Age-related change in sedentary behavior during childhood and adolescence: A systematic review and meta-analysis.
Elli KontostoliAndrew P JonesNatalie PearsonLouise FoleyStuart J H BiddleAndrew J AtkinPublished in: Obesity reviews : an official journal of the International Association for the Study of Obesity (2021)
Sedentary behaviors are highly prevalent in youth and may be associated with markers of physical and mental health. This systematic review and meta-analysis aimed to quantify the age-related change in sedentary behavior during childhood and adolescence. Ten electronic databases were searched. Inclusion criteria specified longitudinal observational studies or control group from an intervention; participants aged ≥5 and ≤18 years; a quantitative estimate of the duration of SB; and English language, peer-reviewed publication. Meta-analyses summarized weighted mean differences (WMD) in device-assessed sedentary time and questionnaire-assessed screen-behaviors over 1-, 2-, 3-, or more than 4-year follow-up. Effect modification was explored using meta-regression. Eighty-five studies met inclusion criteria. Device-assessed sedentary time increased by (WMD 95% confidence interval [CI]) 27.9 (23.2, 32.7), 61.0 (50.7, 71.4), 63.7 (53.3, 74.0), and 140.7 (105.1, 176.4) min/day over 1-, 2-, 3-, and more than 4-year follow-up. We observed no effect modification by gender, baseline age, study location, attrition, or quality. Questionnaire-assessed time spent playing video games, computer use, and a composite measure of sedentary behavior increased over follow-up duration. Evidence is consistent in showing an age-related increase in various forms of sedentary behavior; evidence pertaining to variability across socio-demographic subgroups and contemporary sedentary behaviors are avenues for future research.
Keyphrases
- physical activity
- mental health
- meta analyses
- randomized controlled trial
- cross sectional
- depressive symptoms
- systematic review
- magnetic resonance
- young adults
- autism spectrum disorder
- mental illness
- tyrosine kinase
- early life
- high resolution
- current status
- deep learning
- machine learning
- computed tomography
- virtual reality