Abstract
Background
Polycyclic aromatic hydrocarbons (PAHs) are potent atmospheric pollutants produced by incomplete combustion of organic materials. Pre-clinical and occupational studies have reported a positive association of PAHs with oxidative stress, inflammation and subsequent development of atherosclerosis, a major underlying risk factor for cardiovascular disease (CVD). The aim of the current study is to estimate the association between levels of PAH biomarkers and CVD in a national representative sample of United States (US) adults.
Methods
We examined adult participants (≥20 years of age) from the merged US National Health and Nutrition Examination Survey 2001–2010. Logistic regression models were used to estimate the associations of each urinary PAH biomarker and CVD. Post-exploratory structural equation modeling was then used to address the interdependent response variables (angina, heart attack, stroke and coronary heart disease) as well as the interdependencies of PAH biomarkers.
Results
PAH biomarkers were positively associated with cardiovascular disease in multiple logistic regression models, although some associations were not statistically robust. Using structural equation modelling, latent PAH exposure variable was positively associated with latent CVD level variable in the multivariable adjusted model (β = 0.12; 95% CI: 0.03, 0.20).
Conclusion
A modest association between levels of PAH biomarkers and CVD was detected in US adults. Further prospective studies with adequate sample size are needed to replicate or refute our findings.
Keywords: Cardiovascular disease, polycyclic aromatic hydrocarbons, NHANES, Structural equation modelling
1. INTRODUCTION
Despite advances in prevention, diagnosis and treatment, cardiovascular disease (CVD) remains the number one cause of mortality in United States (U.S.) adults (1). Cardiovascular disease refers to numerous conditions, many of which are related to atherosclerosis which develops when plaque builds up in arterial walls, narrowing the arteries, and decreasing or sometimes completely blocking tissue blood flow (2). Such mechanisms can manifest themselves eventually with adverse clinical outcomes such as coronary heart disease, angina pectoris, heart attack, and stroke.
Epidemiological evidence suggests that exposure to particulate matter present in ambient air may pose an increased CVD risk in humans (3). Polycyclic aromatic hydrocarbons (PAHs) are potent atmospheric pollutants that occur in oil, coal, and tar deposits, and are produced as byproducts of smoking, indoors and outdoors fuel burning and food grilling (4–6). Pre-clinical studies have reported a positive association between exposure to PAHs, oxidative stress and atherosclerosis (7, 8). Epidemiological studies have found a positive association between biomarkers of PAH exposure and serum inflammatory markers of CVD (9). In addition, a positive association between occupational exposure to PAHs and CVD morbidity and mortality has been reported (10, 11). However it is not clear if exposure to PAHs is associated with cardiovascular disease in the general population.
With advantages of recent nationally representative sample surveys and standardized data collection approaches with relatively large samples, we examined the association of PAH exposure and CVD in the United States (US) general population. In addition, we used Structural Equation Modelling approach trying to account for the interdependencies that must be confronted when different PAH biomarkers are studied all at once. We also are accounting for the shared pathogenesis of the response variables, namely the CVD events (angina, heart attack, stroke and coronary heart disease).
2. METHODS
2.1 Study population
The National Health and Nutrition Examination Surveys (NHANES) consist of a series of surveys designed by the National Center for Health Statistics to continuously monitor the health status of the U.S. civilian non-institutionalized population (12). The NHANES survey includes a stratified multistage probability sample. Selection is based on counties, blocks, households and individuals within households, and included oversampling of non-Hispanic Blacks and Mexican Americans in order to provide stable estimates of these groups. Data are collected for a two-year survey cycle.
In the current study we merged 2001–02, 2003–04, 2005–06, 2007–08 and 2009–10 data cycles, where eight analytes of PAHs have been consistently measured. There were 27584 participants who were ≥ 20 years of age. Urinary PAH biomarkers were only measured in a subsample NHANES (n= 7848). Participants with missing information on serum cotinine and other covariates were not included in the final model. This resulted in 7301 participants included in the final analyses.
2.2 Outcome: Cardiovascular disease
A standardized medical condition questionnaire was administered during the personal interview on a broad range of health conditions including coronary heart disease, angina pectoris, heart attack and stroke. Participants were asked “has a doctor or other health professional ever told you that you have: coronary heart disease (CHD)/angina pectoris/heart attack/stroke?” (These were 4 separate questions with the same wording style). A participant was considered a CVD case if she/he answered “yes” to any of the previous questions (0: no event occurrence/1: occurrence of at least one of the 4 clinical events).
2.3 Main exposure: Urinary levels of PAH biomarkers
Detailed urine specimen collection and processing instructions are discussed in the NHANES Laboratory/Medical Technologists Procedures Manual (13). Specific analytes measured in NHANES are monohydroxy-PAH (OH-PAH). The procedure involves enzymatic hydrolysis of urine, with extraction, derivatization and analysis using capillary gas chromatography combined with high resolution mass spectrometry (GCHRMS). This method uses isotope dilution with carbon-13 labeled internal standards. Ions from each analyte and each carbon-13 labeled internal standard are monitored, and the abundance of each ion is measured. The ratios of these ions are used as criteria for evaluating the data. By evaluating these analytes in urine, a measurement of the body burden from PAH exposure is obtained (A detailed description is available online at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/l31pah_c_met.pdf).
The limit of detection (LOD) was defined as the higher LOD calculated by two methods: (i) in direct relation to method blanks prepared in parallel with the unknown samples, as 3 times the standard deviation of the method blanks, and (ii) according to the instrumental detection limit defined as the lowest point in the calibration curve (0.5 pg/uL, or 5 pg/mL in 2-mL urine samples) verified to give a signal with the S/N equal to or greater than 3. The limit of detection for each biomarker and each data cycle can be found in the corresponding NHANES PAH lab files provided as supplementary materials. Less than 1% of the study population has PAH levels below lower detection limit.
Checks were made on the stability of the analytical system. Blanks and standards, as well as quality control materials, were added to each day's run sequence. The blank and standard were analyzed at the beginning of each run to check the system for possible contamination or in the spiking solutions and/or reagents. Two QCLs and two QCHs were prepared and analyzed at the beginning and the end of each run; their concentrations were compared with acceptance criteria to assure the proper operation of the analysis. Relative retention times were examined for the internal standard to ensure the choice of the correct chromatographic peak. More details on quality control procedures can be found in the online supplemental materials.
Seven urinary low molecular weight PAH analytes (1-hydroxynapthol, 2-hydroxynapthol, 2-hydroxyfluorene, 3-hyrdroxyfluorene, 1-hydroxyphenanthrene, 2-hydroxyphenanthrene, 3-hydroxyphenanthrene) and one urinary high molecular weight analyte (1-hydroxypyrene) were consistently available in NHANES 2001–10. Few other biomarkers are not included in the current study because they were not available in all years. All analytes were measured in the same unit; ng/L. Urinary analytes of PAHs were corrected for creatinine concentration to reduce their variability by differences in urinary outputs. Urinary levels of OH-PAH (ng/L) were divided by urinary creatinine level (mg/dL) multiplied by 0.01, i.e., [(ng/L) ÷ (mg/dL*0.01)] and expressed as nanogram per gram of creatinine (ng/g creatinine).
2.4 Covariates
In NHANES, information on age, gender, ethnic self-identification (ESI), alcohol drinking, and poverty-income ratio (PIR) were obtained during a standardized questionnaire during a home interview. Information on anthropometric, physical and laboratory components were obtained during the medical center examination. Body mass index (Kg/m2) was calculated as weight in kilograms divided by height in meters squared. Serum total cholesterol (mg/dL) was measured enzymatically. Serum cotinine (ng/mL) was measured by an isotope dilution-high performance liquid chromatography atmospheric pressure chemical ionization tandem mass spectrometry.
2.5 Statistical analysis
Exploratory data analysis techniques were used to assess the univariate distribution of the study variables. Urinary PAH biomarker levels were log-transformed as a result of their skewed distribution. We ran logistic regression models to calculate the odds ratio ([OR] and 95% confidence interval [CI]) of self-reported CVD, for each urinary OH-PAH, controlling for age (years) and sex. Final models were additionally adjusted for ESI (non-Hispanic White, non-Hispanic Black, Hispanics, and all others), education (less than high school, high school, and above high school), PIR, past-year alcohol drinking, BMI (normal, overweight, obese), total cholesterol (mg/dL), and serum cotinine (ng/mL).
Structural Equation Modelling (SEM) was then used to construct a series of models to estimate the association of PAHs and CVD level. Buncher et al discussed the application of SEM in Environmental Epidemiology early in 1991 (14). Structural equation modeling is a group of statistical methods that can model relationships between one or more independent variables and one or more dependent variables (15). In the current analysis, PAH exposure is a latent construct that is not directly measured but rather assessed indirectly by PAH biomarkers. Instead of simply combining PAH biomarkers by taking the sum and assigning equal weight to each biomarker, they are employed as indicators of a latent construct and hence allows for estimation and removal of the measurement error (15). Limitations of including multiple indicators of the same exposure in regression models (such as collinearity) are accounted for in the SEM approach (16, 17). Similarly a latent construct for CVD level was created via self-reported physician diagnosis of coronary heart disease, angina, heart attack and/or stroke. For both constructs, we defined factor loadings of 0.4 or greater as strongly correlated indicators with the latent construct. This part of the model that relates the measured variables to the corresponding latent construct is the measurement part of the model. The hypothesized association between the two constructs is considered the structural part of the model, regressing the latent CVD level construct as the response variable on PAHs construct. In the initial models, we used maximum likelihood estimation with robust standard errors (MLR). Because MLR does not provide fit indices, in our post-exploratory step we used a robust weighted least squares estimator (WLSMV). We determined goodness of fit of the hypothesized models to the data by several fit indices, including comparative fit index (CFI) ≥0.95 and root mean square error approximation (RMSEA) ≤0.05.(18, 19)
3. RESULTS
Table 1 presents main characteristics of the study population. About one half of the study population was female (51.2%). The majority of the study population was non-Hispanic White (71.1%). The arithmetic mean of serum cotinine was 64.1 ng/mL. Table 2 presents selected percentiles of urinary OH-PAH biomarkers.
Table 1.
Baseline characteristics of the study population (n= 7301). Data for the United States adults ≥ 20 years of age based on the National Health and Nutrition Examination Survey 2001–2010
| Characteristics | Mean values ± std error of mean or sample size (weighted percentages) |
|---|---|
| Age (years) | 46.2 ± 0.3 |
| Sex (%) | |
| Male | 3550 (48.8) |
| Female | 3751 (51.2) |
| Ethnic self-identification (%) | |
| Non-Hispanic White | 3693 (71.1) |
| Non-Hispanic Black | 1378 (10.7) |
| Hispanics | 1919 (12.8) |
| All others | 311 (5.4) |
| Education (%) | |
| Less than high school | 2079 (18.3) |
| High school | 1773 (25.1) |
| Above high school | 3449 (56.6) |
| Income-poverty ratio <1 | 1325 (12.6) |
| Past-year alcohol drinking (%) | 4527 (67.6) |
| Body mass index (kg/m2) | |
| <25 | 2184 (32.7) |
| 25–29.9 | 2542 (33.4) |
| ≥30 | 2575 (33.9) |
| Serum cotinine (ng/mL) | 64.1 ± 2.8 |
| Total cholesterol (mg/dL) | 198.8 ± 0.8 |
| Any CVD (%) | 732 (7.9) |
| Coronary heart disease (%) | 333 (3.7) |
| Angina (%) | 218 (2.4) |
| Heart attack (%) | 307 (3.3) |
| Stroke (%) | 235 (2.4) |
Table 2.
Selected percentiles of urinary biomarkers of polycyclic aromatic hydrocarbons (ng/g creatinine) among participants included in the final analysis. Data for the United States adults 20 years of age based on the National Health and Nutrition Examination Survey 2001–2010
| Biomarkers | 10th percentile | Q1 | Median | Q3 | 90th percentile |
|---|---|---|---|---|---|
| 1-hydroxynaphthalene | 515 | 901 | 2,081 | 6,941 | 17,532 |
| 2-hydroxynaphthalene | 957 | 1,576 | 3,114 | 7,454 | 15,717 |
| 2-hydroxyfluorene | 103 | 142 | 227 | 609 | 1,630 |
| 3-hydroxyfluorene | 33 | 50 | 86 | 279 | 909 |
| 1-hydroxyphenanthrene | 62 | 90 | 141 | 231 | 361 |
| 2-hydroxyphenanthrene | 26 | 39 | 61 | 102 | 178 |
| 3-hydroxyphenanthrene | 36 | 53 | 85 | 158 | 297 |
| 1-hydroxypyrene | 26 | 44 | 83 | 159 | 313 |
The main estimates of the study are presented in Table 3. Individual polycyclic aromatic hydrocarbons were positively associated with self-reported CVD. However, only 1-hydroxynaphalene, 2-hydroxynaphalene, 2-hydroxyfluorene and 3-hydroxyfluorene were statistically robust.
Table 3.
The association of PAHs biomarkers and cardiovascular disease. Data for the United States adults ≥ 20 years of age based on the National Health and Nutrition Examination Survey 2001–2010
| OH-PAH (ng/g creatinine) | Age-sex adjusted odds ratio (95% CI) | Multivariable-adjusted odds ratio (95% CI)a |
|---|---|---|
| 1-Hydroxynaphthalene | 1.13 (1.07, 1.21) | 1.11 (1.04, 1.18) |
| 2-Hydroxynaphthalene | 1.31 (1.19, 1.45) | 1.22 (1.08, 1.38) |
| 2-Hydroxyfluorene | 1.31 (1.18, 1.45) | 1.27 (1.12, 1.43) |
| 3-Hydroxyfluorene | 1.21 (1.11, 1.33) | 1.18 (1.06, 1.32) |
| 1-Hydroxyphenanthrene | 1.12 (1.00, 1.25) | 1.07 (0.94, 1.21) |
| 2-Hydroxyphenanthrene | 1.22 (1.09, 1.37) | 1.11 (0.98, 1.26) |
| 3-Hydroxyphenanthrene | 1.13 (1.00, 1.27) | 1.10 (0.96, 1.25) |
| 1-Hydroxypyrene | 1.20 (1.08, 1.33) | 1.12 (1.00, 1.26) |
Adjusted for age (years), sex, ESI (non-Hispanic White, non-Hispanic Black, Hispanic and all others), education (less than high school, high school and above high school), PIR, past-year alcohol drinking, BMI (normal, overweight and obese), total cholesterol (mg/dL) and serum cotinine (ng/mL)
Figure 1 presents the baseline conceptual model regressing the latent construct of CVD level as the response variables on the level of PAH exposure, measured by eight urinary PAH biomarkers, controlling for age (years) and sex. Results indicated a positive association between PAHs and CVD (β = 0.12; 95% CI: 0.07, 0.17). The factor loadings were all ≥ 0.4 suggesting a strong correlation between the measures and each corresponding construct.
Figure 1.
Model depicting the hypothesized PAH exposure-CVD association. Data for the National Health and Nutrition Examination Survey 2001–2010 (n=7301)
Each latent construct is modeled as a common factor underlying the associated measures. These "loadings" linking constructs to measures are labeled with the Greek character λ "lambda".
β "beta" refers to the linear regression parameter regressing the latent CVD variable on the latent PAH exposure variable.
Age-sex adjusted unstandardized estimates presented.
Table 4 presents the association of PAH exposure level and CVD level constructs additionally adjusting for ESI, education, PIR, alcohol drinking, serum cotinine, total cholesterol and BMI. Our results did not change appreciably (β = 0.12; 95% CI: 0.03, 0.20), suggesting a positive association between PAHs and CVD independent of the potential confounders studied here. Our results were consistent using either MLR or WLSMV estimator. Table 4 also presents the association of PAH and CVD constructs, stratified by sex, ESI and smoking status. Overall, PAH was associated with CVD in the stratified subgroups, although some associations were not statistically robust. We did not detect subgroup variations in the estimates.
Table 4.
Estimated association of polycyclic aromatic hydrocarbons exposure on cardiovascular disease level in adults (≥20+ years), stratified by participants characteristics. Data for the United States based on the National Health and Nutrition Examination Survey 2001–2010.
| Characteristics | Age-sex adjusteda β (95% CI) | Multivariable adjustedb β (95% CI) |
|---|---|---|
| Full sample | 0.12 (0.07, 0.17) | 0.12 (0.03, 0.20) |
| Sex | ||
| Male | 0.06 (−0.01, 0.13) | 0.08 (−0.02, 0.17) |
| Female | 0.18 (0.11, 0.25) | 0.16 (0.07, 0.26) |
| ESI | ||
| NH-White | 0.13 (0.07, 0.19) | 0.13 (0.03, 0.23) |
| NH-Black | 0.10 (0.01, 0.19) | 0.15 (0.04, 0.27) |
| Hispanic | −0.04 (−0.12, 0.04) | 0.01 (−0.10, 0.13) |
| Smoking | ||
| Never | 0.08 (−0.04, 0.20) | 0.11 (−0.01, 0.23) |
| former | 0.03 (−0.09, 0.15) | 0.02 (−0.10, 0.14) |
| Recently active | 0.24 (0.09, 0.39) | 0.25 (0.13, 0.37) |
Adjusted for age and sex, except for stratified variable.
Adjusted for age, sex, ESI, education, PIR, alcohol drinking, serum cotinine, total cholesterol and BMI, except for stratified variable.
A WLSMV estimator was used (probit regression are estimated). Model fit for each of the three models: RMSEA < 0.05; CFI ≥ 0.95.
4. DISCUSSION
Exposure to polycyclic aromatic hydrocarbons measured by eight urinary PAH biomarkers exhibited a positive association with cardiovascular disease in adults ≥ 20 years of age independent of serum cotinine a marker of nicotine exposure as well as other potential confounders. Our results are consistent with findings from previous occupational studies which reported positive associations between exposure to PAHs, and ischemic heart diseases and cardiovascular mortality in occupations that include likely exposure to PAHs (10, 11, 20, 21). Xu et al. used NHANES 2001–04 and reported a positive association between PAH biomarkers and self-reported CVD using logistic regression modes (22). In the current study, a latent CVD construct approach was selected in addition to utilizing the standard binary approach (0: no event occurrence/1: occurrence of at least one of the 4 clinical events) to allow for consideration of the shared pathogenesis in the development of CHD, angina, heart attack and stroke by means of a main common mechanism, namely atherosclerosis (23). A latent PAH variable was also used to account for the interdependencies of the PAH biomarkers as humans are usually exposed to mixtures of PAHs (24). Due to the high cost of detecting parent PAH levels in humans, the most commonly used biomarkers of PAH exposure are urinary OH-PAH biomarkers. Urinary PAH biomarkers have been previously found to correlate well with levels of exposure to PAHs in the general population (25).
The mechanisms underlying the positive association of PAH exposure and CVD remain unknown. Upon exposure to PAHs, detoxification occurs leading to the formation of highly reactive intermediates that can interact with the DNA (26). Such effects of PAHs exposure on plaque buildup in animals were found to be dose dependent (27). Pre-clinical studies have also suggested that PAHs might also exert their atherogenic effect via stimulation of an inflammatory process involving an increased influx of proinflammatory cells into these plaques (8). The role of inflammation as a risk factor for CVD development has been well established (28, 29). Population based studies supported an association between PAH and inflammation (9, 30). A recent study also suggested an association between PAHs and a number of obesity-related cardiometabolic health risk factors (31).
Several of the study limitations merit attention. Of main concern is the cross sectional nature of NHANES which does not allow to draw temporal or causal inferences regarding the association of PAHs and CVD. In addition, our study does not have the data to estimate the sources of exposure to PAHs. Urinary biomarker measurements reflect recent PAH exposure as non-smoking sources of PAHs can vary day-to-day in the general population. Finally, CVD was ascertained by self-report. Accordingly, some recall bias may exist. However, these biases are likely to be non-differential biases, which would minimize any observed association. Notwithstanding these limitations, the study findings are of interest because of the inclusion of a relatively large nationally representative multiethnic sample, the NHANES standardized data collection approaches, and the ability to adjust for potential confounders.
In conclusion, this epidemiological evidence from the current study tends to confirm what prior research found – namely, a positive association between PAH exposure and CVD. Any claim of atherogenic effects of PAH exposure is premature, but given increased prevalence of PAH exposure and CVD in the U.S. and elsewhere, there is a reason to study their linkages. More probing experimentation of a clinical translational character is needed, including research on potential mechanisms.
Supplementary Material
Highlights.
Pre-clinical studies have reported a positive association of PAHs with oxidative stress, inflammation and subsequent development of atherosclerosis, a major underlying risk factor for CVD.
The aim of the current study is to estimate the association of urinary PAH biomarkers and CVD in the US general population.
Structural Equation modelling approach was used to account for the interdependencies of the exposure measures as well as the response outcomes
Cardiovascular disease was positively associated with PAH biomarkers independent of tobacco smoke exposure.
Acknowledgments
The authors would like to thank Dr. James C. Anthony for his valuable suggestions. This work is completed during OA postdoctoral epidemiology fellowship, supported by the National Institute on Drug Abuse (T32DA021129) and Dr. James C. Anthony NIDA Senior Scientist Award (K05DA015799), and by Michigan State University. The content is the sole responsibility of the authors and does not necessarily represent the official views of Michigan State University, the National Institute on Drug Abuse, the National Institute for Occupational Safety and Health, or the Centers for Disease Control and Prevention. The authors declare no conflicts of interests.
Footnotes
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