mohammadi H, Jayedi A, Lazaridi AV, Kermani MAH, Miraghajani M. Ultra-processed food consumption and adult obesity risk: a systematic review and dose-response meta-analysis. Crit Rev Food Sci Nutr. 2021;63(2):249–60. [DOI] [PubMed]
- 15.Clark H, Coll Seck AM, Banerjee A, Peterson S, Dalglish SL, Ameratunga S, Balabanova D, Kishan Bhan M, Bhutta ZA, Borrazzo J, et al. A future for the world’s children? A WHO-UNICEF-Lancet Commission. Lancet. 2020;22:605–58. [DOI] [PubMed] [Google Scholar]
- 16.Amevinya GS, Vandevijvere S, Kelly B, Afagbedzi SK, Aryeetey R, Adjei AP, Quarpong W, Tandoh A, Nanema S, Agyemang C, Zotor F, Laar ME, Mensah K, Laryea D, Asiki G, Holdsworth M, Laar A. Advertising of unhealthy foods and beverages around primary and junior high schools in Ghana’s most urbanized and populous region. Front Public Health. 2022;10:917456. 10.3389/fpubh.2022.917456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1223–49. 10.1016/S0140-6736(20)30752-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Griffith R, O’Connell M, Smith K. The importance of product reformulation versus consumer choice in improving diet quality. Economica. 2017;84:34–53. [Google Scholar]
- 19.Federici C, Detzel P, Petracca F, et al. The impact of food reformulation on nutrient intakes and health, a systematic review of modelling studies. BMC Nutr. 2019;5:2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.World Health Organisation. Global strategy on diet, physical activity and health. Geneva: World Health Organization; 2004. [Google Scholar]
- 21.Popkin BM, Barquera S, Corvalan C, Hofman KJ, Monteiro C, Ng SW, Swart EC, Taillie LS. Towards unified and impactful policies to reduce ultra-processed food consumption and promote healthier eating. Lancet Diabetes Endocrinol. 2021;9:462–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Monteiro CA, Lawrence M, Millett C, Nestle M, Popkin BM, Scrinis G, Swinburn B. The need to reshape global food processing: a call to the United Nations Food Systems Summit. BMJ Glob Health. 2021;6:e006885. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Neal B, Sacks G, Swinburn B, Vandevijvere S, Dunford E, Snowdon W, Webster J, Barquera S, Friel S, Hawkes C, et al. Monitoring the levels of important nutrients in the food supply. Obes Rev. 2013;14:49–58. [DOI] [PubMed] [Google Scholar]
- 24.Rayner M, Wood A, Lawrence M, Mhurchu CN, Albert J, Barquera S, Friel S, Hawkes C, Kelly B, Kumanyika S, L’Abbé M, Lobstein T, Ma J, Macmullan J, Mohan S, Monteiro C, Neal B, Sacks G, Sanders D, Snowdon W, Swinburn B, Vandevijvere S, Walker C, et al. Monitoring health-related food labelling. Obes rev. 2013;14:70–81. [DOI] [PubMed] [Google Scholar]
- 25.Monteiro C, Cannon G, Levy R, Moubarac J, Louzada M, Rauber F, Jaime P. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 2019;22(5):936–41. 10.1017/S1368980018003762. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Baldridge AS, Huffman MD, Taylor F, Xavier D, Bright B, Van Horn LV, Neal B, Dunford E. The healthfulness of the US packaged food and beverage supply: a cross-sectional study. Nutrients. 2019;11(8):1704. 10.3390/nu11081704. PMID: 31344845; PMCID: PMC6722673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Richonnet C, Mosser F, Favre E, Robert M, Martin F, Thiebaut I. Nutritional quality and degree of processing of children’s foods assessment on the French market. Nutrients. 2022;14:171. 10.3390/nu14010171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72. 10.1016/S0140-6736(19)30041-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Lane MM, Davis JA, Beattie S, Gómez-Donoso C, Loughman A, O’Neil A, Jacka F, Berk M, Page R, Marx W, Rocks T. Ultraprocessed food and chronic noncommunicable diseases: a systematic review and meta-analysis of 43 observational studies. Obes Rev. 2021;22(3):e13146. 10.1111/obr.13146. [DOI] [PubMed] [Google Scholar]
- 30.Cordova C, Viallon V, Fontvieille E, Peruchet-Noray L, Jansana A, Wagner K-H, et al. Consumption of ultra-processed foods and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study. Lancet Regional Health-Europe. 2023;35:100771. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.World Health Organization. Fiscal policies for diet and prevention of noncommunicable diseases: technical meeting report, 5–6 May 2015, Geneva: World Health Organization; 2016.
- 32.Romero Ferreiro C, Lora Pablos D, Gómez de la Cámara A. Two dimensions of nutritional value: nutri-score and NOVA. Nutrients. 2021;13(8):2783. 10.3390/nu13082783. PMID: 34444941; PMCID: PMC8399905. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Pellegrino F, Tan M, Richonnet C, Reinert R, Bucher Della Torre S, Chatelan A. What is the nutritional quality of pre-packed foods marketed to children in food stores? A survey in Switzerland. Nutrients. 2024;16(11):1656. 10.3390/nu16111656. PMID: 38892589; PMCID: PMC11175003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Deschasaux-Tanguy M, Huybrechts I, Julia C, Hercberg S, Sarda B, Fialon M, Arnault N, et al. Nutritional quality of diet characterized by the Nutri-Score profiling system and cardiovascular disease risk: a prospective study in 7 European countries. Lancet Regional Health - Europe. 2024;46:101006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Deschasaux M, Huybrechts I, Julie C, Hercberg S, Egnell M, Srour B, et al. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries. BMJ. 2020;370:m3171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Frank T, Ng SW, Miles DR, Swart EC. Applying and comparing various nutrient profiling models against the packaged food supply in South Africa. Public Health Nutr. 2022;25(8):1–31. 10.1017/S1368980022000374. Epub ahead of print. PMID: 35168688; PMCID: PMC9378746. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Vergeer L, Vanderlee L, Ahmed M, Franco-Arellano B, Mulligan C, Dickinson K, et al. A comparison of the nutritional quality of products offered by the top packaged food and beverage companies in Canada. BMC Public Health. 2020;20:1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Li Y, Wang H, Zhang P, Popkin BM, Coyle DH, Ding J, Dong L, Zhang J, Du W, Pettigrew S. Nutritional quality of pre-packaged foods in China under various nutrient profile models. Nutrients. 2022;14:2700. 10.3390/nu14132700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Institute of Medicine. Dietary reference intakes for water, potassium, sodium, chloride, and sulfate. Washington, DC: The National Academies Press; 2005. 10.17226/10925. [Google Scholar]
- 40.Crino M, Sacks G, Dunford E, Trieu K, Webster J, Vandevijvere S, Swinburn B, Wu JY, Neal B. Measuring the healthiness of the packaged food supply in Australia. Nutrients. 2018;10(6):702. 10.3390/nu10060702. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Smith R, Kelly B, Yeatman H, Boyland E. Food marketing influences children’s attitudes, preferences and consumption: a systematic critical review. Nutrients. 2019;11(4):875. 10.3390/nu11040875. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Llewellyn A, Simmonds M, Owen CG, Woolacott N. Childhood obesity as a predictor of morbidity in adulthood: a systematic review and meta-analysis: childhood obesity and adult morbidity. Obes Rev. 2016;17:56–67. 10.1111/obr.12316. [DOI] [PubMed] [Google Scholar]
- 43.Large JF, Madigan C, Pradeilles R, Markey O, Boxer B, Rousham EK. Impact of unhealthy food and beverage consumption on children’s risk of dental caries: a systematic review. Nutr Rev. 2024;82(11):1539–55. 10.1093/nutrit/nuad147. PMID: 38086176; PMCID: PMC11465133. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1: Table S1. Description of the foods categories according to WHO Nutrient Profile Model for African region. * Table S2. Distribution of each foods category according to Nutri-Score.
Data Availability Statement
No datasets were generated or analysed during the current study.