Date of Award


Degree Name

Doctor of Public Health (DrPH)



Second Advisor


Third Advisor



The use of potentially hazardous physical, chemical, biological, and radiological agents is inherent to the teaching, research, and services missions of any university. To manage the risks associated with these agents, it is common for universities to host environmental health & safety (EH&S) programs to protect the safety of the institution’s students, faculty, staff, and visitors. However, since EH&S programs in universities are primarily focused on prevention, it is difficult to estimate the appropriate “industry average” in terms of budget and staffing resources a particular university needs for such programs. Historically, the Campus Safety, Health, and Environmental Management Association (CSHEMA) has collected data on a multitude of statistical measures for benchmarking purposes. CSHEMA currently collects data on a subset of likely predictors using the “vital statistics” survey. Cross-validation and information criteria were used to objectively identify which of the collected statistical measures are critical to the prediction of industry average EH&S program resourcing.

The purpose of this project is to pinpoint the variables that explain the majority of variance in the model, thereby minimizing unnecessary resource allocation dedicated to the collection of irrelevant data and illuminating predictors critical to CSHEMA’s “vital statistics” survey. A total of 109 members of the CSHEMA organization participated in this research project. The dependent variables were: (1) environmental health and safety expenditures and (2) environmental health and safety full-time employees; the independent variables were: (1) total institutional net assignable square footage, (2) total institutional expenditures, (3) research net assignable square footage, (4) institutional research expenditures, (5) total number of enrolled students, and (6) total institutional full-time employees. Based on cross-validation and information criteria followed by robust regression methods: M-estimation, LTS-estimation, S-estimation, and MM-estimation, the findings of the present study indicate that institutional research expenditures, institutional research net assignable square footage, and institutional full-time employees are the optimal set of potential predictors for EH&S expenditures. The optimum predictors for EH&S full-time employees are total institutional net assignable square footage, institutional research expenditures, and total institutional full-time employees. The results indicate that these independent predictor variables should be considered critical variables for CSHEMA’s future vital statistics survey.