Animal models and studies on small samples of obese adults have shown that gut microbial diversity and certain types of bacteria could predict the efficacy of the dietetic treatment to improve body mass index (BMI) and the components of metabolic syndrome (MetS). Gut microbiota could distinguish the obese with metabolic syndrome patient than that metabolically healthy. Dietetic therapy could induce changes in the microbiota that could lead to improvement of BMI and the components of the MetS. The aim of MICROBEkids is to test whether the motivational intervention a motivational intervention (OBEMAT2.0) (PI15/00970) is more effective than the conventional intervention to increase the gut microbial diversity and, as a consequence, to improve BMI and MetS components. The role of gut microbiota (through modulation of the short chain fatty acids) will be analyzed as cardiovascular risk factor and as predictor of treatment success. These objectives will be achieved through a clustered clinical trial design with an intervention group that will receive a motivational therapy compared to a control group that will receive a conventional intervention, both during 12 months. The study sample are 319 children (n= 167 in the intervention group) that were enrolled in the clinical trial OBEMAT2.0 (PI15/00970), have had a comprehensive clinical assessment before the intervention (ages 8 to 14) and after 12 months (+3) of therapy (ages 9 to 15) and furthermore have participated in a biological samples collection for the investigation on childhood obesity (COLOBEPED, reference C.0004585).

The study will provide light to several hypothesis:

- The main hypothesis is that the dietetic intervention in obese children may improve the components of the metabolic syndrome by mediation (at least in part) of changes in the microbiota.

Other secondary hypothesis to be demonstrated are:

• The microbiota (before the treatment) could be a determinant factor of the metabolic syndrome (inflamation, serum lipid profile, insulin resistance) being a key feature differentiating the metabolically healthy obese from the obese with metabolic syndrome.
• A dietary pattern rich in vegetables and fruits is associated to a gut microbiota profile preventing the metabolic syndrome

How these hypothesis will be demonstrated? A motivational structured intervention to reduce weight is applied (under randomized clustered design) to obese children, that are compared to an active intervention (not structured) provided by health care professionals, both groups during 12 months (+3).

A baseline and final assessment (before and after the intervention) are performed, in which the following information is collected:

• Socioeconomics
• Anthropometry (weight, height, waist circumference) to calculate the obesity degree (BMI z- score) and the presence of abdominal obesity
• Body composition: deuterium dilution (in a subsample), bioimpedance, Dual X-Ray Absorptiometry and Air displacement pletismography (BodPod)
• Blood sample drawn: to analyze lipids profile and insulin resistance
• Fecal sample: the gut microbiota diversity and the presence of specific bacteria will be analyzed
• Dietary intake by a food frequency questionnaire: diet will be analyzed as dietary patterns
• Systolic and diastolic blood pressure (which will be adjusted as z-score)

Inclusion Criteria:

• Age range between 8 and <14 years at enrolment (so that, children would end the treatment at maximum age of 15 years
• BMI > 97th percentile of Hernandez references from 1988 (Hernández et al., 1988) as indicated by the Guidelines for Clinical Practice of the Spanish Health System (Grupo de trabajo de la Guía de Práctica Clínica sobre la Prevención y el Tratamiento de la Obesidad Infantojuvenil. Ministerio de Ciencia e Innovación [Spanish Ministry of Sciencee and Innovation], 2009) for the diagnose of the childhood obesity.

Exclusion Criteria:

• Children with eating disorders
• Families not available to attend to scheduled visits
• Simultaneous participation in another clinical trial
• Presence of endocrine disorders (GH disorder, hypothyroidism, Cushing's disease, early puberty or other)
• Lack of command of local languages