The approaches to measuring the potential spatial access to urban health services revisited: distance types and aggregation-error issues

A multi-dimensional access index: Exploring emergency food assistance in New York City

Access to resources and services needs to be considered from a multi-dimensional perspective to capture the complex landscape of human experience. The robust body of research exploring food access has multiple limitations that create an incomplete view of food access, like studies limited to only one mode of transit and inconsistent methods across studies which limit generalizability. This study proposes a framework to formulate a multi-dimensional access index that considers travel time, operating hours, and availability of transit infrastructure across space. We use food pantries in New York City as a case study since there are relatively few of them and they have limited opening hours. We propose an index that quantifies spatiotemporal access by different modes of transportation and takes operating hours of food pantries into account during a one week time period. We compare our results to two traditional access measures and demonstrate that our index provides a significantly different measure of access. We utilize this index to highlight areas of high need but low resources, which shows the importance of this tool to policy makers and service providers. We use our experience of developing this index to highlight the challenges with quantitative analysis of human experience. Our tool is reproducible through an open-access software, which allows researchers and policy-makers to utilize it with parameters that reflect their communities.

Quantifying Population Characteristics Within and Outside a 30-Minute Drive-Time to Health Resources and Services Administration-Supported Health Centers

The Health Resources and Services Administration's (HRSA) Health Center Program provides health care to vulnerable persons across the US, regardless of their ability to pay for health care. We examined characteristics of populations living within and outside a 30-minute drive-time to HRSA-supported health centers to establish a baseline to better understand the differences in these populations. Using a descriptive, cross-sectional study design and geographic information systems, we found that 94% of persons in the US live within a 30-minute drive-time of a health center. Of those outside a 30-minute drive-time to a health center, 11.7 million (60.11%) are rural and over 1.5 million households (20.32%) lack broadband internet access.

Applications and Best Practices for Geospatial Analysis Research in Dermatology

Dermatologic diseases often exhibit distinct geographic patterns, underscoring the significant role of regional environmental, genetic, and sociocultural factors in driving their prevalence and manifestations. Geographic information and geospatial analysis enable researchers to investigate the spatial distribution of adverse health outcomes and their relationship with socioeconomic and environmental risk factors that are inherently geographic. Health geographers and spatial epidemiologists have developed numerous geospatial analytical tools to collect, process, visualize, and analyze geographic data. These tools help provide vital spatial context to the comprehension of the underlying dynamics behind health outcomes. By identifying areas with high rates of dermatologic disease and areas with barriers to access to quality dermatologic care, findings from studies utilizing geospatial analysis can inform the design and targeting of policy and intervention to help improve dermatologic healthcare outcomes and promote health equity. This article emphasizes the significance of geospatial data and analysis in dermatology research. We explore the common processes in data acquisition, harmonization, and geospatial analytics while conducting spatially and dermatologically relevant research. The article also highlights the practical application of geospatial analysis through instances drawn from the dermatology literature.

Spatial methods for measuring access to health care

Access to health care is a universal human right and key indicator of health system performance. Spatial access encompasses geographic factors mediating with the accessibility and availability of health services. Equity of health service access is a global issue, which includes access to the specialized nursing workforce. Nursing research applying spatial methods is in its infancy. Given the use of spatial methods in health research is a rapidly developing field, it is timely to provide guidance to inspire greater application in cardiovascular research. Therefore, the objective of this methods paper is to provide an overview of spatial analysis methods to measure the accessibility and availability of health services, when to consider applying spatial methods, and steps to consider for application in cardiovascular nursing research.

Store-specific grocery shopping patterns and their association with objective and perceived retail food environments

OBJECTIVE

To explore store-specific grocery shopping patterns and assess associations with the objective and perceived retail food environment (RFE).

DESIGN

This cross-sectional study used principal component analysis and hierarchical cluster analysis to identify grocery shopping patterns and logistic regression models to assess their associations with the RFE, while adjusting for household characteristics.

SETTING

The Montpellier Metropolitan Area, France.

PARTICIPANTS

To be eligible for inclusion, participants had to be 18 years of age or older and reside in the Montpellier Metropolitan Area. Analyses were carried out on 415 households.

RESULTS

Households of cluster 'Supermarket' (49 % of households) primarily shopped at supermarkets and were less likely to live near a convenience store. Households of cluster 'Diversified' (18 %) shopped mostly at organic stores, at markets, at specialised stores, and from producers and were more likely to have a market in their activity space. Households of cluster 'Discount' (12 %) primarily shopped at discounters and were less likely to perceive a producer in their activity space. Households of cluster 'Convenience' (12 %) mostly shopped online or in convenience stores. Finally, households of cluster 'Specialized' (9 %) had high expenditures in greengrocers and in other specialised food stores and were more likely to live near a specialised food store.

CONCLUSIONS

This study highlighted the importance of considering both perceived and objective RFE indicators, as well as assessments around the home and in activity space. Understanding how people buy food and interact with their RFE is crucial for policymakers seeking to improve urban food policies.

Gravity models for potential spatial healthcare access measurement: a systematic methodological review

BACKGROUND

Quantifying spatial access to care-the interplay of accessibility and availability-is vital for healthcare planning and understanding implications of services (mal-)distribution. A plethora of methods aims to measure potential spatial access to healthcare services. The current study conducts a systematic review to identify and assess gravity model-type methods for spatial healthcare access measurement and to summarize the use of these measures in empirical research.

METHODS

A two-step approach was used to identify (1) methodological studies that presented a novel gravity model for measuring spatial access to healthcare and (2) empirical studies that applied one of these methods in a healthcare context. The review was conducted according to the PRISMA guidelines. EMBASE, CINAHL, Web of Science, and Scopus were searched in the first step. Forward citation search was used in the second step.

RESULTS

We identified 43 studies presenting a methodological development and 346 empirical application cases of those methods in 309 studies. Two major conceptual developments emerged: The Two-Step Floating Catchment Area (2SFCA) method and the Kernel Density (KD) method. Virtually all other methodological developments evolved from the 2SFCA method, forming the 2SFCA method family. Novel methodologies within the 2SFCA family introduced developments regarding distance decay within the catchment area, variable catchment area sizes, outcome unit, provider competition, local and global distance decay, subgroup-specific access, multiple transportation modes, and time-dependent access. Methodological developments aimed to either approximate reality, fit a specific context, or correct methodology. Empirical studies almost exclusively applied methods from the 2SFCA family while other gravity model types were applied rarely. Distance decay within catchment areas was frequently implemented in application studies, however, the initial 2SFCA method remains common in empirical research. Most empirical studies used the spatial access measure for descriptive purposes. Increasingly, gravity model measures also served as potential explanatory factor for health outcomes.

CONCLUSIONS

Gravity models for measuring potential spatial healthcare access are almost exclusively dominated by the family of 2SFCA methods-both for methodological developments and applications in empirical research. While methodological developments incorporate increasing methodological complexity, research practice largely applies gravity models with straightforward intuition and moderate data and computational requirements.

Inequities in spatial access to health services in Ghanaian cities

Consideration of health equity is fundamental to enhancing the health of those who are economically/socially disadvantaged. A vital characteristic of health equity and therefore health disparity is the level of spatial access to health services and its distribution among populations. Adequate knowledge of health disparity is critical to enhancing the optimal allocation of resources, identification of underserved populations and improving the efficiency and performance of the health system. The provision of such insight for sub-Saharan African (SSA) cities is a challenge and is severely limited in the literature. Accordingly, this study examined the disparities in potential spatial access to health services for four selected urban areas in Ghana based on: (1) the number of physicians per population; (2) access score based on a weighted sum of access components; (3) travel time to health services and (4) the combined evaluation of linkages between travel distance, settlement area, population and economic status. The overall spatial access to health services is low across all selected cities varying between 3.02 and 1.78 physicians per 10 000 persons, whereas the access score is between 1.70 and 2.54. The current number of physicians needs to be increased by about five times to satisfy the World Health Organization's standard. The low spatial access is not equitable across and within the selected cities, where the economically disadvantaged populations were found to endure longer travel distances to access health services. Inequities were found to be embedded within the selected cities where economically poor populations are also disadvantaged in their physical access to healthcare. The health facilities in all cities have reasonable travel distances separating them but are inadequately resourced with physicians. Thus, increasing the physician numbers and related resources at spatially targeted existing facilities would considerably enhance spatial access to health services.

Calculating access to parks and other polygonal resources: A description of open-source methodologies

Public health studies routinely use simplistic methods to calculate proximity-based "access" to greenspace, such as by measuring distances to the geographic centroids of parks or, less frequently, to the perimeter of the park area. Although computationally efficient, these approaches oversimplify exposure measurement because parks often have specific entrance points. In this tutorial paper, we describe how researchers can instead calculate more-accurate access measures using freely available open-source methods. Specifically, we demonstrate processes for calculating "service areas" representing street-network-based buffers of access to parks within set distances and mode of transportation (e.g., 1-km walk or 20-minute drive) using OpenRouteService and QGIS software. We also introduce an advanced method involving the identification of trailheads or parking lots with OpenStreetMap data and show how large parks particularly benefit from this approach. These methods can be used globally and are applicable to analyses of a wide range of studies investigating proximity access to resources.

Quality appraisal of spatial epidemiology and health geography research: A scoping review of systematic reviews

A scoping review of peer-reviewed literature was conducted to understand how systematic reviews assess the methodological quality of spatial epidemiology and health geography research. Fifty-nine eligible reviews were identified and included. Variations in the use of quality appraisal tools were found. Reviews applied existing quality appraisal tools with no adaptations (n = 32; 54%), existing quality appraisal tools with adaptations (n = 9; 15%), adapted tools or methods from other reviews (n = 13; 22%), and developed new quality appraisal tools for the review (n = 5; 8%). Future research should focus on developing and validating a quality appraisal tool that evaluates the spatial methodology within studies.

How Can We Measure Alcohol Outlet Density Around Schools? A Comparison Between Two Buffer-Based Methods

Measuring the density of alcohol outlets around schools is a critical step towards understanding the drivers of drinking among adolescents. Different methodologies have been used in the literature for this purpose, but the implications of using one methodology or another have not been clearly assessed. Our aim was to compare different methods to measure alcohol outlet density and highlight under which characteristics of the environment might be best using each approach. We used Geographic Information Systems to geolocate schools (n = 576) and alcohol outlets (n = 21,732) in Madrid. We defined the density of alcohol outlets as the number of establishments within an area of 400 m around schools measured using two buffering methods: crow flies' and street network distances. We evaluated the agreement between both methods visually and through regression models, including street connectivity, population density, and density of recreational venues as predictors of disagreement. The density of alcohol outlets around schools was higher using crow flies' distances compared to street network distances. The differences between methodologies were wider in areas of higher density of outlets, especially in the downtown areas, where there are higher population density and street connectivity. Our results suggest that the spatial characteristics and morphology of the study area (e.g., street connectivity and population density) should be considered when deciding the methodology to be used to measure alcohol outlet density. Future studies should explore the implications of different exposure measures in their association with drinking prevalence and consumption patterns among different geographical contexts.

A new method for multispace analysis of multidimensional social exclusion

Social phenomena are multidimensional and dependent on geographic space. Numerous methods are capable of representing multidimensional social phenomena through a composite indicator. Among these methods, principal component analysis (PCA) is the most used when considering the geographical perspective. However, the composite indicators built by the method are sensitive to outliers and dependent on the input data, implying informational loss and specific eigenvectors that make multi-space-time comparisons impossible. This research proposes a new method to overcome these problems: the Robust Multispace PCA. The method incorporates the following innovations. The sub-indicators are weighted according to their conceptual importance in the multidimensional phenomenon. The non-compensatory aggregation of these sub-indicators guarantees the function of the weights as of relative importance. Aggregating indicators in dimensions balances the weight structure of dimensions in the composite indicator. A new scale transformation function that eliminates outliers and allows multispatial comparison reduces by 1.52 times the informational loss of the composite indicator of social exclusion in eight cities' urban areas. The Robust Multispace-PCA has a high potential for appropriation by researchers and policymakers, as it is easy to follow, offers more informative and accurate representations of multidimensional social phenomena, and favors the development of policies at multiple geographic scales.

An interactive geographic information system to inform optimal locations for healthcare services

Large health datasets can provide evidence for the equitable allocation of healthcare resources and access to care. Geographic information systems (GIS) can help to present this data in a useful way, aiding in health service delivery. An interactive GIS was developed for the adult congenital heart disease service (ACHD) in New South Wales, Australia to demonstrate its feasibility for health service planning. Datasets describing geographic boundaries, area-level demographics, hospital driving times, and the current ACHD patient population were collected, linked, and displayed in an interactive clinic planning tool. The current ACHD service locations were mapped, and tools to compare current and potential locations were provided. Three locations for new clinics in rural areas were selected to demonstrate the application. Introducing new clinics changed the number of rural patients within a 1-hour drive of their nearest clinic from 44·38% to 55.07% (79 patients) and reduced the average driving time from rural areas to the nearest clinic from 2·4 hours to 1·8 hours. The longest driving time was changed from 10·9 hours to 8·9 hours. A de-identified public version of the GIS clinic planning tool is deployed at https://cbdrh.shinyapps.io/ACHD_Dashboard/. This application demonstrates how a freely available and interactive GIS can be used to aid in health service planning. In the context of ACHD, GIS research has shown that adherence to best practice care is impacted by patients' accessibility to specialist services. This project builds on this research by providing opensource tools to build more accessible healthcare services.

Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia

Disparities in access to health services in rural areas represent a global health issue. Various external factors contribute to these disparities and each root requires specific remedial action to alleviate the issue. This study elucidates an approach to assessing the spatial accessibility of primary care, considering Malaysia's dual public-private system specifically in rural areas, and identifies its associated ecological factors. Spatial accessibility was calculated using the Enhance 2-Step Floating Catchment Area (E2SFCA) method, modified as per local context. Data were secondary sourced from Population and Housing Census data and administrative datasets pertaining to health facilities and road network. The spatial pattern of the E2SFCA scores were depicted using Hot spot Analysis. Hierarchical multiple linear regression and geographical weight regression were performed to identify factors that affect E2SFCA scores. Hot spot areas revolved near the urban agglomeration, largely contributed by the private sector. Distance to urban areas, road density, population density dependency ratios and ethnic composition were among the associated factors. Accurate conceptualization and comprehensive assessment of accessibility are crucial for evidence-based decision making by the policymakers and health authorities in identifying areas that need attention for a more specific and localized planning and development.

Disparities in spatial access to neurological care in Appalachia: a cross-sectional health services analysis

Background

Appalachia is rural and socioeconomically deprived with a heavy burden of neurological disorders and poor access to healthcare providers. Rates of neurological disorders are increasing over time without equal increases in providers, indicating that Appalachian disparities are likely to worsen. Spatial access to neurological care has not been robustly explored for U.S. areas, so we aimed to examine disparities in the vulnerable Appalachian region.

Methods

Using 2022 CMS Care Compare physician data, we conducted a cross-sectional health services analysis, where we computed spatial accessibility of neurologists for all census tracts in the 13 states with Appalachian counties. We stratified access ratios by state, area deprivation, and rural-urban commuting area (RUCA) codes then utilized Welch two-sample t-tests to compare Appalachian tracts with non-Appalachian tracts. Using stratified results, we identified Appalachian areas where interventions would have the largest impact.

Findings

Appalachian tracts (n = 6169) had neurologist spatial access ratios between 25% and 35% lower than non-Appalachian tracts (n = 18,441; p < 0.001). When stratified by rurality and deprivation, three-step floating catchment area spatial access ratios for Appalachian tracts remained significantly lower in the most urban (RUCA = 1 [p < 0.0001) and most rural tracts (RUCA = 9 [p = 0.0093]; RUCA = 10 [p = 0.0227]). We identified 937 Appalachian census tracts where interventions can be targeted.

Interpretation

After stratifying by rural status and deprivation, significant disparities in spatial access to neurologists remained for Appalachian areas, indicating both poorer access in Appalachia and that neurologist accessibility cannot be determined solely by remoteness and socioeconomic status. These findings and our identified disparity areas have broad implications for policymaking and intervention targeting in Appalachia.

Funding

R.B.B. was supported by NIH Award Number T32CA094186. M.P.M. was supported by NIH-NCATS Award Number KL2TR002547.

MHV3SFCA: A new measure to capture the spatial accessibility of health care systems

Good accessibility of health care services is essential to meet the needs of the population and ensure adequate health care coverage. It usually refers to two spatial dimensions: availability (competition between populations for the same medical supply) and reachability (distance between population and medical supply). Traditional indicators of health care accessibility usually fail to consider both of these components simultaneously. Floating-Catchment-Area (FCA) methods were developed to address these shortcomings. This study reviews the existing FCA methods and proposes the Modified Huff-based Variable 3 Steps Floating Catchment Area (MHV3SFCA) method as a new approach. The MHV3SFCA method integrates the strengths of several existing FCA methods into a single method, such as supply competition through the Huff model, and the integration of variable effective catchment sizes. In addition, and as a novelty, the MHV3SFCA relies on the assumption of a constant overall population demand, independent of the distances between population units and supply sites. It also accounts for absolute difference in distances without overestimating distance effects. Based on the results of a simulation study the paper discusses the strengths of the MHV3SFCA method capturing spatial differences in access to health care services.

Are Pivotal Clinical Trials for Drugs Approved for Leukemias and Multiple Myeloma Representative of the Population at Risk?

PURPOSE

There are significant disparities in care and outcomes for patients with leukemias and multiple myeloma (MM). To evaluate the extent to which clinical trials (CTs) match the demographic and geographic diversity of populations affected by leukemias and MM.

METHODS

CTs leading to drug approval were identified from the US Food and Drug Administration databases. Demographic and geographic data were collected from ClinicalTrials.gov and primary manuscripts. Standard descriptive statistics were used to summarize the data in frequencies and proportions, including 95% CIs, by race, ethnicity, sex, and malignancy subtypes.

RESULTS

A total of 41 (67.2%) trials leading to drug approval reported data on race and 20 (48.8%) on ethnicity. These trials included 13,731 patients, of whom 11,209 (81.6%) were White. Among minorities, Asian-Pacific Islanders and Blacks had the highest representation in chronic myeloid leukemia, 147 (12.7%) and 61 (5.3%), and lowest in chronic lymphocytic leukemia, 55 (3%) and 20 (1.1%), respectively. Proportions for Blacks, Native Americans, and Hispanics were significantly low, reflecting under-representation in trials compared with the proportion in the general population. Females were also under-represented in acute myeloid leukemia (44.7% v 60.5%, P < .0001), and males in MM (55.3% v 60.2%, P < .0001) and chronic myeloid leukemia (55.2% v 62.9%, P < .0001). The geographic distribution of trials showed inadequate regional and state participation compared with mortality for all malignancies except MM.

CONCLUSION

There are significant demographic and geographic under-representation and imbalances in pivotal CTs leading to drug approvals for leukemias and MM compared with the population affected. These disparities need to be addressed to make results applicable to all relevant populations.

Patient characteristics associated with access to minimally invasive gynecologic surgery: Changes during the COVID-19 pandemic

Study Objective

To evaluate patient characteristics that affect access to minimally invasive gynecologic surgery (MIGS) subspecialty care and identify changes during the coronavirus disease 2019 pandemic.

Design

Retrospective cohort study of patients referred to MIGS from 2014 to 2016 (historic cohort) compared with those referred to MIGS in 2020 (pandemic cohort). Primary outcome was the interval between referral and first appointment.

Setting

Single-institution academic MIGS division.

Patients

Historic cohort (n = 1082) and pandemic cohort (n = 770).

Interventions

Not applicable.

Measurements and Main Results

Demographics and socioeconomic variables (race, ethnicity, language, insurance, employment, and socioeconomic factors by census tract) and distance from hospital were compared between historic and pandemic cohorts with respect to referral interval using the chi-square, Fisher exact tests, and logistic regression. After adjusting for referral indication, being unemployed and living in an area with less population density, less education, and higher percentage of poverty were associated with a referral interval >30 days in the historic cohort. In the pandemic cohort, only unemployment persisted as a covariate associated with prolonged referral interval and new associated variables were primary language other than English (odds ratio, 3.20; 95% confidence interval [CI], 1.60–6.40) and “other” race (odds ratio, 2.22; 95% CI, 1.34–3.68). The odds of waiting >30 days increased by 6% with the addition of 1 demographic risk factor (95% CI, 1.01–1.10) and by 17% for 3 risk factors (95% CI, 1.03–1.34) in the historic cohort whereas no significant intersectionality was identified in the pandemic cohort. Average referral intervals were significantly shorter during the pandemic (31 vs 50 days, p <.01). Telemedicine appointments had a significantly shorter referral interval than in-person appointments (27 vs 47 days, p <.01). Of patients using telemedicine, a greater proportion were non-Hispanic, English speaking, employed, privately insured, and lived further from the hospital (p <.05).

Conclusion

Time from referral to first appointment at a tertiary-care MIGS practice during the coronavirus disease 2019 pandemic was shorter than that before the pandemic, likely owing to the adoption of telemedicine. Differences in socioeconomic and demographic factors suggest that telemedicine improved access to care and decreased access disparities for many populations, but not for non–English-speaking patients.

Associations between neighborhood characteristics and dating violence: does spatial scale matter?

Background

Dating violence (DV) is a public health problem that could have serious repercussions for the health and well-being of a large number of adolescents. Several neighborhood characteristics could influence these behaviors, but knowledge on such influences is still limited. This study aims at (1) evaluating the associations between neighborhood characteristics and DV, and (2) assessing how spatial scale influences the estimations of the latter associations.

Methods

The Québec Health Survey of High School Students (2016–2017) was used to describe DV. Neighborhoods were operationalized with polygon-based network buffers of varying sizes (ranging from 250 to 1000 m). Multiple data sources were used to describe neighborhood characteristics: crime rate, alcohol outlet density (on-premises and off-premises), walkability, greenness, green spaces density, and youth organizations density. Gendered-stratified logistic regressions were used for assessing the association between neighborhood characteristics and DV.

Results

For boys, off-premises alcohol outlet density (500 m) is associated with an increase in perpetrating psychological DV. Crime rate (500 m) is positively associated with physical or sexual DV perpetration, and crime rate (250 m) is positively associated with physical or sexual DV victimization. Greenness (1000 m) has a protective effect on psychological DV victimization. For girls, walkability (500 m to 1000 m) is associated with a decrease in perpetrating and experiencing psychological DV, and walkability (250 m) is negatively associated with physical or sexual DV victimization.

Conclusions

Several neighborhood characteristics are likely to influence DV, and their effects depend on the form of DV, gender, and spatial scale. Public policies should develop neighborhood-level interventions by improving neighborhood living conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00306-3.

Geographic accessibility to health facilities predicts uptake of community-based tuberculosis screening in an urban setting

Objectives:

Annually, more than 30% of individuals with tuberculosis (TB) remain undiagnosed. We aimed to assess whether geographic accessibility measures can identify neighborhoods that would benefit from TB screening services targeted toward closing the diagnosis gap.

Methods:

We used data from a community-based mobile TB screening program in Carabayllo district, Lima, Peru. We constructed four accessibility measures from the geographic center of neighborhoods to health facilities. We used logistic regression to assess the association between these measures and screening uptake in one’s residential neighborhood versus elsewhere, with quasi-information criterion values to assess the association.

Results:

We analyzed the screening locations for 25,000 Carabayllo residents from 49 neighborhoods. Pedestrian walk time was preferable to Euclidean distance or vehicular time in our models. For each additional 12 minutes walking time between the neighborhood and the health facility, the odds of residents using TB screening units located in their neighborhoods increased by 50% (95% CI: 26%–78%). Females had 9% (95% CI: 3%–16%) increased odds versus males of using a screening unit in their own neighborhood.

Conclusion:

Placing mobile TB screening units in neighborhoods with longer pedestrian time to access health facilities could benefit individuals who face more acute access barriers to health care.

How were we before? An analysis of the potential supply and inequality in the geographic access to critical resources for the COVID-19 treatment

The objective was to analyze the situation of the Metropolitan Area of Brasília (AMB) before the onset of the COVID-19 pandemic, focusing on the availability and geographical accessibility of critical resources for the treatment of acute respiratory crises caused by the SARS-CoV-2 virus. Geographic mapping of the population within the territory and geolocation of health facilities and resources, construction of a relationship network between the potential demand simulated to the public health system and the supply of resources available in December 2019. The relationship analysis is based on the theory of complex networks crossing socioeconomic data available in the CENSUS and information from the National Registry of Health Establishments (CNES) and analyzing the micro relationship of census tracts with the stock and availability of health resources concerning Adult ICU Bed Type II/III and Respirators/Ventilators. The Federal District (DF) health facilities concentrate more than 75% of the relationships of potential access to critical resources for the treatment of COVID-19. Although the regions surrounding the DF, belonging to Goiás state, have the greatest relative vulnerability in the studied territory, they are also the most lacking in spatial accessibility and availability of resources, evidencing a care imbalance within the AMB region.

Geographic barriers to care persist at the community healthcare level: Evidence from rural Madagascar

Geographic distance is a critical barrier to healthcare access, particularly for rural communities with poor transportation infrastructure who rely on non-motorized transportation. There is broad consensus on the importance of community health workers (CHWs) to reduce the effects of geographic isolation on healthcare access. Due to a lack of fine-scale spatial data and individual patient records, little is known about the precise effects of CHWs on removing geographic barriers at this level of the healthcare system. Relying on a high-quality, crowd-sourced dataset that includes all paths and buildings in the area, we explored the impact of geographic distance from CHWs on the use of CHW services for children under 5 years in the rural district of Ifanadiana, southeastern Madagascar from 2018-2021. We then used this analysis to determine key features of an optimal geographic design of the CHW system, specifically optimizing a single CHW location or installing additional CHW sites. We found that consultation rates by CHWs decreased with increasing distance patients travel to the CHW by approximately 28.1% per km. The optimization exercise revealed that the majority of CHW sites (50/80) were already in an optimal location or shared an optimal location with a primary health clinic. Relocating the remaining CHW sites based on a geographic optimum was predicted to increase consultation rates by only 7.4%. On the other hand, adding a second CHW site was predicted to increase consultation rates by 31.5%, with a larger effect in more geographically dispersed catchments. Geographic distance remains a barrier at the level of the CHW, but optimizing CHW site location based on geography alone will not result in large gains in consultation rates. Rather, alternative strategies, such as the creation of additional CHW sites or the implementation of proactive care, should be considered.

Geographic Access to Radiation Therapy Facilities in the United States

BACKGROUND

The current distribution of radiation therapy (RT) facilities in the US is not well established. A comprehensive inventory of US RT facilities was last assessed in 2005, based on data from state regulatory agencies and dosimetric quality assurance bodies. We updated this database to characterize population-level measures of geographic access to RT and analyze changes over the past 15 years.

METHODS

We compiled data from regulatory and accrediting organizations to identify US facilities with linear accelerators used to treat humans in 2018-2020. Addresses were geocoded and analyzed with Geographic Information Services (GIS) software. Geographic access was characterized by assessing the Euclidian distance between zip code tabulation areas (ZCTA)/county centroids and RT facilities. Populations were assigned to each county to estimate the impact of facility changes at the population level. Logistic regressions were performed to identify features associated with increased distance to RT and associated with regions that gained an RT facility between the two time points studied.

RESULTS

In 2020, a total of 2,313 US RT facilities were reported compared to 1,987 in 2005, representing a 16.4% growth in facilities over nearly 15 years. Based on population attribution to ZCTA centroids, 77.9% of the US population lives within 12.5 miles of an RT facility, and 1.8% of the US population lives more than 50 miles from an RT facility. We found that increased distance to RT was associated with non-metro status, less insurance, older median age, and less populated regions. Between 2005 and 2020, the population living within 12.5 miles from an RT facility increased by 2.1 percentage points, while the population living furthest from RT facilities decreased 0.6 percentage points. Regions with improved geographic RT access are more likely to be higher income and better insured.

CONCLUSION

1.8% of the US population has limited geographic access to radiation therapy. We found that people benefiting from improved access to RT facilities are more economically advantaged, suggesting disparities in geographic access may not improve without intervention.

Using the location-allocation P-median model for optimising locations for health care centres in the city of Jeddah City, Saudi Arabia

Considering spatial accessibility of health services is a critical part in the planning and management of health services. There is evidence that poor geographical locations can obstruct prompt basic health care services to some population sections. We developed a location-allocation P-median model for health centres after analysing their sites, demand location of health services and the road network in Jeddah, Saudi Arabia. This model attempts to optimize health care services network and to put forward location recommendations to maximise service coverage. Our model is shown to be useful as it provides a robust evidence base to urban planners and policymakers responsible for making spatial decisions for the development of the health sector. Besides, it follows the paradigm of new urbanism that encourages decentralisation of essential facilities including basic healthcare in cities, where emphasis is on offering all basic services within walkable distances of 15 min. or less.

Spatial Accessibility of Primary Health Care in Rural Areas in Poland

The aim of the study was to assess the spatial accessibility of basic and universal healthcare (understood as primary healthcare (PHC) facilities) in rural statistical localities in Poland. Data from the National Health Fund, Central Statistical Office, National Register of Geographic Names and OpenStreetMap were used in the research. The research was carried out on the basis of modelled distance from the rural statistical localities to the nearest PHC facility. The methods used included network analysis, characteristics of normal point distribution, Theil index, and spatial autocorrelation. Areas where the greatest shortages of access to PHC facilities occurred were indicated on the basis of the analysis of their clustering density. The average distance from rural statistical localities in Poland to PHC facilities is about 5 km. Slightly more than 70% of the distance values are within one standard deviation of the mean. Better access to the examined healthcare facilities is available in the southern and central parts of Poland, while northern and eastern Poland, as well as the border areas, suffer from lower accessibility. Poor access to PHC occurs first of all at the border of Greater Poland Voivodeship with the Kuyavian-Pomeranian Voivodeship, on the border of the Lodz Voivodeship, in Masovian and Swietokrzyskie Voivodeship, and in the ring surrounding Warsaw, as well as in the Pomeranian Voivodeship. The research findings can be used to develop strategies to improve the accessibility of primary care facilities in rural areas.

Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources

GIS-based spatial access measures have been used extensively to monitor social equity and to help develop policy. However, inherent uncertainties in the road datasets used in spatial access estimates remain largely underreported. These uncertainties might result in unrecognized biases within visualization products and decision-making outcomes that strive to improve social equity based on seemingly egalitarian accessibility metrics. To better understand and address these uncertainties, we evaluated variations in travel impedance for car and bus transportation using proprietary, volunteer-information-based, and free (non-volunteer-information-based) street networks. We then interpreted the measured variations through the lens of street data uncertainty and its propagation in a common E2SFCA model of spatial accessibility. Results indicated that travel impedance disagreement propagates through the modeling process to effect agreement of spatial access index (SPAI) estimates among different street sources, with larger uncertainties observed for bus travel than car travel. Higher impedance coefficients (β), a model parameter, reduced the impact of street-source variations on estimates. Less urbanized regions were found to experience higher street-source variations when compared with the core-metropolitan area. We also demonstrated that a relative spatial access measure - the spatial access ratio (SPAR) - reduced uncertainties introduced by the choice of street datasets. Careful selection of reliable street sources and model parameters (e.g., higher β), as well as consideration of the potential for bias, particularly for less urbanized areas and areas reliant on public transportation, is warranted when leveraging SPAI to inform policy. When reliable/accurate road network data is not accessible or data quality information is not available, the SPAR is a suitable alternative or supplement to SPAI for visualization and analyses.

A Review of Recent Spatial Accessibility Studies That Benefitted from Advanced Geospatial Information: Multimodal Transportation and Spatiotemporal Disaggregation

Spatial accessibility provides significant policy implications, describing the spatial disparity of access and supporting the decision-making process for placing additional infrastructure at adequate locations. Several previous reviews have covered spatial accessibility literature, focusing on empirical findings, distance decay functions, and threshold travel times. However, researchers have underexamined how spatial accessibility studies benefitted from the recently enhanced availability of dynamic variables, such as various travel times via different transportation modes and the finer temporal granularity of geospatial data in these studies. Therefore, in our review, we investigated methodological advancements in place-based accessibility measures and scrutinized two recent trends in spatial accessibility studies: multimodal spatial accessibility and temporal changes in spatial accessibility. Based on the critical review, we propose two research agendas: improving the accuracy of measurements with dynamic variable implementation and furnishing policy implications granted from the enhanced accuracy. These agendas particularly call for the action of geographers on the full implementation of dynamic variables and the strong linkage between accessibility and policymaking.

Characterizing the performance of emergency medical transport time metrics in a residentially segregated community

OBJECTIVE

To derive and characterize the performance of various metrics of emergency transport time in assessing for sociodemographic disparities in the setting of residential segregation. Secondarily to characterize racial disparities in emergency transport time of suspected stroke patients in Austin, Texas.

DATA SOURCES

We used a novel dataset of 2518 unique entries with detailed spatial and temporal information on all suspected stroke transports conducted by a public emergency medical service in Central Texas between 2010 and 2018.

STUDY DESIGN

We conducted one-way ANOVA tests with post-hoc pairwise t-tests to assess how mean hospital transport times varied by patient race. We also developed a spatially-independent metric of emergency transport urgency, the ratio of expected duration of self-transport to a hospital and the measured transport time by an ambulance.

DATA COLLECTION/EXTRACTION

We calculated ambulance arrival and destination times using sequential temporospatial coordinates. We excluded any entries in which patient race was not recorded. We also excluded entries in which ambulances' routes did not pass within 100 m of either the patient's location or the documented hospital destination.

PRINCIPAL FINDINGS

We found that mean transport time to a hospital was 2.5 min shorter for black patients compared to white patients. However, white patients' transport times to a hospital were found to be, on average, 4.1 min shorter than expected compared to 3.4 min shorter than expected for black patients. One-way ANOVA testing for the spatially-independent index of emergency transport urgency was not statistically significant, indicating that average transport time did not vary significantly across racial groups when accounting for variations in transport distance.

CONCLUSIONS

Using a novel transport urgency index, we demonstrate that these findings represent race-based variation in spatial distributions rather than racial bias in emergency medical transport. These results highlight the importance of closely examining spatial distributions when utilizing temporospatial data to investigate geographically-dependent research questions.

A model for measuring healthcare accessibility using the behavior of demand: a conditional logit model-based floating catchment area method

BACKGROUND

Estimating realistic access to health services is essential for designing support policies for healthcare delivery systems. Many studies have proposed a metric to calculate accessibility. However, patients' realistic willingness to use a hospital was not explicitly considered. This study aims to derive a new type of potential accessibility that incorporates a patient's realistic preference in selecting a hospital.

METHODS

This study proposes a floating catchment area (FCA)-type metric combined with a discrete choice model. Specifically, a new FCA-type metric (clmFCA) was proposed using a conditional logit model. Such a model estimates patients' realistic willingness to use health services. The proposed metric was then applied to calculate the accessibility of obstetric care services in Korea.

RESULTS

The clmFCA takes advantage of patients' realistic preferences. Specifically, it can represent each patient's heterogeneous characteristics regarding hospital choice. Such characteristics include bypassing behavior, which could not be considered using prior FCA metrics. Empirical analysis reveals that the clmFCA avoids the misestimation of accessibility to health services to an extent.

CONCLUSIONS

The clmFCA offers a new framework that more realistically estimates patients' accessibility to health services. This is achieved by accurately estimating the potential demand for a service. The proposed method's effectiveness was verified through a case study using nationwide data.

Determining optimal clinical target volume margins in high-grade glioma based on microscopic tumor extension and magnetic resonance imaging

Introduction

In this study, we performed a consecutive macropathologic analysis to assess microscopic extension (ME) in high-grade glioma (HGG) to determine appropriate clinical target volume (CTV) margins for radiotherapy.

Materials and methods

The study included HGG patients with tumors located in non-functional areas, and supratotal resection was performed. The ME distance from the edge of the tumor to the microscopic tumor cells surrounding brain tissue was measured. Associations between the extent of ME and clinicopathological characteristics were evaluated by multivariate linear regression (MVLR) analysis. An ME predictive model was developed based on the MVLR model.

Results

Between June 2017 and July 2019, 652 pathologic slides obtained from 30 HGG patients were analyzed. The mean ME distance was 1.70 cm (range, 0.63 to 2.87 cm). The MVLR analysis identified that pathologic grade, subventricular zone (SVZ) contact and O⁶-methylguanine-DNA methyltransferase (MGMT) methylation, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status were independent variables predicting ME (all P < 0.05). A multivariable prediction model was developed as follows: Y_ME = 0.672 + 0.513X_Grade + 0.380X_SVZ + 0.439X_MGMT + 0.320X_IDH + 0.333X_1p/19q. The R-square value of goodness of fit was 0.780. The receiver operating characteristic curve proved that the area under the curve was 0.964 (P < 0.001).

Conclusion

ME was heterogeneously distributed across different grades of gliomas according to the tumor location and molecular marker status, which indicated that CTV delineation should be individualized. The model could predict the ME of HGG, which may help clinicians determine the CTV for individual patients.

Trial registration The trial was registered with Chinese Clinical Trial Registry (ChiCTR2100046106). Registered 4 May 2021-Retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-021-01819-0.

Cycling in one of the most polluted cities in the world: Exposure to noise and air pollution and potential adverse health impacts in Delhi

Background

In India, many cities struggle with extreme levels of air pollution and noise. Delhi, in particular, has the notorious reputation of being one of the most polluted cities in the world. Cyclists constitute a particularly exposed population, since they cycle among motor vehicles without any protection. This paper modeled the cyclists’ exposure to nitrogen dioxide (NO₂) and noise in Delhi, India.

Methods

Using primary data collected on 1,229 kms of roads in Delhi, Generalized Additive Mixed Models with Auto-Regressive terms (GAMMAR) are constructed for noise exposure, NO₂ exposure and NO₂ inhalation doses.

Results

Results show that cyclists are exposed to 47 µg/m³ of NO₂ and 3.3 dB(A) more when cycling on a primary road than on a residential street. Using WHO guideline values for noise and air pollution, we assessed how many minutes of inhaling doses and noise doses become potentially harmful to cyclists’ health in Delhi. Such thresholds are quickly exceeded: after cycling one hour in an area with moderate predicted values of noise and air pollution, the noise dose and inhaled dose of NO₂ will reach 212% and 403 µg on residential streets, and 459% and 482 µg on primary roads, respectively.

Conclusion

Policy makers should take these results into account to minimize cyclists’ exposure, especially for the most deprived people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-021-00272-2.

Is Covid-19 community level testing effective in reaching at-risk populations? Evidence from spatial analysis of New Orleans patient data at walk-up sites

BACKGROUND

This paper evaluates the increase in coverage and use of Covid-19 testing services for vulnerable and hard-to-reach populations through the introduction of community-based walk-up sites in New Orleans, LA. While most GIS work on Covid-19 testing coverage and access has used census tract or ZIP code aggregated data, this manuscript is unique in that it uses individual level demographics and exact addresses to calculate distances actually traveled by patients.

METHODS

We used testing data recorded for 9721 patients at 20 sites operating in May-June 2020. The dataset includes detailed age, race and ethnicity, and testing results as well as the exact address of each individual. Using GIS, we estimated changes in testing coverage for minority neighborhoods and calculated the actual distance covered by individuals. Logistic regression and multivariate linear regression were used to identify socio-demographic variables associated with distance travelled to and used of nearest testing site. We used a secondary dataset from drive-through sites to evaluate change in coverage at the census tract level for the metropolitan area.

RESULTS

Walk-up sites significantly increased testing availability in New Orleans, and specifically in minority neighborhoods. Both African Americans and Asians were more likely (14.7 and 53.0%) to be tested at the nearest walk-up site. They also covered shorter distances to get tested. Being elderly was also significantly and positively associated with testing at the nearest site. Hispanics, however, were not associated with increased proximity to and use of nearest sites, and they traveled an additional 0.745 km to get tested. Individuals who tested positive also travelled significantly longer distances to obtain a test.

CONCLUSIONS

Walk-up sites increased testing availability for some vulnerable populations who took advantage of the sites' proximity, although inequalities appear at the metropolitan scale. As cities are planning community vaccination campaigns, mobile, walk-up sites appear to improve both coverage and accessibility for hard-to-reach populations. With adequate technical (vaccine dose refrigeration) and messaging (addressing reticence to immunization) adaptations, they could constitute a key complementary approach to health facility points of delivery.

Quantifying spatial accessibility of general practitioners by applying a modified huff three-step floating catchment area (MH3SFCA) method

BACKGROUND

It is necessary to ensure sufficient healthcare. The use of current, precise and realistic methods to model spatial accessibility to healthcare and thus improved decision-making is helping this process. Generally, these methods-which include the family of floating catchment area (FCA) methods-incorporate a number of criteria that address topics like access, efficiency, budget, equity and the overall system utilization. How can we measure spatial accessibility? This paper investigates a sophisticated approach for quantifying the spatial accessibility of general practitioners. (GPs). Our objective is the investigation and application of a spatial accessibility index by an improved Huff three-step floating catchment area (MH3SFCA) method.

METHODS

We modify and implement the huff model three-step floating catchment area (MH3SFCA) method and exemplary calculation of the spatial accessibility indices for the test study area. The method is extended to incorporate a more realistic way to model the distance decay effect. To that end, instead of a binary approach, a continuous approach is employed. Therefore, each distance between a healthcare site and the population is incorporated individually. The study area includes Swabia and the city of Augsburg, Germany. The data for analysis is obtained from following data sources: (1) Acxiom Deutschland GmbH (2020) provided a test dataset for the locations of general practitioners (GPs); (2) OpenStreetMap (OSM) data is utilized for road networks; and (3) the Statistische Ämter des Bundes und der Länder (German official census 2011) provided a population distribution dataset stemming from the 2011 Census.

RESULTS

The spatial accessibility indices are distributed in an inhomogeneous as well as polycentric pattern for the general practitioners (GPs). Differences in spatial accessibility are found mainly between urban and rural areas. The transitions from lower to higher values of accessibility or vice versa in general are smooth rather than abrupt. The results indicate that the MH3SFCA method is suited for comparing the spatial accessibility of GPs in different regions. The results of the MH3SFCA method can be used to indicate over- and undersupplied areas. However, the absolute values of the indices do not inherently define accessibility to be too low or too high. Instead, the indices compare the spatial relationships between each supply and demand location. As a result, the higher the value of the accessibility indices, the higher the opportunities for the respective population locations. The result for the study area are exemplary as the test input data has a high uncertainty. Depending on the objective, it might be necessary to further analyze the results of the method.

CONCLUSIONS

The application of the MH3SFCA method on small-scale data can provide an overview of accessibility for the whole study area. As many factors have to be taken into account, the outcomes are too complex for a direct and clear interpretation of why indices are low or high. The MH3SFCA method can be used to detect differences in accessibility on a small scale. In order to effectively detect over- or undersupply, further analysis must be conducted and/or different (legal) constraints must be applied. The methodology requires input data of high quality.

Geographical accessibility and spatial coverage modelling of public health care network in rural and remote India

Background

Long distances to facilities, topographical constraints, inadequate service capacity of institutions and insufficient/ rudimentary road & transportation network culminate into unprecedented barriers to access. These barriers gets exacerbated in presence of external factors like conflict and political disruptions. Thus, this study was conducted in rural, remote and fragile region in India measuring geographical accessibility and modelling spatial coverage of public healthcare network.

Methods

Vector and raster based approaches were used to discern accessibility for various packages of service delivery. Alternative scenarios derived from local experiences were modelled using health facility, population and ancillary data. Based on that, a raster surface of travel time between facilities and population was developed by incorporating terrain, physical barriers, topography and travelling modes and speeds through various land-cover classes. Concomitantly, spatial coverage was modelled to delineate catchment areas. Further, underserved population and zonal statistics were assessed in an interactive modelling approach to ascertain spatial relationship between population, travel time and zonal boundaries. Finally, raster surface of travel time was re-modelled for the conflict situation in villages vulnerable to obstruction of access due to disturbed security scenario.

Results

Euclidean buffers revealed 11% villages without ambulatory & immunization care within 2 km radius. Similarly, for 5 km radius, 11% and 12% villages were bereft of delivery and inpatient care. Travel time accessibility analysis divulged walking scenario exhibiting lowest level of accessibility. Enabling motorized travel improved accessibility measures, with highest degree of accessibility for privately owned vehicle (motorcycle and cars). Differential results were found between packages of services where ambulatory & immunization care was relatively accessible by walking; whereas, delivery and inpatient care had a staggering average of three hours walking time. Even with best scenario, around 2/3rd population remained unserved for all package of services. Moreover, 90% villages in conflict zone grapples with inaccessibility when the scenario of heightened border tensions was considered.

Conclusions

Our study demonstrated the application of GIS technique to facilitate evidence backed planning at granular level. Regardless of the scenario, the analysis divulged inaccessibility to delivery and inpatient care to be most pronounced and majority of population to be unserved. It was suggested to have concerted efforts to bolster already existing facilities and adapt systems approach to exploit synergies of inter-sectoral development.

Disparities in Geographical Access to Hospitals in Portugal

Geographical accessibility to health care services is widely accepted as relevant to improve population health. However, measuring it is very complex, mainly when applied at administrative levels that go beyond the small-area level. This is the case in Portugal, where the municipality is the administrative level that is most appropriate for implementing policies to improve the access to those services. The aim of this paper is to assess whether inequalities in terms of access to a hospital in Portugal have improved over the last 20 years. A population-weighted driving time was applied using the census tract population, the roads network, the reference hospitals’ catchment area and the municipality boundaries. The results show that municipalities are 25 min away from the hospital—3 min less than in 1991—and that there is an association with premature mortality, elderly population and population density. However, disparities between municipalities are still huge. Municipalities with higher rates of older populations, isolated communities or those located closer to the border with Spain face harder challenges and require greater attention from local administration. Since municipalities now have responsibilities for health, it is important they implement interventions at the local level to tackle disparities impacting access to healthcare.

Capturing modelled and perceived spatial access to ambulatory health care services in rural and urban areas in Germany

Studies on social and regional inequalities in access to health care often use spatial indicators such as physician density to measure access to health care. However, the concept of access is more complex, comprising, among others, patient perceptions. In this study, we evaluate the association between different spatial measures of access (i.e. physician density, distance to the nearest provider, and measures based on floating catchment area methods) and measures of perceived spatial access to ambulatory health care in rural and urban areas in Germany. Using correlation and regression analysis, we found that the significance and strength of the relation between perceived and modelled spatial access depends on the type of area and the physician group. The distance to the nearest physician is associated with perceived spatial access to GPs only in rural areas but not in urban areas. More sophisticated measures of spatial access seem not to explain perceived access better than the simpler indicators.

Spatial inequalities in skilled attendance at birth in Ghana: a multilevel analysis integrating health facility databases with household survey data

Objective

This study aimed at using survey data to predict skilled attendance at birth (SBA) across Ghana from healthcare quality and health facility accessibility.

Methods

Through a cross-sectional, observational study, we used a random intercept mixed effects multilevel logistic modelling approach to estimate the odds of having SBA and then applied model estimates to spatial layers to assess the probability of SBA at high-spatial resolution across Ghana. We combined data from the Demographic and Health Survey (DHS), routine birth registers, a service provision assessment of emergency obstetric care services, gridded population estimates and modelled travel time to health facilities.

Results

Within an hour’s travel, 97.1% of women sampled in the DHS could access any health facility, 96.6% could reach a facility providing birthing services, and 86.2% could reach a secondary hospital. After controlling for characteristics of individual women, living in an urban area and close proximity to a health facility with high-quality services were significant positive determinants of SBA uptake. The estimated variance suggests significant effects of cluster and region on SBA as 7.1% of the residual variation in the propensity to use SBA is attributed to unobserved regional characteristics and 16.5% between clusters within regions.

Conclusion

Given the expansion of primary care facilities in Ghana, this study suggests that higher quality healthcare services, as opposed to closer proximity of facilities to women, is needed to widen SBA uptake and improve maternal health.

Measuring Accessibility to Various ASFs from Public Transit using Spatial Distance Measures in Indian Cities

Nowadays, accessibility to facilities is one of the most discussed issues in sustainable urban planning. In the current research, two spatial distance accessibility measures were applied to evaluate the accessibility to amenities, services, and facilities (ASFs) from public transit (PT) by walking distance in six Indian cities. The first stage accounts for distance measures using the Euclidean distance with a new methodical approach derived from the built-up area with a spatial resolution of 30 m from Landsat data, and for the network distance method, the actual road distances using OpenStreetMap (OSM) for different threshold ranges of distances were derived. Meanwhile, in the second stage, indicators such as built-up area, network connectivity, and network density with the percentage of ASFs are evaluated and combined for normalization process for ranking the city. The present study assesses the accessibility to various ASFs from PT at city level and explores whether the actual road network access (by measuring distance) in Indian cities is contributing to a high level of accessibility. It adopts a unique approach using statistical tools while assessing both Euclidean and network distances. It models a framework for overall benchmarking in all six cities by ranking them for their accessibility. The results show various scenarios in terms of the rank of cities, which had been strongly affected by distance metrics (Euclidean vs. network) and thus emphasize the careful use of these measures as supporting tools for planning. This facilitates the identification of the local barriers and problems with network access that affect the actual distance. This unique approach can help policymakers to identify the gaps in PT coverage for reaching ASFs. Furthermore, it helps in crucial implementation by strategic planning that can be achieved using these distance criteria.

Spatial distribution of gambling exposure and vulnerability: an ecological tool to support health inequality reduction

OBJECTIVES

Recent research by Public Health has redefined harmful gambling, shifting the focus from problematic people with irresponsible behaviour to 'gamblogenic' environments. The aim of this research was to support this alternative perspective with concrete ecological tools for characterizing harmful environments. Studies that analyse the spatial distribution of gambling show that people living in the most disadvantaged areas have greater access to gambling and are more affected by the harms of gambling. Despite their quality methodology and usefulness, the scope of geographic access measures has been partially limited. These measures have been mostly structured around a single form of gambling, focus on only one dimension of accessibility (density or proximity) and few of them take into account the risks associated with each type of the game. The main goal of our research was to propose an innovative method to characterize gambling environments in Quebec and address social inequality with respect to gambling exposure. This article more specifically describes the method we used to address the aforementioned shortcomings by developing the gambling exposure index (GEI), a more comprehensive ecological index of all games-weighted by their relative level of risk-to which populations are exposed.

STUDY DESIGN

The study design is a cross-sectional ecological study.

METHODS

The methodological approach was carried out in three stages. A GEI was operationalized and is composed of three dimensions: A dimension of spatial accessibility to gambling sites, a dimension of density of gambling places and a dimension of relative risk associated with different types of game. The two-step floating catchment area (2SFCA) method was used to combine these three dimensions into an overall GEI index. Data were retrieved from a geocoded directory of all gambling sites from Loto-Québec and other commercial databases. The relative risk of each type of game has been expressed by prevalence rates for those specific games in a Quebec population prevalence survey. A vulnerability to gambling index (VGI) was produced based on 6 socio-economic proxies of problem gambling from the 2016 Canadian census. The six variables were weighted and aggregated at the dissemination area (DA) level. Spatial and descriptive statistical analyses were conducted to explore the relationship between VGI and GEI and to identify areas that are highly vulnerable and have a high gambling exposure.

RESULTS

The findings of our analysis reveal widespread geographic exposure to gambling and a significant positive linear relationship between the GEI and the VGI. In many areas, increased accessibility to gambling is significantly associated with a higher vulnerability to gambling. Our findings demonstrate that in 1328 DAs in Quebec, there is a particularly unequal and potentially harmful geographical distribution of gambling, exposing 9% of the population which are theoretically vulnerable to gambling to an increased presence of gambling.

CONCLUSION

This research applied a spatial analytical approach to assess the association between environments, gambling and vulnerability. The GEI and VGI at the DA level can serve as a monitoring tool for policy-makers regarding gambling exposure in the most vulnerable sectors and contribute to prevention and intervention strategies better adapted to the population. The general findings raise the ethical implications of increased marketing development in vulnerable neighbourhoods. As the GEI takes into account both the environmental determinants and the relative risk of games, it is in contributing to the shift in public and scientific discourse, redefining the subject from problematic people to problematic games and environments.

A Review of Models Used for Investigating Barriers to Healthcare Access in Australia

Understanding barriers to healthcare access is a multifaceted challenge, which is often highly diverse depending on location and the prevalent surroundings. The barriers can range from transport accessibility to socio-economic conditions, ethnicity and various patient characteristics. Australia has one of the best healthcare systems in the world; however, there are several concerns surrounding its accessibility, primarily due to the vast geographical area it encompasses. This review study is an attempt to understand the various modeling approaches used by researchers to analyze diverse barriers related to specific disease types and the various areal distributions in the country. In terms of barriers, the most affected people are those living in rural and remote parts, and the situation is even worse for indigenous people. These models have mostly focused on the use of statistical models and spatial modeling. The review reveals that most of the focus has been on cancer-related studies and understanding accessibility among the rural and urban population. Future work should focus on further categorizing the population based on indigeneity, migration status and the use of advanced computational models. This article should not be considered an exhaustive review of every aspect as each section deserves a separate review of its own. However, it highlights all the key points, covered under several facets which can be used by researchers and policymakers to understand the current limitations and the steps that need to be taken to improve health accessibility.

Development of a Method to Locate Deserts and Food Swamps Following the Experience of a Region in Quebec, Canada

Unhealthy eating and food insecurity are recognized risk factors for chronic diseases. Collective and environmental factors, such as geographic access to food condition food choices. The objective of this study was to map food deserts and food swamps in Gaspesie, a region of Quebec (Canada), using geographical information systems (GIS) and field validation. Eleven sectors (5 rural and 6 urban) where 5% of the Gaspesie population lives were considered food deserts. Eight sectors (all rural) constituting 4.5% of the population were considered food swamps. Nearly 88% (3/8) of food swamps were located in disadvantaged and very disadvantaged areas. The Gaspesie region is already actively involved in changing environments to make them conducive to healthy eating for all. The mapping of food deserts can support intersectoral collaboration on food security. Food swamp mapping will make it possible to more accurately characterize the existing food environment in the region. Both indicators will be useful in raising awareness and mobilizing partners for a comprehensive strategy to improve the food environment that is not only based on the food desert indicator alone but also takes into account the presence of food swamps.

Socioeconomic And Survival Differences Among Minorities With Hepatocellular Carcinoma In Florida

Background

Disparities in hepatocellular carcinoma (HCC) have been partly attributed to low socioeconomic status among minorities. We investigated associations between race, socioeconomic characteristics, geographic characteristics and survival in HCC patients in Florida.

Methods

Using the Florida Cancer Data System (FCDS), we analyzed HCC cases diagnosed between 1/1/2004 and 12/31/2013. To ascertain population-level socioeconomic characteristics, we linked FCDS to the 2010–2014 US Census American Community Survey and the 2013 Florida Behavioral Risk Factor Surveillance System. We also estimated patient distance to liver transplant and academic cancer centers. Using Cox proportional hazards, we modeled the association between race and survival.

Results

Of 10,852 patients, 13.1% were Black, 67.1% White, 15.7% Hispanic, and 3.2% Asian. At diagnosis, Blacks were younger with more extensive disease, p <0.001. Transplants were performed in 9.3% of Hispanics, 7.5% of Whites, 5.8% of Asians and 4.2% of Blacks, p <0.001. Median survival was longest in Hispanics and shortest in Blacks, p<0.001 When adjusted for gender, age, payer, SEER stage, surgery type, and receipt of treatment, Blacks had a 17% increased risk of death [hazard ratio (HR) 1.17, 95% confidence interval (CI) 1.07–1.29] and Whites a 9% increased risk of death [HR 1.09, 95% CI 1.02–1.17] compared to Hispanics. As a group, Hispanics lived closest to any transplant or academic cancer center, p <0.001. Neighborhood poverty level was highest where Hispanic patients lived, p <0.001.

Conclusion

Though socioeconomic differences may contribute to disparities, Hispanics survived longer than Blacks and Whites in Florida despite living in the most socioeconomically depressed neighborhoods. Increased access to transplant likely contributed to improved survival. Additional research is needed to identify which individual socioeconomic and geographic determinants contribute most to disparities.

Industrial Sprawl and Residential Housing: Exploring the Interplay between Local Development and Land-Use Change in the Valencian Community, Spain

Urbanization in Mediterranean Europe has occurred in recent decades with expansion of residential, commercial and industrial settlements into rural landscapes outside the traditional metropolitan boundaries. Industrial expansion in peri-urban contexts was particularly intense in Southern Europe. Based on these premises, this work investigates residential and industrial settlement dynamics in the Valencian Community, Spain, between 2005 and 2015, with the aim to clarify the role of industrial expansion in total urban growth in a paradigmatic Mediterranean region. Since the early 1990s, the Valencian industrial sector developed in correspondence with already established industrial nodes, altering the surrounding rural landscape. Six variables (urban hierarchy, discontinuous settlements, pristine land under urban expansion, isolated industrial settlements, within- and out-of-plan industrial areas) were considered with the aim at exploring land-use change. Empirical results indicate a role of industrial development in pushing urban sprawl in coastal Valencia. A reflection on the distinctive evolution of residential and industrial settlements is essential for designing new planning measures for sustainable land management and containment of urban sprawl in Southern Europe. A comparative analysis of different alternatives of urban development based on quantitative assessment of land-use change provides guidelines for local development and ecological sustainability.

Analysis of the geographical accessibility of vape shops in the vicinity of Quebec's secondary and college educational institutions

INTRODUCTION

significant proportion of secondary school students and young adults in Quebec have experimented with electronic cigarettes (e-cigarettes). Both personal and environmental factors have been associated with the use of vaping products by youth. Geographical accessibility to the points of sale of these products may be one of these factors. The purpose of this study is to develop a profile of the spatial distribution of stores specializing in the sale of vaping products (vape shops) in the vicinity of secondary schools, colleges and CEGEPs in the province of Quebec.

METHODS

We calculated the accessibility of businesses to account for geographical exposure. Analyses were conducted to provide a snapshot of the situation in Quebec and to identify associations between the characteristics of educational institutions and geographical accessibility to vape shops.

RESULTS

A total of 299 vape shops were identified. Colleges are closer to a vape shop (median distance: 1.2 km) than are secondary schools (median distance: 2.3 km). Large private colleges located in urban areas are closer to specialized vape shops. Medium or large private secondary schools located in urban and more advantaged areas are also closer to a specialized vape shop.

CONCLUSION

This study is a step in developing an understanding of the location of vaping product shops and their geographical accessibility to young people. Important to consider is the geographical accessibility of young people to non-specialized shops that also sell e-cigarettes and then any potential connections between geographical accessibility to such non-specialized shops and the use of vaping products by young people.

A spatial analysis to evaluate the impact of deregulation policies in the pharmacy sector: Evidence from the case of Navarre

Community pharmacies represent unusual enterprises as their main function is intrinsically related to the provision of healthcare services. Hence, market competition in this sector needs to be regulated, in order to ensure equitable accessibility, efficiency and quality of services. However, recently a general deregulation trend may be observed in Europe. In this paper, we focus on location restrictions, i.e. on demographic and geographic constraints to open new pharmacies, and we evaluate the impact of their relaxation. In particular, we analyze the case of the city of Pamplona (ES), where a striking increase in the number of pharmacies occurred, after the introduction of a new regulatory system in 2000. We evaluate, thanks to an in-depth spatial analysis, the evolution of the system to date and the effects produced on the consumers, in terms of accessibility, and on the competitors, in terms of market shares distribution. By comparing the obtained results with the ones related to the case of a second Spanish city, characterized by more strict restrictions, it emerges that the deregulation risks to produce a limited improvement in terms of accessibility and to exacerbate differences among consumers. Moreover, an increasing number of competitors does not necessarily imply a more equitable distribution of market shares, thus putting at risk the desired effects in terms of cost reduction and service quality improvement.

Methodology for building a geographical accessibility health index throughout metropolitan France

Spatial accessibility to health services is a key factor in terms of public health. Even though some tools are available, establishing accessibility criteria applicable from one geographic scale to another remains difficult. Therefore, we propose a method for creating a health accessibility index applicable on a large geographic scale, based on a methodology that overcomes the limitations of political-administrative divisions and which allows a multi-scalar approach to be implemented. The index highlights, on a national scale, areas of cumulative health disadvantages. This index of accessibility to health care combines accessibility and availability and can be adapted to many geographical scales. As accessibility can be understood in various dimensions, a score could be calculated for various fields such as education and culture. The index can help policymakers to identify under-endowed areas and find optimal locations. In terms of public health, it may be used to understand the mechanisms underlying geographic health disparities.

Demand and level of service inflation in Floating Catchment Area (FCA) methods

Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results.

[Proposal for a methodology to estimate the potential coverage of primary care teamsPropuesta de una metodología para estimar el área de cobertura potencial de los equipos de atención primaria]

OBJECTIVE

To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas.

METHODS

In this methodological study, potential areas were constructed by combinatorial analysis between census tracts and the location of basic health units with working PHC teams in Brazil. Six rules were used to parameterize the algorithm for the construction of potential areas. Thus, six restrictions were applied to enable the model: the selection of census tracts near the basic health unit; contiguous sectors; mutually exclusive sectors; sectors located in the same municipality of basic health units; sum of 4 500 users per health team in each unit; and volume of population ascribed proportional to the number of PHC teams allocated to the unit. Based on 316 594 census tracts and 39 758 basic health units, a neighborhood matrix was developed. To that matrix, a graph algorithm was applied to test combinations of sectors that simultaneously met the stipulated rules.

RESULTS

A total of 1 901 114 arcs were defined, connecting 30 351 census tracts, allowing the construction of 26 907 potential areas. Based on these results, intra-municipal analyses can be performed to monitor PHC indicators. Customizable algorithm parameters can be adjusted to accommodate different sets of rules which may be adapted to different countries.

CONCLUSIONS

The use of geoprocessing approaches creates conditions for the assessment of PHC impact, based on secondary databases at various levels, such as intra-municipal, basic health unit, and even at the team level.

Assessing Spatial Accessibility to Hierarchical Urban Parks by Multi-Types of Travel Distance in Shenzhen, China

Urban green spaces play a critical role in public health and human wellbeing for urban residents. Due to the uneven spatial distribution of urban green spaces in most of cities, the issue of the disparity between supply and demand has aroused public concern. In a case of Shenzhen, a modified Gaussian-based two-step floating catchment area (2SFCA) method is adopted to evaluate the disparity between park provision and the demanders in terms of accessibility at hierarchical levels under four types of distance (e.g., Euclidean distance, walking distance, bicycling distance, and driving distance), which is well aligned with hierarchical systems in urban green spaces in urban planning practice. By contrast and correlation analysis, among the four types of distance, the statistical correlations are relatively high between Euclidean distance and the other three. Nonetheless, the pattern of spatial accessibility under different type of travel distance is apparently variant. Accessibility calculated by Euclidean distance is overestimated relative to that of the other three, while the pattern of walking distance and bicycling distance is similar to each other. The choice of type of distance is worthy of caution when evaluating spatial accessibility by 2SFCA method. Results show that the accessibility to parks at all hierarchical levels is high particularly, particularly at the natural level. However, the disparity between the supply and demand is significant. The percentage of communities that have high population density but low park accessibility is over 40% (equivalent to approximately 55% of the population). The finding may provide implications on access to urban greens paces for urban planners and authorities to develop effective planning strategies.

The Provision and Accessibility to Parks in Ho Chi Minh City: Disparities along the Urban Core—Periphery Axis

In Ho Chi Minh City (HCMC, Vietnam), there is now an urgent need for evaluating access to parks in an effort to ensure better planning within the context of rapid and increasingly privatized urbanization. In this article, we analyze the provision and accessibility to parks in HCMC. To achieve this, the information gathered was then integrated into the geographical information systems (GISs). Based on an Ascending Hierarchical Classification, we were able to identify five different types ranging in their intrinsic characteristics. The accessibility measurements calculated in the GISs show that communities are located an average of at least 879 meters away from parks, which is a relatively short distance. Children have a level of accessibility comparable to that of the overall population. Accessibility also seems to vary greatly throughout the City—populations residing in central districts (planned before 1996) enjoy better accessibility compared to those in peripheral neighborhoods (planned after 1996). Parks located in areas planned between 1996 and 2002 are the least accessible, followed by parks in areas planned after 2003. Our findings suggest possible approaches that could be used to help ensure the quality of parks and their spatial accessibility.