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.
Jairo H. Migueles, Alex V. Rowlands, Florian Huber, Séverine Sabia and Vincent T. van Hees
Alex V. Rowlands, Tatiana Plekhanova, Tom Yates, Evgeny M. Mirkes, Melanie Davies, Kamlesh Khunti and Charlotte L. Edwardson
Introduction: To capitalize on the increasing availability of accelerometry data for epidemiological research it is desirable to compare and/or pool data from surveys worldwide. This study aimed to establish whether free-living physical activity outcomes can be considered equivalent between three research-grade accelerometer brands worn on the dominant and non-dominant wrist. Of prime interest were the average acceleration (ACC) and the intensity gradient (IG). These two metrics describe the volume and intensity of the complete activity profile; further, they are comparable across populations making them ideal for comparing and/or pooling activity data. Methods: Forty-eight adults wore a GENEActiv, Axivity, and ActiGraph on both wrists for up to 7-days. Data were processed using open-source software (GGIR) to generate physical activity outcomes, including ACC and IG. Agreement was assessed using pairwise 95% equivalence tests (±10% equivalence zone) and intra-class correlation coefficients (ICC). Results: ACC was equivalent between brands when measured at the non-dominant wrist (ICC ≥ 0.93), but approximately 10% higher when measured at the dominant wrist (GENEActiv and Axivity only, ICC ≥ 0.83). The IG was equivalent irrespective of monitor brand or wrist (ICC ≥ 0.88). After adjusting ACC measured at the dominant wrist by −10% (GENEActiv and Axivity only), ACC was also within (or marginally outside) the 10% equivalence zone for all monitor pairings. Conclusion: If average acceleration is decreased by 10% for studies deploying monitors on the dominant wrist (GENEActiv and Axivity only), ACC and IG may be suitable for comparing and/or collating physical activity outcomes across accelerometer datasets, regardless of monitor brand and wrist.
Rawan Hashem, Juan P. Rey-López, Mark Hamer, Anne McMunn, Peter H. Whincup, Christopher G. Owen, Alex Rowlands and Emmanuel Stamatakis
Background: There is only scarce number of studies available describing the lifestyle of adolescents living in Arab countries. Hence, we described physical activity (PA) and sedentary behaviors patterns among Kuwaiti adolescents and the associations with parental education. Methods: Cross-sectional data from 435 adolescents (201 boys and 234 girls) were collected from the Study of Health and Activity among Adolescents in Kuwait conducted between 2012 and 2013. Outcome variables included PA (ActiGraph GT1M accelerometers) and sedentary behaviors. Exposure variable was parental education. Descriptive and multiple logistic regression analyses were used to examine the association between parental education and outcome variables. Results: Total sedentary time (minutes per day) was higher in girls [568.2 (111.6)] than in boys [500.0 (102.0)], whereas boys accumulated more minutes in light, moderate, and vigorous PA (all Ps ≤ .001). In total, 3.4% of adolescents spent ≥60 minutes per day of moderate to vigorous PA (by accelerometry), while only 21% met the screen time guidelines. Low/medium maternal education was associated with a higher odds of exceeding screen time guidelines (odds ratio = 2.09; 95% confidence interval, 1.09–4.02). Conclusions: Most Kuwaiti adolescents in this sample were physically inactive and exceeded screen time guidelines. Objective PA was not socially patterned, yet an inverse association between maternal education and screen time behaviors was found.
Alon Eliakim, Bareket Falk, Neil Armstrong, Fátima Baptista, David G. Behm, Nitzan Dror, Avery D. Faigenbaum, Kathleen F. Janz, Jaak Jürimäe, Amanda L. McGowan, Dan Nemet, Paolo T. Pianosi, Matthew B. Pontifex, Shlomit Radom-Aizik, Thomas Rowland and Alex V. Rowlands
This commentary highlights 23 noteworthy publications from 2018, selected by leading scientists in pediatric exercise science. These publications have been deemed as significant or exciting in the field as they (a) reveal a new mechanism, (b) highlight a new measurement tool, (c) discuss a new concept or interpretation/application of an existing concept, or (d) describe a new therapeutic approach or clinical tool in youth. In some cases, findings in adults are highlighted, as they may have important implications in youth. The selected publications span the field of pediatric exercise science, specifically focusing on: aerobic exercise and training; neuromuscular physiology, exercise, and training; endocrinology and exercise; resistance training; physical activity and bone strength; growth, maturation, and exercise; physical activity and cognition; childhood obesity, physical activity, and exercise; pulmonary physiology or diseases, exercise, and training; immunology and exercise; cardiovascular physiology and disease; and physical activity, inactivity, and health.