Heavy exposure of waste collectors to polycyclic aromatic

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Ecotoxicology and Human Environmental Health

Heavy exposure of waste collectors to polycyclic aromatic hydrocarbons in a poor rural area of middle China Jianheng Zheng, WeiWei Zheng, Gengsheng He, Ying Zhou, Songhui Jiang, Peter Spencer, Weimin Ye, Yuxin Zheng, and Weidong Qu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b02024 • Publication Date (Web): 02 Jul 2018 Downloaded from http://pubs.acs.org on July 3, 2018

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Environmental Science & Technology

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Heavy exposure of waste collectors to polycyclic aromatic hydrocarbons in a

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poor rural area of middle China

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Jian Heng Zheng, †, ‡,⊥ Weiwei Zheng, † Ying Zhou, †,‡ Songhui Jiang, † Peter Spencer, §

Weimin Ye, √ Yuxin Zheng, || Gensheng He,* †,‡ Weidong Qu*,†

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† Centers for Water and Health, Key Laboratory of the Public Health Safety, Ministry

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of Education, Key Lab of Health Technology Assessment, National Health

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Commission of the People's Republic of China, Department of Environmental Health,

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School of Public Health, Fudan University, Shanghai, 200032, China.

11 12

§

13

School of Medicine, Oregon Health & Science University, Portland, Oregon, 97239,

14

USA.

Oregon Institute of Occupational Health Sciences, and Department of Neurology,

15 16 17

√

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet,

Stockholm, 171 77, Sweden

18 19

||

20

China

School of Public Health, Qingdao University, 38 Dengzhou Road, Qingdao, 266021,

21 22

‡

Key Laboratory of the Public Health Safety, Department of Nutrition and Food

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Hygiene, Ministry of Education, School of Public Health, Fudan University, Shanghai,

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200032, China

25 26 27

⊥

Key Laboratory of State General Administration of Sport, Shanghai Research

Institute of Sports Science, Shanghai, 200030, China

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1

ACS Paragon Plus Environment


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*Corresponding author: Weidong Qu, Key Laboratory of the Public Health Safety,

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Ministry of Education, Department of Environmental Health, School of Public Health,

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Fudan

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[email protected]. [email protected]

University.

Tel.:

86-21-54237203;

Fax:

86-21-64045165;

E-mail:

34 35 36

Running title: Baseline exposure to PAHs in rubber waste collectors

37 38 39

Competing financial interest declaration: The authors declare that they have no

40

actual or potential competing financial interests.

41 42 43

Abbreviations

44

1-NAP, 1-hydroxynaphthalene; 1-PHE, 1-hydroxyphenanthrene; 1-PYR, 1-hydroxypyrene；

45

2-NAP, 2-hydroxynaphthalene; 2-FLU, 2-hydroxyfluorene; 2-PHE, 2-hydroxyphenanthrene；

46

3-FLU, 3-hydroxyfluorene; 3-PHE, 3-hydroxyphenanthrene; 4-PHE, 4-hydroxyphenanthrene；

47

8-OHdG, 8-hydroxy-deoxyguanosine;

48

aminotransferase; ALP, alkaline phosphatase; ANOVA, analysis of variance; AST, aspartate

49

aminotransferase; BMI, body mass index; CV, coefficient of variance; GGT, gamma-glutamyl

50

transpeptidase; MDLs, method detection limits; OH-PAH, hydroxylated polycyclic

51

aromatic hydrocarbon; PAH, polycyclic aromatic hydrocarbon; PCA, principal component

52

analysis; QC, quality control；RSD, relative standard deviation; SPE, solid phase extraction;

53

HPLC-MS/MS, high performance liquid chromatography-tandem mass spectrometry.

9-PHE, 9-hydroxyphenanthrene;

54 55 56 1


ALT, alanine

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ABSTRACT

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Manual collection and open-air incineration of waste materials is a common

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practice in rural regions of China and beyond. Low-temperature combustion of rubber

60

and plastic waste generates high levels of airborne polycyclic aromatic hydrocarbons

61

(PAHs). We investigated ten urinary hydroxylated PAH metabolites (OH-PAHs), the

62

oxidative damage biomarker (8-hydroxy-deoxyguanosine, 8-OHdG), and four serum

63

biomarkers

64

aminotransferase (ALT) in 41 waste collectors and 122 control subjects residing in the

65

same or a distant rural village in Henan Province. The level of PAH metabolites in

66

urine (median: 17.24 μg/g Cre) was twice that of controls living in the same area

67

without an occupational history involving waste collection (median: 8.16 μg/g Cre)

68

and thrice that of controls living 30 km away (median: 6.07 μg/g Cre). The

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concentrations of OH-PAHs were positively associated with urinary 8-OHdG levels

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(β=0.283, p < 0.05). Serum GGT and ALT were slightly increased in waste collectors.

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Urinary 8-OHdG levels were similar in one-year and longer-term workers, suggesting

72

that rubber and plastic waste collection/incineration carries a high PAH exposure risk.

73

These data provide solid baseline information, emphasizing the importance of

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monitoring the long-term health outcomes of waste collectors and changes in

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exposure patterns associated with rural development and regulation of waste disposal.

including

gamma-glutamyl

transferase

(GGT)

and

alanine

76 77

Key words: Waste collectors; developing area; China; Polycyclic Aromatic

78

Hydrocarbons; metabolites

79 80 81 82 83 84

1



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85 86

Introduction

87

Domestic and commercial solid waste is a threat to public health and the environment if

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it is not stored, collected, and disposed of correctly. The separation, sorting and recycling of

89

solid waste is practiced to different degrees in high-income countries and major Chinese cities.

90

1

91

Since such waste collection methods require no professional training, they are adopted by

92

low-income communities. 3 To some extent waste collection has become an emerging career. 2

93

Manual collection of waste is often aimed at the post-collection separation and recycling of

94

specific and sporadic materials, such as electronic waste (E-waste) 4, scrap metal,

95

clothing and shoes, and rubber and plastics.

96

prolonged engagement with processing E-waste

97

exposure to hazardous pollutants with potential adverse health effects, including tumors and

98

cardiovascular diseases.

99

involved in rubber and plastic industry.

However, in rural areas of China, manual collection of total waste is widely practiced.

10

6-8

5

2

paper,

Previous studies have demonstrated that 9

and scrap metal

5

results in repeated

Few studies have focused on the health status of waste recyclers

100 101

Waste collectors play a key role in the separation, collection and utilization of all

102

reusable rubber and plastic waste. 8 Relatively primitive technologies are employed to harvest

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reusable components while useless parts are mainly disposed of in landfills. 6 In recent years,

104

local Chinese government agencies have regulated to stop waste landfill to prevent migration

105

of pollutants from the waste to groundwater and soil. 11-12 However, without effective methods

106

to dispose of non-recyclable components, waste collectors in rural areas have resorted to

107

burning the refuse in their own backyards. Crude methods of incineration are well known to

108

generate harmful air pollutants that not only contaminate the environment13 but also pose

109

significant health hazards, most especially to the waste collectors. 14-15

110 111

Incineration of solid waste materials such as rubber and plastic generates a variety of 6, 16

112

complex pollutants.

113

from the incomplete combustion or pyrolysis of solid waste. Studies have demonstrated that

Notably, polycyclic aromatic hydrocarbons (PAHs) are generated

1


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17

114

PAHs composition varies with respect to different combustion sources and conditions.

115

lower temperature and oxygen-starved conditions caused by backyard open burning of

116

residential solid waste may result in incomplete combustion and increased PAHs emission. 18

117

Coke-oven workers and pavement workers are typical PAHs-exposed occupational

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populations that experience high rates of oxidative DNA damage, 19-20 organ injuries, 21-22 and

119

an increased risk for many types of cancers, including lung, 23 gastric, 24 skin, lymphatic, and

120

hematopoietic. 25

The

121 122

The present study investigates PAH residues in waste collectors engaged in rubber and

123

plastic garbage recycling in Shenqiu, an impoverished county of Henan, China. We measured

124

ten OH-PAHs, 8-hydroxy-deoxyguanosine (8-OHdG), and serum liver function biomarkers to

125

evaluate the body PAHs burden of waste collectors. We also evaluated the influence of

126

smoking, source risk distance and the working period during which incineration-related PAHs

127

exposure would occur. Our results provided solid evidence of elevated PAHs exposure that

128

could portend future health effects, especially among collectors of rubber and plastic waste.

129 130

Materials and methods

131

1-Hydroxynaphthalene

(1-NAP),

2-hydroxynaphthalene

(2-NAP),

132

9-hydroxyphenanthrene (9-PHE), and 1-hydroxypyrene (1-PYR) were obtained from Dr.

133

Ehrenstorfer (Augsburg, Germany). 3-Hydroxyfluorene (3-FLU), 13C6-3-PHE (98%, 50µg/mL

134

in methylbenzene), D9-2-FLU (95 %), D8-2-NAP (96%), and

135

supplied by Cambridge Isotope Lab (Andover, MA, USA). 2-Hydroxyfluorene (2-FLU),

136

2-hydroxy-phenanthrene (2-PHE), 3-hydroxyphenanthrene (3-PHE), 4-hydroxyphenanthrene

137

(4-PHE), and 1-hydroxyphenanthrene (1-PHE) were purchased from Toronto Research

138

Chemicals (Toronto, Canada). β-Glucuronidase/arylsulphatase from Helix pomatia (5.5/2.6

139

U/mL) was obtained from Sigma (St. Louis, MO, USA). 8-OHdG kits were purchased from

140

TSZ Biological Trade Co., Ltd (San Francisco, CA, USA). Methanol (LC-MS,

141

chromatographic grade, ≥99.9%) was purchased from Fluka (St. Louis, MO, USA). All other

142

reagents were of analytical grade.

1


13

C6-1-PYR (98%) were


143 144

Water was supplied by Milli-Q Integral Water Purification System for Ultrapure Water

145

(MilliporeSigma, Burlington, MA, USA). Solid phase extraction (SPE) cartridges (Bond Elut

146

C18, 500 mg, 6 mL) were obtained from Agilent (Santa Clara, CA, USA). An Eclipse XDB

147

C18 column (100*2.1 mm, 3.5 µm, Agilent, Santa Clara, CA, USA) was used to measure

148

multiple OH-PAHs simultaneously.

149 150

Study population and sample collection

151

The study was approved by the Ethical Review Board of the School of Public Health,

152

Fudan University, Shanghai, People’s Republic of China (IRB00002408, FWA00002399;

153

approval number IRB#2013-03-0418).

154 155

Research was carried out in July 2016 in two randomly selected large villages in Shenqiu

156

County, Henan. According to the on-site survey involving about randomly selected 10% of

157

the residents, people who engaged in rubber and plastic recycling were initially identified and

158

then household survey were conducted to confirm their occupation status. Forty-one active

159

waste collectors were enrolled, and two control groups (N=122) were matched by age and

160

gender. Non-waste collectors lived in the waste treatment area (Control # 1, N=82) or in a

161

village 30 km away that was not involved in waste collection/incineration (Control # 2, N=40).

162

All consented participants (N=163) completed a questionnaire to collect socio-demographic

163

data (age, gender, education, family income, work experience, and working time), physical

164

(medical record and body mass index (BMI)) and lifestyle information, including cigarette

165

smoking and alcohol drinking status. Individuals who have ever smoked at least 1 cigarette

166

per day for 1 year were defined as smokers; otherwise, study participants were considered as

167

non-smokers.

168

were reclassified as non-smokers. 26 Individuals who had drunk alcoholic beverages less than

169

once a week for less than 1 year were defined as non-drinkers; otherwise, they were

170

considered as drinkers. We excluded individuals on long-term medication or who had been

171

diagnosed with hepatitis B infection.

Among smokers, those who had stopped smoking for more than five years

172 1


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Blood and morning first urine samples (fasting time > 8h) from all participants were

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collected on the same day. First, blood biomarkers and urinary creatinine (Cre) were all

175

assayed immediately with the help of the local analysis laboratory (Shenqiu County Center

176

for Disease Control & Prevention). Then, the remaining biosamples were placed on dry ice,

177

transported to Fudan University, Shanghai, where they were stored at -80℃ prior to analysis.

178

Urinary creatinine was determined by the Jaffe method

179

concentration of target compounds and urinary 8-OHdG.

27

to normalize the urinary

180 181

PAH metabolite analysis

182

Urinary OH-PAHs were prepared and analyzed with some modification according to the 28

183

method of Fan and colleagues.

184

isotope-labeled internal standards, then 3.0 mL acetate buffer (pH=5.0) and 20 µL

185

β-glucuronidase / arylsulphatase added and incubated overnight at 37℃. Hydrolyzed samples

186

were extracted using SPE cartridges. The target analytes eluted by methanol were

187

concentrated to 500 µL. Sample analysis was carried out with a 1260 high performance liquid

188

chromatography system (HPLC; Agilent, USA) coupled with a 6460 mass spectrometer

189

(MS/MS, Agilent, USA). The mobile phases were water as solvent A and methanol as solvent

190

B. The gradient elution program was set as follows: 0-4 min, 45-65% solvent B; 4-8 min,

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65-85% solvent B; 8-12 min, 85-95% solvent B, 12-15 min, 95% solvent B; 15 min-15.10

192

min 95-45% solvent B. The flow rate was 0.4 mL/min, and the column temperature was set at

193

40℃. The injection volume was 10 µL. An artificial urine pool spiked with low levels of

194

analytes was measured, and for each analyte, a signal-to-noise ratio (S/N = 3) response of

195

LC-MS/MS was used to calculate method detection limits (MDLs) for all ten OH-PAHs

196

measured in a range of 0.010-0.060 ng/L. The optimized MS/MS parameters and detailed data

197

for each chemical can be found in Table S1 and Table S2.

Briefly, 5.0 mL urine sample were spiked with

198 199

Quality control

200

All regression coefficients (R2) of calibration curves for each analyte were above 0.999.

201

The intra-day and inter-day variability was determined by calculating repeated measurements

202

of quality control (QC) samples. The coefficient of variance (CV) range was 2.1-13.2%, 1



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203

which reflects the precision of the method. Recoveries for all of the analytes were between

204

80-120%. To detect the stability of the method, QC samples (0.03-0.6, 2-10, 5-40 μg/L) were

205

analyzed following each batch of 10 samples; the CV was < 15%. Methanol was used for

206

blanks and run according to exacting standards. In addition, to evaluate the precision and

207

accuracy of the real sample analysis, 10% of the real urine samples in each batch were

208

analyzed for PAHs metabolites in separate batches and the relative percentage difference was

209

in a range of less than ±20%.

210 211

Determination of urinary 8-OHdG

212

Levels of 8-OHdG in urine were measured with an enzyme-linked immunosorbent assay

213

kits. Before analyses, the frozen urine samples were thawed and centrifuged at 10000 rpm for

214

5 min. The supernatant was collected for the measurement according to the instruction

215

provided with the kit.

216 217

Liver function test

218

Serum separated from blood samples was processed for the analysis of γ-glutamyl

219

transpeptidase (GGT), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and

220

aspartate aminotransferase (AST) using methods approved by the International Federation of

221

Clinical Chemistry and Laboratory Medicine (Milan, Italy).

222

Roche Diagnostics and analysis was performed with a Roche Cobas 702 analyzer (Roche

223

Diagnostics, Mannheim, Germany). Samples were analyzed after instrument standardization

224

with the help of calibrators and quality controls. The reference values in China are given in

225

Table S3.

29

The kits were supplied by

226 227

Risk-distance model

228

A risk-distance model was developed to evaluate the distance of subjects in Control # 1

229

from exposure sources, namely the family-based workshops engaged in waste recycling and

230

incineration. A wind rose map of the seasonal wind direction for the source localities was

231

obtained from the Henan Provincial Meteorological Bureau and used for reference. The

232

distance between the location of each participant in Control # 1 and the exposure source was 1


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calculated, and the median distance for the whole group was chosen to represent the risk

234

distance. The association between exposure and sources was analyzed by Loess regression.

235 236

Statistical analysis

237

Statistical analysis was performed using SPSS 22.0. For concentrations of OH-PAH below

238

the MDLs, we used a value of MDLs/2. Data were log-transformed for normalization.

239

Differences between the three groups were analyzed by one-way ANOVA. Difference

240

between two groups was evaluated by the Student t-test (for continuous variables) and

241

Chi-square test (for categorical variables). Pearson correlation coefficients were used to

242

evaluate associations between different variables.

243 244

Modeling was performed by principal component analysis (PCA) to extract the major

245

variance in relation to waste-collection exposure and smoking. The associations between

246

PAHs exposure and oxidative damage levels were evaluated by multivariate linear regression

247

models, with adjustment for age, gender, BMI and smoking status. Two-sided p < 0.05 was

248

considered statistically significant.

249 250

Results

251

2.1 Demographic characteristics

252

Demographic characteristics of the waste collectors and non-waste collectors from two

253

control groups (Control #1 and Control #2) are shown in Table 1. No significant difference (p >

254

0.05) was observed among the three groups for age, sex, BMI, and lifestyle-related factors

255

(smoking and drinking status). Most of the waste collectors and controls were middle-aged

256

adults with a very low education level (> 70% with only primary school education), and

257

approximately half were tobacco smokers or alcohol drinkers. The annual income level of

258

waste collectors was higher than that of the other groups (p < 0.001). Waste collectors had

259

been engaged in this occupation for only a few years. All waste collectors engaged only in

260

rubber and plastic collection and disposed of useless components by open incineration.

261

Table 1 to be inserted here

262 1



263

2.2 Body PAH burden

264 265

The concentrations of ten urinary PAH metabolites were significantly higher in waste

266

collectors than those in the other two groups (all p < 0.05) (Fig. 1). In the control groups,

267

almost all OH-PAHs were significantly higher in smokers than non-smokers (except 1-NAP in

268

Control # 1).

269

Fig.1 to be inserted here

270 271

The concentrations of urinary ΣOH-PAHs (sum of 10 OH-PAHs) in waste collectors

272

ranged from 4.48 μg/g Cre to 69.46 μg/g Cre, with a median value of 17.24 μg/g Cre, which

273

was significantly higher than those in the other two control groups (Fig.1, p < 0.05). When

274

evaluating the influence of smoking on PAH exposure, significant differences in urinary

275

ΣOH-PAHs (p < 0.05) were found between smokers and non-smokers in both control groups.

276

For the group of waste collectors, however, no significant difference could be found by

277

smoking status. In addition, significant gender-related difference in median urinary

278

ΣOH-PAHs (males vs. females = 8.58 vs. 6.73 μg/g Cre) was observed when the entire data

279

from all non-occupational participants were collectively analyzed; by contrast, this pattern

280

was not observed for waste collectors (males vs. females = 19.19 vs. 16.01 μg/g Cre, Fig. S1).

281 282

Among all individual OH-PAH concentrations (Table S4), the highest value was found

283

for ΣOH-NAPs (1-NAP, 2-NAP), which accounted for 61.77% of the total OH-PAHs. This

284

value was followed, in decreasing order, by OH-PYR (1-PYR), OH-PHE (2&3 PHE, 1&9

285

PHE, 4-PHE), which accounted for 13.52% and 14.56% respectively, and OH-FLUs (2-FLU,

286

3-FLU), the contribution of which was only 6.50%.

287 288

PCA was conducted to identify urinary OH-PAHs most specific to occupational exposure.

289

Two principal components (PC) together explained 69% of the total variance based on a Scree

290

Plot. Among urinary OH-PAHs, urinary metabolites of PHE (2&3-PHE, 1&9-PHE, 4-PHE)

291

and PYR (1-PYR) showed higher loading values on PC1 and lower loading values on PC2,

292

whereas urinary metabolites of NAP (1-NAP, 2-NAP) showed lower loading values on PC1 1


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and higher loading values on PC2 (Table S5). Interestingly, PC1 was highly and significantly

294

correlated with occupational exposure status (r = 0.482, p < 0.001), but no such trend was

295

observed with respect to smoking status (r = 0.154, p > 0.05). PC2 was highly and

296

significantly correlated with smoking status (r = 0.254, p < 0.01), while it was not related to

297

waste collection status (r = 0.09, p > 0.05).

298 299

2.3 Biomarkers

300

Urinary 8-OHdG concentration was significantly higher in waste collectors than in the

301

two control groups (p < 0.05, Table 2.). Stratification of the waste collectors group by

302

smoking and drinking status showed no influence of smoking or drinking on 8-OHdG values

303

(p > 0.05, Table 2.). Similarly, serum GGT and ALT levels were significantly higher in waste

304

collectors than in the two control groups (p < 0.05, Table 2.). Serum AST, another important

305

liver function biomarker, was somewhat elevated in waste collectors, although this was not

306

statistically significant. Additionally, GGT levels were higher in waste collectors vs. controls

307

among smokers or alcohol drinkers (p < 0.05, Table 2.).

308

The duration of work experience of waste collectors was not a sensitive factor for the

309

biomarkers when duration on the job was grouped into 1 year, 1-2 years and 2 years & above

310

(p > 0.05).

311 312

2.4 Correlation analysis

313

There was a significant positive relationship (r = 0.426, p < 0.01) between ΣOH-PAHs

314

and 8-OHdG among waste collectors. Almost all the individual OH-PAHs were correlated

315

with each other (p < 0.05), and their Pearson correlation coefficients ranged from 0.304

316

(1-NAP: 1 & 9-PHE) to 0.832 (1-NAP: 2-NAP) (Table 3.).

317 318

Table 3 to be inserted here

319 320

2.5 Exposure source and PAH level

321

The association between exposure sources and individual urinary OH-PAHs is shown in

322

Fig. 2. Based on the local wind rose diagram, the urinary ΣOH-PAHs of the control group 1 1



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323

living in the upwind area were significantly lower than those living in the downwind area (Fig.

324

2a.). When a risk distance model was built based on all the locations and occupational

325

exposure sources, results suggested ΣOH-PAHs in those non-waste collectors were negatively

326

associated with the risk distances by Loess analyses (Fig. 2b.).

327

Discussion

328

The present study shows that non-professional waste collectors in rural Henan Province

329

harbor high levels of PAHs and 8-OHdG that reflect their occupational exposure to hazardous

330

substances, most of which probably arise from airborne exposure to combustion products

331

emitted during waste incineration. Moreover, GGT and ALT, the biomarkers of liver function,

332

are significantly higher in this population relative to age- and sex-matched controls. Even

333

with only one year of service as waste collectors, urinary PAHs and 8-OHdG levels were not

334

significantly different from those of multi-year-exposed waste collectors, indicating that

335

short-term exposure to pollutants has the potential to adversely impact health. Importantly,

336

this study provides baseline information on the PAHs exposure among waste collectors, data

337

that can be used to track with time both exposure levels and health status of individuals

338

associated with this hazardous occupation.

339 340

Exposure-dose level

341

Median ΣOH-PAH levels in urine samples of waste collectors were approximately twice

342

that of the control groups. Such levels are also significantly higher than those of

343

non-occupational populations from China,

344

Non-smoking waste collectors in the present study also had a high urinary level of the PAH

345

exposure biomarker 1-hydroxypyrene (1-PYR); the median level of 1-PYR of 1.95 μg/g Cre,

346

was 65 times higher than the upper level for nonsmokers proposed by Wilhelm and colleagues.

347

33

348

from occupational PAH exposure. Waste collectors in Shenqiu who focused on rubber and

349

plastic disposal also had higher levels of urinary PAHs metabolites than traffic officers 34 and

350

bus drivers

351

suggests that rubber and plastic waste collectors have high occupational exposure to PAHs

30

USA,

31

Canada,

32

and India

30

(See Table S6).

These results demonstrated that elevated urinary 1-PYR among waste collectors originated

35

, but had slightly lower levels than some coke-oven workers.

1


19, 36-37

This

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352

and, thus, may represent a group at risk for future PAH-associated illness and disease.

353

Biomarker

354

8-OHdG is a critical biomarker for evaluating oxidative DNA damage induced by 38

18

355

different stressors.

356

receptors 39 and be metabolized by cytochrome P450 and other metabolic enzymes to generate

357

diol-epoxides, radical cations, or reactive and redox-active o-quinones, which react with DNA

358

to produce adducts and increase reactive oxygen species that cause DNA oxidative damage. 40

359

We found that 8-OHdG levels in the urine of waste collectors were significantly higher than

360

that of the control groups. The high 8-OHdG levels in waste collectors were positively

361

associated with urinary PAH metabolite levels with a dose-response relationship (β = 0.283, p

362

< 0.05, Table S7). Notably, the urinary 8-OHdG levels in one-year workers was not

363

significantly different from those of multi-year-exposed waste collectors. These findings

364

showed that even short-term occupational exposure significantly increased the body burden of

365

8-OHdG. Importantly, this is the first study to show that urinary 8-OHdG levels are not

366

correlated with the duration of occupational exposure. Stated otherwise, even short-term

367

occupational waste collection can substantially increase tissue oxidative DNA damage

368

detectable in urine. In accordance with previous studies, we found a dose-response

369

relationship between urinary 8-OHdG and PAHs, a surrogate for environmental PAH

370

exposures. 19-20

PAHs, which were major pollutants

, can activate aryl hydrocarbon

371 372

Serum GGT is also a sensitive marker of oxidative stress induced by toxic substances and 41

373

an important biomarker of liver injury.

374

its normal concentration range can be used to predict the presence and clinical outcomes of

375

cardiovascular disease, diabetes mellitus, and certain cancers.

376

also reflect the presence of chronic inflammation. Exposure to lead, cadmium, dioxin, and

377

organochlorine pesticides is associated with increased serum GGT in the general population,

378

42, 45

379

Serum ALT was also significantly higher in waste collectors than those of both control groups.

380

AST, another important biomarker of liver function showed no significant difference between

381

groups, but the level was slightly higher in the waste collectors. The stratified analysis found

Studies have demonstrated that serum GGT within

42-44

Elevated serum GGT can

and there is also significant positive correlation between exposure of PAHs and GGT.

1


46


382

that GGT was significantly affected by smoking, drinking and other factors. Taken together,

383

these enzymatic changes suggested that exposure to PAHs, smoking and alcohol may in

384

concert increase the risk of mild liver injury.

385 386

Factors influencing exposure level

387

Individual exposure level is an important factor influencing health outcome. Multiple factors

388

such as the strength of exposure source, pollution concentrations, environmental conditions and

389

the distance between pollution source 47 and individual location are associated with exposure level.

390

48

391

scale by multiple scattered family workshops. Outdoor incineration of waste materials generates

392

airborne PAHs that are inhaled both locally and at a distance. In specific areas, we found clusters

393

of families that were involved in burning waste, such that multiple sources of fumes combined to

394

increase ambient air pollution. We found that urinary OH-PAHs levels were related to the distance

395

between residence and waste incineration site(s). Residents living on the leeward side of the

396

prevailing wind direction showed higher body burdens of PAHs.

In rural areas of China, waste collection, storage and disposal are often carried out on a small

397 398

Exposure biomarker pattern analysis

399

Tobacco smoke

49

and motor vehicle exhaust

50

are important sources of exposure to

400

PAHs and many other toxic compounds that must be considered when evaluating PAHs

401

exposure. The two villages chosen for the present study are located in a developing rural area

402

of Henan with sparse motor vehicles and far from roads carrying heavy traffic typical of

403

urban areas of China. Heavy industry and other PAHs emitters are also absent. Thus, for

404

residents of the Shenqiu villages, urinary levels of PAHs metabolites are scarcely impacted by

405

vehicle exhaust and other sources of air pollution. Current tobacco smoking made little

406

contribution to urinary PAHs of waste collectors, while urinary PAHs levels in control groups

407

were associated with smoking behavior. While smoking undoubtedly contributed to the body

408

burden of PAHs exposure in waste collectors who smoked, it is small relative to that derived

409

from their occupational exposure. The main components (principal components, PC2), with

410

higher contribution of naphthalene and fluorine, were not significantly related to the

411

occupation of waste collection, but were significantly related to smoking. Since analysis of 1


Page 14 of 27

Page 15 of 27


412

tobacco smoke has shown that naphthalene and fluorine are PAH constituents in cigarette

413

smoke, and our results are consistent with those of previous studies 51, the PAHs metabolites,

414

hydrophenanthrene and hydroxypyrene, may be more specific exposure biomarkers for the

415

occupational population involved in rubber and plastic waste collection.

416 417

Waste burning produces airborne pollutants that are chemically complex and vary 17

418

according to material type, combustion temperature and oxygen levels.

419

incineration employs high combustion temperatures (> 850 degree℃) that ensure complete

420

destruction of waste organics. 52 By contrast, temperatures reached in outdoor combustion are

421

only 300-500 degrees℃.

422

at a low combustion temperature generates more PAHs. 54 To estimate differences in exposure

423

to airborne PAHs, we compared the urinary OH-PAH concentrations (percentage composition)

424

in this study with data from other studies of PAH-exposed occupational populations (see

425

Table S5). In the present study, the median urinary 1-PYR content of waste collectors was

426

about 15%, apparently higher than that of bus drivers

427

recycling area

428

waste collectors reached 14%, which is higher than that found in bus drivers (11%), residents

429

in an e-waste recycling area (3%), and jet fuel-exposed workers (4%). These results suggest

430

that the types of PAHs and their respective metabolites from rubber and plastic waste burning

431

are different from those arising from fossil fuel combustion and coal tar production. The

432

health risks associated with an increased prevalence of exposure to PAHs caused by

433

low-temperature waste burning in the general population need to be addressed. It must be

434

noted that some pollutants other than PAHs are also released by open burning, such as

435

polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs); because these chemicals

436

accumulate in the food chain, more than 90% of human exposure is via food ingestion. 57

55

53

Modern waste

Unlike fossil fuels such as kerosene and coal, solid waste burned

(6%) and jet fuel-exposed workers

56

35

(3%), residents in an e-waste

(1%). Metabolites of phenanthrene in

437 438

Since the present study was cross-sectional in design and conducted at a single point in

439

time during the summer months, there is some level of uncertainty given that multiple factors,

440

including seasonal environmental conditions, sampling time, personal lifestyle and occasional

441

events (such as celebrations with fire crackers) may influence the quality of ambient air 1



442

associated with waste combustion. However, the low mobility and similar living habits of

443

Shenqiu’s rural residents supports the reliability of the research results.

444

Taken together, the present study provides baseline data for review of environmental

445

policy; rules are needed to improve waste collection and incineration to minimize the

446

influence on the environment and population health in less developed regions of China.

447

Moreover, these data can help interpret health issues associated with the transition from rural

448

to urban environments and those associated with uncontrolled rapid industrialization resulting

449

in environmental degradation.

450

The present study shows a high PAH exposure risk among rubber and plastic waste

451

collectors in an undeveloped rural area of China. The resident Han population chosen for

452

study has ethnic/genetic homogeneity and a traditional cultural background that can be found

453

in many areas of rural China. Although the sample sizes were modest, these data can be used

454

to evaluate harmfulness, hazards, and health effects for the long term exposure to

455

contaminants from waste incineration. Of the many toxicants produced in the combustion of

456

rubber and plastics, we focused on PAHs with known carcinogenic potential to evaluate

457

pollutant exposure and potential health effects. In future studies, biomarkers that reflect

458

long-term exposure to carcinogenic substances, such as pre-mutagenic O6-methylguanine

459

DNA lesions in blood and other tissues, should be considered.

460

461

Acknowledgements

462

We thank Yi Hu, Liyun Yan, Yifan Yang, Linlin Ma, Xia Zhao, Liying Song and

463

Bingying Li for their help in sample collection. This project was supported by the Key Special

464

Project from the Chinese Ministry of Science & Technology (2017YFC1600200), grants from

465

the Chinese National Natural Science Foundation (No.81325017, No.81773379 &

466

No.81630088), the 4th Three Years Action Plan for Bureau of Health in Shanghai

467

(15GWZK0202), and a grant for Shanghai Outstanding Academic Leaders Plan. The authors

468

are grateful to three anonymous reviewers for many useful suggestions.

469 1


Page 16 of 27

Page 17 of 27


470

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602 603 604 605 606 607 608 609 610 611 612 613 614 615

Page 20 of 27

53. Lemieux, P. M. Evaluation of emissions from the open burning of household waste in barrels. EPA 1998, EPA/600/SR-97/134. 54. Hsu, W. T.; Liu, M. C.; Hung, P. C.; Chang, S. H.; Chang, M. B. PAH emissions from coal combustion and waste incineration. J Hazard. Mater. 2016, 318, 32-40. 55. Lu, S. G.; Li, Y. X.; Zhang, J. Q.; Zhang, T.; Liu, G. H.; Huang, M. Z.; et al. Associations between polycyclic aromatic hydrocarbon (PAH) exposure and oxidative stress in people living near e-waste recycling facilities in China. Environ.Int. 2016, 94, 161-169. 56. Rodrigues, E. G.; Smith, K.; Maule, A. L.; Sjodin, A.; Li, Z.; Romanoff, L.; et al. Urinary polycyclic aromatic hydrocarbon (OH-PAH) metabolite concentrations and the effect of GST polymorphisms among US Air Force personnel exposed to jet fuel. J Occup. Environ. Med. 2014, 56 (5), 465-471. 57. Organization, W. H. Dioxins and their effects on human health. World Health Organization 2016. http://www.who.int/news-room/fact-sheets/detail/dioxins-and-their-effects-on-human-health

(accessed

June 20, 2018).

616 617 618

Table 1. Demographic characteristics of the study population

619 620 621

Table 2. Oxidative and regular liver function biomarkers in different groups

622 623 624

Table 3. Pearson’s correlation coefficients between individual ΣPAHs and 8-OHdG in

625

urine samples collected from the waste collectors

626 627 628

Figure legends

629

Figure 1. Geometric mean concentrations of individual OH-PAHs in urine samples

630

collected from waste collectors (W), controls residing in the same area (C1), and controls

631

residing in a remote area (C2). Participants were stratified by occupational years or smoking

632

status, respectively. The bars indicate 95 % confidence intervals; an asterisk (*) indicates a

633

significant difference (p < 0.05)

634 1


Page 21 of 27


635 636

Figure. 2 Distance between exposure source and residence on PAHs concentrations in

637

urine. a. Living locations of the waste collectors and non-waste collectors. The background is

638

the rose map of summer wind direction and frequency for Shenqiu County, Henan Province,

639

China. The solid circles indicate the residence of non-waste collectors, and the solid triangles

640

indicate the residence of waste collectors. b. Loess regression of urinary ΣPAHs and risk

641

distance of the non-waste collectors (Control #1).

1



Page 22 of 27

Table 1. Demographic characteristics of the study population Waste collectors

Control in the same

Control in the remote p-Value

area (Control 1)

area (Control 2)

Number

41

82

40

-

Age (years)

56.93 ±11.14 a

58.84 ±11.36

58.28 ±9.87

0.597

Gender (Male/Female)

18 / 23

38 / 44

21/19

0.721

< 24

53.66

54.88

42.50

0.155

≥ 24

46.34

45.12

57.50

Smoking (Y/N)

16 / 25

33 / 49

13 / 27

0.702

Alcohol

22 / 19

38 / 44

13 / 27

0.147

≤ 6 years

73.17

80.72

82.50

0.465

7 - 9 years

24.39

16.87

17.50

≥ 9 years

2.44

2.41

5.00

≤ 440

21.95

34.94

30.00

440 - 700

12.20

34.94

25.00

700 - 1400

24.39

16.87

37.50

≥ 1400

41.46

13.25

7.50

3.71 ±1.12

-

-

6~9

-

-

BMI (kg/m2, %)

(Y/N)

Education (%)

Annual income ($, %)

Years involved in

< 0.001

Waste collection Working hours /day b a

: Mean ±S.D. Annual income was converted into U.S. dollars with an average exchange rate

of the year. b

: Working length included hours dealing with waste collection, disposal and burning.


Page 23 of 27


Table 2. Oxidative and regular live function biomarkers in different groups a 8-OHdG (µg/g)

GGT (U/L)

ALT (U/L)

AST (U/L)

ALP (U/L)

Waste collection status Waste collectors

3.65 (1.08)

22.04 (1.12)

24.72 (1.07)

26.29 (1.04)

83.12 (1.04)

Control 1

2.86 (1.06)

b

15.67 (1.11)

b

19.62 (1.04)

b

24.18 (1.03)

80.15 (1.03)

Control 2

2.82 (1.09)

c

15.92 (1.11)

c

20.06 (1.57)

c

24.50 (1.05)

86.36 (1.03)

26.39(1.04)

27.21 (1.02)

85.47 (1.04)

23.48(1.11)

25.59 (1.03)

81.33 (1.03)

20.47(1.05)

23.88 (1.03)

79.62 (1.03)

19.37(1.10)

24.53 (1.05)

83.65 (1.04)

27.03 (1.04)

28.72 (1.02)

87.58 (1.04)

23.05 (1.11)

24.54 (1.03)

79.79 (1.03)

20.07 (1.04)

24.33 (1.04)

80.73 (1.03)

19.47 (1.05)

24.25 (1.03)

83.52 (1.04)

Smoking status Waste collectors Smokers

4.20 (1.12)

31.19 (1.12)

Nonsmokers

3.28 (1.10)

16.79 (1.10)

Smokers

3.08 (1.08)

17.64 (1.13)

Nonsmokers

2.73 (1.07)

14.75 (1.21)

Yes

4.34 (1.10)

32.33 (1.13)

No

3.19 (1.12)

16.32 (1.19)

Yes

2.96 (1.07)

18.80 (1.05)

No

2.75 (1.08)

13.28 (1.07)

c

Controls

c

Alcohol drinking Waste collectors

d

Controls

d

Years involved in waste collection

≤ 1 years

4.34 (1.19)

23.98 (1.04)

27.32 (1.19)

28.21 (1.08)

74.49 (1.07)

1 - 2 years

3.69 (1.16)

17.62 (1.20)

24.39 (1.04)

25.41 (1.07)

77.93 (1.03)

> 2 years

3.52 (1.09)

23.47 (1.15)

24.82 (1.20)

26.55 (1.03)

84.64 (1.05)

a

: Geometric Mean (Standard Error)

b

: Comparison of waste collector and control 1 by one-way analysis of variance

(ANOVA), p < 0.05. c

: Comparison of waste collector and control 2 by one-way analysis of variance

(ANOVA), p < 0.05. d

: Comparison by independent sample t-test, p < 0.05



Page 24 of 27

Table 3. Pearson’s correlation coefficients between individual ΣPAHs and 8-OHdG in urine samples collected from the waste collectors

ΣPAHs 1-NAP 2-NAP

ΣPAHs

1-NAP

2-NAP

2-FLU

3-FLU

2+3PHE

1+9PHE

4-PHE

1-PYR

8-OHdG

1

.887**

.953**

.605**

.595**

.512**

.503**

.527**

.652**

.426**

1

.832**

.522**

.504**

.423**

.304

.357*

.423**

.260

1

.496**

.464**

.349*

.330*

.401**

.580**

.337*

1

.804**

.386*

.376*

.411**

.452**

.319*

1

.530**

.513**

.452**

.322*

.327*

1

.718**

.534**

.481*

.368*

1

.625**

.455*

.500**

1

.475*

.330*

1

.466**

2-FLU 3-FLU 2+3PHE 1+9PHE 4-PHE 1-PYR

1

8-OHdG

* p < 0.05；** p < 0.01


Page 25 of 27


Figure 1

*

*

*

18.0 12.0 6.0 0.0

W C1 C2

W

2-NAP 12.0 9.0

*

*

*

*

6.0 3.0 0.0

W C1 C2

C2

2&3-PHE

Urinary levels ( g/g Cre)

g.

C1

W

*

*

*

*

1.2 0.8 0.4 0.0

W C1 C2

　> 2 years

18.0 12.0 6.0 0.0

C1

W

W

C C1

C2

C2

2-FLU

*

*

*

*

0.9 0.6 0.3 0.0

W C1 C2

W

C1

C2

1.6

*

*

*

*

0.8 0.4 0.0

W C1 C2

W

8.0

*

C1

C2

*

*

6.0 4.0 2.0 0.0

W C1 C2

W

C1

C2

3-FLU 1.2 1.0

*

*

*

*

0.8 0.6 0.4 0.2 0.0

W C1 C2

i.

1&9-PHE

1.2

10.0

f.

1.5 1.2

1-NAP

W

C1

C2

4-PHE 0.6 0.5

*

*

*

*

C1

C2

0.4 0.3 0.2 0.1 0.0

W C1 C2

W

1-PYR

Urinary levels (g/g Cre)

j.

≤ 2 years

24.0

h.

2.0 1.6

≤ 1 years

e.


d.


C2

C1


*


24.0

30.0

c.



30.0

ΣOH-PAHs


b.

ΣOH-PAHs


a.

3.5 2.8

*

*

*

*

2.1 1.4

Waste collectors

Smokers

Control groups

Non-smokers

0.7 0.0

W C1 C2

W

C1

C2

Figure 1. Geometric mean concentrations of individual OH-PAHs in urine samples collected from waste collectors (W), controls residing in the same area (C1), and controls residing in a remote area (C2). Participants were stratified by occupational years or smoking status, respectively. The bars indicate 95% confidence intervals; an asterisk (*) indicates a significant difference (p < 0.05). ACS Paragon Plus Environment

Figure 2 Shenqiu, Henan


Page 26 of 27

N b.

E

Urinary levels of ΣOH-PAHs (μg/g Cre)

a.

100 m Risk distance (m) Figure 2. Distance between exposure source and residence on ΣPAHs concentrations in urine. a. Living locations of the waste collectors and nonwaste collectors. The background is the rose map of summer wind direction and frequency for Shenqiu County, Henan Province, China. The solid circles indicate the residence of non-waste collectors, and the solid triangles indicate the residence of waste collectors. b. Loess regression of urinary ΣPAHs and ACS Paragon Plus Environment

risk distance of the non-waste collectors (Control #1).

Page 27 of 27



Heavy exposure of waste collectors to polycyclic aromatic

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