American Journal of Epidemiology
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Vol. 174, No. 6
Advance Access publication:
August 10, 2011
Low-Carbohydrate Diets, Dietary Approaches to Stop Hypertension-Style Diets,
and the Risk of Postmenopausal Breast Cancer
Teresa T. Fung*, Frank B. Hu, Susan E. Hankinson, Walter C. Willett, and Michelle D. Holmes
* Correspondence to Dr. Teresa T. Fung, Department of Nutrition, Simmons College, 300 The Fenway, Boston, MA 02115 (e-mail:
Initially submitted December 20, 2010; accepted for publication April 8, 2011.
The authors prospectively examined the association between the Dietary Approaches to Stop Hypertension diet
score, overall, animal-based, and vegetable-based low-carbohydrate-diet scores, and major plant food groups and
the risk of postmenopausal breast cancer in 86,621 women in the Nurses’ Health Study. Diet scores were calcu-
lated by using data from up to 7 food frequency questionnaires, with follow-up from 1980 to 2006. The authors
ascertained 5,522 incident cases of breast cancer, including 3,314 estrogen receptor-positive (ERþ) cancers and
826 estrogen receptor-negative (ER?) cancers. After adjustment for potential confounders, the Dietary Ap-
proaches to Stop Hypertension diet score was associated with a lower risk of ER? cancer (relative risk comparing
extreme quintiles ¼ 0.80, 95% confidence interval: 0.64, 1.01; P trend ¼ 0.02). However, this was largely explained
by higher intakes of fruits and vegetables. The authors also observed an inverse association between risk of ER?
cancer and the vegetable-based, low-carbohydrate-diet score (corresponding relative risk ¼ 0.81, 95% confidence
interval: 0.65, 1.01; P trend ¼ 0.03). High total fruit and low-protein vegetable intakes were associated with a lower
risk of ER? cancer (relative risk comparing extreme quintiles ¼ 0.71, 95% confidence interval: 0.55, 0.90; P trend ¼
0.005). No association was found between ERþ tumors and fruit and vegetable intakes. A diet high in fruits and
vegetables, such as one represented by the Dietary Approaches to Stop Hypertension diet score, was associated
with a lower risk of ER? breast cancer. In addition, a diet high in plant protein and fat and moderate in carbohydrate
content was associated with a lower risk of ER? cancer.
breast neoplasms; diet; nutrition assessment
Abbreviations: CI, confidence interval; DASH, Dietary Approaches to Stop Hypertension; ER, estrogen receptor; ER?, estrogen
receptor-negative; ERþ, estrogen receptor-positive; FFQ, food frequency questionnaire; PR?, progesterone receptor-negative;
PRþ, progesterone receptor-positive; RR, relative risk.
Recent data on the use of whole-diet approaches to eval-
uate the association between diet and breast cancer risk have
suggested that adherence to a prudent or healthy eating
pattern reduced the risk (1, 2). Such patterns are usually
characterized by high intakes of fruits, vegetables, whole
grains, and lean meats. However, patterns are identified
a posteriori and only reflect existing eating patterns in the
population. Using preestablished diet quality scores, we
have previously shown that several diets that emphasized
plant foods were associated with a lower risk of estrogen
receptor-negative (ER?) postmenopausal breast cancer (3).
Although we additionally observed an inverse association
between combined intake of vegetables and legumes and
ER? tumors, results for fruit and vegetable intakes from
other studies were less consistent; however, many of those
studies did not conduct separate analyses by the estrogen
receptor status of the tumors (4).
The Dietary Approaches to Stop Hypertension (DASH)
diet emphasizes the intake of plant foods and is promoted
by the US Department of Agriculture as a healthy eating
pattern for the general public (5). This diet encourages the
eating of plant proteins, fruits and vegetables, and a moder-
ate amount of low-fat dairy products and limiting sugary
foods and sodium. Dietary scores that reflect adherence to
652Am J Epidemiol. 2011;174(6):652–660
a DASH-style diet have been linked to a lower risk of colo-
rectalcancer (6,7).However,this scorehasnot beenevaluated
in relation to breast cancer risk.
On the other hand, breast cancer development may, like
colon cancer, also be mediated by the mitotic effect of in-
sulin and insulin-like growth factors (8). Low-carbohydrate
diets might have a low glycemic load, but they can vary
greatly because they can be either plant-based or animal-
based. Their potential to influence breast cancer develop-
ment also has not been evaluated.
In the present analysis, we prospectively examined the
association among the DASH score, low-carbohydrate diets
(overall, animal-based, and plant-based), and the risk of
postmenopausal breast cancer in a large ongoing cohort. In
addition, we explored the association between major plant
food-group contributors to these diets and their associations
with breast cancer. Because we have previously noted dif-
ferences in association when stratifying by estrogen receptor
status (3), we also separately analyzed estrogen receptor-
positive (ERþ) tumors and ER? tumors.
MATERIALS AND METHODS
The Nurses’ Health Study is a cohort study established in
1976 that consists of 121,700 female nurses who were aged
30–55 years and living in 11 US states at the time of study
entry (9). Questionnaires are sent biennially to collect med-
ical, lifestyle, and other health-related information. In 1980,
participants completed a 61-item food frequency question-
naire (FFQ). This questionnairewas expandedtoinclude 116
1998, and 2002.
For the present analysis, we used 1980 as the baseline
who completed the 1980 FFQ with fewer than 10 missing
items and who had plausible total energy intakes (calculated
After excluding those with a history of cancer (n ¼ 3,101)
(except nonmelanoma skin cancer), we included 86,620
women for whom we had follow-up data from 1980 through
2006. This study was approved by the institutional review
board of the Brigham and Women’s Hospital, Boston,
Self-administered semiquantitative FFQs were designed to
assess participants’ average food intakes over the preceding
year. A standard portion size and 9 possible consumption fre-
quency categories, from ‘‘never or <1/month’’ to ‘‘6þ times
per day,’’ were given for each food. Total energy and nutri-
ent intakes were calculated by summing up data from all
foods. Previous validation studies revealed reasonably
good correlations between energy-adjusted nutrients as-
sessed by the FFQ and multiple food records completed
over the preceding year (10).
The computation of low-carbohydrate-diet scores has been
previously described in detail (11). Briefly, percentages of
energy from fat, protein, and carbohydrates were divided
evenly into 11 categories according to percentiles. For fat
and protein, participants in the highest category received 10
received 9 points, and so forth. For carbohydrates, the lowest
intake category received 10 points and the highest received
zero points. We summed the fat, protein, and carbohydrate
scores to create the overall low-carbohydrate-diet score,
which ranged from 0 to 30. In addition, we also created
a vegetable low-carbohydrate-diet score, which was based
on the percent of energy from carbohydrates, vegetable pro-
tein, and vegetable fat, and an animal low-carbohydrate-diet
score, which was based on the percent of energy from carbo-
hydrates, animal protein, and animal fat. Thus, each partici-
pant was given overall, animal, and vegetable scores.
The DASH score has previously been described in detail
(12). Briefly, it consists of 8 components featured in the
DASH diet (13): high intakes of fruits, vegetables, nuts
and legumes, low-fat dairy products, and whole grains and
low intakes of sodium, sweetened beverages, and red and
processed meats. For each component, we classified women
into quintiles according to their intake ranking. Component
scores for fruits, vegetables, nuts and legumes, low-fat dairy
products, and whole grains were used to determine the
women’squintile rankings.Forexample,thosewhose intakes
were in quintile 1 were assigned 1 point and those whose
red and processed meats, and sweetened beverages, low in-
takes were desired. Therefore, those in the lowest quintile
were given a score of 5 points and those in the highest quin-
tile were given a score of 1 point. We then summed up the
component scores to obtain an overall DASH score, ranging
from 8 to 40.
When a participant self-reported a breast cancer diagnosis
in a biennial questionnaire, we contacted her for permission
to obtain and review pathology records to confirm the di-
agnosis and obtain staging, hormone receptor status, and
other relevant information. We only included incidents
of invasive breast cancer in the present study. Deaths were
reported by the postal service, family members, or the Na-
tional Death Index. In the present study, we included only
postmenopausal breast cancer cases to reduce the number
of potential differences in etiology.
Body mass index was calculated from weight reported
on each biennial questionnaire and height reported on the
first questionnaire. Smoking status and average number of
cigarettes smoked, regular intake of a multivitamin, history
of benign breast disease, menopausal status, and use of post-
menopausal hormone therapy were assessed every 2 years.
Data on parity and age at first birth were collected several
times during follow-up. Data on hours per week of vigor-
ous activities were collected in 1980, 1982, and 1984.
Leisure-time physical activity level was measured 7 times,
beginning in 1986, by using validated questions about 10
Diet and Breast Cancer Risk 653
Am J Epidemiol. 2011;174(6):652–660
Author affiliations: Department of Nutrition, Simmons
College, Boston, Massachusetts (Teresa T. Fung); Depart-
ment of Nutrition, Harvard School of Public Health, Boston,
Massachusetts (Teresa T. Fung, Frank B. Hu, Walter C.
Willett); Channing Laboratory, Department of Medicine,
Brigham and Women’s Hospital and Harvard Medical
School, Boston, Massachusetts (Frank B. Hu, Walter C.
Willett, Susan E. Hankinson, Michelle D. Holmes); and
Department of Epidemiology, Harvard School of Public
Health, Boston, Massachusetts (Susan E. Hankinson).
This work was funded by National Institutes of Health
grants CA87969 and CA95589.
Conflict of interest: none declared.
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