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Logo of jwhMary Ann Liebert, Inc.Mary Ann Liebert, Inc.JournalsSearchAlerts
Journal of Women's Health
J Womens Health (Larchmt). 2008 September; 17(7): 1099–1110.
PMCID: PMC2944416

Obesity Reduction Black Intervention Trial (ORBIT): Design and Baseline Characteristics

Marian L. Fitzgibbon, Ph.D.,corresponding author1,,2,,3 Melinda Stolley, Ph.D.,1,,3 Linda Schiffer, M.S., M.P.H.,1 Lisa Sharp, Ph.D.,1 Vicky Singh, Ph.D.,1 Linda Van Horn, Ph.D., R.D.,4 and Alan Dyer, Ph.D.4



Obesity is associated with many chronic diseases, and weight loss can reduce the risk of developing these diseases. Obesity is highly prevalent among Black women, but weight loss treatment for black women has been understudied until recently. The Obesity Reduction black Intervention Trial (ORBIT) is a randomized controlled trial designed to assess the efficacy of a culturally proficient weight loss and weight loss maintenance program for black women. This paper describes the design of the trial, the intervention, and baseline characteristics of the participants.


Two hundred thirteen obese black women aged 30–65 years were randomized to the intervention group or a general health control group. The intervention consists of a 6-month weight loss program followed by a 1-year maintenance program. Weight, dietary intake, and energy expenditure are measured at baseline, 6 months, and 18 months.


More than 40% of participants had a baseline body mass index (BMI) >40 kg/m2 (class III obesity). Intake of fat and saturated fat was higher and consumption of fruit, vegetables, and fiber was lower than currently recommended guidelines. Self-reported moderate to vigorous physical activity was high (median 85 min/day). However, objectively measured physical activity among a subgroup of participants was lower (median 15 min/day).


Weight loss among obese black women has received inadequate attention in relation to the magnitude of the problem. Factors that contribute to successful weight loss and more importantly, weight loss maintenance need to be identified.


The prevalence of obesity has increased dramatically over the past 30 years, and about 32% of adults in the United States are now obese.1,2 Obesity is associated with a variety of chronic conditions, including cardiovascular disease, type 2 diabetes, postmenopausal breast cancer, and colon cancer.3,4 The prevalence of obesity is particularly high among black women (54%), and morbidity and mortality from diseases associated with obesity are higher among black women than among white women.58 Weight loss is associated with numerous benefits, including reduced blood pressure, improved lipid profiles, prevention or delay of type 2 diabetes onset, and reduced risk of postmenopausal breast cancer.911

Overall, weight loss treatment among blacks has been studied less extensively than it has in white populations.12 On behalf of the U.S. Preventive Services Task Force, McTigue et al.13 recently conducted a review of the obesity treatment literature. They searched MEDLINE and the Cochrane Library for reports of randomized controlled trials of obesity treatment interventions published in English between January 1994 and February 2003. Strikingly, more than 75% of the studies either did not report an ethnic breakdown or did not include a substantial number of black participants. Similarly, in a recent randomized trial comparing four weight loss diets, only 6% of the participants were black.14 Even when black women have been well-represented, however, they are often less successful at losing weight than white women.1517 For example, in the Diabetes Prevention Program (DPP), approximately half as many black participants as white participants achieved the 7% weight loss goal at 6 months.18 The black participants did show better weight loss maintenance in the DPP, but they lost less weight than white participants overall because of their lower initial weight loss.18

Weight loss studies that focused specifically on black populations have shown mixed results.17 The Black American Lifestyle Intervention (BALI) weight loss program was developed specifically for black women, and results of a pilot study (n = 67) showed that participants lost 3.5% of body weight over a 10-week period.19 McNabb et al.20 also reported positive results from a 14-week church-based program (n = 39), with a loss of 4.5 kg in the intervention group vs. a gain of 0.9 kg in the control group. Pounds Off with Empowerment (POWER) was a 12-month randomized trial (n = 152) of an intensive lifestyle intervention that was modeled after the DPP.21,22 Eighty-two percent of participants were black. Participants in the intensive lifestyle group lost significantly more weight in 6 months than those in the control group (2.6 kg vs. 0.4 kg, p < 0.01).22 In a trial of a primary care weight management program designed for low-income, obese black women, women in the intervention group lost 2.0 kg in 6 months, compared with a gain of 0.2 kg in the control group (p = 0.03).23 Finally, the small randomized trial that served as a pilot study for the Obesity Reduction Black Intervention Trial (ORBIT) was conducted in two cohorts.24 In the first cohort (n = 27), women received a less intensive weight loss intervention, and there was no difference in weight loss between women in the intervention and control groups. However, the weight loss intervention was intensified for the second cohort (n = 37), and women in the intervention group lost 3.4 kg, whereas those in the control group gained 0.9 kg (p = 0.002).24

Other studies have shown less positive results. For example, the Healthy Eating and Lifestyle Program (HELP) study tested a culturally adapted two-phase weight loss program (n = 237).25 The initial 10-week intervention resulted in modest weight loss (1.7 kg) among the 134 participants who completed phase 1, but there was no treatment effect after phase 2, which lasted 8–18 months.25

Considerably less information is available on maintenance of weight loss among black women.26 The Life Enhancement Awareness Program (LEAP) was a study designed to assess factors associated with both weight loss and weight loss maintenance among black women.27 Although the women who completed the study (n = 10) lost weight (10.7 lb, SD = 10.1, p < 0.01), the study reported an attrition rate of >50% over the course of the 32-week intervention, and there was no control group.27 Another study reported feedback from two small focus groups of black women who had lost at least 10 pounds in the past.28 The women in the first group (n = 6) had maintained the weight loss for at least 1 year, and the women in the second group (n = 6) had regained the weight. Successful women reported that improved energy and physical appearance motivated them to maintain their weight loss, and women who were unsuccessful reported being too “busy” or too “lazy” to maintain the new diet and exercise habits. Factors that facilitated or impeded weight loss and maintenance were not discussed in depth.28

ORBIT is a randomized controlled trial designed to assess the efficacy of a culturally proficient weight loss and maintenance intervention among 213 obese black women between the ages of 30 and 65 years. The aim of this paper is to outline the overall design of ORBIT, describe the intervention, and present baseline characteristics of the randomized women. The primary outcomes (i.e., weight change, weight loss maintenance, and changes in energy intake and energy expenditure) will be described in future publications, as the trial is ongoing.

Materials and Methods

Study design

ORBIT is a randomized controlled trial of a culturally adapted 6-month weight loss intervention followed by a 1-year weight loss maintenance intervention. The study design is shown in Figure 1. Eligible women who gave informed consent and completed a baseline interview were randomized to either the intervention group or the control group Data will be collected after the weight loss intervention (6 months) and the maintenance intervention (18 months). Full Institutional Review Board approval was obtained from the University of Illinois at Chicago (UIC), where the trial is being conducted.

FIG. 1.
Study design of the ORBIT project and participant flow through randomization.

Sample size

The sample size of 100 per group was selected to provide 90% power to detect a difference of 1.1–1.25 kg/m2 in change in body mass index (BMI) between the intervention and control groups at 18 months, assuming a two-sided test at the 5% level. Power calculations also assumed that at least 85% of the women would provide data at 18 months and that the SD in change in BMI would be between 2.2 and 2.5 kg/m2.

Recruitment/screening for eligibility

Because of resource limitations, the study is being conducted in two cohorts of approximately 100 women each. Recruitment for cohort 1 began in May 2005 and ended in August 2005. Recruitment for cohort 2 began in July 2006 and ended in September 2006. Recruitment strategies included a mass e-mail that was sent to all UIC faculty, staff, and students (approximately 36,000 recipients), and face-to-face recruitment from nearby neighborhoods, local grocery stores, churches, nearby healthcare centers, and the UIC Hospital primary care clinics. All recruitment was done within a 2-mile radius of the intervention site.

Women who were interested in the program were asked to complete a short eligibility interview either by telephone (86%) or in person (14%). The eligibility criteria are shown in Table 1. Consistent with principles for conducting a randomized controlled efficacy trial, exclusion criteria were kept to a minimum.29,30 However, because the intervention was not designed for pregnant women, women <30 years old and women who were planning a pregnancy in the next 18 months were excluded. Women > age 65 were excluded because of concerns that obese older women would be less able than younger women to participate safely in the physical activity component of the intervention.

Table 1.
Eligibility Criteria for Participation in ORBIT

Eligible women were given a medical approval form to be signed by their healthcare provider. By signing the form, the provider indicated that the individual was healthy enough to participate safely in a weight loss program including moderate exercise geared toward women with low levels of physical fitness.


All data collectors were trained and certified by a master trainer in both interviewing and anthropometry. All questionnaires were interviewer administered.

Sociodemographic data

This information included date of birth, education, income, occupation, employment status, and marital status.


Height was measured using a Seca 214 portable stadiometer (Seca, Hanover, MD), and weight was measured using a Tanita BWB-800 digital scale (Tanita Corporation of America, Inc., Arlington Heights, IL). Participants removed their shoes and any heavy outer clothing for the anthropometric measurements. Height and weight were measured twice during the baseline interview, to the nearest 0.1 cm and 0.1 kg, respectively. If the two height measurements were more than 0.5 cm apart or if the two weight measurements were more than 0.2 kg apart, a third measurement was taken. The mean of the two closest measurements was used for analysis. BMI was computed from height and weight.

Block ’98 Food Frequency Questionnaire (FFQ)31,32

The Block FFQ asks about frequency of consumption in the past year and usual portion size for 110 different food items. The food list was developed using food intake data from the National Health and Nutrition Examination Survey III (NHANES III). Separate lists were developed using data from blacks, non-Hispanic whites, and Hispanics in order to ensure that the final food list would include foods that are frequently consumed among blacks and Hispanics. In addition, the Block ’98 includes low-fat items that an individual could adopt in attempting to change dietary patterns. Reliability and validity have been established for the measure in a wide range of age, gender, income, and ethnic groups.31,32 Data from the FFQ can be used to calculate nutrient intake, food group intake, and other dietary variables, including the Healthy Eating Index (HEI).3335 The HEI is a measure of overall diet quality developed by United States Department of Agriculture's (USDA) Center for Nutrition Policy and Promotion. Components of the index include servings of the five food groups in the USDA's Food Guide Pyramid, total fat and saturated fat as a percentage of energy, sodium, cholesterol, and variety. Scores range from 0 to 100, with a higher score reflecting a healthier diet.33

International Physical Activity Questionnaire, Long Last 7 Days Telephone Format (IPAQ)36

The long IPAQ is designed to assess physical activity during the last 7 days. The IPAQ was developed by a multinational working group and can be interviewer-administered or self-administered. Items assess physical activity across a diverse set of domains, including leisure time physical activity, domestic and yard physical activity, work-related physical activity, and transport-related physical activity. Participants are asked only to report activity that they engaged in for at least 10 minutes at a time. Separate scores are calculated for walking, moderate-intensity activity, and vigorous-intensity activity for each of the domains. Participants are also asked about time spent sitting on weekdays and weekends. The psychometric properties of the IPAQ compare favorably to other commonly used self-reported physical activity measures.36 To our knowledge, however, this measure has not been validated in obese individuals.

ActiGraph Activity Monitor (cohort 2 only)

An objective measurement of physical activity was obtained for cohort 2 participants using the ActiGraph GT1M activity monitor (ActiGraph, LLC, Pensacola, FL). The ActiGraph is a small, lightweight (3.8 × 3.7 × 1.8 cm, 27 g), uniaxial accelerometer designed to detect normal body motion and filter out motion from other sources.37 The acceleration signal is sampled 30 times per second, and signals are summed at the end of a specified period (1 minute for this study) and stored in nonvolatile flash memory. Participants were asked to wear the ActiGraph during waking hours for 7 days. Study staff called participants several times during the 7 days to remind them to wear the accelerometer and to answer any questions. Activity counts were downloaded from the accelerometers using ActiLife Lifestyle Monitoring System Software (ActiGraph, LLC), and the resulting text files were read and analyzed using SAS for Windows v 9.1 (SAS Institute Inc., Cary, NC). Only days on which the participant wore the accelerometer for at least 10 hours were included in the analysis, and participants who had fewer than 4 valid days were excluded. When the ActiGraph registered 0 counts for at least 20 minutes at a time, it was assumed that the participant was not wearing the accelerometer. A number of prediction equations have been proposed for translating raw accelerometer counts into measures of energy expenditure.38 In the absence of a clear consensus, we chose the widely used thresholds suggested by Freedson et al.39: 1952 counts for moderate activity (≥3 METs) and 5725 counts for vigorous activity (≥6 METs). These thresholds were used to calculate the amount of time spent in moderate, vigorous, and moderate/vigorous physical activity (MVPA), as well as the amount of time spent in bouts of MVPA lasting at least 10 minutes.

Body image

The Figure Rating Scale contains nine schematic figures (silhouettes) of women, displayed in order from underweight to obese (Fig. 2).40 Women in this study were asked to indicate which figure looked most like them and which figure they would like to look like. We derived a body discrepancy (BD) rating by subtracting the ideal body image from the current body image. The BD rating can range from −8 to 8. A BD rating >0 indicates that the participant's current body image is larger than her ideal body image. A BD rating <0 indicates that the participant's current body image is lighter than her ideal body image. A score of 0 indicates that the same figure was chosen for the current and ideal image.

FIG. 2.
Figure Rating Scale showing nine silhouettes of women displayed in order from underweight to obese. (Reprinted with permission from reference 40.)

Data analysis

The Block ’98 FFQs were sent to NutritionQuest (Berkeley, CA) for scoring. Participants with total energy < 500 kcal/day or > 5000 kcal/day were excluded from the analysis. The IPAQ was scored according to the November 2005 long-form scoring protocol.41 As recommended in the scoring protocol, medians are reported for the physical activity data because the data are not normally distributed. Descriptive statistics were calculated using SAS for Windows v. 9.1. Two-sample t tests, chi-square tests, and Wilcoxon rank sum tests were used to test for differences between the intervention and control group at baseline. All analyses were repeated excluding all women who had any missing data.


Weight loss intervention

Table 2 shows the topics covered in the 6-month weight loss intervention curriculum and the first 6 months of control newsletters. To produce and maintain weight loss, it is necessary to create an energy imbalance through a decrease in energy intake and an increase in energy expenditure.42 However, for weight loss programs to be successful among black women, there must be a recognition and incorporation of the practices, attitudes, and beliefs of this particular subgroup.43,44 For example, dietary changes must target foods that are typically reported by black women as being part of their usual dietary patterns. We were cognizant of the importance of offering alternatives that reduce caloric content without sacrificing flavor. Goals for increased physical activity need to account for potential barriers, such as child care, hair styling, and family and work responsibilities.4547 In addition to eating and exercise behaviors, culturally proficient weight loss programs must also incorporate body image, the meaning of weight, and reasons for weight loss.4850

Table 2.
Topics Covered in the 6-Month Weight Loss Intervention Curriculum and Control Newsletters, ORBIT

The conceptual framework guiding the development and delivery of the intervention was based on social cognitive theory (SCT)51 and, thus, focused on changes in cognitions, behaviors, and social support related to weight loss. According to SCT, modeling or observational learning is a powerful contributor to behavioral change.51 Individuals are more likely to model behavior that has a positive outcome, as well as the behavior of someone similar to themselves. The intervention provided ample opportunity for observational learning to occur. For example, although not all of our interventionists were black, our intervention team did include black women who served as potential role models to group members.

All intervention participants were encouraged to adopt a low-fat, high-fiber diet with increased fruit and vegetable consumption and to increase their overall physical activity. Exercise objectives included exercising at a moderate to vigorous level a minimum of 3–4 times per week for at least 30 minutes. Participants also received pedometers and were asked to increase their physical activity to a level equivalent to 10,000 steps per day.

The weight loss intervention was conducted in a small group format and met twice weekly on the university campus. One meeting each week was 90 minutes long and consisted of a weekly weigh-in, a didactic session, and a physical activity session. During the didactic session, the group leaders led discussions related to diet, physical activity, and weight loss for approximately 30–40 minutes. The didactic session was followed by a physical activity session that incorporated aerobic activity as well as strength and flexibility training. To increase the variety, some physical activity sessions included salsa dancing, African dancing, belly dancing, yoga, and Pilates. The second meeting of each week was 60 minutes in length and included a 30–40 minute physical activity class and discussion of topics related to increasing regular physical activity.

Weight loss maintenance intervention

The ability to maintain diet and physical activity patterns that affect long-term weight control requires permanent adoption of healthful behaviors.52,53 During the 1-year ORBIT maintenance phase, the frequency of meetings decreased and emphasis was placed on structuring one's life in a way that supports maintenance of weight loss behaviors. In months 7–12, the group met twice weekly for 45–60 minutes, and each member received monthly motivational interviewing (MI) sessions.54 During the group meetings, the didactic sessions were replaced with a support group conducted by the participants. The topic of each support group session was chosen by a participant, which allowed for tailoring of the material to fit the needs of members of the group. Participants discussed such topics as weight loss myths and how to care for oneself without using food. In months 13–15, the group met once weekly for an exercise class, and women continued to receive monthly MI. Finally, in months 16–18, there were no face-to face group meetings, but women continued to receive MI. Newsletters were sent to intervention participants every other month during the maintenance period.

Motivational interviewing (MI)

As part of our conceptual model based on SCT, we sought multiple avenues to enhance self-efficacy. As a component of the intervention, we provided participants with the opportunity for individual problem solving through MI.54 Participants received monthly MI sessions throughout the 6-month weight loss intervention and the 1-year maintenance intervention. Each MI session addressed either diet or physical activity. Sessions were conducted face-to face or over the phone, and each session lasted approximately 20–30 minutes.

General health intervention control group

Newsletters were sent to control group participants weekly throughout the 6 months of the weight loss intervention and monthly during the 1-year maintenance phase. Control newsletters covered general health and safety topics relevant to adult women. The control group will receive the entire written curriculum at the end of the trial.


As shown in Figure 1, the target recruitment goal of 200 obese black women was met. Two hundred thirteen women were randomized, 107 to the intervention group and 106 to the control group. As shown in Table 3, the mean age was 46.0 years (SD 8.4 years). Participants were well educated, with 44% reporting a college or graduate/professional degree. A majority of the women were employed full-time (72%). About a third of the women were married or living with a partner, and their median income was approximately $42,500. The average BMI was 39.2 (5.7) kg/m2, and more than 40% of participants had a BMI  40 kg/m2. On the body image rating scale,40 all participants reported a discrepancy of at least 1 between their current and ideal body image, with their current body image being larger than their ideal body image. (See silhouettes in Fig. 2.)

Table 3.
Participant Characteristics at Baseline, ORBIT

Table 4 shows estimated total energy and nutrient intake and servings per day of foods from each food group: grains, vegetables, fruits, meat, dairy, and fats, oils, and sweets. The average intake of energy was 2418 (1037) kcal, and mean percentage of energy from fat was 41.3 (6.3)%. Participants reported 3.4 (2.1) servings of vegetables and 1.3 (1.0) servings of fruits per day. The mean HEI score was 53.9 (11.7) out of a possible 100, which falls into the “needs improvement” category; 54% of the women scored in the needs improvement range (51–80), 43% scored in the poor range (< 51), and only 3% scored in the good range (> 80).

Table 4.
Diet at Baseline from Food Frequency Questionnairea: Nutrients and Food Groupsb, ORBIT

Table 5 shows self-reported physical activity for all participants, and Table 6 shows self-reported and objectively measured physical activity for the subgroup of women who wore an accelerometer for 4–7 days. Ninety-four of the 96 cohort 2 participants agreed to wear an accelerometer, but only 70 wore the accelerometer for at least 10 hours per day on at least 4 days. Among these 70 women, median self-reported time spent walking was 24.6 min/day, and median time spent in moderate activity, excluding walking, was 45.0 min/day. In contrast, as measured by the accelerometer, the median time spent in moderate activity (3–<6 METs) was only 15.2 min/day. Also, participants spent essentially no time, on average, in bouts of moderate or vigorous activity that lasted for at least 10 minutes (median 0 min/day). On the IPAQ, participants reported sitting for 420 minutes on weekdays and 300 minutes on weekends.

Table 5.
Self-Reported Physical Activity in the Last 7 Days at Baseline, ORBIT
Table 6.
Self-Reported and Objectively Measured Physical Activity at Baseline in Participants with Valid Accelerometer Records, ORBIT

There were no significant differences between women in the intervention group and women in the control group, except for a difference in percentage of calories from alcohol, which is almost certainly not biologically meaningful (1% vs. 0.5%, p = 0.04). When the analyses were repeated including only the 193 women with no missing data, the results were similar to those shown in Tables 3, ,4,4, and and55.


Obesity is a major cause of morbidity and mortality and is a clear public health concern.55 The high prevalence of obesity among black women places them at increased risk for a number of chronic diseases,12 yet until recently, the experience of black women in weight loss and maintenance trials has been less studied than the experience of white women.12 Most maintenance studies have not reported the ethnic composition of their samples.5658

Lifestyle behaviors, such as dietary and physical activity preferences, are fundamentally linked to individual, familial, cultural, and environmental variables.59 Nonetheless, there is currently no clear consensus as to the basic behavioral mechanisms that underlie individual dietary and physical activity choices.43,60 Therefore, we face a challenge in developing the most salient lifestyle interventions for black women.

In the ORBIT study, 213 obese African American women were randomized either to a 6-month weight loss intervention followed by a 1-year maintenance intervention or to a general health control group. As reported on the Block ’98 FFQ, participants consumed more than the recommended amount of fat and saturated fat and consumed less than the recommended amount of fruits, vegetables, and fiber.61 Dietary factors that appear to affect the accumulation of body fat include foods that are high in energy density and foods that are low in fiber.62 Moreover, data suggest that a high-fiber diet may protect against the development of obesity.63 Women in ORBIT had a baseline HEI score of 53.9, which is lower than the overall score reported for a representative sample of non-Hispanic blacks in the United States (61.1).64 This difference was not unexpected, as obese participants scored significantly lower on the HEI than normal weight participants in a large (n = 10,930) study based on data from the NHANES III.65

Weight reduction can occur only if energy expenditure is elevated above energy intake.66 Overall, studies show that energy expenditure is particularly low among black women,67,68 and NHANES III data suggest that black women have significantly higher odds of physical inactivity than white women.69 In a cross-sectional study of U.S. women aged ≥40, 37.2% of the 745 black participants reported no leisure time physical activity, and only 8.4% reported regular activity, defined as participation in leisure time physical activity  5 times per week and ≥ 30 minutes per session.70 Women in ORBIT reported a median of 85 min/day of MVPA, including walking, on the IPAQ. This level of activity would be higher than the current recommendations of the Institute of Medicine: approximately 60 min/day of moderate-intensity physical activity (e.g., walking/jogging at 4–5 mph).71 By contrast, data from the subgroup of women who wore accelerometers reflected a median of only 15 min/day of MVPA, with no time, on average, spent in bouts of 10 minutes or longer. Jakicic et al.72 observed a similar discrepancy between self-reported exercise and accelometer data in a study of overweight women participating in a behavioral weight loss program. Comparisons between accelerometer data and daily physical activity logs showed that approximately 45% of the women overreported the amount of physical activity they performed.

Research suggests that black women are more tolerant of being overweight and that their social environment is more accepting of larger body sizes.49,73 Considerable evidence shows that normal weight black women are generally more satisfied with their body size than are white women of comparable body weight.49 Among obese black women, however, there is a definite discrepancy between their current and ideal body image.74 This was also the case for ORBIT participants, as would be expected among volunteers for a weight loss program. It is noteworthy that the mean current body image chosen by the women (6.1) does not necessarily reflect their current body size. Also, their choice of an ideal body image is smaller (3.6) than might be expected given the available literature on body image ideals among black women49,74,75 (Fig. 2).

The ORBIT baseline data should be interpreted with the limitations of the study in mind. For example, dietary intake is frequently underreported on self-reported diet measures, and this has been shown to be a particular problem among obese individuals.76,77 This potential limitation may be even more pronounced when obese participants enter a weight loss study, where the desire for weight change is one reason for entering the trial. Studies have shown that obese individuals who underreport their dietary intake are more apt to estimate lower intake of foods that are often considered unhealthful and overreport foods that are considered healthful.7880 Therefore, a social desirability bias in the diet data cannot be ruled out. Given that self-reported dietary intake is prone to error, more precise assessment tools are needed. Currently, however, biological markers that precisely reflect nutritional intake are not available for most nutrients.81 Some data suggest that food diaries are a more precise method of measuring dietary intake than food frequency measures,82,83 but all self-reported measures are vulnerable to underreporting and social desirability bias.

Just as dietary intake is often underreported, physical activity is often overreported when assessed by self-report.72,84 Moreover, there is evidence to support the hypothesis that overweight and obese individuals have a greater tendency than normal weight individuals to overestimate physical activity.85 This study was not designed to compare self-reported and objectively measured physical activity, so participants did not wear the accelerometer during the 7-day period covered by the IPAQ. Nonetheless, the large discrepancy between the two measures of physical activity is striking. We speculate that many of the participants, especially those who had very sedentary office jobs, overestimated the amount of time spent walking or performing other moderate activity over the course of a day. Also, some participants may have ignored the instructions asking them to report only activity that they engaged in for at least 10 minutes at a time. Accurate self-monitoring of physical activity can be difficult, and some people might require training to become proficient.72

We also recognize that individuals volunteer to participate in randomized trials for a variety of reasons, including altruism, curiosity, or interest in the study area. As the study was voluntary and asked for an 18-month commitment, we expect that participants were more highly motivated than average, reducing generalizability. Additionally, in an effort to recruit women who would not be harmed by weight loss but who were not necessarily candidates for or receptive to more aggressive forms of intervention (e.g., gastric bypass), we enrolled participants with a BMI between 30 and 50 kg/m2. Just under half (44%) of our participants had a BMI ≥40 kg/m2 (class III obesity); 30% were in the 30–<35 kg/m2 range (class I obesity) and 27% were in the 35–<40 range (class II obesity). Although approximately 54% of black women in the United States are obese, only about 15% have a BMI  40 kg/m2.2 Finally, although BMI is correlated with percentage of body fat, it does not directly measure body composition. Therefore, at any BMI point, women could vary in their specific amount of body fat.86,87 Future studies should include measures of body composition as well as waist circumference and other physiological changes that occur as a function of weight loss.

The ORBIT baseline data show that it is possible to recruit a group of black women into an 18-month weight loss and weight maintenance trial. It also suggests that this group of obese, middle-aged, and educated women could benefit from reductions in dietary fat and saturated fat and increases in fruit, vegetable, and fiber intake. Our data also highlight the importance of obtaining objective physical activity data as well as self-reported physical activity, given the large discrepancy between these two methodologies. In subsequent papers, we will report on the effect of the intervention on weight loss and weight loss maintenance, as well as on changes in energy intake and energy expenditure.


The ORBIT study is supported by the National Cancer Institute (CA105051).


We thank all the women who gave their time to participate in the study. We also thank our project coordinator and recruitment and intervention staff, whose efforts to effectively recruit participants, conduct the intervention, and retain the women in the study helped advance our knowledge of this understudied population. Finally, we would like to thank Allison Thompson, M.A., Erika Nuber, Guadalupe Compean, and Beth Schneider for their technical assistance.

Disclosure Statement

No competing financial interests exist.


1. Ogden CL. Yanovski SZ. Carroll MD. Flegal KM. The epidemiology of obesity. Gastroenterology. 2007;132:2087. [PubMed]
2. Ogden CL. Carroll MD. Curtin LR. McDowell MA. Tabak CJ. Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295:1549. [PubMed]
3. Calle EE. Thun MJ. Obesity and cancer. Oncogene. 2004;23:6365. [PubMed]
4. NHLBI Obesity Education Initiative Expert Panel. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—The evidence report. Obes Res. 1998;6:51S. [PubMed]
5. Cooper R. Cutler J. Desvigne-Nickens P, et al. Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: Findings of the National Conference on Cardiovascular Disease Prevention. Circulation. 2000;102:3137. [PubMed]
6. Mensah GA. Mokdad AH. Ford ES. Greenlund KJ. Croft JB. State of disparities in cardiovascular health in the United States. Circulation. 2005;111:1233. [PubMed]
7. Singh V. Deedwania P. Dyslipidemia in special populations: Asian Indians, African Americans, and Hispanics. Curr Atheroscler Rep. 2006;8:32. [PubMed]
8. Kittner SJ. White LR. Losonczy KG. Wolf PA. Hebel JR. Black-white differences in stroke incidence in a national sample. The contribution of hypertension and diabetes mellitus. JAMA. 1990;264:1267. [PubMed]
9. Anderson JW. Konz EC. Frederich RC. Wood CL. Long-term weight-loss maintenance: A meta-analysis of U.S. studies. Am J Clin Nutr. 2001;74:579. [PubMed]
10. Douketis JD. Sharma AM. Obesity and cardiovascular disease: Pathogenic mechanisms and potential benefits of weight reduction. Semin Vasc Med. 2005;5:25. [PubMed]
11. Eilat-Adar S. Goldbourt U. Resnick HE. Howard BV. Intentional weight loss, blood lipids and coronary morbidity and mortality. Cur Opin Lipidol. 2005;16:5. [PubMed]
12. Kumanyika S. Obesity, health disparities, and prevention paradigms: Hard questions and hard choices. Prev Chronic Dis. 2005;2:A02. [PMC free article] [PubMed]
13. McTigue KM. Harris R. Hemphill B, et al. Screening and interventions for obesity in adults: Summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2003;139:933. [PubMed]
14. Gardner CD. Kiazand A. Alhassan S, et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight pre-menopausal women: The A to Z Weight Loss Study: A randomized trial. JAMA. 2007;297:969. [PubMed]
15. Kumanyika SK. Obarzanek E. Stevens VJ. Hebert PR. Whelton PK. Weight-loss experience of black and white participants in NHLBI-sponsored clinical trials. Am J Clin Nutr. 1991;53:1631S. [PubMed]
16. Wing RR. Anglin K. Effectiveness of a behavioral weight control program for blacks and whites with NIDDM. Diabetes Care. 1996;19:409. [PubMed]
17. Kumanyika SK. Obesity treatment in minorities. In: Wadden TA, editor; Stunkard AJ, editor. Handbook of obesity treatment. New York: Guilford Press; 2002. p. 416.
18. Wing RR. Hamman RF. Bray GA, et al. Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants. Obes Res. 2004;12:1426. [PMC free article] [PubMed]
19. Kanders BS. Ullmann-Joy P. Foreyt JP, et al. The Black American Lifestyle Intervention (BALI): The design of a weight loss program for working-class African-American women. J Am Diet Assoc. 1994;94:310. [PubMed]
20. McNabb W. Quinn M. Kerver J. Cook S. Karrison T. The Pathways Church-based Weight Loss Program for urban African-American women at risk for diabetes. Diabetes Care. 1997;20:1518. [PubMed]
21. Diabetes Prevention Program (DPP) Research Group. The Diabetes Prevention Program (DPP): Description of lifestyle intervention. Diabetes Care. 2002;25:2165. [PMC free article] [PubMed]
22. Mayer-Davis EJ. D'Antonio AM. Smith SM, et al. Pounds Off With Empowerment (POWER): A clinical trial of weight management strategies for black and white adults with diabetes who live in medically underserved rural communities. Am J Public Health. 2004;94:1736. [PubMed]
23. Davis Martin P. Rhode PC. Dutton GR. Redmann SM. Ryan DH. Brantley PJ. A primary care weight management intervention for low-income African-American women. Obesity. 2006;14:1412. [PubMed]
24. Fitzgibbon ML. Stolley MR. Schiffer L. Sanchez-Johnsen LA. Wells AM. Dyer A. A combined breast health/weight loss intervention for black women. Prev Med. 2005;40:373. [PubMed]
25. Kumanyika SK. Shults J. Fassbender J, et al. Outpatient weight management in African-Americans: The Healthy Eating and Lifestyle Program (HELP) study. Prev Med. 2005;41:488. [PubMed]
26. Barnes A. Goodrick G. Pavlik V. Markesino J. Laws D. Taylor W. Weight loss maintenance in African-American women: Focus group results and questionnaire development. J Gen Intern Med. 2007;22:915. [PMC free article] [PubMed]
27. Walcott-McQuigg JA. Chen SP. Davis K. Stevenson E. Choi A. Wangsrikhun S. Weight loss and weight loss maintenance in African-American women. J Natl Med Assoc. 2002;94:686. [PMC free article] [PubMed]
28. Young DR. Gittelsohn J. Charleston J. Felix-Aaron K. Appel LJ. Motivations for exercise and weight loss among African-American women: Focus group results and their contribution towards program development. Ethn Health. 2001;6:227. [PubMed]
29. Kraemer HC. “Rules” of evidence in assessing the efficacy and effectiveness of treatments. Dev Neuropsychol. 2003;24:705. [PubMed]
30. Nathan PE. Stuart SP. Dolan SL. Research on psychotherapy efficacy and effectiveness: Between Scylla and Charybdis? Psychol Bull. 2000;126:964. [PubMed]
31. Block G. Woods M. Potosky A. Clifford C. Validation of a self-administered diet history questionnaire using multiple diet records. J Clin Epidemiol. 1990;43:1327. [PubMed]
32. Coates RJ. Eley JW. Block G, et al. An evaluation of a food frequency questionnaire for assessing dietary intake of specific carotenoids and vitamin E among low-income black women. Am J Epidemiol. 1991;134:658. [PubMed]
33. Kennedy ET. Ohls J. Carlson S. Fleming K. The Healthy Eating Index: Design and applications. J Am Diet Assoc. 1995;95:1103. [PubMed]
34. U.S. Department of Agriculture. The food guide pyramid. A guide to daily food choice. Home and garden bulletin 252. Washington, DC: USDA Human Nutrition Information Service; 1992.
35. U.S. Department of Agriculture, U.S. Department of Health and Human Services. Home and garden bulletin 232. 4th. Washington, DC: U.S. Government Printing Office; 1995. Nutrition and your health: Dietary guidelines for Americans.
36. Craig CL. Marshall AL. Sjöström M, et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381. [PubMed]
38. Matthew CE. Calibration of accelerometer output for adults. Med Sci Sports Exerc. 2005;37:S512. [PubMed]
39. Freedson PS. Melanson E. Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30:777. [PubMed]
40. Stunkard AJ. Sorensen T. Schulsinger F. Use of the Danish adoption register for the study of obesity and thinness. In: Kety SS, editor; Rowland LP, editor; Sidman RL, editor; Matthysse SW, editor. Genetics of neurological and psychiatric disorders. New York: Raven Press; 1983. p. 115.
41. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ) [Jan 27;2006 ].
42. Stunkard AJ. Current views on obesity. Am J Med. 1996;100:230. [PubMed]
43. Kumanyika SK. Morssink C. Agurs T. Models for dietary and weight change in African-American women: Identifying cultural components. Ethn Dis. 1992;2:166. [PubMed]
44. Braithwaite RL. Lythcott N. Community empowerment as a strategy for health promotion for black and other minority populations. JAMA. 1989;261:282. [PubMed]
45. Nies MA. Vollman M. Cook T. African American women's experiences with physical activity in their daily lives. Public Health Nurs. 1999;16:23. [PubMed]
46. Eyler AA. Baker E. Cromer L. King AC. Brownson RC. Donatelle RJ. Physical activity and minority women: A qualitative study. Health Educ Behav. 1998;25:640. [PubMed]
47. U.S. Department of Health and Human Services. Sisters together: Move more, eat better program guide. Public Health Service, National Institutes of Health; 1999.
48. Sobal J. Social influences on body weight. In: Fairburn CG, editor. Eating disorders and obesity. New York: Guilford Press; 1995. p. 73.
49. Flynn KJ. Fitzgibbon M. Body images and obesity risk among black females: A review of the literature. Ann Behav Med. 1998;20:13. [PubMed]
50. Spring B. Pingitore R. Bruckner E. Penava S. Obesity: Idealized or stigmatized? Sociocultural influences on the meaning and prevalence of obesity. In: Hills A, editor; Wahlquist ML, editor. Fitness and fatness. Great Britain: Smith-Gordon Publishers; 1994. p. 49.
51. Bandura A. Self-efficacy: The exercise of control. New York: W.H. Freeman and Company; 1997.
52. Kumanyika SK. Van Horn L. Bowen D, et al. Maintenance of dietary behavior change. Health Psychol. 2000;19:42. [PubMed]
53. Wing RR. Phelan S. Long-term weight loss maintenance. Am J Clin Nutr. 2005;82:222S. [PubMed]
54. Rollnick S. Mason P. Butler C. Health behavior change: A guide for practitioners. London: Churchill-Livingstone; 1999.
55. Flegal KM. Graubard BI. Williamson DF. Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005;293:1861. [PubMed]
56. Perri MG. Nezu AM. Patti ET. McCann KL. Effect of length of treatment on weight loss. J Consult Clin Psychol. 1989;57:450. [PubMed]
57. Perri MG. The maintenance of treatment effects in the long-term management of obesity. Clin Psychol Sci Pract. 1998;5:526.
58. Bronner Y. Boyington JE. Developing weight loss interventions for African-American women: Elements of successful models. J Natl Med Assoc. 2002;94:224. [PMC free article] [PubMed]
59. Ammerman AS. Lindquist CH. Lohr KN. Hersey J. The efficacy of behavioral interventions to modify dietary fat and fruit and vegetable intake: A review of the evidence. Prev Med. 2002;35:25. [PubMed]
60. Baranowski T. Cullen KW. Nicklas T. Thompson D. Baranowski J. Are current health behavioral change models helpful in guiding prevention of weight gain efforts? Obes Res. 2003;11(Suppl):23S. [PubMed]
62. Key TJ. Schatzkin A. Willett WC. Allen NE. Spencer EA. Travis RC. Diet, nutrition and the prevention of cancer. Public Health Nutr. 2004;7:187. [PubMed]
63. Ludwig DS. Pereira MA. Kroenke CH, et al. Dietary fiber, weight gain, and cardiovascular disease risk factors in young adults. JAMA. 1999;282:1539. [PubMed]
64. Basiotis P. Carlson A. Gerrior S. Juan W. Lino M. The Healthy Eating Index 1999–2000. Washington, DC: U.S. Department of Agriculture; 2002.
65. Guo X. Warden BA. Paeratakul S. Bray GA. Healthy Eating Index and obesity. Eur J Clin Nutr. 2004;58:1580. [PubMed]
66. Hill JO. Wyatt HR. Role of physical activity in preventing and treating obesity. J Appl Physiol. 2005;99:765. [PubMed]
67. James SA. Jamjoum L. Raghunathan TE. Strogatz DS. Furth ED. Khazanie PG. Physical activity and NIDDM in African-Americans. The Pitt County Study. Diabetes Care. 1998;21:555. [PubMed]
68. Carter-Nolan PL. Adams-Campbell LL. Williams J. Recruitment strategies for black women at risk for noninsulin-dependent diabetes mellitus into exercise protocols: A qualitative assessment. J Natl Med Assoc. 1996;88:558. [PMC free article] [PubMed]
69. Winkleby MA. Cubbin C. Changing patterns in health behaviors and risk factors related to chronic diseases, 1990–2000. Am J Health Promot. 2004;19:19. [PubMed]
70. Brownson RC. Eyler AA. King AC. Brown DR. Shyu YL. Sallis JF. Patterns and correlates of physical activity among U.S. women 40 years and older. Am J Public Health. 2000;90:264. [PubMed]
71. Institute of Medicine. Dietary reference intake for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids. 1st. Washington, DC: National Academies Press; 2005. p. 3. [PubMed]
72. Jakicic JM. Polley BA. Wing RR. Accuracy of self-reported exercise and the relationship with weight loss in overweight women. Med Sci Sports Exerc. 1998;30:634. [PubMed]
73. Kumanyika SK. Morssink C. Cultural appropriateness of weight management programs. In: Dalton S, editor. Overweight and weight management, the health professional's guide to understanding and practice. Gaithersburg, MD: Aspen Publishers; 1997. p. 69.
74. Fitzgibbon ML. Blackman LR. Avellone ME. The relationship between body image discrepancy and body mass index across ethnic groups. Obes Res. 2000;8:582. [PubMed]
75. Powell AD. Kahn AS. Racial differences in women's desires to be thin. Int J Eat Disord. 1995;17:191. [PubMed]
76. Johnson RK. Goran MI. Poehlman ET. Correlates of over- and under reporting of energy intake in healthy older men and women. Am J Clin Nutr. 1994;59:1286. [PubMed]
77. Schoeller DA. How accurate is self-reported dietary energy intake? Nutr Rev. 1990;48:373. [PubMed]
78. Mendez MA. Wynter S. Wilks R. Forrester T. Under- and over reporting of energy is related to obesity, lifestyle factors and food group intakes in Jamaican adults. Public Health Nutr. 2004;7:9. [PubMed]
79. Scagliusi FB. Polacow VO. Artioli GG. Benatti FB. Lancha AHJ. Selective underreporting of energy intake in women: Magnitude, determinants, and effect of training. J Am Diet Assoc. 2003;103:1306. [PubMed]
80. Coates RJ. Bowen DJ. Kristal AR, et al. The Women's Health Trial Feasibility Study in Minority Populations: Changes in dietary intakes. Am J Epidemiol. 1999;149:1104. [PubMed]
81. Michels KB. The role of nutrition in cancer development and prevention. Int J Cancer. 2005;114:163. [PubMed]
82. Day N. McKeown N. Wong M. Welch A. Bingham S. Epidemiological assessment of diet: A comparison of a 7-day diary with a food frequency questionnaire using urinary markers of nitrogen, potassium and sodium. Int J Epidemiol. 2001;30:309. [PubMed]
83. Bingham SA. Gill C. Welch A, et al. Validation of dietary assessment methods in the UK arm of EPIC using weighed records, and 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. Int J Epidemiol. 1997;26:S137. [PubMed]
84. Ward DS. Evenson KR. Vaughn A. Rodgers AB. Troiano RP. Accelerometer use in physical activity: Best practices and research recommendations. Med Sci Sports Exerc. 2005;37:S582. [PubMed]
85. Lichtman SW. Pisarska K. Berman ER, et al. Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N Engl J Med. 1992;327:1893. [PubMed]
86. Prentice AM. Jebb SA. Beyond body mass index. Obes Rev. 2001;2:141. [PubMed]
87. Gallagher D. Visser M. Sepulveda D. Pierson RN. Harris T. Heymsfield SB. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol. 1996;143:228. [PubMed]

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