Li, Jingen

Background Disruption in rest‐activity rhythm (RAR) is an emerging risk factor for cardiovascular disease (CVD) and mortality, but the strength of evidence is unclear. Therefore, we conducted a systematic review and meta‐analysis to assess associations between RAR characteristics and cardiovascular disease incidence or prevalence, cardiovascular mortality, and all‐cause mortality. Methods A systematic search was conducted in PubMed, Web of Science, Cochrane Library, and Embase for cohort or cross‐sectional studies published up to August 2025. The exposure variables were nonparametric RAR parameters, including interdaily stability (describing day‐to‐day stability of the RAR), intradaily variability (a measure of RAR fragmentation), and relative amplitude (indicating robustness or strength of the RAR). The primary outcomes were cardiovascular mortality and all‐cause mortality. The secondary outcomes included cardiovascular disease prevalence and incidence. Results Seven studies involving 109 365 participants were included. Pooled results showed that higher intradaily variability was associated with a significantly increased risk of all‐cause mortality (hazard ratio [HR], 1.05 [95% CI, 1.02–1.09]) and cardiovascular disease prevalence (odds ratio, 1.73 [95% CI, 1.21–2.47]). Lower relative amplitude was significantly associated with higher cardiovascular mortality (HR, 1.50 [95% CI, 1.13–1.98]) and all‐cause mortality (HR, 1.46 [95% CI, 1.27–1.68]). Interdaily stability showed no significant associations with any outcome. Conclusions Measures of disrupted rest‐activity rhythms were associated with increased cardiovascular mortality, and all‐cause mortality. These findings support using RAR metrics as early, noninvasive risk indicators. Future work should investigate whether appropriately timed physical activity and sleep, as well as other interventions targeting RAR can mitigate cardiovascular risk.

AbstractAimWhile Baduanjin, a traditional Chinese mind‐body exercise, has shown potential health benefits, its efficacy in improving outcomes for heart failure patients with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF) has not been well documented. We aimed to investigate the adjunctive impact of Baduanjin on exercise capacity and quality of life for HFmrEF/HFpEF.MethodsPatients with HFmrEF/HFpEF were enrolled in this multicenter randomized clinical trial. All participants were randomized to conventional cardiac rehabilitation with or without an additional 12‐week Baduanjin exercise. The primary endpoint was the distance covered in a 6‐min walk test (6MWD), while key secondary outcomes included quality of life measured by the Minnesota Living with Heart Failure Questionnaire (MLHFQ) and cardiopulmonary function including anaerobic threshold (VO2 AT).ResultsA total of 120 patients were enrolled, and 109 completed all session and tests. The mean age of the 120 patients was 60.5 years (SD, 9.21 years), and 23 (19.2%) were women. The Baduanjin group exhibited a 6.14% improvement in 6MWD compared to a 1.32% improvement in the control group (median improvement, 25.0 vs. 5.0 m; p < 0.001) at 12th week. The VO2 AT increased by 25.87% in the Baduanjin group versus 3.94% in the control group (p < 0.001). Quality of life also significantly improved in the Baduanjin group as indicated by MLHFQ score changes (–16.8% vs. –3.99%; p < 0.001).ConclusionsAdding Baduanjin to exercise‐based cardiac rehabilitation for patients with ischemic HFmrEF or HFpEF are generally safe and could provide significant improvements in exercise capacity and quality of life.

Background Although cardiovascular mortality continued declining from 2000 to 2019, the rate of this decrease decelerated. We aimed to assess the trends and disparities in risk factor control and treatment among US adults with atherosclerotic cardiovascular disease to find potential causes of the deceleration. Methods and Results A total of 55 ,021 participants, aged ≥20 years, from the 1999 to 2018 National Health and Nutrition Examination Survey were included, of which 5717 were with atherosclerotic cardiovascular disease. Risk factor control was defined as hemoglobin A1c <7%, blood pressure <140/90 mm Hg, and non–high‐density lipoprotein cholesterol <100 mg/dL. The prevalence of atherosclerotic cardiovascular disease oscillated between 7.3% and 8.9% from 1999 to 2018. A significant increasing trend was observed in the prevalence of diabetes, obesity, heavy alcohol consumption, and self‐reported hypertension within the population with atherosclerotic cardiovascular disease ( P trend ≤0.001). Non–high‐density lipoprotein cholesterol <100 mg/dL increased from 7.1% in 1999 to 2002 to 15.7% in 2003 to 2006, before plateauing. Blood pressure control (<140/90 mm Hg) increased until 2011 to 2014, but declined to 70.1% in 2015 to 2018 ( P trend <0.001, P joinpoint =0.14). Similarly, the proportion of participants achieving hemoglobin A1c control began to decrease after 2006 ( P joinpoint =0.05, P trend =0.001). The percentage of participants achieving all 3 targets increased significantly from 4.5% to 18.6% across 1999 to 2018 ( P trend =0.02), but the increasing trend decelerated after 2005 to 2006 ( P joinpoint <0.001). Striking disparities in risk factor control and medication use persisted between sexes, and between different racial and ethnic populations. Conclusions Worsened control of glycemia, blood pressure, obesity, and alcohol consumption, leveled lipid control, and persistent socioeconomic disparities may be contributing factors to the observed deceleration in decreasing cardiovascular mortality trends.

Introduction: Metabolically obese normal weight (MONW) refers to metabolic abnormalities despite normal body mass index (BMI). Hypothesis: Because obesity is generally defined by BMI, it is assumed that people with MONW do not have excessive adiposity but still have the metabolic dysregulation associated with adiposity. Methods: We included participants aged 20-65 of the National Health and Nutrition Examination Surveys from 1999-2006 and 2011-2018 with normal BMI (18.5-25 kg/m 2 ), fasting blood samples, and DEXA data. According to the AHA criteria, MONW was defined having ≥3 of the following criteria, besides a normal BMI: Hypertriglyceridemia (≥ 150 mg/dL) or treatment for elevated triglycerides; HDL cholesterol level < 40 mg/dL in men or <50 mg/dL in women or treatment for reduced HDL-C; elevated blood pressure (systolic ≥ 130 mmHg and/or diastolic ≥ 85 mmHg) or antihypertensive treatment or history of hypertension; elevated fasting plasma glucose ≥ 100 mg/dL or insulin/oral hypoglycemic treatment and central obesity by waist circumference (≥ 94 cm in men and ≥ 80 cm in women). High fat percentage was defined as ≥25% in men, ≥35% in women. Weighted logistic regression was performed to test the relation between MONW and high fat%, central obesity. Results: Of the 7,887 participants (53.6% men; mean age±SE was 39.23±0.24 years), 2433 (33.4%) had normal BMI included in the analysis. Among these, 148 had MONW (5%). Mean Fat% was 26.08±0.36% in those with MONW versus 21.90±0.17% in those without MONW for men, and 37.02±0.35% versus 33.31±0.21% for women. MONW subjects were 2.21 times more likely to have either central obesity or high fat % (OR 12.09, 95%CI: 6.18-23.67, p<0.01) and 2.18 times more likely to have high fat % (OR=2.84, 95%CI: 1.72-4.67, p<0.01) (see Figure). Conclusions: Most individuals with MONW have either increased fat content, central deposition of fat, or both. That highlights people with normal BMI may still have metabolic complications of adiposity.

Background: The role of body adiposity on metabolic dysregulation in subjects with normal body mass index (BMI) is still under debate with limited population-based evidence. Hypothesis: Body adiposity measured by dual x-ray absorptiometry (DEXA) is associated with metabolic disorders in normal-weight individuals. Methods: We evaluated a sample of adults aged 20-65 who underwent DEXA in the US National Health and Nutrition Examination Surveys from 1999-2006 and 2011-2018. We excluded those with history of cardiovascular disease, cancer, and chronic obstructive pulmonary disease. Weighted logistic regression was performed to test the association between body fat percentage (BF%) and metabolic disorders [e.g., insulin resistance (IR), metabolic syndrome (MS), dyslipidemia, type 2 diabetes mellitus (DM), hypertension]. Models were adjusted for potential confounders while considering complex survey design and were further stratified by sex and BF% as tertiles in normal-weight individuals. IR was tested as a secondary analysis to evaluate the effect on the predicted risk. Results: We included 20,613 individuals (51.5% men, 65.4% non-Hispanic whites), mean age ± SE was 39.42±0.22 years, and 6,424 were normal weight by BMI and represented our study sample. The overall BF% in these subjects measured by DEXA was 28.41±0.19%. In our cohort, metabolic disorders were prevalent in 2.1% to 40.4% of patients (Table 1). Every 10-unit % increase in total BF% was associated with a higher risk for IR, MS, dyslipidemia in the normal weight BMI group (Table 1). Metabolic disorders were associated with BF% tertiles (Figure 1). IR was significantly associated with body fat across all BF% tertiles for men and highest tertiles for women (Figure 2). Conclusion(s): Less than 1/3 of subjects in a representative national sample had a normal BMI. Even in these “normal weight” subjects, increases in body adiposity are significantly associated with increased cardiometabolic disease burden.

Importance Evidence regarding the nature and prevalence of 24-hour activity pattern phenotypes in older adults, especially those related to depression symptoms and cognition, is needed to guide the development of targeted mechanism research and behavioral interventions. Objectives To identify subgroups of older adults with similar 24-hour activity rhythm characteristics and characterize associated depression symptoms and cognitive performance. Design, Setting, and Participants From January to March 2022, a cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination and Survey (NHANES) accelerometer study was conducted. The NHANES used a multistage probability sample that was designed to be representative of noninstitutionalized adults in the US. The main analysis included participants 65 years or older who had accelerometer and depression measures weighted to represent approximately 32 million older adults. Exposures Latent profile analysis identified subgroups with similar 24-hour activity pattern characteristics as measured using extended-cosine and nonparametric methods. Main Outcomes and Measures Covariate-adjusted sample-weighted regressions assessed associations of subgroup membership with (1) depression symptoms defined as 9-Item Patient Health Questionnaire (PHQ-9) scores of 10 or greater (PHQ-9) and (2) having at least psychometric mild cognitive impairment (p-MCI) defined as scoring less than 1 SD below the mean on a composite cognitive performance score. Results The actual clustering sample size was 1800 (weighted: mean [SD] age, 72.9 [7.3] years; 57% female participants). Clustering identified 4 subgroups: (1) 677 earlier rising/robust (37.6%), (2) 587 shorter active period/less modelable (32.6%), (3) 177 shorter active period/very weak (9.8%), and (4) 359 later settling/very weak (20.0%). The prevalence of a PHQ-9 score of 10 or greater differed significantly across groups (cluster 1, 3.5%; cluster 2, 4.7%; cluster 3, 7.5%; cluster 4, 9.0%; χ 2  P = .004). The prevalence of having at least p-MCI differed significantly across groups (cluster 1, 7.2%; cluster 2, 12.0%; cluster 3, 21.0%; cluster 4, 18.0%; χ 2  P &amp;lt; .001). Five of 9 depression symptoms differed significantly across subgroups. Conclusions and Relevance In this cross-sectional study, findings indicate that approximately 1 in 5 older adults in the US may be classified in a subgroup with weak activity patterns and later settling, and approximately 1 in 10 may be classified in a subgroup with weak patterns and shorter active duration. Future research is needed to investigate the biologic processes related to these behavioral phenotypes, including why earlier and robust activity patterns appear protective, and whether modifying disrupted patterns improves outcomes.