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. 2024 Dec 15;16(12):7884–7897. doi: 10.62347/IUMS4514

Association of diethylhexyl phthalate exposure with serum thyroid hormone levels: a systematic review and meta-analysis

Ke Xu 1,*, Huan Sun 2,3,*, Jiafeng Li 2, Xinyao He 1, Xiaoqin Zhou 3,4, Xinran Cheng 1
PMCID: PMC11733379  PMID: 39822510

Abstract

Objective: Evidence suggests that diethylhexyl phthalate (DEHP) may disrupt thyroid hormone homeostasis by targeting multiple components of the hypothalamic-pituitary-thyroid (HPT) axis, potentially harming human health. However, the relationship between DEHP exposure and thyroid function remains debated. We performed a meta-analysis to clarify the association between DEHP exposure and thyroid function. Methods: We searched Medline, Embase, the Cochrane Library, and Web of Science for relevant studies that provided quantitative data on the association between DEHP and thyroid hormones. The ROBINS-E tool was used to assess the quality of included studies. Pearson correlation coefficients or regression coefficients (β) with 95% confidence intervals (CIs) were calculated to evaluate the relationship between DEHP exposure and thyroid hormone levels. Results: Twenty-three studies were included. In adults, thyroxine (TT4) levels (pooled coefficient -0.05, 95% CI [-0.08, -0.03]) and free thyroxine (FT4) levels (pooled coefficient -0.04, 95% CI [-0.06, -0.02]) were negatively associated with urinary DEHP concentration. Additionally, DEHP exposure in adults was positively correlated with thyroid-stimulating hormone (TSH) levels (pooled coefficient 0.03, 95% CI [0.02, 0.04]). In pregnant women, urinary DEHP concentration was negatively correlated with FT4 levels (pooled correlation coefficient -0.04, 95% CI [-0.06, -0.02]). However, no significant association was observed between DEHP exposure and thyroid function in children and adolescents. Conclusion: This meta-analysis demonstrates a significant association between DEHP exposure and serum thyroid hormone levels in adults. However, DEHP exposure appears to have no significant effect on thyroid function in children and adolescents.

Keywords: Diethylhexyl phthalate, thyroid hormone, systematic review, meta-analysis

Introduction

Plastic pollution is a global public health challenge. Phthalate esters (PAEs) are widely used in food and beverage packaging [1], household products [2], toys, pharmaceutical products [3] and so on. Based on side chain differences, PAEs can be divided into two types [4]: high molecular weight PAEs (such as di-iso-octyl phthalate (DEHP), diisonoyl phthalate (DINP)) and low molecular weight PAEs (such as diethyl phthalate (DEP) and butyl benzyl ester (BBzP)). DEHP, the most common phthalate [5], exists widely in the environment [6] because it does not bind to polymers via covalent bonds and is easily released from plastics. Humans are exposed to DEHP through the digestive tract, skin and respiratory tract [7-10]. Once in the body, DEHP is rapidly metabolized into monoesters or hydroxylated metabolites (including mono-(2-ethyl-hexyl) phthalate, MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP). These metabolites have a short elimination half-life and are excreted through urine, feces and sweat [11]. Urinary phthalate metabolite levels are commonly used to assess exposure due to their high concentration in urine.

Thyroid hormone (TH) synthesis and secretion are regulated by the hypothalamic-pituitary-thyroid (HPT) axis. TH is a key endocrine hormone that regulates lipid and glucose metabolism, cell growth, and nervous system development. Limited evidence indicates that DEHP can disrupt thyroid hormone homeostasis through multiple targets in the HPT axis, negatively impacting human health [12]. Several observational studies have shown negative correlations between DEHP metabolites and thyroid hormones (triiodothyronine [T3] or thyroxine [T4]) in the general population, pregnant women, and even children [13]. Conversely, other studies found no association between DEHP and thyroid-stimulating hormone (TSH), free thyroxine (FT4), or free triiodothyronine (FT3) [14-17]. However, variations in metabolite types, inconsistent outcome measures, small sample sizes, and unaccounted potential confounders, such as dietary iodine intake, contribute to the controversy regarding the relationship between DEHP exposure and thyroid function.

Therefore, we conducted a systematic review and meta-analysis to clarify the relationship between DEHP exposure and thyroid function.

Methods

This meta-analysis was conducted and reported in accordance with the Preferred Reporting Items For Systematic Reviews And Meta-Analysis (PRISMA) [18]. The study protocol was registered on the PROSPERO website (CRD42022337510).

Search strategy

We performed a literature search in Ovid MEDLINE, Ovid EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception until May 14, 2022, with an updated search conducted on January 29, 2023. Additionally, we manually reviewed the reference lists of relevant studies to identify further eligible studies. When necessary, we contacted authors via email for more information. No language restrictions were applied. The search strategy included a combination of free terms and medical subject headings (MeSH), such as phthalate, diethylhexyl phthalate, Di (2-ethylhexyl) phthalate, Bis (2-ethylhexyl) phthalate, DEHP, and thyroid. The detailed search strategy is provided in the Supplementary Material.

Selection criteria

We included published studies that examined the associations between urinary phthalate metabolites and serum thyroid hormones. The inclusion criteria were as follows: 1) The study population consisted of the general population, including pregnant women and children. 2) The study measured urinary phthalate metabolites (MEHP, MEHHP, MEOHP, and MECPP) to assess DEHP exposure, and serum thyroid hormones (TSH, TT4, FT4, FT3, TT3) to evaluate thyroid function. 3) The study reported correlation or regression coefficients with 95% confidence intervals (CIs) for the association between DEHP exposure and thyroid function. 4) The study design was a prospective cohort or cross-sectional study.

We excluded the following: 1) Studies involving neonates, as they were indirectly exposed to DEHP through their mothers. 2) Reviews, conference abstracts, editorial materials, and animal studies.

Data extraction and quality assessment

Two reviewers (K.X. and H.S.) independently extracted the following data: first author, publication year, study design, location, population, sample size, age, gender, urinary concentrations of DEHP metabolites, thyroid hormones, and statistical analysis methods.

The Risk of Bias (ROB) in Non-Randomized Studies of Environmental Exposures (ROBINS-E) tool was used to assess the risk of bias and the quality of the included studies [19]. This tool evaluates seven domains: bias due to confounding, bias in participant selection, bias in exposure measurement, bias due to deviations from intended exposures, bias due to missing data, bias in outcome measurement, and bias in the selection of reported results. Two reviewers (H.S. and X.Z.) independently assessed the risk of bias, with disagreements resolved through discussion or consensus with a third reviewer (X.C.).

Strategy for data synthesis

Quantitative methods were used for data synthesis. The data were synthesized using meta-analysis to present the primary and secondary outcomes of the studies in a comparative manner. We pooled the β coefficients with 95% confidence intervals (CIs), and correlation coefficients (r) were converted to Fisher’s Z-values for pooling. Statistical heterogeneity was assessed using the Chi-square test and I2, with p-values ≤ 0.10 and I2 ≥ 50% indicating significant heterogeneity. Given the theoretical heterogeneity among the studies, a random-effects model was applied for pooling. Subgroup analyses were conducted based on different populations, such as children, pregnant women, and adults. Sensitivity analysis was performed, and Egger’s test was used to assess publication bias. All statistical analyses were conducted using R software (version 4.2.1).

Results

Characteristics of included studies

Figure 1 outlines the study selection process. The electronic searches identified 1,026 potentially relevant studies, of which 64 eligible full texts were evaluated after screening titles and abstracts. After full-text evaluation, 41 studies were excluded. Ultimately, we included 23 cohort or cross-sectional studies [20-42]. The characteristics of the included studies are summarized in Table 1. These studies were published between 2007 and 2022, with sample sizes ranging from 61 to 6,003 participants. Six studies involved adults, eight involved pregnant women, eight involved children and adolescents, and one involved participants older than 12 years. Five studies employed Spearman correlation analysis, while the remaining studies used linear regression models.

Figure 1.

Figure 1

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PRISMA flow chart for studies selection.

Table 1.

Characteristics of included studies

Study Study design Sample collection time Location Population Sample Age (years) Gender Urinary concentrations of Diethylhexyl Phthalate (DEHP) metabolites Thyroid hormone Statistical analysis
MEHP MEHHP MEOHP MECPP
Albert 2018 [20] Cross-sectional study 2009-2012 Canada Adults 153 25.9 (6.1) All M 3.1 (1.4-6.2) 13 (5-22) 8.4 (3.4-15) 13 (6-25) TSH/FT3/FT4 Linear regression models
Choi 2020 [21] Cross-sectional study 2015-2017 Korea Adults 1254 47 (15) M: 630 - - - - TT4/TT3/FT4/FT3/TSH Linear regression analysis
F: 624
Huang HBP 2017 [25] Cross-sectional study 2013 Taiwan Adults (≥ 18 years) 358 Adults Adults Adults Adults Adults Adults TSH/FT4/TT4/TT3 Multivariable linear regression models
Minors (< 18 years) 53.4 (17.3) M: 129, F: 150 6.7 (2.5-12.1) 16.4 (9.8-30.1) 10.2 (5.6-16.9) 20.2 (10.9-31.9)
Minors Minors Minors Minors Minors Minors
12.6 (3.2) M: 47, F: 32 7.4 (2.4-12.6) 25.5 (13.6-39.4) 19.6 (9.3-32.3) 34.7 (18.4-63.6)
Huang HB 2021 [26] Cross-sectional study 2013 Taiwan Adults 217 52.7 (17.5) M: 104 7.0 (3.1-12.1) 15.9 (9.8-30.1) 9.93 (5.5-16.4) 19.9 (10.9-32.4) TSH/FT4/TT4/TT3 Multiple regression models
F: 113
Huang PCW 2020 [27] Cross-sectional study 2013 Taiwan Adults 266 53.6 (17.0) M: 124 6.8 16.46 10.28 20.30 TT4/TT3/FT4/TSH Multivariate linear regressions
F: 142
Park 2017 [31] Cross-sectional study 2012-2014 Korean Adults 6003 - M: 2638 - 19.3 (10.7-32.1) 13.2 (7.7-22.4) 21.3 (12.8-34.8) TSH/TT4/TT3 Multiple linear regression models
F: 3365
Derakhshan 2021 [22] Cohort study 2007-2010 The Netherlands Pregnant women 1996 30.9 (4.9) All F 3.7 (0.7-26.8) 16.9 (2.9-110) 11.2 (1.9-72.3) 15.9 (3.3-95.5) TSH/FT4/TT4/FT3/TT3 Multivariable linear regression
Huang HB 2018 [24] Cohort study 2013-2014 Taiwan Pregnant women 98 35.0 (3.5) All F - - - - TSH/FT4/TT4/TT3 Linear mixed models
Huang PC 2021 [28] Cohort study 2005-2006 Taiwan Pregnant women 61 34.0 (3.5) All F - - - - TT4/TT3/FT4/TSH Spearman correlation
Huang PC 2007 [29] Cohort study 2005-2006 Taiwan Pregnant women 76 33.6 (3.3) All F 20.6 (13.1-38.6) - - - TT4/TT3/FT4/TSH Spearman correlation
Huang PC 2016 [30] Cohort study 2013-2014 Taiwan Pregnant women 97 35.1 (3.5) All F 5.1 5.7 5.6 9.5 TT4/TT3/FT4/TSH Spearman correlation
Kuo 2015 [33] Cohort study 2009-2010 Taiwan Pregnant women 148 29.4 (4.9) All F 7.71 14.52 13.4 - TT4/TT3/FT4/TSH Spearman correlation
Yao 2016 [40] Cohort study - China Pregnant women 2521 26.3 (3.5) All F - - - - TT4/TT3/FT4/TSH Spearman correlation
Huang PC 2020 [27] Cohort study 2012-2016 Taiwan Children 166 6.1 (2.4) M: 106 4.99 (1.8-9.9) 21.7 (11.4-38.8) 16 (7.5-29.4) - TT4/TT3/FT4/TSH Generalized estimating equation
F: 66
Kim 2018 [32] Cross-sectional study - Korea Children and adolescents 302 M: 9 (0.8) M: 138 7.8 (3.3-10.4) - - - TSH/TT3/TT4 Multiple linear regression
F: 8.7 (3.7) F: 164
Meeker 2011 [34] Cross-sectional study 2007-2008 United States Adults and Adolescents 1760 - Adults 2.6 (< LOD-5.2) 20.6 (9.8-37.0) 11.2 (5.43-20.5) 30.6 (15.4-50.8) TT4/TT3/FT4/FT3/TSH Multivariable linear regression
M: 737, F 668
Adolescents
M: 185, F: 170
Morgenstern 2017 [35] Cohort study 1998-2006 United States Children 229 3 M: 109 - - - - FT4/TSH Multiple linear regression models
F: 119
Tsai 2016 [37] Cross-sectional study 2012-2013 Taiwan Children and Adolescents 250 7.6 (1.2) M: 146 4.8 (1.9-9.8) 20.6 (10.3-35.9) 14.7 (7.3-26.9) - FT4/TT3/TT4 Multivariate linear regression models
F: 104 TSH
Weng 2017 [38] Cross-sectional study 2013-2014 Taiwan Children 189 9-10 M: 92 4.4 (1.3-9.4) 17.2 (8.0-33.4) 11.1 (5.4-21.9) - FT4/TT4/FT3/TT3/TSH Generalized linear model
F: 97
Wu 2017 [39] Cross-sectional study 2013 China Children aged 5-7 years 216 - M: 107 Urban Urban Urban - FT4/FT3/TSH Multiple linear regression models
F: 109 6 (3.6-13.2) 15.4 (8.6-27.5) 8.3 (5.2-13.7)
Rural Rural Rural
4 (3.2-6.3) 24.4 (10-93.9) 5.6 (4.1-12.3)
Zhao 2022 [41] Cross-sectional study 2017 China Students aged 16-19 years 347 - M: 116 - - - - TT4/TT3/FT4/FT3/TSH Multivariate linear regression
F: 231
Kim 2017 [32] Cohort study 2007-2008 Korea Population (≥ 12 years) 1829 - M: 960 2.1 (0.8-5.3) 20 (9.1-46.6) 11.2 (5.2-25.6) 29.8 (14.7-65.9) TSH/FT4/TT4/FT3/TT3 Multivariate linear regression analyses
F: 869
Yang 2022 [42] Cohort study 2019-2020 China Pregnant women 325 30.8 (3.9) All F 20.70 (14-33.8) 7.67 (5.13-12.6) 13.30 (8.37-20) 24.20 (16-38.6) TSH/FT4
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M: male, F: female.

Quality assessment

The ROBINS-E tool was used to assess risk of bias (ROB) because the included studies involved environmental exposures. Seven domains were evaluated for each study. Two studies did not clearly define certain parameters and were considered to have moderate ROB in those domains. All studies used appropriate methods to assess exposure, resulting in a low ROB for exposure measurement. Eleven studies were cohort studies, where bias due to departures from intended exposures was less likely. Twelve studies were cross-sectional, and sufficient information was not provided to determine ROB in some domains. All studies had low ROB for missing data, outcome measurement, and reported result selection. In total, four studies were judged to have moderate ROB, and the remaining studies had low ROB (Supplementary Table 1).

Associations between DEHP exposure and thyroid function in adults

Eight studies reported associations between DEHP exposure and thyroid function in adults. Meta-analysis showed no correlation between adult DEHP exposure and TT3 levels (pooled coefficient 0.00, 95% CI [-0.03, 0.04], I2 = 87%; Table 2). Subgroup analysis of DEHP metabolites showed no correlation with TT3 levels. However, significant heterogeneity was found among the studies on DEHP and TT3, prompting sensitivity analysis. After excluding one study, a negative correlation between DEHP exposure and TT3 was observed (pooled coefficient -0.00, 95% CI [-0.04, -0.01], I2 = 19%). Subgroup analysis revealed that both MEHP and MEOHP were negatively correlated with TT3, with correlation coefficients of -0.02 (95% CI [-0.04, -0.00], I2 = 70%) and -0.06 (95% CI [-0.12, -0.01], I2 = 0%), respectively (Table 2).

Table 2.

Results of meta-analysis and heterogeneity test of the correlation between Diethylhexyl Phthalate (DEHP) and thyroid hormone in adults

Factors No. Sample size Heterogeneity Effect Model β 95% CI
P (Q) I2 (%)
TT3
    MEHP 4 2108 3.07 2.3 RE -0.01 (-0.07, 0.04)
    MEHHP 7 11194 22.31 73.1 RE -0.00 (-0.05, 0.05)
    MEOHP 6 9365 51.77 90.3 RE -0.03 (-0.13, 0.06)
    MECPP 6 9365 81.93 93.9 RE 0.05 (-0.05, 0.14)
    Pooled correlation - - - 87 RE 0.00 (-0.03, 0.04)
TT4
    MEHP 4 2108 6.37 53 RE -0.01 (-0.08, 0.06)
    MEHHP 7 11194 14.25 58 RE -0.08 (-0.12, -0.05)
    MEOHP 6 9365 7.47 33 RE -0.05 (-0.09, -0.02)
    MECPP 6 9365 25.51 80 RE -0.02 (-0.09, 0.06)
    Pooled correlation - - - 62 RE -0.05 (-0.08, -0.03)
FT4
    MEHP 5 2261 9.28 57 RE -0.07 (-0.15, -0.00)
    MEHHP 7 5344 4.33 0 RE -0.03 (-0.06, -0.01)
    MEOHP 6 3515 21.62 77 RE -0.09 (-0.18, 0.01)
    MECPP 6 3515 5.82 14 RE -0.02 (-0.05, 0.01)
    Pooled correlation - - - 48 RE -0.04 (-0.06, -0.02)
TSH
    MEHP 4 2108 1.93 0 RE 0.03 (-0.01, 0.07)
    MEHHP 7 11194 8.56 30 RE 0.04 (0.01, 0.06)
    MEOHP 6 9365 4.24 0 RE 0.03 (0.00, 0.05)
    MECPP 6 9365 2.14 0 RE 0.03 (0.01, 0.05)
    Pooled correlation - - - 0 RE 0.03 (0.02, 0.04)
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RE: Random effects model, MEHP: mono-(2-ethyl-hexyl) phthalate, MEHHP: mono-(2-ethyl-5-hydroxyhexyl) phthalate, MEOHP: mono-(2-ethyl-5-oxohexyl) phthalate, MECPP: mono-(2-ethyl-5-carboxypentyl) phthalate.

Meta-analysis indicated a negative correlation between adult DEHP exposure and TT4 levels (pooled coefficient -0.05, 95% CI [-0.08, -0.03], I2 = 62%; Table 2). Subgroup analysis showed that MEHHP and MEOHP were negatively correlated with TT4 levels, with correlation coefficients of -0.08 (95% CI [-0.12, -0.05], I2 = 58%) and -0.05 (95% CI [-0.09, -0.02], I2 = 33%), respectively (Table 2).

A negative correlation was also found between adult DEHP exposure and FT4 levels (pooled coefficient -0.04, 95% CI [-0.06, -0.02], I2 = 48%; Table 2). Subgroup analysis of DEHP metabolites showed that MEHHP and MEOHP were negatively correlated with FT4. The correlation coefficients for MEHHP and MEOHP were -0.07 (95% CI [-0.15, -0.00], I2 = 57%) and -0.03 (95% CI [-0.06, -0.01], I2 = 0%), respectively. Significant heterogeneity was noted in the DEHP and FT4 studies, prompting sensitivity analysis. After excluding one study, a stronger negative correlation between DEHP exposure and FT4 was observed (pooled coefficient -0.07, 95% CI [-0.10, -0.04], I2 = 41%). Subgroup analysis showed that MEHP, MEHHP, and MEOHP were negatively correlated with FT4, with pooled correlation coefficients of -0.14 (95% CI [-0.21, -0.07], I2 = 0%), -0.04 (95% CI [-0.07, -0.01], I2 = 0%), and -0.14 (95% CI [-0.24, -0.05], I2 = 76%), respectively (Supplementary Figure 1).

A positive correlation between adult DEHP exposure and TSH levels was found (pooled coefficient 0.03, 95% CI [0.02, 0.04], I2 = 0%; Table 2). Subgroup analysis showed that MEHHP, MEOHP, and MECPP were positively correlated with TSH, with correlation coefficients of 0.04 (95% CI [0.01, 0.06], I2 = 30%), 0.03 (95% CI [0.00, 0.05], I2 = 0%), and 0.03 (95% CI [0.01, 0.05], I2 = 0%), respectively (Table 2).

No publication bias was detected based on the funnel plot and Egger’s test (Supplementary Figure 4).

Associations between DEHP exposure and thyroid function in pregnant women

A total of eight studies reported the association between DEHP exposure and thyroid function in pregnant women. The meta-analysis results showed no correlation between maternal DEHP exposure and TT3 (pooled coefficient -0.02, 95% CI [-0.04, 0.00], I2 = 35%). However, subgroup analysis of different DEHP metabolites revealed that MECPP was negatively correlated with TT3 in pregnant women (pooled coefficient -0.09, 95% CI [-0.15, -0.02], I2 = 35%) (Table 3).

Table 3.

Results of meta-analysis and heterogeneity test of the correlation between Diethylhexyl Phthalate (DEHP) and thyroid hormone in pregnant women

Factors No. Sample size Heterogeneity Effect Model COR 95% CI
P (Q) I2 (%)
TT3
    MEHP 7 5115 4.63 0 RE -0.01 (-0.04, 0.02)
    MEHHP 5 4978 8.05 50.3 RE -0.02 (-0.08, 0.03)
    MEOHP 5 4978 3.25 0 RE -0.00 (-0.03, 0.03)
    MECPP 3 2309 2.12 5.5 RE -0.09 (-0.15, -0.02)
    Pooled correlation - - - 35 RE -0.02 (-0.04, 0.00)
TT4
    MEHP 7 5115 3.14 0 RE -0.02 (-0.05, 0.01)
    MEHHP 5 4978 1.71 0 RE -0.04 (-0.07, -0.01)
    MEOHP 5 4978 3.18 0 RE -0.01 (-0.03, 0.02)
    MECPP 3 2309 2.16 7.4 RE -0.03 (-0.01, 0.04)
    Pooled correlation - - - 0 RE -0.03 (-0.04, -0.01)
FT4
    MEHP 8 5440 15.44 54.7 RE -0.01 (-0.07, 0.04)
    MEHHP 6 5303 12.95 61.4 RE -0.03 (-0.10, 0.03)
    MEOHP 6 5303 13.64 63.3 RE -0.03 (-0.10, 0.04)
    MECPP 4 2634 0 0 RE -0.05 (-0.09, -0.01)
    Pooled correlation - - - 55 RE -0.04 (-0.06, -0.02)
TSH
    MEHP 8 5440 13.34 45.7 RE 0.02 (-0.03, 0.07)
    MEHHP 6 5303 17.6 71.6 RE 0.02 (-0.05, 0.09)
    MEOHP 6 5303 12.22 59.1 RE -0.01 (-0.08, 0.06)
    MECPP 4 2634 5.86 48.8 RE 0.02 (-0.06, 0.10)
    Pooled correlation - - - 64 RE 0.01 (-0.02, 0.05)
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RE: Random effects model, MEHP: mono-(2-ethyl-hexyl) phthalate, MEHHP: mono-(2-ethyl-5-hydroxyhexyl) phthalate, MEOHP: mono-(2-ethyl-5-oxohexyl) phthalate, MECPP: mono-(2-ethyl-5-carboxypentyl) phthalate.

Maternal DEHP exposure was negatively correlated with TT4 (pooled coefficient -0.03, 95% CI [-0.04, -0.01], I2 = 0%). Subgroup analysis indicated a negative correlation between maternal MEHHP exposure and TT4 levels (pooled coefficient -0.04, 95% CI [-0.07, -0.01], I2 = 0%) (Table 3).

A negative correlation between DEHP exposure and FT4 levels was also found (pooled coefficient -0.04, 95% CI [-0.06, -0.02], I2 = 55%). Subgroup analysis showed that maternal MECPP exposure was negatively correlated with FT4 levels (pooled coefficient -0.05, 95% CI [-0.09, -0.01], I2 = 0%). Due to significant heterogeneity between studies on DEHP and FT4 in pregnant women, a sensitivity analysis was conducted. After excluding one study, a negative correlation was observed between DEHP exposure and FT4 in pregnant women (pooled coefficient -0.06, 95% CI [-0.07, -0.04], I2 = 0%). Subgroup analysis revealed negative correlations between FT4 levels and exposures to MEHHP (pooled coefficient -0.06, 95% CI [-0.09, -0.04], I2 = 0%), MEOHP (pooled coefficient -0.05, 95% CI [-0.08, -0.02], I2 = 0%), and MECPP (pooled coefficient -0.05, 95% CI [-0.09, -0.01], I2 = 0%) in pregnant women (Supplementary Figure 2).

No significant association was found between maternal DEHP exposure and TSH levels in this meta-analysis (pooled coefficient 0.00, 95% CI [-0.04, 0.04], I2 = 64%) (Table 3). Even after sensitivity analysis, no correlation was observed between maternal DEHP exposure and TSH (Supplementary Figure 3). The funnel plot and Egger’s test revealed no significant publication bias (Supplementary Figure 5).

Associations between DEHP exposure and thyroid function in children and adolescents

Eight studies examined the association between DEHP exposure and thyroid function in children and adolescents. The meta-analysis results showed that DEHP exposure was positively correlated with TT3 in children and adolescents (pooled coefficient 0.05, 95% CI [0.02, 0.09], I2 = 76%; Table 4). Subgroup analysis of different DEHP metabolites revealed a negative correlation between MEOHP and TT3 in children and adolescents (pooled coefficient 0.09, 95% CI [0.02, 0.15], I2 = 39%; Table 4). No significant correlation was found between DEHP exposure and TT4, FT4, or TSH in children and adolescents.

Table 4.

Results of meta-analysis and heterogeneity test of the correlation between Diethylhexyl Phthalate (DEHP) and thyroid hormone in children and adolescents

Factors No. Sample size Heterogeneity Effect Model β 95% CI
P (Q) I2 (%)
TT3
    MEHP 7 1572 8.40 29 RE 0.05 (-0.01, 0.11)
    MEHHP 7 1572 4.55 0 RE 0.04 (-0.01, 0.09)
    MEOHP 7 1572 9.84 38 RE 0.09 (0.02, 0.15)
    MECPP 3 751 8.46 76 RE -0.01 (-0.19, 0.17)
    Pooled correlation - - - 31 RE 0.05 (0.02, 0.09)
TT4
    MEHP 7 1572 1.87 0 RE 0.02 (-0.03, 0.07)
    MEHHP 7 1572 9.52 37 RE 0.01 (-0.05, 0.08)
    MEOHP 7 1572 9.67 38 RE 0.01 (-0.05, 0.08)
    MECPP 3 751 5.70 65 RE -0.04 (-0.17, 0.08)
    Pooled correlation - - - 19 RE 0.01 (-0.03, 0.04)
FT4
    MEHP 7 1550 4.89 0 RE -0.01 (-0.06, 0.04)
    MEHHP 8 1800 16.20 56 RE 0.03 (-0.04, 0.10)
    MEOHP 8 1800 9.56 27 RE -0.00 (-0.06, 0.05)
    MECPP 4 979 0.87 0 RE -0.01 (-0.07, 0.06)
    Pooled correlation - - - 20 RE 0.00 (-0.02, 003)
TSH
    MEHP 8 1800 8.30 0 RE 0.01 (-0.04, 0.06)
    MEHHP 8 1800 4914.96 100 RE 0.56 (-0.50, 0.95)
    MEOHP 8 1800 7.20 3 RE 0.05 (-0.00, 0.10)
    MECPP 4 979 5.77 48 RE 0.03 (-0.06, 0.12)
    Pooled correlation - - - 99 RE 0.20 (-0.13, 0.49)
Open in a new tab

RE: Random effects model, MEHP: mono-(2-ethyl-hexyl) phthalate, MEHHP: mono-(2-ethyl-5-hydroxyhexyl) phthalate, MEOHP: mono-(2-ethyl-5-oxohexyl) phthalate, MECPP: mono-(2-ethyl-5-carboxypentyl) phthalate.

The funnel plot and Egger’s test revealed no significant publication bias between DEHP exposure and TT3, TT4, or FT4. However, in the analysis of DEHP exposure and TSH, the funnel plot was asymmetrical, and Egger’s test showed a p-value of 0.04, indicating potential publication bias (Supplementary Figure 6).

Sensitivity analysis

To evaluate the stability of the results, sensitivity analysis was performed by omitting one study at a time and checking the consistency of the overall effect estimates. The results indicated that excluding individual studies did not significantly alter the statistical outcomes, demonstrating that the meta-analysis results were stable (Supplementary Figure 7).

Discussion

Thyroid-related medical conditions, such as thyroid dysfunction, thyroid nodules, and autoimmune thyroiditis, have increased globally in recent years, posing a significant threat to human health [17]. A key factor contributing to this rise is widespread exposure to environmental endocrine disruptors. In 2011, a major food safety incident involving DEHP-contaminated food occurred in Taiwan, raising concerns about its safety and potential health impacts. Current research indicates that DEHP and its metabolites can disrupt the regulation of the hypothalamic-pituitary-thyroid (HPT) axis and affect the thyroid endocrine system [43].

DEHP influences thyroid homeostasis through multiple mechanisms. First, it exhibits T3 antagonistic activity and inhibits the expression of the endogenous thyroid hormone receptor-beta (TRβ) gene [44]. DEHP exposure has also been found to suppress thyroid hormone receptor (THR)-mediated transcription, suggesting that it may interfere with THR-regulated gene expression [45]. Animal studies have further shown that DEHP exposure can antagonize thyroid function to varying degrees [46]. For example, changes in the TSH/TSHR signaling pathway [47], proteins related to tyrosine hydroxylase (TH) synthesis, and deiodinase activity [48] have been observed, which in turn disrupt the HPT axis and alter TH levels. DEHP exposure can also lead to oxidative stress, increasing reactive oxygen species (ROS), activating the Ras/Akt/TRHr pathway, and ultimately decreasing TH levels [49]. Additionally, histological analyses have revealed that DEHP exposure can cause thyroid follicular hypertrophy and proliferation, leading to thyroid damage and inflammatory infiltration [50], which can impair iodine uptake by thyroid follicular cells [51].

Although numerous epidemiological studies have investigated the effects of DEHP exposure on thyroid function, meta-analyses have been hindered by significant heterogeneity between studies. These differences may be due to various confounding factors. A Chinese study found that MEHP and MECPP levels were higher in women than in men, and higher in minors than in adults [52]. Moreover, women are generally more susceptible to thyroid disease, and greater DEHP exposure in this population may increase the risk of thyroid dysfunction. Lifestyle factors, such as the use of personal care products and food packaging, also influence DEHP exposure. DEHP is widely present in packaging materials and can leach into food, with frequent consumption of plastic-wrapped or microwave-heated fast food potentially increasing exposure [53]. Occupational exposure to DEHP is also common in industries such as polyvinyl chloride (PVC) film manufacturing, rubber boot production, and PVC flooring and window installation, where exposure levels are significantly higher [54]. Given the wide range of DEHP exposure sources, including sex, diet, and occupation, controlling for all confounding factors in studies is challenging.

Previous research has shown inconsistent associations between DEHP exposure and thyroid function in pregnant women. A study by Huang et al. in Taiwan found that urinary MEOHP levels were negatively correlated with TSH levels in pregnant women, and urinary MECPP levels were negatively correlated with T3 levels [24]. Another repeated measures analysis in Puerto Rico observed a significant negative association between urinary DEHP metabolites and FT4 levels, but no significant association with TSH levels [43]. Our subgroup analysis revealed a significant negative correlation between DEHP and FT4, but no correlation between DEHP and TSH. The duration of exposure in the studies ranged from 18 to 39 weeks of gestation, and previous research has shown that different windows of DEHP exposure during pregnancy can affect thyroid hormone levels differently. This suggests that the timing of DEHP exposure may be a critical factor in determining thyroid dysfunction risk in pregnant women [24]. Other factors, such as iodine intake, nutritional status, and varying detection methods, may also influence thyroid hormone levels. Inadequate adjustment for these confounders could lead to overestimation or underestimation of the true association between DEHP exposure and thyroid function. To address these issues, future studies should collect and test biomarkers at multiple time points across different gestational weeks for longitudinal analyses. This approach would help generate more consistent and robust results, improving our understanding of the potential health risks associated with long-term DEHP exposure.

There is a notably increased demand for thyroid hormone during pregnancy due to changes in hormone metabolism, binding proteins, placental thyroid hormone transfer, and fetal depletion [55]. Both hyperthyroidism and hypothyroidism in pregnant women are associated with adverse birth outcomes, such as preterm birth and low birth weight [56]. In particularly vulnerable populations, like fetuses, even subtle changes in thyroid hormone levels - within the normal range - can lead to serious health effects, including neurocognitive problems [57]. Given this, maternal DEHP exposure may critically impact fetal thyroid hormone homeostasis, especially during the first trimester when the fetus is entirely dependent on the mother’s thyroid hormone. After the first trimester, the fetus begins producing sufficient thyroid hormone on its own, but DEHP exposure should be minimized, if not avoided, during this early period.

In a study by Wu et al., involving 216 primary caregivers of children aged 5-7 years affected by the 2011 Taiwan food scandal, higher DEHP exposure was significantly associated with decreased serum TSH levels in children [50]. Similarly, a Danish study of 845 children aged 4-9 years reported an inverse relationship between DEHP metabolites and FT3/TT3 levels [58]. However, a contrasting U.S. study involving adolescents aged 12-19 found a positive association between DEHP metabolites and T3 and TSH levels [34]. Our meta-analysis identified a positive correlation between MEOHP and TT3 in children, while other DEHP metabolites were not significantly linked to thyroid dysfunction. These varying results could stem from differences in race, age, exposure levels, and exposure duration across studies.

Moreover, increased public awareness of DEHP’s harmful effects in recent years has likely prompted parents to limit their children’s exposure to DEHP-contaminated food and household products, which could explain the lack of significant associations between DEHP exposure and thyroid dysfunction in some studies. This points to the importance of continued education and proactive measures to reduce DEHP exposure, particularly among vulnerable groups such as children and pregnant women.

Our research has several strengths:

Small changes in TH levels due to exposure to environmental endocrine disruptors may not be easily detectable in small populations [59]. Therefore, including a large number of epidemiological studies with a substantial sample size in this meta-analysis enhances the robustness of our findings. We conducted subgroup analyses to explore sources of heterogeneity, identify windows of susceptibility, and examine vulnerable populations. The findings from these studies can guide the assessment of DEHP’s impact on thyroid function across different populations and inform the development of targeted interventions to improve public health.

However, several limitations of this review should be acknowledged. DEHP is non-persistent in the body and is rapidly metabolized, meaning its concentrations in urine samples may be significantly lower than in dust samples, which introduces uncertainty in exposure assessment [60]. Relying on a single type of sample to assess long-term exposure may lead to random errors. Additionally, urine composition can vary depending on the time of sampling, such as between first-morning fasting urine and 24-hour total urine [61]. To better reflect chronic exposure, future studies should collect multiple samples to improve exposure assessment. The use of urine samples to assess DEHP exposure may vary by region, potentially influencing the conclusions.

Different phthalates can coexist, and the “cocktail effect” of phthalate mixtures cannot be entirely ruled out. This means the effect of DEHP on thyroid function may be confounded by other phthalates. Most studies to date have focused on the relationship between a single phthalate and thyroid function, with few evaluating the effects of multiple phthalates.

Non-English-language studies were excluded, and the heterogeneity of the included studies may have affected the meta-analysis results. Finally, the majority of the studies originated from countries in Asia and North America, such as China, Korea, and the United States. There is a lack of relevant studies from other regions, particularly Europe. In summary, more high-quality studies providing detailed data are necessary. The results of our meta-analysis are crucial for environmental and health research, and future studies should focus on identifying potential mechanisms.

Acknowledgements

This study was supported by the Sichuan Science and Technology Project (2019JDPT0034).

Disclosure of conflict of interest

None.

Supporting Information

ajtr0016-7884-f2.pdf (2.4MB, pdf)

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ajtr0016-7884-f2.pdf (2.4MB, pdf)

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