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⁎A74 Changing travel patterns and journeys to health services in Great Britain 1985-2012: an examination health service utilisation using the National Travel Survey
Oral Abstracts / Journal of Transport & Health 2 (2015) S5–S63
S43
http://dx.doi.org/10.1016/j.jth.2015.04.560
nA73 Simulating air pollution exposures in an active population as a function of activity patterns Juan Pablo Orjuela a, Antònia Valentín b, David Donaire b, Edmund Seto c, Michael Jerrett c, Gerard Hoek d, Bert Brunekreef d, Mark Nieuwenhuijsen b, Audrey de Nazelle a a
Imperial College, UK Center for Research in Environmental Epidemiology (CREAL), Spain c University of California Berkeley, USA d Utrecht University, Netherlands b
Abstract Background:
Estimating exposure levels and inhaled doses while traveling is an important part in the assessment of the health impacts of air pollution but it is also a challenging task. There is usually a trade-off between accurate concentrations estimates and sample size. Current research focuses mainly in air quality models for large population sets that do not account for individual variability (e.g. dispersion modelling for a city), or in individual exposure measurements that are applicable to specific groups of interest (e.g. exposure measurements of children or pregnant women). Although some authors have focused in exposure concentrations and travel time, recent studies also suggest that including respiration rates may substantially improve daily doses estimates. This study combines modelled air quality data with individual measurements of routes and physical activity using smartphones, achieving large population applicability while accounting for individual variability and respiration rates.
Methods:
The data were measured in an active population of 172 individuals in Barcelona (Spain) using accelerometry and Global Positioning System (GPS) information from smartphones. A Land Use Regression (LUR) model and a dispersion model were used to estimate concentrations of particulate matter of less than 10 and 2.5 μm (PM10 and PM2.5), nitrogen oxides (NOx), and nitrogen dioxide (NO2) with a spatial resolution of 100 m. Temporal adjustments were performed using information from a background station. Ratios for different microenvironments (e.g. home, work) and transport modes (e.g. car, bicycle, bus) were applied on a minute-by-minute basis. Physical activity levels (measured in METS) were used to estimate breathing rates that in combination with estimated exposure were used to calculate inhaled doses.
Results: Although the subjects spend only 9% of their time in transit, the contribution of this activity to the total inhaled dose is greater than 20%. This increase is mainly due to significantly higher concentrations during transport than being at home (t-test, p 40.001) and increased physical activity (t-test, p4 0.001). The uncertainty analysis shows that total inhaled dose while in transit can vary between 17% and 45%. These results are still part of ongoing analyses. Conclusions:
Using smartphones in combination with air quality models shows that transport may have a substantial contribution to daily inhaled doses due to increased physical activity and concentration levels. However, bias in the sample with a large proportion of cyclists and a lack of reliable transport mode ratios need to be considered in the analysis.
http://dx.doi.org/10.1016/j.jth.2015.04.561
Environmental Justice & Social Equity (A74-A76) nA74 Changing travel patterns and journeys to health services in Great Britain 1985-2012: an examination health service utilisation using the National Travel Survey Julian Hine a, Md Kamruzzaman b, Urbi Banerjee a a b
Ulster University, Northern Ireland, UK Queensland University of Technology, Australia
Abstract 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 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. Although rates of utilisation of health services were
S44
Oral Abstracts / Journal of Transport & Health 2 (2015) S5–S63
significantly lower because of longer journey times. 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.
Conclusions:
This finding, 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 difficult 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.
http://dx.doi.org/10.1016/j.jth.2015.04.562
A75 When Mobility nurtures Active Living: A case study Mauricio Leandro a, Henry Hernández-Vega a a
Universidad de Costa Rica
Abstract Background:
The main campus at Universidad de Costa Rica, built in the decade of 1950´s, was intended for a population of less than ten thousand users. The original plan intended to prioritize pedestrian use by creating a central pedestrian sector with an extended park between the faculty buildings and a perimeter road. Over the years, demand for space has been translated into an important reduction of green areas for new parking and buildings. Currently, the campus serves a growing population of more than forty thousand people. Car use is massive inside the campus. Those changes have deteriorated both the aesthetic and social outcomes needed at an academic institution like the one under study. The current message reflected by the main campus´ infrastructure in terms of mobility is undergoing serious questioning. Therefore, since mid 2012, the university has begun a series of actions to improve pedestrian mobility, parking spaces, travel patterns, and so on. Fixing mobility problems at the campus has become an interesting lab to rethink the very concept of mobility. Old paradigms of mobility are falling apart and the discussion now moves to the rather new but exciting field of active living.
Methods:
Due to the nature of the intervention, a mixed methods approach was chosen. Experts from different backgrounds have been invited to take part in the development and implementation of an Active Mobility Plan which elaborates over the concept of non-motorized transportation towards a vision of a healthy campus. The main goal for that “ad-hoc team of enthusiasts” is to create vibrant and healthy public spaces for pedestrians. Concrete actions included, landscape improvement by tree planting, rethinking the role of public art, a new lighting system for nocturnal activities, outdoor fitness equipment, annual car-free day, wider sidewalks, a shared road space that gives priority to cyclists, and the implementation of bicycle parking facilities.
Results:
Analysis of different sources of data (both quantitative and qualitative) show significant positive evaluation from users. Pedestrian use of facilities has significantly increased since interventions started.
Conclusions:
Conceptualizing mobility on a nontraditional way created the conditions for vibrant and healthy spaces at the university campus.
http://dx.doi.org/10.1016/j.jth.2015.04.563
A76 Inequalities in the distribution of primary care providers: Comparing healthcare disparity among urban and rural Floridian Ruth Steiner a, Ilir Bejleri a, Donna Neff b, Jeff Harman a, Barbara Lutz c, Sulhee Yoon a, Michael Bumbach a a
University of Florida, USA University of Central Florida, USA c University of North Carolina Wilmington b
Abstract Background:
Many economics, sociology, and urban planning researchers have assessed regional inequalities, especially for those populations affected by socioeconomic factors such as low income and unemployment status. Inequalities regarding health and its providers have been documented in the last few decades. In 2010, the Department of Human and Health Service (DHHS) launched the Healthy People 2020 movement with goals to eliminate health inequality/disparity and to encourage healthy development. According to the DHHS, health disparity is defined as “a particular type of health difference that is closely linked with physical distance to service, social, economic, and/or environmental disadvantage”. Health disparity that results from the limited access to healthcare facilities is believed to be associated with the unequal distribution of resources and opportunities such as healthcare service, physical activity facilities, and healthy food. However, empirical studies are insufficient for understanding the extent and magnitude of health disparities in the United States. This study seeks to use the inequality of distribution of healthcare providers as a measure for spatial health disparities in urban and rural areas (AIM1) while also monitoring socioeconomic characteristics of the populations in said areas (AIM2).
Methods: For the first aim, this study will calculate the population per physician ratio for each urban and rural census tract boundary in Florida. The Gini coefficient and Lorenz curve are used to measure the sufficiency or the insufficiency of physician distribution for each urban and rural Florida. These measures are designed to analyze inequality of income or wealth, but they also have been used to study the distribution of health resources such as physician distribution.
S43
http://dx.doi.org/10.1016/j.jth.2015.04.560
nA73 Simulating air pollution exposures in an active population as a function of activity patterns Juan Pablo Orjuela a, Antònia Valentín b, David Donaire b, Edmund Seto c, Michael Jerrett c, Gerard Hoek d, Bert Brunekreef d, Mark Nieuwenhuijsen b, Audrey de Nazelle a a
Imperial College, UK Center for Research in Environmental Epidemiology (CREAL), Spain c University of California Berkeley, USA d Utrecht University, Netherlands b
Abstract Background:
Estimating exposure levels and inhaled doses while traveling is an important part in the assessment of the health impacts of air pollution but it is also a challenging task. There is usually a trade-off between accurate concentrations estimates and sample size. Current research focuses mainly in air quality models for large population sets that do not account for individual variability (e.g. dispersion modelling for a city), or in individual exposure measurements that are applicable to specific groups of interest (e.g. exposure measurements of children or pregnant women). Although some authors have focused in exposure concentrations and travel time, recent studies also suggest that including respiration rates may substantially improve daily doses estimates. This study combines modelled air quality data with individual measurements of routes and physical activity using smartphones, achieving large population applicability while accounting for individual variability and respiration rates.
Methods:
The data were measured in an active population of 172 individuals in Barcelona (Spain) using accelerometry and Global Positioning System (GPS) information from smartphones. A Land Use Regression (LUR) model and a dispersion model were used to estimate concentrations of particulate matter of less than 10 and 2.5 μm (PM10 and PM2.5), nitrogen oxides (NOx), and nitrogen dioxide (NO2) with a spatial resolution of 100 m. Temporal adjustments were performed using information from a background station. Ratios for different microenvironments (e.g. home, work) and transport modes (e.g. car, bicycle, bus) were applied on a minute-by-minute basis. Physical activity levels (measured in METS) were used to estimate breathing rates that in combination with estimated exposure were used to calculate inhaled doses.
Results: Although the subjects spend only 9% of their time in transit, the contribution of this activity to the total inhaled dose is greater than 20%. This increase is mainly due to significantly higher concentrations during transport than being at home (t-test, p 40.001) and increased physical activity (t-test, p4 0.001). The uncertainty analysis shows that total inhaled dose while in transit can vary between 17% and 45%. These results are still part of ongoing analyses. Conclusions:
Using smartphones in combination with air quality models shows that transport may have a substantial contribution to daily inhaled doses due to increased physical activity and concentration levels. However, bias in the sample with a large proportion of cyclists and a lack of reliable transport mode ratios need to be considered in the analysis.
http://dx.doi.org/10.1016/j.jth.2015.04.561
Environmental Justice & Social Equity (A74-A76) nA74 Changing travel patterns and journeys to health services in Great Britain 1985-2012: an examination health service utilisation using the National Travel Survey Julian Hine a, Md Kamruzzaman b, Urbi Banerjee a a b
Ulster University, Northern Ireland, UK Queensland University of Technology, Australia
Abstract 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 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. Although rates of utilisation of health services were
S44
Oral Abstracts / Journal of Transport & Health 2 (2015) S5–S63
significantly lower because of longer journey times. 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.
Conclusions:
This finding, 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 difficult 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.
http://dx.doi.org/10.1016/j.jth.2015.04.562
A75 When Mobility nurtures Active Living: A case study Mauricio Leandro a, Henry Hernández-Vega a a
Universidad de Costa Rica
Abstract Background:
The main campus at Universidad de Costa Rica, built in the decade of 1950´s, was intended for a population of less than ten thousand users. The original plan intended to prioritize pedestrian use by creating a central pedestrian sector with an extended park between the faculty buildings and a perimeter road. Over the years, demand for space has been translated into an important reduction of green areas for new parking and buildings. Currently, the campus serves a growing population of more than forty thousand people. Car use is massive inside the campus. Those changes have deteriorated both the aesthetic and social outcomes needed at an academic institution like the one under study. The current message reflected by the main campus´ infrastructure in terms of mobility is undergoing serious questioning. Therefore, since mid 2012, the university has begun a series of actions to improve pedestrian mobility, parking spaces, travel patterns, and so on. Fixing mobility problems at the campus has become an interesting lab to rethink the very concept of mobility. Old paradigms of mobility are falling apart and the discussion now moves to the rather new but exciting field of active living.
Methods:
Due to the nature of the intervention, a mixed methods approach was chosen. Experts from different backgrounds have been invited to take part in the development and implementation of an Active Mobility Plan which elaborates over the concept of non-motorized transportation towards a vision of a healthy campus. The main goal for that “ad-hoc team of enthusiasts” is to create vibrant and healthy public spaces for pedestrians. Concrete actions included, landscape improvement by tree planting, rethinking the role of public art, a new lighting system for nocturnal activities, outdoor fitness equipment, annual car-free day, wider sidewalks, a shared road space that gives priority to cyclists, and the implementation of bicycle parking facilities.
Results:
Analysis of different sources of data (both quantitative and qualitative) show significant positive evaluation from users. Pedestrian use of facilities has significantly increased since interventions started.
Conclusions:
Conceptualizing mobility on a nontraditional way created the conditions for vibrant and healthy spaces at the university campus.
http://dx.doi.org/10.1016/j.jth.2015.04.563
A76 Inequalities in the distribution of primary care providers: Comparing healthcare disparity among urban and rural Floridian Ruth Steiner a, Ilir Bejleri a, Donna Neff b, Jeff Harman a, Barbara Lutz c, Sulhee Yoon a, Michael Bumbach a a
University of Florida, USA University of Central Florida, USA c University of North Carolina Wilmington b
Abstract Background:
Many economics, sociology, and urban planning researchers have assessed regional inequalities, especially for those populations affected by socioeconomic factors such as low income and unemployment status. Inequalities regarding health and its providers have been documented in the last few decades. In 2010, the Department of Human and Health Service (DHHS) launched the Healthy People 2020 movement with goals to eliminate health inequality/disparity and to encourage healthy development. According to the DHHS, health disparity is defined as “a particular type of health difference that is closely linked with physical distance to service, social, economic, and/or environmental disadvantage”. Health disparity that results from the limited access to healthcare facilities is believed to be associated with the unequal distribution of resources and opportunities such as healthcare service, physical activity facilities, and healthy food. However, empirical studies are insufficient for understanding the extent and magnitude of health disparities in the United States. This study seeks to use the inequality of distribution of healthcare providers as a measure for spatial health disparities in urban and rural areas (AIM1) while also monitoring socioeconomic characteristics of the populations in said areas (AIM2).
Methods: For the first aim, this study will calculate the population per physician ratio for each urban and rural census tract boundary in Florida. The Gini coefficient and Lorenz curve are used to measure the sufficiency or the insufficiency of physician distribution for each urban and rural Florida. These measures are designed to analyze inequality of income or wealth, but they also have been used to study the distribution of health resources such as physician distribution.