Search Results (8,556)

Real estate investment decisions are shaped by a complex environment of macroeconomic, demographic, and structural factors, where traditional linear assessment methods often fail to capture nonlinear relationships influencing aggregate housing market performance. The aim of this article is to develop a data-driven artificial intelligence framework for assessing how macroeconomic and structural conditions influence aggregate housing market performance and for providing a conceptual basis for evaluating real estate investment strategies under different economic contexts. The study uses machine learning algorithms that allow for modeling complex relationships between investment return indicators and key macroeconomic factors, such as economic growth rates, price dynamics, population concentration, and long-term structural changes. Unlike traditional econometric methods, the proposed approach identifies nonlinear and regime-dependent relationships between macroeconomic conditions and housing market performance, providing insights that can support the interpretation of different investment strategies. The results show that the factors determining investment returns are not universal, and their significance depends on the broader economic regime and market structure. This allows us to examine how changing macroeconomic conditions influence aggregate housing market performance and to discuss the potential implications for different investment strategies. The study contributes by proposing an artificial intelligence-based methodological framework that combines predictive modelling with explainable AI to support the analysis of macroeconomic influences on housing markets and to inform strategic real estate investment decision-making within complex socioeconomic systems. Full article

Objective: To examine the reliability, construct validity, and discriminative capacity of the Spanish version of the Economic Living Standards Index Short Form (ELSI_SF) in a sample of older adults in Spain. Methods: This analysis was conducted using baseline data from 133 participants (mean age = 66.2 years, SD = 5.6; 53.8% women) recruited from community health and social centers in the provinces of Cuenca, Albacete, and Toledo within the PEPE cohort. Participants completed the ELSI_SF (25 items), sociodemographic measures, the SF-12 Health Survey, and the International Fitness Scale (IFIS). Internal consistency was assessed using Cronbach’s alpha. Convergent validity was examined through correlations between ELSI_SF scores and education, occupation, physical and mental health, and perceived fitness. Discriminative ability for health-related variables was analyzed using ANOVA and partial η². The internal structure was explored using exploratory factor analysis (EFA) and subsequently examined against the original four-factor theoretical model using confirmatory factor analysis (CFA), based on polychoric correlations and estimation methods appropriate for ordinal data. Results: The mean ELSI_SF score was 23.0 ± 3.9, with most participants classified as having comfortable or good living standards. Internal consistency was acceptable for the total scale (α = 0.779), whereas the ownership restrictions (α = 0.441) and self-rating (α = 0.319) subscales showed low reliability. Significant associations were observed between the ELSI_SF total score and selected socioeconomic and health-related measures. Factor-analytic findings provided only partial support for the original four-domain structure. Although CFA showed favorable CFI, TLI, and RMSEA values, the elevated SRMR and instability of the self-rating factor warrant cautious interpretation of the factorial solution. Conclusions: The Spanish ELSI_SF provides preliminary psychometric evidence supporting the use of its total score among relatively socioeconomically advantaged older adults. However, limitations in subscale reliability, factorial stability, and the restricted socioeconomic variability of the sample preclude definitive validation across the full spectrum of material living standards. Further evaluation in larger, independent, and more socioeconomically heterogeneous samples, particularly including older adults experiencing material deprivation, is required. Full article

Integrated watershed sustainability assessments are still incipient in Ecuador, where scarce and heterogeneous data are limiting factors. This study introduces the Watershed Sustainability Index (WSI) to the Chibunga Basin in Chimborazo, Ecuador, marking its first application in this region. A key aspect of this study is the development of a clear and reproducible method for applying the index, particularly in inter-Andean basins where data are limited. The four dimensions—Hydrology, Environment, Life, and Policy—were assessed through the Pressure–State–Response (PSR) framework by combining secondary statistics, field sampling, GIS land-use analysis, and a two-round Delphi consultation with ten experts to operationalize the institutional (Policy) component. The basin scored 0.38 (low sustainability), with a critical Hydrology dimension (0.08), poor Policy dimension (0.33), moderate–low Life dimension (0.42), and moderate Environment dimension (0.67). The central finding goes beyond these scores: the operationalized PSR framework pinpointed where the management cycle breaks down in practice. Systematically null response scores reveal that unsustainability stems from the failure to translate an existing regulatory framework into formal institutional action, rather than from regulatory absence or physical water scarcity alone, further constrained by unfavorable socioeconomic conditions. The procedure turns the WSI from a scoring tool into a diagnostic one, providing a replicable reference for data-scarce Andean basins. Full article

Background: Depressive symptoms have become a significant public health issue faced by middle-aged and older adults in China. Although previous studies have primarily focused on demographic and socioeconomic factors, the association between modifiable lifestyle behaviors and depressive symptoms still requires further investigation. Objective: To examine the associations between sleep duration, physical activity, digital participation, social participation, and depressive symptoms as well as life satisfaction among middle-aged and older adults in China. Methods: A cross-sectional analysis was conducted using data from the 2020 China Health and Retirement Longitudinal Survey (CHARLS). Depressive symptoms were defined as CES-D-10 scores ≥10, with 13,576 individuals included in the analysis sample. Adjusted prevalence ratios (aPRs) were estimated using modified Poisson regression, while ordinal logistic regression was employed to analyze life satisfaction. The analysis controlled for covariates such as demographics, socioeconomic status, and health status, and accounted for the complex sampling design. Results: The weighted prevalence of depressive symptoms was 44.5%. Sleep deprivation (<7 h/day) was significantly associated with elevated depressive symptoms (aPR = 1.49, 95% CI: 1.33–1.68); participation in recreational activities was significantly associated with reduced depressive symptoms (aPR = 0.86, 95% CI: 0.77–0.96); adequate physical activity was associated with a higher prevalence of elevated depressive symptoms (aPR = 1.17, 95% CI: 1.04–1.32); watching videos (aPR = 0.87, 95% CI: 0.76–0.99) and playing online games (aPR = 0.65, 95% CI: 0.50–0.83) were significantly associated with reduced depressive symptoms; and overall internet use was correlated with lower life satisfaction (OR = 0.90, 95% CI: 0.81–1.00). Women, rural residents, and low-income groups exhibited higher prevalence of elevated depressive symptoms. Conclusion: Sleep deprivation, as well as different types of social engagement, physical activity, and digital behavior, exhibit distinct associations with depressive symptoms in middle-aged and older adults. Behavioral intervention strategies targeting sleep hygiene, leisure activities, and tailored digital behaviors warrant further attention. Full article

Background/Objectives: Social determinants of health are implicated in metabolic dysfunction–associated steatotic liver disease (MASLD), yet longitudinal evidence on incident disease is scarce, and whether individual- and community-level determinants act independently remains unclear. The objective of this study was to examine whether individual food insecurity and neighborhood deprivation are independently associated with incident MASLD. Methods: In this retrospective cohort of 40,693 U.S. adults without baseline MASLD in the diverse NIH All of Us Research Program, food insecurity (two-item Hunger Vital Sign) and neighborhood deprivation (validated five-domain composite) were co-primary exposures, with incident MASLD ascertained from validated diagnostic codes. Proportional hazards models were adjusted for demographic, socioeconomic, and metabolic factors, including obesity. Results: Over 116,220 person-years, 1240 (3.0%) participants developed MASLD. Both associations remained significant after adjustment for demographic, socioeconomic, and major metabolic risk factors, including obesity (food insecurity adjusted hazard ratio [aHR] 1.32, 95% CI 1.13–1.53; neighborhood deprivation aHR 1.20, 95% CI 1.05–1.37). Unadjusted cumulative incidence was highest among participants with both exposures and lowest among those with neither. Findings were consistent across sensitivity analyses; the food-insecurity association remained when neighborhood disadvantage was specified with a census-based index. Conclusions: Food insecurity and neighborhood deprivation were independently associated with higher incidence of MASLD. Nutrition-focused, equity-oriented interventions warrant evaluation to reduce MASLD burden and advance health equity. Full article

The global shift toward an aging population presents significant challenges for healthcare systems. This is compounded by rising disability rates, fragmented care models that struggle to meet complex needs, and a digital divide caused by the emergence of smart technologies. This work aims to evaluate how the digital divide affects the adoption, usability, and perceived benefits of smart home technologies designed to support activities of daily living and health monitoring. The influences of socioeconomic status and geographic location (urban versus rural) on the digital divide are considered. Four databases (Web of Science™, Scopus^®, PubMed^®, and IEEE Xplore^®) were searched between 2014 and 2026, resulting in 71 studies that examined older adults, smart home technologies for daily living or health monitoring, and factors related to the digital divide. Findings were synthesized using the Technology Acceptance Model, Van Dijk’s Digital Divide Framework, and Health Behavior Models. Three key barriers were identified—economic, technical, and social—which disproportionately affected vulnerable groups. Smart Home Health Technologies (SH2Techs) present adoption challenges distinct from standalone devices because they require integrated infrastructure and sustained engagement. Limited research addressing the usability of non-clinical SH2Techs has identified the need for co-design, simplified interfaces, targeted training, and policy reforms to support equitable aging in place. Full article

Background/Objectives: Pulmonary function tests (PFTs), especially spirometry, are important for chronic respiratory disease diagnosis and management, but Baidu-based online search interest in PFT-related information remains insufficiently characterized. This study examined long-term Baidu search activity for a selected PFT-related keyword in China from 2011 to 2024, with attention to pandemic-period changes, provincial variation, spatial inequality, and associated socioeconomic factors. Methods: We analyzed Baidu Index data from 1 January 2011 to 31 December 2024. The selected PFT-related keyword, “pulmonary function instrument,” was compared with “blood pressure monitor” and “blood glucose meter.” Daily Baidu Index values were aggregated into monthly and annual series. Temporal trends, relative search-intensity ratios, interrupted time-series analysis, inequality indices, fixed-effects regression, subgroup heterogeneity, and convergence dynamics were assessed. Results: PFT-related Baidu search activity remained lower than that for blood pressure and glucose monitoring, with relative search-intensity ratios below 0.35. Descriptively, PFT-related searches increased during 2020–2022; however, the re-specified seasonality-adjusted ITSA using unsmoothed monthly observations did not provide strong statistical evidence for an immediate level change at pandemic onset or a sustained slope change. Provincial differences persisted, with higher values generally observed in several eastern coastal provinces. Inequality indices were lower on average during 2020–2022 but fluctuated over time, and beta-convergence analyses provided limited statistical evidence of systematic catch-up among initially low-index provinces. Urbanization, per capita GDP, and population aging were positively associated with PFT-related Baidu Index values, while subgroup findings were interpreted as exploratory ecological associations. Conclusions: PFT-related Baidu search activity in China remained lower than search activity for blood pressure and glucose monitoring and showed persistent provincial variation. These findings suggest lower visibility of PFT-related information within the Baidu-based online environment. Full article

Background/Objectives: Forensic age estimation increasingly relies on non-ionizing magnetic resonance imaging (MRI) evaluation of the knee growth plates. The original five-stage classification proposed by Dedouit et al. was developed using spin-echo proton-density-weighted imaging, and its applicability to gradient-echo sequences with different contrast mechanisms has not been fully established. This study aimed to apply the original, unmodified Dedouit classification to a volumetric three-dimensional Multiple Echo Data Image Combination (3D MEDIC) sequence and to generate corresponding age thresholds in a Turkish sample. Methods: Knee MRI examinations of 309 individuals (153 males, 156 females; age range 9.18–25.97 years) were retrospectively evaluated at a 3-Tesla field strength. Two experienced observers independently staged the distal femoral and proximal tibial epiphyses; intra- and inter-observer agreement were assessed using Cohen’s kappa. Spearman’s correlation and the Mann–Whitney U test, with rank-biserial effect sizes and Bonferroni correction, were used to assess the relationship between age and stage and between-sex differences, respectively. To provide forensically applicable thresholds, we additionally modeled the age at which the probability of complete fusion (Stage V) reached 50%, with 95% bootstrap confidence intervals, and calculated the sensitivity, specificity, and area under the curve (AUC) of Stage V for identifying individuals ≥18 years. Results: Agreement was very good for both epiphyses (kappa = 0.808–0.833). Age correlated strongly with stage for both the femur (rho = 0.70–0.76) and tibia (rho = 0.68–0.74). The 50%-probability age for complete fusion ranged from 15.23 years (tibia, females) to 17.43 years (femur, males). Stage V showed high sensitivity (0.96–0.98) but markedly lower and sex-dependent specificity for the 18-year threshold (0.48–0.58 in females versus 0.77–0.85 in males), indicating that Stage V alone is a poor sole criterion for confirming adult status in females. The youngest age at which Stage V was observed was 14.67 years in females and 16.07–16.16 years in males, markedly younger than thresholds reported using spin-echo imaging in the original Dedouit cohort. However, as an extreme-value statistic based on a single individual, this minimum should not be used as a forensic threshold in isolation. Conclusions: The Dedouit classification remains reproducible when applied to a 3D gradient-echo sequence, but the resulting age thresholds may be influenced by acquisition technique, population-specific factors such as socioeconomic status, or both. Consequently, thresholds derived from different MRI sequences or populations should not be assumed to be interchangeable without local validation. Full article

The relationship between father involvement and child development has received increasing attention. This study employed a three-level meta-analytic model with the aims of clarifying the relationship between father involvement and children’s social behaviors (positive/negative) and analyzing the factors influencing the differences in this relationship. Through literature retrieval and screening, 37 studies were included in this research, and a total of 249 effect sizes were extracted. The results of the meta-analysis show that there is a moderate positive correlation (r = 0.203) between father involvement and children’s positive social behavior, and a low negative correlation (r = −0.087) between father involvement and children’s negative social behavior. This relationship was significantly moderated by children’s age stage, family socioeconomic status, type of father involvement, reporter of father involvement, cultural background and study quality, while children’s gender exerted no moderating effect. These findings highlight the importance of the father’s role in the development of children’s social behaviors. Future research could further focus on the quality of father involvement in different cultural backgrounds and the impact of mother involvement on children’s development. Full article

Background: The 2025 Dietary Reference Intakes for Koreans (KDRIs) revised the acceptable macronutrient distribution ranges (AMDRs), but evidence regarding their association with metabolic syndrome (MS) is limited. Methods: We analyzed data from 14,768 Korean adults aged ≥19 years who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) 2022–2024. Macronutrient intake ratios were classified according to the revised KDRIs. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) after adjustment for demographic, socioeconomic, lifestyle, and dietary factors. Isocaloric substitution analyses estimated the associations of replacing 5% of energy from carbohydrate with fat or protein while maintaining total energy intake. Results: Overall adherence to all three AMDRs was not significantly associated with prevalent MS. Carbohydrate intake > 65%E and fat intake < 15%E were associated with higher odds of prevalent MS, whereas fat intake > 30%E and protein intake > 20%E were associated with lower odds. Significant sex interactions were observed for carbohydrate and fat intake categories, while no significant age interactions were found for the categorical analyses. Theoretical isocaloric substitution of 5%E from carbohydrate with fat or protein was associated with lower odds of prevalent MS, with significant interaction by sex for fat substitution and by age group for both fat and protein substitutions. Conclusions: In this cross-sectional analysis, higher carbohydrate and lower fat intake were associated with higher odds of prevalent MS, whereas higher fat and protein intake and theoretical isocaloric substitution of carbohydrate with fat or protein were associated with lower odds. Full article

The Historic Centre of Córdoba (Spain), designated a Site of Cultural Interest (BIC) and partially recognised as a ‘World Heritage Site’ by UNESCO, is one of the largest in Europe and, in recent decades, has undergone profound functional, economic and social transformations, which have been accelerated by growing tourist activity. These processes have not yet been analysed systematically, despite the fact that the study of urban processes such as touristification and their implications for certain urban dynamics of gentrification is a highly topical issue. This study aims to determine the extent to which the Historic Centre of Córdoba is undergoing a significant process of touristification and its impact on depopulation, gentrification and other functional and land-use transformations. To this end, a series of demographic, socio-economic, tourism-related and property market indicators have been collected and analysed. The results indicate a recent, intense process of touristification that has exacerbated the critical situation of depopulation and residential abandonment, although no significant process of socio-demographic gentrification has been detected. It is concluded that tourism is neither the sole nor even the main cause of this trend of demographic decline and functional and urban changes; rather, there are multiple historical, socio-economic, urban planning and demographic factors that explain them. This study lays the groundwork for a broader investigation of this urban area, which is of such great significance to the city in terms of heritage, history and identity. Full article

Understanding spatiotemporal changes in landscape ecological risk is essential for regional ecological security and sustainable land management, particularly in environmentally sensitive areas. Using land-use data from five time points (2000, 2005, 2010, 2015, and 2020) together with topographic, climatic, vegetation, and socioeconomic data, we assessed landscape ecological risk dynamics in Xinzhou City, a typical ecologically sensitive region in the middle Yellow River Basin. We integrated a landscape ecological risk assessment model, spatial autocorrelation analysis, and an optimal-parameter geographical detector (OPGD) to identify the spatiotemporal patterns and key drivers of ecological risk. Built-up land expanded by 131.47% over the study period, while cropland and grassland both contracted. Land-use change was dominated by bidirectional conversion between cropland and grassland, alongside a net shift of both to built-up land. Overall, ecological risk declined: high- and relatively high-risk areas decreased by 1354.15 km². Spatially, the pattern remained stable, with higher risk in basins and lower risk in mountainous regions, although the trend varied across phases. Risk exhibited significant spatial clustering: low–low clusters remained stable in mountainous ecological source areas, whereas high–high clusters persisted in basin agricultural areas. Elevation was the dominant factor in spatial risk differentiation. Combined natural and anthropogenic factors shaped the overall risk pattern. Despite the regional decline, urbanization-induced disturbance remains the principal driver of local risk increases. Our findings demonstrate the value of coupling long-term land-use data with OPGD to evaluate the relative and interactive contributions of terrain constraints and anthropogenic drivers in complex mountain–basin systems, with implications for spatially targeted ecological restoration and sustainable land management in ecologically sensitive transition zones. Full article

This study investigates the empirical links between climatic/socio-economic factors and Consumer Price Food Indices (CPFIs) across 47 advanced and emerging economies from 2001 to 2022. Utilizing a balanced panel dataset compiled from the World Bank’s World Development Indicators, FAO databases, and UNDP Human Development Reports, the analysis applies fixed-effects and random-effects panel data models to evaluate the drivers of food price dynamics. The empirical results reveal that socio-economic variables, specifically the Human Development Index (HDI), food price inflation, and agricultural productivity, are consistently associated with food indices, underscoring the critical role of structural development and nominal inflationary pressures. Climatic factors, particularly temperature anomalies, also exert a significant impact: a one-degree Celsius increase in temperature anomalies is associated with a 0.82-unit rise in the food price index level, whereas expansions in forest area and agricultural land are linked to price reductions. These findings indicate that food price dynamics are shaped by the intricate interplay of climate variability and socio-economic conditions. Consequently, policy recommendations emphasize targeted investments in socio-economic development, climate adaptation measures (including support for climate-resilient agriculture), and sustainable land management (forest conservation and optimized land use) to enhance food system resilience and support long-term food security. Full article

Background: Dental anxiety is a prevalent condition in pediatric oral healthcare and linked with multiple etiologic factors. Although sociodemographic factors are frequently examined, the influence of internal psychological constructs such as self-esteem remains underexplored in children. This cross-sectional study aims to evaluate the association between dental anxiety and self-esteem among school-age Turkish children. Methods: The study was conducted with 204 participants aged 7–12 years. Dental anxiety and self-esteem were assessed using Corah’s Dental Anxiety Scale and the Rosenberg Self-Esteem Scale, respectively. Group comparisons were performed with the Mann–Whitney U and Kruskal–Wallis tests, and their association was examined with Spearman’s rank correlation. Independent predictors of dental anxiety were further identified through a stepwise multiple linear regression. Results: Dental anxiety was prevalent in 24.5% of participants. No significant differences in anxiety or self-esteem were found by gender, age, or socioeconomic status (p > 0.05). A moderate negative correlation (r = −0.301, p < 0.001) was observed between self-esteem and dental anxiety. Regression analysis confirmed self-esteem as the only significant independent predictor of dental anxiety (Adjusted R² = 0.080, p < 0.001) in this model. Conclusions: Findings indicate that self-esteem is independently associated with pediatric dental anxiety, although the explained variance was modest. Whether incorporating children’s psychological profile into behavioral management improves clinical outcomes remains to be investigated. Full article

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