Brisa N Sanchez, PhD
Brisa N. Sánchez is an Assistant Professor of Biostatistics. She received her Ph.D. in Biostatistics in 2006 from Harvard University. She joined the University of Michigan in 2006 as an Assistant Research Professor, and became an Assistant Professor in 2008. Prior to that she earned a bachelor’s degree in mathematics and a master’s degree in statistics from the University of Texas at El Paso. Three critical events in Dr. Sanchez’s career path were: 1) attending the Mathematical and Theoretical Biology Institute, a summer research experience for undergraduates, 2) participating in the 1999 conference of the Society for the Advancement of Chicanos and Native Americans in Science, a conference primarily geared toward motivating minority undergraduates to pursue careers in science, and 3) being awarded a Howard Hughes Pre-doctoral Fellowship, which funded her PhD studies at Harvard University. The first two events helped her answer a burning question: how can mathematics be used to advance the health of individuals and populations? The third allowed her to pursue the dream of using her quantitative skills toward that goal.
This proposal will develop novel, rigorous methodologies for investigating geographic variation inobesity trends over time and in race/ethnic disparities. Drawing on three scholarly fields (Obesity, Statistics and Geography), these methodologies will help infer possible explanations about which or why population-level policies are efficacious in some, but not other places and monitor progress toward reversing the childhood obesity epidemic by 2015. This project is connected to all priority areas of the Childhood Obesity Team as the methods generated from it will facilitate rigorous measurement of the impact of population-level policies on childhood obesity trends. The funding from New Connections will provide protected time for the PI to develop such methodologies and to make them available for obesity researchers. Additionally, policy-maker friendly evidence regarding geographical clustering of obesity trends and disparities will be provided to diverse audiences at multiple levels of geographical aggregation based on data from the State of California. Because such evidence will be presented in maps at the School-district and State Assembly district levels, there is strong potential to engage key stakeholders and instigate support for obesity prevention policies and programs closest to their locales. In contrast to prior obesity prevalence maps which are updated on a frequent basis, this project develops methodologies to map obesity trends, race/ethnic disparities in prevalence and trends, and systematically test for geographical clustering in trends and difference in clustering by race/ethnicity, offering rigorous analyses that simultaneously consider place and time.
Why I Applied to New Connections
I applied for a prestigious New Connections grant to enhance my ability to confront current professional challenges and fulfill my goal of developing methodologies to address the environmental contributions to childhood obesity and obesity disparities. A New Connections grant will enable me to (1) devote a significant portion of time to conduct research in this area; (2) advance my training to better articulate the necessity of this research, demonstrate its novelty, and ultimately advance childhood obesity research; and (3) position me toward successful promotion. Obtaining a New Connections grant will protect my time to work on biostatistical methods that will enhance our understanding of obesity trends and disparities.
What New Connections Means for my Career
Being part of New Connections means I have the access to and support from a broader network of investigators across the US, who have similar interests and backgrounds. This enhances my professional experience by increasing access to career, professional and personal development opportunities. Coming from a quantitative background, this program enables me to extend my training to substantive research to better understand conceptual models of the roots of childhood obesity and health disparities. Furthermore, it will enhance my ability to communicate to broader audiences such as substantive researchers and policy makers.
My passion is to generate research methodologies with the goal of increasing accuracy in data analysis and overall research quality, that in turn will enable policy makers to make decisions to improve population health. This passion is fueled by my ability to provide improved methodological approaches especially focused on advancing research in environmental epidemiology, social epidemiology, health disparities, and their intersection. My previous and ongoing work proposes the use of latent variables and structural equation models to summarize complex exposure data and research to ensure the correct application of those methodologies. That is, while the capacity to collect data on a multitude of environmental pollutants has increased exponentially in the last several years enabling us to address complex research questions, it also gives rise to a multitude of statistical issues when relating exposure to health outcomes. I am currently applying the methods I developed to examine the role of the chemical environment on childhood obesity thru research in collaboration with the University of Michigan's EPA/NIH Formative Children's Center. I have also conducted research to examine the contribution of the built and social environment to childhood obesity. For example, we examined the proximity of 'junk food stores' to schools, and discussed how environmental planning and commercial zoning regulations around schools may help limit access to less nutritious, calorie dense foods for children. We also showed that limiting access to 'junk foods' that compete with school-provided (healthier) meals at the school-level may reduce childhood obesity. However, to better elucidate the association between these aspects of environment and obesity, it is necessary to better understand the spatial distribution and validity of exposure data, as well as utilize a methodological tools. The goal of the current New Connections grant is to develop such methodologies.
The research goals are to develop novel methodologies to study geographic variation of childhood obesity and obesity disparities. The research targets multiple populations as follows. From an empirical point of view, the proposed research focuses on children in the State of California, the largest, most diverse state in the US. From a policy perspective, the project will develop research products targeted at policy makers at multiple levels of influence to enhance their ability to support policies with user-friendly, yet rigorous research evidence. Finally, from a researcher’s perspective the proposed research targets those conducting childhood and disparities research, by providing methodologies that can be applied in other settings and other populations.
Honors and Awards
Teaching Award, Harvard School of Public Health, 2006
Margaret F. Drolette Award, Harvard School of Public Health, 2006
Howard Hughes Medical Institute Pre-doctoral Fellowship in the Biological Sciences,2001-2006
Model Institutions for Excellence Research Award, University of Texas at El Paso, 2000
Partnership for Excellence in Teacher Education Scholar, U of Texas at El Paso 1997-2000
Outstanding Poster Presentation Award, Joint Mathematics Meetings, 2000
College of Science Banner Bearer, University of Texas at El Paso Commencement, 2000
Outstanding Poster Presentation Award, Society for the Advancement of Chicanos and Native Americans in Science National Conference, 1999
Sánchez BN, Butdz-Jørgensen E, Ryan LM, Hu H (2005), "Structural equation models: a review with applications to environmental epidemiology", Journal of the American Statistical Association, 100: 1443-1455.
Austin SB, Melly SJ, Sánchez BN, Patel A, Buka S, Gortmaker SL (2005), "Clustering of fast food restaurants around schools: a novel application of spatial statistics to the study of food environments",American Journal of Public Health, 95:1575-1581. PMID: 16118369.
Sánchez BN,Ryan LM, Houseman A (2008),"Residual-based diagnostics for latent variable models",Biometrics, 65: 104-115. PMID: 18373712.
Sánchez BN,Raghunathan TE, Diez-Roux AV, Zhu YY (2008), "Combining data from two surveys to assess the effects of neighborhood characteristics on health outcomes", Statistics in Medicine, 27: 5745-5763. PMID: 18693328.
Sánchez BN,Ryan LM, Budtz-Jørgensen E (2009), "An estimating equations approach for latent exposure models with longitudinal outcomes," Annals of Applied Statistics, 3: 830-856.
Morgenstern LB, Escobar J, Sánchez BN, Hughes BA, Zuniga B, Garcia N, Lisabeth LD, (2009) "Fast Food and Neighborhood Stroke Risk", Annals of Neurology,66:165-170. PMID: 19743456.
Sánchez-Vaznaugh E,Sánchez BN, Baek J, Crawford P, (2010) "Competitive food and beverage policies: are they influencing childhood overweight trends?", Health Affairs, 29: 436-446.
Lisabeth LD, Sánchez BN, Escobar J, Hughes R, Meurer WJ, Zuniga B, Garcia N, Morgenstern LB, (2010) "The Food Environment in a Mexican American Community", Health Place, 16(3):598-605.
Sánchez BN, Hu H, Litman H, Tellez-Rojo MM, "Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants ", Environmental Health Perspectives, 119(3), 409-415.
Sánchez BN, Kang S, Mukherjee B, "A Latent variable approach to studies of gene-environment interactions in presence of multiple correlated exposures", Biometrics, in press
Sánchez BN, Sanchez-Vaznaugh EV, Uskila A, Baek J, Zhang L, "Differential impact of food environment nears schools on childhood overweight by race/ethnicity, grade and gender", American Journal of Epidemiology, in press