Falling while walking: A hidden contributor to pedestrian injury

Sickness absence and disability pension after road traffic accidents, a nationwide register-based study comparing different road user groups with matched references

Background

Being injured in a road traffic accident may affect individuals' functional ability and in turn lead to sickness absence (SA) and disability pension (DP). Knowledge regarding long-term consequences in terms of SA and DP following a road traffic accident is lacking, especially comparing different groups of road users and compared to the general population. The aim was to estimate excess diagnosis-specific SA and DP among individuals of different road user groups injured in a road traffic accident compared to matched references without such injury.

Methods

A nationwide register-based study, including all working individuals aged 20-59 years and living in Sweden who in 2015 had in- or specialized outpatient healthcare after a new traffic-related injury (n = 20 177) and population-based matched references (matched on: sex, age, level of education, country of birth, living in cities) without any traffic-related injury during 2014-2015 (n = 100 885). Diagnosis-specific (injury and other diagnoses) SA and DP were assessed during 5 years: 1 year before and 4 years following the accident. Mean SA and DP net days/year for each road user group and mean differences of (excess) SA and DP net days/year compared with their matched references were calculated with independent t-tests with bootstrapped 95% confidence intervals (CIs).

Results

A third of all injured road users were bicyclists, 31% were car occupants, 16% were pedestrians (including fall accidents), and 19% were other and unspecified accidents. Pedestrians and other road users were the groups with the highest mean number of SA days during the first year following the accident (51 and 49 days/year respectively). The matched references had between 8 and 13 SA days/year throughout the study period. The excess SA days/year were elevated for all road user groups all five studied years. Excess SA due to injury diagnoses was 15-35 days/year during the first year following the accident. Excess SA due to diagnoses other than injuries were about eight days/year during the whole study period for pedestrians and car occupants and about zero for the bicyclists. The excess DP was low, although it increased every year after the accident for pedestrians and car occupants; for bicyclists no excess DP was seen.

Conclusion

Higher levels of SA due to injury diagnoses were seen among all road user groups during the first year after the accident compared to their references. Pedestrians and car occupants had more excess SA due to other diagnoses and more excess DP four years after the accident than bicyclists and other road users.

Minimum number of inertial measurement units needed to identify significant variations in walk patterns of overweight individuals walking on irregular surfaces

Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals.

Fall and collision related injuries among pedestrians, sickness absence and associations with accident type and occupation

OBJECTIVES

This study explores pedestrian fall accidents and collisions with other road users in the Swedish road transport system, and sickness absence (SA) in relation to accident type, injury, and occupation. Further, it studies the associations between accident type, occupation, and duration of SA.

METHODS

Data from several national registers were used that included 15,359 working age pedestrians (20-64 years) receiving healthcare after a fall or collision throughout 2014-2016. Individual characteristics, accident type, injury, and occupation were presented and related to SA. Logistic regression was used to estimate odds ratios (OR), with 95% confidence intervals, for associations between accident type, occupation, and SA duration.

RESULTS

About 11,000 pedestrians (72%) were involved in fall accidents in the road traffic environment and well over 4,000 in collisions with another road user; 22% of all injured pedestrians had a new SA. The population had a higher proportion of women and individuals in older age groups (≥45). Of the falls, 31% were due to snow or ice, and these were associated with a higher OR for both short SA (<90 days) 1.76 (95% CI 1.56-1.98) and long SA (≥90 days) 1.81 (95% CI 1.51-2.18), compared to the group slipping, tripping, and stumbling. The working sectors health & social care, and construction had the highest ORs for SA. A higher OR was found for health & social care, short SA 1.58 (95% CI 1.38-1.81), long SA 1.79 (95% CI 1.45-2.20) and for construction, short SA 1.56 (95% CI 1.24-1.96), long SA 1.75 (95% CI 1.26-2.44), compared to the sector finance, communication, & cultural service.

CONCLUSIONS

The OR for having short and long SA was higher in falls due to snow or ice and differed between occupational sectors.

PRACTICAL IMPLICATIONS

This information contributes to the knowledge base for planning a safe road transport system for pedestrians.

Fall history in older adults impacts acceleration profiles after a near collision with a moving pedestrian hazard

BACKGROUND

Environmental hazards (e.g., pedestrian traffic) cause falls and testing environment impacts gait in older adults. However, most fall risk evaluations do not assess real-world moving hazard avoidance.

AIMS

This study examined the effect of fall history in older adults on acceleration profiles before, during, and after a near collision with a moving hazard, in laboratory and real-world settings.

METHODS

Older adults with (n = 14) and without a fall history (n = 15) performed a collision avoidance walking task with a sudden moving hazard in real-world and laboratory settings. Gait acceleration and video data of participants' first-person views were recorded. Four mixed effects multilevel models analyzed the magnitude and variability of mean and peak anteroposterior and mediolateral acceleration while walking before, during, and after the moving hazard in both environments.

RESULTS

In the real-world environment, older adults without a fall history increased their mean anteroposterior acceleration after the moving hazard (p = 0.046), but those with a fall history did not (p > 0.05). Older adults without a fall history exhibited more intersubject variability than those with a fall history in mean (p < 0.001) and peak anteroposterior (p = 0.015) acceleration across environments and epochs. Older adults without a fall history exhibited a slower peak mediolateral reaction during the moving hazard (p = 0.014) than those with a fall history.

CONCLUSIONS

These results suggest that compared to older adults with a fall history, older adults without a fall history are more adaptable and able to respond last-minute to unexpected hazards. Older adults with a fall history exhibited more homogenous responses.

Diagnosis-specific sickness absence among injured working-aged pedestrians: a sequence analysis

BACKGROUND

The knowledge about the long-term consequences in terms of sickness absence (SA) among pedestrians injured in a traffic-related accident, including falls, is scarce. Therefore, the aim was to explore diagnosis-specific patterns of SA during a four-year period and their association with different sociodemographic and occupational factors among all individuals of working ages who were injured as a pedestrian.

METHODS

A nationwide register-based study, including all individuals aged 20-59 and living in Sweden, who in 2014-2016 had in- or specialized outpatient healthcare after a new traffic-related accident as a pedestrian. Diagnosis-specific SA (> 14 days) was assessed weekly from one year before the accident up until three years after the accident. Sequence analysis was used to identify patterns (sequences) of SA, and cluster analysis to form clusters of individuals with similar sequences. Odds ratios (ORs) with 95% confidence intervals (CIs) for association of the different factors and cluster memberships were estimated by multinomial logistic regression.

RESULTS

In total, 11,432 pedestrians received healthcare due to a traffic-related accident. Eight clusters of SA patterns were identified. The largest cluster was characterized by no SA, three clusters had different SA patterns due to injury diagnoses (immediate, episodic, and later). One cluster had SA both due to injury and other diagnoses. Two clusters had SA due to other diagnoses (short-term and long-term) and one cluster mainly consisted of individuals with disability pension (DP). Compared to the cluster "No SA", all other clusters were associated with older age, no university education, having been hospitalized, and working in health and social care. The clusters "Immediate SA", "Episodic SA" and "Both SA due to injury and other diagnoses" were also associated with higher odds of pedestrians who sustained a fracture.

CONCLUSIONS

This nationwide study of the working-aged pedestrians observed diverging patterns of SA after their accident. The largest cluster of pedestrians had no SA, and the other seven clusters had different patterns of SA in terms of diagnosis (injury and other diagnoses) and timing of SA. Differences were found between all clusters regarding sociodemographic and occupational factors. This information can contribute to the understanding of long-term consequences of road traffic accidents.

Evaluating the difference in walk patterns among normal-weight and overweight/obese individuals in real-world surfaces using statistical analysis and deep learning methods with inertial measurement unit data

Unusual walk patterns may increase individuals' risks of falling. Anthropometric features of the human body, such as the body mass index (BMI), influences the walk patterns of individuals. In addition to the BMI, uneven walking surfaces may cause variations in the usual walk patterns of an individual that will potentially increase the individual's risk of falling. The objective of this study was to statistically evaluate the variations in the walk patterns of individuals belonging to two BMI groups across a wide range of walking surfaces and to investigate whether a deep learning method could classify the BMI-specific walk patterns with similar variations. Data collected by wearable inertial measurement unit (IMU) sensors attached to individuals with two different BMI were collected while walking on real-world surfaces. In addition to traditional statistical analysis tools, an advanced deep learning-based neural network was used to evaluate and classify the BMI-specific walk patterns. The walk patterns of overweight/obese individuals showed a greater correlation with the corresponding walking surfaces than the normal-weight population. The results were supported by the deep learning method, which was able to classify the walk patterns of overweight/obese (94.8 ± 4.5%) individuals more accurately than those of normal-weight (59.4 ± 23.7%) individuals. The results suggest that application of the deep learning method is more suitable for recognizing the walk patterns of overweight/obese population than those of normal-weight individuals. The findings from the study will potentially inform healthcare applications, including artificial intelligence-based fall assessment systems for minimizing the risk of fall-related incidents among overweight and obese individuals.

Fall- and collision-related injuries among pedestrians in road traffic environment - A Swedish national register-based study

OBJECTIVE

To investigate the burden of pedestrian injuries, including pedestrian fall injuries (PFI), compared to other transport-related injuries in Sweden and document their characteristics in terms of demographics, causes, type of injuries, and severity level with a focus on long-term consequences.

METHODS

Data were retrieved from the national Swedish Traffic Accident Data Acquisition register. A total of 361,531 fatalities and injuries were reported by emergency hospitals during 2010-2019, of which 127,804 were pedestrians (35%). We assessed the magnitude of PFIs and conducted comparative analyses to assess differences compared to other types of road users regarding sex, age, severity level, injury circumstances, hospital care, causes of accidents, and type of injuries.

RESULTS

Pedestrians were the second largest group of traffic-related deaths in Sweden after car occupants and accounted for just over a quarter of all fatal accidents in the road traffic environment. Of the total number of pedestrian fatalities, three out of four have been in collision accidents and the others in fall-related accidents. In terms of injuries, pedestrians were the largest group among all road users, regardless of the type of accident. PFIs accounted for a third of all injuries in the road traffic environment and nearly half of all injuries resulting in permanent medical impairment (i.e., 2.2 times more long-term consequences among PFIs compared to injured car occupants). Females (particularly middle-aged and older) and older adults were overrepresented, and most PFIs occurred on urban and municipal roads. The causes were often related to maintenance (e.g., slippery surfaces such as ice, snow, leaves or gravel together with uneven pavements and roads are the cause three out of four of PFIs). Among collision injuries, the representation was almost equal for sex and age.

CONCLUSIONS

Injuries and fatalities among pedestrians are a considerable issue in the road traffic environment in Sweden. Contrary to other traffic groups, the incidence has not decreased over time, meaning that this issue must be met with specific measures and address the specific risk factors they are associated with.

PRACTICAL APPLICATION

Including fall accidents in the definition of traffic accidents increases the chances of getting better information about the accidents and taking preventive measures.

Crash test-based assessment of injury risks for adults and children when colliding with personal mobility devices and service robots

Autonomous mobility devices such as transport, cleaning, and delivery robots, hold a massive economic and social benefit. However, their deployment should not endanger bystanders, particularly vulnerable populations such as children and older adults who are inherently smaller and fragile. This study compared the risks faced by different pedestrian categories and determined risks through crash testing involving a service robot hitting an adult and a child dummy. Results of collisions at 3.1 m/s (11.1 km/h/6.9 mph) showed risks of serious head (14%), neck (20%), and chest (50%) injuries in children, and tibia fracture (33%) in adults. Furthermore, secondary impact analysis resulted in both populations at risk of severe head injuries, namely, from falling to the ground. Our data and simulations show mitigation strategies for reducing impact injury risks below 5% by either lowering the differential speed at impact below 1.5 m/s (5.4 km/h/3.3 mph) or through the usage of absorbent materials. The results presented herein may influence the design of controllers, sensing awareness, and assessment methods for robots and small vehicles standardization, as well as, policymaking and regulations for the speed, design, and usage of these devices in populated areas.

Impact of Weather on Pedestrians' Slip Risk

Pedestrians’ slipping injuries are a very typical problem in the Nordic countries, causing varying degrees of injuries and in the worst case, long sick leaves. There is a clear seasonal variation in the number of slips. Sidewalk slipperiness and the risk of slips is a complex combination of weather, winter maintenance activities, number of walkers, and the grip between shoes and surface, as well as human behavioral and physical factors. In this study, the effect of weather on pedestrians’ slipping injuries is studied. Daily weather observations are compared to the slip statistics that have been collected from commuting accident statistics in cases where the way of commuting has been walking. A total of 16 cities from Finland for 14 winters are included in this study. The results reveal that snow on the ground increases the slip risk more than three times compared to no-snow situations. Near zero temperatures and precipitation are very typical on days when slip injuries occur more than usual. However, there are also days when high amounts of slips cannot be explained with the weather. The study also shows that there are significant differences as to the number and timing of slips between different parts of the country.

Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management

BACKGROUND

The interplay of host, agent, and environment implicated in traumatic brain injury (TBI) events is difficult to account for in hypothesis-driven research. Data-driven analysis of injury data can enable insight into injury events in novel ways. This research dissected complex and multidimensional data at the time of the TBI event by exploiting data mining and information visualization methods.

METHODS

We drew upon population-based decade-long health administrative data collected through the routine operation of the publicly funded health system in Ontario, Canada. We applied a computational approach to categorize health records of 235,003 patients with TBI versus the same number of reference patients without TBI, individually matched based on sex, age, place of residence, and neighbourhood income quantile. We adopted the basic concepts of the Haddon Matrix (host, agent, environment) to organize emerging factors significantly related to TBI versus non-TBI events. To explore sex differences, the data of male and female patients with TBI were plotted on heatmaps and clustered using hierarchical clustering algorithms.

RESULTS

Based on detected similarities, the computational technique yielded 34 factors on which individual TBI-event codes were loaded, allowing observation of a set of definable patterns within the host, the agent, and the environment. Differences in the patterns of host, agent and environment were found between male and female patients with TBI, which are currently not identified based on data from injury surveillance databases. The results were internally validated.

CONCLUSIONS

The study outlines novel areas for research relevant to TBI and offers insight into how computational and visual techniques can be applied to advance the understanding of TBI event. Results highlight unique aspects of sex differences of the host and agent at the injury event, as well as differences in exposure to adverse social and environmental circumstances, which can be a function of gender, aiding in future studies of injury prevention and gender-transformative care.

Sickness absence and disability pension among injured working-aged pedestrians - a population-based Swedish register study

Background

The knowledge is scarce about sickness absence (SA) and disability pension (DP) among pedestrians injured in a traffic-related accident, including falls. Thus, the aim was to explore the frequencies of types of accidents and injuries and their association with SA and DP among working-aged individuals.

Methods

A nationwide register-based study, including all individuals aged 16-64 and living in Sweden, who in 2010 had in- or specialized outpatient healthcare after a new traffic-related accident as a pedestrian. Information on age, sex, sociodemographics, SA, DP, type of accident, injury type, and injured body region was used. Frequencies of pedestrians with no SA or DP, with ongoing SA or full-time DP already at the time of the accident, and with a new SA spell >14 days in connection to the accident were analyzed. Crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for new SA were estimated by logistic regression.

Results

In total, 5576 pedestrians received healthcare due to a traffic-related accident (of which 75% were falls, with half of the falls related to snow and ice). At the time of the accident, 7.5% were already on SA and 10.8% on full-time DP, while 20% started a new SA spell. The most common types of injuries were fractures (45%) and external injuries (30%). The body region most frequently injured was the lower leg, ankle, foot, and other (in total 26%). Older individuals had a higher OR for new SA compared with younger (OR 1.91; 95% CI 1.44-2.53, for ages: 45-54 vs. 25-34). The injury type with the highest OR for new SA, compared with the reference group external injuries, was fractures (9.58; 7.39-12.43). The injured body region with the highest OR for new SA, compared with the reference group head, face, and neck, was lower leg, ankle, foot, and other (4.52; 2.78-7.36).

Conclusions

In this explorative nationwide study of the working-aged pedestrians injured in traffic-related accidents including falls, one fifth started a new SA spell >14 days. Fractures, internal injuries, collisions with motor vehicle, and falls related to snow and ice had the strongest associations with new SA.

Measurement Quality Appraisal Instrument for Evaluation of Walkability Assessment Tools Based on Walking Needs

Walking is a sustainable commute mode, and walkability is considered an essential sign of sustainable mobility. To date, many walkability assessment tools have been developed to assess the walkability conditions across the world. However, there is a paucity of comprehensive methods to assess current walkability tools based on walking needs and ensure all walking requirements are included. Thus, researchers and experts are unable to select the most comprehensive tool systematically. The present study attempts to develop a system to evaluate the quality of the existing tools. The instrument focuses on factors related to walking needs frequently observed in all types of walkability assessment tools. Hence, a pilot measurement quality appraisal instrument (MQAI) is developed and tested by a research team with planning and public health backgrounds. The final MQAI is tested by suitable reliability, criterion, and content validity tests. Most appraisal scales display moderate to high reliability for both audits and questionnaires. The MQAI appears as ready for use in several applications, including meta-analyses and systematic reviews. Additionally, the MQAI can be used by practitioners and planners to identify the most comprehensive and efficient assessment tools based on their needs.

A retrospective registry analysis of the transport-related health burden of wheeled recreational devices in Queensland, Australia

OBJECTIVE

Evaluate injury patterns from wheeled recreational devices (WRD) in the public space and explore risk factors for hospital admission.

METHOD

A cross-sectional analysis of WRD injury prevalence and risk factors for hospital admissions was conducted using data from the Queensland Injury Surveillance Unit (QISU) database for 2007 to 2017. Descriptive statistics and a log-binomial regression model were used to calculate adjusted relative risk for hospital admission.

RESULTS

Most WRD injury in the public space was related to stand-alone WRD injury events such as falls, with few reported WRD users being hit by vehicles from 2007 to 2017. Stand-alone WRD injury events had a higher independent risk of hospital admissions when injured in the head/neck/face (RR 2.08, 95%CI 1.6 to 2.8, p<0.001), and when the injury was a fracture (RR 2.57, 95%CI 2.1 to 3.3, p<0.001) or a brain injury (RR 3.19, 95%CI 2.5 to 4.1, p<0.001).

CONCLUSION

Head, brain and facial injuries and fractures are leading preventable factors for hospital admissions due to WRD injury. These types of injuries generate a preventable burden to the health system. Implications for public health: The results support the need to consider legislation regarding mandatory helmet use for non-motorised WRD when used on public roads and footpaths, while further research is conducted. This strategy could reduce the long-term health outcomes associated with head, face and brain injury in young commuters.

Applying deep neural networks and inertial measurement unit in recognizing irregular walking differences in the real world

Falling injuries pose serious health risks to people of all ages, and knowing the extent of exposure to irregular surfaces will increase the ability to measure fall risk. Current gait analysis methods require overly complicated instrumentation and have not been tested for external factors such as walking surfaces that are encountered in the real-world, thus the results are difficult to extrapolate to real-world situations. Artificial intelligence approaches (in particular deep learning networks of varied architectures) to analyze data collected from wearable sensors were used to identify irregular surface exposure in a real-world setting. Thirty young adults wore six Inertial Measurement Unit (IMU) sensors placed on their body (right wrist, trunks at the L5/S1 level, left and right thigh, left and right shank) while walking over eight different surfaces commonly encountered in the living community as well as occupational settings. Three variations of deep learning models were trained to solve this walking surface recognition problem: 1) convolution neural network (CNN); 2) long short term memory (LSTM) network and 3) LSTM structure with an extra global pooling layer (Global-LSTM) which learns the coordination between different data streams (e.g. different channels of the same sensor as well as different sensors). Results indicated that all three deep learning models can recognize walking surfaces with above 0.90 accuracy, with the Global-LSTM yielding the best performance at 0.92 accuracy. In terms of individual sensors, the right thigh based Global-LSTM model reported the highest accuracy (0.90 accuracy). Results from this study provide further evidence that deep learning and wearable sensors can be utilized to recognize irregular walking surfaces induced motion alteration and applied to prevent falling injuries.

Effects of Functional Fitness Enhancement through Taekwondo Training on Physical Characteristics and Risk Factors of Dementia in Elderly Women with Depression

The purpose of this research is to identify the correlations between functional fitness enhancement through a long-term Taekwondo training program and the physical characteristics and risk factors of dementia among elderly women with depression. The study has found that conducting three 60-min Taekwondo training sessions a week for the duration of 12 weeks has enhanced a number of functional fitness indexes, including hand grip strength/weight (p < 0.01), 4-m gait speed (p < 0.001), 3-m timed up and go (p < 0.05), and figure-of-eight track (p < 0.05), and significantly improved general health condition indexes as well, including percent fat (p < 0.05), appendicular skeletal muscle mass index (p < 0.01), systolic blood pressure (p < 0.01), and diastolic blood pressure (p < 0.001). Furthermore, the arteriosclerosis index and cognitive function have been found to be improved with an increase of brain-derived neurotrophic factor (BDNF; which prevents dementia) and a significant decrease of β-amyloid—a risk factor of dementia—as a result of enhancements in serum lipids and adiponectin, confirming the positive effects of functional fitness enhancement on fighting depression, promoting physical characteristics, and reducing the risk factors of dementia.

Model-based economic evaluation of ice cleat distribution programmes for the prevention of outdoor falls among adults from a Swedish societal perspective

Background

Slipping on snow or ice poses a significant health risk among older adults in Sweden. To combat this problem, about 80 Swedish municipalities have distributed ice cleats to older citizens (65+ years old) over the last decade. This paper details a cost–benefit analysis of such programmes.

Materials and methods

We developed a decision-analytical model to estimate the costs and benefits of ice cleat programmes in Swedish municipalities compared with a business-as-usual scenario. The modelled benefits of the programme were based on effect estimates from previous research, data from population and healthcare registers and a survey of attitudes to and actual ice cleat use. The modelled costs of the programme were based on resource use data collected from 34 municipalities with existing ice cleat programmes. We assessed heterogeneity in the potential impact and benefit-to-cost ratios across all Swedish municipalities as a function of the average number of days with snow cover per year. Uncertainty in the cost–benefit results was assessed using deterministic and probabilistic sensitivity analyses.

Results

The average benefit-to-cost ratio was 87, ranging from about 40 in low-risk municipalities to 140 in high-risk municipalities, implying that the potential benefits of ice cleat programmes greatly outweigh their costs. Probabilistic and deterministic sensitivity analyses support the robustness of this conclusion to parameter uncertainty and large changes in assumptions about the magnitude of the impact on ice cleat use and injuries.

Conclusion

The benefits of distributing ice cleats to older adults appear to outweigh the costs from a Swedish societal perspective.

Older adult pedestrian trauma: A systematic review, meta-analysis, and GRADE assessment of injury health outcomes from an aggregate study sample of 1 million pedestrians

This systematic review sought to assess older adult pedestrian injury severity, injury by anatomical location and incidence proportions, including comparisons to younger age groups when available and provide an analysis of the quality of the existing evidence. A structured search was conducted in PubMed, Embase, Scopus, CINAHL, PsycInfo, AMED, Web of Science, LILACS and TRID. STROBE was used to assess the reporting quality of the included studies. Random-effect model meta-analysis served to obtain pooled relative risk, incidence proportions and standardized mean differences for different outcomes due to pedestrian crashes comparing older and younger pedestrians, while meta-analyses could not be conducted for pedestrian falls. We screened 7460 records of which 60 studies (1,012,041 pedestrians) were included in the review. Injured pedestrians 60+ compared to those <60 were found to have a higher relative risk of severe injury (pooled relative risk RR 1.6, 95 % CI: 1.4-2.0 p < 0.001), critical care admission (pooled RR 1.5, 95 %CI: 1.3-1.8 p < 0.001), and fatality (pooled RR of 3.7, 95 % CI: 3.0-4.5 p < 0.001). Pedestrians 60+ also had higher incidence rates of pedestrian falls causing higher injury severity. GRADE was used to evaluate evidence quality, with the results suggesting that the overall quality of the evidence supporting these findings was low. Further research is needed to understand health risks associated with older pedestrian trauma and to develop effective risk management strategies.

Out of the silos: embedding injury prevention into the Sustainable Development Goals

Globally, unintentional injuries contribute significantly to disability and death. Prevention efforts have traditionally focused on individual injury mechanisms and their specific risk factors, which has resulted in slow progress in reducing the burden. The Sustainable Development Goals (SDGs) represent a global agenda for promoting human prosperity while respecting planetary boundaries. While injury prevention is currently only recognised in the SDG agenda via two road safety targets, the relevance of the SDGs for injury prevention is much broader. In this State of the Art Review, we illustrate how unintentional injury prevention efforts can be advanced substantially within a broad range of SDG goals and advocate for the integration of safety considerations across all sectors and stakeholders. This review uncovers injury prevention opportunities within broader global priorities such as urbanisation, population shifts, water safeguarding and corporate social responsibility. We demonstrate the relevance of injury prevention efforts to the SDG agenda beyond the health goal (SDG 3) and the two specific road safety targets (SDG 3.6 and SDG 11.2), highlighting 13 additional SDGs of relevance. We argue that all involved in injury prevention are at a critical juncture where we can continue with the status quo and expect to see more of the same, or mobilise the global community in an 'Injury Prevention in All Policies' approach.

Effects of triceps surae fatigue and weight training level on gait variability and local stability in young adults

Muscle fatigue negatively affects gait, and the changes in gait pattern due to muscle fatigue is influenced by which muscles are fatigued and pre-existing physical activity levels. However, how these factors alter gait stability and variability, measures related to risk of fall, remains unclear. To explore how muscular fatigue affects linear and nonlinear gait features in young adults, the effects of triceps surae fatigue and weight training level on gait variability and local stability, as well as a 12-min recovery time of post-fatigue period, were evaluated in young adults (trained and untrained groups). Some features were estimated, i.e., (i) step length (SL) and step frequency (SF), (ii) average standard deviation of trunk acceleration along strides (VAR), and (iii) local dynamic stability (LDS; maximum Lyapunov exponent). LDS presented a significant increase in the anterior-posterior direction with recovery to trained group. SL and SF changed immediately post-fatigue and recovered for both groups, while VAR increased significantly in all directions, with a recovery in the vertical direction for both groups and in the medial-lateral direction for trained group. Localized fatigue affected the analyzed gait variables independent of the participant's training condition, and an interval of 12 min does not seem to be enough for a complete recovery, suggesting a longer recovery period after tasks involving localized triceps surae fatigue to guarantee basal levels of gait variability and local stability. Graphical abstract Flow chart of the experimental protocol. A) Pre-fatigue: 4 min walking at PWS. B) Post-fatigue: first 4 min walking after fatigue protocol. C) Post-fatigue: second 4 min walking after fatigue protocol. D) Post-fatigue: third 4 min walking after fatigue protocol (PWS, preferred walking speed; AP, anterior-posterior; V, vertical; ML, medial-lateral).

Falls among physically active elderly in senior housings, Bangkok, Thailand: situations and perceptions

PURPOSE

A mixed-method study aimed to assess situations in which falls occur including prevalence and associated risk factors of falls among physically active elderly who are at risk of experiencing a fall in senior housings, Bangkok, Thailand, and their perceptions regarding falls.

PATIENTS AND METHODS

In the first phase, a cross-sectional study was conducted on 64 physically active elderly senior housing residents. Data on sociodemographics, health status, Barthel Index (BI) of activities of daily living, and fall experiences were collected through face-to-face interviews. Data on balance scores were obtained from Time Up and Go (TUG) test and Berg Balance Scale (BBS). In the second phase, a qualitative study was conducted on 41 physically active elderly who had experienced falls. Data regarding perception on falls, fall preventions, and fall management, were gathered through in-depth interviews from November 2017 to December 2017.

RESULTS

The prevalence of falls among participants in senior housings was 64.1%. Univariate analysis found that a higher BI was associated with fall (P<0.004). Multivariate analysis using binary logistic regression showed that a higher BI (OR=6.00, 95% CI=1.24-29.10) together with ≥2 environmental hazards (OR=6.33, 95% CI=1.24-32.29) were associated with fall. The result from content analysis indicated that the elderly were aware that they were at risk of fall. In addition, the elderly also perceived that fall could be avoided even though they did not know how to prevent it.

CONCLUSION

The prevalence of fall among physically active elderly in senior housings was relatively high. A higher BI scale and having ≥2 environmental hazards were associated risk factors of falls. Although the elderly perceived that fall could be avoided, they did not know how to prevent it. The intervention that focuses on environmental modification, balancing enchantment, and education on fall prevention is highly required.