Annals of Epidemiology

Background: Lung cancer in never-smokers is rising, with a substantial proportion harboring the EGFR mutation. While fine particulate matter (PM2.5) is a recognized risk factor, other intervenable pollutants and built environmental factors remain unknown. Objectives: To identify urban characteristics associated with EGFR-mutant (vs. wild-type) lung cancer using high-resolution spatiotemporal data. Methods: We analyzed 2,699 lung cancer patients with documented EGFR status treated at a high-volume academic medical center in New York City. Patient residential addresses were linked to high-resolution (300m x 300m) 5-year cumulative exposures to 3 air pollutants and 26 urban features. We developed Light Gradient Boosting Machine (LightGBM) models to classify EGFR status, comparing a basic clinical model with established predictors (Asian, female, never-smoking status, and adenocarcinoma histology) to an extended model with additional urban factors. Predictive performance was assessed based on discrimination (AUC). Results: We included 2,699 patients, of whom 54.1% were female and 25.8% self-identified as Asian, 11.2% as Black, and 7.4% as Hispanic; and 29% had EGFR-mutated cancer. The extended model showed modest improvements in discrimination (AUC: 0.775 [95% CI, 0.739-0.809] vs. 0.768 [0.723-0.811]), compared to the clinical model. Newly identified factors for EGFR-mutant status included black carbon (BC), nitrogen dioxide (NO2), proximity to airports, reduced access to public transportation, elevated noise levels, and lead exposure. Conclusions: Traffic-related pollutants (BC, NO2) from diesel engines and motor vehicles, and proximity to airports, were among the novel spatiotemporal features associated with EGFR-mutant lung cancer. These results may inform policy interventions.

ABSTRACT: Importance: Rural urban disparities in chronic disease prevalence are well established; however, the extent to which individual level socioeconomic status (SES) contributes to these disparities remains unclear. Objective: To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design: We conducted a retrospective cross sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014 to 2019). Setting: Population based Participants: Adults over 18 years residing in the 27 E REP counties, excluding those missing rural urban residence status. Exposure: HOUSES index, an individual level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome: Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014 to 2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural urban and SES differences for prevalence of each chronic disease. Results: Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance: Individual level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

BackgroundComputed tomography (CT) is a cornerstone of timely diagnosis for stroke, trauma, and oncologic conditions, and delays in access are associated with worsened outcomes. Although Houston, Texas, is home to one of the worlds largest medical complexes, the geographic distribution of CT imaging infrastructure has not been systematically examined against neighborhood-level measures of socioeconomic vulnerability. MethodsWe conducted a cross-sectional geospatial analysis of CT imaging facilities across the Greater Houston metropolitan area. Facility locations -- including hospital-based scanners, independent imaging centers, and freestanding emergency facilities -- were compiled from publicly available imaging directories, Texas Department of State Health Services (DSHS) facility listings, Centers for Medicare & Medicaid Services (CMS) provider data, and CT location data contributed by MD Anderson Cancer Center. Census tract-level indicators (median household income, percent uninsured, poverty rate) were obtained from the U.S. Census Bureau American Community Survey. Facility locations were geocoded and overlaid on census-tract choropleths in ArcGIS Online and ArcGIS StoryMaps to identify tracts with elevated socioeconomic vulnerability and limited proximity to CT infrastructure. ResultsCT imaging facilities were markedly clustered in the central urban core and in higher-income corridors, with hospital-based and independent scanners concentrated in census tracts with lower poverty rates, higher median household income (>$119,300), and higher insurance coverage. Conversely, peripheral and southeastern tracts with elevated poverty (>24%), median household income below $37,800, and uninsured rates exceeding 16% contained comparatively sparse CT infrastructure, generating spatial "gaps" in advanced diagnostic capacity. The pattern persisted across facility type: freestanding emergency and independent imaging centers did not meaningfully compensate for the undersupply of hospital-based scanners in vulnerable communities. ConclusionsIn Houston, the spatial distribution of CT imaging resources mirrors rather than offsets underlying socioeconomic inequality. Neighborhoods with higher poverty and uninsured rates face compounded barriers of distance and coverage. Citywide spatial analysis renders these inequities visible in ways individual clinical encounters cannot, and supports equity-informed health-system planning, targeted investment in underserved catchments, and policies linking imaging-capacity expansion to measurable community need.

Decarceration, the process of reducing incarceration rates, is increasingly viewed as a strategy to improve population health and reduce health inequities. Yet, evidence on its health effects remains limited and may depend on how decarceration occurs. We developed a national decarceration "atlas" to characterize the mechanisms and dynamics of decarceration across more than 2,800 U.S. counties between 1999-2019. Using longitudinal county-level jail and prison data, we identified four operational types of decarceration: reduced pretrial detention, reduced jail time, reduced prison admissions, and reduced prison time. Nearly two-thirds of counties, including most rural counties, experienced at least one decarceration type during the study period. Declines typically followed periods of recent growth and were relatively modest in magnitude, with median reductions of 19% to 38% ten years after onset. The frequency and timing of decarceration types varied by urbanicity, state, and region, with many counties experiencing multiple mechanisms concurrently. Validation against documented case studies of state and local decarceration demonstrated alignment with known legislative and de facto drivers, while revealing substantial sub-state heterogeneity. This atlas provides a scalable framework and hypothesis-generating resource to support comparative studies of decarceration's heterogeneous health effects.

Background: Children with congenital heart disease (CHD) require specialized care and may face worse outcomes if they experience food insecurity (FI). FI is associated with poor nutrition, hospitalizations, and developmental delays, compounding cardiac risks. Limited research evaluated impact of FI on health status among children with CHD. This study examines socioeconomic factors and the relationship between FI and health status in children with CHD. Methods: 2023 National Survey of Children?s Health (NSCH) data were used to compare rates of FI between children ages < 17 years with and without CHD and to assess overall health status of those with CHD. Descriptive, univariate, and multivariable logistic regression were utilized. Results: Among 53,477 children, 1,233(2%) had CHD. FI was reported in 35% of children with CHD vs. 27% without CHD(p=0.005). After adjustment, children with CHD had higher odds of FI (OR 1.49; 95% CI: 1.05?2.12). Hispanic ethnicity, residence in Midwest or South, lower household education, and lower poverty index were significantly associated with FI. Households receiving food assistance had higher FI. Living in grandparent household was associated with lower odds of FI. Within the CHD subgroup, 5% reported fair or poor health. Children with CHD experiencing FI had greater odds of fair or poor health than those without FI (OR 3.91, 95% CI 1.70?9.02; p=0.001). Conclusions: Children with CHD face higher odds of FI, which is strongly associated with worse reported health. Addressing socioeconomic vulnerability and FI may improve outcomes and reduce disparities in this high-risk population through targeted screening and intervention strategies nationwide. Keywords: Congenital Heart Disease, Food Insecurity Screening, National Survey of Children?s Health (NSCH), Health Disparities

BackgroundCommercial motorcycle riders are among the most vulnerable road users in low- and middle-income countries and contribute substantially to the burden of road traffic injuries. The use of personal protective equipment (PPE), including helmets and protective clothing, reduces injury severity; however, uptake remains suboptimal. This study evaluated the effectiveness of a theory-driven health education intervention in improving knowledge, attitudes, and use of PPE among commercial motorcycle riders in Cameroon. MethodsA quasi-experimental, non-randomized controlled before-and-after study was conducted in Limbe (intervention) and Tiko (control) Health Districts between August 4, 2024, and April 6, 2025. Participants were recruited from a cohort of commercial motorcycle riders and followed over an eight-month intervention period. The intervention, guided by the Health Belief Model and developed using the Intervention Mapping framework, combined face-to-face sensitization sessions with mobile phone-based educational messaging adapted to participants literacy levels and communication preferences. Data were collected at baseline and endline using structured questionnaires and direct observation checklists. Intervention effects were estimated using difference-in-differences analysis with generalized estimating equations, adjusting for socio-demographic factors. ResultsA total of 313 riders were enrolled at baseline (183 intervention, 130 control), with 249 retained at endline (149 intervention, 100 control). The intervention was associated with significant improvements in PPE knowledge ({beta} = 2.91; 95% CI: 2.14-3.68; p < 0.001) and attitudes ({beta} = 5.76; 95% CI: 4.32-7.21; p < 0.001) compared with the control group. No statistically significant effect was observed for PPE practice scores ({beta} = 0.21; 95% CI: -0.09-0.52; p = 0.171). Among individual PPE items, helmet use increased significantly in the intervention group relative to the control group (AOR = 2.38; 95% CI: 1.19-9.45; p = 0.036), while no significant effects were observed for gloves, trousers, eyeglasses, or closed-toe shoes. ConclusionThe theory-driven health education intervention significantly improved knowledge and attitudes toward PPE and increased helmet use among commercial motorcycle riders but did not lead to broader improvements in the uptake of other protective equipment. These findings highlight the need for complementary structural and policy interventions to address persistent barriers to PPE use in similar low-resource settings. Trial registrationClinicalTrials.gov Identifier: NCT07087444 (registered July 28, 2025, retrospectively)

ObjectivesAcademic medical institutions are the gatekeepers of the physician workforce and shape the future of medicine by regulating medical school admissions as well as residency training. Although broadly the field of medicine is seeing more representation from traditionally underrepresented groups, the critical decision-making platform of academic medicine continues to be uncharacteristically homogeneous, represented mainly by white males. This is even more pronounced in surgical subspecialties, such as academic neurosurgery. This study aims to quantify this phenomenon, uncover its driving factors, and define opportunities for improvement. MethodsUsing a mixed research methodology, academic neurosurgical faculty in the U.S were identified, and their demographic data was collected. An internet search using Google Scholar and Scopus was conducted to determine scholarly activity using number of publications and h-index. ResultsWe found a significant increase in female faculty in academic neurosurgery within the last decade. Comparing the faculty rank amongst male and female faculty, we found that the majority of female faculty are at the assistant professor level (n=36/79; 45.6%) while male faculty are more at the full professor rank (n=265/582; 45.5%). A similar trend was seen for under-represented minority neurosurgery faculty. Strong scholarly activity corelated with a departmental chair position for male faculty, however, this trend was not true for female faculty. There was a significant difference in the number of publications and h-index in female vs male faculty, but only when including male faculty outliers at the full professor level. ConclusionSlowly but steadily, academic neurosurgery is making progress towards a more diverse and representative workforce in the U.S that better reflects the patient population. Facilitating timely progression of females and URM neurosurgeons into senior professorship and academic leadership roles will further advance this essential progress.

Pulmonary embolism (PE) is a sudden blockage of lung arteries, usually caused by a blood clot that travels from the deep veins of the legs. As the world becomes more sedentary and lifestyle diseases emerge, deaths from PE are expected to rise in the next 20 years. For instance, the United States records annual deaths of 60 per 100,000 people. The degree to which these deaths are affected by demographic, socioeconomic and environmental predisposing factors as well as how they vary across time and space remains an open science question. In this paper, we conduct a detailed statistical and spatial-temporal study PE mortality counts across US counties from 2005 to 2022. Our study shows that study shows that PE mortality is not randomly distributed in space and time but concentrated in most counties in Arkansas, Mississippi, Kansas, Missouri, Oklahoma, Louisiana, Nebraska, Tennessee, and Texas. We also established that age is a statistically significant predictor (mean coefficient of 0.52) of PE mortality especially in counties of Mississippi, Kansas, Missouri, Tennessee, Illinois, Kentucky, Texas and Virginia. Our results thus provide empirical support for prioritizing regionally targeted PE prevention policies. Furthermore, the adopted county-level analysis uncovered granular geographic patterns that are usually obscured in state or national level analysis. Our study thus provides actionable evidence to support geographically tailored strategies aimed at reducing mortality by pinpointing counties with consistently elevated PE mortality risk at different timescales.

Background Meat processing plants in Alberta, Canada experienced among North America's largest COVID-19 outbreaks. We examined health impacts among workers by occupational hierarchy and equity-relevant characteristics. Methods This exploratory sequential mixed-methods study was guided by community-based participatory research and the PROGRESS-Plus framework. Multilingual qualitative interviews and surveys using validated instruments were conducted among meat plant workers who experienced outbreaks. Interviews were analysed using inductive-deductive thematic analysis. Multivariable logistic regression and linear regression estimated associations between occupational group, racialization, facility, and self-reported COVID-19 diagnosis, physical and mental health, and mean Everyday Discrimination Scale score. We integrated findings using joint displays. Findings Qualitative and integrated analysis of thirty-six interviews described occupational hierarchy shaping unequal protection, limited communication, constrained agency, and psychosocial harms, amplified by income insecurity and family separation. Among 187 survey respondents, compared with general labour, skilled labour (aOR 0.38; 95% CI 0.15-0.89) and management (aOR 0.13; 95% CI 0.01-0.75) had lower odds of reported COVID-19 diagnosis. Compared with Black workers, other racialized workers had lower odds of reporting fair or poor mental (aOR 0.24; 95% CI 0.09-0.58) and physical health (aOR 0.20; 95% CI 0.06-0.54). Compared with workers from the primary facility, others reported lower mean everyday discrimination scores ({beta} = -0.54; 95% CI -0.96 to -0.12). Interpretation COVID-19 harms followed workplace social hierarchies. Pandemic preparedness should combine infection-control measures with paid sick leave and income protection, multilingual communication, enforceable anti-discrimination standards, and independent reporting mechanisms. Funding Canadian Institutes for Health Research (CIHR Application no. 469206). Keywords COVID-19, immigrant workers, migrants, essential workers, health equity, occupational health, PROGRESS Plus

Background Physical activity (PA) and body mass index (BMI) shape cardiovascular risk, particularly in women. Yet, little research exists examining intersectional social axes shaping PA and BMI inequities among women living in the United States (US). Methods Data included women sampled in the 2015-2020 National Health and Nutrition Examination Survey. We used Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA) via linear models to examine PA (n=,4591) and BMI (n=4,596) inequities across intersectional strata defined by race/ethnicity, age, education, nativity, and work status. We further quantified the contribution of these strata to the observed inequities and estimated additive fixed effects. Results In the null model, intersectional strata explained 4.6% and 13.8% of the variance in PA and BMI inequities, respectively, with 99.2% for PA and 97.5% for BMI explained by age, race/ethnicity, education, nativity, and occupation status. On average, Asian and Black women, those aged 35-49 years, those born outside the US, and those with less than a high school diploma had the lowest predicted mean PA. For BMI, Black and Hispanic/Latino women and those younger than 64 years had the highest mean BMI. Conclusion PA and BMI inequities are mostly explained by race/ethnicity, age, education, nativity, and work status. Our findings offer insights into universal and potential policy-informed health promotion strategies that may be tailored to women with these social identities and lived experiences that have shaped physical activity and body mass index inequities.

BackgroundOur group previously reported that lung cancer (LC) screening history results and subsequent timing of diagnosis are associated with significant differences in survival outcomes. As a follow-up study, we sought to develop novel personalized risk models that considered screening history for incidence cancers, interval LCs, and prevalence LCs. MethodsUsing data from the CT-arm of the NLST, four independent case-control analyses were conducted to develop parsimonious risk models. Controls (n=26,038) were those never diagnosed with LC. The four LC case groups were 270 prevalence LCs, 44 interval LCs, 206 screen-detected LCs (SDLCs) that had a baseline positive screen, and 164 SDLCs that had a baseline negative screen. For each case-control analysis, univariable analyses identified statistically significant covariates from 48 variables and then significant covariates were included into a stepwise backward selection approach to identify a model with the most informative covariates. ResultsFor prevalence LCs, the model (AUC=0.711) included age, pack-years smoked, BMI, smoking status, smoking onset age, personal history of cancer, family history of LC, alcohol consumption, and milling occupation. For interval LCs, the model (AUC=0.734) included age, smoking status, smoking onset age, cigar smoking, marital status, and asbestos occupation. For baseline positive SDLCs, the model (AUC=0.685) included age, pack-years smoked, BMI, emphysema, chemicals/plastics exposure, and milling occupation. For baseline negative SDLCs, the model (AUC=0.701) included age, pack-years smoked, BMI, smoking status, emphysema, sarcoidosis, and sandblasting occupation. ConclusionsBesides smoking and age, which are inclusion criteria for screening, these models identified other important risk factors which could be used to provide personalized LC risk assessment and screening management.

BackgroundDisparities in injury and death indicate that Latinos and Hispanics are disproportionately affected by firearm violence. Understanding the factors that impact Latino and Hispanic engagement with firearm safety is integral to developing nuanced interventions, yet these factors remain largely understudied. This study explores the social ecological factors related to firearm safety engagement among Latino and Hispanic adults residing in New Mexico. MethodsThe study used a convergent mixed-methods design with quantitative and qualitative components. Data were collected from a predominantly Latino-Hispanic community experiencing high rates of firearm violence near Albuquerque, New Mexico. Quantitative data (n=303) were collected using a community-based survey with a non-random sample on firearm safety engagement, collective efficacy, and sociodemographic characteristics. Qualitative data (n=18) included semi-structured interviews from a subset of the survey population who expressed interest in participating. Quantitative data was used to explore descriptive statistics and correlations between reported levels of collective efficacy and firearm safety engagement. Qualitative data were used to explore the firearm safety experiences of Latino and Hispanic participants. AnalysesMultivariate regression analyses examined associations between collective efficacy (exposure) and engagement with firearm safety (outcome). I also explored associations across key domains: collective efficacy, neighborhood characteristics, individual characteristics, and sociodemographic factors. Interviews were analyzed using framework analysis to generate a cohesive thematic structure informed by a social ecological model. The results from the quantitative and qualitative data were then integrated to develop a robust understanding of social ecological factors related to firearm safety engagement using a mixed methods joint display. ResultsThere were 303 survey participants (40.6% male; 55.1% female; 4.3% other gender identity) and 18 interview participants in this study. 57.1% of survey participants reported engaging with at least one firearm safety practice or initiative. Results from multivariate regression indicated that higher collective efficacy ({beta} = 0.082, p = 0.002), higher informal social control ({beta} = 0.174, p = 0.001), stronger endorsement of gun safety principles ({beta} = 0.079, p < 0.001), being married vs. unmarried ({beta} = -0.334, p < 0.001), speaking Spanish in the home vs. English ({beta} = 1.048, p < 0.001), and not owning a gun ({beta} = - 0.638, p = 0.006) were significantly and positively associated with firearm safety engagement. Themes from the qualitative data included barriers (insecure environment; lack of meaningful engagement) and facilitators (location-specific contributors to safety; collective identity and pride) to firearm safety engagement, organized by social ecological domain. Mixed methods findings indicate factors associated with participants individual firearm safety engagement, while providing insights into the perceived barriers and facilitators across social ecological domains. DiscussionFindings from this mixed-methods study suggest that processes of empowerment and collective efficacy may contribute to greater firearm safety engagement within Latino and Hispanic communities. Findings expand injury prevention research by exploring the factors influencing firearm safety engagement among a marginalized and hard-to-reach population who have disproportionate experiences with firearm victimization, perpetration, and injury. ConclusionThis study offers unique methodological approaches by using concurrent mixed methods and collecting complementary data sources to understand firearm safety engagement among Latinos and Hispanics. Findings highlight the need for culturally specific and community-engaged interventions that address social ecological disparities to strengthen safety practices and reduce firearm-related harms.

Background Despite existing road safety regulations, commercial motorcycle riders commonly referred to as "Boda Bodas" in Uganda continue to experience high rates of injuries due to road traffic accidents resulting from unsafe riding behaviours, contributing significantly to morbidity and mortality among both riders and passengers. Safe riding behaviours are less well documented, as well as factors associated with the observance of those behaviours. This study aimed to determine factors associated with safe riding behaviors for both boda-boda riders and their passengers in Kampala Central Division. Methods A cross-sectional survey study design was conducted using a convergent parallel mixed-methods design guided by the PRECEDE model. Quantitative data were collected from 424 riders through structured questionnaires administered by trained research assistants. Binary Logistic regression was used to determine the independent predictors of safe road riding behaviors, and Adjusted Odds ratios (AORs) have been reported. Data were analyzed using descriptive and inferential statistics, with a p-value <0.05 considered statistically significant. Qualitative data were collected simultaneously with quantitative data through in-depth semi-structured interviews with 10 passengers to capture perceptions of rider behaviors and safety practices. Thematic analysis was applied, and results were triangulated to highlight convergences and divergences between quantitative and qualitative findings, providing a comprehensive understanding of safety determinants for both riders and passengers. Results Of the 424 riders (mean rider age was 29.56 {+/-} 5.71), overall, 276 (65.1%) of riders exhibited unsafe riding behaviors. In the bivariate analysis with Logistic regression, predisposing factors (education, marital status, religion, and willingness to obey traffic regulations), and reinforcing factors (family encouragement) were significantly associated with safe riding behaviors. However, in the adjusted model, secondary (AOR=0.50; 95% CI:0.30-0.85) and post-secondary education (AOR=0.57; 95% CI:0.33-0.98), being married (AOR=0.56; 95% CI:0.34-0.91), Christian religion (AOR=2.98; 95% CI:1.63-5.47), willingness to obey traffic regulations (AOR=0.41; 95% CI:0.24-0.70), union advocacy (AOR=1.76; 95% CI:1.03-3.01), and well-maintained roads (AOR=1.65; 95% CI:1.07-2.55) were significant predictors of safe riding behaviors. Qualitative interviews further highlighted barriers to safety, including a lack of helmets, over-speeding, disregard for traffic regulations, and poor road infrastructure. Conclusions Rider and passenger safety is still low, interdependent, and influenced by multiple factors. Integrated interventions focusing on education, stronger families, religious affiliations, union safety advocacy, and stricter enforcement of traffic regulations are vital for enhancing safety for both riders and passengers.

Background. Tobacco smoke exposure, quantified by serum cotinine, is associated with cardiovascular, metabolic, and sleep-related health risks. The relationship between biomarker-verified tobacco smoke exposure and objectively measured, free-living wrist-worn ambient light patterns has not been examined in a nationally representative U.S. adult sample. Methods. We analyzed NHANES 2011-2014 cross-sectional data from 6,937 adults aged >20 years with valid serum cotinine and wrist-worn Physical Activity Monitor (PAM) ambient light data. Seven light outcomes were modeled using survey-weighted linear regression with log2(cotinine+1) as the continuous exposure across four covariate adjustment levels. Benjamini-Hochberg false discovery rate (FDR) correction was applied across the 7 outcomes within each model. Results. In Model 2 (adjusted for age, sex, race/ethnicity, education, poverty-income ratio, BMI, and survey cycle; N = 6,350), higher serum cotinine was associated with significantly higher nighttime light (beta = +0.024, 95% CI: 0.010, 0.038; p-FDR = 0.014) and lower evening light (beta = -0.031, 95% CI: -0.055, -0.008; p-FDR = 0.042). In exploratory behavioral models without alcohol (Model 3a; N = 5,766), both nighttime and evening associations remained FDR-significant. After additional adjustment for alcohol, which substantially reduced the sample due to 37.6% missingness (Model 3b; N = 3,866), the nighttime association attenuated below the FDR threshold, while the evening association remained FDR-significant. Categorical analyses showed progressively higher nighttime light across cotinine groups, and a hypothesis-generating sex interaction was identified (p-interaction = 0.001). Conclusions. Higher serum cotinine concentrations were associated with higher nighttime and lower evening ambient light after sociodemographic adjustment. Attenuation after behavioral adjustment and the cross-sectional design preclude causal inference. Longitudinal studies with formal mediation analyses are needed to clarify the temporal ordering and mechanisms linking tobacco smoke exposure, smoking-related behaviors, and personal light-dark cycle patterns.

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([&le;]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

BackgroundForensic autopsy cohorts can help estimate the burden of clinically unrecognised cancer that is not captured by routine incidence statistics. We report incidental non-breast malignancies identified as secondary findings in the Sisyphus Study, a prospective forensic autopsy cohort originally established to investigate silent breast cancer prevalence. MethodsThis was a descriptive secondary analysis of 291 consecutive medicolegal autopsies performed in Lisbon, Portugal, between July 2016 and December 2019 (74 male and 217 female decedents). Key exclusions relevant to the present analysis were age below 40 years, major breast-region injury, and known or clinically evident cancer. An incidental cancer was defined as a histologically confirmed malignancy identified at autopsy in an individual without a prior clinical cancer diagnosis. ResultsFifteen incidental non-breast malignancies were identified among 291 decedents, yielding an overall prevalence of 5.15%. Prevalence was 6.76% in males (5/74) and 4.61% in females (10/217). Male findings comprised two colorectal adenocarcinomas, one pancreatic metastatic adenocarcinoma, one gastric adenocarcinoma, and one splenic lymphoma. Female findings comprised six colorectal adenocarcinomas, two lung adenocarcinomas, one perforated gastric adenocarcinoma, and one ovarian metastatic adenocarcinoma. Colorectal malignancies accounted for 8 of 15 cases (53.3%). Metastatic disease was documented in at least five cases, and perforation was present in two gastrointestinal tumours. None of the affected individuals had a prior cancer diagnosis during life. ConclusionsThis cohort demonstrates a measurable burden of clinically silent non-breast cancer, including advanced and potentially fatal disease. Forensic autopsy surveillance may complement conventional cancer surveillance by identifying malignancies that remain invisible to clinical registries. The predominance of colorectal cancer in this series is consistent with missed opportunities for earlier detection, although individual screening histories were unavailable.

Objective: This preliminary public health report assessed acute and chronic health burdens, focusing on cardiovascular health, among unsheltered individuals experiencing homelessness. It aims to guide medical referrals, deliver targeted health education, and prioritize services within a community based nonprofit. Methods: A field based needs assessment used a structured questionnaire to evaluate acute and chronic health burdens. Clinical measures included blood pressure (BP), heart rate (HR), pain scores (normalized to 0 to 10), nicotine use, and diabetes prevalence. Of 72 initial responses, 59 BP, 65 HR, and 66 pain scores were usable. BP was classified per ACC/AHA (2017) guidelines [1], including Hypertensive Crisis. Nicotine and diabetes data from a secondary survey yielded 39 and 38 usable responses of 116. Ethical oversight ensured informed consent, participant capacity assessment, and emergency protocols. Data were analyzed descriptively. Results: Participants were predominantly male (N = 53 of 72) with ages ranging from 24 to 70 years (Mean = 42.96; Median = 41; N = 70). The cohort was primarily White/Caucasian (N = 30) and Black/African American (N = 27). Cardiovascular assessments revealed substantial acute risk: 72.88% (N = 43 of 59) of BP readings were classified as Total High Blood Pressure, and 10.17% (N = 6 of 59) met criteria for Hypertensive Crisis or higher, including readings of 210/137 mmHg and 286/127 mmHg. Mean and median HR were both 96 bpm (N = 65). Chronic symptom burden was notable, with a mean pain score of 3.74 and 19.70% (N = 13) reported severe pain (7 to 10). Self-reported comorbidities included current smoking in 15.38% (N = 6 of 39) and a history of diabetes in 13.16% (N = 5 of 38). Conclusion: Findings show a high prevalence of acute cardiovascular risk, particularly severe hypertension, among the unsheltered population. These results highlight the urgent need for improved outreach, targeted cardiovascular and primary care referrals, and follow up screenings. Expanding health education on the effects of uncontrolled diabetes and smoking is recommended to reduce future cardiovascular events.

Diagnosed diabetes disproportionately burdens socioeconomically disadvantaged populations in the United States, particularly Hispanic communities in the Texas-Mexico border region. Few studies have quantified whether geographic border-region status is independently associated with county-level diagnosed diabetes prevalence after accounting for lifestyle and food-environment factors. This cross-sectional ecological study examined 253 Texas counties using CDC PLACES 2025 health estimates and USDA Food Environment Atlas food-access data, including the 2015 county-level low-food-access measure. Border-region counties were defined using the official La Paz Agreement 32-county definition, which includes counties within 100 km of the US-Mexico boundary. Multiple linear regression with HC3 robust standard errors was used to estimate associations between border-region status, low food access, physical inactivity, and diagnosed diabetes prevalence. Variance inflation factor analysis assessed multicollinearity, and Global Moran's I tested spatial autocorrelation in diagnosed diabetes prevalence and OLS residuals. Border-region counties had 33% higher unadjusted mean diagnosed diabetes prevalence than non-border counties (16.1% vs. 12.1%). After adjustment, border-region status remained significantly associated with a 0.625 percentage-point higher diagnosed diabetes prevalence ({beta} = 0.625, 95% CI [0.357, 0.893], p < 0.001). Physical inactivity was the strongest independent predictor ({beta} = 0.404, 95% CI [0.391, 0.417], p < 0.001). The model explained 96.0% of county-level variance (R{superscript 2} = 0.960, N = 253), reflecting ecological associations among modeled county-level health indicators. Global Moran's I confirmed strong spatial clustering of diagnosed diabetes prevalence (I = 0.5734, p = 0.001), with reduced but significant residual spatial autocorrelation after OLS adjustment (I = 0.1696, p = 0.001). These findings suggest that border-region status is associated with elevated diagnosed diabetes prevalence beyond physical inactivity and low food access, supporting targeted public health investment in the Texas-Mexico border region

Background: Cardiovascular outcomes for young adults, particularly Latino individuals, have worsened, in contrast with trends for older persons. Stress and psychosocial resilience resources have been associated with cardiovascular health (CVH) among middle-aged and older adults, but these associations have not been characterized in young adults and Latino populations. We examined the association between chronic stress, resilience resources, and CVH in PR-OUTLOOK, a large community cohort study of 18-29 year olds residing in Puerto Rico. Methods: Participants (n=2,676; 61.9% female) were assessed between September 2020 and March 2024. The American Heart Association Life?s Essential 8 (LE8), derived from surveys, laboratory assays, and physical examinations (range: 0-100, suboptimal CVH = <80) measured CVH. Surveys assessed chronic stress and resilience resources (optimism, religiosity, spirituality, and social support). Multivariable logistic regression, adjusting for age, sex, marital status, subjective social standing, and maternal education, examined associations between chronic stress and CVH, and the potential protective effect of resilience resources (moderation effect). With mediation analysis, using nonparametric bootstrap standard errors with 1,000 replications, we tested whether resilience factors were in the pathway of the stress-CVH association (mediation effect). Results: High chronic stress was associated with suboptimal CVH (OR=1.46; 95% CI: 1.19, 1.80) and resilience factors did not moderate this association (all p > 0.05); however, optimism and social support mediated it, accounting for 26% and 10% of the association, respectively. Conclusions: Chronic stress was associated with suboptimal CVH directly and indirectly through lower resilience resources. Longitudinal studies should better characterize these associations.

BackgroundYoung sexual and gender minorities of color face compound health risks shaped by interlocking systems of racism, cisgenderism, and class inequality. Spatial health research documents that place shapes health, but existing methods cannot specify the mechanisms through which spatial configurations produce different health outcomes for differently positioned people. This gap prevents targeted intervention. ObjectiveTo develop and pilot test the Spatial Intersectionality Health Framework (SIHF), which specifies three mechanisms through which space produces intersectional health inequities: Layered (multiple oppressive systems activating simultaneously), Positional (the same space producing different health pathways by intersectional position), and Conditional (nominally protective spaces carrying hidden costs for specific positions). We also introduce and validate Intersectional Geographically-Explicit Ecological Momentary Assessment (IGEMA) as the methodology operationalizing SIHF across three data levels. MethodsThe GeoSense study enrolled 32 young sexual and gender minorities of color (ages 18-29) in New York City. IGEMA was implemented across three integrated levels: (1) GPS mobility tracking via participants personal smartphones, linked to census tract structural exposure indices across n=19 participants; (2) ecological momentary assessment of intersectional discrimination with multilevel modeling of mood, stress, and sleep outcomes; and (3) map-guided qualitative interviews with SIHF mechanism coding and intercoder reliability assessment across 92 coded records from 18 participants. This study was conducted as the pilot for NIH R01HL169503. ResultsAll three SIHF mechanisms were empirically detectable. A compound structural gendered racism index outperformed every single-axis alternative in predicting daily mood (b=-0.048, p=.001) and stress (b=0.121, p<.001). The Positional mechanism accounted for 71% of coded harm experiences. Intercoder reliability for mechanism assignment reached kappa=0.824 at Stage 2 reconciliation. Daily intersectional discrimination predicted greater sleep disturbance (b=1.308, p=.004). ConclusionsSIHF and IGEMA together provide an empirically testable framework for specifying how space produces intersectional health inequities. Mechanism specification, not spatial location alone, is the condition for designing research and intervention that reaches the source of harm for multiply marginalized populations.