Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review.

BACKGROUND: Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue. OBJECTIVE: This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design. METHODS: Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources. RESULTS: A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets. CONCLUSIONS: This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity.

A proof of concept for continuous, non-invasive, free-living vital signs monitoring to predict readmission following an acute exacerbation of COPD: a prospective cohort study.

BACKGROUND: The use of vital signs monitoring in the early recognition of an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) post-hospital discharge is limited. This study investigated whether continuous vital signs monitoring could predict an AECOPD and readmission. METHODS: 35 people were recruited at discharge following hospitalisation for an AECOPD. Participants were asked to wear an Equivital LifeMonitor during waking hours for 6 weeks and to complete the Exacerbations of Chronic Pulmonary Disease Tool (EXACT), a 14-item symptom diary, daily. The Equivital LifeMonitor recorded respiratory rate (RR), heart rate (HR), skin temperature (ST) and physical activity (PA) every 15-s. An AECOPD was classified as mild (by EXACT score), moderate (prescribed oral steroids/antibiotics) or severe (hospitalisation). RESULTS: Over the 6-week period, 31 participants provided vital signs and symptom data and 14 participants experienced an exacerbation, of which, 11 had sufficient data to predict an AECOPD. HR and PA were associated with EXACT score (p < 0.001). Three days prior to an exacerbation, RR increased by mean ± SD 2.0 ± 0.2 breaths/min for seven out of 11 exacerbations and HR increased by 8.1 ± 0.7 bpm for nine of these 11 exacerbations. CONCLUSIONS: Increased heart rate and reduced physical activity were associated with worsening symptoms. Even with high-resolution data, the variation in vital signs data remains a challenge for predicting AECOPDs. Respiratory rate and heart rate should be further explored as potential predictors of an impending AECOPD. TRIAL REGISTRATION: ISRCTN registry; ISRCTN12855961. Registered 07 November 2018-Retrospectively registered, https://www.isrctn.com/ISRCTN12855961.

Body mass index across adulthood and the development of airflow obstruction and emphysema.

BACKGROUND: Low body mass index (BMI) is associated with COPD, but temporal relationships between airflow obstruction (AO) development and emphysematous change are unclear. We investigated longitudinal changes in BMI, AO, and lung density throughout adulthood using data from the Framingham Offspring Cohort (FOC). METHODS: BMI trajectories were modelled throughout adulthood in 4587 FOC participants from Exam 2 (mean age = 44), through Exam 9 (mean age = 71), in AO participants and non-AO participants (AO n = 1036), determined by spirometry, using fractional polynomial growth curves. This process was repeated for low lung density (LLD) and non LLD participants (LLD n = 225) determined by Computed Tomography. Spirometry decline was compared separately between tertiles of BMI in those aged <40 years and associations between fat and lean mass (measured using Dual Energy X-ray Absorptiometry, DEXA) and development of AO and LLD were also assessed. Additional analyses were performed with adjustment for smoking volume. RESULTS: The BMI trajectory from 30 years of age was visually lower in the AO group than both non-AO smokers (non-

A digital lifestyle behaviour change intervention for the prevention of type 2 diabetes: a qualitative study exploring intuitive engagement with real-time glucose and physical activity feedback.

BACKGROUND: Mobile health technologies have advanced to now allow monitoring of the acute physiological responses to lifestyle behaviours. Our aim was to explore how people engaged with real-time feedback on their physical activity and glucose levels over several weeks. METHODS: Semi-structured interviews with 26 participants (61.5% female, 56.6 years) at moderate-to-high risk of developing type 2 diabetes were conducted. Interviews were completed after participants took part in an intervention comprising a flash glucose monitor (Freestyle Libre) and a physical activity monitor (Fitbit Charge 2). Purposive sampling ensured representation of ages, genders and group allocations. RESULTS: Inductive thematic analysis revealed how individuals intuitively used, interpreted and acted on feedback from wearable technologies. Six key themes emerged: triggers of engagement with the technologies, links between behaviour and health, lack of confidence, changes to movement behaviours, changes to diet and barriers to lifestyle behaviour change. CONCLUSIONS: Our findings demonstrate that accessing behavioural and physiological feedback can increase self-awareness of how lifestyle impacts short-term health. Some participants noticed a link between the feedback presented by the two devices and changed their behaviour but many did not. Training and educational support, as well as efforts to optimize how feedback is presented to users, are needed to sustain engagement and behaviour change. Extensions of this work to involve people with diabetes are also warranted to explore whether behavioural and physiological feedback in parallel can encourage better diabetes self-management. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN17545949 , 12/05/2017, prospectively registered.

Influence of muscle mass in the assessment of lower limb strength in COPD: validation of the prediction equation.

Absence of established reference values limits application of quadriceps maximal voluntary contraction (QMVC) measurement. The impact of muscle mass inclusion in predictions is unclear. Prediction equations encompassing gender, age and size with (FFM+) and without (FFM-), derived in healthy adults (n=175), are presented and compared in two COPD cohorts recruited from primary care (COPD-PC, n=112) and a complex care COPD clinic (COPD-CC, n=189). Explained variance was comparable between the prediction models (R2: FFM+: 0.59, FFM-: 0.60) as were per cent predictions in COPD-PC (88.8%, 88.3%). However, fat-free mass inclusion reduced the prevalence of weakness in COPD, particularly in COPD-CC where 11.9% fewer were deemed weak.

The influence of South Asian ethnicity on the incremental shuttle walk test in UK adults.

The objective of this study was to compare incremental shuttle walking test (ISWT) performance between South Asian and Caucasian British adults, identify predictors of ISWT distance and produce ethnicity-specific reference equations. Data from a mixed gender sample aged 40-75 years from Leicestershire, United Kingdom, were selected for analyses. Analysis of covariance determined differences in ISWT performance between South Asian and Caucasian British ethnic groups. Linear regressions identified predictors of ISWT distance, which determined the reference equations. In total, 144 participants took part in the study (79 South Asian (54 ± 8 years, 71% female) and 65 Caucasian British (58 ± 9 years, 74% female)). Distance walked for the ISWT was shorter for South Asian individuals compared with Caucasian British (451 ± 143 vs. 575 ± 180 m, p < 0.001). The ethnicity-specific reference equations for ISWT distance explained 33-50% of the variance (standard error of the estimate (SEE): 107-119 m) for South Asians and explained 14-58% of the variance (SEE: 121-169 m) for Caucasian British. Ethnicity univariately explained 12.9% of the variance in ISWT distance and was significantly associated with ISWT distance after controlling for age, gender, height, weight, dyspnoea and lung function ( B = -70.37; 1 = Caucasian British, 2 = South Asian), uniquely explaining 3.7% of the variance. Predicted values for ISWT performance were lower in South Asian people than in Caucasian British. Ethnicity-specific reference equations should account for this.

Harmonising data on the correlates of physical activity and sedentary behaviour in young people: Methods and lessons learnt from the international Children's Accelerometry database (ICAD).

BACKGROUND: Large, heterogeneous datasets are required to enhance understanding of the multi-level influences on children's physical activity and sedentary behaviour. One route to achieving this is through the pooling and co-analysis of data from multiple studies. Where this approach is used, transparency of the methodology for data collation and harmonisation is essential to enable appropriate analysis and interpretation of the derived data. In this paper, we describe the acquisition, management and harmonisation of non-accelerometer data in a project to expand the International Children's Accelerometry Database (ICAD). METHOD: Following a consultation process, ICAD partners were requested to share accelerometer data and information on selected behavioural, social, environmental and health-related constructs. All data were collated into a single repository for cataloguing and harmonisation. Harmonised variables were derived iteratively, with input from the ICAD investigators and a panel of invited experts. Extensive documentation, describing the source data and harmonisation procedure, was prepared and made available through the ICAD website. RESULTS: Work to expand ICAD has increased the number of studies with longitudinal accelerometer data, and expanded the breadth of behavioural, social and environmental characteristics that can be used as exposure variables. A set of core harmonised variables, including parent education, ethnicity, school travel mode/duration and car ownership, were derived for use by the research community. Guidance documents and facilities to enable the creation of new harmonised variables were also devised and made available to ICAD users. An expanded ICAD database was made available in May 2017. CONCLUSION: The project to expand ICAD further demonstrates the feasibility of pooling data on physical activity, sedentary behaviour and potential determinants from multiple studies. Key to this process is the rigorous conduct and reporting of retrospective data harmonisation, which is essential to the appropriate analysis and interpretation of derived data. These documents, made available through the ICAD website, may also serve as a guide to others undertaking similar projects.

Can functional magnetic resonance imaging studies help with the optimization of health messaging for lifestyle behavior change? A systematic review.

Unhealthy behaviors, including smoking, poor nutrition, excessive alcohol consumption, physical inactivity and sedentary lifestyles, are global risk factors for non-communicable diseases and premature death. Functional magnetic resonance imaging (fMRI) offers a unique approach to optimize health messages by examining how the brain responds to information relating to health. Our aim was to systematically review fMRI studies that have investigated variations in brain activation in response to health messages relating to (i) smoking; (ii) alcohol consumption; (iii) physical activity; (iv) diet; and (v) sedentary behavior. The electronic databases used were Medline/PubMed, Web of Science (Core Collection), PsychINFO, SPORTDiscuss, Cochrane Library and Open Grey. Studies were included if they investigated subjects aged ≥10years and were published before January 2017. Of the 13,836 studies identified in the database search, 18 studies (smoking k=15; diet k=2; physical activity/sedentary behavior k=1) were included in the review. The prefrontal cortex was activated in seven (47%) of the smoking-related studies and the physical activity study. Results suggest that activation of the ventromedial, dorsolateral and medial prefrontal cortex regions were predictive of subsequent behavior change following exposure to aversive anti-smoking stimuli. Studies investigating the neurological responses to anti-smoking material were most abundant. Of note, the prefrontal cortex and amygdala were most commonly activated in response to health messages across lifestyle behaviors. The review highlights an important disparity between research focusing on different lifestyle behaviors. Insights from smoking literature suggest fMRI may help to optimize health messaging in relation to other lifestyle behaviors.

Evaluation of the implementation of a whole-workplace walking programme using the RE-AIM framework.

BACKGROUND: Promoting walking for the journey to/from work and during the working day is one potential approach to increase physical activity in adults. Walking Works was a practice-led, whole-workplace walking programme delivered by employees (walking champions). This study aimed to evaluate the implementation of Walking Works using the RE-AIM framework and provide recommendations for future delivery of whole-workplace walking programmes. METHODS: Two cross sectional surveys were conducted; 1544 (28%) employees completed the baseline survey and 918 employees (21%) completed the follow-up survey. Effectiveness was assessed using baseline and follow-up data; reach, implementation and maintenance were assessed using follow-up data only. For categorical data, Chi square tests were conducted to assess differences between surveys or groups. Continuous data were analysed to test for significant differences using a Mann-Whitney U test. Telephone interviews were conducted with the lead organisation co-ordinator, eight walking champions and three business representatives at follow-up. Interviews were transcribed verbatim and analysed to identify key themes related to adoption, implementation and maintenance. RESULTS: Adoption: Five workplaces participated in Walking Works. Reach: 480 (52.3%) employees were aware of activities and 221 (24.1%) participated. IMPLEMENTATION: A variety of walking activities were delivered. Some programme components were not delivered as planned which was partly due to barriers in using walking champions to deliver activities. These included the walking champions' capacity, skills, support needs, ability to engage senior management, and the number and type of activities they could deliver. Other barriers included lack of management support, difficulties communicating information about activities and challenges embedding the programme into normal business activities. Effectiveness: No significant changes in walking to/from work or walking during the working day were observed. Maintenance: Plans to continue activities were mainly dependent on identifying continued funding. CONCLUSIONS: RE-AIM provided a useful framework for evaluating Walking Works. No changes in walking behaviour were observed. This may have been due to barriers in using walking champions to deliver activities, programme components not being delivered as intended, the types of activities delivered, or lack of awareness and participation by employees. Recommendations are provided for researchers and practitioners implementing future whole-workplace walking programmes.

Brain Activation in Response to Personalized Behavioral and Physiological Feedback From Self-Monitoring Technology: Pilot Study.

BACKGROUND: The recent surge in commercially available wearable technology has allowed real-time self-monitoring of behavior (eg, physical activity) and physiology (eg, glucose levels). However, there is limited neuroimaging work (ie, functional magnetic resonance imaging [fMRI]) to identify how people's brains respond to receiving this personalized health feedback and how this impacts subsequent behavior. OBJECTIVE: Identify regions of the brain activated and examine associations between activation and behavior. METHODS: This was a pilot study to assess physical activity, sedentary time, and glucose levels over 14 days in 33 adults (aged 30 to 60 years). Extracted accelerometry, inclinometry, and interstitial glucose data informed the construction of personalized feedback messages (eg, average number of steps per day). These messages were subsequently presented visually to participants during fMRI. Participant physical activity levels and sedentary time were assessed again for 8 days following exposure to this personalized feedback. RESULTS: Independent tests identified significant activations within the prefrontal cortex in response to glucose feedback compared with behavioral feedback (P<.001). Reductions in mean sedentary time (589.0 vs 560.0 minutes per day, P=.014) were observed. Activation in the subgyral area had a moderate correlation with minutes of moderate-to-vigorous physical activity (r=0.392, P=.043). CONCLUSION: Presenting personalized glucose feedback resulted in significantly more brain activation when compared with behavior. Participants reduced time spent sedentary at follow-up. Research on deploying behavioral and physiological feedback warrants further investigation.

Metadata Correction: Brain Activation in Response to Personalized Behavioral and Physiological Feedback From Self-Monitoring Technology: Pilot Study.

[This corrects the article DOI: 10.2196/jmir.8890.].

Moderate-to-Vigorous Physical Activity, Indices of Cognitive Control, and Academic Achievement in Preadolescents.

OBJECTIVE: To assess whether preadolescents' objectively measured moderate-to-vigorous physical activity (MVPA) is associated with cognitive control and academic achievement, independent of aerobic fitness. STUDY DESIGN: A sample of 74 children (Meanage = 8.64 years, SD = .58, 46% girls) were included in the analyses. Daily MVPA (min/d) was measured over 7 days using ActiGraph wGT3X+ accelerometer. Aerobic fitness was measured using a maximal graded exercise test and expressed as maximal oxygen uptake (mL*kg(-1)*min(-1)). Inhibitory control was measured with a modified Eriksen flanker task (reaction time and accuracy), and working memory with an Operation Span Task (accuracy scores). Academic achievement (in reading, mathematics, and spelling) was expressed as standardized scores on the Kaufman Test of Educational Achievement. The relationships were assessed using hierarchical regression models adjusting for aerobic fitness and other covariates. RESULTS: No significant associations were found between MVPA and inhibition, working memory, or academic achievement. Aerobic fitness was positively associated with inhibitory control (P = .02) and spelling (P = .04) but not with other cognitive or academic variables (all P > .05). CONCLUSIONS: Aerobic fitness, rather than daily MVPA, is positively associated with childhood ability to manage perceptual interference and spelling. Further research into the associations between objectively measured MVPA and cognitive and academic outcomes in children while controlling for important covariates is needed.

Associations of mutually exclusive categories of physical activity and sedentary time with markers of cardiometabolic health in English adults: a cross-sectional analysis of the Health Survey for England.

BACKGROUND: Both physical activity and sedentary behaviour have been individually associated with health, however, the extent to which the combination of these behaviours influence health is less well-known. The aim of this study was to examine the associations of four mutually exclusive categories of objectively measured physical activity and sedentary time on markers of cardiometabolic health in a nationally representative sample of English adults. METHODS: Using the 2008 Health Survey for England dataset, 2131 participants aged ≥ 18 years, who provided valid accelerometry data, were included for analysis and grouped into one of four behavioural categories: (1) 'Busy Bees': physically active & low sedentary, (2) 'Sedentary Exercisers': physically active & high sedentary, (3) 'Light Movers': physically inactive & low sedentary, and (4) 'Couch Potatoes': physically inactive & high sedentary. 'Physically active' was defined as accumulating at least 150 min of moderate-to-vigorous physical activity (MVPA) per week. 'Low sedentary' was defined as residing in the lowest quartile of the ratio between the average sedentary time and the average light-intensity physical activity time. Weighted multiple linear regression models, adjusting for measured confounders, investigated the differences in markers of health across the derived behavioural categories. The associations between continuous measures of physical activity and sedentary levels with markers of health were also explored, as well as a number of sensitivity analyses. RESULTS: In comparison to 'Couch Potatoes', 'Busy Bees' [body mass index: -1.67 kg/m(2) (p < 0.001); waist circumference: -1.17 cm (p = 0.007); glycated haemoglobin: -0.12% (p = 0.003); HDL-cholesterol: 0.09 mmol/L (p = 0.001)], 'Sedentary Exercisers' [body mass index: -1.64 kg/m(2) (p < 0.001); glycated haemoglobin: -0.11 % (p = 0.009); HDL-cholesterol: 0.07 mmol/L (p < 0.001)] and 'Light Movers' [HDL-cholesterol: 0.11 mmol/L (p = 0.004)] had more favourable health markers. The continuous analyses showed consistency with the categorical analyses and the sensitivity analyses indicated robustness and stability. CONCLUSIONS: In this national sample of English adults, being physically active was associated with a better health profile, even in those with concomitant high sedentary time. Low sedentary time independent of physical activity had a positive association with HDL-cholesterol.

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 Accelerometer Prediction Equations in Children with Chronic Disease.

The purpose of this study was to assess the criterion validity of existing accelerometer-based energy expenditure (EE) prediction equations among children with chronic conditions, and to develop new prediction equations. Children with congenital heart disease (CHD), cystic fibrosis (CF), dermatomyositis (JDM), juvenile arthritis (JA), inherited muscle disease (IMD), and hemophilia (HE) completed 7 tasks while EE was measured using indirect calorimetry with counts determined by accelerometer. Agreement between predicted EE and measured EE was assessed. Disease-specific equations and cut points were developed and cross-validated. In total, 196 subjects participated. One participant dropped out before testing due to time constraints, while 15 CHD, 32 CF, 31 JDM, 31 JA, 30 IMD, 28 HE, and 29 healthy controls completed the study. Agreement between predicted and measured EE varied across disease group and ranged from (ICC) .13-.46. Disease-specific prediction equations exhibited a range of results (ICC .62-.88) (SE 0.45-0.78). In conclusion, poor agreement was demonstrated using current prediction equations in children with chronic conditions. Disease-specific equations and cut points were developed.

Objectively measured physical activity and sedentary time in youth: the International children's accelerometry database (ICAD).

BACKGROUND: Physical activity and sedentary behaviour in youth have been reported to vary by sex, age, weight status and country. However, supporting data are often self-reported and/or do not encompass a wide range of ages or geographical locations. This study aimed to describe objectively-measured physical activity and sedentary time patterns in youth. METHODS: The International Children's Accelerometry Database (ICAD) consists of ActiGraph accelerometer data from 20 studies in ten countries, processed using common data reduction procedures. Analyses were conducted on 27,637 participants (2.8-18.4 years) who provided at least three days of valid accelerometer data. Linear regression was used to examine associations between age, sex, weight status, country and physical activity outcomes. RESULTS: Boys were less sedentary and more active than girls at all ages. After 5 years of age there was an average cross-sectional decrease of 4.2% in total physical activity with each additional year of age, due mainly to lower levels of light-intensity physical activity and greater time spent sedentary. Physical activity did not differ by weight status in the youngest children, but from age seven onwards, overweight/obese participants were less active than their normal weight counterparts. Physical activity varied between samples from different countries, with a 15-20% difference between the highest and lowest countries at age 9-10 and a 26-28% difference at age 12-13. CONCLUSIONS: Physical activity differed between samples from different countries, but the associations between demographic characteristics and physical activity were consistently observed. Further research is needed to explore environmental and sociocultural explanations for these differences.

The effects of sports participation on the development of left ventricular mass in adolescent boys.

OBJECTIVES: To examine the contribution of body size, biological maturation, and nonelite sports participation to longitudinal changes of left ventricular mass (LVM) in healthy boys. METHODS: One hundred and ten boys (11.0-14.5 years at baseline) were assessed biannually for 2 years. Stature, body mass, and four skinfolds were measured. Lean body mass (LBM) was estimated. Biological maturation was assessed as years from age at peak height velocity (APHV). Sports participation was assessed by questionnaire. LVM was obtained from M-mode echocardiograms using two-dimensional images. To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used in the analysis. RESULTS: LVM increased on average 42 ± 18 g from 11 to 15 years (P < 0.05) and 76 ± 14 g from 3.5 years pre-APHV to 1.5 years post-APHV (P < 0.05). The multilevel model with the best statistical fit (Model B) showed that changes of 1 cm in stature, 1 year post-APHV, and 1 kg of LBM predicts 4.7, 0.5, and 1 g of LVM (P < 0.05), respectively. CONCLUSIONS: Among healthy, male adolescents aged 11-15 years individual differences in growth and biological maturation influence growth of LVM. Subcutaneous adiposity and sports participation were not associated with greater LVM.

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.

A multi-channel opto-electronic sensor to accurately monitor heart rate against motion artefact during exercise.

This study presents the use of a multi-channel opto-electronic sensor (OEPS) to effectively monitor critical physiological parameters whilst preventing motion artefact as increasingly demanded by personal healthcare. The aim of this work was to study how to capture the heart rate (HR) efficiently through a well-constructed OEPS and a 3-axis accelerometer with wireless communication. A protocol was designed to incorporate sitting, standing, walking, running and cycling. The datasets collected from these activities were processed to elaborate sport physiological effects. t-test, Bland-Altman Agreement (BAA), and correlation to evaluate the performance of the OEPS were used against Polar and Mio-Alpha HR monitors. No differences in the HR were found between OEPS, and either Polar or Mio-Alpha (both p > 0.05); a strong correlation was found between Polar and OEPS (r: 0.96, p < 0.001); the bias of BAA 0.85 bpm, the standard deviation (SD) 9.20 bpm, and the limits of agreement (LOA) from -17.18 bpm to +18.88 bpm. For the Mio-Alpha and OEPS, a strong correlation was found (r: 0.96, p < 0.001); the bias of BAA 1.63 bpm, SD 8.62 bpm, LOA from -15.27 bpm to +18.58 bpm. These results demonstrate the OEPS to be capable of carrying out real time and remote monitoring of heart rate.

Effects of intradialytic cycling compared with pedometry on physical function in chronic outpatient hemodialysis: a prospective randomized trial.

BACKGROUND: Individuals on hemodialysis have low physical function and activity levels. Clinical trials have shown improvements in these parameters with exercise programming. Pedometers have not been extensively evaluated in individuals on hemodialysis. This randomized clinical trial compared the effects of intradialytic cycling versus a pedometer program on physical function, physical activity and quality of life. METHODS: Sixty patients were randomly assigned to two study groups. The ergometer group cycled during each hemodialysis session for 24 weeks. Pedometer participants followed a home-based walking program for 24 weeks. The primary outcome was aerobic capacity [VO2peak and 6-minute walk (6MW) test]. Secondary outcomes included lower extremity strength [sit-to-stand (SS) test], flexibility [sit-and-reach (SR) test], physical activity (accelerometer) and health-related quality of life. Measurements were collected at baseline and at 12 and 24 weeks. RESULTS: At 12 and 24 weeks, there was no significant change in the VO2peak or 6MW test between or within study groups. SS testing in the ergometer group improved from 10.2 (SD 3.4) to 11.4 (SD 2.5) cycles from baseline to 24 weeks (P < 0.005). Similarly, in the pedometer group, SS cycles improved from 10.1 (SD 3.3) to 12.2 (SD 3.5) (P < 0.005). The SR test also significantly improved over time in both the study groups. No significant changes were noted for other secondary outcomes. CONCLUSIONS: Both intradialytic cycling and pedometer programming improved aspects of physical function. Neither intervention had a significant effect on aerobic capacity. No significant differences in any outcomes were identified between interventions groups.