Combining Urinary Biomarker Data From Studies With Different Measures of Urinary Dilution.

Background: Guidance is lacking for how to combine urinary biomarker data across studies that use different measures of urinary dilution, that is, creatinine or specific gravity.

Methods: Among 741 pregnant participants from four sites of The Infant Development and Environment Study (TIDES) cohort, we assessed the relation of maternal urinary di-2-ethylhexyl phthalate (DEHP) concentrations with preterm birth. We compared scenarios in which all sites measured either urinary creatinine or specific gravity, or where measure of dilution differed by site. In addition to a scenario with no dilution adjustment, we applied and compared three dilution-adjustment approaches: a standard regression-based approach for creatinine, a standard approach for specific gravity (Boeniger method), and a more recently developed approach that has been applied to both (covariate-adjusted standardization method). For each scenario and dilution-adjustment method, we estimated the association between a doubling in the molar sum of DEHP (∑DEHP) and odds of preterm birth using logistic regression.

Results: All dilution-adjustment approaches yielded comparable associations (odds ratio [OR]) that were larger in magnitude than when we did not perform dilution adjustment. A doubling of ∑DEHP was associated with 9% greater odds of preterm birth (OR = 1.09, 95% confidence interval [CI] = 0.91, 1.30) when applying no dilution-adjustment method, whereas dilution-adjusted point estimates were higher, and similar across all scenarios and methods: 1.13-1.20 (regression-based), 1.15-1.18 (Boeniger), and 1.14-1.21 (covariate-adjusted standardization).

Conclusions: In our applied example, we demonstrate that it is possible and straightforward to combine urinary biomarker data across studies when measures of dilution differ.