Economic burden of disease by industrial sector & gender: Differences in quality-adjusted life years and associated costs
, Department of Epidemiology & Public Health, University of Miami, Miller School of Medicine, Miami, FL
David Lee, PhD
, Department of Epidemiology & Public Health, University of Miami, Miller School of Medicine - NIOSH Research Group, Miami, FL
Manuel A. Ocasio, MSPH
, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL
William G. LeBlanc, PhD
, Department of Epidemiology & Public Health, University of Miami Miller School of Medicine - NIOSH Research Group, Miami, FL
Lora E. Fleming, MD PhD
, European Centre for Environment and Human Health, University of Exeter Medical School, Truro, United Kingdom
Introduction: The health and well-being of any workforce is shaped by exposures in and out of the workplace as well as predetermined sociodemographic circumstances. It is therefore expected that the burden of disease will vary considerably by industry sector. A comprehensive measure of the burden of disease is quality-adjusted life years (QALYs) a standardized metric comprising both changing mortality and morbidity associated with healthcare interventions, lifestyle choices, job choice, or other characteristics. Objective: Estimate and compare differences in QALYs by gender and across the 8 National Occupational Research Agenda (NORA) industry sectors. Methods: Data from the 1997 2010 National Health Interview Survey (NHIS) were used to estimate QALYs for all workers by NORA sector. Differences in QALYs were calculated and translated into economic values using upper- and lower-bound estimates of societal willingness-to-pay per QALY. Results: Among NORA sectors, Wholesale and Retail Trade workers had the highest average QALYs remaining (36.0 years), while Mining was most disadvantaged with 31.7 QALYs remaining. Significant gender differences were also noted with male workers having an average of 4.34 fewer QALYs remaining than women. These gender- and industry-specific differences in health-adjusted life expectancy represent an average economic loss between $550,217-$1.044 million. Conclusion: Results provide a novel perspective on differences in health and longevity among workers and possibly other subgroups, which is helpful for designing workplace benefits and targeted health promotion efforts.
Occupational health and safety
Public health or related public policy
Public health or related research
Describe worker health in terms of morbidity or mortality and the burden of disease among workers through measures of health-related quality of life (HRQL) such as quality-adjusted life years (QALYs). Discuss a preliminary sense of HRQL disparities among worker groups and gender using estimated QALYs. Explain quality-adjusted life expectancy by sector and gender and quantify, both numerically and in monetary terms, the incremental differences across sectors thus providing a new perspective on health disparities among U.S. workers.
Presenting author's disclosure statement:
Qualified on the content I am responsible for because: I am the Principal Investigator on federally funded grants to conduct economic analyses of public health interventions. Among my scientific interests has been the analysis of costs and benefits of interventions treating women offenders with substance use disorder and estimating health-related quality of life among racial groups and by occupation.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.