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The purpose of this study was to compare a technology-based system, an in-person behavioral weight loss intervention, and a combination of both over a 6-month period in overweight adults. Fifty-one subjects (age: 44.2 ± 8.7 years, BMI: 33.7 ± 3.6 kg/m2) participated in a 6-month behavioral weight loss program and were randomized to one of three groups: standard behavioral weight loss (SBWL), SBWL plus technology-based system (SBWL+TECH), or technology-based system only (TECH). All groups reduced caloric intake and progressively increased moderate intensity physical activity. SBWL and SBWL+TECH attended weekly meetings. SBWL+TECH also received a TECH that included an energy monitoring armband and website to monitor energy intake and expenditure. TECH used the technology system and received monthly telephone calls. Body weight and physical activity were assessed at 0 and 6 months. Retention at 6 months was significantly different (P = 0.005) between groups (SBWL: 53%, SBWL+TECH: 100%, and TECH: 77%). Intent-to-treat (ITT) analysis revealed significant weight losses at 6 months in SBWL+TECH (−8.8 ± 5.0 kg, −8.7 ± 4.7%), SBWL (−3.7 ± 5.7 kg, −4.1 ± 6.3%), and TECH (−5.8 ± 6.6 kg, −6.3 ± 7.1%) (P < 0.001). Self-report physical activity increased significantly in SBWL (473.9 ± 800.7 kcal/week), SBWL+TECH (713.9 ± 1,278.8 kcal/week), and TECH (1,066.2 ± 1,371 kcal/week) (P < 0.001), with no differences between groups (P = 0.25). The TECH used in conjunction with monthly telephone calls, produced similar, if not greater weight losses and changes in physical activity than the standard in-person behavioral program at 6 months. The use of this technology may provide an effective short-term clinical alternative to standard in-person behavioral weight loss interventions, with the longer term effects warranting investigation.
The prevalence of overweight and obesity exceeds 65% of adults in the United States (1). These high prevalence rates continue to be a public health concern due to the association with morbidity and mortality of numerous chronic diseases (2–5). Lifestyle interventions that include the combination of reduced energy intake through dietary changes and increased energy expenditure through physical activity promotion have been shown to be effective for reducing body weight by ~10% within a 6-month time period (6). This amount of weight loss has been shown to be significantly associated with improved health outcomes (7–9).
Despite the known effectiveness of lifestyle approaches to reduce body weight, a potential limitation of these interventions is that they have traditionally been delivered within the context of intensive in-person sessions, which typically require weekly attendance by the patient. This may limit the dissemination of these weight loss interventions. Moreover, not all individuals participating in these in-person interventions achieve the commonly reported 10% weight loss (10). Thus, there is a need to develop alternative channels to deliver weight loss interventions effectively and to increase the number of individuals who are able to achieve significant weight loss in interventions that do not include pharmacotherapy or bariatric surgery.
Attempts to use technology to deliver lifestyle behavioral interventions have been shown to result in significant weight loss; however, weight loss has traditionally been less than that observed through in-person interventions (11–14). Recent developments in technology, that include wearable monitors that provide real-time feedback on energy expenditure and physical activity, and enhanced web-based features may improve the effectiveness of technology-based interventions. Polzien et al. (11) have examined the benefits of adding this type of technology to a 12-week in-person weight loss intervention. However, the effectiveness of this technology-based intervention in the absence of in-person sessions has not been examined, and the initial findings of Polzien et al. (11) are in need of replication.
Therefore, the purpose of this study was to evaluate the effectiveness of a technology-based system (TECH) on weight loss when used alone or in combination with a 6-month in-person behavioral weight loss intervention in overweight and obese adults. Body composition, fitness, physical activity, dietary intake, and process measures were also examined as secondary outcomes.
Fifty-one subjects were randomized to participate in this study. Inclusion criteria was as follows: 21–55 years of age, BMI between 25.0 and <40.0 kg/m2, sedentary (exercising <60 min/week), and current access to a computer and the Internet. Subjects were excluded if they were pregnant, taking medications that affected body weight or blood pressure, had a history of chronic disease (diabetes, heart disease, or cancer), had a physical limitation that would prevent exercise, were enrolled in a commercial weight loss program, currently or recently participated in a weight loss study, had lost >5% of current body weight in the past 6 months, were being treated for psychological problems or taking psychotropic medication. Subjects provided written informed consent and obtained physicians consent before study participation. Randomization occurred after eligible subjects completed baseline assessments. All study procedures were approved by the University of Pittsburgh institutional review board.
Eligible subjects participated in a 6-month intervention and were randomized to one of three groups: (i) standard behavioral weight loss (SBWL), (ii) SBWL plus TECH (SBWL+TECH), or (iii) TECH only (TECH).
The 6-month intervention consisted of weekly meetings (three groups and one individual session each month), which focused on behavioral strategies for changing eating and activity behaviors. Subjects were instructed to reduce caloric intake to 1,200–1,800 kcal/day and dietary fat to 20% of total calories. Additionally, subjects were instructed to engage in moderate intensity physical activity, such as brisk walking, that progressed from 100 to 300 min/week. The difference between the energy intake and estimated total energy expenditure was ~500 kcal/day. Self-monitoring of dietary intake, physical activity, and body weight in paper diaries was encouraged and interventionists provided weekly written feedback on these behaviors.
Subjects received the same behavioral intervention content, energy intake goals, and physical activity goals as SBWL. In addition, similar to SBWL, the energy intake and energy expenditure goals were prescribed at a level to elicit an energy deficit of ~500 kcal/day. SBWL+TECH was also provided a technology system (BodyMedia Fit; BodyMedia, Pittsburgh, PA) to use throughout the 6-month intervention. An introductory session instructed participants on the use of the technology system which included an energy monitoring armband, digital display that provided up-to-the-minute feedback on energy expenditure, steps walked, minutes of moderate-to-vigorous intensity physical activity, and personal access to a website to monitor physical activity, dietary intake, and body weight. SBWL+TECH were instructed to wear both the armband and digital display during waking hours, download physical activity data from the armband to the website daily, and to self-monitor dietary intake and body weight using the website. Interventionists accessed individual subjects' websites to set energy expenditure goals, monitor dietary, and physical activity behaviors, and provide weekly written feedback on these behaviors.
TECH received the same program content and behavioral goals for diet, physical activity, and energy deficit as SBWL+TECH, however, instead of attending weekly in-person meetings, behavioral lessons were mailed each week. TECH was provided the use of the technology system and attended an introduction session on the use of the technology system, identical to SBWL+TECH, as well as a 1 h weight loss information session. In addition, subjects in TECH received the same energy expenditure goals as SBWL+TECH. TECH also received one brief scripted telephone call each month from a counselor, who addressed the use of the technology system, current eating and activity behaviors, and strategies to overcome barriers.
Assessments were completed at 0 and 6 months and procedures are described below. Subjects received $50 for completing the 6-month assessment.
Height was measured to the nearest 0.01 cm using a wall-mounted stadiometer (Perspective Enterprises, Portage, MI). Body weight was measured to the nearest 0.1 kg on a Tanita WB-110A electronic scale (Tanita, Arlington Heights, IL) with participants wearing a lightweight hospital gown. BMI was calculated using the height and weight measurements (kg/m2).
Waist and hip circumferences were taken with subjects clothed in a lightweight hospital gown. Waist circumference was measured on the horizontal plane directly over the umbilicus. Hip circumference was measured at the largest part of the hips. Two measures were taken at each site to ensure accuracy; however, if these measures differed by >2.0 cm, a third measurement was taken. The mean value of each site was used.
Percent body fat was assessed using a GE Lunar iDXA dual-energy X-ray absorptiometer (DXA) (GE Healthcare, Madison, WI). Subjects wore a lightweight hospital gown and were asked to remove any jewelry or metal items. All women underwent a urine sample pregnancy test before the scan due to the small levels of radiation that are involved with this procedure. Analysis of the scan was performed by a trained professional.
Cardiorespiratory fitness was assessed during a submaximal exercise test. The speed of the treadmill was constant at 80.4 m/min (3.0 mph) with the grade starting at 0% and increasing by 2.5% every 3 min. Blood pressure, heart rate, and a 12-lead EKG were monitored continuously throughout the test. Termination of the test occurred at 85% of age-predicted maximal heart rate, which was determined by the equation of 220 − age (age-predicted maximal heart rate = 220 − age). Oxygen consumption was assessed by a Viasys Vmax Metabolic Measuring Cart (Viasys, Yorba Linda CA).
Physical activity was assessed with the Paffenbarger Physical Activity Questionnaire (15). This questionnaire was administered via interview by trained personnel and results were reported in kcal/week from physical activity. This questionnaire has been validated and found to be a reliable measure of leisure-time physical activity (16).
Dietary intake was measured using the Block Food Frequency Questionnaire (FFQ) Version 2005, which assesses the usual frequency consumption of specific foods and typical portion sizes over a certain time period. The FFQ obtains information regarding daily energy intake and nutrient intake estimates and has been previously validated (17,18).
Eating behaviors were measured using the Eating Behavior Inventory (EBI) (19), which assesses behaviors that may be related to weight loss such as self-monitoring of food intake and body weight, refusing offers of food and shopping from a list. The EBI consists of 26 items that are rated with a 5-point scale ranging from never or hardly ever to always or almost always. The EBI has been established as a valid tool for measuring changes in weight related behaviors (19,20).
Intervention staff monitored and recorded weekly group and individual session attendance (SBWL and SBWL+TECH), monthly telephone call completion (TECH), daily dietary self-monitoring on either paper food diaries (SBWL) or website (SBWL+TECH and TECH), and armband compliance and time on body (SBWL+TECH and TECH) throughout the 6-month intervention.
Statistical analyses were completed using SPSS Software version 16.0 (SPSS, Chicago, IL). Descriptive statistics were computed for all variables and ANOVA or independent samples t-tests were used to examine any differences between group assignment or completion status. Intention-to-treat (ITT) analysis was conducted carrying the baseline data forward for missing values and included 51 subjects. Analysis using only those who completed baseline and 6-month assessments was conducted for weight loss only. Group differences were examined by 3 × 2 mixed ANOVA (group by time). Post hoc analyses were performed using the Bonferroni adjustment. In cases where data was not normally distributed, a nonparametric test (Kruskal–Wallis) was performed. One-way ANOVA or independent samples t-tests examined differences in process measures between groups among completers. Pearson correlational analyses were performed to examine the relationship between process measures and 6-month weight loss. Statistical significance was defined at P < 0.05.
After attending one of three orientation sessions, a total of 54 individuals provided written consent and completed baseline assessments (Figure 1). Three individuals were excluded from randomization due to a lack of interest in the program and current medication use. Overall, 51 subjects were randomized to SBWL, SBWL+TECH, and TECH with 17 subjects in each group. By 6 months, 12 subjects withdrew from the program for reasons including pregnancy and lack of interest. This resulted in 39 participants (76.5% of eligible subjects) completing baseline and 6-month assessments. Retention rates significantly differed between groups (53% for SBWL, 100% for SBWL+TECH, and 77% for TECH) (P = 0.005) based on χ2 analysis. Baseline characteristics are shown in Table 1. SBWL+TECH weighed significantly more than SBWL (P = 0.02) at baseline and completers had greater hip circumferences than noncompleters (P = 0.01).
Results are presented in Table 2. ITT revealed a significant time effect (P < 0.001) and group × time interaction (P < 0.05) with body weight between baseline and 6 months for SBWL (−3.7 ± 5.7 kg), SBWL+TECH (−8.8 ± 5.0 kg), and TECH (−5.8 ± 6.6 kg). Post hoc analysis revealed a trend for a greater weight loss in SBWL+TECH than SBWL. When baseline body weight was controlled, there were no significant differences observed between groups on percent weight change (P = 0.21). The overall weight loss percentage was −6.4 ± 6.3% with no significant differences between groups (SBWL: −4.1 ± 6.3%; SBWL+TECH: −8.7 ± 4.7%; TECH: −6.3 ± 7.1%) (see Figure 2).
Weight loss among those who completed both baseline and 6-month assessments was significant for SBWL (−7.1 ± 6.2 kg), SBWL+TECH (−8.8 ± 5.0 kg), and TECH (−7.6 ± 6.6 kg) (P < 0.001), however, there were no differences between groups (P = 0.09). When baseline body weight was controlled, there were no differences observed between groups on percent weight change (P = 0.97). The overall weight loss percentage among all conditions was −8.4 ± 5.9% with no differences between groups (SBWL: −7.8 ± 6.9%; SBWL+TECH: −8.7 ± 4.7%; TECH: −8.3 ± 7.1%) (see Figure 2).
ITT indicated significant decreases in waist and hip circumference in SBWL (waist: −4.4 ± 7.1 cm; hip: −4.1 ± 5.8 cm), SBWL+TECH (waist: −8.0 ± 5.7 cm, hip: −6.6 ± 3.9 cm), and TECH (waist: −5.6 ± 7.2 cm; hip: −6.2 ± 6.7 cm) (P < 0.001). Significant reductions in percent body fat were seen at 6 months for SBWL (−1.2 ± 2.5%), SBWL+TECH (−3.3 ± 2.2%), and TECH (−3.1 ± 3.8%) (P < 0.001). There were no differences between groups for percent body fat and waist and hip circumference. Results are shown in Table 2.
Cardiorespiratory fitness significantly improved in SBWL (1.1 ± 2.8 ml/kg/min), SBWL+TECH (2.3 ± 3.2 ml/kg/min), and TECH (1.8 ± 3.2 ml/kg/min) (P < 0.001). Results are shown in Table 2. There was also a significant group effect (P < 0.05), with Bonferroni post hoc analysis revealing trends for a lower improvement in relative VO2 in SBWL compared to SBWL+TECH (P = 0.076) and TECH (P = 0.091). Similarly, significant improvements in the time to reach 85% of age-predicted maximal heart rate at 6 months were observed in SBWL (0.88 ± 1.92 min), SBWL+TECH (1.96 ± 2.07 min), and TECH (2.08 ± 2.42 min) (P < 0.001). Bonferonni post hoc analysis revealed significantly greater improvements in SBWL+TECH compared to SBWL (P = 0.048).
Self-reported physical activity was not normally distributed and therefore a nonparametric (Kruskal–Wallis) test was performed. Significant increases in self-reported physical activity were observed in SBWL (473.9 ± 800.7 kcal/week), SBWL+TECH (713.9 ± 1,278.8 kcal/week), and TECH (1,066.2 ± 1,371 kcal/week) (P < 0.001) (Table 2). There were no differences between treatment groups.
Dietary intake significantly decreased in SBWL (−189.8 ± 751.2 kcal/day), SBWL+TECH (−303.0 ± 248.4 kcal/day), and TECH (−429.5 ± 590.1 kcal/day) (P < 0.001), with no differences between groups (Table 2). Eating behaviors assessed from the EBI significantly improved (P < 0.001) with post hoc analysis revealing greater improvements in weight loss eating behaviors in SBWL+TECH compared to SBWL (P = 0.02).
Process measures among those who completed both the baseline and 6-month assessments are presented in Table 3. Session attendance was 84% among completers, with no differences observed between SBWL (85.7 ± 8.9%) and SBWL+TECH (83.2 ± 14.5%) (P = 0.59). Telephone completion in TECH was 90.1 ± 15.9%. Weight loss at 6 months was not significantly related to attendance (SBWL: r = −0.54, P = 0.13; SBWL+TECH: r = −0.30, P = 0.24) or telephone call completion (TECH: r = 0.10, P = 0.76).
SBWL+TECH (5.9 ± 2.2 days/week) significantly self-monitored dietary intake on more days than SBWL (5.3 ± 2.8 days/week, P < 0.05) or TECH (5.2 ± 2.7 days/week, P < 0.001). Dietary intake self-monitoring was significantly related to weight loss at 6 months when the randomized intervention groups were combined (r = −0.57, P < 0.001) and when analyzed separately for TECH (r = −0.64, P = 0.02).
The armband was worn for an average of 6.4 ± 1.0 days/week, with TECH wearing the armband significantly more hours (17.4 ± 5.9 h/day) than SBWL+TECH (16.2 ± 6.3 h/day) (P = 0.007). Six-month weight loss was not related to armband time on body.
To our knowledge, there have been no previously published studies examining the effectiveness of this TECH (BodyMedia Fit) when used alone or in combination with an in-person behavioral weight loss intervention in overweight and obese adults. The program was successful in producing weight loss in all treatment groups at 6 months and a trend indicated a greater weight loss for those using the technology and attending regular in-person meetings than those in the standard program. Using an earlier version of this technology system, Polzien et al. (11) reported that a combination of the armband technology and face-to-face intervention produced a 2.1 kg greater weight loss at 3 months than the standard program. After 6 months, the present study demonstrated that the combination of technology and face-to-face intervention resulted in weight losses 1.7 and 5.1 kg greater than the standard group based on completers and ITT analyses, respectively. Although the current investigation included a longer, more intensive in-person behavioral program than the previous study, the results are consistent in suggesting that the TECH may produce an additive effect on weight loss, equivalent to ~2 kg, when combined with an in-person behavioral weight loss intervention.
It is interesting that the weight loss in the TECH group was 5.8 kg based on ITT, and 7.6 kg based on objectively measured weight for individuals completing the study. These weight losses were comparable or exceeded the weight loss observed in SBWL based on ITT (3.7 kg) or completer analyses (7.1 kg). Although these results need replication, they may provide some evidence that a technology-based program such as the BodyMedia Fit system, when coupled with a brief monthly intervention telephone call, can result in weight loss that approaches the magnitude of weight loss observed in standard face-to-face weight loss intervention programs for a period of 6 months. However, direct comparison between TECH and SBWL based on this study must be interpreted with caution as the SBWL intervention resulted in less weight loss than is typically observed in these types of interventions within 6 months (6). Moreover, attrition in SBWL was higher than what is typically observed and reported in the literature (6,21,22). While speculative, the lower weight loss observed in SBWL in this study may have been a result of subjects expecting to receive the technology as a component of their intervention due to the eligibility criteria requiring that subjects have access to the internet and be willing to use technology as a component of the intervention. Thus, results of the present study require replication, with future studies closely examining how preference for technology within the context of an intervention affects compliance and retention of participants.
The present study, and in particular, SBWL, resulted in slightly lower retention rates and weight losses after 6 months compared to SBWL programs which generally produce weight losses of ~10% with participant retention near 80% (6). Attrition significantly differed between treatment groups with the highest participant loss detected among the standard group (47%). Despite differences in magnitude and intervention design and length, the trend for the technology to enhance participant retention is consistent with findings by Polzien et al. (11). However, caution should be used when interpreting these results. Due to the poor performance of SBWL, a fair comparison between groups may not be possible. As mentioned previously, we speculate that the high attrition and poor weight loss outcomes in the standard group were a result of not receiving the enhanced program that included the technology system, which may have been preferred by some of the standard group subjects. Future studies should consider assessing group preference at baseline to examine any influence on outcomes.
Regardless of group assignment, significant improvements in cardiorespiratory fitness and reductions in waist and hip circumference, and percent body fat were observed. Furthermore, the current study produced increases in physical activity similar to previous in-person behavioral programs (23) and higher than previous Internet-based programs (12–14) at 6 months. Although not significant, the technology users demonstrated the greatest increases in physical activity, which is similar to the trends observed by Polzien et al. (11). In addition, the lack of differences observed between groups (for weight loss, body composition, and fitness) suggest that the use of the technology system, independent of a face-to-face program but combined with an introductory weight loss session, weekly behavioral mailings, and monthly telephone calls, may have the ability to produce outcomes similar to those seen in standard in-person behavioral weight loss programs.
Across all treatment groups, the intervention produced a reduction in dietary intake from baseline to 6 months which is consistent with previous Internet (12–14), technology-based (11), and in-person behavioral (21,24) programs. Eating behaviors significantly improved at 6 months, with the greatest improvements observed among the combined program. Similarly, those using the technology system and attending in-person sessions self-monitored dietary intake with the greatest frequency. The website used with this technology system included a searchable food database that automatically calculates dietary information such as caloric intake and fat which may make self-monitoring less burdensome than the paper and pencil method. In addition, by regularly self-monitoring dietary intake and uploading energy expenditure information from the armband, individuals using the website could receive feedback on overall calorie balance, which may be beneficial to those trying to lose weight. Polzien et al. (11) did not observe any differences among self-monitoring behaviors between the technology or standard groups. However, more recently, Harvey-Berino et al. (25) observed a trend among an Internet only and Internet plus in-person weight loss group to complete a higher proportion of self-monitoring journals than an in-person program, which suggests that the Internet may facilitate adherence. In the present study, among all groups, higher frequency of self-monitoring dietary intake was significantly related to greater weight losses at 6 months. Consistent with previous reports (6,26), self-monitoring dietary intake is an essential and effective component to weight loss programs, and the technology used in this study may provide an effective technique to traditional diaries to self-monitor key weight loss behaviors.
Participants in the current study were instructed to wear the armband during waking hours and to remove it during any water activities (bathing, showering, and swimming). Throughout the 6-month intervention, the armbands were worn for an average of 16.7 h/day, with a compliance rate between 81–96%. Previous research using the earlier version of the armband indicated the monitor was worn for ~9–10 h/day (11). The present study may have observed higher rates of on-body time due to the smaller and more comfortable design. The high compliance may suggest that the armband energy monitor was widely accepted by participants.
Although there have been no previously published studies reporting the effectiveness of the BodyMedia Fit system, these findings should be interpreted with caution as a result of several limitations. The sample size for this pilot study was relatively small (17 subjects/group), which may have resulted in insufficient Statistical power to detect significant differences between the intervention groups. Poor retention rates and weight loss outcomes in SBWL may limit the ability to make meaningful comparisons between this condition and both TECH and SBWL+TECH. There was low representation of minorities and males, which limits the ability to conduct secondary analyses for ethnic/racial or gender comparisons. Although the present study was longer than the 12 week program reported by Polzien et al. (11), there is limited ability to infer the effectiveness of the technology-based components of the intervention beyond 6 months. The design of this study did not allow us to distinguish which components of the technology-based intervention were the most effective for promoting behavior change and weight loss, and future studies may need to be designed to specifically examine each of these technology components (e.g., armband, food tracking, etc.).
In conclusion, the current investigation was successful in producing weight loss, increasing physical activity, and decreasing dietary intake. Furthermore, the results support the use of a technology-based system, combined with monthly telephone calls to produce weight loss that approaches the magnitude of weight loss and adoption of eating and physical activity behaviors that is typically observed in standard in-person behavioral weight loss interventions. Thus, the commercially available technology used in this study appears to be effective for weight loss, reducing energy intake, and increasing physical activity in the absence of in-person intervention contact. This investigation served as a pilot study, thus, additional studies should be completed to further examine and replicate the results observed on the effects of the use of this technology system, when used alone or combined with an in-person behavioral weight loss intervention. In addition, future studies should examine the use of this system for a longer period of time, to determine whether these findings are sustainable past 6 months. If shown to be effective in future studies, this technology may provide an alternative to in-person lifestyle behavioral intervention for weight loss.
This study was supported by the University of Pittsburgh Obesity and Nutrition Research Center (DK46204). The authors thank the staff and graduate students at the University of Pittsburgh's Physical activity and Weight Management Research Center for their significant contributions to this study.
Disclosure: J.M.J. received a grant from BodyMedia, Inc. (Pittsburgh, Pa) to conduct a nonrelated validation study of the armband technology. J.M.J. was also a consultant to Proctor & Gamble and UPMC Health Plan, and is a scientific advisor to free & Clear. The other authors declared no conflict of interest.