Yaguang Zheng

Abstract

OBJECTIVE: The purpose of this study was to evaluate the psychometric properties of the 22-item Barriers to Healthy Eating (BHE) scale in four independent weight loss studies conducted over 13 years.METHODS: Principal axis factoring with promax rotation was performed to reveal the underlying factor structure. Internal consistency was assessed using Cronbach α, and convergent validity was assessed by correlating the baseline BHE with the Weight Efficacy Lifestyle questionnaire total and subscale scores. Predictive validity was examined by the association of BHE change with weight loss over 6 months.RESULTS: The four studies had similar gender (82.9%-89.9% female) and race (70.5%-81.4% white) distributions. Factor analyses suggested removal of two items and a three-factor structure: self-control and motivation (10 items), daily mechanics (7 items), and social support (3 items). The Cronbach α for the 20-item BHE ranged from 0.849 to 0.881 across the four studies. The BHE and Weight Efficacy Lifestyle questionnaire total and subscale scores were all negatively correlated with each other, showing good convergent validity (r = 0.120-0.544, P < 0.05). BHE change was associated with weight loss from 0 to 6 months (r = 0.282-0.450, P < 0.05).CONCLUSIONS: The BHE scale showed very good psychometric properties over time, supporting its use in measuring barriers to one's ability to adopt or maintain a healthy eating plan.

Abstract

Self-weighing may promote attainment and maintenance of healthy weight; however, the natural temporal patterns and factors associated with self-weighing behavior are unclear. The aims of this secondary analysis were to (1) identify distinct temporal patterns of self-weighing behaviors; (2) explore factors associated with temporal self-weighing patterns; and (3) examine differences in percent weight changes by patterns of self-weighing over time. We analyzed electronically collected self-weighing data from the Health eHeart Study, an ongoing longitudinal research study coordinated by the University of California, San Francisco. We selected participants with at least 12 months of data since the day of first use of a WiFi- or Bluetooth-enabled digital scale. The sample (N = 1041) was predominantly male (77.5%) and White (89.9%), with a mean age of 46.5 ± 12.3 years and a mean BMI of 28.3 ± 5.9 kg/m2 at entry. Using group-based trajectory modeling, six distinct temporal patterns of self-weighing were identified: non-users (n = 120, 11.5%), weekly users (n = 189, 18.2%), rapid decliners (n = 109, 10.5%), increasing users (n = 160, 15.4%), slow decliners (n = 182, 17.5%), and persistent daily users (n = 281, 27.0%). Individuals who were older, female, or self-weighed 6–7 days/week at week 1 were more likely to follow the self-weighing pattern of persistent daily users. Predicted self-weighing trajectory group membership was significantly associated with weight change over time (p <.001). In conclusion, we identified six distinct patterns of self-weighing behavior over the 12-month period. Persistent daily users lost more weight compared with groups with less frequent patterns of scale use.

Abstract

Objective: examine the efficacy and safety of Shenmai to the cardiac rehabilitation in patients received coronary artery bypass grafting. Design: a single-center randomized, single blind clinical trial. Setting: Department of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China. Subjects: Patients with coronary artery disease who received coronary artery bypass grafting in our center were studied. They must be competent to complete the 6-minute walking test without any assistance and without any severe comorbidity. Interventions: in Shemmai group, the participants were treated with Shenmai injection (100 ml/day) right after the surgery to discharge for 9.28 ± 3.75 days and then capsule (3.6 g/day) sequentially for 30 days in addition to the cardiac rehabilitation. In control group, only cardiac rehabilitation was conducted. Main measures: the 6-Minute Walking Test was measured at three time points: one day before operation, on the day of discharge and 30 days follow up. Results: The sample (n = 166) was predominately male (84%), with mean age was 61.12 ± 9.13 years. There was no significant difference between groups in baseline characteristics and the procedural characteristics. There was one death in control group and one stroke in Shenmai group right after the surgery. Overall, there was group (p =.005) and time effect (p <.001) on the 6-minute walking distance. Participants in the Shenmai group walked longer distance in meters compared with control group on the day of discharge (314.54 ± 64.14 vs. 271.29 ± 76.82, P <.001), while no significant differences before operation (399.72 ± 93.19 vs. 403.67 ± 91.99, p =.78) and on 30-day follow up (436.54 ± 67.64 vs. 421.64 ± 83.53, p =.21). Conclusion: Shenmai improves the exercise tolerance in the early stage of the cardiac rehabilitation for patients received coronary artery bypass grafting.

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.