Background: Lifestyle factors sleep duration and media time during childhood differ between countries. This study examined whether sleep duration and media time affect metabolic risk factors insulin resistance (IR), blood lipid profile, and liver enzymes, and whether there is a relationship between sleep time and media time in Turkish obese children and adolescents.
Methods: Subjects included 108 obese children and adolescents (aged 10-15 years) whose lifestyle factors were assessed using a survey containing questions about sleep durations, television viewing, media use, and demographic factors. Metabolic risk factors were compared among groups categorized according to sleep and media duration.
Results: Aspartate aminotransferase (AST), alanine aminotransferase (ALT), and triglyceride (TG) levels and homeostasis model assessment of insulin resistance (HOMA-IR) values were higher in subjects who spent >5 hours/day on media. Children 10-13 years old who slept <9 hours/day were more likely to have higher insulin and HOMA-IR (p < 0.05) levels and lower high-density lipoprotein cholesterol (HDL-C) levels compared with subjects who slept 9-10 hours/day and >10 hours/day. Correlation analysis revealed a negative relationship between sleep time and media time (r = -0.471, p = 0.000).
Conclusions: Short sleep duration was associated with IR and an elevated plasma lipoprotein profile in children and adolescents. Our results suggest that insufficient sleep and excessive media exposure may contribute to metabolic risk in the context of obesity, and therefore, working to improve sleep duration and limit media time could help reduce metabolic risk in obese children and adolescents.
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http://dx.doi.org/10.1089/chi.2015.0126 | DOI Listing |
Chemosphere
January 2025
Nanoqam, Department of Chemistry, University of Quebec at Montreal, H3C 3P8, Canada; École de technologie supérieure, Montréal (Québec), Canada, H3C 1K3. Electronic address:
Sci Total Environ
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Temple University, Department of Civil and Environmental Engineering, 1947 North 12(th) Street, Philadelphia, PA 19122, United States. Electronic address:
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School of Applied Psychology, Griffith University, Australia.
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School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
Most current research in cloud forensics is focused on tackling the challenges encountered by forensic investigators in identifying and recovering artifacts from cloud devices. These challenges arise from the diverse array of cloud service providers as each has its distinct rules, guidelines, and requirements. This research proposes an investigation technique for identifying and locating data remnants in two main stages: artefact collection and evidence identification.
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