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Indeed, several commercial packages exist that perform NMR prediction based on models adjusted to large databases of observed chemical shifts [1 9].
Urinary BPA concentrations ranged from 0.73 to 56.94 ng/mL and were positively associated with increased expression of ESR2 and ESRRA based on models adjusted for potential confounding factors.
Adjusted GM concentrations of 2,5-DCP and 2,4-DCP both decreased between the 2003 2004 and 2009 2010 NHANES cycles based on models adjusted for age and race/ethnicity × income.
Moreover, we estimated negative associations between cadmium and r-MSSD, LF, HF, and TP; between lead and r-MSSD, HF, and TP; and between iron, copper, and arsenic and HF, SDNN, and LF, respectively, based on models adjusted for other metals, creatinine, and covariates (all p < 0.10).
In the overall sample, each doubling of BPb was associated with a 1.3 mmHg increase in SBP (95% CI: 0.1, 2.5) and a 1.0 mmHg increase in DBP (95% CI: 0.3, 1.8) based on models adjusted for race/ethnicity and all model 3 covariates (data not shown).
Based on models adjusted for survey cycle and race/ethnicity × family income, GM concentrations of both 2,4-DCP and 2,5-DCP were significantly higher among 6- to 11-year-old children and older adults (≥ 60 years of age) than among 12- to 19- or 20- to 59-year-old participants (all p < 0.01).
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However, the results based on model 2, adjusted for municipality population distribution, are approximately equivalent to those from a random sample, as shown by results from other studies.
Associations based on spatial models adjusted for maternal smoking (n = 3,752) or maternal education (n = 4,211) were consistent with estimates that were not adjusted for these variables when restricted to the population with available smoking or education data (see Supplemental Material, Tables S3 and S4).
Among the potential confounders, large for gestational age was associated with significantly higher mean BMI z-scores, whereas small for gestational age and preterm delivery were associated with significantly lower mean BMI z-scores based on AMM models adjusted for smoking and all other covariates in the final model (see Supplemental Material, Table S3).
These models were created in preterm cases and controls separately, because of the difference in proportions of cases compared with controls with measurements available at each time point, particularly at visit 4. Finally, we estimated associations based on LMM models adjusted for multiple urinary phthalate metabolites.
Of note, much of the interpretation of our data in this paper, which is descriptive in nature, is based on models that are only adjusted for age (Table 2 and Table 3) and in which multicollinearity does not arise.
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