Air Pollution, Sleep-Disordered Breathing, and Biomarkers of Sudden Cardiac Death Risk in Resource-Limited Settings

About This Grant

ABSTRACT Air pollution is a significant global public health challenge, particularly in low- and middle-income countries (LMICs), where populations face substantial dual exposure to ambient and indoor air pollution, primarily from biomass fuel combustion. Fine particulate matter ≤2.5 microns in diameter (PM2.5) is a major contributor to morbidity and mortality. Previous studies have demonstrated associations between PM2.5 exposure, a higher prevalence of sleep-disordered breathing (SDB), and increased autonomic dysfunction. However, most of these studies have been conducted in high-income countries, limiting their applicability to resource-limited settings where PM2.5 exposure is substantially higher. As a result, the interaction between PM2.5 exposure and SDB and their effects of autonomic dysfunction remains poorly understood in LMICs. This knowledge gap is particularly concerning given the downstream effects of autonomic instability, including heightened cardiac repolarization lability which is a key risk factor for sudden cardiac death (SCD). The interplay between SDB-related intermittent hypoxemia and elevated PM2.5 exposure may amplify cardiac risks, as reflected by the QT Variability Index (QTVI), a validated electrocardiographic (ECG) biomarker of SCD. To address these critical gaps, this study has two specific aims: (1) evaluate the association between elevated PM2.5 exposure and the prevalence of SDB, defined as an apnea-hypopnea index (AHI) ≥5 events per hour, in a Ugandan cohort; and (2) investigate whether elevated PM2.5 exposure is associated with ECG biomarkers of SCD, independent of SDB severity and other cardiovascular risk factors, in the same cohort. This cross-sectional study leverages over a decade of epidemiological research experience in urban and rural Uganda. To achieve these aims, the study will deploy personal air pollution monitoring devices and home-based polysomnography, including single-lead ECG tracings, to collect granular data on PM2.5 exposure, SDB severity, and ECG biomarkers (e.g., QTVI). We hypothesize that elevated PM2.5 exposure will be associated with increased SDB prevalence and higher QTVI values through a dose-dependent mechanism linking air pollution to heightened cardiac risk. By integrating rigorous statistical modeling and sensitivity analyses, this research will provide critical insights into the interactions between poor air quality, SDB, and cardiac repolarization lability. The findings will inform public health policies, guide the design of targeted interventions to improve air quality, and mitigate risks for SCD in LMIC settings.