Sally Picciotto is an Associate Researcher with expertise in the proper adjustment for time-varying confounding affected by prior exposure, which she primarily applies to occupational cohort studies and other complex longitudinal analyses. Current research focuses on applying g-methods (for the correct control of time-varying confounders affected by prior exposure) to longitudinal cohort data involving employment-related exposures. Current projects include studies of metalworking fluids and cancer incidence in autoworkers and of diesel exhaust and cardiorespiratory mortality in miners. In these occupational epidemiology analyses, g-methods are the only way to substantially reduce the healthy worker survivor effect. She has recently become interested in other aspects of the complex relationships between work and health, such as whether paid short-term disability leave can prolong employment among people with specific health conditions and whether and how job loss contributes to depressive symptoms among older Americans.
Research Interests
Control for time-varying confounders affected by prior exposure
Other sources of bias in complex longitudinal studies
Effects of occupational exposures on health
Other aspects of work and health
Education
PhD – Mathematics University of California, San Diego, 1999
MA – Mathematics University of California, San Diego, 1995