Stanford University
Showing 61-70 of 159 Results
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Esther M. John
Professor (Research) of Epidemiology and Population Health and of Medicine (Oncology)
Current Research and Scholarly InterestsDr. John has extensive expertise in conducting population-based epidemiologic studies and has led as Principal Investigator multiple large-scale studies, including multi-center studies with a study site in the San Francisco Bay Area with its diverse population. Many of her studies and collaborations investigated cancer health disparities. Her research has focused on the role of modifiable lifestyle factors (e.g., body size, physical activity, diet), hormonal factors, early-life exposures, genetic variants, and gene-environment interactions; differences in risk factors by race and ethnicity, breast cancer subtypes, and prostate cancer subtypes; risk factors for familial breast cancer and second primary breast cancer, as well as prognostic factors related to survival disparities.
As Principal Investigator, Dr. John has led a number of studies conducted in the San Francisco Bay Area, including:
- the Northern California site of the Breast Cancer Family Registry, an on-going prospective multi-generational cohort of over 13,000 families established in 1995 at six international sites;
- the San Francisco Bay Area Breast Cancer Study, a population-based case-control study in nearly 5,000 African American, Hispanic, and non-Hispanic White women that investigated the role of modifiable lifestyle factors and other risk factors;
- the California site of the Breast Cancer Health Disparities Study that investigated genetic variability and breast cancer risk and survival in Hispanic and non-Hispanic White populations in the context of genetic admixture;
- the Breast Cancer Etiology in Minorities (BEM) Study, a pooled analysis of risk factors for breast cancer subtypes in minoritized racial and ethnic populations;
- the Northern California site of the WECARE Study that investigates risk factors for second primary contralateral breast cancer;
- the Second Primary Breast Cancer Disparities Study, a pooled analysis of risk factors for contralateral and ipsilateral second primary breast cancer in a diverse population;
- the San Francisco Bay Area Prostate Cancer Study, a population-based case-control study of lifestyle and genetic risk factors for advanced and localized disease.
These studies collected and pooled extensive data and biospecimens and continue to support numerous ancillary studies, collaborations and international consortia and have contributed to a better understanding of cancer risk and survival in minoritized racial and ethnic populations.
Dr. John is a founding PI of the LEGACY Girls Study, a prospective cohort established in 2011 that investigates early life exposures in relation to pubertal development outcomes, breast tissue characteristics, and behavioral and psychosocial outcomes in the context of having a family history or breast cancer.
In 2023, Dr. John joined the Stanford investigator team of the MOSAAIC (The Multiethnic Observational Study in American Asian and Pacific Islander Communities) Study, a five-center study to improve health of American Asian, Native Hawaiian, and Pacific Islander populations. -
Ankita Kaulberg
Director of Innovation & Technology, Epidemiology and Population Health
Current Role at StanfordDirector of Innovation & Technology, HEARTS Lab
Stanford School of Medicine -
Mathew Kiang
Assistant Professor of Epidemiology and Population Health (Epidemiology)
BioI am an assistant professor in the Department of Epidemiology and Population Health. My research lies at the intersection of computational epidemiology and social epidemiology. Methodologically, my work revolves around combining disparate data sources in epidemiologically meaningful ways. For example, I work with individual-level, non-health data (e.g., GPS, accelerometer, and other sensor data from smartphones), traditional health data (e.g., survey, health systems, or death certificate data), and third-party data (e.g., cellphone providers or ad-tech data). To do this, I use a variety of methods such as joint Bayesian spatial models, traditional epidemiologic models, dynamical models, microsimulation, and demographic analysis. Substantively, my work focuses on socioeconomic and racial/ethnic inequities. For example, recently, my work has examined inequities in COVID-19 vaccine distribution, cause-specific excess mortality, and drug poisonings. I have an NIDA-funded R00 examining equitable ways to improve treatment for opioid use disorder across structurally disadvantaged groups and am Co-I on a NIDA-funded R21 examining ways to use novel data sources (such as social media) to predict surges in opioid-related mortality.
