Research indicates that low fruit and vegetable intake is a risk factor for many chronic diseases. Despite large-scale education campaigns, the great majority of Americans do not consume recommended levels. We tested the ability of a single brief interactive experience of the
A randomized placebo-controlled, parallel-group trial included 481 low-income, female participants: mean age 50.1 years, 48.4% African American, 51.6% non-Hispanic white, and 92.5% below 185% of the federally designated poverty level. Participants received one of three conditions: 1) a one-time experience with the
Two months after the one-time experience with the CD-ROMs, both intervention groups reported significantly higher intakes of fruits and vegetables than the control group. The
The
Research overwhelmingly implicates low intakes of fruits and vegetables as factors influencing the prevalence of several chronic diseases and poor health (
With the heightened focus on nutrition and its role in prevention of chronic disease, it is imperative to develop cost-effective interventions that can affect larger segments of the population.
Here we describe a randomized controlled parallel-group intervention with a brief, computer-based nutrition behavior-change program.
This screen asks the user to describe his or her eating habits:
Option one: I usually pack lunches.
Image is of a brown-bag sandwich, an apple, and a juice box.
Option two: I usually eat out a lot.
Image is of a burger and fries, and a Chinese food take-away box.
Option three: I enjoy cooking.
Image is of a stove and a barbeque grill.
Listen to the audio for this screen
Try to choose a restaurant that:
Has salads on the menu. Remember to ask for low-fat salad dressings. Lets you choose a baked potato instead of French fries.
Select each tab to learn more.
Listen to the audio for this screen
Hamburger Cheeseburger Big Big Burger Grilled Chicken Sandwich Fish Sandwich French Fries Salad Onion Rings Baked Potato Cookies Pies Frozen Yogurt
Select the items on the menu to learn more.
Listen to the audio for this screen
Try this:
Order 2 regular hamburgers instead of 1 specialty sandwich Order baked potato instead of French fries Order a salad instead of French fries
Select each tab to learn more.
Listen to the audio for this screen
Burrito Taco Fajitas Burrito Supreme Taco Supreme Nachos Taco Salad Vegetarian Taco Refried Beans Chimichangas Salsa Sour Cream
Select the items on the menu to learn more.
Listen to the audio for this screen
Try this:
Order a plain taco or burrito Order a taco salad without the shell. Use less salad dressing Avoid sour cream, guacamole, and cheese on your burritos, tacos, and nachos
Listen to the audio for this screen
The characteristics of the CD-ROM program are described in detail elsewhere (
The University of California Berkeley Committee for Protection of Human Subjects approved the research, and eligible participants provided informed consent. Data collection took place during a nine-month period, from February through October 2002. We gave a $25.00 gift card from a local store to each participant as an incentive to complete the study. We recruited study participants in collaboration with nutrition advisors and staff of the California Expanded Food & Nutrition Education Program in Contra Costa and Stanislaus counties, and the University of California Cooperative Extension and Food Stamps Program in Solano County. Staff included two part-time interviewers at each site, one African American, and one non-Hispanic white. Methods of recruitment included posted flyers inviting participation of study subjects and presentations to classes sponsored by organizations and agencies serving low-income clients. Recruitment sites included community-based organizations and selected programs that provided services to the target population, such as the Welfare to Work program, Food Stamps program, and other social services programs. Recruitment efforts also targeted lower-paid staff at day care centers, Head Start programs, social service agencies, and county offices.
To be eligible for the study, the individual had to be female, African American or non-Hispanic white, midlife (defined as 40 to 65 years of age), and low-income as reflected by their participation in the above programs serving low-income persons.
Participants were interviewed at baseline, primarily at county offices, and were randomized to one of three intervention groups, using a computer-generated randomization scheme. Group 1 received a brief, self-guided 15- to 20-minute interactive experience with a computer-based program,
For the intervention with the reminder calls, two brief telephone calls were made to the participant within the subsequent two-month period. A script for these calls was provided. The interviewer simply asked, “Do you remember the personal goal you set when you did the computer program a few weeks ago? And what was it? How have you done? If you had a hard time, what was the reason?”
Data were collected on age; level of education; race; income; number of persons in household; and food insecurity. Knowledge and attitudes about diet and health were also assessed, and participants were asked about obstacles and barriers to eating fruits and vegetables. Stage of Readiness for Change was assessed at baseline and follow-up and categorized in four stages, corresponding to Precontemplation (“No” to “Have you ever thought about eating more fruits and vegetables?”), Contemplation (“Yes” to that question), Preparation (“Planning to increase fruits and vegetables in the next one to two months”), and Action/Maintenance (“Currently trying to eat more fruits and vegetables”) (
Fruit and vegetable intake was assessed at baseline and follow-up using a modification of the California Dietary Practices Survey (
Linear regression and correlation techniques were used for continuous data, and classification and chi-square evaluation were used for categorical data. Baseline comparisons between groups were examined using chi-square tests for categorical data and analysis of variance for continuous data. To evaluate the effectiveness of the intervention, analysis of covariance was used, with change score as the dependent variable and baseline level as a covariate. Potential effect modification of treatment effect by race; site; education; income; and other variables in the dataset was examined. Potential confounding by those factors was also examined. The only significant covariate was site (Contra Costa, Solano, or Stanislaus County), which was included in all models.
Poverty guidelines for each household size were obtained from the U.S. government for the year 2002 (
Missing values for income (n = 11) and weight (n = 15) were replaced with the median value. Because of small numbers in some categories of education, the lower three categories were combined into one category for some analyses.
Two outcome variables were derived to estimate change in fruit and vegetable intake: occurrences and servings. Occurrences were simply the number of times a fruit or a vegetable was mentioned during the 24-hour recall. For example, a person who had orange juice at breakfast and orange juice at lunch would have two occurrences. Servings were calculated by applying a factor to each occurrence, based on the respondent's reported portion size for that food. For example, the USDA Food Guide Pyramid serving size for vegetables is ½ cup; if the respondent reported the smallest portion, ¼ cup, for green beans, she was credited with ½ of a serving of green beans. Treatment effectiveness was analyzed separately for change in occurrences and change in servings.
Four hundred ninety-one low income, midlife, African American and white women were enrolled and 481 (98%) completed the study. The sample included 48.4 % African American (n = 233) and 51.6% white (n = 248) women.
Change in occurrences was significantly higher in both
In preliminary analyses, change in servings was not significantly different across intervention groups. A significant interaction with education level was found, however, and results are presented separately by education level (
Both
This study has demonstrated that the number of times that fruits and vegetables are consumed by an individual in a population of low-income women can be increased by a single experience with the
The U.S. Preventive Services Task Force (USPSTF) has extensively reviewed the effectiveness of interventions to improve dietary behavior (
It is difficult to compare effect sizes across different studies because of differences in the methods of measurement and differences in the intervals between intervention and evaluation. Among the interventions to increase fruit and vegetable intake reviewed by the USPSTF and the two more recent studies mentioned above, the interval between intervention and measurement of behavior change ranged from two to 18 months. We report here on results after a two-month interval; a one-year follow-up is in progress. For method of measurement, most studies used some form of food-frequency questionnaire, whereas we used a modified 24-hour recall, generally considered more accurate when information on absolute amount of intake by a group is desired, rather than just a ranking (
The outcome variable that was most consistently affected was occurrences of eating fruits and vegetables, while servings were increased only in the less educated participants. There are a number of possible reasons for this. First, the suggestions and goals offered by the
A second possible explanation is that the baseline dietary assessment was itself an important intervention in that group. Abundant anecdotal evidence shows that simply completing a dietary questionnaire can have an effect on dietary habits in some individuals, with responses like “Wow, I never realized I ate so few fruits and vegetables.” Perhaps this was particularly true in the higher education group. As noted, the control group increased by 0.70 occurrences overall and by 1.32 occurrences in the higher education group. This alone may be sufficient justification for conducting routine dietary assessment screening as a potentially useful nutritional intervention.
Regardless of the explanation for the greater apparent effectiveness in increasing the number of occurrences, it is the opinion of one of the authors (GB) that it would be more prudent public health advice to encourage people to increase the number of occurrences, rather than focusing on the number of servings. Recommending “five to nine servings” requires people to learn the definition of a serving, and the recommendation itself probably seems unreachable to many people. (In addition, the epidemiologic literature upon which such recommendations are made has at its basis a calculation of number of times per day, not calculations involving units of measure.) Instead, what is most important is simply that fruits and vegetables show up more often in the daily diet of the population. People already know what a fruit or a vegetable is (salads count, juices count), and they can simply count the number of times they show up on the plate. However, for Asian or Hispanic populations where mixed dishes are the norm, it may be important to have an additional focus on increasing the amount of the vegetables consumed.
Behavior change is difficult, and previously only extensive, intensive interventions have been successful in changing dietary habits (
The first critical feature is the
In addition, it is possible that the simple process of asking individuals to reflect on their diets and to report on their intake is relevant, even if they are reporting that information to a computer. Physicians rarely ask patients to reflect or report on their dietary habits (
In a related issue, the program asks participants to indicate perceived barriers to eating more fruits and vegetables, factors such as “it costs too much,” “it takes too much time,” and “the family doesn't like them.” The program offers this additional opportunity for participants to tell “someone” about their problems.
The second key factor in the success of the
The third critical aspect is that the changes proposed by the
A fourth critical aspect of the
Another aspect that may have contributed to the program’s success is that computer screens are similar to television screens, providing a familiar, non-threatening, and credible medium to program participants. Many participants were women who had little or no experience with computers, yet they required only a few seconds of instruction on using the mouse and had no difficulty using the program independently. Rather than appearing reluctant or intimidated by the computer, participants seemed to find the experience enjoyable and to appreciate the opportunity to use a computer.
Finally, the personal contact between interviewers and participants prior to the start of the CD-ROM experience probably was influential. For the most part, interviewers were of the same ethnic group as participants, and most interviewers were also low-income. In addition, in the group that received the two reminder phone calls, the calls were made by the same interviewer who had interviewed participants at baseline and introduced them to the CD-ROM.
It is worth noting that the
In summary, the following characteristics are key to the success of the
While we tested the
The components of the
The
We acknowledge the contribution of Dr. Clifford Block, who was instrumental in making
The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
Sample Characteristics,
| .83 | |||||
| African American | 233 (48.4) | 76 | 77 | 80 | |
| White non-Hispanic | 248 (51.6) | 86 | 83 | 79 | |
| .51 | |||||
| < $10,000 | 112 (23.3) | 36 | 34 | 42 | |
| $10,000–$15,000 | 46 (9.6) | 17 | 13 | 16 | |
| $15,000–$20,000 | 41 (8.5) | 13 | 17 | 11 | |
| $20,000–$25,000 | 37 (7.7) | 14 | 14 | 9 | |
| $25,000–$35,000 | 82 (17.1) | 31 | 22 | 29 | |
| $35,000–$50,000 | 56 (11.6) | 16 | 22 | 18 | |
| $50,000–$65,000 | 32 (6.7) | 12 | 6 | 14 | |
| > $65,000 | 75 (15.6) | 23 | 32 | 20 | |
| .93 | |||||
| Below poverty | 327 (68.0) | 109 | 113 | 105 | |
| 100–185% of poverty | 118 (24.5) | 41 | 36 | 41 | |
| Above 185% of poverty | 36 (7.5) | 12 | 11 | 13 | |
| .46 | |||||
| Yes | 107 (33.7) | 32 | 35 | 40 | |
| No | 210 (66.0) | 78 | 65 | 67 | |
| Missing | 1 (0.3) | 1 | 0 | 0 | |
| .40 | |||||
| Yes | 66 (20.8) | 18 | 22 | 26 | |
| No | 251 (78.9) | 92 | 78 | 81 | |
| Missing | 1 (0.3) | 1 | 0 | 0 | |
| .02 | |||||
| Yes | 87 (18.1) | 38 | 19 | 30 | |
| No | 394 (81.9) | 124 | 141 | 129 | |
| .44 | |||||
| Elementary school only | 3 (0.6) | 1 | 1 | 1 | |
| Junior high only | 10 (2.1) | 2 | 4 | 4 | |
| High school graduate | 149 (31.0) | 58 | 39 | 52 | |
| More than high school | 319 (66.3) | 101 | 116 | 102 | |
| .30 | |||||
| Yes | 311 (64.7) | 98 | 110 | 103 | |
| No | 170 (35.4) | 64 | 50 | 56 | |
| .37 | |||||
| Underweight (< 18.5) | 6 (1.3) | 0 | 4 | 2 | |
| Normal (18.5–24.9) | 118 (24.5) | 40 | 35 | 43 | |
| Overweight (25–29.9) | 140 (29.1) | 51 | 52 | 37 | |
| Obese (30–34.9) | 96 (20.0) | 30 | 30 | 36 | |
| Obese II (> 35) | 121 (25.2) | 41 | 39 | 41 | |
| .31 | |||||
| 0 | 252 (52.4) | 87 | 75 | 90 | |
| 1 | 107 (22.3) | 29 | 42 | 36 | |
| 2 or more | 122 (25.3) | 46 | 43 | 33 | |
| .86 | |||||
| Precontemplation | 73 (15.2) | 28 | 21 | 24 | |
| Contemplation | 34 (7.1) | 10 | 12 | 12 | |
| Preparation | 33 (6.9) | 8 | 13 | 12 | |
| Action/maintenance | 341 (70.9) | 116 | 114 | 111 | |
| .54 | |||||
| 0 | 30 (6.2) | 8 | 12 | 10 | |
| 1 | 74 (15.4) | 23 | 22 | 29 | |
| 2 | 88 (18.3) | 25 | 31 | 32 | |
| 3 | 75 (15.6) | 23 | 28 | 24 | |
| 4 | 80 (16.6) | 27 | 30 | 23 | |
| 5 or more | 134 (27.9) | 56 | 37 | 41 | |
| 50.1 | 51.1 | 49.7 | 49.6 | .18 | |
Significance of difference of characteristics across intervention groups, by chi square.
Questions on food insufficiency and food stamp participation were not asked of persons with income above $35,000. Some persons with higher incomes could be food insufficient because of the number of persons that income had to support, but they are not included in this count.
Included trade school.
60 participants declined to answer.
Effectiveness of Intervention for Increasing Occurrences of Fruit and Vegetable Intake Among Low-Income Women,
| 1.32 | .016 | |
| 1.20 | .052 | |
| Stress-reduction CD-ROM (n = 159) | 0.71 | --- |
Least squares mean for change, from analysis of covariance model adjusted for baseline level and site.
Compared with stress-reduction CD-ROM intervention group.
Effectiveness of Intervention for Increasing Servings of Fruits and Vegetables Among Low-Income Women,
| High school or less | 1.22 | .01 | |
| 0.78 | .13 | ||
| Stress-reduction CD-ROM | -0.04 | --- | |
| More than high school | 0.87 | .23 | |
| 1.05 | .46 | ||
| Stress-reduction CD-ROM | 1.32 | --- |
Least squares mean for change, from analysis of covariance model adjusted for baseline level and site.
Compared with stress-reduction CD-ROM intervention group.
Effectiveness of Intervention for Increasing Stage of Readiness for Change Among All 481 Low-income Female Participants
| 0.41 | .01 | |
| 0.31 | .15 | |
| Stress-reduction CD-ROM | 0.17 | --- |
Includes persons who were already at the top of the scale, Action/Maintenance, at baseline.
Least squares mean for change, from analysis of covariance model adjusted for baseline level and site. One unit (1.0) equals a move of one level in the four Stage of Readiness for Change level (see Methods) (
Compared to stress-reduction CD-ROM intervention group.