# Presentation: 005210

## Associations between Air Pollutants and Asthma Exacerbations in New York City 

**Associations between Air Pollutants and Asthma Exacerbations in New York City **
- GM Recer1, PL Kinney2, SA Hwang1 and _DA Luttinger_1
- 1Division of Environmental Health Assessment, Center for Environmental Health, New York State Department of Health, Troy NY
- 2Columbia University School of Public Health, New York NY

**Acknowledgements**
- Support for the study provided by New York State Department of Health,
- New York State Department of Environmental Conservation, New York State Energy Research and Development Authority and the Agency for Toxic Substances and Disease Registry (US Dept of Health and Human Services)
**Disclaimer**
- The findings presented here have been peer reviewed by the federal funding agency (ATSDR) but are preliminary pending receipt of final clearance and ATSDR publication.

**Abstract**
- We sought to evaluate temporal associations between a panel of air contaminants and asthma emergency department (ED) visits in communities in the Bronx and Manhattan in New York City (NYC). Time-series analysis was used to determine whether and to what extent various air contaminants were associated with acute asthma exacerbations and whether the magnitude of the air pollution effect differed in the two communities.  Air pollutant data were collected over approximately a two year period from January 1999 through November 2000 at centrally-located measurement stations in each community sampling a broad range of contaminants including ozone, sulfur and nitrogen oxides, particulate matter (PM2.5 and PM10), acidic and basic gases, carbonyl compounds and bioaerosols.  Samples for PM2.5 components including sulfate, elemental and organic carbon and metals were also collected. ED data on asthma visits for the corresponding dates were collected from the 22 hospitals throughout NYC that served the communities surrounding the air monitoring stations. From each hospital, data for patients who lived in zip code areas within approximately 1.5 miles of either measurement site were extracted. We used Poisson regression to test for effects of 14 key air contaminants on daily ED visits, with control for temporal cycles, temperature, and day of week effects.  The core analysis utilized the average exposure for 0-4 day lags.  Sensitivity analyses examined individual lag effects.
- Concentrations of air contaminants were generally similar in the two communities, with mean levels tending to be slightly higher in Manhattan in most cases.  Mean ozone and total pollen levels were significantly higher in the Bronx, compared to Manhattan.  In single-pollutant models, five of 14 key pollutants had statistically significant effects on asthma ED visits in the Bronx: maximum 8 hour ozone, 24 hour nitrogen dioxide, 24 hour sulfur dioxide, 24 hour PM2.5 and maximum 1 hour PM2.5. The results suggest that these pollutants had a statistically detectable impact on acute asthma ED visits in a community with a relatively high baseline rate of acute asthma exacerbations.  Significant associations between asthma ED visits and individual PM2.5 components were not observed. No statistically significant pollution effects were observed in the Manhattan community.  Our findings of more significant air pollution effects in the Bronx likely relate, in part, to greater statistical power for identifying effects in the Bronx where baseline ED visits were greater, but may also reflect greater sensitivity to air pollution effects in the Bronx. In two-pollutant and three-pollutant regression models, ozone and sulfur dioxide, and to a lesser extent, maximum one-hour PM2.5, were the most robust pollutants. The more robust health impacts observed for daily maximum PM2.5 concentration compared to the 24 hour mean suggest that peak exposures may have larger health impacts.   These associations with health effects in the Bronx occurred at ambient air levels that are below the current short-term National Ambient Air Quality Standards.

**Figure 1.  Study Locations.  Cases identified based on residence in shaded zip codes**

- 14 key analytes; single-, two- & three-pollutant models
- Missing pollutant observations were filled in by regression
- Estimation of missing values changed overall means by <10%
- Outcome Measure -- Daily Emergency Department (ED) visits for primary diagnosis of asthma and control conditions (Table 2).
- Cases defined by residence zip code areas within approximately 1.5 mile radius of ambient air monitoring stations (Figure 1).
- GLM with spline smoothing for Season, Temperature
- Day-of-week class variable added to model
- 0-4 day cumulative lag used to account for variability in lag structure (e.g. Figure 2) and observed delay in seeking ED asthma care
- Relative Risks expressed as proportional change in ER visits associated with an increase in pollutant concentration equal to the pollutant’s overall daily mean during the study (Table 1)

**Methods -- Core Model Development**

**Table 1.  Summary statistics [mean (standard deviation)] for pollutants included in Time Series Models.  **The values represent summary statistics of all daily observations from January, 1999 – November, 2000.

- Table 4. **Relative risks from regressions based on daily maximum hourly (SO****2**** and NO****2****) or daily maximum three-hour (elemental and organic carbon) air levels**. Bold text indicates statistical significance at 0.05 level.

**Results  -- Multi-Pollutant Models**

**Summary & Conclusions**

**Table 6.  Relative risks (95% confidence intervals) for control ED visits.  **Results are shown for the five pollutants that showed significant associations with asthma ED visits in the Bronx.  RR per mean increment for each pollutant from Table 1. Bold text indicates statistical significance at the 0.05 level.

**Results  -- Control Health Outcomes**

- The results suggest that the criteria pollutants PM2.5, SO2, O3 and NO2 had a statistically detectable impact on acute asthma ED visits in a community with a relatively high baseline rate of acute asthma exacerbations.
- In two-pollutant and three-pollutant regression models, O3 and SO2, and to a lesser extent, maximum one-hour PM2.5, were the most robust pollutants.
- It is of particular interest that we observed more robust health impacts of the daily maximum PM2.5 concentration compared to the 24 hour mean, suggesting that peak exposures may have larger health impacts with respect to acute asthma exacerbations.
- These associations with health effects in the Bronx occurred at ambient air levels that are below the current short-term National Ambient Air Quality Standards.
**Limitations**
- Recent evidence (e.g., Koutrakis, Sarnat et al.) suggests the validity of ambient air monitors as a surrogate for personal exposure may vary among analytes.
- Five day exposure window could capture asthma ER visits with either slow or sudden progression, but could also weaken or mask associations (e.g., if pollutant has rapid onset, short lasting effect).
- Lack of statistically significant effects in Manhattan may reflect less statistical power in that study area, at least for cases where Manhattan RRs are similar to Bronx RRs.
- Positive but non-significant effects for control conditions may suggest some degree of overestimation of risk by the statistical model used.
**Recommendations**
- US EPA should consider the findings in this study and others identifying respiratory health effects associated with SO2 concentrations below current standards during their 5-year review of the SO2 NAAQS.
- Future time-series studies examining associations between ambient air pollutants and health outcomes would benefit from direct evaluation of the relationship between personal exposure and regional monitoring data.
- More research should be conducted to try to determine if peak, short-term (e.g. hourly) elevated concentrations of PM2.5 are more strongly associated than daily average concentrations with asthma and other health endpoints.  If the science is sufficiently strong, consideration should be given to the effects of short-term PM2.5 excursions in future reviews of the particulate matter NAAQS.
- The high correlations between pollutants (including components of PM2.5; data not shown) make it difficult in these epidemiologic studies to confidently identify critical compounds.  Alternative strategies to address this question should be considered in the future.
- Further evaluation of the statistical methods employed in time-series epidemiological studies is warranted, based on the suggestion of possible model bias indicated by our analysis of control outcomes.
- To the extent that targeted community based asthma interventions are planned with respect to air pollution messages, higher priority should be given to communities with larger asthma burdens.

**Results  -- Single Pollutant Models**