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The effect of smartphone addiction on obesity in children and adolescents.

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Title: The effect of smartphone addiction on obesity in children and adolescents.
Authors: Gill, Eunsun (AUTHOR), Chung, Wankyo (AUTHOR)
Source: Psychology, Health & Medicine. Jul2026, Vol. 31 Issue 6, p1361-1375. 15p.
Subjects: Psychology of middle school students, Risk assessment, Cross-sectional method, Smartphones, Compulsive behavior, Body mass index, T-test (Statistics), Psychology of school children, Probability theory, Multiple regression analysis, Sex distribution, Socioeconomic factors, Chi-squared test, Descriptive statistics, Screen time, Family history (Medicine), Longitudinal method, Odds ratio, Cluster sampling, Childhood obesity, Data analysis software, Confidence intervals, Sleep disorders, Disease risk factors, Adolescence, Children
Geographic Terms: South Korea
Abstract: The objective of this study is to ascertain the long-term risk of obesity associated with smartphone addiction in children and adolescents. We utilized a 4-year dataset from the Korean Children and Youth Survey 2018 (2018–2021). At baseline, the sample comprised 2,607 4th-grade elementary school students and 2,590 1st-grade middle school students (mean age: 11.3 ± 0.3, 14.3 ± 0.3 years, respectively). Of these, 2,718 (52.3%) were boys. Obesity was defined as a body mass index Z-score of at least the 95th percentile according to the 2017 Korean National Growth Charts. During the four-year follow-up period, the prevalence of obesity ranged from 6.9% to 8.4%, while the prevalence of being at high risk of smartphone addiction ranged from 2.1% to 4.8%. The logistic generalized estimating equation (GEE) was employed to examine the risk of obesity in those with addiction to smartphones. The risk of obesity was analyzed by adding smartphone screen time in Model 1, smartphone addiction in Model 2, and smartphone screen time and addiction in Model 3. The GEE results indicated that the odds of obesity increased by 16% in the potential-risk group for smartphone addiction compared to the normal group, even with the same duration of smartphone usage (OR [odds ratio] = 1.16, 95% CI [confidence interval] 1.01–1.33). Although the increase was not statistically significant, the odds of obesity were 1.24 times higher in the high-risk smartphone addiction group (OR = 1.24, 95% CI 0.94–1.65). Spending more than 3 hours on a smartphone was linked to 1.37-fold higher odds of obesity compared to spending less than 1 hour (95% CI 1.14–1.63). Smartphone addiction and overuse among children and adolescents can potentially raise obesity risks. Active interventions are needed to promote healthy smartphone behaviors in children and adolescents. [ABSTRACT FROM AUTHOR]
Copyright of Psychology, Health & Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: The effect of smartphone addiction on obesity in children and adolescents.
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  Data: <searchLink fieldCode="AR" term="%22Gill%2C+Eunsun%22">Gill, Eunsun</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chung%2C+Wankyo%22">Chung, Wankyo</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Psychology%2C+Health+%26+Medicine%22">Psychology, Health & Medicine</searchLink>. Jul2026, Vol. 31 Issue 6, p1361-1375. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Psychology+of+middle+school+students%22">Psychology of middle school students</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Smartphones%22">Smartphones</searchLink><br /><searchLink fieldCode="DE" term="%22Compulsive+behavior%22">Compulsive behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Body+mass+index%22">Body mass index</searchLink><br /><searchLink fieldCode="DE" term="%22T-test+%28Statistics%29%22">T-test (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Psychology+of+school+children%22">Psychology of school children</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+theory%22">Probability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+regression+analysis%22">Multiple regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+distribution%22">Sex distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+factors%22">Socioeconomic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Screen+time%22">Screen time</searchLink><br /><searchLink fieldCode="DE" term="%22Family+history+%28Medicine%29%22">Family history (Medicine)</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Odds+ratio%22">Odds ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+sampling%22">Cluster sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Childhood+obesity%22">Childhood obesity</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep+disorders%22">Sleep disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+risk+factors%22">Disease risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescence%22">Adolescence</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink>
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  Data: The objective of this study is to ascertain the long-term risk of obesity associated with smartphone addiction in children and adolescents. We utilized a 4-year dataset from the Korean Children and Youth Survey 2018 (2018–2021). At baseline, the sample comprised 2,607 4th-grade elementary school students and 2,590 1st-grade middle school students (mean age: 11.3 ± 0.3, 14.3 ± 0.3 years, respectively). Of these, 2,718 (52.3%) were boys. Obesity was defined as a body mass index Z-score of at least the 95th percentile according to the 2017 Korean National Growth Charts. During the four-year follow-up period, the prevalence of obesity ranged from 6.9% to 8.4%, while the prevalence of being at high risk of smartphone addiction ranged from 2.1% to 4.8%. The logistic generalized estimating equation (GEE) was employed to examine the risk of obesity in those with addiction to smartphones. The risk of obesity was analyzed by adding smartphone screen time in Model 1, smartphone addiction in Model 2, and smartphone screen time and addiction in Model 3. The GEE results indicated that the odds of obesity increased by 16% in the potential-risk group for smartphone addiction compared to the normal group, even with the same duration of smartphone usage (OR [odds ratio] = 1.16, 95% CI [confidence interval] 1.01–1.33). Although the increase was not statistically significant, the odds of obesity were 1.24 times higher in the high-risk smartphone addiction group (OR = 1.24, 95% CI 0.94–1.65). Spending more than 3 hours on a smartphone was linked to 1.37-fold higher odds of obesity compared to spending less than 1 hour (95% CI 1.14–1.63). Smartphone addiction and overuse among children and adolescents can potentially raise obesity risks. Active interventions are needed to promote healthy smartphone behaviors in children and adolescents. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychology, Health & Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=194804708
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/13548506.2025.2561741
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 1361
    Subjects:
      – SubjectFull: Psychology of middle school students
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Smartphones
        Type: general
      – SubjectFull: Compulsive behavior
        Type: general
      – SubjectFull: Body mass index
        Type: general
      – SubjectFull: T-test (Statistics)
        Type: general
      – SubjectFull: Psychology of school children
        Type: general
      – SubjectFull: Probability theory
        Type: general
      – SubjectFull: Multiple regression analysis
        Type: general
      – SubjectFull: Sex distribution
        Type: general
      – SubjectFull: Socioeconomic factors
        Type: general
      – SubjectFull: Chi-squared test
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Screen time
        Type: general
      – SubjectFull: Family history (Medicine)
        Type: general
      – SubjectFull: Longitudinal method
        Type: general
      – SubjectFull: Odds ratio
        Type: general
      – SubjectFull: Cluster sampling
        Type: general
      – SubjectFull: Childhood obesity
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Sleep disorders
        Type: general
      – SubjectFull: Disease risk factors
        Type: general
      – SubjectFull: Adolescence
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: South Korea
        Type: general
    Titles:
      – TitleFull: The effect of smartphone addiction on obesity in children and adolescents.
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            NameFull: Gill, Eunsun
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            NameFull: Chung, Wankyo
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            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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