Raw Accelerometer Data Analysis with GGIR R-package: Does Accelerometer Brand Matter?

Gender Gap for Accelerometry-Based Physical Activity Across Different Age Groups in 5 Brazilian Cohort Studies

OBJECTIVES

This study aims to evaluate the gender inequalities in accelerometer-based physical activity (PA) across different age groups using data from 5 Pelotas (Brazil) cohorts.

METHODS

The data come from 4 birth cohort studies, covering all live births in the urban area of Pelotas for each respective year (1982, 1993, 2004, and 2015), and the Como vai? cohort study focusing on 60 years and above. Raw accelerometry data were collected on the nondominant wrist using GENEActive/ActiGraph devices and processed with the GGIR package. Overall PA was calculated at ages 1, 2, 4, 6, 11, 15, 18, 23, 30, and 60+ years, while moderate to vigorous PA was calculated from 6 years onward. Absolute (difference) and relative (ratio) gender inequalities were calculated and intersectionality between gender and wealth was also evaluated.

RESULTS

The sample sizes per cohort ranged from 965 to 3462 participants. The mean absolute gender gap was 19.3 minutes (95% confidence interval, 12.7-25.9), with the widest gap at 18 years (32.9 min; 95% confidence interval, 30.1-35.7) for moderate to vigorous PA. The highest relative inequality was found in older adults (ratio 2.0; 95% confidence interval, 1.92-2.08). Our intersectionality results showed that the poorest men being the most active group, accumulating around 60 minutes more moderate to vigorous PA per day compared with the wealthiest women at age 18.

CONCLUSIONS

Men were more physically active than women in all ages evaluated. PA gender inequalities start at an early age and intensify in transition periods of life. Relative inequalities were marked among older adults.

Rationale and design of Healthy Kids Beyond the Bell: a 2x2 full factorial study evaluating the impact of summer and after-school programming on children's body mass index and health behaviors

BACKGROUND

The Structured Days Hypothesis posits that structure protects children against obesogenic behaviors (e.g., physical inactivity, unhealthy dietary intake) and, ultimately, prevents the occurrence of excessive weight gain. The hours following school (i.e., 3-6 pm school days) and summer vacation are two "windows of vulnerability" when children may experience less structure. Programs that provide a healthy structured environment and may prevent BMI gain exist for both time periods (i.e., after-school programs and summer day camps). Unfortunately, these programs are cost prohibitive for children from low-income families to attend. This study will test the impact of providing vouchers to access existing, community-operated after-school and summer programs on BMI z-score, body composition, and obesogenic behaviors (i.e., physical activity, screen use, diet, and sleep) of children (5-12 years) from schools that primarily serve families with low income.

METHODS

The study will employ a 2x2 factorial design. Participants (N = 480) attending 4 elementary schools in one school district will be randomly assigned to a no treatment control, after-school program voucher only, summer day camp voucher only, or after-school and summer day camp vouchers. Vouchers will cover the full cost of attending a pre-existing community-based after-school or summer camp program. The primary outcome (BMI z-score) will be measured at baseline (before end of school year, ~ May), 3-month follow-up (after summer, ~ August), and 12-month follow-up (end the following school year, ~ May). Secondary outcomes include body composition (i.e., whole-body fat mass, fat free mass, and percent body fat) and obesogenic behaviors (i.e., physical activity, sedentary time, sleep, screen-time, and diet). The study will also employ a rigorous process evaluation which will consider after-school and summer camp program attendance and content. Analyses will examine differences between the four groups in BMI z-score, body composition, and obesogenic behaviors. Incremental cost effectiveness ratios will determine the cost effectiveness of the intervention.

DISCUSSION

The current study will provide critical information for researchers, practitioners, and policy makers seeking to combat the childhood obesity epidemic in children from families with low-income during the school year and summer.

TRIAL REGISTRATION

NCT05880901 . Registered 27 May 2023.

Differences in elementary-age children's accelerometer - measured physical activity between school and summer: three-year findings from the What's UP (Undermining Prevention) with summer observational cohort study

BACKGROUND

Among elementary-aged children (5-12yrs), summer vacation is associated with accelerated gains in Body Mass Index (BMI). A key behavioral driver of BMI gain is a lack of physical activity (PA). Previous studies indicate PA decreases during summer, compared to the school year but whether this difference is consistent among boys and girls, across age, and by income status remains unclear. This study examined differences in school and summer movement behaviors in a diverse cohort of children across three years.

METHODS

Children (N = 1,203, age range 5-14 years, 48% girls) wore wrist-placed accelerometers for a 14-day wear-period during school (April/May) and summer (July) in 2021 to 2023, for a total of 6 timepoints. Mixed-effects models examined changes in school vs. summer movement behaviors (moderate-to-vigorous physical activity [MVPA], sedentary) for boys and girls, separately, and by age and household income groups (low, middle, and upper based on income-to-poverty ratio).

RESULTS

Children provided a total of 35,435 valid days of accelerometry. Overall, boys (+ 9.1 min/day, 95CI 8.1 to 10.2) and girls (+ 6.2 min/day, 95CI 5.4 to 7.0) accumulated more MVPA during school compared to summer. Boys accumulated less time sedentary (-9.9 min/day, 95CI -13.0 to -6.9) during school, while there was no difference in sedentary time (-2.7 min/day, 95CI -5.7 to 0.4) for girls. Different patterns emerged across ages and income groups. Accumulation of MVPA was consistently greater during school compared to summer across ages and income groups. Generally, the difference between school and summer widened with increasing age, except for girls from middle-income households. Accumulation of sedentary time was higher during school for younger children (5-9yrs), whereas for older children (10-14yrs), sedentary time was greater during summer for the middle- and upper-income groups. For boys from low-income households and girls from middle-income households, sedentary time was consistently greater during summer compared to school across ages.

CONCLUSIONS

Children are less active and more sedentary during summer compared to school, which may contribute to accelerated BMI gain. However, this differs by biological sex, age, and income. These findings highlight the complex factors influencing movement behaviors between school and summer.

Improving the identification of bone-specific physical activity using wrist-worn accelerometry: A cross-sectional study in 11-12-year-old Australian children

Physical activity (PA) during childhood and adolescence is important for the accrual of maximal peak bone mass. The precise dose that benefits bone remains unclear as methods commonly used to analyze PA data are unsuitable for measuring bone-relevant PA. Using improved accelerometry methods, this study identified the amount and intensity of PA most strongly associated with bone outcomes in 11-12-year-olds. Participants (n = 770; 382 boys) underwent tibial peripheral quantitative computed tomography to assess trabecular and cortical density, endosteal and periosteal circumference and polar stress-strain index. Seven-day wrist-worn raw acceleration data averaged over 1-s epochs was used to estimate time accumulated above incremental PA intensities (50 milli-gravitational unit (mg) increments from 200 to 3000 mg). Associations between time spent above each 50 mg increment and bone outcomes were assessed using multiple linear regression, adjusted for age, sex, height, weight, maturity, socioeconomic position, muscle cross-sectional area and PA below the intensity of interest. There was a gradual increase in mean R2 change across all bone-related outcomes as the intensity increased in 50 mg increments from >200 to >700 mg. All outcomes became significant at >700 mg (R2 change = 0.6%-1.3% and p = 0.001-0.02). Any further increases in intensity led to a reduction in mean R2 change and associations became non-significant for all outcomes >1500 mg. Using more appropriate accelerometry methods (1-s epochs; no a priori application of traditional cut-points) enabled us to identify that ∼10 min/day of PA >700 mg (equivalent to running ∼10 km/h) was positively associated with pQCT-derived measures of bone density, geometry and strength in 11-12-year-olds.

Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO)

Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.

Accelerometer-derived physical activity and the risk of death, heart failure, and stroke in patients with atrial fibrillation: a prospective study from UK Biobank

OBJECTIVE

Data on cardiovascular outcomes according to objectively measured physical activity (PA) in patients with atrial fibrillation (AF) are scarce. This study explored the associations between PA derived from wrist-worn accelerometers and the risk of death, incident heart failure (HF), and incident stroke in patients with AF.

METHODS

From 37 990 patients with AF in UK Biobank, 2324 patients with accelerometer data were included. Weekly moderate-to-vigorous PA (MVPA) duration was computed from accelerometer data. The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular mortality, incident HF, and incident stroke. Restricted cubic splines estimated the dose-response associations between MVPA duration and the outcomes. The adjusted HRs (aHRs) of the outcomes according to adherence to PA standard guidelines (performing MVPA≥150 min/week) were also evaluated.

RESULTS

The mean age was 66.9±6.2 years and 64.9% were male. During a median follow-up of 6.7 years, there were 181 all-cause deaths, 62 cardiovascular deaths, 225 cases of incident HF, and 91 cases of incident stroke; the overall incidence rate per 1000 patient-years was 11.76, 4.03, 15.16 and 5.99, respectively. There was a linear inverse dose-response relationship between MVPA (≥108 min/week) and all-cause mortality. Performing MVPA for 105-590 min/week was associated with a lower risk of HF than those with no measurable MVPA. The risk of stroke and cardiovascular mortality was not associated with MVPA. Performing guideline-adherent MVPA was related to a 30% lower risk of all-cause mortality (aHR: 0.70 (0.50-0.98), p=0.04) and 33% lower risk of HF (aHR 0.67 (0.49-0.93), p=0.02).

CONCLUSION

In patients with AF, accelerometer-derived PA data supports lower risks of all-cause mortality and HF according to a greater level of MVPA and adherence to PA guidelines. Regular MVPA should be encouraged in patients with AF as a part of integrated management.

Accelerometry-assessed daily physical activity and compliance with recommendations in Spanish children: importance of physical education classes and vigorous intensity

Background

Physical activity (PA) is associated with numerous health benefits. Vigorous PA (VPA) may have a greater impact on public health than lower-intensity PA. The incorporation of a specific recommendation on VPA could complement and improve existing recommendations for average daily moderate-vigorous PA (MVPA). Physical education classes could have a positive impact on children's adherence to average daily physical activity recommendations. The aim was to investigate the association between MVPA and VPA in children, as well as adherence to recommendations, and obesity and the presence of physical education classes.

Methods

A cross-sectional study of physical activity was conducted in a sample of 8 and 9-year-old children in Andalusia (Spain). GENEActiv accelerometers were used, placed on the non-dominant wrist for at least eight consecutive days (24-h protocol). School days with and without physical education class, and weekend days were defined. ROC curves were used to calculate the threshold associated with obesity for average daily MVPA and VPA for recommendations.

Results

A total of 360 schoolchildren were included in the analyses (184 girls). An average of 7.7 (SD 1.4) valid days per participant were evaluated, with 19.9 (SD 10.5) and 11.4 (SD 5.1) minutes of VPA performed by boys and girls respectively. 25.8% of the participants were classified with central obesity. The optimal threshold determined with ROC analysis was 12.5 and 9.5 minutes of average daily VPA for boys and girls, respectively (RecVPA), and 75 minutes of average daily MVPA for both sexes (RecMVPA). The RecVPA showed stronger association with obesity. On school days with physical education class, compared to days without this class, children showed increased VPA and MVPA engagement and better compliance with recommendations, with smaller differences in adherence according to sex or obesity.

Conclusions

On days with physical education class, more physical activity was accumulated at all intensities and greater adherence to the recommendations than on days without this class. VPA had a stronger correlation with the absence of obesity than lower-intensity activity. It was also observed that boys were physically more active and had higher adherence to the recommendations than girls.

Adherence to the WHO recommendation of three weekly days of vigorous intensity activities in children: an accelerometry study of vigorous physical activity bouts

Background

The World Health Organization (WHO) recommends that children and adolescents incorporate vigorous intensity activities (VIAs) at least three days a week. This recommendation has not been sufficiently studied using objective methods, such as accelerometry. Physical education classes and extracurricular sports activities are optimal opportunities for compliance with this recommendation.

Objective

To identify VIAs through bouts of vigorous physical activity (VPA-Bouts) evaluated with accelerometry and, with this, to know the compliance with the recommendation on VIAs.

Methods

A cross-sectional study of the habitual physical activity of 353 children (8-9 years old) was carried out using accelerometry and participation in organized extracurricular sports activities was asked through a questionnaire. School days with and without physical education class, weekends, and the average weekly day were identified, as well as school time and out-of-school time. A VPA-Bout was defined as an interval of at least 60 minutes with a proportion of VPA of at least 16.7% in boys and 12.5% in girls (10.0 and 7.5 minutes/hour of VPA, respectively).

Results

The average daily time in organized extracurricular sports activities declared by questionnaire and the average daily duration of the VPA-Bouts evaluated with accelerometers in the extracurricular period was 21.3 (SD 19.8) and 23.9 (SD 31.2) minutes, respectively, in boys, whereas, in girls it was 20.2 (SD 17.4) and 11.0 (SD 16.9) minutes, respectively. In school time including a physical education class, there was a higher proportion of VPA-Bouts than without these classes (with: 28.6%, without: 2.1%, p < 0.001). Children who reported at least three weekly hours of organized extracurricular sports activities accumulated a higher proportion of school afternoons with VPA-Bouts than those with fewer weekly hours of this type of activities (≥3 hours/week: 27.5%, <3 hours/week: 9.3%, p < 0.001). On the weekend, boys who reported at least three weekly hours of organized extracurricular sports activities performed more VPA-Bouts than those participating in less weekly hours, while in girls no significant differences were observed (weekend; boys, ≥3 hours/week: 26.0%, <3 hours/week: 9.0%, p < 0.001; girls: 8.3%, 8.0%, p = 0.917). Compliance with the recommendation to incorporate VIAs at least three days a week was 23.8%. Children who reported at least three weekly hours of extracurricular sports activities achieved higher compliance than those who reported fewer extracurricular activities (≥3 hours/week: 35.1%, <3 hours/week: 12.7%, p < 0.001). Additionally, boys showed higher compliance rates than girls (boys: 32.9%, girls: 15.3%, p < 0.001).

Conclusion

One in every four children met the WHO recommendation to incorporate VIAs at least three days a week, as evaluated by accelerometry. Physical education classes and extracurricular organized sports activities contributed to compliance with this recommendation.

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.

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.

Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community

Comparisons of actigraphy findings between studies are challenging given differences between brand-specific algorithms. This issue may be minimized by using open-source algorithms. However, the accuracy of actigraphy-derived sleep parameters processed in open-source software needs to be assessed against polysomnography (PSG). Middle-aged adults from the Raine Study (n = 835; F 58%; Age 56.7 ± 5.6 years) completed one night of in-laboratory PSG and concurrent actigraphy (GT3X+ ActiGraph). Actigraphic measures of total sleep time (TST) were analyzed and processed using the open-source R-package GENEActiv and GENEA data in R (GGIR) with and without a sleep diary and additionally processed using proprietary software, ActiLife, for comparison. Bias and agreement (intraclass correlation coefficient) between actigraphy and PSG were examined. Common PSG and sleep health variables associated with the discrepancy between actigraphy, and PSG TST were examined using linear regression. Actigraphy, assessed in GGIR, with and without a sleep diary overestimated PSG TST by (mean ± SD) 31.0 ± 50.0 and 26.4 ± 69.0 minutes, respectively. This overestimation was greater (46.8 ± 50.4 minutes) when actigraphy was analyzed in ActiLife. Agreement between actigraphy and PSG TST was poor (ICC = 0.27-0.44) across all three methods of actigraphy analysis. Longer sleep onset latency and longer wakefulness after sleep onset were associated with overestimation of PSG TST. Open-source processing of actigraphy in a middle-aged community population, agreed poorly with PSG and, on average, overestimated TST. TST overestimation increased with increasing wakefulness overnight. Processing of actigraphy without a diary in GGIR was comparable to when a sleep diary was used and comparable to actigraphy processed with proprietary algorithms in ActiLife.

Comparison of different software for processing physical activity measurements with accelerometry

Several raw-data processing software for accelerometer-measured physical activity (PA) exist, but whether results agree has not been assessed. We examined the agreement between three different software for raw accelerometer data, and associated their results with cardiovascular risk. A cross-sectional analysis conducted between 2014 and 2017 in 2693 adults (53.4% female, 45-86 years) living in Lausanne, Switzerland was used. Participants wore the wrist-worn GENEActive accelerometer for 14 days. Data was processed with the GENEActiv manufacturer software, the Pampro package in Python and the GGIR package in R. For the latter, two sets of thresholds "White" and "MRC" defining levels of PA and two versions (1.5-9 and 1.11-1) for the "MRC" threshold were used. Cardiovascular risk was assessed using the SCORE risk score. Time spent (mins/day) in stationary, light, moderate and vigorous PA ranged from 633 (GGIR-MRC) to 1147 (Pampro); 93 (GGIR-White) to 196 (GGIR-MRC); 19 (GGIR-White) to 161 (GENEActiv) and 1 (GENEActiv) to 26 (Pampro), respectively. Spearman correlations between results ranged between 0.317 and 0.995, while concordance coefficients ranged between 0.035 and 0.968. With some exceptions, the line of perfect agreement was not in the 95% confidence interval of the Bland-Altman plots. Compliance to PA guidelines varied considerably: 99.8%, 98.7%, 76.3%, 72.6% and 50.2% for Pampro, GENEActiv, GGIR-MRC v.1.11-1, GGIR-MRC v.1.4-9 and GGIR-White, respectively. Cardiovascular risk decreased with increasing time spent in PA across most software packages. We found large differences in PA estimation between software and thresholds used, which makes comparability between studies challenging.

Agreement and equivalence of estimated physical activity behaviours, using ENMO- and counts-based processing methods, for wrist-worn accelerometers in adolescents

The present study examined the agreement and equivalence between two physical activity processing methods. Data were obtained from 161 Hong-Kong adolescents (74 girls, age: 12.6 ± 1.7y). Participants wore an Actigraph GT3XBT on their non-dominant wrist for 7d. Time spent sedentary, and in light-(LPA), moderate-(MPA), vigorous-(VPA), and moderate-to-vigorous physical activity (MVPA) were calculated using different processing methods (proprietary counts and Euclidean Norm Minus One (ENMO)). Intraclass correlation coefficients (ICC) were used to examine absolute agreement (ICC2) and consistency (ICC3), and equivalence was assessed using pairwise equivalence tests. Using ENMO, sedentary time and VPA were higher, whereas all other behaviours were lower (compared to counts processing). Agreement ranged from poor (ICC2:0.42(Sedentary)) to moderate (ICC2:0.86(LPA)) and consistency ranged from moderate (ICC3:0.71(sedentary)) to good (ICC3:0.91(LPA)). Methods were not considered equivalent (all p > 0.05). Due to differences in the wear-time validation of processing methods, a sensitivity analyses (sub-sample with the same valid wear time for both methods (n = 56)), resulted in minimal change. Lack of agreement and equivalence between ENMO and counts processing methods suggests that the processing method significantly affects youth physical activity estimates.

Device-measured physical activity and sedentary time in a national sample of Luxembourg residents: the ORISCAV-LUX 2 study

BACKGROUND

Existing information about population physical activity (PA) levels and sedentary time in Luxembourg are based on self-reported data.

METHODS

This observational study included Luxembourg residents aged 18-79y who each provided ≥4 valid days of triaxial accelerometry in 2016-18 (n=1122). Compliance with the current international PA guideline (≥150 min moderate-to-vigorous PA (MVPA) per week, irrespective of bout length) was quantified and variability in average 24h acceleration (indicative of PA volume), awake-time PA levels, sedentary time and accumulation pattern were analysed by linear regression. Data were weighted to be nationally representative.

RESULTS

Participants spent 51% of daily time sedentary (mean (95% confidence interval (CI)): 12.1 (12.0 to 12.2) h/day), 11% in light PA (2.7 (2.6 to 2.8) h/day), 6% in MVPA (1.5 (1.4 to 1.5) h/day), and remaining time asleep (7.7 (7.6 to 7.7) h/day). Adherence to the PA guideline was high (98.1%). Average 24h acceleration and light PA were higher in women than men, but men achieved higher average accelerations across the most active periods of the day. Women performed less sedentary time and shorter sedentary bouts. Older participants (aged ≥55y) registered a lower average 24h acceleration and engaged in less MVPA, more sedentary time and longer sedentary bouts. Average 24h acceleration was higher in participants of lower educational attainment, who also performed less sedentary time, shorter bouts, and fewer bouts of prolonged sedentariness. Average 24h acceleration and levels of PA were higher in participants with standing and manual occupations than a sedentary work type, but manual workers registered lower average accelerations across the most active periods of the day. Standing and manual workers accumulated less sedentary time and fewer bouts of prolonged sedentariness than sedentary workers. Active commuting to work was associated with higher average 24h acceleration and MVPA, both of which were lower in participants of poorer self-rated health and higher weight status. Obesity was associated with less light PA, more sedentary time and longer sedentary bouts.

CONCLUSIONS

Adherence to recommended PA is high in Luxembourg, but half of daily time is spent sedentary. Specific population subgroups will benefit from targeted efforts to replace sedentary time with PA.

A Christmas themed physical activity intervention to increase participation in physical activity during Advent: pilot randomised controlled trial

OBJECTIVES

To examine the recruitment, retention, and preliminary effects of a Christmas themed physical activity intervention designed to increase participation in physical activity and decrease sedentary behaviour in inactive adults.

DESIGN

Pilot randomised controlled trial.

SETTING

Recruitment from social medial platforms, workplaces, and community groups in the UK.

PARTICIPANTS

107 inactive adults (who did not meet the UK guidelines for physical activity) aged 18-75 years.

INTERVENTIONS

The intervention consisted of an email sent to participants each day of Advent (1-24 December 2021), which contained a Christmas themed physical activity idea to be completed that day. Each physical activity idea was presented in three intensity formats, including Easy Elf (light intensity), Moderate Mrs Claus (moderate intensity), and Strenuous Santa (vigorous intensity). The comparator group received a leaflet about healthy living on the 1 December.

MAIN OUTCOME MEASURES

Participants were randomly assigned (2:1) to either the intervention or control and were masked to group allocation before randomisation. Primary outcomes were recruitment rate, retention, and weekly minutes of participation in self-reported moderate-to-vigorous intensity physical activity by use of the exercise vital signs questionnaire. Primary analysis compared change in minutes of moderate-to-vigorous intensity physical activity from baseline to weeks one, two, and three during the Active Advent intervention. Secondary outcomes were participation in muscle strengthening based physical activity (days per week), accelerometer measured moderate-to-vigorous intensity physical activity, light intensity physical activity, total physical activity, and sedentary time (minutes per day), and enjoyment of and adherence to the intervention.

RESULTS

323 individuals expressed interest in participating in the trial and 107 were randomly assigned to the intervention (n=71) or the comparator (n=36) group. The recruitment target (n=105) was reached within 19 days of starting recruitment. 23 (21%) of 107 participants were lost to follow-up. On average, the groups reported participation in similar minutes of moderate-to-vigorous intensity physical activity in weeks one and two. At week three, the adjusted mean difference between groups was 20.6 minutes of participation in moderate-to-vigorous intensity physical activity per week (95% confidence interval -29.7 to 70.9) in favour of the intervention group. Accelerometer data showed that the intervention group spent fewer minutes sedentary per day than comparators (mean difference -58.6 (-113.5 to -3.8)). Overall, 42 (70%) of 60 participants in the intervention group reported that they liked the intervention and 41 (69%) of 59 reported that they completed the Active Advent intervention ideas each day.

CONCLUSIONS

The public were interested to participate in a Christmas themed physical activity intervention during Advent, which might increase physical activity and reduce time sedentary. Enjoyment of, and adherence to the intervention shows the potential benefit that Christmas themed physical activity campaigns/initiatives might have for improving public health.

TRIAL REGISTRATION

ISRCTN12415556.

Wrist accelerometer temporal analysis as a prognostic tool for aged care residents: A sub‐study of the ReMInDAR trial

BACKGROUND

Objective measures for screening, prioritizing, and planning care for frail individuals are essential for appropriate aged care provision. This study evaluates metrics derived from actigraphy measures (captured by wrist accelerometer) as a digital biomarker to identify frail individuals at risk of adverse outcomes, including death, hospitalization, and cognitive decline.

METHODS

This was a secondary study using data from a randomized controlled trial assessing the effectiveness of an ongoing pharmacist service in residential aged care facilities. Three metrics are studied and compared: the Frailty Index, the daily time spent in light time activity, and the temporal correlation of the actigraphy signal, measured by detrended fluctuation analysis. The association between actigraphy-derived metrics at baseline and adverse events within 12 months (death, cognitive decline, and hospitalizations) was assessed using logistic regression.

RESULTS

Actigraphy records were available for 213 participants living in aged-care, median age of 85 years. Individuals with higher temporal correlation (activity is less random) were at lower risk of death (Standardized OR: 0.49; 95% CI 0.34, 0.7, p < 0.001) and hospitalization (Standardized OR: 0.57; 95% CI 0.42, 0.77, p < 0.001) in 12 months, but there was no difference in cognitive decline (Standardized OR: 1; 95% CI 0.74, 1.35, p = 0.98). The predictive model that included temporal correlation had an area under the curve of 0.70 (CI 0.60-0.80) for death and 0.64 (CI 0.54-0.72) for hospitalization.

CONCLUSION

Temporal correlation of the actigraphy signal from aged care residents was strongly associated with death and hospitalization, but not cognitive decline. Digital biomarkers may have a place as an objective, accurate, and low-cost patient metric to support risk stratification and clinical planning.

Association of daily and time-segmented physical activity and sedentary behaviour with mental health of school children and adolescents from rural Northeastern Ontario, Canada

Physical activity (PA) and sedentary behaviour (SED) have been linked to the mental health of children and adolescents, yet the timing of behaviours may play a role in this relationship and clarifying this could inform interventions. We explored cross-sectional associations of PA and SED in varying time segments throughout the school day with the mental health of school-aged children and adolescents from rural Northeastern Ontario, Canada. A total of 161 students (56% female, M = 10.3 years old) wore accelerometers for 8 days (7 nights) and completed a self-report survey (parent reported for children younger than 11). Mental health was measured using the Strengths and Difficulties Questionnaire. Accelerometer-measured SED, light PA (LPA), and moderate and vigorous PA (MVPA) were estimated in the time-segments before school (06:00–08:44), school time (08:45–15:04), after school (15:05–16:59), and evenings (17:00–21:59). Associations were tested with multilevel linear regressions while adjusting for confounding factors. Students spent 72.6 min in MVPA, 209.0 min in LPA, and 621.0 min in SED per day. Daily SED was associated with less conduct problems (β = −0.27, p &lt; 0.05). Evening LPA was inversely associated with hyperactivity (β = −1.45, p &lt; 0.05), while SED was associated with hyperactivity and with peer problems before school (β = 1.70 and β = 1.01, respectively, p &lt; 0.05), and during school (β = −0.83 and β = −0.57, respectively, p &lt; 0.05). No associations were observed for MVPA, emotional symptoms, or prosocial behaviour. In conclusion, displacing SED with LPA in some specific periods of the day may benefit the mental health of students; taking this into account could strengthen interventions.

Physical activity in birth cohorts of three Brazilian cities (Ribeirão Preto, Pelotas, and São Luís): A cross-sectional study

OBJECTIVE

To describe the prevalence of physical activity among subjects from birth cohorts of three cities located in different regions of Brazil according to sociodemographic characteristics and sex, comparing the relationships within and between cohorts.

METHODS

Cross-sectional study involving 12,724 adolescents and young adults who participated in five birth cohorts: Ribeirão Preto [1978/79 (37/39 years old in 2016) and 1994 (22 years in 2016)]; Pelotas [1982 (30 years in 2012) and 1993 (22 years in 2015)], and São Luís [1997/98 (18/19 years in 2016)]. Leisure-time physical activity was evaluated with questionnaires (insufficiently active: <150 min/week and active: ≥150 min/week) and moderate and vigorous physical activity (MVPA) was objectively measured by accelerometry. Those, in each city, were evaluated accordingly to skin color, socioeconomic classification, and study/work activities.

RESULTS

The prevalence of leisure-time physical activity ranged from 29.2% at 30 years old in Pelotas to 54.6% among adolescents from São Luís. The prevalence of leisure-time physical activity was higher among younger people (54.6% in São Luís 1997), while the same was not observed for total physical activity. MVPA (3rd tercile) was higher in the cohorts from Pelotas and São Luís. The prevalence of leisure-time physical activity and MVPA was higher in men. The data showed that the variation in physical activity was associated with sex and sociodemographic conditions in all cohorts.

CONCLUSION

Sociodemographic characteristics should be considered when promoting leisure-time physical activity and actions aimed at young people, and adults who are more socioeconomically vulnerable should be encouraged.

Impact of Virtual vs. In-Person School on Children Meeting the 24-h Movement Guidelines during the COVID-19 Pandemic

The pandemic mitigation strategy of closing schools, while necessary, may have unintentionally impacted children's moderate-to-vigorous physical activity (MVPA), sleep, and time spent watching screens. In some locations, schools used hybrid attendance models, with some days during the week requiring in-person and others virtual attendance. This scenario offers an opportunity to evaluate the impact of attending in-person school on meeting the 24-h movement guidelines. Children (N = 690, 50% girls, K-5th) wore wrist-placed accelerometers for 14 days during October/November 2020. Parents completed daily reports on child time spent on screens and time spent on screens for school. The schools' schedule was learning for 2 days/week in-person and 3 days/week virtually. Using only weekdays (M-F), the 24-h movement behaviors were classified, and the probability of meeting all three was compared between in-person vs. virtual learning and across grades. Data for 4956 weekdays (avg. 7 d/child) were collected. In-person school was associated with a greater proportion (OR = 1.70, 95% CI: 1.33-2.18) of days that children were meeting the 24-h movement guidelines compared to virtual school across all grades. Students were more likely to meet the screen time (OR = 9.14, 95% CI: 7.05-11.83) and MVPA (OR = 1.50, 95% CI: 1.25-1.80) guidelines and less likely to meet the sleep (OR = 0.73, 95% CI: 0.62-0.86) guidelines on the in-person compared to the virtual school days. Structured environments, such as school, have a protective effect on children's movement behaviors, especially physical activity and screen time.

Predictive equations for energy expenditure in adult humans: From resting to free-living conditions

Humans acquire energy from the environment for survival. A central question for nutritional sciences is how much energy is required to sustain cellular work while maintaining an adequate body mass. Because human energy balance is not exempt from thermodynamic principles, the energy requirement can be approached from the energy expenditure. Conceptual and technological advances have allowed understanding of the physiological determinants of energy expenditure. Body mass, sex, and age are the main factors determining energy expenditure. These factors constitute the basis for predictive equations for resting (REE) and total (TEE) energy expenditure in healthy adults. These equations yield predictions that differ up to ~400 kcal/d for REE and ~550 kcal/d for TEE. Identifying additional factors accounting for such variability and the most valid equations appears relevant. This review used novel approaches based on mathematical modeling of REE and analyses of the data from which REE predictive equations were generated. As for TEE, R² and SE were considered because only a few predictive equations are available. From these analyses, Oxford's and Plucker's equations appear valid for predicting REE and TEE in adults, respectively.

Relative protein intake and associations with markers of physical function in those with type 2 diabetes

AIMS

To examine the independent associations between relative protein intake (g kg^-1  day ¹ ) and markers of physical function in those with type 2 diabetes, while also comparing with current guidelines for protein intake.

METHODS

This analysis reports data from the ongoing Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control (CODEC) study. Functional assessments included: Short Physical Performance Battery (SPPB), 60 s sit-to-stand (STS-60), 4-m gait speed, time to rise from a chair (×5) and handgrip strength. Participants also completed a self-reported 4 day diet diary. Regression analyses assessed whether relative protein intake was associated with markers of physical function. Interaction terms assessed whether the associations were modified by sex, age, HbA1c or body mass index (BMI).

RESULTS

413 participants were included (mean ± SD:age = 65.0 ± 7.7 years, 33% female, BMI = 30.6 ± 5.1 kg/m² ). The average total protein intake was 0.88 ± 0.31 g kg^-1  day^-1 . 33% of individuals failed to meet the reference nutrient intake for the United Kingdom (≥0.75 g kg^-1  day^-1 ), and 87% for European recommendations (≥1.2 g kg^-1  day^-1 ). After adjustment, each 0.5 g/kg of protein intake was associated with an 18.9% (95% CI: 2.3, 35.5) higher SPPB score, 22.7% (1.1, 44.3) more repetitions in STS-60, 21.1% (4.5, 37.7) faster gait speed and 33.2% (16.9, 49.5) lower chair rise time. There were no associations with handgrip strength or any interactions.

CONCLUSIONS

Relative protein intake was positively associated with physical function outcomes, even after consideration of total energy intake. As a number of individuals were below the current guidelines, protein intake may be a modifiable factor of importance for people with type 2 diabetes.

Longitudinal change in physical activity and adiposity in the transition from adolescence to early adulthood: the 1993 Pelotas cohort study

Background

In the current Physical Activity Guidelines (PAG) for moderate- and vigorous-intensity physical activity (MVPA), abrupt transition from ≥ 60 min/day [youth PAG] to ≥ 150 min/week (≥ 22 min/day on average) [adult PAG] during emerging adulthood is poorly justified. The aim of this study was to examine body fat mass changes according to whether meeting the youth and adult PAGs in late adolescence (age 18 years) to early adulthood (age 22 years).

Methods

The study sample included 2,099 participants (1,113 females) from the 1993 Pelotas (Brazil) Study. At ages 18 and 22 years, MVPA was measured using wrist-worn accelerometry and fat mass was measured using dual-energy X-ray absorptiometry. MVPA at age 18 was categorized into two groups: 0–59 or ≥ 60 min/day (no [N] or yes [Y] for meeting the youth recommendation, respectively). MVPA at age 22 was categorized into three groups: 0–21, 22–59, or ≥ 60 min/day (N, Y22, or Y60 for not meeting the adult recommendation, meeting the adult recommendation, or meeting the youth recommendation, respectively). The combination of these groups created six MVPA groups (N&N, N&Y22, N&Y60, Y&N, Y&Y22, and Y&Y60). Sex-specific multivariable linear regression analyses were conducted to estimate change in fat mass index (FMI) from age 18 to 22 years in the six MVPA groups.

Results

Among males, compared to Y&Y60 (FMI increase = 1.2 kg/m² [95% CI = 1.0, 1.4]), Y&Y22 and Y&N had larger FMI increases (1.9 [1.6, 2.1] and 1.9 [1.2, 2.5], respectively). Among females, Y&Y60 and Y&Y22 had an equal FMI increase (1.6 [1.4, 1.9] for both groups), while Y&N had a larger FMI increase (2.4 [1.8, 3.0]).

Conclusions

These findings suggest that among those who were active in late adolescence, engaging in ≥ 22 min/day of MVPA in adulthood is associated with lower body fat gain for females, but not for males.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01321-0.

Risk stratification for hospital-acquired venous thromboembolism in medical patients (RISE): Protocol for a prospective cohort study

Background

Hospital-acquired venous thromboembolism (VTE) is one of the leading preventable causes of in-hospital mortality. However, its risk assessment in medically ill inpatients is complicated due to the patients’ heterogeneity and complexity of currently available risk assessment models (RAMs). The simplified Geneva score provides simplicity but has not yet been prospectively validated. Immobility is an important predictor for VTE in RAMs, but its definition is inconsistent and based on subjective assessment by nurses or physicians. In this study, we aim to prospectively validate the simplified Geneva score and to examine the predictive performance of a novel and objective definition of in-hospital immobilization using accelerometry.

Methods and analysis

RISE is a multicenter prospective cohort study. The goal is to recruit 1350 adult inpatients admitted for medical illness in three Swiss tertiary care hospitals. We collect data on demographics, comorbidities, VTE risk and thromboprophylaxis. Mobility from admission to discharge is objectively measured using a wrist-worn accelerometer. Participants are followed for 90 days for the occurrence of symptomatic VTE (primary outcome). Secondary outcomes are the occurrence of clinically relevant bleeding, and mortality. The evolution of autonomy in the activities of daily living, the length of stay, and the occurrence of readmission are also recorded. Time-dependent area under the curve, sensitivity, specificity, and positive and negative predictive values are calculated for each RAM (i.e. the simplified and original Geneva score, Padua, and IMPROVE score) with and without the objective mobility measures to assess their accuracy in predicting hospital-acquired VTE at 90 days.

Ethics and expected impact

The ethics committee approved the protocol and the study was registered on ClinicalTrials.gov as NCT04439383. RISE has the potential to optimize VTE risk stratification, and thus to improve the quality of care of medically hospitalized patients.

Effect of goal-directed mobilisation intervention compared with standard care on physical activity among medical inpatients: protocol for the GoMob-in randomised controlled trial

INTRODUCTION

Despite the fact that immobilisation is a major contributor to morbidity and mortality, patients hospitalised in general internal medicine (GIM) wards spend up to 50% of time in bed. Previous studies in selected patient populations showed increased mobility after implementation of goal-directed mobilisation (GDM). Due to the study design used so far, the degree of evidence is generally low. The effect of GDM on clinical outcomes and economically relevant indicators in patients hospitalised in GIM wards is currently unknown. This study aims to evaluate a GDM intervention compared to standard care on physical activity (de Morton Mobility Index, DEMMI) in medical inpatients.

METHODS AND ANALYSIS

GoMob-in is a randomised, controlled, open-label study with blinded outcome assessment. We plan to enrol 160 inpatients with indication for physiotherapy on GIM wards of a tertiary hospital in Bern, Switzerland. Adult patients newly hospitalised on GIM wards will be included in the study. The primary outcome will be the change in the DEMMI score between baseline and 5 days. Secondary outcomes are change of DEMMI (inclusion to hospital discharge), mobilisation time (inclusion to day 5, inclusion to discharge), in-hospital delirium episodes, number of in-hospital falls, length of stay, number of falls within 3 months, number of re-hospitalisations and all-cause mortality within 3 months, change in independence during activities of daily living, concerns of falling, and quality of life within 3 months and destination after 3 months. Patients in the intervention group will be attributed a regularly updated individual mobility goal level made visible for all stakeholders and get a short educational intervention on GDM.

ETHICS AND DISSEMINATION

This study has been approved by the responsible Ethics Board (Ethikkommission Bern/2020-02305). Written informed consent will be obtained from participants before study inclusion. Results will be published in open access policy peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04760392.

Why machine learning (ML) has failed physical activity research and how we can improve

Measuring physical activity is a critical issue for our understanding of the health benefits of human movement. Machine learning (ML), using accelerometer data, has become a common way to measure physical activity. ML has failed physical activity measurement research in four important ways. First, as a field, physical activity researchers have not adopted and used principles from computer science. Benchmark datasets are common in computer science and allow the direct comparison of different ML approaches. Access to and development of benchmark datasets are critical components in advancing ML for physical activity. Second, the priority of methods development focused on ML has created blind spots in physical activity measurement. Methods, other than cut-point approaches, may be sufficient or superior to ML but these are not prioritised in our research. Third, while ML methods are common in published papers, their integration with software is rare. Physical activity researchers must continue developing and integrating ML methods into software to be fully adopted by applied researchers in the discipline. Finally, training continues to limit the uptake of ML in applied physical activity research. We must improve the development, integration and use of software that allows for ML methods’ broad training and application in the field.

Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance

the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI_95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI_95%: − 6, 7) to 8 (CI_95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.

Relationship Between Parent and Child Physical Activity Using Novel Acceleration Metrics

Background: Raw acceleration data lend themselves to innovative metrics in which comparisons can be made across populations. This study examined whether the intensity gradient (IG) or average acceleration (AvAcc) was associated with body mass index (BMI) in children and adults and explored parent-child associations between time spent in physical activity intensities and BMI. Methods: Parent-child dyads (n = 90) wore a wrist-mounted ActiGraph GT3X+ monitor for ≥ 3 valid days (i.e., ≥ 16 hrs each day). Participants' BMI was calculated. Results: Girls' BMI-z scores were positively associated with parent BMI and inactive time. Parent BMI was negatively associated with boys' inactive time. Parental inactive time predicted girls' BMI-z scores. The metrics were not associated with parent BMI, and no independent effects were observed between the metrics. Associations between boys' IG and BMI z-score were observed. No independent effects were observed between the metrics and no significant associations were observed between boys' BMI z-score and AvAcc. Girls' AvAcc and IG were not associated with BMI z-score and no independent effects were observed between the metrics. Conclusion: Findings support previous research which suggests that parent's activity does not influence their child's activity.

Equivalence of activity outcomes derived from three research grade accelerometers worn simultaneously on each wrist

This study evaluated the equivalence of activity outcomes from three accelerometer brands worn on both wrists during free living. Forty-four adults wore a GENEActiv, ActiGraph and Axivity accelerometer for 7 days. Outcomes were assessed between and within accelerometer brand and wrist location with average acceleration and the intensity gradient (IG) being of particular interest. Pairwise 95% equivalence tests and intra-class correlation coefficients (ICC) evaluated agreement. Average acceleration and the IG were largely equivalent between combinations of accelerometer device and wrists when applying a 10% equivalence zone. There was largely a lack of equivalence between pairings for time spent in acceleration values ≥100 mg. However, equivalence was largely achieved when applying an equivalence zone that encompassed values ranging from 0.3 to 0.45 SDs for IG and time spent above 100 mg and 150 mg. Agreement between pairings tended to be stronger between different brands on the non-dominant (ICCs ≥ 0.73-0.97) versus the dominant wrist (ICCs ≥ 0.57-0.97) and between wrists for the same accelerometer (ICCs ≥ 0.59-0.97) for average acceleration and the IG. These are important findings since device placement is not consistent in studies. Further work that applies an equivalence zone reflecting the variability of the outcome measure is encouraged.

The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities

Physical behaviors (e.g., physical activity and sedentary behavior) have been the focus among many researchers in the biomedical and behavioral science fields. The recent shift from hip- to wrist-worn accelerometers in these fields has signaled the need to develop novel approaches to process raw acceleration data of physical activity and sedentary behavior. However, there is currently no consensus regarding the best practices for analyzing wrist-worn accelerometer data to accurately predict individuals' energy expenditure and the times spent in different intensities of free-living physical activity and sedentary behavior. To this end, accurately analyzing and interpreting wrist-worn accelerometer data has become a major challenge facing many clinicians and researchers. In response, this paper attempts to review different methodologies for analyzing wrist-worn accelerometer data and offer cutting edge, yet appropriate analysis plans for wrist-worn accelerometer data in the assessment of physical behavior. In this paper, we first discuss the fundamentals of wrist-worn accelerometer data, followed by various methods of processing these data (e.g., cut points, steps per minute, machine learning), and then we discuss the opportunities, challenges, and directions for future studies in this area of inquiry. This is the most comprehensive review paper to date regarding the analysis and interpretation of free-living physical activity data derived from wrist-worn accelerometers, aiming to help establish a blueprint for processing wrist-derived accelerometer data.

Physical activity in the early postpartum period in primiparous women

Little is known about early postpartum physical activity (PA).

OBJECTIVES

We aimed to describe PA amount and types and compare moderate-vigorous PA (MVPA) at 12-25 (T1) and 33-46 days (T2) postpartum.

DESIGN

Cross-sectional study.

METHODS

Participants, primiparas delivered vaginally, wore wrist accelerometers and completed questionnaires. Median and interquartile range (IQR) describe minutes/day of PA intensities in total minutes, 5- and 10-minute bouts. Wilcoxon Signed Rank test compared MVPA.

RESULTS

577 (age: 28.3 (SD: 5.1)) had accelerometry or questionnaire at either time-point. 405 had accelerometry at both time-points. Median (IQR) total minutes/day for light, moderate, vigorous and MVPA were 295.8 (256.1-331.7), 54.6 (40-72.7), 0.4 (0.2-0.8), and 55.5 (40.4-74.3), respectively, at T1 and 329 (289.4-367.1), 63.6 (46.9-82.2), 0.6 (0.3-1.3), and 64.5 (47-84.8), respectively, at T2. Median (IQR) minutes/day for MVPA in 5- and 10-minute bouts were 1.6 (0-5.5) and 0 (0-3.8) at T1, and 3 (0-9.2) and 0 (0-5.5) at T2. At T1, 75% (406/541) and at T2, 72.4% (397/548) reported non-impact activities. At T1, 4% and at T2, 13% reported impact/straining activities. MVPA was greater at T2 than T1 (p < 0.0001) with medians (IQR) of: total: 64.7 (47-84.6) vs 56.5 (41-74.9) minutes; 5-minute bouts: 3 (0-9.8) vs 1.7 (0-5.6) minutes; and 10-minute bouts: 1.3(0-6) vs 0(0-3.8) minutes.

CONCLUSIONS

Women had high daily MVPA, though MVPA in bouts remained low. Significant increases in MVPA from T1 to T2 were small, few women reported impact/straining activities. Realistic return to pre-pregnancy PA levels should recognize the relative lack of sustained/strenuous activity in early postpartum.

Normative wrist-worn accelerometer values for self-paced walking and running: a walk in the park

This study aimed to a) determine whether wrist acceleration varies by accelerometer brand, wear location, and age for self-paced "slow", "normal" and "brisk" walking; b) develop normative acceleration values for self-paced walking and running for adults. One-hundred-and-three adults (40-79 years) completed self-paced "slow", "normal" and "brisk" walks, while wearing three accelerometers (GENEActiv, Axivity, ActiGraph) on each wrist. A sub-sample (n = 22) completed a self-paced run. Generalized estimating equations established differences by accelerometer brand, wrist, and age-group (walking only, 40-49, 50-59, 60-69, 70-79 years) for self-paced walking and running. Brand*wrist interactions showed ActiGraph dominant wrist values were ~10% lower than GENEActiv/Axivity values for walking and running, and non-dominant ActiGraph values were ~5% lower for running only (p < 0.001). Acceleration during brisk walking was lower in those aged 70-79 (p < 0.05). Normative acceleration values (non-dominant wrist, all brands; dominant wrist GENEActiv/Axivity) for slow and normal walking were 140 mg and 210 mg. Brisk walking, values were 350 mg in those aged 40-69 years, but 270 mg in those aged 70-79 years. Accelerations >600 mg approximated running. These values facilitate user-friendly interpretation of accelerometer-determined physical activity in large cohort and epidemiological datasets.

Personalised Accelerometer Cut-point Prediction for Older Adults' Movement Behaviours using a Machine Learning approach

BACKGROUND AND OBJECTIVES

Body-worn accelerometers are the most popular method for objectively assessing physical activity in older adults. Many studies have developed generic accelerometer cut-points for defining activity intensity in metabolic equivalents for older adults. However, methodological diversity in current studies has led to a great deal of variation in the resulting cut-points, even when using data from the same accelerometer. In addition, the generic cut-point approach assumes that 'one size fits all' which is rarely the case in real life. This study proposes a machine learning method for personalising activity intensity cut-points for older adults.

METHODS

Firstly, raw accelerometry data was collected from 33 older adults who performed set activities whilst wearing two accelerometer devices: GENEActive (wrist worn) and ActiGraph (hip worn). ROC analysis was applied to generate personalised cut-point for each data sample based on a device. Four cut-points have been considered: Sensitivity optimised Sedentary Behaviour; Specificity optimised Moderate to Vigorous Physical Activity; Youden optimised Sedentary Behaviour; and Youden optimised Moderate to Vigorous Physical Activity. Then, an additive regression algorithm trained on biodata features, that concern the individual characteristics of participants, was used to predict the cut-points. As the model output is a numeric cut-point value (and not discrete), evaluation was based on two error metrics, Mean Absolute Error and Root Mean Square Error. Standard Error of estimation was also calculated to measure the accuracy of prediction (goodness of fit) and this was used for performance comparison between our approach and the state-of-the-art. Hold-out and 10-Fold cross validation methods were used for performance validation and comparison.

RESULTS

The results show that our personalised approach performed consistently better than the state-of-the-art with 10-Fold cross validation on all four cut-points considered for both devices. For the ActiGraph device, the Standard Error of estimation from our approach was lower by 0.33 (Youden optimised Sedentary Behaviour), 9.50 (Sensitivity optimised Sedentary Behaviour), 0.64 (Youden optimised Moderate to Vigorous Physical Activity) and 22.11 (Specificity optimised Moderate to Vigorous Physical Activity). Likewise, the Standard Error of estimation from our approach was lower for the GENEActiv device by 2.29 (Youden optimised Sedentary Behaviour), 41.65 (Sensitivity optimised Sedentary Behaviour), 4.31 (Youden optimised Moderate to Vigorous Physical Activity) and 347.15 (Specificity optimised Moderate to Vigorous Physical Activity).

CONCLUSIONS

personalised cut-point can be predicted without prior knowledge of accelerometry data. The results are very promising especially when we consider that our method predicts cut-points without prior knowledge of accelerometry data, unlike the state-of-the-art. More data is required to expand the scope of the experiments presented in this paper.

Accelerometer-derived physical activity and risk of atrial fibrillation

AIMS

Physical activity may be an important modifiable risk factor for atrial fibrillation (AF), but associations have been variable and generally based on self-reported activity.

METHODS AND RESULTS

We analysed 93 669 participants of the UK Biobank prospective cohort study without prevalent AF who wore a wrist-based accelerometer for 1 week. We categorized whether measured activity met the standard recommendations of the European Society of Cardiology, American Heart Association, and World Health Organization [moderate-to-vigorous physical activity (MVPA) ≥150 min/week]. We tested associations between guideline-adherent activity and incident AF (primary) and stroke (secondary) using Cox proportional hazards models adjusted for age, sex, and each component of the Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF) risk score. We also assessed correlation between accelerometer-derived and self-reported activity. The mean age was 62 ± 8 years and 57% were women. Over a median of 5.2 years, 2338 incident AF events occurred. In multivariable adjusted models, guideline-adherent activity was associated with lower risks of AF [hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.75-0.89; incidence 3.5/1000 person-years, 95% CI 3.3-3.8 vs. 6.5/1000 person-years, 95% CI 6.1-6.8] and stroke (HR 0.76, 95% CI 0.64-0.90; incidence 1.0/1000 person-years, 95% CI 0.9-1.1 vs. 1.8/1000 person-years, 95% CI 1.6-2.0). Correlation between accelerometer-derived and self-reported MVPA was weak (Spearman r = 0.16, 95% CI 0.16-0.17). Self-reported activity was not associated with incident AF or stroke.

CONCLUSIONS

Greater accelerometer-derived physical activity is associated with lower risks of AF and stroke. Future preventive efforts to reduce AF risk may be most effective when targeting adherence to objective activity thresholds.

Stress, physical activity, sedentary behavior, and resilience-The effects of naturalistic periods of elevated stress: A measurement-burst study

Stress is an important consideration for understanding why individuals take part in limited or no physical activity. The negative effects of stress on physical activity do not hold for everyone, so examinations of possible resilience resources that might protect individuals from the harmful effects of stress are required. Accordingly, we conducted a measurement-burst study with 53 university students over a 6-month period to examine the dynamics among stress, physical activity, sedentary behavior, and resilience resources. Participants completed three bursts of 6 days, with each burst separated by an 8-week gap. Expectations regarding the moderating effects of resilience resources were unsupported. Daily reports of academic and general stress were positively associated with sedentary behavior and negatively associated with light and moderate intensity physical activity. Hair cortisol concentration significantly moderated the association between academic stress and sedentary behavior, such that in bursts where cortisol was lower the daily positive association between stress and sedentary behavior was weaker. The finding that academic and general stress are dynamically associated with lower levels of light and moderate intensity physical activity and higher levels of sedentary behavior is an important extension to previous research, which has relied mainly on cross-sectional designs and self-report methods. Future research might examine resilience resources that are specific to the outcomes of interest rather than rely on generic resources.

Device-measured physical activity and its association with physical function in adults with type 2 diabetes mellitus

AIM

To quantify how differences in metrics characterizing physical activity and sedentary behaviour in type 2 diabetes are associated with physical function.

METHODS

This analysis included participants' data from the Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control (CODEC) cross-sectional study. Data were stratified into two groups according to their short physical performance battery (SPPB) score (impaired physical function = SPPB < 10 and normal physical function = SPPB ≥ 10). Hand-grip strength, sit-to-stand 60 (STS-60) and the Duke Activity Status Index (DASI) score were used to assess functional capacity, while physical activity metrics were measured with a wrist-worn accelerometer. The associations between physical activity metrics and measures of functional capacity were analysed using generalized linear modelling.

RESULTS

Some 635 adults (median age 66 years, 34% female) were included in this analysis. Overall, 29% of the cohort scored < 10 in the SPPB test indicating impaired physical function. This group spent more time in prolonged sedentary behaviour (600.7 vs. 572.5 min) and undertook less-intense physical activity. Each sd increase in physical activity volume and intensity gradients for those with impaired physical function was associated with 17% more repetitions for STS-60 with similar associations seen for DASI score. Each sd in sedentary time was associated with 15% fewer repetitions in STS-60 and 16% lower DASI score in those with impaired physical function, whereas in normal physical function group it was 2% and 1%, respectively.

CONCLUSIONS

The strength of the associations for physical activity measures and functional capacity were modified by physical function status, with the strongest association seen in those with impaired physical function.

Utility of wearable physical activity monitors in cardiovascular disease: a systematic review of 11 464 patients and recommendations for optimal use

Aims

Physical activity (PA) plays an important role in primary and secondary prevention of cardiovascular disease (CVD), functioning as a marker of disease progression and response to therapy. Real-world measurement of habitual PA is now possible through wearable activity monitors, however, their use in cardiovascular patients is not well described.

Methods and results

We performed a systematic review to summarize how wearable activity monitors have been used to measure PA in patients with CVD, with 11 464 patients included across 108 studies. Activity monitors were primarily used in the setting of cardiac rehabilitation (46, 43%). Most often, triaxial accelerometers (70, 65%) were instructed to be worn at the hip (58, 54%) for 7 days (n = 54, 50%). Thirty-nine different activity monitors were used, with a range of accelerometer specific settings for collection and reporting of activity data. Activity was reported most commonly as time spent in metabolic equivalent-defined activity levels (49, 45%), while non-wear time was defined in just 16 (15%) studies.

Conclusion

The collecting, processing, and reporting of accelerometer-related outcomes were highly heterogeneous. Most validation studies are limited to healthy young adults, while the paucity of methodological information disclosed renders interpretation of results and cross-study comparison challenging. While accelerometers are promising tools to measure real-world PA, we highlight current challenges facing their use in elderly multimorbid cardiology patients. We suggest recommendations to guide investigators using these devices in cardiovascular research. Future work is required to determine optimal methodology and consensus-based development of meaningful outcomes using raw acceleration data.

Calibration and Cross-Validation of Accelerometer Cut-Points to Classify Sedentary Time and Physical Activity from Hip and Non-Dominant and Dominant Wrists in Older Adults

Accelerometers' accuracy for sedentary time (ST) and moderate-to-vigorous physical activity (MVPA) classification depends on accelerometer placement, data processing, activities, and sample characteristics. As intensities differ by age, this study sought to determine intensity cut-points at various wear locations people more than 70 years old. Data from 59 older adults were used for calibration and from 21 independent participants for cross-validation purposes. Participants wore accelerometers on their hip and wrists while performing activities and having their energy expenditure measured with portable calorimetry. ST and MVPA were defined as ≤1.5 metabolic equivalents (METs) and ≥3 METs (1 MET = 2.8 mL/kg/min), respectively. Receiver operator characteristic (ROC) analyses showed fair-to-good accuracy (area under the curve [AUC] = 0.62-0.89). ST cut-points were 7 mg (cross-validation: sensitivity = 0.88, specificity = 0.80) and 1 count/5 s (cross-validation: sensitivity = 0.91, specificity = 0.96) for the hip; 18 mg (cross-validation: sensitivity = 0.86, specificity = 0.86) and 102 counts/5 s (cross-validation: sensitivity = 0.91, specificity = 0.92) for the non-dominant wrist; and 22 mg and 175 counts/5 s (not cross-validated) for the dominant wrist. MVPA cut-points were 14 mg (cross-validation: sensitivity = 0.70, specificity = 0.99) and 54 count/5 s (cross-validation: sensitivity = 1.00, specificity = 0.96) for the hip; 60 mg (cross-validation: sensitivity = 0.83, specificity = 0.99) and 182 counts/5 s (cross-validation: sensitivity = 1.00, specificity = 0.89) for the non-dominant wrist; and 64 mg and 268 counts/5 s (not cross-validated) for the dominant wrist. These cut-points can classify ST and MVPA in older adults from hip- and wrist-worn accelerometers.

Associations between Device-measured Physical Activity and Cardiometabolic Health in the Transition to Early Adulthood

PURPOSES

The aims of this study were to investigate the cross-sectional and prospective associations between accelerometer-measured physical activity and cardiometabolic health in the transition to adulthood.

METHODS

Data from the 1993 Pelotas (Brazil) Birth Cohort were analysed (N=2,280). Moderate-to-vigorous intensity physical activity (MVPA, measured using a triaxial accelerometer) and cardiometabolic health (total fat mass, blood glucose, non-HDL cholesterol, triglycerides and mean resting blood pressure) were examined at age 18 and 22 yr.

RESULTS

Overall, inverse dose-response associations between MVPA and cardiometabolic health at age 18 and 22 yr were observed in cross-sectional analyses of data from males and females. Prospective analyses showed that, in general, MVPA declined, and cardiometabolic health worsened in this 4-yr period in both males and females. Cardiometabolic health at age 22 reflected both MVPA at age 18 [β: -0.007 (95% CI: -0.014; 0.000)] and changes in MVPA from 18 to 22 yr [β: -0.030 (95% CI: -0.043; -0.016)] in males, but only changes in MVPA in females [β: -0.035 (95% CI: -0.058; -0.011)]. In analyses of change over time, males who improved MVPA by 20-30 min per day showed significant improvements in cardiometabolic health over 4 yr. The magnitude of association was slightly stronger for MVPA in 10-min bouts than for MVPA accumulated in bouts of 1-min, especially in females.

CONCLUSION

MVPA is an important predictor of cardiometabolic health in early adulthood. Strategies to prevent declines in MVPA at this life stage are required to prevent deteriorating cardiometabolic health profiles.

Using a Mobile Phone App to Analyze the Relationship Between Planned and Performed Physical Activity in University Students: Observational Study

BACKGROUND

The relationship between intention and behavior has been well researched, but most studies fail to capture dynamic, time-varying contextual factors. Ecological momentary assessment through mobile phone technology is an innovative method for collecting data in real time, including time-use data. However, only a limited number of studies have examined day-level plans to be physically active and subsequent physical activity behavior using real-time time-use data to better understand this relationship.

OBJECTIVE

This study aims to examine whether plans to be physically active (recorded in advance on an electronic calendar) were associated with objectively assessed physical activity (accelerometry), to identify activities that replaced planned periods of physical activity by using the mobile app Life in a Day (LIAD), and to test the feasibility and acceptability of LIAD for collecting real-time time-use data.

METHODS

The study included 48 university students who were randomly assigned to 1 of 3 protocols, which were defined by 1, 3, or 5 days of data collection. Participants were asked to record their planned activities on a Google Calendar and were provided with mobile phones with LIAD to complete time-use entries in real time for a set of categories (eg, exercise or sports, eating or cooking, school, or personal care). Participants were instructed to wear an accelerometer on their nondominant wrist during the protocol period. A total of 144 days of protocol data were collected from the 48 participants.

RESULTS

Protocol data for 123 days were eligible for analysis. A Fisher exact test showed a statistically significant association between plans and physical activity behavior (P=.02). The congruence between plans and behavior was fair (Cohen κ=0.220; 95% CI 0.028-0.411). Most participants did not plan to be active, which occurred on 75.6% (93/123) of days. Of these 93 days, no physical activity occurred on 76 (81.7%) days, whereas some physical activity occurred on 17 (18.3%) days. On the remaining 24.4% (30/123) of days, some physical activity was planned. Of these 30 days, no physical activity occurred on 18 (60%) days, whereas some physical activity occurred on 12 (40%) days. LIAD data indicated that activities related to screen time most often replaced planned physical activity, whereas unplanned physical activity was often related to active transport. Feasibility analyses indicated little difficulty in using LIAD, and there were no significant differences in feasibility by protocol length.

CONCLUSIONS

Consistent with previous literature, physical activity plans and physical activity behaviors were linked, but not strongly linked. LIAD offers insight into the relationship between plans and behavior, highlighting the importance of active transport for physical activity and the influence of screen-related behaviors on insufficient physical activity. LIAD is a feasible and practical method for collecting time-use data in real time.

Warming from tropical deforestation reduces worker productivity in rural communities

The accelerating loss of tropical forests in the 21st century has eliminated cooling services provided by trees in low latitude countries. Cooling services can protect rural communities and outdoor workers with little adaptive capacity from adverse heat exposure, which is expected to increase with climate change. Yet little is still known about whether cooling services can mitigate negative impacts of heat on labor productivity among rural outdoor workers. Through a field experiment in Indonesia, we show that worker productivity was 8.22% lower in deforested relative to forested settings, where wet bulb globe temperatures were, on average, 2.84 °C higher in deforested settings. We demonstrate that productivity losses are driven by behavioral adaptations in the form of increased number of work breaks, and provide evidence that suggests breaks are in part driven by awareness of heat effects on work. Our results indicate that the cooling services from forests have the potential for increasing resilience and adaptive capacity to local warming.

It is expected that tropical deforestation and related increases in heat exposure have negative impacts on labour productivity, but the size of the effect is not well known. Here, the authors show that deforestation reduces productivity by 8.22% in rural Indonesia and causes behavioural adaptation responses like more work breaks.

Inter-Device Agreement between Fitbit Flex 1 and 2 for Assessing Sedentary Behavior and Physical Activity

This study examined the inter-model agreement between the Fitbit Flex (FF) and FF2 in estimating sedentary behavior (SED) and physical activity (PA) during a free-living condition. 33 healthy adults wore the FF and FF2 on non-dominant wrist for 14 consecutive days. After excluding sleep and non-wear time, data from the FF and FF2 was converted to the time spent (min/day) in SED and PA using a proprietary algorithm. Pearson’s correlation was used to evaluate the association between the estimates from FF and FF2. Mean absolute percent errors (MAPE) were used to examine differences and measurement agreement in SED and PA estimates between FF and FF2. Bland-Altman (BA) plots were used to examine systematic bias between two devices. Equivalence testing was conducted to examine the equivalence between the FF and FF2. The FF2 had strong correlations with the FF in estimating SED and PA times. Compared to the FF, the FF2 yielded similar SED and PA estimates along with relatively low measurement discords and did not have significant systematic biases for SED and Moderate-to-vigorous PA estimates. Our findings suggest that researchers may choose FF2 as a measurement of SED and PA when FF is not available in the market during the longitudinal PA research.

The relationship between activity level and cognitive function in Chinese community-dwelling elderly

To study the relationship between daily activity level and cognitive function in community-dwelling elderly. We collected demographic features, cognitive function, activity level and self-rating depression scale scores in 53 community-dwelling olderly aged 60 years or above. The activity level and moderate-to-vigorous physical activity (MVPA) time were assessed by using the accelerometer for 7 consecutive days. We compared activity level, MVPA time and depression scores between cognitive impaired and normal groups. Cognitive functions were compared in groups with different MVPA level, and the correlation between cognitive function and MVPA time was analysed. Of the 53 subjects, 27 had varying degrees of cognitive impairment. Individuals with cognitive impairment shown significantly shorter MVPA time and higher depression score compared to the cognitive normal group (P < 0.05). After controlling for confounding factors (age, BMI), MVPA time was associated with cognitive function (r = 0.358, P = 0.009). The memory factor score correlated with MVPA time (r = 0.357, P = 0.012) and mean activity level (r = 0.287, P = 0.046). Moderate-to-vigorous physical activity in the elderly was positively related to their cognitive function. Strengthening daily activities may beneficial for the elderly to maintain better cognitive function.

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland–Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.

Study protocol: health survey of Sao Paulo: ISA-Physical Activity and Environment

Background

Many studies have investigated the association between the built environment and physical activity behavior in urban settings. However, most of the studies conducted in low- and middle-income countries were cross-sectional, which are limited to identify behavioral determinants. We propose a prospective cohort study to verify the relationship between built environment features and leisure-time and transport-related physical activity in adults from Sao Paulo city, Brazil.

Methods

Prospective multilevel cohort, denominated “ISA-Physical Activity and Environment”. It will build on the Health Survey of Sao Paulo in 2015 (“Inquérito de Saúde de São Paulo (ISA)” in Portuguese). The Health Survey of Sao Paulo, originally designed as a cross-sectional survey, had a multi-stage sample, covering 150 census tracts distributed in five health administrative areas. Data collection was performed by face-to-face interviews until December 2015 and the sample comprised 4043 individuals aged 12 years or more. The ISA-Physical Activity and Environment study will reassess people who are aged 18 years or more in 2020, including telephone and household interviews. The primary outcome will be leisure-time and transport-related physical activity, assessed through the International Physical Activity Questionnaire long version. Exposure variables will be built environment features in the areas participants live and work in the follow-up. Data analysis will include multivariate multilevel linear and logistic models. We will also conduct cost-effectiveness analysis and develop agent-based models to help inform decision-makers. The study will be conducted by an interdisciplinary research team specialized in physical activity epidemiology, nutritional epidemiology, georeferencing applied to health, statistics, agent-based modeling, public health policy, and health economics.

Discussion

There are few longitudinal studies on the relationship between the built environment and physical activity behavior in low- and middle-income countries. We believe that the ISA-Physical Activity and Environment study will contribute with important results for the progress of the knowledge in this field and for the implementation of policies that promote leisure-time physical activity and active travel in Sao Paulo and similar cities across the world.

Early postpartum physical activity and pelvic floor support and symptoms 1 year postpartum

BACKGROUND

Risks of pelvic organ prolapse and urinary incontinence increase after the first vaginal delivery. During the early postpartum period, a time of active regeneration and healing of the pelvic floor, women may be particularly vulnerable to greater pelvic floor loading.

OBJECTIVE

This prospective cohort study aimed to determine whether objectively measured moderate to vigorous physical activity in the early postpartum period predicts pelvic floor support and symptoms 1 year after the first vaginal birth.

STUDY DESIGN

We enrolled nulliparous women in the third trimester, later excluding those who had a cesarean or preterm delivery. Participants wore triaxial wrist accelerometers at 2 to 3 weeks and 5 to 6 weeks postpartum for ≥4 days. Primary outcomes, assessed 1 year postpartum, included (1) pelvic floor support on Pelvic Organ Prolapse Quantification examination, dichotomized as maximal vaginal descent of <0 cm (better support) vs ≥0 cm (worse support); and (2) pelvic floor symptom burden, considered positive with report of ≥1 bothersome symptom in ≥2 of 6 domains, assessed using the Epidemiology of Prolapse and Incontinence Questionnaire. The primary predictor was average daily moderate to vigorous physical activity. Because we could not eliminate women with pelvic floor changes before pregnancy, we modeled prevalence, rather than risk, ratios for each outcome using modified Poisson regression.

RESULTS

Of 825 participants eligible after delivery, 611 completed accelerometry and 1-year follow-up; 562 completed in-person visits, and 609 completed questionnaires. The mean age was 28.9 years (standard deviation, 5.01). The mean for moderate to vigorous physical activity measured in minutes per day was 57.3 (standard deviation, 25.4) and 68.1 (standard deviation, 28.9) at 2 to 3 weeks and 5 to 6 weeks, respectively. One year postpartum, 53 of 562 participants (9.4%) demonstrated worse vaginal support and 330 of 609 participants (54.2%) met criteria for pelvic floor symptom burden. In addition, 324 (53.1%), 284 (46.6%), 144 (23.6%), and 25 (4.1%) reported secondary outcomes of stress urinary incontinence, overactive bladder, anal incontinence, and constipation, respectively, and 264 (43.4%), 250 (41.0%), and 89 (14.6%) reported no, mild, or moderate to severe urinary incontinence, respectively. The relationship between moderate to vigorous physical activity and outcomes was not linear. On the basis of plots, we grouped quintiles of moderate to vigorous physical activity into 3 categories: first and second quintiles combined, third and fourth quintiles combined, and fifth quintile. In final multivariable models, compared with women in moderate to vigorous physical activity quintiles 3 and 4, those in the lower 2 (prevalence ratio, 0.55; 95% confidence interval, 0.31-1.00) and upper quintile (prevalence ratio, 0.70; 95% confidence interval, 0.35-1.38)) trended toward lower prevalence of worse support. However, we observed the reverse for symptom burden: compared with women in quintiles 3 and 4, those in the lower 2 (prevalence ratio, 1.20; 95% confidence interval, 1.02-1.41) and upper quintile prevalence ratio 1.34 (95% confidence interval, 1.11-1.61) demonstrated higher prevalence of symptom burden. Moderate to vigorous physical activity did not predict any of the secondary outcomes. The presence of a delivery factor with potential to increase risk for levator ani muscle injury did not modify the effect of moderate to vigorous physical activity on outcomes.

CONCLUSION

Except for support, which was worse in women with moderately high levels of activity, early postpartum moderate to vigorous physical activity was either protective or had no effect on other parameters of pelvic floor health. Few women performed substantial vigorous activity, and thus, these results do not apply to women performing strenuous exercise shortly after delivery.

Rise and Recharge: Effects on Activity Outcomes of an e-Health Smartphone Intervention to Reduce Office Workers' Sitting Time

This feasibility study evaluated the effects of an individual-level intervention to target office workers total and prolonged sedentary behaviour during working hours, using an e-health smartphone application. A three-arm (Prompt-30 or 60 min Intervention arm and a No-Prompt Comparison arm), quasi-randomised intervention was conducted over 12 weeks. Behavioural outcomes (worktime sitting, standing, stepping, prolonged sitting, and physical activity) were monitored using accelerometers and anthropometrics measured at baseline, 6 weeks and 12 weeks. Cardiometabolic measures were taken at baseline and 12 weeks. Fifty-six office workers (64% female) completed baseline assessments. The Prompt-60 arm was associated with a reduction in occupational sitting time at 6 (-46.8 min/8 h workday [95% confidence interval = -86.4, -6.6], p < 0.05) and 12 weeks (-69.6 min/8 h workday [-111.0, -28.2], p < 0.05) relative to the No-Prompt Comparison arm. Sitting was primarily replaced with standing in both arms (p > 0.05). Both Intervention arms reduced time in prolonged sitting bouts at 12 weeks (Prompt-30: -27.0 [-99.0, 45.0]; Prompt-60: -25.8 [-98.4, 47.4] min/8 h workday; both p > 0.05). There were no changes in steps or cardiometabolic risk. Findings highlight the potential of a smartphone e-health application, suggesting 60 min prompts may present an optimal frequency to reduce total occupational sedentary behaviour.

Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

Background

In a hospital setting and among older patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and institutionalization. Our aim was to assess the distribution, determinants and predictors of physical activity (PA) levels using wrist-worn accelerometers in older patients hospitalized with acute medical illness.

Methods

Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ≥65 years, able to walk prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. PA levels were defined as < 30 mg for inactivity, 30–99 mg for light and ≥ 100 for moderate PA. Physically active patients were defined as 1) being in the highest quartile of time spent in light and moderate PA or 2) spending ≥20 min/day in moderate PA.

Results

Median [interquartile range - IQR] age was 83 [74–87] years and 60% of participants were male. The median [IQR] time spent inactive and in light PA was 613 [518–663] and 63 [30–97] minutes/day, respectively. PA peaked between 8 and 10 am, at 12 am and at 6 pm. Less than 10% of patients were considered physically active according to definition 2. For both definitions, active patients had a lower prevalence of walking aids and a lower dependency level according to Barthel Index score. For definition 1, use of medical equipment was associated with a 70% reduction in the likelihood of being active: odds ratio (OR) 0.30 [0.10–0.92] p = 0.034; for definition 2, use of walking aids was associated with a 75% reduction in the likelihood of being active: OR = 0.24 [0.06–0.89], p = 0.032.

Conclusion

Older hospitalized patients are physically active only 10% of daily time and concentrate their PA around eating periods. Whether a Barthel Index below 95 prior to admission may be used to identify patients at risk of inactivity during hospital stay remains to be proven.

Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition(s)

This study demonstrates a novel data-driven method of summarising accelerometer data to profile physical activity in three diverse groups, compared with cut-point determined moderate-to-vigorous physical activity (MVPA). GGIR was used to generate average daily acceleration, intensity gradient, time in MVPA and MX metrics (acceleration above which the most active X-minutes accumulate) from wrist-worn accelerometer data from three datasets: office-workers (OW, N = 697), women with a history of post-gestational diabetes (PGD, N = 267) and adults with ≥1 chronic disease (CD, N = 1,325). Average acceleration and MVPA were lower in CD, but not PGD, relative to OW (-5.2 mg and -30.7 minutes, respectively, P < 0.001). Both PGD and CD had poorer intensity distributions than OW (P < 0.001). Application of a cut-point to the M30 showed 7%, 17% and 28%, of OW, PGD and CD, respectively, accumulated 30 minutes of brisk walking per day. Radar plots showed OW had higher overall activity than CD. The relatively poor intensity distribution of PGD, despite similar overall activity to OW, was due to accumulation of more light and less higher intensity activity. These data-driven methods identify aspects of activity that differ between groups, which may be missed by cut-point methods alone. Abbreviations: CD: Adults with ≥1 chronic disease; mg: Milli-gravitational unit; MVPA: Moderate-to-vigorous physical activity; OW: Office workers; PGD: Women with a history of post-gestational diabetes; VPA: Vigorous physical activity.

Physical activity assessment by accelerometry in people with heart failure

Background

International guidelines for physical activity recommend at least 150 min per week of moderate-to-vigorous physical activity (MVPA) for adults, including those with cardiac disease. There is yet to be consensus on the most appropriate way to categorise raw accelerometer data into behaviourally relevant metrics such as intensity, especially in chronic disease populations. Therefore the aim of this study was to estimate acceleration values corresponding to inactivity and MVPA during daily living activities of patients with heart failure (HF), via calibration with oxygen consumption (VO₂) and to compare these values to previously published, commonly applied PA intensity thresholds which are based on healthy adults.

Methods

Twenty-two adults with HF (mean age 71 ± 14 years) undertook a range of daily living activities (including laying down, sitting, standing and walking) whilst measuring PA via wrist- and hip-worn accelerometers and VO₂ via indirect calorimetry. Raw accelerometer output was used to compute PA in units of milligravity (mg). Energy expenditure across each of the activities was converted into measured METs (VO₂/resting metabolic rate) and standard METs (VO₂/3.5 ml/kg/min). PA energy costs were also compared with predicted METs in the compendium of physical activities. Location specific activity intensity thresholds were established via multilevel mixed effects linear regression and receiver operator characteristic curve analysis. A leave-one-out method was used to cross-validate the thresholds.

Results

Accelerometer values corresponding with intensity thresholds for inactivity (< 1.5METs) and MVPA (≥3.0METs) were > 50% lower than previously published intensity thresholds for both wrists and waist accelerometers (inactivity: 16.7 to 18.6 mg versus 45.8 mg; MVPA: 43.1 to 49.0 mg versus 93.2 to 100 mg). Measured METs were higher than both standard METs (34–35%) and predicted METs (45–105%) across all standing and walking activities.

Conclusion

HF specific accelerometer intensity thresholds for inactivity and MVPA are lower than previously published thresholds based on healthy adults, due to lower resting metabolic rate and greater energy expenditure during daily living activities for HF patients.

Trial registration

Clinical trials.gov NCT03659877, retrospectively registered on September 6th 2018.