Yaguang Zheng

Abstract

Objective: To examine the bidirectional relationship between weight change and obstructive sleep apnea (OSA) in the context of a behavioral weight loss intervention. Patients and Methods: Adults who were overweight or obese (N=114) participated in a 12-month behavioral weight loss intervention from April 17, 2012, through February 9, 2015. The apnea-hypopnea index (AHI), a marker of the presence and severity of OSA, was assessed at baseline, 6 months, and 12 months. Linear mixed models evaluated the effect of weight change on the AHI and the effect of OSA (AHI ≥5) on subsequent weight loss. Secondary analyses evaluated the effect of OSA on intervention attendance, meeting daily calorie goals, and accelerometer-measured physical activity. Results: At baseline, 51.8% of the sample (n=59) had OSA. Adults who achieved at least 5% weight loss had an AHI reduction that was 2.1±0.9 (adjusted mean ± SE) events/h greater than those with less than 5% weight loss (P<.05). Adults with OSA lost a mean ± SE of 2.2%±0.9% less weight during the subsequent 6-month interval compared with those without OSA (P=.02). Those with OSA were less adherent to daily calorie goals (mean ± SE: 25.2%±3.3% vs 34.8%±3.4% of days; P=.006) and had a smaller increase in daily activity (mean ± SE: 378.3±353.7 vs 1060.1±377.8 steps/d; P<.05) over 12 months than those without OSA. Conclusion: Behaviorally induced weight loss in overweight/obese adults was associated with significant AHI reduction. However, the presence of OSA was associated with blunted weight loss, potentially via reduced adherence to behaviors supporting weight loss. These results suggest that OSA screening before attempting weight loss may be helpful to identify who may benefit from additional behavioral counseling.

Abstract

The purpose of the study was to describe participants’ experience of daily weighing and to explore factors influencing adherence to daily weighing among individuals who were successful in losing weight during a behavioral weight loss intervention. Participants completed a 12-month weight loss intervention study that included daily self-weighing using a Wi-Fi scale. Individuals were eligible to participate regardless of their frequency of self-weighing. The sample (N = 30) was predominantly female (83.3%) and White (83.3%) with a mean age of 52.9 ± 8.0 years and mean body mass index of 33.8 ± 4.7 kg/m2. Five main themes emerged: reasons for daily weighing (e.g., feel motivated, being in control), reasons for not weighing daily (e.g., interruption of routine), factors that facilitated weighing, recommendations for others about daily weighing, and suggestions for future weight loss programs. Our results identified several positive aspects to daily self-weighing, which can be used to promote adherence to this important weight loss strategy.

Abstract

BACKGROUND: The obesity epidemic is a global concern. Standard behavioral treatment including increased physical activity, reduced energy intake, and behavioral change counseling is an effective lifestyle intervention for weight loss.PURPOSE: To identify distinct step count patterns among weight loss intervention participants, examine weight loss differences by trajectory group, and examine baseline factors associated with trajectory group membership.METHODS: Both groups received group-based standard behavioral treatment while the experimental group received up to 30 additional, one-on-one self-efficacy enhancement sessions. Data were analyzed using group-based trajectory modeling, analysis of variance, chi-square tests, and multinomial logistic regression.RESULTS: Participants (N = 120) were mostly female (81.8%) and white (73.6%) with a mean (SD) body mass index of 33.2 (3.8) kg/m 2. Four step count trajectory groups were identified: active (>10,000 steps/day; 11.7%), somewhat active (7500-10,000 steps/day; 28.3%), low active (5000-7500 steps/day; 27.5%), and sedentary (<5000 steps/day; 32.5%). Percent weight loss at 12 months increased incrementally by trajectory group (5.1% [5.7%], 7.8% [6.9%], 8.0% [7.4%], and 13.63% [7.0%], respectively; P = .001). At baseline, lower body mass index and higher perceived health predicted membership in the better performing trajectory groups. CONCLUSIONS: Within a larger group of adults in a weight loss intervention, 4 distinct trajectory groups were identified and group membership was associated with differential weight loss.

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.

Abstract

BACKGROUND: With the follow-up extending to 5 years, the outcomes of SYNTAX (Synergy Between Percutaneous Coronary Intervention with TAXUS and Cardiac Surgery) trial were comparable between coronary artery bypass graft (CABG) and percutaneous coronary intervention (PCI) in left-main (LM) patients with intermediate SYNTAX scores of 23-32. A subdivision depending on SYNTAX score will help to identify unsuitable LM patients with intermediate SYNTAX scores to receive PCI treatment.METHODS: Between January 2011 and June 2013, 104 patients with LM Coronary Artery Disease (CAD) undergoing PCI were selected retrospectively. We compared clinical outcomes in patients with SYNTAX score <27 and ≥27. The follow-up time was 25.23 ± 7.92 months. Kaplan-Meier survival analyses and Cox proportional hazards models were used to compare various outcomes between two groups.RESULTS: Higher rates of repeated revascularization (18.2% versus 4.2%, P = .027) and major adverse cerebro-cardiovascular events (MACCE) (24.2% versus 7.0%, P = .014) were shown in patients with SYNTAX score ≥ 27. After multivariate adjustment, a significant higher risk of repeated revascularization (hazard ratio: 6.25, 95% confidence interval: 1.48 to 26.37, P = .013) and MACCE (hazard ratio: 4.49, 95% confidence interval: 1.41 to 14.35, P = .011) were also found in patients with SYNTAX score ≥ 27.CONCLUSIONS: Based on the higher rate of repeated revascularization and MACCE, patients with LM CAD and intermediate SYNTAX scores will need a subdivision to identity the one not benefit from PCI. CABG is still the standard treatment method for patients of LM CAD with a SYNTAX score of ≥ 27.

Abstract

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

Abstract

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.

Abstract

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.

Abstract

Background: To date, no investigators have examined electronically recorded self-weighing behavior beyond 9 months or the underlying mechanisms of how self-weighing might impact weight change. Objective: Our aims were to examine electronically recorded self-weighing behavior in a weight-loss study and examine the possible mediating effects of adherence to energy intake and energy expenditure (EE) goals on the association between self-weighing and weight change. Design: This was a secondary analysis of the self-efficacy enhancement arm of the Self Efficacy Lifestyle Focus (SELF) trial, an 18-month randomized clinical trial. Participants/setting: The study was conducted at the University of Pittsburgh (2008-2013). Overweight or obese adults with at least one additional cardiovascular risk factor were eligible. Intervention: Participants in the self-efficacy enhancement arm were given a scale (Carematix, Inc) and instructed to weigh themselves at least 3 days per week or every other day. The scale date- and time-stamped each weighing episode, storing up to 100 readings. Main outcome measures: Weight was assessed every 6 months. Adherence to energy intake and EE goals was calculated on a weekly basis using paper diary data. Statistical analyses performed: Linear mixed modeling and mediation analyses were used. Results: The sample (n=55) was 80% female, 69% non-Hispanic white, mean (standard deviation) age was 55.0 (9.6) years and body mass index (calculated as kg/m2) was 33.1 (3.7). Adherence to self-weighing declined over time (P<0.001). From baseline to 6 months, there was a significant mediation effect of adherence to energy intake (P=0.02) and EE goals (P=0.02) on the association between adherence to self-weighing and percent weight change. Mediation effects were not significant during the second and third 6-month periods of the study. Conclusions: Objectively measured adherence to self-weighing declined over 18 months. During the first 6 months, self-weighing directly impacted weight change and indirectly impacted weight change through changes in energy intake and EE.