research paper on ready to eat food products

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Do Consumers Change Their Perception of Liking, Expected Satiety, and Healthiness of a Product If They Know It Is a Ready-to Eat Meal?

Laura laguna.

1 Instituto de Agroquímica y Tecnología de los Alimentos (IATA, CSIC), Avenida Agustín Escardino Benlloch 7, 46980 Valencia, Spain; [email protected] (L.L.); se.cisc.atai@namzsifs (S.F.)

Beatriz Gómez

2 Facultad de Bromatología, Universidad de Entre Ríos, 2820 Gualeguaychú, Entre Ríos, Argentina; ra.ude.renu.bf@zemogb

María D. Garrido

3 Departamento de Tecnología de Alimentos, Nutrición y Bromatología, Universidad de Murcia, 30003 Murcia, Spain; se.mu@odirragm (M.D.G.); se.mu@seranilb (M.B.L.)

Susana Fiszman

Amparo tarrega, maría b. linares.

A ready-to-eat meal is a prepared meal within a container or package that requires little preparation or heating before consumption. Despite ready-to-eat meals being widely consumed, to date, little information is available on the consumers’ perceptions of such products in comparison to a homemade meal. Thus, three groups of eighty participants took part in the present study; each group evaluated five ready-to-eat meals ( Pasta , Meatballs , Salad , Beans , and a Sandwich ) using one of the following conditions: (i) observation of the packaging, (ii) observation of the meal on a plate (photographs), and (iii) tasting the ready-to-eat product with the packaging being presented alongside the meal. Consumers were asked about their liking, satiety, and healthiness perception. The results showed that both the ready-to-eat pack and sensory quality of the product highly impact liking and healthiness perceptions. Being a ready-to-eat meal in a pack has a negative impact on liking expectations of the meal; however, the sensory quality can either counteract these effects or increase them. Expected satiety of meals depends on the type of meal and varies slightly according to the evaluation condition.

1. Introduction

“Ready meal” or “ready-to-eat”, as terms, can apply to a packaged full meal or main course comprising meat, fish, or vegetables and requiring little preparation and cooking [ 1 ]. Therefore, when consumers buy a ready meal, the ingredients have been already transformed and are presented in a pack where consumers can normally see the product, either by a colour printed image or through a transparent window on the packaging, i.e., sandwiches and salads [ 2 ].

According to the Spanish Association of Manufacturers of Prepared Dishes, in 2018, the consumption of ready-to-eat meals in Spain was 14.64 kg per person, representing an increase of 2.7% from the previous year [ 3 ]. Other countries such as the UK and USA had higher consumption; in 2018, their consumption was 19 and 27.8 kg per person, respectively [ 4 ].

The increase in popularity of ready-to-eat meals has been attributed to the scarcity of time in which to perform households chores [ 5 ]. A lack of time for cooking and the cost-effectiveness of such products have caused the ready-to-eat meals market to grow [ 6 , 7 ], and in Western societies, ready-to-eat meals have become, and continue to be, an essential part of consumers’ lives.

To further understand the importance of convenience for consumers when choosing ready-to-eat meals, some studies have focused on analysing the types of consumers that buy ready-to-eat meals according to different categories, i.e., demography, economy, education, and income [ 8 , 9 ]. However, nowadays the consumption of ready-to-eat meal is not only tied to households with two working parents. Further studies also showed the motivation that drives consumers to choose ready-to-eat meals; it was found that the choice between cooking or eating a ready-to-eat meal depended on the degree of convenience of the product, its sensory characteristics, and its perceived healthiness [ 10 ]. These characteristics are not unique ready-to-eat meals, but apply to all food products.

The Total Food Quality Model [ 11 ], a general framework for analysing food choice and quality perception, distinguishes between expected and experienced quality inferred from informational cues and actual experience, respectively. This model proposes four major dimensions that cover the principal aspects of food quality: taste (but also smell and appearance), health, convenience, and process. The first one is the hedonic quality dimension, and can usually only be determined after consumption. The second one is related to how consumers perceive a food product will affect their health that is mostly based upon consumer trust. Convenience is related to saving time and physical or mental energy in the process of planning, buying, storing and preparing the food, its consumption, cleaning, and disposing of the leftovers. Finally, process is related to the how consumers perceive a food has been produced (organic production, animal welfare, etc.).

Consumer attitudes and beliefs and/or previous experiences [ 12 ] contribute to their expectations. For a given ready meal, trust and the association with the homemade version help consumers create an idea about the product. Therefore, when finally consuming the meal, the actual product characteristics should also match the expected ones.

A particular feature of ready-to-eat meals is that in a supermarket, they are presented as convenient, i.e., precooked and packaged. Therefore, the packaging has an impact on quality perception. As previously reported, there are many packaging factors (images, shape, colour, and orientation of packaging elements) [ 13 , 14 ], as well as information such as the ingredients, nutrition facts, etc., that impact consumer quality expectations.

Regarding healthiness perception, nutritional studies have reported that ready-to-eat products contain more fat, sugar, and salt than homemade meals [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ].

Food satiety perception is a dimension not included in the aforementioned model [ 11 ]. As ready meals are sold as individual, full-portion-sized packs, perception of satiety can be especially relevant. Part of consumers’ opinions can be based upon fulfilling immediate and future needs to bridge the time until a next meal. It has been shown that consumers’ expected satiety judgements are based on the energy content of food, but that they are also related to a learned value based on previous experience [ 22 ], as well as being influenced by other factors, such as familiarity and sensory properties [ 23 ].

Both quality expectation and experience (before and after consumption, respectively) are believed to determine the degree of satisfaction with a product by a confirmation or disconfirmation process [ 24 ]. So, comparisons between before and after consumption experiences will contribute to understanding product quality perception and consumer satisfaction. At present, little information is available on the role of packaging and the sensory properties of ready-to-eat meal products regarding (expected) liking, satiety, and healthiness perception compared to what consumers would expect from a homemade meal.

The initial hypotheses of the present study are that knowing that a food item is a packaged ready to eat meal negatively affects consumer perception, and that the sensory characteristics of the product can modulate this perception. Comparing the perception of ready to eat products in different conditions can broaden our understanding of consumer responses.

Therefore, consumers’ (expected) liking, expected satiety, and healthiness perception of five ready-to-eat meals under different conditions (visually as a meal on a plate, visually as a meal pack, and tasting the meal) were evaluated to determine the impact of the “ready-to-eat” concept and the product’s sensory characteristics on consumer response.

2. Materials and Methods

2.1. ready-to-eat meals.

Five different ready-to-eat meals were bought in a local supermarket: Pasta (carbonara macaroni), Meatballs (garden meatballs), Salad (New Yorker salad), Beans ( Fabada , a traditional Spanish bean stew), and Sandwich (lettuce and egg). Table 1 shows the ingredients and describes the packaging material of the different ready-to-eat meals. The ingredients, weight, and nutritional facts as they are displayed on the packs can be found in Table A1 ( Appendix A ).

List of ingredients and packaging description of the ready-to-eat meals.

2.2. Consumer Tests

Individuals over 18 years of age were invited to take part in the study. Three separate groups of eighty participants with similar characteristics concerning gender (64, 66, and 68% women), age (36, 37, and 35 years on average), and age distribution (60% between 18–40 years of age and 40% older than 40) took part in a sample evaluation. People following any restrictive diet and smokers were excluded. No other demographic features were taken into account.

Figure 1 shows a scheme of the experimental procedure: each group of 80 participants evaluated the five meals under one of the following conditions:

Scheme of the experimental procedure where three different sets of consumers participated in one of the three different conditions and evaluated five meals.

(i) Meal-Photo condition: The participants were asked to observe a photograph of the meal (i.e., the complete contents of the pack) put on a white plate with a knife and fork on the sides. In this setting, the consumers were not aware that the meals were ready-to-eat products. The photographs were taken immediately after cooking/serving the dish ( Table 2 ) using a Nikon D800 (36 Mpx) camera (Nikon GmbH, Düsseldorf, Germany) with a Nikon 50 mm f/1.8 lens(Nikon GmbH, Düsseldorf, Germany) mounted on a Manfrotto tripod (Nikon GmbH, Düsseldorf, Germany) perpendicular to the plate and at the same distance from it. A Nikon SB900 flash (Nikon GmbH, Düsseldorf, Germany) mounted in a soft white umbrella (diameter: 80 cm) at an angle of 45° was also used. The Exchangeable image file format (Efix) data were as follows: focal length = 50 mm; exposition = 1/60 s; aperture = f/8; ISO = 100; colour temperature = 5800 K; flash power = 1/32. Basic adjustments to the RAW files (levels, curves, colour saturation, lens correction, and colour temperature) were made with the Lightroom 4.4 software (Adobe Systems Inc., San Jose, California, USA)). The photographs were coded with three digits using the Photoshop CS6 software (Adobe Systems Inc., San Jose, California, USA). Finally, seven groups of eight photographs were printed (240 pp resolution) on matt photographic paper (Granate Laboratorio, Molina del Segura, Spain) measuring 31 cm × 40 cm to maintain the original size of the dishes, and were mounted on foam sheets (thickness: 5 mm).

Photographs of the ready-to-eat meals presented to the participants (Meal-photo condition).

(ii) Pack Alone condition. The participants were asked to observe the unopened pack of the products. They were free to touch and to inspect the pack. In this condition, they were aware that the meal was ready-to-eat.

(iii) Tasting+Pack condition. The participants were asked to taste the product with an identical, unopened pack of the same product in view; in this condition, the participants knew that the meal was a ready-to-eat product, and were free to touch and inspect the pack. The participants were presented with a small plate and meal portion and were asked to taste it. Five different dishes were prepared appropriately, according to the type of dish (heated for the Pasta , Meatballs , and Beans or served at room temperature for the Sandwich and Salad ) and put on a plate with a knife and fork on the sides. Approximately 80–100 g was served, with all the plates having approximately the same number of calories.

Under each condition, the five samples (photograph of the meal, pack, and product tasted) were presented to the consumers in randomised order.

Consumers were asked to rate their (expected) liking, expected satiety, and healthiness perception for each sample. Liking was evaluated liking using a 9-point hedonic scale ranging from 1 (“dislike very much”) to 9 (“like very much”). Expected satiety was evaluated with a 7-point scale [ 25 ] ranging from 1 (“this meal would not satiate me, I will be hungry straight away”) to 7 (“this meal would be very satiating, it will allow me to fast until dinnertime or more”). Healthiness perception was evaluated on a 9-point scale from 1 (“not very healthy”) to 9 (“very healthy”).

All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Research Ethics Committee of the Universidad de Murcia (Project ID 2933/2020).

2.3. Data Analysis

For each evaluation condition, the individual consumers’ liking scores of the five products were analysed by the internal preference mapping method, obtained by applying a PCA to the liking values of each of the five products with consumers as a variable. The results were expressed as scatter plots of samples and individual consumers in relation to the first two dimensions.

Also, for each evaluation condition, the effect of product on liking, expected satiety, and healthiness perception were studied by two-way ANOVA. A Tukey test was used for post hoc mean comparisons.

For each pair of conditions, the differences between the mean scores of (expected) liking, healthiness perception and expected satiety were studied using Student’s t -tests ( p ≤ 0.05).

Data analyses were conducted using the statistical software package XLSTAT (Addinsoft, Barcelona, Spain, version 2018.2).

3. Results and Discussion

3.1. consumer liking.

Internal preference maps in the three conditions (Meal-Photo, Pack Alone, and Tasting+Pack) are displayed in Figure 2 , Figure 3 and Figure 4 , respectively. The preference map corresponding to the evaluation of the photograph of meal on a plate (Meal-Photo condition) ( Figure 2 ) explains 67.02% of the consumer variability. The first dimension (F1) separated Pasta and Sandwich from Beans , while the second (F2) separated Salad , on the top of the map, from Meatballs . Most consumers appeared on the top, right-hand side of the map, showing their preference for Pasta , Sandwich and Salad and rejection of Beans on the left. Consumers that preferred Beans or Meatballs were few.

Internal preference map of consumer liking scores of the Meal-Photo condition: ( a ) consumers; ( b ) samples.

Internal preference map of consumer liking scores in the Pack Alone condition: ( a ) consumers, ( b ) samples.

Internal preference map of consumer actual liking scores in Tasting+Pack condition: ( a ) consumers, ( b ) samples.

The internal preference map for consumers’ expected liking when evaluating the product as a ready-to-eat meal (Pack Alone condition) is shown in Figure 3 . The first two dimensions explain 66.40% of the variability. Most consumers, placed on the right side of the map, showed higher liking expectation for the Salad and Pasta , and lower liking expectation for Beans on the left half of the map. Few consumers had high expectations for Meatballs (on the top of the map); likewise, few had high expectations for the Sandwich (on the bottom of the map). Both groups were separated by F2.

Figure 4 shows the distribution of products according to the actual consumer liking after tasting the ready-to-eat meals, with the corresponding packaging in view (Tasting+Pack condition). The preference map explains 62.04% of the variability. F1 shows the preference of the consumers for Salad . F2 separates the traditional heartier foods ( Meatballs and Beans ) from the Pasta , Salad , and Sandwich . Salad was the preferred choice of most consumers, but the group was divided according to dislike for the other meals. The group on the top left quadrant disliked food that is hearty, while the group of the bottom left quarter disliked the Pasta .

These results show that the preference patterns were similar among consumers (i.e., they are not scattered all over the map) under the same condition; however, these patterns differed between conditions.

3.2. Effect of Evaluation Condition on the Liking Scores

The two-way ANOVA results showed that the two effects studied (sample and condition) were significant for the liking scores ( F = 25.51, p < 0.001 and F = 17.81, p < 0.001, respectively). The interaction was also significant ( F = 3.61; p < 0.001), indicating that the differences between the samples depended on the condition, and differences between conditions depended on the samples.

In the evaluation of the products as a photograph of the meal on a plate (Meal-Photo condition), participants were not aware that the meal was a ready-to-eat product; they evaluated the expected liking for the meal itself. Values ranged from 5.8 to 7.5 ( Table 3 ); Salad and Pasta obtained the highest expected liking mean values, and Beans received the least expected liking values.

Liking mean values, and standard deviation in parenthesis, of the five products evaluated on a plate (Meal-Photo condition), in the pack (Pack Alone condition) and after tasting with the pack in view (Tasting-Pack alone condition).

* Different superscript letters within the same column (condition) denote significant differences according to the Tukey’s test.

When evaluating the meal as a ready-to-eat product (Pack Alone condition), expected liking values were lower (4.7 to 6.8). Salad elicited the highest expected liking values, while Beans received the lowest. The Spanish word used in liking evaluations (“gustar”) has a heavy hedonic connotation. However, a more specific, food-related word like “tastiness” (“sabroso” in Spanish) could have been used, taking into account some previous findings [ 26 ] that showed that tastiness affects human response differently than preference (and healthiness).

After tasting the meals with the packaging in view, liking values varied from 5.3 to 7.4. Salad was most liked; it was significantly higher than the rest of products, which did not significantly differ.

To evaluate how the concept of ready-to-eat meals affected the liking expectation, the score subtractions of the mean values in different conditions and their significance were analysed ( Figure 5 ). Comparisons between Meal-Photo and Pack Alone conditions indicated whether knowing that a meal was a ready-to-eat product affected liking expectations. All products showed a significant decrease in expected liking values (except Meatballs , whose decrease was not significant) when they were evaluated in their packaging. These results indicate that consumers had a bad perception of packaged ready-to-eat products from the meal photographs, or they expect the industrial product to be worse than a homemade or restaurant meal. Previous studies also found that in comparison with homemade meals, chilled ready-to-eat meals were less desirable and associated with lower sensory quality [ 27 ]. Beyond expected liking, other factors could explain the decrease in the liking scoring. One might be the awareness of the presence of additives, which appeared in the ingredients lists. The ready-to-eat meals contained food additives ( Table 1 ) that are generally linked with unnatural or artificial and unhealthy substances [ 28 , 29 , 30 ]. Furthermore, in this study, consumers could associate the presentation (Meal on a plate photo) with a homemade meal. Moreover, a previous study showed that when consumers are involved in the preparation of a meal, there is an increase in liking scores [ 31 ]; therefore, it is likely that if the presented ready-to-eat meals had required more consumer involvement, they would have received higher liking scores. Although the ready-to-eat meals were presented with the pack displaying the list of ingredients, they have undergone unknown industrial processes, increasing consumer distrust [ 32 ].

Liking mean values of each of the five meals evaluated on a plate (Meal-Photo condition), in the pack (Pack Alone condition), and after tasting with the packaging in view (Tasting+Pack condition). Differences between conditions (Pack- Meal Photo, Tasting Pack-Pack and Tasting pack- Meal Photo) are indicated with line segments over the top of the corresponding columns; significant differences are marked with an asterisk (*). Only the negative part of the standard deviation bars are shown for clarity.

The extent of the decreased liking was different depending on the meal, and was apparently related to the type of packaging. The decrease in expected liking was low for Meatballs and Pasta , which were presented in a plastic tray that is designed to simulate a plate, with a cardboard envelope that could project the idea of a better-quality product.

The highest decrease in expected liking mean values corresponded to the Sandwich and Beans . Packaged sandwiches in a triangle pack (well-known in European countries) are an incipient meal modality in Spain with a narrow range of variety in terms of brands, fillings, and type of bread. The poor result can therefore be attributed to a lack of confidence in this industrial product. In Spain, sandwiches are a familiar meal concept (“bocadillo”) which is available and freshly prepared in cafeteria-like restaurants or at home; however, consumers are not familiar with sandwiches as a ready-to-eat, packed product, which could explain the impact on liking. In contrast, Beans are a traditional, usually homemade Spanish meal (“Fabada”). The fact that they were packaged in a can probably led to the association with food of lesser quality compared to the other types of packaging. Previous studies have shown that consumers usually perceive canned food as being more processed than other ready-to-eat products [ 33 , 34 ].

To evaluate the impact of tasting on the liking of the ready meal products, the differences between the scores obtained when tasting the product with the Tasting+Pack condition and those with the Pack Alone condition were analysed ( Figure 5 ). In addition, the differences between the scores obtained in the Tasting+Pack and Meal-Photo conditions were also studied to determine whether the ready to eat product (Tasting+Pack condition) met the expectations raised by the meal on a plate ( Figure 5 ).

When tasted, the Beans and Salad mean scores increased significantly compared to the expectation created by the corresponding pack ( Figure 5 ). For these products, which saw a significant drop in the expected liking values when presented in the pack, liking values increased after tasting, coming in line with what consumers expected from the meal on a plate photo. These results could be attributed to the sensory quality of products that can counteract the “ready meal” effect; in other words, the product (Tasting+Pack) met the hedonic expectations of consumers. Beans presented the highest recovery effect (actual liking was even slightly higher than expectation after having seen the meal on a plate).

For Sandwich , tasting increased the liking value slightly with respect to the pack evaluation, but the difference was not significant. Sensory quality was found to be insufficient to increase liking, which remained significantly lower than what consumers had expected when observing the meal on a plate. For Pasta and Meatballs , tasting slightly decreased liking with respect to pack evaluation, but the difference was not significant. However, liking values for these products when tasted were significantly lower than expected from the meal due to the conjoint effect of the packaging and poor sensory quality.

Thus, both the Pack Alone and Tasting+Pack conditions influenced liking. Packaging has, in general, a negative impact on meal liking expectations, but sensory quality can influence this in either a positive or a negative way. Therefore, both effects need to be considered to fully understand consumer liking for ready-to-eat products.

3.3. Effect of Evaluation Conditions on Expected Satiety

The two-way ANOVA results showed that the sample and evaluation conditions had significant effect ( F = 174, p < 0.0001 and F = 3.4, p = 0.034, respectively) on expected satiety values; the interaction between both effects was also significant ( F = 2.1, p = 0.028). However, most of the variability depended on the sample, while the effects of condition and their interaction were less significant.

Expected satiety scores were significantly different between samples when a photograph of the product on a plate was evaluated ( Table 4 ). Consumers considered the Sandwich to be the least satiating, with a mean score of 3.5, implying that they would expect to be hungry and need to eat again by mid-afternoon.

Expected satiety mean values, and standard deviation in parenthesis, of the five products evaluated on a plate (Meal-Photo condition), in the pack (Pack Alone condition) and after tasting with the packaging in view (Tasting-Pack alone condition).

* Different superscript letters within the same column (condition) denote significant difference according to Tukey’s test.

For the Salad , expected satiety showed an intermediate mean value (4.0, enough to last until mid-afternoon), while the Pasta , Meatballs and Beans were considered more satiating, with mean scores between 5.3 and 6 (enough to last until dinner).

The patterns of differences in expected satiety between products were similar for the other two conditions, i.e., where meals were evaluated having the pack present (Pack Alone and Tasting+Pack conditions), in which the Sandwich and Salad obtained the lowest mean values ( Table 4 ). Previous authors have shown that one of the most fundamental factors in satiety is the energy content of the meal [ 22 , 35 ]. However, on the packaging, consumers had information concerning the ingredients, caloric content, and nutritional composition; still, the belief that sandwiches and salads were “light” meals influenced the expected satiating scores, even though the energy (Kcal) values were similar between the five dishes. This showed that consumers tend not to pay attention to the information on the label, believing that salads and sandwiches are less caloric. A previous study [ 36 ] showed how a pasta salad labelled as “healthy” or “hearty” influenced self-reported satiety, consumption volume, and subsequent consumption of another food. Pasta , Meatballs and Beans are typically served warm and were probably seen as being more complete, satiating meals.

Regarding the differences between the evaluation conditions, as shown in Figure 6 , the Meatballs and Salad did not show significant differences in satiety perception under any of the conditions. For Pasta and Sandwich, expected satiety was higher in the Pack Alone condition than in the Meal-Photo condition. A difference for Sandwich was also observed when comparing the Tasting Pack and the Meal-Photo conditions. For Bean, the expected satiety was lower when evaluating the packaging alone, but this increased significantly when the product was tasted (Tasting+Pack condition), achieving a value that was similar to that expected from the meal on the plate photo. The Beans were canned, and the contents were perceived as being smaller on the pack than on the plate; however, the sensory characteristics of Beans , related to the rich, strong flavours in this meal, may have reinforced or evoked satiation in consumers, allowing them to achieve a similar score to the expected one based upon looking at a photograph of the meal on a plate. Both flavour and thickness have previously been shown to enhance satiety expectations [ 37 ].

Expected satiety mean values of each meal evaluated on a plate (Meal-Photo condition), in the pack (Pack Alone condition), and after tasting with the packaging in view (Tasting+Pack condition). Differences between conditions (Pack- Meal Photo, Tasting Pack-Pack and Tasting pack- Meal Photo) are indicated with line segments over the top of the corresponding columns; significant differences are marked with an asterisk (*). Only the negative standard deviation bars are shown for clarity.

These results indicate that expected satiety scores were associated with the actual presented meal, rather than whether it was a commercial ready-to-eat product or not, or based upon its sensory properties. Previous authors have shown that consumers have ideas about satiation for each kind of meal based on previous eating experiences [ 38 , 39 ].

Although previous studies [ 22 ] have suggested links between consumer scores of expected satiety and liking (among other factors), in the present study, for all conditions, no significant relationship was found between these variables.

3.4. Effect of Evaluation Conditions on Healthiness Perception

Table 5 shows the scores of healthiness perception of the five products under the three conditions. The ANOVA results indicate that healthiness perception varied depending on the product, evaluation condition, and their interactions ( F = 19.85, p < 0.0001; F = 75.31, p < 0.0001; F = 2.44, p = 0.013, respectively).

Healthiness perception mean values, and the standard deviation in parentheses, of the five products evaluated on a plate (Meal-photo condition), in the pack (Pack alone condition) and after tasting with the packaging in view (Tasting-Pack alone condition).

In the three conditions, Salad was considered the healthiest meal, and Pasta and Meatballs the least healthy.

The perception of healthiness values were significantly lower in the Pack Alone conditions than those obtained through looking at the meal on a plate (Meal-Photo condition), except for Beans , which did not significantly decrease ( Figure 7 ). These results confirm that in consumers’ minds, processed or prepared meals are less healthy than homemade versions. The extent of the difference between the perception of healthiness under these two conditions depended on the product; the highest drop seen (1.3) was for the Sandwich , which was considered healthier on the plate than in the Pack Alone. Salad also showed a strong decrease in healthiness perception (1.1) when evaluated in the Pack Alone condition, when the participants were aware of its being a ready-to-eat product. However, the Salad was still considered the healthiest product (7.1).

Healthiness perception mean values of each of the five meals evaluated on a plate (Meal-Photo condition), in the pack (Pack Alone condition), and after tasting with the packaging in view (Tasting+Pack condition). Differences between conditions (Pack- Meal Photo, Tasting Pack-Pack and Tasting pack- Meal Photo) are indicated with line segments over the top of the corresponding columns; significant differences are marked with an asterisk (*). Only the negative part of the standard deviation bars are shown for clarity.

One or more elements of the packaging can also contribute to such differences (this was not the focus this study). Still, since all products underwent a decrease in healthiness perception when observed in their packaging, changes in perception seem to be based on the preconceptions that consumers had towards commercial, ready-to-eat meals, as opposed to their energy content or nutritional value. Previously, studies have shown how ready-to-eat meals have been associated with high levels of fat, sugar, and salt [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. However, nowadays it cannot be assumed that all homemade meals are healthier than their ready meal counterparts [ 40 ].

Table A1 shows that Salad was the meal with the highest fat and saturated fat content (because of the sauce, bacon, and cheese); however, it scored as the healthiest, because of the belief that a Salad is a light meal. In addition, a previous study reported that consumers have more difficulty perceiving the healthiness of a whole meal than they do when inspecting the individual ingredients [ 41 ].

Further study on using different elements in the packaging design could counterbalance the negative perceptions that consumers have about ready meals. Also, study of the variations between products of the same category with fewer and more controlled differences (e.g., brand, kind of package, and subtler differences in ingredients) should be conducted.

Tasting also had an impact on healthiness perception, even with the knowledge that the meals were ready-to-eat products (Tasting+Pack condition). After tasting, the healthiness perception of Sandwich , Meatballs , and Salad significantly increased compared to the Pack Alone condition, while the values did not significantly differ from those in the Meal-Photo condition. This effect seems to be linked a product’s sensory qualities, which can disconfirm the initial, low expectations that can result from seeing the packaging. Comparing the meal on a plate (Meal-Photo condition) and the tasted meal (Tasting+Pack), only Pasta showed a decrease in the healthiness score.

4. Conclusions

This study aimed to determine whether consumers change their (expected) liking, expected satiety, and healthiness perception when they learn that a meal is ready-to-eat. The evaluation of the meal on a plate, with no indication that it was a commercial, ready-to-eat meal, was included as a way of evaluating consumer expectations regarding the meal, which were then compared to ready-to-eat meal products. These comparisons allowed us to gain a fuller understanding of consumers’ responses to this category of products. Knowing the product was a commercial, ready-to-eat one had a negative impact on liking expectations and healthiness perception compared to when the meal was presented on a plate and consumers were not aware that they were seeing a commercial, ready-to-eat product. This could be explained by the fact that homemade meals are still considered more likeable and healthier, as they do not contain additives that consumers consider a health risk, and are not industrially processed. Additionally, if ready meals required more consumer involvement, they would receive a higher liking score, and consumers would be more trustful. Furthermore, if consumers could read and understand nutritional information concerning homemade meals, their healthiness perception of ready meals might improve.

The sensory quality of ready-to-eat meals can counteract the negative impact on liking and healthiness perception. Therefore, a ready-to-eat product with optimised sensory qualities can be a liked and perceived healthy product, such as might be expected from a homemade or restaurant-bought meal. Satiety expectations were defined by the type of meal and were slightly affected by the packaging information and sensory properties. Future studies are needed to determine the elements (characteristics on the packaging and sensory properties) that maximise liking, healthiness, and satiety perception to optimise both the sensory and packaging properties of ready-to-eat products.

As a limitation, in the present study, consumer variables other than age and gender were not controlled. Some other demographic characteristics might have influenced consumer responses.

Acknowledgments

Author L.L. thanks the Spanish “Juan de la Cierva” program for her contract for her contract (IJCI-2016-27427). Author B.G. is grateful to the “Erasmus Mundus Cruz del Sur” Program for her post-doctoral fellowship, which allowed her to stay in the Food Technology Department, Veterinary School from the University of Murcia.

Nutritional facts of the ready-to-eat products.

Author Contributions

Conceptualisation, B.G., M.D.G. and A.T.; methodology, B.G., M.B.L., A.T. and M.D.G.; formal analysis, B.G. and A.T.; writing, M.B.L., M.D.G., and S.F.; writing—review and editing, L.L. and S.F.; supervision, M.D.G., S.F. and A.T. All authors have read and agreed to the published version of the manuscript.

Authors are grateful to the Spanish Ministry of the Economy and Competitiveness for financial support (project AGL-2016-75403-R) (support of EU FEDER funds).

Conflicts of Interest

The authors declare no conflict of interest.

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Peer-reviewed

Research Article

Effects of Ready-to-Eat-Cereals on Key Nutritional and Health Outcomes: A Systematic Review

* E-mail: [email protected]

Affiliations University Medical Center Groningen, University of Groningen, Center for Medical Biomics, Groningen, The Netherlands, Nutrition Reviewed, Murnau, Germany

Affiliation Cereal Partners Worldwide, Lausanne 1008, Switzerland

• Marion G. Priebe, 
• Jolene R. McMonagle

• Published: October 17, 2016
• https://doi.org/10.1371/journal.pone.0164931
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In many countries breakfast cereals are an important component of breakfast. This systematic review assesses the contribution of consumption of ready-to eat cereal (RTEC) to the recommended nutrient intake. Furthermore, the effects of RTEC consumption on key health parameters are investigated as well as health promoting properties of RTEC.

The Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE and CINAHL have been searched up till 16 th of June 2015. Randomized controlled trials were excluded if RTEC were used during hypocaloric diets, if RTEC were eaten at other times than breakfast and if breakfasts included other products than RTEC, milk and fruit. Observational studies were excluded when “breakfast cereals” were not defined or their definition included cooked cereals. From cross-sectional studies only data concerning energy and nutrient intake as well as micronutrient status were used.

From 4727 identified citations 64 publications met the inclusion criteria of which 32 were cross-sectional studies, eight prospective studies and 24 randomized controlled trials. Consumption of RTEC is associated with a healthier dietary pattern, concerning intake of carbohydrates, dietary fiber, fat and micronutrients, however total sugar intake is higher. Persons consuming RTEC frequently (≥ 5 times/week) have a lower risk of inadequate micronutrient intake especially for vitamin A, calcium, folate, vitamin B 6, magnesium and zinc. Evidence from prospective studies suggests that whole grain RTEC may have beneficial effects on hypertension and type 2 diabetes. Consumption of RTEC with soluble fiber helps to reduce LDL cholesterol in hypercholesterolemic men and RTEC fortified with folate can reduce plasma homocysteine.

One of the review’s strengths is its thorough ex/inclusion of studies. Limitations are that results of observational studies were based on self-reported data and that many studies were funded by food-industry.

Consumption of RTEC, especially of fiber-rich or whole grain RTEC, is implicated with several beneficial nutritional and health outcomes. The effect on body weight, intestinal health and cognitive function needs further evaluation. Of concern is the higher total sugar intake associated with frequent RTEC consumption.

Citation: Priebe MG, McMonagle JR (2016) Effects of Ready-to-Eat-Cereals on Key Nutritional and Health Outcomes: A Systematic Review. PLoS ONE 11(10): e0164931. https://doi.org/10.1371/journal.pone.0164931

Editor: Jacobus van Wouwe, TNO, NETHERLANDS

Received: June 2, 2016; Accepted: October 4, 2016; Published: October 17, 2016

Copyright: © 2016 Priebe, McMonagle. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This systematic review was sponsored by Cereal Partners Worldwide, Lausanne 1008, Switzerland. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: JRM is an employee of Cereal Partners Worldwide, Lausanne 1008, Switzerland. MGP received payment from Cereal Partners Worldwide for conducting the systematic review. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction

Extensive research has been shown that eating breakfast compared to skipping breakfast results in improved macro- and micro-nutrient intake and status [ 1 ], can reduce the risk of weight gain [ 2 ] and has beneficial effects on cognitive and academic performance [ 1 ; 3 ] and development of diseases such as type 2 diabetes [ 4 ] and cardiovascular diseases [ 5 ; 6 ]. In many countries breakfast cereals (BC) are considered the main component of a balanced breakfast. A considerable number of studies are conducted to investigate the impact of the consumption of BC on nutritional and health benefits [ 7 – 12 ]. In addition, several reviews summarize their effects on either specific health outcomes [ 13 ; 14 ] or comprehensively on nutritional and health benefits [ 15 ]. The group of BC comprises many different cereal products and can be divided roughly into cooked cereals, like porridge type breakfasts, and ready-to-eat cereals (RTEC) or “cold” breakfast cereals like corn flakes and muesli. It is obvious that nutritional and health benefits depend on the composition of the breakfast meal. Many observational studies do not differentiate between RTEC and cooked cereals and in intervention trials BC are often either only part of breakfast or consumed not only for breakfast. To obtain more specifically information on nutritional and health benefits of cereals consumed at breakfast it is necessary to consider the specific composition of BC while summarizing and evaluating the available evidence. Therefore, in this systematic review, studies are included that investigate the effect of RTEC only and an attempt is made to relate their specific composition to specific health benefits.

Two questions are addressed:

• To what extent does consumption of RTEC contribute to the recommended nutrient intake of children, adolescents and adults?
• What are the effects of RTEC consumption on key health parameters in healthy persons as well as in persons at risk of disease and what are health promoting properties of RTEC?

Data from all available observational cohort studies and (randomized) controlled trials (RCTs) have been systematically reviewed and summarized. “Key health parameters” assessed were outcomes related to energy metabolism, weight management, cardiovascular health, digestion/gut health, immune function, performance, bone growth and development. RCTs compared either the health effect of consuming different amounts of RTEC or different types of RTEC (e.g. high- vs low-fiber RTEC). Data from cross-sectional studies have not been considered for assessing the effect on health parameters due to their limited strength of evidence.

A protocol of this systematic review is available as supporting information ( S1 Protocol ). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and the guidelines for the Meta-analysis of Observational Studies in Epidemiology (MOOSE) were followed [ 16 ; 17 ]. The PRISMA and MOOSE checklists are available as supporting information ( S1 and S2 Checklists). Due to the low number and the diversity of the studies addressing one specific health outcome a meta-analysis was not carried out.

Data sources and literature search

The Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE and CINAHL have been searched with no time limit and no language restriction on 26 th of February 2014 by MGP (investigator). The following MEDLINE search strategy has been used and adapted for the other electronic databases searched: 1) Breakfast OR fortified OR ready-to-eat, 2) Cereal OR cereals, 3) 1 AND 2. No specific search items have been used for nutritional and health outcomes as we aimed for a wide range. The search was updated with the identical search-strategy on 16 th of June 2015. In addition, the reference lists of all included studies and of review articles have been searched in order to identify additional studies of interest. The title and abstract of each record of the search have been assessed by two reviewers (MGP, JRM) independently. Studies have been rejected if the article, based on the abstract, definitely did not meet the review's inclusion criteria, otherwise the full text of the study has been obtained and screened. Abstracts for which no full text papers were available were excluded. Differences between reviewers' results have been resolved by discussion. Studies were included if they were RCTs or prospective studies and if they assessed energy and nutrient intake or outcomes related to energy metabolism, weight management, cardiovascular health, digestion/gut health, immune function, performance, bone growth and development. Cross-sectional studies were included if they assessed energy intake, nutrient intake and micronutrient status. RTEC were defined as “a cereal food that is processed to the point where it can be eaten without further preparation, as in boxed cereals”, thus cold cereals were defined to be RTEC. RCTs were excluded if they assessed breakfast skippers vs breakfast eaters, if RTEC were used as meal replacer or during hypocaloric diets, if RTEC were eaten at other times than breakfast, if breakfasts included other products than RTEC, milk and fruit and if breakfasts differed in carbohydrate content in studies comparing postprandial blood glucose and/or insulin. Observational studies were excluded when “breakfast cereals” were not defined or the definition of “breakfast cereals” included cooked cereals. From cross-sectional studies only data concerning energy and nutrient intake as well as micronutrient status were used.

Data extraction process and assessment of risk of bias

From original reports of the studies data were extracted by one reviewer (MGP) according to pre-designed extraction forms which were validated and used already in a similar systematic review [ 18 ]. From RCTs the following data were extracted:

• General information: title, authors, country, year of publication, funding, duplicate publication;
• Trial characteristics: design, duration, randomizations, concealment of allocation, blinding, checking of blinding;
• Intervention: length of intervention, dietary advice/diet provided, comparison interventions;
• Participants: population, exclusion criteria, number (total, per compared groups), age, gender, health condition; diagnostic criteria used to define health condition, similarity groups at baseline, assessment of compliance, withdrawals/losses to follow-up;
• Outcomes: outcomes specified above (primary and secondary outcomes of the studies);
• Results: for outcomes and times of assessment (including a measure of variation), intention-to-treat analyses.

The following data were extracted from cohort studies:

• General information: title, authors, country, year of publication, duplicate publication;
• Study characteristics: design, dates of enrolment, follow-up;
• Exposure: type, type of measurement, validation of measurement, time-points measurements;
• Outcome: type, criteria used, type of measurement, validation of measurement;
• Participants: number, characteristics;
• Results: total number of cases, cases in group with lowest and highest intake, results of outcome, confounders adjusted for.

Risk of bias of RCTs and the methodological quality of prospective and cross-sectional studies were evaluated by one reviewer (MGP). The Cochrane Collaboration’s tool for assessing risk of bias [ 19 ] was used for the appraisal of RCTs. The following seven items were assessed and rated as “low”, “high” or “unclear risk” of bias: random sequence generation, allocation concealment, blinding participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other bias. As “other bias” the appropriateness and methodology (washout period, analysis) of the cross-over design in cross-over studies was examined. For the assessment of the quality of observational studies the following criteria were examined [ 18 ]: methods for selecting study participants, number of appropriate confounders investigated and adjusted for; quality of method used to assess dietary intake, e.g. food frequency questionnaire with/without validation, quality of method used to assess outcome measures: e.g. self-report with/without validation, or direct measurement/medical records and additional for prospective studies: duration/completeness of follow-up.

Description of studies

The results of the literature search and the progress through the different stages of the review process are depicted in the PRISMA flow diagram ( Fig 1 ). A total of 64 publications (all published in English) met the inclusion criteria, of which 32 were cross-sectional studies [ 7 ; 9 ; 20 – 49 ], eight prospective studies [ 8 ; 50 – 56 ] and 24 RCTs [ 10 – 12 ; 57 – 77 ].

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Characteristics of cross-sectional studies are presented in Table 1 , those of prospective studies in Table 2 and those of RCTs in Table 3 . The impact of RTEC consumption on nutrient intake was addressed in all cross-sectional studies as well as in three prospective studies (cross-sectional at baseline [ 51 ; 53 ] and prospectively [ 51 ]) and one RCT [ 11 ]. All RCTs and prospective studies assessed health parameters, which were risk factors for cardiovascular disease [ 10 ; 11 ; 52 ; 54 ; 56 ; 58 ; 62 ; 66 ; 68 ; 69 ; 71 ; 72 ; 77 ] and type 2 diabetes [ 50 ; 55 ; 59 ; 60 ; 64 ; 67 ; 70 ; 74 ], BMI/body weight/satiety/food intake [ 8 ; 11 ; 12 ; 51 ; 54 ; 57 ; 59 – 62 ; 65 ; 73 ; 76 ], digestion/gut health [ 10 ; 58 ; 69 ] and cognitive performance [ 53 ; 63 ; 75 ]. No publications were found assessing immune function and bone growth and development. The risk of bias for all individual RTCs is depicted in Fig 2 . Overall the RCTs had a low or unclear risk of bias. Based on the items assessed, all selected observational studies have been judged to be of appropriate methodological quality. As many studies (45 studies, Tables 1 – 3 ) were funded by food industry, funding is also reported together with the results.

Green (+) indicates low risk of bias; Red (-) indicates high risk of bias; and Yellow (?) indicates unclear risk of bias. NA: not applicable, * for cross-over studies only.

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Nutritional benefits—associations and effects of interventions

One prospective [ 54 ] and 31 cross-sectional studies in different countries (15 in the USA [ 7 ; 23 ; 25 ; 27 – 29 ; 31 ; 32 ; 34 ; 36 ; 42 – 44 ; 47 ; 48 ], three in Canada [ 22 ; 24 ; 46 ], two each in Spain [ 33 ; 41 ], Ireland [ 37 ; 39 ], Australia [ 26 ; 45 ] and France [ 9 ; 38 ] and one each in Scotland [ 40 ], Cyprus [ 20 ], Greece [ 35 ], Malaysia [ 21 ] and Guatemala [ 30 ]) investigated the association between RTEC consumption and daily nutrient intake. From two prospective studies [ 51 ; 53 ] baseline data concerning RTEC consumption and daily nutrient intake were also used. One cross-sectional study assessed the impact of RTEC consumption on micronutrient status only [ 49 ].

23 studies included only children/adolescents [ 7 ; 20 – 23 ; 26 ; 27 ; 29 – 31 ; 35 ; 36 ; 38 – 41 ; 43 – 45 ; 47 – 49 ; 51 ], eight studies only adults [ 9 ; 24 ; 25 ; 28 ; 34 ; 37 ; 38 ; 53 ], one study children and adults [ 42 ] and in three studies the age-range comprised children/adolescents and adults [ 32 ; 33 ; 46 ] (categorized in “adult” studies). In cross-sectional studies frequency of RTEC consumption was mainly assessed with single and repeated 24-h dietary recalls ([ 20 – 24 ; 27 – 35 ; 42 ; 44 ; 47 ; 49 ] and [ 9 ; 26 ; 45 ] respectively) ( Table 1 ). In addition, food diaries of 14 [ 7 ; 25 ; 36 ], 7 [ 37 ; 43 ; 46 ] and 3 days [ 78 ] as well as 5 –and 7 day weighted food records were used [ 40 ; 41 ]. Two studies applied the dietary history method [ 38 ; 39 ]. Due to the variation in registration of food intake, comparisons of high or low frequency of RTEC consumption in these studies varies from 1 serving/day vs none to 7/14 day vs < 2/14 days. RTEC consumption at breakfast only was monitored in 20 studies [ 20 – 24 ; 26 ; 28 ; 29 ; 31 ; 32 ; 34 ; 38 ; 40 ; 41 ; 43 ; 45 ; 47 ; 48 ; 51 ; 54 ]. RTEC consumption during the whole day was assessed in 14 studies of which in four it was demonstrated that most of the RTEC were consumed at breakfast (Ireland: 91% [ 37 ], Spain: 67% [ 33 ], France: 89% [ 9 ], Guatemala: 93.2% [ 30 ]) and in three studies that a high percentage of the population was eating RTEC at breakfast (USA: 63% of 10 y olds and 65% of young adults [ 42 ] and 87,3% of 4–12 y old children [ 44 ], Greece: 60% of boys and 58% of girls [ 35 ]). As RTEC, based on these numbers, are predominately eaten at breakfast, all the studies were included. One RCT in adults examined the impact of substituting a traditional breakfast by RTEC on daily macronutrient consumption [ 11 ].

Associations of RTEC consumption with daily intake of energy, macronutrients, cholesterol, dietary fiber (DF) and sodium.

For summarizing cross-sectional data about the association between RTEC consumption and daily intake of energy, macronutrients, cholesterol, DF and sodium in children/adolescents, 33 data sets from 24 studies were available. More data sets per study were available when the investigators reported their results per sex and/or in several age groups ( S1 Table and Table 4 ). 18 of these studies were (in part) funded by food industry. Higher frequency (approximately ≥ 5 serving/week) of RTEC consumption in children/adolescents was associated with higher intake of DF, carbohydrates and total sugars in 75%, 65% and 63% of the data sets respectively and with lower intake of cholesterol and fat, expressed as total amount and as energy percentage in 83%, 50%, and 60% of the data sets respectively. Energy, saturated fat, sodium and protein intake was not associated with RTEC consumption in most data sets (in 77%, 75%, 81% and 86% respectively). Associations were similar in the 6 studies (9 data sets) [ 20 ; 21 ; 41 ; 43 ; 48 ; 51 ] with no food-industry related funding, except that total amount of fat was only reduced in 22% of the 9 data sets and dietary fiber intake was only higher in 25% of the 4 data sets in which it was measured. In the other data sets (78% and 75%) no difference of fat and dietary fiber intake was reported.

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For summarizing the results in adults 16 data sets from 12 studies were available ( S1 Table and Table 4 ). One of these studies [ 28 ] received no food-industry related funding. Higher frequency (approximately ≥ 5 serving/week) of RTEC consumption in adults was associated with higher intake of DF, carbohydrates and total sugars in 93%, 100% and 100% of the data sets respectively and lower intake of fat expressed as energy percentage (in 100% of data sets) but not if expressed as total amount. The associations of RTEC consumption with saturated fat and cholesterol intake were not consistent, whereas most data sets (62%) did not show an association with energy and protein intake.

One study (funded by food industry) investigated the association between RTEC consumption and daily intake of energy, macronutrients, cholesterol, DF and sodium prospectively [ 54 ] ( Table 2 ). In secondary analyses of a RCT, 8–10 y old children were followed for 7.5 y Higher frequency (3 vs 0 serving/3 days) of RTEC consumption at breakfast was associated in girls and boys with a higher percentage of energy intake from carbohydrates and protein as well as a lower percentage from total and saturated fats. In addition, an association with higher intake of DF and lower intake of cholesterol was found whereas energy and sodium intake was not related. For boys, but not for girls, RTEC consumption was associated with higher intake of total sugars.

Associations of RTEC consumption with the percentage of populations receiving inadequate amounts of vitamins and minerals.

17 studies (of which one [ 20 ] was not funded by food industry) investigated the association of frequency of RTEC consumption with the proportion of the population receiving inadequate vitamins and minerals, of which ten studies were conducted in children/adolescents [ 7 ; 20 ; 22 ; 23 ; 26 ; 27 ; 36 ; 39 ; 44 ; 47 ], five studies in adults [ 24 ; 25 ; 33 ; 37 ; 46 ] and two in both categories [ 32 ; 42 ] ( Table 1 ).

Inadequate micronutrient intake was defined as “below the estimated average requirement (EAR)” in ten studies [ 22 – 25 ; 27 ; 32 ; 36 ; 37 ; 44 ; 46 ], as “receiving less than two-thirds of the recommended dietary allowance (RDA)” in three studies [ 20 ; 33 ; 42 ] and as “consuming less than 100% of RDA, “consuming less than 80% of RDA”, “probability of not achieving 100% of EAR “and “percentage who did not achieve LRNI” in one study each [ 7 ; 26 ; 39 ; 47 ]. The EAR is defined as the intake adequate for 50% of the population, the RDA is the average daily dietary intake level that is sufficient to meet the nutrient requirement of nearly all (97 to 98 percent) healthy individuals and the LRNI is the amount estimated to meet the needs of 2.5% of the population with the lowest requirements.

The prevalence of inadequate vitamin and mineral intake by breakfast group (lowest vs highest RTEC consumption) for 14 micronutrients is given in S2 Table . 19 data sets were available for children/adolescents and 11 for adults. In 15 data sets it was assessed whether the prevalence of inadequacy between low and high RTEC consumers is significantly different.

Combining these results, significant reductions of prevalence of inadequacy associated with RTEC consumption were observed for all vitamins and minerals. Prevalence of inadequacy as well as magnitude of reduction varied depending on country, age group, sex and method of assessment ( S2 Table ).

To assess the nutrients for which the prevalence of inadequacy was reduced the most, those nutrients were scored which had the four highest reductions of inadequacy. In case that an equal percentage of reduction was observed for more micronutrients, all micronutrients were scored, thus more micronutrients per reduction level were possible ( S2 Table ). To reduce imbalance due to limited assessment of micronutrients, data of studies were excluded which reported less than eight micronutrients, resulting in 11 data sets for children and eight for adults. The scored micronutrients of different populations were then combined: data of adults in which significance was assessed (7 data sets), data of children in which significance was assessed (6 data sets), all adult and all children/adolescent data sets.

When using only data sets that assessed significance, in children/adolescents as well as in adults, reductions of prevalence of inadequacy due to RTEC consumption were highest for vitamin A (range: 7–21% and 5–37% respectively), calcium (17–39% and 6–40% respectively), folate (5–28% and 7–50% respectively), magnesium (7–11% and 4–26% respectively) and zinc (9% and 19–37% respectively). In adults, high reductions were also seen for vitamin B 6 (7–55%) and C (6–21%).

When combining all data sets, for children/adolescents as well as for adults consistently the greatest reductions of prevalence of inadequacy was observed for vitamin A (range: 7–28% and 5–37% respectively), calcium (17–39% and 6–43% respectively), folate (5–50% and 7–50% respectively), vitamin B 6 (31–37% and 7–55% respectively), magnesium (7–11% and 4–26% respectively) and zinc (9–15% and 19–37% respectively).

Associations of RTEC consumption with micronutrient status.

In two cross-sectional studies (of which one was funded by food industry [ 38 ]) micronutrient status (12 vitamins and minerals) was measured in populations with and without RTEC consumption [ 38 ; 41 ] ( Table 1 ). In Spanish and/or French children and adolescents consumption of RTEC was associated with higher plasma concentrations of vitamin A (0.10 μmol/l [ 41 ]), β-carotene (0.21 μmol/l [ 38 ]), serum folate (4.1 nmol/l [ 41 ]) and lower erythrocyte glutathione reductase (EGR, 0.07 [ 38 ; 41 ]) which indicates a better riboflavin status. In Spanish adults, a better thiamine and riboflavin status (erythrocyte transketolase 0.03, EGR 0.06) as well as higher β-carotene (0.25 μmol/l) and serum folate concentrations (30 μg/l) were found in the RTEC group [ 38 ].

Another study (no industrial funding) investigated the contribution of consumption of folic-acid enriched RTEC to folate and vitamin B 12 status in US children and adolescents [ 49 ] ( Table 1 ). Higher folate and vitamin B 12 concentrations were associated with consumption of enriched RTEC. However, only a very low percentage of this population (< 0.5%) had folate deficiency or low vitamin B-12 status, probably due to consumption of other grain products which are mandatory enriched with folate since 1996. The percentage of persons with marginally low folate and vitamin B-12 status decreased from 3.4% to 1.7% and from 9.6 to 6.6% respectively [ 49 ] due to additional consumption of RTEC.

The effect of RTEC consumption on macronutrient and DF intake.

In healthy adults substituting the habitual breakfast with RTEC (60 g for women/80 g for men) resulted in a higher percentage of energy from carbohydrates and a lower percentage from total and saturated fat [ 11 ] ( Table 3 ) in this study funded by food industry. Intake of energy, protein and cholesterol stayed the same. No effect on DF intake was observed, but the RTEC administered were relatively low in DF, providing 3 and 4 g DF/day for women and men respectively.

Health benefits—associations and effects of interventions

Associations of rtec consumption with risk factors for cardiovascular diseases..

One prospective study investigated the association of consumption of whole grain vs refined grain RTEC with incident heart failure in a large cohort of male physicians [ 56 ] ( Table 2 ). Decreased risk of heart failure was found for frequent consumers of whole grain RTEC (HR: 0.78 (95% CI 0.64–0.96) for 2–6 servings/wk; HR: 0.72 (95% CI 0.55–0.88) for ≥ 7 servings/wk) but not for those consuming refined RTEC.

Another prospective study investigated the association of consumption of whole grain vs refined grain RTEC with incident hypertension in a large cohort of male physicians [ 52 ] ( Table 2 ). Decreased risk of hypertension was clearly demonstrated for participants with a high consumption of whole grain RTEC (HR: 0.87 (0.81–0.94) for 2–6 servings/wk, HR: 0.80 (0.74–0.86) for ≥ 7 servings/wk), whereas the associations with consumption of refined RTEC was weak and not significant in all groups (HR: 0.86 (95% CI 0.76–0.98) for 2–6 servings/wk, HR: 0.86 (95% CI0.74–1.00) for ≥ 7 servings/wk).

One prospective study [ 54 ] ( Table 2 ) investigated the association between low and high RTEC consumption (0 vs 3 servings/3 days) on blood lipids in a group of 660 children, aged 8–10 years at baseline and with serum LDL cholesterol levels between the 80th and the 98th percentile for sex and age. In the high RTEC group total cholesterol was lower in boys (0.10 mmol/l) but not in girls. LDL cholesterol was lower in boys (0.07 mmol/l) but in girls lower HDL cholesterol (0.05 mmol/l) was observed.

The two prospective studies reporting decreased risk of heart failure and hypertension were not funded by food industry [ 56 ; 52 ], whereas the last described prospective study [ 54 ] which was funded by food industry showed mixed results on blood lipids in children.

Effects of RTEC consumption on risk factors for cardiovascular diseases.

Two RCTs, one in children (overweight or at risk of overweight 6- to 12-year-old Mexican children [ 62 ]) and one in Finnish adults [ 11 ] investigated whether increased consumption of RTEC results in a reduction of blood lipids ( Table 3 ).

Twelve weeks of RTEC consumption (≈ 33 g, different corn and rice based types) resulted in an increase in HDL concentrations (as compared to baseline and the control group) when combined with nutritional education [ 62 ] in children. The changes of other lipid parameters, however, were not different.

In adults with serum cholesterol concentrations above 5.0 mmol/l, six weeks of consumption of RTEC (60 g for women/80 g for men) mainly in the morning instead of the habitual Finnish breakfast resulted in a reduction in total cholesterol by 2.5% (0.16 mmol/l) which was partly due to a reduction in HDL cholesterol (LDL was not measured) [ 11 ]. Intake of saturated fat and total fat was decreased by 2.5 and 5.5 energy% respectively.

Both studies were (partially) funded by the food industry and showed mixed results on the parameters investigated.

The effect of RTEC enriched with different types of DF on blood lipids was investigated in five RCTs [ 10 ; 58 ; 69 ; 71 ; 72 ] ( Table 3 ).

Six week consumption of DF-enriched RTEC providing 5.8 or 11.9 g soluble fiber/day consistently lowered total cholesterol and LDL (by 5.9 or 3,5% and 5.7 or 5.7% respectively) in persons with hypercholesterolemia consuming a low-fat diet [ 71 ; 72 ]. The effective soluble fiber was mainly derived from psyllium whereas soluble fiber from pectin [ 72 ] or wheat bran [ 71 ] did not have a significant cholesterol lowering effect.

Three other, more short-term (3–4 wk), RCTs in healthy volunteers [ 10 ; 58 ; 69 ] investigated the effect of RTEC rich in various DF (inulin-enriched vs inulin-free, whole grain wheat vs wheat bran-based, whole grain maize vs refined maize) on various lipid parameters. No effect on total and HDL cholesterol was found, only the inulin-enriched RTEC (9 g inulin/day) was able to reduce LDL cholesterol compared to baseline (by 0.35 mmol/l, 8.3%) but not to control. However, concentrations of triacylglycerols were reduced compared to baseline and to control (by 0.23 mmol/l, 27.4%) [ 69 ].

Four RCTS were industrial funded, of which two [ 71 ; 72 ] showed positive effects on blood lipids and two no effects [ 10 ; 58 ]. Another RCT [ 69 ], without industrial funding, showed mixed effects.

Three RCTs [ 66 ; 68 ; 77 ] investigated the effect of folate-fortified RTEC on plasma homocysteine (tHcy) ( Table 3 ). It was found that cereals fortified with 200 μg per portion could increase plasma folate concentrations by about 12 nmol/l and lower tHcy by about 1 μmol/l in populations selected based on high plasma tHcy concentrations (≥ 10 μmol/l, [ 68 ]) or not consuming vitamin supplements and RTEC [ 77 ]. Consumption of RTEC with 200 μg folate in combination with other vitamins did not result in different effects [ 77 ]. Homocysteine lowering effects were most effective in subjects with lowest plasma folate concentrations and highest baseline tHcy (tHcy reduction- 1.58 μmol/l and -1.87 μmol/l respectively) [ 77 ]. Venn et al [ 68 ] also tested fortification with 100 and 300 μg folate/portion and found similar tHcy results, concluding that 100 μg folate would be sufficient in population with ≥ 10 μmol /l plasma tHcy. Consumption of RTEC enriched with 440 μg folate in combination with RDA amounts of vitamin B 6 and B 12/portion resulted in small differences in plasma folate (7,5 nmol/l) and homocysteine (-0.4 μmol/l) in a population with in general already relatively high baseline folate and low homocysteine concentrations [ 66 ]. In addition, the reduction of the percentage of persons with high homocysteine (>10.4 μmol/l for women or 11.4 μmol/l for men) was greater in the supplemented group (13% to 3.2%) compared to the control group (10.4% to 7.3%). All three RCTs were funded by industry and showed a positive effect of the intervention.

Associations of RTEC consumption with BMI/weight gain.

One prospective study in adults demonstrated that men consuming at least one portion of RTEC/day gained on average 0.59 and 0.46 kg less body weight after 8 and 13 years respectively than men consuming RTEC rarely [ 8 ] ( Table 2 ). They also had a decreased risk of 22% and 12% to become overweight during 8 and 13 years of follow-up. Associations were also examined for whole grain and refined grain RTEC intake separately but these were not different.

Two prospective studies investigated the relationship between consumption of RTEC and BMI in children with a follow up of 7.5 [ 54 ] and 3 years [ 51 ] ( Table 2 ). Both studies were secondary analyses of RCTs with 8–10 year old children including either both intervention groups [ 54 ] or the control group only [ 51 ]. Lower BMI was associated with more frequent RTEC consumption in both sexes in low-income minority children in one study [ 51 ] (every day of RTEC consumption decreased BMI by 2 percentiles), but only in boys in the other (BMI 20.4 vs 20.1, 0–3 times RTEC/week respectively) [ 54 ].

Negative associations of frequent RTEC consumption with body weight gain were found in all three RCTs, two of which [ 8 ; 54 ] were funded by food industry.

Effects of RTEC consumption on body weight, satiety and food intake.

Two RCTs, one in children (overweight or at risk of overweight [ 62 ]) and one in adults [ 11 ] investigated whether increase of consumption of RTEC results in a reduction in body weight ( Table 3 ). Twelve weeks of RTEC consumption (≈ 33 g, different corn and rice based types) in combination with nutritional education not only prevented the weight gain observed in the other groups but it decreased weight (mean -1.01 kg) and body fat gain (0.8%) [ 62 ]. As these changes were different to that observed after the RTEC intervention without nutritional education, it can be assumed that nutritional education is responsible for this positive effect.

In adults, six weeks of consumption of RTEC (60 g for women/80 g for men) mainly in the morning instead of the habitual Finnish breakfast did not result in change in body weight (secondary objective) [ 11 ].

Both RCTs were funded by food industry and showed no effect of RTEC consumption (alone) on body weight reduction.

Seven RCTs [ 12 ; 57 ; 59 ; 61 ; 65 ; 73 ; 76 ] examined the effect of low DF vs high DF RTEC and/or wholemeal RTEC [ 65 ] on postprandial satiety and five of them also on subsequent energy intake [ 12 ; 57 ; 59 ; 61 ; 73 ] ( Table 3 ). The amount of DF administered with the high DF RTEC varied between 2.3 g and 33 g whereas the control RTEC contained 0–4 g. The types of DF were wheat bran [ 12 ; 61 ; 65 ; 73 ], b-glucan [ 59 ; 76 ] and 2 types of arabinoxylans (AX): hydrolysed wheat bran AX and unhydrolysed flax AX [ 57 ]. Visual analog scales were applied in most studies to measure satiety and/or appetite and a questionnaire in one trial [ 73 ]. Three trials reported a significant difference in satiety/appetite measures. The degree of hunger was lower after ingestion of high versus low DF RTEC [ 73 ]. Furthermore, the average appetite score was highest after the high bran RTEC [ 12 ] and the ß-glucan RTECs resulted in a lower combined appetite score independent from dose [ 59 ].

Positive effects on satiety/appetite measured were found in two industrial funded [ 12 ; 59 ] and one not industrial funded RCT [ 73 ]. No effects were found in three industrial funded RCTs [ 57 ; 61 ; 76 ] and one RCT without industrial funding [ 65 ].

In two trials [ 12 ; 61 ] it was found that a large portion of RTEC (71 and 60 g) containing 33 and 28 g of mainly insoluble wheat fiber can reduce subsequent energy intake ( Table 3 ). After breakfasts providing the same energy, food intake at an early subsequent meal (75 min) was reduced by 160 kcal [ 12 ]. In the other trial the lower caloric value of the high DF RTEC was not compensated at lunch (3 h later) resulting in lower cumulative energy intake (93 kcal) [ 61 ]. In another trial [ 73 ] two experiments were conducted with RTEC containing different amounts of wheat bran. In the first experiment a significant difference in cumulative (breakfast and lunch 3.5 h later) energy intake (≈ 140 kcal) was found after the RTECs with the highest (22 and 20 g) compared to that with the lowest DF content (0 g). In the second experiment comparing the RTEC with the lowest and highest amount of DF, a decrease of energy intake at lunch and of cumulative energy intake was observed after the high DF RTEC (≈ 100 and 200 kcal respectively). In a trial with overweight women consumption of RTEC enriched with 15 g AX (19 g total DF) did not result in decreased energy intake at lunch (4 h later) nor decreased cumulative energy intake compared to the low DF RTECs (4 and 3 g DF) [ 57 ]. In addition, RTEC enriched with a low amount of β-glucan (2.3–5.9 g) did not result in lower energy intake at lunch (4 h later) in overweight persons [ 59 ].

Positive effects of consumption of fiber-rich RTEC on subsequent food intake were found in two RCTs [ 12 ; 61 ] funded by food industry and one RCT without industry-related funding [ 73 ], whereas the other two funded RCTs [ 57 ; 59 ] showed no effect. One RCT (industry funded) investigated the effect of modifying the processing procedure of wheat flakes (sour-dough prefermentation, steam cooking omission, reduction sucrose content) on satiety. Modified wheat flakes successfully reduced hunger feelings at 120, 150 and 180 min after ingestion compared to conventionally produced wheat flakes and white wheat bread [ 60 ] ( Table 3 ). The test meals had similar energy content and differed slightly in macronutrient and DF composition.

Associations of RTEC consumption with development of type 2 diabetes.

One prospective study investigated the association between RTEC (cold breakfast cereals) consumption and incident diabetes in male physicians [ 55 ] ( Table 2 ). Decreased risk of diabetes was clearly demonstrated for participants with a high consumption of whole grain RTEC (HR: 0.76 (95% CI 0.66–0.87) for 2–6 servings/wk, HR: 0.60 (95% CI 0.50–0.71) for ≥ 7 servings/wk), whereas the associations with consumption of refined RTEC were not significant in all groups (HR: 0.69 (95% CI 0.53–0.90) for 2–6 servings/wk, HR: 0.95 (95% CI 0.73–1.3) for ≥ 7 servings/wk) [ 55 ].

Another prospective study investigated the association between consumption of whole grain foods and incident diabetes in women [ 50 ] ( Table 2 ). Analyses of HR of specific whole grain foods showed decrease risk of diabetes for high consumption of whole grain breakfast cereals ((HR: 0.71 (95% CI 0.62–0.82) for 5–6 servings/week and HR: 0.66 (95% CI 0.55–0.80) for ≥ 1/day).

Both these prospective studies showing associations between high consumption of whole grain RTEC and decreased risk of diabetes were not industry funded.

Effects of RTEC consumption on risk factors for type 2 diabetes.

Two RCTs examined to what extent postprandial insulinemia is changed in response to RTEC with different content of DF and different GI [ 64 ; 74 ] ( Table 3 ). 136 g whole grain wheat RTEC enriched with corn bran (GI: 49, 50 g available carbohydrates, 63.5 g DF) compared to 60 g low DF RTEC (GI: 125, 50 g available carbohydrates, 2 g DF) consumed with water reduced postprandial the 2h-AUC of insulin by 50% in healthy volunteers [ 64 ]. Half the portion of those RTEC was administered with milk in the other trial in which 2h-AUC of insulin was only decreased (by 14%) in volunteers with high fasting insulin but not in those with normal insulin values [ 74 ]. Both those industrial funded RCTs found positive effects of fiber-rich RTEC on postprandial insulinemia.

Two RCTs investigated whether addition of soluble fiber to RTEC with the same carbohydrate content results in decreased postprandial glucose and insulin responses [ 59 ; 70 ] ( Table 3 ). In overweight volunteers, corn based RTEC with 4–6 g oat β-glucan did not reduce blood glucose but only decreased the 2h-AUC insulin by 14–17% compared to RTEC without β-glucan [ 59 ]. In healthy volunteers, however, addition of 4.5 g soluble fiber from guar gum to wheat RTEC decreased both the 2 h- AUC glucose and insulin by 47% and 34% respectively compared to control [ 70 ]. The industry funded RCT [ 59 ] found mixed results of consumption of RTEC rich in soluble fiber on postprandial glucose and insulin, whereas the RCT without industry-related funding [ 70 ] found reduction of both parameters.

One RCT (food-industry funded) investigated the effect of modified processing of wheat flakes (sourdough pre-fermentation, suppressing steam cooking) and reduced sucrose content on GI and insulinemic index (reference food was white wheat bread) [ 60 ] ( Table 3 ). The GI of modified whole wheat flakes and standard whole wheat flakes was not different. However, the 90 min and 180 min insulinemic index of the modified flakes was decreased by 20 and 12% respectively.

Another RCT (food-industry funded) investigated whether the low GI of a DF-rich RTEC is caused by a slower rate of appearance of starch-derived glucose (Ra gluc , reflecting starch digestion) or a higher glucose uptake from the blood by tissues (Rd gluc ) [ 67 ] ( Table 3 ). The Ra gluc of the high GI RTEC and low GI RTEC was not different. However, the Rd gluc at 30–60 min was 31% higher after the low GI RTEC which was associated with a 125% higher 0–30 min insulin response. It was hypothesized that the higher protein content of the low GI RTEC (11 g) contributed to the higher insulin response and thereby increased Rd gluc which could explain the low GI despite the same rate of starch digestion.

Effect of RTEC consumption on the composition of the colonic microbiota and on bowel function.

One RCT (without industry-related funding) investigated the effect of 4-wk consumption of inulin-rich (9 g inulin/day) compared to inulin-free RTEC on the composition of the microbiota using selective growth media [ 69 ] ( Table 3 ). It was found that the amount of bifidobacteria was higher after the inulin-rich RTEC compared to control, but only after correction for total anaerobes.

Two RCTs (food-industry funded) investigated the effect of 3-wk consumption of one portion whole grain RTEC/day on the composition of the microbiota with fluorescence in situ hybridization [ 10 ; 58 ] ( Table 3 ). One trial compared whole wheat RTEC (48 g, 5.7 g DF) to a wheat- bran based RTEC (48 g, 13 g DF) [ 10 ], whereas the other compared whole grain maize RTEC (48 g, 7 g DF) to refined maize RTEC (48 g, 0.4 g DF) [ 58 ]. In both trials, only whole grain RTEC consumption increased the amount of Bifidobacterium spp. compared to baseline. The increase in Bifidobacterium spp compared to control, however, was only significantly different in the wheat RTEC trial [ 10 ]. In this trial, also the numbers of Lactobacillus/Enterococcus were higher after the intervention with whole wheat RTEC compared to that with the wheat bran based RTEC.

The same three trials, which assessed the effect of DF-rich RTEC on the composition of the microbiota [ 10 ; 58 ; 69 ] ( Table 3 ), monitored also bowel function as secondary outcome. A daily increase of DF in form of 9 g inulin or 7 g maize fiber did not change bowel habits [ 58 ; 69 ]. During the intervention with wheat-bran based RTEC stool frequency was increased compared to that with whole wheat RTEC, and frequency of soft stools and flatulence increased [ 10 ]. Consumption of whole wheat RTEC resulted in more formed stool [ 10 ]. Consumption of DF-rich RTEC did not have an effect on bowel habits in one industrial funded RCT [ 58 ] and one without industry-related funding [ 69 ]. Another industrial funded RCT [ 10 ] reported improved bowel habits.

Association between RTEC consumption and cognitive decline.

One prospective study (food-industry funded) investigated the association between frequency of RTEC consumption and cognitive decline in elderly subjects over 11 years [ 53 ] ( Table 2 ). Daily consumers of RTEC had a pattern of cognitive decline similar to infrequent consumers.

Effect of RTEC consumption on acute cognitive performance.

One RCT in children [ 75 ] and one in adolescents [ 63 ] investigated the effect of RTEC with low and high GI on acute cognitive performance ( Table 3 ). The low GI RTEC (GI 30 [ 63 ] and 42 [ 75 ]) provided a lower amount of energy and carbohydrates, but higher amounts of protein than the high GI RTEC (both GI 77). In children, after the low GI RTEC secondary memory performance was better and decline in accuracy of attention was attenuated. Speed of attention and memory as well as working memory was not affected by GI [ 75 ]. In adolescents verbal episodic memory tasks were performed under divided attention which measured immediate, short-delay and long-delay memory [ 63 ]. No differences were found comparing the raw data scored after high and low GI RTEC consumption. However, when calculating remembering/ forgetting indices for each participant, it was shown that high GI RTEC improved long-delayed memory. Both RCTs were without industry-related funding and showed either positive [ 75 ] or negative effects [ 63 ] of consumption of low GI RTEC on specific cognitive tasks.

Nutritional benefits

Frequent consumption (≥ 5 servings/week) of RTEC compared to low or no RTEC consumption consistently has been associated with a healthier dietary pattern in children and adults in most studies demonstrating a higher consumption of carbohydrates, DF and a reduction of total fat intake and cholesterol (only for children). Thus, current dietary recommendations are more likely to be met by RTEC consumers.

As many RTEC are fortified with micronutrients, it is not surprising that intake of those micronutrients is increased in RTEC consumers. However, increased micronutrient consumption is only relevant in case that micronutrient intake is below the nutritional recommendations. For this reason, we assessed the impact of RTEC consumption on micronutrient inadequacy. Our results show that the reduction of prevalence of inadequacy associated with frequent RTEC consumption is greatest for vitamin A, calcium, folate, vitamin B 6, magnesium and zinc. These results are mainly derived from surveys conducted in the US, Canada and Australia.

These data demonstrate that RTEC, due to fortification, DF content and by stimulating milk intake, can play an important role in reducing the prevalence of micronutrient inadequacy.

Of concern is the total sugar intake which was positively associated in children and adults with frequent RTEC consumption in most studies. Higher consumption of total sugar, which is the sum of free sugars, intrinsic sugars and milk sugars, can be partly explained by higher lactose intake due to an increase in milk consumption. However, it can also partly be due to the sugar content of RTEC (defined as “free” sugar) and dietary recommendations are to decrease ‘free’ sugar intake to less than 10% of the total daily energy consumption [ 79 ; 80 ]. The current intake in some European countries and the US exceeds 10 energy% especially in children [ 81 – 83 ].

Analysis of different RTEC of leading brands in the US market showed that the mean sugar content of 142 types of RTEC was 28.1 g/100 g in 2006 but decreased to 24.8 g/100 g (mean of 151 types) in 2011 [ 84 ]. Even though this is a move in the right direction 24.8 g/100 g is still high. According to the color-coded Traffic Light System for classifying nutrients in solid foods of the Department of Health UK products containing >22.5 g/100 g would be colored red, indicating that this is not a healthy choice [ 85 ]. From this study it cannot be derived whether reductions were predominantly made in RTEC marketed to children or those not marketed to children (generic). This is of interest because it was shown that RTEC for children contained more sugar than generic RTEC (36 g/100 vs 23 g/100 g respectively in the US [ 86 ]; 28.2 g/100 g vs 18.1 g/100 g respectively in Germany [ 87 ]). Interestingly, in a RCT it was shown that children consuming either low-sugar or high sugar cereals did not differ in how much they liked the cereal [ 79 ]. Even though children added sugar to the low-sugar cereal they consumed half the amount of the sugar children in the high-sugar cereal group consumed. They were also more likely to put fresh fruit on their cereal as compared to the children in the high-sugar cereal group. This indicates that low-sugar RTEC are accepted by children and that the benefit of enhanced micronutrient intake due to RTEC consumption does not necessarily need to be accompanied by high sugar intake.

Health benefits

Risk factors for cvd..

Prospective studies that examined associations of low and high consumption of RTEC with health outcomes mostly differentiated between whole grain and refined grain RTEC. No studies were found that investigated associations of whole grain RTEC with cardiovascular disease directly. However, the associations with hypertension [ 52 ] and heart failure [ 56 ] were assessed and a decreased risk of 20 and 28% respectively was found. The inverse association of whole grain RTEC consumption with hypertension is consistent with that of a number of studies investigating associations with whole grain intake in general (women 0.89 [ 88 ], men 0.81 [ 89 ], young adults 0.83 HR [ 90 ]) whereas the magnitude of effect on heart failure was not comparable with that of a study examining the association with whole grain intake in general (0.93 HR [ 91 ]). Beneficial effects of whole grain products are related mainly to the bran fraction of the grain and its high content of micronutrients, like magnesium and zinc, and bioactive components, like phytic and ferulic acid, many having antioxidant properties [ 92 ; 93 ]. Magnesium is one of the micronutrients linked to the prevention of hypertension [ 93 ; 94 ] and oxidative stress is involved in the pathophysiology of cardiovascular disease and heart failure [ 95 ; 96 ]. Furthermore, it is postulated that synergetic effects can occur as different components of whole grain act together to beneficial influence processes involved in development of disease [ 92 ].

In addition, hypocholesterolaemic properties of whole grain have been postulated that are mainly ascribed to viscous soluble fiber [ 97 ]. Reductions in total cholesterol and LDL were seen due to psyllium-enriched RTEC [ 71 ; 72 ] but not with wheat bran RTEC in hypercholesterolemic men [ 71 ]. In normocholesterolemic persons RTEC based on whole grain maize [ 58 ], whole grain wheat and wheat bran [ 10 ] did not affect blood lipids. This is in agreement with the findings of a recent meta-analysis summarizing results of lipid-lowering effects of whole-grain interventions in apparently healthy [ 98 ]. Whole grain products based on wheat did not consistently exert lipid lowering effects in contrary to products based on barley and oat [ 48 ]. Psyllium fiber, like fiber in oat and barley, are soluble whereas wheat or corn fiber are mainly insoluble, which can explain these results.

Elevated plasma concentrations of homocysteine are suggested to be an additional risk factor for the development of cardiovascular disease [ 99 ], although not consistently [ 100 ]. Higher plasma folate concentrations are implicated with lower homocysteine [ 101 ] as well as a reduced risk of developing CVD [ 102 ]. Three studies consistently demonstrated that consumption of RTEC fortified with folate could increase plasma folate concentration and lower plasma homocysteine [ 66 ; 68 ; 77 ]. The effects were most pronounced in persons with low plasma folate and high homocysteine concentrations.

In summary, studies investigating whether RTEC consumption can reduce the risk of development of CVD addressed different risk factors. Prospective studies suggest that consumption of whole grain RTEC may reduce the risk of hypertension and heart failure, which so far has not been assessed in RCTs. RCTs demonstrated that RTEC with soluble fiber from psyllium have lipid lowering potency and folate-enriched RTEC can reduce plasma homocysteine concentrations. These prospective studies did not have industrial funding, whereas the effect of psyllium and folate-enriched RTEC were only investigated in RCTs which were industrial funded.

Weight gain/BMI, satiety and food intake.

Lower weight gain (0.59 and 0.46 kg during 8 and 13 y respectively) and a lower risk of becoming obese (22 and 12%) was associated with frequent RTEC consumption in men without being different between refined and whole grain RTEC [ 8 ]. The magnitude of effect was similar in two prospective studies that examined the association between whole grain food and refined grain food intake [ 103 ; 104 ]. Consumption of whole grain food resulted in 0.49 kg less weight gain during 8 y in men [ 103 ] and 0.39 kg less weight gain during 12 y in women [ 104 ]. In contrary to the RTEC study [ 8 ] refined grain intake was associated with an increase in weight in women (0.43 kg during 12 y) [ 104 ]. However, differences in weight gain found in these studies are quite small and its health impact is difficult to judge.

In 8–10 y old children frequency of RTEC consumption was associated with slightly lower BMI in boys in two prospective studies [ 51 ; 54 ] but in girls only in one study (low-income minority children) [ 51 ]. These studies did not differentiate between types of RTEC. Similar associations between BMI and consumption of breakfast cereals in general (9–10 y girls [ 105 ]) or whole grain foods (13–15 y old boys and girls [ 106 ]) were found, with no sex-related differences. Explanations for these beneficial effects postulated are the more healthy eating pattern of RTEC consumers with increased intakes of whole grain, DF and reduced fat or increased satiety [ 51 ; 54 ] and higher insulin sensitivity in case of whole grain consumers [ 106 ]. Results of two RCTs [ 11 ; 62 ] investigating the effect of high vs low RTEC consumption on body weight do not substantiate results from prospective studies. However, in both trials RTEC with a low content of DF were administered and one was of relative short duration.

Other RCTs explored the effect of DF-rich RTEC on postprandial satiety and food intake. From these trials it seems that postprandial satiety and/or appetite is not affected by higher DF content of RTEC, as only three from seven studies reported a decrease [ 12 ; 59 ; 73 ]. However, consumption of wheat bran RTEC decreased energy intake at a subsequent meal in normal weight subjects [ 12 ; 61 ; 73 ].

In summary, consumption of RTEC (all types) is associated with modest reduction in weight gain or BMI in adults and children in prospective studies, which so far is not substantiated with RCTs. There are indications that RTEC enriched with wheat bran can decrease energy intake at a subsequent meal in normal weight persons, with RCTs without industry-related funding showing similar results as industrial funded RCTs. However, long term RCTs are needed to demonstrate that this results in decreased weight gain. Furthermore, it seems of great interest to not only assess body weight but also fat mass as the results of a recent meta-analyses demonstrated that whole grain interventions can decrease fat mass, despite no effect on body weight [ 107 ].

Type 2 diabetes and risk factors.

Consumption of whole grain RTEC 2–6 times weekly was associated with a decreased the risk of the development of type 2 diabetes by 24% and 29% and ≥ 7 servings/week by 40 and 43% [ 55 ; 50 ]. These finding are consistent with that of studies investigating associations with total whole grain intake (0.79 HR [ 108 ], 0.67 [ 109 ], 0.72 [ 110 ]). Increased intake of bran-derived micronutrients like magnesium and zinc as well as bioactive components may contribute to beneficial effects [ 92 ; 93 ]. Magnesium for example, plays an important role in insulin sensitivity [ 94 ; 111 ; 112 ] and recently the property of zinc to influence synthesis, secretion and the action of insulin has become clear [ 113 ]. In addition, chronic low-grade inflammation and oxidative stress are factors involved in the development of type 2 diabetes, which can be alleviated by certain micronutrients as well as by bioactive compounds,—possibly through synergistic action [ 92 ].

Reduction of postprandial glucose and/or insulin concentrations are considered beneficial as repeated high glucose concentrations and related high insulin concentrations can lead to decreased insulin sensitivity and β-cell function in susceptible persons [ 114 ; 115 ]. Reductions of postprandial glucose and insulin concentrations have been demonstrated for viscous soluble fiber [ 116 ]. The property of RTEC enriched with soluble fiber to decrease postprandial glucose and insulin was shown for guar gum (4.5 g) in healthy [ 70 ], whereas in overweight persons only the insulin response was reduced after RTEC with oat b-glucan [ 59 ].

Evidence from prospective studies, which were all without food-industry related funding, indicates a reduced risk of development of type 2 diabetes due to consumption of whole grain RTEC. However, RCTs investigating the effect of whole grain versus refined grain RTEC on risk factors related to the development of type 2 diabetes are needed to draw a definite conclusion. Addition of soluble fiber seems a promising strategy to reduce not only postprandial glucose but also insulin concentrations (independent from funding sources) and deserves further evaluation. Lower postprandial insulin response is considered beneficial because this would be less demanding for the pancreatic β-cells [ 115 ] and could play a role in preventing insulin resistance [ 117 ]. In addition, more recently, diets with a low insulin load were reported to be associated with lower body fat during puberty [ 118 ] and with lower energy intake in obese adolescents with features of insulin resistance and/or prediabetes [ 119 ].

Strengths and Limitations

This review provides a comprehensive overview of nutritional and health effects that are related to the consumption of RTEC and has identified specific favorable characteristics. One of the review’s strength is the careful selection of studies, excluding studies with cooked cereals or those in which cereals were not defined. In addition, RCTs were not considered in which RTEC were administered at several occasions during the day or breakfasts included other products than RTEC, milk and fruit. This enables us to draw conclusion on the properties of RTEC only. Data about nutritional benefits were derived from large, national representative surveys conducted in a number of different countries in many age-groups, which aids generalizability of results. There are some limitations of this review and the body of evidence. Evidence for nutritional and health benefits is partly derived from observational studies in which dietary data are self-reported. These studies are more prone to bias and confounding than RCTs, therefore results have to be interpreted with caution. For assessing health benefits, however, only prospective studies and no cross-sectional studies, which lack temporal relationship, have been used. As prospective studies were mainly conducted in the US generalizability of these results is uncertain. A large number of studies (45) were (partly) funded by food-industry, which can introduce reporting bias. As we examined and discussed the results also in view of funding sources, we can conclude that reporting bias seems less likely what concerns the prospective studies and most RCTs.

Frequent consumption of RTEC (≥ 5 servings/week) as compared to no or low RTEC consumption is associated with a healthier dietary pattern, concerning intake of carbohydrates, DF, fat and micronutrients, however total sugar intake is higher. The impact of frequent RTEC consumption on inadequacy of micronutrient intake is highest for vitamin A, calcium, folate, vitamin B 6, magnesium and zinc.

Evidence from prospective studies suggests that whole grain RTEC may have beneficial effects on hypertension and type 2 diabetes. These protective effects seem biological plausible, however, to prove a causal relationship RCTs are needed that assess the effect of whole grain versus refined grain RTEC on hypertension and risk factors for type 2 diabetes.

Consumption of RTEC with soluble fiber from psyllium helps to reduce LDL and total cholesterol in hypercholesterolemic men. RTEC fortified with folate have the potency to reduce plasma homocysteine especially in persons with low folate and high homocysteine plasma concentrations. Addition of soluble fiber to RTEC could aid in reducing postprandial glycaemia and insulinemia but more studies are needed to draw a final conclusion. The effect of RTEC on body weight, intestinal health and cognitive function needs further evaluation.

Supporting Information

S1 checklist. prisma checklist for the reporting of systematic reviews of randomized controlled trials..

https://doi.org/10.1371/journal.pone.0164931.s001

S2 Checklist. MOOSE checklist for the Reporting of Meta-analyses of Observational Studies.

https://doi.org/10.1371/journal.pone.0164931.s002

S1 Protocol.

https://doi.org/10.1371/journal.pone.0164931.s003

S1 Table. Differences in daily intake of energy, macronutrients, cholesterol, dietary fiber and sodium of frequent versus low/no RTEC consumers.

https://doi.org/10.1371/journal.pone.0164931.s004

S2 Table. Percentage of population with daily intake of micronutrients below recommended intake by frequency of RTEC consumption.

https://doi.org/10.1371/journal.pone.0164931.s005

Author Contributions

• Conceptualization: JRM MGP.
• Data curation: MGP.
• Formal analysis: MGP.
• Funding acquisition: JRM.
• Investigation: MGP JRM.
• Methodology: MGP.
• Validation: MGP.
• Visualization: MGP.
• Writing – original draft: MGP.
• Writing – review & editing: JRM MGP.
• View Article
• PubMed/NCBI
• Google Scholar
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• 82. Ervin RB, Ogden C.L. Consumption of added sugars among U.S. aduots, 2005–2010. NCHS data brief, no 122 Hyattsville, MD: National Center for Health Statistics 2013.
• 83. Ervin RB, Kit BK, Carroll MD, Ogden C.L. Consumption of added sugar among U.S. children and adolescents, 2005–2008. NCHS data brief, no 87 Hyattsville, MD: National Center for Health Statistics 2012.
• 85. Department of Health UK. Guide to creating a front of pack (FoP) nutrition label for pre-packed products sold through retail outlets. June 2013. https://www.gov.uk/government/publications/front-of-pack-nutrition-labelling-guidance . 2016.

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Introduction, suggestions.

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Current situation and perspectives of ready-to-eat food/meal suppliers

Working Group 2 Members: Takashi Sakata (Leader, Ishinomaki Senshu University), Takeaki Akabane (ADEKA Corp.), Chikako Akagaki (SEVEN-ELEVEN JAPAN Co., Ltd.), Rie Akamatsu (Ochanomizu University and The Japanese Society of Nutrition and Dietetics), Toshihiko Hagiwara (NICHIREI Corp.), Naoki Hayashi (Ajinomoto Co., Inc.), Li Han (Nippon Suisan Kaisha, Ltd.), Hajime Kato (Yano Research Institute Ltd.), Kayo Kurotani and Kazuko Ishikawa-Takata (the National Institutes of Biomedical Innovation, Health and Nutrition), Shunsuke Omoto (Kirin Holdings Company, Ltd.), Takashi Tanaka (YAMAZAKI BAKING Co. Ltd.), and Yoshiko Yokomukai (International Life Science Institute JAPAN)

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Takashi Sakata, for Working Group 2 of the Healthy Diet Research Committee of International Life Sciences Institute, Japan, Current situation and perspectives of ready-to-eat food/meal suppliers, Nutrition Reviews , Volume 78, Issue Supplement_3, December 2020, Pages 27–30, https://doi.org/10.1093/nutrit/nuaa089

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Working Group 2 of the Healthy Diet Research Committee of International Life Sciences Institute Japan (WG2) assessed the concept and practice of healthy eating in the ready-to-eat food/meal industry in Japan. WG2 interviewed 14 arbitrarily selected member companies that included “health” or “nutrition” in their management policy, and sent a questionnaire to 338 member companies of the Japan Ready-Made Meal Association. Ready-to-eat food/meal suppliers mainly referred to Dietary Reference Intakes for Japanese, the Japanese Food Guide, and/or Healthy Japan 21 for their menu construction. They increased dietary fiber, variety, vegetables, whole-grain cereals, millet rice, and soy bean products; and reduced energy, carbohydrates, and salt in “healthy” food. They tended to avoid making direct appeals to health. Many companies reduced the salt content without drawing attention to the practice. They continually strive to improve flavor as the single most important factor for selling healthy food. The cycling of menus is used to increase diversity in food consumption. These industries require both academia and the government to define priorities for increasing and decreasing particular nutrients as the main targets and to establish the maximum time for balancing each nutrient.

Ready-to-eat food or meals in Japan is defined as “food or a meal that can be eaten without cooking or heating at home, workplace, school, etc., such as lunch boxes and daily dishes with a short shelf life.” 1 The sales of ready-to-eat food/meals is growing and, in 2017, they exceeded JPY 10 trillion. 1 The expected increase in the number of elderly people and the results of women’s empowerment in Japan should favor this sector of the food industry.

The main products of these ready-to-eat food/meal suppliers are cooked rice (50%) and daily dishes (34%), namely lunch boxes, rice balls, sandwiches, croquettes, and vegetable salads in the Tokyo metropolitan area. 1 These products are sold mainly via convenience stores (32%), specialty stores (29%), and food supermarkets (26%). 1

We conducted a survey to evaluate the concept of “healthy eating” among ready-to-eat food companies that are expected to grow in Japan, and we summarized the findings for academic research and governmental policy and regulation needed to achieve healthy eating.

Working Group 2 of the Healthy Diet Research Committee of International Life Sciences Institute (ILSI) Japan (WG2) conducted a round-table discussion with the Japan Ready-Made Meal Association (JRMA) to clarify the general business structure, and then performed semistructured interviews to arbitrarily select 14 (of 24 approached) JRMA member companies stating “health” or “nutrition” in their management policy. We administered a nationwide online questionnaire via Google forms to only the 14 selected JRMA member companies via the JRMA. JRMA is a national association comprising 338 regular member companies, 216 supporting member companies, and 40 cooperating companies.

Findings from interviews

Of 24 member companies of JRMA that publish statements on healthy or nutritious food in their policies and were selected for visits by WG2, 14 companies accepted the visit. Annual sales of these 14 companies exceeded JPY 40 billion; the average annual sales of JRMA regular member companies in 2019 totaled JPY 12.6 billion ( Table 1 ).

Characteristics of interviewed companies

Abbreviations: Dept., department; JPY, Japanese yen.

Interviewed companies generally based their meals and menus on Dietary Reference Intakes for Japanese, 2 the Japanese Food Guide, 3 or Healthy Japan 21. 4 These companies intended to increase or improve ingredient variety (n = 5 companies), vegetables (n = 4), dietary fiber (n = 3), lactic acid bacteria (n = 2), green and yellow vegetables, millet rice, organic ingredients, quinoa, ω3-fatty acids, iron, lycopene, calcium, protein, and nutrient balance. They intended to reduce or omit salt (n = 8 companies), energy (n = 5), additives (n = 4), chemical seasoning (n = 3), carbohydrates (n = 2), and lipids.

It was a general tendency of all interviewed companies to avoid direct health appeals such as “reduced salt,” although many of them actually reduced the salt content in their products gradually but continuously. These companies considered direct health appeals to be unpopular and to reduce sales. They emphasized a healthy atmosphere as a whole. It was also noted that some positive wording such as “rice bowl with lots of vegetables” increased sales.

All companies considered good flavor to be the single most important sales factor. Therefore, they regularly worked to improve the flavor of their products and tested the customers’ opinions of the improvements often via face-to-face tastings as points of sale, which resulted in an increase or recovery of the sales.

One company selling warm lunchboxes developed 2 series of cycling menus for 1 week, one with large portions and another relatively fit with respect to energy and salt content. The main customers of the company are busy people who do not pay much attention to nutrition or health. The company intended to increase the variety of ingredients and tried to balance the nutrient intake if the customer purchases the same cycling menu, even without considering the contents of the lunch box. Interestingly, most of these customers purchased the large-portion meals and the fit meals alternately, that is, there was approximately a 50% improvement. This can be an important tactic for improving the nutritional status of laymen without pressing them to behave healthily.

Findings from nationwide questionnaire

JRMA distributed the questionnaire to 338 member companies online in July 2019. In total, 88 companies responded the questionnaire (response rate, 26.0%). Just 50 of the 88 responding companies had annual sales of more than JPY 1 billion. Considering the average annual sales of JRMA regular member companies of JPY 12.6 billion, response rate should have been higher in smaller companies than in large companies. The proportion of responding companies selling via supermarket was approximately twice that of the JRMA regular member companies. Therefore, the results may have sampling bias and, accordingly, may not represent the overall tendency of JRMA members.

Distributions of their main product and route of sales indicated that the composition of these companies approximately, but not entirely, reflected the composition of the JRMA ( Figure 1 ). Therefore, the results may not represent the status quo of all JRMA member companies.

Main products and routes of sales of responding Japan Ready-Made Meal Association member companies (multiple answers, n = 88). Abbreviation: EC, electronic commerce.

Approximately 60% of the responding companies had health- or nutrition-oriented wording in their management policies or on their homepage. Approximately 75% of the responding companies produced health- or nutrition-oriented products ( Figure 2 ). The responding companies most often cited Dietary Reference Intakes for Japanese 2 and Japanese Food Guide Spinning Top as the resources on which they based their the menu design ( Figure 3 ).

Health or nutrient orientation of responding companies (n = 88).

Governmental guidelines or policies on which responding companies based their menu construction (multiple answers, n = 88). *Ministry of Health, Labour and Welfare; **Ministry of Health, Labour and Welfare, and Ministry of Agriculture, Forestry and Fisheries; ***Ministry of Health, Labour and Welfare, Ministry of Agriculture, Forestry and Fisheries, and Ministry of Education, Culture, Sports, Science and Technology.

Nutrients focused on in successful health- or nutrition-oriented products were energy, carbohydrate, dietary fiber, sodium, protein, and lipid. Ingredients in successful health- or nutrition-oriented products were vegetables, whole-grain cereals, soy products, miscellaneous grains, seasoning, animal meat, seafood, fermented products, and oil ( Figure 4 ). There was no marked tendency with regard to focused nutrient or ingredient in failed health- or nutrition-oriented products.

Nutrients and ingredients focused in successful health or nutrition-oriented products (multiple answers, n = 88). Abbreviation: Na, sodium.

The challenges for responding companies in the development and sales of health- or nutrition-oriented products were to produce good-tasting products at a low cost that appeal to the consumer via an efficient production process with stabilization of the food content.

On the basis of the surveys findings, WG2 wants to highlight the importance of developing and disseminating simple and easily understandable guidelines and labeling policies for the production of healthy and nutritious ready-to-eat food/meals. In this regard, WG2 proposes to define priorities for which nutrients to increase or decrease, to prioritize target population (eg, those who are establishing food habits or those who eat without consideration of what they eat), and to indicate the maximum time to balance each nutrient.

Acknowledgments

The WG2 members sincerely express their gratitude for the generous cooperation of Japan Ready-Made Meal Association and its member companies, which was essential for conducting this study. The study plan of the survey was reviewed by the Ethics Committee for Human Studies of Ishinomaki Senshu University (application no. 2018–001) and determined to be a study not requiring the permission of the committee. Although, many authors belong to private companies, all authors wrote a pledge stating that all information gathered during this survey belongs to ILSI Japan and will not be used otherwise without the consent of ILSI Japan.

Author contributions . T.S. supervised the study. All authors equally contributed to develop the research design, conduct the survey, analyze the data, and prepare the manuscript, and all approved the final manuscript.

Funding . This research was conducted as a part of the activities of the International Life Sciences Institute Japan Research Committee, which are not compensated except for travel expenses for academia members, as required.

Declaration of interest . T.S. is a vice president and a member of the Board of Trustees for International Life Sciences Institute (ILSI) Japan. He is also a member of the organizing committee and the program committee for the 8th International Conference on Nutrition and Aging held October 1-2, 2019. R.A. is a member of the program committee for the 8th International Conference on Nutrition and Aging. Companies to which authors belong are members of ILSI Japan and support the organization’s activities.

White Paper of Japan Ready-Made Meal Association (2018) (Digest on-line edition). Japan Ready-Made Meal Association.   http://www.nsouzai-kyoukai.or.jp/wp-content/uploads/hpb-media/hakusho2018_digest1.pdf .

Ministry of Health, Labour and Welfare. Overview of Dietary Reference Intakes for Japanese (2015). Available at: https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/Overview.pdf . Accessed April 18, 2020.

Ministry of Health, Labour and Welfare; Ministry of Agriculture, Forestry, and Fisheries. Japanese Food Guide Spinning Top. Do you have a well-balanced diet? https://www.maff.go.jp/j/balance_guide/b_use/pdf/eng_reiari.pdf . Accessed April 18, 2020.

Ministry of Health, Labour and Welfare. A basic direction for comprehensive implementation of national health promotion. Ministerial Notification No. 430 of the Ministry of Health, Labour and Welfare. Available at: https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/0000047330.pdf . Accessed April 28, 2020.

Author notes

• dietary fiber
• carbohydrates
• biological sciences
• science of nutrition
• whole grains
• healthy diet
• academia (organization)

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Packaging Concepts for Ready-to-Eat Food: Recent Progress

• Review Paper
• Published: 04 December 2017
• Volume 1 , pages 113–126, ( 2017 )

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• Alina Silberbauer 1 &
• Markus Schmid   ORCID: orcid.org/0000-0002-9435-7953 1 , 2  

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During recent years the market for convenience foods has grown rapidly. More and more consumers prefer ready-to-eat (RTE) products because of their advantageous minimal input of time and effort. The increasing awareness of health means there is a need for nutritious, high quality ready meals. Due to technological developments, the packaging industry is continuously coming up with innovative packaging. This is being driven by ecological challenges, policy, and consumer demands. However, only a few studies have hitherto been published on innovative packaging concepts for RTE food. The purpose of this review is to evaluate the status quo and recent progress in this area. It is important to understand the crucial factors for food packaging for RTE food, namely food safety and quality. Packaging concepts have focused on preventing microbial growth, so protecting consumers from food-borne diseases. Bio-based packaging materials such as polylactic acid and chitosan have limited mechanical properties. The use of nanomaterials or natural essential oils to replace synthetic additives could alleviate this. The combination with modified atmosphere packaging showed improvements and prolongation of the shelf life.

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Silberbauer, A., Schmid, M. Packaging Concepts for Ready-to-Eat Food: Recent Progress. J Package Technol Res 1 , 113–126 (2017). https://doi.org/10.1007/s41783-017-0019-9

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Received : 26 July 2017

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DOI : https://doi.org/10.1007/s41783-017-0019-9

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Association of ultra-processed food consumption with all cause and cause specific mortality: population based cohort study

Linked editorial.

Ultra-processed foods linked to higher mortality

• Related content
• Peer review
• Zhe Fang , doctoral student 1 ,
• Sinara Laurini Rossato , adjunct professor 2 3 ,
• Dong Hang , associate professor 3 4 ,
• Neha Khandpur , assistant professor 3 5 6 ,
• Kai Wang , research associate 1 ,
• Chun-Han Lo , resident physician 7 ,
• Walter C Willett , professor 1 3 8 ,
• Edward L Giovannucci , professor 1 3 ,
• Mingyang Song , associate professor 1 3 9
• 1 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
• 2 Laboratory of Research and Extension in Epidemiology (Lapex-Epi), Institute of Geography, Universidade Federal de Uberlândia, Uberlândia, MG, Brazil
• 3 Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
• 4 Department of Epidemiology, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Gusu School, Nanjing Medical University, Nanjing, China
• 5 Division of Human Nutrition and Health, Wageningen University, Wageningen, Netherlands
• 6 Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
• 7 Department of Internal Medicine, Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas, NV, USA
• 8 Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
• 9 Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
• Correspondence to: M Song msong{at}hsph.harvard.edu (or @MingyangSong3 on X/Twitter)
• Accepted 13 March 2024

Objective To examine the association of ultra-processed food consumption with all cause mortality and cause specific mortality.

Design Population based cohort study.

Setting Female registered nurses from 11 US states in the Nurses’ Health Study (1984-2018) and male health professionals from all 50 US states in the Health Professionals Follow-up Study (1986-2018).

Participants 74 563 women and 39 501 men with no history of cancer, cardiovascular diseases, or diabetes at baseline.

Main outcome measures Multivariable Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals for the association of ultra-processed food intake measured by semiquantitative food frequency questionnaire every four years with all cause mortality and cause specific mortality due to cancer, cardiovascular, and other causes (including respiratory and neurodegenerative causes).

Results 30 188 deaths of women and 18 005 deaths of men were documented during a median of 34 and 31 years of follow-up, respectively. Compared with those in the lowest quarter of ultra-processed food consumption, participants in the highest quarter had a 4% higher all cause mortality (hazard ratio 1.04, 95% confidence interval 1.01 to 1.07) and 9% higher mortality from causes other than cancer or cardiovascular diseases (1.09, 1.05 to 1.13). The all cause mortality rate among participants in the lowest and highest quarter was 1472 and 1536 per 100 000 person years, respectively. No associations were found for cancer or cardiovascular mortality. Meat/poultry/seafood based ready-to-eat products (for example, processed meat) consistently showed strong associations with mortality outcomes (hazard ratios ranged from 1.06 to 1.43). Sugar sweetened and artificially sweetened beverages (1.09, 1.07 to 1.12), dairy based desserts (1.07, 1.04 to 1.10), and ultra-processed breakfast food (1.04, 1.02 to 1.07) were also associated with higher all cause mortality. No consistent associations between ultra-processed foods and mortality were observed within each quarter of dietary quality assessed by the Alternative Healthy Eating Index-2010 score, whereas better dietary quality showed an inverse association with mortality within each quarter of ultra-processed foods.

Conclusions This study found that a higher intake of ultra-processed foods was associated with slightly higher all cause mortality, driven by causes other than cancer and cardiovascular diseases. The associations varied across subgroups of ultra-processed foods, with meat/poultry/seafood based ready-to-eat products showing particularly strong associations with mortality.

Introduction

Ultra-processed foods are ready-to-eat/heat industrial formulations made mostly or entirely from substances derived from foods, including flavors, colors, texturizers, and other additives, with little if any intact whole food. 1 Ultra-processed foods, which are typically of low nutritional quality and high energy density, have been dominating the food supply of high income countries, and their consumption is markedly increasing in middle income countries. 2 Ultra-processed food consumption accounts for 57% of daily energy intake among adults and 67% among youths in the US according to the National Health and Nutrition Examination Survey (NHANES). 3 4

Ultra-processed foods usually disproportionately contribute added sugars, sodium, saturated fats and trans fats, and refined carbohydrates to the diet together with low fiber. 5 6 As well as having low nutritional quality, ultra-processed foods may contain harmful substances, such as additives and contaminants formed during the processing. 7 8 9 10 Growing evidence from large prospective cohorts show that ultra-processed food is associated with adverse health outcomes, such as overweight/obesity, cardiovascular diseases, type 2 diabetes, and colorectal cancer. 11 12 13 14 A systematic review showed that high ultra-processed food consumption was associated with increased risk of all cause mortality, cardiovascular diseases, metabolic syndrome, depression, and postmenopausal breast cancer. 15 However, few prospective cohort studies with a follow-up longer than 20 years have examined the association for all cause mortality or cause specific mortality, especially mortality due to cancer. High quality evidence from cohorts with a long follow-up is critical to inform dietary recommendations and food policies.

Leveraging the rich data obtained through repeated assessments for more than 30 years in two large US prospective cohorts, we examined the associations of total ultra-processed food and subgroups of ultra-processed food with mortality from all causes and major individual causes.

Study population

We used data from two large prospective cohorts in the US: the Nurses’ Health Study (NHS) began in 1976 and included 121 700 female registered nurses aged 30-55 years from 11 states; the Health Professionals Follow-up Study (HPFS) began in 1986 and enrolled 51 529 male health professionals aged 40-75 years from all 50 states. Every two years participants completed a mailed questionnaire enquiring about medical and lifestyle information. The baseline of this study was set to 1984 for the NHS and 1986 for the HPFS when the ultra-processed food data were first available. We excluded participants at baseline if they had reported a history of cancer, cardiovascular diseases, or diabetes; left more than 70 food items blank in the food frequency questionnaire or had implausible caloric intakes (<800 or >4200 kcal/d for men; <600 or >3500 kcal/d for women); or had missing data on ultra-processed food intakes. After exclusions, we included 74 563 women from the NHS and 39 501 men from the HPFS (supplementary figure A).

Assessment of ultra-processed food intake

Diet was assessed using a validated semiquantitative food frequency questionnaire administered every four years. 16 We grouped all foods into four categories of the Nova classification: unprocessed or minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods, which has been described in detail elsewhere. 17 we further categorized ultra-processed foods into nine mutually exclusive subgroups (supplementary table B; supplementary figure B): ultra-processed breads and breakfast foods; fats, condiments, and sauces; packaged sweet snacks and desserts; sugar sweetened and artificially sweetened beverages; ready-to-eat/heat mixed dishes; meat/poultry/seafood based ready-to-eat products (for example, processed meat); packaged savory snacks; dairy based desserts; and other. Because alcohol is a well studied risk factor for premature death and a distinct factor in diet, we did not consider alcohol in ultra-processed foods in the primary analysis. Moreover, as wholegrain foods have established benefit for lowering all cause mortality, 18 we removed whole grains from ultra-processed foods in the primary analysis. We measured ultra-processed food intake as servings per day and adjusted it for total energy intake by using the residual method. 19

Ascertainment of outcomes

Death of a cohort member was notified by the next of kin via the post office when questionnaires or newsletters were returned or was identified through searches of the vital records of states and of the National Death Index. Study investigators blinded to the exposure status reviewed death certificates and extracted information from medical records to confirm the cause of death according to ICD-8 (international classification of diseases, 8th revision). The primary outcome of this study was all cause mortality. The secondary outcomes included deaths from cancer (ICD-8 codes 140-207), cardiovascular diseases (ICD-8 codes 390-459), and other causes (including respiratory diseases (ICD-8 codes 460-519) and neurodegenerative diseases (ICD-8 codes 290, 332, 340, 342, and 348)).

Assessment of covariates

Biennial follow-up questionnaires were used to collect self-reported information on body weight, marital status, smoking status and pack years, physical activity, family history of cancer/cardiovascular diseases/diabetes, and physical examination for screening purposes, as well as menopausal status and postmenopausal hormone use for women. We calculated body mass index as weight in kilograms divided by height squared in meters. Physical activity was assessed with a validated questionnaire and converted into metabolic equivalent task hours. 20 Alcohol drinking was measured by food frequency questionnaires as the number of drinks per week (considering one drink as one glass, bottle, or can of beer; one 4 ounce glass of wine; or one shot of liquor) and then converted into grams per day. We assessed overall dietary quality by using the Alternative Healthy Eating Index-2010 (AHEI) score. 21

Statistical analysis

Follow-up time accrued from the date of return of the baseline questionnaire to the date of death or the end of follow-up (30 June 2018 for NHS; 31 January 2018 for HPFS), whichever came first. To better represent long term dietary habits and to minimize within person variation, we calculated cumulative averages of ultra-processed food consumption as the primary exposure. We did primary analyses in pooled cohorts and a secondary analysis in each cohort separately. We used time varying Cox proportional hazards models stratified by age (months), questionnaire cycle (two year interval), and cohort (in pooled analyses) with the counting process data structure to estimate the hazard ratios and 95% confidence intervals according to quarters of ultra-processed food consumption. We calculated P for trend on the basis of the Wald test by assigning the median intake to each quarter and modeling it as a continuous variable. In the multivariable model, we adjusted for race/ethnicity, marital status, physical activity, body mass index, smoking status and pack years, alcohol consumption, physical examination performed for screening purposes, family history of diabetes mellitus, myocardial infarction, or cancer, and menopausal status and hormone use (women only). We carried forward non-missing values from the previous survey cycle to replace missing data. If the value remained missing, we created missing indicators. The percentage of missing data is shown in supplementary table A. We also tested for the dose-response relation by using the restricted cubic spline regression. 22

In secondary analyses, we further categorized ultra-processed foods into mutually exclusive subgroups (supplementary tables B and C) to investigate whether the associations were driven by specific food groups. 13 Furthermore, to assess the independent and combined association of ultra-processed food consumption and overall dietary quality with mortality, we categorized individuals jointly according to quarters of AHEI score and quarters of ultra-processed food intake and estimated the hazard ratios by using participants with the highest quarter of AHEI score and lowest quarter of ultra-processed food intake as the reference.

We did several sensitivity analyses to test the robustness of the results. Firstly, given that people are likely to change their dietary habits after the diagnosis of certain chronic diseases, we stopped updating ultra-processed food consumption after the diagnosis of cardiovascular diseases, cancer, or diabetes during follow-up. Secondly, because of the uncertainty of the etiological time window, we introduced an eight to 12 year lag period between assessment of ultra-processed food intake and each follow-up period (for example, we used ultra-processed food intake from the 1986 questionnaire to assess the mortality risk in the period of 1994 to 1998). Thirdly, we added back to total ultra-processed food whole grains and distilled alcohol individually and in combination (that is, using the standard Nova definition) and repeated the analysis. Finally, we removed from the multivariable model pack years of smoking, which was not adjusted for in most previous studies, and further adjusted for AHEI score, to assess the confounding by smoking and dietary quality, respectively. We also removed from the multivariable model body mass index, which might be a mediator. Furthermore, we did the stratified analysis by major risk factors and repeated the primary analysis with ultra-processed food intake measured by percentage of energy.

We used SAS statistical package (version 9.4) for all the statistical analyses. We considered a P value <0.05 (two sided) to be statistically significant unless otherwise specified.

Patient and public involvement

The public was concerned about the health effects of ultra-processed foods, and their concerns informed our research question. Although participants were not involved in the study design, they played a central role in the conduct of the study by completing the biennial questionnaires in our cohorts, and we appreciate their contributions. We could not directly involve members of the public in this study, as no funding was available or set aside for patient and public involvement and our study team was not trained to work directly with the public.

During a median of 34 years of follow-up, we documented 48 193 deaths (30 188 deaths of women and 18 005 deaths of men), including 13 557 deaths due to cancer, 11 416 deaths due to cardiovascular diseases, 3926 deaths due to respiratory diseases, and 6343 deaths due to neurodegenerative diseases. Table 1 shows the characteristics of participants according to quarters of energy adjusted ultra-processed food consumption throughout follow-up. Participants with higher ultra-processed food consumption were younger, more physically inactive, and more likely to smoke and had higher body mass index, lower consumption of alcohol, whole fruits and vegetables, and whole grains, and lower AHEI score.

Age standardized characteristics of study participants according to quarters of ultra-processed food (UPF) consumption across entire follow-up period. Values are number (percentage) of person years unless stated otherwise

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Table 2 shows the hazard ratios of mortality according to quarters of ultra-processed food consumption. In the age, sex, and total calorie adjusted analysis, we observed strong positive associations between ultra-processed food and mortality outcomes. The associations became substantially attenuated in the multivariable analysis ( table 2 ; supplementary figure C). Compared with participants in the lowest quarter (median 3.0 servings/day), those in the highest quarter (median 7.4 servings/day) had a 4% higher risk of total deaths (multivariable adjusted hazard ratio 1.04, 95% confidence interval 1.01 to 1.07; P for trend=0.005) and a 9% higher risk of other deaths (1.09, 1.05 to 1.13; P for trend<0.001), including an 8% higher risk of neurodegenerative deaths (1.08, 1.01 to 1.17; P for trend=0.1). We found no associations for deaths due to cardiovascular diseases, cancer, or respiratory diseases. The all cause mortality rate among participants in the lowest and highest quarter of ultra-processed food consumption was 1472 and 1536 per 100 000 person years, respectively.

Hazard ratios and 95% confidence intervals for mortality according to quarters of ultra-processed food (UPF) consumption

Table 3 shows the associations for nine subgroups of ultra-processed foods. Meat/poultry/seafood based ready-to-eat products (for example, processed meat) showed the strongest association with higher all cause mortality (hazard ratio 1.13 (1.10 to 1.16) comparing highest versus lowest quarter) and mortality due to individual causes other than cardiovascular diseases and neurodegenerative diseases (hazard ratios ranged from 1.06 to 1.43). Other subgroups also showed an association with higher all cause mortality, including sugar sweetened and artificially sweetened beverages (1.09, 1.07 to 1.12), other ultra-processed foods (mainly composed of artificial sweeteners) (1.08, 1.05 to 1.11), dairy based desserts (1.07, 1.04 to 1.10), and ultra-processed breakfast foods excluding whole grains (1.04, 1.02 to 1.07). When further separating sugar sweetened and artificially sweetened beverages, we found a generally stronger association for sugar sweetened than artificially sweetened beverages; we present these results and those for other selected individual ultra-processed food categories in supplementary table D.

Multivariable hazard ratios and 95% confidence intervals for mortality according to quarters of subgroups of ultra-processed food consumption *

When we examined ultra-processed food intake and AHEI score together ( fig 1 ), we did not observe a consistent association of ultra-processed foods with mortality within each quarter of the AHEI score, whereas AHEI score generally showed an inverse association with mortality within each of the quarters of ultra-processed food consumption.

Joint analysis for mortality according to quarters of ultra-processed food (UPF) consumption and quarters of Alternative Healthy Eating Index-2010 (AHEI) score. Alcohol was removed from calculation of AHEI score. Each participant was categorized according to their quarter of UPF intake and their quarter of AHEI score, resulting in 16 distinct groups. Using this combined variable as exposure, its association with mortality outcomes was assessed, with reference group being participants in highest quarter of AHEI score (Q4) and lowest quarter of UPF intake (Q1). Results were from multivariable Cox proportional hazards model stratified by age (months), questionnaire cycle (two year interval), and cohort and adjusted for total energy intake, race, marital status, physical activity, body mass index, smoking status and pack years, alcohol consumption, physical examination performed for screening purposes, and family history of diabetes mellitus, myocardial infarction, or cancer; for women, also menopausal status and hormone use. Markers denote point estimates of hazard ratios and error bars indicate 95% confidence intervals

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We found similar results in men and women (supplementary table E). The results of sensitivity analyses are summarized in supplementary table F. The lagged analysis showed similar results to the primary analysis. The associations were attenuated when we stopped updating the information on ultra-processed food intake at a diagnosis of chronic disease, likely owing to the increased intake of ultra-processed foods over time (supplementary figures D and E). Unsurprisingly, including wholegrain products in ultra-processed foods weakened the associations, whereas including distilled alcohol strengthened the associations. Removing pack years of smoking from the multivariable model led to a much stronger positive association, whereas adjusting for the AHEI score attenuated the association toward null.

In the stratified analysis by major risk factors, the associations between ultra-processed food intake and all cause mortality seemed to be stronger in participants consuming less alcohol (P for interaction=0.005) and not currently smoking (P for interaction<0.001), but we found no interaction by body mass index or physical activity (supplementary table G). We repeated the primary analysis using percentage of energy to measure ultra-processed food intake and observed similar results (supplementary table H).

In two large prospective cohorts with up to 34 years of follow-up, we found that higher consumption of ultra-processed foods was associated with modestly higher all cause mortality. We found no associations for mortality due to cancer or cardiovascular diseases. The associations varied across subgroups of ultra-processed foods, with meat/poultry/seafood based ready-to-eat products consistently showing associations with higher all cause mortality and cause specific mortality. The associations between ultra-processed food consumption and mortality were attenuated after we accounted for overall dietary quality.

Comparison with other studies and possible explanations

Existing evidence suggests a relation between ultra-processed food consumption and mortality. A meta-analysis of prospective cohorts reported that the highest ultra-processed food consumption was associated with higher all cause mortality compared with the lowest consumption (hazard ratio 1.21, 1.13 to 1.30). 23 Two studies were conducted in the US, 24 25 whereas the other six were conducted in Spain, 26 27 28 France, 29 Italy, 30 and the UK. 31 Unlike our study, which excluded alcohol from ultra-processed foods and carefully controlled for smoking status and pack years, all the above studies included alcohol in ultra-processed foods and adjusted for smoking status (never, former, and current) only. As noted in our sensitivity analysis, pack years of smoking strongly confounded the association—additionally adjusting for smoking pack years remarkably attenuated the hazard ratios toward the null. That may partly explain why the associations found in our study were weaker than those in previous studies. Another possible reason could be tighter control for socioeconomic status because our participants were all health professionals and had similar levels of education.

The evidence on mortality due to cancer is relatively sparse. Consistently, the Moli-sani Study did not observe a statistically significant association but reported a positive association with other mortality. 30 An analysis of three cohorts including the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO), NHANES (1999-2018), and UK Biobank reported null findings for mortality due to cancer in the PLCO and NHANES (1999-2018). 32 By contrast, the UK Biobank study found that every 10% increment in ultra-processed food consumption was associated with a 6% higher cancer mortality. 33 Diet was assessed in the UK Biobank through multiple 24 hour recalls between 2009 and 2012, and 40% of the participants had only one 24 hour recall, thus limiting the ability to capture long term dietary intake.

In agreement with our study, the Prospective Urban and Rural Epidemiology study from 25 high income, middle income, and low income countries in America, Europe, Africa, and Asia observed a null association with mortality due to cardiovascular diseases but a positive association with non-cardiovascular disease mortality. 34 Our findings on the relation between ultra-processed foods and mortality due to cardiovascular diseases are inconsistent with previous evidence from Europe but consistent with the null finding in the US NHANES III (1988-94). 24 25 30 Moreover, a much stronger positive association was reported in the UK Biobank (1.28, 1.13 to 1.45) compared with the two US cohorts (1.12, 1.05 to 1.09; 1.11, 0.92 to 1.34). 32 In addition to the methodological differences mentioned above, different study populations, ultra-processed food compositions, and eating patterns may also contribute. Ultra-processed food intake in our two US cohorts is mainly contributed by “sauces, spreads, and condiments” and “sweet snacks and desserts,” which together accounted for nearly 50% (supplementary figure B), but neither of the two subgroups was associated with increased mortality due to cardiovascular diseases. On the other hand, compelling evidence shows that nuts and (dark) chocolate, common constituents of “sweet snacks and desserts,” are inversely associated with cardiovascular diseases. 35 36 We observed that dark chocolate in the subgroup “packaged sweet snacks and desserts” was associated with decreased mortality (supplementary table D). Therefore, the diverse array of constituents contained in ultra-processed foods with heterogeneous health effects may have contributed to the discrepant findings. Our findings suggest that meat/poultry/seafood based ready-to-eat products and sugar sweetened and artificially sweetened beverages are major factors contributing to the harmful influence of ultra-processed foods on mortality, which is in accordance with previous studies. 13 37 38 39

Few studies have investigated the relation with cause specific mortality other than that due to cancer and cardiovascular diseases. We found that ultra-processed food intake was associated with higher neurodegenerative mortality. Increasing evidence suggests that ultra-processed food is linked to higher risk of central nervous system demyelination (a precursor of multiple sclerosis), 40 lower cognitive function, 41 and dementia. 42 Studies have shown that a diet rich in ultra-processed foods may drive neuroinflammation and impairment of the blood-brain barrier, leading to neurodegeneration. 43 44 Of note, among ultra-processed food subgroups, diary based desserts showed the strongest association with neurodegenerative mortality. Earlier finding from the HPFS and NHS cohorts showed that intake of sherbet/frozen yogurt was associated with an increased risk of Parkinson’s disease. 45 Furthermore, we found a positive association between ultra-processed food intake measured by percentage of energy and respiratory mortality. Emerging evidence suggests that higher ultra-processed food intake is associated with increased risk of respiratory multimorbidity. 46 The increased respiratory mortality associated with processed red meat may be partly due to heme iron and nitrate/nitrite. 47

An important question not answered by previous studies is whether and how food processing level and nutritional quality jointly influence health. We observed that in the joint analysis, the AHEI score but not ultra-processed food intake showed a consistent association with mortality and that further adjustment for the AHEI score attenuated the association of ultra-processed food intake with mortality. Although including AHEI in the multivariable model for ultra-processed food may represent an overadjustment because common foods are included in both the AHEI and ultra-processed food, our data together suggest that dietary quality has a predominant influence on long term health, whereas the additional effect of food processing is likely to be limited. Furthermore, foods may have dual attributes according to their processing level and nutritional quality, and these two features may have quantitatively and even qualitatively different effects on health. Another added value of our study is the exclusion of wholegrain products that fall in the ultra-processed foods from the primary exposure, based on the well established health benefits associated with whole grains. By taking this approach, we aim to rectify the potential misperception that all ultra-processed food products should be universally restricted and to avoid oversimplification when formulating dietary recommendations.

Besides neglecting overall nutritional quality, the ultra-processed food classification system has other limitations. The Nova classification is based on broad categories that do not capture the full complexity of food processing, 48 leading to potential misclassification. Further work is needed to improve the assessment and categorization of ultra-processed foods. On the other hand, dietary guidelines should provide clear and sound food selections that are available, actionable, attainable, and affordable for the largest proportion of the population. Thus, careful deliberation is necessary when considering incorporation of ultra-processed foods into dietary guidelines. 49 50 Again, on the basis of our data, limiting total ultra-processed food consumption may not have a substantial influence on premature death, whereas reducing consumption of certain ultra-processed food subgroups (for example, processed meat) can be beneficial.

We note that mortality is a more complicated endpoint than disease incidence and is also influenced by several factors including early detection, treatment, and individuals’ overall health status. The findings for mortality should not be regarded as synonymous with those pertaining to disease incidence but rather considered as more comprehensive assessment of the health impact of risk factors.

Strengths and limitations of study

The strengths of the study include the prospective study design, large sample size, long follow-up, and detailed, validated, and repeated measurements. In addition, we rigorously controlled for confounding, did thorough sensitivity analyses, explored major specific causes of mortality, and examined individual ultra-processed food subgroups. Several limitations should also be noted. Firstly, we cannot rule out unmeasured and residual confounding due to the nature of the observational study. Secondly, our participants are health professionals and predominantly non-Hispanic white, limiting the generalizability of our findings. Thirdly, as the food frequency questionnaires collected intake of only a limited number of pre-defined items representing the primary source of energy and nutrients in the US population and were not designed to classify foods by processing level, they may not capture the full spectrum of ultra-processed foods. Although the food frequency questionnaires used in our cohorts have been validated for foods and nutrients, they were not specifically validated for ultra-processed foods. Moreover, we classified ultra-processed foods by using the same algorithm throughout follow-up that did not account for changes in the grade of food processing over time. These factors may have introduced non-differential misclassification, likely biasing our results toward the null.

Conclusions

Higher ultra-processed food intake was associated with slightly increased all cause mortality. The mortality associations for ultra-processed food consumption were more modest than those for dietary quality and varied across ultra-processed food subgroups, with meat/poultry/seafood based ready-to-eat products generally showing the strongest and most consistent associations with mortality. The findings provide support for limiting consumption of certain types of ultra-processed food for long term health. Future studies are warranted to improve the classification of ultra-processed foods and confirm our findings in other populations.

What is already known on this topic

Ultra-processed foods have been suggested to have adverse health effects

Evidence is limited on the influence of ultra-processed food consumption on mortality outcomes in large cohorts with long term follow-up and repeated dietary assessment

What this study adds

A higher intake of ultra-processed foods was associated with slightly higher all cause mortality, driven by causes other than cancer and cardiovascular diseases

The positive associations were mainly driven by meat/poultry/seafood based ready-to-eat products, sugar and artificially sweetened beverages, dairy based desserts, and ultra-processed breakfast foods

Dietary quality was observed to have a more predominant influence on mortality outcomes than ultra-processed food consumption

Ethics statements

Ethical approval.

The Nurses’ Health Study I and the Health Professionals Follow-up Study were approved by the Institutional Review Board at the Brigham and Women’s Hospital, the Harvard T.H. Chan School of Public Health (IRB protocol number: 1999-P-011114 and 10162). The completion of the self-administered questionnaire was considered to imply informed consent.

Data availability statement

Data can be shared through mechanisms detailed at https://www.nurseshealthstudy.org and https://www.hsph.harvard.edu/hpfs/ .

Acknowledgments

We thank the participants of the Nurses’ Health Study and the Health Professionals Follow-up Study and the staff of the Channing Division of Network Medicine for their valuable contributions. We acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention’s National Program of Cancer Registries (NPCR) and/or the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program. Central registries may also be supported by state agencies, universities, and cancer centers. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Seattle SEER Registry, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, and Wyoming. The authors assume full responsibility for analyses and interpretation of these data.

Contributors: ZF did the statistical analysis and drafted the manuscript. SLR and NK made a substantial contribution to the concept of the article. DH, WK, CHL, WCW, and ELG were involved in the acquisition and interpretation of data. MS was responsible for the study design. All authors critically assessed, edited, and approved the final manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. MS is the guarantor.

Funding: This work was supported by the US National Institutes of Health grants (UM1 CA186107; P01 CA87969; U01 CA167552; U01 CA261961; R01 CA263776; and K99 CA283146). The funders had no role in considering the study design or in the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit the article for publication.

Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: support from the National Institutes of Health for the submitted work; NK received a consulting fee from the Pan American Health Organization for three months on the topic of nutrition disclosure initiatives and nutrient profiling models; no other relationships or activities that could appear to have influenced the submitted work.

Transparency: The manuscript’s guarantor affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Dissemination to participants and related patient and public communities: The research findings are disseminated to participants through periodic newsletters and study websites at https://www.nurseshealthstudy.org and https://www.hsph.harvard.edu/hpfs/ . The manuscript will be disseminated to the general public through press releases.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

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Ultra-processed foods (UPFs) are harming our health – here’s what to eat instead

I t seems like only yesterday we could enjoy our toast and cereal in the morning without a care in the world. Not anymore. Research published in the The British Medical Journal (BMJ) shows that eating a lot of ultra-processed foods (UPFs) such as sugary cereals, ready meals and fizzy drinks has been linked to poor mental health and a greater risk of dying from heart issues.

UPFs are usually higher in fat, sugar and salt and contain chemicals, colourings, sweeteners and preservatives that extend shelf life. And thanks to Dr Chris van Tulleken, author of the bestselling book Ultra-Processed People: The Science Behind Food That Isn’t Food , it’s a term now popping up everywhere. 

Despite the latest research, this is an area beset by contradictions and confusion, with many of us wondering what exactly constitutes an UPF and if there’s anything left to eat that won’t make us fat or unwell.

“It’s high-fat, high-salt and high-sugar, but these ingredients have been combined into industrial products with exotic additives, which can’t really be described as food. They’re ultra-processed foods, a set of edible substances that are addictive for many and which are now linked to weight gain, early death and, yes – depression,” Dr van Tulleken told The Telegraph .

So which foods should remain on the “naughty list” , to be eaten on rare occasions and which can be part of a healthy diet ?

Swap UPFs for these foods

Swap your ultra-processed sliced white bread – which contains emulsifiers to improve texture and shelf life – for sourdough made from only flour, salt and yeast.

Ditch processed meat which contains chemical preservatives such as nitrates to make it last longer. Get your protein fix from boiled eggs which are also a good source of vitamins D and B12.

Margarine often contains a lot of emulsifiers to keep its texture – stick to good old-fashioned butter (in moderation).

Some cereals are not only high in sugar, but they can also be ultra-processed. Try to avoid ingredients such as butylated hydroxyanisole (BHA), and butylated hydroxytoluene (BHT) which are potentially harmful additives or switch to porridge made with oats and cow’s milk for a filling breakfast.

Avoid flavoured tortilla chips and crisps which are high in calories, fat, and salt, plus many crisps are flavoured artificially with ingredients such as monosodium glutamate and dextrose (a type of sugar). Swap for homemade popcorn – as well as being a good source of fibre, popcorn also contains phenolic acids, a type of antioxidant.

Sweetened low-fat yogurts are high in added sugars, to replace the flavour lost from removing most of the fat. Try choosing a full-fat natural Greek yoghurt, as the fat actually helps you to feel fuller for longer. Or try kefir yoghurt – it’s full of probiotics to feed your gut bacteria.

What does the latest 2024 research on UPFs say?

The research conducted by academics in Australia , published in February 2024, reviewed 14 studies published in the past years to assess the impact of UPF foods on various health measures. The studies followed a total of 9.9 million people who had responded to questions regarding their food preferences and habits.

Based on their answers and health history the researchers concluded that a higher UPF intake was associated with a 50 per cent greater risk of death from cardiovascular disease, a 12 per cent greater risk of type 2 diabetes, and a 48-53 per cent greater risk of developing anxiety.

The scientists concluded there was further “highly suggestive” evidence that eating more UPFs could increase the risk of obesity, type 2 diabetes, sleep problems and dying from heart disease by 40-66 per cent, as well as a 22 per cent greater risk of developing depression and a 21 per cent greater risk of death from any cause. UPFs have been linked to 32 different health conditions in total, with varying degrees of credibility, the researchers concluded.

All in all it’s a pretty damning assessment, adding to the multiple black marks chalked up by highly processed, chemically manipulated foods. 

What is the definition of ultra-processed food?

UPFs now account for almost 60 per cent of the UK diet, and it’s easy to see why the products are popular; they’re cheap, convenient, delicious and designed to be moreish. 

Almost all food is processed to some extent, to make it digestible and tasty, or to delay spoiling. Think flour (made from ground and sifted grains), tinned tomatoes (sealed in a can using heat) and pasta (produced by mixing flour, water and sometimes eggs). 

UPFs are different. The term dates to 2009 when Carlos Monteirom, a professor from the University of São Paulo in Brazil, developed the Nova classification system. This divides food into four groups according to how extensively they have been processed, ranging from group 1, foods that are minimally processed with no added salt, sugar, oils, fats or other additives,  to group 4, which are ultra-processed foods that are formulated in factories, often using multiple processes. Scientists around the world now use the Nova system to study links between eating habits and disease, and evidence is mounting that UPFs can seriously damage our health.

Typical examples in our daily shop include pizzas, breakfast cereals and cereal bars, cakes and biscuits, sweet and savoury snacks, crisps, baked goods like bread, sausage rolls and pastries, ready meals, flavoured yoghurt and yoghurt drinks, fruit drinks, milk drinks, alternative milks and alternative meat products. 

Most of these are obviously UPF and clearly not good for our health; they’re loaded with sugar, salt and/or fat. Additives are a red flag, too. “If there’s an ingredient on the list that you don’t find in a kitchen cupboard, it’s very probably UPF,” says Dr van Tulleken. 

Some UPFs are harder to identify. “Anything with a health claim on it is probably a UPF,” Dr Van Tulleken says. “It’s marketing by companies that have the budget to do it. There’s no health claim on broccoli, oily fish or any of the stuff we know is healthy.” 

For example, the wording on the packet about fibre, vitamins and/or minerals suggests the food has been stripped of nutrients during processing and the manufacturer has added some back in order to be allowed to promote it as healthy. These types of health claims are common on boxes of breakfast cereal, for example.

It’s worth noting that some unfamiliar ingredients don’t necessarily signify UPF. Certain flours sold in the UK are fortified with calcium, iron, thiamine and niacin, and don’t count as UPF.  Corn starch, also known as corn flour, isn’t UPF either, but “modified” corn starch is.

What’s the difference between processed food and ultra-processed food?

Distinguishing unprocessed food (like an apple) from UPF (a chocolate bar) is easy, but the difference between processed and ultra-processed food is not always clear.

In his guide, ‘Ultra-processed foods: what they are and how to identify them’, Prof Monteiro lists the ingredients to look out for that indicate a product is probably UPF. 

Check for: sugars (fructose, high-fructose corn syrup, “fruit juice concentrate”, invert sugar, maltodextrin, dextrose, lactose);  modified oils (hydrogenated or interesterified oils); and protein sources (hydrolysed proteins, soya protein isolate, gluten, casein, whey protein and “mechanically separated meat”). These will be found at the beginning or in the middle of the ingredients list of UPF.

Cosmetic additives are designed to enhance the flavour, appearance and texture of food and are found at the bottom of the ingredients list. They include flavours, flavour enhancers, colours, emulsifiers, emulsifying salts, sweeteners, thickeners, and anti-foaming, bulking, carbonating, foaming, gelling and glazing agents.

What alternatives are there to ultra-processed foods?

Preparing meals and snacks from scratch with unprocessed or minimally processed ingredients is ideal, but for most of us this simply isn’t possible all the time. The good news is there are non-UPF versions of many UPFs – these products are processed rather than ultra-processed. 

Many organic versions of common UPFs, such as tins of baked beans and non-dairy milk alternatives, are not ultra-processed. For example, most ready-meal lasagne is an UPF but Tesco and Marks & Spencer both sell versions that are processed but not ultra-processed, and both score B  for “good nutritional quality”.  

Dr van Tulleken stresses he’s not encouraging anyone to eat ready meals every night just because they’re not ultra-processed.  “There are lots of non-UPF ready meals that are great and convenient, but the evidence shows that if you can possibly cook a lasagne at home, it will be better for you than even the non-UPF convenience meal.”

Dr van Tulleken also recommends Open Food Facts, a free app and online database that makes it easy to differentiate processed from UPF products. UPF is identified as Nova group 4, while processed food is Nova group 3. The database also indicates how nutritious a product is according to the Nutri Score system, a five-point scale that rates food letters from A to E, indicating highest to lowest nutritional quality, and colours from green to red (best to worst).

Why are ultra-processed foods bad for you? 

The new Australian study is the latest of many that have linked UPFs with a range of health problems, including obesity, diabetes, cancer and dementia. Other recent studies from Australia and China suggested UPF can significantly raise the risk of high blood pressure, heart disease, heart attacks and strokes. 

Australian research published last year followed more than 10,000 women for 15 years and found those who consumed the most UPF were 39 per cent more likely to develop high blood pressure than those who consumed the least. High blood pressure is linked to heart disease, disease of the arteries and dementia.

The Chinese research involved more than 325,000 men and women and linked high UPF consumption with a 24 per cent higher chance of problems like heart attack, stroke and angina.  

There is also evidence linking UPF to obesity. It’s thought the soft/creamy texture and intense flavour of many UPFs makes them “hyper palatable”. This confuses the signals between the gut and the brain; we can’t tell when we’re full , so we eat more.

Do ultra-processed foods cause cancer? 

In 2023, the results of a large study by Imperial College London were published in The Lancet medical journal. 

The research, the largest of its kind, involved almost 200,000 UK adults and linked higher consumption of UPF to increased risk of cancer, specifically ovarian and brain cancers.

It’s not clear why UPF seems to be causing us harm. Research suggests it’s not just the high levels of sugar, fat and salt found in UPFs that are the problem, or the additives on their own. “The individual ingredients of UPF may each be harmful, but it is in combination that they do the most harm,” Dr van Tulleken says. The effect of individual molecules on our metabolism is complex, so scientists are still trying to work out exactly how this works.

Some scientists are cautious about studies that suggest UPFs are at the root of disease. They argue most of the research is observational and therefore doesn’t prove that UPF actually causes health problems.  Researchers can adjust results to take into account some but not all of the many lifestyle factors that might influence the results, such as smoking, exercise, sleep and stress.  

But Dr Courtney Scott, a dietician with the Food, Farming and Countryside Commission believes there’s now sufficient evidence to ring alarm bells. “Every study about UPF, as far as I know, has shown a negative impact on health,” she says. “If you combine the consistency of that evidence with what we know about the health benefits of minimally processed food, it means it’s time to start thinking about how we can reduce UPFs in our shops and also in our shopping baskets.”

Which ultra-processed foods should I avoid?

It’s impossible to rank UPFs precisely from least worst to worst for your health – there are too many factors involved.

Some nutritionists suggest that if you do buy UPF, check the label and choose one low in sugar, fat and salt. Try to add lots of good stuff to your plate – for example eat lots of leafy greens with a UPF pizza. Or if you have a UPF meal for dinner, try to eat minimally processed food for the rest of the day.

Similarly, if you have a bacon sandwich for breakfast, opt for a UPF-free dinner with plenty of vegetables.

Processed meat – any that’s been preserved or changed including bacon – is associated with a higher risk of bowel cancer. According to Cancer Research UK, just 25g a day (that’s one measly rasher) raises your risk. Eating large quantities of red meat has been associated with it too. 

When it comes to bacon, the blame is laid with chemicals added in the processing: nitrates and nitrites.

“It’s about doing what you can where you can because we all have to navigate everyday life,” Dr Scott says. “Focus wherever possible on minimally processed food. And I know this is impossible for a lot of people, but wherever possible, cooking those foods yourself so you know exactly what’s gone into them.”

Dr Scott and Dr van Tulleken believe it shouldn’t be up to individual consumers to navigate UPFs on their own. Our supermarkets and high streets are overflowing with UPFs made by food manufacturers who invest significant amounts of money into trying to convince us to buy their products.

“I would like there to be a public health campaign warning people about the research on UPFs, which is very robust, “ Dr van Tulleken says. “UPFs should eventually have warning labels, and our national nutrition guidance should advise people to cut down.”

He isn’t calling for everyone to give up UPF completely. “My interest is in people having more choice and freedom, not telling people what to eat,” he says. “But if 60 per cent of your calories are coming from UPFs, the evidence shows that those products are troubling and are not made with your health in mind.”

Sue Quinn is an award-winning food writer, journalist and author of food blog penadnspoon.com .

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This engineer went from selling food packaging to Subway to creating his own Mexican food brand

From making delivery-only products to selling in stores nationwide, here’s the story behind the top-selling somos foods., by fernando hurtado, gerardo pons and miguel estrada • published may 14, 2024 • updated on may 14, 2024 at 2:02 pm.

A home-cooked meal is a labor of love.

And for Miguel Leal, a Mexican-born entrepreneur, the love for Mexican food is what eventually led him to begin his entrepreneurship career.

Leal and two friends, Daniel Lubetzky and Rodrigo Zuloaga, are the founders of SOMOS Foods , a company of ready-to-eat non-GMO and gluten-free Mexican products.

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Now only a little over two years old, SOMOS Foods is already sold in 9,000 retail stores nationwide, including Whole Foods.

While Leal found success with his food business, he didn't go into that sector right away. As a matter of fact, he initially wanted to pursue a career in engineering.

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"I come from a family of entrepreneurs," Leal said. "I saw both of my grandfathers start their own business and, you know, my dad, my uncle... I saw all the effort and all the risks that they took."

Leal grew up in Monterrey, a city in northern Mexico known for its exceptional barbecue scene and proximity to the U.S.-Mexico border.

At a young age, Leal would watch his family grow businesses, some more successful than others.

But he particularly learned a lot from one of his grandfathers, who created an industrial equipment company named Tolteca.

"My grandfather would bring me in to translate to the people installing equipment at his factory," Leal said.

Leal added that he would watch his grandfather buy discarded equipment from Europe to put in his factory, something that impressed him due to the risks it entailed.

"I was in my early teens and it was just so impressive on me," he said. "Like it just really dawned on me the risk and reward that he was taking."

He eventually grew up to study industrial engineering at one of Mexico's best schools, the Monterrey Institute of Technology . After graduating, he had planned to continue specializing in engineering but opted to pursue an MBA at the University of Pennsylvania instead.

Venturing into entrepreneurship

After graduating with an MBA from UPenn and meeting his wife there, Leal opened his first business in 2002. Select Product Group sold packaging to fast-food restaurants.

"We made food packaging for Subway," Leal said. "It was quite successful, we grew to over a hundred million dollars in sales."

Years later, in 2007, Leal would sell the company to Georgia Pacific, one of the world's largest manufacturers and distributors of tissues, paper and pulp -- an achievement he says really started his entrepreneurship career.

Sometimes you're not going to get the deal. But every time, even if it's positive or negative, it's an opportunity to build the relationship. Miguel Leal

Despite making millions from selling his company, Leal still had to figure out the next step in his career.

"We made a little bit of money," Leal said. "But not enough to retire, so I had to work."

From working paper to food

So here's Leal in 2007, having sold his first multi-million dollar company and thinking ahead on his next challenge.

He was not a recent graduate anymore, and he had two new things to consider in his personal life: a newborn daughter and his wife, Jeanette, had quit her full-time job to become a yoga instructor.

"All of a sudden, not only was I a dad, there were three of us and I was the main breadwinner," Leal said. "It was a lot of pressure on what I was going to do next financially."

So he first thought of starting a restaurant, but after exploring the different possibilities, he opted for a job where he wasn't the boss. He began working for Frito-Lay as a brand manager, where he (sort of) took a break from the stress of running a company and focused on what he loved most: food and people.

"I was the lowest person in the marketing organization and I loved it," he said. "I worked with really smart people and I am here today with so much because of that decision."

Leal wound up working for Frito-Lay for two years and then quit to work for other companies like Danone and KIND until he wound up at Cholula , the Mexican hot sauce maker.

"The most important thing that I learned from that brand was that people are interested in quality food from Mexico," Leal said.

"That was just like a huge, huge eye opener and a point of pride for me," he said. "I was the only Mexican on the team in the U.S. and I just felt like it was amazing, that product."

Who doesn't like Mexican food?

Why does Mexican food have to be cheap, have fillers and low-quality ingredients? Miguel Leal

So how did Leal get the idea to start a Mexican food brand?

According to him, there were several episodes in his life where he contemplated the idea.

One of the first was when he was still in college in Mexico and lived with his grandma.

"She was an old-school Mexican grandma," Leal said, "She would buy things fresh every day. The tortillas, the beans, everything, and just cook. It would be delicious."

But once Leal grew older, he realized not everyone had the time to go buy high-quality ingredients to cook as his grandmother did back in the day.

"I see my kids that are second-generation Hispanic, and, many of my friends from multicultural families, they are all busy, they don't have time to go every day to the market," Leal said.

Then, as he brainstormed what to do, he remembered a conversation he had with Daniel Lubetzky, a friend of his who founded KIND bars in 2017, where he asked himself three simple questions: Why does Mexican food have to be cheap, have fillers and be made of low-quality ingredients?

And so he decided to call Lubetzky and put the idea of making a Mexican food brand to work.

SOMOS is born

"The first thing was, well, we need a name, we need some recipes and we need a team," Leal said.

With the help of Lubetzky and their American wives, Leal was able to get a list of people to hire and a name for the brand that tied both Americans and Mexicans together.

"We wanted a brand that would bring cultures together. And I love (SOMOS), because it has a lot of symmetry," he said.

The word "somos" is Spanish for "we are," and Leal liked that it was a 5-letter word that had perfect symmetry when split in half.

After coming up with the name, Leal and Lubetzky brought in a third friend, Rodrigo Zuloaga, who also worked at KIND and came from a long line of chefs.

"Our first hire was operations, then sales, then finance, and then we were off to the races," Leal said.

Then came the sauce recipe, which Zuloaga worked on from Jalisco, Mexico.

"Rodrigo would send us food in boxes to me at my house," Leal said. "And then we said, Why don't we just do a direct-to-consumer business? These boxes are great.'"

The trio tested direct-to-consumer delivery in 2021, as the coronavirus pandemic ravaged the U.S. The service "tested amazing," exceeding expectations, Leal remembers.

"We were supposed to sell 5,000 cases the first month, and we sold 15,000 cases the first week," Leal said.

From delivery service to grocery store staple

But it would all come crashing down as people began leaving their homes in 2021, and started shopping in stores again.

"We were launching nationally and it was very tough," Leal said. "It was a huge failure financially. It was brutal."

But as they slowly pushed to sell their sauces at retail stores in 2021, they began to see some success.

The big break happened when Leal got their products on display at Expo West, the largest trade show for natural foods in the U.S.

"There are close to 90,000 people that come to it. You have about nine to 10,000 different companies that have a stand and have their food," Leal said.

But the retailers were the most important, who were also present at the show.

"You have all the retailers, everybody from, you know, Whole Foods to Walmart, to 7-Eleven, to Albertsons, to Sprouts," he explained. "It is a make-or-break event for us in the food industry."

So Leal and Lubetzky used their food industry connections to get into meetings with the big retailers, who would eventually help scale up their distribution.

"Daniel, myself, everybody in the team would just reach out to everybody that would pick up the phone and give us an appointment at Expo."

And now, three years after starting SOMOS, the company's products span salsas and vegan entrées like rice and beans.

"I love the brand. I love my job. I love the team. So we're, we're going to continue until I retire," Leal said.

Leal was interviewed for Bísness School, a series that tells the inspiring stories of Latino founders. Subscribe to Bísness School wherever you get your podcasts to get future episodes automatically. Remember, business school is expensive. Bísness School is free.

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