intro to epidemiology
Assignment 4.1 Applying the Bradford Hill Criteria
Instructions:
Attached to this assignment, you will find the articles and instructions necessary to complete Assignment 4.1 Applying the Bradford Hill Criteria.
First, you will read the short article about GMOs found at
The Generic Literacy Project. (Links to an external site.)
This article serves as your example of how to apply the Bradford Hill criteria. As you read, think about how the Bradford Hill criteria were applied to formulate this stance about GMOs. Consider the factors that were identified about GMOs to represent each of the Bradford Hill criteria and, subsequently, form an opinion.
Second, you will read the attached article about a proposed link between French fries and breast cancer. You will then note how the Bradford Hill criteria apply to that article and decide if causation is present based on your application of the Bradford Hill criteria. To complete the assignment, list each of the nine Bradford Hill criteria in a Word document, using the class lecture slides to remind you of the criteria. Next to each one of the criteria, write what you find in the article which corresponds to that criterion–that is, supporting or refuting evidence for each criterion. You may not find evidence for all nine criteria. That is ok. Be sure that you report evidence for at least five of the criteria. After you have noted supporting or refuting evidence for at least five criteria, write a brief summary paragraph stating your conclusion about whether there is a causal link between french fries and breast cancer and why you believe there is or is not based on your application of the Bradford Hill criteria.
Third, you will read the attached article about HPV and cervical cancer. You will apply the Bradford Hill criteria to that article, noting supporting or refuting evidence for each one of the criteria as you did for the previous article. Just as you did before, after noting supporting or refuting evidence for at least five of the Bradford Hill criteria, you will write a brief summary paragraph stating your conclusion about whether there is a causal link between HPV and cervical cancer and why there is or is not based on your application of the Bradford Hill criteria.
Submission Instructions:
Submit your assignment as a Word document
Attachments
Grading Rubric for Epidemiology Assignments Actions
Bradford Hill Case Study.French Fries and Breast Cancer.2006 International_Journal_of_Cancer(1)
HPV causes cervical cancer.journal article (2015)
Grading Rubric for Written Epidemiology Assignments
Levels of Assessment
Criteria
% of overall assignment
grade
Inadequate=D
Adequate=C Above Average=B Exemplary=A
Organization
10% of grade
Writing lacks logical
organization. It shows
some coherence but ideas
lack unity. Answers are
not necessarily found in
response to the question
or topic to which they
belong.
Writing is coherent and
logically organized. Some
points remain misplaced
and stray from the topic.
Some answers are given
to questions and topics
other than those to which
they correctly belong.
Writing is coherent and
logically organized.
Overall unity of ideas is
present. Answers to
questions and topics are
clearly identified as
belonging to a particular
question or topic.
Writing shows high
degree of attention to
logic and reasoning of
points. Writing clearly
leads the reader to the
answer for each question.
Level of Content
60% of grade
Shows some thinking and
reasoning but most ideas
are underdeveloped.
Most answers are not
accurate.
Content indicates thinking
and reasoning applied. A
few answers are not
accurate.
Content indicates original
thinking and develops
ideas with sufficient and
firm evidence. The
majority of answers are
accurate.
Content indicates
synthesis of ideas, in-
depth analysis supports
for the topic. Nearly all
answers are accurate.
Development
20% of grade
Answers and main points
in responses to
questions/topics lack
development. Ideas are
vague with little evidence
of critical thinking.
Answers and main points
are present, but with
limited evidence and
development. Some
critical thinking is present.
Answers and main points
are well-developed with
sufficient and quantity
and quality of supporting
evidence. Critical thinking
is weaved into responses.
Answers and main points
are well-developed,
supported with high
quality and quantity of
evidence. Reveals high
degree of critical thinking.
Writing-Grammar and
Mechanics
10%
Spelling, punctuation, and
grammatical errors are
distracting, making
reading difficult; Sentence
structure errors are
frequent.
Most spelling,
punctuation, and
grammar is correct, and is
not distracting to reader.
Some errors remain.
Responses have few
spelling, punctuation, and
grammatical errors,
allowing reader to follow
ideas clearly. Very few
fragments or run-ons.
Responses are free of
distracting spelling,
punctuation, and
grammatical errors;
absent of sentence-
structure errors.
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HPV Caused Cervical Cancer
Article · January 2015
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IJCBCP (2015) 1–8 © JournalsPub 2015
.
All Rights Reserved Page 1
International Journal of Cell Biology and Cellular Processes
Vol. 1: Issue 1
www.journalspub.com
HPV Caused Cervical
Cancer
Sreenivas Reddy Bathula*, Sharada P.S., B.E. Rangaswamy
Department of Biotechnology, Bapuji Institute of Engineering & Technology, Davangere, Karnataka, India
Abstract
The causative role of human papillomavirus (HPV) in all cancers of the uterine cervix has
been firmly recognized biologically and epidemiologically. Most cancers of the vagina and
anus are likewise caused by HPV, as are a fraction of cancers of the vulva, penis, and
oropharynx. HPV-16 and -18 account for about 70% of cancers of the cervix, vagina, and
anus and for about 30–40% of cancers of the vulva, penis, and oropharynx. Other cancers
causally linked to HPV are non-melanoma skin cancer and cancer of the conjunctiva
.
Although HPV is a necessary cause of cervical cancer, it is not enough cause. Thus, other
cofactors are necessary for development from cervical HPV infection to
cancer.
Long-term
use of hormonal contraceptives, high parity, tobacco smoking, and co-infection with HIV
have been identified as established cofactors; co-infection with Chlamydia trachomatis (CT)
and herpes simplex virus type-2 (HSV-2), immunosuppression, and certain dietary
deficiencies are other probable cofactors. Genetic and immunological host factors and viral
factors other than type, such as variants of type, viral load and viral integration, are likely to
be important but have not been clearly identified
[1].
Keywords: Uterine cervix, oropharynx, conjunctiva, Chlamydia trachomatis, non-melanoma
skin cancer
*Author for Correspondence: Email ID: jaishwa@hotmail.com
INTRODUCTION
Cervical cancer is the second most
common cancer in women worldwide, and
knowledge regarding its cause and
pathogenesis is expanding rapidly. The
common cause is persistent infection with
one of about 15 genotypes of carcinogenic
human papillomavirus (HPV).
There are four major steps in cervical
cancer development: infection of
metaplastic epithelium at the cervical
transformation zone, viral persistence,
progression of persistently infected
epithelium to cervical precancer, and
invasion through the basement membrane
of the epithelium. Infection is extremely
common in young women in their first
decade of sexual activity. Persistent
infections and precancer are recognized,
typically within 5–10 years, from less than
10% of new infections. Invasive cancer
arises over many years, even decades, in a
minority of women with precancer, with a
peak or plateau in risk at about 35–
55 years of age. Each genotype of HPV
acts as an autonomous infection, with
differing carcinogenic risks linked to
evolutionary species. Our understanding
has led to improved prevention and
clinical management strategies, including
improved screening tests and vaccines.
The new HPV-oriented model of cervical
carcinogenesis should gradually replace
older morphological models based only on
cytology and histology. If applied wisely,
HPV-related technology can minimise the
incidence of cervical cancer, and the
morbidity and mortality it causes, even in
low-resource settings
[1]
.
mailto:jaishwa@hotmail.com
HPV Caused Cervical Cancer Bathula et al.
__________________________________________________________________________________________
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 2
THEORY
Cancer
Cancer is a disease in which the body cells
become abnormal and divide without
control. Cancer cells invade nearby tissues
and they may spread through the blood
stream and lymphatic system to other parts
of the body.
Definition of HPV
Human papillomavirus (HPV) is a virus
that can be passed from person to person
through skin-to-skin contact.
More than 100 types of HPV have been
found. More are harmless, but about 30 of
these types infect the genital areas and you
get them through sexual contact with an
infected partner. Usually the body fights
off HPV before it can cause health
problems, if it is not cleared then they may
lead to either low-risk or high risk factors.
Low-risk HPV types (6, 11, 42, 43, and
44) can cause genital warts in both men
and women. These are soft growth on the
skin and mucus membranes of genitals.
They may also be found on the penis,
vulva, urethra, vagina, cervix, and around
and in the anus. Warts are not life
threatening, but can be emotionally hard
for a person to deal with
[2]
.
High-risk HPV types (16, 18, 31, 33, 39,
45, 51, 52, 56, 58, 59, 66, 68, and 73) can
lead to cancers of cervix, vulva, vagina
and anus in women. In men it leads to
cancers of anus and penis.
HPV is a very common virus. It is more
common in young men and women in their
late teens and early 20s. Some researches
suggest that at least three out four people
who have sex will get a genital HPV
infection at some time in their lives.
IS HPV MORE COMMON IN
WOMEN OR MEN?
HPV is just as common in men and
women. But HPV is less likely to cause
serious health problems in men. Most men
with HPV never get symptoms or health
problems from it. There is no approved
test for HPV in men. HPV and genital
warts are just as common in native women
as in women of other
ethnicities.
Cervical cancer is less common in native
women than in African-American and
Hispanic women. But cervical cancer is
more common in native women than in
white women.
In United States, about 12,000 women get
cervical or other genital cancers from HPV
every year.
And about 7,000 men get head, neck and
anal cancers from HPV every year. HPV
and genital warts are just as common in
native women as in women of other
ethnicities.
TRANSMISSION
HPV is primarily spread through vaginal,
anal, or oral sex, but sexual intercourse is
not required for infection to occur. HPV is
spread by skin-to-skin contact. Sexual
contact with an infected partner is the most
common way the virus is spread. Like
many other sexually transmitted diseases,
there often are no signs and symptoms of
genital HPV infection.
YOU CANNOT GET HPV FROM
o Toilet seats;
o Kissing, hugging, or holding hands;
o Being unclean;
o Sharing food or utensils, Family
history.
WHAT DISEASES DOES HPV
INFECTION CAUSES?
o Approximately 12 types of HPV cause
genital warts. These growths may
appear on the outside or inside of the
vagina or on the penis and can spread
to nearby skin. Genital warts also can
grow around the anus, on the vulva, or
on the cervix.
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 3
International Journal of Cell Biology and Cellular Processes
Vol. 1: Issue 1
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o Approximately 15 types of HPV are
linked to cancer of the anus, cervix,
vulva, vaginal and penis they also can
cause cancer of the head and neck.
These types are known as “high-risk
types”
[3]
.
Cervical cancer begins in the women’s
cervix. It is the narrow organ at the bottom
of the uterus that connects to the vagina.
And in the same way it can grow on other
body organs.
HOW DOES HPV CAUSES CANCER
OF CARVIX?
The cervix is covered by a thin layer of
tissue made up of cells. If HPV is present,
it may enter these cells. Infected cells may
become abnormal or damaged and begin to
grow differently. The changes in these
cells may progress to what is known as
precancer. Changes in the thin tissue
covering the cervix are called dysplasia or
cervical intraepithelial neoplasia (CIN). In
most women, the immune system destroys
the virus before it causes cancer. But in
some women, HPV is not destroyed by the
immune system and does not go away. In
these cases, HPV can lead to cancer or,
more commonly, precancer
[4]
.
Types of Cervical Cancer
There are mainly two types of cervical
cancer. They are distinguished by the
appearance of cells under a microscope:
a. Squamous cell carcinoma,
b. Adenocarcinoma.
Squamous Cell Carcinoma
Begin in the thin flat cells that line the
bottom of the cervix. This type of cervical
cancer accounts for 80 to 90 percent of
cervical
cancer.
Adenocarcinoma
Develop in the glandular cells that line the
upper portion of the cervix. These cancers
make up 10 to 20 percent of cervical
cancer.
Sometimes both types of cells are involved
in cervical cancer, other types of cancer
can develop in the cervix, but these are
rare. Like metastatic cervical cancer, they
spread to other parts of body.
Symptoms
When present, common symptoms of
cervical cancer:
Normally appear in the form of a
cauliflower like growths, may also be flat
they can be found on the inside and the
outside of the vagina. These growths may
take weeks or even an year to show after
having sex with an infected partner
[5]
.
Vaginal Bleeding
This includes bleeding between periods,
after sexual intercourse or postmenopausal
bleeding.
Unusual Vaginal Discharge
A watery, pink or swelling discharge is
common.
Pelvic Pain
Pain during intercourse or at other times
may be a sign of abnormal changes to the
cervix or less serious condition.
Signs of Advanced Stages of Cervical
Cancer
o Cervical cancer may spread within
the pelvis, to the lymph nodes or
else, where in the body signs of
advanced cervical cancer includes:
o Weight loss,
o Back pain,
o Leg pain or swelling,
o Involuntary, ongoing release of
urine or feces,
o Bone-fracture,
o Fatigue[6].
Screening Tests for Cervical Cancer
It usually takes years for cervical cancer to
develop. During this time, HPV infection
can cause cells on or around the cervix to
become abnormal which may lead to
cancer.
HPV Caused Cervical Cancer Bathula et al.
__________________________________________________________________________________________
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 4
The two cervical cancer screening methods
are:
a. Pap test,
b. HPV test.
Pap Test (Sometimes called cervical
cytology screening)
o The Pap test is one of the most
reliable and effective cancer
screening methods available for
women. It checks for changes on
your cervix so that problems can be
found and removed before they
turn into cancer.
o Here in the Pap test, the health care
provider will use a swab to collect
cells from your cervix and check
under a microscope for any
problems.
o Women should start getting Pap
tests three years after the first sex,
or by age of 21, whichever comes
first.
o Women should get Pap test at least
once every three years.
HPV Test
o HPV test may also be used with the
Pap test in certain cases. The HPV
test looks for HPV, the virus that
can cause cell changes in the
cervix.
o The HPV test can identify 13–14 of
the high-risk types of HPV
[7]
.
HPV Vaccine against Cervical Cancers
and Genital Warts
The vaccine has been widely tested in girls
and women. It is safe and has no side
effects. The most common side effect is
soreness in the arm.
There are two types of HPV vaccines
namely:
a. Cervarix,
b. Gardasil.
Cervarix
o It is a 3-dose series.
o Only to females.
o Female: 11 or 12 years of age. This
age group has the best response to
the vaccine, and the vaccine must
be given before sexual activity
begins. HPV vaccine can be started
at 9 years. It is also recommended
for females aged 13 through
26 years who have not been
vaccinated.
o Prevents most cases of cervical and
anal cancer in females if the
vaccine is given before a person is
exposed to HPV.
Gardasile
o A series of 3-dose series given for
both males and females.
o Female and male: 11 or 12 years of
age. This age group has the best
response to vaccine, and the
vaccine must be given before
sexual activity beings. HPV
vaccine started at 9 years. It is
recommended for females aged 13
through 26 years who have not
been vaccinated or did not finish
the 3-shot series.
o It is also recommended for males
aged 13 through 21 years who have
not been vaccinated or did not
finish the 3-shot series. It may be
given to males aged 22 through
26 years and should be given to
high-risk males aged 9 through
26 years
[8]
.
BIOLOGICAL MECHANISMS OF
HPV CARCINOGENESIS
In previous decades, our understanding of
cancer pathways was rudimentary and
often incorrect. In the face of such
uncertainty, arguments based on
assumptions of molecular biology were not
particularly convincing. However, with the
large body of work now available it is
possible to develop a reasonable
understanding of the ways in which cancer
may develop and ways in which HPV
infection can drive the process. Thus, we
can say with some confidence that it is
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 5
International Journal of Cell Biology and Cellular Processes
Vol. 1: Issue 1
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plausible for HPV to cause cervical cancer
and, furthermore, we can describe with
reasonable clarity the general steps by
which HPV may do so. Of course there is
a lot of detail still to be revealed, but we
are well on our way to a factual basis for
understanding carcinogenesis rather than
the guesswork and rudimentary models of
just two decades ago.
What follows is a description of selected
information that may illuminate salient
aspects of the natural history of HPV and
reasons why a mostly benign infectious
process sometimes results in malignancy.
It must be understood by readers that the
pathways are based on extensive
experimentation in biopsied human tissues,
in tissue culture, and other kinds of
molecular biology systems. However,
many details of pathway modifications and
aberrant pathway effects are speculative;
they have not been shown to occur inside
the relevant precancerous and cancerous
tissues of living hosts. However, despite
the many holes and inconsistencies, the
models are still quite compelling and
cohesive in facts. In future, we expect to
see these molecular models being tested in
human subjects.
Essentially all HPV types produce warty
lesions but only high risk types promote
the development of cervical cancer to any
appreciable extent. Such differences
between HPV types may seem surprising,
given the high DNA and structural
similarities. However, a large functional
divergence caused by small genetic
changes is the norm in many biological
systems. Variations in carcinogenic
potential among HPVs are principally
governed by the E6 and E7 proteins;
specifically by the capacities of these
proteins to interact with and alter or
destroy key cell cycle regulatory
molecules.
The progress and outcome of an HPV
infection depends on HPV type,
anatomical location, and the nature and
timing of local cellular and tissue
influences. Virions access basal and
parabasal cells in areas of erosion and viral
DNA enters the cell nuclei. Establishment
is tied to the tissue proliferative activity of
epithelial cells and, in the case of
extensive tissue repair; the viral infection
can become widely disseminated.
Persistence in keratinocytes is variable and
related to viral type. Finally, integration of
viral DNA may occur, resulting in lifetime
persistence of certain viral genes in the
cell. In the cervix, detectable infection by
low risk HPV types is of relatively short
duration, whereas infection by most high
risk types lasts longer. On occasions, such
infections may become persistent and last
for years or even decades; it is in these
cases that the risk of cancer is increased.
The establishment of HPV infection can be
modulated by a competent and primed
immune system. In vitro experiments have
revealed an inverse association between
the degree of cervical neoplasia and
interleukin 2 production by peripheral
blood mononuclear cells in response to
HPV-16 E6 and E7 peptides. Women with
CIN 3 or cancer appear to have a
decreased ability to mount a T helper cell
type 1 (Th1) mediated immune response to
HPV E6/E7, compared with women with
CIN 1 or HPV infected women without
lesions. It is possible that a Th1 mediated
cellular immune response could play a role
in host immunological control of HPV
infection and that lack of such an
appropriate response may predispose to the
progression of cervical disease.
If HPV enters immature metaplastic basal
stem cells that are actively dividing the
infection can become widely dispersed and
persistent. In contrast, if infection occurs
only in the parabasal transit amplifying
cells the infection may become transient or
HPV Caused Cervical Cancer Bathula et al.
__________________________________________________________________________________________
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 6
quasi-persistent. The size, histological
grade, and duration of lesions can depend
on the number and types of cells that
become infected by HPV. In either
transient or persistent infection there may
be periodic viral genome amplification,
depending on the activity of the infected
daughter cells, which can lead to variable
detection of the lesion by HPV DNA or
Pap tests.
There is an important difference in host–
virus interactions of carcinogenic HPV
types and low risk HPV types; the former
have activities that more strongly interfere
with a set of host cell cycle control
mechanisms. It is therefore useful to
consider the effects of carcinogenic HPV
types. HPV initially replicates to reach
about 25–50 genomes/cell. The process by
which this occurs is tied to the activities of
four multifunctional viral proteins E1, E2,
E6, and E7. One key activity of E7 is to
overcome the pRB tumour suppressor
block. Binding of E7 to pRB and its
related members result in the liberation of
E2F transcription factors, which play key
roles in promoting host cell and viral DNA
synthesis. E7 also binds and activates
cyclin complexes, such as p33–cyclin
dependent kinase 2, which control
progression through the cell cycle. E6
protein can overcome the p53 protective
control pathways, which are important in
preventing the genetic damage that may
lead to cancer.
HPV genomes attach to host chromatin via
the E2 protein and replicate at a steady
state, once for each cell division. It has
been speculated that a benefit of this
tethered theta mode of replication is that
the loss of HPV DNA from cells by non-
disjunction is minimised and the presence
of low amounts of HPV DNA in cells is
less likely to be detected by intracellular
interference mechanisms that could trigger
apoptosis. As cells differentiate and move
to the surface there is a normal
differentiation and maturation process that
leads to pyknotic condensed cells that
slough from the tissue. However, in virally
infected tissues there is activation of
unscheduled DNA replication in some
spinous cells, accompanied by a switch in
viral DNA replication to the rolling circle
mode, which leads to the production of
viral progeny. This reactivation of DNA
synthesis can be detected by the presence
of punctate proliferating cell nuclear
antigen tissue staining (a protein with a
key role in DNA replication) and the
presence of HPV virions in a subset of
upper layer cells.
HPV E7 proteins of both low and high risk
types have an ability to promote
unscheduled DNA replication in spinous
cells. It is believed that the extent to which
E7 stimulates cells, and the tissue location
at which such stimulation occurs, is
important to malignant progression.
Spinous cells respond to E7 by the
production of a cyclin kinase inhibitor,
p21cip1, translated from sequestered
RNA. In basal and parabasal cells existing
mRNA for p21cip1 is not available and the
protein is typically produced from new
transcripts stimulated by p53; however, if
p53 is inactivated by E6 the p21cip1
cannot be made. Spinous cells thus have a
control advantage lacking in basal cells.
Interestingly, high amounts of E7 can bind
and block the activity of p21cip1. The
relative amounts of E7 and p21cip1 are
believed to determine whether cells re-
enter S phase and replicate viral DNA or
whether cells block viral production. The
inspection of tissues reveals a mutually
exclusive set of spinous cells with high
amounts of either E7 or p21cip1. Cells in
which E7 overcomes the p21cip1 block
can become koilocytes and produce viral
particles. This balance can explain the
patchy expression of the HPV effect in
infected tissues. A key function of the E6
oncoprotein is the destruction of p53, a
protein that is activated upon
phosphorylation via DNA damage sensing
proteins. Activated p53 stops the cell cycle
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 7
International Journal of Cell Biology and Cellular Processes
Vol. 1: Issue 1
www.journalspub.com
in the G phase as a result of direct
stimulation of p21cip1 by this molecule.
Alternatively, in the case of major DNA
damage or high amounts of viral
replication, p53 may activate an apoptotic
pathway. E7 also interferes with
alternative non-p53 dependent apoptotic
pathways. Thus, in the case of E6
mediated destruction of p53, cells are
unable to prevent the accumulation of
genetic mutations. Cells have other
defensive homeostasis mechanisms, but E6
and E7 have counter functions that can lift
the blocks and direct cells to enter S phase.
Therefore, it appears that the development
of malignancy is a consequence of an
aberrant host-virus interaction. A
potentially important event in this process
is the aberrant regulation of E6/E7
expression. In low grade CIN lesions,
E6/E7 expression is mainly found in
differentiating spinous cells that have
withdrawn from the cell cycle. In high
grade CIN lesions and cervical
carcinomas, strong E6/E7 expression is
seen in the proliferating cell
compartments.
HPV DNA is frequently incorporated into
the host genomes in cancers in such a way
that the E2 repressor protein is inactive
and allows overexpression of E6 and E7.
In cases where HPV integration is not
detected, other mutations can be shown in
the E2 protein or in repressor functions,
such as YYI sites, which appear to allow
continuous expression of the E6 and E7
oncoproteins. Yet another way in which
E6 and E7 could be overexpressed in
proliferating cells is by the generation of
chimaeric HPV mRNAs encoding the E6
and E7 proteins that have host sequences
at their 3′ termini. Such RNAs are
frequently more stable and allow more
protein to be synthesized.
In persistent HPV lesions, viral genomes
in the basal cells continue to stimulate the
cells to ignore the DNA damage that may
be accumulating. Cell stimulation by E6
and E7 of high risk carcinogenic HPV
types produces clones with an extended
life span that have passed a point called
mortality 1 or M1, although the cells are
still not immortal. An important step in
immortalisation is related to telomeres.
Normally, telomeres shorten every cell
generation and once they reach a critical
length the cells die. Telomere length is
maintained by telomerase, which in
combination with a capping function, can
stabilize and even lengthen telomeres,
allowing cells to continue dividing. E6 can
activate telomerase and additional cell
mutation(s) can then stabilize the
telomeres and allow cells to pass a second
stage called mortality 2 or M2. It is not
known many additional independent
mutations are needed to transform
immortalised cells fully to malignancy.
One set of mutations allows the cell to
break through the basement membrane by
eliciting a set of novel proteases. Another
mutation(s) allows cells to move in the
dermis. Undoubtedly, metastatic cells have
accumulated many additional mutations
that allow them to create their own
microenvironment for survival in foreign
parts of the body
[9]
.
CONCLUSION
Cervical cancer screening has successfully
decreased squamous cell cervical cancer
incidence and mortality. The American
Cancer Society (ACS) Guideline for the
Early Detection of Cervical Cancer was
last reviewed and updated in 2002; for the
first time, those recommendations
incorporated options including liquid-
based cytology and human papillomavirus
(HPV) DNA testing. Since that time, two
vaccines against the most common cancer-
causing HPV types have been developed
and tested in clinical trials
[2–7]
. Numerous
studies have been published on the
efficacy of these vaccines, as well as
issues related to policy and
implementation
[10]
.
HPV Caused Cervical Cancer Bathula et al.
__________________________________________________________________________________________
IJCBCP (2015) 1–8 © JournalsPub 2015. All Rights Reserved Page 8
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Preschool diet and adult risk of breast cancer
Karin B. Michels1–3*, Bernard A. Rosner3,4, Wm. Cameron Chumlea5, Graham A. Colditz2,3 and Walter C. Willett2,3,6
1Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
2Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
3Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
4Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA
5Departments of Community Health and Pediatrics, Lifespan Health Research Center,
Wright State University School of Medicine, Dayton, OH, USA
6Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
Events before puberty may affect adult risk of breast cancer. We
examined whether diet during preschool age may affect a wom-
an’s risk of breast cancer later in life. We conducted a case-con-
trol study including 582 women with breast cancer and 1,569 con-
trols free of breast cancer selected from participants in the
Nurses’ Health Study and the Nurses’ Health Study II. Informa-
tion concerning childhood diet of the nurses at ages 3–5 years was
obtained from the mothers of the participants with a 30-item food-
frequency questionnaire. An increased risk of breast cancer was
observed among woman who had frequently consumed French
fries at preschool age. For one additional serving of French fries
per week, the odds ratio (OR) for breast cancer adjusted for adult
life breast cancer risk factors was 1.27 (95% confidence interval
[CI] 5 1.12–1.44). Consumption of whole milk was associated with
a slightly decreased risk of breast cancer (covariate-adjusted OR
for every additional glass of milk per day 5 0.90; 95% CI 5 0.82–
0.99). Intake of none of the nutrients calculated was related to the
risk of breast cancer risk in this study. These data suggest a possi-
ble association between diet before puberty and the subsequent
risk of breast cancer. Differential recall of preschool diet by the
mothers of cases and controls has to be considered as a possible
explanation for the observed associations. Further studies are
needed to evaluate whether the association between preschool diet
and breast cancer is reproducible in prospective data not subject
to recall bias.
‘ 2005 Wiley-Liss, Inc.
Key words: breast cancer; nutrition; epidemiology; early life
Factors during early life may play a role in the etiology of
chronic disease. Fetal nutrition and infant growth seem to be pre-
dictive of adult risk of cardiovascular disease, hypertension, diabe-
tes, and obesity.1–5 In addition, maternal weight and diet during
pregnancy, possibly mediated by fetal malnutrition, have been
related to coronary heart disease.6,7 Similarly, nutrition in early
life is linked to later heart disease.8,9
A high birthweight has been associated with the risk of breast
cancer in a number of studies,10–20 but whether this association
operates through fetal nutrition, hormonal factors or other mech-
anisms has not been resolved. Breast tissue is largely undiffer-
entiated until puberty and may be particularly susceptible to
carcinogenic influences during that age period.21,22 Migrant studies
indicate that rates of breast cancer change after migration primarily
affecting the next generation and thus are compatible with modula-
tion of risk during early life.23–25 The impact of radiation exposure
at a young age on breast cancer risk as an adult lends further support
to the existence of a susceptible time period in early life.26–28
DeWaard and Trichopoulos29 and Willett30 have proposed that
an energy-rich diet during puberty and adolescence affects the
growth of mammary glands and enhances the occurrence of pre-
cancerous lesions. The observation that women who experienced
the World War II famine in Norway during puberty had a reduced
risk of breast cancer later in life supports the importance of diet—
whether composition or total energy intake—during early life.31
A number of breast cancer risk factors, such as tallness,32 body
size,32,33 rapid growth during childhood34 and early age at menarche,35
are affected, at least in part, by childhood diet. Although taller
final height,36 an early age at peak growth34 and an early age at
menarche35 are associated with an increase in the risk of breast
cancer in adulthood, a high childhood body mass is inversely
related to the risk of breast cancer.33,37,38
Our present study explores the role of diet during preschool age
on future risk of breast cancer. Information on preschool diet was
gathered from the mothers of participants of the Nurses’ Health
Study and the Nurses’ Health Study II.
Population and methods
The Nurses’ Mothers’ Study is a case-control study nested in
2 prospective cohort studies, the Nurses’ Health Study (NHS) and
the Nurses’ Health Study II (NHS II). These cohorts consist of
121,700 and 116,678 female registered nurses, respectively, born
between 1921–1965. For both cohorts, biennial self-administered
questionnaires provide updated information on demographic,
anthropometric, and lifestyle factors and on newly diagnosed dis-
eases, including breast cancer.
Documentation of breast cancer
On each biennial questionnaire we ask whether breast cancer
has been diagnosed and, if so, the date of diagnosis. We also rou-
tinely search the National Death Index for deaths among women
who did not respond to the questionnaires. We ask women who
report breast cancer (or next of kin, for those who have died with-
out reporting the incident disease) for permission to review the rel-
evant hospital records to confirm the diagnosis. Pathology reports
confirmed a breast cancer diagnosis among >99% of participants
for whom records could be obtained. The analysis presented in this
paper was restricted to cases of invasive breast cancer.
The Nurses’ Mothers’ Study
Details of the Nurses’ Mothers’ Study have been described else-
where.9 Briefly, in 1993 participants in the Nurses’ Health Studies
who had been diagnosed with incident breast cancer up to 1993
and had not reported the death of their mother on a previous ques-
tionnaire were identified, and 2 participants free of breast cancer
at that time who belonged to the same cohort were matched to
each case by year of birth. Matching occurred before it was known
whether the mother was alive and able to participate. Because
some mothers had died or were unable to participate, matching
was incomplete for a substantial number of cases and controls. Of
mothers still living and able to participate, 91% completed and
returned our questionnaire. The study population consisted of 582
Grant sponsor: Massachusetts Department of Public Health.
*Correspondence to: Obstetrics and Gynecology Epidemiology Center,
Brigham and Women’s Hospital, Harvard Medical School, 221 Longwood
Avenue, Boston, MA 02115. Fax: 11-617-732-4899.
E-mail: kmichels@rics.bwh.harvard.edu
Received 14 March 2005; Accepted after revision 10 June 2005
DOI 10.1002/ijc.21407
Published online 10 August 2005 in Wiley InterScience (www.interscience.
wiley.com).
Int. J. Cancer: 118, 749–754 (2006)
‘ 2005 Wiley-Liss, Inc.
Publication of the International Union Against Cancer
nurses with invasive breast cancer and 1,569 nurses free of breast
cancer in 1993.
The mothers were asked to complete a mailed, self-adminis-
tered questionnaire on perinatal and early life events of their
nurse-daughter including information on foods consumed by the
daughter during preschool years. The mothers were asked how
often their nurse-daughter ate or drank an average serving of any
of the 30 food items listed on the questionnaire when she was 3–
5 years old. The dietary part of the questionnaire was structured
like a semiquantitative food-frequency questionnaire (FFQ).39
Information on adult breast cancer risk factors was assembled
from the large databases already established for each of the two
ongoing cohort studies. These variables had been reported by the
nurses themselves and included year of birth, age at menarche,
parity, age at first birth, height and weight. Data ascertained at
baseline before diagnosis of breast cancer among the cases, were
used in the analysis (1976 for NHS and 1989 for NHS II). A fam-
ily history of breast cancer was available from the nurses’ reports
(mother or sisters with breast cancer) as well as from the mothers’
reports (mother herself, grandmothers, or aunts with breast
cancer). We created a variable indicating first- or second-degree
relative(s) with breast cancer.
Fels Longitudinal Study diet assessment validation
The validity of the dietary information provided by the mothers
in the present study could not be directly assessed. To address this
problem, we conducted a small validation study in a similar popu-
lation, the Fels Longitudinal Study. We sampled 33 female Fels
participants born between 1929–195040 for whom 7-day diet
records were kept by their mothers when these participants were
3–6 years old.41 In 1997, we mailed the food questionnaire used in
the Nurses’ Mothers’ Study to the respective Fels mothers asking
them to recall their daughters’ diet during preschool age. The
mothers’ ages in Fels ranged from 60–93 years. We obtained 29
completed diet questionnaires from the mothers. Spearman corre-
lations of mean daily consumption of foods reported by the moth-
ers on the 7-day diet records and on the FFQ were 0.46 (p 5 0.02)
for whole milk, 0.37 (p 5 0.07) for broccoli and 0.36 (p 5 0.07)
for French fries.
Statistical analysis
Frequencies of intake of the individual foods as specified on the
questionnaire were converted into servings/day (e.g., number of
glasses of milk per day) or servings/week depending on the food
and used as continuous variables.
For 718 nurses, complete data on the frequencies of food intake
were available, but for 1,433 participants, data were missing or the
mother did not remember the frequency of intake of one or more
food items. On average, mothers marked the ‘‘don’t remember’’
option for 8.5% of food items and left 3.8% of food items blank.
Overall, the proportion of missingness (blanks and don’t remem-
ber) ranged from 4.5% (for milk) to 21% (for cheese).
Multiple imputation was used to account for dietary data not
observed.42–44 Multiple imputation replaces each missing value
with a number of acceptable values representing a distribution of
possibilities. We created 5 imputed data sets by replacing missing
values with draws from the conditional distribution of the missing
values given the observed values. Each of the 5 imputed data sets
was analyzed as if it were complete; the results from the 5 data
sets were then combined in a manner that takes account of both
the between-imputation and within-imputation variability. The
multiple imputation method used in the present analysis does not
involve sampling of the parameter values in the imputation model
but assumes that the parameter estimates are known without error,
and are therefore not changed at each imputation by adding error
to them.44
Nutrients were calculated from nutrient composition tables for
the year the nurse was 3 years old; using these tables from 1929–
1970 captured changes in the fortification of foods during this time
period when calculating nutrient intake. Nutrient residuals were
obtained by regressing nutrient intake on the log scale on mean-
centered log values of energy intake and exponentiating the result-
ing residuals. The risk of breast cancer among women in the high-
est quintile of nutrient intake was compared to that among women
in the lowest quintile. Nutrient intake was also considered as a
continuous variable, and the risk of breast cancer was estimated
per one standard deviation increase in the particular nutrient using
continuous residuals divided by their standard deviation.
Odds ratios (OR) were obtained using unconditional logistic
regression models. The association between food consumption
and breast cancer was estimated for each individual food item, for
combinations of foods, and for nutrients. Regression models
included adult risk factors for breast cancer obtained from the
Nurses’ Health Studies’ questionnaires: year of birth, age at
menarche, parity, age at first birth, family history of breast cancer
and body mass index (BMI) in 1976 for NHS and in 1989 for
NHS II.
Results
Characteristics of the 582 breast cancer cases and 1,569 controls
are listed in Table I. Among cases, 63% were premenopausal at
diagnosis, 27% were postmenopausal, and 10% were of uncertain
menopausal status. Older age at menarche, higher parity, and
younger age at first birth were associated with reduced risk of
breast cancer in this population. Higher BMI at baseline was asso-
TABLE I – ADULT CHARACTERISTICS OF PARTICIPANTS OF THE NURSES’
HEALTH STUDY AND THE NURSES HEALTH STUDY II WITH BREAST
CANCER (CASES) AND WITHOUT BREAST CANCER (CONTROLS) WHOSE
MOTHER PARTICIPATED IN THE NURSES’ MOTHERS STUDY
Characteristic
Cases (n 5 582) Controls (n 5 1,569)
No. % No. %
NHSI 461 79 1303 83
NHSII 121 21 266 17
Birth year
1921–1925 16 3 93 6
1926–1930 68 12 176 11
1931–1935 105 18 307 20
1936–1940 121 21 347 22
1941–1945 136 23 331 21
1946–1950 70 12 169 11
1951–1955 40 7 86 5
1956–1960 20 3 47 3
1961–1963 6 1 13 1
Age at menarche1
<511 134 23 371 24 12 167 29 427 27 13 179 31 461 30 14 71 12 182 12 151 27 5 117 8
Parity
Nulliparous 69 12 174 11
1 59 10 133 8
2 199 34 500 32
3 155 27 405 26
41 100 17 357 23
Age at first birth
<524 290 57 859 62
25–29 183 36 437 31
301 40 8 99 7
Body Mass Index1
<521 217 37 437 28 21.1–23 165 28 470 30 23.1–25 99 17 269 17 25.1–29 66 11 232 15 >29 35 6 156 10
Family history of breast cancer
No 480 82 1395 89
Yes 102 18 174 11
1Numbers do not always add up to the entire study population
because of missing information on some variables.
750 MICHELS ET AL.
ciated with a lower risk of breast cancer among these mostly
premenopausal women. Family history of breast cancer was asso-
ciated with increased breast cancer risk. The median year of birth
of the mothers was 1914 for case mothers and 1913 for control
mothers.
The results of the logistic regression analysis for all individual
foods are provided in Table II. Regular consumption of French
fries was associated with a significantly increased risk of breast
cancer, with an OR of 1.27 for one additional serving/week (95%
CI 5 1.12–1.44). A slightly decreased risk of breast cancer was
apparent for regular consumption of whole milk, although the
association was of borderline statistical significance (OR per addi-
tional glass of whole milk/day 5 0.90; 95% CI 5 0.82–0.99).
Broccoli consumption was associated with an elevated OR for
breast cancer of borderline statistical significance in the unad-
justed analysis (OR 5 1.24; 95% CI 5 0.98–1.57), but the associ-
ation was attenuated after covariate-adjustment (OR 5 1.16; 95%
CI 5 0.91–1.47).
Among covariates, the most notable correlations with foods
were found for year of birth, possibly reflecting time trends in the
availability of certain foods (the consumption of ice cream, orange
juice, hot dogs, and French fries became more common over time,
consumption of other types of potatoes became less common) or
changes in habits (margarine partly replaced butter, and cod
liver oil became less popular over time and was increasingly
replaced by vitamin supplements). Changes in estimates from the
covariate-adjusted analysis compared to the unadjusted regression
model are accounted for mainly by adjustment for year of birth
(Table II).
The estimates changed for some foods considerably after adjust-
ing for all covariates. After controlling for other covariates, pri-
marily year of birth, we found that the association of breast cancer
risk with broccoli consumption was attenuated, whereas the esti-
mates for consumption of orange juice, cabbage and ground beef
where somewhat strengthened. The strongest changes in the odds
ratios after covariate adjustment were for broccoli and liver con-
sumption; these 2 foods were the least frequently consumed during
childhood, and therefore these estimates were the least stable. The
estimates for French fries (OR 5 1.27; 95% CI 5 1.12–1.44) and
for milk (OR 5 0.90; 95% CI 5 0.82–0.99) did not change appre-
ciably after covariate adjustment.
Foods associated with breast cancer risk were considered
together in a multiple regression model unadjusted for non-dietary
covariates to explore the independent contribution of each food.
French fries were paired with ground beef to capture a fast food
dietary pattern (French fries: OR 5 1.27; 95% CI 5 1.12–1.43),
milk (French fries: OR 5 1.27; 95% CI 5 1.13–1.43), and broc-
coli (French fries: OR 5 1.27; 95% CI 5 1.13–1.43). The results
indicated that the association between consumption of French fries
and risk of breast cancer was not explained by consumption of any
of the other 3 foods. The relation of ground beef consumption with
breast cancer risk was somewhat diminished by the inclusion of
French fries, indicating that the 2 foods might have been custom-
arily consumed together (ground beef: OR 5 1.12; 95% CI 5
0.64–1.97). The consumption of milk and French fries was not
strongly correlated (whole milk: OR 5 0.91; 95% CI 5 0.83–
1.00) nor was that of broccoli and French fries (broccoli: OR 5
1.22; 95% CI 5 0.97–1.54).
The distributions of caloric nutrient intake were within the
range reasonable for girls of preschool age (Table III). No impor-
tant relation between intake of any of the calculated nutrients and
risk of breast cancer was observed in this study (Table III).
Discussion
In our study, which was embedded in the 2 Nurses’ Health
Studies, we found a significant association between frequent con-
sumption of French fries during preschool age as reported by the
mothers of the study participants and breast cancer risk later in
life. For one additional serving of French fries per week during
their preschool years, women had a 27% increased risk of breast
cancer when they were adults. Although consumption of milk and
broccoli were marginally associated with adult breast cancer risk,
no other food or nutrient appeared as strongly correlated with
adult breast cancer risk as did French fries. As consumption of
potatoes themselves was not associated with the risk of breast can-
cer, the preparation of French fries, namely the use of frying fat
high in saturated fats and trans-fatty acids, may be of relevance.
During the period of exposure spanning the years 1924–1970,
preparation of French fries changed: solid shortening was used in
the earlier years, and hydrogenated oils were used in later years.
French fries have also been found to contain acrylamide, an indus-
trial chemical that has been classified as a likely human carcino-
gen due to its DNA-reactive mechanism but was not related to
breast cancer in a Swedish study.45,46
Frequent consumption of French fries did not seem to be a
marker of ‘‘fast food’’ habits, because we did not observe a simi-
lar association of breast cancer risk with frequent consumption of
hot dogs or ground beef. Consumption of French fries, however,
could be a marker of a dietary pattern that we might not have been
able to detect because we assessed only a limited number of foods
with our diet questionnaire.
To our knowledge, no other data on the association between
preschool diet and breast cancer risk are available. The role of
childhood or adolescent diet recalled by the participants them-
selves has been explored in four case-control studies and two
TABLE II – OR AND 95% CI OF ADULT BREAST CANCER AMONG
PARTICIPANTS OF THE NURSES’ HEALTH STUDY AND THE
NURSES’ HEALTH STUDY II WHOSE MOTHER PARTICIPATED
IN THE NURSES’ MOTHERS STUDY1
Food
Unadjusted Adjusted2
OR 95% CI OR 95% CI
Servings/day
Whole milk 0.91 0.83–1.00 0.90 0.82–0.99
Skim or lowfat milk 1.04 0.83–1.29 1.06 0.84–1.33
Cheese 1.07 0.77–1.49 1.04 0.78–1.39
Margarine 1.03 0.94–1.13 1.03 0.94–1.14
Butter 0.93 0.86–1.01 0.94 0.87–1.02
Apples 0.94 0.65–1.36 0.97 0.67–1.42
Oranges 1.09 0.75–1.58 1.02 0.70–1.49
Orange juice 0.95 0.74–1.22 0.85 0.65–1.10
Eggs 0.98 0.62–1.57 1.11 0.69–1.80
Ground beef 1.33 0.76–2.32 1.44 0.81–2.57
Meat as main dish 0.76 0.47–1.22 0.75 0.46–1.22
Meat as sandwich or
mixed dish
0.81 0.48–1.36 0.85 0.49–1.46
Bread 0.96 0.88–1.06 0.98 0.89–1.08
Potatoes 0.98 0.63–1.54 1.06 0.66–1.69
Cereal 1.03 0.73–1.45 0.97 0.67–1.42
Cookies 1.06 0.95–1.19 1.06 0.94–1.19
Multiple vitamins 0.89 0.66–1.21 0.77 0.55–1.06
Cod liver oil 0.90 0.62–1.33 1.03 0.68–1.55
Servings/week
Ice cream 1.06 0.98–1.15 1.04 0.96–1.13
Cabbage/coleslaw 1.03 0.87–1.22 1.10 0.92–1.31
Broccoli 1.24 0.98–1.57 1.16 0.91–1.47
Raw carrots 1.01 0.95–1.08 1.00 0.94–1.08
Cooked carrots 1.05 0.97–1.14 1.05 0.97–1.15
Cooked spinach 0.95 0.84–1.07 0.96 0.88–1.04
Hot dogs 0.95 0.83–1.09 0.96 0.83–1.10
Chicken 0.99 0.89–1.09 0.99 0.89–1.09
Fish/tuna 1.09 0.97–1.22 1.08 0.96–1.21
Liver 0.91 0.61–1.37 1.07 0.70–1.63
Rice 1.02 0.91–1.14 1.03 0.92–1.15
French fries 1.27 1.13–1.43 1.27 1.12–1.44
1Per serving increase of foods/day or week consumed at preschool
age. OR, odds ratio; CI, confidence interval.–2Adjusted for year of
birth, age at menarche, parity, age at first birth, family history of
breast cancer, and adult body mass index.
751PRESCHOOL DIET AND RISK OF BREAST CANCER
T
A
B
L
E
II
I
–
O
R
A
N
D
9
5
%
C
I
O
F
A
D
U
L
T
B
R
E
A
S
T
C
A
N
C
E
R
A
M
O
N
G
P
A
R
T
IC
IP
A
N
T
S
O
F
T
H
E
N
U
R
S
E
S
’
H
E
A
L
T
H
S
T
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D
Y
A
N
D
T
H
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N
U
R
S
E
S
’
H
E
A
L
T
H
S
T
U
D
Y
II
W
H
O
S
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M
O
T
H
E
R
P
A
R
T
IC
IP
A
T
E
D
IN
T
H
E
N
U
R
S
E
S
’
M
O
T
H
E
R
S
S
T
U
D
Y
1
N
u
tr
ie
n
t2
P
ar
am
et
er
Q
1
Q
2
Q
3
Q
4
Q
5
O
R
/I
S
D
in
cr
ea
se
in
in
ta
k
e
T
o
ta
l
ca
lo
ri
es
M
ea
n
in
ta
k
e
5
5
8
8
3
0
1
,0
1
9
1
,1
9
8
1
,4
6
6
U
n
ad
ju
st
ed
O
R
1
.0
1
.1
1
(0
.8
2
–
1
.5
1
)
0
.9
(0
.6
7
–
1
.2
2
)
1
.1
5
(0
.8
4
–
1
.5
7
)
1
.0
2
(0
.7
5
–
1
.3
9
)
1
.0
6
(0
.9
6
–
1
.1
7
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.1
5
(0
.8
4
–
1
.5
9
)
0
.9
1
(0
.6
7
–
1
.2
5
)
1
.1
9
(0
.8
7
–
1
.6
5
)
1
.0
6
(0
.7
7
–
1
.4
6
)
1
.0
7
(0
.9
7
–
1
.1
9
)
P
ro
te
in
(
g
)
M
ea
n
in
ta
k
e
2
3
.3
3
5
.6
4
4
.1
5
1
.8
6
3
.8
U
n
ad
ju
st
ed
O
R
1
.0
1
.1
9
(0
.8
7
–
1
.6
2
)
1
.0
9
(0
.8
1
–
1
.4
8
)
1
.0
2
(0
.7
6
–
1
.3
8
)
1
.1
5
(0
.8
5
–
1
.5
6
)
1
.0
2
(0
.9
3
–
1
.1
3
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.2
1
(0
.8
9
–
1
.6
6
)
1
.1
2
(0
.8
2
–
1
.5
2
)
1
.0
5
(0
.7
8
–
1
.4
3
)
1
.2
1
(0
.8
8
–
1
.6
4
)
1
.0
3
(0
.9
3
–
1
.1
4
)
C
ar
b
o
h
y
d
ra
te
s
(g
)
M
ea
n
in
ta
k
e
5
3
.9
8
1
.3
1
0
1
.3
1
2
0
.1
1
5
0
.0
U
n
ad
ju
st
ed
O
R
1
.0
0
.9
0
(0
.6
6
–
1
.2
2
)
0
.9
7
(0
.7
1
–
1
.3
2
)
0
.8
9
(0
.6
5
–
1
.2
0
)
0
.9
4
(0
.6
9
–
1
.2
8
)
0
.9
9
(0
.9
0
–
1
.0
9
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
.8
8
(0
.6
4
–
1
.2
2
)
0
.9
6
(0
.6
9
–
1
.3
4
)
0
.9
1
(0
.6
6
–
1
.2
6
)
0
.9
7
(0
.7
0
–
1
.3
5
)
1
.0
1
(0
.9
2
–
1
.1
2
)
V
eg
et
ab
le
fa
t
(g
)
M
ea
n
in
ta
k
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2
.5
4
.7
7
.1
1
1
.0
1
8
.7
U
n
ad
ju
st
ed
O
R
1
.0
1
.0
3
(0
.7
5
–
1
.4
0
)
1
.0
4
(0
.7
6
–
1
.4
2
)
0
.9
7
(0
.7
1
–
1
.3
2
)
0
.9
2
(0
.6
8
–
1
.2
5
)
0
.9
9
(0
.8
9
–
1
.0
9
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.0
3
(0
.7
5
–
1
.4
2
)
1
.0
9
(0
.7
9
–
1
.5
0
)
0
.9
8
(0
.7
1
–
1
.3
6
)
0
.9
2
(0
.6
7
–
1
.2
7
)
0
.9
9
(0
.8
9
–
1
.1
0
)
A
n
im
al
fa
t
(g
)
M
ea
n
in
ta
k
e
1
9
.3
3
1
.6
4
0
.2
4
8
.7
6
2
.3
U
n
ad
ju
st
ed
O
R
1
.0
0
.9
4
(0
.7
0
–
1
.3
0
)
1
.1
1
(0
.8
1
–
1
.5
1
)
1
.0
4
(0
.7
6
–
1
.4
1
)
1
.0
9
(0
.8
0
–
1
.4
9
)
1
.0
5
(0
.9
5
–
1
.1
5
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
.9
3
(0
.6
8
–
1
.2
8
)
1
.0
7
(0
.7
7
–
1
.4
8
)
1
.0
3
(0
.7
4
–
1
.4
3
)
1
.0
5
(0
.7
5
–
1
.4
8
)
1
.0
4
(0
.9
4
–
1
.1
5
)
S
at
u
ra
te
d
fa
t
(g
)
M
ea
n
in
ta
k
e
1
0
.7
1
7
.8
2
2
.9
2
7
.6
3
5
.4
U
n
ad
ju
st
ed
O
R
1
.0
1
.0
9
(0
.8
1
–
1
.4
8
)
1
.3
5
(0
.9
9
–
1
.8
4
)
1
.0
7
(0
.7
9
–
1
.4
5
)
1
.1
8
(0
.8
7
–
1
.6
1
)
1
.0
4
(0
.9
5
–
1
.1
5
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.1
9
(0
.8
6
–
1
.6
5
)
1
.3
8
(0
.9
7
–
1
.9
5
)
1
.1
4
(0
.8
7
–
1
.7
8
)
1
.2
4
(0
.8
7
–
1
.7
8
)
1
.0
5
(0
.9
5
–
1
.1
6
)
L
in
o
le
ic
ac
id
(g
)
M
ea
n
in
ta
k
e
1
.5
2
.4
3
.2
4
.1
6
.4
U
n
ad
ju
st
ed
O
R
1
.0
0
.9
3
(0
.6
8
–
1
.2
7
)
0
.8
1
(0
.5
9
–
1
.1
0
)
1
.1
8
(0
.8
6
–
1
.6
2
)
0
.8
5
(0
.6
3
–
1
.1
6
)
0
.9
9
(0
.9
0
–
1
.0
9
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
.9
6
(0
.6
9
–
1
.3
4
)
0
.8
3
(0
.5
9
–
0
.1
6
)
1
.1
8
(0
.8
3
–
1
.6
8
)
0
.8
3
(0
.5
8
–
1
.1
9
)
0
.9
9
(0
.8
9
–
1
.0
9
)
D
ie
ta
ry
fi
b
er
(g
)
M
ea
n
in
ta
k
e
2
.7
4
.5
5
.8
7
.3
1
2
.2
U
n
ad
ju
st
ed
O
R
1
.0
0
.9
2
(0
.6
8
–
1
.2
6
)
0
.9
7
(0
.7
2
–
1
.3
2
)
1
.0
3
(0
.7
6
–
1
.4
1
)
0
.8
7
(0
.6
4
–
1
.1
8
)
0
.9
3
(0
.8
5
–
1
.0
2
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
.9
2
(0
.6
7
–
1
.2
7
)
0
.9
4
(0
.6
8
–
1
.2
9
)
0
.9
8
(0
.7
1
–
1
.3
7
)
0
.8
5
(0
.6
2
–
1
.1
8
)
0
.9
1
(0
.8
3
–
1
.0
1
)
S
u
cr
o
se
(g
)
M
ea
n
in
ta
k
e
3
.3
6
.4
9
.0
1
2
.9
1
9
.6
U
n
ad
ju
st
ed
O
R
1
.0
1
.0
3
(0
.7
5
–
1
.4
1
)
0
.9
2
(0
.6
7
–
1
.2
5
)
0
.9
7
(0
.7
1
–
1
.3
3
)
0
.7
8
(0
.5
8
–
1
.0
6
)
0
.9
5
(0
.8
6
–
1
.0
4
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.0
8
(0
.7
8
–
1
.4
9
)
0
.9
6
(0
.7
0
–
1
.3
2
)
1
.0
3
(0
.7
4
–
1
.4
3
)
0
.8
1
(0
.5
9
–
1
.1
2
)
0
.9
7
(0
.8
8
–
1
.0
7
)
F
o
la
te
(l
g
)
M
ea
n
in
ta
k
e
5
9
.2
9
6
.2
1
2
5
.6
1
5
7
.9
2
0
8
.7
U
n
ad
ju
st
ed
O
R
1
.0
1
.0
4
(0
.7
6
–
1
.4
1
)
0
.9
3
(0
.6
8
–
1
.2
6
)
1
.0
7
(0
.7
8
–
1
.4
7
)
0
.7
9
(0
.5
9
–
1
.0
8
)
0
.9
4
(0
.8
5
–
1
.0
3
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.0
4
(0
.7
5
–
1
.4
4
)
0
.9
5
(0
.6
9
–
1
.3
2
)
1
.1
7
(0
.8
4
–
1
.6
3
)
0
.9
6
(0
.6
3
–
1
.1
8
)
0
.9
6
(0
.8
7
–
1
.0
6
)
V
it
am
in
A
(I
U
)
M
ea
n
in
ta
k
e
2
,0
8
6
4
2
8
2
6
5
5
5
8
9
2
7
1
3
,5
9
7
U
n
ad
ju
st
ed
O
R
1
.0
0
.9
8
(0
.7
2
–
1
.3
4
)
0
.8
7
(0
.6
4
–
1
.1
9
)
1
.0
0
(0
.7
3
–
1
.3
7
)
0
.8
5
(0
.6
3
–
1
.1
5
)
0
.9
6
(0
.8
7
–
1
.0
6
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.0
0
(0
.7
2
–
1
.3
7
)
0
.8
9
(0
.6
5
–
1
.2
2
)
0
.9
6
(0
.6
9
–
1
.3
3
)
0
.8
6
(0
.6
2
–
1
.1
7
)
0
.9
5
(0
.8
6
–
1
.0
5
)
C
ar
o
te
n
e
(I
U
)
M
ea
n
in
ta
k
e
6
7
8
1
6
2
3
2
5
9
6
3
9
2
6
6
8
4
8
U
n
ad
ju
st
ed
O
R
1
.0
1
.0
0
(0
.7
3
–
1
.3
7
)
0
.8
2
(0
.6
0
–
1
.1
1
)
0
.8
4
(0
.6
1
–
1
.1
4
)
0
.8
2
(0
.6
0
–
1
.1
1
)
0
.9
0
(0
.8
2
–
0
.9
9
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
1
.0
2
(0
.7
4
–
1
.4
2
)
0
.8
2
(0
.6
0
–
1
.1
3
)
0
.8
5
(0
.6
2
–
1
.1
7
)
0
.8
5
(0
.6
1
–
1
.1
7
)
0
.9
1
(0
.8
3
–
1
.0
0
)
V
it
am
in
C
(m
g
)
M
ea
n
in
ta
k
e
1
5
.7
4
1
.4
6
9
.0
9
4
.3
1
4
6
.7
U
n
ad
ju
st
ed
O
R
1
.0
0
1
.0
4
(0
.7
6
–
1
.4
2
)
1
.0
6
(0
.7
7
–
1
.4
5
)
0
.8
2
(0
.6
0
–
1
.1
1
)
0
.8
2
(0
.6
0
–
1
.1
1
)
0
.9
1
(0
.8
3
–
1
.0
0
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
1
.1
0
(0
.7
9
–
1
.5
3
)
1
.2
5
(0
.8
9
–
1
.7
5
)
0
.9
2
(0
.6
6
–
1
.3
0
)
0
.9
2
(0
.6
7
–
1
.2
8
)
0
.9
4
(0
.8
5
–
1
.0
4
)
V
it
am
in
E
(m
g
)
M
ea
n
in
ta
k
e
1
.1
9
1
.9
4
2
.5
5
3
.2
3
4
.8
1
U
n
ad
ju
st
ed
O
R
1
.0
0
1
.0
9
(0
.8
0
–
1
.4
9
)
1
.0
3
(0
.7
6
–
1
.3
9
)
0
.8
9
(0
.6
6
–
1
.2
0
)
1
.0
4
(0
.7
7
–
1
.4
1
)
0
.9
6
(0
.8
7
–
1
.0
6
)
C
o
v
ar
ia
te
–
ad
ju
st
ed
O
R
1
.0
0
1
.0
9
(0
.8
3
–
1
.5
8
)
1
.0
1
(0
.7
3
–
1
.4
1
)
0
.8
4
(0
.6
0
–
1
.1
8
)
0
.9
4
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d
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al
s.
752 MICHELS ET AL.
cohort studies of breast cancer.47–52 In a study conducted in British
Columbia, Canada, a reduced breast cancer risk was associated with
self-reported frequent consumption of whole milk and vegetable
oils before age 13 and an increased risk with frequent consumption
of visible fat on meat.7 In a case-control study in Utah, women with
postmenopausal breast cancer reported higher intake of dietary
fiber, whereas women with premenopausal breast cancer reported
lower intake of fiber from grains.48 In that study, fat intake from
dairy products was associated with lower breast cancer risk.48
Potischman et al. reported no strong influence of adolescent diet on
breast cancer risk among women younger than age 45 years.49 High
meat consumption was reported more frequently among women
with breast cancer.49 In a cohort study conducted in Norway, partic-
ipants were asked to recall their milk consumption during childhood
and were then followed prospectively.51 A non-significant inverse
association between milk consumption during childhood and breast
cancer incidence in adulthood was observed.51
Information on eating patterns during adolescence has also been
retrospectively obtained from a subgroup of participants of the
Nurses’ Health Study.50 In a case-control study (of a different popu-
lation than that included in the present analyses), women with breast
cancer were marginally less likely than women without breast can-
cer to report high consumption of eggs during adolescence but
somewhat more likely to report high butter consumption.50 In a ret-
rospective study among 47,355 participants of the Nurses’ Health
Study II, high school diet was assessed in 1998 using a 131-item
FFQ and incident cases of breast cancer between 1989–1998 were
included.52 A high intake of vegetable fat and of vitamin E was
associated with a reduced risk of breast cancer, whereas a high gly-
cemic index was associated with an increased risk.
Information concerning exposure to the Dutch hunger winter
was used in a case-cohort analysis from the Netherlands Cohort
Study.53 No important association was found between residence in
the western part of the Netherlands during adolescence and breast
cancer risk, but individual data on energy intake or dietary compo-
sition were not available.
Validity of maternal recall of diet could not be tested in our
population. A number of studies have explored the validity of
parental reporting of their child’s preschool diet using an FFQ.54
Although mothers generally seemed to be able to report their pre-
school children’s diet with acceptable accuracy, the most notable
concern was overreporting of caloric intake, as well as fruits and
vegetables, dairy products, meat and fat, on the FFQ. We eval-
uated the validity of recall of preschool diet among mothers of
participants of the Fels Longitudinal Study, which used 7-day diet
records the mothers had kept decades earlier and found adequate
validity for some foods of interest in the current study. To our
knowledge, no other data are available on the validity or reprodu-
cibility of maternal or parental recall of children’s diet decades
later.
The observed association between consumption of French fries
and breast cancer risk may have resulted from bias or chance.
Nondifferential misclassification would probably have obscured
any true association. Because mothers were asked to recall their
daughter’s preschool diet after her case status was known, differ-
ential recall has to be considered as a possible explanation of the
observed association. If case mothers overestimated the foods con-
sumed that were considered ‘‘unhealthy,’’ consumption of hot
dogs and ice cream would be expected to have been overestimated
along with consumption of French fries. Reports by case mothers
of high consumption of French fries by their daughters, however,
stand out among all ‘‘unhealthy’’ foods.
Additional research is needed, particularly prospective studies
that eliminate the potential for recall bias, to confirm our findings
and to investigate further the role of diet during early life in breast
cancer etiology.
Acknowledgement
Supported by a grant from the Massachusetts Breast Cancer
Research Grants Program of the Massachusetts Department of
Public Health. The Nurses’ Health Study is supported by Public
Health Service Grant CA40356 from the National Cancer Insti-
tute, and the Nurses’ Health Study II by Public Health Service
Grant CA50385 from the National Cancer Institute, National Insti-
tutes of Health, U.S. Department of Health and Human Services.
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754 MICHELS ET AL.