cluster sample designed to represent the U.S. population on the basis of age, sex, and race/ ethnicity. Certain subpopulations were over­ sampled to allow for more precise estimates. All participants in the survey gave written informed consent. Information on NHANES procedures may be found at the Centers for Disease Control and Prevention Web site (CDC 2009). The NHANES protocol for each survey period was reviewed and approved by the National Center for Health Statistics Institutional Review Board. A total of 7,166 whole­ blood samples from individuals ≥ 3 years of age were used in this study. Collection was performed by antecubital phlebotomy into EDTA­ containing vacutainers and stored at –70°C before analysis. HbAA and HbGA were meas­ ured in 350 µL whole blood and analyzed by high­performance liquid chromatography/ tandem mass spectrometry (HPLC/MS/MS), as described previously (Vesper et al. 2007, 2008). In brief, the adducts of acrylamide and glycidamide at the N­terminal valines of hemoglobin were cleaved from the pro­ tein chain by use of modified Edman reaction with pentafluorophenyl isothiocyanate as the Edman reagent (Mowrer et al. 1986). The resulting pentafluorophenylthiohydantoin reaction products were extracted by use of liq­ uid–liquid extraction and analyzed by HPLC/ MS/MS. Calibrators, reagent blanks, and quality­control materials were processed in the same manner as the samples. Hemoglobin adduct concentrations are reported relative to the amount of hemoglobin used in the analysis. The total hemoglobin content was determined as cyanomethhemoglobin by use of a commercial assay (Stanbio Laboratory, Boerne TX). The detection limits for HbAA and HbGA adducts were 3 and 4 pmol/g hemoglobin, respectively. The interday impre­ cision (n = 20 days) of this method, expressed as percentage coefficient of variation, were 13% for HbAA and 19% for HbGA, on average, determined with three blood pools [HbAA and HbGA concentrations in pico­ moles per gram hemoglobin: pool 1 (135 and 93); pool 2 (103 and 700); pool 3 (62 and 50), respectively. Calibrators were syn­ thesized by Bachem (King of Prussia, PA) from octapeptides with the same amino acid sequence as the N­terminus of the β­chain of hemoglobin reacted with acrylamide and glycidamide at the valine (AA­octapeptide: 96% purity by HPLC/UV and MALDI (matrix­assisted laser desorption/ionization)/ MS; and GA­ octapeptide: 90% purity by HPLC/UV and MALDI/MS). Calibrators were verified for accuracy in­house by HPLC/MS and by the U.S. Food and Drug Administration (FDA)/National Center for Toxicology Research by use of HPLC/MS and that organization’s own standards. The corresponding stable isotope­labeled com ­ pounds [AAo­ctapeptide and GAo­ctapeptide with stablei­sotope labeled valine ( 13C515N)] were synthesized by the same company and used as internal standards. The Edman reagent was obtained from Fluka (St. Louis, MO), and formamide was obtained from USB Corporation (Cleveland, OH). All other reagents were purchased from Fisher Scientific (Fair Lawn, NJ). HbAA, HbGA, and cotinine levels were log10­ transformed for statistical analysis, because the data distribution is skewed to the higher levels. For selected age groups, sexes, and three race/ethnicity groups, we calculated the geometric means and distribution percen­ tiles for HbAA and HbGA, the HbGA:HbAA­ ratio, and the sum of HbAA and HbGA. Race/ ethnicities were selfr­eported as non­ Hispanic black, non­Hispanic white, and Mexican American. Individuals not included in one of these three race/ethnicity groups were included in the total population estimates. Geometric means and percentiles were calcu­ lated with SUDAAN version 9.0 (Research Triangle Institute, Research Triangle Park, NC). SUDAAN uses sample weights and cal­ culates variance estimates that account for the complex survey design. We estimated 95% confidence intervals (CIs) for geometric means were estimated on the basis of the Taylor series linearization method (Shah et al. 1996), and adapted CIs for percentiles from the methods of Korn and Graubard (1998) and Woodruff (1952). For concentrations below the limit of detection (LOD), a level equal to the LOD divided by the square root of 2 was used (Hornung and Reed 1990). Because of the known effect of smoking on acrylamide levels, we divided the data into two groups according to cotinine levels (serum cotinine ≤ 10 ng/mL: nonsmoker group; serum cotinine >10 ng/mL: smoker group) (Pirkle et al. 2006). We calculated covariatea­djusted geomet ­ ric means for selected demographic groups separately for the nonsmoking and smok­ ing populations, using least­squares mul ­ tiple regression adjusted for the covariates of age group (3–11, 12–19, 20–39, 40–59, ≥ 60 years), sex (male and female), and self­ reported race/ethnicity (non­Hispanic white, nonH­ispanic black, and Mexican American ), and the continuous covariates of body sur­ face area (BSA) and the base 10 logarithm of serum cotinine. We used BSA to adjust for blood volume and thus to account for other possible variability affecting delivery of acrylamide to the blood related to body size measures and was calculated according to Mosteller (1987). To arrive at the final model, we used backward elimination with SUDAAN to eliminate the nonsignificant interactions (p > 0.05) one at a time and then the non­ significant main effects. Nonsignificant main Environmental Health Perspectives • volume 118 | number 2 | February 2010 Exposure of the U.S. population to acrylamide effects were kept in the model as confound­ ers when they changed the beta coefficients for significant main effects or interactions by > 10%. Once the backward procedure was completed, main effects and interactions were added back into the model one at a time and kept in the final model when they were sig­ nificant (p < 0.05). Hypothesis tests to com­ pare covariatea­djusted geometric means were performed using the Contrast option in the Regress procedure of SUDAAN. For further details about the final model and observed interactions between the investigated vari­ ables, see Supplemental Material, Model Information, available online (doi:10.1289/ ehp.0901021.S1 via http://dx.doi.org). Results HbAA and HbGA levels were detectable in 99.9% and 97.5% of all samples, respec­ tively, with individual levels ranging from < 3 to 910 pmol/g hemoglobin for HbAA and < 4 to 756 pmol/g hemoglobin for HbGA. Distributions were different in nonsmokers and smokers (Figure 1). Geometric mean HbAA levels were 49.1–72.5 pmol/g hemo­ globin higher in smokers than in nonsmokers when compared across subgroups of sex, age, or race/ethnicity (Table 1); HbGA levels were 31.6–52.2 pmol/g hemoglobin higher. Ratios of HbGA:HbAA ranged from 0.08 to 0.25 units lower in smokers than in nonsmokers when compared across subgroups of sex, age, and race/ethnicity. The intersubject variability (difference between 90th and 10th percentile) for HbAA and HbGA in nonsmokers was 45 pmol/g hemoglobin and 66 pmol/g hemo­ globin, respectively [Supplemental Material, Table 1 (doi:10.1289/ehp.0901021.S1)]. In smokers, it was much larger, with 179 pmol/g hemoglobin and 191 pmol/g Hb, for HbAA and HbGA, respectively (Supplemental Material, Table 2). The subgroups of sex, age, and race/ethnicity showed similar intersubject variability as the entire group of either smok­ ers or nonsmokers (Supplemental Material, Figures 1 and 2). Nonsmokers. In nonsmokers (Table 2), the covariatea­djusted geometric mean HbAA and HbGA levels were highest in children 3–11 years of age [mean, 54.5 (95% CI, 52.4–56.8) pmol/g hemoglobin for HbAA, 73.9 (95% CI, 71.3–76.6) pmol/g hemoglobin for HbGA] and lowest in adults age ≥ 60 years [46.2 (95% CI, 44.3–48.2) pmol/g hemo­ globin for HbAA, 41.8 (95% CI, 38.7–45.2) pmol/g hemoglobin for HbGA]. Among the race/ethnic groups, Mexican Americans had the highest HbAA [54.8 (95% CI, 51.9–57.8) pmol/g Hb] and HbGA levels [57.9 (95% CI, 53.7–62.5) pmol/g Hb]. HbGA lev­ els were higher in men than in women and lowest in non­Hispanic blacks [43.5 (95% CI, 41.1–45.9) pmol/g Hb] compared 279