Search Results (1,149)

The rise in seasonal lifestyle tourism, characterized by winter-escape health and wellness stays and long-term leisure residence, has intensified peak–off-peak imbalances and pressures on the allocation of tourism service supply in tropical island destinations. However, existing research lacks a systematic comparison of seasonal fluctuations and long-term evolution for this subgroup at the city/county level. Therefore, this study aims to characterize the seasonal pattern, long-term trend features, and typological differentiation of seasonal lifestyle tourism at the county level, and to compare differences across types. Using monthly data on seasonal lifestyle tourism for 18 cities/counties in Hainan from 2021 to 2024, we apply TRAMO/SEATS decomposition to identify seasonal structures and measure seasonal amplitude and employ the Hodrick–Prescott (HP) filter to extract trend components and determine their directions of change. We further construct five development types by integrating trend categories and changes in seasonal amplitude and test between-type differences using one-way analysis of variance (ANOVA). Results show that Hainan exhibits a stable “winter–spring peak and summer–autumn trough” pattern (peaks concentrated in January–March and December, with the off-season typically spanning May–October), with strong seasonality and pronounced spatial heterogeneity. The four-year mean seasonal range at the county level is 215.01, with high values clustered in southern Hainan; Haikou remains relatively low, while Wenchang shows an upward trend. Long-term trends are clearly differentiated: 13 counties show sustained growth, 2 show decline, and 3 display a U-shaped recovery (decline followed by rebound). Growth rates also vary substantially, with Qionghai increasing at roughly 27 times the rate of Qiongzhong. Integrating seasonal and trend characteristics yields five types, of which the Robust Development type accounts for the largest share (50%). Between-type differences are mainly reflected in tourism service supply capacity: the number of star-rated hotels (p = 0.033, η² = 0.530) and overnight visitors (p = 0.004, η² = 0.676) differ significantly across types, whereas differences in natural-environment conditions are not significant. This study provides a scientific basis for zoning management and optimizing low-season strategies in Hainan. Full article

The complex topography and harsh natural environment of the Loess Plateau in Longzhong have been suffering from an undefined living circle structure, which has hindered rural planning and development. A rural community living circle is a spatial unit centered on meeting the needs of villagers, within which various service facilities are rationally allocated within a specific spatial scope. To refine its spatial patterns, the concept of living circles was introduced to address travel challenges. The extent of these living circles is affected by the accessibility of public service facilities and barriers to travel. Using land use data, DEM, population density, and road networks, this study employed the MCR model, gravity model, and ArcGIS spatial analysis to examine the patterns of rural community living circles. The focus was on analyzing the living circle structure of rural communities on the Loess Plateau in Longzhong, considering both natural and artificial environmental constraints. The results show: (1) Rural community living circles present multi-scale spatial features. The basic living circle covers a 15 min slow-travel area. The central living circle corresponds to village-level needs, accessible within 35 min by both slow and motorized travel. The town living circle covers a 10 km radius, reachable within 60 min by a mix of transport modes. The county living circle, dominated by motorized travel, represents the top tier of public service configuration. (2) Quantitatively, the delineation identified 2753 basic, 444 central, 19 township, and 1 county-level living circles in the Anding District of Dingxi City. The Northern, Eastern, and Southwest Zones suffer from fragmented mountainous landscapes, limiting mobility and accessibility. The Central Zone, however, benefits from a combination of mountainous terrain and river valley plains, offering superior service accessibility. (3) The analysis results based on the MCR model and gravity model aligned more closely with reality, reflecting the scale patterns of rural community living circles. The results of this study can provide theoretical guidance for rural planning, construction, and management in the hilly and gully areas of the Loess Plateau. Full article

Green space equity is increasingly recognized as a critical environmental condition for healthy aging, yet existing research often overlooks how different green space attributes—accessibility and diversity—are associated with distinct dimensions of older adults’ health. Limited attention has been paid to their nonlinear threshold effects or to the social pathways through which green spaces influence health outcomes. Using the United States county-level panel data from 2020 to 2023, this study integrates fixed-effects models, Extreme Gradient Boosting (XGBoost), and mediation analysis to examine the associations between green accessibility measured by the Two-Step Floating Catchment Area (2SFCA) method, and green diversity measured by the Shannon Index, on the general, physical, and mental health of older adults. Findings indicate that (1) higher green accessibility is associated with better general health, whereas green diversity shows a stronger association with physical health, reflecting its link to more heterogeneous ecosystem service environments. (2) Green accessibility demonstrates the threshold effect, in which the strength of association with health becomes steeper once accessibility approaches higher levels. (3) Green space equity is linked to health partly through social structures. Education clustering and marital stability mediate the associations with general health, while mental health appears to depend more on the social interaction opportunities embedded within green environments than on their physical attributes alone. The study proposes an integrated “physical environment–social structure–health outcome” framework and a threshold-oriented spatial intervention strategy, highlighting the need to prioritize improvements in green accessibility in underserved areas and prioritizing green diversity and age-friendly social functions where accessibility is already high. These findings offer evidence for designing inclusive, health-oriented urban environments for aging populations. Full article

Air pollution has been one of the major threats to public health. The study aimed to determine latent patterns of geographical distribution of health-related air pollutants across the USA and to evaluate real-world cumulative effects of these patterns on public health metrics. It was an ecological study using county-level data on the concentrations of 12 air pollutants over 20 years. Latent class analysis was used to identify the common clusters of life expectancy-associated air pollutants based on their concentration characteristics in the final counties studied (n = 699). Multivariate linear regression analyses were then applied to assess the relationship between the LCA-derived clusters and health measurements with confounding adjustment. We found that PM_2.5 mass, PM₁₀ speciation, and NONO_xNO_y (the reactive nitrogen species) were associated with life expectancy and thus were included in LCA. Among five identified clusters, the one with a more severe pollutant profile was associated with a decreasing life expectancy, an increasing mortality risk among middle-aged and elderly populations (≥45 years), and an increasing mortality rate caused by chronic respiratory conditions, cardiovascular diseases, and neoplasms. Our study brings new perspectives on real-world geographical patterns of air pollution to explain health disparities across the USA. Full article

This paper focuses on whether smart-related built environments are associated with improved housing affordability for economically disadvantaged groups. Smart growth is a planning theme that aims to address the unintended negative consequences of urban sprawl through combining diverse dimensions across land-use diversity, housing diversity, accessibility, and compact development. Focusing on Clackamas County, Multnomah County, and Washington County within the Portland metropolitan area, the analysis uses census-tract-level data to assess both contemporaneous associations in 2013 and changes in affordability between 2013 and 2019. Overall, the findings suggest that smart-growth tools exhibit both potential and limitations with respect to housing affordability. Greater housing-type diversity and lower reliance on single-family residential land use are consistently associated with higher shares and subsequent increases in affordable housing units for low-income groups. In contrast, other smart-growth features—such as land-use mix and accessibility—show weaker or uneven relationships. These findings suggest that smart growth can contribute to expanding affordable housing supply primarily through housing-related components, while other dimensions of smart growth appear to play a limited role. The results underscore that housing-focused strategies play an important role in shaping affordability outcomes under smart growth. Full article

Promoting green industrial development and enhancing high-quality employment are crucial for advancing county-level economic growth and achieving shared prosperity. This study analyzes the spatiotemporal evolution trends of green industrial development and high-quality employment using panel data from 20 mountainous counties (cities and districts) in Zhejiang Province from 2010 to 2023. It employs panel models to investigate the effects and mechanisms through which green industrial development fosters high-quality employment. The results indicate that, during the study period, both green industry development and high-quality employment exhibited uneven progress across the 20 mountainous counties (cities and districts) in Zhejiang. Mechanism analysis revealed that green industrial development significantly promotes high-quality employment through two pathways: industrial structure upgrading and technological progress. The heterogeneity analysis indicates that the impact of green industrial development on high-quality employment varies significantly across different industrial structures, with counties dominated by the tertiary sector showing more substantial promotion effects. The threshold regression analysis reveals a dual-threshold effect of technological progress in promoting high-quality employment through green industrial development, presenting an approximately J-shaped nonlinear relationship. The research findings provide significant support for the sustainable development of the ecological environment and society by addressing current imbalances between ecological preservation and economic or social growth. Full article

Background and Objectives: The effect of growth hormone (GH) on body composition is well recognized, and recombinant human GH (rGH) therapy may improve lean mass and related parameters. The aim of this study was to analyze changes in body composition parameters and lipid profile under rGH treatment in children diagnosed with short stature and to explore potential influencing factors. Materials and Methods: A secondary data analysis was conducted in the Endocrinology Department of the Mures County Hospital, Romania, approved by the local Ethics Committee. All children diagnosed with short stature and receiving rGH treatment were eligible for inclusion if they had four body composition analyses at least 6 months apart. Analyzed variables included age, gender, environment, mean rGH dose, height and body mass index (BMI) SDS, body composition parameters assessed by bioimpedance, and family-related variables. Statistical analysis was performed using SPSS v.25 with a level of significance α = 0.05. Results: There was no statistically significant trend in body composition parameters taken during serial measurements, except for the sarcopenic index and height (p < 0.001). Environment, pubertal development, and family-related variables other than maternal BMI had no significant influence on body composition or lipid profile. Gender differences in body composition revealed that the change in muscle mass (p = 0.009) and skeletal muscle mass (p = 0.013) was statistically significantly higher for boys, and body fat (p = 0.013) for girls. In linear regression analysis, mother’s BMI emerged as a significant predictor for changes in high-density lipoprotein cholesterol (HDL-C) levels (p = 0.032, β = −0.691) during rGH therapy. Body composition changes did not differ by treatment indication. Conclusions: Gender may be associated with treatment-related changes in body composition during pediatric rGH therapy, while maternal BMI may predict HDL-C variation. rGH treatment appears to improve the sarcopenic index and has minimal and variable effects on the lipid profile. Full article

This study aims to examine the methodological applicability of the Theory of Inventive Problem Solving (TRIZ) in the conservation and revitalization of traditional military settlements. Using Zhenjing Village in Jingbian County as a case, the research constructs a systematic framework for contradiction identification and strategy generation. Methods: Through preliminary surveys, data integration, and system modeling, the study identifies major conflicts among authenticity preservation, ecological carrying capacity, and community vitality in Zhenjing Village. Technical contradiction matrices, separation principles, and the Algorithm of Inventive Problem Solving (ARIZ) are employed for structured analysis. Further, system dynamics modeling is used to simulate the effectiveness of strategies and to evaluate the dynamic impacts of various conservation interventions on authenticity maintenance, ecological stress, and community vitality. The research identifies three categories of core technical contradictions and translates the 39 engineering parameters into an indicator system adapted to the cultural heritage conservation context. ARIZ is used to derive the Ideal Final Result (IFR) for Zhenjing Village, which includes self-maintaining authenticity, self-regulating ecology, and self-activating community development, forming a systematic strategy. System dynamics simulations indicate that, compared with “inertial development,” TRIZ-oriented strategies reduce the decline in heritage authenticity by approximately 40%, keep ecological pressure indices below threshold levels, and significantly enhance the sustainability of community vitality. TRIZ enables a shift in the conservation of traditional military settlements from experience-driven approaches toward systematic problem solving. It strengthens conflict-identification capacity and improves the logical rigor of strategy generation, providing a structured and scalable innovative method for heritage conservation in arid and ecologically fragile regions in northern China and similar contexts worldwide. Full article

School-based health centers (SBHCs) provide accessible, comprehensive healthcare to students, particularly in underserved communities, and play a critical role in addressing reproductive health needs. Despite their benefits, the availability of SBHCs remains limited across the U.S., with ongoing debates regarding their role in educational settings, especially concerning reproductive health services. This study assessed public opinion regarding reproductive health services in SBHCs within middle and high schools in Duval County, Florida. A representative sample of 605 adults was surveyed using a Random-Digit-Dialing approach, and data were weighted for analysis. Overall, support for reproductive health services was high, with 68–74% of respondents in high school and 49–57% in middle school favoring services such as STI testing and treatment, pregnancy testing, and providing condoms. Significant differences in support levels are noted across demographic groups, particularly by age and race. The findings indicate strong community support for implementing reproductive health services in SBHCs, highlighting their potential to improve access to essential health services for adolescents. This research provides valuable insights for policymakers to advocate for the expansion of SBHCs to include comprehensive reproductive health services, addressing health disparities among youth. Full article

Background/Objectives: Gestational exposure to substances (GES) is associated with adverse developmental outcomes. Early identification is limited by reliance on self-reported data. This study assessed the incidence and predictors of discordance in GES reporting between birth certificates and Medicaid claims among Medicaid-covered births in Nevada from 2022 to 2024. Methods: A statewide, hospital-clustered, cross-sectional analysis was conducted using linked Medicaid billing and birth record data. Discordance was defined as GES identified in one source but not the other. Incidence per 1000 live births was stratified by demographic characteristics. Multilevel logistic regression assessed patient- and hospital-level predictors, with random hospital intercepts. Results: Among 50,394 live births, the discordance rate was 95.09 per 1000 (95% Confidence Interval: 92.5–97.7). Substantial disparities were observed by race/ethnicity, socioeconomic status, and geography, with higher discordance among White non-Hispanic mothers, those residing in rural or frontier counties, and individuals with lower educational attainment or living in lower-income areas. Modest but meaningful variation was also observed across hospitals, including differences by hospital size and teaching or research status. Conclusions: Findings highlight substantial discordance in GES reporting and underscore the limitations of single-source surveillance. Findings also have clear policy relevance, indicating that improved cross-system data integration would strengthen statewide surveillance, enhance early detection, and support more equitable resource allocation and intervention strategies. Full article

Urban heat and hardscapes increase cooling electricity demand, stressing power grids and disproportionately burdening deprived neighborhoods. While previous studies have documented the cooling benefits of urban tree canopy, most analyses remain at coarse spatial scales and do not isolate the canopy’s marginal effect from built surfaces, limiting their utility for equitable neighborhood-level planning. We introduce a novel neighborhood-scale (census block-group, CBG) model to estimate cooling-season energy demand across Baltimore City and Baltimore County, Maryland. We quantify demand drivers and actionable tree-canopy targets while controlling for built surfaces. Correlation analysis shows demand increases with developed fraction and imperviousness, and decreases with tree canopy and other vegetated or water cover. Using an explainable monotone gradient-boosted tree model (SHAP) with controls for imperviousness and development, we isolate the canopy’s marginal effect. Demand reductions begin once the canopy exceeds ~11% in Baltimore City and ~23% in Baltimore County, with diminishing returns beyond ~18% (City) and ~24% (County). This flattening is strongest in highly impervious CBGs, while low-impervious county areas show renewed reductions at very high canopy (>55–60%), consistent with forest-dominated microclimates. Spatial hotspots cluster in Baltimore City and southern Baltimore County, where low canopy and high hardscapes coincide with elevated demand; 61% of City CBGs fall below the 18% threshold. We translate these findings into priority intervention tiers combining demand, hardscapes, jurisdiction-specific canopy thresholds, and an equity overlay, identifying 21% of City and 1.2% of County CBGs as high-priority targets for greening and energy-relief interventions. Full article

Background and Objectives: Access to anterior cruciate ligament reconstruction (ACLR) varies substantially across health systems, yet national-level data from Eastern Europe remain limited. This study provides the first nationwide, regionally stratified assessment of ACLR activity in Romania, examining geographic variation, socioeconomic and workforce determinants, and inequality. Materials and Methods: We conducted a retrospective cross-sectional analysis of all ACLRs reported in the national administrative hospital database (2017–2023), supplemented with demographic, GDP, and workforce statistics. Outomes included incidence per 100,000 population, private-sector share, and sex distribution. Regional differences were tested using Kruskal–Wallis and Dunn post hoc comparisons. Predictors of ACLR incidence and private-sector utilization were identified through multivariable Poisson and logistic models. Inequality metrics (Gini coefficients, P90/P10 ratios) and sensitivity analyses excluding Bucharest–Ilfov were also performed. Results: A total of 11, 080 ACLRs were recorded. Incidence varied markedly across regions, from a median of 40.0 per 100,000 in Bucharest–Ilfov to <1–3 per 100,000 in the South, South-East, and South-West (p < 0.001). Higher GDP per capita correlated with incidence (ρ = 0.36) and explained 45% of its variance. Private-sector involvement ranged from <5% in Bucharest–Ilfov and the South to 80–100% in the Centre, North-West, and South-East. In adjusted Poisson models, GDP, surgeon availability, and private-sector share were strong independent predictors of incidence (all p < 0.001). Private-sector access was primarily determined by the proportion of private orthopedic surgeons (OR 21.03). National inequality was extreme (Gini 0.842–0.752; P90/P10 > 10⁹), reflecting the concentration of procedures within a small number of counties. Results were consistent across sensitivity analyses. Conclusions: ACLR in Romania displays severe territorial inequities driven by socioeconomic development, workforce distribution, and uneven private-sector capacity. Targeted regional investment and coordinated workforce strategies are necessary to improve equitable access to surgical care. Full article

Climate change and the resulting projected rise in sea level put densely populated urban communities at risk of river flooding, storm surges, and subsurface flooding. Miami finds itself in an increasingly vulnerable position, as compound inundation seems to be a constant and unavoidable occurrence due to its low elevation and limestone geomorphology. Several recent studies on compound overflows have been conducted in Miami-Dade County. However, in-depth research has yet to be conducted on its economic epicenter. Owing to the lack of resilience to tidal surges and extreme precipitation events, Miami’s infrastructure and the well-being of its population may be at risk of flooding. This study applied HEC-RAS 2D to develop one- and two-dimensional water flow models to understand and estimate Miami’s vulnerability to extreme flood events, such as 50- and 100-year return storms. It used Hurricane Irma as a validation and calibration event for extreme event reproduction. The study also explores novel machine learning metamodels to produce a robust sensitivity analysis for the hydrologic model. This research is expected to provide insights into vulnerability thresholds and inform flood mitigation strategies, particularly in today’s unprecedented and intensified weather events. The study revealed that Miami’s inner bay coastline, particularly the downtown coastline, is severely impacted by extreme hydrometeorological events. Under extreme event circumstances, the 35.4 km² area of Miami is at risk of flooding, with 38% of the areas classified as having medium to extreme risk by FEMA, indicating severe infrastructural and community vulnerability. Full article

Crabronid wasps (Hymenoptera: Crabronidae) are ecologically important predators that provide various ecological services by regulating the arthropod populations, enhancing soil processes through nesting, serving as sensitive indicators of habitat condition, and providing pollen transfer for plants. However, as other invertebrates face biodiversity threats, these wasps might be under threat from environmental changes, and we need to assess the biodiversity patterns of these wasps in Yunnan Province. Unfortunately, no information is currently available about the pattern and factors responsible for the assemblages of these wasps within our study region. This study provides the first province-level assessment of habitat suitability, species richness, assemblage structure, and environmental determinants for Crabronidae in Yunnan by integrating species distribution modeling (SDM), multivariate clustering, and ordination analyses. More than 50 species were studied to assess habitat suitability in Yunnan using MaxEnt. Model performance was robust (AUC > 0.7). Suitability patterns varied distinctly among regions. Species richness peaked in southern Yunnan, particularly in the counties of Jinghong, Mengla, Menghai, and Jiangcheng Hani & Yi. Land use/land cover (LULC) variables were the dominant predictors for 90% of species, whereas precipitation-related variables contributed most strongly to the remaining 10%. Ward’s hierarchical clustering grouped the 125 counties into three community assemblage zones, with Zone III comprising the most significant area. A unique species composition was found within a particular zone, and clear separation among zones based on environmental variation was supported by Principal Component Analysis (PCA), which explained more than 70% variability among zones. Furthermore, Canonical Correspondence Analysis (CCA) indicated that both LULC and climatic factors shaped community structure assemblages, with axes 1 and 2 explaining 70% of variance (p = 0.001). The most relevant key factors in each zone were precipitation variables (bio12, bio14, bio17), which were dominant in Zone I; for Zone II, temperature and vegetation variables were most important; and urban, wetland, and water variables were most important in Zone III. Full article

Labor market forecasting relies heavily on economic time-series data, often overlooking the “health–wealth” gradient that links population health to workforce participation. This study develops a machine learning framework integrating non-traditional health and social metrics to predict state-level employment density. Methods: We constructed a multi-source longitudinal dataset (2014–2024) by aggregating county-level Quarterly Census of Employment and Wages (QCEW) data with County Health Rankings to the state level. Using a time-aware split to evaluate performance across the COVID-19 structural break, we compared LASSO, Random Forest, and regularized XGBoost models, employing SHAP values for interpretability. Results: The tuned, regularized XGBoost model achieved strong out-of-sample performance (Test $R^2$ = 0.800). A leakage-safe stacked Ridge ensemble yielded comparable performance (Test $R^2$ = 0.827), while preserving the interpretability of the underlying tree model used for SHAP analysis. Full article