title: Effects of rotating shift work on biomarkers of metabolic syndrome and inflammation.
abstract: OBJECTIVE
  The major function of the circadian system is the internal cycling of physiological and metabolic events. The present study sought to explore the effect of rotating shift work schedule on leucocyte count and its relationship with risk factors of metabolic syndrome (MS).
  
  
  METHODS
  From a population-based design, 1351 men of self-reported European ancestry were included in a cross-sectional study: 877 day workers were compared with 474 rotating shift workers. Medical history, health examination including anthropometric and arterial blood pressure measurements, a questionnaire on health-related behaviours and biochemical determinations was given to all participants.
  
  
  RESULTS
  In comparison with day workers, rotating shift workers had elevated (mean +/- SE) body mass index (27.1 +/- 0.3 vs. 26.3 +/- 0.2, P < 0.0154), waist-hip ratio (0.95 +/- 0.01 vs. 0.93 +/- 0.01, P < 0.00024), diastolic arterial blood pressure (78 +/- 1 vs. 76 +/- 1, P < 0.033), fasting insulin (65.5 +/- 2.9 vs. 55.9 +/- 1.9 pmol L(-1), P < 0.017), Homeostasis Model Assessment index (2.12 +/- 0.11 vs. 1.77 +/- 0.07, P < 0.0027), triglycerides (1.71 +/- 0.1 vs. 1.5 +/- 0.1 mmol L(-1), P < 0.002), uric acid (292.7 +/- 2.8 vs. 282 +/- 3.4 micromol L(-1), P < 0.01) and leucocyte count (7030 +/- 84 vs. 6730 +/- 58, P < 0.0094). In multiple regression analysis, leucocyte count was correlated with rotating shift work independently of age, smoking, education and components of MS.
  
  
  CONCLUSIONS
  The odds ratio for MS in rotating shift workers compared with day workers was 1.51 (95% CI 1.01-2.25), independently of age and physical activity. Increased leucocyte count, a biological marker of systemic inflammation, was associated with rotating shift work.
authors.affiliation: Cardiología Molecular, Instituto de Investigaciones Medicas, A. Lanari, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina.
authors.forename: S
authors.initials: S
authors.lastname: Sookoian
authors.forename: C
authors.initials: C
authors.lastname: Gemma
authors.forename: T
authors.initials: T
authors.lastname: Fernández Gianotti
authors.forename: A
authors.initials: A
authors.lastname: Burgueño
authors.forename: A
authors.initials: A
authors.lastname: Alvarez
authors.forename: C D
authors.initials: CD
authors.lastname: González
authors.forename: C J
authors.initials: CJ
authors.lastname: Pirola
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000032:analysis / Q000097:blood; D002940:Circadian Rhythm / Q000502:physiology*; D003430:Cross-Sectional Studies; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000209:etiology; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000209:etiology*; D009784:Occupational Diseases / Q000097:blood / Q000209:etiology*; D012307:Risk Factors; D014940:Work Schedule Tolerance / Q000502:physiology*
chemical_list: D015415:Biomarkers