Context Common pain conditions appear to have an adverse effect on work, but no comprehensive estimates exist on the amount of productive time lost in the US workforce due to pain.Objective To measure lost productive time (absence and reduced performance due to common pain conditions) during a 2-week period. Design and SettingCross-sectional study using survey data from the American Productivity Audit (a telephone survey that uses the Work and Health Interview) of working adults between August 1, 2001, and July 30, 2002. Participants Random sample of 28902 working adults in the United States. Main Outcome Measures Lost productive time due to common pain conditions (arthritis, back, headache, and other musculoskeletal) expressed in hours per worker per week and calculated in US dollars.Results Thirteen percent of the total workforce experienced a loss in productive time during a 2-week period due to a common pain condition. Headache was the most common (5.4%) pain condition resulting in lost productive time. It was followed by back pain (3.2%), arthritis pain (2.0%), and other musculoskeletal pain (2.0%). Workers who experienced lost productive time from a pain condition lost a mean (SE) of 4.6 (0.09) h/wk. Workers who had a headache had a mean (SE) loss in productive time of 3.5 (0.1) h/wk. Workers who reported arthritis or back pain had mean (SE) lost productive times of 5.2 (0.25) h/wk. Other common pain conditions resulted in a mean (SE) loss in productive time of 5.5 (0.22) h/wk. Lost productive time from common pain conditions among active workers costs an estimated $61.2 billion per year. The majority (76.6%) of the lost productive time was explained by reduced performance while at work and not work absence. ConclusionsPain is an inordinately common and disabling condition in the US workforce. Most of the pain-related lost productive time occurs while employees are at work and is in the form of reduced performance.

Evidence consistently indicates that common conditions including migraine, 1-8 low back pain, 9,10 diabetes, 1 1 , 1 2 allergic rhinitis, 5 , 1 3 -1 8 gastroesophageal reflux, 19-21 and depression 5,10,22-25 dominate healthrelated lost labor time costs. Among these, depression is among the most costly because it is highly prevalent and comorbid with other conditions. Furthermore, although workers with depression are usually present at work, their performance can be substantially reduced.Model-based estimates indicate that depression costs US employers $24 billion annually in lost productive work time. 23 However, some notable limitations challenge the relevance of this and other estimates. Using a human capital approach, this model makes important assumptions regarding the prevalence of depression in the workforce, the duration of depressive episodes, their imputed impact on productive time at work, and the cost to employers. Furthermore, although stated in 1990 terms, the cost estimate is based on data collected in the early to mid-1980s. The management and treatment of depression has changed substantially since the 1980s; use of pharmaceutical care and, more generally, access to care have increased 26 and may have influenced disability status and how work time is lost.

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The American Productivity Audit (APA) is a telephone survey of a random sample of 28,902 U.S. workers designed to quantify the impact of health conditions on work. Lost productive time (LPT) was measured for personal and family health reasons and expressed in hours and dollars. Health-related LPT cost employers 225.8 billion US dollars/year (1685 US dollars/employee per year); 71% is explained by reduced performance at work. Personal health LPT was 30% higher in females and twice as high in smokers (> or =1 pack/day) versus nonsmokers. Workers in high-demand, low-control jobs had the lowest average LPT/week versus the highest LPT for those in low-demand, high-control jobs. Family health-related work absence accounted for 6% of all health-related LPT. Health-related LPT costs are substantial but largely invisible to employers. Costs vary significantly by worker characteristics, suggesting that intervention needs vary by specific subgroups.