Economic Outcomes of the Obese Patient

Abstract

Obesity is a well-established risk factor for many major chronic diseases such as coronary heart disease, hypertension, type 2 diabetes, cerebrovascular disease, and osteoarthritis. It has also been associated as a risk factor for certain types of cancer (1, 2, 3, 4, 5). It stands to reason then that obesity has a sizeable economic burden on the health-care system. This report discusses the literature on the economic impact of obesity, bringing to light the economic outcomes that are primarily impacted by obesity. Also, this report proposes a set of economic outcomes that could be measured in clinical practice or future research studies so that there will be continued assessment of the economic impact of obesity. Economic outcomes are the measures to assess the economic burden that disease places on the nation. They were classically categorized into two components: 1) direct medical outcomes and 2) indirect morbidity and mortality outcomes. Direct medical outcomes, now referred to as “medical-care outcomes,” are the measures of preventive, diagnosis, and treatment services used in the intervention or treatment regimen (e.g., hospital care, physicians services, and medications). Indirect outcomes refer to productivity changes related to illness and death. Morbidity outcomes are days of work lost by people because of illness, restricted activity, and disability. Mortality outcomes are premature death due to disease, and a mortality cost would be the value of future earnings lost by people who die prematurely. Because the definition indirect outcomes varies substantially by the purpose of the analysis, this report refers only to lost-productivity indirect outcomes. This report and proposal focuses on medical care and lost-productivity outcomes and costs (Table 1) because they are more relevant for shorter-length studies (<5 years) and more relevant to manage care organizations and employers—the primary decision makers and payers of health care in the United States. To date, there have been many published reports of studies and models illustrating the association between obesity and medical-care cost and use (6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16). However, there are fewer studies that evaluate the impact of weight loss on medical-care costs. Overall, these studies tend to be short-term, small, or uncontrolled; hence, caution is warranted when interpreting their results. In addition, most of the weight-loss studies measured only one aspect of medical-care cost (e.g., medication changes) (17, 18, 19, 20, 21, 22, 23). Although the evidence of the impact of weight loss on medical-care use and cost is mounting, the evidence of the relationship between obesity and medical-care use and cost has been consistent and generally dose-responsive [i.e., as body mass index (BMI) increases, health-care use increases]. Overall, obesity (BMI ≥30 kg/m2) is associated with greater health-care use and cost, particularly pharmaceutical and laboratory costs. There is no difference in use and costs among obese people by age. Gender differences were explored in one study (6), and obese women contributed 67% of the excess physician visits even though they comprised 51% of the population. In general, women do use more health care than men regardless of their weight (15). Another study that evaluated health-care claims and costs in an employer setting (n = 843) reported that employees with “at-risk” BMIs (defined as ≥27.8 kg/m2 for men and 27.3 kg/m2 for women) had, on average, health-care costs that were $2326 greater over a 3-year period than employees with a lower BMI, supporting evidence that obesity is associated with increased health-care use (24). The association between obesity and medical-care costs in this study was found to be greater in obese women and older obese (≥45 years) employees. In addition, Pronk et al. (15), evaluated health-care use and costs among 5689 managed-care members and found that for every one-unit increase in BMI, there was a 1.9% increase in median costs. Although this does not translate into large cost increases at the individual level ($11.26 per unit increase in BMI per year), the cost does become considerable at the population level. The dominant diagnoses increasing medical-care costs among the obese population are coronary heart disease, type 2 diabetes, hypertension and osteoarthritis (6, 8), suggesting that these comorbidities be preferentially targeted when completing cost evaluations among the obese population. In general, a relatively small percentage of people use the majority of health-care services. This leads to a greater skewed distribution with greater variance than other types of outcomes (i.e., clinical or humanistic). Therefore, when assessing health-care use, the sample size may need to be greater. Additionally, more in-depth evaluation of the outliers is required to explore their legitimacy within the results. This is illustrated in two studies (8, 12) that have similar populations