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Comparison of sleep parameters from wrist-worn ActiGraph and Actiwatch devices.
Liu, Fangyu; Schrack, Jennifer; Wanigatunga, Sarah K; Rabinowitz, Jill A; He, Linchen; Wanigatunga, Amal A; Zipunnikov, Vadim; Simonsick, Eleanor M; Ferrucci, Luigi; Spira, Adam P.
Afiliação
  • Liu F; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Schrack J; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Wanigatunga SK; Center on Aging and Health, Johns Hopkins University, Baltimore, Maryland, USA.
  • Rabinowitz JA; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • He L; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Wanigatunga AA; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Zipunnikov V; Department of Community and Population Health, College of Health, Lehigh University, Bethlehem, Pennsylvania, USA.
  • Simonsick EM; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Ferrucci L; Center on Aging and Health, Johns Hopkins University, Baltimore, Maryland, USA.
  • Spira AP; Center on Aging and Health, Johns Hopkins University, Baltimore, Maryland, USA.
Sleep ; 47(2)2024 Feb 08.
Article em En | MEDLINE | ID: mdl-37257489
ABSTRACT
Sleep and physical activity, two important health behaviors, are often studied independently using different accelerometer types and body locations. Understanding whether accelerometers designed for monitoring each behavior can provide similar sleep parameter estimates may help determine whether one device can be used to measure both behaviors. Three hundred and thirty one adults (70.7 ±â€…13.7 years) from the Baltimore Longitudinal Study of Aging wore the ActiGraph GT9X Link and the Actiwatch 2 simultaneously on the non-dominant wrist for 7.0 ±â€…1.6 nights. Total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, number of wake bouts, mean wake bout length, and sleep fragmentation index (SFI) were extracted from ActiGraph using the Cole-Kripke algorithm and from Actiwatch using the software default algorithm. These parameters were compared using paired t-tests, Bland-Altman plots, and Deming regression models. Stratified analyses were performed by age, sex, and body mass index (BMI). Compared to the Actiwatch, the ActiGraph estimated comparable TST and sleep efficiency, but fewer wake bouts, longer WASO, longer wake bout length, and higher SFI (all p < .001). Both devices estimated similar 1-min and 1% differences between participants for TST and SFI (ß = 0.99, 95% CI 0.95, 1.03, and 0.91, 1.13, respectively), but not for other parameters. These differences varied by age, sex, and/or BMI. The ActiGraph and the Actiwatch provide comparable absolute and relative estimates of TST, but not other parameters. The discrepancies could result from device differences in movement collection and/or sleep scoring algorithms. Further comparison and calibration is required before these devices can be used interchangeably.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Punho / Actigrafia Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Punho / Actigrafia Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article