PM 2.5 and Asthma-Related ER Visits in California Study

Study on the relationship between PM 2.5 levels and asthma-related emergency room visits in California. The research analyzed data from 16 counties over 6 years, using different regression methods to explore correlations. Results suggest a slight negative correlation, indicating air quality may not be a primary factor in asthma-related ER visits. The study highlights the need for more data across a broader demographic range for conclusive findings.

• PM 2.5
• Asthma
• California
• Air Quality
• Regression Methods

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1. PM 2.5 and Asthma-Related Emergency Room Visits in California Maisie Hugdahl 4.24.2014 EAS 4480 Term Project

2. Introduction Many studies have found a link between PM 2.5 and asthma WHO cited more hospital admissions This study s focus: % of days over the US standard (35 micrograms/m3 per 24 hours) # of emergency room visits due to asthma (age- adjusted, per 10,000)

3. Data Source California Environmental Health Tracking Program Data for Los Angeles % Days Above Standard # ER Visits Time Time **Purple line is California average

4. Data Distribution 16 counties 6 years (2001-2006)

5. Methods Apply three different regression methods Compare the slopes and R2 values Find the correlation coefficient Apply the bootstrap and jackknife methods Plot the histograms Compare results to other studies

6. Regressions Type LSR PCA RMA Slope -0.0524 -0.0633 0.4194 R2 0.0156 0.0228 0.0156 Correlation Coefficient Upper Limit Lower Limit -0.1250 0.0808 -0.3205

7. Bootstrap Normally Distributed Normally Distributed

8. Jackknife Normally Distributed Normally Distributed

9. Individual County: LA Type LSR PCA RMA Slope 0.0581 0.0586 0.1072 R2 0.2940 0.2988 0.2940 Correlation Coefficient Upper Limit Lower Limit 0.5422 0.9401 -0.4810 Not enough data!

10. Conclusions Contradictory to other studies Seems to be a slight negative correlation Air quality isn t one of the main causes for asthma- related ER visits? Threshold is too low? More sensitive to different age groups? Need more data Longer time span, more counties