Journeys to health services in Great Britain : an analysis of changing travel patterns 1985-2006

This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2006). The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Regression analyses were conducted to investigate the differences between different socio-spatial groups in these indicators over the period 1985-2006. This study found that journey distances to health facilities were significantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. However, most of their rates of utilisation of health services were found to be significantly lower because their journey times were significantly longer and also gradually increased over the periods. These findings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension.

Changing travel patterns and journeys to health services in Great Britain 1985-2012: An examination health service utilisation using the National Travel Survey

Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.

NPTS urban travel patterns. 1990 Nationwide Personal Transportation Survey (NPTS).

Federal Highway Administration, Washington, D.C.

Travel patterns and transit needs of women /

"Performing organization: Moore Johnson, Inc."--Technical report documentation page.

Research Monograph : Sustainable Australia : Containing travel in master planned estates

Low density suburban development and excessive use of automobiles are associated with serious urban and environmental problems. These problems include traffic congestion, longer commuting times, high automobile dependency, air and water pollution, and increased depletion of natural resources. Master planned development suggests itself as a possible palliative for the ills of low density and high travel. The following study examines the patterns and dynamics of movement in a selection of master planned estates in Australia. The study develops new approaches for assessing the containment of travel within planned development. Its key aim is to clarify and map the relationships between trip generation and urban form and structure. The initial conceptual framework of the report is developed in a review of literature related to urban form and travel behaviour. These concepts are tested empirically in a pilot study of suburban travel activity in master planned estates. A geographical information systems (GIS) methodology is used to determine regional journey-to-work patterns and travel containment rates. Factors that influence self-containment patterns are estimated with a regression model. The key research findings of the pilot study are: - There is a strong relation between urban structural form and patterns of trip generation; - The travel self-containment of Australian master planned estates is lower than the scholarly literature implies would occur if appropriate planning principles to achieve sustainable urban travel were followed; - Proximity to the central business district, income level and education status are positively correlated with travel containment; - Master planned estates depend more on local and regional centres for employment than on the central business district; - The service sector is the major employer in and around master planned estates. It tends to provide part-time and casual employment rather than full-time employment; - Travel self-containment is negative correlated with car dependency. Master planned estates with less car dependent residents, and with good access to public transport, appear to be more self-contained and, consequently, more sustainable than the norm. This research is a useful preliminary examination of travel self-containment in Australian master planned estates. It by no means exhausts the subject. In future research we hope to further assess sustainable travel patterns with more detailed spatial analysis.

Weekly activity-travel behaviour in rural Northern Ireland : differences by context and socio-demographic

Despite a wide variation in access to goods and services between rural areas, common policy interventions are often proposed in Northern Ireland. Questions remain as to the level and form of policy differentiation that is required, if any, both within and between different rural areas. This issue is investigated in this paper through the analysis of activity-travel patterns of individuals living in two rural areas with different levels of area accessibility and area mobility. Three focus groups, 299 questionnaires and 89 activity-travel diaries for 7 days were collected for individuals from these areas. Regression analyses were employed to explore the degree to which different factors influence activity travel behaviour. The results indicate that individuals from rural areas with a higher level of accessibility are more integrated within their local community and as a result, are potentially less at risk of being excluded from society due to immobility. Differences, however, were also found between different groups within an area (e.g. non-car owning individuals who were more reliant on walking, and low-income individuals who made trips of a shorter distance). Based on the study findings and a review of existing policies, this research highlights the need to tailor policy responses to reflect the particular sets of circumstances exhibited in different areas.

Identifying rural disadvantage using a multiday travel diary

This paper identifies transport disadvantage using a 7 day activity-travel diary data from two rural case study areas. A composite participation index (PI) measure was developed for this study based on six indices measuring elements of travel and activity participation. Using the index the paper then goes on to compare these results, with the results obtained from other more traditional indicators used to identify transport disadvantage. These indicators are related to the size of activity space such as unique network distance travelled, number of unique locations visited, activity space area, activity duration, and fullness (shape) of activity spaces. The weaknesses of these indicator based measures are that: firstly, they do not take into account the relativity of the measure between different areas i.e. travel distance in terms of the wider context of available activities within an area; and secondly, these indicators are multi-dimensional and each represents a different qualitative aspect of travel and activity participation. As a result, six individual indices were developed to overcome these problems. These include: participation count index, participation length index, participation area index, participation duration index, participation type index, and participation frequency index. These are then aggregated to assess the relative performance in terms of these different indices and identify the nature of transport disadvantage. GIS was used to visualise individual travel patterns and to derive scores for both the indicator based measures and the index based measures. Factor analysis was conducted to derive weights of the individual indices to form the composite index measure. From this analysis, two intermediate indices were also derived using the underlying factors of the data related to these indices. Using the scores of all these measures, multiple regression analyses were conducted to identify patterns of transport disadvantage.

Mining temporal and spatial travel regularities for transit planning

Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

Travel Characteristics of Marine Anglers Using Oil and Gas Platforms in the Central Gulf of Mexico

This study was designed to evaluate the travel characteristics of avid marine anglers off Louisiana in the Central Gulf of Mexico. It focuses on the complex marine travel patterns involving the extensive assemblage of oil and gas structures. In an intercept approach, marine recreationalf isherman were asked to identify near and offshore travel patterns on the day of the interview. Information was also solicited regarding how respondents selected and located fishing destinations as well as what method of fishing was undertaken that day. Petroleum platforms were a principal fishing destination, and platform anglers traveled an average distance of 75.5 km (40.7 n.mi.) to and from offshore fishing locations. In fishing an average of 6.5 platforms per trip, these anglers traveled about 21.3 km (11.5 n.mi.) between the first and last platform visited. Mean total distances for platform anglers were 96 km (51.8 n.mi). Travel distances for bay, nearshore, and bluewater anglers were also obtained.

Understanding Immigrants' Travel Behavior in Florida: Neighborhood Effects and Behavioral Assimilation

The goal of this study was to develop Multinomial Logit models for the mode choice behavior of immigrants, with key focuses on neighborhood effects and behavioral assimilation. The first aspect shows the relationship between social network ties and immigrants’ chosen mode of transportation, while the second aspect explores the gradual changes toward alternative mode usage with regard to immigrants’ migrating period in the United States (US). Mode choice models were developed for work, shopping, social, recreational, and other trip purposes to evaluate the impacts of various land use patterns, neighborhood typology, socioeconomic-demographic and immigrant related attributes on individuals’ travel behavior. Estimated coefficients of mode choice determinants were compared between each alternative mode (i.e., high-occupancy vehicle, public transit, and non-motorized transport) with single-occupant vehicles. The model results revealed the significant influence of neighborhood and land use variables on the usage of alternative modes among immigrants. Incorporating these indicators into the demand forecasting process will provide a better understanding of the diverse travel patterns for the unique composition of population groups in Florida.

THE INFLUENCE OF URBAN FORM AT DIFFERENT GEOGRAPHICAL SCALES ON TRAVEL BEHAVIOR; EVIDENCE FROM U.S. CITIES

Suburban lifestyle is popular among American families, although it has been criticized for encouraging automobile use through longer commutes, causing heavy traffic congestion, and destroying open spaces (Handy, 2005). It is a serious concern that people living in low-density suburban areas suffer from high automobile dependency and lower rates of daily physical activity, both of which result in social, environmental and health-related costs. In response to such concerns, researchers have investigated the inter-relationships between urban land-use pattern and travel behavior within the last few decades and suggested that land-use planning can play a significant role in changing travel behavior in the long-term. However, debates regarding the magnitude and efficiency of the effects of land-use on travel patterns have been contentious over the years. Changes in built-environment patterns is potentially considered a long-term panacea for automobile dependency and traffic congestion, despite some researchers arguing that the effects of land-use on travel behavior are minor, if any. It is still not clear why the estimated impact is different in urban areas and how effective a proposed land-use change/policy is in changing certain travel behavior. This knowledge gap has made it difficult for decision-makers to evaluate land-use plans and policies. In addition, little is known about the influence of the large-scale built environment. In the present dissertation, advanced spatial-statistical tools have been employed to better understand and analyze these impacts at different scales, along with analyzing transit-oriented development policy at both small and large scales. The objective of this research is to: (1) develop scalable and consistent measures of the overall physical form of metropolitan areas; (2) re-examine the effects of built-environment factors at different hierarchical scales on travel behavior, and, in particular, on vehicle miles traveled (VMT) and car ownership; and (3) investigate the effects of transit-oriented development on travel behavior. The findings show that changes in built-environment at both local and regional levels could be very influential in changing travel behavior. Specifically, the promotion of compact, mixed-use built environment with well-connected street networks reduces VMT and car ownership, resulting in less traffic congestion, air pollution, and energy consumption.