title: The relationship between heavy alcohol use and work productivity loss in active duty military personnel: a secondary analysis of the 1995 Department of Defense Worldwide Survey.
abstract: This cross-sectional study examines the association between heavy alcohol use among active duty military personnel and five work productivity loss events that may have an adverse effect on military performance and readiness. Data for light (N = 3,147) and heavy (N = 2,242) drinkers, categorized by gender and pay grade, were obtained from the 1995 Department of Defense Worldwide Survey. Drinking classification was predefined using a standard algorithm that factored quantity and frequency of wine, beer, and liquor consumed. The relative risks of experiencing a productivity loss event at a particular level and 95% confidence intervals were calculated by applying the Mantel-Haenszel method after adjusting for age. The relative risks for increased self-reported lateness, leaving early, low performance, and on-the-job injury were all higher for heavy drinkers than for light drinkers. This association between the heavy-drinking population and four of five work productivity loss events indicates that prevention programs should target all personnel.
authors.affiliation: Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814-1854, USA.
authors.forename: C A
authors.initials: CA
authors.lastname: Fisher
authors.forename: K J
authors.initials: KJ
authors.lastname: Hoffman
authors.forename: J
authors.initials: J
authors.lastname: Austin-Lane
authors.forename: T C
authors.initials: TC
authors.lastname: Kao
mesh_terms: D000041:Absenteeism; D000062:Accidents, Occupational / Q000706:statistics & numerical data; D000328:Adult; D000437:Alcoholism / Q000145:classification / Q000150:complications* / Q000453:epidemiology* / Q000517:prevention & control; D000465:Algorithms; D003430:Cross-Sectional Studies; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D008889:Military Personnel / Q000706:statistics & numerical data*; D020380:Needs Assessment; D012307:Risk Factors; D012456:Salaries and Fringe Benefits / Q000706:statistics & numerical data; D012720:Severity of Illness Index; D017678:Sex Distribution; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology