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Bidirectional associations of accelerometer measured sedentary behavior and physical activity with knee pain, stiffness, and physical function: The CARDIA study.

Preventive medicine reports | 2021

The objective was to examine bidirectional associations of accelerometer estimated sedentary time and physical activity with reported knee symptoms. Participants were 2,034 adults (mean age 45.3 ± 3.6 years, 58.7% female) from CARDIA. Generalized estimating equations for logistic regression and linear mixed regression models examined associations of accelerometer estimated sedentary time, light-intensity physical activity (LPA), and moderate-to-vigorous intensity physical activity (MVPA) at baseline (2005-06) with knee discomfort, pain, stiffness, and physical function (yes/no and continuous scores from short-form WOMAC function scale) at the 5- and 10-year follow-up exams. Linear regression models examined associations between knee symptoms at the 5-year follow-up with accelerometer estimates at the 10-year follow-up. Models were adjusted for confounders; individuals with comorbidities were excluded in sensitivity analyses. A 30 min/day increment in sedentary time at baseline was associated with lower odds of knee symptoms at the 5- and 10-year follow-up (OR: 0.95, 95% CI range: 0.92-0.98), while LPA and MVPA were associated with greater odds of knee symptoms (LPA OR range: 1.04-1.05, 95% CI range: 1.01-1.09; MVPA OR range: 1.17-1.19, 95% CI range: 1.06-1.32). Report of knee symptoms at the 5-year follow-up was associated with 13.52-17.51 (95% CI range: -29.90, -0.56) fewer minutes/day of sedentary time and 14.58-17.51 (95% CI range: 2.48, 29.38) more minutes/day of LPA at the 10-year follow-up, compared to those reporting no symptoms. Many associations were no longer statistically significant when excluding individuals with comorbidities. Findings support a bidirectional association of accelerometer estimated sedentary time and physical activity with knee symptoms across midlife.

Pubmed ID: 33816086 RIS Download

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Associated grants

  • Agency: NHLBI NIH HHS, United States
    Id: R56 HL125423
  • Agency: NHLBI NIH HHS, United States
    Id: HHSN268201800003I
  • Agency: NHLBI NIH HHS, United States
    Id: HHSN268201800007I
  • Agency: NHLBI NIH HHS, United States
    Id: K01 HL148503
  • Agency: NHLBI NIH HHS, United States
    Id: HHSN268201800005I
  • Agency: NHLBI NIH HHS, United States
    Id: HHSN268201800006I
  • Agency: NHLBI NIH HHS, United States
    Id: R01 HL078972
  • Agency: NHLBI NIH HHS, United States
    Id: HHSN268201800004I

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ActiGraph Activity Monitor Devices (tool)

RRID:SCR_008399

Commercial instrument supplier for human activity monitors. ActiGraph devices are used by researchers and clinicians in hundreds of universities and research organizations in more than 56 countries. ActiGraph activity monitors are the most validated and widely used devices of their kind. ActiGraph activity monitors use triaxial accelerometers and our validated proprietary filtering algorithms to accurately measure the amount and intensity of human activity. They are powered by rechargeable lithium ion batteries, and battery charging and communication are accomplished via a standard USB connection. All ActiGraph activity monitors can be worn at the waist or wrist and are suitable for subjects of all ages. ActiGraph devices have been used in hundreds of research studies in nearly 60 countries around the world since 1992. Leading research facilities including the U.S. National Institute of Health (NIH), the Institute of Child Health in the UK, and Karolinska Institutet in Sweden rely on our products to provide objective activity measurement in dozens of areas including obesity, diabetes, sleep, elderly behavior, and athletics. ActiGraph often works with scientific organizations to develop and implement software and hardware features that reflect the evolving needs of the research community. ActiGraph devices are well recognized as some of the most accurate activity measurement products on the market. Extensive research has confirmed our accuracy against the VO2 and doubly labeled water (DLW) methods of estimating energy expenditure. Keywords: Device, Researcher, Clinician, University, Research, Organization, Obesity, Diabetes, Sleep, Elderly, Behavior, Athletics, Scientific, Activity monitor, Physical, Measurement, Human, Activity,

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