Population-based prediction equations for neurobehavioral tests

Quantitative assessment of neurobehavioral function appraises brain injury from inhaled chemicals. Contemporary predicted values for tests useful in epidemiological studies have been developed with step-wise linear regression. In instances in which age and education do not match those of control groups, these equations assist in the interpretation of results of examinations of individual subjects and pilot studies. In this study, investigators considered brain function tests to be analogous in concept to pulmonary function tests. The authors used the tests to assess 293 adults in three unexposed groups from different areas of the United States. The subjects, who were contacted at random from voter registration rolls, were compensated for their time. The tests included balance, reaction time, strength, hearing, visual performance and cognitive recall, and perceptual motor and memory functions. Regression equations modeled the performance of each test and the influences of demographic factors. The investigators retained all influential factors in the equations. Age was a significant predictor for most tests. Education attainment was not a factor in any of the physiological measures, but it was a determinant in many psychological tests. Prediction equations assist investigators in the quantitative testing of chemically exposed individuals and other brain-injured individuals. The investigators verified the equations against other groups, including additional unexposed populations.