Environmental Research 118 (2012) 101–106

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Environmental Research

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Short-term exposure to sulfur dioxide and daily mortality in 17 Chinesecities: The China air pollution and health effects study (CAPES)

Renjie Chen a, Wei Huang b,n, Chit-Ming Wong c, Zongshuang Wang d, Thuan Quoc Thach c,Bingheng Chen a, Haidong Kan a,n, on behalf of the CAPES Collaborative Groupa School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, Chinab SKJ Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Centre for Environment and Health,

Peking University, Beijing, Chinac Department of Community Medicine, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, Chinad Chinese Academy of Environmental Sciences, Beijing, China

a r t i c l e i n f o

Article history:

Received 14 January 2012

Received in revised form

22 June 2012

Accepted 5 July 2012Available online 24 July 2012

Keywords:

Air pollution

CAPES

Sulfur dioxide

Mortality

Bayesian hierarchical models

51/$ - see front matter & 2012 Elsevier Inc. A

x.doi.org/10.1016/j.envres.2012.07.003

esponding authors.

ail addresses: whuang06@gmail.com (W. Hua

kan@gmail.com (H. Kan).

a b s t r a c t

Sulfur dioxide (SO2) is a major air pollutant and has significant impacts upon human health. Few multi-

city studies in Asia have examined the acute health effects of SO2. As part of the China Air Pollution

and Health Effects Study (CAPES), this study aimed at investigating the short-term association between

SO2 and daily mortality in 17 Chinese cities. We applied two-stage Bayesian hierarchical models to

obtain city-specific and national average estimates for SO2. In each city, we used Poisson regression

models incorporating natural spline smoothing functions to adjust for long-term and seasonal trend of

mortality, as well as other time-varying covariates. We examined the associations by age, gender and

education status. As a result, the combined analysis showed that an increase of 10 mg/m3 of two-day

moving averaged SO2 was associated with 0.75% [95% posterior interval (PI), 0.47 to 1.02], 0.83% (0.95%

PI, 0.47 to 1.19) and 1.25% (95% PI, 0.78 to 1.73) increase of total, cardiovascular and respiratory

mortality, respectively. The effects of SO2 appeared more evident among the elderly. These associations

were generally independent of particles with aerodynamic diameter o10 mm (PM10) but did not

persist after adjustment for nitrogen dioxide (NO2). In conclusions, this largest epidemiologic study

of air pollution in China to date suggests that short-term exposure to SO2 is associated with increased

mortality risk; however, these associations may be attributable to SO2 serving as a surrogate of other

substances. Further studies are needed to tackle the independent health effect of SO2.

& 2012 Elsevier Inc. All rights reserved.

1. Introduction

Sulfur dioxide (SO2) is a major air pollutant and has significantimpacts upon human health (Chen et al., 2007). Following thedramatic growth of the economy growth and energy use, SO2

emissions of China have increased remarkably during the last decade(Su et al., 2011). The impacts of SO2 on local health, long-rangetransport, and climate change are gaining more and more attention.Currently, the Chinese government has adopted ‘‘controlling/redu-cing total SO2 emissions’’ as an index to reflect the efficacy of airpollution control strategy in the country.

SO2 is a respiratory irritant and bronchoconstrictor, and hasbeen associated with cardiovascular abnormalities includingdecrease in heart rate variability (Tunnicliffe et al., 2001).

ll rights reserved.

ng),

Multi-city analyses conducted in Europe (Katsouyanni et al.,1997; Sunyer et al., 2003b) and Canada (Burnett et al., 2000)provided evidence supporting the short-term association betweenSO2 and increased risk of cardiorespiratory mortality and mor-bidity. However, recent findings about the independent healtheffect of SO2 remain inconsistent. For example, after adjusting forPM10 (i.e. particles with aerodynamic diameter o10 mm), Sunyeret al. reported statistically significant associations of ambient SO2

with cardiovascular admissions, particularly for ischemic heartdiseases, in seven European cities (Sunyer et al., 2003b); however,the SO2 association with respiratory admission disappeared afteradjustment for PM10 in the same cities (Sunyer et al., 2003a).

China is one of the few countries with highest SO2 levels in theworld (Su et al., 2011). In 2009, the annual average SO2 concen-tration in 113 major Chinese cities was 42 mg/m3 (Kan et al.,2012), which was much higher than reported levels in developedcountries (Katsouyanni et al., 1997; Sunyer et al., 2003a; Sunyeret al., 2003b). However, only a small number of health studies ofSO2 have been conducted in China (Kan and Chen, 2003; Venners

R. Chen et al. / Environmental Research 118 (2012) 101–106102

et al., 2003; Wong et al., 2001); to our knowledge, only 1 multi-city study, the Public Health and Air Pollution in Asia (PAPA)project, has examined the acute health effects of SO2 in four Asiancities, including 3 cities in China (Hong Kong, Shanghai andWuhan) (Kan et al., 2010; Wong et al., 2008). The objective ofthis analysis was to examine the association between SO2 anddaily mortality in 17 Chinese cities. This analysis was a part of theChina Air Pollution and Health Effects Study (CAPES) (Chen et al.,2011a; Chen et al., 2011b).

2. Materials and methods

2.1. Data

The CAPES project included 17 Chinese cities: Anshan, Beijing, Fuzhou,

Guangzhou, Hangzhou, Hong Kong, Lanzhou, Nanjing, Shanghai, Shenyang,

Suzhou, Taiyuan, Tangshan, Tianjin, Urumqi, Wuhan, and Xi’an. Our study areas

were restricted to the urban areas of these cities, due to inadequate air pollution

monitoring stations in the suburban areas.

We obtained daily mortality data of urban residents in Mainland China from

the Municipal Center for Disease Control and Prevention in each city. In Hong

Kong, the source of mortality data was the Census and Statistics Department.

The causes of death were coded according to the International Classification of

Diseases, 10 (ICD-10). The mortality data were classified into deaths due to total

non-accidental causes (ICD-10: A00-R99), cardiovascular disease (ICD-10: I00-

I99), and respiratory disease (ICD-10: J00-J98). For total mortality, the data were

stratified by gender (female and male), and age (0–4, 5–64, 65þ), and in cities not

including Hong Kong, they were also stratified by educational attainment (low:

illiterate or primary school; high: middle school or above). Education has been

used as a surrogate indicator of socioeconomic status (SES) in air pollution

epidemiological studies (Kan et al., 2008). Cause-specific mortality data were

not available in Lanzhou.

We obtained the air pollution data in Mainland China from the National

Air Pollution Monitoring System under the China National Quality Control for air

monitoring network. In Hong Kong, the source of air pollutant concentrations was

from the Environmental Protection Department. In each city, there were 2�13

monitoring stations and data available from two to seven years after 2000 (apart

from Hong Kong with times series data starting from 1996). Air quality indicators

included SO2, PM10, and nitrogen dioxide (NO2). The methods based on ultraviolet

fluorescence, tapered element oscillating microbalance, chemiluminescence were

used for the measurement of SO2, PM10 and NO2, respectively. We collected 24-h

average concentrations for each pollutant. For the calculation of 24-h mean

concentrations, at least 75% of the one-h values must be available on that

particular day. If a station had more than 25% of the values missing for the whole

period of analysis, we excluded the entire station from the analysis. In each city,

the location of monitoring stations were not in the direct vicinity of traffic or

of industrial sources, and were mandated not to be influenced by local pollution

sources and should also avoid buildings, or housing large emitters such as coal-,

waste-, or oil-burning boilers, furnaces, and incinerators. Thus the monitoring

results should reflect the general background urban air pollution level rather than

local sources such as traffic or industrial combustion. In each city, the daily air

pollutants’ concentrations were averaged from the available monitoring results

measurements across various stations.

To allow adjustment for the effect of weather conditions on mortality, we

collected daily meteorological data (mean temperature and relative humidity) in

each city.

2.2. Statistical analysis

We applied two-stage Bayesian hierarchical models to estimate city-specific

and national average associations between SO2 and daily mortality (Dominici

et al., 2006; Peng et al., 2008).

At the first stage, we used the same analytical protocol as the PAPA project to

obtain the city-specific estimates of SO2 (Wong et al., 2008). We applied Poisson

regression models controlling for overdispersion to investigate the SO2-mortality

associations. To control for possible confounding by time trend (long-term and

seasonality trends) of mortality and weather conditions, we used generalized

linear modeling with natural spline (ns) smoothers (Bell et al., 2004). We included

day of the week (DOW) terms as dichotomous variables for each day of the week

from Monday to Saturday. We applied the partial autocorrelation function (PACF)

to guide the selection of model parameters. Specifically, we used 4 to 6 degrees of

freedom (df) per year for time trend for all mortality outcomes. When the absolute

magnitude of the PACF plot was less than 0.1 for the first 2 lag days, we regarded

the basic model as adequate; if this criterion was not met, we used auto-

regression terms to improve the model (Kan et al., 2008). We used residual plots

and PACF plots to examine residuals of the basic model for discernable patterns

and autocorrelation. After establishing the basic model, we introduced the SO2

concentrations and weather conditions in the model. Based on previous literature

(Bell et al., 2004), we used smoothed spline functions with 3 df (for the whole

period of the study) to control for current-day temperature and relative humidity.

At the second stage, we used Bayesian hierarchical models to obtain the

national average estimates for the effect of SO2 (Dominici et al., 2006; Peng et al.,

2008). This approach provides a flexible tool to pool risk estimates while

accounting for within-city statistical error and between-city variability (hetero-

geneity) of the ‘‘true’’ underlying risks. The model produced a posterior probability

distribution of the pooled mean estimates, from which we estimated the

combined log-relative risks as the posterior mean and 95% posterior interval

(PI). We applied the Bayesian hierarchical models to combine city-specific

estimates by using 2-level normal independent sampling estimation with uniform

priors. This procedure has been used in previous multi-city air pollution epide-

miologic studies in the US (Dominici et al., 2006; Peng et al., 2008). We performed

the Chi-square test to examine heterogeneity of the city-specified estimates

(Cochran’s Q test) (Sutton and Higgins, 2008).

Single-day lag models might underestimate the cumulative association of SO2

with mortality (Bell et al., 2004); therefore, we used a 2-day moving average of

current and previous day concentrations (lag 01) for our analyses. To examine the

potential modifiers, we conducted stratified analyses by gender, age and education

for total mortality. We tested the statistical significance of differences between

effect estimates of the strata of a potential effect modifier (e.g. the difference

between females and males) by calculating the 95% confidence interval (95% CI)

as ðQ1�Q2Þ71:96

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiSE

2

1þSE2

2

q, where Q1 and Q2 are the estimates for the two

categories, and SE1 and SE2 are their respective standard errors (SE) (Zeka et al.,

2006).

We performed several sensitivity analyses to explore the robustness of our

findings. First, we fitted both single-pollutant model and multi-pollutant model

(up to 2 pollutants per model) to assess the stability of SO2’s effects. Second, we

conducted sensitivity analyses to test the effect of alternative values of df for time

trend on the estimated SO2 effects. Third, we examined the effects of SO2 with

other lag structures, including both single-day lag (from lag 0 to lag 7) and multi-

day lag (lag 01). Fourth, as temperature with longer lags might have a greater

effect than air pollution than daily mortality, we conducted sensitivity analyses to

explore the effects of temperature with longer lags (including 0–3 days and 0–7

days) on the estimated SO2 effects.

We conducted the first- and second- stage analyses in R 2.13.1 using the

MGCV and TLNISE packages, respectively. We presented the results as the percent

change in daily mortality per 10 mg/m3 increase of SO2 concentrations.

3. Results

Table 1 shows the basic statistics of study periods, population,daily mortality, SO2, and numbers of air monitoring stations in the17 Chinese cities. Additional descriptive information on PM10 andNO2 are provided in Table 1 of the online appendix. The dailymean numbers of total non-accidental, cardiovascular and respira-tory deaths varied according to the size of the city and rangedfrom 11 to 119, from 6 to 54, and from 1 to 16, respectively. Onaverage, cardiovascular and respiratory diseases accounted for44% and 14% of total non-accidental deaths, respectively. Themean SO2 concentrations varied from 18 mg/m3 (Hong Kong) to100 mg/m3 (Urumqi). Generally, the northern Chinese cities hadhigh levels of SO2 (mean concentrations: 66 mg/m3), comparedwith southern Chinese cities (mean concentrations: 41 mg/m3).

Daily levels of SO2 were highly correlated with PM10 and NO2,with mean correlation coefficients as 0.49 and 0.65, respectively.SO2 was weakly correlated with temperature and humidity.

The associations of SO2 (lag 01) with daily mortality varied bycities and causes of deaths (Figure 1). We observed positive andstatistically significant associations of SO2 with total, cardiovas-cular and respiratory mortality in most of the cities we examined.Chi-square tests show significant heterogeneity for the city-specified effect estimates (po0.05). When considering thenational average association for SO2, we estimated an increaseof 0.75% (95% PI: 0.47 to 1.02) of total mortality, 0.83% (95% PI:0.47 to 1.19) of cardiovascular mortality, and 1.25% (95% PI: 0.78to 1.73) of respiratory mortality associated with a 10 mg/m3

increase of SO2.The associations between SO2 and total mortality varied by

gender, age group, and educational attainment (Table 2). The

Table 1Descriptive data on the study period, population, exposure (SO2), outcome (daily death number) and temperature in the CAPES cities.

City Study periodb Population

(million)

Mean number of deaths per day Daily SO2 concentration (mg/m3) No. of air

monitors

Total Cardiovascular Respiratory Min P25 Mean P75 Max

Anshan 2001–2004 2.4 28 14 2 3 10 59 83 570 2

Beijing 2007–2008 12.3 118 54 14 6 46 41 54 248 12

Fuzhou 2004–2006 1.8 16 7 2 4 13 16 17 66 4

Guangzhou 2007–2008 6.5 79 29 15 5 27 50 64 194 9

Hangzhou 2002–2004 2.5 20 7 4 14 36 51 61 132 10

Hong Kong 1996–2002 6.7 84 24 16 1 10 18 22 110 7

Lanzhoua 2004–2008 1.9 19 – – 6 35 66 89 267 5

Nanjing 2007–2010 3.0 40 23 7 8 30 48 61 147 9

Shanghai 2001–2004 8.5 119 44 14 8 28 45 56 183 9

Shenyang 2005–2008 6.4 67 32 6 7 25 55 76 290 2

Suzhou 2005–2008 4.1 34 13 5 4 31 45 54 174 8

Taiyuan 2004–2008 2.6 24 9 2 6 33 77 108 782 9

Tangshan 2006–2008 1.9 19 8 3 7 40 84 110 398 6

Tianjin 2005–2008 1.2 11 6 1 5 32 67 85 356 13

Urumqi 2006–2007 2.3 17 7 2 4 26 100 147 698 3

Wuhan 2003–2005 4.5 58 33 7 7 30 52 66 183 10

Xi’an 2004–2008 3.4 26 12 7 8 30 48 60 260 7

Abbreviations: SO2, sulfur dioxide; CAPES, China Air Pollution and Health Effects Study.a Cause-specific mortality data were not available in Lanzhou.b All CAPES cities used time-series data of full years.

Increase (%) of totalmortality

Nationalaverage

Xi’an

Wuhan

Urumqi

Tianjin

Tangshan

Taiyuan

Suzhou

Shenyang

Shanghai

Nanjing

Lanzhou

HongKong

Hangzhou

Guangzhou

Fuzhou

Beijing

Anshan

Increase (%) ofcardiovascular mortality

Nationalaverage

Xi’an

Wuhan

Urumqi

Tianjin

Tangshan

Taiyuan

Suzhou

Shenyang

Shanghai

Nanjing

Lanzhou

HongKong

Hangzhou

Guangzhou

Fuzhou

Beijing

Anshan

Increase (%) of respiratory mortality

Nationalaverage

Xi’an

Wuhan

Urumqi

Tianjin

Tangshan

Taiyuan

Suzhou

Shenyang

Shanghai

Nanjing

Lanzhou

HongKong

Hangzhou

Guangzhou

Fuzhou

Beijing

Anshan

5.03.01.0-1.0-2.0-1.0 0.0 1.0 2.0 3.0 -1.0 0.0 1.0 2.0 3.0

Fig. 1. Percent increase of mortality associated with 10 mg/m3 increase of 2-day moving average SO2 concentrations in the CAPES cities, China, 1996–2008–effect estimates

of individual cities (mean and 95% confidence intervals) and national average (mean and 95% posterior intervals) (a. total mortality b. cardiovascular mortality;

c. respiratory mortality) (Cause-specific mortality data were not available in Lanzhou).

R. Chen et al. / Environmental Research 118 (2012) 101–106 103

effect estimate of SO2 among females was slightly higher thanamong males, although their between-gender difference wasstatistically insignificant (p40.05). Deaths under 5 years of agewere too few and therefore were excluded from our analysis. Wedid not observe significant association between SO2 and mortalityamong residents aged 5–64. Among the elderly over 65 years, theeffect estimate was significant and approximately 3 times higherthan those aged 5–64, and the between-age difference wasstatistically significant (po0.05). The effect estimate of SO2

among residents with low educational attainment (illiterate orprimary school) was approximately twice that among those withhigh educational attainment (middle school or above), but thebetween-education difference was statistically insignificant(p40.05).

In the two-pollutant model, the associations of SO2 with totaland cardiopulmonary mortality decreased, but remained positiveand statistically significant, after adding PM10 in the models(Table 3). However, adjustment for NO2 decreased the

R. Chen et al. / Environmental Research 118 (2012) 101–106104

associations and rendered them statistically insignificant. A 10-mg/m3 increase in two-day moving averaged SO2, after adjust-ment for NO2, was associated with a 0.16% (95% PI, �0.06 to 0.38),0.18% (95% PI, �0.18 to 0.54) and 0.44% (95% PI, �0.01 to 0.90)increase of total, cardiovascular and respiratory mortality, respec-tively. Figs. 1 and 2 in the online appendix present the city-specific regression results of SO2 after adjustment for PM10 andNO2, respectively.

Within a range of 4–10 df, a change in the number of degreesof freedom per year for time trend did not substantially affectedthe estimated effects of SO2 (Fig. 2), suggested that our findingswere relatively robust in this respect.

In our analysis of the data, the patterns of lag effects of SO2 ontotal, cardiovascular, and respiratory mortality were similar(Fig. 3). For sinlge-day exposures, the risks were maimal at lag

Table 2Age, gender and education-specific percent (%) increase in total mortality

associated with 10 mg/m3 increase in SO2 (average of lags 0 and 1 of the 24-h

average concentrations) in the CAPES cities.

Estimate (%) 95% PI

Gender

Male 0.60 0.22, 0.98

Female 0.88 0.43, 1.33

Age

5–64 0.27 –0.02, 0.56

4¼65 0.88 0.42, 1.34

Education

Lowa 1.30 0.95, 1.66

Higha 0.60 �0.01, 1.22

Abbreviations: SO2, sulfur dioxide; PI, posterior intervals; CAPES, China Air

Pollution and Health Effects Study.a Low: low educational attainment including illiterate and primary school;

high: high educational attainment including middle school and above.

Table 3Pooled estimates (mean and 95% PI) for the increase in mortality associated with

concentrations) in the CAPES cities, in single- and bi-pollutant models adjusted for co-

Model choice Total mortality

Estimate (%) 95% PI

Single-pollutant model – 0.75 0.47, 1.02

Multi-pollutant model þPM10 0.42 0.17, 0.67

þNO2 0.16 �0.06, 0.38

Abbreviations: SO2, sulfur dioxide; PI, posterior intervals; CAPES, China Air Pollution an

diameter; NO2, nitrogen dioxide.

-0.5

0.0

0.5

1.0

1.5

2.0

4 6 8 10 4 6

Total mortality

Per

cent

incr

ease

in m

orta

lity

Cardiovas

Fig. 2. Percentage changes in daily mortality associated with 10 mg/m3 increase of 2-d

year for time trend, in the CAPES cities, 1996–2008.

0 day to lag 1 day, and then declined; multi-day exposure (lag 0–1day) usually had greater effects than single-day exposures (lag0 to 7 day). The effects of SO2 on total, cardiovascular andrespiratory mortality were positive for all lag days, though theassociations were statistically insignificant for some single-daylags we examined.

The effects of SO2 remained positive and statistically signifi-cant after controlling for extended temperature (Fig. 4). Com-pared with the effects when controlling for current-day (lag0 day) temperature only, additional controlling for extendedtemperature attenuated our effect estimates for SO2.

4. Discussion

Evidence gained in this time-series analysis showed thatambient SO2 was associated with mortality from all causes andfrom cardiopulmonary diseases in 17 Chinese cities. Age, but notgender or education level, might modify the acute effect of SO2.Inclusion of NO2 in the regression model decreased the associa-tion of SO2 with daily morality. To our knowledge, this is thelargest epidemiological study up to date in Asia to examine theshort-term health effects of SO2. These data contribute to thescientific literature on health effects of air pollution for highexposure settings typical in developing countries.

In the combined analysis, an increase of 10 mg/m3 of SO2 wasassociated with 0.75%, 0.83% and 1.25% increase of total, cardio-vascular and respiratory mortality, respectively. The magnitude ofour estimates for SO2 was generally comparable with most priorfindings. For instance, in a meta analysis of 109 time-seriesstudies of air pollution and daily mortality, most of which wereconducted in North America and Europe, Stieb et al. estimatedthat the excess total mortality risk (single-pollutant models)associated with a 10 mg/m3 increase of SO2 was 0.36% (95% CI,

an increase of 10 mg/m3 in SO2 (average of lags 0 and 1 of the 24-h average

pollutants.

Cardiovascular mortality Respiratory mortality

Estimate (%) 95% PI Estimate (%) 95% PI

0.83 0.47, 1.19 1.25 0.78, 1.73

0.38 0.03, 0.73 0.77 0.34, 1.20

0.18 �0.18, 0.54 0.44 �0.01, 0.90

d Health Effects Study; PM10, particulate matter less than 10 mm in aerodynamic

8 10 4 6 8 10

cular mortality Respiratory mortality

ay moving average SO2 concentrations, using various degrees of freedom (df) per

-0.5

0.0

0.5

1.0

1.5

2.0

Total mortality

Per

cent

incr

ease

in m

orta

lity

Cardiovascular mortality Respiratory mortality

0 1 2 3 4 5 6 7 01 0 1 2 3 4 5 6 7 01 0 1 2 3 4 5 6 7 01

Fig. 3. Percent changes in daily mortality associated with 10 mg/m3 increase in SO2 concentrations, using various lag-day structures for SO2 in the CAPES cities, China,

1996–2008.

-0.5

0.0

0.5

1.0

1.5

2.0

Total mortality

Per

cent

incr

ease

in m

orta

lity

Cardiovascular mortality Respiratory mortality

lag 0 lag 0-3 lag 0-7 lag 0 lag 0-3 lag 0-7 lag 0 lag 0-3 lag 0-7

Fig. 4. Percentage changes in daily mortality associated with 10 mg/m3 increase of SO2 concentrations, using various lag-day structures for temperature, in the CAPES

cities, 1996–2008.

R. Chen et al. / Environmental Research 118 (2012) 101–106 105

0.28 to 0.44). A meta analysis of Asian literature indicated thata 10 mg/m3 increase of SO2 was associated with 0.52% (95% CI,0.30 to 0.74) increase of total mortality (Health Effects Institute,2004). In addition, recent large-scale multi-city time-series ana-lyses, which could avoid potential publication bias of metaanalysis, estimated that 10 mg/m3 increase of SO2 was associatedwith 0.6% (95% CI 0.4 to 0.8) increase of total mortality in Europe(Katsouyanni et al., 1997). Interestingly, studies in North Americadid not detect a significant effect of SO2 on daily mortalitypossibly due to the very low levels of SO2 (Burnett et al., 2000;Dominici et al., 2007). The heterogeneity of various findings mayreflect differences in the characteristics of local air pollution orpatterns of exposure among local residents.

The increased mortality risk found in Chinese cities is similarin magnitude, per unit increase of SO2 concentration, to the risksfound in other parts of the world. However, the disease burdenrelated to this increased risk of mortality is greater than that inWestern countries because the SO2 levels in China are much higherthan those reported in developed countries. For example, the meanSO2 concentrations in our study ranged from 18 mg/m3 (Hong Kong)to 100 mg/m3 (Urumqi). In contrast, Sunyer et al. reported thatthe mean SO2 levels in 7 European cities varied from 5 mg/m3

(Stockholm) to 21 mg/m3 (London) (Sunyer et al., 2003b). Thereported mean levels of SO2 in 14 US cities ranged from 8 mg/m3

(Seattle) to 45 mg/m3 (Pittsburgh) (Samet et al., 2000). Therefore,ambient SO2 may represent a major public health concern in thecountry.

After adjusting for PM10, the association of SO2 remainedsignificant in 17 Chinese cities (Table 2), suggesting that SO2 isan important component for the air pollution mixture in China.Although it is well-known that SO2 contribute to particle forma-tion, the current analysis suggests that as a separately regulatedpollutant in China, SO2 may be independently related withadverse health effects, and the Chinese government shouldmaintain ‘‘controlling/reducing total SO2 emissions’’ as a majorair pollution control strategy.

The effect estimate for SO2 decreased and became insignificantafter adjustment for NO2 in these Chinese cities (Table 2); how-ever, SO2 did not confound the effect of NO2 (data not shown).NO2 reduces the association of SO2 with daily mortality, probablybecause both pollutants are emitted from the same source(i.e., fossil fuel combustion or diesel exhaust), or increase togetherdue to the meteorological conditions. SO2 may serve as a surrogateof other toxic substances which are correlated with NO2.

Various factors may modify the health effects of SO2 (Kanet al., 2008). As pointed by the US National Academy of Science(National Research Council, 1998), it is important to understandthe characteristics of individuals who are at increased risk of

R. Chen et al. / Environmental Research 118 (2012) 101–106106

adverse events due to air pollution. The information on modifica-tion of air pollution health effects is inconsistent (Samet, 2008).We did not find statistically significant evidence for effectmodification by gender or education. As also reported previously(Kan et al., 2008; Zeka et al., 2006), however, our study foundhigher susceptibility to SO2 among the elderly. Preexisting cardio-respiratory disorders and inherent frailty among elders maycontribute to their high vulnerability to air pollution. Additionalinvestigation of modifying factors in future studies will enhancepublic policy making, risk assessment and standard setting.

Our analysis has strengths and limitations. These seventeenChinese cities offer advantages for the study of the SO2-mortalityrelationship in that they are generally very densely populated.Most air pollution epidemiologic studies, including ours, useambient pollutant concentrations as surrogates of personal expo-sure, which might induce unavoidable measurement error.Because we were unable to measure the true population expo-sures in these seventeen cities, we could not determine thedirection of the bias and its impact on our findings. Our resultsof two-pollutant models should be interpreted with caution,because both SO2 and NO2 are precursors of secondary particles.Coal combustion was the major source of both particulate andgaseous pollutants (e.g. SO2 and NO2) in China, thus limiting ourability to separate the independent effect for individual pollutant.Due to the limitation of data availability, our study had useddifferent research periods for each city. This might generateuncertainty when combining effect estimates across the cities.However, the observation periods for most CAPES cities werein the 2000s, except for Hong Kong which had an observationperiod between 1996 and 2002. Substantial changes of air pollu-tion levels are usually slow and affect various cities in the sameway. Previous multi-city studies in Europe (Samoli et al., 2005)and Asia (Wong et al., 2008) also used different observationperiods for various cities.

In summary, short-term exposure to SO2 was associated withincreased mortality risk in China. These associations were gen-erally independent of PM10 but did not persist after adjustmentfor NO2. Our results contribute to very limited data in thescientific literature on short-term effects of SO2 for high exposuresettings typical in developing countries. Further studies areneeded to tackle with the independent health effect of SO2.

Acknowledgments

The study was supported by the National Basic Research Program(973 program) of China (2011CB503802), Gong-Yi Program of ChinaMinistry of Environmental Protection (201209008), and Program forNew Century Excellent Talents in University (NCET-09-0314).

The authors declare they have no competing financial interests.

Appendix A. Supporting information

Supplementary data associated with this article can be foundin the online version at http://dx.doi.org/10.1016/j.envres.2012.07.003.

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