Dale W. Esliger

Validation of the Genea Accelerometer

PURPOSE The study aims were: 1) to assess the technical reliability and validity of the GENEA using a mechanical shaker; 2) to perform a GENEA value calibration to develop thresholds for sedentary and light-, moderate-, and vigorous-intensity physical activity; and 3) to compare the intensity classification of the GENEA with two widely used accelerometers. METHODS A total of 47 GENEA accelerometers were attached to a shaker and vertically accelerated, generating 15 conditions of varying acceleration and/or frequency. Reliability was calculated using SD and intrainstrument and interinstrument coefficients of variation, whereas validity was assessed using Pearson correlation with the shaker acceleration as the criterion. Next, 60 adults wore a GENEA on each wrist and on the waist (alongside an ActiGraph and RT3 accelerometer) while completing 10-12 activity tasks. A portable metabolic gas analyzer provided the criterion measure of physical activity. Analyses involved the use of Pearson correlations to establish criterion and concurrent validity and receiver operating characteristic curves to establish intensity cut points. RESULTS The GENEA demonstrated excellent technical reliability (CVintra = 1.4%, CVinter = 2.1%) and validity (r = 0.98, P < 0.001) using the mechanical shaker. The GENEA demonstrated excellent criterion validity using VO2 as the criterion (left wrist, r = 0.86; right wrist, r = 0.83; waist, r = 0.87), on par with the waist-worn ActiGraph and RT3. The GENEA demonstrated excellent concurrent validity compared with the ActiGraph (r = 0.92) and the RT3 (r = 0.97). The waist-worn GENEA had the greatest classification accuracy (area under the receiver operating characteristic curve (AUC) = 0.95), followed by the left (AUC = 0.93) and then the right wrist (AUC = 0.90). The accuracy of the waist-worn GENEA was virtually identical with that of the ActiGraph (AUC = 0.94) and RT3 (AUC = 0.95). CONCLUSION The GENEA is a reliable and valid measurement tool capable of classifying the intensity of physical activity in adults.

Sustained and Shorter Bouts of Physical Activity are Related to Cardiovascular Health

PURPOSE Whereas greater physical activity (PA) is known to prevent cardiovascular disease (CVD), the relative importance of performing PA in sustained bouts of activity versus shorter bouts of activity on CVD risk is not known. The objective of this study was to investigate the relationship between moderate-to-vigorous PA (MVPA), measured in bouts ≥10 and <10 min, and CVD risk factors in a well-characterized community-based sample of white adults. METHODS We conducted a cross-sectional analysis of 2109 participants in the Third Generation Cohort of the Framingham Heart Study (mean age = 47 yr, 55% women) who underwent objective assessment of PA by accelerometry over 5-7 d. Total MVPA, MVPA done in bouts ≥10 min (MVPA(10+)), and MVPA done in bouts <10 min (MVPA(<10)) were calculated. MVPA exposures were related to individual CVD risk factors, including measures of adiposity and blood lipid and glucose levels, using linear and logistic regression. RESULTS Total MVPA was significantly associated with higher HDL levels and with lower triglycerides, BMI, waist circumference, and Framingham risk score (P < 0.0001). MVPA(<10) showed similar statistically significant associations with these CVD risk factors (P < 0.001). Compliance with national guidelines (≥150 min of total MVPA) was significantly related to lower BMI, triglycerides, Framingham risk score, waist circumference, higher HDL, and a lower prevalence of obesity and impaired fasting glucose (P < 0.001 for all). CONCLUSIONS Our cross-sectional observations on a large middle-age community-based sample confirm a positive association of MVPA with a healthier CVD risk factor profile and indicate that accruing PA in bouts <10 min may favorably influence cardiometabolic risk. Additional investigations are warranted to confirm our findings.

Physical activity and inactivity profiling: the next generation.

The accurate measurement of habitual physical activity is fundamental to the study of the relationship between physical activity and health. However, many physical activity measurement techniques produce variables accurate to only the day level, such as total energy expenditure via self-report questionnaire, pedometer step counts, or accelerometer measurements of minutes of moderate to vigorous physical activity. Monitoring technologies providing more detailed information on physical activity and inactivity behaviour can now be used to explore the relationships between health and movement frequency, intensity, and duration more comprehensively. This paper explores the activity-inactivity profile that can be acquired through objective monitoring, with a focus on accelerometry. Using previously collected objective data, a detailed physical activity profile is presented and case study examples of data utilization and interpretation are provided. The rich detail captured through comprehensive profiling creates new surveillance and study possibilities and could possibly inform new physical activity guidelines. Data are presented in various formats to demonstrate the dangers of misinterpretation when monitoring population adherence to Canadas physical activity guidelines. Recommendations for physical activity-inactivity profiling are provided and future research needs identified.

Incidental movement, lifestyle-embedded activity and sleep: new frontiers in physical activity assessment.

Canadian public health messages relating to physical activity have historically focused on the prescription of purposeful exercise, most often assessing leisure-time physical activity (LTPA). Although LTPA contributes to total energy expenditure (TEE), a large part of the day remains neglected unless one also considers the energy expended outside of purposeful exercise. This paper reviews the potential impact of incidental (non-exercise or non-purposeful) physical activity and lifestyle-embedded activities (chores and incidental walking) upon TEE and indicators of health. Given that incidental movement occurs sporadically throughout the day, this form of energy expenditure is perhaps most vulnerable to increasingly ubiquitous mechanization and automation. The paper also explores the relationship of physical inactivity, including sleep, to physical activity, TEE, and health outcomes. Suggestions are provided for a more comprehensive physical activity recommendation that includes all components of TEE. Objective physical activity monitors with time stamps are considered as a better means to capture and examine human movements over the entire day.

International children's accelerometry database (ICAD): Design and methods

BackgroundOver the past decade, accelerometers have increased in popularity as an objective measure of physical activity in free-living individuals. Evidence suggests that objective measures, rather than subjective tools such as questionnaires, are more likely to detect associations between physical activity and health in children. To date, a number of studies of children and adolescents across diverse cultures around the globe have collected accelerometer measures of physical activity accompanied by a broad range of predictor variables and associated health outcomes. The International Childrens Accelerometry Database (ICAD) project pooled and reduced raw accelerometer data using standardized methods to create comparable outcome variables across studies. Such data pooling has the potential to improve our knowledge regarding the strength of relationships between physical activity and health. This manuscript describes the contributing studies, outlines the standardized methods used to process the accelerometer data and provides the initial questions which will be addressed using this novel data repository.MethodsBetween September 2008 and May 2010 46,131 raw Actigraph data files and accompanying anthropometric, demographic and health data collected on children (aged 3-18 years) were obtained from 20 studies worldwide and data was reduced using standardized analytical methods.ResultsWhen using ≥ 8, ≥ 10 and ≥ 12 hrs of wear per day as a criterion, 96%, 93.5% and 86.2% of the males, respectively, and 96.3%, 93.7% and 86% of the females, respectively, had at least one valid day of data.ConclusionsPooling raw accelerometer data and accompanying phenotypic data from a number of studies has the potential to: a) increase statistical power due to a large sample size, b) create a more heterogeneous and potentially more representative sample, c) standardize and optimize the analytical methods used in the generation of outcome variables, and d) provide a means to study the causes of inter-study variability in physical activity. Methodological challenges include inflated variability in accelerometry measurements and the wide variation in tools and methods used to collect non-accelerometer data.

Utilization and Harmonization of Adult Accelerometry Data: Review and Expert Consensus.

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Technical Reliability Assessment of the Actigraph GT1M Accelerometer

The purpose of this study was to determine the reliability of the Actigraph GT1M (Pensacola, FL, USA) accelerometer activity count and step functions. Fifty GT1M accelerometers were initialized to collect simultaneous acceleration counts and steps data using 15-sec epochs. All reliability testing was completed using a mechanical shaker plate to perform six different test conditions in Experiment 1 and 18 test conditions in Experiment 2. The overall intra- and inter-instrument reliability of the GT1M was CVintra = 2.9% and CVinter = 3.5% for counts and CVintra = 1.1% and CVinter = 1.2% for steps. No batch effects were evident in the 50 GT1Ms. The Actigraph GT1M accelerometer demonstrated good reliability for measuring both counts and steps. However, the ability of the GT1M to consistently detect acceleration at a given acceleration and frequency condition varied widely. Future studies clarifying the filtering limitations and the threshold necessary to detect the occurrence of movement are warranted.

Physical Activity Profile of Old Order Amish, Mennonite, and Contemporary Children

PURPOSE This study explored the influence of modernity on the physical activity behaviors (e.g., intensity and timing) of children. METHODS Children aged 8-13 yr living a traditional lifestyle (Old Order Amish [OOA], n = 68; Old Order Mennonite [OOM], n = 120) were compared with children living a contemporary lifestyle (rural Saskatchewan [RSK], n = 132; urban Saskatchewan [USK], n = 93). Physical activity was objectively assessed for seven consecutive days using Actigraph 7164 accelerometers. Custom software was used to reduce the raw accelerometer data into standardized outcome variables. RESULTS On weekdays, there were group differences in moderate physical activity between all lifestyle groups (OOA > OOM > USK > RSK). On the weekend, the group differences in moderate physical activity persisted between, but not within, lifestyle groups (OOA = OOM > USK = RSK). During school hours, all groups had similar activity and inactivity periods; however, they differed in magnitude, with the OOA and OOM being both more sedentary and more active. In comparison with the children in school, the OOA and the OOM children had 44% lower sedentary time out of school compared with only 15% lower for RSK and USK children. CONCLUSIONS Although cross sectional, these data suggest that contemporary/modern living is associated with lower levels of moderate- and vigorous-intensity physical activity compared with lifestyles representative of earlier generations. Analyzing the physical activity and inactivity patterns of traditional lifestyle groups such as the OOA and the OOM can provide valuable insight into the quantity and quality of physical activity necessary to promote health.

Devices for Self-Monitoring Sedentary Time or Physical Activity: A Scoping Review

Background It is well documented that meeting the guideline levels (150 minutes per week) of moderate-to-vigorous physical activity (PA) is protective against chronic disease. Conversely, emerging evidence indicates the deleterious effects of prolonged sitting. Therefore, there is a need to change both behaviors. Self-monitoring of behavior is one of the most robust behavior-change techniques available. The growing number of technologies in the consumer electronics sector provides a unique opportunity for individuals to self-monitor their behavior. Objective The aim of this study is to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary time and/or PA. Methods To identify technologies, four scientific databases were systematically searched using key terms related to behavior, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1, 2015. Results The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored PA, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring PA and/or sedentary behavior; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on PA (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary time (activPAL VT, the Lumo Back, and Darma). Conclusions There are a large number of devices that self-monitor PA; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behavior change interventions, although the growing field of wearable technology may facilitate this to change.

Validation of the Actiheart activity monitor for measurement of activity energy expenditure in children and adolescents with chronic disease

Background/Objectives:The purpose of this study was to develop an activity energy expenditure (AEE) prediction equation for the Actiheart activity monitor for use in children with chronic disease.Subjects/Methods:In total, 63 children, aged 8–18 years with different types of chronic disease (juvenile arthritis, hemophilia, dermatomyositis, neuromuscular disease, cystic fibrosis or congenital heart disease) participated in an activity testing session, which consisted of a resting protocol, working on the computer, sweeping, hallway walking, steps and treadmill walking at three different speeds. During all activities, actual AEE was measured with indirect calorimetry and the participants wore an Actiheart on the chest. Resting EE and resting heart rate were measured during the resting protocol and heart rate above sleep (HRaS) was calculated.Results:Mixed linear modeling produced the following prediction equation: This equation results in a nonsignificant mean difference of 2.1 J/kg/min (limits of agreement: −144.2 to 148.4 J/kg/min) for the prediction of AEE from the Actiheart compared with actual AEE.Conclusions:The Actiheart is valid for the use of AEE determination when using the new prediction equation for groups of children with chronic disease. However, the prediction error limits the use of the equation in individual subjects.