Title: The impact of climate and NO2 outdoor pollution on

prevalence of asthma and allergic rhinitis in Italy.

de Marco R, Poli A, Ferrari M, Accordini S, Giammanco G, Bugiani

M, Villani S, Ponzio M, Bono R, Carrozzi L, Cavallini R,

Cazzoletti L, Dallari R, Ginesu F, Lauriola P, Mandrioli P,

Pattaro C, Perfetti L, Pignato S, Pirina P, Sartori S, Struzzo P.

1

ABSTRACT

The impact of climate and long-term exposure to nitrogen

dioxide (NO2) pollution on asthma and allergic rhinitis was

assessed in a cross-sectional study, carried on in 1999-2000 on

young adults 20-44 yrs old (n=18,873), living in 13 areas from two

different Italian climatic regions (sub-continental and

Mediterranean).

Meteorological data (annual mean temperature (AT) and

temperature range (TR)) and NO2 measurements were collected in each

community for the period 1996-99.

A climate indicator (CLI) was computed as a linear function of

AT and TR and multilevel models were used to assess the effect of

CLI and NO2 adjusting for individual risk factors. Mediterranean

areas had significantly higher prevalence of asthma like symptoms

(p<0.001), mean AT (16.2° vs 12.9°) and lower TR (15.9° vs 22.1°)

and NO2 levels (31.46 vs 57.99) than sub-continental ones. One

increase in one standard deviation of CLI significantly increased

the risk of wheeze (OR=1.23; 95%CI: 1.13-1.34), tightness in the

chest (OR=1.21; 95%CI: 1.11-1.32), shortness of breath (OR=1.21;

95%CI: 1.08-1.36) and asthma attacks (OR=1.19; 95%CI: 1.07-1.31).

After adjusting for the climate effect, an increase of 18.3 g/m3

2

in NO2 levels increased moderately the risk of asthma attacks

(OR=1.13; 95%CI: 0.98-1.32), wheeze (OR=1.11; 95%CI: 0.96-1.28)

and tightness in the chest (OR=1.11; 95%CI: 0.98-1.21). The

increase in NO2 outdoor levels significantly increased the risk of

having allergic rhinitis in the Mediterranean region (OR=1.38;

95%CI: 1.12-1.69) but not in the sub-continental one (OR=1.03;

95%CI: 0.83-1.28).

Our results show that the prevalence of asthma increases when

AT increases and TR decreases: furthermore climate interacts with

NO2 outdoor exposure increasing the risk for allergic rhinitis in

people exposed to stable high temperatures. A potential long term

role for NO2 pollution on asthma is also suggested.

3

INTRODUCTION

Asthma and allergy affect a substantial proportion of the

population and have shown an increasing trend in western

countries. The two international studies on asthma in adults

(ECRHS 1996) and in children (Pearce 1993) have documented up to

tenfold regional differences in the prevalence of asthma and

atopic diseases. Britain, Australia, New Zealand and the USA

showed the highest prevalence rates, whereas Eastern and

Continental Europe, China and Indonesia the lowest. This

variation is not an artefact due to a cultural bias or difference

in diagnostic habits, as it was confirmed when objective markers

of asthma (Chinn 1997) and atopy (Burney 1997) were used.

The reasons for such a wide variation are so far unexplained.

Genetics could be involved to a minor extent, because a

substantial heterogeneity is present among countries with

genetically similar populations or even within the same country.

Environmental factors are likely be involved in explaining this

geographical pattern. Among these, climate could be a candidate.

The influence of climate on asthma has been addressed in several

studies, with contrasting results according to whether acute or

long-term effects were considered. Although on a short-term scales

4

low temperatures may have a direct effect resulting in

exacerbations of asthma symptoms (Piccolo 1988; Lim 1991; Lecha

1998), warmer average temperatures seem to be associated with

increased asthma prevalence (Hales 1998; Guo 1999). In a recent

analysis of international ECRHS data base, a positive association

was found between asthma and asthma-like symptoms prevalence and

the average non-summer temperature (Verlato 2000).

Air pollution is another possible culprit. Researchers have

paid special attention to nitrogen dioxide (NO2) exposure, which

has steadily risen due to increased traffic activity. However,

epidemiologial and clinical studies have mainly addressed the

acute effects of NO2, whereas few population based studies have

evaluated long-term exposure to NO2 with inconsistent results

(Jarvis 1996, Braun-Farlander 1997, Hirsch 1999).

The aim of this study was to evaluate to which extent climate

and outdoor NO2 pollution can explain the geographical variation in

the prevalence rates of asthma and allergic rhinitis, and to

estimate the relative risk for the exposure to different levels of

these two factors. For this purpose, the data collected in the

frame of the multicentre study ECRHS-ITALY 2000, carried out

between January 1999 and June 2000 in nine Italian centres in

northern, central and southern Italy, were used.

5

METHODS

Study design and questionnaire

ECRHS-ITALY 2000 is a multicentre cross-sectional survey on

the young adult population, planned by the Italian group which

performed the former European Community Respiratory Health Survey

(ECRHS) in Italy (ECRHS-Italy 1995). It is an extension of the

first study, partially using the same methodology, specifically

aimed to assess: i) the variations of asthma, asthma-like symptoms

and chronic bronchitis prevalence in Italy; ii) the current

management of asthmatics and the individual and social costs of

asthma in Italy. The survey was carried out between February 1999

and June 2000.

Nine centres participated in the study: six in northern Italy

(Ferrara, Pavia, Sassuolo, Torino, Udine, and Verona); one in

central Italy (Pisa, which comprised the areas of Livorno, Lucca,

and Pisa); and two in southern Italy (Sassari, on the Island of

Sardinia, and Siracusa, on the Island of Sicily, which comprised

three small sub-areas corresponding to three different air

pollution monitoring stations: Augusta, BorgoPriolo, and

Siracusa). All the northern centres belonged to the subcontinental

6

climatic region, while the central/southern centres belonged to

the Mediterranean climatic region. The two climatic regions differ

with respect to the annual mean temperature and to the annual

temperature range. Figure 1 shows the climatic map of Italy with

the centres participating in the study.

The design of the study was the same used in ECRHS stage 1

(ECRHS 1994): each centre identified an up-to-date sampling frame

of the residents of the target area, from which a random sample of

about 3000 people aged 20-44 years (men/women ratio=1/1) was

selected. A two-page screening questionnaire was mailed to each

subject up to three times in the case of non response; finally the

questionnaire was administered by phone to the remaining non

responders.

The questionnaire used has been published elsewhere (de Marco

1999). The first page contained validated questions on the

presence of asthma and asthma-like symptoms, the frequency of

asthma attacks, time of onset and remission of asthma, doctor

diagnosis of asthma, the presence of chronic cough and phlegm, and

smoking habits. The second page collected information related to

indirect costs and use of health services because of asthma. It

was to be filled in only by subjects reporting asthma symptoms.

7

Air Pollution and climatic data

In all the centres, NO2 levels were monitored by Local

Authorities according to Italian Government law on air quality

control. The sampling was made at fixed sites, chosen in

accordance with Local Environmental Authorities: in each area one

or more monitoring sites were chosen close to the living area of

the participant subjects, and not strongly influenced by specific

local pollution sources, such as traffic and industries

(background exposure). NO2 levels were measured continuously with

chemiluminescence. A quality control surveillance was done in each

area twice a month by the local Authorities. The reported annual

mean data were calculated on the hourly mean concentration of NO2.

Overall, data on mean annual NO2 concentration from 13

area/subareas were obtained. The monthly average temperature for

each area was obtained from official meteorological statistics

(Istituto Centrale di Statistica 1998) for the year 1997. The

annual temperature range was defined as the difference between the

average temperature of the hottest and coldest month. As the

average annual temperature and the annual temperature range were

strongly correlated in Italy, each area was characterised by a

climatic indicator (CLI) computed as a linear function of the two

8

variables. For this purpose a Principal Component Analysis of the

mean annual temperature and annual temperature range was

performed, and each area/subarea was assigned the respective score

on the first factor [citare qualche testo o articolo su PCA]. CLI was

strongly and negatively associated with the annual temperature

range (r=-0.98) and positively associated with the mean

temperature (r=0.98).

Data management and statistical analysis

Subjects were classified as having: wheeze, tightness in the chest,

and shortness of breath if they answered affirmatively to the following

questions respectively: “Have you had wheezing or whistling in

your chest at any time in the last 12 months?", “Have you woken up

with a feeling of tightness in your chest at any time in the last

12 months?”, “Have you been woken by an attack of shortness of

breath at any time in the last 12 months?”; asthma attacks, in the

case of a positive response to the question: “Have you had an

attack of asthma in the last 12 months?”; allergic rhinitis, in the case

of a positive response to the question: “Do you have any nasal

allergies, including hay fever?". Current use of asthma drugs was

considered present if subjects answered affirmatively to the

9

question: “Are you currently taking any medicines (including

inhalers, aerosols or tablets) for asthma?”.

Subjects were classified as: non-smokers, if they had not

smoked as a long as a year at least one cigarette per day or one

cigar a week; ex-smokers if they had smoked for at least one year

but not during the last month; smokers if they had smoked for at

least one year and also during the last month. Subjects were also

classified according to socio-economic status in six groups:

managers, entrepreneurs and businessmen; clerks; workers; retired

and unemployed persons; housewives and students; other conditions.

As the centres had different final cumulative response rates

obtained with different rates to the postal waves and different

percentages of telephone interviews, for the sake of comparison

the prevalence rates were adjusted for cumulative response rate

and type of contact (telephone versus postal), and for age and sex

as well. For this purpose, each subject was attributed the median

of the cumulative response rate of the contact to which he/she had

answered (first, second, third postal contact and telephone

interview) and a dummy indicator of the type of interview

(telephone versus postal). Adjusted prevalence rates were then

obtained through a logistic regression model, considering symptoms

as the dependent variable (present versus absent) and sex, age

10

(categorised in five-years age classes), cumulative response, and

type of interview as the covariates. Prevalence in each centre was

estimated setting the distribution of age, sex and type of contact

equal to the overall distribution, and the cumulative response to

the overall mean (Hosmer 1989). Adjusted prevalence rates with

their 95% confidence intervals were obtained using STATA software,

release 7.0 (StataCorp, College Station, TX, USA).

Heterogeneity of the prevalence rates between regions was

assessed by decomposition of the total chi-square according to

Fleiss (Fleiss 1981).

Multilevel binary response models (Goldstein 1995), with

subjects nested within areas/subareas, were used to assess the

independent effect of outdoor NO2 exposure and climate on

individual symptoms. Odds ratios were adjusted for sex, age,

smoking habits, social class, season of response, cumulative

response and type of interview. The models had a random intercept

term at the level of the area/subarea and all predictor variables

as fixed effects. The mean annual NO2 concentration and the climate

indicator were divided by their standard deviation, in order to

express their effect on the prevalence for a change in one

standard deviation (18.3 g/m3 and 1.385 units, respectively). When

a significant interaction between climatic region and NO2 was

11

present, the association between NO2 and the prevalence of symptoms

was estimated by fitting the previous models within each climatic

region (sub-continental and Mediterranean). MLwiN software

(Rasbash 2000) was used to fit all the multilevel regression

models.

12

RESULTS

Out of 25969 eligible subjects in nine centres, 18873 filled

in the questionnaire, with an overall response rate of 72.7%

(Table 1). The percentage of women among responders was 50.7%

(95%CI: 49.9%-51.4%), not significantly different from what was

expected (50%) according to the design of the study, and the

average age of participants was 33.1 years (sd=6.9).

A substantial and statistically significant variation in the

prevalence rates of asthma-like symptoms, asthma and allergic

rhinitis was present among Italian centres, with the Mediterranean

region showing higher rates than the subcontinental region

(wheeze, p<0.001; shortness of breath, p<0.001; tightness in the

chest, p<0.001; asthma attacks, p<0.001; allergic rhinitis,

p=0.05) (Table 2).

The subcontinental region was characterised by a wider

temperature range (22.1 C° versus 15.9 C°) and a lower annual mean

temperature (12.9 C° versus 16.2 C°) than the Mediterranean region

(Table 3). The climate indicator (CLI) always had negative values

for the subcontinental areas and positive values for the

Mediterranean sub-areas. The annual mean concentration of NO2

showed a wide variation (p<0.001) among the monitoring stations

13

corresponding to the 13 areas/subareas, with the subcontinental

region having approximately a two fold average exposure to outdoor

NO2 with respect to the Mediterranean region in each season (Figure

2).

Figures 3a-b show the ecological relationship between wheeze

prevalence, the climate indicator (CLI) and the outdoor NO2

concentration. A strong positive correlation between wheeze

prevalence and the climate indicator was present, indicating that

centres characterised by a higher average annual temperature and a

lower temperature range had the highest prevalence (Figure 3a); an

overall negative association between wheeze and NO2 emerged, due to

the fact that areas/subareas from the Mediterranean climatic

region had lower NO2 outdoor exposure levels. However, when the

association between prevalence and NO2 was considered within each

climatic region, a positive relationship emerged (Figure 3b). This

result exemplifies the pattern of most symptoms, as can be seen in

Table 4, where the effects of climate alone and NO2 alone on

respiratory symptoms are presented. Climate was significantly and

positevely associated with all the asthma-like symptoms except

allergic rhinitis, while NO2 outdoor concentration showed an

opposite pattern. When climate and outdoor NO2 levels were mutually

adjusted (Table 5), climate remained the main determinant of

14

asthma attacks (OR=1.32; 95%CI: 1.12-1.56), wheeze (OR=1.34;

95%CI: 1.16-1.56) and tightness in the chest (OR=1.33; 95%CI:

1.17-1.52). After adjusting for climate, NO2 outdoor exposure was

positively associated with wheeze, asthma attacks, and tightness

in the chest: an increase of 18.3 g/m3 in NO2 exposure increased

the risk of at least 11% of having these symptoms, even if the

association did not reach a statistical significance when using

two tailed tests (p-values ranging from 0.09 to 0.15). A

statistical significant interaction was found between climatic

region and NO2 only for allergic rhinitis (p<0.001), pointing out

that the association between NO2 and the prevalence of allergic

rhinitis varies according to the climatic region (Table 6). NO2 was

not associated with the prevalence of allergic rhinitis in the

subcontinental region (OR=1.03; 95%CI: 0.83-1.28), while it was

significantly associated in the Mediterranean region (OR=1.38;

95%CI: 1.12-1.69).

15

DISCUSSION

The main results of the analysis of the ECRHS-Italy 2000 data,

are:

climate is a strong determinant of asthma attacks and asthma-

like symptoms: low annual temperature range and high annual

temperature (Mediterranean climate) increase the risk of having

asthma. In multicentre studies on air pollution, when centres

belong to different climatic areas, climate could be a strong

confounder if not controlled;

Mediterranean climate has a synergistic effect, with NO2 outdoor

exposure incresing the risk for allergic rhinitis;

the positive association between NO2 outdoor exposure and most

asthma-like symptoms suggests a long-term role of outdoor

pollution in increasing the risk of having asthma and asthma-

like symptoms.

Several studies have assessed the short-term effect of climate

on asthma in different geographic areas, reporting an increase in

daily incidence of acute attacks of asthma on cold and very cold

days (Piccolo 1988; Lim 1991; Lecha 1998). Low temperatures may

have a direct effect, resulting in exacerbations of asthma

16

symptoms by inducing lower airway obstruction in patients with

cold-sensitive asthma (Millqvist 2000).

Few studies have addressed the long-term effect of climate on

asthma. In New Zealand a positive linear association between

average annual temperature and asthma prevalence (Hales 1998) was

found in adults, while in Taiwan a positive association was found

between non-summer temperatures and asthma prevalence in children

(Guo 1999). An ecological analysis of international ECRHS data

(Verlato 2001) suggested that asthma and asthma-like symptoms

increase as the winter temperature increases and the summer

temperature decreases.

Our analysis of Italian data, which guarantee a substantial

variation in climatic conditions, clearly showed that asthma and

asthma-like symptom prevalence increase in those centres

characterized by a higher annual average temperature and a lower

temperature range. Mediterranean centres, situated on or near the

coast, showed higher asthma and asthma-like symptoms prevalence,

in agreement with previous geographical studies reporting a

coastal effect (Laor 1993; Peat 1995).

Given the high correlation between average temperature and

temperature range in the Italian centres, it was impossible to

disentangle the specific effects of the two climate features. The

17

reason for the climate effect on the prevalence of asthma symptoms

is unclear. Higher temperatures and humid coastal climate are

associated with higher levels of allergen exposure. An increased

prevalence of asthma and sensitization to house dust mites

allergen has been found in schoolchildren living at sea level

(Marseille), compared to schoolchildren living in the Alps

(Charpin 1991). In fact, it is known that house dust mites are

more common in coastal, temperate and subtropical climates (Peat

1993; Warner 1996; Alvarez 1997) as well as moulds (Cross 1997),

while cold environment inhibits the growth of both house dust

mites and moulds.

Some acute effects of high temperatures on human morbidity and

mortality have been attributed to increased levels of the ozone,

which tend to peak on high temperature days (Thurston 1999).

Recent studies suggest that there may also be a long-term health

impact of chronic ozone exposure, particularly in the decrement of

baseline lung function and in the development of new cases of

asthma (Nishino 1996; Greer 1993; Kuenzli 1997). Unfortunately,

the data on ozone exposure were not available for all centres at

the time of this analysis. [rif. ozono nel sud Italia]

One could argue that climate could mask a social-economic

effect, since Italian Mediterannean areas had a lower economic

18

development than northern ones in the last century. However, in

our analysis we adjusted for both individual social status and

smoking habits, so that the climate effect emerged in our analysis

is not due to differences in the previous potential confounding

factors.

While climate strongly influences asthma, overall it does not

show a statistically significant association with the prevalence

of allergic rhinitis. This probably reflects the fact that

allergic rhinitis is to a large extent a pollen related disease,

and the type of pollen varies widely even within Italian climatic

regions (D'Amato 1998). The different influence that climate

exerts on asthma and allergic rhinitis respectively suggests that

the two diseases have different environmental determinants in

their causal path. [Diaz-Sanchez 1998/99 – interazione NO2/clima]

The second result of our analysis is related to both the

confounding and the modifying effect of climate on the

relationship between outdoor NO2 pollution and asthma and allergic

rhinitis. In Italy, as in other countries, the climatic trend from

north to south entails a different degree of economic development,

urbanization and industrialization (..); accordingly, the

Mediterranean areas are characterized by lower levels of NO2, which

is mainly due to road transport and combustion processes (Holman

19

1999). For this reason, Mediterranean climate is associated with

increased asthma prevalence and reduced NO2 pollution, and the

opposite holds for the sub-continental climate. As a consequence,

when the association between outdoor NO2 (or other compounds)

pollution and asthma prevalence is studied in different climatic

regions, the crude estimate, which does not control for climate,

is biased (see Table 4) and could lead to completely misleading

results.

Furthermore, our analysis has shown that climate and NO2

pollution have a synergistic effect on allergic rhinitis: indeed,

the increase in NO2 outdoor levels significantly increased the risk

of having allergic rhinitis in the Mediterranean region (OR=1.38;

95%CI: 1.12-1.69), but not in the sub-continental one (OR=1.03;

95%CI: 0.83-1.28), despite the fact that the former had lower

level of NO2 than the latter. Up to now, there is no consistent

evidence from epidemiological studies that high levels of NO2

outdoor exposure increase the prevalence of nasal allergy and hay

fever (Von Mutius 2000; Jones 1998). Experimental studies have

shown that the inflammatory effect of NO2 exposure on the nasal

respiratory epitelium is minimal for normal subjects (Carson

1993), while it could be relevant in susceptible subjects. A 6-

hours exposure to moderate levels of NO2 in subjects with a

20

previous history of nasal allergy may ‘prime’ eosinophils for

subsequent activation by allergen (Wang 1995). Our result seems to

suggest that the effect of the exposure to NO2 on the prevalence of

allergic rhinitis largely depends on the climatic scenario of the

area where the exposure occurs. This could be either because the

effect of NO2 at stable, higher temperatures (Mediterranean

climate) may aggravate the inflammation of respiratory epitelium

in susceptible subjects, making them more prone to react to

airborne allergens (Gluck 2000), or because higher temperatures

could favour the adjuvant effect of NO2 (or other pollution

components), potentiating the pollen effect (Steremberg 1999), or

both. Finally, air pollution and climatic variations could also

have an indirect effect on allergic response by influencing the

pollen production by allergenic plants both quantitatively and

qualitatively (D'Amato 2000).

In our analysis, when climate and outdoor NO2 levels were

mutually adjusted, the exposure to this pollutant resulted

positively associated with all asthma-like symptoms but shortness

of breath. In fact, the effect of NO2 was consistent on most

symptoms, and the strength of the relationship would have been

statistically significant at 5% level for tightness in the chest

and asthma attacks performing one tailed rather than two tailed

21

tests (p=0.046 and p=0.049, respectively). The choice of

performing one tailed tests could have been justified considering

that the effect of pollutants on health is negligible at the most

but surely cannot be protective.

Since NO2 is considered to be a traffic indicator whose

concentration is highly related to other traffic pollutants (i.e.

particulates), our results suggest a long-term effect of traffic

pollution on the prevalence of asthma-like symptoms.

Epidemiological and clinical studies have mainly addressed the

acute effects of NO2 on respiratory health (Schwartz; Braun-

Farlander; Tenias), while few population based surveys have

evaluated the consequences of long-term exposure. Some studies

have found no effect of long-term exposure to NO2 on asthma and

wheeze (Braun-Farlander 1997; Hirsch 1999), whereas other authors

have reported an association between traffic related NO2 exposure,

the prevalence of asthma (Studnicka 1997) and lung function

parameter decrease (Ackermann-Liebrich 1997). The discrepancy of

the results may be partly due to the fact that in none of these

studies the confounding effect of temperature and/or climate was

adjusted for.

In interpreting our results, some points should be considered.

Up to now, ECRHS-ITALY 2000 is the largest epidemiological study

22

on adult asthma carried out in Italy, and the first to allow a

direct comparison of prevalence rates in the two Italian climatic

regions. The response rate was relatively high, guaranteing the

representativeness of the target population. In our analysis we

adjusted for the potential bias which could have occurred due to

difference among centres either in the way the study was performed

(response rate, type of interview, season of response) or in

individual characteristics (age, sex, smoking habits and social

class). Consequently our results truly represent the interplay of

the effects of climate and NO2 pollution on the prevalence of self-

reported asthma and allergic rhinitis in the centres participating

in the survey. However, the centres involved in the study,

particularly the only three Mediterranean centres, may be not

representative of the whole Italian climatic regions, so our

inference cannot be immediately extended to the whole Italian

reality.

Self-reported symptoms were used to estimate the prevalence.

As a consequence, part of the observed variation could be

explained by cultural differences in the reporting of symptoms.

However the questions used to collect information on symptoms were

the same used in the ECRHS (ECRHS 1996) and ECRHS has clearly

demonstrated at an international level that variation in

23

prevalence of reported symptoms reflects variation in objective

markers of asthma and atopy, like bronchial hyperresponsiveness

(Chinn 1997), specific IgE and skin prick tests (Burney 1997).

Accordingly, cultural differences in symptoms reporting are to a

large extent a negligible source of bias when interpreting the

geographical pattern of prevalence in Italy.

As in many other environmental epidemiological studies, the

average concentration of NO2, obtained by official monitoring

stations in each area, was used as a measure of NO2 outdoor

exposure. If this aggregate measure is a good proxy to

characterize the average exposure of people living in a certain

area, certainly it is not to assess the individual exposure. This

kind of misclassification of the individual exposure (non-

differential misclassification) entails an underestimation of the

effect (Rothman ultima edizione). So it is likely that our

estimates of the effect of NO2 outdoor exposure on asthma symptoms

and allergic rhinitis underestimate the true effect.

In conclusion, our analysis shows that in Italy the prevalence

of asthma increases when the annual mean temperature increases and

the temperature range decreases (Mediterranean climate) and that

the effect of NO2 outdoor pollution on the risk of having allergic

rhinitis is affected by climatic conditions. Furthermore, the

24

positive association between NO2 levels and most asthma-like

symptoms, indipendent on climate, suggests a potential long-term

role of this pollutant in increasing the risk of having asthma and

asthma-like symptoms.

25

REFERENCES

The European Community Respiratory Health Survey. Medicine and

Health. European Commission, Directorate-General XII, Office for

Official Publication, L-2920 Luxembourg, 1994.

European Community Respiratory Health Survey. Variations in the

prevalence of respiratory symptoms, self-reported asthma attacks,

and use of asthma medication in the European Community Respiratory

Health Survey (ECRHS). Eur Respir J 1996; 9: 687-95.

Pearce N, Weiland S, Keil U, et al. Self-reported prevalence of

asthma symptoms in children in Australia, England, Germany and New

Zealand: an international comparison using the ISAAC protocol. Eur

Respir J 1993; 6: 1455-61.

Chinn S, Burney P, Jarvis D, Luczynska C. Variation in bronchial

responsiveness in the European Community Respiratory Health Survey

(ECRHS). European Respiratory Journal 1997; 10:2495-501.

Burney P, Malmberg E, Chinn S, Jarvis D, Luczynska C, Lai E. The

distribution of total and specific serum IgE in the European

26

Community Respiratory Health Survey. Journal of Allergy & Clinical

Immunology 1997; 99:314-22

Bjorksten B et al. Prevalence of childhood asthma, rhinitis and

eczema in Scandinavian and Eastern Europe. Eur. Respir. J

1998;12:432-437

Von Ehrenstein O, von Mutius E, Illi S, Hachmeister A, von Kries

R. Reduced prevalence of atopic diseases in children living on a

farm. Epidemiology 1998;9:s118

Godfrey RC. Asthma and IgE levels in rural and urban communities

of the Gambia. Clin Allergy 1975;5:210-207

Holgate ST. The epidemic of asthma and allergy. Nature

1999;402,S25 november,B2-B4

Cookson W. The alliance of genes and environment in asthma and

allergy. Nature 1999;402,S25 november,B5-B11

Von Mutius E, Weiland SK, Fritzsch C, Duhme H, Keil U. Increasing

prevalence of hay fever in two areas of West and East

Germany.Lancet 1998;351:862-866

27

Ackermann-Liebrich U, Luenberger P, Schwartz J,et al. Lung

function and long-term exposure to air pollutants in Switzerland.

Study on air pollutin and lung diseases in adults (SAPALDIA) Team.

Am J Respir Crit Care Med 1997;155:122-9

Oglesby L, Kunzli N, Monn C, Scindler C, Ackerman-Liebrich U,

Luenberger P. Validity of Annoyance Scores for Estimation of Long-

Term Air Pollution Exposure in Epidemiologic Studies. Am J

Epidemiol 2000; 152:75-83

Breslow NE & Day NE. Statistical method in cancer research.

Capter VI. IARC Lyon 1980

Fleiss JL. Statistical methods for rates and proportion. New York

Wiley & Sons 1981,pp138-143

Bruzzi P, Green SB, Byar DP, Brinton LA, Schairer C. Estimating

the population attributable risk for multiple risk factors using

case control data. Am J Epidemiol 1985;122:904-14

28

European Community Respiratory Health Survey - Italy. Prevalence

of asthma and asthma symptoms in a general population sample from

northern Italy. European Community Respiratory Health Survey--

Italy. Allergy 1995; 50:755-9.

Piccolo MC, Perillo GM, Ramon CG, Di Dio V. Outbreaks of asthma

attacks and meteorologic parameters in Bahia Blanca, Argentina.

Ann Allergy 1988; 60: 107-10.

Lim TO, Looi HW, Harun K, Marzida. Asthma and climatic conditions:

experience from Kuantan, Malaysia. Med J Malaysia 1991; 46: 230-4

Lecha Estela LB. Biometeorological classification of daily weather

types for the humid tropics. Int J Biometeorol 1998; 42: 77-83.

Verlato G, Calabrese R, De Marco R. Correlation between asthma and

climate in the EC Respiratory Health Survey

Hales S, Lewis S, Slater T, Crane J, Pearce N. Prevalence of adult

asthma symptoms in relation to climate in New Zealand. Environ

Health Perspect 1998; 106: 607-10.

29

Millqvist E, Johansson A, Bende M, Bake B. Effects of nasal air

temperature on FEV1 and specific airways conductance. Clin Physiol

2000; 20: 212-7.

Guo YL, Linn YC, Sung FC, Huang SL, Ko YC, Lay YS, Su HJ, Shaw CK,

Linn RS, Dockery DW. Climate, traffic-related air pollutants, and

asthmatic prevalence in middle-school children in Taiwan. Environ

Health Perspect 1999; 107: 1001-6.

Goldstein H. Multilevel Statistical Models. London, Edward Arnold:

New York, Wiley, 1995.

Rasbash J, Browne W, Goldstein H, Yang M, Plewis I, Healy M,

Woodhouse G, Draper D, Langford I, Lewis T. A User’s Guide to

MLwiN. Version 2.1. Multilevel Models Project. Institute of

Education, University of London, 2000.

de Marco R, Zanolin ME, Accordini S, Signorelli D, Marinoni A,

Bugiani M, Lo Cascio V, Woods R, Burney P, on behalf of the ECRHS.

A new questionnaire for the repeat of the first stage of the

European Community Respiratory Health Survey: a pilot study. Eur

Respir J 1999; 14: 1044-8.

30

Peat JK, Tovey E, Mellis CM, Leeder SR, Woolcock AJ. Importance of

house dust mite and Alternaria allergens in childhood asthma: an

epidemiological study in two clinatic regions of Austrialia. Clin

Exp Allergy 1993; 23: 812-20.

Warner AM, Bjorksten B, Munir AK, Moller C, Schou C, Kjellman NI.

Childhood asthma and exposure to indoor allergens: low mite levels

are associated with sensitivity. Pediatr Allergy Immunol 1996; 7:

61-7.

Alvarez MJ, Olaguibel JM, Acero S, Quirce S, Garcia BE, Carrillo

T, Cortes C, Tabar AI. Indoor allergens and dwelling

characteristics in two cities in Spain. J Investig Allergol Clin

Immunol 1997; 7: 727-7.

Cross S. Mould spores: the unusual suspects in hay fever.

Community Nurse 1997; 3: 25-6.

Laor A, Cohen L, Danon YL. Effects of time, sex, ethnic origin,

and area of residence on prevalence of asthma in Israeli

adolescents. Brit Med J 1993; 307: 841-844.

31

Peat JK, Toelle BG, Gray EJ, et al. Prevalence and severity of

childhood asthma and allergic sensitisation in seven climatic

regions of New South Wales. Med J Aust 1995; 153: 22-26.

Charpin D, Birnbaum J, Haddi E, et al. Altitude and allergy to

house dust mites. A paradigm of the influence of environmental

exposure on allergic sensitizations. Am Rev Respir Dis 1991; 143:

983-986.

D'Amato G, Spieksman FT, Liccardi G, Jager S, Russo M, Kontov-Fili

K, Micchels H, Weuthrich B, Bonini S. Pollen related allergy in

Europe. Allergy 1998;53:567-78

Holman C. Sources of air pollution. In Air Pollution and Health.

Ed. by Holgate ST, Samet JM, Koren HS, Maynard RL. Academic Press-

London 1999;pp115-148

Nishino N, Abbey DE, McDonnel WF. Long-term ambient concentration

of ozone and development of asthma:the AHSMOG study. Epidemiology

1996;7:S31

32

Greer JR, Abbey DE, Burchette RJ. Asthma related to occupational

and ambient air pollution in non smokers. J. Occup. Med

1995;35:909-915

Kunzli N, Lurmarin F, Segal M et al. Association between lifetime

ambient ozone exposure and pulmonary function in college freshmen.

Results of a pilot study. Environ Res 1997; 72,8-23

Thurston GD, Kazuhiko I. Epidemiological studies of ozone exposure

effects. Ed. by Holgate ST, Samet JM, Koren HS, Maynard RL.

Academic Press-London 1999;pp 485-510

Carson JC, Collier AM, Hu SS, Devlin RB. Effect of nitrogen

dioxide onhuman nasal epithelium. Am J Respir Cell Mol Biol

1993;9:264-270

Wang JH, Devalia JL, Dudlle JM et al. Effect of six-hours exposure

to nitrogen dioxide on early-phase nasal response toallergen

challenge in patients with a history of seasonal allergic

rhinitis. J Allergy Clin Immunology 1995;96:669-676

33

Zemp E, Elsasser S, Shindler C et al. Long-term ambient air

pollution and respiratory symptoms in adults (SAPALDIA) Am J

Respir Crit Care Med 2000 in press

Forsberg B, Stjenberg N, Wall S. People can detect poor air

quality well below guidline concentration: a prevalence study of

annoyance reactions and air pollution from traffic. Occup Environ

Med 1997; 54:44-48

Jones NS, Carney AS, Davis A. The prevalence of allergic

rhinosinusitis: a review. J Laryngol Otol 1998;112:1019-30

Von Mutius E. The environmental predictors of allergic diseases. J

Allergy Clin Immunol 2000;105:9-19

Steerenberg PA, Dormans JA, van Doorn CC. Middendorp S, Vos JG,

van Lovern H. A pollen model in the rat for testing adjuvant

activityof air pollution components. Inhal Toxicol 1999;11:1109-

22.

Gluck U, Gebbers J. Epithelialchanges in seasonal allergic

rhinitis throughout the year: evidenec of coexistent air pollution

34

and local secretoryIgA deficiency. J Othorinolaryngol Relat Spec

2000; 62:68-75.

D'amato G, Liccardi G, D'Amato M. Environmental risk factors

(outdoor air pollution and climatic changes) and increased trends

of respiratory allergy. J Investig Allergol Clin Immunol

2000;10:123-28

Jarvis D, Chinn S, Luczynska C Burney P. Association of

respiratory symptoms and lung function in young adults with use of

domestic gas appliances. Lancet 1996;347:426-431

Istituto Centrale di Statistica. Annuario di statistiche

meteorologiche. Ed. ISTAT, Rome, 1998.

Hosmer DW Jr, Lemeshow S. Applied Logistic Regression. John Wiley

& Sons, New York, 1989.

35

LEGENDS

Figure 1. Climatic map of Italy. Stars indicate centres

participating in ECRHS-ITALY 2000. PV, Pavia; TO, Torino; VR,

Verona; UD, Udine; SL, Sassuolo; FE, Ferrara; PI, Pisa; SS, Sassari;

SR, Siracusa.

Figure 2. Annual mean concentration of NO2 by season and climatic

region (1996-1999).

Figure 3a. Relationship between wheeze prevalence and the climate

indicator (CLI). The continuous line represents the linear

regression of the arcsin prevalence on CLI, weighted by the number

of subjects in each area. The size of symbols is proportional to

the number of subjects in each area.

Figure 3b. Relationship between wheeze prevalence and outdoor NO2

concentration. The continuous line represents the linear

regression of the arcsin prevalence on NO2 mean concentation

considering all the areas, weighted by the number of subjects in

each area. Dotted lines are the regression lines estimated within

36

each climatic region. The size of symbols is proportional to the

number of subjects in each area.

37