The estimated costs of diseases related to overweight and obesity reach almost US$ 2.1 billion in one year. Using population attributable risk factor we could estimate that approximately 10% of these cost is attributable to overweight and obesity. The estimates of direct costs reviewed here may generally be conservative, probably underestimated. The reimbursement rates provided by the Brazilian healthcare system (SUS) are widely recognized as poor estimates of the true costs of health care as shown by some cost-of-illness studies in Brazil, showing much higher costs than the reimbursed values [12
]. If indirect costs such as days lost to sickness, premature mortality, out-of-pocket and home care expenses had been included, the figure would have been far higher. Furthermore, this study focused only on the cost of care provided at public hospitals, the overall cost in Brazil will clearly be higher than reported in this study if also private health care spending had been included.
Costs for women were greater than for men, mainly because of higher ambulatory expenditures (73.3% vs 26.7% of total costs for women and men, respectively). The prevalence rates for overweight and obesity in Brazil differed little between sexes, and women demonstrated almost half of PAR for selected diseases than men, suggesting a greater use of health care system among them.
The largest proportion of costs was attributable to the treatment of cardiovascular diseases (67%), most likely because of higher prevalence of coronary artery disease compared to the selected neoplasms. In a previous study carried out in Brazil, Sichieri et al. [14
] also demonstrated that more than half of hospitalization costs were due to myocardial infarction and other ischemic heart diseases in public health system in Brazil.
Cardiovascular diseases and diabetes mellitus, both very common diseases with high morbidity and mortality rates, are responsible for a significant number of hospitalizations and high costs in Brazil [15
]. Both conditions are related to obesity and probably its prevalence and severity could be reduced with the reduced obesity rates. Wang et al. studied the economic burden of the projected obesity trends in the United States of America (USA), and demonstrated that a hypothetical program that enables a 1% BMI reduction across the US population would avoid up to 2.1-2.4 million incident cases of diabetes, 1.4-1.7million cardiovascular diseases, and 73,000-127,000 cases of cancer [17
The second group of diseases with the highest costs to the public health system was neoplasms. With the trend on increase prevalence of obesity along with the aging population, the increase in cancer cases and costs involved will be enormous.
Hospitalizations expenditures are often more important and contributed to the majority of costs to health systems, as presented in this analysis (approx 68% of total costs). The total expenditures related to all hospital admissions in Brazilian adult population (year 2010) amounted US$ 4.5 billion [18
]. The estimate of obesity-related diseases expenditures accounted for 32.9% of these costs, and approximately 11% of these costs can be attributable to overweight and obesity. Likewise, Schieri et al. also studied the impact of obesity on hospitalizations in Brazil, limiting the analysis to fewer diseases but including workdays lost due to hospitalization. In their study overweight/obesity related costs accounted for at least 3-5% of total hospitalization costs in 2001 [14
The estimated costs with obesity-related diseases are equivalent to 0.09% of the Brazilian gross domestic product in 2010 [19
]. Similarly a recent review for Europe which encompassed both direct and indirect costs estimated obesity-related costs to range from 0.09% to 0.61% of total annual gross domestic income in Western European countries [20
]. In United Kingdom (UK), a review of costs studies of overweight and obesity demonstrated that both conditions were responsible for 7.3% of morbidity and mortality in the UK, contributing over £3 billion to the direct health cost burden to the public health system (4.6% of total expenditure in 2002) [21
]. In Korea total costs represented about 0.22% of the gross domestic product and 3.7% of the national health care expenditures in 2005 [22
]. During the past 20
years, there has been a dramatic increase in obesity in the United States totalled and in 2010, no state had a prevalence of obesity less than 20% and 12 of them had a prevalence of 30% or more [23
]. The medical care costs of obesity in the United States totalled about US$147 billion in 2008 [24
]. A recent review provides an overview research on the economic impact of the obesity epidemic with a broader view of the issue. Besides the high direct medical costs (obese spent 36-100% more than normal-weight controls), absenteeism and presenteeism were 1,5 times higher, and an increase in disability payments and disability insurance premiums were shown [25
There is widespread agreement across this literature that the medical costs associated with obesity are substantial; however, there are important differences between the studies. Possible factors affecting these differences in estimates of costs are: methodology, categories of costs included (direct medical costs for diagnosis and treatment, indirect costs, non medical costs), definitions of weight categories, age groups, and data sources. These discrepancies make it difficult to compare results in different settings.
Some limitations on methods used in this study are worthy of further consideration. Firstly we restricted our analysis to meta-analysis of prospective studies and case–control studies carried out in countries other than Brazil, since no data are available on relative risks based on Brazilian cohorts. So, attributable risks may not reflect the real burden of the diseases in the country. Thus, our assumption is that the relative risks found in international studies could be applied to the Brazilian population. Secondly, in order to interpret PAR as the proportion of cases that could be prevented if the exposure were eliminated, we have to consider that confounding factors were controlled when relative risks were estimated. Thirdly, the overweight and obesity prevalence rates obtained from a Brazilian survey were based on self-reported weight and height, information that can be easily biased. Lastly, DATASUS is an administrative database designed with the purpose of operating the payment for hospitalizations, not for epidemiological purposes. Many limitations of this data can be raised as the quality of input data, coverage (60 to 70%), fraud, duplication of data, among others.