Pioneers and laggards - is the effect of gender equality on health dependent on context?
This study combines data at individual and area level to examine interactions between equality within couples and gender equality in the municipality in which individuals live. The research question is whether the context impacts on the association between gender equality and health. The material consists of data on 37,423 men and 37,616 women in 279 Swedish municipalities, who had their first child in 1978. The couples were classified according to indicators of their level of gender equality in 1980 in the public sphere (occupation and income) and private sphere (child care leave and parental leave) compared to that of their municipality. The health outcome is compensated days from sickness insurance during 1986-1999 with a cut-off at the 85% percentile. Data were analysed using logistic regression with the overall odds as reference. The results concerning gender equality in the private sphere show that among fathers, those who are equal in an equal municipality have lower levels of sick leave than the average while laggards (less equal than their municipality) and modest laggards have higher levels. In the public sphere, pioneers (more equal t han their municipality) fare better than the average while laggards fare worse. For mothers, those who are traditional in their roles in the public sphere are protected from high levels of sick leave, while the reverse is true for those who are equal. Traditional mothers in a traditional municipality have the lowest level of sick leave and pioneers the highest. These results show that there are distinct benefits as well as disadvantages to being a gender pioneer and/or a laggard in comparison to your municipality. The associations are markedly different for men and women.
Backhans
Mona Christina
MC
Public Health Sciences, Karolinska Institutet, Norrbacka, 17176 Stockholm, Sweden. mona.backhans@ki.se
Burström
Bo
B
Lindholm
Lars
L
Månsdotter
Anna
A
D005260:Female; D006305:Health Status Indicators; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D007348:Insurance, Health; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D009790:Occupations; D016524:Parental Leave / Q000706:statistics & numerical data; D010290:Parents; D012737:Sex Factors; D018582:Sick Leave / Q000706:statistics & numerical data; D012959:Socioeconomic Factors; D013548:Sweden