Association between wearable device usage and obesity transition in children and adolescents: a nationwide longitudinal study

Ziyue Sun , Xia Zhong , Yang yang , Jiajia Dang , Shan Cai , Yunfei Liu , Jiaxin Li , Tianyu Huang , Xiaoqian Zhang , Mei Xue , Jing Li , Zhixin Zhang , Yi Song

Metabolism and Target Organ Damage ›› 2025, Vol. 5 ›› Issue (4) : 57

PDF
Metabolism and Target Organ Damage ›› 2025, Vol. 5 ›› Issue (4) :57 DOI: 10.20517/mtod.2025.116
Original Article

Association between wearable device usage and obesity transition in children and adolescents: a nationwide longitudinal study

Author information +
History +
PDF

Abstract

Aim: Wearable devices have the potential to promote healthy behaviors, yet evidence on their effectiveness in pediatric populations remains scarce. This study aims to investigate the association between wearable device usage and the transition to obesity among Chinese children and adolescents, addressing critical gaps in evidence regarding optimal usage patterns and subgroup variations for obesity prevention.

Methods: Using longitudinal data from the 2019-2020 National Student Physical Health Survey (n = 5,006), this study examined associations between wearable device/mobile app usage frequency (categorized as frequent, sometimes, occasional, rare, or never use) and obesity transition among children and adolescents aged 9-18. Multivariable logistic regression models adjusted for demographics were employed, with subgroup analyses stratified by age, sex, and residence.

Results: Compared to frequent users, rare/never users showed a tendency toward higher risks of transitioning to obesity [odds ratio (OR) = 1.50, 95% confidence interval (CI): 1.04-2.18, P = 0.030]. Sometimes users had the lowest risk of physical inactivity (OR = 0.61, 95%CI: 0.51-0.73, P < 0.001), whereas never users demonstrated a higher risk of prolonged sedentary behavior (OR = 1.36, 95%CI: 1.11-1.67, P = 0.003). Subgroup analyses revealed stronger associations in rural areas (OR = 2.99, 95%CI: 1.23-7.25, P = 0.016 for overweight transition in occasional users) and boys (OR = 1.96, 95%CI: 1.05-3.68, P = 0.035 for overweight transition in rarely users).

Conclusion: Moderate, rather than frequent, use of wearable devices may optimally mitigate obesity risk in children, potentially avoiding technology fatigue from overuse. Rural-urban and gender disparities highlight the need for context-specific interventions. Wearable device use may mitigate pediatric obesity risk primarily by reducing sedentary behavior and increasing physical activity time, with optimal benefits at moderate usage frequency. These findings emphasize prioritizing usage quality over device adoption rates in public health strategies.

Keywords

Wearable devices / obesity / physical activity / sedentary behavior / behavioral mediation

Cite this article

Download citation ▾
Ziyue Sun, Xia Zhong, Yang yang, Jiajia Dang, Shan Cai, Yunfei Liu, Jiaxin Li, Tianyu Huang, Xiaoqian Zhang, Mei Xue, Jing Li, Zhixin Zhang, Yi Song. Association between wearable device usage and obesity transition in children and adolescents: a nationwide longitudinal study. Metabolism and Target Organ Damage, 2025, 5(4): 57 DOI:10.20517/mtod.2025.116

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Afshin A, Forouzanfar MH, Reitsma MB, et al; GBD 2015 Obesity Collaborators. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377:13-27. PMCID:PMC5477817

[2]

Wang S,Wang ZH,Ma J.[Trends in overweight and obesity among Chinese children of 7-18 years old during 1985-2014].Zhonghua Yu Fang Yi Xue Za Zhi2017;51:300-5

[3]

Luo D.Socio-economic inequalities in child growth: identifying orientation and forward-looking layout.Lancet Reg Health West Pac2022;21:100412 PMCID:PMC8885566

[4]

Piché ME,Després JP.Obesity phenotypes, diabetes, and cardiovascular diseases.Circ Res2020;126:1477-500

[5]

Chandrasekaran P.The role of obesity in type 2 diabetes mellitus-an overview.Int J Mol Sci2024;25:1882 PMCID:PMC10855901

[6]

Migueles JH,Lubans DR.Effects of an exercise program on cardiometabolic and mental health in children with overweight or obesity: a secondary analysis of a randomized clinical trial.JAMA Netw Open2023;6:e2324839 PMCID:PMC10375312

[7]

Ocagli H,Azzolina D.Physical activity assessment with wearable devices in rheumatic diseases: a systematic review and meta-analysis.Rheumatology2023;62:1031-46

[8]

Smith L,Rahmati M.Association between sedentary behavior and dynapenic abdominal obesity among older adults from low- and middle-income countries.Aging Clin Exp Res2024;36:109 PMCID:PMC11087302

[9]

Pellegrini M,Mychasiuk R,Kramer SF.Measuring sleep quality in the hospital environment with wearable and non-wearable devices in adults with stroke undergoing inpatient rehabilitation.Int J Environ Res Public Health2023;20:3984 PMCID:PMC10001748

[10]

Spring B,Scanlan L.An adaptive behavioral intervention for weight loss management: a randomized clinical trial.JAMA2024;332:21-30 PMCID:PMC11094642

[11]

Li H,Gong L.Improving physical and mental health in women with breast cancer undergoing anthracycline-based chemotherapy through wearable device-based aerobic exercise: a randomized controlled trial.Front Public Health2024;12:1451101 PMCID:PMC11446794

[12]

Song Y,Wang HJ,Lau PW.Age at spermarche: 15-year trend and its association with body mass index in Chinese school-aged boys.Pediatr Obes2016;11:369-74

[13]

National Health Commission of the People’s Republic of China. Screening for Overweight and Obesity among School-Age Children and Adolescents. Available from: https://www.nhc.gov.cn/ewebeditor/uploadfile/2018/03/20180330094031236.pdf. [Last accessed on 17 Dec 2025].

[14]

Dong Y,Chen L.Individual-, family-, and school-level ecological correlates with physical fitness among chinese school-aged children and adolescents: a national cross-sectional survey in 2014.Front Nutr2021;8:684286 PMCID:PMC8424096

[15]

Xiao H,Li J.A method for filling traffic data based on feature-based combination prediction model.Sci Rep2025;15:8441 PMCID:PMC11897214

[16]

Cole TJ,Flegal KM.Establishing a standard definition for child overweight and obesity worldwide: international survey.BMJ2000;320:1240-3 PMCID:PMC27365

[17]

Babu M,Lin X,Snyder MP.Wearable devices: implications for precision medicine and the future of health care.Annu Rev Med2024;75:401-15

[18]

Caldwell JA,Thompson LA.Fatigue and its management in the workplace.Neurosci Biobehav Rev2019;96:272-89

[19]

van Merriënboer JJ, Sweller J. Cognitive load theory in health professional education: design principles and strategies.Med Educ2010;44:85-93

[20]

Schembre SM,Robertson MC.Just-in-time feedback in diet and physical activity interventions: systematic review and practical design framework.J Med Internet Res2018;20:e106 PMCID:PMC5887039

[21]

Basu J.Research on disparities in primary health care in rural versus urban areas: select perspectives.Int J Environ Res Public Health2022;19:7110 PMCID:PMC9222532

[22]

Wang X.Intergenerational care and rural childhood obesity in the digital era: based on screen exposure perspective.SSM Popul Health2024;27:101694 PMCID:PMC11269810

[23]

Zhou M,Zhu W.The impact of parental migration on multidimensional health of children in rural China: the moderating effect of mobile phone addiction.Children2022;10:44 PMCID:PMC9856684

[24]

Liu W,Xia L,Wang Y.Left-behind children's subtypes of antisocial behavior: a qualitative study in China.Behav Sci2022;12:349 PMCID:PMC9598385

[25]

Tønnessen E,Olsen IC,Haugen T.Performance development in adolescent track and field athletes according to age, sex and sport discipline.PLoS One2015;10:e0129014 PMCID:PMC4456243

[26]

Balafoutas L,Sutter M.Closing the gender gap in competitiveness through priming.Nat Commun2018;9:4359 PMCID:PMC6195557

[27]

Alarcón G,Allen NB,Silk JS.Adolescent gender differences in neural reactivity to a friend’s positive affect and real-world positive experiences in social contexts.Dev Cogn Neurosci2020;43:100779 PMCID:PMC7183158

[28]

Veerubhotla A,Ibironke O.Wearable devices for tracking physical activity in the community after an acquired brain injury: a systematic review.PM R2022;14:1207-18

[29]

Strain T,Dempsey PC.Wearable-device-measured physical activity and future health risk.Nat Med2020;26:1385-91 PMCID:PMC7116559

[30]

Wang W,Song W.The effectiveness of wearable devices as physical activity interventions for preventing and treating obesity in children and adolescents: systematic review and meta-analysis.JMIR Mhealth Uhealth2022;10:e32435 PMCID:PMC9034426

[31]

Conger SA,Cretsinger C.Time trends in physical activity using wearable devices: a systematic review and meta-analysis of studies from 1995 to 2017.Med Sci Sports Exerc2022;54:288-98

[32]

Cai S, Wang H, Zhang YH, et al. Could physical activity promote indicators of physical and psychological health among children and adolescents? An umbrella review of meta-analyses of randomized controlled trials. World J Pediatr. 2025;21:159-73.

[33]

Leung AKC,Hon KL.Childhood obesity: an updated review.Curr Pediatr Rev2024;20:2-26

[34]

Zhang Z,Huang J.Impact of the moderating effect of national culture on adoption intention in wearable health care devices: meta-analysis.JMIR Mhealth Uhealth2022;10:e30960 PMCID:PMC9206205

[35]

Xing Y,Cui M.Overview and methods for chinese national surveillance on students’ common diseases and risk factors, 2022.Future2025;3:12

[36]

Li J,Zhang Y.Strategic co-prevention framework for addressing common health challenges among students in China.Future2025;3:7

AI Summary AI Mindmap
PDF

0

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/