Browse Articles

Abstract TH842: Machine Learning–Based Analysis of Behavioral and Social Determinants of Cardiovascular Mortality in Adults With Diabetes

Introduction: Cardiovascular (CV) mortality remains high among adults with diabetes. The impact of behavioral and social factors contributing to this heightened risk is not well understood, and the nonlinear patterns of these determinants can be challenging to capture using traditional linear models. Hypothesis: We hypothesized that explainable machine learning framework based on a tree-based model with Shapley Additive Explanations (SHAP) can capture nonlinear associations between behavioral and social determinants of CV mortality among individuals with diabetes. Methods: Adults with diabetes were identified from the National Health and Nutrition Examination Survey 2007–2018 and linked to the National Death Index. CV mortality was modeled with a tree-based gradient boosting classifier. Feature contributions were assessed using SHAP. SHAP-derived odds ratios (ORs) were obtained by exponentiating differences in mean SHAP values between categories or per-unit increases in continuous variables. Confidence intervals (CIs) were estimated from 1,000 bootstrap samples. Nonlinear associations in continuous variables were modeled using piecewise regression of SHAP values. Results: Among 5,734 adults with diabetes, 516 CV deaths were identified. Of the top 20 contributors in the model, 8 were behavioral or social determinants, accounting for 38% of the model’s explainability. Being U.S.-born was associated with higher odds of CV mortality (OR 1.33, 95% CI 1.33–1.34), as were short (<6 h) and long (>9 h) sleep durations compared with 7–9 h (OR 1.26 and 1.19, respectively). In contrast, recent weight-loss attempts were associated with lower odds (OR 0.68, 95% CI 0.68–0.69). Compared with non-Hispanic Whites, odds were lower among Hispanics (OR 0.81, 95% CI 0.81–0.81). Higher education (college graduate vs less than high school) was associated with reduced odds (OR 0.71, 95% CI 0.71–0.72), as was higher income measured by the income-to-poverty ratio (PIR ≥5 vs <1; OR 0.77, 95% CI 0.77–0.78). Physical activity showed a nonlinear relationship, lowering CV mortality by 0.9% per 10 minutes up to approximately 215 minutes per week, after which further activity yielded minimal benefit. Conclusions: Behavioral and social determinants accounted for a substantial portion of CV mortality risk in adults with diabetes. SHAP-driven interpretability revealed nonlinear relationships, emphasizing modifiable behaviors and social context as key contributors to mortality heterogeneity.

Abstract TU140: Predictors of Smokeless Tobacco and Paan Initiation During the School-to-Work Transition Among Indian Adolescents: A Prospective Cohort Study

Introduction: Tobacco initiation during adolescence remains a critical contributor to India’s cardiovascular and oral-disease burden. With early initiation often occurring between 12–16 years, understanding determinants of first use across the school-to-work transition is essential for prevention. This prospective study evaluated sociodemographic, behavioral, and psychosocial predictors of smokeless tobacco and paan initiation among adolescents in India. Methods: A cohort of 2,412 students (mean age 16.2 ± 1.1 years; 53% female) from 12 secondary schools in western India, a was followed prospectively for 18 months as they transitioned to employment or higher education. Baseline variables included peer and parental use, perceived harm, marketing exposure, stress, and impulsivity. New initiation of smokeless tobacco or paan was recorded at 6-, 12-, and 18-month intervals, with salivary cotinine validation in a 10% random subsample. Cox proportional hazards models identified independent predictors (p < 0.05). Results: At 18 months, 17.4% (95% CI 15.6–19.2) reported new use of tobacco or paan; rural participants showed significantly higher initiation (21.3% vs 13.1% urban, p < 0.01). The median age at first use was 14.6 years (IQR 13–16). Males were nearly 2.5 times more likely to initiate than females (HR 2.5, 95% CI 1.8–3.3). Independent predictors included peer use (HR 2.7, 1.9–3.6), exposure to tobacco/paan marketing (HR 1.9, 1.4–2.5), low perceived harm (HR 1.6, 1.2–2.1), and parental use (HR 1.5, 1.1–2.0). Rural residence independently predicted initiation (HR 1.8, 1.3–2.4) after adjustment for socioeconomic status. High school connectedness (HR 0.7, 0.5–0.9) and accurate awareness of oral health risks (HR 0.8, 0.6–1.0) were protective. Population-attributable fraction estimates suggested that eliminating peer and marketing exposure could prevent approximately 42% of new initiations. Conclusions: Adolescent initiation of smokeless tobacco and paan in India predominantly occurs between 12–16 years, with highest risk among rural males influenced by peer behavior, family modeling, and aggressive marketing. Strengthening early adolescent interventions, enforcing point-of-sale restrictions in rural areas, and incorporating peer-led and digital harm-perception modules into school-exit programs could substantially reduce future tobacco uptake and its cardiometabolic consequences.

Abstract TU180: Pleiotropic and eQTL Analysis of Lipid Traits Identifies Novel Genetic Signals in African-Ancestry Populations

Background: Dyslipidemia is a major, modifiable determinant of cardiovascular disease (CVD). However, the genetic architecture of lipid regulation remains incompletely understood, particularly in African-ancestry populations that experience a disproportionate burden of CVD but are underrepresented in genomic studies. Methods: We conducted meta-analyses of genome-wide association summary statistics for HDL cholesterol, LDL cholesterol, triglycerides, and total cholesterol from the ACCME (n~8,800), AWI-Gen (11,700), and GRC-Uganda (n~6408) cohorts using METAL. Pleiotropic variants were identified with PLEIO, and genome-wide significant loci were assessed for tissue-specific regulatory activity using eQTpLot based on multi-tissue eQTL datasets. Results: We identified 90 genome-wide significant pleiotropic single nucleotide polymorphisms (SNPs) across eight chromosomes. The strongest associations occurred in the APOE, NECTIN2, TOMM40, and APOC1 region on chromosome 19, where the lead variant showed significant multi-trait effects across total cholesterol, LDL, and HDL. Additional genome-wide significant pleiotropic variants were detected near NECTIN2 (P = 8.09 x 10^-133), CETP (P = 9.44 x 10^-90), LIPC (P = 9.42 x 10^-51), PSRC1 (P = 6.99 x 10^-32), and LPL (P = 5.79 x 10^-22). Expression quantitative trait locus (eQTL) analyses demonstrated that these pleiotropic SNPs affected gene expression in lipid-related tissues, including BCAM and APOE in liver and adipose tissue and CETP in liver and arterial wall. These results highlight shared transcriptional regulation across multiple lipid traits within biologically established loci. Conclusions: These findings reveal shared biological pathways underlying dyslipidemia and provide functional evidence linking genetic variation to gene expression in diverse populations. By characterizing ancestry-specific pleiotropic architecture, this work establishes a foundation for developing targeted therapeutic strategies and more accurate, ancestry-informed genomic tools for cardiovascular risk assessment and prevention.

Why it’s hard to guess the high note

Study of nasal heating function based on 40 cases of nasal cavity model

Abstract 58: Clinical and Biomarker Subtypes of Preeclampsia and Future Cardiovascular Health

Background: Preeclampsia is a leading cause of maternal-fetal morbidity and strongly linked to future cardiovascular disease. Prediction and prevention remain limited, in part due to preeclampsia heterogeneity and poorly defined biological subtypes. Better delineation of preeclampsia subtypes could inform strategies to reduce preeclampsia and its short- and long-term morbidity. We aimed to identify novel clinical and biomarker defined subtypes of preeclampsia using unsupervised machine learning and evaluate their associations with postpartum cardiovascular health. Methods: Participants with preeclampsia, defined per ACOG criteria, were identified from the multicenter, prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (NuMoM2b)-Heart Health Study. Participants with pre-pregnancy hypertension were excluded. Clinical and demographic data, placental and cardiovascular biomarkers, and proteomic profiles were analyzed. Two-stage feature selection (Boruta SHAP and volcano filtering) identified informative proteomic markers, integrated with clinical variables. UMAP dimensionality reduction and Gaussian Mixture Model clustering (optimized by silhouette scores) identified subtypes, followed by refinement to maximize between-cluster variance. The resulting subgroups represented phenotypically and biologically distinct preeclampsia endotypes. Postpartum incident hypertension (>=130/80 mmHg or medication use at 2-7 years) was compared across subtypes using modified Poisson regression. Results: Among 298 women with preeclampsia, three subtypes emerged (Figure 1): (1) cardiometabolic – higher body mass index, blood pressure, and maternal inflammatory markers; (2) placentally-mediated – elevated placental analytes and normal maternal cardiometabolic features; and (3) mixed – intermediate cardiometabolic and placental analyte profiles. All subtypes showed high risk of incident hypertension versus women without adverse pregnancy outcomes (n=755). Risk was highest in the cardiometabolic subtype (RR 3.09 [95%CI 2.39-3.97]), followed by placentally mediated (RR 1.97 [1.43-2.73]) and mixed (RR 1.62 [0.98-2.67]) (global Wald test p<0.001; Figure 2). Conclusion: Preeclampsia comprises biologically distinct subtypes with heightened but differential postpartum cardiovascular risk. Recognition of this heterogeneity provides new insights into pathophysiology and may advance precision prevention of preeclampsia and its long-term cardiovascular sequelae.

Abstract TU166: Food Insecurity, Food Assistance, and Cardiovascular Disease Risk Factors Among U.S. Adults

Background: Food insecurity (FI) is defined as limited or uncertain access to adequate food and remains a critical public health concern in the US. National rates of FI have continued to rise, coinciding with persistent disparities in cardiovascular disease (CVD) risk. While participation in food assistance programs aims to alleviate FI, its interaction with FI on CVD risk factors remains unclear. This study examined the association between FI and clustering of CVD risk factors among US adults and its potential moderation by participation in the Supplemental Nutrition Assistance Program (SNAP). Methods: We analyzed 143,820 adults aged ≥18 years from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) dataset. FI was ascertained by affirming the “food ran out in the past 12 months due to lack of money” question. Six CVD risk factors, namely BMI >25 kg/m 2 , self-reported diabetes diagnosis, hypertension, smoking, lack of physical activity, and elevated cholesterol, were examined. Each factor was scored as 1 (risk present) and summed to a risk factor score (range 0-6). Weighted multivariable linear regression models were applied to estimate associations between FI and the CVD risk factor score, adjusting for sociodemographic and alcohol use. Results: Approximately 11.4% of participants reported FI and 9.2% participated in SNAP. The percentages of participants with 0, 1, 2, and 3 or more risk factors were, respectively, 9.6%, 24.4%, 26.8%, and 39.1%. FI was significantly associated with higher CVD risk factor score. Participants with FI had a 0.49 and 0.32 higher CVD risk factor score than those without FI, in unadjusted and adjusted models (standard error 0.0001, 0.0001, all p < 0.0001), respectively. Participation in SNAP did not moderate the association between FI and CVD risk factor score (p=0.27). Conclusions: FI was associated with greater clustering of CVD risk factors among U.S. adults, regardless of SNAP participation. The findings highlight the need for integrated public health strategies addressing not only food access but also dietary patterns, behavioral risk modification, and chronic disease prevention.

Abstract TH847: Explainable Machine Learning–Identified Protective Social, Behavioral, and Clinical Factors for Cardiovascular Diseases

Background: Cardiovascular diseases (CVDs) remain the leading cause of death globally, yet traditional risk tools underweight protective social and behavioral contexts that shape cardiovascular resilience. Explainable machine learning (ML) offers a path to quantify such protective factors while maintaining transparency for population health deployment. Hypothesis: We hypothesize that explainable ML applied to a nationally representative survey can accurately distinguish adults without CVDs and identify a reproducible profile of protective social, behavioral, and clinical factors associated with lower disease prevalence. Methods: We analyzed adults from the 2021 Behavioral Risk Factor Surveillance System (n=116,608); 11 candidate predictors spanned demographics/socioeconomics (age, sex, race/ethnicity, income, insurance), behaviors (smoking, alcohol use, fruit/vegetable intake), and clinical/mental health (diabetes, depressive disorder). Baselines included logistic regression, random forests, support vector machines, and XGBoost that underwent Optuna hyperparameter tuning with nested cross-validation. Discrimination (area under the receiver-operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC)), accuracy, and predictive values, were reported; interpretability used SHAP to quantify direction and magnitude of feature effects. Results: CVD prevalence rose with age (1.3% at 18–24 years to 24.6% at ≥65 years) and was higher in men than women (17.2% vs 12.2%); prevalence was greater in Black non-Hispanic than Hispanic adults (16.7% vs 9.6%) and in lower- versus higher-income groups (23.6% for <$15,000 vs 7.5% for ≥$200,000). On held-out testing, the best XGBoost model achieved AUROC of 0.76 and AUPRC of 0.95, with high negative predictive value (90.49%) and substantially low positive predictive value (32.36%); cross-validation confirmed robustness (mean AUROC=0.76, high AUPRC=0.95) and competitive overall accuracy of 76.98±0.45 across five folds. SHAP analyses consistently highlighted protective profiles characterized by younger age, higher income, health insurance coverage, and absence of diabetes and depressive disorder; dietary variables contributed modestly. Conclusions: Our explainable ML model identified protective profiles against CVDs, while achieving reliable performance. These results support prevention strategies that improve access to care, reduce metabolic risk, and motivate prospective validation.

A bearing fault diagnosis method for complex system based on improved extended belief rule base

Abstract TH818: Associations of Glycemic Control and Diabetes Duration With Incident Dementia: The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS)

Introduction: Diabetes, a modifiable risk factor for dementia, is thought to impart increased risk of dementia through cerebral small vessel disease. While the importance of diabetes in midlife is well-documented, the influence of different glycemic levels, duration of diabetes, and Alzheimer’s disease genetic risk (apolipoprotein [ APOE ] ε4 genotype) in late-life on dementia risk remains uncertain. This could have implications for individualized prevention strategies. In this study, we investigated whether a higher glycemic level and longer duration of diabetes in late-life is associated with a higher risk of dementia, and whether associations vary by APOE ε4 genotype. Methods: We performed a prospective cohort analysis with the Atherosclerosis Risk in Communities Study using up to 11 years of follow-up (baseline, 2011-2013). We defined diabetes as glycated hemoglobin A1c (HbA 1c ) ≥6.5%, self-reported physician diagnosis, or use of any diabetes medication. Among those with diabetes, we categorized participants as having a lower glycemic level (HbA 1c <7%) or higher level (HbA 1c ≥7%), and duration as short (<5 years) or long (≥5 years). We estimated hazard ratios (HR) for incident dementia by HbA 1c levels and by diabetes duration in separate multivariable-adjusted Cox regression models. We tested for statistical multiplicative interaction on the relative risk of dementia by fitting interaction terms between diabetes measures and APOE ε4 genotype in separate regression models. Results: In 5030 participants without dementia (mean age, 75.4 years; 58.6% female; 21% Black; 28% with diabetes), there were 1167 (23.2%) incident dementia cases over a median follow-up of 9.0 years. Compared to no diabetes, a lower glycemic level and higher level were both associated with elevated dementia risk ( P -trend <.0001; Table). A higher glycemic level was associated with an elevated risk of dementia relative to a lower level (HR=1.47 [95% CI: 1.22-1.77]; Table). Compared to no diabetes, both shorter duration and longer duration were associated with an increase in dementia risk ( P -trend <.0001; Table). Longer duration was associated with an increased risk of dementia relative to shorter duration (HR=1.57 [95% CI: 1.24-1.98]; Table). Associations for glycemic level and diabetes duration did not significantly differ by APOE ε4 genotype (all P >.05). Conclusions: Diabetes management in older adults that includes lower glycemic goals may help reduce dementia risk.

Abstract TU113: Implementing a Community-based Cardiovascular-Kidney-Metabolic Health Program: An FQHC&AMC Partnership

The community of Mattapan (Boston, MA, USA) holds one of the city’s highest rates of CVD-related mortality and shortened life expectancy with disproportionate incidence of cardiovascular kidney metabolic (CKM) conditions/sequelae (e.g. hypertension, myocardial infarction, stroke). To address this, a unique partnership between Mattapan Community Health Center, a federally qualified health center, and two AMCs, Boston Medical Center and MassGeneralBrigham, was created to promote CKM health. HEART of Communities is designed to: 1) provide a comprehensive multi-disciplinary care model (via NP, endocrinologist, nutritionist, pharmacist, CHW, and behavioral health care); 2) improve CKM health outcomes and patient engagement; 3) reduce racial health disparities related to adverse CKM events. Objectives: 1) Identify key implementation facilitators and barriers associated with CKM clinic care with a FQHC partnership 2) Understand target population and eligibility criteria relevant to CKM-related disparities 3) Understand risk stratification, program design, and balanced outcomes for evidence-based CKM care The HEART CKM team functions as a single patient-centered unit delivering care through group visits incorporating AHA-guideline directed pharmacotherapy, holistic lifestyle and mental health support, as well as resource allocation addressing unmet social needs like nutrition security and economic mobility. ~1620 patients are expected to enroll for a 6-month intervention over a 3-year period. Inclusion criteria for CKM (Stage 2) are having at least 2 of 3 conditions consistent with CKM (HTN, T2DM, overweight/obesity). All participants will be residents of Mattapan, ≥18 years, and have a primary or specialty care appointment w/in 18 months. Health assessments (AHA’s PREDICT 10-year CVD risk/Life’s Essential 8) and diagnostics will guide med titration. Patients will complete surveys before/after enrollment (PHQ-9, GAD-7, THRIVE). Preliminary data demonstrate feasibility and acceptability along with facilitators like team-based care and organizational alignment. Data capture for clinical outcomes and intervention fidelity are being tracked. This rare partnership centers equity, trust, and patient engagement by addressing CKM disease burden and reducing disparities. HEART seeks to impact the health, lives, and livelihood of the greater community and future partnerships may include expansion to additional communities facing similar disparities and severity of CVD disease.

Abstract WE482: Age- and Sex-Specific Incidence of Cardiovascular Disease Subtypes in Young Adults: Insights from a Large, Diverse Healthcare System

Background: Cardiovascular disease (CVD) is increasingly recognized among younger adults, yet age-, sex-, and race/ethnicity-specific incidence patterns across subtypes remain underexplored. Methods: We analyzed electronic health records from 1,178,551 individuals aged 18–49 years old within a large, diverse healthcare system. Incident myocardial infarction (MI), heart failure (HF), and stroke were ascertained. Incidence rates were estimated per 1,000 person-years (1000 py), stratified by sex, age group (18–29, 30–39, 40–49), and race/ethnicity. Results: Among women across all age groups, stroke had the highest incidence followed by HF then MI. Among men, this pattern held in the 18–29 age group; however, MI incidence rose sharply with age and surpassed HF and stroke in the older groups. MI incidence in men aged 40–49 (i.e., 1.183/1000 py) was over triple that of women (0.369/1000 py). Racial/ethnic differences were notable: HF incidence was highest among non-Hispanic Black patients across all age groups. In contrast, among Hispanic patients, incidences of MI, HF, and stroke were similar across age strata. Non-Hispanic Asian patients demonstrated lower overall incidence compared with other racial and ethnic groups, yet MI was the leading subtype among men aged 40–49 (1.229/1000 py for MI compared to <0.65/1000 py for HF and stroke). Conclusions: Distinct age-, sex-, and race/ethnicity-specific patterns of CVD incidence are evident in young adults. Stroke predominates among women while MI predominates among men. HF rises steeply in men with advancing age among non-Hispanic Black patients, while MI has the highest incidence among non-Hispanic Asian men above age 30. These findings suggest different underlying etiology for CVD subtypes across age, sex, and racial and ethnic groups, and underscore the need for tailored prevention strategies in diverse young populations.

Endophytic Beauveria bassiana in maize: influence of genotype, fungal source, inoculation methods, and time on colonization and fitness of Fall armyworm

Abstract We investigated how Beauveria bassiana isolate origin and maize genotype affect endophytic colonization and suppression of the Fall armyworm (FAW). The objectives were to determine whether isolate origin (insect or soil-derived) influences colonization across maize tissues, assess the role of four genotypes (two landraces and two improved lines), and evaluate FAW fitness on colonized plants. Three indigenous isolates, two insect-derived (Bb11, Bb115) and one soil-derived (DL1.1), were applied to four maize genotypes. These included two landraces (Kokoli Daneri, Ovinonboe) and two improved varieties (Faaba QPM, TZL Composite 4W Benin). Inoculation was performed using foliar spraying and seed coating. Colonization declined over time but varied significantly with isolate, genotype, and tissue type ( p  < 0.0001). Insect-derived isolates achieved higher colonization, particularly in stems and roots of landraces, indicating genotype-dependent compatibility. Bb115 achieved systemic colonization in Kokoli Daneri leaves at 7 days after inoculation. Feeding assays showed that FAW larvae fed on colonized plants had reduced survival, lower larval and pupal weights, and reduced adult fecundity and emergence. FAW fitness was assessed using corrected larval mortality, larval and pupal weight and size, adult emergence, and reproduction (adult emergence, fecundity). The reduction of fitness remained moderate and was more pronounced in landrace and insect isolate combinations. These results emphasize the importance of fungal isolate, maize genotype, inoculation method, and timing in enhancing endophytic biocontrol.

Abstract TU108: Orthostatic Blood Pressure Phenotypes are Associated with Night-Time Blood Pressure Non-Dipping in Older Adults: The Atherosclerosis Risk in Communities (ARIC) Study

Introduction: Nighttime blood pressure (BP) non-dipping (i.e., a blunted reduction in BP during sleep) is associated with higher risk of cardiovascular disease, stroke, cognitive decline and early death among older adults. Orthostatic hypotension (OH) may share a related physiological pattern, marked by higher supine and lower standing BP (resembling night- and daytime BP respectively). Whether measured or symptomatic OH or orthostatic symptoms could identify people with nighttime non-dipping is unknown. Hypothesis: Very old adults with OH would be more likely to have nighttime non-dipping. Methods: Participants in the ARIC study (2021-23) underwent in-office OH assessments (3 supine followed by 6 standing BP measurements, 1 minute apart) and ABPM monitoring (≥20 daytime and ≥7 nighttime BP measurements over 24 hours). Non-dipping was defined as night/day BP ratio >0.9 (reduction in BP of <10%). OH was defined as a drop in average systolic BP (SBP) of ≥20 mm Hg or diastolic BP (DBP) of ≥10 mm Hg from supine to standing, at 1, 3, or 6 minutes after standing (SBP or DBP OH were examined with corresponding non-dipping). Orthostatic symptoms included lightheadedness, dizziness, imbalance, or fainting during the standing maneuver or while in the standing position. We used logistic regression to examine associations of OH and orthostatic symptoms with non-dipping, adjusting for age, sex, race-study center, and antihypertensive medication use. Results: Of the 305 study participants (57% female, mean age 83.3 [SD: 3.5] years), 60% had non-dipping based on SBP and 43% had non-dipping based on DBP. Mean ABPM daytime SBP was 129.7 (SD: 13.3) mm Hg and nighttime SBP was 119.5 (SD: 15.5) mm Hg; 78% used antihypertensive medications (Table 1). People with OH had higher mean night/day BP ratio compared to people without OH for SBP (0.96 vs 0.91) and DBP (0.92 vs 0.88) (Figure). OH during the first minute was associated with non-dipping for both SBP (OR: 2.18 [CI: 1.25, 3.81]) and DBP (2.06 [1.17, 3.64]), whereas OH during the first 3 minutes was associated with SBP non-dipping (2.16 [1.04, 4.48]). Symptoms during the standing maneuver were associated with SBP non-dipping (3.76 [1.35, 10.47]) (Table 2). Conclusion: In this population of very old, community-dwelling adults, OH soon after standing up (both measured and symptomatic) was associated with nighttime non-dipping on ABPM. Performing ABPM could be valuable in patients with early OH to identify nighttime non-dipping.

Abstract WE532: Association of Daily Step Count with All-Cause Mortality Among Older Adults with Hypertension and Resistant Hypertension

Introduction: Physical activity, particularly daily step count, is associated with all-cause mortality in older adults. However, evidence is limited among those with hypertension and apparent treatment-resistant hypertension (a-TRH)–defined as uncontrolled blood pressure despite taking ≥3 antihypertensive medications–who are at high risk for cardiovascular and all-cause death. We hypothesized that higher daily step counts would be associated with lower all-cause mortality in both hypertensive and a-TRH populations. Methods: We analyzed data from NHANES 2005–2006 and 2011–2014, linked to mortality through 2019. The sample included 2,290 older adults aged ≥65 years with valid accelerometer data for daily step calculation (a-TRH = 519; hypertension = 1,771). Daily steps were categorized into quartiles within each group. Survey-weighted Cox proportional hazards models were used to determine associations between daily steps and all-cause mortality, adjusting for demographics, lifestyle factors, and comorbidities, and stratified by hypertension status. Results: Median daily steps were 5,749 [3,470–8,160] in the hypertension group and 4,432 [2,771–6,796] in the a-TRH group. Participants were followed for 7.2 ± 3.5 years and 6.5 ± 3.3 years in the hypertension and a-TRH groups, respectively. During follow-up, 914 deaths occurred (254 [28%] among a-TRH and 660 [72%] among hypertensive participants). Among older adults with hypertension, hazard ratios (HRs) for the second, third, and fourth quartiles were 0.45, 0.27, and 0.25, respectively, compared with the lowest quartile. Among those with a-TRH, HRs across quartiles were 0.51, 0.60, and 0.35 (Table), compared with the lowest quartile. Conclusions: Higher daily step counts were associated with lower all-cause mortality risk among older adults with hypertension and a-TRH. The greatest incremental benefit was observed between the first and second quartiles; compared with the lowest quartile taking about 2,000 daily steps, mortality risk was roughly 50% lower at about 4,000 daily steps. Lower risk continued with higher quartiles, although less pronounced; compared with the lowest quartile, mortality risk was 65–75% lower in the highest quartile taking about 9,000–10,000 daily steps. Among older adults with hypertension–even those with resistant hypertension–increasing daily steps may be a viable intervention for longevity in this high-risk population.

Abstract 45: Age-Standardized Prevalence of Cardiometabolic Risk Factors Across African Regions: A Pooled Analysis of Population-Based Surveys from 18 Countries.

Background: Noncommunicable diseases are rising across Africa, yet regional profiles of key cardiometabolic risk factors remain incompletely characterized. We compared age-standardized prevalence of hypertension, diabetes, overweight, and obesity across African subregions using comparable WHO STEPS data. Methods: We analyzed nationally representative WHO STEPS surveys of adults 18–69 years from 18 countries (survey years varied by country). Country-specific, age-standardized prevalences (direct standardization to the WHO World Standard Population) were pooled overall and by subregion (North, West, East, Central, Southern Africa) using random-effects meta-analysis. We summarized the prevalence estimates by sex and age and between-study heterogeneity was examined using I 2 . Outcomes used standard thresholds: hypertension (SBP ≥140 mmHg and/or DBP ≥90 mmHg or treatment), diabetes (fasting glucose ≥7.0 mmol/L or prior diagnosis), overweight (BMI ≥25), and obesity (BMI ≥30). Results: Across 79,297 participants (mean, SD 36.3 ± 12.9 years) from 18 African countries, pooled prevalence was 6.2% for diabetes, 27.8% for hypertension, 14.5% for obesity, and 36.3% for overweight, with modest between-survey heterogeneity (I 2 =1%). Clear regional patterns emerged across the continent. North Africa exhibited the highest burden of metabolic conditions, with diabetes affecting 9.6% of participants, obesity 23%, and overweight 57%. Southern Africa had the highest hypertension prevalence at 35%, closely followed by West Africa at 32%. In contrast, East and Central Africa showed consistently lower rates across all measures: East Africa had just 6% obesity and 22% overweight, while Central Africa had 49% overweight. Hypertension showed marked age-related increases, reaching approximately 55-57% among those aged 60-69 years. Sex differences in overall hypertension prevalence were minimal (males 26.4% vs females 26.8%). Notably, despite substantial variation in hypertension prevalence across regions, mean systolic blood pressure remained relatively consistent, ranging from 123-127 mmHg. Conclusions: The burden of cardiometabolic risk factors in Africa is high and heterogeneous, with adiposity concentrated in the north and hypertension highest in the south and west. Findings support targeted obesity prevention in high-adiposity regions and scale-up of hypertension case-finding and treatment, particularly among older adults.

Daily briefing: Tiny bones from Neanderthal fetus point to downfall of the species

A cost-sensitive multiclass machine learning framework for postoperative neurosurgical triage (Neuro-TACTIC)

Abstract Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing patient safety against resource constraints. Most existing models collapse this decision into a binary ICU versus non-ICU choice and lack a mechanism to tune risk thresholds to local staffing ratios or definitions of ICU‐level events. We developed Neuro-TACTIC, a cost-sensitive machine learning framework that stratifies postoperative neurosurgical patients into three monitoring levels: regular ward, intermediate care unit, and intensive care unit. An XGBoost-based classifier was trained on 27 demographic, intraoperative, and imaging-derived features from a retrospective cohort of 1072 patients undergoing elective craniotomy. A tunable parameter ζ integrates resource-related and harm-related costs to adjust the balance between over- and under-triage. Generalization was assessed in an independent cohort. Across repeated cross-validation and bootstrap analyses, the framework demonstrated stable behavior across cost settings. At the operating point ζ = 0.975, performance was AUCμ = 0.67 ± 0.03 and weighted F1 = 0.49 ± 0.03 in the development cohort, and AUCμ = 0.60 ± 0.04 and weighted F1 = 0.44 ± 0.06 in the independent evaluation cohort (n = 81). Feature importance analyses identified operative duration, tumor volume, surgical position, body mass index, and patient age as the most influential predictors. This study demonstrates the feasibility of cost-sensitive, three-tier postoperative triage modeling in neurosurgical patients. Neuro-TACTIC is a methodological proof-of-concept; prospective validation and multicenter evaluation are required before clinical deployment.

Abstract TH936: Cardiovascular Health as Defined by Life’s Essential 8 is Associated with Vascular Function in Middle-Aged Females

Introduction: The American Heart Association defines cardiovascular health as a composite measure of four health behaviors (diet, physical activity, nicotine exposure, sleep health) and four health factors (body mass index, blood lipids, blood glucose, blood pressure), collectively known as Life’s Essential 8. Despite substantial evidence linking cardiovascular health to vascular function, gaps exist in understanding this relationship when evaluated using Life’s Essential 8 metrics. This study examined the association between cardiovascular health and endothelial function assessed using flow-mediated dilation (FMD) and arterial stiffness assessed using carotid-to-femoral pulse wave velocity (cfPWV). Hypothesis: Higher cardiovascular health scores were hypothesized to be associated with higher FMD and lower cfPWV. Methods: Baseline data from 35 females (41.6±7.2 years, 60% White, 97.1% non-Hispanic) enrolled in a randomized controlled trial were included in this analysis. The Life’s Essential 8 metrics were measured and quantified to a range of 0-100, with higher scores indicative of a better health behavior or health factor. FMD was obtained via ultrasonography and cfPWV was measured using applanation tonometry by a trained exercise physiologist. Allometric scaling was applied to the percent change FMD to account for differences in baseline vessel diameter to obtain corrected-FMD. Unadjusted linear regression models examined the relationship between overall cardiovascular health score, as measured by Life’s Essential 8 and corrected-FMD and cfPWV. Unadjusted linear regression models also examined the relationship between each Life’s Essential 8 metric and corrected-FMD and cfPWV. Results: The mean Life’s Essential 8 score was 67.6±9.2, with the majority (88.6%) classified as having intermediate cardiovascular health status. The mean corrected-FMD was 7.1±2.6% and cfPWV was 6.5±1.3 m/s. A significant association was observed between Life’s Essential 8 score and corrected-FMD (b = 0.10 (0.05), p = 0.031), but not cfPWV. Of the eight Life’s Essential 8 metrics, only blood pressure was significantly associated with both corrected-FMD (b = 0.04 (0.02), p = 0.016) and cfPWV (b = 0.02 (0.01), p = 0.014). Conclusion: Life’s Essential 8 may be a practical tool for monitoring cardiovascular health in practice-based settings but requires further investigation.

Abstract 11: Early-Life Famine Exposure and Adult Transitions Across Cardiovascular-Kidney-Metabolic Health Stages: A Prospective Cohort Study in China

Introduction: Cardiovascular-kidney-metabolic (CKM) syndrome represents a progressive pathophysiological continuum. While early-life famine exposure has been associated with cardiometabolic outcomes, its impact on transitions across CKM stages remains unknown. Methods: We utilized data from the Kailuan Study, an ongoing, prospective cohort study in China. We included 24,190 participants with complete baseline anthropometric and biochemical data. Eligible participants had a baseline CKM syndrome stage between 0 and 3 and at least two CKM syndrome stage assessments (through Dec 31, 2022). Famine exposure was classified by birth year into fetal-exposed (1959–1961), early-childhood-exposed (1956–1958), and unexposed (1962–1964). Multistate models estimated associations between famine exposure and stage-specific transitions—CKM progression (within stages 0–3), recovery, clinical cardiovascular disease (CVD), and mortality—stratified by baseline CKM stage. Results: Over a median follow-up of 15.9 years, 2,611 participants developed CVD and 1,645 died. Among those with baseline stage 0, famine exposure was not significantly associated with adverse progression. Among those in stage 1, fetal famine was associated with higher risks of progression (hazard ratio [HR] 1.10; 95% CI, 1.00–1.21) and death after progression (HR 1.78; 95% CI, 1.01–3.14); early-childhood famine showed similar patterns: progression (HR 1.09; 95% CI, 1.00–1.18) and death after progression (HR 1.88; 95% CI, 1.12–3.14). For stage 2, fetal and early-childhood famine were associated with increased risks of progression (HR 1.42; 95% CI, 1.22–1.66 and HR 1.89; 95% CI, 1.66–2.16, respectively), clinical CVD (HR 1.19; 95% CI, 1.05–1.34 and HR 1.30; 95% CI, 1.18–1.45), and death (early-childhood HR 1.65; 95% CI, 1.42–1.92). In addition, early-childhood famine was associated with reduced probability of recovery (HR 0.79; 95% CI 0.71-0.87). No statistically significant associations were detected in participants with stage 3 at baseline (n = 196), likely due to limited power. Conclusion: Early-life famine exposure does not raise CVD or mortality risk among metabolically healthy adults, but it markedly accelerates CKM progression once metabolic dysfunction emerges. This underscores two priorities: (1) sustain metabolic health in famine exposed populations, and (2) implementing proactive interventions at the earliest CKM stages (0-1) to prevent progression to more severe stages.