Cardiovascular Disease: Original Article
Traffic-Generated Air Pollution and Myocardial Infarction
Rosenlund, Matsa,b; Bellander, Toma,b; Nordquist, Tobiasc; Alfredsson, Larsb,c
From the aDepartment of Occupational and Environmental Health, Stockholm County Council, Stockholm, Sweden; bInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; and cStockholm Center for Public Health, Stockholm County Council, Stockholm, Sweden.
Submitted 25 October 2007; accepted 17 July 2008; posted 18 December 2008.
Supported by the grants from the Swedish Environmental Protection Administration and the Swedish National Research Program on Health Effects from Air Pollution (SNAP).
Correspondence: Mats Rosenlund, Occupational and Environmental Health, Norrbacka 3rd floor, Karolinska Hospital, SE-171 76 Stockholm, Sweden. E-mail: email@example.com.
Background: Although long-term air pollution exposure has been linked to cardiovascular mortality, data on incidence and nonfatal coronary disease are limited and inconclusive. The aim of this study was to investigate the association between long-term residential exposure to air pollution from traffic and the risk of nonfatal and fatal myocardial infarction.
Methods: The records of all individuals aged 15 to 79 with a first event of myocardial infarction in Stockholm County during 1985 to 1996 were retrieved from a registry. Population controls were randomly selected from the study base stratified by age, sex, and calendar year. Individual socioeconomic data and home addresses were obtained from population censuses 1970 to 1995. Annual air pollution exposure was assessed by dispersion modeling at the home addresses of 24,347 cases and 276,926 controls.
Results: Five-year average traffic-generated air pollution exposure corresponding to a difference in nitrogen dioxide from the fifth to the 95th percentile (31 μg/m3) was associated with an odds ratio for fatal myocardial infarction adjusted for age, sex, calendar year, and socioeconomic status of 1.23 (95% confidence interval [CI] = 1.15–1.32). The corresponding odds ratio was 2.54 (1.96–3.29) among those with least expected misclassification of true individual exposure (those who did not move between censuses). Different time-windows and analyses of other pollutants including carbon monoxide and particles less than 10 μm in diameter (PM10) produced weaker associations. There was no increased risk for nonfatal myocardial infarction (ORs 0.94–0.98).
Conclusions: Long-term exposure to traffic-generated air pollution is associated with fatal myocardial infarction but not with nonfatal infarction.
The effects of short-term exposure to ambient air pollution are well documented in numerous epidemiologic studies, demonstrating associations between daily air pollution levels and hospital admissions or mortality in respiratory and cardiovascular disease.1–7 Cohort and case-control studies have also reported an association between long-term exposure to air pollution and fatal coronary heart disease.8–16 We have previously reported an increased risk for fatal myocardial infarction in a population-based case-control study.16 A recent study limited to women also reported strong associations between the annual average exposure to fine particulate air pollution and incidence of cardiovascular events.17
Several plausible mechanistic pathways have been proposed for the observed association between air pollution exposure and coronary heart disease, including enhanced coagulation and thrombosis, increased susceptibility to arrhythmia, systemic inflammation, and promotion of atherosclerosis.18 Mechanisms, more specific to particle exposure include pulmonary and systemic inflammation, accelerated atherosclerosis,19,20 and altered cardiac autonomic function.21 The pathway of inflammation/accelerated atherosclerosis is supported by studies demonstrating increased levels of inflammatory markers in humans exposed to air pollution, for example, C-reactive protein,22–25 fibrinogen,22,25–29 and platelet count.28 Altered cardiac autonomic control as a mechanistic pathway is supported by studies relating air pollution exposure to changes in heart rate,30–32 heart rate variability,27,30–38 and blood pressure.34,39,40 Nevertheless, it remains unclear to what extent these mechanisms are responsible for the association between chronic air pollution exposure and coronary heart disease.
Most previous studies on long-term exposure to air pollution and coronary heart disease have focused on cardiopulmonary mortality and have only occasionally included cause-specific mortality such as myocardial infarction.8–15 Thus, little is known of long-term air pollution exposure and incidence of coronary heart disease, although recent cohort data on women17 and previous case-control studies provide some support.16,41 Data on incidence and nonfatal coronary heart disease related to long-term air pollution exposure are sparse and inconclusive. Earlier long-term studies used either group-level exposure data (such as average air pollution levels from ambient monitors) assuming the same exposure for inhabitants of large areas and ignoring individual differences due to within-city variation8–10 or calculated levels according to large grids (kilometers) or as the distance to major roads.11,12 Only the baseline address has been available and changes in residential pollution exposure due to subsequent relocation are usually ignored. The aim of this study was to investigate the association between long-term air pollution exposure from traffic assessed by historic emission data, dispersion modeling and geographic information systems42 and the risk of developing fatal and nonfatal myocardial infarction in a large registry-based case-control study.
This is a population-based case-control study of the population aged 15 to 79 years in Stockholm County. Cases of myocardial infarction during 1985 to 1996 were identified using registries of hospital discharges and deaths in accordance with a previously developed and validated method,43 yielding a total of 43,275 cases. Recurrent myocardial infarction cases were excluded using information on previous infarctions from registries of Stockholm County back to 1972, cases occurring outside the County were tracked in registries since 1987. Controls were randomly selected from the study base on 31 December of each year 1984 to 1996 by using registers of the total population of Stockholm County, stratified on sex, age (13 5-year age groups), and calendar year.13 Controls were selected from 1984 to make it possible to calculate incidence rates. The person-time at risk used in the incidence estimates was calculated as the average of the total population on 31 December in the previous and the current year. The total population was derived by multiplying the prevalence of the different categories among the controls with the sampling fraction (the number of persons in Stockholm County in each stratum). One thousand five hundred controls were selected in each of the 338 strata, resulting in a total of 507,000 controls. Controls with a history of myocardial infarction were excluded. Information on occupation, education, income, and marriage was obtained from national population censuses of the years 1970, 1975, 1980, 1985, and 1990. Socioeconomic status was defined as blue collar and lower or upper white collar work, based on the occupational history from the preceding census according to the Swedish social classification system.44 If the individual was unemployed at the preceding census, information from the previous census was used. Individuals without employment (retired/pensioners and students) or with otherwise undefined employment status (homemakers and part-time workers) were coded as missing on socioeconomic status. Educational level was grouped into less than high school and high school or more. Income was divided into 2 groups, below and above the mean for the controls. Marital status was defined as being married or cohabiting according to the latest census or the previous census if data were missing. Sufficient registry data to code socioeconomic status were available for 72%, educational level for 64%, and marital status for 98%.
Air Pollution Exposure
The method for exposure assessment applied in this study has been described in detail elsewhere42 and previously used in other epidemiologic investigations.16,45 Air pollution emission databases were reconstructed for the years 1960, 1970, 1980, 1990, and 2000, based on detailed information on changes in traffic and other historic land-use variations. These databases, comprising information about traffic-generated emissions, provided information for dispersion calculations to obtain annual mean levels of nitrogen dioxide (NO2), carbon monoxide (CO), and particles with an aerodynamic diameter less than 10 μm (PM10) at each home address since 1960. Geographic coordinates for each person's home address were collected during 1980, 1985, and 1990, covering 69% of all participants.
The resolution of dispersion modeling corresponds to grids of 500 m in regional/countryside areas, 100 m in urban areas, and 25 m in the most populated inner-city area. Calibration of the models has been performed to minimize deviation when compared with available measured levels for the corresponding period. Modeled annual NO2 levels based on a 1995 edition of the emission database correlated well (r = 0.96) with measured levels in 16 locations throughout the study region.46
Five-year time-windows of exposure were constructed a priori due to the gap in the information on home addresses between the censuses. Other exposure time-windows were also calculated, including the maximum 25-year average exposure for each individual, to explore the importance of longer cumulative exposures. We would expect those estimates to incorporate more misclassification of exposure due to unknown residency further back in time. Relocation was assumed to occur on average in the middle between 2 censuses for subjects who had moved. Subgroup analyses were also performed on the individuals who did not change residence between the censuses to limit the influence from nondifferential misclassification of exposure.
The association between air pollution and myocardial infarction was analyzed with logistic regression. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). The logistic regression models were adjusted for the matching variables, that is, age (5-year age groups), sex, and calendar year (13 categories). Individuals younger than 35 years were merged into a single age group because of the small number of cases. Different multiple regression models were considered, including income, marital status, educational level, and socioeconomic status. The final model was based on the importance of all covariates and included the matching variables and socioeconomic status. Air pollution variables were used as continuous variables and the results are presented for the 5th-to-95th-percentile difference according to the distribution among controls. Analysis of nonfatal and fatal myocardial infarction within 28 days (divided into deaths occurring inhospital and out-of-hospital within 28 days after onset, respectively) was performed by multinomial logistic regression using all controls as reference. To explore potential effect modification, analyses were performed with interaction terms between the pollutants and other variables; P values for interaction are presented. All statistical analyses were performed with Stata/SE 9.1 (Stata Corp., College Station, TX). The study was approved by the ethical committee at Karolinska Institutet.
The study population and the distribution of exposure among cases and controls are displayed in Table 1. The group of cases included a larger proportion of men and individuals who were married or living with a partner, but a lower percentage of subjects with a high income or a higher education than the controls. The proportion of blue collar and low level white collar workers was higher among controls, whereas upper-level white collar workers were more prevalent among cases. The median level of all air pollutants during the last 5 years was slightly higher among cases than controls. The overall difference between the fifth to the 95th percentile of air pollution exposure was 31.3 μg/m3 for NO2, 25.6 mg/m3 for CO, and 5.7 μg/m3 for PM10.
Five-year average exposure to traffic-generated air pollution appeared to be associated with incidence of myocardial infarction, especially with fatal end points, but not with nonfatal disease (Table 2). A difference in exposure to NO2, CO, and PM10 from the fifth to the 95th percentile was associated with an adjusted OR for fatal myocardial infarction of 1.23 (1.15–1.32), 1.14 (1.07–1.21), and 1.16 (1.09–1.24), respectively. The corresponding figures for the group that did not move between population censuses were 2.54 (1.96–3.2), 2.03 (1.59–2.60), and 1.56 (1.28–1.91), respectively.
The estimates were slightly higher among men, older subjects, lower-level white collar workers, married subjects, those with a higher income, and subjects with higher education (Fig.). However, analyses of potential interaction did not demonstrate any statistically significant difference in OR according to sex (P = 0.82), age (P = 0.79), marital status (P = 0.24), income (P = 0.75), or socioeconomic status (P = 0.49). Due to a high correlation between individual exposures in different time-windows, the relative importance of exposure with different temporal relations to the outcome could not be efficiently explored. Nevertheless, when analyzing the time-windows 1 by 1, the observed ORs decreased monotonically with distance to the outcome. In addition, longer exposure windows appeared to result in lower estimates.
FIGURE Effect modifi...Image Tools
Ambient residential air pollution exposure over several years increases the risk of developing a first-time fatal myocardial infarction. The associations were generally strongest for out-of-hospital deaths and among those with least expected misclassification of true individual exposure (those who did not change residence between population censuses). These results support previous studies that found long-term air pollution exposure increases the risk of fatal cardiovascular disease.8–16,41 We found no indication of an increased risk for nonfatal myocardial infarction associated with long-term air pollution exposure.
Both short-term1–7 and long-term8–17 studies have demonstrated an increased mortality risk from traffic-related air pollution exposure. The particularly high-risk estimates for out-of-hospital death, also reported by others,16,47 imply that mechanisms related to acute effects, such as arrhythmia, may be of special importance. The difference in estimated effects between fatal and nonfatal cases may also suggest that air pollution affects the severity of the response rather than initiating the response. Air pollution might have harmful effects both during the life course of an exposed individual and act via mechanisms with a shorter time scale, such as, caused by a severe form of ischemia and thus resulting in more immediate coronary death. However, no investigation has yet been able to adequately separate the effects of short- and long-term air pollution exposure, and the question of whether variations in air pollution with time or geography, or both, are responsible for the increased mortality risks remains unresolved.
The associations appeared somewhat stronger for married subjects and the more privileged people. Although the differences were not large, these results are supported by previous data from the same population suggesting higher effect estimates among more affluent groups.16 One possible explanation may be that in Stockholm County, more affluent people not only live in the city center or in certain suburbs in close vicinity of the city, but they also tend to work in the city center, which would increase their exposure above categorization based on residency only. The highest odds ratios were observed among subjects who kept their same residence and thus were subjected to a lesser degree of nondifferential misclassification of exposure. Analyses using other time-windows of exposure and extended to cover longer time periods demonstrated consistently lower effect estimates. Although this might be interpreted as an evidence of recent exposure being more important, this is probably due to increasing nondifferential misclassification of exposure in earlier periods with unknown residential history.
Comparison with previous studies is difficult due to differences in exposure assessment, reported air pollution parameters and study design. Even so, our OR of 1.23 for fatal myocardial infarction with a 30 μg/m3 increase in NO2 exposure can be compared with previous American, Dutch, and Norwegian cohort studies as well as our previous case-control study on a smaller portion of the same population. Long-term ambient air pollution exposure defined as NO2 corresponding to 30 μg/m3 was associated with a relative risk for cardiovascular death of 1.37 in the American Six Cities study,8 1.81 in the Dutch cohort,11 and 1.51 in our previous Swedish investigation.16 Given the large discrepancy between the studies regarding study design, exposure assessment, and power, the rather small differences in effect between different indices of residential levels of air pollution from road traffic should be interpreted with caution. Very high effect estimates were recently reported17 in a cohort of US women, demonstrating relative risks of the same magnitude as discussed previously for an increase in fine particulate air pollution of only 10 μg/m3. Indeed, local long-term levels of fine particulate matter (PM2.5) and NO2 in Stockholm have been found to correlate very well.48
In a previous smaller study of the same population, we reported an increased risk of fatal but not nonfatal myocardial infarction being associated with 30-year exposure to ambient air pollution.16 In that study, we applied the same exposure assessment technique but with much better adjustment for individual risk factors, such as, smoking, body mass index, and a large set of other potential confounders.16 Although the present study has higher power, the results may be hampered by limited confounding control compared with the previous study. Other differences include registry outcome data alone in the present study, whereas we previously used data from several partly overlapping sources to assess both exposure and disease (eg, questionnaire and registry data to track relocation and collect confounder information). The present study largely supports our previous results of a higher risk for fatal myocardial infarction associated with long-term residential air pollution exposure, especially for out-of-hospital deaths, although with noticeably higher risk estimates. Although reasons for differences in effect sizes are unknown, some may be due to chance, given the limited power of the earlier study. On the other hand, bias from uncontrolled confounding may have contributed to an overestimation in the present study. Higher estimates may also be due to a more relevant time interval of exposure, with more weight given to recent than past exposures.
The strengths of this study mainly relate to its power and the combination of various population and health care registries of high quality. The identification of cases in the study population was done by combining Swedish hospital discharge registries and death records, a procedure that is expected to result in very few undetected cases. The method for identifying nonfatal cases has been evaluated previously and found to give a very high agreement with diagnostic criteria of myocardial infarction43,49,50 and the loss of death data from the national registry of causes-of-death records is negligible. We cannot rule out that selection bias might have contributed to our results, but it seems unlikely that such bias could explain the results, especially in view of the high quality of the population registries, the complete case identification and the large number of randomly selected controls. In addition, exposure to air pollution was assessed in fine resolutions (down to 25-m grids) by a methodology that has been evaluated and applied in previous large epidemiologic studies of myocardial infarction and lung cancer.16,42,45
The limitations of this study mainly relate to possible selection bias, misclassification of exposure, and uncontrolled confounding. The loss of subjects due to nongeocodable or unknown historical addresses may contribute to some selection processes. Residential stability was differentially related to air pollution levels based on fatal-case versus control status, which may point to selection bias. Among those who did not move, the modeled traffic-related (local contribution) NO2 level for fatal cases during the last 5 years was 14.2 μg/m3 compared with 11.9 μg/m3 for residentially stable controls. Corresponding figures for those who had moved were 12.0 and 11.5 μg/m3. However, it is hard to judge if this points to some unknown selection process (fatal cases residentially stable have higher pollution levels) and it is unlikely that such bias could explain the overall effects. Nondifferential misclassification of exposure was minimized by focusing on those who did not change residence between the censuses. Although the estimates were adjusted for individual coronary risk factors such as age, sex, and socioeconomic status, information on many other potentially important confounders, such as, smoking, body mass index, cholesterol, diet, and hypertension, were not available, making uncontrolled confounding a potential source of bias. Smoking is the most important preventable risk factor for myocardial infarction and potentially related to the residential air pollution exposure. However, smoking is also correlated with socioeconomic status and thus partially controlled for by the adjustment for socioeconomic status. In a previous case-control study on a subgroup of the same population (inhabitants aged 45–70 years in Stockholm County in whom a first myocardial infarction was diagnosed during 1992 to 1994 and matched population controls) suggest that controlling for socioeconomic status as well as individual smoking habits would decrease the effect estimate associated with NO2 exposure during the last 5 years by 24%.16 For example, our OR for fatal myocardial infarction associated with NO2 exposure during the last 5 years and restricted to those who did not change residence would reduce from 2.54 to 2.03. Thus, confounding from smoking likely biased our ORs away from the null value, but this effect is counteracted by the bias toward the null due to nondifferential misclassification of exposure.
In conclusion, this study supports previous data linking long-term exposure to traffic-generated air pollution to the risk of developing myocardial infarction. Furthermore, the results of this study suggest that long-term exposure to air pollution from traffic is not associated with nonfatal coronary heart disease.
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