Association between exposure to particulate matter and heart rate variability in vulnerable and susceptible individuals: Application of the Bayesian kernel machine regression model

Abstract Particulate matter (PM) has various health effects, and individuals are simultaneously exposed to these factors. Vulnerable and susceptible individuals are more sensitive to environmental factors than nonvulnerable individuals. Exposure to PM causes cardiovascular diseases. Heart rate variability (HRV) is a biomarker that may be used to identify cardiovascular diseases, and sensitive monitoring of HRV is required. Most previous studies have evaluated exposure using environmental pollution monitoring devices located in various districts. There is a lack of research exploring the relationship between environmental pollutant exposure in personal living spaces and HRV using both indoor and outdoor measurement devices. This study aimed to investigate the association between exposure to PM and HRV using a model capable of multi-substance analysis in short-term exposures, in vulnerable and susceptible individuals, including patients with environmental disease (patients with arrhythmia, chronic airway disease, and stroke patients) and vulnerable populations (residents of an industrial complex area, the elderly). We measured PM1.0, PM2.5, PM10, and digital biomarkers in 97 participants. We evaluated the impact of short-term PM exposure on 24-h HRV over five days by measuring indoor and outdoor exposure using personalized monitoring equipment and ECG monitoring via wearable devices. The PM was calculated as a daily cumulative value and divided into days with high and low cumulative concentrations. The association between exposure to single particulate and complex mixtures and HRV was compared using multiple linear regression and Bayesian kernel machine regression (BKMR). This study found that HRV showed a negative trend with increased PM exposure on days with high cumulative PM concentrations, with statistically significant associations observed between higher PM concentrations and decreased HRV on days with high exposure. The subgroup analysis revealed that patients with chronic airway disease and residents of industrial complex areas exhibited stronger negative correlations between exposure to PM and HRV. These associations were more pronounced with complex exposure to PM1.0, PM2.5, and PM10. In short-term exposure, it was confirmed that exposure to single and complex PM is negatively associated with HRV, and this relationship varies depending on the sensitive characteristics of individuals. Integrating indoor and outdoor personalized exposure assessments with 24-hour ECG monitoring has reinforced our understanding of the complex interactions between PM and health. Our findings indicate that even 'acceptable' PM levels can harm HRV, suggesting that current thresholds may not adequately protect sensitive individuals. This highlights the need for more stringent, particle size-specific standards for at-risk groups.