In this article, we consider participants of the WHEL Study. Population characteristics, eligibility criteria, randomization procedures, and dietary intervention protocol have been described in detail elsewhere (24
All women enrolled in the WHEL Study who did not have a study endpoint (death or recurrence) by 4 yr of follow-up were eligible for this study (n = 2,718). WHEL Study participants were aged 18−70 yr at cancer diagnosis; treated for primary, operable, and invasive stage I, II, or IIIA breast carcinoma; and at study entry were not receiving or scheduled for chemotherapy and had no evidence of cancer recurrence after initial treatment. Enrollment in another dietary trial, pregnancy, receiving estrogen replacement therapy, and presence of life-threatening medical conditions or diseases were key exclusion criteria.
In this study, we used WHEL baseline, 1-yr, and 4-yr follow-up data and adopted its randomized design for data analysis (control = 1,363, intervention = 1,355). Dietary data at baseline, 1 yr, and 4 yr were available for 2,713 (control = 1,360, intervention = 1,353), 2,465 (control = 1,270, intervention = 1,195), and 2,324 (control = 1,202, intervention = 1,122) women, respectively. At the same time points, 2,718 (control = 1,363, intervention = 1,355), 2,306 (control = 1,174, intervention = 1,132), and 2,146 (control = 1,116, intervention = 1,030) women had their body weight measured.
Informed written consent from study participants was collected in the WHEL Study. The Human Subjects Committee of the University of California, San Diego, and all participating institutions approved the study procedures.
Participants in the intervention group were encouraged to maintain a dietary pattern that included a daily consumption of at least 5 vegetable servings, 16 ounces of vegetable juice (or equivalent vegetable servings), 3 fruit servings, 30 g of fiber (18 g/1,000 kcal), and 15−20% energy from fat (24
). Telephone counseling, monthly cooking classes, and newsletters were the principal methods to promote dietary change in the intervention participants. Control group participants received print materials that included dietary guidelines from the U.S. Department of Agriculture (28
) and the National Cancer Institute (29
) and a bimonthly cohort maintenance newsletter with general health and nutrition information unrelated to the intervention group's dietary goals.
Dietary intake was assessed through a set of four 24-h dietary recalls at baseline, 1 yr, and 4 yr. Trained dietary assessors conducted these recalls by telephone on randomly selected days, stratified for weekend vs. weekdays, over a 3-wk period. The Nutrition Data System for Research (NDS-R) software was used to collect and estimate dietary intakes (NDS-R version 6.0, 2006, University of Minnesota, Minneapolis, MN). NDS-R included more than 18,000 food codes, including many ethnic foods, and over 8,000 brand-name products.
A number of strategies were used to maximize the accuracy of dietary recall data (30
). Dietary assessors completed a training program that included standardized data collection, proper interview technique, and efficient use of dietary analysis software. Participants were trained, before study enrollment, to estimate serving sizes with food models, measuring cups, and spoons, and were provided with 2-dimensional food models for reference during recalls. In addition, assessors used a multipass method that improved recall accuracy by prompting to obtain detailed data about type, amount, and preparation method of foods eaten.
Calculation of Dietary Energy Density
We determined a participant's dietary energy density (kcal/g; 1 kcal = 4.18 kJ) for a dietary recall day by estimating total energy intake (kcal) for that day and dividing it by the total amount (g) of food reported being consumed on that day. Energy density values of the set of 4 days were averaged to derive a mean dietary energy density value for each participant. In our calculations, we excluded all beverages.
Physical Activity Assessment
Physical activity was determined from the Personal Habits questionnaire developed for Women's Health Initiative (WHI) (31
), expressed as metabolic equivalents per week (Metmin/wk) (32
), and completed at baseline, 1 yr, and 4 yr. For the WHEL Study, this questionnaire was calibrated with the standard 7-Day Physical Activity Recall (PAR) (33
) and validated with an accelerometer reading (34
). The accelerometer measured an average of 165 total min of physical activity per week, which was not statistically different from the 187 min reported for the PAR or the 171 min reported with the WHI 9-item questionnaire.
Ascertainment of Body Weight
Weight and height were measured—with the participants wearing light clothing and no shoes—during clinic visits (baseline, Yr 1, and Yr 4) scheduled in the WHEL Study. Body mass index (BMI) was calculated as weight (kg)/height (m2).
Information on cancer stage (I, II, IIIA) and demography was ascertained through medical records and questionnaire, respectively. Age at study entry was categorized into 10-yr age groups (<44, 45−54, 55−64, and ≥65 yr), and race was categorized as non-Hispanic White, African American, Hispanic, Asian American, and others. Other variables included were education (college graduate vs. nongraduate), employment status (yes, no), marital status (married vs. not married), and smoking (current, past, and never). We calculated summary variables such as total fruit and vegetable intake (servings/day) and percent energy intake from fat/day from 24-h dietary recalls.
Validation of Dietary Intake With Biomarkers
Plasma carotenoids are well-known biomarkers of fruit and vegetable intake (35
). The WHEL Study measured plasma carotenoid concentrations on a 28% random sample of subjects identified at baseline and has published plasma carotenoid measurement procedures and baseline to 1-yr results (25
). In this analysis, we report total plasma carotenoid concentrations on the available population (n
= 881) at baseline, 1 yr, and 4 yr. Total plasma carotenoids are=the sum of the individual carotenoids separated and quantified (α
-cryptoxanthin, lycopene, and lutein plus zeaxanthin) using high-performance liquid chromatography methodology (25
). The mean laboratory day-to-day coefficient of variation for total plasma carotenoids was less than 7%.
We compared baseline characteristics of the control and the intervention groups; demographic, behavioral, and cancer related variables, thought to be potential confounders of the relationship between dietary intake and weight, were examined in this respect.
Energy density was calculated using “food only” values. We used baseline values to assess univariable associations of energy density with categories of age, race, and BMI; one-way analysis of variance compared category means against a referent category. We also grouped participants into tertiles of baseline dietary energy density, calculated mean values of total energy intake, physical activity, and body weight for each tertile and compared tertiles using the lowest tertile as referent. We then compared baseline dietary energy density between the control and the intervention group and graphed energy density in each study group at each time period.
We also computed and compared total energy intake, physical activity, and body weight values in each study group at baseline, 1 yr, and 4 yr, testing for group differences with t-tests.
Finally, we used mixed effect models to assess change in energy density, total plasma carotenoids, total energy intake, physical activity, and body weight over the study follow-up period. We chose mixed models, as they are the best option available for correlated data and for data with random missing values. “Unstructured” covariance provided the smallest Akaike's information criterion value and was used in the mixed models.
All calculations were performed using SAS version 9.1 (SAS Institute, Cary, NC). All statistical tests were two-tailed with an alpha level of 0.05.