Citations

Background: Stroke is a major health burden and the second leading cause of death globally, only after ischemic heart disease. While observational studies have elaborated on the effect of physical activity (PA) and sedentary behavior (SB) on stroke risk, their findings remain inconsistent and are often influenced by confounding factors and reverse causation. Mendelian randomization (MR) can help overcome these shortcomings and assess potential causal relationships using genetic variants as proxies for exposures. Methods: We conducted a systematic review and meta-analysis of MR studies investigating the effects of PA and SB on stroke risk. Following PRISMA guidelines, we searched PubMed and Google Scholar through May 2025. Eligible studies used two-sample MR designs to estimate the impact of moderate-to-vigorous physical activity (MVPA) and sedentary leisure behavior (SLB) on stroke outcomes. MVPA exposures included self-reported activity and accelerometer-derived measures (e.g., leisure time MVPA ≥425 mg), while SLB included television, screen time, sitting, etc. Key outcomes of interest were any stroke and ischemic stroke events. Random-effects models were used for meta-analysis and heterogeneity was assessed with the I2 statistic. Leave-one-out sensitivity analyses were performed to ensure robustness of the results. Results: Six studies met inclusion criteria. Genetically predicted MVPA was associated with a lower risk of stroke (pooled OR = 0.73; 95% CI: 0.53–1.01; p = 0.06), though the result was not statistically significant (I2= 79.5%). In contrast, SLB showed a significant association with increased stroke risk (pooled OR = 1.15; 95% CI: 1.01–1.31; p = 0.03; I2 = 89.9%). Sensitivity analyses confirmed that findings were not influenced by any single study. Conclusion: These findings support a causal association between SLB and increased stroke risk, with suggestive but non-significant evidence for MVPA’s protective role. Despite significant association, high heterogeneity warrants conscious interpretation of findings. Further MR studies using standardized exposure definitions and updated genetic data are needed to strengthen the results.

Background: Contemporary data on trends in survival after incident atrial fibrillation (AF) are limited. Methods: Residents of a 27-county area in southern Minnesota and western Wisconsin with new-onset atrial fibrillation or atrial flutter between 2013 and 2023 were identified. An electronic algorithm requiring 1 inpatient code or 2 outpatient codes separated by >7 days but within 1 year was used to define AF. Patients were followed for all-cause mortality through March 31, 2025. Standardized mortality ratios of observed versus expected survival were calculated, and time trends in survival were examined using Cox regression adjusting for demographics, cardiovascular risk factors, comorbid conditions, and area-level measures of socioeconomic status and rurality. Results: There were 44,930 individuals identified with incident AF from 2013-2023 (56.4% male; mean (SD) age 72.8 (13.5) years; 95.8% were non-Hispanic white). Within the first 90 days, the risk of all-cause mortality was greatly elevated compared with individuals of a similar age and sex distribution in the general population (standardized mortality ratios 12.6, 95% CI, 12.1-13.0 and 3.8, 95% CI, 3.6-4.0 for the first 30 days and 31 to 90 days after diagnosis, respectively). This excess risk was observed for all age groups but was greatest in the youngest age group (standardized mortality ratios among 18-64 year olds for the first 30 days: 49.9, 95% CI, 44.6-55.7 and 31 to 90 days: 11.1, 95% CI: 9.4-13.1; Figure ). In the youngest age group, the excess risk persists through 5 years post AF, however, in the oldest age group the excess risk only persisted through 1 year. Survival within the first 90 days improved over the study period (adjusted hazard ratio [aHR], 0.88; 95% CI, 0.79-0.99 for 2023 vs 2013); likewise, among 90-day survivors, survival improved between 2013 and 2023 (aHR,0.82; 95% CI, 0.76-0.88). These trends were driven by improvements in the younger age groups, particularly for death among 90-day survivors (aHR for 18-64 years, 0.66, 95% CI, 0.52-0.83; 65-74 years: 0.77, 95% CI: 0.65-0.90; 75-84 years, 0.84, 95% CI: 0.75-0.95; 85+ years, 0.99, 95% CI: 0.98-1.01). Conclusion: In a Midwestern community, the excess risk of death is high within the first 90 days after incident AF. Furthermore, survival after AF has improved between 2013 and 2023, with the improvement greatest in younger age groups.

Objective: To test the effect of physical activity on the gut microbiome and circulating short chain fatty acids among sedentary overweight/obese adults with prediabetes. We hypothesized that randomization to increased physical activity would result in gut microbiome changes. Methods: \We randomized 77 adults with prediabetes and a sedentary lifestyle into one of two groups: 1) Intervention Group: Invited to engage in home-based moderate intensity walking 3x/week for 30 minutes/session in weeks 1-4 and for 45 minutes/session during weeks 5-8 of the 8-week intervention; or 2) Control Group: Maintained habitual physical activity levels. We performed metagenomic sequencing from stool collected at baseline, week 4, and week 8, with short-chain fatty acids (SCFA) measured from serum collected at baseline and week 8. Taxonomic and functional profiling were performed on the metagenomic reads; alpha diversity metrics were subsequently derived. Linear regression assessed the difference in change between the intervention and control groups for alpha-diversity and SCFA levels. Results: We screened 1,533 participants for eligibility and consented 132. Of these, 87 entered the run-in phase and 77 were randomized. Participants were 51.4±8.9 years old, 87.7% female, and 74% non-Hispanic White. Mean fasting glucose was 103.3±13.2 while mean BMI was 34.4±5.7. In comparison to the control group, the intervention group experienced decreased alpha diversity as characterized by Shannon, Richness, and Faith’s diversity indices by week 8 of the intervention (P<0.05). SCFA levels trended towards improvement in the intervention group, but the results were not statistically significant. Functional analysis of KEGG ontologies revealed themes consistent with a microbiome with enhanced metabolic activity and host-relevant metabolic signaling (Figure). Conclusions: Randomization to a walking intervention resulted in modest gut microbiome changes among adults with overweight/obesity and prediabetes.

Introduction: Adolescent obesity is linked to significantly increased risk of cardiovascular and metabolic comorbidities. Exercise outcomes are often impaired in adolescents with obesity (AO), but it remains unclear whether this reflects compromised cardiovascular reserve or non-cardiovascular factors. This study aimed to characterize mechanisms of reduced exercise performance in AO using cardiopulmonary exercise testing (CPET). The secondary aim was to assess the contribution of excess weight burden by correcting for extra fat mass in AO through estimated standard body mass (eSBM). Methods: We retrospectively analyzed CPET data from asymptomatic AO, defined as BMI ≥ 30 (n = 94), and age-matched, normal-weight controls without obesity (n = 139). In a subset of AO (n = 47), % body fat was measured by bioelectric impedance analysis, and eSBM was calculated as if they have comparable % body fat to controls using median values by sex and age in US adolescents. CPET was performed with a cycle ergometer following a ramp protocol. Results: Both male and female AO exhibited higher resting HR (p < 0.001) while peak HR remained comparable to controls. Absolute peak oxygen consumption (VO2) was higher in female AO (p < 0.001), while males showed no difference. Absolute ventilatory anaerobic threshold (VAT) was elevated in AO in both sexes (p < 0.001). When indexed by total body weight, peak VO2, peak work rate (WR), and VAT were lower in both male and female AO (p < 0.001). Peak respiratory exchange ratio (RER), peak VO2/VAT, and peak WR/peak VO2 were also significantly reduced in AO (p < 0.001). When indexed by eSBM, peak VO2 normalized only in female AO; peak WR remained lower, but VAT normalized in AO of both sexes with overcorrection in females, suggesting comparable submaximal exercise performance to controls. Conclusion: Reduced exercise performance in AO appears characterized by elevated resting HR, early exhaustion near peak exercise (lower peak RER and peak VO2/VAT), and decreased work efficiency (lower peak WR/peak VO2). Indexing CPET parameters by eSBM revealed relatively normal cardiopulmonary performance in AO during submaximal exercise, suggesting that reduced performance primarily reflects premature, fatigue-driven termination of exercise due to excess weight burden rather than true cardiopulmonary compromise. Further study is needed to clarify factors contributing to the observed sex-specific differences in AO exercise performance.

Introduction: Chronic kidney disease affects nearly half of heart failure (HF) patients, underscoring the importance of regular kidney function monitoring. However, longitudinal trajectories of kidney function in HF are not well characterized. Identifying clinical factors linked to long-term changes is critical for improving monitoring and informing early clinical decisions. Hypothesis: We hypothesized that longitudinal kidney function and its associations with clinical variables in HF patients differ from that of demographically similar comparators from the same community. Methods: We analyzed patients with validated HF from a community-based cohort and comparators individually matched to age and sex selected from participants in the Mayo Clinic Biobank cohort. Individuals with end-stage kidney disease, dialysis or kidney transplantation prior to enrollment were excluded. Serum creatinine-based estimated glomerular filtration rate (eGFR) from outpatient and inpatient visits was assessed from enrollment for up to 10 years of follow-up. The median of eGFR for 90-day intervals was used to estimate the follow-up eGFR (Figure 1) . We modeled percentage change from baseline and fit linear mixed-effect models with time, HF status, and their interaction to test whether the eGFR trajectories differed between the two groups. In addition, we examined the association between eGFR trajectories and clinical variables. Results: We studied 1182 HF patients and 825 comparators with at least three eGFR measurements. Median follow-up was 5 years (IQR: 3-10) for HF patients and 8 years (6-9) for comparators. In total, 16245 serum creatinine measurements from HF patients and 9858 from comparators were analyzed. Median age at enrollment was 76 years (67-84) for HF patients and 78 years (70-83) for comparators. A greater decline in percentage change in eGFR was observed in HF patients (-4.23%, 95% CI: -4.75 to -3.70% per year) than in comparators (-1.90%, 95% CI: -2.51 to -1.29% per year; P<0.001, Figure 2 ). Among HF patients, the decline in percentage change in eGFR was greater in the presence of diabetes, hyperlipidemia, or a higher comorbidity burden. Conclusions: In this community study, HF patients exhibited a greater percentage decline in eGFR compared to community comparators. Among HF patients, eGFR decline was more strongly associated with comorbidities—particularly metabolic risk factors—highlighting the relevance of the cardiovascular-kidney-metabolic syndrome in HF.

Background: Coronary heart disease (CHD) remains the leading cause of death in the United States, yet the benefits of modern cardiovascular care are not equitably distributed. Social determinants of health (SDoH), which includes economic stability, education, healthcare access, and neighborhood environment, may substantially shape outcomes among patients with CHD. Our study evaluates the joint association of SDoH burden and CHD with mortality outcomes. Methods: We analyzed adults ≥20 years from the National Health and Nutrition Examination Survey (NHANES) 2000–2018, linked with the National Death Index through 2018. Cumulative SDoH burden was derived from eight domains (employment, poverty-to-income ratio, food insecurity, education, healthcare access, insurance, housing, marital status), categorized as low (0–2), moderate (3–5), or high (6–8). Weighted Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cardiovascular mortality by SDoH burden, stratified by CHD status, with sequential adjustment for demographic and cardiometabolic factors. Results: Among 49.3 million U.S. adults (mean age 46.1 ± 15.6 years; 44.8% female), 3.7% had CHD. Those with CHD were older (64.7 vs 45.4 years, p < 0.001), more often non-Hispanic White (94.2% vs 81.5%), and had greater waist circumference (106.1 vs 87.5 cm) but lower cholesterol (176 vs 202 mg/dL, p < 0.001). Participants with high SDoH burden had lower income and education. In weighted regression, higher SDoH burden and CHD were independently associated with greater all-cause and cardiovascular mortality. Fully adjusted models showed high SDoH burden tripled all-cause mortality risk (HR 3.00, p < 0.001), while CHD further amplified risk. Compared with low SDoH/no CHD, those with CHD and high SDoH burden had nearly a 14-fold higher all-cause mortality (HR 13.6, p < 0.001) and 17-fold higher cardiovascular mortality (HR 17.7, p < 0.001). Findings were consistent across sex, race, and metabolic subgroups, with mortality hazards often exceeding tenfold among those with both CHD and high SDoH burden. Conclusions: Cumulative SDoH burden is strongly and independently associated with mortality among adults with CHD, with evidence of a synergistic effect between biological and social vulnerability. These findings underscore the need for policies and interventions addressing upstream social inequities to improve survival in cardiovascular populations.

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.

Background: Cardiac rehabilitation (CR) is emerging as an essential aspect of secondary prevention in patients recovering from acute myocardial infarction (AMI) or coronary artery disease (CAD). Exercise-based rehabilitation involves high-intensity interval training (HIIT), moderate-intensity continuous training (MICT), and maximum intensity interval training (MIIT). These are integral to improving cardiopulmonary fitness, cardiovascular outcomes, and affect health-related quality of life (HRQoL). HIIT is presumed to show better outcomes, though comparative evidence across exercise types remains inconsistent. Clarifying the differential impact of HIIT, MIIT, and MICT on physical and psychosocial outcomes is vital for optimizing CR. Methods: 5 studies involving 650 post-AMI adults enrolled in CR were included. Most studies compared HIIT and MICT; one study also included maximal-intensity interval training (MIIT), and all others used usual care as a control. Outcomes included cardiorespiratory fitness (VO2 max), functional capacity (6-minute walk test [6MWT]), HRQoL (EQ-5D-5L, MacNew), mental health (PHQ, vitality), sleep quality (PSQI), fatigue (FSS), and physiological measures (blood pressure (BP), lipid profile, stroke volume, VE_peak). A qualitative synthesis of findings was performed due to heterogeneity across studies. Results: All 5 studies indicated that structured exercise improved outcomes. HIIT led to greater gains in VO2max compared to MICT. MIIT, assessed in one study, showed the largest VO2max improvements. HRQoL improved in all modalities across EQ-5D-5L, MacNew, PHQ, and visual analog scales. Functional metrics (6MWT, PPO) and cardiovascular parameters (HDL-C, HR recovery) improved more with HIIT. BP, BMI, and HbA1c improved similarly across groups. In several studies, HIIT had a stronger effect on physical functioning and emotional health. Only HIIT led to a significant drop in depression scores. HDL cholesterol improved more with HIIT. Conclusion: HIIT provides superior gains in cardiorespiratory fitness and physical function compared to MICT or MIIT in CR participants, without compromising safety/quality of life. Mental health, HRQoL, and physiological parameters improve comparably across exercise modalities. These findings support that HIIT is an effective, time-efficient option in contemporary CR planning. Future standardized, large-scale, and long-term studies are needed to assess sustained clinical impact and cardiovascular event reduction.

Introduction: Heart failure (HF) with preserved ejection fraction (HFpEF) is now the predominant HF subtype, largely driven by the syndemic of physical inactivity and overweight/obesity in an aging population. Deranged skeletal muscle energetics and regional ectopic adipose depots are key cardiometabolic pathways in the pathogenesis of HFpEF, both of which may be favorably modified by 1-2 hours/week of resistance exercise (RE). However, its association with HFpEF risk has not been thoroughly examined. We investigated the association between midlife RE behaviors and incident HFpEF in the Atherosclerosis Risk in Communities (ARIC) study. Hypothesis: Participation in RE at midlife is inversely associated with the risk of incident HFpEF. Methods: Our exposure (RE)—including weightlifting and bodyweight resistance exercises—was assessed using the validated Baecke questionnaire and reported weekly RE duration was averaged across Visits 1 and 3 (1987-1995). We dichotomized averaged RE as 0 hr/wk (‘No RE’, reference) and >0 hr/wk (‘Any RE’). Our outcome (incident HFpEF) was identified through committee-adjudicated HF hospitalizations (January 1, 2005 to December 31, 2023) using medical chart abstraction. Participants with prevalent HF, death, or loss to follow-up before January 1, 2005 were excluded. We constructed Cox regression models to evaluate the association between midlife RE and incident HFpEF. Model 1 adjusted for age, sex, race, field center, education, smoking status, alcohol consumption, and non-RE physical activity. Given that adiposity may lie on the causal pathway, waist-height ratio (WHtR; both measured in cm) was added in Model 2. Results: 10,751 Black and White participants (803 incident HFpEF cases) were analyzed over a median follow-up time of 14.4 years (mean±SD Visit 1 age, 53.3±5.6 years; average Visit 1 and 3 WHtR, 0.58±0.08; 24.7% Black; 57.4% female). 1,217 participants (11.3%) reported engaging in RE at Visits 1 and/or 3, with a median duration of 0.84 hr/wk (IQR, 0.50-1.61). Compared to No RE, the fully adjusted hazard ratio (HR) for Model 1 for Any RE was: 0.78 (95% CI, 0.61-1.00, P = 0.05). The association was attenuated after adjustment for WHtR: HR = 0.84 (0.65-1.07, P = 0.16). Conclusion: Participation in RE at midlife is associated with a 22% lower risk of incident HFpEF. To inform public health and clinical guidelines, further studies are needed to clarify the role of RE in HFpEF prevention.

Introduction: Abnormal sleep has been linked to increased dementia risk, but the pathophysiological processes driving this connection are unclear. To provide insight into the biological pathways underlying the relationship between sleep and brain health, we tested the hypothesis that increased obstructive sleep apnea (OSA) severity and shorter habitual sleep duration are associated with a higher burden of Alzheimer’s disease (AD) pathology, neurodegeneration, and neuroinflammation measured through plasma biomarkers. Methods: ARIC participants who took part in the Sleep Heart Health Study at Visit 4 (1996-98) with stored plasma samples at Visit 3 (1993-95) and Visit 5 (2011-13) were examined (n=261; mean age 61.3 years; 43.3% male). OSA severity, categorized based on the number of apneas and hypopneas per hour of sleep (<5 events/hour [Normal], 5 to <15 events/hour [Mild OSA], or ≥15 events/hour [Moderate/Severe OSA]) was assessed via in-home polysomnography, and average habitual sleep duration (<7 hours, 7 to <8 hours, or ≥8 hours) was self-reported. Plasma biomarkers of amyloid beta (Aβ) 42 and 40, phosphorylated Tau 181 (p-Tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured using Quanterix Simoa immunoassays. Covariate-adjusted linear regression models estimated associations of sleep indices in 1996-98 with standardized plasma biomarker measurements in 1993-95 (3 years earlier) and in 2011-13 (15 years later). Covariate-adjusted linear mixed effects models quantified associations of sleep measures with the 5-year rates of change in standardized biomarker levels (1993-2013). Results: Compared to a habitual sleep duration of 8 hours or more, sleeping less than 7 hours per night was associated with higher NfL, a biomarker of neurodegeneration, 15 years later (β = 0.252; 95% confidence interval [CI]: 0.003, 0.501). Sleep indices were not associated with biomarker levels 3 years earlier. Counter to our hypothesis, Moderate/Severe OSA was associated with slower increases in p-Tau181 (β = -0.102; 95% CI: -0.198, -0.006), a biomarker of AD pathology, over a median of 17.9 years. Conclusions: Short habitual sleep duration may impact dementia outcomes through neurodegenerative and other processes rather than through pathways specific to AD pathology or neuroinflammation. Longitudinal studies with sleep measurements in larger, more diverse samples are needed to further distinguish the pathways linking sleep to dementia.