ABSTRACT
OBJECTIVE: To assess how health risk change influences concurrent and subsequent change in absenteeism and presenteeism. METHODS: A retrospective, longitudinal study design analyzed repeated health assessment survey data using maximum likelihood structural equation modeling. RESULTS: A statistically significant relationship was detected between self-reported health risks at one point in time and lower productivity (absenteeism and presenteeism) at the same point in time as well as a longitudinal effect of increasing risks at one point in time associated with decreased productivity at subsequent measurement periods. CONCLUSIONS: Health is a predictor of productivity, and the benefits of improved health on improved productivity are cumulative over time.
Subject(s)
Absenteeism , Efficiency , Health Status , Occupational Health , Presenteeism , Adolescent , Adult , Aged , Female , Health Surveys , Humans , Likelihood Functions , Longitudinal Studies , Male , Middle Aged , Retrospective Studies , Risk Factors , Young AdultABSTRACT
OBJECTIVE: Growing evidence demonstrates a relationship between excess health risk and preventable productivity loss. There is a need to quantify how much lost productivity is avoidable through employer-sponsored health management interventions. This study introduced the Normal Impairment Factor (NIF) to recognize the amount of productivity loss that cannot be mitigated through health management interventions. METHODS: A health assessment questionnaire was administered to 772,750 employees, representing 106 employers within five industry sectors. Researchers used multivariate regression procedures to examine the association between preventable health risks and self-reported productivity loss. RESULTS: Back pain, mental well being, and stress risk were the strongest predictors of on-the-job productivity loss. A strong association was also detected between the number of health risks and productivity loss ranging from 3.4% for those at lowest risk (the NIF group) to 24.0% loss for those at risk for eight risks. CONCLUSIONS: This study demonstrated the utility of the NIF in estimating the level of productivity loss that cannot be regained through health management interventions.