Road Network Distance Research Articles

Gravity, distance, and traffic flows in Mexico

This paper presents an econometric analysis that compares the performance of different measures of distance in a gravity model using state data for Mexico. The estimation shows that at this geographic scale, the definition of distance does not affect the explanatory power of the model significantly. However, time-based definitions of distance have a marginal improvement on the model fit in comparison to length-based measures. When geographic specific fixed effects are unknown, the model shows that distance measured as road network distance is a better predictor. The paper concludes that time-based definitions of distance present several advantages in comparison to traditional length-based definitions. However, at large geographic scales, where relative distances between every geographic unit are long, the use of length-based distance instead of time-based distance to approximate travel costs generates similar results.

Can community gardens and farmers' markets relieve food desert problems? A study of Edmonton, Canada

This article integrates community gardens and farmers' markets into a spatial analysis of food deserts in the City of Edmonton, Canada. Our results show that community gardens and farmers' markets can improve fresh food accessibility and help relieve food desert problems to some extent, especially for mature, inner-suburban neighborhoods. However, based on the minimum road network distance and high need indicators, four neighborhoods throughout the city can still be considered as food deserts even after farmers' markets and community gardens are taken into consideration. Regression results reveal that community gardens tend to cluster with supermarkets, so that neighborhoods that have poor access to supermarkets also tend to have limited access to community gardens.

Distance to School is Associated with Sedentary Time in Children: Findings from the URBAN Study.

Sedentary behavior is associated with overweight and obesity in children, and distance to school has been negatively associated with active commuting to school. It is not known how distance to school relates to sedentary behavior in children. The aim of this study was to investigate the association between distance to school and children’s sedentary behavior during weekdays at times where children interact with the neighborhood environment. Children (5–13 years, n = 295) who participated in the understanding relationships between activity and neighborhoods study (2008–2010) across four New Zealand cities wore a hip-mounted accelerometer for 7 days. Minutes spent sedentary (accelerometer count <100 min−1) were derived for the school travel periods (0800–0859 and 1500–1559) and after school discretionary time (1600–1759). Shortest street network distance to school was calculated from residential addresses using geographical information systems and parsed into tertiles for analysis. Children completed a daily travel log including mode of transport to and from school, which was dichotomized into active (walking and cycling) and passive (motorized) modes. Children living in the second tertile of distance from school were the least sedentary during the school traveling periods (42 ± 10%, mean ± true between-child SD) compared to those living in the first or third distance tertiles (47 ± 10 and 49 ± 10%, respectively); the differences were clear and likely substantial (90% confidence limits ± 6%). Children who traveled by motorized transport were more sedentary for each of the distance tertiles (50 versus 44%, 46 versus 39%, and 54 versus 27% for first, second, and third tertiles, respectively; 90% confidence limits ± 7%). In the period of 1600–1759, girls in the third distance tertile were the most sedentary. The combined effects of 1–2 km distance from school and active commuting to school contributed to least sedentary time in children.

Do changes in residents' fear of crime impact their walking? Longitudinal results from RESIDE

ObjectiveTo examine the influence of fear of crime on walking for participants in a longitudinal study of residents in new suburbs. MethodsParticipants (n=485) in Perth, Australia, completed a questionnaire about three years after moving to their neighbourhood (2007–2008), and again four years later (2011–2012). Measures included fear of crime, neighbourhood perceptions and walking (min/week). Objective environmental measures were generated for each participant's neighbourhood, defined as the 1600m road network distance from home, at each time-point. Linear regression models examined the impact of changes in fear of crime on changes in walking, with progressive adjustment for other changes in the built environment, neighbourhood perceptions and demographics. ResultsAn increase in fear of crime was associated with a decrease in residents' walking inside the local neighbourhood. For each increase in fear of crime (i.e., one level on a five-point Likert scale) total walking decreased by 22min/week (p=0.002), recreational walking by 13min/week (p=0.031) and transport walking by 7min/week (p=0.064). ConclusionThis study provides longitudinal evidence that changes in residents' fear of crime influence their walking behaviours. Interventions that reduce fear of crime are likely to increase walking and produce public health gains.

Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data

Geographically weighted regression (GWR) is an important local technique for exploring spatial heterogeneity in data relationships. In fitting with Tobler’s first law of geography, each local regression of GWR is estimated with data whose influence decays with distance, distances that are commonly defined as straight line or Euclidean. However, the complexity of our real world ensures that the scope of possible distance metrics is far larger than the traditional Euclidean choice. Thus in this article, the GWR model is investigated by applying it with alternative, non-Euclidean distance (non-ED) metrics. Here we use as a case study, a London house price data set coupled with hedonic independent variables, where GWR models are calibrated with Euclidean distance (ED), road network distance and travel time metrics. The results indicate that GWR calibrated with a non-Euclidean metric can not only improve model fit, but also provide additional and useful insights into the nature of varying relationships within the house price data set.

Determining health-care facility catchment areas in Uganda using data on malaria-related visits

To illustrate the use of a new method for defining the catchment areas of health-care facilities based on their utilization. The catchment areas of six health-care facilities in Uganda were determined using the cumulative case ratio: the ratio of the observed to expected utilization of a facility for a particular condition by patients from small administrative areas. The cumulative case ratio for malaria-related visits to these facilities was determined using data from the Uganda Malaria Surveillance Project. Catchment areas were also derived using various straight line and road network distances from the facility. Subsequently, the 1-year cumulative malaria case rate was calculated for each catchment area, as determined using the three methods. The 1-year cumulative malaria case rate varied considerably with the method used to define the catchment areas. With the cumulative case ratio approach, the catchment area could include noncontiguous areas. With the distance approaches, the denominator increased substantially with distance, whereas the numerator increased only slightly. The largest cumulative case rate per 1000 population was for the Kamwezi facility: 234.9 (95% confidence interval, CI: 226.2-243.8) for a straight-line distance of 5 km, 193.1 (95% CI: 186.8-199.6) for the cumulative case ratio approach and 156.1 (95% CI: 150.9-161.4) for a road network distance of 5 km. Use of the cumulative case ratio for malaria-related visits to determine health-care facility catchment areas was feasible. Moreover, this approach took into account patients' actual addresses, whereas using distance from the facility did not.

MSSQ: Manhattan Spatial Skyline Queries

Skyline queries have gained attention lately for supporting effective retrieval over massive spatial data. While efficient algorithms have been studied for spatial skyline queries using the Euclidean distance, these algorithms are (1) still quite computationally intensive and (2) unaware of the road constraints. Our goal is to develop a more efficient algorithm for L1 distance, also known as Manhattan distance, which closely reflects road network distance for metro areas. We present a simple and efficient algorithm which, given a set P of data points and a set Q of query points in the plane, returns the set of spatial skyline points in just O(|P|log|P|) time, assuming that |Q|≤|P|. This is significantly lower in complexity than the best known method. In addition to efficiency and applicability, our algorithm has another desirable property of independent computation and extensibility to L∞ norm distance, which naturally invites parallelism and widens applicability. Our extensive empirical results suggest that our algorithm outperforms the state-of-the-art approaches by orders of magnitude. We also present efficient algorithms that report the changes of the skyline points when single or multiple query points move along the x- or y-axis.

Food mirages: Geographic and economic barriers to healthful food access in Portland, Oregon

This paper investigated the role of grocery store prices in structuring food access for low-income households in Portland, Oregon. We conducted a detailed healthful foods market basket survey and developed an index of store cost based on the USDA Thrifty Food Plan. Using this index, we estimated the difference in street-network distance between the nearest low-cost grocery store and the nearest grocery store irrespective of cost. Spatial regression of this metric in relation to income, poverty, and gentrification at the census tract scale lead to a new theory regarding food access in the urban landscape. Food deserts are sparse in Portland, but food mirages are abundant, particularly in gentrifying areas where poverty remains high. In a food mirage, grocery stores are plentiful but prices are beyond the means of low-income households, making them functionally equivalent to food deserts in that a long journey to obtain affordable, nutritious food is required in either case. Results suggested that evaluation of food environments should, at a minimum, consider both proximity and price in assessing healthy food access for low-income households.

Neighbourhood and consumer food environment is associated with dietary intake among Supplemental Nutrition Assistance Program (SNAP) participants in Fayette County, Kentucky.

The aim of the study was to determine the association between dietary outcomes and the neighbourhood food environment (street network distance from home to stores) and consumer food environment (Nutrition Environment Measurement Survey-Stores (NEMS-S) audit). The neighbourhood food environment was captured by creating 0?5-mile and 1-mile network distance (street distance) around each participant’s home and the nearest food venue (convenience store, grocery store, supermarket, farmers’ market and produce stand). The consumer food environment was captured by conducting NEMS-S in all grocery stores/supermarkets within 0?5 and 1 mile of participants’ homes. Fayette County, KY, USA. Supplemental Nutrition Assessment Program (SNAP) participants, n 147. SNAP participants who lived within 0?5 mile of at least one farmers’ market/produce stand had higher odds of consuming one serving or more of vegetables (OR56?92; 95% CI 4?09, 11?69), five servings or more of grains (OR51?76; 95% CI 1?01, 3?05) and one serving or more of milk (OR53?79; 95% CI 2?14, 6?71) on a daily basis. SNAP participants who lived within 0?5 mile of stores receiving a high score on the NEMS-S audit reported higher odds of consuming at least one serving of vegetables daily (OR53?07; 95% CI 1?78, 5?31). Taken together, both the neighbourhood food environment and the consumer food environment are associated with a healthy dietary intake among SNAP participants.

Abstract TP233: Comprehensive Stroke Center Optimization in the United States

Background: Stroke is a time critical disease. Regionalized systems of care are necessary to ensure that patients can be rapidly transported to hospitals with the necessary resources to provide high quality care. The introduction of comprehensive stroke center (CSC) certification presents a unique opportunity to use systems science to guide the development of population-based stroke care for the US. We aim to describe the impact of optimally placed CSCs on access to stroke care nationwide. Methods: We defined access as the percentage of people per state who could reach a CSC in 60 minutes or less by ground EMS transport, calculated using road network distances, posted speeds and empirically-derived prehospital care intervals. Hospitals certified as Joint Commission primary stroke centers (PSC) by 12/31/2010 were considered candidate sites. A greedy adding algorithm, in which CSCs were sequentially added to the system while building upon the previously prescribed system, was used to sequentially determine the best locations for up to 20 CSCs per state. Results: The average state reached a maximum of 53.3% (IQR 35.0-71.6%) access with a mean marginal increase of 31.0% (IQR 16.2-40.8%) for the 1 st , 8.8% (IQR 5.1-13.1%) for the 2 nd , and 4.2% (IQR 0.0-6.8%) for the 3 rd CSC addition (partial results shown in Figure). Conclusions: Operations research techniques can inform the design of efficient stroke care systems by determining optimal locations for CSCs. However, existing candidate sites are clustered and ground transport alone leaves much of the population without access. Collaborative approaches including prehospital helicopter transport and inter-facility transfers need to be developed to ensure access to high quality care for all Americans.

Two Methods That Define the Scale of Obesogenic Environments: A Case Study of Lewiston–Auburn, Maine

Food environments may contribute to obesity (be obesogenic). However, the number of people living in environments deemed obesogenic may be impacted by how distance to food sources is measured. This study, in Lewiston–Auburn, Maine (L-A), used an existing definition of obesogenic environment based on the ratio of unhealthy to healthy food stores within 800 m, 2010 census data, and visits to all food stores/restaurants to build a geographic information system (GIS). This GIS yielded the population and number of single-parent households living in areas deemed obesogenic when distance was measured by Euclidian distance and by road network distance. L-A had 82 fast food restaurants and 81 food stores. We found that 43% of L-A's 59 647 people lived in obesogneic environments when Euclidian distance was used but only 30% did so using road network distance. Single-parent households were at particular risk of living in obesogenic environments (P < .001, comparison by chi-square).

Creating 'obesogenic realities'; do our methodological choices make a difference when measuring the food environment?

BackgroundThe use of Geographical Information Systems (GIS) to objectively measure ‘obesogenic’ food environment (foodscape) exposure has become common-place. This increase in usage has coincided with the development of a methodologically heterogeneous evidence-base, with subsequent perceived difficulties for inter-study comparability. However, when used together in previous work, different types of food environment metric have often demonstrated some degree of covariance. Differences and similarities between density and proximity metrics, and within methodologically different conceptions of density and proximity metrics need to be better understood.MethodsFrequently used measures of food access were calculated for North East England, UK. Using food outlet data from local councils, densities of food outlets per 1000 population and per km2 were calculated for small administrative areas. Densities (counts) were also calculated based on population-weighted centroids of administrative areas buffered at 400/800/1000m street network and Euclidean distances. Proximity (street network and Euclidean distances) from these centroids to the nearest food outlet were also calculated. Metrics were compared using Spearman’s rank correlations.ResultsMeasures of foodscape density and proximity were highly correlated. Densities per km2 and per 1000 population were highly correlated (rs = 0.831). Euclidean and street network based measures of proximity (rs = 0.865) and density (rs = 0.667-0.764, depending on neighbourhood size) were also highly correlated. Density metrics based on administrative areas and buffered centroids of administrative areas were less strongly correlated (rs = 0.299-0.658).ConclusionsDensity and proximity metrics were largely comparable, with some exceptions. Whilst results suggested a substantial degree of comparability across existing studies, future comparability could be ensured by moving towards a more standardised set of environmental metrics, where appropriate, lessening the potential pitfalls of methodological variation between studies. The researchers’ role in creating their own obesogenic ‘reality’ should be better understood and acknowledged.

Incremental Single-Source Multi-Target A* Algorithm for LBS Based on Road Network Distance

Incremental Single-Source Multi-Target A* Algorithm for LBS Based on Road Network Distance

Spatial accessibility to specific sport facilities and corresponding sport practice: the RECORD Study

BackgroundPhysical activity is considered as a major component of a healthy lifestyle. However, few studies have examined the relationships between the spatial accessibility to sport facilities and sport practice with a sufficient degree of specificity. The aim of this study was to investigate the associations between the spatial accessibility to specific types of sports facilities and the practice of the corresponding sports after carefully controlling for various individual socio-demographic characteristics and neighborhood socioeconomic variables.MethodsData from the RECORD Study involving 7290 participants recruited in 2007–2008, aged 30–79 years, and residing in the Paris metropolitan area were analyzed. Four categories of sports were studied: team sports, racket sports, swimming and related activities, and fitness. Spatial accessibility to sport facilities was measured with two complementary approaches that both take into account the street network (distance to the nearest facility and count of facilities around the dwelling). Associations between the spatial accessibility to sport facilities and the practice of the corresponding sports were assessed using multilevel logistic regression after adjusting for individual and contextual characteristics.ResultsHigh individual education and high household income were associated with the practice of racket sports, swimming or related activities, and fitness over the previous 7 days. The spatial accessibility to swimming pools was associated with swimming and related sports, even after adjustment for individual/contextual factors. The spatial accessibility to facilities was not related to the practice of other sports. High neighborhood income was associated with the practice of a racket sport and fitness.ConclusionsAccessibility is a multi-dimensional concept that integrates educational, financial, and geographical aspects. Our work supports the evidence that strategies to increase participation in sport activities should improve the spatial and financial access to specific facilities, but also address educational disparities in sport practice.

Characterising food environment exposure at home, at work, and along commuting journeys using data on adults in the UK

BackgroundSocio-ecological models of behaviour suggest that dietary behaviours are potentially shaped by exposure to the food environment (‘foodscape’). Research on associations between the foodscape and diet and health has largely focussed on foodscapes around the home, despite recognition that non-home environments are likely to be important in a more complete assessment of foodscape exposure. This paper characterises and describes foodscape exposure of different types, at home, at work, and along commuting routes for a sample of working adults in Cambridgeshire, UK.MethodsHome and work locations, and transport habits for 2,696 adults aged 29–60 were drawn from the Fenland Study, UK. Food outlet locations were obtained from local councils and classified by type - we focus on convenience stores, restaurants, supermarkets and takeaway food outlets. Density of and proximity to food outlets was characterised at home and work. Commuting routes were modelled based on the shortest street network distance between home and work, with exposure (counts of food outlets) that accounted for travel mode and frequency. We describe these three domains of food environment exposure using descriptive and inferential statistics.ResultsFor all types of food outlet, we found very different foodscapes around homes and workplaces (with overall outlet exposure at work 125% higher), as well as a potentially substantial exposure contribution from commuting routes. On average, work and commuting environments each contributed to foodscape exposure at least equally to residential neighbourhoods, which only accounted for roughly 30% of total exposure. Furthermore, for participants with highest overall exposure to takeaway food outlets, workplaces accounted for most of the exposure. Levels of relative exposure between home, work and commuting environments were poorly correlated.ConclusionsRelying solely on residential neighbourhood characterisation greatly underestimated total foodscape exposure in this sample, with levels of home exposure unrelated to levels of away from home exposure. Such mis-estimation is likely to be expressed in analyses as attenuated parameter estimates, suggesting a minimal ‘environmental’ contribution to outcomes of interest. Future work should aim to assess exposure more completely through characterising environments beyond the residential neighbourhood, where behaviours related to food consumption are likely to occur.

Effect of Environmental and Lifestyle Factors on Hypertension: Shimane COHRE Study

BackgroundIn recent years there has been increasing evidence of an association between residential remoteness and hypertension (HTN); however, no study has examined the effects of residential remoteness-lifestyle associations on HTN. The objective of this study was to evaluate the effects of residential remoteness, as measured by road network distance and elevation, and lifestyle associations, including access to daily products as a measure of car use, on HTN in a rural region in Japan.MethodThis is a cross-sectional population based study. We analyzed data from the Shimane COHRE study conducted from 2006 to 2009 in the rural mountainous regions of Japan. After excluding missing data, we conducted a logistic regression analysis of the data for 1,348 individuals and examined the effects of residential remoteness and lifestyle associations, including road network distance, elevation and access to daily products as a measure of car use, on the prevalence of HTN.Principal FindingsIn participants without access to car use, the odds ratios for self-reported HTN (i.e. taking antihypertensive medication) were significantly increased in those living in moderate (odds ratio (OR): 2.21, 95% confidence interval (CI): 1.19–4.08) and far (OR: 2.55, 95% CI: 1.00–6.51) road distances, whereas there were no significant associations in participants with access to car use. There were no significant associations between elevation and HTN for participants either with or without access to car transportation.ConclusionsOur findings show that specific residential remoteness-hypertension associations vary according to access to daily products as a measure of car use in a rural mountainous area of Japan. These results advance the understanding and importance of considering residential environment, “where people live,” in establishing health policy.

Classifying neighbourhoods by level of access to stores selling fresh fruit and vegetables and groceries: identifying problematic areas in the city of Gatineau, Quebec.

Physical access to stores selling groceries, fresh fruit and vegetables (FV) is essential for urban dwellers. In Canadian cities where low-density development practices are common, social and material deprivation may be compounded by poor geographic access to healthy food. This case study examines access to food stores selling fresh FV in Gatineau, Quebec, to identify areas where poor access is coincident with high deprivation. Food retailers were identified using two secondary sources and each store was visited to establish the total surface area devoted to the sale of fresh FV. Four population-weighted accessibility measures were then calculated for each dissemination area (DA) using road network distances. A deprivation index was created using variables from the 2006 Statistics Canada census, also at the scale of the DA. Finally, six classes of accessibility to a healthy diet were constructed using a k-means classification procedure. These were mapped and superimposed over high deprivation areas. Overall, deprivation is positively correlated with better accessibility. However, more than 18,000 residents (7.5% of the population) live in high deprivation areas characterized by large distances to the nearest retail food store (means of 1.4 km or greater) and virtually no access to fresh FV within walking distance (radius of 1 km). In this research, we identified areas where poor geographic access may introduce an additional constraint for residents already dealing with the challenges of limited financial and social resources. Our results may help guide local food security policies and initiatives.

위치 기반 서비스에서 도로 네트워크의 거리 정보를 이용한 사용자 정보 은닉 기법

Recent development in wireless communication technology like GPS as well as mobile equipments like PDA and cellular phone makes location-based services (LBSs) popular. However, because users request a query to LBS servers by using their exact locations while moving on the road network, users' privacy may not be protected in the LBSs. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, we, in this paper, propose a road network distance based cloaking scheme supporting user privacy protection in location-based services. The proposed scheme creates a cloaking area by considering road network distance, in order to support the efficient and safe LBSs on the road network. Finally, we show from our performance analysis that our cloaking scheme outperforms the existing cloaking scheme in terms of cloaking area and service time.

Understanding the impact of trails on residential property values in the presence of spatial dependence

This paper examines the impacts of a multi-purpose trail on residential property values in a hedonic model. Using a large housing data set in combination with street network distances, we show that proximity to trail entrances positively effects property values. Among other things, our study compares the hedonic model results from three different spatial specifications. We pay specific attention to the direct and indirect effects on residential property prices associated with potential changes in house characteristics. In addition, our study predicts property values around trail entrances using a ‘modified spatial predictive process’ approach that is well suited for capturing spatial dependence in large data sets.

Obesity and supermarket access: proximity or price?

We examined whether physical proximity to supermarkets or supermarket price was more strongly associated with obesity risk. The Seattle Obesity Study (SOS) collected and geocoded data on home addresses and food shopping destinations for a representative sample of adult residents of King County, Washington. Supermarkets were stratified into 3 price levels based on average cost of the market basket. Sociodemographic and health data were obtained from a telephone survey. Modified Poisson regression was used to test the associations between obesity and supermarket variables. Only 1 in 7 respondents reported shopping at the nearest supermarket. The risk of obesity was not associated with street network distances between home and the nearest supermarket or the supermarket that SOS participants reported as their primary food source. The type of supermarket, by price, was found to be inversely and significantly associated with obesity rates, even after adjusting for individual-level sociodemographic and lifestyle variables, and proximity measures (adjusted relative risk=0.34; 95% confidence interval=0.19, 0.63) Improving physical access to supermarkets may be one strategy to deal with the obesity epidemic; improving economic access to healthy foods is another.