Alcohol consumption and incidence of workers' compensation claims: a 5-year prospective study of urban transit operators.
BACKGROUND
Numerous studies have linked alcohol impairment on the job to occupational injury. Few studies have looked at the association of nonwork drinking and occupational injury.


METHODS
This study examines first workers' compensation claims after a baseline assessment of alcohol consumption and other occupational variables in 1836 transit operators participating in a medical examination for driver's license renewal. A proportional hazard model was used for the analysis.


RESULTS
Individuals with higher alcohol consumption were more likely to be male, have more years of driving, and have a higher job-stress score. When these variables were controlled for, individuals with higher alcohol consumption were more likely to have a workers' compensation claim over the follow-up period. Individuals reporting a consumption of 10 to 14 drinks per week had a hazard of 1.30 (p = 0.03), and those reporting 15 or more drinks per week had a hazard of 1.27 (p = 0.05) compared with individuals reporting no drinks consumed per week.


CONCLUSIONS
This study indicates that drinking off the job is associated with workers' compensation injury claims. Because it is presumed that most drinking was done outside work, due to high public scrutiny of city transit operators, these results suggest that experience in life outside of work may influence work outcomes. Research should be conducted to identify the mechanisms (e.g., drinking before work, hangover, fatigue) of such effects.
D000328:Adult; D000368:Aged; D000428:Alcohol Drinking / Q000191:economics* / Q000453:epidemiology*; D016001:Confidence Intervals; D003430:Cross-Sectional Studies; D005260:Female; D006306:Health Surveys; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009790:Occupations / Q000706:statistics & numerical data / Q000639:trends; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012307:Risk Factors; D012495:San Francisco / Q000453:epidemiology; D014504:Urban Health / Q000706:statistics & numerical data / Q000639:trends; D014942:Workers' Compensation / Q000191:economics / Q000706:statistics & numerical data / Q000639:trends