Search Results (357)

Background: Development Assistance for Health (DAH) plays a vital role in health financing across Sub-Saharan Africa, particularly in tackling communicable diseases such as HIV/AIDS, malaria, and tuberculosis. Despite its importance, the efficiency and equity of DAH allocation remain contested. Objectives: The study aims to evaluate the cost-effectiveness of DAH in Sub-Saharan Africa from 1995 to 2018, as well as to explore differences in efficiency across diseases and country contexts. Methods: Data were drawn from the Institute for Health Metrics and Evaluation and applied Generalized Cost-Effectiveness Analysis in conjunction with the Gross Domestic Product-based thresholds. Averted Disability-Adjusted Life Years were analyzed across countries and diseases, and countries were categorized by the Human Development Index (HDI) level to assess differential DAH performance. Results: DAH cost-effectiveness showed similar patterns across HDI groups, with roughly equal proportions of cost-effective and dominated outcomes in both low- and middle-HDI countries. Thirteen countries were identified as very cost-effective, nine as cost-effective, and two as non-cost-effective. Twenty-one countries were dominated, reflecting persistent inefficiencies in aid impact that transcends the various levels of development. Conclusions: Tailoring DAH allocation to specific disease burdens and development levels enhances its impact. The study underscores the need for targeted investment and a strategic shift toward integrated health system strengthening. Additionally, microinsurance is highlighted as a key mechanism for improving healthcare access and financial protection in low-income settings. Full article

Happiness is defined as well-being and contentment with life. The growing imperative to evaluate well-being beyond economic growth alone has led to the formulation of holistic indices that better reflect quality of life and sustainable development goals. This has resulted in the emergence of the Happiness Score (HS), which adopts a more holistic and human-centred perspective on development and well-being. The present study takes the Happiness Score as a basis for the identification of some of the main determinants of happiness in an empirical and data-driven perspective. To this end, data from 145 countries was analysed, using statistical methodologies such as Generalised Linear Models (GLM), Principal Component Analysis (PCA), fuzzy set Qualitative Comparison Analysis (fsQCA) and the decision tree machine learning approach. A range of indices were considered to translate the reality of countries in different socio-economic dimensions, the level of development of each country, and the continent to which it belongs. The African continent demonstrates substantial disparities across virtually all variables and is frequently associated with the most unfavourable values for each index. The indicators that exerted the most profound influence on happiness were identified as the freedom to make life choices, literacy rate, and Gross Domestic Product (GDP) per capita. These results inform policy strategies aligned with sustainable development, emphasising that enhancing happiness requires multidimensional action beyond economic indicators—particularly in low- and middle-income countries. Full article

Objective: To characterize the nutritional status of the child population and to identify the most relevant determinants that could influence the early development of obesity and overweight. Methods: A descriptive cross-sectional study was conducted, recruiting a representative sample (698 schoolchildren, aged between 5 and 14, and obtaining information from a total of 414 households), using of anthropometric methods for nutritional assessment, the FIES scale, the KidMed index, and questions from the COSI survey. Results: Overall, 27% of the sample had healthy weight, 22.6% were overweight, and 18.1% were obese, with a higher prevalence among boys, and 86.7% of the sample did not adhere to dietary habits consistent with the Mediterranean diet. Food insecurity was present in 45.6% of the sample. A mean weight increase of 2.6 kg (95% CI: 1.0–4.3) was observed for each additional kilogram the child weighed at birth, 2.0 kg (95% CI: −0.2–4.3) in children living in households with some difficulty making ends meet, and 4.8 kg (95% CI: 1.3–8.3) in those from households reporting that they do not or barely manage to make ends meet. A statistically significant association was found with gross annual household income, with children from households earning less than EUR 12,000 having a 3.6 times higher risk of overweight/obesity compared to those from households earning more than EUR 36,000. Conclusions: The prevalence of obesity and overweight is considerably higher in low-income families and is significantly associated with family economic capacity. Continued epidemiological surveillance of these conditions and their relationship with social determinants is necessary. Full article

This research investigates the multiplier effect of ferry transportation development on the medium-term economy of Samosir Island from 2016 to 2022. The study will provide insights into the implications of ferry transportation for the economies of rural or remote regions like Samosir Island. The analysis was conducted by comparing the multiplier effects before and after the development, utilizing the input–output approach, which encompassed the output multiplier, the multiplier on gross value added (GVA), and the household income multiplier. The findings from the input–output analysis indicate that the average output multiplier for 37 industries on Samosir Island has declined by 0.84% annually, with the average output multiplier recorded at 1.80 in 2016, decreasing to 1.71 by 2022. This suggests that, overall, the advancement of ferry transportation in the medium term is comparatively ineffective in promoting economic growth in rural or remote regions such as Samosir Island. Conversely, the average GVA multiplier rose by 1.04% annually. Similarly, the household income multiplier index experienced an increase of 1.91% each year. This indicates that ferry transportation seems to exert a notable influence on both GVA and the household income multiplier, albeit the effect is comparatively modest. Full article

Since the early 2000s, sustainable development in agriculture has attracted substantial political attention, institutional support, and financial commitment, raising expectations for tangible outcomes. Yet, measurable progress remains uneven. As a leading food exporter, Brazil, in particular, has come under global scrutiny for practices deemed unsustainable—such as deforestation, excessive use of agrochemicals, and socio-environmental conflicts—despite its agricultural sector being a vital contributor to global food security. To provide policymakers with a robust monitoring tool, this study develops a nonlinear regression model that quantifies rural sustainability across economic, social, and environmental dimensions. We selected seven indicators—gross value added, average rural income, life expectancy, schooling years, preservation-area deficit, legal-reserve deficit, and water-scarcity deficit—to compute individual sub-indexes. These are combined into a composite rural sustainability index and applied to data from 141 municipalities in Mato Grosso. The results demonstrate that only municipalities achieving high and balanced scores in all three pillars can be deemed sustainable. Our framework contributes to the growing body of triple-index methodologies by offering a replicable, statistically robust tool tailored to agrarian contexts. It provides actionable insights for regional decision-makers aiming to balance productivity, environmental preservation, and social well-being in agricultural frontier regions. Full article

Extensive cattle farming significantly contributes to Greece’s agricultural economy. In such systems, animals mainly graze on natural grasslands whose biodiversity significantly affects meat quality traits. In Greece, the sector faces several economic challenges, while the literature investigating beef quality produced by these systems is scarce. Hence, this study aimed to (i) evaluate farms’ economic performance; (ii) assess meat quality; and (iii) investigate the presence of heavy metals in liver samples of extensively reared beef cattle. The study involved three farms located in the Axios River Delta, a protected area of significant ecological importance in Northern Greece. A designated questionnaire was used to collect farm technical (herd size, meat production, grazing, feeding, reproduction, animal health) and economic data (income, variable costs). Meat samples of the Longissimus dorsi muscle (ninth rib) from 54 carcasses were collected and subjected to physicochemical (color, pH, texture, chemical composition, fatty acid profile) and microbiological analyses. Additionally, heavy metal analysis was conducted on 14 liver samples. A comparative analysis using parametric and non-parametric tests was performed to assess differences in meat quality traits between the 1st and 15th days of storage. The economic analysis showed that all studied farms operated with losses, with the average gross margin excluding subsidies being negative at EUR 130.5 ± 92.60/year per animal. Beef exhibited low fat content (1.1 ± 1.12%), with an average pH₂₄ value of 5.5 ± 0.36, respectively. The concentrations of polyunsaturated, monounsaturated, and saturated fatty acids were 2.7 ± 0.72%, 44.6 ± 4.71%, and 47.3 ± 4.91%, respectively. Over the 15-day storage period, the yellowness (b*) value (p < 0.01), hue angle (p < 0.001), cohesiveness (p < 0.01), and springiness (p < 0.01) significantly decreased, while the lightness (L*) value significantly increased (p < 0.01). The mean Total Mesophilic Viable Counts and Total Enterobacterales were 5.0 log₁₀ CFU/g and 2.34 log₁₀ CFU/g, respectively, while heavy metal concentrations in bovine livers were below the maximum limits set by the European Commission. The results suggest that, despite the financial losses observed, beef’s improved color parameters during storage, along with other favorable quality traits, highlight the potential of extensive cattle farming to meet consumer demand and support value-added marketing. Full article

Background/Objective: Children with disabilities experience greater participation restrictions in life activities than children without disabilities. This study aimed to explore differences in participation of children/youth with and without cerebral palsy (CP) across home, school, and community settings, and examine participation of children with CP across gross motor function levels, age groups, gender, and income levels. Methods: This was a cross-sectional survey study of parents of children with CP (n = 20) and without CP (n = 20) over a three-month period to investigate the frequency of participation/level of involvement across settings. Participation was assessed using the Participation and Environment Measure for Children and Youth© (PEM-CY), a parent-report measure for children and youth, ages 5 to 17 that explores communication in home, school, and community environments. Results: Significantly greater frequency of participation at home and in the community was found in children without CP. Participation at school was not significantly different between the groups and there were no differences in level of involvement, gender, or income. In children with CP, motor function impacted participation in home and school, and age significantly influenced school participation. Conclusions: Participation in life activities is important for overall child development, health, and well-being; however, children with CP participate less than their typically developing peers. The ability to collect and analyze the frequency of participation and level of involvement across home, school, and community environments using one outcome measure provides valuable information for programming, intervention planning, and potential environment modifications that could improve participation in children with CP. Full article

Amidst a period of sustained inflation and rising living costs, food insecurity is a growing concern in Australia and is correlated with poor diet quality and increased rates of non-communicable diseases. Currently there is a gap in knowledge of the impact of increasing cost-of-living pressures on the affordability of a healthy diet. As affordability plays a key role in food security, this cross-sectional study aimed to examine the costs, affordability, and differential of habitual (unhealthy) and recommended (healthy) diets within the Illawarra region of Australia and compare results to 2022 findings. The Healthy Diets Australian Standardised Affordability and Pricing tool was applied in six locations in the Illawarra, with two randomly selected each from a low, moderate, and high socioeconomically disadvantaged area. Costs were determined for three reference households: a family of four, a single parent family, and a single male. Affordability was determined for the reference households at three levels of income: median gross, minimum-wage, and welfare dependent. Data was compared to data collected in 2022 using the same methods and locations. Recommended diets cost 10.3–36% less than habitual diets depending on household type, but remained unaffordable for welfare dependant households and family households from socioeconomically disadvantaged areas, where diets required 25.5–45.9% of household income. Due to income increases, affordability of both diets has marginally improved since 2022, requiring 0.5–4.8% less household income. This study provides updated evidence that supports the urgent need for policies, interventions, and monitoring to widely assess and improve healthy diet affordability and decrease food insecurity rates. Possible solutions include increasing welfare rates above the poverty line and utilising nudge theory in grocery stores. Full article

Epilepsy, one of the most common neurological diseases in the world, affects around 50 million people, with a notably disproportionate prevalence in individuals residing in low- and middle-income countries (LMICs). Alarmingly, over 80% of annual epilepsy-related fatalities occur within LMICs. The burden of the disease assessed using Disability Adjusted Life Years (DALYs) shows that epilepsy accounts for about 13 million DALYs per year, with LMICs bearing most of this burden due to the disproportionately high diagnostic and treatment gaps. Furthermore, LMICs also endure a significant financial burden, with the cost of epilepsy reaching up to 0.5% of the Gross National Product (GNP) in some cases. Difficulties in the appropriate diagnosis and treatment are complicated by the lack of trained medical specialists. Therefore, in these conditions, adopting artificial intelligence (AI)-based solutions may improve epilepsy care in LMICs. In this theoretical and critical review, we focus on epilepsy and its management in LMICs, as well as on the employment of AI technologies to aid epilepsy care in LMICs. We begin with a general introduction of epilepsy and present basic diagnostic and treatment approaches. We then explore the socioeconomic impact, treatment gaps, and efforts made to mitigate these issues. Taking this step further, we examine recent AI-related developments and their potential as assistive tools in clinical application in LMICs, along with proposals for future directions. We conclude by suggesting the need for scalable, low-cost AI solutions that align with the local infrastructure, policy and community engagement to improve epilepsy care in LMICs. Full article

In the current conditions of development of the country’s market economy, the methodological support for cadastral land valuation requires effective modernization and improvement of the existing mechanisms for determining cadastral value for a fair distribution of land tax among landowners. In this regard, the aim of the study was to develop a methodology for taking into account the qualitative state of soils in the cadastral valuation of agricultural lands in the conditions of an active land market, as well as to modernize the method for taking into account the quality of soils within the framework of the income approach in the conditions of a depressed land market. The study was conducted based on a set of scientific methods: the analytical method was used to conduct an analysis of the scientific review of the problem area and to substantiate the relevance of the study, a cycle of laboratory experiments was conducted using mechanical and chemical analyses, the construction of thematic maps was carried out using the dispersion method, the regression modeling method was used to determine the cadastral value of garden plots, and the land rent capitalization method was used to calculate the cadastral value of agricultural land. Research results were as follows: Methodological recommendations were provided for taking into account the quality of soils in the form of an integral indicator of physical and chemical properties in the model for calculating the specific indicator of cadastral value (SICV) of garden and vegetable lands in the conditions of an active land market. The method of accounting for the qualitative state of soil fertility in the form of a weighted quality score of an agricultural land plot was modernized when determining the specific gross income within the framework of the land rent capitalization method used to calculate the SICV. Based on field work and laboratory experiments, current indicators of soil fertility status were obtained, and soil quality scores for Saint Petersburg were calculated. The possibility of using an integral indicator (soil quality score) as a cost factor instead of a large number of fertility status indicators was proven. Also, models for calculating the SICV of garden and vegetable plots were built for the conditions of an active land market, according to which the cadastral value of land plots in Saint Petersburg was calculated for subsequent land taxation. For agricultural lands, using the example of a land plot of a high-commodity agricultural enterprise (Leningrad Region), the cadastral value was also calculated using the proposed income approach method. The scientific significance of the study lies in the improvement of the methodological foundations of cadastral valuation, as well as the technology of taking into account the quality of soils when calculating the cadastral value. The practical significance of the study lies in the applicability of the results of soil quality assessment and models for calculating the SICV for land taxation; individual market valuation for lending, purchase, and sale; lease of agricultural land; and allocation of land plots on account of a land share. In the area of developing a set of melioration measures on agricultural lands, including the development and implementation of agricultural technologies and technical means to improve soil fertility, the results of laboratory studies to determine the physical and chemical properties of soils can be used. The obtained soil quality scores for Saint Petersburg are also applicable to identifying unused and degraded lands for their transfer to other types of use. Full article

This study examines the spatial relationship of PM_2.5 concentrations across provinces in Thailand and explores the relationship between socio-economic factors and PM_2.5 levels from 2012 to 2022. The study results indicate that PM_2.5 pollution in Thailand is spatially clustered, meaning that PM_2.5 spills over into nearby provinces and is not confined to a single area. The factors that positively affect PM_2.5 concentrations include population density and energy consumption per capita, while industrial density has a negative effect on PM_2.5 levels. Additionally, an Environmental Kuznets Curve (EKC) analysis found that the Gross Provincial Product (GPP) per capita has a U-shaped relationship with the PM_2.5 concentration. In the initial stage of economic growth, as the GPP per capita increases, PM_2.5 concentrations gradually decrease. However, once income reaches USD 56,715 and the economy becomes significantly large, further increases in GPP per capita lead to rising PM_2.5 concentrations. In other words, during the early phase of economic development, PM_2.5 pollution does not intensify significantly. However, once Thailand’s economy reaches a certain scale, continued economic expansion exacerbates PM_2.5 pollution, leading to greater economic and social consequences. The study highlights the importance of integrated collaboration among various organizations in mitigating the widespread impacts of PM_2.5 pollution. Full article

The aim of this study was the economic comparison of two equivalent sheep farms with different reproductive management systems. Financial data were selected from a farm that applied artificial insemination (AI) and from one that applied natural mating (NM). The main objective of the analysis was to estimate the cost of each farm’s products and then to calculate their economic indicators. The AI farm had higher production costs, as a result of higher labor and fixed capital costs. On the other hand, the invested capital for the equipment and buildings of the NM farm was lower. Furthermore, the invested livestock capital based on the genetic value of the animals was higher in the AI farm. The AI farm produced milk, replacement ewe lambs and replacement ram lambs as its primary products, whereas the NM farm produced only milk as its primary product. The production costs for milk were 0.08 EUR/kg lower in the AI farm compared with the NM farm. The AI farm had a higher gross revenue and net and gross profit, resulting from the higher genetic value of the AI farm’s livestock. As indicated, the breeding and sale of genetically improved animals can increase the financial results of a farm and offer alternative sources of income. In conclusion, AI results in more sustainable and economically efficient sheep farming. In this regard, training for farmers and governmental economic support could promote AI application. Finally, the fortification of farmer group initiatives that facilitate the trade of dairy sheep products can accelerate AI utilization in dairy sheep farms in Greece. Full article

Background/Objectives: Follow-up studies in very preterm infants are common, but fewer studies are situated in low- or middle-income countries. In a prospective cohort study, we explored longitudinal motor performance trajectories and influencing factors, including an early motor intervention program. Very preterm infants (gestational age < 32 weeks and/or very-low-birth-weight < 1500 g) in the middle-income country of Suriname were included. Methods: We assessed 149 (49.7% boys) infants (mean gestational age 29⁺⁶, mean birth weight 1271 g) at 3, 12, and 24 months with the Bayley Scales of Infant and Toddler Development for fine motor (FM), gross motor (GM), and composite scores (CSs). Influencing perinatal and environmental factors were explored. Delayed-scoring infants were referred to a motor intervention program. Data were analyzed using mixed-model linear regression. Results: The Bayley mean FM and GM scores decreased between 3 and 12 months and stabilized at 24 months. The mean CS at 3, 12, and 24 months was 102.3, 92.7, and 92.2, respectively. The latter two were significantly below the reference values (100, SD 15, p < 0.01). Birth weight z-scores significantly influenced FM (p = 0.013) and CS (p = 0.009); a lower birth weight was associated with initially lower scores and a smaller decline over time than a higher birth weight. The motor intervention program (n = 54) showed no significant interaction effects at all time points after correction for frequency of interventions (no; 1–5; >5 interventions). Conclusions: Motor performance was normal at 3 months and delayed at 12 and 24 months. Birth weight, but not the early intervention program, influenced longitudinal motor trajectories. We recommend follow-up of motor performance and suggest adding the Prechtl General Movement assessment at 3 months of age. The clinical implementation of the early motor invention program needs additional studies to reach an adequate training level. Full article

A Kuznets-like curve for unemployment suggests that unemployment initially rises with early economic development due to sectoral shifts but decreases as economies mature, diversify, and adapt. This explains how gross national income (GNI) per capita influences or mediates the effect of globalization on unemployment. This study investigates the impact of the interaction between GNI per capita and economic globalization on unemployment rates in 158 countries from 1991 to 2019 using the spatial Durbin model (SDM) and a weight matrix based on cultural, political, social, language, and historical backgrounds and trade pacts (CPSLHT) for better estimates. The results indicate that the direct and indirect effects of gross domestic product (GDP) on unemployment are negative and significant in the short and long term. Population growth positively and significantly impacts unemployment, while female labor force participation shows negative and significant indirect effects. The net migration effect is negative but insignificant in the overall model and becomes significant in the decomposed globalization models. The direct and indirect effects of inflation were consistently negative and significant. Trade openness exerts a significant indirect negative effect on unemployment, while the interaction between GNI per capita and economic globalization, especially through trade and foreign direct investment, also reduces unemployment. Persistent unemployment and spatial spillover effects highlight the importance of regional cooperation. Controlling population growth, enhancing GDP growth, permitting mild inflation, promoting female workforce participation, and adopting effective migration policies can reduce global unemployment. Full article

Construction, like any other economic activity, can contribute to national income by creating employment opportunities, and raising gross domestic product (GDP). Several researchers have studied the challenges of various aspects of the construction industry (CI), ranging from sustainability, the industrial revolution, small and medium enterprise, building information modelling, and intelligent construction, but this research examines the state of the CI in conflict-affected regions by evaluating the challenging factors impacting this sector of the economy. A total of 150 industry experts participated in this survey across three regions (Africa, Eastern Europe, and the Middle East). In total, 35 challenging factors were identified and classified using exploratory factor analysis (EFA). Using version 4 of Smart Partial Least Squares (PLS), structural equation modelling (SEM) was used to build the model, which produced seven constructs: economic, environment and education, government, industrial, sustainability, technology, training and support. 31 challenging factors were outlined under these constructs, with economic challenges such as high inflation, high-interest rates, and foreign direct investment (FDI) being the most critical of those observed. This study will be of great importance to the governments of nations in the formulation of policies for the CI. At the same time, stakeholders in the CI will collaborate in the advancement of the sector in the affected region. Full article