Complex anthropometrics such as area and volume, can identify changes in body size and shape that are not detectable with traditional anthropometrics of lengths, breadths, skinfolds and girths. However, taking these complex with manual techniques (tape measurement and water displacement) is often unsuitable. Three-dimensional (3D) surface imaging systems are quick and accurate alternatives to manual techniques but their use is restricted by cost, complexity and limited access. We have developed a novel low-cost, accessible and portable 3D surface imaging system based on consumer depth cameras. The aim of this study was to determine the validity and repeatability of the system in the measurement of thigh volume. The thigh volumes of 36 participants were measured with the depth camera system and a high precision commercially available 3D surface imaging system (3dMD). The depth camera system used within this study is highly repeatable (technical error of measurement (TEM) of <1.0% intra-calibration and ~2.0% inter-calibration) but systematically overestimates (~6%) thigh volume when compared to the 3dMD system. This suggests poor agreement yet a close relationship, which once corrected can yield a usable thigh volume measurement.

Objectives To evaluate geographic access to free weekly outdoor physical activity events (‘parkrun’) in England, with a particular focus on deprived communities, and to identify optimal locations for future events to further maximise access. Study design This study is a cross-sectional ecological analysis of the socio-economic disparities in geographic access to parkrun events in England in late 2018. Methods We combined geolocation data on all English Lower Layer Super Output Areas and parkrun events to calculate geodesic distances to the nearest event for more than 32,000 communities in England. We use this measure of geographic access to summarise the relationship between access and socio-economic deprivation, measured using the index of multiple deprivation. We then used geographic coordinates of public green spaces in England to conduct a simple location-allocation analysis to identify 200 locations for future event locations that would maximise access. Results In England, 69% of the population live within 5 km of one of the 465 parkrun events. There is a small negative correlation between distance and deprivation, indicating that access is slightly better in more socio-economically deprived areas. Setting up an additional 200 events in optimal locations would improve access: the average distance to the nearest parkrun event would improve by 1.22 km, from 4.65 km to 3.43 km, and approximately 82% of the English population would live within 5 km of a parkrun event. Conclusion Over two-thirds of the English population live within 5 km of a parkrun event, and contrary to our expectation, we find that geographic access is slightly better for those living in more deprived communities. Creating additional events may improve geographic access, but effective strategies will still be needed to increase engagement in new and existing events by those living in socio-economically deprived areas.

Background Whilst the benefits of physical activity for health and wellbeing are recognised, population levels of activity remain low. Significant inequalities exist, with socioeconomically disadvantaged populations being less physically active and less likely to participate in community events. We investigated the perceived benefits from participation in a weekly running/walking event called parkrun by those living in the most socioeconomically deprived areas and doing the least physical activity. Methods A cross-sectional online survey was emailed to 2,318,135 parkrun participants in the UK. Demographic and self-reported data was collected on life satisfaction, happiness, health status, physical activity, motives, and the perceived benefits of parkrun. Motivation, health status and benefits were compared for sub-groups defined by physical activity level at parkrun registration and residential Index of Multiple Deprivation. Results 60,000 completed surveys were received (2.7% of those contacted). Respondents were more recently registered with parkrun (3.1 v. 3.5 years) than the parkrun population and had a higher frequency of parkrun participation (14.5 v. 3.7 parkruns per year). Those inactive at registration and from deprived areas reported lower happiness, lower life satisfaction and poorer health compared to the full sample. They were more likely to want to improve their physical health, rather than get fit or for competition. Of those reporting less than one bout of activity per week at registration, 88% (87% in the most deprived areas) increased their physical activity level and 52% (65% in the most deprived areas) reported improvements to overall health behaviours. When compared to the full sample, a greater proportion of previously inactive respondents from the most deprived areas reported improvements to fitness (92% v. 89%), physical health (90% v. 85%), happiness (84% v. 79%) and mental health (76% v. 69%). Conclusion The least active respondents from the most socioeconomically deprived areas reported increases to their activity levels and benefits to health and wellbeing since participating in parkrun. Whilst the challenge of identifying how community initiatives like parkrun can better engage with underrepresented populations remains, if this can be achieved they could have a critical public health role in addressing inequalities in benefits associated with recreational physical activity.

Background: parkrun has been successful in encouraging people in England to participate in their weekly 5km running and walking events. However, there is substantial heterogeneity in parkrun participation across different communities in England: after controlling for travel distances, deprived communities have significantly lower participation rates. Methods: This paper expands on previous findings by investigating disparities in parkrun participation by ethnic density. We combined geo-spatial data available through the Office for National Statistics with participation data provided by parkrun, and fitted multivariable Poisson regression models to study the effect of ethnic density on participation rates at the Lower layer Super Output Level. Results: We find that areas with higher ethnic density have lower participation rates. This effect is independent of deprivation. Conclusions: An opportunity exists for parkrun to engage with these communities and reduce potential barriers to participation.

Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMi), the waist-hip-ratio (WHR) and waist-by-height 0.5 ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. the aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity. Measurements of size and shape of the human body are an important source of information for a range of scientific fields and applications. Traditional manual anthropometrics have been used extensively in medical practice and epidemiological studies to derive health risk indicators, since it has been suggested that human body shape is dependent on its underlying composition, including soft and skeletal tissues 1. Indices, such as the body mass index (BMI), waist girth and the waist-hip ratio (WHR) are used to assess variations in human body dimensions and physical health 2-4. Of these, BMI is most commonly used in current practice to determine the healthy weight range for individuals based on their height. However, BMI fails to distinguish between quantities of muscle and fat, which are of different density, and therefore is prone to misclassifying muscular individuals as being overweight or obese 5,6. Size measures, such as sagittal diameter, waist girth and WHT.5R have been found to demonstrate improved correlations with quantities of abdominal visceral fat and greater associations with metabolic disease risks compared to BMI 7,8. Relative measures, such as the WHR, provide information about the size of the abdomen relative to the rest of the body, so has been used as a proxy of torso shape and central obesity, defined as excess fat around the abdominal region 7. However, these relatively simple approaches to measuring external human form only utilise a small number of manual anthropometrics, which are prone to human error and limited by their simplicity, as they do not fully describe ...

Recent literature suggests that 2D and 3D anthropometric measures are better predictors of sports performance, than traditional 1D measures. The emergence of 3D scanning systems offers a cheap, easy and effective method of estimating these measures. Therefore the aim of this study was to investigate the repeatability of a depth camera based 3D scanning system, and its agreement with manual methods in the extraction of simple thigh measurements. Using 15 healthy, recreationally active male participants, five measurements of the thigh (upper thigh circumference, mid-thigh circumference, knee circumference, knee to mid-thigh length and mid-thigh to upper thigh length) were taken using an anthropometric tape measure and digital callipers, and scanned using a 4camera Kinect based 3D scanning system (using custom analysis software). Agreement and repeatability was subsequently determined. This study demonstrated a low cost Kinect-based 3D scanning system is capable of extracting length and circumference measures within ~2% and ~3-4%, respectively, with high repeatability, technical error measurements (TEM) of ~1.80% and ~0.7% respectively. The 3D scanning system was able to measure the thigh in good agreement with manual measurement methods, with the presence of systematic bias in circumference. Whilst maintaining a very high degree of repeatability, suggesting it is a suitable method to extract simple thigh measurements.

Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (GM) is an established framework used for the statistical analysis of biological shape variation. These methods quantify biological shape variation after the effects of non-shape variation–location, rotation and scale–have been mathematically held constant, otherwise known as the Procrustes paradigm. The aim of this study was to determine whether shape measures, identified using geometric morphometrics, can provide additional information about the complexity of human morphology and underlying mass distribution compared to traditional body measures. Scale-invariant features of torso shape were extracted from 3D imaging data of 9,209 participants form the LIFE-Adult study. Partial least squares regression (PLSR) models were created to determine the extent to which variations in human torso shape are explained by existing techniques. The results of this investigation suggest that linear combinations of body measures can explain 49.92% and 47.46% of the total variation in male and female body shape features, respectively. However, there are also significant amounts of variation in human morphology which cannot be identified by current methods. These results indicate that Geometric morphometric methods can identify measures of human body shape which provide complementary information about the human body. The aim of future studies will be to investigate the utility of these measures in clinical epidemiology and the assessment of health risk.

Background: Whilst the benefits of physical activity for health and wellbeing are recognised, population levels of activity remain low. Significant inequalities exist, with socioeconomically disadvantaged populations being less physically active and less likely to participate in community events. We investigated the perceived benefits from participation in a weekly running/walking event by those living in the most socioeconomically deprived areas and doing the least physical activity.Methods: A cross-sectional online survey was emailed to 2,318,135 parkrun participants in the UK. Demographic and self-reported data was collected on life satisfaction, happiness, health status, physical activity, motives, and the perceived benefits of parkrun. Motivation, health status and benefits were compared for groups defined by level of physical activity at parkrun registration and residential Index of Multiple Deprivation.Results: 60,000 completed surveys were received (2.7% of those contacted). Respondents were more recently registered with parkrun (3.1 v. 3.5 years) and had a higher frequency of participation than non-respondents (14.5 v. 3.7 parkruns per year). Those who were inactive at registration and from socioeconomically deprived areas reported lower happiness, lower life satisfaction and poorer health than the full sample. They were more likely to want to improve their physical health, rather than get fit or lose weight. Of those reporting less than one bout of activity a week at registration, 88% (87% in the most socioeconomically deprived areas) increased their physical activity level and 52% (65% in the most socioeconomically deprived areas) reported improvements to overall health behaviours. Previously inactive respondents from the most socioeconomically deprived areas reported greater improvements to fitness (93% v. 89%), physical health (90% v. 85%), happiness (83% v. 79%) and mental health (76% v. 69%).Conclusion: The least active respondents from the most socioeconomically deprived areas reported changes to their activity levels and benefits to their health and wellbeing since participating in parkrun. Whilst the challenge of identifying how community initiatives like parkrun can better engage with the least active and most socioeconomically deprived remains, if this can be achieved, then such interventions can have a critical public health role in addressing inequalities in benefits associated with recreational physical activity.