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Milken Institute School of Public Health

 

Yan Wang

Yan Wang

Yan Wang

Associate Professor

School: Milken Institute School of Public Health

Department: Prevention and Community Health

Contact:

Email: Yan Wang
Yan Wang CV
Milken Institute School of Public Health 950 New Hampshire Avenue, NW Washington DC 20052

Yan Wang, MD, DrPH, is an associate professor at the Department of Prevention and Community Health at the George Washington University (GWU) Milken Institute School of Public Health. She joined GWU from University of Maryland at Baltimore (UMB), School of Medicine in 2020, where she had been an associate professor in the Department of Pediatrics. 

Dr. Wang's research has two main focuses. One is on epidemiology and prevention intervention on risky health behaviors and health problems, including substance use, especially tobacco smoking, obesity, risky sexual behaviors, unintentional injuries, mental health disorders, and medical problems, e.g. HIV infection. The other focus is on the application of statistical methodology and causal inference in public health research. She has conducted multilevel modeling, Generalized Estimation Equation (GEE) modeling, survival analyses, and structural equation modeling (e.g. mediation analysis, cross-lagged panel model, exploratory and confirmatory factor analyses, latent class analysis, latent growth modeling, and dyadic analyses). She is also specialized in causal inference, e.g. the evaluation of intervention effect in Randomized Controlled Trial (RCT), cluster RCT, and quasi-experimental designs, including propensity score analysis (PSA), complier average causal effect (CACE), interrupted time series (ITS) design and difference in difference (DID) analyses. She has also conducted research on health disparities. She has published over 110 peer-reviewed articles on health behaviors/problems. She was a PI for two NIH R03 grants and has been a site-PI or a co-I for numerous NIH R01 or equivalent grants. 

Behavioral Health

Biostatistics

Children's Health

Chronic Disease

Community Health

Epidemiology

Health Disparities

Mental Health

Obesity

Prevention

Program Evaluation

Underserved Populations

Women's Health

Doctor of Public Health, Morgan State University, 2007

  • Instructor: The Application of Structural Equational Modeling (SEM) to Public Health Research

  • Co-instructor: Study Design and Evaluation Methods (PUBH 8416)

  • Instructor: Research Leadership (PUBH 8413)

  • Instructor: Independent Study (PUBH 8010)

Dr. Wang's research work has been concentrated on epidemiology and prevention intervention of risky health behaviors/problems, including tobacco smoking, risky health behaviors, overweight/obesity, HIV infection, unintentional injuries, and the prevention intervention. She has assessed the factors and consequences of these risky health behaviors/problems. She has also participated in the design and implementation of over 15 prevention intervention trials to prevent the risk behaviors. Her other focus is on the applied statistical methodology and causal inference. She is familiar with multi-level modeling, survival analysis, dyadic analysis, structural equation modeling including mediation analyses, factor analyses, latent class analyses, and other longitudinal structural equation modeling methods. She is also familiar with propensity score analysis (PSA), Complier Average Causal Effect (CACE) model, Difference in Difference (DID) analysis, and  interrupted time series (ITS) analyses. 

Selected out of >110 publications

  1. Wang, Y., Romm, K.F., Edberg, M., *LoParco, C.R., *Cui, Y., Bingenheimer, J., & Berg, C.J. (in press). Two-part models identifying predictors of cigarette, e-cigarette, and cannabis use and change in use over time among young adults in the US. American Journal on Addictions. doi: 10.1111/ajad.13569.
  2. Wang, Y., *LoParco, C.R., *Cui, Y., *Duan, Z., Levine, H., Bar-Zeev, Y., Abroms, L.C., *Khayat, A., & Berg, C.J. (2023a). Profiles of tobacco product use and related consumer characteristics in the US and Israel: A multiple-group latent class analysis. Global Public Health. 18(1):2267652. doi: 10.1080/17441692.2023.2267652
  3. Wang, Y.,  Karver, T., Berg, C., Barrington, C.,  Donastorg, Y.,  Perez,  M., Gomez, H.,  Davis, W,   Galai , N, Kerrigan, D. (2023b) Substance use and depression impede ART adherence among female sex workers living with HIV in the Dominican Republic. AIDS and Behavior. 27(7):2079-2088. DOI: 10.1007/s10461-022-03940-x. PMID: 36477652.
  4. Wang, Y., Bidell, M., Schabath, M., Pratt-Chapman, M.L. (2023c). The Queering Individual Relational and Knowledge Scales (QUIRKS): Validation of Companion Measures Assessing Lesbian, Gay, Bisesxual, Transgender, Queer, and Intersex Affirming Health Care. Journal of Oncology Navigation and Survivorship. 2023;14:71-80.
  5. Wang, Y., Duan, Z., Romm, K.F., Ma, Y., Evans, W.D., Bennett, B., Klinkhammer, K.E., Wysota, C.N., & Berg, C.J. (2022a). Bidirectional associations between depressive symptoms and cigarette, e-cigarette, cannabis, and alcohol use: Cross-lagged panel analyses among young adults before and during COVID-19. Addictive Behaviors.134: 107422.
  6. Wang Y., Zhu E, Hager ER, Black MM (2022b) Maternal depressive symptoms, attendance of sessions and reduction of home safety problems in a randomized toddler safety promotion intervention trial: A latent class analysis. PLoS ONE 17(1): e0261934.
A complete list of publications can be found at the following link: