Journal of Racial and Ethnic Health Disparities

Importance: Chronic stress may contribute to adverse health outcomes through cumulative physiologic dysregulation. Allostatic load (AL), a composite measure of multisystem physiologic burden, may capture biologic effects of structural, social, and psychosocial stress not reflected by self-reported measures. Objective: To evaluate racial and ethnic differences in AL among women with familial cancer risk and examine how socioeconomic status, psychosocial factors, clinical characteristics, and health behaviors contribute to variations in AL. Design: Cross-sectional study of underrepresented minority participants enrolled in the HERSTORY cohort from October 2023 through September 2025, with comparison participants from the UCLA ATLAS biobank. Setting: UCLA academic health system. Participants: The study included 303 racially and ethnically diverse female HERSTORY participants aged [≥]35 years with a family history of cancer and matched non-Hispanic White female ATLAS participants (n=709). Exposures: Race and ethnicity, age, neighborhood deprivation, cancer history and stage, depression, perceived stress, cancer worry, and physical activity. Main Outcomes and Measures: The primary outcome was AL, calculated from cardiometabolic and organ-function measures. A secondary index incorporated race- and ethnicity-specific neutrophil-to-lymphocyte ratio (NLR) derived from 326,826 women in the UCLA Health population. Multivariable regression models evaluated factors associated with elevated AL. Results: Compared with matched non-Hispanic White participants, Black and Asian/Pacific Islander HERSTORY participants had significantly higher AL after adjustment. Hispanic/Latina participants did not have significantly elevated AL. Older age, greater area-level socioeconomic deprivation, and depression were independently associated with higher AL. Prior cancer diagnosis, cancer worry and perceived stress were not significantly associated with AL, whereas regular physical activity was associated with lower AL. Among cancer patients, advanced stage was associated with greater AL. Conclusions and Relevance: This study demonstrates elevated AL among understudied racial/ethnic minority groups with familial cancer risk and identifies associations with neighborhood deprivation, depression, and physical activity. The association between cancer stage and AL suggests that physiologic stress may reflect variation in cancer burden. The lack of association with perceived stress and cancer worry further indicates that physiologic and self-reported psychosocial measures capture distinct dimensions of stress. The development of race/ethnicity-specific NLR thresholds derived from large population samples provide a benchmark for future studies.

Indiana still faces significant health challenges, ranking among the least healthy U.S. states due to high obesity rates, mental health issues, and other chronic conditions. These disparities are closely linked to inequities in healthcare access, which are largely shaped by social determinants of health. Using data from the Social Vulnerability Index and County Health Rankings and Roadmaps, this study analyzes trends in obesity, mental health, and premature death across Indiana counties before, during, and after the COVID-19 pandemic. Descriptive statistics, correlation analyses, and Negative Binomial regression models were used to evaluate county-level disparities. In 2018, higher rates of uninsured, obese, and physically inactive populations were associated with increased premature death. In 2020, diabetes, smoking, and alcohol consumption were significant factors. By 2022, unemployment, education, obesity, insurance, exercise access, and mental health provider availability were associated with premature death. Findings indicate that socially vulnerable counties experienced amplified health impacts, with obesity rising most sharply where exercise infrastructure was limited and poor mental health days increasing across all counties. These results highlight persistent service gaps and the critical need for targeted investments in recreational infrastructure and mental healthcare. Future research should examine policy influences and causal relationships to inform equity-focused interventions.

Background Cardiovascular-Kidney-Metabolic (CKM) syndrome encompasses interconnected conditions such as type 2 diabetes (T2D), hypertension, hypertriglyceridemia, metabolic syndrome (MetS), and chronic kidney disease (CKD). As CKM progresses, cardiorenal risks increase. Although Glucagon-like peptide-1 receptor agonists (GLP-1 RA) have demonstrated cardiorenal and cardiometabolic benefits, offering an opportunity to slow CKM progression, their use may vary across social determinants of health (SDoH) and stage 2 CKM subgroups. Objective To evaluate the influence of SDoH on access to GLP-1 RA among patients with T2D and other stage 2 CKM conditions. Methods This cross-sectional study used data from the U.S. National Health and Nutrition Examination Survey (NHANES), 2005?2020. Adults aged [≥]30 years with T2D and/or other stage 2 CKM conditions were included. Weighted descriptive analysis, multivariable logistic regression and LASSO were applied to assess associations between SDoH and GLP-1 RA use. Results Among 4,520 participants (representing approximately 84.0 million U.S. adults), weighted mean age was 61.4 years, 48.9% were female, and 61.5% were non-Hispanic White. Among participants with T2D, GLP-1 RA use was higher among individuals with higher education (3.39% vs 1.43%), private insurance (3.00% vs 0.58%), and higher income (4.70% vs 1.87%), while no use was observed among those without routine places for care. In adjusted analyses, individuals with lower income, less than high school education, lack of insurance, and being unmarried had 64%, 51%, 81%, and 40% lower likelihood of GLP-1 RA use, respectively. LASSO identified income, education, insurance, and access to care as predictors. Lower income, lower educational attainment, and lack of insurance were associated with 48%, 34%, and 79% lower likelihood of GLP-1 RA use, respectively, adjusting for age, sex, and race/ethnicity. Conclusion SDoH-driven disparities limit GLP-1 RA access. Expanding GLP-1 RA access by addressing socioeconomic barriers is critical to slowing CKM progression, reducing cardiovascular risk, and mitigating health disparities.

Objective: Type 1 diabetes is related to an increased risk of structural brain alterations, cerebral microbleeds (CMBs), and cognitive deficits. We explored brain volumes and their direct and combined associations with CMBs on cognitive performance in middle-aged individuals with type 1 diabetes. Research Design and Methods: Adults with type 1 diabetes (n=163; mean age 46+/-8 years; diabetes duration 31+/-10 years; 53% women) and 48 matched controls underwent brain MRI and clinical and neuropsychological evaluations. Volumetric MRI measures adjusted to intracranial volume included total brain volume (TBV), white matter volume (WMV), and total volumes of cortex, thalamus, hippocampus, nucleus accumbens, and choroid plexus. Results: Individuals with type 1 diabetes had smaller TBV, WMV, and volumes of cortex, thalamus, and nucleus accumbens, and larger choroid plexus compared to controls (Cohen d=0.39-0.54). Those with type 1 diabetes and 3 or more CMBs had smaller TBV, WMV, and volumes of cortex, thalamus, and nucleus accumbens, compared to those with 0-2 CMBs (Cohen d=0.54-0.92). We found no direct associations between brain volumes and processing speed or executive functions. However, TBV, WMV, nucleus accumbens, and choroid plexus volumes had significant negative synergistic interactions with CMBs on processing speed and executive functions (standardized betas: -0.61 to -0.51 and 0.54 to 0.75, FDR-corrected p=0.006-0.048). Conclusions: Smaller global and regional brain volumes and larger choroid plexus volumes were found in middle-aged individuals with type 1 diabetes compared to healthy controls. Together with CMB burden, structural brain volumetric alterations were associated with accelerated cognitive deficits.

Background Stroke remains one of the leading causes of mortality, disability, and healthcare burden worldwide. Identifying demographic, socioeconomic, lifestyle, and clinical factors associated with stroke is essential for improving prevention strategies and reducing disease burden. This study aimed to identify independent predictors of stroke among U.S. adults using nationally representative Behavioral Risk Factor Surveillance System (BRFSS) data collected between 2021 and 2023. Methods A cross-sectional analysis was conducted using pooled BRFSS data from 2021 to 2023. Adults with complete information on stroke status and study variables were included in the multivariable analysis. Stroke status was determined from self-reported physician diagnosis. Survey-weighted multivariable logistic regression was performed to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for demographic, socioeconomic, lifestyle, and clinical predictors while accounting for the complex BRFSS sampling design. Model discrimination was evaluated using receiver operating characteristic (ROC) curve analysis. Results Among 235,571 participants in the pooled dataset, stroke was more common among older adults and individuals with diabetes, poorer self-reported health, lower income, and smoking history. In the adjusted analysis, increasing age (aOR 1.04, 95% CI 1.04 to 1.04), diabetes (aOR 1.55, 95% CI 1.43 to 1.67), current smoking (aOR 1.44, 95% CI 1.31 to 1.58), multiracial ethnicity (aOR 1.44, 95% CI 1.12 to 1.82), Black race (aOR 1.31, 95% CI 1.15 to 1.50), and poorer general health (aOR 1.58, 95% CI 1.53 to 1.64) were independently associated with higher odds of stroke. Conversely, Asian race (aOR 0.65, 95% CI 0.43 to 0.94), Hispanic ethnicity (aOR 0.65, 95% CI 0.54 to 0.77), higher income (aOR 0.92, 95% CI 0.90 to 0.93), and regular physical activity (aOR 0.86, 95% CI 0.80 to 0.92) were associated with lower odds of stroke. The final model demonstrated good discrimination, with an area under the ROC curve of 0.781 (95% CI 0.774 to 0.788). Conclusions Stroke among U.S. adults is independently associated with a combination of demographic, socioeconomic, lifestyle, and clinical factors. Diabetes, smoking, poor general health, and socioeconomic disadvantage remain important potentially modifiable contributors to stroke risk, whereas regular physical activity appears protective. These findings support targeted public health interventions focused on improving cardiometabolic health, promoting smoking cessation and physical activity, and addressing socioeconomic disparities to reduce the burden of stroke in the United States.

Introduction Smoking prevalence remains higher in rural than in urban populations in the United States. To examine recent trends, we assessed state-level differences in cigarette smoking between urban and rural areas from 2018 to 2024. Methods Using repeated cross-sectional data from the Behavioral Risk Factor Surveillance System, we estimated state-specific logistic regression models to examine the relationship between urban-rural county residence and cigarette smoking. Unadjusted models (model 1) included urban-rural county status and year. Subsequent models (model 2) added age, sex, and race/ethnicity. A final model (model 3) included education and an interaction term between urban-rural county status and year to examine whether gaps in urban-rural smoking changed over time. In states with significant interactions, simple effects tests compared trends for urban-rural groups separately. Results Compared to urban adults, rural adults had higher unadjusted odds of cigarette smoking (odds ratio [OR] range:1.07-1.88) in 88.4% (38/43) of states. Adjusting for demographic covariates (model 2) increased the proportion of states with significant marginal effects of rurality to 90.7% (ORs:1.09-1.87). A final model that also controlled for education (model 3) decreased the proportion of states with significant marginal effects of rurality to 60.5% (ORs:1.10-1.54). Among the 14 states with significant interaction terms, the odds of smoking declined faster among urban than rural residents. Conclusion Urban-rural differences in smoking persist across most states. No state showed a reduction in urban-rural disparities over time, and the urban-rural gap widened in 14 states. Demographic variation accounted for some, but not the majority, of observed urban-rural differences.

Objective: To determine whether continuous glucose monitoring (CGM) identifies clinically relevant glycemic heterogeneity and subclinical end-organ alterations in adults without diabetes. Research Design and Methods: We analyzed 1,017 AI-READI Year 3 participants without diabetes (558 with normoglycemia and 459 with prediabetes by A1C). Fifty-two metrics from 10-day blinded CGM were reduced to nonredundant glycemic axes. Partial Spearman correlations between representative CGM metrics and clinical measures across 13 domains were adjusted for age, sex, and BMI and controlled for false discovery rate. CGM-derived subphenotypes were identified using unsupervised UMAP-HDBSCAN-based clustering. Results: Among 462 glycemic-clinical associations tested, 99 (21.4%) remained significant after false discovery rate correction. Hyperglycemia-related metrics, including mean glucose, time above range, and time in tight range, showed more associations than variability metrics. The strongest signals involved cardiometabolic, cardiovascular, and cognitive measures. Greater hyperglycemia and glucose excursions were associated with lower language performance, slower processing speed, and lower cognitive efficiency ({rho} {approx} -0.10 to -0.14; all P < 0.01). Clustering identified four reproducible glycemic subphenotypes: Healthy, Mild Hyperglycemia, High Variability, and Hyperglycemia. CGM phenotypes reclassified A1C-defined groups: 58.1% of participants with normoglycemia fell into dysglycemic phenotypes, whereas 18.8% of participants with prediabetes fell into more favorable phenotypes. The Hyperglycemia phenotype had the most adverse cardiometabolic profile and lower cognitive performance. Conclusions: In adults without diabetes, CGM revealed glycemic patterns associated with distinct subclinical alterations. CGM-based phenotyping may complement A1C for characterizing early dysglycemia and selecting individuals for longitudinal risk-stratification studies.

Background Non-alcoholic fatty liver disease (NAFLD) has become a common metabolic disorder in paediatric age groups and is a major contributor to the burden of health economics. However, there is a lack of comprehensive data on the prevalence of this condition among children. Methods English language literature published from inception until April 2025 was searched from the electronic databases, i.e., PubMed/Medline, Scopus, Embase, and CINAHL. Original data published in any form that reported NAFLD prevalence among children and/or adolescents in India were included. The subgroup analysis of prevalence was done based on the risk category, i.e., average risk group and high risk group (obesity or overweight, metabolic syndrome, etc.). The prevalence estimates were pooled using the random-effects model. Results A total of 11 studies (six in high-risk populations and 5 in the average-risk general population) comprising data from 3512 individuals were found eligible and were included. The overall pooled estimate of NAFLD prevalence among the children and adolescents was 35.4% (95% CI: 19.7% to 52.9%) with very high heterogeneity(I2=99.0%). The pooled prevalence of NAFLD among average/low risk children and adolescents was 10.7% (95%CI: 5.2% to 20.5%) with high heterogeneity across the studies (I2= 96.6%, p=0.001) whereas the pooled prevalence of NAFLD in high risk overweight/obese children and adolescents was found to be 59.7% (95% CI:55.2% to 64.1%) with moderate heterogeneity across the studies (I2=50.90%; H2=2.04; Q (5) = 10.03; p=0.07) Conclusion This systematic review demonstrates that non-alcoholic fatty liver disease (NAFLD) poses a growing health concern among Indian children and adolescents, as 1 out of 3 children/adolescents is suffering from it, with a disproportionately high burden observed in those who are overweight or obese.

Background: Neighborhood disadvantage indices used in public health research and policy include multiple economic, social, and housing items. However, research has failed to question whether it is necessary to include a multitude of economic, social, and housing variables in a single index. The purpose of this work was to examine three different neighborhood indices: a multidimensional disadvantage index, a unidimensional disadvantage index, and a unidimensional affluence index, and examine their performance with respect to distinguishing between healthy and unhealthy census tract neighborhoods in the United States. Methods: The 2022 disadvantage and affluence indices came from the National Neighborhood Data Archive, which are derived from census tract data from the American Community Survey 5-year estimates (2018-2022). The multidimensional disadvantage index included seven economic, social (e.g., single parent households), and housing items; the unidimensional disadvantage index included three poverty and income items; the unidimensional affluence index included 3 items capturing greater social and economic resources. Data on neighborhood health status (census tract prevalence of obesity, diabetes, and coronary heart disease) was obtained from the Population Level Analysis and Community EStimates database for 2022 and linked to the disadvantage and affluence indices for 83,522 census tracts. Contingency tables examined the degree of correspondence in quintiles across the three different indices and the corresponding disease prevalence in each cell. Generalized linear mixed models regressed the disease prevalence variables on index quintiles to determine the predicted prevalence of disease across the disadvantage gradient for each index. Results: Compared to the unidimensional disadvantage and affluence indices, the multidimensional disadvantage index underestimated disease burden in the most disadvantaged census tracts, and overestimated disease burden in the least disadvantaged tracts. Conclusions: Using a disadvantage or affluence index with a more parsimonious set of items would have greater precision in identifying communities at risk for poor health.

Background: Large-scale biobanks have advanced genomic and epidemiologic research, but many rely on infrequent biological sampling and limited digital phenotyping. The Yamanashi Multi-omics Cohort (YMoC) was established to support longitudinal assessment of molecular, clinical, and behavioural changes in a screening-defined cohort of adults at elevated metabolic risk without diagnosed diabetes. Methods: YMoC is a longitudinal cohort of 215 adults aged 30-70 years in Yamanashi Prefecture, Japan, who met prespecified glycaemic eligibility criteria at health check-up, including fasting plasma glucose 100-125 mg/dL (5.6-6.9 mmol/L) and HbA1c <6.5%. Participants underwent three in-person visits over six months. Measurements include 75-g oral glucose tolerance testing with serial sampling, clinical biochemistry, anthropometry, liver elastography, and collection of blood, urine, stool, and saliva for multi-omics profiling. Between visits, participants wore a Fitbit Inspire 3 and completed daily app-based questionnaires using the Taohealth app. Current molecular data include genome-wide single nucleotide polymorphism array genotyping and longitudinal plasma proteomics in a subset. Conclusions: YMoC is designed to evaluate within-person molecular and phenotypic trajectories in a screening-defined metabolic-risk cohort. The cohort provides a dense longitudinal resource linking clinical assessments, biospecimens, omics assays, and digital phenotyping, including analyses of insulin-resistance-related markers such as homeostasis model assessment of insulin resistance (HOMA-IR).

Background: Early-life growth is associated with individual cardiometabolic risk factors, but its relationship with overall cardiovascular health (CVH) in low- and middle-income countries (LMICs) is unclear. We examined associations of maternal, household, and child growth factors with young-adult CVH across four LMIC birth cohorts. Methods: We analyzed harmonized data from the Consortium of Health-Oriented Research in Transitioning Societies (COHORTS), including 4,582 participants ages 18-30 years from Brazil, Guatemala, the Philippines, and South Africa. CHV was assessed using a modified American Heart Association Life's Simple 7 score based on body mass index (BMI), blood pressure (BP), fasting blood glucose (FBG), and smoking. Site-specific multivariable ordinal logistic regression models evaluated associations between early-life factors and CVH. Results: Men had poorer CVH than women across most sites, largely because of less favorable BP and smoking profiles. Higher birthweight was associated with lower odds of better CVH in Brazil (AOR=0.81; 95% CI: 0.71-0.94) and the Philippines (AOR=0.63; 95% CI: 0.45-0.87). Greater conditional relative weight at 2 years was also inversely associated with CVH in both sites. Birthweight, conditional height and conditional relative weight at 2 years were strongly associated with adult BMI, whereas associations with BP and FBG were weaker. Attained schooling was associated with CVH in Brazil (AOR = 1.13 per year; 95% CI: 1.10-1.16), and the Philippines (AOR = 1.17; 95% CI: 1.10-1.24). Conclusions: Early-life growth patterns and educational attainment are associated with cardiovascular health in young adulthood across diverse LMIC settings, supporting life-course strategies to promote cardiovascular health.

Objective: To examine if food insecurity moderates the relationship between rurality and mental health outcomes (suicide mortality, poor mental health days, frequent mental distress) and to assess if these effects vary across U.S. Census divisions. Methods: This county-level (n=2,397) cross-sectional study used OLS and spatial error regression to analyze public data from sources including the County Health Rankings and USDA. We modeled suicide mortality, poor mental health days, and frequent mental distress as functions of the Index of Relative Rurality (IRR) and food insecurity, controlling for median income and provider rates. The suicide model was also tested across nine U.S. Census divisions. Results: Baseline models revealed a paradox: rurality was a direct risk factor for suicide (B=0.400) but protective for poor mental health days (B=-0.224). The national multivariable model revealed a significant, positive rurality-food insecurity interaction for suicide mortality (B=0.861), indicating a synergistic risk. This interaction was not significant for general mental distress, which was more strongly predicted by income and food insecurity. Regional analysis confirmed the suicide interaction was potent in five divisions, including the Pacific (B=3.048) and Mountain (B=1.712) , but absent in others (e.g., South Atlantic). Conclusions: The drivers of suicide are distinct from those of general mental distress and are geographically heterogeneous. The interaction of rurality and food insecurity creates a compounded risk for suicide. Suicide prevention must be regionally-tailored and address structural inequalities, such as food insecurity, alongside clinical care.

Human immunodeficiency virus (HIV) and hepatitis B virus (HBV) coinfection is associated with accelerated liver disease, but whether coinfection is associated with newly documented social determinants of health (SDoH) is unclear. We conducted a retrospective cohort study using TriNetX across 110 U.S. healthcare organizations (2010-2026). We propensity score matched adults with HIV/HBV to adults with HIV or HBV monoinfection. We organized newly documented SDoH indicators using a dynamic individual-level framework with four clinically recognized domains of social disadvantage: material vulnerability, healthcare access and engagement, interpersonal adversity, and psychosocial vulnerability. Matched cohorts included 10,071 HIV/HBV-HIV pairs and 9,659 HIV/HBV-HBV pairs (mean age, 47 years; 79% male; 66% non-White; median follow-up, 3.3 years). Over 178,900 person-years, HIV/HBV was associated with higher risk of the primary SDoH composite compared with HIV (11.5% vs 9.7%; incidence rate, 2.50 vs 1.97 per 100 person-years; hazard ratio [HR], 1.25; 95% confidence interval [CI], 1.15-1.37) and HBV (11.0% vs 6.4%; incidence rate, 2.39 vs 1.67; HR, 1.50; 95% CI, 1.35-1.67). HIV/HBV was also associated with higher material vulnerability and healthcare access and engagement composites in both comparisons, including housing instability, food insecurity, financial insecurity, insurance instability, and care disengagement/nonadherence (HR range, 1.22-3.33 vs HIV; 1.31-1.94 vs HBV). In the HBV comparison, HIV/HBV was additionally associated with interpersonal adversity, primary support stressors, and violence or victimization (HR range, 1.36-2.16). Findings were robust across sensitivity analyses. HIV/HBV was associated with more newly documented SDoH than monoinfection, supporting dynamic SDoH assessment.

Objectives: To describe age-group differences in inability to afford dental treatment and cost related dental delay, among the US community-dwelling population. Study design: Descriptive analysis of nationally representative survey data. Methods: Using nationally representative Medical Expenditure Panel Survey data (2018-2021), we examined trends in inability to afford dental treatment and cost-related dental treatment delays across four age groups (2-17, 18-39, 40-64, [&ge;]65 years). Weighted analyses accounted for the complex survey design; statistical significance was set at p<0.001. Results: Cost-related delays declined modestly from 2018 to 2021 but remained most prevalent among adults aged 40-64 (4.8% for ages 40-64, 3.4% for ages 18- 64, 2.2% for ages>65 in 2021; p<0.001). Conclusion: Middle-aged adults seem to experience delays due to cost, underscoring the need for dental coverage to expand dental coverage for this group and to reduce their out-of-pocket costs.

Introduction: Breast, cervical, and colorectal cancer screening guidelines changed substantially between 2010 and 2019. We examined trends in the annual utilization of these screenings among commercially insured enrollees in the United States from 2010 to 2019 by age group, geographic region, and screening modality. Methods: We conducted a retrospective, serial cross-sectional analysis of the MarketScan Commercial Claims Database from 2010 through 2019, comprising approximately 141.2 million privately insured enrollees. Annual screening rates, defined as the proportion of eligible enrollees receiving a given test within each calendar year, were estimated for cervical, breast, and colorectal cancer using procedure codes, stratified by age group, screening modality, and geographic residence. These reflect annual utilization rather than up-to-date (guideline-concordant) screening. Temporal trends were evaluated using two-sided Poisson regression, and urban-rural disparities in 2019 were assessed using multivariate generalized estimating equations. Results: Cancer screening utilization remained stagnant or declined across all three cancer types over the study period. Among women aged 30-64 years, cervical cytology alone declined substantially from 28.2% in 2010 to 8.8% in 2019, while co-testing increased from 11.4% to 20.3%. Screening mammography among women aged 50-64 showed minimal change, remaining stable at 45.7% in 2010 and 45.8% in 2019. Colorectal cancer screening across enrollees aged <64 decreased modestly from 7.7% in 2010 to 6.5% in 2019, with a more pronounced decline among adults aged 45-49 years. Across all three cancer types, screening utilization was higher among urban residents than rural residents, with incidence rate ratios ranging from 1.02 to 1.05 in 2019. Conclusions: Utilization of cervical, breast, and colorectal cancer screening among commercially insured adults did not improve between 2010 and 2019. Persistent urban-rural disparities highlight ongoing gaps in preventive care delivery. Targeted interventions may help improve screening utilization, particularly in rural and underserved populations.

Abstract Background: Sub Saharan Africa is experiencing an accelerating epidemiological transition characterized by a growing burden of non-communicable diseases. Although excess body weight is an established risk factor for cardiovascular disease significant variations in hypertension status exist among overweight and obese adults due to individual traits and community environments. This study aimed to identify individual and community level determinants of hypertension among overweight and obese adults in Ethiopia using nationally representative Demographic and Health Survey data. Methods: We analyzed nationally representative data from non pregnant adults aged eighteen years and older with a Body Mass Index of 25 kilograms per meter squared or higher from the two stage cluster sampled 2024-25 Ethiopia Demographic and Health Survey across 797 enumeration areas. The primary outcome was hypertension, defined by elevated blood pressure or current antihypertensive medication use. Two level multivariable logistic regression evaluated fixed effect Adjusted Odds Ratios with 95% Confidence Intervals, alongside cluster random effects and model performance using Intra Class Correlation, Median Odds Ratio, Proportional Change in Variance and the Akaike Information Criterion. Results: Among a total weighted sample of three thousand eight hundred forty-two overweight and obese adults across six hundred twelve clusters, the weighted national prevalence of hypertension was 24.8%. In the final multivariable multilevel model, advancing age, male sex, higher educational status and upper wealth index categories were significant individual level risk factors. At the community level, residing in urban clusters and high community level wealth concentration significantly elevated hypertension odds. The null model revealed substantial clustering, which dropped substantially in the final model, demonstrating that contextual factors account for much of the cluster variations. Conclusions: Both individual metabolic and demographic drivers alongside community level economic and urban environments influence hypertension risk among overweight and obese Ethiopian adults. Cardiovascular health strategies should combine clinical targeted screening with urban structural modifications that facilitate active living environments.

Background. Obesity has been associated with higher risk of dengue virus (DENV) infection and disease, yet its influence on antibody responses to DENV remains undefined. Methods. We evaluated whether nutritional status -- based on BMI z-score (BMIz) -- or blood markers of body fat -- leptin and adiponectin --are associated with binding and/or neutralizing antibody responses to DENV in 85 children in the Nicaraguan Pediatric Dengue Cohort Study who experienced a primary DENV infection in 2019. Associations were estimated using linear models adjusting for age, sex, and DENV infection outcome. Results. Compared to children with normal weight, those with obesity had higher quantities of DENV binding antibodies (fold-change [FC] 1.89, 95% confidence interval [CI] 1.02, 3.48) but no difference in neutralizing antibodies. Likewise, leptin concentration was associated with higher quantities of binding antibodies (FC 1.22, 95%CI 1.09, 1.37), while adiponectin was associated with lower quantities (FC 0.79, 95%CI 0.67, 0.94), and neither was associated with neutralizing antibodies. Lower neutralizing efficiency (neutralizing/binding antibodies) was observed in children with obesity (FC 0.67, 95%CI 0.48, 0.93). Conclusions. Our results indicate that obesity is associated with higher antibody quantity (binding) but not higher quality (neutralization) post-primary DENV infection -- implying that antibodies generated by children with obesity have lower neutralization efficiency, requiring greater quantities to reach similar levels of neutralization than children with normal weight. Further, the agreement among the three models using distinct proxies of body fat -- BMIz, leptin, and adiponectin -- demonstrates that adipokines are useful in supplementing BMIz analysis or as independent predictors of immune responses.

Ayahuasca use has expanded beyond its traditional Amazonian contexts, yet prospective longitudinal data examining depressive symptoms following naturalistic use in the United States remain limited. We conducted an interim analysis of an ongoing prospective observational cohort of adults participating in naturalistic ayahuasca use in Las Vegas, Nevada. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), with higher scores indicating greater depressive symptom severity, at baseline and approximately 48 hours, 30 days, 60 days, and 90 days following exposure. At interim analysis, PHQ-9 data were available for 87 participants at baseline, 61 at 48 hours, 41 at 30 days, 33 at 60 days, and 26 at 90 days. Mean PHQ-9 scores decreased from 8.06 (SD 5.96) at baseline to 4.39 at 48 hours, 3.76 at 30 days, 3.97 at 60 days, and 3.65 at 90 days. Among participants with matched baseline and follow-up assessments, mean changes were -3.58 points at 48 hours, -4.47 at 30 days, -4.48 at 60 days, and -4.76 at 90 days. In a mixed-effects model accounting for repeated observations, PHQ-9 scores remained significantly lower than baseline at 48 hours ({beta}=-3.70; 95% CI -5.09 to -2.31), 30 days ({beta}=-4.34; 95% CI -6.01 to -2.67), 60 days ({beta}=-3.97; 95% CI -5.77 to -2.18), and 90 days ({beta}=-4.25; 95% CI -6.18 to -2.33; all p<0.001). Among participants with baseline PHQ-9 scores [&ge;]5 and matched follow-up data, 69.2% demonstrated a reduction of at least 5 points at 90 days. These interim findings provide preliminary evidence of a sustained longitudinal association between naturalistic ayahuasca exposure and lower depressive symptom scores through 90 days in a U.S.-based cohort. The observational design, self-selection, incomplete follow-up, and absence of a control group preclude causal inference. Continued longitudinal follow-up is needed to determine the durability of this association.

Objectives: To estimate the prevalence of Post-Exertional Malaise (PEM) among adults with prior COVID-19 and associated mental health and disability outcomes. Methods: We conducted a cross-sectional analysis of data from a survey of 9,620 adults with prior COVID-19 in New York City, collected May - June 2024. PEM was measured with the DePaul Symptom Questionnaire - Post Exertional Malaise, categorized by symptom duration (< 14 vs. [&ge;]14 hours). Weighted prevalence estimates were stratified by socio-demographic and clinical characteristics. Modified Poisson regression was used to assess the association of PEM with depression, anxiety, and disability. Results: The prevalence of PEM symptoms was 20.9% overall and 4.0% with symptom duration [&ge;]14 hours, representing over 800,000 New Yorkers affected and over 150,000 who meet a diagnostic criterion for ME/CFS. PEM prevalence was higher among women, transgender and non-binary adults, people of color, and lower educational attainment, chronic comorbidities, or disabilities. PEM was associated with 3 - 4 times higher prevalence of mental health outcomes and 4 - 5 times higher disability scores. Conclusions: PEM symptoms were common and strongly associated with disability and adverse mental health. Screening, pathways to care, and supportive policies are needed to mitigate long-term consequences, particularly among marginalized populations.

Background. The imprecision of current metrics to capture the complex genetic admixture and racial identity among Hispanic/Latino individuals in the United States [US] is a concern. We examined the relationship of self-reported race and genetic ancestry with hypertension [HTN] among Hispanics/Latinos. Methods. Cross-sectional study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), including 10,586 Hispanic/Latino unrelated adults. Genetic ancestry: West African [AA], Amerindian [AI], and European [EA]. Self-reported race: White, Black, Native American, or Multiple/Missing (More than one race or Unknown/Not reported/Refused). HTN: systolic (SBP) [&ge;]130 mmHg, diastolic blood pressure (DBP) [&ge;]80 mmHg, and/or use of HTN medications. Age- and sex adjusted models were used. Results. Self-reported race was White (38{middle dot}6%), Black (3{middle dot}6%), Native American (4{middle dot}1%), and Multiple/Missing (53{middle dot}7%), with Unknown/Not reported/Refused representing 32{middle dot}7%. Black and White Hispanics/Latinos had the greatest AA (55{middle dot}7%) and EA (69{middle dot}3%) ancestries, respectively. Each 10% AA increase was associated with OR 1{middle dot}15, SBP beta +0{middle dot}9 mmHg, and DBP beta +0{middle dot}7 mmHg. Conversely, each 10% AI increase was associated with OR 0{middle dot}83, SBP beta -0{middle dot}4 mmHg, and DBP beta -0{middle dot}6 mmHg. HTN prevalence was highest among those with Black race or in the highest AA quantile (45{middle dot}6% and 48{middle dot}0%, respectively), and lowest among those with Native American race or in the highest AI quantile (37{middle dot}6% and 26{middle dot}7%, respectively). Conclusion. One-third of Hispanics/Latinos did not self-report race. Black or White self-reporting race did somewhat relate to AA or EA ancestry, respectively. HTN profiles were related to self-reported race and genetic ancestry in this admixed population.