Table 1

Poisson regression model between the air pollutant and hemorrhagic fever with renal syndrome
Time lag Univariate Multivariate*
RR (95% CI) P RR (95% CI) P
No time lag 0.998 (0.995–1.000) .025 1.013 (1.008–1.017) < .001
1–month lag 0.972 (0.970–0.975) < .001 1.001 (0.997–1.004) .785
2–month lag 0.938 (0.935–0.940) < .001 0.991 (0.987–0.995) < .001
3–month lag 0.933 (0.931–0.936) < .001 0.983 (0.979–0.987) < .001
4–month lag 0.964 (0.961–0.966) < .001 0.992 (0.988–0.996) < .001
5–month lag 0.997 (0.995–1.000) .022 0.991 (0.988–0.995) < .001
6–month lag 1.024 (1.022–1.026) < .001 1.005 (1.002–1.008) .001
7–month lag 1.036 (1.034–1.037) < .001 1.006 (1.004–1.009) < .001
8–month lag 1.031 (1.030–1.033) < .001 1.002 (1.000–1.005) .036
9–month lag 1.016 (1.014–1.018) < .001 0.999 (1.012–1.031) .360
10–month lag 1.005 (1.002–1.007) < .001 0.993 (0.989–0.997) .001
11–month lag 1.000 (0.998–1.002) .827 0.997 (0.993–1.002) .208
12–month lag 0.990 (0.988–0.992) < .001 0.999 (0.995–1.003) .572

CI confidence interval, RR relative risk.

Dependent variable is the occurrence of hemorrhagic fever with renal syndrome.

*Adjusted for seasonality and climate variables.

Han et al.

Han et al. BMC Public Health 2013 13:347   doi:10.1186/1471-2458-13-347

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