95%CI - 2.8 - 29.9 1.5 - 7.7 1.5 - 6.0 1.4 - 5.8 0.6 - 3.4 5.8 - 611.5 7.7 - 78.2 3.6 - 59.1 5.1 - 27.0 3.5 - 18.1 1.2 - 38.7 2.2 - 15.4 2.7 - 12.3 1.5 - 11.1 1.6 - 9.8 - <0.01 <0.01 <0.01 <0.01 0.44 <0.01 <0.01 <0.01 <0.01 <0.01 <0.05 <0.01 <0.01 <0.01 <0.01 Lin et al. BMC Public Health 2010, 10:747 http://www.biomedcentral.com/1471-2458/10/747 Table 5 Model 3, adjusted risks for metabolic syndrome (MetS) calculated using each MetS component and their combinations as potential risk factors Baseline MetS components and combinations* Adjusted-OR** Overall (N = 1384) P Adults having single MetS component at baseline COB alone Hyper-TG alone Hyper-GL alone Low-HDL alone HBP alone Adults having two MetS components at baseline COB-plus-Hyper-TG COB-plus-Low-HDL COB-plus-HBP HBP-plus-Low-HDL HBP-plus-Hyper-GL COB-plus-Hyper-GL HBP-plus-Hyper-TG Low-HDL-plus-Hyper-TG Hyper-GL-plus-Hyper-TG Hyper-GL-plus-Low-HDL NA‡ 9.1 3.4 3.0 2.9 1.4 59.6 24.6 14.5 11.7 7.9 6.7 5.8 5.7 4.1 3.9 SI† - one risk alone one risk alone one risk alone one risk alone one risk alone 7.6 2.8 2.0 4.7 2.7 0.8 1.6 1.6 1.6 1.1 Page 6 of 8 95%CI - - - - - - 0.8 - 74.5 0.8 - 9.2 0.5 - 8.5 2.1 - 10.9 1.2 - 6.4 0.1 - 5.2 0.6 - 4.3 0.7 - 3.3 0.6 - 4.4 0.4 - 2.9 * Abbreviations: Hyper-GL, hyperglycemia; Low-HDL, Low-HDL cholesterolemia; HBP, high blood pressure; Hyper-TG, hypertriglyceridemia; COB, central obesity. ** Adjusted variables were age and categorical variables including gender, smoking, diet habits, drinking, exercise status, liver enzymes, sonographic fatty liver, hepatovirus infections, hyperinsulinemia and hyperuricemia. † SI, synergistic index, SI value exceeding 1.0 indicates the presence of synergistic interaction. ‡ NA: Not analyzed in this model, analyzed and shown in Table 4, Model 2. SI and 95%CI in bold are considered to be statistically significant. within five years, versus the adults having zero MetS component count (Table 4). Some cardiovascular disease (CVD)-related surveillance studies had similar findings: the MetS component count has been associated with CVD occurrence [20], mortalities [21] and important sur- rogate markers [22]. Furthermore, Schultz and Edington demonstrated that changes in MetS component count were significantly related to the medical costs for work- forces [23]. As a relatively simple measurement, we sug- gest using the MetS component count as a fundamental item for risk assessment in MetS management programs. Throughout our analyses, central obesity was the stron- gest predictor for MetS development out of all risk factors (Table 3 and Table 5), regardless of its combinations with any other individual risk factors (Table 5). Since the “yo- yo” effects appeared in many trials for weight reduction [24], our observation support that prevention for obesity should be strongly prioritized for middle-aged adults in terms of MetS prevention [25]. Previous investigations and our current analyses both agreed that elevated g-GT [26], hyperinsulinemia [27] and sonographic fatty liver [28] are all acceptable predictors for MetS development. However, according to our multivariate analysis (Table 3, Table 4), the ORs of the risk factors mentioned above were not sig- nificantly greater than ORs of MetS components. On the other hand, all measurements of MetS components are available in most medical settings [29], in contrast to many equipment-requiring image examinations or techni- que-dependent measurements of surrogate markers [30-33]. Such a relatively accessible program capable of making its contributions simultaneously to abnormality screening and effective risk assessments, MetS screening program naturally has an important aspect of public health promotion. Our component-component interaction analyses demonstrated several significant compound effects of MetS components on MetS development. In our two- component analyses, the middle-aged adults simulta- neously having HBP and any other MetS component were at a dramatically increased risk for MetS develop- ment (model 3, Table 5, lower rows). The results of the analyses for MetS development were relatively close to clinical observations: together with other risk factors, hypertension had aggravating effects on the cardiovascu- lar risks [34]. In addition, high blood pressure clustered with raised blood glucose or low HDL cholesterol were the riskiest combinations for arterial disease or prema- ture death [35,36]. Health managers should emphasize blood pressure control in workplace-based MetS man- agement programs because of its high abnormality rate among the middle-aged population and its synergistic interactions with other risk factors. The major limitation of this observational investiga- tion is that we did not take into consideration potential