Adjunct Professor of Environmental Health
Dr. Eisen works at the interface between epidemiologic methods and applied public health, bridging the fields of environmental health, statistics and epidemiology. Trained in biostatistics and animated by questions about the occupational and environmental causes of disease, she identifies strategies for overcoming the analytical limitations imposed by conventional approaches to study design and data analysis. By developing new analytical approaches and adapting innovative statistical methods for exposure-response modeling, her research helps to advance the field methodologically, while also advancing new knowledge about the causes of disease.
In her earlier work, Eisen studied the respiratory effects of a variety of occupational exposures, including granite dust containing silica, cotton dust, endotoxin, and metalworking fluids. Her studies of longitudinal decline in pulmonary function among Vermont granite workers exposed to silica identified excess test variability (poor reproducibility) of FEV1 as a biomarker of impaired respiratory health and a source of selection bias in epidemiologic studies. Later, she corroborated this finding in studies of air pollution and workers exposed to asbestos and cotton dust. These findings led to changes in the American Thoracic Society recommendations on Standardization of Spirometry.
Dr. Eisen has published many studies of the health effects of exposure to metalworking fluids in autoworkers. She developed a strategy for reducing selection bias due to the healthy worker survivor effect in a cross-sectional study that clarified the association between exposure to water-based synthetic fluids and asthma. In her ongoing cohort study of cancer in the large UAW-GM cohort of 46,500 workers, and series of nested case-control studies, she has found evidence for causal links between oil based fluids and laryngeal, rectal, and prostate cancer. These studies have contributed substantially to the ongoing controversy about the regulation of this widespread industrial exposure.
She is currently interested in applying nonlinear smoothing techniques, such as penalized splines, to modeling exposure-response curves in the autoworkers and other occupational cohort studies.
MS, 1978, Biostatistics HSPH
ScD, 1982, Biostatistics and Occupational Health