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Phthalate mixtures and insulin resistance: an item response theory approach to quantify exposure burden to phthalate mixtures

Journal of Exposure Science & Environmental Epidemiology (2023)Cite this article

Abstract

Background

Molar sums are often used to quantify total phthalate exposure, but they do not capture patterns of exposure to multiple phthalates.

Objective

To introduce an exposure burden score method for quantifying exposure to phthalate metabolites and examine the association between phthalate burden scores and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR).

Methods

We applied item response theory (IRT) to data from 3474 adults aged 20–60 years in the 2013–2018 National Health and Examination Survey (NHANES) to quantify latent phthalate exposure burden from 12 phthalate metabolites. We compared model fits of three IRT models that used different a priori groupings (general phthalate burden; low molecular weight (LMW) and high molecular weight (HMW) burdens; and LMW, HMW and DEHP burden), and used the best fitting model to estimate phthalate exposure burden scores. Regression models assessed the covariate-adjusted association between phthalate burden scores and HOMA-IR. We compared findings to those using molar sums. In secondary analyses, we examined how the IRT model could be used for data harmonization when a subset of participants are missing some phthalate metabolites, and accounted for measurement error of the phthalate burden scores in estimating associations with HOMA-IR through a resampling approach using plausible value imputation.

Results

A three correlated factors model (LMW, HMW and DEHP burdens) provided the best fit. One interquartile range (IQR) increase in DEHP burden score was associated with 0.094 (95% CI: 0.022, 0.164, p = 0.010) increase in log HOMA-IR, co-adjusted for LMW and HMW burden scores. Findings were consistent when using log molar sums. Associations of phthalate burden and insulin resistance were also consistent when participants were simulated to be missing some phthalate metabolites, and when we accounted for measurement error in estimating burden scores.

Conclusion

Both phthalate molar sums and burden scores are sensitive to associations with insulin resistance. Phthalate burden scores may be useful for data harmonization.

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Fig. 1: Three hypothesized IRT measurement models for phthalate burden.
Fig. 2: Scatter plots of estimated phthalate burden scores from the correlated factors model.
Fig. 3: Adjusted difference (95% CI) in log HOMA-IR per 1 interquartile range (IQR) increase in 3 phthalate burden scores (from correlated factors model) and in log molar sums of phthalates in co-adjusted regression models (N = 1243).
Fig. 4: Adjusted difference and p-values in log HOMA-IR per 1 interquartile range (IQR) increase in 3 phthalate burden scores in the co-adjusted regression model when 50% of the sample had missing MBP, MiBP and MEHP phthalate measures in 100 resamples.
Fig. 5: Sensitivity analysis for the association of phthalate burden scores and log HOMA-IR in co-adjusted regression models.

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Data availability

The NHANES data is publicly available for download, at https://www.cdc.gov/nchs/nhanes/index.htm.

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Funding

YC and SHL were supported by National Institute for Environmental Health Sciences (NIEHS) R03ES033374, R01ES033252 and National Institute of Child Health and Human Development (NICHD) K25HD104918. JPB was supported by NIEHS R01ES030078, R03ES033374 and R01ES033252.

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Authors and Affiliations

  1. Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Yitong Chen & Shelley H. Liu

  2. Department of Psychology, Fordham University, Bronx, NY, USA

    Leah Feuerstahler

  3. Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, Brazil

    Euridice Martinez-Steele

  4. Department of Environmental Health and Engineering, John Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Jessie P. Buckley

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  1. Yitong Chen
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Contributions

YC, SHL and JPB conceptualized and designed the analysis. YC conducted data analysis and led manuscript preparation, drafting and revisions. SHL assisted with drafting the manuscript. SHL, LF, JPB, and EMS advised on analytical issues and critical review of the manuscript. All authors reviewed, edited, and approved the final manuscript.

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Correspondence to Shelley H. Liu.

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Chen, Y., Feuerstahler, L., Martinez-Steele, E. et al. Phthalate mixtures and insulin resistance: an item response theory approach to quantify exposure burden to phthalate mixtures. J Expo Sci Environ Epidemiol (2023). https://doi.org/10.1038/s41370-023-00535-z

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  • DOI: https://doi.org/10.1038/s41370-023-00535-z

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