Sustainable-psycho-nutritional Intervention Program and Its Effects on Health Outcomes and the Environment

Sustainable-psycho-nutritional Intervention Program and Its Effects on Water and Carbon Footprint, Metabolic Biomarkers, and Gut Microbiota in Mexican Population: a m-Health Randomized Clinical Trial

Mexico is going through a major environmental and nutritional crisis, which is related to unsustainable dietary behaviors. Sustainable diets could solve both problems together. However, in Mexico and the world, an intervention program oriented to promoting sustainable diets has not been designed. This study protocol aims to design a 3-stages, 15 weeks, sustainable-psycho-nutritional digital intervention program whose objective is to promote the adherence of the Mexican population to a sustainable diet and to evaluate its effects on dietary water and carbon footprints, metabolic biomarkers, and gut microbiota of this population. The behavior change wheel model and the guide for digital interventions design will be followed. In stage 1, the program will be designed using the sustainable diets model, and the behavior change wheel model. A sustainable food guide, sustainable recipes, and food plans as well as a mobile application will be developed. In stage 2, the intervention will be carried out for 7 weeks, and a follow-up period of 7 weeks, in a sample of Mexican young adults (18 to 35 years) randomly divided into an experimental group (n=50) and a control group (n=50). The nutritional care process model will be used. Anthropometric, biochemical, clinical, dietary, environmental, socioeconomic level and cultural aspects, nutritional-sustainable knowledge, behavioral aspects, and physical activity will be considered. Thirteen behavioral objectives will be included using successive approaches in online workshops twice a week. The population will be monitored using the mobile application that will include behavioral change techniques. In stage 3, the effects of the intervention will be assessed on the dietary water and carbon footprint, lipid profile, serum glucose, and gut microbiota composition of the evaluated population. It is expected to find improvements in health outcomes and a decrease in dietary water and carbon footprints. With this study, the first theoretical-methodological approach to the sustainable-psycho-nutrition approach will be generated.

Study Overview

• Status: Active, not recruiting
• Conditions: Hyperglycemia; Physical Activity; Body Composition; Blood Pressure; Hypercholesterolemia; Hypertriglyceridemia; Gut Microbiota; HDLC; Eating Behavior; Acanthosis Nigricans; Food Intake; Diet Quality
• Intervention / Treatment: Behavioral: Sustainable diet promotion through behavioral change intervention

Detailed Description

1. Introduction:

   The change from the traditional Mexican diet to a Western diet, generated by the nutritional transition, has not only generated a prevalence of more than 75% of metabolic alterations (obesity, type 2 diabetes, cardiovascular diseases, dyslipidemia) and in the gut microbiota of the Mexican population, but it has also generated the water and carbon footprint of their diet to be the highest in the world with more than 8,000 Liters per person per day (L p-1d-1) and 6.01 Kg CO2eq p-1d-1, respectively. This is linked to the aggravation of climate change, with increases of more than 1.0 ºC in the average atmospheric temperatures and the current water crisis that Mexico is going through, which affects 85% of the territory and has been referred to as the worst water drought in history, affecting the water supply of millions of Mexicans.

   One of the proposals for the joint solution of these problems has been the adoption of sustainable and territorial diets, which in Mexico could be carried out through the recovery of its traditional diet, both pre-Hispanic and colonized, which, prepared with low-fat culinary techniques and low content of animal products, can be considered as an appropriate option from a nutritional, cultural, economic and environmental perspective, dimensions that must be present for a diet to be considered as sustainable.

   However, to achieve the adoption of a particular diet, it is necessary to modify the eating behavior of the population. To modify both dietary and unsustainable behaviors in a population, there are multiple strategies, among which intervention programs have stood out. However, to date and both nationally and internationally, no intervention program whose objective is to promote both adequate nutrition to improve health and reduce the environmental impact of dietary behaviors, has been reported. This respecting cultural, social, economic, and psychological aspects of the population.

   Based on the above, this study protocol aims to design a three-stage 15 weeks intervention program, based on the guide to designing interventions of the behavior change wheel model, which includes both nutritional and sustainability elements, in the sense of considering unsustainable dietary behaviors of the Mexican population, in addition to taking into account their social, cultural and economic aspects. In addition to these axes, the basis of behavioral modification intervention programs is psychology. Therefore, it is proposed to design a sustainable-psycho-nutritional intervention program, whose objective is to promote the adherence of the population to sustainable diets. But, in addition, it is proposed to evaluate its effects on environmental indicators, metabolic biomarkers, and gut microbiota, as well as clinical aspects and body composition in a Mexican population sample. Because of the effectiveness of technologies use in nutritional and environmental interventions, the intervention program will be a digital one, for which a mobile application is being designed to evaluate and monitor the intervened population. Therefore, this will be a m-Health intervention program.

   One of the hypotheses of the work is that a sustainable-psycho-nutritional intervention digital program can modify the eating behavior of a Mexican population group and guide it towards a sustainable diet, generating decreases in glucose levels, total cholesterol (TC), LDL cholesterol (LDL-C), and triglycerides (TG), and increases in HDL cholesterol (HDL-C) levels. Likewise, another hypothesis is that this type of program can modify the composition of the gut microbiota of the population, promoting the proliferation of bacteria related to metabolic health; reduce the water and carbon footprint of the sample's diets; maintain adequate body fat levels in the population with an adequate body fat percentage or reduce them in the overweight or obese population; maintain blood pressure levels in the healthy population and lower them in the population with high blood pressure, and reduce the presence of acanthosis nigricans.

2. Methods:

It is proposed to carry out a quasi-experimental longitudinal study of three stages that will be related to each other.

2.1 Stage 1: Design of the program: A sustainable-psycho-nutritional intervention program will be designed based on the characteristics of a sustainable diet for the national context of Mexico, adaptable to any regional context. It will include a mobile application that is being designed for this project, which will include a sustainable food guide, sustainable-psycho-nutritional workshops, sustainable recipes and food plans, and behavioral change techniques. The program will be designed based on the sustainable diets model and concept, the behavior change wheel model, the guideline for the development and evaluation of digital behavioral interventions in health care, and the guide to designing interventions of the behavior change wheel, which incorporate 3 stages and 8 development steps.

2.1.1 Mobile application design: A mobile application (app) will be developed in collaboration with software and mobile applications developers and will be based on the user-centered methodology, and the guide for the design of digital interventions. It will contain the following behavioral modification techniques: education through workshops videos; persuasion by sending messages of risks and benefits, encouragement and coercion using a token economy, nudges by messaging, self-monitoring by graphical progress viewing, successive approaches by behavioral objectives addressing, and guides, through a sustainable food guide that will be designed by means of linear programming optimization using MATLAB®, and graphic design programs such as Canva®, Adobe Illustrator®, and BioRender®. For the token economy system, cut-off points will be established to be charged to the app. Additionally, educational workshops and meal plans will be designed, following the model of sustainable diets, and using the Nutriecology® Nutritional-Ecological software and the Nutrimind® Software for diet calculation. Likewise, the guidelines for the prescription of meal plans, menu design, and recipes for the Mexican population will be followed. Prior to the launch of the mobile application, its feasibility, acceptability, quality, and usability will be assessed. Also, it will be evaluated following the APEASE criteria, which include evaluating 1) Affordability, 2) Practicability, 3) Effectiveness, and Cost-effectiveness, 4) Acceptability, 5) Side-effects/safety, and 6) Equity.

2.1.2 Behavior change intervention design process:

The process of design of the intervention will include:

Stage 1: Understand the behavior:

Step 1: Define the problem in behavioral terms:

This step will be based on the available scientific evidence on the country's dietary and environmental situation, which reveals a high prevalence of overweight, obesity, and associated pathologies such as type 2 diabetes, dyslipidemia, and hypertension. Also, the highest values of dietary water and carbon footprints were found. These problems are mainly related to inadequate food consumption (which will be further detailed) and lack of physical activity.

Step 2: Select target behavior:

The target behaviors will be lack of physical activity performance, inadequate consumption of Mexican foods and dishes, fruits and vegetables, whole grains, legumes, seeds, and healthy fats, dairy products, eggs, fish and shellfish, chicken, red meat (beef and pork, and, in some cases, goat and lamb) and processed, ultra-processed foods and added and free sugars, as well as foods high in trans and saturated fats.

Step 3: Specify the target behavior and Step 4: Identify what needs to change:

Targets behaviors will be established as a goal-setting strategy, which has been reported to be one of the most effective methods for modifying dietary behaviors. Also, they will be addressed as successive approximations toward a sustainable diet, another effective behavior change technique. Targets behaviors will be:

1. Increase physical activity.
2. Increase the consumption of sustainable Mexican foods and dishes.
3. Increase the consumption of fruits and vegetables.
4. Increase the consumption of whole grains.
5. Increase the consumption of legumes.
6. Increase the intake of seeds and healthy fats.
7. Reduce dairy consumption.
8. Reduce the consumption of eggs.
9. Reduce consumption of fish and shellfish.
10. Reduce chicken consumption.
11. Reduce the consumption of red (beef, pork, goat, and lamb) and processed meats.
12. Reduce the consumption of ultra-processed foods.
13. Reduce the intake of added and free sugars, as well as foods with a high content of trans and saturated fats.

All foods whose consumption will be promoted will be aligned with the sustainability characteristics for the Mexican context, on the recommendations of a healthy diet provided by the WHO, and on the model QC7G for food and nutrition education, which will specify which foods to select, in which quantities, when to consumed them and how to prepare them. In addition to when to perform physical activity, specifying type and duration.

Stage 2: Identify intervention options:

Step 5: Intervention functions:

The intervention functions from the behavior change wheel model will be: education, persuasion, incentivization, and coercion. These will be verified in relation to the APEASE criterion.

Step 6: Policy categories:

The policy category of the behavior change wheel model will be the guidelines. Therefore, a nutritional-sustainable food guide will be designed, using linear programming optimization, based on the FAO recommendations for the development of dietary guidelines, and covering the elements of the sustainable diets model as follows: 1) Wellness and Health: ABCD; A: anthropometric and body composition; B: biochemical data; C: clinical data. D: Dietetics. 2) Biodiversity, environment, and climate: carbon footprint and gray water footprint. 3) Equity and fair trade: food prices and socioeconomic level of the population. 4) "Eco-friendly", local, and seasonal foods: green and blue water footprint, locally produced and seasonal foods. 5) Cultural heritage and skills: Traditional Mexican diet, Mexican Diet Quality Index Adapted (IACDMx), and nutritional education based on a traditional diet. 6) Food needs, nutrients, food security, and access: personalized food plan according to individual requirements, preferences, and contexts.

Subsequently, this nutritional-sustainable food guide will be accompanied by a system of equivalent foods that, in addition to incorporating the food's nutrients, will integrate their environmental impact. The calculation of the environmental impact will be made based on the calculation of the total, green, blue, and gray water footprint, using the Water Footprint Assessment method for Mexico. Likewise, the greenhouse gas emissions of foods will be calculated, using the Life Cycle Assessment method for food production and processing through pre-quantified databases. The prices and cultural characteristics of the main consumed foods in Mexico will be included. Prices will be obtained based on fieldwork in supermarkets, and a review of supermarket databases, while cultural aspects will be determined based on a literature review of the traditional Mexican diet.

Once sustainability dimensions are calculated, a sustainable recipe book will be developed, including examples of food plans with individualization options. These food plans will be made up of a distribution of equivalent food rations and examples of menus that meet the nutritional and sustainability characteristics of the Mexican population, with adaptation options.

Stage 3: Identify content and implementation options:

Step 7: Behavior change techniques:

Specific behavior change techniques will be used covering the selected intervention functions as follows:

• Education: successive approximations in the workshops addressing the target objectives.
• Persuasion: Nudges, risk, and benefits communication.
• Incentivization, coercion, and monitoring: messaging, remainders, and token economy through food registers by writing and photos on the mobile application.
• Social support: forum in the mobile app where participants can share pictures of their foods and their physical activity performance. Also, will be able to like the photos of other participants and comment on the photos. Also, a chat for the resolution of doubts between user and administrator will be included in the mobile application.

Step 8: Mode of delivery:

The mode of delivery will be digital since a mobile application is being designed and the workshops will be delivered on digital platforms in videos.

2.2 Stage 2: Application of the sustainable-psycho-nutritional intervention program 2.2.1 Participants Once the intervention program has been designed, it will be applied to a sample of Mexican young adults from the south of Jalisco, randomly divided into two groups: an experimental group (n=50) and a control group (n=50). This is based on recommendations for group designs in behavior modification programs. The sample size is according to the minimum suggested for nutritional interventions, and taking into account the possible desertion of the participants during the intervention, which can amount to more than 50% of the initial sample. It will be included a population between 18 and 35 years old, with Body Mass Index (BMI) values from 18.5 to 40, with or without risk factors for the development of chronic diseases, but without diagnosis with previous pharmacological treatment. The inclusion, exclusion, and elimination criteria will be detailed in further sections. Also, for being included in the study cut-off points to identify inadequate consumption and physical activity were established. The population will be invited to participate through social networks and posters at strategic points, such as Universities, gyms, and the downtown city. Young adults were selected as the population for this study since they are already considered adults who make autonomous food decisions, but at the same time, their young age makes them susceptible to behavioral modification. In addition, they represent parents or future parents, as well as the active population of Mexico, so providing nutritional-sustainable education to these people could generate long-term benefits for their health and that of their families.

2.2.2 Procedure: Participants will be evaluated following the nutritional care process model. The first evaluation will be performed at the beginning of the intervention at baseline, and according to individual requirements, the behavioral objectives will be individually adapted and will be addressed for 7 weeks, considering 2 objectives per week, thus providing 2 weekly educational workshops. Also, personalized food plans will be prescribed, according to the linear programming optimization performed at MATLAB®.

After 7 weeks of educational and nutritional intervention, at week 8, the experimental population will be divided into two sub-groups, where one group will stop being intervened completely (n = 25), and another will continue to receive messages through the mobile application (n = 25) for 8 weeks. Finally, at week 15, a final evaluation will be carried out. Participants will be evaluated in regard to Anthropometric, Biochemical, Clinical, Dietetics, Environmental, Socioeconomic level, and cultural aspects, Nutritional-sustainable knowledge, Behavioral aspects, and Physical activity (ABCD-ESNBP). These aspects will be evaluated according to the nutritional care process model, thus identifying the problem of the population, establishing the etiology, and stating the signs and symptoms.

2.2.3 Sustainable-psycho-nutritional indicators: The ABCD-ESNBP indicators will be included in a complete clinical history that will be uploaded to the mobile application and will be evaluated according to the outcomes section.

2.3 Stage 3: Effects of the sustainable-psycho-nutritional intervention program: As the last stage of this protocol, the corresponding laboratory analyses, and statistical tests will be carried out.

2.3.1 Metabolic biomarkers analysis: For the analysis of metabolic biomarkers, colorimetric enzymatic methods will be used using the Spinreact® S. A/S A. U (Girona, Spain) laboratory kits, for fasting glucose determination (Cat. No. 1001190), TC (Cat. No. 41022), LDL-C (Cat. No. BSIS51-E), HDL-C (Cat. No. BSIS37-E) and TG (Cat. No. 1001313). The reference points for glucose values and lipid profiles will be taken from the regulations in force in Mexico.

2.3.2 Gut microbiota analysis: For the analysis of the gut microbiota, the real-time quantitative polymerase chain reaction (qPCR) method will be followed. First, DNA will be extracted from the collected stool samples, following the protocol for rapid purification of genomic DNA from stool samples. The Qiagen brand commercial kit (1066790ES, USA) will be used. This procedure integrates two stages: lysis and separation of impurities from stool samples, for which Inhibitex Buffer will be used and DNA purification will be carried out by means of centrifugation columns. Once the bacterial DNA samples are obtained, they will be stored and labeled in sterile plastic microtubes (Eppendorf 1.6 mL) at a temperature of -80°C until further analysis.

Next, the purity of the DNA will be verified, and its concentration will be determined using a NanoDrop Lite spectrophotometer (Thermo Scientific, Waltham, MA, USA). 1 µL of the DNA stock of each sample will be placed on the lens of the equipment and the sample will be read at a wavelength of 260 nm for DNA quantification and at 280 nm for protein quantification. The purity will be determined by calculating the index performed by the team, by dividing the reading at 260 nm by the reading at 280 nm and will be considered acceptable in a range of 1.5 to 2. The concentration of the purified coproDNA sample will be measured by their absorbance ratio of 260/280 nm using the same spectrophotometer. This analysis corresponds to the absorbance index of nucleic acids and provides the final concentration in ng/µL.

Once the previous analyzes have been completed, the identification of the gut microbiota will be carried out using the qPCR molecular technique, on the StepOne Applied BioSystems platform, using the SYBR Green reagent as DNA detection chemistry. This reagent is considered an agent that intercalates into the DNA double helix and fluoresces as the DNA copies are synthesized. Therefore, at a higher concentration of the DNA of interest (bacterial), the equipment will record a higher fluorescence signal. In this case, the analysis of interest will be carried out in the V3-V4 hypervariable region of the bacterial 16S rRNA gene. For this analysis, specific primers will be used. The bacterial load and relative abundance of the main bacteria present in the intestine (Firmicutes and Bacteroidetes) will be determined, as well as those related to particular types of diets, for example, Lactobacillus and Bifidobacterium that are related to healthy, vegetarian, and Mediterranean diets, Faecalibacterium prausnitzii that is related to healthy diets and an anti-inflammatory effect, as well as Akkermansia muciniphila, which besides of being related to anti-inflammatory effects is associated to the consumption of the Mexican pre-Hispanic diet. The presence of Prevotella copri will also be identified, which is one of the bacteria most related to plant-based diets and is considered anti-inflammatory and glucose modulator. The presence of Bilophila wadsworthia will also be identified, as it is related to diets with a high content of foods of animal origin, mainly dairy and meat, as well as in westernized diets. Likewise, the presence of Clostridium coccoides will be analyzed, as it is related to obesity and a high fat intake. Also, Streptococcus thermophilus will be included because it is related to dairy consumption. The exact procedure to follow regarding the qPCR run, as well as the specific conditions and temperatures of the analysis, are presented in a previous Mexican investigation.

2.3.3 Evaluation of the adherence to the program: To measure the adherence of the intervened population to the program, an adapted questionnaire will be applied, which will consist of the contrast of the recommendations provided with the performance of the behaviors to promote. For example, questions about the type and intensity of physical activity performed and the amount and frequency of consumption of each of the foods included in the behavioral objectives will be included.

2.3.4 Statistical analyses: The distribution of the data will be analyzed with the Kolmogorov Smirnov test. Descriptive analysis will be performed, including means, standard deviations, and medians. Next, the effects of the program on the selected variables will be assessed by comparing them between evaluations and between groups with t-student tests for paired and unpaired data, respectively, if a normal distribution is found. For no normally distributed data, the Wilcoxon test (repetitive measures) and the U de Mann Whitney test (independent groups) will be used. For no categorical variables, the chi-squared test will be used. Correlation analyses will also be performed, considering Pearson correlation for normally distributed data and Spearman correlations for no normally distributed data. Likewise, simple, and multiple linear regression models will be carried out, as well as binary logistic regression analysis reporting odds ratios, to identify relationships and risks between variables. Statistical analysis will be performed at the STATA V12® program.

2.4 Ethical and biosafety considerations: This project has been already evaluated and approved by the Ethics Committee of the Center for Studies and Research in Behavior, of the University Center for Biological and Agricultural Sciences (CUCBA) from the University of Guadalajara with the number CUCBA/CEIC/CE/002/2022 and by the Technical Research Committee of the University Center of the South (CUSUR), with the number 2021D001. This protocol is also registered on Clinical Trials.gov (ID: NCT05457439). When performing the intervention, the Declaration of Helsinki and biosafety protocols of the Secretary of Health of Mexico will be followed all the time. All participants will sign an informed consent and their identities will be protected by the Federal Law on Protection of Personal Data Held by Private Parties.

Both due to regulations in research with human beings, and due to the situation of the COVID-19 pandemic, a strict biosafety protocol will be followed, where mouth covers will be always worn, both by the evaluating staff and by the participants. Likewise, the sample collection personnel will wear protective glasses and sterile gloves and constant disinfection of the work area will be carried out. In addition, hazardous biological waste will be disposed of in a special trash can in accordance with the provisions of the Ministry of Health.

3. Discussion: By developing this program, the first bases for the Mexican population (and future populations) to achieve a healthy and sustainable diet will be generated. Which can have positive effects on health outcomes and decrease the environmental impact of food consumption; thus addressing two of the main problems afflicting the world population. Also, a new concept is being proposed: The Sustainable-Psycho-Nutrition, which is an approach based on behavioral science that integrates the psychological, social, cultural, economic, nutritional, and environmental aspects of eating behavior, whose objective is to generate the necessary bases to carry out behavioral change interventions, to guide the eating behavior of the population, towards sustainable eating behaviors. Within this term, the nutritional-ecological education concept is also being launched, whose objective is to get people to acquire and performed the appropriate behavioral repertoire to determine what, how much, when, and how to eat, in relation to when, how much, and how energy is spent to maintain or recover their physical well-being, considering at all times the environmental impact of their behaviors and selecting the most sustainable foods, regarding the environment, culture, economy, preferences, food security, health, nutrition, among other factors.

Besides those aspects, the mobile application that is currently being developed is going to be a tool that will facilitate the promotion of sustainable diets first at the national level in Mexico, and forward, worldwide. Also, the first sustainable food guide for Mexico's context will be generated. Which will consider not only sustainability aspects but psychological and behavioral aspects. Moreover, the workshops, recipes, and food plans that are going to be created will serve as tools for the health and environmental sector of the country to promote the consumption of sustainable diets. Finally, the link between gut microbiota and sustainable diets is a new aspect that this study will be characterized for the first time, specifically for the Mexican population. Finally, this project intends to bring attention to the importance of considering behavioral interventions and techniques for promoting sustainable diets.

• Study Type: Interventional
• Enrollment (Actual): 112
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Mariana Lares Michel, PhD Student; Phone Number: +523411017629; Email: mariana.lmichel@alumnos.udg.mx
• Study Contact Backup: Name: Fatima E Housni, PhD; Phone Number: 46142 +523415752222; Email: fatima.housni@cusur.udg.mx

Study Locations

• Mexico
  • Jalisco
    • Ciudad Guzmán, Jalisco, Mexico, 49000
      • Instituto de Investigaciones en Comportamiento Alimentario y Nutrición (IICAN), University of Guadalajara

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 35 years (Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Being between 18 and 35 years old
• Being Mexican
• Reside in the South of Jalisco for at least 1 year
• Levels of physical activity below what is recommended and what is established as a criterion for inclusion in the study
• Consuming amounts of food below or above that established as criteria for inclusion in the study or in a lesser or greater frequency than recommended, according to the type of food
• Have a Smartphone
• Not having consumed antibiotics at least 3 months before the intervention
• Have a BMI between 18.5 and 40
• Not having a medical diagnosis of chronic disease under pharmacological treatment
• Not having a medical diagnosis of gastrointestinal disease

Exclusion Criteria:

• Not signing the informed consent
• Not accepting to donate blood and/or stool samples
• Not being able to stand up to take anthropometric data
• Perform levels of physical activity above the minimum established as criteria for inclusion in the study
• Consume adequate levels of the foods to be promoted in the intervention program
• Being pregnant or lactating
• Suffer from a chronic disease such as type 2 diabetes mellitus, arterial hypertension, dyslipidemia, under medication
• Suffering from an autoimmune disease such as type 1 diabetes, hypo or hyperthyroidism
• Having a gastrointestinal disease such as Crohn's disease, ulcerative colitis, etc.
• Having used antibiotics less than 3 months ago
• Taking antidepressant medications or corticosteroids
• Consume probiotics or nutritional supplements, except protein powder

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Experimental Group; Will be evaluated at baseline and will be intervened for 7 weeks, receiving educational workshops twice a week, addressing the target behaviors. They will also be prescribed a personalized food plan, will receive daily messages through the mobile application, and will have a doubt resolution chat. They will have a digital forum to post photos and comments about their food intake, and physical activity performance, and to like and comment on other participants' photos. They will be asked to enter food records and photos of their food intake into the mobile application, for which they will receive points for performing the expected behavior in a token economy. They will have access to their data for auto-monitoring. In week 8, the experimental group will be evaluated and divided into two sub-groups. One will be completely stopped intervening (n = 25) and one will continue receiving messages through the mobile app, but will no longer have workshops and food plan prescriptions (n = 25).	Behavioral: Sustainable diet promotion through behavioral change intervention; 15 weeks digital intervention to promote sustainable diets through workshops, and behavioral change techniques in a mobile application, to decrease environmental impact of diets and improve health.
No Intervention: Control Group; The control group will be evaluated at baseline and will not be intervened. Anyway, they will be evaluated at weeks 8 (as monitoring) and 15, at the end of the intervention.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from Baseline Gut Microbiota at week 8 and 15	Identification of Firmicutes, Bacteroidetes, Lactobacillus, Bifidobacterium, Faecalibacterium prausnitzii, Akkermansia muciniphila, Prevotella copri, Bilophila wadsworthia, Clostridium coccoides, and Streptococcus thermophilus relative abundance by qPCR with specific primers	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Glucose Levels at week 8 and 15	Determination of glucose levels by colorimetric enzymatic methods	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline LDL Cholesterol Levels at week 8 and 15	Determination of LDL Cholesterol Levels by colorimetric enzymatic methods	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline HDL Cholesterol Levels at week 8 and 15	Determination of HDL Cholesterol Levels by colorimetric enzymatic methods	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Total Cholesterol Levels at week 8 and 15	Determination of Total Cholesterol Levels by colorimetric enzymatic methods	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Triglycerides Levels at week 8 and 15	Determination of Triglycerides Levels by colorimetric enzymatic methods	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Systolic and Diastolic Blood Presure at week 8 and 15	Blood pressure will be evaluated with a sphygmomanometer and following the Mexican normativity	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Acanthosis Nigricans at week 8 and 15	Clinical signs of insulin resistance (acanthosis nigricans) will be evaluated by physical exploration, searching for hyperpigmentation and thickening of the skin with velvety, in visible flex areas	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline weight at week 8 and 15	The weight will be evaluated with an Omron® bioimpedance scale (HBF-511T-E/HBF-511B-E), following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Body Fat Percentage at week 8 and 15	The percentage of body fat will be evaluated with an Omron® bioimpedance scale (HBF-511T-E/HBF-511B-E), following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Food Intake at week 8 and 15	Caloric-nutritional and food intake will be assessed through average data taken from 24-hour recalls, dietary records, and by a validated adapted Food Frequency Questionnaire (CFCA).	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Diet Quality at week 8 and 15	Diet quality will be analyzed by an adapted version of the Mexican Diet Quality Index (ICDMx).	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Physical Activity at week 8 and 15	The IPAQ questionnaire will be used, and the type, frequency, intensity, and duration will be evaluated	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Dietary Water Footprint at week 8 and 15	Dietary water footprint (total, green, blue, and grey) will be calculated using the Water Footprint Assessment method in its version for Mexico's context	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Dietary Carbon Footprint at week 8 and 15	Dietary carbon footprint is also going to be calculated using the Life Cycle Assessment method considering food production and processing greenhouse gas emissions as food system boundaries	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Nutritional-sustainable knowledge at week 8 and 15	Will be evaluated through a designed questionnaire, based on the psychological capacity presented in the COM-B model	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from Signs of nutrient deficiencies or excess at week 8 and 15	Signs of nutrient deficiencies or excess will also be evaluated in relation to hair, nails, mouth, tongue, edema, and mucous membranes appearance	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Muscle Mass at week 8 and 15	The muscle mass will be evaluated with an Omron® bioimpedance scale (HBF-511T-E/HBF-511B-E), following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Visceral Fat at week 8 and 15	The visceral fat will be evaluated with an Omron® bioimpedance scale (HBF-511T-E/HBF-511B-E), following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Body Mass Index (BMI) at week 8 and 15	The BMI will be calculated considering weight/height2	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Waist Circumference at week 8 and 15	The waist circumference will be evaluated using a Lufkin® metal tape measure, following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Change from Baseline Hips Circumference at week 8 and 15	The hips circumference will be evaluated using a Lufkin® metal tape measure, following validated techniques	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Height evaluation	The height will be evaluated with a Smartmet® stadiometer, following validated techniques	Baseline (week 0)
Change from Baseline Eating behavior at week 8 and 15	Eating behavior will be assessed through questions about food preparation, food shopping places, food preferences, and about following specific diets at the moment of the evaluation. Those aspects will be evaluated through a designed questionnaire.	Baseline (week 0), monitoring measure (week 8) and end of intervention (week 15)
Psychological aspects (COM-B model aspects)	Psychological aspects such as motivation, capability, and opportunity will be assessed through a questionnaire.	Baseline (week 0)
Food allergies and intolerances	Will be assessed through a designed questionnaire.	Baseline (week 0)

Collaborators and Investigators

• Sponsor: University of Guadalajara
• Collaborators: Universidad de Granada; Tecnológico Nacional de México, campus Ciudad Guzmán
• Investigators: Principal Investigator: Fatima E Housni, PhD, University of Guadalajara

Publications and helpful links

General Publications

• Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011 Apr 23;6:42. doi: 10.1186/1748-5908-6-42.
• Lares-Michel M, Housni FE, Aguilera Cervantes VG, Reyes-Castillo Z, Michel Nava RM, Llanes Canedo C, Lopez Larios MJ. The water footprint and nutritional implications of diet change in Mexico: a principal component analysis. Eur J Nutr. 2022 Sep;61(6):3201-3226. doi: 10.1007/s00394-022-02878-z. Epub 2022 Apr 19.
• Lares-Michel M, Housni FE, Aguilera Cervantes VG, Carrillo P, Michel Nava RM, Llanes Canedo C. Eat Well to Fight Obesity... and Save Water: The Water Footprint of Different Diets and Caloric Intake and Its Relationship With Adiposity. Front Nutr. 2021 Jul 1;8:694775. doi: 10.3389/fnut.2021.694775. eCollection 2021.
• Lares-Michel M, Housni FE, Aguilera Cervantes VG. A quantitative estimation of the water footprint of the Mexican diet, corrected for washing and cooking water. Food Sec 2021. https://doi.org/10.1007/s12571-021-01160-0
• Willett W, Rockstrom J, Loken B, Springmann M, Lang T, Vermeulen S, Garnett T, Tilman D, DeClerck F, Wood A, Jonell M, Clark M, Gordon LJ, Fanzo J, Hawkes C, Zurayk R, Rivera JA, De Vries W, Majele Sibanda L, Afshin A, Chaudhary A, Herrero M, Agustina R, Branca F, Lartey A, Fan S, Crona B, Fox E, Bignet V, Troell M, Lindahl T, Singh S, Cornell SE, Srinath Reddy K, Narain S, Nishtar S, Murray CJL. Food in the Anthropocene: the EAT-Lancet Commission on healthy diets from sustainable food systems. Lancet. 2019 Feb 2;393(10170):447-492. doi: 10.1016/S0140-6736(18)31788-4. Epub 2019 Jan 16. No abstract available. Erratum In: Lancet. 2019 Feb 9;393(10171):530. Lancet. 2019 Jun 29;393(10191):2590. Lancet. 2020 Feb 1;395(10221):338. Lancet. 2020 Oct 3;396(10256):e56.
• López-Espinoza A, Martínez Moreno AG. La Educación en Alimentación y Nutrición. 2016. México: McGrawHill
• López-Espinoza A, Magaña González C. Hábitos Alimentarios: Psicobiología y socioantropología de la alimentación. 2014. México: McGrawHill
• Vijayapushpam T, Antony GM, Rao GM, Rao DR. Nutrition and health education intervention for student volunteers: topic-wise assessment of impact using a non-parametric test. Public Health Nutr. 2010 Jan;13(1):131-6. doi: 10.1017/S1368980009990255. Epub 2009 Jun 23.
• Gabrielli S, Dianti M, Maimone R, Betta M, Filippi L, Ghezzi M, Forti S. Design of a Mobile App for Nutrition Education (TreC-LifeStyle) and Formative Evaluation With Families of Overweight Children. JMIR Mhealth Uhealth. 2017 Apr 13;5(4):e48. doi: 10.2196/mhealth.7080.
• West R, Michie S. A Guide to Development and Evaluation of Digital Behaviour Change Interventions in Healthcare. London; 2016.
• Hedin B, Katzeff C, Eriksson E, Pargman D. A Systematic Review of Digital Behaviour Change Interventions for More Sustainable Food Consumption. Sustainability, 11(2638), 1-23. 10.3390/su11092638
• Pieniak Z, Zakowska-Biemans S, Kostyra E, Raats M. Sustainable healthy eating behaviour of young adults: towards a novel methodological approach. BMC Public Health. 2016 Jul 15;16:577. doi: 10.1186/s12889-016-3260-1.
• Michie S, Atkins L, West R. The behaviour change wheel a guide to designing interventions (First edition). 2014. Silverback Publishing.
• Mor E, Garreta M, Galofré M. Diseño Centrado en el Usuario en Entornos Virtuales de Aprendizaje, de la Usabilidad a la Experiencia del Estudiante. 10.
• West R, Michie S. A guide to development and evaluation of digital behaviour interventions in healthcare. (First edition). 2016. Silverback Publishing.
• Spiegelhalter D. Risk and Uncertainty Communication. Annual Review of Statistics and Its Application. 2017; 4:31-60. https://doi.org/10.1146/annurev-statistics-010814-020148
• Friis R, Skov LR, Olsen A, Appleton KM, Saulais L, Dinnella C, Hartwell H, Depezay L, Monteleone E, Giboreau A, Perez-Cueto FJA. Comparison of three nudge interventions (priming, default option, and perceived variety) to promote vegetable consumption in a self-service buffet setting. PLoS One. 2017 May 31;12(5):e0176028. doi: 10.1371/journal.pone.0176028. eCollection 2017.
• Rigby RR, Mitchell LJ, Hamilton K, Williams LT. The Use of Behavior Change Theories in Dietetics Practice in Primary Health Care: A Systematic Review of Randomized Controlled Trials. J Acad Nutr Diet. 2020 Jul;120(7):1172-1197. doi: 10.1016/j.jand.2020.03.019. Epub 2020 May 20.
• Maillot M, Vieux F, Amiot MJ, Darmon N. Individual diet modeling translates nutrient recommendations into realistic and individual-specific food choices. Am J Clin Nutr. 2010 Feb;91(2):421-30. doi: 10.3945/ajcn.2009.28426. Epub 2009 Nov 25.
• Pérez-Lizaur AB, Berenice Palacios González, Ana Laura Castro Becerra, Isabel Flores Galicia. Sistema Mexicano de Alimentos Equivalentes. Ogali; 2014.
• Bertha P-L Ana Bertha. Desarrollo del Plan alimentario. Dietas normales y terapéuticas: los alimentos en la salud y la enfermedad. Sexta edición. 2014. p. 1-14.
• Martínez Moreno AG. Control conductual y obesidad infantil. México obeso: actualidades y perspectivas. Editorial Universitaria. 2015. p. 238-49.
• Martínez-Moreno AG. Modificación de la conducta alimentaria. Una asignatura para nutriólogos. La educación en alimentación y nutrición. [Internet] McGraw Hill. p. 253-66. Available from: https://www.researchgate.net/profile/Alma-Gabriela-Martinez-Moreno
• Michie S, Atkins L, West R. The behaviour change wheel: a guide to designing interventions. 2014.
• Kazdin A, Modificacion de la conducta y sus aplicaciones.
• Duthie SJ, Duthie GG, Russell WR, Kyle JAM, Macdiarmid JI, Rungapamestry V, Stephen S, Megias-Baeza C, Kaniewska JJ, Shaw L, Milne L, Bremner D, Ross K, Morrice P, Pirie LP, Horgan G, Bestwick CS. Effect of increasing fruit and vegetable intake by dietary intervention on nutritional biomarkers and attitudes to dietary change: a randomised trial. Eur J Nutr. 2018 Aug;57(5):1855-1872. doi: 10.1007/s00394-017-1469-0. Epub 2017 May 30.
• Medina-Vera I, Sanchez-Tapia M, Noriega-Lopez L, Granados-Portillo O, Guevara-Cruz M, Flores-Lopez A, Avila-Nava A, Fernandez ML, Tovar AR, Torres N. A dietary intervention with functional foods reduces metabolic endotoxaemia and attenuates biochemical abnormalities by modifying faecal microbiota in people with type 2 diabetes. Diabetes Metab. 2019 Apr;45(2):122-131. doi: 10.1016/j.diabet.2018.09.004. Epub 2018 Sep 25.
• Swan WI, Vivanti A, Hakel-Smith NA, Hotson B, Orrevall Y, Trostler N, Beck Howarter K, Papoutsakis C. Nutrition Care Process and Model Update: Toward Realizing People-Centered Care and Outcomes Management. J Acad Nutr Diet. 2017 Dec;117(12):2003-2014. doi: 10.1016/j.jand.2017.07.015. Epub 2017 Oct 5. No abstract available.
• Suverza A, Haua K. El ABCD de la evaluación del estado de nutrición 1th ed. McGraw-Hill; 2010
• Porchas-Quijada M, Reyes-Castillo Z, Munoz-Valle JF, Duran-Barragan S, Aguilera-Cervantes V, Lopez-Espinoza A, Vazquez-Del Mercado M, Navarro-Meza M, Lopez-Uriarte P. IgG Anti-ghrelin Immune Complexes Are Increased in Rheumatoid Arthritis Patients Under Biologic Therapy and Are Related to Clinical and Metabolic Markers. Front Endocrinol (Lausanne). 2019 Apr 18;10:252. doi: 10.3389/fendo.2019.00252. eCollection 2019.
• Pinheiro AC, Rojas P, Carrasco F, Gomez P, Mayas N, Morales I. Acanthosis nigricans as an indicator of insulin resistance in Chilean adult population. Nutr Hosp. 2011 Sep-Oct;26(5):940-4. doi: 10.1590/S0212-16112011000500003.
• Ortega, R. M., Pérez-Rodrigo, C., & López-Sobaler, A. M. (2015). Métodos de evaluación de la ingesta actual: registro o diario diétetico. Revista Española de Nutrición Comunitaria, 21(1), 34-41. 10.14642/RENC.2015.21.sup1.5048
• Green RF, Joy EJM, Harris F, Agrawal S, Aleksandrowicz L, Hillier J, Macdiarmid JI, Milner J, Vetter SH, Smith P, Haines A, Dangour AD. Greenhouse gas emissions and water footprints of typical dietary patterns in India. Sci Total Environ. 2018 Dec 1;643:1411-1418. doi: 10.1016/j.scitotenv.2018.06.258. Epub 2018 Jul 4.
• Ruiz Cerrillo S. Modelo de cálculo de la huella de carbono para el sistema mexicano de alimentos equivalentes. Journal of Negative and No Positive Results, 2(6), 226-232. 10.19230/jonnpr.1240
• Fresan U, Martinez-Gonzalez MA, Sabate J, Bes-Rastrollo M. The Mediterranean diet, an environmentally friendly option: evidence from the Seguimiento Universidad de Navarra (SUN) cohort. Public Health Nutr. 2018 Jun;21(8):1573-1582. doi: 10.1017/S1368980017003986. Epub 2018 Jan 30.
• Lares-Michel M, Housni FE, Cervantes VGA, Cañedo CL, Carmona M del CB, Toro HBD, Nava RMM. The relationship between consumption, socioeconomic level and reasons of tomato intake in Mexico. Agricultural Sciences, 2018; 9, 777-791. 10.4236/as.2018.97055
• Verain MCD, Snoek HM, Onwezen MC, Reinders MJ, Bouwman EP. Sustainable food choice motives: The development and cross-country validation of the Sustainable Food Choice Questionnaire (SUS-FCQ). Food Quality and Preference, 2012; 93(104267), 1-11. https://doi.org/10.1016/j.foodqual.2021.104267
• Bacchetti De Gregoris T, Aldred N, Clare AS, Burgess JG. Improvement of phylum- and class-specific primers for real-time PCR quantification of bacterial taxa. J Microbiol Methods. 2011 Sep;86(3):351-6. doi: 10.1016/j.mimet.2011.06.010. Epub 2011 Jun 17.
• Senghor, B., Sokhna, C., Ruimy, R., & Lagier, J. C. (2018). Gut microbiota diversity according to dietary habits and geographical provenance. Human Microbiome Journal, 7(8), 1-9. https://doi.org/10.1016/j.humic.2018.01.00143
• Avila-Nava A, Noriega LG, Tovar AR, Granados O, Perez-Cruz C, Pedraza-Chaverri J, Torres N. Food combination based on a pre-hispanic Mexican diet decreases metabolic and cognitive abnormalities and gut microbiota dysbiosis caused by a sucrose-enriched high-fat diet in rats. Mol Nutr Food Res. 2017 Jan;61(1). doi: 10.1002/mnfr.201501023. Epub 2016 Aug 8.
• Meslier V, Laiola M, Roager HM, De Filippis F, Roume H, Quinquis B, Giacco R, Mennella I, Ferracane R, Pons N, Pasolli E, Rivellese A, Dragsted LO, Vitaglione P, Ehrlich SD, Ercolini D. Mediterranean diet intervention in overweight and obese subjects lowers plasma cholesterol and causes changes in the gut microbiome and metabolome independently of energy intake. Gut. 2020 Jul;69(7):1258-1268. doi: 10.1136/gutjnl-2019-320438. Epub 2020 Feb 19.
• Ramirez-Farias C, Slezak K, Fuller Z, Duncan A, Holtrop G, Louis P. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. Br J Nutr. 2009 Feb;101(4):541-50. doi: 10.1017/S0007114508019880. Epub 2008 Jul 1.
• Scher JU, Sczesnak A, Longman RS, Segata N, Ubeda C, Bielski C, Rostron T, Cerundolo V, Pamer EG, Abramson SB, Huttenhower C, Littman DR. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. Elife. 2013 Nov 5;2:e01202. doi: 10.7554/eLife.01202.
• Asnicar F, Berry SE, Valdes AM, Nguyen LH, Piccinno G, Drew DA, Leeming E, Gibson R, Le Roy C, Khatib HA, Francis L, Mazidi M, Mompeo O, Valles-Colomer M, Tett A, Beghini F, Dubois L, Bazzani D, Thomas AM, Mirzayi C, Khleborodova A, Oh S, Hine R, Bonnett C, Capdevila J, Danzanvilliers S, Giordano F, Geistlinger L, Waldron L, Davies R, Hadjigeorgiou G, Wolf J, Ordovas JM, Gardner C, Franks PW, Chan AT, Huttenhower C, Spector TD, Segata N. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat Med. 2021 Feb;27(2):321-332. doi: 10.1038/s41591-020-01183-8. Epub 2021 Jan 11.
• Chavez-Carbajal A, Nirmalkar K, Perez-Lizaur A, Hernandez-Quiroz F, Ramirez-Del-Alto S, Garcia-Mena J, Hernandez-Guerrero C. Gut Microbiota and Predicted Metabolic Pathways in a Sample of Mexican Women Affected by Obesity and Obesity Plus Metabolic Syndrome. Int J Mol Sci. 2019 Jan 21;20(2):438. doi: 10.3390/ijms20020438.
• Magkos F, Tetens I, Bugel SG, Felby C, Schacht SR, Hill JO, Ravussin E, Astrup A. The Environmental Foodprint of Obesity. Obesity (Silver Spring). 2020 Jan;28(1):73-79. doi: 10.1002/oby.22657.
• Valerino-Perea S, Lara-Castor L, Armstrong MEG, Papadaki A. Definition of the Traditional Mexican Diet and Its Role in Health: A Systematic Review. Nutrients. 2019 Nov 17;11(11):2803. doi: 10.3390/nu11112803.
• Johnston JL, Fanzo JC, Cogill B. Understanding sustainable diets: a descriptive analysis of the determinants and processes that influence diets and their impact on health, food security, and environmental sustainability. Adv Nutr. 2014 Jul 14;5(4):418-29. doi: 10.3945/an.113.005553. Print 2014 Jul.
• Spahn JM, Reeves RS, Keim KS, Laquatra I, Kellogg M, Jortberg B, Clark NA. State of the evidence regarding behavior change theories and strategies in nutrition counseling to facilitate health and food behavior change. J Am Diet Assoc. 2010 Jun;110(6):879-91. doi: 10.1016/j.jada.2010.03.021.
• Gazan R, Brouzes CMC, Vieux F, Maillot M, Lluch A, Darmon N. Mathematical Optimization to Explore Tomorrow's Sustainable Diets: A Narrative Review. Adv Nutr. 2018 Sep 1;9(5):602-616. doi: 10.1093/advances/nmy049.
• Paivarinta E, Itkonen ST, Pellinen T, Lehtovirta M, Erkkola M, Pajari AM. Replacing Animal-Based Proteins with Plant-Based Proteins Changes the Composition of a Whole Nordic Diet-A Randomised Clinical Trial in Healthy Finnish Adults. Nutrients. 2020 Mar 28;12(4):943. doi: 10.3390/nu12040943.
• Petry NM. A comparison of young, middle-aged, and older adult treatment-seeking pathological gamblers. Gerontologist. 2002 Feb;42(1):92-9. doi: 10.1093/geront/42.1.92.
• Swinburn BA, Caterson I, Seidell JC, James WP. Diet, nutrition and the prevention of excess weight gain and obesity. Public Health Nutr. 2004 Feb;7(1A):123-46. doi: 10.1079/phn2003585.
• Rodriguez-Lara A, Plaza-Diaz J, Lopez-Uriarte P, Vazquez-Aguilar A, Reyes-Castillo Z, Alvarez-Mercado AI. Fiber Consumption Mediates Differences in Several Gut Microbes in a Subpopulation of Young Mexican Adults. Nutrients. 2022 Mar 13;14(6):1214. doi: 10.3390/nu14061214.
• Macedo-Ojeda G, Vizmanos-Lamotte B, Marquez-Sandoval YF, Rodriguez-Rocha NP, Lopez-Uriarte PJ, Fernandez-Ballart JD. Validation of a semi-quantitative food frequency questionnaire to assess food groups and nutrient intake. Nutr Hosp. 2013 Nov 1;28(6):2212-20.
• Macedo-Ojeda G, Marquez-Sandoval F, Fernandez-Ballart J, Vizmanos B. The Reproducibility and Relative Validity of a Mexican Diet Quality Index (ICDMx) for the Assessment of the Habitual Diet of Adults. Nutrients. 2016 Aug 23;8(9):516. doi: 10.3390/nu8090516.
• Brain K, Burrows TL, Rollo ME, Hayes C, Hodson FJ, Collins CE. The Effect of a Pilot Dietary Intervention on Pain Outcomes in Patients Attending a Tertiary Pain Service. Nutrients. 2019 Jan 16;11(1):181. doi: 10.3390/nu11010181.
• Hickl O, Heintz-Buschart A, Trautwein-Schult A, Hercog R, Bork P, Wilmes P, Becher D. Sample Preservation and Storage Significantly Impact Taxonomic and Functional Profiles in Metaproteomics Studies of the Human Gut Microbiome. Microorganisms. 2019 Sep 19;7(9):367. doi: 10.3390/microorganisms7090367.
• Rinninella E, Cintoni M, Raoul P, Lopetuso LR, Scaldaferri F, Pulcini G, Miggiano GAD, Gasbarrini A, Mele MC. Food Components and Dietary Habits: Keys for a Healthy Gut Microbiota Composition. Nutrients. 2019 Oct 7;11(10):2393. doi: 10.3390/nu11102393.
• Verhoog S, Taneri PE, Roa Diaz ZM, Marques-Vidal P, Troup JP, Bally L, Franco OH, Glisic M, Muka T. Dietary Factors and Modulation of Bacteria Strains of Akkermansia muciniphila and Faecalibacterium prausnitzii: A Systematic Review. Nutrients. 2019 Jul 11;11(7):1565. doi: 10.3390/nu11071565.
• Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, Kayser BD, Levenez F, Chilloux J, Hoyles L; MICRO-Obes Consortium; Dumas ME, Rizkalla SW, Dore J, Cani PD, Clement K. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. 2016 Mar;65(3):426-36. doi: 10.1136/gutjnl-2014-308778. Epub 2015 Jun 22.
• Laue H, Smits TH, Schumacher UK, Claros MC, Hartemink R, Cook AM. Identification of Bilophila wadsworthia by specific PCR which targets the taurine:pyruvate aminotransferase gene. FEMS Microbiol Lett. 2006 Aug;261(1):74-9. doi: 10.1111/j.1574-6968.2006.00335.x.
• Zinocker MK, Lindseth IA. The Western Diet-Microbiome-Host Interaction and Its Role in Metabolic Disease. Nutrients. 2018 Mar 17;10(3):365. doi: 10.3390/nu10030365.
• Jamar G, Santamarina AB, Dias GC, Masquio DCL, de Rosso VV, Pisani LP. Relationship between fatty acids intake and Clostridium coccoides in obese individuals with metabolic syndrome. Food Res Int. 2018 Nov;113:86-92. doi: 10.1016/j.foodres.2018.07.002. Epub 2018 Jul 4.
• Furet JP, Quenee P, Tailliez P. Molecular quantification of lactic acid bacteria in fermented milk products using real-time quantitative PCR. Int J Food Microbiol. 2004 Dec 15;97(2):197-207. doi: 10.1016/j.ijfoodmicro.2004.04.020.
• Gila-Diaz A, Arribas SM, Lopez de Pablo AL, Lopez-Gimenez MR, Phuthong S, Ramiro-Cortijo D. Development and Validation of a Questionnaire to Assess Adherence to the Healthy Food Pyramid in Spanish Adults. Nutrients. 2020 Jun 3;12(6):1656. doi: 10.3390/nu12061656.

Helpful Links

• Encuesta Nacional de Salud y Nutrición (ENSANUT). Resultados. 2018.
• Sequía generalizada en México | Ciencia de la NASA
• Food and Agriculture Organization of the United Nations, World Health Organization. Sustainable healthy diets: guiding principles. 2019.
• Almaguer González J, García Ramírez H, Padilla Mirazo M, González Ferral M. La dieta de la milpa Modelo de atencion Meso Americana Saludable y Culturalmente Pertinente. 2019
• North American Association for Environmental Education [NAAEE] / Secretaría de Medio Ambiente y Recursos Naturales [SEMARNAT] [NAAEE/SEMARNAT]. Guía para elaborar programas de educación ambiental no formal. 2009
• Food and Agriculture Organization of the United Nations. Guías alimentarias y sostenibilidad
• World Health Organization [WHO]. Healthy diet. Fact Sheet N°394. 2015
• Secretaría de Salud. 2012. Norma oficial mexicana NOM-253-SSA1-2012, para la disposición de sangre humana y sus componentes con fines terapéuticos.
• Diario Oficial de la Federación [DOF]. (31 de mayo de 2010b). Norma Oficial Mexicana NOM-030-SSA2-2009, Para la prevención, detección, diagnóstico, tratamiento y control de la hipertensión arterial sistémica. Secretaría de Salud.
• Hoekstra AY, Chapagain AK, Aldaya MM, Mekonnen MM. The water footprint assessment manual: Setting the global standard. Londres: Earthscan. 2012
• The Kap Survey model - Knowledge attitude and practices
• Organización Mundial de la Salud [OMS]. (2008). Advocacy, communication and social mobilization for TB control - A guide to developing knowledge, attitude and practices surveys. Geneva, Switzerland: Organización Mundial de la Salud.
• Fautsch Y, Glasauer P, Nutrition Division. Guidelines for assessing nutrition-related knowledge, attitudes and practices. Rome, Italy: FAO; 2014
• Diario Oficial de la Federación [DOF]. (13 de julio de 2012). Norma Oficial Mexicana NOM-037-SSA2-2012, Para la prevención, tratamiento y control de las dislipidemias. Secretaría de Salud.
• NORMA Oficial Mexicana NOM-015-SSA2-2010, Para la prevención, tratamiento y control de la diabetes mellitus
• The World Medical Association-Declaración de Helsinki de la AMM - Principios éticos para las investigaciones médicas en seres humanos

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2022
• Primary Completion (Estimated): December 1, 2023
• Study Completion (Estimated): December 1, 2023

Study Registration Dates

• First Submitted: June 24, 2022
• First Submitted That Met QC Criteria: July 9, 2022
• First Posted (Actual): July 14, 2022

Study Record Updates

• Last Update Posted (Actual): November 29, 2023
• Last Update Submitted That Met QC Criteria: November 28, 2023
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Keywords: Sustainable Diets; Behavior Change; Gut Microbiota; Environmental Impact of Diets; Nutritional and Environmental Education; Mexican Population; Water Footprint; Carbon Footprint; Eating Behavior; m-Health
• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Skin Diseases; Lipid Metabolism Disorders; Hyperlipidemias; Dyslipidemias; Hyperpigmentation; Pigmentation Disorders; Melanosis; Hyperglycemia; Hypercholesterolemia; Hypertriglyceridemia; Acanthosis Nigricans
• Other Study ID Numbers: CIP/T/04/22

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: It has not been decided if individual participant data is going to be shared. It will be decided according to the development of the intervention.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No