Epidemiologic studies have linked long-term exposure to fine particulate matter (PM) air pollution with cardiovascular morbidity and mortality by using cardiovascular events such as acute myocardial infarction or cardiovascular death.1 Several biologic pathways have been proposed to be responsible for these deleterious effects, including the induction of pulmonary and systemic inflammation, enhanced coagulation, arrhythmias, hypertension, and the development and progression of atherosclerosis, the major underlying pathology for cardiovascular events.1 To examine possible atherogenic effects of air pollution, it is necessary to investigate biologic markers that inform the degree of atherosclerotic disease, such as the ankle-brachial index, coronary artery calcification, or the carotid intima–media thickness.
Two studies have examined the effect of long-term exposures to air pollution on atherosclerosis and the results have been controversial. Animal experiments show that long-term exposure to fine particulate matter induces the development and progression of atherosclerosis.2,3 Epidemiologic evidence remains scarce. In a large unselected population-based study, we have shown an association between residential traffic exposure and coronary artery calcification (a reliable measure of early coronary atherosclerosis) and have found evidence for an association of high PM with coronary artery calcification.4 Only 2 studies have shown small increases in carotid intima-media thickness (a measure of general atherosclerosis) with higher PM exposure.5,6
The prevalence and extent of atherosclerosis is largely dependent on the type of vascular bed that is studied.7 In an ageing population, atherosclerosis of the coronary arteries and coronary events represent leading causes of death in industrialized countries. However, peripheral atherosclerosis and peripheral arterial disease (PAD) are less prevalent.7 Although calcification of different vascular beds share common risk factors, the effect size of different risk factors varies.8
The ankle–brachial index is a continuous marker for the degree of subclinical peripheral atherosclerosis, making use of the physiologic increase in the blood pressure pulse in peripheral arteries compared with the proximal segments. A hemodynamically relevant stenosis of the arterial lumen leads to a decrease in the ratio that correlates with the severity of the stenosis.7 An index below 0.9 confers an increased risk of all-cause and cardiovascular mortality and is a frequently used cutpoint to diagnose peripheral arterial disease.9
In this study, we investigated the association of long-term residential exposure to traffic and fine particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) with ankle–brachial index and prevalence of peripheral arterial disease in the population-based Heinz Nixdorf Recall Study in Germany. We used this well-characterized study population to examine whether ambient air pollution (a highly prevalent environmental exposure) is related to atherosclerosis in the peripheral vascular bed independently from atherosclerosis of the coronary arteries.
We used baseline data from the ongoing population-based, prospective Heinz Nixdorf Recall cohort study. The study design has been described in detail elsewhere.10 It was approved by the relevant institutional ethics committees and follows strict internal and external quality-assurance protocols. Briefly, the cohort comprises 4814 men and women aged 45–75 years from 3 large adjacent cities (Mülheim, Essen, and Bochum) of the densely populated and highly industrialized Ruhr Area in Germany. The study area covers a region of about 600 km2 with almost 1.2 million inhabitants. Subjects were randomly selected from mandatory lists of residence. The response proportion was 56%.
We used a residence-based approach to characterize exposure to urban air pollution.11 Briefly, home addresses of participants were geocoded with a geographic information system (MapInfo GmbH, Raunheim, Germany), based on data from mandatory surveys with a precision of at least ±0.5 m. We estimated the daily mean values for PM2.5 on a spatial scale of 5 km with the EURAD dispersion and chemistry transport model,12 using input data from official emission inventories, meteorologic, and regional topography data on a scale of 1 km2. The model was validated by comparing the daily model-derived values with measured air pollution data from monitoring sites, which showed a very good agreement (correlation between modeled daily averages of PM2.5 and measured PM2.5 0.86–0.88, depending on season).12 Annual mean values for the year 2002, which constitutes the midpoint of the baseline examination, were calculated for PM2.5 and assigned to each individual address. These PM2.5 concentrations represent the mean annual urban background concentration in each 25 km2 grid cell in the study region.
To assess additional PM contributions because of traffic on a small spatial scale, we calculated distances between residences and major roads (mean daily vehicle count 10,000–130,000), using official digitized maps with a precision of at least ±0.5 m. The reference line for distance measurements was the median strip between the oncoming traffic lanes. Distances were categorized as 0–10 m, 11–20 m, 21–30 m, 31–40 m, 41–50 m, 51–100 m, 101–150 m, 151–200 m, and greater than 200 m.
Main Outcome Measures
For the assessment of subclinical peripheral atherosclerosis, systolic brachial and ankle blood pressures were measured according to a standard protocol. All investigators were trained and certified in Doppler technique and regularly monitored throughout the study. Measurements were performed in the same order for each subject: left foot, right foot, right arm, and left arm. All pressure measurements were performed using a 8-MHz Doppler transducer (Kranzbühler, Logidop, Germany). For the measurement of the systolic brachial pressure, the Doppler transducer was placed over the cubital segment of the brachial artery. A cuff of appropriate size was rapidly inflated to a pressure 20 mm Hg above the value at which pulse noise diminished. Maximal adjusted cuff pressure was 300 mm Hg. Deflation velocity was 2 mm Hg/s. The first reappearance of sound was recorded as the systolic pressure. Measurements of the ankle artery pressures were performed analogously for the posterior tibial and dorsalis pedis arteries of both feet. ABI was calculated per leg as the ratio of the highest systolic brachial pressure, measured in the right and left arm, and the highest ankle artery pressure measured either in the posterior tibial or the dorsalis pedis artery.
Medical history of peripheral arterial disease was assessed by a standardized interview. A history of peripheral arterial disease was considered present if the subject could indicate precisely which kind of surgical or interventional procedures had been performed for peripheral arterial disease. All subjects with an ankle–brachial index less than 0.9 in 1 or both legs or a history of peripheral arterial disease treatment were considered cases.13
Risk Factor Assessment
The baseline assessment included a self-administered questionnaire and a personal interview for risk factor assessment and comprehensive laboratory tests. Coronary artery calcification was measured with nonenhanced electron-beam computed tomography scanning and the calcification score was computed according to Agatston.14,15 Presence of clinically manifest coronary heart disease was defined as a self-reported history of myocardial infarction or application of a coronary stent or angioplasty or bypass surgery. Systemic systolic blood pressure was measured following the WHO MONICA blood pressure recording protocol.16 Height and weight were measured according to a standardized protocol. Regular medication use was recorded and categorized using the anatomic-therapeutic-chemical classification of the World Health Organization. Lipid-lowering medication included 3-hydroxy-3-methyl-glutaryl coenzyme A reductase inhibitors (“statins”), fibrates, bile acid sequestrants, and nicotinic acid derivatives. Diabetes mellitus was defined as a prior physician diagnosis of diabetes or taking an antidiabetic drug or having a blood glucose level of 200 mg/dL or higher, or having a fasting blood glucose level of 126 mg/dL or higher. Physical inactivity was defined as no regular physical exercise. The smoking variables included indicator variables for current regular smoker, recent former smoker (cessation of smoking within last year), and long-term former smoker (cessation of smoking more than 1 year ago) and a continuous variable for number of cigarettes smoked per day. Environmental tobacco smoke exposure was assessed as frequent exposure at home or at the workplace or in other places (yes/no).
To control for socioeconomic status, years of schooling, and type of secondary and professional education were assessed and placed into 3 categories.17 To adjust for contextual effects acting independently from the individual-level variables, an ecologic variable was created for living in the northern part of the study region, comprising lower income residential areas with higher population density and more industrial activity.
The study population of 4348 consisted of participants for whom data on ankle–brachial index, peripheral arterial disease, and all covariates were available. To examine the association of air pollution and peripheral atherosclerosis independently of coronary atherosclerosis, we conducted the analyses in the complete study population, in participants without coronary heart disease (n = 4053) and in participants without high coronary calcification (calcification score below the 75th age- and sex-specific percentile, n = 3075).
First, we analyzed the ankle–brachial index as the dependent variable with linear regression. Participants with an index greater than 1.3, indicating Moenckeberg's medial calcinosis, were excluded from this analysis (454 for complete study population, 426 among those without coronary heart disease, and 347 among those without high coronary calcification). For the evaluation of residential traffic exposure, we categorized distance into 0–50 m, 51–100 m, 101–200 m, and more than 200 m (reference). Alternatively, we used the natural logarithm of distance, to account for the steep decline in traffic-related emissions in linear analysis. For distances greater than 200 m, we assigned a value of 400 m, where traffic emissions have usually reached background concentrations.18 PM2.5 concentration was examined on a linear scale or in categories according to quartiles of the PM2.5 distribution with the lowest quarter as reference. Second, the prevalence of peripheral arterial disease was examined with logistic regression with exposure variables included either as continuous variables or as categorized variables.
Next to the unadjusted models, we included age, sex, city, and area of residence in all models. Factors known to modify cardiovascular risk that were also associated with the exposure of interest (diabetes, blood pressure, body mass index, smoking status, environmental tobacco smoke, physical inactivity, socioeconomic status, medication with lipid-lowering medication, and antihypertensive medication) were added in a separate step.
Several studies have pointed to a possible modifying effect of individual characteristics such as sex, age, smoking, obesity, diabetes, and medication with statins on the association of air pollution with atherosclerosis or with mediating mechanisms such as inflammation.4,5,19,20 We therefore included interaction terms between exposure and the hypothesized modifying factors and conducted stratified analyses to evaluate differential effects. All subgroup analyses were also conducted stratified by sex.
Due to the skewed distribution of the truncated outcome variable ankle–brachial index, we repeated the analysis after normalizing by the natural log. To reduce misclassification of exposure due to spending a relevant part of the day away from home, as is probably the case with full-time employed participants, we examined the strength of the association with ankle–brachial index in the subgroup of retirees and homemakers who have not worked full-time during the last 5 years prior to the baseline analysis (n = 1490). In a subset of the study population, where information on household income was available (n = 3659), we adjusted for income (3 categories) in a separate step and examined the change in estimate. In addition, we conducted analyses after excluding the most influential subject from the database. To examine the influence of the composite definition of peripheral arterial disease, we calculated an odds ratio defined by an ankle–brachial index less than 0.9, without taking the self-reported history of interventions into account. We also used a different cutpoint in the logistic regression analyses, dichotomizing this index at 1.0. To investigate the independent association of air pollution and ankle–brachial index from the association of air pollution and coronary calcification, we additionally adjusted for coronary calcification.
The eFigure (https://links.lww.com/A728) illustrates the study area with the location of the participants’ homes and major roads and the distribution of the annual PM2.5 concentration. Most participants (n = 3687, 84.8%) lived more than 200 m away from a major road; 3.1%, 4.7%, and 7.5% of subjects lived within 50 m, 51– 100 m, and 101–200 m, respectively. The mean annual PM2.5 exposure was 22.8 μg/m3, ranging from 19.8 to 26.8 μg/m3.
Baseline characteristics of the study population (n = 4348) according to level of traffic and PM2.5 exposure are summarized in Table 1. Individuals living close to a major road were characterized by a higher level of cardiovascular risk factors, a lower ankle–brachial index and a higher prevalence of peripheral arterial disease. In the range of ankle–brachial index values less than 1.3, the index was only weakly correlated with the degree of coronary calcification (Spearman correlation coefficient, −0.09).
Residential proximity to a major road was weakly associated with ankle–brachial index in the complete study group. In the crude analysis, living within 101–200, 51–100, and 50 m or less was associated with a −0.021 (95% CI = −0.037 to −0.006), −0.008 (−0.028 to 0.011), and −0.032 (−0.056 to −0.009) absolute decrease in ankle–brachial index, respectively. After adjustment for covariates, estimates were attenuated to −0.015 (−0.030 to 0.0), −0.002 (−0.021 to 0.016), and −0.024 (−0.047 to −0.001), respectively. No clear exposure–response relation was observed for the complete study group and for participants without coronary heart disease (Fig. 1). Associations were largely confined to the closest distance category. In women we found evidence of an exposure–response relation, whereas no clear pattern was observed in men.
On stratification according to individual characteristics, we observed slightly stronger associations with ankle–brachial index in elderly and obese subjects, smokers, and subjects taking statin medication, but confidence intervals overlapped considerably and estimates for interaction terms were inconclusive (Table 2). We found no association between PM2.5 and ankle–brachial index in the complete study group or when stratifying according to individual characteristics. Subgroup analyses further stratified by sex did not yield any additional information due to rapidly decreasing sample sizes resulting in imprecise estimates (data not shown).
Living within 50 m of high traffic was associated with prevalence of peripheral arterial disease in the complete study group. No associations were observed for the other distance categories. In the crude analysis, living within 101–200 m, 51–100 m, and 50 m or less was associated with an OR of 1.18 (95% CI = 0.77–1.81), 1.14 (0.66–1.96), and 2.09 (1.23–3.53), respectively. Adjustment for covariates attenuated the estimates to 1.07 (0.68–1.68), 1.02 (0.58–1.80), and 1.77 (1.01–3.10), respectively. Living within 50 m of a major road was associated with peripheral arterial index in subjects without coronary heart disease and women, whereas no association was seen in men (Fig. 2). There was no indication of an exposure–response relationship.
Effect estimates for high traffic exposure (≤50 m) and PAD differed according to individual characteristics. Odds ratios in the full model were elevated in participants without high coronary calcification, smokers, elderly, and nondiabetic subjects (Table 3). For PM2.5 exposure, we did not find consistent associations in the full sample or when stratifying into subgroups.
Results were qualitatively unchanged when modeling distance as a continuous variable (natural logarithm of distance), showing weak associations with ankle–brachial index and peripheral arterial disease for a halving of the distance within 400 m (data not shown).
Sensitivity analyses showed that exponential transformation of the outcome variable ankle–brachial index did not affect model fit and estimates to a notable degree. Including household income in a subset of the study population (n = 3658) did not influence the point estimate. When excluding the most influential subject from the analysis, the estimated change in ankle–brachial index was reduced only slightly. Adjusting for coronary artery calcification did not change the estimate to a large extent (for the category ≤50 m, the fully adjusted decrease in ankle–brachial index was −0.021; −0.044 to 0.002).
The association between high exposure to residential traffic (≤50 m) and ankle–brachial index was restricted to the group of subjects (n = 1490) who had not been working full-time during the last 5 years prior to the baseline analysis and therefore presumably had spent more time at home (adjusted absolute decrease in ankle–brachial index −0.040; −0.078 to −0.002), in contrast to the 2403 subjects who had been working full-time during this period (−0.014; −0.042 to 0.014). A clear association of PM2.5 with ankle–brachial index was not shown in either subgroup.
The adjusted OR for the association of proximity to traffic (≤50 m) and prevalence of peripheral arterial disease was slightly higher, when peripheral arterial disease was defined as an ankle–brachial index less than 0.9 only (2.00; 1.12–3.56). Shifting the cutpoint to an index less than 1.0 attenuated the effect estimate considerably (1.40; 0.88–2.21).
The main result of our study is that long-term residential exposure to high traffic is weakly associated with a decrease in ankle–brachial index, a measure of subclinical peripheral atherosclerosis, and with prevalence of peripheral arterial disease. These associations were independent of the degree of atherosclerosis in the coronary vascular bed. Associations of traffic exposure and measures of peripheral atherosclerosis were generally stronger in women, whereas associations in men were inconsistent. In contrast, we did not find associations between modeled PM2.5 and either ankle–brachial index or peripheral arterial disease.
Despite the small effect size, these estimates provide evidence of a potential chronic mechanism by which air pollution might be linked to the development of cardiovascular disease. Most studies have investigated short-term exposures that provoke acute pathophysiologic changes, such as functional measures of early-stage atherosclerosis21–24 or cardiovascular events that occur when plaques have already been formed in the vascular bed.1 Our study points to traffic-related air pollution as a possible cause of the underlying pathology, namely the development and progression of atherosclerosis, the major cause of cardiovascular disease. Only a few studies have linked long-term exposure to ambient PM or traffic with measures of central or coronary atherosclerosis, showing weak to moderate associations.4–6 The current study uses ankle–brachial index, which quantifies subclinical atherosclerosis in the peripheral vascular bed. Different vascular beds are known to be influenced by cardiovascular risk factors in different ways.7 In fact, ankle–brachial index and the amount of coronary artery calcification were not closely correlated in our study population. Our results show that the association between chronic traffic exposure and atherosclerosis is not limited to the coronary vascular bed, but extends to the peripheral vascular bed, independent of clinically manifest coronary heart disease and the degree of coronary calcification.
The size of the effect was generally small in our study. Small decreases in ankle–brachial index are not relevant for the clinical management of patients. Nevertheless, an OR of 1.77 for peripheral arterial disease in persons highly exposed to air pollution is not a negligible clinical effect, and is comparable with results for other clinical outcomes such as cardiovascular morbidity and mortality.11,25 Because we adjusted for factors that possibly lie on the mechanistic pathway of the effect of air pollution on cardiovascular health, such as hypertension and lipid status, our estimates represent a conservative approach.
In exposure–response analyses, the associations were largely confined to the closest distance category of living within 50 m of a major road. The majority of traffic-related particles are in the ultrafine (<100 nm) size range.26 The concentration of ultrafine particles declines steeply perpendicular to the road, usually reaching background concentrations within 200–400 m.18 This could explain why associations with ankle–brachial index and peripheral arterial disease were restricted to the closest distance category where concentrations of traffic-related ultrafine particles are high. Traffic-related particles have been shown to exert an adverse effect on vascular reactivity.24,27,28 Although several studies now suggest a role for traffic-related air pollution in the pathogenesis of atherosclerosis, it has not been possible to identify clearly the intermediaries of this process.
Long-term PM2.5 exposure, quantified as the 2002 annual mean PM2.5 concentration at the home address, was not related to ankle–brachial index or peripheral arterial disease in our study population. Several factors might explain our finding. First, the degree of spatial resolution, averaging PM2.5 over a grid cell size of 25 km2, is probably not sufficient to capture small-scale spatial variations in PM2.5 exposure, leading to exposure misclassification. This low level of resolution also causes the exposure differences due to traffic (only within 200–400 m of a major road) to be undetectable. Indeed, annual PM2.5 exposure was not correlated with distance measurements in this study.
Second, although a range from 19.8–26.8 μg/m2 in annual PM2.5 mean can be considered substantial, given the small size of our study area (approximately 20 × 30 km), the absolute PM2.5 exposure contrast might not be sufficient to see small effects.
Third, PM is a mass-based measure that contains no information on the chemical or physical properties of the particulates. Certain constituents and characteristics of PM, such as oxidative properties, concentration of transition metals, and number of ultrafine particles, may confer toxicity that is not strongly correlated with PM2.5 concentration.29–32
We found considerable differences in association between subgroups. Most important, although the association was more pronounced in women, there was no consistent association of traffic exposure with ankle–brachial index or peripheral arterial disease in men.
Some of these differences might be explained by subgroup-specific exposure misclassification with men and younger participants spending more time away from home. Sensitivity analyses revealed a stronger association in homemakers and participants who had not been working full time during the 5 years prior to the baseline analysis, of whom the majority were women or elderly.
Stronger associations with subclinical markers of atherosclerosis for subjects receiving statin therapy were also observed by others.5 Although the use of statins is probably not a causal factor, it might be an indicator of a long-standing dyslipidemic metabolic state that confers an increased risk for the development of atherosclerosis, because 1 hypothesized pathway of PM action on the cardiovascular system is the oxidation of low-density lipoprotein cholesterol.33
The stronger association in smokers contrasts with prior findings.5,6,11 We speculate that the concurrent exposure to cigarette smoke and high exposure to residential traffic could have a superadditive effect on possible mediating processes such as the induction of inflammation or the generation of oxygen radicals by PM, but no definitive explanations exist.
Our results also suggest a stronger association in obese subjects, which agree with the hypothesis that the development of atherosclerotic disease is mediated by inflammatory mechanisms.20,21 Obesity or diabetes lead to increased inflammatory activity, and the already up-regulated inflammatory pathways might be more susceptible to changes induced by additional traffic-related PM exposure.
Exposure misclassification is a prominent concern in air pollution epidemiology. We used a residence-based approach, capturing the location where the major part of the day is spent.34 However, other important sources of exposure are missed with this approach, such as occupation-related exposures, time spent in traffic and indoor sources of particles. These other sources of exposure could be related to the exposure at the residence and therefore bias the estimate.
The ankle–brachial index decreases only when a hemodynamically relevant stenosis of the lumen of the conduit arteries exists. The possibility of activating or developing collateral vessels attenuates the relationship between the degree of stenosis and the decrease in ankle–brachial index. Moreover, conditions associated with vascular calcification can cause incompressible arteries. On the other hand, successful treatment of peripheral arterial disease leads to an increase in ankle–brachial index. These characteristics might have led to a misclassification of our main outcome measure. Self-report of interventions for peripheral arterial disease might have led to outcome misclassification in the analyses. However, sensitivity analyses with peripheral arterial disease defined only by ankle–brachial index less than 0.9 revealed largely unchanged results. Because of the lack of time between exposure and outcome, we cannot draw causal conclusions from this study. Considering the low precision in the adjustment for some confounders, such as physical inactivity, residual confounding might be a further source of bias.
The strengths of this study include the large study population that was recruited as a random sample from a complete list of residents, the wealth of detailed information on personal characteristics and cardiovascular risk factors, the highly standardized assessment of outcomes and covariates, and the precision of the distance measurements. The study area is characterized by high exposure contrasts to traffic-related emissions due to the proximity of residences to high-volume roads in this metropolitan area. Furthermore, this geographically coherent and uniform study area ensures similar exposure characteristics for air pollution due to long-range transport.
In conclusion, we showed that long-term residential exposure to high traffic is weakly associated with the ankle–brachial index, a measure of subclinical atherosclerosis, and with prevalence of peripheral arterial disease in women. Although prospective studies on subclinical measures of atherosclerosis are still needed, this study adds to evidence on the proatherogenic effect of air pollution.
We thank R. Krapoth (city administration of Mülheim), F. Knospe and M. Moldzio (both city administration of Essen), and G. Zickuhr (city administration of Bochum) for their valuable support in geocoding the addresses and calculation of distances; the North Rhine-Westphalia State Agency for Nature, Environment, and Consumer Protection for providing air quality data; the investigative group and the study staff of the Heinz Nixdorf Recall Study; and Sarstedt AG & Co. for laboratory equipment.
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