Search Results (1,642)

Background: Men who have sex with men (MSM) using HIV pre-exposure prophylaxis (PrEP) experience a high burden of human papillomavirus (HPV) infection and related diseases, yet data on HPV vaccination among this group in Brazil remain limited. Aims: The aims of this study were to estimate the prevalence of complete HPV vaccination and to identify factors associated with vaccination completion among MSM using PrEP in Brazil. Methods: We conducted a cross-sectional online survey between May and September 2025 among MSM aged ≥18 years, residing in Brazil and currently using oral PrEP. Participants were recruited through virtual snowball sampling and targeted advertisements on social media and a gay geosocial networking application. Data were collected using a structured, self-administered questionnaire hosted on REDCap^®. Complete HPV vaccination was defined as self-reported receipt of all doses recommended according to the participant’s age and clinical condition. Sociodemographic characteristics, relationship patterns, sexual behaviors, lubricant use during sexual activity, and history of sexually transmitted infections (STIs) were assessed. Adjusted prevalence ratios (aPRs) and 95% confidence intervals (95% CIs) were estimated using Poisson regression with robust (sandwich) variance. Results: A total of 872 MSM using PrEP were included, of whom 59.4% reported complete HPV vaccination. In adjusted analyses, complete vaccination was more frequent among participants reporting both steady and casual partners (aPR = 1.90; 95% CI: 1.36–2.65) or only casual partners (aPR = 1.72; 95% CI: 1.24–2.39), those reporting lubricant use during sexual activity (aPR = 1.41; 95% CI: 1.23–1.61), and those with a diagnosis of chlamydia and/or gonorrhea in the previous 12 months (aPR = 1.22; 95% CI: 1.08–1.36). Conclusions: Although HPV vaccination coverage among MSM using PrEP in Brazil is higher than that reported for MSM in general, it remains incomplete in a population with regular contact with specialized health services. Integrating systematic assessment and delivery of HPV vaccination into PrEP care may help increase vaccination completion and reduce missed opportunities for prevention. Full article

Background/Objectives: We investigated the association between leisure-time physical activity (LTPA) and liver fibrosis, and whether this relationship differs by obesity and diabetes status. Methods: We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES) 2017–March 2020 cycle. LTPA was assessed using the Global Physical Activity Questionnaire (GPAQ) and classified as physically active if engaging in ≥600 metabolic equivalent (MET)-minutes per week of moderate-to-vigorous activity, or inactive. Clinically significant liver fibrosis was defined as liver stiffness measurement (LSM) ≥ 8.0 kPa on transient elastography. Multivariable logistic and linear regression models estimated adjusted odds ratios (ORs) for significant liver fibrosis, with additional subgroup analyses according to obesity and diabetes status. Results: In 7662 U.S. adults, physically active participants (n = 2721) had a lower prevalence of significant fibrosis than inactive individuals (5.4% vs. 11.4%, p < 0.001). In multivariable analysis, Participants who were physically active were associated with 42% lower odds of having fibrosis (OR 0.58, 95% confidence interval [CI] 0.41–0.82; p = 0.004). This association remained consistent in subgroup analyses stratified by obesity and diabetes status, even in the non-obese subgroup with body mass index (BMI) < 30 kg/m² (OR 0.54, 95% CI 0.32–0.91; p = 0.022) and the non-diabetic subgroup (OR 0.59, 95% CI 0.39–0.90; p = 0.016). Conclusions: Regular moderate-to-vigorous LTPA was independently associated with lower likelihood of clinically significant liver fibrosis. This beneficial association was significant regardless of obesity or diabetes status, suggesting that LTPA may play a clinically meaningful role in populations at high risk for progressive liver disease. Full article

Objective: This study aimed to investigate the association between time to admission (TTA) and long-term mortality in patients with hip fractures, enabling surgeons to assess individual risks and prevent adverse outcomes. Methods: Demographic and clinical data of patients with hip fractures were obtained from medical records in our hospital. Patients aged 65 years or older were included. TTA was defined as the time from injury to first presentation at our institution. The primary outcome was long-term all-cause mortality. The regular multivariate Cox regression, restricted cubic spline, and two-piecewise model were used to explain the linear and curvilinear association between TTA and long-term mortality. The analyses were performed using EmpowerStats and R. Results: A total of 2361 patients were included in our study. There were 743 males and 1618 females, with a mean age of 79.44 ± 6.71 years. There were 1745 intertrochanteric fractures and 616 femoral neck fractures. We divided the patients into four groups according to TTA distribution: TTA ≤ 6 h, 6 h < TTA ≤ 12 h, 12 h < TTA ≤ 24 h, and TTA > 24 h, and the corresponding long-term mortality rates were 254 (25.53%), 85 (32.20%), 127 (32.56%), and 267 (37.50%). A curvilinear association was observed between TTA delay and long-term mortality in geriatric hip fractures, with 24 h serving as an inflection point. When TTA was less than 24 h, every one-hour increase in TTA was associated with a 1.6% increase in long-term mortality (HR = 1.016, 95% CI: 1.008–1.024; p < 0.001). When TTA exceeded 24 h, the long-term mortality risk showed no significant further increase with TTA (HR = 1.000, 95% CI: 1.000–1.000; p = 0.531). Conclusions: This study suggests that delayed admission is associated with a worse prognosis, and the mortality risk increases by approximately 1.6% per hour of delay within the first 24 h, after which the risk appears to stabilize. The first 24 h post-injury may represent a critical window for intervention. Full article

An integrated field–analytical framework was applied to quantify the impact of two small-settlement treatment facilities (TF1 and TF2) on the Irtysh River (East Kazakhstan). The main objective of this study is to quantify effluent-driven dilution and non-conservative changes in key water-quality indicators downstream of TF1 and TF2 and to evaluate parsimonious models for predicting effluent-outlet BOD and COD from upstream measurements. Paired upstream–downstream control sections are sampled in 2024–2025 for 22 indicators, and plant influent–effluent records are compiled for key wastewater variables. Chloride-based conservative mixing indicated very strong dilution (approximately $D\approx 2.0\times {10}^3$ for TF1 and $D\approx 4.2\times {10}^2$ for TF2). Deviations from the mixing line were summarized using a transformation diagnostic $\theta$. At TF1, several constituents exceeded mixing expectations ($\theta \approx 13$ for COD, $\theta \approx 42$ for ammonium, and $\theta \approx 6$ for phosphates), while nitrate shows net attenuation $\theta <0$. At TF2, $\theta$ values cluster near unity, indicating modest deviations. Under a small-sample regime $\left(\mathrm{N}=10\right)$ and leave-one-out validation, regularized regression provided accurate forecasts of effluent-outlet BOD and COD. Lasso under LOOCV performed best (BOD_after: RMSE = 0.626, MAE = 0.459, and $R^2=0.976$; COD_after: RMSE = 0.795, MAE = 0.634, and $R^2=0.997$). The results reconcile strong reach-scale dilution with constituent-specific local departures and support targeted modernization and operational forecasting for water-quality management in small facilities. Full article

Breast cancer remains a leading cause of mortality among women worldwide, motivating the development of transparent and reproducible risk models for clinical decision making. Using the open-access SEER Breast Cancer dataset (November 2017 release), we analyzed 4005 women diagnosed between 2006 and 2010 with infiltrating duct and lobular carcinoma (ICD-O-3 8522/3). Thirty-one clinical and demographic variables were preprocessed with one-hot encoding and z-score standardization, and the lymph node ratio was derived to characterize metastatic burden. Two supervised models, L1-regularized logistic regression and a feedforward artificial neural network, were compared under identical preprocessing, fixed 60/20/20 data splits, and stratified five-fold cross-validation. To define clinically meaningful endpoints and handle censoring, we reformulated mortality prediction as fixed-horizon classification at 3 and 5 years, and evaluated discrimination, calibration, and operating thresholds. Logistic regression demonstrated consistently strong performance, achieving test ROC-AUC values of 0.78 at 3 years and 0.75 at 5 years, with substantially superior calibration (Brier score less than or equal to 0.12, ECE less than or equal to 0.03). A structured hyperparameter search with repeated-seed evaluation identified optimal neural network architectures for each horizon, yielding test ROC-AUC values of 0.74 at 3 years and 0.73 at 5 years, but with markedly poorer calibration (ECE 0.19 to 0.23). Bootstrap analysis showed no significant AUC difference between models at 3 years, but logistic regression exhibited greater stability across folds and lower sensitivity to feature pruning. Overall, L1-regularized logistic regression provides competitive discrimination (ROC-AUC 0.75 to 0.78), markedly superior probability calibration (ECE below 0.03 versus 0.19 to 0.23 for the neural network), and approximately 40% lower cross-validation variance, supporting its use for scalable screening, risk stratification, and triage workflows on structured registry data. Full article

Low-income individuals are unlikely to save relatively large sums on a regular basis; however, many still fall short of even the modest threshold required for long-term financial security. This study examines the determinants of benchmark-defined undersaving among retail e-payment agents (REAs) operating in the urban slums of Lagos, Nigeria. We use a contingent valuation survey, descriptive analysis, and logistic regression to examine how selected behavioural and demographic factors, alongside a 60-day experimental intervention—the Programmed Microsaving Scheme (PMSS), a hard daily commitment savings device—affect the likelihood of undersaving, defined as saving less than 12% of each REA’s average daily income. While the PMSS appears to have contributed to improvements in post-treatment saving participation and performance among REAs, it did not significantly increase the likelihood of reaching or exceeding the benchmark savings threshold. Consistent with this, average daily income, age, gender, marital status, education, and religion are statistically insignificant predictors of benchmark-defined undersaving. In contrast, self-control, measured using a literature-validated instrument, exhibits a statistically significant negative association with benchmark-defined undersaving, indicating that higher self-control reduces the likelihood of failing to meet the benchmark. Measured risk aversion similarly shows no significant association. Notably, this study introduces a novel 60-day PMSS, co-designed with REAs and neobanks to accommodate daily income savings—a characteristic of the informal sector largely overlooked in the literature on commitment savings devices. From a policy perspective, the findings suggest that while short-horizon commitment devices (such as the 60-day PMSS) and financial literacy are associated with improvements in microsavings among low-income daily earners, achieving benchmark-level saving might require longer-term and more adaptive mechanisms that address income volatility and mitigate other inherent risks. Full article

This study examines the motivations, socio-demographic profiles, and behavioural orientations of residents in Northern Italy toward mountain and forest visitation, with a focus on their propensity to engage in forest-based health and wellness activities. The analysis draws on a large stratified survey conducted between December 2023 and January 2024, involving 1218 respondents, of whom 976 reported regular forest visitations. Exploratory factor analysis identifies two main attitudinal dimensions: “Health and Wellness-Driven Forest Engagement”, centred on psychophysical restoration, and “Comfort-Oriented Forest Use”, related to accessibility and low physical effort. Regression models show that wellness-oriented engagement is strongly associated with psychological well-being, walking and hiking habits, and gender, while comfort-oriented use reflects seasonal patterns and preferences for easily accessible forests. A small subset of respondents reports discomfort in forest environments, forming a distinct attitudinal barrier. Overall, the results indicate substantial potential for forest-based wellness tourism to support healthier lifestyles and diversify mountain economies. Policy implications highlight the need for accessible infrastructures, targeted communication, and the integration of wellness-oriented services into regional development strategies. Full article

Background & Objectives: Periodontal disease (PD) is a common oral disease that affects the supporting structures of the teeth and is a leading cause of tooth loss worldwide. This study aimed to estimate the prevalence of PD among 9th-grade teachers in the northern West Bank and examine its association with key behavioral and socioeconomic factors. Methods: A cross-sectional study was conducted among 920 teachers selected through proportional stratified random sampling from governmental and private schools. Periodontal health was assessed using the WHO Community Periodontal Index for Treatment Needs (CPITN), and oral hygiene status was measured with the Simplified Oral Hygiene Index (S-OHI). A structured questionnaire was administered to collect data on socioeconomic status, oral hygiene practices, dietary habits, and smoking behaviours. Data was analysed using descriptive statistics, bivariate and multivariate logistic regression. Results: Only 11.8% of participants exhibited completely healthy gingiva, with the mean condition ranging between calculus and shallow pockets. Oral hygiene practices were the strongest predictors of periodontal outcomes: frequent tooth brushing (Adjusted Odds Ratio: AOR = 0.015), morning brushing (AOR = 0.015), and regular toothbrush replacement (AOR = 2.514) were protective. Higher red meat intake was negatively associated with periodontal health (AOR = 0.032), while frequent nut consumption was protective (AOR = 0.227). The number of cigarettes smoked per week was positively associated with PD (AOR = 1.085). Conclusions: PD is highly prevalent among Palestinian adults, with significant behavioural and lifestyle-related determinants. Targeted oral health interventions are urgently needed to improve adults’ oral health. Full article

Foodborne pathogens remain a major global concern, demanding rapid, accessible, and determination technologies. Conventional methods, such as culture assays and polymerase chain reaction, offer high accuracy but are time-consuming for on-site testing. This study presents a portable, smartphone-assisted dual-mode biosensor that combines colorimetric and photothermal speckle imaging for improved sensitivity in lateral flow assays (LFAs). The prototype device, built using low-cost components ($500), uses a Raspberry Pi for illumination control, image acquisition, and machine learning-based signal analysis. Colorimetric features were derived from normalized RGB intensities, while photothermal responses were obtained from speckle fluctuation metrics during periodic plasmonic heating. Multivariate linear regression, with and without LASSO regularization, was used to predict Salmonella concentrations. The comparison revealed that regularization did not significantly improve predictive accuracy indicating that the unregularized linear model is sufficient and that the extracted features are robust without complex penalization. The fused model achieved the best performance (R² = 0.91) and consistently predicted concentrations down to a limit of detection (LOD) of 10⁴ CFU/mL, which is one order of magnitude improvement of visual and benchtop measurements from previous work. Blind testing confirmed robustness but also revealed difficulty distinguishing between negative and 10³ CFU/mL samples. This work demonstrates a low-cost, field-deployable biosensing platform capable of quantitative pathogen detection, establishing a foundation for the future deployment of smartphone-assisted, machine learning-enabled diagnostic tools for broader monitoring applications. Full article

Background: Adolescence is a formative period for lifelong dietary patterns, yet Korean adolescents show low fruit and vegetable intake, high sugar and sodium consumption, and rising obesity, highlighting the importance of multidimensional assessment that integrates behavioral, cultural, environmental, and competency-related factors. Methods: A total of 1010 adolescents aged 12–18 years completed an online cross-sectional survey assessing food intake, dietary and physical activity behaviors, dietary culture, and Food Literacy (FL) competencies. Standardized scores were used for hierarchical and K-means clustering to identify dietary practice patterns, and between-cluster differences were examined using ANOVA. Correlation and regression analyses were conducted to examine associations between Dietary Guideline Adherence (DGA) and FL. Results: Four clusters were identified—selective intake–low support (20.4%), regular habits–unbalanced intake (33.3%), high adherence (23.2%), and low adherence (23.1%)—with significant differences in DGA total and domain scores (p < 0.001). The high-adherence cluster showed balanced intake, regular routines, and strong household support, whereas the low-adherence cluster showed poor diet quality, irregular behaviors, and lower socioeconomic status. FL differed across clusters (p < 0.001) and correlated with DGA (r = 0.496, p < 0.01). Total FL predicted DGA (β = 0.496, p < 0.001), explaining 25% of its variance (R² = 0.246). Conclusions: Adolescent diet quality appears to be associated with behavioral, cultural, and competency-related factors. These findings suggest that cluster-specific strategies—such as fat–sugar–sodium reduction, promotion of low-sodium and diverse diets, and maintenance of balanced-dietary patterns—may support tailored school- and community-based nutrition programs and inform further longitudinal and intervention research. Full article

The energy transition in Ibero-American countries demands significant diversification, yet the vast potential of offshore renewable energies (ORE) remains largely untapped. Slow adoption is often attributed to the hostile marine environment, high investment costs, and a lack of institutional, regulatory, and industrial readiness. A critical barrier for policymakers is the absence of methodologically robust tools to assess national preparedness. Existing indices typically rely on simplistic weighting schemes or are susceptible to known flaws, such as the rank reversal phenomenon, which undermines their credibility for strategic decision-making. This study addresses this gap by developing a multi-criteria decision-making (MCDM) framework based on a problem-specific synthesis of established optimization principles to construct a comprehensive Offshore Readiness Index (ORI) for 13 Ibero-American countries. The framework moves beyond traditional methods by employing an advanced weight-elicitation model rooted in the Robust Ordinal Regression (ROR) paradigm to analyze 42 sub-criteria across five domains: Regulation, Planning, Resource, Industry, and Grid. Its methodological core is a non-linear objective function that synergistically combines a Shannon entropy term to promote a maximally unbiased weight distribution and to prevent criterion exclusion, with an epistemic regularization penalty that anchors the solution to expert-derived priorities within each domain. The model is guided by high-level hierarchical constraints that reflect overarching policy assumptions, such as the primacy of Regulation and Planning, thereby ensuring strategic alignment. The resulting ORI ranks Spain first, followed by Mexico and Costa Rica. Spain’s leadership is underpinned by its exceptional performance in key domains, supported by specific enablers, such as a dedicated renewable energy roadmap. The optimized block weights validate the model’s structure, with Regulation (0.272) and Electric Grid (0.272) receiving the highest importance. In contrast, lower-ranked countries exhibit systemic deficiencies across multiple domains. This research offers a dual contribution: methodological innovation in readiness assessment and an actionable tool for policy instruments. The primary policy conclusion is clear: robust regulatory frameworks and strategic planning are the pivotal enabling conditions for ORE development, while industrial capacity and infrastructure are consequent steps that must follow, not precede, a solid policy foundation. Full article

Objective: Current data on the association between attention-deficit/hyperactivity disorder (ADHD) and essential hypertension (EH) in pediatric populations are very limited, as most research has focused on adults. This study investigated the long-term prevalence of EH in Israeli youth aged 5–18 years with ADHD, examining also trends in antihypertensive medication use. Methods: A retrospective cohort study was conducted using data from Leumit Health Services. The ADHD cohort (N = 18,558) was compared in a 1:2 ratio to controls (N = 37,116), who were strictly matched for age, gender, birth year and quarter, socioeconomic status (SES), sectors, region, and cumulative years of LHS membership up to the index date. Diagnoses of ADHD and EH were identified using ICD-9/10 codes, depending on the year of diagnosis. Logistic regression analyses were used to assess the associations between ADHD, EH and the use of antihypertensive medications over a 20-year follow-up. Results: ADHD-diagnosed children had a higher prevalence of EH, with odds ratios (ORs) of 3.17 (95% CI: 1.46–7.16, p = 0.0017) at 5 years, 2.94 (95% CI: 1.45–6.09, p = 0.0013) at 10 years, and 1.92 (95% CI: 1.26–2.93, p = 0.0015) at 20 years. ADHD patients showed a greater use of antihypertensive medications, including calcium channel blockers (OR 1.85, 95% CI: 1.02–3.35, p = 0.035), renin angiotensin system blockers (OR 2.20, 95% CI: 1.15–4.25, p = 0.013), and diuretics (OR 1.77, 95% CI: 1.21–2.60, p = 0.0028). Conclusions: These findings highlight an association between ADHD diagnosis and EH, suggesting regular cardiovascular monitoring of children with ADHD. Further studies are needed to uncover the role of stimulant medications and shared biological and behavioral factors involved in the pathogenesis. Full article

Vista landscapes of historic cities embody unique spatial order and cultural memory, and the scientific quantification of their visual quality presents a common challenge for both heritage conservation and urban renewal. Focusing on the Beijing Central Axis, this study integrates VR panoramic technology with the SBE-SD evaluation method to develop a visual quality assessment framework suitable for vista landscapes of historic cities, systematically evaluating sectional differences in scenic beauty and identifying their key influencing factors. Thirteen typical viewing places and 17 assessment points were selected, and panoramic images were captured at each point. The evaluation framework comprising 3 first-level factors, 11 secondary factors, and 24 third-level factors was established, and a corresponding scoring table was designed through which students from related disciplines were recruited to conduct the evaluation. After obtaining valid data, scenic beauty values and landscape factor scores were analyzed, followed by correlation tests and backward stepwise regression. The results show the following: (1) The scenic beauty of the vista landscapes along the Central Axis shows sectional differentiation, with the middle section achieving the highest scenic beauty value, followed by the northern section, with the southern section scoring the lowest; specifically, Wanchunting Pavilion South scored the highest, while Tianqiao Bridge scored the lowest. (2) In terms of landscape factor scores, within spatial form, color scored the highest, followed by texture and scale, with volume scoring the lowest; within marginal profile, integrity scored higher than visual dominance; within visual structure, visual organization scored the highest, followed by visual patches, with visual hierarchy scoring the lowest. (3) Regression analysis identified six key influencing factors, ranked in descending order of significance as follows: color coordination degree of traditional buildings, spatial openness, spatial symmetry, hierarchy sense of buildings, texture regularity of traditional buildings, and visual dominance of historical landmark buildings. This study establishes a quantitative assessment pathway that connects subjective perception and objective environment with a replicable process, providing methodological support for the refined conservation and optimization of vista landscapes in historic cities while demonstrating the application potential of VR panoramic technology in urban landscape evaluation. Full article

This study investigates how economic growth, financial integration, social integration, and knowledge management shape CO₂ emissions in Saudi Arabia using quarterly data from 1995Q1 to 2024Q4. It applies kernel-regularized quantile regression to capture nonlinear and state-dependent effects across the conditional distribution of emissions without imposing restrictive parametric assumptions, while regularization mitigates overfitting and multicollinearity. The results reveal strong distributional heterogeneity. Economic growth is emission-augmenting and is strongest at the lower tail, weaker around the median, and positive again in the upper tail. Financial integration reduces emissions across quantiles, most strongly under low-emission states, while social integration is mostly near-neutral beyond the lower tail. Knowledge management increases emissions throughout, and quantile Granger causality is concentrated in the upper quantiles, indicating stronger predictive linkages when emissions are high. Based on these findings, this study proposes precise, quantile-specific policy guidelines across the distribution. Full article

In citrus cultivation practice, regular monitoring of leaf leaf relative water content (RWC) can effectively guide water management, thereby improving fruit quality and yield. When applying hyperspectral technology to citrus leaf moisture monitoring, the precise quantification of RWC still needs to address issues such as data noise and algorithm adaptability. The noise interference and spectral aliasing in RWC sensitive bands lead to a decrease in the accuracy of moisture inversion in hyperspectral data, and the combined sensitive bands of chlorophyll (LCC) in citrus leaves can affect its estimation accuracy. In order to explore the optimal prediction model for RWC of citrus leaves and accurately control irrigation to improve citrus quality and yield, this study is based on 401–2400 nm spectral data and extracts noise robust features through continuous wavelet transform (CWT) multi-scale decomposition. A high-precision estimation model for citrus leaf RWC is established, and the potential of CWT in RWC quantitative inversion is systematically evaluated. This study is based on the multi-scale analysis characteristics of CWT to probe the time–frequency characteristic patterns associated with RWC and LCC in citrus leaf spectra. Pearson correlation analysis is used to evaluate the effectiveness of features at different decomposition scales, and the successive projections algorithm (SPA) is further used to eliminate band collinearity and extract the optimal sensitive band combination. Finally, based on the selected RWC and LCC-sensitive bands, a high-precision predictive model for citrus leaf RWC was established using partial least squares regression (PLSR). The results revealed that (1) CWT preprocessing markedly boosts the estimation accuracy of RWC and LCC relative to the original spectrum (max improvements: 6% and 3%), proving it enhances spectral sensitivity to these two indices in citrus leaves. (2) Combining CWT and SPA, the resulting predictive model showed higher inversion accuracy than the original spectra. (3) Integrating RWC Scale7 and LCC Scale5-2224/2308 features, the CWT-SPA fusion model showed optimal predictive performance (R² = 0.756, RMSE = 0.0214), confirming the value of multi-scale feature joint modeling. Overall, CWT-SPA coupled with LCC spectral traits can boost the spectral response signal of citrus leaf RWC, enhancing its prediction capability and stability. Full article