ABSTRACT
BACKGROUND: Greater public transport use has been linked to higher physical activity levels. However, neither the amount of physical activity associated with each daily public transport trip performed, nor the potential total physical activity gain associated with an increase in trips/day, has been determined. Using objective measures, we aimed to quantify the association between public transport use, physical activity and sedentary time. METHODS: A longitudinal study of Australian adults living in Hobart, Tasmania, who were infrequent bus users (≥ 18 years; used bus ≤ 2 times/week). The number of bus trips performed each day was determined from objective smartcard data provided by the public transportation (bus) provider across a 36-week study timeframe. Accelerometer measured steps/day (primary outcome), moderate-to-vigorous physical activity (min/day), and sedentary time (min/day) were assessed across four separate one-week periods. RESULTS: Among 73 participants across 1483 day-level observations, on days that public transport was used, participants achieved significantly more steps (ß = 2147.48; 95%CI = 1465.94, 2829.03), moderate to vigorous physical activity (ß = 22.79; 95% CI = 14.33, 31.26), and sedentary time (ß = 37.00; 95% CI = 19.80, 54.21) compared to days where no public transport trips were made. The largest increase in steps per day associated with a one-trip increase was observed when the number of trips performed each day increased from zero to one (ß = 1761.63; 95%CI = 821.38, 2701.87). The increase in the number of steps per day was smaller and non-significant when the number of trips performed increased from one to two (ß = 596.93; 95%CI=-585.16, 1779.01), and two to three or more (ß = 632.39; 95%CI=-1331.45, 2596.24) trips per day. Significant increases in sedentary time were observed when the number of trips performed increased from zero to one (ß = 39.38; 95%CI = 14.38, 64.39) and one to two (ß = 48.76; 95%CI = 25.39, 72.12); but not when bus trips increased from two to three or more (ß=-27.81; 95%CI=-76.00, 20.37). CONCLUSIONS: Greater public transport use was associated with higher physical activity and sedentary behaviour. Bus use may yield cumulative increases in steps that amount to 15-30% of the daily recommended physical activity target. A policy and public health focus on intersectoral action to promote public transport may yield meaningful increases in physical activity and subsequent health benefits.
Subject(s)
Accelerometry , Exercise , Sedentary Behavior , Transportation , Humans , Transportation/methods , Male , Female , Adult , Longitudinal Studies , Middle Aged , Tasmania , AustraliaABSTRACT
Disruptive events cause decreased functionality of transportation infrastructures and enormous financial losses. An effective way to reduce the effects of negative consequences is to establish an optimal restoration plan, which is recognized as a method for resilience enhancement and risk reduction in the transportation system. This study takes the total travel time as the resilience measure to formulate a bilevel optimization model for a given scenario. However, the uncertainties involved in restoration activities cannot be overlooked. In this context, the inherent uncertainty is represented with a set of scenarios generated via the Latin hypercube technique. To assess the risk under uncertainty, a conditional value at risk with regret (CVaR-R) measure is introduced when considering the existence of worst-case scenarios. Then, the bilevel programming model is transformed from the deterministic case to the stochastic case, where the upper-level problem determines the restoration sequence to minimize CVaR-R and the lower-level problem is a traffic assignment problem. An integrated framework based on a novel genetic algorithm and the Frank-Wolfe algorithm is designed to solve the stochastic model. Numerical experiments are conducted to demonstrate the properties of the proposed bilevel programming model and the performance of the solution algorithm. The proposed methodology provides new insights into the restoration optimization problem, which provides a reference for emergency decision-making.
Subject(s)
Algorithms , Transportation , Uncertainty , Transportation/methods , Models, Theoretical , HumansABSTRACT
BACKGROUND: This study aimed to compare the overall prevalence, stratified by sex and age group of global physical activity (GPA), active commuting to school (ACS), and sedentary behavior (SB) among adolescents from ten Latin American countries, and to assess the correlation of Development Index with the indicators. METHODS: This research is grounded on data from the Global School-Based Student Health Survey (2009-2015) and the 2015 Brazilian National School Health Survey. The prevalence and 95% confidence intervals for GPA (≥5 d/wk), ACS (≥1 d/wk), and SB (>2 h/d) were calculated using the chi-square test to compare the sexes (male; female) and age group (≤13 y; 14 y; 15 y; ≥16 y). We also performed Pearson correlation analysis with the Human Development Index. RESULTS: The prevalence of indicators ranged from 16.1% to 28.2% for GPA, from 56.7% to 71.2% for ACS, and from 20.7% to 62.6% for SB. Boys generally had a higher prevalence of GPA and ACS, and girls had a higher prevalence of SB. The prevalence of the indicators by age group varied between countries, with significant differences observed in some, depending on each indicator. A positive correlation was observed between Human Development Index, GPA, and SB. CONCLUSION: Health promotion policies must include guidelines that encourage and promote a more active and less sedentary lifestyle among young people in Latin America, considering specific groups, the local socioeconomic context, and differences between countries.
Subject(s)
Exercise , Health Surveys , Schools , Sedentary Behavior , Transportation , Humans , Adolescent , Male , Female , Latin America , Transportation/methods , Students/statistics & numerical data , Sex Factors , Prevalence , Child , Brazil/epidemiologyABSTRACT
With the continuous development of large-scale engineering projects such as construction projects, relief support, and large-scale relocation in various countries, engineering logistics has attracted much attention. This paper addresses a multimodal material route planning problem (MMRPP), which considers the transportation of engineering material from suppliers to the work zones using multiple transport modes. Due to the overall relevance and technical complexity of engineering logistics, we introduce the key processes at work zones to generate a transport solution, which is more realistic for various real-life applications. We propose a multi-objective multimodal transport route planning model that minimizes the total transport cost and the total transport time. The model by using the ε - constraint method that transforms the objective function of minimizing total transportation cost into a constraint, resulting in obtaining pareto optimal solutions. This method makes up for the lack of existing research on the combination of both engineering logistics and multimodal transportation, after which the feasibility of the model and algorithm is verified by examples. The results show that the model solution with the introduction of the key processes at work zones produces more time-efficient and less time-consuming route planning results, and that the results obtained using the ε - constraint method are more reliable than the traditional methods for solving multi-objective planning problems and are more in line with the decision maker's needs.
Subject(s)
Algorithms , Models, Theoretical , Transportation , Transportation/methods , Engineering/methods , Humans , WorkplaceABSTRACT
Built environment approaches that improve active transportation infrastructure and environmental design can increase physical activity. Funded by the Centers for Disease Control and Prevention, the Texas Department of State Health Services rejuvenated the Texas Plan4Health program from 2018 to 2023 to expand such approaches in Texas by providing technical assistance to teams of local public health professionals and planners to identify and implement projects connecting people to everyday destinations via active transport in their communities. However, the COVID-19 pandemic prompted Texas Plan4Health to modify the delivery of technical assistance to accommodate restrictions on travel and in-person gatherings. We used qualitative methods to conduct a postintervention process evaluation to describe the modified technical assistance process, understand the experiences of the 4 participating communities, and identify short-term outcomes and lessons learned. Texas Plan4Health helped communities overcome common barriers to built environment change, facilitated collaboration across community public health and planning professionals, and educated professionals about active transportation infrastructure and the relationship between their disciplines, thereby increasing community capacity to implement built environment improvements. This outcome, however, was mediated by the pre-existing resources and previous experiences with active transportation planning among the participating communities. Public health practitioners seeking to improve active transportation infrastructure and environmental design for physical activity should consider community-engaged approaches that advance partnership-building and collaborative experiential education among public health, planning, and other local government representatives, directing particular attention and additional training toward communities with fewer resources.
Subject(s)
Built Environment , COVID-19 , Exercise , Health Promotion , Humans , Texas , COVID-19/prevention & control , COVID-19/epidemiology , Health Promotion/methods , Public Health/methods , SARS-CoV-2 , Transportation/methods , Health Planning Technical AssistanceABSTRACT
BACKGROUND: Active transport- for example walking and bicycling to travel from place to place- may improve physical fitness and health and mitigate climate change if it replaces motorised transport. The aim of this study is to analyse the active transport behaviour of adults living in Germany, to investigate differences among population groups and to determine whether climate protection is a frequent motive for this behaviour. METHODS: This study uses self-reported data of 4,971 adults who participated in a national health survey (German Health Update 2021), which was conducted as a telephone survey from July to December 2021. Associations between active transport behaviour and corresponding motives with sociodemographic and health-related variables were analysed using logistic regression models. RESULTS: Of the adult population, 83% use active transport at least once a week. The frequency and duration of walking per week are significantly higher than those for bicycling (walking 214 min/week; bicycling 57 min/week). Those with a lower education level are less likely to practise active transport than those with a higher education level. Furthermore, women are less likely to use a bicycle for transport than men. Among those practising active transport, the most frequently mentioned motive is "is good for health" (84%) followed by "to be physically active" (74%) and "is good for the climate/environment" (68%). Women and frequent bicyclists (at least 4 days/week) mention climate protection as a motive more often than men and those bicycling occasionally. CONCLUSIONS: The improvement of active transport, especially among people with lower education and women (for bicycling), may benefit from better insights into motives and barriers. Climate protection is an important motivator for practising active transport within the adult population living in Germany and should therefore have greater emphasis in behavioural change programmes.
Subject(s)
Bicycling , Motivation , Transportation , Walking , Humans , Germany , Female , Male , Adult , Bicycling/statistics & numerical data , Bicycling/psychology , Middle Aged , Cross-Sectional Studies , Walking/statistics & numerical data , Walking/psychology , Young Adult , Aged , Transportation/statistics & numerical data , Transportation/methods , Adolescent , Climate Change , Health Behavior , Health SurveysABSTRACT
Encouraging routine COVID-19 vaccinations is likely to be a crucial policy challenge for decades to come. To avert hundreds of thousands of unnecessary hospitalizations and deaths, adoption will need to be higher than it was in the autumn of 2022 or 2023, when less than one-fifth of Americans received booster vaccines1,2. One approach to encouraging vaccination is to eliminate the friction of transportation hurdles. Previous research has shown that friction can hinder follow-through3 and that individuals who live farther from COVID-19 vaccination sites are less likely to get vaccinated4. However, the value of providing free round-trip transportation to vaccination sites is unknown. Here we show that offering people free round-trip Lyft rides to pharmacies has no benefit over and above sending them behaviourally informed text messages reminding them to get vaccinated. We determined this by running a megastudy with millions of CVS Pharmacy patients in the United States testing the effects of (1) free round-trip Lyft rides to CVS Pharmacies for vaccination appointments and (2) seven different sets of behaviourally informed vaccine reminder messages. Our results suggest that offering previously vaccinated individuals free rides to vaccination sites is not a good investment in the United States, contrary to the high expectations of both expert and lay forecasters. Instead, people in the United States should be sent behaviourally informed COVID-19 vaccination reminders, which increased the 30-day COVID-19 booster uptake by 21% (1.05 percentage points) and spilled over to increase 30-day influenza vaccinations by 8% (0.34 percentage points) in our megastudy. More rigorous testing of interventions to promote vaccination is needed to ensure that evidence-based solutions are deployed widely and that ineffective but intuitively appealing tools are discontinued.
Subject(s)
COVID-19 Vaccines , COVID-19 , Immunization, Secondary , Reminder Systems , Transportation , Vaccination , Adult , Female , Humans , Male , Middle Aged , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , Evidence-Based Practice , Health Education/methods , Health Education/statistics & numerical data , Health Policy/trends , Immunization, Secondary/statistics & numerical data , Influenza Vaccines/administration & dosage , Pharmacies/statistics & numerical data , Reminder Systems/classification , Reminder Systems/statistics & numerical data , Text Messaging/statistics & numerical data , Time Factors , Transportation/economics , Transportation/methods , United States , Vaccination/statistics & numerical dataABSTRACT
Over the last 4 decades, physical activity researchers have invested heavily in determining "what works" to promote healthy behaviors in schools. Single and multicomponent school-based interventions that target physical education, active transportation, and/or classroom activity breaks effectively increased physical activity among children and youth. Yet, few of these interventions are ever scaled-up and implemented under real-world conditions and in diverse populations. To achieve population-level health benefits, there is a need to design school-based health-promoting interventions for scalability and to consider key aspects of the scale-up process. In this opinion piece, we aim to identify challenges and advance knowledge and action toward scaling-up school-based physical activity interventions. We highlight the key roles of planning for scale-up at the outset, scale-up pathways, trust among partners and program support, program adaptation, evaluation of scale-up, and barriers and facilitators to scaling-up. We draw upon our experience scaling-up effective school-based interventions and provide a solid foundation from which others can work toward bridging the implementation-to-scale-up gap.
Subject(s)
Exercise , Health Promotion , School Health Services , Humans , School Health Services/organization & administration , Health Promotion/methods , Child , Physical Education and Training/methods , Schools , Adolescent , Program Evaluation , Transportation/methodsABSTRACT
Horses revolutionized human history with fast mobility1. However, the timeline between their domestication and their widespread integration as a means of transport remains contentious2-4. Here we assemble a collection of 475 ancient horse genomes to assess the period when these animals were first reshaped by human agency in Eurasia. We find that reproductive control of the modern domestic lineage emerged around 2200 BCE, through close-kin mating and shortened generation times. Reproductive control emerged following a severe domestication bottleneck starting no earlier than approximately 2700 BCE, and coincided with a sudden expansion across Eurasia that ultimately resulted in the replacement of nearly every local horse lineage. This expansion marked the rise of widespread horse-based mobility in human history, which refutes the commonly held narrative of large horse herds accompanying the massive migration of steppe peoples across Europe around 3000 BCE and earlier3,5. Finally, we detect significantly shortened generation times at Botai around 3500 BCE, a settlement from central Asia associated with corrals and a subsistence economy centred on horses6,7. This supports local horse husbandry before the rise of modern domestic bloodlines.
Subject(s)
Animal Husbandry , Domestication , Horses , Transportation , Animals , Female , Male , Animal Husbandry/history , Asia , Europe , Genome/genetics , History, Ancient , Horses/classification , Horses/genetics , Reproduction , Transportation/history , Transportation/methods , PhylogenyABSTRACT
BACKGROUND: The purpose of this study was to investigate the effects of a walking school bus intervention on children's active commuting to school. METHODS: We conducted a randomized controlled trial (RCT) in Houston, Texas (Year 1) and Seattle, Washington (Years 2-4) from 2012 to 2016. The study had a two-arm, cluster randomized design comparing the intervention (walking school bus and education materials) to the control (education materials) over one school year October/November - May/June). Twenty-two schools that served lower income families participated. Outcomes included percentage of days students' active commuting to school (primary, measured via survey) and moderate-to-vigorous physical activity (MVPA, measured via accelerometry). Follow-up took place in May or June. We used linear mixed-effects models to estimate the association between the intervention and outcomes of interest. RESULTS: Total sample was 418 students [Mage=9.2 (SD = 0.9) years; 46% female], 197 (47%) in the intervention group. The intervention group showed a significant increase compared with the control group over time in percentage of days active commuting (ß = 9.04; 95% CI: 1.10, 16.98; p = 0.015) and MVPA minutes/day (ß = 4.31; 95% CI: 0.70, 7.91; p = 0.02). CONCLUSIONS: These findings support implementation of walking school bus programs that are inclusive of school-age children from lower income families to support active commuting to school and improve physical activity. TRAIL REGISTRATION: This RCT is registered at clinicaltrials.gov (NCT01626807).
Subject(s)
Schools , Transportation , Walking , Humans , Walking/statistics & numerical data , Female , Male , Child , Transportation/methods , Health Promotion/methods , Washington , Texas , Students , Exercise , Motor Vehicles , Accelerometry , Poverty , Program Evaluation , Cluster AnalysisABSTRACT
BACKGROUND: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. METHODS: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. RESULTS: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. CONCLUSIONS: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.
Subject(s)
Exercise , Transportation , Walking , Humans , Colombia , Transportation/methods , Walking/statistics & numerical data , Taxes , Socioeconomic Factors , Cities , Bicycling/statistics & numerical data , Female , Male , AdultABSTRACT
Recognizing the evolution pattern of traffic condition and making accurate prediction play a vital role in intelligent transportation systems (ITS). With the massive increase of available traffic data, deep learning-based models have attracted considerable attention for their impressive performance in traffic forecasting. However, the majority of existing approaches neglect to model of asynchronously dynamic spatio-temporal correlation and fail to consider the impact of historical traffic data on future condition. Additionally, the attribute of deep learning method presents challenges in interpreting the explicit spatiotemporal relationships. In order to enhance the accuracy of traffic prediction as well as extract comprehensive and explainable spatial-temporal relevance in traffic networks, we propose a novel attention-based local spatial and temporal relation discovery (ALSTRD) model. Our model firstly implements feature representation learning to effectively express latent input traffic information. Then, a local attention mechanism structure is established to model asynchronous dependencies of historical input data. Finally, another attention network and the Pearson Correlation Coefficient method are introduced to extract the elaborate influence of the historical traffic condition of neighboring roads on the future condition of the target road. The experiment results on several datasets demonstrate that our model achieves significant improvements in prediction accuracy compared to other baseline methods, which can be attributed to its ability to extract the fine-grained correlation among historical traffic data and capture the dynamic association between past and future data. In addition, the incorporation of attention mechanism and Pearson Correlation Coefficient promotes the model's ability to elucidate spatiotemporal correlations among traffic data, thereby providing a more robust explanation.
Subject(s)
Attention , Deep Learning , Forecasting , Neural Networks, Computer , Attention/physiology , Transportation/methods , Humans , Spatio-Temporal AnalysisABSTRACT
In the United States, selected subgroups of historically marginalized populations include people with disabilities and people in racial/ethnic minority groups ("critical populations") who have been disproportionately affected by COVID-19. These groups are also more likely to use public transit to access essential resources; thus, understanding transit agencies' communication strategies to reach these populations during crises is of utmost importance. We conducted a content analysis of 16 transit agencies' webpages and Twitter® accounts during the first 6 months of the pandemic to assess alignment of agencies' COVID-19-related communications with best practices in crisis communication across five themes: perceivability, navigability, understandability, suitability, and content. Findings suggested that transit agencies frequently communicated about schedule changes and safety, eg, masking, station sanitation, and reflected racial/ethnic diversity in images. Yet, less than half consistently used communication strategies known to enhance accessibility and uptake of messaging among critical populations, eg, alternative text, and even less reflected disability diversity in images. We offer recommendations for public transit agencies to move beyond compliance to effectively address the needs of ridership most substantially impacted by public health emergencies.
Subject(s)
COVID-19 , Communication , Pandemics , SARS-CoV-2 , Humans , COVID-19/epidemiology , United States , Transportation/methods , Internet , Minority Groups , Disabled PersonsABSTRACT
OBJECTIVE: The health benefits of active commuting have been reported. However, few studies have assessed commuting modes using objective methods. This study clarified the association between changes in objectively measured commuting modes and body weight among Japanese workers. METHODS: This longitudinal study used data from the annual health examinations and personnel records of a company with branches in all prefectures of Japan. Data from 2018 and 2019 were used as the baseline and follow-up data, respectively. The commuting mode was assessed using the commuting mode code included in the personnel records and classified into 3 types: walking, public transport, and car or motorcycle. The participants were classified into 9 categories based on the combination of their commuting modes in 2018 and 2019. Body weight was measured objectively during health examinations. The 1-year changes in body weight were calculated for the 9 categories and assessed using an analysis of covariance with adjustments for covariates. RESULTS: The analysis included 6551 workers (men: 86.8%; mean age: 42.8 years). Overall, body weights tended to increase (+0.40 kg/y). The participants who switched to more active commuting, such as from car or motorcycle to walking (-0.13 kg/y), from car or motorcycle to public transport (+0.10 kg/y), and from public transport to walking (-0.07 kg/y), exhibited small weight gains or losses. A similar trend was observed even after adjustment. CONCLUSIONS: Changing to a more active commuting mode may prevent weight gain among workers.
Subject(s)
Body Weight , Transportation , Walking , Humans , Longitudinal Studies , Male , Adult , Japan , Transportation/methods , Female , Middle Aged , Motorcycles , East Asian PeopleABSTRACT
BACKGROUND: Recent modifications to low-dose CT (LDCT)-based lung cancer screening guidelines increase the number of eligible individuals, particularly among racial and ethnic minorities. Because these populations disproportionately live in metropolitan areas, we analyzed the association between travel time and initial LDCT completion within an integrated, urban safety-net health care system. METHODS: Using Esri's StreetMap Premium, OpenStreetMap, and the r5r package in R, we determined projected private vehicle and public transportation travel times between patient residence and the screening facility for LDCT ordered in March 2017 through December 2022 at Parkland Memorial Hospital in Dallas, Texas. We characterized associations between travel time and LDCT completion in univariable and multivariable analyses. We tested these associations in a simulation of 10,000 permutations of private vehicle and public transportation distribution. RESULTS: A total of 2,287 patients were included in the analysis, of whom 1,553 (68%) completed the initial ordered LDCT. Mean age was 63 years, and 73% were underrepresented minorities. Median travel time from patient residence to the LDCT screening facility was 17 minutes by private vehicle and 67 minutes by public transportation. There was a small difference in travel time to the LDCT screening facility by public transportation for patients who completed LDCT versus those who did not (67 vs 66 min, respectively; P=.04) but no difference in travel time by private vehicle for these patients (17 min for both; P=.67). In multivariable analysis, LDCT completion was not associated with projected travel time to the LDCT facility by private vehicle (odds ratio, 1.01; 95% CI, 0.82-1.25) or public transportation (odds ratio, 1.14; 95% CI, 0.89-1.44). Similar results were noted across travel-type permutations. Black individuals were 29% less likely to complete LDCT screening compared with White individuals. CONCLUSIONS: In an urban population comprising predominantly underrepresented minorities, projected travel time is not associated with initial LDCT completion in an integrated health care system. Other reasons for differences in LDCT completion warrant investigation.
Subject(s)
Early Detection of Cancer , Health Services Accessibility , Lung Neoplasms , Safety-net Providers , Tomography, X-Ray Computed , Humans , Lung Neoplasms/diagnosis , Lung Neoplasms/epidemiology , Lung Neoplasms/diagnostic imaging , Male , Middle Aged , Female , Early Detection of Cancer/methods , Early Detection of Cancer/statistics & numerical data , Tomography, X-Ray Computed/methods , Aged , Safety-net Providers/statistics & numerical data , Health Services Accessibility/statistics & numerical data , Health Services Accessibility/standards , Texas/epidemiology , Urban Population/statistics & numerical data , Travel/statistics & numerical data , Mass Screening/methods , Mass Screening/statistics & numerical data , Mass Screening/standards , Transportation/statistics & numerical data , Transportation/methodsABSTRACT
In the field of healthcare logistics, the reliance on conventional transport methods such as cars for the delivery of monoclonal antibodies (mAbs) is susceptible to challenges posed by traffic and infrastructure, leading to increased and unpredictable transport times. Recognizing the potential role of drones in mitigating these challenges, we aimed to investigate the impact of medical drone transport on the stability of mAbs. Compromised stability could lead to aggregation and immunogenicity, thereby jeopardizing the efficacy and safety of mAbs. We studied the transportation of vials as well as ready-to-administer infusion bags with blinatumomab, tocilizumab, and daratumumab. The methodology involved the measurement of both temperature and mechanical shock during drone transport. Moreover, the analytical techniques High Performance Size-Exclusion Chromatography (HP-SEC), Dynamic Light Scattering (DLS), Light Obscuration (LO), Micro-Flow Imaging (MFI), and Nanoparticle Tracking Analysis (NTA) were employed to comprehensively assess the presence of aggregates and particle formation. The key findings revealed no significant differences between car and drone transport, indicating that the stability of mAbs in both vials and infusion bags was adequately maintained during drone transport. This suggests that medical drones are a viable and reliable means for the inter-hospital transport of mAbs, paving the way for more efficient and predictable logistics in healthcare delivery.
Subject(s)
Antibodies, Monoclonal , Drug Stability , Transportation , Antibodies, Monoclonal/chemistry , Transportation/methods , Humans , Drug Packaging/methods , Hospitals , TemperatureABSTRACT
Transportation is an underrecognized, but modifiable barrier to accessing cancer care, especially for clinical trials. Clinicians, insurers, and health systems can screen patients for transportation needs and link them to transportation. Direct transportation services (i.e., ride-sharing, insurance-provided transportation) have high rates of patient satisfaction and visit completion. Patient financial reimbursements provide necessary funds to counteract the effects of transportation barriers, which can lead to higher trial enrollment, especially for low socioeconomic status and racially and ethnically diverse patients. Expanding transportation interventions to more cancer patients, and addressing knowledge, service, and system gaps, can help more patients access needed cancer care.
Subject(s)
Health Services Accessibility , Neoplasms , Humans , Clinical Trials as Topic , Medical Oncology/organization & administration , Medical Oncology/methods , Neoplasms/therapy , Patient Satisfaction , Transportation/methods , Transportation of Patients/methods , Transportation of Patients/organization & administration , Transportation of Patients/economicsABSTRACT
Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.
Subject(s)
Exercise , Transportation , Walking , Humans , Male , Female , Middle Aged , Adult , Walking/statistics & numerical data , Transportation/statistics & numerical data , Transportation/methods , Bicycling/statistics & numerical data , United States , Aged , Surveys and Questionnaires , Health Status , Socioeconomic Factors , AdolescentABSTRACT
BACKGROUND: Knowledge of changes in the domains of physical activity (PA) during the transition period from primary to secondary education and the factors associated with these changes, are prerequisites for the design of effective PA promotion strategies. Therefore, the first aim of this study was to systematically review changes in general, leisure-time, school, transport, work, and home PA across the transition from primary to secondary education. The second aim was to systematically review the individual, social, and physical environmental factors that were associated with these changes. METHODS: Records published up until September 2023 were retrieved from five electronic databases. We included longitudinal and cross-sectional studies that investigated general or domain-specific PA from 2 years before to 2 years after the transition from primary to secondary education. Information on source, study characteristics, sample characteristics, PA, and factors were extracted from the papers included. We reported the direction of change in general and domain-specific PA and the direction of association of the factors with change in general and domain-specific PA. RESULTS: Forty-eight papers were included in the study. The evidence on changes in PA and associated factors was greatest for general PA. A limited number of the studies investigated the separate domains of leisure-time, school, and transport. Most studies on general and school PA reported a decline in PA, but there were no consistent results for the domains of leisure-time and transport. With respect to the associated factors, evidence was predominantly found for individual factors and to a lesser degree for physical environmental and social environmental factors. None of the factors were consistently associated with changes in general or domain-specific PA during the school transition. CONCLUSIONS: For the design of targeted PA promotion strategies, further studies are warranted to explore changes in the specific domains of PA across the transition from primary to secondary education, especially in the domains of leisure-time, transport, home, and work PA. In addition, the interactions between factors at different socioecological levels to influence changes in PA need to be addressed more in the future. TRIAL REGISTRATION: PROSPERO CRD42020190204.
Subject(s)
Exercise , Leisure Activities , Schools , Humans , Adolescent , Child , Transportation/methodsABSTRACT
To understand the environmental determinants of physical activity (PA), precise spatial localization is crucial. This cross-sectional study focuses on the spatiotemporal distribution of PA among Czech adolescents (n = 171) using Global Positioning System loggers and accelerometers. The results showed that adolescents spent most of their time in sedentary behavior, with 57.2% and 58.5% of monitored time at home and school, respectively. The park and playground had the lowest proportion of sedentary behavior but also the lowest amount of moderate to vigorous PA (MVPA). However, when considering the time spent in each domain, the highest proportion of MVPA was seen in publicly accessible playgrounds (13.3% of the time). Chi-square analysis showed that the relative distribution of different PA intensities did not differ across spatial domains. Based on these results, the authors propose 2 key strategies for increasing MVPA in adolescents: Increase the time spent in activity-supportive environments, such as parks and playgrounds, and design techniques to increase MVPA at home and school settings.