Search Results (5,293)

In the United States, although the gaps in health insurance coverage by sexual orientation have been closing since the implementation of the Affordable Care Act and legalization of same-sex marriage, the LGB group (i.e., lesbian, gay, bisexual) continues to report healthcare utilization and access inequities such as more delayed or unmet care. The extant research has often examined healthcare utilization and access inequities due to affordability (e.g., out-of-pocket costs). However, healthcare utilization and access inequities are only partially explained by cost reasons; there are non-cost reasons that have not been adequately empirically examined. The present study innovatively includes discrimination structural variables to understand how social structure is associated with healthcare utilization and access inequities of LGB people. It focuses on two routine health services—regular check-ups and prescription medications—for LGB people who have chronic diseases. Additionally, sexual orientation may intersect with sex assigned at birth (sex, hereafter, i.e., male, female) to impact healthcare utilization and access inequities. The current study applies quantitative intersectional analysis to understand healthcare utilization and access inequities from a sexual orientation and sex intersectional lens and for easier and clearer interpretations of intersectional results and more actionable policy implications for inter-categorical groups. Using the 2023 National Health Interview Survey (weighted N = 136,231,053), we conducted quantitative intersectional analysis for logistic regression using complex survey data. First, we fit a series of logistic regression models with sexual orientation–sex interactions for routine healthcare utilization and access outcomes, adjusting for covariates. Second, we calculated average marginal predictions for inter-categorical groups by interacting sexual orientation and sex and other covariates. Third, we computed risk ratios of average marginal predictions for all the covariates. Lastly, we examined the interaction of inter-categorical groups/sexual orientation and structural variables. Our results show that experiencing a higher level of discrimination is positively associated with underutilization of regular check-ups and lower access to prescription medications, and this effect is stronger for LGB people. Further, LGB women are least likely to utilize regular check-ups and LGB men are least likely to access prescription medications among the inter-categorical groups. Highlighting structural issues of healthcare utilization and access offers new evidence on healthcare utilization and access inequities that can inform policies for raising awareness of and addressing structural issues. The intersectional analyses suggest that relevant policies target LGB women and LGB men. Full article

Understanding how drivers respond to feedback and incentives is crucial for designing data-driven interventions that enhance road safety. This study investigates driver profiling and behavioral change using high-resolution telematics data collected through the OSeven DrivingStar smartphone application within the O7Insurance project. The naturalistic driving experiment was divided into two main phases: a baseline period with personalized feedback (Phase A) and an incentive-based phase (Phase B) comprising two gamified driving challenges with distinct reward criteria. Using data from 86 active participants, k-means clustering identified three driver profiles—Low-Exposure Cautious, Balanced/Average, and High-Risk Drivers—based on exposure, harsh events, speeding, and mobile phone use. The Balanced/Average group exhibited statistically significant improvements during both challenges, reducing speeding frequency and intensity (e.g., from 4.8% to 3.7%, p < 0.01), while High-Risk Drivers achieved moderate reductions in speeding intensity (from 6.4 to 5.3 km/h, p < 0.05). Low-Exposure Cautious Drivers maintained stable, low-risk performance throughout. These findings demonstrate that incentive-based telematics schemes can effectively influence driving behavior, particularly among drivers with moderate risk levels. The study contributes to the growing body of research on gamified driver feedback by linking behavioral clustering with responsiveness to incentives, providing a foundation for adaptive and personalized road safety interventions. Full article

Background: For very-rare cancers such as pheochromocytoma and paraganglioma (PPGL), center-level case volume is uniformly low, rendering the traditional volume–outcome paradigm uninformative. This study examines whether cancer programs’ institutional resources, after adjusting for tumor-specific case volume, impact overall survival (OS) after surgery. Methods: The 2004–2021 National Cancer Database was queried for patients with a diagnosis of PPGL with malignant potential. Demographics, clinicopathologic characteristics, socioeconomic status, and treatment and survival variables—together with program resource tier (high resource = Academic/Research + Comprehensive Community Cancer Programs; low resource = Community Cancer + Integrated Network Programs), were extracted. IPW-Cox proportional hazard model and survival analysis were performed. Results: 1306 patients were identified, of whom 1066 (81.6%) were treated at high-resource programs. Mean age was 59.0 years and 55.1% were female (n = 719). Median follow-up was 61.7 months (maximum 207 months). Mortality was 28.3% (n = 278). Age, race, median income, tumor size, and surgical approach did not differ by resource tier. Patients treated at high- vs. low-resource programs differed by Charlson– Deyo score (p = 0.008), gender (p = 0.033), insurance status (p = 0.004), and distance traveled to facility (p < 0.001). On adjusted survival analysis, treatment at a high-resource program was associated with improved OS (HR = 0.64, p = 0.043) and a mean survival advantage of 23 months (p = 0.009) vs. a low-resource program. Age (HR = 1.03), tumor size >10 cm (HR = 4.18), and metastasis (HR = 4.17) independently predicted worse OS. Conclusions: Despite uniformly low PPGL case volumes nationally, treatment at high-resource cancer programs was associated with a 23-month longer mean survival and a 36% lower risk of death compared with low-resource cancer programs. Further studies are needed to identify the specific institutional factors that drive this survival advantage in rare cancers. Full article

This paper presents a comprehensive methodology to forecast the daily energy demand associated with recharging private electric vehicles in urban areas. The approach is based on plausible scenarios regarding the penetration of battery-powered vehicles and the availability of charging infrastructure. Accurate space and time forecasting of charging activities and power requirements is a critical issue in supporting the transition from conventional to battery-powered vehicles for urban mobility. This technological shift represents a key milestone toward achieving the zero-emissions target set by the European Green Deal for 2050. The methodology leverages Floating Car Data (FCD) samples. The widespread use of On-Board Units (OBUs) in private vehicles for insurance purposes ensures the methodology’s applicability across diverse geographical contexts. In addition to FCD samples, the estimation of charging demand for private electric vehicles is informed by a large-scale, detailed survey conducted by ENEA in Italy in 2023. Funded by the Ministry of Environment and Energy Security as part of the National Research on the Electric System, the survey explored individual charging behaviors during daily urban trips and was designed to calibrate a discrete choice model. To date, the methodology has been applied to the Metropolitan Area of Rome, demonstrating robustness and reliability in its results on two different scenarios of analysis. Each demand/supply scenario has been evaluated in terms of the hourly distribution of peak charging power demand, at the level of individual urban zones or across broader areas. Results highlight the role of the different components of power demand (at home or at other destinations) in both scenarios. Charging at intermediate destinations exhibits a dual peak pattern—one in the early morning hours and another in the afternoon—whereas home-based charging shows a pronounced peak during evening return hours and a secondary peak in the early afternoon, corresponding to a decline in charging activity at other destinations. Power distributions, as expected, sensibly differ from one scenario to the other, conditional to different assumptions of private and public recharge availability and characteristics. Full article

Background: Diabetes disproportionately affects U.S. subgroups, yet non-Hispanic multiracial adults are underrepresented in epidemiologic studies. This study aimed to examine behavioral and sociodemographic predictors of diabetes in this population. Methods: We analyzed data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) using a cross-sectional design that incorporated survey weights, strata, and primary sampling units. Binary logistic regression was employed to identify predictors of diabetes, including variables with p ≤ 0.20 from bivariate models in the multivariable analysis. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. Results: The study included a total of 6429 participants. Obesity (AOR = 4.16; 95% CI: 3.33, 33.23), being overweight (AOR = 2.05; 1.62, 2.60), poor general health (AOR = 2.82; 2.38, 38.35), age ≥ 65 years (AOR = 3.08; 2.60, 3.65), male sex (AOR = 1.34; 1.15, 1.58), and health insurance (AOR = 2.14; 1.35, 3.61) were associated with higher odds of diabetes. Physical activity (AOR = 0.76; 0.64, 0.90) and alcohol consumption (AOR = 0.55; 0.47, 47.65) were linked to lower odds of diabetes. Smoking status showed no significant association after adjustment. Conclusions: In non-Hispanic multiracial adults, factors such as adiposity and older age increased the risk of diabetes, while physical activity and alcohol consumption offered protective benefits. These findings indicate that current diabetes prevention strategies are applicable to this subgroup, and public health initiatives should prioritize their inclusion in outreach, screening, and intervention efforts. Full article

Agricultural insurance, as a stabilizer, is crucial for the promotion of agricultural modernization. Therefore, exploring the impact mechanism of agricultural insurance on agricultural modernization and seeking ways to promote it has important practical significance. This study uses China’s provincial panel data from 2008 to 2023 to empirically analyze the direct effect of agricultural insurance on agricultural modernization. The mediation effect, spatial Durbin, and threshold models are used to further explore the internal mechanism of agricultural insurance on agricultural modernization. Results reveal that (1) agricultural insurance plays a significant role in promoting agricultural modernization, with its robustness verified across various models and endogeneity tests. (2) Agricultural insurance can promote agricultural modernization effectively by expanding the scale of agricultural operations, increasing agricultural capital input, enhancing agricultural technology input, and promoting green agricultural production. (3) Agricultural insurance has a positive spatial spillover effect on the development of agricultural modernization in neighboring provinces. Furthermore, there is a threshold effect of agricultural insurance in promoting agricultural modernization, showing stronger effects in rural areas where the human capital level exceeds the single threshold or where the economic development level falls between the single and triple thresholds. (4) Heterogeneity analysis reveals that agricultural insurance exerts stronger promotional effects on agricultural modernization in non-grain-producing regions, in eastern and central areas, and during the initial stages of insurance development. The study proposes recommendations such as the differentiated promotion of agricultural insurance, enhancing the directionality of agricultural insurance policies, and improving the linkage mechanism between agricultural insurance and credit. Full article

Background: Pneumoconiosis is associated with chronic pulmonary and systemic complications, yet its relationship with pleural empyema remains insufficiently defined. This study evaluated the risk of pleural empyema among individuals with pneumoconiosis using a nationwide population-based cohort. Methods: Using Taiwan’s National Health Insurance database, we identified 14,441 patients with newly diagnosed pneumoconiosis and 57,764 matched controls by age, sex, and index year. Pleural empyema was ascertained using ICD-based definitions. Cox proportional hazards models, stratified and cluster-adjusted to account for matched design, were used to estimate hazard ratios (HRs). Competing-risk models, propensity score matching, E-value estimation, and mediation analysis were performed to evaluate robustness and residual confounding. Results: During follow-up, the incidence of pleural empyema was significantly higher in the pneumoconiosis cohort than in controls (2.33 vs. 1.02 per 1000 person-years). Pneumoconiosis was associated with an increased risk of pleural empyema (adjusted HR = 1.79, 95% CI: 1.47–2.18), consistent across subgroup analyses and competing-risk models. The strongest associations were observed among younger individuals and those without comorbidities. Sensitivity analyses, including 1:1 propensity score matching, yielded similar effect estimates. The E-value suggested that only a strong unmeasured confounder could fully explain the observed association. Conclusions: Patients with pneumoconiosis face a substantially elevated risk of developing pleural empyema, independent of demographic factors, comorbidities, corticosteroid use, and healthcare utilization. Intensified monitoring for pleural complications in pneumoconiosis patients who develop respiratory infections may lead to earlier diagnosis and a reduction in the negative outcomes associated with pleural empyema. Full article

In fraud detection, centralized approaches often face challenges related to data protection, security, and potential data breaches. Such methods require sensitive healthcare and insurance data to be pooled in one location, which increases vulnerability to misuse. This paper introduces FraudNetX, a privacy-preserving fraud detection framework, by utilizing Vertical Federated Learning (VFL) to address centralized system limitations. VFL enables models to be trained collaboratively while ensuring data privacy and security through quantifiable Differential Privacy (DP) guarantees (ε = 1.0, δ = 1 × 10⁵). FraudNetX implements a noise injection based on Differential Privacy (DP) with Gaussian noise (s = 1.2) in the process of training the model to guarantee confidentiality of the personal data. This research entails two partner organizations, which are a hospital and an insurance company, in an actual VFL configuration. The model is trained on 10 communication rounds in this federated setup, and the local optimization of each client is followed by the global aggregation step. Hospitals and insurers can learn fraud patterns without sharing their data. The proposed FraudNetX is a hybrid architecture which is composed of Feedforward Neural Networks (FFNNs) and transformer encoders. An adaptive weighting strategy has been applied to handle category imbalance concern and enhance recall of a few categories which are hard to detect, especially in fraud involving minorities, balancing the recall performance. The framework also includes a decision model that uses hospital data and claim behavior to classify each claim as legitimate, under review, or fraudulent. The experimental evaluation on the real-world dataset demonstrates that FraudNetX enhances the accuracy and F1-score of fraud detection (accuracy = 99.91%, F1 = 99.94%, ROC-AUC = 0.98) but does not violate data privacy. Full article

Disabled people face discrimination in healthcare settings, yet the compounding effects of intersectional identities remain underexplored. This project examines how different types of discrimination affect healthcare access and outcomes. We conducted a cross-sectional study of disability-based, race-based, gender-based, and sexuality-based discrimination using the 2022 National Survey on Health and Disability (NSHD; n = 2725) administered October 2021–January 2022. Measures used in this study include: (1) demographics; (2) types of discrimination; (3) unmet healthcare needs. Our sample was not nationally representative, as it consisted primarily of white, college-educated participants. Data were analyzed using summary statistics (STATA crosstab) among respondents with health insurance (n = 2566). Chi-squared tests were used to determine statistical significance. We fit logistic regression models for categorical responses (STATA logit), adjusting for participant characteristics. Some participants (41%; n = 2566) reported experiencing at least one form of discrimination, with 4.9% reporting race-, 15.08% gender-, 5.9% sexuality-, and 38.3% disability-based discrimination. Most participants (94%; n= 2412) reported at least one unmet healthcare need, from unmet prostheses (2.6%) to unmet dental care (34.8%). Compared with other care types, participants had the lowest odds ratio (OR = 0.38, p < 0.001) of having their preventive care or specialist care needs met. These findings highlight that discrimination contributes to disparities in particular areas of healthcare access and emphasizes a need for tailored interventions and additional research. Full article

Background: Obesity, gastrointestinal disorders, and mental health conditions are major drivers of employer healthcare expenditures, yet nutrition-focused interventions are infrequently reimbursed by health insurance. Precision nutrition, which integrates genetic, gut microbiome, biometric, and behavioral data to guide personalized dietary and lifestyle changes, may offer a scalable approach to reducing costs associated with diet-responsive conditions. Objectives: To evaluate the impact of a precision nutrition digital therapeutic on employer medical spending for diet-responsive conditions in self-insured U.S. health plans. Methods: We conducted a retrospective cohort study of medical claims from January 2022 to December 2024 across seven U.S. self-insured employers. Employees enrolled in a precision nutrition digital therapeutic (n = 258) were compared with never-enrolled peers (n = 8268). We estimated treatment effects using a two-stage difference-in-differences model with member and calendar-month fixed effects and clustered standard errors, focusing on per-member-per-year (PMPY) employer-paid medical spending overall and for predefined diet-responsive condition categories. PMPY estimates were defined conditional on months with positive employer-paid spending and therefore reflect changes in the intensity of spending among members generating claims rather than unconditional per-capita costs. Results: Enrollment in the precision nutrition digital therapeutic was associated with a −$3012 PMPY reduction in diet-responsive medical spending (p = 0.021) relative to non-enrolled peers on this conditional basis. The largest relative reductions were observed for digestive disorders (−$9240 PMPY; p = 0.029) and obesity (−$4884 PMPY; p = 0.007), with a smaller reduction for anxiety-related conditions (−$1356 PMPY; p = 0.043). Total medical spending decreased by −$4044 PMPY but this change did not reach statistical significance (p = 0.09). Conclusions: In this multi-employer claims analysis, participation in a precision nutrition digital therapeutic was associated with lower employer-paid medical expenditures for diet-responsive conditions, particularly digestive disorders and obesity. These findings suggest that precision nutrition digital therapeutics may represent a scalable strategy for employers to address the economic burden of chronic disease within self-insured health plans by reducing the intensity of medical spending among members. Full article

Background: Atopic dermatitis (AD) is a common pediatric skin disease that is associated with other atopic comorbidities, all of which correlate with higher rates of neurocognitive alterations such as developmental delays and ADHD. Methods: We conducted a retrospective chart review from January 2022 through January 2024 and identified 79 children aged 0–5 years who were prescribed dupilumab in the Massachusetts General Brigham healthcare system. We defined the patient population (including demographics, atopic comorbidities, and neurocognitive burden), and assessed whether time to treatment access varied by patient or prescriber characteristics. Results: The mean age at dupilumab initiation was 3.4 years, and 62.0% of patients were male. The cohort was diverse (48.1% White, 25.3% Black, 16.5% Hispanic/Latino, 10.1% Asian/other), with 48.1% publicly insured. Atopic comorbidities were common: 64.6% had food allergies, 34.2% had asthma, and 10.1% had eosinophilic esophagitis (EOE); 73.4% had two or more atopic diagnoses. Neurodevelopmental disorders affected 43.0% of patients, with speech and language delay most frequent (25.3%) and higher rates among those with EOE (87.5% vs. 38.0%, p < 0.01). The mean time to dupilumab approval was 20.9 days, with dermatologists achieving faster approvals than other specialists (10.6 vs. 51.9 days, p < 0.001). Conclusions: Our findings reveal infrequently reported high rates of atopic and neurologic comorbidities in young children with AD and underscore the importance of coordinated inter-specialty collaboration to ensure timely access to dupilumab for these patients. Full article

The recent expansion of sustainability studies has reshaped corporate governance and public oversight with direct implications for financial exposure and risk management. In particular, environmental auditing generates decision-useful signals on environmental liabilities, remediation and compliance costs, and budgetary/fiscal risks that affect both corporate financing conditions (e.g., cost of capital) and public finance resilience. This study conducts a comparative examination of environmental auditing practices in Moldova and Bulgaria over 2020–2025, asking how audit mandates, coverage, and disclosure practices inform banks, insurers, investors, and budget holders. Using documents from national legal databases and supervisory portals, we apply descriptive content analysis across structural, substantive, and procedural dimensions, with special attention to financial-risk channels (contingent liabilities, sanction risk, value-for-money and procurement risks). We find that Bulgaria exhibits stronger institutional implementation capacity, while Moldova shows legislative innovation; in both cases, stronger transparency, public participation, and digital audit analytics are needed to quantify fiscal and enterprise-level ESG risks. Overall, this paper positions environmental auditing as a governance lever linking sustainability oversight to finance- and risk-related outcomes, aligning with focus on sustainable finance, ESG disclosure, and governance. Full article

Background/Objectives: Iran carries a significant burden of mental health disorders. This study aimed to describe the status of mental health and mental health care in Iran between 2012 and 2023, addressing inequalities and mapping existing challenges in the mental health care system. Methods: A systematic literature review was conducted. Databases including Medline, CINAHL, APA PsycINFO, Scopus, Web of Science, and the Cochrane Library, as well as local databases such as SID, Magiran, and Noormags, were searched to identify studies related to mental health care in Iran. A total of 59 studies met the inclusion criteria. An inductive approach and thematic analysis were used to synthesize themes from the data. Results: Lower socioeconomic status (SES) was associated with higher rates of mental disorders due to poverty-related stressors and limited access to quality care. Gender disparities revealed that women are more vulnerable to mental health problems, exacerbated by perceived gender inequality. Ethnic minorities and undocumented migrant populations faced inadequate healthcare services, resulting in poorer mental health outcomes. Children and older adults also experienced mental health challenges influenced by sociodemographic factors. The main challenge for mental health care is establishing mechanisms to ensure more equitable access for all citizens. Additional challenges include limited awareness among policymakers, insufficient budget allocation, weak prevention programs, and poor intra- and inter-sectoral coordination and collaboration. A shortage of mental health care providers, as well as deficiencies in structure, system processes, and resources, further hinder progress. Conclusions: Socioeconomic factors exacerbate the challenges of Iran’s under-resourced mental health system. To address these issues, equity considerations must be integrated into mental health policies. Key interventions include the routine monitoring of mental health indicators, expanding insurance coverage for mental health services, and establishing dedicated services for children. Full article

This study examines participatory approaches to manage geo-hydrological risks associated with climate change, focusing on floods, landslides, and coastal erosion. The objective is to map hazards, participatory methods and tools, communication channels, stakeholder consultations, and governance scales involved. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for systematic reviews and covering the period 2000–2024, it analyses 236 peer-reviewed articles from Europe. It also examines 49 practical case studies from three Italian Public Consultation platforms, complementing the Europe-wide academic corpus to inform transferability to Italian governance setting. Results highlight a dominant academic emphasis on flood risks and climate change adaptation, likely driven by recent disasters and global policy initiatives, whereas landslides, coastal erosion, and integrated geo-hydrological risks remain underrepresented. Surveys, semi-structured interviews, and workshops are the most common consultation approaches, with more structured tools mainly preferred in multi-hazard settings to ensure comparability. Dissemination relied largely on face-to-face and online channels, while innovative approaches such as creative workshops and citizen-science initiatives are emerging. Stakeholder involvement typically included citizens, local authorities, experts, and voluntary associations, whereas key intermediaries such as local media, insurance agencies, cultural institutions, and universities are seldom engaged. Overall, the review identifies priorities for thematic diversification, integration of multi-hazard perspectives, improved methodological reporting, and broader inclusivity to strengthen participatory climate-risk governance. Full article

Background: Metabolic syndrome (MetS) comprises a cluster of metabolic abnormalities that increase the risk of type 2 diabetes mellitus (T2DM) and cardiometabolic morbidity. Although widely recognized, evidence on its documentation and follow-up in primary care is limited. This study aimed to evaluate the extent of MetS documentation in electronic medical records (EMRs), examine follow-up patterns and metabolic changes over time, and assess the incidence and predictors of new-onset T2DM according to baseline MetS severity. Methods: A retrospective cohort study was conducted on 8170 adults aged 30–50 years, insured by Clalit Health Services in Southern Israel, who met ATP III criteria for MetS in 2008 and were followed through 2015. MetS severity was classified as mild (three components), moderate (four), or severe (five). Changes in metabolic indices were assessed longitudinally, and predictors of T2DM were analyzed using Kaplan–Meier survival and multivariable Cox regression models. Results: Although all participants met the diagnostic criteria, only 1.6% had a recorded MetS diagnosis. Over the eight years of follow-up, 26% developed T2DM, with incidence increasing from 21% among those with mild MetS to 49% among those with severe MetS (p < 0.0001). Fasting plasma glucose rose significantly (median +13 mg/dL, p < 0.001), BMI remained stable, and modest improvements were observed in blood pressure and lipid levels. Elevated fasting glucose (HR 2.13, p < 0.001), higher BMI (HR 1.33, p = 0.010), and lower HDL (HR 1.26, p = 0.045) independently predicted diabetes onset. Conclusions: MetS remains markedly under-documented and insufficiently integrated into primary care follow-up. Despite regular clinical follow-up, improvements in metabolic indices were limited. These findings highlight the need for structured strategies to enhance MetS recognition and long-term management within routine practice. Full article