Lifestyle habits associated with cardiac conduction disease

Risk Factors for Disease Aggravation in Older Patients With Non-communicable Diseases: Interpretive Structural and Hierarchical Holographic Modelling

AIMS

This study aimed to analyse and determine the risk factors of disease aggravation faced by older patients with non-communicable diseases (NCDs) and their interwoven correlations.

DESIGN

We employed a descriptive and cross-sectional study, which followed the STROBE guidelines for reporting.

METHODS

We conducted a semi-structured in-depth interview with 26 older patients with NCDs from a hospital in Qingdao, China between July and August 2022 on the basis of the literature review. Then, we analysed data using the directed content analysis and determined risk factors through a focus group discussion and the Delphi consultation. Afterward, we combined interpretive structural modelling and hierarchical holographic modelling to construct a hierarchical structure model and drew relationship framework diagrams to exhibit diversified risk factors and complex interwoven correlations.

RESULTS

We identified 30 risk factors from individual, interpersonal, organisational, community and policy levels. The hierarchical structure model constructed by interpretive structural modelling demonstrated a four-layer structure, and the individual and interpersonal levels were at the highest layer. The relationship framework diagrams demonstrated the identification process of risk factors and interwoven correlations at individual and organisational levels.

CONCLUSIONS

Risk factors causing disease aggravation amongst older patients with NCDs are diverse. To delay the progression of NCDs, we should comprehensively explore risk factors, interpret the root causes and effects of risks from multiple perspectives and consider the interaction amongst multi-level risk factors to develop precise measures related to risk control.

IMPACT

Controlling risk factors is an effective measure to postpone disease aggravation. Through this study, we provide a scientific and comprehensive basis for clinical risk screening so that healthcare providers can sense potential risk factors for disease aggravation in older patients' surroundings and formulate targeted nursing measures according to the risk factors faced by different patients.

PATIENT OR PUBLIC CONTRIBUTION

Patients participated in interviews to supplement risk factors included in our study. Experts provided opinions on the inclusion, exclusion and modification of risk factors.

Physical Activity Modifies the Risk of Incident Cardiac Conduction Disorders Upon Inflammation: A Population-Based Cohort Study

BACKGROUND

Emerging evidence suggests a central role for inflammation in cardiac conduction disorder (CCD). It is unknown whether habitual physical activity could modulate the inflammation-associated risks of incident CCD in the general population.

METHODS AND RESULTS

This population-based cohort was derived from the China Kailuan study, including a total of 97 192 participants without prior CCD. The end points included incident CCD and its subcategories (atrioventricular block and bundle-branch block). Systemic inflammation was indicated by the monocyte-to-lymphocyte ratio (MLR). Over a median 10.91-year follow-up, 3747 cases of CCD occurred, with 1062 cases of atrioventricular block and 2697 cases of bundle-branch block. An overall linear dose-dependent relationship was observed between MLR and each study end point (all P-nonlinearity≥0.05). Both higher MLR and physical inactivity were significantly associated with higher risks of conduction block. The MLR-associated risks of developing study end points were higher in the physically inactive individuals than in those being physically active, with significant interactions between MLR levels and physical activity for developing CCD (P-interaction=0.07) and bundle-branch block (P-interaction<0.05) found. Compared with those in MLR quartile 2 and being physically active, those in the highest MLR quartile and being physically inactive had significantly higher risks for all study end points (1.42 [95% CI, 1.24-1.63], 1.62 [95% CI, 1.25-2.10], and 1.33 [95% CI, 1.13-1.56], respectively, for incident CCD, atrioventricular block, and bundle-branch block).

CONCLUSIONS

MLR should be a biomarker for the risk assessment of incident CCD. Adherence to habitual physical activity is favorable for reducing the MLR-associated risks of CCD.

Role of ideal cardiovascular health metrics in reducing risk of incident arrhythmias

AIMS

Cardiovascular health (CVH) has been proven to reduce cardiovascular disease burden and mortality, but data are lacking regarding cardiac arrhythmias. The aim of this study was to assess the association between CVH metrics and atrial fibrillation/flutter (AF), ventricular arrhythmias, and bradyarrhythmias.

METHODS AND RESULTS

This study analysed data from the Atherosclerosis Risk in Communities (ARIC) cohort, with participants recruited from four different communities across the United States. Cardiovascular health metrics were scored at baseline (1987-89) following the American Heart Association's recommendations and categorized as poor, intermediate, or ideal. Arrhythmia episodes were diagnosed by International Classification of Diseases (ICD)-9 code. Adjusted associations were estimated using Cox models and event rates and population attributable fractions were calculated by CVH metrics category. The study population consisted of 13 078 participants, with 2548 AF, 1363 ventricular arrhythmias, and 706 bradyarrhythmias occurred. The adjusted hazard ratios (HRs) for ideal (vs. poor) CVH metrics were 0.59 [95% confidence interval (CI): 0.50-0.69] for AF, 0.38 (95% CI: 0.28-0.51) for ventricular arrhythmias, and 0.70 (95% CI: 0.51-0.97) for bradyarrhythmia. The risk of incident arrhythmias decreased steadily as the CVH metrics improved from 0 to 14 scores. The adjusted population attributable fractions were calculated to be 29.9% for AF, 54.4% for ventricular arrhythmias, and 21.9% for bradyarrhythmia, respectively. The association between CVH metrics and incident arrhythmias was also seen in people who remained free of coronary heart disease over the follow-up.

CONCLUSION

Achieving ideal CVH metrics recommendations by AHA in midlife was associated with a lower risk of incident arrhythmias later in life.

Incidence and prognosis of cardiac conduction system diseases in hypertension: the STEP trial

Patients with cardiac conduction system diseases (CSD) may have increased incidence and mortality of cardiovascular events. Here we report a post hoc analysis of the Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients (STEP) randomized clinical trial (ClinicalTrials.gov number, NCT03015311) concerning the effect of intensive blood pressure (BP) control on the incidence of new-onset CSD and the prognostic implications of preexisting or new-onset CSD. The incidence of new-onset CSD was similar in the intensive (n = 205, 6.42%) and standard (n = 188, 5.94%) treatment arms. Participants with preexisting CSD had a higher risk for acute decompensated heart failure. Increased age, male sex and increased body mass index were independently associated with increased risk for new-onset CSD. Our results suggest that intensive BP control may not reduce the incidence of new-onset CSD compared with standard BP control.

Distinct uric acid trajectories are associated with incident cardiac conduction block

BACKGROUND

The association of longitudinal uric acid (UA) changes with cardiac conduction block risk is unclear. We aimed to identify the trajectories of UA and explore its association with cardiac conduction block.

METHODS

A total of 67,095 participants with a mean age of 53.12 years were included from the Kailuan cohort in Tangshan, China, who were free of cardiac conduction block and with repeated measurements of UA from 2006 to 2012. UA trajectories during 2006 to 2012 were identified by group-based trajectory modeling. Cox proportional hazard regression models were used to assess the association of UA trajectories with cardiac conduction block.

RESULTS

We categorized three observed discrete trajectories of UA during 2006-2012 period: low-stable, moderate-stable, and high-stable. Over a median follow-up of 6.19 years, we identified 1405 (2.09%) incident cardiac conduction block. Compared to those in the low-stable trajectory, the adjusted hazard ratios (HRs) (95% confidence interval [CI]) of cardiac conduction block in the moderate-stable and high-stable trajectory were 1.30 (1.16-1.47) and 1.86 (1.56-2.22), and HRs of atrioventricular block were 1.39 (1.12-1.72) and 2.90 (2.19-3.83), and HRs of bundle branch blocks were 1.27 (1.10-1.47) and 1.43 (1.13-1.79). Notably, although the average UA level in the moderate-stable UA trajectory group is within the normal range, the risk of cardiac conduction block has increased.

CONCLUSIONS

The moderate-stable and high-stable trajectories are associated with increased risk for new-onset cardiac conduction block. Monitoring UA trajectories may assist in identifying subpopulations at higher risk for cardiac conduction block.

Effects of body mass index and blood pressure on atrioventricular block: Two-sample mendelian randomization

BACKGROUND

Observational studies have suggested associations between some atherogenic risk factors and atrioventricular (AV) block.

OBJECTIVE

The purpose of this study was to investigate the causal effects of several cardiometabolic exposures on AV block and evaluate the role of coronary artery disease (CAD) as a mediator on the causal pathway by mendelian randomization analysis.

METHODS

Two-sample bidirectional mendelian randomization was performed to assess the causal effects of cardiometabolic traits on AV block and examine causality inversely. The exposures of interest included body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glucose, fasting insulin, low-density lipoprotein, high-density lipoprotein, and triglyceride. Multivariable mendelian randomization was then conducted to disentangle the effect of each significant exposure. Mediation effect of CAD on the causal pathways were estimated by two-step, two-sample mendelian randomization.

RESULTS

Genetically predicted elevation of BMI (odds ratio [OR] 1.40; 95% confidence interval [CI] 1.10-1.78; P = .006), SBP (OR 1.02; 95% CI 1.00-1.03; P = .015), and DBP (OR 1.04; 95% CI 1.01-1.07; P = .005) were significantly associated with increased AV block risk. Effects of the other exposures were insignificant. There were no reverse causal effects. Multivariable mendelian randomization showed causal effects of increased BMI, SBP, and DBP on AV block after mutual adjustment. CAD mediated 14.20% (8.82%, 16.46%), 26.32% (25.00%, 26.47,%) and 12.20% (7.69%, 15.94%) of AV block risk from BMI, SBP and DBP, respectively.

CONCLUSION

Elevated BMI, SBP, and DBP exhibited causal effects on AV block. The impacts were partly mediated by CAD.

Association Between New-Onset Type 2 Diabetes and Cardiac Conduction Diseases: A Prospective Cohort Study

BACKGROUND

Cardiac conduction diseases can lead to life-threatening outcomes. However, the evidence on risk factors for conduction disease that is needed to underpin prevention strategies is limited. The present study aimed to determine the association between type 2 diabetes and cardiac conduction diseases.

METHODS AND RESULTS

This study included 101 080 participants free of prevalent diabetes and cardiac conduction diseases at baseline from the Kailuan Study. All participants were monitored biennially until December 31, 2020. During follow-up, 14 397 participants were diagnosed as having type 2 diabetes. For each case subject, 1 control subject was randomly selected, matched for age (±1 year) and sex. The final analysis comprised 10 744 case-control pairs. Cox regression models with age as the underlying time scale were used. During a median follow-up of 5.46 years, 571 incident events occurred, including 164 atrioventricular blocks, 414 bundle-branch blocks (BBBs), 274 right BBBs, and 210 left BBBs. After adjustment for potential confounders, participants with type 2 diabetes diagnosed had greater relative risks for most outcomes relative to controls, with hazard ratios of 1.42 (95% CI, 1.18-1.67) for conduction diseases, 1.40 (95% CI, 1.00-1.96) for atrioventricular blocks, 1.43 (95% CI, 1.16-1.75) for BBBs, and 1.69 (95% CI, 1.15-2.49) for left BBBs. In contrast, no association between diabetes and right BBB was observed.

CONCLUSIONS

In this study, participants with type 2 diabetes are at an increased risk of cardiac conduction disease but not associated with the development of right BBB.

U-Shaped Association Between Monocyte-Lymphocyte Ratio and Risk of Cardiac Conduction Block

Purpose

Inflammation plays a critical role in the development of cardiac conduction block (CCB), which is associated with an increased risk of morbidity and mortality. The monocyte-lymphocyte ratio (MLR) acts as a novel inflammatory marker; however, its association with CCB has not yet been studied. This study aimed to investigate the association between MLR and CCB risk.

Patients and Methods

In total, 82,472 CCB-free participants were identified from the Kailuan study. MLR was calculated using the monocyte count/lymphocyte count. The participants were stratified based on quartiles of MLR levels. Incident CCB and its subtypes were ascertained from electrocardiograms at biennial follow-up visits. The Cox proportional hazards model and restricted cubic spline analysis were used to investigate the association between MLR with CCB and its subtypes.

Results

During a median follow-up of 10.4 years, 3222 incident CCB cases were observed. A U-shaped association was observed between MLR and CCB risk (Pnonlinearity <0.05). After multivariate adjustment, individuals in the highest MLR quartile had a hazard ratio (HR) of 1.212 (95% CI: 1.097-1.340; Q4 vs Q2), while those in the lowest MLR quartile had an HR of 1.106 (95% CI: 1.000-1.224; Q1 vs Q2). Sensitivity and subgroup analyses yielded consistent results. The U-shaped association persisted for atrioventricular block (AVB) in subtype analyses.

Conclusion

MLR was significantly associated with an increased risk of new-onset CCB. Assessing MLR may have clinical relevance for predicting CCB risk, providing valuable insights for preventive strategies and patient management.

Pre-Registered Clinical Trial Number

The pre-registered clinical trial number is ChiCTR-TNC-11001489.

Obesity and Cardiac Conduction Block Disease in China

Importance

Although a high body mass index (BMI) has been found to be associated with increased risk of cardiac conduction block (CCB) in older adults, no further studies have investigated the association between obesity and CCB in the general population.

Objective

To investigate the association between obesity and CCB, including its subtypes.

Design, Setting, and Participants

This cohort study used data from participants in the Kailuan Study in China (2006-2018) who had completed a physical examination in 2006 (baseline) and had not experienced CCB before baseline. Data analysis was conducted from March to September 2023.

Exposures

Obesity status was defined by BMI in 3 groups: normal weight (18.5 to <24), overweight (24 to <28), and obesity (≥28).

Main Outcome and Measures

The primary outcome was CCB, which was diagnosed from standard 12-lead electrocardiography. The primary end point included high-grade atrioventricular block (HAVB), complete right bundle branch block, complete left bundle branch block, left anterior fascicular block (LAFB), and left posterior fascicular block. First-degree atrioventricular block (FAVB), second-degree type 1 AVB, HAVB, complete and incomplete right and left bundle branch block, LAFB, and left posterior fascicular block were considered separately as secondary end points.

Results

Among 86 635 participants (mean [SD] age, 50.8 [11.9] years; 68 205 males [78.7%]), there were 33 259 individuals with normal weight (38.4%), 37 069 individuals with overweight (42.8%), and 16 307 individuals with obesity (18.8%). The mean (SD) follow-up was 10.6 (3.07) years. In the multivariable Cox proportional hazards regression analysis, obesity was associated with an increased risk of incident CCB (hazard ratio [HR], 1.21; 95% CI, 1.04-1.42) vs normal BMI. In secondary analysis, obesity was associated with an increased risk of FAVB (HR, 1.44; 95% CI, 1.21-1.73), HAVB (HR, 1.99; 95% CI, 1.03-3.82), and LAFB (HR, 1.29; 95% CI, 1.03-1.62) vs normal BMI. There was no association between obesity and other CCB subtypes. Obesity was associated with a greater increase in risk of CCB vs normal BMI in older (aged ≥65 years; HR, 1.44; 95% CI, 1.05-1.96) vs younger (aged <65 years; HR, 1.13; 95% CI, 0.96-1.34) participants (P for interaction < .001) and those with diabetes (HR, 2.16; 95% CI, 1.24-3.76) vs without diabetes (HR, 1.19; 95% CI, 1.02-1.39) (P for interaction = .02).

Conclusions and Relevance

This study found that obesity was associated with an increased risk of CCB, with greater increases in risk for FAVB, HAVB, and LAFB. Individuals who were older and those who had diabetes had larger increases in risk.

Elevated high-sensitivity C-reactive protein levels increase the risk of new-onset cardiac conduction disorders

BACKGROUND

Previous studies have reported that inflammatory responses can promote the onset of cardiovascular diseases; however, its association with cardiac conduction disorders remains unclear. The present community-based cohort study aimed to elucidate the effects of inflammatory responses on the risk of developing cardiac conduction disorders.

METHODS

After the exclusion of participants failing to meet the inclusion criteria, 86,234 eligible participants (mean age: 50.57 ± 11.88 years) were included. The participants were divided into high-sensitivity C-reactive protein (hsCRP)  ≤  3 mg/L, and hsCRP > 3 mg/L groups based on hsCRP values. Multivariate Cox proportional hazard model was used to analyze the relationship between inflammatory responses and various cardiac conduction disorders.

RESULTS

After adjusting for confounding factors, we observed that compared with the hsCRP ≤ 3 mg/L group, the hsCRP > 3 mg/L group exhibited increased risks of atrioventricular block (hazard ratio [HR]:1.64, 95%confidence interval [CI] 1.44-1.87) and left (HR:1.25, 95% CI 1.07-1.45) and right bundle branch block (HR:1.31, 95% CI 1.17-1.47). Moreover, the risk of various cardiac conduction disorders increased for every 1 standard deviation increase in log (hsCRP). The restricted cubic spline function confirmed a linear relationship between log (hsCRP) and the risk of developing cardiac conduction disorders (All nonlinearity P > 0.05).

CONCLUSIONS

High hsCRP levels are an independent risk factor for cardiac conduction disorders, and hsCRP levels are dose-dependently associated with the risk of conduction disorders. Our study results may provide new strategies for preventing cardiac conduction disorders.