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Open Access Research article

Worksite health screening programs for predicting the development of Metabolic Syndrome in middle-aged employees: a five-year follow-up study

Yu-Cheng Lin123, Jong-Dar Chen4, Su-Huey Lo5 and Pau-Chung Chen2*

Author Affiliations

1 Health Management Center, Tao-Yuan General Hospital, Tao-Yuan, Taiwan

2 Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, Taipei, Taiwan

3 School of Medicine, Fu Jen Catholic University, Taipei, Taiwan

4 Department of Family Medicine, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan

5 Department of Internal Medicine, Tao-Yuan General Hospital, Tao-Yuan, Taiwan

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BMC Public Health 2010, 10:747  doi:10.1186/1471-2458-10-747

Published: 2 December 2010

Abstract

Background

Metabolic syndrome (MetS) management programs conventionally focus on the adults having MetS. However, risk assessment for MetS development is also important for many adults potentially at risk but do not yet fulfill MetS criteria at screening. Therefore, we conducted this follow-up study to explore whether initial screening records can be efficiently applied on the prediction of the MetS occurrence in healthy middle-aged employees.

Methods

Utilizing health examination data, a five-year follow-up observational study was conducted for 1384 middle-aged Taiwanese employees not fulfilling MetS criteria. Data analyzed included: gender, age, MetS components, uric acid, insulin, liver enzymes, sonographic fatty liver, hepatovirus infections and lifestyle factors. Multivariate logistic regression was used to estimate the adjusted odds ratios (OR) and 95% confidence interval (CI) of risk for MetS development. The synergistic index (SI) values and their confidence intervals of risk factor combinations were calculated; and were used to estimate the interacting effects of coupling MetS components on MetS development.

Results

Within five years, 13% (175 out of 1384) participants fulfilled MetS criteria. The ORs for MetS development among adults initially having one or two MetS components were 2.8 and 7.3, respectively (both p < 0.01), versus the adults having zero MetS component count at screening. Central obesity carried an OR of 7.5 (p < 0.01), which far exceeded other risk factors (all ORs < 2.7). Synergistic effects on MetS development existed between coupling MetS components: 1. High blood pressure plus low-HDL demonstrated an OR of 11.7 (p < 0.01) for MetS development and an SI of 4.7 (95% CI, 2.1-10.9). 2. High blood pressure plus hyperglycemia had an OR of 7.9 (p < 0.01), and an SI of 2.7 (95% CI, 1.2-6.4).

Conclusion

MetS component count and combination can be used in predicting MetS development for participants potentially at risk. Worksite MetS screening programs simultaneously allow for finding out cases and for assessing risk of MetS development.