Daily physical activity assessment with accelerometers: new insights and validation studies

A Lean and Performant Hierarchical Model for Human Activity Recognition Using Body-Mounted Sensors

Here we propose a new machine learning algorithm for classification of human activities by means of accelerometer and gyroscope signals. Based on a novel hierarchical system of logistic regression classifiers and a relatively small set of features extracted from the filtered signals, the proposed algorithm outperformed previous work on the DaLiAc (Daily Life Activity) and mHealth datasets. The algorithm also represents a significant improvement in terms of computational costs and requires no feature selection and hyper-parameter tuning. The algorithm still showed a robust performance with only two (ankle and wrist) out of the four devices (chest, wrist, hip and ankle) placed on the body (96.8% vs. 97.3% mean accuracy for the DaLiAc dataset). The present work shows that low-complexity models can compete with heavy, inefficient models in classification of advanced activities when designed with a careful upstream inspection of the data.

Movement Analysis with Inertial Measurement Unit Sensor After Surgical Treatment for Distal Radius Fractures

Inertial measurement unit (IMU) has recently been used to evaluate a movement of a body segment to provide accurate information of movement's characteristics. IMU systems have been validated to successfully measure joint angle during upper limb range of motion (ROM). The study aimed to retrospectively evaluate, using an IMU, the ROM recovery of the wrist after surgical treatment for distal-radius fractures with Kirschner wire fixation (KWF) or with volar plate fixation (VPF) and screws. To assess pain in the wrist joint, muscle-fatigue (MF), and functional difficulties in activities of daily living, we evaluated the patients through patient-related wrist evaluation questionnaire (PRWE) scale, disability of the arm, shoulder and hand (DASH) scale, Hand Grip Strength (HGS), and surface electromyography (EMG). We used a single IMU composed of three-axis gyroscope, a three-axis accelerometer, and a magnetometer. We calculated the value of ROM as a percentage with respect to the unaffected wrist. We also recorded surface-EMG signals over biceps brachialis, flexor carpi radialis (FCR), extensor carpi radialis (ECR), and pronator teres muscles. Forty patients were recruited for our study. Ulnar deviation (UD) was significantly higher for VPF than for KWF (p = 0.017); supination was significantly higher for VPF than for KWF (p = 0.031). The percentage of decay of the median frequency of FCR of volar plate was significantly higher than KWF. The HGS of KWF was significantly higher than VPF. In literature, there were no significant differences between the two types of treatment at long-term follow-up. Our results demonstrate a superior efficacy of VPF in terms of ROM improvement in UD and supination, but for these patients, muscle fatigue is greater than the KWF group. Based on the data available, VPF is similar to KWF for the treatment of distal radius fractures. The IMU sensor could be used in the future to evaluate ROM after surgery during patient's rehabilitation and to compare the effects with stratified analysis regarding age and fracture type, paralleled with cost-effectiveness analysis.

Total and activity-induced energy expenditure measured during a year in children with inflammatory bowel disease in clinical remission remain lower than in healthy controls

BACKGROUND

Pediatric inflammatory bowel disease (IBD) is often associated with growth retardation due to malnutrition. However, knowledge on total energy expenditure (TEE), active-induced energy expenditure (AEE) and physical activity remains limited in children with IBD.

OBJECTIVE

Assessment of TEE using the doubly labelled water (DLW) method, resting energy expenditure (REE) using indirect calorimetry, and physical activity level using the actigraph GT3X+ in children with IBD (in remission) and healthy controls.

METHODS

TEE, REE, AEE and physical activity were measured in 21 children with IBD and 24 healthy controls at baseline. IBD children parameters were monitored further after 6 and 12 months. Predicted REE and TEE values (using Schoefield and the actigraph GT3X+, for REE and TEE respectively) were compared to measured values.

RESULTS

Mean ages at baseline were 14.8 ± 1.5 and 13.2 ± 2 years in children with IBD and in healthy control children, respectively. Measured TEE_DLW was significantly lower (P < 0.001) in children with IBD compared to the healthy control group. REE corrected by FFM^0.5, REE and AEE were also significantly lower in children with IBD. Children with IBD had AEE of 17.5% of TEE and had a significantly higher sedentary behaviour as compared to healthy children.

CONCLUSIONS

This study suggests that TEE and AEE are reduced in children with IBD in clinical remission which may result in a reduced moderate and vigorous physical activity level. Our result also highlights that the actigraph GT3X + might give good prediction of TEE in children with IBD at group level but it remains highly variable at individual level.

Embedded Motivational Interviewing combined with a smartphone app to increase physical activity in people with sub-acute low back pain: Study protocol of a cluster randomised control trial

BACKGROUND

Motivational Interviewing is an evidence-based, client-centred counselling technique that has been used effectively to increase physical activity, including for people with low back pain. One barrier to implementing Motivational Interviewing in health care settings more broadly is the extra treatment time with therapists. The aim of this paper is to describe the design of a cluster randomised controlled trial evaluating the effect of an intervention that pairs Motivational Interviewing embedded into usual physiotherapy care with a specifically designed app to increase physical activity in people with sub-acute low back pain.

METHODS

The study is a cluster randomised controlled in which patients aged over 18 years who have sub-acute low back pain (3-12 weeks duration) are recruited from four public hospital outpatient clinics. Based on the recruitment site, participants either receive usual physiotherapy care or the Motivational Interviewing intervention over 6 consecutive weekly outpatient sessions with a specifically designed app designed to facilitate participant-led physical activity behaviour change in between sessions. Outcome measures assessed at baseline and 7 weeks are: physical activity as measured by accelerometer (primary outcome), and pain-related activity restriction and pain self-efficacy (secondary outcomes). Postintervention interviews with physiotherapists and participants will be conducted as part of a process evaluation.

DISCUSSION

This intervention, which comprises trained physiotherapists conducting conversations about increasing physical activity with their patients in a manner consistent with Motivational Interviewing as part of usual care combined with a specifically designed app, has potential to facilitate behaviour change with minimal extra therapist time.

A Social Networking and Gamified App to Increase Physical Activity: Cluster RCT

INTRODUCTION

Appealing approaches to increasing physical activity levels are needed. This study evaluated whether a social and gamified smartphone app (Active Team) could be one such approach.

STUDY DESIGN

A 3-group cluster RCT compared the efficacy of Active Team with a basic self-monitoring app and waitlist control group.

SETTING/PARTICIPANTS

Australian adults (N=444, mean age of 41 years, 74% female) were recruited in teams (n=121) and randomly assigned (1:1:1) to the Active Team (n=141, 39 teams), self-monitoring app (n=160, 42 teams), or waitlist group (n=143, 40 teams). Data were collected in 2016-2017, and analysis was conducted in 2018-2019.

INTERVENTION

Active Team is a 100-day app-based, gamified, online social networking physical activity intervention.

MAIN OUTCOME MEASURES

The primary outcome was change in objective physical activity from baseline to 3-month follow-up. Secondary outcomes included objective physical activity at 9 months and self-reported physical activity, quality of life, depression, anxiety and stress, well-being, and engagement.

RESULTS

Mixed models indicated no significant differences in objective physical activity between groups at 3 (F=0.17, p=0.84; Cohen's d=0.03, 95% CI= -0.21, 0.26) or 9 months (F=0.23, p=0.92; d=0.06, 95% CI= -0.17, 0.29) and no significant differences for secondary outcomes of quality of life, depression, anxiety and stress, or well-being. Self-reported moderate-to-vigorous physical activity was significantly higher in the Active Team group at the 9-month follow-up (F=3.05, p=0.02; d=0.50, 95% CI=0.26, 0.73). Engagement was high; the Active Team group logged steps on an average of 72 (SD=35) days and used the social and gamified features an average of 89 (SD=118) times.

CONCLUSIONS

A gamified, online social networking physical activity intervention did not change objective moderate-to-vigorous physical activity, though it did increase self-reported moderate-to-vigorous physical activity and achieve high levels of engagement. Future work is needed to understand if gamification, online social networks, and app-based approaches can be leveraged to achieve positive behavior change.

TRIAL REGISTRATION

This study is registered at Australian and New Zealand Clinical Trial Registry (protocol: ANZCTR12617000113358).

The Association Between Time-Use Behaviors and Physical and Mental Well-Being in Adults: A Compositional Isotemporal Substitution Analysis

BACKGROUND

Substantial evidence links activity domains with health and well-being; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This study used compositional data analysis to estimate the difference in physical and mental well-being associated with reallocating time between behaviors.

METHODS

Participants (n = 430; 74% female; 41 [12] y) wore an accelerometer for 7 days and reported their body mass index; health-related quality of life (QoL); and symptoms of depression, anxiety, and stress. Regression models determined whether time-use composition, comprising sleep, sedentary behavior, light physical activity (LPA), and moderate to vigorous physical activity (MVPA), was associated with well-being. Compositional isotemporal substitution models estimated the difference in well-being associated with reallocating time between behaviors.

RESULTS

Time-use composition was associated with body mass index and physical health-related QoL. Reallocating time to MVPA from sleep, sedentary behavior, and LPA showed favorable associations with body mass index and physical health-related QoL, whereas reallocations from MVPA to other behaviors showed unfavorable associations. Reallocations from LPA to sedentary behavior were associated with better physical health-related QoL and vice versa.

CONCLUSION

Results reinforce the importance of MVPA for physical health but do not suggest that replacing sedentary behavior with LPA is beneficial for health and well-being.

Characterizing Behavioral Activity Rhythms in Older Adults Using Actigraphy

Wrist actigraphy has been used to assess sleep in older adult populations for nearly half a century. Over the years, the continuous raw activity data derived from actigraphy has been used for the characterization of factors beyond sleep/wake such as physical activity patterns and circadian rhythms. Behavioral activity rhythms (BAR) are useful to describe individual daily behavioral patterns beyond sleep and wake, which represent important and meaningful clinical outcomes. This paper reviews common rhythmometric approaches and summarizes the available data from the use of these different approaches in older adult populations. We further consider a new approach developed in our laboratory designed to provide graphical characterization of BAR for the observed behavioral phenomenon of activity patterns across time. We illustrate the application of this new approach using actigraphy data collected from a well-characterized sample of older adults (age 60+) with osteoarthritis (OA) pain and insomnia. Generalized additive models (GAM) were implemented to fit smoothed nonlinear curves to log-transformed aggregated actigraphy-derived activity measurements. This approach demonstrated an overall strong model fit (R2 = 0.82, SD = 0.09) and was able to provide meaningful outcome measures allowing for graphical and parameterized characterization of the observed activity patterns within this sample.

Validity and bias on the online active Australia survey: activity level and participant factors associated with self-report bias

Background

This study examined the criterion validity of the online Active Australia Survey, using accelerometry as the criterion, and whether self-report bias was related to level of activity, age, sex, education, body mass index and health-related quality of life.

Methods

The online Active Australia Survey was validated against the GENEActiv accelerometer as a direct measure of activity. Participants (n = 344) wore an accelerometer for 7 days, completed the Active Australia Survey, and reported their health and demographic characteristics. A Spearman’s rank coefficient examined the association between minutes of moderate-to-vigorous physical activity recorded on the Active Australia Survey and GENEActiv accelerometer. A Bland-Altman plot illustrated self-report bias (the difference between methods). Linear mixed effects modelling was used to examine whether participant factors predicted self-report bias.

Results

The association between moderate-to-vigorous physical activity reported on the online Active Australia Survey and accelerometer was significant (r_s = .27, p < .001). Participants reported 4 fewer minutes per day on the Active Australia Survey than was recorded by accelerometry (95% limits of agreement −104 – 96 min) but the difference was not significant (t(343) = −1.40, p = .16). Self-report bias was negatively associated with minutes of accelerometer-recorded moderate-to-vigorous physical activity and positively associated with mental health-related quality of life.

Conclusions

The online Active Australia Survey showed limited criterion validity against accelerometry. Self-report bias was related to activity level and mental health-related quality of life. Caution is recommended when interpreting studies using the online Active Australia Survey.

Association between Hydration Status and Body Composition in Healthy Adolescents from Spain

At present, obesity and overweight are major public health concerns. Their classical determinants do not sufficiently explain the current situation and it is urgent to investigate other possible causes. In recent years, it has been suggested that water intake could have important implications for weight management. Thus, the aim of this study was to examine the effect of hydration status on body weight and composition in healthy adolescents from Spain. The study involved 372 subjects, aged 12-18 years. Water intake was assessed through the validated "hydration status questionnaire adolescent young". Anthropometric measurements were performed according to the recommendations of the International Standards for Anthropometric Assessment (ISAK) and body composition was estimated by bioelectrical impedance analysis. Water intake normalized by body weight was positively correlated with body water content (boys (B): r = 0.316, p = 0.000; girls (G): r = 0.245, p = 0.000) and inversely with body mass index (BMI) (B: r = -0.515, p = 0.000; G: r = -0.385, p =0.000) and fat body mass (B: r = -0.306, p = 0.000; G: r = -0.250, p = 0.001). Moreover, according to BMI, overweight/obese individuals consumed less water than normal weight ones. In conclusion, higher water balance and intake seems to be related with a healthier body composition. In conclusion, higher water balance and intake is associated with a healthier body composition.

Estimating energy expenditure from wrist and thigh accelerometry in free-living adults: a doubly labelled water study

BACKGROUND

Many large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion.

METHODS

Measurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg m-2) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation.

RESULTS

Mean TEE and AEE derived from DLW were 11.6 (2.3) MJ day-1 and 49.8 (16.3) kJ day-1 kg-1. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day-1 kg-1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day-1 kg-1, r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day-1, r ~ 0.90).

CONCLUSIONS

In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.

Moving beyond self-report data collection in the natural environment: A review of the past and future directions for ambulatory assessment in eating disorders

OBJECTIVE

In recent years, ecological momentary assessment (EMA) has been used to repeatedly assess eating disorder (ED) symptoms in naturalistic settings, which has allowed for increased understanding of temporal processes that potentiate ED behaviors. However, there remain notable limitations of self-report EMA, and with the rapid proliferation of technology there are ever-increasing possibilities to improve ambulatory assessment methods to further the understanding and treatment of EDs. Therefore, the purpose of this review was to (a) systematically review the studies in EDs that have utilized ambulatory assessment methods other than self-report, and (b) provide directions for future research and clinical applications.

METHOD

A systematic literature search of electronic databases was conducted, and data regarding study characteristics and methodological quality were extracted.

RESULTS

The search identified 17 studies that used ambulatory assessment methods to gather objective data, and focused primarily on autonomic functioning, physical activity, and cognitive processes in ED and control groups.

DISCUSSION

Together the literature demonstrates the promise of using a range of ecologically valid ambulatory assessment approaches in EDs, though there remains limited research that has utilized methods other than self-report (e.g., wearable sensors), particularly in recent years. Going forward, there are several technology-enhanced momentary assessment methods that have potential to improve the understanding and treatment of EDs.

Wearable oxygen uptake and energy expenditure monitors

Obesity is a major health issue in both developed and developing countries. The balance between energy intake and exercise is important, and measurements of both energy intake and energy expenditure are required. Many studies have attempted to monitor energy intake via wearable technology, but no standard methods have yet been developed for this purpose. This is in marked contrast to the long history of measurement and estimation of energy expenditure. Indirect calorimetry is commonly used in the laboratory. Energy expenditure associated with daily activity is the most important measure, although a number of alternative measures have also been proposed. This mini-review discusses the current status of energy expenditure measurement.

Training-induced changes in daily energy expenditure: Methodological evaluation using wrist-worn accelerometer, heart rate monitor, and doubly labeled water technique

INTRODUCTION

Wrist-mounted motion sensors can quantify the volume and intensity of physical activities, but little is known about their long-term validity. Our aim was to validate a wrist motion sensor in estimating daily energy expenditure, including any change induced by long-term participation in endurance and strength training. Supplemental heart rate monitoring during weekly exercise was also investigated.

METHODS

A 13-day doubly labeled water (DLW) measurement of total energy expenditure (TEE) was performed twice in healthy male subjects: during two last weeks of a 12-week Control period (n = 15) and during two last weeks of a 12-week combined strength and aerobic Training period (n = 13). Resting energy expenditure was estimated using two equations: one with body weight and age, and another one with fat-free mass. TEE and activity induced energy expenditure (AEE) were determined from motion sensor alone, and from motions sensor combined with heart rate monitor, the latter being worn during exercise only.

RESULTS

When body weight and age were used in the calculation of resting energy expenditure, the motion sensor data alone explained 78% and 62% of the variation in TEE assessed by DLW at the end of Control and Training periods, respectively, with a bias of +1.75 (p <.001) and +1.19 MJ/day (p = .002). When exercise heart rate data was added to the model, the combined wearable device approach explained 85% and 70% of the variation in TEE assessed by DLW with a bias of +1.89 and +1.75 MJ/day (p <.001 for both). While significant increases in TEE and AEE were detected by all methods as a result of participation in regular training, motion sensor approach underestimated the change measured by DLW: +1.13±0.66 by DLW, +0.59±0.69 (p = .004) by motion sensor, and +0.98±0.70 MJ/day by combination of motion sensor and heart rate. Use of fat-free mass in the estimation of resting energy expenditure removed the biases between the wearable device estimations and the golden standard reference method of TEE and demonstrated a training-induced increase in resting energy expenditure by +0.18±0.13 MJ/day (p <.001).

CONCLUSIONS

Wrist motion sensor combined with a heart rate monitor during exercise sessions, showed high agreement with the golden standard measurement of daily TEE and its change induced by participation in a long-term training protocol. The positive findings concerning the validity, especially the ability to follow-up the change associated with a lifestyle modification, can be considered significant because they partially determine the feasibility of wearable devices as quantifiers of health-related behavior.

Meta-analysis of the effect of bariatric surgery on physical activity

BACKGROUND

Obesity leads to impairment of physical activity as measured by an inability to perform activities of daily living. Literature on the effect of bariatric surgery on physical activity is conflicting.

OBJECTIVE

The aim of this study was to perform a meta-analysis of the effect of bariatric surgery on physical activity from studies employing objective measurement and self-reporting of physical activity before and after bariatric surgery.

METHODS

Bibliographic databases were searched systematically for relevant literature until December 31, 2018. Studies employing objective and self-reported measurement of physical activity were included. Study quality was assessed using Risk of Bias in Nonrandomized Studies - of Interventions tool. Meta-analysis was performed using random effects model and presented as standardized mean difference (SMD) with 95% confidence intervals (CI).

RESULTS

Twenty studies identified 5886 patients suitable for the analysis. Physical activity showed significant improvement at 0-6 months (SMD: .50; 95% CI: .25-.76; P = .0001), >6-12 months (SMD: .58; 95% CI: .26-.91; P = .0004), and >12-36 months (SMD: .82; 95% CI: .27-1.36; P = .004) after bariatric surgery. Self-reported assessment after bariatric surgery showed significant improvement at 0-6 months (SMD: .65; 95% CI: .29-1.01; P = .0004), >6 to 12 months (SMD: .53; 95% CI: .18-.88; P = .003), and >12-36 months (SMD: .51; 95% CI: .46-.55; P < .00001). Objective assessment after bariatric surgery did not show improvement at 0-6 months (SMD: .31; 95%CI:-.05-.66; P = .09), but showed significant improvement at >6-12 months (SMD: .85; 95% CI:-.07-1.62; P = .03), and >12-36 months (SMD: 1.99; 95% CI: 1.13-2.86; P < .00001) after bariatric surgery.

CONCLUSIONS

Bariatric surgery improves physical activity significantly in a population with obesity up to 3 years after surgery. Objective measurement of physical activity does not show significant improvement within 6 months of bariatric surgery but begins to improve at >6 months. Self-reported measurement of physical activity begins to show improvement within 6 months of a bariatric procedure.

Validity of energy expenditure estimation methods during 10 days of military training

Wearable physical activity (PA) monitors have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established research methods has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors and a PA log against doubly labeled water (DLW) during British Army Officer Cadet (OC) training. For 10 days of training, twenty (10 male and 10 female) OCs (mean ± SD: age 23 ± 2 years, height 1.74 ± 0.09 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK) on the dominant wrist, wore one commercially available monitor (Fitbit SURGE, USA) on the non-dominant wrist, and completed a self-report PA log. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analyzed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement (LoA) were employed to compare TEE from each estimation method to DLW. Average daily TEE from DLW was 4112 ± 652 kcal·day^-1 against which the GENEActiv showed near identical average TEE (mean bias ± LoA: -15 ± 851 kcal^. day^-1 ) while Fitbit tended to underestimate (-656 ± 683 kcal·day^-1 ) and the PA log substantially overestimate (+1946 ± 1637 kcal·day^-1 ). Wearable physical activity monitors provide a cheaper and more practical method for estimating free-living TEE than DLW in military settings. The GENEActiv accelerometer demonstrated good validity for assessing daily TEE and would appear suitable for use in large-scale, longitudinal military studies.

Physical activity prescription for general practice patients with cardiovascular risk factors-the PEPPER randomised controlled trial protocol

BACKGROUND

The health benefits of physical exercise have been shown to be important in the prevention of cardiovascular diseases in patients with hypertension, dyslipidaemia or diabetes. However, few strategies have demonstrated efficacy and practicality in the promotion of physical exercise among this group of patients in general practice.

METHODS

The PEPPER clinical study is a randomised controlled trial to evaluate the efficacy over a period of 12 months, in terms of physical activity level, of an intervention based on structured information delivery, a personalised written physical activity prescription in number of steps per day, a pedometer and a pedometer logbook, in 35 to 74-year-old patients with cardiovascular risk factors. 140 patients will be recruited in 15 GP practices and randomised in the intervention group or in the control group where patients will receive verbal advice of physical exercise. The primary outcome is the change at three months in total energy expenditure measured by an accelerometer over a 7-day period. Secondary outcomes include changes at 3 and 12 months in physical activity levels (accelerometer and International Physical Activity Questionnaire), quality of life (SF-36), blood pressure, weight, waist circumference, perceived obstacles to physical activity and patient compliance with the recommended strategy. Both groups will be compared using mixed models.

DISCUSSION

The results are expected at the end of 2019. If the intervention proves effective in durably increasing the level of physical activity, this strategy could be tested in a larger trial to examine its impact on cardiovascular diseases.

TRIAL REGISTRATION

US National Institutes of Health Clinical Trials Registry NCT02317003 , December 15, 2014.

Gender, age and socioeconomic variation in 24-hour physical activity by wrist-worn accelerometers: the FinHealth 2017 Survey

Assessing movement over 24 hours increases our understanding of the total physical activity level and its patterns. In the FinHealth 2017 Survey, a population-based health examination study, 940 participants between 25 and 93 years were instructed to wear an accelerometer (Actigraph GT9X Link) on their non-dominant wrist for 24 hours on 7 consecutive days. Physical activity information was extracted from 100-Hz triaxial 60-second epoch data as average vector magnitude counts per minute (VM cpm). Results were analyzed by gender, 10-year age-groups, employment status, and education. Hourly means were plotted and compared. Analyses included 915 participants (44% men) who wore the device at least 10 hours on 4 or more days, with mean wear time being 149.5 hours (standard deviation of 615.2 minutes).Women had higher average VM cpm than men (p < 0.001), with significant gender differences in all age-groups until 65 years and older. Total physical activity was lower with age, unemployment, and retirement, where the hourly patterns mirrored the findings. Our findings agree with previous large-scale wrist-accelerometry data, but extend current knowledge by providing data on gender and socioeconomic variation in physical activity across 24 hours in a population-based adult sample representing a broad age range.

Validity and responsiveness to change of the Active Australia Survey according to gender, age, BMI, education, and physical activity level and awareness

BACKGROUND

This study aimed to investigate the validity of the Active Australia Survey across different subgroups and its responsiveness to change, as few previous studies have examined this.

METHODS

The Active Australia Survey was validated against the ActiGraph as an objective measure of physical activity. Participants (n = 465) wore the ActiGraph for 7 days and subsequently completed the Active Australia Survey. Moderate activity, vigorous activity and total moderate and vigorous physical activity were compared using Spearman rank-order correlations. Changes in physical activity between baseline and 3-month assessments were correlated to examine responsiveness to change. The data were stratified to assess outcomes according to different subgroups (e.g., gender, age, weight, activity levels).

RESULTS

With regards to the validity, a significant correlation of ρ = 0.19 was found for moderate physical activity, ρ = 0.33 for vigorous physical activity and ρ = 0.23 for moderate and vigorous physical activity combined. For vigorous physical activity correlations were higher than 0.3 for most subgroups, whereas they were only higher than 0.3 in those with a healthy weight for the other activity outcomes. With regards to responsiveness to change, a correlation of ρ = 0.32 was found for moderate physical activity, ρ = 0.19 for vigorous physical activity and ρ = 0.35 for moderate and vigorous physical activity combined. For moderate and vigorous activity combined correlations were higher than 0.4 for several subgroups, but never for vigorous physical activity.

CONCLUSIONS

Little evidence for the validity of Active Australia Survey was found, although the responsiveness to change was acceptable for several subgroups. Findings from studies using the Active Australia Survey should be interpreted with caution.

TRIAL REGISTRATION

World Health Organisation Universal Trial Number: U111-1119-1755. Australian New Zealand Clinical Trials Registry, ACTRN12611000157976 . Registration date: 8 March 2011.

Device-measured physical activity, sedentary behaviour and cardiometabolic health and fitness across occupational groups: a systematic review and meta-analysis

BACKGROUND

With approximately 8 hours of one's waking day spent at work, occupational tasks and environments are important influencers on an individual's physical activity (PA) and sedentary behaviours. Little research has compared device-measured physical activity, sedentary behaviour and cardiometabolic outcomes between occupational groups.

OBJECTIVE

To compare device-measured movement (sedentary time [ST], light intensity physical activity [LPA], moderate-to-vigorous intensity physical activity [MVPA], and steps) across occupations. The secondary objective was to examine whether cardiometabolic and fitness outcomes differed by occupation.

METHODS

Five bibliographic databases were searched to identify all studies which included working age, employed adults from high-income countries, and reported on device-measured movement within occupations. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses and narrative syntheses.

RESULTS

The review includes 132 unique studies with data from 15,619 participants. Working adults spent ~ 60% of their working and waking time engaged in sedentary behaviour; a very small proportion (~ 4%) of the day included MVPA. On average, workers accumulated 8124 steps/day. Office and call center workers' steps/day were among the lowest, while those of postal delivery workers were highest. Office workers had the greatest ST and the lowest time in LPA both at work and during wakeful time. However, office workers had the greatest minutes sent in MVPA during wakeful hours. Laborers had the lowest ST and spent a significantly greater proportion of their work time in LPA and MVPA. Healthcare and protective services workers had higher levels of LPA at work compared to other occupations. Workers in driving-based occupations tended to have a higher body mass index and blood pressure.

CONCLUSION

This review identifies that occupational and wakeful time PA and ST differed between occupations. Future studies are needed to assess whether patterns differ by age and sex, describe leisure-time movement and movement patterns, and the relationship with cardiometabolic health.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017070448 .

The relationship between physical activity and appetite in patients with heart failure: A prospective observational study

INTRODUCTION

Physical activity and appetite are important components for maintaining health. Yet, the association between physical activity and appetite in heart failure (HF) populations is not completely understood. The aim of the present study was to investigate the relationship between physical activity, functional capacity, and appetite in patients with HF.

METHODS

This was a prospective observational study. In total, 186 patients diagnosed with HF, New York Heart Association (NYHA) class II-IV (mean age 70.7, 30% female), were included. Physical activity was measured using a multi-sensor actigraph for seven days and with a self-reported numeric rating scale. Physical capacity was measured by the six-minute walk test. Appetite was measured using the Council on Nutrition Appetite Questionnaire. Data were collected at inclusion and after 18 months. A series of linear regression analyses, adjusted for age, NYHA class, and B-type natriuretic peptide were conducted.

RESULTS

At baseline, higher levels of physical activity and functional capacity were significantly associated with a higher level of appetite in the unadjusted models. In the adjusted models, number of steps ( p = 0.019) and the six-minute walk test ( p = 0.007) remained significant. At the 18-month follow-up, all physical activity variables and functional capacity were significantly associated with appetite in the unadjusted regression models. In the adjusted models, number of steps ( p = 0.001) and metabolic equivalent daily averages ( p = 0.040) remained significant.

CONCLUSION

A higher level of physical activity measured by number of steps/day was associated with better self-reported appetite, both at baseline and the 18-month follow-up. Further research is needed to establish causality and explore the intertwined relationship between activity and appetite in patients with HF.

Adaptation and Validation of the Hydration Status Questionnaire in a Spanish Adolescent-Young Population: A Cross Sectional Study

The achievement of adequate hydration status is essential for mental and physical performance and for health in general, especially in children and adolescents. Nevertheless, little is known about hydration status of this population, mainly due to the limited availability of research tools; thus, the objective of the current study was to adapt and validate our hydration status questionnaire in a Spanish adolescent-young population. The questionnaire was validated against important hydration markers: urine colour, urine specific gravity, haemoglobin, haematocrit and total body water and involved 128 subjects aged between 12⁻17 years. Water intake was also estimated through a three-day dietary record and physical activity was assessed through accelerometers. Participants completed the questionnaire twice. Water balance and water intake were correlated with urine specific gravity and with total body water content. Water intake obtained by the questionnaire was correlated with results from the three-day dietary record. The intraclass correlation coefficient indicated moderate concordance between both recordings and the Cronbach's alpha revealed high consistency. The Bland and Altman method indicated that the limits of agreement were acceptable to reveal the reliability of the estimated measures. In conclusion, this is the first time that a questionnaire is valid and reliable to estimate hydration status of adolescent-young populations.

Concurrent validity of the Fitbit for assessing sedentary behavior and moderate-to-vigorous physical activity

Background

Recent advances in sensor technologies have promoted the use of consumer-based accelerometers such as Fitbit Flex in epidemiological and clinical research; however, the validity of the Fitbit Flex in measuring sedentary behavior (SED) and physical activity (PA) has not been fully determined against previously validated research-grade accelerometers such as ActiGraph GT3X+. Therefore, the purpose of this study was to examine the concurrent validity of the Fitbit Flex against ActiGraph GT3X+ in a free-living condition.

Methods

A total of 65 participants (age: M = 42, SD = 14 years, female: 72%) each wore a Fitbit Flex and GT3X+ for seven consecutive days. After excluding sleep and non-wear time, time spent (min/day) in SED and moderate-to-vigorous PA (MVPA) were estimated using various cut-points for GT3X+ and brand-specific algorithms for Fitbit, respectively. Repeated measures one-way ANOVA and mean absolute percent errors (MAPE) served to examine differences and measurement errors in SED and MVPA estimates between Fitbit Flex and GT3X+, respectively. Pearson and Spearman correlations and Bland-Altman (BA) plots were used to evaluate the association and potential systematic bias between Fitbit Flex and GT3X+. PROC MIXED procedure in SAS was used to examine the equivalence (i.e., the 90% confidence interval with ±10% equivalence zone) between the devices.

Results

Fitbit Flex produced similar SED and low MAPE (mean difference [MD] = 37 min/day, P = .21, MAPE = 6.8%), but significantly higher MVPA and relatively large MAPE (MD = 59–77 min/day, P < .0001, MAPE = 56.6–74.3%) compared with the estimates from GT3X+ using three different cut-points. The correlations between Fitbit Flex and GT3X+ were consistently higher for SED (r = 0.90, ρ = 0.86, P < .01), but weaker for MVPA (r = 0.65–0.76, ρ = 0.69–0.79, P < .01). BA plots revealed that there is no apparent bias in estimating SED.

Conclusion

In comparison with the GT3X+ accelerometer, the Fitbit Flex provided comparatively accurate estimates of SED, but the Fitbit Flex overestimated MVPA under free-living conditions. Future investigations using the Fitbit Flex should be aware of present findings.

Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches

BACKGROUND

Objective measures using accelerometer-based activity monitors have been extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure PA and SB precisely, the field is shifting towards machine learning-based (ML) approaches for calibration and validation of accelerometer-based activity monitors. Nevertheless, various parameters regarding the use and development of ML-based models, including data type (raw acceleration data versus activity counts), sampling frequency, window size, input features, ML technique, accelerometer placement, and free-living settings, affect the predictive ability of ML-based models. The effects of these parameters on ML-based models have remained elusive, and will be systematically reviewed here. The open challenges were identified and recommendations are made for future studies and directions.

METHOD

We conducted a systematic search of PubMed and Scopus databases to identify studies published before July 2017 that used ML-based techniques for calibration and validation of accelerometer-based activity monitors. Additional articles were manually identified from references in the identified articles.

RESULTS

A total of 62 studies were eligible to be included in the review, comprising 48 studies that calibrated and validated ML-based models for predicting the type and intensity of activities, and 22 studies for predicting activity energy expenditure.

CONCLUSIONS

It appears that various ML-based techniques together with raw acceleration data sampled at 20-30 Hz provide the opportunity of predicting the type and intensity of activities, as well as activity energy expenditure with comparable overall predictive accuracies regardless of accelerometer placement. However, the high predictive accuracy of laboratory-calibrated models is not reproducible in free-living settings, due to transitive and unseen activities together with differences in acceleration signals.

ActiGraph GT3X+ and Actical Wrist and Hip Worn Accelerometers for Sleep and Wake Indices in Young Children Using an Automated Algorithm: Validation With Polysomnography

Objectives: Our count-scaled algorithm automatically scores sleep across 24 hours to process sleep timing, quantity, and quality. The aim of this study was to validate the algorithm against overnight PSG in children to determine the best site placement for sleep. Methods: 28 children (5-8 years) with no history of sleep disturbance wore two types of accelerometers (ActiGraph GT3X+ and Actical) at two sites (left hip, non-dominant wrist) for 24-h. Data were processed using the count-scaled algorithm. PSG data were collected using an in-home Type 2 device. PSG-actigraphy epoch sensitivity (sleep agreement) and specificity (wake agreement) were determined and sleep outcomes compared for timing (onset and offset), quantity [sleep period time (SPT) and total sleep time (TST)], and quality metrics [sleep efficiency and waking after sleep onset (WASO)]. Results: Overall, sensitivities were high (89.1% to 99.5%) and specificities low (21.1% to 45.7%). Sleep offset was accurately measured by actigraphy, regardless of brand or placement site. By contrast, sleep onset agreed with PSG using hip-positioned but not wrist-positioned devices (difference ActiGraph : PSG 21 min, P < .001; Actical : PSG 14 min, P < .001). The ActiGraph at the wrist accurately detected WASO and sleep efficiency, but under (-34 min, P < .001) and overestimated (5.8%, P < .001) these at the hip. The Actical under- and over-estimated these variables respectively at both sites. Results for TST varied ranging from significant differences to PSG of -26 to 21 min (ActiGraph wrist and hip respectively) and 9 min (ns) to 59 min for Actical (wrist and hip respectively). Conclusion: Overall the count-scaled algorithm produced high sensitivity at the expense of low specificity in comparison with PSG. A best site placement for estimates of all sleep variables could not be determined, but overall the results suggested ActiGraph GT3X+ at the hip may be superior for sleep timing and quantity metrics, whereas the wrist may be superior for sleep quality metrics. Both devices placed at the hip performed well for sleep timing but not for sleep quality. Differences are likely linked to freedom of movement of the wrist vs the trunk (hip) during overnight sleep.

The Accuracy of Smart Devices for Measuring Physical Activity in Daily Life: Validation Study

Background

Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices.

Objectives

The aim of this study was, therefore, to investigate convergent validity of 3 Android Wear smartwatches—Polar M600 (Polar Electro Oy, Kempele, Finland), Huawei Watch (Huawei Technologies Co, Ltd, Shenzhen, Guangdong, China), Asus Zenwatch3 (AsusTek Computer Inc, Taipei, Taiwan)—and Fitbit Charge with an ActiGraph accelerometer for measuring steps and moderate to vigorous physical activity (MVPA) on both a day level and 15-min level.

Methods

A free-living protocol was used in which 36 adults engaged in usual daily activities over 2 days while wearing 2 different wearables on the nondominant wrist and an ActiGraph GT3X+ accelerometer on the hip. Validity was evaluated on both levels by comparing each wearable with the ActiGraph GT3X+ accelerometer using correlations and Bland-Altman plots in IBM SPSS 24.0.

Results

On a day level, all devices showed strong correlations (Spearman r=.757-.892) and good agreement (interclass correlation coefficient, ICC=.695-.885) for measuring steps, whereas moderate correlations (Spearman r=.557-.577) and low agreement (ICC=.377-.660) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for measuring steps but a variation between over- and undercounting of MVPA. On a 15-min level, all devices showed strong correlations (Spearman r=.752-.917) and good agreement (ICC=.792-.887) for measuring steps, whereas weak correlations (Spearman r=.116-.208) and low agreement (ICC=.461-.577) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for steps but under- or overestimation for MVPA depending on the device.

Conclusions

In sum, all 4 consumer-level devices can be considered accurate step counters in free-living conditions. This study, however, provides evidence of systematic bias for all devices in measurement of MVPA. The results on a 15-min level also indicate that these devices are not sufficiently accurate to provide correct real-time feedback.

Accelerometer Data Processing and Energy Expenditure Estimation in Preschoolers

PURPOSE

To assess the capacity of different acceleration metrics from wrist accelerations to estimate total energy expenditure (TEE) and activity energy expenditure (AEE) using doubly labeled water in preschool children.

METHODS

Thirty-nine preschoolers (5.5 ± 0.1 yr) were included. Total energy expenditure was measured using doubly labeled water during 14 d, and AEE was then calculated using a predicted basal metabolic rate. Participants wore a wGT3X-BT accelerometer on their nondominant wrist for ≥5 d. We derived the following metrics from raw accelerations: raw ActiGraph activity counts using the normal filter and the low-frequency extension; and alternate summary metrics, such as the Euclidian norm minus 1g (ENMO), Euclidian norm of the high-pass-filtered accelerations (HFEN), the bandpass-filtered accelerations, the HFEN plus Euclidean norm of low-pass filtered accelerations minus 1g (HFEN+) and the mean amplitude deviation.

RESULTS

Alternate summary metrics explained a larger proportion of the variance in TEE and AEE than ActiGraph's activity counts (counts, 7-8 and 25% of TEE and AEE; alternate summary metrics, 13%-16% and 35%-39% of TEE and AEE). Adjustments for body weight and height resulted in an explanation of 51% of AEE by ENMO. All of the metrics adjusted for fat mass and fat-free mass explained up to 84% and 67% of TEE and AEE, respectively.

CONCLUSIONS

ENMO and the other alternate summary metrics explained more of the variance in TEE and AEE than the ActiGraph's activity counts in 5-yr-old children, suggesting further exploration of these variables in studies on physical activity and energy expenditure in preschoolers. Our results need confirmation in other populations with wider age groups and varying body compositions.

The Role of Wearable Devices in Multiple Sclerosis

Multiple sclerosis (MS) is the most common neurological disorder in young adults. The prevalence of walking impairment in people with MS (pwMS) is estimated between 41% and 75%. To evaluate the walking capacity in pwMS, the patient reported outcomes (PROs) and performance-based tests (i.e., the 2-minute walk test, the 6-minute walk test, the Timed 25-Foot Walk Test, the Timed Up and Go Test, and the Six Spot Step Test) could be used. However, some studies point out that the results of both performance-based tests and objective measures (i.e., by accelerometer) could not reflect patient reports of walking performance and impact of MS on daily life. This review analyses different motion sensors embedded in smartphones and motion wearable device (MWD) that can be useful to measure free-living walking behavior, to evaluate falls, fatigue, sedentary lifestyle, exercise, and quality of sleep in everyday life of pwMS. Caveats and limitations of MWD such as variable accuracy, user adherence, power consumption and recharging, noise susceptibility, and data management are discussed as well.

Simultaneous Validation of Seven Physical Activity Questionnaires Used in Japanese Cohorts for Estimating Energy Expenditure: A Doubly Labeled Water Study

BACKGROUND

Physical activity questionnaires (PAQs) used in large-scale Japanese cohorts have rarely been simultaneously validated against the gold standard doubly labeled water (DLW) method. This study examined the validity of seven PAQs used in Japan for estimating energy expenditure against the DLW method.

METHODS

Twenty healthy Japanese adults (9 men; mean age, 32.4 [standard deviation {SD}, 9.4] years, mainly researchers and students) participated in this study. Fifteen-day daily total energy expenditure (TEE) and basal metabolic rate (BMR) were measured using the DLW method and a metabolic chamber, respectively. Activity energy expenditure (AEE) was calculated as TEE - BMR - 0.1 × TEE. Seven PAQs were self-administered to estimate TEE and AEE.

RESULTS

The mean measured values of TEE and AEE were 2,294 (SD, 318) kcal/day and 721 (SD, 161) kcal/day, respectively. All of the PAQs indicated moderate-to-strong correlations with the DLW method in TEE (rho = 0.57-0.84). Two PAQs (Japan Public Health Center Study [JPHC]-PAQ Short and JPHC-PAQ Long) showed significant equivalence in TEE and moderate intra-class correlation coefficients (ICC). None of the PAQs showed significantly equivalent AEE estimates, with differences ranging from -547 to 77 kcal/day. Correlations and ICCs in AEE were mostly weak or fair (rho = 0.02-0.54, and ICC = 0.00-0.44). Only JPHC-PAQ Short provided significant and fair agreement with the DLW method.

CONCLUSIONS

TEE estimated by the PAQs showed moderate or strong correlations with the results of DLW. Two PAQs showed equivalent TEE and moderate agreement. None of the PAQs showed equivalent AEE estimation to the gold standard, with weak-to-fair correlations and agreements. Further studies with larger sample sizes are needed to confirm these findings.

Strength exercises during physical education classes in secondary schools improve body composition: a cluster randomized controlled trial

BACKGROUND

Metabolic health in people with obesity is determined by body composition. In this study, we examined the influence of a combined strength exercise and motivational programme -embedded in the school curriculum- on adolescents body composition and daily physical activity.

METHODS

A total of 695 adolescents (11-15y) from nine Dutch secondary schools participated in a one year cluster randomised controlled trial (RCT). In the intervention schools, physical education teachers were instructed to spend 15-30 min of all physical education lessons (2× per week) on strength exercises. Monthly motivational lessons were given to stimulate students to be more physically active. Control schools followed their usual curriculum. The primary outcome measure was body composition assessed by the deuterium dilution technique. Daily physical activity and sedentary behaviour measured by accelerometry served as a secondary outcome.

RESULTS

After 1 year, a 1.6% fat mass difference was found in favour of the intervention group (p = .007). This reflected a 0.9 kg difference in fat free mass (intervention>control; p = .041) and 0.7 kg difference in fat mass (intervention

CONCLUSION

In 11-15 year olds, the combination of strength exercises plus motivational lessons contributed to an improvement in body composition and a smaller decrease in physical activity level. TRIAL REGISTRATION ID: ( NTR5676 - retrospectively registered 8 February 2016; enrolment of first participant: 2 March 2015).

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Key Words

• Body composition
• Cluster randomised controlled trial
• Motivation
• Overweight and obesity
• Physical activity
• School-based
• Strength exercises

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MESH Headings

• Adolescent
• Adolescent Behavior
• Body Composition
• Child
• Cluster Analysis
• Curriculum
• Female
• Humans
• Male
• Motivation
• Muscle Strength
• Netherlands
• Obesity/prevention & control
• Physical Education and Training/methods
• Program Evaluation/methods
• Retrospective Studies
• School Health Services
• Schools
• Students

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Grants

• 525001004 ZonMw

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Affiliation(s)

G. A. Ten Hoor Department of Human Biology and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands Department of Work and Social Psychology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
G. M. Rutten Department of Health Promotion, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands
G. J. P. Van Breukelen Department of Methodology and Statistics, CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
G. Kok Department of Work and Social Psychology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
R. A. C. Ruiter Department of Work and Social Psychology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
K Meijer Department of Human Biology and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands
S. P. J. Kremers Department of Health Promotion, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands
F. J. M. Feron Department of Social Medicine, CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
R. Crutzen Department of Health Promotion, CAPHRI, Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
A. M. J. W. Schols Department of Respiratory Medicine, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands
G. Plasqui Department of Human Biology and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, P.O. Box 616, 6200 MD Maastricht, The Netherlands

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Validity of a triaxial accelerometer and simplified physical activity record in older adults aged 64-96 years: a doubly labeled water study

BACKGROUND

The aim was to examine the validity of a triaxial accelerometer (ACCTRI) and a simplified physical activity record (sPAR) in estimating total energy expenditure (TEE) and physical activity level (PAL) in older adults with the doubly labeled water (DLW) method.

METHODS

A total of 44 Japanese elderly individuals (64-96 years), of which 28 were community-dwelling healthy adults with or without sporting habits (S or NS group) and 16 were care home residents with frailty (F group), were included in the study. Basal metabolic rate (BMR) was measured by indirect calorimetry, TEE was obtained by the DLW method, and PAL was calculated as TEE/BMR. Daily step count was monitored by a pedometer (Lifecorder). The 24-h average metabolic equivalent was assessed by ACCTRI and sPAR.

RESULTS

The TEE_DLW in men was 2704 ± 353, 2308 ± 442, and 1795 ± 338 kcal d^-1, and that in women was 2260 ± 208, 1922 ± 285, and 1421 ± 274 kcal d^-1 for the S, NS, and F groups, respectively. ACCTRI and sPAR systematically underestimated actual TEE (- 14.2 ± 11.6 and - 15.3 ± 12.3% for ACCTRI and sPAR, respectively). After diet-induced thermogenesis was taken into account for ACCTRI and sPAR, TEE_DLW was significantly correlated with TEE_ACCTRI (R² = 0.714) and TEE_sPAR (R² = 0.668). PAL_DLW was also significantly correlated with PAL_ACCTRI (R² = 0.438) and PAL_sPAR (R² = 0.402).

CONCLUSIONS

Age, living conditions, frailty, and sporting habits contribute to TEE and PAL in the elderly population. ACCTRI and sPAR underestimated TEE and PAL, and adequate corrections are required. The corrected ACCTRI and sPAR are both useful tools to estimate TEE and PAL.

Do weather changes influence physical activity level among older adults? - The Generation 100 study

Introduction

Understanding how individual and environmental factors impact physical activity (PA) level is important when building strategies to improve PA of older adults. No studies have examined how hour-to-hour weather changes influence PA in older adults or how the association between weather and PA eventually is related to cardiorespiratory fitness (CRF) measured as peak oxygen uptake. The aim of this study was therefore to examine how hour-to-hour changes in weather effects hour-to-hour PA in a cohort of Norwegian older adults across CRF levels, gender and seasons.

Methods

PA was assessed objectively in 1219 older adults (70–77 years, 51% females) using the Actigraph GT3X+ accelerometer, and quantified as counts·min^-1 (CPM). Weather (Norwegian meteorological Institute) and CRF (MetaMax II) were measured objectively. Panel data analysis added a longitudinal dimension when 110.888 hours of weather- and PA data were analyzed.

Results

Older adults had a higher PA level in warmer (597 CPM) than colder months (556 CPM) (p<0.01). Fixed effects regression-models revealed that increasing temperatures (per hour) influenced PA positively in both colder and warmer months (all, p<0.01), with greater influence in fitter vs. less fit participants (p<0.01). In warmer months, increasing precipitation negatively influenced PA in both unfit females and unfit males (p<0.01). In colder months, increasing precipitation positively influenced PA for moderately fit to fit males (p<0.01), but not for females and unfit males.

Conclusion

To the best of our knowledge, this is the first study to examine the association between weather conditions and objectively-measured-PA among Norwegian older adults. Our findings demonstrates that unfit older adults will be less likely to participate in PA when the weather is unpleasant, compared to those highly fit. The data suggests that the impact of weather should not be ignored when planning public health strategies for increasing PA among older adults.

Understanding the Nature of Measurement Error When Estimating Energy Expenditure and Physical Activity via Physical Activity Recall

Background: The National Health and Nutrition Examination Survey physical activity questionnaire (PAQ) is used to estimate activity energy expenditure (AEE) and moderate to vigorous physical activity (MVPA). Bias and variance in estimates of AEE and MVPA from the PAQ have not been described, nor the impact of measurement error when utilizing the PAQ to predict biomarkers and categorize individuals.Methods: The PAQ was administered to 385 adults to estimate AEE (AEE:PAQ) and MVPA (MVPA:PAQ), while simultaneously measuring AEE with doubly labeled water (DLW; AEE:DLW) and MVPA with an accelerometer (MVPA:A).Results: Although AEE:PAQ [3.4 (2.2) MJ·d−1] was not significantly different from AEE:DLW [3.6 (1.6) MJ·d−1;P > .14], MVPA:PAQ [36.2 (24.4) min·d−1] was significantly higher than MVPA:A [8.0 (10.4) min·d−1;P < .0001]. AEE:PAQ regressed on AEE:DLW and MVPA:PAQ regressed on MVPA:A yielded not only significant positive relationships but also large residual variances. The relationships between AEE and MVPA, and 10 of the 12 biomarkers were underestimated by the PAQ. When compared with accelerometers, the PAQ overestimated the number of participants who met the Physical Activity Guidelines for Americans.Conclusions: Group-level bias in AEE:PAQ was small, but large for MVPA:PAQ. Poor within-participant estimates of AEE:PAQ and MVPA:PAQ lead to attenuated relationships with biomarkers and misclassifications of participants who met or who did not meet the Physical Activity Guidelines for Americans.

A study of measurement properties of the Life-Space Assessment questionnaire in older adults with chronic obstructive pulmonary disease

OBJECTIVE

To test the measurement properties (reliability, interpretability, and validity) of the Life-Space Assessment questionnaire for older adults with chronic obstructive pulmonary disease.

DESIGN

Clinimetric study.

SETTING

Pneumology service, ambulatory care, São Paulo, SP, Brazil.

PARTICIPANTS

Consecutive sample of older adults ( n = 62; 38 (61%) men, 24 (39%) women) with chronic obstructive pulmonary disease.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Life-Space Assessment questionnaire assesses five space levels visited by the older adult in four weeks prior to the assessment. We tested the following measurement properties of this questionnaire: reliability (reproducibility assessed by a type-2,1 intraclass correlation coefficient (ICC_2,1); internal consistency assessed by the Cronbach's alpha; measurement error by determining the standard error of measurement (SEM)), interpretability (minimum detectable change with 90% confidence (MDC₉₀); ceiling and floor effects by calculating the proportion of participants who achieved the minimum and maximum scores), and validity by Pearson's correlation test between the Life-Space Assessment questionnaire scores and number of daily steps assessed by accelerometry.

RESULTS

Reproducibility (ICC_2,1) was 0.90 (95% confidence interval (CI): 0.84-0.94), and internal consistency (Cronbach's α) was 0.80 (range = 0.76-0.80 for each item deleted). SEM was 3.65 points (3%), the MDC₉₀ was 0.20 points, and we observed no ceiling (2%) or floor (6%) effects. We observed an association between the score of the Life-Space Assessment questionnaire and daily steps ( r = 0.43; P = 0.01).

CONCLUSION

Life-Space Assessment questionnaire shows adequate measurement properties for the assessment of life-space mobility in older adults with chronic obstructive pulmonary disease.

Comparison of Two Generations of ActiGraph Accelerometers: The CARDIA Study

PURPOSE

This study aimed to examine the comparability of the ActiGraph 7164 and wGT3X-BT wear time, count-based estimates, and average time per day in physical activity of different intensities.

METHODS

We studied 87 Coronary Artery Risk Development in Young Adults (CARDIA) participants 48-60 yr of age who simultaneously wore the 7164 and wGT3X-BT accelerometers at the waist in 2015-2016, with wear time of ≥4 of 7 d, ≥10 h·d for both monitors. Freedson cutpoints (counts per minute) were used to define sedentary (<100), light (100-1951), moderate (1952-5724), and vigorous activity (≥5725). Agreement was evaluated using paired-difference tests, intraclass correlation coefficients, and Bland-Altman plots. Given systematic differences in count-based estimates between monitors, a calibration formula applied to the wGT3X-BT values was obtained by linear regression.

RESULTS

Total detected wear time minutes per day was nearly identical between the 7164 and the wGT3X-BT (881.5 ± 70.9 vs 880.3 ± 78.1, P = 0.72). The wGT3X-BT values were calibrated to the 7164 values by dividing counts by 1.088. After calibration, no differences were observed between the 7164 and the wGT3X-BT in total counts per day (310,184 ± 129,189 vs 307,085 ± 135,362, P = 0.48), average counts per min per day (349.5 ± 139.5 vs 346.5 ± 147.2, P = 0.54), sedentary (513.2 ± 93.6 vs 509.6 ± 98.6, P = 0.23), light (335.3 ± 81.5 vs 338.7 ± 81.1, P = 0.22), moderate (31.0 ± 21.9 vs 30.3 ± 23.4, P = 0.31), or moderate-to-vigorous minutes per day (33.1 ± 24.6 vs 32.0 ± 26.0, P = 0.13). A significant difference was observed for vigorous minutes per day (0.2 ± 1.0 vs 0.0 ± 0.3, P < 0.01); however, the absolute difference was marginal. Intraclass correlation coefficients showed excellent agreement for all measures (0.95-0.99).

CONCLUSIONS

After applying a calibration formula, the 7164 and wGT3X-BT were comparable for total wear time, count-based estimates, and average minutes per day in sedentary, light, moderate, and moderate-to-vigorous activity. Findings illustrate a novel methodological approach to facilitate accelerometer data harmonization.

Reliability and Construct Validity of the SENS Motion® Activity Measurement System as a Tool to Detect Sedentary Behaviour in Patients with Knee Osteoarthritis

Physical inactivity is important to address, and an objective way of measuring inactivity is by accelerometry. The objective of this study was to determine the reliability and construct validity of the SENS motion system to record physical activity and inactivity in patients with knee osteoarthritis. Participants with an age > 40 years and an average weekly pain above 0 on a numeric rating scale (0 = no pain, 10 = worst pain) were included. Participants had a total of two study visits and at each visit participants completed a standardized activity. Data from 24 participants were analysed. A mean agreement of 99% (SD 3%) for sedentary behaviour and a mean agreement of 97% (SD 9%) for active behaviour were found. The agreement for “walking” was 28% (SD 18%). Mean agreement between recordings on the two visits was 96% (SD 8%) for sedentary behaviour and 99% (SD 1%) for active behaviour. The SENS motion activity measurement system can be regarded as a reliable and valid device for measuring sedentary behaviour in patients with knee OA, whereas detection of walking is not reliable and would require further work.

Free-Living Responses in Energy Balance to Short-Term Overfeeding in Adults Differing in Propensity for Obesity

OBJECTIVE

Free-living adaptive responses to short-term overfeeding (OF) were explored as predictors of longitudinal weight change in adults classified as having obesity resistance (OR) or obesity proneness (OP) based on self-identification and personal/family weight history.

METHODS

Adults identified as OP (n = 21; BMI: 23.8 ± 2.5 kg/m² ) and OR (n = 20; BMI: 20.2 ± 2.1 kg/m² ) completed 3 days of eucaloric feeding (EU; 100% of energy needs) and 3 days of OF (140% of energy needs). Following each condition, adaptive responses in physical activity (PA), total daily energy expenditure, ad libitum energy intake, and energy balance were objectively measured for 3 days in a free-living environment. Body mass and composition were measured annually by using dual-energy x-ray absorptiometry for 5 years. Adaptive responses to OF were correlated with 5-year changes in body mass and composition.

RESULTS

Increases in sedentary time correlated with longitudinally measured changes in fat mass (r = 0.34, P = 0.04) in the cohort taken as a whole. Those with OP reduced their levels of PA following OF, whereas those with OR maintained or increased their PA. No other variables were found to correlate with weight gain.

CONCLUSIONS

Failure to decrease sedentary behavior following short-term OF is one mechanism that may be contributing to fat mass gain.

Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry

Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions.

NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.

Obstructive Sleep Apnea Syndrome, Objectively Measured Physical Activity and Exercise Training Interventions: A Systematic Review and Meta-Analysis

A systematic review of English and French articles using Pubmed/Medline and Embase included studies assessing objective physical activity levels of obstructive sleep apnea (OSA) patients and exploring the effects of exercise training on OSA severity, body mass index (BMI), sleepiness, and cardiorespiratory fitness [peak oxygen consumption (VO2peak)]. Two independent reviewers analyzed the studies, extracted the data, and assessed the quality of evidence. For objective physical activity levels, eight studies were included. The mean number of steps per day across studies was 5,388 (95% CI: 3,831–6,945; p < 0.001), which was by far lower than the recommended threshold of 10,000 steps per day. For exercise training, six randomized trials were included. There was a significant decrease in apnea–hypopnea-index following exercise training (mean decrease of 8.9 events/h; 95% CI: −13.4 to −4.3; p < 0.01), which was accompanied by a reduction in subjective sleepiness, an increase in VO2peak and no change in BMI. OSA patients present low levels of physical activity and exercise training is associated with improved outcomes. Future interventions (including exercise training) focusing on increasing physical activity levels may have important clinical impacts on both OSA severity and the burden of associated co-morbidities. Objective measurement of physical activity in routine OSA management and well-designed clinical trials are recommended.

Registration # CRD42017057319 (Prospero).

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Validity of Combination Use of Activity Record and Accelerometry to Measure Free-Living Total Energy Expenditure in Female Endurance Runners

Yoshida, A, Ishikawa-Takata, K, Tanaka, S, Suzuki, N, Nakae, S, Murata, H, Taguchi, M, and Higuchi, M. Validity of combination use of activity record and accelerometry to measure free-living total energy expenditure in female endurance runners. J Strength Cond Res 33(11): 2962-2970, 2019-Herein, we attempted to prove the validity of a new approach to assessing total energy expenditure (TEE) that combines activity recording and accelerometry in athletes. Eight female endurance runners participated in this study. We measured TEE over 8 days in the regular training season by using the doubly labeled water (DLW) method. In the combined method, an activity record of the rating of perceived exertion (RPE) was used to estimate energy expenditure (EE) during the training period, whereas a triaxial accelerometer was used to evaluate EE during the nontraining time over the TEE measurement period using the DLW method. Training EE was calculated from the subjects' individual rating of perceived exertion-EE correlations provided by the exercise tolerance test. Resting metabolic rate (RMR) was measured using indirect calorimetry. There were no significant differences in TEE, activity-induced EE (AEE), or physical activity level (PAL; TEE/RMR) between the DLW method and the combined method (TEE, 3,032 ± 344 vs. 3,033 ± 495 kcal·d; AEE, 1,585 ± 303 vs. 1,586 ± 442 kcal·d; and PAL, 2.68 ± 0.37 vs. 2.68 ± 0.48, respectively). Significant positive correlations and no systematic errors were observed in AEE and PAL. Intraclass correlation coefficients were high (TEE, 0.785; AEE, 0.841; and PAL, 0.779, respectively). These findings suggest that the combined method has high validity against the DLW method. Thus, the combined method would be able to estimate free-living TEE in the regular training season for female endurance runners.

Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water

PURPOSE

To compare the degree to which four accelerometer metrics-total activity counts per day (TAC per day), steps per day (steps per day), physical activity energy expenditure (PAEE) (kcal·kg·d), and moderate- to vigorous-intensity physical activity (MVPA) (min·d)-were correlated with PAEE measured by doubly labeled water (DLW). Additionally, accelerometer metrics based on vertical axis counts and triaxial counts were compared.

METHODS

This analysis included 684 women and 611 men age 43 to 83 yr. Participants wore the Actigraph GT3X on the hip for 7 d twice during the study and the average of the two measurements was used. Each participant also completed one DLW measurement, with a subset having a repeat. PAEE was estimated by subtracting resting metabolic rate and the thermic effect of food from total daily energy expenditure estimated by DLW. Partial Spearman correlations were used to estimate associations between PAEE and each accelerometer metric.

RESULTS

Correlations between the accelerometer metrics and DLW-determined PAEE were higher for triaxial counts than vertical axis counts. After adjusting for weight, age, accelerometer wear time, and fat free mass, the correlation between TAC per day based on triaxial counts and DLW-determined PAEE was 0.44 in women and 0.41 in men. Correlations for steps per day and accelerometer-estimated PAEE with DLW-determined PAEE were similar. After adjustment for within-person variation in DLW-determined PAEE, the correlations for TAC per day increased to 0.61 and 0.49, respectively. Correlations between MVPA and DLW-determined PAEE were lower, particularly for modified bouts of ≥10 min.

CONCLUSIONS

Accelerometer measures that represent total activity volume, including TAC per day, steps per day, and PAEE, were more highly correlated with DLW-determined PAEE than MVPA using traditional thresholds and should be considered by researchers seeking to reduce accelerometer data to a single metric.

Unobtrusive Estimation of Cardiorespiratory Fitness with Daily Activity in Healthy Young Men

Despite the importance of cardiorespiratory fitness, no practical method exists to estimate maximal oxygen consumption (VO₂max) without a specific exercise protocol. We developed an estimation model of VO₂max, using maximal activity energy expenditure (aEEmax) as a new feature to represent the level of physical activity. Electrocardiogram (ECG) and acceleration data were recorded for 4 days in 24 healthy young men, and reference VO₂max levels were measured using the maximal exercise test. aEE was calculated using the measured acceleration data and body weight, while heart rate (HR) was extracted from the ECG signal. aEEmax was obtained using linear regression, with aEE and HR as input parameters. The VO₂max was estimated from the aEEmax using multiple linear regression modeling in the training group (n = 16) and was verified in the test group (n = 8). High correlations between the estimated VO₂max and the measured VO₂max were identified in both groups, with a 15-hour recording being sufficient to produce a highly accurate VO₂max estimate. Additional recording time did not significantly improve the accuracy of the estimation. Our VO₂max estimation method provides a robust alternative to traditional approaches while only requiring minimal data acquisition time in daily life.

Energy expenditure estimation from respiration variables

The aim of this study was to develop and cross-validate two models to estimate total energy expenditure (TEE) based on respiration variables in healthy subjects during daily physical activities. Ninety-nine male and female subjects systematically varying in age (18-60 years) and body mass index (BMI; 17-36 kg*m-2) completed eleven aerobic activities with a portable spirometer as the criterion measure. Two models were developed using linear regression analyses with the data from 67 randomly selected subjects (50.0% female, 39.9 ± 11.8 years, 25.1 ± 5.2 kg*m-2). The models were cross-validated with the other 32 subjects (49% female, 40.4 ± 10.7 years, 24.7 ± 4.6 kg*m-2) by applying equivalence testing and Bland-and-Altman analyses. Model 1, estimating TEE based solely on respiratory volume, respiratory rate, and age, was significantly equivalent to the measured TEE with a systematic bias of 0.06 kJ*min-1 (0.22%) and limits of agreement of ±6.83 kJ*min-1. Model 1 was as accurate in estimating TEE as Model 2, which incorporated further information on activity categories, heart rate, sex, and BMI. The results demonstrated that respiration variables and age can be used to accurately determine daily TEE for different types of aerobic activities in healthy adults across a broad range of ages and body sizes.

Systemic effects of chronic obstructive pulmonary disease in young-old adults' life-space mobility

PURPOSE

The objective was to assess whether dyspnea, peripheral muscle strength and the level of physical activity are correlated with life-space mobility of older adults with COPD.

PATIENTS AND METHODS

Sixty patients over 60 years of age (40 in the COPD group and 20 in the control group) were included. All patients were evaluated for lung function (spirometry), life-space mobility (University of Alabama at Birmingham Study of Aging Life-Space Assessment), dyspnea severity (Modified Dyspnea Index), peripheral muscle strength (handgrip dynamometer), level of physical activity and number of daily steps (accelerometry). Groups were compared using unpaired t-test. Pearson's correlation was used to test the association between variables.

RESULTS

Life-space mobility (60.41±16.93 vs 71.07±16.28 points), dyspnea (8 [7-9] vs 11 [10-11] points), peripheral muscle strength (75.16±14.89 vs 75.50±15.13 mmHg), number of daily steps (4,865.4±2,193.3 vs 6,146.8±2,376.4 steps), and time spent in moderate to vigorous activity (197.27±146.47 vs 280.05±168.95 minutes) were lower among COPD group compared to control group (p<0.05). The difference was associated with the lower mobility of COPD group in the neighborhood.

CONCLUSION

Life-space mobility is decreased in young-old adults with COPD, especially at the neighborhood level. This impairment is associated to higher dyspnea, peripheral muscle weakness and the reduced level of physical activity.

Correlates of Agreement between Accelerometry and Self-reported Physical Activity

Supplemental digital content is available in the text.

Purpose

Understanding factors that influence accurate assessment of physical activity (PA) and sedentary behavior (SB) is important to measurement development, epidemiologic studies, and interventions. This study examined agreement between self-reported (International Physical Activity Questionnaire—Long Form [IPAQ-LF]) and accelerometry-based estimates of PA and SB across six countries and identified correlates of between-method agreement.

Methods

Self-report and objective (accelerometry-based) PA and SB data were collected in 2002–2011 from 3865 adult participants in eight cities from six countries (Belgium, Czech Republic, Denmark, Spain, United Kingdom, and United States). Between-method relative agreement (correlation) and absolute disagreement (mean difference between conceptually and intensity-matched IPAQ-LF and accelerometry-based PA and SB variables) were estimated. Also, sociodemographic characteristics and PA patterns were examined as correlates of between-method agreement.

Results

Observed relative agreement (relationships of IPAQ-LF with accelerometry-based PA and SB variables) was small to moderate (r = 0.05–0.37) and was moderated by sociodemographic (age, sex, weight status, and education) and behavioral (PA-type) factors. The absolute disagreement was large, with participants self-reporting higher PA intensity and total time in moderate-to-vigorous-intensity PA than accelerometry. Also, self-reported sitting time was lower than accelerometry-based sedentary behavior. After adjusting for sociodemographic and behavioral factors, the absolute disagreement between pairs of IPAQ-LF and accelerometry-based PA variables remained significantly different across cities/countries.

Conclusions

Present findings suggest systematic cultural and/or linguistic and sociodemographic differences in absolute agreement between the IPAQ-LF and the accelerometry-based PA and SB variables. These results have implications for the interpretation of international PA and SB data and correlate/determinant studies. They call for further efforts to improve such measures.

Subjective and objective assessment of physical activity - Influence of newly diagnosed exercise induced bronchoconstriction and gender

AIM

To investigate if occurrence of newly diagnosed exercise induced bronchoconstriction (EIB) would affect adolescents' ability to assess their physical activity.

METHODS

99 selected adolescents with and 47 adolescents without self-reported exercise induced dyspnea were included. All of the 146 adolescents then performed a standardized exercise challenge test on a treadmill with dry-air inhalation to detect EIB. Free living physical activity was assessed during seven days with both accelerometer (objective assessment) and a validated activity diary (subjective assessment). Height, weight and subjective sleep were recorded.

RESULTS

Out of the 146 adolescents 49 were diagnosed with EIB. Forty-six of the adolescents with EIB (35 girls and 11 boys) and 84 of the control adolescents (45 girls and 39 boys) had complete 7 day activity diary and accelerometer data. There were no differences in age, BMI and sleep between EIB and control adolescents. Boys with EIB overestimated subjective assessment compared to objective assessment more than girls with EIB. No difference was seen between control boys and girls. Furthermore, boys with EIB reported a much higher frequency of high intensity exercise than girls with EIB, but no difference was observed between control boys and girls.

CONCLUSION

Adolescent boys with newly diagnosed EIB overestimated their physical activity compared to EIB girls. Caution may thus be used when choosing methods measuring level of physical activity in this group and especially when investigating gender differences.