Osteological profiling of femoral diaphysis and neck in aquatic, semiaquatic, and terrestrial carnivores and rodents: effects of body size and locomotor habits

The increased limb bone density documented previously for aquatic tetrapods has been proposed to be an adaptation to overcome buoyancy during swimming and diving. It can be achieved by increasing the amount of bone deposition or by reducing the amount of bone resorption, leading to cortical thickening, loss of medullary cavity, and compaction of trabecular bone. The present study examined the effects of locomotor habit, body size, and phylogeny on the densitometric, cross-sectional, and biomechanical traits of femoral diaphysis and neck in terrestrial, semiaquatic, and aquatic carnivores, and in terrestrial and semiaquatic rodents (12 species) by using peripheral quantitative computed tomography, three-point bending, and femoral neck loading tests. Groupwise differences were analyzed with the univariate generalized linear model and the multivariate linear discriminant analysis supplemented with hierarchical clustering. While none of the individual features could separate the lifestyles or species adequately, the combinations of multiple features produced very good or excellent classifications and clusterings. In the phocid seals, the aquatic niche allowed for lower femoral bone mineral densities than expected based on the body mass alone. The semiaquatic mammals mostly had high bone mineral densities compared to the terrestrial species, which could be considered an adaptation to overcome buoyancy during swimming and shallow diving. Generally, it seems that different osteological properties at the levels of mineral density and biomechanics could be compatible with the adaptation to aquatic, semiaquatic, or terrestrial niches.

Lifestyle and Cardiac Structure and Function in Healthy Midlife Population

The association between lifestyle and cardiac structure and function measures, such as global longitudinal strain and diastolic function in a healthy midlife general population, is not well known. A subpopulation of the Northern Finland Birth Cohort 1966 took part in follow-up, including echocardiography (n = 1,155) at the age of 46. All antihypertensive medication users (n = 164), patients with diabetes (n = 70), subjects with any cardiac diseases (n = 24), and subjects with echocardiography abnormalities (n = 21) were excluded. Moderate to vigorous physical activity (MVPA) was recorded with a wrist-worn accelerometer over 14 days and categorized into high, moderate, and low MVPA groups. Similarly, alcohol consumption was categorized as low, moderate, and high-dose users of alcohol and smoking as nonsmokers, former, and current smokers. The total number of healthy subjects included in the study was 715 (44% males). Left ventricular mass index and left atrial end-systolic volume index were significantly higher in the high MVPA group compared with the low MVPA group (adjusted main effect p = 0.002 and p <0.001, respectively). Cardiac function did not differ among the physical activity groups. High alcohol consumption was associated with impaired global longitudinal strain and diastolic function (adjusted main effect p = 0.002 and p = 0.004, respectively) but not with any cardiac structure variables. Smoking was not associated with cardiac structure or function. In healthy middle-aged adults, MVPA was independently associated with structural changes in the heart but not with cardiac function. High alcohol consumption was associated with impaired modern cardiac function measures but not with cardiac structure.

Comparison and agreement between device-estimated and self-reported sleep periods in adults

OBJECTIVES

Discriminating sleep period from accelerometer data remains a challenge despite many studies have adapted 24-h measurement protocols. We aimed to compare and examine the agreement among device-estimated and self-reported bedtime, wake-up time, and sleep periods in a sample of adults.

MATERIALS AND METHODS

Participants (108 adults, 61 females) with an average age of 33.1 (SD 0.4) were asked to wear two wearable devices (Polar Active and Ōura ring) simultaneously and record their bedtime and wake up time using a sleep diary. Sleep periods from Polar Active were detected using an in-lab algorithm, which is openly available. Sleep periods from Ōura ring were generated by commercial Ōura system. Scatter plots, Bland-Altman plots, and intraclass correlation coefficients (ICCs) were used to evaluate the agreement between the methods.

RESULTS

Intraclass correlation coefficient values were above 0.81 for bedtimes and wake-up times between the three methods. In the estimation of sleep period, ICCs ranged from 0.67 (Polar Active vs. sleep diary) to 0.76 (Polar Active vs. Ōura ring). Average difference between Polar Active and Ōura ring was -1.8 min for bedtimes and -2.6 min for wake-up times. Corresponding values between Polar Active and sleep diary were -5.4 and -18.9 min, and between Ōura ring and sleep diary -3.6 min and -16.2 min, respectively.

CONCLUSION

Results showed a high agreement between Polar Active activity monitor and Ōura ring for sleep period estimation. There was a moderate agreement between self-report and the two devices in estimating bedtime and wake-up time. These findings suggest that potentially wearable devices can be interchangeably used to detect sleep period, but their accuracy remains limited.Key MessagesEstimation of sleep period from different devices could be comparable.Difference between sleep periods from monitors and sleep diary are under 20 min.Device-based estimation of sleep period is encouraged in population-based studies.

Polycystic ovary syndrome is associated with weight-loss attempts and perception of overweight independent of BMI: a population-based cohort study

OBJECTIVE

Up to 70% of women with polycystic ovary syndrome (PCOS) have pre-obesity or obesity. The aim of this study was to investigate whether women with PCOS have more weight-loss attempts than women without PCOS, regardless of BMI. Moreover, women's weight perceptions in relation to previous weight-loss attempts were evaluated.

METHODS

A population-based birth cohort study included women with (n = 278) and without PCOS (control individuals, n = 1560) who were examined at ages 31 and 46 years with questionnaires and clinical examinations.

RESULTS

Women with PCOS had more weight-loss attempts compared with control individuals at age 31 (47% vs. 34%, p < 0.001) and 46 years (63% vs. 47%, p < 0.001). At age 46 years, PCOS was associated with multiple weight-loss attempts in the adjusted model (odds ratio: 1.43 [95% CI: 1.00-2.03], p = 0.05). The perception of having overweight was more prevalent in those with PCOS, even among participants with normal weight, at age 31 (PCOS 47% vs. control 34%, p = 0.014) and 46 years (PCOS 60% vs. control 39%, p = 0.001).

CONCLUSIONS

Women with PCOS were more likely to have experienced multiple weight-loss attempts and a perception of having overweight compared with control individuals, regardless of obesity status.

Replacing sedentary time with physical activity and sleep: Associations with cardiometabolic health markers in adults

This study aimed to examine the associations of sedentary time, and substituting sedentary time with physical activity and sleep, with cardiometabolic health markers while accounting for a full 24 h of movement and non-movement behaviors, cardiorespiratory fitness (CRF), and other potential confounders. The participants were 4585 members of the Northern Finland Birth Cohort 1966, who wore a hip-worn accelerometer at the age of 46 years for 14 consecutive days. Time spent in sedentary behaviors, light-intensity physical activity (LPA), and moderate-to-vigorous-intensity physical activity (MVPA) were determined from the accelerometer and combined with self-reported sleep duration to obtain the 24-h time use. CRF was estimated from the peak heart rate in a submaximal step test. An isotemporal substitution paradigm was used to examine how sedentary time and substituting sedentary time with an equal amount of LPA, MVPA, or sleep were associated with adiposity markers, blood lipid levels, and fasting glucose and insulin. Sedentary time was independently and adversely associated with the markers of cardiometabolic health, even after adjustment for CRF, but not in partition models including LPA, MVPA, sleep, and CRF. Substituting 60, 45, 30, and 15 min/day of sedentary time with LPA or MVPA was associated with 0.2%-13.7% favorable differences in the cardiometabolic health markers after accounting for LPA, MVPA, sleep, CRF, and other confounders. After adjustment for movement and non-movement behaviors within the 24-h cycle, reallocating additional time to both LPA and MVPA was beneficially associated with markers of cardiometabolic health in middle-aged adults regardless of their CRF level.

Compositional association of 24-h movement behavior with incident major adverse cardiac events and all-cause mortality

Cardiovascular disease (CVD) causes a high disease burden. Physical activity (PA) reduces CVD morbidity and mortality. We aimed to determine the relationship between the composition of moderate-to-vigorous PA (MVPA), light PA (LPA), sedentary behavior (SB), and sleep during midlife to the incidence of major adverse cardiac events (MACE) and all-cause mortality at a 7-year follow-up. The study population consisted of Northern Finland Birth Cohort 1966 members who participated in the 46-year follow-up in 2012 and were free of MACE (N = 4147). Time spent in MVPA, LPA, and SB was determined from accelerometer data. Sleep time was self-reported. Hospital visits and deaths were obtained from national registers. Participants were followed until December 31, 2019, or first MACE occurrence (acute myocardial infarction, unstable angina pectoris, stroke, hospitalization due to heart failure, or death due to CVD), death from another cause, or censoring. Cox proportional hazards model was used to estimate hazard ratios of MACE incidence and all-cause mortality. Isotemporal time reallocations were used to demonstrate the dose-response association between time spent in behaviors and outcome. The 24-h time composition was significantly associated with incident MACE and all-cause mortality. More time in MVPA relative to other behaviors was associated with a lower risk of events. Isotemporal time reallocations indicated that the greatest risk reduction occurred when MVPA replaced sleep. Higher MVPA associates with a reduced risk of incident MACE and all-cause mortality after accounting for the 24-h movement composition and confounders. Regular engagement in MVPA should be encouraged in midlife.

Effects of a home-based, exergaming intervention on physical function and pain after total knee replacement in older adults: a randomised controlled trial

Objectives

To investigate the effects of 4 months of customised, home-based exergaming on physical function and pain after total knee replacement (TKR) compared with standard exercise protocol.

Methods

In this non-blinded randomised controlled trial, 52 individuals aged 60-75 years undergoing TKR were randomised into an exergaming (intervention group, IG) or a standard exercising group (control group, CG). Primary outcomes were physical function and pain measured before and after (2 months and 4 months) surgery using the Oxford Knee Score (OKS) and Timed Up and Go (TUG) test. Secondary outcomes included measures of the Visual Analogue Scale, 10m walking, short physical performance battery, isometric knee extension and flexion force, knee range of movement and satisfaction with the operated knee.

Results

Improvement in mobility measured by TUG was greater in the IG (n=21) at 2 (p=0.019) and 4 months (p=0.040) than in the CG (n=25). The TUG improved in the IG by -1.9 s (95% CI, -2.9 to -1.0), while it changed by -0.6 s (95% CI -1.4 to 0.3) in the CG. There were no differences between the groups in the OKS or secondary outcomes over 4 months. 100% of patients in the IG and 74% in the CG were satisfied with the operated knee.

Conclusion

In patients who have undergone TKR, training at home with customised exergames was more effective in mobility and early satisfaction and as effective as standard exercise in pain and other physical functions. In both groups, knee-related function and pain improvement can be considered clinically meaningful.

Trial registration number

NCT03717727.

Effectiveness of Gamification in Knee Replacement Rehabilitation: Protocol for a Randomized Controlled Trial With a Qualitative Approach

BACKGROUND

Exergames can provide encouraging exercise options. Currently, there is limited evidence regarding home-based exergaming in the postoperative phase of total knee replacement (TKR).

OBJECTIVE

This study aimed to investigate the effects of a 4-month postoperative home-based exergame intervention with an 8-month follow-up on physical function and symptoms among older persons undergoing TKR compared with home exercise using a standard protocol. In addition, a concurrent embedded design of a mixed methods study was used by including a qualitative component within a quantitative study of exergame effects.

METHODS

This was a dual-center, nonblinded, two-arm, parallel group randomized controlled trial with an embedded qualitative approach. This study aimed to recruit 100 patients who underwent their first unilateral TKR (aged 60-75 years). Participants were randomized to the exergame or standard home exercise arms. Participants followed a custom-made exergame program independently at their homes daily for 4 months. The primary outcomes at 4 months were function and pain related to the knee using the Oxford Knee Score questionnaire and mobility using the Timed Up and Go test. Other outcomes, in addition to physical function, symptoms, and disability, were game user experience, exercise adherence, physical activity, and satisfaction with the operated knee. Assessments were performed at the preoperative baseline and at 2, 4, and 12 months postoperatively. Exergame adherence was followed from game computers and using a structured diary. Self-reported standard exercise was followed for 4 months of intervention and physical activity was followed for 12 months using a structured diary. Qualitative data on patients' perspectives on rehabilitation and exergames were collected through laddering interviews at 4 and 12 months.

RESULTS

This study was funded in 2018. Data collection began in 2019 and was completed in January 2022. The COVID-19 pandemic caused an unavoidable situation in the study for recruitment, data collection, and statistical analysis. As of November 2020, a total of 52 participants had been enrolled in the study. Primary results are expected to be published by the end of 2022.

CONCLUSIONS

Our study provides new knowledge on the effects of postoperative exergame intervention among older patients with TKR. In addition, this study provides a new understanding of gamified postoperative rehabilitation, home exercise adherence, physical function, and physical activity among older adults undergoing TKR.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03717727; https://clinicaltrials.gov/ct2/show/NCT03717727.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/38434.

Movement characteristics during customized exergames after total knee replacement in older adults

Introduction

There is limited understanding of how older adults can reach kinematic goals in rehabilitation while performing exergames and conventional exercises, and how similar or different the kinematics during exergaming are when compared with conventional therapeutic exercise with similar movement. The aim of this study was to describe the movement characteristics performed during exercise in custom-designed exergames and conventional therapeutic exercises among patients who have undergone unilateral total knee replacement (TKR). In addition, the secondary aim was to assess the relation of these exercise methods, and to assess participants' perceived exertion and knee pain during exergaming and exercising.

Materials and methods

Patients up to 4 months after the TKR surgery were invited in a single-visit exercise laboratory session. A 2D motion analysis and force plates were employed to evaluate movement characteristics as the volume, range, and intensity of movement performed during custom-designed knee extension-flexion and weight shifting exergames and conventional therapeutic exercises post TKR. The perceived exertion and knee pain were assessed using the Borg Rating of Perceived Exertion and Visual Analog Scale, respectively.

Results

Evaluation of seven patients with TKR [age median (IQR), 65 (10) years] revealed that the volume and intensity of movement were mostly higher during exergames. Individual goniometer-measured knee range of motion were achieved either with exergames and conventional therapeutic exercises, especially in knee extension exercises. The perceived exertion and knee pain were similar after exergames and conventional therapeutic exercises.

Conclusions

During custom-designed exergaming the patients with TKR achieve the movement characteristics appropriate for post-TKR rehabilitation without increasing the stress and pain experienced even though the movement characteristics might be partly different from conventional therapeutic exercises by the volume and intensity of movement. Physical therapists could consider implementing such exergames in rehabilitation practice for patients with TKR once effectiveness have been approved and they are widely available.

Accelerometer-measured physical activity is associated with knee breadth in middle-aged Finns - a population-based study

Background

Articular surface size is traditionally considered to be a relatively stable trait throughout adulthood. Increased joint size reduces bone and cartilage tissue strains. Although physical activity (PA) has a clear association with diaphyseal morphology, the association between PA and articular surface size is yet to be confirmed. This cross-sectional study aimed to clarify the role of moderate-to-vigorous PA (MVPA) in knee morphology in terms of tibiofemoral joint size.

Methods

A sample of 1508 individuals from the population-based Northern Finland Birth Cohort 1966 was used. At the age of 46, wrist-worn accelerometers were used to monitor MVPA (≥3.5 METs) during a period of two weeks, and knee radiographs were used to obtain three knee breadth measurements (femoral biepicondylar breadth, mediolateral breadth of femoral condyles, mediolateral breadth of the tibial plateau). The association between MVPA and knee breadth was analyzed using general linear models with adjustments for body mass index, smoking, education years, and accelerometer weartime.

Results

Of the sample, 54.8% were women. Most individuals were non-smokers (54.6%) and had 9—12 years of education (69.6%). Mean body mass index was 26.2 (standard deviation 4.3) kg/m². MVPA was uniformly associated with all three knee breadth measurements among both women and men. For each 60 minutes/day of MVPA, the knee breadth dimensions were 1.8—2.0% (or 1.26—1.42 mm) larger among women (p < 0.001) and 1.4—1.6% (or 1.21—1.28 mm) larger among men (p < 0.001).

Conclusions

Higher MVPA is associated with larger tibiofemoral joint size. Our findings indicate that MVPA could potentially increase knee dimensions through similar biomechanical mechanisms it affects diaphyseal morphology, thus offering a potential target in reducing tissue strains and preventing knee problems. Further studies are needed to confirm and investigate the association between articulation area and musculoskeletal health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05475-7.

Detecting hip osteoarthritis on clinical CT: a deep learning application based on 2-D summation images derived from CT

We developed and compared deep learning models to detect hip osteoarthritis on clinical CT. The CT-based summation images, CT-AP, that resemble X-ray radiographs can detect radiographic hip osteoarthritis and in the absence of large training data, a reliable deep learning model can be optimized by combining CT-AP and X-ray images.

INTRODUCTION

In this study, we aimed to investigate the applicability of deep learning (DL) to assess radiographic hip osteoarthritis (rHOA) on computed tomography (CT).

METHODS

The study data consisted of 94 abdominopelvic clinical CTs and 5659 hip X-ray images collected from Cohort Hip and Cohort Knee (CHECK). The CT slices were sequentially summed to create radiograph-like 2-D images named CT-AP. X-ray and CT-AP images were classified as rHOA if they had osteoarthritic changes corresponding to Kellgren-Lawrence grade 2 or higher. The study data was split into 55% training, 30% validation, and 15% test sets. A pretrained ResNet18 was optimized for a classification task of rHOA vs. no-rHOA. Five models were trained using (1) X-rays, (2) downsampled X-rays, (3) combination of CT-AP and X-ray images, (4) combination of CT-AP and downsampled X-ray images, and (5) CT-AP images.

RESULTS

Amongst the five models, Model-3 and Model-5 performed best in detecting rHOA from the CT-AP images. Model-3 detected rHOA on the test set of CT-AP images with a balanced accuracy of 82.2% and was able to discriminate rHOA from no-rHOA with an area under the receiver operating characteristic curve (ROC AUC) of 0.93 [0.75-0.99]. Model-5 detected rHOA on the test set at a balanced accuracy of 82.2% and classified rHOA from no-rHOA with an ROC AUC of 0.89 [0.67-0.97].

CONCLUSION

CT-based summation images that resemble radiographs can be used to detect rHOA. In addition, in the absence of large training data, a reliable DL model can be optimized by combining CT-AP and X-ray images.

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms

PURPOSE

Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction algorithms for activity class prediction from hip-based raw acceleration data.

METHODS

The hip-based raw acceleration data collected from 27 participants was split into training (70 %) and validation (30 %) subsets. A total of 206 time- (TD) and frequencydomain (FD) features were extracted from 6-second non-overlapping windows of the signal. Feature selection was done using seven filter-based, two wrapper-based, and one embedded algorithm, and classification was performed with artificial neural network (ANN), support vector machine (SVM), and random forest (RF). For every combination between the feature selection method and the classifiers, the most appropriate feature subsets were found and used for model training within the training set. These models were then validated with the left-out validation set.

RESULTS

The appropriate number of features for the ANN, SVM, and RF ranged from 20 to 45. Overall, the accuracy of all the three classifiers was higher when trained with feature subsets generated using filter-based methods compared with when they were trained with wrapper-based methods (range: 78.1 %-88 % vs. 66 %-83.5 %). TD features that reflect how signals vary around the mean, how they differ with one another, and how much and how often they change were more frequently selected via the feature selection methods.

CONCLUSIONS

A subset of TD features from raw accelerometry could be sufficient for ML-based activity classification if properly selected from different axes.

Leisure-time physical activity is associated with socio-economic status beyond income - Cross-sectional survey of the Northern Finland Birth Cohort 1966 study

We apply neoclassical economic modelling augmented with behavioral aspects to provide a detailed empirical investigation into indicators of socio-economic status (SES) as determinants of leisure-time physical activity. We utilize the data from the Northern Finland Birth Cohort 1966 obtained at the most recent time point during 2012-2014 (response rate 67 %), at which time the participants were approximately 46 years old. Our final study sample consists of 3,335 employed participants (1520 men, 1815 women; 32.3 % of the target population). We apply logistic regression methods for estimating how the probability of being physically active is related to various indicators of socio-economic status, taking into account physical activity at work and individual lifestyle, family- and health-related factors. Overall, our findings show that belonging to a higher socio-economic group, whether defined by income level, educational attainment, or occupational status, is associated with higher leisure-time physical activity. However, when we analyze different socio-economic groups, defined in terms of education, income and occupation, separately, we find that income is not a significant determinant of leisure-time physical activity within any of the particular SES groups. Further, we find that leisure-time physical activity is negatively associated with higher screen time (i.e., watching TV and sitting at a computer), and other aspects of unhealthy lifestyle, and positively associated with self-assessed health. In addition, we note that proxies for individual motivational factors and childhood physical activity, such as the grade point average and the grade achieved in physical education when leaving basic education, are strongly correlated with leisure-time physical activity in middle age among men, but not among women. Our results are in line with behavioral economics reasoning that social comparisons and environments affect behaviors. We emphasize the importance of considering behavioral economic factors when designing policies to promote physical activity.

Accumulation patterns of sedentary time and breaks and their association with cardiometabolic health markers in adults

Breaking up sedentary time with physical activity (PA) could modify the detrimental cardiometabolic health effects of sedentary time. Our aim was to identify profiles according to distinct accumulation patterns of sedentary time and breaks in adults, and to investigate how these profiles are associated with cardiometabolic outcomes. Participants (n = 4439) of the Northern Finland Birth Cohort 1966 at age 46 years wore a hip-worn accelerometer for 7 consecutive days during waking hours. Uninterrupted ≥1-min sedentary bouts were identified, and non-sedentary bouts in between two consecutive sedentary bouts were considered as sedentary breaks. K-means clustering was performed with 65 variables characterizing how sedentary time was accumulated and interrupted. Linear regression was used to determine the association of accumulation patterns with cardiometabolic health markers. Four distinct groups were formed as follows: "Couch potatoes" (n = 1222), "Prolonged sitters" (n = 1179), "Shortened sitters" (n = 1529), and "Breakers" (n = 509). Couch potatoes had the highest level of sedentariness and the shortest sedentary breaks. Prolonged sitters, accumulating sedentary time in bouts of ≥15-30 min, had no differences in cardiometabolic outcomes compared with Couch potatoes. Shortened sitters accumulated sedentary time in bouts lasting <15 min and performed more light-intensity PA in their sedentary breaks, and Breakers performed more light-intensity and moderate-to-vigorous PA. These latter two profiles had lower levels of adiposity, blood lipids, and insulin sensitivity, compared with Couch potatoes (1.1-25.0% lower values depending on the cardiometabolic health outcome, group, and adjustments for potential confounders). Avoiding uninterrupted sedentary time with any active behavior from light-intensity upwards could be beneficial for cardiometabolic health in adults.

Association Between Vertebral Dimensions and Lumbar Modic Changes

STUDY DESIGN

Population-based birth cohort study.

OBJECTIVE

The aim of this study was to evaluate the relationship between vertebral dimensions and lumbar MC.

SUMMARY OF BACKGROUND DATA

Low back pain (LBP) has become the leading cause of disability worldwide. Modic changes (MC) of the lumbar spine are one potential LBP-associated etiological factor. Mechanical stress is considered to play a key role in the development of MC through damage to endplates. There is speculation that vertebral dimensions play a role in some degenerative changes in the spine. Previous studies have also shown a positive association between moderate-to-vigorous physical activity (MVPA) and both vertebral dimensions and MC. In this study, we aimed to evaluate the relationship between vertebral dimensions and MC.

METHODS

The study population consisted of 1221 participants from the Northern Finland Birth Cohort 1966 who underwent lumbar magnetic resonance imaging (MRI) and physical activity measurements at the age of 46-48. The presence of Type 1 (MC1) and Type 2 (MC2) MC and the height, axial cross-sectional area (CSA), and volume of the L4 vertebra were determined from MRI scans. MVPA (≥3.5 metabolic equivalents) was measured by a wrist-worn accelerometer. We analyzed the association between lumbar MC and vertebral height, CSA, and volume using logistic regression models before and after adjustment for sex, height, weight, smoking, education level, and MVPA.

RESULTS

Vertebral height was positively associated with the presence of MC2 (odds ratio [OR] 3.51; 95% confidence interval [CI] 1.43-8.65), whereas vertebral CSA was not associated with the presence of lumbar MC. Vertebral volume was positively associated with the presence of any MC (OR 1.04; 95% CI 1.00-1.07), but the association did not persist when analyzing MC1 and MC2 separately.

CONCLUSION

Vertebral height was associated with the presence of MC2. Further studies are needed to clarify the role of vertebral dimensions as independent risk factors for MC.Level of Evidence: 3.

Discrimination of Low-Energy Acetabular Fractures from Controls Using Computed Tomography-Based Bone Characteristics

The incidence of low-energy acetabular fractures has increased. However, the structural factors for these fractures remain unclear. The objective of this study was to extract trabecular bone architecture and proximal femur geometry (PFG) measures from clinical computed tomography (CT) images to (1) identify possible structural risk factors of acetabular fractures, and (2) to discriminate fracture cases from controls using machine learning methods. CT images of 107 acetabular fracture subjects (25 females, 82 males) and 107 age-gender matched controls were examined. Three volumes of interest, one at the acetabulum and two at the femoral head, were extracted to calculate bone volume fraction (BV/TV), gray-level co-occurrence matrix and histogram of the gray values (GV). The PFG was defined by neck shaft angle and femoral neck axis length. Relationships between the variables were assessed by statistical mean comparisons and correlation analyses. Bayesian logistic regression and Elastic net machine learning models were implemented for classification. We found lower BV/TV at the femoral head (0.51 vs. 0.55, p = 0.012) and lower mean GV at both the acetabulum (98.81 vs. 115.33, p < 0.001) and femoral head (150.63 vs. 163.47, p = 0.005) of fracture subjects when compared to their matched controls. The trabeculae within the femoral heads of the acetabular fracture sides differed in structure, density and texture from the corresponding control sides of the fracture subjects. Moreover, the PFG and trabecular architectural variables, alone and in combination, were able to discriminate fracture cases from controls (area under the receiver operating characteristics curve 0.70 to 0.79). In conclusion, lower density in the acetabulum and femoral head with abnormal trabecular structure and texture at the femoral head, appear to be risk factors for low-energy acetabular fractures.

Polygenic Risk Scores and Physical Activity

Supplemental digital content is available in the text.

Purpose

Polygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples.

Methods

We calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC; N = 759–11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966; N = 3263–4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC.

Results

The PRS accounted from 0.07% to 1.44% of the variation (R²) in the self-reported and objectively measured PA volumes (P value range = 0.023 to <0.0001) in the FTC and NFBC1966. For both self-reported and objectively measured PA, individuals in the highest PRS deciles had significantly (11%–28%) higher PA volumes compared with the lowest PRS deciles (P value range = 0.017 to <0.0001).

Conclusions

PA is a multifactorial phenotype, and the PRS constructed based on UK Biobank results accounted for statistically significant but overall small proportion of the variation in PA in the Finnish cohorts. Using identical methods to assess PA and including less common and rare variants in the construction of PRS may increase the proportion of PA explained by the PRS.

Association between device-measured physical activity and lumbar Modic changes

Background

Modic changes (MC) in the lumbar spine are considered one potential etiological factor behind low back pain (LBP). Multiple risk factors for MC have been suggested, including male gender, smoking and factors affecting hyperloading and mechanical stress such as high body mass index (BMI), strenuous physical work and high occupational and leisure-time physical activity (PA). So far, the effect of PA on the occurrence of MC has remained under debate due to contradictory findings. The purpose of this study was to investigate the possible association between device-measured moderate-to-vigorous PA (MVPA) (≥ 3.5 METs) and lumbar MC.

Methods

The study had 1374 participants from the Northern Finland Birth Cohort 1966. At the age of 46–48, PA was measured by a wrist-worn accelerometer, and lumbar magnetic resonance imaging (MRI) was carried out to determine MC. We analyzed the association between Type 1 (MC1) and Type 2 (MC2) MC and daily amount of MVPA (min/day) using sex-stratified logistic regression models before and after adjustment for BMI, socioeconomic status, smoking, and accelerometer wear time.

Results

Among men, increased amount of MVPA was positively associated with any MC (adjusted OR corresponding to every 60 min/day of MVPA 1.41; 95% confidence interval (CI) 1.01 to 1.95) and MC2 (OR 1.54; 95% CI 1.14 to 2.08), but not with MC1 (OR 1.06; 95% CI 0.80 to 1.39). Among women, we only found a positive association between MVPA and MC1 before adjustments (unadjusted OR 1.42; 95% CI 1.06 to 1.92).

Conclusion

Among men, increased amount of MVPA was associated with increased odds of any MC and particularly MC2. Among women, MVPA was not independently associated with MC.

Correlates of physical activity behavior in adults: a data mining approach

PURPOSE

A data mining approach was applied to establish a multilevel hierarchy predicting physical activity (PA) behavior, and to methodologically identify the correlates of PA behavior.

METHODS

Cross-sectional data from the population-based Northern Finland Birth Cohort 1966 study, collected in the most recent follow-up at age 46, were used to create a hierarchy using the chi-square automatic interaction detection (CHAID) decision tree technique for predicting PA behavior. PA behavior is defined as active or inactive based on machine-learned activity profiles, which were previously created through a multidimensional (clustering) approach on continuous accelerometer-measured activity intensities in one week. The input variables (predictors) used for decision tree fitting consisted of individual, demographical, psychological, behavioral, environmental, and physical factors. Using generalized linear mixed models, we also analyzed how factors emerging from the model were associated with three PA metrics, including daily time (minutes per day) in sedentary (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA), to assure the relative importance of methodologically identified factors.

RESULTS

Of the 4582 participants with valid accelerometer data at the latest follow-up, 2701 and 1881 had active and inactive profiles, respectively. We used a total of 168 factors as input variables to classify these two PA behaviors. Out of these 168 factors, the decision tree selected 36 factors of different domains from which 54 subgroups of participants were formed. The emerging factors from the model explained minutes per day in SED, LPA, and/or MVPA, including body fat percentage (SED: B = 26.5, LPA: B = - 16.1, and MVPA: B = - 11.7), normalized heart rate recovery 60 s after exercise (SED: B = -16.1, LPA: B = 9.9, and MVPA: B = 9.6), average weekday total sitting time (SED: B = 34.1, LPA: B = -25.3, and MVPA: B = -5.8), and extravagance score (SED: B = 6.3 and LPA: B = - 3.7).

CONCLUSIONS

Using data mining, we established a data-driven model composed of 36 different factors of relative importance from empirical data. This model may be used to identify subgroups for multilevel intervention allocation and design. Additionally, this study methodologically discovered an extensive set of factors that can be a basis for additional hypothesis testing in PA correlates research.

Association between chronic diseases and falls among a sample of older people in Finland

Background

Falls are a major problem for older people and recurrent fallers are especially prone to severe consequences due to falls. This study investigated the association between chronic conditions and falls.

Methods

Responses from 872 older persons (age 65–98) to a health questionnaire were used in the analyses. Characteristics and disease prevalence between recurrent fallers, one-time fallers and non-fallers were compared. A hierarchical clustering method was applied to find combinations of chronic conditions that were associated with recent recurrent falling.

Results

The results showed that recurrent fallers had a higher number of diseases (median 4, interquartile range, IQR = 2.0–5.0) compared to non-fallers (median 2, IQR = 1.0–3.0). Eight clusters were formed based on the data. The participants in the low chronic disease cluster were younger, more physically active, not frail, and had fewer geriatric conditions. Multiple chronic disease cluster participants were older, less physically active, overweight (body mass index, BMI > 30), at risk of malnutrition, and had more geriatric conditions. Significantly increased risk of recurrent falls relative to the low chronic cluster was found for respondents in the osteoporosis cluster and multiple chronic disease cluster (OR = 5.65, 95% confidence interval CI: 1.23–25.85, p = 0.026, and OR = 13.42, 95% CI: 2.47–72.96, p = 0.002, respectively). None of the clusters were associated with increased risk of one-time falling.

Conclusions

The results implicate that the number of chronic diseases is related with risk of recurrent falling. Furthermore, the results implicate the potential of identifying certain combinations of chronic diseases that increase fall risk by analyzing health record data, although further studies are needed with a larger population sample.

A Persuasive mHealth Behavioral Change Intervention for Promoting Physical Activity in the Workplace: Feasibility Randomized Controlled Trial

Background

Employees in an office setting are more likely to remain physically inactive. Physical inactivity has become one of the major barriers to overcoming the risk factors for anxiety, depression, coronary heart disease, certain cancers, and type 2 diabetes. Currently, there is a gap in mobile health (mHealth) apps to promote physical activity (PA) for workers in the workplace. Studies on behavior change theories have concluded that health apps generally lack the use of theoretical constructs.

Objective

The objective of this study was to study the feasibility of a persuasive app aimed at encouraging PA among employees and to understand the motivational aspects behind the implementation of mHealth apps among office workers.

Methods

A 4-week study using a mixed methods (quantitative and qualitative) design was conducted with office-based employees in cities in 4 countries: Oulu, Finland; Carlow, Ireland; London, United Kingdom; and Dhaka, Bangladesh. Of the 220 invited participants (experimental group, n=115; control group, n=105), 84 participated (experimental group, n=56; control group, n=28), consisting of working-age volunteers working in an office setting. Participants used 2 different interventions: The experimental group used an mHealth app for PA motivation, and the control group used a paper diary. The purpose was to motivate employees to engage in healthier behavior regarding the promotion of PA in the workplace. A user-centered design process was followed to design, develop, and evaluate the mHealth app, incorporating self-determination theory (SDT) and using game elements. The paper diary had no specific theory-driven approach, design technique, nor game elements.

Results

Compliance with app usage remained relatively low, with 27 participants (experimental group, n=20; control group, n=7) completing the study. The results support the original hypothesis that the mHealth app would help increase PA (ie, promoting daily walking in the workplace) in comparison to a paper diary (P=.033). The mHealth app supported 2 of the basic SDT psychological needs, namely autonomy (P=.004) and competence (P=.014), but not the needs of relatedness (P=.535).

Conclusions

The SDT-based mHealth application motivated employees to increase their PA in the workplace. However, compliance with app usage remained low. Future research should further develop the app based on user feedback and test it in a larger sample.

Nocturnal finger skin temperature in menstrual cycle tracking: ambulatory pilot study using a wearable Oura ring

Background

Body temperature is a common method in menstrual cycle phase tracking because of its biphasic form. In ambulatory studies, different skin temperatures have proven to follow a similar pattern. The aim of this pilot study was to assess the applicability of nocturnal finger skin temperature based on a wearable Oura ring to monitor menstrual cycle and predict menstruations and ovulations in real life.

Methods

Volunteer women (n = 22) wore the Oura ring, measured ovulation through urine tests, and kept diaries on menstruations at an average of 114.7 days (SD 20.6), of which oral temperature was measured immediately after wake-up at an average of 1.9 cycles (SD 1.2). Skin and oral temperatures were compared by assessing daily values using repeated measures correlation and phase mean values and differences between phases using dependent t-test. Developed algorithms using skin temperature were tested to predict the start of menstruation and ovulation. The performance of algorithms was assessed with sensitivity and positive predictive values (true positive defined with different windows around the reported day).

Results

Nocturnal skin temperatures and oral temperatures differed between follicular and luteal phases with higher temperatures in the luteal phase, with a difference of 0.30 °C (SD 0.12) for skin and 0.23 °C (SD 0.09) for oral temperature (p < 0.001). Correlation between skin and oral temperatures was found using daily temperatures (r = 0.563, p < 0.001) and differences between phases (r = 0.589, p = 0.004). Menstruations were detected with a sensitivity of 71.9–86.5% in window lengths of ±2 to ±4 days. Ovulations were detected with the best-performing algorithm with a sensitivity of 83.3% in fertile window from − 3 to + 2 days around the verified ovulation. Positive predictive values had similar percentages to those of sensitivities. The mean offset for estimations were 0.4 days (SD 1.8) for menstruations and 0.6 days (SD 1.5) for ovulations with the best-performing algorithm.

Conclusions

Nocturnal skin temperature based on wearable ring showed potential for menstrual cycle monitoring in real life conditions.

Residential relocation trajectories and neighborhood density, mixed land use and access networks as predictors of walking and bicycling in the Northern Finland Birth Cohort 1966

Background

Given the high global prevalence of physical inactivity, there is a need to design cities that support active modes of transportation. High density diverse neighborhoods with good access networks have been associated with enhanced walking and cycling, but there is a lack of large-scale longitudinal studies utilizing a life course perspective to model residential relocation trajectories. The objectives of the present longitudinal study were to model and visualize residential relocation trajectories between 31 and 46 years of age based on neighborhood density, mixed land use and access networks (DMA), and to assess neighborhood DMA as a predictor of self-reported regular walking and cycling and objectively measured physical activity.

Methods

Based on data from the Northern Finland Birth Cohort 1966 (N = 5947), we used self-reported regular walking and cycling and objectively measured physical activity as outcome variables and objectively assessed neighborhood DMA as the main explanatory variable. We conducted sequence analysis to model residential relocation trajectories, and generalized linear mixed models and Fisher’s exact test were used to explore longitudinal associations between neighborhood DMA and physical activity.

Results

Over 80% of the participants lived in a neighborhood with the same level of neighborhood DMA during the follow-up. Relocation occurred more often from higher to lower DMA neighborhoods than reverse. Increased neighborhood DMA was associated with increased regular walking (OR 1.03; 95% CI: 1.00, 1.05; p = 0.023) and cycling (OR 1.17; 95% CI: 1.12, 1.23; p <  0.001). Residential relocation trajectory from lower to highest neighborhood DMA increased the odds of starting regular walking (OR 3.15; 95% CI: 1.50, 7.14; p = 0.001) and cycling (OR 2.63; 95% CI: 1.23, 5.79; p = 0.009) as compared to higher to lower neighborhood DMA trajectory.

Conclusions

The results strongly support the hypothesis that increasing urban DMA can enhance regular walking and cycling at population level and so improve public health. The findings have implications for zoning and transportation policies, favoring the creation of dense and diverse neighborhoods with good access networks to support regular walking and cycling.

Structural risk factors for low-energy acetabular fractures

In this study, we aimed to clarify proximal femur and acetabular structural risk factors associated with low-energy acetabular fractures in the elderly using three-dimensional (3D) computed tomography (CT). Pelvic bones and femurs were segmented and modeled in 3D from abdominopelvic CT images of 121 acetabular fracture patients (mean age 72 ± 12 years, range 50-98 years, 31 females and 90 males) and 121 age-gender matched controls with no fracture. A set of geometric parameters of the proximal femur and the acetabulum was measured. An independent-samples t-test or a Mann-Whitney U test was used for statistical analyses. The fractured side was used for proximal femur geometry, while the contralateral side was used for acetabular geometry. The neck shaft angle (NSA) was significantly smaller (mean 122.1° [95% CI 121.1°-123.2°] vs. 124.6° [123.6°-125.6°], p = 0.001) and the femoral neck axis length (FNALb) was significantly longer (78.1 mm [77.0-79.2 mm] vs. 76.0 mm [74.8-77.2 mm], p = 0.026) in the fracture group than in the controls when genders were combined. The NSA was significantly smaller both for females (120.2° [117.8°-122.6°] vs. 124.7° [122.5°-127.0°], p = 0.007) and for males (122.7° [121.5°-123.8°] vs. 124.6° [123.4°-125.7°], p = 0.006) in the fracture group. However, only males showed a significantly longer FNALb (80.0 mm [78.9-81.1 mm] vs. 77.8 mm [76.6-79.0 mm], p = 0.025). No statistically significant associations of acetabular geometry with fractures were found. However, the mean values of the acetabular angle of Sharp (34°), the lateral center-edge angle (40°), the anterior center-edge angle (62°), and the posterior center-edge angle (105°) indicated possible over-coverage. In conclusion, our findings suggest that proximal femur geometry is associated with low-energy acetabular fractures. Especially elderly subjects with an NSA smaller than normal have an increased risk of acetabular fractures.

Intensity and temporal patterns of physical activity and cardiovascular disease risk in midlife

Physical activity (PA) and sedentary time (SED) are associated with the risk of cardiovascular disease (CVD), but the temporal patterns of these behaviors most beneficial for cardiovascular health remain unknown. We aimed to identify the intensity and temporal patterns of PA and SED measured continuously by an accelerometer and their relationship with CVD risk. At the age of 46 years, 4582 members (1916 men; 2666 women) of the Northern Finland Birth Cohort 1966 study underwent continuous measurement of PA with Polar Active (Polar Electro, Finland) accelerometers for one week. X-means clustering was applied based on 10 min average MET (metabolic equivalent) values during the measurement period. Ten-year risk of CVD was estimated using the Framingham risk model. Most of the participants had low risk for CVD. Four distinct PA clusters were identified that were well differentiable by the intensity and temporal patterns of activity (inactive, evening active, moderately active, very active). A significant difference in 10-year CVD risk across the clusters was found in men (p = 0.028) and women (p < 0.001). Higher levels of HDL cholesterol were found in more active clusters compared to less active clusters (p < 0.001) in both genders. In women total cholesterol was lower in the moderately active cluster compared to the inactive and evening active clusters (p = 0.001). Four distinct PA clusters were recognized based on accelerometer data and X-means clustering. A significant difference in CVD risk across the clusters was found in both genders. These results can be used in developing and promoting CVD prevention strategies.

Effect of Physical Activity on Plasma PCSK9 in Subjects With High Risk for Type 2 Diabetes

Background

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a liver serine protease regulating LDL cholesterol metabolism. PCSK9 binds to LDL receptors and guides them to lysosomes for degradation, thus increasing the amount of circulating LDL cholesterol. The aim of the study was to investigate associations between physical activity and plasma PCSK9 in subjects with high risk for type 2 diabetes (T2D).

Methods

Sixty-eight subjects from both genders with a high risk for T2D were included to a randomized controlled trial with a 3-month physical activity intervention. Physical activity intensities and frequencies were monitored throughout the intervention using a hip worn portable accelerometer. The plasma was collected before and after intervention for analysis of PCSK9 and cardiovascular biomarkers.

Results

Plasma PCSK9 did not relate to physical activity although number of steps were 46% higher in the intervention group than in the control group (p < 0.029). Total cholesterol was positively correlated with plasma PCSK9 (R = 0.320, p = 0.008), while maximal oxygen uptake was negatively associated (R = -0.252, p = 0.044). After the physical activity intervention PCSK9 levels were even stronger inversely associated with maximal oxygen uptake (R = -0.410, p = 0.0008) and positively correlated with HDL cholesterol (R = 0.264, p = 0.030). Interestingly, plasma PCSK9 levels were higher in the beginning than at the end of the study.

Conclusion

The low physical activity that our subjects with high risk for T2D could perform did not influence plasma PCSK9 levels. Intervention with higher physical activities might be more effective in influencing PCSK9 levels.

Technologies for fall risk assessment and conceptual design in personal health record system

Falls among older people are a major economic and public health problem. Due to the demographic change and aging of populations, there is an urgent need for accurate screening tools to identify those at risk to target effective falls prevention strategies. Clinical fall risk assessments are costly and time-consuming and thus cannot be performed frequently. Technologies provide means for assessing fall risk during daily living, making self-evaluations and fast methods for fall risk assessment for professional use. This study collects and evaluates existing technological solutions for fall risk assessment including various different sensor technologies. The study also presents one easy to use solution for assessing fall risk and suggests a concept-design for integrating sensor-based solutions into the Finnish national Kanta Personal Health Record. The optimal solution for technological fall risk assessment is still unclear. A wide implementation still requires extensive validation studies, adoption to health care processes and novel IoT -solutions for collecting large amounts of sensor data. Thorough methods should be utilised in designing the privacy and security aspects of fall risk assessment solutions, as well as different user profiles, to allow suitable interfaces and visualisations to users. It should always be clear what kind of data are collected from users and how the data are utilised. The consent of the users should also always be collected.

Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

BACKGROUND

Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration.

OBJECTIVE

To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy.

METHODS

A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied.

RESULTS

Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression.

CONCLUSIONS

Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.

Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches

BACKGROUND

Objective measures using accelerometer-based activity monitors have been extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure PA and SB precisely, the field is shifting towards machine learning-based (ML) approaches for calibration and validation of accelerometer-based activity monitors. Nevertheless, various parameters regarding the use and development of ML-based models, including data type (raw acceleration data versus activity counts), sampling frequency, window size, input features, ML technique, accelerometer placement, and free-living settings, affect the predictive ability of ML-based models. The effects of these parameters on ML-based models have remained elusive, and will be systematically reviewed here. The open challenges were identified and recommendations are made for future studies and directions.

METHOD

We conducted a systematic search of PubMed and Scopus databases to identify studies published before July 2017 that used ML-based techniques for calibration and validation of accelerometer-based activity monitors. Additional articles were manually identified from references in the identified articles.

RESULTS

A total of 62 studies were eligible to be included in the review, comprising 48 studies that calibrated and validated ML-based models for predicting the type and intensity of activities, and 22 studies for predicting activity energy expenditure.

CONCLUSIONS

It appears that various ML-based techniques together with raw acceleration data sampled at 20-30 Hz provide the opportunity of predicting the type and intensity of activities, as well as activity energy expenditure with comparable overall predictive accuracies regardless of accelerometer placement. However, the high predictive accuracy of laboratory-calibrated models is not reproducible in free-living settings, due to transitive and unseen activities together with differences in acceleration signals.

Associations of fitness and physical activity with orthostatic responses of heart rate and blood pressure at midlife

Cardiorespiratory fitness (CRF) and physical activity (PA) are associated with autonomic function, but their associations to orthostatic autonomic responses are unclear in epidemiological setting. We hypothesized that higher CRF and PA would associate with higher immediate vagal responses and lower incidence of adverse findings during orthostatic test. At age of 46, 787 men and 938 women without cardiorespiratory diseases and diabetes underwent an orthostatic test (3-minutes sitting, 3-minutes standing) with recording of RR intervals (RRi) and blood pressure (BP) by finger plethysmography. Acute responses of RRi (30:15 ratio) and BP were calculated. CRF was measured by a submaximal step test and daily amount of moderate-to-vigorous PA (MVPA) for 2 weeks by wrist-worn accelerometer. Lifelong PA was based on questionnaires at ages of 14, 31, and 46. High CRF was significantly associated with higher RRi 30:15 ratio (adjusted standardized β = 0.17, P < 0.001) and milder acute decrease of systolic BP while standing (β = 0.10, P = 0.001), while MVPA was not (β = 0.04 for RRi 30:15 ratio and β = 0.05 for systolic BP acute response). High lifelong PA was significantly associated with higher RRi 30:15 ratio (β = 0.08, P = 0.002) but not with acute systolic BP response. Those in the lowest tertile of CRF had 9.2-fold risk (P = 0.002) of having postural orthostatic tachycardia syndrome compared to more fit. Cardiorespiratory fitness and lifelong physical activity, but not current physical activity, were independently associated with higher cardiac vagal response to orthostasis. The present results underscore the importance fitness and lifelong physical activity in prevention of abnormal autonomic function and related cardiovascular risk.

Feasibility of mobile mental wellness training for older adults

Mobile technology has been increasingly adopted in promotion of mental health among older people. This study assessed the feasibility of a mobile mental wellness training application for individual use and for group work from the perspectives of older adults and social care professionals. The older individuals recruited for the study were participants in a Circle of Friends group and family caregivers' peer support group offered by the communal senior services. The qualitative and quantitative results of interviews, questionnaires, observation, and application usage were reported. Seven older adults started using the application independently at home in parallel with the group activity. This study revealed new information regarding the barriers to the older adults' full adoption of such mobile technologies. The results indicated that there may be potential in the incorporation of mobile technologies in promotion of mental health of older people at group settings.

Fitness, Fatness, Physical Activity, and Autonomic Function in Midlife

PURPOSE

Although low cardiorespiratory fitness (CRF), physical inactivity, and obesity are associated with impaired autonomic function, they are also extensively interrelated. The present study aimed to assess the extent to which they contribute to autonomic function independently of each other.

METHODS

At the age of 46 yr, 1383 men and 1761 women without cardiorespiratory diseases and diabetes underwent assessments of vagally mediated heart rate (HR) variability (root mean square of successive differences in R-R interval (rMMSD)), peak HR during a submaximal step test (CRF), and 60-s HR recovery (HRR). Moderate-to-vigorous physical activity (MVPA; ≥3.5 METs, 2 wk) was measured by wrist-worn accelerometer and body fat percentage (Fat%) by bioimpedance.

RESULTS

In men, CRF and Fat% were significantly associated with higher rMSSD (standardized β = 0.31 and -0.16) and HRR (β = 0.19 and -0.18), whereas higher MVPA was linked with higher HRR (β = 0.13) when including CRF, MVPA, and Fat% in the initial regression. After adjustments for other lifestyle and cardiometabolic factors, CRF remained significantly associated with rMMSD (β = 0.24) and HRR (β = 0.14), as did MVPA with HRR (β = 0.11). In women, CRF was associated with rMSSD (β = 0.23) and HRR (β = 0.15), and MVPA (β = 0.17) and Fat% (β = -0.07) with HRR, when CRF, MVPA, and Fat% were adjusted for each other. After further adjustments, CRF remained a significant determinant of rMSSD (β = 0.20) and HRR (β = 0.13), as did MVPA with HRR (β = 0.15). The final models explained 23% and 21% of variation in rMSSD and HRR in men, and 10% and 12% in women, respectively.

CONCLUSIONS

CRF was a more important determinant of cardiac autonomic function than MVPA and body fat. Furthermore, MVPA but not body fat was independently associated with cardiac autonomic function in both men and women.

Feasibility of Gamified Mobile Service Aimed at Physical Activation in Young Men: Population-Based Randomized Controlled Study (MOPO)

Background

The majority of young people do not meet the recommendations on physical activity for health. New innovative ways to motivate young people to adopt a physically active lifestyle are needed.

Objective

The study aimed to study the feasibility of an automated, gamified, tailored Web-based mobile service aimed at physical and social activation among young men.

Methods

A population-based sample of 496 young men (mean age 17.8 years [standard deviation 0.6]) participated in a 6-month randomized controlled trial (MOPO study). Participants were randomized to an intervention (n=250) and a control group (n=246). The intervention group was given a wrist-worn physical activity monitor (Polar Active) with physical activity feedback and access to a gamified Web-based mobile service, providing fitness guidelines, tailored health information, advice of youth services, social networking, and feedback on physical activity. Through the trial, the physical activity of the men in the control group was measured continuously with an otherwise similar monitor but providing only the time of day and no feedback. The primary outcome was the feasibility of the service based on log data and questionnaires. Among completers, we also analyzed the change in anthropometry and fitness between baseline and 6 months and the change over time in weekly time spent in moderate to vigorous physical activity.

Results

Mobile service users considered the various functionalities related to physical activity important. However, compliance of the service was limited, with 161 (64.4%, 161/250) participants visiting the service, 118 (47.2%, 118/250) logging in more than once, and 41 (16.4%, 41/250) more than 5 times. Baseline sedentary time was higher in those who uploaded physical activity data until the end of the trial (P=.02). A total of 187 (74.8%, 187/250) participants in the intervention and 167 (67.9%, 167/246) in the control group participated in the final measurements. There were no differences in the change in anthropometry and fitness from baseline between the groups, whereas waist circumference was reduced in the most inactive men within the intervention group (P=.01). Among completers with valid physical activity data (n=167), there was a borderline difference in the change in mean daily time spent in moderate to vigorous physical activity between the groups (11.9 min vs −9.1 min, P=.055, linear mixed model). Within the intervention group (n=87), baseline vigorous physical activity was inversely associated with change in moderate to vigorous physical activity during the trial (R=−.382, P=.01).

Conclusions

The various functionalities related to physical activity of the gamified tailored mobile service were considered important. However, the compliance was limited. Within the current setup, the mobile service had no effect on anthropometry or fitness, except reduced waist circumference in the most inactive men. Among completers with valid physical activity data, the trial had a borderline positive effect on moderate to vigorous physical activity. Further development is needed to improve the feasibility and adherence of an integrated multifunctional service.

Trial registration

Clinicaltrials.gov NCT01376986; http://clinicaltrials.gov/ct2/show/NCT01376986 (Archived by WebCite at http://www.webcitation.org/6tjdmIroA)

Low level activity thresholds for changes in NMR biomarkers and genes in high risk subjects for Type 2 Diabetes

Our objectives were to determine if there are quantitative associations between amounts and intensities of physical activities (PA) on NMR biomarkers and changes in skeletal muscle gene expressions in subjects with high risk for type 2 diabetes (T2D) performing a 3-month PA intervention. We found that PA was associated with beneficial biomarker changes in a factor containing several VLDL and HDL subclasses and lipids in principal component analysis (P = <0.01). Division of PA into quartiles demonstrated significant changes in NMR biomarkers in the 2nd - 4th quartiles compared to the 1st quartile representing PA of less than 2850 daily steps (P = 0.0036). Mediation analysis of PA-related reductions in lipoproteins showed that the effects of PA was 4-15 times greater than those of body weight or fat mass reductions. In a subset study in highly active subjects' gene expressions of oxidative fiber markers, Apo D, and G0/G1 Switch Gene 2, controlling insulin signaling and glucose metabolism were significantly increased. Slow walking at speeds of 2-3 km/h exceeding 2895 steps/day attenuated several circulating lipoprotein lipids. The effects were mediated rather by PA than body weight or fat loss. Thus, lower thresholds for PA may exist for long term prevention of cardio-metabolic diseases in sedentary overweight subjects.

Effect of progressive high-impact exercise on femoral neck structural strength in postmenopausal women with mild knee osteoarthritis: a 12-month RCT

It is uncertain whether subjects with mild knee osteoarthritis, and who may be at risk of osteoporosis, can exercise safely with the aim of improving hip bone strength. This RCT showed that participating in a high-impact exercise program improved femoral neck strength without any detrimental effects on knee cartilage composition.

INTRODUCTION

No previous studies have examined whether high-impact exercise can improve bone strength and articular cartilage quality in subjects with mild knee osteoarthritis. In this 12-month RCT, we assessed the effects of progressive high-impact exercise on femoral neck structural strength and biochemical composition of knee cartilage in postmenopausal women.

METHODS

Eighty postmenopausal women with mild knee radiographic osteoarthritis were randomly assigned into the exercise (n = 40) or control (n = 40) group. Femoral neck structural strength was assessed with dual-energy X-ray absorptiometry. The knee cartilage region exposed to exercise loading was measured by the quantitative MRI techniques of T2 mapping and delayed gadolinium-enhanced MRI of cartilage (dGEMRIC). Also, an accelerometer-based body movement monitor was used to evaluate the total physical activity loading on the changes of femoral neck strength in all participants. Training effects on the outcome variables were estimated by the bootstrap analysis of covariance.

RESULTS

A significant between-group difference in femoral neck bending strength in favor of the trainees was observed after the 12-month intervention (4.4%, p < 0.01). The change in femoral neck bending strength remained significant after adjusting for baseline value, age, height, and body mass (4.0%, p = 0.020). In all participants, the change in bending strength was associated with the total physical activity loading (r = 0.29, p = 0.012). The exercise participation had no effect on knee cartilage composition.

CONCLUSION

The high-impact training increased femoral neck strength without having any harmful effect on knee cartilage in women with mild knee osteoarthritis. These findings imply that progressive high-impact exercise is a feasible method in seeking to prevent hip fractures in postmenopausal women whose articular cartilage may also be frail.

Use of Information and Communication Technologies Among Older People With and Without Frailty: A Population-Based Survey

Background

Use of information and communication technologies (ICT) among seniors is increasing; however, studies on the use of ICT by seniors at the highest risk of health impairment are lacking. Frail and prefrail seniors are a group that would likely benefit from preventive nutrition and exercise interventions, both of which can take advantage of ICT.

Objective

The objective of the study was to quantify the differences in ICT use, attitudes, and reasons for nonuse among physically frail, prefrail, and nonfrail home-dwelling seniors.

Methods

This was a population-based questionnaire study on people aged 65-98 years living in Northern Finland. A total of 794 eligible individuals responded out of a contacted random sample of 1500.

Results

In this study, 29.8% (237/794) of the respondents were classified as frail or prefrail. The ICT use of frail persons was lower than that of the nonfrail ones. In multivariable logistic regression analysis, age and education level were associated with both the use of Internet and advanced mobile ICT such as smartphones or tablets. Controlling for age and education, frailty or prefrailty was independently related to the nonuse of advanced mobile ICT (odds ratio, OR=0.61, P=.01), and frailty with use of the Internet (OR=0.45, P=.03). The frail or prefrail ICT nonusers also held the most negative opinions on the usefulness or usability of mobile ICT. When opinion variables were included in the model, frailty status remained a significant predictor of ICT use.

Conclusions

Physical frailty status is associated with older peoples’ ICT use independent of age, education, and opinions on ICT use. This should be taken into consideration when designing preventive and assistive technologies and interventions for older people at risk of health impairment.

Measuring Physical Activity in Free-Living Conditions-Comparison of Three Accelerometry-Based Methods

We examined the agreement in time spent on different physical activity (PA) levels using (1) mean amplitude deviation (MAD) of raw acceleration from the hip, (2) wrist-worn Polar Active, and (3) hip-worn Actigraph counts using Freedson's cut-points among adults under free-living conditions. PA was measured in 41 volunteers (mean age 47.6 years) for 14 days. Two MET-based threshold sets were used for MAD and Polar Active for sedentary time (ST) and time spent in light (LPA), moderate (MPA), and vigorous (VPA) PA. Actigraph counts were divided into PA classes, ≤100 counts/min for ST and Freedson's cut-points for LPA, MPA, and VPA. Analysis criteria were simultaneous use of devices for at least 4 days of >500 min/d. The between-method differences were analyzed using a repeated measures analysis of variance test. Bland-Altman plots and ROC graphs were also employed. Valid data were available from 27 participants. Polar Active produced the highest amount of VPA with both thresholds (≥5 and ≥6 MET; mean difference 17.9-30.9 min/d, P < 0.001). With the threshold 3-6 MET for MPA, Polar Active indicated 19.2 min/d more than MAD (95% CI 5.8-32.6) and 51.0 min/d more than Actigraph (95% CI 36.7-65.2). The results did not differ with 3.5-5 MET for MPA [F_{(1.44, 37.43)} = 1.92, P = 0.170]. MAD and Actigraph were closest to each other for ST with the threshold < 1.5 MET (mean difference 22.2 min/d, 95% CI 7.1-37.3). With the threshold <2 MET, Polar Active and Actigraph provided similar results (mean difference 7.0 min/d, 95% CI -17.8-31.7). Moderate to high agreement (area under the ROC curve 0.806-0.963) was found between the methods for the fulfillment of the recommendation for daily moderate-to-vigorous PA of 60 min. In free-living conditions the agreement between MAD, Polar Active, and Actigraph for measuring time spent on different activity levels in adults was dependent on the activity thresholds used and PA intensity. ROC analyses showed moderate to high agreement for the fulfillment of the recommendation for daily MVPA. Without additional statistical adjustment, these methods cannot be used interchangeably when measuring daily PA, but any of the methods can be used to identify persons with insufficient daily amount of MVPA.

Assistive technologies at home for people with a memory disorder

The aim of this study was to assess in practice whether assistive technologies support and facilitate the work of a family caregiver or care staff, and whether these technologies support the independence of a person with a memory disorder. A comprehensive set of supportive devices and alarm systems were experimentally tested in the care of five test subjects in an assisted living facility by eight nurses, and in the care of four test subjects in a home environment by three family caregivers and one care team. Questionnaires, diaries and logged data were used to evaluate the benefits of the devices. Simple aids and alarm systems that did not need much adjusting were considered most useful by caregivers and nurses, though multiple false alarms occurred during the test period. Technical connection problems, complex user interface, and inadequate sound quality were the primary factors reducing the utility of the tested devices. Further experimental research is needed to evaluate the utility of assistive technologies in different stages of a memory disorder.

Headache Children with Temporomandibular Disorders have Several Types of Pain and other Symptoms

The aim was to investigate the association between temporomandibular disorders (TMD) and overall muscle tenderness, depressive symptoms, sleep difficulties, headache frequency and related symptoms in children with primary headache in comparison with controls. Based on an unselected population sample of 1135 Finnish schoolchildren classified according to the type of headache at age 12, altogether 297 children aged 13-14 from different headache groups and healthy controls were randomly selected for an interview and clinical examinations. Children with migraine had more TMD signs than children with nonmigrainous headaches or healthy controls. High TMD total scores were associated with palpation tenderness in other parts of the body and with frequent headache attacks. We conclude that children with overall headache, migraine in particular, and high total TMD scores showed an increased overall tenderness to muscle palpation and multiply manifested hypersensitivity pain.

Effects of Exercise on Patellar Cartilage in Women with Mild Knee Osteoarthritis

PURPOSE

This study aims to investigate the effects of exercise on patellar cartilage using T2 relaxation time mapping of magnetic resonance imaging in postmenopausal women with mild patellofemoral joint osteoarthritis (OA).

METHODS

Eighty postmenopausal women (mean age, 58 (SD, 4.2) yr) with mild knee OA were randomized to either a supervised progressive impact exercise program three times a week for 12 months (n = 40) or a nonintervention control group (n = 40). Biochemical properties of cartilage were estimated using T2 relaxation time mapping, a parameter sensitive to collagen integrity, collagen orientation, and tissue hydration. Leg muscle strength and power, aerobic capacity, and self-rated assessment with the Knee Injury and Osteoarthritis Outcome Score were also measured.

RESULTS

After intervention, full-thickness patellar cartilage T2 values had medium-size effect (d = 0.59; 95% confidence interval, 0.16 to 0.97; P = 0.018); the change difference was 7% greater in the exercise group compared with the control group. In the deep half of tissue, the significant exercise effect size was medium (d = 0.56; 95% confidence interval, 0.13 to 0.99; P = 0.013); the change difference was 8% greater in the exercise group compared with controls. Furthermore, significant medium-size T2 effects were found in the total lateral segment, lateral deep, and lateral superficial zones in favor of the exercise group. Extension force was 11% greater (d = 0.63, P = 0.006) and maximal aerobic capacity was 4% greater (d = 0.55, P = 0.028) in the exercise group than in controls. No changes in Knee Injury and Osteoarthritis Outcome Score emerged between the groups.

CONCLUSIONS

Progressively implemented high-impact and intensive exercise creates enough stimuli and exerts favorable effects on patellar cartilage quality and physical function in postmenopausal women with mild knee OA.

Profiles of sedentary and non-sedentary young men - a population-based MOPO study

BACKGROUND

Sedentary behavior is associated with poor well-being in youth with adverse trajectories spanning to adulthood. Still, its determinants are poorly known. Our aim was to profile sedentary and non-sedentary young men and to clarify their differences in a population-based setting.

METHODS

A total of 616 men (mean age 17.9, SD 0.6) attending compulsory conscription for military service completed a questionnaire on health, health behavior, socioeconomic situation and media use. They underwent a physical (body composition, muscle and aerobic fitness) and medical examination. Profiles were formed by principal component analysis (PCA).

RESULTS

A total of 30.1 % men were sedentary (daily leisure-time sitting ≥5 h) and 28.9 % non-sedentary (sitting ≤2 h). The sedentary men had more body fat, more depressive symptoms, but lower fitness and life satisfaction than non-sedentary men. However, according to PCA, profiles of unhealthy eating, life-dissatisfaction, and gaming were detected both among sedentary and non-sedentary men, as well as high self-rated PA and motives to exercise.

CONCLUSION

Determinants of sedentary and non-sedentary lifestyles were multiple and partially overlapping. Recognizing individual patterns and underlying factors of the sedentary lifestyle is essential for tailored health promotion and interventions.

Correlation of Subchondral Bone Density and Structure from Plain Radiographs with Micro Computed Tomography Ex Vivo

Osteoarthritis causes changes in the subchondral bone structure and composition. Plain radiography is a cheap, fast, and widely available imaging method. Bone tissue can be well seen from plain radiograph, which however is only a 2D projection of the actual 3D structure. Therefore, the aim was to investigate the relationship between bone density- and structure-related parameters from 2D plain radiograph and 3D bone parameters assessed from micro computed tomography (µCT) ex vivo. Right tibiae from eleven cadavers without any diagnosed joint disease were imaged using radiography and with µCT. Bone density- and structure-related parameters were calculated from four different locations from the radiographs of proximal tibia and compared with the volumetric bone microarchitecture from the corresponding regions. Bone density from the plain radiograph was significantly related with the bone volume fraction (r = 0.86; n = 44; p < 0.01). Mean homogeneity index for orientation of local binary patterns (HI_angle,mean) and fractal dimension of vertical structures (FD_Ver) were related (p < 0.01) with connectivity density (HI_angle,mean: r = −0.73, FD_Ver: r = 0.69) and trabecular separation (HI_angle,mean: r = 0.73, FD_Ver: r = −0.70) when all ROIs were pooled together (n = 44). Bone density and structure in tibia from standard clinically available 2D radiographs are significantly correlated with true 3D microstructure of bone.

Bone and cartilage characteristics in postmenopausal women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis

OBJECTIVES

To evaluate the association between radiographically-assessed knee osteoarthritis and femoral neck bone characteristics in women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis.

METHODS

Ninety postmenopausal women (mean age [SD], 58 [4] years; height, 163 [6] cm; weight, 71 [11] kg) participated in this cross-sectional study. The severity of radiographic knee osteoarthritis was defined using Kellgren-Lawrence grades 0=normal (n=12), 1=doubtful (n=25) or 2=minimal (n=53). Femoral neck bone mineral content (BMC), section modulus (Z), and cross-sectional area (CSA) were measured with DXA. The biochemical composition of ipsilateral knee cartilage was estimated using quantitative MRI measures, T2 mapping and dGEMRIC. The associations between radiographic knee osteoarthritis grades and bone and cartilage characteristics were analyzed using generalized linear models.

RESULTS

Age-, height-, and weight-adjusted femoral neck BMC (p for linearity=0.019), Z (p for linearity=0.033), and CSA (p for linearity=0.019) increased significantly with higher knee osteoarthritis grades. There was no linear relationship between osteoarthritis grades and knee cartilage indices.

CONCLUSIONS

Increased DXA assessed hip bone strength is related to knee osteoarthritis severity. These results are hypothesis driven that there is an inverse relationship between osteoarthritis and osteoporosis. However, MRI assessed measures of cartilage do not discriminate mild radiographic osteoarthritis severity.

Association between low-frequency ultrasound and hip fractures -- comparison with DXA-based BMD

BACKGROUND

New methods for diagnosing osteoporosis and evaluating fracture risk are being developed. We aim to study the association between low-frequency (LF) axial transmission ultrasound and hip fracture risk in a population-based sample of older women.

METHODS

The study population consisted of 490 community-dwelling women (78-82 years). Ultrasound velocity (V(LF)) at mid-tibia was measured in 2006 using a low-frequency scanning axial transmission device. Bone mineral density (BMD) at proximal femur measured using dual-energy x-ray absorptiometry (DXA) was used as the reference method. The fracture history of the participants was collected from December 1997 until the end of 2010. Lifestyle-related risk factors and mobility were assessed at 1997.

RESULTS

During the total follow-up period (1997-2010), 130 women had one or more fractures, and 20 of them had a hip fracture. Low V(LF) (the lowest quartile) was associated with increased hip fracture risk when compared with V(LF) in the normal range (Odds ratio, OR = 3.3, 95% confidence interval (CI) 1.3-8.4). However, V(LF) was not related to fracture risk when all bone sites were considered. Osteoporotic femoral neck BMD was associated with higher risk of a hip fracture (OR = 4.1, 95% CI 1.6-10.5) and higher risk of any fracture (OR = 2.4, 95% CI 1.6-3.8) compared to the non-osteoporotic femoral neck BMD. Decreased VLF remained a significant risk factor for hip fracture when combined with lifestyle-related risk factors (OR = 3.3, 95% CI 1.2-9.0).

CONCLUSION

Low V(LF) was associated with hip fracture risk in older women even when combined with lifestyle-related risk factors. Further development of the method is needed to improve the measurement precision and to confirm the results.

Assessment of risk of femoral neck fracture with radiographic texture parameters: a retrospective study

PURPOSE

To investigate whether femoral neck fracture can be predicted retrospectively on the basis of clinical radiographs by using the combined analysis of bone geometry, textural analysis of trabecular bone, and bone mineral density (BMD).

MATERIALS AND METHODS

Formal ethics committee approval was obtained for the study, and all participants gave informed written consent. Pelvic radiographs and proximal femur BMD measurements were obtained in 53 women aged 79-82 years in 2006. By 2012, 10 of these patients had experienced a low-impact femoral neck fracture. A Laplacian-based semiautomatic custom algorithm was applied to the radiographs to calculate the texture parameters along the trabecular fibers in the lower neck area for all subjects. Intra- and interobserver reproducibility was calculated by using the root mean square average coefficient of variation to evaluate the robustness of the method.

RESULTS

The best predictors of hip fracture were entropy (P = .007; reproducibility coefficient of variation < 1%), the neck-shaft angle (NSA) (P = .017), and the BMD (P = .13). For prediction of fracture, the area under the receiver operating characteristic curve was 0.753 for entropy, 0.608 for femoral neck BMD, and 0.698 for NSA. The area increased to 0.816 when entropy and NSA were combined and to 0.902 when entropy, NSA, and BMD were combined.

CONCLUSION

Textural analysis of pelvic radiographs enables discrimination of patients at risk for femoral neck fracture, and our results show the potential of this conventional imaging method to yield better prediction than that achieved with dual-energy x-ray absorptiometry-based BMD. The combination of the entropy parameter with NSA and BMD can further enhance predictive accuracy.

Effects of high-impact training on bone and articular cartilage: 12-month randomized controlled quantitative MRI study

Osteoarthritis and osteoporosis often coexist in postmenopausal women. The simultaneous effect of bone-favorable high-impact training on these diseases is not well understood and is a topic of controversy. We evaluated the effects of high-impact exercise on bone mineral content (BMC) and the estimated biochemical composition of knee cartilage in postmenopausal women with mild knee osteoarthritis. Eighty women aged 50 to 66 years with mild knee osteoarthritis were randomly assigned to undergo supervised progressive exercise three times a week for 12 months (n = 40) or to a nonintervention control group (n = 40). BMC of the femoral neck, trochanter, and lumbar spine was measured by dual-energy X-ray absorptiometry (DXA). The biochemical composition of cartilage was estimated using delayed gadolinium-enhanced magnetic resonance imaging (MRI) cartilage (dGEMRIC), sensitive to cartilage glycosaminoglycan content, and transverse relaxation time (T2) mapping that is sensitive to the properties of the collagen network. In addition, we evaluated clinically important symptoms and physical performance-related risk factors of falling: cardiorespiratory fitness, dynamic balance, maximal isometric knee extension and flexion forces, and leg power. Thirty-six trainees and 40 controls completed the study. The mean gain in femoral neck BMC in the exercise group was 0.6% (95% CI, -0.2% to 1.4%) and the mean loss in the control group was -1.2% (95% CI, -2.1% to -0.4%). The change in baseline, body mass, and adjusted body mass change in BMC between the groups was significant (p = 0.005), whereas no changes occurred in the biochemical composition of the cartilage, as investigated by MRI. Balance, muscle force, and cardiorespiratory fitness improved significantly more (3% to 11%) in the exercise group than in the control group. Progressively implemented high-impact training, which increased bone mass, did not affect the biochemical composition of cartilage and may be feasible in the prevention of osteoporosis and physical performance-related risk factors of falling in postmenopausal women.