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Hypothetical impact of the Mexican front-of-pack labeling on intake of critical nutrients and energy

Journal of Health, Population and Nutrition volume 42, Article number: 124 (2023) Cite this article

Abstract

Background

Since 2020 in Mexico, front-of-pack warning labels (FOPWL) have been implemented in processed products. Evidence supports warning labels allow consumers to identify unhealthy products. We aimed to evaluate the hypothetical impact of the FOPWL regulation on the Mexican population’s intake of critical nutrients and energy, based on the replacement of food and beverages using 4 hypothetical scenarios which represented the phases of the regulation.

Methods

Dietary data were collected using a standardized 24-h dietary recall from the 2016 Mexican National Health and Nutrition Survey (n = 4184). To evaluate the hypothetical impact of FOPWL, the nutritional content of critical nutrients in processed products was evaluated according to the Mexican Official Standard 051 (NOM-051). Then, we replaced products with several warning labels (WL) with those with a fewer number of them or with non-processed food. For the replacement, 4 hypothetical scenarios were established: scenario 1: the current consumption of the Mexican Population, scenario 2: the replacement during the first phase of the norm, scenario 3: the replacement in the second phase and scenario 4: the replacement in the last phase. We estimated the means, confidence intervals (CI 95%), and the mean percentage change of energy, saturated fat, trans-fat, added sugars, and sodium intake during the second, third, and the fourth scenarios.

Results

According to the norm, in the second scenario, the majority of the products presented a label for energy (52.6%) whereas in the third (56.4%) and fourth (61.2%) scenarios were for sodium. In contrast, trans-fat was the least labeled nutrient in all the scenarios (from 2.1 to 4.1%). In the fourth scenario, we observed a reduction of the intake of energy intake to 15.4% as well as saturated fat (− 20%, CI 95% − 18.4; − 21.6), trans-fat (− 8.2%, CI 95% − 6.4; − 10.1) and sodium (− 12.7%, CI 95% − 11.3; − 14.1). The most important reduction was observed for added sugars intake (until − 54.1%, CI 95% − 51; − 57.1).

Conclusions

FOPWL could be an effective strategy to decrease energy consumption and nutrients of concern. If consumers use the FOPWL, it would be an important change in critical nutrients intake. These results support that FOPWL might help the Mexican population to choose healthier nutrition alternatives.

Background

Non-communicable diseases (NCDs) are the leading cause of death worldwide [1] and contribute to more than half of the global burden of disease [2]. Unhealthy diets, typically high in sugars, sodium saturated and trans-fats, low in fruits and vegetables and high-sugar drinks, are one of the main risk factors for ill health [2]. In 2017, 11 million deaths worldwide of which 22% among adults, mostly those caused by NCDs like type 2 diabetes, cardiovascular disease and cancers were attributable to unhealthy diets [3]. In Mexico, according to the National Health and Nutrition Survey (ENSANUT by its acronym in Spanish, 2018) [4], there was an increase in the prevalence of overweight and obesity (from 71.3 to 75.2%) between 2012 and 2018 and the proportion of adults with type 2 diabetes also increased from 9.2 (6.4 million) to 10.3% (8.6 million) in the same period. Besides, diabetes is the main cause of disability and the third cause of mortality in Mexico [4].

The high intake of sodium, added sugars, saturated and trans-fats has been associated with increased risk for NCDs [5]. High levels of this dietary components are found in processed and ultra-processed food and beverages, as defined by the NOVA food classification [6]. This food classification is a system that categorizes foods according to the nature, extent and purpose of food processing, rather than by nutrients [6]. In Mexico, added sugars and saturated fats contribute 12.5 and 11.2% (respectively) to total energy intake [7] Therefore, it is important to reduce the intake of these nutrients and to look for strategies to help the population decrease their intake.

However, in the last decades, diet went through major changes, and the energy intake per capita increased by 580 kcal/day globally [8, 9]. The changes are attributed to the increase in processed and energy-dense food [8]. Mexico is not an exception and has followed the same trend of ultra-processed food; according to NOVA classification, they are the food group that “use many ingredients including food additives that improve palatability, processed raw materials and ingredients that are rarely used in home cooking” [6]. In 2013, Mexico had the highest sales of ultra-processed foods among Latin American countries and the fourth worldwide [10]. Furthermore, from 1984 to 2016 [11], the energy contribution of ultra-processed foods and processed food to household purchases increased from 10.5 kcal to 23.1% and from 5.7 to 6.5% kcal, respectively. In contrast, unprocessed or minimally processed foods decreased from 69.8 to 61.4% kcal [11].

Guidance to choose healthy foods using the Front-of-Pack Warning Label (FOPWL) system for processed food is an important cost-effective policy to reduce the intake of critical nutrients [12,13,14,15,16] along with educational nutrition programs. The FOPWL is part of a group of strategies established to improve the food environment. In Mexico, the official FOPWL Regulation (Official Mexican Standards, NOM-51, for its Spanish acronym) went into effect October 2020 and determines the eligibility of foods and the thresholds for the content of energy, saturated fat, trans-fat, added sugars and sodium in processed food per 100 g or ml, based on the Pan American Health Organization (PAHO) nutrient profile model. To give time to the food industry to adapt its products according to the standard, the implementation will be carried out in 3 phases. The first phase of the regulation began in October 2020, the second will begin in October 2023 and the last phase will begin in October 2025 although the thresholds for them will become progressively stricter over 5 years across the phases.

Under the NOM-51, processed foods must include warning labels (WL) when the content of the previous nutrients of interest exceeds the thresholds. For example, a product will bear the “Excess sugar” and “Excess saturated fat” label if the product’s sugar or saturated fat content is 10% or more of the total calories. The “Excess trans-fat” label will be used if trans-fat content is 1% or more. For the “Excess sodium,” label, criteria include 1 mg or more of sodium per calorie or 300 mg or more of sodium in beverages and packaged foods; for non-caloric beverages, 45 mg or more of sodium [17]. In consequence, a product within a food group with more WL is less healthy for consumption. Thus, it is expected that consumers with different levels of literacy will understand easily the nutritional content and will discriminate between a healthy and unhealthy product allowing them to make more informed choices in a practical way [18]. In Latin American countries, a number of studies evaluated the FOPWL impact on awareness [19, 20], understanding [20,21,22], acceptability [23], use [19] and the effects on healthfulness perceptions [24, 25]. However, only one Chilean study evaluated the impact of FOPWL on household beverage purchases [16]. Besides, FOPWL is a public policy whose compliance must be monitored and evaluated either by the government or by academia. This is an effort to hypothetically evaluate the impact of the policy on the consumption of energy and critical nutrients that could be observed if FOPWL were used by the Mexican population. Previous studies have proved that modeling is useful to accurately estimate the nutrient intakes when processed food is replaced using healthier alternatives [26,27,28]. These studies are frequently used to anticipate dietary changes before they are implemented in populations like in Mexico. Therefore, we aimed to assess the potential of the FOPWL on Mexican population’s intake of critical nutrients and energy by replacing products with several WL with those with a fewer number of them or with non-processed food in four hypothetical scenarios represented the phases of the regulation.

Methods

Study design and sample

The National Health and Nutrition Survey of 2016 (ENSANUT 2016, for its Spanish acronym) is a cross-sectional, multistage, probabilistic, stratified, cluster survey with national and urban/rural representativeness [29], carried out between May and September of 2016. Data on 29,795 individuals from 9474 randomly selected households, were collected with a response rate of 78%. The main objective was to characterize the health and nutritional status of the Mexican population [29]. The specific survey methodology and the sampling procedures were described previously [29]. All participants signed informed consent, and the study protocol was approved by the Ethics, Research and Biosafety Committee of the National Institute of Public Health (INSP-Spanish acronym).

Dietary information was obtained for a random subsample of ∼ 15% (n = 4341). For the present analysis, we included adults, adolescents, school-aged children, and preschool children. We excluded pregnant and lactating females (n = 89), participants with an extreme energy intake (± 3 standard deviations of the ratio of energy intake and energy requirement, n = 64) and breastfed children (n = 4). Thus, the analytical sample included 4184 participants.

Assessment of dietary intake

Dietary data were collected using a standardized 24-h dietary recall applied by trained personnel. An automated software was used to collect this data, which was an adapted version of the original method created by the United States Department of Agriculture [30]. To capture more accurately the food intake and avoid underestimation, a multiple five-pass methods was used [30]. Participants reported all food and beverages consumed in the previous 24 h period, and the type and amount of food items consumed were recorded. Participants under 15 years were assisted by the person responsible for food preparation in their household.

To estimate nutrient content, first food and beverages reported in the 24-h recalls were classified in processed and unprocessed food according to NOVA classification [6] (See Additional file 1: Table 1). For unprocessed food, we estimated energy and nutrient content using the 2016 INSP food composition table (Nutrient Database, Compilation of the Mexican National Institute of Public Health, unpublished material, 2016). Most processed food in the 24-h recall were not at the brand level, with some exceptions such as boxed cereals and some cereal-based desserts. For non-branded products, such as chips, we selected the best-selling brand in Mexico using the Nielsen Consumer Panel (2016), which is a global leader in retail measurement services. For the selected product at the brand level, the nutritional content was matched using the 2017 INFORMAS database [31] (a database of food composition of package foods and beverages that were available in the main chains of retail stores in Mexico). We were able to match 82% of products to their specific nutrition composition. If the nutritional content of the selected brand was not available, an average of the brands in the database was estimated. For the remaining products, for which no brand was available, we used the nutritional content of the 2016 INSP food composition table.

The Mexican regulation

Details of the official FOPWL Regulation (Official Mexican Standards, NOM-51) were described previously [17]. The FOPWL consists of a black octagon with white borders which highlights that the product has an excess in the critical nutrients (added sugars, sodium, trans and saturated fat) and energy per 100 g using the wording “Excess in” in front of the package (Table 1). To give time to the food industry to adapt its products according to the standard, the implementation will be carried out progressively in 3 phases. The first phase of the regulation began in October 2020, the second will begin in October 2023 and the last phase will begin in October 2025.

Table 1 Criteria of the front-of-pack warning label (FOPWL) regulation, NOM-051. Mexico 2019
Full size table

Packaged food with added salt, fat, or sugars was required to carry the FOPWL if the content of them exceeded the established thresholds in the norm, the details of each phase are presented in Table 1. The evaluation of critical nutrients to determine if a product would bear a label varied between the phases of the norm, the thresholds become stricter across the phases. Under the regulation, processed foods must include warning labels (WL) when the content of the nutrients of interest exceeds the thresholds described in Table 1. During the first and second phase of the norm, the evaluation was as follows: if added sugars was added, sugars and calories were evaluated. If fats were added, saturated fats, trans-fats and calories were evaluated; finally, if sodium was added, only sodium was evaluated. In the second and third phases, the thresholds were the same. For the third phase, all critical nutrients must be evaluated if the product contained at least one of them. Three types of products were exempted from labeling: unpackaged products, culinary ingredients (e.g., oils and salt), and products for infants and young children, including infant formula.

FOPWL assessment and replacement

We estimated the amount and type of WL each processed food would have, according to the FOPWL Regulation. Accordingly, these items could have zero to five WL. For the replacement, we consider two criteria: the number of labels and the type of processed food. Thus, we created 18 food groups, within which the number of WL varied (Table 2). Given this variation, we used products with 0 or 1 WL to replace products with 2 or more labels. However, there were food groups in which there were no products with 0 or 1 WL; therefore, we selected the product with less WL. For some products, we were unable to find a suitable alternative, for which, we simulated the effect of reducing product’s intake by 5%. This 5% approach is a hypothetical scenario. For example, in the food group “Salted bread” for the product rye bread which has 0 labels, we did not find a processed product to replace it with.

Table 2 Number of warning labels (WL) by food groups for processed food (n = 420)
Full size table

Four scenarios were established to evaluate the replacement and they are given as follows: Scenario 1 represents the current consumption of the Mexican Population, scenario 2 simulates the replacement during the first phase of the norm and each product was replaced by a similar one with less WL and the same amount in grams, scenario 3 simulates the replacement during the second phase of the norm, and scenario 4 simulates the replacement during the third and last phase of the norm. In this last scenario, we also aimed to replace packaged items with WL with non-processed food and beverages. For example, mayonnaise was replaced in the second and third scenarios with mayonnaise light. However, in the fourth scenario, there was no option to replace it with; thus, we reduced its consumption by 5%.

Sociodemographic variables

We included the following sociodemographic characteristics: sex, age group, socioeconomic status (SES), locality (rural: < 2 500 inhabitants/urban: ≥ 2 500 inhabitants) and geographic region (North, Center, South and Mexico City). We created 4 age groups: adults (≥ 20 years), adolescents (12–19 years), school-aged children (5–11 years) and preschool children (1–4 years). The SES variable was created using principal component analysis which included household characteristics and goods. This variable was divided into tertiles and used as a proxy for low, medium, and high SES.

Statistical analysis

Energy and nutrient intake of the population was estimated and presented in means and 95% confidence intervals (95% CI). Furthermore, intake was stratified by sociodemographic characteristics. Finally, we estimated the mean percentage change of energy, saturated fat, trans-fat, added sugars and sodium intake for the second, third and fourth scenarios. For that, first we estimated the intake differences of critical nutrients, we used the first scenario as reference and compared with the second, third and fourth scenarios, and then these differences were transformed into percentages. All statistical analyses were performed using Stata version 14 (College Station, TX, USA), and the SVY module was used to adjust the complex sampling design of ENSANUT 2016.

Results

Baseline sociodemographic characteristics of participants are described in Table 3. Most of the participants were adults (60.3%), women (51.4%), from the urban area (74.9%), south region (36.1%) and the high socioeconomic level (48.3%).

Table 3 Sociodemographic population characteristics. National Survey of Health and Nutrition (ENSANUT) 2016, Mexico (n = 4184)
Full size table

Concerning food and beverages FOPWL evaluation, 1527 unique products were reported in the 24-h recalls, 27.5% (n = 420) of which were processed products and candidates to be evaluated by the NOM-051. The number of WL by norm scenarios represented in percentage are shown in Fig. 1. According to the criteria of the norm, in the second scenario, 12.1% of the food products would not bear a WL, this percentage decreased gradually across phases until 6.4% in the fourth scenario. The products that would have only one label decreased between scenarios (from 25.5 to 19.8%); thus, the products that would declare 2, 3 and 4 labels increased between the second and the fourth scenarios from 31 to 34.8%, 28.3 to 33.3% and 3.1 to 5.7%, respectively. In this study, none of the products would declare WL for all the critical nutrients.

Fig. 1
figure 1

Percentage of warning labels in processed food by scenarios according to the criteria of the front-of-pack warning label (FOPWL) regulation, NOM-051. Mexico 2019

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During the second scenario, the most labeled nutrient was energy (52.6%) and in the third (56.4%) and fourth scenarios was sodium (61.2%), while trans-fat was the least, from 2.4 to 4.1% in the second and fourth phases, respectively. The WL for saturated fat (32.4%) and added sugars (2.4%) did not change between the second and third scenarios of the norm only in scenario 4 (Fig. 2). Regarding the replacement of food and beverages according to the FOPWL regulation, among the products consumed by the Mexican population, the replacement of the products increased across the scenarios in 55.9%, 57.6% and 82% in the second (first phase of the norm), third (second phase of the norm), and fourth scenarios (third phase of the norm), respectively.

Fig. 2
figure 2

Percentage of warning labels by critical nutrient in processed food according to the criteria of the front-of-pack warning label (FOPWL) regulation, NOM-051. Mexico 2019

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Mean intakes of energy, saturated fat, trans-fat, added sugars and sodium before and after the replacement of food according to the FOPWL criteria for all the population are presented in Table 4. We observed changes in the critical nutrients consumption after the replacement. In general, for all the Mexican population, we found an important decrease in the critical nutrients intake when we replaced food according to the FOPWL criteria during the second, third and fourth scenarios. When we stratified the critical nutrient intake by socioeconomic characteristics, we observed the same behavior (See Additional file 2: Table 2).

Table 4 Critical nutrient intake before and after the replacement with FOPWL criteria in the Mexican population. Mexico, ENSANUT 2016
Full size table

The mean percentage change of energy, saturated fat, trans-fat, added sugars and sodium intake during the second, third and fourth scenarios was estimated in Fig. 3. During the second and third scenarios, we observed a small or a constant reduction in the consumption for all the critical nutrients across the scenarios. In contrast, in the fourth scenario, we observed the most important reduction for energy (− 15.4%, CI95% − 14.5; − 16.3), saturated fat (− 20%, CI95% − 18.4; − 21.6), sodium (− 12.7%, CI95% − 11.3; − 14.1) and trans-fat intake (− 8.2%, CI 95% − 6.4; − 10.1). Among the nutrients in this scenario, the most important reduction was for added sugars intake (− 54.1%, CI 95% − 51; − 57.1).

Fig. 3
figure 3

Percentage change in the mean intake of energy, saturated fat, trans-fat, sodium and added sugars after the replacement with FOPWL criteria in all the Mexican population. Mexico, ENSANUT 2016. *Comparison: Scenario 1 versus Scenario 2; Scenario 1 versus Scenario 3 and Scenario 1 versus Scenario 4

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Discussion

In this study, we evaluate the hypothetical impact of the FOPWL regulation, and we observed a reduction of energy, saturated fat, trans-fat, added sugars and sodium intake, after a simulated replacement of commonly consumed foods in the Mexican diet, with products that would have less WL according to the FOPWL criteria in all the population and by socioeconomics characteristics across the three phases of the norm. The most important reduction was observed for added sugars intake. To our knowledge, this is the first study in Mexico to evaluate through food and beverage replacement the potential impact of the FOPWL norm under the assumption that consumers would replace consumed products with those with a fewer WL or with non-processed food.

The results in these analyses are consistent with similar studies. In a previous study also in Mexico [32], processed food was replaced with food that complied with the Mexican Committee of Nutrition Experts (based on the dietary intake recommendations from the World Health Organization) and Federal Commission for the Protection against Sanitary Risks Nutrition Criteria (based on the cutoff points established by the food and beverage industry) and then compared with the baseline consumption [32]. Similar to our study, a reduction was seen for energy (− 5.4%), saturated fat (− 18.9%), trans-fat (− 20%), total sugar (− 36.8%) and sodium (− 10.7%) intake [32]. The criteria for evaluating critical nutrients were different from the FOPWL used for this analysis, hence the differences in reductions. Besides, an increase in fiber intake was shown; however, we did not evaluate fiber and micronutrients intake since our focus was in the assessment on the critical nutrients that FOWPL regulation involved. However, it would be likely that in our replacement simulation, fiber would also increase since we increased the consumption of foods rich in dietary fiber during the replacement.

In this study, the greatest reduction was observed for added sugars in all the population and by socioeconomic characteristics. A possible explanation is the high intake of sugar-sweetened beverages in the Mexican population. In 2012, added sugars consumption represented 12.5% of total energy and 70% of them came from sugar-sweetened beverages [33]. Due to the high intake, Mexico is the first in the ranking of mortality and morbidity attributable to these beverages [34, 35]. Further, in a recent national survey ENSANUT 2018, adults (85.8%), adolescents (85.7%), school-aged children (85.7%), preschool-aged children (83.3%) reported an important consumption of these beverages [36], despite the efforts to discourage their consumption in the last years.

The impact of Chile’s Law of Food Labeling and Advertising which includes the FOPWL was evaluated on household beverage purchases [16]. Using fixed-effects models they compared the observed volume and calorie sugar content in beverage purchases after the regulation, with a counterfactual based on pre-regulation trends. The volume of high-in beverage purchases decreased by 22.8 ml/capita/day (95% CI − 22.9 to − 22.7; p < 0.001) or 27% after the regulation was implemented. Nonetheless, it is not certain whether the observed changes were due to reformulation or a real change in consumer behavior.

In the Netherlands, in young adults (aged 19–30 years), a substitution of current food intake with those that complied with the Choices Program (an international nutrient profiling system to determine whether foods are eligible to carry a healthier option label) was conducted [37]. After the replacement, they observed that median energy intake was reduced by 16% as well as for nutrients with a maximal intake limit (from 23 for sodium to 62% for trans-fat). Contrary to our study, they showed a greater reduction in trans-fat intake in relation to other nutrients. This may be explained because of the differences in dietary patterns or higher content of this nutrient in Dutch-processed food. Besides, in this study, the trans-fat intake could underestimate since the labeling regulation in force in 2016 presented some deficiencies that allowed to declare 0 g of trans-fats when they were below 0.5 g per portion.

Furthermore, during the third scenario, the cutoff points for trans-fat and saturated fat did not change; if the cutoff points for them would be stricter in the last phase of the norm, there would be more products to replace hence we could observe a greater reduction in these nutrients. Moreover, the trans-fats intake might be already conditioned by other efforts such as the Action Plan to eliminate industrially produced trans fatty acids 2020–2025 and the Replace initiative from the World Health Organization (WHO), where the elimination of trans-fats in industrial food processes is proposed [38]. However, we expect that the reductions shown for all the nutrients in this study will be more important since the food industry will have the opportunity to modify the nutritional content of their products according to the cutoff points of the norm. Thus, even if consumers did not change their dietary choices, in expectation they would consume less amount of energy, saturated fat, trans-fat, added sugars and sodium from the newly reformulated products.

The Mexican Government has implemented different strategies to enhance the dietary quality of the population, such as taxes on junk food and sugary beverages, banning the sale of processed foods and sugary beverages in schools, establishing restrictions for advertising directed to children, implementing physical activity programs and bike lanes in the community, and making public water fountains more available [39,40,41,42,43]. Unlike previous measures, the FOPWL regulation has the advantage that can be monitored and enforced and have the possibility to change the cultural norms that regulate consumer demand, thus food supply over time [18].

Our assumption regarding product substitution is in line with existing empirical results in Chile. Specifically, evidence from Chile shows that WL mainly encourage product substitution within the same food category [44]. Moreover, some studies provide evidence of the underlying mechanisms behind the purchase adjustments after the WL implementation in Chile, accounting for the simultaneous response to this policy by consumers and producers. For example, Barahona et al., in the case of breakfast cereals in Chile, showed product substitution between labeled and unlabeled cereals due to the interplay between updates in healthfulness beliefs by consumers because of the information conveyed by WL and price adjustments by producers in response to the cost linked to product reformulation [45]. Meanwhile, Pachali et al. found, likewise for breakfast cereals in Chile, that reductions in the nutrients of concern resulted from consumers substituting labeled for unlabeled cereals [46]. Moreover, Pachali et al. showed this substitution was reinforced by a price decrease across unlabeled cereals [46]. The authors pointed out that this price decrease was a producers’ response to the new composition of consumers demanding unlabeled cereals that were more price-sensitive than previous consumers before the WL implementation [46]. However, it is worth noting that the expected WL effect is likely to be food group specific in light of the findings by Araya et al., who showed no clear change in purchases of chocolates and cookies in Chile [47]. Evidence in Mexico in the context of the sugar-sweetened-beverage tax showed that sugar content is a demand driver, aside from prices and products’ brand, so consumers are likely to decrease their demand when producers reformulate their products in case this reformulation leads to a sweetness reduction (i.e., sugar reduction with no substitution for non-nutritive sweeteners) [48]. Thus, if WL encouraged reformulation in Mexico, consumers would likely adjust their demand downwards, at least for sugar-sweetened beverages. Finally, aside from reformulation, producers might respond to WL by removing/launching products. However, evidence from South Africa shows that this update in producers’ product portfolios has a minor contribution to the overall purchase changes linked to sugar-density taxes on sugar-sweetened beverages, which encourage reformulation as WL does [49]. In light of all these results, we consider our product substitution assumption consistent with existing evidence. However, we acknowledge our estimate could be conservative by overlooking producers' response to WL (i.e., reformulation and price adjustments) and how consumers react to this response. When the FOPWL regulation would be finished, there will be more food products options, thus more variability to select food products for the replacement; unfortunately, this was not possible due to the scope of this work and the phase of the FOPWL regulation.

Previous studies have proved that modeling is useful to accurately estimate the nutrient intakes when processed food is replaced using healthier alternatives [26,27,28]. These studies are frequently used to anticipate dietary changes before they are implemented in populations like in Mexico. Thus, the data could be turned into nutrition policies and help decision-makers to design policies based in evidence that would help to decrease diet and non-communicable diseases.

Healthy foods are often unaffordable or unavailable, the increase in urbanization causes population to change their dietary habits, to move away from producing and cooking their own food to prepared foods (high in sugar, salt and fat) [50]. Besides, marketing influences food choices, and unhealthy foods are an important target, especially among children [51]. Therefore, legislation and policies should focus on regulating prices, production, processing and distribution to make healthy foods more accessible as well as to restrict marketing to reduce the promotion of unhealthy food. FOPWL regulation is an important strategy to help population to identify unhealthy food in a simple way [52], along with public health interventions that can emphasize the importance of balanced diets on maintaining good health. The community health programs can educate children, parents, teachers and community leaders about the impact of their nutrition choices on health [53, 54].

Furthermore, through this simulation, we can estimate the potential impact of the FOPWL explained uniquely by change in consumer’s behavior. In Mexico, when the implementation of the regulation is completed, it will be difficult to determine if intake changes are because of consumer’s behavior, product reformulation, changes in marketing, other policies or the interaction of all of them.

This study presented some limitations. First, it is uncertain if the Mexican population will replace products with less WL or with non-processed products. This is possible since the population choices and intakes are determined by an array of factors, and not only on the presence or absence of WL [55]. Moreover, ENSANUT 2016 is a cross-sectional observational dataset; for this analysis, we used self-reported intake data which may be affected by measurement error. Further research is necessary to know if this error is randomly distributed through the different subgroups or whether it affects systematically certain subpopulations. However, in the Mexican population, this database is the most comprehensive nationally representative data to study dietary intake. Another limitation may be the availability of products presented in 2017 from the INFORMAS dataset [31]. Further, despite the results observed, we were confronted an important limitation to replace sugar-sweetened beverages, which was the low variability of the number of warning labels in this group of drinks between 0 and 2 WL. During the second and third scenarios, the replacement was using the same drink; thus, the reduction would be greater in the third scenario if more options were available. Finally, our results will need to be corroborated by future observational studies when the implementation of the regulation will be finished.

Conclusion

In this study, we showed that the FOPWL could be an effective strategy to decrease the consumption of added sugars, trans-fat, saturated fat added sugars and sodium intake if replacement of products is done by the population. The use of FOPWL would lead to an important change in critical nutrients intake previously associated with cardio metabolic diseases, and this is particularly important in Mexico considering the high rates of overweight and obesity and the complication of these diseases. It is important to promote the use of warning labels to discourage the use of processed food intake. However, this must go with nutritional education to raise awareness of the implications of a good diet in the population. Besides, food environment, food system, and nutritional education strategies should encourage the intake of non-processed food or minimally processed food.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due to the request of the funder. The funder has requested to safeguard the information for five years.

Abbreviations

FOPWL:

Front-of-pack warning labels

NOM-051:

Mexican Official Standard 051

CI 95%:

Confidence intervals

NCDs:

Non-communicable diseases

PAHO:

Pan American Health Organization

WL:

Warning labels

ENSANUT 2016:

The National Health and Nutrition Survey of 2016, Spanish acronym

INSP:

The National Institute of Public Health, Spanish acronym

References

  1. GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1345–422. https://doi.org/10.1016/S0140-6736(17)32366-8.

    Article  Google Scholar 

  2. Benziger CP, Roth GA, Moran AE. The global burden of disease study and the preventable burden of NCD. Glob Heart. 2016;11(4):393–7.

    Article  PubMed  Google Scholar 

  3. Collaborators GBDD. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72.

    Article  Google Scholar 

  4. INEGI INSP, de Salud S. Encuesta Nacional de Salud y Nutrición 2018: presentación de resultados. Mexico City (Mexico): INEGI. 2019. https://www.inegi.org.mx/contenidos/programas/ensanut/2018/doc/ensanut_2018_presentacion_resultados.pdf. Accessed 10 Jun 2020

  5. Pan American Health Organization. Nutrient Profile Model [Internet]. Washington, DC; 2016 [cited 2023 Sep 29]. p. 6. Available from: http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/publications/2015/who-regional-office-for-europe-nutrient-profile-model-2015.

  6. Monteiro CA, Cannon G, Moubarac JC, Levy RB, Louzada MLC, Jaime PC. The UN decade of nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr. 2018;21(1):5–17.

    Article  PubMed  Google Scholar 

  7. Marrón-Ponce JA, Flores M, Cediel G, Monteiro CA, Batis C. Associations between consumption of ultra-processed foods and intake of nutrients related to chronic non-communicable diseases in Mexico. J Acad Nutr Diet. 2019. https://doi.org/10.1016/j.jand.2019.04.020.

    Article  PubMed  Google Scholar 

  8. Popkin BM. Nutrition, agriculture and the global food system in low and middle income countries. Food Policy. 2014;47(91):6.

    Google Scholar 

  9. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012;70(1):3–21.

    Article  PubMed  Google Scholar 

  10. Pan American Health Organization (PAHO). Ultra-processed food and drink products in Latin America: trends, impact on obesity, policy implications. PAHO; Washington, DC; 2015.

  11. Marron-Ponce JA, Tolentino-Mayo L, Hernandez FM, Batis C. Trends in ultra-processed food purchases from 1984 to 2016 in Mexican households. Nutrients. 2018;11(1):45.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kleinert S, Horton R. Rethinking and reframing obesity. Lancet. 2015;385(9985):2326–8.

    Article  PubMed  Google Scholar 

  13. Lobstein T, Jackson-Leach R, Moodie ML, Hall KD, Gortmaker SL, Swinburn BA, et al. Child and adolescent obesity: part of a bigger picture. Lancet. 2015;385(9986):2510–20.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Organisation for Economic Co-operation and Development. Promoting sustainable consumption. Good practices in OECD countries. [monografía en internet]. Paris: OECD Publications, 2008 [citado mar 2022]. Disponible en: https://www.oecd.org/greengrowth/40317373.pdf.

  15. Organización Panamericana de la Salud, Organización Mundial de la Salud. Modelo de perfil de nutrientes de la Organización Panamericana de la Salud [monografía en internet]. Washington, DC: OPS. 2016. [citado mar 2022 Disponible en: http://iris.paho.org/xmlui/bitstream/handle/123456789/18622/9789275318737_spa.pdf.

  16. Taillie LS, Reyes M, Colchero MA, Popkin BM, Corvalán C. An evaluation of Chile’s law of food labeling and advertising on sugar-sweetened beverage purchases from 2015 to 2017: a before-and-after study. PLoS Med. 2020;17(2):e1003015.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Secretaría de Salud. Modificación de la Norma Oficial Mexicana NOM-051-SCFI/SSA1–2010. Especificaciones generales de etiquetado para alimentos y bebidas no alcohólicas preenvasados-Información comercial y sanitaria, publicada el 5 de abril de 2010. Se adicionan los incisos 3.2; 3.5; 3.17; 3.18; 3.21; 3.40; 4.2.9 con sus subincisos y se ajusta la numeración subsecuente; 4.5 con sus subincisos y el Apéndice Normativo A. Ciudad de México: Diario Oficial de la Federación; 2014.

  18. White M, Barquera S. Mexico adopts food warning labels, why now? Health Syst Reform. 2020;6(1):e1752063.

    Article  PubMed  Google Scholar 

  19. Correa T, Fierro C, Reyes M, Dillman Carpentier FR, Taillie LS, Corvalan C. Responses to the Chilean law of food labeling and advertising: exploring knowledge, perceptions and behaviors of mothers of young children. Int J Behav Nutr Phys Act. 2019;16(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Freire WB, Waters WF, Rivas-Marino G, Nguyen T, Rivas P. A qualitative study of consumer perceptions and use of traffic light food labelling in Ecuador. Public Health Nutr. 2017;20(5):805–13.

    Article  PubMed  Google Scholar 

  21. Reyes M, Garmendia ML, Olivares S, Aqueveque C, Zacarias I, Corvalan C. Development of the Chilean front-of-package food warning label. BMC Public Health. 2019;19(1):906.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Khandpur N, de Morais SP, Mais LA, Bortoletto Martins AP, Spinillo CG, Garcia MT, et al. Are front-of-package warning labels more effective at communicating nutrition information than traffic-light labels? A randomized controlled experiment in a Brazilian Sample. Nutrients. 2018;10(6):688.

    Article  PubMed  PubMed Central  Google Scholar 

  23. de Morais SP, Mais LA, Khandpur N, Ulian MD, Bortoletto Martins AP, Garcia MT, et al. Consumers’ opinions on warning labels on food packages: a qualitative study in Brazil. PLoS ONE. 2019;14(6):e0218813.

    Article  Google Scholar 

  24. Cabrera M, Machin L, Arrua A, Antunez L, Curutchet MR, Gimenez A, et al. Nutrition warnings as front-of-pack labels: influence of design features on healthfulness perception and attentional capture. Public Health Nutr. 2017;20(18):3360–71.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Arrua A, Machin L, Curutchet MR, Martinez J, Antunez L, Alcaire F, et al. Warnings as a directive front-of-pack nutrition labelling scheme: comparison with the guideline daily amount and traffic-light systems. Public Health Nutr. 2017;20(13):2308–17.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Schickenberg B, van Assema P, Brug J, Verkaik-Kloosterman J, Ocke MC, de Vries NK. Replacing foods high in saturated fat by low-saturated fat alternatives: a computer simulation of the potential effects on reduction of saturated fat consumption. Br J Nutr. 2009;102(3):478–83.

    Article  PubMed  Google Scholar 

  27. Thomson JL, Tussing-Humphreys LM, Onufrak SJ, Zoellner JM, Connell CL, Bogle ML, et al. A simulation study of the potential effects of healthy food and beverage substitutions on diet quality and total energy intake in lower Mississippi delta adults. J Nutr. 2011;141(12):2191–7.

    Article  CAS  PubMed  Google Scholar 

  28. Verger EO, Holmes BA, Huneau JF, Mariotti F. Simple changes within dietary subgroups can rapidly improve the nutrient adequacy of the diet of French adults. J Nutr. 2014;144(6):929–36.

    Article  CAS  PubMed  Google Scholar 

  29. Romero-Martinez M, Shamah-Levy T, Cuevas-Nasu L, Gomez-Humaran IM, Gaona-Pineda EB, Gomez-Acosta LM, et al. Methodological design of the National Health and Nutrition Survey 2016. Salud Publica Mex. 2017;59(3):299–305.

    PubMed  Google Scholar 

  30. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr. 2003;77(5):1171–8.

    Article  CAS  PubMed  Google Scholar 

  31. Tolentino-Mayo L, Rincón-Gallardo S, Bahena-Espina L, Ríos V, Barquera S. Knowledge and use of nutrient labelling of industrialized foods and beverages in Mexico. Salud Publica Mex. 2018;60(3):328–37.

    Article  PubMed  Google Scholar 

  32. Mendoza R, Tolentino-Mayo L, Hernandez-Barrera L, Nieto C, Monterrubio-Flores EA, Barquera S. Modifications in the consumption of energy, sugar, and saturated fat among the Mexican adult population: simulation of the effect when replacing processed foods that comply with a front of package labeling system. Nutrients. 2018;10(1):101.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Sanchez-Pimienta TG, Batis C, Lutter CK, Rivera JA. Sugar-sweetened beverages are the main sources of added sugar intake in the Mexican population. J Nutr. 2016;146(9):1888S-S1896.

    Article  CAS  PubMed  Google Scholar 

  34. Singh GM, Micha R, Khatibzadeh S, Lim S, Ezzati M, Mozaffarian D, et al. Estimated global, regional, and national disease burdens related to sugar-sweetened beverage consumption in 2010. Circulation. 2015;132(8):639–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Pan American Health Organization. Taxes on sugar-sweetened beverages as a public health strategy: the experience of Mexico. PAHO. 2015. https://iris.paho.org/xmlui/handle/123456789/18391.

  36. Shamah-Levy T, Vielma-Orozco E, Heredia-Hernández O, Romero-Martínez M, Mojica-Cuevas J, Cuevas-Nasu L, et al. Encuesta Nacional de Salud y Nutrición 2018–19: Resultados Nacionales. Salud Publica Mex. 2020;62(6):917–23.

    Article  Google Scholar 

  37. Roodenburg AJ, van Ballegooijen AJ, Dotsch-Klerk M, van der Voet H, Seidell JC. Modelling of usual nutrient intakes: potential impact of the choices programme on nutrient intakes in young Dutch adults. PLoS ONE. 2013;8(8):e72378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Organización Mundial de la Salud. Plan de acción para eliminar los ácidos grasos trans de producción industrial 2020–2025. 2020 [Internet]. [consultado abril del 2022]. Puede encontrarse en: https://iris.paho.org/handle/10665.2/52231.

  39. Cecchini M, Sassi F, Lauer JA, Lee YY, Guajardo-Barron V, Chisholm D. Tackling of unhealthy diets, physical inactivity, and obesity: health effects and cost-effectiveness. Lancet. 2010;376(9754):1775–84.

    Article  PubMed  Google Scholar 

  40. Rayner M, Wood A, Lawrence M, Mhurchu CN, Albert J, Barquera S, et al. Monitoring the health-related labelling of foods and non-alcoholic beverages in retail settings. Obes Rev. 2013;14(supl 1):70–81.

    Article  PubMed  Google Scholar 

  41. Batis C, Pedraza LS, Sanchez-Pimienta TG, Aburto TC, Rivera-Dommarco JA. Energy, added sugar, and saturated fat contributions of taxed beverages and foods in Mexico. Salud Publica Mex. 2017;59(5):512–7.

    Article  PubMed  Google Scholar 

  42. Pratt M, Charvel-Orozco AS, Hernández-Ávila M, Reis RS, Sarmiento O. Obesity prevention lessons from Latin America. Prev Med. 2014;69(supl 1):120–2.

    Article  Google Scholar 

  43. Colchero MA, Zavala JA, Batis C, Shamah-Levy T, Rivera-Dommarco JA. Cambios en los precios de bebidas y alimentos con impuesto en áreas rurales y semirrurales de México. Salud Publica Mex. 2017;59(2):137–46.

    PubMed  Google Scholar 

  44. Barahona N, Otero C, Otero S, Kim J. On the design of food labeling policies; 2023.

  45. Barahona N, Otero C, Otero S. Equilibrium effects of food labeling policies. Econometrica. 2023;91:839–68.

    Article  Google Scholar 

  46. Pachali MJ, Kotschedoff MJW, van Lin A, Bronnenberg BJ, van Herpen E. How do nutritional warning labels affect prices? J Mark Res. 2023;60:92–109.

    Article  Google Scholar 

  47. Araya S, Elberg A, Noton C, Schwartz D. Identifying food labeling effects on consumer behavior. Mark Sci. 2022;41:982–1003.

    Article  Google Scholar 

  48. Salgado Hernández JC, Ng SW. Simulating international tax designs on sugar-sweetened beverages in Mexico. PLoS ONE. 2021;16:e0253748.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Bercholz M, Ng SW, Stacey N, Swart EC. Decomposing consumer and producer effects on sugar from beverage purchases after a sugar-based tax on beverages in South Africa. Econ Hum Biol. 2022;46:101136.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Baker P, Machado P, Santos T, Sievert K, Backholer K, Hadjikakou M, et al. Ultra-processed foods and the nutrition transition: global, regional and national trends, food systems transformations and political economy drivers. Obes Rev. 2020;21(12):e13126.

    Article  PubMed  Google Scholar 

  51. Sadeghirad B, Duhaney T, Motaghipisheh S, Campbell NR, Johnston BC. Influence of unhealthy food and beverage marketing on children’s dietary intake and preference: a systematic review and meta-analysis of randomized trials. Obes Rev. 2016;17(10):945–59.

    Article  CAS  PubMed  Google Scholar 

  52. Kelly B, Jewell J. Front-of-pack nutrition labelling in the European region: identifying what works for governments and consumers. Public Health Nutr. 2019;22(6):1125–8.

    Article  PubMed  PubMed Central  Google Scholar 

  53. World Health Organization. Tackling NCDs: ‘best buys’ and other recommended interventions for the prevention and control of noncommunicable diseases World Health Organization. 2017. https://apps.who.int/iris/handle/10665/259232

  54. World Heart Federation. Global dietary changes threaten health [Internet]. 2023. Available from: https://world-heart-federation.org/resource/global-dietary-changes-threaten-health/

  55. Batis C, Rodriguez-Ramirez S, Ariza AC, Rivera JA. Intakes of energy and discretionary food in mexico are associated with the context of eating: mealtime, activity, and place. J Nutr. 2016;146(9):1907S-S1915.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We would like to thank all the participants for taking part in this study.

Funding

This research is funded by Bloomberg Philantropies (Grant Number 43003). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. Center for Nutrition and Health Research, National Institute of Public Health, Avenida Universidad 655, Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico

    Paola Villaverde, Lizbeth Tolentino-Mayo, Carlos Cruz-Casarrubias, Juan C. Salgado, Tania C. Aburto & Simón Barquera

  2. National Council of Humanities, Science and Technology, Mexico. Av. de los Insurgentes Sur 1582, Crédito Constructor, Benito Juárez, 03940, Mexico City, CDMX, Mexico

    Juan C. Salgado

Authors
  1. Paola Villaverde
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  2. Lizbeth Tolentino-Mayo
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  3. Carlos Cruz-Casarrubias
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  4. Juan C. Salgado
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  5. Tania C. Aburto
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  6. Simón Barquera
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Contributions

LT-M formulated the research question and directed the research and had primary responsibility for the final content; PV conducted the research, analyzed the data, and drafted the paper; LT-M, CC-C, TCA, JCS and SB, critically revised the article. SB is responsible for the funding acquisition. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Lizbeth Tolentino-Mayo.

Ethics declarations

Ethics approval and consent to participate

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Ethics, Research and Biosafety Committee of the National Institute of Public Health (INSP-Spanish acronym). Written informed consent was obtained from all subjects/patients.

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The authors give the publisher the consent for the above manuscript entitled “Hypothetical impact of the Mexican front-of-pack labeling on dietary intake of critical nutrients and energy″ to be published in the Journal of Health, Population and Nutrition.

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Supplementary Information

Additional file 1: Table 1.

Categories of processed food according to NOVA classification.

Additional file 2: Table 2.

Critical nutrient intake before and after the replacement with FOPWL criteria by sociodemographic characteristics. Mexico, ENSANUT 2016.

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Villaverde, P., Tolentino-Mayo, L., Cruz-Casarrubias, C. et al. Hypothetical impact of the Mexican front-of-pack labeling on intake of critical nutrients and energy. J Health Popul Nutr 42, 124 (2023). https://doi.org/10.1186/s41043-023-00462-7

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Journal of Health, Population and Nutrition

ISSN: 2072-1315

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