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

Abstract

Molar sums are often used to quantify total phthalate exposure, but they do not capture patterns of exposure to multiple phthalates. 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). 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. A three correlated factors model (LMW, HMW and DEHPburdens) 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 measurementerror in estimating burden scores. Both phthalate molar sums and burden scores are sensitive to associations with insulin resistance. Phthalate burden scores may be useful for data harmonization.