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Our recent study of three accelerometer brands in various ambulatory activities showed that the mean amplitude deviation (MAD) of the resultant acceleration signal performed best in separating different intensity levels and provided excellent agreement between the three devices. The objective of this study was to derive a regression model that estimates oxygen consumption (VO2) from MAD values and validate the MAD-based cut-points for light, moderate and vigorous locomotion against VO2 within a wide range of speeds. 29 participants performed a pace-conducted non-stop test on a 200 m long indoor track. The initial speed was 0.6 m/s and it was increased by 0.4 m/s every 2.5 minutes until volitional exhaustion. The participants could freely decide whether they preferred to walk or run. During the test they carried a hip-mounted tri-axial accelerometer and mobile metabolic analyzer. The MAD was calculated from the raw acceleration data and compared to directly measured incident VO2. Cut-point between light and moderate activity was set to 3.0 metabolic equivalent (MET, 1 MET = 3.5 ml · kg-1 · min-1) and between moderate and vigorous activity to 6.0 MET as per standard use. The MAD and VO2 showed a very strong association. Within individuals, the range of r values was from 0.927 to 0.991 providing the mean r = 0.969. The optimal MAD cut-point for 3.0 MET was 91 mg (milligravity) and 414 mg for 6.0 MET. The present study showed that the MAD is a valid method in terms of the VO2 within a wide range of ambulatory activities from slow walking to fast running. Being a device-independent trait, the MAD facilitates directly comparable, accurate results on the intensity of physical activity with all accelerometers providing tri-axial raw data.

Background: Stiff landings with less knee flexion and high vertical ground-reaction forces have been shown to be associated with an increased risk of anterior cruciate ligament (ACL) injury. The literature on the association between other sagittal plane measures and the risk of ACL injuries with a prospective study design is lacking. Purpose: To investigate the relationship between selected sagittal plane hip, knee, and ankle biomechanics and the risk of ACL injury in young female team-sport athletes. Study Design: Case-control study; Level of evidence, 3. Methods: A total of 171 female basketball and floorball athletes (age range, 12-21 years) participated in a vertical drop jump test using 3-dimensional motion analysis. All new ACL injuries, as well as match and training exposure data, were recorded for 1 to 3 years. Biomechanical variables, including hip and ankle flexion at initial contact (IC), hip and ankle ranges of motion (ROMs), and peak external knee and hip flexion moments, were selected for analysis. Cox regression models were used to calculate hazard ratios (HRs) with 95% CIs. The combined sensitivity and specificity of significant test variables were assessed using a receiver operating characteristic (ROC) curve analysis. Results: A total of 15 noncontact ACL injuries were recorded during follow-up (0.2 injuries/1000 player-hours). Of the variables investigated, landing with less hip flexion ROM (HR for each 10° increase in hip ROM, 0.61 [95% CI, 0.38-0.99]; P < .05) and a greater knee flexion moment (HR for each 10-N·m increase in knee moment, 1.21 [95% CI, 1.04-1.40]; P = .01) was significantly associated with an increased risk of ACL injury. Hip flexion at IC, ankle flexion at IC, ankle flexion ROM, and peak external hip flexion moment were not significantly associated with the risk of ACL injury. ROC curve analysis for significant variables showed an area under the curve of 0.6, indicating a poor combined sensitivity and specificity of the test. Conclusion: Landing with less hip flexion ROM and a greater peak external knee flexion moment was associated with an increased risk of ACL injury in young female team-sport players. Studies with larger populations are needed to confirm these findings and to determine the role of ankle flexion ROM as a risk factor for ACL injury. Increasing knee and hip flexion ROMs to produce soft landings might reduce knee loading and risk of ACL injury in young female athletes.

Due to modern lifestyles, physical activity (PA) has decreased at a population level, resulting in health concerns worldwide. Increased level of PA can reduce mortality and morbidity in pulmonary diseases, such as asthma and chronic obstructive pulmonary disease (COPD). Many previous studies on the association between pulmonary function and PA assessed PA by questionnaires. We aimed to study the cross-sectional association between pulmonary function and objectively measured PA and sedentary behavior (SB) in population-based data. A total of 4729 subjects participated in the Health 2011 survey, which represents the Finnish adult population. Of these, 1511 completed spirometry and the required 4-day accelerometer wear time. Spirometry values of forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) were determined. We compared the differences in daily PA measured with triaxial accelerometer between those with obstructive or restrictive spirometry results (defined as FEV1/FVC < −1.65 z-score, lower limit of normal [LLN] and FVC < −1.65 z-score, respectively) and those with FEV1 < −1.65 z-score to those with normal spirometry in adjusted logistic regression analysis. Airway obstruction, pulmonary restriction, and FEV1 < LLN were associated with less time spent in moderate (adjusted odds ratio [OR] 0.63, 95% confidence interval [CI] 0.40-0.99; OR 0.65, 95% CI 0.43–1.00; OR 0.58, 95% CI 0.39–0.87, respectively) and moderate-to-vigorous level of PA (OR 0.65, 95% CI 0.43–0.98; OR 0.63, 95% CI 0.42–0.94; OR 0.56, 95% CI 0.38–0.82, respectively). Those with restrictive spirometry had greater time spent sedentary and a lower daily step count when compared to those with normal spirometry. Respective ORs with 95% CIs were 1.09 (1.01–1.19) and 0.85 (0.75–0.96). Our results show the association between impaired pulmonary function and measured lower level of daily PA. Restriction associated with greater time spent sedentary and a lower daily step count when compared with those with normal spirometry, airway obstruction, and FEV1 < LLN.

The aim of this study was to examine the associations of cardiometabolic health markers with device-measured sedentary behavior (SB) duration and different intensities of physical activity (PA) among overweight working-aged adults with low self-reported PA levels. This cross-sectional analysis included 144 subjects (42 men) with mean age of 57 (SD 6.5) years and mean BMI of 31.7 (SD 4) kg/m 2 . SB and standing time, breaks in sedentary time, light PA (LPA) and moderate-to-vigorous PA (MVPA) were measured for 4 consecutive weeks (mean 25 days, SD 4) with hip-worn accelerometers. Fasting plasma glucose, insulin, HbA 1c , triglycerides and total cholesterol, HDL and LDL were measured from venous blood samples. HOMA-IR index was calculated as a surrogate of insulin resistance. The associations were examined using linear models. LPA, MVPA, and daily steps associated with better insulin sensitivity and favorable plasma lipid profile, when adjusted for age, sex and BMI, whereas greater proportion of SB associated with insulin resistance and unfavorable lipid profile. As all PA intensities associated with better cardiometabolic health, the total daily duration of PA may be more relevant than intensity in maintaining metabolic health in overweight adults, if the current guidelines for PA are not met. Trial Registration: ClinicalTrials.gov NCT03101228, registered 05/04/2017, https://clinicaltrials.gov/show/NCT03101228 .

Hip-worn accelerometers are commonly used to assess habitual physical activity, but their accuracy in precisely measuring sedentary behavior (SB) is generally considered low. The angle for postural estimation (APE) method has shown promising accuracy in SB measurement. This method relies on the constant nature of Earth’s gravity and the assumption that walking posture is typically upright. This study investigated how cardiorespiratory fitness (CRF) and body mass index (BMI) are related to APE output. A total of 3475 participants with adequate accelerometer wear time were categorized into three groups according to CRF or BMI. Participants in low CRF and high BMI groups spent more time in reclining and lying postures (APE ≥ 30°) and less time in sitting and standing postures (APE < 30°) than the other groups. Furthermore, the strongest partial Spearman correlation with CRF (r = 0.284) and BMI (r = −0.320) was observed for APE values typical for standing. The findings underscore the utility of the APE method in studying associations between SB and health outcomes. Importantly, this study emphasizes the necessity of reserving the term “sedentary behavior” for studies wherein the classification of SB is based on both intensity and posture.

Background Longitudinal studies demonstrate an average decline in physical activity (PA) from adolescence to young adulthood. However, while some subgroups of adolescents decrease activity, others increase or maintain high or low activity. Activity domains may differ between subgroups (exhibiting different PA patterns), and they offer valuable information for targeted health promotion. Hence, the aim of this study was to identify PA patterns from adolescence to young adulthood; also to explore the associations of (i) changes in PA domains and in sedentary time, (ii) sociodemographic factors, and (iii) self-rated health with diverging PA patterns. Methods The observational cohort study data encompassed 254 adolescents at age 15 and age 19. K-means cluster analysis for longitudinal data was performed to identify participant clusters (patterns) based on their accelerometry-measured moderate-to-vigorous PA (MVPA). Logistic regressions were applied in further analysis. Results Five PA patterns were identified: inactivity maintainers ( n  = 71), activity maintainers ( n  = 70), decreasers from moderate (to low) PA ( n  = 61), decreasers from high (to moderate) PA ( n  = 32), and increasers ( n  = 20). At age 15, participation in sports clubs (SC, 41–97%) and active commuting (AC, 47–75%) was common in all the patterns. By age 19, clear dropout from these activities was prevalent (SC participation mean 32%, AC 31–63%). Inactivity maintainers reported the lowest amount of weekly school physical education. Dropout from SC – in contrast to non-participation in SC – was associated with higher odds of being a decreaser from high PA, and with lower odds of being an inactivity maintainer. Maintained SC participation was associated with higher odds of belonging to the decreasers from high PA, and to the combined group of activity maintainers and increasers; also with lower odds of being an inactivity maintainer. Maintenance/adoption of AC was associated with decreased odds of being an inactivity maintainer. Self-reported health at age 19 was associated with the patterns of maintained activity and inactivity. Conclusions PA patterns diverge over the transition to adulthood. Changes in SC participation and AC show different associations with diverging PA patterns. Hence, tailored PA promotion is recommended.

Estimation of oxygen consumption (VO2) from accelerometer data is typically based on prediction equations developed in laboratory settings using steadily paced and controlled test activities. These equations may not capture the temporary changes in VO2 occurring in sporadic real-life physical activity. In this study, we introduced a novel floating epoch for accelerometer data analysis and hypothesized that an adaptive epoch length provides a more consistent estimation of VO2 in irregular activity conditions than a 6 s constant epoch. Two different activity tests were conducted: a progressive constant-speed test (CS) performed on a track and a 6 min back-and-forth walk test including accelerations and decelerations (AC/DC) performed as fast as possible. Twenty-nine adults performed the CS test, and sixty-one performed the AC/DC test. The data were collected using hip-worn accelerometers and a portable metabolic gas analyzer. General linear models were employed to create the prediction models for VO2 that were cross-validated using both data sets and epoch types as training and validation sets. The prediction equations based on the CS test or AC/DC test and 6 s epoch had excellent performance (R2 = 89%) for the CS test but poor performance for the AC/DC test (31%). Only the VO2 prediction equation based on the AC/DC test and the floating epoch had good performance (78%) for both tests. The overall accuracy of VO2 prediction is compromised with the constant length epoch, whereas the prediction model based on irregular acceleration data analyzed with a floating epoch provided consistent performance for both activities.

Background Varying trends in children’s and adolescents’ physical activity (PA) have been reported during the last 10–20 years. Trends in sedentary behavior (SB) have been studied only rarely. The purpose of the present study was to describe population-based trends in accelerometer-measured PA, standing and SB, among Finnish 7-15-year-old children and adolescents, and to evaluate the potential influence of the COVID-19 pandemic on these behaviors. Method A cross-sectional population-based Finnish school-aged physical activity Study (FSPA) measured daily steps, vigorous (VPA), moderate (MPA), moderate-to-vigorous (MVPA), light physical activity (LPA), standing, and SB by an accelerometer for seven consecutive days in 2016, 2018, and 2022 ( n  = 7.080, 57% girls). The data was analyzed by multivariate regression analysis. Results In 2016, participants took on average 10.305 steps per day, and spent 0:15 (h: min) in VPA, 1:37 in MPA, 1:52 in MVPA, 3:48 in LPA, 0:55 in standing and 7:52 in SB. From 2016 to 2018, daily steps, MPA, LPA, and standing increased [229 steps (95% Confidence Interval, CI 70–387), 0:03 (CI 0:01 − 0:04), 0:11 (CI 0:09 − 0:14), and 0:07 (CI 0:05 − 0:08), respectively], while VPA and SB decreased [0:01 (CI 0:00–0:02) and 0:20 (CI 0:16 − 0:24), respectively]. From 2018 to 2022, daily PA and standing declined [751 steps (CI 562–939), VPA 0:02 (CI 0:01 − 0:03), MPA 0:09 (CI 0:07 − 0:11), MVPA 0:11 (CI 0:09 − 0:14), LPA 0:08 (CI 0:05 − 0:11), and standing 0:01 (CI 0:01 − 0:03)] while SB increased 0:21 (CI 0:16 − 0:25) indicating potential influence of the pandemic. Conclusions Children and adolescents became physically less active from 2016 to 2022. The potential effects of the COVID-19 were seen as declined PA and increased sedentariness from 2018 to 2022.

Background: The isokinetic dynamometry is considered a gold standard in muscle strength testing. The reliability of lower limb isokinetic strength measurements has not been thoroughly evaluated. Objective: To examine the test−retest reliability of isokinetic ankle plantar and dorsiflexion, ankle inversion and eversion, knee extension and flexion and hip abduction and adduction strength in physically active adults using Biodex System 4 Pro. Methods: Peak torques (PTs) and average peak torques (APTs) of the dominant and nondominant lower limbs were tested twice in 19 physically active adults 7 to 14 days apart. Results: The intraclass correlation coefficients (ICC) values varied from excellent to moderate and coefficient of variation of typical error (CVTE) values were 6.6–19.5%. Change in the mean expressed as a percent varied from −3.1% to 9.6%. There was no difference in the reliability between PT and APT values. Dominant lower limb was more reliable in every case if there was difference between limbs. Conclusion: Test−retest reliability of isokinetic ankle, knee and hip strength in physically active adults using Biodex System 4 is mostly good or excellent. However, the observed range of the random variation has to be noted when using it in scientific follow-up studies or evaluation of patient progress in clinical settings.

Accelerometer data can be used to estimate incident oxygen consumption (VO2) during physical activity. Relationships between the accelerometer metrics and VO2 are typically determined using specific walking or running protocols on a track or treadmill. In this study, we compared the predictive performance of three different metrics based on the mean amplitude deviation (MAD) of the raw three-dimensional acceleration signal during maximal tests performed on a track or treadmill. A total of 53 healthy adult volunteers participated in the study, 29 performed the track test and 24 the treadmill test. During the tests, the data were collected using hip-worn triaxial accelerometers and metabolic gas analyzers. Data from both tests were pooled for primary statistical analysis. For typical walking speeds at VO2 less than 25 mL/kg/min, accelerometer metrics accounted for 71–86% of the variation in VO2. For typical running speeds starting from VO2 of 25 mL/kg/min up to over 60 mL/kg/min, 32–69% of the variation in VO2 could be explained, while the test type had an independent effect on the results, except for the conventional MAD metrics. The MAD metric is the best predictor of VO2 during walking, but the poorest during running. Depending on the intensity of locomotion, the choice of proper accelerometer metrics and test type may affect the validity of the prediction of incident VO2.