Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

Gait differences between COPD and healthy controls: systematic review and meta-analysis.

BACKGROUND: Despite the importance of gait as a determinant of falls, disability and mortality in older people, understanding of gait impairment in COPD is limited. This study aimed to identify differences in gait characteristics during supervised walking tests between people with COPD and healthy controls. METHODS: We searched 11 electronic databases, supplemented by Google Scholar searches and manual collation of references, in November 2019 and updated the search in July 2021. Record screening and information extraction were performed independently by one reviewer and checked for accuracy by a second. Meta-analyses were performed in studies not considered at a high risk of bias. RESULTS: Searches yielded 21 085 unique records, of which 25 were included in the systematic review (including 1015 people with COPD and 2229 healthy controls). Gait speed was assessed in 17 studies (usual speed: 12; fast speed: three; both speeds: two), step length in nine, step duration in seven, cadence in six, and step width in five. Five studies were considered at a high risk of bias. Low-quality evidence indicated that people with COPD walk more slowly than healthy controls at their usual speed (mean difference (MD) -19 cm·s-1, 95% CI -28 to -11 cm·s-1) and at a fast speed (MD -30 cm·s-1, 95% CI -47 to -13 cm·s-1). Alterations in other gait characteristics were not statistically significant. CONCLUSION: Low-quality evidence shows that people with COPD walk more slowly than healthy controls, which could contribute to an increased falls risk. The evidence for alterations in spatial and temporal components of gait was inconclusive. Gait impairment appears to be an important but understudied area in COPD.

Physical activity and body mass related to catch-up lung function growth in childhood: a population-based accelerated cohort study.

OBJECTIVE: The existence of catch-up lung function growth and its predictors is uncertain. We aimed to identify lung function trajectories and their predictors in a population-based birth cohort. METHODS: We applied group-based trajectory modelling to z-scores of forced expiratory volume in 1 second (zFEV1) and z-scores of forced vital capacity (zFVC) from 1151 children assessed at around 4, 7, 9, 10, 11, 14 and 18 years. Multinomial logistic regression models were used to test whether potential prenatal and postnatal predictors were associated with lung function trajectories. RESULTS: We identified four lung function trajectories: a low (19% and 19% of the sample for zFEV1 and zFVC, respectively), normal (62% and 63%), and high trajectory (16% and 13%) running in parallel, and a catch-up trajectory (2% and 5%) with catch-up occurring between 4 and 10 years. Fewer child allergic diseases and higher body mass index z-score (zBMI) at 4 years were associated with the high and normal compared with the low trajectories, both for zFEV1 and zFVC. Increased children's physical activity during early childhood and higher zBMI at 4 years were associated with the catch-up compared with the low zFEV1 trajectory (relative risk ratios: 1.59 per physical activity category (1.03-2.46) and 1.47 per zBMI (0.97-2.23), respectively). No predictors were identified for zFVC catch-up growth. CONCLUSION: We found three parallel-running and one catch-up zFEV1 and zFVC trajectories, and identified physical activity and body mass at 4 years as predictors of zFEV1 but not zFVC catch-up growth.

Lung-function trajectories: relevance and implementation in clinical practice.

Lung development starts in utero and continues during childhood through to adolescence, reaching its peak in early adulthood. This growth is followed by gradual decline due to physiological lung ageing. Lung-function development can be altered by several host and environmental factors during the life course. As a result, a range of lung-function trajectories exist in the population. Below average trajectories are associated with respiratory, cardiovascular, metabolic, and mental health comorbidities, as well as with premature death. This Review presents progressive research into lung-function trajectories and assists the implementation of this knowledge in clinical practice as an innovative approach to detect poor lung health early, monitor respiratory disease progression, and promote lung health. Specifically, we propose that, similar to paediatric height and weight charts used globally to monitor children's growth, lung-function charts could be used for both children and adults to monitor lung health status across the life course. To achieve this proposal, we introduce our free online Lung Function Tracker tool. Finally, we discuss challenges and opportunities for effective implementation of the trajectory concept at population level and outline an agenda for crucial research needed to support such implementation.

Real-world walking cadence in people with COPD.

Introduction: The clinical validity of real-world walking cadence in people with COPD is unsettled. Our objective was to assess the levels, variability and association with clinically relevant COPD characteristics and outcomes of real-world walking cadence. Methods: We assessed walking cadence (steps per minute during walking bouts longer than 10 s) from 7 days' accelerometer data in 593 individuals with COPD from five European countries, and clinical and functional characteristics from validated questionnaires and standardised tests. Severe exacerbations during a 12-month follow-up were recorded from patient reports and medical registries. Results: Participants were mostly male (80%) and had mean±sd age of 68±8 years, post-bronchodilator forced expiratory volume in 1 s (FEV1) of 57±19% predicted and walked 6880±3926 steps·day-1. Mean walking cadence was 88±9 steps·min-1, followed a normal distribution and was highly stable within-person (intraclass correlation coefficient 0.92, 95% CI 0.90-0.93). After adjusting for age, sex, height and number of walking bouts in fractional polynomial or linear regressions, walking cadence was positively associated with FEV1, 6-min walk distance, physical activity (steps·day-1, time in moderate-to-vigorous physical activity, vector magnitude units, walking time, intensity during locomotion), physical activity experience and health-related quality of life and negatively associated with breathlessness and depression (all p<0.05). These associations remained after further adjustment for daily steps. In negative binomial regression adjusted for multiple confounders, walking cadence related to lower number of severe exacerbations during follow-up (incidence rate ratio 0.94 per step·min-1, 95% CI 0.91-0.99, p=0.009). Conclusions: Higher real-world walking cadence is associated with better COPD status and lower severe exacerbations risk, which makes it attractive as a future prognostic marker and clinical outcome.

Association between physical activity over a 10-year period and current insomnia symptoms, sleep duration and daytime sleepiness: a European population-based study.

OBJECTIVES: To explore the relationship between physical activity over a 10-year period and current symptoms of insomnia, daytime sleepiness and estimated sleep duration in adults aged 39-67. DESIGN: Population-based, multicentre cohort study. SETTING: 21 centres in nine European countries. METHODS: Included were 4339 participants in the third follow-up to the European Community Respiratory Health Survey (ECRHS III), who answered questions on physical activity at baseline (ECRHS II) and questions on physical activity, insomnia symptoms, sleep duration and daytime sleepiness at 10-year follow-up (ECRHS III). Participants who reported that they exercised with a frequency of at least two or more times a week, for 1 hour/week or more, were classified as being physically active. Changes in activity status were categorised into four groups: persistently non-active; became inactive; became active; and persistently active. MAIN OUTCOME MEASURES: Insomnia, sleep time and daytime sleepiness in relation to physical activity. RESULTS: Altogether, 37% of participants were persistently non-active, 25% were persistently active, 20% became inactive and 18% became active from baseline to follow-up. Participants who were persistently active were less likely to report difficulties initiating sleep (OR 0.60, 95% CI 0.45-0.78), a short sleep duration of ≤6 hours/night (OR 0.71, 95% CI 0.59-0.85) and a long sleep of ≥9 hours/night (OR 0.53, 95% CI 0.33-0.84) than persistently non-active subjects after adjusting for age, sex, body mass index, smoking history and study centre. Daytime sleepiness and difficulties maintaining sleep were not related to physical activity status. CONCLUSION: Physically active people have a lower risk of some insomnia symptoms and extreme sleep durations, both long and short.

Short-term effects of air pollution and weather on physical activity in patients with chronic obstructive pulmonary disease (COPD).

INTRODUCTION: Patients with chronic obstructive pulmonary disease (COPD) accumulate low levels of physical activity. How environmental factors affect their physical activity in the short-term is uncertain. AIM: to assess the short-term effects of air pollution and weather on physical activity levels in COPD patients. METHODS: This multi-center panel study assessed 408 COPD patients from Catalonia (Spain). Daily physical activity (i.e., steps, time in moderate-to-vigorous physical activity (MVPA), locomotion intensity, and sedentary time) was recorded in two 7-day periods, one year apart, using the Dynaport MoveMonitor. Air pollution (nitrogen dioxide (NO2), particulate matter below 10 µm (PM10) and a marker of black carbon (absorbance of PM2.5: PM2.5ABS), and weather (average and maximum temperature, and rainfall) were estimated the same day (lag zero) and up to 5 days prior to each assessment (lags 1-5). Mixed-effect distributed lag linear regression models were adjusted for age, sex, weekday, public holidays, greenness, season, and social class, with patient and city as random effects. RESULTS: Patients (85% male) were on average (mean ± SD) 68 ± 9 years old with a post-bronchodilator forced expiratory volume in 1 s (FEV1) of 57 ± 18% predicted. Higher NO2, PM10 and PM2.5ABS levels at lag four were associated with fewer steps, less time in MVPA, reduced locomotion intensity, and longer sedentary time (e.g., coefficient (95% CI) of -60 (-105, -15) steps per 10 µg/m3 increase in NO2). Higher average and maximum temperatures at lag zero were related to more steps and time in MVPA, and less sedentary time (e.g., +85 (15, 154) steps per degree Celsius). Higher rainfall at lag zero was related to fewer steps and more sedentary time. CONCLUSION: Air pollution affects the amount and intensity of physical activity performed on the following days in COPD patients, whereas weather affects the amount of physical activity performed on the same day.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Spirometric patterns in young and middle-aged adults: a 20-year European study.

BACKGROUND: Understanding the natural history of abnormal spirometric patterns at different stages of life is critical to identify and optimise preventive strategies. We aimed to describe characteristics and risk factors of restrictive and obstructive spirometric patterns occurring before 40 years (young onset) and between 40 and 61 years (mid-adult onset). METHODS: We used data from the population-based cohort of the European Community Respiratory Health Survey (ECRHS). Prebronchodilator forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were assessed longitudinally at baseline (ECRHS1, 1993-1994) and again 20 years later (ECRHS3, 2010-2013). Spirometry patterns were defined as: restrictive if FEV1/FVC≥LLN and FVC<10th percentile, obstructive if FEV1/FVC

Shaping urban environments to improve respiratory health: recommendations for research, planning, and policy.

Urban areas carry a large burden of acute (infectious) and chronic respiratory diseases due to environmental conditions such as high levels of air pollution and high population densities. Car-dominated cities often lack walkable areas, which reduces opportunities for physical activity that are fundamentally important for healthy lungs. The already restricted amount of green space available-with often poorly selected plants-could produce pollen and subsequently provoke or worsen allergic diseases. Less affluent neighbourhoods often carry a larger respiratory disease burden. A multisectoral approach with more diverse policy measures and urban innovations is needed to reduce air pollution (eg, low emission zones), to increase public space for walking and cycling (eg, low traffic neighbourhoods, superblocks, 15-minute cities, and car-free cities), and to develop green cities (eg, planting of low-allergy trees). Stricter EU air quality guidelines can push these transformations to improve the respiratory health of citizens. Advocacy by medical respiratory societies can also make an important contribution to such changes.

Validation of Constant Work Rate Cycling Endurance Time for Use in Chronic Obstructive Pulmonary Disease Clinical Trials.

Rationale: A COPD Foundation working group sought to identify measures of exercise endurance, a meaningful aspect of physical functioning in everyday life among patients with chronic obstructive pulmonary disease (COPD) that is not fully accepted in regulatory decision making, hampering drug development. Objectives: To demonstrate, as we previously asserted (Casaburi COPD 2022;9:252), that constant work rate cycling endurance time is an appropriate exercise endurance measure in patients with COPD. Methods: To validate this assertion, we assembled an integrated database of endurance time responses, including 8 bronchodilator (2,166 subjects) and 15 exercise training (3,488 subjects) studies (Casaburi COPD 2022;9:520). Results: Construct validity was demonstrated: 1) peak physiologic and perceptual responses were similar for constant work rate and incremental cycling; 2) after bronchodilator therapy, there were greater increases in endurance time in patients with more severe airflow limitation; 3) after exercise training, endurance time increases were similar across airflow limitation severities; and 4) there were correlations between changes in endurance time and changes in mechanistically related physiologic and perceptual variables. Test-retest reliability was demonstrated, with consistency of changes in endurance time at two time points after the intervention. Responsiveness was confirmed, with significant increases in endurance time after active (but not placebo) bronchodilator therapy, with greater increases seen with more severe airflow limitation and after exercise training. On the basis of regression analysis using multiple anchor variables, the minimum important difference for endurance time increase is estimated to be approximately 1 minute. Conclusions: Constant work rate cycling endurance time is a valid exercise endurance measure in COPD, suitable for contributing to the evaluation of treatment benefit supporting regulatory decision making and evidence-based therapeutic recommendations.

Early life exposures contributing to accelerated lung function decline in adulthood - a follow-up study of 11,000 adults from the general population.

Background: We aimed to assess whether exposure to risk factors in early life from conception to puberty continue to contribute to lung function decline later in life by using a pooled cohort comprising approx. 11,000 adults followed for more than 20 years and with up to three lung function measurements. Methods: Participants (20-68 years) in the ECRHS and NFBC1966 cohort studies followed in the periods 1991-2013 and 1997-2013, respectively, were included. Mean annual decline in maximum forced expired volume in 1 s (FEV1) and forced vital capacity (FVC) were main outcomes. Associations between early life risk factors and change in lung function were estimated using mixed effects linear models adjusted for sex, age, FEV1, FVC and height at baseline, accounting for personal smoking. Findings: Decline in lung function was accelerated in participants with mothers that smoked during pregnancy (FEV1 2.3 ml/year; 95% CI: 0.7, 3.8) (FVC 2.2 ml/year; 0.2, 4.2), with asthmatic mothers (FEV1 2.6 ml/year; 0.9, 4.4) (FEV1/FVC 0.04 per year; 0.04, 0.7) and asthmatic fathers (FVC 2.7 ml/year; 0.5, 5.0), and in women with early menarche (FVC 2.4 ml/year; 0.4, 4.4). Personal smoking of 10 pack-years contributed to a decline of 2.1 ml/year for FEV1 (1.8, 2.4) and 1.7 ml/year for FVC (1.3, 2.1). Severe respiratory infections in early childhood were associated with accelerated decline among ever-smokers. No effect-modification by personal smoking, asthma symptoms, sex or cohort was found. Interpretation: Mothers' smoking during pregnancy, parental asthma and early menarche may contribute to a decline of FEV1 and FVC later in life comparable to smoking 10 pack-years. Funding: European Union's Horizon 2020; Research Council of Norway; Academy of Finland; University Hospital Oulu; European Regional Development Fund; Spanish Ministry of Science and Innovation; Generalitat de Catalunya.

Ambient temperature and seasonal variation in inpatient mortality from respiratory diseases: a retrospective observational study.

Background: The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain. Methods: We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2 and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation. Findings: The study analysed 1 710 012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103 845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure. Interpretation: Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season. Funding: European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

Investigating the prognostic value of digital mobility outcomes in patients with chronic obstructive pulmonary disease: a systematic literature review and meta-analysis.

BACKGROUND: Reduced mobility is a central feature of COPD. Assessment of mobility outcomes that can be measured digitally (digital mobility outcomes (DMOs)) in daily life such as gait speed and steps per day is increasingly possible using devices such as pedometers and accelerometers, but the predictive value of these measures remains unclear in relation to key outcomes such as hospital admission and survival. METHODS: We conducted a systematic review, nested within a larger scoping review by the MOBILISE-D consortium, addressing DMOs in a range of chronic conditions. Qualitative and quantitative analysis considering steps per day and gait speed and their association with clinical outcomes in COPD patients was performed. RESULTS: 21 studies (6076 participants) were included. Nine studies evaluated steps per day and 11 evaluated a measure reflecting gait speed in daily life. Negative associations were demonstrated between mortality risk and steps per day (per 1000 steps) (hazard ratio (HR) 0.81, 95% CI 0.75-0.88, p<0.001), gait speed (<0.80 m·s-1) (HR 3.55, 95% CI 1.72-7.36, p<0.001) and gait speed (per 1.0 m·s-1) (HR 7.55, 95% CI 1.11-51.3, p=0.04). Fewer steps per day (per 1000) and slow gait speed (<0.80 m·s-1) were also associated with increased healthcare utilisation (HR 0.80, 95% CI 0.72-0.88, p<0.001; OR 3.36, 95% CI 1.42-7.94, p=0.01, respectively). Available evidence was of low-moderate quality with few studies eligible for meta-analysis. CONCLUSION: Daily step count and gait speed are negatively associated with mortality risk and other important outcomes in people with COPD and therefore may have value as prognostic indicators in clinical trials, but the quantity and quality of evidence is limited. Larger studies with consistent methodologies are called for.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases.

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings. Methods: Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data. Results and discussion: The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of -0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, -0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases.

Laboratory and free-living gait performance in adults with COPD and healthy controls.

Background: Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised). Methods: This case-control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately. Results: Slower walking speed (-11 cm·s-1, 95% CI: -20 to -3) and lower cadence (-6.6 steps·min-1, 95% CI: -12.3 to -0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups. Conclusion: Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD.

Impact of long-term exposure to ambient ozone on lung function over a course of 20 years (The ECRHS study): a prospective cohort study in adults.

Background: While the adverse effects of short-term ambient ozone exposure on lung function are well-documented, the impact of long-term exposure remains poorly understood, especially in adults. Methods: We aimed to investigate the association between long-term ozone exposure and lung function decline. The 3014 participants were drawn from 17 centers across eight countries, all of which were from the European Community Respiratory Health Survey (ECRHS). Spirometry was conducted to measure pre-bronchodilation forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) at approximately 35, 44, and 55 years of age. We assigned annual mean values of daily maximum running 8-h average ozone concentrations to individual residential addresses. Adjustments were made for PM2.5, NO2, and greenness. To capture the ozone-related change in spirometric parameters, our linear mixed effects regression models included an interaction term between long-term ozone exposure and age. Findings: Mean ambient ozone concentrations were approximately 65 µg/m³. A one interquartile range increase of 7 µg/m³ in ozone was associated with a faster decline in FEV1 of -2.08 mL/year (95% confidence interval: -2.79, -1.36) and in FVC of -2.86 mL/year (-3.73, -1.99) mL/year over the study period. Associations were robust after adjusting for PM2.5, NO2, and greenness. The associations were more pronounced in residents of northern Europe and individuals who were older at baseline. No consistent associations were detected with the FEV1/FVC ratio. Interpretation: Long-term exposure to elevated ambient ozone concentrations was associated with a faster decline of spirometric lung function among middle-aged European adults over a 20-year period. Funding: German Research Foundation.

Resilience characterized and quantified from physical activity data: A tutorial in R.

Consistent physical activity is key for health and well-being, but it is vulnerable to stressors. The process of recovering from such stressors and bouncing back to the previous state of physical activity can be referred to as resilience. Quantifying resilience is fundamental to assess and manage the impact of stressors on consistent physical activity. In this tutorial, we present a method to quantify the resilience process from physical activity data. We leverage the prior operationalization of resilience, as used in various psychological domains, as area under the curve and expand it to suit the characteristics of physical activity time series. As use case to illustrate the methodology, we quantified resilience in step count time series (length = 366 observations) for eight participants following the first COVID-19 lockdown as a stressor. Steps were assessed daily using wrist-worn devices. The methodology is implemented in R and all coding details are included. For each person's time series, we fitted multiple growth models and identified the best one using the Root Mean Squared Error (RMSE). Then, we used the predicted values from the selected model to identify the point in time when the participant recovered from the stressor and quantified the resulting area under the curve as a measure of resilience for step count. Further resilience features were extracted to capture the different aspects of the process. By developing a methodological guide with a step-by-step implementation, we aimed at fostering increased awareness about the concept of resilience for physical activity and facilitate the implementation of related research.