Literature DB >> 29442253

Socioeconomic inequality in screen time frequency in children and adolescents: the weight disorders survey of the CASPIAN IV study.

Ramin Heshmat1, Mostafa Qorbani2,3, Nafiseh Mozaffarian4, Shirin Djalalinia5, Ali Sheidaei6, Mohammad Esmaeil Motlagh7, Saeid Safiri8, Kimia Gohari6, Asal Ataie-Jafari9, Gelayol Ardalan4, Hamid Asayesh10, Morteza Mansourian11, Roya Kelishadi4.   

Abstract

BACKGROUND: This study aimed to assess the socioeconomic inequality and determinants of screen time (ST) frequency in Iranian children and adolescents.
METHODS: This nationwide study was conducted as part of a national school-based surveillance program among 36,486 students consisting of 50.79% boys and 74.23% urban inhabitants, aged 6-18 years, living in urban and rural areas of 30 provinces of Iran. Socioeconomic inequality in ST, including the time spent for ST, watching TV and leisure-time working with computer, was assessed across quintiles of SES using concentration index (C) and slope index of inequality (SII).
RESULTS: Overall, 36,486 students completed the study (response rate 91.25%). Their mean (SD) age was 12.14 (3.36) years. The national estimation of frequency of ST was 31.66% (95% CI 31.16-32.17) with ascending change from 20.80% (95% CI 19.81-21.82) to 36.66% (95% CI 35.47-37.87) from the first to the last quintal of SES. Estimated C value at national level was positive (0.08), which indicate inequality was in favor of low SES groups. Considering the SII values, at national level [- 0.16 (- 0.39, 0.06)], the absolute difference in ST frequency between the bottom and top of the socioeconomic groups had descending trends. In multivariate logistic regression model, family history of obesity, generalized obesity and age were the main significant determinants of prolonged ST, watching TV, and computer working (P < 0.001).
CONCLUSIONS: Socioeconomic inequality in ST frequency was in favor of low SES groups. These findings are useful for health policies, better programming and future complementary analyses.

Entities:  

Keywords:  Inequality; Iran; Oaxaca–Blinder decomposition; Screen time

Mesh:

Year:  2018        PMID: 29442253     DOI: 10.1007/s12519-017-0115-5

Source DB:  PubMed          Journal:  World J Pediatr            Impact factor:   2.764


  43 in total

1.  Association between screen time and metabolic syndrome in children and adolescents in Korea: the 2005 Korean National Health and Nutrition Examination Survey.

Authors:  Hee-Taik Kang; Hye-Ree Lee; Jae-Yong Shim; Youn-Ho Shin; Byoung-Jin Park; Yong-Jae Lee
Journal:  Diabetes Res Clin Pract       Date:  2010-03-29       Impact factor: 5.602

2.  The evolving definition of "sedentary".

Authors:  Russell R Pate; Jennifer R O'Neill; Felipe Lobelo
Journal:  Exerc Sport Sci Rev       Date:  2008-10       Impact factor: 6.230

3.  American Academy of Pediatrics: Children, adolescents, and television.

Authors: 
Journal:  Pediatrics       Date:  2001-02       Impact factor: 7.124

4.  Longitudinal sedentary behavior changes in adolescents in Ho Chi Minh City.

Authors:  Nguyen H H D Trang; Tang K Hong; Hidde P van der Ploeg; Louise L Hardy; Patrick J Kelly; Michael J Dibley
Journal:  Am J Prev Med       Date:  2013-03       Impact factor: 5.043

5.  Economic and other barriers to adopting recommendations to prevent childhood obesity: results of a focus group study with parents.

Authors:  Kendrin R Sonneville; Nancy La Pelle; Elsie M Taveras; Matthew W Gillman; Lisa A Prosser
Journal:  BMC Pediatr       Date:  2009-12-21       Impact factor: 2.125

6.  Associations between sedentary behavior and blood pressure in young children.

Authors:  David Martinez-Gomez; Jared Tucker; Kate A Heelan; Gregory J Welk; Joey C Eisenmann
Journal:  Arch Pediatr Adolesc Med       Date:  2009-08

7.  Relationship between screen time and metabolic syndrome in adolescents.

Authors:  Amy E Mark; Ian Janssen
Journal:  J Public Health (Oxf)       Date:  2008-03-28       Impact factor: 2.341

8.  Associations between factors within the home setting and screen time among children aged 0-5 years: a cross-sectional study.

Authors:  Valerie Carson; Ian Janssen
Journal:  BMC Public Health       Date:  2012-07-23       Impact factor: 3.295

9.  Temporal trends and recent correlates in sedentary behaviours in Chinese children.

Authors:  Zhaohui Cui; Louise L Hardy; Michael J Dibley; Adrian Bauman
Journal:  Int J Behav Nutr Phys Act       Date:  2011-08-26       Impact factor: 6.457

10.  Methodology and Early Findings of the Fourth Survey of Childhood and Adolescence Surveillance and Prevention of Adult Non-Communicable Disease in Iran: The CASPIAN-IV Study.

Authors:  Roya Kelishadi; Gelayol Ardalan; Mostafa Qorbani; Asal Ataie-Jafari; Maryam Bahreynian; Mahnaz Taslimi; Mohammad Esmaeil Motlagh; Ramin Heshmat
Journal:  Int J Prev Med       Date:  2013-12
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  1 in total

1.  Why do apprentices smoke much more than high school students? Understanding educational disparities in smoking with a Oaxaca-blinder decomposition analysis.

Authors:  Sandra Chyderiotis; Tarik Benmarhnia; Stanislas Spilka; François Beck; Raphaël Andler; Stéphane Legleye; Gwenn Menvielle
Journal:  BMC Public Health       Date:  2020-06-12       Impact factor: 3.295

  1 in total

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