Sedentary behaviour in youth
Abstract
The purpose of this review is to describe the amount of time children spend in sedentary behaviour and to determine if there are specific factors that associate with sedentary behaviour in children. The following search terms were used to identify relevant articles: sedentary behaviour, inactivity, television, computer, video games, small screen, sitting, prevalence, patterns, correlates, factors and determinants. The databases used to conduct the search included PubMed, PsycINFO, ERIC (Education Resources Information Center) and Academic Search Premier. The studies reviewed were limited to those that sampled children (2-18 years), were written in English and used a measure of sedentary behaviour as the dependent variable. Several studies reported the time spent watching television or the proportion of children at or above a threshold for television viewing (eg, ≥3 h/day). Among the accelerometer studies included, the National Health and Nutrition Examination Survey is the largest and reported ∼6.1, 7.5 and 8.0 h/day mean sedentary time in children 6-11, 12-15 and 16-19 years old, respectively. Taken together, the existing literature across the world indicates a slightly higher level of sedentary behaviour in older children. Higher levels of sedentary behaviour were also reported in non-white children, children from lower socioeconomic status background and children from households with more access to televisions/computers. Lower levels of sedentary behaviour were reported in children whose parents have rules/limitations on screen time.
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Leisure-time screen-based sedentary behaviors can increase risk for adverse cardiometabolic, social, and health outcomes throughout youth and adulthood.
“Leisure-time screen-based sedentary behaviors (e.g., television, computer, videogames) can increase risk for a host of adverse cardiometabolic, social, and health outcomes throughout youth and adulthood (Pate et al., 2011; Sisson et al., 2009; Utter et al., 2003; Sardinha et al., 2008; Lou, 2014; Biswas et al., 2015; Chassiakos et al., 2016).”
From Reciprocal associations between screen time and emotional disorder symptoms during adolescence (2019) · cites this paper as Pate et al., 2011
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“, television, computer, videogames) can increase risk for a host of adverse cardiometabolic, social, and health outcomes throughout youth and adulthood (Pate et al., 2011; Sisson et al., 2009; Utter et al., 2003; Sardinha et al., 2008; Lou, 2014; Biswas et al., 2015; Chassiakos et al., 2016).”
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- Authors
- Pate, R. R., Mitchell, J. A., Byun, W., & Dowda, M.
- Affiliations
- University of South Carolina (US)
- Corresponding author
- Pate, Russell R
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2011-08-11
- Volume
- 45
- Issue
- 11
- Pages
- 906-913
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W2042091688
- Cited by
- 375
- References
- 85
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 17 · 2023: 13 · 2022: 23 · 2021: 29 · 2020: 28 · 2019: 29 · 2018: 33 · 2017: 37 · 2016: 26 · 2015: 45 · 2014: 33 · 2013: 34 · 2012: 12
- FWCI
- 2.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Social Sciences › Education › Child Development and Digital Technology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- sedentary behavior, children, youth, television viewing, screen time, video games, computer use, sitting time, socioeconomic status, accelerometer-measured sedentary time
- MeSH terms
- Acceleration, Adolescent, Adolescent Behavior, Child, Child Behavior, Female, Humans, Leisure Activities, Male, Television, Time Factors, Body Mass Index, Young Adult, Sedentary Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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