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Identifying populations at high risk for occupational back injury with neutral networks.

Authors
Landsittel-DP; Gardner-LI; Arena-VC
Source
Hum Ecol Risk Assess 1998 Dec; 4(6):1337-1352
NIOSHTIC No.
20025317
Abstract
For this study a simulation is conducted to investigate the accuracy of neural networks and logistic regression in identifying populations at high risk for occupational back injury. In contrast to most standard regression techniques, neural networks do not rely on linearity or explicitly specifying the nature of the association. Because the underlying relationships between work exposures, personal risk factors, and injury are often not well defined, neural networks may prove useful for injury risk assessment. Accuracy was assessed by comparing the injury status to the predicted level of risk in each worker. In simulations of a non-linear association, workers (used in the training data) were correctly classified 85% of the time with neural networks, 74% of the time with the main effects logistic model, and 79% of the time with the fully-specified logistic model. Using the test data, however, workers were correctly classified 67% of the time with neural networks, and 71% and 69% of the time with the main effects and fully-specified logistic models, respectively. Simulations of a null association indicated that neural networks may be more likely to overfit random associations. These findings provide a valuable guide concerning statistical methodology for identifying high-risk worker populations.
Keywords
Occupational-health; Back-injuries; Simulation-methods; Musculoskeletal-system-disorders; Risk-factors; Injuries; Worker-health; Work-environment; Risk-analysis; Models; Statistical-analysis
Contact
National Institute for Occupational Safety and Health, 1095 Willowdale Road, M/S P1133, Morgantown, WV 26505
CODEN
HERAFR
Publication Date
19981215
Document Type
Journal Article
Editors
Wassell-JT; Bailer-AJ
Fiscal Year
1999
NTIS Accession No.
NTIS Price
Issue of Publication
6
ISSN
1080-7039
NIOSH Division
DSR; EID
Source Name
Human and Ecological Risk Assessment
State
WV; PA; OH
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