Global Heart (Aug 2020)
A Global Analysis of Associations between Fine Particle Air Pollution and Cardiovascular Risk Factors: Feasibility Study on Data Linkage
Abstract
Background: This paper presents a feasibility study of data linkage between global air pollution data and clinical medical data to assess the associations of PM2.5 with cardiovascular risk factors. Methods: Cardiovascular risk factor data were obtained from the SUrvey of Risk Factors (SURF) for coronary heart disease (CHD) patients from 10 countries in Europe, Asia, and the Middle-East. Annual average PM2.5 concentrations were estimated using recent global WHO PM2.5 maps combining satellite and surface monitoring data for the location of the 71 participating centers. Associations of PM2.5 with risk factors were assessed by mixed-effect generalized estimation equation models adjusted by sex, age, exercise, body mass index, and smoking. In the final model there was further adjustment for country. Results: Linkage between cardiovascular risk factor data and PM2.5 via the postal address of participating hospitals was shown to be feasible, however with several limitations noted. Eight thousand three hundred and ninety two patients (30% women) were included. Globally, an increase of 10 μg/m3 in PM2.5 was significantly associated with decreased BP and increased glucose. After controlling for country, an increase of 10 μg/m3 in PM2.5 was associated with decreased BP and increased LDL (SBP: –0.45 mmHg [95% CI: –0.85, –0.06]; DBP: –0.47 mmHg [–0.73, –0.20]; LDL: 0.04 mmol/L [0.01, 0.08]). The association with glucose attenuated (0.08 mmol/L [–0.23, 0.16]). Conclusion: It is feasible to link PM2.5 and cardiovascular risk factors but it is still challenging to interpret these observed associations due to unavailability of potential confounders. After country adjustment, PM2.5 was associated with small increases in LDL and small decreases in BP. Highlights: There are limited studies on the association between air pollution and cardiovascular risk factors for patients with established coronary heart disease in low- and middle-income countries; Data linkage is an efficient and cost-effective method to maximize the use of existing data to investigate more health related research questions; It is feasible to determine global associations of air pollution and cardiovascular risk factors by data linkage but it is still challenging in terms of interpretation.
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