The Medical Care Costs of Obesity: An Instrumental Variables Approach

Study Questions:

What are the medical care costs of obesity?

Methods:

The investigators used the method of instrumental variables to model estimates of medical care costs related to obesity. One model used data from offspring to examine genetic variation in weight as a natural experiment. Data on costs were from the Medical Expenditure Panel Survey (MEPS) for 2000-2005. The MEPS is a comprehensive, nationally representative survey of the US civilian noninstitutionalized population that has been conducted annually since 1996 and uses an overlapping panel design. Respondents are surveyed about their medical care use and expenditures over the course of 2 years through five interview rounds. Measures of medical spending in the models included total medical expenditures, expenditures by all third party payers (typically public and private insurers), and also expenditures by all payers on specific categories of care: inpatient, outpatient, prescription drugs, and other (which includes dental, vision, home health care services, and medical equipment, but excludes spending on over-the-counter medications). The study sample was limited to adults between the ages of 20 and 64 with biological children between the ages of 11 years (132 months) and 20 years (240 months), and excludes pregnant women. Factors included in the models included gender, race/ethnicity (white, black, Hispanic, other race), respondent age (indicator variables for whether age in years is 20-34, 35-44, 45-54, or 55-64), education level (no high school diploma, high school graduate, some college, bachelor’s degree or higher), census region (northeast, midwest, south, or west), whether the respondent lives in an MSA, household composition (number of household members age 0-5 years, 6-17, 18-64, and 65 or older), whether the survey information was self-reported as opposed to proxy reported, whether the individual was employed, fixed effects for year, the gender of the oldest child, and the age of the oldest child in months.

Results:

The average body mass index (BMI) was 28.17 for men and 27.37 for women. For both the men and women, the prevalence of obesity was 28%. Among men, 79% incurred some medical expenditures in the survey year, and the unconditional average medical expenditures in that year were $1,999 in 2005 dollars. Among women, 88% incurred some medical expenditures, and the unconditional average medical expenditures in that year were $2,617. The impact of obesity on annual medical costs (in 2005 dollars) was estimated to be $2,741 for men and women together. For women, the annual cost was estimated at $3,613, and for men, the cost was $1,152. These averages were driven by individuals with very high BMI and very high medical expenditures. Results for specific subgroups indicate that the impact of obesity on medical costs was higher for the uninsured ($3,153) than for those with private insurance ($2,568), but the difference was not statistically significant. The impact of obesity on third party medical expenditures was significantly higher for women ($3,220) than men ($967, which was not statistically significant). For women, obesity raised predicted medical expenditures by roughly 180%, from $1,928 to $5,363. The largest relative increase in expenditures occurred among the uninsured, for whom obesity raises medical expenditures by 540%, from $512 to $3,271. Estimates indicate that the annual direct medical cost of obesity averaged $26.0 billion over the 6-year period, of which $23.2 billion (89%) was borne by third party payers. In the most recent data, from 2005, the cost of obesity in this population was $28.8 billion, of which $25.7 billion (89%) was borne by third party payers.

Conclusions:

The investigators concluded that medical costs related to obesity are considerably higher than previously thought. These results suggest that 20.6% of US national health expenditures are spent treating obesity-related illness.

Perspective:

The results of this paper are extremely concerning, and suggest that in order to truly control health care costs, efforts at preventing and reducing obesity should be a very high priority for our medical care system and national public health policy.

Keywords: Genetic Variation, Insurance Carriers, Body Weight, Hispanic Americans, Pyrrolidinones, Body Mass Index, Medically Uninsured, Prescription Drugs, Health Expenditures, Obesity, Energy Metabolism, Insurance, Health, Reimbursement


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