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The number and proportion of people aged 60 years old and over is increasing worldwide. Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death. This deterioration is the primary risk factor for major chronic diseases including diabetes, cardiovascular disease, and neurodegenerative disorders.
The incidence of chronic conditions frequently rises sharply with age, after long exposure to unhealthful lifestyles involving the consumption of unhealthy diets and physical inactivity. Consequently, integrated dietary strategies and actions are required to promote healthy ageing and target major causes of morbidity and mortality in senior populations.
The promising field of precision nutrition is rising as a therapeutic approach that aims to design tailored dietary interventions to prevent and manage chronic diseases. Indeed, precision nutrition approaches contemplate the interindividual heterogeneity caused by genetic/epigenetic dissimilarities, individual facets such as age and gender, the lifestyle and environmental exposome diversity, microbiome variations, and singular behavioral/psychological features.
On the other hand, the inclusion of potentially bioactive compounds and functional foods as promoters of healthy aging within personalised dietary patterns could be an effective strategy to delay the aging process and age-related chronic diseases.
One of the main limitations of a dietary prescription is the lack of compliance, due to the complexity of the prescription itself and/or the lack of commitment of the individual. The inclusion of digital tools to empower and motivate individuals and to support them in the management of the dietary strategy could overcome this limitation.
With this background, the general objective of this investigation is to design precision nutritional strategies based on the inclusion of functional foods and digital tools for preventing age-related chronic diseases in pre-senior and senior populations. Additionally, this study proposes alternative tools for cognitive assessments increasing the accessibility to cognitive assessment tools for this population as well as an innovative digital tool for cognitive stimulation which is personalized, monitored, and evidence-based.
This study is designed as a 12-week, randomized parallel intervention trial, with two arms: 1) Control group, who follows a control diet based on the current dietary guidelines of the Spanish Society of Community Nutrition (SENC) using the Healthy Eating Plate method (Harvard), and 2) Nutriprecision Group, which were instructed to follow the Nutriprecision diet based on the inclusion of digital tools and functional foods, whose postprandial effects were previously evaluated by randomized, cross-over, double-blind studies in senior subjects in the Centre for Nutrition Research (UNAV) and IMDEA-ALIMENTACIÓN. The incremental area under the curve (iAUC) for glucose and insulin was calculated for all designed foods and was compared with their reference products. Additionally, lipid profile and satiety were measured at fasting and at 15, 30, 45, 60, 90, and 120 min after starting the food intake. In all these studies, the reference and test foods were administered once in random order, with a wash-out period between 7 days and 14 days among assays.
This multi-centric study was carried out in the Nutrition Intervention Unit of the Centre for Nutrition Research in the University of Navarra and the Nutritional and Clinical Trials Unit in IMDEA-ALIMENTACIÓN by qualified professionals (nurse, doctor-dietician, dieticians, pharmacists).
A total of five visits had been established along with the 12-weeks trial: 1) study information and screening; 2) day 0: start of the intervention; 3) day 28: group session (control group)/follow-up visit (Nutriprecision group); 4) day 56: group session (control group)/follow-up visit (Nutriprecision group) and 5) day 84: end of the intervention.
At the start and finish days of the study, participants visited the Nutrition Intervention Unit or the Clinical Trials Unit in a fasting state. Participants were instructed to collect the first-morning urine sample. Additionally, volunteers from the University of Navarra self-collected fecal samples at baseline using OMNIgene.GUT kits from DNA Genotek. Volunteers were also informed of a digital-based procedure for cognitive assessment and other digital tools available depending on the assigned intervention (experimental VS control).
Blood samples were drawn by venipuncture after a 12 h overnight fast in a clinical setting. After 10 minutes of rest and having answered the Mini Nutritional Assessment (MNA) and the Mini-Mental State Examination (MMSE) questionnaires, blood pressure was measured. Later, anthropometric measurements and body composition analysis were performed. Global cognitive performance was also assessed by the Guttmann NeuroPersonalTrainer platform. The duration of these visits was approximately 1 hour.
On the 28th and 56th study days, participants assigned to the control group attended online group sessions and received intensive education and advice to increase the adherence to the dietary strategy. Sessions consisted of informative talks about the prescribed dietary pattern, food label use, seasonal shopping lists, meal plans and recipes, physical activity and exercise recommendations, sleep habits, etc. Contrary, participants allocated to the Nutriprecision group attended in person visits with the dieticians, to evaluate the adherence to the assigned nutritional treatment. Additionally, anthropometric, body composition, and blood pressure measurements were assessed. Participants were also asked to fill different questionnaires about health status (SF-36 Health Survey), gastrointestinal symptoms (gastrointestinal symptoms rating scale, GSRT), dietary assessment (7-day recall), Mediterranean diet adherence (14-Item Mediterranean Diet Assessment Tool), physical activity (International Physical Activity Questionnaire, IPAQ) and drug therapy modifications. Moreover, the Nutriprecision group were asked to collect a sensory perception questionnaire and a food consumption record of the precision foods administered.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control diet | Placebo Comparator | A conventional diet based on the current Spanish Mediterranean dietary guidelines: Spanish Society of Community Nutrition (SENC). |
|
| Nutriprecision diet | Experimental | A Mediterranean, balanced diet based on the inclusion of precision foods designed and developed within the framework of Nutriprecision project. A mobile application to empower and support the management of the dietary prescription. A digital tool for cognitive stimulation. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Control diet | Other | Control diet: A Mediterranean conventional diet based on the current dietary guidelines of the Spanish Society of Community Nutrition (SENC). Participants were strongly advised to use the Healthy Eating Plate (Harvard) to structure and prepare the main meals (lunch and dinner). In this way, at least ½ of the plate should be composed of vegetables, ¼ of lean protein, and ¼ of low glycemic index carbohydrates. The diet encourages participants to eat 5 times/day (breakfast, lunch, dinner, and two snacks). Overall, the control diet was based on high consumption of vegetables and fruits, whole grains, healthy fats (olive oil), and healthy proteins (legumes, fish, and lean meat). There was not energy restriction in the control diet. |
| Measure | Description | Time Frame |
|---|---|---|
| Change From Baseline General Health Status at 3 Months | General health score encompassed twelve parameters, on a scale of 0 to 21, with higher scores indicating a worse overall health:
| 0 months and 3 months |
| Measure | Description | Time Frame |
|---|---|---|
| Change From Baseline Weight at 3 Months | Weight was measured by a digital scale | 0 months and 3 months |
| Baseline height | Height was recorded using a wall-mounted stadiometer (Seca 220, Vogel & Halke, Germany). |
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Inclusion Criteria:
Men and women aged 50-80 years
BMI >27 kg/m2
One or more of the following risk factors:
Exclusion Criteria:
Relevant functional or structural digestive abnormalities (malformations, angiodysplasia, active peptic ulcers, chronic inflammatory diseases, or malabsorption)
Endocrine disorders (hyperthyroidism or uncontrolled hypothyroidism)
Undergone surgical interventions with permanent sequelae (gastroduodenostomy)
Pharmacological treatments with immunosuppressants, cytotoxic agents, systemic corticosteroids, or other drugs that could potentially cause hepatic steatosis or alteration of liver tests
Active cancer in the last five years or under therapy
Weight loss ≥3 kg in the last three months
Instable drug therapy in the last three months
Severe psychiatric disorders
No autonomy
Inability to follow the diet (food allergies, intolerances)
Difficulties to follow scheduled visits
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| Name | Affiliation | Role |
|---|---|---|
| Itziar Abete Goñi, PhD | Centre for Nutrition Research - University of Navarra | Principal Investigator |
| Santiago Navas Carretero, PhD | Centre for Nutrition Research - University of Navarra | Principal Investigator |
| M Ángeles Zulet Alzórriz, Professor | Centre for Nutrition Research - University of Navarra | Study Director |
| Carlos Javier González Navarro, PhD | Centre for Nutrition Research - University of Navarra | Study Director |
| J. Alfredo Martínez Hernández, Professor | Centre for Nutrition Research - University of Navarra | Study Director |
| Viviana Loria Kohen, PhD | IMDEA Food | Principal Investigator |
| Ana Ramirez Molina, PhD | IMDEA Food | Study Chair |
| Guillermo Reglero Rada, Professor | IMDEA Food | Study Chair |
| Elena Aguilar Aguilar, PhD | IMDEA Food |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Centre for Nutrition Research, University of Navarra | Pamplona | Navarre | 31008 | Spain |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 28829397 | Background | de Toro-Martin J, Arsenault BJ, Despres JP, Vohl MC. Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome. Nutrients. 2017 Aug 22;9(8):913. doi: 10.3390/nu9080913. | |
| 31601025 | Background | Gonzalez-Muniesa P, Martinez JA. Precision Nutrition and Metabolic Syndrome Management. Nutrients. 2019 Oct 9;11(10):2411. doi: 10.3390/nu11102411. |
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| ID | Term |
|---|---|
| D050177 | Overweight |
| D009765 | Obesity |
| D007333 | Insulin Resistance |
| D006973 | Hypertension |
| D005247 | Feeding Behavior |
| D009043 | Motor Activity |
| D007249 | Inflammation |
| ID | Term |
|---|---|
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
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The participants are randomly assigned to Control or NUTRIPRECISION strategy.
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|
| Nutriprecision diet | Other | Nutriprecision diet: a Mediterranean balanced diet based on the inclusion of precision foods designed according to the particularities of the senior population. The selected precision foods were a) fruit compote, b) smoothie, c) extruded meat product, d) wholemeal bread, e) wholemeal biscuit and f) microwaveable deep-frozen vegetable products. The diet encourages participants to eat 5 times/day with a conventionally balanced distribution of macronutrients (50% of the total caloric value from carbohydrates, 20% from proteins, and 30% from lipids). There was not energy restriction, although the energy requirements of the participants were adjusted to a BMI of 25 kg/m2 to avoid an overestimate of calorie intake. A mobile application designed and developed to provide volunteers with information about follow-up visits, the assigned diet, recommendations, and messages to motivate them during the intervention. A digital tool for cognitive stimulation. |
|
| 0 months |
| Change From Baseline Body Mass Index at 3 Months | Body mass index was calculated using the standard formula: weight (kg)/height (m)2 | 0 months and 3 months |
| Change From Baseline Fat Mass at 3 Months | Fat mass was measured by Bioelectrical impedance analysis (BIA, SC-330, Tanita) | 0 months and 3 months |
| Change From Baseline Lean Mass at 3 Months | Lean mass was measured by Bioelectrical impedance analysis (BIA, SC-330, Tanita) | 0 months and 3 months |
| Change From Baseline Waist Circumference at 3 Months | Waist Circumference was measured by with a tape measure | 0 months and 3 months |
| Change From Baseline Hip Circumference at 3 Months | Hip Circumference was measured by with a tape measure | 0 months and 3 months |
| Change From Baseline Systolic Blood Pressure at 3 Months | Systolic Blood Pressure was measured using an automatic monitor device (Intelli Sense. M6, OMRON Healthcare, Hoofdorp, the Netherlands) | 0 months and 3 months |
| Change From Baseline Diastolic Blood Pressure at 3 Months | Diastolic Blood Pressure was measured using an automatic monitor device (Intelli Sense. M6, OMRON Healthcare, Hoofdorp, the Netherlands) | 0 months and 3 months |
| Change From Baseline Serum Triglycerides at 3 Months | Triglycerides were measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Total Cholesterol at 3 Months | Total cholesterol was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum LDL-Cholesterol at 3 Months | LDL-cholesterol was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum HDL-Cholesterol at 3 Months | HDL-cholesterol was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Uric Acid at 3 Months | Uric acid was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Glucose at 3 Months | Glucose was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Insulin at 3 Months | Insulin was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Glycosylated hemoglobin (HbA1C) at 3 Months | Glycosylated hemoglobin (HbA1C) was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Aspartate Aminotransferase at 3 Months | Aspartate aminotransferase was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Alanine Aminotransferase at 3 Months | Alanine aminotransferase was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Serum Gamma-glutamyltransferase at 3 Months | Gamma glutamyltransferase was measured in fasting conditions | 0 months and 3 months |
| Change From Baseline Physical Activity Level at 3 Months | Physical activity was measured by the International Physical Activity Questionnaire (IPAQ) | 0 months and 3 months |
| Change From Baseline Dietary Intake at 3 Months | Dietary intake was measured by a 7-day recall | 0 months and 3 months |
| Change From Baseline Mediterranean Diet Adherence at 3 Months | Mediterranean diet adherence was measured by the 14-Item Mediterranean Diet Assessment Tool | 0 months and 3 months |
| Change From Baseline Health Status at 3 Months | Health status was measured by the SF-36 Health Survey | 0 months and 3 months |
| Change From Baseline Gastrointestinal Symptoms at 3 Months | Gastrointestinal symptoms were measured by the gastrointestinal symptoms rating scale, GSRT | 0 months and 3 months |
| Change From Baseline Sensory Perception of Precision Foods at 3 Months | Sensory perception of precision foods was measured by the sensory perception questionnaire | 1 month and 3 months |
| Food Consumption of the Precision Foods | Food consumption of the precision foods was measured by a food consumption record | 1 month, 2 months and 3 months |
| Change From Baseline Risk of Malnutrition at 3 Months | Risk of malnutrition was measured by the Mini Nutritional Assessment (MNA) questionnaire | 0 months and 3 months |
| Change From Baseline Cognitive Impairment at 3 Months | Cognitive impairment was measured by the Mini-Mental State Examination (MMSE) questionnaire | 0 months and 3 months |
| Change From Baseline Cognitive Function at 3 Months | Cognitive function was measured by the Guttmann NeuroPersonalTrainer platform | 0 months and 3 months |
| Baseline Gut Microbiota Composition | Gut Microbiota Composition will be measured using OMNIgene.GUT kits from DNA Genotek | 0 months |
| Usability of the digital tools | Usability will be measured using the System Usability Scale (SUS) | 3 months |
| Baseline subjective hunger | Visual analogue scale rating in a scale from 0 to 100 mm, for the quantification of the perceived hunger before the experimental food intake | Baseline |
| Postprandial subjective hunger | Visual analogue scale rating in a scale from 0 to 100 mm, for the quantification of the perceived hunger measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Baseline subjective fullness | Visual analogue scale rating in a scale from 0 to 100 mm for the quantification of the perceived fullness before the experimental food intake | Baseline |
| Postprandial subjective fullness | Visual analogue scale rating in a scale from 0 to 100 mm, for the quantification of the perceived fullness measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Baseline subjective satiety | Visual analogue scale rating in a scale from 0 to100 mm for the quantification of the perceived satiety before the experimental food intake. | Baseline |
| Postprandial subjective satiety | Visual analogue scale rating in a scale from 0 to100 mm for the quantification of the perceived satiety measured at 15, 30, 45, 60, 90 and 120 minutes after experimental food intake | Up to 120 minutes |
| Baseline subjective desire to eat | Visual analogue scale rating in a scale from 0 to 100 mm for the quantification of the perceived desire to eat before the experimental food intake at baseline. | Baseline |
| Postprandial subjective desire to eat | Visual analogue scale rating in a scale from 0 to 100 mm for the quantification of the perceived desire to eat measured at 15, 30, 45, 60, 90 and 120 minutes after experimental food intake | Up to 120 minutes |
| Baseline subjective thirst | Visual analogue scale rating in a scale from 0 to 100 mm for the quantification of the perceived thirst before the experimental food intake at baseline | Baseline |
| Postprandial subjective thirst | Visual analogue scale ratings in a scale from 0 to 100 mm for the quantification the perceived thirst measured at 15, 30, 45, 60, 90 and 120 minutes after experimental food intake | Up to 120 minutes |
| Baseline blood glucose concentration | Blood glucose concentration before experimental food intake | Baseline |
| Baseline blood insulin concentration | Blood insulin concentration before experimental food intake | Baseline |
| Incremental area under the curve (iAUC) for glucose | The incremental area under the curve (AUCi) for glucose was calculated via the geometric sums of the areas of the triangles and trapezoids above the fasting glucose concentration over a 2-h period | 0,15,30,45,60,90,120 |
| Incremental area under the curve (iAUC) for insulin | The incremental area under the curve (AUCi) for insulin was calculated via the geometric sums of the areas of the triangles and trapezoids above the fasting insulin concentration over a 2-h period | 0,15,30,45,60,90,120 |
| Baseline blood high density lipoprotein cholesterol (HDL) concentration | Blood high density lipoprotein cholesterol (HDL) concentration before experimental food intake | Baseline |
| Baseline blood low density lipoprotein cholesterol (LDL) concentration | Blood low density lipoprotein cholesterol (LDL) concentration before experimental food intake | Baseline |
| Baseline blood triglyceride concentration | Blood triglyceride concentration before experimental food intake | Baseline |
| Postprandial blood glucose concentration | Blood glucose concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Postprandial blood insulin concentration | Blood insulin concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Postprandial blood total cholesterol concentration | Blood total cholesterol concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Postprandial blood high density lipoprotein cholesterol (HDL) concentration | Blood high density lipoprotein cholesterol (HDL) concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Postprandial blood low density lipoprotein cholesterol (LDL) concentration | Blood low density lipoprotein cholesterol (LDL) concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Postprandial blood triglyceride concentration | Blood triglyceride concentration measured at 15, 30, 45, 60, 90 and 120 minutes after the experimental food intake | Up to 120 minutes |
| Helena Marcos Pasero | IMDEA Food | Study Chair |
| Susana Molina | IMDEA Food | Study Chair |
| Carmen Crespo | IMDEA Food | Study Chair |
| Cristina Galarregui Miquelarena | Centre for Nutrition Research - University of Navarra | Study Chair |
| Blanca Martínez de Morentín, MD | Centre for Nutrition Research - University of Navarra | Study Chair |
| Salomé Pérez Díez | Centre for Nutrition Research - University of Navarra | Study Chair |
| María Hernández Ruiz de Eguilaz | Centre for Nutrition Research - University of Navarra | Study Chair |
| Veronica Ciaurriz Fernández | Centre for Nutrition Research - University of Navarra | Study Chair |
| María Zabala Navó | Centre for Nutrition Research - University of Navarra | Study Chair |
| Begoña de Cuevillas García | Centre for Nutrition Research - University of Navarra | Study Chair |
| José Manuel Iniesta Chamorro | Universidad Politécnica de Madrid (UPM) | Study Chair |
| Paloma Chausa Fernández | Universidad Politécnica de Madrid (UPM) | Study Chair |
| José Tapia Galisteo | Universidad Politécnica de Madrid (UPM) | Study Chair |
| Elena Hernando Pérez | Universidad Politécnica de Madrid (UPM) | Study Chair |
| Enrique J. Gómez Aguilera | Universidad Politécnica de Madrid (UPM) | Study Chair |
| Alexis Álvarez Rollán | Grupo I.C.A. Informática y Comunicaciones Avanzadas, S.L. | Study Chair |
| Alejandro García Rudolph | Institut Guttmann, University Institute attached to the Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain; Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain; The Health Sciences Research Institute of the Germans | Study Chair |
| Alberto García Molina | Institut Guttmann, University Institute attached to the Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain; Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain; The Health Sciences Research Institute of the Germans | Study Chair |
| Josep Maria Tormos Muñoz | Institut Guttmann, University Institute attached to the Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain; Universitat Autònoma de Barcelona, Bellaterra, Cerdanyola del Vallès, Spain; The Health Sciences Research Institute of the Germans | Study Chair |
| Background | Brooke, JB (1996). SUS - a quick and dirty usability scale. In: Usability Evaluation in Industry, Jordan, P, Thomas, B, Weerdmeester, B, and McLelland, I(eds), Taylor and Francis: London |
| D012816 |
| Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D006946 | Hyperinsulinism |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D001522 | Behavior, Animal |
| D001519 | Behavior |
| D010335 | Pathologic Processes |