Student Research: Eric V. Barton, MD
, Occupational and Environmental Medicine (OEM),
An Analysis of the Association Between Obesity and Work Productivity Impairment Among King County Workers
An Analysis of the Association Between Obesity and Work Productivity Impairment
Among King County Workers
Eric V. Barton, MD, Sverre Vedal, MD, MSc, Peggy Hannon, PhD
Objective: This study examines the industry-specific obesity prevalence among King County workers and the association between weight category, based on body mass index (BMI), and work productivity impairment within this population.
Methods: Using data drawn from the HealthLinks Trial baseline survey which included the Work
Productivity and Activity Impairment (WPAI) questionnaire, regression analyses were conducted examining the associations between weight category and work productivity impairment.
Results: The prevalence of overweight and obesity among the study participants was 52.24%, based on a BMI > 25. Among the industries represented, retail trade had the highest prevalence of overweight and obesity at 62.60%. Linear regression modeling demonstrated a statistically-significant association between weight category and work productivity impairment. The adjusted model predicts that an underweight (BMI < 18.5) worker will have an average impairment percentage point increase of 6.22 (p=0.036) compared to a recommended weight worker. An obese (BMI ≥ 30) worker will have an average increase of 2.81 (p = 0.011). There was no statistically-significant change in impairment between overweight (BMI ≥ 25 to < 30) and recommended (BMI ≥ 18.5 to < 25) weight workers. The impairment percentage point increase for underweight and obese workers was attenuated in the adjusted model after controlling for perceived health status.
Conclusions: This study predicts that on average, underweight and obese workers will have higher work productivity impairment than recommended weight workers. Workplace wellness program interventions may wish to target employees in these weight categories to maximize work productivity gains.