Do common symptoms in women predict long spells of sickness absence? A prospective community-based study on Swedish women 40 to 50 years of age.
OBJECTIVE
To investigate whether a high level of commonly experienced physical and mental symptoms could predict long spells of sickness absence in Swedish women and, further, to investigate the causal pattern of socioeconomic and psychosocial factors in relation to long spells of sickness absence.


METHODS
A questionnaire containing items on socioeconomic and psychosocial variables was sent to a random population of women, 40 to 50 years of age, living in a rural Swedish community. The response rate was 81.7% (397 women). Data on long spells of sickness absence (>14 days) for the year following the baseline survey were obtained from the social insurance office. Odds ratios (OR) were used to estimate bivariate associations. Multiple logistic regression analysis was used to test for confounding and effect modification.


RESULTS
Women suffering from a high level of common symptoms were at risk of subsequent long spells of sickness absence, OR = 3.39 (1.86-6.17). High demands at work and an active job position (i.e. the combination of high demands and a high degree of job control) were both associated with long spells of sickness absence, OR = 2.16 (1.12-4.17) and OR = 1.92 (1.01-3.67). The combined exposure (high level of common symptoms and an active job position) increased the odds for long spells of sickness absence (OR = 9.13; 3.39-24.58) with synergy noted.


CONCLUSIONS
The finding that women with common symptoms are at risk of future sickness absence is of particular importance in a primary health care setting. The finding that women in active job positions had a higher risk of sickness absence might be an effect of modern working conditions for women.
Krantz
Gunilla
G
Nordic School of Public Health, Göteborg, Sweden. gunillak@nhv.se
Ostergren
Per-Olof
PO
D000041:Absenteeism; D000328:Adult; D015984:Causality; D017281:Cost of Illness; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D011584:Psychology; D018582:Sick Leave / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D013548:Sweden / Q000453:epidemiology; D016387:Women's Health; D014931:Women, Working / Q000523:psychology / Q000706:statistics & numerical data*