Using a Consumer Wearable Activity Monitoring Device to Study Physical Activity and Sleep Among Adolescents in Project Viva: Cohort Study

Overview

Journal JMIR Pediatr Parent

Date 2025 Feb 4

PMID 39903900

Authors

Yutong Zhang

Nicole Bornkamp

Marie-France Hivert

Emily Oken

Peter James

Affiliations

Soon will be listed here.

Abstract

Background: The increasing prevalence of physical inactivity and insufficient sleep in adolescents likely contribute to worsening cardiometabolic and mental health. However, obtaining accurate behavioral measures is a challenge. Consumer wearable devices offer a user-friendly method to assess physical activity and sleep.

Objective: This study aimed to describe the process and the preliminary results of physical activity and sleep collected using a consumer wearable Fitbit device in an adolescent cohort.

Methods: We provided Fitbit Charge 2 or Charge 3 wrist-worn activity monitors to adolescent participants in Project Viva, a Boston, Massachusetts area cohort, from 2017 to 2022. We invited participants to wear the devices for ≥7 days for 24 hours a day to measure their physical activity, heart rate, and sleep, and allowed them to keep the device as a participation incentive.

Results: We collected over 7 million minutes of physical activity, heart rate, and sleep data from 677 participants, 53% (356/677) of whom were female. The mean (SD) age of participants was 17.7 (0.7) years. Among the 677 participants, 65% (n=439) were non-Hispanic White, 14% (n=947) were non-Hispanic Black, 10% (n=69) were Hispanic, 3.2% (n=22) were non-Hispanic Asian, and 7.8% (n=53) belonged to other races. Participants demonstrated a high adherence to the research protocol, with the mean (SD) wear duration of 7.5 (1.1) days, and 90% of participants (612/677) had 5 or more days wearing the device for >600 minutes/day. The mean (SD) number of steps was 8883 (3455) steps/day and the mean (SD) awake sedentary time was 564 (138) minutes/day. Male participants were more often engaged in very active (27 minutes/day) and moderately active physical activity (29 minutes/day) compared with female participants (15 and 17 minutes/day, respectively). Over 87% (588/677) of participants had sleep data available for 5 or more days, among whom the average nightly sleep duration was 7.9 (SD 0.9) hours.

Conclusions: This study demonstrated the feasibility of using consumer wearable devices to measure physical activity and sleep in a cohort of US adolescents. The high compliance rates provide valuable insights into adolescent behavior patterns and their influence on chronic disease development and mental health outcomes.

References

Lang C, Kalak N, Brand S, Holsboer-Trachsler E, Puhse U, Gerber M . The relationship between physical activity and sleep from mid adolescence to early adulthood. A systematic review of methodological approaches and meta-analysis. Sleep Med Rev. 2015; 28:32-45. DOI: 10.1016/j.smrv.2015.07.004. View

Korczak D, Madigan S, Colasanto M . Children's Physical Activity and Depression: A Meta-analysis. Pediatrics. 2017; 139(4). DOI: 10.1542/peds.2016-2266. View

Aili K, Astrom-Paulsson S, Stoetzer U, Svartengren M, Hillert L . Reliability of Actigraphy and Subjective Sleep Measurements in Adults: The Design of Sleep Assessments. J Clin Sleep Med. 2016; 13(1):39-47. PMC: 5181612. DOI: 10.5664/jcsm.6384. View

Wang X, Cai Z, Jiang W, Fang Y, Sun W, Wang X . Systematic review and meta-analysis of the effects of exercise on depression in adolescents. Child Adolesc Psychiatry Ment Health. 2022; 16(1):16. PMC: 8886903. DOI: 10.1186/s13034-022-00453-2. View

Haghayegh S, Khoshnevis S, Smolensky M, Diller K . Accuracy of PurePulse photoplethysmography technology of Fitbit Charge 2 for assessment of heart rate during sleep. Chronobiol Int. 2019; 36(7):927-933. DOI: 10.1080/07420528.2019.1596947. View

Saunders T, Chaput J, Tremblay M . Sedentary behaviour as an emerging risk factor for cardiometabolic diseases in children and youth. Can J Diabetes. 2014; 38(1):53-61. DOI: 10.1016/j.jcjd.2013.08.266. View

Vooijs M, Alpay L, Snoeck-Stroband J, Beerthuizen T, Siemonsma P, Abbink J . Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. Interact J Med Res. 2014; 3(4):e14. PMC: 4259960. DOI: 10.2196/ijmr.3056. View

Evenson K, Goto M, Furberg R . Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015; 12:159. PMC: 4683756. DOI: 10.1186/s12966-015-0314-1. View

Stahl S, An H, Dinkel D, Noble J, Lee J . How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough?. BMJ Open Sport Exerc Med. 2016; 2(1):e000106. PMC: 5117066. DOI: 10.1136/bmjsem-2015-000106. View

10.

Fore R, Hart J, Choirat C, Thompson J, Lynch K, Laden F . Embedding Mobile Health Technology into the Nurses' Health Study 3 to Study Behavioral Risk Factors for Cancer. Cancer Epidemiol Biomarkers Prev. 2020; 29(4):736-743. PMC: 7171700. DOI: 10.1158/1055-9965.EPI-19-1386. View

11.

Zhang J, Paksarian D, Lamers F, Hickie I, He J, Merikangas K . Sleep Patterns and Mental Health Correlates in US Adolescents. J Pediatr. 2016; 182:137-143. DOI: 10.1016/j.jpeds.2016.11.007. View

12.

de Zambotti M, Baker F, Willoughby A, Godino J, Wing D, Patrick K . Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents. Physiol Behav. 2016; 158:143-9. PMC: 5498752. DOI: 10.1016/j.physbeh.2016.03.006. View

13.

Nelson M, Kaminsky L, Dickin D, Montoye A . Validity of Consumer-Based Physical Activity Monitors for Specific Activity Types. Med Sci Sports Exerc. 2016; 48(8):1619-28. DOI: 10.1249/MSS.0000000000000933. View

14.

Gradisar M, Gardner G, Dohnt H . Recent worldwide sleep patterns and problems during adolescence: a review and meta-analysis of age, region, and sleep. Sleep Med. 2011; 12(2):110-8. DOI: 10.1016/j.sleep.2010.11.008. View

15.

Brand S, Kirov R . Sleep and its importance in adolescence and in common adolescent somatic and psychiatric conditions. Int J Gen Med. 2011; 4:425-42. PMC: 3119585. DOI: 10.2147/IJGM.S11557. View

16.

Mahmood A, Kim H, Kedia S, Dillon P . Wearable Activity Tracker Use and Physical Activity Among Informal Caregivers in the United States: Quantitative Study. JMIR Mhealth Uhealth. 2022; 10(11):e40391. PMC: 9732754. DOI: 10.2196/40391. View

17.

Glabska D, Guzek D, Mellova B, Zadka K, Zywczyk K, Gutkowska K . The National After-School Athletics Program Participation as a Tool to Reduce the Risk of Obesity in Adolescents after One Year of Intervention: A Nationwide Study. Int J Environ Res Public Health. 2019; 16(3). PMC: 6388155. DOI: 10.3390/ijerph16030405. View

18.

Gupta N, Mueller W, Chan W, Meininger J . Is obesity associated with poor sleep quality in adolescents?. Am J Hum Biol. 2002; 14(6):762-8. DOI: 10.1002/ajhb.10093. View

19.

Godino J, Wing D, de Zambotti M, Baker F, Bagot K, Inkelis S . Performance of a commercial multi-sensor wearable (Fitbit Charge HR) in measuring physical activity and sleep in healthy children. PLoS One. 2020; 15(9):e0237719. PMC: 7473549. DOI: 10.1371/journal.pone.0237719. View

20.

Hysing M, Pallesen S, Stormark K, Lundervold A, Sivertsen B . Sleep patterns and insomnia among adolescents: a population-based study. J Sleep Res. 2013; 22(5):549-56. DOI: 10.1111/jsr.12055. View