Search Results (1,319)

Population-based evidence on sleep quality in Kazakhstan remains limited. This study describes sleep quality as a multidimensional construct among adults in Kazakhstan using data collected during the first national survey wave after the adoption of a single national time zone. The survey was designed as a national post-transition baseline assessment and not as an evaluation of the causal impact of the time-zone reform. Associations with socio-demographic, behavioural, clinical, and regional factors were examined. We conducted a nationally representative cross-sectional survey of adults aged 18–69 years in Kazakhstan from May to October 2025 using a multistage stratified cluster design. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as a global PSQI score > 5. Complete PSQI data were available for 5872 participants. Descriptive analyses examined the global PSQI score and the seven component scores. Survey-weighted multivariable logistic regression was used to identify factors independently associated with poor sleep quality. The weighted prevalence of poor sleep quality was 28.1%, and the weighted mean global PSQI score was 4.43. The greatest component burden was attributable to sleep latency (mean 0.87), subjective sleep quality (0.82), and sleep disturbances (0.80), whereas use of sleep medication contributed minimally (0.11). Poor sleep quality was more common among women, older adults, urban residents, and participants with diabetes, current smoking, heavy episodic drinking, and depressive symptoms. In the adjusted model, female sex (aOR 1.37, 95% CI 1.19–1.57), age 55 years or older versus 18–24 years (1.98, 1.53–2.55), diabetes (1.47, 1.22–1.78), current smoking (1.28, 1.10–1.50), heavy episodic drinking (1.43, 1.16–1.76), and depressive symptoms (4.26, 3.52–5.15) were independently associated with higher odds of poor sleep quality. Rural residence was inversely associated with the outcome (0.71, 0.61–0.84). Compared with the North, higher odds were observed in the Central region (2.00, 1.46–2.74), East (1.94, 1.48–2.53), West (1.48, 1.17–1.88), and Almaty city (2.18, 1.72–2.76). Poor sleep quality is common among adults in Kazakhstan and is characterized primarily by difficulties with sleep initiation, perceived sleep quality, and nocturnal disturbances. The findings provide national post-transition baseline evidence and suggest that sleep health surveillance in Kazakhstan should prioritize demographic, mental health, behavioural, and regional inequalities while avoiding causal interpretation of the time-zone reform itself. Full article

Digital financial services have expanded rapidly across emerging economies and are often presented as tools for advancing women’s economic inclusion. However, the extent to which digital finance is associated with lower gender inequality depends on the broader structural conditions in which women live and work. This study examines the relationship between digital financial participation, labor market integration, and gender inequality in Brazil using nationally representative microdata from the 2025 Global Findex survey. Three outcomes are examined: digital account ownership, use of any digital payment, and engagement in merchant digital payments. Multivariate logit models show moderate gender gaps at early stages of digital financial participation. However, these gaps are not uniform across the population. The interaction results show that gender differences are concentrated mainly among individuals outside employment and among those without internet access. Among employed and digitally connected individuals, the gender gap becomes small and statistically insignificant across the three outcomes. A nonlinear decomposition shows that observable socioeconomic characteristics explain only a small share of the aggregate gender gap, especially for account ownership and any digital payment use. Additional robustness checks using probit and complementary log-log models support the main pattern of results. This suggests that the gender gap cannot be explained only by differences in education, income, employment, or internet access, and may also reflect unobserved household, institutional, or social constraints. The findings suggest that digital finance alone does not equalize participation. Rather, women’s digital financial participation is closely associated with their position in the labor market and their access to digital infrastructure. Because the analysis is based on cross-sectional data, the results should be interpreted as conditional associations rather than causal effects. Digital financial expansion is therefore more likely to support gender inclusion when it is linked to broader policies that strengthen women’s labor force attachment, digital connectivity, and economic autonomy. Full article

Background: Maternal mortality remains a major global health challenge, disproportionately affecting black and Indigenous women. Hypertensive disorders of pregnancy and postpartum hemorrhage are the leading direct causes of maternal death. Artificial intelligence (AI) tools have emerged as potential strategies for predicting these complications, yet concerns persist about their equity and validation across racial groups. Methods: A rapid review was conducted in five databases, PubMed, EMBASE, Web of Science, Scopus and LILACS, to synthesize recent evidence on the use of AI for preventing maternal mortality due to hypertension and postpartum hemorrhage. Studies published in the last five years that included racial or ethnic data were selected and analyzed narratively. Results: Ten studies met the inclusion criteria, showing high predictive accuracy of AI models (AUROC often >0.95) for severe maternal outcomes. However, few models incorporated racial variables or underwent external validation in racially diverse or low-resource populations. Evidence suggests that unrepresentative datasets may perpetuate or exacerbate existing health inequities. Conclusions: AI demonstrates strong technical performance in predicting maternal complications but limited equity in application. Broader racial representation, external validation, and ethical governance are essential for ensuring that AI-based tools reduce rather than reinforce racial disparities in maternal mortality. Full article

The global energy transition is frequently advocated as a means to achieve environmental sustainability. However, its distributional impacts remain inadequately understood, particularly in developing nations where approximately 666 million individuals still lack access to electricity. This study investigates whether the expansion of renewable energy consumption mitigates or exacerbates socioeconomic inequality across 82 developing economies from 2000 to 2022. Employing a multi-method econometric framework that considers cross-sectional dependence, heterogeneity, and nonlinear dynamics, we analyze three dimensions of equity: income inequality, monetary poverty, and disparities in electricity access between urban and rural populations. The findings reveal a complex relationship. While the expansion of renewable energy is associated with improvements in income distribution, it is also linked to persistent poverty and unequal access to energy services. This tension reflects what we term the “biomass paradox,” wherein the continued reliance on traditional biomass in low-income countries constrains the inclusiveness of energy transitions. Quantile regression analysis reveals that the effect of renewable energy reverses across the distribution: renewable energy slightly widens the energy access gap in countries where disparities are already small, but narrows it substantially in countries where the gap is widest. The results further indicate that the equity effects of renewable energy vary across contexts and are particularly sensitive to initial conditions and institutional capacity. In settings with weak governance, renewable expansion shows no statistically distinguishable effect on equity outcomes, whereas in stronger institutional environments, its effects become more transformative. These findings suggest that aggregate renewable energy targets that do not differentiate between traditional and modern sources may be misleading. More broadly, achieving a just energy transition necessitates not only expanding renewable capacity but also strengthening governance frameworks and directing investments toward contexts where energy inequalities are most pronounced. Full article

Background: Dementia and Type 2 diabetes (T2D) represent two of the most pressing global public health challenges of our time, both exacerbated by physical inactivity. These conditions disproportionately affect Global Majority populations, who experience earlier onset, higher prevalence, and poorer access to culturally appropriate preventive care. However, conventional research and interventions often overlook the sociocultural and structural factors that underpin this disparity. This study synthesises current evidence to understand how these three conditions intersect and to identify equitable pathways for prevention and support. Methods: A meta-narrative review approach was employed to integrate evidence from diverse biomedical, public health, sociocultural and intervention science traditions. Searches were undertaken across MEDLINE/PubMed-adapted searches, CINAHL, PsycINFO, Web of Science Core Collection, AMED and ASSIA, supplemented by grey literature searching and citation chasing. Five meta-narratives were identified: biomedical and epidemiological, public health, health disparities, sociocultural and behavioural, and intervention science. Cross-narrative synthesis produced a conceptual framework linking upstream determinants, lifestyle factors, and disease outcomes. Results: The review revealed that structural inequities such as deprivation, environmental barriers and sociocultural factors including stigma, gendered norms, limited access to culturally appropriate facilities that restrict physical activity (PA) opportunities within Global Majority communities. These constraints elevate T2D and dementia risk through biological pathways involving insulin resistance, vascular injury, and neuroinflammation. Community-based participatory research (CBPR) interventions particularly those delivered in trusted cultural or faith settings emerged as effective strategies to improve PA, glycaemic control, and cognitive well-being. Conclusions: This synthesis reframes dementia and diabetes as interlinked within a wider syndemic driven by structural and sociocultural inequities. The proposed framework underscores the importance of culturally grounded, community-led approaches to promote brain health, reduce risk, and achieve equitable healthy ageing among Global Majority populations. Full article

Climate change represents one of the defining global health challenges of the 21st century, with far-reaching implications for population health, health systems, and health equity. The acceleration of environmental change, evidenced by record-breaking global temperatures, extreme weather events, and ecological degradation, poses a direct threat to achieving Sustainable Development Goal 3 (SDG 3), which aims to ensure healthy lives and promote well-being for all. This manuscript presents a narrative review and policy analysis of the intersection of climate change and global public health in light of the outcomes of the 2025 United Nations Climate Change Conference (COP30) in Belém, Brazil. Drawing on peer-reviewed literature, major institutional reports, and relevant policy documents, we explore how climate change exacerbates communicable and non-communicable diseases, undermines health system resilience, and disproportionately affects vulnerable populations worldwide. Particular attention is given to heat-related morbidity, infectious disease expansion, air pollution, food and water insecurity, displacement, gender inequities, antimicrobial resistance, and mental health impacts. The paper highlights the significance of the Belém Health Action Plan (BHAP), which is treated here as a COP30-associated action framework that places health more centrally within climate policy discussions. However, major challenges remain, including its voluntary orientation, the absence of dedicated financing mechanisms within the framework itself, and limited clarity on accountability arrangements, as identified through our synthesis of the available policy and evidence base. We argue that achieving SDG 3 is no longer feasible without integrating climate adaptation and mitigation into health systems and policies, and that progress will depend on translating global commitments into context-specific country strategies, governance arrangements, and implementation pathways. Full article

The paper is concerned with three-dimensional Hall-magnetohydrodynamics for partial viscosity terms. By applying basic inequality and energy estimates, we prove the global existence of classical solution for small initial data. Additionally, the local existence of classical solution is also obtained. The smallness conditions are given by the suitable Sobolev norms. Furthermore, the existence of classical solutions with large initial data can be obtained when the coefficients of viscosity sufficiently large. Full article

This paper investigates the problem of exponential synchronization for a class of quaternion-valued inertial neural networks with mixed time delays under aperiodic intermittent control. First, a neural network model incorporating both discrete and distributed delays is established. To overcome the limitations of conventional approaches, a novel quaternion-based controller is proposed, which operates without relying on model order reduction or quaternion decomposition techniques, thereby achieving global exponential synchronization of the system. Furthermore, by constructing an appropriate Lyapunov function and combining the algebraic properties of quaternions with inequality techniques, sufficient conditions for synchronization are rigorously derived within the Lyapunov stability framework. Numerical simulations are conducted to demonstrate the effectiveness of the proposed control strategy and validate the theoretical results. Finally, an image encryption application is developed to further corroborate the practical viability of the proposed scheme, wherein the original image is encrypted into a noise-like pattern without information leakage and perfectly recovered upon synchronization, with quantitative error analysis confirming high-precision exponential synchronization. Full article

Urban infrastructure is crucial to urban development and determines urban functionality, resilience, and sustainability. Effective planning for urban infrastructure development and municipal services driving economic development and improving the quality of urban life. However, many urban areas of countries in the Global South suffer from contextually inappropriate urban planning. This has led to uncontrolled expansion, urban sprawl and inadequate public infrastructure. This study answers the following research questions: What are the main challenges in urban and infrastructure planning, and what are possible solutions to mitigate them for sustainable urban development? Based on a review of 75 studies, keyword co-occurrence analysis and thematic analysis reveal seven key challenges in urban infrastructure planning: governance and institutional challenges; economic constraints and funding gaps; environmental and climate change challenges; urbanization and population growth; technological gaps and innovation difficulties; political instability and conflict; and social inequality and exclusion. To mitigate these issues, this study suggests that the concerned policymakers in the Global South prioritize governance and institutional reform, adopt technological and nature-based solutions and strengthen public–private partnerships, community-based engagement, and capacity building. Full article

This paper proposes finite-time (FT) and fixed-time (FXT) neurodynamic models with time-varying coefficients for solving inverse quasi-variational inequality problems (IQVIPs). Two projected models with time-dependent gains are developed to enhance convergence speed and transient performance. A nominal model establishes the equivalence between equilibrium points and IQVIP solutions. Under Lipschitz continuity and strong monotonicity assumptions, the existence, uniqueness, and global convergence of the proposed models are ensured. By employing Lyapunov stability theory, finite-time and fixed-time convergence of the continuous-time models are rigorously established, where explicit settling-time bounds independent of initial conditions are derived for the FXT case. Furthermore, the robustness of the proposed models under bounded disturbances is analyzed. To validate the theoretical findings, a discrete-time implementation based on the forward Euler method is developed. Numerical experiments demonstrate that all trajectories converge within a uniform upper bound, showing convergence behavior consistent with the fixed-time characteristics of the continuous-time model. Although the convergence time varies with initial conditions, it remains uniformly bounded, which is consistent with the fixed-time stability characteristics of the continuous-time model. The proposed framework provides a computationally efficient and scalable approach for solving IQVIPs, with potential applications in traffic equilibrium, communication networks, distributed control systems, and multi-agent coordination. Its adaptive structure and fixed-time convergence properties make it particularly suitable for real-time optimization in dynamic and uncertain environments. Full article

Methane emission reduction represents a critical pathway for near-term climate mitigation. Super-emitter control is widely recognized as the most cost-effective mitigation strategy; however, the prevalence of these sources varies significantly across countries and sectors, resulting in heterogeneity in abatement difficulty and policy priorities. In this study, we integrate recently emerging satellite-based point-source emission datasets to develop a cross-scale analytical framework that systematically characterizes methane emission rate distributions across countries and sectors. Analysis of the full Carbon Mapper dataset shows that sources exceeding 5000 kg h⁻¹ account for only 3.34% of total point sources, yet contribute more than 25.18% of total equivalent emissions. Gini coefficients range from 0.46 to 0.60 across countries, indicating pronounced inequality in emission distributions and mitigation costs. Integrating these distributional characteristics with economic capacity indicators further shows that countries with highly concentrated, high-intensity point sources—particularly oil- and gas-dominated nations such as Turkmenistan and Uzbekistan—offer the highest cost-effective mitigation potential and should be prioritized as global methane action breakthroughs. Among these, economically advanced countries are positioned to lead by demonstration, while nations with high mitigation potential but limited economic capacity represent optimal targets for international climate finance and technology transfer. These findings provide satellite-derived evidence to inform differentiated, country- and sector-specific mitigation pathways. Full article

Amid intensifying climate crises, widening inequalities, and geopolitical volatility, spatial economic resilience (SER) has become critical for regions facing systemic uncertainty. Traditional land-intensive productivity models prove increasingly untenable as spatial resources become finite and development space constrained. China’s new quality productivity (NQP) has emerged as a strategic response emphasizing innovation-driven structural renewal and territorial coordination. Conceptually, NQP is positioned as a SER-oriented strategy prioritizing adaptability, recoverability, and transformability. However, its actual associations remains theoretically overlooked and empirically untested, with existing research viewing it narrowly as technological upgrading while neglecting institutional dimensions, spatial dependencies, and multi-scalar heterogeneities. This study explores how NQP relates to SER from a spatio-temporal perspective: (1) How do the technological and institutional dimensions of NQP relate to SER? (2) What are the spatial patterns of NQP-SER associations across multi-scale locations? Employing XGBoost-SHAP, spatial generalized difference-in-differences, and Geographical Gaussian Process Regression across provincial, city, and enterprise scales in China, we find that NQP’s two dimensions relate to SER very differently. The technological–industrial dimension is the strongest predictor of SER at the provincial scale, exhibiting threshold-type, non-linear associations, while its predictive salience attenuates at the city and enterprise scales, where industrial structure and firm-specific fundamentals are more strongly associated with resilience. The institutional dimension, by contrast, is not positively associated with above-expectation resilience: once common shocks and provincial heterogeneity are absorbed, higher institutional policy intensity is negatively associated with SER, both within provinces and across neighbouring provinces. Spatially, provincial associations rely on coordination and interregional spillovers, while city associations concentrate in nodal clusters where the strength of association depends on capability–context alignment. The findings provide practical theoretical and analytical guidance for tailored policy-making in structurally diverse Global South facing ongoing uncertainty. Full article

Background: Ageism is a global public health concern associated with poorer health outcomes and inequities in care. Culturally adapted instruments are needed to assess ageist attitudes among healthcare professionals in Spain. This study aimed to cross-culturally adapt and evaluate the preliminary psychometric properties of the Spanish version of the Fraboni Scale of Ageism (FSA-SV). Methods: A methodological study was conducted, including translation and back-translation, expert review, and a pilot test. Content validity was assessed using the content validity index (CVI), the modified kappa coefficient, and Aiken’s V. A descriptive cross-sectional pilot study was conducted with 101 healthcare professionals from a single health department in Valencia to evaluate comprehension and reliability. Internal consistency was examined using Cronbach’s alpha and McDonald’s omega. Results: Content validity indices indicated acceptable agreement among experts (S-CVI = 0.745; Aiken’s V = 0.770). All items were retained to preserve conceptual and structural equivalence with the original instrument. The FSA-SV demonstrated high internal consistency (Cronbach’s alpha = 0.903; McDonald’s omega = 0.915). The mean total score was 51.2 (SD = 9.62), with no significant associations observed between ageism and participants’ sociodemographic or professional variables. Conclusions: This pilot study represents a first step in the cross-cultural adaptation and preliminary psychometric evaluation of the FSA-SV for use among healthcare professionals in Spain. The results suggest that the instrument shows promising initial properties for the preliminary assessment of ageism, supporting its potential utility in future research and in evaluating educational and organizational interventions aimed at reducing ageism and improving the quality and safety of care for older adults. Further studies with larger, more diverse samples are required to evaluate additional psychometric properties, including the factorial structure. Full article

We develop a fast Chebyshev spectral collocation method for a coupled system of nonlinear Klein–Gordon equations augmented by Caputo-type fractional memory integrals. The governing equations retain the classical second-order time derivative as the leading operator and incorporate weakly singular convolution integrals modelling viscoelastic memory damping. The spatial discretisation employs Chebyshev–Gauss–Lobatto collocation, while the temporal integration uses a Newmark scheme (${\beta }_{\mathrm{NM}}=1/4$) combined with an implicit–explicit linearisation in which the linear spatial operator is treated implicitly and the nonlinear terms are treated explicitly through a second-order extrapolation. This linearisation eliminates the need for Newton–Raphson iterations at each time step. To overcome the dense memory bottleneck arising from two distinct fractional orders $\alpha \ne \beta$, the convolution memory kernels are compressed by independent sum-of-exponentials approximations obtained from a double-exponential quadrature of the kernel’s integral representation, which significantly reduces the computational complexity of the history term. A rigorous stability estimate and a global convergence bound are established using a discrete Grönwall inequality. Numerical experiments confirm the theoretical temporal and spatial convergence rates and demonstrate the practical speed-up afforded by the sum-of-exponentials acceleration. A solitary wave collision scenario illustrates the method’s capability to capture asymmetric dispersive wakes generated by the fractional memory. Full article

Open fiscal data in Ecuador remains largely unexplored beyond basic descriptive reporting, despite its potential for territorial intelligence and fiscal planning. This study examines how taxpayers are distributed across Ecuador’s provinces and economic sectors by applying a Big Data pipeline built on Apache Spark 3.5, PostgreSQL 14/PostGIS 3.2, and Python 3.11 spatial libraries to the SRI Tax Registry, comprising approximately 2.5 million records. The analysis combined K-Means and DBSCAN clustering with spatial autocorrelation methods, including Moran’s Index and LISA, to identify concentration patterns and territorial dependencies. The findings show that 68% of taxpayers are located in three provinces, namely Pichincha (34%), Guayas (24%), and Azuay (10%), with a spatial Gini coefficient of 0.61 reflecting considerable fiscal inequality across the country. A Global Moran’s Index of 0.49 (p < 0.001) confirms that neighboring provinces tend to share similar taxpayer densities, while LISA revealed five High–High clusters in major urban centers and six Low–Low clusters in the Amazon region and northern border. DBSCAN identified 27 spatial groupings, including secondary economic nuclei in cities like Ambato, Riobamba, and Machala that autocorrelation models alone do not capture. The methodology is replicable and offers a practical basis for designing place-based fiscal policies in similar contexts. These results provide tax authorities and regional planners with an empirically grounded, scalable framework for identifying territories with fiscal formalization gaps and designing geographically targeted interventions to reduce territorial inequality in Ecuador and in comparable developing-country contexts. Full article