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Women in Sports Often Underrepresented in Exercise Science Studies

Photo courtesy of the New York Times

Photo courtesy of the New York Times

Women have been subject to sexual discrimination in sports since before the 18th century. In the late 1800s and early 1900s, women began to play sports competitively, often competing in tennis, archery, croquet and bowling. By the 1920s and 1930s, only few women competed in varsity athletics in college. The suffrage movement in the late 19th and early 20th centuries allowed the first feminist movement to spur women involvement in sports. During World War II, many women were instilled with a sense of self-esteem and self-confidence when replacing men’s jobs while they were overseas. In 1972, Title IX (of the Education Amendments of 1972) protected people from discrimination based on sex in education and federally funded programs.

Yet even with the progress women have made, sexual discrimination and prejudice against women still exists, not only in sports, but also in sports science studies.

Bethany Brookshire, an author for Science News magazine, comments on prejudice in sports science studies against women pointing out that, “Women are making up for a historical bias against them in sports. Not surprisingly, there’s also historically been a bias in sports science…Over time, athletes (and convenient student populations) have become more diverse, but diversity in studies of those athletes has continued to lag behind.”

Photo courtesy of Health Host

Photo courtesy of Health Host

Bruce Gladden, an exercise physiologist at Auburn University, attributes this bias to “a matter of convenience” and “studying the people nearest at hand.” In statistical terms, this is a convenience sample. A convenience sample by definition is a sampling method in which the sample is made up of individuals easiest to reach, and it typically results in a biased sample of like-minded individuals. These studies do not use a variety of individuals and yet still attempt to give results representing all people.

Although exercise studies have begun to use more diverse individuals, women are still underrepresented compared to men.

Joe Costello is an exercise physiologist at the University of Portsmouth in England, and while studying the effects of cold exposure to athletes for training recovery, he noticed that women were severely underrepresented compared to the men in the study. This spurred him and his colleagues to see if women were underrepresented in all sports science studies.

So in April of 2014, Joe Costello, Francois Bieuzen, and Chris M. Bleakely produced a study published in the European Journal of Sports Science, which basically asked one simple question: “Where are all the female participants in Sports and Exercise Medicine Research?”

After analyzing major sports and exercise science journals over a three year period, they concluded that females were significantly under-represented across all of the journals, and that “Sports and Exercise Medicine practitioners should be cognizant of sexual dimorphism and gender disparity in the current literature.”

In Bethany Brookshire’s article “Women in sports are often underrepresented in science” in Science News, she talks about how after researching Joe Costello’s studies, she wanted to know if the representation of women in sports science studies was improving, since 2014.

Her analysis of two studies from Medicine and Science in Sports and Exercise and the American Journal of Sports Medicine from 2015 gave her the results in the following pie charts.

graph-1

Brookshire also found that the biggest difference between the representation of men and women was found in sports performance studies.

graph-2

So why are women underrepresented in exercise science?

Some reasons behind the exclusion and underrepresentation of women include getting the same results for men and women, logistic and funding issues, and cultural and societal factors. Some scientists claim that no previous studies on certain topics show differences between men and women, so they feel it is easier to just use men and apply results to both men and women. If logistics become an issue, women are usually the ones who get slated in exercise science studies. For example, statistics show that women are often not as willing to participate in invasive studies or biopsies as men are. Cultural and societal reasons perpetuate the underrepresentation by showing bias against women’s sports in general. This can be seen in men’s sports being played more on television than female sports, and the fact that the U.S. men’s soccer team gets paid significantly more than the U.S. women’s soccer team, even though the women are ranked higher than the men.

However, the biggest factor is women’s menstrual cycles.

Marie Murphy, exercise scientist at Ulster University, says that “[women] should be no more variable than [men]” if you revisit them when they are not on their menstrual cycles. “I think if you’re looking for an excuse you’ll find one,” Murphy states, giving her perspective on the underrepresentation of women.

Because menstruation affects hormone levels and iron levels in women, some scientists are weary of using them in studies, fearing that the varying levels will affect their results. However, scientists advocating for equal representation of women believe that studies and experiments should be altered so that the physical changes that occur during a woman’s menstrual cycle do not affect the results.

Now you may be wondering, so what can we do to change this? Exercise science studies must include men and women equally if they expect to apply their results/findings to both men and women. As more women enter all fields of science, more women will naturally be incorporated in studies. There is still much inequality in these fields of study, and if they continue to be male dominated, women will never get equal representation, whether it is in scientific studies, job position, or pay. As young women soon entering the workforce, go out there and fight for representation.

By Giavanna Tabbachino’17, Guest Writer

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