Experts warn that alcohol and smoking are now being linked to new health issues.

The news comes from the American Heart Association.

Recent studies, including a global analysis detailed by the American Heart Association, show that alcohol and smoking are associated with an increased risk of irregular heartbeats and breast cancer.

Matt Cardy, Getty Images
Matt Cardy, Getty Images
Matt Cardy, Getty Images

“Identifying shared risk factors is important for developing interventions that support optimal health, such as smoking cessation and alcohol restriction, which could potentially reduce the global incidence of breast cancer and atrial fibrillation/flutter substantially,” study co-author Shu Wang, M.D., Ph.D., director of the Breast Disease Center at Peking University People’s Hospital in Beijing, said.

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It's been known for decades that drinking alcohol and lighting up a cigarette increases a woman's breast cancer risk.

Matt Cardy, Getty Images
Matt Cardy, Getty Images
Matt Cardy, Getty Images

The National Institute on Alcohol Abuse and Alcoholism notes that drinking alcohol, even light consumption, increases the likelihood of women developing breast cancer.

Smoking/Alcohol Increases Risk Of Irregular Heartbeats

But now the American Heart Association is issuing an alert warning women that those lifestyle habits also increase the threat of developing irregular heartbeats.

a close up of a monitor screen with a heart beat
Photo by Joshua Chehov on Unsplash
a close up of a monitor screen with a heart beat

A major study, published this week in the Journal of the American Heart Association, involved data from 200 countries.

It showed that women 55 and older are most in danger. It also found that the highest risk is in Western nations, including the U.S.

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“One of the most surprising aspects of our findings was how common both breast cancer and atrial fibrillation/flutter diagnoses were among women ages 55 and older in high-income regions, which highlights the influence of lifestyle,” Wang said. “This is the first study combining global data with machine learning to show the relationship between the conditions, their location across the world and the shared risk factors of these two conditions.”

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