Demographic factors, fatigue, and driving accidents: An examination of the published literature

Accid Anal Prev. 2011 Mar;43(2):516-32. doi: 10.1016/j.aap.2009.12.018.

Abstract

This article reviews the literature pertaining to the association between demographic variables (e.g., age, sex, race, socio-economic status) with fatigue, and when feasible, accident risk. It also explores their potential influence and interaction with some working arrangements, commute time, personality characteristics, and circadian chronotype. Fatigue has been implicated in a range of impairments that can have detrimental effects on individuals, and it is differentially associated with conventional demographic variables. However, several major methodological limitations prevent clear conclusions. First, there is absence of a shared definition both within and across disciplines. Second, although fatigue has been investigated using a variety of diverse designs, they have either been too weak to substantiate causality or lacked ecological validity. Third, while both subjective and objective measures have been used as dependent variables, fatigue has been more often found to be more strongly linked with the former. Fourth, with the exception of age and sex, the influence of other demographic variables is unknown, since they have not yet been concomitantly assessed. In instances when they have been assessed and included in statistical analyses, they are considered as covariates or confounders; thus, their contribution to the outcome variable is controlled for, rather than being a planned aspect of investigation. Because the interaction of demographic factors with fatigue is largely a neglected area of study, we recommend greater interdisciplinary collaborations, incorporation of multiple demographic variables as independent factors, and use of within-participant analyses. These recommendations would provide meaningful results that may be used to inform public policy and preventive strategies.

Publication types

  • Review

MeSH terms

  • Accidents, Traffic / prevention & control*
  • Accidents, Traffic / statistics & numerical data
  • Age Factors
  • Demography*
  • Fatigue / complications*
  • Fatigue / epidemiology
  • Fatigue / prevention & control
  • Female
  • Humans
  • Male
  • Sex Factors
  • Socioeconomic Factors