Objective: This study aimed to explore whether screen time and the screen type impacted various health aspects of children, including physical activity (PA), sleep quality, and eating habits. Additionally, we investigated whether children's eating behavior while using electronic devices affects their physical and mental health.
Methods: We conducted an online survey asking for screen use (duration, type, and purpose), PA, eating habits, sleep problems, and level of depression. The participants were children between the ages of 3 and 7 years, and the survey was answered by the participants' parents from March 3 to March 20, 2021.
Results: A screen time of ≥2 h in children was associated with various clinical characteristics, such as body mass index (BMI), sleep problems, depression, decreased PA, and unusual eating habits. Children's food eating behavior while using electronic devices was predicted by a total screen time ≥2 h, smartphone screen time ≥2 h, sleep problems, owning electronic devices, and eating unhealthy food.
Conclusion: There was an interplay among children's PAs, eating behaviors, depression, sleep problems, and screen time in this pandemic era. Therefore, guiding children on the correct use of electronic devices and helping them eat healthy are paramount during this COVID-19 pandemic.
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http://dx.doi.org/10.30773/pi.2021.0239 | DOI Listing |
Nutrients
January 2025
Department of Community Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania.
Background/objectives: This study aimed to investigate the lifestyle and the behavioral factors that influence the nutritional status of adolescents from Transylvania, Romania.
Methods: The Global School-Based Student Health Survey (GSHS) was used to collect data from 900 adolescents between 11 and 18 years old from the Transylvania region, Romania. This study assessed nutritional status by calculating BMI indicators adjusted to Z-Score, cut-off points according to the World Health Organization (WHO), using self-reported weight and height; perceived health status; food vulnerability; physical activity; addictive behaviors (cigarette, alcohol and drug consumption); number of hours spent in front of the computer/phone; hand and oral hygiene; sitting time/day; and sleep.
Int J Mol Sci
January 2025
Endocrinology Research Center, Moscow 117292, Russia.
Analyzing the genetic architecture of hereditary forms of diabetes in different populations is a critical step toward optimizing diagnostic and preventive algorithms. This requires consideration of regional and population-specific characteristics, including the spectrum and frequency of pathogenic variants in targeted genes. As part of this study, we used a custom-designed NGS panel to screen for mutations in 28 genes associated with the pathogenesis of hereditary diabetes mellitus in 506 unrelated patients from Russia.
View Article and Find Full Text PDFChildren (Basel)
January 2025
Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, 107 Wiggins Road, Saskatoon, SK S7N 5E5, Canada.
Background/objectives: The COVID-19 pandemic created a growing need for insights into the mental health of children and youth and their use of coping mechanisms during this period. We assessed mood symptoms and related factors among children and youth in Saskatchewan. We examined if coping abilities mediated the relationship between risk factors and mood states.
View Article and Find Full Text PDFChildren (Basel)
December 2024
Department of Physical Education, Sport and Recreation, Universidad de La Frontera, Temuco 4811230, Chile.
: This study aimed to (i) investigate the association between lifestyle parameters (i.e., screen time [ST], food habits, and physical activity [PA]) and health-related quality of life (HRQoL) with executive functions (EFs, i.
View Article and Find Full Text PDFAntioxidants (Basel)
December 2024
Food Science Program, Division of Food, Nutrition and Exercise Sciences, University of Missouri, Columbia, MO 65211, USA.
Purple corn pericarp, a processing waste stream, is an extremely rich source of phytochemicals. Optimal polyphenol extraction parameters were identified using response surface methodology (RSM) by combining a deep eutectic solvent (DES) and ultrasound-assisted extraction (UAE) method. After DES characterization, Plackett-Burman design was used to screen five explanatory variables, namely, time, Temp (temperature), water, Amp (amplitude), and S/L (solid-to-liquid ratio).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!