Occupational injury and illness rates are used by
employers and regulatory agencies to monitor the health and
safety of workers. Changes in the rates are interpreted to
reflect actions taken or not taken by the employer. The
purpose of this study was to delineate external factors,
those factors outside the control of employers, which
influence occupational injury and illness rates. The
results of this study are useful in interpreting changes in
the occupational injury and illness rates as a function of
changes in the external factors.
A review of the literature provided information on the
type of external forces which would be expected to influence
occupational injury/illness rates. The factors selected for
the data analysis included economic indicators, regulatory
budget and performance measures, firm size, and leniency in
workers' compensation claim determination as measured by the
proportion of denied claims.
Data were collected on the injury/illness incidence,
lost workday case incidence, and lost workday rates for the
state of Oregon for 1978 through 1987. Multiple linear
regression models were constructed for each of the
injury/illness rates using a step-down variable selection
process to determine the predictor variables for each model.
Separate models were constructed for each dependent variable
using the values of the predictor variables for the same
year and for the preceding year.
The results supported the hypotheses that the
unemployment rate, gross state product, number of serious
violations cited by OSHA, and percentage of claims denied by
the Workers' Compensation Board influence occupational
injury and illness rates. Total OSHA expenditures and the
number of inspections conducted by OSHA in a given year
demonstrated positive relationships with lost workday cases
incidence and injury/illness incidence rates, respectively;
the positive associations were contrary to the hypothesized
relationships. Models can be constructed using data on
external factors to predict injury/illness incidence, lost
workday case incidence, and lost workday rates. The
unemployment rate was the most useful variable in predicting
occupational injury and illness rates. / Graduation date: 1991
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/38145 |
| Date | 29 April 1991 |
| Creators | Farmer, Rainier H. |
| Contributors | Rossignol, Annette M. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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