Technologies that assess the location of physical activity and sedentary behavior: a systematic review

Background: The location in which physical activity and sedentary behavior are performed can provide valuable behavioral information, both in isolation and synergistically with other areas of physical activity and sedentary behavior research. Global positioning systems (GPS) have been used in physical activity research to identify outdoor location; however, while GPS can receive signals in certain indoor environments, it is not able to provide room- or subroom-level location. On average, adults spend a high proportion of their time indoors. A measure of indoor location would, therefore, provide valuable behavioral information. Objective: This systematic review sought to identify and critique technology which has been or could be used to assess the location of physical activity and sedentary behavior. Methods: To identify published research papers, four electronic databases were searched using key terms built around behavior, technology, and location. To be eligible for inclusion, papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed up to February 4, 2015. This was supplemented by backward and forward reference searching. In an attempt to include novel devices which may not yet have made their way into the published research, searches were also performed using three Internet search engines. Specialized software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms. Results: A total of 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras, and radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems, and 21 wearable cameras. Real-time locating systems determine the indoor location of a wearable tag via the known location of reference nodes. Although the type of reference node and location determination method varies between manufacturers, Wi-Fi appears to be the most popular method. Conclusions: The addition of location information to existing measures of physical activity and sedentary behavior will provide important behavioral information

Accuracy of Sedentary Behavior-Triggered Ecological Momentary Assessment for Collecting Contextual Information: Development and Feasibility Study

Background: Sedentary behavior has received much attention in the scientific community over the past decade. There is growing evidence that sedentary behavior is negatively associated with physical and mental health. However, an in-depth understanding of the social and environmental context of sedentary behavior is missing. Information about sedentary behavior, such as how everyday sedentary behavior occurs throughout the day (eg, number and length of sedentary bouts), where, when, and with whom it takes place, and what people are doing while being sedentary, is useful to inform the development of interventions aimed at reducing sedentary time. However, examining everyday sedentary behavior requires specific methods. Objective: The purpose of this paper is (1) to introduce sedentary behavior–triggered Ecological Momentary Assessment (EMA) as a methodological advancement in the field of sedentary behavior research and (2) to examine the accuracy of sedentary behavior–triggered EMA in 3 different studies in healthy adults. Moreover, we compare the accuracy of sedentary behavior–triggered EMA to simulations of random-trigger designs. Methods: Sedentary behavior–triggered EMA comprises a continuous assessment of sedentary behavior via accelerometers and repeated contextual assessments via electronic diaries (ie, an application on a smartphone). More specifically, the accelerometer analyzes and transfers data regarding body position (a sitting or lying position, or an upright position) via Bluetooth Low Energy (BLE) to a smartphone in real time and triggers the deployment of questionnaires. Each time a participant spends a specified time (eg, 20 minutes) in a sedentary position, the e-diary triggers contextual assessments. To test the accuracy of this method, we calculated a percentage score for all triggered prompts in relation to the total number of bouts that could trigger a prompt. Results: Based on the accelerometer recordings, 29.3% (5062/17278) of all sedentary bouts were classified as moderate-to-long (20-40 minutes) and long bouts (≥ 41 minutes). On average, the accuracy by participant was 82.77% (3339/4034; SD 21.01%, range 71.00-88.22%) on the study level. Compared to simulations of random prompts (every 120 minutes), the number of triggered prompts was up to 47.9% (n=704) higher through the sedentary behavior–triggered EMA approach. Nearly 40% (799/2001) of all prolonged sedentary bouts (≥ 20 minutes) occurred during work, and in 57% (1140/2001) of all bouts, the participants were not alone. Conclusions: Sedentary behavior–triggered EMA is an accurate method for collecting contextual information on sedentary behavior in daily life. Given the growing interest in sedentary behavior research, this sophisticated approach offers a real advancement as it can be used to collect social and environmental contextual information or to unravel dynamic associations. Furthermore, it can be modified to develop sedentary behavior–triggered mHealth interventions

Advancing the objective measurement of physical activity and sedentary behaviour context

Objective data from national surveillance programmes show that, on average, individuals accumulate high amounts of sedentary time per day and only a small minority of adults achieve physical activity guidelines. One potential explanation for the failure of interventions to increase population levels of physical activity or decrease sedentary time is that research to date has been unable to identify the specific behavioural levers in specific contexts needed to change behaviour. Novel technology is emerging with the potential to elucidate these specific behavioural contexts and thus identify these specific behavioural levers. Therefore the aims of this four study thesis were to identify novel technologies capable of measuring the behavioural context, to evaluate and validate the most promising technology and to then pilot this technology to assess the behavioural context of older adults, shown by surveillance programmes to be the least physically active and most sedentary age group. Study one Purpose: To identify, via a systematic review, technologies which have been used or could be used to measure the location of physical activity or sedentary behaviour. Methods: Four electronic databases were searched using key terms built around behaviour, technology and location. To be eligible for inclusion papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed from the inception of the database up to 04/02/2015. Searches were also performed using three internet search engines. Specialised software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms. Results: 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras and Radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems and 21 wearable cameras. Conclusion: The addition of location information to existing measures of physical activity and sedentary behaviour will provide important behavioural information. Study Two Purpose: This study investigated the Actigraph proximity feature across three experiments. The aim of Experiment One was to assess the basic characteristics of the Actigraph RSSI signal across a range of straight line distances. Experiment Two aimed to assess the level of receiver device signal detection in a single room under unobstructed conditions, when various obstructions are introduced and the impacts these obstructions have on the intra and inter unit variability of the RSSI signal. Finally, Experiment Three aimed to assess signal contamination across multiple rooms (i.e. one beacon being detected in multiple rooms). Methods: Across all experiments, the receiver(s) collected data at 10 second epochs, the highest resolution possible. In Experiment One two devices, one receiver and one beacon, were placed opposite each other at 10cm increments for one minute at each distance. The RSSI-distance relationship was then visually assessed for linearity. In Experiment Two, a test room was demarcated into 0.5 x 0.5 m grids with receivers simultaneously placed in each demarcated grid. This process was then repeated under wood, metal and human obstruction conditions. Descriptive tallies were used to assess the signal detection achieved for each receiver from each beacon in each grid. Mean RSSI signal was calculated for each condition alongside intra and inter-unit standard deviation, coefficient of variation and standard error of the measurement. In Experiment Three, a test apartment was used with three beacons placed across two rooms. The researcher then completed simulated conditions for 10 minutes each across the two rooms. The percentage of epochs where a signal was detected from each of the three beacons across each test condition was then calculated. Results: In Experiment One, the relationship between RSSI and distance was found to be non-linear. In Experiment Two, high signal detection was achieved in all conditions; however, there was a large degree of intra and inter-unit variability in RSSI. In Experiment Three, there was a large degree of multi-room signal contamination. Conclusion: The Actigraph proximity feature can provide a binary indicator of room level location. Study Three Purpose: To use novel technology in three small feasibility trials to ascertain where the greatest utility can be demonstrated. Methods: Feasibility Trial One assessed the concurrent validity of electrical energy monitoring and wearable cameras as measures of television viewing. Feasibility Trial Two utilised indoor location monitoring to assess where older adult care home residents accumulate their sedentary time. Lastly, Feasibility Trial Three investigated the use of proximity sensors to quantify exposure to a height adjustable desk Results: Feasibility Trial One found that on average the television is switched on for 202 minutes per day but is visible in just 90 minutes of wearable camera images with a further 52 minutes where the participant is in their living room but the television is not visible in the image. Feasibility Trial Two found that residents were highly sedentary (sitting for an average of 720 minutes per day) and spent the majority of their time in their own rooms with more time spent in communal areas in the morning than in the afternoon. Feasibility Trial Three found a discrepancy between self-reported work hours and objectively measured office dwell time. Conclusion: The feasibility trials outlined in this study show the utility of objectively measuring context to provide more detailed and refined data. Study Four Purpose: To objectively measure the context of sedentary behaviour in the most sedentary age group, older adults. Methods: 26 residents and 13 staff were recruited from two care homes. Each participant wore an Actigraph GT9X on their non-dominant wrist and a LumoBack posture sensor on their lower back for one week. The Actigraph recorded proximity every 10 seconds and acceleration at 100 Hz. LumoBack data were provided as summaries per 5 minutes. Beacon Actigraphs were placed around each care home in the resident s rooms, communal areas and corridors. Proximity and posture data were combined in 5 minute epochs with descriptive analysis of average time spent sitting in each area produced. Acceleration data were summarised into 10 second epochs and combined with proximity data to show the average count per epoch in each area of the care home. Mann-Whitney tests were performed to test for differences between care homes. Results: No significant differences were found between Care Home One and Care Home Two in the amount of time spent sitting in communal areas of the care home (301 minutes per day and 39 minutes per day respectively, U=23, p=0.057) or in the amount of time residents spent sitting in their own room (215 minutes per day and 337 minutes per day in Care Home One and Two respectively, U=32, p=0.238). In both care homes, accelerometer measured average movement increases with the number of residents in the communal area. Conclusion: The Actigraph proximity system was able to quantify the context of sedentary behaviour in older adults. This enabled the identification of levers for behaviour change which can be used to reduce sedentary time in this group. Overall conclusion: There are a large number of technologies available with the potential to measure the context of physical activity or sedentary time. The Actigraph proximity feature is one such technology. This technology is able to provide a binary measure of proximity via the detection or non-detection of Bluetooth signal: however, the variability of the signal prohibits distance estimation. The Actigraph proximity feature, in combination with a posture sensor, is able to elucidate the context of physical activity and sedentary time

Novel technology to help understand the context of physical activity and sedentary behaviour.

When used in large, national surveillance programmes, objective measurement tools provide prevalence estimates of low physical activity guideline compliance and high amounts of sedentary time. There are undoubtedly a plethora of reasons for this but one possible contributing factor is the current lack of behavioural context offered by accelerometers and posture sensors. Context includes information such as where the behaviour occurs, the type of activity being performed and is vital in allowing greater refinement of intervention strategies. Novel technologies are emerging with the potential to provide this information. Example data from three ongoing studies is used to illustrate the utility of these technologies. Study one assesses the concurrent validity of electrical energy monitoring and wearable cameras as measures of television viewing. This study found that on average the television is switched on for 202 min d(-1) but is visible in just 90 min of wearable camera images with a further 52 min where the participant is in their living room but the television is not visible in the image. Study two utilises indoor location monitoring to assess where older adult care home residents accumulate their sedentary time. This study found that residents were highly sedentary (sitting for an average of 720 min d(-1)) and spent the majority of their time in their own rooms with more time spent in communal areas in the morning than in the afternoon. Lastly, study three discusses the use of proximity sensors to quantify exposure to a height adjustable desk. These studies are example applications of this technology, with many other technologies available and applications possible. The adoption of these technologies will provide researchers with a more complete understanding of the behaviour than has previously been available

Short- and long-term effects of a multi-component physical activity intervention in primary school

There is compelling evidence that physical activity has numerous health benefits during childhood and adolescence. Insufficient levels of physical activity on the other hand can consequently affect cardiovascular and bone health, which may result in severe chronic diseases later in life. Cardiovascular disease and osteoporosis are two of the major chronic diseases affecting a large proportion of the adult population. Both diseases have their origins in childhood and it has been shown that for both, physical activity plays an important role in their prevention. The number of children not being sufficiently active has reached an alarming level and threatens to impose major health burdens worldwide. Thus, developing effective strategies to enhance children’s physical activity levels is of paramount interest for public health. School provides an optimal setting for physical activity promotion, since all children spend a large portion of their time there. This dissertation discusses a school-based randomized controlled trial aimed at increasing children’s physical activity levels and consequently their cardiovascular and bone health. The „Kinder- und Jugendsportstudie“ (KISS) is a school-based physical activity intervention lasting one school year. Of all primary school classes in the cantons of Aargau and Baselland comprising about 10% of the Swiss population, 28 first and fifth grade classes were randomly selected and allocated into an intervention (16 classes; n=297 children) and a control (12 classes, n=205 children) group. The mandatory and stringent multi-component intervention program consisted of daily physical education lessons, daily short activity breaks during academic lessons, and physical activity homework. Children in the control group had the compulsory three physical educations per week. The aim of this dissertation was to assess the effectiveness of KISS on cardiovascular risk and bone health and to explore whether the program was sufficiently effective in order to maintain health benefits over the following three years. In addition, this dissertation will provide a systematic update of existing school-based intervention studies aiming at increasing children’s physical activity and a quantification of physical education-related physical activity. There is strong evidence that school provides a promising setting for physical activity promotion. All school-based intervention studies done in recent years showed positive effects in at least one domain of physical activity. The most successful interventions had the design of a randomized controlled trial, were done over one school year using a multi-component approach integrated into the school curriculum, taught by physical education experts and involving family members. A common intervention strategy was to increase quantity and/or quality of physical education lessons. The particular role of physical education and its contribution to overall physical activity was the center of attention in the second publication of this dissertation. Even if children’s physical activity levels during physical education are relatively low, physical education contributes substantially to overall physical activity. Due to its nature of being a randomized controlled trial in children with a stringent physical activity program in and outside physical education over one school year and with the inclusion of physical education experts, KISS had excellent pre-conditions for being an effective program. Indeed, the results after nine month of intervention are promising. Compared to controls, children of the intervention group showed 14% reduced cardiovascular risk score, 5% reduced body mass index and skinfold thickness, 6% improved aerobic fitness, 18% higher physical activity levels, and 5-8% higher bone mineral content and bone mineral density. Three years after cessation of the program, intervention children still showed higher aerobic fitness and bone mineral content levels at weight-bearing sites of the skeleton compared to the control group. All other beneficial effects have disappeared. Even if short-term effects of the intervention are promising, the major key from a public health perspective is whether the effects of the prevention done during childhood will persist into late adolescence and adulthood. Although the maintained effects on aerobic fitness and bone health have considerable impact on public health, most of the beneficial health effects were not maintained three years after the intervention. This indicates that an intervention over one year is too short for maintained overall health effects. Thus, physical activity programs throughout the school years are needed. Our findings contribute to the growing body of evidence that school-based interventions can increase children’s health; however the major challenge now, is to find effective implementation strategies to transfer such programs into the real-world setting

24- hour movement behaviors and fitness in preschoolers: acompositional and isotemporal reallocation analysis

This study analyzed the associations between the 24-hour movement behaviors composition and fitness in preschoolers and investigated predicted changes in fitness when time in active behaviors is reallocated. This cross-sectional study was carried out with 270 preschoolers (132 boys; 3.97 ± 0.80 years-old). Light and moderate-to-vigorous physical activity (LPA and MVPA), and sedentary behavior (SB) were verified using an accelerometer. Sleep time was obtained through interviews with parents. Components of physical fitness (cardiorespiratory fitness—CRF, speed-agility, and lower-body muscular strength) were assessed using the PREFIT Battery. To verify the association between 24-hour movement behaviors and physical fitness, the compositional analysis was used, and for the time reallocation, the compositional isotemporal substitution analysis was used for active behaviors (LPA and MVPA). The daily composition, adjusted for body mass index, sex, and age, was significantly associated with CRF (P = .007; r2 = 0.29), speed-agility (P < .001; r2 = 0.14), and lower-body muscular strength (P = .01; r2 = 0.07). For CRF, the addition of MVPA, at the expense of any other behavior, was associated with significant improvements. For speed-agility and lower-body muscular strength, only reallocations between sleep and LPA yielded significant associations. The variation in CRF, speed-agility, and lower-body muscular strength was associated with the 24 hours movement composition, and reallocating 5, 10 or 15 minutes of SB or sleep for MVPA was significantly positive for CRF (P < .05). The present findings highlight the relevance of decreasing SB and increasing physical activity practice, particularly at high intensities, to promote a better CRF profile for preschoolers

Do attributes in the physical environment influence children's physical activity? A review of the literature

BACKGROUND: Many youth today are physically inactive. Recent attention linking the physical or built environment to physical activity in adults suggests an investigation into the relationship between the built environment and physical activity in children could guide appropriate intervention strategies. METHOD: Thirty three quantitative studies that assessed associations between the physical environment (perceived or objectively measured) and physical activity among children (ages 3 to 18-years) and fulfilled selection criteria were reviewed. Findings were categorized and discussed according to three dimensions of the physical environment including recreational infrastructure, transport infrastructure, and local conditions. RESULTS: Results across the various studies showed that children's participation in physical activity is positively associated with publicly provided recreational infrastructure (access to recreational facilities and schools) and transport infrastructure (presence of sidewalks and controlled intersections, access to destinations and public transportation). At the same time, transport infrastructure (number of roads to cross and traffic density/speed) and local conditions (crime, area deprivation) are negatively associated with children's participation in physical activity. CONCLUSION: Results highlight links between the physical environment and children's physical activity. Additional research using a transdisciplinary approach and assessing moderating and mediating variables is necessary to appropriately inform policy efforts

Understanding the Relationship between Activity and Neighbourhoods (URBAN) Study: research design and methodology

<p>Abstract</p> <p>Background</p> <p>Built environment attributes are recognized as being important contributors to physical activity (PA) engagement and body size in adults and children. However, much of the existing research in this emergent public health field is hindered by methodological limitations, including: population and site homogeneity, reliance on self-report measures, aggregated measures of PA, and inadequate statistical modeling. As an integral component of multi-country collaborative research, the Understanding the Relationship between Activity and Neighbourhoods (URBAN) Study seeks to overcome these limitations by determining the strengths of association between detailed measures of the neighborhood built environment with PA levels across multiple domains and body size measures in adults and children. This article outlines the research protocol developed for the URBAN Study.</p> <p>Methods and design</p> <p>The URBAN Study is a multi-centered, stratified, cross-sectional research design, collecting data across four New Zealand cities. Within each city, 12 neighborhoods were identified and selected for investigation based on higher or lower walkability and Māori demographic attributes. Neighborhoods were selected to ensure equal representation of these characteristics. Within each selected neighborhood, 42 households are being randomly selected and an adult and child (where possible) recruited into the study. Data collection includes: objective and self-reported PA engagement, neighborhood perceptions, demographics, and body size measures. The study was designed to recruit approximately 2,000 adults and 250 children into the project. Other aspects of the study include photovoice, which is a qualitative assessment of built environment features associated with PA engagement, an audit of the neighborhood streetscape environment, and an individualized neighborhood walkability profile centered on each participant's residential address. Multilevel modeling will be used to examine the individual-level and neighborhood-level relationships with PA engagement and body size.</p> <p>Discussion</p> <p>The URBAN Study is applying a novel scientifically robust research design to provide urgently needed epidemiological information regarding the associations between the built environment and health outcomes. The findings will contribute to a larger, international initiative in which similar neighborhood selection and PA measurement procedures are utilized across eight countries. Accordingly, this study directly addresses the international priority issues of increasing PA engagement and decreasing obesity levels.</p

Associations among physical activity, ADHD symptoms, and executive function in children with ADHD

Attention Deficit Hyperactivity Disorder (ADHD) is one of the leading childhood psychiatric disorders and is a costly public health problem. ADHD causes multiple impairments and while stimulant medications are effective in treating core symptoms of ADHD, some children are not responsive to medications, there is little known about their long-term effects, and they can cause numerous deleterious side effects. Research suggests that physical activity positively impacts some of the same neurobiological mechanisms that have been implicated in ADHD and may have a particularly beneficial effect for children with ADHD by moderating fundamental cognitive deficiencies and behavioral symptoms that characterize this disorder. One of the primary cognitive impairments in ADHD children is executive function (EF). Children with ADHD consistently perform worse on a range of EF tasks relative to those without ADHD (Wilcutt et al., 2005). There is extensive research to support that physical activity selectively improves EF performance in older adults (Colcombe &amp; Kramer, 2003) and some evidence that it has a small effect on cognition in children (Sibley &amp; Etnier, 2003; Tomporowski et al., 2008). Despite evidence and rationale supporting the potential for physical activity to benefit children with ADHD, there is very little research in this area. Therefore, the purpose of this study was to investigate the extent to which physical activity is associated with ADHD symptoms and EF task performance in children with ADHD. Eighteen boys (M age = 10.61, SD = 1.50), who had been diagnosed by a medical professional and were currently taking stimulant medication, were recruited from the community for participation in the study. Children came to the testing site to complete four measures of EF: planning (Tower of London); working memory (Digit Span); processing speed (Children's Colors Trails Test 1 and 2); and inhibition (Conner's Continuous Performance Test, CPT II). Parents completed rating scales (ADHD Rating Scale IV; Behavior Assessment System for Children, 2nd Edition) to assess their child's ADHD symptoms. The most relevant outcome variables from each task and the rating scales were chosen for analysis. Physical activity was measured with an accelerometer (Yamax NL-1000) that participants wore for seven consecutive days providing daily step counts (steps) and minutes per day spent in moderate-to-vigorous intensity physical activity (MVPA). Regression analyses were used with physical activity as a predictor of EF performance and ADHD symptoms. Results revealed that MVPA was a significant predictor of performance on the Tower of London, adjusted R2 = .28, F (1, 16) = 7.61, p &lt; .05. Additionally, although non-significant, correlations for 5 of the other 6 EF outcome measures with both measures of physical activity (steps and MVPA) were in the hypothesized direction, with higher physical activity predictive of better EF performance. There were no significant results for ADHD symptoms. This study provides promising results that physical activity is associated with EF, specifically planning abilities, in children with ADHD. These findings are especially encouraging given that the participants were all receiving medication treatment for ADHD. Given that EF deficits in ADHD children negatively affect their school experience and performance, further research is warranted to examine the impact of physical activity on EF in ADHD children

Accelerometer-measured physical activity in Norwegian adolescents. Results from The Fit Futures Study

This thesis examined the prevalence and patterns of accelerometer-measured physical activity in a cohort of urban-rural older adolescents in Northern Norway, participating in the Fit Futures Study. The thesis also assessed the validity of self-reported physical activity against accelerometer measurements, and explored the association between accelerometer-measured physical activity and subsequent change in five different measures of body composition over 2 years of follow-up. We found that less than 25 % of older adolescent boys and girls fulfilled the global physical activity recommendations. The self-reported physical activity questionnaire seems to be able to rank physical activity levels, and the validity is fairly stable across strata of sex, BMI, and education. However, the validity in providing information on absolute physical activity levels is limited. Minutes spent in baseline moderate-to-vigorous physical activity were not associated with subsequent changes in measures of body composition in neither sex. Sedentary time and light physical activity were associated with changes in lean body mass in girls, but not boys. The findings are interpreted in light of the substantial changes in habits and body composition that occur during adolescence. As few adolescents seem to adhere to the PA guidelines, there is a need for more research on how to promote and implement physical activity in a way that is tailored to adolescents