Annals of Epidemiology最新文献

{"title":"Describing county-level clustering patterns of suicide among Veterans Health Administration patients and all American adults, 2018–2019, using exploratory spatial data analysis","authors":"A.R. Cunningham ,&nbsp;V. Lebakula ,&nbsp;A.G. Cosby ,&nbsp;A. Kapadia ,&nbsp;J. Trafton ,&nbsp;A. Peluso","doi":"10.1016/j.annepidem.2025.08.014","DOIUrl":"10.1016/j.annepidem.2025.08.014","url":null,"abstract":"<div><h3>Purpose</h3><div>Veterans account for 7 % of the adult American population but nearly 14 % of the country’s adult suicides. With a distinct geodemographic profile, veterans represent an important subpopulation for spatial analysis, and their access to Veterans Health Administration (VHA) care can make them a uniquely reachable group for policy interventions and research. Better understanding of VHA patterns in context can inform prevention strategies.</div></div><div><h3>Methods</h3><div>Hotspot analysis, a type of exploratory spatial data analysis (ESDA), was used to identify county-level clusters with high or low empirical Bayesian smoothed suicide rates among VHA patients in 2018–2019. A parallel analysis was conducted for all American adults. Clusters were then described using county-level characteristics previously linked to suicide prevalence.</div></div><div><h3>Results</h3><div>Clusters among VHA patients and the general population often overlapped and shared similar features. Cold spots were associated with lower elevations, higher incomes, and higher education levels, whereas hotspots were associated with higher elevations. All cold spots in the general population and most clusters among VHA patients occurred in metropolitan areas, however VHA hotspots also occurred in metropolitan areas.</div></div><div><h3>Conclusions</h3><div>Juxtaposing VHA and general adult ESDA results elucidates patterns of VHA suicides in context, highlighting spatial clusters as targets for interventions and research.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 148-153"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictors of migraine prevalence among different age groups in Hong Kong Chinese women: Machine learning analyses on the MECH-HK cohort.","authors":"Yafei Wu, Harry Qin, Shengnan Wang, Qingling Yang, Yan Zhang, Harry Haoxiang Wang, Yao Jie Xie","doi":"10.1016/j.annepidem.2025.07.017","DOIUrl":"10.1016/j.annepidem.2025.07.017","url":null,"abstract":"<p><strong>Purpose: </strong>To identify age-specific predictors of migraine prevalence among Chinese women.</p><p><strong>Methods: </strong>In this cross-sectional analysis, 54 predictors were collected from the MECH-HK cohort. Migraine was assessed by the ICHD 3rd edition. Machine learning was employed to select a streamlined subset of predictors. Participants were categorised as young and middle age group (<60 years) and old age group (≥60 years) for analysis.</p><p><strong>Results: </strong>The mean age of participants was 54.3 years. Migraine prevalence was higher in women under 60 than in older women (10.7 % vs. 6.0 %, P < 0.001). Lasso selected seven (<60 years) and twelve (≥60 years) predictors, respectively. The top three predictors among women under 60 were fatigue, migraine family history, and PSQI, explaining 6.6 %, 5.0 %, and 4.9 % of variation, respectively. Their ORs (95 % CIs) were 1.61 (1.37-1.89), 3.93 (2.77-5.57), and 1.29 (1.12-1.48), respectively. For older women, the top three predictors were experience of hunger, smartphone usage time, and migraine family history, explaining 2.0 %, 1.8 %, and 1.6 % of variation, respectively, with ORs (95 % CIs) of 2.16 (1.21-3.84), 1.24 (1.03-1.48), and 2.26 (1.16-4.40), respectively.</p><p><strong>Conclusion: </strong>Migraine family history and experience of hunger were shared predictors for migraine prevalence in both ages. Other predictors differentially influence migraine prevalence across ages.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"34-42"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concordance of number of chronic conditions estimated from electronic health record or self-report","authors":"Mary J. Kwasny ,&nbsp;Laura M. Curtis ,&nbsp;Lauren A. Opsasnick ,&nbsp;Scott Hur ,&nbsp;Michael S. Wolf","doi":"10.1016/j.annepidem.2025.08.023","DOIUrl":"10.1016/j.annepidem.2025.08.023","url":null,"abstract":"<div><h3>Purpose</h3><div>Self-report or electronic health records can be used to calculate number of chronic conditions for study participants. Although agreement for specific conditions can be found in the literature, there is a lack of information on how the total number of conditions compares between the two sources.</div></div><div><h3>Methods</h3><div>Using a long-standing cohort study, the number of chronic conditions was estimated for 351 participants using self-report and data from their electronic health record. Agreement for each condition, and for total number of conditions was estimated using a weighted kappa with 95 % Confidence Interval (CI), and using Lin’s concordance coefficient, and a Bland-Altman plot. Predictors of discord were identified using generalized linear models with concordant pairs as reference.</div></div><div><h3>Results</h3><div>Discord varied by condition but ranged from 3.7 % (diabetes, kappa=0.86) to 33.2 % (hyperlipidemia, kappa=0.31). While the mean number of chronic conditions was similar, it showed poor agreement [weighted kappa= 0.46 (95 % CI: 0.41, 0.52)], and did not show pattern of discrepancy as the average number of chronic conditions increased. Discrepancies were related to condition, male sex, and lower education.</div></div><div><h3>Conclusion</h3><div>There are opportunities to ensure that electronic health records are complete, and that patients receive adequate health education to become aware of the conditions that they have.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 141-147"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association between metabolic syndrome and risk of severe infection: A population-based cohort study","authors":"Ming Zhao ,&nbsp;Jiayi Huang ,&nbsp;Luojia Dai ,&nbsp;Chenyu Liang ,&nbsp;Yankun Liu ,&nbsp;Haili Wang ,&nbsp;Xin Zhang ,&nbsp;Shuzhen Zhao ,&nbsp;Chengnan Guo ,&nbsp;Zhenqiu Liu ,&nbsp;Tiejun Zhang","doi":"10.1016/j.annepidem.2025.08.015","DOIUrl":"10.1016/j.annepidem.2025.08.015","url":null,"abstract":"<div><h3>Purpose</h3><div>The association between metabolic syndrome (MetS) and severe infection remains inconclusive. We investigated the potential associations between MetS and its components and severe infection in a large population-based cohort.</div></div><div><h3>Methods</h3><div>We used data from Shanghai Suburban Adult Cohort and Biobank which includes 35,193 participants who were enrolled in 2016 and 2017 with follow-up until March 2024. Severe infections, defined as those requiring hospital admission or resulting in mortality, were identified through medical records. Cox proportional hazards models were used to analyze the associations between MetS and its components with incident severe infection.</div></div><div><h3>Results</h3><div>During a median of 6.96 years of follow-up, a total of 1143 (11.78 %) severe infections occurred in participants with MetS and 2337 (9.18 %) in No MetS group. MetS was associated with an increased risk of severe infection compared to the No MetS group (HR, 1.19; 95 % CI, 1.11–1.28). Among the individual components, elevated waist circumference, fasting blood glucose, and reduced HDL cholesterol were associated with increased severe infection risk, whereas elevated blood pressure alone was associated with reduced severe infection risk (HR, 0.91; 95 % CI, 0.85–0.98). The risk of severe infection also increased with increasing number of MetS components, with the highest risk found in the presence of all 5 components (HR, 1.70; 95 % CI, 1.39–2.07).</div></div><div><h3>Conclusions</h3><div>MetS was associated with an increased risk of severe infection. Further studies are warranted to elucidate the association between MetS and severe infection.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 107-113"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlates of single morbidities and multimorbidity in children: A cross-sectional study","authors":"Alex Luther ,&nbsp;Danielle Fearon ,&nbsp;Ian Colman ,&nbsp;Joel A. Dubin ,&nbsp;Laura Duncan ,&nbsp;Scott T. Leatherdale ,&nbsp;Dillon Browne ,&nbsp;Mark A. Ferro","doi":"10.1016/j.annepidem.2025.08.039","DOIUrl":"10.1016/j.annepidem.2025.08.039","url":null,"abstract":"<div><div>This study investigated and compared correlates of multimorbidity with other single morbidity statuses (physical illness only, mental disorder only, neurodevelopmental disorder only) among children in Canada. The epidemiological sample included 33,715 children aged 5–17 years from the Canadian Health Survey of Children and Youth. Classification of children by morbidity status was based on reports from the person most knowledgeable (PMK). Multinomial logistic regression quantified associations between demographic and psychosocial characteristics and morbidity status using odds ratios (ORs) and 95 % confidence intervals (CIs). Female (OR=0.5 [0.5–0.6]) and immigrant children (OR=0.6 [0.5–0.8]) were less likely to report multimorbidity, as well as singular morbidity statuses. Older children (OR=2.3 [2.1–2.6]) were more likely to report multimorbidity. Elevated parent stress (OR:2.1 [1.7–2.5]), worse parent mental health (OR=3.0 [2.4–3.7]), and communities perceived as less safe (OR:1.5 [1.2–2.0]) were associated with higher odds of multimorbidity. Differences in magnitudes of association across morbidity statuses for child age and sex, as well as PMK mental health, and stress levels represent opportunities to identify at-risk children to aid in the prevention of multimorbidity. Strong associations between parent stress and mental health and child morbidity highlight the need to adopt integrated health services that use a family-centred model of care.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 160-165"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Family incarceration and barriers to mental health care among low-income US veterans","authors":"Alexander Testa PhD ,&nbsp;Luis Mijares MS ,&nbsp;Jack Tsai PhD","doi":"10.1016/j.annepidem.2025.08.006","DOIUrl":"10.1016/j.annepidem.2025.08.006","url":null,"abstract":"<div><h3>Background</h3><div>Family member incarceration is a risk factor for mental health challenges. However, less research has investigated the relationship between family member incarceration and barriers to mental health services.</div></div><div><h3>Methods</h3><div>Data were drawn from the 2023 National Veteran Homeless and Other Poverty Experiences (NV-HOPE) Survey, a nationally representative sample of US veterans living at or below 300 % of the federal poverty level (N = 978). Logistic regression models were used to examine the association between family member incarceration and self-reported barriers to mental health care, adjusting for demographic, socioeconomic, and military service characteristics.</div></div><div><h3>Results</h3><div>Overall, 42.1 % of veterans reported that a family member had been incarcerated. Veterans with an incarcerated family member had 1.63 times greater odds of reporting any barrier to mental health care (95 % CI: 1.13–2.33). Specific barriers to mental health care reported by these veterans included embarrassment (OR = 2.25, 95 % CI = 1.18, 4.29), being treated differently by peers (OR = 2.51, 95 % CI = 1.24, 5.08), not knowing where to seek help (OR = 2.25, 95 % CI = 1.23, 4.10), inadequate transportation (OR = 7.01, 95 % CI = 2.99, 16.41), difficulty scheduling appointments (OR = 2.84, 95 % CI = 1.65, 4.89), and treatment cost (OR = 1.72, 95 % CI = 1.14, 2.60).</div></div><div><h3>Conclusions</h3><div>Family member incarceration is associated with increased barriers to mental health care among low-income US veterans. These findings highlight the potential value of programs within veteran healthcare that address the barriers to mental health access, especially among those with a history of family member incarceration.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 89-94"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging mediation analysis as a tool to study mechanisms underlying health inequities.","authors":"Judith J M Rijnhart, Ryan J Bailey, Jessica Agbodo, Vishakha Agrawal, Valerie M Rodriguez-Olmo, Jason L Salemi","doi":"10.1016/j.annepidem.2025.07.002","DOIUrl":"10.1016/j.annepidem.2025.07.002","url":null,"abstract":"<p><strong>Purpose: </strong>To describe three statistical approaches that help gain a comprehensive understanding of mechanisms underlying health inequities: univariate regression analysis, effect modification analysis, and mediation analysis.</p><p><strong>Methods: </strong>We described how univariate regression analysis, effect modification analysis, and mediation analysis can be used to gain insight into mechanisms underlying health inequities. We demonstrated the application of these approaches using a motivating example from the Health and Retirement Study in which we studied the role of education in ethnic disparities in episodic memory.</p><p><strong>Results: </strong>Univariate regression analysis showed that Hispanic individuals on average had lower episodic memory scores compared to non-Hispanic individuals. Effect modification analysis showed that the beneficial effect of education on episodic memory was less strong in Hispanic individuals compared to non-Hispanic individuals. Mediation analysis showed that the ethnic disparity in episodic memory was not only driven by effect modification, but also by differences in the distribution of education years across ethnic groups.</p><p><strong>Conclusion: </strong>The combined study of effect modification and mediation provides a comprehensive understanding of the mechanisms that cause and sustain health inequities. Insight into these mechanisms is crucial to determine targets for interventions and policies aimed at eliminating health inequities.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"1-6"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144644079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal trends in COVID-19 vaccine uptake among social housing residents compared to the general population in Ontario, Canada: A population-based panel study","authors":"Gina Agarwal MBBS PhD ,&nbsp;Homa Keshavarz PhD ,&nbsp;Ricardo Angeles MD PhD ,&nbsp;Melissa Pirrie PhD ,&nbsp;Francine Marzanek BEd ,&nbsp;Francis Nguyen MPH ,&nbsp;Jasdeep Brar HBSc ,&nbsp;J. Michael Paterson MSc","doi":"10.1016/j.annepidem.2025.08.024","DOIUrl":"10.1016/j.annepidem.2025.08.024","url":null,"abstract":"<div><h3>Background</h3><div>This study examined temporal trends in COVID-19 vaccine uptake among social housing residents compared to the general population in Ontario, Canada, during the first year of vaccine availability.</div></div><div><h3>Methods</h3><div>We analyzed 2021 COVID-19 vaccination data from Ontario administrative databases. The social housing population was identified using postal codes of designated social housing buildings. Vaccination rates were compared quarterly across age and sex categories between social housing residents and the general population.</div></div><div><h3>Results</h3><div>In 2021, there were 14,842,488 eligible individuals identified in Ontario administrative health data, with 328,276 individuals residing in social housing. By the end of 2021, 75.45 % of adult social housing residents were fully vaccinated (2 or more COVID-19 vaccine doses) compared to 87.46 % of the general adult population. This gap persisted over time and across sexes. Over the same period, 30.61 % of the children and youth in social housing achieved full vaccination rates compared to 30.21 % of the general population, with greater vaccine uptake among females.</div></div><div><h3>Conclusion</h3><div>Despite COVID-19 vaccination policies aimed at prioritizing vulnerable groups in Ontario, Canada, adult social housing residents had lower vaccination rates compared to the general population. Children and youth in social housing achieved slightly higher vaccination coverage. These findings underscore the need for more targeted efforts to improve vaccine accessibility and uptake among social housing residents.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 154-159"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144911888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rising maternal obesity and persistent suboptimal gestational weight gain among women living with HIV in Kenya: A retrospective cohort study 2008–2017","authors":"Nazha M. Diwan ,&nbsp;Betty Mbithe ,&nbsp;John Kinuthia ,&nbsp;Tony J. Cagle ,&nbsp;Charles Kibaara ,&nbsp;Andrew Nagy Adly ,&nbsp;Michael H. Chung ,&nbsp;Angela M. Bengtson","doi":"10.1016/j.annepidem.2025.08.001","DOIUrl":"10.1016/j.annepidem.2025.08.001","url":null,"abstract":"<div><h3>Purpose</h3><div>To describe trends in pre-pregnancy BMI (ppBMI), gestational weight gain (GWG), and associations with birth outcomes among women living with HIV (WLWH) in Kenya.</div></div><div><h3>Methods</h3><div>WLWH who initiated antenatal care ≤ 14 weeks of gestation at the Coptic Hope Center in Nairobi and Maseno, Kenya between 2008 and 2017 were identified. PpBMI was defined using first-trimester BMI (Kg/m²); GWG was assessed using weekly GWG rate in the second-and-third trimesters per National Academy of Medicine (NAM) guidelines. Associations between GWG z-scores and birthweight, low/high birthweight, and emergency cesarean-section (c-section) were examined using mixed-effects models.</div></div><div><h3>Results</h3><div>We identified 1190 pregnancies, of which more than half had overweight (34.3 %) or obese (18.0 %) ppBMI, 45.1 % had normal ppBMI, and 2.6 % were underweight. From 2008–2017, obese ppBMI among WLWH doubled, while normal ppBMI decreased by 8.2 %. Suboptimal GWG rates, both above and below NAM-recommendations, were common across ppBMI categories. A one-unit increase in GWG z-score was associated with higher birthweight (+45.96, 95 % CI: 15.29–75.17) and increased risk of emergency c-section (aRR=1.35, 95 % CI: 1.03–1.82).</div></div><div><h3>Conclusion</h3><div>From 2008–2017, maternal obesity among WLWH in Kenya increased, while GWG rates remained suboptimal. Future studies should examine barriers and possible interventions to address rising ppBMI and promote healthy GWG among WLWH.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"110 ","pages":"Pages 81-88"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144805235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Where you live and where you receive care: Using cross-classified multilevel modeling to examine hospital and neighborhood variation in in-hospital mortality and mortality disparities.","authors":"Alina Schnake-Mahl, Ana V Diez Roux, Bian Liu, Louisa W Holaday, Albert Siu, Edwin McCulley, Usama Bilal, Katherine A Ornstein","doi":"10.1016/j.annepidem.2025.07.021","DOIUrl":"10.1016/j.annepidem.2025.07.021","url":null,"abstract":"<p><strong>Purpose: </strong>Both hospitals and neighborhoods likely play important roles in driving health outcomes and inequities, but there has been limited prior research examining both contexts simultaneously. In this analysis we examine the contributions of these two critical contexts, neighborhoods and hospitals, to variation in in-hospital mortality and mortality disparities.</p><p><strong>Methods: </strong>We used cross-classified multi-level models, a statistical technique that can incorporate data from multiple non-nested levels, to examine the variation in contribution of neighborhoods and hospitals to in-hospital mortality. Our study focuses on COVID-19 in hospital mortality from New York State in 2020, as a methodological case study of cross classified multilevel modeling, given the well documented variation in COVID-19 in-hospital mortality across contexts.</p><p><strong>Results: </strong>We found that nearly one in five patients hospitalized for COVID-19 died, and there was substantial variation in risk of in-hospital mortality by neighborhoods and hospitals, with more variation across hospitals (τ₀₀:0.29) than across neighborhoods (τ₀₀:0.02). Neighborhoods did not explain hospital variability and vice versa: both contexts appeared to contribute independently to in-hospital mortality rates. We also found several hospital, neighborhood, and individual factors were associated with in hospital mortality disparities in fully adjusted models: lower hospital quality and safety-net hospitals, social vulnerability, older age, not having private insurance, and being Hispanic or non-Hispanic other.</p><p><strong>Conclusions: </strong>Our findings suggest the importance of simultaneously considering hospital and neighborhood contexts to understand in-hospital outcome disparities. Understanding the contribution of these critical contexts has important implications for targeting interventions to ensure equitable hospital outcomes despite inequities in neighborhood and hospital contexts.</p>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":" ","pages":"16-22"},"PeriodicalIF":3.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12750337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}