SHORT COMMUNICATION

Giuseppe Migliaretti

Æ Ennio Cadum

Æ Enrica Migliore Franco Cavallo 

# Traffic air pollution and hospital admission for asthma: a case–control approach in a Turin (Italy) population

Received: 13 April 2004 / Accepted: 4 August 2004 / Published online: 22 February 2005  Springer-Verlag 2005

Abstract Objectives : This study investigated the relationship between traffic air pollution and asthma, using a case–control design applied to routinely collected data. Methods : Subjects resident in Turin during the period 1997–1999 and admitted for asthma were defined as

cases; patients admitted for causes other than respiratory diseases or heart diseases were defined as controls

. Nitrogen dioxide and total suspended particulate wereconsidered as indicators of traffic air pollution. Statistical analysis were performed, separately for young (0– 14 years), adult (15–64 years) and elderly (>64 years) patients, with a logistic regression model; results are expressed as percentage of risk modification for a 10 g/

m 3 increase in exposure to pollutants. Results : The risk of emergency admissions for asthma rose significantly with increased exposure to nitrogen dioxide [2.4%, 95% Confidence Interval: 0.5%; 4.3%], and total suspended particulate [2.3%, 95% Confidence Interval: 1.1%–3.6%]. The significant association was evident, in particular, among young and elderly patients for both pollutants. Conclusion : Using a case–control design botheasy to use and manage, the study confirms the significant association between hospital emergency admissions for asthma and exposure to nitrogen dioxide and total suspended particulate pollutants.

Keywords Air pollution

Æ Nitrogen dioxide

Æ Total suspended particulate

Æ Asthma

Æ Respiratory health

Æ Emergency admission

Æ Case–controls study 

### Introduction

International literature has documented the short-term and long-term effects that air pollution has on public health and mortality (Dockery et al. 1993 ; Pope et al. 1995 ; Barbone et al. 1994 ; Biggeri et al. 1996 ; Pope et al. 2002). The defining of the potential effects of environmental pollution on health remains a issue in both the attribution of exposure and the identification of many confounding factors, which are often difficult to control. However, one usual outcome of the short-term effects of air pollution is the hospital admission for respiratory causes. Close correlation between an increase in air pollution and the number of hospital admissions for respiratory causes has been shown in European (Vigotti et al. 1996 ; Spix et al. 1998 ; Atkinson et al. 2001 ; Fusco et al. 2001 ; Biggeri et al. 2001 ; Sunyer et al. 2002

, 2003 ) and non-European (Bates and Szito 1987 ; Thurston et al 1992 ; Burnet et al. 1994 ; Schwartz 1994) studies; in particular close association has been shown betweenexposure to urban air pollution and emergency admissions for asthma. In most of those studies, the statistical methods were based on time–series data to control the association for the effects of long-term seasonal variations and/orcyclical components in changes in exposure and frequency of health events. Few studies have used a case– control design to determine the relationship between hospital admission and urban air pollution. A case– control study carried out on the population of Ravenna (Ciccone et al. 1995), to analyse the relationship between the number of hospital admissions and sulphur dioxide levels, showed an association between the risk of admission for chronic bronchitis and increased exposure to sulphur dioxide. A similar study on the Novara population (Panella et al. 2000) showed a positive association between nitrogen dioxide exposure and emergency admissions for respiratory causes. The literature also reports no association betweenurban air pollution and hospital admission for respiraG. Migliaretti ( & )

Æ E. Migliore

Æ F. Cavallo Department of Public Health and Microbiology, University of Turin, Via Santena 5 bis, Turin, Italy E-mail: giuseppe.migliaretti@unito.it Tel.: +39-011-6706559 Fax: +39-011-6706551

E. Cadum Unit of Environmental Epidemiology, Regional Agency of Environmental Protection, Turin, Italy Int Arch Occup Environ Health (2005) 78: 164–169 DOI 10.1007/s00420-004-0569-3tory causes (Wilkinson et al. 1999). For these reasons further investigation are required on the effects of traffic air pollution on public health.



### Objectives

Using a case–control design based on routinely collecteddata, our study analysed the association between exposure to nitrogen dioxide and total suspended particulateand emergency hospital admissions for asthma in subjects resident in Turin in the period from January 1997 to December 1999.



### Materials and methods

Air-pollution data

Air-pollution data were provided by the Regional Agency for Environmental Protection in Piedmont (ARPA), Air Quality Control Division. During the period from January 1997 to December 1999, reliable data were available from ten monitoring stations located in different quadrants of Turin. In agreement with the literature (World Health Organization 1992), in this study, the levels of nitrogen dioxide [NO 2 , measured in microgrammes per cubic metre ( lg/m 3)] and total suspended particulate [TSP, measured in microgrammes per cubic metre ( lg/m 3)] were considered as indicators of traffic air pollution (World Health Organization 1999 ; MicromedeX 2002). NO 2 is a surrogate of components of motor vehicle emission, and TSP, usually considereda proxy indicator for overall air pollution, is also considered a good indicator of exposure to vehicular pollution; for those reasons both pollutants have been considered in our study. All stations monitored hourly NO 2 , using a chemiluminescence method, and TSP, using a b-attenuation method. Other details of the monitoring sites, measurement methods and indicators can be found in the literature (Citta ` di Torino 1999).The various components of airborne pollutants dissolve at different rates; some remain suspended for along time, while others dissolve more rapidly. As suggested by other studies on the short-term effects of air pollution (Katsouyanni et al. 1996 ; Vigotti et al. 1996 ; Sunyer et al. 1997

, 2002

, 2003 ; Spix et al. 1998 ; Atkinson et al. 2001 ; Fusco et al. 2001 ; Biggeri et al. 2001 ), the best indicator for NO 2 exposure is the daily mean level,computed as means of the measurements at the monitoring stations, and for TSP exposure, the means of the daily total levels measured by each monitoring station. Those methods were also used in this study.

Pollution data: how to complete missing data

The missing values at each monitoring station, ranging from 3.3% (36 of the total 1,095 days) to 13.5% (148 of the total 1,095 days) [values comparable with other studies (Sunyer et al. 1997)], were replaced with availablemeasurements from the other monitoring stations, following a common procedure used in other studies (Katsouyanni et al. 1996 ; Sunyer et al. 1997

, 2002

, Vigotti et al. 1996 ; Spix et al. 1998 ; Atkinson et al. 2001 ):
(a) Stations that lacked over 25% of data for the entire study period were excluded (b) The daily data were defined as lacking when either fewer than 75% of the daily hourly data, or over 25% of the 8-h moving average, were not available, with the specification that, for each 8-h interval, at least 75% of the hourly data were required. When data were not available at one or more stations on certain days, they were substituted with the weighted mean of values from other monitoring stations when available.

Briefly: X estimate 1⁄4 X d  X y X

k ;

where X d = daily mean of the other monitoring sites, X y

= k yearly mean of the j monitoring site, X k = mean for the k year of all monitoring sites(c) When information was not available for all monitoring stations, the days with missing values werereplaced with the average of the values of the pollutant recorded the previous and the next day, if these were not missing as well.
In all other cases, the data were reported as missing.

Meteorological data

Meteorological information was drawn from the daily recordings of the Environmental Protection Agency for Piedmont (ARPA), Air Quality Division. Daily mean temperature and humidity were the indicators selectedon the basis of previous epidemiological evidence (Katsouyanni et al. 1996); other meteorological data used in the study were wind velocity and solar radiation.

Admission data

Admission data were extracted from the regional archive of hospital discharge records routinely collected by the Epidemiology Service of the Piedmont Region. The study was based on emergency admissions of patients resident in Turin 1 in the period from January 1997 to December 1999, including those admitted during the final months of 1999 and discharged in 2000. For each patient demographic data, place of residence, period and

1 The population resident in Turin in the period 1997–1999 was approximately 870,000 and there were 12 hospitals in Turin (Banca Dati Demografica Evolutiva Piemonte 2003 ; Citta ` di Torino 1999 ; Costa et al. 1998 ). 165details of admission, and primary and secondary diagnosis were available. In the study we considered separately young patients (0–14 years), adult patients (15–64 years) and elderly patients (>64 years), because some respiratory illnesses, such as the diagnostic category of asthma, may include syndromes of a different nature in children from those in adults and elderly people (Martinez et al. 1995). Case and control groups were defined in accordance with the literature (Ciccone et al. 1995 ; Panella et al. 2000). Based on the patient’s primary diagnosis, coded according to the International Classification of Diseases, 9th Revision (ICD-9), cases were defined as those patients resident in Turin and admitted for asthma (ICD-9 code 493) (ncases =1,401). As suggested in the literature, patients admitted for causes other than respiratory diseases (ICD-9 codes 460–487, 490–492, 494–496 and 500–519) or heart diseases (ICD-9 codes 390–405 and 410–429), because they are associated with air pollution exposures were defined as controls (ncontrols =201,071).

Definition of exposure and control factors

For each pollutant, the average of the level measured on the admission day and on the previous 2 days (lag 2) and the average of the level measured on the admission day and on the previous 3 days (lag 3) were considered as the indicators of exposure. As the literature confirms (World Health Organization 1992 ; Biggeri et al. 2001 ), lag 3 was thought to be a good indicator of a patient’s total exposure. As confirmed by the literature (MicromedeX 2002), nitrogen dioxide and the total suspended particulate, as other pollutants, were influenced by variations in the weather (seasonality) (Fig. 1 ). In the analysis, the month of admission, coded as summer (April–September) and winter (October–March) in accordance with other studies (Sunyer et al. 2003 ) was considered as the seasonality indicator; meteorological parameters considered in the analysis were temperature, humidity, solar radiation and wind velocity. In accordance with other studies (Fusco et al. 2001 ; Sunyer et al. 2002) temperature and humidity were considered the principal meteorological factors influencing the pollutants in the study. The geographical characteristics of Turin suggested ageneral homogeneity in the distribution of meteorological and air pollution levels for day (information by the Public Health Office, Public Health Laboratory, USSL 1, Turin, Italy); for this reason a uniform distribution of the meteorological parameters and the air pollution levels of the city were considered. The other effects of theseason on health were considered to be randomly distributed among cases and controls. The different probability of admission, according to the day of admission, was controlled by the day of the week on which the patient was admitted, classified as day of week (coded 1: Monday, 7: Sunday) and workday or holiday (coded 1: workday, 2: holiday). Otheradjustment factors were gender (coded 1: male, 2: female) and age of patient (considered as continuous variable). Since information about the subjects’ tobacco use and social status were unavailable; education levels (coded 1: elementary, 1–4: graduate) were used to compensate partially for this gap.

Statistical analysis

The pollutants and meteorological factors were considered in the analysis as continuous variables to quantify the increase in risk by unit increase of exposure. The correlation between pollutants and temperature and humidity was analysed by Pearson coefficient (overall period and separately for season). We used logistic regression models (Clayton and Hills 1998 ) to analyse the association between emergency admission for asthma and nitrogen dioxide and total suspended particulate concentrations. The models, which included gender, age, daily mean temperature, daily mean humidity, season (winter/summer), day of the week and holidays, were used separately for each pollutant. To analyse the independent effects of two pollutants, in subsequent analysis both pollutants were included in the same model. On the basis of odds ratio Fig. 1 Nitrogen dioxide and total suspended particulate levels by day of recording (period: 1 January 1997–31 December 1999) 166values estimated by the models, the results have been shown as percentage increase (increase%) in risk and relative 95% confidence interval (95% CI), by 10 lg/m 3increase in nitrogen dioxide and total suspended particulate exposure.



### Results

Table 1 presents a description of nitrogen dioxide and total suspended particulate levels separately for cases and controls; a description of temperature, humidity and number of admission by day (day of the week and workday/holiday) is also included. Figure 1 shows daily pollutant levels in the period January 1997–December 1999, presenting differentconcentrations for cold and warm seasons. A low correlation between daily pollutant, temperature and humidity levels was found (Table 2).Subsequent analyses presented a significant association between a general increase in the risk of emergency admissions for asthma and an increase in exposure to both pollutants (Table 3 , model including one pollutant). The results showed a mean increase of 2.4%, (95% CI: 0.5%; 4.3%) and 2.3% (95% CI: 1.1%; 3.6%) for a 10 lg/m 3 increase in exposure to NO 2 and TSP, respectively. The association was evident, principally, among young and elderly patients for both pollutants: 2.3% (95% CI: 0.3%; 4.4%) and 7.7%, (95% CI: 0.2%; 15.2%) for NO 2 ; 1.9% (95% CI: 0.4%; 3.4%) and 8.3% (95% CI: 2.9%; 13.7%) for TSP, respectively, for young and elderly patients. A positive, but not statistically significant, association was found for the adult patients for both pollutants.

The association between pollutants and the outcome was generally more unstable when both pollutants were included in the same model (Table 3 ), suggesting that the effects observed may be due to particulates derived from source correlated with NO 2 levels, probably trafficrelated sources.



### Conclusions and discussion

Turin, for its geographical characteristics, presents a more homogeneous distribution of meteorological and air pollution levels, by day, throughout the whole city area, in comparison with other cities (Vigotti et al. 1996 ; Fusco et al. 2001 ; Biggeri et al. 2001 ). We found no significant differences (Kruskal–Wallis test p =0.18 and P =0.32 for NO 2 and TSP, respectively) and a positive correlation (Pearson’s correlation coefficient: r =0.71,
p =0.002 and r =0.79, p =0.001 for NO 2 and TSP, respectively) among the ten monitoring stations. For those reasons, the daily mean level for NO 2 and the daily total level for TSP, computed from measurements provided by each station, were considered to be good Table 1 Summary of environmental variables and numbers admitted, by admission day (work/holiday), for cases and controls

Parameter Temperature (C) Humidity (%) NO 2 ( lg/m 3) TSP ( lg/m 3)

Controls Mean 14.3 58.7 112.7 105.3 SD 7.6 17.5 30.2 44.2 Median 14.5 60.7 107.7 95.9 Cases Mean 13.1 58.7 117.1 113.9 SD 7.1 17.6 30.0 43.8 Median 13.2 60.2 113.0 107.2 Total Mean 14.3 58.7 112.7 105.3 SD 7.6 17.5 30.2 44.2 Median 14.5 60.7 107.7 96.0

Workday Holiday Total

Controls

n 197,653 3,418 201,071 Row (%) 98.3 1.7 Cases

n 1,365 3,643 1,401 Row (%) 97.4 2.6 Table 2 Pearson correlation coefficient for NO 2 , TSP and meteorological parameters, total and separately for season

Parameter NO 2 TSP Temperature

Total NO 2 1 TSP 0.80 1 Temperature

0.33

0.45 1 Humidity

0.20

0.04

0.05 Winter NO 2 1 TSP 0.77 1 Temperature 0.09

0.10 1 Humidity

0.24

0.08

0.14 Summer NO 2 1 TSP 0.69 1 Temperature

0.19

0.07 1 Humidity

0.38

0.22 0.23

Table 3 Percentage increase in hospital admissions for asthma by 10 lg/m 3 increase in NO 2 and TSP exposure (and relative 95% CI)

Age category NO 2 TSP

Increase (%) a 95% CI Increase (%) a 95% CI

Inf Sup Inf Sup

Model including one pollutant

<15 years 2.30 0.30 4.40 1.90 0.40 3.40 15–64 years 3.10

0.01 7.70 2.30

0.01 5.20 >64 years 7.70 0.20 15.20 8.30 2.91 13.68 Total 2.40 0.50 4.30 2.30 1.10 3.60 Model including both pollutants

<15 years 1.71

0.02 5.00

0.12

0.03 2.50 15–64 years 1.20

0.06 6.50 0.90

0.04 5.61 >64 years 0.91

0.08 5.91 1.2

0.01 4.32 Total 1.10

0.02 3.82 0.91

0.02 3.11

aComputed as (adjusted OR · 10 lg/m 3 · 100) 167indicators of the NO 2 and TSP daily concentration in Turin. As the literature shows (Holme  ́ n et al. 1997 ; Sunyer et al. 1997), asthma morbidity has been increasing in the past few years, and the reasons have not yet been explained (Department of Health Advisor Group on the Medical Effects of Air Pollution Episodes 1995); in particular, traffic air pollution could exacerbate the existing asthma symptoms (Fusco et al. 2001 ). Our paper focused the effects of traffic air pollution on asthma admissions, showing a positive, significant, association between asthma admission during the period 1997–1999 andexposure to nitrogen dioxide and total suspended particulate. The association was particularly evident amongthe young and elderly patients. The positive but nonsignificant association among the adults patients, in accord with other studies (Sunyer et al. 1997 ; Fusco et al. 2001 ; Biggeri et al. 2001 ), could also be attributable to the difficulty in defining the exposure for the adults (children and elderly people are more sedentary than adults). Moreover, we tried to analyse the independent effectsof two pollutants with a model, including both pollutants in the same model. These models were limited by the collinearity among NO 2 and TSP, generated by the same source (as the correlation coefficient confirms); for this reason the model that included both pollutants was more unstable, and suggests that the effects observed may be due to particulates derived from traffic-related sources correlated with NO 2
. In the interpretation of the results of this study the possible effect of passive smoking (the regional archive of hospital discharge forms did not permit exact control for the subjects’ smoking status), and the risk of diseasemisclassification, frequent in asthma diagnosis, especially in the pre-school population, should be taken into consideration. A confounding factor not considered in the study was indoor exposure; in Turin, residences present a really homogeneous distribution for heating (mostly central heating) and cooking (mostly gas cooking) (Costa et al. 1998 ); for this reason indoor exposure should not affect the results. Studies on the effects of atmospheric pollution on health contend with thorny difficulties, foremost ofwhich are the heterogeneity of pollutants and the difficulty in measuring them accurately. Several groups of common air pollutants in urban air have been the object of studies by the International Agency for Cancer Research (IARC). However, none of the monitors in the air quality control network manages to measure all components directly; thus, no air quality parameter currently measured can be considered exhaustive in the complex and variable mixture that is summarized underthe term ‘urban air pollution’. In this respect the nitrogen dioxide and total suspended particulate pollutants could be considered to be good indicators of exposure to vehicular traffic pollution (World Health Organization 1999 ; MicromedeX 2002). The case–control approach used in this study takes into the model the time of occurrence of the events, even for the series of controls. It has a natural baseline, not influenced by exposure, so that the occurrence among cases and controls can be compared; it needs no adjustments for complex cyclical trends or for introducing smoothing parameters. Despite some limitations, our study shows results comparable to the risks reported in other studies on Italian and European populations and based on design and statistical methods that are difficult to carry out (Burnett et al. 1994 ; Schwartz et al. 1994 ; Spix et al. 1998 ; Atkinson et al. 2001 ; Fusco et al. 2001 ; Biggeri et al. 2001 ; Sunyer et al. 2002

, 2003 ). In conclusion, using a study design that was both easy to use and to bemanaged, we have shown that our results are comparable to those from studies with a more complex design that are published in the literature; in particular, the results show the importance of nitrogen dioxide and total suspended particles in the analysis of the effects of traffic air pollution on public health and underline the need for further research in this area.



### References

Atkinson RW, Anderson HR, Sunyer J, Ayres J, Baccini M, Vonk JM, Boumghar A, Forastiere F, Forsberg B, Touloumi G, Schwartz J, Katsouyanni K (2001) Acute effects of particulate air pollution on respiratory admissions: results from APHEA 2 project. Air pollution and health: a European approach. Am J Respir Crit Care Med 164:1860–1866 Banca Dati Demografica Evolutiva della regione Piemonte (BDDE), a cura del Settore Statistico Regionale (2003) (http:// www.regione.piemonte.it/stat/bdde/index.htm) Barbone F, Bovenzi M, Cavallieri F, Stanta G (1994) Air pollution and lung cancer in Trieste, Italy. Am J Epidemiol 141:1161– 1169 Bates DV, Szito R (1987) Hospital admission and air pollutants in southern Ontario: the acid summer haze effect. Environ Res 43:317–331 Biggeri A, Barbone F, Lagazio C, Bovenzi M, Stanta G (1996) Air pollution and lung cancer, Italy: spatial analysis of risk as a function of distance from sources. Environ Health Perspect 104:750–754Biggeri A, Bellini P, Terracini B (2001) Italian MISA group. Metaanalysis of the Italian studies on short-term effects of air pollution. Epidemiol Prev 25 [Suppl 2]:1–71 Burnett RT, Dales RE, Raizanne ME (1994) Effects of low ambient level of ozone and sulfates on the frequency of respiratory admission to Ontario hospitals. Environ Res 65:172–194Ciccone G, Faggiano F, Falasca P (1995) Inquinamento atmosferico da SO2 e ricoveri ospedalieri a Ravenna: un’analisi casocontrollo. Epidemiol Prev 19:99–104 Citta ` di Torino (1999) Rapporto sullo stato dell’ambiente e sulla sostenibilita ` della Citta ` di Torino. Rapporto Clayton D, Hills M (1998) Statistical models in epidemiology. Oxford Science Publications, Oxford Costa G, Cardano M, Demaria M (1998) Torino: Storie di salute in una grande citta ` . Citta ` di Torino, Ufficio di Statistica, Osservatorio socio-economico Department of Health Advisor Group on the Medical effects of Air Pollution Episodes (1995) Asthma and outdoor air pollution. HMSO, London Dockery DW, Pope CA III, Xu X, Spengler JD, Ware JH, Fay M,Ferris BG, Speizer FE (1993) An association between air pollution and mortality in six US cities. N Engl J Med 329:1753– 1759 168Fusco D, Forastiere F, Michelozzi P, Spadea T, Ostro B, Arca M, Perucci CA (2001) Air pollution and hospital admissions for respiratory conditions in Rome, Italy. Eur Respir J 17:1143– 1150 Holme  ́ n A, Blomqvist J, Frindberg H (1997) Frequency of patients with acute asthma in relation to ozone, nitrogen dioxide, other pollutants of ambient air and meteorological observations. Int Arch Occup Environ Health 69:317–322 Katsouyanni K, Zmirou D, Spix C (1996) Short-term effects ofurban air pollution on health: a European approach using epidemiologic time series data. The Aphea protocol. J Epidemiol Community Health 5 [Suppl 1]:S12–S18 Martinez FD, Wright AL, Halonen M, Morgan WJ (1995) Asthma and wheezing in the first 6 years of life. N Engl J Med 332:133– 138MICROMEDEX healthcare series (2002) (http://www.medicina.unito.it/oldweb/basi_dati.html) Panella M, Palin L, Binotti M, Tommasini V, Di Stanislao F (2000) The role of atmospheric nitrogen dioxide in the risk of hospitaladmission in the patient with respiratory pathology. Epidemiology 11:367–368 Pope A, Thun M, Namboudiri M (1995) Particulate air pollution as a predictor of mortality in a prospective study of US adults. Am J Respir Crit Care Med 151:669–674 Pope CA III, Burnett RT, Thun MJ, Calle EE, Krewski D, Ito K, Thurston G (2002) Lung cancer, cardiopulmonary mortality and long-term exposure to fine particulate air pollution. JAMA 287:1132–1141 Schwartz J (1994) Air pollution and hospital admission for the elderly in Birmingham, Alabama. Am J Epidemiol 139:589–590 Spix C, Anderson HR, Schwartz J (1998) Short-term effects of air pollution on hospital admissions of respiratory diseases in Europe: a quantitative summary of Aphea study results. Arch Environ Health 1:54–64 Sunyer J, Spix C, Quenel P, Ponce-de-Leon A, Ponka A, Barumandzadeh T, Toulumi G, Bacharova L, Wojtyniak B, Vonk J,Bisanti L, Schwartz J, Katsouyanni K (1997) Urban air pollution and emergency admission for asthma in four European cities: the Aphea project. Thorax 52:760–765 Sunyer J, Basagana X, Belmonte J, Anto JM (2002) Effect of nitrogen dioxide and ozone on the risk of dying in patients with severe asthma. Thorax 57:687–693Sunyer J, Atkinson R, Ballester F, Le Tertre A, Ayres JG, Forastiere F, Forsberg B, Vonk JM, Bisanti L, Anderson RH,Schwartz J, Katsouyanni K (2003) APHEA 2 study. Respiratory effects of sulphur dioxide: a hierarchical multicity analysis in the APHEA . Occup Environ Med 60:e2 Thurston GD, Ito K, Kinney PL, Lippmann M (1992) A multiyear study of air pollution and respiratory hospital admission in three New York state metropolitan areas: results for 1988 and 1989 summers. J Expo Anal Environ Epidemiol 2:429–450 Vigotti MA, Rossi G, Bisanti L, Zanobetti A, Schwartz J (1996) Short-term effects of urban air pollution on respiratory health in Milan, Italy, 1980–1989. J Epidemiol Community Health 50 [Suppl 1]: Wilkinson P, Elliott P, Grundy C, Shaddick G, Thakrar B, Walls P, Falconer S (1999) Case–control study of hospital admission with asthma in children aged 5–14 years: relation with road traffic in north west London. Thorax 54:1070–1074 World Health Organization (1992) Acute effects on health of smog episodes. WHO Regional Publications, European Series, no. 43. WHO Regional Office for Europe, Geneva World Health Organization (1999) Guidelines for air quality. WHO, Geneva 169