tbuckley/cabot-search huggingface dataset:
Abstract P2157: Social Determinants of Health and Health Behaviors Among Adults with Multiple Chronic Diseases: The LINKED-HEARTS Program
Authors: Yuling Chen, Janice Dugbartey, Sarah Slone, Bunmi Ogungbe, Lisa Cooper, Yvonne Commodore-Mensah, Cheryl Dennison Himmelfarb
Journal: Circulation (2025)

Introduction: Social determinants of health (SDoH) contribute to cardiovascular outcomes and health disparities. Despite a recent focus on structural drivers of health disparities, the associations between SDoH and health behaviors among adults with multiple chronic diseases remains understudied. Objectives: To examine the association between SDoH and health behaviors in the “LINKED-HEARTS” (a Cardiometabolic Health Program LINKED with Community Health WorkErs and Mobile HeAlth TelemonitoRing To reduce Health DisparitieS) Program. Method: We conducted a cross-sectional analysis using baseline data from the “LINKED-HEARTS” Program, an ongoing cluster-randomized controlled trial of adults with uncontrolled hypertension in addition to diabetes or chronic kidney disease (CKD). The outcome was adherence to three or more cardiometabolic health promoting behaviors: healthy diet (Mediterranean Eating Pattern for Americans scale), moderate or vigorous physical activity (≥ 150 minutes/week), non-smoking, and recommended sleep duration (7–9 hours/night). The exposures were SDoH ( Table ). To examine the association between SDoH and health behaviors (&gt; 3 vs. ≥ 3), we conducted a multivariable logistic regression analysis, adjusting for demographics (age, sex, race/ethnicity), marital status, and general health status. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were calculated. Results: The study included 214 adults with hypertension in addition to diabetes or CKD, with a mean age of 64 years (±SD 12.3), of whom 61.1% were female, 52.8% were non-Hispanic Black adults. Of the adults included, only 28% (n=60) reported engaging in three or more health behaviors. Participants who reported experiencing any financial strain were 64% less likely to adhere to three or more health behaviors (aOR 0.36, 95% CI: 0.14-0.96) compared to those who never experienced financial strain ( Table ). Additionally, those who reported frequent social isolation were 56% less likely to adhere to ≥ 3 health behaviors (aOR 0.44, 95% CI: 0.21-0.93) compared to those who reported no feelings of social isolation. Conclusion: Financial strain and social isolation were associated with fewer health behaviors among adults with multiple chronic diseases. These findings indicate the need to continually assess and address SDoH in interventions aimed at improving lifestyle behaviors and cardiovascular health outcomes in high-risk populations.
Abstract 036: Proteomic Profiles of the Plant-based Diets and Cardiometabolic Disease Risk
Authors: Qianyan Zheng, Zicheng Wang, Marta Guasch, Fenglei Wang, JoAnn Manson, Lu Qi, Qi Sun, Liming Liang, Zsu-Zsu Chen, Robert Gerszten, Meir Stampfer, Walter Willett, Frank Hu, A Heather Eliassen, Danielle Haslam, Shilpa Bhupathiraju
Journal: Circulation (2025)

Background: Plant-based diets are recommended to lower the risk of type 2 diabetes (T2D) and coronary heart disease (CHD). Proteomic responses to plant-based diets may reveal biological pathways underlying the associations between plant-based diets and cardiometabolic disease risk. Hypothesis: Proteomic profiles reflecting adherence and biological response to an overall plant-based diet index (PDI) and a healthy PDI (hPDI) will associate with lower risks of T2D and CHD, but to an unhealthy PDI (uPDI) will associate with higher risks. Methods: We analyzed baseline plasma Olink antibody-based proteomic profiling and food frequency questionnaire (FFQ) data from 1,660 participants in the Nurses’ Health Study (NHS), NHSII, and Health Professional Follow-up Study. First, proteome-wide association analyses were conducted among 532 proteins for each PDI, adjusting for demographics, lifestyle, and BMI. For proteins with p &lt;0.05, we applied elastic net regression with 10-fold cross-validation to develop plasma proteomic profiles related to baseline self-reported PDIs in a training set (n=1,162). We validated these profiles in a testing set (n=498). Multivariable Cox regression models examined associations between proteomic profiles of PDIs and incident T2D and CHD, adjusting for respective FFQ-derived PDI scores and many potential confounders. Results: We documented 173 T2D cases and 85 CHD cases during median follow-up periods of 23 and 24 years. We identified proteomic profiles comprised of 35, 54, and 40 proteins that correlated with (Spearman r) the FFQ-derived PDI (0.23), hPDI (0.29), and uPDI (0.23) scores, respectively. Each SD increment in the proteomic profiles of the PDI and hPDI was associated with a lower incident T2D risk (PDI: HR=0.59 [0.50, 0.69]; hPDI: HR=0.75 [0.64, 0.88]), whereas the proteomic profile of the uPDI was associated with a higher incident T2D risk (HR=1.37 [1.17, 1.60]). Each SD increment in the PDI proteomic profile, but not the hPDI proteomic profile, was associated with a lower incident CHD risk (HR=0.76 [0.60, 0.96]), whereas the uPDI proteomic profile was associated with a higher incident CHD risk (HR=1.28 [1.02, 1.60]). All the associations remained statistically significant after further adjustment for BMI, except for the association between the hPDI proteomic profile and T2D risk (HR=0.87 [0.73, 1.03]). Conclusions: Proteomic profiles of PDIs were associated with risks of T2D and CHD, independent of self-reported diet measures.
Abstract P3085: Influence of the 5-minute Rest Period on Home Blood Pressure Monitoring in Postpartum Women
Authors: Jaemyung Kim, Bethany Barone Gibbs, Kara Whitaker
Journal: Circulation (2025)

Introduction: Home blood pressure (BP) monitoring is a practical approach for out-of-office measurement, allowing confirmation of elevated BP outside of the clinic setting. Patients are instructed to complete a 5-minute seated rest prior to home BP measurements for accuracy; however, compliance with this rest period and its impact on home BP readings remain unknown. Hypothesis: We hypothesize (1) participants would not consistently complete the 5-minute rest prior to home BP measurements, and (2) readings following the 5-minute rest would be significantly lower and have higher consistency within measurements compared to non-compliant readings. Methods: Participants were postpartum women (3 months after delivery; n = 40) enrolled in the multi-site Postpartum 24/7 pilot cohort study. Participants were instructed to assess BP twice on two occasions (morning and night) for 7 days using the Omron 5 series BP monitor, with 5 minutes of quiet, seated rest before the first measurement. A thigh-worn activPAL3 micro was concurrently used to assess compliance with the 5-minute rest. Given 1-minute epoch lengths from the BP monitor data, we defined compliance as readings with at least 4 minutes of continuous sitting from the activPAL3 before the BP reading. The compliance rate was the percentage of compliant measurements. The random and fixed effects of the 5-minute rest and intraclass correlation coefficients (ICC) of BP readings were calculated using a linear mixed model. Results: Participants (mean age: 30.6 ± 4.2 years; mean body mass index: 28.7 ± 6.6 kg/m 2 ) had 1,034 BP readings, with an average of 25.9 of 28 (92.5%) requested readings per person. Of these, 47.2% of BP readings were considered compliant with the 5-minute rest. Systolic BP was significantly lower by -2.83 mmHg (95% CI: -4.21, -1.47) in rest-compliant readings compared to non-compliant readings, though diastolic BP was similar. ICCs for rest-compliant systolic and diastolic BP readings were 0.708 and 0.690, respectively, suggesting moderate consistency; the corresponding ICCs for non-compliant readings were lower at 0.598 for systolic and 0.581 for diastolic BP. Conclusions: Participants were able to complete most home BP readings but with low compliance with the 5-minute rest period, which affected systolic BP values and overall BP consistency. Future research should assess rest compliance rates in more general populations and its impact on clinical decision-making and outcomes.
Abstract MP04: Association of Mediterranean Diet Score Components with Weight Loss: Findings from the MAINTAIN PRIME Study
Authors: Maribel Cedillo, Jesell Zepeda, Chaorong Wu, Polina Kukhareva, Anuhya Yalavarty, Bernadette Kiraly, Michael Flynn, Kensaku Kawamoto, Margaret Conroy
Journal: Circulation (2025)

Introduction: Caloric intake and diet quality are important for weight management. This study leverages data from the MAINTAIN PRIME weight maintenance trial, which recruited participants with recent, intentional weight loss ≥ 5%. We analyzed the association between diet quality and percentage weight loss at study enrollment. Methods: We assessed diet quality with the Mediterranean Diet Score (MDS), a validated 14-item survey, and examined individual components, each with 2 or 3 categorical levels. The association between percentage weight loss and MDS components was analyzed using gamma regression with log link across three models: Model 1 controlled for gender, Model 2 for gender and weight loss medication use, and Model 3 for gender, medication use, and education. Rate ratios (RR) and 95% confidence intervals (CI) were calculated for each MDS component. Results: Baseline weight and Mediterranean Diet Score (MDS) data were collected from 262 participants. Adjusted RR values for each component of the MDS are found in Table 1. Key findings include: Commercial pastries (cookies, cakes, etc.) The RR of 0.89 across all models (p &lt;0.01), suggests a clear association between consuming more commercial pastries and less weight loss. Those who consume more are likely to experience about 11% less weight loss compared to those who consume less or none. Carbonated or sugar-sweetened beverages (CSSB): The RR of 0.90 across all three models (p ≤ 0.01) suggests that individuals who consume more CSSB experience 10% less weight loss compared to those who consume fewer or no CSSB. Nuts: The RR of 0.89–0.90 across all models (p = 0.01) indicates that a higher intake of nuts per week is associated with less weight loss. Red meat: Across the models, a higher red meat consumption was associated with less weight loss. While the association is not statistically significant in Model 1 (p = 0.11), it becomes significant in Model 2 (p = 0.03) and Model 3 (p = 0.02). Therefore, adjusting for additional variables strengthens the observed association. In Model 3, the RR of 0.91 indicates 9% less weight loss compared to those with lower or no red meat intake. Conclusions: A higher consumption of commercial pastries, carbonated or sugar-sweetened beverages, nuts, and red meat was negatively associated with less weight loss, highlighting their potential role in hindering weight loss efforts. Our findings highlight the importance of diet quality management.
Abstract P3090: 3-Minute Heart Health App: A Feasibility Study
Authors: Iya Abdulkarim, Joseph Metzger, Steven Stovitz, Jeremy Van't Hof
Journal: Circulation (2025)

Background: Cardiovascular (CV) health can be estimated using CV risk factors or can be evaluated more precisely by investigating individual fitness and subclinical disease. Current options involve expensive procedures requiring specialist monitoring and interpretation or radiation exposure and have inequitable access. In contrast, the change in heart rate in one minute after maximum exercise, or heart rate recovery (HRR) is a significant predictor of mortality that does not require specialized equipment and can be done in many settings. In this feasibility study, we aim to assess max heart rate achieved by adults after two minutes of exercise and determine HRR using a Bluetooth heart rate monitor. Methods: We developed the 3-Minute Heart Health App to facilitate this accessible approach to evaluating heart health. We partnered with a primary care clinic to enroll healthy, asymptomatic patients after their visit and listed the study on the University StudyFinder website. For this ongoing pilot study, the app is being paired with a chest band heart rate monitor. When exercise begins, the app provides a countdown timer and displays the patient’s percent of age-adjusted max heart rate (MHR) achieved. After 2 minutes of exercise, the app signals participants to stop and heart rate is monitored for 1 minute. The app then displays the age-adjusted Heart Fitness Grade and HRR (Figure 1). Results: Pilot testing has allowed us to strategically design and optimize the user experience while exploring feasibility of this approach. Of eight patients approached in clinic, seven consented and enrolled. An additional four participants were recruited via StudyFinder. Age ranged from 23 to 73 years; 10/11 were able to achieve &gt;70% of MHR and 7/11 reached &gt;85% of MHR in 2 minutes. Average HRR was 39 bpm; all but 1 had HRR &gt;25bpm. Participant feedback included desiring different exercises to increase heart rate and alternative heart rate monitor devices. There was overall enthusiasm about a routine evaluation of cardiovascular health that participants can monitor over time. Conclusion: Our preliminary findings suggest that the 3-Minute Heart Health test is acceptable and can be implemented in an outpatient setting This study is ongoing and more data are being collected to further determine acceptability and to evaluate characteristics of participants who reach a target MHR with normal/abnormal HRR.
Abstract MP38: The Implications of COVID-19 Pandemic for The Black-White Diabetes Mortality Gap: Has The Disparity’s Dynamic Changed?
Authors: Alexander Sergeev
Journal: Circulation (2025)

Background: Previous studies have investigated racial disparities in diabetes mellitus, including the existence of diabetes mortality gap between African Americans and whites. However, it remains unknown whether the coronavirus SARS-CoV-2 (COVID-19) pandemic changed the magnitude of earlier documented Black-White gap in diabetes mortality. Study Objective: To investigate the dynamic change in the magnitude of the Black-White diabetes mortality gap in relation to COVID-19 pandemic. Methods: Diabetes mortality rates in relation to race, adjusting for major covariates, were analyzed using the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database on underlying causes of death in the United States. Diabetes mortality was analyzed for the three years preceding the pandemic (2017-2019; defined as pre-COVID era diabetes mortality) and the first three years of the pandemic (March 2020 to February 2023; defined as COVID-era diabetes mortality). Diabetes deaths were identified in the CDC WONDER database using the ICD-10 codes E10-E11. To adjust for multiple covariates, general linear modeling (GLM) analysis was conducted (SAS, ver. 9.4). Results: Both African Americans and whites experienced an increase in diabetes mortality rates from the pre-COVID-era to COVID-era period: from 11.0/100,000 to 15.1/100,000 (crude mortality rates) and from 12.4/100,000 to 15.9/100,000 age-adjusted mortality rates) in African Americans; from 10.9/100,000 to 14.1/100,000 (crude mortality rates) and from 8.3/100,000 to 10.3/100,000 age-adjusted mortality rates) in whites. However, when comparing the magnitude of the change in diabetes mortality rates between the pre-COVID and COVID-era periods, the multivariate-adjusted diabetes mortality rate increase in African Americans was 4.26/100,000 greater than in whites (p=0.028). Conclusions: COVID-19 pandemic had a statistically significant impact on the magnitude of racial gap in diabetes mortality. Further research investigating the underlying mechanisms of these findings is warranted.
Abstract P1029: Projecting Disease Paths over the Course of Heart Disease: A Multi-state Non-Markov Framework
Authors: Ming Ding, Feng-Chang Lin, Michelle Meyer
Journal: Circulation (2025)

Background: In existing literature, prevention and prediction of heart disease have largely focused on one endpoint. However, the development of heart disease is a multi-state process that is biologically inseparable. Only a few studies investigated the course of heart disease using multi-state Markov models, which are unsuitable to the course of heart disease due to several reasons. First, by assuming present state is independent of past history, Markov models do not allow for multimorbidity, a common condition for heart disease. Second, risk factors of heart disease interplay and affect future states, which violates the Markov assumption. Finally, the transition probabilities estimated from Markov modelsare time-specific, and these high-dimensional matrices are not straightforward for public health interpretation. Method: We have developed a multi-state non-Markov framework that splits disease state into substates by conditioning on past states (Ding et al. BMC Medical Research Methodology. 2024. In revision. doi: https://doi.org/10.1101/2024.09.18.24313882). As the substates track history of past states, transition rates between substates can be synthesized into one summary estimate, disease path. The derivation of the disease path can be found in our second paper (Ding et al. medRxiv. 2024. doi: https://doi.org/10.1101/2024.09.18.24313882). We applied our method to identify disease paths over the course of heart disease using the Atherosclerosis Risk in Communities Study (ARIC). We obtained the ARIC data from NHLBI BioLINCC. Results: We modeled the course of heart disease in five states: healthy, at metabolic risk, coronary heart disease (CHD), heart failure, and mortality ( Figure 1a ). By applying our framework, the disease states were divided into substates by conditioning on past disease history ( Figure 1b ), where transition rates between substates were estimated and used to project disease paths in the whole population. In this mid- to old-age population, the most likely disease path was “Healthy → at metabolic risk → mortality” (37%) for healthy participants at baseline, and the most likely disease path was “At metabolic risk → mortality” (51%) for at-metabolic-risk participants at baseline ( Figure 2 ). The distribution of disease path was similar across sex and race subgroups. Impact: The path of heart disease characterizes the disease course in a summary manner and may elucidate pathophysiology of heart disease at the population level.
Abstract 006: Mid- and late-life exposure to cardiovascular risk factors and subsequent risk of dementia
Authors: Sanaz Sedaghat, Hongyan Ning, Katherine Giorgio, Natalia Lakomski, Aishwarya Saravanan, John Stephen, Maxwell Mansolf, Alden Gross, Archana Singh-Manoux, Claudia Satizabal, Deborah Levine, Emily Briceno, Farzaneh Sorond, Jayandra Himali, Lenore Launer, Djass Mbangdadji, David Li, Lihui Zhao, Oscar Lopez, Sudha Seshadri, Timothy Hughes, Vilmundur Gudnason, Allison Aiello, Suzanne Judd, Donald Lloyd-Jones, Pamela Lutsey, Rachel Zmora, Elizabeth Peterson, Denise Scholtens, Norrina Allen
Journal: Circulation (2025)

Introduction: Dementia has a long preclinical phase, with pathological and brain changes emerging decades before clinical symptoms appear. Cardiovascular risk factors throughout life contribute to dementia risk, but their effects vary based on their timing and duration. Identifying critical periods of influence is key for developing targeted prevention strategies. Hypothesis: We hypothesize the association between cardiovascular risk factors and dementia varies across the lifespan. Methods: We pooled data for 39,524 individuals from seven cohort studies (Whitehall II, ARIC, CHS, HAAS, MESA, SALSA, and FHS) as part of the Dementia Risk Prediction Pooling Project. We imputed trajectories of body mass index (BMI), systolic blood pressure (SBP), fasting glucose, and cholesterol for each participant starting from age 40 years. Time-weighted average exposures during midlife (ages 40-64 years) and later life (ages 65+ years) were calculated, and hazard ratios for dementia incidence were estimated using Cox proportional hazards models. These models accounted for competing risks of death and were adjusted for sex, race, cohort, educational level, and depressive symptoms. Results: Over a median follow-up of 14 years, there were 5,654 dementia cases and 10,819 deaths. Joint modeling of midlife and late-life risk factors revealed higher BMI, fasting glucose, and cholesterol in midlife were each independently associated with elevated risk of dementia. In contrast, higher late-life values for these factors were associated with lower risk of dementia (Figure). For example, compared to BMI &lt; 20, a BMI ≥ 30 in midlife was associated with a 70% higher risk of dementia, while in late life, it was associated with a 50% lower risk. No association was found between late-life SBP and dementia, but higher midlife SBP was linked to higher risk of dementia. Using rank-based cut offs for risk factors instead of clinical ones did not change the findings. Conclusion: Midlife, but not later-life, levels of cardiovascular risk factors have a stronger effect on dementia risk, highlighting a critical period for intervention.
Abstract 001: Intergenerational social mobility and cardiovascular health among caregivers and their offspring: results from the Study of Latino Youth (SOL Youth)
Authors: Monica Batalha, Paola Filigrana, Krista Perreira, Amanda McClain, Amber Pirzada, Martha Daviglus, Christina Cordero, Alan Delamater, Linda Gallo, Carmen Isasi
Journal: Circulation (2025)

Introduction: Socioeconomic position (SEP) is one of the main determinants of cardiovascular health (CVH). Among Hispanic/Latino populations living in the US, economic hardship is a leading stressor and a risk factor for suboptimal CVH. However, little is known about how changes in SEP can influence CVH across generations. Hypothesis: We hypothesized worse CVH for offspring and caregivers with persistent low SEP versus higher intergenerational SEP. Methods: The Hispanic Community Children’s Health Study/Study of Latino Youth (SOL Youth; 2012-2014) is a cross-sectional study of 1466 Hispanic/Latino youth (aged 8-16 years). Social mobility was assessed using the grandparents' and caregivers' SEP. Grandparents' SEP was defined using the highest level of education attained by grandmother or grandfather: lower (&lt;High school) or higher (≥High school). Caregivers' SEP was defined according to their education and income: lower (education &lt;High school and income &lt;30k) or higher (education ≥High school or income ≥30k). Social mobility was classified as stable low, downward, upward, and stable high groups. CVH was assessed for caregivers and offspring based on Life's Essential 8 (LE-8). We conducted survey linear regression models to investigate the association between social mobility and caregivers' (n=848) and offspring's (n=1217) CVH, adjusting for age, sex, place of birth, Hispanic/Latino background, and field center. Results: Among caregivers, lower total LE-8 scores were observed for stable low [β= -3.91(-7.33; -0.49)] and downward [β= -4.85 (-9.61; -0.09)] groups compared to those in the stable high group. Lower BMI scores were observed in the stable low [β= -7.87 (-15.31; -0.43)] compared to those in the stable high group. Lower diet [β= -8.57(-16.75; -0.38)] and nicotine exposure [β= -22.23 (-34.48; -9.98)] scores were observed in the downward group compared to the stable high group. Among offspring, lower total LE-8 [β= -3.00 (-5.24; -0.75)] and glucose [β= -4.96 (-7.89; -2.04) scores were observed in the stable low compared to the stable high group. Conclusions: Among Hispanic/Latinos, the intergenerational persistence of low SEP was associated with worse CVH in caregivers and their offspring compared to remaining in high SEP. Our findings highlight that disadvantages transferred across generations may help explain how CVH disparities emerge early in life. Future policies focused on structural interventions are needed to address these disparities in CVH.