Juliet Mancino

Changes in Adipose Tissue Depots and Metabolic Markers Following a 1-Year Diet and Exercise Intervention in Overweight and Obese Patients With Type 2 Diabetes

OBJECTIVE We aim to characterize the effects on total body fat and distribution of a 1-year intensive lifestyle intervention (ILI) for weight loss in overweight and obese adults with type 2 diabetes and to examine whether changes in adipose tissue (AT) depots were associated with changes in metabolic biomarkers. RESEARCH DESIGN AND METHODS Participants were 54 females and 38 males (age 57.8 ± 6.7 years [mean ± SD]; BMI 31.7 ± 3.5 kg/m2) enrolled in the Look AHEAD (Action for Health in Diabetes) trial randomized to ILI or diabetes support and education (DSE) from whom baseline and 1-year MRI measures of total AT (TAT) and regional (arm, trunk, leg) AT, including subcutaneous AT (SAT), visceral AT (VAT), and intermuscular AT (IMAT), were acquired. We tested whether mean changes in ILI and DSE were equal and, within groups, whether changes were different from zero. Regression models tested whether changes in AT compartments were associated with metabolic variable changes. RESULTS Body weight changed −0.52 ± 3.62 kg (P = 0.31) in DSE and −7.24 ± 5.40 kg (P < 0.0001) in ILI. Mean ILI changes were different from DSE (P < 0.001 for TAT, SAT, and IMAT and P < 0.01 for VAT in females). Within ILI, SAT and VAT decreased in males and females (P < 0.0001), but IMAT was unchanged (0.00 ± 0.54 kg; P = 0.99). In DSE, SAT and VAT did not change, but IMAT increased by 0.46 ± 0.55 kg (P < 0.001). Controlling for weight loss, reduction of specific AT depots was associated with improvement in metabolic biomarkers. CONCLUSIONS Weight loss of 7–10% from an ILI over 1 year reduced SAT and VAT and prevented an increase in IMAT. Reductions in AT depots were associated with improvements in biomarkers.

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.

The SELF Trial: A self-efficacy based behavioral intervention trial for weight-loss maintenance

The SELF Trial examined the effect of adding individual self‐efficacy (SE) enhancement sessions to standard behavioral weight loss treatment (SBT).

The SMARTER pilot study: Testing feasibility of real-time feedback for dietary self-monitoring

Self-monitoring (SM) of food intake is central to weight loss treatment. Technology makes it possible to reinforce this behavior change strategy by providing real-time feedback (FB) tailored to the diary entry. To test the feasibility of providing 1–4 daily FB messages tailored to dietary recordings via a smartphone, we conducted a 12-week pilot randomized clinical trial in Pittsburgh, PA in US in 2015. We compared 3 groups: SM using the Lose It! smartphone app (Group 1); SM + FB (Group 2); and SM + FB + attending three in-person group sessions (Group 3). The sample (N = 39) was mostly white and female with a mean body mass index of 33.76 kg/m2. Adherence to dietary SM was recorded daily, weight was assessed at baseline and 12 weeks. The mean percentage of days adherent to dietary SM was similar among Groups 1, 2, and 3 (p = 0.66) at 53.50% vs. 55.86% vs. 65.33%, respectively. At 12 weeks, all groups had a significant percent weight loss (p < 0.05), with no differences among groups (− 2.85% vs. − 3.14% vs. − 3.37%) (p = 0.95); 26% of the participants lost ≥ 5% of their baseline weight. Mean retention was 74% with no differences among groups (p = 0.37). All groups adhered to SM at levels comparable to or better than other weight loss studies and lost acceptable amounts of weight, with minimal intervention contact over 12 weeks. These preliminary findings suggest this 3-group approach testing SM alone vs. SM with real-time FB messages alone or supplemented with limited in-person group sessions warrants further testing in a larger, more diverse sample and for a longer intervention period.

Trajectories of Weight Change and Predictors Over 18-Month Weight Loss Treatment

BACKGROUND Obesity research has typically focused on weight change patterns using the whole sample in randomized clinical trials (RCTs), ignoring subsets of individuals with varying weight change trajectories (e.g., continuing to lose, or maintaining weight). The purpose was to explore possible trajectories of weight change and their associated predictors. METHODS We conducted a secondary analysis of data from two RCTs using standard behavioral treatment for weight loss. Group-based trajectory modeling was used to identify distinct classes of percent weight change trajectories over 18 months. RESULTS The sample (N = 338) was primarily female (85.2%), White (73.7 %), 45.7 ± 9.0 years old, with 15.6 ± 2.8 years of education. Three trajectory groups were identified: good responders (>15% weight loss), fair responders (5%-10% weight loss), and poor responders (<5% weight loss). The good responders had a significantly larger decrease in perceived Barriers to Healthy Eating subscale scores than the fair and poor responders (p < .01). Compared to the poor responders, there was a significant decrease in fat gram intake in the good responders (p = .01). CONCLUSIONS Good responders differed from poor responders in decreasing their perceived barriers to healthy eating (e.g., managing emotions, social support, and daily mechanics of adopting a healthy diet) and reducing fat intake. Good responders differed from fair responders in perceived barriers to healthy eating. CLINICAL RELEVANCE Clinicians need to focus on how we can assist those who are being unsuccessful in adopting some of the behaviors observed among those who have experienced successful weight loss and maintainers.

Chapter 9 – Current Theoretical Bases for Nutrition Intervention and Their Uses

Abstract This chapter discusses contemporary theoretical basis for dietary interventions for disease prevention and management and their applications in practice. This chapter (1) introduces key concepts related to the application of theory in understanding and improving diet and eating-related behaviors, (2) reviews behavioral issues related to adopting healthful diets, (3) discusses dietary interventions, and (4) highlights important issues and constructs that cut across theories. Six theoretical models that are in current use and can be particularly useful for understanding the processes of changing eating habits in clinical and community settings are described: social cognitive theory, the stages of change construct from the transtheoretical model, consumer information processing, the theory of planned behavior, multiattribute utility theory, and the social ecological model. The central elements of each theory and how they can be used to guide dietary interventions are described in this chapter.