Exploring the relationship between urban form and nonwork travel through time use analysis

Ensuring convenient access to cancer screening, diagnosis, and treatment is essential for mitigating and preventing the disease. Geographical accessibility plays a crucial role in cancer mitigation and healthcare planning, particularly in low-income countries such as Nepal. A spatial perspective is crucial for improving cancer mitigation planning and evidence-based policy formulation. This study examined the spatial accessibility and population coverage at the municipal level in Bagmati province, Nepal. This study utilized spatial data, including LULC, DEM, OSM road networks, population distribution, and location of cancer hospitals, to calculate three different scenarios for reaching these hospitals. Based on that, a raster surface of travel time between residences and cancer hospitals was developed. We incorporated terrain, physical barriers, travel modes, speeds, and topography through various land-cover classes. Accordingly, underserved populations and zonal statistics were assessed using an interactive modeling approach to determine the spatial relationship between population, travel time, and zonal boundaries. The motorized travel scenario exhibited the highest spatial accessibility, followed by the bicycling and walking scenarios. It varied significantly across the three scenarios. The motorized scenario has the highest accessibility, with 72.57% of people covered within a 30-min travel time. Motorized scenario has a maximum people coverage of 96.78% within a 360-min travel time. Kathmandu Valley and Chitawan urban areas showed higher accessibility across all scenarios, attributed to easy road networks. Rural and mountainous regions in the middle hills of the northern and eastern parts have low accessibility, attributed to steep slopes, scattered settlements, and sparse infrastructure. The findings demonstrate significant spatial disparities across various travel scenarios, underscoring the need for spatially informed health planning and policy development. These insights provide a foundation for addressing problems and enhancing cancer care delivery in Nepal using spatial techniques.

The COVID-19 pandemic led to a substantial increase in the number of people working from home (telecommuting), in turn leading to unprecedented changes in mobility patterns worldwide. Due to the changing context of the pandemic, there is still a significant gap in knowledge regarding the effects of working from home on workers’ travel patterns. The main goal of this work is to unravel the interrelationship between telecommuting during the COVID-19 pandemic, the frequency of active travel for non-work utilitarian purposes, and local accessibility levels around workers’ homes. This study uses a longitudinal approach by analyzing travel and telecommuting behavior data from a two-wave survey administered in Montreal in 2019, pre-pandemic, and 2021, during COVID-19 (n = 452). Through a set of weighted multi-level linear regressions, we study the effects of telecommuting on the frequency of active travel for non-work utilitarian purposes, mediated by local accessibility around the household. Results show that the effect of telecommuting on non-work active travel for utilitarian purposes is highly dependent on local accessibility levels around the person’s household. For workers living in high local accessibility areas, an increase in telecommuting during the pandemic has induced an increase in active trips for non-work utilitarian purposes. On the other hand, for workers residing in low local accessibility neighborhoods, the effect is the opposite. This research provides insights into the effects of telecommuting on non-work active travel, an area that is currently of interest to policy-makers and practitioners working towards increasing the level of physical activity among individuals through travel.

An enhanced approach for modeling spatial accessibility for in vitro fertilization services in the rural Midwestern United States

BackgroundActive travel (walking or cycling for transport) is associated with favourable health outcomes in adults. However, little is known about the concurrent patterns of health behaviour associated with active travel. We used compositional data analysis to explore differences in how people doing some active travel used their time compared to those doing no active travel, incorporating physical activity, sedentary behaviour and sleep.MethodsWe analysed cross-sectional data from the 2014/15 United Kingdom Harmonised European Time Use Survey. Participants recorded two diary days of activity, and we randomly selected one day from participants aged 16 years or over. Activities were categorised into six mutually exclusive sets, accounting for the entire 24 h: (1) sleep; (2) leisure moderate to vigorous physical activity (MVPA); (3) leisure sedentary screen time; (4) non-discretionary time (work, study, chores and caring duties); (5) travel and (6) other. This mixture of activities was defined as a time-use composition. A binary variable was created indicating whether participants reported any active travel on their selected diary day. We used compositional multivariate analysis of variance (MANOVA) to test whether mean time-use composition differed between individuals reporting some active travel and those reporting no active travel, adjusted for covariates. We then used adjusted linear regression models and bootstrap confidence intervals to identify which of the six activity sets differed between groups.Results6143 participants (mean age 48 years; 53% female) provided a valid diary day. There was a statistically significant difference in time-use composition between those reporting some active travel and those reporting no active travel. Those undertaking active travel reported a relatively greater amount of time in leisure MVPA and travel, and a relatively lower amount of time in leisure sedentary screen time and sleep.ConclusionsCompared to those not undertaking active travel, those who did active travel reported 11 min more in leisure MVPA and 18 min less in screen time per day, and reported lower sleep. From a health perspective, higher MVPA and lower screen time is favourable, but the pattern of sleep is more complex. Overall, active travel was associated with a broadly health-promoting composition of time across multiple behavioural domains, which supports the public health case for active travel.

Urban commuting in Jakarta, Indonesia, remains heavily reliant on motorcycles, yet riders exhibit diverse travel behaviors and underlying motivations. Drawing on survey data from 1143 commuters from Bogor, Depok, Tangerang, and Bekasi to Jakarta, this study first applies latent class cluster analysis to identify four distinct user segments: solo, regular medium-distance academic commuters; solo, regular medium-distance work commuters; solo, regular long-distance work commuters; and accompanied, occasional long-distance social/recreational commuters. This study then employs the Rasch model to quantify each group’s latent motivational drivers across twelve functional and psychosocial factors. Results indicate that support for unplanned trips is the strongest motivator for academic and long-distance work riders; ease of navigation underpins choices by academic, medium-distance work, and recreational commuters; traffic-congestion avoidance drives academic and recreational users; departure-time flexibility is paramount for medium-distance workers; and personal independence ranks highest for long-distance workers. By contrast, predictable travel time, perceived safety, and limited public-transport coverage consistently rank as weak motivators across all segments. Based on these insights, this study recommends tailored and innovative interventions, such as app-based microtransit for on-demand flexibility, park-and-ride facilities for long-distance commuters, last-mile e-micromobility services for medium-distance users, and integrated campus-shuttle systems for students, complemented by enhanced real-time information and targeted safety measures. Collectively, these strategies aim to match motorcycles’ core advantages while guiding riders toward more sustainable, multimodal options.

Assessing the spatial accessibility and spatial equity of public libraries' physical locations

Examination of relationships between urban form, household activities, and time allocation in the Atlanta Metropolitan Region

Spatial difference analysis for accessibility to high level hospitals based on travel time in Shenzhen, China

Active travel offers many societal benefits, including improving people’s mental and physical health and minimising our impacts on the environment. Increasing active travel is particularly important amongst children and young people (CYP), who are building habits which they will carry into adulthood. Studies on active travel amongst CYP are limited, however, with most research focusing on adult participants or on adult perceptions of children. This study sought to understand CYP’s interactions with the built and natural environment–and therefore their access to active travel–through the Capability, Opportunity, Motivation, Behaviour (COM-B) model. With a stakeholder group representing local government, youth organisations and active travel organisations, we co-created two bilingual questionnaires–one for young people aged 12–16 years living in Wales and the other for parents of young people aged 12–16 years living in Wales. Both questionnaires collected information on behaviour and perceived capability, opportunity and motivation of CYP to engage with their natural and built environments. The questionnaires included a discrete choice experiment (DCE), which proposed a series of binary choice questions indicating preferences based on landscape, journey time and type of travel. A total of 124 questionnaires (38 young people and 86 parents) were returned for analysis. These data indicate that CYP’s time spent outdoors is not dependent upon geography (rural/urban/suburban), season, or school holidays. There was a significant difference in capability, opportunity and motivation between parents and CYP, with parents over-estimating the psychological capability of CYP to engage outdoors. The preference data indicate that active travel is the favoured mode of transport, with both CYP and parents stating that they would increase travel time in order to travel actively. While this response is not consistent with respondent’s day-to-day travel choices, it suggests that the limitations to active travel may be psychological capability and automatic motivation, rather than a lack of opportunity.

The spatial organization of accessibility and functional hierarchy: The case of Israel

The accessibility of primary health care is fundamentally important to people’s life quality and wellbeing. Based on the block group level 2010 census data from the U.S. Census Bureau and primary health care data from Association of American Medical Colleges, this study focuses on measuring the primary health care accessibility using an extended kernel-density two Step Float Catchment Area method. The study area is the Mississippi State, which is ranked last state for health care. The objectives of this study are to calculate the accessibility and analyze the spatial and non-spatial disadvantages of communities in accessibility of primary health care of the Mississippi State. Results showed that the two-step floating catchment area integrated by a Gaussian function method is a viable method of calculating accessibility. Overall, urban and the fringe areas have higher spatial accessibility to primary health care, while lower accessibility areas are the suburban and rural areas. Relatively, Hinds County, Madison County, Rankin County, Lamer County, Forrest County, Jones County, Lauderdale County, and Lee County have higher accessibility, while some counties have lower accessibility, such as Marshall County, Winston County, Noxubee County, Wilkinson County, Smith County, and Greene County. From the factor analysis, those urban areas showed greater mobility disadvantages and higher health care needs. Besides, the attempts to integrate the health needs index and the mobility index with the spatial accessibility helps to balance accessibility with different non-spatial conditions. Additionally, this study provides implications for public policy about the health care distribution and the high health needs population.

Measuring the spatial accessibility and capacity of healthcare facilities is an important task to improve the quality of health services and reduce the pressure on them. This research assesses the current spatial accessibility and capacity of two-level of healthcare facilities (comprehensive healthcare centers and hospitals) in the Greater Irbid Municipality using the enhanced two-step floating catchment area (E2SFCA) method. To do this, Network analysis techniques including original-destination matrix (OD), service area, and location-allocation were employed for determining the travel time from residents' points towards every healthcare facility, the service coverage and capacity within travel time zones, and the number of served areas by every healthcare facility. Then, optimum locations for new healthcare facilities that improve the accessibility and capacity rates were determined. The results show that while all areas in the study area are located within a 30-minute drive from the hospital's locations, 18 out of 23 areas are within 15 minutes drive towards the comprehensive health centers. This means that 28.80% of the population needs more than 15 minutes of driving time to access the second level of healthcare services. In addition, the annual average of the actual patient-doctor ratio ranges from 1338 to 2900 patients per doctor in the hospitals, and 2676 to 8524 patients per doctor in the comprehensive healthcare centers, and thus, the health services are inadequate in the study area. Furthermore, the suggested new healthcare facilities in terms of the numbers and optimum location would improve the spatial accessibility and the capacity ratio.

Does walking and bicycling more mean exercising less? Evidence from the U.S. and the Netherlands

The potential for a population at a given location to utilize a health service can be estimated using a newly developed measure called the supply-concentric demand accumulation (SCDA) spatial availability index. Spatial availability is the amount of demand at the given location that can be satisfied by the supply of services at a facility, after discounting the intervening demand among other populations that are located nearer to a facility location than the given population location. This differs from spatial accessibility measures which treat absolute distance or travel time as the factor that impedes utilization. The SCDA is illustrated using pulmonary rehabilitation (PR), which is a treatment for people with chronic obstructive pulmonary disease (COPD). The spatial availability of PR was estimated for each Census block group in Georgia using the 1105 residents who utilized one of 45 PR facilities located in or around Georgia. Data was provided by the Centers for Medicare & Medicaid Services. The geographic patterns of the SCDA spatial availability index and the two-step floating catchment area (2SFCA) spatial accessibility index were compared with the observed PR utilization rate using bivariate local indicators of spatial association. The SCDA index was more associated with PR utilization (Morans I = 0.607, P < 0.001) than was the 2SFCA (Morans I = 0.321, P < 0.001). These results suggest that the measures of spatial availability may be a better way to estimate the health care utilization potential than measures of spatial accessibility.

This study elaborates on a model system developed in earlier papers to predict the perceived value and use of travel information. The value of travel information is conceptualized as the extent to which the information allows the individual to make better activity–travel scheduling decisions at the beginning of the day and during execution of the schedule. By taking the broader schedule context into account, the model is sensitive to the impact of information and decisions on the full activity–travel pattern. Furthermore, the model includes Bayesian mechanisms to make sure that beliefs about travel times, and other uncertain events, and the credibility of the information source are updated each time information is received and the real travel time is experienced. This paper describes the results of numerical simulations conducted to illustrate the system and to derive theoretical implications from the model. The simulations show that the schedule context, learning, and expected information gain in combination determine the perceived value of information and that none of these factors can be ignored in the derivation of estimates of these values. A theoretical analysis further shows how decision trees can be pruned to reduce a potential problem of combinatorics.