高度に加工された食品は老化を早め、肥満を促進する

「超加工食品」を1日に3品以上食べる人は、そうした食品をめったに食べない人に比べて、染色体の末端部位にありDNAとタンパク質から成る「テロメア」が短くなる確率が2倍になる

スペイン・University of NavarraのMaria Bes-Rastrollo、Amelia Marti両教授が率いる研究チームは2008年に55歳以上でDNAサンプルを提供し、その後2年ごとに食生活に関する詳細なデータも提供した886人について調べた。この男性645人、女性241人を超加工食品の消費量に応じて、4グループに均等に分けた。

　このうち超加工食品の摂取が多いグループは、家族歴に心血管疾患、糖尿病、血中脂肪異常がみられる可能性がより高かった。一方、超加工食品の摂取が少ないグループは、繊維、オリーブオイル、果物、野菜やナッツ類の摂取が多い地中海食と関連付けられた。

　さらに超加工食品の摂取が最も少ないグループに対し、他の3グループが短いテロメアを持っている確率は、超加工食品の摂取量が多くなるにつれて29％、40％、82％と増えていった。

Ultra-processed food consumption and the risk of short telomeres in an elderly population of the Seguimiento Universidad de Navarra (SUN) Project

Lucia Alonso-Pedrero, Ana Ojeda-Rodríguez, Miguel A Martínez-González, Guillermo Zalba, Maira Bes-Rastrollo, Amelia Marti

The American Journal of Clinical Nutrition, Volume 111, Issue 6, June 2020, Pages 1259–1266, https://doi.org/10.1093/ajcn/nqaa075

Published: 24 April 2020

https://academic.oup.com/ajcn/article-abstract/111/6/1259/5824715

Abstract

Background

Telomere length (TL) is a marker of biological age that may be affected by dietary factors through oxidation and inflammation mechanisms. In addition, ultra-processed food (UPF) consumption has increased worldwide and it has been associated with the risk of developing several diseases.

Objectives

We aimed to evaluate the association between UPF consumption and the risk of having short telomeres in an elderly population of the Seguimiento Universidad de Navarra (SUN) Project.

Methods

This is a cross-sectional study of 886 participants (645 men and 241 women) aged 57–91 y recruited from the SUN Project (Spain, 1999–2018). TL was measured from saliva samples by real-time qPCR at baseline and UPF consumption was collected using a validated 136-item FFQ and classified according to the NOVA system. We evaluated the association between consumption of energy-adjusted UPF categorized into quartiles (low, medium-low, medium-high, and high consumption) and the risk of having short telomeres (<20th percentile) using logistic regression models.

Results

Those participants with the highest UPF consumption had almost twice the odds of having short telomeres compared with those with the lowest consumption (adjusted OR: 1.82; 95% CI: 1.05, 3.22; P-trend = 0.03).

Conclusions

A higher consumption of UPF (>3 servings/d) was associated with higher risk of having shorter telomeres in an elderly Spanish population of the SUN Project.

This trial was registered at clinicaltrials.gov as NCT02669602.

高度に加工された食品は肥満のリスクを上げる

（※　忙しいため、訳すのは省略しました。管理者記載）

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https://academic.oup.com/ajcn/article/104/5/1433/4564389?ijkey=e7d0521a242bf174775955850dd11b6e6aecce64&keytype2=tf_ipsecsha

Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study

Raquel de Deus Mendonça, Adriano Marçal Pimenta, Alfredo Gea, Carmen de la Fuente-Arrillaga, Miguel Angel Martinez-Gonzalez, Aline Cristine Souza Lopes, Maira Bes-Rastrollo

The American Journal of Clinical Nutrition, Volume 104, Issue 5, November 2016, Pages 1433–1440, https://doi.org/10.3945/ajcn.116.135004

Published: 12 October 2016

ABSTRACT

Background: Ultraprocessed food consumption has increased in the past decade. Evidence suggests a positive association between ultraprocessed food consumption and the incidence of overweight and obesity. However, few prospective studies to our knowledge have investigated this potential relation in adults.

Objective: We evaluated the association between ultraprocessed food consumption and the risk of overweight and obesity in a prospective Spanish cohort, the SUN (University of Navarra Follow-Up) study.

Design: We included 8451 middle-aged Spanish university graduates who were initially not overweight or obese and followed up for a median of 8.9 y. The consumption of ultraprocessed foods (defined as food and drink products ready to eat, drink, or heat and made predominantly or entirely from processed items extracted or refined from whole foods or synthesized in the laboratory) was assessed with the use of a validated semiquantitative 136-item food-frequency questionnaire. Cox proportional hazards models were used to estimate adjusted HRs and 95% CIs for incident overweight and obesity.

Results: A total of 1939 incident cases of overweight and obesity were identified during follow-up. After adjustment for potential confounders, participants in the highest quartile of ultraprocessed food consumption were at a higher risk of developing overweight or obesity (adjusted HR: 1.26; 95% CI: 1.10, 1.45; P-trend = 0.001) than those in the lowest quartile of consumption.

Conclusions: Ultraprocessed food consumption was associated with a higher risk of overweight and obesity in a prospective cohort of Spanish middle-aged adult university graduates. Further longitudinal studies are needed to confirm our results. This trial was registered at clinicaltrials.gov as NCT02669602.

INTRODUCTION

Obesity is a worldwide problem with increasing prevalence. In 2014, more than half a billion adults were obese, and 39% were overweight. In the Americas, ∼30% of women and 25% of men were obese, and in the Eastern Mediterranean ∼25% of women and 15% of men were obese (1).

Changes in the food system continuously promote obesity. There is now a greater availability of ready-to-eat or -heat foods known as ultraprocessed foods, which are products that have little, if any, whole foods and are manufactured with substances extracted from foods or synthesized in laboratories (dyes, flavorings, and other additives) (2). They have high amounts of fat, sugar, and salt and a high energy density and low fiber content; they are extremely palatable foods that are aggressively advertised (3) and contain a large diversity of chemical additives. Examples of ultraprocessed foods include breakfast cereals, reconstituted meat products, soft drinks, and ready-to-eat foodstuffs (2).

Several prospective studies have been carried out to assess the relation between dietary components and obesity. An analysis of 3 American cohorts, the Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-Up Study, showed that the consumption of foodstuffs such as sweets, desserts, processed meats, fries, and sugar-sweetened beverages were strongly associated with weight gain in US adults (4). However, the relation between the consumption of foods aggregated according to their degree of processing (i.e., ultraprocessed foods) and excess weight has only recently been analyzed.

A cross-sectional times series study in 15 Latin American countries revealed an association between sales of ultraprocessed foods and changes in body weight in 12 countries from 2000 to 2009 (5). Cross-sectional studies have demonstrated an association between the consumption of these foods and the risk of metabolic syndrome in adolescents (6) and obesity in adolescents and adults (7, 8). A study of children aged 3–8 y in a low-income community in Brazil showed that ultraprocessed food consumption was an important predictor of the increase in total cholesterol and LDL cholesterol (9). On the other hand, a study with data from the 2008–2012 United Kingdom National Diet and Nutrition Survey showed no association between ultraprocessed food consumption and body weight. However, diets with smaller quantities of ultraprocessed foods have better nutritional quality (10).

Studies have shown an association between specific types of ultraprocessed foods, such as soft drinks, and being overweight or obese. However, no prospective cohort study to our knowledge has been performed to evaluate the association between all ultraprocessed foods as a group and the incidence of overweight and obesity in adults. Therefore, in this study (NCT02669602), we evaluated the association of ultraprocessed food consumption with the incidence of overweight and obesity in a Mediterranean cohort with a prolonged follow-up.

METHODS

Study population

The SUN (University of Navarra Follow-Up) Project is a dynamic and multipurpose prospective cohort study with permanently open recruitment conducted in Spain among university graduates since December 1999. The participants are followed up biennially with the use of questionnaires distributed by post or electronic mail. Details of its design have been published elsewhere (11, 12).

Up to March 2012, the SUN data set included 21,291 participants who had answered the baseline questionnaire. In this study, we excluded those classified as overweight or obese [BMI (in kg/m2) ≥25] at baseline (n = 6340), individuals who reported total energy intake values outside of predefined limits [low: <3347 kJ/d or <800 kcal/d in men and <2092 kJ/d or <500 kcal/d in women; high: >16,736 kJ/d or >4000 kcal/d in men and >14,644 kJ/d or >3500 kcal/d in women (n = 1713)] (13), women who were pregnant at baseline or became pregnant during the follow-up period (n = 2739), and individuals who reported a previously diagnosed chronic disease at baseline (e.g., diabetes, cancer, cardiovascular disease) (n = 618). In addition, we excluded participants with a weight change >10 kg in the 5 y preceding entry into the study to reduce potential sources of confounding by other causes of weight changes (n = 260). Among the remaining participants, 1106 subjects were lost to follow-up, and 64 participants had missing values in ≥1 variable of interest. After these exclusions, a total of 8451 participants were included in the final analyses (Figure 1). The retention rate of the study was ∼89%.

FIGURE 1

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Flowchart of participants.

FIGURE 1

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Flowchart of participants.

This study was conducted according to Declaration of Helsinki guidelines, and all procedures involving human subjects were approved by the University of Navarra institutional review board. Voluntary completion of the baseline self-administrated questionnaire was considered to imply informed consent.

Exposure assessment: ultraprocessed food consumption

Dietary exposures were assessed at baseline through a self-administered 136-item semiquantitative food-frequency questionnaire (FFQ) that was previously validated in Spain (14, 15). Frequencies of consumption were measured in 9 categories (ranging from never or almost never to >6 servings/d), and the FFQ included a typical portion size for each item. Daily food consumption was estimated by multiplying the portion size by the consumption frequency for each food item.

The foods were classified according to NOVA (2) based on the extent and purpose of applied food processing. There are 4 groups in this classification scheme. The first group includes foods that are fresh or processed in ways that did not add substances such as salt, sugar, oils, or fats and infrequently contain additives. Processes used are aimed to extend life, allow storage for long use, and facilitate or diversify preparation (freezing, drying, and pasteurization). Examples are fruits and vegetables, grains (cereals), flours, nuts and seeds, fresh and pasteurized milk, natural yogurt with no added sugar or artificial sweeteners, meat and fish, tea, coffee, drinking water, spices, and herbs. The second group contains processed culinary ingredients. These are substances obtained from the first group or from nature and may contain additives to preserve the original properties. Examples are salt, sugar, honey, vegetable oils, butter, lard, and vinegar. The third group is processed food made with the addition of substances such as salt, sugar, or oil and the use of processes such as smoking, curing, or fermentation. Examples are canned or bottled vegetables and legumes, fruits in syrup, canned fish, cheeses, freshly made bread, and salted or sugared nuts and seeds. The fourth group is ultraprocessed food and drink products that are made predominantly or entirely from industrial substances and contain little or no whole foods. These products are ready to eat, drink, or heat. Examples include carbonated drinks, sausages, biscuits (cookies), candy (confectionery), fruit yogurts, instant packaged soups and noodles, sweet or savory packaged snacks, and sugared milk and fruit drinks (2). It is this fourth group that is the main subject of this study. Supplemental Table 1 describes the classification of FFQ foods according to NOVA. The frequency of ultraprocessed food consumption was estimated with the use of the sum of the food items from the fourth group in the FFQ (total of 33 items). The sample was divided into quartiles according to total consumption (servings/d).

Outcome assessment

Self-reported weight and height were validated with a previous study (16). The outcome used the incidence of overweight and obesity (BMI ≥25) during follow-up and was defined as the first time participants reached a BMI of 25 during follow-up.

Assessment of other variables

The baseline questionnaire also included questions relating to the following variables: sex, age, marital status, educational status, smoking status, physical activity, television watching, siesta sleep, diet and dietary habits, and snacking between main meals. Physical activity was evaluated with the use of a validated 17-item questionnaire (17). Total energy, macronutrient, fiber, and alcohol intake and fruit, vegetable, fast-food, fried-food, processed meat, nonprocessed meat, and sugar-sweetened beverage consumption was assessed with the use of the FFQ (15). Nutrient intake scores were computed with the use of a computer program developed specifically by our dietitians for this purpose. Adherence to the Mediterranean dietary pattern was evaluated with the use of a well-known score (18).

Statistical analyses

Differences in baseline characteristics of participants according to ultraprocessed food consumption quartiles were evaluated with ANOVA and adjusted for sex and age. To evaluate the relation between ultraprocessed food consumption at baseline and the subsequent risk of the development of overweight and obesity during follow-up, we used Cox proportional hazards models, and to estimate HRs and 95% CIs we used the lowest quartile as the reference category.

The follow-up period was defined as the interval between the date of recruitment and date of the return of the follow-up questionnaire in which the participant was classified as overweight or obese for the first time (for incident cases). The date of death or of the last questionnaire was used for noncases.

Tests for linear trends were conducted by assigning medians of ultraprocessed food consumption to each category and treating this variable as a continuous variable in the respective Cox regression model. We fitted a first model without any adjustment (crude), a second model adjusted for age and sex, and a third multivariable-adjusted model adjusted for age, sex, marital status, educational status, baseline BMI, physical activity, television watching, siesta sleep, smoking status, snacking between meals, and following a special diet. Total energy intake was not included as a covariate because it may plausibly mediate the association of ultraprocessed foods and overweight and obesity. We evaluated the interaction between exposure, sex, and BMI with the use of a likelihood ratio test that compared the fully adjusted Cox regression model and the same model with interaction product terms (3 df). Nelson-Aalen cumulative hazards estimates were plotted for overweight and obesity incidence according to ultraprocessed food consumption quartiles at baseline. We used inverse probability weighting to adjust the Nelson-Aalen curves for baseline potential confounders.

To test the proportional hazard assumption, we calculated a Cox regression with the exposure as a continuous time-varying covariate to check that the HR did not vary over time, obtaining a nonsignificant result, suggesting that the proportionality assumption was met. We also checked the proportionality of hazards model with the use of a Grambsch-Therneau test of the scaled Schoenfeld residuals from a Cox model on the 3 dummy variables of the upper ultraprocessed quartiles (19). The P value of the global test was 0.72.

To determine the contribution of each food item to the between-person variance in ultraprocessed food consumption (13), we constructed a series of nested least-squares linear regression models after stepwise-selection regression analyses. The additional contribution of a given food item was reflected in the change in the cumulative R2.

Sensitivity analyses were conducted by repeating the multivariable-adjusted Cox regression models with the following changes: 1) additional adjustment excluding fruit and vegetable consumption, 2) exclusion of those participants under the 5th percentile and over the 95th percentile of total energy intake, 3) additional adjustment for total energy intake, 4) additional adjustment for family history of obesity, 5) additional adjustment for weight gain >3 kg in the 5 y before entering the cohort, 6) exclusion of participants who were early incident cases of overweight (those who became overweight after only 2 y of follow-up), and 7) inclusion of subjects with prevalent chronic diseases.

All analyses were performed with Stata version 12.1 (StataCorp LP). P < 0.05 was considered significant.

RESULTS

A total of 2967 (35.1%) men and 5484 (64.9%) women were included in this analysis, and the mean ± SD age of the participants was 37.6 ± 11.0 y. The main baseline characteristics of participants according to quartiles of total ultraprocessed food consumption are presented in Table 1. Participants in the fourth quartile of ultraprocessed food consumption had the highest BMI, were more likely to be current smokers, watched more television, and had the highest total energy and fat intake and the lowest protein and total fiber than those in the first quartile. Moreover, on average, they consumed more fast food, fried foods, processed and other meats, and sugar-sweetened beverages. In contrast, they had the lowest intakes of vegetables and were less likely to follow special diets. In addition, they had the highest prevalence of snacking between main meals. In addition, the adherence to the Mediterranean diet score varied according to quartiles of ultraprocessed food (i.e., the higher the consumption of ultraprocessed foods, the less adherence to the Mediterranean diet).

TABLE 1

Baseline characteristics of participants according to their consumption of ultraprocessed foods1

1

All values are means ± SDs unless otherwise indicated. P values were adjusted for sex and age with the use of ANOVA. MET, metabolic equivalent; SUN, University of Navarra Follow-Up.

2

Sum of hamburgers, sausages, and pizza.

3

Sum of sausages, hamburgers, and ham.

TABLE 2

Main sources of ultraprocessed foods1

1

Cumulative R2 values were determined with the use of nested regression analyses after a stepwise selection.

2

Includes ham, sausages, chorizo, salami, mortadella, and hamburgers.

3

Includes biscuits and chocolate cookies.

4

Includes muffins, doughnuts, croissants or other pastries, and confectionery.

During the follow-up period (median: 8.9 y; person-years: 66,625), we observed 1939 incident cases of overweight and obesity. In the multivariate models, when we assessed the risk of overweight and obesity according to quartiles of ultraprocessed foods consumption (Table 3), participants with higher ultraprocessed food intake (highest quartile) presented a 26% relatively higher risk of developing overweight or obesity than those in the lowest quartile (HR: 1.26; 95% CI: 1.10, 1.45). The estimates showed a statistically significant linear trend (P = 0.001). The Nelson-Aalen curves exhibited a higher incidence of overweight and obesity with increasing baseline quartiles of ultraprocessed food intake (Figure 2). No significant interaction between sex or BMI and ultraprocessed food consumption was observed. Results in the sensitivity analyses described previously were not substantially changed in any of the scenarios (Table 4).

TABLE 3

Cox proportional HRs and 95% CIs for incident overweight and obesity according to baseline consumption of ultraprocessed foods1

Nelson-Aalen curves showing the outcome of new-onset overweight depending on ultraprocessed food consumption at baseline. Adjusted for sex, age, marital status, educational status, physical activity, television watching, siesta sleep, smoking status, snacking between meals, following a special diet at baseline, baseline BMI, and consumption of fruit and vegetables with the use of inverse probability weighting. Q, quartile.

DISCUSSION

In this prospective cohort study with initially healthy, middle-aged, Spanish adults, higher ultraprocessed food consumption was associated with an increased risk of overweight and obesity incidence for a mean of ∼9 y of follow-up, even after adjusting for potential confounding factors.

Recent ecological and cross-sectional studies on ultraprocessed food consumption and the risk of overweight and obesity have shown an association between increased ultraprocessed food consumption and obesity among adolescents and adults (5, 7, 8, 20). To our knowledge, this is the first prospective epidemiologic study to assess this association among adults.

The food and drinks classified as ultraprocessed foods are mostly manufactured by large and powerful transnational companies. These companies focus their marketing on the individual’s lack of time compared with the expediency, convenience, and accessibility of these products (21, 22). However, ultraprocessed foods tend to be nutritionally unbalanced and have a high energy content and amounts of fat, added or free sugar, sodium, and chemical additives in addition to being poor in micronutrients and fiber (3, 21, 23, 24). This nutritional composition is caused by several industrial processes, such as the removal of water, which increases the shelf life and reduces transportation costs but increases the energy density per portion. In addition, to confer greater stability, ultraprocessed foods have a greater amount of trans and saturated fats and synthetic additives (24). Ultraprocessed foods are also designed to be irresistible and to favor consumption (because of the use of salt, sugar, and fat but also because of marketing and other characteristics such as portion size and convenience), and the processing also affects food behavior and the capacity for self-control (2, 3). This new classification proposal of foods according to the degree of processing (2) therefore seems to be a good way of assessing their intake and relation to health outcomes because it can identify the consumption of a group of foods and drinks with low nutritional quality rather than just a certain food or nutrient.

The sales of ultraprocessed foods increased between 2000 and 2013. Despite the United States being the largest buyer, sales of these products in Spain grew 18.5%, followed by Canada, Germany, and Mexico (5). In a longitudinal study of food and beverage consumer packaged goods purchased by US households, the 2000–2012 Nielsen Homescan Panel showed that 61% of the energy in purchases by US households in 2012 was derived from ultraprocessed foods (25). The 2008–2012 United Kingdom National Diet and Nutrition Survey, a large national cross-sectional study of diet, showed that diets with a higher intake of minimally processed foods and lower intake of ultraprocessed foods are associated with a more healthy food profile, but this was not associated with body weight (10). Studies from Canada and Brazil, conducted with data from national household food budget surveys, have also demonstrated a direct association between ultraprocessed food consumption and a diet with a high energy density and intake of sugars, sodium, and total and saturated fats and an inverse association with fiber intake (3, 21). Moreover, a study from Brazil that examined data from a national household food budget survey showed that higher ultraprocessed food consumption was associated with the lowest intakes of vitamin B-12, vitamin D, niacin, iron, selenium, and magnesium (26).

We believe that ultraprocessed food consumption may increase the risk of overweight and obesity by increasing the total intake of calories, added and free sugars, and fats and providing an inadequate relation of nutrients potentially involved in the genesis of the accumulation of body fat (1, 3, 21,–24, 26). A cross-sectional study from the United States with data from NHANES 2009–2010 showed that ultraprocessed food represented 57.9% of energy intake and that ∼90% of this amount was derived from added sugars (23). The participants in our cohort with a higher daily consumption of ultraprocessed foods had a higher consumption of total calories and fat, a lower consumption of proteins and fibers, and a lower adherence to the Mediterranean dietary pattern.

The Nurses’ Health Study showed a strong association between the percentage of calories from saturated and trans fats and weight gain (27). Results from the Nurses’ Health Study II also showed that an increase in dietary energy density was a risk factor for obesity (28). A meta-analysis of cohort studies and randomized clinical trials has provided evidence of the relation between the intake of sugar and the development of overweight and obesity (29). On the other hand, the consumption of natural foods such as fruits, vegetables, fish, and fiber—but not red meat—is inversely associated with the incidence of overweight and obesity (4, 30).

Our findings stress the importance of promoting and enhancing healthy and sustainable food standards, which requires structural and behavioral changes. Food systems should improve the supply of healthy foods and foster healthier food choices (31). This may be accomplished by promoting and enhancing eating habits based on foods and cuisine, such as the Mediterranean dietary pattern. Several studies have demonstrated its association with the reduction of weight gain because it consists predominantly of fruits, vegetables, legumes, nuts, olive oil, and fish (17, 32). Therefore, the Mediterranean diet is based on the consumption of fresh foods; multiple studies have demonstrated its preventive effect against chronic diseases (32,–35).

Some limitations may be observed in this study. The assessment of ultraprocessed food consumption was performed with the use of an FFQ that was not specifically designed to collect data regarding this new classification of foods. Therefore, there is the potential for some degree of misclassification of ultraprocessed food consumption inherent in our methodology. However, our FFQ was previously validated and represents the main foods ingested by the studied population (15), including ultraprocessed foods. Hamburgers are classified as an ultraprocessed food according to NOVA (2). Hamburgers are not ground beef but are a dish made of industrial breads, sauces, reconstituted meat, processed cheese, bacon, etc. Therefore, we included hamburgers in the ultraprocessed food group. Some hamburgers can be homemade, and doubts may arise about their inclusion in this group. Unfortunately, our study could not differentiate between fast-food and homemade hamburgers. Even when we removed hamburgers from the ultraprocessed foods, the results were only slightly attenuated (HR: 1.23; 95% CI: 1.07, 1.41; P-trend = 0.003).

Self-reported data were used to evaluate the BMI and to classify the overweight and obesity incident cases. This may not be precise enough, especially because we cannot accurately specify the date of onset of the overweight or obese status. Nevertheless, this method was previously validated (16). In addition, the participants were health professionals, and this fact is likely to have increased the validity of their self-reported anthropometric data.

Potential confounding may still be possible. Nevertheless, we adjusted for several potential confounding factors related to lifestyle. Caution is needed in extrapolating the results to the general population because the SUN participants are volunteer university graduates. This group could be more aware of health, thus causing a selection bias that implies that the magnitude of the risk between ultraprocessed food consumption and excess weight may be even greater in the general population. Conversely, the participants have a higher educational status and are capable of providing better quality self-reported data, thus reducing the potential for misclassification bias. Nevertheless, we must be cautious with regard to the generalization of the results because they do not depend on the statistical representativeness of the sample but on the biological mechanisms underlying the observed association.

The main strengths of this study are its prospective design, the use of validated methods (15, 16), the relatively large sample size, and the long follow-up period. In addition, this is one of the first longitudinal studies to our knowledge to evaluate the relation between ultraprocessed food intake and overweight and obesity. Further studies should be performed to investigate whether there is a relation between increased ultraprocessed food intake and major causes of death, such as cardiovascular diseases and cancer.

The results suggest that increased ultraprocessed food consumption is associated with a greater risk of overweight and obesity. Strategies for reducing the consumption of this group of foods, such as the maintenance of a traditional food culture and strengthening of the Mediterranean diet, should be encouraged as preventive approaches for obesity. However, further longitudinal studies in different contexts are necessary to confirm our findings.

The authors’ responsibilities were as follows—RdDM, ACSL, and MB-R: analyzed the data and drafted the manuscript; MB-R: obtained the funding and designed the study; AMP, AG, and CdlF-A: helped to design the study and interpreted the data; MAM-G: helped to design the study and was the founder of the SUN project; and all authors: read and approved the final manuscript. None of the authors reported a conflict of interest related to the study.