Abstract
The rising trend in the prevalence of obesity, which is a major risk factor for a number of diseases notably diabetes and cardiovascular diseases, has become a major public health concern in many countries during the past decades. This development has also led to an increased cost burden on the public health care delivery system that has been documented in many studies. The standard approach taken for estimating the cost burden attributed to a risk factor is the so-called PAR (Population Attributed Risk) approach; an approach that is based on cross-sectional data. In this paper, the methods and findings of two studies that have documented the cost burden attributed to overweight and obesity on the public health care delivery system in Sweden are contrasted: one using the PAR approach and one using a statistical modeling approach based on longitudinal hospital care data for 15 years for 33 000 individuals. The main motivation for this paper is that the study using the PAR approach is only available in the Swedish language. The PAR approach estimated a cost burden of 3 600 million SEK (390 million Euro), equavalent to 1.9% of national health care expenditure, out of which 1 800 million SEK (190 million Euro) were spent on hospital care. The statistical modeling approach estimated the corresponding cost burden for hospital care at 2 100 million SEK (230 million Euro). The statistical modeling approach presents no estimates of the total cost burden attributed to overweight and obesity.
Acknowledgements
Unrestricted funding for this study has been provided by: Landstingsförbundet (Federation of Swedish County Council) and Pharmaceutical Group Strategic Marketing, Johnson & Johnson, New Jersey, USA.
Notes
1However, as a measure of the risks of obesity-related disease, BMI has a few drawbacks. First, BMI is a measure of weight and does not discriminate between body fat and lean mass Citation13, which is especially important for young muscular men and the elderly. Second, BMI does not take into account the distribution of fat within the body. For instance, abdominal adiposity has been implicated as particularly important in explaining the development of insulin resistance and Type 2 diabetes mellitus Citation14, Citation15, and some researchers consequently prefer the waist-to-hip ratio (WHR) as it is more sensitive to fat location. BMI was established by using life insurance statistics and is probably a good marker in adults, even if it does not measure the anatomy exactly. WHR is better in adults but not reliable in children. Citation16.