Prognostic Significance of Different Ventricular Ectopic Burdens During Submaximal Exercise in Asymptomatic UK Biobank Subjects.

BACKGROUND: The consequences of exercise-induced premature ventricular contractions (PVCs) in asymptomatic individuals remain unclear. This study aimed to assess the association between PVC burdens during submaximal exercise and major adverse cardiovascular events (MI/HF/LTVA: myocardial infarction [MI], heart failure [HF], and life-threatening ventricular arrhythmia [LTVA]), and all-cause mortality. Additional end points were MI, LTVA, HF, and cardiovascular mortality. METHODS: A neural network was developed to count PVCs from ECGs recorded during exercise (6 minutes) and recovery (1 minute) in 48 315 asymptomatic participants from UK Biobank. Associations were estimated using multivariable Cox proportional hazard models. Explorative studies were conducted in subgroups with cardiovascular magnetic resonance imaging data (n=6290) and NT-proBNP (N-terminal Pro-B-type natriuretic peptide) levels (n=4607) to examine whether PVC burden was associated with subclinical cardiomyopathy. RESULTS: Mean age was 56.8±8.2 years; 51.1% of the participants were female; and median follow-up was 12.6 years. Low PVC counts during exercise and recovery were both associated with MI/HF/LTVA risk, independently of clinical factors: adjusted hazard ratio (HR), 1.2 (1-5 exercise PVCs, P<0.001) and HR, 1.3 (1-5 recovery PVCs, P<0.001). Risks were higher with increasing PVC count: HR, 1.8 (>20 exercise PVCs, P<0.001) and HR, 1.6 (>5 recovery PVCs, P<0.001). A similar trend was observed for all-cause mortality, although associations were only significant for high PVC burdens: HRs, 1.6 (>20 exercise PVCs, P<0.001) and 1.5 (>5 recovery PVCs, P<0.001). Complex PVC rhythms were associated with higher risk compared with PVC count alone. PVCs were also associated with incident HF, LTVA, and cardiovascular mortality, but not MI. In the explorative studies, high PVC burden was associated with larger left ventricular volumes, lower ejection fraction, and higher levels of NT-proBNP compared with participants without PVCs. CONCLUSIONS: In this cohort of middle-aged and older adults, PVC count during submaximal exercise and recovery were both associated with MI/HF/LTVA, all-cause mortality, HF, LTVAs, and cardiovascular mortality, independent of clinical and exercise test factors, indicating an incremental increase in risk as PVC count rises. Complex PVC rhythms were associated with higher risk compared with PVC count alone. Underlying mechanisms may include the presence of subclinical cardiomyopathy.

Dose-response of accelerometer-measured physical activity, step count, and cancer risk in the UK Biobank: a prospective cohort analysis.

BACKGROUND: Cancer is an age-related condition, but changes to modifiable lifestyle-related behaviours, including physical activity, could impact risk. While step count is an accessible metric of activity for older adults, its association with cancer risk remains poorly understood. We investigated the association between accelerometer-measured total activity, step count, and cancer risk. METHODS: We analysed data from a prospective UK Biobank cohort of consenting participants who wore wrist-based Axivity AX3 accelerometer devices for 7 days between June 1, 2013 and Dec 23, 2015, had valid accelerometer data, and no previous cancer diagnosis at baseline. Machine learning models estimated total physical activity (vector magnitude) and step count. The primary outcome, a composite of 13 cancers previously associated with physical activity, was obtained from national registries. Hazard ratios (HR) and were calculated using Cox proportional hazard models, with attained age as the underlying timescale and adjustment for sex, ethnicity, smoking status, alcohol consumption, education, and Townsend Deprivation Index. The impact of reallocating time between behaviours was evaluated using compositional data analyses. Dose-response associations were assessed with restricted cubic splines. FINDINGS: We analysed data from 86 556 participants, who were followed up during an average of 6·1 years (age range 43-78; 48 478 [56%] female and 38 078 [44%] male; 83 830 [97%] white). 5577 incident malignant cancers occurred among these 86 556 participants. Greater total physical activity was associated with a lower risk of physical-activity-related cancer (HR per 1 SD [+8·33 milligravity per day] 0·85, 95% CI 0·81-0·89). Reallocating 30 min/day from other activities to moderate-to-vigorous physical activity behaviour was associated with lower cancer risk (HR 0·96, 0·94-0·98), as was reallocating 1 h/day to light intensity activity (HR 0·94, 0·92-0·96), compared with the mean behaviour composition among included participants. Compared with taking 5000 steps per day, taking 10 000 daily steps was associated with a significantly lower risk of physical-activity-related cancer (HR 0·81, 0·73-0·90). INTERPRETATION: In this sample from the UK Biobank, higher total physical activity and daily step count were associated with lower risk of physical-activity-related cancers. Findings suggest additional physical activity time, irrespective of intensity, may be beneficial. Increasing low intensity activity time and increasing daily step counts could be practical public health interventions to lower cancer risk, especially for aging adults. FUNDING: National Institute of Health Oxford Cambridge Scholars Program, Wellcome Trust, Swiss Re, Health Data Research UK, and Cancer Research UK.

A systematic review of the performance of actigraphy in measuring sleep stages.

The accuracy of actigraphy for sleep staging is assumed to be poor, but examination is limited. This systematic review aimed to assess the performance of actigraphy in sleep stage classification of adults. A systematic search was performed using MEDLINE, Web of Science, Google Scholar, and Embase databases. We identified eight studies that compared sleep architecture estimates between wrist-worn actigraphy and polysomnography. Large heterogeneity was found with respect to how sleep stages were grouped, and the choice of metrics used to evaluate performance. Quantitative synthesis was not possible, so we performed a narrative synthesis of the literature. From the limited number of studies, we found that actigraphy-based sleep staging had some ability to classify different sleep stages compared with polysomnography.

The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: A systematic review.

BACKGROUND: Accelerometer measures of physical behaviours (physical activity, sedentary behaviour and sleep) in observational studies offer detailed insight into associations with health and disease. Maximising recruitment and accelerometer wear, and minimising data loss remain key challenges. How varying methods used to collect accelerometer data influence data collection outcomes is poorly understood. We examined the influence of accelerometer placement and other methodological factors on participant recruitment, adherence and data loss in observational studies of adult physical behaviours. METHODS: The review was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). Observational studies of adults including accelerometer measurement of physical behaviours were identified using database (MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus and Cumulative Index to Nursing & Allied Health Literature) and supplementary searches to May 2022. Information regarding study design, accelerometer data collection methods and outcomes were extracted for each accelerometer measurement (study wave). Random effects meta-analyses and narrative syntheses were used to examine associations of methodological factors with participant recruitment, adherence and data loss. RESULTS: 123 accelerometer data collection waves were identified from 95 studies (92.5% from high-income countries). In-person distribution of accelerometers was associated with a greater proportion of invited participants consenting to wear an accelerometer (+ 30% [95% CI 18%, 42%] compared to postal distribution), and adhering to minimum wear criteria (+ 15% [4%, 25%]). The proportion of participants meeting minimum wear criteria was higher when accelerometers were worn at the wrist (+ 14% [ 5%, 23%]) compared to waist. Daily wear-time tended to be higher in studies using wrist-worn accelerometers compared to other wear locations. Reporting of information regarding data collection was inconsistent. CONCLUSION: Methodological decisions including accelerometer wear-location and method of distribution may influence important data collection outcomes including recruitment and accelerometer wear-time. Consistent and comprehensive reporting of accelerometer data collection methods and outcomes is needed to support development of future studies and international consortia. Review supported by the British Heart Foundation (SP/F/20/150002) and registered (Prospero CRD42020213465).

Device-measured movement behaviours in over 20,000 China Kadoorie Biobank participants.

BACKGROUND: Movement behaviours, including physical activity, sedentary behaviour, and sleep have been shown to be associated with several chronic diseases. However, they have not been objectively measured in large-scale prospective cohort studies in low-and middle-income countries. We aim to describe the patterns of device-measured movement behaviours collected in the China Kadoorie Biobank (CKB) study. METHODS: During 2020 and 2021, a random subset of 25,087 surviving CKB individuals participated in the 3rd resurvey of the CKB. Among them, 22,511 (89.7%) agreed to wear an Axivity AX3 wrist-worn triaxial accelerometer for seven consecutive days to assess their habitual movement behaviours. We developed a machine-learning model to infer time spent in four movement behaviours [i.e. sleep, sedentary behaviour, light intensity physical activity (LIPA), and moderate-to-vigorous physical activity (MVPA)]. Descriptive analyses were performed for wear-time compliance and patterns of movement behaviours by different participant characteristics. RESULTS: Data from 21,897 participants (aged 65.4 ± 9.1 years; 35.4% men) were received for demographic and wear-time analysis, with a median wear-time of 6.9 days (IQR: 6.1-7.0). Among them, 20,370 eligible participants were included in movement behavior analyses. On average, they had 31.1 mg/day (total acceleration) overall activity level, accumulated 7.7 h/day (32.3%) of sleep time, 8.8 h/day (36.6%) sedentary, 5.7 h/day (23.9%) in light physical activity, and 104.4 min/day (7.2%) in moderate-to-vigorous physical activity. There was an inverse relationship between age and overall acceleration with an observed decline of 5.4 mg/day (17.4%) per additional decade. Women showed a higher activity level than men (32.3 vs 28.8 mg/day) and there was a marked geographical disparity in the overall activity level and time allocation. CONCLUSIONS: This is the first large-scale accelerometer data collected among Chinese adults, which provides rich and comprehensive information about device-measured movement behaviour patterns. This resource will enhance our knowledge about the potential relevance of different movement behaviours for chronic disease in Chinese adults.

Charting a Course for Smartphones and Wearables to Transform Population Health Research.

The use of data from smartphones and wearable devices has huge potential for population health research, given the high level of device ownership; the range of novel health-relevant data types available from consumer devices; and the frequency and duration with which data are, or could be, collected. Yet, the uptake and success of large-scale mobile health research in the last decade have not met this intensely promoted opportunity. We make the argument that digital person-generated health data are required and necessary to answer many top priority research questions, using illustrative examples taken from the James Lind Alliance Priority Setting Partnerships. We then summarize the findings from 2 UK initiatives that considered the challenges and possible solutions for what needs to be done and how such solutions can be implemented to realize the future opportunities of digital person-generated health data for clinically important population health research. Examples of important areas that must be addressed to advance the field include digital inequality and possible selection bias; easy access for researchers to the appropriate data collection tools, including how best to harmonize data items; analysis methodologies for time series data; patient and public involvement and engagement methods for optimizing recruitment, retention, and public trust; and methods for providing research participants with greater control over their data. There is also a major opportunity, provided through the linkage of digital person-generated health data to routinely collected data, to support novel population health research, bringing together clinician-reported and patient-reported measures. We recognize that well-conducted studies need a wide range of diverse challenges to be skillfully addressed in unison (eg, challenges regarding epidemiology, data science and biostatistics, psychometrics, behavioral and social science, software engineering, user interface design, information governance, data management, and patient and public involvement and engagement). Consequently, progress would be accelerated by the establishment of a new interdisciplinary community where all relevant and necessary skills are brought together to allow for excellence throughout the life cycle of a research study. This will require a partnership of diverse people, methods, and technologies. If done right, the synergy of such a partnership has the potential to transform many millions of people's lives for the better.

Accelerometer measured physical activity and the incidence of cardiovascular disease: Evidence from the UK Biobank cohort study.

BACKGROUND: Higher levels of physical activity (PA) are associated with a lower risk of cardiovascular disease (CVD). However, uncertainty exists on whether the inverse relationship between PA and incidence of CVD is greater at the highest levels of PA. Past studies have mostly relied on self-reported evidence from questionnaire-based PA, which is crude and cannot capture all PA undertaken. We investigated the association between accelerometer-measured moderate, vigorous, and total PA and incident CVD. METHODS AND FINDINGS: We obtained accelerometer-measured moderate-intensity and vigorous-intensity physical activities and total volume of PA, over a 7-day period in 2013-2015, for 90,211 participants without prior or concurrent CVD in the UK Biobank cohort. Participants in the lowest category of total PA smoked more, had higher body mass index and C-reactive protein, and were diagnosed with hypertension. PA was associated with 3,617 incident CVD cases during 440,004 person-years of follow-up (median (interquartile range [IQR]): 5.2 (1.2) years) using Cox regression models. We found a linear dose-response relationship for PA, whether measured as moderate-intensity, vigorous-intensity, or as total volume, with risk of incident of CVD. Hazard ratios (HRs) and 95% confidence intervals for increasing quarters of the PA distribution relative to the lowest fourth were for moderate-intensity PA: 0.71 (0.65, 0.77), 0.59 (0.54, 0.65), and 0.46 (0.41, 0.51); for vigorous-intensity PA: 0.70 (0.64, 0.77), 0.54 (0.49,0.59), and 0.41 (0.37,0.46); and for total volume of PA: 0.73 (0.67, 0.79), 0.63 (0.57, 0.69), and 0.47 (0.43, 0.52). We took account of potential confounders but unmeasured confounding remains a possibility, and while removal of early deaths did not affect the estimated HRs, we cannot completely dismiss the likelihood that reverse causality has contributed to the findings. Another possible limitation of this work is the quantification of PA intensity-levels based on methods validated in relatively small studies. CONCLUSIONS: In this study, we found no evidence of a threshold for the inverse association between objectively measured moderate, vigorous, and total PA with CVD. Our findings suggest that PA is not only associated with lower risk for of CVD, but the greatest benefit is seen for those who are active at the highest level.

Correction: Accelerometer measured physical activity and the incidence of cardiovascular disease: Evidence from the UK Biobank cohort study.

[This corrects the article DOI: 10.1371/journal.pmed.1003487.].

Physical activity in relation to circulating hormone concentrations in 117,100 men in UK Biobank.

PURPOSE: Physical activity may reduce the risk of some types of cancer in men. Biological mechanisms may involve changes in hormone concentrations; however, this relationship is not well established. Therefore, we aimed to investigate the associations of physical activity with circulating insulin-like growth factor-I (IGF-I), sex hormone-binding globulin (SHBG, which modifies sex hormone activity), and total and free testosterone concentrations, and the extent these associations might be mediated by body mass index (BMI). METHODS: Circulating concentrations of these hormones and anthropometric measurements and self-reported physical activity data were available for 117,100 healthy male UK Biobank participants at recruitment. Objectively measured accelerometer physical activity levels were also collected on average 5.7 years after recruitment in 28,000 men. Geometric means of hormone concentrations were estimated using multivariable-adjusted analysis of variance, with and without adjustment for BMI. RESULTS: The associations between physical activity and hormones were modest and similar for objectively measured (accelerometer) and self-reported physical activity. Compared to men with the lowest objectively measured physical activity, men with high physical activity levels had 14% and 8% higher concentrations of SHBG and total testosterone, respectively, and these differences were attenuated to 6% and 3% following adjustment for BMI. CONCLUSION: Our results suggest that the associations of physical activity with the hormones investigated are, at most, modest; and following adjustment for BMI, the small associations with SHBG and total testosterone were largely attenuated. Therefore, it is unlikely that changes in these circulating hormones explain the associations of physical activity with risk of cancer either independently or via BMI.

Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease.

OBJECTIVE: To improve classification of movement behaviours in free-living accelerometer data using machine-learning methods, and to investigate the association between machine-learned movement behaviours and risk of incident cardiovascular disease (CVD) in adults. METHODS: Using free-living data from 152 participants, we developed a machine-learning model to classify movement behaviours (moderate-to-vigorous physical activity behaviours (MVPA), light physical activity behaviours, sedentary behaviour, sleep) in wrist-worn accelerometer data. Participants in UK Biobank, a prospective cohort, were asked to wear an accelerometer for 7 days, and we applied our machine-learning model to classify their movement behaviours. Using compositional data analysis Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence. RESULTS: In leave-one-participant-out analysis, our machine-learning method classified free-living movement behaviours with mean accuracy 88% (95% CI 87% to 89%) and Cohen's kappa 0.80 (95% CI 0.79 to 0.82). Among 87 498 UK Biobank participants, there were 4105 incident CVD events. Reallocating time from any behaviour to MVPA, or reallocating time from sedentary behaviour to any behaviour, was associated with lower CVD risk. For an average individual, reallocating 20 min/day to MVPA from all other behaviours proportionally was associated with 9% (95% CI 7% to 10%) lower risk, while reallocating 1 hour/day to sedentary behaviour from all other behaviours proportionally was associated with 5% (95% CI 3% to 7%) higher risk. CONCLUSION: Machine-learning methods classified movement behaviours accurately in free-living accelerometer data. Reallocating time from other behaviours to MVPA, and from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD, and should be promoted by interventions and guidelines.

Ribosomal oxygenases are structurally conserved from prokaryotes to humans.

2-Oxoglutarate (2OG)-dependent oxygenases have important roles in the regulation of gene expression via demethylation of N-methylated chromatin components and in the hydroxylation of transcription factors and splicing factor proteins. Recently, 2OG-dependent oxygenases that catalyse hydroxylation of transfer RNA and ribosomal proteins have been shown to be important in translation relating to cellular growth, TH17-cell differentiation and translational accuracy. The finding that ribosomal oxygenases (ROXs) occur in organisms ranging from prokaryotes to humans raises questions as to their structural and evolutionary relationships. In Escherichia coli, YcfD catalyses arginine hydroxylation in the ribosomal protein L16; in humans, MYC-induced nuclear antigen (MINA53; also known as MINA) and nucleolar protein 66 (NO66) catalyse histidine hydroxylation in the ribosomal proteins RPL27A and RPL8, respectively. The functional assignments of ROXs open therapeutic possibilities via either ROX inhibition or targeting of differentially modified ribosomes. Despite differences in the residue and protein selectivities of prokaryotic and eukaryotic ROXs, comparison of the crystal structures of E. coli YcfD and Rhodothermus marinus YcfD with those of human MINA53 and NO66 reveals highly conserved folds and novel dimerization modes defining a new structural subfamily of 2OG-dependent oxygenases. ROX structures with and without their substrates support their functional assignments as hydroxylases but not demethylases, and reveal how the subfamily has evolved to catalyse the hydroxylation of different residue side chains of ribosomal proteins. Comparison of ROX crystal structures with those of other JmjC-domain-containing hydroxylases, including the hypoxia-inducible factor asparaginyl hydroxylase FIH and histone N(ε)-methyl lysine demethylases, identifies branch points in 2OG-dependent oxygenase evolution and distinguishes between JmjC-containing hydroxylases and demethylases catalysing modifications of translational and transcriptional machinery. The structures reveal that new protein hydroxylation activities can evolve by changing the coordination position from which the iron-bound substrate-oxidizing species reacts. This coordination flexibility has probably contributed to the evolution of the wide range of reactions catalysed by oxygenases.

A validation study of the Eurostat harmonised European time use study (HETUS) diary using wearable technology.

BACKGROUND: The central aim was to examine the accuracy of the full range of daily activities recorded in self-report time-use diaries against data from two objective passive data collection devices (wearable camera and accelerometer) serving as criterion reference instruments. This enabled systematic checks and comparisons on the timing, sequence and duration of activities recorded from the three data sources. METHODS: Participants (n = 148) were asked to complete a single-day self-report paper time-use diary designed for use in the Harmonised European Time Use Study (HETUS), while simultaneously wearing a camera that continuously recorded images of their activities, and an accelerometer tracking physical movement. In a reconstruction interview shortly after the data collection period, participants viewed the camera images to help researchers interpret the image sequences. Of the initial 148 recruits (multi-seed snowball sample, 59% women, aged 18-91, 43% > 40) 131 returned usable diary and camera records (of whom 124 also provided a usable whole-day accelerometer record. We compare time allocation estimates from the diary and camera records, and also match the diary and camera records to the simultaneously recorded accelerometer vector magnitudes. RESULTS: The data were examined at three analytic levels: aggregate, individual diarist and timeslot. The most important finding is that the estimates of mean daily time devoted to 8 of the 10 main activities differ by < 10% in the camera and diary records. The single case of major divergence (eating) can be explained by a systematic difference between the procedures followed by the self-reporting diarist and the observer coding the camera records. There are more substantial differences at the respondent level, paired t-tests showing significant differences in time spent in the 4/10 categories. 45% of all variation in the accelerometer vector magnitudes in the timeslots is explained by camera and diary records. Detailed activity classifications perform much better than METs as predictors of actigraphy. CONCLUSIONS: The comparison of the diary with the camera and accelerometer records strongly supports using diary methodology for studying the full range of daily activity, particularly at aggregate levels. Accelerometer data could be combined with diary measures to improve estimation of METs equivalents for various types of active and sedentary behaviour.

Association of Cardiovascular Risk Factors With MRI Indices of Cerebrovascular Structure and Function and White Matter Hyperintensities in Young Adults.

Importance: Risk of stroke and brain atrophy in later life relate to levels of cardiovascular risk in early adulthood. However, it is unknown whether cerebrovascular changes are present in young adults. Objective: To examine relationships between modifiable cardiovascular risk factors and cerebrovascular structure, function, and white matter integrity in young adults. Design, Setting, and Participants: A cross-sectional observational study of 125 young adults (aged 18-40 years) without clinical evidence of cerebrovascular disease. Data collection was completed between August 2014 and May 2016 at the University of Oxford, United Kingdom. Final data collection was completed on May 31, 2016. Exposures: The number of modifiable cardiovascular risk factors at recommended levels, based on the following criteria: body mass index (BMI) <25; highest tertile of cardiovascular fitness and/or physical activity; alcohol consumption <8 drinks/week; nonsmoker for >6 months; blood pressure on awake ambulatory monitoring <130/80 mm Hg; a nonhypertensive diastolic response to exercise (peak diastolic blood pressure <90 mm Hg); total cholesterol <200 mg/dL; and fasting glucose <100mg/dL. Each risk factor at the recommended level was assigned a value of 1, and participants were categorized from 0-8, according to the number of risk factors at recommended levels, with higher numbers indicating healthier risk categories. Main Outcomes and Measures: Cerebral vessel density, caliber and tortuosity, brain white matter hyperintensity lesion count. In a subgroup (n = 52), brain blood arrival time and cerebral blood flow assessed by brain magnetic resonance imaging (MRI). Results: A total of 125 participants, mean (SD) age 25 (5) years, 49% women, with a mean (SD) score of 6.0 (1.4) modifiable cardiovascular risk factors at recommended levels, completed the cardiovascular risk assessment and brain MRI protocol. Cardiovascular risk factors were correlated with cerebrovascular morphology and white matter hyperintensity count in multivariable models. For each additional modifiable risk factor categorized as healthy, vessel density was greater by 0.3 vessels/cm3 (95% CI, 0.1-0.5; P = .003), vessel caliber was greater by 8 µm (95% CI, 3-13; P = .01), and white matter hyperintensity lesions were fewer by 1.6 lesions (95% CI, -3.0 to -0.5; P = .006). Among the 52 participants with available data, cerebral blood flow varied with vessel density and was 2.5 mL/100 g/min higher for each healthier category of a modifiable risk factor (95% CI, 0.16-4.89; P = .03). Conclusions and Relevance: In this preliminary study involving young adults without clinical evidence of cerebrovascular disease, a greater number of modifiable cardiovascular risk factors at recommended levels was associated with higher cerebral vessel density and caliber, higher cerebral blood flow, and fewer white matter hyperintensities. Further research is needed to verify these findings and determine their clinical importance.

Exploring the opportunities for food and drink purchasing and consumption by teenagers during their journeys between home and school: a feasibility study using a novel method.

OBJECTIVE: To investigate the feasibility and acceptability of using wearable cameras as a method to capture the opportunities for food and drink purchasing/consumption that young people encounter on their regular journeys to and from school. DESIGN: A qualitative study using multiple data-collection methods including wearable cameras, global positioning system units, individual interviews, food and drink purchase and consumption diaries completed by participants over four days, and an audit of food outlets located within an 800 m Euclidean buffer zone around each school. SETTING: A community setting. SUBJECTS: Twenty-two students (fourteen girls and eight boys) aged 13-15 years recruited from four secondary schools in two counties of England. RESULTS: Wearable cameras offered a feasible and acceptable method for collecting food purchase and consumption data when used alongside traditional methods of data collection in a small number of teenagers. We found evidence of participants making deliberate choices about whether or not to purchase/consume food and drink on their journeys. These choices were influenced by priorities over money, friends, journey length, travel mode and ease of access to opportunities for purchase/consumption. Most food and drink items were purchased/consumed within an 800 m Euclidean buffer around school, with items commonly selected being high in energy, fat and sugar. Wearable camera images combined with interviews helped identify unreported items and misreporting errors. CONCLUSIONS: Wearable camera images prompt detailed discussion and generate contextually specific information which could offer new insights and understanding around eating behaviour patterns. The feasibility of scaling up the use of these methods requires further empirical work.

Wearable cameras can reduce dietary under-reporting: doubly labelled water validation of a camera-assisted 24 h recall.

Preliminary research has suggested that wearable cameras may reduce under-reporting of energy intake (EI) in self-reported dietary assessment. The aim of the present study was to test the validity of a wearable camera-assisted 24 h dietary recall against the doubly labelled water (DLW) technique. Total energy expenditure (TEE) was assessed over 15 d using the DLW protocol among forty adults (n 20 males, age 35 (sd 17) years, BMI 27 (sd 4) kg/m2 and n 20 females, age 28 (sd 7) years, BMI 22 (sd 2) kg/m2). EI was assessed using three multiple-pass 24 h dietary recalls (MP24) on days 2-4, 8-10 and 13-15. On the days before each nutrition assessment, participants wore an automated wearable camera (SenseCam (SC)) in free-living conditions. The wearable camera images were viewed by the participants following the completion of the dietary recall, and their changes in self-reported intakes were recorded (MP24+SC). TEE and EI assessed by the MP24 and MP24+SC methods were compared. Among men, the MP24 and MP24+SC measures underestimated TEE by 17 and 9%, respectively (P< 0.001 and P= 0.02). Among women, these measures underestimated TEE by 13 and 7%, respectively (P< 0.001 and P= 0.004). The assistance of the wearable camera (MP24+SC) reduced the magnitude of under-reporting by 8% for men and 6% for women compared with the MP24 alone (P< 0.001 and P< 0.001). The increase in EI was predominantly from the addition of 265 unreported foods (often snacks) as revealed by the participants during the image review. Wearable cameras enhance the accuracy of self-report by providing passive and objective information regarding dietary intake. High-definition image sensors and increased imaging frequency may improve the accuracy further.

The use of a wearable camera to capture and categorise the environmental and social context of self-identified eating episodes.

Research investigating the influence of the environmental and social factors on eating behaviours in free-living settings is limited. This study investigates the utility of using wearable camera images to assess the context of eating episodes. Adult participants (N = 40) wore a SenseCam wearable camera for 4 days (including 1 familiarisation day) over a 15-day period in free-living conditions, and had their diet assessed using three image-assisted multiple-pass 24-hour dietary recalls. The images of participants' eating episodes were analysed and annotated according to their environmental and social contexts; including eating location, external environment (indoor/outdoor), physical position, social interaction, and viewing media screens. Data for 107 days were used, with a total of 742 eating episodes considered for annotation. Twenty nine per cent (214/742) of the episodes could not be categorised due to absent images (12%, n = 85), dark/blurry images (8%, n = 58), camera not worn (7%, n = 54) and for mixed reasons (2%, n = 17). Most eating episodes were at home (59%) and indoors (91%). Meals at food retailers were 24.8 minutes longer (95% CI: 13.4 to 36.2) and were higher in energy (mean difference = 1196 kJ 95% CI: 242, 2149) than at home. Most episodes were seated at tables (27%) or sofas (26%), but eating standing (19%) or at desks (18%) were common. Social interaction was evident for 45% of episodes and media screens were viewed during 55% of episodes. Meals at home watching television were 3.1 minutes longer (95% CI: -0.6 to 6.7) and higher in energy intake than when no screen was viewed (543 kJ 95% CI: -32 to 1120). The environmental and social context that surrounds eating and dietary behaviours can be assessed using wearable camera images.

Device-Measured Physical Activity in 3506 Individuals with Knee or Hip Arthroplasty.

PURPOSE: Hip and knee arthroplasty aims to reduce joint pain and increase functional mobility in patients with osteoarthritis; however, the degree to which arthroplasty is associated with higher physical activity is unclear. The current study sought to assess the association of hip and knee arthroplasty with objectively measured physical activity. METHODS: This cross-sectional study analyzed wrist-worn accelerometer data collected in 2013-2016 from UK Biobank participants (aged 43-78 yr). Multivariable linear regression was performed to assess step count, cadence, overall acceleration, and activity behaviors between nonarthritic controls, end-stage arthritic, and postoperative cohorts, controlling for demographic and behavioral confounders. From a cohort of 94,707 participants with valid accelerometer wear time and complete self-reported data, electronic health records were used to identify 3506 participants having undergone primary or revision hip or knee arthroplasty and 68,389 nonarthritic controls. RESULTS: End-stage hip or knee arthritis was associated with taking 1129 fewer steps per day (95% confidence interval (CI), 811-1447; P < 0.001) and having 5.8 fewer minutes per day (95% CI, 3.0-8.7; P < 0.001) of moderate-to-vigorous activity compared with nonarthritic controls. Unilateral primary hip and knee arthroplasties were associated with 877 (95% CI, 284-1471; P = 0.004) and 893 (95% CI, 232-1554; P = 0.008) more steps than end-stage osteoarthritic participants, respectively. Postoperative unilateral hip arthroplasty participants demonstrated levels of moderate-to-vigorous physical activity and daily step count equivalent to nonarthritic controls. No difference in physical activity was observed between any cohorts in terms of overall acceleration, or time spent in daily light activity, sedentary behavior, or sleep. CONCLUSIONS: Hip and knee arthroplasties are associated with higher levels of physical activity compared with participants with end-stage arthritis. Unilateral hip arthroplasty patients, in particular, demonstrate equivalence to nonarthritic peers at more than 1 yr after surgery.

Self-supervised learning for human activity recognition using 700,000 person-days of wearable data.

Accurate physical activity monitoring is essential to understand the impact of physical activity on one's physical health and overall well-being. However, advances in human activity recognition algorithms have been constrained by the limited availability of large labelled datasets. This study aims to leverage recent advances in self-supervised learning to exploit the large-scale UK Biobank accelerometer dataset-a 700,000 person-days unlabelled dataset-in order to build models with vastly improved generalisability and accuracy. Our resulting models consistently outperform strong baselines across eight benchmark datasets, with an F1 relative improvement of 2.5-130.9% (median 24.4%). More importantly, in contrast to previous reports, our results generalise across external datasets, cohorts, living environments, and sensor devices. Our open-sourced pre-trained models will be valuable in domains with limited labelled data or where good sampling coverage (across devices, populations, and activities) is hard to achieve.