Published OnlineFirst November 1, 2012; DOI: 10.1158/1055-9965.EPI-12-0843
Cancer
Epidemiology,
Biomarkers
& Prevention
Research Article
Assessment of the Effects of Severe Obesity and Lifestyle
Risk Factors On Stage of Endometrial Cancer
Marisa A. Bittoni1,2, James L. Fisher2, Jeffrey M. Fowler3, George L. Maxwell5, and Electra D. Paskett1,2,4
Abstract
Background: Lifestyle risk factors, including obesity, have been associated with increased risk of endometrial cancer (EC). Women with higher obesity levels tend to have less aggressive EC disease stage and
histology. This study further investigated associations between nonmodifiable risk factors, such as age, race,
and grade, and modifiable lifestyle factors, such as diet and physical activity expenditure, in relation to severe
obesity and late versus early EC stage at diagnosis.
Methods: Demographic, anthropometric, and lifestyle surveys were administered to 177 women with
histologically confirmed EC. Logistic regression analyses assessed the relationship between obesity and other
risk factors on EC stage at diagnosis.
Results: In multivariate models, body mass index (BMI) < 35 was not significantly associated with late EC
stage at diagnosis (OR ¼ 1.67, P ¼ 0.219) when adjusting for grade and age. Grade was significantly associated
with EC stage when controlling for BMI and age (OR ¼ 8.48, P ¼ .000). Women more than the age of 60 had
a fourfold increased risk of diagnosis at late versus early EC stage when adjusting for other risk factors.
Age had a confounding effect on the obesity-EC stage association.
Conclusions: Our results corroborate those of past studies showing that BMI is not an independent risk
factor for EC stage and that age may have confounded the obesity-EC stage association. Because of mixed
results and implications for treatment outcomes, however, further research examining these variables is
warranted.
Impact: Our results provide further insight into the obesity EC-stage association, especially the confounding
effect of age. Future studies should examine modifiable lifestyle factors in larger and more diverse populations.
Cancer Epidemiol Biomarkers Prev; 22(1); 76–81. 2012 AACR.
Introduction
Endometrial cancer (EC) is the most common gynecologic cancer in the United States, with more than 46,470
new cases expected in 2012 (1). Risk factors for EC include
early age at menarche, nulliparity, menopause and obesity. Obese women have up to 9 times the risk of developing EC as their normal-weight counterparts (2, 3), and
obesity is also the most potentially modifiable risk factor
for EC (4). The mechanism by which obesity may increase
cancer risk is by increasing circulating levels of estrone,
which leads to excess estrogen, increases the mitotic
activity of endometrial cells, and promotes cellular replication that leads to hyperplasia and carcinoma (5).
Authors' Affiliations: 1Division of Epidemiology, The Ohio State University
College of Public Health; 2Division of Population Sciences, The Ohio State
University Comprehensive Cancer, Center; Departments of 3Gynecologic
Oncology, and 4Internal Medicine, The Ohio State University College of
Medicine, Columbus, Ohio; and 5Department of Obstetrics and Gynecology, Inova Fairfax Hospital, Falls Church, Virginia
Corresponding Author: Marisa A. Bittoni, PO Box 21170, Columbus, OH
43221. Phone: 614-206-3518; Fax: 614-459-8798; E-mail:
[email protected]
doi: 10.1158/1055-9965.EPI-12-0843
2012 American Association for Cancer Research.
76
Past studies have shown that women with higher levels
of obesity tend to have less aggressive disease stage and
histology of EC (3, 6–8), which is because of a higher
incidence of better-differentiated, less invasive adenocarcinomas with less frequent lymph node metastases (8). A
survival advantage because of obesity, however, has not
always been shown, as a significant percentage of obese
women may exhibit lymph node metastasis at diagnosis
(7). Cohn and colleagues found that morbidly obese
patients [body mass index (BMI) > 40 kg/m2] with Stage
2 EC had significantly worse 5-year survival rates than
obese patients (BMI ¼ 30–40 kg/m2) or those with ideal
body weights (defined by Cohn and colleagues as BMI <
30 kg/m2; ref. 9).
Others have observed that the relationship between
obesity and EC may be confounded by other factors, such
as tumor grade, age, and race. Temkin and colleagues
found that BMI was not an independent risk factor for EC
survival, and that the apparent protective effect of obesity
on survival was because of obese subjects being younger,
and having lower grade and earlier stage tumors (3).
While most studies have examined the effect of obesity
on EC survival, associations between obesity and EC
stage, as well as the effect of other risk factors, have not
been well documented (6, 10).
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Obesity and Stage of Endometrial Cancer
Diet and physical activity, especially diets consisting of
high fat, high glycemic load, and low fruit/vegetable
consumption, as well as low levels of physical activity,
have also shown associations with increased EC risk, but
no documented associations have been found with EC
stage (11–14). As earlier stage EC normally has better
prognosis, it is especially important to identify modifiable
risk factors that are associated with late versus early stage
disease. Fader and colleagues confirmed the importance
of examining modifiable risk factors, especially the effect
of healthier lifestyles, with regard to EC outcomes (15).
The purpose of this study was to further investigate the
association between obesity and other risk factors on EC
stage at diagnosis. The effect of both nonmodifiable risk
factors, such as age, race, and grade, and modifiable
lifestyle factors, such as diet (fat, fruit/vegetable consumption, and glycemic load) and physical activity
expenditure, were examined in relation to severe obesity
and late versus early stage at EC diagnosis.
Materials and Methods
Study design/participants
Women from 3 hospitals [The Ohio State University
(OSU), Walter Reed Army Medical Center, and Duke
University Medical Center] who were diagnosed with EC
were asked to consent to this study during their preoperative visit with a gynecologic oncologist. Criteria for
inclusion in this study were: age 18 years or more, histologically confirmed EC diagnosis, and literacy in English.
Women were asked to complete the questionnaires before
surgery. Of 208 women who were eligible to participate in
this study, 177 women agreed to provide consent, resulting in a response rate of 85%. This study was approved by
the Institutional Review Boards of all participating
institutions.
pants. Odds ratios obtained from logistic regression analyses were used to assess the relationship between obesity
and other risk factors on EC stage at diagnosis. The
outcome variable was EC stage, as defined by the International Federation of Gynecology and Obstetrics (FIGO;
ref. 18). EC stage was dichotomized as early stage (1/2)
versus late stage (3/4) because of the small sample size.
Obesity was defined by the formula for BMI ¼ weight
(kg)/height(m)2. Because of small strata, BMI was dichotomized using the median (BMI < 35 ¼ 0 vs. 35 ¼ 1), which
is defined as Class II/severe obesity (19). Age was also
dichotomized in this analysis using the median (age 60
¼ 0 vs. >60 ¼ 1). Race was assessed as white ¼ 1 versus
non-white ¼ 0. Grade was dichotomized using the FIGO
classifications (well or moderately differentiated ¼ 0 vs.
poorly differentiated ¼ 1), with the categories combined
because of small strata. Lifestyle variables included total
calories, fruits, and vegetables consumed per day, total
grams of carbohydrate, fat and fiber consumed per day,
glycemic load, and total energy expenditure (metabolic
equivalents, or METs), which were also dichotomized
based on their median values. Log transformations were
conducted on highly skewed variables. Women whose
cancer stage and grade were missing or could not be
assessed were excluded from the analyses (n ¼ 3 and 5,
respectively), resulting in data from 169 women available
for this analysis.
Univariate logistic regression analyses were first conducted between obesity and risk factors related to EC
stage at diagnosis. Using forward selection, the variables
were added to a multivariable model by selecting the
variables with the lowest P value until the P value was
no longer significant (alpha ¼ 0.05). Analyses were conducted using Stata 10 (20).
Results
Data collection/measures
Demographic and anthropometric data were obtained
from perioperative clinic data during presurgical visits
with the gynecologic oncologist. Trained oncology nurses
recorded the information in the patient’s medical chart.
Dietary intake data (past 30 days) were obtained using
the validated General Population Food Frequency Questionnaire (FFQ), developed by the Fred Hutchinson Cancer Research Center (FHCRC; ref. 16). Completed questionnaires were scanned and assessed at the FHCRC to
obtain dietary nutrient data, which were subsequently
sent to our group for statistical analyses.
Physical activity data were obtained from the validated
Women’s Health Initiative (WHI) survey that assessed
recreational physical activity, including mild, moderate
and strenuous physical activity (17).
Statistical analysis
Descriptive statistics (frequencies, means, and standard
deviations) were calculated using demographic, anthropometric, pathology, and lifestyle measures from partici-
www.aacrjournals.org
Table 1 displays the descriptive characteristics of women by EC stage. Overall, 68% of women had a BMI 30,
which is considered obese, and half the women were
severely obese (median BMI ¼ 35). Women diagnosed at
late versus early EC stage were older (median ¼ 63 and 58
years, respectively), were less likely to be severely obese
(BMI 35; 40% and 55% kg/m2, respectively), and were
more likely to have poorly differentiated tumors (39% vs.
9%, respectively; P < 0.0001). The mean calorie intake and
METs were 1,561 and 8, respectively, with no significant
differences in diet and physical activity variables by EC
stage at diagnosis.
Table 2 displays the lifestyle variables by level of obesity
and shows that the mean calories and fat intake were
significantly higher for severely obese women compared
with those who were not severely obese (P < 0.05). Both of
the physical activity variables were significantly lower for
severely obese versus women who were not severely
obese (P < 0.05).
The results of univariate and multivariate logistic
regression models are shown in Table 3. In the univariate
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Bittoni et al.
Table 1. Demographic and lifestyle characteristics of study participants by EC stage (N ¼ 169)
EC Stage
Variable
Early (n ¼ 126)
Late (n ¼ 43)
Total
Age (years)
21–44
45–54
55–64
65
Mean(SD)/median
BMI
19–24
25–29
30–34
35–39
40
Mean(SD)/median
Race
White
Non-white
Gradea
Well differentiated
Moderately differentiated
Poorly differentiated
Diet
Calories (kcal/d)
Carbohydrate (g/day)
Fat (g/d)
Fiber (g/d)
Glycemic load
Fruit (number/d)
Vegetables (number/d)
Physical activity
Total minutes per week
Metabolic equivalents (kg/cal/wk)
n(%)
8(6.4)
37(29.4)
51(40.5)
30(23.8)
58.2(10.5)/59
n(%)
18(14.5)
21(16.9)
17(13.7)
24(19.4)
44(35.5)
36.8(11.2)/36
n(%)
95(80.5)
23(19.5)
n(%)
82(69.5)
26(22.0)
10(8.5)
Mean(SD)
1407.0(465.4)
189.7(95.8)
60.4(34.5)
15.9(7.4)
87.9(49.0)
0.7(0.4)
0.5(0.4)
Mean(SD)
152.9(142.2)
8.4(8.1)
n(%)
2(5.7)
4(11.4)
13(37.1)
16(45.7)
62.6(11.4)/62
n(%)
2(5.7)
9(25.7)
10(28.6)
7(20.0)
7(20.0)
34.1(7.4)/33
n(%)
30(88.2)
4(11.8)
n(%)
10(30.3)
10(30.3)
13(39.4)
Mean(SD)
1583.4(728.3)
180.9(61.7)
50.1(25.2)
16.7(6.7)
81.2(26.5)
0.7(0.4)
0.5(0.4)
Mean(SD)
133.2(132.3)
8.8(8.0)
n(%)
10(6.2)
41(25.7)
64(39.8)
46(28.6)
59.1(10.7)/60
n(%)
20(12.6)
30(18.9)
27(17.0)
31(18.4)
51(32.1)
36.2(10.6)/35
n(%)
125(82.2)
27(17.8)
n(%)
92(60.9)
36(23.9)
23(15.2)
Mean(SD)
1561.4(693.4)
194.3(89.1)
58.9(34.7)
16.6(7.5)
90.8(45.4)
0.7(0.4)
0.5(0.4)
Mean(SD)
144.8(138.8)
8.3(8.1)
Median
1280.2
162.6
54.8
13.8
75.6
0.9
0.7
Median
123.3
4.3
Median
1456.0
189.9
45.4
16.2
82.0
0.9
0.7
Median
100.0
5.5
Median
1439.2
178.1
51.7
15.9
80.5
0.9
0.7
Median
100.1
4.6
NOTE: Cells may not add up to total N because of missing data.
a
P < 0.0001 for grade based on a c2 test; there were no other statistically significant differences by EC stage.
analysis, BMI < 35 was marginally associated with late EC
stage (OR ¼ 2.18, P ¼ 0.051). Age > 60 was significantly
associated with late EC stage (OR ¼ 3.39, P ¼ 0.004). Grade
showed a 7-fold increased risk of being in late versus early
EC stage for women with poorly differentiated cancer (P ¼
0.000). Grade and age were assessed for possible interactions with BMI, but neither was significant.
The multivariate model (Table 3) shows that BMI < 35
was not significantly associated with late EC stage at
diagnosis (OR ¼ 1.67, P ¼ 0.219) when adjusting for grade
and age. Grade was significantly associated with EC stage
at diagnosis when controlling for BMI and age (OR ¼ 8.48,
P ¼ .000). There was almost a 4-fold increased risk of being
diagnosed in late versus early EC stage for women more
than the age of 60 when adjusting for other factors. Age
was also shown to be a confounder for obesity and grade,
as the ORs decreased by 18% and 10%, respectively, when
78
Cancer Epidemiol Biomarkers Prev; 22(1) January 2013
it was added to the model. In addition, age was associated
with obesity (x2 ¼ 4.42; P ¼ 0.03) and was also associated
with stage in each strata of severely obese and not severely
obese women (x2 ¼ 3.86, P ¼ 0.05; x2 ¼ 4.28, P ¼ 0.04,
respectively), thereby rendering it a confounder.
Discussion
This study examined the associations of severe obesity and other modifiable and nonmodifiable risk factors
on EC stage at diagnosis. The results showed that BMI
was not an independent predictor of EC stage in this
study, which confirms the results of several studies,
including a recent study using WHI data (3, 21), but the
authors indicated that because of the close monitoring
in the WHI trial and other study characteristics, participants may not have been representative of the general
Cancer Epidemiology, Biomarkers & Prevention
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Obesity and Stage of Endometrial Cancer
Table 2. Lifestyle variables of study participants by obesity level
Severely obese
(BMI 35)
Diet
a
Calories (kcal/d)
Carbohydrate (g/d)
Fat (g/d)a
Fiber (g/d)
Glycemic load
Fruit (number/d)
Vegetables (number/d)
Physical activity
Total minutes per weeka
Metabolic equivalentsa (kg/cal/wk)
Not severely obese
(BMI < 35)
Total (N ¼ 169)
Mean(SD)
Median
Mean(SD)
Median
Mean(SD)
Median
1716.7(820.5)
202.2(108.0)
66.7(37.0)
15.8(8.0)
101.6(58.9)
0.7(0.4)
0.5(0.6)
Mean(SD)
89.6(88.1)
4.4(4.6)
1495.0
169.3
64.2
14.7
82.3
0.9
0.5
Median
62.5
3.5
1406.0(412.3)
179.8(67.7)
49.9(20.0)
16.6(6.5)
89.3(35.1)
0.7(0.4)
0.6(0.5)
Mean(SD)
208.9(153.5)
13.1(11.6)
1332.3
168.9
45.7
15.4
86.5
1.0
1.0
Median
167.5
9.0
1561.4(693.4)
194.3(89.1)
58.9(34.7)
16.2(7.5)
90.8(45.4)
0.7(0.4)
0.5(0.4)
Mean(SD)
144.8(138.8)
8.3(8.1)
1439.2
178.1
51.7
15.9
80.5
0.9
0.7
Median
100.1
4.6
NOTE: Median BMI ¼ 35 was the cutoff point used to define severely obese and not severely obese.
P < 0.05 based on t tests; there were no other significant differences by obesity level.
a
population. In contrast to our results, several studies
have shown independent associations of obesity with
EC stage (6–8, 22).
Grade and age were associated with EC stage at diagnosis in this study, as expected, with an 8- and 4-fold
increase, respectively, in the odds of being in late versus
early EC stage for women with poorer grade and older age
(60). Age was also a confounder. Our results corroborate
those of Temkin and colleagues, which also showed
factors such as age and grade to be confounders in the
obesity-EC stage association (3).
Diet and physical activity variables showed no significant associations with EC stage at diagnosis in this study,
although the groups differed significantly with respect to
several dietary and physical activity factors, such as
increased caloric and fat intake, along with decreased
physical activity levels among severely obese women,
which was expected. The diets of women in this study
were also relatively high in glycemic load, which has
shown associations with increased EC risk in past studies
(12). Many participants also reported low overall levels of
energy expenditure from recreational physical activity in
this study, which has also shown increased EC risk (13).
Others have suggested that the efficacy of dietary factors
in preventing cancer may be stage dependent (23). Therefore, future studies on this issue are warranted, as the
identification of modifiable risk factors can affect treatment outcomes, as previously discussed.
Table 3. Results of univariate and multivariate logistic regression analyses on late versus early stage EC
(N ¼ 169)
Univariate
BMI < 35
Age > 60 years
Race (non-white)
Grade (poor vs. well/moderate differentiation)
Dietary fat (g)
Carbohydrate (g)
Fiber (g)
Fruits consumed (per day)
Vegetables consumed (per day)
Glycemic load
Physical activity expenditure (METs)
Multivariate
BMI < 35
Age > 60 years
Grade (poor vs. well/moderate differentiation)
www.aacrjournals.org
OR
95% CI
P
2.18
3.39
1.82
7.02
1.32
1.08
1.54
0.97
1.04
1.08
0.98
(1.00–4.77)
(1.47–7.81)
(0.58–5.67)
(2.71–13. 20)
(0.49–3.57)
(0.40–2.89)
(0.57–4.16)
(0.62–1.60)
(0.69–1.65)
(0.40-2.89)
(0.92–1.04)
0.051
0.004
0.304
0.000
0.580
0.877
0.388
0.923
0.819
0.877
0.546
1.67
3.81
8.48
(0.37–4.20)
(1.44–10.08)
(2.90–14.40)
0.219
0.007
0.000
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Bittoni et al.
Because of inconsistent results in the obesity-EC association among researchers, as previously indicated, further studies are warranted, as this information can be
useful in the management and treatment of EC in obese
women (3, 7, 9). For example, obese patients have been
shown to be less likely to undergo lymph node evaluation
than ideal body weight women because of a less aggressive disease stage and histology in obese women, as well
as increased difficulty reported in conducting lymph node
dissection (7). However, it was concluded that conducting
adequate lymphadenectomy is important for obese women who are in earlier EC stage, as their risk of extrauterine
disease, including lymph node metastases, can be similar
to that of ideal weight women (7, 8).
Strengths of this study include that it examined a
population of women with severe versus nonsevere BMI,
who had histologically confirmed EC from 3 diverse sites
in the United States. Demographic and anthropometric
data were obtained from perioperative clinic data versus
self-report; only diet and physical activity data were selfreported. Trained study staff ensured uniformity of data
collection and consistent reporting procedures across
sites.
Limitations of this study include its cross-sectional
design, which limited the ability to make causal inferences, and the fact that we were not able to assess survival.
Misclassification of diet and physical activity variables
could have occurred, as those surveys were based on
participant recall. The low reported mean caloric intake
(1,561 calories) may have been underestimated, which is a
common problem with FFQs (24). In addition, the limited
sample size may have resulted in reduced power. The BMI
cutoff point of 35, which defines severe obesity, is justified,
as women with EC are typically overweight or obese (10).
Selection bias could also have occurred, as the women
who agreed to participate in this study may have been
different from those who did not participate. Therefore,
these results may not be generalizable to all women with
EC.
Future research is needed in larger and more diverse
populations of women with EC to further elucidate the
relationship between modifiable and nonmodifiable risk
factors, such as obesity, age, race, diet, and physical
activity on EC stage, as well as their effect on survival.
This information would be useful for better management
and treatment of EC, as well as improved EC outcomes.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Authors' Contributions
Conception and design: M.A. Bittoni, J.L. Fisher, E.D. Paskett.
Development of methodology: M.A. Bittoni, J.L. Fisher
Acquisition of data (provided animals, acquired and managed patients,
provided facilities, etc.): J. Fowler, G. Maxwell
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M.A. Bittoni, J.L. Fisher, G. Maxwell
Writing, review, and/or revision of the manuscript: M.A. Bittoni, J.L.
Fisher, J. Fowler, G. Maxwell, E.D. Pasket
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M.A. Bittoni
Study supervision: M.A. Bittoni
Grant Support
This study was funded by the Department of Defense Telemedicine and
Advanced Technology Center, Award Number W81XWH-05-2-00065. The
opinions or assertions contained herein are the private views of the authors
and are not to be construed as official or as reflecting the views of the
Department of the Army or the Department of Defense.
Received August 5, 2012; revised October 5, 2012; accepted October 22,
2012; published OnlineFirst November 1, 2012.
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Published OnlineFirst November 1, 2012; DOI: 10.1158/1055-9965.EPI-12-0843
Assessment of the Effects of Severe Obesity and Lifestyle Risk
Factors On Stage of Endometrial Cancer
Marisa A. Bittoni, James L. Fisher, Jeffrey M. Fowler, et al.
Cancer Epidemiol Biomarkers Prev 2013;22:76-81. Published OnlineFirst November 1, 2012.
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