Guiding Questions
A1. What is the association between physical activity and health-related outcomes?
Is there a dose-response association (volume, duration, frequency, intensity)?
Does the association vary by type or domain of physical activity?
A2. What is the association between sedentary behaviour and health-related outcomes?
Is there a dose-response association (total volume and the frequency, duration and intensity of interruption)?
Does the association vary by type and domain of sedentary behaviour?
Inclusion Criteria
Population: Children aged 5 to under 18 years of age
Exposure: Greater volume, duration, frequency or intensity of physical activity; greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour.
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity; lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour.
The GRADE Evidence Profiles developed for the 2019 Australian 24-Hour Movement Guidelines for Children and Young People (5-17 years) by Okely et al. (1) were used as a basis for this update for children and adolescents, given the rigor in methods and recency in included evidence. The following modifications were made to the GRADE assessments from the Okely update: 1) evidence from observational studies evaluating associations was upgraded one level if the studies were well-conducted longitudinal studies with no serious risk of bias, to better reflect the certainty in findings regarding associations from such studies and 2) evidence from all studies was downgraded one level if there was only one study, due to inability to assess consistency. The development of the Australian guideline utilized the GRADE-ADOLOPMENT approach, leveraging the work done in Canada in the development of their 24-hour guidelines (2, 3). For each PICO, identified systematic reviews were incorporated into the existing Evidence Profiles according to the study designs included in the review. A summary of findings for each review is provided. In cases where the identified systematic reviews suggested differences in the quality assessment (risk of bias, inconsistency, indirectness, imprecision, or other risk of bias) or overall certainty, the evidence profiles were edited accordingly. Additional evidence reviewed for the US Physical Activity Guidelines Advisory Committee report were included in the draft Evidence Profiles to contextualize the overall body of evidence.
View in own window
Outcomes | Importance |
---|
Physical fitness (e.g. cardiorespiratory, motor development, muscular fitness) | Critical |
Cardiometabolic health (e.g. blood pressure, dyslipidaemia, glucose, insulin resistance) | Critical |
Bone health | Critical |
Adiposity | Critical |
Adverse effects (e.g. injuries and harms) | Critical |
Mental health (e.g. depressive symptoms, self-esteem, anxiety symptoms, ADHD) | Critical |
Cognitive outcomes (e.g. academic performance, executive function) | Critical |
Prosocial behaviour (e.g. conduct problems, peer relations, social inclusion) | Important |
Sleep duration and quality | Important |
Evidence identified
Twenty-one reviews were identified (published from 2017 to 2019) that examined the association between physical activity and/or sedentary behaviour and health-related outcomes among children and adolescents (4–24).
Fourteen reviews examined the relationship between physical activity and health-related outcomes, five reviews examined the relationship between sedentary behaviour and health-related outcomes, and two reviews included both physical activity and sedentary behaviour (). The most commonly reported outcomes in the reviews were measures of adiposity and cardiometabolic health. No reviews were identified that evaluated the association between physical activity and adverse effects, mental health outcomes, or sleep outcomes and no reviews were identified that evaluated the association between sedentary behaviour and physical fitness, adverse effects, cognitive outcomes, or prosocial behaviour.
Furthermore, none of the existing reviews robustly examined whether there was a dose-response association between physical activity or sedentary behaviour and health-related outcomes, whether the association varied by type or domain of physical activity or sedentary behaviour, and whether physical activity modified the effect of sedentary behaviour on mortality.
In most cases, each review was narrowly scoped to look at specific types of physical activity (e.g., high-intensity interval training, school-based physical activity programs) or sedentary behaviour (e.g., objectively-measured sedentary time) and limited inclusion to specific study designs (e.g., only randomized controlled trials).
Few reviews (three) included evidence published into 2019. About half of the reviews included evidence published from database inception through at least 2017; seven reviews searched through 2014, 2015, or 2016 and three reviews did not report search dates. Extracted data for each review is included in Appendix 1A.
None of the systematic reviews were rated as having high credibility based on the AMSTAR 2 instrument. Six were rated as having moderate credibility, 10 were rated as having low credibility, and 5 were rated as having critically low credibility. Given concerns regarding the comprehensiveness and the validity of the results presented in reviews rated as having very low credibility, they were not incorporated into the final Evidence Profiles. presents the ratings for each review according to all the AMSTAR 2 main domains.
Table A.1Systematic Reviews Assessed
View in own window
Author, Year | Behavi our | Outcomes | |
---|
PA | SB | Physical fitness | CM health | Bone health | Adiposity | AEs | Mental health | Cognitive outcomes | Prosocial behaviour | Sleep duration and quality | Last search date | # of included studies | AMSTAR 2 |
---|
Bea, 2017 (4) | X | | | X | | | | | | | | 2015 | 13 | Moderate |
Belmon, 2019 (5) | | X | | | | | | | | | X | Jan 2017 | 45 | Low |
Cao, 2019 (6) | X | | X | | | | | | | | | Feb 2019 | 17 | Low |
Collins, 2018 (7) | X | | | | | X | | | | | | June 2017 | 18 | Low |
Eddolls, 2017 (8) | X | | | X | | X | | | | | | Sept 2016 | 13 | Low |
Errisuriz, 2018 (9) | X | | X | | | X | | | | | | NR | 12 | Critically Low |
Fang, 2019 (10) | | X | | | | X | | | | | | May 2019 | 16 | Low |
Koedijk, 2017 (11) | | X | | | X | | | | | | | Jan 2019 | 17 | Moderate |
Krahenbühl, 2018 (12) | X | | | | X | | | | | | | 2016 | 21 | Critically Low |
Lee, 2018 (13) | X | | | | | X | | | | | | Jan 2014 | 27 | Critically Low |
Marker, 2019 (14) | | X | | | | X | | | | | | June 2018 | 24 | Low |
Marques, 2018 (15) | X | | | | | | | | X | | | 2016 | 51 | Moderate |
Martin, 2017 (16) | X | | | | | X | | | X | | | Mar 2015 | 15 | Moderate |
Miguel-Berges, 2018 (17) | X | | | | | X | | | | | | July 2015 | 36 | Low |
Mohammadi, 2019 (18) | X | X | | | | X | | | | | | Aug 2017 | 17 | Low |
Pozuelo-Carrascosa, 2018 (19) | X | | | X | | | | | | | | Feb 2018 | 19 | Moderate |
Singh, 2019 (20) | X | | | | | | | | X | X | | Sept 2017 | 58 | Critically Low |
Skrede, 2019 (21) | X | X | | X | | | | | | | | April 2018 | 30 | Critically Low |
Stanczykiewicz, 2019 (22) | | X | | | | | | X | | | | NR | 31 | Low |
Verswijveren, 2018 (23) | X | | | X | | | | | | | | 2017 | 29 | Moderate |
Xue, 2019 (24) | X | | | | | | | | X | | | NR | 19 | Low |
Abbreviations: AEs = adverse effects; CM = cardiometabolic; PA = physical activity; SB = sedentary behaviour
Table A.2Credibility Ratings (AMSTAR 2)
View in own window
Author, Year | PICO1 | A priori Methods2 | Study Design Selection3 | Search Strategy4 | Study Selection5 | Data Extraction6 | Excluded Studies7 | Included Studies8 | RoB Assess-ment9 | Funding Sources10 | Statistical Methods11 | Impact of RoB12 | RoB Results13 | Heterogeneity14 | Publication Bias15 | COI16 | Overall Rating17 |
---|
Bea, 2017 (4) | Y | N | N | PY | Y | Y | PY | PY | Y | N | N/A | N/A | Y | N | N/A | Y | Moderate |
Belmon, 2019 (5) | Y | N | N | PY | Y | Y | PY | PY | N | N | N/A | N/A | Y | N | N/A | Y | Low |
Cao, 2019 (6) | Y | N | N | PY | Y | Y | PY | Y | N | N | Y | Y | N | Y | Y | Y | Low |
Collins, 2018 (7) | Y | N | N | PY | Y | Y | N | Y | PY | N | Y | Y | Y | Y | Y | Y | Low |
Eddolls, 2017 (8) | Y | N | N | PY | N | N | PY | N | Y | N | N/A | N/A | Y | Y | N/A | Y | Low |
Errisuriz, 2018 (9) | Y | N | N | N | Y | Y | PY | PY | N | N | N/A | N/A | N | N | N/A | Y | Critically Low |
Fang, 2019 (10) | Y | N | N | PY | Y | N | PY | PY | Y | N | N | N | N | Y | Y | Y | Low |
Koedijk, 2017 (11) | Y | N | N | PY | Y | Y | Y | PY | PY | N | N/A | N/A | Y | Y | N/A | Y | Moderate |
Krahenbühl, 2018 (12) | Y | N | N | PY | N | N | PY | PY | N | N | N/A | N/A | N | N | N/A | Y | Critically Low |
Lee, 2018 (13) | Y | N | N | PY | Y | Y | N | PY | N | N | N/A | N/A | N | Y | N/A | N | Critically Low |
Marker, 2019 (14) | Y | N | N | PY | N | Y | PY | N | N | N | Y | Y | N | Y | Y | Y | Low |
Marques, 2018 (15) | Y | N | N | PY | Y | Y | PY | PY | PY | N | N/A | N/A | Y | Y | N/A | Y | Moderate |
Martin, 2017 (16) | Y | N | N | PY | Y | N | PY | Y | Y | N | N/A | N/A | Y | N | N/A | N | Moderate |
Miguel-Berges, 2018 (17) | Y | N | N | PY | Y | Y | Y | PY | Y | Y | N/A | N/A | N | N | NA | N | Low |
Mohammadi, 2019 (18) | Y | N | N | PY | Y | Y | PY | PY | PY | N | N/A | N/A | Y | Y | N/A | Y | Low |
Pozuelo-Carrascosa, 2018 (19) | Y | N | N | PY | Y | Y | PY | Y | Y | N | Y | N | Y | Y | Y | Y | Moderate |
Singh, 2019 (20) | Y | N | N | PY | Y | Y | N | PY | PY | N | N/A | N/A | Y | Y | N/A | Y | Critically Low |
Skrede, 2019 (21) | Y | N | N | N | Y | N | PY | PY | N | N | N | N | N | N | N/A | Y | Critically Low |
Stanczykiewicz, 2019 (22) | Y | N | N | Y | Y | Y | PY | Y | PY | N | Y | N | Y | Y | Y | Y | Low |
Verswijveren, 2018 (23) | Y | N | N | PY | Y | Y | PY | PY | PY | N | N/A | N/A | Y | Y | N/A | Y | Moderate |
Xue, 2019 (24) | Y | N | N | PY | Y | N | PY | Y | PY | N | N | N | N | Y | Y | Y | Low |
Abbreviations: COI = conflict of interest; N = no; PICO = population, intervention, comparator, outcome; PY = partial yes; RoB = risk of bias; CM = cardiometabolic; PA = physical activity; SB = sedentary behaviour; Y = yes
- 1
Did the research questions and inclusion criteria for the review include the components of PICO?
- 2
Did the report of the review contain an explicit statement that the review methods were established prior to the conduct of the review and did the report justify any significant deviations from the protocol?
- 3
Did the review authors explain their selection of the study designs for inclusion in the review?
- 4
Did the review authors use a comprehensive literature search strategy?
- 5
Did the review authors perform study selection in duplicate?
- 6
Did the review authors perform data extraction in duplicate?
- 7
Did the review authors provide a list of excluded studies and justify the exclusions?
- 8
Did the review authors describe the included studies in adequate detail?
- 9
Did the review authors use a satisfactory technique for assessing the risk of bias (RoB) in individual studies that were included in the review?
- 10
Did the review authors report on the sources of funding for the studies included in the review?
- 11
If meta-analysis was performed did the review authors use appropriate methods for statistical combination of results?
- 12
If meta-analysis was performed, did the review authors assess the potential impact of RoB in individual studies on the results of the meta-analysis or other evidence synthesis?
- 13
Did the review authors account for RoB in individual studies when interpreting/discussing the results of the review?
- 14
Did the review authors provide a satisfactory explanation for, and discussion of, any heterogeneity observed in the results of the review?
- 15
If they performed quantitative synthesis did the review authors carry out an adequate investigation of publication bias (small study bias) and discuss its likely impact on the results of the review?
- 16
Did the review authors report any potential sources of conflict of interest, including any funding they received for conducting the review?
- 17
Shea et al. 2017. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. (25)
A.1. Physical Activity
Table A.1.a. Physical fitness and physical activity, children and adolescents (PDF, 135K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Physical fitness (e.g., cardiorespiratory, motor development, muscular fitness)
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles developed to support the development of the Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.b. Cardiometabolic health and physical activity, children and adolescents (PDF, 144K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Cardiometabolic health (e.g., blood pressure, dyslipidaemia, glucose, insulin resistance)
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.c. Bone health and physical activity, children and adolescents (PDF, 113K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Bone health
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.d. Adiposity/body composition and physical activity, children and adolescents (PDF, 126K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Adiposity/Body composition
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.e. Adverse effects and physical activity, children and adolescents (PDF, 90K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Adverse effects
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.f. Mental health and physical activity, children and adolescents (PDF, 131K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Mental health (e.g., depressive symptoms, self-esteem, anxiety symptoms, ADHD)
*Importance: CRITCAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.g. Cognitive outcomes and physical activity, children and adolescents (PDF, 108K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Cognitive outcomes (e.g., academic performance, executive function)
*Importance: CRITCAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.h. Prosocial behaviour and physical activity, children and adolescents (PDF, 101K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Prosocial behaviour (e.g., conduct problems, peer relations, social inclusion)
*Importance: IMPORTANT
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.1.I. Sleep duration and quality and physical activity, children and adolescents (PDF, 51K)
Questions: What is the association between physical activity and health-related outcomes? Is there a dose response association (volume, duration, frequency, intensity)? Does the association vary by type or domain of PA?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, duration, frequency, or intensity of physical activity
Comparison: No physical activity or lesser volume, duration, frequency, or intensity of physical activity
Outcome: Sleep duration and quality
*Importance: IMPORTANT
No GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years)(26) and no systematic reviews identified by WHO.
A.2. Sedentary Behaviour
Table A.2.a. Physical fitness and sedentary behaviour, children and adolescents (PDF, 111K)
Questions: What is the association between sedentary behaviour and health-related outcomes? Is there a dose response association (total volume and the frequency, duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Physical fitness (e.g., cardiorespiratory, motor development, muscular fitness)
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.b. Cardiometabolic health and sedentary behaviour, children and adolescents (PDF, 101K)
Questions: What is the association between sedentary behaviour and health-related outcomes? Is there a dose response association (total volume and the frequency, duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Cardiometabolic health (e.g., blood pressure, dyslipidaemia, glucose, insulin resistance)
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.c. Bone health and sedentary behaviour, children and adolescents (PDF, 87K)
Questions: What is the association between sedentary behaviour and health-related outcomes? Is there a dose response association (total volume and the frequency, duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Bone health
*Importance: CRITICAL
Bone health outcomes not reviewed in Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years) (26). Red font denotes information from WHO update using review of existing systematic reviews.
Table A.2.d. Adiposity/body composition and sedentary behaviour, children and adolescents (PDF, 112K)
Questions: What is the association between sedentary behaviour and health-related outcomes? Is there a dose response association (total volume and the frequency, duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Adiposity/Body composition
*Importance: CRITICAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.e. Adverse effects and sedentary behaviour, children and adolescents (PDF, 50K)
Questions: What is the association between sedentary behaviour and health-related outcomes? Is there a dose response association (total volume and the frequency, duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Adverse effects
*Importance: CRITICAL
No GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years)(26) and no systematic reviews identified by WHO.
Table A.2.f. Mental health and sedentary behaviour, children and adolescents (PDF, 94K)
Questions: What is the association between sedentary behaviour duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Mental health (e.g., depressive symptoms, self-esteem, anxiety symptoms, ADHD)
*Importance: CRITCAL
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.g. Cognitive outcomes and sedentary behaviour, children and adolescents (PDF, 96K)
Questions: What is the association between sedentary behaviour duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Cognitive outcomes (e.g., academic performance, executive function)
*Importance: CRITCAL
Black font is from original GRADE Evidence Profiles for academic achievement from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.h. Prosocial behaviour and sedentary behaviour, children and adolescents (PDF, 103K)
Questions: What is the association between sedentary behaviour duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Prosocial behaviour (e.g., conduct problems, peer relations, social inclusion)
*Importance: IMPORTANT
Black font is from original GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years).(26) Red font denotes additions based on WHO update using review of existing systematic reviews.
Table A.2.i. Sleep duration and quality and sedentary behaviour, children and adolescents (PDF, 88K)
Questions: What is the association between sedentary behaviour duration and intensity of interruption)? Does the association vary by type and domain of sedentary behaviour?
Population: Children aged 5-under 18 years of age
Exposure: Greater volume, decreased frequency, duration or intensity of interruption of sedentary behaviour
Comparison: Lesser volume, increased frequency, duration or intensity of interruption of sedentary behaviour
Outcome: Sleep duration and quality
*Importance: IMPORTANT
No GRADE Evidence Profiles from Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (12-17 years)(26) and no systematic reviews identified by WHO.
References
- 1.
Okely
AD, Ghersi
D, Loughran
SP, Cliff
DP, Shilton
T, Jones
RA, et al. Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (13-17 years): An Integration of Physical Activity, Sedentary Behaviour, and Sleep — Research Report. Australian Government, Department of Health.; 2019. Contract No.: Available from
https://www1.health.gov.au/internet/main/publishing.nsf/Content/ti-5-17years. (accessed 29 July 2020)..
- 2.
Carson
V, Hunter
S, Kuzik
N, Gray
CE, Poitras
VJ, Chaput
JP, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme. 2016/06/17 ed2016. p. S240–65. [
PubMed: 27306432]
- 3.
Poitras
VJ, Gray
CE, Borghese
MM, Carson
V, Chaput
JP, Janssen
I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme. 2016/06/17 ed2016. p. S197–239. [
PubMed: 27306431]
- 4.
Bea
JW, Blew
RM, Howe
C, Hetherington-Rauth
M, Going
SB. Resistance Training Effects on Metabolic Function Among Youth: A Systematic Review. Pediatr Exerc Sci. 2017/01/05 ed2017. p. 297–315. [
PMC free article: PMC6240908] [
PubMed: 28050919]
- 5.
Belmon
LS, van Stralen
MM, Busch
V, Harmsen
IA, Chinapaw
MJM. What are the determinants of children’s sleep behavior? A systematic review of longitudinal studies. Sleep Med Rev. 2018/12/12 ed2019. p. 60–70. [
PubMed: 30529431]
- 6.
Cao
M, Quan
M, Zhuang
J. Effect of High-Intensity Interval Training versus Moderate-Intensity Continuous Training on Cardiorespiratory Fitness in Children and Adolescents: A Meta-Analysis. Int J Environ Res Public Health. 2019/05/06 ed2019. [
PMC free article: PMC6539300] [
PubMed: 31052205]
- 7.
Collins
H, Fawkner
S, Booth
JN, Duncan
A. The effect of resistance training interventions on weight status in youth: a meta-analysis. Sports medicine - open. 2018/08/22 ed2018. p. 41. [
PMC free article: PMC6102165] [
PubMed: 30128805]
- 8.
Eddolls
WTB, McNarry
MA, Stratton
G, Winn
CON, Mackintosh
KA. High-Intensity Interval Training Interventions in Children and Adolescents: A Systematic Review. Sports Med. 2017/06/24 ed2017. p. 2363–74. [
PMC free article: PMC5633633] [
PubMed: 28643209]
- 9.
Errisuriz
VL, Golaszewski
NM, Born
K, Bartholomew
JB. Systematic Review of Physical Education-Based Physical Activity Interventions Among Elementary School Children. J Prim Prev. 2018/05/01 ed2018. p. 303–27. [
PubMed: 29705883]
- 10.
Fang
K, Mu
M, Liu
K, He
Y. Screen time and childhood overweight/obesity: A systematic review and meta-analysis. Child Care Health Dev. 2019/07/05 ed2019. p. 744–53. [
PubMed: 31270831]
- 11.
Koedijk
JB, van Rijswijk
J, Oranje
WA, van den Bergh
JP, Bours
SP, Savelberg
HH, et al. Sedentary behaviour and bone health in children, adolescents and young adults: a systematic review. Osteoporos Int. 2017/05/27 ed2017. p. 2507–19. [
PMC free article: PMC5550522] [
PubMed: 28547135]
- 12.
Krahenbuhl
T, Guimaraes
RF, Barros Filho
AA, Goncalves
EM. Bone Geometry and Physical Activity in Children and Adolescents: Systematic Review. Rev Paul Pediatr2018. p. 230–7. [
PMC free article: PMC6038793] [
PubMed: 29412432]
- 13.
Lee
JE, Pope
Z, Gao
Z. The Role of Youth Sports in Promoting Children’s Physical Activity and Preventing Pediatric Obesity: A Systematic Review. Behav Med. 2016/06/24 ed2018. p. 62–76. [
PubMed: 27337530]
- 14.
Marker
C, Gnambs
T, Appel
M. Exploring the myth of the chubby gamer: A meta-analysis on sedentary video gaming and body mass. Soc Sci Med. 2019/07/03 ed2019. p. 112325. [
PubMed: 31262505]
- 15.
Marques
A, Santos
DA, Hillman
CH, Sardinha
LB. How does academic achievement relate to cardiorespiratory fitness, self-reported physical activity and objectively reported physical activity: a systematic review in children and adolescents aged 6-18 years. Br J Sports Med. 2017/10/17 ed2018. p. 1039. [
PubMed: 29032365]
- 16.
Martin
R, Murtagh
EM. Effect of Active Lessons on Physical Activity, Academic, and Health Outcomes: A Systematic Review. Research quarterly for exercise and sport. 2017/03/23 ed2017. p. 149–68. [
PubMed: 28328311]
- 17.
Miguel-Berges
ML, Reilly
JJ, Moreno Aznar
LA, Jimenez-Pavon
D. Associations Between Pedometer-Determined Physical Activity and Adiposity in Children and Adolescents: Systematic Review. Clin J Sport Med. 2017/07/14 ed2018. p. 64–75. [
PubMed: 28704256]
- 18.
Mohammadi
S, Jalaludin
MY, Su
TT, Dahlui
M, Mohamed
MNA, Majid
HA. Dietary and physical activity patterns related to cardio-metabolic health among Malaysian adolescents: a systematic review. BMC Public Health. 2019/03/02 ed2019. p. 251. [
PMC free article: PMC6396523] [
PubMed: 30819123]
- 19.
Pozuelo-Carrascosa
DP, Cavero-Redondo
I, Herraiz-Adillo
A, Diez-Fernandez
A, Sanchez-Lopez
M, Martinez-Vizcaino
V. School-Based Exercise Programs and Cardiometabolic Risk Factors: A Meta-analysis. Pediatrics. 2018/10/20 ed2018.
- 20.
Singh
AS, Saliasi
E, van den Berg
V, Uijtdewilligen
L, de Groot
RHM, Jolles
J, et al. Effects of physical activity interventions on cognitive and academic performance in children and adolescents: a novel combination of a systematic review and recommendations from an expert panel. Br J Sports Med. 2018/08/01 ed2019. p. 640–7. [
PubMed: 30061304]
- 21.
Skrede
T, Steene-Johannessen
J, Anderssen
SA, Resaland
GK, Ekelund
U. The prospective association between objectively measured sedentary time, moderate-to-vigorous physical activity and cardiometabolic risk factors in youth: a systematic review and meta-analysis. Obes Rev. 2018/10/03 ed2019. p. 55–74. [
PubMed: 30270500]
- 22.
Stanczykiewicz
B, Banik
A, Knoll
N, Keller
J, Hohl
DH, Rosinczuk
J, et al. Sedentary behaviors and anxiety among children, adolescents and adults: a systematic review and meta-analysis. BMC Public Health. 2019/05/02 ed2019. p. 459. [
PMC free article: PMC6492316] [
PubMed: 31039760]
- 23.
Verswijveren
S, Lamb
KE, Bell
LA, Timperio
A, Salmon
J, Ridgers
ND. Associations between activity patterns and cardio-metabolic risk factors in children and adolescents: A systematic review. PLoS One. 2018/08/17 ed2018. p. e0201947. [
PMC free article: PMC6095515] [
PubMed: 30114269]
- 24.
Xue
Y, Yang
Y, Huang
T. Effects of chronic exercise interventions on executive function among children and adolescents: a systematic review with meta-analysis. Br J Sports Med. 2019/02/10 ed2019. [
PubMed: 30737201]
- 25.
Shea
BJ, Reeves
BC, Wells
G, Thuku
M, Hamel
C, Moran
J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008. [
PMC free article: PMC5833365] [
PubMed: 28935701]
- 26.
Australia Co. Australian 24-Hour Movement Guidelines for Children (5-12 years) and Young People (13-17 years): An Integration of Physical Activity, Sedentary Behaviour, and Sleep. 2019. p. 148.
- 27.
2018 Physical Activity Guidelines Advisory Committee. 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Washington, DC. 2018. p. 1–779.
- 28.
Carson
V, Ridgers
ND, Howard
BJ, Winkler
EA, Healy
GN, Owen
N, et al. Light-intensity physical activity and cardiometabolic biomarkers in US adolescents. PLoS One. 2013;8(8):e71417. [
PMC free article: PMC3739773] [
PubMed: 23951157]
- 29.
Aggio
D, Ogunleye
AA, Voss
C, Sandercock
GR. Temporal relationships between screen-time and physical activity with cardiorespiratory fitness in English schoolchildren: a 2-year longitudinal study. Prev Med. 2012;55(1):37–9. [
PubMed: 22561029]
- 30.
Hjorth
MF, Chaput
JP, Michaelsen
K, Astrup
A, Tetens
I, Sjodin
A. Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8-11 year-old Danish children: a repeated-measures study. BMC Public Health. 2013;13:808. [
PMC free article: PMC3846279] [
PubMed: 24010811]
- 31.
- 32.
Aggio
D, Smith
L, Hamer
M. Effects of reallocating time in different activity intensities on health and fitness: a cross sectional study. Int J Behav Nutr Phys Act. 2015;12:83. [
PMC free article: PMC4482052] [
PubMed: 26104041]
- 33.
Aires
L, Pratt
M, Lobelo
F, Santos
RM, Santos
MP, Mota
J. Associations of cardiorespiratory fitness in children and adolescents with physical activity, active commuting to school, and screen time. J Phys Act Health. 2011;8: Suppl 2:S198–S205. [
PubMed: 21918233]
- 34.
Ciesla
E, Mleczko
E, Bergier
J, Markowska
M, Nowak-Starz
G. Health-Related Physical Fitness, BMI, physical activity and time spent at a computer screen in 6 and 7-year-old children from rural areas in Poland. Ann Agric Environ Med. 2014;21(3):617–21. [
PubMed: 25292140]
- 35.
Dencker
M, Bugge
A, Hermansen
B, Andersen
LB. Objectively measured daily physical activity related to aerobic fitness in young children. J Sports Sci. 2010;28(2):139–45. [
PubMed: 20035491]
- 36.
Dowda
M, Pfeiffer
KA, Lobelo
F, Porter
DE, Pate
RR. Cardiorespiratory fitness and proximity to commercial physical activity facilities among 12th grade girls. J Adolesc Health. 2012;50(5):497–502. [
PMC free article: PMC3336089] [
PubMed: 22525114]
- 37.
Drenowatz
C, Kobel
S, Kettner
S, Kesztyus
D, Steinacker
JM. Interaction of sedentary behaviour, sports participation and fitness with weight status in elementary school children. Eur J Sport Sci. 2014;14(1):100–5. [
PubMed: 24533500]
- 38.
Filho
VCB, da Silva Lopes
A, Bozza
R, Rech
CR, de Campos
W. Correlates of cardiorespiratory and muscular fitness among Brazilian adolescents. Am J Health Behav. 2014;38(1):42–52. [
PubMed: 24034679]
- 39.
Grontved
A, Ried-Larsen
M, Froberg
K, Wedderkopp
N, Brage
S, Kristensen
PL, et al. Screen time viewing behaviors and isometric trunk muscle strength in youth. Med Sci Sports Exerc. 2013;45(10):1975–80. [
PubMed: 24048320]
- 40.
Hay
J, Maximova
K, Durksen
A, Carson
V, Rinaldi
R, Torrance
B, et al. Physical activity intensity and cardiometabolic risk in youth. Arch Pediatr Adolesc Med. 2012;166(11):1022–9. [
PubMed: 22965682]
- 41.
Lämmle
L, Woll
A, Mensink
GB, Bos
K. Distal and proximal factors of health behaviors and their associations with health in children and adolescents. Int J Environ Res Public Health. 2013;10(7):2944–78. [
PMC free article: PMC3734470] [
PubMed: 23863614]
- 42.
Machado-Rodrigues
AM, MJ
C-e-S, Mota
J, Padez
C, Ronque
E, Cumming
SP, et al. Cardiorespiratory fitness, weight status and objectively measured sedentary behaviour and physical activity in rural and urban Portuguese adolescents. J Child Health Care. 2012;16(2):166–77. [
PubMed: 22363047]
- 43.
Martinez-Gomez
D, Ortega
FB, Ruiz
JR, Vicente-Rodriguez
G, Veiga
OL, Widhalm
K, et al. Excessive sedentary time and low cardiorespiratory fitness in European adolescents: the HELENA study. Arch Dis Child. 2011;96(3):240–6. [
PubMed: 21220264]
- 44.
Poethko-Muller
C, Krug
S. Social and health related risk factors for low cardio respiratory fitness in German adolescents: Results of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS). J Public Health. 2014;22(2):187–96.
- 45.
Ruiz
JR, Ortega
FB, Castillo
R, Martin-Matillas
M, Kwak
L, Vicente-Rodriguez
G, et al. Physical activity, fitness, weight status, and cognitive performance in adolescents.. J Pediatr. 2010;157(6):917–22. [
PubMed: 20673915]
- 46.
Sandercock
GR, Ogunleye
AA. Independence of physical activity and screen time as predictors of cardiorespiratory fitness in youth. Pediatr Res. 2013;73(5):692–7. [
PubMed: 23417036]
- 47.
Santos
R, Mota
J, Okely
AD, Pratt
M, Moreira
C, MJ
C-e-S, et al. The independent associations of sedentary behaviour and physical activity on cardiorespiratory fitness. Br J Sports Med. 2014;48(20):1508–12. [
PubMed: 23410883]
- 48.
Simhaee
D, Corriveau
N, Gurm
R, Geiger
Z, Kline-Rogers
E, Goldberg
C, et al. Recovery heart rate: an indicator of cardiovascular risk among middle school children. Pediatr Cardiol. 2013;34(6):1431–7. [
PubMed: 23483242]
- 49.
Tucker
JS, Martin
S, Jackson
AW, Morrow
JR, Jr., Greenleaf
CA, Petrie
TA. Relations between sedentary behavior and FITNESSGRAM healthy fitness zone achievement and physical activity. Journal of physical activity & health. 2014;11(5):1006–11. [
PubMed: 23799274]
- 50.
Berentzen
NE, Smit
HA, van
RL, Gehring
U, Kerkhof
M, Postma
DS, et al. Screen time, adiposity and cardiometabolic markers: mediation by physical activity, not snacking, among 11-year-old children. Int J Obes. 2014;38(10):1317–23. [
PubMed: 24946910]
- 51.
Dumith
SC, Garcia
LM, da Silva
KS, Menezes
AM, Hallal
PC. Predictors and health consequences of screen-time change during adolescence-1993 Pelotas (Brazil) birth cohort study. J Adolesc Health. 2012;51:(6 Suppl):S16–S21. [
PMC free article: PMC3508419] [
PubMed: 23283154]
- 52.
Gopinath
B, Hardy
LL, Kifley
A, Baur
LA, Mitchell
P. Activity behaviors in schoolchildren and subsequent 5-yr change in blood pressure. Med Sci Sports Exerc. 2014;46(4):724–9. [
PubMed: 24056270]
- 53.
Grontved
A, Ried-Larsen
M, Moller
NC, Kristensen
PL, Wedderkopp
N, Froberg
K, et al. Youth screen-time behaviour is associated with cardiovascular risk in young adulthood: the European Youth Heart Study. Eur J Prev Cardiol. 2014;21(1):49–56. [
PubMed: 22767966]
- 54.
Hjorth
MF, Chaput
JP, Damsgaard
CT, Dalskov
SM, Andersen
R, Astrup
A, et al. Low physical activity level and short sleep duration are associated with an increased cardio-metabolic risk profile: a longitudinal study in 8-11 year old Danish children. PLoS One. 2014;9(8):e104677. [
PMC free article: PMC4125285] [
PubMed: 25102157]
- 55.
Wennberg
P, Gustafsson
PE, Dunstan
DW, Wennberg
M, Hammarstrom
A. Television viewing and low leisure-time physical activity in adolescence independently predict the metabolic syndrome in mid-adulthood. Diabetes Care. 2013;36(7):2090–7. [
PMC free article: PMC3687313] [
PubMed: 23340896]
- 56.
Atkin
AJ, Ekelund
U, Moller
NC, Froberg
K, Sardinha
LB, Andersen
LB, et al. Sedentary time in children: influence of accelerometer processing on health relations. Med Sci Sports Exerc. 2013;45(6):1097–104. [
PubMed: 23274612]
- 57.
Berendes
A, Meyer
T, Hulpke-Wette
M, Herrmann-Lingen
C. Association of elevated blood pressure with low distress and good quality of life: results from the nationwide representative German Health Interview and Examination Survey for Children and Adolescents. Psychosom Med. 2013;75(4):422–8. [
PubMed: 23645707]
- 58.
Chaput
JP, Saunders
TJ, Mathieu
ME, Henderson
M, Tremblay
MS, O’Loughlin
J, et al. Combined associations between moderate to vigorous physical activity and sedentary behaviour with cardiometabolic risk factors in children. Appl Physiol Nutr Metab. 2013;38(5):477–83. [
PubMed: 23668753]
- 59.
Chinapaw
MJ, Altenburg
TM, van
EM, Gemke
RJ, Vrijkotte
TG. Screen time and cardiometabolic function in Dutch 5-6 year olds: cross-sectional analysis of the ABCD-study. BMC Public Health. 2014;14:933. [
PMC free article: PMC4169832] [
PubMed: 25200635]
- 60.
Colley
RC, Garriguet
D, Janssen
I, Wong
SL, Saunders
TJ, Carson
V, et al. The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: results from the Canadian Health Measures Survey. BMC Public Health. 2013;13:200. [
PMC free article: PMC3599834] [
PubMed: 23497190]
- 61.
Ekelund
U, Luan
J, Sherar
LB, Esliger
DW, Griew
P, Cooper
A, et al. Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents.[Erratum appears in JAMA. 2012 May 9;307(18):1915 Note: Sardinha L [corrected to Sardinha, L B]; Anderssen, S A [corrected to Anderson, L B]]. JAMA. 2012;307(7):704–12. [
PMC free article: PMC3793121] [
PubMed: 22337681]
- 62.
Fang
YL, Liang
L, Fu
JF, Gong
CX, Xiong
F, Liu
GL, et al. Level of non-high-density-lipoprotein cholesterol and its related factors in Chinese Han students. Hong Kong J Paediatr. 2013;18(4):210–6.
- 63.
Giussani
M, Antolini
L, Brambilla
P, Pagani
M, Zuccotti
G, Valsecchi
MG, et al. Cardiovascular risk assessment in children: role of physical activity, family history and parental smoking on BMI and blood pressure. J Hypertens. 2013;31(5):983–92. [
PubMed: 23425707]
- 64.
Gopinath
B, Baur
LA, Hardy
LL, Kifley
A, Rose
KA, Wong
TY, et al. Relationship between a range of sedentary behaviours and blood pressure during early adolescence. J Hum Hypertens. 2012;26(6):350–6. [
PubMed: 21614023]
- 65.
Hardy
L, E
D-W, Thrift
A, Okely
A, Baur
L. Screen time and metabolic risk factors among adolescents. Pediatr Adolesc Med. 2010;164(7):643–9. [
PubMed: 20603465]
- 66.
Henderson
M, Gray-Donald
K, Mathieu
ME, Barnett
TA, Hanley
JA, O’Loughlin
J, et al. How are physical activity, fitness, and sedentary behavior associated with insulin sensitivity in children?
Diabetes Care. 2012;35(6):1272–8. [
PMC free article: PMC3357250] [
PubMed: 22492585]
- 67.
Henderson
M, Gray-Donald
K, Rabasa-Lhoret
R, Bastard
JP, Barnett
TA, Benedetti
A, et al. Insulin secretion and its association with physical activity, fitness and screen time in children. Obesity. 2014;22(2):504–11. [
PubMed: 24030901]
- 68.
Martinez-Gomez
D, Rey-Lopez
JP, Chillon
P, Gomez-Martinez
S, Vicente-Rodriguez
G, Martin-Matillas
M, et al. Excessive TV viewing and cardiovascular disease risk factors in adolescents. The AVENA cross-sectional study. BMC Public Health. 2010;10:274. [
PMC free article: PMC2892447] [
PubMed: 20500845]
- 69.
Pahkala
K, Heinonen
OJ, Lagstrom
H, Hakala
P, Hakanen
M, Hernelahti
M, et al. Clustered metabolic risk and leisure-time physical activity in adolescents: effect of dose?
Br J Sports Med. 2012;46(2):131–7. [
PubMed: 20961920]
- 70.
Rey-Lopez
JP, Bel-Serrat
S, Santaliestra-Pasias
A, de Moraes
AC, Vicente-Rodriguez
G, Ruiz
JR, et al. Sedentary behaviour and clustered metabolic risk in adolescents: the HELENA study. Nutr Metab Cardiovasc Dis. 2013;23(10):1017–24. [
PubMed: 22906564]
- 71.
Saunders
TJ, Tremblay
MS, Mathieu
ME, Henderson
M, O’Loughlin
J, Tremblay
A, et al. Associations of sedentary behavior, sedentary bouts and breaks in sedentary time with cardiometabolic risk in children with a family history of obesity. PLoS One. 2013;8(11):e79143. [
PMC free article: PMC3835898] [
PubMed: 24278117]
- 72.
Sisson
SB, Shay
CM, Camhi
SM, Short
KR, Whited
T. Sitting and cardiometabolic risk factors in U.S. adolescents. J Allied Health. 2013;42(4):236–42. [
PubMed: 24326921]
- 73.
Staiano
AE, Harrington
DM, Broyles
ST, Gupta
AK, Katzmarzyk
PT. Television, adiposity, and cardiometabolic risk in children and adolescents. Am J Prev Med. 2013;44(1):40–7. [
PMC free article: PMC3527837] [
PubMed: 23253648]
- 74.
Stamatakis
E, Coombs
N, Jago
R, Gama
A, Mourao
I, Nogueira
H, et al. Type-specific screen time associations with cardiovascular risk markers in children. Am J Prev Med. 2013;44(5):481–8. [
PubMed: 23597812]
- 75.
Vaisto
J, Eloranta
AM, Viitasalo
A, Tompuri
T, Lintu
N, Karjalainen
P, et al. Physical activity and sedentary behaviour in relation to cardiometabolic risk in children: cross-sectional findings from the Physical Activity and Nutrition in Children (PANIC) Study. Int J Behav Nutr Phys Act. 2014;11:55. [
PMC free article: PMC4008488] [
PubMed: 24766669]
- 76.
Yoshinaga
M, Hatake
S, Tachikawa
T, Shinomiya
M, Miyazaki
A, Takahashi
H. Impact of lifestyles of adolescents and their parents on cardiovascular risk factors in adolescents. J Atheroscler Thromb. 2011;18(11):981–90. [
PubMed: 21836372]
- 77.
You
MA, Son
YJ. Prevalence of metabolic syndrome and associated risk factors among Korean adolescents: analysis from the Korean national survey. Asia Pac J Public Health. 2012;24(3):464–71. [
PubMed: 21527432]
- 78.
Carson
V, Janssen
I. Volume, patterns, and types of sedentary behavior and cardio-metabolic health in children and adolescents: a cross-sectional study. BMC Public Health. 2011;11:274. [
PMC free article: PMC3112118] [
PubMed: 21542910]
- 79.
Barlett
ND, Gentile
DA, Barlett
CP, Eisenmann
JC, Walsh
DA. Sleep as a mediator of screen time effects on US children’s health outcomes: A prospective study. J Child Media. 2012;6(1):37–50.
- 80.
Basterfield
L, Pearce
MS, Adamson
AJ, Frary
JK, Parkinson
KN, Wright
CM, et al. Physical activity, sedentary behavior, and adiposity in English children. Am J Prev Med. 2012;42(5):445–51. [
PubMed: 22516483]
- 81.
Basterfield
L, Pearce
MS, Adamson
AJ, Reilly
JK, Parkinson
KN, Reilly
JJ, et al. Effect of choice of outcome measure on studies of the etiology of obesity in children. Ann Epidemiol. 2012;22(12):888–91. [
PubMed: 23084839]
- 82.
- 83.
Drenowatz
C, Kobel
S, Kettner
S, Kesztyus
D, Wirt
T, Dreyhaupt
J, et al. Correlates of weight gain in German children attending elementary school. Prev Med. 2013;57(4):310–4. [
PubMed: 23769901]
- 84.
Fuller-Tyszkiewicz
M, Skouteris
H, Hardy
LL, Halse
C. The associations between TV viewing, food intake, and BMI. A prospective analysis of data from the Longitudinal Study of Australian Children. Appetite. 2012;59(3):945–8. [
PubMed: 23000277]
- 85.
Hands
BP, Chivers
PT, Parker
HE, Beilin
L, Kendall
G, Larkin
D. The associations between physical activity, screen time and weight from 6 to 14 yrs: The Raine Study. J Sci Med Sport. 2011;14(5):397–403. [
PubMed: 21531620]
- 86.
Hjorth
MF. Fatness predicts decreased physical activity and increased sedentary time, but not vice versa: Support from a longitudinal study in 8- to 11-year-old children. Int J Obes. 2014;38(7):959–65. [
PubMed: 24304596]
- 87.
Kwon
S, Burns
TL, Levy
SM, Janz
KF. Which contributes more to childhood adiposity-high levels of sedentarism or low levels of moderate-through-vigorous physical activity? The Iowa Bone Development Study. J Pediatr. 2013;162(6):1169–74. [
PMC free article: PMC3664130] [
PubMed: 23305957]
- 88.
Lin
LJ, Chang
HY, Luh
DL, Hurng
BS, Yen
LL. The trajectory and the related physical and social determinants of body mass index in elementary school children: results from the child and adolescent behaviors in long-term evolution study. J Obes. 2014;2014:728762. [
PMC free article: PMC4119650] [
PubMed: 25114800]
- 89.
Magee
CA, Caputi
P, Iverson
DC. Patterns of health behaviours predict obesity in Australian children. J Paediatr Child Health. 2013;49(4):291–6. [
PubMed: 23574555]
- 90.
Miller
DP. Associations between the home and school environments and child body mass index. Soc Sci Med. 2011;72(5):677–84. [
PubMed: 21227558]
- 91.
Olafsdottir
S, Berg
C, Eiben
G, Lanfer
A, Reisch
L, Ahrens
W, et al. Young children’s screen activities, sweet drink consumption and anthropometry: results from a prospective European study. Eur J Clin Nutr. 2014;68(2):223–8. [
PubMed: 24253759]
- 92.
Wijga
AH, Scholtens
S, Bemelmans
WJ, Kerkhof
M, Koppelman
GH, Brunekreef
B, et al. Diet, Screen Time, Physical Activity, and Childhood Overweight in the General Population and in High Risk Subgroups: Prospective Analyses in the PIAMA Birth Cohort. J Obes. 2010;2010. [
PMC free article: PMC2915806] [
PubMed: 20721356]
- 93.
Williams
SM, Taylor
RW, Taylor
BJ. Secular changes in BMI and the associations between risk factors and BMI in children born 29 years apart. Pediatr Obes. 2013;8(1):21–30. [
PubMed: 23001951]
- 94.
Chen
YC, Tu
YK, Huang
KC, Chen
PC, Chu
DC, Lee
YL. Pathway from central obesity to childhood asthma. Physical fitness and sedentary time are leading factors. Am J Respir Crit Care Med. 2014;189(10):1194–203. [
PubMed: 24669757]
- 95.
Mitchell
JA, Pate
RR, Beets
MW, Nader
PR. Time spent in sedentary behavior and changes in childhood BMI: a longitudinal study from ages 9 to 15 years. Int J Obes. 2013;37(1):54–60. [
PubMed: 22430304]
- 96.
Mitchell
JA, Rodriguez
D, Schmitz
KH, udrain-McGovern
J. Greater screen time is associated with adolescent obesity: a longitudinal study of the BMI distribution from Ages 14 to 18. Obesity. 2013;21(3):572–5. [
PMC free article: PMC3630469] [
PubMed: 23592665]
- 97.
Altenburg
TM, Singh
AS, van
MW, Brug
J, Chinapaw
MJ. Direction of the association between body fatness and self-reported screen time in Dutch adolescents. Int J Behav Nutr Phys Act. 2012;9:4. [
PMC free article: PMC3398280] [
PubMed: 22273542]
- 98.
Augustin
NH, Mattocks
C, Cooper
AR, Ness
AR, Faraway
JJ. Modelling fat mass as a function of weekly physical activity profiles measured by actigraph accelerometers. Physiol Meas. 2012;33(11):1831–9. [
PubMed: 23110964]
- 99.
Barnett
TA, O’Loughlin
J, Sabiston
CM, Karp
I, Belanger
M, Van
HA, et al. Teens and screens: the influence of screen time on adiposity in adolescents. Am J Epidemiol. 2010;172(3):255–62. [
PubMed: 20616201]
- 100.
- 101.
Gilbert-Diamond
D, Li
Z, chi-Mejia
AM, McClure
AC, Sargent
JD. Association of a television in the bedroom with increased adiposity gain in a nationally representative sample of children and adolescents. Jama Pediatr. 2014;168(5):427–34. [
PMC free article: PMC4141563] [
PubMed: 24589630]
- 102.
Veitch
J, van Stralen
MM, Chinapaw
MJ, Te Velde
SJ, Crawford
D, Salmon
J, et al. The neighborhood social environment and body mass index among youth: a mediation analysis. Int J Behav Nutr Phys Act. 2012;9:31. [
PMC free article: PMC3331800] [
PubMed: 22429957]
- 103.
- 104.
Van den Bulck
J, Hofman
A. The television-to-exercise ratio is a predictor of overweight in adolescents: results from a prospective cohort study with a two year follow up. Prev Med. 2009;48(4):368–71. [
PubMed: 19463482]
- 105.
Mamun
AA, O’Callaghan
MJ, Williams
G, Najman
JM. Television watching from adolescence to adulthood and its association with BMI, waist circumference, waist-to-hip ratio and obesity: a longitudinal study. Public Health Nutr. 2013;16(1):54–64. [
PMC free article: PMC10271642] [
PubMed: 22687709]
- 106.
- 107.
Huang
HM, Chien
LY, Yeh
TC, Lee
PH, Chang
PC. Relationship between media viewing and obesity in school-aged children in Taipei, Taiwan. J Nurs Res. 2013;21(3):195–203. [
PubMed: 23958609]
- 108.
Xi
B, Wang
C, Wu
L, Zhang
M, Shen
Y, Zhao
X, et al. Influence of physical inactivity on associations between single nucleotide polymorphisms and genetic predisposition to childhood obesity. Am J Epidemiol. 2011;173(11):1256–62. [
PubMed: 21527513]
- 109.
Yi
X, Yin
C, Chang
M, Xiao
Y. Prevalence and risk factors of obesity among school-aged children in Xi’an, China. Eur J Pediatr. 2012;171(2):389–94. [
PubMed: 21912892]
- 110.
Zurriaga
O, Perez-Panades
J, Quiles
IJ, Gil
CM, Anes
Y, Quinones
C, et al. Factors associated with childhood obesity in Spain. The OBICE study: a case-control study based on sentinel networks. Public Health Nutr. 2011;14(6):1105–13. [
PubMed: 21299916]
- 111.
Al-Hazzaa
HM, Abahussain
NA, Al-Sobayel
HI, Qahwaji
DM, Musaiger
AO. Physical activity, sedentary behaviors and dietary habits among Saudi adolescents relative to age, gender and region. Int J Behav Nutr Phys Act. 2011;8:140. [
PMC free article: PMC3339333] [
PubMed: 22188825]
- 112.
Al-Hazzaa
HM, Abahussain
NA, Al-Sobayel
HI, Qahwaji
DM, Musaiger
AO. Lifestyle factors associated with overweight and obesity among Saudi adolescents. BMC Public Health. 2012;12:354. [
PMC free article: PMC3433359] [
PubMed: 22591544]
- 113.
Allender
S, Kremer
P, de Silva-Sanigorski
A, Lacy
K, Millar
L, Mathews
L, et al. Associations between activity-related behaviours and standardized BMI among Australian adolescents. J Sci Med Sport. 2011;14(6):512–21. [
PubMed: 21683651]
- 114.
Al-Nakeeb
Y, Lyons
M, Collins
P, Al-Nuaim
A, Al-Hazzaa
H, Duncan
MJ, et al. Obesity, physical activity and sedentary behavior amongst British and Saudi youth: a cross-cultural study. Int J Environ Res Public Health. 2012;9(4):1490–506. [
PMC free article: PMC3366625] [
PubMed: 22690207]
- 115.
Badawi
NES, Barakat
AA, El Sherbini
SA, Fawzy
HM. Prevalence of overweight and obesity in primary school children in Port Said city. Gaz Egypt Paediatr Assoc. 2013;61(1):31–6.
- 116.
Beets
MW, Foley
JT. Comparison of 3 different analytic approaches for determining risk-related active and sedentary behavioral patterns in adolescents. J Phys Act Health. 2010;7(3):381–92. [
PubMed: 20551496]
- 117.
Bener
A, Al-Mahdi
HS, Ali
AI, Al-Nufal
M, Vachhani
PJ, Tewfik
I. Obesity and low vision as a result of excessive Internet use and television viewing. Int J Food Sci Nutr. 2011;62(1):60–2. [
PubMed: 20645888]
- 118.
Bingham
DD, Varela-Silva
MI, Ferrao
MM, Augusta
G, Mourao
MI, Nogueira
H, et al. Socio-demographic and behavioral risk factors associated with the high prevalence of overweight and obesity in Portuguese children. Am J Hum Biol. 2013;25(6):733–42. [
PubMed: 24000096]
- 119.
Bishwalata
R, Singh
AB, Singh
AJ, Devi
LU, Singh
RK. Overweight and obesity among schoolchildren in Manipur, India. Natl Med J India. 2010;23(5):263–6. [
PubMed: 21250579]
- 120.
Bozza
R, de
CW, raujo Bacil
ED, Barbosa
F, V, Hardt
JM, da Silva
PM. [Sociodemographic and behavioral factors associated with body adiposity in adolescents]. [Portuguese]. Rev Paul Pediatr. 2014;32(3):241–6. [
PMC free article: PMC4227347] [
PubMed: 25479856]
- 121.
Bracale
R, Milani
L, Ferrara
E, Balzaretti
C, Valerio
A, Russo
V, et al. Childhood obesity, overweight and underweight: a study in primary schools in Milan. Eat Weight Disord. 2013;18(2):183–91. [
PMC free article: PMC3664740] [
PubMed: 23760847]
- 122.
Braithwaite
I, Stewart
AW, Hancox
RJ, Beasley
R, Murphy
R, Mitchell
EA, et al. The worldwide association between television viewing and obesity in children and adolescents: cross sectional study. PLoS One. 2013;8(9):e74263. [
PMC free article: PMC3783429] [
PubMed: 24086327]
- 123.
Brown
JE, Broom
DH, Nicholson
JM, Bittman
M. Do working mothers raise couch potato kids? Maternal employment and children’s lifestyle behaviours and weight in early childhood. Social Science & Medicine. 2010;70(11):1816–24. [
PubMed: 20299142]
- 124.
Brown
JE, Nicholson
JM, Broom
DH, Bittman
M. Television viewing by school-age children: Associations with physical activity, snack food consumption and unhealthy weight. Soc Indic Res. 2011;101(2):221–5.
- 125.
Busch
V, Manders
LA, De
L, Jr. Screen time associated with health behaviors and outcomes in adolescents. Am J Health Behav. 2013;37(6):819–30. [
PubMed: 24001631]
- 126.
Cameron
AJ, van Stralen
MM, Brug
J, Salmon
J, Bere
E, Chinapaw
MJ, et al. Television in the bedroom and increased body weight: potential explanations for their relationship among European schoolchildren. Pediatr Obes. 2013;8(2):130–41. [
PubMed: 23239631]
- 127.
Carriere
C, Langevin
C, Lamireau
T, Maurice
S, Thibault
H. Dietary behaviors as associated factors for overweight and obesity in a sample of adolescents from Aquitaine, France. J Physiol Biochem. 2013;69(1):111–8. [
PubMed: 22773296]
- 128.
Carson
V, Janssen
I. The mediating effects of dietary habits on the relationship between television viewing and body mass index among youth. Pediatr Obes. 2012;7(5):391–8. [
PubMed: 22461393]
- 129.
Carson
V, Stone
M, Faulkner
G. Patterns of sedentary behavior and weight status among children. Pediatr Exerc Sci. 2014;26(1):95–102. [
PubMed: 24092774]
- 130.
Casiano
H, Kinley
D. Media use and health outcomes in adolescents: Findings form a nationally representative survey. J Can Acad Child Adolesc Psychiatry. 2012;21(4):296–301. [
PMC free article: PMC3490531] [
PubMed: 23133464]
- 131.
Chahal
H, Fung
C, Kuhle
S, Veugelers
PJ. Availability and night-time use of electronic entertainment and communication devices are associated with short sleep duration and obesity among Canadian children. Pediatr Obes. 2013;8(1):42–51. [
PubMed: 22962067]
- 132.
Chaput
JP, Lambert
M, Mathieu
ME, Tremblay
MS, O’
LJ, Tremblay
A. Physical activity vs. sedentary time: independent associations with adiposity in children. Pediatr Obes. 2012;7(3):251–8. [
PubMed: 22461356]
- 133.
Chaput
JP, Leduc
G, Boyer
C, Belanger
P, LeBlanc
AG, Borghese
MM, et al. Objectively measured physical activity, sedentary time and sleep duration: independent and combined associations with adiposity in canadian children. Nutr Diabetes. 2014;4:e117. [
PMC free article: PMC4079924] [
PubMed: 24911633]
- 134.
Chen
LP, Ziegenfuss
JY, Jenkins
SM, Beebe
TJ, Ytterberg
KL. Pediatric obesity and self-reported health behavior information. Clin Pediatr. 2011;50(9):872–5. [
PubMed: 21357199]
- 135.
Colley
RC, Wong
SL, Garriguet
D, Janssen
I, Connor
GS, Tremblay
MS. Physical activity, sedentary behaviour and sleep in Canadian children: parent-report versus direct measures and relative associations with health risk. Health Rep. 2012;23(2):45–52. [
PubMed: 22866540]
- 136.
de
JE, Visscher
TL, Hirasing
RA, Heymans
MW, Seidell
JC, Renders
CM. Association between TV viewing, computer use and overweight, determinants and competing activities of screen time in 4- to 13-year-old children. Int J Obes. 2013;37(1):47–53. [
PubMed: 22158265]
- 137.
Decelis
A, Jago
R, Fox
KR. Physical activity, screen time and obesity status in a nationally representative sample of Maltese youth with international comparisons. BMC Public Health. 2014;14:664. [
PMC free article: PMC4091762] [
PubMed: 24973912]
- 138.
Drake
KM, Beach
ML, Longacre
MR, Mackenzie
T, Titus
LJ, Rundle
AG, et al. Influence of sports, physical education, and active commuting to school on adolescent weight status. Pediatrics. 2012;130(2):e296–e304. [
PMC free article: PMC3408684] [
PubMed: 22802608]
- 139.
- 140.
Dupuy
M, Godeau
E, Vignes
C, Ahluwalia
N. Socio-demographic and lifestyle factors associated with overweight in a representative sample of 11-15 year olds in France: results from the WHO-Collaborative Health Behaviour in School-aged Children (HBSC) cross-sectional study. BMC Public Health. 2011;11:442. [
PMC free article: PMC3123212] [
PubMed: 21649892]
- 141.
Ekstedt
M, Nyberg
G, Ingre
M, Ekblom
O, Marcus
C. Sleep, physical activity and BMI in six to ten-year-old children measured by accelerometry: a cross-sectional study. Int J Behav Nutr Phys Act. 2013;10:82. [
PMC free article: PMC3691618] [
PubMed: 23800204]
- 142.
Ercan
S, Dallar
YB, Onen
S, Engiz
O. Prevalence of obesity and associated risk factors among adolescents in Ankara, Turkey. J Clin Res Pediatr Endocrinol. 2012;4(4):204–7. [
PMC free article: PMC3537287] [
PubMed: 23149433]
- 143.
Farajian
P, Panagiotakos
DB, Risvas
G, Malisova
O, Zampelas
A. Hierarchical analysis of dietary, lifestyle and family environment risk factors for childhood obesity: the GRECO study. Eur J Clin Nutr. 2014;68(10):1107–12. [
PubMed: 24824010]
- 144.
Fernandes
RA, Christofaro
DG, Cardoso
JR, Ronque
ER, Freitas
J, I, Kawaguti
SS, et al. Socioeconomic status as determinant of risk factors for overweight in adolescents. Cien Saude Colet. 2011;16(10):4051–7. [
PubMed: 22031134]
- 145.
Fernandez-Alvira
JM, Te Velde
SJ, De
B, I, Bere
E, Manios
Y, Kovacs
E, et al. Parental education associations with children’s body composition: mediation effects of energy balance-related behaviors within the ENERGY-project. Int J Behav Nutr Phys Act. 2013;10:80. [
PMC free article: PMC3695820] [
PubMed: 23800170]
- 146.
Ferrar
K, Olds
T. Thin adolescents: Who are they? What do they do? Socio-demographic and use-of-time characteristics. Prev Med. 2010;51(3–4):253–8. [
PubMed: 20630482]
- 147.
Garmy
P, Clausson
EK, Nyberg
P, Jakobsson
U. Overweight and television and computer habits in Swedish school-age children and adolescents: a cross-sectional study. Nurs Health Sci. 2014;16(2):143–8. [
PMC free article: PMC4237184] [
PubMed: 23796145]
- 148.
Ghavamzadeh
S, Khalkhali
HR, Alizadeh
M. TV viewing, independent of physical activity and obesogenic foods, increases overweight and obesity in adolescents. J Health Popul Nutr. 2013;31(3):334–42. [
PMC free article: PMC3805883] [
PubMed: 24288947]
- 149.
Gonzalez Montero de
EM, Herraez
A, Marrodan
S, M.D. [Determining factors in body mass index of Spanish schoolchildren based on the National Health Surveys]. [Spanish]. Endocrinologia y Nutricion. 2013;60(7):371–8. [
PubMed: 23665404]
- 150.
Govindan
M, Gurm
R, Mohan
S, Kline-Rogers
E, Corriveau
N, Goldberg
C, et al. Gender differences in physiologic markers and health behaviors associated with childhood obesity. Pediatrics. 2013;132(3):468–74. [
PubMed: 23940242]
- 151.
Goyal
JP, Kumar
N, Parmar
I, Shah
VB, Patel
B. Determinants of Overweight and Obesity in Affluent Adolescent in Surat City, South Gujarat region, India. Indian J Community Health. 2011;36(4):296–300. [
PMC free article: PMC3263151] [
PubMed: 22279261]
- 152.
Graff
M, North
K. Screen time behaviours may interact with obesity genes, independent of physical activity, to influence adolescent BMI in an ethnically diverse cohort. Pediatr Obes. 2013;8(6):e74–e9. [
PMC free article: PMC3838440] [
PubMed: 24039247]
- 153.
Gregori
D, Foltran
F, Ghidina
M, Zobec
F, Berchialla
P. Familial environment in high- and middle-low-income municipalities: a survey in Italy to understand the distribution of potentially obesogenic factors. Public Health. 2012;126(9):731–9. [
PubMed: 22789548]
- 154.
Grydeland
M, Bergh
IH, Bjelland
M, Lien
N, Andersen
LF, Ommundsen
Y, et al. Correlates of weight status among Norwegian 11-year-olds: The HEIA study. BMC Public Health. 2012;12:1053. [
PMC free article: PMC3538064] [
PubMed: 23216675]
- 155.
Hardy
LL, King
L, Hector
D, Lloyd
B. Weight status and weight-related behaviors of children commencing school. Prev Med. 2012;55(5):433–7. [
PubMed: 22995371]
- 156.
Hatami
M, Taib
MN, Jamaluddin
R, Saad
HA, Djazayery
A, Chamari
M, et al. Dietary factors as the major determinants of overweight and obesity among Iranian adolescents. A cross-sectional study. Appetite. 2014;82:194–201. [
PubMed: 25068789]
- 157.
Herman
KM, Sabiston
CM, Mathieu
ME, Tremblay
A, Paradis
G. Sedentary behavior in a cohort of 8- to 10-year-old children at elevated risk of obesity. Prev Med. 2014;60:115–20. [
PubMed: 24398174]
- 158.
Rajmil
L, Lopez-Aguila
S, Mompart-Penina
A. [Health-related quality of life and factors associated with overweight and obesity in the pediatric population of Catalonia, Spain]. [Spanish]. Med Clin. 2011;137: Suppl 2:37–41. [
PubMed: 22310362]
- 159.
Hong
TK, Nguyen
HH, Dibley
MJ, Sibbritt
DW, Phan
NT, Tran
TM. Factors associated with adolescent overweight/obesity in Ho Chi Minh city. Int J Pediatr Obes. 2010;5(5):396–403. [
PubMed: 20233155]
- 160.
Hsu
YW, Johnson
C. Correlates of overweight status in Chinese youth: An East-West paradox. Am J Health Behav. 2011;35(4):496–506. [
PubMed: 22040595]
- 161.
Inanc
BB, Sahin
DS, Oguzoncul
AF, Bindak
R, Mungan
F. Prevalence of obesity in elementary schools in mardin, South-eastern of Turkey: a preliminary study. Balkan Med J. 2012;29(4):424–30. [
PMC free article: PMC4115880] [
PubMed: 25207047]
- 162.
Ismailov
RM, Leatherdale
ST. Rural-urban differences in overweight and obesity among a large sample of adolescents in Ontario. Int J Pediatr Obes. 2010;5(4):351–60. [
PubMed: 20053147]
- 163.
Jahns
L, Adair
L, Mroz
T, Popkin
BM. The declining prevalence of overweight among Russian children: income, diet, and physical activity behavior changes. Econ Hum Biol. 2012;10(2):139–46. [
PMC free article: PMC3268832] [
PubMed: 21840274]
- 164.
Januszek-Trzciakowska
A, Malecka-Tendera
E, Klimek
K, Matusik
P. Obesity risk factors in a representative group of Polish prepubertal children. Arch Med Sci. 2014;10(5):880–5. [
PMC free article: PMC4223122] [
PubMed: 25395938]
- 165.
Jayawardene
W, Lohrmann
D, YoussefAgha
A. Discrepant body mass index: behaviors associated with height and weight misreporting among US adolescents from the National Youth Physical Activity and Nutrition Study. Childhood obesity. 2014;10(3):225–33. [
PubMed: 24828965]
- 166.
Jones
RA, Okely
AD, Caputi
P, Cliff
DP. Relationships between child, parent and community characteristics and weight status among young children. Int J Pediatr Obes. 2010;5(3):256–64. [
PubMed: 19900149]
- 167.
Kantanista
A, Osinski
W. Underweight in 14 to 16 year-old girls and boys: prevalence and associations with physical activity and sedentary activities. Ann Agric Environ Med. 2014;21(1):114–9. [
PubMed: 24738508]
- 168.
Katzmarzyk
PT, Barreira
TV, Broyles
ST, Champagne
CM, Chaput
JP, Fogelholm
M, et al. Relationship between lifestyle behaviors and obesity in 9-11 year old children: Results from a 12-country study (in press). Obesity. 2015.
- 169.
Katzmarzyk
PT, Barreira
TV, Broyles
ST, Champagne
CM, Chaput
JP, Fogelholm
M, et al. Physical Activity, Sedentary Time, and Obesity in an International Sample of Children (in press). Med Sci Sports Exerc. 2015. [
PubMed: 25751770]
- 170.
Kettner
S, Kobel
S, Fischbach
N, Drenowatz
C, Dreyhaupt
J, Wirt
T, et al. Objectively determined physical activity levels of primary school children in south-west Germany. BMC Public Health. 2013;13:895. [
PMC free article: PMC3852634] [
PubMed: 24073638]
- 171.
Kimbro
RT, Brooks-Gunn
J, McLanahan
S. Young children in urban areas: links among neighborhood characteristics, weight status, outdoor play, and television watching. Soc Sci Med. 2011;72(5):668–76. [
PMC free article: PMC3058513] [
PubMed: 21324574]
- 172.
Kristiansen
H, Juliusson
PB, Eide
GE, Roelants
M, Bjerknes
R. TV viewing and obesity among Norwegian children: the importance of parental education. Acta Paediatr. 2013;102(2):199–205. [
PubMed: 23121043]
- 173.
Kuhle
S, Allen
AC, Veugelers
PJ. Perinatal and childhood risk factors for overweight in a provincial sample of Canadian grade 5 students. Int J Pediatr Obes. 2010;5(1):88–96. [
PubMed: 19565401]
- 174.
Kuriyan
R, Thomas
T, Sumithra
S, Lokesh
DP, Sheth
NR, Joy
R, et al. Potential factors related to waist circumference in urban South Indian children. Indian Pediatr. 2012;49(2):124–8. [
PubMed: 21719930]
- 175.
Lane
A, Harrison
M, Murphy
N. Screen time increases risk of overweight and obesity in active and inactive 9-year-old Irish children: a cross sectional analysis. Journal of physical activity & health. 2014;11(5):985–91. [
PubMed: 23799255]
- 176.
Leatherdale
ST, Papadakis
S. A multi-level examination of the association between older social models in the school environment and overweight and obesity among younger students. J Youth Adolesc. 2011;40(3):361–72. [
PubMed: 20013351]
- 177.
Lee
B, Kim
H, Lee
SK, Yoon
J, Chung
SJ. Effects of exposure to television advertising for energy-dense/nutrient-poor food on children’s food intake and obesity in South Korea. Appetite. 2014;81:305–11. [
PubMed: 24996594]
- 178.
Legnani
E, Legnani
RF, Filho
VC, Krinski
K, Elsangedy
HM, de
CW, et al. [Factors associated with overweight in students from tri-border region: Argentina, Brazil and Paraguay]. [Spanish]. Arch Latinoam Nutr. 2010;60(4):340–7. [
PubMed: 21866683]
- 179.
Liou
YM, Liou
TH, Chang
LC. Obesity among adolescents: sedentary leisure time and sleeping as determinants. J Adv Nurs. 2010;66(6):1246–56. [
PubMed: 20546358]
- 180.
Lissner
L, Lanfer
A, Gwozdz
W, Olafsdottir
S, Eiben
G, Moreno
LA, et al. Television habits in relation to overweight, diet and taste preferences in European children: the IDEFICS study. Eur J Epidemiol. 2012;27(9):705–15. [
PMC free article: PMC3486991] [
PubMed: 22911022]
- 181.
Marques
A, Gaspar De
MM. Trends and correlates of overweight and Obesity among adolescents from 2002 to 2010: A three-cohort study based on a representative sample of Portuguese adolescents. Am J Hum Biol. 2014;26(6):844–9. [
PubMed: 25176416]
- 182.
Martinez-Gomez
D, Moreno
LA, Romeo
J, Rey-Lopez
P, Castillo
R, Cabero
MJ, et al. Combined influence of lifestyle risk factors on body fat in Spanish adolescents-the Avena study. Obes Facts. 2011;4(2):105–11. [
PMC free article: PMC6444635] [
PubMed: 21577017]
- 183.
Masse
LC, Blanck
HM, Valente
M, Atienza
AA, gurs-Collins
T, Weber
D, et al. Association between self-reported household practices and body mass index of US children and adolescents. Prev Chronic Dis. 2012;9:E174. [
PMC free article: PMC3523893] [
PubMed: 23237244]
- 184.
McConley
RL, Mrug
S, Gilliland
M. Mediators of maternal depression and family structure on child BMI: Parenting quality and risk factors for child overweight. Obesity. 2011;19(2):345–52. [
PubMed: 20798670]
- 185.
Mejia
D, Berchtold
A, Belanger
RE, Kuntsche
EN, Michaud
PA, Suris
JC. Frequency and effects of meeting health behaviour guidelines among adolescents. Eur J Public Health. 2013;23(1):8–13. [
PubMed: 22544912]
- 186.
Melkevik
O, Torsheim
T, Rasmussen
M. Patterns of screen-based sedentary behavior and physical activity and associations with overweight among Norwegian adolescents: A latent profile approach. Nor Epidemiol. 2010;20(1):109–17.
- 187.
Morley
BC, Scully
ML, Niven
PH, Okely
AD, Baur
LA, Pratt
IS, et al. What factors are associated with excess body weight in Australian secondary school students?
Med J Aust. 2012;196(3):189–92. [
PubMed: 22339525]
- 188.
Mungrue
K, Fyzul
A, Ramroop
S, Persad
T, Asgarali
A. Are teenagers at risk for developing cardiovascular disease in later life?
Int J Adolesc Med Health. 2013;25(1):75–80. [
PubMed: 23314517]
- 189.
Mushtaq
MU, Gull
S, Mushtaq
K, Shahid
U, Shad
MA, Akram
J. Dietary behaviors, physical activity and sedentary lifestyle associated with overweight and obesity, and their socio-demographic correlates, among Pakistani primary school children. Int J Behav Nutr Phys Act. 2011;8. [
PMC free article: PMC3250930] [
PubMed: 22117626]
- 190.
- 191.
Olds
TS, Maher
CA, Ridley
K, Kittel
DM. Descriptive epidemiology of screen and nonscreen sedentary time in adolescents: A cross sectional study. Int J Behav Nutr Phys Act. 2010;7. [
PMC free article: PMC3024298] [
PubMed: 21194427]
- 192.
Peart
T, Velasco Mondragon
HE, Rohm-Young
D, Bronner
Y, Hossain
MB. Weight status in US youth: the role of activity, diet, and sedentary behaviors. Am J Health Behav. 2011;35(6):756–64. [
PubMed: 22251766]
- 193.
Peltzer
K, Pengpid
S. Overweight and obesity and associated factors among school-aged adolescents in Ghana and Uganda. Int J Environ Res Public Health. 2011;8(10):3859–70. [
PMC free article: PMC3210586] [
PubMed: 22073017]
- 194.
Perez
VS, Novalbos-Ruiz
JP, Rodriguez-Martin
A, Martinez-Nieto
JM, Lechuga-Sancho
AM. Implications of family socioeconomic level on risk behaviors in child-youth obesity. Nutr Hosp. 2013;28(6):1951–60. [
PubMed: 24506374]
- 195.
Pitrou
I, Shojaei
T, Wazana
A, Gilbert
F, Kovess-Masfety
V. Child overweight, associated psychopathology, and social functioning: a French school-based survey in 6- to 11-year-old children. Obesity. 2010;18(4):809–17. [
PubMed: 19713951]
- 196.
Rani
MA, Sathiyasekaran
BW. Behavioural determinants for obesity: a cross-sectional study among urban adolescents in India. J Prev Med Public Health / Yebang Uihakhoe Chi. 2013;46(4):192–200. [
PMC free article: PMC3740224] [
PubMed: 23946877]
- 197.
Rey-Lopez
JP, Ruiz
JR, Vicente-Rodriguez
G, Gracia-Marco
L, Manios
Y, Sjostrom
M, et al. Physical activity does not attenuate the obesity risk of TV viewing in youth. Pediatr Obes. 2012;7(3):240–50. [
PubMed: 22434777]
- 198.
Rivera
IR, Silva
MA, Silva
RD, Oliveira
BA, Carvalho
AC. Physical inactivity, TV-watching hours and body composition in children and adolescents. Arq Bras Cardiol. 2010;95(2):159–65. [
PubMed: 20563518]
- 199.
- 200.
Seo
DC, Niu
J. Trends in underweight and overweight/obesity prevalence in Chinese youth, 2004-2009. Int J Behav Med. 2014;21(4):682–90. [
PubMed: 23744048]
- 201.
Shan
XY, Xi
B, Cheng
H, Hou
DQ, Wang
Y, Mi
J. Prevalence and behavioral risk factors of overweight and obesity among children aged 2-18 in Beijing, China. Int J Pediatr Obes. 2010;5(5):383–9. [
PubMed: 20233154]
- 202.
Sigmundova
D, Sigmund
E, Hamrik
Z, Kalman
M. Trends of overweight and obesity, physical activity and sedentary behaviour in Czech schoolchildren: HBSC study. Eur J Public Health. 2014;24(2):210–5. [
PMC free article: PMC3966283] [
PubMed: 23813709]
- 203.
Sisson
SB, Broyles
ST, Baker
BL, Katzmarzyk
PT. Television, reading, and computer time: correlates of school-day leisure-time sedentary behavior and relationship with overweight in children in the U.S.
Journal of physical activity & health. 2011;8: Suppl 2:S188–S97. [
PubMed: 21918232]
- 204.
Sluyter
JD, Scragg
RK, Plank
LD, Waqa
GD, Fotu
KF, Swinburn
BA. Sizing the association between lifestyle behaviours and fatness in a large, heterogeneous sample of youth of multiple ethnicities from 4 countries. Int J Behav Nutr Phys Act. 2013;10:115. [
PMC free article: PMC3853713] [
PubMed: 24119635]
- 205.
Stamatakis
E, Coombs
N, Jago
R, Gama
A, Mour+úo
I, Nogueira
H, et al. Associations between indicators of screen time and adiposity indices in Portuguese children. Prev Med. 2013;56(5):299–303. [
PubMed: 23435406]
- 206.
Stroebele
N, McNally
J, Plog
A, Siegfried
S, Hill
JO. The association of self-reported sleep, weight status, and academic performance in fifth-grade students. J Sch Health. 2013;83(2):77–84. [
PMC free article: PMC3552381] [
PubMed: 23331266]
- 207.
- 208.
Taber
DR, Stevens
J, Poole
C, Maciejewski
ML, Evenson
KR, Ward
DS. State disparities in time trends of adolescent body mass index percentile and weight-related behaviors in the United States. J Community Health. 2012;37(1):242–52. [
PMC free article: PMC3363325] [
PubMed: 21773818]
- 209.
Tambalis
KD, Panagiotakos
DB, Kavouras
SA, Papoutsakis
S, Sidossis
LS. Higher prevalence of obesity in Greek children living in rural areas despite increased levels of physical activity. J Paediatr Child Health. 2013;49(9):769–74. [
PMC free article: PMC3773292] [
PubMed: 23724863]
- 210.
Thibault
H, Carriere
C, Langevin
C, Kossi
DE, Barberger-Gateau
P, Maurice
S. Prevalence and factors associated with overweight and obesity in French primary-school children. Public Health Nutr. 2013;16(2):193–201. [
PMC free article: PMC10271746] [
PubMed: 22953729]
- 211.
Thibault
H, Contrand
B, Saubusse
E, Baine
M, Maurice-Tison
S. Risk factors for overweight and obesity in French adolescents: physical activity, sedentary behavior and parental characteristics. Nutrition. 2010;26(2):192–200. [
PubMed: 19577429]
- 212.
Tin
SP, Ho
DS, Mak
KH, Wan
KL, Lam
TH. Association between television viewing and self-esteem in children. J Dev Behav Pediatr. 2012;33(6):479–85. [
PubMed: 22772822]
- 213.
Vaezghasemi
M, Lindkvist
M, Ivarsson
A, Eurenius
E. Overweight and lifestyle among 13-15 year olds: a cross-sectional study in northern Sweden. Scand J Public Health. 2012;40(3):221–8. [
PubMed: 22637360]
- 214.
Wang
C, Chen
P, Zhuang
J. A national survey of physical activity and sedentary behavior of Chinese city children and youth using accelerometers. Res Q Exerc Sport. 2013;84: Suppl 2:S12–S28. [
PubMed: 24527563]
- 215.
Wang
N, Xu
F, Zheng
LQ, Zhang
XG, Li
Y, Sun
GZ, et al. Effects of television viewing on body fatness among Chinese children and adolescents. Chin Med J. 2012;125(8):1500–3. [
PubMed: 22613659]
- 216.
Wijtzes
AI, Bouthoorn
SH, Jansen
W, Franco
OH, Hofman
A, Jaddoe
VW, et al. Sedentary behaviors, physical activity behaviors, and body fat in 6-year-old children: the generation R study. Int J Behav Nutr Phys Act. 2014;11:96. [
PMC free article: PMC4145220] [
PubMed: 25124336]
- 217.
- 218.
Yako
YY, Hassan
MS, Erasmus
RT, van der
ML, Janse van
RS, Matsha
TE. Associations of MC3R polymorphisms with physical activity in South African adolescents. Journal of physical activity & health. 2013;10(6):813–25. [
PubMed: 23072813]
- 219.
Yen
CF, Hsiao
RC, Ko
CH, Yen
JY, Huang
CF, Liu
SC, et al. The relationships between body mass index and television viewing, internet use and cellular phone use: the moderating effects of socio-demographic characteristics and exercise. Int J Eat Disord. 2010;43(6):565–71. [
PubMed: 19718665]
- 220.
Zhang
J, Seo
DC, Kolbe
L, Middlestadt
S, Zhao
W. Trends in overweight among school children and adolescents in seven Chinese provinces, from 1991-2004. Int J Pediatr Obes. 2010;5(5):375–82. [
PubMed: 20233156]
- 221.
Zhang
J, Seo
DC, Kolbe
L, Middlestadt
S, Zhao
W. Associated trends in sedentary behavior and BMI among Chinese school children and adolescents in seven diverse Chinese provinces. Int J Behav Med. 2012;19(3):342–50. [
PubMed: 21748473]
- 222.
Hajian-Tilaki
K, Heidari
B. Prevalences of overweight and obesity and their association with physical activity pattern among Iranian adolescents aged 12-17 years. Public Health Nutr. 2012;15(12):2246–52. [
PMC free article: PMC10271770] [
PubMed: 22578771]
- 223.
Faulkner
G, Carson
V, Stone
M. Objectively measured sedentary behaviour and self-esteem among children. Ment Health Phys Act. 2014;7(1):25–9.
- 224.
Jackson
LA, von Eye
A, Fitzgerald
HE, Witt
EA, Zhao
Y. Internet use, videogame playing and cell phone use as predictors of children’s body mass index (BMI), body weight, academic performance, and social and overall self-esteem. Comput Human Behav. 2011;27(1):599–604.
- 225.
Jackson
LA, von Eye
A, Fitzgerald
HE, Zhao
Y, Witt
EA. Self-concept, self-esteem, gender, race and information technology use. Comput Human Behav. 2010;26(3):323–8.
- 226.
Jeong
EJ, Kim
DH. Social activities, self-efficacy, game attitudes, and game addiction. Cyberpsychol Behav Soc Netw. 2011;14(4):213–21. [
PubMed: 21067285]
- 227.
Kiraly
O, Griffiths
MD, Urban
R, Farkas
J, Kokonyei
G, Elekes
Z, et al. Problematic internet use and problematic online gaming are not the same: findings from a large nationally representative adolescent sample. Cyberpsychol Behav Soc Netw. 2014;17(12):749–54. [
PMC free article: PMC4267705] [
PubMed: 25415659]
- 228.
- 229.
Nihill
GFJ, Lubans
DR, Plotnikoff
RC. Associations between sedentary behavior and self-esteem in adolescent girls from schools in low-income communities. Ment Health Phys Act. 2013;6(1):30–5.
- 230.
Racine
EF, DeBate
RD, Gabriel
KP, High
RR. The relationship between media use and psychological and physical assets among third- to fifth-grade girls. J Sch Health. 2011;81(12):749–55. [
PubMed: 22070506]
- 231.
Bowers
AJ, Berland
M. Does recreational computer use affect high school achievement?. Educ Technol Res Dev. 2013;61(1):51–69.
- 232.
Brunborg
GS, Mentzoni
RA, Froyland
LR. Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems?
J Behav Addict. 2014;3(1):27–32. [
PMC free article: PMC4117274] [
PubMed: 25215212]
- 233.
Romer
D, Bagdasarov
Z, More
E. Older versus newer media and the well-being of United States youth: results from a national longitudinal panel. J Adolesc Health. 2013;52(5):613–9. [
PubMed: 23375827]
- 234.
- 235.
Esmaeilzadeh
S, Kalantari
H-A. Physical fitness, physical activity, sedentary behavior and academic performance among adolescent boys in different weight statuses. Med J Nutrition Metab. 2013;6(3):207–16.
- 236.
Ferguson
CJ. The influence of television and video game use on attention and school problems: a multivariate analysis with other risk factors controlled. J Psychiatr Res. 2011;45(6):808–13. [
PubMed: 21144536]
- 237.
Kiatrungrit
K, Hongsanguansri
S. Cross-sectional study of use of electronic media by secondary school students in Bangkok, Thailand. Shanghai Jingshen Yixue. 2014;26(4):216–26. [
PMC free article: PMC4194004] [
PubMed: 25317008]
- 238.
Martinez-Gomez
D, Veiga
OL, Gomez-Martinez
S, Zapatera
B, Martinez-Hernandez
D, Calle
ME, et al. Gender-specific influence of health behaviors on academic performance in Spanish adolescents: the AFINOS study. Nutr Hosp. 2012;27(3):724–30. [
PubMed: 23114936]
- 239.
Munoz-Miralles
R, Ortega-Gonzalez
R, Batalla-Martinez
C, Lopez-Moron
MR, Manresa
JM, Toran-Monserrat
P. [Access and use of new information and telecommunication technologies among teenagers at high school, health implications. JOITIC Study]. [Spanish]. Aten Primaria. 2014;46(2):77–88. [
PMC free article: PMC6983583] [
PubMed: 24035765]
- 240.
Ozmert
EN, Ince
T, Pektas
A, Ozdemir
R, Uckardes
Y. Behavioral correlates of television viewing in young adolescents in Turkey. Indian Pediatr. 2011;48(3):229–31. [
PubMed: 21169649]
- 241.
- 242.
Shashi Kumar
R, Das
RC, Prabhu
HR, Bhat
PS, Prakash
J, Seema
P, et al. Interaction of media, sexual activity and academic achievement in adolescents. Armed Forces Med J India. 2013;69(2):138–43. [
PMC free article: PMC3862597] [
PubMed: 24600087]
- 243.
Vassiloudis
I, Yiannakouris
N, Panagiotakos
DB, Apostolopoulos
K, Costarelli
V. Academic performance in relation to adherence to the Mediterranean diet and energy balance behaviors in Greek primary schoolchildren. Journal of nutrition education and behavior. 2014;46(3):164–70. [
PubMed: 24433816]
- 244.
O’Dea
JA, Mugridge
AC. Nutritional quality of breakfast and physical activity independently predict the literacy and numeracy scores of children after adjusting for socioeconomic status. Health Educ Res. 2012;27(6):975–85. [
PubMed: 22798563]
- 245.
Hoza
B, Smith
AL, Shoulberg
EK, Linnea
KS, Dorsch
TE, Blazo
JA, et al. A randomized trial examining the effects of aerobic physical activity on attention-deficit/hyperactivity disorder symptoms in young children. J Abnorm Child Psychol. 2014. [
PMC free article: PMC4826563] [
PubMed: 25201345]
- 246.
Howie
EK, Beets
MW, Pate
RR. Acute classroom exercise breaks improve on-task behavior in 4th and 5th grade students: A dose-response. Ment Health Phys Act. 2014;7(2):65–71.
- 247.
Gentile
DA, Swing
EL, Lim
CG, Khoo
A. Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychol Pop Media Cult. 2012;1(1):62–70.
- 248.
- 249.
Janssen
I, Boyce
WF, Pickett
W. Screen time and physical violence in 10 to 16-year-old Canadian youth. Int J Public Health. 2012;57(2):325–31. [
PubMed: 21110059]
- 250.
- 251.
Parkes
A, Sweeting
H, Wight
D, Henderson
M. Do television and electronic games predict children’s psychosocial adjustment? Longitudinal research using the UK Millennium Cohort Study. Arch Dis Child. 2013;98(5):341–8. [
PMC free article: PMC3625829] [
PubMed: 23529828]
- 252.
- 253.
Swing
EL, Gentile
DA, Anderson
CA, Walsh
DA. Television and video game exposure and the development of attention problems. Pediatrics. 2010;126(2):214–21. [
PubMed: 20603258]
- 254.
Willoughby
T, Adachi
PJ, Good
M. A longitudinal study of the association between violent video game play and aggression among adolescents. Dev Psychol. 2012;48(4):1044–57. [
PubMed: 22040315]
- 255.
Demirok
M, Ozdamli
F, Hursen
C, Ozcinar
Z, Kutguner
M, Uzunboylu
H. The relationship of computer games and reported anger in young people. Australian Journal of Guidance and Counselling. 2012;22(1):33–43.
- 256.
Griffiths
LJ, Dowda
M, Dezateux
C, Pate
R. Associations between sport and screen-entertainment with mental health problems in 5-year-old children. Int J Behav Nutr Phys Act. 2010;7:30. [
PMC free article: PMC2867988] [
PubMed: 20409310]
- 257.
Przybylski
AK. Electronic gaming and psychosocial adjustment. Pediatrics. 2014;134(3):e716–e22. [
PubMed: 25092934]
- 258.
Rech
RR, Halpern
R, Tedesco
A, Santos
DF. Prevalence and characteristics of victims and perpetrators of bullying. J Pediatr. 2013;89(2):164–70. [
PubMed: 23642427]
- 259.
Rosen
L. Media and technology use predicts ill-being among children, preteens and teenagers independent of the negative health impacts of exercise and eating habits. Comput Human Behav. 2014;35:364–75. [
PMC free article: PMC4338000] [
PubMed: 25717216]
- 260.
Shokouhi-Moqhaddam
S, Khezri-Moghadam
N, Javanmard
Z, Sarmadi-Ansar
H, Aminaee
M, Shokouhi-Moqhaddam
M, et al. A Study of the Correlation between Computer Games and Adolescent Behavioral Problems. Addict Health. 2013;5(1–2):43–50. [
PMC free article: PMC3905568] [
PubMed: 24494157]
- 261.
Singh
GK, Yu
SM. The Impact of Ethnic-Immigrant Status and Obesity-Related Risk Factors on Behavioral Problems among US Children and Adolescents. Scientifica. 2012;2012:648152. [
PMC free article: PMC3820528] [
PubMed: 24278722]
- 262.
van Egmond-Frohlich
AW, Weghuber
D, de
ZM. Association of symptoms of attention-deficit/hyperactivity disorder with physical activity, media time, and food intake in children and adolescents. PLoS One. 2012;7(11):e49781. [
PMC free article: PMC3498177] [
PubMed: 23166770]