Do air pollution and neighborhood greenness exposures improve the predicted cardiovascular risk?

Background Numerous studies show associations between exposure to Particulate Matter and Cardiovascular disease (CVD). Current cardiovascular equations incorporate the major risk factors for CVD. The patients' environment, however, is not incorporated in these equations. Methods In a retrospective analysis, we assessed the contribution of neighborhood greenness and particulate matter (coarse-PM and PM < 2.5 μm–PM_2.5) to the development of CVD by analyzing the change in prediction abilities. We included members of the largest health-care provider in Southern-Israel, who had at least one cardiovascular risk factor (dyslipidemia, diabetes, hypertension or smokers). PM exposure and neighborhood greenness (Normalized Difference Vegetation Index-NDVI) were assessed by satellite-based models. We used pooled logistic mixed regressions to obtain the CVD risks including conventional risk factors (i.e. age, gender, blood-pressure, etc.) and measured the model performance with and without PM and NDVI. Results We included 23,110 subjects, of whom 12% had CVD. Coarse-PM exposure was associated with stroke and Myocardial-Infarction (MI) (OR 1.02,p < 0.01 for both). NDVI was associated with MI: OR 0.72(p < 0.01) for NDVI 0.1–0.2; and OR 0.52(p = 0.270) for NDVI > 0.2. The c-statistics slightly improved from 77.30%–77.40% for the prediction of MI (p = 0.004) and from 75.60%–75.76% for the prediction of stroke (p = 0.027). Calibration was fair in all models. The associations were partially mediated through the patients' comorbidities. Conclusion The negligible improvement in the prediction performance, despite significant associations with PM and NDVI, may be due to partial mediation of these associations through the conventional cardiovascular risk factors, suggesting the importance in assessing the environmental effects on more basic physiological pathways when addressing the contribution to the cardiovascular risk.