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

Jordan R. Kuiper, Katie M. O'Brien, Barrett M. Welch, Emily S. Barrett, Ruby H.N. Nguyen, Sheela Sathyanarayana, Ginger L. Milne, Shanna H. Swan, Kelly K. Ferguson, Jessie P. Buckley

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)533-540
Number of pages8
JournalEpidemiology
Volume33
Issue number4
DOIs
StatePublished - Jul 1 2022

Bibliographical note

Funding Information:
J.R.K. and J.P.B. were supported by NIH OD U24 OD023382 and NIEHS R01 ES030078. B.M.W., K.M.O., and K.K.F. were supported by the Intramural Research Program of the National Institute of Environmental Health Sciences, National Institutes of Health. E.S.B. was supported by NIEHS P30 ES005022. R.H.N.N., G.L.M., and S.S. were supported by NIEHS R01ES016863 and R01ES025169.

Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.

Keywords

  • Biomarkers
  • Creatinine
  • Dilution
  • Specific gravity
  • Standardization
  • Urine

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Intramural
  • Research Support, N.I.H., Extramural

Fingerprint

Dive into the research topics of 'Combining Urinary Biomarker Data From Studies With Different Measures of Urinary Dilution'. Together they form a unique fingerprint.

Cite this