Abstract
BACKGROUND:
Volatile organic compounds (VOCs) are associated with adverse respiratory outcomes at high occupational exposures. However, whether exposure levels found in the general population have similar effects is unknown.
METHODS:
We analyzed data on 1,342 adult participants in the 2011–2012 National Health and Nutrition Examination Survey aged ≥18 years old who had urinary VOC metabolites and spirometry measurements available. Linear regression models adjusting for covariates were fitted to estimate the associations of VOC exposures levels and spirometry outcomes, while accounting for survey design and sampling weights to generate nationally representative estimates.
RESULTS:
The urinary metabolites for xylene, acrylamide, acrolein, 1,3-butadiene, cyanide, toluene, 1-bromopropane, acrylonitrile, propylene oxide, styrene, ethylbenzene, and crotonaldehyde in our analysis were all detected in >75% of participants. Forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) ratio % was lower with urinary metabolites of acrylamide (β: −2.65, 95% CI: −4.32, −0.98), acrylonitrile (β: −1.02, 95% CI: −2.01, −0.03), and styrene (β: −3.13, 95% CI: −5.35, −0.90). FEV1 % predicted was lower with the urinary metabolites of acrolein (β: −7.77, 95% CI: −13.29, −2.25), acrylonitrile (β: −2.05, 95% CI: −3.77, −0.34), propylene oxide (β: −2.90, 95% CI: −5.50, −0.32), and styrene (β: −4.41, 95% CI: −6.97, −1.85).
CONCLUSIONS:
This is the first study of a representative sample of the U.S. adult population to reveal associations of acrylonitrile, propylene oxide, and styrene urinary metabolites with reduced lung function at non-occupational exposures. Results also support previous evidence of acrylamide and acrolein’s association with adverse respiratory outcomes.
Keywords: Volatile organic compounds, Urinary metabolites, Lung Function, Spirometry
INTRODUCTION
Volatile organic compounds (VOCs) are a wide variety of ubiquitous carbon-containing chemicals that readily evaporate at room temperature [1]. The main source of human exposure is indoor VOCs that emanate from commonly used household and industrial products such as paints, wood preservatives, floor or wall coverings, building materials, office equipment, aerosol sprays, personal care products, cleaning agents, insecticides and pesticides, solvents and synthetic rubber, resin, and polymers [2]. The levels of indoor VOCs increase with home cigarette smoking, the presence of garage attachment to homes, use of VOC-containing products, and reduced home ventilation [3]. Outdoor sources of VOC exposure include traffic and industrial emissions, oil and gas extractions, biomass burning, and background biogenic emissions [4]. Due to their widespread production and use, as well as their volatility, VOCs are ubiquitously present in the environment [2]. The main route of exposure to VOCs is inhalation, and experimental animal models suggest that some VOCs have pulmonary toxicity by causing irritation, inflammation, and oxidative stress, as well as by promoting immunoglobulin (Ig) E responsiveness that results from altered T cell activity and interaction with antigens [5].
Most studies on the respiratory effect of VOCs in ambient air and biological samples have been conducted in occupational settings with exposure levels of magnitude higher than levels experienced by the general population [2]. The few general population studies have mainly defined exposure based on indoor air VOC concentration to estimate personal exposure and have been limited in assessing internal dose [6–9]. The latter has been reported to be more appropriate for evaluating the health effects associated with human exposure to VOCs, since environmental exposure estimates vary with respiration rate, absorption, distribution, metabolism, and excretion of the chemicals [6–9]. Other studies have used blood VOC levels which have short half-lives of a few hours, and only a few studies have included urinary VOC metabolites which are less volatile and more stable than the parent compounds for examining potential respiratory outcomes [6–10]. Moreover, the association of several VOCs such as 1,3 butadiene, cyanide, 1-bromopropane, acrylonitrile, propylene oxide, or crotonaldehyde in urine or blood with lung function has not been previously investigated. Therefore, we aimed to examine the association of several VOCs urinary metabolites with lung function in a representative sample of the U.S. adult population.
METHODS
Data Source
We used data from participants in the 2011–2012 National Health and Nutrition Examination Survey (NHANES). This was the only NHANES cycle that included data on urinary VOC metabolites and spirometry. NHANES is a survey conducted by the National Center for health status of the American non-institutionalized civilian population [11]. It uses a complex multistage sampling design to generate a sample representative of the U.S. population. The protocols for NHANES were approved by the CDC and NCHS Institutional Review Boards (IRB), and informed consent was obtained from all participants (details on IRB at http://www.cdc.gov/nchs/nhanes/irba98.htm). This secondary data analysis was approved by a university IRB as not human subjects research.
Of the 1,783 adults aged ≥18 who participated in NHANES 2011–2012 and had VOC data, 1,487 also had spirometry data. After exclusion of participants with missing data on covariates including smoking (n=4), body mass index (BMI) (n=13), and household income (n=128), the final sample for analysis was 1,342 participants.
Urinary VOC Metabolites
Spot urine samples were collected from a sub-sample of NHANES participants, and were analyzed for VOC metabolites using ultra performance liquid chromatography coupled with electrospray tandem mass spectrometry. The VOC metabolites included in our analysis, their abbreviations, parent compounds, and limits of detection (LODs) are reported in Table 1. Samples with levels <LOD were imputed with LOD/√2. Details on CDC laboratory methods and quality control are published elsewhere [12]. Urinary samples were collected on the same day as spirometry was performed and within a three and a half hours interval, during physical examinations at mobile examination centers.
Table 1:
Distribution of crude and creatinine-standardized urinary VOC metabolites, NHANES 2011–2012 (N = 1,342)
| Urinary Metabolites | Abbreviations | Parent Compounds | LOD | % Detected | Crude GM (SE) μg/L) | Creatinine-Corrected GM (SE) (ng/mL) |
|---|---|---|---|---|---|---|
|
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| 2-Methylhippuric acid | 2MH | Xylene | 5.00 | 93.4 | 27.62 (1.95) | 30.64 (2.01) |
| 3-Methylhippuric acid & 4-Methylhippuric acid | 34M | Xylene | 8.00 | 99.9 | 178.68 (10.53) | 198.20 (9.53) |
|
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| N-Acetyl-S-(2-carbamoylethyl)-L-Cysteine | AAM | Acrylamide | 2.20 | 99.9 | 39.69 (1.83) | 44.03 (1.23) |
| N-Acetyl-S-(N-methylcarbamoyl)-L-Cysteine | AMC | Acrylamide | 6.26 | 99.9 | 126.46 (6.09) | 140.28 (5.33) |
|
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| N-Acetyl-S- (2-Carboxyethyl)-L-Cysteine | CEM | Acrolein | 6.96 | 98.9 | 75.65 (3.76) | 83.92 (2.60) |
| N-Acetyl-S- (3-Hydroxypropyl)-L-Cysteine | HPM | Acrolein | 13.00 | 100.0 | 180.84 (8.84) | 200.59 (5.81) |
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| N-Acetyl-S- (3,4-Dihydroxybutyl)-L-Cysteine | DHB | 1,3-Butadiene | 5.25 | 100.0 | 242.79 (10.86) | 269.32 (6.45) |
| N-Acetyl-S- (4-hydroxy-2-butenyl)-L-Cysteine | MB3 | 1,3-Butadiene | 0.60 | 96.3 | 4.18 (0.24) | 4.64 (0.20) |
|
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| 2-Aminothiazoline-4-carboxylic acid | ATC | Cyanide | 15.00 | 95.8 | 95.22 (6.23) | 105.62 (5.39) |
|
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| N-Acetyl-S-(benzyl)-L-Cysteine | BMA | Toluene | N.50 | 99.4 | 6.63 (0.36) | 7.36 (0.28) |
|
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| N-Acetyl-S-(n-propyl)-L-Cysteine | BPM | 1-Bromopropane | 1.20 | 78.5 | 4.81 (0.31) | 5.33 (0.28) |
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| N-Acetyl-S-(2-cyanoethyl)-L-Cysteine | CYM | Acrylonitrile | 0.50 | 86.1 | 1.82 (0.14) | 2.02 (0.12) |
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| N-Acetyl-S- (2-hydroxypropyl)-L-Cysteine | HP2 | Propylene oxide | 5.30 | 95.0 | 30.21 (1.58) | 33.51 (1.56) |
|
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| Mandelic acid | MAD | Styrene | 12.00 | 98.6 | 113.93 (7.09) | 126.38 (4.84) |
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| Phenylglyoxylic acid | PHG | Ethylbenzene, styrene | 12.00 | 99.0 | 162.65 (8.65) | 180.42 (7.26) |
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| N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-Cysteine | PMM | Crotonaldehyde | 1.13 | 100.0 | 201.80 (7.85) | 223.84 (8.88x) |
Abbreviations: LOD: level of detection; GM: geometric mean; SE: standard error; 2MH: 2-Methylhippuric acid; 34M: 3-Methylhippuric acid & 4-Methylhippuric acid; AAM: N-Acetyl-S-(2-carbamoylethyl)-L-Cysteine; AMC: N-Acetyl-S-(N-methylcarbamoyl)-L-Cysteine; CEM: N-Acetyl-S-(2-Carboxyethyl)-L-Cysteine; HPM: N-Acetyl-S- (3-Hydroxypropyl)-L-Cysteine; DHB: N-Acetyl-S- (3,4-Dihydroxybutyl)-L-Cysteine; MB3: N-Acetyl-S- (4-hydroxy-2-butenyl)-L-Cysteine; ATC: 2-Aminothiazoline-4-carboxylic acid; BMA: N-Acetyl-S-(benzyl)-L-Cysteine; BPM: N-Acetyl-S-(n-propyl)-L-Cysteine; CYM: N-Acetyl-S-(2-cyanoethyl)-L-Cysteine; HP2: N-Acetyl-S- (2-hydroxypropyl)-L-Cysteine; MAD: Mandelic acid; PHG: Phenylglyoxylic acid; PMM: N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-Cysteine
Spirometry
Spirometry was performed on participants by trained technicians following a pretest screening questionnaire to determine medical safety. Each participant underwent five to eight maneuvers considered acceptable and reproducible by American Thoracic Society (ATS) criteria [13]. Our analysis used pre-bronchodilator forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) ratio and FEV1 % predicted estimated using reference equation defined by Hankinson based on the U.S. population [14]. The FEV1/FVC ratio is used to define lung function impairment whereas FEV1 % predicted is used to quantify the severity of airflow obstruction [14].
Covariates
Data on participants’ age, sex, race/ethnicity, annual family income, and cigarette smoking was collected using standard questionnaires. Poverty income ratio (PIR), a ratio of family income to poverty, was estimated using guidelines and adjustment for family size, year and state. Smoking was categorized as: (1) “never smoker” (answer “No” to question, “Have you smoked at least 100 cigarettes in your life?”); (2) “current smokers” (answer “Yes” to question, “Do you now smoke cigarettes?”); and (3) “past smokers” (answer “Yes” to question, “Have you smoked at least 100 cigarettes in your life?” and answer “No” to the question, “Do you now smoke cigarettes?”). Pack-years of smoking was calculated as packs of cigarettes smoked per day multiplied by years smoked. Given the importance of smoking as a contributor to some VOCs, our analysis further included exposure to secondhand smoke (SHS) in homes, defined as living with a household member who smoked inside the home. BMI was calculated as weight (kilograms) divided by height (meters) squared and categorized as underweight (<18.5 kg/m2), normal (18.5 to 24.9 kg/m2), overweight (25.0 to 29.9 kg/m2), or obese (≥30.0 kg/m2) [15, 16].
Statistical Analysis
We performed descriptive analyses to examine the distribution of crude and creatinine-corrected levels of urinary VOC metabolites (calculated by dividing urinary metabolite concentrations by creatinine concentration to adjust for urinary concentration). We estimated P-values for the comparison in geometric means of creatinine-corrected urinary VOC metabolites by characteristics of study participants. We log10-transformed the crude and creatinine-corrected levels of urinary VOC metabolites due to their skewed distribution to improve normality and spread. We explored the intercorrelation between log10-transformed creatinine-corrected VOCs using spearman correlations. Linear regression was used to calculate the regression coefficient (β) and 95% confidence interval (CI) for the association of crude urinary VOC metabolites with FEV1/FVC % and FEV1 % predicted. The models were adjusted for age, PIR, BMI, height, and log-transformed pack-years of cigarette smoking used as continuous variables and sex, race/ethnicity, smoking status, and SHS exposure used as categorical variables. To correct for urine dilution in the regression analysis, urinary creatinine was included as a separate independent variable in the models, along with the crude VOC metabolites concentrations as recommended by Barr et al. [17]. This approach ensures that the associations of the exposures are independent of the effects of creatinine [17, 18]. Since smoking is an important source of VOCs, we performed sensitivity analyses, excluding smokers and participants with chronic obstructive pulmonary disease (COPD) defined as post-bronchodilator FEV1/FVC <0.70. To examine whether the association of VOC urinary metabolites with lower lung function differed with smoking status, asthma, obesity, sex, and race/ethnicity, we tested these variables for effect modification on a multiplicative scale by including interaction terms in the models. Subgroup analysis was subsequently performed on significant effect modifiers to identify at-risk groups for reduced lung function associated with VOC exposure. The analyses were performed in SAS (Version 9.4; SAS Institute, Cary, NC), accounting for the NHANES sampling weights and complex survey design to generate nationally representative estimates. P-values <0.05 were considered statistically significant in all analyses.
RESULTS
VOC Levels Overall and by Characteristics of Study Participants
Among the 1,342 participants included in our analysis, VOC metabolites were detected in >76% of urine samples; metabolites for xylene, acrylamide, acrolein, 1,3-butadiene, and crotonaldehyde were detected in ≥99.9% of urine samples (Table 1). The median age of participants was 40.7 years. About half were female (50.2%); 67.0% were non-Hispanic White, 11.5% were non-Hispanic Black, 7.3% were Mexican American, and the remaining 14.2% were of ‘Other’ race/ethnicity. Approximately 16.1% had the lowest PIR ≤1, 18.2% and 22.2% were past and current smokers respectively, 10.2% were exposed to SHS, and 33.2% and 33.0% had a BMI indicative of overweight or obese, respectively (Table 2).
Table 2:
Geometric means (GM [SE]) urinary creatinine-corrected VOCs by participants characteristics, NHANES 2011–2012 (N = 1,342)
| Characteristics | All (%) | 2MH + 34M | AAM + AMC | CEM + HPM | DHB + MB3 | ATC | BMA | BPM | CYM | HP2 | MAD | PHG | PMM |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
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| All participants | 100 | 300.46 (14.86) | 244.40 (8.34) | 382.75 (12.32) | 297.43 (7.61) | 110.39 (4.98) | 7.24 (0.25) | 5.05 (0.24) | 4.40 (0.36) | 38.35 (1.70) | 145.30 (5.81) | 200.63 (7.49) | 299.92 (10.47) |
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| Age groups | |||||||||||||
| 18 to 39 years | 42.6 | 259.49 (12.61) | 198.64 (10.69) | 321.37 (13.68) | 267.07 (8.40) | 97.76 (5.02) | 6.59 (0.30) | 5.01 (0.38) | 3.98 (0.57) | 34.61 (1.25) | 132.41 (5.13) | 174.12 (7.96) | 244.08 (9.96) |
| 40 to 59 years | 38.3 | 344.23 (30.44) | 286.55 (17.37) | 460.71 (25.11) | 312.06 (13.31) | 116.87 (8.83) | 7.18 (0.34) | 4.88 (0.47) | 6.04 (0.84) | 41.71 (2.33) | 160.39 (12.13) | 217.71 (15.09) | 365.38 (25.71) |
| ≥ 60 years | 19.1 | 317.15 (46.15) | 281.94 (9.78) | 398.69 (27.73) | 343.35 (11.24) | 129.06 (7.05) | 9.09 (0.76) | 5.50 (0.56) | 2.91 (0.58) | 40.75 (4.66) | 146.61 (8.24) | 233.53 (8.58) | 319.51 (24.35) |
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| Sex | |||||||||||||
| Males | 49.8 | 276.78 (18.97) | 218.25 (10.68) | 370.31 (17.00) | 286.00 (8.14) | 71.00 (4.74) | 6.03 (0.24) | 4.30 (0.28) | 4.44 (0.53) | 33.30 (1.85) | 137.83 (5.04) | 185.33 (8.79) | 276.39 (15.08) |
| Females | 50.2 | 325.91 (20.26) | 273.40 (13.44) | 395.48 (21.09) | 309.21 (10.69) | 170.92 (9.14) | 8.69 (0.43) | 5.92 (0.46) | 4.36 (0.60) | 44.12 (3.79) | 153.09 (8.96) | 217.04 (9.25) | 325.20 (15.98) |
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| Race/ethnicity | |||||||||||||
| Non-Hispanic White | 67.0 | 329.62 (15.13) | 281.86 (11.04) | 391.36 (17.13) | 314.55 (9.46) | 109.49 (5.74) | 7.06 (0.29) | 4.66 (0.31) | 4.60 (0.42) | 41.30 (2.12) | 149.55 (8.29) | 216.89 (7.61) | 323.85 (14.82) |
| Non-Hispanic Black | 11.5 | 224.23 (13.81) | 164.58 (6.75) | 341.20 (12.51) | 251.35 (6.85) | 94.78 (5.53) | 8.13 (0.40) | 3.86 (0.44) | 4.80 (0.47) | 28.11 (1.87) | 126.37 (5.47) | 165.71 (4.00) | 233.49 (9.29) |
| Mexican American | 7.3 | 230.65 (28.87) | 185.96 (18.54) | 345.53 (24.26) | 279.44 (23.51) | 121.98 (16.25) | 6.19 (0.78) | 8.29 (0.88) | 3.16 (0.67) | 39.96 (4.13) | 138.97 (9.05) | 160.01 (18.32) | 250.21 (29.35) |
| Other | 14.2 | 281.83 (27.98) | 197.65 (11.75) | 398.77 (24.75) | 270.31 (7.48) | 123.41 (10.33) | 8.09 (0.34) | 7.22 (0.79) | 3.91 (0.50) | 34.08 (1.73) | 145.29 (8.17) | 182.11 (9.90) | 280.68 (18.62) |
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| PIR | |||||||||||||
| ≤ 1 | 16.1 | 331.81 (59.98) | 253.57 (31.94) | 441.43(56.94) | 300.25 (18.04) | 115.13 (12.39) | 6.12 (0.33) | 4.46 (0.36) | 8.50 (2.08) | 38.04 (3.11) | 152.11 (12.09) | 204.83 (21.68) | 355.05 (53.08) |
| 1 to 3 | 34.9 | 302.68 (18.26) | 253.00 (13.54) | 394.42 (21.30) | 303.63 (8.23) | 113.76 (8.39) | 7.53 (0.56) | 4.89 (0.30) | 5.03 (0.80) | 38.48 (2.28) | 148.40 (7.42) | 201.53 (8.50) | 307.90 (19.80) |
| > 3 | 49.0 | 289.27 (21.16) | 235.57 (8.73) | 357.44 (16.67) | 292.19 (10.94) | 106.56 (5.83) | 7.45 (0.34) | 5.38 (0.34) | 3.21 (0.31) | 38.37 (2.63) | 140.98 (7.97) | 198.63 (10.04) | 278.43 (14.79) |
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| Smoker | |||||||||||||
| Never | 59.1 | 229.50 (13.96) | 179.95 (7.06) | 288.56 (8.93) | 266.50 (7.78) | 106.98 (5.47) | 7.32 (0.32) | 5.45 (0.30) | 1.85 (0.11) | 34.26 (1.89) | 124.91 (4.15) | 176.25 (8.07) | 212.41 (8.28) |
| Current | 18.2 | 894.84 (82.95) | 631.46 (35.72) | 1,145.28 (70.09) | 416.60 (18.07) | 133.49 (9.71) | 6.78 (0.30) | 4.00 (0.30) | 124.94 (14.00) | 68.55 (4.38) | 264.69 (15.44) | 316.72 (18.39) | 1,055.19 (59.94) |
| Past | 22.2 | 243.07 (17.73) | 246.45 (11.11) | 319.42 (13.15) | 299.26 (8.79) | 102.05 (9.12) | 7.47 (0.57) | 5.03 (0.55) | 2.55 (0.26) | 31.58 (3.35) | 130.42 (9.53) | 192.10 (7.68) | 257.68 (18.17) |
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| SHS | |||||||||||||
| No | 89.8 | 270.46 (15.49) | 223.25 (6.53) | 341.24 (8.40) | 286.09 (6.89) | 109.38 (4.97) | 7.30 (0.24) | 5.28 (0.25) | 3.14 (0.21) | 35.83 (1.48) | 136.35 (5.45) | 189.70 (6.93) | 262.90 (8.82) |
| Yes | 10.2 | 761.95 (102.98) | 544.37 (65.13) | 1,056.56 (150.61) | 419.60 (29.30) | 119.76 (0.11) | 6.77 (0.53) | 3.42 (0.39) | 87.50 (20.43) | 69.54 (10.95) | 254.90 (21.53) | 329.31 (31.89) | 961.68 (151.21) |
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| BMI | |||||||||||||
| Normal | 31.6 | 336.51 (26.54) | 256.56 (20.44) | 405.77 (36.28) | 305.69 (13.10) | 122.16 (9.14) | 7.79 (0.57) | 6.11 (0.53) | 4.97 (0.96) | 43.44 (3.21) | 155.12 (11.36) | 210.73 (15.39) | 340.66 (35.12) |
| Underweight | 2.0 | 331.75 (86.15) | 378.50 (94.47) | 494.04 (133.84) | 351.07 (28.69) | 179.16 (36.53) | 6.87 (1.74) | 3.36 (0.74) | 14.75 (11.74) | 41.74 (9.32) | 164.11 (15.07) | 231.97 (26.41) | 523.62 (161.30) |
| Overweight | 33.2 | 285.39 (23.82) | 228.11 (8.31) | 364.64 (11.25) | 290.44 (11.86) | 106.14 (8.36) | 7.15 (0.41) | 4.69 (0.29) | 3.72 (0.44) | 38.27 (2.50) | 147.63 (6.36) | 199.70 (6.27) | 286.43 (9.24) |
| Obese | 33.0 | 282.27 (22.15) | 243.58 (13.93) | 374.27 (16.01) | 293.83 (10.30) | 101.22 (5.76) | 6.87 (0.28) | 4.63 (0.37) | 4.31 (0.68) | 33.94 (2.32) | 133.31 (8.30) | 190.62 (11.32) | 268.85 (13.79) |
Abbreviations: 2MH: 2-Methylhippuric acid; 34M: 3-Methylhippuric acid & 4-Methylhippuric acid; AAM: N-Acetyl-S-(2-carbamoylethyl)-L-Cysteine; AMC: N-Acetyl-S-(N-methylcarbamoyl)-L-Cysteine; CEM: N-Acetyl-S- (2-Carboxyethyl)-L-Cysteine; HPM: N-Acetyl-S- (3-Hydroxypropyl)-L-Cysteine; DHB: N-AcetylS- (3,4-Dihydroxybutyl)-L-Cysteine; MB3: N-Acetyl-S- (4-hydroxy-2-butenyl)-L-Cysteine; ATC: 2-Aminothiazoline-4-carboxylic acid; BMA: N-Acetyl-S-(benzyl)-L-Cysteine; BPM: N-Acetyl-S-(n-propyl)-L-Cysteine; CYM: N-Acetyl-S-(2-cyanoethyl)-L-Cysteine; HP2: N-Acetyl-S- (2-hydroxypropyl)-L-Cysteine; MAD: Mandelic acid; PHG: Phenylglyoxylic acid; PMM: N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-Cysteine. PIR: poverty-income ratio; SHS: secondhand smoke; BMI: body mass index. Bold font indicates significant difference in urinary VOC metabolites by study participants’ characteristics
The levels (GM) of creatinine-corrected VOC urinary metabolites, in decreasing order, were N-Acetyl-S- (2-Carboxyethyl)-L-Cysteine (CEM) + N-Acetyl-S-(3-Hydroxypropyl)-L-Cysteine (HPM) (acrolein metabolites), 2-Methylhippuric acid (2MH) + 3-Methylhippuric acid & 4-Methylhippuric acid (34M) (xylene metabolites), N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-Cysteine (PMM) (crotonaldehyde metabolite), and N-Acetyl-S-(3,4-Dihydroxybutyl)-L-Cysteine (DHB) + N-Acetyl-S- (4-hydroxy-2-butenyl)-L-Cysteine (MB3) (butadiene metabolites). These were followed by N-Acetyl-S-(2-carbamoylethyl)-L-Cysteine (AAM) + N-Acetyl-S-(N-methylcarbamoyl)-L-Cysteine (AMC) (acrylamide metabolites), Phenylglyoxylic acid (PHG) (ethylbenzene and styrene metabolites), and mandelic acid (MAD) (styrene metabolite). The remaining VOC metabolites were 2-Aminothiazoline-4-carboxylic acid (ATC) (cyanide metabolite), N-Acetyl-S- (2-hydroxypropyl)-L-Cysteine (HP2) (propylene oxide metabolite), N-Acetyl-S-(benzyl)-L-Cysteine (BMA) (toluene metabolite), N-Acetyl-S-(n-propyl)-L-Cysteine (BPM) (1-bromopropane metabolite), and N-Acetyl-S-(2-cyanoethyl)-L-Cysteine (CYM) (acrylonitrile metabolite) (Table 2).
The description of the levels of creatinine-corrected urinary VOC metabolites by participants’ characteristics are reported in supplementary materials. Notably, creatinine-corrected levels of metabolites for xylene, acrylamide, acrolein, 1,3-butadiene, acrylonitrile, propylene oxide, styrene, ethylbenzene or styrene, and crotonaldehyde were higher in current smokers than past smokers or non-smokers, as well as in those exposed to SHS than those unexposed. Creatinine-corrected levels of metabolites of cyanide were higher in current smokers than past smokers or non-smokers, while levels of 1-bromopropane metabolites were lower in those exposed to SHS (Table 2).
Intercorrelation of Urinary VOC Metabolites
There were strong positive correlations between urinary creatinine-corrected levels of the acrolein metabolite with crotonaldehyde (r: 0.60), 1-bromopropane (r: 0.50), and butadiene metabolites (r: 0.52), and between crotonaldehyde and styrene metabolites (r: 0.53). The remaining correlations were moderate, weak, or non-significant (Figure 1).
Figure 1:
Heatmap for intercorrelation between urinary creatinine-corrected VOC metabolites
Urinary VOC Metabolites and Reduced Lung Function
In analysis adjusted for covariates, FEV1/FVC % was lower with the urinary metabolites of acrylamide (β: −2.65, 95% CI: −4.32, −0.98), acrylonitrile (β: −1.02, 95% CI: −2.01, −0.03), and styrene (β: −3.13, 95% CI: −5.35, −0.90) (Figure 2). FEV1 % predicted was lower with the urinary metabolites of acrolein (β: −7.77, 95% CI: −13.29, −2.25), acrylonitrile (β: −2.05, 95% CI: −3.77, −0.34), propylene oxide (β: −2.90, 95% CI: −5.50, −0.32), and styrene (β: −4.41, 95% CI: −6.97, −1.85) (Figure 3).
Figure 2:
Restricted cubic splines for the associations of urinary VOC metabolites with FEV1/FVC %.
Models adjusted for age, PIR, BMI, height, log-transformed pack-years of cigarette smoking, and urinary creatinine used as continuous variables and sex, race/ethnicity, past and current smoking status, and SHS exposure. Bold red font indicates significant difference in urinary VOC metabolites with FEV1/FVC %.; * = P < 0.05, ** = P < 0.01
Figure 3:
Restricted cubic splines for the associations of urinary VOC metabolites with FEV1 % predicted.
Models adjusted for age, PIR, BMI, height, log-transformed pack-years of cigarette smoking, and urinary creatinine used as continuous variables and sex, race/ethnicity, past and current smoking status, and SHS exposure. Bold red font indicates significant difference in urinary VOC metabolites with FEV1 % predicted. * = P < 0.05, ** = P < 0.01.
In a sensitivity analysis, the association of urinary acrylamide metabolites with FEV1/FVC % persisted after exclusion of smokers or participants with COPD and the association of urinary acrylonitrile and styrene metabolites with FEV1/FVC % persisted after excluding participants with COPD. The association of urinary acrolein, propylene oxide, and styrene metabolites with FEV1 % predicted persisted after exclusion of smokers or participants with COPD. The association of urinary acrylonitrile metabolite with FEV1/FVC % only persisted after exclusion of participants with COPD.
In effect modification testing, the association of urinary VOC metabolites with spirometry values did not differ significantly by asthma status, smoking, body mass, or sex. The associations of urinary metabolites for acrylamide (Pinteraction=0.004), acrolein (Pinteraction=0.006), and styrene (Pinteraction=0.004) with FEV1/FVC differed with race/ethnicity (Supplemental Table 1). In subgroup analysis, lower FEV1/FVC were found in non-Hispanic White participants in relation to urinary metabolites for acrylamide (β: −3.96, 95% CI: −6.29, −1.64) and styrene (β: −5.02, 95% CI: −7.52, −2.52). Despite significant effect modification by race/ethnicity, acrolein urinary metabolite was not associated with FEV1/FVC in any racial/ethnic subgroup (Supplemental Table 2).
DISCUSSION
This analysis of a U.S. representative sample identified urinary VOC metabolites of acrylamide, acrolein, acrylonitrile, propylene oxide, and styrene as associated with reduced lung function in adults. It is the first study, to our knowledge, to suggest an association of urinary VOC metabolites with adverse respiratory outcomes in a general population study.
Acrylamide
Acrylamide is a conjugated reactive molecule used in the synthesis of polyacrylamide polymers to make chemicals for water purification, sewage treatment, and to manufacture paper, cosmetic products, plastics, glue, or soap; it is also a component of tobacco smoke [19]. Acrylamide became of accrued interest when it was found to be generated during the heating at temperatures ≥120°C of foods, such as starchy foods (e.g., potatoes, grains), making human exposure to this chemical nearly universal [20]. Acrylamide exposure in the general population occurs through food and contaminated water ingestion and from tobacco smoke; whereas inhalation and dermal contact are the main exposure routes in occupational settings [19].
General population studies on acrylamide exposure and respiratory outcomes are very scarce and only one included lung function measurements. In that study conducted among 3,271 Chinese adults, urinary acrylamide metabolites, including AAM measured in spot urine, were associated with lower FEV1 and FVC volumes [21]. Furthermore, C-reactive protein mediated these associations, suggesting that systemic inflammation might be a potential mechanism [21]. There is evidence that acrylamide may affect the respiratory system even when exposure occurs through routes other than inhalation [22, 23]. Oral administration of food containing 157 mg acrylamide/day for four weeks to 14 adults also led to leukocyte activation and production of reactive oxygen species due to glutathione reduction, causing oxidative stress and systemic inflammation [24]. Both mechanisms are well-known to be associated with impaired lung function [25]. In a study of 8-week old Swiss male mice, oral administration of 26 μg of acrylamide induced alterations of lung microstructure accompanied by lung inflammation, bronchiolar epithelium hypertrophy, and alveolar epithelium hyperplasia [22]. Moreover, oral acrylamide has been shown to worsen allergic asthma and asthma severity and control in BALB/c mice [23]. Acrylamide is also an airway irritant that can directly damage respiratory epithelium when inhaled [26].
Acrolein
Acrolein is a colorless reactive aldehyde with a pungent odor used in the manufacturing of several organic chemicals such as biocides [27]. It is also formed from the combustion of organic products such as gasoline, diesel fuel, wood, plastics, and tobacco as well as from carbohydrates, vegetable oils, animal fats, and amino acids during heating of foods [27]. Small amounts of acrolein are produced endogenously from lipid peroxidation [27]. Exposure of the general population to acrolein occurs through inhalation, tobacco smoke, and food ingestion [28].
Despite the widespread exposure to acrolein through inhalation, research on the chemical and respiratory outcomes is limited and no study has investigated its association with reduced lung function using biomarkers of exposure. A French study on air pollution conducted in 4,643 school-aged children found that acrolein measured in classroom air was associated with higher asthma prevalence, after adjusting for age, sex, SHS, and parental asthma and allergy [29]. In the U.S., outdoor acrolein exposure estimated from the 2005 National-Scale Air Toxics Assessment was found to be associated with a marginal increase in asthma attacks among adult participants of the National Health Interview Survey from 2000 to 2009 [30]. The mechanisms through which acrolein may impair lung function are multiple. Acrolein is highly irritating and has been shown to cause respiratory epithelium injuries in rats after acute exposure to ≥1.5 mg/m3 acrolein and after acute exposure to 0.35 or 0.69 mg/m3 acrolein, human volunteers experienced nasal irritation and lower respiratory rate, a reflex response to protect the lungs [31, 32]. Acrolein may trigger antigenic-type bronchial hyperreactivity with increased lipid mediators of bronchoconstriction and delayed influx of neutrophils [31]. Moreover, acrolein can lead to mucus hyperproduction either by acting on lung epithelial cells or through inflammation; due to its solubility and reactivity with lung tissues, the chemical can also alter the integrity alveolo-capillary membrane [31, 33].
Acrylonitrile
Acrylonitrile is used as a chemical intermediate in the manufacturing of acrylic fibers in home goods and furnishings, resins, plastics, rubbers, and other products such as acrylamide; it is sometimes combined with styrene and butadiene to form acrylonitrile–styrene–butadiene (ABS) resins [34]. Besides occupational exposure to the chemical, concerns to the general public have been raised with exposure from smoking, food packaging, and when using products made with acrylonitrile polymers [34]. Acrylonitrile is conjugated with glutathione and oxidation by cytochrome P450 to form epoxide 2 cyanoethylene oxide. Consistent with our findings, acrylonitrile is a known irritant to airways and mucous membranes [35]. It depletes glutathione, causing oxidative stress, a factor associated with impaired lung function [36]. Another potential effect could be endocrine disruption; acrylonitrile is reportedly associated with reduced blood testosterone concentrations among workers exposed to the chemical [37]. This effect may be mediated by oxidative stress which activates nuclear factor κB signaling pathway, to modulate the expression of the Bax apoptotic protein and contribute to testicular apoptosis [38]. All these mechanisms (irritation, oxidative stress, inflammation, and endocrine disruption) are well-known to impair lung function [25]. However, there have not been previous studies on biomarkers of acrylonitrile exposure and respiratory outcomes in the general population. Our results on the association of the urinary acrylonitrile metabolite should be interpreted with caution, since they may also be a proxy for acrylamide exposure, which we found to be associated with impaired lung function in this analysis.
Styrene
Styrene is a derivative of benzene used to make plastic and resins to which the general population is exposed through ingestion of contaminated food, tobacco smoke, and inhalation of emissions from combustion of styrene polymers and traffic [39, 40]. It has been reported to irritate skin and mucous membranes, and has been linked in occupational settings with respiratory symptoms that subside when exposure is eliminated [41]. A recent systematic review on nonmalignant respiratory morbidity in workers from industries using styrene found that 13 of the 15 included studies reported an association between styrene exposure and asthma or obliterative bronchiolitis [42]. Among fiberglass reinforcement industry workers’ exposure to high styrene levels, the chemical was associated with higher prevalence of cough, phlegm, wheezing, and breathlessness as well as reduced lung function [41]. Yet, the evidence of an association in general populations is limited to one study, and no study has investigated the association of styrene with lung function [43]. The Leipzig Allergy High-Risk Children Study (LARS) observed that styrene assessed in infants’ bedrooms with passive sampling for four weeks after birth was associated with higher risk of respiratory infections at six weeks, but not with wheezing [43]. Mechanistically, exposure to styrene can cause irritation, and can trigger interferon γ production and promote allergic sensitization by increasing antigen-presenting activity leading to IgE production, eosinophilic inflammation, and airway hyperreactivity [43].
Propylene Oxide
Propylene oxide is used as a solvent and as a chemical for the synthesis of polyurethane and propylene glycol; it is also used in food additives, herbicides, and insecticides [44]. Due to its extensive use, the general population is exposed via inhalation, ingestion, and dermal absorption [44]. The chemical has been described as an irritant, causing nasal irritation and difficulty breathing after acute inhalation exposure [45]. In long-term inhalation studies conducted in Fischer 344 rats and B6C3F1 mice, propylene oxide was observed to cause increases in the incidences of inflammatory lesions, hyperplastic changes, and to increase the risk of nasal tumors at high exposures [46]. In rodent models, propylene oxide conjugates with glutathione, causing its depletion in the lungs and subsequent oxidative stress [47]. Although the propylene oxide metabolite in urine was detected in 95% of our study participants and inhalation is a route of exposure, we found no previous epidemiological study on its respiratory effects in humans.
Limitations and Strengths
The present study has some limitations. Due to the cross-sectional design of NHANES, the temporality between the exposures and lung function could not be established. Urinary VOC metabolites were only measured in a single spot urine sample. Though data on urinary VOC metabolites are available for analysis in more recent NHANES cycles, spirometry was not performed past the NHANES 2011–2012 cycle. CYM, used as the urinary metabolite for acrylonitrile, may not be specific to the chemical and may also be a proxy for acrylamide exposure as well. Nevertheless, our study has major strengths. It includes a large sample representative of the U.S. population, which increases the generalizability of the findings on the national scale. Urinary VOC metabolites have a half-life of days; they capture both indoor and outdoor VOC exposures and are a better measure of internal dose than environmental exposure assessment and blood VOCs that have short half-lives of only hours [6–10]. Urinary VOC metabolite analyses were performed by the CDC laboratories with rigorous quality control and quality assurance procedures and our analysis extensively adjusted for covariates, which minimized residual confounding. Importantly, our analysis is the first to examine the association of several urinary metabolites for VOCs such as 1,3 butadiene, cyanide, 1-bromopropane, acrylonitrile, propylene oxide, or crotonaldehyde with lung function reduction in a general population.
Conclusions
This cross-sectional analysis of a sample representative of the U.S. adult population found that urinary VOC metabolites of acrylamide, acrolein, acrylonitrile, propylene oxide, and styrene are associated with reduced lung function measured using spirometry. Future research should include prospective studies with repeated exposure measures to confirm these associations and to examine their underlying mechanisms. Studies should also examine whether reducing exposure to VOCs can help prevent the VOC-associated adverse respiratory effects found in this study.
Supplementary Material
Table 3:
Sensitivity analysis for associations of urinary VOC metabolites with FEV1/FVC % and FEV1 % predicted, NHANES 2011–2012
| Urinary Metabolites | Parent Compounds | After excluding smokers | After excluding participants with COPD | ||
|---|---|---|---|---|---|
|
|
|
||||
| FEV1/FVC | FEV1 % predicted | FEV1/FVC | FEV1 % predicted | ||
|
| |||||
| 2MH + 34M | Xylene | −0.21 (−2.25, 1.82) | −1.20 (−3.63, 1.23) | −0.76 (−2.28, 0.75) | −1.82 (−4.29, 0.65) |
|
| |||||
| AAM + AMC | Acrylamide | −2.42 (−3.78, −1.07) ** | −1.85 (−6.45, 2.74) | −2.62 (−4.38, −0.85) ** | −2.96 (−6.36, 0.44) |
|
| |||||
| CEM + HPM | Acrolein | −0.50 (−2.57, 1.56) | −7.34 (−13.41, −1.27) * | −1.52 (−3.08, 0.03) | −7.74 (−12.76, −2.72) ** |
|
| |||||
| DHB + MB3 | 1,3−Butadiene | −0.24 (−2.40, 1.91) | −2.92 (−7.58, 1.74) | −1.27 (−3.28, 0.75) | −5.37 (−10.37, −0.36) * |
|
| |||||
| ATC | Cyanide | 0.20 (−1.17, 1.58) | −1.32 (−5.01, 2.36) | −0.42 (−1.62, 0.78) | −2.49 (−6.44, 1.47) |
|
| |||||
| BMA | Toluene | −0.31 (−1.46, 0.85) | 0.85 (−1.51, 3.20) | −0.99 (−2.06, 0.08) | −2.16 (−5.27, 0.94) |
|
| |||||
| BPM | 1−Bromopropane | −0.62 (−1.2, −0.03) * | −0.88 (−3.32, 1.59) | −0.46 (−1.17, 0.25) | −0.37 (−2.39, 1.66) |
|
| |||||
| CYM | Acrylonitrile | −0.78 (−2.54, 0.97) | −2.18 (−4.92, 0.57) | −1.05 (−2.06, −0.03) * | −2.42 (−4.17, −0.68) ** |
|
| |||||
| HP2 | Propylene oxide | −0.48 (−1.81, 0.85) | −2.26 (−4.36, −0.16) * | −0.70 (−2.07, 0.68) | −2.56 (−4.94, −0.17) * |
|
| |||||
| MAD | Styrene | −2.45 (−5.23, 0.34) | −3.76 (−6.90, −0.62) * | −3.17 (−5.48, 0.86) * | −4.50 (−7.23, −1.76) ** |
|
| |||||
| PHG | Ethylbenzene, styrene | −0.37 (−2.67, 1.93) | 0.84 (−4.44, 6.11) | −0.56 (−3.43, 2.31) | 1.02 (−4.38, 6.42) |
|
| |||||
| PMM | Crotonaldehyde | −0.31 (−2.73, 2.12) | −1.25 (−5.00, 2.50) | −0.97 (−2.43, 0.50) | −2.51 (−6.24, 1.22) |
P < 0.05
P < 0.01
Models adjusted for age, PIR, BMI, height, and urinary creatinine used as continuous variables and sex, race/ethnicity, and SHS exposure. In sensitivity analysis among participants without COPD, we additionally adjusted for past and current smoking status and log-transformed pack-years of cigarette smoking.
Bold font indicates urinary VOC metabolites associated with FEV1/FVC % and FEV1 % predicted
HIGHLIGHTS.
In a sample representative of U.S. adults, urinary metabolites of acrylamide, acrylonitrile, and styrene were associated with lower FEV1/FVC ratio.
Urinary metabolites of acrolein, acrylonitrile, propylene oxide, and styrene were associated with lower FEV1 % predicted.
In sensitivity analysis, most associations of urinary volatile organic compounds metabolites with lower lung function persisted after excluding smokers and participants with COPD.
Funding:
Angelico Mendy’s contribution was partly funded by grant P30 ES006096 from the U.S. NIH. Dr. Merianos’ work was partly funded by grant R21ES032161 and K01DA044313, Dr. Mahabee-Gittens’s work was partly funded by R01ES03743 and R01ES027815, and Dr. Mersha’s work was partially funded by R01HL132344 and R01HG011411.
Footnotes
Disclosures: The authors have no disclosure related to the submitted manuscript.
Conflict of Interest
The authors have no conflict of interest to disclose
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