The association between health and sickness absence among Danish and non-Western immigrant cleaners in Denmark

Int Arch Occup Environ Health. 2013 May;86(4):397-405. doi: 10.1007/s00420-012-0773-5. Epub 2012 Apr 18.

Abstract

Purpose: The aim of the study is to investigate the association between health and sickness absence among Danish and non-Western immigrant cleaners in Denmark.

Methods: This study is based on a cross-sectional analysis of baseline data from 2007 to 2008. The study population includes 276 cleaners, 144 Danish and 132 non-Western immigrant cleaners. Cumulative sickness absences during a 6-month period from administrative records were subdivided into no sickness absence (0 days), low occurrence of sickness absence (1-10 days) and high occurrence of sickness absence (over 10 days). Measures of health consisted of self-report and objective assessments. The relationship between sickness absence and health was analyzed through multinomial logistic regression, stratified by immigrant status.

Results: For both Danish and non-Western immigrant cleaners, poor self-reported health was significantly related to high occurrence of sickness absence. Among Danish cleaners, high blood pressure was related to high occurrence of sickness absence. Among non-Western immigrant cleaners, total body pain and having one or more diagnosed chronic disease were related to high occurrence of sickness absence. No association between health and low occurrence of sickness absence was found.

Conclusions: The findings confirm the importance of health for high occurrence of sickness absence, in both ethnic groups. Moreover, low occurrence of sickness absence was not related to the health conditions investigated.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Chronic Disease
  • Cross-Sectional Studies
  • Denmark
  • Emigrants and Immigrants / statistics & numerical data*
  • Female
  • Health Status Indicators
  • Health Status*
  • Housekeeping
  • Humans
  • Hypertension / ethnology
  • Logistic Models
  • Male
  • Middle Aged
  • Musculoskeletal Pain / ethnology
  • Odds Ratio
  • Self Report
  • Sick Leave / statistics & numerical data*