Dietary patterns and risk of cervical cancer: a case-control study in Uruguay

doi:10.4236/ojog.2011.12006

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Open Journal of Obstetrics and Gynecology, 2011, 1, 25-30

doi:10.4236/ojog.2011.12006 Published Online June 2011 (http://www.SciRP.org/journal/ojog/

OJOG

Published Online June 2011 in SciRes. http://www.scirp.org/journal/OJOG

Dietary patterns and risk of cervical cancer: a case-control

study in Uruguay

Eduardo De Stefani1, Gisele Acosta1, Hugo Deneo-Pellegrini1, Alvaro L. Ronco2, María Mendilaharsu1,

Gabriel Landó1, María E. Luaces1, Cecilia Silva1

1Epidemiology Group, Department of Pathology, School of Medicine, Montevideo, Uruguay;

2Department of Epidemiology and Statistics, University of Maldonado, Maldonado, Uruguay.

Email: [email protected]

Received 5 May 2011; revised 30 May 2011; accepted 10 June 2011.

ABSTRACT

In the time period 1996-2004, a case-control study on

diet and cervical cancer was conducted at the Na-

tional Cancer Institute in Uruguay. The study in-

cluded 268 cases and 536 controls with non-neoplas-

tic diseases. The foods and beverages in the food-

frequency questionnaire were included in a factor

analytic model. This method retained three factors

which were labeled as the drinker, red meat, and pru-

dent patterns. The model explained 60% of the vari-

ance. Whereas the red me at and drinker patterns were

directly associated with the risk of cervical cancer

(OR for red meat pattern 1.79, 95% CI 1.12-2.86), on

the other hand, the prudent pattern was inversely

associated with cervical cancer (OR 0.60, 95% CI

0.38-0.93). To our knowledge, this study was the first

one using factor analysis in order to elucidate the role

of the d i et in relation with cervical cancer.

Keywords: Dietary Patterns; Cervical Cancer

1. INTRODUCTION

Cervical cancer is the third cancer site in frequency in

Uruguay, following breast cancer and colorectal cancer.

This malignancy shows an age-standardized incidence

rate of 17.5 per 100,000 Uruguayan women [1]. A pre-

vious study conducted in Uruguay showed that cancer of

the uterine cervix presented a steady decline in mortality

from the early fifties until the late eighties [2]. More

precisely, in the time period 1953-1957, this decline

reached mortality rates of 4.4 per 100,000 women,

which implies a relative risk of 0.56.

The main risk factors for cervical cancer are related to

the infection caused by human papilloma virus (HPV)

and related sexual activities. Smoking and other envi-

ronmental risks have been studied in detail [3,4] and

tobacco smoke has been considered a potential carcino-

gen in cervical cancer.

The role of the diet has been examined in a rather

small number of studies and the consistency of the find-

ings is limited [3,5]. In a monograph by the World Can-

cer Research Fund [5] carrots have been suggested as a

possible protective vegetable, but aside from this finding,

little else is known about the role that diet plays in cer-

vical cancer.

Since traditional approaches to research into cervical

cancer have been considered limited due to the high col-

linearity of individual foods or nutrients, we decided to

use factor analysis in this study, in the view that it could

offer a new approach in the etiology of cervical carci-

noma. This analytical method consists of reducing a

large number of foods to a smaller number of factors [6],

and has been employed to date in the study of numerous

cancer sites [6-10]. We considered that this approach

could offer new information regarding the role of diet in

the etiology of cervical carcinoma.

2. SUBJECTS AND METHODS

2.1. Selection of Cases

In the time period 1990-2000 all newly diagnosed and

microscopically confirmed patients with carcinoma of

the cervix were considered eligible for the study. A total

of 274 patients were approached and only 5 refused the

interview, leaving a final total of 268 patients (response

rate 97.8%). Two hundred and sixty (260) patients pre-

sented squamous cell carcinoma of the cervix (97.3%)

and 8 patients showed undifferentiated carcinoma

(2.7%). All the cases were diagnosed by biopsy and were

admitted to the National Institute of Cancer, Uruguay.

2.2. Selection of Controls

In the same time period and in the same Institute, all

female patients with non neoplastic diseases which were

E. D. Stefani et al. / Open Journal of Obstetrics and Gynecology 1 (2011) 25-30

not related to tobacco smoking or alcohol drinking and

without recent changes in their diets were considered

eligible for the study. A total of 2,136 patients were

asked for voluntary participation in the study, and 2074

accepted the interview. Only 62 women refused the in-

terview (response rate 97.1%).

From this pool of controls, 536 patients were included

in the study. These controls were randomly selected fol-

lowing a control/case ratio of 2:1 and were frequency

matched to cases on age and residence. These patients

presented the following conditions: sebaceous cyst (140,

26.1%), seborrheic keratosis (130, 24.2%), breast ab-

scess (109, 20.3%), osteomielitis (55, 10.3%), lipoma

(41, 7.6%), injuries (26, 4.9%), varicose veins (16,

3.0%), diseases of the genital tract (11, 2.1%), and hy-

datid cyst (8, 1.5%). All the cases and controls were of

Hispanic White ancestry.

2.3. Inteviews and Questionnaire

All the participants (cases and controls) were inter-

viewed after admission to the Institute by two trained

social workers. Proxy interviews were not accepted. The

patients were administered a structured questionnaire

which included the following sections: sociodemo-

graphics (age, residence, education, income), a complete

occupational history based on the last four jobs, self re-

ported height and weight 5 years prior to the interview, a

complete history of cancer among first-degree relatives,

a complete history of smoking (age at start, age at quit,

number of cigarettes smoked per day, type of tobacco,

type of cigarette), a complete history of alcohol drinking

(age at start, age at quit, number of glasses per day or

week, type of alcoholic beverage), a complete history of

mate consumption (age at start, age at quit, number of

litres of the beverage, mate temperature), menstrual and

reproductive events (age at menarche, age at menopause,

number of livebirths, abortion, age at first pregnancy,

age at last pregnancy, breastfeeding, age at first inter-

course, number of sexual partners), and a food-fre-

quency questionnaire (FFQ) focused on meat consump-

tion, dairy foods, total vegetables and total fruits.

2.4. Statistical Analysis

The food groups were categorized using a Likert-type

scale and were introduced in a factor analysis among

controls. The factor analysis retained three factors [6,11]

after running the scree plot. The factorability was meas-

ured through Cronbach alpha and sampling adequacy

was tested through the Kaiser-Meyer-Olkin statistic. The

factors were then rotated using the orthogonal varimax

method and normalized by the Kaiser procedure. The

factors were scored through the Thompson regression

method [12] and the scores were applied to cases and

controls. The scored patterns were correlated by selected

variables using Spearman rank correlations.

The relative risks of cervical carcinoma was approxi-

mated by the odds ratios, using unconditional multiple

logistic regression [13]. In short, we fitted a model

which included as independent variables the following

terms: age (continuous), residence (categorical), ur-

ban/rural status (categorical), education (categorical),

smoking index (categorical), number of partners (cate-

gorical), age at first intercourse (categorical), total en-

ergy intake (continuous), and all three scored dietary

patterns. The reason for including all four score patterns

is the fact that dietary patterns are conditional on one

another. All the calculations were performed using

STATA [14].

3. RESULTS

The distribution of cases and controls by sociodemo-

graphics and tobacco variables is shown in Ta b l e 1 . As

expected from the matched design, age and residence

were similar among cases and controls. Also, education

and income were similar for both groups of participants.

On the contrary, current smokers showed an odds ratio

of 1.7 (95% CI 1.1-2.7) when compared with never

smokers. Also, an early age at first intercourse and a

high number of sexual partners were directly associated

with risk of cervical cancer (OR for high number of

partners 2.7, 95% CI 1.6-4.4).

The factor loadings matrix for controls is shown in

Table 2. Factor 1 presented high loadings for salted meat,

beer, and hard liquor and was labeled as the drinker pat-

tern. The pattern showed a high negative loading for

wine consumption and the pattern explained 31.8 % of

the variance. Factor 2 displayed high loadings for red

meat, and barbecued meat and high negative loading for

whole milk and was labeled as the red meat pattern. This

pattern explained 16.2% of the variance. Factor 3

showed high loadings for total vegetables and total fruits

and was called the prudent pattern, explaining 12.0% of

the variance. The total variance was 60%, a high value

indeed.

Spearman rank correlations between dietary patterns

and the selected variables are shown in Table 3. The

drinker pattern was inversely associated with age and

directly associated with smoking intensity, years smoked,

and number of sexual partners. The red mea t pattern was

inversely associated with age, and directly associated

with parity, and early age at first intercourse. Finally, the

prudent pattern was highly correlated with education.

Patient characteristics among factor quartiles for con-

trols are shown in Table 4. The drinker pattern displayed

a positive gradient for smoking intensity and number of

sexual partners and an inverse gradient for red meat in-

E. D. Stefani et al. / Open Journal of Obstetrics and Gynecology 1 (2011) 25-30

OJOG

take. The red meat pattern was negatively associated

with years of education and a clear increased gradient

for means of meat intake. Finally, the prudent pattern

displayed a positive gradient for education, raw vegeta-

bles consumption and an inverse association with red

meat intake.

Table 1. Distribution of cases and controls for sociodemographics, tobacco use, and sexual events.

Cases Controls

Variable Category No % N

o % Global p-value

Age (years) 20 - 29 10 3.7 20 3.7

30 - 39 55 20.5 110 20.5

40 - 49 74 27.6 148 27.6

50 - 59 56 20.9 112 20.9

60 - 69 51 19.0 102 19.0

70 - 79 16 6.0 32 6.0

80 - 89 6 2.2 12 2.2 1.00

Residence Montevideo 138 51.5 276 51.5

Other counties 130 48.5 260 48.5 1.00

Percentage of rural patients Urban 246 91.8 491 91.6

Rural 22 8.2 45 8.4 0.93

Education (yrs) 0 - 3 60 22.4 125 23.3

4 - 6 138 31.5 264 49.3

7 + 70 26.1 147 27.4 0.84

Income (U$D) < = 67 76 28.4 162 30.2

68 + 101 37.7 200 37.3

Unknown 91 33.9 174 32.5 0.85

Smoking Never smokers 151 56.3 324 62.3

Former 25 9.3 66 12.3

Current 1 - 14 43 16.1 70 13.1

Current 15 + 49 18.3 66 12.3 0.04

Age at first intercourse 30 + 4 1.5 41 7.6

20 - 29 62 22.1 215 40.1

15 - 19 179 66.8 261 48.7

< = 14 23 8.6 19 3.5 <0.0001

No partners 0 - 1 102 38.1 281 53.5

2 88 32.8 152 28.4

3 37 13.8 54 10.1

4 + 41 15.3 43 8.0 <0.0001

No patients 268 100.0 536 100.0

Table 2. Factor loadings matrix among controls1.

Drinker Red meat Prudent

Food groups Factor 1 Factor 2 Factor 3

Red meat 0.02 0.52 −0.36

Salted meat 0.50 0.03 −0.02

Barbecued meat −0.00 0.41 −0.03

Processed meat −0.03 0.31 0.11

Whole milk −0.02 −0.57 −0.39

Total vegetables −0.02 0.04 0.61

Total fruits 0.04 −0.08 0.56

Beer 0.51 0.02 0.02

Wine −0.46 0.08 −0.00

Hard liquor 0.52 0.01 0.00

Mate −0.02 0.34 −0.11

Variance (%) 31.8 16.2 12.0

Cumulative variance 31.8 48.0 60.0

1Loadings higher than 0.39 are typed in bold.

E. D. Stefani et al. / Open Journal of Obstetrics and Gynecology 1 (2011) 25-30

Table 3. Spearman rank correlations between dietary patterns and selected variables.

Dietary patterns

Variables Drinker Red meat Prudent

Age −0.13 −0.19 0.03

Education 0.09 −0.05 0.22

Smoking intensity 0.21 0.09 −0.00

Smoking duration 0.20 0.08 0.00

No of livebirths 0.02 0.18 −0.07

Age of intercourse 0.04 0.14 −0.01

No of partners 0.11 −0.04 0.04

Table 4. Participant characteristics for controls by factor quartile.

Variable Category Drinker Red meat Prudent

Age (years) 1 52.4 54.0 49.4

2 51.8 49.9 50.5

3 50.3 50.6 52.1

4 47.4 47.1 49.8

Education 1 6.3 7.4 6.3

(years) 2 7.0 7.1 6.2

3 6.7 6.6 7.3

4 7.7 6.5 7.9

Smoking 1 3.9 4.8 5.6

(cigarettes/day) 2 5.1 5.5 4.8

3 6.1 4.3 5.8

4 6.4 6.9 5.4

Meat 1 7.8 2.5 7.7

(servings/week) 2 5.3 4.2 6.1

3 5.1 6.4 5.1

4 3.8 8.9 3.0

Vegetables 1 3.9 2.8 1.3

(servings/week) 2 3.4 3.2 2.5

3 2.9 3.4 3.6

4 2.0 2.8 4.9

Age of first intercourse 1 19.5 19.5 20.3

2 20.0 19.1 19.5

3 18.9 20.4 18.8

4 19.2 19.7 19.1

No partners 1 1.7 1.9 1.6

2 1.8 2.3 2.1

3 1.8 2.6 1.8

4 2.1 2.9 1.8

1 Numbers in each cell corresponds to mean values of the variable.

Odds ratios of cervical cancer for dietary patterns are

shown in Table 5. Cancer of the cervix was positively

associated with red meat and drinker patterns (OR for

highest category versus the lowest one for red meat pat-

tern 1.79, 95% CI 1.12-2.86, p-value for linear trend =

0.02). On the other hand, cervical cancer was inversely

associated with the prudent pattern (OR 0.60, 95% CI

0.38-0.93).

E. D. Stefani et al. / Open Journal of Obstetrics and Gynecology 1 (2011) 25-30 29

Table 5. Odds ratios of carcinoma of the cervix for dietary patterns1.

Dietary pattern Category Cases/Controls OR 95 % CI

Drinker Low 60/134 1.0 reference

2 54/134 1.07 0.66 - 1.71

3 68/134 1.23 0.78 - 1.94

High 86/134 1.49 0.95 - 2.31

p-value for trend 0.053

Continuous 1.08 0.99 - 1.18

Red meat Low 47/134 1.0 reference

2 65/134 1.31 0.81 - 2.12

3 61/134 1.30 0.81 - 2.10

High 95/134 1.79 1.12 - 2.86

p-value for trend 0.02

Continuous 1.13 1.00 - 1.28

Prudent Low 87/134 1.0 reference

2 71/134 0.87 0.57 - 1.33

3 57/134 0.67 0.43 - 1.04

High 53/134 0.60 0.38 - 0.93

p-value for trend 0.01

Continuous 0.83 0.73 - 0.95

1Adjusted for age, residence, education, income, age at first intercourse, number of partners, smoking, total energy intake and all scores for dietary patterns.

4. DISCUSSION

To our knowledge, the present study is the first one on

factor analysis and risk of cervical cancer. The principal

components approach has some limitations related to the

FFQ and the management of the data. The inclusion of

foods and beverages should be validated previously to

the factor analysis being run. In fact, principal compo-

nents analysis should be conducted in order to obtain the

simple structure following Thurstone’s criteria [15,16].

In our model, this simple structure was obtained through

the rotated principal components analysis.

In our study, an early age at first intercourse, a high

number of sexual partners, and a high number of live-

births were directly associated with cervical cancer risk,

replicating previous reports [3,17-19]. It has been sug-

gested that the male factor could be related to the etiol-

ogy of cervical cancer through venereal diseases, which

could foster the infection of their spouses with HPV

[17-21]. The drinker pattern displayed a clear gradient

associated with the number of partners, and so did the

red me at pattern.

In the present study, cigarette smoking did not signify

an important risk in cancer of the cervix. It should be

noted that in general, the intensity of smoking and the

duration of this habit are not particularly high among

women of low socioeconomic status in Uruguay [22].

Furthermore, when cigarette smoking was controlled by

the above sexual and reproductive variables, the risk was

close to null. Nevertheless, smoking intensity displayed

a positive gradient for the drinker pattern. It is worth

noting that Gunnell et al. [23] also found a synergy be-

tween HPV infection and smoking duration.

The role of red meat was positively associated with

cervical cancer in our study. This could be explained by

the presence of heterocyclic amines in red meat, which

are powerful carcinogens in animals [24]. Moreover, red

meat is an important source of fat and cholesterol and it

has been suggested that whereas heterocyclic amines act

as initiators, fat plays a role of promoter [25]. Further

studies on the role of red meat in cervical cancer are

warranted.

Finally the effect of total vegetables and total fruits

was particularly protective in the etiology of cervical

cancer [26]. This applies mainly to the strata of women

with a high number of sexual partners. In fact, vegeta-

bles and fruits were the main components of the prudent

pattern.

Like other case-control studies, this study has its limi-

tations and strengths. The major limitations are selec-

tions bias, recall bias, and the possibility of error due to

multiple comparisons (that is, chance findings). Perhaps,

the lack of information about HPV status is a major li-

mitation. Therefore, in the place of HPV we attempted to

use the age at first intercourse and number of partners as

proxy indicators of this infection. Another limitation is

the rather small amount of foods used as a routine in the

E. D. Stefani et al. / Open Journal of Obstetrics and Gynecology 1 (2011) 25-30

FFQ administered by the Cancer Institute. Among the

strengths, in the first place, is the power of the study,

measured by the sampling adequacy, which allowed the

estimation of small ORs as significant. Secondly, all the

cases were validated by expert pathologists, and finally,

the high response rate among cases and controls suggests

that participants were drawn from the same population

base.

In summary, we conducted a factor analysis on the re-

lationship between foods and beverages and risk of cer-

vical cancer. Whereas the red meat pattern was directly

associated with this malignancy, the prudent pattern was

inversely associated with cancer of the cervix. In short,

the main novelty of this study is the use of factor analy-

sis in cervical cancer to evaluate the role of diet in this

malignancy.

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