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The Costs of Obesity in the Workplace
Eric A. Finkelstein, PhD, Marco daCosta DiBonaventura, PhD, Somali M. Burgess, PhD, and Brent C. Hale, RPh
Objective: To quantify per capita and aggregate medical expenditures and
the value of lost productivity, including absenteeism and presenteeism,
because of overweight, and grade I, II, and III obesity among U.S. employ-
ees. Methods: Cross-sectional analysis of the 2006 Medical Expenditure
Panel Survey and the 2008 National Health and Wellness Survey. Results:
Among men, estimates range from ?$322 for overweight to $6087 for
grade III obese men. For women, estimates range from $797 for overweight
to $6694 for grade III. In aggregate, the annual cost attributable to obesity
among full-time employees is $73.1 billion. Individuals with a body mass
index ?35 represent 37% of the obese population but are responsible for
61% of excess costs. Conclusions: Successful efforts to reduce the preva-
lence of obesity, especially among those with a body mass index ?35, could
result in significant savings to employers.
research also reveals the extent to which obesity is responsible for
the high rates of medical expenditures faced by public and private
payers. Thorpe et al1estimate that obesity is responsible for 27% of
the rise in inflation-adjusted health care spending among the work-
ing-age population that occurred between 1987 and 2001. Annual
medical expenditures attributable to obesity may now be as high as
$147 billion per year,2with private insurers paying the medical bill
for roughly half of this total.
On a per capita basis, using data from 2000 to 2001,
Finkelstein et al2showed that overweight- and obesity-attributable
medical expenditures ranged from $170 per employee per year for
overweight (body mass index [BMI] 25.0 to 29.9) male employees
to ?$1500 per employee per year for grade II (BMI 35.0 to 39.9)
obese female employees. Although much of these costs are initially
covered by private insurers, they are ultimately passed along to
employers, and subsequently to employees, in the form of higher
premiums, copayments, and deductibles for medical services.
In addition to per capita medical expenditures, Finkelstein et
al2also reported increasing rates of absenteeism associated with
increasing BMI. The largest difference occurred for grade III (BMI
40?) obese women, who missed almost 1 week more of work per
year than women of normal weight.
There is also growing evidence that obese employees are less
productive while on the job, termed “presenteeism.”3–5A recent
he rising prevalence of obesity and related morbidities in the
United States has been well documented.1A growing body of
analysis of the costs of presenteeism comes from Ricci and Chee.6
They applied the Caremark Work and Health Interview to measure
lost productive time as the sum of self-reported absenteeism and
presenteeism. Their measure of presenteeism is defined as the
average amount of time between arriving at work and starting work
on days when an employee is not feeling well and the average
frequency of engaging in five specific behaviors: losing concentra-
tion, repeating a job, working more slowly than usual, feeling
fatigued at work, and doing nothing at work.
In aggregate, Ricci and Chee6estimate that obese workers
cost U.S. employers an additional $11.7 billion per year compared
with normal weight workers as a result of increased absenteeism
and presenteeism, with presenteeism accounting for roughly two
thirds of this total. Nevertheless, they do not report attributable
costs at the per capita level or present separate estimates by select
obesity strata. These are significant omissions given that many
obesity interventions—ranging from disease management programs
to medical and surgical interventions (eg, bariatric surgery)—target
specific subsets of the obese population. Therefore, it is important
to understand the per capita and total costs generated by each strata.
The goal of this analysis is to extend the Finkelstein et al2and
Ricci and Chee6analyses by presenting per capita and aggregate
estimates of medical expenditures, absenteeism, and presenteeism
separately for overweight and grade I (BMI 30 to 34.9), II (BMI 35 to
39.9), and III obesity. These estimates can then be used to estimate
potential savings resulting from targeted obesity prevention and treat-
ment efforts aimed at specific subsets of the obese population.
Medical Expenditure Sample
To estimate medical expenditures attributable to obesity, we
used the publicly available 2006 Medical Expenditure Panel Survey
(MEPS). MEPS is a nationally representative survey of the civilian
noninstitutionalized population that quantifies an individual’s total
annual medical spending by type of service and source of payment.
This includes all expenditures for office-based visits, hospital out-
patient visits, emergency room visits, hospital inpatient stays, home
health care, dental care, vision aids, other medical equipment and
services (eg, orthopedic items, medical equipment, disposable sup-
plies), and expenditures for prescription medicines.
MEPS also includes BMI of each household member, based
on self-reports, along with other sociodemographic characteristics.
Because of the focus on employees, we limited the sample to
full-time employees aged 18 and older, minus pregnant women and
From the Health Services and Systems Research Program (Dr Finkelstein),
Duke-NUS Graduate Medical School, Singapore; Health Economics and
Outcomes Research (Dr DiBonaventura), KantarHealth, New York, NY; and
Global Health Outcomes Strategy and Research (Dr Burgess, Mr Hale),
Allergan Inc., Irvine, Calif.
represent those of Duke-NUS, KantarHealth, or Allergan, Inc.
Authors Eric Andrew Finkelstein, Eric Marco d DiBonaventura, Somali M
Burgess, Brent C Hale received funding for this research from Allergan Inc.
The JOEM Editorial Board and planners have no financial interest related to this
Address correspondence to: Eric Finkelstein, Health Services and Systems
Research Program, Duke-NUS Graduate Medical School Singapore, 8 Col-
lege Road, Singapore 169857; E-mail: email@example.com.
Copyright © 2010 by American College of Occupational and Environmental
Y Review previous data on how obesity contributes medical
expenditures, absenteeism, and presenteeism.
Y Summarize the new findings on per capita and aggregate
estimates of medical expenditures, absenteeism, and pre-
Y Discuss the cost estimates for different categories of
obesity, including the authors’ suggestion as to which
groups should be targeted for obesity prevention and
JOEM•Volume 52, Number 10, October 2010
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© 2010 American College of Occupational and Environmental Medicine
Finkelstein et alJOEM•Volume 52, Number 10, October 2010