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.

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 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.

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

Objective: Readmissions to the PICU are associated with increased morbidity and mortality. A prediction model that can identify children at risk of readmission at the time of transfer can allow providers to intervene and potentially improve patient outcomes. The objective of this study was to derive and validate machine learning models to predict PICU readmission at the time of transfer. Design: Retrospective observational cohort study Setting: Three quaternary care PICUs in the city of Chicago Patients: All children admitted to the PICU between 2012 and 2019. Measurements: The primary outcome was unplanned readmission to the PICU within 48 hours of transfer to the inpatient ward. Predictor variables included vital signs, patient characteristics, and laboratory results. We developed and externally validated four models to predict PICU readmission: logistic regression, elastic net, random forest, and XGBoost. Main Results: This study included 35,601 patients, with readmission rates ranging from 2.2-3.7% by site. The performance of models during internal validation was consistent at the three sites, with the area under the receiver operating characteristic (AUC) values between 0.70 and 0.73 and no difference across the four models. Model performance decreased significantly during external validation (AUCs of 0.60-0.69). The variables most important to the prediction differed at each site. Conclusion: Machine learning models for predicting readmissions to the PICU have limited generalizability. Locally derived models demonstrated modest performance in our study and could potentially inform provider decision-making if prospectively validated. Externally developed models are unlikely to perform well at predicting PICU readmissions.

The Asian population in Los Angeles is among the largest and most heterogeneous in the U.S. This is true culturally and health-wise. Older Asians have differing risks for cardiovascular and cardiometabolic disease, depending on their ethnicity, health literacy, and lifestyle choices. This pilot examines several of these factors in a small but diverse group of older Asian adults who attended community health events from 2024-2025. Self-reported and biometric data were collected at five such events hosted by the Asian Pacific Health Corps at UCLA. The pilot generated health literacy and lifestyle (HLL) scores for all participating attendees and explored how they relate to their socio-demographics, healthcare habits, and predictions of their own health data. Overall, there were significantly more females than males with higher HLL scores (p = 0.027). College education (p = 0.028) and "normal" ranges for biometric data (e.g., blood pressure, BMI, blood glucose, cholesterol) were related to higher median HLL scores. With a few exceptions, fewer than 50% accurately predicted their biometric numbers regardless of HLL scores, suggesting a disconnect between perception and reality, and that better provider-patient communication may help foster greater patient understanding about their chronic conditions. These HLL score distributions indicate that educational attainment, better awareness of one's health, and high health literacy are individual factors that may influence older Asians' understanding and potential approach to managing their health conditions.

Background: Epic Cosmos is a relatively new centralized electronic health record dataset with high potential utility in perinatal epidemiologic research. Objectives: The study objectives were to develop replicable steps to create longitudinal, linked maternal-infant cohorts in Cosmos, assess completeness of key variables, evaluate potential selection bias with restrictions for longitudinal healthcare encounters, and provide an example epidemiologic analysis. Methods: We created maternal-infant cohorts by starting with live births during 2023-2024 recorded in the BirthFact data table and joining with additional data tables as needed. We selected and created variables for perinatal characteristics, common comorbidities, and routinely measured vital signs and laboratory values, and assessed variable completeness. We sequentially restricted the birth cohort for maternal-infant linkage and longitudinal healthcare from first-trimester prenatal care encounter through infant follow-up care within 12 weeks post-discharge from birth hospitalization. Finally, we conducted an example analysis of the association between high systolic blood pressure in the first trimester ([&ge;]140 mm Hg) and later onset of preeclampsia among those with chronic hypertension. Results: The total linked birth cohort included 2,624,186 pregnancies. Completeness was >90% for most variables assessed but was 77% for racial and ethnic group and 76% for body mass index at delivery. Characteristics of the cohort were similar to those reported for the entire United States birth population based on birth certificate data, including similar regional and racial-ethnic composition. Longitudinal cohort restriction requiring linked records from first trimester prenatal care through infant follow-up care reduced the cohort size to 509,148 pregnancies. However, restriction had minimal effects on cohort characteristics. In the example analysis, high systolic blood pressure was associated with increased risk of preeclampsia among those with chronic hypertension (aRR: 1.26; 95% CI: 1.22, 1.30). Conclusions: This study provides a rigorous and reproducible approach to creating longitudinal, linked maternal-infant cohorts in Epic Cosmos and the analytical findings suggest high data quality and representativeness.

While SARS-CoV-2 and influenza continue to place a significant burden on population health, within-household differences in decisions towards vaccination and seeking care across these two pathogens, and across sociodemographic groups, remain largely unexplored. By conducting a household-level survey in Illinois, we found that many individuals made inconsistent decisions about vaccination: among all adults, 29% were vaccinated for only one of COVID-19 or influenza, and among those with children in the home, 39% lived with a child whose influenza or COVID-19 vaccination status differed from their own. A higher proportion of adults were vaccinated against COVID-19 compared to influenza, while the opposite was true for those younger than 18 years old. These differences hold even when accounting for disparities in coverage by age, race/ethnicity, political affiliation, and socioeconomic status. While vaccinated individuals consistently reported wanting to protect themselves or others, those who declined vaccination reported highly heterogeneous reasons ranging from resource constraints to distrust or misconceptions about vaccination. These differences are even more pronounced for COVID-19, with larger partisan gaps and higher refusal driven by safety concerns, lack of trust, or religious reasons than those who decide not to get the influenza vaccine. In contrast to vaccination, the decision to seek medical care when sick showed opposite sociodemographic trends, that are likely attributable to illness severity. Our findings highlight that closing gaps in COVID-19 and influenza vaccination coverage will require an integrative strategy that accounts for diverse motivations, fears, and barriers to access, while addressing social inequalities common to both diseases.

This cross-sectional study aimed to examine the prevalence of alcohol use and its sociodemographic correlates among adults with cardiovascular disease (CVD). We analyzed data from two large US cohorts: the All of Us Research Program (2017-2023) and the National Health and Nutrition Examination Survey (NHANES, 1999-2016). Both CVD diagnosis and past-year alcohol consumption were self-reported. Risky drinking was defined as exceeding moderate drinking or binge drinking (All of Us), or moderate/heavy drinking (NHANES). Multivariable logistic regression was used to exam associations with sociodemographic and lifestyle factors. Among 32,788 current drinkers with CVD in the All of Us cohort, 15% exceeded moderate drinking thresholds and 26% reported binge drinking. Older age, female sex, and higher socioeconomic status were inversely associated with risky drinking, while smoking was positively associated. In NHANES, moderate drinking rose from 47.3% to 57.2% and heavy drinking from 6.7% to 7.2%. Moderate/heavy drinking was positively associated with age <65 but inversely with age [&ge;]65. Higher education and income were linked to moderate drinking, while current smoking was strongly associated with heavy drinking. These results highlight the need to integrate holistic screening for alcohol use, tobacco use, and social context into routine cardiovascular care.

Background: Black and Latino adults in the United States experience a disproportionate burden of cardiometabolic conditions due to interacting behavioral, social, and structural drivers of health. Less is known about the impact of integrating digital health tools into CHW-led interventions to improve cardiometabolic health. This trial evaluates a multilevel community-digital health promotion model delivered by CHWs to improve service utilization, health behaviors and cardiometabolic health among Black and Latino adults. Methods: This community-partnered trial uses a randomized delayed-control group with a phased recruitment design. Four cohorts (N = 664) are enrolled through three community-based organizations (CBOs). Eligible participants are 18 years who self-identify as Black or Latino, and have prediabetes/diabetes, hypertension, or overweight/obesity. Participants are allocated to either (1) a multilevel intervention consisting of CBO and CHW capacity building combined with individualized CHW-led lifestyle coaching and group activities supported by digital tools, or (2) a delayed control group receiving SMS-only cardiometabolic health education. Data collected at baseline, 6, 9, and 18 months include surveys and health metrics. Qualitative data are collected from participants and community partners to assess intervention acceptability, implementation facilitators and barriers, and sustainability. Results: The primary outcome is health service utilization at 6 and 9 months. Secondary outcomes include health behaviors, health metrics, and social determinants of health. Sustainability of health behaviors and health metrics is assessed at 18 months. Conclusions: Findings will provide evidence to inform scalable, sustainable community-digital health models for CHW-supported cardiometabolic health interventions in underserved communities.

Objective: To verify the association between perceived social & emotional support and self-reported food insecurity in the United States Design: Cross-sectional secondary data analysis Setting: Behavioral Risk Factor Surveillance System (BRFSS) data from 2024, collected via a nationwide telephone survey. Food insecurity was defined as responding always, usually, or sometimes to "During the past 12 months how often did the food that you bought not last, and you didn't have money to buy more?" Social support was measured using a BRFSS item assessing the frequency with which respondents received the social and emotional support they needed. Adjusted logistic regression models were used to assess the relationship between these variables while controlling for a wide variety of demographic, socioeconomic, and health status factors. Participants: Adults (n = 190,577) aged 18-80 years old (72.3% non-Hispanic White) Results: Individuals who reported only "sometimes" receiving the social and emotional support they need were more likely to report food insecurity as compared to those who "always" receive such support (aOR = 1.75; 95% CI 1.56, 1.96). Conclusions: These findings indicate that decreased social support may put individuals at higher risk of food insecurity. Future work should seek to understand the mechanisms of this association to inform targeted policy and other interventional programs.

Background: An increasing demand for organic food has risen due to perceived health benefits. Current evidence for the health effects of organic food is limited. Objective: To evaluate the association between organic food purchase as a proxy for organic food consumption and hypertension in a nationally representative population of the US. Methods: This was a cross-sectional study that included 9173 participants aged >= 18 and had available data of both organic food purchase and hypertension from the National Health and Nutrition Examination Survey 2007-2010. Organic food purchase and frequency were obtained from survey questionnaires. Hypertension was defined as having either a systolic BP >= 130 mm Hg/ diastolic BP >= 80 mm Hg, currently taking antihypertensive medication, or self-reported diagnosis of hypertension. We used multivariable logistic regression with sample weights and adjustment of potential confounders to assess associations (adjusted odds ratio [aOR] and 95% confidence intervals [CI]) between organic food purchase and hypertension status. Results: Findings suggest an 11% decrease in odds of hypertension (aOR = 0.89, 95% CI: 0.75-1.06) among organic food purchasers compared to non-purchasers. Lower odds of hypertension were observed across all categories of organic food purchasing frequency, with 13% lower among rarely purchasing organic food (aOR = 0.87, 95% CI: 0.67-1.14), 9% lower (aOR = 0.91, 95% CI: 0.71-1.16) among sometimes purchasing organic food, and 17% lower (aOR = 0.83, 95% CI: 0.55-1.27) among always or mostly purchasing organic food, as compared to those who never purchased organic food. Conclusion: Our findings suggest that organic food purchase, a proxy for organic food consumption, may be associated with lower odds of hypertension. These findings may reflect either the true benefits of organic food consumption, including lower pesticide amounts and higher nutrient content, or the health-seeking behaviors among health-conscious, healthy, and highly educated individuals.

Background: Comprehensive assessment of hypertension-mediated organ damage (HMOD) across multiple organ systems remains limited in sub-Saharan Africa. We aimed to determine the prevalence and predictors of multidomain HMOD in a geographically diverse Ghanaian adult population. Methods: This secondary analysis of the Ghana Heart Study included 1,106 adults from four regions. Multidomain HMOD was defined as a pre-specified 9-domain TOD composite score ?2, based on the ESH/ESC 2018 guidelines framework. Logistic regression and ROC analysis were used to identify predictors and compare discriminative performance. Results: Mean age was 46.9 (17.2) years and 58% were female. Multidomain HMOD prevalence was 21.2% (235/1,106) and increased steeply with age: 8.6% (<45 years), 20.6% (45?59 years), and 44.4% (?60 years). Hypertension prevalence was 73% in the HMOD group versus 28% in those without HMOD (p < 0.001). The strongest independent associations were peripheral artery disease (OR 41.2), valvular burden (OR 14.4), and ECG-LVH (OR 9.0). baPWV showed superior discriminative performance (AUC 0.827, 95% CI 0.794?0.860) compared with the ASCVD Pooled Cohort Equations (AUC 0.466; ?AUC +0.351, DeLong test p < 0.001). Conclusions: One in five Ghanaian adults has hypertension-mediated organ damage in ?2 organ systems. baPWV is the strongest predictor and substantially improves risk stratification beyond conventional scores. These findings support the use of baPWV to guide hypertension management and HMOD assessment in West Africa.

Importance: Hereditary breast and ovarian cancer (HBOC) variant carriers benefit from risk-reducing interventions, but only if identified. The extent to which carriers are clinically recognized, and whether recognition is equitable across diverse populations, is poorly characterized in a single large U.S. cohort. Objective: To estimate P/LP HBOC carrier prevalence across genetic ancestry groups, quantify documented clinical genetic testing among carriers, and evaluate ancestry and socioeconomic disparities in testing. Design, Setting, and Participants: Cross-sectional analysis of the All of Us Research Program Controlled Tier (Curated Data Repository v8/C2024Q3R9), comprising participants with short-read whole genome sequencing and linked electronic health record (EHR) and survey data. Carriers were ascertained from research genomic data independent of clinical testing. Exposures: Genetically inferred ancestry (African [AFR], Admixed American [AMR], East Asian [EAS], European [EUR], Middle Eastern [MID], South Asian [SAS]); self-reported household income and educational attainment. Main Outcomes and Measures: (1) Carrier prevalence with Wilson 95% CIs; (2) documented clinical genetic testing (procedure codes) among carriers; (3) adjusted odds of documented testing among women, by ancestry, before and after socioeconomic adjustment, using multivariable logistic regression. Results: Among 414,830 participants, P/LP HBOC carrier prevalence was 1.42% (95% CI, 1.38-1.45) overall and similar across ancestry groups (AFR 1.24%, AMR 1.32%, EAS 1.19%, EUR 1.52%, MID 1.68%, SAS 1.33%; overlapping CIs). Among 250,071 women in the testing analysis, documented clinical genetic testing was rare: only 74 of 5,878 carriers overall (1.3%) and 59 of 3,572 European-ancestry carriers (1.7%) had a documented test, with counts below reportable thresholds in all other ancestry groups. African-ancestry women had lower adjusted odds of documented testing than European-ancestry women (Model 1 adjusted odds ratio [aOR], 0.32; 95% CI, 0.27-0.39), an association that attenuated but persisted after adjustment for income and education (Model 2 aOR, 0.48; 95% CI, 0.40-0.58; P < 0.001); Admixed American women also had reduced adjusted odds (aOR, 0.71; 95% CI, 0.61-0.84). Lower income and lower education were independently and dose-dependently associated with lower testing odds (income <$25,000 aOR, 0.46; high-school education aOR, 0.54). Conclusions and Relevance: High-risk HBOC variant carriers are present across all ancestry groups at similar frequencies, yet documented clinical genetic testing was disparate in the different ancestry groups. African-ancestry women experience a testing gap that is not fully explained by socioeconomic position, implicating structural barriers in access and referral. Population-level strategies that decouple carrier identification from current referral pathways may be required to close this gap.

BackgroundPredictors of arterial health impairment from childhood to adolescence remain largely unknown. We investigated associations of childhood cardiometabolic risk factors with several measures of arterial health in adolescence. MethodsAltogether, 222 children were examined at age 7-9 years and eight years later at age 15-17 years. Body fat percentage (BF%), glucose, insulin, lipids, blood pressure (BP), and inflammation biomarkers were measured and homeostatic model assessment for insulin resistance (HOMA-IR), a metabolic syndrome score (MetSscore), and an inflammation score were calculated at baseline. Pulse wave velocity (PWV) and cardio-ankle vascular index (CAVI) were assessed using impedance cardiography and carotid intima-media thickness (cIMT), carotid distensibility (cDIST), Youngs elastic modulus (YEM), and stiffness index (SI) using ultrasonography. Associations of childhood cardiometabolic risk factors with measures of arterial health were analyzed using linear regression models adjusted for childhood age and sex. ResultsBF% was positively associated with PWV (standardized regression coefficient {beta}=0.207, p=0.008), CAVI ({beta}=0.171, p=0.031), cIMT ({beta}=0.146, p=0.034), and YEM ({beta}=0.164, p=0.016). HOMA-IR was positively associated with PWV ({beta}=0.242, p=0.001) and CAVI ({beta}=0.216, p=0.004) and inversely with cDIST ({beta}=-0.162, p=0.015). MetSscore was positively associated with PWV ({beta}=0.266, p<0.001), CAVI ({beta}=0.219, p=0.004), and YEM ({beta}=0.141, p=0.032) and inversely with cDIST ({beta}=-0.140, p=0.035). SBP was positively associated with PWV ({beta}=0.257, p<0.001) and YEM ({beta}=0.156, p=0.018) and inversely with cDIST ({beta}=0.169, p=0.012). ConclusionIncreased adiposity, insulin resistance, elevated SBP, and cardiometabolic risk factor clustering in childhood association of arterial stiffness and reduced arterial distensibility in adolescence, emphasizing prevention of cardiovascular diseases since childhood.

Abstract Background. Area-level cancer disparities are routinely estimated from public county data in which rates based on small counts (fewer than 16 cases or deaths) are suppressed. Analysts typically drop suppressed counties (complete-case analysis). Because suppression depends on case counts tied to population size and demographic composition, this missingness may be informative, but its effect on the disparity estimate has not, to our knowledge, been quantified. Methods. In a cross-sectional ecological study of 3,143 U.S. counties (analytic sample 3,018 with computable exposure) using one frozen public release of NCI State Cancer Profiles incidence and mortality data and ACS 2018-2022 5-year data, we estimated the most- versus least-deprived ICE(race+income) quintile rate ratio (RR) and rate difference for female breast, stomach, and cervix cancers under four suppression-handling methods: complete-case, available-case, bounding, and model-based small-area estimation. We characterized which counties were erased, and, following the ADEMP framework, ran a Monte Carlo simulation (1,000 replicates per cell; Monte Carlo standard error of bias approximately 0.0025) calibrated to the release to measure bias against a known truth. Analyses were pre-registered. Results. The suppressed fraction rose with rarity: 7.4% of counties for breast, 61.3% for stomach, and 75.7% for cervix incidence. Suppression was concentrated in the most-deprived quintile (cervix, 81.8% suppressed vs 63.8% least-deprived) and overwhelmingly removed rural rather than minority residents (cervix: 81% of the rural but 9% of the minority population erased). For breast (little suppression) the RR was 0.87 (95% CI 0.85-0.89) and identical across methods; for cervix incidence the complete-case RR (1.56) exceeded the model-based estimate (1.50), and for cervix mortality (91% suppressed) complete-case (1.86) exceeded model-based (1.56) by 16% with a wide bounding interval (1.88-2.62). In calibrated simulation, population-weighted complete-case bias was small (less than 2%) at the observed deprivation-county-size correlation and grew with rarity, threshold, and unweighted aggregation; its direction was conditional, becoming positive (over-estimation) as deprived counties became smaller. Conclusions. Complete-case handling of suppressed counties over-estimates rare-cancer area disparities relative to methods that retain them, while silently erasing most of the rural and most-deprived communities the estimate is meant to represent. The effect is negligible for common cancers and grows with rarity. Public-data disparity analyses should report the suppressed fraction and use bounded or model-based estimates by default. Keywords: cancer disparities; small-count suppression; Index of Concentration at the Extremes; informative missingness; small-area estimation; rural health.

Background: Nitrogen dioxide (NO2) is a surrogate for traffic and industrial air pollution associated with adverse respiratory outcomes. Whether elevated NO2 and temperature jointly influence adult-onset asthma (AOA) risk is unclear, especially among subgroups with varying lifestyle and exposure profiles. We investigated further in the prospective All of Us research program. Methods: Among 596,926 U.S. participants who consented to electronic health record release, annual average NO2 concentrations from satellite data were linked to residential locations for 376,535 individuals. We used multivariable Cox regression to estimate associations between NO2, temperature, and incident AOA, adjusting for co-pollutants and potential confounders. We analyzed 4-category cross-classification variables between NO2 (high>75th percentile vs. low<=75th percentile) and maximum or average temperature (high>median vs. low<=median). We also stratified by sex, age, income, and smoking status. Additive interactions were estimated using Relative Excess Risk due to Interaction, Attributable Proportion, and Synergy Index. Results: We identified 10,413 incident AOA cases over an average 4-year follow-up. Participants with the highest categories of NO2 and temperature exposure had significantly higher risk compared to those with the lowest (HRHigh NO2 x High Max. Temp.=1.37, 95%CI:1.26-1.49; HRHigh NO2 x High Average Temp.=1.49, 95%CI:1.38-1.61). The joint association of high NO2 and high maximum temperature was more pronounced among ever-smokers (HR=1.59, 95%CI:1.40-1.81) than never-smokers (HR=1.26, 95%CI:1.13-1.41). Interaction analyses supported super-additive interactions of high NO2 and high average temperature on AOA risk, particularly among ever smokers, lower-income participants, and younger adults. Conclusion: Our findings highlight the respiratory health threat of long-term joint exposure to elevated NO2 and average temperature, particularly among vulnerable subgroups.

This report presents findings from a baseline cross sectional survey of autistic adults and adults with intellectual and developmental disabilities (IDD) connected to Our Stomping Ground (OSG), a nonprofit organization in northern Virginia committed to supported independent living. The survey was administered in 2022 and 2023 as the first wave of a planned longitudinal study, with the primary goal of establishing a comparable starting point between two groups: adults who were living, or preparing to live, independently in an OSG apartment building, and adults with disabilities who were continuing to live at home with family. A total of 76 adults completed the survey out of 98 potential participants. The two groups were well-matched at baseline across a wide range of characteristics, which is exactly what a sound longitudinal design requires. This comparability means that when follow up data are collected, any observed differences between the groups can be more confidently attributed to the experience of independent living rather than to pre-existing differences. These findings provide the empirical foundation for the longitudinal phase of this study and offer a meaningful snapshot of the health, well-being, and support needs of autistic adults and adults with IDD at a pivotal life stage.

Background: Non-communicable diseases (NCDs) account for approximately 75% of global deaths, with 79% occurring in low- and middle-income countries. Tobacco use remains a major modifiable risk factor, contributing to more than 8 million deaths annually. In Zambia, evidence on tobacco use among individuals with hypertension, diabetes mellitus, and cardiovascular disease remains limited. This study assessed the prevalence and determinants of tobacco use among adults with NCDs in Zambia. Methods: We conducted a secondary analysis of the 2017 Zambia STEPS survey. The analytic sample included 716 adults aged 18-69 years with self-reported hypertension, diabetes, and/or cardiovascular disease. Tobacco use was defined as current smoking or smokeless tobacco use. Multivariable logistic regression was used to estimate adjusted odds ratios (AORs), accounting for the complex survey design. Results: Among 716 participants, 65.5% had hypertension, 7.7% diabetes, and 26.8% cardiovascular disease; 89.5% had multimorbidity. The overall prevalence of tobacco use was 12.2%. Prevalence was 12.2% among those with hypertension, 5.5% among those with diabetes, and 14.1% among those with cardiovascular disease. Tobacco use was significantly higher among males. Female sex was associated with lower odds of tobacco use (AOR = 0.16, 95% CI: 0.05-0.54, p = 0.004). Secondary education (AOR = 0.15, 95% CI: 0.03-0.66) and higher education (AOR = 0.04, 95% CI: 0.01-0.44) were protective. Alcohol consumption increased the odds of tobacco use (AOR = 5.23, 95% CI: 1.17-23.28). Conclusion: Tobacco use remains common among adults with NCDs in Zambia. Integration of tobacco cessation interventions into routine NCD care is urgently needed.