Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study

Background Accelerometers objectively assess physical activity (PA) and are currently used in several large-scale epidemiological studies, but there is no consensus for processing the data. This study compared the impact of wear-time assessment methods and using either vertical (V)-axis or vector ma...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:BMC public health Ročník 14; číslo 1; s. 1210
Hlavní autoři: Keadle, Sarah Kozey, Shiroma, Eric J, Freedson, Patty S, Lee, I-Min
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 24.11.2014
BioMed Central Ltd
Springer Nature B.V
Témata:
Accelerometers
Accelerometry - instrumentation
Accelerometry - methods
Adult
Aged
Algorithms
Analysis
Automatic Data Processing - instrumentation
Automatic Data Processing - methods
Biostatistics
Biostatistics and methods
Body Mass Index
Cohort Studies
Data processing
Environmental Health
Epidemiologic Measurements
Epidemiology
Exercise - physiology
Female
Humans
Medical research
Medicine
Medicine & Public Health
Middle Aged
Monitoring, Ambulatory - instrumentation
Physical Examination
Public Health
Research Article
Sample Size
Studies
Time Factors
Vaccine
Womens health
Measurement
Sedentary behavior
Physical activity
Exposure assessment
Behavioral epidemiology
ISSN:1471-2458, 1471-2458
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Background Accelerometers objectively assess physical activity (PA) and are currently used in several large-scale epidemiological studies, but there is no consensus for processing the data. This study compared the impact of wear-time assessment methods and using either vertical (V)-axis or vector magnitude (VM) cut-points on accelerometer output. Methods Participants (7,650 women, mean age 71.4 y) were mailed an accelerometer (ActiGraph GT3X+), instructed to wear it for 7 days, record dates and times the monitor was worn on a log, and return the monitor and log via mail. Data were processed using three wear-time methods (logs, Troiano or Choi algorithms) and V-axis or VM cut-points. Results Using algorithms alone resulted in "mail-days" incorrectly identified as "wear-days" (27-79% of subjects had >7-days of valid data). Using only dates from the log and the Choi algorithm yielded: 1) larger samples with valid data than using log dates and times, 2) similar wear-times as using log dates and times, 3) more wear-time (V, 48.1 min more; VM, 29.5 min more) than only log dates and Troiano algorithm. Wear-time algorithm impacted sedentary time (~30-60 min lower for Troiano vs. Choi) but not moderate-to-vigorous (MV) PA time. Using V-axis cut-points yielded ~60 min more sedentary time and ~10 min less MVPA time than using VM cut-points. Conclusions Combining log-dates and the Choi algorithm was optimal, minimizing missing data and researcher burden. Estimates of time in physical activity and sedentary behavior are not directly comparable between V-axis and VM cut-points. These findings will inform consensus development for accelerometer data processing in ongoing epidemiologic studies.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ISSN:1471-2458
1471-2458
DOI:10.1186/1471-2458-14-1210