Search Results (237)

Background/Objectives: Childhood cancer outcomes are influenced by clinical, socioeconomic, and territorial factors, particularly in resource-limited settings. This study characterized pediatric cancer patients from Córdoba and Sucre, Colombia, and evaluated factors associated with clinical outcomes in a regional referral center. Methods: A retrospective hospital-based study included 434 patients aged 0–18 years diagnosed between 2018 and 2024. Sociodemographic, clinical, and territorial socioeconomic variables were analyzed using the Multidimensional Poverty Index (MPI). Clinical outcomes were classified as favorable, non-favorable, or death. Firth-penalized logistic regression models were used to assess adjusted associations. Results: Hematologic malignancies predominated (65.9%), with acute lymphoblastic leukemia as the most frequent diagnosis. Most patients came from municipalities with moderate or high multidimensional poverty (85.2%), and the rural territories of origin showed greater deprivation in education, employment, housing, water access, and sanitation. Favorable outcomes occurred in 82.9% of patients, while 8.5% had non-favorable outcomes and 8.5% died. Older age and non-hematologic malignancies were associated with non-favorable outcomes. Mortality was associated with older age, subsidized health insurance, and non-hematologic malignancies. MPI and rural residence were not independently associated with outcomes after adjustment. Conclusions: Although MPI was not independently associated with clinical outcomes, it identified substantial territorial deprivation. Integrating clinical and territorial indicators may support equity-oriented surveillance and pediatric oncology interventions. Full article

Disaster risk perception in informal urban settlements remains insufficiently understood despite its importance for climate adaptation and urban resilience policies. This study evaluated disaster risk perception among residents of nine informal settlements in Greater Santo Domingo, Dominican Republic, focusing on the relationship between the subjective risk of disaster, poverty, and socio-environmental vulnerability. A mixed-methods approach was applied using the RISKPERCEP algorithm and a structured survey composed of 98 questions grouped into key perception variables. A total of 198 surveys were conducted across four municipalities, supported by expert consultation, probabilistic sample-size calculation, and statistical analyses including chi-square tests and Cramér’s V coefficients. The results revealed a generalized moderate underestimation of climate-related risks, mainly associated with limited understanding of hazards, weak institutional trust, low personal involvement, poor memory of past disasters, and reduced concern about consequences. Socioeconomic deprivation, particularly among women, retirees, and low-income groups, was strongly associated with higher perceived vulnerability. Statistical analyses demonstrated a dense and multidimensional network of interdependent social, economic, and spatial variables shaping vulnerability. The study concludes that low disaster risk perception constitutes a major barrier to climate adaptation in informal settlements and highlights the need for integrated public policies combining social protection, climate education, urban resilience, and community-based adaptation strategies. The implications of this study point to the use of a disaster risk perception inquiry method at the community level, structured around specific variables that allow the identification of underlying causes of the widespread underestimation of disaster risk. This approach enables the design of adaptive policies—both structural and non-structural—that explicitly incorporate these aspects when formulating resilience measures. Future research should aim to generalize the study to other communities across the country, preceded by addressing the limitations identified. Full article

Understanding multidimensional deprivation requires consideration not only of who experiences overlapping disadvantages but also of how those disadvantages vary geographically. This study provides a comprehensive descriptive assessment of geographic variation in multidimensional deprivation across the United States using pooled 2022–2023 American Community Survey (ACS) Public Use Microdata Sample data and a Multidimensional Deprivation Index (MDI) constructed using the Alkire–Foster methodology. The MDI incorporates eight indicators spanning four equally weighted dimensions of well-being: economic security, education, health, and housing. Variation is examined across four nested geographic scales—Census regions, Census divisions, states, and all 2487 Public Use Microdata Areas (PUMAs)—using the Headcount Ratio (H), Average Deprivation Intensity (A), and the MDI. The results reveal substantial geographic differences in multidimensional deprivation across the United States, with progressively finer geographic scales revealing increasingly localized patterns. Geographic areas with similar overall MDI values often differ substantially in the composition of deprivation, underscoring the importance of examining the composition as well as the overall level of deprivation. Across all geographic scales, differences in multidimensional deprivation primarily reflect variation in deprivation incidence rather than deprivation intensity, while the PUMA-level analysis suggests that important local variation is obscured by broader regional and state averages. The principal contribution of this study is its integrated multiscale framework. Rather than developing a new deprivation measure or evaluating formal spatial dependence, the analysis applies an established Alkire–Foster methodology to recent nationally representative ACS microdata. This framework provides a consistent descriptive assessment of multidimensional deprivation across multiple nested geographic scales. The findings establish a descriptive empirical benchmark for geographically informed policy discussions and for demonstrating that both the level and composition of multidimensional deprivation vary systematically across geographic scales and that important local variation is obscured by broader regional and state averages. Full article

How SME development affects poverty reduction and income inequality remains a contested issue, particularly in transition economies characterized by structural and regional disparities. Existing studies often treat SMEs as a homogeneous phenomenon. As a result, evidence on the relationship between SME development, multidimensional poverty, and income inequality remains limited. This study examines the relationship between SME development, multidimensional poverty, and income inequality across 15 regions of Kazakhstan during 2005–2024 using panel data and Driscoll–Kraay estimators. Poverty is assessed using incidence, depth, and severity. SME development is measured using indicators capturing quantitative expansion and qualitative contribution. The findings identify unemployment and income inequality as the most robust drivers of poverty. Income growth reduces poverty depth and severity but is also associated with higher income inequality. SME development exhibits heterogeneous socioeconomic effects. Indicators reflecting SME value added are associated with lower poverty and inequality, whereas increases in the number of enterprises or SME output do not necessarily improve social outcomes and may be linked to higher poverty intensity. The results indicate that the developmental impact of SMEs depends on productivity, value creation, and structural transformation rather than enterprise quantity, highlighting the importance of quality-oriented SME policies for inclusive growth. Full article

Despite Nigeria’s vast and diverse untapped potential in solar, wind, biomass, and small-scale hydropower, a significant and persistent gap remains between national policy ambition and the practical implementation of renewable energy projects. This study investigates the underlying structural reasons why existing sustainable energy strategies have failed to significantly reduce fossil fuel dependency or resolve chronic electricity shortages, particularly within underserved semi-urban and rural communities where energy poverty remains a major barrier to development. Through a comprehensive thematic analysis of current regulatory frameworks, international development reports, and peer-reviewed academic literature, this research identifies critical bottlenecks in the energy transition process, with a specific focus on the deployment of solar mini-grids and decentralized energy systems as viable alternatives to the struggling national grid. The findings reveal that progress is hindered not by a lack of natural resources or high-level policy intent but by fragmented institutional coordination, weak regulatory enforcement, and a lack of robust de-risking mechanisms necessary to attract essential private sector investment. To bridge this implementation gap, this paper proposes a multi-dimensional strategic framework centered on fostering inter-agency synergy, implementing specialized capacity-building programs, and stabilizing financial foundations for renewable infrastructure. Full article

Energy poverty remains a persistent challenge in South Africa, despite relatively high levels of electricity access in urban townships. This study investigates household energy consumption patterns, energy-related challenges, and community perceptions of renewable energy in South Africa. In this study, a quantitative research design was employed, using a structured questionnaire administered to households selected from both electrified and non-electrified areas. The data were analyzed using descriptive statistics and inferential analysis with the Statistical Package for the Social Sciences (SPSS Version 30). The findings demonstrated that although electricity is widely used for basic services such as cooking and lighting, many households continue to rely on multiple fuels to meet their daily energy needs. This practice of energy stacking reflects ongoing concerns about affordability, reliability, and safety, and highlights that access to electricity alone does not guarantee energy security. Households also report significant financial pressure from energy costs, as well as health and fire risks associated with the use of unsafe alternative fuels. While awareness of renewable energy is present within the community, knowledge levels are uneven and not strongly associated with demographic factors, suggesting the need for more inclusive and targeted engagement strategies. Overall, the study demonstrates that energy poverty in urban South African townships extends beyond physical grid connection and is shaped by complex socio-economic and safety considerations. By foregrounding community perspectives, this research contributes to the international literature on multidimensional energy poverty and supports the design of integrated, people-centered interventions that advance affordable, reliable, and clean energy transitions in the Global South. Full article

Background/Objectives: Child social vulnerability is a multidimensional phenomenon influenced by poverty, material deprivation, inequality, and institutional protection. This study analysed child and adolescent social vulnerability in Europe between 2017 and 2023 and developed a Child Social Vulnerability Index (CSVI). Methods: A longitudinal ecological study was conducted using Eurostat country-year data from European countries. Indicators included severe child poverty, severe material deprivation, income inequality (Gini index), preventive healthcare expenditure, and social protection expenditure. Descriptive, longitudinal, principal component, and cluster analyses were performed. Results: The findings revealed substantial differences in child social vulnerability across European countries. Poverty, material deprivation, and inequality were strongly associated, supporting the multidimensional nature of vulnerability. Principal Component Analysis supported the internal structure of the child Social Vulnerability Index (CSVI), identifying two components that explained 76.35% of the variance. The CSVI showed a very high correlation with the first principal component (r = 0.97, p < 0.001) confirming its structural consistency. Longitudinal analyses revealed a significant decline in child social vulnerability between 2017 and 2023 with an additional reduction during the COVID-19/post-COVID period. Cluster analysis identified three distinct European vulnerability profiles based on the CSVI and institutional protection dimension. Conclusions: Child social vulnerability in Europe is shaped by the interaction of socioeconomic inequalities and institutional protection mechanisms. The CSVI provides a useful tool for monitoring vulnerability and informing policies to reduce inequalities and promote child and adolescent well-being. Full article

Inflation has become a major global economic issue, affecting household welfare and poverty reduction efforts, especially in developing countries. Despite growing scholarly attention, understanding of its conceptual foundations, emerging themes, and future research directions remains limited. This review analyzes international studies on inflation and household poverty from 2015 to 2025. Following PRISMA 2020 guidelines, 147 peer-reviewed English-language articles were selected from an initial pool of 659 records in the Scopus database and analyzed using the Biblioshiny package in R for performance metrics and science mapping. The findings reveal a rapidly growing and diverse research area, with an average annual growth rate of 20.77%, involving 362 authors across 147 journals. Most research focuses on high-income nations such as the United States, China, and the UK, while regions heavily affected by inflation-driven poverty, such as Sub-Saharan Africa and Central Asia, are less represented. Thematic analysis identifies five key areas: macroeconomic instability and inequality; household well-being and food security; energy poverty and commodity prices; COVID-19 and external economic threats; and multidimensional poverty combined with social policies. Around 30% of the publications feature international collaboration, reflecting increased global cooperation. Life-cycle analysis indicates the field is in a growth phase and may reach maturity around 2036. Overall, this review provides a detailed overview of the development and structure of research on inflation and household poverty, highlights notable geographic and thematic gaps, and offers valuable insights for future studies and policies aimed at reducing inflation’s adverse effects on vulnerable economies. Full article

Nigeria has pursued exchange rate unification as a deliberate macroeconomic policy objective since the Structural Adjustment Programme (SAP) of 1986, culminating in the full unification of June 2023. Despite the centrality of this policy to Nigeria’s economic governance, its poverty implications have received insufficient empirical examination. This study investigates the effect of exchange rate unification on poverty in Nigeria over the period 1986–2024, using the Autoregressive Distributed Lag (ARDL) bounds testing approach. Exchange rate unification is operationalised as the ratio of the official to the parallel market exchange rate, a continuous measure of the degree of rate convergence achieved at each point in time, which is mathematically the inverse of the conventional parallel market premium used to measure exchange rate distortion. While the parallel market premium measures the degree of exchange rate distortion, that is, how far apart the two rates are, the ERU ratio employed in this study measures the degree of exchange rate unification achieved, that is, how close the two rates are to convergence. Poverty is measured using the Multidimensional Poverty Index (MPI). The MPI is constructed using Principal Component Analysis (PCA) from per capita income, life expectancy at birth, agricultural value-added per worker, and household consumption expenditure per capita. The study finds that exchange rate unification significantly worsens poverty in both the short and long run, consistent with the sharp naira depreciation, inflationary pass-through, and deterioration in cost of living observed following Nigeria’s exchange rate reforms. GDP growth reduces poverty marginally in the long run, confirming a modest pro-poor growth effect. These findings establish that exchange rate unification, while necessary for long-run macroeconomic efficiency, imposes significant poverty costs that require deliberate complementary fiscal and social protection policies to mitigate. Full article

Multidimensional poverty is a socioeconomic problem that results from nonlinear interdependencies of various socioeconomic indicators such as educational, health, and living standards indices. This paper considers an XAI-based approach for studying the structural topology and dependency structures of multidimensional poverty systems. It relies on a combination of machine learning approaches, network science, spectral graph theory, and entropy-based complexity measures for revealing the systemic interdependencies between different poverty indicators. The structure of interdependencies between socioeconomic indices associated with education is represented by the multilayer perceptron (MLP). The interpretability of the model is provided via the computation of SHAP values by means of the KernelSHAP method. Higher-order interactions between variables are revealed via the construction and analysis of SHAP-based interaction networks. The proposed methodology is then employed on the GEMPI 2025 dataset consisting of 109 countries. The results show significant consistency in the structural map (R² = 0.9890) in combination with stable internal consistency in cross-validation (R² = 0.9864, SD = 0.0074). The SHAP analysis shows that standards of living and health have a high influence on the structural mapping of education, while the contribution of income-related features is lower compared to other features. Entropy analysis points toward partially fragmented dependency networks with a moderate concentration of explanatory influences (H = 1.705). The proposed framework can be used to characterize structural dependencies, identify influencing system components, and map informational processes in multidimensional poverty systems by combining the methodology of explainable artificial intelligence with entropy–spectral network analysis. Full article

Climate change represents one of the most critical global challenges, generating environmental, social, and economic impacts that disproportionately affect developing countries such as Peru. This study aims to analyze climate change vulnerability and resilience in Peru during the period 2005–2023, integrating climate data, evidence of glacial retreat, and the assessment of biophysical, socioeconomic, and institutional factors. A mixed-methods approach was applied, combining statistical analysis of temperature and precipitation trends based on official data from SENAMHI and INEI, with a qualitative assessment of ecosystem dynamics and social vulnerability. The results show a sustained increase in temperature, with an average rate of 0.18 °C per decade, along with irregular precipitation patterns and significant regional differences. In addition, a loss of 1.9 million hectares of Amazon forest was identified, alongside high levels of socioeconomic vulnerability in Andean and Amazon regions, where poverty, agricultural dependence, and limited access to services reduce adaptive capacity. The findings confirm that climate vulnerability in Peru is multidimensional, resulting from the interaction between environmental changes and structural social inequalities. In this context, Nature-based Solutions (NbS) and Community-based Adaptation (CBA) emerge as effective strategies to strengthen territorial resilience, although their implementation requires improved governance, long-term financing, and integration of local knowledge. Full article

The study investigates the interrelationship between the performance of the regional economy in Italy and the multidimensionality of wellbeing, as defined by the ISTAT Benessere Equo e Sostenibile (BES) model. Based on panel data from 19 Italian regions and 2 autonomous provinces—Trentino and Bolzano (2012–2023)—the research aims to explore whether there is a link between regional GDP and the three BES dimensions: Benessere (B), Equità (E), and Sostenibilità (S). The innovative contribution of this paper is not the creation of a novel theoretical model, but a multilayered empirical approach that combines panel data methods, machine learning, and clustering. This approach makes it possible to reveal nonlinearities, complex interactions, and regional heterogeneity in BES–GDP relationships. The analysis of the Benessere dimension based on k-Nearest Neighbors reveals nonlinear dynamics related to health, mobility, security, digital access, and socio-economic conditions. Furthermore, cluster analysis identifies territorial development regimes according to the Benessere dimension. The Equità dimension is estimated using boosting regression and clustering models that emphasize the role of income, poverty risk, healthcare pressure, labour-market participation, youth exclusion, deprivation, and access to essential services. Finally, the Sostenibilità dimension is explored using boosting regression and random forest models to estimate interactions among environmental quality, climate stress, energy transition, innovation, digital skills, service reliability, and regional economic performance. The findings demonstrate a structural connection between well-being, equity, sustainability, and the economic performance of Italian regions. The results also confirm the hypothesis that Italy has multiple development regimes that differ geographically. Full article

This study examines the multidimensional nature of poverty and its underlying local determinants within the Suri Sadar Sub-Division of Birbhum District, Eastern India, an area marked by sharp ecological and socio-economic contrasts. Adopting a mixed-method approach, the research integrates primary household survey data (2024-25) with secondary spatial datasets to construct a comprehensive analytical framework. The extent and intensity of multidimensional poverty were measured using the Alkire–Foster (AF) method, while the determinants were identified through a Binary Logistic Regression model. Findings reveal that multidimensional poverty in the region is deeply rooted in the intersection of human, environmental, and spatial factors rather than mere income deprivation. Approximately 26.8 per cent of households were found to be multidimensionally poor, with the western plateau blocks, i.e., Rajnagar, Khoyrasole, and Md. Bazar, showing the highest deprivation levels. Spatial poverty drivers include education, agriculture, and gender equality improvements. Policy implications emphasise the need for geographically tailored, multi-sectoral interventions that focus on human capability, investing in infrastructure, and promoting gender-inclusive development. By elucidating the localized dynamics of poverty, this research contributes to the broader discourse on spatial inequality and sustainable development in rural Eastern India, offering actionable insights for evidence-based regional planning and targeted poverty alleviation. Full article

This paper examines the effects of public infrastructure spending across Ecuadorian cantons on adequate employment and the multidimensional poverty rate over the period 2008–2022, assessing whether such spending operated as a mechanism of convergence. The analysis is grounded in the hypothesis that infrastructure investment yields stronger effects in cantons characterized by lower initial levels of development. The coefficient of primary interest, associated with the interaction between low initial development and infrastructure expenditure, takes a value of −0.9542, which theoretically indicates a substantially larger impact on outcome variables in lagging cantons. This pattern is consistent with convergence theory and with the notion of investment spillovers, often described as a trickle-down process of development. Nevertheless, the estimated effect is marginally significant at the 10% level. In light of these results, the discussion revisits the convergence hypothesis by emphasizing the role of endogenous and institutional factors in shaping inclusive development across Ecuadorian cantons. The discussion underscores the importance of public expenditure quality in Latin America (LATAM) as a critical factor impacting the region’s economic growth, social equity, and overall development. Full article

Given China’s strategic need to alleviate poverty and promote high-quality development in the Yellow River Basin, in this paper, we adopt the unique perspective of ecological migration to dynamically analyze changes in the spatial structure, spatial differentiation, trajectory, and formation mechanism of multidimensional poverty. This study finds the following: (1) In recent years, multidimensional poverty in the contiguous poverty-stricken areas represented by Liupan Mountain in Ningxia has shown a tendency to change from overall poverty to partial poverty. (2) The influence of rural per capital net income on multidimensional poverty has been gradually slowing down over time, which reflects the evolution of the concentrated contiguous poverty-stricken areas represented by the Liupan Mountain area in Ningxia from absolute poverty to relative poverty. (3) Geographical capital and economic development exert a high degree of direct impact on multidimensional poverty. However, as key carriers of spatial reconstruction, ecological migration is not a direct first-order input factor. Instead, it indirectly influences the spatial reconstruction of poverty by reshaping the distribution of population, housing, cultivated land, and infrastructure, with its effects reflected in core indicators such as per capita cultivated land and ecological vulnerability. Establishing a long-term poverty alleviation mechanism for advantageous industries, building a multidimensional education system for poverty reduction, and implementing ecological migration are important pathways to alleviate and eliminate multidimensional poverty in this region. Full article