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Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents

Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents
Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents
Objective: To examine the independent associations between sleep duration, four technology types (computer use, mobile telephones, TV viewing and video gaming) and body mass index (BMI) z-score. We propose a theoretical path model showing direct effects of four technology types on BMI z-score and sleep duration as well as the indirect effects of each technology on BMI z-score while considering sleep duration as a mediator.

Methods: Consenting adolescents (n=632; 63.9% girls, aged 11-18 years) were recruited to the Midlands Adolescent Schools sleep Education Study. The School Sleep Habits Survey (SSHS) and Technology Use Questionnaire (TUQ) were administered. Objective measures of height (cm) and weight (kg) were obtained for BMI z-score calculation.

Results: Weekday use of all technology types was significantly associated with reduced weekday sleep duration after adjustment (? (computer use)=-0.38, P<0.01; ? (mobile telephone)=-0.27, P<0.01; ? (TV viewing)=-0.35, P<0.01; and ? (video gaming)=-0.39, P<0.01). Use of all technology types, with the exception of mobile telephones, was significantly associated with increased BMI z-score after adjustment (? (computer use)=0.26, P<0.01; ? (TV viewing)=0.31, P<0.01; and ? (video gaming)=0.40, P<0.01). Our path model shows that weekday sleep duration was significantly and negatively associated with BMI z-score (?=-0.40, P<0.01).

Conclusion: Weekday sleep duration potentially mediates the effects of some technologies on BMI z-score. If confirmed, improving sleep through better management of technology use could be an achievable intervention for attenuating obesity.
0307-0565
1-7
Arora, T.
68b9f09d-3bb7-460f-8f0c-6e1fe805162f
Hussain, S.
ff6f81c2-7f8a-44bf-9e3c-0d8d540c62d1
Lam, K.B.
43b999c1-9c86-4877-81c7-83d7e414623c
Yao, Guiqing
d777f84c-cf3d-4fad-bbc1-ea01dec01695
Thomas, N.G.
104313d8-fe40-49bd-a9ca-535fa52adde7
Taheri, S.
27680e3f-1654-4a07-bc9d-e8a9dcb621a7
Arora, T.
68b9f09d-3bb7-460f-8f0c-6e1fe805162f
Hussain, S.
ff6f81c2-7f8a-44bf-9e3c-0d8d540c62d1
Lam, K.B.
43b999c1-9c86-4877-81c7-83d7e414623c
Yao, Guiqing
d777f84c-cf3d-4fad-bbc1-ea01dec01695
Thomas, N.G.
104313d8-fe40-49bd-a9ca-535fa52adde7
Taheri, S.
27680e3f-1654-4a07-bc9d-e8a9dcb621a7

Arora, T., Hussain, S., Lam, K.B., Yao, Guiqing, Thomas, N.G. and Taheri, S. (2013) Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents. International Journal of Obesity, 1-7. (doi:10.1038/ijo.2012.209). (PMID:23295500)

Record type: Article

Abstract

Objective: To examine the independent associations between sleep duration, four technology types (computer use, mobile telephones, TV viewing and video gaming) and body mass index (BMI) z-score. We propose a theoretical path model showing direct effects of four technology types on BMI z-score and sleep duration as well as the indirect effects of each technology on BMI z-score while considering sleep duration as a mediator.

Methods: Consenting adolescents (n=632; 63.9% girls, aged 11-18 years) were recruited to the Midlands Adolescent Schools sleep Education Study. The School Sleep Habits Survey (SSHS) and Technology Use Questionnaire (TUQ) were administered. Objective measures of height (cm) and weight (kg) were obtained for BMI z-score calculation.

Results: Weekday use of all technology types was significantly associated with reduced weekday sleep duration after adjustment (? (computer use)=-0.38, P<0.01; ? (mobile telephone)=-0.27, P<0.01; ? (TV viewing)=-0.35, P<0.01; and ? (video gaming)=-0.39, P<0.01). Use of all technology types, with the exception of mobile telephones, was significantly associated with increased BMI z-score after adjustment (? (computer use)=0.26, P<0.01; ? (TV viewing)=0.31, P<0.01; and ? (video gaming)=0.40, P<0.01). Our path model shows that weekday sleep duration was significantly and negatively associated with BMI z-score (?=-0.40, P<0.01).

Conclusion: Weekday sleep duration potentially mediates the effects of some technologies on BMI z-score. If confirmed, improving sleep through better management of technology use could be an achievable intervention for attenuating obesity.

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e-pub ahead of print date: 8 January 2013
Organisations: Primary Care & Population Sciences

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Local EPrints ID: 352885
URI: https://eprints.soton.ac.uk/id/eprint/352885
ISSN: 0307-0565
PURE UUID: 69e184b8-3db7-4e8d-bae9-1cd93ef4690c

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Date deposited: 22 May 2013 13:33
Last modified: 16 Jul 2019 21:32

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Contributors

Author: T. Arora
Author: S. Hussain
Author: K.B. Lam
Author: Guiqing Yao
Author: N.G. Thomas
Author: S. Taheri

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