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As people age, their ability to respond to the stress of current and accumulated environmental exposures may diminish due to physiologic and metabolic changes, resulting in increased susceptibility to health problems related to environmental contamination and other challenges.1 Preventing, postponing, or slowing down common diseases of aging are important goals,2 and reducing environmental exposures may help meet these goals.3
Cardiovascular disease (CVD) is an important cause of both morbidity and mortality in the United States, especially among the elderly, accounting for 38% of total mortality in 2002.4 Weight management, healthy diet, appropriate exercise, and avoidance of tobacco smoke exposure are recommended to reduce the risk.5 Environmental factors, such as air pollution6–8 and lead exposures,9–12 also contribute to the burden of CVD, but underlying biologic mechanisms are poorly understood.
Air pollution and lead exposures may affect cardiovascular health through the autonomic nervous system. Heart rate variability provides a noninvasive and quantitative measure of cardiac autonomic function.13 Decreased variability independently predicts mortality in middle-age and elderly subjects, in patients with diabetes, and in survivors of myocardial infarction and other coronary heart diseases.14–17 Decreased heart rate variability has also been associated with short-term exposures to air pollution18–23 and lead.24–27
Oxidative stress occurs when the production of reactive oxygen species exceeds the antioxidant capability of the cell,28 resulting in several adverse physiological consequences.29–31 Both air pollution and lead exposures can increase generation of reactive oxygen species and induce oxidative stress.32–35 Associations between air pollution, lead exposures, and heart rate variability were modified by underlying CVD and genotype,18,19,21,22,36 and so oxidative stress-related conditions may affect susceptibility to air pollution and lead. If oxidative stress is a common mechanism linking both air pollution and lead exposures with cardiac autonomic dysfunction, then individuals with high lead body burden may experience an even greater cardiac response to air pollution exposure. We tested this hypothesis by examining whether bone lead levels, which represent cumulative lead exposure, modify the short-term effects of air pollution on heart rate variability.
Participants were drawn from the Normative Aging Study, a longitudinal study of aging established by the US Veterans Administration (VA) in 1963.37 The methods are described in detail elsewhere.18,36 Briefly, 2280 community-dwelling men aged 21 to 80 years from the Greater Boston area were enrolled between 1963 and 1968 if they had no history of known chronic diseases. At each subsequent visit, extensive physical examination, laboratory, anthropometric, and questionnaire data were collected.
Beginning in 2000, during each participant's regularly scheduled evaluation in the VA system, we measured heart rate variability. Participants visited the study center in the morning after an overnight fast and abstinence from smoking. We collected data related to cardiovascular risk including body mass index, heart rate, systolic and diastolic blood pressure, and fasting blood glucose. Blood pressure was measured with the subject seated. Cigarette smoking, alcohol consumption, medical history (including respiratory and cardiovascular conditions), and subjects’ use of medications were ascertained by questionnaire. We recorded the temperature of the room where the heart rate variability was measured.
Beginning in 1991, participants who gave their informed consent were invited to undergo bone lead measurements. Bone lead levels were measured between 1991 and 2002. For the 75% of subjects with more than 1 bone lead measurement during this period, the measurement taken closest to the date of the heart-rate-variability measurement was used for this analysis. Characteristics of participants with and without bone lead measurements were similar.10
From November 14, 2000, to December 22, 2004, 671 active cohort members were examined. Of these, we excluded the following: 110 subjects with problematic heart rate measurements (atrial fibrillation, atrial bigeminy and trigeminy, pacemakers, irregular rhythm, irregular sinus rhythm, frequent ventricular ectopic activity, ventricular bigeminy, multifocal atrial tachycardia, or measurement time less than 3.5 minutes); subjects without tibia and paella lead measurements (n = 131 and n = 142, respectively); 10 subjects with high uncertainties (greater than 10 and 15 μg/g for tibia and patella, respectively); subjects with extreme tibia and patella lead levels, (n = 5 and n = 9, respectively); and 29 subjects with missing values of potential confounding factors. Hence, 384 (tibia) and 369 (patella) subjects were available for analyses. All participants had given written informed consent. This study was reviewed and approved by the Institutional Review Boards of Harvard School of Public Health and the VA Boston Healthcare System.
Measurement of Heart Rate Variability
Heart rate variability was measured between 6:00 am and 1:00 pm with a 2-channel (5-lead) electrocardiogram (ECG) monitor (Model: Trillium 3000; Forest Medical, East Syracuse, NY). After the participant had rested for 5 minutes, the ECG was recorded (sampling rate of 256 Hz per channel) for approximately 7 minutes with the subject seated. The ECG digital recordings were processed, and heart rate and variability measures were calculated with PC-based software (Trillium 3000 PC Companion Software for MS Windows; Forest Medical), which conforms to established guidelines.13 Beats were automatically detected and assigned tentative annotations, and then an experienced scanner reviewed the results to correct for any mislabeled beats or artifacts. We used only normal-to-normal beat intervals in the analysis. We used the best 4-consecutive-minute intervals for the variability calculations and computed high frequency (0.15–0.4 Hz) and low frequency (0.04–0.15 Hz) using a fast Fourier transform.
Bone Lead Measurements
Bone lead levels were measured with a K-shell x-ray fluorescence instrument at the midtibial shaft and the patella. The physical principles, technical specifications, and validation of this instrument are described in detail elsewhere.38 The tibia consists mainly of pure cortical bone, and the patella of pure trabecular bone, thus representing the 2 main bone compartments. Lead in trabecular bone (patella) has a faster turnover rate and therefore reflects more recent exposure than the lead in the cortical bone (tibia). The x-ray fluorescence instrument provides an unbiased estimate of bone lead levels (normalized for bone mineral content as micrograms of lead per gram of bone mineral) and an estimate of the uncertainty associated with each measurement.
Bone lead and heart rate variability were not measured simultaneously, with most of the bone lead measurements taken well before the heart rate variability measurements (median 3.2 years). Previously, we used estimated patella lead levels to account for the decay trend of patella lead levels over time.36 Lead levels in patella bone decreased 23% in the 3-year follow-up (7.7%/yr); no change in tibia lead levels occurred.39 Following other studies which predicted “peak tibial lead,” assuming first-order exponential kinetics,40,41 we accounted for the declining trend in patella lead levels by estimating patella lead as follows.
Estimated patella lead = measured patella lead × (1–0.0767)d, where d denotes the difference in years between dates of bone lead and heart rate variability measurement.
Air Pollution and Weather Data
Particulate matter <2.5 μm in aerodynamic diameter (PM2.5), black carbon, and sulfate were measured at the Harvard School of Public Health monitoring site, which is 1 km from the examination site. Ozone, temperature and dew-point temperature were obtained from Massachusetts Department of Environmental Protection local monitoring sites. To control for weather in the analyses of heart rate variability, we used apparent temperature, defined as a person's perceived air temperature.42,43 Apparent temperature combines the effects of heat and humidity in 1 variable and has been associated with both pollution and heart rate variability. We used 48-hour moving averages of PM2.5 and black carbon, and 4-hour averages of ozone matched on the time of measuring heart rate variability for each subject as our exposure indices, because a previous study showed the strongest association in these exposure periods (lags).18 Sulfate was measured as daily integrated mean concentrations, and so we used averages of the same and the previous days’ levels of sulfate as the exposure variable.
Other Long-Term Exposures: Traffic and Educational Attainment
Subjects’ residential addresses since enrollment were assigned latitude and longitude using standard methods.44,45 Cumulative traffic exposure was calculated by summing the product of average daily traffic and road length in meters for roads within 100 m of addresses using the MassHighway 2002 Road Inventory and ArcGIS software (version 9; ESRI, Redlands, WA). We calculated a weighted average of cumulative traffic exposure for each subject by duration of each residence.
Individual educational attainment was reported by participants as the highest level of education achieved. We used 3 categories: did not graduate from high school; graduated from high school; and graduated from a 4-year college or higher.45
Linear regression analyses were conducted to assess the association between heart rate variability and air pollutants. To improve normality and stabilize the variance, we used log10-transformed measures of heart rate variability as the response variables. Previously, we identified, a priori, the biologically important covariates for inclusion: age, body mass index, fasting blood glucose, antihypertensive medications (beta-blockers, calcium channel blockers, and ACE inhibitors), cigarette smoking, alcohol consumption, season (spring/summer/fall/winter) and apparent temperature.18,36 These variables were kept in the regression models regardless of significance. We also included 2 additional potential confounders: mean arterial pressure, which changed the effect estimates by more than 10%, and the temperature of the room where the heart rate variability measurement was taken. Room temperature did not change the associations between air pollution and heart rate variability but may account for some variance in the cardiac measurements. Finally, individual education attainment and cumulative traffic were included in the models as potential confounders. To account for the nonlinear association of apparent temperature with heart rate variability, a cubic spline with 3 degrees of freedom was used (model 1). We used log-transformed cumulative traffic because the distribution was skewed. To evaluate whether cumulative bone lead levels modify the effects of air pollutants on heart rate variability, we introduced interaction terms between quartiles of tibia or patella lead and each air pollutant in the models. Tests for linear trend of air pollution effects across quartiles of bone lead were computed. We calculated adjusted percent changes for an increase equal to the interquartile range (IQR) for each air pollutant, with 95% confidence intervals. We included the covariances as well as the variances in computing the standard errors of the effect estimates for the interaction terms.
We also calculated the residuals of the regression of bone lead on individual education attainment and cumulative traffic, our other 2 long-term exposures. These residuals represent the information in bone lead levels that cannot be explained by education and cumulative traffic, allowing us to evaluate whether long-term lead exposure is modifying the effect of air pollution on heart rate variability, independent of these other life-course experiences. Then we categorized these residuals into quartiles and ran the regression models above without education and traffic as covariates (model 2).
The mean ± SD age of study participants was 73 ± 6.5 years, and the median concentrations of lead were 19 μg/g in tibia and 23 μg/g in patella. The correlation between tibia and patella lead levels was 0.66. Table 1 shows demographic and clinical characteristics of subjects stratified by quartile of tibia lead levels. Older age and history of diabetes, ischemic heart disease, and hypertension were related to higher concentrations of tibia lead. Cumulative cigarette smoking (pack-years) was marginally associated with tibia lead levels. Individual education attainment was significantly inversely associated with tibia lead levels, but cumulative traffic was not. The low frequency component of heart rate variability decreased slightly with increasing tibia lead levels (p for trend = 0.14). When stratified by quartile of patella lead levels, smoking status and pack-years of cigarettes were associated with quartiles of patella lead, but no association with history of diabetes, ischemic heart disease and hypertension was found (eTable, available with the online version of this article). The other trends were not much different from those stratified by quartile of tibia lead levels.
Table 2 shows distributions of air pollution and apparent temperature and their correlations. The correlations between ambient particle pollutants were relatively high. Ozone was significantly correlated with PM2.5 (r = 0.51) and sulfate (r = 0.58), but not with black carbon (r = −0.01). The correlation coefficients with apparent temperature ranged from 0.33 for black carbon to 0.58 for ozone.
In a model including all 384 subjects, an IQR increase in PM2.5 (7 μg/m3) was associated with a 15% decrease (95% confidence interval = −27.9% to 1.2%) in high-frequency heart rate variability after adjustment for potential confounders. Ozone (16 ppb) was associated with a 21% reduction (−32.7% to −7.8%) in low-frequency heart rate variability. Black carbon and sulfate, and tibia lead and patella lead were more weakly associated with decreased high-frequency and low-frequency heart rate variability (data not shown).
The effects of air pollution across quartiles of bone lead are presented in Table 3. In the fully adjusted model (model 1), high frequency decreased by 22% (−37.4% to −1.7%) in association with 1 IQR increase in PM2.5 in subjects with high tibia lead levels (quartile 4), whereas little effect was observed in persons with relatively low tibia lead levels (quartiles 1–3). No important differences were observed across quartiles of tibia lead in the association between PM2.5 and low frequency. PM2.5 was associated with high frequency in the third and fourth quartiles of patella lead, and the effect of PM2.5 on high frequency was slightly stronger in persons with high patella lead levels (p for trend = 0.08). The association between ozone and reduced high frequency became stronger at higher levels of tibia lead, reaching 38% (−54.6% to −14.9%) in the fourth quartile of tibia lead (p for trend <0.01). Similarly, reductions in low frequency with ozone became stronger across the quartiles of tibia lead (p for trend <0.01), reaching 38% (−51.9% to −20.4%) with the highest tibia lead levels. Ozone associations across strata of patella lead were similar to those with tibia lead. Sulfate produced graded reductions in high frequency (p for trend <0.01) and low frequency heart rate variability (p for trend = 0.04) across the quartiles of tibia lead. One IQR increase in sulfate (2.5 μg/m3) was associated with a 22% decrease (−40.4% to 1.6%) in high frequency in the fourth quartile of tibia lead levels, whereas a 51% increase (5.4%–115.5%) in the first quartile of lead. Weaker less significant decreasing trends for sulfate were found across the quartiles of patella lead. Black carbon associations with heart rate variability did not differ across quartiles of tibia and patella lead. For quartiles of education and cumulative traffic-adjusted bone lead levels (model 2), the overall trends were slightly weaker.
In this large study of community-dwelling older men, we found evidence of effect modification by cumulative lead exposure in associations of sulfate and ozone with heart rate variability. This modification seems to be largely independent of individual education attainment or earlier traffic particle exposure. People who have been exposed to higher concentrations of lead may be more susceptible to impairments in cardiac autonomic function on days with higher levels of ozone and ambient fine particles. We do not know of previous studies that have assessed the interaction between air pollution and lead exposure in association with a health outcome.
Older adults and persons with diabetes are consistently reported as being more sensitive to fine particles, suggesting that impairment of antioxidant defense due to aging or preexisting oxidative stress-related conditions might play a role in the impact of particles on a susceptible population.18,46–48 Therefore, we hypothesized that chronic lead exposure, also known to increase oxidative stress, would modify the effect of ambient air pollutants.
In the present study, ozone associations with heart rate variability became stronger across quartiles of both tibia and patella lead levels, and the dose-response relations seemed either linear or to have thresholds. We previously reported that ozone exposure is independently associated with low frequency heart rate variability, which reflects largely sympathetic activity.18 Other studies have also found a relation between ozone and alterations in heart rate variability.22,23 In addition, numerous epidemiologic studies have demonstrated that ozone exposure is associated with increased total and cardiovascular mortality,49–52 acute myocardial infarction,53,54 and ventricular arrhythmias.55 Ozone is a secondary air pollutant, formed by the reaction of nitrogen dioxide with hydrocarbons in the presence of sunlight. Ozone can irritate lung epithelium,56 but because ozone is not thought to penetrate the lung, it may affect the autonomic nervous system through indirect inflammatory response due to generation of reactive oxygen species. Thus, we expected that persons with low lead levels would have less oxidative stress and would be less responsive to ozone exposure, whereas people exposed to lead chronically would retain high bone lead levels and have greater autonomic responses to the additional oxidative stress caused by ozone in both parasympathetic and sympathetic branches of the nervous system. Blood lead, a marker of recent lead exposure, may better indicate oxidative stress than bone lead, but blood lead measurements among the participants ceased just as heart rate variability measurements began. Future studies should consider evaluating interactions between blood lead and air pollution.
Though time-activity pattern data were not available for participants, they are elderly and likely to spend most of their time indoors. Ozone concentrations are low indoors, and so ozone may be acting a proxy for other, secondary, particle pollutants, such as sulfate. This hypothesis is supported by research showing that ambient ozone is a good predictor of personal exposure to sulfate57 and that both ozone and sulfate had similar associations with inflammation, oxidative stress, blood coagulation and autonomic dysfunction.58
We also found interactions between sulfate and tibia lead. Sulfates represent mainly regionally transported particles from coal-burning power plants and constitute the majority of PM2.5.59 In this study, sulfate and PM2.5 were relatively highly correlated (r = 0.91, Table 2). Sulfates have been associated with mortality and respiratory morbidity,60 but few studies have shown associations between sulfate particles and cardiovascular endpoints. Sulfate was positively associated with CVD mortality among elderly people61 and with CVD hospital admissions in the warm season.62 Sulfate exposure independently predicted reduced vascular reactivity, which is related to increased cardiovascular risk, especially in people with type-2 diabetes.47 In addition, secondary particles (primarily sulfates) were weakly associated with decreased heart rate variability.19
In our study, sulfate, but not other air pollutants, was positively related with heart rate variability measures in subjects with the lowest bone lead levels. People in this quartile were younger and less likely to have diabetes, ischemic heart disease, and hypertension (Table 1). However, this association controlled for fasting blood glucose (diabetes) and mean arterial pressure (an index related to hypertension). Additional adjustment for use of statins, which have antioxidant and antiinflammatory activity and may block the effect of ambient particles,47 and ischemic heart disease did not change this association. Elevated heart rate variability may be induced by stimulation of irritant receptors in the lung parenchyma and respiratory airways, which may increase bronchoconstriction and vagal responses of the heart associated with bradyarrhythmia.63 If what we saw is a valid association, stratifying by individual lead levels when examining the effect of sulfate on heart rate variability is important, lest the positive association in people with low lead levels dilute the negative association in those with high lead levels. This is a possible reason why we did not see a main effect of sulfate on heart rate variability in the whole population. Further epidemiologic and animal studies are needed to confirm this finding.
Bone lead weakly modified the association between PM2.5 and heart rate variability, although a significant reduction in high frequency was found among subjects with the highest tibia lead levels. Furthermore, associations with black carbon, which is mainly emitted by motor vehicles, were similar across quartiles of tibia and patella lead levels. This result, along with the consistent findings for the secondary pollutants, sulfate, and ozone, suggests that particle components have differential effects on the cardiovascular system. Sulfate exists as metal oxides, such as vanadium sulfate in fine particles, and therefore higher concentrations of sulfate may be paralleled by higher concentrations of toxic metals.64 These divalent metals may share the same mechanical pathway as lead for influence on the cardiac function, whereas ultrafine particles consisting of black carbon may have a different pathway. The weak association with PM2.5 may reflect the combined effects of sulfate and black carbon, the main constituents of PM2.5.
The observed effect modification by bone lead may be attributable to factors in the life experience of participants that correlate with cumulative lead exposure, other than individual education attainment and cumulative traffic, which we considered. Low socioeconomic status (eg, educational attainment, income, assets) is a well-known determinant of bone lead levels.45,65 Further, most adults have accumulated a substantial body burden of lead through past exposures to traffic particles from combustion of leaded gasoline.66 Bone lead modified air pollution and its associations with heart rate variability in the models adjusted for individual education attainment and cumulative traffic. In addition, utilization of education and cumulative traffic-adjusted bone lead levels (regression residuals) slightly reduced the strength but not the pattern of the trends seen using the bone lead quartiles. Thus, these other life-course experiences do not fully explain current susceptibility to air pollution among participants with higher cumulative lead exposure.
The trends in association between air pollution and heart rate variability across quartiles of tibia and patella lead levels were inconsistent, especially for sulfate. Tibia and patella lead have shown inconsistent associations with health outcomes in other epidemiologic studies: patella lead but not tibia lead has been associated with declines in hematocrit and hemoglobin,67 an increased risk of hypertension,68 and a steeper decline in cognitive function.69 However, tibia lead but not patella lead has been associated with an increased risk of hypertension,9 lower birth weight,70 and increased risk of age-related cataracts.71 These observed inconsistencies might be due to different lead kinetics and toxicity, with different clearance half-times in these cumulative lead exposure markers.
Previous evaluations of study participants did not show substantial main effects of lead on heart rate variability.36 Although low-level lead exposure is only weakly associated with cardiac autonomic function, it may play a role in enhancing the effects of ozone and sulfate. Lead exposure increases the generation of reactive oxygen species by depletion of glutathione and protein-bound sulfhydryl groups, leading to oxidative stress.72 Lead induces iron-dependent lipid peroxidation in liposomal membranes.73 Lead exposure also down-regulates nitric oxide generation.74 Further, lead inhibits the intracellular calcium messenger system and alters calcium homeostasis because of its mimicry of the calcium ion.75,76 These effects are associated with sympathetic excitation and vagal withdrawal.75,77,78
We have reported36 that associations between patella bone lead levels on heart rate variability are stronger among study participants with metabolic syndrome (a set of cardiovascular risks that increases the odds of developing type-2 diabetes, hypertension and coronary heart disease) and with individual components of metabolic syndrome.36 Thus, the increased sensitivity with higher cumulative lead exposure to air pollution could be attributed to higher prevalence of metabolic syndrome and its component conditions among participants in higher-lead quartiles. However, when we restricted to the subpopulation without metabolic syndrome (n = 275), the overall trends by lead quartile were similar (data not shown), suggesting that the observed interactions with lead may be independent of metabolic syndrome.
We have remarked previously on limitations of this study.18,36 The subjects are predominantly white men, and so results may not be generalizable to women or to other racial/ethnic groups. Use of a single ambient monitoring site instead of personal exposure monitoring may misclassify exposure. However, PM2.5 is spatially homogeneous in the Boston metropolitan area79 and outdoor particle measures are uniformly distributed across urban areas, suggesting that ambient particle concentrations are a good surrogate for personal exposure in greater Boston.57 Although bone lead data were not available for all subjects with heart rate variability measurements, characteristics of subjects who did and did not have bone lead levels measures were similar, and so the current study population is representative of the whole study sample.
In summary, long-term exposure to low-level lead, as measured in bone, modified the associations between cardiac autonomic function and short-term exposure to air pollution, especially secondary pollutants such as sulfate and ozone. This study provides evidence that people with higher past exposures to lead are at increased risk of adverse health outcomes from air pollution. Although in the United States leaded gasoline is no longer sold to the general public, and airborne concentrations have dropped dramatically,80 this study points to the enduring legacy of the accumulated exposure to this contaminant. Airborne exposure, diet, genetics, occupation, place of residence, age, and secular trends all influence accumulation of lead in bones where it is released over a lifetime.81 Additionally, although air quality has improved significantly, health-based standards are still violated in many communities.82
We thank Elaine R. Dibbs and Jordan D. Awerbach for their contributions to the VA Normative Aging Study. We are also grateful to the reviewers for suggestions that greatly improved the paper.
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