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Archived Final Evidence Review

Final Evidence Review for Healthy Diet: Counseling Adults with CVD, January 2003

Originally published on: January 8, 2014

This recommendation statement is currently archived and inactive. It should be used for historical purposes only. Click here for copyright and source information .

Disclaimer:Recommendations made by the USPSTF are independent of the U.S. government. They should not be construed as an official position of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.

Archived: Preface

Michael P. Pignone, M.D., M.P.H.a; Alice Ammerman, Dr.P.H., R.D.b; Louise Fernandez, R.D., P.A.-C., M.P.H.b; C. Tracy Orleans, Ph.D.c; Nola Pender, Ph.D., R.N., F.A.A.N.d; Steven Woolf, M.D., M.P.H.e; Kathleen N. Lohr, Ph.D.f; Sonya Sutton, B.S.P.H.g

The authors of this article are responsible for its contents, including any clinical or treatment recommendations. No statement in this article should be construed as an official position from the Agency for Healthcare Research and Quality, or the U.S. Department of Health and Human Services.

Address correspondence to: Michael P. Pignone, M.D., M.P.H., Division of General Internal Medicine, UNC School of Medicine, 5039 Old Clinic Building, CB No. 7110 UNC Hospitals, Chapel Hill, NC 27599-7110; E-mail: pignone@med.unc.edu.

Select for copyright and reprint information. The USPSTF recommendations based on this review are online.


The summaries of the evidence briefly present evidence of effectiveness for preventive health services used in primary care clinical settings, including screening tests, counseling, and chemoprevention. They summarize the more detailed Systematic Evidence Reviews, which are used by the U.S. Preventive Services Task Force (USPSTF) to make recommendations.

Archived: Epidemiology

Diseases associated with unhealthy dietary behavior rank among the leading causes of illness and death in the United States.1, 2 Major diseases in which diet plays a role include coronary heart disease, some types of cancer, stroke, hypertension, obesity, osteoporosis, and non-insulin-dependent diabetes mellitus.1 All of these diseases are major causes of morbidity and mortality in this country.3 Although diet is associated with multiple health outcomes, the ability of counseling to change dietary patterns and improve health is unclear. In this report, counseling is defined as a cooperative mode of interaction between the patient and primary care physician or related healthcare staff to assist patients in adopting behaviors associated with improved health outcomes.4

To address the question of whether counseling can improve dietary patterns, we performed an extensive systematic evidence review on behalf of the U.S. Preventive Services Task Force (USPSTF).1 This larger report comprehensively updated the chapter on dietary counseling from the second edition of the Guide to Clinical Preventive Services,5 and it is available from the Agency for Healthcare Research and Quality (AHRQ) at http://www.uspreventiveservicestaskforce.org.

In 1996, the USPSTF recommended counseling adults and children older than 2 years of age to limit intakes of saturated fat and cholesterol, to maintain caloric balance in diets, and to emphasize foods that are high in fiber.5 An updated recommendation,6 dealing specifically with the question of dietary counseling, accompanies this summary of the evidence and is also available at http://www.uspreventiveservicestaskforce.org.

Archived: Methods

We searched the MEDLINE® database for randomized controlled trials (RCTs) published between 1966 and December 2001 that examined the effectiveness of counseling in changing dietary behavior. Search terms are provided in Appendix Table 1. We supplemented our searches by reviewing the bibliographies of included articles and querying experts in the field during an extensive peer review process.

We included only studies that had been conducted with patients similar to those found in primary care practices and that had measured dietary behavior change. We excluded studies that specifically recruited patients with previously diagnosed chronic illnesses (e.g., heart disease, diabetes, renal failure) or that required special diets (e.g., prenatal interventions); however, we did include studies that enrolled patients with known risk factors for chronic diseases (e.g., elevated cholesterol, hypertension, obesity, family history of heart disease). Studies that enrolled only overweight or obese patients for the purpose of weight management were not included; a forthcoming USPSTF report on screening for obesity will examine these articles.7

All included articles used a randomized controlled study design. Because our main outcome of interest was dietary change, we excluded studies that reported only biochemical markers (e.g., serum vitamin A level) or anthropomorphic measures (e.g., weight, proportion of body fat) with no direct measure of dietary behavior. We also excluded studies in which the diet was externally controlled (i.e., provided in a residential institution or distributed by researchers). Trials had to be of at least 3 months' duration and have a minimum retention rate of 50 percent for inclusion.

Senior investigators reviewed titles and abstracts to identify which full manuscripts to review and made the final decisions about inclusion or exclusion. Other team members then reviewed individual articles and abstracted selected information into evidence tables. When multiple articles described the same study, we used the most complete article as the main source of data and used the other articles for supplemental information. Team members discussed disagreements with reviewers and made final decisions by consensus.

We used net change in consumption, defined as change in the intervention group from baseline to followup minus the change in the control group from baseline to followup, as the main outcome. We reported unadjusted outcomes from the article when they were presented. In some cases when necessary data were not presented in the article, we were able to calculate them from other information that was presented.

To facilitate comparison of effectiveness of counseling on dietary change across studies that used a variety of different outcome measures, two investigators independently classified the magnitude of dietary change in each study as "small," "medium," or "large." The study team resolved disagreements by consensus. We developed a definition of small, medium, and large changes based on the distribution of findings from the studies and the limited information available about the relationship between dietary change and health outcomes.

For saturated fat, we defined small as an absolute net difference between intervention and control groups of 0 to 1.2 percentage points, medium as a difference of 1.3 to 3.0 percentage points, and large as a difference of greater than 3.0 percentage points. When studies reported only change in proportion of calories from total fat, we classified large as a difference of greater than 10 percentage points, medium as a difference of 5.1 to 9.9 percentage points and small as a difference of less than or equal to 5 percentage points. We classified effect sizes based on the difference in the number of servings of fruit and vegetables per day consumed by the intervention and control groups. We defined small as a difference of less than 0.3 servings per day, medium as a difference of 0.4 to 0.9 servings per day, and large as a difference of greater than or equal to 1.0 serving per day. For fiber we defined a small effect size as a net difference of less than 2.0 g per day of fiber, medium as 2.0 to 4.0 g per day, and large as greater than 4.0 g per day.

If studies did not provide data on our main outcomes of interest, we used the relative change in the outcome reported (e.g., grams of fat consumed, dietary risk scores) to guide our definition of magnitude of change. The relative change was defined as the net change divided by the baseline value in the control group. A relative change of 25 percent or greater was considered large, 10 percent to 24 percent medium, and less than 10 percent small.

Analysis of Factors Influencing Effect Size

We examined the effect of different intervention characteristics, including intensity, the risk status of the patient populations studied, the study setting, and the use of well-proven counseling elements, on the magnitude of change in dietary behavior achieved. We considered trials that examined multiple nutrients as separate studies for these analyses. Because of concern about double-counting studies, we repeated the analyses with each study's effect counted only once (once using the largest effect and again using the smallest effect) and found similar results. Because of heterogeneity in the outcomes, we did not attempt meta-analysis.

Two senior reviewers independently rated the intensity of the dietary intervention as "low," "medium," or "high" based on the number and length of counseling contacts. Interventions with only one contact of 30 minutes or less were considered low intensity, those with six or more contacts of 30 minutes or more each were considered high intensity, and all others were considered medium intensity.

Each study's intervention "setting" was classified as:

  1. Performed within the primary care clinic (by the usual primary care provider or referral to a dietitian or nutritionist).
  2. Conducted in a special research clinic.
  3. Conducted using self-help materials and/or interactive health communications (e.g., telephone messages or computer-generated mailings).

Finally, we examined the studies to determine whether they included as part of their intervention any of seven counseling elements (using a dietary assessment, enlisting family involvement, providing social support, using group counseling, emphasizing food interaction, encouraging goal setting, and using advice appropriate to the patient group being studied) that have been effective in previous research on dietary behavior change.8

Quality Assessment

Using the techniques established by the USPSTF Methods group, we rated the quality of each article as good or fair, based on criteria affecting internal validity.9 All studies that would be considered poor quality were excluded before the final review stage.

Role of the Funding Agency

This evidence report was funded through a contract to the RTI-University of North Carolina Evidence-based Practice Center from AHRQ. Staff of the funding agency contributed to the study design, reviewed draft and final manuscripts, and made editing suggestions.

Archived: Results

We identified a total of 129 abstracts for review from our literature searches. After review of the 129 abstracts, we identified 74 articles examining the effect of counseling on dietary behavior. After full article review, we excluded an additional 49 articles from our analysis because they did not meet our eligibility criteria. Reasons for exclusion are provided in Appendix Table 2.

We retained 21 studies reported in 25 articles that met our eligibility criteria.10-34 Across this body of literature, 17 studies addressed changes in consumption of dietary fat, 10 studies addressed changes in consumption of fruits and vegetables, and 7 studies addressed changes in consumption of dietary fiber, for a total of 34 intervention "arms." Eleven studies addressed changes in one dietary element and 10 addressed changes in 2 or 3 elements. Four studies included interventions for other behavioral risk factors for chronic disease, such as offering smoking cessation or encouraging increased physical activity.21, 23, 25, 30 All included studies were considered to be of good quality, based on randomized design, high retention rates, and use of appropriate outcome measures.

Intervention Characteristics

Eight studies were performed in primary care settings. In seven of the eight studies, primary care providers performed the dietary counseling,10, 11, 20, 27, 28, 30, 34 and in the remaining study, nutrition counseling was performed through referral within the clinic.23 Five studies used self-help materials and/or interactive health communications (e.g., telephone messages, computer-generated mailings) to deliver counseling.12, 14, 15, 22, 31 Eight studies were performed in special research clinics,13, 16, 21, 24, 25, 29, 32, 33 with counseling performed in most cases by a nutritionist or other specially trained counselor.

Nearly all the studies provided information on the dietary assessment tool used to assess outcomes and, in some cases, to guide counseling. Of the 21 studies, 12 used some version of a validated food frequency questionnaire, 2 used single- or multi-day diet recall, 2 used food diaries, and 4 used other specific instruments. One study did not report how assessment was performed.24 The full systematic evidence review,1 available online (http://www.uspreventiveservicestaskforce.org), gives more information about the specific assessment instruments and their accuracy and reliability.

Effect of Counseling on Intake of Saturated Fat

Table 1 describes the 17 studies that examined the effect of counseling on intake of dietary fat. Nine studies reported specifically on change in the percentage of calories from saturated fat.13-16, 24-26, 28, 29 The remaining eight studies used other measures of fat intake, including grams of saturated or total fat consumed or study-specific outcome scales.10-12, 20-23, 30 Studies that measured only total fat intake focused much of their interventions on reducing saturated fat intake and hence are retained in this analysis.

Six studies focusing on the effect of counseling on reducing patients' consumption of saturated fat achieved a large effect (>3 percentage point reduction),12.13.16.24.25.29 five achieved a medium effect (1.3 to 3.0 percentage point absolute reduction),14, 20, 21, 23, 30 and six had only a small effect (less than 1.3 percentage points).10, 11, 15, 22, 27, 28 For the nine studies reporting change in percentage of calories from saturated fat, net reductions ranged from 0.9 to 5.3 percentage points.

Effect of Counseling on Fruit and Vegetable Intake

We identified 10 studies that examined the effect of counseling on fruit and vegetable intake (Table 2).12-15, 21, 22, 28, 31-33 Most of the studies (6 of 10) did not define which foods (e.g., potatoes or legumes) were considered fruits or vegetables or what constituted a serving.11, 12, 14, 15, 21, 33 Among these 10 studies, three demonstrated that dietary counseling produced small to no increases (<0.3 servings per day) in fruit and vegetable consumption,12, 21, 28 five demonstrated medium increases ranging from 0.3 to 0.8 servings per day,13.15.22.31.33 and two demonstrated large effects, increasing fruit and vegetable consumption by 1.4 and 3.2 servings per day.14, 32

Effect of Counseling on Fiber Intake

Seven studies examined the effect of counseling on fiber intake (Table 3).10, 11, 14, 15, 23, 28, 34 Five studies showed small increases in the amount of additional fiber consumed (range, 0.3 g to 1.6 g per day).10, 11, 15, 23, 28 One study reported differences in daily fiber intake between intervention and control groups of 2.7 g for men and 6.0 g for women at 1-year followup,34 and another found a net change of 3 g.14

Factors Affecting Response to Dietary Counseling

Next, we examined the characteristics of the available trials that could possibly explain the differences in effectiveness that we found. Explanatory factors included the intensity of the intervention, the risk status of the patient, the setting for delivery of the intervention, and the use of specific counseling elements that had previously been shown to be effective in producing behavior change. The findings presented combine interventions for the intake of all nutrients (fat, fruit and vegetable, fiber) together, as there were too few studies of counseling about fruit and vegetable or fiber intake alone to make comparisons among intervention characteristics.

Intensity of the Intervention

As depicted in Table 4, studies using higher intensity interventions produced larger effect sizes than studies using lower intensity interventions. Among nine study arms classified as high intensity, five (55 percent) produced large changes in dietary behavior, three (33 percent) produced medium changes, and one (11 percent) produced only a small change. Of the 18 medium-intensity study arms, one (6 percent) produced a large effect, 10 (55 percent) produced medium effects, and 7 (39 percent) produced small effects. Of the 7 low-intensity study arms, 1 (14 percent) produced a large effect, 1 (14 percent) produced a medium effect, and 5 (71 percent) produced small effects. Higher intensity studies enrolled either patients at risk for chronic disease or selected motivated patients at average risk who may not be representative of the usual patients in primary care practices. They also used well-trained counselors (most often dietitians or nutritionists) to provide counseling.

Risk Status of Patients

Twenty-one study arms were conducted using unselected patients, and 13 were conducted using patients with identified risk factors for chronic disease. After stratifying by intervention intensity, we could find no clear relationship between the risk status of the patients and the effect size achieved.

Setting

Studies conducted in special research clinics were more likely to produce larger effects than studies performed in other settings, in large part because the interventions in these clinics were of higher intensity. In addition, most involved counseling by trained personnel (usually dietitians or nutritionists) who were focused mainly on counseling about diet. Primary-care-based interventions produced small or medium effects; more intensive studies produced larger effects. Studies using interactive health communications had effects that were larger than those with direct primary care counseling but smaller than those found in research-clinic based studies.

Counseling Components

Several components of counseling are thought to be associated with improved behavioral outcomes: using a dietary assessment, enlisting family involvement, providing social support, using group counseling, emphasizing food interaction (such as taste testing, cooking), encouraging goal setting, and using advice appropriate to the patient group being studied.1 We examined each study to determine how many of these elements were included in their interventions. Many interventions were not described in sufficient detail to determine with certainty the absence or presence of these study components. The total number of identified components ranged from 0 to 7, with a median of 2.

As shown in Table 5, studies employing a greater number of components had larger effect sizes. Of 6 study arms employing three or more components, 4 (67 percent) produced large effects and 2 (33 percent) produced medium effects; among 24 study arms employing 1 to 2 components, 4 (17 percent) produced large effects, 11 (46 percent) produced medium effects, and 9 (37 percent) produced small effects. Among 4 study arms reporting no components, all produced small effects.10, 11 We did not identify a sufficient number of studies to determine whether any single component was associated with an independent effect on the magnitude of change in dietary behavior.

Archived: Discussion

Researchers have used a wide range of interventions to examine the effect of behavioral counseling on dietary patterns among predominantly healthy adult patients. Among the studies we identified, low-intensity interventions in unselected primary care adult patients produced small or medium changes in self-reported dietary outcomes. Medium- to high-intensity interventions generally produced medium or large changes in dietary behavior, but these studies were generally conducted either in adult patients with known risk factors for chronic disease or performed in special research clinics with highly motivated or selected patients. These interventions also generally used highly trained providers who focused on dietary behavioral change. The specific health effects of these dietary behavior changes are not clear, but epidemiological data suggest that the moderate or large differences in dietary behavior are likely to be associated with lower rates of cardiovascular disease and possibly some forms of cancer.1

Among the factors affecting the response to dietary counseling, the intensity of the intervention was strongly associated with the magnitude of dietary change: medium- to high-intensity interventions produced larger changes than low-intensity interventions. Interventions conducted in special, study-specific research clinics were generally more effective than those performed in primary care clinics, but the effect of study setting was highly correlated with intensity. Interventions using self-help materials and interactive communications (computer-tailored mailings, telephone counseling) along with brief provider advice produced medium changes and appeared to be relatively feasible for use in primary care practices that have system support for their delivery. Interventions using greater numbers of well-proven counseling elements also were more likely to produce large or medium effect sizes than those reporting use of few or no components.

Our systematic review has several limitations. First, because we are extracting information from published studies, we are missing several pieces of important data that were not reported regularly. Second, identifying the appropriate measure of dietary change is difficult. Our main outcome measure, self-reported change in dietary behavior, relies on individual self-report, usually from validated food frequency questionnaires that have limited ability to measure small changes in dietary intake accurately and precisely. In addition, patients receiving dietary interventions may be more likely to report positive changes in dietary behavior than control patients, which could also lead to an overestimation of actual benefit. Although the use of biomarkers is often recommended as a more objective means of measurement, it is unclear whether available biochemical markers accurately reflect actual change in diet, may be influenced by medication use and smoking, and may not be any better correlated with health outcomes than patient self-report.

Because we also have little direct evidence about the effect of dietary changes on the risk for important health outcomes,1 we cannot determine with certainty whether the small changes in dietary behavior seen in the lower-intensity trials will translate into changes in the incidence of chronic disease.

The lack of standard outcome measures for each nutrient makes synthesis of the available evidence, including meta-analysis, difficult to perform and interpret. To provide some means of comparison, we rated study outcomes as small, medium, and large, but these definitions were not developed a priori and only partially reflect the limited body of data that links dietary change with specific health outcomes. We did not formally assess for publication bias; smaller trials with negative results may not have been published, which could lead to an overly optimistic impression of the effect of counseling. Finally, we did not have sufficient information to determine the relationship between the cost of dietary interventions and the effect achieved.

Future research should address promising leads already highlighted in this paper and identify novel means to deliver dietary advice in effective and efficient ways. Broadly speaking, research can be pursued along several dimensions. First, research is warranted as to whether dietary assessment leads to more effective counseling and subsequent behavior change when compared with general dietary advice not preceded by an assessment. Better assessment tools for measuring dietary change, including better validated biochemical markers and novel means of documenting dietary consumption, such as hand-held computer diaries, will be useful to address concerns about measurement bias. The interaction between clinical interventions and broader public health, environmental, legislative, and economic interventions to change dietary behavior requires further study as well.

In addition, more in-depth examinations of the effectiveness of specific components and intensities of dietary counseling are needed. Studies with longer followup periods and linkages to actual health outcomes will also be important. The paucity of studies evaluating referral to health professionals outside the primary care setting for either one-on-one or group counseling is striking. Studies of dietary interventions delivered by special research clinics are common, but they are not representative of the resources typically available to primary care providers.

Better epidemiologic studies and randomized trials assessing the clinical as well as population-level benefits of small dietary changes would help clarify the effectiveness of brief counseling interventions. Studies examining the effectiveness of interventions to change consumption of other foods, food patterns, or nutrients, including fish, the Mediterranean diet, legumes, sodium, and calcium or dairy products are warranted, as they each appear to have important relationships to health outcomes.1 Finally, cost-effectiveness studies comparing interventions through different health communication channels and at varying levels of intensity are needed to determine the most feasible approaches. This information, along with data concerning the health benefits of incremental dietary change, will help determine the relative value of dietary counseling compared with other clinical preventive interventions.

Archived: Acknowledgements

This study was developed by the RTI-UNC Evidence-based Practice Center under contract to the Agency for Healthcare Research and Quality (Contract No. 290-97-0011), Rockville, MD. We acknowledge the assistance of David Atkins, M.D., M.P.H., Chief Medical Officer of the AHRQ Center for Practice and Technology Assessment and Jean Slutsky, P.A., M.S.P.H., the Task Order Officer, for their advice and counsel throughout this project. Finally, we thank our RTI-UNC EPC colleagues Russell Harris, M.D., M.P.H., Co-Director of the RTI-UNC Clinical Prevention Center (University of North Carolina), Linda Lux, M.P.A. and Loraine Monroe of RTI for their assistance in this project and production of this article.

 

Archived: Notes

Author Affiliations

[a] Pignone: Division of General Internal Medicine, University of North Carolina at Chapel Hill School of Medicine, North Carolina.
[b] Ammerman and Fernandez: University of North Carolina at Chapel Hill School of Public Health, North Carolina.
[c] Orleans: The Robert Wood Johnson Foundation, Princeton, NJ.
[d] Pender: Professor Emeritus, University of Michigan, Plainfield, IL.
[e] Woolf: Department of Family Medicine, Preventive Medicine and Community Health, Virginia Commonwealth University, Fairfax, VA.
[f] Lohr: RTI International, Research Triangle Park, North Carolina and School of Public Health, University of North Carolina at Chapel Hill, North Carolina.
[g] Sutton: RTI International, Research Triangle Park, North Carolina.

 

Copyright and Source Information

This document is in the public domain within the United States. Requests for linking or to incorporate content in electronic resources should be sent via the USPSTF contact form.

Source: Pignone MP, Ammerman A, Fernandez L, Fernandez L, Orleans CT; Pender N, Woolf S, Lohr KN, Sutton S. Counseling to promote a healthy diet in adults: A summary of the evidence for the U.S. Preventive Services Task Force. Am J Prev Med 2003;24(1):84-101.

 

Archived: Appendix Table 1. Search Strategy

Step Search History Number of Articles
1. exp counseling 17,519
2. exp diet or exp nutrition 149,189
3. 1 and 2 655
4. dietary counseling
or diet counseling
or nutrition counseling
506
5. 3 or 4 1,043
6. limit 5 to human and English language 923
7. limit 6 to randomized controlled trial 115
8. exp randomized controlled trial
or exp single-blind method
or exp double-blind method
or exp random allocation
106,493
9. 6 and 8 30
10. 7 or 9 129

Archived: Appendix Table 2. Articles Excluded for Review in This Report, by Author and Reason for Exclusion

Author, Year Reason for exclusion
Aubin et al., 199835 No control group
Bakx et al., 199736 17 year follow-up of a one-time intervention in 1977
Barratt et al., 199437 Nonclinical intervention (worksite)
Brannon et al., 199738 No control group
Burr et al., 198939 Postmyocardial infarction subjects
Caggiula et al., 199640 No diet outcomes
Calfas et al., 200041 No true control group; comparable diet outcomes not presented
Campbell et al., 199842 Patients with known cardiovascular disease
Cupples and McKnight, 199443 Patients with angina
Crouch et al., 198644 No diet outcomes
DeBusk et al., 199445 Postmyocardial infarction subjects
De Lorgeril et al., 199446 Postmyocardial infarction subjects
Dyson et al., 199747 No control group
Ershoff et al., 198348 No diet outcomes
Family Heart Study Group, 199449 No diet outcomes
Fletcher, 198750 Postmyocardial infarction subjects
Ford and Sciamanna, 199719 Not an intervention (editorial)
Foreyt et al., 197951 No control group; no diet outcomes
George et al., 199352 No diet outcomes
Gosselin et al., 199653 No diet outcomes
Heller et al., 198954 No diet outcomes
Heller et al., 199455 Poor quality due to differential loss to follow-up
Henkin et al., 200056 No diet outcomes
Hjermann et al., 198157 No diet outcomes for full study population
Howard-Pitney et al., 199758 Nonclinical intervention
Hunt et al., 197659 Prenatal care patients only
Kuehl et al., 199360 No control group
Lee-Han et al., 198861 Patients with breast dysplasia
Luepker et al., 197862 No diet outcomes
Lytle et al., 199663 Nonclinical intervention
Masley et al., 200164 Patients with known cardiovascular disease
Miettinen et al., 198565 No diet outcomes
MRFIT Investigators, 198266 No diet outcomes
Naglak et al., 199867 No control group
Neil et al., 199568 No diet outcomes
Neyses et al., 1985[69]] No diet outcomes
Nikolaus et al., 199170 Three week inpatient metabolic ward study
Ornish 199871 Control group information not available
Ornish et al., 199072 Patients with known cardiovascular disease
OXCHECK Study Group 199473
OXCHECK Study Group 199574
No control group
Pritchard et al., 199975 No diet outcomes
Ridgeway et al., 199976 No diet outcomes
Shannon et al., 199477 Non-comparable groups
Smith et al., 197678 No diet outcomes
Tershakovec et al., 199879 Non-comparable groups
Tomson et al., 199580 No diet outcomes
Waber et al., 198181 No diet outcomes
Winkleby et al., 199782 Nonclinical intervention

 

Archived: Table 1. Counseling to Reduce Dietary Fat: Study Descriptions

Author
Year
Sample Population Level of Risk Baseline Patient Numbers Retention Rate Setting Intervention and Control Group Counseling Provider and Resources Intensity
Beresford et al., 199210 Adult men and women in North Carolina, USA; 35% black Unselected Intv: 120
Cont: 122
79% Primary care

Intv: RN on-site provided 5 min intro to self-help materials with phone F/U 10 d later

Cont: no intervention

Low
Beresford et al., 199711 Adult men and women in family practice clinics, USA Unselected Intv: 1,010
Cont: 1,111
86% Primary care

Intv: trained MD-delivered 3 min intro to self-help booklet; reminder letter from MD

Cont: NR

Low
Campbell et al., 199412
Tailored msg vs. control
Adult men and women of family practices: 2 urban and 2 rural in North Carolina, USA Unselected Intv: NR
Cont: NR
82% Mailings and computer-generated messages

Intv: Self-administered surveys in office delivered by staff; tailored messages mailed home

Cont: self-administered surveys only; no messages

Low
Coates et al., 199913 Post-menopausal women in research clinics of Women's Health Trial: 28% black, 16% Hispanic At risk Intv: 1,324
Cont: 883
75% to 85% Research clinic

Intv: RD-delivered group sessions wkly for 6 wks, biweekly for 6 wks, monthly for 9 mo

Cont: given Dietary Guidelines for Americans; no counseling

High
Delichatsios, Friedman et al., 200114 Adult men and women in a large multisite, multispecialty group practice - Harvard Vanguard Medical Associates in Massachusetts, USA; 72% women, 45% white, 45% black Unselected NR 50% Mailings and computer-generated messages

Intv: weekly diet-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Cont: weekly physical activity-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Medium
Delichatsios, Hunt et al., 200115 Adult men and women patients from 6 group HMO practices in the primary care research network of Harvard Pilgrim HealthCare, Massachusetts, USA Unselected Intv: 230
Cont: 274
Intv: 85%
Cont: 92%
Mailings and computer-generated messages

Intv: mailed personalized dietary recommendations and 2 educational booklets; endorsement by trained (1 hour) MD or NP; 2 motivational phone counseling sessions by trained MPH student telephone counselors. RD consultation if needed.

Cont: NR

Medium
Henderson et al., 199016; Insull et al., 199017; Kristal et al., 199218; White et al., 199219 Adult women 45-69 yrs at increased risk for breast cancer participating in Women's Health Trial in Ohio, Texas, Washington, USA At risk Intv: 448
Cont: 457
86% Research clinic

Intv: RD delivered 8 group counseling meetings, followed by 4 meetings, then 20 monthly meetings

Cont: no intervention

High
Keyserling et al., 199720 Adult men and women, low income w/ hypercholesterolemia in community and rural health centers
North Carolina, USA
At risk Intv: 184
Cont: 188
95% Primary care

Intv: On-site MD (trained for intv in 1.5 hr) delivered diet assess and 3 sessions of 5-10 min counseling; followed up by referral to on-site (if available) or off-site RD if persistent hypercholesterolemia

Cont: usual care

Medium
Knutsen and Knutsen, 199121 Adult men at increased risk for CVD and their families
Tromso, Norway
At risk M: 1,373
F: 1,143
C: 2,838
M: 77%
F: 82%
C: 39%
Research clinic

Intv: MD and RD each made 1 home visit for CHD risk factor diet assessment and counseling

Cont: NR

Medium
Kristal et al., 200022 Adult men and women enrollees of Group Health Cooperative of Puget Sound HMO, Washington, USA Unselected Intv: 729
Cont: 730
86.5% Mailings and computer-generated messages

Intv: self-help materials, dietary analysis with behavioral feedback, and semi-monthly newsletters mailed home; trained health educator delivered one motivational phone call

Cont: usual care - no intervention

Medium
Lindholm et al., 199523 Adult men and women at increased risk for CHD in 32 county health centers
Lund, Sweden
At risk Intv: 339
Cont: 342
Intv: 92%
Cont: 95%
Primary care

Intv: usual health care advice from MD (see Cont) plus trained MD or RN delivered 6 group health care advice sessions which discussed 6 separate videos about 6 risk factors for heart disease

Cont: usual health care advice from MD to reduce dietary fat, reduce weight if necessary, to stop smoking; pamphlet to reinforce instructions

High
Mojonnier et al., 198024 Adult men and women with hyperlipidemia in study centers, USA At risk Intv: NR
Cont: NR
70% Research clinic

Intv: RD and nutrition aids delivered 4 different multidimensional interventions including assessment, self-teaching or group-teaching or individual teaching, or multi-method

Cont: followup at 6 or 9 mo for repeat measurements; no intervention

Medium

Neaton et al., 198125

(The MRFIT Study)

Adult men at increased risk for CHD: MRFIT Multicenter Study, USA At risk Intv: 5,825
Cont: 5,766
91% Research clinic

Intv: 10 initial intensive sessions followed by counseling sessions approx. every 4 mo; provider NR

Cont: 3 screenings plus annual risk factor measurement and medical exam

High
Ockene et al., 199626 and Ockene et al., 199927* Adult men and women with hyperlipidemia in HMOs
USA
At risk Intv: NR
Cont: NR
80% Primary care

Intv: MDs (trained for 3 hr) delivered nutrition counseling and staff provided office support

Cont: usual care

Medium
Roderick et al., 199728 Adult men and women with hypercholesterolemia in general practice from 4 regions, United Kingdom Unselected Intv: 473
Cont: 483
Intv: 86%
Cont: 74%
Primary care

Intv: RNs on-site (trained for intv by RD) delivered dietary assessment, advice and F/U

Cont: standard health education materials

Medium
Simkin-Silverman et al., 199529 Premenopausal women at research centers Pennsylvania, USA Unselected Intv: 267
Cont: 253
97% Research clinic

Intv: Trained RD and behavioral interventionists led wkly group meetings x 10 wks then biweekly x 10 wks

Cont: no intervention

High
Steptoe et al., 199930 Adult men and women at increased risk for CHD in 20 general practices in London, England At risk Intv: 316
Cont: 567
59% Primary care

Intv: RN trained (4 days) in behavioral counseling delivered 2 to 3 individual counseling sessions-20 minutes each and 1 or 2 phone F/U

Cont: NR

Medium

* total baseline participants = 1,162, not divided by groups.
Note: C indicates males and females combined; Cont indicates control; F, females; F/U, followup; Intv, intervention; M, males; msg, message; NR, not reported; RD, registered dietician.

Table 1. Counseling to Reduce Dietary Fat: Study Outcomes

Author
Year
Main Outcomea Baseline
Values
Duration of
Followup
Final
Followup
Values
Change from
Baseline to
Final Followup
Net Difference
in Changeb
or Difference at
Final Followup
P-value Relative
Changec
Effect
Sized
Beresford et al., 199210 Grams of total fat

Intv: 66 g
Cont: 67 g

3 mo NR NR

3.8 g

NR 6% Small
Beresford et al., 199711 % calories as total fat

Intv: 37.6%
Cont: 37.5%

12 mo NR

Intv: -1.5%
Cont: -0.3%

1.2%

P <0.01

3% Small

Campbell et al., 199412

Tailored msg vs. control

Grams of saturated fat

Intv: 18.7 g
Cont: 16.3 g

4 mo

Intv: 13.9 g
Cont: 15.8 g

Intv: -4.8 g
Cont: -0.5 g

4.3 g

P = 0.036

26%

Large
Grams of total fat

Intv: 45.6 g
Cont: 41.1 g

Intv: 35.3 g
Cont: 39.8 g

Intv: -10.3 g
Cont: -1.3 g

9 g

P = 0.033

22%

Coates et al., 199913

% calories as saturated fat

Intv: 13.2%
Cont:12.9%

18 mo NR

Intv: -4.4%
Cont: -0.9%

3.5%

NR

27%

Large

% calories as total fat

Intv: 39.7%
Cont: 39.1%

Intv: -14.1%
Cont: -2.5%

11.6 %

NR

30%

Delichatsios, Friedman et al., 200114 % calories as saturated fat

Intv: 10.1%
Cont: 10.3%

6 mo

Intv: 8.8%
Cont: 10.5%

Intv: -1.3%
Cont: +0.2%

1.5%

P <0.05

15% Medium
Delichatsios, Hunt et al., 200115 % calories as saturated fat

Intv: 10.6%
Cont: 10.3%

3 mo

Intv: 9%
Cont: 9.7%

Intv: -1.6%
Cont: -0.6%

1.0%

NR 10% Small

Henderson et al., 199016; Insull et al., 199017; Kristal et al., 199218; White et al., 199219

% calories as saturated fat

Intv: 13.8%
Cont: 13.6%

24 mo

Intv: 7.2%
Cont: 12.3%

Intv: -6.6%
Cont: -1.3%

5.3 %

P <0.001

39%

Large

% calories as total fat

Intv: 39.1%
Cont: 38.9%

24 mo

Intv: 22.6%
Cont: 36.8%

Intv: -16.5%
Cont: -2.1%

14.4 %

P <0.0001

37%

Keyserling et al., 199720 Dietary risk assessment score (scale: 0 to 98)

Intv: 22.0
Cont: 22.0

12 mo NR

Intv: -5.3
Cont: -2.0

3.3

P <0.001

15% Medium
Knutsen and Knutsen, 199121 % of subjects using butter for cooking NR 6 yrs

Intv:
M: 20%
F: 20%

Cont:
M: 36%
F: 36%

NR

M: 16%
F: 16%
C: 10%

NR NA Medium
Kristal et al., 200022

Fat score: 1 to 4
1 = low fat
4 = high fat

Intv: 2.29
Cont: 2.30

12 mo

Intv: 2.20
Cont: 2.30

Intv: -0.09
Cont: 0.00

0.09

P <0.001

4% Small
Lindholm et al., 199523 Grams of total fat NR 18 mo NR NR

14.6 g

P <0.001

NA Medium
Mojonnier et al., 198024

% calories as saturated fat

Intv: 13.9%
Cont: 13.3%

6 and 9 mo F/U combined

Intv: 10.5%
Cont: 12.8%

Intv: -3.9%
Cont: -0.5%

3.4%

P <0.001

26%

Large

% calories as total fat

Intv: 37.8%
Cont: 36.3%

Intv: 33.9%
Cont: 36.6%

Intv: -3.9%
Cont: +0.3%

4.2%

P <0.01

12%

Neaton et al., 198125

(The MRFIT Study)

% calories as saturated fat

Intv: 14.0%
Cont:14.0%

3 yrs

Intv: 10.0%
Cont: 13.5%

Intv: -3.9%
Cont: -0.4%

3.5%

NR

25%

Large

% calories as total fat

Intv: 38.3%
Cont: 38.2%

Intv: 33.8%
Cont: 38.0%

Intv: -4.5%
Cont: -0.2%

4.3%

NR

12%

Ockene et al., 199626

Ockene et al., 199927

% calories as saturated fat

Intv: 10.7%
Cont: 10.7%

12 mo

NR

Intv: -1.1%
Cont: 0%

1.1%

P = 0.01

10%

Small

% calories as total fat

Intv: 30.7%
Cont: 31.2%

NR

Intv: -2.3%
Cont: -0.7%

1.6%

P = 0.11

5%

Roderick et al., 199728

% calories as saturated fat

Intv: 13.7%
Cont: 14.0%

12 mo NR

Intv: -1.5%
Cont: -0.6%

0.9%

NR

6%

Small

% calories as total fat

Intv: 34.3%
Cont: 34.2%

Intv: -2.4%
Cont -0.9%

1.4%

4%

Simkin-Silverman et al., 199529

% calories as saturated fat

Intv: 12.3%
Cont: 11.8%

6 mo NR

Intv: -4.3%
Cont: -0.4%

3.9%

P <0.001

33%

Large

% calories as total fat

Intv: 36.1%
Cont: 35.5%

Intv: -11.1%
Cont: -1.0%

10.1%

28%

Steptoe et al., 199930 DINE Fat score

Intv: 30.5%
Cont: 28.2%

12 mo

Intv: 23.4
Cont: 23.9

Intv: -7.1
Cont: -4.3

2.8%

P <0.05

10% Medium

a Outcomes in this table are reported in the following order of preference depending on the data available from each study: (1) percentage of calories from saturated or total fat; (2) grams of saturated or total fat; and (3) other methods of measuring change in diet as presented by the authors of specific studies.
b Baseline minus followup value for the intervention group minus baseline minus followup value for the control group.
c Absolute change in the intervention group from baseline to followup divided by the baseline value of the control group.
d Effect size categories are assigned based on (in order of preference) net difference in change, difference at final followup, or relative change.

Note: C indicates males and females combined; Cont indicates control; F, females; F/U, followup; Intv, intervention; M, males; msg, message; NA, not available; NR, not reported.

Archived: Table 2. Counseling to Increase Intake of Fruit or Vegetables: Study Descriptions

Author
Year
Sample Population Level of Risk Baseline Patient Numbers Retention Rate Setting Intervention and Control Group
Counseling Provider and Resources
Intensity
Campbell et al., 199412

Tailored msg vs. control

Adult men and women of family practices: 2 urban and 2 rural in North Carolina, USA Unselected Intv: NR
Cont: NR
82% Mailings and computer-generated messages Intv: Self-administered surveys in office delivered by staff; messages mailed home

Cont: self-administered surveys only; no messages

Low
Coates et al., 199913 Post-menopausal in research clinics of Women's Health Trial
28% black, 16% Hispanic
At risk Intv: 1,324
Cont: 883
75% to 85% Research clinic Intv: RD-delivered group sessions weekly x 6 weeks, biweekly x 6 weeks, monthly x 9 months

Cont: given Dietary Guidelines for Americans; no counseling

High
Delichatsios, Friedman et al., 200114 Adult men and women in a large multisite, multi-specialty group practice—Harvard Vanguard Medical Associates in Massachusetts, USA; 72% women, 45% white, 45% black Unselected NR NR Mailings and computer-generated messages: home Intv: weekly diet-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Cont: weekly physical activity-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Medium
Delichatsios, Hunt et al., 200115 Adult men and women patients from 6 group HMO practices in the primary care research network of Harvard Pilgrim HealthCare, Massachusetts, USA Unselected Intv: 230
Cont: 274
Intv: 85%
Cont: 92%
Mailings and computer-generated messages Intv: mailed personalized dietary recommendations and 2 educational booklets; endorsement by 1 hour-trained MD or NP; 2 motivational phone counseling sessions by trained MPH student telephone counselors. RD consultation if needed.

Cont: NR

Medium
Knutsen and Knutsen, 199121 Adult men at increased risk for CVD and their families
Tromso, Norway
At risk 2,838 39% Research clinic Intv: MD or RD each made 1 home visit for CHD risk factor counseling and diet assessment and counseling

Cont: NR

Medium
Kristal et al., 200022 Adult men and women enrollees of Group Health Cooperative of Puget Sound HMO, Washington, USA Unselected Intv: 729
Cont: 730
86.5% Mailings and computer-generated messages Intv: self-help materials, dietary analysis with behavioral feedback, and semi-monthly newsletters mailed home; trained health educator-delivered motivational phone call

Cont: usual care - no intervention

Medium
Lutz et al., 199931

Tailored msg w/ goal vs. control

Adult men and women Unselected Intv: 177
Cont: 180
81% Mailings and computer-generated messages Intv: self-administered assessment mailed home; tailored messages were mailed home

Cont: no newsletter

Low
Maskarinec et al., 199932 Healthy adult women over age 35 consuming less than 5 servings of fruit and vegetables daily in a study center
Hawaii, USA
Unselected Intv: 13
Cont: 16
88% Research clinic Intv: RD delivered monthly counseling sessions (1st 2 individual, next 3 group) with phone F/U as needed to increase fruits and vegetables

Cont: RD delivered general healthy eating counseling based on the USDA Dietary Guidelines

High
Roderick et al., 199728 Adult men and women with hypercholesterolemia in general practice from 4 regions,
United Kingdom
Unselected Intv: 473
Cont: 483
Intv: 86%
Cont: 74%
Primary care Intv: RNs on-site (trained for intv by RD) delivered dietary assessment, advice and F/U

Cont: standard health education materials

Small
Siero et al., 200033

Group education and tailored msg vs. control

Low income adult men and women at increased risk for CVD in primary care practices and at home,
The Netherlands
At risk Intv: NR
Cont: NR
NR Research clinic Intv: messages were mailed home; group sessions 2 hr each led by group instructor, not otherwise specified

Cont: received printed leaflet with the Dutch nutritional guidelines

High

Note: Cont indicates control; F/U, followup; Intv, intervention; msg, message; NP, nurse practitioner; NR, not reported; RD, registered dietician; RN, registered nurse.

 

Table 2. Counseling to Increase Intake of Fruit or Vegetables: Study Outcomes

Author
Year
Main Outcome Baseline
Values
Duration of
Followup
Final
Followup
Values
Change from
Baseline to
Final Followup
Net Difference
in Changea
or Difference at
Final Followup
P-value Relative
Changeb
Effect
Size
Campbell et al., 199412

Tailored msg vs. control

Servings of fruit and vegetables per day Intv: 3.6
Cont: 3.6
4 mo Intv: 3.3
Cont: 3.3
Intv: -0.3
Cont: -0.3
0 servings P = 0. 817 0% Small
Coates et al., 199913 Servings of fruit per day Intv: 1.53
Cont: 1.52
18 mo NR Intv: +0.54
Cont: +0.02
0.53 servings NR 35% Medium

Servings of vegetables per day

Intv: 1.62
Cont: 1.65

Intv: +0.35
Cont: +0.08

0.27 servings NR 16%
Delichatsios, Friedman et al., 200114 Combined fruits and vegetables Intv: 6.6
Cont: 5.9
6 mo Intv: 7.7
Cont: 5.6
Intv: +1.1
Cont: -0.3
1.4 servings NR 24% Large
Delichatsios, Hunt et al., 200115 Servings of fruit and vegetables per day Intv: 2.9
Cont: 3.3
Intv: 2.9
Cont: 3.3
Intv: 4.0
Cont: 3.7
Intv: +1.1
Cont: +0.4
0.7 servings NR 21% Medium
Knutsen and Knutsen, 199121 % of subjects eating >4 fruits per week NR 6 yrs

Intv: 43%
Cont: 39%

NR 4% NR NA Small
% of subjects eating vegetables with dinner NR NR

Intv: 51%
Cont: 53%

NR 2% NR NA Small
Kristal et al., 200022 Servings of fruit and vegetables per day Intv: 3.62
Cont: 3.47
12 mo Intv: 4.09
Cont: 3.61
Intv: +0.47
Cont: +0.14
0.33 servings P <0.001 10% Medium
Lutz et al., 199931

Tailored msg w/ goal vs. control

Mean servings of fruits and vegetables per day Intv: 3.5
Cont: 3.5
6 mo Intv: 4.4
Cont: 3.6
Intv: +0.9
Cont: +0.1
0.8 servings P <0.002 23% Medium
Maskarinec et al., 199932 Servings of fruit and vegetables per day Intv: 3.2
Cont: 3.3
6 mo Intv: 7.4
Cont: 4.1
Intv: 4.2
Cont: 0.8
3.4 servings P = 0.0001 100% Large
Roderick et al., 199728 Servings of fruit and vegetables per week NR 12 mo NR Intv: 1.09
Cont: 0.03
0.94 servings NR NA Medium
Siero et al., 200033

Group education and tailored msg vs. control

Fruits and vegetables grams/day Intv: 426 g
Cont: 416 g
16 wks Intv: 494 g
Cont: 395 g
Intv: +68g
Cont: -21 g
+99 g NR 24% Medium

aBaseline minus followup value for the intervention group minus baseline minus followup value for the control group.
bAbsolute change in the intervention group from baseline to followup divided by the baseline value of the control group.

Note: Cont indicates control; Intv, intervention; msg, message; NA, not available; NR, not reported.

Archived: Table 3. Counseling To Increase Intake of Fiber: Study Descriptions

Author, Year Sample Population Level of Risk Baseline Patient Numbers Retention Rate Setting Intervention and Control Group Counseling Provider and Resources Intensity
Baron et al., 199034 Adult men and women in a group general practice, Abingdon, UK Unselected Intv: 187
Cont: 181
91% Primary care Intv: RN delivered 30 min group or individual diet advice and 2 F/Us

Cont: RN F/U visit at 1 and 3 months; no dietary advice
Medium
Beresford et al., 199210 Adult men and women in primary care 35% black North Carolina, USA Unselected Intv: 120 Cont: 122 79% Primary care

Intv: RN on site provides 5 min intro to self-help materials with phone F/U 10 d later

Cont: baseline interview only

Low
Beresford et al., 199711 Adult men and women in family practice clinics, USA Unselected Intv: 1,010 Cont: 1,111 86% Primary care

Intv: MD-delivered 3-min intro to self-help booklet + reminder letter from MD

Cont: NR

Low
Delichatsios, Friedman et al., 200114 Adult men and women in a large multisite, multi-specialty group practice—Harvard Vanguard Medical Associates in Massachusetts, USA; 72% women, 45% white, 45% black Unselected NR NR Mailings and computer-generated messages

Intv: weekly diet-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Cont: weekly physical activity-related educational feedback, advice, and behavioral counseling for 5-7 minutes by a totally automated, telephone-linked computer-based voice communication system

Medium
Delichatsios, Hunt et al., 200115 Adult men and women patients from 6 group HMO practices in the primary care research network of Harvard Pilgrim HealthCare, Massachusetts, USA Unselected Intv: 230 Cont: 274 Intv: 85% Cont: 92% Mailings and computer-generated messages

Intv: mailed personalized dietary recommendations and 2 educational booklets; endorsement by 1 hour-trained MD or NP; 2 motivational phone counseling sessions by trained MPH student telephone counselors. RD consultation if needed.

Cont: NR

Medium
Lindholm et al., 199523 Adult men and women at increased risk for CHD in 32 county health centers Lund, Sweden At risk Intv: 339 Cont: 342 Intv: 92% Cont: 95% Primary care

Intv: MD- or RD-delivered group health care advice sessions

Cont: usual health care advice from MD to reduce dietary fat, reduce weight if necessary, to stop smoking; pamphlet to reinforce instructions

High
Roderick et al., 199728 Adult men and women with hypercholesterolemia in general practice from 4 regions, United Kingdom Unselected Intv: 473 Cont: 483 Intv: 86% Cont: 74% Primary care

Intv: RNs on-site (trained for intv by RD) delivered dietary assessment, advice and F/U

Cont: standard health education materials

Medium

Note: Cont indicates control; F/U, followup; Intv, intervention; NR, not reported; RD, registered dietician; RN, registered nurse.

Table 3. Interventions To Increase Intake of Fiber: Study Outcomes

Author, Year Main Outcome Baseline Values Duration of Followup Final
Followup Values
Change from Baseline to Final Followup Net Difference in Changea or Difference at Final Followup P-value Relative Changeb Effect Size
Baron et al., 199034 Grams of fiber per day

Intv:
M: 20.4 g
F: 18.9 g

Cont:
M: 19.3 g
F: 16.4 g

12 mo

Intv:
M: 22.8 g
F: 21.4 g

Cont:
M: 20.1 g
F: 15.4 g

NR M: 2.7 g
F: 6.0 g
NS M: 14%
F: 37%
Medium
Beresford et al., 199210 Grams of fiber per day (adjusted) Intv: 14 g
Cont: 15 g
3 mo NR NR 0.6 g NR 4% Small
Beresford et al., 199711 Grams of fiber per 1,000 kcal

Intv: 10 g per 1,000 kcal

Cont: 10 g per 1,000 kcal

12 mo NR

Intv: +0.5 g per 1,000 kcal

Cont: +0.2 g per 1,000 kcal

0.3 g NS 3% Small
Delichatsios, Friedman et al., 200114 Grams of fiber per day Intv: 21 g
Cont: 20 g
6 mo Intv: 22 g
Cont: 18 g
Intv: +1 g
Cont: -2 g
3 g P <0.05 15% Medium
Delichatsios, Hunt et al., 200115 Grams of fiber per day Intv: 7.3 g
Cont: 8.2 g
3 mo Intv: 9.3 g
Cont: 9.0 g
Intv: +2 g
Cont: +0.8 g
1.2 g NR 15% Small
Lindholm et al., 199523 Grams of fiber per day NR 18 mo NR NR 0.9 g P <0.001 NA Small
Roderick et al., 199728 Grams of fiber per day Intv: 23.3 g
Cont: 23.2 g
12 mo NR Intv: +0.9
Cont: -0.2
1.1 g CI
(-0.2 - 2.23)c
4% Small

a Baseline minus followup value for the intervention group minus baseline minus followup value for the control group.
b Absolute change in the intervention group from baseline to followup divided by the baseline value of the control group.
c P-value not reported, confidence interval given instead.

Note: Cont indicates control; Intv, intervention; NA not available; NS, not significant; NR, not reported.

Archived: Table 4. Effect of Patient Risk Status and Intervention Intensity on Dietary Change

Intervention Intensity Unselected Patients "At Risk" Patients
Low Intensity Beresford et al., 199210 (fat)
Beresford et al., 199210 (fiber)
Beresford et al., 199711 (fat)
Beresford et al., 199711 (fiber)
Campbell et al., 199412 (F&V)
Lutz et al., 199931 (F/V)
Campbell et al., 199412 (fat)
 
Medium Intensity Delichatsios, Hunt et al., 200115 (fat)
Kristal et al., 200022 (fat)
Baron et al., 199034 (fiber)
Delichatsios, Friedman et al., 200114 (fat)
Delichatsios, Friedman et al., 200114 (F/V)
Delichatsios, Friedman et al., 200114 (fiber)
Delichatsios, Hunt et al., 200115 (F/V)
Delichatsios, Hunt et al., 200115 (fiber)
Kristal et al., 200022 (F/V)
Roderick et al., 199728 (fat)
Roderick et al., 199728 (fiber)
Roderick et al., 199728 (F/V)
Knutsen and Knutsen, 199121 (F/V)
Ockene et al., 199927 (fat)
Keyserling et al., 199720 (fat)
Knutsen and Knutsen, 199121 (fat)
Steptoe et al., 199930 (fat)
Mojonnier et al., 198024 (fat)
High Intensity Maskarinec et al., 199932 (F/V)
Simkin-Silverman et al., 199529 (fat)
Lindholm et al., 199523 (fiber)
Coates et al., 199913 (F/V)
Lindholm et al., 199523 (fat)
Siero et al., 200033 (F/V)
Coates et al., 199913 (fat)
Henderson et al., 199016 (fat)
Neaton et al., 198125 (fat)

Note: Plain text indicates a small effect; italic text, a medium effect; bold text, a large effect; F/V, fruits and vegetables.

Archived: Table 5. Relationship Between the Number of Effective Intervention Elements and Change in Dietary Behavior

Amount of Change in Dietary Behavior 0 Components 1-2 Components 3-7 Components
Small Effect Beresford et al., 199210 (fat)
Beresford et al., 199210 (fiber)
Beresford et al., 199711 (fat)
Beresford et al., 199711 (fiber)
Campbell et al., 199412 (F/V)
Delichatsios, Hunt et al., 200115 (fat)
Knutsen and Knutsen, 199121 (F/V)
Kristal et al., 200022 (fat)
Lindholm et al., 199523 (fiber)
Ockene et al., 199927 (fat)
Roderick et al., 199728 (fat)
Roderick et al., 199728 (fiber)
Roderick et al., 199728 (F/V)
 
Medium Effect   Baron et al., 199034 (fiber)
Delichatsios, Friedman et al., 200114 (fat)
Delichatsios, Friedman et al., 200114 (fiber)
Delichatsios, Hunt et al., 200115 (fat)
Delichatsios, Hunt et al., 200115 (fiber)
Knutsen and Knutsen, 199121 (fat)
Kristal et al., 200022 (F/V)
Lindholm et al., 199523 (fat)
Lutz et al., 199931 (F/V)
Siero et al., 200033 (F/V)
Steptoe et al., 199930 (fat)
Coates et al., 199913 (F/V)
Keyserling et al., 199720 (fat)
Large Effect   Campbell et al., 199412 (fat)
Delichatsios, Friedman et al., 200114 (F/V)
Mojonnier et al., 198024 (fat)
Simkin-Silverman et al., 199529 (fat)
Coates et al., 199913 (fat)
Henderson et al., 199016 (fat)
Maskarinec et al., 199932 (F/V)
Neaton et al., 198125 (fat)

Note: F/V indicates fruits and vegetables.

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Current as of: January 2003

Internet Citation: Final Evidence Review: Healthy Diet: Counseling Adults with CVD, January 2003. U.S. Preventive Services Task Force. February 2014.
https://www.uspreventiveservicestaskforce.org/Page/Document/final-evidence-review41/diet-for-adults-at-increased-risk-for-cardiovascul

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