title: Utilizing the metabolic syndrome component count in workers' health surveillance: An example of day-time vs. day-night rotating shift workers.
abstract: OBJECTIVE
  To establish a practical method for assessing the general metabolic health conditions among different employee groups, this study utilized the total count of metabolic syndrome (MetS) elements as a parameter, and performed a retrospective analysis comparing changes of MetS component count (MSC) of 5 years among day-time work (DW) and day-andnight rotating shift work (RSW) employees.
  
  
  METHODS
  The data of personal histories, physical examinations, blood tests, abdominal sonographic examinations and occupational records were collected from a cohort of workers in an electronics manufacturing company. We first defined the arithmetic mean value of MSC as MSC density (MSCD) for the employee group; then we compared the changes of MSCD over 5 years between DW and RSW workers. Occupational, personal and health records were analyzed for the 1077 workers with an initial mean age of 32.4 years (standard deviation (SD): 6.2 years), including 565 RSW workers (52%).
  
  
  RESULTS
  The initial MSCDs were 1.26 and 1.12 (p = 0.06) for DW and RSW workers, respectively; after 5 years, the increments of MSCD for DW and RSW workers were 0.10 and 0.39, respectively (p < 0.01). By performing multivariate logistic regression analyses, and comparing with DW co-workers, final results indicated that the workers exposed to RSW have 1.7-fold increased risk of elevated MSCD (95% confidence interval (CI): 1.28-2.25, p < 0.01); and are 38% less likely (adjusted rate ratio (aRR) 0.62, 95% CI: 0.45-0.86, p < 0.01) to attain decreased MSCD.
  
  
  CONCLUSIONS
  These observations demonstrate that changes of MSCD are significantly different between DW and RSW workers, and are increasingly associated with RSW exposure. In conclusion, MSCD can represent the general metabolic health conditions of a given employee group; MSC, MSCD and their transitional changes can be applied as simple and standardized tools for monitoring metabolic health risk profiles when managing employee health, at both the individual and company levels.
authors.affiliation: En Chu Kong Hospital, New Taipei, Taiwan (Department of Occupational Medicine). gphinx@gmail.com, pchen@ntu.edu.tw.
authors.forename: Yu Cheng
authors.initials: YC
authors.lastname: Lin
authors.affiliation: Taiwan Adventist Hospital, Taipei, Taiwan (Department of Environmental and Occupational Medicine).
authors.forename: I-Chun
authors.initials: IC
authors.lastname: Hsieh
authors.affiliation: National Taiwan University College of Public Health, Taipei, Taiwan (Institute of Occupational Medicine and Industrial Hygiene).
authors.forename: Pau-Chung
authors.initials: PC
authors.lastname: Chen
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology*; D009784:Occupational Diseases / Q000453:epidemiology*; D016272:Occupational Health; D012189:Retrospective Studies; D012307:Risk Factors; D011795:Surveys and Questionnaires; D013624:Taiwan / Q000453:epidemiology; D014940:Work Schedule Tolerance; D016526:Workload / Q000706:statistics & numerical data*
keywords: day-and-night rotating shift work; metabolic syndrome; occupational health; physical examination