Night-shift work and cardiovascular risk among employees of a public university

Rev Assoc Med Bras (1992). 2012 Mar-Apr;58(2):168-77.
[Article in English, Portuguese]

Abstract

Objective: To estimate the association between night-shift work and high cardiovascular risk.

Methods: Cross-sectional study carried out with 211 workers of both genders, aged between 30 and 64 years, working on the health campus of a public university in the state of Minas Gerais, Brazil. Night-shift work was defined as a work shift between 7 pm and 7 am, and high cardiovascular risk was calculated based on the Framingham score. The association between night-shift work and high cardiovascular risk was estimated by the prevalence ratio (PR) and its 95% confidence interval (95% CI) after adjusting for potential confounding factors, calculated by Poisson regression.

Results: Night-shift work was performed by 38.4% of the individuals, and high cardiovascular risk was diagnosed in 28% of the sample. Hypertension was more prevalent among night-shift compared with day-shift workers (p < 0.05). In the bivariate analysis, night-shift work, passive and high job strain categories at the demand-control scale, work time > 120 months, schooling > 9 years, family income > 6 minimum wages, level 2 abdominal obesity, and triglyceride levels > 150 mg/dL were associated with high cardiovascular risk (p < 0.05). After multivariate analysis, night-shift work remained independently associated with high cardiovascular risk (PR = 1.67; 95% CI = 1.10-2.54).

Conclusion: The prevalence of high cardiovascular risk was 67% higher among night-shift workers. This association should be considered when discussing the promotion of workers' health regarding changes in the work process.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brazil / epidemiology
  • Cardiovascular Diseases / epidemiology*
  • Circadian Rhythm / physiology
  • Cross-Sectional Studies
  • Female
  • Humans
  • Hypertension / epidemiology
  • Male
  • Middle Aged
  • Prevalence
  • Risk Factors
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Universities / statistics & numerical data*
  • Work Schedule Tolerance / physiology*
  • Workforce