Background: Previous studies have analyzed the relationship between screen time and cardiometabolic disease risk factors among adolescents, but few have examined the longitudinal effects of screen time on cardiometabolic health into adulthood using nationally representative data.
Objective: To determine prospective associations between screen time and later cardiometabolic disease over a 24-year period using a nationally representative adolescent cohort.
Design: Longitudinal prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) collected from 1994 to 2018.
Participants: Adolescents aged 11-18 years old at baseline (1994-1995) followed for 24 years.
Main Measures: Predictors: screen time (five repeated measures of self-reported television and video watching from adolescence to adulthood).
Outcomes: Five repeated measures of body mass index (BMI); two repeated measures of waist circumference, hypertension, hyperlipidemia, and diabetes collected at 15- and 24-year follow-up exams.
Key Results: For the 7105 adolescents in the sample (49.7% female, 35.0% non-white), the baseline adolescent average screen time per day was 2.86 ± 0.08 hours per day, which generally declined through 24-year follow-up. Average BMI at baseline was 22.57 ± 0.13 kg/m, which increased to 30.27 ± 0.18 kg/m through follow-up. By 24-year follow-up, 43.4% of participants had obesity, 8.4% had diabetes, 31.8% had hypertension, and 14.9% had hyperlipidemia. In mixed-effects generalized linear models, each additional hour of screen time per day was associated with 0.06 (95% CI 0.04-0.09) within-person increase in BMI. Each additional hour of screen time per day was associated with higher within-person odds of high waist circumference (AOR 1.17, 95% CI 1.09-1.26), obesity (AOR 1.09, 95% CI 1.03-1.15), and diabetes (AOR 1.17, 95% CI 1.07-1.28). Screen time was not significantly associated with hypertension or hyperlipidemia.
Conclusions: In this prospective cohort study, higher screen time in adolescence was associated with higher odds of select indicators of cardiometabolic disease in adulthood.
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http://dx.doi.org/10.1007/s11606-022-07984-6 | DOI Listing |
Nutrients
January 2025
Department of Community Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania.
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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!