Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm.

Background and Objectives: Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.

Individual and family predictors of ultra-processed food consumption in Spanish children. The SENDO project.

BRACKGROUND: Ultra-processed food (UPF) consumption is increasing exponentially, becoming a matter of concern for Public Health, given its adverse health effects. OBJECTIVE: To identify individual and family factors predicting UPF consumption in childhood. DESIGN: The SENDO project is an ongoing prospective dynamic cohort of Spanish children. In this study, we used baseline information of participants recruited between January 2015 and June 2021. Dietary information was collected with a validated semi-quantitative FFQ, and food items were classified using the NOVA classification. Individual and family factors associated with UPF consumption (p< 0.20) in univariate analyses were introduced in a model of generalized estimating equations (GEE) which accounted for intra-cluster correlations between siblings. SETTING: The SENDO proyect (Spain), 2015-2021. PARTICIPANTS: Spanish children are recruited at the age of 4-5 years and followed yearly through online questionnaires completed by parents. RESULTS: In this sample of 806 participants (49% girls; mean age 5 years [SD: 0.90]), the mean UPF consumption was 37.64 % of total energy intake (sd: 9.59). Large family size and longer exposure to screens predicted higher consumption of UPF. On the other hand, better knowledge of children's dietary recommendations, healthy dietary attitudes towards child's eating habits and longer breastfeeding were associated with lower consumption of UPF. All these factors accounted for approximately 16% of the variability on the consumption of UPF in childhood. CONCLUSION: Since most of the factors identified in this study are modifiable, they should be considered in public health strategies aimed at promoting heathy dietary habits in early life.

[Validation of the anthropometric data reported by parents of participants in the SENDO project]. / Validación de los datos antropométricos declarados por padres de participantes en el proyecto SENDO.

INTRODUCTION: Objective: to analyze the validity of self-reported somatometry data through a self-reported online questionnaire. Method: the SENDO project (Follow-up of Children for Optimal Development) is a prospective, dynamic pediatric cohort. Participants are recruited when they are between 4 and 6 years old, and followed annually through an online questionnaire. In a subsample of 82 participants, we compared the anthropometric information reported in the baseline questionnaire with the direct measurements collected by the investigating staff. To do this, we calculated the intraclass correlation index (ICC) and the Bland-Altman coefficient. Results: the ICC was 0.96 (95 % confidence interval [CI]: 0.94-0.98 for weight; 0.95 (95 % CI: 0.92-0.96) for height; 0.75 (95 % CI: 0.64-0.86) for waist circumference; and 0.84 (95 % CI: 0.76-0.89) for hip circumference. In relation to the indices calculated from these measurements, we found an ICC of 0.84 (95 % CI: 0.77-0.90) for body mass index; 0.46 (95 % CI: 0.27-0.62) for waist-hip ratio; and 0.59 (95 % CI: 0.43-0.72) for waist-height index. The Bland-Altman index ranged from 3.7 % for weight to 8.5 % for body mass index. Conclusions: we found a high correlation and concordance between the data collected in the physical exam and those reported by the parents. Our results indicate that the anthropometric measures provided by parents, especially those with which they are most familiar, are valid and can be used in epidemiological research.

INTRODUCCIÓN: Objetivo: analizar la validez de las medidas antropométricas declaradas por los padres de los participantes en el proyecto SENDO. Método: el proyecto SENDO (Seguimiento del Niño para un Desarrollo Óptimo) es una cohorte pediátrica abierta y prospectiva. Los participantes se reclutan cuando tienen entre 4 y 6 años, y se siguen anualmente mediante un cuestionario "online". En una submuestra de 82 participantes, se comparó la información antropométrica declarada en el cuestionario basal con las mediciones directas recogidas por el personal investigador. Para ello, se calcularon el índice de correlación intraclase (ICC) y el coeficiente de mala clasificación de Bland-Altman. Resultados: el ICC fue de 0,96 (intervalo de confianza [IC] del 95 %: 0,94-0,98) para el peso; de 0,95 (IC 95 %: 0,92-0,96) para la altura; de 0,75 (IC 95 %: 0,64-0,86) para el perímetro de la cintura, y de 0,84 (IC 95 %: 0,76-0,89) para el perímetro de la cadera. En relación a los índices calculados a partir de esas mediciones, se encontró un ICC de 0,84 (IC 95 %: 0,77-0,90) para el índice de masa corporal; de 0,46 (IC 95 %: 0,27-0,62) para el cociente cintura-cadera, y de 0,59 (IC 95 %: 0,43-0,72) para el índice cintura-altura. El índice de mala clasificación de Bland-Altman osciló entre el 3,7 % para el peso y el 8,5 % para el índice de masa corporal. Conclusiones: se encontró una muy elevada concordancia para la información antropométrica declarada por los padres y la medida de forma directa. Los resultados indican que las medidas antropométricas referidas por los padres, especialmente aquellas con los que están más familiarizados, son válidas y pueden utilizarse en la investigación epidemiológica.