2008 Germany With MetS† Without MetS‡ Spain With MetS Without MetS Italy With MetS Without MetS 2020 Germany With MetS† Without MetS‡ Spain With MetS Without MetS Italy With MetS Without MetS 628 407 116 397 258 958 901 270 301 384 629 877 1,952 5,265 1,264 1,703 126 699 432 1,256 330 817 1,222 1,599 2,820 8,026 817 1,124 333 1,952 412 1,240 813 2,117 1,109 1,500 CVD-cardiovascular disease. † hypertension patients with MetS, ‡ hypertension patients without MetS. 1Drug costs relate to antihypertensive treatments only, 2physician costs relate to visits to the clinic as a result of hypertension for check-ups and assessment of antihypertensive medication, 3CVD costs relate to ambulatory and hospitalisation costs for the management of each event, 4type 2 diabetes costs relate to the management of each patients and the costs of non-CVD related complications. Type 2 diabetes4 Total 16,582 24,427 1,967 5,341 968 597 3,472 2,178 1,909 2,682 4,877 5,957 27,208 38,955 1,600 3,811 2,743 5,329 816 2,852 8,964 12,523 2,701 6,187 four and the probability of each combination occurring in each age and sex group. These probabilities were applied to country-specific prevalence data to break- down individuals into each risk group. We have no rea- son to assume that such conditional structures would be different between the U.S. and the three European coun- tries as the clustering of individual MetS risk factors is unlikely to be significantly different. Our estimates of the economic burden of MetS in patients with hypertension are on the conservative side for a number of reasons. First, no data were available to distribute costs of antihypertensive medications across risk groups and therefore costs have been distributed evenly across each of the five risk groups. Data suggest that the quantity and type of antihypertensive medica- tion does differ between those with and without MetS. Those with MetS use significantly more ACE-inhibitors and ARBs and in general use antihypertensive drugs sig- nificantly more frequently than those without the syn- drome [17,50]. A redistribution of costs accounting for this would not increase the overall drug costs, but would increase the proportion of drug costs that are attributable to MetS. Second, the number of cardiovas- cular events occurring in the population was predicted using data derived from a population initially free of cardiovascular disease (a proportion of the population had type 2 diabetes). The model therefore does not take into account the costs attributable to those hypertensive subjects with MetS and established cardiovascular dis- ease, which would increase the total cost of illness. Finally, we only included healthcare costs in our model. Including costs relating to the loss in productivity due to morbidity or premature mortality would inflate cost- of-illness estimates by between 1.28 fold [51] and 10 fold [52]. Such wide estimates reflect the different meth- odologies used to calculate productivity losses. Future prevalence estimates and costs are based on projected changes in the demographics of each country Scholze et al. BMC Public Health 2010, 10:529 http://www.biomedcentral.com/1471-2458/10/529 Page 7 of 12 Table 2 Annual cost-of-illness (Euros, millions) of hypertension and the proportion of costs attributable to MetS; 2008 and 2020 Annual costs Drug1 Physician2 CVD3 Figure 4 Proportion of drug, physician, cardiovascular and type 2 diabetes costs to total annual costs for patients with hypertension and MetS; 2008.