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Original Contribution |

Low-Fat Dietary Pattern and Risk of Colorectal Cancer:  The Women's Health Initiative Randomized Controlled Dietary Modification Trial FREE

Shirley A. A. Beresford, PhD; Karen C. Johnson, MD; Cheryl Ritenbaugh, PhD; Norman L. Lasser, MD; Linda G. Snetselaar, PhD; Henry R. Black, MD; Garnet L. Anderson, PhD; Annlouise R. Assaf, PhD; Tamsen Bassford, MD; Deborah Bowen, PhD; Robert L. Brunner, PhD; Robert G. Brzyski, MD; Bette Caan, DrPH; Rowan T. Chlebowski, MD; Margery Gass, MD; Rosanne C. Harrigan, EdD; Jennifer Hays, PhD; David Heber, MD; Gerardo Heiss, MD; Susan L. Hendrix, DO; Barbara V. Howard, PhD; Judith Hsia, MD; F. Allan Hubbell, MD; Rebecca D. Jackson, MD; Jane Morley Kotchen, MD; Lewis H. Kuller, MD; Andrea Z. LaCroix, PhD; Dorothy S. Lane, MD; Robert D. Langer, MD; Cora E. Lewis, MD; JoAnn E. Manson, MD; Karen L. Margolis, MD; Yasmin Mossavar-Rahmani, PhD; Judith K. Ockene, PhD; Linda M. Parker, DSc; Michael G. Perri, PhD; Lawrence Phillips, MD; Ross L. Prentice, PhD; John Robbins, MD; Jacques E. Rossouw, MD; Gloria E. Sarto, MD; Marcia L. Stefanick, PhD; Linda Van Horn, PhD; Mara Z. Vitolins, DrPH; Jean Wactawski-Wende, PhD; Robert B. Wallace, MD; Evelyn Whitlock, MD
[+] Author Affiliations

Author Affiliations: University of Washington, Seattle (Dr Beresford); University of Tennessee Health Science Center, Memphis (Dr Johnson); University of Arizona, Tucson/Phoenix (Drs Ritenbaugh and Bassford); University of Medicine and Dentistry of New Jersey, Newark (Dr Lasser); University of Iowa, Iowa City/Davenport (Drs Snetselaar and Wallace); Rush University Medical Center, Chicago, Ill (Dr Black); Fred Hutchinson Cancer Research Center, Seattle, Wash (Drs Anderson, Bowen, LaCroix, and Prentice); Brown University, Providence, RI (Dr Assaf); University of Nevada, Reno (Dr Brunner); University of Texas Health Science Center, San Antonio (Dr Brzyski); Kaiser Permanente Division of Research, Oakland, Calif (Dr Caan); Harbor-UCLA Research and Education Institute, Torrance, Calif (Dr Chlebowski); University of Cincinnati, Cincinnati, Ohio (Dr Gass); University of Hawaii, Honolulu (Dr Harrigan); Baylor College of Medicine, Houston, Tex (Dr Hays); University of California at Los Angeles (Dr Heber); University of North Carolina, Chapel Hill (Dr Heiss); Wayne State University School of Medicine/Hutzel Hospital, Detroit, Mich (Dr Hendrix); MedStar Research Institute/Howard University, Washington, DC (Dr Howard); George Washington University, Washington, DC (Dr Hsia); University of California, Irvine (Dr Hubbell); Ohio State University, Columbus (Dr Jackson); Medical College of Wisconsin, Milwaukee (Dr Kotchen); University of Pittsburgh, Pittsburgh, Pa (Dr Kuller); State University of New York at Stony Brook (Dr Lane); University of California at San Diego, La Jolla/Chula Vista (Dr Langer); University of Alabama at Birmingham (Dr Lewis); Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (Dr Manson); University of Minnesota, Minneapolis (Dr Margolis); Albert Einstein College of Medicine, Bronx, NY (Dr Mossavar-Rahmani); University of Massachusetts/Fallon Clinic, Worcester (Dr Ockene); University of Miami, Miami, Fla (Dr Parker); University of Florida, Gainesville/Jacksonville (Dr Perri); Emory University, Atlanta, Ga (Dr Phillips); University of California at Davis, Sacramento (Dr Robbins); National Heart, Lung, and Blood Institute, Bethesda, Md (Dr Rossouw); University of Wisconsin, Madison (Dr Sarto); Stanford Prevention Research Center, Stanford, Calif (Dr Stefanick); Northwestern University, Chicago/Evanston, Ill (Dr Van Horn); Wake Forest University School of Medicine, Winston-Salem, NC (Dr Vitolins); University at Buffalo, Buffalo, NY (Dr Wactawski-Wende); and Kaiser Permanente Center for Health Research, Portland, Ore (Dr Whitlock).

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JAMA. 2006;295(6):643-654. doi:10.1001/jama.295.6.643.
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Context Observational studies and polyp recurrence trials are not conclusive regarding the effects of a low-fat dietary pattern on risk of colorectal cancer, necessitating a primary prevention trial.

Objective To evaluate the effects of a low-fat eating pattern on risk of colorectal cancer in postmenopausal women.

Design, Setting, and Participants The Women’s Health Initiative Dietary Modification Trial, a randomized controlled trial conducted in 48 835 postmenopausal women aged 50 to 79 years recruited between 1993 and 1998 from 40 clinical centers throughout the United States.

Interventions Participants were randomly assigned to the dietary modification intervention (n = 19 541; 40%) or the comparison group (n = 29 294; 60%).The intensive behavioral modification program aimed to motivate and support reductions in dietary fat, to increase consumption of vegetables and fruits, and to increase grain servings by using group sessions, self-monitoring techniques, and other tailored and targeted strategies. Women in the comparison group continued their usual eating pattern.

Main Outcome Measure Invasive colorectal cancer incidence.

Results A total of 480 incident cases of invasive colorectal cancer occurred during a mean follow-up of 8.1 (SD, 1.7) years. Intervention group participants significantly reduced their percentage of energy from fat by 10.7% more than did the comparison group at 1 year, and this difference between groups was mostly maintained (8.1% at year 6). Statistically significant increases in vegetable, fruit, and grain servings were also made. Despite these dietary changes, there was no evidence that the intervention reduced the risk of invasive colorectal cancer during the follow-up period. There were 201 women with invasive colorectal cancer (0.13% per year) in the intervention group and 279 (0.12% per year) in the comparison group (hazard ratio, 1.08; 95% confidence interval, 0.90-1.29). Secondary analyses suggested potential interactions with baseline aspirin use and combined estrogen-progestin use status (P = .01 for each). Colorectal examination rates, although not protocol defined, were comparable between the intervention and comparison groups. Similar results were seen in analyses adjusting for adherence to the intervention.

Conclusion In this study, a low-fat dietary pattern intervention did not reduce the risk of colorectal cancer in postmenopausal women during 8.1 years of follow-up.

Clinical Trials Registration ClinicalTrials.gov Identifier: NCT00000611

Figures in this Article

The Women's Health Initiative (WHI) Dietary Modification Trial is a randomized controlled trial designed in 1991-1992 to test whether a low-fat eating pattern with increased fruits, vegetables, and grains reduces the risk of breast cancer, colorectal cancer, or, secondarily, coronary heart disease in postmenopausal women. At that time, international comparisons suggested that countries with 50% lower fat intake than the US population had approximately one third the risk of colorectal cancer.1,2 Migration studies supported this hypothesis. Women migrating from countries with low fat consumption to countries with high fat consumption experienced the higher colorectal cancer rates of their new country.3,4 Fairly consistent evidence existed for an effect of dietary fat, vegetables and fruits, and grains on colorectal cancer risk from within-country observational studies,2,58 although the protective effect of lower fat intake was no longer clear after adjusting for energy intake.2,9 The WHI Dietary Modification Trial is the first randomized trial to directly address the health effects of a low-fat eating pattern in predominantly healthy postmenopausal women from diverse racial/ethnic, geographic, and socioeconomic backgrounds. This article reports the principal results for colorectal cancer.

Study Population

Recruitment of postmenopausal women aged 50 to 79 years who were interested in 1 or more components of the clinical trials was conducted by 40 clinical centers throughout the United States.

Recruitment was typically by direct mail from purchased lists,10 enhanced by advertising and other community promotion. Details of the study design and recruitment have been published previously.1012 Eligibility criteria for the dietary modification trial included willingness to be randomized to an intervention or comparison group and having a fat intake at baseline of 32% or more of total calories as evaluated by the WHI food frequency questionnaire.13 Major exclusions made at screening included women with any prior colorectal cancer or breast cancer, other cancers in the last 10 years, type 1 diabetes, medical conditions with predicted survival of less than 3 years, or adherence concerns, including having meals frequently prepared away from home.

Between 1993 and 1998, 48 835 eligible women were randomly assigned to an intervention or a comparison group in the ratio of 2:3 for cost-efficiency (Figure 1). Randomization was based on a permuted-block algorithm with block sizes of 5, 10, or 15 and stratified by clinical center and age group (50-54, 55-59, 60-69, and 70-74 years).14 All women provided written informed consent at baseline, as approved by institutional review boards. Of the women randomized into this trial, 16% were simultaneously randomized into 1 of the arms of the hormone therapy trial (conjugated equine estrogen trial or estrogen-plus-progestin trial)11 and 25 210 were subsequently randomized into a trial of calcium and vitamin D supplementation.14

Figure 1. Participant Flow in the Dietary Modification Component of the Women's Health Initiative
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*Categories are presented for which exclusions are known. More than 1 reason could be given for exclusion.

Intervention

The intervention was designed to promote dietary change with the goals of reducing total fat to 20% of energy intake, increasing vegetables and fruits to at least 5 servings daily and grains to at least 6 servings daily.15,16 We refer to this as a low-fat eating pattern. The intervention did not include total energy reduction or weight loss goals. Although not a separate focus of the intervention, it was anticipated that by reducing fat to 20% of energy intake, saturated fat would also be reduced (7% energy intake). The intervention was an intensive behavioral modification program, using 18 group sessions in the first year and quarterly sessions thereafter, led by specially trained and certified nutritionists.15 Each participant was given her own dietary fat-gram goal according to her height. The intervention emphasized self-monitoring techniques and introduced other tailored and targeted strategies, such as motivational interviewing,17 to lower fat intake throughout the intervention period. Comparison group participants received a copy of the US Department of Health and Human Services' Dietary Guidelines for Americans18 and other health-related materials but were not asked to make dietary changes.

Evaluation Procedures

Dietary intake was monitored using the WHI food frequency questionnaire at 1 year13 and in a rotating one-third subsample every year thereafter. Reported values after year 1 are based on the 3-year intervals in which all participants were assessed. At baseline, all women completed a 4-day food record after receiving instruction in keeping food records. Nutrition staff at each clinical center checked each record for completeness. The records of women who developed colorectal cancer were analyzed in a case-case design to contrast intervention and comparison cases according to baseline dietary intake.

Fasting blood specimens were obtained at baseline, at the first annual follow-up, and in a 5.8% subsample (n = 2816) at years 3 and 6 and were centrally stored at −70°C. Biomarkers of dietary change (plasma total cholesterol, plasma triglycerides, serum γ-tocopherol and serum total carotenoids [α- and β-carotene, β-cryptoxanthin, zeaxanthin, and lutein]) were measured in baseline and year 3 specimens from the 5.8% subsample after excluding participants experiencing a trial end point during the previous year.

Women completed a medical update questionnaire every 6 months, and medical records were sought for all women reporting colorectal cancer. Locally trained, blinded physician adjudicators reviewed medical records and pathology reports from the self-reported colorectal cancer cases (available for 97%). Colorectal cancer was confirmed by blinded central adjudicators and coded using the 1992 Surveillance, Epidemiology, and End Results system.19 In all clinical centers, study personnel involved in delivery of the dietary intervention were not part of outcomes ascertainment or adjudication.

The medical update also monitored the frequencies of bowel examinations and incident intestinal polyps or adenomas. Frequency of bowel examinations was not dictated by the WHI protocol. Decisions regarding screening and diagnostic workups for colorectal cancer were made by the women's personal physicians.

Definitions of Outcomes and Subgroups

The primary study outcome was invasive colorectal cancer incidence; subclassifications of colorectal cancer were secondary outcomes. These include groupings within the intestinal tract of distinct etiology20; namely, invasive cancer of the proximal colon (cecum, ascending colon, hepatic flexure of colon, transverse colon, splenic flexure), of the distal colon (descending colon, sigmoid colon),2123 and of the rectum, including rectosigmoid junction.24 Results are also presented for total cancer incidence, total cancer mortality, total mortality, and a global index to provide a context for the colorectal cancer results. Throughout the trial, a global index end point was monitored. This consisted of the first to occur of invasive breast cancer, colorectal cancer, coronary heart disease, or death from other causes. The intervention effects on breast cancer and cardiovascular disease are reported separately.25,26

Potential interactions were explored in subgroups of participants identified prior to analysis. These were baseline health characteristics known to influence colorectal cancer risk and baseline dietary patterns. Two post hoc interactions were also examined with composite variables of baseline hormone therapy use and assignment to the active treatment group in the hormone therapy trial.

Statistical Analysis

The protocol-designated analysis to evaluate the efficacy of the low-fat eating pattern intervention was a weighted log-rank test, with weights defined by time since randomization as 0 at randomization rising linearly to 1 at 10 years of follow-up, and constant (at 1) thereafter. Design assumptions included a linear dependence of colorectal cancer risk on percentage of energy from fat, with 80% lower colorectal cancer incidence for a 20%- compared with a 40%-energy-from-fat diet (from observational studies2,5,9). Information from the Women's Health Trial27 suggested that women in the intervention group would consume a 13% lower percentage of energy from fat in the intervention compared with the comparison group at 1 year, which was projected to decrease linearly to an 11% difference by 10 years. With a sample size of 48 000 women, the study had 90% power to detect a 20% relative reduction in colorectal cancer incidence over a mean 9 years of follow-up.11

Intervention effects on incidence rates were assessed using time-to-event methods based on the intention-to-treat principle. Women without the diagnosis were censored for that event at the time of their last follow-up contact. Comparisons of rates of colorectal cancer (intervention effects) are presented as hazard ratios (HRs) and nominal 95% confidence intervals (95% CIs) from Cox regression models, stratified by age, prior colorectal cancer, and randomization status in the hormone therapy trial. Although history of colorectal cancer was an exclusion criterion, after randomization, 16 women were found to have reported prior colorectal cancer. Consistent with the intention-to-treat principle, these women were included as a separate stratum in the Cox models, but these women reported no further diagnoses of colorectal cancer. Adjustment for participation in the calcium and vitamin D trial was based on the randomization date as a time-dependent covariate. Cumulative disease rates over time were estimated using the Kaplan-Meier method. Annualized incidence rates were calculated as the ratio of number of events to total person-years of follow-up. Since colon cancer has a long preclinical phase,28 perhaps as long as 10 years, analyses exploring variation in intervention effect by period of follow-up were conducted by classifying events into early (0-24 months), middle (25-60 months), and late (≥61 months) follow-up. A test for trend with time was used to assess departure from nonproportional effects.

Tests for interactions were performed as likelihood ratio tests in expanded Cox models. Continuous variables were tested on the original linear scale but are described with relevant categories. Subgroups using baseline dietary factors obtained from 4-day food records were analyzed using a case-only approach,29,30 essentially equivalent to a test that would arise from a “full-cohort” analysis of interaction. Because about 23 interactions were tested, at least 1 significant test would be expected to occur by chance at the .05 level of significance.

We examined the extent to which the intervention was associated with change in other hypothesized dietary risk factors for colorectal cancer, including biomarkers. Differential changes at 3 years were expressed as a percentage of initial mean.

Analyses were carried out using SAS statistical software, version 9.1 (SAS Institute Inc, Cary, NC). P<.05 was considered statistically significant for all analyses.

A total of 19 541 women (40%) were assigned to the intervention group and 29 294 (60%) were assigned to the comparison group. The last intervention session was held in August 2004, and end points were accrued to the study through March 2005. Mean length of follow-up was 8.1 (SD, 1.7) years (maximum, 11.2 years).

Baseline Characteristics

Colorectal cancer risk characteristics were very similar in the 2 study groups, including age, self-reported race/ethnicity, education, family history of colorectal cancer, prior colorectal cancer screening, alcohol use, and mean intake of energy, fat, fiber, red meat, vegetables and fruits, grains, calcium, and folate (Table 1). There were small imbalances in 3 characteristics: reported use of aspirin at baseline with respect to both frequency (P = .03) and duration (P = .01), proportion of women randomized to the various groups in the hormone therapy trials (P = .05), and proportion of women subsequently joining the randomized trial of calcium and vitamin D supplementation (P<.001).

Table Graphic Jump LocationTable 1. Baseline Participant Characteristics Pertinent to Colorectal Cancer Risk
Dietary Behavior Change

By the end of the first year, the difference in percentage of energy from fat between the comparison group and the interventions groups was 10.7% (Figure 2). During the entire intervention period, the differential reduction in percentage of energy from fat was about 70% of the design goals of the trial. Relatively few women met the dietary target of 20% energy from fat (31.4% at year 1 and 14.4% at year 6). Reductions in saturated fat consumption and increases in fruit and vegetable servings and servings of grain (Figure 2) were statistically significant by 1 year. The intervention was also associated with statistically significant increases in dietary intake of folate and in plasma total carotenoids and reductions in reported red meat consumption, total vitamin E intake, weight, serum cholesterol, and plasma γ-tocopherol (Table 2).

Figure 2. Differences in Mean Dietary Intake Between Intervention and Comparison Groups for Each Year of Follow-up
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Differences were calculated by subtracting comparison group data from intervention group data. Error bars indicate 95% confidence intervals.

Table Graphic Jump LocationTable 2. Percentage Changes From Baseline to Year 3 for Dietary Factors and Selected Biomarkers Related to Colorectal Cancer Risk*
Colorectal Cancer Risk and Other Clinical Outcomes

As of March 31, 2005, there were 201 cases of invasive colorectal cancer (0.13% per year) in the intervention group and 279 (0.12% per year) in the comparison group, similar to national statistics for women in this age range (0.12%).19 The WHI low-fat eating pattern intervention did not reduce the risk of invasive colorectal cancers (HR, 1.08; 95% CI, 0.90-1.29) (Table 3). Adjustment for the small imbalance in aspirin use did not alter these results (HR, 1.08; 95% CI, 0.90-1.29). The cumulative hazards for colorectal cancer in the 2 groups were very similar over follow-up time (weighted P = .29) (Figure 3). There was no evidence of a time trend for invasive colorectal cancer in secondary analyses (P = .60 for trend), with HRs in the early, middle, and late periods of 1.24 (95% CI, 0.85-1.81), 0.91 (95% CI, 0.68-1.22), and 1.19 (95% CI, 0.89-1.60), respectively.

Table Graphic Jump LocationTable 3. Annualized Incidence Rate of Outcomes in Intervention vs Comparison Groups
Figure 3. Kaplan-Meier Estimated Cumulative Hazards for Invasive Colorectal Cancer (N = 48 835)
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HR indicates hazard ratio; CI, confidence interval.

There was no evidence of reduced risk for any category of colorectal cancer outcome associated with the intervention. The estimated intervention effects in proximal and distal colon cancer were somewhat different (HRs, 1.25 vs 0.86; P = .07 from likelihood ratio test), but there was no other evidence of differential effect by colorectal cancer subsite. None of the HRs for total cancer incidence, total cancer mortality, global index, or total mortality were statistically significant. The annualized incidence rates of colon polyps or adenomas (self-report) were lower in the intervention group than in the comparison group (2.16% vs 2.35%, respectively; HR, 0.91; 95% CI, 0.87-0.95). No differences were seen between groups for tumor characteristics (Table 4).

Table Graphic Jump LocationTable 4. Annualized Incidence Rate of Invasive Colorectal Cancer by Tumor Characteristics in Intervention vs Comparison Groups

Colorectal clinical examination rates were similar between the intervention groups (Figure 4). There were small differences in the percentage of women with no colonoscopy or sigmoidoscopy during follow-up (45.7% for intervention vs 44.1% for comparison; P = .04). Overall, 10.6% in the intervention group and 9.9% in the comparison group had neither colon nor rectal screenings during follow-up (P = .30).

Figure 4. Bowel Examinations by Dietary Intervention vs Comparison Group and Follow-up Year
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Subgroup Analyses

Among the 23 subgroups examined, only the interactions with aspirin use and the composite variable of combined hormone use (personal use at baseline or randomization to active estrogen plus progestin) were significant at the .01 level (Figure 5). Although the risk of colon cancer increased with age, there was no interaction of intervention with age at baseline (P = .18). Intervention HRs were not significantly different among the 4 different racial/ethnic groups with sufficient numbers of events (P = .78). The estimated intervention effect was lower in baseline high-dose aspirin users compared with that in nonusers (P = .01); however, the higher incidence observed (0.19%) in this subgroup of comparison women is an anomaly, suggesting that other factors may be relevant. No interaction was seen with duration of aspirin use, statin use, or nonaspirin nonsteroidal anti-inflammatory drug use at baseline, or with aspirin use during follow-up, examined as a time-dependent covariate.

Figure 5. Invasive Colorectal Cancer Hazard Ratios and Annualized Incidence by Baseline Demographic and Medical History Characteristics
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Error bars indicate 95% confidence intervals.
*Interaction test from likelihood ratio test (factors on the continuous scale were tested as continuous variables when possible.
†Cox regression models stratified according to age group, hormone therapy study participation, and prevalence condition; calcium and vitamin D study participation was adjusted as a time-dependent variable.
‡Body mass index was calculated as weight in kilograms divided by the square of height in meters.

Using data from the baseline 4-day food record of cases, no interactions with intervention effect were found with energy intake, percentage of energy from fat, percentage of energy from saturated fat, or dietary fiber. Similarly, using baseline food frequency questionnaire data, there were no interactions with servings of vegetables and fruits (Figure 6), of red meat, or of grains or folate intake. The interaction test with baseline alcohol consumption was not significant (P = .09) and did not appreciably change when folate intake was considered.

Figure 6. Invasive Colorectal Cancer Hazard Ratios and Annualized Incidence by Baseline Dietary Factors
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Error bars indicate 95% confidence intervals.
*Interaction test from likelihood ratio test (factors on the continuous scale were tested as continuous variables when possible.
†Cox regression models stratified according to age group, hormone therapy study participation, and prevalence condition; calcium and vitamin D study participation was adjusted as a time-dependent variable.
‡Case-only analysis using 4-day food record data; no annualized rates available.
§Data are from food frequency questionnaire.

Further Analyses

To explore the effect of nonadherence to trial activities, a Cox regression model was fit censoring follow-up for a participant when she first became nonadherent (did not attend the annual clinic visit or, for intervention women, completed 50% or fewer intervention sessions in a given year). Inverse censoring probability weights, derived from Cox regression models of 18 baseline variables (demographic, dietary, psychosocial, family history of colorectal cancer, physical activity, body mass index, alcohol consumption, multivitamin use, and randomization into the hormone therapy trial) for intervention and comparison groups separately, were used to adjust for the imbalance created by the adherence censoring.25

Adherence rates from these models were 85%, 75%, and 66% at years 3, 6, and 9, respectively, among comparison women and 61%, 37%, and 25% among intervention women. The difference between adherent intervention vs adherent comparison women in percentage of energy from fat (from the food frequency questionnaire) was 12.1%, 11.4%, 10.4%, and 9.5% at years 1, 3, 6, and 9. The HR for colorectal cancer from the inverse probability–weighted analysis was 1.09 (95% CI, 0.88-1.36). Exploratory analyses using other adherence measures did not appreciably change the interpretation.

An intervention aimed toward a low-fat eating pattern did not reduce colorectal cancer risk in postmenopausal women. Despite a significant change in fat intake and increases in vegetable, fruit, and grain consumption, the intervention hazard ratio is in the direction of an increased risk. There were no substantial differences in tumor characteristics or in rates of bowel screening between groups. Although self-reported incidence of colorectal polyps or adenomas was lower in the intervention group, no evidence of a trend toward lower colorectal cancer risk with time in the intervention group was observed over the mean 8.1-year study period.

These findings are consistent with the findings from the Polyp Prevention Trial,31 a secondary prevention trial of polyp recurrence, which had a similar goal for fat, fruit, and vegetable intake but also included a goal of 18 g/1000 kcal of dietary fiber.32 The Polyp Prevention Trial observed no effect on polyp recurrence in the 2079 participants followed up for 4 years.32 A small trial in Toronto, Ontario, of high fiber and low fat showed no effect on recurrence of neoplastic polyps, but, within an intensive counseling subgroup, concentrations of fecal bile acids appeared to be reduced.33 A small factorial trial in Australia of a low-fat intervention, β-carotene supplementation, or wheat bran supplementation found no reduction in recurrence rates of adenomas but suggested that the combination of low fat and wheat bran reduced the transition from smaller to larger adenomas.34

Since the WHI Dietary Modification Trial was designed, the hypothesized relationship between dietary fat and risk of colorectal cancer has been questioned.35 More recently, higher red meat consumption has been associated with increased colorectal cancer risk,23,3639 particularly in the distal colon.23 The putative mechanism may be related to heme, the iron carrier of red meat, rather than to its fat content.23 In the WHI, the dietary intervention reduced red meat consumption (Table 2), with no apparent overall benefit on colorectal cancer risk but, perhaps, some shift in risk in distal vs proximal colon cancers.

Mixed support exists for an influence of vegetables and fruits on colorectal cancer risk.37,4042 Some of the antioxidants they contain have not proved efficacious in reducing colorectal adenomas or preventing incident colorectal cancer in randomized trials.4345 Regular consumption of alcohol has been associated with elevated risk of colorectal cancer in some prospective studies, particularly among persons with low folate status.46 This pattern was not found in the comparison group of this study. Observations in East Africa by Burkitt47 led to the hypothesis that very high fiber reduces colorectal cancer risk. This has mixed support from observational studies4850 and polyp and adenoma recurrence trials.31,33,34,51,52 A European trial found an adverse effect of soluble fiber on colorectal adenoma recurrence,51 while an Arizona trial found no effect of wheat bran supplement on colorectal adenoma recurrence.52 Our study is consistent with lack of association in that women in the intervention group modestly increased their fiber (Table 2) with no apparent benefit over 8.1 years of follow-up.

The observed interactions between the intervention and baseline aspirin use, and between intervention and use of combined hormone therapy, are consistent with synergistic effects of a low-fat dietary pattern and these potentially protective agents. However, given the large number of interactions tested, these findings could also have occurred by chance.

While the trial was ongoing, national dietary recommendations moved from recommending less than 30% of energy from fat intake through 1997 to 25% to 35% of energy from fat in 2002.53 From National Health and Nutrition Examination Survey (NHANES) data, in 1977, women reported consuming 40.5% of their energy from fat, while in 1987, the average was only 35.9%,54 and in 2000, the average was 33% (NHANES 1999-2000). Organizations including the National Cancer Institute, American Cancer Society, and Institute for Cancer Prevention have recommended both lower fat intake and increased vegetable and fruit use.55,56

One explanation for a lack of intervention effect on colorectal cancer could be that the intervention did not achieve a large enough difference between the intervention and comparison groups. Although the changes achieved were substantial, and likely as large as could be achieved in a trial of free-living individuals, they fell short of the original design assumptions based on the Women's Health Trial studies.27 Using food frequency data, the WHI intervention on average achieved only about 70% of the designed reduction in fat. If design assumptions are revised to take into account this departure from goal, the predicted HR would have been 0.86, an effect size excluded by these results. The power to detect this effect size under the observed comparison group incidence rate and the achieved adherence is approximately 40%.

Whether greater adherence, intervention of longer duration, or initiation of change at an earlier age would influence colorectal cancer risk remain unanswered questions. The self-reported first occurrence of polyps or adenomas was lower in dietary intervention women, suggesting that longer follow-up (currently planned) may reveal delayed benefit in favor of the intervention. Yet no time trends regarding colorectal cancer risk over 8 years of follow-up have been seen. To the extent that the WHI Dietary Modification Trial intervention addressed the recommendations from national organizations, the current results suggest that changing dietary patterns to meet these recommendations in mid to late life will have limited or no benefit in preventing colorectal cancers in postmenopausal women.

The strengths of this study are its randomized design, long-term follow-up, large numbers of participants, diversity of race/ethnicity and socioeconomic status, and high retention rate. The limitations of this study include not attaining intervention goals as designed for reducing fat intake or achieving large separation from the comparison group in increased fruit, vegetable, or grain intake. Thus the potential intervention effect of the WHI low-fat dietary pattern may be underestimated. Furthermore, there was no study-specified colonoscopy, nor was there systematic screening for adenomatous polyps; hence, the incidence of both colorectal cancer and polyps or adenomas would be underestimated.

In conclusion, there is no evidence that a low-fat dietary pattern intervention reduces colorectal cancer risk over an average of 8.1 years of follow-up. Evidence from this study, along with that from polyp prevention trials, strongly suggests that lowering dietary fat intake and increasing fruit, vegetable, and fiber intake in mid to late life cannot be expected to reduce the risk of colorectal cancer in this length of time.

Corresponding Author: Shirley A. A. Beresford, PhD, Department of Epidemiology, University of Washington, Box 357236, Seattle, WA 98195-7236 (beresfrd@u.washington.edu).

Author Contributions: Dr Prentice had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Ritenbaugh, Lasser, Snetselaar, Black, Anderson, Assaf, Bassford, Bowen, Harrigan, Hays, Kuller, Manson, Margolis, Prentice, Robbins, Rossouw, Van Horn, Wactawski-Wende, Wallace.

Acquisition of data: Beresford, Johnson, Ritenbaugh, Lasser, Snetselaar, Black, Assaf, Bassford, Brunner, Brzyski, Caan, Chlebowski, Gass, Harrigan, Hays, Heber, Heiss, Hendrix, Howard, Hsia, Hubbell, Jackson, Kotchen, Kuller, LaCroix, Lane, Langer, Lewis, Manson, Margolis, Mossavar-Rahmani, Ockene, Parker, Perri, Phillips, Prentice, Robbins, Sarto, Stefanick, Van Horn, Wactawski-Wende, Wallace, Whitlock.

Analysis and interpretation of data: Beresford, Johnson, Ritenbaugh, Lasser, Snetselaar, Black, Anderson, Bowen, Caan, Chlebowski, Howard, Jackson, Kuller, LaCroix, Lewis, Manson, Mossavar-Rahmani, Perri, Prentice, Rossouw, Stefanick, Van Horn, Vitolins, Wactawski-Wende.

Drafting of the manuscript: Beresford, Ritenbaugh, Howard, Mossavar-Rahmani, Van Horn, Vitolins.

Critical revision of the manuscript for important intellectual content: Beresford, Johnson, Ritenbaugh, Lasser, Snetselaar, Black, Anderson, Assaf, Bassford, Bowen, Brunner, Brzyski, Caan, Chlebowski, Gass, Harrigan, Hays, Heber, Heiss, Hendrix, Howard, Hsia, Hubbell, Jackson, Kotchen, Kuller, LaCroix, Lane, Langer, Lewis, Manson, Margolis, Mossavar-Rahmani, Ockene, Parker, Perri, Phillips, Prentice, Robbins, Rossouw, Sarto, Stefanick, Van Horn, Wactawski-Wende, Wallace, Whitlock.

Statistical analysis: Anderson, Prentice.

Obtained funding: Beresford, Snetselaar, Black, Assaf, Bowen, Brunner, Heiss, Hendrix, Howard, Hubbell, Kuller, Lane, Langer, Lewis, Manson, Ockene, Prentice, Robbins, Rossouw, Stefanick, Van Horn, Wactawski-Wende, Wallace.

Administrative, technical, or material support: Beresford, Johnson, Ritenbaugh, Lasser, Snetselaar, Anderson, Assaf, Bassford, Brunner, Brzyski, Harrigan, Hays, Heber, Heiss, Hendrix, Hsia, Hubbell, Jackson, Kotchen, Kuller, Lane, Langer, Lewis, Manson, Margolis, Ockene, Perri, Phillips, Prentice, Robbins, Rossouw, Stefanick, Van Horn, Wactawski-Wende, Wallace, Whitlock.

Study supervision: Johnson, Black, Anderson, Assaf, Brunner, Chlebowski, Hays, Heiss, Hendrix, Howard, Hubbell, Ockene, Parker, Perri, Prentice, Robbins, Stefanick, Van Horn, Wallace.

Financial Disclosures: Dr Black has received research grants from Pfizer and AstraZeneca, was on the speaker’s bureaus for Pfizer, Novartis, Sanofi-Aventis, Bristol-Myers Squibb, Searle, Pharmacia, and Boehringer, and served as a consultant or on an advisory board for Myogen, Merck Sharp and Dohme, Novartis, Mylan-Bertek, Pfizer, Bristol-Myers Squibb, and Sanofi-Aventis. Dr Howard has served on the advisory boards of Merck, Schering Plough, and the Egg Nutrition Council, has received research support from Merck and Pfizer, and has consulted for General Mills. Dr Assaf is an employee of Pfizer. No other disclosures were reported.

Funding/Support: The Women's Health Initiative program was funded by the National Heart, Lung, and Blood Institute of the National Institutes of Health, Department of Health and Human Services.

Role of the Sponsor: The funding organization has representation on the Steering Committee, which governs the design and conduct of the study, the interpretation of the data, and the preparation and approval of manuscripts. The National Heart, Lung, and Blood Institute Program Office reviewed the manuscript.

WHI Investigators: For a complete list of the WHI investigators, see the companion article in this issue, “Low-Fat Dietary Pattern and Risk of Invasive Breast Cancer: The Women's Health Initiative Randomized Controlled Dietary Modification Trial” (JAMA . 2006;295:629-642.).

Acknowledgment: We gratefully acknowledge the dedicated efforts of the Women's Health Initiative participants and of key Women's Health Initiative investigators and staff, especially the contributions of LieLing Wu, MS, of the Clinical Coordinating Center of the Fred Hutchinson Cancer Research Center, Seattle, Wash, who contributed invaluable statistical expertise.

Carroll KK, Khor HT. Dietary fat in relation to tumorigenesis.  Prog Biochem Pharmacol. 1975;10:308-353
PubMed
Prentice RL, Sheppard L. Dietary fat and cancer: consistency of the epidemiologic data, and disease prevention that may follow from a practical reduction in fat consumption.  Cancer Causes Control. 1990;1:81-97
PubMed   |  Link to Article
McMichael AJ, Giles GG. Cancer in migrants to Australia: extending the descriptive epidemiological data.  Cancer Res. 1988;48:751-756
PubMed
Thomas DB, Karagas MR. Cancer in first and second generation Americans.  Cancer Res. 1987;47:5771-5776
PubMed
Howe GR, Benito E, Castelleto R.  et al.  Dietary intake of fiber and decreased risk of cancers of the colon and rectum: evidence from the combined analysis of 13 case-control studies.  J Natl Cancer Inst. 1992;84:1887-1896
PubMed   |  Link to Article
Steinmetz KA, Potter JD. Food-group consumption and colon cancer in the Adelaide Case-Control Study, I: vegetables and fruit.  Int J Cancer. 1993;53:711-719
PubMed   |  Link to Article
Steinmetz KA, Kushi LH, Bostick RM, Folsom AR, Potter JD. Vegetables, fruit, and colon cancer in the Iowa Women's Health Study.  Am J Epidemiol. 1994;139:1-15
PubMed
Trock B, Lanza E, Greenwald P. Dietary fiber, vegetables, and colon cancer: critical review and meta-analyses of the epidemiologic evidence.  J Natl Cancer Inst. 1990;82:650-661
PubMed   |  Link to Article
Howe GR, Aronson KJ, Benito E.  et al.  The relationship between dietary fat intake and risk of colorectal cancer: evidence from the combined analysis of 13 case-control studies.  Cancer Causes Control. 1997;8:215-228
PubMed   |  Link to Article
Hays J, Hunt JR, Hubbell FA.  et al.  The Women's Health Initiative recruitment methods and results.  Ann Epidemiol. 2003;13:(9 suppl)  S18-S77
PubMed   |  Link to Article
Women's Health Initiative Study Group.  Design of the Women's Health Initiative clinical trial and observational study.  Control Clin Trials. 1998;19:61-109
PubMed   |  Link to Article
Ritenbaugh C, Patterson RE, Chlebowski RT.  et al.  The Women's Health Initiative Dietary Modification trial: overview and baseline characteristics of participants.  Ann Epidemiol. 2003;13:(9 suppl)  S87-S97
PubMed   |  Link to Article
Patterson RE, Kristal AR, Tinker LF, Carter RA, Bolton MP, Agurs-Collins T. Measurement characteristics of the Women's Health Initiative food frequency questionnaire.  Ann Epidemiol. 1999;9:178-187
PubMed   |  Link to Article
Anderson GL, Manson J, Wallace R.  et al.  Implementation of the Women's Health Initiative study design.  Ann Epidemiol. 2003;13:(9 suppl)  S5-S17
PubMed   |  Link to Article
Tinker LF, Burrows ER, Henry H, Patterson RE, Rupp JW, Van Horn L. The Women's Health Initiative: overview of the nutrition components. In: Krummel DA, Kris-Etherton PM, eds. Nutrition in Women's Health. Gaithersburg, Md: Aspen; 1996:510-542
Women's Health Initiative Study Group.  Dietary adherence in the Women's Health Initiative Dietary Modification Trial.  J Am Diet Assoc. 2004;104:654-658
PubMed   |  Link to Article
Bowen D, Ehret C, Pedersen M.  et al.  Results of an adjunct dietary intervention program in the Women's Health Initiative.  J Am Diet Assoc. 2002;102:1631-1637
PubMed   |  Link to Article
US Department of Agriculture.  Dietary Guidelines for Americans. 3rd ed. Washington, DC: Dept of Health and Human Services; 1990
Ries LA, Kosary CL, Hankey BF.  et al.  SEER Cancer Statistics Review, 1975-2002. 2005. Available at: http://seer.cancer.gov/csr/1975_2002/. Accessed October 10, 2005
Iacopetta B. Are there two sides to colorectal cancer?  Int J Cancer. 2002;101:403-408
PubMed   |  Link to Article
Larsson SC, Rafter J, Holmberg L, Bergkvist L, Wolk A. Red meat consumption and risk of cancers of the proximal colon, distal colon and rectum: the Swedish Mammography Cohort.  Int J Cancer. 2005;113:829-834
PubMed   |  Link to Article
Kim MK, Sasaki S, Otani T, Tsugane S. Dietary patterns and subsequent colorectal cancer risk by subsite: a prospective cohort study.  Int J Cancer. 2005;115:790-798
PubMed   |  Link to Article
Chao A, Thun MJ, Connell CJ.  et al.  Meat consumption and risk of colorectal cancer.  JAMA. 2005;293:172-182
PubMed   |  Link to Article
Wu X, Chen VW, Martin J.  et al.  Subsite-specific colorectal cancer incidence rates and stage distributions among Asians and Pacific Islanders in the United States, 1995 to 1999.  Cancer Epidemiol Biomarkers Prev. 2004;13:1215-1222
PubMed   |  Link to Article
Prentice RL, Caan B, Chlebowski RT.  et al.  Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative randomized controlled dietary modification trial.  JAMA. 2006;295:629-642
Link to Article
Howard BV, Van Horn L, Hsia J.  et al.  Low-fat dietary pattern and risk of cardiovascular disease: the Women's Health Initiative randomized controlled dietary modification trial.  JAMA. 2006;295:655-666
Link to Article
Insull W, Henderson MM, Prentice RL.  et al.  Results of a randomized feasibility study of a low-fat diet.  Arch Intern Med. 1990;150:421-427
PubMed   |  Link to Article
Winawer SJ. Natural history of colorectal cancer.  Am J Med. 1999;106:(1A)  3S-6S
PubMed   |  Link to Article
Yang Q, Khoury MJ, Flanders WD. Sample size requirements in case-only designs to detect gene-environment interaction.  Am J Epidemiol. 1997;146:713-720
PubMed   |  Link to Article
Clayton D, McKeigue PM. Epidemiological methods for studying genes and environmental factors in complex diseases.  Lancet. 2001;358:1356-1360
PubMed   |  Link to Article
Schatzkin A, Lanza E, Corle D.  et al. Polyp Prevention Trial Study Group.  Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas.  N Engl J Med. 2000;342:1149-1155
PubMed   |  Link to Article
Lanza E, Schatzkin A, Daston C.  et al.  Implementation of a 4-y, high-fiber, high-fruit-and-vegetable, low-fat dietary intervention: results of dietary changes in the Polyp Prevention Trial.  Am J Clin Nutr. 2001;74:387-401
PubMed
McKeown-Eyssen GE, Bright-See E, Bruce WR.  et al. Toronto Polyp Prevention Group.  A randomized trial of a low fat high fibre diet in the recurrence of colorectal polyps.  J Clin Epidemiol. 1994;47:525-536
PubMed   |  Link to Article
MacLennan R, Macrae F, Bain C.  et al.  Randomized trial of intake of fat, fiber, and beta carotene to prevent colorectal adenomas.  J Natl Cancer Inst. 1995;87:1760-1766
PubMed   |  Link to Article
Law M. Dietary fat and adult diseases and the implications for childhood nutrition: an epidemiologic approach.  Am J Clin Nutr. 2000;72:(5 suppl)  1291S-1296S
PubMed
Mathew A, Sinha R, Burt R.  et al.  Meat intake and the recurrence of colorectal adenomas.  Eur J Cancer Prev. 2004;13:159-164
PubMed   |  Link to Article
Chiu BC, Gapstur SM. Changes in diet during adult life and risk of colorectal adenomas.  Nutr Cancer. 2004;49:49-58
PubMed   |  Link to Article
Norat T, Bingham S, Ferrari P.  et al.  Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition.  J Natl Cancer Inst. 2005;97:906-916
PubMed   |  Link to Article
Norat T, Lukanova A, Ferrari P, Riboli E. Meat consumption and colorectal cancer risk: dose-response meta-analysis of epidemiological studies.  Int J Cancer. 2002;98:241-256
PubMed   |  Link to Article
Giovannucci E. Diet, body weight, and colorectal cancer: a summary of the epidemiologic evidence.  J Womens Health (Larchmt). 2003;12:173-182
PubMed   |  Link to Article
Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk.  Am J Clin Nutr. 2003;78:(3 suppl)  559S-569S
PubMed
Smith-Warner SA, Elmer PJ, Fosdick L.  et al.  Fruits, vegetables, and adenomatous polyps: the Minnesota Cancer Prevention Research Unit case-control study.  Am J Epidemiol. 2002;155:1104-1113
PubMed   |  Link to Article
Greenberg ER, Baron JA, Tosteson TD.  et al. Polyp Prevention Study Group.  A clinical trial of antioxidant vitamins to prevent colorectal adenoma.  N Engl J Med. 1994;331:141-147
PubMed   |  Link to Article
Albanes D, Malila N, Taylor PR.  et al.  Effects of a supplemental alpha-tocopherol and beta-carotene on colorectal cancer: results from a controlled trial (Finland).  Cancer Causes Control. 2000;11:197-205
PubMed   |  Link to Article
Hofstad B, Almendingen K, Vatn M.  et al.  Growth and recurrence of colorectal polyps: a double-blind 3-year intervention with calcium and antioxidants.  Digestion. 1998;59:148-156
PubMed   |  Link to Article
Giovannucci E, Stampfer MJ, Colditz GA.  et al.  Folate, methionine, and alcohol intake and risk of colorectal adenoma.  J Natl Cancer Inst. 1993;85:875-884
PubMed   |  Link to Article
Burkitt DP. Related disease—related cause?  Lancet. 1969;2:1229-1231
PubMed   |  Link to Article
Bingham SA, Day NE, Luben R.  et al.  Dietary fibre in food and protection against colorectal cancer in the European Prospective Investigation Into Cancer and Nutrition (EPIC): an observational study.  Lancet. 2003;361:1496-1501
PubMed   |  Link to Article
Potter JD. Colorectal cancer: molecules and populations.  J Natl Cancer Inst. 1999;91:916-932
PubMed   |  Link to Article
Peters U, Sinha R, Chaterjee N.  et al. Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Project Team.  Dietary fibre and colorectal adenoma in a colorectal cancer early detection programme.  Lancet. 2003;361:1491-1495
PubMed   |  Link to Article
Bonithon-Kopp C, Kronberg O, Giacosa A, Rath U, Faivre J. Calcium and fibre supplementation in prevention of colorectal adenoma recurrence: a randomized intervention trial.  Lancet. 2000;356:1300-1306
PubMed   |  Link to Article
Alberts DS, Martinez ME, Roe DJ.  et al.  Lack of effect of a high-fiber cereal supplement on the recurrence of colorectal adenomas: Phoenix Colon Cancer Prevention Physicians' Network.  N Engl J Med. 2000;342:1156-1162
PubMed   |  Link to Article
Gifford KD. Dietary fats, eating guides, and public policy: history, critique, and recommendations.  Am J Med. 2002;113:(suppl 9B)  89S-106S
PubMed   |  Link to Article
Heini AF, Weinsier RL. Divergent trends in obesity and fat intake patterns: the American paradox.  Am J Med. 1997;102:259-264
PubMed   |  Link to Article
Harnack L, Nicodemus K, Jacobs DR Jr, Folsom AR. An evaluation of the Dietary Guidelines for Americans in relation to cancer occurrence.  Am J Clin Nutr. 2002;76:889-896
PubMed
 Dietary Guidelines for Americans 2005. US Department of Health and Human Services and Department of Agriculture. Available at: http://www.healthierus.gov/dietaryguidelines/. Accessed October 18, 2005

Figures

Figure 1. Participant Flow in the Dietary Modification Component of the Women's Health Initiative
Graphic Jump Location

*Categories are presented for which exclusions are known. More than 1 reason could be given for exclusion.

Figure 2. Differences in Mean Dietary Intake Between Intervention and Comparison Groups for Each Year of Follow-up
Graphic Jump Location

Differences were calculated by subtracting comparison group data from intervention group data. Error bars indicate 95% confidence intervals.

Figure 3. Kaplan-Meier Estimated Cumulative Hazards for Invasive Colorectal Cancer (N = 48 835)
Graphic Jump Location

HR indicates hazard ratio; CI, confidence interval.

Figure 4. Bowel Examinations by Dietary Intervention vs Comparison Group and Follow-up Year
Graphic Jump Location
Figure 5. Invasive Colorectal Cancer Hazard Ratios and Annualized Incidence by Baseline Demographic and Medical History Characteristics
Graphic Jump Location

Error bars indicate 95% confidence intervals.
*Interaction test from likelihood ratio test (factors on the continuous scale were tested as continuous variables when possible.
†Cox regression models stratified according to age group, hormone therapy study participation, and prevalence condition; calcium and vitamin D study participation was adjusted as a time-dependent variable.
‡Body mass index was calculated as weight in kilograms divided by the square of height in meters.

Figure 6. Invasive Colorectal Cancer Hazard Ratios and Annualized Incidence by Baseline Dietary Factors
Graphic Jump Location

Error bars indicate 95% confidence intervals.
*Interaction test from likelihood ratio test (factors on the continuous scale were tested as continuous variables when possible.
†Cox regression models stratified according to age group, hormone therapy study participation, and prevalence condition; calcium and vitamin D study participation was adjusted as a time-dependent variable.
‡Case-only analysis using 4-day food record data; no annualized rates available.
§Data are from food frequency questionnaire.

Tables

Table Graphic Jump LocationTable 1. Baseline Participant Characteristics Pertinent to Colorectal Cancer Risk
Table Graphic Jump LocationTable 2. Percentage Changes From Baseline to Year 3 for Dietary Factors and Selected Biomarkers Related to Colorectal Cancer Risk*
Table Graphic Jump LocationTable 3. Annualized Incidence Rate of Outcomes in Intervention vs Comparison Groups
Table Graphic Jump LocationTable 4. Annualized Incidence Rate of Invasive Colorectal Cancer by Tumor Characteristics in Intervention vs Comparison Groups

References

Carroll KK, Khor HT. Dietary fat in relation to tumorigenesis.  Prog Biochem Pharmacol. 1975;10:308-353
PubMed
Prentice RL, Sheppard L. Dietary fat and cancer: consistency of the epidemiologic data, and disease prevention that may follow from a practical reduction in fat consumption.  Cancer Causes Control. 1990;1:81-97
PubMed   |  Link to Article
McMichael AJ, Giles GG. Cancer in migrants to Australia: extending the descriptive epidemiological data.  Cancer Res. 1988;48:751-756
PubMed
Thomas DB, Karagas MR. Cancer in first and second generation Americans.  Cancer Res. 1987;47:5771-5776
PubMed
Howe GR, Benito E, Castelleto R.  et al.  Dietary intake of fiber and decreased risk of cancers of the colon and rectum: evidence from the combined analysis of 13 case-control studies.  J Natl Cancer Inst. 1992;84:1887-1896
PubMed   |  Link to Article
Steinmetz KA, Potter JD. Food-group consumption and colon cancer in the Adelaide Case-Control Study, I: vegetables and fruit.  Int J Cancer. 1993;53:711-719
PubMed   |  Link to Article
Steinmetz KA, Kushi LH, Bostick RM, Folsom AR, Potter JD. Vegetables, fruit, and colon cancer in the Iowa Women's Health Study.  Am J Epidemiol. 1994;139:1-15
PubMed
Trock B, Lanza E, Greenwald P. Dietary fiber, vegetables, and colon cancer: critical review and meta-analyses of the epidemiologic evidence.  J Natl Cancer Inst. 1990;82:650-661
PubMed   |  Link to Article
Howe GR, Aronson KJ, Benito E.  et al.  The relationship between dietary fat intake and risk of colorectal cancer: evidence from the combined analysis of 13 case-control studies.  Cancer Causes Control. 1997;8:215-228
PubMed   |  Link to Article
Hays J, Hunt JR, Hubbell FA.  et al.  The Women's Health Initiative recruitment methods and results.  Ann Epidemiol. 2003;13:(9 suppl)  S18-S77
PubMed   |  Link to Article
Women's Health Initiative Study Group.  Design of the Women's Health Initiative clinical trial and observational study.  Control Clin Trials. 1998;19:61-109
PubMed   |  Link to Article
Ritenbaugh C, Patterson RE, Chlebowski RT.  et al.  The Women's Health Initiative Dietary Modification trial: overview and baseline characteristics of participants.  Ann Epidemiol. 2003;13:(9 suppl)  S87-S97
PubMed   |  Link to Article
Patterson RE, Kristal AR, Tinker LF, Carter RA, Bolton MP, Agurs-Collins T. Measurement characteristics of the Women's Health Initiative food frequency questionnaire.  Ann Epidemiol. 1999;9:178-187
PubMed   |  Link to Article
Anderson GL, Manson J, Wallace R.  et al.  Implementation of the Women's Health Initiative study design.  Ann Epidemiol. 2003;13:(9 suppl)  S5-S17
PubMed   |  Link to Article
Tinker LF, Burrows ER, Henry H, Patterson RE, Rupp JW, Van Horn L. The Women's Health Initiative: overview of the nutrition components. In: Krummel DA, Kris-Etherton PM, eds. Nutrition in Women's Health. Gaithersburg, Md: Aspen; 1996:510-542
Women's Health Initiative Study Group.  Dietary adherence in the Women's Health Initiative Dietary Modification Trial.  J Am Diet Assoc. 2004;104:654-658
PubMed   |  Link to Article
Bowen D, Ehret C, Pedersen M.  et al.  Results of an adjunct dietary intervention program in the Women's Health Initiative.  J Am Diet Assoc. 2002;102:1631-1637
PubMed   |  Link to Article
US Department of Agriculture.  Dietary Guidelines for Americans. 3rd ed. Washington, DC: Dept of Health and Human Services; 1990
Ries LA, Kosary CL, Hankey BF.  et al.  SEER Cancer Statistics Review, 1975-2002. 2005. Available at: http://seer.cancer.gov/csr/1975_2002/. Accessed October 10, 2005
Iacopetta B. Are there two sides to colorectal cancer?  Int J Cancer. 2002;101:403-408
PubMed   |  Link to Article
Larsson SC, Rafter J, Holmberg L, Bergkvist L, Wolk A. Red meat consumption and risk of cancers of the proximal colon, distal colon and rectum: the Swedish Mammography Cohort.  Int J Cancer. 2005;113:829-834
PubMed   |  Link to Article
Kim MK, Sasaki S, Otani T, Tsugane S. Dietary patterns and subsequent colorectal cancer risk by subsite: a prospective cohort study.  Int J Cancer. 2005;115:790-798
PubMed   |  Link to Article
Chao A, Thun MJ, Connell CJ.  et al.  Meat consumption and risk of colorectal cancer.  JAMA. 2005;293:172-182
PubMed   |  Link to Article
Wu X, Chen VW, Martin J.  et al.  Subsite-specific colorectal cancer incidence rates and stage distributions among Asians and Pacific Islanders in the United States, 1995 to 1999.  Cancer Epidemiol Biomarkers Prev. 2004;13:1215-1222
PubMed   |  Link to Article
Prentice RL, Caan B, Chlebowski RT.  et al.  Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative randomized controlled dietary modification trial.  JAMA. 2006;295:629-642
Link to Article
Howard BV, Van Horn L, Hsia J.  et al.  Low-fat dietary pattern and risk of cardiovascular disease: the Women's Health Initiative randomized controlled dietary modification trial.  JAMA. 2006;295:655-666
Link to Article
Insull W, Henderson MM, Prentice RL.  et al.  Results of a randomized feasibility study of a low-fat diet.  Arch Intern Med. 1990;150:421-427
PubMed   |  Link to Article
Winawer SJ. Natural history of colorectal cancer.  Am J Med. 1999;106:(1A)  3S-6S
PubMed   |  Link to Article
Yang Q, Khoury MJ, Flanders WD. Sample size requirements in case-only designs to detect gene-environment interaction.  Am J Epidemiol. 1997;146:713-720
PubMed   |  Link to Article
Clayton D, McKeigue PM. Epidemiological methods for studying genes and environmental factors in complex diseases.  Lancet. 2001;358:1356-1360
PubMed   |  Link to Article
Schatzkin A, Lanza E, Corle D.  et al. Polyp Prevention Trial Study Group.  Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas.  N Engl J Med. 2000;342:1149-1155
PubMed   |  Link to Article
Lanza E, Schatzkin A, Daston C.  et al.  Implementation of a 4-y, high-fiber, high-fruit-and-vegetable, low-fat dietary intervention: results of dietary changes in the Polyp Prevention Trial.  Am J Clin Nutr. 2001;74:387-401
PubMed
McKeown-Eyssen GE, Bright-See E, Bruce WR.  et al. Toronto Polyp Prevention Group.  A randomized trial of a low fat high fibre diet in the recurrence of colorectal polyps.  J Clin Epidemiol. 1994;47:525-536
PubMed   |  Link to Article
MacLennan R, Macrae F, Bain C.  et al.  Randomized trial of intake of fat, fiber, and beta carotene to prevent colorectal adenomas.  J Natl Cancer Inst. 1995;87:1760-1766
PubMed   |  Link to Article
Law M. Dietary fat and adult diseases and the implications for childhood nutrition: an epidemiologic approach.  Am J Clin Nutr. 2000;72:(5 suppl)  1291S-1296S
PubMed
Mathew A, Sinha R, Burt R.  et al.  Meat intake and the recurrence of colorectal adenomas.  Eur J Cancer Prev. 2004;13:159-164
PubMed   |  Link to Article
Chiu BC, Gapstur SM. Changes in diet during adult life and risk of colorectal adenomas.  Nutr Cancer. 2004;49:49-58
PubMed   |  Link to Article
Norat T, Bingham S, Ferrari P.  et al.  Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition.  J Natl Cancer Inst. 2005;97:906-916
PubMed   |  Link to Article
Norat T, Lukanova A, Ferrari P, Riboli E. Meat consumption and colorectal cancer risk: dose-response meta-analysis of epidemiological studies.  Int J Cancer. 2002;98:241-256
PubMed   |  Link to Article
Giovannucci E. Diet, body weight, and colorectal cancer: a summary of the epidemiologic evidence.  J Womens Health (Larchmt). 2003;12:173-182
PubMed   |  Link to Article
Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk.  Am J Clin Nutr. 2003;78:(3 suppl)  559S-569S
PubMed
Smith-Warner SA, Elmer PJ, Fosdick L.  et al.  Fruits, vegetables, and adenomatous polyps: the Minnesota Cancer Prevention Research Unit case-control study.  Am J Epidemiol. 2002;155:1104-1113
PubMed   |  Link to Article
Greenberg ER, Baron JA, Tosteson TD.  et al. Polyp Prevention Study Group.  A clinical trial of antioxidant vitamins to prevent colorectal adenoma.  N Engl J Med. 1994;331:141-147
PubMed   |  Link to Article
Albanes D, Malila N, Taylor PR.  et al.  Effects of a supplemental alpha-tocopherol and beta-carotene on colorectal cancer: results from a controlled trial (Finland).  Cancer Causes Control. 2000;11:197-205
PubMed   |  Link to Article
Hofstad B, Almendingen K, Vatn M.  et al.  Growth and recurrence of colorectal polyps: a double-blind 3-year intervention with calcium and antioxidants.  Digestion. 1998;59:148-156
PubMed   |  Link to Article
Giovannucci E, Stampfer MJ, Colditz GA.  et al.  Folate, methionine, and alcohol intake and risk of colorectal adenoma.  J Natl Cancer Inst. 1993;85:875-884
PubMed   |  Link to Article
Burkitt DP. Related disease—related cause?  Lancet. 1969;2:1229-1231
PubMed   |  Link to Article
Bingham SA, Day NE, Luben R.  et al.  Dietary fibre in food and protection against colorectal cancer in the European Prospective Investigation Into Cancer and Nutrition (EPIC): an observational study.  Lancet. 2003;361:1496-1501
PubMed   |  Link to Article
Potter JD. Colorectal cancer: molecules and populations.  J Natl Cancer Inst. 1999;91:916-932
PubMed   |  Link to Article
Peters U, Sinha R, Chaterjee N.  et al. Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Project Team.  Dietary fibre and colorectal adenoma in a colorectal cancer early detection programme.  Lancet. 2003;361:1491-1495
PubMed   |  Link to Article
Bonithon-Kopp C, Kronberg O, Giacosa A, Rath U, Faivre J. Calcium and fibre supplementation in prevention of colorectal adenoma recurrence: a randomized intervention trial.  Lancet. 2000;356:1300-1306
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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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