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Abstract Background Interventions for preventing or reducing the development of lifestyle-related disorders should be investigated as these conditions are becoming increasingly prevalent and having large effects on quality of life and life expectancy globally. The aim of this pilot study was to prepare for a full-scale randomised controlled trial by evaluating the short-term changes resulting from a function-based preventive intervention aimed at lifestyle-related disorders on a small group of physically inactive 40-year-old people. Change in objectively measured physical activity, functional capacity according to a risk profile, and goal attainment were main outcomes. Methods Participants (n = 27) underwent functional examinations including tests of fitness, strength, mobility, balance, and posture as well as standard medical examinations including weight measures, blood pressure and blood tests and were randomised to two groups. The intervention group (n = 15) received feedback from all the examinations and lifestyle counselling based on a functional profile. The control group (n = 12) received feedback only from the standard medical examination. Follow-up was at 3–4 months. Changes in physical activity measured with accelerometers, functional levels on the functional profile, goal attainment and subjective assessments of health-related quality of life, motivation, function, and physical activity were examined, as were standard medical parameters. Results Change in mean time in moderate or more intense physical activity was 9 min higher in the intervention group (95% confidence interval -6.35, 24.51) and change in sedentary time was 42 min lower (-95.24, 11.32). The intervention group showed a higher increase in motivation for change 1.58 on 10-point scale (0.20, 2.97) and indicated more improvement on the functional risk levels concerning fitness (-0.06, 0.90). Correlation between objectively measured and self-assessed physical activity and function increased after the intervention. Most participants in the intervention group achieved some or all of their goals. Conclusions This small-scale pilot intervention with functional examinations and lifestyle counselling showed positive tendencies for change in short-term physical activity level. It seemed to lead to better understanding of personal functional capacity and increased motivation for lifestyle changes. Setting and fulfilling meaningful goals for lifestyle-related changes seemed to influence levels on the functional profile in positive directions. Research on larger and more diverse populations will be necessary to better understand the implications of the intervention. Trial registration ClinicalTrials.gov: NCT05535296 first posted on 10/09/2022.

Abstract Background The enormous effect of lifestyle-related disorders on health of the global population warrants the development of preventive interventions. Focusing on musculoskeletal health and physical activity may be a way to encourage necessary lifestyle changes by making them more concrete and understandable. The aims of the current study were to develop a function-based preventive intervention aimed at lifestyle-related disorders in physically inactive 40-year-old people and to investigate the feasibility of the intervention. The feasibility study aimed to solve practical and logistical challenges and to develop the intervention based on the experiences of participants and involved clinical personnel according to defined criteria. Methods Development of the standardised functional examination was based on literature-validated tests and clinical reasoning. Development of a risk profile was based on the functional examination and similar profiles which have already proved feasible. The feasibility of the functional examination and risk profile, together with function-based lifestyle counselling was tested on 27 participants in a pilot study with two physiotherapist examinations over a four-month period. Practical results and feedback from participants and collaborating personnel were examined. Results The functional examination consists of 20 established tests not requiring specialised equipment or training which were deemed relevant for a middle-aged population and a sub-maximal ergometer test. The risk profile consists of seven functional dimensions: cardiovascular fitness, strength in upper extremity, lower extremity and trunk, mobility, balance and posture, and three non-functional dimensions: weight, self-assessed physical activity and pain. Each dimension contains at least two measures. The participants appreciated the intervention and found it motivating for making lifestyle changes. They found the tests and risk profile understandable and could see them as tools to help achieve concrete goals. The examination required 60–75 min for one physiotherapist. The recruitment rate was low and recruited participants were highly motivated to making lifestyle changes. Conclusion This project developed a functional test battery and risk profile aimed at inactive 40-year-olds which fulfilled our feasibility criteria. Functional screening and lifestyle counselling were found to be of value to a sub-group of inactive 40-year-olds who were already motivated to improve their health situations. Trial registration ClinicalTrials.gov: NCT05535296 first posted on 10/09/2022.

Abstract Background Observational studies investigating the association between accelerometer-measured physical activity and health all use absolute measures of physical activity intensity. However, intervention studies suggest that the physical activity intensity required to improve health is relative to individual fitness. The aim of this study was to investigate the associations between accelerometer-measured absolute and relative physical activity intensity and cardiometabolic health, and what implications these associations may have on the interpretation of health-associated physical activity. Methods A sample of the cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) consisting of 4,234 men and women aged 55–64 years was studied. Physical activity intensity was measured by accelerometry and expressed as absolute (e.g., metabolic equivalents of task) or relative (percentage of maximal oxygen consumption). Fitness was estimated by the submaximal Ekblom-Bak test. A composite (‘metabolic syndrome’) score combined measures of waist circumference, systolic blood pressure, high-density lipoprotein, triglycerides, and glycated hemoglobin. Associations of absolute and relative physical activity intensity with the health indicators (i.e., fitness and metabolic syndrome score) were studied by partial least squares regression. Analyses were stratified by fitness level. Results Both absolute and relative physical activity intensity associated with the health indicators. However, the strongest associations for absolute intensity varied depending on fitness levels, whereas the associations for relative intensity were more synchronized across fitness groups. The dose–response relationship between moderate-to-vigorous intensity and the health indicators was stronger for relative than for absolute intensity. The absolute and relative moderate-to-vigorous intensity cut-offs intersected at the 5th fitness percentile, indicating that the absolute intensity cut-off is too low for 95% of individuals in this sample. While 99% of individuals fulfilled the general physical activity recommendations based on absolute intensity measures, only 21% fulfilled the recommendations based on relative intensity measures. In relation to a “sufficient” fitness level, 9% fulfilled the recommendations. Conclusions Accelerometer-measured relative physical activity intensity represents the intensity related to health benefits regardless of fitness level. Traditional absolute moderate intensity accelerometer cut-offs are too low for most individuals and should be adapted to the fitness level in the sample studied. Absolute and relative physical activity intensity cannot be used interchangeably.

Summary: Background: Previous population-based studies investigating the relationship between physical activity and the gut microbiota have relied on self-reported activity, prone to reporting bias. Here, we investigated the associations of accelerometer-based sedentary (SED), moderate-intensity (MPA), and vigorous-intensity (VPA) physical activity with the gut microbiota using cross-sectional data from the Swedish CArdioPulmonary bioImage Study. Methods: In 8416 participants aged 50–65, time in SED, MPA, and VPA were estimated with hip-worn accelerometer. Gut microbiota was profiled using shotgun metagenomics of faecal samples. We applied multivariable regression models, adjusting for sociodemographic, lifestyle, and technical covariates, and accounted for multiple testing. Findings: Overall, associations between time in SED and microbiota species abundance were in opposite direction to those for MPA or VPA. For example, MPA was associated with lower, while SED with higher abundance of Escherichia coli. MPA and VPA were associated with higher abundance of the butyrate-producers Faecalibacterium prausnitzii and Roseburia spp. We observed discrepancies between specific VPA and MPA associations, such as a positive association between MPA and Prevotella copri, while no association was detected for VPA. Additionally, SED, MPA and VPA were associated with the functional potential of the microbiome. For instance, MPA was associated with higher capacity for acetate synthesis and SED with lower carbohydrate degradation capacity. Interpretation: Our findings suggest that sedentary and physical activity are associated with a similar set of gut microbiota species but in opposite directions. Furthermore, the intensity of physical activity may have specific effects on certain gut microbiota species. Funding: European Research Council, Swedish Heart-Lung Foundation, Swedish Research Council, Knut and Alice Wallenberg Foundation.

Galectin-1 plays a functional role in human metabolism and the levels are altered in obesity and type 2 diabetes (T2D). This study investigates the association of cardiorespiratory fitness (CRF) with galectin-1 and the interconnection with body fatness. Cross-sectional data from the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot was analyzed, including a sample of 774 middle-aged individuals. A submaximal cycle ergometer test was used to estimate CRF as an indirect measure of the physical activity (PA) level. Serum-galectin-1 concentration was determined from venous blood collected after an overnight fast. Body mass index (BMI) was used as an indirect measure of body fatness. CRF was significantly associated with galectin-1, when controlled for age and sex (regression coefficient (regr coeff) = -0.29, p

Abstract Background The number of steps by an individual, has traditionally been assessed with a pedometer, but increasingly with an accelerometer. The ActiLife software (AL) is the most common way to process accelerometer data to steps, but it is not open source which could aid understanding of measurement errors. The aim of this study was to compare assessment of steps from the open-source algorithm part of the GGIR package and two closed algorithms, AL normal (n) and low frequency extension (lfe) algorithms to Yamax pedometer, as reference. Free-living in healthy adults with a wide range of activity level was studied. Results A total 46 participants divided by activity level into a low-medium active group and a high active group, wore both an accelerometer and a pedometer for 14 days. In total 614 complete days were analyzed. A significant correlation between Yamax and all three algorithms was shown but all comparisons were significantly different with paired t-tests except for ALn vs Yamax. The mean bias shows that ALn slightly overestimated steps in the low-medium active group and slightly underestimated steps in high active group. The mean percentage error (MAPE) was 17% and 9% respectively. The ALlfe overestimated steps by approximately 6700/day in both groups and the MAPE was 88% in the low-medium active group and 43% in the high active group. The open-source algorithm underestimated steps with a systematic error related to activity level. The MAPE was 28% in the low-medium active group and 48% in the high active group. Conclusion The open-source algorithm captures steps fairly well in low-medium active individuals when comparing with Yamax pedometer, but did not show satisfactory results in more active individuals, indicating that it must be modified before implemented in population research. The AL algorithm without the low frequency extension measures similar number of steps as Yamax in free-living and is a useful alternative before a valid open-source algorithm is available.

The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect of physical activity (PA) interventions or population surveillance. Methods have been evaluated previously, but none utilize the temporal aspects of the accelerometry data. In this study, we investigated the energy expenditure prediction from acceleration measured at the subjects’ hip, wrist, thigh, and back using recurrent neural networks utilizing temporal elements of the data. The acceleration was measured in children (N = 33) performing a standardized activity protocol in their natural environment. The energy expenditure was modelled using Multiple Linear Regression (MLR), stacked long short-term memory (LSTM) networks, and combined convolutional neural networks (CNN) and LSTM. The correlation and mean absolute percentage error (MAPE) were 0.76 and 19.9% for the MLR, 0.882 and 0.879 and 14.22% for the LSTM, and, with the combined LSTM-CNN, the best performance of 0.883 and 13.9% was achieved. The prediction error for vigorous intensities was significantly different (p < 0.01) from those of the other intensity domains: sedentary, light, and moderate. Utilizing the temporal elements of movement significantly improves energy expenditure prediction accuracy compared to other conventional approaches, but the prediction error for vigorous intensities requires further investigation.

Abstract Background Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically less validated. The present study aimed to determine the validity of Oura Ring step-count and energy expenditure (EE) in both laboratory and free-living. Methods Oura Ring EE was compared against indirect calorimetry in the laboratory, followed by a 14-day free-living study with 32 participants wearing an Oura Ring and reference monitors (three accelerometers positioned at hip, thigh, and wrist, and pedometer) to evaluate Oura EE variables and step count. Results Strong correlations were shown for Oura versus indirect calorimetry in the laboratory (r = 0.93), and versus reference monitors for all variables in free-living (r ≥ 0.76). Significant (p

Abstract Background Physical inactivity is a main cause of childhood obesity which tracks into adulthood obesity, making it important to address early in life. Physical activity on prescription (PAP) is an evidence-based intervention that has shown good effect on physical activity levels in adults, but has not been evaluated in children with obesity. This project aims to evaluate the prerequisites, determinants, and feasibility of implementing PAP adapted to children with obesity and to explore children’s, parents’, and healthcare providers’ experiences of PAP. Methods In the first phase of the project, healthcare providers and managers from 26 paediatric clinics in Region Västra Götaland, Sweden, will be invited to participate in a web-based survey and a subset of this sample for a focus group study. Findings from these two data collections will form the basis for adaptation of PAP to the target group and context. In a second phase, this adapted PAP intervention will be evaluated in a clinical study in a sample of approximately 60 children with obesity (ISO-BMI > 30) between 6 and 12 years of age and one of their parents/legal guardians. Implementation process and clinical outcomes will be assessed pre- and post-intervention and at 8 and 12 months’ follow-up. Implementation outcomes are the four core constructs of the Normalization Process Theory; coherence, cognitive participation, collective action, and reflexive monitoring; and appropriateness, acceptability, and feasibility of the PAP intervention. Additional implementation process outcomes are recruitment and attrition rates, intervention fidelity, dose, and adherence. Clinical outcomes are physical activity pattern, BMI, metabolic risk factors, health-related quality of life, sleep, and self-efficacy and motivation for physical activity. Lastly, we will explore the perspectives of children and parents in semi-structured interviews. Design and analysis of the included studies are guided by the Normalization Process Theory. Discussion This project will provide new knowledge regarding the feasibility of PAP for children with obesity and about whether and how an evidence-based intervention can be fitted and adapted to new contexts and populations. The results may inform a larger scale trial and future implementation and may enhance the role of PAP in the management of obesity in paediatric health care in Sweden. Trial registration ClinicalTrials.gov Identifier: NCT04847271 , registered 14 April 2021.

Abstract Chronotype reflects individual preferences for timing activities throughout the day, determined by the circadian system, environment and behavior. The relationship between chronotype, physical activity, and cardiovascular health has not been established. We studied the association between chronotype, physical activity patterns, and an estimated 10-year risk of first-onset cardiovascular disease (CVD) in the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot cohort. A cross-sectional analysis was performed in a middle-aged population (n = 812, 48% male). Self-assessed chronotype was classified as extreme morning, moderate morning, intermediate, moderate evening, or extreme evening. Time spent sedentary (SED) and in moderate to vigorous physical activity (MVPA) were derived from hip accelerometer. The newly introduced Systematic COronary Risk Evaluation 2 (SCORE2) model was used to estimate CVD risk based on gender, age, smoking status, systolic blood pressure, and non-HDL cholesterol. Extreme evening chronotypes exhibited the most sedentary lifestyle and least MVPA (55.3 ± 10.2 and 5.3 ± 2.9% of wear-time, respectively), with a dose-dependent relationship between chronotype and SED/MVPA (p

Objectives This study aimed to identify main sex-specific correlates of cardiorespiratory fitness (CRF) in a population-based, urban sample of Swedish adults.Design Cross-sectional.Setting Multi-site study at university hospitals, data from the Gothenburg site.Participants A total of 5308 participants (51% women, aged 50–64 years) with a valid estimated VO2max, from submaximal cycle test, in the Swedish CArdioPulmonary bioImage Study (SCAPIS), were included.Primary and secondary outcomes A wide range of correlates were examined including (a) sociodemographic and lifestyle behaviours, (b) perceived health, anthropometrics and chronic conditions and (c) self-reported as well as accelerometer-derived physical activity and sedentary behaviours. Both continuous levels of estimated VO2max as well as odds ratios (OR) and confidence intervals (CI)s of low VO2max (lowest sex-specific tertile) were reported.Results In multivariable regression analyses, higher age, being born abroad, short education, high waist circumference, poor perceived health, high accelerometer-derived time in sedentary and low in vigorous physical activity, as well as being passive commuter, correlated independently and significantly with low VO2max in both men and women (OR range 1.31–9.58). Additionally in men, financial strain and being an ex-smoker are associated with higher odds for low VO2max (OR 2.15; 95% CI 1.33 to 3.48 and OR 1.40; 95% CI 1.09 to 1.80), while constant stress with lower odds (OR 0.61; 95% CI 0.43 to 0.85). Additionally in women, being a regular smoker is associated with lower odds for low VO2max (OR 0.64; 95% CI 0.45 to 0.92).Conclusions The present study provides important reference material on CRF and correlates of CRF in a general middle-aged population, which can be valuable for future research, clinical practice and public health work. If relations are causal, increased knowledge about specific subgroups will aid in the development of appropriate, targeted interventions.

BackgroundPrevious evidence supports a beneficial effect of physical activity on executive function across the whole lifespan. Yet, the interrelationships of the intensities of physical activity, cardiorespiratory fitness, and executive function require further investigation in adults.AimUsing unfiltered accelerometry data and high-resolution intensity classification, we sought to estimate the associations of physical activity with cardiorespiratory fitness and executive function in adult office workers.MethodsWe included 343 full-time office workers (mean age: 42.41 years, range of age: 36−49 years). Executive function was assessed using Stroop, Trail making tests (part-B), and 2-back tests, and a composite score was produced to reflect the general executive function performance. Physical activity was assessed using the Actigraph GT3X+-monitor, worn by each participant for seven days at the hip. Raw accelerometry data were processed by the 10 Hz frequency extended method and divided into 22 intensity bins and sleep time. Cardiorespiratory fitness was estimated using the submaximal Ekblom-Bak cycle ergometer test. Data were analyzed using partial least squares regressions.ResultsIn adults, cardiorespiratory fitness was closely correlated with a wide range of absolute physical activity intensity patterns. A higher level of executive function in adults was associated with both higher absolute physical activity intensities and cardiorespiratory fitness, which was independent of age, sex, and education levels. A very weak association between intensities, fitness, and executive function was observed in high-fit adults. Among low-fit adults, although a positive association started already toward the upper end of moderate intensity, there still appeared to be an association between intensities, cardiorespiratory fitness, and executive function. That is, cardiorespiratory fitness may mediate the association between absolute physical activity intensities and executive function up to a certain level.ConclusionThe maintenance of executive function in adulthood was related to both physical activity intensities and cardiorespiratory fitness, while their interrelationship was not equal across fitness levels. It is highly recommended to consider the cardiorespiratory fitness level in future studies that focus on executive functions in aging as well when designing individualized physical activity training programs.

Abstract Background This pilot study aimed to describe physical activity (PA) and self‐perceived function, health and quality of life (QoL) prior to oncological treatment in patients with head and neck cancer (HNC). Methods In a prospective study including 49 patients, self‐perceived PA (Saltin‐Grimby scale) and health‐related QoL (European Organization for Research and Treatment of Cancer Quality of Life questionnaire Core 30 and EQ‐5D) were assessed. Further, PA was also measured by an accelerometer attached to the thigh for eight consecutive days. The accelerometer PA was compared to the PA of a reference population assessed with the same method. Results presented are from data collected before start of oncological treatment. Results The patients (44‐79 years, 65% males) spent most of their time in sedentary behavior: a median of 555 minutes/day in bed (39% of total) and 606 minutes/day sitting (41%). Only 129 minutes/day were spent moving/walking. Patients with higher education, reduced physical function and higher fatigue were less physically active (P ≤ .01). Further, the different PA measures demonstrated a pattern of being less physically active compared to the reference population. Conclusions Patients diagnosed for HNC may have low PA level. Assessment of PA from accelerometer data may be an important component of oncological treatment to identify patients in need for PA intervention that may enhance treatment outcome.

Abstract Background Physical activity (PA) during childhood is important for preventing future metabolic syndrome (MetS). To examine the relationship between PA and MetS in more detail, accurate measures of PA are needed. Previous studies have only utilized a small part of the information available from accelerometer measured PA. This study investigated the association between measured PA and MetS in children with a new method for data processing and analyses that enable more detailed interpretation of PA intensity level. Methods The association between PA pattern and risk factors related to MetS was investigated in a cross- sectional sample of children (n = 2592, mean age 10.9 years, 49.4% male) participating in the European multicenter I. Family study. The risk factors examined include body mass index, blood pressure, high-density lipoprotein cholesterol, insulin resistance and a combined risk factor score (MetS score). PA was measured by triaxial accelerometers and raw data was processed using the 10 Hz frequency extended method (FEM). The PA output was divided into an intensity spectrum and the association with MetS risk factors was analyzed by partial least squares regression. Results PA patterns differed between the European countries investigated, with Swedish children being most active and Italian children least active. Moderate intensity physical activity was associated with lower insulin resistance (R 2 = 2.8%), while vigorous intensity physical activity was associated with lower body mass index (R 2 = 3.6%), MetS score (R 2 = 3.1%) and higher high-density lipoprotein cholesterol (R 2 = 2.3%). PA of all intensities was associated with lower systolic- and diastolic blood pressure, although the associations were weaker than for the other risk factors (R 2 = 1.5% and R 2 = 1.4%). However, the multivariate analysis implies that the entire PA pattern must be considered. The main difference in PA was observed between normal weight and overweight children. Conclusions The present study suggests a greater importance of more PA corresponding to an intensity of at least brisk walking with inclusion of high-intense exercise, rather than a limited time spent sedentary, in the association to metabolic health in children. The methods of data processing and statistical analysis enabled accurate analysis and interpretation of the health benefits of high intensity PA that have not been shown previously.

Abstract Background Self-perceived mental health problems among adolescents has had an upward trend. Concurrently, adolescents’ physical activity (PA) has been falling whilst sedentary time (SED) has increased. There is a lack of research using accelerometer measured PA and SED to study their relationships to perceived stress and psychosomatic symptoms, both frequently observed mental health problems among adolescents. Whether coping strategies is one of the mechanisms underlying such relationship is less clear. Methods A total of 2283 13-year olds were enrolled in the baseline examination of the STARS (STudy of Adolescence Resilience and Stress) study in Western Sweden. Light-, moderate-, vigorous-intensity PA (LPA, MPA and VPA) and SED were measured using hip-worn ActiGraph GT3X+ accelerometer. A total of 1284 adolescents provided valid accelerometer data (at least 4 days with ≥10 h per day). PA and SED during school-time and leisure-time were analysed separately. Surveys were utilized to monitor perceived stress, psychosomatic symptoms and the use of coping strategies “shift-persist”. Logistic regression and mediation analyses were performed adjusting for gender, ethnicity, socioeconomic status and puberty development. Results We observed that more time spent in PA was associated with less stress in adolescents. The associations were observed for LPA (Odds ratio for LPA per 60 min: 0.557 (95% CI 0.399–0.776), VPA (Odds ratio for VPA per 15 min: 0.688 (95% CI 0.588–0.806) and MVPA (Odds ratio for MVPA per 15 min: 0.795 (95%CI 0.718–0.879) during leisure time, but not during school time. Similar associations were observed between leisure time PA and psychosomatic symptoms. The associations remained statistically significant even after adjusting for the confounders. Further, our data showed that adolescents who engaged more time in PA during leisure time were more likely to adopt the coping strategies of “shift-persist”. Mediation analysis showed that the use of “shift-persist” mediated the associations between leisure time PA and stress/psychosomatic symptoms. Conclusions Leisure time physical activity, irrespective of intensity, may facilitate successful coping with stress and stress-related mental health problems in adolescents.

Abstract Background High occupational physical activity is associated with lower health. Shoe-based movement sensors can provide an objective measurement of occupational physical activity in a lab setting but the performance of such methods in a free-living environment have not been investigated. The aim of the current study was to investigate the feasibility and accuracy of shoe sensor-based activity classification in an industrial work setting. Results An initial calibration part was performed with 35 subjects who performed different workplace activities in a structured lab setting while the movement was measured by a shoe-sensor. Three different machine-learning models (random forest (RF), support vector machine and k-nearest neighbour) were trained to classify activities using the collected lab data. In a second validation part, 29 industry workers were followed at work while an observer noted their activities and the movement was captured with a shoe-based movement sensor. The performance of the trained classification models were validated using the free-living workplace data. The RF classifier consistently outperformed the other models with a substantial difference in in the free-living validation. The accuracy of the initial RF classifier was 83% in the lab setting and 43% in the free-living validation. After combining activities that was difficult to discriminate the accuracy increased to 96 and 71% in the lab and free-living setting respectively. In the free-living part, 99% of the collected samples either consisted of stationary activities or walking. Conclusions Walking and stationary activities can be classified with high accuracy from a shoe-based movement sensor in a free-living occupational setting. The distribution of activities at the workplace should be considered when validating activity classification models in a free-living setting.

There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, validate the performance in a workplace setting and compare it to the most commonly used accelerometer positions. Models for EE estimation were calibrated in a laboratory setting for the shoe, hip, thigh and wrist worn accelerometers. These models were validated in a free-living workplace setting. Furthermore, additional models were developed from free-living data. All sensor positions performed well in the laboratory setting. When the calibration models derived from laboratory data were validated in free living, the shoe, hip and thigh sensors displayed higher correlation, but lower agreement, with measured EE compared to the wrist sensor. Using free-living data for calibration improved the agreement of the shoe, hip and thigh sensors. This study suggests that the performance of a shoe-based accelerometer is similar to the most commonly used sensor positions with regard to PA measurement. Furthermore, it highlights limitations in using the relationship between accelerometer output and EE from a laboratory setting to estimate EE in a free-living setting.

Background: The objective and accurate assessment of children’s sedentary and physical behavior is important for investigating their relation to health. The purpose of this study is to validate a simple and robust method for the identification of sitting, standing, walking, running and biking performed by preschool children, children and adolescents in the age from 3 to 16 years from a single thigh-worn accelerometer. Method: A total of 96 children were included in the study and all subjects followed a structured activity protocol performed in the subject’s normal kindergarten or school environment. Thigh acceleration was measured using the Axivity AX3 (Axivity, Newcastle, UK) device. Method development and accuracy was evaluated by equally dividing the subjects into a development and test group. Results: The sensitivity and specificity for identifying sitting and standing was above 99.3% and for walking and running above 82.6% for all age groups. The sensitivity and specificity for identifying biking was above 85.8% for children and adolescents and above 64.8% for the preschool group using running bikes. Conclusion: The accurate assessment of sitting, standing, walking, running and biking from thigh acceleration and with children in the age range of 3 to 16 is valid, although not with preschool children using running bikes.

An improved method of physical activity accelerometer data processing, involving a wider frequency filter than the most commonly used ActiGraph filter, has been shown to better capture variations in physical activity intensity in a lab setting. The aim of the study was to investigate how this improved measure of physical activity affected the relationship with markers of cardiometabolic health. Accelerometer data and markers of cardiometabolic health from 725 adults from two samples, LIV 2013 and SCAPIS pilot, were analyzed. The accelerometer data was processed using both the original ActiGraph method with a low-pass cut-off at 1.6 Hz and the improved method with a low-pass cut-off at 10 Hz. The relationship between the physical activity intensity spectrum and a cardiometabolic health composite score was investigated using partial least squares regression. The strongest association between physical activity and cardiometabolic health was shifted towards higher intensities with the 10 Hz output compared to the ActiGraph method. In addition, the total explained variance was higher with the improved method. The 10 Hz output enables correctly measuring and interpreting high intensity physical activity and shows that physical activity at this intensity is stronger related to cardiometabolic health compared to the most commonly used ActiGraph method.

Accelerometer calibration for physical activity (PA) intensity is commonly performed using Metabolic Equivalent of Task (MET) as criterion. However, MET is not an age-equivalent measure of PA intensity, which limits the use of MET-calibrated accelerometers for age-related PA investigations. We investigated calibration using VO2net (VO2gross − VO2stand; mL⋅min−1⋅kg−1) as criterion compared to MET (VO2gross/VO2rest) and the effect on assessment of free-living PA in children, adolescents and adults. Oxygen consumption and hip/thigh accelerometer data were collected during rest, stand and treadmill walk and run. Equivalent speed (Speedeq) was used as indicator of the absolute speed (Speedabs) performed with the same effort in individuals of different body size/age. The results showed that VO2net was higher in younger age-groups for Speedabs, but was similar in the three age-groups for Speedeq. MET was lower in younger age-groups for both Speedabs and Speedeq. The same VO2net-values respective MET-values were applied to all age-groups to develop accelerometer PA intensity cut-points. Free-living moderate-and-vigorous PA was 216, 115, 74 and 71 min/d in children, adolescents, younger and older adults with VO2net-calibration, but 140, 83, 74 and 41 min/d with MET-calibration, respectively. In conclusion, VO2net calibration of accelerometers may provide age-equivalent measures of PA intensity/effort for more accurate age-related investigations of PA in epidemiological research.

In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect of wider frequency filters on measurements of PA, sedentary behavior (SED), and capturing of noise. Apart from the standard AG band-pass filter (0.29–1.63 Hz), modified filters with low-pass component cutoffs at 4 Hz, 10 Hz, or removed were analyzed. Calibrations against energy expenditure were performed with lab data from children and adults to generate filter-specific intensity cut-points. Free-living accelerometer data from children and adults were processed using the different filters and intensity cut-points. There was a contribution of acceleration related to PA at frequencies up to 10 Hz. The contribution was more pronounced at moderate and vigorous PA levels, although additional acceleration also occurred at SED. The classification discrepancy between AG and the wider filters was small at SED (1–2%) but very large at the highest intensities (>90%). The present study suggests an optimal low-pass frequency filter with a cutoff at 10 Hz to include all acceleration relevant to PA with minimal effect of noise.

ActiGraph is the most common accelerometer in physical activity research, but it has measurement errors due to restrictive frequency filtering. This study investigated biomechanically how different frequency filtering of accelerometer data affects assessment of activity intensity and age-group differences when measuring physical activity. Data from accelerometer at the hip and motion capture system was recorded during treadmill walking and running from 30 subjects in three different age groups: 10, 15, and >20 years old. Acceleration data was processed to ActiGraph counts with original band-pass filter at 1.66 Hz, to counts with wider filter at either 4 or 10 Hz, and to unfiltered acceleration according to “Euclidian norm minus one” (ENMO). Internal and external power, step frequency, and vertical displacement of center of mass (VD) were estimated from the motion capture data. Widening the frequency filter improved the relationship between higher locomotion speed and counts. It also removed age-group differences and decreased within-group variation. While ActiGraph counts were almost exclusively explained by VD, the counts from the 10 Hz filter were explained by VD and step frequency to an equal degree. In conclusion, a wider frequency filter improves assessment of physical activity intensity by more accurately capturing individual gait patterns.