Search Results (160)

The 12 November 2025 G4 geomagnetic storm—the third most intense of solar cycle 25—was triggered by a complex shock-ICME (interplanetary coronal mass ejection) structure as a result of three ICMEs and driven shocks that arrived on 11–12 November. The main enhancement in the interplanetary magnetic field occurred in the sheath region behind the shock driven by the second ICME. The Dst index reached −217 nT (the SYM-H index reached −254 nT) and the maximum Kp index was 9-. To comprehensively analyze the causes of the storm and its complex effects on near-Earth space, we used a multi-instrumental data set, involving data from satellite missions (ACE, SDO, PROBA2), GNSS networks, ionosondes, optical instruments, high-frequency radars (SuperDARN-like), and cosmic ray monitors. The auroral oval expanded equatorward (down to ~35° N in America). We recorded a super equatorial plasma bubble that almost reached the auroral oval boundary. The equatorial anomaly crests intensified, exceeding 175 TECU, and shifted poleward (8–10°). At mid-latitudes, the F2 layer critical frequency exhibited a strong negative disturbance (−50%) during the main phase, followed by an unusually prolonged and intense positive phase (+100%). GPS Precise Point Positioning errors increased to 2–3 m at high latitudes and in regions affected by the equatorial bubble. The event also featured a Forbush decrease and ground-level enhancement (GLE 77 according to the database hosted by the University of Oulu) associated with the X5.1 solar flare. The results underscore the complex chain of processes from solar storm to geomagnetic and ionospheric responses, highlighting the risks to satellite-based navigation and communication systems. Full article

Social determinants of health (SDoH) comprise a broad array of social conditions, such as access to food and housing, that facilitate or impede individual behavior. The aim of this study was to assess the association between SDoH and cigarette smoking-related outcomes among U.S. adults (aged ≥18 years) by using data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS). Cross-sectional data were obtained from the Social Determinants and Health Equity (SD/HE) module, conducted in 33 states, the District of Columbia, and Puerto Rico as part of the 2023 BRFSS. We examined four indicators of adverse SDoH (i.e., food insecurity, housing insecurity, utility insecurity, and lack of reliable transportation) and three cigarette smoking-related outcomes (i.e., cigarette smoking status, menthol cigarette smoking, and past-year quit attempt). All analyses were conducted with SAS 9.4 and used BRFSS sampling weights to adjust for the complex sampling design. Among 45,160 respondents, 2991 (7.8%) were adults who smoked cigarettes in the past month, of whom 570 (16.5%) reported making a quit attempt in the past 12 months. Menthol cigarette use was reported by 634 (22.0%) adults who smoked cigarettes in the past month. In adjusted analyses, each SDoH measure (i.e., food insecurity (aOR = 1.70, 95% CI: 1.19–2.41, p < 0.01), housing insecurity (aOR = 1.66, 95% CI: 1.06–2.59, p < 0.05), utility insecurity (aOR = 1.92, 95% CI: 1.01–3.65, p < 0.05), and lack of reliable transportation (aOR = 1.67, 95% CI: 1.03–2.73, p < 0.05)) was significantly associated with making a quit attempt in the past 12 months. Food insecurity was significantly associated with the odds of current cigarette smoking. Food insecurity and utility insecurity were independent risk factors for using menthol cigarettes. U.S. adults experiencing adverse SDoH are trying to stop smoking at higher rates than adults not experiencing adverse SDoH. Findings demonstrate that SDoH is a strong predictor of cigarette smoking status, menthol cigarette smoking, and past-year quit attempts among U.S. adults. Full article

Background: Antegrade continence enemas (ACEs) are administered by appendicostomy or cecostomy to manage bowel conditions. Cecostomies utilize buttons while appendicostomies utilize the appendix for colonic flushing. This study evaluates the outcomes and overall burden of these procedures in a mixed urban–rural population, highlighting unique social determinants of health (SDoH) and access factors. Methods: A retrospective cohort analysis of 31 pediatric patients was conducted at a tertiary academic hospital where 8 underwent a Malone-type ACE (MACE) and 23 underwent a laparoscopic cecostomy (LC) between 2014 and 2024. Results: Age at surgery was significantly higher in the MACE group versus the LC group (14.6 vs. 8.1 years). Patients who underwent MACE had longer hospital stays than patients who underwent LC (7.5 vs. 4.5 days, p = 0.014) and significantly higher 30-day readmissions (5 vs. 2, p = 0.001). Granulation tissue was significant in LC (82.6%) compared to MACE (13.5%, p = 0.001). Moreover, need for surgical revision occurred more in the MACE group (25%). Analysis of SDoH revealed that most of the cohort lived in areas with low childhood opportunity and high socioeconomic deprivation, particularly those undergoing MACE. Financially, MACE was associated with substantially higher total, direct, and indirect costs than LC, with the difference in total cost reaching statistical significance. Conclusions: In this setting,10-year complication rates were low. This reflects the development of a new dedicated longitudinal bowel management program in mid-Missouri. Functional outcomes at the end of the 10-year period were comparable between both cohorts with the achievement of continence. These findings support tailoring surgical approaches to patient needs. Full article

Background and Objectives: Social Determinants of Health (SDoH) are factors that can contribute to health inequities. Improving the conditions in which people are born, grow, and live requires collaboration between professionals from different health sectors. Given their health and well-being-focused care, nurses are crucial to promoting health equity in the care they provide. Thus, their knowledge, attitudes, and actions—i.e., practice—(KAP) regarding SDoH could serve as a helpful starting point for promoting care that also focuses on non-medical factors. This study aims to map the SDoH assessed in the literature in relation to nurses’ and nursing students’ KAPs, using the Dahlgren–Whitehead Rainbow Model as a logical framework. Methods: Following PRISMA guidelines, a systematic literature review was conducted using PubMed, Scopus, Web of Science, CINAHL, and PsycINFO. Records published until June 2024 were selected from primary studies involving nurses and nursing students, with no time limits. The assessed determinants were adapted and categorised according to the Rainbow Model Levels. Results: 22 results were eligible. The SDoH (in general), poverty, social justice, social gradient, social inclusion and exclusion, discrimination, diversity, equity and inequality, food insecurity and access to nutritious food, employment status, geographical isolation, healthcare services, housing difficulties, transportation, social support, individual lifestyle factors, and health literacy were assessed on KAPs. Conversely, health equity has been assessed just for knowledge and attitudes. Considering the latter level of the Rainbow Model and the relative categorisation of the results, age, sex, and constitutional factors were not examined in the studies included in this review. Conclusions: This review maps the most and least frequently assessed SDoH in relation to KAP. As nurses are essential to providing care that considers SDoH, improving health outcomes, and addressing health inequities, and advocating for community health, it would be valuable to enhance nursing education from baccalaureate through postgraduate courses. Moreover, a strong relationship with different healthcare professionals is needed. Full article

Cancer health disparities represent profound inequalities in incidence, outcomes, and survivorship across populations. While traditionally examined through distinct lenses of either molecular biology or social epidemiology, these disparities arise from the complex interplay of genetic susceptibility, epigenetic dysregulation, and social determinants of health (SDoH). This review proposes that DNA damage and genomic instability serve as a critical mechanistic bridge, integrating exposures from the societal level to cellular dysfunction. We synthesize evidence demonstrating how SDoH—such as systemic inequities, environmental exposures, and chronic stress—converge with genetic and epigenetic factors to disproportionately increase DNA damage burden, impair repair mechanisms, and accelerate tumorigenesis in marginalized communities. Using the elevated gastrointestinal cancer rates among Native Hawaiians and Pacific Islanders (NH/PI) as a case study, we illustrate how historical, environmental, and socioeconomic factors interact with biological pathways to drive disparities. The review highlights key advances in DNA damage research—from somatic mutation theory to the modern understanding of chronic genomic stress—and explores how innovations in single-cell genomics, biomarker discovery, and computational modeling can unravel disparity etiologies. We argue that a translational framework linking social exposure data to molecular biomarkers of DNA damage is essential for moving beyond descriptive disparities to mechanistic understanding. Ultimately, addressing cancer equity requires interdisciplinary strategies that bridge molecular oncology, public health, and community-engaged research, targeting the root causes where social inequities become biologically embedded as genomic instability. Full article

Background and aims: Amid global aging, the role of diet in cognitive health is crucial. The healthful plant-based diet index (hPDI) is linked to cardiometabolic benefits, but its association with cognitive function in older adults, particularly through nutritional status and across different socio-geographic contexts, remains unclear. This study investigated the association between hPDI and multidimensional cognitive function, the mediating role of nutritional status, and potential associated modifications by urban–suburban location and gender. Methods: A community-based cross-sectional study was conducted in Shanghai, China, involving 2079 older adults (aged ≥60). Dietary intake was assessed by a validated food frequency questionnaire (FFQ) to calculate hPDI. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment-Basic (MoCA-B), and Clinical Dementia Rating (CDR). Nutritional status was measured by the Mini Nutritional Assessment (MNA). Hierarchical regression, interaction, and mediation analyses were performed, adjusting for comprehensive covariates based on social determinants of health (SDoH). Results: Higher hPDI was significantly associated with better cognitive scores (MMSE: β = 0.083, p < 0.001; MoCA-B: β = 0.069, p < 0.001) and lower odds of worse CDR (OR = 0.944, p < 0.001) in fully adjusted models. In the cross-sectional mediation analysis, MNA statistically mediated a significant proportion of the observed associations (MMSE: 41.25%; MoCA-B: 53.68%; CDR: 38.98%). The protective association was consistent across urban and suburban areas. However, a significant three-way interaction (hPDI × Gender × Area, p < 0.01) was found, with no cognitive benefit observed for males in suburban areas. Conclusions: Adherence to a healthful plant-based diet is associated with better cognitive function in older adults, partly statistically mediated by improved nutritional status. While this association is geographically equitable in Shanghai, suburban males do not appear to benefit, highlighting the need for gender- and context-sensitive dietary interventions. Full article

Background: Personal protective measures help prevent infection and disease transmission during health crises such as Coronavirus disease 2019 (COVID-19). Populations facing barriers to adhering to these measures are more vulnerable to the health crisis. This study investigated the association of social drivers of health (SDoH), self-efficacy, and adverse substance use behavior changes with ability to practice COVID-19 personal protective behaviors among persons who inject drugs (PWID) with hepatitis C virus (HCV) infection history. Methods: This study used the Hepatitis C Real Options (HERO) study’s COVID-19 survey data (n = 157). The association of inability to practice COVID-19 personal protective behaviors (hand washing, social distancing, etc.) with (a) SDoH difficulties (employment, housing, etc.); (b) adverse substance use behavior change (overdose, injecting behavior, etc.); and (c) self-efficacy was tested using logistic regression. Results: Inability to practice any personal protective behaviors was more likely among those experiencing any vs. no SDoH difficulties [adjusted odds ratio (aOR) (95% confidence interval (CI))] = 4.57 (1.57, 16.40); p = 0.003] but less likely for those with higher overall self-efficacy [aOR (95% CI) = 0.55 (0.32, 0.93); p = 0.025] and self-efficacy for setting goals [aOR (95% CI) = 0.63 (0.40, 0.96); p = 0.031]. The association between adverse substance use behavior changes and the outcome was not significant. Conclusions: Greater SDoH difficulties and lower self-efficacy were associated with greater inability to practice COVID-19 personal protective behaviors. Interventions to meet SDoH-related challenges and increase self-efficacy could help encourage practice of personal protective behaviors and economically reduce disease burden during health crises. Full article

Background/Objectives: Continuous trauma-system monitoring is limited by the lack of scalable, low-cost tools. The Pavia Trauma Management Epidemiology (PaTraME) project uses routinely collected ICD-9-CM discharge data (SDO) and the Trauma Mortality Probability Model (TMPM) to derive Injury Severity Score (XISS) and probability of death (TMPM-POD), creating a cost-free surveillance framework for regional trauma networks. Methods: We conducted a retrospective study of all major-trauma admissions (XISS > 15) in Pavia Province from 2014 to 2021. Anonymized SDO records were linked with emergency department flows and mortality registries. XISS and TMPM-POD were computed for each case. Case volumes, severity distributions, hub-centralization, and mortality (in-hospital, 30-day, and 180-day) were analyzed using trend and regression models (p < 0.05). Conclusions: We identified 1959 major-trauma admissions. Volumes increased up to 2019, dropped during the COVID-19 pandemic, and partially recovered in 2021 (p < 0.001). Overall, 61.5% of patients were admitted to hub centers, with an upward trend (p < 0.001). Hubs treated more severe trauma (median XISS 17 vs. 16; TMPM-POD 0.06 vs. 0.05, both p < 0.001). In-hospital mortality remained stable (8.2–11.4%, p = 0.828). TMPM-POD showed strong agreement with observed in-hospital mortality (Lin’s concordance correlation coefficient 0.81), though calibration worsened at higher risk levels. PaTraME confirms TMPM-POD as a valid mortality predictor and demonstrates a reproducible administrative-data framework for trauma surveillance. Rising hub admissions and stable mortality despite increasing complexity suggest improved system performance. Stratification of XISS and TMPM-POD between hub and spoke centers highlights peripheral hospitals managing disproportionately severe cases, informing targeted resource allocation and supporting quality improvement via automated dashboards. Full article

Refugees often face significant barriers to healthcare access and integration, contributing to poor health outcomes. Although perceptions of health are known predictors of self-reported health status, little is known about how refugees themselves conceptualize health. This study employed a community-engaged, transformative mixed-methods design to explore refugee health perceptions in the Denver-metro area. Data collection included 149 surveys and 27 interviews with refugees and asylum seekers conducted between November 2018 and March 2019. Hierarchical linear regression was used to assess associations between social determinants of health (SDoH) and self-reported health, while qualitative data were analyzed using a constant comparative approach. The final regression model explained 75.8% of the variance in self-reported health (R² = 0.758, p < 0.001). Significant predictors included country of origin (Burma: −3.419, p = 0.030; Somalia: −9.155, p < 0.001), age (1.901, p < 0.001), sex (male: −3.252, p < 0.001), and education level (−0.999, p < 0.001). Qualitative findings revealed themes such as health as the ability to live life and health as happiness, each shaped by cultural context, community connectedness, and perceptions of safety. Integrating these findings highlights how structural conditions and culturally rooted understandings of well-being intersect to shape refugee health after resettlement. This study underscores the need for public health and clinical interventions that center refugee-defined priorities and suggests future research should incorporate constructs, such as happiness and culturally grounded notions of safety, that emerged as central to health in this study. Full article

Background/Objectives: Type 2 diabetes (T2D) is a substantial health burden on foreign-born Haitian Americans (FBHAs) in the United States, who experience poorer health outcomes for T2D, in particular, cardiovascular disease and diabetes nephropathy. Understanding the factors that contribute to these disparities is essential. The purpose of this study was to examine the association between demographic, clinical, diabetes self-management, and social determinants of health (SDoH) factors with continuous glucose monitor (CGM-derived) glycemic indices in adult FBHAs with T2D. Methods: A cross-sectional exploratory correlation study was conducted in two urban health clinics, focusing on FBHAs aged 21 or older who had T2D for at least one year. Data were analyzed using SAS 6.4, employing descriptive statistics, bivariate correlations, and multiple regression models. Results: The study included 59 participants (49.2% male; mean age = 51.7 years, SD = 9.9), with an average T2D duration of 7.7 years (SD = 6.8) and an average of 1.63 (SD = 1.30) chronic diseases. A total of 29% were overweight while 21% had obesity with a mean HbA_1c of 58 mmol/mol (7.5%). A higher body weight and poorer dietary habits were associated with elevated glucose levels (standardized β ≈ 0.25 and −0.24). Greater race-related stress was correlated with greater glucose variability (β ≈ 0.46). Conclusions: These findings highlight the importance of addressing SDoH, such as race-related stress and food insecurity, to improve T2D self-management among FBHAs. Assessing and mitigating these risk factors can enhance glycemic control and health outcomes. Additionally, the findings demonstrate that CGM is feasible and acceptable for this population, showing exploratory findings and preliminary effect sizes that provide a strong basis for future, large-scale investigations. Full article

To address the problems of the traditional Supply–Demand Optimization (SDO) algorithm in wireless sensor network (WSN) node deployment—such as blind search direction, weak global exploration capability, coarse boundary handling, and insufficient maintenance of population diversity—this paper proposes a Multi-Strategy Enhanced Supply–Demand Optimization algorithm (MESDO). The proposed MESDO is validated on the CEC2017 and CEC2022 benchmark test suites. The results demonstrate that MESDO achieves superior performance in unimodal, multimodal, hybrid, and composite function optimization: for unimodal functions, it enhances local exploitation precision via elite-guided search to quickly converge to optimal regions; for multimodal functions, the adaptive differential evolution operator effectively avoids local optima by expanding exploration scope; for hybrid and composite functions, the centroid-based opposition learning boundary control maintains stable population diversity, ensuring adaptability to complex solution spaces. These advantages enable MESDO to effectively avoid premature convergence. According to the Friedman test, MESDO ranks first on CEC2017 (d = 30), CEC2022 (d = 10), and CEC2022 (d = 20), with average rankings of 1.20, 1.67, and 1.33, respectively—significantly outperforming the second-ranked SDO (average rankings of 3.60, 3.25, and 3.83). Finally, MESDO is applied to WSN deployment optimization. Its average coverage rate (86.80%) exceeds that of SDO (84.41%) by 2.39 percentage points, while its minimum coverage (84.80%) is 21.21 percentage points higher than that of AOO (69.96%). Moreover, its standard deviation (8.1308 × 10⁻³) is the lowest among all compared algorithms. The convergence curve reveals that MESDO achieves 82% coverage within 50 iterations, which is significantly faster than SDO (80 iterations) and IWOA (100 iterations). The node deployment distribution further shows that the generated nodes are uniformly distributed without coverage blind spots. In summary, MESDO demonstrates superior optimization accuracy, convergence speed, and stability in both function optimization and WSN deployment, providing a reliable and efficient approach for WSN deployment optimization. Full article

Adverse childhood experiences (ACEs) are established predictors of long-term health risks. While pediatric practices increasingly screen for social drivers of health (SDOH) and other family psycho-social stressors, routine ACEs screening is not recommended due to lack of evidence for long-term benefit and concerns over stigmatization, re-traumatization, and non-standardized follow-up protocols. We piloted routine ACEs screening in Pediatric Primary Care practices that already routinely screen for SDOH, maternal depression and intimate partner violence (IPV). This retrospective chart review (2016–2020) explored the extent to which these family psycho-social screenings could serve as a relative proxy for ACEs identification. Among 1492 participants (738 children aged 0–5 and 690 caregivers mean age 30.3 ± 6.9), ACE and SDOH screening results were significantly associated (p < 0.002), particularly with housing insecurity (p < 0.014). However, 51.7% of individuals who reported a positive ACE screen were not flagged by the SDOH measure (false negatives), indicating relatively poor sensitivity. The negative predictive value for negative SDOH screens and negative ACEs was higher at 86%. These findings suggest that SDOH screening misses over half of true positives, and therefore reliance on SDOH screening alone may underestimate ACE exposure in pediatric primary care. Full article

Zero-sum beliefs about human–nature relations represent a relatively understudied psychological construct that can shape prosocial behaviours directed toward both the natural environment and humans. Yet, little is known about the individual difference factors that contribute to these beliefs. This study investigates whether Need for Cognition, Tolerance of Ambiguity, and Social Dominance Orientation (SDO) predict zero-sum beliefs about the human–nature relationship (ZSB-NH). A cross-sectional, online survey (N = 355 Australians, M_Age = 52.77) assessed Need for Cognition, Tolerance of Ambiguity, SDO, and ZSB-NH, with hierarchical multiple regression revealing that together, Need for Cognition, Tolerance of Ambiguity, and SDO explained 29.9% of the variance in ZSB-NH. However, only SDO, and specifically SDO-Anti-Egalitarianism, significantly predicted ZSB-NH, with a positive and large effect. Need for Cognition and Tolerance of Ambiguity were not significant predictors of ZSB-NH, despite significant negative correlations with ZSB-NH, highlighting the importance of multivariate research to reveal the true effects of these predictors. The findings contribute to the limited research on ZSB-NH, suggesting that interventions should target hierarchical attitudes to influence zero-sum beliefs about the human relationship with nature. Full article

Background: How individuals develop and form perspectives of those around them differs from person to person. Factors such as childhood parental bonding styles can affect how prejudice forms. Social dominance in adulthood may also be affected by childhood experiences through the bonding received. Not many studies examine how an individual’s Social Dominance Orientationcan be influenced by parental bonding styles in childhood. Furthermore, few studies that investigated neural correlates are associated with these two variables. As such, this study aims to establish how parental bonding in childhood affects brain regions that are also implicated in adult SDO. Methods: Ninety-one participants were recruited and underwent magnetic resonance imaging (MRI). Social Dominance Orientation (SDO) and Parental Bonding Index (PBI) were collected. We used DARTEL package in SPM12 to conduct a whole-brain analysis. The ROI analyses were focused on amygdala grey matter volume (GMV). Results: This study identified a strong correlation between PBI and SDO. Interestingly, PBI_Care and PBI_Protection scores significantly predicted SDO scores. SDO was positively associated with amygdala GMV, PBI_Care was negatively associated with amygdala GMV, and PBI_Protection was positively associated with amygdala GMV. Conclusions: Our results show that PBI and SDO are highly correlated as well as their association with the amygdala and other key regions of the brain. Full article

Background: In the field of autonomous driving, existing object detection algorithms still face challenges such as excessive parameter counts and insufficient detection accuracy, particularly when handling dense targets, occlusions, distant small targets, and variable backgrounds in complex road scenarios, where balancing real-time performance and accuracy remains difficult. Methods: This study introduces the SDO-YOLO algorithm, an enhancement of YOLOv11n. First, to significantly reduce the parameter count while preserving feature representation capabilities, spatial-channel reconstruction convolution is employed to enhance the HGNetv2 network, streamlining redundant computations in feature extraction. Then, a large-kernel separable attention mechanism is introduced, decoupling two-dimensional convolutions into cascaded one-dimensional dilated convolutions, which expands the receptive field while reducing computational complexity. Next, to substantially improve detection accuracy, a reparameterized generalized feature pyramid network is constructed, incorporating CSPStage structures and dynamic channel regulation strategies to optimize multi-scale feature fusion efficiency during inference. Results: Evaluations on the KITTI dataset show that SDO-YOLO achieves a 2.8% increase in mAP@0.5 compared to the baseline, alongside reductions of 7.9% in parameters and 6.3% in computation. Generalization tests on BDD100K and UA-DETRAC datasets yield mAP@0.5 improvements of 1.9% and 3.7%, respectively, over the baseline. Conclusions: SDO-YOLO achieves improvements in both accuracy and efficiency, demonstrating strong robustness across diverse scenarios and adaptability across datasets. Full article