Characteristics of the 296 women in the validation study subgroup are shown in along with characteristics of the full cohort. Mean acrylamide intake was 20.1 mcg/day in the full cohort and 19.3 mcg/day in the validation group. Intake in relation to body weight was 0.3 mcg/kg body weight/day, somewhat lower than the estimated 0.4 mcg/kg/d for the overall U.S. population including men and children.(20
) Women in the validation group were slightly older and more likely to be postmenopausal than women in the full cohort. The two groups were very similar in macro- and micro-nutrient intakes and servings per day of major food groups.
Characteristics of the validation study subgroup and the full NHS II Cohort (Mean ± SD)
shows the contribution of various foods to acrylamide intake in this cohort. The major food sources of acrylamide were French fries (23%), caffeinated coffee (13%), cold breakfast cereal (12%), and potato chips (9%). These are similar to FDA estimates of food sources of acrylamide in the US.(20
Contribution of foods to acrylamide intake in the Nurses' Health Study 2 cohort (1999).
shows characteristics of the validation group according to quartile of total acrylamide and glycidamide adducts (AA+GA-Hb). Acrylamide intake as measured by the FFQ increased across blood quartiles from 15.5 mcg/day [0.22 mcg/kg/day] in the lowest quartile to 21.9 mcg/day [0.31 mcg/kg/day] in the highest quartile. Servings per day of major acrylamide-contributing foods also increased across quartiles. Women in the highest versus lowest quartile ate more French fries, coffee, cold breakfast cereal, and potato chips. Macronutrient intake was similar across quartiles, but alcohol intake was lower in the highest quartile. Alcohol and BMI were both associated with adduct levels independent of acrylamide intake. Adjusting for laboratory batch, age, and calorie-adjusted acrylamide intake, BMI was positively correlated with AA-Hb (r=0.17, p=0.006) and negatively correlated with GA-Hb (r=−0.11, p=0.07). Alcohol intake was negatively correlated with AA-Hb (r=−0.18, p=0.002). Neither alcohol nor BMI were significantly correlated with the sum of AA+GA-Hb.
Characteristics of the study population by quartile of blood adducts levels
The adduct levels were strongly correlated with each other. The correlation was 0.69 between AA-Hb and GA-Hb, 0.92 between AA-Hb and sum of AA+GA-Hb, and 0.91 between GA-Hb and AA+GA-Hb (all p<0.0001). Adduct levels were not correlated with the length of storage of the blood samples, and mean adduct levels were similar for blood samples collected in 1998 versus 1999 and 2000.
Reproducibility of acrylamide adduct measures
Forty-five women in the validation group provided two blood samples at least 10 months apart. These samples were used to determine the stability of acrylamide and glycidamide adducts over time. The average age in the reproducibility subgroup was 44, and average acrylamide intake from the 1999 FFQ was 19.7 mcg/day (0.28 mcg/kg/d). Median time between blood samples was 23 months, with a range of 10 to 32 months. The intraclass correlation coefficients were 0.78 for AA-Hb, 0.80 for GA-Hb, and 0.77 for AA+GA-Hb.
Validation of FFQ acrylamide
shows the correlation between FFQ acrylamide and Hb adduct levels. Adjusting only for laboratory batch, the correlation was 0.19 (95% CI: 0.08–0.30) for AA-Hb, 0.24 (0.13–0.35) for GA-Hb, and 0.24 (0.12–0.34) for AA+GA-Hb. Adjustment for energy intake improved the correlations, while adjustment for age had no effect. Correlations adjusted for age and energy intake were 0.26 (0.14–0.36) for AA-Hb, 0.31 (0.20–0.41) for GA-Hb, and 0.31 (0.20–0.41) for AA+GA-Hb. We further adjusted correlations for BMI and alcohol intake, as both were associated with adduct levels independent of acrylamide intake. Adjusting for such factors reduces variation in adduct levels that is unrelated to intake. This gave correlations of 0.27 (0.16–0.38) for AA-Hb, 0.33 (0.22–0.43), and 0.32 (0.21–0.42).
Pearson correlations (95% CI) between 1999 FFQ acrylamide and hemoglobin adducts of acrylamide and glycidamide
Because we had only one blood measurement per person in the full group, the observed correlations were attenuated due to random within-person variation in the blood measures. Intraclass correlation coefficients from the reproducibility analysis were used to de-attenuate these correlations, and corrected confidence intervals were calculated using the method of Rosner and Willett.(26
) Because of the high stability of adduct levels over time, the de-attenuation only slightly improved the correlations. Corrected correlations were 0.29 (95% CI: 0.17–0.40) for AA-Hb, 0.35 (0.24–0.46) for GA-Hb, and 0.34 (0.23–0.45) for AA+GA-Hb.
We conducted several analyses to investigate whether misclassification of smoking status might be affecting our results. Five women in our validation sample reported that they quit smoking between the 1997 and 1999 questionnaires. It is possible these women quit smoking shortly enough before giving a blood sample that their adduct levels still reflected cigarette exposure. However, excluding these women did not affect our correlation results. Additionally, excluding one non-smoking woman with an unusually high AA-Hb value (148 pmol/g) had no effect.
Cross-tabulation of quartiles of FFQ acrylamide and quartiles of AA+GA-Hb are shown in . Based on the FFQ classification, 47% of those in the lowest quartile of acrylamide intake were in the lowest quartile of AA+GA-Hb. Of those in the highest quartile of FFQ acrylamide, 30% were in the highest quartile of AA+GA-Hb. Overall, 31% of participants were classified in the same quartile for both FFQ acrylamide and acrylamide adducts. For AA-Hb alone, 29% of participants were classified in the same quartile, and for GA-Hb, 31% were classified in the same quartile.
Cross-tabulation of FFQ acrylamide quartile and AA+GA-Hb adduct quartile
shows mean adduct levels according to decile of FFQ acrylamide intake. The mean sum of AA+GA-Hb adducts was 82.4 pmol/g (SE±3.8) for the lowest decile of intake and 110.2 (±5.5) for the highest decile of intake.
Mean (±SE) AA+GA-Hb adducts by decile of FFQ acrylamide intake.
We also conducted several stratified correlation analyses to see if the association between FFQ acrylamide and Hb adducts varied among different groups. There was no appreciable difference in correlations among women with longer and shorter times between the blood draw and the FFQ. There was also no difference between women with higher or lower BMIs or between women who did and did not consume alcohol (data not shown).
We performed stepwise regression to determine which of the top 20 acrylamide-contributing foods from the FFQ were most predictive of Hb adducts (). All models included terms for laboratory batch, age, BMI, alcohol intake, and total energy intake. Potato chips, sweet potatoes/yams, caffeinated coffee, cold breakfast cereal, French fries, prune juice, popcorn, and decaffeinated coffee were the most predictive of the sum of acrylamide and glycidamide adducts. The partial correlation between adduct levels and foods in the model ranged from 0.09 to 0.21.
Stepwise regression predicting Hb adducts from top 20 acrylamide-contributing foods