Search Results (439)

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

Zoning policies play a critical role in shaping the geography of urban and suburban development in the United States. Using data from the National Zoning and Land-Use Database and tract-level census data from 42 Metropolitan Statistical Areas, we classify metros into four zoning regime types based on the relative restrictiveness of urban and suburban land-use policies and compare trends in population growth and neighborhood change across these regimes. Our findings show that suburban areas have outpaced urban cores in population growth across all zoning configurations, with the most pronounced growth occurring in metros where restrictive urban zoning coexists with permissive suburban regulation. This growth is disproportionately concentrated in affluent suburban neighborhoods, suggesting a spatial sorting of access to resources and amenities. We also find that urban–suburban gentrification gaps are the smallest in these asymmetrical zoning regimes, suggesting that permissive suburban land use may facilitate spillover effects from constrained cores. These findings suggest that zoning asymmetries shape not only the geography of growth but also the spatial dynamics of gentrification. We argue for a metropolitan perspective on land-use governance to better understand the interconnected nature of suburbanization and the spatial expansion of gentrification. Full article

Regulatory air pollution monitoring is performed using a sparse monitoring network designed to provide background concentrations of pollutants but may miss small area variations due to local emission sources. Low-cost air pollution sensors operated by trained citizen scientists provide an opportunity to fill this gap. We describe the development and implementation of an air pollution monitoring and community engagement plan in response to resident concerns regarding excessive smoke production from a neighborhood restaurant. Particulate matter (PM_2.5) was measured using a low-cost, portable sensor. When cooking was taking place, the highest PM_2.5 readings were within 50 m of the source (mean PM_2.5 36.9 µg/m³) versus greater than 50 m away (mean PM_2.5 13.0 µg/m³). Sharing results with local government officials did not result in any action to address the source of the smoke emissions, due to lack of jurisdiction. A review of air pollution regulations across the United States indicated that only seven states regulate food cookers and six states specifically exempted cookers from air pollution regulations. Concerns about the smoke were communicated with the restaurant owner who eventually changed the cooking fuel. Following this change, less smoke was observed from the restaurant and PM_2.5 measurements were reduced to background levels. Although current environmental health regulations may not protect residents living near sources of food cooker-based sources of PM_2.5, community engagement shows promise in addressing these emissions. Full article

Indoor radon constitutes a public health issue in various regions across the United States as the second leading cause of lung cancer following tobacco smoke. The U.S. Environmental Protection Agency advises radon mitigation interventions for residential buildings with indoor radon concentrations exceeding the threshold level of 4 pCi/L. Despite considerable research assessing the technical effectiveness of radon mitigation systems, there remains a gap in understanding their broader influence on occupant behavior and preferences in residential design. This study aims to investigate the impact of residing in radon-mitigated homes within the Commonwealth of Kentucky—an area known for elevated radon concentrations—on occupants’ preferences regarding healthy home design attributes. The objectives of this research are twofold: firstly to determine if living in radon-mitigated homes enhances occupant awareness and consequently influences their preferences toward health-related home attributes and secondly to quantitatively evaluate and compare the relative significance homeowners assign to health-related attributes such as indoor air quality, thermal comfort, and water quality relative to conventional attributes including home size, architectural style, and neighborhood quality. The overarching purpose is to explore the potential role radon mitigation initiatives may play in motivating occupants towards healthier home construction and renovation practices. Using choice-based conjoint (CBC) analysis, this paper compares preferences reported by homeowners from radon-mitigated homes against those from non-mitigated homes. While the findings suggest a relationship between radon mitigation and increased preference for indoor air quality, the cross-sectional design limits causal interpretation, and the possibility of reverse causation—where health-conscious individuals are more likely to seek mitigation—must be considered. The results provide novel insights into how radon mitigation efforts might effectively influence occupant priorities towards integrating healthier design elements in residential environments. Full article

Urban outdoor thermal comfort (OTC) has become an increasingly critical issue under the pressures of urbanization and climate change. Comparative analyses of urban blocks with distinct spatial morphologies are essential for identifying OTC issues and proposing targeted optimization strategies. However, existing studies predominantly rely on microclimate numerical simulations, while comparative assessments of OTC from the human thermal perception perspective remain limited. This study employs the thermal walk method, integrating microclimatic measurements with thermal perception questionnaires, to conduct on-site OTC investigations across three urban blocks with contrasting spatial morphologies—a business district (BD), a residential area (RA), and a historical neighborhood (HN)—in Beijing, a hot summer and cold winter climate city. The results reveal substantial OTC differences among the blocks. However, these differences demonstrated great seasonal and temporal variations. In summer, BD exhibited the best OTC (mTSV = 1.21), while HN performed the worst (mTSV = 1.72). In contrast, BD showed the poorest OTC in winter (mTSV = −1.57), significantly lower than HN (−1.11) and RA (−1.05). This discrepancy was caused by the unique morphology of different blocks. The sky view factor emerged as a more influential factor affecting OTC over building coverage ratio and building height, particularly in RA (r = 0.689, p < 0.01), but its impact varied by block, season, and sunlight conditions. North–South streets generally perform better OTC than East–West streets, being 0.26 units cooler in summer and 0.20 units warmer in winter on the TSV scale. The study highlights the importance of incorporating more applicable physical parameters to optimize OTC in complex urban contexts and offering theoretical support for designing climate adaptive urban spaces. Full article

Youth violence—the deliberate use of physical force or harm by young people between the ages of 10 and 24 to intimidate or cause harm to others, both online and offline—is a critical public health issue in the United States. Yet, successfully predicting future violent offenders is a complex and challenging task, as the question of why some youths resort to extreme violence while others refrain from it—despite facing similar risk factors—remains widely debated. This article highlights both risk and protective factors of youth violence through a socio-ecological lens to offer a comprehensive understanding of the multifaceted factors driving youth violence in the United States. To understand the interconnectedness between individual factors and the broader environments in which individuals are embedded, we outline the risk and protective factors related to youth violence across five socio-ecological levels: (1) individual, (2) interpersonal, (3) neighborhood, (4) cultural, and (5) life course. Approaching youth violence from a holistic lens offers a greater opportunity to mitigate contributing factors and to address the deleterious impacts of this complex issue. Practice and research implications are discussed. Full article

Background: Suicidal ideation among adolescents remains a major public health challenge. Exposure to neighborhood violence is associated with increased risk of mental health distress and school-related vulnerabilities. This study investigates the predictors of suicidal ideation among U.S. adolescents who have witnessed neighborhood violence. Methods: Data were drawn from the 2023 Youth Risk Behavior Survey (YRBS), a nationally representative survey of high school students in the United States. A subsample of 3495 adolescents who reported witnessing neighborhood violence was analyzed. Key variables included sociodemographic characteristics, mental health symptoms, perceived school safety, and experiences of victimization. Multivariable logistic regression was used to identify factors associated with suicidal ideation, defined as seriously considering suicide in the past year. Analyses were conducted using Jamovi (version 2.6), with statistical significance set at p < 0.05. Results: The prevalence of suicidal ideation in the sample was 34.2%. Bisexual adolescents had significantly higher odds of suicidal ideation compared to heterosexual peers (OR = 2.34, p < 0.001). Depressive symptoms were the strongest predictor (OR = 7.51, p < 0.001). Both perceived lack of safety at school and differences in ethnic and population backgrounds were significant. Black and Hispanic/Latino adolescents had lower odds compared to White peers. Conclusions: Findings highlight sexual identity, depressive symptoms, school safety concerns, and ethnic and population background differences as key correlates of suicidal ideation. Culturally responsive, trauma-informed interventions are urgently needed for youth exposed to community violence. Full article

The European Union (EU) is striving to achieve its goal of being climate-neutral by 2050. Aligned with the European Green Deal and in search of means to decarbonize its urban environments, the EU advocates for smart positive energy districts (PEDs). PEDs contribute to the United Nations’ (UN) sustainable development goals (SDGs) of “Sustainable Cities and Communities”, “Affordable and Clean Energy”, and “Climate Action”. PEDs are urban neighborhoods that generate renewable energy to a higher extent than they consume, mainly through the utilization of innovative technologies and renewable energy sources. In accordance with the EU 2050 aim, the PED concept is attracting growing research interest. PEDs can transform existing energy systems and aid in achieving carbon neutrality and sustainable urban development. PED is a novel concept and its implementation is challenging. This study aims to present the emerging technologies enabling the proliferation of PEDs by identifying the main challenges and potential solutions to effective adoption and implementation of PEDs. This paper examines the importance and utilization of cyber-physical systems (CPSs), digital twins (DTs), artificial intelligence (AI), the Internet of Things (IoT), edge computing, and blockchain technologies, which are all fundamental to the creation of PEDs for enhancing energy efficiency, sustainable energy, and user engagement. These systems combine physical infrastructure with digital technologies to create intelligent and autonomous systems to optimize energy production, distribution, and consumption, thus positively contributing to achieving smart and sustainable development. Full article

LiDAR point clouds, as direct carriers of 3D spatial information, comprehensively record the geometric features and spatial topological relationships of object surfaces, providing intelligent systems with rich 3D scene representation capability. However, current point cloud semantic segmentation methods primarily extract features through operations such as convolution and pooling, yet fail to adequately consider sparse features that significantly influence the final results of point cloud-based scene perception, resulting in insufficient feature representation capability. To address these problems, a sparse feature dynamic graph convolutional neural network, abbreviated as SFDGNet, is constructed in this paper for LiDAR point clouds of complex scenes. In the context of this paper, sparse features refer to feature representations in which only a small number of activation units or channels exhibit significant responses during the forward pass of the model. First, a sparse feature regularization method was used to motivate the network model to learn the sparsified feature weight matrix. Next, a split edge convolution module, abbreviated as SEConv, was designed to extract the local features of the point cloud from multiple neighborhoods by dividing the input feature channels, and to effectively learn sparse features to avoid feature redundancy. Finally, a multi-neighborhood feature fusion strategy was developed that combines the attention mechanism to fuse the local features of different neighborhoods and obtain global features with fine-grained information. Taking S3DIS and ScanNet v2 datasets, we evaluated the feasibility and effectiveness of SFDGNet by comparing it with six typical semantic segmentation models. Compared with the benchmark model DGCNN, SFDGNet improved overall accuracy $\left(OA\right)$, mean accuracy $\left(mAcc\right)$, mean intersection over union $\left(mIoU\right)$, and $sparsity$ by $1.8\%$, $3.7\%, 3.5\%$, and $85.5\%$ on the S3DIS dataset, respectively. The $mIoU$ on the ScanNet v2 validation set, $mIoU$ on the test set, and $sparsity$ were improved by $3.2\%, 7.0\%$, and $54.5\%$, respectively. Full article

A growing knowledge base highlights the importance of accounting for a variety of social and structural determinants of health (SDOH) when understanding mental and behavioral health among adolescents and young adults. The objective of the current study is to examine patterns of self-reported SDOH deficits and characterize participant health indicators and social identity across classes. Data is from a cross-sectional national study of young people who were recruited through study advertisements on social media and surveyed online. Data were collected between June 2022 and October 2023. Eligibility included (1) ages 13–22 years, (2) living in the United States, and (3) proficient in English. Health indicators included suicide attempts, suicidal ideation, drug overdose, perceived likelihood of living to age 35, non-suicidal self-injury, recent alcohol use, and depression. Five classes of SDOH deficits were identified: (1) Economic Instability, (2) Low Overall SDOH Deficits, (3) High Social SDOH Deficits (adversity and discrimination), (4) High Economic SDOH Deficits, and (5) High Overall SDOH Deficits. Differences across class by health indicators and marginalized identity were found, with high proportions of gender minority and sexual minority youth in both the High Overall SDOH Deficit group and the High Social SDOH Deficit classes. Black youth were more likely to be part of the High Economic SDOH Deficits class. The findings encourage a public health approach that recognizes that improving the health of today’s young people must be connected to policies that reduce poverty, improve neighborhoods, and increase access to basic goods, services, and healthcare. Full article

Agricultural terraces are critical landscape elements that promote sustainable rural development by enhancing water retention, mitigating soil erosion, and conserving cultural heritage. In northeastern Türkiye, particularly in the mountainous Erikli neighborhood of Uzundere, traditional terraces face growing threats due to land abandonment, topographic fragility, and socio–economic decline. This study applies a spatial–functional assessment framework that integrates UAV–based photogrammetry, GIS analysis, terrain modeling, and DBSCAN clustering to evaluate terrace conditions. UAVs provided high–resolution topographic data, which supported the delineation of terrace boundaries and morphometric classification using an adapted ALPTER model. A combined Terrace Density Index (TDI) and Functional Status Index (FSI) approach identified zones where terraces are structurally intact but functionally degraded. Results indicate that 76.4% of terraces fall within the meso and macro classes, yet 58% show partial or complete degradation. Cohesive terrace clusters are located near settlements, while isolated units in peripheral zones display higher vulnerability. This integrated approach demonstrates the analytical potential of drone–supported spatial diagnostics for monitoring landscape degradation. The method is scalable and adaptable to other terraced regions, offering practical tools for site–specific land use planning, heritage conservation, and resilience–based restoration strategies. Full article

While racial inequalities in assortative mating and fertility have been well documented, the role of neighborhoods has frequently been overlooked in explaining these disparities. In this study, I use restricted birth record data from the state of California with neighborhood-level socioeconomic and demographic data to explore the roles of neighborhoods and structural neighborhood inequality in mediating racial inequality in assortative mating and fertility in 2018 and 2019. Overall, neighborhood disadvantage, particularly disadvantage measured in a neighborhood’s mobility network, mediated a substantial proportion of the disparity in fathers’ educational attainment between White and Black or Hispanic mothers in California in 2018 and 2019. Additionally, while I observe evidence of Black and Hispanic neighborhoods having significantly greater fertility rates than White neighborhoods, this gap can be entirely explained by neighborhood disadvantage. Lastly, a significant share of the fertility gap between less-educated White and Black women is mediated by neighborhood disadvantage. This study motivates more research at the intersection of assortative mating and fertility at the neighborhood scale. Full article

This paper proposes a distributed data-driven adaptive iterative learning control (DAILC) method to address the challenges of modeling and voltage regulation in isolated AC microgrids subject to disturbances and sensor saturation. Firstly, by utilizing the input–output data from the microgrid, a time-varying linear data microgrid model is developed for the distributed renewable energy generation unit (DREGU) that is independent of the microgrid’s physical information. Subsequently, the DAILC algorithm is developed from the microgrid data model, which only uses the input data and the corresponding saturated outputs from each DREGU, along with embedded measurement disturbances. Additionally, we verify the convergence of this algorithm, demonstrating that it can ensure the error in voltage restoration converges to a small neighborhood around the origin, even under conditions of sensor saturation and disturbances. Finally, through a simulation involving four DREGU nodes, we confirm the effectiveness of the proposed distributed DAILC method. Full article

This study aims to improve the accuracy of small-scale landslide susceptibility maps (LSMs) by comparing two critical terrain factors—slope and relief energy. Slope is commonly used in LSMs, but its values are significantly sensitive to the spatial resolution of digital elevation models (DEMs). Although some studies have also addressed the effect of DEM resolution on relief parameters, direct comparisons between slope and relief energy remain limited. This research examines how these factors perform at different DEM resolutions and compare them to identify the most effective predictor for small-scale LSMs. Using the frequency ratio method, two LSM scenarios were evaluated: one using slope alongside geological units, and another using relief energy instead of slope, with various neighborhood distances. The study was conducted over a 29,785 km² area in the Pannonian part of Croatia. The findings indicate that relief energy is more stable across different DEM resolutions and enhances the accuracy of LSMs, particularly in large and geologically diverse regions. These results suggest that relief energy may serve as a more reliable factor for small-scale LSMs, offering practical implications for improving landslide risk prediction and land management strategies. Full article

The study explores the features of spatiotemporal circles of residents’ daily walking. Through a survey of residents’ walking activity in 16 residential communities, the walking purpose, distance, time, and speed of different residents were analyzed, and the circles of residents’ walking activities in historic and modern districts were identified. It is found that residents’ walking activities showed obvious spatiotemporal and individual differences. Walking activities on weekdays mainly focus on short distances (0.5–1 km) and short duration (5–15 min) for commuting and basic needs, while walking activities on weekends tend to be longer distances (more than 2 km) and longer duration (15–40 min) for leisure purposes. There are significant differences in distance and speed between walking activities in the historic and modern districts, with residents of the historic districts walking a smaller range but more diverse destinations, and residents of the modern districts walking to a wider range but fewer types of destinations. The study provides a scientific basis for multi-circle planning strategies of community life units, and it contributes to the localized adaptation of the “15-minute city” concept by revealing how historical and modern districts shape distinct spatiotemporal circles for walkability in Chinese cities. Full article