Department of Environmental Health and Engineering, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Environ Int. 2021 Nov;156:106656. doi: 10.1016/j.envint.2021.106656. Epub 2021 May 29.
Urinary biomarkers are often corrected for sample dilution using creatinine, which is influenced by sociodemographic factors and certain health conditions. It is unknown whether these factors similarly influence specific gravity.
To identify predictors of specific gravity and creatinine and compare methods for correcting estimated chemical concentrations for sample dilution using these measures.
We assessed predictors of urinary specific gravity and creatinine among NHANES 2007-2008 participants (n = 7257). We corrected concentrations of mono-n-butyl phthalate (MnBP) for dilution using two methods, each applied to both specific gravity and creatinine: correction using a sample mean of the dilution indicator (i.e., specific gravity or creatinine) and covariate-adjusted standardization. We compared distributions and assessed the agreement of uncorrected or corrected concentrations visually using Bland-Altman plots and statistically by Kendall's τ. We stratified all analyses by age category (i.e., 6-19 or 20+ years of age).
Gender, race/ethnicity, body mass index, and height were associated with urinary specific gravity and creatinine. Distributions of corrected MnBP concentrations were comparable for both methods and dilution indicators, but agreement between methods was greater for specific gravity. Additionally, specific gravity- and creatinine-corrected MnBP concentrations had slightly greater agreement with each other when corrected using a covariate-adjusted standardization method.
Specific gravity, like creatinine, is associated with sociodemographic and body composition variables. Accounting for these factors as part of the dilution correction method may be important to minimize bias.
尿液生物标志物通常使用肌酐进行样本稀释校正，而肌酐受社会人口统计学因素和某些健康状况的影响。目前尚不清楚这些因素是否同样影响比重。
确定比重和肌酐的预测因素，并比较使用这些指标校正估计化学浓度样本稀释的方法。
我们评估了 NHANES 2007-2008 参与者（n=7257）尿液比重和肌酐的预测因素。我们使用两种方法校正单丁基邻苯二甲酸酯（MnBP）的浓度，每种方法均应用于比重和肌酐：使用稀释指标（即比重或肌酐）的样本均值进行校正和协变量调整的标准化。我们比较了分布，并通过 Bland-Altman 图和 Kendall's τ 进行视觉和统计评估未校正或校正浓度的一致性。我们根据年龄类别（6-19 岁或 20 岁以上）对所有分析进行分层。
性别、种族/民族、体重指数和身高与尿液比重和肌酐有关。两种方法和稀释指标的校正 MnBP 浓度分布相似，但比重法的一致性更好。此外，使用协变量调整的标准化方法校正时，比重和肌酐校正的 MnBP 浓度彼此之间的一致性稍高。
与肌酐一样，比重与社会人口统计学和身体成分变量有关。作为稀释校正方法的一部分考虑这些因素可能很重要，可以最大程度地减少偏倚。
