Nitromethane Exposure from Tobacco Smoke and Diet in the U.S. Population: NHANES, 2007-2012.

Nitromethane is a known toxicant and suspected human carcinogen. Exposure to nitromethane in a representative sample of the civilian, noninstitutionalized population in the United States ≥12 years old was assessed using 2007-2012 National Health and Nutritional Examination Survey (NHANES) data. Nitromethane was detected in all 8000 human blood samples collected, of which 6730 were used for analyses reported here. Sample-weighted median blood nitromethane was higher among exclusive combusted tobacco users (exclusive smokers; 774 ng/L) than nonusers of tobacco products (625 ng/L). In stratified sample-weighted regression analysis, smoking 0.5 pack of cigarettes per day was associated with a statistically significant increase in blood nitromethane by 150 ng/L, and secondhand smoke exposure (serum cotinine >0.05 ng/mL and <10 ng/mL) was statistically significant with a 31.1 ng/L increase in blood nitromethane. Certain dietary sources were associated with small but statistically significant increases in blood nitromethane. At median consumption levels, blood nitromethane was associated with an increase of 7.55 ng/L (meat/poultry), 9.32 ng/L (grain products), and 14.5 ng/L (vegetables). This is the first assessment of the magnitude and relative source apportionment of nitromethane exposure in the U.S. population.

Ethylbenzene and styrene exposure in the United States based on urinary mandelic acid and phenylglyoxylic acid: NHANES 2005-2006 and 2011-2012.

Ethylbenzene and styrene are air toxicants with widespread nonoccupational exposure sources, including tobacco smoke and diet. Ethylbenzene and styrene (EB/S) exposure was quantified from their common metabolites measured in spot urine samples obtained from participants (≥6 years old) in the 2005-2006 and 2011-2012 cycles of the National Health and Nutrition Examination Survey (NHANES; N = 4690). EB/S metabolites mandelic acid (MA) and phenylglyoxylic acid (PGA) were measured using ultra-high performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS). MA and PGA were detected in 98.9% and 90.6% of tested urine specimens, respectively. Exclusive smokers had 2-fold and 1.6-fold higher median urinary MA and PGA, respectively, compared with non-users. Sampleweighted regression analysis among exclusive smokers showed that smoking 0.5 pack cigarettes per day significantly increased MA (+97.9 µg/L) and PGA (+69.3 µg/L), controlling for potential confounders. In comparison, exposure from the median daily dietary intake of grain products increased MA by 1.95 µg/L and was not associated with statistically significant changes in urinary PGA levels. Conversely, consuming vegetables and fruit was associated with decreased MA and PGA. These results confirm tobacco smoke as a major source of ethylbenzene and styrene exposure for the general U.S. population.

The statistical performance of an MCF-7 cell culture assay evaluated using generalized linear mixed models and a score test.

Biological assays often utilize experimental designs where observations are replicated at multiple levels, and where each level represents a separate component of the assay's overall variance. Statistical analysis of such data usually ignores these design effects, whereas more sophisticated methods would improve the statistical power of assays. This report evaluates the statistical performance of an in vitro MCF-7 cell proliferation assay (E-SCREEN) by identifying the optimal generalized linear mixed model (GLMM) that accurately represents the assay's experimental design and variance components. Our statistical assessment found that 17beta-oestradiol cell culture assay data were best modelled with a GLMM configured with a reciprocal link function, a gamma error distribution, and three sources of design variation: plate-to-plate; well-to-well, and the interaction between plate-to-plate variation and dose. The gamma-distributed random error of the assay was estimated to have a coefficient of variation (COV) = 3.2 per cent, and a variance component score test described by X. Lin found that each of the three variance components were statistically significant. The optimal GLMM also confirmed the estrogenicity of five weakly oestrogenic polychlorinated biphenyls (PCBs 17, 49, 66, 74, and 128). Based on information criteria, the optimal gamma GLMM consistently out-performed equivalent naive normal and log-normal linear models, both with and without random effects terms. Because the gamma GLMM was by far the best model on conceptual and empirical grounds, and requires only trivially more effort to use, we encourage its use and suggest that naive models be avoided when possible.