Occupational epidemiology and work related inequalities in health: a gender perspective for two complementary approaches to work and health research

J Epidemiol Community Health. 2007 Dec;61 Suppl 2(Suppl 2):ii39-45. doi: 10.1136/jech.2007.059774.

Abstract

Objectives: To provide a framework for epidemiological research on work and health that combines classic occupational epidemiology and the consideration of work in a structural perspective focused on gender inequalities in health.

Methods: Gaps and limitations in classic occupational epidemiology, when considered from a gender perspective, are described. Limitations in research on work related gender inequalities in health are identified. Finally, some recommendations for future research are proposed.

Results: Classic occupational epidemiology has paid less attention to women's problems than men's. Research into work related gender inequalities in health has rarely considered either social class or the impact of family demands on men's health. In addition, it has rarely taken into account the potential interactions between gender, social class, employment status and family roles and the differences in social determinants of health according to the health indicator analysed.

Conclusions: Occupational epidemiology should consider the role of sex and gender in examining exposures and associated health problems. Variables should be used that capture the specific work environments and health conditions of both sexes. The analysis of work and health from a gender perspective should take into account the complex interactions between gender, family roles, employment status and social class.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Epidemiologic Research Design*
  • Female
  • Health Status Indicators
  • Household Work / statistics & numerical data
  • Humans
  • Male
  • Occupational Health / statistics & numerical data*
  • Prejudice*
  • Sex Factors
  • Socioeconomic Factors
  • Women's Health
  • Women, Working / statistics & numerical data