The association between neighborhood obesogenic factors and prostate cancer risk and mortality: the Southern Community Cohort Study.

Background: Prostate cancer is one of the leading causes of cancer-related mortality among men in the United States. We examined the role of neighborhood obesogenic attributes on prostate cancer risk and mortality in the Southern Community Cohort Study (SCCS). Methods: From the total of 34,166 SCCS male participants, 28,356 were included in the analysis. We assessed the relationship between neighborhood obesogenic factors [neighborhood socioeconomic status (nSES) and neighborhood obesogenic environment indices including the restaurant environment index, the retail food environment index, parks, recreational facilities, and businesses] and prostate cancer risk and mortality by controlling for individual-level factors using a multivariable Cox proportional hazards model. We further stratified prostate cancer risk analysis by race and body mass index (BMI). Results: Median follow-up time was 133 months [interquartile range (IQR): 103, 152], and the mean age was 51.62 (SD: ± 8.42) years. There were 1,524 (5.37%) prostate cancer diagnoses and 98 (6.43%) prostate cancer deaths during follow-up. Compared to participants residing in the wealthiest quintile, those residing in the poorest quintile had a higher risk of prostate cancer (aHR = 1.32, 95% CI 1.12-1.57, p = 0.001), particularly among non-obese men with a BMI < 30 (aHR = 1.46, 95% CI 1.07-1.98, p = 0.016). The restaurant environment index was associated with a higher prostate cancer risk in overweight (BMI ≥ 25) White men (aHR = 3.37, 95% CI 1.04-10.94, p = 0.043, quintile 1 vs. None). Obese Black individuals without any neighborhood recreational facilities had a 42% higher risk (aHR = 1.42, 95% CI 1.04-1.94, p = 0.026) compared to those with any access. Compared to residents in the wealthiest quintile and most walkable area, those residing within the poorest quintile (aHR = 3.43, 95% CI 1.54-7.64, p = 0.003) or the least walkable area (aHR = 3.45, 95% CI 1.22-9.78, p = 0.020) had a higher risk of prostate cancer death. Conclusion: Living in a lower-nSES area was associated with a higher prostate cancer risk, particularly among Black men. Restaurant and retail food environment indices were also associated with a higher prostate cancer risk, with stronger associations within overweight White individuals. Finally, residing in a low-SES neighborhood or the least walkable areas were associated with a higher risk of prostate cancer mortality.

Enhancing Health Care Accessibility and Equity Through a Geoprocessing Toolbox for Spatial Accessibility Analysis: Development and Case Study.

BACKGROUND: Access to health care services is a critical determinant of population health and well-being. Measuring spatial accessibility to health services is essential for understanding health care distribution and addressing potential inequities. OBJECTIVE: In this study, we developed a geoprocessing toolbox including Python script tools for the ArcGIS Pro environment to measure the spatial accessibility of health services using both classic and enhanced versions of the 2-step floating catchment area method. METHODS: Each of our tools incorporated both distance buffers and travel time catchments to calculate accessibility scores based on users' choices. Additionally, we developed a separate tool to create travel time catchments that is compatible with both locally available network data sets and ArcGIS Online data sources. We conducted a case study focusing on the accessibility of hemodialysis services in the state of Tennessee using the 4 versions of the accessibility tools. Notably, the calculation of the target population considered age as a significant nonspatial factor influencing hemodialysis service accessibility. Weighted populations were calculated using end-stage renal disease incidence rates in different age groups. RESULTS: The implemented tools are made accessible through ArcGIS Online for free use by the research community. The case study revealed disparities in the accessibility of hemodialysis services, with urban areas demonstrating higher scores compared to rural and suburban regions. CONCLUSIONS: These geoprocessing tools can serve as valuable decision-support resources for health care providers, organizations, and policy makers to improve equitable access to health care services. This comprehensive approach to measuring spatial accessibility can empower health care stakeholders to address health care distribution challenges effectively.

Towards an Explainable AI Platform to Study Interruptions in Cancer Radiation Therapy.

Radiation therapy interruptions drive cancer treatment failures; they represent an untapped opportunity for improving outcomes and narrowing treatment disparities. This research reports on the early development of the X-CART platform, which uses explainable AI to model cancer treatment outcome metrics based on high-dimensional associations with our local social determinants of health dataset to identify and explain causal pathways linking social disadvantage with increased radiation therapy interruptions.

Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data.

This study integrates geographical information systems (GIS) with a mathematical optimization technique to enhance emergency medical services (EMS) coverage in a county in the northeast of Iran. EMS demand locations were determined through one-year EMS call data analysis. We formulated a maximal covering location problem (MCLP) as a mixed-integer linear programming model with a capacity threshold for vehicles using the CPLEX optimizer, an optimization software package from IBM. To ensure applicability to the EMS setting, we incorporated a constraint that maintains an acceptable level of service for all EMS calls. Specifically, we implemented two scenarios: a relocation model for existing ambulances and an allocation model for new ambulances, both using a list of candidate locations. The relocation model increased the proportion of calls within the 5-minute coverage standard from 69% to 75%. With the allocation model, we found that the coverage proportion could rise to 84% of total calls by adding ten vehicles and eight new stations. The incorporation of GIS techniques into optimization modelling holds promise for the efficient management of scarce healthcare resources, particularly in situations where time is of the essence.

Predictors of in-hospital mortality among patients with symptoms of stroke, Mashhad, Iran: an application of auto-logistic regression model.

BACKGROUND: Stroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to emergency medical services (EMS). Moreover, transport delays have been documented to affect stroke outcomes. This study aimed to examine the spatial variations in in-hospital mortality among patients with symptoms of stroke transferred by EMS, and determine its related factors using the auto-logistic regression model. METHODS: In this historical cohort study, we included patients with symptoms of stroke transferred to Ghaem Hospital of Mashhad, as the referral center for stroke patients, from April 2018 to March 2019. The auto-logistic regression model was applied to examine the possible geographical variations of in-hospital mortality and its related factors. All analysis was performed using the Statistical Package for the Social Sciences (SPSS, v. 16) and R 4.0.0 software at the significance level of 0.05. RESULTS: In this study, a total of 1,170 patients with stroke symptoms were included. The overall mortality rate in the hospital was 14.2% and there was an uneven geographical distribution. The results of auto-logistic regression model showed that in-hospital stroke mortality was associated with age (OR = 1.03, 95% CI: 1.01-1.04), accessibility rate of ambulance vehicle (OR = 0.97, 95% CI: 0.94-0.99), final stroke diagnosis (OR = 1.60, 95% CI: 1.07-2.39), triage level (OR = 2.11, 95% CI: 1.31-3.54), and length of stay (LOS) in hospital (OR = 1.02, 95% CI: 1.01-1.04). CONCLUSION: Our results showed considerable geographical variations in the odds of in-hospital stroke mortality in Mashhad neighborhoods. Also, the age- and sex-adjusted results highlighted the direct association between such variables as accessibility rate of an ambulance, screening time, and LOS in hospital with in-hospital stroke mortality. Thus, the prognosis of in-hospital stroke mortality could be improved by reducing delay time and increasing the EMS access rate.

A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran.

BACKGROUND: Despite significant advances in the quality and delivery of specialized stroke care, there still persist remarkable spatial variations in emergency medical services (EMS) transport delays, stroke incidence, and its outcomes. Therefore, it is very important to investigate the possible geographical variations of in-hospital stroke mortality and to identify its associated factors. METHODS: This historical cohort study included suspected stroke cases transferred to Ghaem Hospital of Mashhad by the EMS from March 2018 to March 2019. Using emergency mission IDs, the pre-hospital emergency data were integrated with the patient medical records in the hospital. We used the Bayesian approach for estimating the model parameters. RESULTS: Out of 301 patients (142 (47.2%) females vs. 159 (52.8%) males) with a final diagnosis of stroke, 61 (20.3%) cases had in-hospital mortality. Results from Bayesian spatial log-logistic proportional odds (PO) model showed that age (PO=1.07), access rate to EMS (PO=0.78), arrival time (evening shift vs. day shift, PO=0.09), and sequelae variables (PO=9.20) had a significant association with the odds of in-hospital stroke mortality (P<0.05). Furthermore, the odds of in-hospital stroke mortality were higher in central urban areas compared to suburban areas. CONCLUSION: Marked regional variations were found in the odds of in-hospital stroke mortality in Mashhad. There was a direct association between age and odds of in-hospital stroke mortality. Hence, the prognosis of in-hospital stroke mortality could be improved by better control of hypertension, prevention of the occurrence of sequelae, increasing the access rate to EMS, and optimizing shift work schedule.

Geospatial epidemiology of hospitalized patients with a positive influenza assay: A nationwide study in Iran, 2016-2018.

INTRODUCTION: Seasonal influenza is a significant public health challenge worldwide. This study aimed to investigate the epidemiological characteristics and spatial patterns of severe hospitalized influenza cases confirmed by polymerase chain reaction (PCR) in Iran. METHODS: Data were obtained from Iran's Ministry of Health and Medical Education and included all hospitalized lab-confirmed influenza cases from January 1, 2016, to December 30, 2018 (n = 9146). The Getis-Ord Gi* and Local Moran's I statistics were used to explore the hotspot areas and spatial cluster/outlier patterns of influenza. We also built a multivariable logistic regression model to identify covariates associated with patients' mortality. RESULTS: Cumulative incidence and mortality rate were estimated at 11.44 and 0.49 (per 100,000), respectively, and case fatality rate was estimated at 4.35%. The patients' median age was 40 (interquartile range: 22-63), and 55.5% (n = 5073) were female. The hotspot and cluster analyses revealed high-risk areas in northern parts of Iran, especially in cold, humid, and densely populated areas. Moreover, influenza hotspots were more common during the colder months of the year, especially in high-elevated regions. Mortality was significantly associated with older age (adjusted odds ratio [aOR]: 1.01, 95% confidence interval [CI]: 1.01-1.02), infection with virus type-A (aOR: 1.64, 95% CI: 1.27-2.15), male sex (aOR: 1.77, 95% CI: 1.44-2.18), cardiovascular disease (aOR: 1.71, 95% CI: 1.33-2.20), chronic obstructive pulmonary disease (aOR: 1.82, 95% CI: 1.40-2.34), malignancy (aOR: 4.77, 95% CI: 2.87-7.62), and grade-II obesity (aOR: 2.11, 95% CI: 1.09-3.74). CONCLUSIONS: We characterized the spatial and epidemiological heterogeneities of severe hospitalized influenza cases confirmed by PCR in Iran. Detecting influenza hotspot clusters could inform prioritization and geographic specificity of influenza prevention, testing, and mitigation resource management, including vaccination planning in Iran.

Mortality due to noninfectious lower respiratory diseases: A spatiotemporal, cross-sectional study.

Background and Aims: Geography plays an important role in the incidence of respiratory diseases. The aim of this study was to investigate the epidemiology and geographical distribution of death due to noninfectious lower respiratory diseases (NILRDs). Methods: Data related to all death due to NILRD in Kerman Province between 2012 and 2018 were extracted from the National Mortality Registry. The underlying causes of death were extracted from the registry based on the assigned codes from ICD-10 (International Classification of Diseases 10th Revision) classification. The existence of spatial clusters and outliers was evaluated using local indicators of spatial association statistics. Results: The frequency of death due to NILRD was 8005 persons during the 7 years of the study. The main cause of death was chronic lower respiratory disease (54.2%). Other causes of death were, respectively, lung diseases due to external agents (1.09%), other respiratory diseases mainly affecting the interstitium (1.16%), other diseases of pleura (0.57%), and other diseases of the respiratory system (42.13%). The age- and sex-adjusted mortality rates due to NILRD in the north and center of the province increased significantly from 2012 to 2018. Also, the results of cluster analysis identified northern regions as the clustered areas of NILRD. Conclusions: Our findings showed a significant increase in mortality due to NILRD in Kerman Province during the 7 years of the study. To reduce this type of death, health policymakers should have environmental health plans and basic solutions, such as a warning system to reduce the commuting on highly air-polluted days and to control pollutants, especially in the industrial areas of the north of this province.

Access to the COVID-19 services during the pandemic - a scoping review.

Appropriate accessibility to coronavirus disease 2019 (COVID-19) services is essential in the efficient management of the pandemic. Different geospatial methods and approaches have been used to measure accessibility to COVID-19 health-related services. This scoping review aimed to summarize and synthesize the geospatial studies conducted to measure accessibility to COVID-19 healthcare services. Web of Science, Scopus, and PubMed were searched to find relevant studies. From 1113 retrieved unique citations, 26 articles were selected to be reviewed. Most of the studies were conducted in the USA and floating catchment area methods were mostly used to measure the spatial accessibility to COVID-19 services including vaccination centres, Intensive Care Unit beds, hospitals and test sites. More attention is needed to measure the accessibility of COVID-19 services to different types of users especially with combining different non-spatial factors which could lead to better allocation of resources especially in populations with limited resources.

One-year spatiotemporal database of Emergency Medical Service (EMS) calls in Mashhad, Iran: data on 224,355 EMS calls.

OBJECTIVES: Emergency Medical Services (EMS) is the first point of service for the people who are in critical condition and in need of urgent health care. In Iran, as in other countries, people in need of emergency services often die or are left with a permanent injury due to the poor EMS-related infrastructure. It has been shown that a detailed examination of the response times and the spatiotemporal pattern of EMS calls for service can lead to improvements in time-sensitive patient outcomes. We performed a spatiotemporal study in city of Mashhad, the second-most populous city of Iran, to investigate the pattern of the EMS calls and now wish to release a comprehensive dataset resulting from this study. DATA DESCRIPTION: The data include three data files plus a data dictionary file. Data file 1 contains the characteristics of EMS requests including sex, age group, date of call, different time periods of each EMS missions, the census tracts' ID of callers, the chief complaint, and the EMS mission result. Two spatial data files include the boundaries of the census tracts in Mashhad and the point location of all EMS stations, respectively. A data dictionary file defines all fields and values across the data files.

Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach.

Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disaster. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, particularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clusters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.

Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018.

BACKGROUND: Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. METHODS: This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran's I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. RESULTS: The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19-13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65-11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010-2014 and 2017-2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. CONCLUSION: The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008-2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

Evaluation of zoonotic platyhelminthe infections identified in slaughtered livestock in Iran, 2015-2019.

BACKGROUND: Platyhelminth infections of livestock can result in considerable economic losses. This study aims to evaluate the spatial frequency of cystic echinococcosis (CE), dicrocoeliasis, and fascioliasis in livestock slaughtered in Iran during the years 2015-2019 and estimate direct costs associated with organ condemnation due to these parasites. METHODS: Abattoir data from 413 abattoirs representing all 31 Iranian provinces were collected from the Iran Veterinary Organization. Infection prevalence was calculated per year at the province level. The Local Moran's I statistic was performed to evaluate spatial autocorrelation of animals positive at slaughter for the years 2015-2019. Direct costs associated with condemned livers were calculated for each parasitic condition, with costs associated with condemned lungs also included for CE. RESULTS: Overall prevalence values for the study timeframe were as follows: sheep and goat fascioliasis 1.56% (95% CI: 1.56-1.56%), cattle fascioliasis 3.86% (95% CI: 3.85-3.88%), sheep and goat dicrocoeliasis 4.63% (95% CI: 4.62-4.63%), cattle dicrocoeliasis 3.08% (95% CI: 3.07-3.09%), sheep and goat CE 5.32% (95% CI: 5.32-5.33%), and cattle CE 7.26% (95% CI: 7.24-7.28%). Northwest Iran had the highest prevalence of CE and fascioliasis. High infection areas for Dicrocoelium spp. included the provinces of Zanjan, Gilan, Qazvin, and Tehran, which are located in northern Iran. Direct economic losses for sheep and goat fascioliasis, dicrocoeliasis, and CE for the study period were US$13,842,759, US$41,771,377, and US$22,801,054, respectively. Direct economic losses for cattle fascioliasis, dicrocoeliasis, and CE for the study period were US$1,989,200, US$1,668,986, and US$2,656,568, respectively. CONCLUSION: Our findings provide valuable data for future monitoring of these important parasitic diseases in Iranian livestock. Disease control strategies are required to reduce the economic and public health impact of these platyhelminths.

Use of geographical information systems in multiple sclerosis research: A systematic scoping review.

INTRODUCTION: Geographical information system (GIS) and spatial analysis have an emerging role in the understanding and management of health-related outcomes. However, there is a knowledge gap about the extent to which GIS has supported multiple Sclerosis (MS) research. Therefore, this review aimed to explore the types of GIS applications and the complexity of their visualisation in MS research. METHODS: A systematic scoping review was conducted based on York's five-stage framework. PubMed, Scopus and Web of Science were searched for relevant studies published between 2000 and 2020 using a comprehensive search strategy based on the main concepts related to GIS and MS. Grounded, inductive analysis was conducted to organize studies into meaningful application areas. Further, we developed a tool to assess the visualisation complexity of the selected papers. RESULTS: Of 3,723 identified unique citations, 42 papers met our inclusion criteria for the final review. One or more of the following types of GIS applications were reported by these studies: (a) thematic mapping (37 papers); (b) spatial cluster detection (16 papers); (c) risk factors detection (16 papers); and (d) health access and planning (two papers). In the majority of studies (88%), the score of visualisation complexity was relatively low: three or less from the range of zero to six. CONCLUSIONS: Although the number of studies using GIS techniques has dramatically increased in the last decade, the use of GIS in the areas of MS access and planning is still under-researched. Additionally, the capacity of GIS in visualising complex nature of MS care system is not yet fully investigated.

Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice.

BACKGROUND: Response time to cardiovascular emergency medical requests is an important indicator in reducing cardiovascular disease (CVD) -related mortality. This study aimed to visualize the spatial-time distribution of response time, scene time, and call-to-hospital time of these emergency requests. We also identified patterns of clusters of CVD-related calls. METHODS: This cross-sectional study was conducted in Mashhad, north-eastern Iran, between August 2017 and December 2019. The response time to every CVD-related emergency medical request call was computed using spatial and classical statistical analyses. The Anselin Local Moran's I was performed to identify potential clusters in the patterns of CVD-related calls, response time, call-to-hospital arrival time, and scene-to-hospital arrival time at small area level (neighborhood level) in Mashhad, Iran. RESULTS: There were 84,239 CVD-related emergency request calls, 61.64% of which resulted in the transport of patients to clinical centers by EMS, while 2.62% of callers (a total of 2218 persons) died before EMS arrival. The number of CVD-related emergency calls increased by almost 7% between 2017 and 2018, and by 19% between 2017 and 2019. The peak time for calls was between 9 p.m. and 1 a.m., and the lowest number of calls were recorded between 3 a.m. and 9 a.m. Saturday was the busiest day of the week in terms of call volume. There were statistically significant clusters in the pattern of CVD-related calls in the south-eastern region of Mashhad. Further, we found a large spatial variation in scene-to-hospital arrival time and call-to-hospital arrival time in the area under study. CONCLUSION: The use of geographical information systems and spatial analyses in modelling and quantifying EMS response time provides a new vein of knowledge for decision makers in emergency services management. Spatial as well as temporal clustering of EMS calls were present in the study area. The reasons for clustering of unfavorable time indices for EMS response requires further exploration. This approach enables policymakers to design tailored interventions to improve response time and reduce CVD-related mortality.

Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015-2019: a data note.

OBJECTIVES: The leading factors of paediatric, pedestrian road traffic injuries (PPRTIs) are associated with the characteristics of immediate environment. Spatial analysis of data related to PPRTIs could provide useful knowledge for public health specialists to prevent and decrease the number of accidents. Therefore, we aim to release the datasets which have been used to conduct a multiple-scale spatial analysis of PPRTIs in the city of Mashhad, Iran, between 2015-2019. DATA DESCRIPTION: The data include four datasets. The base PPRTIs dataset includes motor vehicle accidents and their attributes in the city of Mashhad between March 2015 and March 2019. The attribute data includes the month, day of the week, hour of the day, place (longitude and latitude) of each accident, age range of the child and gender. Furthermore, three spatial datasets about the city of Mashhad are introduced; (1) the digital boundaries of Neighbourhood, (2) road network dataset (street lines) and (3) urban suburbs of Mashhad.

Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015-2019.

BACKGROUND: Paediatric, pedestrian road traffic injuries (PPRTIs) constitute a major cause of premature death in Iran. Identification of high-risk areas would be the primary step in designing policy intervention for PPRTI reduction because environmental factors play a significant role in these events. The present study aims to determine high-risk areas for PPRTIs at three different geographical scales, including the grid network, the urban neighbourhood and the street levels in Mashhad, Iran during the period 2015-2019. METHODS: This cross-sectional retrospective study was based on all pedestrian accidents with motor vehicles involving children (less than 18 years of age) between March 2015 and March 2019 in the city of Mashhad, which is the second-most populous city in Iran. The Anselin Local Moran's I statistic and Getis-Ord Gi* were performed to measure spatial autocorrelation and hotspots of PPRTIs at the geographical grid network and neighbourhood level. Furthermore, a spatial buffer analysis was used to classify the streets according to their PPRTI rate. RESULTS: A total of 7390 PPRTIs (2364 females and 4974 males) were noted during the study period. The children's mean age was 9.7 ± 5.1 years. Out of the total PPRTIs, 43% occurred on or at the sides of the streets, 25 of which labelled high-risk streets. A high-high cluster of PPRTI was discovered in the eastern part of the city, while there was a low-low such cluster in the West. Additionally, in the western part of the city, older children were more likely to become injured, while in the north-eastern and south-eastern parts, younger children were more often the victims. CONCLUSIONS: Spatial analysis of PPRTIs in an urban area was carried out at three different geographical scales: the grid network, the neighbourhood and the street level. The resulting documentation contributes reliable support for the implementation and prioritization of preventive strategies, such as improvement of the high-risk streets and neighbourhoods of the city that should lead to decreasing numbers of PPRTIs.

An age-integrated approach to improve measurement of potential spatial accessibility to emergency medical services for urban areas.

OBJECTIVE: This study aimed to develop an age-included approach to measure the potential accessibility to Emergency medical services (EMS) across urban and suburban areas of Mashhad city in Iran. METHODS: We used an improved version of two-step floating catchment area (2SFCA) and enhanced 2SFCA (E2SFCA) methods to measure the potential accessibility to EMS services with inclusion of age factor. This enabled us to better model accessibility of the older population to the EMS. We used 22 800 records of EMS enquiries from July to September 2018 to evaluate and assess the potential improvement in access to the EMS with incorporating age in the model. RESULTS: Suburb areas had less potential accessibility compared with central urban due to the high density of EMS stations in the city center areas. Our model showed slight improvement in potential accessibility measurement as a result of the proposed age-integrated method. CONCLUSION: An age-integrated index of accessibility method takes into account the age distribution of the population in service area is highly associated with actual measures of accessibility to EMS services. Identifying areas with poor access to EMS will help policymakers to design better policy planning to allocate resources and improve provision of EMS services.

Colorectal cancer risk factors in north-eastern Iran: A retrospective cross-sectional study based on geographical information systems, spatial autocorrelation and regression analysis.

Colorectal cancer (CRC) is the second most common cancer among females and the third most common malignancy in males in the world. No single risk factor has been identified, but there are many interrelated factors that together cause the disease. This retrospective, cross-sectional study aimed to identify potential spatial factors contributing to its geographical distribution. Data concerning 1,089 individuals with CRC from the Khorasan-Razavi Province in Iran, located in the North-East of the country, were obtained from the national CRC registry. Local Moran's I statistic was performed to identify clustered areas of CRC occurrence and ordinary least squared regression was calculated to predict frequency of the disease based on a set of variables, such as diet, body mass index (BMI) and the proportion of the population ≥50 years of age. Some dissimilarities related to the geography in the province and also some neighbourhood-related similarities and dissimilarities of CRC occurrence in the city of Mashhad were found. A significant regression equation was found (F (4,137)=38.304, P<.000) with an adjusted R2 of 0.6141. The predicted CRC frequency was -58.3581 with the coefficients for average BMI=+1.594878; fibre intake=-0.610335; consumption of red meat +0.078970; and ≥50-year age group =+0.000744. All associations were statistically significant, except the consumption of red meat one. The study results illuminate the potential underlying risk factors in areas where the CRC risk is comparatively high and how the CRC risk factors may play a role in CRC geographic disparity. Further research is required to explain the patterns observed. We conclude that people should include more fibre in their daily diet and decline their BMI to decrease risk of CRC.

Comparing potential spatial access with self-reported travel times and cost analysis to haemodialysis facilities in North-eastern Iran.

End-stage renal disease patients regularly need haemodialysis three times a week. Their poor access to haemodialysis facilities is significantly associated with a high mortality rate. The present cross-sectional study aimed to measure the potential spatial access to dialysis services at a small area level (census tract level) in North Khorasan Province, Iran. The patients were interviewed to obtain their travel information. The two-step floating catchment area (2SFCA) method was used to measure the spatial accessibility of patients to the dialysis centres. The capacity of the dialysis centre was defined as the number of active dialysis facilities in each centre and the haemodialysis patients in each area were considered as the users of dialysis services. The travel cost from each patient's residence to the haemodialysis facilities was visualized by the Kriging interpolation algorithm in the study area. Spatial accessibility to the dialysis centre was poor in the northern part of the study area. Fortunately, there were not many haemodialysis patients in that area. Patients' travel costs were high in the northern areas compared to the rest of study area. We observed a statistically significant reverse correlation between the self-reported travel time and computed spatial accessibility (-0.570, P value <0.01, two-tailed spearman test). This study supports the notion that the 2SFCA method could be associated with revealed access time to dialysis facilities, especially in low traffic and in flat areas such as northern Khorasan. The mapping of patients' distribution and interpolated travel cost to the haemodialysis facilities could help policymakers to allocate health resources to the areas where the need is greater.