Associations of urinary polycyclic aromatic

0 downloads 0 Views 912KB Size Report
Al-Daghri, N.M., Alokail, M.S., Abd-Alrahman, S.H., Draz, H.M., Yakout, S.M., Clerici, M.,. 2013. Polycyclic aromatic hydrocarbon exposure and pediatric asthma ...

Science of the Total Environment 618 (2018) 542–550

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Associations of urinary polycyclic aromatic hydrocarbon metabolites with fractional exhaled nitric oxide and exhaled carbon monoxide: A cross-sectional study Yun Zhou a,b, Yuewei Liu c, Huizhen Sun a,b, Jixuan Ma a,b, Lili Xiao a,b, Limin Cao a,b, Wei Li a,b, Bin Wang a,b, Jing Yuan a,b,⁎, Weihong Chen a,b,⁎ a

Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China c Hubei Provincial Key Laboratory for Applied Toxicology, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei 430079, China b

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Estimating associations of urinary PAH metabolites (OH-PAHs) with FeNO and eCO levels • Urinary PAH metabolites were significantly associated with levels of eCO and FeNO. • Associations of urinary PAH metabolites and eCO were stronger in smokers than that in non-smokers. • PAH metabolites were associated with FeNO decline in smokers, while FeNO increase in non-smokers.

a r t i c l e

i n f o

Article history: Received 11 July 2017 Received in revised form 26 October 2017 Accepted 28 October 2017 Available online xxxx Editor: Yolanda Picó Keywords: Urinary monohydroxyl metabolites PAHs Biomarkers of exposure FeNO eCO Tobacco smoking

a b s t r a c t Exposure to Polycyclic aromatic hydrocarbons (PAHs) has been associated with inflammatory responses. Fractional exhaled nitric oxide (FeNO) and exhaled carbon monoxide (eCO) are both important inflammatory mediators especially in airways. However, few studies have investigated associations of PAH exposures with FeNO or eCO. Therefore, we aimed to quantify the associations of urinary PAH metabolites with FeNO and eCO levels, and investigate their potential effect modifiers by linear mixed models among 4133 participants from the Wuhan-Zhuhai cohort in China. We further performed stratified analyses to estimate effect modification. We found significant associations of increased urinary PAH metabolites with elevated eCO and FeNO. Among all participants, each 1% increase of 1-hydroxynaphthalene, 2-hydroxynaphthalene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 3hydroxyphenanthrene, and total PAH metabolites was significantly associated with a 12.6% (95% confidence interval: 9.3%, 15.9%), 9.7% (6.5%, 12.9%), 7.5% (4.1%, 10.9%), 3.2% (0.2%, 6.2%), 2.7% (0.1%, 5.3%), and 6.5% (2.7%, 10.4%) increased eCO level, respectively; while each 1% increase of urinary 1-hydroxynaphthalene, 9hydroxyphenanthrene, 3-hydroxyphenanthrene, and 2-hydroxyphenanthrene was associated with a − 3.0% (−5.8%, −0.2%), 2.9% (0.3%, 5.6%), 3.2% (1.0%, 5.4%), and 4.5% (2.2%, 6.9%) change of FeNO level, respectively. Positive associations between certain urinary PAH metabolites and eCO were observed among both ever-smokers and non-smokers, and the associations were stronger among ever-smokers than that among non-smokers. Increased

⁎ Corresponding authors at: Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China. E-mail addresses: [email protected], [email protected] (W. Chen).

https://doi.org/10.1016/j.scitotenv.2017.10.294 0048-9697/© 2017 Elsevier B.V. All rights reserved.

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

543

urinary PAH metabolites were associated with decreased FeNO among ever-smokers and elevated FeNO levels among non-smokers. Our findings suggest that PAH exposures may impair airway through inducing inflammatory response, especially among ever-smokers. © 2017 Elsevier B.V. All rights reserved.

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are considered as one kind of the most widespread organic environmental pollutants. The US Environmental Protection Agency (EPA) has classified seven PAH compounds as probable human carcinogens, including benz[a]anthracene, benzo[a]pyrene, benzo[b]fluoranthene, benzo[k]fluoranthene, chrysene, dibenz(a,h)anthracene, and indeno(1,2,3-cd)pyrene (U.S. EPA, 1993; ATSDR, 2011). Exposure to PAHs is associated with increased risk of malignant tumors in skin, lung, bladder, liver, and stomach (Mastrangelo et al., 1996; Boffetta et al., 1997; Liao et al., 2014; White et al., 2016). Recent studies reported that inhalation or dietary intake of PAHs can impair respiratory system, leading to lung function decline and respiratory diseases (i.e. COPD and asthma) (Burstyn et al., 2003; Al-Daghri et al., 2013; Zhou et al., 2016b). However, the mechanism for PAHs causing respiratory damages is unclear. Oxidative stress and inflammatory response have been implicated in the pathogenesis of lung diseases (MacNee, 2001; Gerritsen et al., 2005). Although certain classical markers of oxidative stress and inflammation such as reactive oxygen species (ROS) and Creactive protein (CRP) are increased after exposure to PAHs (Park et al., 2008; Farzan et al., 2016), they mainly reflect the levels of systemic inflammation and are nonspecific to lung or airway injury. Endogenous nitric oxide (NO) is an important inflammatory mediator. Accumulated experimental evidence suggest that inflammation can induce inducible nitric oxide synthase (iNOS), which are expressed in resident and inflammatory cells and activated by inflammatory cytokines (Tatsumi et al., 2000; Kwon et al., 2001). iNOS can produce NO and lead to elevated NO level in exhaled breath (Fractional exhaled nitric oxide, FeNO). Therefore, FeNO originates in the airway epithelium, and acts as an important marker of airway inflammation (Martini et al., 2012; Haccuria et al., 2014). Similar to NO, CO is another important biological mediator reflecting the inflammation Exhaled CO (eCO) from humans is recently related with endogenous levels of CO, which is induced by inducible heme oxygenase (HO-1), and increased after oxidant injuries and inflammation (Choi and Alam, 1996; Slebos et al., 2003; Barnes et al., 2006). Both FeNO and eCO are also important biological inflammatory mediators, and can be used as specific and easy-to-measure clinical markers of some respiratory system diseases (Zayasu et al., 1997; Van Muylem et al., 2007; Zhang et al., 2013). The levels of eCO and FeNO can be affected by air pollutants such as cigarette smoke, cooking fuel or traffic exhaust, which are important sources of PAHs (McSharry et al., 2005; Sundy et al., 2007; Alshaarawy et al., 2013; Zhang et al., 2013; Berhane et al., 2014; Obaseki et al., 2014). However, the association of PAH exposures with eCO or FeNO is still unclear. In the present study, we used urinary monohydroxyl metabolites of naphthalene, fluorene, phenanthrene, and pyrene to assess human exposures to PAHs from all sources. We also measured the levels of eCO and FeNO for 4133 adults from the Wuhan-Zhuhai Cohort in China. Our aim was to investigate the associations of urinary PAH metabolites with eCO and FeNO among adult residents in Wuhan and Zhuhai, China, as well as their potential effect modifiers. 2. Materials and methods 2.1. Study population This cross-section study is a sub-study of a community-based and prospective cohort, the Wuhan-Zhuhai cohort study, which has been

described elsewhere (Song et al., 2014). In brief, the study was established between 2011 and 2012, and enrolled 4812 participants aged 18 to 81 who lived in Wuhan (N = 3053) or Zhuhai City (N = 1759) for more than five years. All the residents were informed by community committees and invited for examinations voluntarily. Residents who had severe illnesses or unable to attend clinic visits were excluded from the study. A face-to-face interview was conducted for each participant by trained investigators. Health and lifestyle questionnaires covered information on demographic characteristics, occupational hazards exposure, smoking history, passive smoking history, alcohol consumption, regular physical activity, cooking and disease history. Smoking amount (pack-years) for each smoker was calculated as packs of cigarettes per day multiplied by years of smoking. Passive smoking amount was calculated as hours of cigarettes per week multiplied by years of passive smoking. With exclusion of 679 participants who failed to complete collection of urine, or measurements for eCO or FeNO, there were 4133 participants enrolled in the final analysis. All participants in this study have given written informed consent for participation. The research protocol was approved by the Ethics and Human Subject Committee of Tongji Medical College, Huazhong University of Science and Technology. 2.2. Urinary PAH metabolite and urinary Creatinine determination We extracted 3 ml of the urine sample to measure the concentrations of twelve PAH metabolites, including 1-hydroxynaphthalene (1-OHNa), 2-hydroxynaphthalene (2-OHNa), 2-hydroxyfluorene (2-OHFlu), 9hydroxyfluorene (9-OHFlu), 1-hydroxyphenanthrene (1-OHPh), 2hydroxyphenanthrene (2-OHPh), 3-hydroxyphenanthrene (3-OHPh), 4-hydroxyphenanthrene (4-OHPh), 9-hydroxyphenanthrene (9OHPh), 1-hydroxypyrene (1-OHP), 6-hydroxychrysene (6-OHChr), and 3-hydroxybenzo[a]pyrene (3-OHBaP). The samples were buffered with sodium acetate (0.5 M, pH 5.0), spiked with diluted internal standards. Deuterated1-hydroxypyrene, deuterated 1-hydroxynaphthalene (Toronto Research Chemicals, Toronto, Canada and C/D/N isotopes Inc. Beijing, China, respectively), and hydrolyzed enzymatically by βGlucuronidase with sulphatase activity (Sigma-Aldrich, Milan, Italy) at 37 °C overnight. After hydrolysis, samples were extracted by n-hexane, and the extracts were evaporated under a gentle stream of nitrogen (N-EVAP 112, Organomation Associates Inc., MA, USA). BSTFA [N,O-Bis (trimethylsilyl) trifluoroacetammide with 1% trimethylchlorosilane, Regis Technologies, Inc. Morton Grove] was added to the residue and the mixture was incubated at 90 °C for 45 min. After derivatization, 1 μl of each sample was injected on the gas chromatography–mass spectrometry (Agilent 5975B/6890 N GC/MS System, Santa Clara, CA, USA). The identification and quantification of urinary PAH metabolites were based on the retention time, mass-to-charge ratio, and peak area using a linear regression curve obtained from separate internal standard solutions (Campo et al., 2008; Li et al., 2012). For quality control, we fitted a standard curve for each 100 samples and calculated R square (R2 N 0.996). Reproducibility was also assessed with repeated measurements from 10% samples with coefficient of variation below 10%. The recoveries of 12 OH-PAHs were in the range of 54–92%. The concentrations of both 6-OHCHR and 3-OHBAP in urine were below the limits of detection (LOD), and we therefore did not include the two urinary PAH metabolites in the final analysis. The LOD for the urinary PAH metabolites ranged from 0.1 to 0.9 μg/l, and the concentrations of those samples below the LOD were replaced by 50% of the LOD value. We measured the levels of

544

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

urinary creatinine by using a fully automated clinical chemistry analyzer (BS-200, Shenzhen Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, China), calibrated and calculated urinary PAH metabolite concentrations as μg/mmol creatinine (Cr). 2.3. Determinations of eCO and FeNO eCO was tested by using a hand-held battery operated meter (MicroCO meter, CareFusion, Kent, UK). Each participant was advised to inspire fully and hold their breath for 20 s before exhaling slowly in resting state. The unit was turned off and the mouthpiece and adapter removed for at least 1 min to allow re-equilibration with ambient air and to dry the surface of the sensor before repeating a measurement. Three readings were obtained from each participant and averaged for analysis. FeNO was measured by a Nano Coulomb Nitric Oxide Analyzer (SV-02E, Sunvou Medical Electronics CO., Ltd., Wuxi, China). Each participant was advised not to eat food for at least 2 h before the test. Two plateau values were obtained, recorded in accordance with the American Thoracic Society/European Respiratory Society recommendations (Society and Society, 2005). The range of CO analyzer is 0– 100 ppm with 1 ppm resolution; while FeNO analyzer is 1–500 ppb with a resolution of 0.1 ppb. 2.4. Statistical analysis Urinary PAH metabolites, eCO and FeNO concentrations were all logtransformed due to their right-skewed distributions. Demographic characteristics of the participants were assessed according to quartiles of ∑ OH-PAHs. p trend values of the quartile coefficients were estimated by including the original urinary PAH metabolites in the model as a continuous variable. Wilcoxon rank sum test was used to compare the difference of urinary PAH metabolite levels between each two subgroups (eversmokers and nonsmokers; or Wuhan and Zhuhai). We quantified the associations of each urinary PAH metabolite with eCO and FeNO respectively by using linear mixed models including city as a random effect, with adjustment for gender, age, body mass index, income, occupational hazard exposure, smoking amount, passive smoking amount, alcohol consumption, regular physical activity, cooking meals at home, heart diseases and asthma, and frequency of food intake which were assumed to be potential confounders of the association between PAH exposure and eCO/FeNO based on previous studies. Both continuous and categorical models were used to calculate the estimates for percent changes and 95% confidence intervals (CIs) of eCO or FeNO by each 1% increase of each urinary PAH metabolite in continuous analysis. We also calculated the percent changes of eCO and FeNO for the second, third and fourth quartiles of urinary PAH metabolites, compared with the first quartile by categorical models. We further analyzed the dose-response relationships among ever-smokers (including current and former smokers) and non-smokers (including both passive and never smokers). Stratified analyses were conducted to investigate whether covariates (age, gender, body mass index, smoking status, alcohol consumption, regular physical activity and cooking meals at home) could modify the associations of ∑OH-PAHs with eCO or FeNO levels. Effect modification by each covariate in the associations was tested by including an interaction term of ∑OH-PAHs multiplied by the covariate in the linear mixed models. All analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC). 3. Results 3.1. Baseline characteristics Demographic characteristics of the participants by quartiles of ∑ OH-PAHs are presented in Table 1. The mean age of 4133 subjects (1342 males, 32.5%) was 53 years. The percentage of male participants decreased monotonically with quartiles of ∑ OH-PAHs (p b 0.001),

whereas age and exhaled CO levels increased with elevated ∑ OHPAHs (both p b 0.05). No differences were found in body mass index, drinking amount, passive smoking amount, and number of participant with smoking status, regular physical activity, heart diseases or asthma across the quartiles of ∑OH-PAHs. The levels of ∑OH-PAHs metabolites were different between cities. Participants living in Wuhan had higher urinary PAH metabolite levels than those in Zhuhai (p = 0.002). From the results of subgroups (shown in Appendices Table A), we observed that 91.8% of the ever-smokers were males. Both eCO and FeNO levels were higher among ever-smokers than that among non-smokers (both p b 0.05). In total, the urinary PAH metabolite concentrations of four samples with 4-OHPh (0.97%), forty two with 2-OHPh (1.14%) and four with 1OHP (0.97%) were below the LOD. Table 2 shows the distributions of the ten and total urinary PAH metabolite levels. We observed significant differences of urinary PAH metabolite levels between ever-smokers and non-smokers (all p b 0.05), except for 3-OHPh and 2-OHPh. Compared to non-smokers, ever-smokers had higher levels of 1-OHNa, 2-OHNa, and 2-OHFlu, and lower levels of 9-OHFlu, 4-OHPh, 9-OHPh, 3-OHPh, 1-OHPh, 2-OHPh, 1-OHP and ∑OH-PAHs. We also found higher levels of all the OH-PAHs, eCO and FeNO among participants in Wuhan than those in Zhuhai (all p b 0.05), except for 1-OHPh (shown in Appendices Table B). Current smokers have the highest eCO and the lowest FeNO levels. High level of ∑OH-PAHs was found among non-smokers (including passive smokers and never smokers) (shown in Appendices Table C). 3.2. Associations of urinary PAH metabolite concentrations with eCO and FeNO levels In continuous models, 1% change of 1-OHNa, 2-OHNa, 2-OHFlu, 4OHPh, 3-OHPh, and ∑OH-PAHs were significantly positively associated with 12.6% (95%CI: 9.3%, 15.9%), 9.7% (6.5%, 12.9%), 7.5% (4.1%, 10.9%), 3.2% (0.2%, 6.2%), 2.7% (0.1%, 5.3%), and 6.5% (2.7%, 10.4%) change of eCO level; while 1% increase of 1-OHNa, 9-OHPh, 3-OHPh, and 2OHPh were associated with −3.0% (−5.8%, −0.2%), 2.9% (0.3%, 5.6%), 3.2% (1.0%, 5.4%), and 4.5% (2.2%, 6.9%) increase of FeNO (data not shown). We further calculated by categorical analysis, the results showed monotonic associations between eCO and 1-OHNa, 2-OHNa, 2-OHFlu, and ∑ OH-PAHs; while a monotonic association between FeNO and 9-OHFlu (Fig. 1). Stratified analyses showed that age is a potential effect modifier of the association between urinary PAH metabolites and FeNO (Table 3). The significant association was stronger among participants aged b 45 than those aged over 45. We also found that smoking status can modify the associations of ∑OH-PAHs with both eCO and FeNO (p values for effect modification b0.05). Hence, we further quantified the doseresponse relationships of urinary PAH metabolites with eCO and FeNO among both ever-smokers and non-smokers. For eCO, each 1% increase of 1-OHNa, 2-OHNa, 2-OHFlu, and ∑OH-PAHs were positively associated with a 28.2%, 25.8%, 17.1% and 11.3% increased eCO levels (Table 4), and remarkable monotonic associations of eCO with 1-OHNa and 2OHNa were observed among ever-smokers (Fig. 2a). Among nonsmokers, each 1% increase of 1-OHNa, 2-OHNa, 2-OHFlu, 4-OHPh, 3OHPh, 1-OHPh, and ∑ OH-PAHs were associated with a 5.0%, 3.2%, 4.8%, 3.2%, 2.6%, 2.9%, and 3.9% increased eCO levels (Table 4). We also observed significantly positive monotonic associations of eCO with 1OHNa, 2-OHNa, 2-OHFlu, 3-OHPh, and 1-OHPh among non-smokers in categorical models (Fig. 2a). Meanwhile, the associations of 1-OHNa, 2-OHNa and 2-OHFlu with eCO among ever-smokers were stronger than those among non-smokers. The associations between total and ten PAH metabolites and FeNO among non-smokers and ever-smokers were estimated and the results were shown in Table 4 and Fig. 2b. For non-smokers, each 1% increase of 2-OHNa, 9-OHFlu, 4-OHPh, 9-OHPh, 3-OHPh, 2-OHPh and ∑OH-PAHs were associated with a 4.1%, 2.8%, 3.2%, 3.9%, 3.9%, 5.3% and 4.0%

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

545

Table 1 Characteristics of all participants by quartile of total urinary PAH metabolite levels (N = 4133). Quartile of total urinary PAH metabolite levels, μg/mmol Cra

p valued

Characteristics

All participants

Q1

Q2

Q3

Q4

No. observations Male, n (%) Age, year, mean ± SD Body mass index, kg/m2, mean ± SD Income b30,000 RMB/year, n (%) ≥30,000 RMB/year, n (%) Ever exposed to occupational hazards, n (%) Smoking status, n (%) Current smokersb Former smokersb Passive smoker Never smokers Smoking amount, pack-year, mean ± SD Passive smoking amount, hour/week-year, mean ± SD Alcohol consumption, n (%) Alcohol consumption, time/week-year, mean ± SD Physical activity, n (%) Cooking meals at home, n (%) Heart disease, n (%)c Asthma, n (%) City Wuhan Zhuhai eCO, ppm, median (IQR) FeNO, ppb, median (IQR)

4133 1342 (32.5) 53.1 ± 13.1 24.0 ± 3.4

1032 432 (41.9) 51.0 ± 13.3 24.2 ± 3.4

1034 365 (35.3) 52.3 ± 12.9 24.0 ± 3.5

1033 314 (30.4) 54.0 ± 12.5 24.0 ± 3.3

1034 231 (22.3) 55.1 ± 13.2 23.7 ± 3.4

2356 (57.0) 1777 (43.0) 1296 (31.4)

554 (53.7) 478 (46.3) 319 (30.9)

616 (59.6) 418 (40.4) 333 (32.2)

603 (58.4) 430 (41.6) 338 (32.7)

583 (56.4) 451 (43.6) 306 (29.6)

688 (16.6) 164 (4.0) 1315 (31.8) 1966 (47.6) 5.2 ± 14.1 69.5 ± 160.5 672 (16.3) 26.0 ± 81.9 1979 (47.9) 3042 (73.6) 1117 (27.0) 48 (1.2)

167 (16.2) 50 (4.8) 308 (29.8) 507 (49.1) 4.7 ± 14.0 53.3 ± 134.6 176 (17.1) 24.0 ± 75.0 487 (47.2) 703 (68.1) 240 (23.2) 11 (1.1)

187 (18.1) 46 (4.4) 320 (30.9) 481 (46.5) 5.7 ± 14.1 70.2 ± 157.6 187 (18.1) 27.9 ± 84.3 474 (45.8) 757 (73.2) 276 (26.7) 14 (1.4)

198 (19.2) 36 (3.5) 352 (34.1) 447 (43.3) 6.1 ± 15.2 80.5 ± 175.8 182 (17.6) 32.4 ± 91.4 489 (47.3) 782 (75.7) 299 (28.9) 14 (1.4)

136 (13.2) 32 (3.1) 335 (32.4) 531 (51.4) 4.3 ± 13.2 73.8 ± 169.7 127 (12.3) 19.9 ± 75.1 529 (51.2) 800 (77.4) 302 (29.2) 9 (0.9)

2805 (67.9) 1328 (32.1) 4 (7) 21.3 (16.9)

592 (57.4) 440 (42.6) 4 (6) 21.1 (17.6)

730 (70.6) 304 (29.4) 5 (7) 20.7 (16.3)

758 (73.4) 275 (26.6) 4 (8) 21.9 (16.6)

725 (70.1) 309 (29.9) 5 (7) 21.6 (17.0)

– b0.001 b0.001 0.72 0.56 – – 0.90 0.11b – – – – 0.002 0.53 0.45 0.94 0.39 0.66 0.27 0.21 0.002 – – 0.001 0.07

Abbreviations: FeNO, Fractional exhaled nitric oxide; eCO, exhaled carbon monoxide; SD, standard deviation; IQR, interquartile range. a The levels of urinary PAH metabolites were divided into quartiles based on its distribution among all the subjects. b Current and former smokers were defined as ever-smokers. c The 10th version of the International Classification of Diseases (ICD-10) was used to classify heart diseases (ICD-10 codes: I00-I09, I11, I13, and I20-I51). d p trend value of the quartile coefficients were estimated by including the original urinary PAH metabolites in the model as a continuous variable.

increase of FeNO levels (Table 4). Significantly monotonic associations were found between FeNO and 9-OHFlu or 2-OHPh (Fig. 2b). No significant associations were observed between any urinary PAH metabolites and FeNO level among ever-smokers (all p N 0.05), except for 1-OHNa, which were significantly associated with a 8.3% decrease of FeNO (Table 4). Increased urinary PAH metabolites were associated with decrease FeNO among ever-smokers and elevated FeNO levels among non-smokers. 4. Discussion Exposure to PAHs is a risk factor not only for cancer but also for nonmalignant respiratory effects such as chronic obstructive pulmonary

diseases (COPD) and asthma (Burstyn et al., 2003; Al-Daghri et al., 2013; Zhou et al., 2016b). We recently observed that urinary PAH metabolites were significantly associated with lung function decline (Zhou et al., 2016b), but the possible mechanisms of PAHs impair respiratory system remain unclear. In this study, we found that urinary PAH metabolites were positive associated with FeNO and eCO levels. Both FeNO and eCO are not only important markers of oxidative stress and inflammation in airways, but also are critical for the process or development of respiratory system diseases (Zayasu et al., 1997; Yamaya et al., 1998; Van Muylem et al., 2007). Higher FeNO and eCO levels have been observed in patients with lung diseases, especially asthma and COPD (Alving et al., 1993; Kharitonov et al., 1994; Malerba et al., 2014). Meanwhile, some studies reported the levels of FeNO and eCO decreased after

Table 2 Distributions of urinary PAH metabolites, eCO and FeNO. Ever-smokers

p valuea

Urinary PAH metabolites

All participants

Non-smokers

Mean ± SD

Median (IQR)

Mean ± SD

Median (IQR)

Mean ± SD

Median (IQR)

1-OHNa, μg/mmol Cr 2-OHNa, μg/mmol Cr 9-OHFlu, μg/mmol Cr 2-OHFlu, μg/mmol Cr 4-OHPh, μg/mmol Cr 9-OHPh, μg/mmol Cr 3-OHPh, μg/mmol Cr 1-OHPh, μg/mmol Cr 2-OHPh, μg/mmol Cr 1-OHP, μg/mmol Cr ∑OH-PAHs, μg/mmol Cr eCO, ppm FeNO, ppb

0.76 ± 0.99 2.38 ± 23.57 2.22 ± 17.04 0.47 ± 2.02 0.64 ± 4.54 1.39 ± 9.97 0.69 ± 5.53 0.58 ± 1.82 0.4 ± 3.26 1.05 ± 1.33 10.58 ± 53.82 7.92 ± 10.78 24.43 ± 17.15

0.52 (0.51) 1.07 (1.17) 0.83 (1.25) 0.26 (0.25) 0.27 (0.28) 0.58 (0.60) 0.27 (0.31) 0.24 (0.31) 0.15 (0.16) 0.70 (0.75) 5.75 (4.83) 4 (7) 21.31 (16.87)

0.86 ± 0.84 1.81 ± 2.69 1.27 ± 2.55 0.4 ± 1.14 0.42 ± 2.3 0.89 ± 4.44 0.45 ± 2.01 0.34 ± 0.59 0.28 ± 2.28 0.84 ± 1.06 7.55 ± 16.95 18.62 ± 15.48 25.09 ± 14.75

0.67 (0.58) 1.32 (1.10) 0.70 (0.83) 0.28 (0.22) 0.25 (0.25) 0.54 (0.48) 0.27 (0.26) 0.20 (0.18) 0.14 (0.12) 0.59 (0.56) 5.56 (4.04) 15 (19) 21.88 (15.75)

0.73 ± 1.02 2.53 ± 26.42 2.47 ± 19.08 0.49 ± 2.19 0.7 ± 4.96 1.52 ± 10.96 0.75 ± 6.13 0.64 ± 2.02 0.43 ± 3.47 1.1 ± 1.39 11.36 ± 59.76 5.15 ± 6.84 24.25 ± 17.72

0.49 (0.48) 1.00 (1.16) 0.88 (1.37) 0.26 (0.25) 0.28 (0.29) 0.60 (0.63) 0.27 (0.32) 0.26 (0.37) 0.15 (0.16) 0.73 (0.80) 5.81 (5.07) 4 (4) 21.09 (17.17)

b0.001 b0.001 b0.001 0.03 b0.001 0.01 0.45 b0.001 0.40 b0.001 0.01 b0.001 b0.001

Abbreviations: FeNO, Fractional exhaled nitric oxide; eCO, exhaled carbon monoxide; 1-OHNa, 1-hydroxynaphthalene; 2-OHNa, 2-hydroxynaphthalene; 9-OHFlu, 9-hydroxyfluorene; 2OHFlu, 2-hydroxyfluorene; 4-OHPh, 4-hydroxyphenanthrene; 9-OHPh, 9-hydroxyphenanthrene; 3-OHPh, 3-hydroxyphenanthrene; 1-OHPh, 1-hydroxyphenanthrene; 2-OHPh, 2hydroxyphenanthrene; 1-OHP, 1-hydroxypyrene; ∑OH-PAHs, the total of PAH metabolites; SD, standard deviation; IQR, interquartile range. a Wilcoxon rank sum test was used to compare the difference of urinary PAH metabolite levels between the two subgroups.

546

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

Fig. 1. Association of urinary PAH metabolites with eCO and FeNO among all participants (N = 4133). The level of each urinary PAH metabolite was divided into quartiles based on its distribution among all participants. Abbreviations: FeNO, Fractional exhaled nitric oxide; eCO, exhaled carbon monoxide; 1-OHNa, 1-hydroxynaphthalene; 2-OHNa, 2hydroxynaphthalene; 9-OHFlu, 9-hydroxyfluorene; 2-OHFlu, 2-hydroxyfluorene; 4-OHPh, 4-hydroxyphenanthrene; 9-OHPh, 9-hydroxyphenanthrene; 3-OHPh, 3hydroxyphenanthrene; 1-OHPh, 1-hydroxyphenanthrene; 2-OHPh, 2-hydroxyphenanthrene; 1-OHP, 1-hydroxypyrene; ∑OH-PAHs, the total of PAH metabolites. All linear mixed models were adjusted for gender (male/female), age (continuous), body mass index (continuous), income (low/high), occupational hazards exposure (yes/no), heart disease (yes/no), asthma (yes/no), smoking amount (continuous, pack/day-years), passive smoking amount (continuous, hours/week-years), alcohol consumption (continuous, times/week-years), regular physical activity (yes/no), cooking meals at home (yes/no), frequency of food intake including wheat (continuous, times/week), vegetables (continuous, times/week), meat (continuous, times/week), fish (continuous, times/week) and milk (continuous, times/week), and included city as a random effect in models.

Table 3 Association of total urinary PAH metabolites with eCO and FeNO levels, stratified by selected characteristics (N = 4133). Stratification characteristic

N (%)

eCOa

FeNOa b

Percent change Gender Male Female Age b45 45–59 ≥60 Body Mass Index b18.5 18.5–23.9 ≥24 Smoking status Current or former Never Alcohol consumption Yes No Regular physical activity Yes No Cooking meals at home Yes No

p value for interaction

c

Percent change

0.6 1342 (32.5) 2791 (67.5)

9.4 (1.2, 17.7) 4.1 (−0.2, 8.4)

1082 (26.2) 1753 (42.4) 1298 (31.4)

0.8 (−6.5, 8.1) 11 (4.6, 17.3) 4.1 (−2.3, 10.5)

152 (3.7) 2038 (49.3) 1943 (47.0)

−7.1 (−26.7, 12.5) 8.9 (3.5, 14.3) 5.0 (−0.7, 10.8)

852 (20.6) 3281 (79.4)

13.3 (2.2, 24.4) 4.3 (0.4, 8.1)

672 (16.3) 3461 (83.7)

15.6 (2.8, 28.5) 6.1 (2.1, 10.0)

1979 (47.9) 2154 (52.1)

6.8 (1.6, 12.1) 6.7 (1.2, 12.2)

3042 (73.6) 1091 (26.4)

6.3 (2.1, 10.6) 9.8 (1.2, 18.4)

p value for interactionc 0.9

2.2 (−3.7, 8.2) 2.5 (−1.4, 6.5) 0.3

0.01 7.1 (1.3, 12.8) 3.5 (−1.5, 8.6) −2.4 (−8.9, 4.0)

0.3

0.7 12.3 (−9.3, 33.8) 3.2 (−1.4, 7.8) 1 (−3.8, 5.8)

b0.001

b0.001 −4.7 (−12.6, 3.2) 4 (0.4, 7.6)

0.7

0.9 4.9 (−4.4, 14.2) 2.2 (−1.3, 5.7)

0.5

0.8 2.6 (−2.1, 7.3) 2.2 (−2.3, 6.7)

0.5

0.6 3.5 (−0.2, 7.2) −0.9 (−7.8, 5.9)

Abbreviations: FeNO, fractional exhaled nitric oxide; eCO, exhaled carbon monoxide; CI, confidence interval; a These models were adjusted for gender (male/female), age (continuous), body mass index (continuous), income (low/high), occupational hazards exposure (yes/no), heart disease (yes/no), asthma (yes/no), smoking amount (continuous, pack/day-years), passive smoking amount (continuous, hours/week-years), alcohol consumption (continuous, times/weekyears), regular physical activity (yes/no), cooking meals at home (yes/no), frequency of food intake including wheat (continuous, times/week), vegetables (continuous, times/week), meat (continuous, times/week), fish (continuous, times/week) and milk (continuous, times/week), and included city as a random effect in models. b Percent changes for the relationship of urinary PAH metabolites with FeNO or eCO was conducted by continuous analyses. c p values for effect modification were calculated by adding an interaction term of log-transformed ∑OH-PAHs (as a continuous variable) and the stratification variable in linear mixed models.

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

547

Table 4 Association between urinary PAH metabolites and FeNO or eCO levels among non-smokers and ever-smokers. Urinary PAH metabolites

Percent changea eCO

1-OHNa 2-OHNa 9-OHFlu 2-OHFlu 4-OHPh 9-OHPh 3-OHPh 1-OHPh 2-OHPh 1-OHP ∑OH-PAHs

FeNO

Non-smokers (N = 3281)

Ever-smokers (N = 852)

Non-smokers (N = 3281)

Ever-smokers (N = 852)

5.0 (1.6, 8.5) 3.2 (0.0, 6.4) 1.4 (−1.2, 4.1) 4.8 (1.4, 8.3) 3.2 (0.2, 6.2) 2.6 (−0.5, 5.7) 2.6 (0.0, 5.1) 2.9 (0.3, 5.5) 2.7 (−0.1, 5.6) −1.5 (−5.1, 2.0) 3.9 (0.0, 7.8)

28.2 (19.6, 36.8) 25.8 (15.7, 35.8) −1.0 (−8.4, 6.4) 17.1 (6.8, 27.3) 0.2 (−8.6, 9.1) −0.3 (−9.2, 8.5) 0.0 (−8.0, 8.0) 3.4 (−5.2, 12.0) −1.6 (−10.1, 6.9) −6.4 (−15.5, 2.6) 11.3 (0.0, 22.7)

−0.7 (−3.9, 2.4) 4.1 (1.2, 7.1) 2.8 (0.4, 5.3) 2.4 (−0.8, 5.6) 3.2 (0.4, 6.0) 3.9 (1.0, 6.8) 3.9 (1.5, 6.3) 0.6 (−1.8, 3.0) 5.3 (2.6, 7.9) 0.6 (−2.7, 3.9) 4.0 (0.4, 7.6)

−8.3 (−14.4, −2.3) −5.7 (−12.8, 1.4) −1.2 (−6.4, 3.9) −3.5 (−10.7, 3.7) −2.1 (−8.3, 4.1) −1.9 (−8.0, 4.3) −1.3 (−6.9, 4.2) −3.5 (−9.4, 2.5) 0.5 (−5.4, 6.4) −3.3 (−9.5, 2.9) −4.7 (−12.6, 3.2)

Abbreviations: 1-OHNa,1-hydroxynaphthalene; 2-OHNa, 2-hydroxynaphthalene; 9-OHFlu, 9-hydroxyfluorene; 2-OHFlu, 2-hydroxyfluorene; 4-OHPh, 4-hydroxyphenanthrene; 9-OHPh, 9-hydroxyphenanthrene; 3-OHPh, 3-hydroxyphenanthrene; 1-OHPh, 1-hydroxyphenanthrene; 2-OHPh, 2-hydroxyphenanthrene; 1-OHP, 1-hydroxypyrene; ∑OH-PAHs, the total of PAH metabolites; FeNO, Fractional exhaled nitric oxide; eCO, exhaled carbon monoxide; CI, confidence interval. a Percent change for the relationship of each urinary PAH metabolite with log-transformed FeNO or eCO was conducted by continuous analyses, with adjustment for gender (male/ female), age (continuous), body mass index (continuous), income (low/high), occupational hazards exposure (yes/no), heart disease (yes/no), asthma (yes/no), smoking amount (continuous, pack/day-years), passive smoking amount (continuous, hours/week-years), alcohol consumption (continuous, times/week-years), regular physical activity (yes/no), cooking meals at home (yes/no), frequency of food intake including wheat (continuous, times/week), vegetables (continuous, times/week), meat (continuous, times/week), fish (continuous, times/week) and milk (continuous, times/week), and included city as a random effect in models.

anti-inflammatory therapy in asthmatic patients (Zayasu et al., 1997; Silkoff et al., 2001). The American Thoracic Society recommended to apply FeNO measurements for monitoring and detection of chronic inflammatory airway disease including asthma (Dweik et al., 2011). Previous studies have also demonstrated that exposures to PAHs can induce inflammatory responses, such as increasing total WBC count, and levels of serum CRP and cytokines (Interleukin-6 and Interleukin-10) (Leem et al., 2005; Alshaarawy et al., 2013). To our knowledge, only a few studies have investigated the association between PAH exposures and the levels of FeNO or eCO. One study enrolled 89 healthy children reported that increased levels of FeNO were significantly associated with higher prenatal PAH exposure (Jedrychowski et al., 2012), which is consistent with our results among non-smokers. As environmental pollutants, PAHs can deposit on the thin alveolar epithelium directly and retain in the pulmonary alveolar area after exposure. Meanwhile, PAHs can generate reactive oxygen species or reactive nitrogen species through redox cycling after metabolized by the cytochrome P450 enzymes (Palackal et al., 2002; Kuang et al., 2013). Our findings that urinary PAH metabolites were associated with eCO and FeNO indicate that PAH exposures may induce inflammation in respiratory system. Cigarette smoke is an important source of PAHs. In a large-scale study in China, the eCO level among current smoker was about 3-fold higher than that among never smokers (Zhang et al., 2013), which was similar to results of other studies from other countries (Pearce et al., 2005; Hung et al., 2006). Hence, many studies suggest using eCO as a biomarker to assess cigarette smoke exposure (Deveci et al., 2004; Sandberg et al., 2011; Zhang et al., 2013). In this study, we noted that the association of eCO with 1-OHNa and 2-OHNa was stronger among ever-smokers than non-smokers. Naphthalene is one kind of low molecular weight PAHs, which are more likely generated by low or moderate temperature combustion process, such as cigarette and domestic coal burning, because of its low boiling point and high volatility. Gmeiner et al. determined seventeen polycyclic aromatic hydrocarbons in cigarette smoke, they found that naphthalene has the highest concentration (236 ng per cigarette) among the 17 determined PAHs (Gmeiner et al., 1997). Our findings show higher levels of 1-OHNa, 2-OHNa and 2OHFlu in ever-smokers than those in non-smokers, and the associations between the three urinary PAH metabolites and eCO were stronger than those among non-smokers. Li et al. conducted a study among the US population to investigate the concentration and profile of 22 urinary PAH metabolites. They found that all the detectable metabolite concentrations were higher in smokers than those in non-smokers,

especially1-OHNa and 2-OHNa, which were 3–4 times higher in smokers than those in non-smokers (Li et al., 2008). High molecular weight PAHs were high toxic and carcinogenic, while low molecular weight PAHs are considered to be acutely toxic and noncarcinogenic (Eisler, 1987). Our findings suggest that low molecular weight PAHs especially naphthalene more likely induce inflammatory responses in airways. Interestingly, we also found that smoking is a potential effect modifier of associations between urinary PAH metabolites and eCO, as well as urinary PAH metabolites and FeNO. For eCO, positive associations were found among both ever-smokers and non-smokers, and the associations were stronger among ever-smokers than that among non-smokers. Previous studies have demonstrated that smoking can increase eCO level. Deveci et al. observed that eCO levels were significantly positively correlated with both smoking amount and smoking duration (Deveci et al., 2004). The interaction between urinary PAH metabolites and smoking on FeNO was different from that on eCO. The dose-response relationships between urinary PAH metabolites and FeNO among eversmokers was inconsistent with those among non-smokers. Increased urinary PAH metabolites were associated with decreased FeNO among ever-smokers, while related with elevated FeNO levels among nonsmokers. Similarly, Jedrychowski et al. found the positive relationships among healthy children (non-smokers) (Jedrychowski et al., 2012). Sundy et al. found that smoking can lower FeNO level (Sundy et al., 2007). Furthermore, McSharry et al. observed that short-term effect (hours since last cigarette) of smoking was associated with elevated FeNO level, while long-term effect was associated with FeNO reduction (McSharry et al., 2005). One possible mechanism for reduced FeNO among smokers might be that cigarette smoke contains high NO levels, which may reduce endogenous NO synthesis by feedback inhibition (Kharitonov et al., 1995). Inhalation, dietary and dermal are the three routes of PAH exposures. Although the patterns of PAH exposures in individuals are not the same, previous studies have shown that dietary intake and inhalation are the main routes of PAH exposures (Xia et al., 2010; Gungormus et al., 2014), while dermal exposure is 33 times lower than inhalation exposure base on the concentration of benzo[a]pyrene equivalent (Gungormus et al., 2014). In this study, we found significantly positive associations of urinary PAH metabolites with eCO and FeNO in non-smokers. Meanwhile, we also observed the lowest percentage of ever-smokers, while highest percentage of cooking meals at home at the highest quartile of total PAH metabolite levels. There were

548

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

Fig. 2. Association between Urinary PAH Metabolites and eCO (a) and FeNO (b) among Ever-smokers (N = 852) and Non-smokers (N = 3281). Ever-smokers included both current and former smokers, and non-smokers included both passive and never smokers. Abbreviations: eCO, exhaled carbon monoxide; FeNO, fractional exhaled nitric oxide; 1-OHNa, 1hydroxynaphthalene; 2-OHNa, 2-hydroxynaphthalene; 9-OHFlu, 9-hydroxyfluorene; 2-OHFlu, 2-hydroxyfluorene; 4-OHPh, 4-hydroxyphenanthrene; 9-OHPh, 9-hydroxyphenanthrene; 3-OHPh, 3-hydroxyphenanthrene; 1-OHPh, 1-hydroxyphenanthrene; 2-OHPh, 2-hydroxyphenanthrene; 1-OHP, 1-hydroxypyrene; ∑OH-PAHs, the total of PAH metabolites. All linear mixed models were adjusted for gender (male/female), age (continuous), body mass index (continuous), income (low/high), occupational hazards exposure (yes/no), heart disease (yes/ no), asthma (yes/no), smoking amount (continuous, pack/day-years), passive smoking amount (continuous, hours/week-years), alcohol consumption (continuous, times/week-years), regular physical activity (yes/no), cooking meals at home (yes/no), frequency of food intake including wheat (continuous, times/week), vegetables (continuous, times/week), meat (continuous, times/week), fish (continuous, times/week) and milk (continuous, times/week), and included city as a random effect in models.

about 80% of the non-smokers in this study cooked meals at home, and most of the participants (93.8%) used gas as cooking fuel. PAHs can release into the air from gas burning. Our findings indicate that except for cigarette smoke, traffic exhaust, dietary intake and cooking fuel are main sources of PAH exposures, and associated with changes of inflammation biomarkers. We also noted that the ∑OH-PAHs concentration among Wuhan participants were higher than that among Zhuhai participants. The concentrations of some air pollutants such as PM2.5

andPM10 exposure in Zhuhai are much lower than those in Wuhan (Zhou et al., 2016a). Meanwhile, the smoking amount of the participants living in Wuhan (6.71 pack-years) is also much higher than that in Zhuhai (1.98 pack-years) in this study. Different environmental exposure levels may lead to the differences of internal doses of PAH exposures between the two cities. Our study has several advantages. First, we conducted a study with a large sample size to investigate the associations between urinary PAH

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

metabolites and FeNO or eCO. Second, considering the influence of cigarette smoke, we divided all participants into two subgroups according to smoking status to further quantify the associations among eversmokers and non-smokers separately. One limitation of this study is that ambient CO was not taken into account, which could affect exhaled CO level and lead to overestimating the influence of urinary PAH metabolites (Antuni et al., 2000). In addition, the participants enrolled in this study were from two cities (Wuhan and Zhuhai) in China, where living conditions are different, although we adjusted for the study areas. Moreover, we cannot prove causality because of our cross-sectional observational design. Further longitudinal studies are needed to confirm the findings. 5. Conclusions This study shows positive associations between urinary PAH metabolites and airway inflammation markers among adult residents in Wuhan and Zhuhai, China. Elevated urinary 1-OHNa, 9-OHPh, 3-OHPh, and 2-OHPh were significantly associated with increased FeNO levels, while elevated urinary 1-OHNa, 2-OHNa, 2-OHFlu, 4-OHPh, 3-OHPh, and ∑ OH-PAHs were significantly associated with increased eCO levels. The associations of urinary PAH metabolites and eCO were stronger among ever-smokers than non-smokers. Increased urinary PAH metabolites were associated with decreased FeNO among ever-smokers and elevated FeNO levels among non-smokers. These findings emphasize the needs to reduce PAH exposure for preventing inflammation in airways. Competing financial interests The authors declare no competing financial interests. Acknowledgements We thank the study participants from the two cities for their help. Funding This work was supported by the key project of the National Natural Science Foundation of China [91543207], the Foundation for Innovative Research Team of Huazhong University of Science and Technology [2016YXZD044], and the Seed Foundation of Huazhong University and Science and Technology [2016JCTD116]. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2017.10.294. References Agency for Toxic Substance & Disease Registry, 2011. Polycyclic aromatic hydrocarbons (PAHs): what health effects are associated with PAH exposure? https:// www.atsdr.cdc.gov/csem/csem.asp?csem=13&po=11 Al-Daghri, N.M., Alokail, M.S., Abd-Alrahman, S.H., Draz, H.M., Yakout, S.M., Clerici, M., 2013. Polycyclic aromatic hydrocarbon exposure and pediatric asthma in children: a case-control study. Environ. Health 12, 1. Alshaarawy, O., Zhu, M., Ducatman, A., Conway, B., Andrew, M.E., 2013. Polycyclic aromatic hydrocarbon biomarkers and serum markers of inflammation. A positive association that is more evident in men. Environ. Res. 126, 98–104. Alving, K., Weitzberg, E., Lundberg, J.M., 1993. Increased amount of nitric oxide in exhaled air of asthmatics. Eur. Respir. J. 6, 1368–1370. American Thoracic Society, 2005. ATS/ERS recommendations for standardized procedures for the online and offline measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide, 2005. Am. J. Respir. Crit. Care Med. 171, 912–930. Antuni, J.D., Kharitonov, S.A., Hughes, D., Hodson, M.E., Barnes, P.J., 2000. Increase in exhaled carbon monoxide during exacerbations of cystic fibrosis. Thorax 55, 138–142. Barnes, P.J., Chowdhury, B., Kharitonov, S.A., Magnussen, H., Page, C.P., Postma, D., Saetta, M., 2006. Pulmonary biomarkers in chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 174, 6–14.

549

Berhane, K., Zhang, Y., Salam, M.T., Eckel, S.P., Linn, W.S., Rappaport, E.B., Bastain, T.M., Lurmann, F., Gilliland, F.D., 2014. Longitudinal effects of air pollution on exhaled nitric oxide: the Children's Health Study. Occup. Environ. Med. 71, 507–513. Boffetta, P., Jourenkova, N., Gustavsson, P., 1997. Cancer risk from occupational and environmental exposure to polycyclic aromatic hydrocarbons. Cancer Causes Control 8, 444–472. Burstyn, I., Boffetta, P., Heederik, D., Partanen, T., Kromhout, H., Svane, O., Langard, S., Frentzel-Beyme, R., Kauppinen, T., Stucker, I., Shaham, J., Ahrens, W., Cenee, S., Ferro, G., Heikkila, P., Hooiveld, M., Johansen, C., Randem, B.G., Schill, W., 2003. Mortality from obstructive lung diseases and exposure to polycyclic aromatic hydrocarbons among asphalt workers. Am. J. Epidemiol. 158, 468–478. Campo, L., Rossella, F., Fustinoni, S., 2008. Development of a gas chromatography/mass spectrometry method to quantify several urinary monohydroxy metabolites of polycyclic aromatic hydrocarbons in occupationally exposed subjects. B, Analytical technologies in the biomedical and life sciences.]–>J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 875, 531–540. Choi, A.M., Alam, J., 1996. Heme oxygenase-1: function, regulation, and implication of a novel stress-inducible protein in oxidant-induced lung injury. Am. J. Respir. Cell Mol. Biol. 15, 9–19. Deveci, S.E., Deveci, F., Acik, Y., Ozan, A.T., 2004. The measurement of exhaled carbon monoxide in healthy smokers and non-smokers. Respir. Med. 98, 551–556. Dweik, R.A., Boggs, P.B., Erzurum, S.C., Irvin, C.G., Leigh, M.W., Lundberg, J.O., Olin, A.C., Plummer, A.L., Taylor, D.R., American Thoracic Society Committee on Interpretation of Exhaled Nitric Oxide Levels for Clinicalm A, 2011. An official ATS clinical practice guideline: interpretation of exhaled nitric oxide levels (FENO) for clinical applications. Am. J. Respir. Crit. Care Med. 184, 602–615. Eisler, R., 1987. Polycyclic Aromatic Hydrocarbon Hazards to Fish, Wildlife and Invertebrates: A Synoptic Review. Contaminant Hazard Reviews Report; Biological Report. Farzan, S.F., Chen, Y., Trachtman, H., Trasande, L., 2016. Urinary polycyclic aromatic hydrocarbons and measures of oxidative stress, inflammation and renal function in adolescents: NHANES 2003–2008. Environ. Res. 144, 149–157. Gerritsen, W.B., Asin, J., Zanen, P., van den Bosch, J.M., Haas, F.J., 2005. Markers of inflammation and oxidative stress in exacerbated chronic obstructive pulmonary disease patients. Respir. Med. 99, 84–90. Gmeiner, G., Stehlik, G., Tausch, H., 1997. Determination of seventeen polycyclic aromatic hydrocarbons in tobacco smoke condensate. J. Chromatogr. A 767, 163–169. Gungormus, E., Tuncel, S., Hakan Tecer, L., Sofuoglu, S.C., 2014. Inhalation and dermal exposure to atmospheric polycyclic aromatic hydrocarbons and associated carcinogenic risks in a relatively small city. Ecotoxicol. Environ. Saf. 108, 106–113. Haccuria, A., Michils, A., Michiels, S., Van Muylem, A., 2014. Exhaled nitric oxide: a biomarker integrating both lung function and airway inflammation changes. J. Allergy Clin. Immunol. 134, 554–559. Hung, J., Lin, C.H., Wang, J.D., Chan, C.C., 2006. Exhaled carbon monoxide level as an indicator of cigarette consumption in a workplace cessation program in Taiwan. J. Formos. Med. Assoc. 105, 210–213. Jedrychowski, W., Maugeri, U., Mroz, E., Flak, E., Rembiasz, M., Jacek, R., Sowa, A., 2012. Fractional exhaled nitric oxide in healthy non-asthmatic 7-year olds and prenatal exposure to polycyclic aromatic hydrocarbons: nested regression analysis. Pediatr. Pulmonol. 47, 1131–1139. Kharitonov, S.A., Yates, D., Robbins, R.A., Logan-Sinclair, R., Shinebourne, E.A., Barnes, P.J., 1994. Increased nitric oxide in exhaled air of asthmatic patients. Lancet 343, 133–135. Kharitonov, S.A., Robbins, R.A., Yates, D., Keatings, V., Barnes, P.J., 1995. Acute and chronic effects of cigarette smoking on exhaled nitric oxide. Am. J. Respir. Crit. Care Med. 152, 609–612. Kuang, D., Zhang, W., Deng, Q., Zhang, X., Huang, K., Guan, L., Hu, D., Wu, T., Guo, H., 2013. Dose-response relationships of polycyclic aromatic hydrocarbons exposure and oxidative damage to DNA and lipid in coke oven workers. Environ. Sci. Technol. 47, 7446–7456. Kwon, S., Newcomb, R.L., George, S.C., 2001. Mechanisms of synergistic cytokine-induced nitric oxide production in human alveolar epithelial cells. Nitric Oxide 5, 534–546. Leem, J.H., Kim, J.H., Lee, K.H., Hong, Y., Lee, K.H., Kang, D., Kwon, H.J., 2005. Asthma attack associated with oxidative stress by exposure to ETS and PAH. J. Asthma 42, 463–467. Li, Z., Sandau, C.D., Romanoff, L.C., Caudill, S.P., Sjodin, A., Needham, L.L., Patterson Jr., D.G., 2008. Concentration and profile of 22 urinary polycyclic aromatic hydrocarbon metabolites in the US population. Environ. Res. 107, 320–331. Li, X., Feng, Y., Deng, H., Zhang, W., Kuang, D., Deng, Q., Dai, X., Lin, D., Huang, S., Xin, L., He, Y., Huang, K., He, M., Guo, H., Zhang, X., Wu, T., 2012. The dose-response decrease in heart rate variability: any association with the metabolites of polycyclic aromatic hydrocarbons in coke oven workers? PLoS One 7, e44562. Liao, L.M., Hofmann, J.N., Kamangar, F., Strickland, P.T., Ji, B.T., Yang, G., Li, H.L., Rothman, N., Zheng, W., Chow, W.H., Gao, Y.T., Shu, X.O., 2014. Polycyclic aromatic hydrocarbons and risk of gastric cancer in the Shanghai Women's Health Study. Int. J. Mol. Epidemiol. Genet. 5, 140–144. MacNee, W., 2001. Oxidative stress and lung inflammation in airways disease. Eur. J. Pharmacol. 429, 195–207. Malerba, M., Radaeli, A., Olivini, A., Damiani, G., Ragnoli, B., Montuschi, P., Ricciardolo, F.L., 2014. Exhaled nitric oxide as a biomarker in COPD and related comorbidities. Biomed. Res. Int. 2014, 271918. Martini, A., Sbardella, D., Bertini, L., Capanna, S., Spalletta, M., D'Ovidio, M.C., 2012. Airway inflammation in professional divers: FeNO as a marker. Undersea Hyperb. Med. 39, 901–907. Mastrangelo, G., Fadda, E., Marzia, V., 1996. Polycyclic aromatic hydrocarbons and cancer in man. Environ. Health Perspect. 104, 1166–1170. McSharry, C.P., McKay, I.C., Chaudhuri, R., Livingston, E., Fraser, I., Thomson, N.C., 2005. Short and long-term effects of cigarette smoking independently influence exhaled nitric oxide concentration in asthma. J. Allergy Clin. Immunol. 116, 88–93.

550

Y. Zhou et al. / Science of the Total Environment 618 (2018) 542–550

Obaseki, D.O., Adeniyi, B., Jumbo, J., Oyewo, A., Irabor, I., Erhabor, G.E., 2014. Respiratory symptom, lung function and exhaled carbon monoxide among a sample of traffic workers in Lagos, Nigeria: a pilot survey. Niger. Med. J. 55, 306–309. Palackal, N.T., Lee, S.H., Harvey, R.G., Blair, I.A., Penning, T.M., 2002. Activation of polycyclic aromatic hydrocarbon trans-dihydrodiol proximate carcinogens by human aldo-keto reductase (AKR1C) enzymes and their functional overexpression in human lung carcinoma (A549) cells. J. Biol. Chem. 277, 24799–24808. Park, J.H., Mangal, D., Tacka, K.A., Quinn, A.M., Harvey, R.G., Blair, I.A., Penning, T.M., 2008. Evidence for the aldo-keto reductase pathway of polycyclic aromatic transdihydrodiol activation in human lung A549 cells. Proc. Natl. Acad. Sci. U. S. A. 105, 6846–6851. Pearce, M.S., Hayes, L., Newcastle Heart, P., Newcastle Thousand Families, S., 2005. Selfreported smoking status and exhaled carbon monoxide: results from two population-based epidemiologic studies in the north of England. Chest 128, 1233–1238. Sandberg, A., Skold, C.M., Grunewald, J., Eklund, A., Wheelock, A.M., 2011. Assessing recent smoking status by measuring exhaled carbon monoxide levels. PLoS One 6, e28864. Silkoff, P.E., McClean, P., Spino, M., Erlich, L., Slutsky, A.S., Zamel, N., 2001. Dose-response relationship and reproducibility of the fall in exhaled nitric oxide after inhaled beclomethasone dipropionate therapy in asthma patients. Chest 119, 1322–1328. Slebos, D.J., Ryter, S.W., Choi, A.M., 2003. Heme oxygenase-1 and carbon monoxide in pulmonary medicine. Respir. Res. 4, 7. Song, Y., Hou, J., Huang, X., Zhang, X., Tan, A., Rong, Y., Sun, H., Zhou, Y., Cui, X., Yang, Y., Guo, Y., Zhang, Z., Luo, X., Zhang, B., Hou, F., He, X., Xie, J., Wu, T., Chen, W., Yuan, J., 2014. The Wuhan-Zhuhai (WHZH) cohort study of environmental air particulate matter and the pathogenesis of cardiopulmonary diseases: study design, methods and baseline characteristics of the cohort. BMC Public Health 14, 994. Sundy, J.S., Hauswirth, D.W., Mervin-Blake, S., Fernandez, C.A., Patch, K.B., Alexander, K.M., Allgood, S., McNair, P.D., Levesque, M.C., 2007. Smoking is associated with an agerelated decline in exhaled nitric oxide. Eur. Respir. J. 30, 1074–1081. Tatsumi, T., Matoba, S., Kawahara, A., Keira, N., Shiraishi, J., Akashi, K., Kobara, M., Tanaka, T., Katamura, M., Nakagawa, C., Ohta, B., Shirayama, T., Takeda, K., Asayama, J., Fliss, H., Nakagawa, M., 2000. Cytokine-induced nitric oxide production inhibits

mitochondrial energy production and impairs contractile function in rat cardiac myocytes. J. Am. Coll. Cardiol. 35, 1338–1346. United States Environmental Protection Agency, 1993. Provisional guidance for quantitative risk assessment of polycyclic aromatic hydrocarbons. https://cfpub.epa.gov/ncea/ risk/recordisplay.cfm?deid=49732. Van Muylem, A., Knoop, C., Estenne, M., 2007. Early detection of chronic pulmonary allograft dysfunction by exhaled biomarkers. Am. J. Respir. Crit. Care Med. 175, 731–736. White, A.J., Bradshaw, P.T., Herring, A.H., Teitelbaum, S.L., Beyea, J., Stellman, S.D., Steck, S.E., Mordukhovich, I., Eng, S.M., Engel, L.S., Conway, K., Hatch, M., Neugut, A.I., Santella, R.M., Gammon, M.D., 2016. Exposure to multiple sources of polycyclic aromatic hydrocarbons and breast cancer incidence. Environ. Int. 89–90, 185–192. Xia, Z., Duan, X., Qiu, W., Liu, D., Wang, B., Tao, S., Jiang, Q., Lu, B., Song, Y., Hu, X., 2010. Health risk assessment on dietary exposure to polycyclic aromatic hydrocarbons (PAHs) in Taiyuan, China. Sci. Total Environ. 408, 5331–5337. Yamaya, M., Sekizawa, K., Ishizuka, S., Monma, M., Mizuta, K., Sasaki, H., 1998. Increased carbon monoxide in exhaled air of subjects with upper respiratory tract infections. Am. J. Respir. Crit. Care Med. 158, 311–314. Zayasu, K., Sekizawa, K., Okinaga, S., Yamaya, M., Ohrui, T., Sasaki, H., 1997. Increased carbon monoxide in exhaled air of asthmatic patients. Am. J. Respir. Crit. Care Med. 156, 1140–1143. Zhang, Q., Li, L., Smith, M., Guo, Y., Whitlock, G., Bian, Z., Kurmi, O., Collins, R., Chen, J., Lv, S., Pang, Z., Chen, C., Chen, N., Xiong, Y., Peto, R., Chen, Z., China Kadoorie Biobank Study, C, 2013. Exhaled carbon monoxide and its associations with smoking, indoor household air pollution and chronic respiratory diseases among 512,000 Chinese adults. Int. J. Epidemiol. 42, 1464–1475. Zhou, Y., Liu, Y., Song, Y., Xie, J., Cui, X., Zhang, B., Shi, T., Yuan, J., Chen, W., 2016a. Shortterm effects of outdoor air pollution on lung function among female non-smokers in China. Sci Rep 6, 34947. Zhou, Y., Sun, H., Xie, J., Song, Y., Liu, Y., Huang, X., Zhou, T., Rong, Y., Wu, T., Yuan, J., Chen, W., 2016b. Urinary polycyclic aromatic hydrocarbon metabolites and altered lung function in Wuhan, China. Am. J. Respir. Crit. Care Med. 193, 835–846.