Acrylamide exposure measured by food frequency questionnaire and hemoglobin adduct levels and...

Acrylamide exposure measured by food frequency questionnaireand hemoglobin adduct levels and prostate cancer risk in theCancer of the Prostate in Sweden Study

Kathryn M. Wilson†,*, Katarina Bälter*, Hans-Olov Adami, Henrik Grönberg, Anna C.Vikström, Birgit Paulsson, Margareta Törnqvist**, and Lorelei A. Mucci**Department of Epidemiology (KMW, H-OA, LAM) and Department of Nutrition (KMW), HarvardSchool of Public Health, Boston, MA, Department of Medical Epidemiology and Biostatistics,Karolinska Institutet, Stockholm, Sweden (KB, H-OA, HG), Department of Environmental Chemistry,Stockholm University, Stockholm, Sweden (ACV, BP, MT), and Channing Laboratory, Brigham andWomen’s Hospital and Harvard Medical School, Boston, MA (LAM)

AbstractAcrylamide, a probable human carcinogen, is formed during the cooking of many commonlyconsumed foods. Data are scant on whether dietary acrylamide represents an important cancer riskin humans. We studied the association between acrylamide and prostate cancer risk using twomeasures of acrylamide exposure: intake from a food frequency questionnaire (FFQ) and acrylamideadducts to hemoglobin. We also studied the correlation between these two exposure measures. Weused data from the population-based case-control study Cancer of the Prostate in Sweden (CAPS).Dietary data was available for 1499 cases and 1118 controls. Hemoglobin adducts of acrylamidewere measured in blood samples from a subset of 170 cases and 161 controls. We calculated oddsratios (ORs) for the risk of prostate cancer in high versus low quantiles of acrylamide exposure usinglogistic regression. The correlation between FFQ acrylamide intake and acrylamide adducts in non-smokers was 0.25 (95% confidence interval: 0.14–0.35), adjusted for age, region, energy intake, andlaboratory batch. Among controls the correlation was 0.35 (95% CI: 0.21–0.48); among cases it was0.15 (95% CI: 0.00–0.30). The OR of prostate cancer for the highest versus lowest quartile ofacrylamide adducts was 0.93 (95% CI: 0.47–1.85, p-value for trend=0.98). For FFQ acrylamide, theOR of prostate cancer for the highest versus lowest quintile was 0.97 (95% CI: 0.75–1.27, ptrend=0.67). No significant associations were found between acrylamide exposure and risk ofprostate cancer by stage, grade, or PSA level. Acrylamide adducts to hemoglobin and FFQ-measuredacrylamide intake were moderately correlated. Neither measure of acrylamide exposure –hemoglobin adducts or FFQ – was associated with risk of prostate cancer.

Keywordsacrylamide; diet; prostate cancer

†Corresponding author: Kathryn M. Wilson, Harvard School of Public Health, Department of Nutrition, 665 Huntington Ave, 3rd Floor,Boston, MA 02115, [email protected] Tel: 617-487-5859 Fax: 617-432-2435.*These authors contributed equally to this work.**These authors contributed equally to this work.None of the authors reported any conflict of interest.

NIH Public AccessAuthor ManuscriptInt J Cancer. Author manuscript; available in PMC 2010 July 16.

Published in final edited form as:Int J Cancer. 2009 May 15; 124(10): 2384–2390. doi:10.1002/ijc.24175.

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IntroductionIn 2002, researchers at Stockholm University reported that high levels of acrylamide are formedduring the cooking of many commonly consumed foods that are prepared at high temperatures.(1) This finding was confirmed by others, and acrylamide has now been detected in a diverseset of foods including breads, cereals, fried potato products, and coffee.(2–4) In fact,acrylamide is ubiquitous in the human diet, with more than thirty percent of calories consumedcoming from foods with detectable levels of acrylamide.(5) Because acrylamide is classifiedas a probable human carcinogen(6), the discovery caused alarm that exposure to acrylamidein diet could be an important cancer risk factor.

The data establishing acrylamide as a probable carcinogen are based on animal and in vitrostudies. Rats given acrylamide in water(7,8) show increased tumor rates at daily doses of about1 mg/kg body weight. Furthermore, glycidamide, the primary metabolite of acrylamide, is amutagenic compound that is reactive with DNA.(9,10) A recent prospective study amongDutch women found an increased risk of ovarian cancer overall and of endometrial canceramong never-smoking women with increased acrylamide intake (11), which suggestsacrylamide may also act through a hormonal pathway.

Studies of human exposure to acrylamide have generally found no association betweenexposure and cancer risk. Nine studies have examined the association between dietaryacrylamide intake and risk of cancers at various sites: colorectal, kidney, bladder, breast, oral,esophageal, larynx, ovarian, endometrial, and prostate.(11–19) Of these, the only report of asignificant association between higher acrylamide intake and cancer risk was for ovarian andendometrial cancer in a cohort of Dutch women.(11)

These studies all estimated acrylamide intake using food-frequency questionnaires (FFQs) toassess diet. It is not well-known, however, whether FFQs can accurately measure acrylamideintake in the diet. Acrylamide content in a particular food varies with specific cooking andprocessing methods for both homemade and commercially prepared foods, which makesmeasuring individual intake difficult. Several reports(20–22) have attempted to assess thevalidity of FFQs by comparing them to acrylamide adducts to hemoglobin (Hb), a biomarkerof acrylamide exposure that represents the internal dose of acrylamide over approximately fourmonths.(23) Results of these studies have varied.

In this study, we build on the epidemiological evidence using data from a population-basedcase-control study of prostate cancer in Sweden. First we assessed FFQ-assessed acrylamideintake by comparing intakes with acrylamide adducts to hemoglobin in a subset of the studypopulation. Second, we studied the association between acrylamide exposure and prostatecancer risk using two measures of acrylamide exposure: FFQ intake and hemoglobin adducts.In addition to total prostate cancer, we also examine the risk of prostate cancer subtypes. Inaddition, this is the first report to use Hb adducts of acrylamide to study the association betweenacrylamide exposure and prostate cancer risk in humans.

Subjects and MethodsParticipants

The Cancer of the Prostate in Sweden (CAPS) study is a population-based case-control studyof prostate cancer previously described in detail.(24) Cases were drawn from four of the sixregional cancer registries in Sweden and diagnosed between 2001 and 2002. Participants fromthe northern and central regions were between 35 and 79 years old, and those from the southernregions were between 35 and 65 years. Cases were incident cases of pathologically orcytologically verified prostate cancer. Cases were informed about the study and asked to

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participate through their treatment physicians. The average time period between date ofdiagnosis and date when the questionnaire was sent out to the cases was 5 months. Clinicaldata on TNM (tumor, nodes, and metastasis) stage, Gleason score, and serum prostate-specificantigen (PSA) level at diagnosis was obtained from linkage to the National Prostate CancerRegistry. Clinical data was available for 95% of cases in the study.

Control subjects were randomly selected from the Swedish Population Registry, whichmaintains complete coverage of the population, and were frequency matched to cases by five-year age groups and region of residence. Controls were contacted by mail and received thesame information about the study as cases.

Overall, 1895 prostate cancer cases were invited to participate. Of those, 1499 (79%) completeda baseline lifestyle and health questionnaire and 1400 (74%) donated a blood sample. Of 1684invited controls, 1130 (67%) completed a questionnaire and 879 (52%) donated blood.

All study participants gave informed consent at the time of enrollment in the study. The studywas approved by the ethics committees at Karolinska Institutet and Umeå University.

Dietary assessmentAs part of the baseline questionnaire, all participants completed a self-administered 261-itemFFQ that assessed usual intake of foods over the previous 12 months. Data from the SwedishNational Food Administration was used to calculate total energy intake and intake of nutrientsbased on questionnaire responses.

Data on the median acrylamide content of foods from the Swedish National FoodAdministration(25) was used to calculate usual intake of acrylamide through diet. Acrylamideintake was calculated based on the consumption of 18 foods and the assigned content ofacrylamide per kilo food were as follow:fried potatoes (292 μg/kg), chips & popcorn (744μg/kg), ground meat dishes (64μg/kg), cereal (184 μg/kg), crispbread (rye) (527 μg/kg), crispbread( wheat) (93 μg/kg), black pudding (40 μg/kg), buns & cookies (115 μg/kg), pancakes (21 μg/kg), sausage (40 μg/kg), fish sticks (30 μg/kg), coffee 25 μg/kg), bread made of rye (122 μg/kg), crackers (205 μg/kg), and muesli (31 μg/kg). Some values are the average value based onseveral analyses, for example, the content for crisp bread (rye) is the average valued from threedifferent types of crisp breads. The acrylamide content in cakes and bread made from wheat,was less then 30 μg/kg, and the content was therefore set to zero in our calculations. Acrylamideintake was calculated by multiplying the acrylamide content of a serving of the food by thefrequency of consumption of that food and summing across all acrylamide-containing itemson the FFQ. The resulting acrylamide intake is in micrograms per day. Acrylamide and otherintakes were calorie-adjusted using the residual method.(26)

We restricted our study to the 2617 men who completed the FFQ component of thequestionnaire. Sixteen were excluded because of unreasonably high or low energy intakes, andone was excluded because of missing acrylamide data. After these exclusions, we had 1499cases and 1118 controls with dietary acrylamide information.

Measurement of acrylamide adducts in bloodAs a biomarker of acrylamide exposure, acrylamide adducts to Hb were measured in bloodsamples from a random sample of 377 men in the CAPS study. Participants received a bloodsampling kit along with the questionnaire and informed consent form. They were given fourtubes (heparin, plasma and EDTA-treated) and were instructed to donate blood at the nearestclinic. Unprocessed blood samples were sent by overnight mail to the Umeå Biobank, wheresamples were divided into plasma, serum, white and red blood cell components and stored ina freezer at −80°C until the time of analysis.

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Red blood cell samples were analyzed for acrylamide adducts to hemoglobin. Briefly, theglobin was precipitated from the red blood cell samples, and the globin samples were thenprepared for analysis of Hb adducts to N-terminal valine according to the N-alkyl Edmanmethod. (27,28) Calibration curves were established from calibration samples preparedaccording to the procedure, using reference globin with known acrylamide-adduct level.(28)

The samples were processed in four batches of approximately 100 samples each. Throughoutthe analysis control samples of two different concentrations were run about 15 times in eachbatch (in addition to the calibration curve). The mean coefficient of variation (CV) was 3.9%within batches. The case/control status of the samples was unknown during the analysis. Bychance, more case samples were included in batches one and two, and more controls were inbatches three and four. Mean acrylamide adduct levels decreased over the four batches. Withineach batch, mean adduct levels were similar for cases and controls, suggesting that thedifference between batches was due to laboratory drift. Laboratory batch was adjusted for inall analyses.

Eleven samples were not processed because the cells were clotted. Men who reported usingtobacco products (cigarettes, pipes, or snuff) at the time of the questionnaire (N=40) wereexcluded from the statistical analysis, as tobacco users are exposed to much higher levels ofacrylamide through tobacco than through the diet. (Mean levels of acrylamide adducts in thesemen was 152 pmol/g globin compared to 52 pmol/g in non-smoking men.) After exclusions,170 cases and 161 controls were used in the analysis of Hb adducts of acrylamide.

Statistical analysisFor the comparison of FFQ acrylamide intake and acrylamide adduct levels, partial Pearsoncorrelation coefficients between FFQ acrylamide intake and acrylamide adducts to Hb werecalculated in the subset of men with blood measurements. We evaluated correlations separatelyamong cases and controls. Correlations were adjusted for age, region, and laboratory batch.Acrylamide intake and Hb adducts were log-transformed to improve normality.

To measure the association between acrylamide adduct levels and risk of prostate cancer weused unconditional logistic regression models with indicator variables for quartile ofacrylamide adducts. Quartiles were created based on the distribution among the controls. Agegroup and region, which were matching factors in this study, were included in all models, aswas laboratory batch. Fully adjusted models also included variables for BMI (continuous) andformer smoking (yes/no). To test for a dose-response trend across quartiles of acrylamideadducts, we also modeled adducts as a continuous variable to see the effect of a 10 pmol/gincrease on cancer risk.

To measure the association between dietary acrylamide intake and risk of prostate cancer, weused unconditional logistic regression models with indicator variables for quintile of calorie-adjusted acrylamide intake. Quintiles were created based on the distribution of intake amongthe controls. Age group and region were included in all models. Fully adjusted models alsoincluded variables for BMI (continuous), former and current smoking (yes/no indicators),education (four categories), zinc intake (ordinal quartiles), and total energy intake (continuous).Employment status and civil (marital) status were also considered as potential confounders.Several other nutrients and foods were considered as potential confounders including: alcohol,alpha-linolenic acid, calcium, vitamin D, folate, phytoestrogens, red meat, fish, and tomatointake. None of these was included in the final models, as they had little effect on theacrylamide-prostate cancer effect estimates or precision. Data on all confounders was collectedin the self-administered mailed questionnaire. To test for a dose-response trend across quintilesof acrylamide intake, we modeled acrylamide as a continuous variable using the median intakein each quintile. Using the quintile medians reduces the impact of outliers and measurement

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error in the FFQ. We used this continuous variable to estimate the effect of a 10 μg/day increasein acrylamide intake.

All statistical analysis was done using SAS 9.1.

ResultsCharacteristics of the study population

Cases and controls were similar in acrylamide intake estimated from the FFQ and in acrylamideadducts to hemoglobin (Table 1). Mean intake was 44.5 μg/day among controls and 43.8 μg/day among cases. In the subset of men with acrylamide adduct measurements, the mean adductlevel adjusted for laboratory batch was 53.7 pmol/g globin among controls and 54.7 pmol/gglobin among cases. Cases were more likely to come from the Northern regions of Sweden.Cases and controls were similar in age, education, BMI, height, smoking status, and diet,including daily intakes of dairy, red meat, fish, fruits, vegetables, and total energy intake.

Acrylamide intake ranged from 8 to 125 μg/day, or 0.08 to 1.59 μg/kilogram body weight perday. The top food contributors to acrylamide intake were crispbread, coffee, other bread, friedpotatoes, and buns and cakes (Figure 1). Crispbread, coffee, other bread, and fried potatoeswere also the major contributors to variation in acrylamide intake between quintiles. There wasa significant (p<0.0001) correlation between acrylamide intake and intake of carbohydrates,fiber, and zinc (all positive) and alcohol (negative). Acrylamide intake was not correlated withage or height and was weakly correlated with BMI (r=0.05, p=0.01).

Correlation between Hb Adducts and FFQ acrylamideThe partial correlation between FFQ acrylamide intake and acrylamide adducts to Hb was 0.25(95% CI: 0.14–0.35), adjusted for age, region, energy intake, and laboratory batch. Amongcontrols only, the correlation was 0.35 (95% CI: 0.21–0.48). Among cases, it was 0.15 (95%CI: 0.00–0.30). Correlations between acrylamide adducts and acrylamide intake measured inμg/kg body weight per day were almost identical to the correlations with acrylamide intake inμg/day. Adjustment for energy intake improved the correlations by reducing within-personmeasurement error. Without adjustment for calories, the correlation between FFQ acrylamideand adduct levels was 0.19 (95% CI: 0.08–0.29), adjusted for age, region, and batch.

Association between acrylamide adducts to hemoglobin and prostate cancer riskAs shown in Table 2, no significant association was seen between quartile of acrylamide Hbadducts and prostate cancer risk. Adjusting for age, region, BMI, former smoking, andlaboratory batch, the relative risk for the highest versus lowest quartile of acrylamide adductswas 0.93 (95% CI: 0.47–1.85). For a 10 pmol/g globin increase in acrylamide adducts, therelative risk of prostate cancer was 1.00 (CI: 0.86–1.16, p=0.98). Among never smokers only,the association was similar; for a 10 pmol/g globin increase in acrylamide adducts, the relativerisk of prostate cancer was 0.91 (CI: 0.75–1.11, p=0.36).

No association was found between acrylamide adducts and specific prostate cancer subtypesincluding advanced disease, localized disease, high- or low-grade disease, or high- or low-PSAdisease (Table 3).

Association between dietary acrylamide from FFQ and prostate cancer riskFor dietary acrylamide calculated from the FFQ, there was no association between higherintakes and prostate cancer risk (Table 4). The relative risk for the highest versus lowest quintileof acrylamide intakes was 0.97 (CI: 0.75–1.27), adjusting for age, region, BMI, education,smoking, and zinc and energy intake. For a 10 μg/day increase in acrylamide intake, the RR

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of prostate cancer was 0.99 (CI: 0.92–1.06, p=0.67). Similar results were seen when the analysiswas limited to non-smokers only and never-smokers only. Among non-smokers, a 10 μg/dayincrease in acrylamide intake was associated with a relative risk of 1.02 (CI: 0.94–1.09,p=0.68). Among never-smokers, a 10 μg/day increase in acrylamide intake was associated witha relative risk of 0.97 (CI: 0.86–1.08, p=0.94).

No association was found between acrylamide intake and specific prostate cancer subtypesincluding advanced disease, localized disease, high- or low-grade disease, or high- or low-PSAdisease (Table 3). Again, these results were similar when restricted to non-smokers only.

Intake of the five foods that contribute most to acrylamide intake in this study was examined(Table 5). We found no association between crispbread, other bread, or coffee intake andprostate cancer risk, but a suggestion of increased risk for men in the highest tertile of intakeof fried potatoes and buns/cakes. However, no p-value for trend was significant. Furthermore,this increased risk was unchanged when dietary acrylamide was also included in the models,suggesting that any association between these foods and prostate cancer risk is due to chanceor to components other than acrylamide.

DiscussionWe found a moderate correlation between acrylamide adducts to Hb and FFQ acrylamideintake, but no association between either Hb adducts or FFQ acrylamide intake and prostatecancer risk. In addition, there was no association between exposure measure and risk of specificsubtypes of prostate cancer, either by grade or stage. This is the first study to examine theassociation between Hb adducts of acrylamide and prostate cancer risk in humans, and it is thefirst study to examine acrylamide exposure and risk of various subtypes of prostate cancer.

Correlation between Hb Adducts and FFQ acrylamideWe found a moderate correlation between acrylamide adducts to Hb and FFQ acrylamideintake. This correlation was higher among controls than among cases. This difference may bedue to recall or selection bias or to recent changes in the diets of cases after diagnosis.

Three other papers have examined the correlation between acrylamide adducts and FFQ-calculated acrylamide intake with varying results. In the Malmö Diet and Cancer Cohort,Wirfalt, et al.(21) found a correlation of 0.60 in non-smoking men. This correlation is probablyoverstated as some participants were selected based on high or low consumption of acrylamide-rich foods, introducing greater between-person variation in intake. Kütting et al.(29) found low(0.17–0.18) but statistically significant correlations between adduct levels and FFQ acrylamidein a study of 828 non-smokers. These results were not adjusted for age or energy intake, andin fact, these correlations are quite similar to our unadjusted results. This underscores theimportance of adjustment for energy intake in studies using FFQs, as energy adjustment hasbeen shown to reduce within-person measurement error and improve FFQ performance.(30)Bjellaas et al.(22) found no correlation between adduct levels and FFQ acrylamide among 50people. The length of the FFQ and the number of items used to calculate acrylamide intakewere not stated. In addition, age, sex, and energy intake were not adjusted for in the correlationanalysis.

It is important to note that FFQ acrylamide and acrylamide adducts to hemoglobin do notmeasure the same thing. FFQ measurements estimate dietary intake of acrylamide, whereashemoglobin adducts also take into account the absorption and metabolism of dietaryacrylamide. In addition, the FFQ assesses the past year of intake, while Hb adducts reflect thepast several months of exposure. Therefore, the two measures would not likely be perfectlycorrelated even in the absence of measurement error. In addition, it is possible that measuring

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adducts of both acrylamide and glycidamide might result in higher correlations betweenadducts and the FFQ, as this would help account for some differences in metabolism betweenindividuals. Our observed correlations can be seen as an estimate of the lower bound of FFQvalidity.

Acrylamide adduct levels and prostate cancer riskThis is the first study to examine the association between acrylamide adduct levels and prostatecancer risk in humans. We found no association between adduct levels of acrylamide and riskof overall prostate cancer or prostate cancer subtypes. Our ability to study specific subtypessuch as advanced or localized disease was limited by low sample sizes in the subgroup withblood data.

The major limitation of our biomarker analysis is related to the biologically relevant time periodof acrylamide exposure. Due to the case-control design, blood samples for cases were collectedafter cancer diagnosis and do not necessarily reflect acrylamide exposure during developmentof the cancer. In addition, hemoglobin adducts of acrylamide reflect only the previous severalmonths of exposure rather than the long-term dietary exposure that is likely most relevant tothe development of prostate cancer.

Dietary acrylamide and prostate cancer riskWe found no association between FFQ-measured acrylamide intake and risk of overall prostatecancer. We also found no association between intake of the major acrylamide-contributingfoods and prostate cancer risk. Our findings are similar to those of Pelucchi et al. (17) in anetwork of hospital-based case-control studies in Italy and Switzerland and to those ofHogervorst et al. (19) in a prospective cohort study in the Netherlands, who found noassociation between acrylamide intake and prostate cancer risk overall or in non-smoking menonly.

Prostate cancer is a clinically heterogeneous disease, and risk factors may play different rolesin disease incidence and progression.(31) Therefore it is important to examine prostate cancerrisk according to stage and grade of prostate cancer when possible. Ours is the first study toexamine acrylamide intake and risk of prostate cancer subtypes. The risk estimates remainednull across different stages, grades, and PSA-levels of cases.

Random measurement error in acrylamide intake is likely. Because the FFQ was not originallydesigned to assess preparation of foods, food items with different cooking methods andsubstantially different acrylamide contents are sometimes grouped into a single FFQ question.In addition, the acrylamide content of foods varies widely depending on specific processingand cooking parameters, resulting in large differences in acrylamide content between differentbrands of the same foods and even between different production batches within the same brand.However, our analysis suggests that FFQ acrylamide intake does provide useful informationon acrylamide exposure. Even with error in our measurement of absolute acrylamide intakes,we are likely to correctly rank individuals in the highest and lowest quintiles of intake.

Differential measurement error is also likely. The difference between cases and controls in thecorrelation between FFQ acrylamide and adduct levels suggest that FFQ accuracy varies bydisease status. It is not clear how such recall bias might affect our results. Further study ofacrylamide intake in prospective cohorts will be necessary to eliminate the possibility of recallbias.

Strengths of our study include its large size, an FFQ with information on most commonlyconsumed high-acrylamide food items, and information on subtypes of prostate cancer. Inaddition, we used both FFQ and biomarker measurements of acrylamide exposure, which

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strengthens our findings of no significant association between dietary acrylamide and prostatecancer risk.

ConclusionsIt is important to note that these results are not at odds with risk estimates based on toxicologicalstudies. Such studies suggest very small increases in cancer risks for the levels of acrylamidetaken in the diet. Using animal study data, Hagmar and Törnqvist estimate a relative risk of1.015–1.05 for humans consuming acrylamide at levels greater than 1 μg/kg/day, whichrepresents less than 2% of the population.(32) Even very large case-control or cohort studiesdo not have the power to rule out such small relative risks.

AcknowledgmentsFunding/Support: This project was supported by the US Department of Defense Prostate Cancer Program, PC031057and by the Swedish Cancer Society. KMW is partially supported by NCI/NIH Training Grant T32 CA09001.

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30. Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hennekens CH, Speizer FE.Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol1985;122(1):51–65. [PubMed: 4014201]

31. Giovannucci E, Liu Y, Platz EA, Stampfer MJ, Willett WC. Risk factors for prostate cancer incidenceand progression in the health professionals follow-up study. Int J Cancer 2007;121(7):1571–8.10.1002/ijc.22788 [PubMed: 17450530]

32. Hagmar L, Törnqvist M. Inconclusive results from an epidemiological study on dietary acrylamideand cancer. Br J Cancer 2003;89(4):774, 5. author reply 775–6. 10.1038/sj.bjc.6601016 [PubMed:12915892]

Wilson et al.


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Figure 1.Contribution of foods to acrylamide intake.

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Table 1

Characteristics of the study population by disease status

Full Study Population Blood Cohort

Cases Controls Cases Controls

N 1489 1111 170 161

Age (mean ± SD) 66.8±7.3 67.7±7.5 67.5±7.4 67.3±7.3

Region (%)

North 31% 18% 28% 16%

South 69% 82% 72% 84%

Education Level (%)

9 years of less 46% 46% 42% 48%

10–12 years 40% 42% 46% 42%

13+ years 14% 11% 12% 10%

BMI (mean ± SD) 26.2±3.4 26.2±3.4 26.0±3.1 26.5±3.3

Height (cm) (mean ± SD) 177±8 176±8 176±14 176±7

Smoking

Never Smokers (%) 39% 38% 43% 48%

Former Smokers (%) 49% 48% 56% 52%

Current Smokers (%) 11% 12% -- --

Dietary characteristics (mean ± SD)

Acrylamide Intake (μg/d) 43.8±13.7 44.5±14.5 45.1±12.8 43.9±13.4

Acrylamide in μg/kg/day 0.54±0.18 0.56±0.20 0.56±0.17 0.54±0.18

Acryl. Adduct (pmol/g globin)* na na 54.7±16.5 53.7±14.9

Total energy intake (kcal/d) 2283±646 2219±656 2287±643 2293±600

Zinc 11.6±1.9 11.7±1.8 11.3±1.7 11.8±1.8

Food Intakes (serv/d) (mean ± SD)

Dairy 5.7±3.1 5.6±3.1 5.7±2.9 5.6±2.8

Red Meat 1.4±0.7 1.3±0.7 1.3±0.7 1.4±0.7

Fish 0.5±0.4 0.5±0.4 0.5±0.3 0.5±0.3

Crispbread 2.4±2.0 2.6±2.1 2.6±1.8 2.5±1.7

Other bread 2.9±1.8 2.8±1.8 3.0±1.8 2.8±1.7

Fruit 1.9±1.4 1.7±1.2 2.0±1.3 2.0±1.4

Vegetables 2.7±1.8 2.5±1.7 2.5±1.5 2.8±1.6

Baked Goods 1.0±0.9 0.9±0.8 1.0±0.9 0.9±0.8

Coffee 3.1±1.9 3.1±2.0 3.1±1.9 3.0±1.8

Disease Characteristics among Cases [N (% of cases)]

CaP Mortality 205 (14%) - 23 (14%) -

Advanced cases** 535 (36%) - 62 (36%) -

Localized cancer** 1020 (69%) - 111 (65%) -

Gleason Grade sum (mean ± SD) 6.5±1.2 - 6.4±1.1 -

PSA Level (mean ± SD) 88.5±359.7 - 64.6±168.5 -


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*Adduct levels are adjusted for laboratory batch.

**Advanced case: death from CaP, or N1, or M1, or T4 or T3. Localized cancer: T1-T2, N0/M0


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Tabl

e 2

Rel

ativ

e ris

k of

pro

stat

e ca

ncer

by

quar

tile

of a

cryl

amid

e he

mog

lobi

n ad

duct

s

Qua

rtile

of a

cryl

amid

e he

mog

lobi

n ad

duct

sPe

r 10

uni

t

Q1

(Low

est)

Q2

Q3

Q4

(Hig

hest

)In

cr in

leve

l*

Med

ian

Hb

addu

cts

32 p

mol

/g39

pm

ol/g

50 p

mol

/g56

pm

ol/g

# ca

se/c

ont

40/4

031

/41

47/4

152

/39

Bas

ic M

odel

O

R1.

000.

781.

120.

981.

02

95

% C

I--

0.39

–1.5

60.

57–2

.17

0.50

–1.9

20.

87–1

.18

p-

valu

e--

0.48

0.75

0.96

0.85

Mul

tivar

iabl

e M

odel

O

R1.

000.

740.

980.

931.

00

95

% C

I--

0.37

–1.4

90.

50–1

.93

0.47

–1.8

50.

86–1

.16

p-

valu

e--

0.40

0.95

0.84

0.98

Bas

ic m

odel

: adj

uste

d fo

r age

in 5

-yea

r int

erva

ls, r

egio

n (n

orth

/sou

th),

and

labo

rato

ry b

atch

.

Mul

tivar

iabl

e m

odel

: adj

uste

d fo

r age

in 5

-yea

r int

erva

ls, r

egio

n (n

orth

/sou

th),

labo

rato

ry b

atch

, BM

I (co

ntin

uous

) and

form

er sm

okin

g (y

es/n

o).

* Acr

ylam

ide

addu

cts m

odel

ed a

s con

tinuo

us v

aria

ble.


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Tabl

e 3

Rel

ativ

e ris

k of

pro

stat

e ca

ncer

subt

ypes

for g

iven

incr

ease

in H

b ad

duct

s or F

FQ a

cryl

amid

e in

take

Pros

tate

Can

cer

Subt

ypes

PSA

leve

l

Adv

ance

dL

ocal

ized

Hig

h-G

rade

Low

-Gra

deH

igh

Low

Per

10 p

mol

/g g

lobi

n in

crea

se in

Hb

addu

cts1

# ca

se/c

ont

62/1

6211

1/16

168

/161

84/1

6110

0/16

163

/161

OR

1.09

0.94

1.19

0.86

1.04

0.95

95%

CI

0.89

–1.3

30.

78–1

.13

0.98

–1.4

50.

70–1

.06

0.87

–1.2

50.

77–1

.18

p-va

lue

0.4

0.5

0.08

0.15

0.65

0.64

Per

10 μ

g/d

incr

ease

in F

FQ a

cryl

amid

e in

take

2

# ca

se/c

ont

516/

1066

988/

1066

612/

1066

675/

1066

223/

1066

589/

1066

OR

0.98

0.98

0.99

0.99

0.96

1.05

95%

CI

0.90

–1.0

70.

91–1

.06

0.91

–1.0

80.

91–1

.07

0.88

–1.0

30.

96–1

.14

p-va

lue

0.64

0.66

0.84

0.73

0.25

0.33

Adv

ance

d di

seas

e: d

eath

, N1,

M1

or T

4 or

T3.

Loc

aliz

ed d

isea

se: T

1-T2

with

N0

and

M0.

Hig

h-gr

ade

dise

ase:

Gle

ason

sum

7–1

0. L

ow-g

rade

dis

ease

: Gle

ason

sum

2–6

. Hig

h PS

A d

isea

se: >

10. L

ow P

SAdi

seas

e: ≤

10.

1 Hb

addu

cts m

odel

ed a

s con

tinuo

us v

aria

ble.

Res

ults

adj

uste

d fo

r age

in 5

-yea

r int

erva

ls, r

egio

n (n

orth

/sou

th),

labo

rato

ry b

atch

, BM

I (co

ntin

uous

), an

d fo

rmer

smok

ing.

2 Acr

ylam

ide

inta

ke m

odel

ed a

s con

tinuo

us v

aria

ble

usin

g m

edia

n in

take

in e

ach

quin

tile.

Res

ults

adj

uste

d fo

r age

in 5

yea

r int

erva

ls, r

egio

n (n

orth

/sou

th),

educ

atio

n (4

cat

egor

ies)

, for

mer

and

cur

rent

smok

ing,

BM

I (co

ntin

uous

), zi

nc in

take

(ord

inal

qua

rtile

s), a

nd e

nerg

y in

take

(con

tinuo

us).


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Tabl

e 4

Rel

ativ

e ris

k of

pro

stat

e ca

ncer

by

quin

tile

of d

ieta

ry a

cryl

amid

e in

take

Qui

ntile

of d

ieta

ry a

cryl

amid

e in

take

Per

10 μ

g/

Q1

(Low

)Q

2Q

3Q

4Q

5 (H

igh)

day

Incr

ease

*

Inta

ke ra

nge

8–33

μg/

d33

–40 μg

/d40

–47 μg

/d47

–56 μg

/d56

–125

μg/

d

# ca

se/c

ont

294/

210

326/

216

269/

214

294/

216

255/

210

Bas

ic M

odel

O

R1.

001.

170.

991.

030.

940.

97

95

% C

I--

0.91

–1.4

90.

77–1

.27

0.81

–1.3

20.

73–1

.21

0.91

–1.0

4

p-

valu

e--

0.21

0.93

0.81

0.65

0.39

Mul

tivar

iabl

e M

odel

O

R1.

001.

140.

991.

060.

970.

99

95

% C

I--

0.89

–1.4

70.

76–1

.28

0.82

–1.3

70.

75–1

.27

0.92

–1.0

6

p-

valu

e--

0.31

0.92

0.65

0.84

0.67

Bas

ic m

odel

: adj

uste

d fo

r age

in 5

-yea

r int

erva

ls a

nd re

gion

(nor

th/s

outh

).

Mul

tivar

iabl

e m

odel

: adj

uste

d fo

r age

in 5

-yea

r int

erva

ls, r

egio

n (n

orth

/sou

th),

educ

atio

n (4

cat

egor

ies)

, for

mer

and

cur

rent

smok

ing,

BM

I (co

ntin

uous

), zi

nc in

take

(ord

inal

qua

rtile

s), a

nd e

nerg

y in

take

(con

tinuo

us).

* Acr

ylam

ide

inta

ke m

odel

ed a

s con

tinuo

us v

aria

ble

usin

g m

edia

n in

take

in e

ach

quin

tile.


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Table 5

Relative risk of prostate cancer by category of intake of high-acrylamide foods

Category of food intake

p-trend*1 (Low) 2 3 (High)

Crispbread

# case/cont 511/349 554/421 373/296

OR 1.00 0.98 0.94

95% CI -- 0.81–1.19 0.75–1.18 0.58

Also adjusted for dietary acrylamide

OR 1.00 0.98 0.96

95% CI -- 0.80–1.21 0.74–1.25 0.76

Other Bread

# case/cont 589/486 353/248 496/332

OR 1.00 1.11 1.01

95% CI -- 0.90–1.36 0.83–1.24 0.97


OR 1.00 1.11 1.01

95% CI -- 0.90–1.36 083–1.24 0.96

Coffee

# case/cont 579/428 320/250 539/388

OR 1.00 0.94 1.01

95% CI -- 0.76–1.16 0.83–1.22 0.86


OR 1.00 0.94 1.04

95% CI -- 0.75–1.17 0.83–1.30 0.66

Fried Potatoes

# case/cont 240/246 749/511 449/309

OR 1.00 1.36 1.31

95% CI -- 1.10–1.69 1.03–1.66 0.16


OR 1.00 1.36 1.32

95% CI -- 1.09–1.69 1.03–1.69 0.14

Buns & Cakes

# case/cont 356/318 626/434 456/314

OR 1.00 1.25 1.26

95% CI -- 1.02–1.53 0.99–1.59 0.26


OR 1.00 1.24 1.25

95% CI -- 1.01–1.52 0.98–1.58 0.28

Models adjusted for age in 5 year intervals, region (north/south), education (4 categories), former and current smoking, BMI (continuous), zinc intake(ordinal quartiles), and energy intake (continuous).


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*p-value for food intake as a continuous variable using median intake for each category.


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