# Weight History, Smoking, Physical Activity  and Breast Cancer Risk among French-Canadian Women Non-Carriers of More FrequentBRCA1/2 Mutations

Authors: Vishnee Bissonauth; Bryna Shatenstein; Eve Fafard; Christine Maugard; André Robidoux; Steven Narod; Parviz Ghadirian
Journal: Journal of Cancer Epidemiology
 (2009)

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## Abstract

Several lifestyle factors play a significant role in determining an individual's risk of breast cancer. Many of them could be modified to protect against the malignancy. A nested case-control study was conducted to examine the association between selected lifestyle factors and non-BRCA-related breast cancer risk among French-Canadian women. Some 280 women with breast cancer and who were nongene carriers of mutated BRCA gene were recruited as cases. Another 280 women, without any cancer and nongene carriers of mutated BRCA gene served as controls. A tested lifestyle questionnaire was interviewer administered to incident cases to obtain information on weight history, smoking, physical activity, and other lifestyle risk factors. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated in logistic regression models.
Comparing cases to controls, breast cancer risk was higher among subjects who reached their maximum body mass index (BMI) at an older age (>50 years) (OR=2.83; 95% CI: 2.34–2.91). A positive association was noted between breast cancer risk and weight gain of >34 lbs compared to weight gain of ≤15 lbs, since the age of 20 (OR=1.68; 95% CI: 1.10–2.58). Weight gain of >24 lbs compared to weight gain of ≤9 lbs, since the age of 30 also resulted in the same relationship (OR=1.96; 95% CI: 1.46–3.06). Similarly, since the age of 40, weight gain of >12 lbs compared to weight gain of ≤1 lb was associated with increased breast cancer risk (OR=1.91; 95% CI: 1.53–2.66). Women who smoked >9 pack-years of cigarettes had a 59% higher breast cancer risk (P=.05). Subjects who engaged in >24.8 metabolic-equivalent- (MET-) hours per week compared to ≤10.7 MET-hours per week of moderate physical activity had a 52% (P=.01) decreased risk and total physical activity between 16.2 and 33.2 MET-hours per week compared to ≤16.2 MET-hours per week, resulted in a 43% (P=.05) lower risk of breast cancer. In conclusion, weight history did affect breast cancer risk. Moreover, smoking appeared to raise the risk, whereas moderate physical activity had a protective effect.


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## Body

## 1. Introduction

Breast cancer was the second main cause of all
causes of death among Canadian women in 2007 [1–3]. It is now known  that germline mutations in
the BRCA breast cancer susceptibility
gene increase susceptibility to breast and ovarian cancers, with an average
cumulative risk for breast  cancers by the age of 70 of 65% in BRCA1-mutation carriers and of 39% in BRCA2 mutation carriers [4]. Several lifestyle factors  may play a
significant role in determining an individual’s risk of breast cancer and could
be modified to protect against development of malignancy. For example, obesity,
a serious public health problem that is reaching epidemic proportions in many
countries, significantly contributes to the development of certain cancers, including breast cancers [5]. Although anthropometric characteristics have been evaluated as possible
determinants of breast cancer risk [6, 7], studies on the association of
obesity with breast cancer risk in Western women have led to contradictory
results. In addition, among commonly-studied lifestyle
factors, physical activity has been the focus of numerous investigations. A 3%
decrease in breast cancer risk has been observed for each 1-hour increase per
week in recreational physical activity during adolescence, [8]. Indeed, a recent study has concluded that there is an increased risk for
development of breast cancer in the presence of obesity and low levels of
physical activity [9].  Likewise, smoking plays a highly
significant role in cardiovascular and respiratory disease as well as in lung
cancer and could affect breast cancer risk. However, the evidence is
contradictory [5], and a collaborative reanalysis of the evidence from 53 epidemiological
studies worldwide found that smoking had little or no independent
effect on the risk of women developing breast cancer [10]. Most studies to date have addressed the
relationship between lifestyle factors and breast cancer risk among sporadic
cases or gene mutation carriers. To our knowledge, this is the first study
which has addressed the issue in a specific population such as French
Canadians, a group with a shared, specific genetic background and relatively
more common BRCA mutations. Because it is currently not known whether lifestyle
influences breast cancer risk in BRCA nongene
carriers, we undertook the present study to examine associations between
selected lifestyle factors and breast cancer risk among French-Canadian women
who were noncarriers of the 6 more frequent founder mutations of BRCA1/2.


## 2. Materials and Methods

### 2.1. Study Population

The study subjects were identified from
participants in an ongoing genetic breast cancer study, which began
recruitment in 2004. Breast cancer patients who attended the Breast Center
of Centre Hospitalier de l’Université de
Montréal (CHUM) Hotel-Dieu were invited to participate during a follow-up
appointment. They were French-Canadian women (those who were born in the province of Québec
and having a maternal or paternal origin from the descendants of French origins
who had settled in Canada) with early-onset breast cancer. Early onset of breast
cancer is as breast cancer occurring at a younger age, without metastasis and
considered to be
disease with a large inherited component, that is, stemming from a mutation
passed on from parent to child. In this study, cases
who were ≤50 years old at diagnosis, with
non-BRCA related invasive breast cancer, were eligible for the study, while those
with in situ breast cancer had to have a positive family history of breast
cancer or ovarian cancer to be eligible for this study. Cases >50 years old
with invasive or in situ breast cancer had to have a positive family history of
breast or ovarian cancer to be eligible for this study.The diagnosis of breast cancer was confirmed by review
of pathology reports and medical records by physicians and geneticists at the
Chair of Breast Cancer of the Research
Center of University of Montreal
(RC-CHUM).For the current study, cases and controls were tested
for founder mutations. These women also provided written consent forBRCA gene testing, designed to detect
the presence of 6 specific mutations found more frequently in families of
French-Canadian descent [11]. A DNA-based test was conducted to
identify any of 6 founder mutations in BRCA1 or BRCA2. These 6 mutations (BRCA1 3875delGTCT, BRCA1 2953delGTAinsC,
BRCA1 C4446T, BRCA2 8765delAG, BRCA2 3398delAAAAG, BRCA2 6085G>T) account for approximately 85% of all BRCA mutations in the French-Canadian population. If they were not carriers of these mutations, they became eligible cases
for this study.Eligible
cases were identified and interviewed, in order to construct a computerized
pedigree and obtain information regarding sociodemographic characteristics and
breast cancer risk factors. The inclusion criteria for cases stipulated that
subjects must be French-Canadian women of all ages, recruited by the research
team of the Epidemiology Research Unit of RC-CHUM from 2004–2006, noncarriers of any of
the 6 founder mutations mentioned
above, and having primary breast cancer without metastasis. The exclusion
criteria for cases were non-French-Canadian women, being too ill to answer the
questionnaires and affected by cancers other than breast cancer.Some 285 noncarriers of these mutations with
breast cancer (all ages) were selected sequentially until the target sample was
achieved, from the mentioned above cohort of 513 French-Canadian women
diagnosed from 2004 to 2006. Of these women, 2 cases (0.7%) refused to
participate after being contacted, and 3 subjects (1%) changed their address
and were unreachable at the time of data collection. Therefore 280 eligible
cases (98%) were interviewed.Control
subjects were women from families with breast cancer (n=265), except for 15,
(5.4%) who came from the same families as cases. Of these: 8 had a sister-sister
relationship; 4 had an aunt-niece relationship; 2 had a mother-daughter
relationship; 1 had a grandmother-granddaughter relationship (see Table 5).The inclusion criteria for controls were as follows:
French-Canadian women of all ages, recruited at RC-CHUM, subjects not carrying
any of the 6 founder mutations
mentioned above and free from cancer. The exclusion criteria for controls were non-French-Canadian women, being too ill to answer the questionnaires and affected
by cancer.They were matched for age group (by 10-year age
intervals) to cases. A total of 300 eligible controls were identified, of whom
13 (4%) were unreachable, and 7 (2%) refused to participate after the study was
explained to them. In all, 280 eligible control subjects (93%) were
interviewed.


### 2.2. Assessment of Lifestyle Factors

To assess weight history, participants were asked
about their current weight and their weight when they were 20, 30, and 40 years
old. They were also asked to give their highest weight (excluding pregnancies)
as well as their age at their highest weight.To
evaluate participation in sports activities or physical exercise 2 years prior
to diagnosis (cases) or interview (controls), the study subjects were asked in
which seasons, how often, and the average duration per session they engaged in
each of the 12 most common types of leisure-time physical activities in Canada. This
section of the questionnaire was developed and used over more than 10 years of
studies on cancer epidemiology by the Epidemiology Research Unit,
CHUM-Hôtel-Dieu. Physical activities included walking, jogging or running,
gardening or yard work, housework, golf, tennis, bowling or curling, swimming
or water exercise, skiing or skating, bicycling, social dancing and other
strenuous exercise. They indicated their usual frequency of participation in
each of the above-mentioned activities by choosing 1 of the following
categories: never, less than once per month, 1–3 times per month, 1-2 times per
week, 3–6 times per week or every day. The average time per episode for each of
the 12 activities included less than 15, 15–30, 31–60 minutes, and more than 60
minutes. Intensity was categorized as moderate or vigorous, and classification
was based on the amount of energy or effort a participant expended in
performing the activity [12]. Overall, physical activity exposure was quantified in
terms of metabolic equivalents (MET), representing the number of kilocalories
per hour each kilogram of body weight expended in activities [12].
MET-hours per week for each activity were computed by multiplying the MET score
by activity duration. Moderate physical activity was defined as MET score of 4,
and for vigorous physical activity, it was defined as 7 [12]. Finally, total physical
activity for each participant, as measured by weekly MET-hours, was quantified
by summing overall intensity activities.To
assess smoking habits, the subjects were asked if they ever smoked, and if they
were currently smoking, their age at smoking initiation, age at smoking cessation,
and average cigarettes consumption per day. A pack-year index was computed by
multiplying the total number of years smoked by average consumption (in packs
per day) over the smoking period.Menopausal status was classified as
either premenopause, natural postmenopause, surgical post menopause, or
unknown, based on self-report of menstrual history. Age at menopause was the
age at last natural menstrual cycle followed by one year of amenorrhea. For
stratified analyses, categories of premenopausal and postmenopausal that
included both natural and surgical menopausal groups were used. Women with
unknown menopausal status were excluded from the stratified analyses.For other lifestyle factors, the study subjects
completed an in person interviewer-administered core questionnaire that
included information regarding age, place of residence, education, height,
weight and history of weight change, reproductive history, parity,
breastfeeding, age at menarche, oral contraception, hormone replacement
therapy, marital status, tamoxifen use and alcohol consumption. They also
completed an interviewer-administered 164-items semiquantitative food
frequency questionnaire (FFQ) over the telephone, on the possible role of diet
in breast cancer risk, which permitted the quantification of alcohol
consumption in the etiology of breast cancer. The FFQ was developed by the
National Cancer Institute of Canada.


### 2.3. Statistical Analysis

Descriptive statistics were compiled to
characterize the study population and to examine case-control differences.
Demographic features and potential risk factors between cases and controls were
compared byt-test for continuous
variables and by the chi-square (χ2)
test for categorical variables.Conditional logistic regression analysis was
used to compute the odds ratios (ORs) and associated 95% confidence intervals
(95% CIs) of breast cancer for the variables of interest. Because of the
limited sample size, only those variables that were confounders in this dataset
and for which there was a strong biological rationale were considered. Two sets
of analyses were performed. In the first model, univariate modeling was applied
to identify potential confounding variables. AP-value less than .05 was
considered to be statistically significant [13]. In the second model, multivariate analysis was applied to control for
confounding factors, and these results are presented below. Variables
considered as confounders were age, education, physical activity, smoking,
alcohol consumption, and total energy intake. Lifestyle variables were
classified according to tertile distribution, with the lowest tertile being the
reference category. The control group was used to create tertile cut points.
Tests for linear trend were undertaken, and dose-response trends in risk calculation
were evaluated for all analyses by fitting the continuous variable into the
model with Wald values [14]. Tests for linear trend were performed by replacing the indicator
lifestyle variable in each multivariate model with a single variable representing
the median value of the indicator variable for a given category and by using
the Wald X2 value calculated for the regression coefficient of this
variable to test the null hypothesis of no linear trend component in non-BRCA
related breast cancer risk across tertiles. All tests were 2-sided.Models were run separately for both pre- and
postmenopausal women and were adjusted for age. Women were considered as
postmenopausal if they reported having no menstrual periods at least 1 year
before data collection.


## 2.1. Study Population

The study subjects were identified from
participants in an ongoing genetic breast cancer study, which began
recruitment in 2004. Breast cancer patients who attended the Breast Center
of Centre Hospitalier de l’Université de
Montréal (CHUM) Hotel-Dieu were invited to participate during a follow-up
appointment. They were French-Canadian women (those who were born in the province of Québec
and having a maternal or paternal origin from the descendants of French origins
who had settled in Canada) with early-onset breast cancer. Early onset of breast
cancer is as breast cancer occurring at a younger age, without metastasis and
considered to be
disease with a large inherited component, that is, stemming from a mutation
passed on from parent to child. In this study, cases
who were ≤50 years old at diagnosis, with
non-BRCA related invasive breast cancer, were eligible for the study, while those
with in situ breast cancer had to have a positive family history of breast
cancer or ovarian cancer to be eligible for this study. Cases >50 years old
with invasive or in situ breast cancer had to have a positive family history of
breast or ovarian cancer to be eligible for this study.The diagnosis of breast cancer was confirmed by review
of pathology reports and medical records by physicians and geneticists at the
Chair of Breast Cancer of the Research
Center of University of Montreal
(RC-CHUM).For the current study, cases and controls were tested
for founder mutations. These women also provided written consent forBRCA gene testing, designed to detect
the presence of 6 specific mutations found more frequently in families of
French-Canadian descent [11]. A DNA-based test was conducted to
identify any of 6 founder mutations in BRCA1 or BRCA2. These 6 mutations (BRCA1 3875delGTCT, BRCA1 2953delGTAinsC,
BRCA1 C4446T, BRCA2 8765delAG, BRCA2 3398delAAAAG, BRCA2 6085G>T) account for approximately 85% of all BRCA mutations in the French-Canadian population. If they were not carriers of these mutations, they became eligible cases
for this study.Eligible
cases were identified and interviewed, in order to construct a computerized
pedigree and obtain information regarding sociodemographic characteristics and
breast cancer risk factors. The inclusion criteria for cases stipulated that
subjects must be French-Canadian women of all ages, recruited by the research
team of the Epidemiology Research Unit of RC-CHUM from 2004–2006, noncarriers of any of
the 6 founder mutations mentioned
above, and having primary breast cancer without metastasis. The exclusion
criteria for cases were non-French-Canadian women, being too ill to answer the
questionnaires and affected by cancers other than breast cancer.Some 285 noncarriers of these mutations with
breast cancer (all ages) were selected sequentially until the target sample was
achieved, from the mentioned above cohort of 513 French-Canadian women
diagnosed from 2004 to 2006. Of these women, 2 cases (0.7%) refused to
participate after being contacted, and 3 subjects (1%) changed their address
and were unreachable at the time of data collection. Therefore 280 eligible
cases (98%) were interviewed.Control
subjects were women from families with breast cancer (n=265), except for 15,
(5.4%) who came from the same families as cases. Of these: 8 had a sister-sister
relationship; 4 had an aunt-niece relationship; 2 had a mother-daughter
relationship; 1 had a grandmother-granddaughter relationship (see Table 5).The inclusion criteria for controls were as follows:
French-Canadian women of all ages, recruited at RC-CHUM, subjects not carrying
any of the 6 founder mutations
mentioned above and free from cancer. The exclusion criteria for controls were non-French-Canadian women, being too ill to answer the questionnaires and affected
by cancer.They were matched for age group (by 10-year age
intervals) to cases. A total of 300 eligible controls were identified, of whom
13 (4%) were unreachable, and 7 (2%) refused to participate after the study was
explained to them. In all, 280 eligible control subjects (93%) were
interviewed.


## 2.2. Assessment of Lifestyle Factors

To assess weight history, participants were asked
about their current weight and their weight when they were 20, 30, and 40 years
old. They were also asked to give their highest weight (excluding pregnancies)
as well as their age at their highest weight.To
evaluate participation in sports activities or physical exercise 2 years prior
to diagnosis (cases) or interview (controls), the study subjects were asked in
which seasons, how often, and the average duration per session they engaged in
each of the 12 most common types of leisure-time physical activities in Canada. This
section of the questionnaire was developed and used over more than 10 years of
studies on cancer epidemiology by the Epidemiology Research Unit,
CHUM-Hôtel-Dieu. Physical activities included walking, jogging or running,
gardening or yard work, housework, golf, tennis, bowling or curling, swimming
or water exercise, skiing or skating, bicycling, social dancing and other
strenuous exercise. They indicated their usual frequency of participation in
each of the above-mentioned activities by choosing 1 of the following
categories: never, less than once per month, 1–3 times per month, 1-2 times per
week, 3–6 times per week or every day. The average time per episode for each of
the 12 activities included less than 15, 15–30, 31–60 minutes, and more than 60
minutes. Intensity was categorized as moderate or vigorous, and classification
was based on the amount of energy or effort a participant expended in
performing the activity [12]. Overall, physical activity exposure was quantified in
terms of metabolic equivalents (MET), representing the number of kilocalories
per hour each kilogram of body weight expended in activities [12].
MET-hours per week for each activity were computed by multiplying the MET score
by activity duration. Moderate physical activity was defined as MET score of 4,
and for vigorous physical activity, it was defined as 7 [12]. Finally, total physical
activity for each participant, as measured by weekly MET-hours, was quantified
by summing overall intensity activities.To
assess smoking habits, the subjects were asked if they ever smoked, and if they
were currently smoking, their age at smoking initiation, age at smoking cessation,
and average cigarettes consumption per day. A pack-year index was computed by
multiplying the total number of years smoked by average consumption (in packs
per day) over the smoking period.Menopausal status was classified as
either premenopause, natural postmenopause, surgical post menopause, or
unknown, based on self-report of menstrual history. Age at menopause was the
age at last natural menstrual cycle followed by one year of amenorrhea. For
stratified analyses, categories of premenopausal and postmenopausal that
included both natural and surgical menopausal groups were used. Women with
unknown menopausal status were excluded from the stratified analyses.For other lifestyle factors, the study subjects
completed an in person interviewer-administered core questionnaire that
included information regarding age, place of residence, education, height,
weight and history of weight change, reproductive history, parity,
breastfeeding, age at menarche, oral contraception, hormone replacement
therapy, marital status, tamoxifen use and alcohol consumption. They also
completed an interviewer-administered 164-items semiquantitative food
frequency questionnaire (FFQ) over the telephone, on the possible role of diet
in breast cancer risk, which permitted the quantification of alcohol
consumption in the etiology of breast cancer. The FFQ was developed by the
National Cancer Institute of Canada.


## 2.3. Statistical Analysis

Descriptive statistics were compiled to
characterize the study population and to examine case-control differences.
Demographic features and potential risk factors between cases and controls were
compared byt-test for continuous
variables and by the chi-square (χ2)
test for categorical variables.Conditional logistic regression analysis was
used to compute the odds ratios (ORs) and associated 95% confidence intervals
(95% CIs) of breast cancer for the variables of interest. Because of the
limited sample size, only those variables that were confounders in this dataset
and for which there was a strong biological rationale were considered. Two sets
of analyses were performed. In the first model, univariate modeling was applied
to identify potential confounding variables. AP-value less than .05 was
considered to be statistically significant [13]. In the second model, multivariate analysis was applied to control for
confounding factors, and these results are presented below. Variables
considered as confounders were age, education, physical activity, smoking,
alcohol consumption, and total energy intake. Lifestyle variables were
classified according to tertile distribution, with the lowest tertile being the
reference category. The control group was used to create tertile cut points.
Tests for linear trend were undertaken, and dose-response trends in risk calculation
were evaluated for all analyses by fitting the continuous variable into the
model with Wald values [14]. Tests for linear trend were performed by replacing the indicator
lifestyle variable in each multivariate model with a single variable representing
the median value of the indicator variable for a given category and by using
the Wald X2 value calculated for the regression coefficient of this
variable to test the null hypothesis of no linear trend component in non-BRCA
related breast cancer risk across tertiles. All tests were 2-sided.Models were run separately for both pre- and
postmenopausal women and were adjusted for age. Women were considered as
postmenopausal if they reported having no menstrual periods at least 1 year
before data collection.


## 3. Results

### 3.1. Characteristics of Study Subjects

Selected characteristics of cases
and controls are summarized in Table1. Mean (±SD) age of the cases was 51.9±8.2 years and 50.0±9.8 years for the controls (P= .01). Differences in age
distribution were noticeable between cases and controls with a slight excess of
younger control subjects. Cases had significantly higher education levels than
the controls (P= .01). The
nulliparous rate of the cases was significantly higher than that of the
controls (P= .01), and cases also had
fewer children than the controls (P= .01).
There were more postmenopausal women among the cases than the controls (P= .01), perhaps due to the above
mentioned different age distribution among cases and controls. The cases were
significantly more likely to have smoked at any time in their lives than the
controls (P= .03). The controls were
more likely to have reached their maximum lifetime weight at an earlier age (39
years) than the cases (47 years) (P= .01),
while history of weight change indicated that the cases had significantly
higher maximum lifetime weight than the controls (155.8 v/s 149.9) (P= .04). Higher weight gain since
adolescence and adulthood was observed among cases than the controls (P= .01). Controls practiced more moderate
physical activity than the cases (P= .01).
The cases were more likely to have greater total energy intake (P= .01) and alcohol (ethanol) intake (P= .03)  than the controls, whereas no
difference was apparent between study groups in the use of oral contraceptives
and hormone replacement therapy, age at menarche and at menopause, current
weight, weight at the age of 20, 30, and 40, and vigorous and total physical
activity.Table 1
Selected
characteristics of the study population.
VariablesCases
(n=280) (%)Controls
(n=280) (%)Pvalue1Age
(years, mean ± SD)51.9±8.250.0±9.8.01<303431–40172741–50454151–60292361+65Education
attainment (years,
mean ± SD)13.4±3.012.8±3.1.01Marital
statusSingle12.511.1Married/Common-law70.466.4Separated/divorced13.914.6Widowed3.27.9.15ParityNulliparous27.115.4.01≥172.984.6.01Menopausal
statusYes203145No77135.01Oral
contraceptive useEver87.985.0Never12.115.0.40Hormone
replacement therapyYes26.833.6No73.266.4.10SmokingEver63.653.6Never36.446.4.02Smoking10.3±13.47.8±12.8.03(pack-years,
mean ± SD)Age
at menarche(years,
mean ± SD)12.5±1.512.7±1.6.12Age at menopause (years)45.4±6.945.3±7.9.20Age at maximum weight(years)46.6±11.939.4±12.5.01Current weight (lbs)146.6±25.3143.1±25.1.10Weight at the age of 20 (lbs)116.7±16.0119.9±19.7.06Weight at the age of 30 (lbs)129.9±21.0127.4±14.8.18Weight at the age of 40 (lbs)141.8±28.1137.4±29.8.20Maximum lifetime weight (lbs)155.8±26.4149.9±28.5.04Weight gain since the age of 20 (lbs)30.0±22.623.2±21.8.01Weight gain since the age of 30 (lbs)21.3±20.415.0±18.7.01Weight gain since the age of 40 (lbs)12.4±14.96.9±15.2.01Physical activity (MET-hours/week)Moderate (4)18.8±13.521.8±14.8.01Vigorous (7)8.1±12.07.1±11.0.29Total26.9±20.028.9±18.8.22Total energy intake (Kcal)2025.6±674.21782.1±626.3.01All1P  values are
univariate and derived by student’s t-test
for continuous variables with the χ2 test for categorical variables.MET: metabolic equivalent.


### 3.2. Weight History

The risk of breast cancer in relation to weight
history is presented in Tables2 and 4 reporting the results stratified
by menopausal status. After adjusting for age, education, physical activity,
smoking, alcohol consumption, and total energy intake, breast cancer risk was
increased when subjects reached their maximum body mass index (BMI) at an older
age (>50 years) (OR = 2.83; 95% CI: 2.34–2.91). In addition, a positive
association was noted between maximum weight gain of more than 34 lbs compared to weight
gain of ≤15 lbs, since age 20 (OR = 1.68; 95% CI: 1.10–2.58). Weight gain of more
than 24 lbs compared to weight gain of ≤9 lbs since the age of 30 also
showed similar results (OR = 1.96; 95% CI: 1.46–3.06). Likewise, a positive
association with breast cancer risk (OR = 1.91; 95% CI: 1.53–2.66) was observed
for a weight gain after the age of 40 of more than 12 lbs compared to a weight
gain of ≤1 lb. Weight gain of more than 25 lbs from the age of 30 to the age of 40 presented an
increased risk of breast cancer in both pre- (OR = 1.62; 95% CI: 1.42–1.97) and
postmenopausal women (OR = 1.98; 95% CI: 1.11–2.03). Weight gain of more than 25 lbs from the age of 40 to the age of
50 presented an increased risk of breast cancer in postmenopausal women
(OR = 2.01; 95% CI: 1.45–2.91) as well as weight gain of more than 25 lbs from the age of 50 to the age of
60 showed an increased risk of breast cancer in postmenopausal women (OR = 1.79;
95% CI: 1.21–2.33). No association was apparent between breast cancer risk and
current BMI, and BMI at the age of 20, 30, 40, under 49, and over 50 years.
Furthermore, maximum lifetime BMI did not show any significant association with
breast cancer risk (data not reported).Table 2
Odd ratios and 95% confidence intervals for
breast cancer risk associated with weight history.
VariablesQ1Q2Q3P
for trendCurrentBMI*Range (kg/m2)≤21.1>21.1 and ≤25.0>25.0Cases/Controls91/9298/9491/94Univariate OR (95% CI)1.001.34 (0.35–1.41)1.76 (0.91–1.78).08MultivariateORa (95% CI)1.25 (0.76–1.85)1.55 (0.77–1.89).09Age at maximum BMIRange (years)≤39>39 and ≤50>50Cases/Controls58/126108/94114/60Univariate OR (95%
CI)1.002.50 (1.65–3.78)2.65
(2.60–3.41).01MultivariateORa (95% CI)2.77 (1.76–4.85)2.83 (2.34–2.91).01Weight gain since the age of 20Range (lbs)≤15>15 and ≤34>34Cases/Controls80/11593/78107/87Univariate OR (95%
CI)1.001.71 (1.13–2.60)1.67
(1.18–2.64).01MultivariateORa (95% CI)1.76 (1.13–2.72)1.68 (1.10–2.58).01Weight gain since the age of 30Range (lbs)≤9>9 and ≤24>24Cases/Controls68/117106/84106/79Univariate OR (95%
CI)1.002.31 (1.52–3.50)2.17
(1.44–3.28).01MultivariateORa (95% CI)2.25
(1.75–3.49)1.96 (1.46–3.06).01Weight gain since the age of 40Range (lbs)≤1>1 and ≤12>12Cases/Controls55/12080/63103/60Univariate OR (95%
CI)1.001.95 (1.16–2.74)1.99
(1.47–2.49).01MultivariateORa (95% CI)1.82 (1.36–3.10)1.91 (1.53–2.66).01BMI* at interview.Adjusteda for age,
education, physical activity, smoking, alcohol consumption and total energy
intake.


### 3.3. Lifestyle Factors

#### 3.3.1. Smoking

The ORs and 95% CIs for breast cancer risk by
smoking status for all age groups are enumerated in Table3; these results
also appear in Table 4, where they are stratified by menopausal status. After
adjusting for age, education, physical activity, alcohol consumption and total
energy intake, women who smoked more than 9 pack-years had a 59% greater risk
of breast cancer (OR = 1.59; 95% CI: 1.57–2.87) (Table 3). A 63% higher risk of
breast cancer was also noted among premenopausal women (OR = 1.63; 95% CI:
1.23–2.47), with a 49% increased risk among postmenopausal women (OR = 1.49; 95%
CI: 1.33–2.31) (Table 4).Table 3
Odd ratios and 95% confidence intervals for
breast cancer risk associated with lifestyle factors, including smoking and
physical activity.
VariablesQ1Q2Q3P
for trendSmokingRange (pack-years)≤0>0 and ≤9.0>9.0Cases/Controls106/13467/66107/80Univariate OR (95% CI)1.001.28
(0.84–1.96)1.69 (1.15–2.49).03MultivariateORa (95% CI)1.35
(0.86–2.09)1.59 (1.57–2.87).05Moderate physical activityRange (MET-hours/week)≤10.7>10.7 and ≤24.8>24.8Cases/Controls80/10891/95109/77Univariate OR (95% CI)1.000.68
(0.45–1.02)0.52 (0.35–0.79).01MultivariateORb (95% CI)0.67
(0.44–1.03)0.48 (0.31–0.74).01Vigorous
physical activityRange (MET-hours/week)≤0.11>0.11 and ≤7.2>7.2Cases/Controls91/9491/9298/94Univariate OR (95% CI)1.001.02
(0.68–1.54)1.08 (0.72–1.61).93MultivariateORb (95% CI)1.01
(0.66–1.56)1.05 (0.66–1.52).94Total physical activityRange (MET-hours/week)≤16.2> 6.2 and ≤33.2>33.2Cases/Controls87/10089/98104/82Univariate OR (95% CI)1.000.69
(0.46–1.03)0.72 (0.48–1.08).14MultivariateORb (95% CI)0.57 (0.37–0.87)0.66 (0.43–1.01).05Adjusteda for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedb for age,
education, alcohol consumption, smoking, and total energy intake.Table 4
Multivariable adjusted odd ratios and 95%
confidence intervals for breast cancer risk in relation to BMI,
weight gain, smoking, and physical activity, by menopausal status.
VariablePremenopausalPostmenopausalCases/Controls OR (95% CI)Cases/Controls OR (95% CI)Current BMI (kg/m2)*≤22.520/451.0a64/561.0a>22.5 and ≤26.030/471.37 (0.96–2.60)68/501.65
(0.96–2.70)>26.027/431.02 (0.52–2.07)71/391.19
(0.92–2.01)P  for trend.56.35Weight gain (lbs) from the age of 30 to the age of 40≤1327/491.0a65/491.0a>13 and ≤2525/401.55 (0.81–1.86)70/511.95
(0.88–2.17)>2525/461.62 (1.42–1.97)68/451.98 (1.11–2.03)P  for trend.05.03Weight gain (lbs) from the age of 40 to the age of 50≤1366/521.0a>13 and ≤2567/552.01 (0.74–2.80)>2570/382.01 (1.45–2.91)P   for trend.04Weight gain (lbs) from the age of 50 to the age of 60≤1369/501.0a>13 and ≤2571/471.86 (0.62–1.97)>2563/481.79 (1.21–2.33)P for trend.03Smoking (pack-years)≤017/411.0b62/551.0b>0 and ≤931/451.30 (0.76–1.86)70/471.62
(0.90–1.93)>929/491.63 (1.23–2.47)71/431.49 (1.33–2.31)P  for trend.05.04Moderate physical activity (MET-hours/week)≤10.725/401.0c69/451.0c>10.7 and ≤24.832/470.57 (0.26–1.60)60/530.65
(0.96–1.71)>24.820/480.36 (0.22–0.67)74/470.42 (0.12–0.59)P for trend.02.03Vigorous physical activity (MET-hours/week)≤0.1127/431.0c68/501.0c>0.11 and ≤7.226/450.97 (0.56–1.64)62/471.05
(0.46–1.73)>7.224/471.02 (0.71–1.57)73/480.99
(0.72–1.91)P for trend.76.95Total physical activity (MET-hours/week)≤16.226/441.0c67/491.0c>16.2 and ≤33.225/460.70 (0.46–1.24)70/520.65
(0.46–1.83)>33.226/450.63 (0.41–0.97)66/440.89 (0.35–0.91)P for trend.05.05BMI* at interview.Adjusteda for age,
education, physical activity, smoking, alcohol consumption, and total energy
intake.Adjustedb for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedc for age,
education, alcohol consumption, smoking, and total energy intake.Table 5
Matched cases and controls by relationship: 15 subjects.
Age of diagnosis of breast cancer cases (index cases)Age of controls (relatives) at interviewRelationshipSister-sister:54745458424560503948394939513541Sub total of subjects: 8Aunt-niece5067393150294230Sub total of subjects: 4Mother-daughter35506244Sub total of subjects: 2Grandmother-granddaughter6223Sub total of subjects: 1Grand total of subjects: 15


#### 3.3.2. Physical Activity

Women who practiced >24.8 MET-hours compared to ≤10.7 MET-hours of
moderate physical activity weekly had a 52% lower risk of breast cancer
(OR = 0.48; 95% CI:0.31–0.74) (Table 3). Moreover, total physical activity
between 16.2 and 33.2 MET-hours per week compared to ≤16.2 MET-hours per week also showed
a 43% decreased risk of breast cancer (OR = 0.57; 95% CI: 0.37–0.87), and for
>33.2 MET-hours per week, there was a nonsignificantly reduced risk
(OR = 0.66; 95% CI: 0.43–1.01). A protective effect of moderate physical activity
of more than 24.8 MET-hours per week was observed among both premenopausal
(OR = 0.36; 95% CI: 0.22–0.67) and postmenopausal women (OR = 0.42; 95% CI:
0.12–0.59). A similar outcome was noted for total physical activity of more
than 33.2 MET-hours per week for both premenopausal (OR = 0.63; 95% CI: 0.41–0.97)
and postmenopausal women (OR = 0.88; 95% CI: 0.35–0.91) (Table 4). However, no
statistically significant association was apparent between vigorous physical
activity (>7.2 MET-hours/week) and breast cancer risk, regardless of menopausal
status.


### 4. Discussion

The present case-control study
provides results on lifestyle factors and breast cancer risk among
French-Canadian women who are noncarriers of the 6 most frequentBRCA1/2 mutations in this population. To
our knowledge, this is the first epidemiological investigation to assess the
possible role of common lifestyle variables in the etiology of breast cancer in
such a sample. Previous research on lifestyle and breast cancer risk has been
mostly undertaken on either sporadic subjects or among BRCA mutation carriers.Our
findings concur with previous work reporting that weight gain since youth is
related to increased sporadic breast cancer risk [15–19]. Our results also demonstrate  that weight
gain has a stronger positive association among postmenopausal than
premenopausal women. A recent case-control study of changes in body weight and
the risk of breast cancer in BRCA mutation carriers reported that among BRCA1 mutation carriers, a weight gain of more than 10 lbs between the age of 18 and 30 was associated with a 44% greater risk of breast cancer diagnosed between
the age of 30 and 40 [20]. Moreover, these results bolster those of our
research group’s recent case-control study of a group of French-Canadian BRCA carriers, indicating that weight
gain from the age of 18 and 30  was positively associated with breast cancer risk
[21]. On the other hand, recent prospective data from the Black Women's
Health Study suggested that weight gain in this population was not linked with
postmenopausal breast cancer risk providing evidence for differential results
in other ethnic populations. The findings also indicated that BMI ≥25
at the age of 18 of relative to <20 was associated with 32% and 47% reduced
risks of breast cancer among premenopausal and postmenopausal African-American
women, respectively, [22]. A likely contributor to the discrepancy in
findings between Black and White women with regard to current BMI, weight gain,
and postmenopausal breast cancer risk is the difference in distributions of
estrogen receptor (ER) and progesterone receptor (PR) status. African-American
women have a considerably lower proportion of breast carcinomas that are ER+,
PR+, or both, than White women [22].As
women age, particularly after menopause, obese women have a high level of serum
estrogen as a consequence of adrostenedione conversion to estrone in adipose
tissue, and also due to decreasing concentrations of sex hormone-binding
globulin that elevates serum free estrogen [23, 24]. High estrogen production may promote tumor
growth. Our study also found that age at attainment of maximum BMI might be an
important facet of body size when assessing breast cancer risk. Understanding
the importance of age as a predictor of breast cancer risk involves
consideration of the influence of adipose tissue on estrogen production and
circulation, particularly postmenopause. From the onset of menopause, adipose
tissue becomes the primary estrogen producer, and triacylglycerol and insulin
levels rise simultaneously. The combination of these events is believed to
lengthen a woman’s exposure to more active estrogen [25, 26]. It has also been hypothesized that the
effects of obesity may be stronger among older, postmenopausal women, due to
the longer period of time they are subjected to the proliferative actions of
elevated circulating estrogens from adipose tissue. Indeed, a higher breast
cancer risk among older postmenopausal women compared to younger women has been
suggested by a pooled analysis of 7 prospective studies [27]. Therefore, one may expect that women who
reach their maximum BMI later in life will be at greater risk for breast
cancer.Our
study showed that more than 9 pack-years of smoking had a significant positive
association with breast cancer risk among both pre- and postmenopausal women;
however, this result does not support our previous report of a reduced risk of
breast cancer in carriers ofBRCA gene mutations who had smoked more than 4 pack-years [28]. The weaker breast cancer risk in these
subjects may have been associated with lower levels of circulating estrogens [29]. In contrast, a recent case-control study
among Polish women indicated an increased risk of invasive breast cancer with
the consumption of ≥10
cigarettes/d among both premenopausal (OR = 2.55; 95% CI: 1.81–3.60) and
postmenopausal (OR = 1.78; 95% CI: 1.33–2.37) women [30]. Likewise, another recent study [31] suggested that BRCA mutation carriers who smoked had 2.3-fold (95% CI: 1.6–3.5)
and 2.6-fold (95% CI: 1.8–3.9), respectively, greater risk of breast cancer.
Cigarette smoke contains compounds that damage DNA, and the repair of such
damage may be impaired in women with germline mutations. Some genotoxic carcinogens in tobacco smoke are mammary
carcinogens in rodents [32]. The enzymatic machinery required for their
metabolic activation is present in human mammary epithelial cells [33], and there is evidence of carcinogen-DNA
adducts in human mammary tissue [34, 35], some of which may be smoking-related.Finally, our study found that moderate physical
activity was related to a decreased risk of breast cancer regardless of
menopause status. Physical activity has received much attention for its
salutary effect on breast cancer risk, as it is one of the few modifiable risk
factors for breast cancer. Numerous epidemiological investigations have
reported a reduced risk of breast cancer with increasing levels of
physical activity [36, 37]. In 2002, the International Agency for
Research on Cancer (IARC) concluded that “convincing" evidence exists
for an inverse association between breast cancer risk and physical activity
[38]. Our finding is also consistent with most recent work in
this field. For instance in a case-control study by Kamarudin et al. [39], inactive women had a 3.5-fold significantly
higher breast cancer risk compared to those who exercised regularly. Data from
the California Teachers Study [40]   (110599 women, 2649 invasive and 593 in situ cases) also demonstrated a 20%
reduction of invasive, and 31% decrease of in
situ, breast cancer risk among women who exercised regularly >5
hours/week per year. The authors reported a linear diminution of risk with
escalating amounts of exercise. Recently, a population-based case-control study
in Massachusetts
established that neither lifetime recreational nor strenuous occupational
physical activity appeared to be associated with breast carcinoma risk in situ. In contrast, recreational
physical activity was associated with a reduced risk of invasive
breast cancer in this investigation. After adjustment for potentially
confounding factors, women averaging >6 hours per week of strenuous
recreational activity over their lifetime had a 23% decrease in the
risk of invasive breast cancer when compared to women reporting no
recreational activity (95% CI: 0.65–0.92; P=.05  for trend) [41].Several biological mechanisms have been
proposed to explain the lower risk of breast cancer associated with physical
activity. In adolescents and young women who are very active, vigorous exercise
is accompanied by delayed menarche, irregular and anovulatory menstrual cycles,
and a shortened luteal phase [42–45]. Furthermore, postmenopausal women who are
physically active have lower levels of estrone and estradiol [46–48] as well as elevated sex hormone-binding globulin
[49]. Higher estrogen and lower levels of sex hormone-binding
globulin are associated with heightened breast cancer risk in postmenopausal
women [50]. Other potential mechanisms include the prevention of weight
gain, regulation of insulin sensitivity, and alterations in immune
function [51–54].Like all other case-control investigations, the
present study has certain limitations. While retrospective measures may result
in recall bias, such a problem is likely to be minimized since the same method
served to collect information from cases and controls. Moreover, the likelihood
of obtaining false information on maximum lifespan weight and age when this
weight occurred can be discounted, as weight gain for a majority of women is a
constant concern, and they can recall their highest weight and its timing with
relatively  good precision [21]. As with most case-control studies, selection
and recall bias may have influenced our results.The
present work has a number of strengths. A major strength is its
population-based design, which included only incident cases who had undergone
genetic testing for 6 specificBRCA gene mutations more frequently found in French-Canadian families and who
provided full information about known breast cancer risk factors. In addition, the response rate for both cases
and controls was high (over 90%), suggesting that the potential for selection
bias was low.The main protective effects exerted
by certain lifestyle factors identified in
this paper are consistent with current recommendations by the American Cancer
Society for breast cancer prevention [55, 56]. Because of the
multifactorial process in breast cancer development, and the tendency for
lifestyle variables to cluster, inconsistent and inconclusive data have emerged
on breast cancer risk even from well-designed epidemiological research.
Consequently, it is essential to continuously update knowledge on the risk
factors and their impact on breast cancer. This could help women make
beneficial changes in their behavior by addressing diet and physical activity
patterns that could reduce their breast cancer risk. In such a context, it is
interesting that recent evidence suggests that more than 50% of cancer
incidence could be prevented if knowledge of risk factors was applied to
changes in behavior [57]. The ultimate goal of such research is to
contribute to novel prevention strategies and to decrease the number of women
at risk for developing breast cancer.In summary, we found that weight history did affect breast
cancer risk. Moreover, smoking appeared to raise the risk, whereas moderate
physical activity had a protective effect. Further research is warranted to
confirm these associations in other study populations and hopefully in larger
sample sizes.


## 3.1. Characteristics of Study Subjects

Selected characteristics of cases
and controls are summarized in Table1. Mean (±SD) age of the cases was 51.9±8.2 years and 50.0±9.8 years for the controls (P= .01). Differences in age
distribution were noticeable between cases and controls with a slight excess of
younger control subjects. Cases had significantly higher education levels than
the controls (P= .01). The
nulliparous rate of the cases was significantly higher than that of the
controls (P= .01), and cases also had
fewer children than the controls (P= .01).
There were more postmenopausal women among the cases than the controls (P= .01), perhaps due to the above
mentioned different age distribution among cases and controls. The cases were
significantly more likely to have smoked at any time in their lives than the
controls (P= .03). The controls were
more likely to have reached their maximum lifetime weight at an earlier age (39
years) than the cases (47 years) (P= .01),
while history of weight change indicated that the cases had significantly
higher maximum lifetime weight than the controls (155.8 v/s 149.9) (P= .04). Higher weight gain since
adolescence and adulthood was observed among cases than the controls (P= .01). Controls practiced more moderate
physical activity than the cases (P= .01).
The cases were more likely to have greater total energy intake (P= .01) and alcohol (ethanol) intake (P= .03)  than the controls, whereas no
difference was apparent between study groups in the use of oral contraceptives
and hormone replacement therapy, age at menarche and at menopause, current
weight, weight at the age of 20, 30, and 40, and vigorous and total physical
activity.Table 1
Selected
characteristics of the study population.
VariablesCases
(n=280) (%)Controls
(n=280) (%)Pvalue1Age
(years, mean ± SD)51.9±8.250.0±9.8.01<303431–40172741–50454151–60292361+65Education
attainment (years,
mean ± SD)13.4±3.012.8±3.1.01Marital
statusSingle12.511.1Married/Common-law70.466.4Separated/divorced13.914.6Widowed3.27.9.15ParityNulliparous27.115.4.01≥172.984.6.01Menopausal
statusYes203145No77135.01Oral
contraceptive useEver87.985.0Never12.115.0.40Hormone
replacement therapyYes26.833.6No73.266.4.10SmokingEver63.653.6Never36.446.4.02Smoking10.3±13.47.8±12.8.03(pack-years,
mean ± SD)Age
at menarche(years,
mean ± SD)12.5±1.512.7±1.6.12Age at menopause (years)45.4±6.945.3±7.9.20Age at maximum weight(years)46.6±11.939.4±12.5.01Current weight (lbs)146.6±25.3143.1±25.1.10Weight at the age of 20 (lbs)116.7±16.0119.9±19.7.06Weight at the age of 30 (lbs)129.9±21.0127.4±14.8.18Weight at the age of 40 (lbs)141.8±28.1137.4±29.8.20Maximum lifetime weight (lbs)155.8±26.4149.9±28.5.04Weight gain since the age of 20 (lbs)30.0±22.623.2±21.8.01Weight gain since the age of 30 (lbs)21.3±20.415.0±18.7.01Weight gain since the age of 40 (lbs)12.4±14.96.9±15.2.01Physical activity (MET-hours/week)Moderate (4)18.8±13.521.8±14.8.01Vigorous (7)8.1±12.07.1±11.0.29Total26.9±20.028.9±18.8.22Total energy intake (Kcal)2025.6±674.21782.1±626.3.01All1P  values are
univariate and derived by student’s t-test
for continuous variables with the χ2 test for categorical variables.MET: metabolic equivalent.


## 3.2. Weight History

The risk of breast cancer in relation to weight
history is presented in Tables2 and 4 reporting the results stratified
by menopausal status. After adjusting for age, education, physical activity,
smoking, alcohol consumption, and total energy intake, breast cancer risk was
increased when subjects reached their maximum body mass index (BMI) at an older
age (>50 years) (OR = 2.83; 95% CI: 2.34–2.91). In addition, a positive
association was noted between maximum weight gain of more than 34 lbs compared to weight
gain of ≤15 lbs, since age 20 (OR = 1.68; 95% CI: 1.10–2.58). Weight gain of more
than 24 lbs compared to weight gain of ≤9 lbs since the age of 30 also
showed similar results (OR = 1.96; 95% CI: 1.46–3.06). Likewise, a positive
association with breast cancer risk (OR = 1.91; 95% CI: 1.53–2.66) was observed
for a weight gain after the age of 40 of more than 12 lbs compared to a weight
gain of ≤1 lb. Weight gain of more than 25 lbs from the age of 30 to the age of 40 presented an
increased risk of breast cancer in both pre- (OR = 1.62; 95% CI: 1.42–1.97) and
postmenopausal women (OR = 1.98; 95% CI: 1.11–2.03). Weight gain of more than 25 lbs from the age of 40 to the age of
50 presented an increased risk of breast cancer in postmenopausal women
(OR = 2.01; 95% CI: 1.45–2.91) as well as weight gain of more than 25 lbs from the age of 50 to the age of
60 showed an increased risk of breast cancer in postmenopausal women (OR = 1.79;
95% CI: 1.21–2.33). No association was apparent between breast cancer risk and
current BMI, and BMI at the age of 20, 30, 40, under 49, and over 50 years.
Furthermore, maximum lifetime BMI did not show any significant association with
breast cancer risk (data not reported).Table 2
Odd ratios and 95% confidence intervals for
breast cancer risk associated with weight history.
VariablesQ1Q2Q3P
for trendCurrentBMI*Range (kg/m2)≤21.1>21.1 and ≤25.0>25.0Cases/Controls91/9298/9491/94Univariate OR (95% CI)1.001.34 (0.35–1.41)1.76 (0.91–1.78).08MultivariateORa (95% CI)1.25 (0.76–1.85)1.55 (0.77–1.89).09Age at maximum BMIRange (years)≤39>39 and ≤50>50Cases/Controls58/126108/94114/60Univariate OR (95%
CI)1.002.50 (1.65–3.78)2.65
(2.60–3.41).01MultivariateORa (95% CI)2.77 (1.76–4.85)2.83 (2.34–2.91).01Weight gain since the age of 20Range (lbs)≤15>15 and ≤34>34Cases/Controls80/11593/78107/87Univariate OR (95%
CI)1.001.71 (1.13–2.60)1.67
(1.18–2.64).01MultivariateORa (95% CI)1.76 (1.13–2.72)1.68 (1.10–2.58).01Weight gain since the age of 30Range (lbs)≤9>9 and ≤24>24Cases/Controls68/117106/84106/79Univariate OR (95%
CI)1.002.31 (1.52–3.50)2.17
(1.44–3.28).01MultivariateORa (95% CI)2.25
(1.75–3.49)1.96 (1.46–3.06).01Weight gain since the age of 40Range (lbs)≤1>1 and ≤12>12Cases/Controls55/12080/63103/60Univariate OR (95%
CI)1.001.95 (1.16–2.74)1.99
(1.47–2.49).01MultivariateORa (95% CI)1.82 (1.36–3.10)1.91 (1.53–2.66).01BMI* at interview.Adjusteda for age,
education, physical activity, smoking, alcohol consumption and total energy
intake.


## 3.3. Lifestyle Factors

### 3.3.1. Smoking

The ORs and 95% CIs for breast cancer risk by
smoking status for all age groups are enumerated in Table3; these results
also appear in Table 4, where they are stratified by menopausal status. After
adjusting for age, education, physical activity, alcohol consumption and total
energy intake, women who smoked more than 9 pack-years had a 59% greater risk
of breast cancer (OR = 1.59; 95% CI: 1.57–2.87) (Table 3). A 63% higher risk of
breast cancer was also noted among premenopausal women (OR = 1.63; 95% CI:
1.23–2.47), with a 49% increased risk among postmenopausal women (OR = 1.49; 95%
CI: 1.33–2.31) (Table 4).Table 3
Odd ratios and 95% confidence intervals for
breast cancer risk associated with lifestyle factors, including smoking and
physical activity.
VariablesQ1Q2Q3P
for trendSmokingRange (pack-years)≤0>0 and ≤9.0>9.0Cases/Controls106/13467/66107/80Univariate OR (95% CI)1.001.28
(0.84–1.96)1.69 (1.15–2.49).03MultivariateORa (95% CI)1.35
(0.86–2.09)1.59 (1.57–2.87).05Moderate physical activityRange (MET-hours/week)≤10.7>10.7 and ≤24.8>24.8Cases/Controls80/10891/95109/77Univariate OR (95% CI)1.000.68
(0.45–1.02)0.52 (0.35–0.79).01MultivariateORb (95% CI)0.67
(0.44–1.03)0.48 (0.31–0.74).01Vigorous
physical activityRange (MET-hours/week)≤0.11>0.11 and ≤7.2>7.2Cases/Controls91/9491/9298/94Univariate OR (95% CI)1.001.02
(0.68–1.54)1.08 (0.72–1.61).93MultivariateORb (95% CI)1.01
(0.66–1.56)1.05 (0.66–1.52).94Total physical activityRange (MET-hours/week)≤16.2> 6.2 and ≤33.2>33.2Cases/Controls87/10089/98104/82Univariate OR (95% CI)1.000.69
(0.46–1.03)0.72 (0.48–1.08).14MultivariateORb (95% CI)0.57 (0.37–0.87)0.66 (0.43–1.01).05Adjusteda for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedb for age,
education, alcohol consumption, smoking, and total energy intake.Table 4
Multivariable adjusted odd ratios and 95%
confidence intervals for breast cancer risk in relation to BMI,
weight gain, smoking, and physical activity, by menopausal status.
VariablePremenopausalPostmenopausalCases/Controls OR (95% CI)Cases/Controls OR (95% CI)Current BMI (kg/m2)*≤22.520/451.0a64/561.0a>22.5 and ≤26.030/471.37 (0.96–2.60)68/501.65
(0.96–2.70)>26.027/431.02 (0.52–2.07)71/391.19
(0.92–2.01)P  for trend.56.35Weight gain (lbs) from the age of 30 to the age of 40≤1327/491.0a65/491.0a>13 and ≤2525/401.55 (0.81–1.86)70/511.95
(0.88–2.17)>2525/461.62 (1.42–1.97)68/451.98 (1.11–2.03)P  for trend.05.03Weight gain (lbs) from the age of 40 to the age of 50≤1366/521.0a>13 and ≤2567/552.01 (0.74–2.80)>2570/382.01 (1.45–2.91)P   for trend.04Weight gain (lbs) from the age of 50 to the age of 60≤1369/501.0a>13 and ≤2571/471.86 (0.62–1.97)>2563/481.79 (1.21–2.33)P for trend.03Smoking (pack-years)≤017/411.0b62/551.0b>0 and ≤931/451.30 (0.76–1.86)70/471.62
(0.90–1.93)>929/491.63 (1.23–2.47)71/431.49 (1.33–2.31)P  for trend.05.04Moderate physical activity (MET-hours/week)≤10.725/401.0c69/451.0c>10.7 and ≤24.832/470.57 (0.26–1.60)60/530.65
(0.96–1.71)>24.820/480.36 (0.22–0.67)74/470.42 (0.12–0.59)P for trend.02.03Vigorous physical activity (MET-hours/week)≤0.1127/431.0c68/501.0c>0.11 and ≤7.226/450.97 (0.56–1.64)62/471.05
(0.46–1.73)>7.224/471.02 (0.71–1.57)73/480.99
(0.72–1.91)P for trend.76.95Total physical activity (MET-hours/week)≤16.226/441.0c67/491.0c>16.2 and ≤33.225/460.70 (0.46–1.24)70/520.65
(0.46–1.83)>33.226/450.63 (0.41–0.97)66/440.89 (0.35–0.91)P for trend.05.05BMI* at interview.Adjusteda for age,
education, physical activity, smoking, alcohol consumption, and total energy
intake.Adjustedb for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedc for age,
education, alcohol consumption, smoking, and total energy intake.Table 5
Matched cases and controls by relationship: 15 subjects.
Age of diagnosis of breast cancer cases (index cases)Age of controls (relatives) at interviewRelationshipSister-sister:54745458424560503948394939513541Sub total of subjects: 8Aunt-niece5067393150294230Sub total of subjects: 4Mother-daughter35506244Sub total of subjects: 2Grandmother-granddaughter6223Sub total of subjects: 1Grand total of subjects: 15


### 3.3.2. Physical Activity

Women who practiced >24.8 MET-hours compared to ≤10.7 MET-hours of
moderate physical activity weekly had a 52% lower risk of breast cancer
(OR = 0.48; 95% CI:0.31–0.74) (Table 3). Moreover, total physical activity
between 16.2 and 33.2 MET-hours per week compared to ≤16.2 MET-hours per week also showed
a 43% decreased risk of breast cancer (OR = 0.57; 95% CI: 0.37–0.87), and for
>33.2 MET-hours per week, there was a nonsignificantly reduced risk
(OR = 0.66; 95% CI: 0.43–1.01). A protective effect of moderate physical activity
of more than 24.8 MET-hours per week was observed among both premenopausal
(OR = 0.36; 95% CI: 0.22–0.67) and postmenopausal women (OR = 0.42; 95% CI:
0.12–0.59). A similar outcome was noted for total physical activity of more
than 33.2 MET-hours per week for both premenopausal (OR = 0.63; 95% CI: 0.41–0.97)
and postmenopausal women (OR = 0.88; 95% CI: 0.35–0.91) (Table 4). However, no
statistically significant association was apparent between vigorous physical
activity (>7.2 MET-hours/week) and breast cancer risk, regardless of menopausal
status.


## 3.3.1. Smoking

The ORs and 95% CIs for breast cancer risk by
smoking status for all age groups are enumerated in Table3; these results
also appear in Table 4, where they are stratified by menopausal status. After
adjusting for age, education, physical activity, alcohol consumption and total
energy intake, women who smoked more than 9 pack-years had a 59% greater risk
of breast cancer (OR = 1.59; 95% CI: 1.57–2.87) (Table 3). A 63% higher risk of
breast cancer was also noted among premenopausal women (OR = 1.63; 95% CI:
1.23–2.47), with a 49% increased risk among postmenopausal women (OR = 1.49; 95%
CI: 1.33–2.31) (Table 4).Table 3
Odd ratios and 95% confidence intervals for
breast cancer risk associated with lifestyle factors, including smoking and
physical activity.
VariablesQ1Q2Q3P
for trendSmokingRange (pack-years)≤0>0 and ≤9.0>9.0Cases/Controls106/13467/66107/80Univariate OR (95% CI)1.001.28
(0.84–1.96)1.69 (1.15–2.49).03MultivariateORa (95% CI)1.35
(0.86–2.09)1.59 (1.57–2.87).05Moderate physical activityRange (MET-hours/week)≤10.7>10.7 and ≤24.8>24.8Cases/Controls80/10891/95109/77Univariate OR (95% CI)1.000.68
(0.45–1.02)0.52 (0.35–0.79).01MultivariateORb (95% CI)0.67
(0.44–1.03)0.48 (0.31–0.74).01Vigorous
physical activityRange (MET-hours/week)≤0.11>0.11 and ≤7.2>7.2Cases/Controls91/9491/9298/94Univariate OR (95% CI)1.001.02
(0.68–1.54)1.08 (0.72–1.61).93MultivariateORb (95% CI)1.01
(0.66–1.56)1.05 (0.66–1.52).94Total physical activityRange (MET-hours/week)≤16.2> 6.2 and ≤33.2>33.2Cases/Controls87/10089/98104/82Univariate OR (95% CI)1.000.69
(0.46–1.03)0.72 (0.48–1.08).14MultivariateORb (95% CI)0.57 (0.37–0.87)0.66 (0.43–1.01).05Adjusteda for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedb for age,
education, alcohol consumption, smoking, and total energy intake.Table 4
Multivariable adjusted odd ratios and 95%
confidence intervals for breast cancer risk in relation to BMI,
weight gain, smoking, and physical activity, by menopausal status.
VariablePremenopausalPostmenopausalCases/Controls OR (95% CI)Cases/Controls OR (95% CI)Current BMI (kg/m2)*≤22.520/451.0a64/561.0a>22.5 and ≤26.030/471.37 (0.96–2.60)68/501.65
(0.96–2.70)>26.027/431.02 (0.52–2.07)71/391.19
(0.92–2.01)P  for trend.56.35Weight gain (lbs) from the age of 30 to the age of 40≤1327/491.0a65/491.0a>13 and ≤2525/401.55 (0.81–1.86)70/511.95
(0.88–2.17)>2525/461.62 (1.42–1.97)68/451.98 (1.11–2.03)P  for trend.05.03Weight gain (lbs) from the age of 40 to the age of 50≤1366/521.0a>13 and ≤2567/552.01 (0.74–2.80)>2570/382.01 (1.45–2.91)P   for trend.04Weight gain (lbs) from the age of 50 to the age of 60≤1369/501.0a>13 and ≤2571/471.86 (0.62–1.97)>2563/481.79 (1.21–2.33)P for trend.03Smoking (pack-years)≤017/411.0b62/551.0b>0 and ≤931/451.30 (0.76–1.86)70/471.62
(0.90–1.93)>929/491.63 (1.23–2.47)71/431.49 (1.33–2.31)P  for trend.05.04Moderate physical activity (MET-hours/week)≤10.725/401.0c69/451.0c>10.7 and ≤24.832/470.57 (0.26–1.60)60/530.65
(0.96–1.71)>24.820/480.36 (0.22–0.67)74/470.42 (0.12–0.59)P for trend.02.03Vigorous physical activity (MET-hours/week)≤0.1127/431.0c68/501.0c>0.11 and ≤7.226/450.97 (0.56–1.64)62/471.05
(0.46–1.73)>7.224/471.02 (0.71–1.57)73/480.99
(0.72–1.91)P for trend.76.95Total physical activity (MET-hours/week)≤16.226/441.0c67/491.0c>16.2 and ≤33.225/460.70 (0.46–1.24)70/520.65
(0.46–1.83)>33.226/450.63 (0.41–0.97)66/440.89 (0.35–0.91)P for trend.05.05BMI* at interview.Adjusteda for age,
education, physical activity, smoking, alcohol consumption, and total energy
intake.Adjustedb for age,
education, physical activity, alcohol consumption, and total energy intake.Adjustedc for age,
education, alcohol consumption, smoking, and total energy intake.Table 5
Matched cases and controls by relationship: 15 subjects.
Age of diagnosis of breast cancer cases (index cases)Age of controls (relatives) at interviewRelationshipSister-sister:54745458424560503948394939513541Sub total of subjects: 8Aunt-niece5067393150294230Sub total of subjects: 4Mother-daughter35506244Sub total of subjects: 2Grandmother-granddaughter6223Sub total of subjects: 1Grand total of subjects: 15


## 3.3.2. Physical Activity

Women who practiced >24.8 MET-hours compared to ≤10.7 MET-hours of
moderate physical activity weekly had a 52% lower risk of breast cancer
(OR = 0.48; 95% CI:0.31–0.74) (Table 3). Moreover, total physical activity
between 16.2 and 33.2 MET-hours per week compared to ≤16.2 MET-hours per week also showed
a 43% decreased risk of breast cancer (OR = 0.57; 95% CI: 0.37–0.87), and for
>33.2 MET-hours per week, there was a nonsignificantly reduced risk
(OR = 0.66; 95% CI: 0.43–1.01). A protective effect of moderate physical activity
of more than 24.8 MET-hours per week was observed among both premenopausal
(OR = 0.36; 95% CI: 0.22–0.67) and postmenopausal women (OR = 0.42; 95% CI:
0.12–0.59). A similar outcome was noted for total physical activity of more
than 33.2 MET-hours per week for both premenopausal (OR = 0.63; 95% CI: 0.41–0.97)
and postmenopausal women (OR = 0.88; 95% CI: 0.35–0.91) (Table 4). However, no
statistically significant association was apparent between vigorous physical
activity (>7.2 MET-hours/week) and breast cancer risk, regardless of menopausal
status.


## 4. Discussion

The present case-control study
provides results on lifestyle factors and breast cancer risk among
French-Canadian women who are noncarriers of the 6 most frequentBRCA1/2 mutations in this population. To
our knowledge, this is the first epidemiological investigation to assess the
possible role of common lifestyle variables in the etiology of breast cancer in
such a sample. Previous research on lifestyle and breast cancer risk has been
mostly undertaken on either sporadic subjects or among BRCA mutation carriers.Our
findings concur with previous work reporting that weight gain since youth is
related to increased sporadic breast cancer risk [15–19]. Our results also demonstrate  that weight
gain has a stronger positive association among postmenopausal than
premenopausal women. A recent case-control study of changes in body weight and
the risk of breast cancer in BRCA mutation carriers reported that among BRCA1 mutation carriers, a weight gain of more than 10 lbs between the age of 18 and 30 was associated with a 44% greater risk of breast cancer diagnosed between
the age of 30 and 40 [20]. Moreover, these results bolster those of our
research group’s recent case-control study of a group of French-Canadian BRCA carriers, indicating that weight
gain from the age of 18 and 30  was positively associated with breast cancer risk
[21]. On the other hand, recent prospective data from the Black Women's
Health Study suggested that weight gain in this population was not linked with
postmenopausal breast cancer risk providing evidence for differential results
in other ethnic populations. The findings also indicated that BMI ≥25
at the age of 18 of relative to <20 was associated with 32% and 47% reduced
risks of breast cancer among premenopausal and postmenopausal African-American
women, respectively, [22]. A likely contributor to the discrepancy in
findings between Black and White women with regard to current BMI, weight gain,
and postmenopausal breast cancer risk is the difference in distributions of
estrogen receptor (ER) and progesterone receptor (PR) status. African-American
women have a considerably lower proportion of breast carcinomas that are ER+,
PR+, or both, than White women [22].As
women age, particularly after menopause, obese women have a high level of serum
estrogen as a consequence of adrostenedione conversion to estrone in adipose
tissue, and also due to decreasing concentrations of sex hormone-binding
globulin that elevates serum free estrogen [23, 24]. High estrogen production may promote tumor
growth. Our study also found that age at attainment of maximum BMI might be an
important facet of body size when assessing breast cancer risk. Understanding
the importance of age as a predictor of breast cancer risk involves
consideration of the influence of adipose tissue on estrogen production and
circulation, particularly postmenopause. From the onset of menopause, adipose
tissue becomes the primary estrogen producer, and triacylglycerol and insulin
levels rise simultaneously. The combination of these events is believed to
lengthen a woman’s exposure to more active estrogen [25, 26]. It has also been hypothesized that the
effects of obesity may be stronger among older, postmenopausal women, due to
the longer period of time they are subjected to the proliferative actions of
elevated circulating estrogens from adipose tissue. Indeed, a higher breast
cancer risk among older postmenopausal women compared to younger women has been
suggested by a pooled analysis of 7 prospective studies [27]. Therefore, one may expect that women who
reach their maximum BMI later in life will be at greater risk for breast
cancer.Our
study showed that more than 9 pack-years of smoking had a significant positive
association with breast cancer risk among both pre- and postmenopausal women;
however, this result does not support our previous report of a reduced risk of
breast cancer in carriers ofBRCA gene mutations who had smoked more than 4 pack-years [28]. The weaker breast cancer risk in these
subjects may have been associated with lower levels of circulating estrogens [29]. In contrast, a recent case-control study
among Polish women indicated an increased risk of invasive breast cancer with
the consumption of ≥10
cigarettes/d among both premenopausal (OR = 2.55; 95% CI: 1.81–3.60) and
postmenopausal (OR = 1.78; 95% CI: 1.33–2.37) women [30]. Likewise, another recent study [31] suggested that BRCA mutation carriers who smoked had 2.3-fold (95% CI: 1.6–3.5)
and 2.6-fold (95% CI: 1.8–3.9), respectively, greater risk of breast cancer.
Cigarette smoke contains compounds that damage DNA, and the repair of such
damage may be impaired in women with germline mutations. Some genotoxic carcinogens in tobacco smoke are mammary
carcinogens in rodents [32]. The enzymatic machinery required for their
metabolic activation is present in human mammary epithelial cells [33], and there is evidence of carcinogen-DNA
adducts in human mammary tissue [34, 35], some of which may be smoking-related.Finally, our study found that moderate physical
activity was related to a decreased risk of breast cancer regardless of
menopause status. Physical activity has received much attention for its
salutary effect on breast cancer risk, as it is one of the few modifiable risk
factors for breast cancer. Numerous epidemiological investigations have
reported a reduced risk of breast cancer with increasing levels of
physical activity [36, 37]. In 2002, the International Agency for
Research on Cancer (IARC) concluded that “convincing" evidence exists
for an inverse association between breast cancer risk and physical activity
[38]. Our finding is also consistent with most recent work in
this field. For instance in a case-control study by Kamarudin et al. [39], inactive women had a 3.5-fold significantly
higher breast cancer risk compared to those who exercised regularly. Data from
the California Teachers Study [40]   (110599 women, 2649 invasive and 593 in situ cases) also demonstrated a 20%
reduction of invasive, and 31% decrease of in
situ, breast cancer risk among women who exercised regularly >5
hours/week per year. The authors reported a linear diminution of risk with
escalating amounts of exercise. Recently, a population-based case-control study
in Massachusetts
established that neither lifetime recreational nor strenuous occupational
physical activity appeared to be associated with breast carcinoma risk in situ. In contrast, recreational
physical activity was associated with a reduced risk of invasive
breast cancer in this investigation. After adjustment for potentially
confounding factors, women averaging >6 hours per week of strenuous
recreational activity over their lifetime had a 23% decrease in the
risk of invasive breast cancer when compared to women reporting no
recreational activity (95% CI: 0.65–0.92; P=.05  for trend) [41].Several biological mechanisms have been
proposed to explain the lower risk of breast cancer associated with physical
activity. In adolescents and young women who are very active, vigorous exercise
is accompanied by delayed menarche, irregular and anovulatory menstrual cycles,
and a shortened luteal phase [42–45]. Furthermore, postmenopausal women who are
physically active have lower levels of estrone and estradiol [46–48] as well as elevated sex hormone-binding globulin
[49]. Higher estrogen and lower levels of sex hormone-binding
globulin are associated with heightened breast cancer risk in postmenopausal
women [50]. Other potential mechanisms include the prevention of weight
gain, regulation of insulin sensitivity, and alterations in immune
function [51–54].Like all other case-control investigations, the
present study has certain limitations. While retrospective measures may result
in recall bias, such a problem is likely to be minimized since the same method
served to collect information from cases and controls. Moreover, the likelihood
of obtaining false information on maximum lifespan weight and age when this
weight occurred can be discounted, as weight gain for a majority of women is a
constant concern, and they can recall their highest weight and its timing with
relatively  good precision [21]. As with most case-control studies, selection
and recall bias may have influenced our results.The
present work has a number of strengths. A major strength is its
population-based design, which included only incident cases who had undergone
genetic testing for 6 specificBRCA gene mutations more frequently found in French-Canadian families and who
provided full information about known breast cancer risk factors. In addition, the response rate for both cases
and controls was high (over 90%), suggesting that the potential for selection
bias was low.The main protective effects exerted
by certain lifestyle factors identified in
this paper are consistent with current recommendations by the American Cancer
Society for breast cancer prevention [55, 56]. Because of the
multifactorial process in breast cancer development, and the tendency for
lifestyle variables to cluster, inconsistent and inconclusive data have emerged
on breast cancer risk even from well-designed epidemiological research.
Consequently, it is essential to continuously update knowledge on the risk
factors and their impact on breast cancer. This could help women make
beneficial changes in their behavior by addressing diet and physical activity
patterns that could reduce their breast cancer risk. In such a context, it is
interesting that recent evidence suggests that more than 50% of cancer
incidence could be prevented if knowledge of risk factors was applied to
changes in behavior [57]. The ultimate goal of such research is to
contribute to novel prevention strategies and to decrease the number of women
at risk for developing breast cancer.In summary, we found that weight history did affect breast
cancer risk. Moreover, smoking appeared to raise the risk, whereas moderate
physical activity had a protective effect. Further research is warranted to
confirm these associations in other study populations and hopefully in larger
sample sizes.



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*Source: 748367-2009-04-16.xml*