Objectively Measured Physical Activity Is Associated with Vertebral Size in Midlife

Deep learning in sex estimation from a peripheral quantitative computed tomography scan of the fourth lumbar vertebra-a proof-of-concept study

Sex estimation is a key element in the analysis of unknown skeletal remains. The vertebrae display clear sex discrepancy and have proven accurate in conventional morphometric sex estimation. This proof-of-concept study aimed to investigate the possibility to develop a deep learning algorithm for sex estimation even from a single peripheral quantitative computed tomography (pQCT) slice of the fourth lumbar vertebra (L4). The study utilized a total of 117 vertebrae from the Terry Anatomical Collection. There were 58 male and 59 female cadavers, all of the white ethnicity, with the average age at death 49 years and a range of 24 to 77 years. A coronal pQCT scan was taken from the midway of the L4 corpus. Sex estimation was performed in a total of 19 neural network architectures implemented in the AIDeveloper software. Of the explored architectures, a LeNet5-based algorithm reached the highest accuracy of 86.4% in the test set. Sex-specific classification rates were 90.9% among males and 81.8% among females. This preliminary finding advances the field by encouraging and directing future research on artificial intelligence-based methods in sex estimation from individual skeletal traits such as the vertebrae. Combining quickly obtained imaging data with automated deep learning algorithms may establish a valuable pipeline for forensic anthropology and provide aid when combined with traditional methods.

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.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

The association between physical activity and vertebral dimension change in early adulthood - The Northern Finland Birth Cohort 1986 study

Small vertebral size is a well-known risk factor for vertebral fractures. To help understanding the factors behind vertebral size, we aimed to investigate whether physical activity and participation in high-impact exercise are associated with the growth rate of the vertebral cross-sectional area (CSA) among young adults. To conduct our study, we utilized the Northern Finland Birth Cohort 1986 as our study population (n = 375). Questionnaire data about physical activity was obtained at 16, 18 and 19 years of age and lumbar magnetic resonance imaging scans at two timepoints, 20 and 30 years of age. We used generalized estimating equation (GEE) models to conduct the analyses. We did not find any statistically significant associations between vertebral CSA, physical activity, and high-impact exercise in our study sample. We conclude that neither physical activity nor high-impact sports seem to influence the change in vertebral CSA among young adults.

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Physical activity does not influence the growth rate of the vertebral body.

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High-impact sports are not associated with the change in vertebral CSA among adults.

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The study was conducted using longitudinal MRI data.

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.

Baseline anthropometric indices predict change in vertebral size in early adulthood - A 10-year follow-up MRI study

The vertebral cross-sectional area (CSA) has an independent effect on vertebral strength. Recent evidence has shown that vertebral dimensions significantly increase in the third decade of life, and that lifestyle factors such as body size and composition are clearly associated with vertebral CSA. This study aimed to test the hypothesis that general anthropometric traits (stature, total body mass, lean body mass, fat mass, body mass index, waist circumference), each objectively measured at baseline, predict the change in vertebral CSA over the subsequent decade. A representative sample of young Northern Finnish adults was used (n = 371) with repeated magnetic resonance imaging (MRI) scans from ~20 and ~30 years (baseline and follow-up, respectively). Vertebral CSA was measured from the MRI scans with high reliability and low measurement error. The statistical analysis was performed using linear regression models adjusted for sex and exact length of MRI interval. According to the regression models, in descending order of effect size, lean body mass (standardized beta coefficient 0.243 [95% confidence interval 0.065-0.420]), total body mass (0.158 [0.043-0.273]), body mass index (0.125 [0.026-0.224]), waist circumference (0.119 [0.010-0.228]), and fat mass (0.104 [0.004-0.205]) were positively and significantly associated with CSA gain over the follow-up, whereas stature (0.079 [-0.066-0.224]) was not associated with CSA change. The results of this study suggest that anthropometric indices may be used for estimating subsequent change in vertebral size. In particular, greater lean body mass seems to be beneficial for vertebral size and thus potentially also for vertebral strength. Future studies should aim to replicate these associations in a dataset with longitudinal anthropometric trajectories and identify the potential common factors that influence both anthropometric traits and vertebral CSA gain.