Search Results (962)

The changing global climate and rapid urbanization make extreme rainstorm events frequent, and the flood disaster caused by rainstorm has become a prominent problem of urban public safety in China, which severely restricts the healthy and sustainable development of social economy. The weight calculation method of traditional risk assessment model is single and ignores the difference of multi-dimensional information space involved in risk analysis. This study constructs a flood risk assessment model by incorporating natural, social, and economic factors into an indicator system structured around four dimensions: hazard, exposure, vulnerability, and disaster prevention and mitigation capacity. A combination of the Analytic Hierarchy Process (AHP) and the entropy weight method is employed to optimize both subjective and objective weights. Taking the central urban area of Wuhan with a high flood risk as an example, based on the risk assessment values, spatial autocorrelation analysis, cluster analysis, outlier analysis, and hotspot analysis are applied to explore the spatial clustering characteristics of risks. The results show that the overall assessment level of flood hazard in central urban area of Wuhan is medium, the overall assessment level of exposure and vulnerability is low, and the overall disaster prevention and mitigation capability is medium. The overall flood risk levels in Wuchang and Jianghan are the highest, while some areas in Qingshan and Hanyang have the lowest levels. The spatial characteristics of each dimension evaluation index show obvious autocorrelation and spatial differentiation. These findings aim to provide valuable suggestions and references for reducing urban disaster risks and achieving sustainable urban development. Full article

Road networks are essential for access, resource distribution, and population evacuation during natural events. These challenges are pronounced in rural areas, where network redundancy is limited and communities may have social disparities. While traditional risk management systems often focus on the physical consequences of hazard events alone, specialized literature increasingly suggests the development of a more comprehensive approach for risk assessment, where not only physical aspects associated with infrastructure, such as damage level or disruptions, but also the social and economic attributes of the affected population are considered. Consequently, this paper proposes a Vulnerability Access Index (VAI) to support road network decision-making that integrates the social vulnerability of rural communities exposed to natural events, their accessibility to nearby critical infrastructure, and physical risk. The research methodology considers (i) the Social Vulnerability Index (SVI) calculation based on socioeconomic variables, (ii) Importance Index estimation (I_imp) to evaluate access to critical infrastructure, (iii) VAI calculation combining SVI and I_imp, and (iv) application to a case study in the influence area of the Villarrica volcano in southern Chile. The results show that when incorporating social variables and accessibility, infrastructure criticality varies significantly compared to the infrastructure criticality assessment based solely on physical risk, modifying the decision-making regarding road infrastructure robustness and resilience improvements. Full article

This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in South Korea, the model incorporates both maximum ground deformation and subsidence velocity to construct a dynamic hazard index. Social vulnerability is quantified using five demographic and infrastructural indicators, and a two-stage analytic hierarchy process (AHP) is applied with dependency correction to mitigate inter-variable redundancy. The resulting high-resolution risk maps highlight spatial mismatches between geotechnical hazards and social exposure, revealing vulnerable segments in Gongju and Iksan that require prioritized maintenance and mitigation. The framework also addresses data limitations by interpolating groundwater levels and estimating train speed using spatial techniques. Designed to be scalable and transferable, this methodology offers a practical decision-support tool for infrastructure managers and policymakers aiming to enhance the resilience of linear transport systems. Full article

Tuberculosis (TB) remains a leading cause of death in Bangladesh, disproportionately affecting low socio-economic status (SES) populations. This review, guided by the WHO Social Determinants of Health framework and Rockefeller-Lancet Planetary Health Report, examined how social, economic, and ecological factors link SES to TB burden. The first literature search identified 28 articles focused on SES-TB relationships in Bangladesh. A second search through snowballing and conceptual mapping yielded 55 more papers of diverse source types and disciplines. Low-SES groups face elevated TB risk due to smoking, biomass fuel use, malnutrition, limited education, stigma, financial barriers, and hazardous housing or workplaces. These factors delay care-seeking, worsen outcomes, and fuel transmission, especially among women. High-SES groups more often face comorbidities like diabetes, which increase TB risk. Broader contextual drivers include urbanisation, weak labour protections, cultural norms, and poor governance. Recommendations include housing and labour reform, gender parity in education, and integrating private providers into TB programmes. These align with the WHO End TB Strategy, UN SDGs and Planetary Health Quadruple Aims, which expand the traditional Triple Aim for health system design by integrating environmental sustainability alongside improved patient outcomes, population health, and cost efficiency. Future research should explore trust in frontline workers, reasons for consulting informal carers, links between makeshift housing and TB, and integrating ecological determinants into existing frameworks. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

Background/Objectives: Agricultural workers in Spain with a migratory background face challenging working and living conditions that significantly affect their health. This study aimed to explore how professionals in healthcare, social services, civil society organisations, and labour institutions perceive that the working conditions affect the physical health of this population. Methods: A qualitative descriptive study was conducted through 92 semi-structured interviews with professionals from six provinces in Spain. Data were analysed using thematic analysis following Braun and Clarke’s six-phase framework. Rigour was ensured through triangulation, independent coding, and interdisciplinary consensus. Results: Two overarching themes were identified: (1) the health consequences of workplace demands and environmental hazards, and (2) navigating health services such as sick leave and disability permits. These findings highlight how the impact of precarious working conditions and limited access to healthcare affect the physical health of migrant agricultural workers. Conclusions: The professionals interviewed described and relate precarious working conditions with adverse health outcomes among migrant agricultural workers. Their insights reveal the need for systemic reforms to enforce labour rights, ensure access to health services, and address the structural factors that contribute to exclusion and vulnerability. Full article

The sustainable management of Municipal Solid Waste (MSW) relies heavily on community participation in separating it at the source and delivering it to collection systems. These practices are crucial for reducing pollution, protecting ecosystems, and maximizing resource recovery. However, in the Global South context, with conditions of socioeconomic vulnerability, community participation in the sustainable management of MSW remains limited, highlighting the need to generate context-specific interventions. MSW includes items such as household appliances, batteries, and electronic devices, which require specialized handling due to their size, hazardous components, or material complexity. This study implemented a Community-Based Social Marketing approach during the research and design phases of an intervention focused on promoting source separation and management of hard-to-manage MSW in five municipalities within the administrative region of Norte de Santander (Colombia), which borders Venezuela. Using a mixed-methods approach, we collected data from 1775 individuals (63.83% women; M _age = 33.48 years; SD = 17.25), employing social mapping, focus groups, semi-structured interviews, participant observation, and a survey questionnaire. The results show that the source separation and delivery of hard-to-manage MSW to collection systems are limited by a set of psychosocial, structural, and institutional barriers that interact with each other, affecting communities’ willingness and capacity for action. Furthermore, a prediction model of willingness to engage in separation and delivery behaviors showed a good fit (R2 = 0.83). The strongest predictors were awareness of the negative consequences of non-participation and perceived environmental benefits, with subjective norms contributing to a lesser extent. Based on these results, we designed a context-specific intervention focused on reducing these barriers and promoting community engagement in the sustainable management of hard-to-manage MSW. Full article

Background/Objectives: Despite the numerous health benefits of exclusive breastfeeding (EBF) for the infant and the mother, EBF rates in Lao People’s Democratic Republic, Lao PDR, remain at 40%. We investigate how barriers to EBF were overcome by a social transfer intervention. Methods: Data from the Social Transfers for Exclusive Breastfeeding ongoing randomised controlled trial (RCT) (n = 298) in Vientiane, Lao PDR, was used. Mothers in the RCT were randomised equally into a control group, an unconditional transfer group and a conditional transfer group and followed up to six months (n = 280). We used logistic and Cox proportional hazards regression models to investigate the association of predictor variables with EBF at six months and the risk of EBF cessation in each of the three groups. Results: Greater breastfeeding self-efficacy increased the odds of EBF at six months in both intervention groups (unconditional transfer OR 1.39 [95% CI 1.09, 1.87, p = 0.02] and conditional transfer OR 1.26 [1.01, 1.61, p = 0.05]) and reduced the risk of EBF cessation (unconditional transfer HR 0.87 [0.77, 0.98, p = 0.02]). Maternal secondary and tertiary education in the intervention groups showed higher odds of EBF at six months and lower EBF cessation risk. Participants in the intervention group that intended to exclusively breastfeed in pregnancy showed a reduced EBF cessation risk in both intervention groups. Conclusions: Social transfers helped overcome the exclusive breastfeeding barrier of a higher education level and working status and improved EBF outcomes for mothers who intended to exclusively breastfeed and wanted the pregnancy. Breastfeeding self-efficacy positively influences EBF outcome, regardless of whether the mother received a social transfer or not. Full article

Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster risk assessment model through systematic analysis of four key factors—hazard (H), exposure (E), susceptibility/sensitivity (S), and disaster prevention capabilities (C)—and establishes an evaluation index system. Using the Analytic Hierarchy Process (AHP), we determined indicator weights and quantified flood risk via the following formula R = H × E × V × C. After we applied this model to 16 towns in coastal Zhejiang Province, the results reveal three distinct risk tiers: low (R < 0.04), medium (0.04 ≤ R ≤ 0.1), and high (R > 0.1). High-risk areas (e.g., Longxi and Shitang towns) are primarily constrained by natural hazards and socioeconomic vulnerability, while low-risk towns benefit from a robust disaster mitigation capacity. Risk typology analysis further classifies towns into natural, social–structural, capacity-driven, or mixed profiles, providing granular insights for targeted flood management. The spatial risk distribution offers a scientific basis for optimizing flood control planning and resource allocation in the district. Full article

The number of publications in the scientific literature dealing with geomorphological mapping has increased over the last two decades. Although geomorphological maps are utilised in various contexts, such as hazard assessment, archaeology, and tourism, there is a noticeable lack of interaction between geomorphological products and the social sciences. This study aims to provide a qualitative assessment of the literature on geomorphological maps published in the 2000s with the intent of identifying the purpose of mapping and its field of application. Additionally, a comparative analysis was conducted of the articles relating to both geomorphological maps and social issues to identify the tools that facilitate this interdisciplinary collaboration. The results facilitated the identification of the primary fields of interest for map production, showing that only a limited number of articles employed geomorphological maps for social purposes, for instance, enhancing risk awareness and educating the population about natural hazards. Moreover, the analysis reveals that only a limited number of geomorphological maps are intended to be accessible to people without a high degree of education in earth sciences. In particular, this study highlights a lack of attention to non-specialist users who may struggle to understand the information contained in geomorphological maps. This issue limits the dissemination of geomorphological maps, which are, however, vital for territorial planning and practical purposes. The analyses prompted the authors to consider novel applications of research tools to enhance the dissemination of geomorphological maps, even among non-specialist users. Full article

Introduction: Air pollution is a risk factor for a variety of cardiopulmonary diseases and is a contributing factor to cancer, diabetes, and cognitive impairment. The impact on mortality is not clearly elucidated. Objectives: The goal of this study is to determine the impact (if any) of air pollution on the 5-year mortality of patients in the American Family Cohort (AFC) dataset. Methods: The AFC dataset is derived from the American Board of Family Medicine PRIME Registry electronic health record data. It includes longitudinal information from 6.6 million unique patients from an estimated 800 primary care practices across 47 states, with 40% coming from rural areas. The Environmental Protection Agency’s Air Quality Index (AQI) measures were downloaded for the study period (2016–2022). Using the Python library pandas, the AFC and EPA datasets were merged with respect to date, time, and location. Cox Regression Models were performed on the merged dataset to determine the impact (if any) of air quality on patients’ five-year survival. In the model, AQI was handled as a time-independent (time-fixed) covariate. Results: The group with AQI > 50 had an adjusted hazard of death that was 4.02 times higher than the hazard of death in the group with AQI ≤ 50 (95% CI: 3.36, 4.82, p < 0.05). The hazard of death was 6.73 times higher in persons older than 80 years of age (95% CI: 5.47, 8.28; p < 0.05) compared to those younger than 80 years of age. Black/African American patients had a 4.27 times higher hazard of death (95%CI: 3.47, 5.26; p < 0.05) compared to other races. We also found that regional effects played a role in survival. Conclusions: Poor air quality was associated with a higher hazard of mortality, and this phenomenon was particularly pronounced in Black/African American patients and patients older than 80 years of age. Air pollution is an important social determinant of health. Public health initiatives that improve air quality are necessary to improve health outcomes. Full article

Background: High-voltage electrical injuries (HVEIs) represent a complex and life-threatening entity, frequently involving multi-organ damage. While traditionally linked to occupational hazards, train surfing—riding on moving trains—and train climbing—scaling stationary carriages—have emerged as increasingly common causes among adolescents. Popularized via social media, these behaviors expose individuals to the invisible danger of electric arcs from 15,000-volt railway lines, often resulting in extensive burns, cardiac complications, and severe trauma. This study presents a 30-year retrospective analysis comparing cardiac biomarkers and clinical outcomes in train-surfing injuries versus work-related HVEIs. Methods: All patients with confirmed high-voltage injury (≥1000 volts) admitted to a Level 1 burn center between 1994 and 2024 were retrospectively analyzed. Exclusion criteria comprised low-voltage trauma, suicide, incomplete records, and external treatment. Clinical and laboratory parameters—including total body surface area (TBSA), Abbreviated Burn Severity Index (ABSI), electrocardiogram (ECG) findings, intensive care unit (ICU) and hospital stay, mortality, and cardiac biomarkers (creatine kinase [CK], CK-MB, lactate dehydrogenase [LDH], aspartate transaminase [AST], troponin, and myoglobin)—were compared between the two cohorts. Results: Of 81 patients, 24 sustained train-surfing injuries and 57 were injured in occupational settings. Train surfers were significantly younger (mean 16.7 vs. 35.2 years, p = 0.008), presented with greater TBSA (49.9% vs. 17.9%, p = 0.008), higher ABSI scores (7.3 vs. 5.1, p = 0.008), longer ICU stays (53 vs. 17 days, p = 0.008), and higher mortality (20.8% vs. 3.5%). ECG abnormalities were observed in 51% of all cases, without significant group differences. However, all cardiac biomarkers were significantly elevated in train-surfing injuries at both 72 h and 10 days post-injury (p < 0.05), suggesting more pronounced cardiac and muscular damage. Conclusions: Train-surfing-related high-voltage injuries are associated with markedly more severe systemic and cardiac complications than occupational HVEIs. The significant biomarker elevation and critical care demands highlight the urgent need for targeted prevention, public awareness, and early cardiac monitoring in this high-risk adolescent population. Full article

Purpose: Despite increasing rates of prostate cancer among men, prostate cancer risk assessments continue to rely on invasive laboratory tests like prostate-specific antigen and Gleason score tests. This study aimed to develop a noninvasive, data-driven risk model for patients to evaluate themselves before deciding whether to visit a hospital. Materials and Methods: To train the model, data from the National Health Insurance Sharing Service cohort datasets, comprising 347,575 individuals, including 1928 with malignant neoplasms of the prostate, 5 with malignant neoplasms of the penis, 18 with malignant neoplasms of the testis, and 14 with malignant neoplasms of the epididymis, were used. The risk model harnessed easily accessible inputs, such as history of treatment for diseases including stroke, heart disease, and cancer; height; weight; exercise days per week; and duration of smoking. An additional 286,727 public datasets were obtained from the National Health Insurance Sharing Service, which included 434 (0.15%) prostate cancer incidences. Results: The risk calculator was built based on Cox proportional hazards regression, and I validated the model by calibration using predictions and observations. The concordance index was 0.573. Additional calibration of the risk calculator was performed to ensure confidence in accuracy verification. Ultimately, the actual proof showed a sensitivity of 60 (60.5) for identifying a high-risk population. Conclusions: The feasibility of the model to evaluate prostate cancer risk without invasive tests was demonstrated using a public dataset. As a tool for individuals to use before hospital visits, this model could improve public health and reduce social expenses for medical treatment. Full article

Hazards stemming from extreme natural events have exhibited heightened prominence in recent years. The natural hazard management process adopts a comprehensive approach that encompasses all stakeholders involved in the disaster management cycle. “Actions for Resilience” (A4R) represents a standardised concept derived from ISO/TR 22370:2020 that integrates principles from various scientific disciplines to enhance resilience in systems, whether they are socio-ecological systems, communities, or organisations. A4R emphasises proactive measures and interventions aimed at fostering resilience rather than merely reacting to crises or disruptions. It recognises that resilience is a multifaceted concept influenced by various factors, including social, economic, environmental, and institutional dimensions. Central to A4R is the understanding of complex system dynamics. Also, A4R involves rigorous risk assessment to identify potential threats and vulnerabilities within a system, as well as to build adaptive capacity within systems. A4R advocates for the development of resilience metrics and monitoring systems to assess the effectiveness of interventions and track changes in resilience over time. These metrics may include indicators related to social cohesion, ecosystem health, economic stability, and public infrastructure resilience. In this context, the study aims to apply the proposed hierarchy of factors and group decision-making using fuzzy numbers to identify strategic priorities for improving the urban resilience of the pilot area. The identified priority factors are then analysed across different scenarios, and corresponding actions are described in detail. Full article

Refugee settlements are often positioned around natural borders, which often have a heightened danger of environmental hazards. Here, we aim to better understand why settlements are in environmentally vulnerable land and what social and physical factors contribute to this phenomenon. To do this, we present a holistic narrative that maps climate threats among displaced populations in Cox’s Bazar district, Bangladesh, while contextualizing environmental vulnerability by incorporating historical and social constraints. Using ArcGIS, an online mapping program, we illustrate the overlap between different climatic events and how these vulnerabilities compound and intensify one another. We also discuss the history of natural migration and settlement pertaining to the physical landscape and the sociopolitical reasons refugees remain in environmentally vulnerable areas. Overall, we find an emerging trend that may be broadly applicable to instances of forced displacement; physical settlement locations near international borders demarcated by landforms may be more vulnerable to the effects of climate change and extreme climate events. However, physical, social, and political reasons often cement these locations. Recommendations include enhancing the resilience of refugee camps through infrastructure improvements, sustainable land management, and reforestation efforts, which would benefit both the environment and local and refugee communities. Full article