Interpreting the Results of a Modified Gravity Model: Examining Access to Primary Health Care Physicians in Five Canadian Provinces and Territories

Primary health care (PHC) encompasses an array of health and social services that focus onpreventative, diagnostic, and basic care measures to maintain wellbeing and address illnesses.In Canada, PHC involves the provision of first-contact health care services by providers suchas family physicians and general practitioners – collectively referred as PHC physicians here.Ensuring access is a key requirement of effective PHC delivery. This is because havingaccess to PHC has been shown to positively impact a number of health outcomes.MethodsWe build on recent innovations in measuring potential spatial access to PHC physicians usinggeographic information systems (GIS) by running and then interpreting the findings of amodified gravity model. Elsewhere we have introduced the protocol for this model. In thisarticle we run it for five selected Canadian provinces and territories. Our objectives are topresent the results of the modified gravity model in order to: (1) understand how potentialspatial access to PHC physicians can be interpreted in these Canadian jurisdictions, and (2)provide guidance regarding how findings of the modified gravity model should be interpretedin other analyses.ResultsRegarding the first objective, two distinct spatial patterns emerge regarding potential spatialaccess to PHC physicians in the five selected Canadian provinces: (1) a clear north–southpattern, where southern areas have greater potential spatial access than northern areas; and (2)while gradients of potential spatial access exist in and around urban areas, access outside ofdensely-to-moderately populated areas is fairly binary. Regarding the second objective, weidentify three principles that others can use to interpret the findings of the modified gravitymodel when used in other research contexts

Ontologies for Bioinformatics

The past twenty years have witnessed an explosion of biological data in diverse database formats governed by heterogeneous infrastructures. Not only are semantics (attribute terms) different in meaning across databases, but their organization varies widely. Ontologies are a concept imported from computing science to describe different conceptual frameworks that guide the collection, organization and publication of biological data. An ontology is similar to a paradigm but has very strict implications for formatting and meaning in a computational context. The use of ontologies is a means of communicating and resolving semantic and organizational differences between biological databases in order to enhance their integration. The purpose of interoperability (or sharing between divergent storage and semantic protocols) is to allow scientists from around the world to share and communicate with each other. This paper describes the rapid accumulation of biological data, its various organizational structures, and the role that ontologies play in interoperability

Injury surveillance in low-resource settings using Geospatial and Social Web technologies

<p>Abstract</p> <p>Background</p> <p>Extensive public health gains have benefited high-income countries in recent decades, however, citizens of low and middle-income countries (LMIC) have largely not enjoyed the same advancements. This is in part due to the fact that public health data - the foundation for public health advances - are rarely collected in many LMIC. Injury data are particularly scarce in many low-resource settings, despite the huge associated burden of morbidity and mortality. Advances in freely-accessible and easy-to-use information and communication (ICT) technology may provide the impetus for increased public health data collection in settings with limited financial and personnel resources.</p> <p>Methods and Results</p> <p>A pilot study was conducted at a hospital in Cape Town, South Africa to assess the utility and feasibility of using free (non-licensed), and easy-to-use Social Web and GeoWeb tools for injury surveillance in low-resource settings. Data entry, geocoding, data exploration, and data visualization were successfully conducted using these technologies, including Google Spreadsheet, Mapalist, BatchGeocode, and Google Earth.</p> <p>Conclusion</p> <p>This study examined the potential for Social Web and GeoWeb technologies to contribute to public health data collection and analysis in low-resource settings through an injury surveillance pilot study conducted in Cape Town, South Africa. The success of this study illustrates the great potential for these technologies to be leveraged for public health surveillance in resource-constrained environments, given their ease-of-use and low-cost, and the sharing and collaboration capabilities they afford. The possibilities and potential limitations of these technologies are discussed in relation to the study, and to the field of public health in general.</p

Comparing Circular and Network Buffers to Examine the Influence of Land Use on Walking for Leisure and Errands

Background: There is increasing interest in examining the influence of the built environment onphysical activity. High-resolution data in a geographic information system is increasingly being usedto measure salient aspects of the built environment and studies often use circular or road networkbuffers to measure land use around an individual\u27s home address. However, little research hasexamined the extent to which the selection of circular or road network buffers influences theresults of analysis.The objective of this study is to examine the influence of land use type (residential, commercial,recreational and park land and institutional land) on \u27walking for leisure\u27 and \u27walking for errands\u27using 1 km circular and line-based road network buffers. Data on individual walking patterns isobtained from a survey of 1311 respondents in greater Vancouver and respondent\u27s postal codecentroids were used to construct the individual buffers. Logistic regression was used for statisticalanalysis.Results: Using line-based road network buffers, increasing proportion of institutional landsignificantly reduced the odds of \u27walking for leisure 15 minutes or less per day\u27 no significant resultswere found for circular buffers. A greater proportion of residential land significantly increased theodds of \u27walking for errands less than 1 hour per week\u27 for line-based road network buffer whileno significant results for circular buffers. An increased proportion of commercial land significantlydecreased the odds of \u27walking for errands less than 1 hour per week\u27 for both circular and linebasedroad network buffers.Conclusion: The selection of network or circular buffers has a considerable influence on theresults of analysis. Land use characteristics generally show greater associations with walking usingline-based road network buffers than circular buffers. These results show that researchers need tocarefully consider the most appropriate buffer with which to calculate land use characteristics

Association Of Supermarket Characteristics With The Body Mass Index Of Their Shoppers

Background Research on the built food environment and weight status has mostly focused on the presence/absence of food outlets while ignoring their internal features or where residents actually shop. We explored associations of distance travelled to supermarkets and supermarket characteristics with shoppers’ body mass index (BMI). Methods Shoppers (n=555) of five supermarkets situated in different income areas in the city were surveyed for food shopping habits, demographics, home postal code, height and weight. Associations of minimum distance to a supermarket (along road network, objectively measured using ArcGIS), its size, food variety and food basket price with shoppers’ BMI were investigated. The ‘food basket’ was defined as the mixture of several food items commonly consumed by residents and available in all supermarkets. Results Supermarkets ranged in total floor space (7500–135 000 square feet) and had similar varieties of fruits, vegetables and cereals. The majority of participants shopped at the surveyed supermarket more than once per week (mean range 1.2 ± 0.8 to 2.3 ± 2.1 times per week across the five supermarkets, p &lt; 0.001), and identified it as their primary store for food (52% overall). Mean participant BMI of the five supermarkets ranged from 23.7 ± 4.3 kg/m2 to 27.1 ± 4.3 kg/m2 (p &lt; 0.001). Median minimum distance from the shoppers’ residence to the supermarket they shopped at ranged from 0.96 (0.57, 2.31) km to 4.30 (2.83, 5.75) km (p &lt; 0.001). A negative association was found between food basket price and BMI. There were no associations between BMI and minimum distance to the supermarket, or other supermarket characteristics. After adjusting for age, sex, dissemination area median individual income and car ownership, BMI of individuals who shopped at Store 1 and Store 2, the supermarkets with lowest price of the ‘food basket’, was 3.66 kg/m2 and 3.73 kg/m2 higher compared to their counterparts who shopped at the supermarket where the ‘food basket’ price was highest (p &lt; 0.001). Conclusions The food basket price in supermarkets was inversely associated with BMI of their shoppers. Our results suggest that careful manipulation of food prices may be used as an intervention for decreasing BMI

A Web-based graphical user interface for evidence-based decision making for health care allocations in rural areas

<p>Abstract</p> <p>Background</p> <p>The creation of successful health policy and location of resources increasingly relies on evidence-based decision-making. The development of intuitive, accessible tools to analyse, display and disseminate spatial data potentially provides the basis for sound policy and resource allocation decisions. As health services are rationalized, the development of tools such graphical user interfaces (GUIs) is especially valuable at they assist decision makers in allocating resources such that the maximum number of people are served. GIS can used to develop GUIs that enable spatial decision making.</p> <p>Results</p> <p>We have created a Web-based GUI (wGUI) to assist health policy makers and administrators in the Canadian province of British Columbia make well-informed decisions about the location and allocation of time-sensitive service capacities in rural regions of the province. This tool integrates datasets for existing hospitals and services, regional populations and road networks to allow users to ascertain the percentage of population in any given service catchment who are served by a specific health service, or baskets of linked services. The wGUI allows policy makers to map trauma and obstetric services against rural populations within pre-specified travel distances, illustrating service capacity by region.</p> <p>Conclusion</p> <p>The wGUI can be used by health policy makers and administrators with little or no formal GIS training to visualize multiple health resource allocation scenarios. The GUI is poised to become a critical decision-making tool especially as evidence is increasingly required for distribution of health services.</p

Mass casualty modelling: a spatial tool to support triage decision making

BACKGROUND:During a mass casualty incident, evacuation of patients to the appropriate health care facility is critical to survival. Despite this, no existing system provides the evidence required to make informed evacuation decisions from the scene of the incident. To mitigate this absence and enable more informed decision making, a web based spatial decision support system (SDSS) was developed. This system supports decision making by providing data regarding hospital proximity, capacity, and treatment specializations to decision makers at the scene of the incident.METHODS:This web-based SDSS utilizes pre-calculated driving times to estimate the actual driving time to each hospital within the inclusive trauma system of the large metropolitan region within which it is situated. In calculating and displaying its results, the model incorporates both road network and hospital data (e.g. capacity, treatment specialties, etc.), and produces results in a matter of seconds, as is required in a MCI situation. In addition, its application interface allows the user to map the incident location and assists in the execution of triage decisions.RESULTS:Upon running the model, driving time from the MCI location to the surrounding hospitals is quickly displayed alongside information regarding hospital capacity and capability, thereby assisting the user in the decision-making process.CONCLUSIONS:The use of SDSS in the prioritization of MCI evacuation decision making is potentially valuable in cases of mass casualty. The key to this model is the utilization of pre-calculated driving times from each hospital in the region to each point on the road network. The incorporation of real-time traffic and hospital capacity data would further improve this model

Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices

<p>Abstract</p> <p>Background</p> <p>Over the past several decades researchers have produced substantial evidence of a social gradient in a variety of health outcomes, rising from systematic differences in income, education, employment conditions, and family dynamics within the population. Social gradients in health are measured using deprivation indices, which are typically constructed from aggregated socio-economic data taken from the national census – a technique which dates back at least until the early 1970's. The primary method of index construction over the last decade has been a Principal Component Analysis. Seldom are the indices constructed from survey-based data sources due to the inherent difficulty in validating the subjectivity of the response scores. We argue that this very subjectivity can uncover spatial distributions of local health outcomes. Moreover, indication of neighbourhood socio-economic status may go underrepresented when weighted without expert opinion. In this paper we propose the use of geographic information science (GIS) for constructing the index. We employ a GIS-based Order Weighted Average (OWA) Multicriteria Analysis (MCA) as a technique to validate deprivation indices that are constructed using more qualitative data sources. Both OWA and traditional MCA are well known and used methodologies in spatial analysis but have had little application in social epidemiology.</p> <p>Results</p> <p>A survey of British Columbia's Medical Health Officers (MHOs) was used to populate the MCA-based index. Seven variables were selected and weighted based on the survey results. OWA variable weights assign both local and global weights to the index variables using a sliding scale, producing a range of variable scenarios. The local weights also provide leverage for controlling the level of uncertainty in the MHO response scores. This is distinct from traditional deprivation indices in that the weighting is simultaneously dictated by the original respondent scores and the value of the variables in the dataset.</p> <p>Conclusion</p> <p>OWA-based MCA is a sensitive instrument that permits incorporation of expert opinion in quantifying socio-economic gradients in health status. OWA applies both subjective and objective weights to the index variables, thus providing a more rational means of incorporating survey results into spatial analysis.</p

Pedestrian Injury and the Built Environment: An Environmental Scan of Hotspots

Background: Pedestrian injury frequently results in devastating and costly injuries and accountsfor 11% of all road user fatalities. In the United States in 2006 there were 4,784 fatalities and 61,000&nbsp;injuries from pedestrian injury, and in 2007 there were 4,654 fatalities and 70,000 injuries. In&nbsp;Canada, injury is the leading cause of death for those under 45 years of age and the fourth mostcommon cause of death for all ages Traumatic pedestrian injury results in nearly 4000hospitalizations in Canada annually. These injuries result from the interplay of modifiableenvironmental factors. The objective of this study was to determine links between the built&nbsp;environment and pedestrian injury hotspots in Vancouver.Methods: Data were obtained from the Insurance Corporation of British Columbia (ICBC) forthe 6 year period from 2000 to 2005 and combined with pedestrian injury data extracted from theBritish Columbia Trauma Registry (BCTR) for the same period. High incident locations (hotspots)for pedestrian injury in the City of Vancouver were identified and mapped using geographicinformation systems (GIS), and the characteristics of the built environment at each of the hotspot&nbsp;locations were examined by a team of researchers.Results: The analysis highlighted 32 pedestrian injury hotspot locations in Vancouver. 31 of 32hotspots were situated on major roads. Likewise, the majority of hotspots were located ondowntown streets. The \u27downtown eastside\u27 was identified as an area with multiple high-incidentlocations, including the 2 highest ranked pedestrian injury hotspots. Bars were present at 21 of the&nbsp;hotspot locations, with 11 of these locations being judged to have high alcohol establishmentdensity.Conclusion: This study highlighted the disproportionate burden of pedestrian injury centred onthe downtown eastside area of Vancouver. The environmental scan revealed that important passive&nbsp;pedestrian safety countermeasures were only present at a minority of high-incident locations. More&nbsp;importantly, bars were highly associated with risk of pedestrian injury. This study is the basis forpotential public health intervention by clearly indicating optimal locations for signalized pedestrian&nbsp;crosswalks