Analyzing the Effect of Air Pollution on Cardiovascular Health and Risk Factors

As a major public health concern, air pollution adds to the already overwhelming burden of cardiovascular disease. In this paper, we analyze the role of major risk factors involved in disease development and progression due to air pollution exposure on cardiovascular health. In this manuscript, we present a new predictive model, the Pollution- Cardiovascular Health (PCH) Model that estimates cardiovascular risk associated with ambient air pollutant exposure. The person and the place: PCH Model combines environmental context with patient health records for a full risk picture. The PCH Model uses state-of-the-art statistical and machine learning algorithms to consider parameters describing the type of pollutant, concentration, exposure duration, as well as individual health characteristics. This complete view permits extra correct & individualized risk predictions. In comparison, our results show the superior predictive efficiency and stability of the PCH Model. All performance improvements of the PCH Model as compared to two other baselines were statistically significant supporting its superior predictive capacity over both tested schemes. The results highlight the need for public health strategies and policies to lower air pollution concentrations, with potential benefits on cardiovascular risk factors. In conclusion, the PCH Model is an important improvement in cardiovascular disease predictive modeling and can provide a number of public health implications for interventional strategies as well as policy implementations. Given the credibility and reliability of an integrated environmental and health data to assess cardiovascular risk, that PCH Model approach can help healthcare providers as well as policymakers with strategies in place for mitigating air pollution adverse effects on development.