90 VOLUME 116 | NUMBER 1 | January 2008 • Environmental Health Perspectives

Research | Children’s Health

Recent international data indicate that currently the increase of asthma and allergies in

children is most pronounced in the more

advanced developing countries (Asher et al.

2006). The reasons remain unclear, but this

trend could be attributed to changes associated with environment and lifestyle factors

during the modernization process (Douwes

and Pearce 2002). Among others, the increasing level of ambient air pollution may affect

children’s asthma and allergies (Schneider

and Freeman 2001; Watts 2006), and indoor

air pollution is another major health problem

in developing countries (Bruce et al. 2000).

Because China has the largest population in

the world, an increase in asthma and allergies

will affect a large number of individuals.

Outdoor air pollution has been a significant issue in China, especially in the coalburning areas (Cheng et al. 2002; Mestl and

Fang 2003). The respiratory effects of ambient air pollution in China have been reviewed

(Aunan and Pan 2004). Coal is still the major

source of energy, constituting about 75% of

all energy sources (Chen et al. 2004), and

consequently coal smoke, with suspended

particulate matter (PM) and sulfur dioxide

dominating. Furthermore, the rapidly growing number of motor vehicles accelerates

emissions of other ambient air pollutants such

as nitrogen dioxide and ozone (Chen et al.

2004). Ambient O3 levels in Shanghai,

China, have been related to daily mortality in

winter (Zhang et al. 2006) but not in summer, and O3 levels in Hong Kong have been

related to asthma hospital admission in children (Lee et al. 2006).

Indoor air pollution is another important

issue in China. The best known source is wood

and coal burning for cooking or heating in

dwellings in rural areas, which produces significant particle pollution in developing countries,

including China, with pronounced impairment

of respiratory health (Bruce et al. 2000). In

urban areas, however, this has been widely

replaced by cleaner energy sources at home,

such as gas and electricity. Noticeably, chemical

emissions from new building materials and furniture, such as formaldehyde, are problematic

in urban areas. High indoor levels of formaldehyde have been measured in China (Cai et al.

2002), Korea (Kim and Kim 2005), and

Singapore (Ooi et al. 1998). Respiratory effects

of chemical emissions from new building materials, such as indoor paint, have been detected

in Europe (Wieslander et al. 1997), but there is

a lack of similar studies from China. Moreover,

tobacco smoking is common in China, but

there is not much focus on respiratory effects of

environmental tobacco smoke (ETS) at home

or at work (Chen et al. 1988; Qian et al. 2007;

Venners et al. 2001).

Besides the dwellings, school is a particularly important indoor environment for children and adolescents. There are very few

studies of school environments from mainland

China (Lee and Chang 2000; Mi et al. 2006;

Zhao 1991). Studies from Western countries

have shown that schools can be contaminated

by various indoor pollutants, such as molds,

bacteria, allergens, particles, volatile organic

compounds, and formaldehyde (Cooley et al.

1998; Daisey et al. 2003; Mendell and Heath

2005; Norback et al. 1990; Smedje et al.

1997). Western studies have shown that the

school environment may exacerbate asthma

symptoms, allergic reactions, and other respiratory symptoms (Daisey et al. 2003; Mendell

and Heath 2005). Indoor air at schools in

urban areas can be contaminated by ambient

urban air pollution and traffic pollutants, and

vicinity to busy roads may affect children’s respiratory health (Holguin et al. 2007; Janssen

et al. 2003; Kim et al. 2004; Morgenstern

et al. 2007).

In this study, our first aim was to examine

the relationship between respiratory symptoms in junior high school students and exposure to elevated levels of air pollution in

classrooms in Taiyuan city, Shanxi province, a

coal-burning area in China. Another aim was

to study the relationship between respiratory

symptoms in the junior high school students

and exposure to elevated levels of ambient air

pollution from outside the schools. Our third

aim was to study associations between respiratory symptoms in the students and selected

exposures in the dwellings, such as ETS and

new building materials and furniture—proxy

variables for chemical material emissions.

Materials and Methods

Study design. We performed a school-based,

cross-sectional study in Taiyuan, Shanxi

Address correspondence to Z. Zhao, Department of

Occupational and Environmental Medicine,

University Hospital and Uppsala University, Uppsala,

Sweden, SE 751-85. Telephone: 46 (0)18 611 36 46.

Fax: 46 (0)18 51 99 78. E-mail: zhuohui.zhao@

medsci.uu.se

The authors declare they have no competing

financial interests.

Received 20 June 2007; accepted 8 October 2007.

Asthmatic Symptoms among Pupils in Relation to Winter Indoor and

Outdoor Air Pollution in Schools in Taiyuan, China

Zhuohui Zhao,1 Zheng Zhang,2 Zhuanhua Wang,2 Martin Ferm,3 Yanling Liang,4 and Dan Norbäck1

1Department of Occupational and Environmental Medicine, University Hospital and Uppsala University, Uppsala, Sweden; 2Institute

of Biotechnology, Shanxi University, Taiyuan, Shanxi Province, People’s Republic of China; 3IVL Swedish Environmental Research

Institute, Gothenburg, Sweden; 4Institute of High School Student Health Care, Taiyuan, Shanxi Province, People’s Republic of China

BACKGROUND: There are few studies on associations between children’s respiratory heath and air

pollution in schools in China. The industrial development and increased traffic may affect the

indoor exposure to air pollutants in school environment. Moreover, there is a need to study respiratory effects of environmental tobacco smoke (ETS) and emissions from new building materials in

homes in China.

OBJECTIVES: We studied the associations between pupils’ asthmatic symptoms and indoor and

outdoor air pollution in schools, as well as selected home exposures, in a coal-burning city in

north China.

METHODS: A questionnaire survey was administered to pupils (11–15 years of age) in 10 schools in

urban Taiyuan, collecting data on respiratory health and selected home environmental factors.

Indoor and outdoor school air pollutants and climate factors were measured in winter.

RESULTS: A total of 1,993 pupils (90.2%) participated; 1.8% had cumulative asthma, 8.4% wheezing,

29.8% had daytime attacks of breathlessness. The indoor average concentrations of sulfur dioxide,

nitrogen dioxide, ozone, and formaldehyde by class were 264.8, 39.4, 10.1, and 2.3 μg/m3, respectively. Outdoor levels were two to three times higher. Controlling for possible confounders, either

wheeze or daytime or nocturnal attacks of breathlessness were positively associated with SO2, NO2,

or formaldehyde. In addition, ETS and new furniture at home were risk factors for wheeze, daytime

breathlessness, and respiratory infections.

CONCLUSIONS: Indoor chemical air pollutants of mainly outdoor origin could be risk factors for

pupils’ respiratory symptoms at school, and home exposure to ETS and chemical emissions from

new furniture could affect pupils’ respiratory health.

KEY WORDS: air pollution, asthma, China, formaldehyde, indoor, nitrogen dioxide, ozone, outdoor,

school, sulfur dioxide. Environ Health Perspect 116:90–97 (2008). doi:10.1289/ehp.10576

available via http://dx.doi.org/ [Online 9 October 2007]
province, China. Data on respiratory symptoms were collected by individual questionnaires as well as information on personal and

home environment factors. Air pollutants

including SO2, NO2, O3, and formaldehyde

and climatic factors were measured both

indoors and outdoors in classrooms and

schools. 

Study locations and selection process. Ten

junior high schools were arbitrarily selected in

December 2004 within urban areas of Taiyuan

city (3 million inhabitants), situated at 500 km

southwest of Beijing (Figure 1). Taiyuan is one

of the most heavily polluted cities in the world,

and Shanxi province is the major coal mining

area, with two-thirds of China’s domestic coal

production. The headmasters of 10 selected

schools were contacted, and all agreed to participate.

Study population. In each of the 10 schools,

five first-year classes were arbitrary selected, in

different parts and floors in the school buildings. If there were fewer than five first-year

classes, all were selected. The study population

consisted of 2,209 pupils (11–15 years of age)

in 46 classes; 1,993 (90.2%) completed the

questionnaire. There were no reports on health

complaints or environmental problems from

any of the schools before the investigation.

Classroom characteristics. An inspection

was performed in the 46 classrooms by the

main author (Z.Z.), including measurement of

room volume, floor area, number of students,

and fleece factor. Fleece factor (square meters

per cubic meter) was calculated as the ratio

between the surface area of fabrics (square

meters) and the room volume (cubic meters)

(Skov et al. 1990). The schools were constructed with concrete and bricks, and none

had mechanical ventilation. The floor material

was bare concrete, with no paint, and the

floors were cleaned by wet mopping one to

three times per day by the pupils. No signs of

moisture, water damage, or indoor mold

growth could be observed in any of the selected

classrooms, and very few classrooms had

indoor plants. The mean number (± SD) of

pupils per classroom was 48 ± 8 (range, 33–60),

and each student occupied 1 ± 0.15 m2 on average (range, 0.6–1.2). The mean room volume

was 193 ± 18 m3 (range, 161–225 m3). There

were small amounts of curtains and upholsters

in some classes; the average fleece factor was

0.03 ± 0.03 m2/m3 (range, 0–0.14).

Air pollution measurements. Indoor levels

of SO2, NO2, O3, and formaldehyde were

measured in the selected classrooms (maximum five per school), and outdoor levels were

measured at one representative location in

each school by diffusion samplers. For SO2,

NO2, and O3, samplers were obtained from

IVL Swedish Environmental Research

Institute Ltd. (Gothenburg, Sweden); for

formaldehyde, SKC UME × 100 samplers

were obtained from SKC (Eighty Four, PA,

USA). The sampling time was a continuous

7-day period for each sampler. Indoor samplers were placed approximately 2 m above

the floor. Outdoor samplers were placed

2.5–3.5 m above the ground, under a wellventilated plastic cover protecting them from

rain and snowfall. Thirty-four classes had

indoor measurements of SO2, NO2, and O3,

and 31 classes had measurements of formaldehyde, with measures missing in one school

because of technical failures. The concentrations were analyzed by accredited laboratories

specializing in analyzing the samplers, and

were reported as average values across the

7-day measurement period. To evaluate how

the indoor air was affected by outdoor air pollution, the ratios between indoor and outdoor

concentrations were calculated.

Climate measurements. Indoor and outdoor temperature, relative humidity (RH),

and CO2 concentration were measured by a

direct-reading instrument with in-built data

logger (Q-TrakTM IAQ-monitor; TSI Inc.,

St Paul, MN, USA). The indoor climate measurements were performed for 1 hr with full

class occupancy, during normal conditions.

The outdoor measurements were performed

for approximately 30 min, in parallel with the

indoor measurements. Because equipment

was lacking, climate measurements could only

be performed in three classrooms per school

at one time. We calculated the fresh air supply rate in the classrooms from the estimated

equilibrium CO2 concentration (parts per

million) by the following formula, with the

equilibrium CO2 concentration estimated

manually from the CO2 graphs:

A = P/(Cmean – C0) × 106/3,600, [1]

where A is the personal outdoor air supply

rate (cubic meters per hour), P denotes the

personal emission rate of CO2 in liters per

hour, and Cmean and C0 denote the mean

CO2 levels inside and outside classrooms,

respectively (Norback et al. 1992). In the calculations, we assumed a personal CO2 emission equal to sedentary office work at sea level

(18 L/hr), and used the actual outdoor CO2

levels from our measurements. We calculated

the air exchange rate by dividing the estimated total outdoor air supply rate (cubic

meters per hour) (student number × A) by the

total volume of the classroom.

Questionnaire. Students were given a selfadministered questionnaire to collect data on

their respiratory health, parental asthma or

allergy, and selected factors in the home environment. Questions on respiratory health

were mainly based on the International Study

of Asthma and Allergy in Childhood

(ISAAC) (Asher et al. 1995), the European

Community Respiratory Health Survey

(ECRHS) (Janson et al. 2001), and previous

school studies in Sweden (Smedje et al.

1997) and in Shanghai, China (Mi et al.

2006). They included yes/no questions on

cumulative asthma, doctor-diagnosed asthma,

current asthma, and allergies to furry pets or

pollen. Moreover, there were questions on

respiratory symptoms (without using the

School air pollution and asthma in Chinese pupils 

Environmental Health Perspectives • VOLUME 116 | NUMBER 1 | January 2008 91

Figure 1. Map of the 10 selected schools in urban areas in Taiyuan, Shanxi province, China. Modified from

Taiyuan Urban Planning Committee (2007). 
word asthma) including wheeze or whistling

in the chest, daytime or nocturnal attacks of

breathlessness in the preceding 12 months,

and recent respiratory infections defined as

either cold, upper respiratory infection, or

middle ear infection in the preceding

3 months. Finally, there were questions on

parental asthma or allergy and current home

environment, including recent home paintings, new floor material, and new furniture in

the preceding 12 months, and ETS at home,

which was classified into four categories:

never smoking, or smoking one to three

times per month, one to four times per week,

and every day. Subjects with a lack of information on ETS were classified as a separate

category. The questionnaire was translated

from Swedish to Chinese and translated back

to Swedish by another person. The survey

was performed 1 week before the classroom

inspections and measurements, distributed in

the school by the class teachers, and answered

at home in cooperation with the parents. The

study was approved by an ethical committee

of Uppsala University and performed with

informed consent from pupils and parents

before the study. All the personal information from questionnaire was kept confidential. All data analyses were done at the

university hospital and Uppsala University,

Sweden.

Data analysis. Generally, we used multiple logistic regression model to analyze associations between response (pupils’ respiratory

health on individual level ) and exposure

(indoor and outdoor air pollution on class

level and school level), controlling for age,

sex, parental asthma or allergy, and home

environmental factors (new painting, new

floor material, new furniture, and ETS).

Initially, we fit a conventional logistic

model by adding the continuous variables of

indoor or outdoor exposure one by one (no

mutual adjustment) in the model in Stata SE,

version 8.0 (StataCorp., College Station, TX,

USA). Second, we applied a hierarchical

model for the same continuous variables, with

each exposure variable separately included in

the model, using MLwin 2.0 (Rasbabsh et al.

2005). Subsequently, the multivariate hierarchical regression model was fit with mutual

adjustment between personal and home environmental factors and both indoor and outdoor air pollutants. In the hierarchical model,

we applied a random intercept logit link–

binomial model, accounting for the hierarchical structure of the data. It was estimated by

iterative generalized least square, first-order

marginal quasi-likelihood followed by secondorder penalized quasi-likelihood. Odds ratios

(OR) with 95% confidence interval (95%

CIs) were applied.

Additionally, we performed sensitivity

analyses, stratified by sex and parental asthma

or allergy. Correlation analyses between different exposure factors were performed by a

rank correlation test not requiring normal distribution (Kendall’s tau-β). In all statistical

analyses, two-tailed tests and a 5% level of

significance were applied.

Results

Questionnaire data. Prevalence of respiratory

health and home environmental factors for all

subjects are given in Table 1, stratified by sex,

as well as prevalence in subsets of participants

who were involved in the indoor measurements. Girls accounted for 49.3% of participants, and the mean age for the participants

was 13 years. The prevalence of asthma or

allergies was low, but respiratory symptoms

were common. For daytime attacks of breathlessness, breathlessness after exercise was more

common. The prevalence of demographic

characteristics, home environment factors,

and asthmatic symptoms was similar between

total subjects and the subsets of participants.

The only sex difference in symptoms was for

daytime attacks of breathlessness after exercise, where girls had a higher prevalence than

boys (p < 0.001). In home environment factors, girls reported new floor at home more

often than boys (p < 0.001). A small percentage of pupils (11.2%) reported parental

asthma or allergy. Pupils with parental

asthma or allergy had a higher prevalence of

cumulative incidence of asthma (p < 0.05),

wheeze (p < 0.001), and daytime attacks of

breathlessness (p < 0.001) and pollen or pet

allergy (p < 0.05).

Climate measurements. Climate measurements were performed in 24 classrooms. The

average CO2 level was 2,211 ± 1,005 ppm

(range, 789–4,170 ppm) with an average

room temperature of 14.7 ± 2,2°C (range

11.2–18.4°C) and RH of 42 ± 10% (range

Zhao et al.

92 VOLUME 116 | NUMBER 1 | January 2008 • Environmental Health Perspectives

Table 1. Demographic characteristics, home environmental factors, and asthmatic symptoms among pupils.

With indoor air With indoor climate

Total Boys Girls measurementsa measurementsb

Characteristic (n = 1,993) (n = 1,005) (n = 976) (n = 1,480) (n = 1,056)

Age [years (mean ± SD)] 12.8 ± 0.6 12.9 ± 0.7 12.7 ± 0.6 12.8 ± 0.6 12.8 ± 0.6

Girls (%) 50.7 — — 50.9 50.8

Parental asthma or allergy (%) 11.1 11.4 10.9 11.0 10.1

Home environmental factors (%)

New painting 14.0 13.8 14.2 14.3 13.7

New floor 6.7 4.4 9.0 7.3 6.7

New furniture 38.3 39.2 37.4 40.7 39.6

ETS

Never 20.1 20.7 19.5 19.9 19.2

1–3 times/month 26.5 28.2 24.9 26.5 27.9

1–4 times/week 17.1 16.9 17.3 17.5 15.6

Daily 36.4 34.2 38.3 36.1 37.3

Asthma and aasthmatic symptoms (%)

Cumulative asthma 1.8 2.1 1.4 1.9 2.5

Doctor-diagnosed asthma 1.2 1.2 1.1 1.2 1.4

Current asthma attacks 0.4 0.5 0.3 0.5 0.7

Current asthma medication 0.5 0.4 0.6 0.5 0.5

Current airway symptoms in the preceding 12 months (%)

Wheeze or whistling in the chest 8.4 9.6 7.2 8.1 7.6

Daytime attacks of breathlessnessc 29.8 25.8 34.0 30.5 28.9

Daytime attacks of breathlessness at rest 5.4 4.6 6.1 5.8 5.4

Daytime attacks of breathlessness after exercise 27.7 23.4 32.4 30.0 28.4

Nocturnal attacks of breathlessness 2.1 1.8 2.5 2.6 2.3

Furry pet or pollen allergy (%) 3.8 3.2 4.3 3.7 3.4

Respiratory infections in the preceding 3 months (%) 39.3 37.5 41.2 39.6 39.8

aThirty-four of 46 classes with indoor SO2, NO2, and O3 measurements were included; formaldehyde was not included because three classes (from one school) had missing measurements. bThirty-one of 46 classes with indoor climatic measurements were included. cDaytime attacks of breathlessness either at rest or after exercise.
31–62%). The average air exchange rate was

2.86 ± 1.85 ac/h (range, 0.91–7.32). The average outdoor CO2 level was 522 ± 26 ppm

(range, 480–559 ppm) with an average outdoor

temperature of –1.8 ± 2,2°C (range, –5.5 to

2.6°C) and RH of 52 ± 11% (range, 30–64%).

Indoor and outdoor SO2, NO2, O3, and

formaldehyde. Descriptive data on indoor and

outdoor concentrations and indoor/outdoor

ratio are given in Table 2. Frequency distribution graphs of indoor SO2, NO2, and O3 are

given in Figure 2. Indoor SO2 and NO2 were

approximately normally distributed, whereas

O3 data were more skewed. For formaldehyde,

there was little variation within either indoor

or outdoor concentrations, and five classrooms

(from four schools) had indoor levels below the

detection limit ( < 1 μg/m3). For SO2, five of

10 outdoor samples were close to saturation,

and three samplers were completely saturated.

In case of complete saturation, we used the saturation concentration (1,015 μg/m3). For SO2

and formaldehyde, the indoor levels were

approximately 40% of the outdoor levels, for

NO2 78%, and for O3 91%. Between indoor

and outdoor levels of air pollutants, there were

no significant correlations except for SO2 (tau-β

0.33; p < 0.01). Within outdoor concentrations

of air pollutants, there were no significant correlations; within indoor concentrations, SO2,

NO2, and O3 were positively correlated,

whereas there was a negative correlation

between NO2 and formaldehyde (tau-β 0.36;

p < 0.05). For the correlated indoor pollutants,

the tau-β coefficient for SO2–NO2 was 0.74

(p < 0.001), SO2–O3 of 0.51 (p < 0.01), and

NO2–O3 of 0.41 (p < 0.01). The indoor climate variables (temperature, RH, CO2, air

exchange rate) were not significantly correlated

with indoor pollutant concentration, except

that formaldehyde had a positive correlation

with room temperature (tau-β 0.41; p < 0.05).

Associations between air pollution and

pupils’ respiratory health. By the conventional

logistic model (Table 3), results show that at

higher outdoor level of formaldehyde, wheeze,

and daytime attacks of breathlessness were

more common. At higher indoor levels of

SO2, wheeze and nocturnal attacks of breathlessness were more common; and at higher

indoor levels of NO2 and formaldehyde, nocturnal breathlessness was more common.

Higher levels of O3 suggested a marginal significance with daytime attacks of breathlessness (p = 0.05). However, in regard to

its skewed distribution, O3 was additionally

analyzed as categorical variable in the same

models, using the 10 classrooms with lowest

level as reference category, the 10 next classrooms as middle category (level 1), and the

other 14 classroom with the highest O3 levels

as the highest category (level 2). We found an

association between O3 and daytime attacks

of breathlessness: for level 1, OR = 1.65 (95%

CI, 1.16–2.36), and for level 2, OR = 1.62

(95% CI, 1.15–2.29). And we found an association between O3 and nocturnal attacks of

breathlessness: for level 1, OR = 8.69 (95%

CI, 1.02–74.05), and for level 2, OR = 8.49

(95% CI, 1.01–71.06) ).

As a next step, we applied a three-level

hierarchical model controlling for a cluster

effect on class or school level for indoor and

outdoor pollutants (Table 4). At a higher level

of outdoor formaldehyde, positive associations

(OR > 1) still remained with wheeze and daytime attacks of breathlessness with a slight lack

of statistical significance. At higher indoor levels of SO2, NO2, and formaldehyde, nocturnal

attacks of breathlessness were more common.

In the final step, we performed a threelevel hierarchical model with mutual adjustment for all four indoor air pollutants, still

keeping all outdoor pollutants at the school

level and the same control factors as before in

the individual level (Table 5). Higher levels of

indoor SO2 were associated with more

wheeze, and higher levels of indoor formaldehyde and O3 were associated with nocturnal

attacks of breathlessness.

Because similar results were obtained by

the hierarchic and conventional logistic regression models, we performed sensitivity analysis

by conventional multiple logistic regression

analysis (no mutual adjustment). Similar ORs

were obtained for boys and girls, and for those

with and without parental asthma/allergy.

Examples are presented in Figure 3 for associations between wheeze or whistling in the chest

and indoor level of SO2, and associations

between daytime attacks of breathlessness and

outdoor level of formaldehyde. The effects

School air pollution and asthma in Chinese pupils 

Environmental Health Perspectives • VOLUME 116 | NUMBER 1 | January 2008 93

Table 2. Indoor and outdoor air pollutants in classrooms and schools. 

No.a Mean ± SD Range 

Indoor air pollutants (μg/m3)

SO2 34 264.8 ± 139.0 60.0–641.1

NO2 34 39.4 ± 9.5 15.5–61.6

O3 34 10.1 ± 10.4 3.0–61.2

Formaldehyde 31 2.3 ± 1.1 1.0–5.0

Outdoor air pollutants (μg/m3)

SO2 10 712.8 ± 189.3 476.0–1,015.0

NO2 10 52.3 ± 9.5 37.9 –65.2

O3 10 12.4 ± 3.3 7.1–17.5

Formaldehyde 9 5.8 ± 0.6 5.0–7.0

Indoor/outdoor ratios

SO2 34 0.38 ± 0.17 0.11–0.76

NO2 34 0.78 ± 0.22 0.38–1.19

O3 34 0.91 ± 0.93 0.18–5.1

Formaldehyde 31 0.39 ± 0.18 0.14–0.83

aNumber of classrooms and schools with available pollutant measurements.

Figure 2. Histograms of indoor air pollutants SO2 (A), NO2 (B), and O3 (C). Data on 34 classrooms with available measurements were applied.

10

8

6

4

2

0

0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0

SO2 (μg/m3)

Frequency

20

15

10

5

0

Frequency

0.0

NO2 (μg/m3)

10.0 20.0 30.0 40.0 50.0 60.0 70.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

O3 (μg/m3)

25

20

15

10

5

0

Frequency

A B C
tended to be stronger for the subgroup without parental asthma or allergy.

Associations between personal and home

environmental factors and respiratory health.

In the last three-level model, we evaluated personal factors and home environmental factors,

controlled for pollutant exposure in schools.

Higher age was related to more nocturnal

attacks of breathlessness but fewer airway

infections. Females still had more daytime

attacks of breathlessness. Those with parental

asthma/allergy or with new furniture at home

reported more wheeze and daytime attacks of

breathlessness. ETS at home was related to

wheeze, daytime attacks of breathlessness, and

respiratory infections, of which the latter

showed a consistent associations for all three

ETS categories. For comparison, we also fit

conventional multiple logistic regression models, excluding controlling for school environment. Results for the above associations were

similar (data not shown).

Discussion

We found that elevated levels of air pollutants

in classrooms in the heavily polluted city

of Taiyuan, China, were associated with

pupils’ respiratory symptoms. In addition,

environmental factors at home such as ETS

and emissions from new furniture seemed to

exacerbate children’s respiratory symptoms.

Except for formaldehyde, outdoor levels of

the pollutants outside the schools were not

related to symptoms.

The questionnaire survey in this study

had a high response rate of 90.2%, and the

questions were answered with the help of parents before the school environment measurements were started. Schools were arbitrarily

selected within the urban areas of Taiyuan,

and first-year classes were arbitrarily selected

within the schools. There were no indications

of selection bias when comparing classes participating in the questionnaire study with

those included in the classroom measurements. Because the data had a three-level

hierarchical structure (school, classroom, individual), we made additional analyses with

three-level hierarchical models. Results were

mostly consistent, with some differences in

p-values in different models. Sensitivity analyses gave relatively similar results. Cigarette

smoking is a well-established risk factor for

asthma. However, four (of 1,993) students

reported their own smoking. We did not

control this factor in the association analysis.

Thus, we have no indications of selection

effects or effects of selection on a particular

statistical model, but the cross-sectional study

design limits the possibility of drawing

conclusions based on causal relationships.

Moreover, the high general air pollution level

in the city may have limited the possibility of

getting sufficient variation in the overall exposure to air pollutants in the study population.

The prevalence of respiratory symptoms

and airway infections was high, whereas the

prevalence of diagnosed asthma and allergy to

furry pets or pollen was low. The discrepancy

between diagnosed asthma and asthmatic

symptoms, sex differences, and the validity of

the symptom reporting in this school study

have been discussed previously (Zhao et al.

2006). A similar low prevalence of asthma

among children in Taiyuan has been reported

previously in a large Chinese study (Chen

2004). Moreover, a high prevalence of respiratory symptoms and airway infections has

previously been reported from other Asian

school studies in Shanghai (Mi et al. 2006)

and the Republic of Korea (Kim et al. 2007).

None of the schools had mechanical ventilation, and opening windows was the only way to

ventilate the classrooms. This might increase the

Zhao et al.

94 VOLUME 116 | NUMBER 1 | January 2008 • Environmental Health Perspectives

Table 4. Hierarchical multiple logistic regression on asthmatic symptoms associated with indoor and outdoor air pollutants [OR (95% CI)].

a

Wheeze or Daytime attacks Nocturnal attacks Furry pet Respiratory

Cumulative asthma whistling in the chest of breathlessness of breathlessness or pollen allergy infection

Indoor

SO2 1.12 (0.71–1.76) 1.15 (0.94–1.42) 1.04 (0.90–1.20) 1.27 (1.02–1.59)* 1.12 (0.92–1.36) 0.93 (0.84–1.04)

NO2 1.32 (0.55–3.14) 1.04 (0.77–1.39) 0.95 (0.78–1.16) 1.45 (1.00–2.08)* 1.04 (0.76–1.43) 0.92 (0.79–1.08)

O3 1.21 (0.77–1.92) 0.99 (0.80–1.25) 1.08 (0.94–1.25) 1.04 (0.73–1.49) 1.10 (0.86–1.39) 0.92 (0.79–1.07)

CH2O 0.81 (0.49–1.33) 1.13 (0.89–1.44) 1.00 (0.84–1.19) 1.40 (1.02–1.92)* 1.15 (0.89–1.48) 1.04 (0.90–1.20)

Outdoor

SO2 0.97 (0.70–1.35) 1.03 (0.82–1.29) 1.00 (0.87–1.16) 1.05 (0.83–1.32) 1.06 (0.89–1.27) 0.98 (0.89–1.08)

NO2 0.66 (0.37–1.18) 1.02 (0.65–1.60) 0.92 (0.60–1.22) 0.94 (0.59–1.51) 1.00 (0.71–1.40) 0.89 (0.74–1.07)

O3 0.50 (0.11–2.28) 0.59 (0.20–1.27) 0.64 (0.19–1.96) 0.61 (0.19–1.96) 0.70 (0.29–1.67) 0.84 (0.52–1.33)

CH2O 1.89 (0.83–4.32) 1.64 (0.96–2.83) 1.36 (0.99–1.86) 1.63 (0.90–2.95) 1.09 (0.68–1.75) 0.92 (0.72–1.18)

CH2O, formaldehyde. aThree-level hierarchical logistic model (school–class–student) was applied for the same available data as in conventional logistic regression model (see Table 3 for available data

information). Each air pollutant was included in the model separately, controlling for age, sex, parental asthma or allergy, ETS at home, recent home painting, new floor and new furniture in the preceding 12 months. ORs refer to a step change of 100 μg/m3

, 10 μg/m3, 10 μg/m3, and 1 μg/m3 of SO2, NO2, O3, and formaldehyde, respectively. *p < 0.05.

Table 3. Conventional multiple logistic regression on asthmatic symptoms associated with indoor and outdoor air pollutants [OR (95% CI)].

a

Wheeze or Daytime attacks Nocturnal attacks Furry pet Respiratory

Cumulative asthma whistling in the chest of breathlessness of breathlessness or pollen allergy infection

Indoor

SO2

b 1.14 (0.85–1.54) 1.18 (1.03–1.35)* 1.07 (0.98–1.16) 1.28 (1.02–1.59)* 1.12 (0.92–1.36) 0.94 (0.86–1.02)

NO2

b 1.26 (0.80–1.98) 1.12 (0.91–1.39) 1.00 (0.80–1.41) 1.45 (1.00–2.45)* 1.05 (0.77–1.42) 0.93 (0.82–1.05)

O3

b 1.27 (0.95–1.71) 1.05 (0.87–1.27) 1.12 (1.00–1.26) 1.04 (0.76–1.42) 1.10 (0.87–1.39) 0.93 (0.82–1.04)

CH2Oc 0.79 (0.48–1.28) 1.24 (1.03–1.48)* 1.04 (0.93–1.16) 1.40 (1.02–1.92)* 1.14 (0.89–1.46) 1.04 (0.96–1.15)

Outdoor

SO2

d 0.90 (0.73–1.11) 1.04 (0.94–1.14) 0.96 (0.90–1.02) 1.02 (0.84–1.23) 1.04 (0.91–1.19) 0.98 (0.93–1.04)

NO2

d 0.71 (0.50–1.01)) 1.00 (0.83–1.20) 0.97 (0.86–1.08) 1.04 (0.72–1.50) 0.98 (0.76–1.27) 0.95 (0.86–1.06)

O3

d 0.65 (0.22–1.87) 0.67 (0.39–1.14) 0.85 (0.62–1.17) 0.83 (0.29–2.35) 0.66 (0.32–1.38) 0.89(0.66–1.19)

CH2Oe 1.11 (0.59–2.07) 1.38 (1.03–1.85)* 1.42 (1.19–1.70)** 1.72 (0.98–3.03) 1.17 (0.78–1.74) 0.99 (0.84–1.17)

CH2O, formaldehyde. aEach air pollutant variable is included in the model separately, controlling for age, sex, parental asthma or allergy, ETS at home, recent home painting, new floor and new furniture in

the preceding 12 months. ORs refer to a step change of 100μg/m3

, 10μg/m3, 10μg/m3, and 1 μg/m3 of SO2, NO2, O3, and formaldehyde, respectively. The individual exposure to air pollutants was addressed the same as the classroom level for indoor exposure and the school level for outdoor exposure, respectively. bApplied for available data in 34 classes across

10 schools (n = 1,480). cApplied for available data in 31 classes across 9 schools (n = 1,362). dApplied for available data in 10 schools (n = 1,993). eApplied for available data in 9 schools

(n = 1,836). *p < 0.05. **p < 0.001. For indoor O3 and daytime attacks of breathlessness, p = 0.05.
indoor level of outdoor pollutants. We could

not demonstrate any correlation between air

exchange rate and air pollution levels, possibly

because air exchange was measured during 1 hr

of normal daytime activity, whereas air pollutants were measured day and night during

1 week. Positive correlation between indoor

SO2, NO2, and O3 could be attributed to the

same major origin of these pollutants from outdoors, and the negative correlation between

indoor NO2 and formaldehyde might indicate

reactive chemistry. Further, the poor correlation

between indoor and outdoor levels of pollutants

indicated that the indoor exposure of these outdoor pollutants was largely determined by

room-specific characteristics, such as ventilation. Because pupils spend most of their school

time indoors, our study illustrates the need to

measure indoor levels of air pollutants of outdoor origin in different indoor environments.

Elevated levels of indoor SO2 were associated with more wheeze and nocturnal attacks

of breathlessness. We found very high indoor

levels of SO2 (weekly mean, 265 μg/m3; range,

60–641 μg/m3), and outdoor levels were two

to three times higher. Most samplers were over

an order of magnitude higher than the World

Health Organization (WHO) 24-hr standard

(mean, 20 μg/m3 for 24-hr, and 500 μg/m3

for 10 min) (WHO 2005). More than half of

10 outdoor samples were close to saturation

by the diffusive sampler measurement, and the

outdoor levels were probably underestimated.

The mean indoor/outdoor ratio for SO2 was

0.38 (range, 0.11–0.76), lower than indoor/

outdoor ratios for NO2 and O3. This can be

explained by the higher water solubility of

SO2, which can be captured on wet surfaces

such as wet concrete floor caused by frequent

wet cleaning. Respiratory effects of outdoor

SO2 have been demonstrated in other studies

from China (Chen et al. 2004), but to our

knowledge there are no previous studies on

respiratory effects of SO2 exposure at school.

Some studies have failed to demonstrate associations between SO2 and asthmatic symptoms (Garcia-Marcos et al. 1999; Goldstein

and Weinstein 1986), but usually at lower

exposure levels [e.g., annual mean of 75 μg/m3

(Garcia-Marcos et al. 1999)] than in our

study. The level of outdoor particles is high in

Taiyuan, and annual PM10 (PM with aerodynamic diameter < 10 μm) can be 252 μg/m3

according to the local monitoring station. In

that the main source for both PM10 and SO2 is

coal combustion, there should be an association

between PM10 and SO2. Because we did not

control for PM in our study, we could not

exclude the possibility that observed health

associations for SO2 might be attributed partly

to PM exposure.

Indoor NO2 levels were associated with

nocturnal attacks of breathlessness, both in the

logistic regression and the three-level hierarchical model, but this association was not significant after mutual adjustment. The level of

indoor NO2 was relatively high (weekly mean,

39 μg/m3; range, 16–62 μg/m3), because all

schools were located in urban areas near busy

roads. None of the schools had any gas heaters

in the classrooms, so we did not expect any

indoor sources of NO2. The weekly mean NO2

level outside the schools was 52 μg/m3, slightly

lower than outdoor levels in a similar school

study from Shanghai (weekly mean, 63 μg/m3),

where respiratory effects of indoor NO2 were

detected (Mi et al. 2006). The WHO air quality guideline for NO2 is 40 μg/m3 as an annual

mean, and 200 μg/m3 for 1-hr mean (WHO

2005). It can be expected that the rapid increase

School air pollution and asthma in Chinese pupils 

Environmental Health Perspectives • VOLUME 116 | NUMBER 1 | January 2008 95

Figure 3. Sensitivity analysis stratified by sex and parental asthma or allergy. Two examples of sensitivity

analyses were presented for associations between wheeze or whistling in the chest and indoor level of

SO2 (A) and associations between daytime attacks of breathlessness and outdoor level of formaldehyde

(B). ORs and 95% CIs were calculated by conventional logistic regression model. 

*p < 0.05; **p < 0.01. #p < 0.001.

Boy

Girl

0.75

SO2 [OR (95% CI)]

A

1.00 1.25 1.50 1.75 0.75 1.00 1.25 1.50 1.75 2.00 0.50

CH2O [OR (95% CI)]

* B

*

*

**

#

With parental

asthma/allergy

Without parental

asthma/allergy

Boy

Girl

With parental

asthma/allergy

Without parental

asthma/allergy

Table 5. Hierarchical multiple logistic model with mutual adjustment for indoor air pollutants associated with asthmatic symptoms [OR (95% CI)].a

Wheeze or Daytime attacks Nocturnal attacks Furry pet Respiratory

Cumulative asthma whistling in the chest of breathlessness of breathlessness or pollen allergy infection

Age 0.52 (0.23–1.20) 1.29 (0.90–1.85) 1.15 (0.94–1.42) 2.09 (1.11–3.92)** 1.09 (0.67–1.78) 0.78 (0.64–0.95)*

Sex (boy = 0, girl = 1) 0.30 (0.09–0.97)* 0.76 (0.48–1.19) 1.65 (1.27–2.14)# 1.17 (0.54–2.55) 0.94 (0.51–1.71) 1.18 (0.93–1.51)

Parental asthma or allergy 2.67 (0.69–10.4) 2.66 (1.49–4.75)# 1.89 (1.26–2.83)# 0.96 (0.28–3.34) 1.81 (0.81–4.02) 0.98 (0.65–1.46)

Home environmental factors

New painting 2.10 (0.54–8.18) 0.99 (0.52–1.87) 1.43 (0.97–2.11) 1.96 (0.76–5.06) 0.66 (0.26–1.71) 1.23 (0.84–1.80)

New floor 1.76 (0.31–10.1) 1.67 (0.77–3.60) 0.61 (0.35–1.04) 1.31 (0.39–4.38) 1.84 (0.66–5.14) 0.79 (0.47–1.31)

New furniture 0.83 (0.27–2.55) 1.76 (1.10–2.81)** 1.31 (1.00–1.72)** 1.24 (0.55–2.82) 1.47 (0.78–2.75) 1.03 (0.79–1.33)

ETS

Never 1 1 1 1 1 1

1–3 times/month 1.05 (0.24–4.63) 1.94 (0.81–4.62) 1.23 (0.81–1.87) 1.59 (0.38–6.57) 0.67 (0.24–1.89) 1.90 (1.28–2.83)**

1–4 times/week 2.28 (0.54–9.52) 3.55 (1.51–8.39)** 1.61 (1.03–2.52)** 2.26 (0.54–9.43) 0.53 (0.16–1.82) 1.83 (1.19–2.82)**

Daily 0.16 (0.02–1.62) 2.29 (1.00–5.21)* 1.23 (0.83–1.83) 1.63 (0.42–6.39) 1.07 (0.44–2.61) 1.65 (1.13–2.42)**

Indoor air pollutants

SO2 0.90 (0.24–3.42) 1.55 (1.06–2.27)** 1.16 (0.90–1.50) 1.06 (0.46–2.44) 1.11 (0.67–1.87) 0.89 (0.68–1.15)

NO2 3.20 (0.53–19.1) 0.71 (0.45–1.12) 0.77 (0.55–1.09) 1.46 (0.46–4.58) 0.94 (0.47–1.87) 1.08 (0.76–1.52)

O3 0.66 (0.15–2.89) 0.79 (0.42–1.51) 1.22 (0.82–1.81) 2.72 (1.03–7.18)** 0.95 (0.43–2.11) 0.98 (0.66–1.47)

CH2Ob 1.11 (0.55–2.23) 1.11 (0.87–1.41) 0.93 (0.78–1.10) 1.92 (1.24–2.97)** 1.09 (0.79–1.51) 1.05 (0.88–1.24)

Outdoor air pollutants

SO2 1.04 (0.53–2.07) 0.78 (0.59–1.03) 0.87 (0.73–1.03) 1.14 (0.71–1.82) 0.96 (0.67–1.37) 1.04 (0.88–1.24)

NO2 0.27 (0.04–1.63) 2.21 (0.99–4.98) 1.44 (0.88–2.37) 0.31 (0.08–1.20) 1.34 (0.48–3.75) 0.79 (0.48–1.29)

O3 4.24 (0.04–448) 0.12 (0.01–1.24) 0.31 (0.08–1.18) 17.9 (0.46–693) 0.44 (0.03–7.43) 1.28 (0.35–4.76)

CH2Ob 4.61 (1.09–19.5)* 1.32 (0.86–2.04) 1.29 (0.99–1.68) 2.03 (0.91–4.54) 1.05 (0.60–1.85) 0.94 (0.72–1.23)

CH2O, formaldehyde. aThree-level hierarchical logistic model (school-class-student) was applied with mutual adjustment with all factors (personal, home exposure, indoor and outdoor air pollutants)

included in the model simultaneously. ORs for air pollutants both indoor and outdoor refer to a step change of 100, 10, 10, and 1 μg/m3 for SO2, NO2, O3, and formaldehyde, respectively.

Air pollutants data with available measurements were applied. bFor the one school with missing formaldehyde measurement, the average value of available measurements of the other

schools was applied. *p < 0.05. **p < 0.01. #

p < 0.001.
of the number of cars in China will lead to a

further increase of urban NO2 levels.

We found indications of a slight association between levels of O3 and respiratory

symptoms in the conventional model, and

these become more significant when the

indoor O3 level was classified in three categories (low, middle, high). The weekly mean

O3 levels were relatively low, both indoors and

outdoors (10 μg/m3 and 12 μg/m3, respectively), lower than outside Shanghai schools

(21 μg/m3) and lower than the rural background annual mean of 60 μg/m3 at a monitoring station (Lin An) west of Shanghai (Mi

et al. 2006). It is well known that O3 is consumed in urban areas due to chemical reactions, for example, between O3 and NO to

form NO2. Because our data are weekly

means, we cannot exclude peak exposure at

higher levels. Our data are not directly comparable with the WHO air quality guideline of

100 μg/m3 as 8-hr mean value (WHO 2005).

Surprisingly, we found associations

between indoor levels of formaldehyde and

wheeze and nocturnal attacks of breathlessness, and associations between outdoor

formaldehyde and daytime attacks of breathlessness. In many countries, formaldehyde is

considered an indoor air pollutant, but we

found consistently higher levels outdoors

(mean indoor/outdoor ratio, 0.38). One reason could be that formaldehyde in our study

is an indicator of reactive chemistry, and possibly is associated with other stronger local

irritants (Sundell and Zuber 1996; Wilkins

et al. 2001). There were no temperature correction for the uptake rate of the formaldehyde diffusion samplers, but low outdoor

temperature would lead to an underestimation, not an overestimation, of the true outdoor level. In Shanghai, similar outdoor levels

of formaldehyde (7–9 μg/m3) have been

measured in winter at higher outdoor temperatures (Mi et al. 2006). The reasons for our

findings remain unclear, but indicate a need

for more measurements of outdoor formaldehyde in Asia, and in warmer climate zones, to

identify possible sources. Indoor formaldehyde levels were lower than in Shanghai

schools (Mi et al. 2006) and in Swedish

schools (Smedje et al. 1997). The reason may

be that the schools in Taiyuan did not have

new furniture, chip board, or other obvious

formaldehyde sources. In Chinese dwellings

with formaldehyde emissions from furniture

containing chipboard, much higher formaldehyde levels (320–950 μg/m3) have been measured (Cai et al. 2002). Our weekly mean levels

are not directly comparable with the WHO air

quality guideline value of 100 μg/m3 as

30-min mean value (WHO 1987).

The home environment is the indoor

environment where children spend most of

their time. We studied selected factors in the

dwellings, but had no information on type of

fuel for cooking and heating, or signs of

dampness or molds in the dwellings in this

study, all well-known risk factors for respiratory health (Bruce et al. 2000). Data on these

factors have been collected in a subsequent

2-year follow up study in the same 10 schools

(unpublished data). Eighty percent used natural gas for cooking, 7% biological gas, 4%

coal or coal brackets, 4% electricity, and 5%

other types of fuels (including wood).

Thirteen percent reported signs of dampness

at home, and 3.2% reported indoor molds.

This indicates that only a minority had a

high exposure to particles from indoor wood

or coal burning, and visible indoor molds

were rare, possibly due to the cold and

dry climate.

ETS exposure is also common in Chinese

homes (Yang et al. 1999). After controlling

for age, sex, parental asthma or allergy, and

exposures at school, we found associations

between ETS exposure at home and both

asthmatic symptoms and respiratory infections. Significant associations with respiratory

infection also presented in the subset of subjects with missing answers on ETS. This indicated there might be ETS exposure within

this group (no significant associations were

found for other respiratory symptoms in this

group). These positive findings are in agreement with other studies on ETS (Hugg et al.

2007; Tanaka et al. 2007), but to our knowledge there are fewer data reported from China

(Chen et al. 1988; Qian et al. 2007; Venners

et al. 2001). Another common indoor problem in dwellings is chemical emission from

new building materials such as paint, floor

materials, and furniture. We found an

increase of both wheeze and daytime attacks

of breathlessness in homes with new furniture. This could be explained by the emission

of formaldehyde or other chemicals from new

furniture. To our knowledge, there are no

previous international publications on associations between respiratory symptoms and new

materials in Chinese dwellings.

In conclusion, indoor exposure at school

to chemical air pollutants of mainly outdoor

origin such as SO2, NO2, and formaldehyde

was associated with asthmatic symptoms.

ETS and emissions from new furniture in the

dwelling could influence the prevalence of

asthmatic symptoms in schoolchildren in

Taiyuan city. Moreover, our study indicated

a need for further measurements and epidemiologic studies on indoor and outdoor

formaldehyde in China and in warmer climates. This is one of the few studies from

mainland China on respiratory health effects

in relation to the school environment. From

a public health perspective, it is important to

create a school environment that does not

impair children’s respiratory health.

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