BMC Public Health (Jan 2013)

Determinants in adolescence for adult sickness absence in women and men: a 26-year follow-up of a prospective population based cohort (Northern Swedish cohort)

  • Mittendorfer-Rutz Ellenor,
  • Hensing Gunnel,
  • Westerlund Hugo,
  • Backheden Magnus,
  • Hammarström Anne

DOI
https://doi.org/10.1186/1471-2458-13-75
Journal volume & issue
Vol. 13, no. 1
p. 75

Abstract

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Abstract Background To date little is known regarding how factors measured in adolescence predict sickness absence in adulthood, and whether different patterns of factors exist for women and men that could contribute to an explanation of adult gender differences in sickness absence. Methods All pupils in the last year of compulsory school in the municipality of Luleå with complete information from surveys (questionnaires) in 1981 and 1983 (compulsory and upper-secondary schooling; 16 and 18 years of age, N=719) were followed with register data on medically certified sickness absence (1993–2007). Generalised linear models were applied to calculate Risk Ratios with 95% Confidence Intervals (CI) comparing annual mean numbers of sickness absence spells in exposed versus unexposed groups. Results In the multivariate model, the following factors were found to be predictive of future sickness absence in women: participating in an upper secondary school program in 1983 dominated by women (> 60%): 1.41 (95% CI 1.00 – 1.97); sometimes sickness absence from school in 1981: 1.60 (95% CI 1.18 – 2.17) and low parental socioeconomic status in 1981: 2.20 (95% CI 1.44 – 3.38). In men, low school grades in 1981: 4.36 (95% CI 2.06 – 9.22) and fathers not in gainful employment in 1981: 2.36 (95% CI 1.53 – 3.66) were predictive. Conclusion The findings suggest that sickness absence in adulthood is predicted by factors measured in adolescence. These predictors may differ for women and men. For women, early life absence and social environmental factors, for men low achievements at school and lack of employment of their father seem to be predictive.

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