Confinement due to the COVID-19 pandemic can influence dietary profiles, especially those of adolescents, who are highly susceptible to acquiring bad eating habits. Adolescents’ poor dietary habits increase their subsequent risk of degenerative diseases such as obesity, diabetes, cardiovascular pathologies, etc. Our aim was to study nutritional modifications during COVID-19 confinement in adolescents aged 10 to 19 years, compare them with their usual diet and dietary guidelines, and identify variables that may have influenced changes. Data were collected by an anonymous online questionnaire on food intake among 820 adolescents from Spain, Italy, Brazil, Colombia, and Chile. The results show that COVID-19 confinement did influence their dietary habits. In particular, we recorded modified consumption of fried food, sweet food, legumes, vegetables, and fruits. Moreover, gender, family members at home, watching TV during mealtime, country of residence, and maternal education were diversely correlated with adequate nutrition during COVID-19 confinement. Understanding the adolescents’ nutrition behavior during COVID-19 lockdown will help public health authorities reshape future policies on their nutritional recommendations, in preparation for future pandemics.

Aim: to describe physical activity and ultra-processed foods consumption, their changes and sociodemographic predictors among adolescents from countries in Europe (Italy and Spain) and Latin America (Brazil, Chile, and Colombia) during the SARS-CoV-2-pandemic period. Methods: Cross-sectional study via web survey. International Physical Activity Questionnaire (IPAQ) and weekly ultra-processed food consumption data were used. To compare the frequencies of physical activity status with sociodemographic variables, a multinomial logistic and a multiple logistic regression for habitual ultra-processed foods was performed. In final models, p < 0.05 was considered significant. Results: Sample of 726 adolescents, mostly females (59.6%) aged 16–19 years old (54.3%). Adolescents from Latin America presented odds ratio (OR) 2.98 (CI 95% 1.80–4.94) of being inactive and those whose mothers had higher level of education were less active during lockdown [OR 0.40 (CI 95% 0.20–0.84)]. The habitual ultra-processed consumption was also high during this period in all countries, and more prevalent in Latin America. Conclusion: A higher prevalence of inactivity was observed in this population, but reductions of physical activity and habitual ultra-processed consumption during the pandemic were more pronounced in Latin America. Our findings reinforce the importance of promoting a healthy lifestyle, i.e., exercise and diet, during periods of social isolation.

Research into the relationship between an Energy-adjusted Diet-Inflammatory Index (E-DII) and a wider health-related biomarkers profile is limited. Much of the existing evidence centers on traditional metabolic biomarkers in populations with chronic diseases, with scarce data on healthy individuals. Thus, this study aims to investigate the association between an E-DII score and 30 biomarkers spanning metabolic health, endocrine, bone health, liver function, cardiovascular, and renal functions, in healthy individuals. 66,978 healthy UK Biobank participants, the overall mean age was 55.3 (7.9) years were included in this cross-sectional study. E-DII scores, based on 18 food parameters, were categorised as anti-inflammatory (E-DII < -1), neutral (-1 to 1), and pro-inflammatory (>1). Regression analyses, adjusted for confounding factors, were conducted to investigate the association of 30 biomarkers with E-DII. Compared to those with an anti-inflammatory diet, individuals with a pro-inflammatory diet had increased levels of 16 biomarkers, including six cardiometabolic, five liver, and four renal markers. The concentration difference ranged from 0.27 SD for creatinine to 0.03 SD for total cholesterol. Conversely, those on a pro-inflammatory diet had decreased concentrations in six biomarkers, including two for endocrine and cardiometabolic. The association range varied from -0.04 for IGF-1 to -0.23 for SHBG. This study highlighted that a pro-inflammatory diet was associated with an adverse profile of biomarkers linked to cardiometabolic health, endocrine, liver function, and renal health.

Obesity is a worry because it is associated with a greater burden of disease, and it has been shown to be related to the health habits and physical condition of children and adolescents. Objective: To associate physical fitness, screen time, and sleep habits with the different categories of obesity in schoolchildren from the extreme south of Chile. Methods: 583 schoolchildren were included in this cross-sectional analysis. The screen time and sleep habits were measured with the Sleep Self-Report questionnaire, while the physical fitness was assessed with the Alpha Fitness test battery. The Body Mass Index/age (BMI/age) and the Waist-to-Height ratio (WtHr) were used to define adiposity using the following categories: healthy weight/low-risk waist-to-height ratio (H/LR), healthy weight/high-risk waist-to-height ratio (H/HR), overweight/low-risk waist to height ratio (O/LR), and overweight/high-risk waist to height ratio (O/HR). Results: A considerable number of schoolchildren (23.2%) presented sleep problems, while the mean screen time was 9.3 (95% CI: 8.4; 10.1) hours/day. Schoolchildren classified as H/HR showed better physical fitness than the O/HR group but worse physical fitness than the H/LR group. Conclusions: Significant differences were evidenced in the physical fitness between the adiposity categories, which could open future lines of research concerning the characterization of the healthy weight-obese adiposity categories in children.

Objective: To analyze the perception of physical fitness, screen time, and self-reported sleep hygiene in children and adolescents (CA) from the extreme south of Chile and its associations with waist-to-height ratio (WtHr). Material and methods: An observational cross-sectional study was conducted in a sample of 594 schoolchildren from 5th to 8th grade of primary education, belonging to municipal educational establishments in the Magallanes region, Chile. Cardiorespiratory fitness was assessed through the 20-m shuttle run test, muscle strength through handgrip and the standing broad jump test, physical fitness perception through the International Fitness Scale, and central obesity through the waist-to-height index. In addition, sleep hygiene and screen time were measured. Results: More than 92% of CA spent more than two hours a day watching or using screens. In addition, CA with excess central adiposity had a lower perception of physical fitness, and lower muscle strength and cardiorespiratory fitness compared to CA with normal values of adiposity. Conclusions: CA of the present study spent a high number of hours watching or using screens and had poor sleep quality. In addition, excessive central adiposity was associated with lower physical fitness.

Antecedentes: Aunque se ha documentado la eficacia de las intervenciones vía mobile health (mHealth) para aumentar el ejercicio físico, existe evidencia limitada sobre la motivación, las barreras y los beneficios asociados a la práctica de ejercicio físico en este tipo de intervenciones mHealth. Objetivo: Examinar las diferencias de motivación, barreras y beneficios entre el ejercicio físico vía mHealth y presencial. Método: Estudio preexperimental en 37 adultos (96,5% mujeres, 43 ±10,5 años) del Biobío, Chile, quienes participaron de una intervención de ejercicio físico vía mHealth. Se utilizó el Cuestionario de la Regulación de la Conducta en el Ejercicio (BREQ-3), y la Escala de Beneficios/Barreras para el Ejercicio (EBBS). Resultados: Luego de la intervención, el grupo de ejercicio físico mHealth presentó mayor puntaje de motivación de tipo regulación externa (3,25 ±3,79 v/s 1,08 ±1,60; t(33,676)= 2,434, p= 0,020, d= 0,676), un menor puntaje de motivación de tipo integrada (3,25 ±3,79 v/s 1,08 ±1,60; t(33,676)= 2,434, p= 0,020, d= 0,676), y un menor índice de autodeterminación en la práctica de ejercicio físico (45,25 ±26,54 v/s 67,38 ±19,61; t(35)= - 2,635, p= 0,012, d= 0,908) que el grupo de ejercicio físico presencial. No se observaron diferencias significativas en las barreras y beneficios para la práctica de ejercicio físico. Conclusiones: El ejercicio vía mHealth generó una mayor motivación externa y una menor motivación integrada en comparación con el ejercicio presencial. Estos hallazgos respaldan el potencial de la tecnología mHealth para promover la motivación en la actividad física y superar las barreras percibidas. Palabras clave: ejercicio; mobile health; motivación; barreras y facilitadores; intervención. Background: Although the efficacy of interventions via mobile health (mHealth) to increase physical exercise has been documented, there is limited evidence on the motivation, barriers and benefits associated with practicing of physical exercise in this type of mHealth intervention. Objective: To examine the differences in motivation, barriers and benefits between the practice of physical exercise via mHealth and in person. Method: Pre-experimental study in 37 adults (96.5% women, 43 ±10.5 years old) from the Biobío, Chile, who participated in a physical exercise intervention via mHealth. The Exercise Behavior Regulation Questionnaire (BREQ-3), and the Exercise Benefits/Barriers Scale (EBBS). Results: After the intervention, the mHealth physical exercise group presented a higher external regulation type motivation score (3.25 ±3.79 v/s 1.08 ±1.60; t(33.676)= 2.434, p= 0.020, d= 0.676), a lower integrated motivation score (3.25 ±3.79 v/s 1.08 ±1.60; t(33.676)= 2.434, p= 0.020, d= 0.676), and a lower index of self-determination in the practice of physical exercise (45.25 ±26.54 v/s 67.38 ±19.61; t(35)= -2.635, p= 0.012, d= 0.908) than the group face-to-face physical exercise. No significant differences were observed in the barriers and benefits for the practice of physical exercise. Conclusions: The exercise via mHealth generated greater external motivation and less integrated motivation compared to the face-to-face exercise. These findings support the potential of mHealth technology to promote physical activity motivation and overcome perceived barriers. Keywords: exercise; mobile health; motivation; barriers and facilitators; intervention.