Sushama D. Acharya

The Effect of Electronic Self-Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial

Technology may improve self‐monitoring adherence and dietary changes in weight loss treatment. Our study aimed to investigate whether using a personal digital assistant (PDA) with dietary and exercise software, with and without a feedback message, compared to using a paper diary/record (PR), results in greater weight loss and improved self‐monitoring adherence. Healthy adults (N = 210) with a mean BMI of 34.01 kg/m2 were randomized to one of three self‐monitoring approaches: PR (n = 72), PDA with self‐monitoring software (n = 68), or PDA with self‐monitoring software and daily feedback messages (PDA+FB, n = 70). All participants received standard behavioral treatment. Self‐monitoring adherence and change in body weight, waist circumference, and diet were assessed at 6 months; retention was 91%. All participants had a significant weight loss (P < 0.01) but weight loss did not differ among groups. A higher proportion of PDA+FB participants (63%) achieved ≥5% weight loss in comparison to the PR group (46%) (P < 0.05) and PDA group (49%) (P = 0.09). Median percent self‐monitoring adherence over the 6 months was higher in the PDA groups (PDA 80%; PDA+FB 90%) than in the PR group (55%) (P < 0.01). Waist circumference decreased more in the PDA groups than the PR group (P = 0.02). Similarly, the PDA groups reduced energy and saturated fat intake more than the PR group (P < 0.05). Self‐monitoring adherence was greater in the PDA groups with the greatest weight change observed in the PDA+FB group.

SMART trial: A randomized clinical trial of self-monitoring in behavioral weight management-design and baseline findings

BACKGROUND The primary form of treatment for obesity today is behavioral therapy. Self-monitoring diet and physical activity plays an important role in interventions targeting behavior and weight change. The SMART weight loss trial examined the impact of replacing the standard paper record used for self-monitoring with a personal digital assistant (PDA). This paper describes the design, methods, intervention, and baseline sample characteristics of the SMART trial. METHODS The SMART trial used a 3-group design to determine the effects of different modes of self-monitoring on short- and long-term weight loss and on adherence to self-monitoring in a 24-month intervention. Participants were randomized to one of three conditions (1) use of a standard paper record (PR); (2) use of a PDA with dietary and physical activity software (PDA); or (3), use of a PDA with the same software plus a customized feedback program (PDA + FB). RESULTS We screened 704 individuals and randomized 210. There were statistically but not clinically significant differences among the three cohorts in age, education, HDL cholesterol, blood glucose and systolic blood pressure. At 24 months, retention rate for the first of three cohorts was 90%. CONCLUSIONS To the best of our knowledge, the SMART trial is the first large study to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper records. This study has the potential to reveal significant details about self-monitoring patterns and whether technology can improve adherence to this vital intervention component.

Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers

Objectives: To describe participants’ adherence to multiple components (attendance, energy intake, fat gram, exercise goals, and self-monitoring eating and exercise behaviors) of a standard behavioral treatment program (SBT) for weight loss and how adherence to these components may influence weight loss and biomarkers (triglycerides, low density lipoproteins [LDL], high density lipoprotein, and insulin) during the intensive and less-intensive intervention phases. Methods: A secondary analysis of a randomized clinical trial consisting of a SBT with either fat-restricted standard or lacto-ovo vegetarian diet. The 12-month intervention was delivered in 33 group sessions. The first six months reflected the intensive phase; the second six months, the less-intensive intervention phase. We conducted the analysis without regard to treatment assignment. Eligible participants included overweight/obese adults (N = 176; mean body mass index = 34.0 kg/m2). The sample was 86.9% female, 70.5% White, and 44.4 ± 8.6 years old. The outcome measures included weight and biomarkers. Results: There was a significant decline in adherence to each treatment component over time (P < 0.0001). In the first six months, adherence to attendance, self-monitoring and the energy goal were significantly associated with greater weight loss (P < 0.05). Adherence to attendance and exercise remained significantly associated with weight loss in the second six months (P < 0.05). Adherence to attendance, self-monitoring and exercise had indirect effects through weight loss on LDL, triglycerides, and insulin (P < 0.05). Conclusions: We observed a decline in adherence to each treatment component as the intervention intensity was reduced. Adherence to multiple treatment components was associated with greater weight loss and improvements in biomarkers. Future research needs to focus on improving and maintaining adherence to all components of the treatment protocol to promote weight loss and maintenance.

The Use of mHealth to Deliver Tailored Messages Reduces Reported Energy and Fat Intake

Background:Evidence supports the role of feedback in reinforcing motivation for behavior change. Feedback that provides reinforcement has the potential to increase dietary self-monitoring and enhance attainment of recommended dietary intake. Objective:The aim of this study was to examine the impact of daily feedback (DFB) messages, delivered remotely, on changes in dietary intake. Methods:This was a secondary analysis of the Self- Monitoring And Recording using Technology (SMART) Trial, a single-center, 24-month randomized clinical trial of behavioral treatment for weight loss. Participants included 210 obese adults (mean body mass index, 34.0 kg/m2) who were randomized to either a paper diary (PD), personal digital assistant (PDA), or PDA plus daily tailored feedback messages (PDA + FB). To determine the role of daily tailored feedback in dietary intake, we compared the self-monitoring with DFB group (DFB group; n = 70) with the self-monitoring without DFB group (no-DFB group, n = 140). All participants received a standard behavioral intervention for weight loss. Self-reported changes in dietary intake were compared between the DFB and no-DFB groups and were measured at baseline and at 6, 12, 18, and 24 months. Linear mixed modeling was used to examine percentage changes in dietary intake from baseline. Results:Compared with the no-DFB group, the DFB group achieved a larger reduction in energy (−22.8% vs −14.0%; P = .02) and saturated fat (−11.3% vs −0.5%; P = .03) intake and a trend toward a greater decrease in total fat intake (−10.4% vs −4.7%; P = .09). There were significant improvements over time in carbohydrate intake and total fat intake for both groups (P values < .05). Conclusion:Daily tailored feedback messages designed to target energy and fat intake and delivered remotely in real time using mobile devices may play an important role in the reduction of energy and fat intake.

Health-related quality of life among participants in the SMART weight loss trial.

Obesity has been associated with a decreased health-related quality of life (HRQoL); however, the association between weight change and HRQoL is unclear. This secondary analysis of the SMART (Self Monitoring And Recording using Technology) trial, a clinical trial of behavioral weight loss treatment, provides evidence that quality of life improves with weight loss.

Socio-demographic, anthropometric, and psychosocial predictors of attrition across behavioral weight-loss trials.

Preventing attrition is a major concern in behavioral weight loss intervention studies. The purpose of this analysis was to identify baseline and six-month predictors associated with participant attrition across three independent clinical trials of behavioral weight loss interventions (PREFER, SELF, and SMART) that were conducted over 10 years. Baseline measures included body mass index, Barriers to Healthy Eating, Beck Depression Inventory-II (BDI), Hunger Satiety Scale (HSS), Binge Eating Scale (BES), Medical Outcome Study Short Form (MOS SF-36 v2) and Weight Efficacy Lifestyle Questionnaire (WEL). We also examined early weight loss and attendance at group sessions during the first 6 months. Attrition was recorded at the end of the trials. Participants included 504 overweight and obese adults seeking weight loss treatment. The sample was 84.92% female and 73.61% white, with a mean (± SD) age of 47.35 ± 9.75 years. After controlling for the specific trial, for every one unit increase in BMI, the odds of attrition increased by 11%. For every year increase in education, the odds of attrition decreased by 10%. Additional predictors of attrition included previous attempts to lose 50-79 lbs, age, not possessing health insurance, and BES, BDI, and HSS scores. At 6 months, the odds of attrition increased by 10% with reduced group session attendance. There was also an interaction between percent weight change and trial (p<.001). Multivariate analysis of the three trials showed education, age, BMI, and BES scores were independently associated with attrition (ps ≤ .01). These findings may inform the development of more robust strategies for reducing attrition.

Weight Loss Is More Important Than the Diet Type in Improving Adiponectin Levels Among Overweight/Obese Adults

Objective: The study objective was to compare the effect of a standard calorie- and fat-restricted diet (STD-D) and a calorie- and fat-restricted lacto-ovo-vegetarian diet (LOV-D) on total and high-molecular-weight (HMW) adiponectin levels after 6 months of behavioral intervention. Design: This study is an ancillary study to a randomized clinical trial. Subjects: Subjects included 143 overweight/obese adults (STD-D = 79; LOV-D = 64). Intervention: Both groups received the same standard behavioral intervention; the only difference was that LOV-D participants were instructed to eliminate meat, poultry, and fish from their diet. Measures: Weight, dietary intake with the 3-day food diary, and total and HMW adiponectin levels were measured. Results: Both groups significantly increased total (STD-D +7.2 ± 17.8%; LOV-D +9.4 ± 21.8%) and HMW adiponectin levels (STD-D +18.5 ± 32.9%; LOV-D +15.8 ± 34.5%; ps < 0.05) with no significant differences between the groups. We found significant associations between weight loss and increases in total (β (SE) = −.071(.27); p = 0.003) and HMW adiponectin (β (SE) = −1.37(.47); p = 0.001) levels independent of the diet type. Weight loss at the higher quartile was associated with improvements of adiponectin levels (p < 0.05). Conclusion: Weight loss was associated with increased total and HMW adiponectin levels regardless of the diet type. Enhancing weight loss may be a means to improve adiponectin levels.

Diet Quality and Use of a Personal Digital Assistant: Transitioning from the Standard Paper Diary to Electronic Diaries

Obesity is a chronic disorder caused by complex interactions among genetic, metabolic, cultural, environmental, and psychosocial factors. The recent 2009–2010 National Health and Nutrition Examination Survey (NHANES) indicated no change in the prevalence rate of obesity among adults from the previous 6 years (2003–2008) with 35.5 % of men and 35.8 % of women being obese (body mass index (BMI) ≥30) [1]. The same survey showed that the prevalence of obesity among children and adolescents was 16.9 % [2] indicating that obesity is still a significant public health problem. Research has demonstrated several health benefits by as little as 5–10 % reduction in excess body weight [3]. Efforts to improve weight loss have focused on standard behavioral treatment (SBT) programs that require lifestyle changes such as adopting healthy eating and exercise habits. A healthy and safe approach to weight loss includes creating a caloric deficit such as a reduction in total caloric intake by 500–1,000 kcal/day, which is expected to result in a weight loss of 1–2 lb per week [4]. Additionally, it is recommended that one engage in a moderate intensity aerobic physical activity program for a minimum of 30 min 5 days per week or vigorous intensity aerobic activity for at least 20 min 3 days per week [5]. The third component of SBT is use of behavior strategies such as goal setting, self-monitoring, and provision of feedback on progress made toward the goals [6]. Despite increasing emphasis on greater dietary intake of vegetables, fruit, and whole grains, intake of these foods is well below the recommended levels [7], and new methods for supporting individuals in making long-term, healthful dietary changes are needed.

Total and high-molecular-weight adiponectin levels in relation to insulin resistance among overweight/obese adults

Objective To determine whether baseline levels or intervention-associated changes in total and high molecular weight (HMW) adiponectin levels were associated with insulin resistance after six months of behavioral treatment for weight loss. Design An ancillary study to a behavioral weight loss trial; the intervention was delivered in group sessions. Methods Participants included 143 overweight/obese adults with a mean BMI of 33.7 kg/m2. The sample was 88% female, 67% white, and 44.2 ± 8.5 years old. Circulating adiponectin levels (total and HMW) and the homeostasis model assessment (HOMA) of insulin resistance were measured and evaluated. Results At baseline, there was significant inverse associations between total adiponectin and HOMA (p < 0.001) and between HMW adiponectin and HOMA (p < 0.001) independent of weight. At 6-mo, there was a 17% improvement in HOMA, 8% increase in total adiponectin, 17% increase in HMW adiponectin levels, and 8.72% weight loss (p’s for all< 0.001). There was also a significant inverse association between changes in total adiponectin and HOMA (p = 0.04) that was independent of baseline weight and weight loss. In contrast, the association between changes in HMW adiponectin and HOMA was attenuated after adjustment for weight loss. Conclusions An increased level of total adiponectin was associated with improved insulin sensitivity, regardless of baseline weight and weight loss. However, baseline total and HMW adiponectin levels were more strongly associated with HOMA than changes in these measures at six months. HMW adiponectin level was not related more closely to insulin resistance than total adiponectin level.