Exposure Levels and Health Risks of Phthalate Alternatives: A Urinary Metabolite Study

Abstract

Phthalate alternatives are increasingly replacing traditional phthalates (PAEs) as plasticizers due to growing regulatory and health concerns. However, these alternatives and their metabolites have been detected in both environmental and biological matrices, raising concerns regarding potential health risks. Here, we used ultrahigh performance liquid chromatography–tandem mass spectrometry to detect nine metabolites of four PAE alternatives (aPAEs) in 176 urine samples collected from residents of Chengdu and Suining, Sichuan Province, China. Our results revealed that seven metabolites were commonly present in the urine samples, with total metabolite concentrations ranging from 2.52 to 6300 ng/mL. The median concentrations were 21.1 ng/mL in Chengdu and 39.8 ng/mL in Suining. The compositional profiles of these metabolites in urine samples from both cities were similar, with mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP) identified as the predominant metabolite, representing over 50% of the total concentration. Notably, teenagers exhibited higher exposure levels compared to other age groups. Despite these findings, the estimated internal exposures remained well below health-based guidance values and toxicological reference levels, suggesting that the current exposure level may not pose acute health risks. This study highlights the widespread occurrence of aPAE metabolites in human urine and underscores continued biomonitoring and risk assessment of these emerging pollutants.

1. Introduction

Phthalates (PAEs), also known as phthalate esters, are commonly used as plasticizers in a variety of products, including polyvinyl chloride (PVC) plastics, resins, toys, and food packaging materials. However, PAEs have been recognized as harmful substances by the U.S. Environmental Protection Agency (USEPA), which classifies them as “chemicals of concern”. PAEs are ubiquitous in various environmental matrixes and have been linked to adverse health outcomes, such as reproductive toxicity, , diabetes, endocrine disruption, and an increased prevalence of allergies and asthma in children, effects on neonatal birth weight, and the increased coronary heart disease risk. Consequently, the use of PAEs has been restricted in many countries and regions. In response to these concerns, safer alternatives to traditional PAE plasticizers have been developed. These alternatives are now widely used in household products, including PVC plastics, solvents, stabilizers, and additives in cosmetics, medical devices, and personal care items. −

According to the data of the Organization for Economic Co-operation and Development (OECD) and USEPA, most PAE alternatives (aPAEs) are now classified as high-production volume chemicals. However, plasticizers do not form stable and strong covalent bonds with polymeric materials, making them prone to migration from products into the surrounding environment. PAE alternatives and their metabolites have been detected in a variety of media, including indoor dust, sediment, , drinking water, air, food, personal care products, clothing, medical devices, hair, urine, − and breast milk. The widespread occurrence of these substances in both environmental and biological matrices suggests that plasticizers are not only metabolized in living organisms but also degraded in the environment. Furthermore, these findings suggest that the direct ingestion of monoesters from environmental matrices may represent a previously overlooked pathway of exposure to plasticizers within the population.

Exposure to PAEs has emerged as a significant public health concern. , Due to their widespread presence in the environment, analysis of plasticizers in samples is particularly vulnerable to background contamination. While PAEs are rapidly metabolized and conjugated by phase I enzymes in organisms, their metabolites are less likely to be contaminated. Consequently, urinary aPAE metabolites have been demonstrated to serve as effective biomarkers for assessing internal exposure doses of maternal PAEs. The presence of PAE metabolites in human urine has been previously monitored in international studies. − U.S. biomonitoring data from 2001 to 2016 indicated that the composition characteristics of PAE metabolites in human urine have exhibited temporal changes. With the increasing use of aPAEs, the metabolite concentrations of some traditional PAE plasticizers decreased, while the metabolite concentrations of aPAEs increased. Current biological monitoring of aPAEs has primarily performed in Europe and North America, with fewer studies conducted in China, despite evidence of widespread exposure. − Several Chinese studies have reported on urinary concentrations of PAE metabolites in cities such as Beijing and Shanghai, highlighting exposure across different age groups and the associated health risks. However, studies with detailed demographic information are scarce, and research in eastern coastal cities does not fully reflect the exposure levels in the broader population. More efforts are needed to investigate PAE exposure in the western interior regions of China.

In this study, human urine samples were collected from two cities, Chengdu and Suining, Sichuan Province, both located in the interior of western China and with similar geographical, cultural, and dietary characteristics. However, these two cities are different in terms of economic development, educational levels, demographic compositions, and so on. The aim of the current study was to investigate the geographic distribution and demographic-related differences in urinary aPAE metabolites and to assess the potential health risks associated with the aPAEs.

2. Methods and Materials

2.1. Chemicals and Reagents

Nine aPAE metabolites were included in this study. The full names, abbreviations, CAS registry numbers, and supplier information for each metabolite are listed in Table S1 of the Supporting Information. A suite of 9 aPAE metabolites, i.e., mono-2-ethylhexyl terephthalate (MEHTP), mono-2-ethyl-5-hydroxyhexyl terephthalate (MEHHTP), mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP), cyclohexane-1,2-dicarboxylic acid-mono-isononyl ester (MINCH), cyclohexane-1,2-dicarboxylic acid-mono (hydroxy-isononyl) ester (MHNCH), cyclohexane-1,2-dicarboxylic acid-mono (carboxy isononyl) ester (MCOCH), cyclohexane-1,2-dicarboxylic acid-mono (oxo-isononyl) ester (MONCH), mono-2-propyl-6-hydroxy heptyl phthalate (MPHHP), and mono-2-ethylhexyl adipate (MEHA), and labeled mono-2-ethylhexyl phthalate (MEHP-d ₄), as a surrogate standard for the quantification of the targeted metabolites, were purchased from WITEGA Laboratorien Berlin-Adlershof GmbH (Berlin, Germany). Conventional PAEs have been substituted with these aPAEs, which could be biodegraded to some stable metabolites (already validated by biomonitoring and metabolic pathway investigations). Their frequent occurrence in biological matrices ensures robust exposure quantification, enabling accurate risk evaluation and cross-study comparisons in human exposure.

Oasis HLB Vac cartridges (60 mg, 3 mL) were supplied by Waters (Milford, MA, USA). β-glucuronidase (≥100,000 units/mL) was obtained from Sigma-Aldrich (St. Louis, MO, USA). HPLC-grade acetonitrile (ACN), ethyl acetate (ETAC), and methanol were obtained from Fisher Scientific (Pittsburgh, PA, USA). Analytical grade solvent of glacial acetic acid was sourced from Aladdin (Shanghai, China), and formic acid (98%–100%) was purchased from Merck (Darmstadt, Germany). Ultrapure water (18.2 MΩ cm) was prepared through a Milli-Q Integral system (Millipore, USA).

2.2. Sample Collection and Preparation

This study involved healthy individuals from two cities: Suining, a prefecture-level city in Sichuan Province, and Chengdu, the provincial capital of Sichuan Province. In Suining, a majority of the samples were collected from the students of a local primary school. The sampling procedure was to collect the midstream portion of morning urine into 50 mL polypropylene (PP) centrifuge tubes. A total of 176 urine samples were obtained, with 137 from Suining and 39 from Chengdu. Concurrently with the collection of samples, information regarding age, sex, body mass index (BMI), and dietary characteristics was gathered through the administration of questionnaires. Individuals with a history of endocrine diseases, urinary system diseases, or other major illnesses or taking drugs within 1 week were excluded from the study during the recruitment process. The collected urine samples were stored in a −20 °C refrigerator. Each participant signed an informed consent form. The sampling was approved by the Ethics Committee of the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, and the School of Environment and Health, Jianghan University.

The analysis of aPAE metabolites in a human urine sample was conducted following established procedures , with some modifications. In brief, approximately 1.0 mL of human urine sample was spiked with 50 ng MEHP-d ₄ as a surrogate standard, buffered with 0.5 mL of ammonium acetate solution (pH 6.0) with 20 μL of β-glucuronidase, and incubated in an orbital shaker at 37 °C for 2 h. After incubation, 1 mL of 1% formic acid in water was added, and SPE extraction was carried out to remove proteins, macromolecules, and other impurities. The sample was loaded onto an Oasis HLB cartridge preconditioned with 3 mL of ACN and 3 mL of 1% formic acid in water. Once the sample passed through, the cartridge was washed with 2 mL of 1% formic acid in water and 1 mL of water, and dried under vacuum. The target compounds were eluted with 2 mL of ACN and 2 mL of ETAC. The eluate was dried with nitrogen, and 1 mL of ACN/water mixture (1:1, v/v) was used to redissolve for analysis.

2.3. Instrumental Analysis

Metabolites of aPAEs were determined using an Exion LC AD series ultrahigh performance liquid chromatography system-triple quadrupole mass spectrometer (UPLC-MS/MS, AB Sciex, Framingham, MA, USA). A BEH C18 column (2.1 × 100 mm, 1.7 μm, Waters, Milford, MA, USA) connected in series to a guard BEH C18 column (2.1 × 5 mm, 1.7 μm, Waters) at 30 °C was used for LC separation. The flow rate was 0.4 mL/min, and the sample injection volume was 5 μL. Milli-Q water and ACN containing 0.1% acetic acid were used as mobile phases A and B, respectively. The negative electrospray ionization (ESI) multiple-reaction monitoring (MRM) mode was run with the following gradient conditions: 0–1 min, 10% B; 1–3 min, 90% B; 3–3.5 min, 90% B; 3.6–5 min, 10% B. The optimized ion spray voltage and temperature were set at 4500 V and 450 °C, respectively. All selected masses, collision energies, and declustering potentials are provided in Table S2. The typical total chromatograms of 9 metabolites are shown in Figure S1.

2.4. Quality Assurance and Quality Control

To minimize background contamination, all plastic vessels and glassware used in the experiment were rinsed three times with 3 mL of water and 3 mL of methanol and then dried before use. This process ensured low detectable background values (0.00–1.65 ng/mL).

The average recoveries for metabolites in urine samples were ranged from 54% to 97%, with standard deviations (SDs) below 27%. Standard curves of target metabolites with concentrations ranging from 0.01 to 500 ng/mL were prepared in ACN/water (1:1, v/v) for quantification, with all regression coefficients greater than 0.99. During instrumental analysis, a midpoint calibration standard was inserted after every 25 samples to monitor instrumental drift in sensitivity. The limits of detection (LODs) and limits of quantitation (LOQs) were defined as the concentration that would produce signal-to-noise (S/N) ratios of 3 and 10, respectively. The concentrations of targeted analytes in urine samples were corrected by using the corresponding internal standards. Detailed information on procedure blanks, recoveries, LODs and LOQs for targeted analytes and QA/QC data are presented in Table S3.

2.5. Estimated Daily Intake

Urinary levels of MEHHTP, MECPTP, MINCH, MHNCH, MCOCH, MONCH, and MPHHP were used to calculate the estimated daily intake (EDI) values for their parent compounds. The daily intake for DEHTP, DINCH, or DPHP was estimated using the following equation, a simplified approach describing a two- or more-compartment model:

$$\mathrm{EDI}=\frac{C\times V\times M_1}{F_{\mathrm{ue}}\times \mathrm{bw}\times M_2\times 1000}$$

EDI is the daily intake of aPAEs per body weight per day (μg/kg bw/day). C is the concentration (ng/mL) of aPAE metabolites in urine, V is the volume of daily urinary excretion (mL, data are derived from the research in Table S4), M ₁ is the molecular weights of parent aPAEs (g/mol), M ₂ is the molecular weights of aPAE metabolites (g/mol), and F _ue is the excretion molar fraction of the urinary monoester metabolites in reference to the ingested amounts of parent aPAEs, which were derived after oral doses of the parent compounds. We used 0.130, 0.128, and 0.107 as the F _ue for MECPTP, MHNCH + MCOCH, and MPHHP to calculate the EDIs of DEHTP, DINCH, and DPHP. The “1000” is used to transform the unit of EDI from ng/kg bw/day to μg/kg bw/day, and bw stands for body weight (kg).

2.6. Statistical Analysis

IBM SPSS 27.0 and GraphPad Prism 8 were used for statistical analysis and visualization, respectively. Descriptive statistics, including geometric mean (GM), median, and range, were applied to the measured concentrations. Concentrations below the LOQs were assigned a value equal to the half-LOQs (LOQs/2) for statistical analysis. The normality of measured concentration data was analyzed by Kolmogorov–Smirnov tests. For non-normally distributed data, p-values were evaluated using the Mann–Whitney U test or Bonferroni-adjusted Mann–Whitney U test to identify potential significant difference in concentrations. Statistically significant was considered as a value of p < 0.05. Correlation between chemical concentration in urine samples was calculated using nonparametric Spearman rank correlation.

3. Results and Discussion

3.1. Concentration Levels and Exposure Profiles of aPAE Metabolites in Urine

Table provides an overview of the GM, median, concentration range, and detection rates of aPAE metabolites in urine from two cities in southwestern China. Except for MEHTP, metabolites of bis­(7-methyloctyl) cyclohexane-1,2-dicarboxylate (DINCH, a typical PAE alternative) and di­(2-ethylhexyl) terephthalate (DEHTP, a typical PAE alternative) were detected in all urine samples. The metabolite MEHTP was detected in only one sample from Suining with a detection rate of 0.568%. This may be due to the fact that MEHTP is a primary metabolite of DEHTP, which is subsequently transformed into a secondary metabolite of side chain oxidized metabolites in urine. MPHHP, which is derived from di-(2-propylheptyl) phthalate (DPHP), was detected in 100% of the urine samples. In contrast, MEHA, which is derived from bis­(2-ethylhexyl) adipate (DEHA), had a detection rate of only 12.5%. Seven of the nine metabolites were detected in 100% of the samples, suggesting that participants were ubiquitously exposed to three aPAEs, DEHTP, DINCH, and DPHP.

1. Concentrations of aPAE Metabolites in Urine (ng/mL) from Two Cities in China.

	DEHTP			DINCH				DPHP	DEHA
	MEHTP	MEHHTP	MECPTP	MINCH	MHNCH	MCOCH	MONCH	MPHHP	MEHA	Sum
All samples (n = 176)
GM	n.d.	7.11	16.2	1.53	0.657	1.23	2.09	0.536	0.049	36.2
Median	n.d.	8.95	17.7	1.20	0.738	1.60	2.98	0.694	0.079	38.4
Min	n.d.	0.361	0.867	0.758	0.023	0.078	0.118	0.023	n.d.	2.5
Max	0.119	181	831	4760	569	390	534	18.5	0.300	6300
DR (%)	0.568	100	100	100	100	100	100	100	12.5	100
Chengdu (n = 39)
GM	n.d.	3.30	9.36	2.09	0.725	0.887	1.44	0.387	0.037	24.9
Median	n.d.	3.69	10.1	0.987	0.713	1.04	2.38	0.512	0.055	21.1
Min	n.d.	0.361	0.867	0.758	0.023	0.087	0.118	0.023	n.d.	2.52
Max	n.d.	75.3	98.8	591	56.3	9.87	18.1	8.23	0.300	699
DR (%)	0	100	100	100	100	100	100	100	41.0	100
Suining (n = 137)
GM	n.d.	8.85	19.0	1.40	0.639	1.35	2.32	0.587	0.102	40.2
Median	n.d.	10.0	19.9	1.22	0.760	1.75	3.05	0.776	0.093	39.8
Min	n.d.	0.542	0.951	0.784	0.026	0.078	0.139	0.027	n.d.	4.27
Max	0.119	181	831	4760	569	390	534	18.4	0.220	6300
DR (%)	0.730	100	100	100	100	100	100	100	4.38	100

^aParent compound.

^bMetabolite.

^cThe total concentrations of the 9 aPAE metabolites analyzed.

^dGeometric mean.

^eNot detected.

^fDetection rate.

Notable difference was observed in the detection rate of MEHA, a metabolite of DEHA, between the two cities. The detection rate in Chengdu (41.0%) was significantly higher than that in Suining (4.38%). For the other seven metabolites of DEHTP, DINCH, and DPHP (three aPAEs), i.e., MEHHTP, MECPTP, MINCH, MHNCH, MCOCH, MONCH, and MPHHP, the detection rates were 100%. The highest concentrations of MECPTP (maximum: 831 ng/mL), MINCH (4760 ng/mL), MHNCH (569 ng/mL), and MONCH (534 ng/mL) were observed in individual samples, which may be attributable to individual differences, , but caution should be exercised when interpreting the maximum values. Figure A illustrates the comparison of metabolite concentrations between the two cities. The metabolite concentrations of aPAEs in urine samples from the general population in Chengdu were generally lower than those in Suining. Notably, this regional disparity aligns with a Norwegian study that supports the inverse correlation between educational attainment and urinary levels of DINCH metabolites (MHNCH and MCOCH). The observed pattern may result from education-driven behavioral changes, including conscious avoidance of plasticized products or enhanced awareness of chemical exposure risks. Statistically significant differences were observed in the total concentrations of aPAE metabolites in urine from the two cities of Chengdu (median: 21.1 ng/mL) and Suining (39.8 ng/mL), with three metabolites (MEHHTP, MECPTP, and MINCH) exhibiting obvious differences in concentrations (p < 0.01).

1.

Concentrations (A) and composition profiles (B) of aPAE metabolites in urine from Chengdu and Suining, Sichuan Province, China. Bottom and top of the box represent the first and third quartiles. The band inside the box shows the median. The whiskers represent the 5th and the 95th percentile (**p < 0.01).

Among the DEHTP metabolites, MECPTP was found to have the highest concentration (median: 17.7 ng/mL). Previous studies have reported high levels of MECPTP in the urine of pregnant women in Mexico (median: 1.70 ng/mL), as well as in children in Indonesia (3.60 ng/mL) and Saudi Arabia (128 ng/mL). Urinary MECPTP concentrations in Suining were lower than those found in nail salon workers in Boston (median: 26.9 ng/mL), but slightly higher than those found in Israel females (8.20 ng/mL) and Thai children (8.00 ng/mL). MECPTP is a metabolite of the PAE alternative DEHTP, which serves as the primary alternative to di­(2-ethylhexyl)-phthalate (DEHP, a widely used traditional plasticizer in many regions, where its use is increasingly restricted). Consequently, DEHTP has been frequently utilized as an alternative plasticizer in various other polymeric materials. Another study conducted by our group revealed that the primary PAE alternative found in indoor dust samples across regions om China is also DEHTP, indicating widespread exposure to DEHTP among the general Chinese population.

The median concentrations of the four DINCH metabolites, specifically MINCH (Chengdu: 0.987 ng/mL, Suining: 1.22 ng/mL), MHNCH (Chengdu: 0.713 ng/mL, Suining: 0.760 ng/mL), MCOCH (Chengdu: 1.04 ng/mL, Suining: 1.75 ng/mL), and MONCH (Chengdu: 2.38 ng/mL, Suining: 3.05 ng/mL), were relatively low. This finding is consistent with the results of the previously mentioned indoor dust study, which reported a low detection rate and concentration of DINCH metabolites. The detected levels of DINCH metabolites are comparable to those observed in other countries and regions, as illustrated in Table S5. The plasticizers sold in China are mainly the traditional PAEs, which may explain that relatively lower levels of DINCH metabolites detected in urine from southwestern China.

The limited monitoring data on the metabolites of DPHP (i.e., MPHHP) and DEHA (MEHA) in human urine make it challenging to draw firm conclusions. However, concentration data for their parent compounds (DPHP and DEHA) in indoor dust and breast milk suggest that low levels of these metabolites in urine found in this study are not unexpected. According to the all above comparisons, the observed levels of DEHTP and DINCH metabolites vary across different countries and regions, likely due to differences in the use of DEHTP and DINCH in various applications such as food packaging, toy manufacturing, personal care products, and PVC-based interior materials. Moreover, variations in these exposure levels may reflect differences in the regulations for legacy PAEs and the rate at which alternative plasticizers are being adopted. It should be noted that, within the past decade, both the European Commission and the United States have prohibited or restricted application of certain PAEs in cosmetics, childcare products, and food-contact materials. , China has also implemented similar restrictions in application of traditional PAEs in certain products. These discrepancies in exposure levels could also be influenced by the timing of the studies, due to evolution in industrialization and regulatory standards evolve.

Figure B shows pollution patterns in Chengdu patterns for aPAE metabolites in urine from Chengdu and Suining based on the percentage contribution of each metabolite to the total concentrations, which exhibits somewhat similarity. MECPTP was the predominant metabolite in urine samples from both cities, accounting for 51.9% (Chengdu) and 52.9% (Suining), respectively. This observation aligns with previous research on human metabolism and urinary excretion for aPAE metabolites, where MECPTP has been identified as the primary metabolite excreted in urine. , It was followed by MEHHTP, with 18.9% in Chengdu and 26.7% in Suining. Collectively, the metabolites of DEHTP (MECPTP and MEHHTP) contributed more than 70% of the total concentrations of metabolites in both cities. For the metabolites of DINCH, MONCH was the main component in both cities, accounting for 12.2% in Chengdu and 8.12% in Suining, respectively. The remaining two metabolites (MPHHP and MEHA) accounted for 2%–6% of total concentrations. Overall, the sum concentrations of metabolites of DEHTP and DINCH in both cities accounted for more than 97% of the total concentrations. It is notable that MEHTP, MEHA and MPHHP are all primary metabolites corresponding to the parent compound. These may be metabolized in vivo to their corresponding secondary or tertiary metabolites, hence the relatively low concentrations observed. −

Spearman correlation analysis was used to examine the relationships between the concentrations for metabolites of the PAE alternative in urine. As shown in Figure , a significant correlation was found between MECPTP and MEHHTP (r = 0.296, p < 0.01), due likely to both being secondary metabolites of DEHTP. Positive correlations were also observed among several secondary metabolites of DINCH, including MHNCH, MONCH, and MCOCH. A strong positive correlation was observed among MINCH, MHNCH, MONCH, and MCOCH (r = 0.985–0.997, p < 0.01), which can be attributed to the fact that they are all metabolites of DINCH. In contrast, the weak correlation between MEHA and other aPAE metabolites is consistent with a previous finding, which reported a low correlation between DEHA (parent compound of MEHA) and other aPAEs in indoor dust, indicating that DEHA may have a distinct source or exposure pathway.

2.

Spearman correlations among concentrations of aPAE metabolites in urine (**p < 0.01).

3.2. Factors Influencing Exposure Profiles of aPAE Metabolites

Table presents the demographic and dietary characteristics of the study population. A total of 176 volunteers participated with a mean age of 16.5 ± 11.3 years. Of the participants, 58.5% were male. The average body mass index (BMI) of the participants was found to be 18.7 ± 3.73. Due to the low concentrations of MEHA and MPHHP, subsequent analyses were focused solely on the metabolites of DEHTP and DINCH (i.e., MEHHTP, MECPTP, MINCH, MHNCH, MCOCH, and MONCH). The samples were classified into three BMI groups, namely, underweight, normal weight, and overweight (Table S6). The BMI standards for children and adolescents (2–17 years) followed the criteria in Table S6. The statistical analysis indicated no significant correlation between the BMI and the urinary concentrations of metabolites (Figure C).

2. Basic Demographic and Dietary Characteristics of the General Population.

Parameters		n	Percentage (%)
Subjects	All	176	100
Sex	Male	103	58.5
	Female	73	41.5
Age	Children (2–10)	9	5.1
	Teenagers (11–17)	122	69.3
	Adults (18–45)	45	25.6
BMI	Underweight	13	7.4
	Normal weight	141	80.1
	Overweight	22	12.5
Eating egg frequency	Low (three times a week and below)	46	26.1
	Moderate (four to six times)	46	26.1
	High (more than six times a week)	84	47.7
Eating meat frequency	Low (three times a week and below)	10	5.7
	Moderate (four to six times)	47	26.7
	High (more than six times a week)	119	67.6
Drinking milk frequency	Low (three times a week and below)	62	35.2
	Moderate (four to six times)	37	21.0
	High (more than six times a week)	77	43.8

^aBody Mass Index, BMI = bw/H², bw is body weight (kg), H is height (m). ,

3.

Demographics-related differences from sex (A), age (B), and BMI (C) in urinary metabolite concentrations of DEHTP and DINCH. Bottom and top of the box represent the first and third quartiles. The band inside the box shows the median. The whiskers represent the 5th and the 95th percentile. (*p < 0.05; **p < 0.01 by Mann–Whitney U and Jonckheere–Terpstra tests). The numbers in parentheses in the figure legend indicate the number of urine samples.

Dietary intake is the primary route of human exposure to PAEs. Foods such as water, milk, meat, and baby foods are linked to PAE exposure. Many cooking techniques and procedures are responsible for the occurrence, migration, and transformation of PAEs in foods. Given the pervasive use of plastic products in food packaging materials and similar containers, , we evaluated the dietary habits of participants, with a focus on the frequency of meat consumption, egg intake, and milk drinking, to explore potential dietary influences on urinary metabolite levels. Participants were categorized based on their consumption frequencies of certain products: low (less than four times per week), moderate (four to six times), and high (more than six times) (Table ). However, the analysis revealed no significant correlation between dietary factors and urinary concentrations of PAE metabolites.

The six urinary aPAE metabolites were compared from a sexual perspective (Figure A). The results revealed that the total urinary concentration of the six metabolites was generally higher in females than males. However, the concentration of MONCH was found to be lower in females compared to males. Despite these differences, none of the concentration variations were statistically significant.

The relationship between age and the urinary concentration of six aPAE metabolites was evaluated across three age groups: children (2–10 years), teenagers (11–17 years), and adults (over 18 years) (Figure B). The results showed that the levels of the six metabolites of two aPAEs were strongly correlated with age. Teenagers exhibited significantly higher urinary levels of two DENTP metabolites (MEHHTP and MECPTP) compared to the other age groups (p < 0.01). As for the four DINCH metabolites (MINCH, MHNCH, MCOCH, and MONCH), total urinary concentrations were significantly lower children than in teenagers (p < 0.05) and adults (p < 0.01), indicating potential differences in exposure sources across age groups. The results were similar to those of previous studies on PAE metabolites (mPAEs), with urinary median concentrations of mPAEs such as mono-n-butyl phthalate, monomethyl phthalate, monobenzyl phthalate, and the DEHP metabolites being obviously higher in minors than adults. Diet was identified as the primary exposure route for aPAEs in the general population. − Teenagers and adults may experience reduced exposure to plastic-related chemicals, likely due to heightened awareness of health and hygiene, resulting in a decreased use of plastic products and reduced consumption of plastic-packaged foods. In contrast, students, especially in primary schools, may be more exposed to dust, plastic stationery, and toys. − Although urinary concentrations of aPAE metabolites were relatively higher in teenagers than adults and children, the small pediatric cohort (n = 9, 5.1%) introduces potential variability and limits the generalizability of these findings. This aligns with established biomonitoring principles, which highlight the necessity of adequate sample sizes across age groups to ensure statistical reliability. − Consequently, conclusions regarding childhood exposure should be interpreted cautiously, and future investigations with larger pediatric cohorts are critical to validate these observations.

3.3. Exposure Risk Assessments

The calculated EDIs of the parent aPAEs, derived from the aPAE metabolites, are shown in Table . We calculated EDIs of DEHTP, DINCH, and DPHP based on the urinary concentrations of MECPTP, MHNCH + MCOCH, and MPHHP, respectively. For the whole population, the median and 95th percentile EDIs of DEHTP were 6.16 and 25.8 μg/kg bw/day, respectively. The median and 95th percentile EDIs of DINCH were 0.968 and 6.25 μg/kg bw/day, respectively. For DPHP, the median and 95th percentile EDIs were 0.298 and 1.73 μg/kg bw/day, respectively. Significant differences in the EDIs of DEHTP were found between Chengdu (median: 4.36 μg/kg bw/day) and Suining (6.57 μg/kg bw/day) (p < 0.01). In contrast, no significant differences were observed in the EDIs of DINCH and DPHP between the two cities (p > 0.05). In addition, the EDIs of DEHTP and DINCH except for DPHP were age-related. The EDI of DEHTP was significantly higher in teenagers than that in children and adults (p < 0.05). Although the EDI of DPHP was higher in teenagers and adults than in children, no significant differences were found (p > 0.05). The median EDIs of DINCH for teenagers (1.07 μg/kg bw/day, p < 0.01) and adults (1.09 μg/kg bw/day, p < 0.05) were about 2 fold higher compared to that of children (0.491 μg/kg bw/day). The findings provided conclusive evidence that children were less vulnerable to aPAE exposure compared to adults. The estimated EDIs for children remain uncertain, as the F _ue values of aPAEs for children are unknown, and the F _ue values for adults were thus adopted in the calculation of children’s EDIs. Previous research indicated that children were more likely to produce oxidized metabolites rather than monoesters. Consequently, the actual exposure doses of children to DEHTP and DINCH may be underestimated.

3. Estimated Daily Intake (EDI, μg/kg bw/day), Risk Quotients (RQ), and Hazard Quotient (HQ) of DEHTP, DINCH, and DPHP from Different Cities and Ages.

	DEHTP			DINCH			DPHP
	EDI	RQ	HQ	EDI	RQ	HQ	EDI	RQ	HQ	HI
All samples (n = 171)
GM	5.89	0.008	0.011	0.896	6.98 × 10–4	8.96 × 10–4	0.259	0.003	0.003	0.016
Median	6.16	0.008	0.011	0.968	7.61 × 10–4	9.68 × 10–4	0.298	0.005	0.003	0.018
P95	25.8	0.039	0.048	6.25	5.93 × 10–3	6.25 × 10–3	1.73	0.021	0.017	0.075
IQR	7.71	0.011	0.014	1.65	1.22 × 10–3	1.65 × 10–3	0.433	0.006	0.004	0.021
MAX	305	0.461	0.566	390	0.320	0.390	8.12	0.132	0.081	0.578
Chengdu (n = 38)
GM	3.57	0.004	0.007	0.807	4.98 × 10–04	8.07 × 10–04	0.191	0.002	0.002	0.011
Median	4.36	0.004	0.008	0.863	5.41 × 10–04	8.63 × 10–04	0.262	0.002	0.003	0.010
P95	28.7	0.030	0.053	23.6	0.013	0.024	1.83	0.013	0.018	0.073
IQR	6.83	0.006	0.013	1.33	6.30 × 10–04	1.33 × 10–03	0.381	0.004	0.004	0.023
MAX	31.8	0.035	0.059	26.0	0.015	0.026	3.50	0.037	0.035	0.096
Suining (n = 133)
GM	5.95	0.008	0.011	0.885	7.00 × 10–04	8.85 × 10–04	0.255	0.003	0.003	0.016
Median	6.57	0.009	0.012	0.968	7.80 × 10–04	9.68 × 10–04	0.298	0.005	0.003	0.018
P95	25.6	0.041	0.047	5.96	0.0057	0.0060	1.73	0.021	0.017	0.078
IQR	7.57	0.011	0.014	1.65	0.0014	0.0016	0.443	0.006	0.004	0.021
MAX	305	0.461	0.566	390	0.320	0.390	8.12	0.132	0.081	0.578
Children (n = 27)
GM	3.97	0.006	0.007	0.403	3.29 × 10–04	4.03 × 10–04	0.151	0.002	0.002	0.010
Median	4.78	0.006	0.003	0.491	3.49 × 10–04	4.91 × 10–04	0.214	0.002	0.002	0.011
P95	20.5	0.031	0.038	4.09	3.56 × 10–03	4.09 × 10–03	1.56	0.025	0.016	0.053
IQR	5.36	0.009	0.010	0.779	7.18 × 10–04	7.79 × 10–04	0.371	0.007	0.004	0.013
MAX	21.6	0.037	0.040	5.45	4.95 × 10–03	5.45 × 10–03	1.71	0.028	0.017	0.058
Teenagers (n = 101)
GM	7.39	0.012	0.014	1.05	9.28 × 10–04	1.05 × 10–03	0.280	0.004	0.003	0.020
Median	7.26	0.012	0.006	1.07	1.08 × 10–03	1.07 × 10–03	0.350	0.005	0.004	0.020
P95	33.5	0.050	0.062	5.92	5.69 × 10–03	5.92 × 10–03	2.15	0.033	0.021	0.095
IQR	8.36	0.013	0.015	2.28	1.82 × 10–03	2.28 × 10–03	0.395	0.006	0.004	0.021
MAX	305	0.461	0.566	390	0.320	0.390	8.12	0.132	0.081	0.578
Adults (n = 43)
GM	4.41	0.004	0.008	1.02	5.59 × 10–04	1.02 × 10–03	0.302	0.003	0.003	0.014
Median	4.93	0.004	0.005	1.09	6.01 × 10–04	1.09 × 10–03	0.325	0.003	0.003	0.017
P95	25.9	0.026	0.048	22.7	0.013	0.023	2.63	0.019	0.026	0.067
IQR	6.68	0.006	0.012	1.25	5.56 × 10–04	1.25 × 10–03	0.625	0.005	0.006	0.024
MAX	31.8	0.035	0.059	26.0	0.015	0.026	3.50	0.037	0.035	0.096

^aGeometric mean.

^b95th percentile.

^cInterquartile range.

To evaluate the potential health risks associated with exposure to aPAEs, risk quotient (RQ), and hazard quotient (HQ) were calculated based on established methodologies. The RQ was calculated as a ratio to compare the concentrations of the typical metabolites of DEHTP, DINCH, and DPHP with human biomonitoring (HBM) values. No adverse health effects are expected below 1. The HBM values for DEHTP and DINCH were based on the guidance values of the German Human Biomonitoring Commission (HBM-I), and the HBM value for DPHP was based on the human biomonitoring guidance values for the general population (HBM-GV_GenPop). The German HBM-I values for MECPTP, a DEHTP metabolite, are 1800 ng/mL for children and teenagers and 2800 ng/mL for adults, respectively. Similarly, for DINCH metabolites, the combined HBM-I values of MHNCN and MCOCH are 3000 ng/mL for children and teenagers and 4500 ng/mL for adults, respectively. Differentiated biological exposure thresholds have been established for MPHHP, a DPHP metabolite, with HBM-GV_GenPop set at 140 ng/mL for children and teenagers and 220 ng/mL for adults, respectively.

HQ was calculated as a ratio to compare the EDI value with the tolerable daily intake (TDI) reference values for DEHTP and DINCH and reference doses (RfD) for DPHP. HQs was used to assess the hazards posed by exposures of people to individual aPAEs, which greater than 1 indicates potential health risks to humans. The TDI value for DEHTP is 540 μg/kg bw/day, as established by the German HBM Commission, whereas for DINCH, the TDI is 1000 μg/kg bw/day, as defined by the European Food and Safety Authority (EFSA). The RfD for DPHP (100 μg/kg bw/day) was derived from the human equivalent BMDL₁₀ (the benchmark dose resulting in a 10% extra cancer incidence) based on thyroid follicular hypertrophy/hyperplasia. HI was calculated as the cumulative metric of HQs for aPAEs sharing common adverse outcome. The values of HI above 1 indicate that the aggregate exposure to these compounds exceeds the TDI or RfD, thereby indicating a probability of combined toxic effects through additive or synergistic interactions.

Table presents the risk assessment based on the HBM and similar TDI/RfD references. The highest calculated RQs were 0.461 for DEHTP, 0.320 for DINCH, and 0.132 for DPHP, all of which are well below 1. For HQs, the DEHTP (maximum: 0.566), DINCH (maximum: 0.390), and DPHP (maximum: 0.081) do not pose a toxicological risk. The RQ and HQ for DEHTP exhibited significant spatial and age-related variations. Notably, DEHTP exposure was significantly higher in Suining (median RQ: 0.009, HQ: 0.012) compared to Chengdu (median RQ: 0.004, HQ: 0.008) (p < 0.01). The median RQ of DEHTP in teenagers (0.012) were 2 times higher than that in children (0.006) and 3 times higher than that in adults (0.004) (p < 0.01). Similarly, the maximum RQ and HQ of DEHTP in teenagers (0.461 and 0.566, respectively) were over 10 times higher than those in children (0.037 and 0.040, respectively) and adults (0.035 and 0.059, respectively). DINCH exhibited low exposure risks, with more than half of the RQs and HQs being 1000 times below the thresholds. All RQs and HQs for DPHP were considerably below 1. The median values (RQ: 0.005; HQ: 0.003) were approximately 250-fold lower than this threshold, while the maximum values (RQ: 0.132; HQ: 0.081) were still nearly 10-fold lower than this safety limit. Moreover, to determine the equivalence between the two risk assessment methods, RQs and HQs were compared and evaluated using linear regression analysis and Bland–Altman analysis. All aPAEs showed strong correlations with correlation coefficients of R exceeding 0.93. The Bland–Altman analysis revealed strong concordance between RQ and HQ measurements. More than 95% of the measurements remained clustered within acceptable limits of agreement and were closely distributed around the mean difference line (Figure ).

4.

Methodological comparison of risk assessment approaches for aPAEs. Regression and Bland–Altman plots comparing RQs and HQs for DEHTP (A, B), DINCH (C, D), and DPHP (E, F). Horizontal blue lines denote mean differences, with red dashed lines marking limits of agreement (mean difference ± 1.96 SD) (B, D, F).

Overall, the maximum value of HIs (0.578) of aPAEs in this study is well below the thresholds, indicating no acute health risks. It should be noted that the concentrations of aPAE metabolites were determined in the first morning urine void, which was the only sample available in this study. However, for plasticizers with short elimination half-lives, particularly when dietary intake is the primary exposure pathway, this sampling method may result in an underestimation of exposure by a factor of up to 2. ,

4. Conclusion

This study presented the concentrations and exposure profiles of aPAE metabolites in urine collected in Chengdu and Suining, Sichuan Province, in southwestern China. The factors influencing the exposure of the aPAEs were further examined. The metabolites of DENTP, DINCH, and DPHP, such as MEHHTP, MECPTP, and MINCH, were commonly found in urine samples (detection rate: 100%), among which MECPTP was identified as the most predominant metabolite of aPAEs, accounting for more than 50% of the total concentrations. Analysis of correlations between regional and demographic factors (sex, age, and BMI) with urinary metabolites revealed that females and teenagers are generally at relatively higher exposure risk. Urinary metabolite concentrations for DEHTP, DINCH, and DPHP, at both median and maximum levels, were well below the health-based limit values.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/envhealth.5c00080.

• Source of target analytes, optimized LC-MS/MS parameters, QA/QC details, complied urinary concentrations of target analytes, parameters for risk assessment, and total chromatograms of metabolites (PDF)

Jing Ren: Sample analysis, Data curation, and Writing–original draft. Qingqing Zhu: Writing–review and editing. Chunyang Liao: Conceptualization, Writing–review and editing, Supervision, and Funding acquisition. Guibin Jiang: Resources and Supervision. All authors contributed extensively to conducting the experiments and revising the paper.

The authors declare no competing financial interest.

Published as part of Environment & Health special issue “New Pollutants: Challenges and Prospects”.