Many people with a family history of alcohol use disorder (AUD) struggle with certain cognition issues that often accompany AUD itself, even if they don’t themselves drink dangerously, according to a novel study. The findings suggest that these issues may be markers of vulnerability for the condition. A family history of AUD—having one or more first-degree relatives with the disorder—increases the risk of developing it, owing to genetic and environmental factors.
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Women With Alcohol-Related Liver Disease Have Greater Mortality Risk Than Men
Investigators from the Smidt Heart Institute at Cedars-Sinai and colleagues found that women with fatty liver disease related to alcohol consumption have almost twice the risk of dying within a certain time period than men with the same condition. The findings, published in the peer-reviewed Journal of Hepatology, highlight the need for women who are at risk of developing liver disease to avoid excess alcohol consumption.
Alcohol Abuse Can Accelerate Aging, Study Finds
The brains and blood of people with a history of excessive drinking show cellular evidence of premature aging. DNA taken from people with alcohol use disorder showed signs of changes in genetic regions indicative of increased biological age. Accelerated biological aging may help explain why excessive alcohol use has been shown to be a significant risk factor for premature death and neurodegenerative diseases.
Alcohol References in Music Can Influence Drinking
At least one in four contemporary songs references alcohol, according to an analysis of multiple studies that hints at the effects of music exposure on listeners’ drinking. Music is nearly ubiquitous in modern life, thanks partly to smartphones and streaming services. A 2022 study found that we listen to (on average) 961 hours of music per year, or 2 hours and 38 minutes per day.
Study Suggests Artificial Intelligence Can Help Identify Patients in Need of Alcohol Treatment
An artificial intelligence-based program efficiently and accurately identified patients’ risky alcohol use by analyzing their health records, according to a study published in Alcohol: Clinical and Experimental Research. The artificial intelligence-based natural language processing algorithm accurately identified three times more patients with risky alcohol use compared to diagnostic codes alone.