Download Food groups and risk of oral and pharyngeal cancer

Int. J. Cancer: 77, 705–709 (1998)
r 1998 Wiley-Liss, Inc.
Publication of the International Union Against Cancer
Publication de l’Union Internationale Contre le Cancer
FOOD GROUPS AND RISK OF ORAL AND PHARYNGEAL CANCER
Fabio LEVI1*, Cristina PASCHE1, Carlo LA VECCHIA2, Franca LUCCHINI1, Silvia FRANCESCHI3 and Philippe MONNIER4
Vaudois des Tumeurs, Institut Universitaire de Médecine Sociale et Préventive, Lausanne, Switzerland
2Istituto di Ricerche Farmacologiche ‘‘Mario Negri’’ and Istituto di Statistica Medica e Biometria, Università degli Studi di Milano,
Milan, Italy
3Servizio di Epidemiologia, Centro di Riferimento Oncologico (CRO), Aviano (PN), Italy
4Service d’oto-Rhino-Laryngologie, Centre Hospitalier Universitaire, Vaudois, Lausanne, Switzerland
1Registre
The role of specific food groups and diet variety on the risk
of oral and pharyngeal cancer has been considered using data
from a case-control study conducted between 1992 and 1997
in the Swiss Canton of Vaud. Cases were 156 patients (126
males, 30 females) aged under 75 (median age 56) years with
incident, histologically confirmed cancer of the oral cavity
and pharynx, and controls were 284 subjects (246 males, 38
females, median age 57 years), admitted to the same university hospital for a wide spectrum of acute, non-neoplastic
conditions unrelated to tobacco and alcohol consumption or
to long-term modification of diet. After allowance for education, alcohol, tobacco and total energy intake, significant
trends of increasing risk with more frequent intake emerged
for eggs (OR 5 2.3 for the highest tertile), red meat (OR 5
2.1) and pork and processed meat (OR 5 3.2). Inverse trends
in risk were observed for milk (OR 5 0.4 for the highest
tertile), fish (OR 5 0.5), raw vegetables (OR 5 0.3), cooked
vegetables (OR 5 0.1), citrus fruit (OR 5 0.4) and other fruits
(OR 5 0.2). The addition of a serving per day of fruit or
vegetables was associated with an about 50% reduction in oral
cancer risk. The most favourable diet for oral cancer risk is
therefore given by infrequent consumption of red and processed meat and eggs and, most of all, frequent vegetable and
fruit intake. Diet diversity was inversely related to oral and
pharyngeal cancer: ORs were 0.35 for the highest tertile of
total diversity, 0.24 for vegetable and 0.34 for fruit diversity.
In terms of attributable risk, high meat intake accounted for
49% of oral and pharyngeal cancers in this population, low
vegetable intake for 65% and low fruit intake for 54%. Int. J.
Cancer 77:705–709, 1998.
r 1998 Wiley-Liss, Inc.
Earlier work on dietary correlates of oral and pharyngeal cancer
found little association with any specific food or nutrient (Graham
et al., 1977), but subsequent studies showed decreased risks with
increasing consumption of fresh fruit and green leaf and other
vegetables (Marshall et al., 1982, 1992). Work from the United
States (Winn et al., 1984) and Brazil (Franco et al., 1989), as well
as the largest study available to date on diet and oral and
pharyngeal cancer (a population-based case-control investigation
conducted in 4 areas of the United States [McLaughlin et al.,
1988]) indicated a protection by fresh fruit, which was not totally
explained by b-carotene, vitamin C or fibre content.
In case-control studies conducted in northern Italy (Franceschi et
al., 1991; La Vecchia et al., 1991), the strongest protection was also
related to frequent fruit consumption, and this was independent
from major potential confounding factors, including tobacco,
alcohol and social class correlates. As in the U.S. data (McLaughlin
et al., 1988), b-carotene, but not retinol, was inversely related with
risk of cancers of the oral cavity and pharynx, but the association
was not stronger than with measures of fruit consumption (odds
ratio [OR] for the upper level 5 0.3). It is likely, therefore, that this
inverse relationship was not specific but simply reflected a
generally poorer diet in the cases.
Thus, foods and food patterns have a quantifiable role in oral and
pharyngeal cancer risk not only in developing countries but also in
developed ones (La Vecchia et al., 1997b). The precise dietary
pattern that may entail a reduced oral and pharyngeal cancer risk,
however, remains unclear. To provide further information on the
issue, we considered data of a case-control study conducted in the
French-speaking region of Switzerland, a relatively high-incidence
area for oral cancer on a European scale (Levi et al., 1995).
MATERIAL AND METHODS
A case-control study of oral and pharyngeal cancer was conducted between January 1992 and June 1997 in the Swiss Canton of
Vaud.
Cases were subjects with incident (i.e., diagnosed within the year
before the interview), histologically confirmed cancers of the oral
cavity and pharynx (International Classification of Diseases, 9th
Revision, 141.0–141.9, 143.0–146.9, 148.0–149.9, excluding lip
[140.0–140.9], salivary gland [142.0–142.9] and nasopharyngeal
neoplasms [147.0–147.9]), who had been admitted to the University Hospital of Lausanne, Switzerland. Cases identified and
interviewed were linked with the incidence data from the Vaud
Cancer Registry (Levi et al., 1997) to verify the correspondence of
their socio-demographic characteristics with all incident cases. A
total of 156 cases (oral cavity or oropharynx, 112; pharynx, 44; 126
males, 30 females), aged 26–72 (median age 55) years, were
interviewed.
Controls were patients aged #75 years residing in the same
geographical area, whose admission diagnosis was of acute,
non-neoplastic diseases, judged to be unrelated to tobacco, alcohol
or long-term modification of diet. Controls came from similar
catchment area as cases and were selected in comparable strata of
age. A total of 284 controls (246 males, 38 females) aged 23–74
(median age 58) years were interviewed. They were also admitted
to the same university hospital in Lausanne for a wide spectrum of
acute conditions, including traumas (19%, mostly sprains and
fractures), non-traumatic orthopaedic diseases (25%, mostly low
back pain and disk disorders), surgical conditions (40%, mostly
abdominal, such as acute appendicitis, peritonitis, urinary stones,
cholecystitis, cholelithiasis or strangulated hernia) and miscellaneous other disorders (16%, including acute medical, eye/nose/
throat and skin diseases).
All interviews were conducted in the hospital. Twenty-two
percent of cases and 15% of controls approached for interview
refused. The structured questionnaire included information on
socio-demographic characteristics and life-style habits (e.g., smoking, physical exercise), anthropometric factors and a problemoriented medical history. Information on alcohol included, for each
type of beverage (wine, beer or spirits), data on days per week and
drinks per day, the age at starting and the duration of the habit, in
years.
Grant sponsor: Swiss Foundation for Research Against Cancer; Grant
sponsor: Vaud League Against Cancer; Grant number: AKT 413.
*Correspondence to: Registre vaudois des tumeurs, Institut universitaire
de médecine sociale et préventive, Centre Hospitalier Universitaire Vaudois, Falaises 1, Casier 15, CH-1011 Lausanne, Switzerland. Fax: (41)21–
323 03 03. E-mail: [email protected]
Received 4 February 1998; Revised 2 April 1998
LEVI ET AL.
706
An interviewer-administered food-frequency questionnaire
(FFQ), adapted from a validated Italian one (Franceschi et al.,
1993; Decarli et al., 1996), was used to assess subjects’ habitual
diet, including total energy. Average weekly frequency of consumption of specific foods or food groups as well as complex recipes
(including the most common ones in the diet) during the 2 years
prior to cancer diagnosis or hospital admission (for controls) were
elicited. Intakes lower than once a week but at least once a month
were coded as 0.5 per week.
The FFQ included 79 foods, food groups or recipes grouped into
6 sections: (i) bread and cereal dishes; (ii) meat, poultry, fish and
foods used as meat substitutes; (iii) vegetables (side dishes); (iv)
fruit; (v) sweets/desserts and soft drinks; and (vi) milk and dairy
products. Another section dealt with alcoholic beverage consumption. At the end of some sections, 1 or 2 summary questions were
included concerning all food items or dishes of a certain type (e.g.,
any type of meat). Several questions aimed at assessing fat intake
pattern were also included.
Data analysis
Food items and recipes were categorised into 14 groups: milk
and dairy products (10 questions), bread and cereal dishes (8
questions), soups (2 questions), eggs (2 questions), poultry (2
questions), red meat (beef, veal, lamb; 6 questions), pork and
processed meat (4 questions), fish (3 questions), raw vegetables (4
questions), cooked vegetables (8 questions), potatoes (2 questions),
citrus fruit (2 questions), other fruit (8 questions) and cakes and
desserts (6 questions). The total weekly frequency of intake of food
items and recipes included in the same group was subdivided into
approximate tertiles based on the control distribution. Diversity
was computed as the total number of different foods consumed at
least once per week (La Vecchia et al., 1997a). Besides total
diversity, vegetable, fruit and meat diversity were considered.
Subjects were subdivided into tertiles of diversity based on the
distribution of controls.
ORs and the corresponding 95% confidence intervals (CIs) were
computed using unconditional multiple logistic regression models
(Breslow and Day, 1980). All regression equations included terms
for age in quinquennia, years of education, tobacco (never,
ex-smokers, current smokers of ,15 and $15 cigarettes per day
plus pipe/cigar) and alcohol (non-drinkers, drinkers of ,15 and
$15 drinks per week and ex-drinkers) consumption and total
energy (other than alcohol, quintiles) intake.
Intake frequency of each food group was also introduced as a
continuous variable. In these models, the unit of measurement for
each food group was set at 7 per week. Hence, these models give an
estimate of the OR relative to an increase of 1 average serving per
day.
Using the distribution of the risk factors in the cases and the ORs
from the logistic models, population attributable risks were computed, i.e., the proportion of cancers of the oral cavity and pharynx
that would have been avoided if all subjects were in the most
favourable intake tertile level. The method described by Bruzzi et
al. (1985) implies knowledge of the ORs and of the joint
distribution of the risk factors in the population of cases only and,
thus, can be applied to hospital-based case-control studies. The
attributable risk for each factor describes the theoretical percent of
cases that would be prevented if all subjects were moved into the
exposure level associated with the lowest risk of that factor.
Variance estimates and the corresponding 95% CIs were based on
the method described by Benichou and Gail (1990) (Mezzetti et al.,
1996).
RESULTS
Table I gives the distribution of oral cancer cases and controls
according to sex, age group, education and tobacco/alcohol consumption. Cases were somewhat less educated and significantly
more frequently smokers (OR 5 7.1 for current and 1.6 for ex- vs.
TABLE I – DISTRIBUTION OF 156 CASES OF ORAL AND PHARYNGEAL CANCER
AND OF 284 CONTROLS BY SEX, AGE GROUP, YEARS OF EDUCATION,
SMOKING STATUS AND ALCOHOL CONSUMPTION: VAUD, SWITZERLAND
(1992–1997)
Characteristic
Sex
Male
Female
Age (years)
,45
45–54
55–64
$65
Education (years)
,9
9–12
$13
Smoking status
Never-smoker
Ex-smoker
Current smokers
,15 cigarettes/day
$15 cigarettes/day
pipe/cigar only
Alcohol (drinks/week)
Non-drinker
,15
$15
Ex-drinker
Cases
Controls
Number
%
Number
%
126
30
80.8
19.2
246
38
86.6
13.4
14
58
53
31
9.0
37.2
34.0
19.9
54
70
80
80
19.0
24.6
28.2
28.2
13
96
47
8.3
61.5
30.1
38
159
87
13.4
56.0
30.6
11
20
125
11
109
5
7.1
12.8
80.1
7.1
69.9
3.2
109
72
103
21
75
7
38.4
25.3
36.3
7.4
26.4
2.5
12
16
122
6
7.7
10.2
78.2
3.9
56
126
89
13
19.7
44.4
31.3
4.6
never-smokers) and heavy alcohol drinkers (OR 5 10.2 for $15
drinks per week as compared to non-drinkers). The association was
present for beer (OR 5 4.9), wine (OR 5 9.4) and spirit (OR 5 5.1)
drinkers.
Table II gives the upper limit of intake tertiles of each food group
and the corresponding multivariate ORs after allowance for
education, alcohol, tobacco and total energy intake. Intakes of
bread, soups, poultry, cheese and cakes/desserts were not significantly related to oral and pharyngeal cancer risk. Significant trends
of increasing risk with more frequent intake emerged for eggs
(OR 5 2.3 for the highest tertile), red meat (OR 5 2.1) and pork
and processed meat (OR 5 3.2). Inverse trends in risk were
observed for milk (OR 5 0.4 for the highest tertile), fish (OR 5
0.5), raw vegetables OR 5 0.3), cooked vegetables (OR 5 0.1),
citrus fruit (OR 5 0.4) and other fruits (OR 5 0.2).
Table III gives the ORs for an increase of 1 serving per day of
each food group significantly related to oral cancer risk. These were
0.8 for milk, 1.5 for eggs, 1.4 for meat and pork, 0.8 for fish, 0.6 for
raw vegetables, 0.4 for cooked vegetables, 0.7 for citrus fruits and
0.5 for other fruits. Thus, an additional portion of fruit or
vegetables per day seemed to convey a protection of 30–50% on
oral cancer risk. Simultaneous inclusion of meat and vegetables or
fruit led to ORs of 1.3 for meat and pork, 0.6 for raw vegetables, 0.4
for cooked vegetables, 0.7 for citrus fruits and 0.5 for other fruits.
Vegetable, fruit, meat and total diversity are considered in Table
IV. Compared with subjects in the lowest tertile, ORs were 0.24 for
those in the highest tertile of vegetable, 0.34 of fruit and 0.35 of
total diversity. The trends in risk were significant. In contrast, the
ORs for subsequent tertiles of meat diversity were 1.14 and 1.82,
but the corresponding trend in risk was nonsignificant.
DISCUSSION
Our present data confirm that dietary patterns and, in particular,
food-intake patterns have a relevant role in the risk of oral and
pharyngeal cancer. This holds true also even after allowance for
alcohol and tobacco, by far the major risk factors for oral cancer in
Western countries, as well as for social class indicators and total
energy intake. As previously reported in 11 of 13 studies on the
DIET AND OROPHARYNGEAL CANCER
707
(CI)1
TABLE II – ODDS RATIOS (OR) AND 95% CONFIDENCE INTERVALS
OF ORAL AND PHARYNGEAL CANCER AMONG
156 CASES AND 284 CONTROLS ACCORDING TO INTAKE TERTILE OF SELECTED FOOD GROUPS: VAUD, SWITZERLAND
(1992–1997)
Food group
Milk
Upper limit (servings/week)
OR
(95% CI)
Bread and cereals
Upper limit (servings/week)
OR
(95% CI)
Soups
Upper limit (servings/week)
OR
(95% CI)
Eggs
Upper limit (servings/week)
OR
(95% CI)
Poultry
Upper limit (servings/week)
OR
(95% CI)
Red meat
Upper limit (servings/week)
OR
(95% CI)
Pork and processed meat
Upper limit (servings/week)
OR
(95% CI)
Fish
Upper limit (servings/week)
OR
(95% CI)
Cheese
Upper limit (servings/week)
OR
(95% CI)
Raw vegetables
Upper limit (servings/week)
OR
(95% CI)
Cooked vegetables
Upper limit (servings/week)
OR
(95% CI)
Potatoes
Upper limit (servings/week)
OR
(95% CI)
Citrus fruits
Upper limit (servings/week)
OR
(95% CI)
Other fruits
Upper limit (servings/week)
OR
(95% CI)
Cakes and desserts
Upper limit (servings/week)
OR
(95% CI)
Intake tertile
12
x21
(trend)
2
3
4.0
1
11.0
0.33
(0.18–0.62)
0.38
(0.21–0.70)
11.31**
17.3
1
26.5
1.71
(0.94–3.13)
1.69
(0.82–3.49)
2.75
0.5
1
1.0
1.33
(0.75–2.34)
1.42
(0.77–2.62)
1.23
1.0
1
3.0
1.33
(0.76–2.34)
2.32
(1.28–4.22)
7.46**
0.5
1
1.0
1.05
(0.59–1.90)
0.92
(0.46–1.11)
0.08
2.0
1
3.5
1.42
(0.78–2.56)
2.14
(1.15–3.99)
5.78*
2.0
1
4.5
2.29
(1.20–4.36)
3.21
(1.66–6.24)
11.35**
1.0
1
1.5
0.76
(0.43–1.35)
0.54
(0.30–0.96)
4.40*
4.0
1
7.7
1.35
(0.78–2.32)
1.19
(0.66–2.14)
0.38
5.0
1
8.5
0.63
(0.37–1.08)
0.30
(0.16–0.58)
13.07**
5.2
1
8.6
0.42
(0.25–0.72)
0.14
(0.07–0.19)
31.69**
2.0
1
3.5
0.92
(0.51–1.65)
1.22
(0.70–2.14)
0.50
1.5
1
3.5
0.34
(0.20–0.60)
0.38
(0.20–0.73)
12.95**
5.2
1
11.0
0.42
(0.25–0.73)
0.22
(0.11–0.44)
29.66**
1.2
1
4.0
0.93
(0.54–1.61)
1.02
(0.52–2.03)
0.00
1Estimates from multiple logistic regression equations including terms for age, sex, education, smoking,
alcohol and non-alcohol total energy (other than alcohol) intake.–2Reference category: *p , 0.05, **p ,
0.01.
issue, the strongest factor was the protection conveyed by fruit and
vegetables (Potter and Steinmetz, 1996). The addition of 1 serving
per day of fruit or vegetable appeared to reduce oral cancer risk by
about 50%.
This protection by fruit and vegetables has been related to
selected micronutrients, including b-carotene and other carot-
enoids (La Vecchia et al., 1991; Zheng et al., 1993). The data,
however, were also consistent with the hypothesis that a more
varied diet (and hence probably richer in several nutrients) may be
protective against oral carcinogenesis. A simple explanation for this
protective effect is that individuals eating more varied foods are
more likely to consume a number of beneficial compounds (La
LEVI ET AL.
708
TABLE III – ODDS RATIOS (OR) AND CORRESPONDING 95% CONFIDENCE
INTERVALS (CI)1 AMONG 156 CASES OF ORAL AND PHARYNGEAL CANCER
AND 284 CONTROLS FOR AN INTAKE INCREASE OF 1 SERVING PER DAY
OF SELECTED FOOD GROUPS: VAUD, SWITZERLAND (1992–1997)
Food group
OR (95% CI)
Milk
Eggs
Red meat
Pork and processed meat
Fish
Raw vegetables
Cooked vegetables
Citrus fruit
Other fruits
0.80 (0.66–0.97)
1.46 (1.14–1.86)
1.35 (1.07–1.69)
1.37 (1.13–1.67)
0.85 (0.74–0.98)
0.64 (0.52–0.80)
0.44 (0.33–0.59)
0.73 (0.61–0.88)
0.51 (0.38–0.68)
1Adjusted for age, sex, education smoking, alcohol and total energy
(other than alcohol) intake.
TABLE IV – ODDS RATIOS (OR) AND CORRESPONDING 95% CONFIDENCE
INTERVALS (CI) AMONG 156 CASES OF ORAL AND PHARYNGEAL CANCER
AND 284 CONTROLS ACCORDING TO DIVERSITY OF INTAKE OF SELECTED
FOOD GROUPS: VAUD, SWITZERLAND (1992–1997)
Food group
Vegetable
Fruit
Meat
Total diversity
Diversity1
OR
(95% CI)2
OR adjusted for
number of
servings (95% CI)3
,34
3–5
.5
x21 (trend)
,34
3–4
.4
x21 (trend)
,34
3–5
.5
x21 (trend)
,164
16–19
.19
x21 (trend)
1
0.38 (0.22–0.64)
0.22 (0.11–0.43)
22.306
1
0.53 (0.30–0.95)
0.25 (0.12–0.54)
14.726
1
1.14 (0.65–1.99)
1.94 (1.08–3.50)
4.665
1
0.52 (0.30–0.91)
0.31 (0.16–0.60)
12.666
1
0.41 (0.24–0.7)
0.24 (0.12–0.48)
18.546
1
0.58 (0.32–1.04)
0.34 (0.15–0.76)
8.486
1
1.14 (0.64–2.01)
1.82 (0.91–3.34)
3.51
1
0.54 (0.30–0.96)
0.35 (0.17–0.70)
9.376
1Number of items consumed at least weekly.–2Estimates from
multiple logistic regression equations including terms for age, sex,
education, smoking, alcohol and total energy (other than alcohol)
intake.–3As in footnote 2, plus total weekly servings.–4Reference
category.–5p , 0.05.–6p , 0.01.
Vecchia et al., 1997a) since oral carcinogenesis seems to be
favoured by a generally poorer diet (Franceschi et al., 1990). It is
also possible, however, that pre-cancerous lesions of the oral cavity
induce modifications in dietary practices (e.g., decreased citrus and
fruit consumption), which will therefore be the consequence, rather
than the cause, of the disease.
In this study, the most favourable diet appears, however, to be a
combination of frequent fruit and vegetable intake and infrequent
intake of certain types of meat. A large, multicentric, U.S. study
also found some direct association between meat, saturated fats and
cholesterol intake and oral cancer risk, and in another study from
northern Italy (La Vecchia et al., 1991), an association was found
with retinol, an indicator of meat intake. In this study, direct
relationships were observed with eggs, pork and sausages, which
again may reflect an unfavourable effect of animal fats and
cholesterol (Franceschi et al., 1991; Marshall and Boyle, 1996) and
possibly of carcinogens in broiled meat (de Meester and Gerber,
1995) but also may be a general indicator of a poorer diet. As in
previous studies (Marshall et al., 1992; Marshall and Boyle, 1996),
little indication emerged for an association between bread and
cereals and oral cancer.
Our study was hospital-based and is, therefore, open to some of
the related criticisms (Breslow and Day, 1980). However, the link
of its case series with a cancer registration system (Levi et al.,
1997), the satisfactory participation of cases and controls and the
inclusion of only acute conditions unrelated to alcohol, tobacco and
long-term diet modification in the comparison group are reassuring
against selection bias. With reference to information bias and
confounding, we administered in the same structured way a
validated FFQ, allowing for a measure of total energy intake
(Willett and Stampfer, 1986) besides alcohol, tobacco and sociodemographic correlates of oral cancer. Most multivariate ORs,
however, were not materially different from age-adjusted ones,
suggesting that even more detailed allowance for covariates is
unlikely to explain the associations observed. The results obtained
for alcohol drinking and tobacco smoking, moreover, were consistent with available knowledge on the issue (Blot et al., 1988;
Franceschi et al., 1990; La Vecchia et al., 1997b).
Since cases were representative of all incident cases in this
population, we were able to derive population attributable risks
(Bruzzi et al., 1985). Tobacco accounted for 69% of oral and
pharyngeal cancers in this population (95% CI 51–88%) and
alcohol for 72% (95% CI 62–82%). Although these 2 factors
accounted for the largest proportion of cases, the population
attributable risks for dietary factors were far from negligible, being
49% (95% CI 27–71%) for high meat or pork intake, 65% (95% CI
46–84%) for low vegetable consumption and 54% (95% CI
33–76%) for low fruit consumption. There is, therefore, ample
scope for prevention of oral and pharyngeal cancer (Negri et al.,
1993), a neoplasm whose prognosis has shown little sign of
improvement over the last few years (Franceschi et al., 1992).
ACKNOWLEDGEMENTS
The contributions of Mrs. G. Bidois, Dr. E. Brossard (of the Vaud
Cancer Registry’s staff) and Dr. E. Negri with computing assistance
are gratefully acknowledged.
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