Shift work and age as interactive predictors of body mass index among offshore workers

Scand J Work Environ Health. 2002 Feb;28(1):64-71. doi: 10.5271/sjweh.648.


Objectives: This study investigated shift pattern (day shifts versus day-night rotation) and its interactions with age, and with years of shiftwork exposure, as predictors of body mass index (BMI).

Methods: Survey data were collected from offshore personnel working day shifts (N=787) or day-night shifts (N=787); information was obtained about shift pattern and years of shiftwork exposure, height, weight, demographic factors, and smoking habits. Hierarchical multiple regression was used to test a model in which BMI was predicted by additive and interactive effects of shift pattern, age, and exposure years with control for confounding variables.

Results: In a multivariate analysis (controlling for job type, education and smoking), BMI was predicted by the main effects of age and years of shiftwork exposure. Shift pattern was not significant as a main effect, but it interacted significantly with the curvilinear age term and with the linear and curvilinear components of shiftwork exposure. In the day shift group, age but not exposure predicted BMI; the opposite was true of the day-night shift group. The increase in BMI with an increase in age and exposure years was steeper for the day-night shift group than for the day shift group.

Conclusions: The significant interaction effects found in this study were consistent with the view that continued exposure to day-night shift work gives rise to increases in BMI, over and above the normative effects of ageing on BMI shown by day-shift workers.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aging / physiology*
  • Body Mass Index*
  • Circadian Rhythm
  • Data Collection
  • Health Behavior
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Obesity / epidemiology*
  • Obesity / physiopathology
  • Occupational Exposure / statistics & numerical data*
  • Predictive Value of Tests
  • Risk Assessment
  • Risk Factors
  • Sampling Studies
  • Time Factors
  • United Kingdom / epidemiology
  • Work Schedule Tolerance*
  • Workplace*