Recent technological advances have transformed the research on physical activity initially based on questionnaire data to the most recent objective data from accelerometers. The shift to availability of raw accelerations has increased measurement accuracy, transparency, and the potential for data harmonization. However, it has also shifted the need for considerable processing expertise to the researcher. Many users do not have this expertise. The R package GGIR has been made available to all as a tool to convermulti-day high resolution raw accelerometer data from wearable movement sensors into meaningful evidence-based outcomes and insightful reports for the study of human daily physical activity and sleep. This paper aims to provide a one-stop overview of GGIR package, the papers underpinning the theory of GGIR, and how research contributes to the continued growth of the GGIR package. The package includes a range of literature-supported methods to clean the data and provide day-by-day, as well as full recording, weekly, weekend, and weekday estimates of physical activity and sleep parameters. In addition, the package also comes with a shell function that enables the user to process a set of input files and produce csv summary reports with a single function call, ideal for users less proficient in R. GGIR has been used in over 90 peer-reviewed scientific publications to date. The evolution of GGIR over time and widespread use across a range of research areas highlights the importance of open source software development for the research community and advancing methods in physical behavior research.
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- Author: Jairo H. Migueles x
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Jairo H. Migueles, Alex V. Rowlands, Florian Huber, Séverine Sabia, and Vincent T. van Hees
Maria Jose Arias-Tellez, Francisco M. Acosta, Jairo H. Migueles, Jose M. Pascual-Gamarra, Elisa Merchan-Ramirez, Clarice M. de Lucena Martins, Jose M. Llamas-Elvira, Borja Martinez-Tellez, and Jonatan R. Ruiz
The role of lifestyle behaviors on neck adipose tissue (NAT), a fat depot that appears to be involved in the pathogenesis of different cardiometabolic diseases and in inflammatory status, is unknown. In this cross-sectional and exploratory study, the authors examined the relationship between sedentary time and physical activity (PA) with neck adiposity in young adults. A total of 134 subjects (69% women, 23 ± 2 years) were enrolled. The time spent in sedentary behavior and PA of different intensity were objectively measured for 7 consecutive days (24 hr/day), using a wrist (nondominant)-worn accelerometer. The NAT volume was assessed using computed tomography, and the compartmental (subcutaneous, intermuscular, and perivertebral) and total NAT volumes were determined at the level of vertebra C5. Anthropometric indicators and body composition (by dual-energy X-ray absorptiometry) were determined. The time spent in light physical activity and moderate physical activity (MPA) and the overall PA were inversely associated with the intermuscular NAT volume in men, as were the MPA and overall PA with total NAT volume (all ps ≤ .04). Sedentary time was directly related to the total NAT volume (p = .04). An opposite trend was observed in women, finding a direct relationship of MPA with the subcutaneous NAT; of light physical activity, MPA, and overall PA with the perivertebral NAT; and of light physical activity with total NAT volumes (all ps ≤ .05). The observed associations were weak, and after adjusting for multiplicity, the results became nonsignificant (p > .05). These findings suggest that the specific characteristics of PA (time and intensity) might have sex-dependent implications in the accumulation of NAT.
