Dietary Fat, Fiber, and Carbohydrate Intake in Relation to Risk of Endometrial Cancer

Abstract

Background

Macronutrients such as fat and fiber have been hypothesized to play a role in the etiology of endometrial cancer.

Methods

To investigate these associations, the authors analyzed data from the Nurses’ Health Study (NHS). From 1980 to 2006, 669 invasive adenocarcinoma cases were identified over 1.3 million person-years of follow-up. Dietary intake was assessed in 1980 and updated every 2–4 years. Cox proportional hazard models were used to calculate relative risks (RRs), controlling for total energy and other risk factors.

Results

Overall, the authors found no significant associations between most dietary factors and endometrial cancer risk. Total fat was associated with a borderline significant decreased risk (top vs. bottom quintile RR=0.78; 95% confidence interval [CI]=0.60, 0.99; P_trend=0.18). Findings for animal fat were similar. No inverse associations between dietary fibers and cancer risk were observed. Cereal fiber was modestly positively associated with risk (top vs. bottom quintile RR=1.38, 95%CI=1.07, 1.79; P_trend = 0.05). The inverse association with animal fat intake and a positive association with carbohydrate intake were observed among premenopausal but not among postmenopausal women.

Conclusions

In this large prospective study, no overall association was observed between dietary fat, fiber, or carbohydrates with endometrial cancer risk, although several of the relationships may vary by menopausal status.

Impact

Dietary fat and fiber intake do not appear to play a major role in endometrial cancer etiology overall. However, further evaluation of these associations, particularly in premenopausal women, is needed.

INTRODUCTION

Endometrial cancer is the seventh most common malignancy among women worldwide and the most common invasive gynecologic cancer in US women, with 40,100 new cases projected to occur in 2008 (1), The role of increased levels of estrogen is well established (2, 3), and circulating estrogen levels are associated with increased risk of endometrial cancer (4, 5). Most of the risk factors for endometrial cancer can be substantially explained within the framework of the unopposed estrogen hypothesis, (6) although other mechanisms such as inflammation (7) also have been proposed.

Several components of diet have been proposed to influence endometrial cancer risk by modulating the production, metabolism, and excretion of endogenous hormones, especially estrogen. One in vitro study suggested that physiological diurnal elevations in plasma free fatty acids which are increased by high fat consumption, obesity, and stress may increase free estradiol, thereby exerting a promotional effect on endometrial cancer (8). In the only animal study, in Donryu rats, a high-fat diet led to an early elevation and continued high levels of the serum estrogen: progesterone ratio and an increase in the incidence of uterine adenocarcinomas (9). Glycemic load and glycemic index are used to indicate the carbohydrate content of foods according to their postprandial glycemic effects and high-glycemic load and glycemic index diet are thought to result in high circulating insulin levels (10) and thereby might influence the incidence of endometrial cancer (6).

To date, evidence for an association between dietary fat and fiber and endometrial cancer is limited and results from observational studies inconsistent. Eleven of 14 case-control studies supported the hypotheses that high fat or low dietary fiber intake could increase the risk of endometrial cancer (11–21), three found no association (22–24). In the few prospective studies, dietary fiber and most of the fatty acids were not associated with risk (25, 26). In one case-control (27) and four cohort studies (28–31), carbohydrate intake or glycemic load were positively associated with risk of endometrial cancer while 2 other reported no significant associations (18, 25).

In the current study, we evaluated the associations of dietary fat, fiber, and carbohydrates (including glycemic load) with risk of endometrial cancer using 26 years of prospectively collected data from the NHS cohort.

MATERIALS AND METHODS

Study population

The NHS began in 1976, and included 121,701female registered nurses aged 30–55 years who resided in one of 11 states in the U.S. at that time. The cohort has been followed biennially by mailed questionnaire to update exposure information and any new disease diagnoses; the follow-up rate has been at least 90% for each follow-up cycle. Deaths are confirmed through report by family members and the National Death Index.

In this analysis, follow-up began in 1980 when dietary intake was first queried. At baseline, we excluded women who had hysterectomy (n=20,612), did not respond to or had more than 10 missing items on the 1980 food frequency questionnaire (FFQ), or total energy intakes <500 or >3500 kcal/day (n=28,487), died before 1980 (n=747), or reported any type of cancer before 1980 (excluding nomelanoma skin cancer, n=3,660). Since obesity is an important risk factor for endometrial cancer, we also excluded women with missing body mass index (BMI) at baseline (n=166, these women could reenter the analysis in subsequent cycles once information on BMI was available). A total of 68,070 women remained for analysis.

During each follow-up cycle, we excluded deaths, those with a diagnosis of any cancer including endometrial cancer, as well as those who had their uterus removed in the previous period. The women with missing BMI during the last 2 consecutive periods were also excluded in the next follow-up cycle but could reenter the analysis in subsequent cycles once information on BMI was available. For subsequent FFQs with about 130 items, those with more than 70 items blank food items, or total caloric intakes <600 or >3500 kcal/day were excluded.

Endometrial cancer cases

From 1978 forward, participants were asked to report in their questionnaires any new diagnosis of endometrial cancer. From June 1, 1980 through May 31, 2006, a total of 1,384 women reported endometrial cancer. For 1,104 cases, medical records including the diagnosis, histologic type, presence of invasion and stage were obtained. From these, we identified 669 cases of invasive adenocarcinoma defined by the International Federation of Gynecology and Obstetrics as stage IB to IVB. The primary reasons for exclusion were that the tumor was non-invasive (n=316) or non-epithelial (n=60) or a type of epithelial cancer (n=58) other than adenocarcinoma (e.g., clear cell).

Assessment of intake of fat, fiber, and carbohydrates

A 61-item FFQ for collecting dietary information was administered in 1980. An expanded FFQ with approximately 130 food items was sent to women in 1984, 1986, 1990, 1994, 1998, and 2002 to assess usual food intakes in the previous year. A common unit or portion size for each food was specified, and participants were asked how often, on average, they had consumed that amount of food or beverage during the previous year. The average daily intake of each nutrient was calculated by multiplying the frequency of consumption of each item by its nutrient content per serving and totaling the nutrient intake for all food items.

Values for total, animal, and vegetable fat and specific fatty acids were computed primarily from the USDA database (32). AOAC fiber (the enzymatic gravimetric method), the standard total dietary fiber method in the United States, was used to calculate dietary fiber. Total fiber, fiber from cereals and separately from vegetables also were calculated. Glycemic load values were calculated by multiplying each food’s glycemic index by its carbohydrate value and by the frequency of consumption, then summing over all foods (33).

Dietary variables were energy-adjusted as previously described (34). This approach addresses whether the composition of the diet, independent of total energy intake, is most relevant to the risk of endometrial cancer. Given dietary intake was assessed up to 7 times over a 26-year period, we assessed intake in several ways: cumulative average intake (the average intake from the available FFQs up to each follow-up cycle), recent intake (current intake, at the beginning of a 4-year interval), and baseline intake were used to assess the effect of cumulative exposure, short latency, and long latency, respectively. If intake on one or more questionnaires was missing, the cumulative average intake was calculated by averaging the available data. For recent intake, we carried forward the last available dietary data, and if data from more than one questionnaire was missing, recent intake was considered missing. All the dietary data were used prospectively.

In addition, in secondary analyses, we assessed non-energy adjusted nutrient intake, the percentage of energy from fat and carbohydrates, and grams of fiber per 1000 kcal, all in relation to endometrial cancer risk.

Assessment of covariates

Information on most potential confounding factors, including weight, smoking, oral contraceptive (OC) use, postmenopausal hormone use (PMH), age at menopause, age at last birth, hypertension, and diabetes was collected in 1976 and subsequent questionnaires. If data were not available, those women were assigned to a missing category for that period. BMI was calculated from height at baseline and from the biennially updated report of current weight. We carried forward the weight reported in the prior questionnaire cycle if it was missing in the current cycle. A nurse was classified as postmenopausal from the time she returned a questionnaire reporting natural menopause. PMH was first assessed in 1976; women were queried about current and past postmenopausal hormone therapy use and duration. From 1978, information on the type of hormone used was collected. OC use was queried biennially until 1984 when women were 38 to 63 years of age and few women were still current users. Neither alchohol intake nor physical activity were confounders in these analyses, and hence were not included in the final multivariable models.

Data analyses

Each participant contributed person-time from the date of the return of the 1980 questionnaire through June 1, 2006, hysterectomy, death, loss to follow-up, or diagnosis of endometrial cancer or other cancer, whichever came first. Incidence rates of endometrial cancer in each category of the exposure variable were calculated as the number of incident cases divided by the total person-time at risk. Incidence rate ratios (IRRs) were computed as the ratio of the incidence rate in the exposure category of interest to the incidence rate in the referent category. To adjust the RRs for multiple covariates, we used Cox proportional hazard models conditioned on age (months) and follow-up cycle. In all multivariate models, we included the following covariates (see Table 3 for detail on how covariates were controlled in multivariate models): total energy, smoking, OC use, PMH use, age at menopause, parity, age at last birth, age at menarche, hypertension, diabetes, and BMI. In secondary analyses, to show the impact of not accounting for total energy intake in multivariable models, we present the association between macro-nutrients that were not energy adjusted with disease risk. Since there was no prior rationale for specific cut points for intakes of fat or dietary fiber, we categorized exposure in quintile categories to maintain an adequate number of participants in each category. Tests for linear trend for the nutrients were calculated by including the median for each quintile in the final multivariate model.

Table 3.

Cumulative Average Intake of Fat and Risk of Endometrial Cancer, NHS Cohort (1980–2006)

			Age-adjusted model*		Multi-adjusted model†		Multi-adjusted model‡
	# of Cases	Median (g/d)	RR	95% CI	RR	95% CI	RR	95% CI
Total energy (kcal/d)
Q1	110	1024	1.00		1.00
Q2	138	1422	1.27	0.99, 1.63	1.26	0.98, 1.62
Q3	134	1638	1.24	0.96, 1.59	1.23	0.96, 1.59
Q4	156	1882	1.45	1.13, 1.85	1.44	1.13, 1.84
Q5	131	2273	1.24	0.96, 1.59	1.22	0.95, 1.57
Ptrend				0.07		0.09
Total fat
Q1	153	50.0	1.00		1.00		1.00
Q2	115	60.5	0.80	0.63, 1.02	0.78	0.61, 1.00	1.11	0.87, 1.42
Q3	151	62.5	1.08	0.86, 1.35	1.02	0.81, 1.28	1.09	0.85, 1.39
Q4	139	67.0	1.02	0.81, 1.29	0.96	0.76, 1.21	1.28	1.01, 1.63
Q5	111	75.4	0.84	0.66, 1.08	0.78	0.60, 0.99	1.17	0.91, 1.49
Ptrend				0.55		0.18		0.14
Animal fat
Q1	133	28.0	1.00		1.00		1.00
Q2	144	34.4	1.14	0.90, 1.44	1.07	0.84, 1.35	1.26	0.98, 1.61
Q3	152	38.9	1.21	0.96, 1.53	1.09	0.86, 1.38	1.31	1.03, 1.68
Q4	124	43.3	1.02	0.80, 1.31	0.90	0.70, 1.15	1.23	0.96, 1.58
Q5	116	52.8	0.96	0.75, 1.23	0.84	0.65, 1.08	1.16	0.90, 1.49
Ptrend				0.51		0.07		0.51
Vegetable fat
Q1	137	14.1	1.00		1.00		1.00
Q2	151	19.3	1.15	0.91, 1.45	1.14	0.91, 1.44	1.07	0.83, 1.38
Q3	114	22.5	0.88	0.69, 1.13	0.88	0.68, 1.13	1.38	1.09, 1.75
Q4	144	25.7	1.11	0.88, 1.40	1.13	0.90, 1.43	1.19	0.93, 1.52
Q5	123	31.1	0.95	0.74, 1.21	0.99	0.77, 1.26	1.24	0.97, 1.58
Ptrend				0.62		0.91		0.08
Saturated fat
Q1	138	17.6	1.00		1.00		1.00
Q2	148	21.1	1.14	0.91, 1.44	1.09	0.86, 1.37	1.02	0.80, 1.31
Q3	136	23.7	1.09	0.86, 1.38	1.01	0.80, 1.29	1.12	0.88, 1.43
Q4	133	25.2	1.10	0.86, 1.40	1.00	0.79, 1.28	1.22	0.96, 1.56
Q5	114	29.3	0.97	0.76, 1.25	0.90	0.70, 1.16	1.11	0.87, 1.42
Ptrend				0.75		0.32		0.22
Mono-unsaturated fat
Q1	150	18.9	1.00		1.00		1.00
Q2	128	28.9	0.94	0.74, 1.19	0.92	0.73, 1.17	0.93	0.73, 1.19
Q3	130	24.1	0.94	0.74, 1.19	0.90	0.71, 1.14	1.00	0.79, 1.28
Q4	158	26.1	1.20	0.96, 1.50	1.11	0.89, 1.40	1.18	0.94, 1.49
Q5	103	30.1	0.80	0.62, 1.03	0.74	0.58, 0.96	1.01	0.79, 1.29
Ptrend				0.38		0.12		0.43
Poly-unsaturated fat
Q1	127	7.6	1.00		1.00		1.00
Q2	147	9.1	1.20	0.94, 1.52	1.15	0.91, 1.46	1.00	0.77, 1.28
Q3	137	10.1	1.15	0.90, 1.46	1.08	0.85, 1.38	1.23	0.96, 1.56
Q4	131	11.2	1.11	0.87, 1.42	1.04	0.81, 1.33	1.12	0.87, 1.43
Q5	127	13.0	1.11	0.87, 1.42	1.05	0.82, 1.34	1.23	0.96, 1.56
Ptrend				0.62		1.00		0.07
Trans fatty acids
Q1	158	2.2	1.00		1.00		1.00
Q2	120	2.9	0.80	0.63, 1.01	0.76	0.60, 0.97	0.85	0.66, 1.09
Q3	139	3.3	0.97	0.77, 1.21	0.91	0.72, 1.14	1.00	0.79, 1.26
Q4	135	3.8	0.95	0.76, 1.20	0.89	0.70, 1.12	1.11	0.90, 1.44
Q5	117	4.7	0.84	0.66, 1.07	0.81	0.63, 1.03	1.01	0.79, 1.28
Ptrend				0.40		0.21		0.35
ω-3 fatty acids
Q1	119	0.05	1.00		1.00		1.00
Q2	123	0.10	1.04	0.81, 1.33	1.03	0.80, 1.33	0.99	0.76, 1.27
Q3	125	0.14	0.98	0.76, 1.25	0.93	0.73, 1.20	1.08	0.84, 1.39
Q4	135	0.19	1.07	0.83, 1.36	1.00	0.78, 1.28	0.98	0.76, 1.26
Q5	164	0.29	1.22	0.96, 1.54	1.10	0.87, 1.40	1.18	0.92, 1.49
Ptrend				0.07		0.38		0.15

^*Adjust for age and follow-up period

^†Adjust for total energy (continuous), smoking [never(reference), past, current], oral contraceptive use [never (reference), < 3 years, 3–5 years, > 5 years], postmenopausal hormone use [premenopausal, postmenopausal never(reference), past, current E only, current E+P], age at menopause [pre/unknown menopause, <45 yr, 45–46 yr, 47–48 yr (reference), 49–50 yr, 51–52 yr, 53+ yr] parity [nulliparous (reference), 1–2 & age at last birth<30, 1–2 & age at last birth>=30, 3–4 & age at last birth<30, 3–4 & age at last birth>=30, 5+], age at menarche [< 12, 12 (reference), > 12], hypertension (yes, no), diabetes (yes, no), BMI (continuous).

^‡Dietary factors (not energy-adjusted), multivariate-adjusted except for total energy.

To assess whether the relationships between fat and dietary fiber intake and endometrial cancer risk varied across categories of other risk factors, we performed stratified analyses. Further, interaction terms were calculated as the products of a binary stratification factor (e.g., menopausal status) and the median for each quintile of our dietary exposures (modeled continuously) and evaluated using the likelihood ratio test.

RESULTS

A total of 669 cases of invasive adenocarcinoma were identified among about 1.3 million person-years of follow-up. Characteristics of the study population at the midpoint (1990) are summarized in Table 1. In 1990, women with high total fat intake were more likely to be obese and diabetic, and were less likely to be postmenopausal or to use PMH. Women with high fiber intake were less likely to smoke, to have used OCs or to be hypertensive, and were more likely to use PMH. Finally, women with high carbohydrate intake were less likely to be obese and ever smokers, and had a lower prevalence of OC use and diabetes.

Table 1.

Age-standardized Prevalence of Potential Endometrial Cancer Risk Factors by Quintile Categories of Cumulative Average Energy-Adjusted Dietary Factors Among Women in the NHS Cohort, 1990

Quintile of intake	Total Fat			Total Fiber			Carbohydrates
	Q1	Q3	Q5	Q1	Q3	Q5	Q1	Q3	Q5
Median (g/d)	51.0	62.3	73.9	11.1	15.5	21.2	145.7	180.8	212.8
Age (yrs)	55.4	55.4	55.4	55.3	55.4	55.5	55.4	55.4	55.4
Age at menopause (yrs)	49.8	49.9	49.6	49.5	49.8	49.9	49.7	49.9	49.8
Parity among parous women	3.1	3.2	3.3	3.3	3.2	3.1	3.2	3.2	3.1
Age at last birth (yrs)	31.3	31.6	31.3	31.5	31.5	31.3	31.2	31.6	31.5
Age at menarche (yrs)	12.4	12.5	12.5	12.5	12.5	12.4	12.4	12.5	12.5
BMI (continuous, kg/m2)	24.9	25.7	26.4	25.6	25.9	25.2	26.0	25.8	24.9
BMI≥30 (%)	13.0	16.0	20.8	17.0	17.0	14.5	18.5	17.0	13.2
Ever Smoked (%)	57.8	56.1	60.0	66.6	56.8	51.6	70.0	55.6	47.8
Postmenopausal (%)	60.8	60.4	56.4	57.0	59.9	61.2	56.6	59.8	61.1
Ever used oral contraceptives (%)	48.8	49.4	49.3	49.8	49.2	47.8	52.7	49.2	46.0
Ever used postmenopausal hormones (%)*	42.8	41.8	37.4	35.2	41.1	44.9	40.4	42.2	41.0
Diabetes (%)	3.1	3.8	4.8	3.3	3.9	4.2	4.4	3.7	3.2
Hypertension (%)	27.1	24.8	24.8	26.4	25.6	24.3	27.5	24.3	25.5

^*Among postmenopausal women

Table 2 shows the Spearman correlations of the cumulative averaged intake of dietary factors. The upper part of the table displays correlations for energy-adjusted dietary factors and the lower part displays correlations between non-energy adjusted values. All the correlation coefficients are statistically significant (p<0.05). For the energy-adjusted values, the correlation coefficients for total fat with the fat subtypes ranged from 0.17 to 0.95, and the correlation coefficient with carbohydrates is −0.76. Saturated fat and mono-unsaturated fat also were highly correlated with animal fat (r= 0.90, 0.75, respectively). Similarly, total fiber was also highly correlated with vegetable fiber and cereal fiber (r= 0.70, 0.51 respectively).

Table 2.

Correlations of Cumulative Averaged, Energy-Adjusted Intake of Dietary Factors, NHS Cohort (1980–2006)^*

	Total energy	Total fat	Animal fat	Vegetable fat	Saturated fat	Mono- unsaturated fat	Poly- unsaturated fat	Trans fat	ω-3 fat	Total fiber	Vegetable fiber	Cereal fiber	Carbohy- drates	Glycemic load
Total energy	1.00	-	-	-	-	-	-	-	-	-	-	-	-	-
Total fat	0.84	1.00	0.77	0.17	0.88	0.95	0.36	0.62	−0.36	−0.52	−0.31	−0.41	−0.76	−0.63
Animal fat	0.64	0.86	1.00	−0.42	0.90	0.75	−0.12	0.37	−0.33	−0.53	−0.26	−0.54	−0.75	−0.63
Vegetable fat	0.68	0.64	0.21	1.00	0.15	0.14	0.78	0.31	0.03	0.10	−0.02	0.28	0.11	0.12
Saturated fat	0.77	0.95	0.94	0.45	1.00	0.82	0.06	0.50	−0.42	−0.58	−0.36	−0.50	−0.71	−0.60
Mono-unsaturated fat	0.79	0.98	0.87	0.59	0.93	1.00	0.35	0.66	−0.37	−0.52	−0.31	−0.41	−0.74	−0.59
Poly-unsaturated fat	0.78	0.78	0.44	0.89	0.62	0.75	1.00	0.45	0.06	−0.02	−0.02	0.11	−0.16	−0.12
Trans fatty acids	0.67	0.82	0.66	0.61	0.76	0.83	0.72	1.00	−0.42	−0.45	−0.36	−0.18	−0.37	−0.22
Ω-3 fatty acids	0.24	0.03	−0.08	0.21	−0.06	−0.01	0.24	−0.13	1.00	0.38	0.40	0.25	0.15	0.03
Total fiber	0.63	0.33	0.11	0.51	0.21	0.27	0.50	0.18	0.44	1.00	0.70	0.51	0.52	0.37
Vegetable fiber	0.43	0.22	0.10	0.30	0.13	0.18	0.34	0.05	0.46	0.76	1.00	0.15	0.19	0.07
Cereal fiber	0.51	0.25	−0.00	0.54	0.13	0.20	0.46	0.22	0.34	0.68	0.35	1.00	0.51	0.43
Carbohydrates	0.83	0.49	0.24	0.64	0.41	0.43	0.61	0.41	0.29	0.76	0.46	0.68	1.00	0.92
Glycemic load	0.81	0.49	0.26	0.62	0.41	0.44	0.60	0.44	0.23	0.69	0.40	0.64	0.98	1.00

^*The upper, right half of the table displays correlations of energy-adjusted dietary factors; the lower, left half displays correlations for non-energy adjusted dietary factors. All correlations are statistically significant at p<0.05. Correlations 0.7 or larger are bolded.

The RRs according to quintiles of cumulative intake of total energy, energy-adjusted dietary fat, fiber, and carbohydrates are shown in tables 3–5. Although we observed significantly elevated risk for the 4^th quintile of total energy intake compared with the lowest quintile (RR=1.44, 95%CI=1.13, 1.84), neither the top vs. bottom category comparison nor the trend test for total energy intake was significant. No increased risk of endometrial cancer was observed with higher intakes of total fat or vegetable fat or specific fatty acids. In fact, after adjusting for other risk factors, intakes of total and animal fat were associated with slightly lower risk. The RR in the top vs. bottom quintile RR of total and animal fat were 0.78 (95% CI=0.60, 0.99; P_trend =0.18) and 0.84 (95%CI=0.65, 1.08; P_trend =0.07) (Table 3). Saturated and mono-unsaturated fats, which are highly correlated with animal fat, had RRs close to those of animal fat but the trend tests were not significant. However, when we looked at the absolute values of animal fat without adjusting for total energy (Table 3, last column), we observed a non-significant increased risk. After adjusting for total energy in the multivariate model, non-energy-adjusted animal fat intake had RRs similar to those observed for energy-adjusted values (data not shown).

Table 5.

Energy-Adjusted Dietary Intakes and Risk of Endometrial Cancer Stratified by Menopausal Status, NHS Cohort (1980–2006)

	Premenopausal*				Postmenopausal†				Pheterogeneity
	# of Cases	Median	RR	95% CI	# of Cases	Median	RR	95% CI
Total Energy
Q1	19	1069	1.00		84	1158	1.00		0.93
Q2	7	1372	0.40	0.17, 0.95	126	1447	1.51	1.14, 1.99
Q3	18	1602	0.98	0.51, 1.87	114	1660	1.37	1.04, 1.82
Q4	21	1854	1.09	0.58, 2.04	124	1896	1.51	1.14, 1.99
Q5	28	2267	1.42	0.77, 2.57	97	2276	1.19	0.89, 1.60
Ptrend				0.09				0.12
Animal Fat
Q1	20	30.8	1.00		107	26.9	1.00		0.0008
Q2	24	38.0	1.04	0.57, 1.89	115	32.7	1.09	0.84, 1.42
Q3	24	43.5	0.92	0.50, 1.67	122	36.9	1.14	0.87, 1.48
Q4	14	48.0	0.51	0.26, 1.02	104	41.0	0.98	0.75, 1.29
Q5	11	60.4	0.36	0.17, 0.76	97	49.4	0.95	0.71, 1.25
Ptrend				0.0009				0.80
Carbohydrates
Q1	10	125	1.00		81	148	1.00		0.94
Q2	15	156	1.49	0.67, 3.32	112	172	1.20	0.91, 1.59
Q3	26	171	2.72	1.30, 5.68	125	186	1.35	1.03, 1.78
Q4	19	184	2.07	0.96, 4.48	103	198	1.10	0.83, 1.47
Q5	23	207	2.87	1.35, 6.08	117	218	1.23	0.92, 1.63
Ptrend				0.004				0.27
Cereal fiber
Q1	17	1.35	1.00		76	2.12	1.00		0.05
Q2	25	2.35	1.54	0.82, 2.87	104	3.11	1.26	0.94, 1.70
Q3	21	2.95	1.27	0.66, 2.43	121	3.83	1.41	1.06, 1.89
Q4	17	3.70	1.17	0.59, 2.32	109	4.67	1.24	0.92, 1.66
Q5	13	5.20	1.09	0.52, 2.29	135	6.30	1.48	1.11, 1.97
Ptrend				0.88				0.02

^*Adjust for total energy (continuous), smoking [never(reference), past, current], oral contraceptive use [never (reference), < 3 years, 3, 5 years, > 5 years], parity [nulliparous (reference), 1, 2 & age at last birth<30, 1, 2 & age at last birth>=30, 3, 4 & age at last birth<30, 3, 4 & age at last birth>=30, 5+], age at menarche [< 12, 12 (reference), > 12], hypertension (yes, no), diabetes (yes, no), BMI (continuous).

^†Adjust for total energy (continuous), smoking [never(reference), past, current], oral contraceptive use [never (reference), < 3 years, 3, 5 years, > 5 years], postmenopausal hormone use [postmenopausal never(reference), past, current E only, current E+P], age at menopause [pre/unknown menopause, <45 yr, 45, 46 yr, 47, 48 yr (reference), 49, 50 yr, 51, 52 yr, 53+ yr], parity [nulliparous (reference), 1, 2 & age at last birth<30, 1, 2 & age at last birth>=30, 3, 4 & age at last birth<30, 3, 4 & age at last birth>=30, 5+], age at menarche [< 12, 12 (reference), > 12], hypertension (yes, no), diabetes (yes, no), BMI (continuous).

We did not observe the hypothesized decreased risk associated with fiber intake (Table 4). Energy-adjusted and non-energy adjusted values of dietary fiber had similar RRs. In fact, high intakes of total fiber and several types of fiber, particularly cereal fiber, were associated with an elevated risk of endometrial cancer. The RR in the top (vs. bottom) quintile of total, vegetable, and cereal fiber were 1.21 (95%CI=0.94, 1.57), 1.21 95%CI=0.94, 1.55), and 1.38 (95%CI=1.07, 1.79), respectively. Similar borderline positive associations were observed with intakes of either total carbohydrates or glycemic load. The RR in the highest (vs. lowest) quintile of carbohydrates and glycemic load were 1.29 (95% CI= 1.00, 1.67) and 1.29 (95% CI=0.99, 1.67) (Table 4). As expected, given the positive correlation between fiber and total energy intake, fiber intake that was not energy-adjusted had stronger positive associations with endometrial cancer (top vs. bottom quintile RR for total fiber =1.54, 95% CI=1.19, 1.99; P_trend =0.003). This association was attenuated by further adjusting for carbohydrate intake (RR for the top vs. bottom quintile decreased to 1.24; 95% CI=0.88, 1.75), and in the same model, the RR of non-energy-adjusted carbohydrate for the top vs. bottom quintile decreased from 1.51 to 1.36 (95% CI=0.96, 1.92).

Table 4.

Cumulative Average Intake of Dietary Fiber and Carbohydrates and Risk of Endometrial Cancer, NHS Cohort (1980–2006)

			Age-adjusted model*		Multi-adjusted model†		Multi-adjusted model‡
	# of Cases	Median (g/d)	RR	95% CI	RR	95% CI	RR	95% CI
Total fiber
Q1	100	10.7	1.00		1.00		1.00
Q2	121	13.5	1.17	0.89, 1.52	1.11	0.85, 1.45	1.35	1.03, 1.76
Q3	131	15.4	1.21	0.93, 1.57	1.11	0.85, 1.44	1.22	0.93, 1.60
Q4	151	17.5	1.31	1.02, 1.69	1.20	0.92, 1.55	1.32	1.02, 1.72
Q5	166	21.3	1.33	1.03, 1.71	1.21	0.94, 1.57	1.54	1.19, 1.99
Ptrend				0.02		0.13		0.003
Vegetable fiber
Q1	108	3.2	1.00		1.00		1.00
Q2	136	4.5	1.23	0.95, 1.58	1.20	0.93, 1.54	1.43	1.10, 1.87
Q3	133	5.4	1.17	0.91, 1.51	1.14	0.88, 1.47	1.50	1.16, 1.95
Q4	133	6.4	1.13	0.87, 1.45	1.07	0.83, 1.39	1.39	1.06, 1.81
Q5	159	8.5	1.29	1.01, 1.65	1.21	0.94, 1.55	1.46	1.12, 1.89
Ptrend				0.11		0.30		0.04
Fruit fiber
Q1	111	1.4	1.00		1.00		1.00
Q2	110	2.5	0.94	0.72, 1.22	0.86	0.66, 1.11	1.40	1.07, 1.82
Q3	135	3.6	1.10	0.85, 1.41	0.97	0.75, 1.25	1.41	1.08, 1.83
Q4	154	4.8	1.19	0.93, 1.52	1.03	0.80, 1.32	1.49	1.15, 1.94
Q5	159	7.1	1.14	0.89, 1.46	0.97	0.76, 1.25	1.52	1.17, 1.97
Ptrend				0.11		0.69		0.09
Cereal fiber
Q1	98	1.9	1.00		1.00		1.00
Q2	133	2.8	1.34	1.03, 1.74	1.27	0.98, 1.65	0.99	0.76, 1.30
Q3	149	3.5	1.47	1.14, 1.90	1.37	1.06, 1.77	1.13	0.87, 1.46
Q4	135	4.3	1.30	1.00, 1.68	1.22	0.94, 1.59	1.04	0.80, 1.32
Q5	154	6.0	1.38	1.07, 1.78	1.38	1.07, 1.79	1.21	0.94, 1.56
Ptrend				0.07		0.05		0.006
Carbohydrates
Q1	104	141.0	1.00		1.00		1.00
Q2	131	166.7	1.25	0.97, 1.62	1.19	0.92, 1.55	1.35	1.04, 1.76
Q3	164	180.3	1.55	1.21, 1.99	1.51	1.18, 1.93	1.51	1.17, 1.95
Q4	128	193.3	1.19	0.92, 1.54	1.18	0.91, 1.53	1.51	1.17, 1.96
Q5	142	214.8	1.25	0.97, 1.61	1.29	1.00, 1.67	1.51	1.17, 1.96
Ptrend				0.14		0.08		0.002
Glycemic load
Q1	104	72.8	1.00		1.00		1.00
Q2	145	87.3	1.36	1.06, 1.76	1.30	1.01, 1.67	1.40	1.08, 1.82
Q3	143	95.7	1.36	1.06, 1.75	1.33	1.03, 1.71	1.52	1.17, 1.97
Q4	142	104.0	1.34	1.04, 1.72	1.33	1.03, 1.72	1.54	1.19, 2.00
Q5	135	118.3	1.25	0.97, 1.62	1.29	0.99, 1.67	1.48	1.14, 1.92
Ptrend				0.15		0.07		0.006

^*Adjust for age and follow-up period

^†Adjust for total energy (continuous), smoking [never(reference), past, current], oral contraceptive use [never (reference), < 3 years, 3–5 years, > 5 years], postmenopausal hormone use [premenopausal, postmenopausal never(reference), past, current E only, current E+P], age at menopause [pre/unknown menopause, <45 yr, 45–46 yr, 47–48 yr (reference), 49–50 yr, 51–52 yr, 53+ yr] parity [nulliparous (reference), 1–2 & age at last birth<30, 1–2 & age at last birth>=30, 3–4 & age at last birth<30, 3–4 & age at last birth>=30, 5+], age at menarche [< 12, 12 (reference), > 12], hypertension (yes, no), diabetes (yes, no), BMI (continuous).

^‡Dietary factors (not energy-adjusted), multivariable-adjusted.

When we assessed baseline and recent intake, instead of cumulative average intake, results were similar but slightly attenuated. Findings for latency analyses also were very similar. Therefore only results for the cumulative average intakes are shown.

When stratified by menopausal status, the association between energy-adjusted animal fat and endometrial cancer was seen primarily in the small group of premenopausal women (top vs. bottom quintile RR=0.36, 95%CI=0.17, 0.76; P_trend =0.0009) (Table 5). Total and monounsaturated fats had similar but weaker associations (data not shown). No association was observed among postmenopausal women (P_{heterogeneity} =0.0008). Carbohydrate intake was positively associated with risk among premenopausal women (top vs. bottom quintile RR=2.87, 95%CI=1.38, 6.08) but not among postmenopausal women, although the test for heterogeneity was not significant (P_{heterogeneity} =0.94) (Table 5). Glycemic load had similar but weaker associations (data not shown). We also evaluated carbohydrates and animal fat in the same model to assess their independent association with risk. However, since these macronutrients were highly inversely correlated, CIs became wider and were no longer statistically significant. The RRs for the top vs. bottom quintiles of animal fat and carbohydrates were 0.47 (95%CI=0.18, 1.23) and 1.57 (95%CI=0.60, 4.10), respectively. When assessed by menopausal status, the positive association between cereal fiber was observed primarily among postmenopausal women, but this difference was marginally significant (P_{heterogeneity} = 0.05) (Table 5). We also stratified by BMI (BMI<30 vs. BMI≥30) and smoking (never vs. ever), but our findings for nutrients and endometrial cancer did not vary substantially across these exposures.

Finally, we assessed percentage of energy from total fat and from carbohydrates, as well as total fiber (g/1000 kcal) in relation to endometrial cancer risk (Figures 1–3). The percentage of energy from total fat was associated with a non-significantly lower risk of endometrial cancer (top vs. bottom category RR=0.87, 95% CI=0.65, 1.15, P_trend=0.13). Animal fat had similar associations (data not shown). The percentage of energy from carbohydrates was positively associated with risk (top vs. bottom category RR=1.30, 95% CI=0.98, 1.73, P_trend=0.03). Total fiber was associated with a significantly increased risk (top vs. bottom category RR=1.26, 95% CI=0.98, 1.62, P_trend=0.02), although this association was attenuated and became non-significant after further adjustment for percentage of energy from carbohydrates. After stratification, similar to what was seen in Table 5, the associations of cancer risk with fat and carbohydrates were stronger among premenopausal women (data not shown).

Figure 1.

Cumulative Average Intake of % of Energy from Total Fat and Risk of Endometrial Cancer, NHS Cohort (1980–2006)

Figure 3.

Cumulative Average Intake of Total Fiber and Risk of Endometrial Cancer, NHS Cohort (1980–2006)

DISCUSSION

In this prospective study, intakes of most dietary fats and carbohydrates were not clearly related to the risk of endometrial cancer overall, although a possible positive association with carbohydrate intake was suggested. In contrast to our hypothesis, total and cereal fiber were modestly positively associated with risk, but these associations were no longer significant after controlling for carbohydrate intake. Our data also suggest that some of these associations may vary by menopausal status.

In the majority of case-control studies, dietary fat or animal food intake has been positively associated with risk of endometrial cancer (11–19, 35, 36). Several case-control studies reported no association (22–24) or a weak inverse association with mono-unsaturated fat intake (24). In one of two other cohort studies to assess these associations, the Canadian National Breast Screening Study, most macronutrients were not related to the risk of endometrial cancer, but a decreased risk was observed with animal fat intake (RR in highest quartile= 0.60, 95%CI=0.40, 0.90) (25) among postmenopausal women. In another U.S. cohort study among postmenopausal women with 216 cases, dietary intake of most animal foods was not related to or was only weakly related to risk (26). In a recent meta-analysis, a positive association with total, saturated, and animal fat was observed in case-control studies, however, the limited available cohort data did not support these associations (12).

Although our study found little association overall between glycemic load/carbohydrates and cancer risk, carbohydrate intake was significantly positively associated with risk among premenopausal women. Several other studies have reported modest positive associations (27–31) as well. In the prospective Iowa Women’s Health Study, a positive association was observed between glycemic load and risk (top vs. bottom quintile RR=1.46, 95% CI = 1.02, 2.08; P_trend = 0.02) among nondiabetic postmenopausal women (29). The Canadian National Screening Study reported that glycemic load, but neither carbohydrates nor the glycemic index, was positively associated with risk among premenopausal (RR in highest quartile=1.55, 95%CI=1.05, 2.29) and obese women (RR in highest quartile=1.88, 95%CI= 1.08, 3.29) (31). The Swedish Mammography Cohort Study found RRs comparing extreme quartiles of 1.90 (95% CI= 0.84, 4.31) for carbohydrate intake and 2.99 (95% CI=1.17, 7.67) for glycemic load among overweight women with low physical activity (30). In the European Prospective Investigation into Cancer and Nutrition cohort study, although total carbohydrates and glycemic index/load were not associated with endometrial cancer overall, total carbohydrate intake was associated with increased risk among postmenopausal women (RR in highest quartile=1.26, 95%CI=0.95, 1.65) (28). In an Italian hospital-based case-control study, glycemic index and glycemic load were significantly associated with elevated risk of endometrial cancer and the associations were stronger in older women, in those with higher BMI, and in PMH users (27). Although several other studies found no associations between carbohydrates and endometrial cancer (18, 25), results from the above studies suggested glycemic load/carbohydrates might have modest positive associations with endometrial cancer risk which are generally consistent with the positive association we observed among premenopausal women.

In our study, most fat subtypes had no significant associations with endometrial cancer except for total and animal fat which were associated with a possible nonlinear decreased risk in the small group of premenopausal women. We also observed a nonlinear increased risk associated with carbohydrate intake among premenopausal women. Because of the strong inverse correlation between these two macronutrients, it is hard to distinguish their effects and thus these associations need to be assessed in even larger studies. The biological mechanisms for these possible associations are unclear. High-glycemic-index diets are thought to be associated with hyperinsulinemia and decreased insulin sensitivity (6). Higher circulating plasma insulin levels have been associated with lower sex hormone-binding globulin (SHBG) production, leading to higher free estrogen levels (37–41). Among premenopausal women, insulin provides a key stimulus to ovarian androgen synthesis, especially among women with polycystic ovary syndrome, and therefore, by inducing anovulation and progesterone deficiency (6), may increase risk of endometrial cancer. To our knowledge, no prior prospective studies have assessed insulin levels and risk of endometrial cancer in premenopausal women. A case-control study nested within the European Prospective Investigation into Cancer and Nutrition found that women with elevated serum levels of C-peptide had a modestly increased risk of endometrial cancer, suggesting hyperinsulinaemia may influence endometrial cancer risk among both pre- and post-menopausal women(42). In a prospective case-cohort study, a positive association was found between serum insulin level and risk of endometrial cancer among post-menopausal women(43).

Dietary fiber was proposed to have an inverse association with endometrial cancer, possibly by increasing the fecal excretion of estrogens and thereby reducing plasma estrogen levels (44, 45). However, in our study, we did not observe inverse associations with total dietary fiber or fiber subtypes. Cereal fiber had a stronger positive association with endometrial cancer risk among postmenopausal women, but there was no clear trend. The results from previous case-control studies and cohort studies are inconsistent. Most of the case-control studies supported the hypothesis that dietary fiber decreased the risk of endometrial cancer (13, 14, 17, 21, 23). In a meta-analysis, an inverse association between fiber intake and risk was observed (RR= 0.71, 95% CI=0.59, 0.85) comparing the top vs. bottom dietary fiber intake) from eight case-control studies(46). In contrast, in the only prospective study that evaluated this association, no association was noted (25, 46).

In our secondary analysis, associations of percent of energy from fat/carbohydrates and grams of fiber per 1000 kcal with risk were similar to those of energy-adjusted factors. The non-significant or borderline significant associations of non-energy adjusted intakes were attenuated after adjusting for total energy in the multivariate models, suggesting that if there is any association of non-energy adjusted intakes and cancer risk, it is likely due to total energy intake.

In our large prospective cohort study, we collected repeated dietary assessments over two decades. The prospective nature and high follow-up rate minimized recall and selection biases. The repeated dietary assessments reduce measurement error, which should result in more accurate estimates, although some non-differential misclassification is unavoidable. Residual confounding is minimized in this study, since potential risk factors are tightly controlled, and adjusting for covariates changed the results only slightly. However, caution is warranted in interpreting these findings, because of the small number of premenopausal cases (n=93). In multivariable models, we adjusted for BMI, hypertension, and diabetes, factors that could be on the causal pathway linking dietary factors with endometrial cancer, thus raising the possibility of statistical over-adjustment. However, the composition of the diet, independent of its influence on energy balance, was of primary interest in this analysis hence accounting for other factors related to energy balance was appropriate. Also of note, in our previous analyses, the percentage of calories from fat was only weakly associated with weight gain(47) and, in several randomized trials of weight loss, those assigned a low-fat diet did not lose more weight than those assigned other types of reduced calorie diets(48, 49). Also, adjusting for hypertension and diabetes did not substantially alter our results.

In summary, the findings in this prospective study did not support the hypothesis that dietary fat is an important cause of endometrial cancer. Although we found no overall associations between dietary fat, fiber or carbohydrates with endometrial cancer, several of the associations appeared to vary by menopausal status and these warrant evaluation in other prospective studies.

Figure 2.

Cumulative Average Intake of % of Energy from Carbohydrates and Risk of Endometrial Cancer, NHS Cohort (1980–2006)