Device-measured physical activity and cardiac structure by magnetic resonance.

BACKGROUND AND AIMS: Although extreme cardiac adaptions mirroring phenotypes of cardiomyopathy have been observed in endurance athletes, adaptions to high levels of physical activity within the wider population are under-explored. Therefore, in this study, associations between device-measured physical activity and clinically relevant cardiac magnetic resonance volumetric indices were investigated. METHODS: Individuals without known cardiovascular disease or hypertension were included from the UK Biobank. Cardiac magnetic resonance data were collected between 2015 and 2019, and measures of end-diastolic chamber volume, left ventricular (LV) wall thickness, and LV ejection fraction were extracted. Moderate-to-vigorous-intensity physical activity (MVPA), vigorous-intensity physical activity (VPA), and total physical activity were assessed via wrist-worn accelerometers. RESULTS: A total of 5977 women (median age and MVPA: 62 years and 46.8 min/day, respectively) and 4134 men (64 years and 49.8 min/day, respectively) were included. Each additional 10 min/day of MVPA was associated with a 0.70 [95% confidence interval (CI): 0.62, 0.79] mL/m2 higher indexed LV end-diastolic volume (LVEDVi) in women and a 1.08 (95% CI: 0.95, 1.20) mL/m2 higher LVEDVi in men. However, even within the top decile of MVPA, LVEDVi values remained within the normal ranges [79.1 (95% CI: 78.3, 80.0) mL/m2 in women and 91.4 (95% CI: 90.1, 92.7) mL/m2 in men]. Associations with MVPA were also observed for the right ventricle and the left/right atria, with an inverse association observed for LV ejection fraction. Associations of MVPA with maximum or average LV wall thickness were not clinically meaningful. Results for total physical activity and VPA mirrored those for MVPA. CONCLUSIONS: High levels of device-measured physical activity were associated with cardiac remodelling within normal ranges.

Footwear fit as a causal factor in diabetes-related foot ulceration: A systematic review.

AIMS: Incorrectly fitting footwear (IFF) poses a risk of trauma to at-risk feet with diabetes. The aim of this systematic review was to summarise and assess the evidence that IFF is a statistically significant cause of ulceration. METHODS: We searched PubMed, Scopus, Web of Science and Google Scholar for English-language peer-reviewed studies reporting the number or percentage of people with diabetes-related foot ulceration (DFU) attributed to wearing IFF and included a physical examination of the footwear worn. Two independent reviewers assessed the risk of bias using the Newcastle-Ottawa scale. RESULTS: 4318 results were retrieved excluding duplicates with 45 studies shortlisted. Ten studies met the inclusion criteria with most rated as fair (n = 6) or good (n = 3). There is some evidence that DFU is significantly associated with IFF, but this is limited: only 3 of 10 included studies found a statistically significant percentage of those with DFU were wearing IFF or inappropriate footwear which included fastening, material, type or fit (15.0%-93.3%). Risk of bias in these three studies ranged from 'fair' to 'poor'. IFF definitions were often unreported or heterogeneous. Only one study reported IFF-related ulcer sites: 70% were at plantar hallux/toes and 10% at plantar metatarsal heads. CONCLUSIONS: There is some evidence that IFF is a cause of DFU, but further research is needed, which defines IFF, and methodically records footwear assessment, ulcer location and physical activity. Researchers need to uncover why IFF is worn and if this is due to economic factors, a need for footwear education or other reasons.

Twenty-four-hour physical behaviour profiles across type 2 diabetes mellitus subtypes.

AIM: To investigate how 24-h physical behaviours differ across type 2 diabetes (T2DM) subtypes. MATERIALS AND METHODS: We included participants living with T2DM, enrolled as part of an ongoing observational study. Participants wore an accelerometer for 7 days to quantify physical behaviours across 24 h. We used routinely collected clinical data (age at onset of diabetes, glycated haemoglobin level, homeostatic model assessment index of beta-cell function, homeostatic model assessment index of insulin resistance, body mass index) to replicate four previously identified subtypes (insulin-deficient diabetes [INS-D], insulin-resistant diabetes [INS-R], obesity-related diabetes [OB] and age-related diabetes [AGE]), via k-means clustering. Differences in physical behaviours across the diabetes subtypes were assessed using generalized linear models, with the AGE cluster as the reference. RESULTS: A total of 564 participants were included in this analysis (mean age 63.6 ± 8.4 years, 37.6% female, mean age at diagnosis 53.1 ± 10.0 years). The proportions in each cluster were as follows: INS-D: n = 35, 6.2%; INS-R: n = 88, 15.6%; OB: n = 166, 29.4%; and AGE: n = 275, 48.8%. Compared to the AGE cluster, the OB cluster had a shorter sleep duration (-0.3 h; 95% confidence interval [CI] -0.5, -0.1), lower sleep efficiency (-2%; 95% CI -3, -1), lower total physical activity (-2.9 mg; 95% CI -4.3, -1.6) and less time in moderate-to-vigorous physical activity (-6.6 min; 95% CI -11.4, -1.7), alongside greater sleep variability (17.9 min; 95% CI 8.2, 27.7) and longer sedentary time (31.9 min; 95% CI 10.5, 53.2). Movement intensity during the most active continuous 10 and 30 min of the day was also lower in the OB cluster. CONCLUSIONS: In individuals living with T2DM, the OB subtype had the lowest levels of physical activity and least favourable sleep profiles. Such behaviours may be suitable targets for personalized therapeutic lifestyle interventions.

Greater hepatic lipid saturation is associated with impaired glycaemic regulation in men with metabolic dysfunction-associated steatotic liver disease but is not altered by 6 weeks of exercise training.

AIMS: To examine the impact of impaired glycaemic regulation (IGR) and exercise training on hepatic lipid composition in men with metabolic dysfunction-associated steatotic liver disease (MASLD). MATERIALS AND METHODS: In Part A (cross-sectional design), 40 men with MASLD (liver proton density fat fraction [PDFF] ≥5.56%) were recruited to one of two groups: (1) normal glycaemic regulation (NGR) group (glycated haemoglobin [HbA1c] < 42 mmol∙mol-1 [<6.0%]; n = 14) or (2) IGR group (HbA1c ≥ 42 mmol∙mol-1 [≥6.0%]; n = 26). In Part B (randomized controlled trial design), participants in the IGR group were randomized to one of two 6-week interventions: (1) exercise training (EX; 70%-75% maximum heart rate; four sessions/week; n = 13) or (2) non-exercise control (CON; n = 13). Saturated (SI; primary outcome), unsaturated (UI) and polyunsaturated (PUI) hepatic lipid indices were determined using proton magnetic resonance spectroscopy. Additional secondary outcomes included liver PDFF, HbA1c, fasting plasma glucose (FPG), homeostatic model assessment of insulin resistance (HOMA-IR), peak oxygen uptake (VO2 peak), and plasma cytokeratin-18 (CK18) M65, among others. RESULTS: In Part A, hepatic SI was higher and hepatic UI was lower in the IGR versus the NGR group (p = 0.038), and this hepatic lipid profile was associated with higher HbA1c levels, FPG levels, HOMA-IR and plasma CK18 M65 levels (rs ≥0.320). In Part B, hepatic lipid composition and liver PDFF were unchanged after EX versus CON (p ≥ 0.257), while FPG was reduced and VO2 peak was increased (p ≤ 0.030). ΔVO2 peak was inversely associated with Δhepatic SI (r = -0.433) and positively associated with Δhepatic UI and Δhepatic PUI (r ≥ 0.433). CONCLUSIONS: Impaired glycaemic regulation in MASLD is characterized by greater hepatic lipid saturation; however, this composition is not altered by 6 weeks of moderate-intensity exercise training.

Feasibility of Using a GENEActiv Accelerometer with Triaxial Acceleration and Temperature Sensors to Monitor Adherence to Shoulder Sling Wear Following Surgery.

BACKGROUND: Self-reported adherence to sling wear is unreliable due to recall bias. We aim to assess the feasibility and accuracy of quantifying sling wear and non-wear utilising slings pre-fitted with a GENEActiv accelerometer that houses triaxial acceleration and temperature sensors. METHODS: Ten participants were asked to wear slings for 480 min (8 h) incorporating 180 min of non-wear time in durations varying from 5-120 min. GENEActiv devices were fitted in sutured inner sling pockets and participants logged sling donning and doffing times. An algorithm based on variability in acceleration in three axes and temperature change was developed to identify sling wear and non-wear and compared to participants' logs. RESULTS: There was no significant difference between algorithm detected non-wear duration (mean ± standard deviation = 172.0 ± 6.8 min/participant) and actual non-wear (179.7 ± 1.0 min/participant). Minute-by-minute agreement of sensor-detected wear and non-wear with participant reported wear was 97.3 ± 1.5% (range = 93.9-99.0), with mean sensitivity 94.3 ± 3.5% (range = 86.1-98.3) and specificity 99.1 ± 0.8% (range = 93.7-100). CONCLUSION: An algorithm based on accelerometer-assessed acceleration and temperature can accurately identify shoulder sling wear/non-wear times. This method may have potential for assessing whether sling wear adherence after shoulder surgeries have any bearing on patient functional outcomes.

Capturing How the Accelerometer Measured Physical Activity Profile Differs in People with Diabetic Foot Ulceration.

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, with treatment requiring offloading. This study aimed to capture how the accelerometer-assessed physical activity profile differs in those with DFUs compared to those with diabetes but without ulceration (non-DFU). Participants were requested to wear an accelerometer on their non-dominant wrist for up to 8days. Physical activity outcomes included average acceleration (volume), intensity gradient (intensity distribution), the intensity of the most active sustained (continuous) 5-120 min of activity (MXCONT), and accumulated 5-120 min of activity (MXACC). A total of 595 participants (non-DFU = 561, DFU = 34) were included in the analysis. Average acceleration was lower in DFU participants compared to non-DFU participants (21.9 mg [95%CI:21.2, 22.7] vs. 16.9 mg [15.3, 18.8], p < 0.001). DFU participants also had a lower intensity gradient, indicating proportionally less time spent in higher-intensity activities. The relative difference between DFU and non-DFU participants was greater for sustained activity (MXCONT) than for accumulated (MXACC) activity. In conclusion, physical activity, particularly the intensity of sustained activity, is lower in those with DFUs compared to non-DFUs. This highlights the need for safe, offloaded modes of activity that contribute to an active lifestyle for people with DFUs.

Hotspots: Adherence in home foot temperature monitoring interventions for at-risk feet with diabetes-A narrative review.

BACKGROUND: Home foot temperature monitoring (HFTM) is recommended for those at moderate to high ulcer risk. Where a > 2.2°C difference in temperature between feet (hotspot) is detected, it is suggested that individuals (1) notify a healthcare professional (HCP); (2) reduce daily steps by 50%. We assess adherence to this and HFTM upon detecting a recurrent hotspot. METHODS: PubMed and Google Scholar were searched until 9 June 2023 for English-language peer-reviewed HFTM studies which reported adherence to HFTM, daily step reduction or HCP hotspot notification. The search returned 1030 results excluding duplicates of which 28 were shortlisted and 11 included. RESULTS: Typical adherence among HFTM study participants for >3 days per week was 61%-93% or >80% of study duration was 55.6%-83.1%. Monitoring foot temperatures >50% of the study duration was associated with decreased ulcer risk (Odds Ratio: 0.50, p < 0.001) in one study (n = 173), but no additional risk reduction was found for >80% adherence. Voluntary dropout was 5.2% (Smart mats); 8.1% (sock sensor) and 4.8%-35.8% (infrared thermometers). Only 16.9%-52.5% of participants notified an HCP upon hotspot detection. Objective evidence of adherence to 50% reduction in daily steps upon hotspot detection was limited to one study where the average step reduction was a pedometer-measured 51.2%. CONCLUSIONS: Ulcer risk reduction through HFTM is poorly understood given only half of the participants notify HCPs of recurrent hotspots and the number of reducing daily steps is largely unknown. HFTM adherence and dropout are variable and more research is needed to determine factors affecting adherence and those likely to adhere.

Structured group education programme and accompanying mHealth intervention to promote physical activity in women with a history of gestational diabetes: A randomised controlled trial.

AIMS: Assess effectiveness of a hybrid intervention targeting physical activity in women with prior gestational diabetes. METHODS: Randomised controlled trial with parallel arms. 293 women (35.1 ± 5.1 years; 40% ethnic minority) recruited from two hospitals and randomised to routine care or hybrid lifestyle intervention comprising two group sessions and access to a mobile web app. Primary outcome was a change in objectively measured physical activity at 12 months. Secondary outcomes included self-efficacy for exercise, quality of life and anxiety and depression. Linear regression compared outcome measures between groups. RESULTS: 83% of intervention participants attended at least one group session, of who 66% registered to use the app. There was a non-significant increase in physical activity at 12 months (between-group difference of 0.95 mg [95% CI: -0.46 to 2.37]), equivalent to approximately 500 steps per day. Intervention participants reported higher self-efficacy for exercise (0.54, 95% CI: 0.05 to 1.102; p = 0.029), lower anxiety (-0.91, 95% CI: -1.74 to -0.09; p = 0.031), and higher quality of life (0.05, 95% CI: 0.004 to 0.09; p = 0.032), compared to controls. CONCLUSIONS: The intervention improved confidence in exercise and quality of life. Further research is needed to improve participant engagement with physical activity interventions in multi-ethnic populations with a history of gestational diabetes.

Impaired lower limb muscle mass, quality and function in end stage liver disease: A cross-sectional study.

NEW FINDINGS: What is the central question of this study? To what extent does musculoskeletal impairment occur (i.e., muscle mass, quality and function) in patients with end stage liver disease (ESLD) by comparison to a healthy age/sex-matched control group? What is the main finding and its importance? Muscle mass, quality and function are impaired in patients with ESLD (compared to age/sex matched controls). Importantly, greater impairments were seen in lower limb compared to arm and trunk muscle groups. These findings may suggest that there should be greater consideration of muscle health in functionally relevant lower limb muscle groups. ABSTRACT: Sarcopenia is associated with reduced quality of life and increased mortality in patients with end stage liver disease (ESLD). Historically, sarcopenia identification in ESLD utilised L3 skeletal muscle index (SMI). There are few data on muscle quality and function within lower limb muscle groups with high functional relevance. The aim of this prospective case-control study was to evaluate the quadriceps muscle in patients with ESLD. Muscle mass and quality were evaluated using MRI (quadriceps anatomical cross sectional area (ACSA), quadriceps volume index, L3 SMI, quadriceps intermuscular adipose tissue (IMAT)), mid-arm muscle circumference (MAMC) and ultrasonography (vastus lateralis (VL) thickness and quadriceps ACSA). Muscle strength/function was assessed by handgrip strength, peak quadriceps isokinetic torque and chair rise time. Thirty-nine patients with ESLD (55 years, 61% male, 48% alcoholic related liver disease (ArLD), 71% Child-Pugh B/C) and 18 age/sex-matched healthy control participants (HC) were studied. Quadriceps mass was significantly reduced in ESLD versus HC (-17%), but L3 SMI and MAMC were unchanged. Quadriceps IMAT percentage was increased in ESLD (+103%). Handgrip strength (-15%), peak isokinetic torque (-29%), and chair rise time (+56%) were impaired in ESLD. Ultrasound measures of VL thickness (r = 0.56, r = 0.57, r = 0.42) and quadriceps ACSA (r = 0.98, r = 0.86, r = 0.67) correlated to MRI quadriceps ACSA, quadriceps volume and L3 SMI, respectively. Quadriceps muscle mass, quality, and function were impaired in patients with ESLD, whereas conventional assessments of muscle (L3 SMI and MAMC) highlighted no differences between ESLD and HC. Full evaluation of lower limb muscle health is essential in ESLD in order to accurately assess sarcopenia and target future interventions.

Validation of an automated sleep detection algorithm using data from multiple accelerometer brands.

To evaluate the criterion validity of an automated sleep detection algorithm applied to data from three research-grade accelerometers worn on each wrist with concurrent laboratory-based polysomnography (PSG). A total of 30 healthy volunteers (mean [SD] age 31.5 [7.2] years, body mass index 25.5 [3.7] kg/m2 ) wore an Axivity, GENEActiv and ActiGraph accelerometer on each wrist during a 1-night PSG assessment. Sleep estimates (sleep period time window [SPT-window], sleep duration, sleep onset and waking time, sleep efficiency, and wake after sleep onset [WASO]) were generated using the automated sleep detection algorithm within the open-source GGIR package. Agreement of sleep estimates from accelerometer data with PSG was determined using pairwise 95% equivalence tests (±10% equivalence zone), intraclass correlation coefficients (ICCs) with 95% confidence intervals and limits of agreement (LoA). Accelerometer-derived sleep estimates except for WASO were within the 10% equivalence zone of the PSG. Reliability between data from the accelerometers worn on either wrist and PSG was moderate for SPT-window duration (ICCs ≥ 0.65), sleep duration (ICCs ≥ 0.54), and sleep onset (ICCs ≥ 0.61), mostly good for waking time (ICCs ≥ 0.80), but poor for sleep efficiency (ICCs ≥ 0.08) and WASO (ICCs ≥ 0.08). The mean bias between all accelerometer-derived sleep estimates worn on either wrist and PSG were low; however, wide 95% LoA were observed for all sleep estimates, apart from waking time. The automated sleep detection algorithm applied to data from Axivity, GENEActiv and ActiGraph accelerometers, worn on either wrist, provides comparable measures to PSG for SPT-window and sleep duration, sleep onset and waking time, but a poor measure of wake during the sleep period.

Reference values for wrist-worn accelerometer physical activity metrics in England children and adolescents.

BACKGROUND: Over the last decade use of raw acceleration metrics to assess physical activity has increased. Metrics such as Euclidean Norm Minus One (ENMO), and Mean Amplitude Deviation (MAD) can be used to generate metrics which describe physical activity volume (average acceleration), intensity distribution (intensity gradient), and intensity of the most active periods (MX metrics) of the day. Presently, relatively little comparative data for these metrics exists in youth. To address this need, this study presents age- and sex-specific reference percentile values in England youth and compares physical activity volume and intensity profiles by age and sex. METHODS: Wrist-worn accelerometer data from 10 studies involving youth aged 5 to 15 y were pooled. Weekday and weekend waking hours were first calculated for youth in school Years (Y) 1&2, Y4&5, Y6&7, and Y8&9 to determine waking hours durations by age-groups and day types. A valid waking hours day was defined as accelerometer wear for ≥ 600 min·d-1 and participants with ≥ 3 valid weekdays and ≥ 1 valid weekend day were included. Mean ENMO- and MAD-generated average acceleration, intensity gradient, and MX metrics were calculated and summarised as weighted week averages. Sex-specific smoothed percentile curves were generated for each metric using Generalized Additive Models for Location Scale and Shape. Linear mixed models examined age and sex differences. RESULTS: The analytical sample included 1250 participants. Physical activity peaked between ages 6.5-10.5 y, depending on metric. For all metrics the highest activity levels occurred in less active participants (3rd-50th percentile) and girls, 0.5 to 1.5 y earlier than more active peers, and boys, respectively. Irrespective of metric, boys were more active than girls (p < .001) and physical activity was lowest in the Y8&9 group, particularly when compared to the Y1&2 group (p < .001). CONCLUSIONS: Percentile reference values for average acceleration, intensity gradient, and MX metrics have utility in describing age- and sex-specific values for physical activity volume and intensity in youth. There is a need to generate nationally-representative wrist-acceleration population-referenced norms for these metrics to further facilitate health-related physical activity research and promotion.

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).

Life expectancy following a cardiovascular event in individuals with and without type 2 diabetes: A UK multi-ethnic population-based observational study.

BACKGROUND AND AIMS: We aimed to evaluate the life expectancy following the first cardiovascular disease (CVD) event by type 2 diabetes (T2D) status and ethnicity. METHODS AND RESULTS: We used the Clinical Practice Research Datalink database in England (UK), linked to the Hospital Episode Statistics information, to identify individuals with and without T2D who survived a first CVD event between 1st Jan 2007 and 31st Dec 2017; subsequent death events were extracted from the Office for National Statistics database. Ethnicity was categorised as White, South Asian (SA), Black, or other. Flexible parametric survival models were used to estimate survival and predict life expectancy. 59,939 individuals with first CVD event were included: 7596 (12.7%) with T2D (60.9% men; mean age at event: 69.7 years [63.2 years in SA, 65.9 in Black, 70.2 in White]) and 52,343 without T2D (56.7% men; 65.9 years [54.7 in Black, 58.2 in SA, 66.3 in White]). Accounting for potential confounders (sex, deprivation, lipid-lowering medication, current smoking, and pre-existing hypertension), comparing individuals with vs without T2D the mortality rate was 53% higher in White (hazard ratio [HR]: 1.53 [95% CI: 1.44, 1.62]), corresponding to a potential loss of 3.87 (3.30, 4.44) life years at the age of 50 years in individuals with T2D. No evidence of a difference in life expectancy was observed in individuals of SA (HR: 0.82 [0.52, 1.29]; -1.36 [-4.58, 1.86] life years), Black (HR: 1.26 [0.59, 2.70]; 1.21 [-2.99, 5.41] life years); and other (HR: 1.64 [0.80, 3.39]; 3.89 [-2.28, 9.99] life years) ethnic group. CONCLUSION: Following a CVD event, T2D is associated with a different prognosis and life years lost among ethnic groups.

Associations between Hospitalization and Device-Assessed Physical Activity in a Representative Sample of Older Adults.

BACKGROUND: Evidence investigating associations between hospitalization and physical activity is scarce and limited to specific populations of older adults. OBJECTIVE: The current study aimed to describe the impact of past hospitalization on current physical activity levels of a large representative sample of European older adults with accelerometry data. METHODS: A representative sample of 856 European older adults aged 50 years and over was included in this study. Hospital admission and utilization (i.e., accumulated times and length of stay in hospital) in the last 12 months were self-reported retrospectively. Physical activity volume (mg) and distribution of intensity (intensity gradient) were assessed with thigh-worn accelerometers. RESULTS: Multivariate linear regressions indicated that hospital admission (15% of the sample) was associated with reduced physical activity volume (-4.29 mg; 95% confidence interval (95% CI), -9.07 to 0.47) of participants. Each additional hospital admission was associated with lower volume (-2.29 mg; 95% CI, -4.65 to 0.06) and poorer distribution of intensity (-0.07; 95% CI, -0.11 to -0.04). Total length of stay was not associated with physical activity. CONCLUSIONS: This study suggests that hospital admission and the number of times admitted, but not accumulated length of stay, may curb physical activity levels of older adults. Public health strategies to promote successful aging should target post-hospitalization physical activity.

Absolute intensity thresholds for tri-axial wrist and waist accelerometer-measured movement behaviors in adults.

AIM: This study was aimed to: (1) compare raw triaxial acceleration data from GENEActiv (GA) and ActiGraph GT3X+ (AG) placed on the non-dominant wrist; (2) compare AG placed on the non-dominant and dominant wrist, and waist; (3) derive brand- and placement-specific absolute intensity thresholds for inactive and sedentary time, and physical activity intensity in adults. METHODS: Eighty-six adults (44 men; 34.6 ± 10.8 years) performed nine activities while simultaneously wearing GA and AG on wrist and waist. Acceleration (in gravitational equivalent units; mg) was compared with oxygen uptake (measured with indirect calorimetry). RESULTS: Increases in acceleration mirrored increases in intensity of activities, regardless of device brand and placement. Differences in acceleration between GA and AG worn at the non-dominant wrist were small but tended to be high at lower intensity activities. Thresholds for differentiating inactivity (<1.5 MET) from activity (≥1.5 MET) ranged from 25 mg (AG non-dominant wrist; sensitivity 93%, specificity 95%) to 40 mg (AG waist; sensitivity 78%, specificity 100%). For moderate intensity (≥3 METs), thresholds ranged from 65 mg (AG waist; sensitivity 96%, specificity 94%) to 92 mg (GA non-dominant; sensitivity 93%, specificity 98%); vigorous intensity (≥6 METs) thresholds ranged from 190 mg (AG waist; sensitivity 82%, specificity 92%) to 283 mg (GA non-dominant; sensitivity 93%, specificity 98%). CONCLUSION: Raw triaxial acceleration outputs from two widely used accelerometer brands may have limited comparability in low intensity activities. Thresholds derived in this study can be utilized in adults to reasonably classify movement behaviors into categories of intensity.

Physical activity volume and intensity distribution in relation to bone, lean and fat mass in children.

Considering physical activity (PA) volume and intensity may provide novel insights into the relationships of PA with bone, lean, and fat mass. This study aimed to assess the associations of PA volume, PA intensity distribution, including moderate-to-vigorous PA (MVPA) with total-body-less-head bone mineral content (BMC), lean, and fat mass in children. A population sample of 290 Finnish children (158 females) aged 9-11 years from the Physical Activity and Nutrition in Children (PANIC) Study was studied. PA, including MVPA, was assessed with a combined heart rate and movement sensor, and the uniaxial acceleration was used to calculate average-acceleration (a proxy metric for PA volume) and intensity-gradient (reflective of PA intensity distribution). Linear regression analyzed the associations of PA volume, PA intensity and MVPA with BMC, lean mass, and fat mass assessed by dual-energy X-ray absorptiometry. PA volume was positively associated with BMC in females (unstandardised regression coefficient [ß] = 0.26) and males (ß = 0.47), and positively associated with lean (ß = 7.33) and negatively associated with fat mass in males (ß = -20.62). PA intensity was negatively associated with BMC in males (ß = -0.13). MVPA was positively associated with lean mass in females and males (ß = 0.007 to 0.012), and negatively associated with fat mass in females and males (ß = -0.030 to -0.029). PA volume may be important for improving BMC in females and males, and increasing lean and reducing fat mass in males, whereas MVPA may be important for favorable lean and fat outcomes in both sexes.

Can quantifying the relative intensity of a person's free-living physical activity predict how they respond to a physical activity intervention? Findings from the PACES RCT.

OBJECTIVES: To determine whether quantifying both the absolute and relative intensity of accelerometer-assessed physical activity (PA) can inform PA interventions. We hypothesised that individuals whose free-living PA is at a low relative intensity are more likely to increase PA in response to an intervention, as they have spare physical capacity. METHOD: We conducted a secondary data analysis of a 12-month randomised controlled trial, Physical Activity after Cardiac EventS, which was designed to increase PA but showed no improvement. Participants (N=239, 86% male; age 66.4 (9.7); control N=126, intervention N=113) wore accelerometers for 7 days and performed the incremental shuttle walk test (ISWT) at baseline and 12 months. PA intensity was expressed in absolute terms (intensity gradient) and relative to acceleration at maximal physical capacity (predicted from an individual's maximal ISWT walking speed). PA outcomes were volume and absolute intensity gradient. RESULTS: At baseline, ISWT performance was positively correlated with PA volume (r=0.50, p<0.001) and absolute intensity (r=0.50, p<0.001), but negatively correlated with relative intensity (r=-0.13, p=0.025). Relative intensity of PA at baseline moderated the change in absolute intensity (p=0.017), but not volume, of PA postintervention. Low relative intensity at baseline was associated with increased absolute intensity gradient (+0.5 SD), while high relative intensity at baseline was associated with decreased absolute intensity gradient (-0.5 SD). CONCLUSION: Those with low relative intensity of PA were more likely to increase their absolute PA intensity gradient in response to an intervention. Quantifying absolute and relative PA intensity of PA could improve enables personalisation of interventions.

Physical activity volume, intensity, and incident cardiovascular disease.

AIMS: The interplay between physical activity (PA) volume and intensity is poorly understood in relation to cardiovascular disease (CVD) risk. This study aimed to investigate the role of PA intensity, over and above volume, in relation to incident CVD. METHODS AND RESULTS: Data were from 88 412 UK Biobank middle-aged adults (58% women) without prevalent CVD who wore accelerometers on their dominant wrist for 7 days, from which we estimated total PA energy expenditure (PAEE) using population-specific validation. Cox proportional hazards regressions modelled associations between PAEE (kJ/kg/day) and PA intensity (%MVPA; the fraction of PAEE accumulated from moderate-to-vigorous-intensity PA) with incident CVD (ischaemic heart disease or cerebrovascular disease), adjusted for potential confounders. There were 4068 CVD events during 584 568 person-years of follow-up (median 6.8 years). Higher PAEE and higher %MVPA (adjusted for PAEE) were associated with lower rates of incident CVD. In interaction analyses, CVD rates were 14% (95% confidence interval: 5-23%) lower when MVPA accounted for 20% rather than 10% of 15 kJ/kg/d PAEE; equivalent to converting a 14 min stroll into a brisk 7 min walk. CVD rates did not differ significantly between values of PAEE when the %MVPA was fixed at 10%. However, the lowest CVD rates were observed for combinations of both higher PAEE and %MVPA. CONCLUSION: Reductions in CVD risk may be achievable through higher PA volume and intensity, with the role of moderately intense PA appearing particularly important. This supports multiple approaches or strategies to PA participation, some of which may be more practical or appealing to different individuals.

Self-reported walking pace: A simple screening tool with lowest risk of all-cause mortality in those that 'walk the talk'.

To determine whether the association between self-reported walking pace and all-cause mortality (ACM) persists across categories of accelerometer-assessed physical activity status. Data from 93,709 UK Biobank participants were included. Physical activity was assessed using wrist-worn accelerometers for 7-days. Participants accumulating <150 min/week moderate-to-vigorous- activity were classed as "inactive", ≥150 min/week moderate (≥3 METs) activity as "somewhat active" excluding those with ≥150 min/week upper-moderate-to-vigorous activity (≥4.3 METs), who were classed as "high-active". Over a 6.3 y (median) follow-up, 2,173 deaths occurred. More than half of slow walkers were "inactive", but only 26% of steady and 12% of brisk walkers. Associations between walking pace and ACM were consistent with those for activity. "High active" brisk walkers had the lowest risk of ACM (Hazard Ratio (HR) 0.22; 95% CI: 0.17,0.28), relative to "inactive" slow walkers. Within those classed as "inactive", steady (HR 0.54; 0.46,0.64) and brisk walkers (HR 0.42; 0.34,0.52) had lower risk than slow walkers. In conclusion, self-reported walking pace was associated with accelerometer-assessed physical activity with both exposures having similar associations with ACM. "inactive", steady, and brisk walkers had lower ACM risk than slow walkers. The pattern was similar for "High active" participants. Overall, "High active" brisk walkers had lowest risk.

Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health.

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.