As vulnerable road users, pedestrians and cyclists are facing a growing number of injuries and fatalities, which has raised increasing safety concerns globally. Based on the crash records collected in the Australian Capital Territory (ACT) in Australia from 2012 to 2021, this research firstly establishes an extended crash dataset by integrating road network features, land use features, and other features. With the extended dataset, we further explore pedestrian and cyclist crashes at macro- and micro-levels. At the macro-level, random parameters negative binomial (RPNB) model is applied to evaluate the effects of Suburbs and Localities Zones (SLZs) based variables on the frequency of pedestrian and cyclist crashes. At the micro-level, binary logit model is adopted to evaluate the effects of event-based variables on the severity of pedestrian and cyclist crashes. The research findings show that multiple factors are associated with high frequency of pedestrian total crashes and fatal/injury crashes, including high population density, high percentage of urban arterial road, low on-road cycleway density, high number of traffic signals and high number of schools. Meanwhile, many factors have positive relations with high frequency of cyclist total crashes and fatal/injury crashes, including high population density, high percentage of residents cycling to work, high median household income, high percentage of households with no motor vehicle, high percentage of urban arterial road and rural road, high number of bus stops and high number of schools. Additionally, it is found that more severe pedestrian crashes occur: (i) at non-signal intersections, (ii) in suburb areas, (iii) in early morning, and (iv) on weekdays. More severe cyclist crashes are observed when the crash type is overturned or struck object/pedestrian/animal; when more than one cyclist is involved; and when crash occurs at park/green space/nature reserve areas.

UNASSIGNED: Annually since 2008; over 38% of fatally injured motorcycle riders and 20% of pedalcyclists involved in traffic crashes were under the influence of alcohol, yet public health surveillance of alcohol involvement in these injuries is underdeveloped. This study determined alcohol involvement among fatally and non-fatally injured pedalcycle and motorcycle riders and compared findings across three national public-use datasets.
UNASSIGNED: Using the 2019 National Emergency Medical Services Information System (NEMSIS), the Fatality Analysis Reporting System (FARS), and National Electronic Injury Surveillance System (NEISS) datasets, we identified alcohol involvement in fatal and non-fatal injuries to pedalcycle and motorcycle riders (≥21 years). Alcohol involvement was positive based on the clinician\'s evaluation of alcohol at the scene (NEMSIS) or within the ED record (NEISS); or when Blood Alcohol Content (BAC) values were ≥.01 (FARS). Pedalcycle and motorcycle injuries were identified across datasets using: 1) ICD10 codes for pedalcycle (V10-V19) or motorcycle (V20-V29) within the cause of injury and EMS respondent\'s impression of the encounter variables (NEMSIS); 2) product codes for bicycles or moped/power-assisted cycle/minibike/two-wheeled, powered, off-road vehicles (NEISS); and 3) American National Standard Institute\'s classifications for pedalcycle and motorcycle in the person and vehicle type variables (FARS). The descriptive epidemiology was compared across datasets.
UNASSIGNED: There were 26,295 pedalcyclist and 50,122 motorcycle rider injuries resulting in an EMS response within NEMSIS data; 10.2% and 8.5% of these injuries respectively involved alcohol. These estimates were greater than the 7.3% of pedalcyclist and 6.1% of moped/power-assisted cycle/minibike/two-wheeled, powered, off-road vehicle injuries involving alcohol among patients who presented to an ED within the NEISS dataset. Based on FARS data, alcohol was involved in 27.0% of pedalcyclist and 42.0% of motorcyclist fatal injuries. Regardless of the data source, pedalcyclist and motorcycle fatal and non-fatal injuries were more likely to involve alcohol among middle-aged adults compared to older and early aged adults, and for men compared to women, with proportions that were generally 3-8% higher for men.
UNASSIGNED: Measures for pedalcycle and motorcycle injuries and alcohol involvement vary substantially across national public-use datasets. Standardized, valid, and feasible methods are needed to accurately inform injury prevention efforts.

Engagement in physical activity, across various sports, promotes a diverse microbiota in active individuals. This study examines the gut microbiota of Colombian athletes, specifically weightlifters (n = 16) and road cyclists (n = 13), compared to non-athletes (n = 15). Using Kruskal-Wallis tests, the physical activity level of a group of non-athletic individuals and the sports experience of a group of professional athletes is analyzed. The median age of participants is 24 years, comprising 25 men and 19 women. The microbiota is collected using fecal samples. Participants provided these samples during their pre-competitive stage, specifically during the concentration phase occurring two weeks prior to national competitions. This timing is chosen to capture the microbial composition during a period of heightened physical preparation. Questionnaire responses and microbial composition assessments identify disparities among groups. Microbial composition analysis explores core microbiome, abundance, and taxonomy using Pavian, MicrobiomeAnalyst 2.0, and GraPhlAn. ANCOM-BC2 reveals differentially abundant species. Road cyclists exhibit decreased Bacteria and increased Archaea abundance. Phylum-level variations included Planctomycetes, Acidobacteria, and Proteobacteria, while Bacteroidetes prevailed. Key families influencing gut microbiota are Bacteroidaceae, Muribaculaceae, and Selenomonadaceae. Weightlifters exhibit unique viral and archaeal community connections, while cyclists showed specialized microbial interplay influenced by endurance exercise. Correlation network analysis emphasizes distinctive microbial interactions within athlete groups, shedding light on the impact of physical activities on gut microbiota and athlete health.

Cyclists are particularly vulnerable to travel-related exposure to air pollution. Understanding the factors that increase exposure is crucial for promoting healthier urban environments. Machine learning models have successfully predicted air pollutant concentrations, but they tend to be less interpretable than classical statistical ones, such as linear models. This study aimed to develop a predictive model to assess cyclists\' exposure to fine particulate matter (PM2.5) in urban environments. The model was generated using geo-temporally referenced data and machine learning techniques. We explored several models and found that the gradient boosting machine learning model best fitted the PM2.5 predictions, with a minimum root mean square error value of 5.62 μg m-3. The variables with greatest influence on cyclist exposure were the temporal ones (month, day of the week, and time of the day), followed by meteorological variables, such as temperature, relative humidity, wind speed, wind direction, and atmospheric pressure. Additionally, we considered relevant attributes, which are partially linked to spatial characteristics. These attributes encompass street typology, vegetation density, and the flow of vehicles on a particular street, which quantifies the number of vehicles passing a given point per minute. Mean PM2.5 concentration was lower in bicycle paths away from vehicular traffic than in bike lanes along streets. These outcomes underscore the need to thoughtfully design public transportation routes, including bus routes, concerning the network of bicycle pathways. Such strategic planning attempts to improve the air quality in urban landscapes.

Over the past few decades, a growing attention has been directed toward cycling due to its positive impacts on social, economic, and health aspects. Various countries are adopting and implementing strategies to promote cycling as a daily mode of transport. The main objective of this study is to improve cyclists\' safety by investigating the impact of different layouts of on-road cycle lanes at two-lane two-way roads on drivers\' interactions with cyclists using driving simulator. Three layouts of on-road cycle lanes were tested and compared, namely, uncolored, colored, and island separation, along with a control case where no cycle lane was provided. In addition, the impact of road alignments (straight sections, left and right curves) and the presence of an opposing vehicle were investigated. The driving simulator at Qatar University was used to conduct this study. A total of 92 subjects participated in this study. According to the results, on-road cycle lanes can significantly increase the safety of cyclists compared to shared lanes with motorized traffic. Moreover, the results showed that the drivers\' intrusion to the opposite lane in the presence of opposing vehicles can be eliminated by providing on-road cycle lanes. That is, drivers\' crash risk can also be reduced through the provision of on-road cycle lanes. Comparison of different on-road cycle lane treatments showed that uncolored cycle lanes outperformed the other layouts in terms of lateral clearance between the driver and the cyclist for right and straight alignments. On the other hand, the colored cycle lane showed better results for the left alignment. The findings of this study could be useful for designing on-road bicycle infrastructure to eliminate possible vehicle-cyclist and vehicle-vehicle conflicts and minimize crash risk.

Increasing the role of cycling is necessary to reduce physical inactivity. While promoting cycling, attention should also be given to traffic safety. Hence, a better understanding on the underlying factors and safety recommendations of cyclist crashes is needed. This study aims to increase knowledge on fatal single-bicycle crashes (SBCs), where other road users are not collided with.
Data from in-depth investigated fatal cyclist crashes in Finland is analyzed from 2010 to 2019. The study presents descriptive analysis of the characteristics, underlying factors, and safety recommendations of SBCs (n = 82) and other cyclist crashes (n = 151). Logistic regression analysis and chi-squared tests were performed to identify significant characteristics for SBCs.
Fatal SBCs commonly involved people aged 60 or older, males, and cyclist not wearing a helmet. Cyclist\'s health issues influenced the crash in 62.2% of the SBCs. Compared to other cyclist crashes, health issues, alcohol, males, other crash locations than intersections, and weekends were highlighted in SBCs. Safety recommendations emphasized human factors, such as informing cyclist about underlying factors and the use of safety equipment.
In addition to human factors, the safety recommendations included suggestions regarding the bicycle, the traffic environment, and traffic regulations. This highlights the need to focus on different safety improvement actions to reduce SBCs. This study identified key characteristics of SBCs, which may help traffic safety authorities address this road safety issue and ultimately help to promote cyclist safety.
Cooperation between the actors including health care providers and the police is also proposed to address cyclists\' health issues that contribute to SBCs.

Road traffic injuries remain one of the common and leading causes of death among children and adolescents till the age of 19 years. Road safety is important for children since their physical activity, active travel, independence and development are largely affected by it. Solutions for road safety with benefits for people as well as an economy exist which should be implemented effectively and efficiently. These solutions which combine engineering, legislation and behavioural interventions should be implemented in an integrated Safe Systems Approach. The future of the children must be safeguarded from these injuries and every effort towards it being converted into \"bygone figures\" must be done diligently and honestly. The various risk factors and interventions possibly explained in this review article shall help in better understanding of the causes and possible guidelines at a policy level to prevent road traffic injuries in children.

Background: Traffic accidents are an important issue for public health and a threat for sustainable development, with pedestrians and cyclists having been recognized as the most vulnerable actors on the streets. The objective of this study was to analyze the profiles of pedestrians and cyclists who died as a result of traffic accidents in Colombia during the 1998-2019 period. Methods: An observational and descriptive study, with the deaths due to traffic accidents in Colombia between 1998 and 2019 as data source. Secondary data were taken from the Vital statistics of Colombia (EEVV), published by Departamento Administrativo Nacional de Estadística (DANE). A trend analysis of the number of deaths during the period under study was performed, and such number was examined against sex to identify potential differences. Multiple correspondence analysis was employed to elaborate the profile of pedestrians and cyclists who die due to traffic accidents. Three profiles were prepared for each road actor: a global profile, one for 1998, and another for 2019. Results: The mortality profiles are different for pedestrians and cyclists, and, in turn, there are also demographic, geographic, and socioeconomic conditions in each type of road actor, which determine higher mortality risks. High population density, younger age group in the cyclists and adults among the pedestrians, low schooling levels and absence of health insurance are suggested as key factors in these profiles. Related to sex, for men is not possible to establish a profile. Women\'s cases are commonly related to health insurance, age, and population density. Conclusions: Several contextual and demographic characteristics in pedestrians and cyclists allow delimiting mortality profiles. The profiles that were identified suggest the need to articulate road safety policies with other social and development policies in order to coordinate and integrate intersectoral actions that reduce mortality in these road actors.

Road trauma is a major public health concern, often resulting in reduced health-related quality of life and prolonged absenteeism from work even after so-called \'minor\' injuries that do not result in hospitalization. This manuscript compares pre-injury health, sociodemographic characteristics and injury details between age, sex, and road user categories in a cohort of 1,480 road trauma survivors.
This was a prospective observational inception cohort study of road trauma survivors recruited between July 2018 and March 2020 from three trauma centres in British Columbia, Canada. Participants were aged ≥ 16 years and arrived in a participating emergency department within 24 h of involvement in a motor vehicle collision. Data were collected from structured interviews and review of medical records.
The cohort of 1,480 road trauma survivors included 280 pedestrians, 174 cyclists, 118 motorcyclists, 683 motor vehicle drivers, and 225 passengers. Median age was 40 (IQR = [27, 57]) years; 680 (46%) were female. Males and younger patients were significantly more likely to report better pre-injury physical health. Motorcyclists and cyclists tended to report better physical health and less severe somatic symptoms, whereas pedestrians and motor vehicle drivers reported better mental health. Injury severity and hospital admission rates were higher in pedestrians and motorcyclists and lower in motorists. Upper and lower extremity injuries were most common in pedestrians, cyclists and motorcyclists, whereas neck injuries were most common in motor vehicle drivers and passengers.
In a large cohort of road trauma survivors, overall injury severity was low. Motorcyclists and pedestrians, but not cyclists, had more severe injuries than motorists. Extremity injuries were more common in vulnerable road users. Future research will investigate one-year recovery outcomes and identify risk factors for poor recovery.

Purpose: The aim of the study was to compare bone mineral density (BMD) in the lumbar spine (LSBMD) and the femoral neck (FBMD) in male road cyclists (RC n = 39), mountain cyclists (MC n = 30) and controls (C n = 27) and to determine the factors associated with BMD in the same group of participants. Methods: BMD, fat mass (FM) and fat-free mass (FFM) were measured using DXA. Calcium intake (Cal), exercise energy expenditure (EEE) and energy availability (EA) were assessed using self-reported questionnaires. Samples for circulating hormones were also obtained. VO2max was estimated by a cycloergometric test. Results: After adjustment for body mass, in cyclists LSBMD (RC 0.98 ± 0.12; MC 0.98 ± 0.10 g/cm2) was significantly lower than in C (1.11 ± 0.10; p < .001), while FBMD resulted in no significant difference in cyclists compared to C (p = 0.213). EA (kcal/FFM/day) was different in cyclists and in C (p < .05). In C, EEE and EA were positively associated with LSBMD (R = 0.561, R = 0.656, respectively, p < .01), whereas only EA was associated with FBMD (R = 0.554, p < .05); a positive association between EA and FBMD was found in MC (R = 0.464, p < .05). A negative relationship between VO2max and LSBMD in RC (R = -0.418, p < .05) and a positive one between EEE and LSBMD in MC were found (R = 0.605, p < .001). CaI, free testosterone and cortisol were unrelated to BMD. Conclusion: Both the RC and MC had lower LSBMD than C, whereas no difference was found between the two groups of cyclists. The factors associated with BMD are manifold, vary in relation to the measurement site and are likely different in RC, MC and C.