There are many causes of divorce and understanding them all is an arduous task. Factors vary and large datasets are necessary to isolate particular “features” that make a divorce more likely. A new study has discovered one such factor and it has to do with the gender ratio of the workplace.
According to the research, published in Biology Letters, if you work in a sector with more members of the opposite sex, you are more likely to get a divorce. This correlation is stronger for men than it is for women. Men working in female-dominated settings are about 15 percent more likely to get a divorce. For women in male-dominated jobs, this figure is 10 percent.
Working out this risk was possible thanks to an impressive dataset. The researchers used all of Denmark's marriage and divorce data for heterosexual couples over a period of over 20 years. This gave them the ability to control for individual factors, such as education, length of the marriage, and the presence of children. And the difference popped up.
“What we looked at here is the proportion of men and women in your professional sectors, whether you have many colleagues of the opposite sex compared to having many colleagues of the same sex, and how that links to divorce rates,” lead author Dr Caroline Uggla, from Stockholm University, told IFLScience.
“The most important finding, once controlled for other factors, is that there seems to be an association with the sex ratio of your sector.”
The researchers also found something interesting when it came to people's education level. Higher education attainment tends to be associated with lower divorce rates but in this particular study, the team found that this didn't apply to men.
“Highly educated men who work in women-dominated sectors are more likely to divorce than lower-educated men working in women-dominated sectors," Dr Uggla explained. "Lower-educated women working with lots of men were more likely to divorce but there was no such pattern for highly educated women.”
The researchers note that the research can be expanded upon, incorporating other factors that they were unable to investigate. For example, personality types might play a role in such differences. There could also be time trends within the data due to changing attitudes, a changing society, and changes to certain job sectors.