Search Results (3,294)

Background: The Canada Health Act (CHA), enacted in 1984, guarantees universal access to medically necessary care, yet inequities in hospital use persist. Acute length of stay (ALOS) is a key indicator of hospital efficiency, patient recovery, and healthcare system performance, with prolonged stays linked to higher costs, avoidable infections, and strain on acute care capacity. Understanding patterns in ALOS is critical not only for hospital management but also for public health, as extended stays can limit timely access to care and exacerbate population-level health inequities. Objective: This study examines social, geographic, and clinical gradients in ALOS and investigates whether the effects of admission urgency vary by sex, neighbourhood income, and rural–urban residence within a universal healthcare system. Methods: Using 2024–2025 hospital discharge data from the Canadian Institute for Health Information, this study examined ALOS as a function of comorbidity, sex, socioeconomic status, rural–urban residence (geography), and admission type (urgent versus elective). Interaction effects between admission urgency and key social and geographic variables were evaluated to assess subgroup differences in ALOS. Results: Disparities in ALOS were evident. Older age, male sex, urgent admission, and greater comorbidity were associated with longer stays, whereas higher neighbourhood income and urban residence were linked to shorter stays. Interaction analyses revealed substantial heterogeneity: compared with elective rural admissions, urgent urban admissions had 30.4% longer ALOS. Urgent admissions also amplified socioeconomic and sex-based differences, with male patients experiencing 27.9% longer stays than females. Conclusions: From a public health perspective, these findings highlight how system capacity constraints and social inequities jointly shape hospital use. Reducing avoidable variation in ALOS will require policies that strengthen acute care surge capacity, improve coordination for urgent admissions, and address upstream socioeconomic and geographic barriers to care, thereby promoting more equitable and efficient hospital services. Full article

As key headwater regions of the upper Yangtze River, the Yalong and Dadu River basins are expected to experience highly uncertain hydrological responses under climate warming. However, the nonlinear and spatially heterogeneous evolution of streamflow across multiple time-frequency scales remains insufficiently understood. In this study, a SWAT model driven by CMIP6 climate projections under four shared socioeconomic pathways (SSP1-2.6 to SSP5-8.5) was coupled with multivariate wavelet coherence, spatial wavelet transform, and change-point detection methods to investigate the spatiotemporal evolution of streamflow and extreme risks during 2017–2100. Results indicate that precipitation is the primary driver of streamflow variability, with streamflow responding rapidly, while air temperature mainly regulates seasonal intensity via snowmelt. Streamflow seasonal intensity exhibits a northwest-southeast gradient, with low variability upstream and high sensitivity downstream, reflecting precipitation-concentrated, forested canyons where rapid lateral flow and dry-season evapotranspiration amplify flow contrasts. Moreover, hydrological nonstationarity and extreme risks are projected to intensify, with structural regime shifts emerging in the 2040s–2050s and extreme high-flow magnitudes doubling under SSP5-8.5, accompanied by more frequent drought-flood alternations. These findings highlight an upstream buffering-downstream sensitivity pattern, emphasizing the need for spatially differentiated water resources management under nonstationary climate conditions. Full article

Toxoplasma gondii establishes latent infection in a substantial proportion of the global population, yet the long-term health consequences of this infection remain incompletely characterized. We conducted a retrospective observational matched cohort study using longitudinal electronic health record data from a nationwide integrated healthcare provider, including members aged 18–45 years who underwent routine Toxoplasma serologic screening, typically performed in obstetric evaluation, excluding patients with clinical toxoplasmosis, immunosuppression, or HIV. Seropositive individuals were matched 1:1 without replacement to seronegative controls to align demographic, temporal, and socioeconomic variables. Time-to-event associations with predefined medical conditions were evaluated using Cox proportional hazards models with false discovery rate correction. The final cohort included 19,443 seropositive individuals and 19,443 matched controls (96.7% female), with a tight baseline balance of demographic and temporal characteristics. During follow-up, seropositivity was associated with increased risks of tobacco dependence (aHR 1.65), alcohol dependence (2.32), suicide attempt (1.82), motor vehicle accidents (1.22), and work accidents (1.27), as well as multiple infectious conditions, including hepatitis B (1.55), hepatitis C (2.15), and syphilis (2.43), with an overall trend toward increased all-cause mortality (1.32, 95% CI [1.00–1.74]). These findings suggest that asymptomatic Toxoplasma infection in young adults is associated with increased long-term behavioral and medical comorbidity. Full article

Artificial light at night (ALAN) data is widely used in urban function analysis and socio-economic activity monitoring, but its application at the micro-scale of cities still faces challenges. This study utilizes high spatial resolution SDGSAT-1 nighttime light data to explore the spatial heterogeneity of ALAN at the street scale in two representative Chinese cities—Beijing and Guangzhou. By integrating multi-source data (such as building vector data, road networks, and point of interest data), a multi-dimensional indicator system covering urban morphology, functional structure, and transportation accessibility is constructed. Based on this, the study employs a Geographically Weighted Random Forest (GWRF) model combined with the Shapley Additive Explanations (SHAP) method to deeply analyze the non-linear relationships between ALAN intensity and multiple driving factors, as well as their spatial variability. Results demonstrate the superiority of the GWRF model over global models in capturing spatial non-stationarity, with R² values of 0.67 for Beijing and 0.74 for Guangzhou, compared to 0.62 and 0.71 for the random forest models, respectively. Road density is the dominant factor influencing nighttime light intensity in both Beijing and Guangzhou. However, the relationship between ALAN and its driving factors varies across these cities. In Beijing, a balanced multi-factor model is observed, whereas in Guangzhou, ALAN intensity is primarily driven by road density, with secondary influences from other factors like sky view factor. This study validates SDGSAT-1 for micro-scale analysis, offering a scientific basis for differentiated urban lighting planning. Full article

Housing prices exert a notable impact on labor force sustainability, a key component of socioeconomic sustainable development. Skyrocketing housing costs tend to postpone young adults’ marriage and childbearing schedules, reduce their fertility intentions, and eventually lead to a shrinking labor force. It is therefore essential to explore the intrinsic links between housing prices, fertility intentions, and labor force sustainability. Based on data on China’s commercial housing prices, fertility rates, and related socioeconomic indicators from 2005 to 2024, this paper analyzes the theoretical mechanisms of how housing prices affect fertility intentions. It examines the trends of housing prices, housing price-to-income ratios, and disposable income growth at the national level, and further discusses the heterogeneous characteristics of these indicators in eastern, central, western, and northeastern China. In addition, this study analyzes the overall trends and regional disparities of fertility rates, conducts regression analyses combined with mortality rates and population growth rates, and implements correlation analyses between housing prices and fertility rates at national and regional levels. Using 2018 and 2022 CFPS data with control variables including education years, household registration type, employment nature, gender, and number of siblings, an improved interaction terms fixed-effects model is adopted to empirically examine the impact of housing prices on fertility intentions. The reliability of the results is verified by three methods: parallel trend test, alternative estimation method, and data source replacement. Full article

Frequent flash floods threaten human well-being, hydropower infrastructure, and ecosystems. However, the long-term evolution of flash flood patterns over recent decades remains insufficiently understood, particularly in data-scarce high-altitude regions. Using multi-source remote sensing data integrated with historical disaster records and field investigations, this study examined the spatiotemporal evolution and driving factors of flash floods across the Qinghai–Tibet Plateau (QTP). The results indicate that flash floods have increased exponentially, which may be influenced by disaster management policies, with peaks in July–August and frequent occurrences from April to September. The seasonal trajectory of the center of gravity of flash floods from April to September exhibited a clear directional pattern. Regions with the highest disaster density were concentrated in the headwaters of five major rivers, including the Yarlung Zangbo, Jinsha, Nu, Lancang, and Yellow Rivers. Shapley Additive Explanation (SHAP) and Random Forest analyses reveal that soil moisture, anthropogenic intensity, and seasonal runoff variability are the dominant driving factors. With ongoing socioeconomic development, intensified human activities have become a key contributor to the increasing frequency of flash floods. These findings highlight the value of remote sensing-based assessments for flash flood monitoring and early warning and provide scientific support for risk mitigation, loss reduction, and the advancement of water-related targets under the United Nations’ Sustainable Development Goals. Full article

This study presents a comparative analysis of residential segregation among the three largest foreign-born populations residing in Spain: Moroccans, Romanians, and Colombians. Using data from Spain’s Population and Housing Census (INE), the research analyzed the segregation index across 34 urban areas in medium-sized cities. Three urban areas in Catalonia were selected for the intraurban case studies, and Pearson correlation coefficients were calculated for 60 sociodemographic variables. The objectives were to identify indicators that helped diagnose potential segregation contexts and to explore residential patterns by country of origin. The study was grounded in a central premise: the foreign-born population cannot be treated as a homogeneous group, as aggregation conceals group-specific inequalities and differentiated spatial configurations. The findings showed that segregation occurred. Moroccans exhibited the highest levels of segregation, which was associated with socioeconomic vulnerability and also a marked residential preference for central urban areas. Colombians displayed lower levels of segregation and greater territorial dispersion, pointing to broader residential access. Romanians presented intermediate and heterogeneous patterns, which combined localized concentrations with peripheral settlement. The results highlighted how intraurban differentiation emerged from interactions between different migrant profiles, housing opportunity structures, and urban morphology, providing an empirical basis on which to design targeted urban policies. Full article

Maternal vaccination against respiratory syncytial virus (RSV) represents a major advance in early-life infection prevention. Although clinical efficacy and early real-world effectiveness are well established, sustained population-level impact depends on equitable uptake. This review synthesizes determinants influencing maternal RSV vaccination within the evolving dual-strategy landscape that includes both maternal vaccination and infant monoclonal antibody prophylaxis. A structured narrative review was conducted following PRISMA principles. PubMed/MEDLINE and Google Scholar were searched for studies published between January 2022 and February 2026. Eligible studies examined behavioral, interpersonal, structural, economic, and policy determinants of maternal RSV vaccination uptake, as well as early implementation and modelling evidence. Findings were integrated within a multilevel analytical framework. Maternal uptake is shaped by interacting determinants across individual, healthcare provider, and health system domains. Key drivers include perceived infant disease severity, vaccine safety confidence, perceived effectiveness, and prior antenatal vaccination behavior. Healthcare provider recommendation consistently emerges as the strongest facilitator. Coverage variability reflects differences in reimbursement, antenatal care integration, and national policy endorsement. The coexistence of maternal vaccination and infant monoclonal antibody strategies introduces additional comparative decision-making complexity. Early implementation data indicate heterogeneous uptake and socioeconomic gradients, while modelling demonstrates sensitivity to coverage, timing, epidemiology, and cost. Translating biological efficacy into sustained public health benefit requires coordinated behavioral, structural, and policy strategies, strong provider engagement, and context-sensitive implementation frameworks to ensure equitable coverage. Full article

Objectives: While the previous literature has established that meteorological conditions are associated with COVID-19 mortality fluctuations, the relative effect of each of these highly correlated factors remains unclear. This study aims to conduct a comparative analysis to determine which of three main meteorological variables—Ambient Temperature, Ultraviolet (UV) Index, and Sunlight Duration—have the strongest negative association with COVID-19 mortality. The objective is to quantify and rank their impact over a 7-to-21-day biological exposure window. Methods: We conducted retrospective spatiotemporal analyses in the form of panel Poisson Distributed Lag Models (PDLMs) regression using daily data from 21 January 2020 to 10 January 2023, spanning 129 distinct geographical regions worldwide. To ensure a direct and fair comparison of effect sizes, all meteorological and environmental variables were Z-score standardized. We estimated three independent PDLMs—each focusing separately on UV Index, Ambient Temperature, and Sunlight Duration—with lags ranging from 7 to 21 days. These models controlled for overarching time trends and utilized a categorical variable to account for Region Fixed Effects modeling time-invariant regional health and socioeconomic determinants (e.g., obesity, age demographics, healthcare capacity). Furthermore, distributed lags of daily PM2.5 (air pollution) and relative humidity were explicitly included in each model as dynamic confounders. Results: The comparison of PDLM results reveals that the UV Index has the strongest negative association with COVID-19 mortality. A one standard deviation increase in the UV Index corresponds to a massive, highly significant cumulative reduction in deaths observed 1 to 3 weeks later (p < 0.001). Sunlight Duration is the second-strongest protective meteorological factor, whereas Ambient Temperature has the weakest effect. The distributed lags of particulate matter (PM2.5) and relative humidity were found to be statistically insignificant when modeled alongside the meteorological variables. Conclusions: After standardizing variables and controlling for dynamic environmental confounders like air pollution and humidity, the study findings provide robust empirical evidence that meteorological conditions have a strong significant association with COVID-19 mortality fluctuation with a temporal delay, overcoming the confounding effects of merely dry or clear-air conditions. Full article

Does where an incident happens affect how quickly first responders arrive? Timely emergency responses are important to urban safety. However, the combined influence of street-level environments, operational conditions, and neighborhood contexts on dispatch performance remains unclear. We examined such geographical complexity by modeling geographic predictors for whether emergency vehicles successfully arrived at incidents in the city of Dallas within the city’s eight-minute benchmark. Using 250,647 incidents and 56 million GPS points along emergency dispatch routes in 2016, we compiled fourteen spatial and operational variables for every incident to train a Bayesian-optimized random forest classifier. The fourteen variables characterized street network topology, roadway attributes, land use, and socioeconomic status, and the model achieved an accuracy of 77.26% in predicting whether emergency response arrived at an incident within eight minutes. A longer distance to dispatch stations, dispatching from non-nearest stations, and low street–network integration were the strongest predictors of unsuccessful responses. Higher-income areas showed slightly elevated unsuccessful rates linked to frequent construction-related disruptions. These findings highlight emergency response as a coupled spatial–operational–temporal process and underscore the need for context-sensitive dispatch strategies and coordinated urban planning. Full article

Smallholder farming remains a critical livelihood source for rural communities in South Africa, particularly in the Eastern Cape Province. However, cropland abandonment has become an escalating concern, undermining food security, household incomes, and the long-term sustainability of agricultural systems. This study assessed the socio-economic and climate-related factors influencing cropland abandonment in the former homelands of Transkei. A mixed-methods approach was used, combining a quantitative survey, a qualitative focus group discussion, and a key informant interview. Data were analysed using descriptive statistics, a double-hurdle model, and thematic analysis. The descriptive results revealed that the average respondent was 57 years, with a predominantly male majority (57.47%), a primary education (40.27%), and a mean average household size of 5.4. About 51.58% of household heads were married and 48.42% were single, with a mean household income of R63 155 (3680.26 USD). The econometric results from the first hurdle model indicated that education level, farming experience, rainfall variability, access to irrigation, and off-farm income significantly influenced the decision to abandon cropland. The second hurdle model demonstrated that the extent of cropland abandonment was shaped by labour availability, access to credit, rainfall patterns, cooperative membership, and farming experience. The study concluded that cropland abandonment in the former Transkei was influenced by different factors. Therefore, the study would recommend targeted policy interventions that strengthen human capital, improve access to agricultural support services, and promote youth participation and collective farming structures to revitalise smallholder agriculture and enhance rural food security. Full article

The Jordan Valley, a critical agro-ecosystem in Jordan, faces escalating challenges from chronic water scarcity compounded by environmental and socio-economic pressures, necessitating a systems perspective to understand cross-sector interactions beyond isolated sectoral issues. This study interprets socio-ecological interactions influencing sustainability outcomes in the region and identifies key feedback loops and adaptive responses under water scarcity through an integrated Socio-Ecological Systems (SES) and Water–Energy–Food–Ecosystems (WEFE) framework. Employing a qualitative document analysis (QDA) design, a purposive collection of peer-reviewed studies and institutional publications (n = 50) published between 2002 and 2025 was assembled and systematically coded using a structured deductive–inductive strategy grounded in SES components and WEFE domain interactions. Results reveal seven interconnected themes: water scarcity as a structural constraint, agricultural intensification and resource pressures, climate change as a stress multiplier, ecosystem degradation and service loss, pollution and environmental quality challenges, socio-economic vulnerability and livelihood constraints, and fragmented governance with coordination gaps. These themes highlight reinforcing loops where scarcity promotes groundwater reliance and non-conventional water use, intensification heightens salinity and contamination risks, climate variability escalates irrigation demands, and ecological degradation diminishes buffering capacity, while socio-economic limitations hinder adaptation and governance fragmentation impairs integrated planning and enforcement. While prior studies have examined water scarcity, agricultural intensification, or climate impacts in isolation, this study advances the literature by synthesizing these dynamics through an integrated SES–WEFE analytical lens, revealing reinforcing system feedbacks and governance constraints that are not visible within single-sector or descriptive syntheses. Full article

Wild edible fruits (WEFs) represent an important yet underutilised component of biodiversity-based nutrition and functional food research. This structured narrative review critically synthesises current evidence on the phytochemical composition and nutritional relevance, biological activities, and sustainability dimensions of WEFs, with emphasis on fruit pulp as the primary edible tissue. A systematic search strategy following PRISMA-based principles was applied to enhance methodological transparency; however, due to high heterogeneity in species, analytical methods, and outcome measures, quantitative meta-analysis was not feasible. The review integrates compositional data (phenolics, carotenoids, tocopherols, sterols, vitamin C, and minerals) with reported bioactivities, while explicitly distinguishing between in vitro assays, in vivo studies, and limited clinical evidence. Particular attention is given to analytical variability, bioavailability constraints, dose–response relationships, and translational limitations that affect the interpretation of antioxidant and other health-related claims. Beyond bioactivity, the manuscript contextualises WEFs within socio-economic, conservation, and sustainable food system frameworks. By combining chemical characterisation, evidence hierarchy, and sustainability analysis, this review provides a critical and multidisciplinary perspective that advances understanding of WEFs and identifies priorities for future research, including standardised methodologies and well-designed human intervention trials. Full article

Understanding the long-term production trends of MDFLAM panels, which are widely used in panel furniture manufacturing, is important for evaluating the sector’s competitiveness and environmental performance. In this study, MDF/HDF production data for Türkiye covering the period 1995–2024 were analyzed. The observations for 1995–2019 were used for model estimation, while the period 2020–2024 was reserved for out-of-sample validation. Production projections for 2025–2030 were generated using the ARIMA time series model. The relationships between fiberboard production and selected socio-economic variables (population, GDP per capita, forest area, and number of enterprises) were evaluated through correlation analysis. While strong correlations were observed in the level data, additional analysis using first-differenced (growth rate) series indicated that these relationships are weak and statistically insignificant in the short term, suggesting that the observed associations are largely influenced by common time trends. Assuming that approximately 60% of total fiberboard production consists of MDFLAM, future GWP values were estimated using verified EPD data. The results indicate that production is expected to continue increasing in the coming years. Although negative GWP values are observed due to biogenic carbon storage during the production stage, this reflects temporary carbon sequestration rather than a permanent reduction in atmospheric emissions. Emissions are expected to increase during end-of-life stages as the stored carbon is released. Overall, the study provides a forward-looking framework by integrating time-series forecasting with EPD-based environmental indicators, offering a useful basis for sustainability assessment and policy-oriented decision-making in the wood-based panel sector. Full article

This study identifies motivational profiles among high school students regarding access to the University of Guanajuato, Yuriria Campus, within the framework of Sustainable Development Goal 4 (SDG 4). Using a survey of 306 students from diverse public and private institutions in southern Guanajuato, we applied K-means clustering analysis with validation techniques (elbow method, silhouette, bootstrap) to examine five key dimensions: family support, university interest, academic perception, transport accessibility, and self-efficacy. The analysis revealed three distinct profiles: (1) “Privileged and committed” (21%), with high scores in all variables and predominantly from private schools; (2) “Supported but not captivated” (65%), with moderate resources but low specific interest in the institution; and (3) “Vulnerable and disconnected” (14%), facing multiple barriers including low family support, economic constraints, and rural origin. ANOVA confirmed significant differences between clusters (p < 0.001). The inclusion of socioeconomic variables allowed for a deeper characterization of equity gaps. These findings provide evidence-based insights for designing targeted recruitment and retention strategies aligned with SDG 4, demonstrating how educational data analytics can inform sustainable higher education policies in regional contexts. Full article