There were 302,453 hospital admissions for MI in the 21 cities during the study period. shows the counts for all of the cities broken into categories by age group, sex, and previous and secondary diagnosis. shows the distribution of environmental factors by city, including the study period, the total population, PM, AT, and the counts of hospital admissions for MI. The average PM10 across all cities was 27 μg/m3.
Counts of hospital admissions for MI in total and by age group, sex, secondary diagnoses, and previous admissions among residents of 21 U.S. cities.
Counts of hospital admissions for MI and distribution of environmental factors.
We first looked at the lag structure of the association between PM10 and the risk of hospitalization for MI by simultaneously estimating the effect of PM10 from lag days 0 to 2. The combined estimates of percent change in risk [and 95% confidence interval (CI)] of emergency hospitalization for MI are shown in together with the estimate of lag day 0 alone. The PM10 effect is mainly associated with the change in risk on the day of hospitalization; therefore, the rest of the analysis was done for lag day 0. also shows the percent change of the combined estimates for PM10 at lag day 0 from the sensitivity analysis, where the control periods were chosen using the same time-stratified approach but such that exposures on the case day were compared with exposures occurring on days of the same month with the same value of AT (TEMP) as the case day.
Figure 1 Combined random-effect estimated change in risk (and 95% CI) of hospitalization for MI associated with a 10 μg/m3 increase in daily PM10 on the same day and for lag days 0–2. Results are shown for our main model and (only for lag day 0) (more ...)
The results shown in using the two different referent selection schemes are consistent and show a very similar estimated effect. Overall, we found that for each 10 μg/m3 increase in the concentration of PM10, there was a 0.65% (95% CI, 0.3–1%) increase in the risk of hospitalization for an MI among the study population. When matching by AT (TEMP in ), we found a 0.64% (95% CI, 0.1–1.2%) increase. There was no evidence that the variation in effects size estimates by city was greater than would be expected giving their standard errors, with a chi-square value for heterogeneity of 17.8 (21 df, p = 0.6).
shows the results of the stratified analysis to examine effect modification by age group, sex, and previous admissions for atrial fibrillation, COPD, CHF, and diabetes and secondary diagnosis for pneumonia. We did not find a statistically significant modification of effect, but we found that acute or chronic lower respiratory disease had important effects on response to PM10. In subjects with a previous admission for COPD, we found a 1.3% change (95% CI, −0.1 to 2.8) for a 10 μg/m3 increase in PM10 in the risk of hospitalization for MI, whereas the risk was halved in subjects without a previous admission for COPD (0.6%, 95% CI, 0.3–1). In subjects with a secondary diagnosis of pneumonia, we found a 1.4% change (95% CI, −0.8 to 3.6) in the risk of hospitalization for MI, compared with a 0.6% change (95% CI, 0.3–1) in subjects without a secondary diagnosis of pneumonia. No significant heterogeneity was found when combining the stratified results.
Stratified analysis for several effect modifiers: combined random-effect estimated change in risk (and 95% CI) of hospitalization for MI associated with a 10 μg/m3 increase in daily PM10 on the same day. W/out, without.
None of the other effect modifiers we examined (age, sex, CHF, atrial fibrillation, diabetes) showed much evidence for effect modification except perhaps for sex, with a suggestive difference for males (0.9%; 95% CI, 0.2–1.6) versus females (0.5%; 95% CI, 0.05–1.97).
Finally, the shape of the exposure–response relationship between MI hospitalizations and PM10 is shown in . The exposure response is almost linear, but with a steeper slope at levels of PM10 < 50 μg/m3.
Combined random-effect estimated of the dose–response relationship between MI emergency hospital admissions and PM10, computed by fitting a piecewise linear spline, with slope changes at 20 μg/m3 and 50 μg/m3.