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Table 4 Extreme influence analysis of different air pollution factors from 2008 to 2014 using two-pollutant models. Relative risk (RR) and 95% confidence interval (CI) were used to estimate the cumulative influence of air pollution factors in total IS cases

From: Association between short-term exposure to air pollution and ischemic stroke onset: a time-stratified case-crossover analysis using a distributed lag nonlinear model in Shenzhen, China

pollutantextreme-low influenceextreme-high influence
lag0–6lag0–8lag0–10lag0–12lag0–13lag0–14lag0–6lag0–8lag0–10lag0–12lag0–13lag0–14
SO20.98 (0.87,1.10)0.99 (0.87,1.13)1.00 (0.86,1.16)0.99 (0.85,1.17)0.99 (0.84,1.17)0.98 (0.82,1.17)1.14 (0.98,1.32)1.29 (1.09,1.52)1.42 (1.18,1.71)1.50 (1.22,1.84)1.50 (1.21,1.86)1.48 (1.17,1.87)
NO20.88 (0.77,1.00)0.87 (0.75,1.01)0.86 (0.73,1.03)0.86 (0.71,1.04)0.85 (0.70,1.04)0.85 (0.68,1.05)1.32 (1.13,1.54)1.36 (1.14,1.62)1.37 (1.13,1.67)1.37 (1.10,1.70)1.36 (1.08,1.71)1.34 (1.05,1.72)
PM100.81 (0.71,0.92)0.79 (0.68,0.92)0.79 (0.66,0.94)0.81 (0.67,0.97)0.82 (0.67,1.00)0.84 (0.68,1.04)1.09 (0.95,1.26)1.17 (1.00,1.37)1.24 (1.04,1.47)1.26 (1.04,1.53)1.25 (1.02,1.54)1.23 (0.98,1.53)
O31.13 (0.97,1.32)1.17 (0.99,1.38)1.21 (1.00,1.45)1.24 (1.02,1.52)1.27 (1.03,1.56)1.29 (1.03,1.61)1.07 (0.94,1.22)1.11 (0.96,1.28)1.15 (0.99,1.35)1.20 (1.01,1.42)1.22 (1.03,1.45)1.25 (1.04,1.49)
  1. Note: Estimates were generated using a quasi-Poisson regression model combined with time-stratified case-crossover design and distributed lag non-linear model (DLNM), adjusting for meteorological factors, holiday, and time stratum. The extreme-high influence was estimated by the RR of ischemic stroke by comparing the 99th percentile of daily air pollution value to the median value, whereas the extreme-low influence was estimated by comparing the 1st percentile of daily air pollution value to the median value