To assess global information-seeking behavior related to air pollution (AP) and its cardiovascular implications using Google Trends data.
Approach:
Data Analysis: A retrospective analysis of Google Trends data from June 2020 to June 2025 was conducted, focusing on specific AP and cardiovascular disease (CVD) search terms.
Statistical Methods: Pearson correlation coefficients, partial correlation analysis, ARIMAX modeling, and Granger causality testing were used to evaluate temporal and correlational patterns.
Key Findings:
Moderate positive correlations were found between air pollution and cardiovascular disease-related search terms (r = 0.275; 0.295; 0.386, p < 0.01).
Search volumes were highest for 'Chest Pain' and 'High Blood Pressure', while engagement for PMâ‚‚.â‚… and AQI was low.
Twenty-seven countries exhibited concurrent air pollution and cardiovascular disease information-seeking behavior.
Interpretation:
The analysis indicates moderate information-seeking behavior linking air pollution and cardiovascular disease.
Limitations:
The study relies on Google Trends data, which may not fully represent the population's health information-seeking behavior.
Search terms may not capture all relevant aspects of AP and CVD.
Conclusion:
Findings highlight the association between air pollution and cardiovascular health information-seeking behavior.
