Spatial Index Research Articles

Epidemiology and geographical patterns of common childhood cancers in Iran: Evidence from the National Cancer Registry

IntroductionCancer is projected to become the primary cause of death in the 21st century. Although childhood cancer is relatively rare, it remains a significant contributor to mortality among children. This study examines the geographical distribution of childhood cancer incidence in Iranian provinces using data from the National Cancer Registry between 2014 and 2018. Materials and methodsThis registry-based study analyzed data from 14,711 children under 20 diagnosed with common childhood cancers, sourced from the Iranian National Population-based Cancer Registry for the period 2014–2018. The age-standardized incidence rates (ASR) were calculated using direct standardization methods and reported per 1 million person-years. Spatial autocorrelation measures, including global and local indices such as Moran's I and Getis-Ord's G, were employed to identify high-risk and low-risk areas, assess overall spatial dependence, and pinpoint specific clusters and hotspots of incidence rates. ResultsASR for childhood cancer in Iran was 119.56 per 1 million individuals aged 0–19 years. Boys had a higher ASR (129.98) than girls (107.68). Childhood cancer cases increased from 2765 in 2014 to 3354 in 2018, with leukemia as the most common type, followed by brain and nervous system, lymphoma, bone, and connective and soft tissue cancers. Spatial analysis identified high-risk clusters in central Iran (Isfahan, Yazd, Tehran) and low-risk clusters in the northeast (Kermanshah, West and East Azerbaijan, Kurdistan). ConclusionThis study highlights high childhood cancer incidence in Iran, particularly among boys and in central regions, with elevated leukemia rates. These findings call for targeted prevention strategies and further research to address geographic and gender disparities and to improve care programs.

Designing a Multitemporal Analysis of Land Use Changes and Vegetation Indices to Assess the Impacts of Severe Forest Fires Before Applying Control Measures

Forest fires represent a significant intersection between nature and society, often leading to the loss of natural resources, soil nutrients, and economic opportunities, as well as causing desertification and the displacement of communities. Therefore, the objective of this work is to analyze the multitemporal conditions of a sixth-generation forest fire through the use and implementation of tools such as remote sensing, photointerpretation with geographic information systems (GISs), thematic information on land use, and the use of spatial indices such as the Normalized Difference Vegetation Index (NDVI), the Normalized Burned Ratio (NBR), and its difference (dNBR) with satellite images from Sentinel-2. To improve our understanding of the dynamics and changes that occurred due to the devastating forest fire in Los Guájares, Granada, Spain, in September 2022, which affected 5194 hectares and had a perimeter of 150 km, we found that the main land use in the study area was forest, followed by agricultural areas which decreased from 1956 to 2003. We also observed the severity of burning, shown with the dNBR, reflecting moderate–low and moderate–high levels of severity. Health and part of the post-fire recovery process, as indicated by the NDVI, were also observed. This study provides valuable information on the spatial and temporal dimensions of forest fires, which will favor informed decision making and the development of effective prevention strategies.

Spatial Distribution of Public Lower Secondary School and its Impact on Students’ Enrolment in Ogun Central Senatorial District Ogun State, Nigeria

Given the quest for universal basic education, the large enrolments in the Nigerian secondary educational institutions has resulted in the problem of over-crowded classes, shortage of teachers and shortages of classroom, which portend enormous challenges to the development of the educational sector in Ogun state. Using Ogun Central as a case study, the study identified the spatial pattern of the schools; analyzing students’ enrolment trends in the area, and identifying the factors associated with the observed pattern. Spatial analysis tool in ArcGIS was used to analyze both the spatial accessibility index and the students’ annual enrolment trend of the lower secondary school in the area. The result of the nearest neighbor analysis for the spatial pattern of lower secondary schools in the study revealed a random pattern. This pattern implies that the lower secondary schools are located far from one another, which indicates, that for students to attend the schools, most of them need to cover long distances. The spatial distribution of junior secondary school is influenced by socioeconomic status, environmental factors, demographic characteristics, transportation infrastructure, and geographic accessibility, which are key determinants of educational equity. Linear regression analysis was employed to identify trends and predict future enrollments of students. Further, the results of the trend analysis of enrolments of students in the zone from 2020 – 2023 reveal a negative trend. This implies a decrease in students’ enrolment as the year increases. The four years (2020 – 2023) annual trend of enrolments in the zone is represented by the negative trend y = -3180.3x + 99400. This result suggests that the students’ enrolments in the zone would gradually keep decreasing as time goes on if quick remedial actions are not taken. However, factors such as shortage of teachers, shortage of classrooms, COVID-19, insufficient infrastructural facilities and fuel subsidy removal could be responsible for the negative enrolment trend

Study by Spatial Distance Index Analysis of the Agave Weevil Scyphophorus acupunctatus1 Ghynlled in the State of Mexico

Study by Spatial Distance Index Analysis of the Agave Weevil Scyphophorus acupunctatus1 Ghynlled in the State of Mexico

Mapping barriers to food, energy, and water systems equity in the United States

Barriers to affordable, accessible, high-quality food, energy, and water systems (FEWS) harm social equity. Connections within and across FEWS suggest that co-occurring barriers to equity can compound vulnerability. We hypothesized that barriers to FEW resources are strongly associated with geographic location, both within and across FEWS, as they rely heavily on localized sociopolitical and natural environments. This study explored the geographic relationships between FEWS barriers and social equity through a spatial analysis of census tracts within the United States. Cluster analyses showed that all FEWS barriers had a positive spatial autocorrelation (Moran's I = 0.12–0.94), with energy barriers being the most spatially clustered and affordability barriers being the least spatially clustered. In 54 % of census tracts, we observed the co-occurrence of low barriers to water quality and access. Barriers to FEWS affordability almost always co-occurred in parallel (e.g., high barriers to affordability in one system co-occurred with high barriers to affordability in another system). Finally, we developed a spatial index of the barriers to FEWS equity to determine vulnerability at the census tract scale, which had a positive spatial autocorrelation (Moran's I = 0.41). Clusters and intersections of FEWS equity barriers suggest that resources are interconnected, resulting in additional challenges for people living in these areas. The maps of barriers to equity in FEWS are useful tools that could help stakeholders (e.g., federal agencies, city planners, utilities) distribute FEWS resources fairly and begin engagement with communities about FEWS barriers in their local context.

LiDAR-Based Modeling of Individual Tree Height to Crown Base in Picea crassifolia Kom. in Northern China: Comparing Bayesian, Gaussian Process, and Random Forest Approaches

This study compared hierarchical Bayesian, mixed-effects Gaussian process regression, and random forest models for predicting height to crown base (HCB) in Qinghai spruce (Picea crassifolia Kom.) forests using LiDAR-derived data. Both modeling approaches were applied to a dataset of 510 trees from 16 plots in northern China. The models incorporated tree-level variables (height, diameter at breast height, crown projection area) and plot-level spatial competition indices. Model performance was evaluated using leave-one-plot-out cross-validation. The Gaussian mixed-effects process model (with an RMSE of 1.59 and MAE of 1.25) slightly outperformed the hierarchical Bayesian model and the random forest model. Both models identified LiDAR-derived tree height, DBH, and LiDAR-derived crown projection area as primary factors influencing HCB. The spatial competition index (SCI) emerged as the most effective random effect, with the lowest AIC and BIC values, highlighting the importance of local competition dynamics in HCB formation. Uncertainty analysis revealed consistent patterns across the predicted values, with an average relative uncertainty of 33.89% for the Gaussian process model. These findings provide valuable insights for forest management and suggest that incorporating spatial competition indices can enhance HCB predictions.

Potential Conflict Diagnosis, Simulation Optimization and Coordination of Production-Living-Ecological Space in Gully Areas of the Loess Plateau, China

The gully areas on the Loess Plateau have always been ecologically fragile agricultural areas. These areas often face the common problem of intensified conflicts in production-living-ecological space during economic development, and there is an urgent need for systematic spatial governance. This study innovatively developed a full process technical framework of "identification diagnosis - simulation optimization - coordinated governance" for potential conflicts in the production-living-ecological space, and used Huachi County in the gully area of the Loess Plateau as an example for empirical research. Under this framework, we analyzed the transfer patterns of production, living, and ecological space in the research area; Improved the spatial suitability evaluation index system of "multi-dimensional + multi-objective"; The conflict determination matrix was used to identify the scope, scale, type, and intensity of potential spatial conflicts; We conducted spatial optimization simulations under two scenarios: prioritizing ecological protection and prioritizing social and livelihood development, and designed an overall spatial optimization plan; Propose spatial collaborative governance strategies based on the theory of public space governance. Research shows that this framework has good applicability for the research area and is more direct for guiding subsequent spatial planning and policy practice. The potential conflict between production space and ecological space in Huachi County is the most common, the potential conflict intensity between living space and production space is the largest, and the potential conflict risk between living space and ecological space is rising. To coordinate potential conflicts in space, it is necessary to establish a vertical allocation type of spatial function coordination chain of “goal + collaboration + adjustment”, as well as a horizontal negotiation type of spatial configuration coordination chain of “allocation + cooperation + balance”, forming a “double vertical and double horizontal” spatial coordination framework.

Evaluation of perceptual indicators of physical environment affecting the inducement of citizen’s sense of place in urban neighborhoods

Cities in the past made it simple for people and space to interact. However, in today’s world, city planning and foreseeing strategies and options to create a desirable place that fits human life have become more important due to the spread of urbanization and the emergence of new problems brought about by the frequent implementation of foreign and Western patterns in urban neighborhoods. Sense of place is a behavioral science concept that plays a crucial role in forming user communication bases and creating an environment that eventually fosters a sense of belonging by attracting users’ happiness. Because of this, architects and urban planners are now more cognizant of the ideas and signs of a feeling of place in the actual physical surroundings of metropolitan areas. However, the debate remains as to what these indicators actually are and how they might affect the sense of place that residents have. This study combines analytical and descriptive methods. This study employed a questionnaire and survey approach to determine the physical characteristics impacting the feeling of place. The statistical population consisted of 150 residents of Tehran Municipality District 1′s Zaferanieh area. Questions were posed using a basic random technique to the statistical population. For data analysis, SPSS was utilized. This form of external validity applies to the questionnaire instrument. To assess this questionnaire’s reliability, Cronbach’s alpha coefficient was employed. The reliability of the questionnaire is deemed adequate, as indicated by the coefficients that exceed 0.7. Certain factors significantly contribute to creating a sense of place in urban communities, according to the findings of the regression analysis and correlation coefficient. With regard to the physical elements affecting the Zaferanieh neighborhood’s feeling of place, factor analysis revealed that the use and activity index, at 11.252%, has the least influence and the spatial quality index, at 17.021%, has the most.

Multidimensional Healthcare Access Barriers to Prostate-Specific Antigen Testing: A Nation-Wide Panel Study in the United States From 2006 to 2020.

Rising metastatic prostate cancer incidence has renewed debate regarding benefits of prostate-specific antigen (PSA) screening. Identifying barriers to accessing screening for individuals at high risk of lethal prostate cancer may slow this rise. We examined associations of access barriers with receipt of PSA testing, stratified by sociodemographic factors. We pooled data from male respondents to Behavior Risk Factor Surveillance Systems (BRFSS) surveys from 2006 to 2020. Questions related to affordability (insurance, cost of visits) and accommodation (regular primary care provider (PCP), physician recommending a PSA test) were considered as individual-level barriers. For availability, we linked provider density from the 2012 Area Health Resource File and estimated driving times to closest health facility within Micropolitan and Metropolitan Statistical Area (MMSA) using Google Earth Engine. These measures were used to compute a spatial accessibility index. We fit survey-weighted, covariate-adjusted logistic regression models to estimate associations of barriers with receipt of PSA within the past 2 years and examined effect modification by sociodemographic factors. There were 185,643 participants, of whom 73% were White, 11% were Black, 4% were Asian, and 11% were Hispanic. Physician recommendation was the strongest predictor of having a PSA test (aOR: 14.5, 95% CI: 13.6, 15.6). Not having a regular PCP (aOR: 0.29, 95% CI: 0.27, 0.31), insurance (aOR: 0.64, 95% CI: 0.58, 0.71), and prohibitive cost of care (aOR: 0.82, 95% CI: 0.75, 0.90) were associated with lower PSA testing. Access barriers were stronger predictors of PSA testing for Asian and White participants compared to other groups (Phet < 0.004 for insurance and regular PCP) and for those with college education compared to those without (Phet < 0.05 for insurance, perceived unaffordability). Physician recommendation was the strongest predictor of receipt of PSA testing, regardless of sociodemographic grouping. Future studies should consider access barriers jointly and across sociodemographic strata.

The Mitigating Effect of Green Space's Spatial and Temporal Patterns on the Urban Heat Island in the Context of Urban Densification: A Case Study of Xi'an

Growing evidence highlights a strong link between urban densification and urban heat island (UHI) effects. However, there is a lack of research on time-based analyses of urban green space spatial patterns using urban densification indices to mitigate UHI effects. Addressing this gap, this study focuses on the central district of Xi'an, utilizing urban density data, MODIS LST products, and Landsat series imagery. The Coordination Coupling Degree Model (CCDM) is applied to longitudinally assess the mitigating effects of urban green space spatial patterns on UHI under different scales of spatial densification. The CCDM results show a significant overall improvement in the coordination coupling degree between green space spatial indices and LST in Xi'an's central district from 2013 to 2023. However, variations across administrative districts suggest that regional planning policies have differentially influenced green space patterns and UHI effects over time. Furthermore, a global negative correlation between the urban densification index and changes in the coordination coupling degree indicates that continued urbanization in Xi'an's central district could exacerbate the urban thermal environment. This study provides valuable insights into green space planning and UHI mitigation strategies in the context of urban densification.

Advancing urban health in Portugal: exploring liveability and its association with mental morbidity

Abstract Background As cities face challenges posed by urbanisation, it becomes essential to understand how city planning can contribute to protecting public health. In this study, we aimed to assess the liveability of different areas in Lisbon, Portugal, by developing a liveability index at the parish level. Secondly, we aimed to explore its association with hospitalisation due to mental disorders. Methods The liveability index was built based on the World Health Organisation’s Urban Health Index methodology. We obtained data on liveability related to housing, socio-economic conditions and access to services (e.g. healthcare) from the 2011 census and other open data sources for Lisbon’s parishes (n = 22). Data on hospital admissions due to mental disorders was sourced at the parish level from the national database for hospital morbidity for the period 2013-2016 and sex-age-standardised. Binomial negative regression was employed to estimate the association between the liveability index tertiles and observed hospital admissions. We used the expected number of hospitalisations as the offset variable and tested for spatial autocorrelation among the regression residuals. Results Our analysis showed that living in the most liveable parishes is associated with a significant decrease in the standardised admission ratio due to mental disorders, compared to living in the least liveable areas (Incidence Relative Ratio=0.643; 95% CI: 0.427, 0.967). We did not observe any geographical pattern in the regression residuals (Moran’s I= -0.035, p = 0.427). Conclusions Our findings show disparities in liveability among Lisbon’s parishes and identify a protective association between living in higher liveability areas and hospital admissions due to mental disorders. This work should prompt further studies concerning this subject to inform urban planning policies to improve liveability and equally reduce the risk of mental health-related harm within cities. Key messages • A spatial index to assess liveability in urban areas was developed. The association between the liveability of Lisbon’s parishes and hospital admissions due to mental disorders was explored. • We found a significant protective association between higher liveability and hospital admissions due to mental disorders. This work is relevant to inform the implementation of urban planning policies.

360° CZT-SPECT/CT cameras: 99mTc- and 177Lu-phantom-based evaluation under clinical conditions

PurposeFor the first time, three currently available 360° CZT-SPECT/CT cameras were compared under clinical conditions using phantom-based measurements.MethodsA 99mTc- and a 177Lu-customized NEMA IEC body phantom were imaged with three different cameras, StarGuide (GE Healthcare), VERITON-CT versions 200 (V200) and 400 (V400) (Spectrum Dynamics Medical) under the same clinical conditions. Energy resolution and volumetric sensitivity were evaluated from energy spectra. Vendors provided the best reconstruction parameters dedicated to visualization and/or quantification, based on their respective software developments. For both 99mTc- and 177Lu-phantoms, noise level, quantification accuracy, and recovery coefficient (RC) were performed with 3DSlicer. Image quality metrics from an approach called “task-based” were computed with iQMetrix-CT on 99mTc visual reconstructions to assess, through spatial frequencies, noise texture in the background (NPS) and contrast restitution of a hot insert (TTF). Spatial resolution indices were calculated from frequencies corresponding to TTF10% and TTF50%.ResultsDespite the higher sensitivity of VERITON cameras and the enhanced energy resolution of the V400 (3.2% at 140 keV, 5.2% at 113 keV, and 3.6% at 208 keV), StarGuide presents comparable image quality. This highlights the need to differentiate sensitivity from count quality, which is influenced by hardware design (collimator, detector block) and conditions image quality as well as the reconstruction process (algorithms, scatter correction, noise regulation). For 99mTc imaging, the quantitative image optimization approach based on RCmean for StarGuide versus RCmax for V200 and V400 systems (RCmean/RCmax: 0.9/1.8; 0.5/0.9; 0.5/0.9 respectively—Ø37 mm). SRTB10/50 showed nearly equivalent spatial resolution performances across the different reconstructed images. For 177Lu imaging, the 113 keV imaging of the V200 and V400 systems demonstrated strong performances in both image quality and quantification, while StarGuide and V400 systems offer even better potential due to their ability to exploit signals from both the 113 and 208 keV peaks. 177Lu quantification was optimized according to RCmax for all cameras and reconstructions (1.07 ± 0.09—Ø37 mm).ConclusionsThe three cameras have equivalent potential for 99mTc imaging, while StarGuide and V400 have demonstrated higher potential for 177Lu. Dedicated visual or quantitative reconstructions offer better specific performances compared to the unified visual/quantitative reconstruction. The task-based approach appears to be promising for in-depth comparison of images in the context of system characterization/comparison and protocol optimization.

Fluorescence spatial anisotropy of emission dipoles in an orthogonal imaging system

In this study, we explore the relatively unexplored spatially anisotropic fluorescence emission induced by rotationally polarized excitation light in orthogonal imaging systems, a phenomenon that is particularly pronounced in orthogonal setups compared to coaxial configurations. Despite its significance, this aspect has been largely neglected, given the prevalent use of coaxial Fluorescence Polarization Microscope (FPM) setups. Our research endeavors to bridge this gap by formulating a physical model to investigate the polarization-dependent emission of dipoles and the corresponding fluorescence signal within an orthogonal imaging configuration. Additionally, we introduce the Fluorescence Spatial Anisotropy Index (FSAI) to quantify fluorescence spatial anisotropy.

A 3D X-tree optimized for Complex Indoor Building Models

Abstract. Studying complex indoor buildings is crucial for population evacuation research in our modern world, where indoor spaces are the primary living environment. However, the existing spatial indexes do not fully align with the unique characteristics of indoor space, leading to a significant bottleneck in the efficiency of searching many space areas. This article introduces a novel model that can efficiently retrieve and update compact three-dimensional indoor space by introducing space X-trees. Our experiments, which have shown that the introduction of X-trees, which can dynamically adjust the size of space nodes, has significantly improved the retrieval speed during the query operation process, underscore the reliability and potential of our new model.

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

Mangroves Invaded by Spartina alterniflora Loisel: A Remote Sensing-Based Comparison for Two Protected Areas in China

Mangroves are one of the world’s most productive and ecologically important ecosystems, and they are threatened by the widespread invasion of Spartina alterniflora Loisel in China. As few studies have examined the spatial pattern differences of S. alterniflora invasion and the nearby mangroves in different latitudes, we chose the Zhangjiang Estuary and the Dandou Sea, two representative mangrove–salt marsh ecotones in the north and south of the Tropic of Cancer, as the study areas for comparison. The object-based image analysis and visual interpretation methods were combined to construct fine-scale mangrove and S. alterniflora maps using high-resolution satellite imagery from 2005 to 2019. We applied spatial analysis, centroid migration, and landscape indexes to analyze the spatio–temporal distribution changes of mangroves and S. alterniflora in these two ecotones over time. We used the landscape expansion index to investigate the S. alterniflora invasion process and expansion patterns. The annual change rates of mangrove and S. alterniflora areas in the Zhangjiang Estuary showed a continuous growth trend. However, the mangrove areas in the Dandou Sea showed a fluctuating trend of increasing, decreasing, and then increasing again, while S. alterniflora areas kept rising from 2005 to 2019. Spartina alterniflora showed larger annual change rates compared with mangroves, indicating rapid S. alterniflora invasion in the intertidal zones. The opposite centroid migration directions of mangroves and S. alterniflora and the decreasing distances between the mangrove and S. alterniflora centroids indirectly revealed the fierce competition between mangroves and S. alterniflora for habitat resources. Both regions saw a decrease in mangrove patch integrality and connectivity. The integrality of mangrove patches in the Zhangjiang Estuary was always higher than those in the Dandou Sea. We observed the growth stage (2011–2014) and outbreak stage (2014–2019) of S. alterniflora expansion in the Zhangjiang Estuary and the outbreak stage (2005–2009) and plateau stage (2009–2019) of S. alterniflora expansion in the Dandou Sea. The expansion pattern of S. alterniflora varies in time and place. Since the expansion of S. alterniflora in the outbreak stage is rapid, with a large annual change rate, early warning of S. alterniflora invasion is quite important for the efficient and economical removal of the invasive plant. Continuous and accurate monitoring of S. alterniflora is highly necessary and beneficial for the scientific management and sustainable development of coastal wetlands.

Developing GIS-Based Algorithm of Stand Spatial Structure Index and Its Implementation

Accurate information of the fine-scale spatial patterns of trees and their interactions within a stand is critical for explaining the competition, health and vigor status, and future development of a stand. There are a number of indices which can show such patterns, but the stand spatial structure index is the most important. This index can be quantified based on the spatial information of trees (tree positions) within a stand and has paramount importance in identifying candidate trees to be thinned. This study develops a software tool (algorithm), which can conveniently and accurately estimate the stand spatial structure index. Our proposed algorithm considers the spatial relationships between a reference tree and its four adjacent trees, and computes the three most important stand structure indices (neighborhood comparison, uniform angle index and species mingling) using GIS (ArcEngine) and the C# programming language. The implementation of the developed algorithm (stand spatial structure index) shows that, for any reference tree assumed, its four adjacent trees identified by each of the three stand spatial structure indices (uniform angle index—UAI, mingling—M and neighborhood comparison—NC) are the same, indicating the consistency and accuracy between the three-stand spatial structural indices. For the same tree species in a forest stand, the computational results from each of the spatial structure indices used (UAI, M, NC) are also the same. Thus, the results of this algorithm developed in this study are consistent with that of the Winkelmass1.0 software (a type of software used to simulate stand spatial structure). As this article is based on the GIS technique, the computational results can be visually displayed and implemented on actual maps, making it more convenient and intuitive for forest management. The proposed approach will be useful for accurately identifying the trees to be thinned and helpful for maintaining the vigor stand structure. This study also demonstrates the implementation of the algorithm to the real-world data and proves that the computational process is simple and efficient. The application of this algorithm for the identification of trees to be thinned may help the stakeholders to focus their attention towards multi-functional forest management. The algorithm will also provide an important basis for optimizing thinning and maintaining well-structured forest stands.

Spatial disparities in access to NHS dentistry: a neighbourhood-level analysis in England.

Over the past decade, access to National Health Service (NHS) dentistry in England has been problematic. There are increasing media reports of patients being unable to find treatment at a local NHS dentist. However, the extent of this issue varies by location and by the characteristics of the neighbourhood. The study uses official data sources on NHS dental provision and population. Travel accessibility is measured using car journey times. An advanced form of Floating Catchment Area accessibility is used, which accounts for supply competition, varying catchments, and distance decay. Spatial availability and accessibility indices are calculated. Ways in which the method can be used to explore various types of 'what-if' scenarios are outlined. Both availability and accessibility vary by the level of neighbourhood deprivation and the urban/rural nature of the neighbourhood. A case study, based on a real-world situation, shows the impact on the local neighbourhood of the closure of a dental practice. For all neighbourhoods, NHS dental provision is generally less than would be needed to provide basic dental care. The interpretation of outputs needs to take account of edge-effects near to Scotland and Wales. Possible improvements include the inclusion of other modes of travel and the exclusion of the population that does not want to access NHS care.

Analysis of the epidemiological trends and spatial patterns of esophageal cancer among male populations in China's mainland from 1990 to 2021.

This study aimed to delineate the temporal patterns of esophageal cancer epidemic trends and spatial clustering patterns among male populations in China's mainland from 1990 to 2021. This analysis aimed to provide a scientific rationale and empirical data to facilitate the formulation of targeted prevention and control strategies. Data on the number of cases and deaths, crude and age-standardized incidence and mortality rates of esophageal cancer in men were collected from the Global Burden of Disease Study and the Chinese Cancer Registry Annual Report. Global and local Moran's I spatial autocorrelation index was employed to quantify spatial clustering, and a disease map was drawn. From 1990 to 2021, the cumulative incidence and mortality of esophageal cancer in men were 6 100 342 and 5 972 294, respectively. The crude incidence and death rates increased in 2021, yet the age-standardized rates decreased significantly. Cixian County in Hebei Province had the highest age-standardized rates. The disease displayed spatial clustering, with relatively high rates in Shandong, Jiangsu, and Hebei Provinces. Since 1990, the incidence and mortality of esophageal cancer among men in mainland China have remained high, imposing a considerable burden. Although age-adjusted rates have declined, they are still relatively high overall, especially in Shandong, Hebei, and Jiangsu Provinces.

SGIR-Tree: Integrating R-Tree Spatial Indexing as Subgraphs in Graph Database Management Systems

Efficient spatial query processing in Graph Database Management Systems (GDBMSs) has become increasingly important owing to the prevalence of spatial graph data. However, current GDBMSs lack effective spatial indexing, causing performance issues with complex spatial graph queries. This study proposes a spatial index called Subgraph Integrated R-Tree (SGIR-Tree) for efficient spatial query processing in GDBMSs. The SGIR-Tree integrates the hierarchical R-Tree structure with the graph structure of GDBMSs by converting R-Tree elements into graph components like nodes and edges. The Minimum Bounding Rectangle (MBR) information of spatial objects and R-Tree nodes is stored as properties of these graph elements, and the leaf nodes are directly connected to the spatial nodes. This approach combines the efficiency of spatial indexing with the flexibility of graph databases, thereby allowing spatial query results to be directly utilized in graph traversal. Experiments using OpenStreetMap datasets demonstrate that the SGIR-Tree outperforms the previous approaches in terms of query overhead and index overhead. The results are expected to improve spatial graph data processing in various fields, including location-based service and urban planning, significantly advancing spatial data management in GDBMSs.