Increase in Medical Emergency Calls and Calls for Central Nervous System Symptoms during a Severe Air Pollution Event, January 2013, Jinan City, China
Supplement1 Daily values of PM10 in January haze event 2013 and six winter months of 2011 and 2012, Jinan City
1 2 3 4 5 6 7
100200300400500600700
Period
Daily average concentration of PM10
Jan 2011 Feb 2011 Dec 2011 Jan 2012 Feb 2012 Dec 2012 Jan 2013 Daily concentration of PM10 (μg/m3)
Supplement 2 Coefficients and standard error of average temperature, relative humidity and PM10 on health problems calls in January haze e vent 2013 compared with reference period, Jinan City
Health problems calls
January haze event 2013 controlling for average temperature and relative humidity a
January haze event 2013
controlling for with average temperature and relative humidity and plus PM10
b
Average temperature Relative humidity Average temperature Relative humidity PM10
Non-accidental emergency calls 0.0025 (0.0018) 0.0005 (0.0003) 0.0024 (0.0019) 0.0005 (0.0003) 0.0001 (0.0001) Calls for central nervous system
syndromes -0.0051 (0.0034) -0.0002 (0.0006) -0.0047 (0.0035) -0.0001 (0.0006) -0.0001 (0.0002) Headache -0.0101 (0.0235) 0.0022 (0.0039) -0.0117 (0.0239) 0.0017 (0.0049) 0.0004 (0.0012) Dizziness -0.0001 (0.0089) 0.0006 (0.0015) -0.0007 (0.0091) 0.0005 (0.0016) 0.0001 (0.0004) Syncope 0.0001 (0.0006) -0.0001 (0.0001) 0.0012 (0.0071) -0.0003 (0.0013) -0.0003 (0.0004)
Coma -0.0059 (0.0056) -0.0001 (0.0009) -0.0068 (0.0057) -0.0004 (0.0010) 0.0002 (0.0003) Convulsions -0.0134 (0.0093) -0.0007 (0.0016) -0.0120 (0.0095) -0.0003 (0.0017) -0.0003 (0.0005)
Paralysis -0.0413 (0.0397) 0.0020 (0.0026) -0.0371 (0.0362) 0.0030 (0.0027) -0.0008 (0.0007) Epilepsy 0.0199 (0.0157) -0.0036 (0.0027) 0.0242 (0.0161) -0.0025 (0.0029) -0.0010 (0.0009)
a showed no positive associations of average temperature and relative humidity with any health problems calls.
b showed no positive associations of average temperature and relative humidity, PM10 with any health problems calls.
Supplement 3 Effects of PM10 related to non-accidental emergency calls and calls for CNS.
Methods
A generalized linear model (GLM) with a quasi-Poisson regression was used to estimate the associations of PM10 exposures on lag0 day to lag7 day with non-accidental emergency calls and calls for CNS syndromes for the study period and reference period. Considered the maximum lag effect occurred in lag2 day, the results showed the lag pattern of PM10 from lag0 to lag4. To control potential confounding effects, variables of daily average temperature and relative humidity (RH), year, day of week (DOW) and public holidays were included in the regression model. Only wither months were enrolled in this model, the average temperature and RH were added in the regression model without natural cubic spline smoothing. Excess relative risk (ERR) and 95% confidence intervals (95% CI) were estimated for PM10 with a 10μg/m3 increase. The model used the following formula 1:
logE(Yt)=Intercept+β1Zt+β2Temperature+β3RH+β4Year+β5DOW+β6Holiday (1)
where E(Yt) is the expected daily non-accidental emergency calls and calls for CNS syndromes, respectively, at day t with Var(Yt)= φE(Yt), φ is the over-dispersion parameter; Zt is PM10 exposure variables, lag0 day to lag4 day; Year is the dummy variable for year of 2011, 2012 and 2013; DOW is the dummy variable for day of the week; Holiday is a binary variable of 1 for holiday days and 0 for not holiday days. β1, β2, β3, β4, β5, β6 are the coefficients for Zt, Temperature, RH, Year, DOW and Holiday.
In order to control the confounding effect of Ozone (O3), a sensitivity analysis of two air pollutants regression model was conducted. ERRs and 95%CI were estimated for PM10with a 10μg/m3 increase on lag0 day to lag4 day controlled O3, and compared with single pollutant regression model.
Results
TableS1 showed the lag pattern of PM10’s effects on non-accidental emergency calls and calls for CNS syndromes in January haze event 2013 and reference period. Increased associations were observed for most lag days, but none was significant. The stronger association of non-accidental emergency calls with PM10 occurred on lag2 day, which showed the same trend in calls for CNS syndromes. Consistently results were observed for two pollutants in the regression model.
Table S1. Excess relative risk (ERR) and 95% confidence intervals (95% CI) of non-accidental emergency calls and calls for central nervous system syndromes associated with a 10μg/m3 increase in PM10 exposure on lag0-lag4 day and controlled with O3, respectively, Jinan City
Health problems calls Single pollutant regression model Two pollutants regression model Non-accidental emergency calls
Lag0 0.01 (-0.23, 0.24) -0.04 (-0.28, 0.20)
Lag1 0.10 (-0.12, 0.33) 0.10 (-0.13, 0.32)
Lag2 0.16 (-0.05, 0.38) 0.17 (-0.05, 0.38)
Lag3 0.11 (-0.10, 0.32) 0.14 (-0.08, 0.35)
Lag4 -0.03 (-0.23, 0.18) -0.01 (-0.21, 0.19)
Calls for central nervous systemsyndromes
Lag0 -0.10 (-0.54, 0.34) -0.21 (-0.66, 0.24)
Lag1 -0.01 (-0.42, 0.40) -0.03 (-0.44, 0.38)
Lag2 0.24 (-0.16, 0.64) 0.24 (-0.14, 0.65)
Lag3 0.22 (-0.17, 0.61) 0.28 (-0.11, 0.67)
Lag4 -0.03 (-0.40, 0.34) 0.01 (-0.37, 0.38)