Particulate air pollution, generally measured as particle matter with aerodynamic diameter <10 μm (PM10), is associated with increased risk of hospital admissions and deaths from cardiovascular causes.1–4 Studies have been carried out in North America,5 Western Europe,6–8 and Asia.9,10 Although the association of airborne particles with cardiovascular events is clear, the mechanisms behind these associations are still under study.11 Studying associations with specific cardiovascular endpoints is proving to be important to understanding the physiopathological mechanisms activated by the ambient air pollution. Recently, attention has been focused on whether PM air pollution is a trigger of myocardial infarction (MI)12–15; other specific clinical manifestations such as heart failure, arrhythmias, and sudden cardiac arrest have also been studied.16–18
Limited, but growing, evidence from recent epidemiologic studies suggests that persons with comorbid conditions (including diabetes, hypertension, congestive heart failure, recent myocardial infarction, and respiratory conditions) may be at increased risk of cardiovascular morbidity and mortality associated with ambient air pollution levels.19–22 However, there is considerable uncertainty in the risk estimates for susceptible populations. The most recent reports from the U.S. National Research Council23 have emphasized the need for consideration of susceptible subgroups, including persons with underlying cardiovascular and respiratory diseases.
The objectives of this study were to estimate the short-term association between PM10 and daily hospital admissions in 9 Italian cities, and to identify subjects who, due to demographic characteristics or preexisting medical conditions, are particularly susceptible to air particles.
We considered all emergency hospitalizations of residents of 9 Italian cities (Bologna, Florence, Mestre, Milan, Palermo, Pisa, Rome, Taranto, and Turin), aged ≥65 years, discharged with a diagnosis of cardiac disease between 1 January 2001 and 31 December 2005. For each city, data were collected on primary diagnosis from the regional hospital discharge registry. Events were further restricted to admissions within the city boundaries to increase the likelihood that exposure corresponded with the measured air pollution. We selected primary diagnoses of cardiac diseases (ICD-9 code 390–429); acute coronary syndrome, including acute myocardial infarction (ICD-9 code 410) and unstable angina (ICD-9 code 411); arrhythmias and conduction disorders (ICD-9 codes 426, 427); and heart failure (ICD-9 code 428). Cases of acute coronary syndrome were also identified by complications reported in the primary diagnosis (427.1, 427.41, 427.42, 427.5, 428.1, 429.5, 429.6, 429.71, 429.79, 429.81, 518.4, 780.2, 785.51, 414.10, 423.0), together with acute MI as secondary diagnosis.
Age, sex, and previous selected diseases were the effect modifiers of primary interest. For each subject, we collected information on previous diseases from hospital admissions in the preceding 2-year period, using a record linkage procedure with the Hospital Discharge Registry. Health conditions were categorized into “chronic” or “acute” conditions. Chronic conditions were based on all primary and secondary discharge diagnoses from hospitalizations between 29 days and 2 years before the index admission; acute conditions were based on all primary and secondary discharge diagnoses from hospitalizations in the 4 weeks before index admission. We identified diseases as potential effect modifiers based on the following criteria: (1) diseases related to oxidative stress and systemic inflammation, autonomous nervous system disorders, coagulation disorders and atherosclerosis, and diabetes; (2) pulmonary diseases that may have heart complications in their natural course; (3) chronic diseases that may generally impair vital functions, such as cancer, chronic hepatic conditions, and renal failure. The diseases hypothesized as susceptible conditions and their ICD-9 codes are reported in the online material (eAppendix 1, http://links.lww.com/EDE/A570).
Air pollution data were provided by regional environmental agencies. We collected data on PM10 (daily average, μg/m3). Hourly data were available from several monitoring stations for each city; an algorithm was implemented to impute missing values and derive daily summaries in each center, as reported elsewhere.24,25 Meteorologic variables (air temperature, dew-point temperature, and barometric pressure) were available from the Air Force monitoring network. One weather monitoring station was used for each city, usually from the nearby airport.
The methods used to analyze data are described in detail in another paper dealing with the short-term effects of ozone in the same cities.26 Briefly, we used a time-stratified case-crossover design to study the association between PM10 and hospitalization for cardiac diseases, and effect modification by individual characteristics.27,28 We used conditional logistic regression analysis to control for possible confounding factors, including the population decrease during the summer vacations in Italy, holidays, influenza epidemics, barometric pressure, and high and low temperature. We defined the population decrease during summer as a 3-level variable assuming value “2” in the 2-week period around 15 August, value “1” from 16 July to 31 August (with the exception of the 2-week period specified before), and value “0” on the remaining days of the year.
We fitted both constrained (cubic polynomial) distributed lag-models and single-lag models29 for each city to assess the lag structure of the associations between PM10 and hospitalization for cardiac diseases within a 6-day period. This analysis was used to suggest the lag with the strongest effect, which was then evaluated in the effect modification analysis described later in the text.
To investigate the potential modification of the effect of PM10 on the risk of hospitalization, we included in each city-specific regression model an interaction term that was the product of PM10 values and the specific effect modifier under study. We used lags 0 and 0–1 to consider an immediate air pollution effect on cardiac conditions, as suggested from the available literature and as confirmed in our analysis.
A pooled estimate was obtained from city-specific results by applying a random-effects meta-analysis with maximum likelihood. For each pooled estimate, we estimated the P values of tests for heterogeneity across cities.
We report all effect modification with P <0.15, because of the general low power for tests of interaction. P values for interaction provide evidence on the extent to which the apparent effect modification is due to chance.
All results were expressed as the percent increase in risk and 95% confidence interval (95% CI) associated with a 10-μg/m3 increase in PM10. All analyses were done using SAS software (Statistical Analysis System, version 8.2, SAS Institute, Inc) and R software (version 2.8.1, R Foundation for Statistical Computing).
Table 1 summarizes the number of hospital admissions and PM10 levels at each participating city (ordered from north to south of Italy), from 1 January 2001 to 31 December 2005. A total of 167,895 emergency hospitalizations of persons ≥65 years of age with a principal diagnosis of cardiac diseases were considered. Hospital admissions due to acute coronary syndrome, arrhythmias, and conduction disorders, and heart failure accounted for 24%, 21%, and 27% of total hospital cardiac admission, respectively. The daily mean values of PM10 were higher in the northern cities, such as Turin and Milan, than in southern cities, except Taranto.
The Figure shows the association between PM10 and hospital admissions, by diagnosis and by lag. The analysis of the lag structure suggested an immediate effect of PM10 on all cardiac diseases, arrhythmias and conduction disorders, on heart failure at lag 0, and on acute coronary syndrome at lag 0–1. These lags were chosen for subsequent analyses and presentation of the results. For total cardiac admissions, the increased risk for 10-μg/m3 increase in PM10 was 1.0% (95% CI = 0.7% to 1.4%). The association was slightly higher for acute coronary syndrome (lag 0–1, 1.1% [0.4% to 1.9%]) and for heart failure (lag 0, 1.4% [0.7% to 2.0%]) than for arrhythmias and conduction disorders (lag 0, 1.0% [0.2% to 1.8%]). The association was weaker on subsequent days for all cardiac diseases and specific cardiac diseases.
There were fewer than 1000 cases of at least one of the specific cardiac hospitalizations in 3 cities (Mestre, Pisa, and Taranto), thus precluding a finer stratification. We excluded these cities from the susceptibility analysis. Age and sex distribution of the outcomes under study, together with pooled effect estimates for the 6 larger cities, are reported in Table 2. The age distributions varied across conditions, with a lower proportion of very elderly persons (≥85 years) among cases with acute coronary syndrome (6%) than among heart failure patients (29%). No important differences in effect estimates by age were seen for all cardiac conditions, arrhythmias and conduction disorders, and heart failure. For acute coronary syndrome, we found an important difference of the effect by age, with patients aged 75–84 years more susceptible than other age groups (lag 0–1, 2.6% [1.5% to 3.8%]; test for interaction, P = 0.001). The sex distribution of the cases differed for specific conditions, with more men having acute coronary syndrome and more women having heart failure. The PM10-effect on hospital admissions for cardiac diseases was slightly higher in women (1.3% [0.8% to 1.8%]) than in men (0.8% [0.3% to 1.2%]; test for interaction, P = 0.091), whereas a clear effect modification by sex was observed for the PM10—heart failure relationship, which was higher for women (2.0%, [1.2% to 2.8%]; test for interaction, P = 0.022). In contrast, the effect estimate for arrhythmias and conduction disorders was higher in men than in women (1.9% [0.8% to 3.0%]; test for interaction, P = 0.020).
Table 3 reports results of possible effect modification by a priori-identified chronic conditions for all cardiac diseases and acute coronary syndrome, and Table 4 for arrhythmias and conduction disorders and heart failure. None of them was a striking marker of susceptibility, although there were some suggestions that are worth noting. Previous arrhythmias and conduction disorders increased the risk of PM-related cardiac admissions (1.6% [0.8% to 2.3%]; test for interaction, P = 0.12); subjects with chronic pulmonary diseases had a higher risk for coronary admissions than other subjects (3.2% [0.6% to 6.0%]; test for interaction, P = 0.12); those who had impaired pulmonary circulation (7.1% [−1.0% to 15.8%]; test for interaction, P = 0.13) and previous arrhythmias and conduction disorders (2.0% [0.4% to 3.5%]; test for interaction, P = 0.12) had a higher risk for arrhythmias and conduction disorders admissions. A stronger PM10 effect on heart failure admissions was suggested for hypertension (2.1% [1.0% to 3.2%]; test for interaction, P = 0.13) and previous arrhythmias (2.3% [1.0% to 3.5%]; test for interaction, P = 0.12). Finally, some indications of negative effect modifications were found, especially related to acute coronary syndrome.
There was no evidence of effect modification for subjects who had recent hospitalizations, although a sign of higher effects on acute coronary syndrome was found in subjects with recent low respiratory tract infections (9.7% [−3.1% to 24.1%]) and in those with recent heart failure (4.4% [−1.2% to 10.4%]) (data not shown).
Because the strongest effect of PM10 on acute coronary syndrome was found among 75–84-year-old subjects (2.2% [1.0% to 3.4%]), we repeated the analysis of the susceptibility factors for this age-group (data not shown). Again, none among the a priori chronic and acute conditions was an important marker of individual susceptibility, although there were indications of higher effects in subjects with hypertension (3.0% [0.6% to 5.4%]), chronic pulmonary diseases (2.5% [−1.6% to 6.9%]), cirrhosis and other chronic liver diseases (6.0% [−6.3% to 19.8%]), previous arrhythmias and conduction disorders (3.9% [−4.5% to 13.0%]), previous heart failure (4.2% [−3.7% to 12.7%]), and acute low respiratory infections (11.1%, [−8.3% to 34.5%]).
We found that PM10 concentrations in 9 Italian cities are associated with an immediate increased risk of hospital admissions for cardiac diseases in persons ≥65 years of age, in particular for acute coronary syndrome, arrhythmias, and heart failure. Harmful effects of PM varied by age and sex for the specific conditions investigated. We did not find a clear marker of susceptibility in previous chronic diseases. Subjects who had been previously diagnosed with a cardiac disease were somewhat more likely to be rehospitalized with the same disease or another cardiac complication than healthy people or persons with other chronic diseases. There was also a tendency toward stronger associations of PM10 with acute coronary syndrome among chronic respiratory patients.
The PM10 effect (1.0%) on admission for all cardiac diseases is comparable with that reported in previous multicity studies in persons ≥65 years of age.11 A short latency between pollutant exposure and cardiac hospitalizations observed for all, as well as specific, heart diseases (lag 0 or 0–1) has also been reported previously. Zanobetti et al22 observed a high increase of cardiovascular admissions associated with PM at lag 0, dropping to a modest effect at lag 1 and 2. More recently, Dennekamp et al18 reported an increase in cardiac arrests on the same day of PM exposure; the effect decreased at lag 1 and disappeared in the subsequent 2 days. This trend is also coherent with other previous studies,14–,30–36 which found effects of air particles on heart diseases within 3 days from the peak concentration. These immediate effects on the heart are consistent with those reported in most studies. However, some studies have reported a persistent increase of inflammatory markers (such as fibrinogen, C-reactive protein, and sediment rate) for up to 4 weeks after exposure to high concentrations of particles of various sizes.37 This is not entirely consistent with a rapidly extinguishing effect on the heart. Further study is needed to better comprehend the damage mechanisms of airborne particles on specific heart diseases.
Susceptibility for Heart Failure
Women were at higher risk of PM-related hospitalization for heart failure. Other studies have also suggested that women may be at greater risk for cardiovascular mortality related to PM.17 However, women's susceptibility for heart failure, independently from other factors, was not observed in one previous paper that examined the effect modification by sex.33
There were some indications in our study that subjects with previously diagnosed cardiovascular diseases, such as hypertension and arrhythmias, were more likely to be hospitalized for heart failure after a PM10 increase. The same has been reported in most previous studies,16,33,38 using various PM sizes and effect measures. Susceptibility for heart failure has been previously reported in hypertensive subjects compared with those who do not suffer from hypertension.35 We did not observe a greater risk of heart failure among persons with recent acute MIs following exposure, although Wellenius16 found a congestive heart failure increase up to 10% in those with acute MI versus 3% in those without.
Susceptibility for Acute Coronary Syndrome
Two acute clinical expressions of ischemic heart disease (myocardial infarction and unstable angina) followed heart failure in their strength of association with air pollution (1.1%). Our estimates confirm results in previous studies, although the effect size varies greatly among studies, perhaps as a result of the different ischemic diseases included in the analyses and the different particle sizes analyzed. We included acute MI and unstable angina pectoris, whereas most previous studies considered all ischemic heart diseases or only acute MI. Only one study, to our knowledge, analyzed acute MI and unstable angina pectoris15 as we did; it reported an increase in risk as high as 4.5%, associated with a 10-μg/m3 increase in PM. Dominici et al38 found a 1.2% increase in ischemic heart disease admissions related to PM2.5, and Zanobetti39 found a 0.7% increase in acute MI admissions for exposure to PM10; however, Mann et al,30 Sullivan et al,31 and Bhaskaran et al32 did not find a relation between PM10 and ischemic heart disease admissions. In the United States, Barnett et al33 estimated a 2.7% increase related to PM2.5 in acute MI admissions in contrast to a 1.6% increase in ischemic heart disease in the same population. Finally, Lanki34 found a 0.3% increase in acute MI admissions in Europe associated with PM10. Most of these studies, apart from those by Dominici38 and Mann,30 analyzed emergency hospitalizations, and most of them studied only subjects ≥65 years of age.
The susceptibility for acute coronary syndrome that we found in subjects 75–84 years of age confirms previous suggestions of effect modification by age, as reported in a European study34 evaluating particle number concentration (a proxy indicator of ultrafine particles) and hospitalization with a first acute MI in subjects ≥75 years of age. Our results are also consistent with a report of higher levels of inflammatory markers (fibrinogen, C-reactive protein, and sediment rate) after exposure to ultrafine particles in persons ≥78 years of age than in younger subjects.37 Our results suggest inflammatory reaction triggered by PM as a possible mechanism of coronary damage and, in turn, acute MI, independent of underlying chronic disease.
The apparent susceptibility to acute coronary syndrome we found in subjects with chronic pulmonary disease is in agreement with a previous study14 that showed a higher probability of acute MI in patients with chronic obstructive pulmonary disease (COPD) (1.3% increase), compared with 0.6% in subjects without COPD. A possible interpretation is that particle exposure accelerates the development of the cardiac complication in COPD patients, possibly by means of an inflammatory reaction or an impairment of coagulation. A study40 showed an increased risk of mortality after air pollution exposure as high as 1.4% (95%CI = 1.0%–2.0%) among COPD patients with electrocardiographic signs of acute MI or ischemia.
Susceptibility for Arrhythmias and Conduction Disorders
Although numerous studies have explored the relationship between daily PM exposure and heart rate variability, the strength, the direction, and the putative mechanism (oxidative stress/inflammation or autonomic imbalance)11 of this relationship are not yet clearly defined.41 We found a clear effect of PM10 on hospitalization for arrhythmias and conduction disorders, and an indication that PM10 can exacerbate heart-rate disorders among those who already suffered from the problem. Recent studies have shown that exposure to air particles is associated with reduced heart rate variability.42,43 Reduced heart rate variability is in turn a risk factor for arrhythmia. In contrast, those diagnosed with changes in pulmonary circulation showed a higher risk of hospitalization for arrhythmias and conduction disorders (7.1%). These results might suggest that both inflammation and autonomic imbalance could have a role, depending on the underlying disease in exposed subjects.
One final aspect of our results should be underlined. We observed some negative effect modifications for specific heart diseases, although these did not reach statistical significance. We did not have a priori hypotheses about a possible protective effect, as it was deemed unlikely. Nevertheless, the apparently protective results for acute coronary syndrome observed in people with pulmonary circulatory diseases, arrhythmias, cancer, or diabetes could suggest that some factors may prevent the air pollution effect in these patients. Factors related to the disease itself could play a protective role in these chronic patients, either preventing exposure to the air pollution or interfering with the damage mechanisms (eg, medical treatment).
Some limitations need to be addressed. First, this study is characterized by a certain degree of exposure misclassification. Person-specific information on PM10 exposure is lacking, and ambient concentrations were used instead. Personal exposure depends on time spent indoors, time that windows are kept open, daily activity patterns, location of residence, and so forth. Therefore, outdoor concentrations misrepresent personal exposure, especially in population subgroups such as those who are already sick. Second, statistical power was limited for the analysis of specific subgroups, and imprecise estimates could have obscured important relationships. This was especially true for testing effect modification by chronic and acute conditions. In addition, chronic and acute conditions were based on hospital discharge records and suffer from limits of accuracy of the source and from the short duration (2 years) during which we collected information on chronic diseases.
In conclusion, we found important effects of PM10 on hospital admissions in people ≥65 years of age for all cardiac diseases, acute coronary syndrome, arrhythmias and conduction disorders, and heart failure. The harmful effects of PM10 on the heart differed by age and sex: people 75–84 years of age were more likely to have an ischemic heart episode when exposed to PM10; the PM10-related effect on heart failure was more frequent in women, whereas the effect on arrhythmias and conduction disorders were more frequent in men. This mixed pattern of cardiac effects by age and sex could represent specific consequences (as yet unknown) of air pollution on the different pathogenetic mechanisms of heart diseases. Our analyses do not indicate clear effect modification for specific previous conditions, and only some suggestions have emerged. The overall indication is that the air pollution effects on cardiac conditions are not limited to already diseased subjects.
We thank Margaret Becker for revising the English. EPIAIR collaborative group. Milan: Bisanti L, Randi G, Rognoni M; Mestre-Venice: Simonato L, Tessari R; Turin: Berti G, Cadum E, Chiusolo M, Galassi C, Grosa M, Ivaldi C, Pelosini R, Poncino S; Bologna: Caranci N, Miglio R, Pace G, Pacelli B, Pandolfi P, Scarnato C, Zanini G; Florence: Accetta G, Baccini M, Barchielli A, Biggeri A, Chellini E, Grechi D, Mallone S, Nuvolone D; Pisa: Baldacci S, Serinelli M, Viegi G, Vigotti MA; Rome: Colais P, Faustini A, Forastiere F, Perucci CA, Stafoggia M; Taranto: Primerano R, Serinelli M, Vigotti MA; Cagliari: Dessì P; Palermo: Cernigliaro A, Scondotto S.
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