Prevalence of metabolic syndrome Tsai TY et al. correlation between malignancy and MS have shown that patients with MS have a 1.6-fold higher risk of death from cancer than those without MS.9 Therefore, clarifying the factors related to MS and to identify high-risk cases early may be of utmost importance for public health. Workers are an important part of any institution. Since the promulgation of the Ottawa Charter for Health Promotion by the WHO in 1986, global support for work- place health promotion has encouraged employers to hold health promotion activities to ensure employee health.10 With increasing competition in the global market and the rapid development of technology, all countries (including Taiwan) seek to foster growth in high-tech industries. Facilitated by support from the government, high-tech products comprised 71.2% of all exports from Taiwan in 2006 with a value of US$159.5 billion.11 Taiwan is a pivotal site for high-tech industry development in the world, but increasing demand for high-tech products may increase the already heavy workload for workers in this industry. Therefore, the health status of high-tech industry workers requires immediate attention. Many previous studies have focused on musculoskeletal discomfort,12 workplace stress,13 skin disease,14 and lumbar pain,15 among other issues, but there is a relative paucity of data pertaining to metabolic abnormalities in the workplace. Most impor- tantly, the medical expenses related to MS are considerable and thus cannot be overlooked. Goetzel et al.16 found that obesity poses a burden of US$644 per worker on companies, due to medical expenses and loss of productivity. Moreover, this cost rises to US$3,719 with the occurrence of MS,17 which may have a major impact on the fiscal performance of the company. Therefore, our study aimed to understand the prevalence of MS and related factors in high-tech industry workers, which should facilitate the development of strategies for promoting appropriate workplace health. METHODS Research design and participants This study was cross-sectional. The subjects were workers from a company in the integrated circuit industry; the company contracted a hospital in Taiwan for health examination services in 2008. A total of 4,666 workers providing informed consent were included in this study, and the study was reviewed and approved by the Institutional Review Board of the target hospital. Data characteristics and diagnostic criteria Analytical data were obtained from the health examina- tion database. These data included gender, age, height, body weight, blood pressure, waist circumference, and blood biochemistry markers (i.e., white blood cell count (WBC), hemoglobin concentration, fasting blood glucose levels, high-density lipoprotein cholesterol (HDL-C), triglycerides, uric acid (UA), creatinine, aspartate aminotransferase (AST), and alanine aminotransferase (ALT)). The body mass index (BMI) was calculated by dividing weight (in kg) by height (in m2). Systolic and diastolic blood pressures were measured using an automatic sphygmomanometer (UDEX-IIa, UEDA Corp., Tokyo, Japan) and recorded in the seated position after participants had rested for at least 5 min. Waist circumference was measured with a heavy- duty inelastic plastic fiber tape measure to the nearest 0.5 cm, while the subject stood balanced on both feet with 1532 CLINICS 2011;66(9):1531-1535 the feet touching each other and both arms hanging freely. Hemoglobin concentration, ALT, AST, triglycerides, fasting blood glucose, UA, WBC, and HDL-C were evaluated by automatic bio-assays (Olympus AU-640, Tokyo, Japan). MS was defined as the presence of three or more of the following five criteria proposed by the Taiwan National Health Department:18 (1) fasting blood glucose $100 mg/dl or self-reported diabetes mellitus; (2) blood pressure $130/ 85 mmHg or self-reported hypertension; (3) HDL-C choles- terol ,40 mg/dl in men or ,50 mg/dl in women; (4) triglycerides $150 mg/dl; and (5) waist circumference $90 cm in men or $80 cm in women. Statistical analysis Descriptive and inferential analyses were conducted in accordance with the study’s aims and the nature of the variables. For descriptive analysis, subjects were grouped according to the presence of MS. Differences in various factors between groups are expressed with averages, standard deviations (SDs), and percentages. Besides gender, which is shown as a percentage, other variables with continuous distributions are expressed as averages with SD. For inferential analysis, t-tests and chi-square tests were used to explore the relationship between analytical variables and MS. Multiple logistic regression analysis with the simultaneous entry method was further used to determine risk factors and their adjusted odds ratios (AORs). All analyses were conducted with Statistical Package for Social Sciences (SPSS) version 15.0 software (SPSS, Inc., Chicago, IL), and p,0.05 was considered significant. RESULTS The 4,666 high-tech industry workers enrolled in this study included 2,344 men and 2,322 women. Among subjects, the overall prevalence of MS was 8.2% (382/ 4,666) with 14.0% (328/2,344) in men and 2.3% (54/2,322) in women, revealing a higher MS prevalence in men (p,0.01). Based on the 2007 population census published by the Department of Health,19 the age-standardized prevalence was 5.9%, which was also higher in men than in women (10.1% vs. 1.7%, p,0.01). Additionally, men also showed higher BMIs, WBCs, liver enzyme levels, creatinine, UA, and hemoglobin, as compared to women (p,0.01). Subjects with MS averaged 33.5 years in age, as opposed to 30.2 years for those without MS. On average, workers with MS had significantly higher BMIs and abnormal blood samples, as compared to those without MS (Table 1). Our analysis also showed that the most common metabolic abnormalities among men and women with MS was higher waist circumference, which was followed by irregular blood pressure and hypertriglyceridemia; these disorders had prevalences of 82.0%, 81.4%, and 73.2% in males and 98.2%, 88.9%, and 64.8% in females, respectively (Table 2). Multivariate analysis revealed that men had an AOR of 3.94 (95% confidence interval (CI) = 2.2926.78) for devel- oping MS, as compared to women. A one-year increase in age was associated with a 6% (95% CI = 1.04-1.09) increase in the risk of MS. An increase in BMI of one raised the AOR for MS by 2% (95% CI = 1.0121.02). Regarding blood biochem- istry markers, an increase of one unit of ALT increased the AOR for MS by 30% (95% CI = 1.2621.35). An increase of one unit of UA or WBC was associated with an increase of