‘I could go months without having a period’ part 3

 

Women with irregular menstrual cycles may have more than double the risk of ovarian cancer compared to women who have regular monthly periods, new research suggests.

The American Cancer Society estimates that nearly 22,000 American women will be diagnosed with ovarian cancer in 2014, and more than 14,000 will die from the disease. One reason ovarian cancer remains so deadly is there are no reliable early detection tools for it. When found, it’s often in the later stages when treatment is less effective.

Some research has suggested that women who ovulate less frequently may have some protection against ovarian cancer. For example, women who take birth control pills, which prevent ovulation, have a lower risk of ovarian cancer. The new study sought to see if women who naturally have irregular periods, and perhaps ovulate less frequently, had a lower rate of ovarian cancer.

The study included more than 14,000 women who were part of the Kaiser Permanente Health Plan in Alameda, Calif., between 1959 and 1967. The researchers followed the women's health over the next 50 years or until death. All had at least one child, and none used fertility drugs to conceive, according to the study.

Any woman who is concerned should talk to her doctor, he said. Her physician can let her know if she’s at an increased risk of developing ovarian cancer.

Takeaway

women on exercise bikes at gym Overexercising can cause missed periods. Missed periods are usually not a sign of a serious condition, but they can indicate:

low body weight
excessive exercise
pregnancy
stress
hormonal imbalance

However, less commonly, missing a period or having irregular periods may indicate ovarian cancer. More common symptoms of ovarian cancer include:

pelvic or belly pain
eating less
feeling full quickly
feeling the need to urinate often
urinating frequently

If a person has symptoms of ovarian cancer, they should see a doctor for an evaluation. The outlook for ovarian cancer can improve with early diagnosis and detection.

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