Miao Huang , Ru Fu , Xiexiong Zhao , Tao Liu , Xiaogang Li , Weihong Jiang
{"title":"Life’s Essential 8 and healthy longevity among people with and without cardiometabolic multimorbidity: A prospective study of UK Biobank","authors":"Miao Huang , Ru Fu , Xiexiong Zhao , Tao Liu , Xiaogang Li , Weihong Jiang","doi":"10.1016/j.ajpc.2026.101433","DOIUrl":"10.1016/j.ajpc.2026.101433","url":null,"abstract":"<div><h3>Aims</h3><div>To investigate the impact of Life's Essential 8 (LE8) on mortality risk and life expectancy in patients with and without cardiometabolic multimorbidity (CMM).</div></div><div><h3>Methods</h3><div>264,675 participants from UK Biobank were categorized into low, moderate, and high cardiovascular health (CVH) levels based on LE8 score. Baseline disease status was categorized as no cardiometabolic diseases (CMD), single cardiometabolic disease (SCMD), or CMM. The Cox proportional hazards model was used to assess the risk of all-cause mortality, and the flexible parametric survival model was employed to estimate life expectancy.</div></div><div><h3>Results</h3><div>During a median follow-up of 14.27 years, 20,335 all-cause deaths occurred. For each 10-point increase in LE8 score, the risk of all-cause mortality declined by approximately 20 % whether in groups of CMD-free, SCMD, or CMM. Compared to the CMD-free with high CVH group, the adjusted hazard ratio (HR) of all-cause mortality was 2.86 (95 % CI: 1.79–4.55) for CMM patients with high CVH, and 6.49 (95 % CI: 5.56–7.58) for CMM patients with low CVH. High CVH levels reduced CMM-related mortality risk by 66.12 %. Compared to those with low CVH, residual life expectancy at age 45 of participants with high CVH extended by 11.05 years (95 % CI: 10.97–11.14) in CMD-free group, 8.73 years (95 % CI: 8.56–8.92) in SCMD group, and 8.12 years (95 % CI: 7.59–8.64) in CMM group. Among CVH components, the tobacco/nicotine score had the greatest impact on mortality risk and life expectancy.</div></div><div><h3>Conclusions</h3><div>Regardless of CMM statuses, higher LE8 scores were consistently associated with lower mortality risk and longer residual life expectancy.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101433"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samuel D. Slavin , Martha L. Daviglus , Olga Garcia-Bedoya , Yasmin Mossavar-Rahmani , Frank Penedo , Krista Perreira , Sylvia Wassertheil-Smoller , Alberto Ramos , Raymond Rigat , Gregory Talavera , Andrew Telzak , Murray A. Mittleman
{"title":"Patient-clinician communication and cardiovascular outcomes: An analysis of the hispanic community health study/study of latinos (HCHS/SOL), 2008-2019","authors":"Samuel D. Slavin , Martha L. Daviglus , Olga Garcia-Bedoya , Yasmin Mossavar-Rahmani , Frank Penedo , Krista Perreira , Sylvia Wassertheil-Smoller , Alberto Ramos , Raymond Rigat , Gregory Talavera , Andrew Telzak , Murray A. Mittleman","doi":"10.1016/j.ajpc.2026.101493","DOIUrl":"10.1016/j.ajpc.2026.101493","url":null,"abstract":"<div><h3>Background</h3><div>Strong patient-clinician communication may improve health outcomes for Hispanic/Latino individuals.</div></div><div><h3>Objective</h3><div>We assessed the association between patient-clinician communication and cardiovascular (CV) events or death in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).</div></div><div><h3>Methods</h3><div>HCHS/SOL is a longitudinal cohort study of individuals aged 18–74 who identified as Hispanic/Latino at 4 U.S. metropolitan areas. Participants' ratings of communication with clinicians during the year before enrollment were used to generate a 3-level communication score. The primary outcome was the composite of myocardial infarction (MI), heart failure events (HF), stroke, and all-cause mortality. The secondary outcomes included the components of the primary outcome. The association between the baseline communication score and outcomes of interest was assessed with Cox proportional hazards models adjusting for possible confounders. We also used multivariable linear regression to assess the cross-sectional association between communication and AHA Life’s Essential 8 (LE8), a measure of CV risk factors. All analyses accounted for the complex survey design.</div></div><div><h3>Results</h3><div>Our sample included 10,527 individuals without prior CV events and at least one medical encounter in the year before enrollment. The median age at enrollment was 41 years (IQR 29, 53), 59% were female, and 71% perceived high-quality communication with clinicians. The mean follow-up time was 9.4 years. High-quality communication was associated with the following results in our fully adjusted analyses: composite outcome (aHR 0.73; 95% CI 0.51, 1.03; <em>p</em> = 0.073), CV events (aHR 0.82, 95% CI 0.44, 1.51, <em>p</em> = 0.520), all-cause mortality (aHR 0.54; 95% CI 0.37, 0.80; <em>p</em> = 0.002).</div></div><div><h3>Conclusions</h3><div>High-quality patient-clinician communication was associated with a non-significant trend toward a lower rate of CV events and death, driven by a significant association with lower all-cause mortality.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101493"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147702668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pedro Rafael Vieira de Oliveira Salerno , Zhuo Chen , Ian Swain , Garima Sharma , Patricia F. Rodriguez Lozano , Chantal Elamm , Weichuan Dong , Khurram Nasir , Zulqarnain Javed , Salil V Deo , Sanjay Rajagopalan , Sadeer Al-Kindi
{"title":"The socio-environmental exposome and maternal cardiometabolic health in the us: a machine learning approach","authors":"Pedro Rafael Vieira de Oliveira Salerno , Zhuo Chen , Ian Swain , Garima Sharma , Patricia F. Rodriguez Lozano , Chantal Elamm , Weichuan Dong , Khurram Nasir , Zulqarnain Javed , Salil V Deo , Sanjay Rajagopalan , Sadeer Al-Kindi","doi":"10.1016/j.ajpc.2026.101455","DOIUrl":"10.1016/j.ajpc.2026.101455","url":null,"abstract":"<div><h3>Background</h3><div>There are substantial disparities in American maternal health, with certain groups experiencing disproportionately high rates of pregnancy-related complications and adverse outcomes. Social and Environmental Determinants of Health (SEDH) may play a role in influencing maternal health in pre-pregnancy and gestational scenarios, but remain poorly understood.</div></div><div><h3>Objectives</h3><div>We aimed to investigate the association between SEDH with pre-pregnancy and gestational conditions related to maternal cardiometabolic health throughout the US using a machine learning approach.</div></div><div><h3>Methods</h3><div>We conducted a cross-sectional study analyzing US county-level first live birth data from mothers between 20 and 34 years of age from 2016 to 2022 sourced from the Natality dataset (CDC-WONDER database). We employed the random forest analysis to assess the relationship between 48 SEDH and six distinct outcomes, representing three pre-pregnancy conditions (pre-pregnancy obesity, pre-pregnancy diabetes, and pre-pregnancy hypertension) and three pregnancy conditions (gestational diabetes, gestational hypertension, and eclampsia).</div></div><div><h3>Results</h3><div>Our study included data from 573 US counties. The three most important SEDH identified were per capita income for pre-pregnancy obesity, percentage of Hispanic population for pre-pregnancy hypertension, and severe housing problems for gestational hypertension. We provide prevalence predictions of cardiometabolic maternal risk factors for the majority of US counties (2731 out of 3194), revealing a clustering of these conditions in the southeastern US.</div></div><div><h3>Conclusion</h3><div>We uncovered relevant associations between SEDH and pre-pregnancy/gestational conditions. Our findings help improve understanding of the complex dynamics driving maternal health disparities and emphasize the pressing need to implement targeted interventions to address underlying determinants of health inequities.</div></div><div><h3>Condensed abstract</h3><div>In the US, certain groups experience disproportionately high rates of pregnancy-related complications and adverse outcomes. In this study, we investigate the association between Social and Environmental Determinants of Health (SEDH) with pre-pregnancy and gestational conditions related to maternal cardiometabolic health. We conducted a cross-sectional study analyzing U.S. county-level first live birth data from mothers between 20 and 34 years of age from 2016 to 2022, sourced from the Natality dataset (CDC-WONDER database).We employed the random forest analysis to assess the relationship between 48 SEDH and six distinct outcomes, representing three pre-pregnancy conditions (pre-pregnancy obesity, pre-pregnancy diabetes, and pre-pregnancy hypertension) and three pregnancy conditions (gestational diabetes, gestational hypertension, and eclampsia). Our study included data from 573 US counties. The thre","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101455"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147702753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mikaila P. Reyes , Alexander C. Razavi , Harpreet S. Bhatia
{"title":"Association of lipoprotein(a) with ASCVD risk in women by menopausal status: the UK Biobank","authors":"Mikaila P. Reyes , Alexander C. Razavi , Harpreet S. Bhatia","doi":"10.1016/j.ajpc.2026.101465","DOIUrl":"10.1016/j.ajpc.2026.101465","url":null,"abstract":"","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101465"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147703131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Colin Harper , Anika Misra , Aniruddh P. Patel , So Mi Cho , Satoshi Koyama , Gina M. Peloso , Whitney Hornsby , Tetsushi Nakao , Pradeep Natarajan
{"title":"Polygenic risk scores enhance LDL cholesterol–based risk stratification for coronary artery disease","authors":"Colin Harper , Anika Misra , Aniruddh P. Patel , So Mi Cho , Satoshi Koyama , Gina M. Peloso , Whitney Hornsby , Tetsushi Nakao , Pradeep Natarajan","doi":"10.1016/j.ajpc.2026.101487","DOIUrl":"10.1016/j.ajpc.2026.101487","url":null,"abstract":"<div><h3>Background</h3><div>Genetic risk for coronary artery disease (CAD) can be estimated using polygenic risk scores (PRS), but greater clarity is needed on how PRS might inform clinical risk assessment and prevention. We assessed the risk for CAD jointly conferred by LDL-C and CAD PRS relative to established treatment thresholds.</div></div><div><h3>Methods</h3><div>This study followed 257,158 UK Biobank (UKBB) participants and 67,668 from the <em>All of Us</em> Research Program (AoU), a longitudinal U.S. cohort, without prior CAD, stroke, or diabetes. In UKBB, Cox proportional hazards models estimated CAD hazard ratios for each LDL-C × CAD PRS stratum relative to individuals with LDL-C < 100 mg/dL. The severe hypercholesterolemia (LDL-C ≥ 190 mg/dL) group, the guideline-designated threshold for statin initiation, served as a benchmark against which groups were compared. Parallel analyses were performed in AoU cross-sectionally.</div></div><div><h3>Results</h3><div>Over a median (IQR) follow-up of 13.5 (12.8–14.2) years, 13,886 (5.4%) participants developed CAD in UKBB. Higher CAD PRS was associated with CAD risk that was comparable to, or in some strata exceeding, that associated with LDL-C ≥ 190 mg/dL by pairwise Wald tests at progressively lower LDL-C concentrations in both cohorts.</div></div><div><h3>Conclusions</h3><div>Individuals with high genetic risk and moderate LDL-C elevations, representing 14.8% of the study population, have CAD risk comparable to or greater than that of SH. Consideration of dynamic LDL-C thresholds among those with high CAD PRS may identify individuals with risk sufficiently high to warrant preventive therapy.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101487"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147706770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"AJPC 2025 in review: A year of growth & clearer mandate for actionable prevention","authors":"Khurram Nasir , Izza Shahid","doi":"10.1016/j.ajpc.2026.101580","DOIUrl":"10.1016/j.ajpc.2026.101580","url":null,"abstract":"","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101580"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147706775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhenyang Cao , Binyan Chen , Jinghao Zhou , Jijie Jin , Dmitry Abramov , Shengzhang Chen , Pan Huang , Jianghua Zhou
{"title":"Liver fibrosis biomarkers as a prognostic tool beyond the defining components in cardiovascular-kidney-metabolic syndrome","authors":"Zhenyang Cao , Binyan Chen , Jinghao Zhou , Jijie Jin , Dmitry Abramov , Shengzhang Chen , Pan Huang , Jianghua Zhou","doi":"10.1016/j.ajpc.2026.101438","DOIUrl":"10.1016/j.ajpc.2026.101438","url":null,"abstract":"<div><h3>Background</h3><div>Despite the multisystem nature of Cardiovascular-Kidney-Metabolic (CKM) syndrome, hepatic dysfunction markers are rarely included. We evaluated whether two noninvasive liver fibrosis scores (LFSs)—the Fibrosis-4 Index (FIB-4) and the non-alcoholic fatty liver disease fibrosis score (NFS)—independently predict all-cause mortality (ACM) and cardiovascular mortality (CVM) in CKM, and whether they complement CKM staging to better capture mortality risk heterogeneity.</div></div><div><h3>Methods</h3><div>We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 (n=32,197) and the UK Biobank (n=88,590). The least absolute shrinkage and selection operator (LASSO) selected a parsimonious covariate set for the baseline Cox model, to which FIB-4 or NFS was added separately. Incremental prognostic value was assessed by discrimination (C-index, time-dependent area under the receiver operating characteristic curve [AUC]), model fit (likelihood ratio test [LRT]), and clinical utility (decision curve analysis). We also compared the original CKM staging with a CKM-Liver staging that added an intermediate-to-high fibrosis-risk indicator.</div></div><div><h3>Results</h3><div>Survival declined with higher LFS, and both scores independently predicted ACM and CVM. Adding FIB-4 or NFS modestly improved discrimination and model fit (ACM ΔC-index=0.009 and 0.008; LRT <em>P</em><0.001), with similar findings for CVM. Time-dependent AUCs were 0.74-0.79 for ACM and 0.75-0.81 for CVM. The CKM-Liver staging yielded modest overall gains but showed steeper risk gradients in advanced stages.</div></div><div><h3>Conclusions</h3><div>FIB-4 and NFS are readily accessible and independent predictors of mortality in CKM. Adding LFSs provides modest but consistent incremental prognostic value and refines risk stratification. LFSs may serve as practical, complementary markers within a multi-organ CKM risk assessment framework.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101438"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147706779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adi Siddharth , David Zidar , Budhaditya Bose , Rakesh Gullapelli , Juan C Nicholas , Khurram Nasir , Sadeer Al-Kindi
{"title":"Hematologic biomarkers of aging (HemeAge) and cardiovascular risk: a machine learning analysis in two cohorts","authors":"Adi Siddharth , David Zidar , Budhaditya Bose , Rakesh Gullapelli , Juan C Nicholas , Khurram Nasir , Sadeer Al-Kindi","doi":"10.1016/j.ajpc.2026.101460","DOIUrl":"10.1016/j.ajpc.2026.101460","url":null,"abstract":"<div><h3>Background</h3><div>Chronological age inadequately reflects aging variability and cardiovascular risk. Biological age derived from routine complete blood count (CBC) parameters may provide a more actionable marker.</div></div><div><h3>Objective</h3><div>To develop a machine learning model of biological age using CBC data (HemeAge) and evaluate associations with mortality and major adverse cardiovascular events (MACE) in two large cohorts.</div></div><div><h3>Methods</h3><div>An XGBoost model was trained on 53,355 NHANES participants (1999–2010) to predict chronological age from CBC parameters. The model was applied to 109,844 Houston Methodist CVD Registry patients, generating \"delta age\" (predicted minus chronological age). Patients were classified as Resilient (delta < –10), Proportionate (–10 ≤ delta ≤ 10), or Accelerated (delta > 10). Cox models assessed mortality and MACE risk, adjusting for demographics and clinical factors.</div></div><div><h3>Results</h3><div>Red cell distribution width, mean cell volume, and neutrophil count were key age predictors. Accelerated aging associated with increased mortality risk (HR 3.05, 95% CI 2.41–3.85) and MACE (HR 1.37, 95% CI 1.24–1.51) versus proportionate aging. Resilient aging conferred reduced risk for mortality (HR 0.59, 95% CI 0.52–0.68) and MACE (HR 0.76, 95% CI 0.72–0.81). Associations were strongest in midlife (ages 40–80) and for death and heart failure outcomes and persisted across age-stratified and continuous models.</div></div><div><h3>Conclusions</h3><div>HemeAge independently predicts mortality and cardiovascular risk beyond chronological age. These accessible hematologic markers may enhance risk stratification and inform targeted prevention strategies.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"26 ","pages":"Article 101460"},"PeriodicalIF":5.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147702870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}