Yaguang Zheng

Faculty

Yaguang Zheng Headshot

Yaguang Zheng

PhD RN

Assistant Professor

1 212 998 5170

433 FIRST AVENUE
NEW YORK, NY 10010
United States

Accepting PhD students

Yaguang Zheng is an Assistant Professor at NYU Rory Meyers College of Nursing. Her research focuses on cardiometabolic risk reduction by leveraging mobile health, electronic health records, and data science techniques. Prof. Zheng has explored behavioral phenotypes through the use of wireless devices in clinical trials and real-world settings and their impacts on cardiometabolic disease prevention and management. Zheng’s initial work focused on lifestyle behavior changes through mobile health, more specifically, using mobile health for self-monitoring and its impact on weight-loss outcomes. After identifying a critical knowledge gap in the area of engagement with mobile health, Zheng conducted a pilot study that found that older adults were able to use multiple mobile devices to improve diabetes self-management, debunking traditional perceptions of older adults as being skeptical of multiple mobile technologies.

Zheng has also applied machine learning algorithms to analyze data from a large real-world sample that has yielded varied patterns of use of wireless devices over the course of a year, findings which are helping to target subgroups of individuals who need long-term engagement in using mobile health devices. More recently, Zheng has worked on electronic health record data, including mobile health data from wearable devices, like continuous glucose monitors, which has real-world application for clinical practice.

Prior to joining the NYU Meyers faculty, Zheng was a postdoctoral scholar supported by NIH grant T32 NR008857 Technology: Research in Chronic and Critical Illness at the University of Pittsburgh School of Nursing.

PhD in Nursing, University of Pittsburgh

Chronic disease
Diabetes
Informatics
Obesity

American Medical Informatics Association
American Heart Association
American Diabetes Association

Post-doctoral trainee, Technology: Research in Chronic and Critical Illness (T32 NR008857) (2020)
New Investigator Travel Award, American Heart Association EPI/NPAM 2014 Scientific Sessions (2014)
Ruth Perkins Kuehn Scholarship, Sigma Theta Tau, Eta Chapter (2014)

Identify unsuitable patients with left main coronary artery disease in intermediate SYNTAX scores treated by percutaneous coronary intervention

Zhang, C., Zheng, Y., Liu, X., Cheng, Y., Liu, Y., Yao, Y., Wang, X., & Xu, J. (2017). (Vols. 20, Issues 6, pp. E258-E262). 10.1532/hsf.1741
Abstract
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

Modern Methods for Modeling Change in Obesity Research in Nursing

Sereika, S. M., Zheng, Y., Hu, L., & Burke, L. E. (2017). (Vols. 39, Issues 8, pp. 1028-1044). 10.1177/0193945917697221
Abstract
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.

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

Burke, L. E., Zheng, Y., Ma, Q., Mancino, J., Loar, I., Music, E., Styn, M., Ewing, L., French, B., Sieworek, D., Smailagic, A., & Sereika, S. M. (2017). (Vols. 6, pp. 278-285). 10.1016/j.pmedr.2017.03.017
Abstract
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.

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

Zheng, Y., Sereika, S. M., Danford, C. A., Imes, C. C., Goode, R. W., Mancino, J., & Burke, L. E. (2017). (Vols. 49, Issues 2, pp. 177-184). 10.1111/jnu.12283
Abstract
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 (

Association between Self-Weighing and Percent Weight Change : Mediation Effects of Adherence to Energy Intake and Expenditure Goals

Zheng, Y., Sereika, S. M., Ewing, L. J., Danford, C. A., Terry, M. A., & Burke, L. E. (2016). (Vols. 116, Issues 4, pp. 660-666). 10.1016/j.jand.2015.10.014
Abstract
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

The Impact of Racial and Socioeconomic Disparities on Binge Eating and Self-Efficacy among Adults in a Behavioral Weight Loss Trial

Goode, R., Ye, L., Zheng, Y., Ma, Q., Sereika, S. M., & Burke, L. E. (2016). (Vols. 41, Issues 3, pp. e60-e67). 10.1093/hsw/hlw032
Abstract
Abstract
The prevalence of obesity is a significant problem among racial and ethnic minorities and those of low socioeconomic status (SES). Psychosocial barriers, such as binge eating and low self-efficacy, are known to hinder the adoption of a more healthful diet. There is limited research identifying racial and SES differences in binge eating and self-efficacy. Further investigations of these constructs may allow researchers to improve the effectiveness of weight management interventions and increase social worker involvement. In this article, the authors examine the socioeconomic and racial differences in binge eating and eating self-efficacy in a sample of individuals seeking weight loss treatment (N = 151). They explore associations between various sociodemographic variables and the Binge Eating Scale and Weight Efficacy Lifestyle Questionnaire (WEL). At baseline, nonwhite participants or those with fewer years of education exhibited more confidence resisting eating when food was available. Moreover, nonwhite participants reported more self-confidence eating under social pressure and had higher total WEL scores than white participants. However, at six months, nonwhite participants' WEL scores decreased. White participants increased their total WEL scores and obtained a higher percent weight change by the end of the intervention. Additional investigations on the dynamics affecting the development of self-efficacy are warranted.

Neighborhood factors and six-month weight change among overweight individuals in a weight loss intervention

Mendez, D. D., Gary-Webb, T. L., Goode, R., Zheng, Y., Imes, C. C., Fabio, A., Duell, J., & Burke, L. E. (2016). (Vols. 4, pp. 569-573). 10.1016/j.pmedr.2016.10.004
Abstract
Abstract
The purpose of this study was to examine the neighborhood environment and the association with weight change among overweight/obese individuals in the first six months of a 12-month weight loss intervention, EMPOWER, from 2011 to 2015. Measures of the neighborhood environment included neighborhood racial composition, neighborhood income, and neighborhood food retail stores density (e.g., grocery stores). Weight was measured at baseline and 6 months and calculated as the percent weight change from baseline to 6 months. The analytic sample (N = 127) was 91% female and 81% white with a mean age of 51 (± 10.4) years. At 6 months, the mean weight loss was 8.0 kg (± 5.7), which was equivalent to 8.8% (± 6%) of baseline weight. Participants living in neighborhoods in which 25–75% of the residents identified as black had the greatest percentage of weight loss compared to those living in neighborhoods with < 25% or > 75% black residents. No other neighborhood measures were associated with weight loss. Future studies testing individual-level behavioral weight loss interventions need to consider the influence of neighborhood factors, and how neighborhood-level interventions could be enhanced with individual-level interventions that address behaviors and lifestyle changes.

Patterns of self-weighing behavior and weight change in a weight loss trial

Zheng, Y., Zheng, Y., Burke, L. E., Danford, C. A., Ewing, L. J., Terry, M. A., & Sereika, S. M. (2016). (Vols. 40, Issues 9, pp. 1392-1396). 10.1038/ijo.2016.68
Abstract
Abstract
Background/Objectives: Regular self-weighing has been associated with weight loss and maintenance in adults enrolled in a behavioral weight loss intervention; however, few studies have examined the patterns of adherence to a self-weighing protocol. The study aims were to (1) identify patterns of self-weighing behavior; and (2) examine adherence to energy intake and step goals and weight change by self-weighing patterns. Subjects/Methods: This was a secondary analysis of self-monitoring and assessment weight data from a 12-month behavioral weight loss intervention study. Each participant was given a scale that was Wi-Fi-enabled and transmitted the date-stamped weight data to a central server. Group-based trajectory modeling was used to identify distinct classes of trajectories based on the number of days participants self-weighed over 51 weeks. Results: The sample (N=148) was 90.5% female, 81.1% non-Hispanic white, with a mean (s.d.) age of 51.3 (10.1) years, had completed an average of 16.4 (2.8) years of education and had mean body mass index of 34.1 (4.6) kg m-2. Three patterns of self-weighing were identified: high/consistent (n=111, 75.0% self-weighed over 6 days per week regularly); moderate/declined (n=24, 16.2% declined from 4-5 to 2 days per week gradually); and minimal/declined (n=13, 8.8% declined from 5-6 to 0 days per week after week 33). The high/consistent group achieved greater weight loss than either the moderate/declined and minimal/declined groups at 6 months (-10.19%±5.78%, -5.45%±4.73% and -2.00%±4.58%) and 12 months (-9.90%±8.16%, -5.62%±6.28% and 0.65%±3.58%), respectively (P

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

Goode, R. W., Ye, L., Sereika, S. M., Zheng, Y., Mattos, M., Acharya, S. D., Ewing, L. J., Danford, C., Hu, L., Imes, C. C., Chasens, E., Osier, N., Mancino, J., & Burke, L. E. (2016). (Vols. 20, pp. 27-33). 10.1016/j.eatbeh.2015.11.009
Abstract
Abstract
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 10years. 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 6months. 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±9.75years. 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 50-79lbs, age, not possessing health insurance, and BES, BDI, and HSS scores. At 6months, the odds of attrition increased by 10% with reduced group session attendance. There was also an interaction between percent weight change and trial (p

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention : A Scientific Statement from the American Heart Association

Burke, L. E., Ma, J., Azar, K. M., Bennett, G. G., Peterson, E. D., Zheng, Y., Riley, W., Stephens, J., Shah, S. H., Suffoletto, B., Turan, T. N., Spring, B., Steinberger, J., & Quinn, C. C. (2015). (Vols. 132, Issues 12, pp. 1157-1213). 10.1161/CIR.0000000000000232
Abstract
Abstract
~