Meat Intake, Heterocyclic Amines, and Risk of Breast ...To study the effects of meat intake,...
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Vol. 6, 573-581, August 1997 Cancer Epidemiology, Biomarkers & Prevention 573
Meat Intake, Heterocyclic Amines, and Risk of Breast Cancer:
A Case-Control Study in Uruguay1
Eduardo De Stefani,2 Alvaro Ronco,
Maria Mendilaharsu, Martha Guidobono, andHugo Deneo-Pellegrini
Registro Nacional de Cancer, Avenida Brasil 3080, Department 402 [H. D. S.,
A. R., M. M., M. G., H. D-P.], and Departamento de Anatomia Patologicala,
Hospital de Clinicas [H. D-P.], Montevideo, Uruguay I 1300
Abstract
To study the effects of meat intake, including heterocydic
amine exposure, on the risk of breast cancer, weconducted a hospital-based case-control study involving352 patients with breast cancer and 382 controls. Astrong effect of red meat, total meat, beef, fried meat,and heterocydic amine exposure was found, after
controffing for potential confounders. The odds ratio for
the highest quartile of 2-amino-3-methylimidazo[4,5-fiquinoline exposure was 3.34 (95% confidence
interval 1.85-6.02). According to these results, meatintake and chemicals formed during the cooking process
appear to be strong risk factors in human breast
carcinogenesis.
Introduction
Breast cancer is a major public health problem in Uruguayanwomen, with an age-adjusted incidence rate of9l.0 per 100,000
(1). This very high rate is unusual in developing countries like
Uruguay, and the reasons for it are unknown.The Uruguayan population is exposed to a diet with large
amounts of red meat, mainly beef (2). According the Food andAgriculture Organization, the consumption of red meat in Urn-
guay was 80.1 kg/year in 1977, compared with 54.6 kg/year in
United States in the same year (2). It has been suggested thatmeat intake could be a risk factor for this disease (3). Moreover,
the pyrolisis of amino acids in meat during cooking at hightemperature leads to the formation of heterocyclic aromatic
amines. These amines are highly mutagenic and induce tumors
in several sites, including breast, in different animal species (4).
Therefore, we undertook a case-control study on breast cancerand diet to estimate the risk of this disease associated with meat
intake and with heterocycic aromatic amines resulting from the
process of cooking meat.
Received 1/8/97; revised 4/15/97; accepted 4/21/97.
The costs of publication of this article were defrayed in part by the payment of
page charges. This article must therefore be hereby marked advertisement in
accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
I This work was supported by a grant from the Comision Uruguaya de Lucha
contra el Cancer.2 To whom requests for reprints should be addressed.
Subjects and Methods
In the time period between May 1994 and November 1996, allnewly diagnosed cases of breast cancer occurring in the sixmajor hospitals of Montevideo, Uruguay, were considered el-igible for this study. A total of 365 cases were identified, 10 ofwhom refused the interview and 3 of whom were too ill to
answer the questionnaire, leading to a total of 352 interviewedcases, with a response rate of 96.4%. In the same time periodand in the same hospitals, 390 patients hospitalized for non-neoplastic diseases were considered eligible for the study. Eight
patients refused to be interviewed, leading to a control series of
382 patients (response rate, 97.9%). The diseases among thecontrol series are shown in Table 1 . Controls were frequencymatched to cases on the following variables: age (5-year inter-vals), sex, and residence (Montevideo or other counties).
Both cases and controls were subjected to a face-to-face
interview by two trained interviewers to complete a question-naire containing the following sections: (a) demographic data;(b) occupational history; (c) smoking history; (d) a history ofalcohol consumption, including beer, wine, and hard liquor; (e)
anthropometric variables (height, weight, and body mass index
calculated as the Quetelet index); and (f) family history ofcancer in first-degree relatives.
Furthermore, the interview included a food frequency
questionnaire covering 64 food items plus vitamin and mineralsupplements and questions about soft drinks, coffee, coffeewith milk, tea, tea with milk, and mate ingestion. Participantswere asked how often, on average, they consumed the amount
of each food over the 2 years prior to the interview or to theonset of symptoms. Because the questionnaire did not includedportion sizes, these were determined by a nutritionist accordingto local practices. These portion sizes were specific for womenin Uruguayan population. The questionnaire allowed the cal-
culation of total energy intake, as well as intake of a number ofmacro- and micronutrients. Among them, protein, carbohy-
drates, total fat, saturated fat, cholesterol, vitamin A, vitamin C,carotenoids, and vitamin E were calculated. Furthermore, the
Table I Distribution of controls by d isease category
ICD-9” Disease No. %
550-553 Abdominal hernia 90 23.6
800-829 Traumatic fractures 70 18.3
360-379 Eye disorders 58 15.2
451-456 Varicose veins 38 9.9
540 Acute appendicitis 32 8.4
122 Hydatid cyst 29 7.6
830-959 Trauma 23 6.0
680-709 Diseases of the skin 20 5.2
710-739 Osteoarticular diseases 16 4.2
280-289 Diseases of the blood 6 1.6
Total 382 100.0
a lCD International C lassification of Diseases.
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574 Meat Intake, Heterocydic Amines, and Breast Cancer
Table 2 Distribution of cases and controls for se lected variables (1)
VariableNo.
Cases ControlsP
(%)No.(%)
Age (years)
20-29 4 (1.1) 9 (2.4)
30-39 33 (9.4) 42 (11.0)
40-49 50 (14.2) 58 (15.2)
50-59 85 (24.1) 86 (22.5)60-69 87 (24.7) 88 (23.0)
70-79 78 (22.2) 83 (21.7)
80-89 15 (4.3) 16 (4.2) 0.85
Residence
Montevideo 183 (52.0) 201 (52.6)
Other counties 169 (48.0) 181 (47.4) 0.92
Urban/rural status
Urban 292 (83.0) 328 (85.9)
Rural 60 (17.0) 54 (14.1) 0.32
Education (years)
0-5 174 (49.4) 199 (52.1)
�6 178 (50.6) 183 (47.9) 0.52
Monthly income (United States dollars)
�147 116 (33.0) 125 (32.7)
�148 117 (33.2) 123 (32.2)
Unknown 1 19 (33.8) 134 (35.1) 0.93
Family history of breast cancer
No 265 (75.3) 342 (89.5)
Yes 87 (24.7) 40 (10.5) <0.001
Body mass index
�18.7 98 (27.8) 101 (26.4)
18.8-21.2 70 (19.9) 98 (25.7)
21.3-24.2 97 (27.6) 86 (22.5)
�24.3 87 (24.7) 97 (25.4) 0.19
Alcohol drinking
Never drinkers 249 (70.7) 307 (80.4)
Ever drinkers 103 (29.3) 75 (19.6) 0.009
Menopausal status
Premenopausal 75 (21 .3) 99 (25.9)
Postmenopausal 277 (78.7) 283 (74.1) 0.17
Age at menarche (years)
�15 32 (9.1) 60 (15.7)
12-14 234 (66.5) 264 (69.1)
�11 86 (24.4) 58 (15.2) 0.006
Parity (no. of live births)
Nuliparous 76 (21.6) 49 (12.8)
1-2 135 (38.4) 130 (34.0)
3-4 84 (23.9) 105 (27.5)�5 57 (16.2) 98 (25.7) 0.0004
Age at first pregnancy (years)
�19 81 (23.0) 1 19 (31.2)
20-24 88 (25.0) 121 (31.7)
�25 108 (30.7) 93 (24.3) 0.01
History of benign breast disease
No 309 (87.8) 354 (92.7)
Yes 43 (12.2) 28 (7.0) 0.03
Total energy intake (kcal)
�l577 74 (21.0) 110 (28.8)
1578-2080 76 (21.6) 108 (28.3)
2081-2592 103 (29.3) 82 (21.5)
�2593 99 (28.1) 82 (21.5) 0.01
Total fat intake (g)
�68.7 57 (16.2) 127 (33.2)
68.8-82.3 87 (24.7) 96 (25.1)
82.4-96.5 89 (25.3) 95 (24.9)
�96.6 1 19 (33.8) 64 (16.8) <0.001
Vegetables (servings/year)
�538 98 (27.8) 87 (22.8)
539-727 88 (25.0) 94 (24.6)
728-948 84 (23.9) 100 (26.2)
�949 82 (23.3) 101 (26.4) 0.05
No. of patients 352 (100) 382 (100)
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Cancer Epidemio1oaj�, Biomarkers & Prevention 575
Table 3 Mean concen tration of heterocy cic amines in f oods (in �g/g)a
Food IQ MeIQx PHiP
Fried beef
Broiled beef
Broiled lamb
Broiled chicken
Fried fish
Broiled fish
Fried egg
3.79
0.50
NAb
NA
0.61
1.80
0.10
2.35
2.1 1
1.01
2.33
6.44
2.20
NA
13.19
15.70
4230
38.10
19.60
37.50
NA
a According to values reported in Refs. 9-19.
b NA, not available.
questionnaire included queries concerning the cooking method(frying, broiling, barbecuing, and boiling) of the foods, includ-ing meats and eggs. This questionnaire was previously used in
case-control studies on diet and cancer (3, 5, 6). Nutrient intakewas calculated using specially designed software that uses local
food composition tables (7). All nutrients were energy adjustedby the residual method of Willett and Stampfer (8) and latercategorized into four levels, according to the quartile distribu-tion among the combined sample of cases and controls. Intake
of specific foods was recorded as servings per year.The food composition table for heterocycic amine content
was based on data in the literature (9-19) and total estimated
content of IQ,3 2-a.mino-3,8-dimethylimidazo[4,5-fjquinoxa-line, and PHiP for this data base was calculated as continuousvariables in ng/g. Because the questionnaire assessed the pro-portion ofdifferent meats cooked by frying, broiling, or boiling,
total intake of arilamines was calculated as follows: frequency
of consumption of fried and broiled meats X [(portion size ingrams X arylamine content for each fried and broiled meataccording to literature data)/100 g]. The frequency of consump-tion of each fried and broiled meat was obtained from the food
frequency questionnaire. The three arilamines were categorized
according to the quartile distribution among the combinedsample of cases and controls.
ORs and 95% CIs were calculated by unconditional logis-tic regression (20). ORs were estimated for all women, pre-menopausal women, and postmenopausal women. We classi-
fled a woman as postmenopausal when she reported naturalmenopause or hysterectomy with bilateral oophorectomy. Forwomen who reported hysterectomy without bilateral oophorec-
tomy, menopause was assigned to the median value of age atmenopause for the combined sample of cases and controls.Potential confounders were included in the multivariate models.Decisions on which covariates to include in the final modelswere based on (a) biological plausibility, (b) whether the co-variate entered the model at the 0.10 level of significance, and
(c) whether the covariate acted as a confounder of the primaryassociation of interest (confounding was considered present if
the regression coefficient of the primary independent variablechanged more than 10% after addition of the potentially con-founding variable to the model). These confounders were age(continuous), residence (Montevideo or other counties), familyhistory of breast cancer in a first-degree relative (no or yes), ageat menarche, parity, previous history of benign breast disease
(no or yes), total energy intake (continuous), vegetable intake,
and total fat intake. Age at menarche, parity, vegetable intake,
3 The abbreviations used are: IQ, 2-amino-3-methylimidazo[4,5-flquinoline;
PHiP, 2-amino-1-methyl-6-phenylimidazo[4,5-flpyridine; OR, odds ratio; CI,
confidence interval.
and total fat intake were entered in the models as categoricalvariables (Table 2). All calculations were performed using theEGRET software (21).
Results
Compared to controls, significantly more cases had a family
history of breast cancer in first-degree relatives, early age at
menarche, high parity, late age at first full-term pregnancy, ahistory of benign breast disease, and a history of alcohol con-
sumption (Table 2). Age, residence, urban/rural status, educa-tion, and income were similar among both series of patients.
Concentrations of heterocycic amines in various fooditems are shown in Table 3. Elevated concentrations of PHiPwere reported in fried beef, broiled beef, and broiled lamb.
These food items are frequently consumed by the Uruguayan
population.ORs of breast cancer associated with different meats are
shown in Table 4. Whereas red meat, beef, lamb, and total meatintake were associated with significantly increased risks of
breast cancer, white meat (poultry plus fish), poultry, and fishintake were associated with negative dose-response patterns. Inparticular, white meat displayed an OR of 0.59 (95% CI,0.36-0.97) for the highest quartile of intake. Beef intake was
associated with the highest increase in risk among postmeno-pausal women (OR, 4.75; 95% CI, 2.30-9.79); the dose-re-
sponse pattern was also highly significant. When differentmeats (beef, lamb, poultry, and fish) were analyzed accordingto the cooking method (frying, broiling, or boiling), a signifi-cant association for fried meat was evident, with an OR of 2.71for the highest quartile of intake (Table 5). The effect of broiled
meat was not significant, and boiled meat was associated witha significant reduction in risk for the uppermost quartile of
consumption (OR, 0.42; 95% CI, 0.23-0.78). ORs of breastcancer for heterocycic amine exposure, according to the cook-ing methods and to the values reported in the literature, areshown in Table 6. All heterocycic amines were associated withsignificant increases in risk and IQ displayed a 3-fold increasein risk for all women (pre- and postmenopausal). PHiP was
associated with a positive gradient of risks and a highly signif-icant dose-response. In particular, postmenopausal women
were associated with a 3-fold increase in risk for the highestquartile of estimated consumption of PHiP.
ORs of breast cancer for total fat and vegetable intake,with and without adjustment for meat intake in a multivariate
model, are shown in Table 7. Whereas total fat intake wasassociated with a positive gradient of risks, vegetable intakedisplayed a protective effect. Total fat intake reduced risk by65% after further adjustment for beef intake. On the other hand,
vegetable intake risk estimates remained unchanged after in-
clusion of a term for beef in the model.
Discussion
The present study shows increased risks of breast cancer for
increasing intake of red meat, beef, and fried meat and esti-mated intake of heterocycic amines. These risk estimates werefully controlled for confounders, including total energy and
total fat intake, which were strong risk factors in this data set.A number of previous studies showed an effect of meat con-sumption on the risk of breast cancer (22-31), and this effectwas attributed mostly to the fat content of meat. In our study,
we found increasing risks of breast cancer associated with
increasing meat consumption, controffing for fat intake, sug-
gesting another mechanism for meat in breast carcinogenesis.
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Table 4 Relative risks of breast cancer associated with meat variables
All risks are adjusted for age, residence, familyenergy, vegetable intake, and fat intake.
history of breast cancer in a first-degree relative, age at menarche, parity, previous history of benign breast disease, total
.Meat variable
Quartile P for
trendI
�601
II ifi Iv
Total meat’�” s336 337-468 469-600
All subjectsCases 59 79 94 120
Controls 127 108 84 63
OR 1.0 1.29 1.63 2.26
95% CI 0.80-2.09 0.97-2.75 1 .24-4.12 0.006
prelncnopausalc
Cases 11 11 19 34
Controls 29 27 22 21
OR I .0 0.90 1.27 2.42
95% CI 0.28-2.95 0.37-4.32 0.75-7.85 0.11
Postmenopausal�
Cases 48 68 75 86
Controls 98 81 62 42
OR 1.0 1.33 1.58 2.19
95% CI 0.77-2.29 0.87-2.89 1.06-4.51 0.03
Red meaf2e �24l 242-386 387-520 �521
All subjects
Cases 56 76 99 121
Controls 128 107 88 59
OR 1.0 1.25 1.76 2.62
95% CI 0.77-2.05 1.04-2.99 1.41-4.85 0.001
PremenopausalCases 9 10 24 32
Controls 27 25 25 22
OR 1.0 1.41 2.13 3.01
95% CI 0.38-5.29 0.59-7.60 0.77-1 1.7 0.09
Postmenopausal
Cases 47 66 75 89
Controls 101 82 63 37
OR 1.0 1.29 1.57 2.79
95% CI 0.75-2.23 0.86-2.89 1.35-5.75 0.006
Whitemeata.f �36 37-70 71-104 �105
All subjects
Cases 110 78 103 61
Controls 83 90 129 80OR I .0 0.67 0.60 0.59
95% CI 0.42-1.06 0.39-0.93 0.36-0.97 0.02
Premenopausal
Cases 23 19 26 7
Controls 27 30 21 21OR 1.0 0.62 1.36 0.28
95% CI 0.22-1.78 0.50-3.66 0.08-1.03 0.31Postmenopausal
Cases 87 59 77 54
Controls 56 60 108 59OR 1.0 0.60 0.48 0.63
95% CI 0.35-1.04 0.29-0.78 0.36-1.09 0.03
Processed meat” �52 53-104 105-206 �207
All subjects
Cases 92 68 85 107
Controls 114 93 91 84OR 1.0 0.80 0.85 0.88
95% Cl 0.50-1.27 0.53-1.34 0.54-1.43 0.64
Premenopausal
Cases 17 12 13 33
Controls 26 22 26 25
OR 1.0 0.66 0.48 1.3095% CI 0.20-2.16 0.15-1.58 0.43-3.92 0.56
Postmenopausal
Cases 75 56 72 74
Controls 88 71 65 59OR 1.0 0.80 0.91 0.7395% CI 0.47-135 0.54-1.53 0.42-1.30 0.38
Beer �154 155-234 235-364 �365All subjects
Cases 54 85 98 115Controls I 26 136 76 44
OR 1.0 1.23 2.09 3.8495% CI 0.76-1.99 1.23-3.55 2.09-7.05 <0.001
576 Meat Intake, Heterocydlic Amines, and Breast Cancer
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Cancer Epidemiology, Bionsarkers & Prevention 577
Table 4 Continued
All risks are adjusted for age, residence, family history of b
energy, vegetable intake, and fat intake.
roast cancer in a first -degree relative, age at menarche, panty, previous history of be nign breast disease, total
Meat variableQuartile P for
trendI II ifi IV
Premenopausal
Cases 7 20 21 27
Controls 27 34 20 18
OR 1.0 1.91 2.41 2.60
95% CI 0.57-6.41 0.69-8.41 0.69-9.82 0.16
Postmenopausal
Cases 47 65 77 88
Controls 99 102 56 26
OR 1.0 1.15 2.02 4.75
95% CI 0.67-1.97 1.10-3.73 2.30-9.79 <0.001
L�bag �l2 13-52 �53
All subjects
Cases 276 24 52
Controls 336 26 20
OR 1.0 1.05 2.38
95% CI 0.56-1.99 1.27-4.47 0.01
Premenopausal
Cases 56 7 12
Controls 86 5 8
OR 1.0 1.32 1.4595% CI 0.32-5.36 0.40-5.28 0.53
Postmenopausal
Cases 220 17 40
Controls 250 21 12
OR 1.0 0.88 2.90
95% CI 0.42-1.84 1.34-6.27 0.02
Poultrya;a �24 25-52 �53
All subjects
Cases 150 150 52
Controls 132 183 67
OR 1 .0 0.75 0.78
95% CI 0.52-1.06 0.48-1.27 0.18
Premenopausal
Cases 35 32 8
Controls 40 42 17OR 1.0 0.62 0.32
95% CI 0.27-1.40 0.10-1.10 0.06
Postmenopausal
Cases 115 118 44
Controls 92 141 50
OR 1.0 0.73 0.85
95% CI 0.49-1.09 0.50-1.47 0.35
� �l2 13-52 �53
All subjects
Cases 148 163 41
Controls 136 193 53OR 1.0 0.76 0.64
95% CI 0.54-1.09 0.38-1.09 0.06Premenopausal
Cases 28 43 4
Controls 44 44 11
OR 1.0 1.97 0.54
95% CI 0.88-4.37 0. 1 1-2.65 0.65
Poatmenopausal
Cases 120 120 37
Controls 92 149 42
OR 1.0 0.62 0.63
95% CI 0.41-0.93 0.35-1.12 0.04
a Intake in servings per year.
b Total meat includes red meat, white meat, and processed meat
C Premenopausal was defined as women who reported regular vaginal bleeding over the course of the last year.
d Postmenopausal was defined as women who reported lack of regular vaginal bleeding for more than I year.
e Red meat includes beef, lamb, and processed meat.
1White meat includes poultry and fish.
S Intake of lamb, poultry, and fish was categorized in tertiles.
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All risks are adjusted for age, residence, family history of
energy, vegetable intake, and fat intake.
breast cancer in a first-degree relative, age at menarche, parity, previous history of benign breast disease, total
Cooking methodQuartile P for
trendI II m iv
�104 105-156 157-208 �209
87
125
1.0
65
107
1.0
81
133
1.16
0.73-1.85
84
85
1.36
0.83-2.22
122
57
2.71
1.61-4.55 <0.001
10
27
1.0
17
34
1.68
033-5.37
17
18
2.92
0.88-9.73
31
20
2.82
0.91-8.77 0.05
55
80
1.0
64
99
1.08
0.64-1.84
67
67
1.10
0.63-1.92
91
37
2.57
1.39-4.74 0.004
105-168 �169
83
116
0.83
0.53-1.30
75
82
0.86
0.53-1.39
107
59
1.57
0.95-2.59 0.10
17
31
0.57
0.19-1.76
19
19
1 .24
0.40-3.89
26
24
0.69
0.21-2.22 0.95
66
850.89
0.54-1.46
56
63
0.73
0.42-1.26
81
35
1.88
1.04-3.39 0.12
13
25
1.0
Fried meat”
All subjects
Cases
Controls
OR
95% CI
Premenopausalc
Cases
Controls
OR
95% CI
Postmenopausal’�
Cases
Controls
OR
95% CI
Broiledmeat” �52 53-104
All subjects
Cases
Controls
OR
95% CI
Premenopausal
Cases
Controls
OR
95% CI
Postmenopausal
Cases
Controls
OR
95% CI
Boiled meat”
All subjects
Cases 77 116 119 40
Controls 78 130 114 60
OR 1.0 0.80 0.81 0.42
95% CI 0.50-1.27 0.51-1.29 0.23-0.78 0.02
Premenopausal
Cases 13 25 24 13
Controls 14 27 36 22
OR 1.0 0.91 0.55 0.29
95% CI 0.26-3.17 0.16-1.86 0.07-1.25 0.06
Postmenopausal
Cases 64 91 95 27
Controls 64 103 78 38
OR 1.0 0.85 0.98 0.44
95% CI 0.51-1.42 0.58-1.68 0.21-0.90 0.16
74
100
I .0
�42 43-78 79-130 � 131
a Meats included were beef, lamb, poultry, fish, and bacon.
b Servings per year.
C Premenopausal was defined as women who reported regular vaginal bleeding over the course of the last year.
d Postmenopausal was defined as women who reported lack of regular vaginal bleeding for more than 1 year.
578 Meat Intake, Heterocydlic Amines, and Breast Cancer
Table 5 Relative risks of breast cancer associated with cooking method’�
Because meat and fat intake are highly correlated, it could bedifficult to evaluate separate effects of meat and fat. In our dataset, the correlation between heterocylic amines and energy-adjusted total fat was only 0.43. Therefore, we included in allmodels a term for energy-adjusted fat intake and a term for totalenergy intake. As a result, the correlation between meat van-ables and fat dropped from 0.43 to 0.39. This allowed us toestimate separate ORs for meat variables (including heterocy-
clic amines) and for total fat intake.
Whereas fried meat was strongly associated with the riskof breast cancer, broiled meat showed only a marginal increase
in risk. Moreover, boiled meat intake was associated with asignificant reduction in risk. The risk estimates for boiled meatcould be due to the presence of cooked vegetables in stew,
which is the richest source of this food item in this population.The findings concerning fried meat are in accordance with
previous studies (32-33), which suggest that this food item isthe richest source of heterocycic amines. These chemicals are
on March 17, 2020. © 1997 American Association for Cancer Research. cebp.aacrjournals.org Downloaded from
All risks are adjusted for age, residence, family history of
energy, vegetable intake, and fat intake.
breast cancer in a first-degree relative. age at menarche, parity, previous history of benign breast disease, total
Heterocyclic
amine
Quartile P for
trendI II m N
�0.42 0.43-0.66 0.67-1.01 �l.02
92
81
1.87
1.10-3.15
130
54
3.34
1.85-6.02
18
21
2.70
0.76-933
32
20
2.15
038-8.05
<0.001
0.24
74
60
1.75
0.96-3.19
98
34
3.80
1.90-7.60
3.43-4.52 �433
99
85
1.60
0.99-238
120
62
2.13
I .27-3.55
IQ
All subjects
Cases 53 77
Controls 124 123
OR 1.0 1.22
95% CI 0.75-1.99
Premenopausal’�
Cases 7 18
Controls 27 31
OR 1.0 1.89
95% CI 0.54-6.52
Postmenopausal”
Cases 46 59
Controls 97 92
OR 1.0 1.11
95% CI 0.64-1.92 <0.001
MeIQxc �2.50 231-3.42
All subjects
Cases 63 70
Controls 123 112
OR 1.0 1.12
95% CI 0.70-1.79 0.002
Premenopausal
Cases 11 22
Controls 33 29
OR 1.0 2.03
95% CI 0.69-5.97 0.23
Postmenopausal
Cases 52 48
Controls 90 83
OR 1.0 0.92
95% CI 0.54-1.78 0.006
PHiP �11.07 11.08-15.26
All subjects
Cases 68 68 102 114
Controls 119 112 83 68
OR 1.0 1.06 1.81 2.59
95% CI 0.65-1.73 1.06-3.09 1.42-4.70 <0.001
Premenopausal
Cases 13 15 19 28
Controls 32 28 15 24
OR 1.0 1.19 1.24 1.16
95% CI 0.38-3.71 0.34-4.49 0.34-4.01 0.84
Postmenopausal
Cases 55 53 83 86
Controls 87 84 68 44
OR 1.0 1.02 1.85 3.31
95% CI 0.58-1.79 0.99-3.46 1.60-6.87 <0.001
16
19
233
0.77-8.28
26
18
1.97
0.60-6.42
83
66
1.49
0.86-237
94
44
2.14
1.17-3.89
15.27-20.14 �20.l5
a Premenopausal were defined as women who reported regular vaginal bleeding over the course of the last year.
b Postmenopausal were defmed as women who reported lack of regular vaginal bleeding for more than 1 year.
C MeIQx, 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline.
Cancer Epidemiology, Biomarkers & Prevention 579
Table 6 Relative risks of breast cancer associated with heterocyclic amine exposure (ng/g)
strong carcinogens in experimental animals (32-36), leading to studies, heterocycic amine effect was suggested by the cookingthe production of colonic, pulmonary, renal, and mammary method (frying or broiling) or through queries concerning thetumors. It has been suggested (32-33) that heterocyclic amines doneness of meat. The present study combined both the cook-could be important chemicals in human breast carcinogenesis, ing method and the estimated content of heterocyclic amines inpossibly as initiating agents. the diet. Although the validity of our estimation of the content
This study provides some support to the carcinogenic of heterocyclic amines is open to question, it represents, to ourpotential of heterocyclic amine exposure in breast cancer. Pre- knowledge, the first attempt to estimate these substances, and itvious studies in other cancer sites, mainly colon and lung, were could represent an important step to obtain reliable estimates of
partially supportive of such an association (6, 37-40). In those heterocyclic amines in the diet. Our results were mostly similar
on March 17, 2020. © 1997 American Association for Cancer Research. cebp.aacrjournals.org Downloaded from
580 Meat Intake, Heterocyclic Amines, and Breast Cancer
21. EGRET Reference Manual, Revision 3. Seattle, WA: Statistics and Epide-
miology Research Corp., 1992.
Table 7 Relative risks of breast cancer assoc iated with total fat and vegetable intake, with and w ithout adjustment for m eat intake
Variable Cases/controls OR1” 95% CI 0R2” 95% CI
Total fa(
�68.7
68.8-82.3
82.4-963
�96.6
P for trend
57/127
87/96
89/95
1 19/64
1.0
1.60
1.44
3.16
<0.001
1.01-2.55
0.89-2.33
1.90-5.25
1.0
1.37
1.03
2.08
0.03
0.84-2.21
0.62-1.73
1.21-3.57
Vegetables”
�538
539-727
728-948
�949
P for trend
98/87
88/94
84/100
82/101
1.0
0.67
0.51
0.45
<0.001
0.43-1.05
0.32-0.80
0.28-0.72
1.0
0.66
0.52
0.46
0.001
0.41-1.06
0.32-0.84
0.28-0.75
a Adjusted for age (continuous), residence, family history of breast cancer in a first-degree relative, age at menarche, parity, menopausal status, history of benign breast
disease, and total energy intake (continuous).b Adjusted for the same variables as OR1 plus beef intake.
C Intake in grams per day.
d Intake in servings per year.
for pre- and postmenopausal women, although the small sampleof premenopausal women resulted in wider CIs and in a lowerpower to detect differences among both subsets of women.
Recent studies have emphasized the interplay between
heterocyclic amines from meat and the metabolic phenotype inthe etiology of colon cancer (41-43). In particular, rapid N-acetyltransferase metabolizers are at increased risk of coloncancer; rapid metabolizers who eat well-done meat have a6-fold increased risk in risk of colon cancer (42). It would be of
high importance to establish whether the same interactions withthe metabolic phenotype are present in breast cancer. Because
metabolic phenotype was not measured in our study, we wereunable to estimate this joint effect in our patients.
This study has limitations. First, our estimates of hetero-cyclic amines should be considered a first step in constructinga reliable data base for these important substances. Also, the
effect of the disease in hospitalized patients could modify theusual diet, leading to under- or overestimation of the resultingORs. Nevertheless, our estimates for meat variables are in linewith those observed in previous studies (22-31). On the otherhand, controls were selected from the same hospitals as the
cases, they presented similar residence, and they had similareducational levels. Therefore, they could be considered mem-
bers of the same (secondary) population base (44). In conclu-sion, a high intake of fried meat and a high intake of hetero-
cyclic amines were significantly associated with an increased
risk of breast cancer.
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