
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39251808
72147
10.1038/s41598-024-72147-y
Article
Association between urinary phthalate metabolites and Anemia in US adults
Ma Huimiao 12
Deng Wenqi 1
Liu Junxia liujunxia1983@sina.cn

2
Ding Xiaoqing dingxiaoqing1973@sina.com

2
1 https://ror.org/05damtm70 grid.24695.3c 0000 0001 1431 9176 Beijing University of Chinese Medicine, Beijing, 100029 China
2 https://ror.org/05damtm70 grid.24695.3c 0000 0001 1431 9176 Department of Hematology, Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, 100078 China
9 9 2024
9 9 2024
2024
14 2104118 1 2024
4 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Initial research indicates a possible connection between exposure to phthalates and the development of anemia. To fill the gap in epidemiological data, our study utilized data from across the United States, representative on a national scale, to evaluate the association between the concentration of phthalate metabolites in urine and both anemia and iron levels. We gathered data on 11,406 individuals from the National Health and Nutrition Examination Survey (NHANES) database, spanning 2003–2018. We conducted logistic and linear regression analyses, adjusted for potential confounding factors, to evaluate the correlations between different phthalate metabolites and anemia, as well as serum iron levels, including gender-stratified analysis. Most urinary phthalate metabolites were positively correlated with an increased risk of anemia, and the majority were negatively correlated with serum iron levels. The study revealed that for every unit increase in ln-transformed metabolite concentrations, the odds ratios (ORs) for anemia increased to varying degrees, depending on the phthalate: Monobutyl phthalate (MBP) at 1.08 (95% CI 1.01–1.17, P = 0.0314), mono(3-carboxypropyl) phthalate (MCPP) at 1.17 (95% CI 1.10–1.24, P < 0.0001), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) at 1.08 (95% CI 1.02–1.15, P = 0.0153), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) at 1.14 (95% CI 1.07–1.21, P < 0.0001), mono(2-ethyl-5-carboxypentyl) phthalate (MECPP) at 1.11 (95% CI 1.03–1.18, P = 0.0030), monocarboxynonyl phthalate (MCNP) at 1.11 (95% CI 1.03–1.19, p = 0.0050), and monocarboxyoctyl phthalate (MCOP) at 1.13 (95% CI 1.07–1.19, P < 0.0001). Increased levels of MBP, MEHP, MBzP, MCPP, MEHHP, MEOHP, MIBP, MECPP, MCNP, and MCOP were linked with changes in serum iron levels, ranging from − 0.99 µg/dL (95% CI − 1.69 to − 0.29) to − 3.72 µg/dL (95% CI − 4.32 to − 3.11). Mixed-exposure analysis shows consistency with single-exposure model. Further mediation analysis showed that the association between single urinary phthalates and the risk of anemia was mediated by serum iron with a mediation ratio of 24.34–95.48% (P < 0.05). The presence of phthalate metabolites in urine shows a positive correlation with the prevalence of anemia, which was possibly and partly mediated by iron metabolism. Nonetheless, to confirm a definitive causal link and comprehend the underlying mechanisms of how phthalate exposure influences anemia, additional longitudinal and experimental research is required.

Subject terms

Environmental impact
Environmental sciences
Diseases
Risk factors
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Anemia, characterised by suboptimal haemoglobin or red blood cell counts, manifests clinically in varied forms. Globally, this condition constitutes a significant health concern, afflicting nearly one-third of the population1. Anemia is significantly correlated with adverse pregnancy outcomes in women and may also serve as a risk or prognostic indicator for conditions such as heart failure2,3. Beyond its health implications, anemia diminishes physical vigour and work efficiency in the adult workforce, thereby impacting productivity4. An increasing trend in anemia among the elderly underscores its escalating role as both a health and economic challenge5. Given that the majority of cases are linked to iron deficiency6, targeted strategies to mitigate anemia are imperative.

Phthalates, known as diesters of phthalic acid, are a prevalent group of chemicals used as plasticizers in a vast range of products. Their presence extends beyond industrial and medical items such as cleaning supplies, medical devices7,8 (including intravenous fluid bags, catheters, gloves) to everyday consumer products like toys, food packaging materials9, cosmetics, and personal care products10,11. The ubiquitous nature of phthalates, coupled with their non-covalent bonding to plastics, facilitates their easy release into the environment12, leading to widespread human exposure through dietary intake, inhalation, and skin contact. This raises significant environmental and health concerns13,14.

A multitude of studies has linked phthalate exposure to several detrimental health outcomes, including reproductive and developmental problems15,16, hormonal imbalances17, and an increased risk of diseases like coronary heart disease18 and hypertension19. Despite regulations aimed at reducing phthalate exposure, their metabolites continue to be found in the general populace, indicating ongoing exposure. Phthalate metabolites in human urine, typically present as glucuronide conjugates, are primarily excreted by the kidneys20. Urinary measurements of these metabolites are deemed more reliable and accurate than other biological samples, owing to the absence of active esterases that can degrade the original phthalate metabolites18.

Emerging evidence from animal studies has demonstrated that phthalate exposure can lead to decreased haemoglobin levels and red blood cells21,22. Moreover, research from two separate studies on pregnant women in China23,24 and one cross-sectional study based on a Korean database25 identified a negative relationship between the levels of phthalate metabolites in urine and hemoglobin concentrations. Nevertheless, the epidemiological evidence regarding the effect of phthalate exposure on anemia prevalence remains scarce. Thus, employing data representative of the United States, our research examines the link between phthalate exposure, anemia, and serum iron levels, aiming to explore this association within the general US population.

Materials and methods

Study population and design

NHANES is a biennial survey that evaluates the health and dietary habits of the non-institutionalized civilian populace in the US26. This effort is spearheaded by the National Center for Health Statistics, part of the Centers for Disease Control and Prevention (CDC). (https://www.cdc.gov/nchs/nhanes/index.htm). To ensure the sample reflects the broader population, NHANES employs a "layered multistage probability sampling" technique. Our research analysed data from 8 continuous NHANES cycles from 2003/2004 to 2017/2018. We excluded participants based on the following criteria: (1) below 20 years old, (2) missing data on hemoglobin (Hgb) and Urinary phthalate metabolites, (3) participants who were pregnant. After these exclusions, our study encompassed 11,406 qualified participants aged 20 years and older (Fig. 1). The Ethical Review Board of The National Center for Health Statistics approved our study. Additionally, all involved individuals provided informed consent at the time the specimens were collected.Fig. 1 Flow chart of participants selection. NHANES National Health and Nutrition Examination Survey.

Assessment of anemia

Based on the criteria set by the World Health Organization (WHO)27, anemia was characterized by Hgb concentrations less than 12 g/dL in females and under 13 g/dL in males.

Urinary phthalate metabolites

Participant urine samples were collected to assess exposure to phthalate metabolites. The methodology, quality assurance, monitoring, and outcome determination are based on established research and detailed on the Centers for Disease Control and Prevention's website in 2021. High-performance liquid chromatography–electrospray ionization–tandem mass1spectrometry (HPLC–ESI–MS/MS) was employed by the National Center for Environmental Health (NCEH) to analyze the phthalate metabolites. Detailed contents of analysis methods can be queried on the website (https://wwwn.cdc.gov/Nchs/Nhanes/analyticguidelines.aspx). Our study selected 12 metabolites from all 8 testing rounds, excluding those with measurements below the limit of detection (LOD) in over 40% of samples. In our study, urinary concentrations of phthalate metabolites were above the detection limit for at least 90% of the subjects. For values below this limit, the detection threshold was divided by the square root of two as a replacement28. The study analysed 11 specific phthalate metabolites, which are as follows: Monoethyl phthalate (MEP), Mono-isobutyl phthalate (MIBP), Monobutyl phthalate (MBP), Monobenzyl phthalate (MBzP), Mono (3-carboxypropyl) phthalate (MCPP), Mono (2-ethylhexyl) phthalate (MEHP), Mono (2-ethyl-5-oxohexyl) phthalate (MEOHP), Mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), Mono (2-ethyl-5-carboxypentyl) phthalate (MECPP), Monocarboxynonyl phthalate (MCNP),Monocarboxyoctyl phthalate (MCOP). The detailed protocol is described (https://wwwn.cdc.gov/Nchs/Nhanes/analyticguidelines.aspx).

Covariates

During the familial interview, an array of demographic variables including gender, age, marital status, Academic level, race, and the Poverty Income Ratio (PIR) were meticulously collected utilizing a standardized questionnaire. Concurrently, lifestyle factors encompassing smoking and alcohol consumption status, as well as Body Mass Index (BMI), were assessed. Additionally, a comprehensive medical history encompassing hypertension, hypercholesterolemia, diabetes mellitus, coronary artery disease, congestive heart failure, and any oncological conditions was meticulously compiled.

Educational attainment was systematically categorized into three distinct echelons: sub-high school level, high school diploma or its equivalent, and college degree or higher. Racial and ethnic classifications were delineated into five major categories: Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, and Other Race. The familial PIR served as a quantitative metric to gauge the family’s economic standing relative to the poverty threshold, subsequently categorized into tertiles: less than 1.3, between 1.3 and 3.5, and greater than 3.5.

Individuals were classified as smokers if they had a lifetime consumption of 100 cigarettes or more, and as alcohol consumers if they ingested a minimum of 12 alcoholic beverages annually. Standardized methodologies were employed to derive laboratory measurements, encompassing White Blood Cell (WBC) count, Red Blood Cell (RBC) count, platelet count, hematocrit, Mean Cell Volume (MCV), Mean Cell Hemoglobin Concentration (MCHC), Mean Cell Hemoglobin (MCH), serum iron, ferritin, urinary creatinine analysis.

Statistical analysis

All data analyses were conducted using the R statistical software (version 4.2.0) and Empower Stats software (available at http://www.empowerstats.net). The data were weighted and analysed in accordance with the existing NHANES guidelines. Continuous variables that follow a normal distribution were reported as the mean ± standard deviation, while categorical variables were shown as frequencies or percentages. The study detailed the concentrations of 11 different urinary phthalate metabolites and assessed their distribution. The normality of continuous variables was evaluated using the Kolmogorov–Smirnov test. To better align with a normal distribution, concentrations of urinary phthalate metabolites underwent a natural logarithm (ln) transformation before statistical analysis. The analysis utilized logistic regression to investigate the influence of exposure factors on diseases. Urinary phthalate metabolite levels were divided into quartiles, with the first quartile being the reference group. For accounting for other variables potentially impacting anemia, multivariate regression analysis was conducted using three separate models. Model 1 did not adjust for any covariates. Model 2 included adjustments for gender, age, and race. Model 3 entailed adjustments for all covariates (Covariates were included as potential confounders in the final models if they changed the estimates of urinary phthalate metabolites on Anemia by more than 10% or were significantly associated with Anemia. The following covariates were selected a priori on the basis of established associations and/or plausible biological relations and tested: Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy,Creatinine(urine).). Furthermore, taking into account the impact of gender, the data were stratified by sex to conduct subgroup analyses, ensuring a nuanced examination of the results. Linear regression was also employed to investigate the influence of exposure factors on serum iron levels in adults. We employed smoothing curve fitting and the Generalized Additive Model (GAM) to investigate potential non-linear relationships. Mediation analyses used the quasi-Bayesian Monte Carlo method with 1000 simulations based on normal approximation. The final Weighted Quantile Sum (WQS) index is calculated as the average of the weights derived from 1000 bootstrap samples. All analyses used a significance level of P < 0.05 to determine statistical significance.

Results

Baseline characteristics

The study encompassed 11,406 participants, with a mean age of 49.71 ± 17.68 years, consisting of 49.54% males and 50.46% females. Among the participants, 10.01% had anemia.

The clinical characteristics of patients with and without anemia are detailed in Table 1. Patients in the anemic group were significantly older than those in the non-anemic group, with mean ages of 53.13 ± 18.32 years and 46.97 ± 16.69 years, respectively (P < 0.05). The anemic group had a higher proportion of females (70.38% compared to 29.62% in the non-anemic group, P < 0.05) and a higher prevalence of Non-Hispanic Black ethnicity (46.07%). Additionally, the mean body mass index (BMI) was slightly higher in the anemic group at 29.82 ± 8.04 kg/m2, compared to 28.92 ± 6.83 kg/m2 in the non-anemic group (P < 0.05). Patients with anemia also tended to have lower levels of education and annual household income. Notably, there was a higher incidence of comorbid conditions such as hypertension, dyslipidemia, diabetes, heart failure, coronary heart disease, and cancer among anemic patients compared to their non-anemic counterparts. Concurrently, hematological assessments indicated that the levels of Hematocrit, Mean Cell Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC) and serum iron were significantly lower in the anemic population.Table 1 Weighted characteristics of the study population based on Anemia.

	Non-anemia (N = 10,264)	Anemia (N = 1142)	P-value	
Age	46.97 ± 16.69	53.13 ± 18.32	< 0.0001	
Gender (%)			< 0.0001	
 Male	50.45	29.62		
 Female	49.55	70.38		
Race (%)			< 0.0001	
 Mexican American	8.19	8.46		
 Other Hispanic	5.60	5.88		
 Non-Hispanic White	68.89	46.07		
 Non-Hispanic Black	9.70	31.63		
 Other race	7.62	7.96		
Academic level (%)			< 0.0001	
 Less than high school	15.43	22.02		
 High school or equivalent	23.29	25.39		
 College or above	61.28	52.59		
Marital status (%)			< 0.0001	
 Married	71.95	74.24		
 Separated	2.26	4.56		
 Never married	25.79	21.20		
PIR (%)			< 0.0001	
 < 1.3	18.83	28.03		
 1.3–3.5	32.24	33.84		
 > 3.5	41.82	27.62		
 Mean ± SD	3.07 ± 1.65	2.52 ± 1.64		
Drinking (%)			< 0.0001	
 No	17.11	25.09		
 Yes	61.30	50.48		
 Missing	21.60	24.43		
Smoking (%)			< 0.0001	
 No	55.22	62.70		
 Yes	44.78	37.30		
BMI (kg/m2)	28.92 ± 6.83	29.82 ± 8.04	0.0007	
Hypertension (%)			< 0.0001	
 No	69.04	54.15		
 Yes	30.96	45.85		
High cholesterol (%)			0.0056	
 No	56.05	53.21		
 Yes	32.71	37.91		
 Missing	11.24	8.88		
Diabetes (%)			< 0.0001	
 No	91.07	79.39		
 Yes	8.93	20.61		
Congestive heart failure (%)			< 0.0001	
 No	98.30	93.06		
 Yes	1.70	6.94		
Coronary heart disease (%)			< 0.0001	
 No	96.63	92.51		
 Yes	3.37	7.49		
Cancer or malignancy (%)			< 0.0001	
 No	90.76	85.85		
 Yes	9.24	14.15		
White blood cell (103 cells/uL)	7.31 ± 2.24	7.37 ± 8.59	0.5872	
Red blood cell (106 cells/uL)	4.74 ± 0.45	4.15 ± 0.52	< 0.0001	
Platelet (103 cells/uL)	246.16 ± 61.77	266.44 ± 85.75	< 0.0001	
Hematocrit (%)	42.54 ± 3.57	34.29 ± 2.96	< 0.0001	
Mean cell volume (fL)	89.90 ± 4.83	83.52 ± 9.78	< 0.0001	
Mean cell hemoglobin (pg)	30.61 ± 1.94	27.60 ± 4.21	< 0.0001	
MCHC (g/dL)	34.05 ± 0.94	32.94 ± 1.75	< 0.0001	
Serum iron (µg/dL)	89.83 ± 35.46	54.12 ± 33.10	< 0.0001	
BMI body mass index, PIR ratio of family income to poverty.

The distributions of urinary phthalate metabolite concentrations and urinary creatinine levels

In our study, 11 different urinary phthalate metabolites were detected in over 90% of the participants, showing widespread exposure within the sample group. Table 2 in the study displays the interquartile ranges for the average concentrations of these metabolites along with urinary creatinine levels. It's noteworthy that Monoethyl phthalate (MEP) had the highest concentration among all the phthalate metabolites in the urinary samples. Additionally, a pairwise Pearson correlation test conducted on the concentrations of these 11 metabolites revealed significant statistical correlations (P < 0.001) with correlation coefficients (r values) ranging between 0.18 and 0.98 (Supplemental Table 1).Table 2 Distribution of exposure biomarkers (N = 11,406), NHANES, USA, 2003–2018.

Analyte	% > LOD	Mean	P25	P50	P75	
Urinary phthalate metabolites (µg/L)	
 MBP	98.47	25.50	6.00	13.03	26.00	
 MEP	99.96	285.65	19.67	53.64	171.98	
 MEHP	92.55	4.52	0.57	1.30	3.10	
 MBZP	97.28	11.03	2.00	4.82	11.66	
 MCPP	98.40	5.89	0.80	1.80	4.00	
 MEHHP	99.94	28.74	4.20	9.20	20.68	
 MEOHP	99.51	16.81	2.70	5.80	12.50	
 MIBP	99.78	12.99	3.60	7.60	14.90	
 MECPP	99.94	39.30	6.80	14.40	30.60	
 MCNP	98.31	4.69	1.00	2.00	4.10	
 MCOP	99.96	28.58	3.41	7.70	21.30	
Creatinine, urine (mg/dL)	100	125.26	64.00	111.00	169.00	
MEP monoethyl phthalate, MBP monobutyl phthalate, MIBP mono-isobutyl phthalate, MCPP mono (3-carboxypropyl) phthalate, MEHP mono(2-ethylhexyl) phthalate, MBzP monobenzyl phthalate, MEOHP mono(2-ethyl-5-oxohexyl) phthalate, MEHHP mono(2-ethyl-5-hydroxyhexyl) phthalate, MECPP mono(2-ethyl-5-carboxypentyl) phthalate, MCOP monocarboxyoctyl phthalate, MCNP monocarboxynonyl phthalate.

The relationship between the concentrations of phthalate metabolites in urine and the occurrence of anemia

Table 3 presents the results from both univariable and multivariable logistic regression analyses that explore the association between urinary phthalate metabolite levels and the occurrence of anemia. In the adjusted multivariable model (Model 3), a significant association was observed for several metabolites, including MBP, MCPP, MEHHP, MEOHP, MECPP, MCNP, and MCOP with the incidence of anemia. The adjusted odds ratios (ORs) for anemia per unit increase in the ln-transformed concentrations of the metabolites were as follows: MBP at 1.08 (95% CI 1.01, 1.17, P = 0.0314), MCPP at 1.17 (95% CI 1.10, 1.24, P < 0.0001), MEHHP at 1.08 (95% CI 1.02, 1.15, P = 0.0153), MEOHP at 1.14 (95% CI 1.07, 1.21, P < 0.0001), MECPP at 1.11 (95% CI 1.03, 1.18, P = 0.0030), MCNP at 1.11 (95% CI 1.03, 1.19, P = 0.0050), and MCOP at 1.13 (95% CI 1.07, 1.19, P < 0.0001). Compared to individuals in the lowest quartile of exposure, those in the highest quartile experienced a 1.33-fold, 1.66-fold, 1.29-fold, 1.54-fold, 1.32-fold, 1.33-fold, and 1.56-fold increased risk of anemia, respectively, for these metabolites (P for trend < 0.05).Table 3 Logistic regression associations of urinary phthalates ln (µg/L) with anemia in adults.

	MODEL 1
OR (95% CI) P-value	MODEL 2
OR (95% CI) P-value	MODEL 3
OR (95% CI) P-value	
MBP	1.11 (1.05, 1.17) < 0.0001	1.07 (1.02, 1.13) 0.0099	1.08 (1.01, 1.17) 0.0314	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.19 (0.99, 1.42) 0.0652	1.12 (0.93, 1.35) 0.2418	1.14 (0.93, 1.41) 0.2133	
  Quartile 3	1.26 (1.05, 1.51) 0.0115	1.19 (0.99, 1.43) 0.0685	1.22 (0.98, 1.53) 0.0817	
  Quartile 4	1.42 (1.19, 1.69) 0.0001	1.27 (1.06, 1.53) 0.0103	1.33 (1.04, 1.70) 0.0247	
  P for trend	< 0.0001	0.0081	0.0230	
MEP	1.06 (1.02, 1.10) 0.0020	0.99 (0.95, 1.03) 0.6467	0.99 (0.94, 1.04) 0.6319	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.28 (1.07, 1.53) 0.0065	1.14 (0.95, 1.38) 0.1577	1.22 (0.99, 1.51) 0.0579	
  Quartile 3	1.27 (1.06, 1.52) 0.0086	1.02 (0.84, 1.23) 0.8457	1.06 (0.85, 1.31) 0.6234	
  Quartile 4	1.32 (1.10, 1.58) 0.0023	0.99 (0.82, 1.20) 0.9495	1.04 (0.83, 1.30) 0.7358	
  P for trend	0.0059	0.5672	0.7387	
MEHP	0.99 (0.94, 1.05) 0.8128	1.05 (0.99, 1.11) 0.1294	1.06 (0.99, 1.13) 0.1097	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	0.87 (0.69, 1.10) 0.2543	0.82 (0.64, 1.04) 0.0964	0.75 (0.58, 0.97) 0.0265	
  Quartile 3	0.88 (0.69, 1.12) 0.3018	0.90 (0.70, 1.16) 0.4102	0.83 (0.63, 1.09) 0.1845	
  Quartile 4	0.93 (0.74, 1.19) 0.5837	1.02 (0.79, 1.31) 0.8991	0.98 (0.74, 1.29) 0.8634	
  P for trend	0.8030	0.0644	0.0847	
MBZP	1.06 (1.01, 1.11) 0.0099	1.09 (1.04, 1.14) 0.0008	1.05 (0.99, 1.13) 0.1141	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.10 (0.92, 1.31) 0.2937	1.13 (0.94, 1.36) 0.1797	1.14 (0.93, 1.40) 0.2117	
  Quartile 3	1.11 (0.93, 1.32) 0.2598	1.14 (0.95, 1.38) 0.1567	1.16 (0.93, 1.43) 0.1863	
  Quartile 4	1.28 (1.07, 1.52) 0.0057	1.41 (1.18, 1.70) 0.0002	1.31 (1.03, 1.66) 0.0276	
  P for trend	0.0071	0.0003	0.0332	
MCPP	1.08 (1.03, 1.13) 0.0021	1.12 (1.07, 1.18) < 0.0001	1.17 (1.10, 1.24) < 0.0001	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.25 (1.04, 1.50) 0.0151	1.26 (1.05, 1.52) 0.0137	1.37 (1.11, 1.69) 0.0036	
  Quartile 3	1.29 (1.08, 1.55) 0.0050	1.34 (1.12, 1.62) 0.0018	1.56 (1.26, 1.95) < 0.0001	
  Quartile 4	1.26 (1.05, 1.50) 0.0134	1.43 (1.18, 1.72) 0.0002	1.66 (1.32, 2.09) < 0.0001	
  P for trend	0.0157	0.0002	< 0.0001	
MEHHP	1.04 (0.99, 1.09) 0.0985	1.06 (1.01, 1.11) 0.0244	1.08 (1.02, 1.15) 0.0153	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.26 (1.05, 1.50) 0.0123	1.21 (1.01, 1.46) 0.0399	1.21 (0.98, 1.49) 0.0757	
  Quartile 3	1.37 (1.15, 1.63) 0.0005	1.37 (1.14, 1.64) 0.0007	1.37 (1.11, 1.70) 0.0039	
  Quartile 4	1.19 (0.99, 1.43) 0.0582	1.23 (1.02, 1.48) 0.0336	1.29 (1.02, 1.64) 0.0311	
  P for trend	0.0481	0.0206	0.0260	
MEOHP	1.08 (1.03, 1.14) 0.0007	1.10 (1.05, 1.16) 0.0002	1.14 (1.07, 1.21) < 0.0001	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.32 (1.10, 1.59) 0.0024	1.29 (1.07, 1.55) 0.0079	1.31 (1.06, 1.62) 0.0119	
  Quartile 3	1.42 (1.19, 1.70) 0.0001	1.41 (1.17, 1.69) 0.0003	1.47 (1.18, 1.83) 0.0006	
  Quartile 4	1.37 (1.14, 1.64) 0.0006	1.39 (1.16, 1.68) 0.0005	1.54 (1.22, 1.95) 0.0003	
  P for trend	0.0007	0.0004	0.0004	
MIBP	1.10 (1.04, 1.17) 0.0004	1.07 (1.01, 1.14) 0.0179	1.07 (0.99, 1.16) 0.0812	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.02 (0.85, 1.22) 0.8393	1.02 (0.85, 1.23) 0.8281	1.00 (0.81, 1.23) 0.9862	
  Quartile 3	1.06 (0.89, 1.27) 0.4913	1.03 (0.86, 1.24) 0.7540	0.98 (0.79, 1.22) 0.8634	
  Quartile 4	1.31 (1.10, 1.56) 0.0019	1.20 (1.00, 1.44) 0.0459	1.17 (0.92, 1.49) 0.2044	
  P for trend	0.0021	0.0530	0.2600	
MECPP	1.05 (1.00, 1.10) 0.0770	1.08 (1.02, 1.13) 0.0056	1.11 (1.03, 1.18) 0.0030	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.27 (1.06, 1.52) 0.0082	1.26 (1.05, 1.52) 0.0125	1.26 (1.03, 1.55) 0.0268	
  Quartile 3	1.33 (1.12, 1.59) 0.0015	1.33 (1.11, 1.60) 0.0020	1.34 (1.07, 1.66) 0.0090	
  Quartile 4	1.18 (0.99, 1.42) 0.0684	1.27 (1.05, 1.53) 0.0134	1.32 (1.04, 1.67) 0.0214	
  P for trend	0.0749	0.0134	0.0287	
MCNP	1.02 (0.97, 1.08) 0.4101	1.07 (1.01, 1.13) 0.0285	1.11 (1.03, 1.19) 0.0050	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.00 (0.84, 1.19) 0.9751	1.02 (0.85, 1.22) 0.8674	1.02 (0.83, 1.25) 0.8690	
  Quartile 3	0.99 (0.84, 1.18) 0.9526	1.08 (0.90, 1.30) 0.3852	1.19 (0.96, 1.47) 0.1162	
  Quartile 4	1.07 (0.90, 1.27) 0.4415	1.23 (1.02, 1.48) 0.0266	1.33 (1.06, 1.67) 0.0153	
  P for trend	0.4400	0.0182	0.0060	
MCOP	1.06 (1.02, 1.11) 0.0049	1.10 (1.05, 1.15) < 0.0001	1.13 (1.07, 1.19) < 0.0001	
 Quintiles	
  Quartile 1	Reference	Reference	Reference	
  Quartile 2	1.25 (1.05, 1.50) 0.0130	1.31 (1.09, 1.58) 0.0041	1.27 (1.03, 1.56) 0.0250	
  Quartile 3	1.23 (1.03, 1.47) 0.0233	1.33 (1.10, 1.60) 0.0026	1.31 (1.06, 1.62) 0.0128	
  Quartile 4	1.32 (1.11, 1.58) 0.0020	1.49 (1.24, 1.79) < 0.0001	1.56 (1.26, 1.94) < 0.0001	
  P for trend	0.0054	< 0.0001	0.0001	
MODEL 1: No covariates were adjusted. MODEL 2: Age, Gender, Race were adjusted. MODEL 3: Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine (urine) were adjusted. 95% CI, 95% confidence interval; OR, odds ratio.

Gender-specific subgroup analysis yielded variable results (Fig. 2): in men, elevated levels of MCPP, MEOHP, MECPP, and MCOP were linked to heightened anemia risk. In women, positive correlations with anemia were noted for MCPP, MCNP, and MCOP. Figure 3 displays the association between urinary phthalate metabolites and anemia, where positive correlations were noted across all these metabolites. The concurrent analysis shows that most urinary phthalate metabolites are negatively associated with hemoglobin levels in adults, as detailed in Supplemental Table 3.Fig. 2 Multivariate odds ratio for Anemia according to urinary phthalates levels by gender. Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine(urine) were adjusted. 95% CI 95% confidence interval, OR odds ratio.

Fig. 3 Association between urinary phthalate metabolites and anemia. The vertical axis represents log OR of anemia. Adjusted for all covariates.

To assess the overall effect of the metabolites on anemia, we applied weighted quantile sum regression, as shown in Fig. 4. This analysis found a significant positive correlation between the overall effect of the metabolites and anemia outcomes. For every interquartile range (IQR) increase in the WQS index, the risk of anemia increased by 0.1875 (95% CI 0.0886–0.2865, P = 0.0002).Fig. 4 Impact of Phthalates on Anemia: Weighted Quantile Sum (WQS) Analysis Models were adjusted for Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine(urine).

Association between urinary phthalate metabolite concentrations and serum iron

Table 4 illustrates the findings from multiple linear regression analyses, indicating a predominantly negative association between urinary phthalate metabolite concentrations and serum iron levels in Model 3. An increase in MBP, MEHP, MBZP, MCPP, MEHHP, MEOHP, MIBP, MECPP, MCNP, MCOP levels was associated with a − 0.99 µg/dL (95% confidence interval [CI] − 1.69 to − 0.29), − 3.37 µg/dL (95% CI − 4.01 to − 2.72), − 1.08 µg/ dL (95% CI − 1.70 to − 0.45), − 2.65 µg/dL (95% CI − 3.25 to − 2.05), − 3.23 µg/dL (95% CI − 3.82 to − 2.63), − 3.72 µg/dL (95% CI − 4.32 to − 3.11), − 1.10 µg/dL (95% CI − 1.85 to − 0.36), − 2.96 µg/dL (95% CI − 3.59 to − 2.32), − 0.99 µg/dL (95% CI − 1.67 to − 0.31), and − 1.28 µg/dL (95% CI − 1.80 to − 0.76) change in serum iron levels. Furthermore, in both the crude and adjusted models, there is a correlation between serum iron levels and the incidence of anemia ([OR] 0.96, 95% CI 0.96–0.97, P < 0.05). Additionally, a lower serum iron level is associated with a higher risk of anemia. This trend is evident in Supplemental Table 2 (P for trend < 0.05). To explore the overall effect of the metabolites on serum iron, we applied WQS regression, as shown in Fig. 5. The analysis revealed a significant negative correlation between the overall effect of phthalates and serum iron concentrations. Specifically, for each interquartile range (IQR) increase in the WQS index, serum iron levels decrease by − 4.730 µg/dL (95% CI − 5.6659 to − 3.7990, P < 0.0001).Table 4 Linear regression associations of urinary phthalates ln (µg/L) with serum iron (µg/dL)in adults.

	Male
β (95% CI) P-value	Female
β (95% CI) P-value	Total
β (95% CI) P-value	
MBP	− 1.16 (− 2.20, − 0.12) 0.0287	− 0.70 (− 1.65, 0.26) 0.1522	− 0.99 (− 1.69, − 0.29) 0.0055	
MEP	0.21 (− 0.44, 0.86) 0.5255	0.24 (− 0.42, 0.89) 0.4807	0.21 (− 0.25, 0.67) 0.3781	
MEHP	− 3.75 (− 4.64, − 2.86) < 0.0001	− 2.84 (− 3.78, − 1.90) < 0.0001	− 3.37 (− 4.01, − 2.72) < 0.0001	
MBZP	− 1.62 (− 2.53, − 0.71) 0.0005	− 0.51 (− 1.38, 0.35) 0.2446	− 1.08 (− 1.70, − 0.45) 0.0007	
MCPP	− 3.23 (− 4.10, − 2.37) < 0.0001	− 2.04 (− 2.88, − 1.20) < 0.0001	− 2.65 (− 3.25, − 2.05) < 0.0001	
MEHHP	− 3.46 (− 4.29, − 2.62) < 0.0001	− 2.91 (− 3.75, − 2.06) < 0.0001	− 3.23 (− 3.82, − 2.63) < 0.0001	
MEOHP	− 3.97 (− 4.82, − 3.11) < 0.0001	− 3.34 (− 4.21, − 2.46) < 0.0001	− 3.72 (− 4.32, − 3.11) < 0.0001	
MIBP	− 1.28 (− 2.37, − 0.19) 0.0214	− 0.80 (− 1.85, 0.25) 0.1344	− 1.10 (− 1.85, − 0.36) 0.0038	
MECPP	− 3.08 (− 3.97, − 2.20) < 0.0001	− 2.75 (− 3.66, − 1.85) < 0.0001	− 2.96 (− 3.59, − 2.32) < 0.0001	
MCNP	− 1.62 (− 2.61, − 0.63) 0.0013	− 0.43 (− 1.38, 0.51) 0.3697	− 0.99 (− 1.67, − 0.31) 0.0044	
MCOP	− 2.03 (− 2.78, − 1.28) < 0.0001	− 0.60 (− 1.32, 0.13) 0.1070	− 1.28 (− 1.80, − 0.76) < 0.0001	
Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine (urine) were adjusted. 95% CI, 95% confidence interval; β, Beta.

Fig. 5 Impact_of_Phthalates_on_Serum_Iron_Levels:_WQS_Analysis. Models were adjusted for Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine(urine).

Serum iron as a mediator in the relationship between urinary phthalates and anemia

Our study investigated the mediation role of serum iron in the relationship between urinary phthalate levels and anemia. Significant total effects on anemia were noted for several phthalates. MBP had a total effect of 0.0105 (95% CI 0.0020, 0.0194, P = 0.0180) with 28.56% of the effect mediated through serum iron (95% CI 6.35, 105.65%, P = 0.0220). MCPP showed a total effect of 0.0234 (95% CI 0.0162, 0.0312, P < 0.0001), with serum iron mediating 39.79% (95% CI 27.06, 59.08%, P < 0.0001) of this effect. MEHHP exhibited a total effect of 0.0113 (95% CI 0.0036, 0.0190, P = 0.0020), with 95.48% mediated by serum iron (95% CI 56.20, 284.12%, P = 0.0020). MEOHP demonstrated a total effect of 0.0166 (95% CI 0.0088, 0.0240, P < 0.0001), with serum iron accounting for 72.46% of the effect (95% CI 47.51, 133.02%, P < 0.0001). MECPP recorded a total effect of 0.0127 (95% CI 0.0053, 0.0202, P = 0.0020), with a 72.97% mediation by serum iron (95% CI 44.24, 171.44%, P = 0.0020). MCNP and MCOP also displayed significant total effects with MCNP showing a mediated proportion of 24.34% (95% CI 8.17, 63.03%, P < 0.0001) and MCOP at 26.59% (95% CI 14.89, 43.09%, P < 0.0001). These results underscore the important mediating role of serum iron in the relationship between phthalate exposure and anemia risk, as shown in Table 5.Table 5 Serum iron as a mediator in the relationship between ln-transformed urinary phthalates (µg/L) and anemia.

Phthalates	Total effect
Estimate (95% CI) P-value	Direct effects
Estimate (95% CI) P-value	Mediation effect
Estimate (95% CI) P-value	Proportion mediated
Estimate (95% CI) P-value	
MBP	0.0105 (0.0020, 0.0194) 0.0180	0.0075 (− 0.0004, 0.0158) 0.0780	0.0030 (0.0007, 0.0055) 0.0120	0.2856 (0.0635, 1.0565) 0.0220	
MEP	− 0.0031 (− 0.0118, 0.0053) 0.4700	− 0.0020 (− 0.0102, 0.0058) 0.6380	− 0.0011 (− 0.0033, 0.0012) 0.3600	0.3631 (− 3.6334, 3.5717) 0.5900	
MEHP	0.0094 (0.0000, 0.0185) 0.0500	− 0.0030 (− 0.0123, 0.0058) 0.5280	0.0124 (0.0095, 0.0156) < 0.0001	1.3164 (0.3840, 7.3130) 0.0500	
MBZP	0.0076 (− 0.0014, 0.0173) 0.0980	0.0036 (− 0.0046, 0.0126) 0.4380	0.0040 (0.0015, 0.0067) < 0.0001	0.5301 (− 1.8248, 4.0868) 0.0980	
MCPP	0.0234 (0.0162, 0.03120) < 0.0001	0.0141 (0.0072, 0.0217) < 0.0001	0.0093 (0.0070, 0.0120) < 0.0001	0.3979 (0.2706, 0.5908) < 0.0001	
MEHHP	0.0113) 0.0036, 0.0190) 0.0020	0.0005 (− 0.0070, 0.0078) 0.9040	0.0108 (0.0084, 0.0136) < 0.0001	0.9548 (0.5620, 2.8412) 0.0020	
MEOHP	0.0166 (0.0088, 0.0240) < 0.0001	0.0046 (− 0.0030, 0.0120) 0.2700	0.0120 (0.0094, 0.0150) < 0.0001	0.7246 (0.4751, 1.3302) < 0.0001	
MIBP	0.0088 (0.0000, 0.0182) 0.0500	0.0053 (− 0.0031, 0.0142) 0.2340	0.0035 (0.0012, 0.0063) 0.0020	0.3962 (− 0.0652, 2.6273) 0.0520	
MECPP	0.0127 (0.0053, 0.0202) 0.0020	0.0034 (− 0.0041, 0.0110) 0.3860	0.0092 (0.0069, 0.0118) < 0.0001	0.7297 (0.4424, 1.7144) 0.0020	
MCNP	0.0127 (0.0043, 0.0207) < 0.0001	0.0096 (0.0019, 0.0175) 0.0200	0.0031 (0.0010, 0.0054) < 0.0001	0.2434 (0.0817, 0.6303) < 0.0001	
MCOP	0.0198 (0.0117, 0.0276) < 0.0001	0.0145 (0.0069, 0.0225) < 0.0001	0.0053 (0.0030, 0.0076) < 0.0001	0.2659 (0.1489, 0.4309) < 0.0001	
Age, Gender, Race, Academic level, Marital status, PIR, drinking, Smoking, BMI, Hypertension, High cholesterol, Diabetes, Congestive heart failure, Coronary heart disease, Cancer or malignancy, Creatinine(urine) were adjusted.

Discussion

In our study utilizing the NHANES dataset, a representative cross-sectional sample of the US population, we uncovered positive correlations between urinary phthalate metabolite concentrations and the incidence of anemia. Specifically, individuals in the highest quartile of urinary phthalate metabolite concentrations demonstrated an increased risk of anemia compared to those in the lowest quartile. Additionally, our analysis revealed a negative correlation between urinary phthalate metabolites and both serum iron levels and hemoglobin (Hgb) concentrations, suggesting a potential mechanistic link between phthalate exposure and anemia.

Internationally, similar studies underscore the concern. A prospective cohort study in China investigated the relationship between prenatal exposure to phthalates and maternal anemia23 revealing that exposure to specific phthalates such as MMP, MBP, MEHP, MEOHP, and MEHHP elevated anemia risk. Additionally, samples from pregnant women in another prospective cohort study in Wuhan24 showed that after adjustment for false discovery rate (FDR), each unit increase in the natural log-transformed concentration of phthalates was associated with anemia, with adjusted odds ratios (ORs) being 1.25 for MEHP, 1.22 for MEOHP and MECPP, and a marginally significant association for MEHHP (adjusted OR = 1.19).

In South Korea25, data from the Korean National Environmental Health Survey (KONEHS) of 3722 adults indicated that individuals in the highest quartile for urinary phthalate metabolite concentrations had significantly higher risks of anemia.

Shifting focus to the United States, the situation presents a similarly concerning picture. In the US, more than 340 million pounds of phthalates are consumed each year29. This high level of consumption raises serious concerns about potential health risks and environmental degradation. Although studies in South Korea and China have begun to explore the connection between phthalate exposure and anemia, this relationship remains under-researched in the US. Given America's substantial phthalate usage, investigating this link in a domestic context becomes critical. While findings from Asian studies offer valuable knowledge, the US’s unique environmental, dietary, and lifestyle aspects may lead to different exposure effects and health implications. Our study targeting the US population comprehensively examined a broader range of metabolites and their impacts on a wider demographic. Our research provided specific adjusted odds ratios (ORs) related to the increase in anemia risk for each unit increase in the natural log-transformed concentrations of these phthalate metabolites. The ORs ranged from 1.08 to 1.17, indicating a significant yet moderate increase in the risk of anemia. Our study also compared anemia risks between the highest and lowest quartile groups for different metabolites, revealing that the risk increased by 1.29–1.66 times in the highest quartile group. Our study also discovered that the risk of anemia associated with phthalate exposure may differ between men and women, potentially due to variations in biology, hormone levels, or patterns of exposure. Alternatively, the difference could be attributed to gender-specific metabolic or reactive responses to these chemicals.

Phthalate-induced anemia is a complex phenomenon influenced by multiple mechanisms. The following discussion elaborates on how different phthalates may contribute to this condition. Phthalates may reduce oxidative stress and antioxidant capacity in red blood cells (RBCs) and affect anemia. Studies have shown that dimethyl phthalate (DMP) negatively impacts the antioxidant defenses of RBCs by diminishing levels of essential antioxidant enzymes, thereby compromising the oxidative integrity of red blood cells. For instance, exposure to DMP in rats has been associated with increased oxidative stress within RBCs, as evidenced by significant alterations in oxidative biomarkers21,30.

Phthalates may impact anemia through systemic inflammation and iron metabolism. Phthalate exposure is linked to systemic conditions such as non-alcoholic fatty liver disease (NAFLD), where inflammation secondary to obesity diminishes serum iron levels31,32. This inflammation-mediated reduction in iron availability is crucial as it impairs the iron-dependent processes of erythropoiesis, thereby contributing to the development of anemia.

Exposure to certain phthalates like Di (2-ethylhexyl) phthalate (DEHP) may induce renal damage, particularly in sensitive populations such as children33. This kidney damage can lead to impaired production of erythropoietin34, a critical hormone for the stimulation of red blood cell production in the bone marrow. Reduced erythropoietin levels result in decreased RBC production, manifesting as normocytic anemia.

Phthalates may promote anemia through direct effects on iron and hemoglobin homeostasis. Despite the limited scope of current research, emerging evidence underscores the significant impact of phthalates on anemia and iron metabolism. In a key study35, adult male Wistar rats were administered a single oral dose of pure Di-n-butyl Phthalate (DBP) (2.4 g/kg). The results showed significant reductions in blood iron and hemoglobin levels at 3 h post-administration, with corresponding increases in ferritin (Ft) and transferrin (Tf) levels in the spleen, and decreases in the liver. Additionally, hemosiderin levels significantly increased in both the liver and spleen. In another experiment36, 3-week-old Sprague-Dawley rats received a 1000 mg/kg dose of DEHP via gavage, leading to a significant decrease in liver iron levels in all DEHP-treated groups. These studies indicate that specific phthalates might hasten the dissociation of hemoglobin and transferrin into unbound iron within the liver and spleen, potentially leading to diminished blood iron levels and a consequent reduction in bone marrow hemoglobin production35. As a result, it may lead to the onset of anemia. Our study revealed that most phthalate metabolite concentrations were positively associated with the risk of anemia and negatively associated with serum iron and hemoglobin levels. Furthermore, serum iron was found to mediate the relationship between phthalate metabolites and anemia, corroborating findings from animal studies.

In our study, we synthesized the correlations between phthalate metabolites and anemia using the NHANES dataset, a well-recognized cross-sectional design. This research uniquely contributes to understanding the impact of plasticizers on anemia in the US population, a topic previously unexplored. We also investigated potential mechanisms of anemia development by examining the relationship between phthalate metabolites and serum iron levels. However, the study has several limitations. Firstly, the cross-sectional nature of NHANES constrains our ability to establish causal relationships between phthalate metabolites and anemia. Despite the reliability of our findings, NHANES lacks certain medical validations. Secondly, the measurement of plasticizer exposure might not accurately represent long-term exposure due to variability. While using urinary creatinine as a covariate to adjust for urinary dilution is a common method, it cannot completely eliminate the influence of all confounding factors, which may lead to potential biases in the interpretation of the results. Thirdly, limited sample sizes for laboratory tests relevant to anemia (like ferritin and vitamin deficiencies) in the database could impact the precision of our results. Fourthly, our findings might not be fully applicable to younger individuals, as participants under 20 were excluded from the analysis. Lastly, the anemia data, based solely on laboratory diagnoses, might not fully represent patients with a history of anemia, potentially leading to incomplete results.

Conclusion

In our extensive analysis of data from a representative sample of the adult population in the United States, we observed a positive correlation between the presence of phthalate metabolites in urine and the prevalence of anemia, a relationship that appears to be partially mediated by iron metabolism. This research significantly enhances our understanding by establishing links between various phthalate metabolites and reduced serum iron levels. To the best of our knowledge, this is the first comprehensive study to examine the impact of phthalate esters on anemia and serum iron levels across the general American population. The insights from this cross-sectional study offer a novel perspective on the potential health effects of phthalate exposure. Although the cross-sectional nature of the study limits our ability to establish causality, the associations identified underscore the pressing need for further research. These findings necessitate more extensive longitudinal and experimental studies to explore the causal relationships and underlying mechanisms between phthalate exposure, anemia, and iron imbalances. Such future research could significantly impact public health policies and interventions aimed at reducing phthalate exposure and mitigating its associated health risks.

Supplementary Information

Supplementary Tables.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72147-y.

Author contributions

X.D. designed the study; H.M. wrote the manuscript; J.L. and W.D. performed the statistical analysis. All authors read and approved the final manuscript.

Data availability

The datasets utilized in our study are accessible in the NHANES repository, maintained by the CDC and open to the public. These can be found at (https://wwwn.cdc.gov/nchs/nhanes/ContinuousNhanes/Default.aspx?BeginYear=2003).

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study exclusively involves secondary data analyses, utilizing statistical data from the NHANES website without any identifiable personal information. Given this context, no additional ethical approval is needed for conducting the current study.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Huimiao Ma and Wenqi Deng.
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