Secondary Logo

Journal Logo

Short-Term Effects of Air Pollution in a Cohort of Patients With Chronic Obstructive Pulmonary Disease

Faustini, Annunziata; Stafoggia, Massimo; Cappai, Giovanna; Forastiere, Francesco


The Figure legend gives the unit of measure for the interquartile range of pollutants as milligrams. It should be micrograms.

Epidemiology. 24(1):177, January 2013.

doi: 10.1097/EDE.0b013e31826767c2
Air Pollution

Background: Although damage to the respiratory system from air pollutants has been recognized, research on susceptibility to air pollution in patients with chronic obstructive respiratory disease (COPD) has produced contradictory results. We studied the short-term effects of particulate matter (PM10, PM2.5), nitrogen dioxide (NO2), and ozone (O3) on cardiac and respiratory mortality in a COPD cohort. We assessed age, sex, and previous diseases as effect modifiers.

Methods: Using hospital data (1998–2009) and pharmaceutical data (2005–2009), we enrolled 145,681 COPD subjects, aged 35+ years and residents of Rome, and followed them from 2005 to 2009. A comparison group of people without COPD (1,710,557 subjects) was also studied. We analyzed deaths due to all natural causes (International Classification of Diseases - Ninth Revision codes 1–799). Statistical analyses were carried out using Poisson regression and a case-crossover approach.

Results: PM10, PM2.5, and NO2 (0- to 5-day lag) were associated with daily mortality, with stronger effects in people with COPD. The mortality associated with PM10 (per interquartile range [IQR] = 16 μg/m3) was five times more in COPD patients (3.5% [95% confidence interval = −0.1% to 7.2%]) than in other subjects (0.7% [−0.8% to 2.2%]). Effects on respiratory mortality among COPD subjects were particularly elevated from PM2.5 (IQR = 11 μg/m3) (11.6% [2.0% to 22.2%]) and NO2 (IQR = 24 μg/m3) (19.6% [3.5% to 38.2%]). Older age, male sex, preexisting heart conduction disorders, and cerebrovascular diseases were associated with stronger effects in COPD subjects.

Conclusions: COPD patients are more susceptible to air pollutants, especially PM10 and NO2. These results suggest a need for more protective air pollution standards for susceptible groups.

Supplemental Digital Content is available in the text.

From the Department of Epidemiology, Regional Health Service of Lazio, Rome, Italy.

Submitted 26 August 2011; accepted 30 March 2012

Supported, in part, by the Italian Ministry of Health under the “Programma Strategico: Impatto sanitario associato alla residenza in siti inquinati, in territori interessati da impianti di smaltimento/incenerimento rifiuti ed alla esposizione ad inquinamento atmosferico in aree urbane”––Convenzione n. 41, 2008.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article ( This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.

Correspondence: Annunziata Faustini, Epidemiology Department, Regional Health Service of Lazio, V. S. Costanza n 53, 00198 Rome, Italy. E-mail:

Since 1999, the American Thoracic Society1 has recognized adverse effects of air pollution (in particular, particulate matter with an aerodynamic diameter of <10 and <2.5 microns [PM10 and PM2.5]) on outcomes related to chronic obstructive pulmonary disease (COPD). These include airway obstructive symptoms, reduction of forced expiratory volume in the first second and forced vital capacity, increased rate of decline in pulmonary function, increased frequency of hospitalization, and mortality. It is well-known from several multicity observational studies carried out in various parts of the world2 that air pollution damages the respiratory system, and these epidemiologic findings are biologically plausible because airways are the first system targeted by air pollutants. More recently, cohort studies have shown that air pollution may induce both the onset and the acute exacerbation of chronic respiratory diseases.3–5

In the last decade, research interest has shifted toward the hypothesis that people with specific characteristics could be particularly susceptible to air pollutants, with the possibility that the size of susceptible groups in various populations could help explain observed geographical differences in air pollution effects. The World Health Organization has defined susceptibility, in the context of air pollution, as the likelihood of having a significantly larger-than-average response to a specified exposure.6 Several approaches have been used to explore susceptibility due to respiratory diseases, in particular asthma and COPD. Increased effects due to long-term exposure to air pollutants (chronic, often irreversible, and occurring after several years of latency) have been reported in a COPD cohort study,7 whereas the hypothesis that COPD can modify the short-term effects of air pollutants (acute, often reversible, associated with changes in daily exposure, and occurring within a few days) has been assessed in three studies.8–10 The initial hospital-based cohort study of COPD patients from Barcelona8 found extremely large increases of natural (11%) and respiratory (18%) mortality per 20 µg/m3 increase in PM10, but these results were not confirmed in two subsequent case-crossover studies.9,10

Given these uncertainties, we conducted a population-based cohort study of patients with COPD to evaluate whether they are more susceptible than other persons to short-term effects of air pollutants.

Back to Top | Article Outline


The Study Design

We estimated the association between the daily variations in air pollutants and daily mortality during 2005–2009 in a cohort of COPD residents of the city of Rome (Lazio region), which we identified through two sources: the regional dataset of hospital discharges (complete coverage of all public and private hospitals) and the regional dataset of pharmaceutical prescriptions (from all general practitioners and specialists). We compared the effect estimates for the cohort with those obtained during the same period for the general population of Rome without COPD. The source of mortality data was the regional register of causes of death. We examined whether age, sex, and comorbidities (based on hospitalization records in the 5-year period before death) were effect modifiers.

Back to Top | Article Outline

The COPD Cohort: Definition and Enrollment

We categorized a patient as having COPD when the principal diagnosis at hospital discharge was COPD (International Classification of Diseases, Ninth Revision [ICD-9] codes 490–492, 494, 496) or when the patient had a principal diagnosis of respiratory failure (ICD-9 codes 518.5, 518.8, 786.0), “cor pulmonale” (ICD-9 codes 416.9), or congestive heart failure (ICD-9 codes 428.0) with a secondary diagnosis of COPD. Any subject discharged from any hospital in the Lazio region during 1998–2004, still alive and residing in Rome on 1 January 2005, was enrolled on this date. Further, we enrolled all subjects discharged in the subsequent 2005–2009 period from any hospital in the region if they were a resident in Rome at the time of discharge and had not been hospitalized with COPD since 1998. In case of multiple hospitalizations, the date of first hospitalization in the period 1998–2009 was used to define the subjects as COPD cases. In addition, we considered as COPD cases all subjects in the region who had filled at least five packages of prescription for respiratory medications over a period of 4–12 months11 during 2005–2009 and had not been hospitalized with COPD since 1998. The algorithm, as well as the codes that we used from the Anatomical Therapeutic Chemical classification of medication, are reported in detail in the eAppendix (

All COPD subjects were followed from 1 January 2005 until 30 November 2009. The eligibility criteria were age 35+ years at first COPD diagnosis and being alive and a resident in Rome at identification. Residence in Rome, migration, and vital status were checked during the period 2005–2009 using the General Population Registry of Rome.

Only deaths that occurred in Rome were included as outcomes to minimize exposure misclassification. A record linkage with the regional mortality registry identified the cause of death, starting from 30 days after identification until 31 December 2009. All natural causes of death (ICD-9 codes 1–799), cardiac (ICD-9 codes 390–429), cerebrovascular (ICD-9 codes 430–438), and respiratory (ICD-9 codes 460–519) causes were analyzed.

Back to Top | Article Outline

The Non-COPD Comparison Population

We considered the entire general population resident in Rome during 2005–2009 who did not suffer from COPD as the comparison group. For this purpose, we selected all deaths with the above ICD codes that occurred between 31 January 2005 and 31 December 2009 in persons age 35+ years who resided and died in Rome, who had not received a hospital diagnosis of COPD or its complications from 1998 to 2009, and who had not been prescribed medications in the amount and period used to define COPD subjects.

We obtained information on chronic medical conditions for all deceased persons (for both the COPD cohort and the comparison population) using a record-linkage procedure with the regional hospital discharge registry during the 5-year period before death. Principal and secondary diagnoses were considered (ICD-9 codes are reported in eAppendix,

Back to Top | Article Outline

Environmental Data

Data on air pollution were provided by the Regional Environmental Protection Agency. Daily levels of PM10, PM2.5, nitrogen dioxide (NO2), and ozone (O3) from April through September, were available from three fixed monitoring stations (two for O3), which were representative of city background levels. All data were available for the period 2005–2009 except for the data on PM2.5, which were available since 2006. Missing values for a given pollutant on a specific day from a specific monitoring station were imputed using the average measurement of that pollutant for that day at the other monitors, weighted by the ratio of the yearly average at that monitor and the yearly average at the other monitoring stations for the same pollutant.12 A daily completeness measure of at least 75% per season was used as an inclusion condition for the monitored data. Daily averages and interquartile ranges (IQRs), defined as the difference between the first and third quartiles of the daily concentrations, were estimated for each pollutant except O3, which was expressed as a daily maximum 8-hour running mean. Information on daily temperature, humidity, and barometric pressure was provided by the Italian Air Force Meteorological Service. Apparent temperature was calculated from air temperature and dew-point temperature, which is a proxy of relative humidity.13

Back to Top | Article Outline

Statistical Analysis

A time-series analysis was performed to study the association between daily pollutants and daily mortality in both COPD and comparison subjects. Poisson regression analysis was applied, controlling the effect of time trend using triple interaction terms for year, month, and day of the week (similar to a “time-stratified” case-crossover analysis that selects control days as the same day of the week within the same month of the same year), apparent temperature above the median (lag 0–1 days, penalized spline), air temperature below the median (lag 1–6 days, penalized spline), influenza epidemics, and population decreases during summer or during holidays. Details are reported in our previous articles on short-term effects of air pollution.14–16 In detail, we adjusted for apparent temperature above the median (lag 0-1 days), to take into account the confounding effect of high temperatures on mortality, which is known to be immediate. In addition, we adjusted for air temperature below the median (lag 1-6 days) to control the confounding effect of low temperatures, which is more delayed than the effect of high temperatures. In both cases, penalized splines were used to guarantee a high degree of flexibility in the estimation of exposure–response relationships. In the mortality analysis of the COPD cohort, person-days at risk were considered as offset to properly account for the changes in the dynamic population during follow-up.

We explored the effect of six daily lag intervals of the pollutant effect on mortality. Cumulative unconstrained lags were analyzed with intervals selected a priori to differentiate “immediate” (lag 0-1 days), “delayed” (lag 2-5 days), and “prolonged” (lag 0-5 days) effects. The overall estimates of pollutant effects were also obtained from a time-stratified case-crossover analysis (see below) to verify possible differences with respect to the Poisson regression approach before evaluating individual effect modifiers.

We therefore carried out case-cross over analyses17 stratified by month within both the COPD and non-COPD groups to assess possible effect modification of age, sex, and other chronic diseases (5-year hospitalizations) on the association between air pollutants and mortality. We applied conditional logistic regression, selecting control days by means of the time-stratified approach18 (which is designed to control season, long-term trend, and day of the week), and considering the other covariates as in a Poisson regression approach. Each effect modifier was tested by adding the interaction terms between each potential effect modifier (one at a time) and the pollutant.

Results are expressed as percentage increases in mortality (and 95% confidence intervals [CIs]) relative to IQR increases in each pollutant. IQR was preferred to an a priori fixed increase of concentration (eg, 10 µg/m3) due to differences among pollutants in the variability of daily values. The extent of heterogeneity of effect estimates between the two groups (COPD and non-COPD) was assessed by testing the differences between the regression coefficients, and by the relative effect modification P value9; the corresponding variance was computed by adding variances from the two strata, assuming zero covariance. Finally, because the two stratum-specific log-odds ratios (ORs) are normally distributed, we assumed a normal distribution for their difference, and the P value of effect modification was derived from a normal distribution with a mean equal to the difference of the two log-OR, and a variance equal to the sum of the corresponding variances, as reported elsewhere.10

Differences between the COPD and the non-COPD groups, as well as among the various subgroups, were considered to be present when the P value of relative effect modification was <0.05; differences were considered to be suggestive when the effect estimate in one group was twice that of the referent group, and the P value ranged between 0.05 and 0.20.

Because the comparison could be biased by possible differences in sex and age distributions (with the COPD cohort expected to be older and with more men), the mortality effects were standardized by age and sex, using as weights the relative frequencies of age groups and sex in the total population via the direct standardization method. All analyses were conducted with SAS (version 9.1), R (version 2.10.0), and STATA (version 10.0).

Back to Top | Article Outline


There were 147,541 subjects who matched our COPD definition in the study period; 1,860 (1%) of them moved away from Rome or died before follow-up began. A large proportion of the cohort members (112,174 subjects [77%]) was enrolled using pharmaceutical data and did not have a previous hospitalization for COPD. Among those enrolled from hospital data, the principal diagnosis was COPD for 73%, respiratory failure for 18%, and cardiac complications for 10%.

There were 15,884 deaths due to the specified natural causes among the 145,681 COPD subjects (mortality rate = 3.96 per 100 person-years) and 84,974 in the general population of Rome age 35+ years without COPD (1,710,557 subjects) (mortality rate = 1.0 per 100 person-years) (Table 1). After adjusting for both sex and age, mortality remained 2.8 times higher in COPD than in non-COPD subjects. Subjects with COPD were older, and in each age group mortality was higher in COPD subjects than in those without COPD; the greatest differences were observed in the youngest and the oldest categories, with sex-adjusted relative risks of dying equal to 3.5 and 3.3, respectively. Women and men were not equally distributed in the two groups, but the age-adjusted risks of dying did not differ by sex (Table 1). Cardiac mortality accounted for 29% of the deaths in the COPD cohort and 30% in non-COPD subjects, respectively; cerebrovascular mortality accounted for 6% and 10%; and respiratory mortality accounted for 16% and 4%.



The annual average daily concentrations were 36.4 μg/m3 for PM10 and 20.2 μg/m3 for PM2.5 (Table 2), both below the limits recommended by European Union (EU) legislation (40 and 25 μg/m3, respectively).19 The annual average concentration of NO2 (60 μg/m3) was higher than the EU limit (40 μg/m3), and in almost 20% of days, monitored NO2 was double the recommended limit. The 8-hour running mean concentration of O3 was <100 μg/m3, but >25% of the study days exceeded this threshold. The variability of gaseous pollutants (as estimated by standard deviation and IQR) was higher than that of particles.



The Figure shows the effects of increasing pollutants on mortality at several cumulative lags, among people with and without COPD. Daily mortality was associated with PM10, PM2.5, and NO2, and these effects were stronger in COPD than in non-COPD subjects, especially at lags 2–5 and 0–5. An immediate effect (lag 0–1 days) of ozone on mortality was observed only in subjects without COPD.

Table 3 shows the cumulative effects (lag 0–5 days) for all natural causes of death and 3 subgroups. The effect of PM10 overall was five times higher in COPD (3.5% [95% CI = −0.1% to 7.2%]) than in non-COPD subjects (0.7% [−0.8% to 2.2%]) (test for relative effect modification, P = 0.16). PM2.5 and NO2 effects on overall mortality in the COPD group were almost twice that in subjects without COPD, although the CIs were large. Cardiac and cerebrovascular mortality showed similar PM and O3 effects on COPD and non-COPD subjects, with large CIs. Finally, strong effects on respiratory mortality were found for PM10 (10.0% [1.2% to 19.4%]), PM2.5 (11.6% [2.0% to 22.2%]), and NO2 (19.6% [3.5% to 38.2%]) in the COPD cohort. The estimates were three to seven times higher than in subjects without COPD, and there was a suggestion of effect modification for NO2 (test for relative effect modification, P = 0.13). In the entire study population, the PM10 effect was 1.1% (−0.3% to 2.5%); the PM2.5 effect was 1.5% (−0.1% to 3.1%); and the NO2 effect was 4.4% (2.0% to 6.9%). Results with the case-crossover approach were very similar to those obtained from the Poisson regression (eTable 1,



To evaluate effect modification within the COPD and non-COPD groups, we focused on PM10; the results of the analysis of effect modification for PM2.5 and NO2 are reported in eTables 2 and 3 ( Age modified the effect of PM10 on natural mortality (Table 4). Among subjects with COPD, the effect was stronger in those age 65–74 years (5.1%) and even stronger in those 85+ years of age (8.7%) compared with those aged 35–64 years (−5.2%); we found clear effect modification (test for interaction, P = 0.05) in the oldest group among those with COPD, and less so among non-COPD subjects (test for interaction, P = 0.19). The difference remained strong in the oldest age group (relative effect modification, P = 0.07) when comparing COPD with non-COPD. Also, sex modified the effect of PM10 on mortality, although only among non-COPD subjects, for whom women’s mortality increased more (1.5%) than the men’s mortality (−0.8%) (test for interaction, P = 0.10). Comparing the two groups, the effects of air pollution were higher in men with COPD (4.1%) than in those without (−0.8%), and the small P values of the difference (P value = 0.05) provide some assurance that the effect modification was not simply due to chance.



Several chronic diseases modified the PM10–mortality relationship (Table 4). When compared with a total mortality increase of 3.5% after PM10 exposure, COPD subjects who also had heart conduction disorders (16.9%) (test for interaction, P = 0.01), or cerebrovascular disease (9%) (test for interaction, P = 0.05) had larger effect estimates than other COPD subjects. The stronger effects in these subgroups were confirmed when non-COPD subjects were also considered (relative effect modification, P = 0.08 and 0.07, respectively) (Table 4). Some other conditions suggested an association, with a larger effect of PM10 among non-COPD subjects (test for interaction, P = 0.2), namely diseases of pulmonary circulation, heart conduction disorders, arrhythmias, cerebrovascular diseases, and lower respiratory tract infections.

Finally, the PM10 effects among the COPD subjects were higher during the warm period of the year (7.0% for all natural mortality and 15.0% for respiratory mortality) than during the cold period (2.9% and 9.0%, respectively). In contrast, the PM10-related risks of dying among those without COPD were higher in the cold than in the warm season (1.3% vs. −4.3% for natural mortality and 6.4% vs. 0.5% for respiratory mortality).

We performed an additional analysis evaluating air pollution effects in COPD subjects according to the enrollment source. We found stronger effects for mortality among those identified through hospital discharges than among those recruited from pharmaceutical data for PM10 (5.6% [95% CI = 0.9% to 10.5%]), PM2.5 (6.2% [0.9% to 11.9%]), and NO2 (13.4% [4.7% to 22.9%]) (eTable 4, However, for cardiac and respiratory mortalities, there was a large overlap of the CIs and a higher respiratory mortality related to PM10 for subjects who had been enrolled from the pharmaceutical data. Similar effect estimates were found among those identified as COPD cases from hospital discharges during 1998–2004 and during 2005–2009 (eTable 4,

We carried out a sensitivity analysis after excluding subjects admitted during heat-wave period in 2003. More specifically, we excluded persons enrolled from May to August 2003 (n = 818) among whom 234 deaths were observed up to 2009. The results do not show important differences from the main analysis (eTable 5,

Back to Top | Article Outline


We found that short-term exposures to PM10, PM2.5, and NO2 were associated with effects on mortality due to natural and especially respiratory causes in subjects with COPD and in those without, with larger effects in the COPD cohort. Among COPD patients, older age, male sex, preexisting heart conduction disorders, and cerebrovascular diseases were associated with a stronger susceptibility.

The short-term effects of PM10 on daily mortality have been frequently estimated in the general population (ranging from 0.3% to 1.5% per 10 μg/m3).2 The effect of PM10 on respiratory mortality is generally stronger than that on other types of mortality.14,20,21 Our results for the city of Rome support this. However, the hypothesis of a higher susceptibility of respiratory patients to short-term exposure to air pollutants has been explored only in a few studies,8–10 with contradictory results.

Our results for COPD subjects (3.5% increase in natural mortality overall and 10% increase in respiratory mortality for 16.3 µg/m3 PM10) clearly indicate higher risk, especially considering the already high background mortality in this population (COPD patients’ relative risk of death was almost three times higher than non-COPD subjects). Furthermore, respiratory mortality among COPD subjects was elevated for both PM2.5 and NO2, which are the pollutants more related to vehicular traffic. For these pollutants, the results in the literature are available only for the general population, and they indicate lower effect estimates than observed here. One study in the United States reported a 1.0% increase in natural mortality and a 2.0% increase in respiratory mortality22 for 10 µg/m3 PM2.5. The effect of NO2 (10 µg/m3) has been reported23 in Europe as 0.3% and 0.4% for natural and respiratory mortality, respectively. A recent study in Italy reported higher estimates for NO2 (2.1% and 3.5%, respectively) for the same causes of death.15

There are strengths of this study that should be underlined as they are innovative and might have improved the validity of the results. First, in the definition of COPD we included subjects identified not only from hospital diagnoses but also from pharmaceutical data, which account for almost 77% of the identified COPD cohort. This strategy, still under development in environmental epidemiology, increased the size and power of the study and reduced the misclassification of COPD cases as noncases, which is likely to occur when true COPD cases, treated in outpatient settings and without a need for hospitalization, are classified as noncases. Second, the introduction of a comparison group is a new aspect, with previous cohort studies carried out only among COPD patients.7,8 This approach improves the assessment of susceptibility because it allows comparison of effect estimates in subjects with and without COPD from the same pollutant concentrations on the same days. The two groups are also likely to be similar in other environmental and behavioral factors related to mortality but not analyzed here. Third, thanks to the availability of large and complete datasets of previous hospitalizations, we were able to explore a period up to 5 years to detect the specific diseases that confer susceptibility to COPD subjects.

Our conclusion that COPD subjects are susceptible to air pollutants is based on the mortality increase associated with air pollution that is five times higher in the diseased group. When we restricted analysis to patients with a diagnosis of COPD from hospital records, the effect estimates for air pollution were somewhat larger than that in the overall cohort. In addition, it should be noted that the comparison was affected by residual misclassification: deaths in non-COPD subjects included persons (25% of the total) with some evidence of COPD but who did not meet our definition of COPD (a secondary COPD diagnosis from a hospital discharge or prescription of respiratory medicines with insufficient frequency). The impact of this misclassification was to reduce the differences between COPD and non-COPD subjects (data not shown).

The effect of PM10 on natural mortality differed greatly between COPD and non-COPD subjects, suggesting a hypothesis of susceptibility due to COPD; however, the fact that the highest estimates occurred in the oldest people in both groups, suggests that some of the susceptibility may be explained by age. Older people are susceptible to airborne particulate, independent of whether they suffer from COPD,20,24 and a stronger oxidative stress has been hypothesized to explain this susceptibility because higher inflammatory markers are found in very old people.25 On the other hand, the four-fold difference between the oldest COPD and the oldest non-COPD subjects (and the small P values for this difference) supports the hypothesis that COPD is associated with higher susceptibility, even among the oldest subjects.

A possible obstacle to concluding that male COPD subjects are particularly susceptible to air pollution is related to the age and sex distribution in the two groups of subjects with and without COPD (and the different age–sex specific mortality rates).26 However, when we standardized for age in the comparison between sexes, the PM10 effect estimates changed only modestly: they were 4.4% and 2.7% for men and women, respectively, in COPD subjects and −0.6% and 1.3% in non-COPD subjects.

Diseases that modified the effect of air pollution in the COPD group were heart conduction disorders and cerebrovascular diseases. The pathogenetic mechanisms for these conditions are very similar to those attributed to air pollutants in causing cardiovascular damage, such as coagulation problems,27 fibrinolytic function impairment,28 and heart rate variability.29,30 A hypothesis to explain COPD susceptibility could be that stronger effects were obtained because air pollutants stimulate specific mechanisms of COPD progression, such as systemic inflammation and systemic oxidative stress, as well as cardiac autonomic dysfunction and ischemic and thrombotic mechanisms.31

Additional aspects and limitations are important to mention. First, despite the population of Rome being large and our being able to enroll all COPD subjects, this is still a one-city study, and the statistical power to detect air pollution effects is limited, especially for testing effect modification. Most of our effect estimates have large CIs, especially for interactions. Second, unlike for natural and respiratory mortalities, we found strong effects for cardiac mortality, both among COPD and non-COPD patients, without differences between them. It is clear that the role that comorbidities and relative treatments could play in the two groups should be further studied. In addition, the evaluation of air pollution effects by COPD severity is an open and interesting issue that needs additional work. Third, given that COPD and asthma have in common several drug treatments, our COPD case definition using pharmaceutical prescriptions could have introduced some misclassification with asthma, probably larger than that introduced using hospital diagnosis. Fourth, because a long recruitment period had elapsed between the recruitment of COPD cases during 1998–2004 and the actual study period (2005–2009), survival bias is possible. However, the short-term effects were not different between the COPD cases identified earlier and those identified later. Finally, we were not able to estimate the role of smoking and other behavioral factors in our data.

In conclusion, COPD patients have high mortality rates, and air pollution precipitated death in these subjects more strongly than in the general population. The air pollution effects were particularly high in very old subjects, in men, and in patients with previous heart conduction disorders and cerebrovascular diseases. A revision of EU legislation on air pollution is due by 2013. Some consideration may need to be given to susceptible populations when setting permissible levels of air pollution.



Back to Top | Article Outline


1. American Thoracic Society. . What constitutes an adverse health effect of air pollution? Am J Respir Crit Care Med. 2000;161:665–673
2. Pope CA 3rd, Dockery DW. Health effects of fine particulate air pollution: lines that connect. J Air Waste Manag Assoc. 2006;56:709–742
3. Jerrett M, Shankardass K, Berhane K, et al. Traffic-related air pollution and asthma onset in children: a prospective cohort study with individual exposure measurement. Environ Health Perspect. 2008;116:1433–1438
4. Gehring U, Wijga AH, Brauer M, et al. Traffic-related air pollution and the development of asthma and allergies during the first 8 years of life. Am J Respir Crit Care Med. 2010;181:596–603
5. Andersen ZJ, Hvidberg M, Jensen SS, et al. Chronic obstructive pulmonary disease and long-term exposure to traffic-related air pollution: a cohort study. Am J Respir Crit Care Med. 2011;183:455–461
6. WHO for Europe. Health Aspect of Air Pollution – Answer to Follow-up Questions From CAFé. Report on a WHO Working Group Meeting.. 2004 Bonn, Germany, 15–16 January
7. Zanobetti A, Bind MA, Schwartz J. Particulate air pollution and survival in a COPD cohort. Environ Health. 2008;7:48
8. Sunyer J, Schwartz J, Tobías A, Macfarlane D, Garcia J, Antó JM. Patients with chronic obstructive pulmonary disease are at increased risk of death associated with urban particle air pollution: a case-crossover analysis. Am J Epidemiol. 2000;151:50–56
9. Bateson TF, Schwartz J. Who is sensitive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers. Epidemiology. 2004;15:143–149
10. Forastiere F, Stafoggia M, Berti G, et al.SISTI Group. Particulate matter and daily mortality: a case-crossover analysis of individual effect modifiers. Epidemiology. 2008;19:571–580
11. Anecchino C, Rossi E, Fanizza C, De Rosa M, Tognoni G, Romero MWorking Group ARNO Project. . Prevalence of chronic obstructive pulmonary disease and pattern of comorbidities in a general population. Int J Chron Obstruct Pulmon Dis. 2007;2:567–574
12. Biggeri A, Bellini P, Terracini B. [Meta-analysis of the Italian studies on short-term effects of air pollution–MISA 1996-2002]. Epidemiol Prev. 2004;28(4-5 Suppl):4–100
13. Steadman RG. The assessment of sultriness. Part I: a temperature-humidity index based on human physiology and clothing science. J Applied Meteorol. 1979;18:861–873
14. Faustini A, Stafoggia M, Berti G, et al.EpiAir Collaborative Group. The relationship between ambient particulate matter and respiratory mortality: a multi-city study in Italy. Eur Respir J. 2011;38:538–547
15. Chiusolo M, Cadum E, Stafoggia M, et al. Short term effects of nitrogen dioxide on mortality and susceptibility factors in ten Italian cities: the EpiAir Study. Environ Health Perspect. 2011;119:1233–1238
16. Stafoggia M, Forastiere F, Faustini A, et al.EpiAir Group. Susceptibility factors to ozone-related mortality: a population-based case-crossover analysis. Am J Respir Crit Care Med. 2010;182:376–384
17. Maclure M. The case-crossover design: a method for studying transient effects on the risk of acute events. Am J Epidemiol. 1991;133:144–153
18. Levy D, Lumley T, Sheppard L, Kaufman J, Checkoway H. Referent selection in case-crossover analyses of acute health effects of air pollution. Epidemiology. 2001;12:186–192
19. EU. . Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe. Available at: Accessed May 12, 2011.
20. Fischer P, Hoek G, Brunekreef B, Verhoeff A, van Wijnen J. Air pollution and mortality in The Netherlands: are the elderly more at risk? Eur Respir J Suppl. 2003;40:34s–38s
21. Wong CM, Vichit-Vadakan N, Kan H, Qian Z. Public Health and Air Pollution in Asia (PAPA): a multicity study of short-term effects of air pollution on mortality. Environ Health Perspect. 2008;116:1195–1202
22. Zanobetti A, Schwartz J. The effect of fine and coarse particulate air pollution on mortality: a national analysis. Environ Health Perspect. 2009;117:898–903
23. Samoli E, Aga E, Touloumi G, et al. Short-term effects of nitrogen dioxide on mortality: an analysis within the APHEA project. Eur Respir J. 2006;27:1129–1138
24. Aga E, Samoli E, Touloumi G, et al. Short-term effects of ambient particles on mortality in the elderly: results from 28 cities in the APHEA2 project. Eur Respir J Suppl. 2003;40:28s–33s
25. Zeka A, Sullivan JR, Vokonas PS, Sparrow D, Schwartz J. Inflammatory markers and particulate air pollution: characterizing the pathway to disease. Int J Epidemiol. 2006;35:1347–1354
26. Mamdani M, Sykora K, Li P, et al. Reader’s guide to critical appraisal of cohort studies: 2. Assessing potential for confounding. BMJ. 2005;330:960–962
27. Rückerl R, Ibald-Mulli A, Koenig W, et al. Air pollution and markers of inflammation and coagulation in patients with coronary heart disease. Am J Respir Crit Care Med. 2006;173:432–441
28. Mills NL, Törnqvist H, Gonzalez MC, et al. Ischemic and thrombotic effects of dilute diesel-exhaust inhalation in men with coronary heart disease. N Engl J Med. 2007;357:1075–1082
29. Gold DR, Litonjua A, Schwartz J, et al. Ambient pollution and heart rate variability. Circulation. 2000;101:1267–1273
30. Dennekamp M, Akram M, Abramson MJ, et al. Outdoor air pollution as a trigger for out-of-hospital cardiac arrests. Epidemiology. 2010;21:494–500
31. Brook RD, Rajagopalan S, Pope CA 3rd, et al.American Heart Association Council on Epidemiology and Prevention, Council on the Kidney in Cardiovascular Disease, and Council on Nutrition, Physical Activity and Metabolism. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation. 2010;121:2331–2378
Back to Top | Article Outline


We thank Margaret Becker for revising the English, Francesco Troiano for providing data on air pollutants, and Silvia Cascini for placing the program to identify the pharmaceutical COPD cases at our disposal.

Supplemental Digital Content

Back to Top | Article Outline
© 2012 Lippincott Williams & Wilkins, Inc.