Weighing in on the Costs of Obesity
 As
the prevalence of obesity increases throughout the world,
more attention must be paid to the economic consequences of
the condition. A wide range of values has been presented as
being “the cost” of obesity in the United States.
Some estimates appearing in the popular press might more reasonably
be called “guesstimates,” as little or no information
supporting the values has been reported. Given the different
cost estimates that have been put forth and the general lack
of consensus in this area, it is hard to know the true economic
burden of obesity. To evaluate cost estimates more accurately,
it is useful to consider the reasons for this uncertainty.
The cost of obesity in the United States hinges on estimates of several key factors, including the prevalence of obesity, the health consequences of obesity, and the proper assignment of costs for these health consequences. None of these factors is well known.
Several issues contribute to this lack of definite values. First, there are several ways in which obesity results in economic burdens. Medical costs and lost work days are the most obvious consequences. Medical costs can be estimated using the medical claims databases of private insurers or government agencies. But even when using these existing databases, estimates of obesity medical care costs vary substantially. This reflects uncertainty in medical care coding.
Some medical encounters may be coded explicitly as obesity-related, but this is not the usual case. Rather, claims databases generally present only the resources used for a particular condition, without indicating the risk factors and patient characteristics associated with that condition. A researcher would, therefore, need to make assumptions about which conditions are the result of obesity, and then determine what proportion of the cost of treatment for each condition is a consequence of obesity.
Researchers have used several approaches with national databases; some have estimated costs in a single year, while others have modeled obesity-related costs over a longer period of time. In calculating the annual cost of obesity, Colditz (1999) considered costs associated with type 2 diabetes, coronary heart disease, hypertension, gall bladder disease, osteoarthritis, and cancer of the breast, endometrium, and colon as potentially attributable to obesity, and assigned a proportion of the costs, ranging from 5 percent of breast cancer costs to 22 percent of gall bladder disease costs, to obesity. In an earlier study, Colditz (1992) excluded osteoarthritis and endometrial cancer entirely.
Thompson and colleagues (1999) estimated the excess costs of
obesity by modeling the higher prevalence of hypertension,
hypercholesterolemia, type 2 diabetes, and coronary heart
disease in the obese population using data from the National
Health and Nutrition Examination Study, and then calculating
the rate of stroke and other cardiac death from the Framingham
Heart Study. The unique contribution
of this study is the two-stage model, which allows the researchers
to consider how certain obesity-related conditions serve as
risk factors for other conditions.
A lack of consistency in the thresholds for overweight and obesity
further complicates the situation. While the World Health
Organization recommendations will guide future research, a
variety of body mass index (BMI) values
have been used to define obesity in previous studies. However,
some literature suggests that waist circumference may be more
highly correlated with health care costs than BMI (Cornier
et al. 2003). There is also uncertainty about the BMI values
derived from national databases, where height and weight tend
to be self-reported and might not be accurate.
Assessments of the costs and benefits of various interventions
for obesity have also been conducted. These include nutritional
and behavioral interventions as well as surgical interventions.
However, some of these studies have used outcome measures
such as cost per kilogram/pound lost (Pritchard et al. 1999;
Martin et al. 1995) or cost per unit of BMI lost (Goldfield
et al. 2001) instead of generally-accepted metrics such as
cost per quality-adjusted life year (e.g., Craig and Tseng
2002; Wang 2003). Because of the diverse measures, it is difficult
to compare across these studies.
There are many other obesity-related costs. For example,
a recent study found that obese women, but not obese men,
in their 50s and 60s tended to have lower median net worth
than their normal to overweight counterparts (Fonda et al.
2004). A number of studies have estimated years of life lost
as a result of obesity (Fontaine et al. 2003; Peeters et al.
2003). Still others have considered whether nursing home placement
is more likely among obese older Americans (Zizza et al. 2002).
Employers are very interested in costs of obesity, not only
in terms of higher insurance premiums, but also in terms of
increased absenteeism and diminished productivity (Thompson
et al. 1998).
There are a number of reasons for the wide range of estimates that exists in the literature. The key to interpreting these studies is careful review of their parameters. Which diseases were included? How was it determined which costs resulted from obesity? How was obesity defined? As the importance of the issue increases, future studies should provide clear information on the definitions, conditions, and cost attributions used for estimating the burden of obesity. Use of consensus values or values from previous studies will allow better comparisons across different evaluations, and greater confidence in cost estimates put forward.
Footnotes
The Framingham Heart Study is the longest-running cardiovascular surveillance in the U.S. More information regarding study design, methods, and a bibliography is available at http://www.nhlbi.nih.gov/about/framingham.
BMI is calculated by dividing a person’s body weight (in kg) by the square of the height in meters. In adults, overweight is defined as a BMI of 25 to 29.9, and obesity is defined as a BMI of 30 or greater.
References
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Colditz GA. Economic costs of obesity. Am J Clin Nutr 1992;55(2 Suppl):503S-507S.
Cornier M-A, Tate CW, Grunwald GK, and Bessesen DH. Relationship between waist circumference, body mass index, and medical care costs. Obes Res 2002;10: 1167-1172.
Craig BM, Tseng DS. Cost-effectiveness of gastric bypass for severe obesity. Am J Med 2002;113(6):491-498.
Fonda SJ, Fultz NH, Jenkins KR, Wheeler LM, Wray LA. Relationship of body mass and net worth for retirement-aged men and women. Research on Aging 2004;26(1):153-176.
Fontaine KR, Redden DT, Wang C, Westfall AO, Allison DB. Years of life lost due to obesity. JAMA 2003;8;289(2):187-93.
Goldfield GS, Epstein LH, Kilanowski CK, Paluch RA, Kogut-Bossler B. Cost-effectiveness of group and mixed family-based treatment for childhood obesity. Int J Obes Relat Metab Disord 2001;25(12):1843-9.
Martin LF, Tan TL, Horn JR, Bixler EO, Kauffman GL, Becker DA, Hunter SM. Comparison of the costs associated with medical and surgical treatment of obesity. Surgery. 1995;118(4):599-606; discussion 606-7.
Peeters A, Barendregt JJ, Willekens F, Mackenbach JP, Al Mamun A, Bonneux L; NEDCOM, the Netherlands Epidemiology and Demography Compression of Morbidity Research Group. Obesity in adulthood and its consequences for life expectancy: a life-table analysis. Ann Intern Med 2003;138(1): 24-32.
Pritchard DA, Hyndman J, Taba F. Nutritional counselling in general practice: a cost effective analysis. J Epidemiol Community Health 1999;53(5):311-316.
Thompson D, Edelsberg J, Colditz GA, Bird AP, Oster G. Lifetime health and economic consequences of obesity. Arch Intern Med 1999;159(18):2177-2183.
Thompson D, Edelsberg J, Kinsey KL, Oster G. Estimated economic costs of obesity to U.S. businesses. Am J Health Promot 1998;13(2):120-127.
Wang F, Schultz AB, Musich S, McDonald T, Hirschland D, Edington DW. The relationship between National Heart, Lung, and Blood Institute Weight Guidelines and concurrent medical costs in a manufacturing population. Am J Health Promot 2003;17(3):183-189.
Zizza CA, Herring A, Stevens J, Popkin BM. Obesity affects nursing-care facility admission among whites but not blacks. Obes Res 2002;10(8):816-23.
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