Search Results (523)

Background: Esophageal adenocarcinoma (EAC) and squamous cell carcinoma (ESCC) follow divergent incidence trajectories in the United States. Rising use of electronic nicotine delivery systems (ENDS) and evolving demographic risk profiles may be reshaping these trends. We aimed to characterize national incidence patterns of EAC and ESCC from 2000 through 2022—stratified by age, sex, and race/ethnicity—and to place these in the context of changing behavioral exposures. Methods: We performed a retrospective cohort study using Surveillance, Epidemiology, and End Results SEER 21 registry data (covering 48% of the U.S. population). We included first-primary, histologically confirmed EAC (ICD-O-3 codes 8140–8576) and ESCC (8050–8084) in individuals aged ≥ 15 years diagnosed between 2000 and 2022. Age-adjusted incidence rates (per 100,000 person-years; 2000 U.S. standard) and annual percent changes (APCs) were estimated via Joinpoint regression models. Results: A total of 90,290 EAC and 47,916 ESCC cases were identified. EAC incidence increased from 2.3 to 2.8 per 100,000 (APC +0.90%; 95% CI, 0.45–1.35), with the largest relative rises in ages 15–39 years (APC +1.50%) and among women (APC +2.65%). Non-Hispanic Black and American Indian/Alaska Native populations experienced the most pronounced EAC increases. Overall ESCC incidence declined (APC −0.78%; 95% CI, −1.10 to −0.46), though Asian/Pacific Islander (+3.59%) and American Indian/Alaska Native (+1.58%) groups saw rising rates. Conclusions: EAC incidence continues to climb—especially in younger adults, women, and select racial/ethnic minorities—while ESCC declines are uneven. These histology-specific patterns highlight the urgency of tailored prevention, targeted early-detection efforts, and mechanistic studies on emerging exposures such as vaping. Full article

Background: Fall injury is a sentinel event for mortality among older adults, and activity intensity may play a role in mitigating this outcome. This study assessed the relationship between activity intensity and all-cause mortality following fall injury among community-dwelling U.S. older adults. Methods: For this retrospective cohort study, we pooled 12 years of data from the National Health Interview Survey and identified older adults (aged 65 years and older) who sustained fall injuries (N = 2454). The outcome variable was time to death following a fall injury. We defined activity intensity as a binary variable, none-to-low and normal-to-high, using the American Heart Association’s weekly 500 Metabolic Equivalent of Task (MET) as a cutoff. We controlled for sociodemographic, healthcare access, and health characteristics; performed survey-weighted Cox proportional hazard regression analysis; and reported the adjusted mortality risks (plus 95% confidence interval (CI)). Results: The survey comprised 2454 older adults with fall injuries, representing 863,845 US older adults. The population was predominantly female (68%), non-Hispanic White (85%), and divorced/separated (54%). During the follow-up period, 45% of the study population died. Approximately 81% of the study population had low activity levels. However, between 2006 and 2017, the proportion of the study population with low physical activity decreased from 90% to 67%. After adjusting for sociodemographic, healthcare access, and health characteristics, none-to-low activity intensity was associated with 50% increased mortality risk (aHR: 1.50; 95% CI: 1.20–1.87). Conclusions: Promoting higher physical activity levels may significantly reduce the all-cause mortality risk following fall injury among older adults. Full article

Background/Objectives: Spanish-speaking patients face persistent barriers in accessing equitable audiological care, particularly when standardized language-appropriate tools are lacking. Two Spanish-language sentence recognition tests, the Spanish AzBio Sentence (SAzB) and the Latin American Hearing in Noise Test (LAH), are commonly used to evaluate speech perception in adults with hearing loss. However, performance differences between these measures may influence referral decisions for hearing intervention, such as cochlear implantation. This study compared test performance under varying noise and spatial conditions to guide appropriate test selection and reduce the risk of misclassification that may contribute to healthcare disparities. Methods: Twenty-one bilingual Spanish/English speaking adults with normal bilateral hearing completed speech perception testing using both the SAzB and LAH. Testing was conducted under two spatial configurations: (1) speech and noise presented from the front (0° azimuth) and (2) speech to the simulated poorer ear and noise to the better ear (90°/270° azimuth). Conditions included quiet and three signal-to-noise ratios (+10, +5, and 0 dB). Analyses included paired t-tests and one-way ANOVAs. Results: Participants scored significantly higher on the LAH than on the SAzB across all SNR conditions and configurations, with ceiling effects observed for the LAH. SAzB scores varied by language dominance, while LAH scores did not. No other differences were observed based on any further demographic information. Conclusions: The SAzB provides a more challenging and informative assessment of speech perception in noise. Relying on easier tests like the LAH may obscure real-world difficulties and delay appropriate referrals for hearing loss intervention, including cochlear implant evaluation. Selecting the most appropriate test is critical to avoiding under-referral and ensuring Spanish-speaking patients receive equitable and accurate care. Full article

Identifying hospitals that disproportionately serve minority and publicly insured patients is important because patients at these hospitals often experience worse outcomes. Studies commonly identify disproportion by using the top decile of hospitals with the greatest proportion of Black discharges nationally. Our study aimed to identify a broader measure that accounts for disproportion by multiple characteristics. Using fee-for-service Medicare data, we classified hospitals as either serving disproportionately or not, examined overlaps in classification, and assessed differences in hospital quality. We found that using a combined measure for any hospitals in the top decile or above a threshold of twice their local healthcare market average of Black, Hispanic, minority, or dual-eligible discharges classified 28.1% (n = 680/2420) of hospitals as serving disproportionately, compared to only 10% (n = 242/2420) when using the top decile of a single characteristic. The combined measure detected moderate differences in hospital star quality ratings (mean difference of 0.57–0.87, all p-values < 0.001; standardized mean difference: 0.50–0.79, 95% CIs all above 0). The combined measure identified hospitals that were smaller, more rural, and served other minorities, namely, Asian and American Indian populations. Future work should consider using this combined measure to more comprehensively identify hospitals that disproportionately serve minority or publicly insured patients. Full article

Background/Objectives: This paper presents cranial MMS data for an American Indian (AI) sample from New Mexico. We compare these data to other population reference samples to understand biological distance and classification patterns. Methods: Cranial MMS data was collected from CT scans of AI individuals (n = 839) in the New Mexico Decedent Image Database. We used 12 traits following a published protocol for CT data and excluded nasal bone contour. The AI sample is compared to other samples of African American or Black, Asian, Hispanic, and White individuals to assess biological distance and classification accuracy. Results: Biological distance analysis indicated similarity among the AI, Hispanic, and Black samples, but dissimilarity among the Asian and White samples to the AI sample. Classification accuracy was low for the overall model, with Hispanic and Black individuals frequently misclassifying as AI. Conclusions: As is true everywhere, ideas about identity are complex in New Mexico. AI and Hispanic individuals in NM self-ascribe to one or both social groups. We found that biological data cannot meaningfully differentiate between these social groups, as crania are morphologically similar when examining cranial MMS traits. These results, coupled with New Mexican identity and genetics, contributes to the difficulty in group attribution in forensic casework. Nevertheless, the reference data for AI presented here can provide more robust statistics that support the likelihood of AI and Hispanic affinity in population affinity analysis. We underscore the need for an understanding of regional population history and structure and reference samples while assessing population affinity in forensic casework. Full article

Background: The coronavirus disease 2019 (COVID-19) pandemic exacerbated food insecurity in the United States, with older adults facing heightened vulnerability due to fixed incomes, chronic illness, and limited mobility. Methods: A cross-sectional online survey was conducted with 4961 urban U.S. adults aged 65 and older. Food insecurity was assessed using the USDA Six-Item Short Form. Paired sample t-tests, chi-square tests, and multivariate logistic regression were used to examine demographic predictors of food insecurity before and during the pandemic. Results: Logistic regression indicated that race and income were significant predictors of food insecurity. African American and Hispanic participants were 92.1% and 126.4%, respectively, more likely to experience food insecurity than White participants (p < 0.001). Compared with those earning less than USD 50,000, participants earning USD 50,000–USD 100,000 and USD 100,000+ were 32.4% and 63.8% less likely to experience food insecurity (p < 0.001). Bivariate analyses showed that food insecurity increased most among African Americans (9.2%) and middle-income participants (USD 50,000–USD 100,000: 11.0%). Education did not remain significant in the adjusted model. Conclusions: Older adults of color and those with lower incomes were disproportionately impacted by food insecurity during the pandemic. The findings highlight the need for targeted, equity-driven policy responses to mitigate food insecurity in older adulthood. Full article

Background/Objectives: Youth perceptions of their environments provide critical insight into the social and physical determinants of health. This study investigated how Hispanic and African American children conceptualize health within their neighborhood and school settings. Methods: A total of 44 participants (29 Hispanic, 15 African American; Mean age = 9.27 years, SD = 1.28 years) participated in a photovoice project, capturing photographs and quotes in response to two guiding prompts: (1) “What does your dream of a healthy community look like?” and (2) “What should we do to make your community healthier?” Results: Thematic analysis of participants’ quotes and photographs yielded four overarching themes across both neighborhood and school environments: (1) access to nutritious food options, (2) opportunities for physical activity and recreation, (3) clean and safe spaces, and (4) access to extracurricular and community-based programs. A fifth theme, emergency preparedness and response, emerged uniquely within school context. Participants also proposed context-specific solutions to address identified health concerns. Conclusions: These findings emphasize the importance of environmental context in shaping child and preadolescent health perceptions and priorities. The results support the development of children and adolescent-informed, community-level interventions aimed at improving environmental health conditions, particularly in underserved communities disproportionately affected by poverty and structural inequities. Full article

Patterns of family caregiving of older adults have been identified based on aspects such as care-related tasks and intensity and are associated with caregiver well-being. A gap remains, however, in understanding how individual-, relational-, and cultural-level factors concurrently inform caregiving groups within multicultural families. In this study, we identified caregiving patterns among Mexican American individuals aiding older adults by drawing from a variety of care recipient and caregiver characteristics. We also assessed relationships between established subgroups and perceived caregiver stress. Using data from the 2016 Hispanic Established Populations for the Epidemiological Study of the Elderly (Caregiver supplement, Wave 9, N = 460), we performed latent class analysis to determine caregiving subgroups from 8 indicator variables representing patient needs, family characteristics, and caregiver health and support. Findings identified four caregiving subgroups that varied based on older adults’ care needs and caregivers’ family status, nativity, and health. Results from multivariable linear regression indicated that caregivers from the Moderate Burden/Non-cohabitating group perceived significantly less stress than those in the Elevated Burden & Health Risk group. In conclusion, we demonstrated how multi-level factors shape caregiving patterns, which can inform support efforts for multicultural families. Full article

This study explores how intersecting disabilities and ethnic identities influence key career-related factors, including career decision self-efficacy, career outcome expectations, perceived career barriers, and social support, among college students with disabilities from diverse racial and ethnic backgrounds. Background/Objectives: Applying social cognitive career theory (SCCT) and intersectionality frameworks, this research addresses a critical gap in understanding the unique challenges and strengths experienced by underrepresented students with disabilities in postsecondary education. Method: Quantitative data were collected from approximately 306 participants representing various ethnic groups, including African American, Asian American, Hispanic, and other ethnic backgrounds, alongside European American peers. Results: Findings revealed that underrepresented students with disabilities reported significantly stronger ethnic identity affirmation but also perceived greater career-related barriers compared to their European American counterparts. These results demonstrate the need for culturally responsive career development practices and inclusive campus environments that affirm students’ multiple identities. Conclusions: Implications are discussed for higher education professionals, rehabilitation counselors, disability service providers, and career counselors seeking to promote equitable career outcomes and identity-conscious support systems. Full article

Infants born to mothers who self-identify as Hispanic account for a substantial and growing share of births in the United States, yet limited research has examined disparities in birth outcomes across Hispanic origin subgroups. This study aims to document trends and identify important factors associated with Cesarean section (C-section), low birthweight, and prematurity within the Hispanic population. We use data from the National Vital Statistics System (2011–2021), covering nearly all U.S. births. We compare outcomes across Hispanic, non-Hispanic White, and non-Hispanic Black mothers and further disaggregate by Hispanic origin (Mexican, Puerto Rican, Cuban, Central/South American, and Other/Unknown). We use logistic regression and classification tree models to assess associations between maternal, infant, and clinical factors and birth outcomes. We find that Hispanic mothers have birth outcomes similar to non-Hispanic Whites and better than non-Hispanic Blacks. However, prematurity rates among Hispanics have slightly increased over time. Mexican mothers exhibit the most favorable outcomes, while Cuban mothers show higher rates of C-section, and Puerto Rican mothers show higher rates of low birthweight and prematurity. Logistic regression results highlight multiple births, breech presentation, and hypertensive conditions as important factors associated with adverse birth outcomes. Our biomedical approach emphasizes physiological and clinical risk factors such as multiple births, breech presentation, hypertensive conditions, and obesity. In parallel, our biosocial analysis incorporates demographic, socioeconomic, and behavioral variables to contextualize how social determinants interact with biology to influence outcomes. Complementing these findings, our classification tree analysis identifies inadequate gestational weight gain (less than 15 pounds) as a prominent risk factor for both low birthweight and prematurity. Additionally, obesity emerges as a significant factor linked to an increased likelihood of C-section. While birth outcomes among Hispanic mothers are generally favorable, subgroup differences and emerging disparities highlight the need for disaggregated research and culturally tailored public health interventions. Full article

Background: Endometrioid ovarian carcinoma is a subtype of epithelial ovarian carcinoma and is the second most common type of malignant ovarian neoplasm. Studies investigating delayed treatment of ovarian cancer have identified significant impacts on overall survival rates. This study utilizes the Surveillance, Epidemiology, and End Results (SEER) database to identify cases of endometrioid ovarian carcinomas and factors associated with delays in time to treatment (TTT) greater than one month. Methods: The SEER database was queried to identify females with biopsy-confirmed cases of ovarian endometrioid carcinoma from 2010 to 2015. Chi-square tests, two-sided Fisher’s exact tests, and multivariable binary logistic regressions were completed using SPSS version 29.0.2. Statistical significance was confirmed when p < 0.05. Results: A total of 11,235 relevant patients were identified within the SEER database. A majority were Non-Hispanic White (69.2%), aged 50–59 (30.1%), had an annual income of $75,000+ (58.9%), resided in urban communities (90.0%), and were diagnosed with AJCC stage 1 disease (62.0%). When investigating treatment, 94.9% of patients received treatment within 1 month of diagnosis, while 5.1% experienced a delay of over 1 month before starting treatment. Multivariable binary logistic regression analysis demonstrated that American Indian and Alaksa Native (AIAN) patients independently experienced a +376% increased likelihood of treatment delays exceeding 1 month (aOR 4.76; 95% CI 1.32–17.08; p = 0.017). Patients diagnosed at AJCC stage III (aOR 1.88; 95% CI: 1.22–2.91; p = 0.004) or stage IV (aOR: 4.50; 95% CI: 2.75–7.38; p < 0.001) additionally had +88% and +350% higher odds of treatment delays greater than 1 month, respectively. Conclusions: AIAN patients and those presenting with later stage disease for endometrioid ovarian carcinoma face significantly longer TTT, indicating disparities in timely care. Our findings demonstrate an urgent need for targeted interventions to address systemic barriers contributing to delayed treatment in these populations. Full article

Background/Objective: Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss. Intravitreal anti-vascular endothelial growth factor (VEGF) therapy is the primary treatment for neovascular AMD. This study aimed to assess racial, ethnic, and gender representation in U.S.-based randomized controlled trials (RCTs) of anti-VEGF therapies. Methods: A systematic PubMed search identified 19 eligible RCTs. Titles and abstracts were screened, and demographic data were independently extracted and cross-verified. Chi-squared analysis was used to evaluate disparities in participant representation. Risk of bias was assessed using the ROBIS checklist. Results: Among 8003 participants across 19 trials, 92.3% were Caucasian. Asian, African American, Hispanic/Latino, and American Indian participants collectively comprised just over 5%. This underrepresentation of non-Caucasian groups was statistically significant (p < 0.01, df = 4) and not associated with study sponsorship. Gender analysis showed 59% female and 41% male participation, which was not statistically significant (p = 0.83, df = 1). Conclusions: Non-Caucasian populations remain significantly underrepresented in anti-VEGF RCTs for AMD. This raises concerns about the generalizability of trial findings to diverse populations. Future clinical trials must prioritize inclusive recruitment to ensure equitable, evidence-based care for all patients. Full article

Background/Objective: Dry eye syndrome affects 16 million Americans with USD 52 billion in annual healthcare costs. With large language models (LLMs) increasingly used for healthcare information, understanding their performance in delivering equitable dry eye guidance across diverse populations is critical. This study aims to evaluate and compare five major LLMs (Grok, ChatGPT, Gemini, Claude.ai, and Meta AI) regarding dry eye syndrome information delivery across different demographic groups. Methods: LLMs were queried using standardized prompts simulating a 62-year-old patient with dry eye symptoms across four demographic categories (White, Black, East Asian, and Hispanic males and females). Responses were analyzed for word count, readability, cultural sensitivity scores (0–3 scale), keyword coverage, and response times. Results: Significant variations existed across LLMs. Word counts ranged from 32 to 346 words, with Gemini being the most comprehensive (653.8 ± 96.2 words) and Claude.ai being the most concise (207.6 ± 10.8 words). Cultural sensitivity scores revealed Grok demonstrated highest awareness for minority populations (scoring 3 for Black and Hispanic demographics), while Meta AI showed minimal cultural tailoring (0.5 ± 0.5). All models recommended specialist consultation, but medical term coverage varied significantly. Response times ranged from 7.41 s (Meta AI) to 25.32 s (Gemini). Conclusions: While all LLMs provided appropriate referral recommendations, substantial disparities exist in cultural sensitivity, content depth, and information delivery across demographic groups. No LLM consistently addressed the full spectrum of dry eye causes across all demographics. These findings underscore the importance for physician oversight and standardization in AI-generated healthcare information to ensure equitable access and prevent care delays. Full article

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder with significant racial and ethnic disparities in prevalence, disease severity, and outcomes. Cardiovascular complications, including pericarditis, myocarditis, valvular disease, and conduction abnormalities, contribute to increased morbidity and mortality in SLE patients. This study examines racial and ethnic disparities in cardiovascular outcomes among hospitalized SLE patients in the United States. Methods: This retrospective study utilized the National Inpatient Sample (NIS) database from 2016 to 2021 to analyze hospitalizations of adult patients (≥18 years) with a primary or secondary diagnosis of SLE. Patients were stratified into racial/ethnic groups: White, Black, Hispanic, Asian, Native American, and Other. Primary outcomes include major adverse cardiovascular events (MACEs), which are a composite of in-hospital mortality, myocardial infarction (MI), sudden cardiac death, and other SLE-related outcomes including cardiac, pulmonary, and renal involvement. Statistical analyses included multivariable logistic regression models adjusted for demographic, socioeconomic, and hospital-related factors to assess racial disparities. Results: The study included 514,750 White, 321,395 Black, and 146,600 Hispanic patients, with smaller proportions of Asian, Native American, and Other racial groups. Black patients had significantly higher odds of in-hospital mortality (OR = 1.17, 95% CI = 1.08–1.26, p < 0.001) and sudden cardiac death (OR = 1.64, 95% CI = 1.46–1.85, p < 0.001) compared to White patients. Asian patients also exhibited increased mortality risk (OR = 1.37, 95% CI = 1.14–1.63, p = 0.001) as compared to Whites. Conversely, Black (OR = 0.90, 95% CI = 0.85–0.96, p = 0.01) and Hispanic (OR = 0.87, 95% CI = 0.80–0.96, p = 0.03) patients had lower odds of MI. Racial disparities in access to care, socioeconomic status, and comorbidity burden may contribute to these differences. Conclusion: Significant racial and ethnic disparities exist in cardiovascular outcomes among hospitalized SLE patients. Black and Asian individuals face higher in-hospital all-causes mortality and sudden cardiac death risks, while Black and Hispanic patients exhibit lower MI rates. Addressing social determinants of health, improving access to specialized care, and implementing targeted interventions may reduce disparities and improve outcomes in minority populations with SLE. Full article

Previous studies about the COVID-19 pandemic on STEMI patient outcomes have conflicting results. It remains unclear if this may be attributed to regional differences and/or differences during COVID-19 wave periods. Using the American Heart Association Get With The Guidelines–Coronary Artery Disease registry data, we evaluated (1) time metrics related to STEMI system goals and (2) regional variation in STEMI incidence and in-hospital mortality during pandemic wave time periods. The study included all patients 18–100 years old admitted with STEMI (n = 72,516) to 1 of 435 American Heart Association Get With The Guidelines–Coronary Artery Disease hospitals (1 October 2019–31 December 2021). Of these, 70.8% were male and 73.0% non-Hispanic White, with a median age of 63 (IQR 18) years. Compared to pre-pandemic time frames, patients with STEMI had a higher risk profile, delayed time to treatment, were treated with fibrinolytic therapy or primary PCI, and were transferred for primary PCI at similar rates, and had higher adjusted in-hospital mortality (during the second wave in the South and Midwest). Preservation of STEMI systems of care resulted in an overall lower in-hospital mortality rate than predicted, although opportunities exist to improve treatment delays. Regional differences in mortality rates require further study. Full article