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Phthalate levels and related factors in children aged 6–12 years
Environmental Pollution xxx (2016) 1e7
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Phthalate levels and related factors in children aged 6e12 years* Wei Wu a, Feng Zhou b, Yue Wang b, Yong Ning a, Jian-Ye Yang c, *, Yi-Kai Zhou b, ** a
School of Laboratory Medicine, Hubei University of Chinese Medicine, 1 Huangjia Lake West Road, Wuhan 430065, China MOE Key Laboratory of Environment & Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China c Institute of Clinical Medicine, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 August 2016 Received in revised form 13 November 2016 Accepted 16 November 2016 Available online xxx
Although previous studies showed that children are widely exposed to phthalates, the sources of phthalate exposure for school-aged children in China are not well understood. This study aimed to assess phthalate metabolite levels and explore the factors influencing exposure in children. We collected demographic data and biological samples from 336 children aged 6e12 years. We calculated urinary concentrations of 14 mono-phthalate metabolites and conducted chi-square (c2) tests and logistic regression analysis to determine the variables associated with phthalate levels. Mono-n-butyl phthalate (MnBP) and mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were the most abundant urinary phthalate metabolites. In addition, housing type, decorating materials in the home, and frequency of canned food consumption were associated with exposure to low molecular weight phthalates. Water source, duration of time spent playing with toys, residential area, and frequency of canned food consumption were associated with exposure to high molecular weight phthalates. Based on these results, potential strategies to reduce exposure to phthalates include avoiding plastic food containers and chemical fragrances as well as eating fewer processed foods, especially canned foods, and foods in plastic packaging. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Phthalate metabolite Relate factors School-aged children
1. Introduction Phthalate esters (PAEs), which are synthetic chemicals, are ubiquitous environmental contaminants (Myridakis et al., 2015). As such, they have been identified as global pollutants and have received increasing public attention in recent years (Liu et al., 2016). Many consumer products contain specific members of this family of chemicals (Zhang et al., 2014), including cosmetics, clothing, nutritional supplements, pharmaceuticals, dentures, medical devices, children's toys, glow sticks, modeling clay, automobiles, food packaging, cleaning materials, waxes, insecticides, and lubricants (Johns et al., 2015; Kim et al., 2011). In general, high molecular weight phthalates (HMWP; metabolites >250 Da), such as di-2-ethylhexyl phthalate (DEHP), benzylbutyl phthalate (BzBP), di-isononyl phthalate (DiNP), and di-n-octyl phthalate (DnOP), are
*
This paper has been recommended for acceptance by Eddy Y. Zeng. * Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (J.-Y. Yang), [email protected] (Y.-K. Zhou).
primarily used in the production of polyvinyl chloride (PVC) (Smarr et al., 2015; Tellez-Rojo et al., 2013). Low molecular weight phthalates (LMWP), such as dimethyl phthalate (DMP), diethyl phthalate (DEP), and dibutyl phthalates (DBP), are often used in personal care products (Specht et al., 2014). Because phthalate plasticizers are not chemically bound to PVC, they can leach, migrate, or evaporate into indoor air and the atmosphere, foodstuffs, and other materials (Upson et al., 2013; Van Holderbeke et al., 2014). Therefore, phthalates are detected not only in consumer products but also in food and the indoor environment, including the air and dust (Van Holderbeke et al., 2014; Wang et al., 2013). As a result, humans are exposed through ingestion, inhalation, and dermal exposure throughout their entire lifetime, including during intrauterine development (Sakhi et al., 2014). Children, especially those of school age, are exposed to phthalates more extensively and at higher levels than adults (Shi et al., 2015). Phthalate diesters are rapidly metabolized after exposure, and metabolites of phthalate compounds are found almost universally in human urine and have been detected in amniotic fluid (Zhu et al., 2016). Higher urinary phthalate metabolite levels are generally measured in children than in adolescents and adults, which could
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
be related with more frequent exposure to toys and canned food containing phthalates (Gao et al., 2016). In addition, the mouthing behaviors of infants and children can lead to additional phthalate intake. Past human studies have linked early-life phthalate exposure with altered neurological development, childhood allergies, and decreased anogenital distance in boys (Shi et al., 2012). Several phthalate metabolites exhibit anti-androgenic activity, and there is evidence that some developmental endpoints vary by sex (Chen et al., 2013). Phthalate exposure in early development and even preconception can adversely affect an individual's health long after childhood. Therefore, exposure to PAEs during childhood development affects the health of not only children but also the entire society (Mieritz et al., 2012; Mouritsen et al., 2013). However, there has been very little research on phthalate levels and related factors in China, and research is urgently needed. The specific aims of the present study were to assess the exposure to PAEs, by measuring their metabolites in urine samples from children aged 6e12 years, and to investigate the factors that influence phthalate exposure in children. 2. Materials and methods 2.1. Study population In this cross-sectional study, data were collected from January 2014 to July 2014 in Shiyan (101 790 N, 32 650 E) western Hubei Province, central China. Children aged 6e12 years, who were residents of the region and attended school, underwent thorough clinical examinations. Children with liver disease, blood disorders, inherited diseases, or hormone diseases were excluded. The Human Ethical Committee of the National Health Research Institutes in China approved the study. Each of the participants' parents/ guardians provided written, informed consent at enrollment. 2.2. Urine sampling Each child collected the total volume of their first morning urinary void in 750 mL polyethylene containers, which were prewashed in 10% nitric acid (>3 h) and rinsed twice in purified water. At the schools, field workers stored the urine samples in a cooler (4 C) and checked the questionnaires for missing answers. The filled urine container was weighed in the laboratory, and two 2-mL urine samples were transanalytes. None of the containers showed contamination during the washing procedure or from excretion from the container material. 2.3. Survey instrument We used a self-administered questionnaire, which was developed based on a previous questionnaire used in the US, Peru, and Congo and further adapted to the setting in China (Bai et al., 2016). Prior to use, the questionnaire was reviewed by a team of six child health experts to assess the relevance and wording of the questions as well as accuracy of the translation into Chinese. Then, the questionnaire was pilot tested with 20 children to ensure that the questions were clear and understandable to all participants. A strict and standardized quality assurance/quality control procedure was used during the entire process. The questionnaire was divided into three sections: sociodemographic information, living conditions, and children's lifestyle. Socio-demographic information included gender (boy or girl), residential area (urban or rural), age, maternal education (college degree, high school, or middle school or below), paternal education, maternal occupation (farmer, worker, professional), paternal
occupation (farmer, worker, professional), maternal use of hair dye in the home (yes or no), parental smoking inside (none, 1e10, or >10 cigarettes), and total annual household income (<$3,000, $3000e8,000, or >$8000). Living conditions included housing type (roughcast houses, brick-wood structure, or reinforced concrete), domestic fuel type (wood, coal, or gas), decorating materials (bricks, wall paints, or tiles), residence close to the road (yes or no), and average housing area (<10, 10 to <30, or 30 m2). Children's lifestyle information included outside activity duration (<1, 1 to <2, or 2 h), duration of time playing with toys (<1, 1 to <2, or 2 h), frequency of dairy product consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of puffed food consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of canned food consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of wrapping food in plastic (none, sometimes, or frequently), and water source (tap water, well water, or pond water). Considering that children stay with their parents, we went to each selected home several times to ensure that all eligible children from the school had the opportunity to be invited to participate in the survey, with the aim of collecting more representative data. Questionnaires were distributed to the children by postgraduate students. To accurately assess the factors related with children's phthalate levels, participants and their parents were asked to respond without referring to the literature or consulting others. Additionally, children and their parents were asked to provide written commitment not to disclose the questions to their neighbors when they signed the written informed consent. 2.4. Exposure assessment Urinary phthalate and creatinine concentrations were measured at the Department of Institute of Clinical Medicine, Renmin Hospital, Hubei University of Medicine, Shiyan. The following phthalate metabolites were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS): monomethyl phthalate (MMP), monoethyl phthalate (MEP), monoisobutyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), monobenzyl phthalate (MBzP), mono(carboxyoctyl) phthalate (MCOP), mono-(3-carboxypropyl) phthalate (MCPP), mono-n-octyl phthalate (MOP), mono-cyclohexyl phthalate (MCHP), mono-isononyl phthalate (MiNP), mono (2-ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-(2-ethyl5-oxohexyl) phthalate (MEOHP). Mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) was analyzed using isotope dilution LC-MS/MS with preceding enzymatic deconjugation followed by automatic solid-phase extraction. The following solvents were used for LC separation: A, 0.1% acetic acid in acetonitrile and B, 0.1% acetic acid in water. Solvent programming involved 0.0e2.0 min, 10% B; 17.0 min, 25% B; 21 min, 30% B; 23 min, 60% B; 25 min, 70% B; 27 min, 90% B; and 32 min, 10% B. For all analytes, good separation was obtained with a retention time on the column of 6.68e27.22 min. The analysis quality was checked using chemical blank samples and an in-house quality control in all of the sample batches that were analyzed. The inter-day variation, expressed as the relative standard deviation (RSD), was <10.0% for all analytes except MOP (15.2%) and MiNP (13.8%), and the recovery of spiked samples was >90.0% for all analytes except MiNP (85.6%), MOP (80.6%), and MCHP (78.6%). Values for metabolites at levels less than the limit of detection (LOD) were replaced with the LOD divided by the square root of two (Wolff et al., 2010). Urinary creatinine was determined with a creatinine kit (UCR ELISA Kit, Shanghai, China) using an automatic biochemical analyzer (ClinitekStatus, SIEMENS, Germany). Individual and summed metabolite concentrations were divided by urinary creatinine
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
Table 1 Characteristics of the participating children aged 6e12 years (n ¼ 336). Characteristic
n (%)
Gender Boys Girls Residential area Urban Rural Maternal education College degree High school Middle school or below Paternal occupation Farmer Worker Professional Maternal occupation Farmer Worker Professional Maternal use of hair dye in the home No Yes Parental smoking in the home None 1e10 cigarettes 10 cigarettes Annual household income ($) <3000 3000e8000 >8000 Housing type Roughcast Brick-wood Reinforced concrete Domestic fuel type Wood Coal Gas Decorating materials Bricks Tiles Wall paint Residence close to the road Yes No Average housing area (m2) <10 10 to <30 30 Outside activity duration (hours) <1 0 to <2 2 Time playing with toys (hours) <1 <1 to >2 2 Frequency of dairy product consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of puffer food consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of canned food consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of wrapping food in plastic None Sometimes Frequently
180 (53.6) 156 (46.4) 158 (47.0) 178 (53.0) 80 (23.4) 144 (42.9) 112 (33.3) 201 (59.8) 84 (25.0) 51 (15.3) 196 (58.4) 89 (26.4) 51 (15.3) 216 (64.4) 120 (35.6) 120 (35.6) 90 (26.7) 126 (37.7) 31 (9.3) 224 (66.7) 81 (24.1) 64 (19.2) 150 (44.5) 122 (36.3) 73 (21.8) 143 (42.6) 120 (35.6) 111 (33.1) 100 (29.8) 125 (37.1) 187 (55.6) 149 (44.4) 61 (18.1) 213 (63.4) 62 (18.5) 102 (30.6) 139 (41.2) 95 (28.2) 87 (26.0) 146 (43.5) 103 (30.6) 153 (45.3) 96 (28.7) 87 (25.9) 76 (22.7) 194 (57.4) 67 (19.9) 140 (41.6) 123 (36.6) 73 (21.8) 30 (8.8) 166 (49.5) 140 (41.7)
(continued on next page)
3
Table 1 (continued ) Characteristic
n (%)
Water source Tap water Well water Pond water
140 (41.6) 138 (40.8) 58 (17.6)
levels (mg/g) to control for urine dilution. For statistical analyses, we used volume- and creatininecorrected pollutant concentrations. Where more than one metabolite of the parent phthalate was measured, the sums of the corresponding phthalate metabolite concentrations were calculated (phthalate) by summing the concentrations of each respective metabolite. 2.5. Statistical analysis To reduce multiple comparisons, we combined the phthalate metabolites into two groups representing similar sources and similar biologic activity, based on the chain length of the parent phthalates: LMWP (MEP, MMP, MnBP, and MiBP) and HMWP (MBzP, MiNP, MnOP, MCNP, MCOP, MEPP, and SDEHP) [Supplemental Material, Table S1]. We express the sum of HMWP as the molar sum (MEHP; molecular weight 278) so that the units were the same as those of the other analytes. We considered and controlled for covariates known or suspected to be potential confounders and/or effect modifiers: gender, residential area, maternal education, paternal occupation, maternal occupation, maternal use of hair dye in the home, total household income, parental smoking inside, annual household income, housing type, domestic fuel type, decorating materials, residence close to the road, average housing area, outside activity duration (hours), time playing with toys, frequency of dairy product consumption, frequency of puffed food consumption, frequency of canned food consumption, frequency of wrapping food in plastic, and water source. We divided each phthalate metabolite into quartiles and then combined the two middle quartiles to create three categories: low (25th percentile), moderate (25e75th percentile), and high (75th percentile). For preliminary analysis of the differences between each variable, we conducted chi-square (c2) analyses (Zeng et al., 2014), stratified by each major potential effect modifier and confounder. Then, logistic regression analyses were performed to examine the associations between the individual-level dependent variable and independent variables, while controlling for important covariates (Valvi et al., 2015). Odds ratios (ORs) and 95% confidence intervals (CIs) are reported. PCA with varimax rotation was applied to ln-transformed urinary metabolite concentrations. MannWhitney U tests were used to compare phthalate levels between the sexes. All study aims were tested based on a two-tailed significance level of 0.05. SAS version 9.2 (SAS Statistical Institute, Inc, Cary, NC) and R v2.7 (The R Foundation for Statistical Computing, Vienna, Austria) were used for all data manipulation and statistical analysis. 3. Results and discussion 3.1. Demographic characteristics Of the 358 children that were enrolled, 22 children were excluded for missing variables or urine samples, resulting in 336 children aged 6e12 years with complete information (180 boys and
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
156 girls). The median age was 9.2 years, and 47% were from urban areas. Most of the participants (66.7%) had an annual household income of $3000e8000. Maternal education was primarily a high school education (42.9%). Farming represented the majority of maternal (58.4%) and paternal (59.8%) occupations. Only a small proportion of participants consumed dairy products (25.9%), puffer food (19.9%), or canned food (21.8%) 1e2 times a day [Table 1]. 3.2. Phthalate metabolite distributions The distributions of the 14 phthalate metabolites concentrations are presented in Table 2. MnBP, MEHP, and MEHHP were detected in all samples. The remaining phthalates were found in 85% of the samples, except MCHP, MiNP, and MOP, which were above the LOD in <46.8%, 58.5%, and <55.6% of the samples, respectively. MnBP (geometric mean, 60.0 mg/L) and MEHHP (geometric mean, 42.4 mg/ L) were the most abundant PAEs in urine. Strong correlations were observed between MEOHP, MEHP, and MEHHP, which are oxidative metabolites of DEHP (all rs > 0.85, all P < 0.01) [Supplemental Material, Table S2]. MBzP and MEHP concentrations were moderately correlated with MnBP concentrations (rs ¼ 0.65 and 0.49, Table 2 Distribution of urinary phthalate metabolite concentrations for 336 children aged 6e12 years, reported as uncorrected (ng/mL) and specific gravity (SG)-corrected values (mg/g). Phthalate metabolite
LOD
>LOD (%)
Percentile GM
25
50
75
95
MMP SG-corrected MEP SG-corrected MiBP SG-corrected MnBP SG-corrected MBzP SG-corrected MCOP SG-corrected MCPP SG-corrected MOP SG-corrected MCHP SG-corrected MiNP SG-corrected MEHP SG-corrected MECPP SG-corrected MEHHP SG-corrected MEOHP SG-corrected P 4.8P SG-corrected P 68. SG-corrected P 61.8 SG-corrected
0.6
92.6
0.6
96.4
0.7
88.5
0.8
100
0.6
88.6
0.7
97.4
0.4
96.8
0.8
55.6
0.6
46.8
0.4
58.5
0.6
100
0.8
98.4
0.4
100
0.7
96.3
36.0 34.8 31.7 30.8 16.2 17.2 60.0 61.2 2.8 2.9 23.9 22.8 5.9 5.8 2.3 2.2 1.3 1.2 1.5 1.4 10.6 10.4 14.8 12.6 42.4 40.6 12.0 10.8 144.0 138.6 113.2 106.8 79.7 80.4
6.1 5.7 7.5 7.4 6.1 6.4 10.0 10.7 1.2 1.2 8.6 8.5 2.2 2.3 LOD LOD LOD LOD LOD LOD 3.3 3.2 6.3 5.9 9.4 8.9 4.5 4.2 62.3 59.8 63.6 64.8 35.7 34.8
18.5 17.9 14.0 13.5 10.6 10.7 34.7 33.6 2.7 2.8 20.6 21.8 5.4 5.8 1.1 1.2 LOD LOD 0.6 0.5 4.4 4.2 11.8 10.8 17.7 15.8 7.3 6.8 107.1 102.8 88.4 91.2 52.9 50.9
40.2 38.7 26.5 24.9 25.9 17.2 77.6 75.9 3.4 3.5 34.1 33.7 8.8 9.4 1.3 1.2 0.9 0.8 0.6 0.5 10.3 9.8 20.3 22.6 43.6 40.8 13.2 14.8 192.2 186.5 123.0 120.8 83.9 88.7
141.6 138.9 108.8 112.5 40.3 38.9 208.8 204.6 6.3 6.4 50.0 48.7 12.0 10.8 5.0 4.8 2.3 2.0 2.4 2.6 25.0 22.6 29.5 27.6 163.8 169.4 37.2 34.8 387.0 368.9 259.5 261.8 202.8 216.8
LOD, limits of detection; GM, geometric mean; MMP, monomethyl phthalate; MEP, monoethyl phthalate; MiBP, mono-isobutyl phthalate; MnBP, mono-n-butyl phthalate; MBzP, monobenzyl phthalate; MCOP, mono(carboxyoctyl) phthalate; MCPP, mono-(3-carboxypropyl) phthalate; MOP, mono-n-octyl phthalate; MCHP, mono-cyclohexyl phthalate; MiNP, mono-isononyl phthalate; MEHP, mono (2ethylhexyl) phthalate; MECPP, mono-(2-ethyl-5-carboxypentyl) phthalate; MEHHP, mono-(2-ethyl-5-hydroxyhexyl) phthalate; MEOHP, mono-(2-ethyl-5oxohexyl) phthalate; LMWP, low molecular weight phthalate; HMWP, high molecular weight phthalate; DEHP, di-2-ethylhexyl phthalate.
respectively). In the comparison of phthalate levels between the sexes, MEP, MnBP, and MBzP levels were significantly higher in boys (P < 0.001), and MEHHP levels were significantly lower in boys (Supplemental Material, Table S3). These results differ from the lack of statistically significant differences between the sexes in studies with children 8e13 years of age in Mexico and children 6e8 years of age in New York City (Lewis et al., 2013; Teitelbaum et al., 2012). In the present study, MnBP concentrations were the highest (geometric mean, 60.0 mg/L), similar to the findings of previous studies, in which the geometric mean MnBP concentrations were 67.0 ng/mL (Gao et al., 2016) and 61.2 ng/mL (Guo et al., 2011a); this could be related with the wide use of DBP. In the present study, the P geometric mean total phthalate metabolite level ( DEHP) was 79.7 ng/mL, which was the highest of the phthalate metabolites; MnOP concentrations were the lowest, which is similar to the findings in a study with Austrian children aged 6e15 years (not detected (nd)-2.3 ng/mL) (Hartmann et al., 2015), perhaps because of the less frequent use of DnOP and the ready degradation (Upson et al., 2013). The urinary MEHP concentrations (10.4 mg/g) were similar to previously reported urinary levels in Korea (11.4 mg/g) (Kim et al., 2014) and for Chinese children aged 8e11 years (11.4 mg/ g) (Wang et al., 2015a,b,c). However, the levels of some phthalate metabolites, especially MEHHP (geometric mean, 40.6 mg/g), seem to be higher than those reported for children in Germany aged 8e10 years (14.3 mg/g) (Kasper-Sonnenberg et al., 2014) and Canada aged 6e11 years (19.99 mg/g) (Arbuckle et al., 2016). This might indicate an increase in phthalate exposure in China over the years (Guo et al., 2011b). 3.3. Factors influencing lower phthalate metabolite exposure Based on the c2 tests, the following variables were significant for MMP distribution: residential area (c2 ¼ 12.78, P ¼ 0.002), maternal occupation (c2 ¼ 12.53, P ¼ 0.05), housing type (c2 ¼ 12.29, P ¼ 0.002), decorating materials (c2 ¼ 18.85, P ¼ 0.004), frequency of canned food consumption (c2 ¼ 13.31, P ¼ 0.04), frequency of wrapping food in plastic (c2 ¼ 20.96, P ¼ 0.00), and water source (c2 ¼ 10.10, P ¼ 0.04) [see Supplemental Material, Table S4]. These variables were included in the logistic regression model, in which only the following two variables were significant: use of paint on the walls as a decorating material (reference, bricks; OR ¼ 6.00; 95% CI: 1.65, 21.80) and higher frequency of wrapping food in plastic (OR ¼ 3.26; 95% CI: 1.98, 10.88) [Table 3]. Of the potential variables influencing the MEP distribution, a housing type of reinforced concrete (reference, roughcast; OR ¼ 0.284; 95% CI: 0.102, 0.791) was significant in the logistic regression analysis. Based on the c2 tests, the following variables were significant for MnBP distribution: residential area (c2 ¼ 43.82, P ¼ 0.000), total annual household income (c2 ¼ 14.49, P ¼ 0.03), domestic fuel type (c2 ¼ 20.33, P ¼ 0.002), and decorating materials (c2 ¼ 26.38, P ¼ 0.000). These variables were included in the logistic regression model, and rural residential area (reference, urban; OR ¼ 0.084; 95% CI: 0.009, 0.861) and housing type of reinforced concrete (reference, roughcast; OR ¼ 0.28; 95% CI: 0.10, 0.79) were significant. In the analysis of the MiBP distribution, a rural residential area (reference, urban; OR ¼ 0.24; 95% CI: 0.21, 0.74) and maternal use of hair dye in the home (reference, no use; OR ¼ 3.25; 95% CI: 1.24, 11.58) were significant. Therefore, demographic variables and living condition may have an effect on low phthalate metabolite levels. Using paint as a decorating material can increase exposure to MMP, which is a metabolite of DMP. A survey in the United States also found that DMP is a controversial chemical in building materials and household furnishings; it can be inhaled in the form of dust particles from
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7 Table 3 Logistic regression analysis for factors associated with monomethyl phthalate (MMP). Characteristic
B
SE
MMP 1 1.36 1.62 2 1.71 1.42 Residential area a Urban 0 Rural 0.25 0.84 Maternal occupation Farmer 0 Worker 0.2 0.59 Professional 1.3 0.58 Housing type Reinforced concrete 0 Brick-wood 0.56 0.62 Roughcast 0.5 0.62 Decorating materials Wall paint 0 Tiles 0.7 0.86 Bricks 1.79 0.66 Frequency of canned food consumption 1e2 times a month 0 1e2 times a week 0.0 0.74 1e2 times a day 0.9 0.93 Frequency of wrapping food with plastic None 0 Sometimes 0.8 0.82 Frequently 1.18 0.62 Water source Tap water 0 Well water 0.7 0.70 Pond water 1.2 0.88
c2
P
0.70 1.46
0.40 0.23
0.09
0.77
1.28 (0.25, 6.66)
0.13 5.08
0.71 0.02
0.81 (0.25, 2.58) 0.27 (0.09, 0.84)
0.81 0.77
0.37 0.38
1.76 (0.52, 5.97) 0.58 (0.17, 1.95)
0.68 7.41
0.41 0.01
0.49 (0.09, 2.66) 6.00 (1.65, 21.8)
0.00 1.05
0.99 0.31
0.99 (0.24, 4.19) 0.38 (0.06, 2.39)
1.02 5.01
0.31 0.03
0.44 (0.09, 2.17) 3.26 (1.98, 10.88)
1.09 1.98
0.30 0.16
0.48 (0.12, 1.90) 0.29 (0.05, 1.62)
OR (95% CI)
OR, odds ratio; CI, confidence interval; MMP, monomethyl phthalate; 0a, Referent.
sources such as vinyl flooring and upholstery (Kamrin, 2009). Under UV light irradiation of the surface of painted murals, photodegradation results in the release of 0.221e0.737 mSv/h PAEs (Barreca et al., 2014). In the present study, children living in rural areas had less MiBP and MnBP exposure than children living in urban areas. The urban areas in the present study are heavily industrialized and have considerable commercial activity. The high MnBP concentrations might have originated from contaminated vehicle and pipe (e.g., electrical poles and lampposts) run-off and infrastructure around industrial plants. As we expected, maternal use of hair dye in the home increased children's MiBP exposure. A number of personal care products and cosmetics, such as fragrances, skin lotions, nail polish, and eye shadows, contain some types of phthalates (e.g., DEP, DBP, and DiBP) that act as solvents, fixatives, or alcohol denaturization (Tian et al., 2016). Girls who use more shampoo and shower gel have marginally significantly higher urinary MnBP (P ¼ 0.06) and MiBP (P ¼ 0.06) concentrations (Chen et al., 2015). In a study of personal care products in New York, DEP and DBP in perfumes and nail polishes were generally on the order of 1000 mg/g (Guo and Kannan, 2013). By nature, hairspray and perfume are highly volatilized and have adhesive qualities, leaving residue on bathroom surfaces, which could have contributed to the high levels in the present study. 3.4. Factors influencing higher phthalate metabolite exposure Based on the c2 tests, the following variables were significant for MBzP distribution: residential area (c2 ¼ 62.33, P ¼ 0.000), total annual household income (c2 ¼ 12.29, P ¼ 0.06), time playing with toys (c2 ¼ 9.56, P ¼ 0.05), and water source (c2 ¼ 12.89, P ¼ 0.01); in the logistic regression model, 2 h playing with toys (reference, <1 h; OR ¼ 7.03; 95% CI: 1.00, 49.58) and use of well water
5
(reference, tap water; OR ¼ 3.69; 95% CI: 1.58, 8.59) and pond water (reference, tap water; OR ¼ 4.90; 95% CI: 1.66, 14.48) as the water source were significant. Based on the c2 tests, the following variables were significant for MCOP distribution: parental smoking inside (c2 ¼ 6.79, P ¼ 0.05), frequency of dairy product consumption (c2 ¼ 13.92, P ¼ 0.03), and frequency of puffer food consumption (c2 ¼ 12.17, P ¼ 0.04). These variables were included in the logistic regression model, and eating puffer food 1e2 times a day (reference, 1e2 times a month; OR ¼ 7.54; 95% CI: 1.38, 8.17) and 1e2 times a week (reference, 1e2 times a month; OR ¼ 3.52; 95% CI: 1.14, 4.36) were significant. Regarding MCPP distribution, which is another DnOP metabolite, eating canned food 1e2 times a day was significant (reference, 1e2 times a month; OR ¼ 3.36; 95% CI: 1.22, 26.66). As expected, children who frequently played with toys had greater MBzP exposure. MBzP is a metabolite of BBP, which is an important component of PVC and soft plastics that find their way into children's mouths as toys (Koniecki et al., 2011). In the present study, children who frequently consumed puffer food and canned food had greater MCOP and MCPP exposure. Phthalates can migrate into food from plasticized PVC materials such as the tubing typically used in the milking process, lid gaskets, food-packaging films, gloves used in the preparation of foods, and conveyor belts (Darbre and Harvey, 2008). A large study showed that contaminated food is the most important source of exposure to HMWP. In an assessment of phthalate contamination in canned dinners and canned mackerel fillet in tomato sauce, the estimated dietary exposure was high and dominated by DEHP and DiNP (400e500 ng/kg body weight [bw]/day), followed by BBP and DnOP (30e40 ng/kg bw/day) (Sakhi et al., 2014). Because the MCHP, MiNP, and MOP levels were below the LOD, we did not conduct analyses with these metabolites. 3.5. Factors influencing DEHP metabolite exposure Based on the c2 tests, the following variables were significant for MCOP distribution, which is a metabolite of DEHP: residential area (c2 ¼ 11.79, P ¼ 0.003), domestic fuel type (c2 ¼ 13.76, P ¼ 0.008), outside activity duration (c2 ¼ 10.65, P ¼ 0.003), and frequency of canned food consumption (c2 ¼ 14.01, P ¼ 0.03). The logistic regression model indicated that 1e2 h of outside activity (reference, <1 h; OR ¼ 0.10; 95% CI: 0.02, 0.73), >2 h of outside activity (reference, <1 h; OR ¼ 0.06; 95% CI: 0.00, 0.81), eating canned food 1e2 times a week (reference, 1e2 times a month; OR ¼ 17.67; 95% CI: 1.26, 24.75), and eating canned food 1e2 times a day (reference, 1e2 times a month; OR ¼ 32.90; 95% CI: 4.07, 26.86) were significant. Regarding the three secondary oxidized metabolites of DEHP (MEHHP, MEOHP, and MECPP), the use of coal (reference, wood; OR ¼ 0.183; 95% CI: 0.04, 0.91) and gas (reference, wood; OR ¼ 0.12; 95% CI: 0.02, 0.65) for domestic fuel were associated with MEHHP exposure. Maternal use of hair dye in the home (OR ¼ 3.37; 95% CI: 1.14, 9.95) and eating canned food (OR ¼ 8.06; 95% CI: 1.96, 33.20) were associated with MEOHP exposure. Regarding MECPP levels, the use of well water (reference, tap water; OR ¼ 3.54; 95% CI: 1.45, 8.65) and pond water (reference, tap water; OR ¼ 3.90; 95% CI: 1.32, 11.58) as the water source were significant. Frequently wrapping food in plastic was significantly associated with MEHHP levels (reference, none; OR ¼ 6.59; 95% CI: 1.41, 30.71). Our data indicate that routine outdoor physical activity could accelerate the excretion of DEHP in children. A study from Germany also supports this finding; DEHP and DiNP metabolites rapidly declined to levels 5e10 times lower than initial levels within 24 h of fasting and remained low after exercise. We also found that, of the three types of domestic fuel that we investigated (wood, coal, and
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gas), the use of natural gas was associated with less MEPP exposure. The burning of wood and coal results in thick black smoke that could contain phthalates, and children could be exposed through inhalation (Wang et al., 2016). Water is thought to be another principle route of exposure to many phthalates. In the present study, MEP, MBP, and MEOHP exposure was higher for those who drank well water or pond water than for those who drank tap water. Based on the measurement of 16 PAEs in water samples from 19 sites, the total PAE congener concentration ranged from 1.07 mg/L to 7.12 mg/L in Zhejiang province (Wang et al., 2015a,b,c). In addition, DEHP and DBP are the dominant PAEs in water treatment plants in China, contributing between 61% and 95% of the PAEs in water (Wang et al., 2015a,b,c). In the present study, people living around pond water may have placed garbage in the water, and through leaching and abrasion, PAEs could have been released, which may also help to explain the greater phthalate exposure than with tap water. In addition, food packaging materials, especially plastic bags or wraps, are contamination sources for phthalates in dairy products.
Funding This study was financially supported by the National Natural Science Foundation of China (No. 81273024). Acknowledgements The authors declare they have no actual or potential competing financial interests. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2016.11.049.
3.6. Principal component analysis For the PCA and correlation analyses, molar concentration levels were used, and the total DEHP metabolite value consisted of MEHHP, MEOHP, and MECPP concentrations (Table 4). Five factors were retained with Eigen values > 1.000 and that expressed 62.6% of the variance. Lower phthalate metabolite levels were associated with factors 1 and 3, higher phthalate metabolite levels were associated with factors 2 and 4, and the levels of the metabolites of DEHP were associated with factors 1 and 2. The phthalate relationships indicate that plastic and food packaging are a possible source. Studies conducted in Switzerland and Greece also reported that the use of consumer products and food are major influencers of phthalate exposure (Wormuth et al., 2006; Myridakis et al., 2015). 4. Conclusion Children, particularly those of school age, should be regarded as at special risk of the potential effects of phthalates on reproduction and development. In our comprehensive study, we assessed 14 phthalate metabolites in urine samples from children aged 6e12 years, which reflect the pollution of PAEs in children. In addition, we systematically analyzed the factors influencing phthalate metabolite levels [Supplemental Material, Table S5], which
Table 4 Principal component analysis: rotated component matrix and total variance explained. Component
1
2
3
4
Eigenvalue % of variance Cumulative % MMP MEP MiBP MnBP MBzP MCOP MCPP MOP SDEHP
1.192 21.360 21.360 0.424 0.755 0.681 0.556
1.477 16.410 37.771
1.177 13.073 50.844 0.532
1.058 11.761 62.604 0.216
0.599 0.280 0.878 0.582
0.279 0.301 0.584
0.461
indicated that exposure to all phthalates can be reduced by changing habits and other behaviors, such as avoiding processed foods, especially canned foods; foods wrapped in plastic; and soft plastic toys manufactured before phthalates were banned from such products as well as less frequent use of plastic containers and chemical fragrances.
0.692
Coefficients <0.200 are not presented. Rotation converged in 6 iterations. MMP, monomethyl phthalate; MEP, monoethyl phthalate; MiBP, mono-isobutyl phthalate; MnBP, mono-n-butyl phthalate; MBzP, monobenzyl phthalate; MCOP, mono(carboxyoctyl) phthalate; MCPP, mono-(3-carboxypropyl) phthalate; MOP, mono-n-octyl phthalate; DEHP, di-2-ethylhexyl phthalate.
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Phthalate levels and related factors in children aged 6e12 years* Wei Wu a, Feng Zhou b, Yue Wang b, Yong Ning a, Jian-Ye Yang c, *, Yi-Kai Zhou b, ** a
School of Laboratory Medicine, Hubei University of Chinese Medicine, 1 Huangjia Lake West Road, Wuhan 430065, China MOE Key Laboratory of Environment & Health, Institute of Environmental Medicine, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China c Institute of Clinical Medicine, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 August 2016 Received in revised form 13 November 2016 Accepted 16 November 2016 Available online xxx
Although previous studies showed that children are widely exposed to phthalates, the sources of phthalate exposure for school-aged children in China are not well understood. This study aimed to assess phthalate metabolite levels and explore the factors influencing exposure in children. We collected demographic data and biological samples from 336 children aged 6e12 years. We calculated urinary concentrations of 14 mono-phthalate metabolites and conducted chi-square (c2) tests and logistic regression analysis to determine the variables associated with phthalate levels. Mono-n-butyl phthalate (MnBP) and mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were the most abundant urinary phthalate metabolites. In addition, housing type, decorating materials in the home, and frequency of canned food consumption were associated with exposure to low molecular weight phthalates. Water source, duration of time spent playing with toys, residential area, and frequency of canned food consumption were associated with exposure to high molecular weight phthalates. Based on these results, potential strategies to reduce exposure to phthalates include avoiding plastic food containers and chemical fragrances as well as eating fewer processed foods, especially canned foods, and foods in plastic packaging. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Phthalate metabolite Relate factors School-aged children
1. Introduction Phthalate esters (PAEs), which are synthetic chemicals, are ubiquitous environmental contaminants (Myridakis et al., 2015). As such, they have been identified as global pollutants and have received increasing public attention in recent years (Liu et al., 2016). Many consumer products contain specific members of this family of chemicals (Zhang et al., 2014), including cosmetics, clothing, nutritional supplements, pharmaceuticals, dentures, medical devices, children's toys, glow sticks, modeling clay, automobiles, food packaging, cleaning materials, waxes, insecticides, and lubricants (Johns et al., 2015; Kim et al., 2011). In general, high molecular weight phthalates (HMWP; metabolites >250 Da), such as di-2-ethylhexyl phthalate (DEHP), benzylbutyl phthalate (BzBP), di-isononyl phthalate (DiNP), and di-n-octyl phthalate (DnOP), are
*
This paper has been recommended for acceptance by Eddy Y. Zeng. * Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (J.-Y. Yang), [email protected] (Y.-K. Zhou).
primarily used in the production of polyvinyl chloride (PVC) (Smarr et al., 2015; Tellez-Rojo et al., 2013). Low molecular weight phthalates (LMWP), such as dimethyl phthalate (DMP), diethyl phthalate (DEP), and dibutyl phthalates (DBP), are often used in personal care products (Specht et al., 2014). Because phthalate plasticizers are not chemically bound to PVC, they can leach, migrate, or evaporate into indoor air and the atmosphere, foodstuffs, and other materials (Upson et al., 2013; Van Holderbeke et al., 2014). Therefore, phthalates are detected not only in consumer products but also in food and the indoor environment, including the air and dust (Van Holderbeke et al., 2014; Wang et al., 2013). As a result, humans are exposed through ingestion, inhalation, and dermal exposure throughout their entire lifetime, including during intrauterine development (Sakhi et al., 2014). Children, especially those of school age, are exposed to phthalates more extensively and at higher levels than adults (Shi et al., 2015). Phthalate diesters are rapidly metabolized after exposure, and metabolites of phthalate compounds are found almost universally in human urine and have been detected in amniotic fluid (Zhu et al., 2016). Higher urinary phthalate metabolite levels are generally measured in children than in adolescents and adults, which could
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be related with more frequent exposure to toys and canned food containing phthalates (Gao et al., 2016). In addition, the mouthing behaviors of infants and children can lead to additional phthalate intake. Past human studies have linked early-life phthalate exposure with altered neurological development, childhood allergies, and decreased anogenital distance in boys (Shi et al., 2012). Several phthalate metabolites exhibit anti-androgenic activity, and there is evidence that some developmental endpoints vary by sex (Chen et al., 2013). Phthalate exposure in early development and even preconception can adversely affect an individual's health long after childhood. Therefore, exposure to PAEs during childhood development affects the health of not only children but also the entire society (Mieritz et al., 2012; Mouritsen et al., 2013). However, there has been very little research on phthalate levels and related factors in China, and research is urgently needed. The specific aims of the present study were to assess the exposure to PAEs, by measuring their metabolites in urine samples from children aged 6e12 years, and to investigate the factors that influence phthalate exposure in children. 2. Materials and methods 2.1. Study population In this cross-sectional study, data were collected from January 2014 to July 2014 in Shiyan (101 790 N, 32 650 E) western Hubei Province, central China. Children aged 6e12 years, who were residents of the region and attended school, underwent thorough clinical examinations. Children with liver disease, blood disorders, inherited diseases, or hormone diseases were excluded. The Human Ethical Committee of the National Health Research Institutes in China approved the study. Each of the participants' parents/ guardians provided written, informed consent at enrollment. 2.2. Urine sampling Each child collected the total volume of their first morning urinary void in 750 mL polyethylene containers, which were prewashed in 10% nitric acid (>3 h) and rinsed twice in purified water. At the schools, field workers stored the urine samples in a cooler (4 C) and checked the questionnaires for missing answers. The filled urine container was weighed in the laboratory, and two 2-mL urine samples were transanalytes. None of the containers showed contamination during the washing procedure or from excretion from the container material. 2.3. Survey instrument We used a self-administered questionnaire, which was developed based on a previous questionnaire used in the US, Peru, and Congo and further adapted to the setting in China (Bai et al., 2016). Prior to use, the questionnaire was reviewed by a team of six child health experts to assess the relevance and wording of the questions as well as accuracy of the translation into Chinese. Then, the questionnaire was pilot tested with 20 children to ensure that the questions were clear and understandable to all participants. A strict and standardized quality assurance/quality control procedure was used during the entire process. The questionnaire was divided into three sections: sociodemographic information, living conditions, and children's lifestyle. Socio-demographic information included gender (boy or girl), residential area (urban or rural), age, maternal education (college degree, high school, or middle school or below), paternal education, maternal occupation (farmer, worker, professional), paternal
occupation (farmer, worker, professional), maternal use of hair dye in the home (yes or no), parental smoking inside (none, 1e10, or >10 cigarettes), and total annual household income (<$3,000, $3000e8,000, or >$8000). Living conditions included housing type (roughcast houses, brick-wood structure, or reinforced concrete), domestic fuel type (wood, coal, or gas), decorating materials (bricks, wall paints, or tiles), residence close to the road (yes or no), and average housing area (<10, 10 to <30, or 30 m2). Children's lifestyle information included outside activity duration (<1, 1 to <2, or 2 h), duration of time playing with toys (<1, 1 to <2, or 2 h), frequency of dairy product consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of puffed food consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of canned food consumption (1e2 times a month, 1e2 times a week, or 1e2 times a day), frequency of wrapping food in plastic (none, sometimes, or frequently), and water source (tap water, well water, or pond water). Considering that children stay with their parents, we went to each selected home several times to ensure that all eligible children from the school had the opportunity to be invited to participate in the survey, with the aim of collecting more representative data. Questionnaires were distributed to the children by postgraduate students. To accurately assess the factors related with children's phthalate levels, participants and their parents were asked to respond without referring to the literature or consulting others. Additionally, children and their parents were asked to provide written commitment not to disclose the questions to their neighbors when they signed the written informed consent. 2.4. Exposure assessment Urinary phthalate and creatinine concentrations were measured at the Department of Institute of Clinical Medicine, Renmin Hospital, Hubei University of Medicine, Shiyan. The following phthalate metabolites were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS): monomethyl phthalate (MMP), monoethyl phthalate (MEP), monoisobutyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), monobenzyl phthalate (MBzP), mono(carboxyoctyl) phthalate (MCOP), mono-(3-carboxypropyl) phthalate (MCPP), mono-n-octyl phthalate (MOP), mono-cyclohexyl phthalate (MCHP), mono-isononyl phthalate (MiNP), mono (2-ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-(2-ethyl5-oxohexyl) phthalate (MEOHP). Mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) was analyzed using isotope dilution LC-MS/MS with preceding enzymatic deconjugation followed by automatic solid-phase extraction. The following solvents were used for LC separation: A, 0.1% acetic acid in acetonitrile and B, 0.1% acetic acid in water. Solvent programming involved 0.0e2.0 min, 10% B; 17.0 min, 25% B; 21 min, 30% B; 23 min, 60% B; 25 min, 70% B; 27 min, 90% B; and 32 min, 10% B. For all analytes, good separation was obtained with a retention time on the column of 6.68e27.22 min. The analysis quality was checked using chemical blank samples and an in-house quality control in all of the sample batches that were analyzed. The inter-day variation, expressed as the relative standard deviation (RSD), was <10.0% for all analytes except MOP (15.2%) and MiNP (13.8%), and the recovery of spiked samples was >90.0% for all analytes except MiNP (85.6%), MOP (80.6%), and MCHP (78.6%). Values for metabolites at levels less than the limit of detection (LOD) were replaced with the LOD divided by the square root of two (Wolff et al., 2010). Urinary creatinine was determined with a creatinine kit (UCR ELISA Kit, Shanghai, China) using an automatic biochemical analyzer (ClinitekStatus, SIEMENS, Germany). Individual and summed metabolite concentrations were divided by urinary creatinine
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
Table 1 Characteristics of the participating children aged 6e12 years (n ¼ 336). Characteristic
n (%)
Gender Boys Girls Residential area Urban Rural Maternal education College degree High school Middle school or below Paternal occupation Farmer Worker Professional Maternal occupation Farmer Worker Professional Maternal use of hair dye in the home No Yes Parental smoking in the home None 1e10 cigarettes 10 cigarettes Annual household income ($) <3000 3000e8000 >8000 Housing type Roughcast Brick-wood Reinforced concrete Domestic fuel type Wood Coal Gas Decorating materials Bricks Tiles Wall paint Residence close to the road Yes No Average housing area (m2) <10 10 to <30 30 Outside activity duration (hours) <1 0 to <2 2 Time playing with toys (hours) <1 <1 to >2 2 Frequency of dairy product consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of puffer food consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of canned food consumption 1e2 times a month 1e2 times a week 1e2 times a day Frequency of wrapping food in plastic None Sometimes Frequently
180 (53.6) 156 (46.4) 158 (47.0) 178 (53.0) 80 (23.4) 144 (42.9) 112 (33.3) 201 (59.8) 84 (25.0) 51 (15.3) 196 (58.4) 89 (26.4) 51 (15.3) 216 (64.4) 120 (35.6) 120 (35.6) 90 (26.7) 126 (37.7) 31 (9.3) 224 (66.7) 81 (24.1) 64 (19.2) 150 (44.5) 122 (36.3) 73 (21.8) 143 (42.6) 120 (35.6) 111 (33.1) 100 (29.8) 125 (37.1) 187 (55.6) 149 (44.4) 61 (18.1) 213 (63.4) 62 (18.5) 102 (30.6) 139 (41.2) 95 (28.2) 87 (26.0) 146 (43.5) 103 (30.6) 153 (45.3) 96 (28.7) 87 (25.9) 76 (22.7) 194 (57.4) 67 (19.9) 140 (41.6) 123 (36.6) 73 (21.8) 30 (8.8) 166 (49.5) 140 (41.7)
(continued on next page)
3
Table 1 (continued ) Characteristic
n (%)
Water source Tap water Well water Pond water
140 (41.6) 138 (40.8) 58 (17.6)
levels (mg/g) to control for urine dilution. For statistical analyses, we used volume- and creatininecorrected pollutant concentrations. Where more than one metabolite of the parent phthalate was measured, the sums of the corresponding phthalate metabolite concentrations were calculated (phthalate) by summing the concentrations of each respective metabolite. 2.5. Statistical analysis To reduce multiple comparisons, we combined the phthalate metabolites into two groups representing similar sources and similar biologic activity, based on the chain length of the parent phthalates: LMWP (MEP, MMP, MnBP, and MiBP) and HMWP (MBzP, MiNP, MnOP, MCNP, MCOP, MEPP, and SDEHP) [Supplemental Material, Table S1]. We express the sum of HMWP as the molar sum (MEHP; molecular weight 278) so that the units were the same as those of the other analytes. We considered and controlled for covariates known or suspected to be potential confounders and/or effect modifiers: gender, residential area, maternal education, paternal occupation, maternal occupation, maternal use of hair dye in the home, total household income, parental smoking inside, annual household income, housing type, domestic fuel type, decorating materials, residence close to the road, average housing area, outside activity duration (hours), time playing with toys, frequency of dairy product consumption, frequency of puffed food consumption, frequency of canned food consumption, frequency of wrapping food in plastic, and water source. We divided each phthalate metabolite into quartiles and then combined the two middle quartiles to create three categories: low (25th percentile), moderate (25e75th percentile), and high (75th percentile). For preliminary analysis of the differences between each variable, we conducted chi-square (c2) analyses (Zeng et al., 2014), stratified by each major potential effect modifier and confounder. Then, logistic regression analyses were performed to examine the associations between the individual-level dependent variable and independent variables, while controlling for important covariates (Valvi et al., 2015). Odds ratios (ORs) and 95% confidence intervals (CIs) are reported. PCA with varimax rotation was applied to ln-transformed urinary metabolite concentrations. MannWhitney U tests were used to compare phthalate levels between the sexes. All study aims were tested based on a two-tailed significance level of 0.05. SAS version 9.2 (SAS Statistical Institute, Inc, Cary, NC) and R v2.7 (The R Foundation for Statistical Computing, Vienna, Austria) were used for all data manipulation and statistical analysis. 3. Results and discussion 3.1. Demographic characteristics Of the 358 children that were enrolled, 22 children were excluded for missing variables or urine samples, resulting in 336 children aged 6e12 years with complete information (180 boys and
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
156 girls). The median age was 9.2 years, and 47% were from urban areas. Most of the participants (66.7%) had an annual household income of $3000e8000. Maternal education was primarily a high school education (42.9%). Farming represented the majority of maternal (58.4%) and paternal (59.8%) occupations. Only a small proportion of participants consumed dairy products (25.9%), puffer food (19.9%), or canned food (21.8%) 1e2 times a day [Table 1]. 3.2. Phthalate metabolite distributions The distributions of the 14 phthalate metabolites concentrations are presented in Table 2. MnBP, MEHP, and MEHHP were detected in all samples. The remaining phthalates were found in 85% of the samples, except MCHP, MiNP, and MOP, which were above the LOD in <46.8%, 58.5%, and <55.6% of the samples, respectively. MnBP (geometric mean, 60.0 mg/L) and MEHHP (geometric mean, 42.4 mg/ L) were the most abundant PAEs in urine. Strong correlations were observed between MEOHP, MEHP, and MEHHP, which are oxidative metabolites of DEHP (all rs > 0.85, all P < 0.01) [Supplemental Material, Table S2]. MBzP and MEHP concentrations were moderately correlated with MnBP concentrations (rs ¼ 0.65 and 0.49, Table 2 Distribution of urinary phthalate metabolite concentrations for 336 children aged 6e12 years, reported as uncorrected (ng/mL) and specific gravity (SG)-corrected values (mg/g). Phthalate metabolite
LOD
>LOD (%)
Percentile GM
25
50
75
95
MMP SG-corrected MEP SG-corrected MiBP SG-corrected MnBP SG-corrected MBzP SG-corrected MCOP SG-corrected MCPP SG-corrected MOP SG-corrected MCHP SG-corrected MiNP SG-corrected MEHP SG-corrected MECPP SG-corrected MEHHP SG-corrected MEOHP SG-corrected P 4.8P SG-corrected P 68. SG-corrected P 61.8 SG-corrected
0.6
92.6
0.6
96.4
0.7
88.5
0.8
100
0.6
88.6
0.7
97.4
0.4
96.8
0.8
55.6
0.6
46.8
0.4
58.5
0.6
100
0.8
98.4
0.4
100
0.7
96.3
36.0 34.8 31.7 30.8 16.2 17.2 60.0 61.2 2.8 2.9 23.9 22.8 5.9 5.8 2.3 2.2 1.3 1.2 1.5 1.4 10.6 10.4 14.8 12.6 42.4 40.6 12.0 10.8 144.0 138.6 113.2 106.8 79.7 80.4
6.1 5.7 7.5 7.4 6.1 6.4 10.0 10.7 1.2 1.2 8.6 8.5 2.2 2.3 LOD LOD LOD LOD LOD LOD 3.3 3.2 6.3 5.9 9.4 8.9 4.5 4.2 62.3 59.8 63.6 64.8 35.7 34.8
18.5 17.9 14.0 13.5 10.6 10.7 34.7 33.6 2.7 2.8 20.6 21.8 5.4 5.8 1.1 1.2 LOD LOD 0.6 0.5 4.4 4.2 11.8 10.8 17.7 15.8 7.3 6.8 107.1 102.8 88.4 91.2 52.9 50.9
40.2 38.7 26.5 24.9 25.9 17.2 77.6 75.9 3.4 3.5 34.1 33.7 8.8 9.4 1.3 1.2 0.9 0.8 0.6 0.5 10.3 9.8 20.3 22.6 43.6 40.8 13.2 14.8 192.2 186.5 123.0 120.8 83.9 88.7
141.6 138.9 108.8 112.5 40.3 38.9 208.8 204.6 6.3 6.4 50.0 48.7 12.0 10.8 5.0 4.8 2.3 2.0 2.4 2.6 25.0 22.6 29.5 27.6 163.8 169.4 37.2 34.8 387.0 368.9 259.5 261.8 202.8 216.8
LOD, limits of detection; GM, geometric mean; MMP, monomethyl phthalate; MEP, monoethyl phthalate; MiBP, mono-isobutyl phthalate; MnBP, mono-n-butyl phthalate; MBzP, monobenzyl phthalate; MCOP, mono(carboxyoctyl) phthalate; MCPP, mono-(3-carboxypropyl) phthalate; MOP, mono-n-octyl phthalate; MCHP, mono-cyclohexyl phthalate; MiNP, mono-isononyl phthalate; MEHP, mono (2ethylhexyl) phthalate; MECPP, mono-(2-ethyl-5-carboxypentyl) phthalate; MEHHP, mono-(2-ethyl-5-hydroxyhexyl) phthalate; MEOHP, mono-(2-ethyl-5oxohexyl) phthalate; LMWP, low molecular weight phthalate; HMWP, high molecular weight phthalate; DEHP, di-2-ethylhexyl phthalate.
respectively). In the comparison of phthalate levels between the sexes, MEP, MnBP, and MBzP levels were significantly higher in boys (P < 0.001), and MEHHP levels were significantly lower in boys (Supplemental Material, Table S3). These results differ from the lack of statistically significant differences between the sexes in studies with children 8e13 years of age in Mexico and children 6e8 years of age in New York City (Lewis et al., 2013; Teitelbaum et al., 2012). In the present study, MnBP concentrations were the highest (geometric mean, 60.0 mg/L), similar to the findings of previous studies, in which the geometric mean MnBP concentrations were 67.0 ng/mL (Gao et al., 2016) and 61.2 ng/mL (Guo et al., 2011a); this could be related with the wide use of DBP. In the present study, the P geometric mean total phthalate metabolite level ( DEHP) was 79.7 ng/mL, which was the highest of the phthalate metabolites; MnOP concentrations were the lowest, which is similar to the findings in a study with Austrian children aged 6e15 years (not detected (nd)-2.3 ng/mL) (Hartmann et al., 2015), perhaps because of the less frequent use of DnOP and the ready degradation (Upson et al., 2013). The urinary MEHP concentrations (10.4 mg/g) were similar to previously reported urinary levels in Korea (11.4 mg/g) (Kim et al., 2014) and for Chinese children aged 8e11 years (11.4 mg/ g) (Wang et al., 2015a,b,c). However, the levels of some phthalate metabolites, especially MEHHP (geometric mean, 40.6 mg/g), seem to be higher than those reported for children in Germany aged 8e10 years (14.3 mg/g) (Kasper-Sonnenberg et al., 2014) and Canada aged 6e11 years (19.99 mg/g) (Arbuckle et al., 2016). This might indicate an increase in phthalate exposure in China over the years (Guo et al., 2011b). 3.3. Factors influencing lower phthalate metabolite exposure Based on the c2 tests, the following variables were significant for MMP distribution: residential area (c2 ¼ 12.78, P ¼ 0.002), maternal occupation (c2 ¼ 12.53, P ¼ 0.05), housing type (c2 ¼ 12.29, P ¼ 0.002), decorating materials (c2 ¼ 18.85, P ¼ 0.004), frequency of canned food consumption (c2 ¼ 13.31, P ¼ 0.04), frequency of wrapping food in plastic (c2 ¼ 20.96, P ¼ 0.00), and water source (c2 ¼ 10.10, P ¼ 0.04) [see Supplemental Material, Table S4]. These variables were included in the logistic regression model, in which only the following two variables were significant: use of paint on the walls as a decorating material (reference, bricks; OR ¼ 6.00; 95% CI: 1.65, 21.80) and higher frequency of wrapping food in plastic (OR ¼ 3.26; 95% CI: 1.98, 10.88) [Table 3]. Of the potential variables influencing the MEP distribution, a housing type of reinforced concrete (reference, roughcast; OR ¼ 0.284; 95% CI: 0.102, 0.791) was significant in the logistic regression analysis. Based on the c2 tests, the following variables were significant for MnBP distribution: residential area (c2 ¼ 43.82, P ¼ 0.000), total annual household income (c2 ¼ 14.49, P ¼ 0.03), domestic fuel type (c2 ¼ 20.33, P ¼ 0.002), and decorating materials (c2 ¼ 26.38, P ¼ 0.000). These variables were included in the logistic regression model, and rural residential area (reference, urban; OR ¼ 0.084; 95% CI: 0.009, 0.861) and housing type of reinforced concrete (reference, roughcast; OR ¼ 0.28; 95% CI: 0.10, 0.79) were significant. In the analysis of the MiBP distribution, a rural residential area (reference, urban; OR ¼ 0.24; 95% CI: 0.21, 0.74) and maternal use of hair dye in the home (reference, no use; OR ¼ 3.25; 95% CI: 1.24, 11.58) were significant. Therefore, demographic variables and living condition may have an effect on low phthalate metabolite levels. Using paint as a decorating material can increase exposure to MMP, which is a metabolite of DMP. A survey in the United States also found that DMP is a controversial chemical in building materials and household furnishings; it can be inhaled in the form of dust particles from
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7 Table 3 Logistic regression analysis for factors associated with monomethyl phthalate (MMP). Characteristic
B
SE
MMP 1 1.36 1.62 2 1.71 1.42 Residential area a Urban 0 Rural 0.25 0.84 Maternal occupation Farmer 0 Worker 0.2 0.59 Professional 1.3 0.58 Housing type Reinforced concrete 0 Brick-wood 0.56 0.62 Roughcast 0.5 0.62 Decorating materials Wall paint 0 Tiles 0.7 0.86 Bricks 1.79 0.66 Frequency of canned food consumption 1e2 times a month 0 1e2 times a week 0.0 0.74 1e2 times a day 0.9 0.93 Frequency of wrapping food with plastic None 0 Sometimes 0.8 0.82 Frequently 1.18 0.62 Water source Tap water 0 Well water 0.7 0.70 Pond water 1.2 0.88
c2
P
0.70 1.46
0.40 0.23
0.09
0.77
1.28 (0.25, 6.66)
0.13 5.08
0.71 0.02
0.81 (0.25, 2.58) 0.27 (0.09, 0.84)
0.81 0.77
0.37 0.38
1.76 (0.52, 5.97) 0.58 (0.17, 1.95)
0.68 7.41
0.41 0.01
0.49 (0.09, 2.66) 6.00 (1.65, 21.8)
0.00 1.05
0.99 0.31
0.99 (0.24, 4.19) 0.38 (0.06, 2.39)
1.02 5.01
0.31 0.03
0.44 (0.09, 2.17) 3.26 (1.98, 10.88)
1.09 1.98
0.30 0.16
0.48 (0.12, 1.90) 0.29 (0.05, 1.62)
OR (95% CI)
OR, odds ratio; CI, confidence interval; MMP, monomethyl phthalate; 0a, Referent.
sources such as vinyl flooring and upholstery (Kamrin, 2009). Under UV light irradiation of the surface of painted murals, photodegradation results in the release of 0.221e0.737 mSv/h PAEs (Barreca et al., 2014). In the present study, children living in rural areas had less MiBP and MnBP exposure than children living in urban areas. The urban areas in the present study are heavily industrialized and have considerable commercial activity. The high MnBP concentrations might have originated from contaminated vehicle and pipe (e.g., electrical poles and lampposts) run-off and infrastructure around industrial plants. As we expected, maternal use of hair dye in the home increased children's MiBP exposure. A number of personal care products and cosmetics, such as fragrances, skin lotions, nail polish, and eye shadows, contain some types of phthalates (e.g., DEP, DBP, and DiBP) that act as solvents, fixatives, or alcohol denaturization (Tian et al., 2016). Girls who use more shampoo and shower gel have marginally significantly higher urinary MnBP (P ¼ 0.06) and MiBP (P ¼ 0.06) concentrations (Chen et al., 2015). In a study of personal care products in New York, DEP and DBP in perfumes and nail polishes were generally on the order of 1000 mg/g (Guo and Kannan, 2013). By nature, hairspray and perfume are highly volatilized and have adhesive qualities, leaving residue on bathroom surfaces, which could have contributed to the high levels in the present study. 3.4. Factors influencing higher phthalate metabolite exposure Based on the c2 tests, the following variables were significant for MBzP distribution: residential area (c2 ¼ 62.33, P ¼ 0.000), total annual household income (c2 ¼ 12.29, P ¼ 0.06), time playing with toys (c2 ¼ 9.56, P ¼ 0.05), and water source (c2 ¼ 12.89, P ¼ 0.01); in the logistic regression model, 2 h playing with toys (reference, <1 h; OR ¼ 7.03; 95% CI: 1.00, 49.58) and use of well water
5
(reference, tap water; OR ¼ 3.69; 95% CI: 1.58, 8.59) and pond water (reference, tap water; OR ¼ 4.90; 95% CI: 1.66, 14.48) as the water source were significant. Based on the c2 tests, the following variables were significant for MCOP distribution: parental smoking inside (c2 ¼ 6.79, P ¼ 0.05), frequency of dairy product consumption (c2 ¼ 13.92, P ¼ 0.03), and frequency of puffer food consumption (c2 ¼ 12.17, P ¼ 0.04). These variables were included in the logistic regression model, and eating puffer food 1e2 times a day (reference, 1e2 times a month; OR ¼ 7.54; 95% CI: 1.38, 8.17) and 1e2 times a week (reference, 1e2 times a month; OR ¼ 3.52; 95% CI: 1.14, 4.36) were significant. Regarding MCPP distribution, which is another DnOP metabolite, eating canned food 1e2 times a day was significant (reference, 1e2 times a month; OR ¼ 3.36; 95% CI: 1.22, 26.66). As expected, children who frequently played with toys had greater MBzP exposure. MBzP is a metabolite of BBP, which is an important component of PVC and soft plastics that find their way into children's mouths as toys (Koniecki et al., 2011). In the present study, children who frequently consumed puffer food and canned food had greater MCOP and MCPP exposure. Phthalates can migrate into food from plasticized PVC materials such as the tubing typically used in the milking process, lid gaskets, food-packaging films, gloves used in the preparation of foods, and conveyor belts (Darbre and Harvey, 2008). A large study showed that contaminated food is the most important source of exposure to HMWP. In an assessment of phthalate contamination in canned dinners and canned mackerel fillet in tomato sauce, the estimated dietary exposure was high and dominated by DEHP and DiNP (400e500 ng/kg body weight [bw]/day), followed by BBP and DnOP (30e40 ng/kg bw/day) (Sakhi et al., 2014). Because the MCHP, MiNP, and MOP levels were below the LOD, we did not conduct analyses with these metabolites. 3.5. Factors influencing DEHP metabolite exposure Based on the c2 tests, the following variables were significant for MCOP distribution, which is a metabolite of DEHP: residential area (c2 ¼ 11.79, P ¼ 0.003), domestic fuel type (c2 ¼ 13.76, P ¼ 0.008), outside activity duration (c2 ¼ 10.65, P ¼ 0.003), and frequency of canned food consumption (c2 ¼ 14.01, P ¼ 0.03). The logistic regression model indicated that 1e2 h of outside activity (reference, <1 h; OR ¼ 0.10; 95% CI: 0.02, 0.73), >2 h of outside activity (reference, <1 h; OR ¼ 0.06; 95% CI: 0.00, 0.81), eating canned food 1e2 times a week (reference, 1e2 times a month; OR ¼ 17.67; 95% CI: 1.26, 24.75), and eating canned food 1e2 times a day (reference, 1e2 times a month; OR ¼ 32.90; 95% CI: 4.07, 26.86) were significant. Regarding the three secondary oxidized metabolites of DEHP (MEHHP, MEOHP, and MECPP), the use of coal (reference, wood; OR ¼ 0.183; 95% CI: 0.04, 0.91) and gas (reference, wood; OR ¼ 0.12; 95% CI: 0.02, 0.65) for domestic fuel were associated with MEHHP exposure. Maternal use of hair dye in the home (OR ¼ 3.37; 95% CI: 1.14, 9.95) and eating canned food (OR ¼ 8.06; 95% CI: 1.96, 33.20) were associated with MEOHP exposure. Regarding MECPP levels, the use of well water (reference, tap water; OR ¼ 3.54; 95% CI: 1.45, 8.65) and pond water (reference, tap water; OR ¼ 3.90; 95% CI: 1.32, 11.58) as the water source were significant. Frequently wrapping food in plastic was significantly associated with MEHHP levels (reference, none; OR ¼ 6.59; 95% CI: 1.41, 30.71). Our data indicate that routine outdoor physical activity could accelerate the excretion of DEHP in children. A study from Germany also supports this finding; DEHP and DiNP metabolites rapidly declined to levels 5e10 times lower than initial levels within 24 h of fasting and remained low after exercise. We also found that, of the three types of domestic fuel that we investigated (wood, coal, and
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W. Wu et al. / Environmental Pollution xxx (2016) 1e7
gas), the use of natural gas was associated with less MEPP exposure. The burning of wood and coal results in thick black smoke that could contain phthalates, and children could be exposed through inhalation (Wang et al., 2016). Water is thought to be another principle route of exposure to many phthalates. In the present study, MEP, MBP, and MEOHP exposure was higher for those who drank well water or pond water than for those who drank tap water. Based on the measurement of 16 PAEs in water samples from 19 sites, the total PAE congener concentration ranged from 1.07 mg/L to 7.12 mg/L in Zhejiang province (Wang et al., 2015a,b,c). In addition, DEHP and DBP are the dominant PAEs in water treatment plants in China, contributing between 61% and 95% of the PAEs in water (Wang et al., 2015a,b,c). In the present study, people living around pond water may have placed garbage in the water, and through leaching and abrasion, PAEs could have been released, which may also help to explain the greater phthalate exposure than with tap water. In addition, food packaging materials, especially plastic bags or wraps, are contamination sources for phthalates in dairy products.
Funding This study was financially supported by the National Natural Science Foundation of China (No. 81273024). Acknowledgements The authors declare they have no actual or potential competing financial interests. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2016.11.049.
3.6. Principal component analysis For the PCA and correlation analyses, molar concentration levels were used, and the total DEHP metabolite value consisted of MEHHP, MEOHP, and MECPP concentrations (Table 4). Five factors were retained with Eigen values > 1.000 and that expressed 62.6% of the variance. Lower phthalate metabolite levels were associated with factors 1 and 3, higher phthalate metabolite levels were associated with factors 2 and 4, and the levels of the metabolites of DEHP were associated with factors 1 and 2. The phthalate relationships indicate that plastic and food packaging are a possible source. Studies conducted in Switzerland and Greece also reported that the use of consumer products and food are major influencers of phthalate exposure (Wormuth et al., 2006; Myridakis et al., 2015). 4. Conclusion Children, particularly those of school age, should be regarded as at special risk of the potential effects of phthalates on reproduction and development. In our comprehensive study, we assessed 14 phthalate metabolites in urine samples from children aged 6e12 years, which reflect the pollution of PAEs in children. In addition, we systematically analyzed the factors influencing phthalate metabolite levels [Supplemental Material, Table S5], which
Table 4 Principal component analysis: rotated component matrix and total variance explained. Component
1
2
3
4
Eigenvalue % of variance Cumulative % MMP MEP MiBP MnBP MBzP MCOP MCPP MOP SDEHP
1.192 21.360 21.360 0.424 0.755 0.681 0.556
1.477 16.410 37.771
1.177 13.073 50.844 0.532
1.058 11.761 62.604 0.216
0.599 0.280 0.878 0.582
0.279 0.301 0.584
0.461
indicated that exposure to all phthalates can be reduced by changing habits and other behaviors, such as avoiding processed foods, especially canned foods; foods wrapped in plastic; and soft plastic toys manufactured before phthalates were banned from such products as well as less frequent use of plastic containers and chemical fragrances.
0.692
Coefficients <0.200 are not presented. Rotation converged in 6 iterations. MMP, monomethyl phthalate; MEP, monoethyl phthalate; MiBP, mono-isobutyl phthalate; MnBP, mono-n-butyl phthalate; MBzP, monobenzyl phthalate; MCOP, mono(carboxyoctyl) phthalate; MCPP, mono-(3-carboxypropyl) phthalate; MOP, mono-n-octyl phthalate; DEHP, di-2-ethylhexyl phthalate.
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Please cite this article in press as: Wu, W., et al., Phthalate levels and related factors in children aged 6e12 years, Environmental Pollution (2016), http://dx.doi.org/10.1016/j.envpol.2016.11.049