Search Results (720)

Background/Objectives: Stroke is the leading cause of death and disability among adults in China. Most survivors experience debilitating symptoms, including limb weakness, pain, fatigue, and depression, which impair quality of life and increase caregiver burden. This study aimed to identify clusters of symptoms and functional status in patients with stroke, their associated factors, and the influence of family burden. Methods: From February 2023 to February 2024, 779 patients with stroke from three Chinese tertiary hospitals completed an electronic questionnaire covering demographics and Patient-Reported Outcomes Measurement Information System measures, including depression, anxiety, pain interference, physical and cognitive function, social participation, and family burden. Using SPSS 26.0 and Mplus 8.0, chi-square tests, analysis of variance, latent class analysis, and multiple logistic regression were performed. Results: Latent class analysis identified three distinct symptom–functional clusters among stroke patients: “low-symptom high-function” (36.4%), “moderate-symptom moderate-function” (54.6%), and “high-symptom low-function” (9.0%). Multinomial logistic regression revealed that age ≥ 60 years (OR = 0.15, p = 0.001), freelancing (OR = 2.75, p = 0.019), unemployment (OR = 2.73, p = 0.018), monthly income ≥ 5000 yuan (OR = 2.56, p = 0.026), no medical insurance (OR = 4.26, p = 0.01), living alone (OR = 2.45, p = 0.031), and family burden (OR = 0.95, p < 0.001) were associated with the “high-symptom low-function class”. Conclusions: Chinese stroke patients exhibit substantial heterogeneity in symptom and functional profiles. To optimize stroke rehabilitation, healthcare professionals should develop targeted management strategies, prioritizing high-risk populations, particularly socio-economically vulnerable and socially isolated patients. Full article

Few national comparisons exist on healthcare utilization among e-scooter users, and prior research was limited by the absence of e-scooter-specific ICD-10-CM codes before 2021. Using newly implemented codes, this cross-sectional study compared emergency department disposition and injury patterns between e-scooter riders and bicyclists using the 2021 Nationwide Emergency Department Sample (n = 239,457 weighted encounters). Multivariable logistic regression adjusted for demographic, geographic, and temporal confounders, with interaction terms for insurance status, substance use, and motor vehicle involvement. E-scooter riders were more often female (46.5% vs. 24.7%) and under age 18 (47.6% vs. 37.4%) than bicyclists. Overall adjusted odds of admission or transfer did not differ significantly between groups (OR = 1.03; 95% CI: 0.86–1.23). Motor vehicle involvement significantly modified this relationship, with e-scooter riders showing higher odds of admission (OR = 1.67; 95% CI: 1.12–2.48). No significant effect modification was detected for insurance status or substance use. E-scooter riders more frequently sustained distal extremity fractures consistent with low-energy falls, while bicyclists experienced more proximal fractures and internal trauma. Updated ICD-10-CM codes improve e-scooter injury surveillance, and motor vehicle involvement represents a priority target for mode-specific prevention and infrastructure investment. Full article

Background/Objectives: Cardiovascular comorbidities are frequent in patients with solid malignancies, but their distribution across tumor types and their association with recorded all-cause mortality remain insufficiently defined. This study assessed clinically defined cardiovascular phenotypes across major cancer groups and examined their association with recorded all-cause mortality. Methods: We performed a retrospective cohort study of 2020 consecutive adult patients hospitalized with malignancies at University Hospital “Tsaritsa Yoanna—ISUL” between September 2023 and December 2025. Patients were classified as having respiratory, gastrointestinal, genitourinary, breast, or other solid malignancies. Four non-mutually exclusive cardiovascular phenotypes were predefined: atherosclerotic, cardiometabolic, structural heart disease, and thromboembolic. Mortality status was ascertained through the National Health Insurance Fund database and hospital electronic records. As complete time-to-event data were unavailable, mortality was analyzed as a binary outcome using multivariable logistic regression. Results: Recorded all-cause mortality occurred in 471 patients (23.3%) and differed significantly across solid tumor types (p < 0.001). Mortality was highest in respiratory cancers (42.3%), followed by gastrointestinal cancers (30.2%), other malignancies (23.5%), genitourinary cancers (14.9%), and breast cancer (9.1%). Cardiovascular phenotypes also differed across tumor groups. In the fully adjusted model, structural heart disease was associated with recorded all-cause mortality status after multivariable adjustment (OR 1.61, 95% CI 1.16–2.23, p = 0.004). The atherosclerotic phenotype showed a borderline association (OR 1.42, 95% CI 1.00–2.02, p = 0.051), whereas cardiometabolic and thromboembolic phenotypes were not associated with recorded mortality after multivariable adjustment. Model AUC was 0.771. When cardiovascular burden was modeled continuously, each additional cardiovascular factor was associated with higher odds of recorded all-cause mortality status (OR 1.12, 95% CI 1.03–1.21, p = 0.005). Conclusions: Cardiovascular profiles differed across cancer types. Structural heart disease was the most consistent cardiovascular phenotype associated with recorded all-cause mortality, while overall cardiovascular burden provided additional but modest mortality-related information. In our cohort, routinely recorded cardiovascular diagnoses helped characterize mortality-related clinical profiles. However, these findings should be viewed as observational and hypothesis-generating, and further longitudinal studies are needed before any clinical use can be recommended. Full article

Background: Influenza poses a serious threat to the health of older adults, and vaccination is a key strategy for prevention. As an economically developed city, Suzhou has a rapidly aging population, yet the influenza vaccination rate among older adults remains substantially lower than that in developed countries. There is an urgent need to understand the current vaccination status and its associated factors to inform future strategies for improving vaccination coverage. Objectives: To compare influenza- and vaccine-related knowledge, attitudes, practices, and information access channels between vaccinated and unvaccinated older adults (≥60 years) in Suzhou, and to identify factors associated with vaccination behavior in economically developed areas. Methods: A comparative cross-sectional survey was conducted from April to August 2024 across six districts or county-level cities randomly selected from Suzhou’s ten county-level administrative divisions. Participants were divided into vaccinated and unvaccinated groups based on their influenza vaccination status during the 2023–2024 influenza season. A two-stage sampling method was employed: the six districts were selected as primary sampling units; within each district, eligible older adults (aged ≥60 years) were randomly selected from two independent sampling frames—the vaccination information system for the vaccinated group and the basic public health service system for the unvaccinated group. Face-to-face structured interviews were conducted using a questionnaire consisting of four sections; data were entered using EpiData 13.1 and analyzed using SPSS 27.0. The χ² test, t-test, and multivariable logistic regression were used for statistical analysis. Results: Among 4622 valid older adults (vaccinated: n = 2007; unvaccinated: n = 2615), the vaccinated group scored significantly higher on influenza-related knowledge (4.06 ± 2.21 vs. 3.16 ± 2.33, p < 0.001), vaccine-related knowledge (2.10 ± 1.18 vs. 0.67 ± 1.07, p < 0.001), and perceived influenza risk scores (2.72 ± 1.42 vs. 2.26 ± 1.64, p < 0.001). Vaccine safety and efficacy endorsement were also markedly higher among the vaccinated group (70.3% vs. 22.0%; 49.7% vs. 9.3%). Regarding information sources, the vaccinated group relied more on healthcare institutions (54.56% vs. 46.92%), whereas the unvaccinated group relied more on television (60.34% vs. 51.17%). Multivariable logistic regression revealed that awareness of the influenza vaccine (aOR = 9.151, 95%CI: 6.32–13.25), having a planned vaccination site (aOR = 2.66, 95%CI: 2.01–3.54), and perceiving the vaccine as safe (aOR = 1.81, 95%CI: 1.31–2.49) were positively associated with vaccination, while rural household registration (aOR = 0.76, 95%CI: 0.63–0.93), full-time employment (aOR = 0.41, 95%CI: 0.28–0.60), and hypertension (aOR = 0.79, 95%CI: 0.65–0.94) were inversely associated. Conclusions: Compared with the unvaccinated group, the vaccinated group demonstrated significantly better influenza- and vaccine-related knowledge, risk perception, and recognition of vaccine safety and efficacy, and relied more on healthcare institutions for information. Multivariable regression analysis identified awareness of the influenza vaccine as the strongest associated factor. These findings suggest that vaccination coverage could be improved by strengthening vaccine knowledge promotion through healthcare professionals and increasing awareness of vaccination policies that integrate medical insurance reimbursement. Full article

This prospective study investigated the association of dog ownership with the onset of disabling dementia and mortality using propensity score weighting based on the physical, social, and psychological characteristics of dog owners, and then examined the potential causality of this relationship using an instrumental variable model. Additionally, we examined the costs and effects of dog ownership using cost-effectiveness analysis. Overall, 11,224 older adults selected using stratified and random sampling strategies in 2016 were analyzed. Dog ownership was defined as current, past, and never. Disabling dementia was defined according to a physician rating under the long-term care insurance system in Japan and mortality was ascertained by the Japanese national vital statistics during the approximately 7.5-year follow-up period. Current and past dog owners had an odds ratio (OR) of 0.53 (95% CI: 0.43–0.66) and 0.97 (0.86–1.09) of the onset of disabling dementia compared to never owners. ORs for mortality were 0.63 (0.51–0.79) in current dog owners and 0.88 (0.78–0.99) in past dog owners. Causal analysis showed that current dog owners (OR = 0.52, 95% CI: 0.27–0.98) and past dog owners (OR = 0.75, 95% CI: 0.55–1.03) had low ORs for incident dementia compared to never dog ownership. Corresponding values for mortality showed low ORs, but no significant effect on current dog owners (OR = 0.59, 95% CI: 0.35–1.01) and past dog owners (OR = 0.77, 95% CI: 0.60–1.00) compared to never owners. Results of cost-effectiveness analysis showed that dog ownership produced small but positive gains in quality-adjusted life years (QALYs) and was dominant (cost-saving and QALY-increasing) from the public payer perspective, reducing publicly financed medical and long-term care costs while increasing QALYs; when private dog-ownership costs were included in a scenario analysis, the incremental cost-effectiveness ratio (ICER) was ¥6,744,174 per QALY compared with no-dog status. This prospective study shows that dog ownership has a potential protective effect against the onset of disabling dementia in older adults. The study also revealed the potential of dog ownership to reduce public spending with regard to long-term care and medical expenditures. Full article

Background: People living with dementia (PLWD) are at increased risk for medical complications, including urinary tract infections (UTIs), which are often presented atypically with delirium or behavioral changes. These atypical presentations frequently prompt psychiatric consultation and complicated medical management. As the aging population grows, understanding how dementia influences UTI-related outcomes is critical for C-L psychiatrists working at the interface of medicine and psychiatry. Methods: This retrospective cohort study used the 2021 National Inpatient Sample (NIS) to identify adult inpatients with a principal diagnosis of UTI. Patients were stratified by the presence of a comorbid dementia diagnosis. Multivariate logistic and linear regression models adjusted for demographic, clinical, and hospital-level covariates were used to examine associations between dementia and outcomes: in-hospital mortality (primary), length of stay (LOS), hospital charges, and discharge disposition (secondary). Adjusted models included available demographic, socioeconomic, comorbidity, and hospital-level covariates, including age, sex, race/ethnicity, median household income quartile by patient ZIP code, insurance type, Charlson Comorbidity Index, hospital region, urban hospital location, and hospital teaching status. Results: Among 295,494 hospitalizations for UTI, 78,990 (26.7%) involved patients with dementia. Compared to those without dementia, PLWD were significantly older (mean age 82.5 vs. 69.5 years), more likely to be female, and had greater comorbidity burden. Adjusted analyses revealed that dementia was linked to higher odds of in-hospital mortality (aOR: 1.28, 95% CI: 1.03–1.58), longer LOS (+0.93 days, p < 0.01), and increased hospital charges (+$3243.50, p < 0.01). Additionally, PLWD had lower odds of discharge to home (aOR: 0.53) and higher odds of discharge to skilled nursing facilities (aOR: 1.94). Conclusions: Among patients hospitalized with a principal diagnosis of UTI, comorbid dementia was linked with higher in-hospital mortality, longer length of stay, higher hospital charges, and lower likelihood of discharge home. These findings should be interpreted in the context of important limitations of administrative data, including residual confounding and inability to distinguish symptomatic UTI from asymptomatic bacteriuria. Full article

Geographic variation (GV) in screening patterns for breast cancer exists among Zip Code Tabulation Areas (ZCTAs) in Florida, but most spatial analyses are based on frequentist point estimates which do not formally represent uncertainty. This study used a three-stage analytical approach to the breast cancer screening data at the zip code tract (ZCTA) level in Hillsborough County, Florida (n = 55 ZCTAs): first, a frequentist Poisson regression was applied with diagnostics for multicollinearity; second, global spatial autocorrelation (GSA) analysis was conducted using Moran’s I; and third, a Bayesian Poisson and a Bayesian negative binomial regression were performed, both estimated via the No-U-Turn Sampler in the brms/Stan framework. In ArcGIS Pro 3.6, spatial analyses were carried out. The dependent variable was the number of breast cancer screening exams conducted at the ZCTA level over the study period. Across all racial/ethnic subgroups, the observed number of screenings was correlated with the number of females in the household, while no independent correlation was found for median household income, insurance status or age by stratum variables after adjustment. There was no significant and strong spatial autocorrelation across the study area (Moran’s I = 0.003, z = 0.326, p = 0.745). The Poisson model did best among the Bayesian models with a Bayesian R² of 0.91, RMSE of 5.40, and MBE of 0.02. The results show the usefulness of Bayesian uncertainty quantification in small area public health surveillance and offer a framework for quantifying geographic variation in screening activity in a probabilistic manner. The results only compare screening examination (not population-standardized screening rates) and should be considered to reflect screening volume rather than screening participation. Full article

Background: Health literacy has become an important determinant of population health. Understanding health literacy levels among physical examination populations in China and examining their associations with social support and quality of life can provide evidence to guide preventive health strategies. Methods: A cross-sectional survey was conducted from May 2023 to May 2024 among 416 individuals undergoing routine physical examinations at a tertiary hospital in Xi’an, China. Participants completed a socio-demographic characteristics questionnaire, the Health Literacy Surveillance Rapid Assessment Questionnaire, the Social Support Rating Scale and the Euro-Qol five-dimension questionnaire. Descriptive statistics, correlation analyses, and multiple linear regression models were used to examine health literacy status, associated factors, and the former’s relationships with social support and quality of life. Results: Health literacy in the physical examination population was higher than the national average, and the proficiency rate was 52.4%. The findings indicate a significant and positive association between social support and health literacy (r = 0.398, p < 0.01); health literacy was found to be significantly and positively associated with quality of life (r = 0.216, p < 0.01). According to the multiple linear regression analysis, factors correlated with health literacy included age, gender, place of residence, marital status, educational level, monthly household income, payment method for physical examinations, frequency of physical examinations, and social support. Conclusions: Enhancing the health education competencies of medical personnel to enable effective dissemination of health information during physical examinations, promoting family involvement in health management to cultivate collective health awareness and practices, and improving the medical insurance system to encourage regular physical examinations are effective strategies for strengthening public health literacy. Full article

This article examines the later life experiences of women who participated in the revolutionary period in Cork city and county who did not go on to marry. Many within this cohort of Cork female activists experienced poverty, ill health, economic dependency and loneliness in the aftermath of the revolutionary period. Their unmarried status left these women particularly vulnerable in a patriarchal state structured—legally, economically and culturally—on an essentialist view of the married, childbearing woman. The invisibility of adult dependency in Ireland was summed up in the 1926 Census of Population report: ‘no account is taken in this inquiry of adults who may be supported out of the household income’. Mary Daly notes the ‘high proportion of the population working within a family economy which had little reliance on money incomes and waged employment’. This may, as she states, ‘have reduced the numbers exposed to the blunt instrument of unemployment’ in the context of the 1930s depression. However, the emotional and psychological effects of economic dependency have not been considered in any depth. The lack of statutory benefits for lower-class single women who were unable to access paid employment and who did not have the requisite social insurance stamps meant that they faced a vista of poverty and dependency on charity and family members. The latter were often begrudging and indisposed to assume the financial burdens of those who they often deemed economically ‘unproductive’. This article argues that, in so many cases, financial dependency resulted in the loss of agency and autonomy for unmarried women. Full article

As extreme weather events increasingly threaten global food systems, accurately assessing climate risks and predicting regional crop yields remains a critical challenge. Conventional prediction models often rely on direct weather-to-yield relationships, bypassing continuous crop physiological responses and limiting their capacity to capture fine-grained temporal impacts of meteorological anomalies. To address this, we propose a novel two-stage spatiotemporal functional framework that integrates high-resolution daily weather trajectories with satellite-derived indicators, utilizing the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) to represent canopy structural vigor and hydraulic status, respectively. In the first stage, a Historical Functional Linear Model (HFLM) dynamically maps daily meteorological trajectories (temperature, precipitation, and solar radiation) onto continuous physiological curves under strict temporal causality constraints. This generates bivariate coefficient surfaces that reveal dynamic windows of vulnerability and capture divergent, lagged physiological responses to climate stress. In the second stage, a spatially heterogeneous functional additive model integrates these weather-shaped physiological trajectories alongside raw meteorological dynamics as joint predictors for county-level yields. By extracting functional principal components and modeling flexible non-linear biological responses while accounting for continuous spatial heterogeneity, this dual-channel frameworkcaptures key aspects of both chronic physiological stress and acute meteorological shocks. Validated across a 25-year (2000–2024) U.S. Corn Belt panel, the proposed DC-FAM achieves a mean weighted mean squared prediction error (WMSPE) of 242.33 (bu/acre)² and a median out-of-sample $R_{\mathrm{cv}}^2$ of 0.422, outperforming all benchmarks including a random forest. Attribution of the 2012 flash drought further demonstrates the framework’s capacity to mechanistically trace the complete disaster propagation chain from anomalous spring warming to mid-summer hydraulic failure. The proposed framework provides a transparent, biophysically grounded tool for decoding dynamic climate stress trajectories and disaster propagation chains, offering potential implications for adaptive farm management and precision agricultural insurance. Full article

Background/Objectives: Prediabetes significantly increases the risk of type 2 diabetes and related complications. Limited data exist for prediabetes among minority groups in Israel, particularly Bedouins. In the Negev region, Jewish and Bedouin populations differ markedly in culture and socioeconomic status. This study aimed to identify gender- and ethnicity-specific predictors of prediabetes. Methods: This retrospective, population-based observational exploratory study used data from 28,754 adults aged 20–65 years insured by Clalit Health Services in Southern Israel (2010–2020). Individuals with prediabetes were matched 1:1 with controls by age, gender, ethnicity, and year of diagnosis. Multivariate logistic regression models stratified by gender and ethnicity identified independent predictors. Results: Prediabetes was identified at significantly younger ages among Bedouins than Jews (6.8 years in men, 11.3 in women). The strongest predictor across all subgroups was metabolic syndrome (OR 2.0–4.0). Gestational diabetes was a major risk factor in women, particularly Jewish (OR 3.6). Cardiovascular disease and the use of statins or thiazide diuretics were independently associated with increased odds of prediabetes. Triglyceride-to-HDL cholesterol ratio was consistently elevated among prediabetes patients. Conclusions: Metabolic and medication-related factors contribute significantly to prediabetes-associated risk, with distinct gender and ethnic patterns. Culturally tailored early interventions and individualized risk profiling may enhance diabetes prevention in Southern Israel. Full article

Background: Lynch syndrome (LS) is the most common hereditary cause of colorectal cancer (CRC), and colorectal surveillance has been shown to reduce death from CRC in this high-risk population. This study aimed to examine adherence to recommended endoscopic surveillance intervals in a LS cohort and identify factors associated with adherence. Methods: A retrospective review was performed of 1403 lower endoscopic procedure (LEP) reports from 540 individuals with LS completed between May 2001 and September 2023. Adherence was calculated by comparing the endoscopists’ recommended interval to the actual date of the subsequent procedure. Reports from individuals with ≥2 LEPs and those with follow-up intervals within the study period were included (n = 1170). A mixed-effect logistic regression analysis identified factors associated with adherence. Results: Among 1170 LEPs from 295 LS carriers, 67.4% were performed within the recommended interval. However, 68.8% of individuals had at least one procedure that was delayed. Increased adherence was significantly associated with prior detection of CRC (OR 9.30, 95% CI 1.16–74.32, p = 0.035) on an LEP. Marital status was significantly associated with adherence, with higher rates among married (OR 1.73, 95% CI 1.05–2.85, p = 0.030) and divorced/widowed individuals (OR 2.32, 95% CI 1.14–4.72, p = 0.020). Current smokers had a lower rate of adherence (OR 0.33, 95% CI 0.13–0.82, p = 0.018). No significant associations were observed with age, biological sex, race, or insurance status. Conclusions: Nearly one third of LEPs in our LS cohort were delayed. Efforts to address barriers and enhance adherence are essential to optimize outcomes for this high-risk population. Full article

Estimation of rice crop yield at the village level is essential because village is the Insurance Unit (IU) for rice crop in many regions in India, and timely and accurate yield information at this scale supports timely and transparent claim settlements for farmers and supports local agricultural planning. To achieve this, a multi-source satellite data-based machine learning approach was used to estimate rice yield at the village level using optical and SAR data, climatic data and land surface model-derived parameters in Kakinada of Andhra Pradesh, India. The predictor dataset included seasonal cumulative rainfall, seasonal Normalized Difference Vegetation Index (NDVI)-Max, seasonal NDVI-Mean, seasonal Land Surface Water Index (LSWI)-Max, seasonal LSWI-Mean, season total Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and season total Root Zone Soil Moisture (RZSM), and season total backscatter of the Sentinel-1 VH polarization were used to represent crop greenness, moisture status, photosynthetic activity, soil water availability, canopy structure, and seasonal water supply. For model development and validation, village-level rice yield data from 2017 to 2023 was used, which was collected through Crop Cutting Experiment (CCE) at the maturity stage of Kharif season. In this study, four machine learning models such as Random Forest (RF), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gradient Boosting (GB) were evaluated. The multi-source satellite data and yield data for the period 2017–2021 were used to train the models, which were independently tested on 2022 data and then applied to predict the rice yield in 2023. Leave-One-Year-Out (LOYO) cross-validation was also conducted on the 2017–2022 data to assess temporal robustness and generalization capability across years. Among the evaluated models, Random Forest exhibited the best overall performance. For the independent test year 2022, RF achieved an R² of 0.465, RMSE of 415.34 kg ha⁻¹, MAE of 322.22 kg ha⁻¹, and MAPE of 10.36%. For the prediction year 2023, RF achieved improved accuracy with an R² of 0.838, RMSE of 325.75 kg ha⁻¹, MAE of 262.21 kg ha⁻¹, and MAPE of 7.68%. Further, LOYO cross-validation also showed the robustness of RF, achieving the highest mean R² of 0.702 and mean RMSE of 384.73 kg ha⁻¹. The results illustrate that multi-source satellite data combined with machine learning can be a reliable and operationally useful tool in predicting village-level rice yield, which can be used for crop insurance claim settlement. Full article

Background: Infective endocarditis (IE) requires 4–6 weeks of intravenous antimicrobial therapy, and timely transition to outpatient parenteral antimicrobial therapy (OPAT) allows clinically stable patients to complete treatment outside the hospital. Because OPAT requires home infusion services or post-acute facility placement that typically depend on coverage, insurance status may strongly influence length of stay (LOS); national data on this association in IE remain limited. Methods: We performed a retrospective cross-sectional analysis of the 2016–2019 National Inpatient Sample (NIS) using ICD-10-CM codes I33 and I38 to identify adult IE hospitalizations. Patients were classified as insured (Medicare, Medicaid, or private insurance) or uninsured (self-pay or no charge). Outcomes included mean and prolonged LOS (>14 and >28 days), in-hospital mortality, discharge against medical advice (AMA), and hospitalization costs. Comparisons used chi-square and Student’s t-tests with appropriate NIS survey weighting. Multivariable Gamma regression (LOS, cost) and logistic regression (binary outcomes) were performed, adjusting for age, sex, race/ethnicity, income quartile, injection drug use (IDU), Elixhauser Comorbidity Index, and hospital characteristics, with an insurance × IDU interaction term. Results: Of 87,211 weighted IE hospitalizations, 81,667 (93.6%) were insured and 5544 (6.4%) were uninsured. Uninsured patients were younger (mean age 40.1 vs. 59.4 years) with lower comorbidity burden but higher injection drug use (IDU) prevalence (38.7% vs. 15.5%). Mean LOS was longer among the uninsured (15.5 vs. 12.4 days, p < 0.001); LOS > 14 days occurred in 35.8% vs. 26.6%, and LOS > 28 days in 18.5% vs. 9.2% (both p < 0.001). AMA discharge was four-fold higher among the uninsured (22.2% vs. 5.5%, p < 0.001), while unadjusted in-hospital mortality was similar (9.0% vs. 9.4%, p = 0.32). LOS and AMA disparities persisted in both IDU and non-IDU subgroups, with a six-fold AMA disparity among non-IDU patients (15.2% vs. 2.5%). Based on multivariable analysis, uninsured status remained independently associated with prolonged LOS > 28 days (adjusted odds ratio [aOR] 1.46, 95% CI 1.30–1.65), AMA discharge (aOR 3.51, 95% CI 3.10–3.97), and—after accounting for age and comorbidity differences—higher in-hospital mortality (aOR 1.25, 95% CI 1.10–1.43). Conclusions: Uninsured adults hospitalized with IE experienced longer stays, markedly higher AMA rates, and—after adjustment for age and comorbidity—higher in-hospital mortality than insured patients. These findings are consistent with nonclinical barriers to discharge—particularly limited OPAT and post-acute care access—and suggest that the younger, less comorbid profile of uninsured patients masks an underlying outcome disparity. The results identify uninsured IE patients as a population that may benefit from alternative care models and policy reforms expanding safe post-acute antimicrobial therapy. Full article

Background/Objectives: People with disabilities face a disproportionately higher disease burden alongside reduced healthcare accessibility, resulting in elevated unmet healthcare needs (UHN). Understanding the factors that drive UHN—and whether these factors differ by disability status—is critical for developing targeted public health interventions. Methods: A secondary cross-sectional analysis was conducted using linked national survey and administrative data—specifically the Korea National Health and Nutrition Examination Survey (KNHANES) cycles VI to VIII (2013–2021) linked with National Health Insurance Service (NHIS) administrative records—to examine determinants of healthcare access and utilization barriers by disability status. Independent variables were selected based on Andersen’s Behavioral Model of Health Services Use for vulnerable populations, encompassing predisposing factors, enabling factors, and need factors (including functional status indicators). Interaction terms between disability status and sex, and between disability status and household income level, were introduced to identify effect modification by disability status. Results: People with registered disabilities had significantly higher UHN compared to those without disabilities. The contributing factors to UHN differed between the two groups, with sex and household income showing statistically significant interaction effects with disability status, indicating that their associations with UHN vary depending on whether an individual has a registered disability. Conclusions: UHN in people with disabilities is shaped by a distinct set of determinants compared to the general population. The overall pattern of contributing factors differed between people with and without disabilities across multiple dimensions. These findings highlight the need for tailored healthcare policies that account for the unique vulnerabilities of people with disabilities, rather than applying uniform strategies across all population groups. Full article