Table 1. Summary estimates for studies of PM10 and daily mortality by GAM or non-GAM statistical model and by single-city or multicity study design.
| Studies |
No. of estimates |
Summary
Estimate |
95% CI |
| 1 No numerical estimate for 95% CI given. Graphical representation of marginal posterior distribution for PM10 indicated that effect was very unlikely to be due to chance. Note that in the paper by Dominici et al. (2002), the pooled estimate using default convergence criteria is 0.41 (posterior standard error 0.05). We have chosen the estimate given in the earlier published report (Samet et al., 2000) |
| GAM |
|
|
|
| All studies |
172 |
0.60 |
(0.52, 0.68) |
| NMMAPS |
90 |
0.5 |
No numerical estimate1 |
| APHEA 2 |
21 |
0.6 |
(0.4, 0.8) |
| Single city studies |
61 |
0.68 |
(0.57, 0.79) |
| Single city studies (adjusted for publication bias) |
|
0.6 |
(0.5, 0.8) |
| Non-GAM |
|
|
|
| Single city studies |
26 |
0.55 |
(0.38, 0.73) |
| Single city studies (adjusted for publication bias) |
|
0.4 |
(0.2, 0.6) |
| All Studies (GAM and Non-GAM) |
198 |
0.59 |
(0.52, 0.66) |
% change in mortality per 10 µg/m3 increase in
PM10
Source: WHO Regional Office for Europe
Health Aspects of Air Pollution - answers to follow-up questions from CAFE (2004), Section 5.5
Related publication:
Other Figures & Tables on this publication:
Table 2. Summary of meta-analysis of time-series studies published during the period 1996–2001
Table 3: Summary of studies measuring short-term effect on lung function
Table 4: Short-term effects of ozone on lung function, biological and other responses
Fig. 1: Funnel plot of black smoke and "daily all cause mortality" in 47 studies.
Table 1. Summary estimates for studies of PM10 and daily mortality by GAM or non-GAM statistical model and by single-city or multicity study design.
